Comparing SMAP to Macro-scale and Hyper-resolution Land Surface Models over Continental U. S.

Science.gov (United States)

Pan, Ming; Cai, Xitian; Chaney, Nathaniel; Wood, Eric

2016-04-01

SMAP sensors collect moisture information in top soil at the spatial resolution of ~40 km (radiometer) and ~1 to 3 km (radar, before its failure in July 2015). Such information is extremely valuable for understanding various terrestrial hydrologic processes and their implications on human life. At the same time, soil moisture is a joint consequence of numerous physical processes (precipitation, temperature, radiation, topography, crop/vegetation dynamics, soil properties, etc.) that happen at a wide range of scales from tens of kilometers down to tens of meters. Therefore, a full and thorough analysis/exploration of SMAP data products calls for investigations at multiple spatial scales - from regional, to catchment, and to field scales. Here we first compare the SMAP retrievals to the Variable Infiltration Capacity (VIC) macro-scale land surface model simulations over the continental U. S. region at 3 km resolution. The forcing inputs to the model are merged/downscaled from a suite of best available data products including the NLDAS-2 forcing, Stage IV and Stage II precipitation, GOES Surface and Insolation Products, and fine elevation data. The near real time VIC simulation is intended to provide a source of large scale comparisons at the active sensor resolution. Beyond the VIC model scale, we perform comparisons at 30 m resolution against the recently developed HydroBloks hyper-resolution land surface model over several densely gauged USDA experimental watersheds. Comparisons are also made against in-situ point-scale observations from various SMAP Cal/Val and field campaign sites.

Predicting Bond Betas using Macro-Finance Variables

DEFF Research Database (Denmark)

Aslanidis, Nektarios; Christiansen, Charlotte; Cipollini, Andrea

We conduct in-sample and out-of-sample forecasting using the new approach of combining explanatory variables through complete subset regressions (CSR). We predict bond CAPM betas and bond returns conditioning on various macro-fi…nance variables. We explore differences across long-term government ...... bonds, investment grade corporate bonds, and high-yield corporate bonds. The CSR method performs well in predicting bond betas, especially in-sample, and, mainly high-yield bond betas when the focus is out-of-sample. Bond returns are less predictable than bond betas....

Predicting the size and elevation of future mountain forests: Scaling macroclimate to microclimate

Science.gov (United States)

Cory, S. T.; Smith, W. K.

2017-12-01

Global climate change is predicted to alter continental scale macroclimate and regional mesoclimate. Yet, it is at the microclimate scale that organisms interact with their physiochemical environments. Thus, to predict future changes in the biota such as biodiversity and distribution patterns, a quantitative coupling between macro-, meso-, and microclimatic parameters must be developed. We are evaluating the impact of climate change on the size and elevational distribution of conifer mountain forests by determining the microclimate necessary for new seedling survival at the elevational boundaries of the forest. This initial life stage, only a few centimeters away from the soil surface, appears to be the bottleneck to treeline migration and the expansion or contraction of a conifer mountain forest. For example, survival at the alpine treeline is extremely rare and appears to be limited to facilitated microsites with low sky exposure. Yet, abundant mesoclimate data from standard weather stations have rarely been scaled to the microclimate level. Our research is focusing on an empirical downscaling approach linking microclimate measurements at favorable seedling microsites to the meso- and macro-climate levels. Specifically, mesoclimate values of air temperature, relative humidity, incident sunlight, and wind speed from NOAA NCEI weather stations can be extrapolated to the microsite level that is physiologically relevant for seedling survival. Data will be presented showing a strong correlation between incident sunlight measured at 2-m and seedling microclimate, despite large differences from seedling/microsite temperatures. Our downscaling approach will ultimately enable predictions of microclimate from the much more abundant mesoclimate data available from a variety of sources. Thus, scaling from macro- to meso- to microclimate will be possible, enabling predictions of climate change models to be translated to the microsite level. This linkage between measurement

An empirical tool to evaluate the safety of cyclists: Community based, macro-level collision prediction models using negative binomial regression.

Science.gov (United States)

Wei, Feng; Lovegrove, Gordon

2013-12-01

Today, North American governments are more willing to consider compact neighborhoods with increased use of sustainable transportation modes. Bicycling, one of the most effective modes for short trips with distances less than 5km is being encouraged. However, as vulnerable road users (VRUs), cyclists are more likely to be injured when involved in collisions. In order to create a safe road environment for them, evaluating cyclists' road safety at a macro level in a proactive way is necessary. In this paper, different generalized linear regression methods for collision prediction model (CPM) development are reviewed and previous studies on micro-level and macro-level bicycle-related CPMs are summarized. On the basis of insights gained in the exploration stage, this paper also reports on efforts to develop negative binomial models for bicycle-auto collisions at a community-based, macro-level. Data came from the Central Okanagan Regional District (CORD), of British Columbia, Canada. The model results revealed two types of statistical associations between collisions and each explanatory variable: (1) An increase in bicycle-auto collisions is associated with an increase in total lane kilometers (TLKM), bicycle lane kilometers (BLKM), bus stops (BS), traffic signals (SIG), intersection density (INTD), and arterial-local intersection percentage (IALP). (2) A decrease in bicycle collisions was found to be associated with an increase in the number of drive commuters (DRIVE), and in the percentage of drive commuters (DRP). These results support our hypothesis that in North America, with its current low levels of bicycle use (macro-level CPMs. Copyright © 2012. Published by Elsevier Ltd.

Comparing the photocatalytic activity of TiO2 at macro- and microscopic scales

DEFF Research Database (Denmark)

Torras-Rosell, Antoni; Johannsen, Sabrina Rostgaard; Dirscherl, Kai

2016-01-01

. The photocatalytic properties of TiO2 at macro- and microscopic scales are investigated by comparing photocatalytic degradation of acetone and electrochemical experiments to Kelvin probe force microscopy. The good agreement between the macro- and microscopic experiments suggests that Kelvin probe force microscopy...

Multi-scale-nonlinear interactions among macro-MHD mode, micro-turbulence, and zonal flow

International Nuclear Information System (INIS)

Ishizawa, Akihiro; Nakajima, Noriyoshi

2007-01-01

This is the first numerical simulation demonstrating that macro-magnetohydrodynamic (macro-MHD) mode is exited as a result of multi-scale interaction in a quasi-steady equilibrium formed by a balance between zonal flow and micro-turbulence via reduced-two-fluid simulation. Only after obtaining the equilibrium which includes zonal flow and the turbulence caused by kinetic ballooning mode is this simulation of macro-MHD mode, double tearing mode, accomplished. In the quasi-steady equilibrium a macro-fluctuation which has the same helicity as that of double tearing mode is a part of the turbulence until it grows as a macro-MHD mode finally. When the macro-MHD grows it effectively utilize free energy of equilibrium current density gradient because of positive feedback loop between suppression of zonal flow and growth of the macro-fluctuation causing magnetic reconnection. Thus once the macro-MHD grows from the quasi-equilibrium, it does not go back. This simulation is more comparable with experimental observation of growing macro-fluctuation than traditional MHD simulation of linear instabilities in a static equilibrium. (author)

Detection of macro-ecological patterns in South American hummingbirds is affected by spatial scale

DEFF Research Database (Denmark)

Rahbek, Carsten; Graves, Gary R.

2000-01-01

Scale is widely recognized as a fundamental conceptual problem in biology, but the question of whether species-richness patterns vary with scale is often ignored in macro-ecological analyses, despite the increasing application of such data in international conservation programmes. We tested for s...... peaks, decreasing the power of statistical tests to discriminate the causal agents of regional richness gradients. Ideally, the scale of analysis should be varied systematically to provide the optimal resolution of macro-ecological pattern....

Sequential use of the STICS crop model and of the MACRO pesticide fate model to simulate pesticides leaching in cropping systems.

Science.gov (United States)

Lammoglia, Sabine-Karen; Moeys, Julien; Barriuso, Enrique; Larsbo, Mats; Marín-Benito, Jesús-María; Justes, Eric; Alletto, Lionel; Ubertosi, Marjorie; Nicolardot, Bernard; Munier-Jolain, Nicolas; Mamy, Laure

2017-03-01

The current challenge in sustainable agriculture is to introduce new cropping systems to reduce pesticides use in order to reduce ground and surface water contamination. However, it is difficult to carry out in situ experiments to assess the environmental impacts of pesticide use for all possible combinations of climate, crop, and soils; therefore, in silico tools are necessary. The objective of this work was to assess pesticides leaching in cropping systems coupling the performances of a crop model (STICS) and of a pesticide fate model (MACRO). STICS-MACRO has the advantage of being able to simulate pesticides fate in complex cropping systems and to consider some agricultural practices such as fertilization, mulch, or crop residues management, which cannot be accounted for with MACRO. The performance of STICS-MACRO was tested, without calibration, from measurements done in two French experimental sites with contrasted soil and climate properties. The prediction of water percolation and pesticides concentrations with STICS-MACRO was satisfactory, but it varied with the pedoclimatic context. The performance of STICS-MACRO was shown to be similar or better than that of MACRO. The improvement of the simulation of crop growth allowed better estimate of crop transpiration therefore of water balance. It also allowed better estimate of pesticide interception by the crop which was found to be crucial for the prediction of pesticides concentrations in water. STICS-MACRO is a new promising tool to improve the assessment of the environmental risks of pesticides used in cropping systems.

Propagation Path Loss Models for 5G Urban Micro- and Macro-Cellular Scenarios

DEFF Research Database (Denmark)

Sun, Shu; Rappaport, Theodore S.; Rangan, Sundeep

2016-01-01

This paper presents and compares two candidate large-scale propagation path loss models, the alpha-beta-gamma (ABG) model and the close-in (CI) free space reference distance model, for the design of fifth generation (5G) wireless communication systems in urban micro- and macro-cellular scenarios....

Micro- and macro-scale self-organization in a dissipative plasma

International Nuclear Information System (INIS)

Skoric, M.M.; Sato, T.; Maluckov, A.; Jovanovic, M.S.

1998-10-01

We study a nonlinear three-wave interaction in an open dissipative model of stimulated Raman backscattering in a plasma. A hybrid kinetic-fluid scheme is proposed to include anomalous kinetic dissipation due to electron trapping and plasma wave breaking. We simulate a finite plasma with open boundaries and vary a transport parameter to examine a route to spatio-temporal complexity. An interplay between self-organization at micro (kinetic) and macro (wave/fluid) scales is revealed through quasi-periodic and intermittent evolution of dynamical variables, dissipative structures and related entropy rates. An evidence that entropy rate extrema correspond to structural transitions is found. (author)

Residual stress relaxation measurements across interfaces at macro-and micro-scales using slitting and DIC

Energy Technology Data Exchange (ETDEWEB)

Blair, A; Daynes, N; Hamilton, D; Horne, G; Hodgson, D Z L; Shterenlikht, A [Department of Mechanical Engineering, University of Bristol, Bristol BS8 1TR (United Kingdom); Heard, P J; Scott, T B, E-mail: mexas@bristol.ac.u [Interface Analysis Centre, University of Bristol, Bristol BS2 8BS (United Kingdom)

2009-08-01

In this paper digital image correlation is used to measure relaxation of residual stresses across an interface. On the macro scale the method is applied to a tri-layer bonded aluminium sample, where the middle layer is in tension and the top and the bottom layers are in compression. High contrast speckle pattern was sprayed onto the surface. The relaxation was done with the slitting saw. Three dimensional image correlation was used. On the micro scale the technique was applied to a heat treated large grain brass loaded in tension. Mechanical and electro polishing was used for surface preparation. A focused ion beam was used for slitting across a grain boundary and for imaging. Grain orientation was measured using electron back-scattering diffraction. Two dimensional image correlation was employed. In all macro- and micro-scale experiments the range of measured relaxation was sub-pixel, almost at the limit of the resolution of the image correlation algorithms. In the macro-scale experiments, the limiting factor was low residual stress, due to low shear strength of the Araldite glue used for bonding. Finite element simulation of the relaxation agreed only qualitatively with the experimental results at both size scales. The methodology is intended for use with inverse methods, i.e. the measured relaxation is applied as the boundary conditions to an appropriate FE model which produces stresses equal to the relaxed residual stresses, but with opposite sign. The main conclusion is that the digital image correlation method could be used to measure relaxation caused by slitting in heterogeneous materials and structures at both macro- and micro-scales. However, the repeatability of the techniques needs to be improved before residual stresses can be determined confidently. Acknowledgments The authors gratefully acknowledge Airbus UK for provision of materials. They thank Dr Richard Burguete, Airbus UK, and Prof Peter Flewitt, Department of Physics, University of Bristol, for

Residual stress relaxation measurements across interfaces at macro-and micro-scales using slitting and DIC

International Nuclear Information System (INIS)

Blair, A; Daynes, N; Hamilton, D; Horne, G; Hodgson, D Z L; Shterenlikht, A; Heard, P J; Scott, T B

2009-01-01

In this paper digital image correlation is used to measure relaxation of residual stresses across an interface. On the macro scale the method is applied to a tri-layer bonded aluminium sample, where the middle layer is in tension and the top and the bottom layers are in compression. High contrast speckle pattern was sprayed onto the surface. The relaxation was done with the slitting saw. Three dimensional image correlation was used. On the micro scale the technique was applied to a heat treated large grain brass loaded in tension. Mechanical and electro polishing was used for surface preparation. A focused ion beam was used for slitting across a grain boundary and for imaging. Grain orientation was measured using electron back-scattering diffraction. Two dimensional image correlation was employed. In all macro- and micro-scale experiments the range of measured relaxation was sub-pixel, almost at the limit of the resolution of the image correlation algorithms. In the macro-scale experiments, the limiting factor was low residual stress, due to low shear strength of the Araldite glue used for bonding. Finite element simulation of the relaxation agreed only qualitatively with the experimental results at both size scales. The methodology is intended for use with inverse methods, i.e. the measured relaxation is applied as the boundary conditions to an appropriate FE model which produces stresses equal to the relaxed residual stresses, but with opposite sign. The main conclusion is that the digital image correlation method could be used to measure relaxation caused by slitting in heterogeneous materials and structures at both macro- and micro-scales. However, the repeatability of the techniques needs to be improved before residual stresses can be determined confidently. Acknowledgments The authors gratefully acknowledge Airbus UK for provision of materials. They thank Dr Richard Burguete, Airbus UK, and Prof Peter Flewitt, Department of Physics, University of Bristol, for

Modelling PM10 aerosol data from the Qalabotjha low-smoke fuels macro-scale experiment in South Africa

CSIR Research Space (South Africa)

Engelbrecht, JP

2000-03-30

Full Text Available for combustion in cooking and heating appliances are being con- sidered to mitigate human exposure to D-grade coal combustion emissions. In 1997, South Africa's Department of Minerals and Energy conducted a macro-scale experiment to test three brands of low...

Modeling Macro- and Micro-Scale Turbulent Mixing and Chemistry in Engine Exhaust Plumes

Science.gov (United States)

Menon, Suresh

1998-01-01

Simulation of turbulent mixing and chemical processes in the near-field plume and plume-vortex regimes has been successfully carried out recently using a reduced gas phase kinetics mechanism which substantially decreased the computational cost. A detailed mechanism including gas phase HOx, NOx, and SOx chemistry between the aircraft exhaust and the ambient air in near-field aircraft plumes is compiled. A reduced mechanism capturing the major chemical pathways is developed. Predictions by the reduced mechanism are found to be in good agreement with those by the detailed mechanism. With the reduced chemistry, the computer CPU time is saved by a factor of more than 3.5 for the near-field plume modeling. Distributions of major chemical species are obtained and analyzed. The computed sensitivities of major species with respect to reaction step are deduced for identification of the dominant gas phase kinetic reaction pathways in the jet plume. Both the near field plume and the plume-vortex regimes were investigated using advanced mixing models. In the near field, a stand-alone mixing model was used to investigate the impact of turbulent mixing on the micro- and macro-scale mixing processes using a reduced reaction kinetics model. The plume-vortex regime was simulated using a large-eddy simulation model. Vortex plume behind Boeing 737 and 747 aircraft was simulated along with relevant kinetics. Many features of the computed flow field show reasonable agreement with data. The entrainment of the engine plumes into the wing tip vortices and also the partial detrainment of the plume were numerically captured. The impact of fluid mechanics on the chemical processes was also studied. Results show that there are significant differences between spatial and temporal simulations especially in the predicted SO3 concentrations. This has important implications for the prediction of sulfuric acid aerosols in the wake and may partly explain the discrepancy between past numerical studies

Coupled hygrothermal, electrochemical, and mechanical modelling for deterioration prediction in reinforced cementitious materials

DEFF Research Database (Denmark)

Michel, Alexander; Geiker, Mette Rica; Lepech, M.

2017-01-01

In this paper a coupled hygrothermal, electrochemical, and mechanical modelling approach for the deterioration prediction in cementitious materials is briefly outlined. Deterioration prediction is thereby based on coupled modelling of (i) chemical processes including among others transport of hea......, i.e. information, such as such as corrosion current density, damage state of concrete cover, etc., are constantly exchanged between the models....... and matter as well as phase assemblage on the nano and micro scale, (ii) corrosion of steel including electrochemical processes at the reinforcement surface, and (iii) material performance including corrosion- and load-induced damages on the meso and macro scale. The individual FEM models are fully coupled...

Studying neighborhood crime across different macro spatial scales: The case of robbery in 4 cities.

Science.gov (United States)

Hipp, John R; Wo, James C; Kim, Young-An

2017-11-01

Whereas there is a burgeoning literature focusing on the spatial distribution of crime events across neighborhoods or micro-geographic units in a specific city, the present study expands this line of research by selecting four cities that vary across two macro-spatial dimensions: population in the micro-environment, and population in the broader macro-environment. We assess the relationship between measures constructed at different spatial scales and robbery rates in blocks in four cities: 1) San Francisco (high in micro- and macro-environment population); 2) Honolulu (high in micro- but low in macro-environment population); 3) Los Angeles (low in micro- but high in macro-environment population); 4) Sacramento (low in micro- and macro-environment population). Whereas the socio-demographic characteristics of residents further than ½ mile away do not impact robbery rates, the number of people up to 2.5 miles away are related to robbery rates, especially in the two cities with smaller micro-environment population, implying a larger spatial scale than is often considered. The results show that coefficient estimates differ somewhat more between cities differing in micro-environment population compared to those differing based on macro-environment population. It is therefore necessary to consider the broader macro-environment even when focusing on the level of crime across neighborhoods or micro-geographic units within an area. Copyright © 2017 Elsevier Inc. All rights reserved.

Multi-scale modeling and analysis of convective boiling: towards the prediction of CHF in rod bundles

International Nuclear Information System (INIS)

Niceno, B.; Sato, Y.; Badillo, A.; Andreani, M.

2010-01-01

In this paper we describe current activities on the project Multi-Scale Modeling and Analysis of convective boiling (MSMA), conducted jointly by the Paul Scherrer Institute (PSI) and the Swiss Nuclear Utilities (Swissnuclear). The long-term aim of the MSMA project is to formulate improved closure laws for Computational Fluid Dynamics (CFD) simulations for prediction of convective boiling and eventually of the Critical Heat Flux (CHF). As boiling is controlled by the competition of numerous phenomena at various length and time scales, a multi-scale approach is employed to tackle the problem at different scales. In the MSMA project, the scales on which we focus range from the CFD scale (macro-scale), bubble size scale (meso-scale), liquid micro-layer and triple interline scale (micro-scale), and molecular scale (nano-scale). The current focus of the project is on micro- and meso- scales modeling. The numerical framework comprises a highly efficient, parallel DNS solver, the PSI-BOIL code. The code has incorporated an Immersed Boundary Method (IBM) to tackle complex geometries. For simulation of meso-scales (bubbles), we use the Constrained Interpolation Profile method: Conservative Semi-Lagrangian 2nd order (CIP-CSL2). The phase change is described either by applying conventional jump conditions at the interface, or by using the Phase Field (PF) approach. In this work, we present selected results for flows in complex geometry using the IBM, selected bubbly flow simulations using the CIP-CSL2 method and results for phase change using the PF approach. In the subsequent stage of the project, the importance of effects of nano-scale processes on the global boiling heat transfer will be evaluated. To validate the models, more experimental information will be needed in the future, so it is expected that the MSMA project will become the seed for a long-term, combined theoretical and experimental program

Nondestructive chemical imaging of wood at the micro-scale: advanced technology to complement macro-scale evaluations

Science.gov (United States)

Barbara L. Illman; Julia Sedlmair; Miriam Unger; Carol Hirschmugl

2013-01-01

Chemical images help understanding of wood properties, durability, and cell wall deconstruction for conversion of lignocellulose to biofuels, nanocellulose and other value added chemicals in forest biorefineries. We describe here a new method for nondestructive chemical imaging of wood and wood-based materials at the micro-scale to complement macro-scale methods based...

Quantum manifestation of systems on the macro-scale – the concept ...

Indian Academy of Sciences (India)

Transition amplitude; inelastic scattering; macro-scale quantum effects. ... ingly large wavelength of ∼5 cm for typical parameters (electron energy ε ∼ 1 keV ...... and hence as the generator of the transition amplitude wave at its position. As.

Predictive Maturity of Multi-Scale Simulation Models for Fuel Performance

International Nuclear Information System (INIS)

Atamturktur, Sez; Unal, Cetin; Hemez, Francois; Williams, Brian; Tome, Carlos

2015-01-01

The project proposed to provide a Predictive Maturity Framework with its companion metrics that (1) introduce a formalized, quantitative means to communicate information between interested parties, (2) provide scientifically dependable means to claim completion of Validation and Uncertainty Quantification (VU) activities, and (3) guide the decision makers in the allocation of Nuclear Energy's resources for code development and physical experiments. The project team proposed to develop this framework based on two complimentary criteria: (1) the extent of experimental evidence available for the calibration of simulation models and (2) the sophistication of the physics incorporated in simulation models. The proposed framework is capable of quantifying the interaction between the required number of physical experiments and degree of physics sophistication. The project team has developed this framework and implemented it with a multi-scale model for simulating creep of a core reactor cladding. The multi-scale model is composed of the viscoplastic self-consistent (VPSC) code at the meso-scale, which represents the visco-plastic behavior and changing properties of a highly anisotropic material and a Finite Element (FE) code at the macro-scale to represent the elastic behavior and apply the loading. The framework developed takes advantage of the transparency provided by partitioned analysis, where independent constituent codes are coupled in an iterative manner. This transparency allows model developers to better understand and remedy the source of biases and uncertainties, whether they stem from the constituents or the coupling interface by exploiting separate-effect experiments conducted within the constituent domain and integral-effect experiments conducted within the full-system domain. The project team has implemented this procedure with the multi- scale VPSC-FE model and demonstrated its ability to improve the predictive capability of the model. Within this

Predictive Maturity of Multi-Scale Simulation Models for Fuel Performance

Energy Technology Data Exchange (ETDEWEB)

Atamturktur, Sez [Clemson Univ., SC (United States); Unal, Cetin [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Hemez, Francois [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Williams, Brian [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Tome, Carlos [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

2015-03-16

The project proposed to provide a Predictive Maturity Framework with its companion metrics that (1) introduce a formalized, quantitative means to communicate information between interested parties, (2) provide scientifically dependable means to claim completion of Validation and Uncertainty Quantification (VU) activities, and (3) guide the decision makers in the allocation of Nuclear Energy’s resources for code development and physical experiments. The project team proposed to develop this framework based on two complimentary criteria: (1) the extent of experimental evidence available for the calibration of simulation models and (2) the sophistication of the physics incorporated in simulation models. The proposed framework is capable of quantifying the interaction between the required number of physical experiments and degree of physics sophistication. The project team has developed this framework and implemented it with a multi-scale model for simulating creep of a core reactor cladding. The multi-scale model is composed of the viscoplastic self-consistent (VPSC) code at the meso-scale, which represents the visco-plastic behavior and changing properties of a highly anisotropic material and a Finite Element (FE) code at the macro-scale to represent the elastic behavior and apply the loading. The framework developed takes advantage of the transparency provided by partitioned analysis, where independent constituent codes are coupled in an iterative manner. This transparency allows model developers to better understand and remedy the source of biases and uncertainties, whether they stem from the constituents or the coupling interface by exploiting separate-effect experiments conducted within the constituent domain and integral-effect experiments conducted within the full-system domain. The project team has implemented this procedure with the multi- scale VPSC-FE model and demonstrated its ability to improve the predictive capability of the model. Within this

A rate-dependent multi-scale crack model for concrete

NARCIS (Netherlands)

Karamnejad, A.; Nguyen, V.P.; Sluys, L.J.

2013-01-01

A multi-scale numerical approach for modeling cracking in heterogeneous quasi-brittle materials under dynamic loading is presented. In the model, a discontinuous crack model is used at macro-scale to simulate fracture and a gradient-enhanced damage model has been used at meso-scale to simulate

General predictive model of friction behavior regimes for metal contacts based on the formation stability and evolution of nanocrystalline surface films.

Energy Technology Data Exchange (ETDEWEB)

Argibay, Nicolas [Sandia National Lab. (SNL-CA), Livermore, CA (United States); Cheng, Shengfeng [Virginia Polytechnic Inst. and State Univ. (Virginia Tech), Blacksburg, VA (United States); Sawyer, W. G. [Univ. of Florida, Gainesville, FL (United States); Michael, Joseph R. [Sandia National Lab. (SNL-CA), Livermore, CA (United States); Chandross, Michael E. [Sandia National Lab. (SNL-CA), Livermore, CA (United States)

2015-09-01

The prediction of macro-scale friction and wear behavior based on first principles and material properties has remained an elusive but highly desirable target for tribologists and material scientists alike. Stochastic processes (e.g. wear), statistically described parameters (e.g. surface topography) and their evolution tend to defeat attempts to establish practical general correlations between fundamental nanoscale processes and macro-scale behaviors. We present a model based on microstructural stability and evolution for the prediction of metal friction regimes, founded on recently established microstructural deformation mechanisms of nanocrystalline metals, that relies exclusively on material properties and contact stress models. We show through complementary experimental and simulation results that this model overcomes longstanding practical challenges and successfully makes accurate and consistent predictions of friction transitions for a wide range of contact conditions. This framework not only challenges the assumptions of conventional causal relationships between hardness and friction, and between friction and wear, but also suggests a pathway for the design of higher performance metal alloys.

Predator-prey interactions as macro-scale drivers of species diversity in mammals

DEFF Research Database (Denmark)

Sandom, Christopher James; Sandel, Brody Steven; Dalby, Lars

Background/Question/Methods Understanding the importance of predator-prey interactions for species diversity is a central theme in ecology, with fundamental consequences for predicting the responses of ecosystems to land use and climate change. We assessed the relative support for different...... mechanistic drivers of mammal species richness at macro-scales for two trophic levels: predators and prey. To disentangle biotic (i.e. functional predator-prey interactions) from abiotic (i.e. environmental) and bottom-up from top-down determinants we considered three hypotheses: 1) environmental factors...... that determine ecosystem productivity drive prey and predator richness (the productivity hypothesis, abiotic, bottom-up), 2) consumer richness is driven by resource diversity (the resource diversity hypothesis, biotic, bottom-up) and 3) consumers drive richness of their prey (the top-down hypothesis, biotic, top...

Numerical analysis of macro-crack formation behavior within the lump coke; Cokes sonai kiretsu shinten kiko no kaiseki

Energy Technology Data Exchange (ETDEWEB)

Aoki, H; Sato, H; Miura, T [Tohoku University, Sendai (Japan). Faculty of Engineering

1995-03-15

The thermal stress analysis within lump coke was studied in order to investigate macro-crack formation and deformation behavior which strongly influence heat and mass transfer in a coke oven chamber. The dilatation of plastic layer, heating rate dependence of thermophysical and mechanical properties of coal/coke, creep in the plastic and semi-coke layers, macro-crack propagation and radiative heat transfer within the macro-crack were considered in an analytical model. The macro-crack propagation was determined from the estimated crack tip stress intensity factor, K{sub I}, at the macro-crack tip compared with the plane strain fracture toughness, K{sub IC}, through the unsteady-state calculation. Calculated results on crack formation and deformation behavior of lump coke were in good agreement with experimental observations in a laboratory-scale oven chamber. The analytical model could predict micro-crack formation within the lump coke normal to the heated wall and the coke surface close to the heated wall. 12 refs., 13 figs.

The MARKAL-MACRO model and the climate change

International Nuclear Information System (INIS)

Kypreos, S.

1996-07-01

MARKAL-MACRO and its extensions is a model appropriate to study partial and general equilibrium in the energy markets and the implications of the carbon dioxide mitigation policy. The main advantage of MM is the explicit treatment of energy demand, supply and conversion technologies, including emission control and conservation options, within a general equilibrium framework. The famous gap between top-down and bottom-up models is resolved and the economic implications of environmental and supply policy constraints can be captured either in an aggregated (Macro) or in a sectorial (Micro) level. The multi-regional trade version of the model allows to study questions related to efficient and equitable allocation of cost and benefits associated with the climate change issue. Finally, the stochastic version of the model allows to assess policies related to uncertain and even catastrophic effects and define appropriate hedging strategies. The report is divided in three parts: - the first part gives an overview of the new model structure. It describes its macro economic part and explains its calibration, - the second part refers to the model applications for Switzerland when analyzing the economic implications of curbing CO 2 emissions or policies related to the introduction of a carbon tax, including a hedging strategy, - the last part is organized in form of Appendices and gives a mathematical description and some potential extensions of the model. It describes also a sensitivity analysis done with MARKAL-MACRO in 1992. (author) figs., tabs., refs

Chondrocyte deformations as a function of tibiofemoral joint loading predicted by a generalized high-throughput pipeline of multi-scale simulations.

Directory of Open Access Journals (Sweden)

Scott C Sibole

Full Text Available Cells of the musculoskeletal system are known to respond to mechanical loading and chondrocytes within the cartilage are not an exception. However, understanding how joint level loads relate to cell level deformations, e.g. in the cartilage, is not a straightforward task. In this study, a multi-scale analysis pipeline was implemented to post-process the results of a macro-scale finite element (FE tibiofemoral joint model to provide joint mechanics based displacement boundary conditions to micro-scale cellular FE models of the cartilage, for the purpose of characterizing chondrocyte deformations in relation to tibiofemoral joint loading. It was possible to identify the load distribution within the knee among its tissue structures and ultimately within the cartilage among its extracellular matrix, pericellular environment and resident chondrocytes. Various cellular deformation metrics (aspect ratio change, volumetric strain, cellular effective strain and maximum shear strain were calculated. To illustrate further utility of this multi-scale modeling pipeline, two micro-scale cartilage constructs were considered: an idealized single cell at the centroid of a 100×100×100 μm block commonly used in past research studies, and an anatomically based (11 cell model of the same volume representation of the middle zone of tibiofemoral cartilage. In both cases, chondrocytes experienced amplified deformations compared to those at the macro-scale, predicted by simulating one body weight compressive loading on the tibiofemoral joint. In the 11 cell case, all cells experienced less deformation than the single cell case, and also exhibited a larger variance in deformation compared to other cells residing in the same block. The coupling method proved to be highly scalable due to micro-scale model independence that allowed for exploitation of distributed memory computing architecture. The method's generalized nature also allows for substitution of any macro-scale

Chondrocyte Deformations as a Function of Tibiofemoral Joint Loading Predicted by a Generalized High-Throughput Pipeline of Multi-Scale Simulations

Science.gov (United States)

Sibole, Scott C.; Erdemir, Ahmet

2012-01-01

Cells of the musculoskeletal system are known to respond to mechanical loading and chondrocytes within the cartilage are not an exception. However, understanding how joint level loads relate to cell level deformations, e.g. in the cartilage, is not a straightforward task. In this study, a multi-scale analysis pipeline was implemented to post-process the results of a macro-scale finite element (FE) tibiofemoral joint model to provide joint mechanics based displacement boundary conditions to micro-scale cellular FE models of the cartilage, for the purpose of characterizing chondrocyte deformations in relation to tibiofemoral joint loading. It was possible to identify the load distribution within the knee among its tissue structures and ultimately within the cartilage among its extracellular matrix, pericellular environment and resident chondrocytes. Various cellular deformation metrics (aspect ratio change, volumetric strain, cellular effective strain and maximum shear strain) were calculated. To illustrate further utility of this multi-scale modeling pipeline, two micro-scale cartilage constructs were considered: an idealized single cell at the centroid of a 100×100×100 μm block commonly used in past research studies, and an anatomically based (11 cell model of the same volume) representation of the middle zone of tibiofemoral cartilage. In both cases, chondrocytes experienced amplified deformations compared to those at the macro-scale, predicted by simulating one body weight compressive loading on the tibiofemoral joint. In the 11 cell case, all cells experienced less deformation than the single cell case, and also exhibited a larger variance in deformation compared to other cells residing in the same block. The coupling method proved to be highly scalable due to micro-scale model independence that allowed for exploitation of distributed memory computing architecture. The method’s generalized nature also allows for substitution of any macro-scale and/or micro-scale

Estimating Dynamic Equilibrium Models using Macro and Financial Data

DEFF Research Database (Denmark)

Christensen, Bent Jesper; Posch, Olaf; van der Wel, Michel

We show that including financial market data at daily frequency, along with macro series at standard lower frequency, facilitates statistical inference on structural parameters in dynamic equilibrium models. Our continuous-time formulation conveniently accounts for the difference in observation...... of the estimators and estimate the model using 20 years of U.S. macro and financial data....

Analysis of the Economic Impact of Large-Scale Deployment of Biomass Resources for Energy and Materials in the Netherlands. Appendix 2. Macro-economic Scenarios

International Nuclear Information System (INIS)

Banse, M.

2009-03-01

The Bio-based Raw Materials Platform (known as PGG), which is part of the Energy Transition programme in the Netherlands, commissioned the Agricultural Economics Research Institute (LEI) and the Copernicus Institute of Utrecht University to study the macro-economic impact of large-scale deployment of biomass for energy and materials in the Netherlands. Two model approaches were applied based on a consistent set of scenario assumptions: a bottom-up study including techno-economic projections of fossil and bio-based conversion technologies and a top-down study including macro-economic modelling of (global) trade of biomass and fossil resources. The results of the top-down study (part 2) including macro-economic modelling of (global) trade of biomass and fossil resources, are presented in this report

Handbook of damage mechanics nano to macro scale for materials and structures

CERN Document Server

2015-01-01

This authoritative reference provides comprehensive coverage of the topics of damage and healing mechanics. Computational modeling of constitutive equations is provided as well as solved examples in engineering applications. A wide range of materials that engineers may encounter are covered, including metals, composites, ceramics, polymers, biomaterials, and nanomaterials. The internationally recognized team of contributors employ a consistent and systematic approach, offering readers a user-friendly reference that is ideal for frequent consultation. Handbook of Damage Mechanics: Nano to Macro Scale for Materials and Structures is ideal for graduate students and faculty, researchers, and professionals in the fields of Mechanical Engineering, Civil Engineering, Aerospace Engineering, Materials Science, and Engineering Mechanics.

Biology meets Physics: Reductionism and Multi-scale Modeling of Morphogenesis

DEFF Research Database (Denmark)

Green, Sara; Batterman, Robert

2017-01-01

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 ...... 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....... 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 present a challenge to reductive explanations in both physics and biology. The problem refers to the scale...

Evolutionary modelling of the macro-economic impacts of catastrophic flood events

NARCIS (Netherlands)

Safarzynska, K.E.; Brouwer, R.; Hofkes, M.

2013-01-01

This paper examines the possible contribution of evolutionary economics to macro-economic modelling of flood impacts to provide guidance for future economic risk modelling. Most macro-economic models start from a neoclassical economic perspective and focus on equilibrium outcomes, either in a static

Optimizing Prediction Using Bayesian Model Averaging: Examples Using Large-Scale Educational Assessments.

Science.gov (United States)

Kaplan, David; Lee, Chansoon

2018-01-01

This article provides a review of Bayesian model averaging as a means of optimizing the predictive performance of common statistical models applied to large-scale educational assessments. The Bayesian framework recognizes that in addition to parameter uncertainty, there is uncertainty in the choice of models themselves. A Bayesian approach to addressing the problem of model uncertainty is the method of Bayesian model averaging. Bayesian model averaging searches the space of possible models for a set of submodels that satisfy certain scientific principles and then averages the coefficients across these submodels weighted by each model's posterior model probability (PMP). Using the weighted coefficients for prediction has been shown to yield optimal predictive performance according to certain scoring rules. We demonstrate the utility of Bayesian model averaging for prediction in education research with three examples: Bayesian regression analysis, Bayesian logistic regression, and a recently developed approach for Bayesian structural equation modeling. In each case, the model-averaged estimates are shown to yield better prediction of the outcome of interest than any submodel based on predictive coverage and the log-score rule. Implications for the design of large-scale assessments when the goal is optimal prediction in a policy context are discussed.

Modeling air concentration over macro roughness conditions by Artificial Intelligence techniques

Science.gov (United States)

Roshni, T.; Pagliara, S.

2018-05-01

Aeration is improved in rivers by the turbulence created in the flow over macro and intermediate roughness conditions. Macro and intermediate roughness flow conditions are generated by flows over block ramps or rock chutes. The measurements are taken in uniform flow region. Efficacy of soft computing methods in modeling hydraulic parameters are not common so far. In this study, modeling efficiencies of MPMR model and FFNN model are found for estimating the air concentration over block ramps under macro roughness conditions. The experimental data are used for training and testing phases. Potential capability of MPMR and FFNN model in estimating air concentration are proved through this study.

MACRO

International Nuclear Information System (INIS)

Rogner, H.H.

1989-01-01

The description is given to MACRO which is a numerically formulated macroeconomic model constructed to reflect the economy of the European Community. The model belongs to the group of general equilibrium models often applied in long-term macroeconomic energy modeling. Furthermore, MACRO was designed so as to interact with other more technically oriented energy demand and supply models. It's main objective is to provide consistency checks between assumptions concerning energy trade, energy prices, resource availability and energy-related capital requirements. 5 figs

Bio-based economy in the Netherlands. Macro-economic outline of a large-scale introduction of green resources in the Dutch energy supply

International Nuclear Information System (INIS)

Van der Hoeven, D.

2009-03-01

The Bio-based Raw Materials Platform (PGG), part of the Energy Transition in The Netherlands, commissioned the Agricultural Economics Research Institute (LEI) and the Copernicus Institute of Utrecht University to conduct research on the macro-economic impact of large scale deployment of biomass for energy and materials in the Netherlands. Two model approaches were applied based on a consistent set of scenario assumptions: a bottom-up study including technoeconomic projections of fossil and bio-based conversion technologies and a topdown study including macro-economic modelling of (global) trade of biomass and fossil resources. The results of the top-down and bottom-up modelling work are reported separately. This is the public version of studies [nl

Volume changes at macro- and nano-scale in epoxy resins studied by PALS and PVT experimental techniques

Energy Technology Data Exchange (ETDEWEB)

Somoza, A. [IFIMAT-UNCentro, Pinto 399, B7000GHG Tandil (Argentina) and CICPBA, Pinto 399, B7000GHG Tandil (Argentina)]. E-mail: asomoza@exa.unicen.edu.ar; Salgueiro, W. [IFIMAT-UNCentro, Pinto 399, B7000GHG Tandil (Argentina); Goyanes, S. [LPMPyMC, Depto. de Fisica, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Ciudad Universitaria, Pabellon I, 1428 Buenos Aires (Argentina); Ramos, J. [Materials and Technology Group, Departamento de Ingenieria Quimica y M. Ambiente, Escuela University Politecnica, Universidad Pais Vasco/Euskal Herriko Unibertsitatea, Pz. Europa 1, 20018 Donostia/San Sebastian (Spain); Mondragon, I. [Materials and Technology Group, Departamento de Ingenieria Quimica y M. Ambiente, Escuela University Politecnica, Universidad Pais Vasco/Euskal Herriko Unibertsitatea, Pz. Europa 1, 20018 Donostia/San Sebastian (Spain)

2007-02-15

A systematic study on changes in the volumes at macro- and nano-scale in epoxy systems cured with selected aminic hardeners at different pre-cure temperatures is presented. Free- and macroscopic specific-volumes were measured by PALS and pressure-volume-temperature techniques, respectively. An analysis of the relation existing between macro- and nano-scales of the thermosetting networks developed by the different chemical structures is shown. The result obtained indicates that the structure of the hardeners governs the packing of the molecular chains of the epoxy network.

Monitoring and assessment of soil erosion at micro-scale and macro-scale in forests affected by fire damage in northern Iran.

Science.gov (United States)

Akbarzadeh, Ali; Ghorbani-Dashtaki, Shoja; Naderi-Khorasgani, Mehdi; Kerry, Ruth; Taghizadeh-Mehrjardi, Ruhollah

2016-12-01

Understanding the occurrence of erosion processes at large scales is very difficult without studying them at small scales. In this study, soil erosion parameters were investigated at micro-scale and macro-scale in forests in northern Iran. Surface erosion and some vegetation attributes were measured at the watershed scale in 30 parcels of land which were separated into 15 fire-affected (burned) forests and 15 original (unburned) forests adjacent to the burned sites. The soil erodibility factor and splash erosion were also determined at the micro-plot scale within each burned and unburned site. Furthermore, soil sampling and infiltration studies were carried out at 80 other sites, as well as the 30 burned and unburned sites, (a total of 110 points) to create a map of the soil erodibility factor at the regional scale. Maps of topography, rainfall, and cover-management were also determined for the study area. The maps of erosion risk and erosion risk potential were finally prepared for the study area using the Revised Universal Soil Loss Equation (RUSLE) procedure. Results indicated that destruction of the protective cover of forested areas by fire had significant effects on splash erosion and the soil erodibility factor at the micro-plot scale and also on surface erosion, erosion risk, and erosion risk potential at the watershed scale. Moreover, the results showed that correlation coefficients between different variables at the micro-plot and watershed scales were positive and significant. Finally, assessment and monitoring of the erosion maps at the regional scale showed that the central and western parts of the study area were more susceptible to erosion compared with the western regions due to more intense crop-management, greater soil erodibility, and more rainfall. The relationships between erosion parameters and the most important vegetation attributes were also used to provide models with equations that were specific to the study region. The results of this

A Multiphysics Framework to Learn and Predict in Presence of Multiple Scales

Science.gov (United States)

Tomin, P.; Lunati, I.

2015-12-01

Modeling complex phenomena in the subsurface remains challenging due to the presence of multiple interacting scales, which can make it impossible to focus on purely macroscopic phenomena (relevant in most applications) and neglect the processes at the micro-scale. We present and discuss a general framework that allows us to deal with the situation in which the lack of scale separation requires the combined use of different descriptions at different scale (for instance, a pore-scale description at the micro-scale and a Darcy-like description at the macro-scale) [1,2]. The method is based on conservation principles and constructs the macro-scale problem by numerical averaging of micro-scale balance equations. By employing spatiotemporal adaptive strategies, this approach can efficiently solve large-scale problems [2,3]. In addition, being based on a numerical volume-averaging paradigm, it offers a tool to illuminate how macroscopic equations emerge from microscopic processes, to better understand the meaning of microscopic quantities, and to investigate the validity of the assumptions routinely used to construct the macro-scale problems. [1] Tomin, P., and I. Lunati, A Hybrid Multiscale Method for Two-Phase Flow in Porous Media, Journal of Computational Physics, 250, 293-307, 2013 [2] Tomin, P., and I. Lunati, Local-global splitting and spatiotemporal-adaptive Multiscale Finite Volume Method, Journal of Computational Physics, 280, 214-231, 2015 [3] Tomin, P., and I. Lunati, Spatiotemporal adaptive multiphysics simulations of drainage-imbibition cycles, Computational Geosciences, 2015 (under review)

Multi-scale modeling of composites

DEFF Research Database (Denmark)

Azizi, Reza

A general method to obtain the homogenized response of metal-matrix composites is developed. It is assumed that the microscopic scale is sufficiently small compared to the macroscopic scale such that the macro response does not affect the micromechanical model. Therefore, the microscopic scale......-Mandel’s energy principle is used to find macroscopic operators based on micro-mechanical analyses using the finite element method under generalized plane strain condition. A phenomenologically macroscopic model for metal matrix composites is developed based on constitutive operators describing the elastic...... to plastic deformation. The macroscopic operators found, can be used to model metal matrix composites on the macroscopic scale using a hierarchical multi-scale approach. Finally, decohesion under tension and shear loading is studied using a cohesive law for the interface between matrix and fiber....

Simultaneous Feedback Models with Macro-Comparative Cross-Sectional Data

Directory of Open Access Journals (Sweden)

Nate Breznau

2018-06-01

Full Text Available Social scientists often work with theories of reciprocal causality. Sometimes theories suggest that reciprocal causes work simultaneously, or work on a time-scale small enough to make them appear simultaneous. Researchers may employ simultaneous feedback models to investigate such theories, although the practice is rare in cross-sectional survey research. This paper discusses the certain conditions that make these models possible if not desirable using such data. This methodological excursus covers the construction of simultaneous feedback models using a structural equation modeling perspective. This allows the researcher to test if a simultaneous feedback theory fits survey data, test competing hypotheses and engage in macro-comparisons. This paper presents methods in a manner and language amenable to the practicing social scientist who is not a statistician or matrix mathematician. It demonstrates how to run models using three popular software programs (MPlus, Stata and R, and an empirical example using International Social Survey Program data.

Relevance of the hadronic interaction model in the interpretation of multiple muon data as detected with the MACRO experiment

International Nuclear Information System (INIS)

Ambrosio, M.; Antolini, R.; Aramo, C.; Auriemma, G.; Baldini, A.; Barbarino, G. C.; Barish, B. C.; Battistoni, G.; Bellotti, R.; Bemporad, C.; Bernardini, P.; Bilokon, H.; Bisi, V.; Bloise, C.; Bower, C.; Bussino, S.; Cafagna, F.; Calicchio, M.; Campana, D.; Carboni, M.; Castellano, M.; Cecchini, S.; Cei, F.; Chiarella, V.; Coutu, S.; De Benedictis, L.; De Cataldo, G.; Dekhissi, H.; De Marzo, C.; De Mitri, I.; De Vincenzi, M.; Di Credico, A.; Erriquez, O.; Favuzzi, C.; Forti, C.; Fusco, P.; Giacomelli, G.; Giannini, G.; Giglietto, N.; Grassi, M.; Gray, L.; Grillo, A.; Guarino, F.; Guarnaccia, P.; Gustavino, C.; Habig, A.; Hanson, K.; Hawthorne, A.; Heinz, R.; Iarocci, E.; Katsavounidis, E.; Kearns, E.; Kyriazopoulou, S.; Lamanna, E.; Lane, C.; Levin, D. S.; Lipari, P.; Longley, N. P.; Longo, M. J.; Maaroufi, F.; Mancarella, G.; Mandrioli, G.; Manzoor, S.; Neri, A. Margiotta; Marini, A.; Martello, D.; Marzari-Chiesa, A.; Mazziotta, M. N.; Mazzotta, C.; Michael, D. G.; Mikheyev, S.; Miller, L.; Monacelli, P.; Montaruli, T.; Monteno, M.; Mufson, S.; Musser, J.; Nicolo, D.; Nolty, R.; Okada, C.; Orth, C.; Osteria, G.; Palamara, O.; Patera, V.; Patrizii, L.; Pazzi, R.; Peck, C. W.; Petrera, S.; Pistilli, P.; Popa, V.; Raino, A.; Rastelli, A.; Reynoldson, J.; Ronga, F.; Rubizzo, U.; Sanzgiri, A.; Satriano, C.; Satta, L.; Scapparone, E.; Scholberg, K.; Sciubba, A.; Serra-Lugaresi, P.; Severi, M.; Sioli, M.; Sitta, M.; Spinelli, P.; Spinetti, M.; Spurio, M.; Steinberg, R.; Stone, J. L.; Sulak, L. R.; Surdo, A.; Tarle, G.; Togo, V.; Walter, C. W.; Webb, R.

1999-01-01

With the aim of discussing the effect of the possible sources of systematic uncertainties in simulation models, the analysis of multiple muon events from the MACRO experiment at Gran Sasso is reviewed. In particular, the predictions from different currently available hadronic interaction models are compared

The Generalist Model: Where do the Micro and Macro Converge?

Directory of Open Access Journals (Sweden)

Shari E. Miller

2008-12-01

Full Text Available Although macro issues are integral to social work, students continue to struggle with the acquisition of knowledge and skills pertaining to larger systems. Educators have developed innovative methods to integrate learning across systems of various sizes however it appears an imbalance persists. This challenge is supported by baccalaureate student responses to a social work program evaluation. Four years of data from 295 undergraduate students revealed that they felt less prepared to practice with larger, macro systems. Changes in curriculum to reflect collaboration and holism, and more research are needed to adequately provide macro learning and macro practice opportunities within the generalist model and in the context of the current socio-economic-political environment.

Evaluation of Micro- and Macro-Scale Petrophysical Characteristics of Lower Cretaceous Sandstone with Flow Modeling in µ-CT Imaged Geometry

Science.gov (United States)

Katsman, R.; Haruzi, P.; Waldmann, N.; Halisch, M.

2017-12-01

In this study petrophysical characteristics of rock samples from 3 successive outcrop layers of Hatira Formation Lower Cretaceous Sandstone in northen Israel were evaluated at micro- and macro-scales. The study was carried out by two complementary methods: using conventional experimental measurements of porosity, pore size distribution and permeability; and using a 3D µCT imaging and modeling of signle-phase flow in the real micro-scale sample geometry. The workfow included µ-CT scanning, image processing, image segmentation, and image analyses of pore network, followed by fluid flow simulations at a pore-scale. Upscaling the results of the micro-scale flow simulations yielded a macroscopic permeabilty tensor. Comparison of the upscaled and the experimentally measured rock properties demonstrated a reasonable agreement. In addition, geometrical (pore size distribution, surface area and tortuosity) and topological (Euler characteristic) characteristics of the grains and of the pore network were evaluated at a micro-scale. Statistical analyses of the samples for estimation of anisotropy and inhomogeneity of the porous media were conducted and the results agree with anisotropy and inhomogeneity of the upscaled permeabilty tensor. Isotropic pore orientation of the primary inter-granular porosity was identified in all three samples, whereas the characteristics of the secondary porosity were affected by precipitated cement and clay matrix within the primary pore network. Results of this study provide micro- and macro-scale characteristics of the Lower Cretaceous sandstone that is used in different places over the world as a reservoir for petroleum production and png;base64,R0lGODlhHAARAHcAMSH+GlNvZnR3YXJlOiBNaWNyb3NvZnQgT2ZmaWNlACH5BAEAAAAALAAABAAYAA0AhAAAAAAAAAAAOgAAZgA6kABmtjoAADoAZjo6kDqQ22YAAGa2/5A6AJA6ZpDb/7ZmALb//9uQOtv///+2Zv/bkP//tv//2wECAwECAwECAwECAwECAwECAwECAwECAwECAwVtICBaTGAWIkCaA5S+QKWgZCJSBgo8hASrjJ4osgDqABOB45dcwpopKIznmwpFkxas9uOmqDBZMawYxxS2iakn

Hydrocarbon Migration from the Micro to Macro Scale in the Gulf of Mexico

Science.gov (United States)

Johansen, C.; Marty, E.; Silva, M.; Natter, M.; Shedd, W. W.; Hill, J. C.; Viso, R. F.; Lobodin, V.; Krajewski, L.; Abrams, M.; MacDonald, I. R.

2016-02-01

In the Northern Gulf of Mexico (GoM) at GC600, ECOGIG has been investigating the processes involved in hydrocarbon migration from deep reservoirs to sea surface. We studied two individual vents, Birthday Candles (BC) and Mega-Plume (MP), which are separated by 1km on a salt supported ridge trending from NW-SE. Seismic data depicts two faults, also separated by 1km, feeding into the surface gas hydrate region. BC and MP comprise the range between oily, mixed, and gaseous-type vents. In both cases bubbles are observed escaping from gas hydrate out crops at the sea floor and supporting chemosynthetic communities. Fluid flow is indicated by features on the sea floor such as hydrate mounds, authigenic carbonates, brine pools, mud volcanoes, and biology. We propose a model to describe the upward flow of hydrocarbons from three vertical scales, each dominated by different factors: 1) macro (capillary failure in overlying cap rocks causing reservoir leakage), 2) meso (buoyancy driven fault migration), and 3) micro (hydrate formation and chemosynthetic activity). At the macro scale we use high reflectivity in seismic data and sediment pore throat radii to determine the formation of fractures in leaky reservoirs. Once oil and gas leave the reservoir through fractures in the cap rock they migrate in separate phases. At the meso scale we use seismic data to locate faults and salt diapirs that form conduits for buoyant hydrocarbons follow. This connects the path to the micro scale where we used video data to observe bubble release from individual vents for extended periods of time (3h-26d), and developed an image processing program to quantify bubble release rates. At mixed vents gaseous bubbles are observed escaping hydrate outcrops with a coating of oil varying in thickness. Bubble oil and gas ratios are estimated using average bubble size and release rates. The relative vent age can be described by carbonate hard ground cover, biological activity, and hydrate mound formation

Relevance of the hadronic interaction model in the interpretation of multiple muon data as detected with the MACRO experiment

CERN Document Server

Ambrosio, M; Aramo, C; Auriemma, G; Baldini, A; Barbarino, G C; Barish, B C; Battistoni, G; Bellotti, R; Bemporad, C; Bernardini, P; Bilokon, H; Bisi, V; Bloise, C; Bower, C; Bussino, S; Cafagna, F; Calicchio, M; Campana, D; Carboni, M; Castellano, M G; Cecchini, S; Cei, F; Chiarella, V; Coutu, S; De Benedictis, L; De Cataldo, G; Dekhissi, H; De Marzo, C; De Mitri, I; De Vincenzi, M; Di Credico, A; Erriquez, O; Favuzzi, C; Forti, C; Fusco, P; Giacomelli, G; Giannini, G; Giglietto, N; Grassi, M; Gray, L; Grillo, A; Guarino, F; Guarnaccia, P; Gustavino, C; Habig, A; Hanson, K; Hawthorne, A; Heinz, R; Iarocci, Enzo; Katsavounidis, E; Kearns, E T; Kyriazopoulou, S; Lamanna, E; Lane, C; Levin, D S; Lipari, P; Longley, N P; Longo, M J; Maaroufi, F; Mancarella, G; Mandrioli, G; Manzoor, S; Margiotta-Neri, A; Marini, A; Martello, D; Marzari-Chiesa, A; Mazziotta, M N; Mazzotta, C; Michael, D G; Mikheyev, S P; Miller, L; Monacelli, P; Montaruli, T; Monteno, M; Mufson, S L; Musser, J; Nicolò, D; Nolty, R; Okada, C; Orth, C; Osteria, G; Palamara, O; Patera, V; Patrizii, L; Pazzi, R; Peck, C W; Petrera, S; Pistilli, P; Popa, V; Rainó, A; Rastelli, A; Reynoldson, J; Ronga, F; Rubizzo, U; Sanzgiri, A; Satriano, C; Satta, L; Scapparone, E; Scholberg, K; Sciubba, A; Serra-Lugaresi, P; Severi, M; Sioli, M; Sitta, M; Spinelli, P; Spinetti, M; Spurio, M; Steinberg, R; Stone, J L; Sulak, Lawrence R; Surdo, A; Tarle, G; Togo, V; Walter, C W; Webb, R

1999-01-01

With the aim of discussing the effect of the possible sources of systematic uncertainties in simulation models, the analysis of multiple muon events from the MACRO experiment at Gran Sasso is reviewed. In particular, the predictions $9 from different currently available hadronic interaction models are compared. (9 refs).

Prediction of Coal Face Gas Concentration by Multi-Scale Selective Ensemble Hybrid Modeling

Directory of Open Access Journals (Sweden)

WU Xiang

2014-06-01

Full Text Available A selective ensemble hybrid modeling prediction method based on wavelet transformation is proposed to improve the fitting and generalization capability of the existing prediction models of the coal face gas concentration, which has a strong stochastic volatility. Mallat algorithm was employed for the multi-scale decomposition and single-scale reconstruction of the gas concentration time series. Then, it predicted every subsequence by sparsely weighted multi unstable ELM(extreme learning machine predictor within method SERELM(sparse ensemble regressors of ELM. At last, it superimposed the predicted values of these models to obtain the predicted values of the original sequence. The proposed method takes advantage of characteristics of multi scale analysis of wavelet transformation, accuracy and fast characteristics of ELM prediction and the generalization ability of L1 regularized selective ensemble learning method. The results show that the forecast accuracy has large increase by using the proposed method. The average relative error is 0.65%, the maximum relative error is 4.16% and the probability of relative error less than 1% reaches 0.785.

Retention prediction and separation optimization under multilinear gradient elution in liquid chromatography with Microsoft Excel macros.

Science.gov (United States)

Fasoula, S; Zisi, Ch; Gika, H; Pappa-Louisi, A; Nikitas, P

2015-05-22

A package of Excel VBA macros have been developed for modeling multilinear gradient retention data obtained in single or double gradient elution mode by changing organic modifier(s) content and/or eluent pH. For this purpose, ten chromatographic models were used and four methods were adopted for their application. The methods were based on (a) the analytical expression of the retention time, provided that this expression is available, (b) the retention times estimated using the Nikitas-Pappa approach, (c) the stepwise approximation, and (d) a simple numerical approximation involving the trapezoid rule for integration of the fundamental equation for gradient elution. For all these methods, Excel VBA macros have been written and implemented using two different platforms; the fitting and the optimization platform. The fitting platform calculates not only the adjustable parameters of the chromatographic models, but also the significance of these parameters and furthermore predicts the analyte elution times. The optimization platform determines the gradient conditions that lead to the optimum separation of a mixture of analytes by using the Solver evolutionary mode, provided that proper constraints are set in order to obtain the optimum gradient profile in the minimum gradient time. The performance of the two platforms was tested using experimental and artificial data. It was found that using the proposed spreadsheets, fitting, prediction, and optimization can be performed easily and effectively under all conditions. Overall, the best performance is exhibited by the analytical and Nikitas-Pappa's methods, although the former cannot be used under all circumstances. Copyright © 2015 Elsevier B.V. All rights reserved.

Analysis of the Economic Impact of Large-Scale Deployment of Biomass Resources for Energy and Materials in the Netherlands. Macro-economics biobased synthesis report

International Nuclear Information System (INIS)

Hoefnagels, R.; Dornburg, V.; Faaij, A.; Banse, M.

2009-03-01

The Bio-based Raw Materials Platform (PGG), part of the Energy Transition in The Netherlands, commissioned the Agricultural Economics Research Institute (LEI) and the Copernicus Institute of Utrecht University to conduct research on the macro-economic impact of large scale deployment of biomass for energy and materials in the Netherlands. Two model approaches were applied based on a consistent set of scenario assumptions: a bottom-up study including technoeconomic projections of fossil and bio-based conversion technologies and a topdown study including macro-economic modelling of (global) trade of biomass and fossil resources. The results of the top-down and bottom-up modelling work are reported separately. The results of the synthesis of the modelling work are presented in this report

Clinimetrics and clinical psychometrics: macro- and micro-analysis.

Science.gov (United States)

Tomba, Elena; Bech, Per

2012-01-01

Clinimetrics was introduced three decades ago to specify the domain of clinical markers in clinical medicine (indexes or rating scales). In this perspective, clinical validity is the platform for selecting the various indexes or rating scales (macro-analysis). Psychometric validation of these indexes or rating scales is the measuring aspect (micro-analysis). Clinical judgment analysis by experienced psychiatrists is included in the macro-analysis and the item response theory models are especially preferred in the micro-analysis when using the total score as a sufficient statistic. Clinical assessment tools covering severity of illness scales, prognostic measures, issues of co-morbidity, longitudinal assessments, recovery, stressors, lifestyle, psychological well-being, and illness behavior have been identified. The constructive dialogue in clinimetrics between clinical judgment and psychometric validation procedures is outlined for generating developments of clinical practice in psychiatry. Copyright © 2012 S. Karger AG, Basel.

Are Macro variables good predictors? A prediction based on the number of total medals acquired

Directory of Open Access Journals (Sweden)

Shahram Shafiee

2012-01-01

Full Text Available A large amount of effort is spent on forecasting the outcome of sporting events. Moreover, there are large quantities of data regarding the outcomes of sporting events and the factors which are assumed to contribute to those outcomes. In this paper we tried to predict the success of nations at the Asian Games through macro-economic, political, social and cultural variables. we used the information of variables include urban population, Education Expenditures, Age Structure, GDP Real Growth Rate, GDP Per Capita, Unemployment Rate, Population, Inflation Average, current account balance, life expectancy at birth and Merchandise Trade for all of the participating countries in Asian Games from 1970 to 2006 in order to build the model and then this model was tested by the information of variables in 2010. The prediction is based on the number of total medals acquired each country. In this research we used WEKA software that is a popular suite of machine learning software written in Java. The value of correlation coefficient between the predicted and original ranks is 90.42%. Neural Network Model, between 28 countries mentioned, predicts their ranks according to the maximum difference between predicted and original ranks of 19 countries (67.85% is 3, the maximum difference between predicted and original ranks of 8 countries (28.57% is between 4 to 6 and the difference between predicted and original ranks of 1 countries (3.57% is more than 6.

Prediction of tire/wet road friction and its variation with speed from road macro- and microtexture, and tire-related properties

OpenAIRE

Do , Minh Tan; Delanne , Yves

2004-01-01

In this paper, validation of a model for the speed dependency of friction is presented. Based on the shape of the friction – speed curve, the model assumes that calculation of friction at any speed would need an estimate of friction at very low speed, and the knowledge of its variation with speed described by the Stribeck curve. Two existing models developed at LCPC are then coupled to predict friction versus speed from the following characteristics: road surface macro and microtexture,...

Prediction of Tire/Wet Road Friction and its Variation with speed from Road Macro- and Microtexture, and Tire-Related Properties

OpenAIRE

DO, MT; DELANNE, Y

2004-01-01

In this paper, validation of a model for the speed dependency of friction is presented. Based on the shape of the friction - speed curve, the model assumes that calculation of friction at any speed would need an estimate of friction at very slow speed, and the knowledge of its variation with speed described by the Stribeck curve. Two existing models developed at LCPC are then coupled to predict friction versus speed from the following characteristics road surface macro and microtexture, rubbe...

Transport phenomena of macro and micro flows behind orifice and flow accelerated corrosion

International Nuclear Information System (INIS)

Fujisawa, Nobuyuki; Hayase, Toshiyuki; Ohara, Taku; Ikohagi, Toshiaki

2008-01-01

This paper describes experiment and numerical simulations for macro and micro flows behind an orifice model in a square pipe, which are carried from the viewpoint of flow accelerated corrosion (FAC). The measurements of velocity field behind the orifice model were carried out using particle image velocimetry, and the variations of velocity field with respect to the accuracy of the orifice position were studied. It is found that the reattachment behavior of the flow is highly influenced by the orifice position, which is a critical problem for predicting the pipe thinning phenomena by FAC. The DNS simulation was also conducted for calculating the macro flow behind the orifice. The result suggests that the DNS simulation is applicable to the prediction of pipe thinning macro flow for highly aged nuclear plant. The micro flow simulation can predict the pipe thinning phenomena near the wall. (author)

MARKAL-MACRO: A linked model for energy-economy analysis

International Nuclear Information System (INIS)

Manne, A.S.; Wene, C.O.

1992-02-01

MARKAL-MACRO is an experiment in model linkage for energy and economy analysis. This new tool is intended as an improvement over existing methods for energy strategy assessment. It is designed specifically for estimating the costs and analyzing the technologies proposed for reducing environmental risks such as global climate change or regional air pollution. The greenhouse gas debate illustrates the usefulness of linked energy-economy models. A central issue is the coupling between economic growth, the level of energy demands, and the development of an energy system to supply these demands. The debate is often connected with alternative modeling approaches. The competing philosophies may be labeled ''top-down macroeconomic'' and ''bottom-up engineering'' perspectives. MARKAL is a systems engineering (physical process) analysis built on the concept of a Reference Energy System (RES). MARKAL is solved by means of dynamic linear programming. In most applications, the end use demands are fixed, and an economically efficient solution is obtained by minimizing the present value of energy system's costs throughout the planning horizon. MACRO is a macroeconomic model with an aggregated view of long-term economic growth. The basis input factors of production are capital, labor and individual forms of energy. MACRO is solved by nonlinear optimization

Microstructure Charaterization of a Hardened and Tempered Tool Steel: from Macro to Nano Scale

DEFF Research Database (Denmark)

Højerslev, Christian; Somers, Marcel A. J.; Carstensen, Jesper V.

2002-01-01

The microstructure of a conventionally heat treated PM AISI M3:2 tool steel, was characterised by a combination of light optical and electron microscopy, covering the range from micro to nano scale. Dilatometry and X-ray diffractometry were used for an overall macro characterisation of the phases...

Electrical current at micro-/macro-scale of undoped and nitrogen-doped MWPECVD diamond films

Science.gov (United States)

Cicala, G.; Velardi, L.; Senesi, G. S.; Picca, R. A.; Cioffi, N.

2017-12-01

Chemical, structural, morphological and micro-/macro-electrical properties of undoped and nitrogen-(N-)doped diamond films are determined by X-ray photoelectron spectroscopy, Raman and photoluminescence spectroscopies, field emission scanning electron microscopy, atomic force microscopy, scanning capacitance microscopy (SCM) and two points technique for I-V characteristics, respectively. The characterization results are very useful to examine and understand the relationship among these properties. The effect of the nitrogen incorporation in diamond films is investigated through the evolution of the chemical, structural, morphological and topographical features and of the electrical behavior. The distribution of the electrical current is first assessed at millimeter scale on the surface of diamond films and then at micrometer scale on small regions in order to establish the sites where the carriers preferentially move. Specifically, the SCM images indicate a non-uniform distribution of carriers on the morphological structures mainly located along the grain boundaries. A good agreement is found by comparing the electrical currents at the micro- and macro-scale. This work aims to highlight phenomena such as photo- and thermionic emission from N-doped diamond useful for microelectronic engineering.

Development and validation of logistic prognostic models by predefined SAS-macros

Directory of Open Access Journals (Sweden)

Ziegler, Christoph

2006-02-01

Full Text Available In medical decision making about therapies or diagnostic procedures in the treatment of patients the prognoses of the course or of the magnitude of diseases plays a relevant role. Beside of the subjective attitude of the clinician mathematical models can help in providing such prognoses. Such models are mostly multivariate regression models. In the case of a dichotomous outcome the logistic model will be applied as the standard model. In this paper we will describe SAS-macros for the development of such a model, for examination of the prognostic performance, and for model validation. The rational for this developmental approach of a prognostic modelling and the description of the macros can only given briefly in this paper. Much more details are given in. These 14 SAS-macros are a tool for setting up the whole process of deriving a prognostic model. Especially the possibility of validating the model by a standardized software tool gives an opportunity, which is not used in general in published prognostic models. Therefore, this can help to develop new models with good prognostic performance for use in medical applications.

Line-scan macro-scale Raman chemical imaging for authentication of powdered foods and ingredients

Science.gov (United States)

Adulteration and fraud for powdered foods and ingredients are rising food safety risks that threaten consumers’ health. In this study, a newly developed line-scan macro-scale Raman imaging system using a 5 W 785 nm line laser as excitation source was used to authenticate the food powders. The system...

Comparing an Annual and a Daily Time-Step Model for Predicting Field-Scale Phosphorus Loss.

Science.gov (United States)

Bolster, Carl H; Forsberg, Adam; Mittelstet, Aaron; Radcliffe, David E; Storm, Daniel; Ramirez-Avila, John; Sharpley, Andrew N; Osmond, Deanna

2017-11-01

A wide range of mathematical models are available for predicting phosphorus (P) losses from agricultural fields, ranging from simple, empirically based annual time-step models to more complex, process-based daily time-step models. In this study, we compare field-scale P-loss predictions between the Annual P Loss Estimator (APLE), an empirically based annual time-step model, and the Texas Best Management Practice Evaluation Tool (TBET), a process-based daily time-step model based on the Soil and Water Assessment Tool. We first compared predictions of field-scale P loss from both models using field and land management data collected from 11 research sites throughout the southern United States. We then compared predictions of P loss from both models with measured P-loss data from these sites. We observed a strong and statistically significant ( loss between the two models; however, APLE predicted, on average, 44% greater dissolved P loss, whereas TBET predicted, on average, 105% greater particulate P loss for the conditions simulated in our study. When we compared model predictions with measured P-loss data, neither model consistently outperformed the other, indicating that more complex models do not necessarily produce better predictions of field-scale P loss. Our results also highlight limitations with both models and the need for continued efforts to improve their accuracy. Copyright © by the American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America, Inc.

An Alternative Macro-economic Model for the Classroom

Science.gov (United States)

Holmes, Bryan

1976-01-01

Presents Michal Kalecki's macro-economic model and two-sector version of the model by Robinson and Eatwell as circular flow diagrams. Advantages of using this approach in first-year undergraduate economics programs are discussed. Available from: General Secretary, Economics Association, Room 340, Hamilton House, Mabledon Place, London WC1H 9BH,…

Modeling PM10 gravimetric data from the Qalabotjha low-smoke fuels macro-scale experiment in South Africa

International Nuclear Information System (INIS)

Engelbrecht, J.P.; Swanepoel, L.; Zunckel, M.; Chow, J.C.

1998-01-01

D-grade domestic coal is being widely used for household cooking and heating purposes by the poorer urban communities in South Africa. The smoke from the combustion of coal has had a severe impact on the health of communities living in the rural townships and cities. To alleviate this escalating problem, the Department of Minerals and Energy of South Africa evaluated low-smoke fuels as an alternative source of energy. The technical and social implications of such fuels were investigated in the course of the Qalabotjha Low-Smoke Fuels Macro-Scale Experiment. Three low-smoke fuels (Chartech, African Fine Carbon (AFC) and Flame Africa) were tested in Qalabotjha over a 10 to 20 day period. This paper presents results from a PM10 TEOM continuous monitor at the Clinic site in Qalabotjha over the mentioned monitoring period. Both the fuel-type and the wind were found to have an effect on the air particulate concentrations. An exponential model which incorporates both these variables is proposed. This model allows for all measured particulate concentrations to be re-calculated to zero wind values. From the analysis of variance (ANOVA) calculations on the zero wind concentrations, it is concluded that the combustion of low-smoke fuels did make a significant improvement to the air quality in Qalabotjha over the period when these were used

Changes in Income at Macro Level Predict Sex Ratio at Birth in OECD Countries.

Science.gov (United States)

Kanninen, Ohto; Karhula, Aleksi

2016-01-01

The human sex ratio at birth (SRB) is approximately 107 boys for every 100 girls. SRB was rising until the World War II and has been declining slightly after the 1950s in several industrial countries. Recent studies have shown that SRB varies according to exposure to disasters and socioeconomic conditions. However, it remains unknown whether changes in SRB can be explained by observable macro-level socioeconomic variables across multiple years and countries. Here we show that changes in disposable income at the macro level positively predict SRB in OECD countries. A one standard deviation increase in the change of disposable income is associated with an increase of 1.03 male births per 1000 female births. The relationship is possibly nonlinear and driven by extreme changes. The association varies from country to country being particular strong in Estonia. This is the first evidence to show that economic and social conditions are connected to SRB across countries at the macro level. This calls for further research on the effects of societal conditions on general characteristics at birth.

Micro-Scale Experiments and Models for Composite Materials with Materials Research

DEFF Research Database (Denmark)

Zike, Sanita

Numerical models are frequently implemented to study micro-mechanical processes in polymer/fibre composites. To ensure that these models are accurate, the length scale dependent properties of the fibre and polymer matrix have to be taken into account. Most often this is not the case, and material...... properties acquired at macro-scale are used for micro-mechanical models. This is because material properties at the macro-scale are much more available and the test procedures to obtain them are well defined. The aim of this research was to find methods to extract the micro-mechanical properties of the epoxy...... resin used in polymer/fibre composites for wind turbine blades combining experimental, numerical, and analytical approaches. Experimentally, in order to mimic the stress state created by a void in a bulk material, test samples with finite root radii were made and subjected to a double cantilever beam...

Micro- and macro-geographic scale effect on the molecular imprint of selection and adaptation in Norway spruce.

Directory of Open Access Journals (Sweden)

Marta Scalfi

Full Text Available Forest tree species of temperate and boreal regions have undergone a long history of demographic changes and evolutionary adaptations. The main objective of this study was to detect signals of selection in Norway spruce (Picea abies [L.] Karst, at different sampling-scales and to investigate, accounting for population structure, the effect of environment on species genetic diversity. A total of 384 single nucleotide polymorphisms (SNPs representing 290 genes were genotyped at two geographic scales: across 12 populations distributed along two altitudinal-transects in the Alps (micro-geographic scale, and across 27 populations belonging to the range of Norway spruce in central and south-east Europe (macro-geographic scale. At the macrogeographic scale, principal component analysis combined with Bayesian clustering revealed three major clusters, corresponding to the main areas of southern spruce occurrence, i.e. the Alps, Carpathians, and Hercynia. The populations along the altitudinal transects were not differentiated. To assess the role of selection in structuring genetic variation, we applied a Bayesian and coalescent-based F(ST-outlier method and tested for correlations between allele frequencies and climatic variables using regression analyses. At the macro-geographic scale, the F(ST-outlier methods detected together 11 F(ST-outliers. Six outliers were detected when the same analyses were carried out taking into account the genetic structure. Regression analyses with population structure correction resulted in the identification of two (micro-geographic scale and 38 SNPs (macro-geographic scale significantly correlated with temperature and/or precipitation. Six of these loci overlapped with F(ST-outliers, among them two loci encoding an enzyme involved in riboflavin biosynthesis and a sucrose synthase. The results of this study indicate a strong relationship between genetic and environmental variation at both geographic scales. It also

Micro- and macro-geographic scale effect on the molecular imprint of selection and adaptation in Norway spruce.

Science.gov (United States)

Scalfi, Marta; Mosca, Elena; Di Pierro, Erica Adele; Troggio, Michela; Vendramin, Giovanni Giuseppe; Sperisen, Christoph; La Porta, Nicola; Neale, David B

2014-01-01

Forest tree species of temperate and boreal regions have undergone a long history of demographic changes and evolutionary adaptations. The main objective of this study was to detect signals of selection in Norway spruce (Picea abies [L.] Karst), at different sampling-scales and to investigate, accounting for population structure, the effect of environment on species genetic diversity. A total of 384 single nucleotide polymorphisms (SNPs) representing 290 genes were genotyped at two geographic scales: across 12 populations distributed along two altitudinal-transects in the Alps (micro-geographic scale), and across 27 populations belonging to the range of Norway spruce in central and south-east Europe (macro-geographic scale). At the macrogeographic scale, principal component analysis combined with Bayesian clustering revealed three major clusters, corresponding to the main areas of southern spruce occurrence, i.e. the Alps, Carpathians, and Hercynia. The populations along the altitudinal transects were not differentiated. To assess the role of selection in structuring genetic variation, we applied a Bayesian and coalescent-based F(ST)-outlier method and tested for correlations between allele frequencies and climatic variables using regression analyses. At the macro-geographic scale, the F(ST)-outlier methods detected together 11 F(ST)-outliers. Six outliers were detected when the same analyses were carried out taking into account the genetic structure. Regression analyses with population structure correction resulted in the identification of two (micro-geographic scale) and 38 SNPs (macro-geographic scale) significantly correlated with temperature and/or precipitation. Six of these loci overlapped with F(ST)-outliers, among them two loci encoding an enzyme involved in riboflavin biosynthesis and a sucrose synthase. The results of this study indicate a strong relationship between genetic and environmental variation at both geographic scales. It also suggests that an

Multi-scale modelling of the hydro-mechanical behaviour of argillaceous rocks

International Nuclear Information System (INIS)

Van den Eijnden, Bram

2015-01-01

Feasibility studies for deep geological radioactive waste disposal facilities have led to an increased interest in the geomechanical modelling of its host rock. In France, a potential host rock is the Callovo-Oxfordian clay-stone. The low permeability of this material is of key importance, as the principle of deep geological disposal strongly relies on the sealing capacity of the host formation. The permeability being coupled to the mechanical material state, hydro-mechanical coupled behaviour of the clay-stone becomes important when mechanical alterations are induced by gallery excavation in the so-called excavation damaged zone (EDZ). In materials with microstructure such as the Callovo-Oxfordian clay-stone, the macroscopic behaviour has its origin in the interaction of its micromechanical constituents. In addition to the coupling between hydraulic and mechanical behaviour, a coupling between the micro (material microstructure) and macro scale will be made. By means of the development of a framework of computational homogenization for hydro-mechanical coupling, a double-scale modelling approach is formulated, for which the macro-scale constitutive relations are derived from the microscale by homogenization. An existing model for the modelling of hydro-mechanical coupling based on the distinct definition of grains and intergranular pore space is adopted and modified to enable the application of first order computational homogenization for obtaining macro-scale stress and fluid transport responses. This model is used to constitute a periodic representative elementary volume (REV) that allows the representation of the local macroscopic behaviour of the clay-stone. As a response to deformation loading, the behaviour of the REV represents the numerical equivalent of a constitutive relation at the macro-scale. For the required consistent tangent operators, the framework of computational homogenization by static condensation is extended to hydro-mechanical coupling. The

Growth structure and environment. 6 contributions to the macro economic model development

International Nuclear Information System (INIS)

Wier, Mette

1998-04-01

This thesis comprises 6 papers on the application of macro economic models to environmental problems. Interactions between the economic and the ecological models are elucidated and a description is given of a possible systematization of of the environmental-economic cycle within a macro economic model. Economic and technological limitations affecting the potential environmental advantages are discussed. In the second part of the thesis the general interdependence of production and consumption, and the various forms of environmental stress is analyzed. For this purpose an environment-related input-output model is presented, where for each industry there are given emissions and/or consumption of natural resources (so-called environmental coefficients), which are likely to originate from the activities of this industry. As examples of macro economic modelling,the nitrogen cycle in Denmark, environmental effects of consumer choice, use of building materials and emission due to energy generation and consumption etc. are analyzed. (EG) 146 refs

A national-scale model of linear features improves predictions of farmland biodiversity.

Science.gov (United States)

Sullivan, Martin J P; Pearce-Higgins, James W; Newson, Stuart E; Scholefield, Paul; Brereton, Tom; Oliver, Tom H

2017-12-01

Modelling species distribution and abundance is important for many conservation applications, but it is typically performed using relatively coarse-scale environmental variables such as the area of broad land-cover types. Fine-scale environmental data capturing the most biologically relevant variables have the potential to improve these models. For example, field studies have demonstrated the importance of linear features, such as hedgerows, for multiple taxa, but the absence of large-scale datasets of their extent prevents their inclusion in large-scale modelling studies.We assessed whether a novel spatial dataset mapping linear and woody-linear features across the UK improves the performance of abundance models of 18 bird and 24 butterfly species across 3723 and 1547 UK monitoring sites, respectively.Although improvements in explanatory power were small, the inclusion of linear features data significantly improved model predictive performance for many species. For some species, the importance of linear features depended on landscape context, with greater importance in agricultural areas. Synthesis and applications . This study demonstrates that a national-scale model of the extent and distribution of linear features improves predictions of farmland biodiversity. The ability to model spatial variability in the role of linear features such as hedgerows will be important in targeting agri-environment schemes to maximally deliver biodiversity benefits. Although this study focuses on farmland, data on the extent of different linear features are likely to improve species distribution and abundance models in a wide range of systems and also can potentially be used to assess habitat connectivity.

A Fractional Micro-Macro Model for Crowds of Pedestrians Based on Fractional Mean Field Games

Institute of Scientific and Technical Information of China (English)

Kecai Cao; Yang Quan Chen; Daniel Stuart

2016-01-01

Modeling a crowd of pedestrians has been considered in this paper from different aspects. Based on fractional microscopic model that may be much more close to reality, a fractional macroscopic model has been proposed using conservation law of mass. Then in order to characterize the competitive and cooperative interactions among pedestrians, fractional mean field games are utilized in the modeling problem when the number of pedestrians goes to infinity and fractional dynamic model composed of fractional backward and fractional forward equations are constructed in macro scale. Fractional micromacro model for crowds of pedestrians are obtained in the end.Simulation results are also included to illustrate the proposed fractional microscopic model and fractional macroscopic model,respectively.

A Cellular Automaton / Finite Element model for predicting grain texture development in galvanized coatings

Science.gov (United States)

Guillemot, G.; Avettand-Fènoël, M.-N.; Iosta, A.; Foct, J.

2011-01-01

Hot-dipping galvanizing process is a widely used and efficient way to protect steel from corrosion. We propose to master the microstructure of zinc grains by investigating the relevant process parameters. In order to improve the texture of this coating, we model grain nucleation and growth processes and simulate the zinc solid phase development. A coupling scheme model has been applied with this aim. This model improves a previous two-dimensional model of the solidification process. It couples a cellular automaton (CA) approach and a finite element (FE) method. CA grid and FE mesh are superimposed on the same domain. The grain development is simulated at the micro-scale based on the CA grid. A nucleation law is defined using a Gaussian probability and a random set of nucleating cells. A crystallographic orientation is defined for each one with a choice of Euler's angle (Ψ,θ,φ). A small growing shape is then associated to each cell in the mushy domain and a dendrite tip kinetics is defined using the model of Kurz [2]. The six directions of basal plane and the two perpendicular directions develop in each mushy cell. During each time step, cell temperature and solid fraction are then determined at micro-scale using the enthalpy conservation relation and variations are reassigned at macro-scale. This coupling scheme model enables to simulate the three-dimensional growing kinetics of the zinc grain in a two-dimensional approach. Grain structure evolutions for various cooling times have been simulated. Final grain structure has been compared to EBSD measurements. We show that the preferentially growth of dendrite arms in the basal plane of zinc grains is correctly predicted. The described coupling scheme model could be applied for simulated other product or manufacturing processes. It constitutes an approach gathering both micro and macro scale models.

A Macro Model of Squeeze-Film Air Damping in the Free-Molecule Regime

KAUST Repository

Hong, Gang; Ye, Wenjing

2009-01-01

An accurate macro model for free‐molecule squeeze‐film air damping on micro plate resonators is present. This model relates air damping directly with device dimensions and operation parameters and therefore provides an efficient tool for the design of high‐performance micro resonators. The construction of the macro model is based on Molecular Dynamics (MD) simulations and analytical traveling‐time distribution. Its accuracy is validated via the comparison between the calculated quality factors of several micro resonators and the available experimental measurements and full MD simulation results. It has been found that the relative errors of the quality factors of two resonators, as compared with experimental data, are 3.9% and 5.7% respectively. The agreements between the macro model results and MD simulation results, on the other hand, are excellent in all cases considered.

A Macro Model of Squeeze-Film Air Damping in the Free-Molecule Regime

KAUST Repository

Hong, Gang

2009-11-30

An accurate macro model for free‐molecule squeeze‐film air damping on micro plate resonators is present. This model relates air damping directly with device dimensions and operation parameters and therefore provides an efficient tool for the design of high‐performance micro resonators. The construction of the macro model is based on Molecular Dynamics (MD) simulations and analytical traveling‐time distribution. Its accuracy is validated via the comparison between the calculated quality factors of several micro resonators and the available experimental measurements and full MD simulation results. It has been found that the relative errors of the quality factors of two resonators, as compared with experimental data, are 3.9% and 5.7% respectively. The agreements between the macro model results and MD simulation results, on the other hand, are excellent in all cases considered.

Scaling predictive modeling in drug development with cloud computing.

Science.gov (United States)

Moghadam, Behrooz Torabi; Alvarsson, Jonathan; Holm, Marcus; Eklund, Martin; Carlsson, Lars; Spjuth, Ola

2015-01-26

Growing data sets with increased time for analysis is hampering predictive modeling in drug discovery. Model building can be carried out on high-performance computer clusters, but these can be expensive to purchase and maintain. We have evaluated ligand-based modeling on cloud computing resources where computations are parallelized and run on the Amazon Elastic Cloud. We trained models on open data sets of varying sizes for the end points logP and Ames mutagenicity and compare with model building parallelized on a traditional high-performance computing cluster. We show that while high-performance computing results in faster model building, the use of cloud computing resources is feasible for large data sets and scales well within cloud instances. An additional advantage of cloud computing is that the costs of predictive models can be easily quantified, and a choice can be made between speed and economy. The easy access to computational resources with no up-front investments makes cloud computing an attractive alternative for scientists, especially for those without access to a supercomputer, and our study shows that it enables cost-efficient modeling of large data sets on demand within reasonable time.

Model Predictive Control for a Small Scale Unmanned Helicopter

Directory of Open Access Journals (Sweden)

Jianfu Du

2008-11-01

Full Text Available Kinematical and dynamical equations of a small scale unmanned helicoper are presented in the paper. Based on these equations a model predictive control (MPC method is proposed for controlling the helicopter. This novel method allows the direct accounting for the existing time delays which are used to model the dynamics of actuators and aerodynamics of the main rotor. Also the limits of the actuators are taken into the considerations during the controller design. The proposed control algorithm was verified in real flight experiments where good perfomance was shown in postion control mode.

The asymmetric effect of coal price on the China's macro economy using NARDL model

Science.gov (United States)

Hou, J. C.; Yang, M. C.

2016-08-01

The present work endeavors to explore the asymmetric effect of coal price on the China's macro economy by applying nonlinear autoregressive distributed lag (NARDL) model for the period of January 2005 to June 2015. The obtained results indicate that the coal price has a strong asymmetric effect on China's macro economy in the long-run. Namely one percent increase in coal price leads to 0.6194 percent of the China's macro economy increase; and while the coal price is reduces by 1 percent, the China's macro economy will decrease by 0.008 percent. These data indicate that when coal price rises, the effect on China's macro economy is far greater than the price decline. In the short-run, coal price fluctuation has a positive effect on the China's macro economy.

Application of macro material flow modeling to the decision making process for integrated waste management systems

International Nuclear Information System (INIS)

Vigil, S.A.; Holter, G.M.

1995-04-01

Computer models have been used for almost a decade to model and analyze various aspects of solid waste management Commercially available models exist for estimating the capital and operating costs of landfills, waste-to-energy facilities and compost systems and for optimizing system performance along a single dimension (e.g. cost or transportation distance). An alternative to the use of currently available models is the more flexible macro material flow modeling approach in which a macro scale or regional level approach is taken. Waste materials are tracked through the complete integrated waste management cycle from generation through recycling and reuse, and finally to ultimate disposal. Such an approach has been applied by the authors to two different applications. The STELLA simulation language (for Macintosh computers) was used to model the solid waste management system of Puerto Rico. The model incorporated population projections for all 78 municipalities in Puerto Rico from 1990 to 2010, solid waste generation factors, remaining life for the existing landfills, and projected startup time for new facilities. The Pacific Northwest Laboratory has used the SimScript simulation language (for Windows computers) to model the management of solid and hazardous wastes produced during cleanup and remediation activities at the Hanford Nuclear Site

A comparison between MARKAL-MACRO and MARKAL

International Nuclear Information System (INIS)

Schepers, E.

1995-11-01

Differences between CO 2 -reduction scenarios of the MARKAL-MACRO model and the MARKAL model are studied. Also attention is paid to the rebound effect, i.e. the effect on a price decrease leads to an increase of the energy demand, and energy savings will result in a redistribution of saved income over other goods and services. MARKAL is an energy supply model and MACRO is a macro-economic model. The combination of the two is an example of a hard-linked model between a top-down model (MACRO) and a bottom-up model (MARKAL). 15 figs., 5 tabs., 18 refs., 2 appendices

Hydrogen Macro System Model User Guide, Version 1.2.1

Energy Technology Data Exchange (ETDEWEB)

Ruth, M.; Diakov, V.; Sa, T.; Goldsby, M.; Genung, K.; Hoseley, R.; Smith, A.; Yuzugullu, E.

2009-07-01

The Hydrogen Macro System Model (MSM) is a simulation tool that links existing and emerging hydrogen-related models to perform rapid, cross-cutting analysis. It allows analysis of the economics, primary energy-source requirements, and emissions of hydrogen production and delivery pathways.

Path Loss, Shadow Fading, and Line-Of-Sight Probability Models for 5G Urban Macro-Cellular Scenarios

DEFF Research Database (Denmark)

Sun, Shu; Thomas, Timothy; Rappaport, Theodore S.

2015-01-01

This paper presents key parameters including the line-of-sight (LOS) probability, large-scale path loss, and shadow fading models for the design of future fifth generation (5G) wireless communication systems in urban macro-cellular (UMa) scenarios, using the data obtained from propagation...... measurements in Austin, US, and Aalborg, Denmark, at 2, 10, 18, and 38 GHz. A comparison of different LOS probability models is performed for the Aalborg environment. Both single-slope and dual-slope omnidirectional path loss models are investigated to analyze and contrast their root-mean-square (RMS) errors...

Thermo-mechanical efficiency of the bimetallic strip heat engine at the macro-scale and micro-scale

International Nuclear Information System (INIS)

Arnaud, A; Boughaleb, J; Monfray, S; Boeuf, F; Skotnicki, T; Cugat, O

2015-01-01

Bimetallic strip heat engines are energy harvesters that exploit the thermo-mechanical properties of bistable bimetallic membranes to convert heat into mechanical energy. They thus represent a solution to transform low-grade heat into electrical energy if the bimetallic membrane is coupled with an electro-mechanical transducer. The simplicity of these devices allows us to consider their miniaturization using MEMS fabrication techniques. In order to design and optimize these devices at the macro-scale and micro-scale, this article proposes an explanation of the origin of the thermal snap-through by giving the expressions of the constitutive equations of composite beams. This allows us to evaluate the capability of bimetallic strips to convert heat into mechanical energy whatever their size is, and to give the theoretical thermo-mechanical efficiencies which can be obtained with these harvesters. (paper)

Pesticide volatilization from soil and plant surfaces: Measurements at different scales versus model predictions

Energy Technology Data Exchange (ETDEWEB)

Wolters, A.

2003-07-01

Simulation of pesticide volatilization from plant and soil surfaces as an integral component of pesticide fate models is of utmost importance, especially as part of the PEC (predicted environmental concentrations) models used in the registration procedures for pesticides. Experimentally determined volatilization rates at different scales were compared to model predictions to improve recent approaches included in European registration models. To assess the influence of crucial factors affecting volatilization under well-defined conditions, a laboratory chamber was set-up and validated. Aerodynamic conditions were adjusted to fulfill the requirements of the German guideline on assessing pesticide volatilization for registration purposes. At the semi-field scale, volatilization rates were determined in a wind-tunnel study after soil surface application of pesticides to gleyic cambisol. The following descending order of cumulative volatilization was observed: chlorpyrifos > parathion-methyl > terbuthylazine > fenpropimorph. Parameterization of the models PEARL (pesticide emission assessment at regional and local scales) and PELMO (pesticide leaching model) was performed to mirror the experimental boundary conditions. (orig.)

A multi-scale energy demand model suggests sharing market risks with intelligent energy cooperatives

NARCIS (Netherlands)

G. Methenitis (Georgios); M. Kaisers (Michael); J.A. La Poutré (Han)

2015-01-01

textabstractIn this paper, we propose a multi-scale model of energy demand that is consistent with observations at a macro scale, in our use-case standard load profiles for (residential) electric loads. We employ the model to study incentives to assume the risk of volatile market prices for

Analysis of effective diffusivity of cement based materials by multi-scale modelling

International Nuclear Information System (INIS)

Dridi, Wissem

2013-01-01

This paper presents a simplified composite model, which considers the contribution of each phase participating to the transport within OPC pastes and concretes. At the micrometer scale, the phases considered hereafter are capillary porosity (macro-porosity) and the Low Density and the High Density C-S-H both containing gel pores (nano-porosity). Predicted values of tritiated water (HTO) diffusivity in OPC pastes with various (w/c) ratios are confronted to experimental results with a good agreement. The approach is then extended to mortars and concretes scale where microstructure is described by a three phase composite sphere assemblage. Here, elementary phase distribution is assumed to change as a function of distance from aggregate surface. Model results about HTO diffusivities of mortars and concretes are presented with some experimental values. The competition between the more diffusing ITZ zone and the less diffusing bulk matrix is investigated from a sensitive analysis. The dominance of the ITZ control is confirmed. (authors)

The development of macros program-based cognitive evaluation model via e-learning course mathematics in senior high school based on curriculum 2013

Directory of Open Access Journals (Sweden)

Djoko Purnomo

2017-02-01

Full Text Available The specific purpose of this research is: The implementation of the application of the learning tool with a form cognitive learning evaluation model based macros program via E-learning at High School grade X at july-december based on 2013 curriculum. The method used in this research followed the procedures is research and development by Borg and Gall [2]. In second year, population analysis has conducted at several universities in Semarang. The results of the research and application development of macro program-based cognitive evaluation model is effective which can be seen from (1 the student learning result is over KKM, (2 The student independency affects learning result positively, (3 the student learning a result by using macros program-based cognitive evaluation model is better than students class control. Based on the results above, the development of macros program-based cognitive evaluation model that have been tested have met quality standards according to Akker (1999. Large-scale testing includes operational phase of field testing and final product revision, i.e trials in the wider class that includes students in mathematics education major in several universities, they are the Universitas PGRI Semarang, Universitas Islam Sultan Agung and the Universitas Islam NegeriWalisongo Semarang. The positive responses is given by students at the Universitas PGRI Semarang, Universitas Islam Sultan Agung and the Universitas Islam NegeriWalisongo Semarang.

Novel patch modelling method for efficient simulation and prediction uncertainty analysis of multi-scale groundwater flow and transport processes

Science.gov (United States)

Sreekanth, J.; Moore, Catherine

2018-04-01

The application of global sensitivity and uncertainty analysis techniques to groundwater models of deep sedimentary basins are typically challenged by large computational burdens combined with associated numerical stability issues. The highly parameterized approaches required for exploring the predictive uncertainty associated with the heterogeneous hydraulic characteristics of multiple aquifers and aquitards in these sedimentary basins exacerbate these issues. A novel Patch Modelling Methodology is proposed for improving the computational feasibility of stochastic modelling analysis of large-scale and complex groundwater models. The method incorporates a nested groundwater modelling framework that enables efficient simulation of groundwater flow and transport across multiple spatial and temporal scales. The method also allows different processes to be simulated within different model scales. Existing nested model methodologies are extended by employing 'joining predictions' for extrapolating prediction-salient information from one model scale to the next. This establishes a feedback mechanism supporting the transfer of information from child models to parent models as well as parent models to child models in a computationally efficient manner. This feedback mechanism is simple and flexible and ensures that while the salient small scale features influencing larger scale prediction are transferred back to the larger scale, this does not require the live coupling of models. This method allows the modelling of multiple groundwater flow and transport processes using separate groundwater models that are built for the appropriate spatial and temporal scales, within a stochastic framework, while also removing the computational burden associated with live model coupling. The utility of the method is demonstrated by application to an actual large scale aquifer injection scheme in Australia.

SPSS macros to compare any two fitted values from a regression model.

Science.gov (United States)

Weaver, Bruce; Dubois, Sacha

2012-12-01

In regression models with first-order terms only, the coefficient for a given variable is typically interpreted as the change in the fitted value of Y for a one-unit increase in that variable, with all other variables held constant. Therefore, each regression coefficient represents the difference between two fitted values of Y. But the coefficients represent only a fraction of the possible fitted value comparisons that might be of interest to researchers. For many fitted value comparisons that are not captured by any of the regression coefficients, common statistical software packages do not provide the standard errors needed to compute confidence intervals or carry out statistical tests-particularly in more complex models that include interactions, polynomial terms, or regression splines. We describe two SPSS macros that implement a matrix algebra method for comparing any two fitted values from a regression model. The !OLScomp and !MLEcomp macros are for use with models fitted via ordinary least squares and maximum likelihood estimation, respectively. The output from the macros includes the standard error of the difference between the two fitted values, a 95% confidence interval for the difference, and a corresponding statistical test with its p-value.

Validation of model predictions of pore-scale fluid distributions during two-phase flow

Science.gov (United States)

Bultreys, Tom; Lin, Qingyang; Gao, Ying; Raeini, Ali Q.; AlRatrout, Ahmed; Bijeljic, Branko; Blunt, Martin J.

2018-05-01

Pore-scale two-phase flow modeling is an important technology to study a rock's relative permeability behavior. To investigate if these models are predictive, the calculated pore-scale fluid distributions which determine the relative permeability need to be validated. In this work, we introduce a methodology to quantitatively compare models to experimental fluid distributions in flow experiments visualized with microcomputed tomography. First, we analyzed five repeated drainage-imbibition experiments on a single sample. In these experiments, the exact fluid distributions were not fully repeatable on a pore-by-pore basis, while the global properties of the fluid distribution were. Then two fractional flow experiments were used to validate a quasistatic pore network model. The model correctly predicted the fluid present in more than 75% of pores and throats in drainage and imbibition. To quantify what this means for the relevant global properties of the fluid distribution, we compare the main flow paths and the connectivity across the different pore sizes in the modeled and experimental fluid distributions. These essential topology characteristics matched well for drainage simulations, but not for imbibition. This suggests that the pore-filling rules in the network model we used need to be improved to make reliable predictions of imbibition. The presented analysis illustrates the potential of our methodology to systematically and robustly test two-phase flow models to aid in model development and calibration.

Simulation of UMTS Capacity and Quality of Coverage in Urban Macro- and Microcellular Environment

Directory of Open Access Journals (Sweden)

P. Pechac

2005-12-01

Full Text Available This paper deals with simulations of a radio interface of thirdgeneration (3G mobile systems operating in the WCDMA FDD modeincluding propagation predictions in macro and microcells. In the radionetwork planning of 3G mobile systems, the quality of coverage and thesystem capacity present a common problem. Both macro and microcellularconcepts are very important for implementing wireless communicationsystems, such as Universal Mobile Telecommunication Systems (UMTS indense urban areas. The aim of this paper is to introduce differentimpacts - selected bit rate, uplink (UL loading, allocation and numberof Nodes B, selected propagation prediction models, macro andmicrocellular environment - on system capacity and quality of coveragein UMTS networks. Both separated and composite simulation scenarios ofmacro and microcellular environments are presented. The necessity of aniteration-based simulation approach and site-specific propagationmodeling in microcells is proven.

The role of money in modern macro models

OpenAIRE

Seitz, Franz; Schmidt, Markus A.

2013-01-01

This paper is the starting point of a series of analyses aiming at re-discovering the role of money for monetary policy purposes. It provides an overview of the role of money in modern macro models. In particular, we are focussing on New Keynesian and New Monetarist models to investigate their main findings and most significant shortcomings in considering money properly. As a further step, we ask about the role of financial intermediaries in this respect. In dealing with these issues, we dist...

Modelling of vector hysteresis at macromagnetic scale: Open questions and challenges

International Nuclear Information System (INIS)

Cardelli, E.; Faba, A.

2016-01-01

After a short review of some experimental evidences the motivations that lead to the practical need of phenomenological modelling for the analysis of magnetic materials at macro-scale, and some challenging formulations are presented and discussed. Examples of practical applications are reported.

Predicting growth of the healthy infant using a genome scale metabolic model.

Science.gov (United States)

Nilsson, Avlant; Mardinoglu, Adil; Nielsen, Jens

2017-01-01

An estimated 165 million children globally have stunted growth, and extensive growth data are available. Genome scale metabolic models allow the simulation of molecular flux over each metabolic enzyme, and are well adapted to analyze biological systems. We used a human genome scale metabolic model to simulate the mechanisms of growth and integrate data about breast-milk intake and composition with the infant's biomass and energy expenditure of major organs. The model predicted daily metabolic fluxes from birth to age 6 months, and accurately reproduced standard growth curves and changes in body composition. The model corroborates the finding that essential amino and fatty acids do not limit growth, but that energy is the main growth limiting factor. Disruptions to the supply and demand of energy markedly affected the predicted growth, indicating that elevated energy expenditure may be detrimental. The model was used to simulate the metabolic effect of mineral deficiencies, and showed the greatest growth reduction for deficiencies in copper, iron, and magnesium ions which affect energy production through oxidative phosphorylation. The model and simulation method were integrated to a platform and shared with the research community. The growth model constitutes another step towards the complete representation of human metabolism, and may further help improve the understanding of the mechanisms underlying stunting.

Model Predictive Control for Flexible Power Consumption of Large-Scale Refrigeration Systems

DEFF Research Database (Denmark)

Shafiei, Seyed Ehsan; Stoustrup, Jakob; Rasmussen, Henrik

2014-01-01

A model predictive control (MPC) scheme is introduced to directly control the electrical power consumption of large-scale refrigeration systems. Deviation from the baseline of the consumption is corresponded to the storing and delivering of thermal energy. By virtue of such correspondence...

Traffic Flow Prediction Model for Large-Scale Road Network Based on Cloud Computing

Directory of Open Access Journals (Sweden)

Zhaosheng Yang

2014-01-01

Full Text Available To increase the efficiency and precision of large-scale road network traffic flow prediction, a genetic algorithm-support vector machine (GA-SVM model based on cloud computing is proposed in this paper, which is based on the analysis of the characteristics and defects of genetic algorithm and support vector machine. In cloud computing environment, firstly, SVM parameters are optimized by the parallel genetic algorithm, and then this optimized parallel SVM model is used to predict traffic flow. On the basis of the traffic flow data of Haizhu District in Guangzhou City, the proposed model was verified and compared with the serial GA-SVM model and parallel GA-SVM model based on MPI (message passing interface. The results demonstrate that the parallel GA-SVM model based on cloud computing has higher prediction accuracy, shorter running time, and higher speedup.

CT-Based Micro-Mechanical Approach to Predict Response of Closed-Cell Porous Biomaterials to Low-Velocity Impact

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Mehrdad Koloushani

2018-03-01

Full Text Available In this study, a new numerical approach based on CT-scan images and finite element (FE method has been used to predict the mechanical behavior of closed-cell foams under impact loading. Micro-structural FE models based on CT-scan images of foam specimens (elastic-plastic material model with material constants of bulk aluminum and macro-mechanical FE models (with crushable foam material model with material constants of foams were constructed. Several experimental tests were also conducted to see which of the two noted (micro- or macro- mechanical FE models can better predict the deformation and force-displacement curves of foams. Compared to the macro-structural models, the results of the micro-structural models were much closer to the corresponding experimental results. This can be explained by the fact that the micro-structural models are able to take into account the interaction of stress waves with cell walls and the complex pathways the stress waves have to go through, while the macro-structural models do not have such capabilities. Despite their high demand for computational resources, using micro-scale FE models is very beneficial when one needs to understand the failure mechanisms acting in the micro-structure of a foam in order to modify or diminish them.

Macro-architectured cellular materials: Properties, characteristic modes, and prediction methods

Science.gov (United States)

Ma, Zheng-Dong

2017-12-01

Macro-architectured cellular (MAC) material is defined as a class of engineered materials having configurable cells of relatively large (i.e., visible) size that can be architecturally designed to achieve various desired material properties. Two types of novel MAC materials, negative Poisson's ratio material and biomimetic tendon reinforced material, were introduced in this study. To estimate the effective material properties for structural analyses and to optimally design such materials, a set of suitable homogenization methods was developed that provided an effective means for the multiscale modeling of MAC materials. First, a strain-based homogenization method was developed using an approach that separated the strain field into a homogenized strain field and a strain variation field in the local cellular domain superposed on the homogenized strain field. The principle of virtual displacements for the relationship between the strain variation field and the homogenized strain field was then used to condense the strain variation field onto the homogenized strain field. The new method was then extended to a stress-based homogenization process based on the principle of virtual forces and further applied to address the discrete systems represented by the beam or frame structures of the aforementioned MAC materials. The characteristic modes and the stress recovery process used to predict the stress distribution inside the cellular domain and thus determine the material strengths and failures at the local level are also discussed.

A novel macro-model for spin-transfer-torque based magnetic-tunnel-junction elements

Science.gov (United States)

Lee, Seungyeon; Lee, Hyunjoo; Kim, Sojeong; Lee, Seungjun; Shin, Hyungsoon

2010-04-01

Spin-transfer-torque (STT) switching in magnetic-tunnel-junction (MTJ) has important merits over the conventional field induced magnetic switching (FIMS) MRAM in avoiding half-select problem, and improving scalability and selectivity. Design of MRAM circuitry using STT-based MTJ elements requires an accurate circuit model which exactly emulates the characteristics of an MTJ in a circuit simulator such as HSPICE. This work presents a novel macro-model that fully emulates the important characteristics of STT-based MTJ. The macro-model is realized as a three terminal sub-circuit that reproduces asymmetric resistance versus current (R-I) characteristics and temperature dependence of R-I hysteresis of STT-based MTJ element.

An adaptive two-stage analog/regression model for probabilistic prediction of small-scale precipitation in France

Science.gov (United States)

Chardon, Jérémy; Hingray, Benoit; Favre, Anne-Catherine

2018-01-01

Statistical downscaling models (SDMs) are often used to produce local weather scenarios from large-scale atmospheric information. SDMs include transfer functions which are based on a statistical link identified from observations between local weather and a set of large-scale predictors. As physical processes driving surface weather vary in time, the most relevant predictors and the regression link are likely to vary in time too. This is well known for precipitation for instance and the link is thus often estimated after some seasonal stratification of the data. In this study, we present a two-stage analog/regression model where the regression link is estimated from atmospheric analogs of the current prediction day. Atmospheric analogs are identified from fields of geopotential heights at 1000 and 500 hPa. For the regression stage, two generalized linear models are further used to model the probability of precipitation occurrence and the distribution of non-zero precipitation amounts, respectively. The two-stage model is evaluated for the probabilistic prediction of small-scale precipitation over France. It noticeably improves the skill of the prediction for both precipitation occurrence and amount. As the analog days vary from one prediction day to another, the atmospheric predictors selected in the regression stage and the value of the corresponding regression coefficients can vary from one prediction day to another. The model allows thus for a day-to-day adaptive and tailored downscaling. It can also reveal specific predictors for peculiar and non-frequent weather configurations.

Improving predictions of large scale soil carbon dynamics: Integration of fine-scale hydrological and biogeochemical processes, scaling, and benchmarking

Science.gov (United States)

Riley, W. J.; Dwivedi, D.; Ghimire, B.; Hoffman, F. M.; Pau, G. S. H.; Randerson, J. T.; Shen, C.; Tang, J.; Zhu, Q.

2015-12-01

Numerical model representations of decadal- to centennial-scale soil-carbon dynamics are a dominant cause of uncertainty in climate change predictions. Recent attempts by some Earth System Model (ESM) teams to integrate previously unrepresented soil processes (e.g., explicit microbial processes, abiotic interactions with mineral surfaces, vertical transport), poor performance of many ESM land models against large-scale and experimental manipulation observations, and complexities associated with spatial heterogeneity highlight the nascent nature of our community's ability to accurately predict future soil carbon dynamics. I will present recent work from our group to develop a modeling framework to integrate pore-, column-, watershed-, and global-scale soil process representations into an ESM (ACME), and apply the International Land Model Benchmarking (ILAMB) package for evaluation. At the column scale and across a wide range of sites, observed depth-resolved carbon stocks and their 14C derived turnover times can be explained by a model with explicit representation of two microbial populations, a simple representation of mineralogy, and vertical transport. Integrating soil and plant dynamics requires a 'process-scaling' approach, since all aspects of the multi-nutrient system cannot be explicitly resolved at ESM scales. I will show that one approach, the Equilibrium Chemistry Approximation, improves predictions of forest nitrogen and phosphorus experimental manipulations and leads to very different global soil carbon predictions. Translating model representations from the site- to ESM-scale requires a spatial scaling approach that either explicitly resolves the relevant processes, or more practically, accounts for fine-resolution dynamics at coarser scales. To that end, I will present recent watershed-scale modeling work that applies reduced order model methods to accurately scale fine-resolution soil carbon dynamics to coarse-resolution simulations. Finally, we

Macro-scale turbulence modelling for flows in porous media; Modelisation a l'echelle macroscopique d'un ecoulement turbulent au sein d'un milieu poreux

Energy Technology Data Exchange (ETDEWEB)

Pinson, F

2006-03-15

- This work deals with the macroscopic modeling of turbulence in porous media. It concerns heat exchangers, nuclear reactors as well as urban flows, etc. The objective of this study is to describe in an homogenized way, by the mean of a spatial average operator, turbulent flows in a solid matrix. In addition to this first operator, the use of a statistical average operator permits to handle the pseudo-aleatory character of turbulence. The successive application of both operators allows us to derive the balance equations of the kind of flows under study. Two major issues are then highlighted, the modeling of dispersion induced by the solid matrix and the turbulence modeling at a macroscopic scale (Reynolds tensor and turbulent dispersion). To this aim, we lean on the local modeling of turbulence and more precisely on the k - {epsilon} RANS models. The methodology of dispersion study, derived thanks to the volume averaging theory, is extended to turbulent flows. Its application includes the simulation, at a microscopic scale, of turbulent flows within a representative elementary volume of the porous media. Applied to channel flows, this analysis shows that even within the turbulent regime, dispersion remains one of the dominating phenomena within the macro-scale modeling framework. A two-scale analysis of the flow allows us to understand the dominating role of the drag force in the kinetic energy transfers between scales. Transfers between the mean part and the turbulent part of the flow are formally derived. This description significantly improves our understanding of the issue of macroscopic modeling of turbulence and leads us to define the sub-filter production and the wake dissipation. A f - <{epsilon}>f - <{epsilon}{sub w}>f model is derived. It is based on three balance equations for the turbulent kinetic energy, the viscous dissipation and the wake dissipation. Furthermore, a dynamical predictor for the friction coefficient is proposed. This model is then

Predicting habitat suitability for rare plants at local spatial scales using a species distribution model.

Science.gov (United States)

Gogol-Prokurat, Melanie

2011-01-01

If species distribution models (SDMs) can rank habitat suitability at a local scale, they may be a valuable conservation planning tool for rare, patchily distributed species. This study assessed the ability of Maxent, an SDM reported to be appropriate for modeling rare species, to rank habitat suitability at a local scale for four edaphic endemic rare plants of gabbroic soils in El Dorado County, California, and examined the effects of grain size, spatial extent, and fine-grain environmental predictors on local-scale model accuracy. Models were developed using species occurrence data mapped on public lands and were evaluated using an independent data set of presence and absence locations on surrounding lands, mimicking a typical conservation-planning scenario that prioritizes potential habitat on unsurveyed lands surrounding known occurrences. Maxent produced models that were successful at discriminating between suitable and unsuitable habitat at the local scale for all four species, and predicted habitat suitability values were proportional to likelihood of occurrence or population abundance for three of four species. Unfortunately, models with the best discrimination (i.e., AUC) were not always the most useful for ranking habitat suitability. The use of independent test data showed metrics that were valuable for evaluating which variables and model choices (e.g., grain, extent) to use in guiding habitat prioritization for conservation of these species. A goodness-of-fit test was used to determine whether habitat suitability values ranked habitat suitability on a continuous scale. If they did not, a minimum acceptable error predicted area criterion was used to determine the threshold for classifying habitat as suitable or unsuitable. I found a trade-off between model extent and the use of fine-grain environmental variables: goodness of fit was improved at larger extents, and fine-grain environmental variables improved local-scale accuracy, but fine-grain variables

Performance Assessment of Turbulence Models for the Prediction of the Reactor Internal Flow in the Scale-down APR+

International Nuclear Information System (INIS)

Lee, Gonghee; Bang, Youngseok; Woo, Swengwoong; Kim, Dohyeong; Kang, Minku

2013-01-01

The types of errors in CFD simulation can be divided into the two main categories: numerical errors and model errors. Turbulence model is one of the important sources for model errors. In this study, in order to assess the prediction performance of Reynolds-averaged Navier-Stokes (RANS)-based two equations turbulence models for the analysis of flow distribution inside a 1/5 scale-down APR+, the simulation was conducted with the commercial CFD software, ANSYS CFX V. 14. In this study, in order to assess the prediction performance of turbulence models for the analysis of flow distribution inside a 1/5 scale-down APR+, the simulation was conducted with the commercial CFD software, ANSYS CFX V. 14. Both standard k-ε model and SST model predicted the similar flow pattern inside reactor. Therefore it was concluded that the prediction performance of both turbulence models was nearly same. Complex thermal-hydraulic characteristics exist inside reactor because the reactor internals consist of fuel assembly, control rod assembly, and the internal structures. Either flow distribution test for the scale-down reactor model or computational fluid dynamics (CFD) simulation have been conducted to understand these complex thermal-hydraulic features inside reactor

An adaptive two-stage analog/regression model for probabilistic prediction of small-scale precipitation in France

Directory of Open Access Journals (Sweden)

J. Chardon

2018-01-01

Full Text Available Statistical downscaling models (SDMs are often used to produce local weather scenarios from large-scale atmospheric information. SDMs include transfer functions which are based on a statistical link identified from observations between local weather and a set of large-scale predictors. As physical processes driving surface weather vary in time, the most relevant predictors and the regression link are likely to vary in time too. This is well known for precipitation for instance and the link is thus often estimated after some seasonal stratification of the data. In this study, we present a two-stage analog/regression model where the regression link is estimated from atmospheric analogs of the current prediction day. Atmospheric analogs are identified from fields of geopotential heights at 1000 and 500 hPa. For the regression stage, two generalized linear models are further used to model the probability of precipitation occurrence and the distribution of non-zero precipitation amounts, respectively. The two-stage model is evaluated for the probabilistic prediction of small-scale precipitation over France. It noticeably improves the skill of the prediction for both precipitation occurrence and amount. As the analog days vary from one prediction day to another, the atmospheric predictors selected in the regression stage and the value of the corresponding regression coefficients can vary from one prediction day to another. The model allows thus for a day-to-day adaptive and tailored downscaling. It can also reveal specific predictors for peculiar and non-frequent weather configurations.

On the Application of Macros to the Automation of different Dating Models Using ''210 Pb

International Nuclear Information System (INIS)

Gasco, C.; Anton, M. P.; Ampudia, J.

2002-01-01

Different Dating models based on 210 Pb measurements, used for verifying recent events are shown in this report as well as, models that describe different processes affecting the vertical distribution of radionuclides in lacustrine and marine sediments. Macro-Commands are programmes included in calculation work sheets that allow automatised operations to run. In this report macros are used to: a) obtain 210 Pb results from a data base created from different sampling campaigns b) apply different dating models automatically c) optimise the diffusion coefficient employed by models through standards deviation calculations among experimental values and those obtained by the model. (Author) 21 refs

Explanatory IRT Analysis Using the SPIRIT Macro in SPSS

Directory of Open Access Journals (Sweden)

DiTrapani, Jack

2018-04-01

Full Text Available Item Response Theory (IRT is a modeling framework that can be applied to a large variety of research questions spanning several disciplines. To make IRT models more accessible for the general researcher, a free tool has been created that can easily conduct one-parameter logistic IRT (1PL analyses using the convenient point-and-click interface in SPSS without any required downloads or add-ons. This tool, the SPIRIT macro, can fit 1PL models with person and item covariates, DIF analyses, multidimensional models, multigroup models, rating scale models, and several other variations. Example explanatory models are presented with an applied dataset containing responses to an ADHD rating scale. Illustrations of how to fit basic 1PL models as well as two more complicated analyses using SPIRIT are given.

%lrasch_mml: A SAS Macro for Marginal Maximum Likelihood Estimation in Longitudinal Polytomous Rasch Models

Directory of Open Access Journals (Sweden)

Maja Olsbjerg

2015-10-01

Full Text Available Item response theory models are often applied when a number items are used to measure a unidimensional latent variable. Originally proposed and used within educational research, they are also used when focus is on physical functioning or psychological wellbeing. Modern applications often need more general models, typically models for multidimensional latent variables or longitudinal models for repeated measurements. This paper describes a SAS macro that fits two-dimensional polytomous Rasch models using a specification of the model that is sufficiently flexible to accommodate longitudinal Rasch models. The macro estimates item parameters using marginal maximum likelihood estimation. A graphical presentation of item characteristic curves is included.

Imaging Catalysts at Work: A Hierarchical Approach from the Macro- to the Meso- and Nano-scale

DEFF Research Database (Denmark)

Grunwaldt, Jan-Dierk; Wagner, Jakob Birkedal; Dunin-Borkowski, Rafal E.

2013-01-01

This review highlights the importance of developing multi-scale characterisation techniques for analysing operating catalysts in their working environment. We emphasise that a hierarchy of insitu techniques that provides macro-, meso- and nano-scale information is required to elucidate and optimise....../heat/mass transport gradients in shaped catalysts and catalyst grains and c)meso- and nano-scale information about particles and clusters, whose physical and electronic properties are linked directly to the micro-kinetic behaviour of the catalysts. Techniques such as X-ray diffraction (XRD), infrared (IR), Raman, X......-ray photoelectron spectroscopy (XPS), UV/Vis, and X-ray absorption spectroscopy (XAS), which have mainly provided global atomic scale information, are being developed to provide the same information on a more local scale, often with sub-second time resolution. X-ray microscopy, both in the soft and more recently...

Scaling strength distributions in quasi-brittle materials from micro-to macro-scales: A computational approach to modeling Nature-inspired structural ceramics

International Nuclear Information System (INIS)

Genet, Martin; Couegnat, Guillaume; Tomsia, Antoni P.; Ritchie, Robert O.

2014-01-01

This paper presents an approach to predict the strength distribution of quasi-brittle materials across multiple length-scales, with emphasis on Nature-inspired ceramic structures. It permits the computation of the failure probability of any structure under any mechanical load, solely based on considerations of the microstructure and its failure properties by naturally incorporating the statistical and size-dependent aspects of failure. We overcome the intrinsic limitations of single periodic unit-based approaches by computing the successive failures of the material components and associated stress redistributions on arbitrary numbers of periodic units. For large size samples, the microscopic cells are replaced by a homogenized continuum with equivalent stochastic and damaged constitutive behavior. After establishing the predictive capabilities of the method, and illustrating its potential relevance to several engineering problems, we employ it in the study of the shape and scaling of strength distributions across differing length-scales for a particular quasi-brittle system. We find that the strength distributions display a Weibull form for samples of size approaching the periodic unit; however, these distributions become closer to normal with further increase in sample size before finally reverting to a Weibull form for macroscopic sized samples. In terms of scaling, we find that the weakest link scaling applies only to microscopic, and not macroscopic scale, samples. These findings are discussed in relation to failure patterns computed at different size-scales. (authors)

Modelling turbulence around and inside porous media based on the second moment closure

International Nuclear Information System (INIS)

Kuwata, Yusuke; Suga, Kazuhiko

2013-01-01

Highlights: • A novel turbulence model for flows in porous media is proposed. • Three stress tensors emerging in double averaging N–S are individually modelled. • The most advanced second moment closure is applied for the macro-scale stress. • A one equation and the Smagorinsky models are applied to the other stresses. • Promising results are obtained in test flows around and inside porous media. -- Abstract: To predict turbulence in porous media, a new approach is discussed. By double (both volume and Reynolds) averaging Navier–Stokes equations, there appear three unknown covariant terms in the momentum equation. They are namely the dispersive covariance, the macro-scale and the micro-scale Reynolds stresses, in the present study. For the macro-scale Reynolds stress, the TCL (two-component-limit) second moment closure is applied whereas the eddy viscosity models are applied to the other covariant terms: the Smagorinsky model and the one-equation eddy viscosity model, respectively for the dispersive covariance and the micro-scale Reynolds stress. The presently proposed model is evaluated in square rib array flows and porous wall channel flows with reasonable accuracy though further development is required

Relationship between water quality and macro-scale parameters (land use, erosion, geology, and population density) in the Siminehrood River Basin.

Science.gov (United States)

Bostanmaneshrad, Farshid; Partani, Sadegh; Noori, Roohollah; Nachtnebel, Hans-Peter; Berndtsson, Ronny; Adamowski, Jan Franklin

2018-10-15

To date, few studies have investigated the simultaneous effects of macro-scale parameters (MSPs) such as land use, population density, geology, and erosion layers on micro-scale water quality variables (MSWQVs). This research focused on an evaluation of the relationship between MSPs and MSWQVs in the Siminehrood River Basin, Iran. In addition, we investigated the importance of water particle travel time (hydrological distance) on this relationship. The MSWQVs included 13 physicochemical and biochemical parameters observed at 15 stations during three seasons. Primary screening was performed by utilizing three multivariate statistical analyses (Pearson's correlation, cluster and discriminant analyses) in seven series of observed data. These series included three separate seasonal data, three two-season data, and aggregated three-season data for investigation of relationships between MSPs and MSWQVs. Coupled data (pairs of MSWQVs and MSPs) repeated in at least two out of three statistical analyses were selected for final screening. The primary screening results demonstrated significant relationships between land use and phosphorus, total solids and turbidity, erosion levels and electrical conductivity, and erosion and total solids. Furthermore, water particle travel time effects were considered through three geographical pattern definitions of distance for each MSP by using two weighting methods. To find effective MSP factors on MSWQVs, a multivariate linear regression analysis was employed. Then, preliminary equations that estimated MSWQVs were developed. The preliminary equations were modified to adaptive equations to obtain the final models. The final models indicated that a new metric, referred to as hydrological distance, provided better MSWQV estimation and water quality prediction compared to the National Sanitation Foundation Water Quality Index. Crown Copyright © 2018. Published by Elsevier B.V. All rights reserved.

Simulation of water movement and isoproturon behaviour in a heavy clay soil using the MACRO model

Directory of Open Access Journals (Sweden)

T. J. Besien

1997-01-01

Full Text Available In this paper, the dual-porosity MACRO model has been used to investigate methods of reducing leaching of isoproturon from a structured heavy clay soil. The MACRO model was applied to a pesticide leaching data-set generated from a plot scale experiment on a heavy clay soil at the Oxford University Farm, Wytham, England. The field drain was found to be the most important outflow from the plot in terms of pesticide removal. Therefore, this modelling exercise concentrated on simulating field drain flow. With calibration of field-saturated and micropore saturated hydraulic conductivity, the drain flow hydrographs were simulated during extended periods of above average rainfall, with both the hydrograph shape and peak flows agreeing well. Over the whole field season, the observed drain flow water budget was well simulated. However, the first and second drain flow events after pesticide application were not simulated satisfactorily. This is believed to be due to a poor simulation of evapotranspiration during a period of low rainfall around the pesticide application day. Apart from an initial rapid drop in the observed isoproturon soil residue, the model simulated isoproturon residues during the 100 days after pesticide application reasonably well. Finally, the calibrated model was used to show that changes in agricultural practice (deep ploughing, creating fine consolidated seed beds and organic matter applications could potentially reduce pesticide leaching to surface waters by up to 60%.

Predicting ecosystem dynamics at regional scales: an evaluation of a terrestrial biosphere model for the forests of northeastern North America.

Science.gov (United States)

Medvigy, David; Moorcroft, Paul R

2012-01-19

Terrestrial biosphere models are important tools for diagnosing both the current state of the terrestrial carbon cycle and forecasting terrestrial ecosystem responses to global change. While there are a number of ongoing assessments of the short-term predictive capabilities of terrestrial biosphere models using flux-tower measurements, to date there have been relatively few assessments of their ability to predict longer term, decadal-scale biomass dynamics. Here, we present the results of a regional-scale evaluation of the Ecosystem Demography version 2 (ED2)-structured terrestrial biosphere model, evaluating the model's predictions against forest inventory measurements for the northeast USA and Quebec from 1985 to 1995. Simulations were conducted using a default parametrization, which used parameter values from the literature, and a constrained model parametrization, which had been developed by constraining the model's predictions against 2 years of measurements from a single site, Harvard Forest (42.5° N, 72.1° W). The analysis shows that the constrained model parametrization offered marked improvements over the default model formulation, capturing large-scale variation in patterns of biomass dynamics despite marked differences in climate forcing, land-use history and species-composition across the region. These results imply that data-constrained parametrizations of structured biosphere models such as ED2 can be successfully used for regional-scale ecosystem prediction and forecasting. We also assess the model's ability to capture sub-grid scale heterogeneity in the dynamics of biomass growth and mortality of different sizes and types of trees, and then discuss the implications of these analyses for further reducing the remaining biases in the model's predictions.

Constraints on genes shape long-term conservation of macro-synteny in metazoan genomes

Directory of Open Access Journals (Sweden)

Putnam Nicholas H

2011-10-01

Full Text Available Abstract Background Many metazoan genomes conserve chromosome-scale gene linkage relationships (“macro-synteny” from the common ancestor of multicellular animal life 1234, but the biological explanation for this conservation is still unknown. Double cut and join (DCJ is a simple, well-studied model of neutral genome evolution amenable to both simulation and mathematical analysis 5, but as we show here, it is not sufficent to explain long-term macro-synteny conservation. Results We examine a family of simple (one-parameter extensions of DCJ to identify models and choices of parameters consistent with the levels of macro- and micro-synteny conservation observed among animal genomes. Our software implements a flexible strategy for incorporating genomic context into the DCJ model to incorporate various types of genomic context (“DCJ-[C]”, and is available as open source software from http://github.com/putnamlab/dcj-c. Conclusions A simple model of genome evolution, in which DCJ moves are allowed only if they maintain chromosomal linkage among a set of constrained genes, can simultaneously account for the level of macro-synteny conservation and for correlated conservation among multiple pairs of species. Simulations under this model indicate that a constraint on approximately 7% of metazoan genes is sufficient to constrain genome rearrangement to an average rate of 25 inversions and 1.7 translocations per million years.

Numerical investigation of room-temperature deformation behavior of a duplex type γTiAl alloy using a multi-scale modeling approach

International Nuclear Information System (INIS)

Kabir, M.R.; Chernova, L.; Bartsch, M.

2010-01-01

Room-temperature deformation of a niobium-rich TiAl alloy with duplex microstructure has been numerically investigated. The model links the microstructural features at micro- and meso-scale by the two-level (FE 2 ) multi-scale approach. The deformation mechanisms of the considered phases were described in the micro-mechanical crystal-plasticity model. Initial material parameters for the model were taken from the literature and validated using tensile experiments at macro-scale. For the niobium-rich TiAl alloy further adaptation of the crystal plasticity parameters is proposed. Based on these model parameters, the influences of the grain orientation, grain size, and texture on the global mechanical behavior have been investigated. The contributions of crystal deformation modes (slips and dislocations in the phases) to the mechanical response are also analyzed. The results enable a quantitative prediction of relationships between microstructure and mechanical behavior on global and local scale, including an assessment of possible crack initiation sites. The model can be used for microstructure optimization to obtain better material properties.

Meta-modeling of the pesticide fate model MACRO for groundwater exposure assessments using artificial neural networks

Science.gov (United States)

Stenemo, Fredrik; Lindahl, Anna M. L.; Gärdenäs, Annemieke; Jarvis, Nicholas

2007-08-01

mapped for a small field. It was shown that the area of the field that contributes most to leaching depends on the properties of the compound in question. It is concluded that the simulation meta-model of MACRO should prove useful for mapping relative pesticide leaching risks at large scales.

Data assimilation in optimizing and integrating soil and water quality water model predictions at different scales

Science.gov (United States)

Relevant data about subsurface water flow and solute transport at relatively large scales that are of interest to the public are inherently laborious and in most cases simply impossible to obtain. Upscaling in which fine-scale models and data are used to predict changes at the coarser scales is the...

Global Energy and Water Cycle Experiment (GEWEX) and the Continental-scale International Project (GCIP)

Science.gov (United States)

Vane, Deborah

1993-01-01

A discussion of the objectives of the Global Energy and Water Cycle Experiment (GEWEX) and the Continental-scale International Project (GCIP) is presented in vugraph form. The objectives of GEWEX are as follows: determine the hydrological cycle by global measurements; model the global hydrological cycle; improve observations and data assimilation; and predict response to environmental change. The objectives of GCIP are as follows: determine the time/space variability of the hydrological cycle over a continental-scale region; develop macro-scale hydrologic models that are coupled to atmospheric models; develop information retrieval schemes; and support regional climate change impact assessment.

Circuit models and SPICE macro-models for quantum Hall effect devices

International Nuclear Information System (INIS)

Ortolano, Massimo; Callegaro, Luca

2015-01-01

Precise electrical measurement technology based on the quantum Hall effect is one of the pillars of modern quantum electrical metrology. Electrical networks including one or more QHE elements can be used as quantum resistance and impedance standards. The analysis of these networks allows metrologists to evaluate the effect of the inevitable parasitic parameters on their performance as standards. This paper presents a concise review of the various circuit models for QHE elements proposed in the literature, and the development of a new model. This last model is particularly suited to be employed with the analogue electronic circuit simulator SPICE. The SPICE macro-model and examples of SPICE simulations, validated by comparison with the corresponding analytical solution and/or experimental data, are provided. (paper)

Application of a two-dimensional model for predicting the pressure-flow and compression properties during column packing scale-up.

Science.gov (United States)

McCue, Justin T; Cecchini, Douglas; Chu, Cathy; Liu, Wei-Han; Spann, Andrew

2007-03-23

A two-dimensional model was formulated to describe the pressure-flow behavior of compressible stationary phases for protein chromatography at different temperatures and column scales. The model was based on the assumption of elastic deformation of the solid phase and steady-state Darcy flow. Using a single fitted value for the empirical modulus parameters, the model was applied to describe the pressure-flow behavior of several adsorbents packed using both fluid flow and mechanical compression. Simulations were in agreement with experimental data and accurately predicted the pressure-flow and compression behavior of three adsorbents over a range of column scales and operating temperatures. Use of the described theoretical model potentially improves the accuracy of the column scale-up process, allowing the use of limited laboratory scale data to predict column performance in large scale applications.

MACRO MODEL OF SEAT BELT USE BY CAR DRIVERS AND PASSENGERS

Directory of Open Access Journals (Sweden)

Kazimierz JAMROZ

2013-12-01

Full Text Available The article presents some problems of seat belt use by car drivers and passengers. It looks in particular at seat belt use and effectiveness in selected countries. Next, factors of seat belt use are presented and methodology of model development. A macro model of seat belt use is presented based on data from around fifty countries from different continents.

Development of a modified equilibrium model for biomass pilot-scale fluidized bed gasifier performance predictions

International Nuclear Information System (INIS)

Rodriguez-Alejandro, David A.; Nam, Hyungseok; Maglinao, Amado L.; Capareda, Sergio C.; Aguilera-Alvarado, Alberto F.

2016-01-01

The objective of this work is to develop a thermodynamic model considering non-stoichiometric restrictions. The model validation was done from experimental works using a bench-scale fluidized bed gasifier with wood chips, dairy manure, and sorghum. The model was used for a further parametric study to predict the performance of a pilot-scale fluidized biomass gasifier. The Gibbs free energy minimization was applied to the modified equilibrium model considering a heat loss to the surroundings, carbon efficiency, and two non-equilibrium factors based on empirical correlations of ER and gasification temperature. The model was in a good agreement with RMS <4 for the produced gas. The parametric study ranges were 0.01 < ER < 0.99 and 500 °C < T < 900 °C to predict syngas concentrations and its LHV (lower heating value) for the optimization. Higher aromatics in tar were contained in WC gasification compared to manure gasification. A wood gasification tar simulation was produced to predict the amount of tars at specific conditions. The operating conditions for the highest quality syngas were reconciled experimentally with three biomass wastes using a fluidized bed gasifier. The thermodynamic model was used to predict the gasification performance at conditions beyond the actual operation. - Highlights: • Syngas from experimental gasification was used to create a non-equilibrium model. • Different types of biomass (HTS, DM, and WC) were used for gasification modelling. • Different tar compositions were identified with a simulation of tar yields. • The optimum operating conditions were found through the developed model.

Study on developing energy-macro model

Energy Technology Data Exchange (ETDEWEB)

Kim, Young Duk [Korea Energy Economics Institute, Euiwang (Kenya)

1999-12-01

It analyzed the effect of international oil price on domestic economy and its path, time difference and degree of effect. First of all, it analyzed whether the long-term relationship between international oil price and price exists focusing on integral relationship, and estimated dynamic price fluctuation by using error correction model. Moreover, using structural VAR model, it analyzed what kind of shocking reactions are showed when the increase of international oil price affects on domestic macro economic variables. Commonly it is estimated that price is increasing in a long term not in a short term as the international oil price is increasing. When the international oil price increases, it is estimated that its effect in a short term is insignificant because of direct price control by the government and then its spreading effect on economy shows a long-term effect by deepening the price control. (author). 16 refs., 3 figs., 10 tabs.

On the predictivity of pore-scale simulations: estimating uncertainties with multilevel Monte Carlo

KAUST Repository

Icardi, Matteo

2016-02-08

A fast method with tunable accuracy is proposed to estimate errors and uncertainties in pore-scale and Digital Rock Physics (DRP) problems. The overall predictivity of these studies can be, in fact, hindered by many factors including sample heterogeneity, computational and imaging limitations, model inadequacy and not perfectly known physical parameters. The typical objective of pore-scale studies is the estimation of macroscopic effective parameters such as permeability, effective diffusivity and hydrodynamic dispersion. However, these are often non-deterministic quantities (i.e., results obtained for specific pore-scale sample and setup are not totally reproducible by another “equivalent” sample and setup). The stochastic nature can arise due to the multi-scale heterogeneity, the computational and experimental limitations in considering large samples, and the complexity of the physical models. These approximations, in fact, introduce an error that, being dependent on a large number of complex factors, can be modeled as random. We propose a general simulation tool, based on multilevel Monte Carlo, that can reduce drastically the computational cost needed for computing accurate statistics of effective parameters and other quantities of interest, under any of these random errors. This is, to our knowledge, the first attempt to include Uncertainty Quantification (UQ) in pore-scale physics and simulation. The method can also provide estimates of the discretization error and it is tested on three-dimensional transport problems in heterogeneous materials, where the sampling procedure is done by generation algorithms able to reproduce realistic consolidated and unconsolidated random sphere and ellipsoid packings and arrangements. A totally automatic workflow is developed in an open-source code [2015. https://bitbucket.org/micardi/porescalemc.], that include rigid body physics and random packing algorithms, unstructured mesh discretization, finite volume solvers

Dynamic modeling and adaptive vibration suppression of a high-speed macro-micro manipulator

Science.gov (United States)

Yang, Yi-ling; Wei, Yan-ding; Lou, Jun-qiang; Fu, Lei; Fang, Sheng; Chen, Te-huan

2018-05-01

This paper presents a dynamic modeling and microscopic vibration suppression for a flexible macro-micro manipulator dedicated to high-speed operation. The manipulator system mainly consists of a macro motion stage and a flexible micromanipulator bonded with one macro-fiber-composite actuator. Based on Hamilton's principle and the Bouc-Wen hysteresis equation, the nonlinear dynamic model is obtained. Then, a hybrid control scheme is proposed to simultaneously suppress the elastic vibration during and after the motor motion. In particular, the hybrid control strategy is composed of a trajectory planning approach and an adaptive variable structure control. Moreover, two optimization indices regarding the comprehensive torques and synthesized vibrations are designed, and the optimal trajectories are acquired using a genetic algorithm. Furthermore, a nonlinear fuzzy regulator is used to adjust the switching gain in the variable structure control. Thus, a fuzzy variable structure control with nonlinear adaptive control law is achieved. A series of experiments are performed to verify the effectiveness and feasibility of the established system model and hybrid control strategy. The excited vibration during the motor motion and the residual vibration after the motor motion are decreased. Meanwhile, the settling time is shortened. Both the manipulation stability and operation efficiency of the manipulator are improved by the proposed hybrid strategy.

Macro Dark Matter

CERN Document Server

Jacobs, David M; Lynn, Bryan W.

2015-01-01

Dark matter is a vital component of the current best model of our universe, $\\Lambda$CDM. There are leading candidates for what the dark matter could be (e.g. weakly-interacting massive particles, or axions), but no compelling observational or experimental evidence exists to support these particular candidates, nor any beyond-the-Standard-Model physics that might produce such candidates. This suggests that other dark matter candidates, including ones that might arise in the Standard Model, should receive increased attention. Here we consider a general class of dark matter candidates with characteristic masses and interaction cross-sections characterized in units of grams and cm$^2$, respectively -- we therefore dub these macroscopic objects as Macros. Such dark matter candidates could potentially be assembled out of Standard Model particles (quarks and leptons) in the early universe. A combination of earth-based, astrophysical, and cosmological observations constrain a portion of the Macro parameter space; ho...

A hybrid model for dissolved oxygen prediction in aquaculture based on multi-scale features

Directory of Open Access Journals (Sweden)

Chen Li

2018-03-01

Full Text Available To increase prediction accuracy of dissolved oxygen (DO in aquaculture, a hybrid model based on multi-scale features using ensemble empirical mode decomposition (EEMD is proposed. Firstly, original DO datasets are decomposed by EEMD and we get several components. Secondly, these components are used to reconstruct four terms including high frequency term, intermediate frequency term, low frequency term and trend term. Thirdly, according to the characteristics of high and intermediate frequency terms, which fluctuate violently, the least squares support vector machine (LSSVR is used to predict the two terms. The fluctuation of low frequency term is gentle and periodic, so it can be modeled by BP neural network with an optimal mind evolutionary computation (MEC-BP. Then, the trend term is predicted using grey model (GM because it is nearly linear. Finally, the prediction values of DO datasets are calculated by the sum of the forecasting values of all terms. The experimental results demonstrate that our hybrid model outperforms EEMD-ELM (extreme learning machine based on EEMD, EEMD-BP and MEC-BP models based on the mean absolute error (MAE, mean absolute percentage error (MAPE, mean square error (MSE and root mean square error (RMSE. Our hybrid model is proven to be an effective approach to predict aquaculture DO.

Climate change and macro-economic cycles in pre-industrial europe.

Science.gov (United States)

Pei, Qing; Zhang, David D; Lee, Harry F; Li, Guodong

2014-01-01

Climate change has been proven to be the ultimate cause of social crisis in pre-industrial Europe at a large scale. However, detailed analyses on climate change and macro-economic cycles in the pre-industrial era remain lacking, especially within different temporal scales. Therefore, fine-grained, paleo-climate, and economic data were employed with statistical methods to quantitatively assess the relations between climate change and agrarian economy in Europe during AD 1500 to 1800. In the study, the Butterworth filter was adopted to filter the data series into a long-term trend (low-frequency) and short-term fluctuations (high-frequency). Granger Causality Analysis was conducted to scrutinize the associations between climate change and macro-economic cycle at different frequency bands. Based on quantitative results, climate change can only show significant effects on the macro-economic cycle within the long-term. In terms of the short-term effects, society can relieve the influences from climate variations by social adaptation methods and self-adjustment mechanism. On a large spatial scale, temperature holds higher importance for the European agrarian economy than precipitation. By examining the supply-demand mechanism in the grain market, population during the study period acted as the producer in the long term, whereas as the consumer in the short term. These findings merely reflect the general interactions between climate change and macro-economic cycles at the large spatial region with a long-term study period. The findings neither illustrate individual incidents that can temporarily distort the agrarian economy nor explain some specific cases. In the study, the scale thinking in the analysis is raised as an essential methodological issue for the first time to interpret the associations between climatic impact and macro-economy in the past agrarian society within different temporal scales.

Modeling macro-and microstructures of Gas-Metal-Arc Welded HSLA-100 steel

Science.gov (United States)

Yang, Z.; Debroy, T.

1999-06-01

Fluid flow and heat transfer during gas-metal-arc welding (GMAW) of HSLA-100 steel were studied using a transient, three-dimensional, turbulent heat transfer and fluid flow model. The temperature and velocity fields, cooling rates, and shape and size of the fusion and heat-affected zones (HAZs) were calculated. A continuous-cooling-transformation (CCT) diagram was computed to aid in the understanding of the observed weld metal microstructure. The computed results demonstrate that the dissipation of heat and momentum in the weld pool is significantly aided by turbulence, thus suggesting that previous modeling results based on laminar flow need to be re-examined. A comparison of the calculated fusion and HAZ geometries with their corresponding measured values showed good agreement. Furthermore, “finger” penetration, a unique geometric characteristic of gas-metal-arc weld pools, could be satisfactorily predicted from the model. The ability to predict these geometric variables and the agreement between the calculated and the measured cooling rates indicate the appropriateness of using a turbulence model for accurate calculations. The microstructure of the weld metal consisted mainly of acicular ferrite with small amounts of bainite. At high heat inputs, small amounts of allotriomorphic and Widmanstätten ferrite were also observed. The observed microstructures are consistent with those expected from the computed CCT diagram and the cooling rates. The results presented here demonstrate significant promise for understanding both macro-and microstructures of steel welds from the combination of the fundamental principles from both transport phenomena and phase transformation theory.

Water scaling in the North Sea oil and gas fields and scale prediction: An overview

Energy Technology Data Exchange (ETDEWEB)

Yuan, M

1997-12-31

Water-scaling is a common and major production chemistry problem in the North Sea oil and gas fields and scale prediction has been an important means to assess the potential and extent of scale deposition. This paper presents an overview of sulphate and carbonate scaling problems in the North Sea and a review of several widely used and commercially available scale prediction software. In the paper, the water chemistries and scale types and severities are discussed relative of the geographical distribution of the fields in the North Sea. The theories behind scale prediction are then briefly described. Five scale or geochemical models are presented and various definitions of saturation index are compared and correlated. Views are the expressed on how to predict scale precipitation under some extreme conditions such as that encountered in HPHT reservoirs. 15 refs., 7 figs., 9 tabs.

Nitrate reduction in geologically heterogeneous catchments — A framework for assessing the scale of predictive capability of hydrological models

International Nuclear Information System (INIS)

Refsgaard, Jens Christian; Auken, Esben; Bamberg, Charlotte A.; Christensen, Britt S.B.; Clausen, Thomas; Dalgaard, Esben; Effersø, Flemming; Ernstsen, Vibeke; Gertz, Flemming; Hansen, Anne Lausten; He, Xin; Jacobsen, Brian H.; Jensen, Karsten Høgh; Jørgensen, Flemming; Jørgensen, Lisbeth Flindt; Koch, Julian; Nilsson, Bertel; Petersen, Christian; De Schepper, Guillaume; Schamper, Cyril

2014-01-01

In order to fulfil the requirements of the EU Water Framework Directive nitrate load from agricultural areas to surface water in Denmark needs to be reduced by about 40%. The regulations imposed until now have been uniform, i.e. the same restrictions for all areas independent of the subsurface conditions. Studies have shown that on a national basis about 2/3 of the nitrate leaching from the root zone is reduced naturally, through denitrification, in the subsurface before reaching the streams. Therefore, it is more cost-effective to identify robust areas, where nitrate leaching through the root zone is reduced in the saturated zone before reaching the streams, and vulnerable areas, where no subsurface reduction takes place, and then only impose regulations/restrictions on the vulnerable areas. Distributed hydrological models can make predictions at grid scale, i.e. at much smaller scale than the entire catchment. However, as distributed models often do not include local scale hydrogeological heterogeneities, they are typically not able to make accurate predictions at scales smaller than they are calibrated. We present a framework for assessing nitrate reduction in the subsurface and for assessing at which spatial scales modelling tools have predictive capabilities. A new instrument has been developed for airborne geophysical measurements, Mini-SkyTEM, dedicated to identifying geological structures and heterogeneities with horizontal and lateral resolutions of 30–50 m and 2 m, respectively, in the upper 30 m. The geological heterogeneity and uncertainty are further analysed by use of the geostatistical software TProGS by generating stochastic geological realisations that are soft conditioned against the geophysical data. Finally, the flow paths within the catchment are simulated by use of the MIKE SHE hydrological modelling system for each of the geological models generated by TProGS and the prediction uncertainty is characterised by the variance between the

Nitrate reduction in geologically heterogeneous catchments — A framework for assessing the scale of predictive capability of hydrological models

Energy Technology Data Exchange (ETDEWEB)

Refsgaard, Jens Christian, E-mail: jcr@geus.dk [Geological Survey of Denmark and Greenland (GEUS) (Denmark); Auken, Esben [Department of Earth Sciences, Aarhus University (Denmark); Bamberg, Charlotte A. [City of Aarhus (Denmark); Christensen, Britt S.B. [Geological Survey of Denmark and Greenland (GEUS) (Denmark); Clausen, Thomas [DHI, Hørsholm (Denmark); Dalgaard, Esben [Department of Earth Sciences, Aarhus University (Denmark); Effersø, Flemming [SkyTEM Aps, Beder (Denmark); Ernstsen, Vibeke [Geological Survey of Denmark and Greenland (GEUS) (Denmark); Gertz, Flemming [Knowledge Center for Agriculture, Skejby (Denmark); Hansen, Anne Lausten [Department of Geosciences and Natural Resource Management, University of Copenhagen (Denmark); He, Xin [Geological Survey of Denmark and Greenland (GEUS) (Denmark); Jacobsen, Brian H. [Department of Food and Resource Economics, University of Copenhagen (Denmark); Jensen, Karsten Høgh [Department of Geosciences and Natural Resource Management, University of Copenhagen (Denmark); Jørgensen, Flemming; Jørgensen, Lisbeth Flindt [Geological Survey of Denmark and Greenland (GEUS) (Denmark); Koch, Julian [Department of Geosciences and Natural Resource Management, University of Copenhagen (Denmark); Nilsson, Bertel [Geological Survey of Denmark and Greenland (GEUS) (Denmark); Petersen, Christian [City of Odder (Denmark); De Schepper, Guillaume [Université Laval, Québec (Canada); Schamper, Cyril [Department of Earth Sciences, Aarhus University (Denmark); and others

2014-01-01

In order to fulfil the requirements of the EU Water Framework Directive nitrate load from agricultural areas to surface water in Denmark needs to be reduced by about 40%. The regulations imposed until now have been uniform, i.e. the same restrictions for all areas independent of the subsurface conditions. Studies have shown that on a national basis about 2/3 of the nitrate leaching from the root zone is reduced naturally, through denitrification, in the subsurface before reaching the streams. Therefore, it is more cost-effective to identify robust areas, where nitrate leaching through the root zone is reduced in the saturated zone before reaching the streams, and vulnerable areas, where no subsurface reduction takes place, and then only impose regulations/restrictions on the vulnerable areas. Distributed hydrological models can make predictions at grid scale, i.e. at much smaller scale than the entire catchment. However, as distributed models often do not include local scale hydrogeological heterogeneities, they are typically not able to make accurate predictions at scales smaller than they are calibrated. We present a framework for assessing nitrate reduction in the subsurface and for assessing at which spatial scales modelling tools have predictive capabilities. A new instrument has been developed for airborne geophysical measurements, Mini-SkyTEM, dedicated to identifying geological structures and heterogeneities with horizontal and lateral resolutions of 30–50 m and 2 m, respectively, in the upper 30 m. The geological heterogeneity and uncertainty are further analysed by use of the geostatistical software TProGS by generating stochastic geological realisations that are soft conditioned against the geophysical data. Finally, the flow paths within the catchment are simulated by use of the MIKE SHE hydrological modelling system for each of the geological models generated by TProGS and the prediction uncertainty is characterised by the variance between the

Predicting Species Distributions Using Record Centre Data: Multi-Scale Modelling of Habitat Suitability for Bat Roosts.

Science.gov (United States)

Bellamy, Chloe; Altringham, John

2015-01-01

Conservation increasingly operates at the landscape scale. For this to be effective, we need landscape scale information on species distributions and the environmental factors that underpin them. Species records are becoming increasingly available via data centres and online portals, but they are often patchy and biased. We demonstrate how such data can yield useful habitat suitability models, using bat roost records as an example. We analysed the effects of environmental variables at eight spatial scales (500 m - 6 km) on roost selection by eight bat species (Pipistrellus pipistrellus, P. pygmaeus, Nyctalus noctula, Myotis mystacinus, M. brandtii, M. nattereri, M. daubentonii, and Plecotus auritus) using the presence-only modelling software MaxEnt. Modelling was carried out on a selection of 418 data centre roost records from the Lake District National Park, UK. Target group pseudoabsences were selected to reduce the impact of sampling bias. Multi-scale models, combining variables measured at their best performing spatial scales, were used to predict roosting habitat suitability, yielding models with useful predictive abilities. Small areas of deciduous woodland consistently increased roosting habitat suitability, but other habitat associations varied between species and scales. Pipistrellus were positively related to built environments at small scales, and depended on large-scale woodland availability. The other, more specialist, species were highly sensitive to human-altered landscapes, avoiding even small rural towns. The strength of many relationships at large scales suggests that bats are sensitive to habitat modifications far from the roost itself. The fine resolution, large extent maps will aid targeted decision-making by conservationists and planners. We have made available an ArcGIS toolbox that automates the production of multi-scale variables, to facilitate the application of our methods to other taxa and locations. Habitat suitability modelling has the

Inverse and Predictive Modeling

Energy Technology Data Exchange (ETDEWEB)

Syracuse, Ellen Marie [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

2017-09-27

The LANL Seismo-Acoustic team has a strong capability in developing data-driven models that accurately predict a variety of observations. These models range from the simple – one-dimensional models that are constrained by a single dataset and can be used for quick and efficient predictions – to the complex – multidimensional models that are constrained by several types of data and result in more accurate predictions. Team members typically build models of geophysical characteristics of Earth and source distributions at scales of 1 to 1000s of km, the techniques used are applicable for other types of physical characteristics at an even greater range of scales. The following cases provide a snapshot of some of the modeling work done by the Seismo- Acoustic team at LANL.

Using Genome-scale Models to Predict Biological Capabilities

DEFF Research Database (Denmark)

O’Brien, Edward J.; Monk, Jonathan M.; Palsson, Bernhard O.

2015-01-01

Constraint-based reconstruction and analysis (COBRA) methods at the genome scale have been under development since the first whole-genome sequences appeared in the mid-1990s. A few years ago, this approach began to demonstrate the ability to predict a range of cellular functions, including cellul...

Use of satellite and modeled soil moisture data for predicting event soil loss at plot scale

Science.gov (United States)

Todisco, F.; Brocca, L.; Termite, L. F.; Wagner, W.

2015-09-01

The potential of coupling soil moisture and a Universal Soil Loss Equation-based (USLE-based) model for event soil loss estimation at plot scale is carefully investigated at the Masse area, in central Italy. The derived model, named Soil Moisture for Erosion (SM4E), is applied by considering the unavailability of in situ soil moisture measurements, by using the data predicted by a soil water balance model (SWBM) and derived from satellite sensors, i.e., the Advanced SCATterometer (ASCAT). The soil loss estimation accuracy is validated using in situ measurements in which event observations at plot scale are available for the period 2008-2013. The results showed that including soil moisture observations in the event rainfall-runoff erosivity factor of the USLE enhances the capability of the model to account for variations in event soil losses, the soil moisture being an effective alternative to the estimated runoff, in the prediction of the event soil loss at Masse. The agreement between observed and estimated soil losses (through SM4E) is fairly satisfactory with a determination coefficient (log-scale) equal to ~ 0.35 and a root mean square error (RMSE) of ~ 2.8 Mg ha-1. These results are particularly significant for the operational estimation of soil losses. Indeed, currently, soil moisture is a relatively simple measurement at the field scale and remote sensing data are also widely available on a global scale. Through satellite data, there is the potential of applying the SM4E model for large-scale monitoring and quantification of the soil erosion process.

Use of satellite and modelled soil moisture data for predicting event soil loss at plot scale

Science.gov (United States)

Todisco, F.; Brocca, L.; Termite, L. F.; Wagner, W.

2015-03-01

The potential of coupling soil moisture and a~USLE-based model for event soil loss estimation at plot scale is carefully investigated at the Masse area, in Central Italy. The derived model, named Soil Moisture for Erosion (SM4E), is applied by considering the unavailability of in situ soil moisture measurements, by using the data predicted by a soil water balance model (SWBM) and derived from satellite sensors, i.e. the Advanced SCATterometer (ASCAT). The soil loss estimation accuracy is validated using in situ measurements in which event observations at plot scale are available for the period 2008-2013. The results showed that including soil moisture observations in the event rainfall-runoff erosivity factor of the RUSLE/USLE, enhances the capability of the model to account for variations in event soil losses, being the soil moisture an effective alternative to the estimated runoff, in the prediction of the event soil loss at Masse. The agreement between observed and estimated soil losses (through SM4E) is fairly satisfactory with a determination coefficient (log-scale) equal to of ~ 0.35 and a root-mean-square error (RMSE) of ~ 2.8 Mg ha-1. These results are particularly significant for the operational estimation of soil losses. Indeed, currently, soil moisture is a relatively simple measurement at the field scale and remote sensing data are also widely available on a global scale. Through satellite data, there is the potential of applying the SM4E model for large-scale monitoring and quantification of the soil erosion process.

Prediction of scale potential in ethylene glycol containing solutions

Energy Technology Data Exchange (ETDEWEB)

Sandengen, Kristian; Oestvold, Terje

2006-03-15

This work presents a method for scale prediction in MEG (Mono Ethylene Glycol / 1,2-ethane-diol) containing solutions. It is based on an existing PVT scale model using a Pitzer ion interaction model for the aqueous phase. The model is well suited for scale prediction in saline solutions, where the PVT part is necessary for calculating CO{sub 2} phase equilibria being critical for carbonate scale. MEG influences the equilibria contained in the model, and its effect has been added empirically. Thus the accuracy of the model is limited by the amount of available experimental data. The model is applicable in the range 0-99wt% MEG and includes a wide variety of salts. In addition to the aspects of scale modelling in MEG+water solutions, this work presents new experimental data on CaSO4 solubility (0-95wt% MEG and 22-80 deg.C). CaSO4 solubility is greatly reduced by MEG to an extent that ''Salting-out'' is possible. (author) (tk)

Macro optical projection tomography for large scale 3D imaging of plant structures and gene activity.

Science.gov (United States)

Lee, Karen J I; Calder, Grant M; Hindle, Christopher R; Newman, Jacob L; Robinson, Simon N; Avondo, Jerome J H Y; Coen, Enrico S

2017-01-01

Optical projection tomography (OPT) is a well-established method for visualising gene activity in plants and animals. However, a limitation of conventional OPT is that the specimen upper size limit precludes its application to larger structures. To address this problem we constructed a macro version called Macro OPT (M-OPT). We apply M-OPT to 3D live imaging of gene activity in growing whole plants and to visualise structural morphology in large optically cleared plant and insect specimens up to 60 mm tall and 45 mm deep. We also show how M-OPT can be used to image gene expression domains in 3D within fixed tissue and to visualise gene activity in 3D in clones of growing young whole Arabidopsis plants. A further application of M-OPT is to visualise plant-insect interactions. Thus M-OPT provides an effective 3D imaging platform that allows the study of gene activity, internal plant structures and plant-insect interactions at a macroscopic scale. © The Author 2016. Published by Oxford University Press on behalf of the Society for Experimental Biology.

Prediction of Mineral Scale Formation in Geothermal and Oilfield Operations using the Extended UNIQUAC Model. Part I: Sulphate Scaling Minerals

DEFF Research Database (Denmark)

Garcia, Ada V.; Thomsen, Kaj; Stenby, Erling Halfdan

2005-01-01

Pressure parameters are added to the Extended UNIQUAC model presented by Thomsen and Rasmussen (1999). The improved model has been used for correlation and prediction of solid-liquid equilibrium (SLE) of scaling minerals (CaSO4, CaSO4·2H2O, BaSO4 and SrSO4) at temperatures up to 300°C and pressur...

Digital holographic setups for phase object measurements in micro and macro scale

Directory of Open Access Journals (Sweden)

Lédl Vít

2015-01-01

Full Text Available The measurement of properties of so called phase objects is being solved for more than one Century starting probably with schlieren technique 1. Classical interferometry served as a great measurement tool for several decades and was replaced by holographic interferometry, which disposes with many benefits when compared to classical interferometry. Holographic interferometry undergone an enormous development in last decade when digital holography has been established as a standard technique and most of the drawbacks were solved. The paper deals with scope of the huge applicability of digital holographic interferometry in heat and mass transfer measurement from micro to macro scale and from simple 2D measurement up to complex tomographic techniques. Recently the very complex experimental setups are under development in our labs combining many techniques leading to digital holographic micro tomography methods.

Writing Excel Macros with VBA

CERN Document Server

Roman, Steven

2008-01-01

To achieve the maximum control and flexibility from Microsoft® Excel often requires careful custom programming using the VBA (Visual Basic for Applications) language. Writing Excel Macros with VBA, 2nd Edition offers a solid introduction to writing VBA macros and programs, and will show you how to get more power at the programming level: focusing on programming languages, the Visual Basic Editor, handling code, and the Excel object model.

Micro-macro multilevel latent class models with multiple discrete individual-level variables

NARCIS (Netherlands)

Bennink, M.; Croon, M.A.; Kroon, B.; Vermunt, J.K.

2016-01-01

An existing micro-macro method for a single individual-level variable is extended to the multivariate situation by presenting two multilevel latent class models in which multiple discrete individual-level variables are used to explain a group-level outcome. As in the univariate case, the

Two approaches for the analysis of masonry structures : Micro and macro-modeling

NARCIS (Netherlands)

Laurenco, P.B.; Rots, J.G.; Blaauwendraad, J.

1995-01-01

Two models for the micro- and macro-analysis of masonry structures are presented. For the micromodeling of masonry, an interface failure criterion that includes a straight tension cut-off, the Coulomb friction law and an elliptical cap is proposed. The inelastic behavior includes tensile strength

Watershed-scale evaluation of the Water Erosion Prediction Project (WEPP) model in the Lake Tahoe basin

Science.gov (United States)

Erin S. Brooks; Mariana Dobre; William J. Elliot; Joan Q. Wu; Jan Boll

2016-01-01

Forest managers need methods to evaluate the impacts of management at the watershed scale. The Water Erosion Prediction Project (WEPP) has the ability to model disturbed forested hillslopes, but has difficulty addressing some of the critical processes that are important at a watershed scale, including baseflow and water yield. In order to apply WEPP to...

Two-scale characterization of deformation-induced anisotropy of polycrystalline metals

International Nuclear Information System (INIS)

Watanabe, Ikumu; Terada, Kenjiro

2004-01-01

The anisotropic macro-scale mechanical behavior of polycrystalline metals is characterized by incorporating the micro-scale constitutive model of single crystal plasticity into the two-scale modeling based on the mathematical homogenization theory. The two-scale simulations are conducted to analyze the macro-scale anisotropy induced by micro-scale plastic deformation of the polycrystalline aggregate. In the simulations, the micro-scale representative volume element (RVE) of a polycrystalline aggregate is uniformly loaded in one direction, unloaded to macroscopically zero stress in a certain stage of deformation and then re-loaded in the different directions. The last re-loading calculations provide different macro-scale responses of the RVE, which can be the appearance of material anisotropy. We then try to examine the effects of the intergranular and intragranular behaviors on the anisotropy by means of various illustrations of plastic deformation process in stead of the use of pole figures for the change of crystallographic orientations

SAS macro programs for geographically weighted generalized linear modeling with spatial point data: applications to health research.

Science.gov (United States)

Chen, Vivian Yi-Ju; Yang, Tse-Chuan

2012-08-01

An increasing interest in exploring spatial non-stationarity has generated several specialized analytic software programs; however, few of these programs can be integrated natively into a well-developed statistical environment such as SAS. We not only developed a set of SAS macro programs to fill this gap, but also expanded the geographically weighted generalized linear modeling (GWGLM) by integrating the strengths of SAS into the GWGLM framework. Three features distinguish our work. First, the macro programs of this study provide more kernel weighting functions than the existing programs. Second, with our codes the users are able to better specify the bandwidth selection process compared to the capabilities of existing programs. Third, the development of the macro programs is fully embedded in the SAS environment, providing great potential for future exploration of complicated spatially varying coefficient models in other disciplines. We provided three empirical examples to illustrate the use of the SAS macro programs and demonstrated the advantages explained above. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

Event-triggered decentralized robust model predictive control for constrained large-scale interconnected systems

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Ling Lu

2016-12-01

Full Text Available This paper considers the problem of event-triggered decentralized model predictive control (MPC for constrained large-scale linear systems subject to additive bounded disturbances. The constraint tightening method is utilized to formulate the MPC optimization problem. The local predictive control law for each subsystem is determined aperiodically by relevant triggering rule which allows a considerable reduction of the computational load. And then, the robust feasibility and closed-loop stability are proved and it is shown that every subsystem state will be driven into a robust invariant set. Finally, the effectiveness of the proposed approach is illustrated via numerical simulations.

Crack formation mechanisms during micro and macro indentation of diamond-like carbon coatings on elastic-plastic substrates

DEFF Research Database (Denmark)

Thomsen, N.B.; Fischer-Cripps, A.C.; Swain, M.V.

1998-01-01

of cracking and the fracture mechanisms taking place. In the study various diamond-like carbon (DLC) coatings deposited onto stainless steel and tool steel were investigated. Results primarily for one DLC system will be presented here. (C) 1998 Published by Elsevier Science S.A. All rights reserved.......In the present study crack formation is investigated on both micro and macro scale using spherical indenter tips. in particular, systems consisting of elastic coatings that are well adhered to elastic-plastic substrates are studied. Depth sensing indentation is used on the micro scale and Rockwell...... indentation on the macro scale. The predominant driving force for coating failure and crack formation during indentation is plastic deformation of the underlying substrate. The aim is to relate the mechanisms creating both delamination and cohesive cracking on both scales with fracture mechanical models...

Predicting continental-scale patterns of bird species richness with spatially explicit models

DEFF Research Database (Denmark)

Rahbek, Carsten; Gotelli, Nicholas J; Colwell, Robert K

2007-01-01

the extraordinary diversity of avian species in the montane tropics, the most species-rich region on Earth. Our findings imply that correlative climatic models substantially underestimate the importance of historical factors and small-scale niche-driven assembly processes in shaping contemporary species-richness......The causes of global variation in species richness have been debated for nearly two centuries with no clear resolution in sight. Competing hypotheses have typically been evaluated with correlative models that do not explicitly incorporate the mechanisms responsible for biotic diversity gradients....... Here, we employ a fundamentally different approach that uses spatially explicit Monte Carlo models of the placement of cohesive geographical ranges in an environmentally heterogeneous landscape. These models predict species richness of endemic South American birds (2248 species) measured...

Mathematical modelling of the influenced of diffusion rate on macro nutrient availability in paddy field

Science.gov (United States)

Renny; Supriyanto

2018-04-01

Nutrition is the chemical compounds that needed by the organism for the growth process. In plants, nutrients are organic or inorganic compounds that are absorbed from the roots of the soil. It consist of macro and micro nutrient. Macro nutrients are nutrition that needed by plants in large quantities, such as, nitrogen, calcium, pottacium, magnesium, and sulfur. The total soil nutrient is the difference between the input nutrient and the output nutrients. Input nutrients are nutrient that derived from the decomposition of organic substances. Meanwhile, the output nutrient consists of the nutrients that absorbed by plant roots (uptake), the evaporated nutrients (volatilized) and leached nutrients. The nutrient transport can be done through diffusion process. The diffusion process is essential in removing the nutrient from one place to the root surface. It will cause the rate of absorption of nutrient by the roots will be greater. Nutrient concept in paddy filed can be represented into a mathematical modelling, by making compartment models. The rate of concentration change in the compartment model forms a system of homogeneous linear differential equations. In this research, we will use Laplaces transformation to solve the compartment model and determined the dynamics of macro nutrition due to diffusion process.

A cross-comparison of different techniques for modeling macro-level cyclist crashes.

Science.gov (United States)

Guo, Yanyong; Osama, Ahmed; Sayed, Tarek

2018-04-01

Despite the recognized benefits of cycling as a sustainable mode of transportation, cyclists are considered vulnerable road users and there are concerns about their safety. Therefore, it is essential to investigate the factors affecting cyclist safety. The goal of this study is to evaluate and compare different approaches of modeling macro-level cyclist safety as well as investigating factors that contribute to cyclist crashes using a comprehensive list of covariates. Data from 134 traffic analysis zones (TAZs) in the City of Vancouver were used to develop macro-level crash models (CM) incorporating variables related to actual traffic exposure, socio-economics, land use, built environment, and bike network. Four types of CMs were developed under a full Bayesian framework: Poisson lognormal model (PLN), random intercepts PLN model (RIPLN), random parameters PLN model (RPPLN), and spatial PLN model (SPLN). The SPLN model had the best goodness of fit, and the results highlighted the significant effects of spatial correlation. The models showed that the cyclist crashes were positively associated with bike and vehicle exposure measures, households, commercial area density, and signal density. On the other hand, negative associations were found between cyclist crashes and some bike network indicators such as average edge length, average zonal slope, and off-street bike links. Copyright © 2018 Elsevier Ltd. All rights reserved.

How can results from macro economic analyses of the energy consumption of households be used in macro models? A discussion of theoretical and empirical literature about aggregation

International Nuclear Information System (INIS)

Halvorsen, Bente; Larsen, Bodil M.; Nesbakken, Runa

2001-01-01

The literature on energy demand shows that there are systematic differences in income- and price elasticity from analyses based on macro data and micro data. Even if one estimates models with the same explanatory variables, the results may differ with respect to estimated price- and income sensitivity. These differences may be caused by problems involved in transferring micro properties to macro properties, or the estimated macro relationships have failed to adequately consideration the fact that households behave differently in their energy demand. Political goals are often directed towards the entire household sector. Partial equilibrium models do not capture important equilibrium effects and feedback through the energy markets and the economy in general. Thus, it is very interesting, politically and scientifically, to do macro economic model analyses of different political measures that affect the energy consumption. The results of behavioural analyses, in which one investigates the heterogeneity of the energy demand, must be based on information about individual households. When the demand is studied based on micro data, it is difficult to aggregate its properties to a total demand function for the entire household sector if different household sectors have different behaviour. Such heterogeneity of behaviour may for instance arise when households in different regions have different heating equipment because of regional differences in the price of electricity. The subject of aggregation arises immediately when one wants to draw conclusions about the household sector based on information about individual households, whether the discussion is about the whole population or a selection of households. Thus, aggregation is a topic of interest in a wide range of problems

Linking ground motion measurements and macro-seismic observations in France: A case study based on the RAP (accelerometric) and BCSF (macro-seismic) databases

International Nuclear Information System (INIS)

Lesueur, Ch.

2011-01-01

Comparison between accelerometric and macro-seismic observations is made for three mw∼4.5 earthquakes of eastern France between 2003 and 2005. Scalar and spectral instrumental parameters are processed from the accelerometric data recorded by nine accelerometric stations located between 29 km and 180 km from the epicentres. Macro-seismic data are based on the French internet reports. In addition to the individual macro-seismic intensity, analysis of the internal correlation between the encoded answers highlights four predominant fields of questions, bearing different physical meanings: 1) 'vibratory motions of small objects', 2) 'displacement and fall of objects', 3) 'acoustic noise', and 4) 'personal feelings'. Best correlations between macro-seismic and instrumental observations are obtained when the macro-seismic parameters are averaged over 10 km radius circles around each station. macro-seismic intensities predicted by published pgv-intensity relationships quite agree with the observed intensities, contrary to those based on pga. The correlations between the macro-seismic and instrumental data, for intensities between ii and v (ems-98), show that pgv is the instrumental parameter presenting the best correlation with all macro-seismic parameters. The correlation with response spectra, exhibits clear frequency dependence over a limited frequency range [0.5-33 hz]. Horizontal and vertical components are significantly correlated with macro-seismic parameters between 1 and 10 hz, a range corresponding to both natural frequencies of most buildings and high energy content in the seismic ground motion. Between 10 and 25 hz, a clear lack of correlation between macro-seismic and instrumental data is observed, while beyond 25 hz the correlation coefficient increases, approaching that of the PGA correlation level. (author)

Towards Realising FollowMe User Profiles for Macro-Intelligent Environments

Directory of Open Access Journals (Sweden)

Luke Whittington

2013-07-01

Full Text Available In this paper, we introduce the concept of a Large-Scale Intelligent Environment (LSIE and provide an introduction to the use of bigraphs as a formal method for description and modelling. We then propose our MacroIE model as a solution to the LSIE problem and describe how that model may be implemented to achieve a continuity-of-experience to end users as they travel from place-to-place (a technology we call FollowMe. Our initial experiments with these implementations are presented, providing some valuable insights and promise for future refinement towards real-world deployment.

A Study on the development of macro environmental economic model(I)

Energy Technology Data Exchange (ETDEWEB)

Chung, Young Keun; Han, Min Jung [Korea Environment Institute, Seoul (Korea)

1998-12-01

This study is the first year study of the two year research project for developing a macro environmental economic model to analyze environment and economics. By using this model, the economic effects of investment on pollution reduction and on energy conservation are analyzed. Also, a comprehensive modeling of analyzing effects of environmental tax, reduction on greenhouse gas emission, and problems on foreign exchange on environment and economy is a main goal of this study. It is planned to develop a simulation program for the estimation of model and policies using environmental and economic data. 126 refs., 2 figs., 5 tabs.

Synopsis Session III and IV 'Water and ion mobility, up-scaling and implementation in model approaches'

International Nuclear Information System (INIS)

2013-01-01

The contributions of Session III 'Water and ion mobility' and Session IV 'Up-scaling and implementation in model approaches' were merged for the proceedings volume. The range of scales we are interested in starts at molecular scale (1-3 Angstrom) to crystal scale (3 Angstrom-2 nm) over particle scale with 2-200 nm dimension to the particle/macro-aggregate scale with 0.2-1500 μm. Methods available to study the particle scale concerning pore structure and connectivity which determines water mobility are under dry conditions N 2 adsorption and Hg intrusion, whereas under the hydrated state methods like X-Ray tomography and X-ray and neutron scattering are available. Going down in size molecular modeling, x-ray and neutron diffraction modeling and water adsorption gravimetry are inter alia available. There are resolution limits to the methods presented in session II (e.g. BIB-SEM) on pore characterization as e.g. the clay matrix characterization being only possible under a limited clay induration and pore throats being on the limit of resolution. These pore throats however are very important for as macroscopic phenomena observed. One methodological approach to bridge the gap between the molecular/crystal scale and the particle/macro-aggregate scale (FIB-SEM) is to use complementary techniques as cryo-NMR, N 2 and water ad-/desorption and TEM

Micromechanics model for predicting anisotropic electrical conductivity of carbon fiber composite materials

Science.gov (United States)

Haider, Mohammad Faisal; Haider, Md. Mushfique; Yasmeen, Farzana

2016-07-01

Heterogeneous materials, such as composites consist of clearly distinguishable constituents (or phases) that show different electrical properties. Multifunctional composites have anisotropic electrical properties that can be tailored for a particular application. The effective anisotropic electrical conductivity of composites is strongly affected by many parameters including volume fractions, distributions, and orientations of constituents. Given the electrical properties of the constituents, one important goal of micromechanics of materials consists of predicting electrical response of the heterogeneous material on the basis of the geometries and properties of the individual phases, a task known as homogenization. The benefit of homogenization is that the behavior of a heterogeneous material can be determined without resorting or testing it. Furthermore, continuum micromechanics can predict the full multi-axial properties and responses of inhomogeneous materials, which are anisotropic in nature. Effective electrical conductivity estimation is performed by using classical micromechanics techniques (composite cylinder assemblage method) that investigates the effect of the fiber/matrix electrical properties and their volume fractions on the micro scale composite response. The composite cylinder assemblage method (CCM) is an analytical theory that is based on the assumption that composites are in a state of periodic structure. The CCM was developed to extend capabilities variable fiber shape/array availability with same volume fraction, interphase analysis, etc. The CCM is a continuum-based micromechanics model that provides closed form expressions for upper level length scales such as macro-scale composite responses in terms of the properties, shapes, orientations and constituent distributions at lower length levels such as the micro-scale.

Immunopositivity for histone macroH2A1 isoforms marks steatosis-associated hepatocellular carcinoma.

Directory of Open Access Journals (Sweden)

Francesca Rappa

Full Text Available Hepatocellular carcinoma (HCC is one of the most common cancers worldwide. Prevention and risk reduction are important and the identification of specific biomarkers for early diagnosis of HCC represents an active field of research. Increasing evidence indicates that fat accumulation in the liver, defined as hepatosteatosis, is an independent and strong risk factor for developing an HCC. MacroH2A1, a histone protein generally associated with the repressed regions of chromosomes, is involved in hepatic lipid metabolism and is present in two alternative spliced isoforms, macroH2A1.1 and macroH2A1.2. These isoforms have been shown to predict lung and colon cancer recurrence but to our knowledge, their role in fatty-liver associated HCC has not been investigated previously.We examined macroH2A1.1 and macroH2A1.2 protein expression levels in the liver of two murine models of fat-associated HCC, the high fat diet/diethylnistrosamine (DEN and the phosphatase and tensin homolog (PTEN liver specific knock-out (KO mouse, and in human liver samples of subjects with steatosis or HCC, using immunoblotting and immunohistochemistry.Protein levels for both macroH2A1 isoforms were massively upregulated in HCC, whereas macroH2A1.2 was specifically upregulated in steatosis. In addition, examination of human liver samples showed a significant difference (p<0.01 in number of positive nuclei in HCC (100% of tumor cells positive for either macroH2A1.1 or macroH2A1.2, when compared to steatosis (<2% of hepatocytes positive for either isoform. The steatotic areas flanking the tumors were highly immunopositive for macroH2A1.1 and macroH2A1.2.These data obtained in mice and humans suggest that both macroH2A1 isoforms may play a role in HCC pathogenesis and moreover may be considered as novel diagnostic markers for human HCC.

Multi-Scale Analysis for Characterizing Near-Field Constituent Concentrations in the Context of a Macro-Scale Semi-Lagrangian Numerical Model

Science.gov (United States)

Yearsley, J. R.

2017-12-01

The semi-Lagrangian numerical scheme employed by RBM, a model for simulating time-dependent, one-dimensional water quality constituents in advection-dominated rivers, is highly scalable both in time and space. Although the model has been used at length scales of 150 meters and time scales of three hours, the majority of applications have been at length scales of 1/16th degree latitude/longitude (about 5 km) or greater and time scales of one day. Applications of the method at these scales has proven successful for characterizing the impacts of climate change on water temperatures in global rivers and on the vulnerability of thermoelectric power plants to changes in cooling water temperatures in large river systems. However, local effects can be very important in terms of ecosystem impacts, particularly in the case of developing mixing zones for wastewater discharges with pollutant loadings limited by regulations imposed by the Federal Water Pollution Control Act (FWPCA). Mixing zone analyses have usually been decoupled from large-scale watershed influences by developing scenarios that represent critical scenarios for external processes associated with streamflow and weather conditions . By taking advantage of the particle-tracking characteristics of the numerical scheme, RBM can provide results at any point in time within the model domain. We develop a proof of concept for locations in the river network where local impacts such as mixing zones may be important. Simulated results from the semi-Lagrangian numerical scheme are treated as input to a finite difference model of the two-dimensional diffusion equation for water quality constituents such as water temperature or toxic substances. Simulations will provide time-dependent, two-dimensional constituent concentration in the near-field in response to long-term basin-wide processes. These results could provide decision support to water quality managers for evaluating mixing zone characteristics.

In-Hospital Risk Prediction for Post-stroke Depression. Development and Validation of the Post-stroke Depression Prediction Scale

NARCIS (Netherlands)

Thóra Hafsteinsdóttir; Roelof G.A. Ettema; Diederick Grobbee; Prof. Dr. Marieke J. Schuurmans; Janneke van Man-van Ginkel; Eline Lindeman

2013-01-01

Background and Purpose—The timely detection of post-stroke depression is complicated by a decreasing length of hospital stay. Therefore, the Post-stroke Depression Prediction Scale was developed and validated. The Post-stroke Depression Prediction Scale is a clinical prediction model for the early

Design-based modeling of magnetically actuated soft diaphragm materials

Science.gov (United States)

Jayaneththi, V. R.; Aw, K. C.; McDaid, A. J.

2018-04-01

Magnetic polymer composites (MPC) have shown promise for emerging biomedical applications such as lab-on-a-chip and implantable drug delivery. These soft material actuators are capable of fast response, large deformation and wireless actuation. Existing MPC modeling approaches are computationally expensive and unsuitable for rapid design prototyping and real-time control applications. This paper proposes a macro-scale 1-DOF model capable of predicting force and displacement of an MPC diaphragm actuator. Model validation confirmed both blocked force and displacement can be accurately predicted in a variety of working conditions i.e. different magnetic field strengths, static/dynamic fields, and gap distances. The contribution of this work includes a comprehensive experimental investigation of a macro-scale diaphragm actuator; the derivation and validation of a new phenomenological model to describe MPC actuation; and insights into the proposed model’s design-based functionality i.e. scalability and generalizability in terms of magnetic filler concentration and diaphragm diameter. Due to the lumped element modeling approach, the proposed model can also be adapted to alternative actuator configurations, and thus presents a useful tool for design, control and simulation of novel MPC applications.

A multi-scale modeling framework for individualized, spatiotemporal prediction of drug effects and toxicological risk

Directory of Open Access Journals (Sweden)

Juan Guillermo eDiaz Ochoa

2013-01-01

Full Text Available In this study, we focus on a novel multi-scale modeling approach for spatiotemporal prediction of the distribution of substances and resulting hepatotoxicity by combining cellular models, a 2D liver model, and whole-body model. As a case study, we focused on predicting human hepatotoxicity upon treatment with acetaminophen based on in vitro toxicity data and potential inter-individual variability in gene expression and enzyme activities. By aggregating mechanistic, genome-based in silico cells to a novel 2D liver model and eventually to a whole body model, we predicted pharmacokinetic properties, metabolism, and the onset of hepatotoxicity in an in silico patient. Depending on the concentration of acetaminophen in the liver and the accumulation of toxic metabolites, cell integrity in the liver as a function of space and time as well as changes in the elimination rate of substances were estimated. We show that the variations in elimination rates also influence the distribution of acetaminophen and its metabolites in the whole body. Our results are in agreement with experimental results. What is more, the integrated model also predicted variations in drug toxicity depending on alterations of metabolic enzyme activities. Variations in enzyme activity, in turn, reflect genetic characteristics or diseases of individuals. In conclusion, this framework presents an important basis for efficiently integrating inter-individual variability data into models, paving the way for personalized or stratified predictions of drug toxicity and efficacy.

Multi-physics and multi-scale deterioration modelling of reinforced concrete part I: Coupling transport and corrosion at the material scale

DEFF Research Database (Denmark)

Michel, Alexander; Geiker, Mette Rica; Stang, Henrik

2015-01-01

is fully coupled, i.e. information, such as temperature and moisture distribution, phase assemblage, corrosion current density, damage state of concrete cover, etc., are continuously exchanged between the models. Although not explicitly outlined in this paper, such an analysis may be further integrated...... models are sketched to describe (i) transport of heat and matter in porous media as well as phase assemblage in hardened Portland cement, (ii) corrosion of reinforcement, and (iii) material performance including corrosion-induced damages on the meso and macro scale. The presented modelling framework...

Multi-scale enhancement of climate prediction over land by improving the model sensitivity to vegetation variability

Science.gov (United States)

Alessandri, A.; Catalano, F.; De Felice, M.; Hurk, B. V. D.; Doblas-Reyes, F. J.; Boussetta, S.; Balsamo, G.; Miller, P. A.

2017-12-01

Here we demonstrate, for the first time, that the implementation of a realistic representation of vegetation in Earth System Models (ESMs) can significantly improve climate simulation and prediction across multiple time-scales. The effective sub-grid vegetation fractional coverage vary seasonally and at interannual time-scales in response to leaf-canopy growth, phenology and senescence. Therefore it affects biophysical parameters such as the surface resistance to evapotranspiration, albedo, roughness lenght, and soil field capacity. To adequately represent this effect in the EC-Earth ESM, we included an exponential dependence of the vegetation cover on the Leaf Area Index.By comparing two sets of simulations performed with and without the new variable fractional-coverage parameterization, spanning from centennial (20th Century) simulations and retrospective predictions to the decadal (5-years), seasonal (2-4 months) and weather (4 days) time-scales, we show for the first time a significant multi-scale enhancement of vegetation impacts in climate simulation and prediction over land. Particularly large effects at multiple time scales are shown over boreal winter middle-to-high latitudes over Canada, West US, Eastern Europe, Russia and eastern Siberia due to the implemented time-varying shadowing effect by tree-vegetation on snow surfaces. Over Northern Hemisphere boreal forest regions the improved representation of vegetation-cover consistently correct the winter warm biases, improves the climate change sensitivity, the decadal potential predictability as well as the skill of forecasts at seasonal and weather time-scales. Significant improvements of the prediction of 2m temperature and rainfall are also shown over transitional land surface hot spots. Both the potential predictability at decadal time-scale and seasonal-forecasts skill are enhanced over Sahel, North American Great Plains, Nordeste Brazil and South East Asia, mainly related to improved performance in

Topoclimatic modeling for minimum temperature prediction at a regional scale in the Central Valley of Chile

International Nuclear Information System (INIS)

Santibáñez, F.; Morales, L.; Fuente, J. de la; Cellier, P.; Huete, A.

1997-01-01

Spring frost may strongly affect fruit production in the Central Valley of Chile. Minimum temperatures are spatially variable owing to topography and soil conditions. A methodology for forecasting minimum temperature at a regional scale in the Central Valley of Chile, integrating spatial variability of temperature under radiative frost conditions, has been developed. It uses simultaneously a model for forecasting minimum temperatures at a reference station using air temperature and humidity measured at 6 pm, and topoclimatic models, based on satellite infra-red imagery (NOAA/AVHRR) and a digital elevation model, to extend the prediction at a regional scale. The methodological developments were integrated in a geographic information system for geo referencing of a meteorological station with satellite imagery and modeled output. This approach proved to be a useful tool for short range (12 h) minimum temperature prediction by generating thermal images over the Central Valley of Chile. It may also be used as a tool for frost risk assessment, in order to adapt production to local climatological conditions. (author)

International scale implementation of the CNOSSOS-EU road traffic noise prediction model for epidemiological studies

International Nuclear Information System (INIS)

Morley, D.W.; Hoogh, K. de; Fecht, D.; Fabbri, F.; Bell, M.; Goodman, P.S.; Elliott, P.; Hodgson, S.; Hansell, A.L.; Gulliver, J.

2015-01-01

The EU-FP7-funded BioSHaRE project is using individual-level data pooled from several national cohort studies in Europe to investigate the relationship of road traffic noise and health. The detailed input data (land cover and traffic characteristics) required for noise exposure modelling are not always available over whole countries while data that are comparable in spatial resolution between different countries is needed for harmonised exposure assessment. Here, we assess the feasibility using the CNOSSOS-EU road traffic noise prediction model with coarser input data in terms of model performance. Starting with a model using the highest resolution datasets, we progressively introduced lower resolution data over five further model runs and compared noise level estimates to measurements. We conclude that a low resolution noise model should provide adequate performance for exposure ranking (Spearman's rank = 0.75; p < 0.001), but with relatively large errors in predicted noise levels (RMSE = 4.46 dB(A)). - Highlights: • The first implementation of CNOSSOS-EU for national scale noise exposure assessment. • Road traffic noise model performance with varying resolution of inputs is assessed. • Model performance is good with low resolution inputs (r_s = 0.75). • This model will be applied in epidemiological studies of European cohorts. - The CNOSSOS-EU road traffic noise model estimates can be used for international scale exposure assessment when parameterised with freely available low resolution covering a large geographic area.

Spatiotemporal property and predictability of large-scale human mobility

Science.gov (United States)

Zhang, Hai-Tao; Zhu, Tao; Fu, Dongfei; Xu, Bowen; Han, Xiao-Pu; Chen, Duxin

2018-04-01

Spatiotemporal characteristics of human mobility emerging from complexity on individual scale have been extensively studied due to the application potential on human behavior prediction and recommendation, and control of epidemic spreading. We collect and investigate a comprehensive data set of human activities on large geographical scales, including both websites browse and mobile towers visit. Numerical results show that the degree of activity decays as a power law, indicating that human behaviors are reminiscent of scale-free random walks known as Lévy flight. More significantly, this study suggests that human activities on large geographical scales have specific non-Markovian characteristics, such as a two-segment power-law distribution of dwelling time and a high possibility for prediction. Furthermore, a scale-free featured mobility model with two essential ingredients, i.e., preferential return and exploration, and a Gaussian distribution assumption on the exploration tendency parameter is proposed, which outperforms existing human mobility models under scenarios of large geographical scales.

Mechanistically-Based Field-Scale Models of Uranium Biogeochemistry from Upscaling Pore-Scale Experiments and Models

International Nuclear Information System (INIS)

Tim Scheibe; Alexandre Tartakovsky; Brian Wood; Joe Seymour

2007-01-01

Effective environmental management of DOE sites requires reliable prediction of reactive transport phenomena. A central issue in prediction of subsurface reactive transport is the impact of multiscale physical, chemical, and biological heterogeneity. Heterogeneity manifests itself through incomplete mixing of reactants at scales below those at which concentrations are explicitly defined (i.e., the numerical grid scale). This results in a mismatch between simulated reaction processes (formulated in terms of average concentrations) and actual processes (controlled by local concentrations). At the field scale, this results in apparent scale-dependence of model parameters and inability to utilize laboratory parameters in field models. Accordingly, most field modeling efforts are restricted to empirical estimation of model parameters by fitting to field observations, which renders extrapolation of model predictions beyond fitted conditions unreliable. The objective of this project is to develop a theoretical and computational framework for (1) connecting models of coupled reactive transport from pore-scale processes to field-scale bioremediation through a hierarchy of models that maintain crucial information from the smaller scales at the larger scales; and (2) quantifying the uncertainty that is introduced by both the upscaling process and uncertainty in physical parameters. One of the challenges of addressing scale-dependent effects of coupled processes in heterogeneous porous media is the problem-specificity of solutions. Much effort has been aimed at developing generalized scaling laws or theories, but these require restrictive assumptions that render them ineffective in many real problems. We propose instead an approach that applies physical and numerical experiments at small scales (specifically the pore scale) to a selected model system in order to identify the scaling approach appropriate to that type of problem. Although the results of such studies will

Mechanistically-Based Field-Scale Models of Uranium Biogeochemistry from Upscaling Pore-Scale Experiments and Models

Energy Technology Data Exchange (ETDEWEB)

Tim Scheibe; Alexandre Tartakovsky; Brian Wood; Joe Seymour

2007-04-19

Effective environmental management of DOE sites requires reliable prediction of reactive transport phenomena. A central issue in prediction of subsurface reactive transport is the impact of multiscale physical, chemical, and biological heterogeneity. Heterogeneity manifests itself through incomplete mixing of reactants at scales below those at which concentrations are explicitly defined (i.e., the numerical grid scale). This results in a mismatch between simulated reaction processes (formulated in terms of average concentrations) and actual processes (controlled by local concentrations). At the field scale, this results in apparent scale-dependence of model parameters and inability to utilize laboratory parameters in field models. Accordingly, most field modeling efforts are restricted to empirical estimation of model parameters by fitting to field observations, which renders extrapolation of model predictions beyond fitted conditions unreliable. The objective of this project is to develop a theoretical and computational framework for (1) connecting models of coupled reactive transport from pore-scale processes to field-scale bioremediation through a hierarchy of models that maintain crucial information from the smaller scales at the larger scales; and (2) quantifying the uncertainty that is introduced by both the upscaling process and uncertainty in physical parameters. One of the challenges of addressing scale-dependent effects of coupled processes in heterogeneous porous media is the problem-specificity of solutions. Much effort has been aimed at developing generalized scaling laws or theories, but these require restrictive assumptions that render them ineffective in many real problems. We propose instead an approach that applies physical and numerical experiments at small scales (specifically the pore scale) to a selected model system in order to identify the scaling approach appropriate to that type of problem. Although the results of such studies will

Dynamic subgrid scale model used in a deep bundle turbulence prediction using the large eddy simulation method

International Nuclear Information System (INIS)

Barsamian, H.R.; Hassan, Y.A.

1996-01-01

Turbulence is one of the most commonly occurring phenomena of engineering interest in the field of fluid mechanics. Since most flows are turbulent, there is a significant payoff for improved predictive models of turbulence. One area of concern is the turbulent buffeting forces experienced by the tubes in steam generators of nuclear power plants. Although the Navier-Stokes equations are able to describe turbulent flow fields, the large number of scales of turbulence limit practical flow field calculations with current computing power. The dynamic subgrid scale closure model of Germano et. al (1991) is used in the large eddy simulation code GUST for incompressible isothermal flows. Tube bundle geometries of staggered and non-staggered arrays are considered in deep bundle simulations. The advantage of the dynamic subgrid scale model is the exclusion of an input model coefficient. The model coefficient is evaluated dynamically for each nodal location in the flow domain. Dynamic subgrid scale results are obtained in the form of power spectral densities and flow visualization of turbulent characteristics. Comparisons are performed among the dynamic subgrid scale model, the Smagorinsky eddy viscosity model (Smagorinsky, 1963) (that is used as the base model for the dynamic subgrid scale model) and available experimental data. Spectral results of the dynamic subgrid scale model correlate better with experimental data. Satisfactory turbulence characteristics are observed through flow visualization

Study on high density multi-scale calculation technique

International Nuclear Information System (INIS)

Sekiguchi, S.; Tanaka, Y.; Nakada, H.; Nishikawa, T.; Yamamoto, N.; Yokokawa, M.

2004-01-01

To understand degradation of nuclear materials under irradiation, it is essential to know as much about each phenomenon observed from multi-scale points of view; they are micro-scale in atomic-level, macro-level in structural scale and intermediate level. In this study for application to meso-scale materials (100A ∼ 2μm), computer technology approaching from micro- and macro-scales was developed including modeling and computer application using computational science and technology method. And environmental condition of grid technology for multi-scale calculation was prepared. The software and MD (molecular dynamics) stencil for verifying the multi-scale calculation were improved and their movement was confirmed. (A. Hishinuma)

Toward seamless hydrologic predictions across spatial scales

Directory of Open Access Journals (Sweden)

L. Samaniego

2017-09-01

Full Text Available Land surface and hydrologic models (LSMs/HMs are used at diverse spatial resolutions ranging from catchment-scale (1–10 km to global-scale (over 50 km applications. Applying the same model structure at different spatial scales requires that the model estimates similar fluxes independent of the chosen resolution, i.e., fulfills a flux-matching condition across scales. An analysis of state-of-the-art LSMs and HMs reveals that most do not have consistent hydrologic parameter fields. Multiple experiments with the mHM, Noah-MP, PCR-GLOBWB, and WaterGAP models demonstrate the pitfalls of deficient parameterization practices currently used in most operational models, which are insufficient to satisfy the flux-matching condition. These examples demonstrate that J. Dooge's 1982 statement on the unsolved problem of parameterization in these models remains true. Based on a review of existing parameter regionalization techniques, we postulate that the multiscale parameter regionalization (MPR technique offers a practical and robust method that provides consistent (seamless parameter and flux fields across scales. Herein, we develop a general model protocol to describe how MPR can be applied to a particular model and present an example application using the PCR-GLOBWB model. Finally, we discuss potential advantages and limitations of MPR in obtaining the seamless prediction of hydrological fluxes and states across spatial scales.

Toward seamless hydrologic predictions across spatial scales

Science.gov (United States)

Samaniego, Luis; Kumar, Rohini; Thober, Stephan; Rakovec, Oldrich; Zink, Matthias; Wanders, Niko; Eisner, Stephanie; Müller Schmied, Hannes; Sutanudjaja, Edwin H.; Warrach-Sagi, Kirsten; Attinger, Sabine

2017-09-01

Land surface and hydrologic models (LSMs/HMs) are used at diverse spatial resolutions ranging from catchment-scale (1-10 km) to global-scale (over 50 km) applications. Applying the same model structure at different spatial scales requires that the model estimates similar fluxes independent of the chosen resolution, i.e., fulfills a flux-matching condition across scales. An analysis of state-of-the-art LSMs and HMs reveals that most do not have consistent hydrologic parameter fields. Multiple experiments with the mHM, Noah-MP, PCR-GLOBWB, and WaterGAP models demonstrate the pitfalls of deficient parameterization practices currently used in most operational models, which are insufficient to satisfy the flux-matching condition. These examples demonstrate that J. Dooge's 1982 statement on the unsolved problem of parameterization in these models remains true. Based on a review of existing parameter regionalization techniques, we postulate that the multiscale parameter regionalization (MPR) technique offers a practical and robust method that provides consistent (seamless) parameter and flux fields across scales. Herein, we develop a general model protocol to describe how MPR can be applied to a particular model and present an example application using the PCR-GLOBWB model. Finally, we discuss potential advantages and limitations of MPR in obtaining the seamless prediction of hydrological fluxes and states across spatial scales.

Predictions for an invaded world: A strategy to predict the distribution of native and non-indigenous species at multiple scales

Science.gov (United States)

Reusser, D.A.; Lee, H.

2008-01-01

Habitat models can be used to predict the distributions of marine and estuarine non-indigenous species (NIS) over several spatial scales. At an estuary scale, our goal is to predict the estuaries most likely to be invaded, but at a habitat scale, the goal is to predict the specific locations within an estuary that are most vulnerable to invasion. As an initial step in evaluating several habitat models, model performance for a suite of benthic species with reasonably well-known distributions on the Pacific coast of the US needs to be compared. We discuss the utility of non-parametric multiplicative regression (NPMR) for predicting habitat- and estuary-scale distributions of native and NIS. NPMR incorporates interactions among variables, allows qualitative and categorical variables, and utilizes data on absence as well as presence. Preliminary results indicate that NPMR generally performs well at both spatial scales and that distributions of NIS are predicted as well as those of native species. For most species, latitude was the single best predictor, although similar model performance could be obtained at both spatial scales with combinations of other habitat variables. Errors of commission were more frequent at a habitat scale, with omission and commission errors approximately equal at an estuary scale. ?? 2008 International Council for the Exploration of the Sea. Published by Oxford Journals. All rights reserved.

Sensitivity of point scale surface runoff predictions to rainfall resolution

Directory of Open Access Journals (Sweden)

A. J. Hearman

2007-01-01

Full Text Available This paper investigates the effects of using non-linear, high resolution rainfall, compared to time averaged rainfall on the triggering of hydrologic thresholds and therefore model predictions of infiltration excess and saturation excess runoff at the point scale. The bounded random cascade model, parameterized to three locations in Western Australia, was used to scale rainfall intensities at various time resolutions ranging from 1.875 min to 2 h. A one dimensional, conceptual rainfall partitioning model was used that instantaneously partitioned water into infiltration excess, infiltration, storage, deep drainage, saturation excess and surface runoff, where the fluxes into and out of the soil store were controlled by thresholds. The results of the numerical modelling were scaled by relating soil infiltration properties to soil draining properties, and in turn, relating these to average storm intensities. For all soil types, we related maximum infiltration capacities to average storm intensities (k* and were able to show where model predictions of infiltration excess were most sensitive to rainfall resolution (ln k*=0.4 and where using time averaged rainfall data can lead to an under prediction of infiltration excess and an over prediction of the amount of water entering the soil (ln k*>2 for all three rainfall locations tested. For soils susceptible to both infiltration excess and saturation excess, total runoff sensitivity was scaled by relating drainage coefficients to average storm intensities (g* and parameter ranges where predicted runoff was dominated by infiltration excess or saturation excess depending on the resolution of rainfall data were determined (ln g*<2. Infiltration excess predicted from high resolution rainfall was short and intense, whereas saturation excess produced from low resolution rainfall was more constant and less intense. This has important implications for the accuracy of current hydrological models that use time

Monitoring multi-year macro ocean litter dynamics and backward-tracking simulation of litter origins on a remote island in the South China Sea

Science.gov (United States)

Ko, Chia-Ying; Hsin, Yi-Chia; Yu, Teng-Lang; Liu, Kuo-Lieh; Shiah, Fuh-Kwo; Jeng, Ming-Shiou

2018-04-01

Ocean litter has accumulated rapidly and is becoming a major environmental concern, yet quantitative and regular observations and exploration that track litter origins are limited. By implementing monthly sample collections over five years (2012–2016) at Dongsha Island, a remote island in the northern South China Sea (SCS), we assessed macro ocean litter dynamics, identified source countries of individual plastic bottles, and analyzed the origins of the litter by a backward-tracking model simulation considering both the effects of current velocity and windage. The results showed that large amounts of litter, which varied monthly and annually in weight and quantity, reached the island during the study years, and there were spatial differences in accumulation patterns between the north and south coasts. Styrofoam and plastic bottles were the two primary sources of macro ocean litter both annually and monthly, and most of the litter collected on the island originated from China and Vietnam, which were collectively responsible for approximately 47.5%–63.7% per month. The simulation indicated that current advection at the near-surface depths and low windage at the sea surface showed similar patterns, while medium to high windage exhibited comparable expression patterns in response to potential source regions and drifting time experiments. At either the surface with low windage or current advection at depths of 0.5 m and 1 m, macro ocean litter in the Western Philippine Sea, i.e. through the Luzon Strait between Taiwan and the Philippines, was an important contributor to the litter bulk from October to March, whereas the litter was predicted to mainly originate from the southwestern SCS from April to September. With an increasing windage effect, litter in the Taiwan Strait was predicted to be an additional major potential source. Surprisingly, a small proportion of the macro ocean litter was predicted to continuously travel in the northern SCS for a long duration

Prediction of a Francis turbine prototype full load instability from investigations on the reduced scale model

Science.gov (United States)

Alligné, S.; Maruzewski, P.; Dinh, T.; Wang, B.; Fedorov, A.; Iosfin, J.; Avellan, F.

2010-08-01

The growing development of renewable energies combined with the process of privatization, lead to a change of economical energy market strategies. Instantaneous pricings of electricity as a function of demand or predictions, induces profitable peak productions which are mainly covered by hydroelectric power plants. Therefore, operators harness more hydroelectric facilities at full load operating conditions. However, the Francis Turbine features an axi-symmetric rope leaving the runner which may act under certain conditions as an internal energy source leading to instability. Undesired power and pressure fluctuations are induced which may limit the maximum available power output. BC Hydro experiences such constraints in a hydroelectric power plant consisting of four 435 MW Francis Turbine generating units, which is located in Canada's province of British Columbia. Under specific full load operating conditions, one unit experiences power and pressure fluctuations at 0.46 Hz. The aim of the paper is to present a methodology allowing prediction of this prototype's instability frequency from investigations on the reduced scale model. A new hydro acoustic vortex rope model has been developed in SIMSEN software, taking into account the energy dissipation due to the thermodynamic exchange between the gas and the surrounding liquid. A combination of measurements, CFD simulations and computation of eigenmodes of the reduced scale model installed on test rig, allows the accurate calibration of the vortex rope model parameters at the model scale. Then, transposition of parameters to the prototype according to similitude laws is applied and stability analysis of the power plant is performed. The eigenfrequency of 0.39 Hz related to the first eigenmode of the power plant is determined to be unstable. Predicted frequency of the full load power and pressure fluctuations at the unit unstable operating point is found to be in general agreement with the prototype measurements.

Prediction of a Francis turbine prototype full load instability from investigations on the reduced scale model

International Nuclear Information System (INIS)

Alligne, S; Maruzewski, P; Avellan, F; Dinh, T; Wang, B; Fedorov, A; Iosfin, J

2010-01-01

The growing development of renewable energies combined with the process of privatization, lead to a change of economical energy market strategies. Instantaneous pricings of electricity as a function of demand or predictions, induces profitable peak productions which are mainly covered by hydroelectric power plants. Therefore, operators harness more hydroelectric facilities at full load operating conditions. However, the Francis Turbine features an axi-symmetric rope leaving the runner which may act under certain conditions as an internal energy source leading to instability. Undesired power and pressure fluctuations are induced which may limit the maximum available power output. BC Hydro experiences such constraints in a hydroelectric power plant consisting of four 435 MW Francis Turbine generating units, which is located in Canada's province of British Columbia. Under specific full load operating conditions, one unit experiences power and pressure fluctuations at 0.46 Hz. The aim of the paper is to present a methodology allowing prediction of this prototype's instability frequency from investigations on the reduced scale model. A new hydro acoustic vortex rope model has been developed in SIMSEN software, taking into account the energy dissipation due to the thermodynamic exchange between the gas and the surrounding liquid. A combination of measurements, CFD simulations and computation of eigenmodes of the reduced scale model installed on test rig, allows the accurate calibration of the vortex rope model parameters at the model scale. Then, transposition of parameters to the prototype according to similitude laws is applied and stability analysis of the power plant is performed. The eigenfrequency of 0.39 Hz related to the first eigenmode of the power plant is determined to be unstable. Predicted frequency of the full load power and pressure fluctuations at the unit unstable operating point is found to be in general agreement with the prototype measurements.

Nano- and Macro-wear of Bio-carbo-nitrided AISI 8620 Steel Surfaces

Science.gov (United States)

Arthur, Emmanuel Kwesi; Ampaw, Edward; Zebaze Kana, M. G.; Adetunji, A. R.; Olusunle, S. O. O.; Adewoye, O. O.; Soboyejo, W. O.

2015-12-01

This paper presents the results of an experimental study of nano- and macro-scale wear in a carbo-nitrided AISI 8620 steel. Carbo-nitriding is carried out using a novel method that involves the use of dried, cyanide-containing cassava leaves, as sources of carbon and nitrogen. These are used in a pack cementation that is used to diffuse carbon and nitrogen into case layers at intermediate temperatures [673.15 K, 723.15 K, 773.15 K, and 823.15 K (400 °C, 450 °C, 500 °C, and 550 °C)]. Nano- and macro-scale wear properties are studied in the case-hardened surfaces, using a combination of nano-scratch and pin-on-disk experiments. The measured wear volumes (at both nano- and macro-length scales) are shown to increase with decreasing pack cyaniding temperature. The nano- and macro-wear resistances are also shown to be enhanced by the in situ diffusion of carbon and nitrogen from cyanide-containing bio-processed waste. The underlying wear mechanisms are also elucidated via atomic force microscopy and scanning electron microscopy observations of the wear tracks. The implications of the results are discussed for the design of hardened carbo-nitrided steel surfaces with improved wear resistance.

Micro and Macro Segregation in Alloys Solidifying with Equiaxed Morphology

Science.gov (United States)

Stefanescu, Doru M.; Curreri, Peter A.; Leon-Torres, Jose; Sen, Subhayu

1996-01-01

To understand macro segregation formation in Al-Cu alloys, experiments were run under terrestrial gravity (1g) and under low gravity during parabolic flights (10(exp -2) g). Alloys of two different compositions (2% and 5% Cu) were solidified at two different cooling rates. Systematic microscopic and SEM observations produced microstructural and segregation maps for all samples. These maps may be used as benchmark experiments for validation of microstructure evolution and segregation models. As expected, the macro segregation maps are very complex. When segregation was measured along the central axis of the sample, the highest macro segregation for samples solidified at 1g was obtained for the lowest cooling rate. This behavior is attributed to the longer time available for natural convection and shrinkage flow to affect solute redistribution. In samples solidified under low-g, the highest macro-segregation was obtained at the highest cooling rate. In general, low-gravity solidification resulted in less segregation. To explain the experimental findings, an analytical (Flemings-Nereo) and a numerical model were used. For the numerical model, the continuum formulation was employed to describe the macroscopic transports of mass, energy, and momentum, associated with the microscopic transport phenomena, for a two-phase system. The model proposed considers that liquid flow is driven by thermal and solutal buoyancy, and by solidification shrinkage. The Flemings-Nereo model explains well macro segregation in the initial stages of low-gravity segregation. The numerical model can describe the complex macro segregation pattern and the differences between low- and high-gravity solidification.

Towards agile large-scale predictive modelling in drug discovery with flow-based programming design principles.

Science.gov (United States)

Lampa, Samuel; Alvarsson, Jonathan; Spjuth, Ola

2016-01-01

Predictive modelling in drug discovery is challenging to automate as it often contains multiple analysis steps and might involve cross-validation and parameter tuning that create complex dependencies between tasks. With large-scale data or when using computationally demanding modelling methods, e-infrastructures such as high-performance or cloud computing are required, adding to the existing challenges of fault-tolerant automation. Workflow management systems can aid in many of these challenges, but the currently available systems are lacking in the functionality needed to enable agile and flexible predictive modelling. We here present an approach inspired by elements of the flow-based programming paradigm, implemented as an extension of the Luigi system which we name SciLuigi. We also discuss the experiences from using the approach when modelling a large set of biochemical interactions using a shared computer cluster.Graphical abstract.

Improving catchment discharge predictions by inferring flow route contributions from a nested-scale monitoring and model setup

Science.gov (United States)

van der Velde, Y.; Rozemeijer, J. C.; de Rooij, G. H.; van Geer, F. C.; Torfs, P. J. J. F.; de Louw, P. G. B.

2011-03-01

Identifying effective measures to reduce nutrient loads of headwaters in lowland catchments requires a thorough understanding of flow routes of water and nutrients. In this paper we assess the value of nested-scale discharge and groundwater level measurements for the estimation of flow route volumes and for predictions of catchment discharge. In order to relate field-site measurements to the catchment-scale an upscaling approach is introduced that assumes that scale differences in flow route fluxes originate from differences in the relationship between groundwater storage and the spatial structure of the groundwater table. This relationship is characterized by the Groundwater Depth Distribution (GDD) curve that relates spatial variation in groundwater depths to the average groundwater depth. The GDD-curve was measured for a single field site (0.009 km2) and simple process descriptions were applied to relate groundwater levels to flow route discharges. This parsimonious model could accurately describe observed storage, tube drain discharge, overland flow and groundwater flow simultaneously with Nash-Sutcliff coefficients exceeding 0.8. A probabilistic Monte Carlo approach was applied to upscale field-site measurements to catchment scales by inferring scale-specific GDD-curves from the hydrographs of two nested catchments (0.4 and 6.5 km2). The estimated contribution of tube drain effluent (a dominant source for nitrates) decreased with increasing scale from 76-79% at the field-site to 34-61% and 25-50% for both catchment scales. These results were validated by demonstrating that a model conditioned on nested-scale measurements improves simulations of nitrate loads and predictions of extreme discharges during validation periods compared to a model that was conditioned on catchment discharge only.

Assessing allometric models to predict vegetative growth of mango (Mangifera indica; Anacardiaceae) at the current-year branch scale.

Science.gov (United States)

Normand, Frédéric; Lauri, Pierre-Éric

2012-03-01

Accurate and reliable predictive models are necessary to estimate nondestructively key variables for plant growth studies such as leaf area and leaf, stem, and total biomass. Predictive models are lacking at the current-year branch scale despite the importance of this scale in plant science. We calibrated allometric models to estimate leaf area and stem and branch (leaves + stem) mass of current-year branches, i.e., branches several months old studied at the end of the vegetative growth season, of four mango cultivars on the basis of their basal cross-sectional area. The effects of year, site, and cultivar were tested. Models were validated with independent data and prediction accuracy was evaluated with the appropriate statistics. Models revealed a positive allometry between dependent and independent variables, whose y-intercept but not the slope, was affected by the cultivar. The effects of year and site were negligible. For each branch characteristic, cultivar-specific models were more accurate than common models built with pooled data from the four cultivars. Prediction quality was satisfactory but with data dispersion around the models, particularly for large values. Leaf area and stem and branch mass of mango current-year branches could be satisfactorily estimated on the basis of branch basal cross-sectional area with cultivar-specific allometric models. The results suggested that, in addition to the heteroscedastic behavior of the variables studied, model accuracy was probably related to the functional plasticity of branches in relation to the light environment and/or to the number of growth units composing the branches.

Predictability and environmental drivers of chlorophyll fluctuations vary across different time scales and regions of the North Sea

Science.gov (United States)

Blauw, Anouk N.; Benincà, Elisa; Laane, Remi W. P. M.; Greenwood, Naomi; Huisman, Jef

2018-02-01

Phytoplankton concentrations display strong temporal variability at different time scales. Recent advances in automated moorings enable detailed investigation of this variability. In this study, we analyzed phytoplankton fluctuations at four automated mooring stations in the North Sea, which measured phytoplankton abundance (chlorophyll) and several environmental variables at a temporal resolution of 12-30 min for two to nine years. The stations differed in tidal range, water depth and freshwater influence. This allowed comparison of the predictability and environmental drivers of phytoplankton variability across different time scales and geographical regions. We analyzed the time series using wavelet analysis, cross correlations and generalized additive models to quantify the response of chlorophyll fluorescence to various environmental variables (tidal and meteorological variables, salinity, suspended particulate matter, nitrate and sea surface temperature). Hour-to-hour and day-to-day fluctuations in chlorophyll fluorescence were substantial, and mainly driven by sinking and vertical mixing of phytoplankton cells, horizontal transport of different water masses, and non-photochemical quenching of the fluorescence signal. At the macro-tidal stations, these short-term phytoplankton fluctuations were strongly driven by the tides. Along the Dutch coast, variation in salinity associated with the freshwater influence of the river Rhine played an important role, while in the central North Sea variation in weather conditions was a major determinant of phytoplankton variability. At time scales of weeks to months, solar irradiance, nutrient conditions and thermal stratification were the dominant drivers of changes in chlorophyll concentrations. These results show that the dominant drivers of phytoplankton fluctuations differ across marine environments and time scales. Moreover, our findings show that phytoplankton variability on hourly to daily time scales should not be

Predictive Mechanical Characterization of Macro-Molecular Material Chemistry Structures of Cement Paste at Nano Scale - Two-phase Macro-Molecular Structures of Calcium Silicate Hydrate, Tri-Calcium Silicate, Di-Calcium Silicate and Calcium Hydroxide

Science.gov (United States)

Padilla Espinosa, Ingrid Marcela

Concrete is a hierarchical composite material with a random structure over a wide range of length scales. At submicron length scale the main component of concrete is cement paste, formed by the reaction of Portland cement clinkers and water. Cement paste acts as a binding matrix for the other components and is responsible for the strength of concrete. Cement paste microstructure contains voids, hydrated and unhydrated cement phases. The main crystalline phases of unhydrated cement are tri-calcium silicate (C3S) and di-calcium silicate (C2S), and of hydrated cement are calcium silicate hydrate (CSH) and calcium hydroxide (CH). Although efforts have been made to comprehend the chemical and physical nature of cement paste, studies at molecular level have primarily been focused on individual components. Present research focuses on the development of a method to model, at molecular level, and analysis of the two-phase combination of hydrated and unhydrated phases of cement paste as macromolecular systems. Computational molecular modeling could help in understanding the influence of the phase interactions on the material properties, and mechanical performance of cement paste. Present work also strives to create a framework for molecular level models suitable for potential better comparisons with low length scale experimental methods, in which the sizes of the samples involve the mixture of different hydrated and unhydrated crystalline phases of cement paste. Two approaches based on two-phase cement paste macromolecular structures, one involving admixed molecular phases, and the second involving cluster of two molecular phases are investigated. The mechanical properties of two-phase macromolecular systems of cement paste consisting of key hydrated phase CSH and unhydrated phases C3S or C2S, as well as CSH with the second hydrated phase CH were calculated. It was found that these cement paste two-phase macromolecular systems predicted an isotropic material behavior. Also

A micro-macro constitutive model for finite-deformation viscoelasticity of elastomers with nonlinear viscosity

Science.gov (United States)

Zhou, Jianyou; Jiang, Liying; Khayat, Roger E.

2018-01-01

Elastomers are known to exhibit viscoelastic behavior under deformation, which is linked to the diffusion processes of the highly mobile and flexible polymer chains. Inspired by the theories of polymer dynamics, a micro-macro constitutive model is developed to study the viscoelastic behaviors and the relaxation process of elastomeric materials under large deformation, in which the material parameters all have a microscopic foundation or a microstructural justification. The proposed model incorporates the nonlinear material viscosity into the continuum finite-deformation viscoelasticity theories which represent the polymer networks of elastomers with an elastic ground network and a few viscous subnetworks. The developed modeling framework is capable of adopting most of strain energy density functions for hyperelastic materials and thermodynamics evolution laws of viscoelastic solids. The modeling capacity of the framework is outlined by comparing the simulation results with the experimental data of three commonly used elastomeric materials, namely, VHB4910, HNBR50 and carbon black (CB) filled elastomers. The comparison shows that the stress responses and some typical behaviors of filled and unfilled elastomers can be quantitatively predicted by the model with suitable strain energy density functions. Particularly, the strain-softening effect of elastomers could be explained by the deformation-dependent (nonlinear) viscosity of the polymer chains. The presented modeling framework is expected to be useful as a modeling platform for further study on the performance of different type of elastomeric materials.

Using Scaling to Understand, Model and Predict Global Scale Anthropogenic and Natural Climate Change

Science.gov (United States)

Lovejoy, S.; del Rio Amador, L.

2014-12-01

The atmosphere is variable over twenty orders of magnitude in time (≈10-3 to 1017 s) and almost all of the variance is in the spectral "background" which we show can be divided into five scaling regimes: weather, macroweather, climate, macroclimate and megaclimate. We illustrate this with instrumental and paleo data. Based the signs of the fluctuation exponent H, we argue that while the weather is "what you get" (H>0: fluctuations increasing with scale), that it is macroweather (Hdecreasing with scale) - not climate - "that you expect". The conventional framework that treats the background as close to white noise and focuses on quasi-periodic variability assumes a spectrum that is in error by a factor of a quadrillion (≈ 1015). Using this scaling framework, we can quantify the natural variability, distinguish it from anthropogenic variability, test various statistical hypotheses and make stochastic climate forecasts. For example, we estimate the probability that the warming is simply a giant century long natural fluctuation is less than 1%, most likely less than 0.1% and estimate return periods for natural warming events of different strengths and durations, including the slow down ("pause") in the warming since 1998. The return period for the pause was found to be 20-50 years i.e. not very unusual; however it immediately follows a 6 year "pre-pause" warming event of almost the same magnitude with a similar return period (30 - 40 years). To improve on these unconditional estimates, we can use scaling models to exploit the long range memory of the climate process to make accurate stochastic forecasts of the climate including the pause. We illustrate stochastic forecasts on monthly and annual scale series of global and northern hemisphere surface temperatures. We obtain forecast skill nearly as high as the theoretical (scaling) predictability limits allow: for example, using hindcasts we find that at 10 year forecast horizons we can still explain ≈ 15% of the

MacroBac: New Technologies for Robust and Efficient Large-Scale Production of Recombinant Multiprotein Complexes.

Science.gov (United States)

Gradia, Scott D; Ishida, Justin P; Tsai, Miaw-Sheue; Jeans, Chris; Tainer, John A; Fuss, Jill O

2017-01-01

Recombinant expression of large, multiprotein complexes is essential and often rate limiting for determining structural, biophysical, and biochemical properties of DNA repair, replication, transcription, and other key cellular processes. Baculovirus-infected insect cell expression systems are especially well suited for producing large, human proteins recombinantly, and multigene baculovirus systems have facilitated studies of multiprotein complexes. In this chapter, we describe a multigene baculovirus system called MacroBac that uses a Biobricks-type assembly method based on restriction and ligation (Series 11) or ligation-independent cloning (Series 438). MacroBac cloning and assembly is efficient and equally well suited for either single subcloning reactions or high-throughput cloning using 96-well plates and liquid handling robotics. MacroBac vectors are polypromoter with each gene flanked by a strong polyhedrin promoter and an SV40 poly(A) termination signal that minimize gene order expression level effects seen in many polycistronic assemblies. Large assemblies are robustly achievable, and we have successfully assembled as many as 10 genes into a single MacroBac vector. Importantly, we have observed significant increases in expression levels and quality of large, multiprotein complexes using a single, multigene, polypromoter virus rather than coinfection with multiple, single-gene viruses. Given the importance of characterizing functional complexes, we believe that MacroBac provides a critical enabling technology that may change the way that structural, biophysical, and biochemical research is done. © 2017 Elsevier Inc. All rights reserved.

Macro-Finance Determinants of the Long-Run Stock-Bond Correlation

DEFF Research Database (Denmark)

Asgharian, Hossein; Christiansen, Charlotte; Hou, Ai Jun

itself. Macro-finance variables and the lagged realized correlation are simultaneously significant in forecasting the long-run stock-bond correlation. The behavior of the long-run stock-bond correlation is very different when estimated taking the macro-finance variables into account. Supporting......We investigate the long-run stock-bond correlation using a novel model that combines the dynamic conditional correlation model with the mixed-data sampling approach. The long-run correlation is affected by both macro-finance variables (historical and forecasts) and the lagged realized correlation...

Analysis of the economic impact of large-scale deployment of biomass resources for energy and materials in the Netherlands : macro-economics biobased synthesis report

NARCIS (Netherlands)

Hoefnagels, R.; Dornburg, V.; Faaij, A.; Banse, M.A.H.

2011-01-01

The Bio-based Raw Materials Platform (PGG), part of the Energy Transition in The Netherlands, commissioned the Agricultural Economics Research Institute (LEI) and the Copernicus Institute of Utrecht University to conduct research on the macro-economic impact of large scale deployment of biomass for

Using a micro-level model to generate a macro-level model of productive successful aging.

Science.gov (United States)

Johnson, Jessica K M; Sarkisian, Natalia; Williamson, John B

2015-02-01

Aging successfully entails good physical and cognitive health, as well as ongoing participation in social and productive activity. This study hones in on participation in productive activity, a factor that makes an important contribution to successful aging. One conceptual model of productive activity in later life specifies the antecedents and consequences of productivity. This study draws on that micro-level model to develop a corresponding macro-level model and assesses its utility for examining the predictors of and explaining the relationships between one form of productivity (labor force participation rates) and one aspect of well-being (average life expectancy) among males and females. Random effects regression models and path analysis were used to analyze cross-national longitudinal data for 24 high-income Organization for Economic Co-operation and Development (OECD) countries at seven time points (1980-2010; 168 observations total). OECD countries with higher labor force participation rates among older workers have higher life expectancies. Labor force participation mediates the effects of gross domestic product per capita on male and female life expectancy, and it mediates the effect of self-employment rate for men, but it acts as a suppressor with regard to the effect of public spending on male and female life expectancy. A well-known micro-level model of productive activity can be fruitfully adapted to account for macro-level cross-national variation in productivity and well-being. © The Author 2014. Published by Oxford University Press on behalf of The Gerontological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Restricted gene flow at the micro- and macro-geographical scale in marble trout based on mtDNA and microsatellite polymorphism

Directory of Open Access Journals (Sweden)

Patarnello Tomaso

2011-04-01

Full Text Available Abstract Background The genetic structure of the marble trout Salmo trutta marmoratus, an endemic salmonid of northern Italy and the Balkan peninsula, was explored at the macro- and micro-scale level using a combination of mitochondrial DNA (mtDNA and microsatellite data. Results Sequence variation in the mitochondrial control region showed the presence of nonindigenous haplotypes indicative of introgression from brown trout into marble trout. This was confirmed using microsatellite markers, which showed a higher introgression at nuclear level. Microsatellite loci revealed a strong genetic differentiation across the geographical range of marble trout, which suggests restricted gene flow both at the micro-geographic (within rivers and macro-geographic (among river systems scale. A pattern of Isolation-by-Distance was found, in which genetic samples were correlated with hydrographic distances. A general West-to-East partition of the microsatellite polymorphism was observed, which was supported by the geographic distribution of mitochondrial haplotypes. Conclusion While introgression at both mitochondrial and nuclear level is unlikely to result from natural migration and might be the consequence of current restocking practices, the pattern of genetic substructuring found at microsatellites has been likely shaped by historical colonization patterns determined by the geological evolution of the hydrographic networks.

Construction of Modular Hydrogel Sheets for Micropatterned Macro-scaled 3D Cellular Architecture.

Science.gov (United States)

Son, Jaejung; Bae, Chae Yun; Park, Je-Kyun

2016-01-11

Hydrogels can be patterned at the micro-scale using microfluidic or micropatterning technologies to provide an in vivo-like three-dimensional (3D) tissue geometry. The resulting 3D hydrogel-based cellular constructs have been introduced as an alternative to animal experiments for advanced biological studies, pharmacological assays and organ transplant applications. Although hydrogel-based particles and fibers can be easily fabricated, it is difficult to manipulate them for tissue reconstruction. In this video, we describe a fabrication method for micropatterned alginate hydrogel sheets, together with their assembly to form a macro-scale 3D cell culture system with a controlled cellular microenvironment. Using a mist form of the calcium gelling agent, thin hydrogel sheets are easily generated with a thickness in the range of 100 - 200 µm, and with precise micropatterns. Cells can then be cultured with the geometric guidance of the hydrogel sheets in freestanding conditions. Furthermore, the hydrogel sheets can be readily manipulated using a micropipette with an end-cut tip, and can be assembled into multi-layered structures by stacking them using a patterned polydimethylsiloxane (PDMS) frame. These modular hydrogel sheets, which can be fabricated using a facile process, have potential applications of in vitro drug assays and biological studies, including functional studies of micro- and macrostructure and tissue reconstruction.

Complex fluids with mobile charge-regulating macro-ions

Science.gov (United States)

Markovich, Tomer; Andelman, David; Podgornik, Rudi

2017-10-01

We generalize the concept of charge regulation of ionic solutions, and apply it to complex fluids with mobile macro-ions having internal non-electrostatic degrees of freedom. The suggested framework provides a convenient tool for investigating systems where mobile macro-ions can self-regulate their charge (e.g., proteins). We show that even within a simplified charge-regulation model, the charge dissociation equilibrium results in different and notable properties. Consequences of the charge regulation include a positional dependence of the effective charge of the macro-ions, a non-monotonic dependence of the effective Debye screening length on the concentration of the monovalent salt, a modification of the electric double-layer structure, and buffering by the macro-ions of the background electrolyte.

Improving catchment discharge predictions by inferring flow route contributions from a nested-scale monitoring and model setup

Directory of Open Access Journals (Sweden)

Y. van der Velde

2011-03-01

Full Text Available Identifying effective measures to reduce nutrient loads of headwaters in lowland catchments requires a thorough understanding of flow routes of water and nutrients. In this paper we assess the value of nested-scale discharge and groundwater level measurements for the estimation of flow route volumes and for predictions of catchment discharge. In order to relate field-site measurements to the catchment-scale an upscaling approach is introduced that assumes that scale differences in flow route fluxes originate from differences in the relationship between groundwater storage and the spatial structure of the groundwater table. This relationship is characterized by the Groundwater Depth Distribution (GDD curve that relates spatial variation in groundwater depths to the average groundwater depth. The GDD-curve was measured for a single field site (0.009 km² and simple process descriptions were applied to relate groundwater levels to flow route discharges. This parsimonious model could accurately describe observed storage, tube drain discharge, overland flow and groundwater flow simultaneously with Nash-Sutcliff coefficients exceeding 0.8. A probabilistic Monte Carlo approach was applied to upscale field-site measurements to catchment scales by inferring scale-specific GDD-curves from the hydrographs of two nested catchments (0.4 and 6.5 km². The estimated contribution of tube drain effluent (a dominant source for nitrates decreased with increasing scale from 76–79% at the field-site to 34–61% and 25–50% for both catchment scales. These results were validated by demonstrating that a model conditioned on nested-scale measurements improves simulations of nitrate loads and predictions of extreme discharges during validation periods compared to a model that was conditioned on catchment discharge only.

Measurement of the decoherence function with the MACRO detector at Gran Sasso

International Nuclear Information System (INIS)

Ahlen, S.; Ambrosio, M.; Antolini, R.; Auriemma, G.; Baldini, A.; Barbarino, G.C.; Barish, B.C.; Battistoni, G.; Bellotti, R.; Bemporad, C.; Bernardini, P.; Bilokon, H.; Bisi, V.; Bloise, C.; Bussino, S.; Cafagna, F.; Calicchio, M.; Campana, D.; Campana, P.; Carboni, M.; Cecchini, S.; Cei, F.; Chiarella, V.; Chiera, C.; Cobis, A.; Cormack, R.; Corona, A.; Coutu, S.; DeCataldo, G.; Dekhussi, H.; DeMarzo, C.; De Vincenzi, M.; Di Credico, A.; Diehl, E.; Erriquez, O.; Favuzzi, C.; Ficenec, D.; Forti, C.; Foti, L.; Fusco, P.; Giacomelli, G.; Giannini, G.; Giglietto, N.; Giubellino, P.; Grassi, M.; Green, P.; Grillo, A.; Guarino, F.; Gustavino, C.; Habig, A.; Heinz, R.; Hong, J.T.; Iarocci, E.; Katsavounidis, E.; Kearns, E.; Klein, S.; Kyriazopoulou, S.; Lamanna, E.; Lane, C.; Lee, C.; Levin, D.S.; Lipari, P.; Liu, G.; Liu, R.; Longo, M.J.; Ludlam, G.; Mancarella, G.; Mandrioli, G.; Margiotta-Neri, A.; Marin, A.; Marini, A.; Martello, D.; Marzari Chiesa, A.; Masera, M.; Matteuzzi, P.; Michael, D.G.; Miller, L.; Monacelli, P.; Monteno, M.; Mufson, S.; Musser, J.; Nutter, S.; Okada, C.; Osteria, G.; Palamara, O.; Parlati, S.; Patera, V.; Patrizii, L.; Pazzi, R.; Peck, C.W.; Petrakis, J.; Petrera, S.; Pignatano, N.D.; Pistilli, P.; Predieri, F.; Ramello, L.; Reynoldson, J.; Ronga, F.; Rosa, G.; Satriano, C.; Satta, L.; Scapparone, E.; Scholberg, K.; Sciubba, A.; Serra Lugaresi, P.; Severi, M.; Sitta, M.; Spinelli, P.; Spinetti, M.; Spurio, M.; Steele, J.; Steinberg, R.; Stone, J.L.; Sulak, L.R.; Surdo, A.; Tarle, G.; Togo, V.; Valente, V.; Walter, C.W.; Webb, R.; Worstell, W.

1992-01-01

A measurement of the underground muon decoherence function has been performed using the multiple muon events collected by the MACRO detector at the Gran Sasso National Laboratory. A detector-independent analysis is presented for different zenith regions and rock depths; this allows direct comparison with any model of hadronic interactions. The measured decoherence function is compared with the predictions of a Monte Carlo simulation based on data taken by recent collider experiments

Macro-economic factors influencing the architectural business model shift in the pharmaceutical industry.

Science.gov (United States)

Dierks, Raphaela Marie Louisa; Bruyère, Olivier; Reginster, Jean-Yves; Richy, Florent-Frederic

2016-10-01

Technological innovations, new regulations, increasing costs of drug productions and new demands are only few key drivers of a projected alternation in the pharmaceutical industry. The purpose of this review is to understand the macro economic factors responsible for the business model revolution to possess a competitive advantage over market players. Areas covered: Existing literature on macro-economic factors changing the pharmaceutical landscape has been reviewed to present a clear image of the current market environment. Expert commentary: Literature shows that pharmaceutical companies are facing an architectural alteration, however the evidence on the rationale driving the transformation is outstanding. Merger & Acquisitions (M&A) deals and collaborations are headlining the papers. Q1 2016 did show a major slowdown in M&A deals by volume since 2013 (with deal cancellations of Pfizer and Allergan, or the downfall of Valeant), but pharmaceutical analysts remain confident that this shortfall was a consequence of the equity market volatility. It seems likely that the shift to an M&A model will become apparent during the remainder of 2016, with deal announcements of Abbott Laboratories, AbbVie and Sanofi worth USD 45billion showing the appetite of big pharma companies to shift from the fully vertical integrated business model to more horizontal business models.

Macro-Finance Determinants of the Long-Run Stock-Bond Correlation

DEFF Research Database (Denmark)

Asgharian, Hossein; Christiansen, Charlotte; Hou, Ai Jun

2016-01-01

We investigate long-run stock–bond correlation using a model that combines the dynamic conditional correlation model with the mixed-data sampling approach and allows long-run correlation to be affected by macro-finance factors (historical and forecasts). We use macro-finance factors related...... to inflation and interest rates, illiquidity, state of the economy, and market uncertainty. Macro-finance factors, particularly their forecasts, are good at forecasting long-run stock–bond correlation. Supporting the flight-to-quality phenomenon, long-run correlation tends to be small and negative when...

Pathways for scale and discipline reconciliation: current socio-ecological modelling methodologies to explore and reconstitute human prehistoric dynamics

OpenAIRE

Saqalli , Mehdi; Baum , Tilman

2016-01-01

International audience; This communication elaborates a plea for the necessity of a specific modelling methodology which does not sacrifice two modelling principles: explanation Micro and correlation Macro. Three goals are assigned to modelling strategies: describe, understand and predict. One tendency in historical and spatial modelling is to develop models at a micro level in order to describe and by that way, understand the connection between local ecological contexts, acquired through loc...

'Time is costly': modelling the macroeconomic impact of scaling-up antiretroviral treatment in sub-Saharan Africa.

Science.gov (United States)

Ventelou, Bruno; Moatti, Jean-Paul; Videau, Yann; Kazatchkine, Michel

2008-01-02

Macroeconomic policy requirements may limit the capacity of national and international policy-makers to allocate sufficient resources for scaling-up access to HIV care and treatment in developing countries. An endogenous growth model, which takes into account the evolution of society's human capital, was used to assess the macroeconomic impact of policies aimed at scaling-up access to HIV/AIDS treatment in six African countries (Angola, Benin, Cameroon, Central African Republic, Ivory Coast and Zimbabwe). The model results showed that scaling-up access to treatment in the affected population would limit gross domestic product losses due to AIDS although differently from country to country. In our simulated scenarios of access to antiretroviral therapy, only 10.3% of the AIDS shock is counterbalanced in Zimbabwe, against 85.2% in Angola and even 100.0% in Benin (a total recovery). For four out of the six countries (Angola, Benin, Cameroon, Ivory Coast), the macro-economic gains of scaling-up would become potentially superior to its associated costs in 2010. Despite the variability of HIV prevalence rates between countries, macro-economic estimates strongly suggest that a massive investment in scaling-up access to HIV treatment may efficiently counteract the detrimental long-term impact of the HIV pandemic on economic growth, to the extent that the AIDS shock has not already driven the economy beyond an irreversible 'no-development epidemiological trap'.

Nonpointlike-parton model with asymptotic scaling and with scaling violationat moderate Q2 values

International Nuclear Information System (INIS)

Chen, C.K.

1981-01-01

A nonpointlike-parton model is formulated on the basis of the assumption of energy-independent total cross sections of partons and the current-algebra sum rules. No specific strong-interaction Lagrangian density is introduced in this approach. This model predicts asymptotic scaling for the inelastic structure functions of nucleons on the one hand and scaling violation at moderate Q 2 values on the other hand. The predicted scaling-violation patterns at moderate Q 2 values are consistent with the observed scaling-violation patterns. A numerical fit of F 2 functions is performed in order to demonstrate that the predicted scaling-violation patterns of this model at moderate Q 2 values fit the data, and to see how the predicted asymptotic scaling behavior sets in at various x values. Explicit analytic forms of F 2 functions are obtained from this numerical fit, and are compared in detail with the analytic forms of F 2 functions obtained from the numerical fit of the quantum-chromodynamics (QCD) parton model. This comparison shows that this nonpointlike-parton model fits the data better than the QCD parton model, especially at large and small x values. Nachtman moments are computed from the F 2 functions of this model and are shown to agree with data well. It is also shown that the two-dimensional plot of the logarithm of a nonsinglet moment versus the logarithm of another such moment is not a good way to distinguish this nonpointlike-parton model from the QCD parton model

Measuring Impact of Uncertainty in a Stylized Macro-Economic Climate Model within a Dynamic Game Perspective

NARCIS (Netherlands)

Stienen, V.F.; Engwerda, Jacob

2018-01-01

In this paper we try to quantify/measure the main factors that influence the equilibrium outcome and pursued strategies in a simplistic model for the use of fossil versus green energy over time. The model is derived using the standard Solow macro-economic growth model in a two-country setting within

Improving Wind Farm Dispatchability Using Model Predictive Control for Optimal Operation of Grid-Scale Energy Storage

Directory of Open Access Journals (Sweden)

Douglas Halamay

2014-09-01

Full Text Available This paper demonstrates the use of model-based predictive control for energy storage systems to improve the dispatchability of wind power plants. Large-scale wind penetration increases the variability of power flow on the grid, thus increasing reserve requirements. Large energy storage systems collocated with wind farms can improve dispatchability of the wind plant by storing energy during generation over-the-schedule and sourcing energy during generation under-the-schedule, essentially providing on-site reserves. Model predictive control (MPC provides a natural framework for this application. By utilizing an accurate energy storage system model, control actions can be planned in the context of system power and state-of-charge limitations. MPC also enables the inclusion of predicted wind farm performance over a near-term horizon that allows control actions to be planned in anticipation of fast changes, such as wind ramps. This paper demonstrates that model-based predictive control can improve system performance compared with a standard non-predictive, non-model-based control approach. It is also demonstrated that secondary objectives, such as reducing the rate of change of the wind plant output (i.e., ramps, can be considered and successfully implemented within the MPC framework. Specifically, it is shown that scheduling error can be reduced by 81%, reserve requirements can be improved by up to 37%, and the number of ramp events can be reduced by 74%.

Biofilm Formation Mechanisms of Pseudomonas aeruginosa Predicted via Genome-Scale Kinetic Models of Bacterial Metabolism

Science.gov (United States)

2016-03-15

RESEARCH ARTICLE Biofilm Formation Mechanisms of Pseudomonas aeruginosa Predicted via Genome-Scale Kinetic Models of Bacterial Metabolism Francisco G...jaques.reifman.civ@mail.mil Abstract A hallmark of Pseudomonas aeruginosa is its ability to establish biofilm -based infections that are difficult to...eradicate. Biofilms are less susceptible to host inflammatory and immune responses and have higher antibiotic tolerance than free-living planktonic

Comparison of the Berg Balance Scale and Fullerton Advanced Balance Scale to predict falls in community-dwelling adults.

Science.gov (United States)

Jeon, Yong-Jin; Kim, Gyoung-Mo

2017-02-01

[Purpose] The purpose of this study was to investigate and compare the predictive properties of Berg Balance Scale and Fullerton Advanced Balance Scales, in a group of independently-functioning community dwelling older adults. [Subjects and Methods] Ninety-seven community-dwelling older adults (male=39, female=58) who were capable of walking independently on assessment were included in this study. A binary logistic regression analysis of the Berg Balance Scale and Fullerton Advanced Balance Scale scores was used to investigate a predictive model for fall risk. A receiver operating characteristic analysis was conducted for each, to determine the cut-off for optimal levels of sensitivity and specificity. [Results] The overall prediction success rate was 89.7%; the total Berg Balance Scale and Fullerton Advanced Balance Scale scores were significant in predicting fall risk. Receiver operating characteristic analysis determined that a cut-off score of 40 out of 56 on the Berg Balance Scale produced the highest sensitivity (0.82) and specificity (0.67), and a cut-off score of 22 out of 40 on the Fullerton Advanced Balance Scale produced the highest sensitivity (0.85) and specificity (0.65) in predicting faller status. [Conclusion] The Berg Balance Scale and Fullerton Advanced Balance Scales can predict fall risk, when used for independently-functioning community-dwelling older adults.

An Introduction to Macro- Level Spatial Nonstationarity: a Geographically Weighted Regression Analysis of Diabetes and Poverty.

Science.gov (United States)

Siordia, Carlos; Saenz, Joseph; Tom, Sarah E

2012-01-01

Type II diabetes is a growing health problem in the United States. Understanding geographic variation in diabetes prevalence will inform where resources for management and prevention should be allocated. Investigations of the correlates of diabetes prevalence have largely ignored how spatial nonstationarity might play a role in the macro-level distribution of diabetes. This paper introduces the reader to the concept of spatial nonstationarity-variance in statistical relationships as a function of geographical location. Since spatial nonstationarity means different predictors can have varying effects on model outcomes, we make use of a geographically weighed regression to calculate correlates of diabetes as a function of geographic location. By doing so, we demonstrate an exploratory example in which the diabetes-poverty macro-level statistical relationship varies as a function of location. In particular, we provide evidence that when predicting macro-level diabetes prevalence, poverty is not always positively associated with diabetes.

Development of a long term macro econometric model for strategic analysis and cost assessments in nuclear R and D fields

International Nuclear Information System (INIS)

Mankin, Shuichi; Yamazaki, Shigeki.

1985-11-01

A Long Term Macro Econometric Model (LTMEMO) has been developed for the purpose of generating economic scenarios for strategic analysis and for cost assessments of technologies in the field of nuclear research and development. The program system of the model is composed of such sub-programs as related social and economic statistic data base and its treatment program, identification and estimation programs of various econometric functions, simulation programs for future projections, and a reference econometric model program. The reference econometric model in the program system would be improved and modified easily by using data base and other sub-programs as the purpose of data retrieval, application of economic hypothesis, and scenario generation. The reference model belongs to a category of such standard types as macro-econometric, deterministic, and descriptive one, however, it was deviated based on the combination of Keynesian theories and Neo-classical theories and was modified by system engineering aspects. The model obtained good performances in such various econometric tests as statistical examinations in parameter estimation of each functions and so called partial tests, total tests, and final tests. Macro economic scenarios α and β, long term projections through 2030 of macro economy in our country were evaluated appropriately by this model. This report describes the process in the development of the model from needs of econometric model in nuclear fields to examples of economic scenarios generated by this model. Some consideration are taken into descriptions on the deviation of each functions and on the application of economic theories for practical use of this program system at the time of modification and improvements of the reference model. (author)

Parser Macros for Scala

OpenAIRE

Duhem, Martin; Burmako, Eugene

2015-01-01

Parser macros are a new kind of macros that allow developers to create new language constructs and to define their own syntax for using them. In this report, we present why parser macros are useful and the kind of problems that they help to solve. We will also see how they are implemented and gain insight about how they take advantage from scala.meta, the new metaprogramming toolkit for Scala. Finally, we will discuss what are the current limitations of parser macros and what is left for futu...

Scale problems in assessment of hydrogeological parameters of groundwater flow models

Science.gov (United States)

Nawalany, Marek; Sinicyn, Grzegorz

2015-09-01

An overview is presented of scale problems in groundwater flow, with emphasis on upscaling of hydraulic conductivity, being a brief summary of the conventional upscaling approach with some attention paid to recently emerged approaches. The focus is on essential aspects which may be an advantage in comparison to the occasionally extremely extensive summaries presented in the literature. In the present paper the concept of scale is introduced as an indispensable part of system analysis applied to hydrogeology. The concept is illustrated with a simple hydrogeological system for which definitions of four major ingredients of scale are presented: (i) spatial extent and geometry of hydrogeological system, (ii) spatial continuity and granularity of both natural and man-made objects within the system, (iii) duration of the system and (iv) continuity/granularity of natural and man-related variables of groundwater flow system. Scales used in hydrogeology are categorised into five classes: micro-scale - scale of pores, meso-scale - scale of laboratory sample, macro-scale - scale of typical blocks in numerical models of groundwater flow, local-scale - scale of an aquifer/aquitard and regional-scale - scale of series of aquifers and aquitards. Variables, parameters and groundwater flow equations for the three lowest scales, i.e., pore-scale, sample-scale and (numerical) block-scale, are discussed in detail, with the aim to justify physically deterministic procedures of upscaling from finer to coarser scales (stochastic issues of upscaling are not discussed here). Since the procedure of transition from sample-scale to block-scale is physically well based, it is a good candidate for upscaling block-scale models to local-scale models and likewise for upscaling local-scale models to regional-scale models. Also the latest results in downscaling from block-scale to sample scale are briefly referred to.

Scale problems in assessment of hydrogeological parameters of groundwater flow models

Directory of Open Access Journals (Sweden)

Nawalany Marek

2015-09-01

Full Text Available An overview is presented of scale problems in groundwater flow, with emphasis on upscaling of hydraulic conductivity, being a brief summary of the conventional upscaling approach with some attention paid to recently emerged approaches. The focus is on essential aspects which may be an advantage in comparison to the occasionally extremely extensive summaries presented in the literature. In the present paper the concept of scale is introduced as an indispensable part of system analysis applied to hydrogeology. The concept is illustrated with a simple hydrogeological system for which definitions of four major ingredients of scale are presented: (i spatial extent and geometry of hydrogeological system, (ii spatial continuity and granularity of both natural and man-made objects within the system, (iii duration of the system and (iv continuity/granularity of natural and man-related variables of groundwater flow system. Scales used in hydrogeology are categorised into five classes: micro-scale – scale of pores, meso-scale – scale of laboratory sample, macro-scale – scale of typical blocks in numerical models of groundwater flow, local-scale – scale of an aquifer/aquitard and regional-scale – scale of series of aquifers and aquitards. Variables, parameters and groundwater flow equations for the three lowest scales, i.e., pore-scale, sample-scale and (numerical block-scale, are discussed in detail, with the aim to justify physically deterministic procedures of upscaling from finer to coarser scales (stochastic issues of upscaling are not discussed here. Since the procedure of transition from sample-scale to block-scale is physically well based, it is a good candidate for upscaling block-scale models to local-scale models and likewise for upscaling local-scale models to regional-scale models. Also the latest results in downscaling from block-scale to sample scale are briefly referred to.

Large-scale linear programs in planning and prediction.

Science.gov (United States)

2017-06-01

Large-scale linear programs are at the core of many traffic-related optimization problems in both planning and prediction. Moreover, many of these involve significant uncertainty, and hence are modeled using either chance constraints, or robust optim...

Integrating SMOS brightness temperatures with a new conceptual spatially distributed hydrological model for improving flood and drought predictions at large scale.

Science.gov (United States)

Hostache, Renaud; Rains, Dominik; Chini, Marco; Lievens, Hans; Verhoest, Niko E. C.; Matgen, Patrick

2017-04-01

Motivated by climate change and its impact on the scarcity or excess of water in many parts of the world, several agencies and research institutions have taken initiatives in monitoring and predicting the hydrologic cycle at a global scale. Such a monitoring/prediction effort is important for understanding the vulnerability to extreme hydrological events and for providing early warnings. This can be based on an optimal combination of hydro-meteorological models and remote sensing, in which satellite measurements can be used as forcing or calibration data or for regularly updating the model states or parameters. Many advances have been made in these domains and the near future will bring new opportunities with respect to remote sensing as a result of the increasing number of spaceborn sensors enabling the large scale monitoring of water resources. Besides of these advances, there is currently a tendency to refine and further complicate physically-based hydrologic models to better capture the hydrologic processes at hand. However, this may not necessarily be beneficial for large-scale hydrology, as computational efforts are therefore increasing significantly. As a matter of fact, a novel thematic science question that is to be investigated is whether a flexible conceptual model can match the performance of a complex physically-based model for hydrologic simulations at large scale. In this context, the main objective of this study is to investigate how innovative techniques that allow for the estimation of soil moisture from satellite data can help in reducing errors and uncertainties in large scale conceptual hydro-meteorological modelling. A spatially distributed conceptual hydrologic model has been set up based on recent developments of the SUPERFLEX modelling framework. As it requires limited computational efforts, this model enables early warnings for large areas. Using as forcings the ERA-Interim public dataset and coupled with the CMEM radiative transfer model

Model Development to Predict Phenological scale of Table Grapes (cvs. Thompson, Crimson and Superior Seedless and Red Globe using Growing Degree Days

Directory of Open Access Journals (Sweden)

Nicolas Verdugo-Vásquez

2017-09-01

Full Text Available Phenological models have been made mainly for winegrape cultivars, despite the economic importance of table grapes. The aim of this work was to develop and validate models for predicting phenological scales of table grapes (cvs. Thompson, Crimson and Superior Seedless and Red Globe grown under semi-arid conditions. Measurements of phenology were carried out weekly from budburst to harvest during four growing seasons (2009-2013. Phenology models were developed using the Mitscherlich monomolecular equation where the dependent and independent variables were the Eichhorn and Lorenz phenological (ELP scale modified by Coombe and the growing degree days (GDD, respectively. Results indicated that there were strong non-linear correlations between the ELP scale and GDD for the four cultivars with coefficient of determinations (R2 ranging between 0.97-0.99. Also, validation indicated that the models were able to predict ELP scale with a root mean square (RMSE and mean absolute error (MAE ranging between 2.1-2.4 and 1.35-1.69, respectively. The prediction variability (expressed in days was between 4.4-19.4 days, obtaining the best results for the flowering period. This study suggested that the phenological models based on GDD could be useful planning tools for farming, especially from budburst to veraison of table grape cultivars.

Macro-economic impact of large-scale deployment of biomass resources for energy and materials on a national level—A combined approach for the Netherlands

International Nuclear Information System (INIS)

Hoefnagels, Ric; Banse, Martin; Dornburg, Veronika; Faaij, André

2013-01-01

Biomass is considered one of the most important options in the transition to a sustainable energy system with reduced greenhouse gas (GHG) emissions and increased security of enegry supply. In order to facilitate this transition with targeted policies and implementation strategies, it is of vital importance to understand the economic benefits, uncertainties and risks of this transition. This article presents a quantification of the economic impacts on value added, employment shares and the trade balance as well as required biomass and avoided primary energy and greenhouse gases related to large scale biomass deployment on a country level (the Netherlands) for different future scenarios to 2030. This is done by using the macro-economic computable general equilibrium (CGE) model LEITAP, capable of quantifying direct and indirect effects of a bio-based economy combined with a spread sheet tool to address underlying technological details. Although the combined approach has limitations, the results of the projections show that substitution of fossil energy carriers by biomass, could have positive economic effects, as well as reducing GHG emissions and fossil energy requirement. Key factors to achieve these targets are enhanced technological development and the import of sustainable biomass resources to the Netherlands. - Highlights: • We analyse large scale production of bioenergy and biochemicals in the Netherlands. • The scenarios include up to 30% substitution of fossil fuels by biomass in 2030. • Resulting in strong greenhouse gas savings and positive macro-economic effects. • Large amounts of imported biomass are required to meet the domestic demand. • This requires high rates of technological change and strict sustainability criteria

Drift-Scale THC Seepage Model

International Nuclear Information System (INIS)

C.R. Bryan

2005-01-01

The purpose of this report (REV04) is to document the thermal-hydrologic-chemical (THC) seepage model, which simulates the composition of waters that could potentially seep into emplacement drifts, and the composition of the gas phase. The THC seepage model is processed and abstracted for use in the total system performance assessment (TSPA) for the license application (LA). This report has been developed in accordance with ''Technical Work Plan for: Near-Field Environment and Transport: Coupled Processes (Mountain-Scale TH/THC/THM, Drift-Scale THC Seepage, and Post-Processing Analysis for THC Seepage) Report Integration'' (BSC 2005 [DIRS 172761]). The technical work plan (TWP) describes planning information pertaining to the technical scope, content, and management of this report. The plan for validation of the models documented in this report is given in Section 2.2.2, ''Model Validation for the DS THC Seepage Model,'' of the TWP. The TWP (Section 3.2.2) identifies Acceptance Criteria 1 to 4 for ''Quantity and Chemistry of Water Contacting Engineered Barriers and Waste Forms'' (NRC 2003 [DIRS 163274]) as being applicable to this report; however, in variance to the TWP, Acceptance Criterion 5 has also been determined to be applicable, and is addressed, along with the other Acceptance Criteria, in Section 4.2 of this report. Also, three FEPS not listed in the TWP (2.2.10.01.0A, 2.2.10.06.0A, and 2.2.11.02.0A) are partially addressed in this report, and have been added to the list of excluded FEPS in Table 6.1-2. This report has been developed in accordance with LP-SIII.10Q-BSC, ''Models''. This report documents the THC seepage model and a derivative used for validation, the Drift Scale Test (DST) THC submodel. The THC seepage model is a drift-scale process model for predicting the composition of gas and water that could enter waste emplacement drifts and the effects of mineral alteration on flow in rocks surrounding drifts. The DST THC submodel uses a drift-scale

Modeling of the inhomogeneity of grain refinement during combined metal forming process by finite element and cellular automata methods

Energy Technology Data Exchange (ETDEWEB)

Majta, Janusz; Madej, Łukasz; Svyetlichnyy, Dmytro S.; Perzyński, Konrad; Kwiecień, Marcin, E-mail: mkwiecie@agh.edu.pl; Muszka, Krzysztof

2016-08-01

The potential of discrete cellular automata technique to predict the grain refinement in wires produced using combined metal forming process is presented and discussed within the paper. The developed combined metal forming process can be treated as one of the Severe Plastic Deformation (SPD) techniques that consists of three different modes of deformation: asymmetric drawing with bending, namely accumulated angular drawing (AAD), wire drawing (WD) and wire flattening (WF). To accurately replicate complex stress state both at macro and micro scales during subsequent deformations two stage modeling approach was used. First, the Finite Element Method (FEM), implemented in commercial ABAQUS software, was applied to simulate entire combined forming process at the macro scale level. Then, based on FEM results, the Cellular Automata (CA) method was applied for simulation of grain refinement at the microstructure level. Data transferred between FEM and CA methods included set of files with strain tensor components obtained from selected integration points in the macro scale model. As a result of CA simulation, detailed information on microstructure evolution during severe plastic deformation conditions was obtained, namely: changes of shape and sizes of modeled representative volume with imposed microstructure, changes of the number of grains, subgrains and dislocation cells, development of grain boundaries angle distribution as well as changes in the pole figures. To evaluate CA model predictive capabilities, results of computer simulation were compared with scanning electron microscopy and electron back scattered diffraction images (SEM/EBSD) studies of samples after AAD+WD+WF process.

Evaluating Predictive Uncertainty of Hyporheic Exchange Modelling

Science.gov (United States)

Chow, R.; Bennett, J.; Dugge, J.; Wöhling, T.; Nowak, W.

2017-12-01

Hyporheic exchange is the interaction of water between rivers and groundwater, and is difficult to predict. One of the largest contributions to predictive uncertainty for hyporheic fluxes have been attributed to the representation of heterogeneous subsurface properties. This research aims to evaluate which aspect of the subsurface representation - the spatial distribution of hydrofacies or the model for local-scale (within-facies) heterogeneity - most influences the predictive uncertainty. Also, we seek to identify data types that help reduce this uncertainty best. For this investigation, we conduct a modelling study of the Steinlach River meander, in Southwest Germany. The Steinlach River meander is an experimental site established in 2010 to monitor hyporheic exchange at the meander scale. We use HydroGeoSphere, a fully integrated surface water-groundwater model, to model hyporheic exchange and to assess the predictive uncertainty of hyporheic exchange transit times (HETT). A highly parameterized complex model is built and treated as `virtual reality', which is in turn modelled with simpler subsurface parameterization schemes (Figure). Then, we conduct Monte-Carlo simulations with these models to estimate the predictive uncertainty. Results indicate that: Uncertainty in HETT is relatively small for early times and increases with transit times. Uncertainty from local-scale heterogeneity is negligible compared to uncertainty in the hydrofacies distribution. Introducing more data to a poor model structure may reduce predictive variance, but does not reduce predictive bias. Hydraulic head observations alone cannot constrain the uncertainty of HETT, however an estimate of hyporheic exchange flux proves to be more effective at reducing this uncertainty. Figure: Approach for evaluating predictive model uncertainty. A conceptual model is first developed from the field investigations. A complex model (`virtual reality') is then developed based on that conceptual model

Multi-scale enhancement of climate prediction over land by increasing the model sensitivity to vegetation variability in EC-Earth

Science.gov (United States)

Alessandri, Andrea; Catalano, Franco; De Felice, Matteo; Van Den Hurk, Bart; Doblas Reyes, Francisco; Boussetta, Souhail; Balsamo, Gianpaolo; Miller, Paul A.

2017-08-01

The EC-Earth earth system model has been recently developed to include the dynamics of vegetation. In its original formulation, vegetation variability is simply operated by the Leaf Area Index (LAI), which affects climate basically by changing the vegetation physiological resistance to evapotranspiration. This coupling has been found to have only a weak effect on the surface climate modeled by EC-Earth. In reality, the effective sub-grid vegetation fractional coverage will vary seasonally and at interannual time-scales in response to leaf-canopy growth, phenology and senescence. Therefore it affects biophysical parameters such as the albedo, surface roughness and soil field capacity. To adequately represent this effect in EC-Earth, we included an exponential dependence of the vegetation cover on the LAI. By comparing two sets of simulations performed with and without the new variable fractional-coverage parameterization, spanning from centennial (twentieth century) simulations and retrospective predictions to the decadal (5-years), seasonal and weather time-scales, we show for the first time a significant multi-scale enhancement of vegetation impacts in climate simulation and prediction over land. Particularly large effects at multiple time scales are shown over boreal winter middle-to-high latitudes over Canada, West US, Eastern Europe, Russia and eastern Siberia due to the implemented time-varying shadowing effect by tree-vegetation on snow surfaces. Over Northern Hemisphere boreal forest regions the improved representation of vegetation cover tends to correct the winter warm biases, improves the climate change sensitivity, the decadal potential predictability as well as the skill of forecasts at seasonal and weather time-scales. Significant improvements of the prediction of 2 m temperature and rainfall are also shown over transitional land surface hot spots. Both the potential predictability at decadal time-scale and seasonal-forecasts skill are enhanced over

Macro-prudential policy on liquidity: What does a DSGE model tell us?

OpenAIRE

Chadha, Jagjit S.; Corrado, Luisa

2011-01-01

The financial crisis has led to the development of an active debate on the use of macro-prudential instruments for regulating the banking system, in particular for liquidity and capital holdings. Within the context of a micro-founded macroeconomic model, we allow commercial banks to choose their optimal mix of assets, apportioning these either to reserves or private sector loans. We examine the implications for quantities, relative non-financial and financial prices from standard macroeconomi...

Scaling laws for modeling nuclear reactor systems

International Nuclear Information System (INIS)

Nahavandi, A.N.; Castellana, F.S.; Moradkhanian, E.N.

1979-01-01

Scale models are used to predict the behavior of nuclear reactor systems during normal and abnormal operation as well as under accident conditions. Three types of scaling procedures are considered: time-reducing, time-preserving volumetric, and time-preserving idealized model/prototype. The necessary relations between the model and the full-scale unit are developed for each scaling type. Based on these relationships, it is shown that scaling procedures can lead to distortion in certain areas that are discussed. It is advised that, depending on the specific unit to be scaled, a suitable procedure be chosen to minimize model-prototype distortion

Advanced Macro-Model with Pulse-Width Dependent Switching Characteristic for Spin Transfer Torque Based Magnetic-Tunnel-Junction Elements

Science.gov (United States)

Sojeong Kim,; Seungjun Lee,; Hyungsoon Shin,

2010-04-01

In spin transfer torque (STT)-based magnetic tunnel junction (MTJ), the switching depends on the current pulse-width as well as the magnitude of the switching current. We present an advanced macro-model of an STT-MTJ for a circuit simulator such as HSPICE. The macro-model can simulate the dependence of switching behavior on current pulse-width in an STT-MTJ. An imaginary resistor-capacitor (RC) circuit is adopted to emulate complex timing behavior which cannot be described nicely by existing functions in HSPICE. Simulation results show the resistance-current (R-I) curve and timing behavior is in good agreement with the experimental data.

Scaling prediction errors to reward variability benefits error-driven learning in humans.

Science.gov (United States)

Diederen, Kelly M J; Schultz, Wolfram

2015-09-01

Effective error-driven learning requires individuals to adapt learning to environmental reward variability. The adaptive mechanism may involve decays in learning rate across subsequent trials, as shown previously, and rescaling of reward prediction errors. The present study investigated the influence of prediction error scaling and, in particular, the consequences for learning performance. Participants explicitly predicted reward magnitudes that were drawn from different probability distributions with specific standard deviations. By fitting the data with reinforcement learning models, we found scaling of prediction errors, in addition to the learning rate decay shown previously. Importantly, the prediction error scaling was closely related to learning performance, defined as accuracy in predicting the mean of reward distributions, across individual participants. In addition, participants who scaled prediction errors relative to standard deviation also presented with more similar performance for different standard deviations, indicating that increases in standard deviation did not substantially decrease "adapters'" accuracy in predicting the means of reward distributions. However, exaggerated scaling beyond the standard deviation resulted in impaired performance. Thus efficient adaptation makes learning more robust to changing variability. Copyright © 2015 the American Physiological Society.

Unified Modeling Language description of the object-oriented multi-scale adaptive finite element method for Step-and-Flash Imprint Lithography Simulations

International Nuclear Information System (INIS)

Paszynski, Maciej; Gurgul, Piotr; Sieniek, Marcin; Pardo, David

2010-01-01

In the first part of the paper we present the multi-scale simulation of the Step-and-Flash Imprint Lithography (SFIL), a modern patterning process. The simulation utilizes the hp adaptive Finite Element Method (hp-FEM) coupled with Molecular Statics (MS) model. Thus, we consider the multi-scale problem, with molecular statics applied in the areas of the mesh where the highest accuracy is required, and the continuous linear elasticity with thermal expansion coefficient applied in the remaining part of the domain. The degrees of freedom from macro-scale element's nodes located on the macro-scale side of the interface have been identified with particles from nano-scale elements located on the nano-scale side of the interface. In the second part of the paper we present Unified Modeling Language (UML) description of the resulting multi-scale application (hp-FEM coupled with MS). We investigated classical, procedural codes from the point of view of the object-oriented (O-O) programming paradigm. The discovered hierarchical structure of classes and algorithms makes the UML project as independent on the spatial dimension of the problem as possible. The O-O UML project was defined at an abstract level, independent on the programming language used.

Plant interactions alter the predictions of metabolic scaling theory

DEFF Research Database (Denmark)

Lin, Yue; Berger, Uta; Grimm, Volker

2013-01-01

Metabolic scaling theory (MST) is an attempt to link physiological processes of individual organisms with macroecology. It predicts a power law relationship with an exponent of 24/3 between mean individual biomass and density during densitydependent mortality (self-thinning). Empirical tests have...... processes can scale up to the population level. MST, like thermodynamics or biomechanics, sets limits within which organisms can live and function, but there may be stronger limits determined by ecological interactions. In such cases MST will not be predictive....... of plant stand development that includes three elements: a model of individual plant growth based on MST, different modes of local competition (size-symmetric vs. -asymmetric), and different resource levels. Our model is consistent with the observed variation in the slopes of self-thinning trajectories...

Prediction of microsegregation and pitting corrosion resistance of austenitic stainless steel welds by modelling

Energy Technology Data Exchange (ETDEWEB)

Vilpas, M. [VTT Manufacturing Technology, Espoo (Finland). Materials and Structural Integrity

1999-07-01

The present study focuses on the ability of several computer models to accurately predict the solidification, microsegregation and pitting corrosion resistance of austenitic stainless steel weld metals. Emphasis was given to modelling the effect of welding speed on solute redistribution and ultimately to the prediction of weld pitting corrosion resistance. Calculations were experimentally verified by applying autogenous GTA- and laser processes over the welding speed range of 0.1 to 5 m/min for several austenitic stainless steel grades. Analytical and computer aided models were applied and linked together for modelling the solidification behaviour of welds. The combined use of macroscopic and microscopic modelling is a unique feature of this work. This procedure made it possible to demonstrate the effect of weld pool shape and the resulting solidification parameters on microsegregation and pitting corrosion resistance. Microscopic models were also used separately to study the role of welding speed and solidification mode in the development of microsegregation and pitting corrosion resistance. These investigations demonstrate that the macroscopic model can be implemented to predict solidification parameters that agree well with experimentally measured values. The linked macro-micro modelling was also able to accurately predict segregation profiles and CPT-temperatures obtained from experiments. The macro-micro simulations clearly showed the major roles of weld composition and welding speed in determining segregation and pitting corrosion resistance while the effect of weld shape variations remained negligible. The microscopic dendrite tip and interdendritic models were applied to welds with good agreement with measured segregation profiles. Simulations predicted that weld inhomogeneity can be substantially decreased with increasing welding speed resulting in a corresponding improvement in the weld pitting corrosion resistance. In the case of primary austenitic

Stratification of the state of Santa Catarina in macro-environments for bean cultivation

Directory of Open Access Journals (Sweden)

Juliano Garcia Bertoldo

2009-01-01

Full Text Available The purpose of this study was to suggest a division of the State of Santa Catarina in macro-environments forexperimentation and bean production. Data of the traits grain yield and plant cycle were evaluated in 10 common beangenotypes grown in nine environments. The data were submitted to the Student-Newman Keuls test, to detect differencesbetween environments, and the Best Linear Unbiased Prediction, to predict the environmental values. The results showed: (adifferences between the regions of Santa Catarina for the traits grain yield and plant cycle, which had a significant positivecorrelation of 0.26 (b Based on the genotypes and environments studied the state can be divided in two macro-environments(MA1 and MA2 and four micro-environments (MI1, MI2, MI3 and MI4. The state of Santa Catarina may be roughly dividedin at least two macro-environments for the recommendation of new cultivars.

Multi-scale approach for predicting fish species distributions across coral reef seascapes.

Directory of Open Access Journals (Sweden)

Simon J Pittman

Full Text Available Two of the major limitations to effective management of coral reef ecosystems are a lack of information on the spatial distribution of marine species and a paucity of data on the interacting environmental variables that drive distributional patterns. Advances in marine remote sensing, together with the novel integration of landscape ecology and advanced niche modelling techniques provide an unprecedented opportunity to reliably model and map marine species distributions across many kilometres of coral reef ecosystems. We developed a multi-scale approach using three-dimensional seafloor morphology and across-shelf location to predict spatial distributions for five common Caribbean fish species. Seascape topography was quantified from high resolution bathymetry at five spatial scales (5-300 m radii surrounding fish survey sites. Model performance and map accuracy was assessed for two high performing machine-learning algorithms: Boosted Regression Trees (BRT and Maximum Entropy Species Distribution Modelling (MaxEnt. The three most important predictors were geographical location across the shelf, followed by a measure of topographic complexity. Predictor contribution differed among species, yet rarely changed across spatial scales. BRT provided 'outstanding' model predictions (AUC = >0.9 for three of five fish species. MaxEnt provided 'outstanding' model predictions for two of five species, with the remaining three models considered 'excellent' (AUC = 0.8-0.9. In contrast, MaxEnt spatial predictions were markedly more accurate (92% map accuracy than BRT (68% map accuracy. We demonstrate that reliable spatial predictions for a range of key fish species can be achieved by modelling the interaction between the geographical location across the shelf and the topographic heterogeneity of seafloor structure. This multi-scale, analytic approach is an important new cost-effective tool to accurately delineate essential fish habitat and support

Macro-institutional Complexity in Logistics

DEFF Research Database (Denmark)

Wessel, Frederic; Kinra, Aseem; Kotzab, Herbert

2016-01-01

structure and transactional costs, the concept of environmental complexity is applied to the logistics management perspective. Thereby, the impacts which a given framework on a macro-institutional level might have on the situation and leeway in decision-making at the firm (micro) or the supply chain (meso......In this paper, the interlink between the concept of macro-institutional complexity in logistics and the dynamics in the logistics practice of Eastern Europe will be examined. Referring to the importance of different authors having ascribed to the external environmental uncertainty on organizational......) levels will be analysed. Furthermore, a quantitative modelling approach will be presented and exemplified by using the case of logistics infrastructure in Eastern Europe....

Estimation of Scale Deposition in the Water Walls of an Operating Indian Coal Fired Boiler: Predictive Modeling Approach Using Artificial Neural Networks

Science.gov (United States)

Kumari, Amrita; Das, Suchandan Kumar; Srivastava, Prem Kumar

2016-04-01

Application of computational intelligence for predicting industrial processes has been in extensive use in various industrial sectors including power sector industry. An ANN model using multi-layer perceptron philosophy has been proposed in this paper to predict the deposition behaviors of oxide scale on waterwall tubes of a coal fired boiler. The input parameters comprises of boiler water chemistry and associated operating parameters, such as, pH, alkalinity, total dissolved solids, specific conductivity, iron and dissolved oxygen concentration of the feed water and local heat flux on boiler tube. An efficient gradient based network optimization algorithm has been employed to minimize neural predictions errors. Effects of heat flux, iron content, pH and the concentrations of total dissolved solids in feed water and other operating variables on the scale deposition behavior have been studied. It has been observed that heat flux, iron content and pH of the feed water have a relatively prime influence on the rate of oxide scale deposition in water walls of an Indian boiler. Reasonably good agreement between ANN model predictions and the measured values of oxide scale deposition rate has been observed which is corroborated by the regression fit between these values.

Ability of the MACRO Model to Predict Long-Term Leaching of Metribuzin and Diketometribuzin

DEFF Research Database (Denmark)

Rosenbom, Annette E; Kjær, Jeanne; Henriksen, Trine

2009-01-01

In a regulatory context, numerical models are increasingly employed to quantify leaching of pesticides and their metabolites. Although the ability of these models to accurately simulate leaching of pesticides has been evaluated, little is known about their ability to accurately simulate long...... alternative kinetics (a two-site approach), we captured the observed leaching scenario, thus underlining the necessity of accounting for the long-term sorption and dissipation characteristics when using models to predict the risk of groundwater contamination.......-term leaching of metabolites. A Danish study on the dissipation and sorption of metribuzin, involving both monitoring and batch experiments, concluded that desorption and degradation of metribuzin and leaching of its primary metabolite diketometribuzin continued for 5-6 years after application, posing a risk...

A statistical forecast model using the time-scale decomposition technique to predict rainfall during flood period over the middle and lower reaches of the Yangtze River Valley

Science.gov (United States)

Hu, Yijia; Zhong, Zhong; Zhu, Yimin; Ha, Yao

2018-04-01

In this paper, a statistical forecast model using the time-scale decomposition method is established to do the seasonal prediction of the rainfall during flood period (FPR) over the middle and lower reaches of the Yangtze River Valley (MLYRV). This method decomposites the rainfall over the MLYRV into three time-scale components, namely, the interannual component with the period less than 8 years, the interdecadal component with the period from 8 to 30 years, and the interdecadal component with the period larger than 30 years. Then, the predictors are selected for the three time-scale components of FPR through the correlation analysis. At last, a statistical forecast model is established using the multiple linear regression technique to predict the three time-scale components of the FPR, respectively. The results show that this forecast model can capture the interannual and interdecadal variation of FPR. The hindcast of FPR during 14 years from 2001 to 2014 shows that the FPR can be predicted successfully in 11 out of the 14 years. This forecast model performs better than the model using traditional scheme without time-scale decomposition. Therefore, the statistical forecast model using the time-scale decomposition technique has good skills and application value in the operational prediction of FPR over the MLYRV.

Predicting patient exposure to nickel released from cardiovascular devices using multi-scale modeling.

Science.gov (United States)

Saylor, David M; Craven, Brent A; Chandrasekar, Vaishnavi; Simon, David D; Brown, Ronald P; Sussman, Eric M

2018-04-01

Many cardiovascular device alloys contain nickel, which if released in sufficient quantities, can lead to adverse health effects. However, in-vivo nickel release from implanted devices and subsequent biodistribution of nickel ions to local tissues and systemic circulation are not well understood. To address this uncertainty, we have developed a multi-scale (material, tissue, and system) biokinetic model. The model links nickel release from an implanted cardiovascular device to concentrations in peri-implant tissue, as well as in serum and urine, which can be readily monitored. The model was parameterized for a specific cardiovascular implant, nitinol septal occluders, using in-vitro nickel release test results, studies of ex-vivo uptake into heart tissue, and in-vivo and clinical measurements from the literature. Our results show that the model accurately predicts nickel concentrations in peri-implant tissue in an animal model and in serum and urine of septal occluder patients. The congruity of the model with these data suggests it may provide useful insight to establish nickel exposure limits and interpret biomonitoring data. Finally, we use the model to predict local and systemic nickel exposure due to passive release from nitinol devices produced using a wide range of manufacturing processes, as well as general relationships between release rate and exposure. These relationships suggest that peri-implant tissue and serum levels of nickel will remain below 5 μg/g and 10 μg/l, respectively, in patients who have received implanted nitinol cardiovascular devices provided the rate of nickel release per device surface area does not exceed 0.074 μg/(cm 2  d) and is less than 32 μg/d in total. The uncertainty in whether in-vitro tests used to evaluate metal ion release from medical products are representative of clinical environments is one of the largest roadblocks to establishing the associated patient risk. We have developed and validated a multi-scale

Drift-Scale THC Seepage Model

Energy Technology Data Exchange (ETDEWEB)

C.R. Bryan

2005-02-17

The purpose of this report (REV04) is to document the thermal-hydrologic-chemical (THC) seepage model, which simulates the composition of waters that could potentially seep into emplacement drifts, and the composition of the gas phase. The THC seepage model is processed and abstracted for use in the total system performance assessment (TSPA) for the license application (LA). This report has been developed in accordance with ''Technical Work Plan for: Near-Field Environment and Transport: Coupled Processes (Mountain-Scale TH/THC/THM, Drift-Scale THC Seepage, and Post-Processing Analysis for THC Seepage) Report Integration'' (BSC 2005 [DIRS 172761]). The technical work plan (TWP) describes planning information pertaining to the technical scope, content, and management of this report. The plan for validation of the models documented in this report is given in Section 2.2.2, ''Model Validation for the DS THC Seepage Model,'' of the TWP. The TWP (Section 3.2.2) identifies Acceptance Criteria 1 to 4 for ''Quantity and Chemistry of Water Contacting Engineered Barriers and Waste Forms'' (NRC 2003 [DIRS 163274]) as being applicable to this report; however, in variance to the TWP, Acceptance Criterion 5 has also been determined to be applicable, and is addressed, along with the other Acceptance Criteria, in Section 4.2 of this report. Also, three FEPS not listed in the TWP (2.2.10.01.0A, 2.2.10.06.0A, and 2.2.11.02.0A) are partially addressed in this report, and have been added to the list of excluded FEPS in Table 6.1-2. This report has been developed in accordance with LP-SIII.10Q-BSC, ''Models''. This report documents the THC seepage model and a derivative used for validation, the Drift Scale Test (DST) THC submodel. The THC seepage model is a drift-scale process model for predicting the composition of gas and water that could enter waste emplacement drifts and the effects of mineral

Resolution, Scales and Predictability: Is High Resolution Detrimental To Predictability At Extended Forecast Times?

Science.gov (United States)

Mesinger, F.

The traditional views hold that high-resolution limited area models (LAMs) down- scale large-scale lateral boundary information, and that predictability of small scales is short. Inspection of various rms fits/errors has contributed to these views. It would follow that the skill of LAMs should visibly deteriorate compared to that of their driver models at more extended forecast times. The limited area Eta Model at NCEP has an additional handicap of being driven by LBCs of the previous Avn global model run, at 0000 and 1200 UTC estimated to amount to about an 8 h loss in accuracy. This should make its relative skill compared to that of the Avn deteriorate even faster. These views are challenged by various Eta results including rms fits to raobs out to 84 h. It is argued that it is the largest scales that contribute the most to the skill of the Eta relative to that of the Avn.

101 Ready-To-Use Excel Macros

CERN Document Server

Alexander, Michael

2012-01-01

Save time and be more productive with this helpful guide to Excel macros! While most books about Excel macros offer only minor examples, usually aimed at illustrating a particular topic, this invaluable resource provides you with the tools needed to efficiently and effectively program Excel macros immediately. Step-by-step instructions show you how to create VBA macros and explain how to customize your applications to look and work exactly as you want them to. By the end of the book, you will understand how each featured macro works, be able to reuse the macros included in the book and online,

Shape shifting predicts ontogenetic changes in metabolic scaling in diverse aquatic invertebrates

DEFF Research Database (Denmark)

Glazier, Douglas S.; Hirst, Andrew G.; Atkinson, D.

2016-01-01

in metabolic scaling that deviate from 3/4-power scaling predicted by general models. Here, we show that in diverse aquatic invertebrates, ontogenetic shifts in the scaling of routine metabolic rate from near isometry (bR = scaling exponent approx. 1) to negative allometry (bR

Fully predictive simulation of real-scale cable tray fire based on small-scale laboratory experiments

Energy Technology Data Exchange (ETDEWEB)

Beji, Tarek; Merci, Bart [Ghent Univ. (Belgium). Dept. of Flow, Heat and Combustion Mechanics; Bonte, Frederick [Bel V, Brussels (Belgium)

2015-12-15

This paper presents a computational fluid dynamics (CFD)-based modelling strategy for real-scale cable tray fires. The challenge was to perform fully predictive simulations (that could be called 'blind' simulations) using solely information from laboratory-scale experiments, in addition to the geometrical arrangement of the cables. The results of the latter experiments were used (1) to construct the fuel molecule and the chemical reaction for combustion, and (2) to estimate the overall pyrolysis and burning behaviour. More particularly, the strategy regarding the second point consists of adopting a surface-based pyrolysis model. Since the burning behaviour of each cable could not be tracked individually (due to computational constraints), 'groups' of cables were modelled with an overall cable surface area equal to the actual value. The results obtained for one large-scale test (a stack of five horizontal trays) are quite encouraging, especially for the peak Heat Release Rate (HRR) that was predicted with a relative deviation of 3 %. The time to reach the peak is however overestimated by 4.7 min (i.e. 94 %). Also, the fire duration is overestimated by 5 min (i.e. 24 %). These discrepancies are mainly attributed to differences in the HRRPUA (heat release rate per unit area) profiles between the small-scale and large-scale. The latter was calculated by estimating the burning area of cables using video fire analysis (VFA).

Estimating the magnitude of prediction uncertainties for field-scale P loss models

Science.gov (United States)

Models are often used to predict phosphorus (P) loss from agricultural fields. While it is commonly recognized that model predictions are inherently uncertain, few studies have addressed prediction uncertainties using P loss models. In this study, an uncertainty analysis for the Annual P Loss Estima...

Experimental prediction of severe droughts on seasonal to intra-annual time scales with GFDL High-Resolution Atmosphere Model

Science.gov (United States)

Yu, Z.; Lin, S.

2011-12-01

Regional heat waves and drought have major economic and societal impacts on regional and even global scales. For example, during and following the 2010-2011 La Nina period, severe droughts have been reported in many places around the world including China, the southern US, and the east Africa, causing severe hardship in China and famine in east Africa. In this study, we investigate the feasibility and predictability of severe spring-summer draught events, 3 to 6 months in advance with the 25-km resolution Geophysical Fluid Dynamics Laboratory High-Resolution Atmosphere Model (HiRAM), which is built as a seamless weather-climate model, capable of long-term climate simulations as well as skillful seasonal predictions (e.g., Chen and Lin 2011, GRL). We adopted a similar methodology and the same (HiRAM) model as in Chen and Lin (2011), which is used successfully for seasonal hurricane predictions. A series of initialized 7-month forecasts starting from Dec 1 are performed each year (5 members each) during the past decade (2000-2010). We will then evaluate the predictability of the severe drought events during this period by comparing model predictions vs. available observations. To evaluate the predictive skill, in this preliminary report, we will focus on the anomalies of precipitation, sea-level-pressure, and 500-mb height. These anomalies will be computed as the individual model prediction minus the mean climatology obtained by an independent AMIP-type "simulation" using observed SSTs (rather than using predictive SSTs in the forecasts) from the same model.

Predicting Gran alkalinity and calcium concentrations in river waters over a national scale using a novel modification to the G-BASH model

International Nuclear Information System (INIS)

Cresser, Malcolm S.; Ahmed, Nayan; Smart, Richard P.; Arowolo, Toyin; Calver, Louise J.; Chapman, Pippa J.

2006-01-01

Monthly stream water calcium and Gran alkalinity concentration data from 11 sub-catchments of the Nether Beck in the English Lake District have been used to appraise the transferability of the Scottish, River Dee-based G-BASH model. Readily available riparian zone geochemistry and flow paths were used initially to predict minimum and mean stream water concentrations at the Nether Beck, based on calibration equations from the River Dee catchment data. Predicted values significantly exceeded observed values. Differences in runoff between the two areas, leading to a dilution effect in the Nether Beck, explained most of the difference between observed and predicted values. Greater acid deposition in the Lake District also reduced stream water Gran alkalinity concentrations in that area. If regional differences in precipitation, evapotranspiration and pollutant deposition are incorporated into the model, it may then be used reliably to predict catchment susceptibility to acidification over a wide regional (national) scale. - A modified G-BASH model predicts calcium and Gran alkalinity in streams at a national scale, taking account of regional deposition and climatic variations

Development and testing of watershed-scale models for poorly drained soils

Science.gov (United States)

Glenn P. Fernandez; George M. Chescheir; R. Wayne Skaggs; Devendra M. Amatya

2005-01-01

Watershed-scale hydrology and water quality models were used to evaluate the crrmulative impacts of land use and management practices on dowrzstream hydrology and nitrogen loading of poorly drained watersheds. Field-scale hydrology and nutrient dyyrutmics are predicted by DRAINMOD in both models. In the first model (DRAINMOD-DUFLOW), field-scale predictions are coupled...

Micro-processus et macro-structures

Directory of Open Access Journals (Sweden)

Aaron Victor Cicourel

2008-10-01

Full Text Available Des approches sociologiques traditionnelles ont défini des macro-structures sociales comme un niveau particulier de la réalité sociale, à distinguer des micro-épisodes de l’action sociale. Cela les a conduits à concevoir ces macro-structures et à mener des recherches sur elles de manière plus ou moins indépendante des pratiques observables de la vie quotidienne. Cicourel soutient que les faits (macro-sociaux ne sont pas simplement donnés, mais émergent de pratiques routinières de la vie de tous les jours. Le macro, au sens de descriptions résumées, hors contexte, normalisées et typifiées, est un produit typique des procédures interactives et organisationnelles qui transforment les micro-événements en structures macro-sociales. Ainsi une précondition pour l’intégration des phénomènes micro- et macro-sociaux dans notre théorie et dans notre méthodologie renvoie à l’identification des processus contribuant à la création de macro-structures par des inférences routinières, des interprétations et des procédure de résumé. Le texte montre aussi que les différences entre approches micro-sociologiques apparaissent parallèles à celles existant entre approches micro et macro. On se centrant sur de petits fragments d’interactions conversationnelles, certains travaux micro-sociologiques tendent à ignorer ce qui informe ces interactions conversationnelles pour les participants eux-mêmes. Les comptes rendus décontextualisés produits par de telles méthodes ressemblent à la décontextualisation résultant des procédures macro-sociologiques d’agrégation. Contre cela, Cicourel défend la constitution de bases de données comparatives n’incluant pas seulement le contexte des interactions de face à face, mais étudiant aussi les phénomènes sociaux de manière systématique à travers différents contextes.Micro-processes and macro-structures. Notes on articulation between different levels of analysis

Economic Model Predictive Control for Large-Scale and Distributed Energy Systems

DEFF Research Database (Denmark)

Standardi, Laura

Sources (RESs) in the smart grids is increasing. These energy sources bring uncertainty to the production due to their fluctuations. Hence,smart grids need suitable control systems that are able to continuously balance power production and consumption.  We apply the Economic Model Predictive Control (EMPC......) strategy to optimise the economic performances of the energy systems and to balance the power production and consumption. In the case of large-scale energy systems, the electrical grid connects a high number of power units. Because of this, the related control problem involves a high number of variables......In this thesis, we consider control strategies for large and distributed energy systems that are important for the implementation of smart grid technologies.  An electrical grid has to ensure reliability and avoid long-term interruptions in the power supply. Moreover, the share of Renewable Energy...

%HPGLIMMIX: A High-Performance SAS Macro for GLMM Estimation

Directory of Open Access Journals (Sweden)

Liang Xie

2014-06-01

Full Text Available Generalized linear mixed models (GLMMs comprise a class of widely used statistical tools for data analysis with fixed and random effects when the response variable has a conditional distribution in the exponential family. GLMM analysis also has a close relationship with actuarial credibility theory. While readily available programs such as the GLIMMIX procedure in SAS and the lme4 package in R are powerful tools for using this class of models, these progarms are not able to handle models with thousands of levels of fixed and random effects. By using sparse-matrix and other high performance techniques, procedures such as HPMIXED in SAS can easily fit models with thousands of factor levels, but only for normally distributed response variables. In this paper, we present the %HPGLIMMIX SAS macro that fits GLMMs with large number of sparsely populated design matrices using the doubly-iterative linearization (pseudo-likelihood method, in which the sparse-matrix-based HPMIXED is used for the inner iterations with the pseudo-variable constructed from the inverse-link function and the chosen model. Although the macro does not have the full functionality of the GLIMMIX procedure, time and memory savings can be large with the new macro. In applications in which design matrices contain many zeros and there are hundreds or thousands of factor levels, models can be fitted without exhausting computer memory, and 90% or better reduction in running time can be observed. Examples with a Poisson, binomial, and gamma conditional distribution are presented to demonstrate the usage and efficiency of this macro.

Importance of ecohydrological modelling approaches in the prediction of plant behaviour and water balance at different scales

Science.gov (United States)

García-Arias, Alicia; Ruiz-Pérez, Guiomar; Francés, Félix

2017-04-01

Vegetation plays a main role in the water balance of most hydrological systems. However, in the past it has been barely considered the effect of the interception and evapotranspiration for hydrological modelling purposes. During the last years many authors have recognised and supported ecohydrological approaches instead of traditional strategies. This contribution is aimed to demonstrate the pivotal role of the vegetation in ecohydrological models and that a better understanding of the hydrological systems can be achieved by considering the appropriate processes related to plants. The study is performed in two scales: the plot scale and the reach scale. At plot scale, only zonal vegetation was considered while at reach scale both zonal and riparian were taken into account. In order to assure the main role of the water on the vegetation development, semiarid environments have been selected for the case studies. Results show an increase of the capabilities to predict plant behaviour and water balance when interception and evapotranspiration are taken into account in the soil water balance

Macro and intergranular stress responses of austenitic stainless steel to 90° strain path changes

International Nuclear Information System (INIS)

Gonzalez, D.; Kelleher, J.F.; Quinta da Fonseca, J.; Withers, P.J.

2012-01-01

Highlights: ► We measure and model the macro and IG stresses of ASS to 90° strain path changes. ► The macro stress–strain curves show a clear Bauschinger effect on reloading. ► This is only partially captured by the model. ► The measured {h k l} families show an earlier microyield than predicted. ► This difference is more noticeable for a strain path with a higher reversibility. - Abstract: Strain path history can play a crucial role in sensitising/desensitising metals to various damage mechanisms and yet little work has been done to quantify and understand how intergranular strains change upon path changes, or their effect on the macroscopic behaviour. Here we have measured, by neutron diffraction, and modelled, by crystal plasticity finite elements, the stress–strain responses of 316L stainless steel over three different 90° strain path changes using an assembled microstructure of randomly oriented crystallites. The measurements show a clear Bauschinger effect on reloading that is only partially captured by the model. Further, measurements of the elastic response of different {h k l} grain families revealed an even earlier onset of yield for strain paths reloaded in compression while a strain path reloaded in tension showed good agreement with corresponding predictions. Finally, we propose that the study of strain path effects provides a more rigorous test of crystal plasticity models than conventional in situ diffraction studies of uniaxial loading.

Macro-mechanical material model for fiber reinforced metal matrix composites

CERN Document Server

Banks-Sills, L

1999-01-01

The stress-strain behavior of a metal matrix composite reinforced with unidirectional, continuous and periodic fibers is investigated. Three-dimensional micro-mechanical analyses of a unit cell by means of the finite element method $9 and homogenization-localization are carried out. These calculations allow the determination of material behavior of the in-plane, as well as the fiber directions. The fibers are assumed to be elastic and the matrix elasto-plastic. $9 The matrix material is governed by a von Mises yield surface, isotropic hardening and an associated flow rule. With the aid of these analyses, the foundation to a macro-mechanical material model is presented which is employed to $9 consider an elementary problem. The model includes an anisotropic yield surface with isotropic hardening and an associated flow rule. A beam in bending containing square fibers under plane strain conditions is analyzed by means of $9 the model. Two cases are considered: one in which the fibers are symmetric with respect t...

Equivalent Electromagnetic Constants for Microwave Application to Composite Materials for the Multi-Scale Problem

Directory of Open Access Journals (Sweden)

Keisuke Fujisaki

2013-11-01

Full Text Available To connect different scale models in the multi-scale problem of microwave use, equivalent material constants were researched numerically by a three-dimensional electromagnetic field, taking into account eddy current and displacement current. A volume averaged method and a standing wave method were used to introduce the equivalent material constants; water particles and aluminum particles are used as composite materials. Consumed electrical power is used for the evaluation. Water particles have the same equivalent material constants for both methods; the same electrical power is obtained for both the precise model (micro-model and the homogeneous model (macro-model. However, aluminum particles have dissimilar equivalent material constants for both methods; different electric power is obtained for both models. The varying electromagnetic phenomena are derived from the expression of eddy current. For small electrical conductivity such as water, the macro-current which flows in the macro-model and the micro-current which flows in the micro-model express the same electromagnetic phenomena. However, for large electrical conductivity such as aluminum, the macro-current and micro-current express different electromagnetic phenomena. The eddy current which is observed in the micro-model is not expressed by the macro-model. Therefore, the equivalent material constant derived from the volume averaged method and the standing wave method is applicable to water with a small electrical conductivity, although not applicable to aluminum with a large electrical conductivity.

Macro- and micro-designed chitosan-alginate scaffold architecture by three-dimensional printing and directional freezing

International Nuclear Information System (INIS)

Reed, Stephanie; Wu, Benjamin M; Lau, Grace; Delattre, Benjamin; Lopez, David Don; Tomsia, Antoni P

2016-01-01

While many tissue-engineered constructs aim to treat cartilage defects, most involve chondrocyte or stem cell seeding on scaffolds. The clinical application of cell-based techniques is limited due to the cost of maintaining cellular constructs on the shelf, potential immune response to allogeneic cell lines, and autologous chondrocyte sources requiring biopsy from already diseased or injured, scarce tissue. An acellular scaffold that can induce endogenous influx and homogeneous distribution of native stem cells from bone marrow holds great promise for cartilage regeneration. This study aims to develop such an acellular scaffold using designed, channeled architecture that simultaneously models the native zones of articular cartilage and subchondral bone. Highly porous, hydrophilic chitosan-alginate (Ch-Al) scaffolds were fabricated in three-dimensionally printed (3DP) molds designed to create millimeter scale macro-channels. Different polymer preform casting techniques were employed to produce scaffolds from both negative and positive 3DP molds. Macro-channeled scaffolds improved cell suspension distribution and uptake overly randomly porous scaffolds, with a wicking volumetric flow rate of 445.6 ± 30.3 mm 3 s −1 for aqueous solutions and 177 ± 16 mm 3 s −1 for blood. Additionally, directional freezing was applied to Ch-Al scaffolds, resulting in lamellar pores measuring 300 μm and 50 μm on the long and short axes, thus creating micrometer scale micro-channels. After directionally freezing Ch-Al solution cast in 3DP molds, the combined macro- and micro-channeled scaffold architecture enhanced cell suspension uptake beyond either macro- or micro-channels alone, reaching a volumetric flow rate of 1782.1 ± 48 mm 3 s −1 for aqueous solutions and 440.9 ± 0.5 mm 3 s −1 for blood. By combining 3DP and directional freezing, we can control the micro- and macro-architecture of Ch-Al to drastically improve cell influx into and distribution within the

Prediction of Fracture Behavior in Rock and Rock-like Materials Using Discrete Element Models

Science.gov (United States)

Katsaga, T.; Young, P.

2009-05-01

The study of fracture initiation and propagation in heterogeneous materials such as rock and rock-like materials are of principal interest in the field of rock mechanics and rock engineering. It is crucial to study and investigate failure prediction and safety measures in civil and mining structures. Our work offers a practical approach to predict fracture behaviour using discrete element models. In this approach, the microstructures of materials are presented through the combination of clusters of bonded particles with different inter-cluster particle and bond properties, and intra-cluster bond properties. The geometry of clusters is transferred from information available from thin sections, computed tomography (CT) images and other visual presentation of the modeled material using customized AutoCAD built-in dialog- based Visual Basic Application. Exact microstructures of the tested sample, including fractures, faults, inclusions and void spaces can be duplicated in the discrete element models. Although the microstructural fabrics of rocks and rock-like structures may have different scale, fracture formation and propagation through these materials are alike and will follow similar mechanics. Synthetic material provides an excellent condition for validating the modelling approaches, as fracture behaviours are known with the well-defined composite's properties. Calibration of the macro-properties of matrix material and inclusions (aggregates), were followed with the overall mechanical material responses calibration by adjusting the interfacial properties. The discrete element model predicted similar fracture propagation features and path as that of the real sample material. The path of the fractures and matrix-inclusion interaction was compared using computed tomography images. Initiation and fracture formation in the model and real material were compared using Acoustic Emission data. Analysing the temporal and spatial evolution of AE events, collected during the

Influence of dry cohesion on the micro- and macro-mechanical properties of dense polydisperse powders & grains

Science.gov (United States)

Kievitsbosch, Robert; Smit, Hendrik; Magnanimo, Vanessa; Luding, Stefan; Taghizadeh, Kianoosh

2017-06-01

Understanding how cohesive granular materials behave is of interest for many industrial applications, such as pharmaceutical or food and civil engineering. Models of the behaviour of granular materials on the microscopic scale can be used to obtain macroscopic continuum relations by a micro-macro transition approach. The Discrete Element Method (DEM) is used to inspect the influence of cohesion on the micro and macro behaviour of granular assemblies by using an elasto-plastic cohesive contact model. Interestingly, we observe that frictional samples prepared with different cohesion values show a significant difference in pressure and coordination number in the jammed regime; the differences become more pronounced when packings are closer to the jamming density, i.e. the lowest density where the system is mechanically stable. Furthermore, we observe that cohesion has an influence on the jamming density for frictional samples, but there is no influence on the jamming density for frictionless samples.

Genome-scale biological models for industrial microbial systems.

Science.gov (United States)

Xu, Nan; Ye, Chao; Liu, Liming

2018-04-01

The primary aims and challenges associated with microbial fermentation include achieving faster cell growth, higher productivity, and more robust production processes. Genome-scale biological models, predicting the formation of an interaction among genetic materials, enzymes, and metabolites, constitute a systematic and comprehensive platform to analyze and optimize the microbial growth and production of biological products. Genome-scale biological models can help optimize microbial growth-associated traits by simulating biomass formation, predicting growth rates, and identifying the requirements for cell growth. With regard to microbial product biosynthesis, genome-scale biological models can be used to design product biosynthetic pathways, accelerate production efficiency, and reduce metabolic side effects, leading to improved production performance. The present review discusses the development of microbial genome-scale biological models since their emergence and emphasizes their pertinent application in improving industrial microbial fermentation of biological products.

Design of scaled down structural models

Science.gov (United States)

Simitses, George J.

1994-07-01

In the aircraft industry, full scale and large component testing is a very necessary, time consuming, and expensive process. It is essential to find ways by which this process can be minimized without loss of reliability. One possible alternative is the use of scaled down models in testing and use of the model test results in order to predict the behavior of the larger system, referred to herein as prototype. This viewgraph presentation provides justifications and motivation for the research study, and it describes the necessary conditions (similarity conditions) for two structural systems to be structurally similar with similar behavioral response. Similarity conditions provide the relationship between a scaled down model and its prototype. Thus, scaled down models can be used to predict the behavior of the prototype by extrapolating their experimental data. Since satisfying all similarity conditions simultaneously is in most cases impractical, distorted models with partial similarity can be employed. Establishment of similarity conditions, based on the direct use of the governing equations, is discussed and their use in the design of models is presented. Examples include the use of models for the analysis of cylindrical bending of orthotropic laminated beam plates, of buckling of symmetric laminated rectangular plates subjected to uniform uniaxial compression and shear, applied individually, and of vibrational response of the same rectangular plates. Extensions and future tasks are also described.

A generalized macro-assembler

International Nuclear Information System (INIS)

Kaul, Mohan Lai

1970-01-01

The objective of this research is to study existing macro assemblers, and to create a generalized macro assembler, MAG-I, which is a system independent of a source language, and provides the following possibilities: development of any existing language, translation from a language to another, and creation of a new language. The user can choose his own notations to define macros. The system is implemented on an IBM 360/91 computer. Programs are written in symbolic language and the input/output software is written in Fortran [fr

Micro-CT Pore Scale Study Of Flow In Porous Media: Effect Of Voxel Resolution

Science.gov (United States)

Shah, S.; Gray, F.; Crawshaw, J.; Boek, E.

2014-12-01

In the last few years, pore scale studies have become the key to understanding the complex fluid flow processes in the fields of groundwater remediation, hydrocarbon recovery and environmental issues related to carbon storage and capture. A pore scale study is often comprised of two key procedures: 3D pore scale imaging and numerical modelling techniques. The essence of a pore scale study is to test the physics implemented in a model of complicated fluid flow processes at one scale (microscopic) and then apply the model to solve the problems associated with water resources and oil recovery at other scales (macroscopic and field). However, the process of up-scaling from the pore scale to the macroscopic scale has encountered many challenges due to both pore scale imaging and modelling techniques. Due to the technical limitations in the imaging method, there is always a compromise between the spatial (voxel) resolution and the physical volume of the sample (field of view, FOV) to be scanned by the imaging methods, specifically X-ray micro-CT (XMT) in our case In this study, a careful analysis was done to understand the effect of voxel size, using XMT to image the 3D pore space of a variety of porous media from sandstones to carbonates scanned at different voxel resolution (4.5 μm, 6.2 μm, 8.3 μm and 10.2 μm) but keeping the scanned FOV constant for all the samples. We systematically segment the micro-CT images into three phases, the macro-pore phase, an intermediate phase (unresolved micro-pores + grains) and the grain phase and then study the effect of voxel size on the structure of the macro-pore and the intermediate phases and the fluid flow properties using lattice-Boltzmann (LB) and pore network (PN) modelling methods. We have also applied a numerical coarsening algorithm (up-scale method) to reduce the computational power and time required to accurately predict the flow properties using the LB and PN method.

Predicting the performance uncertainty of a 1-MW pilot-scale carbon capture system after hierarchical laboratory-scale calibration and validation

Energy Technology Data Exchange (ETDEWEB)

Xu, Zhijie; Lai, Canhai; Marcy, Peter William; Dietiker, Jean-François; Li, Tingwen; Sarkar, Avik; Sun, Xin

2017-05-01

A challenging problem in designing pilot-scale carbon capture systems is to predict, with uncertainty, the adsorber performance and capture efficiency under various operating conditions where no direct experimental data exist. Motivated by this challenge, we previously proposed a hierarchical framework in which relevant parameters of physical models were sequentially calibrated from different laboratory-scale carbon capture unit (C2U) experiments. Specifically, three models of increasing complexity were identified based on the fundamental physical and chemical processes of the sorbent-based carbon capture technology. Results from the corresponding laboratory experiments were used to statistically calibrate the physical model parameters while quantifying some of their inherent uncertainty. The parameter distributions obtained from laboratory-scale C2U calibration runs are used in this study to facilitate prediction at a larger scale where no corresponding experimental results are available. In this paper, we first describe the multiphase reactive flow model for a sorbent-based 1-MW carbon capture system then analyze results from an ensemble of simulations with the upscaled model. The simulation results are used to quantify uncertainty regarding the design’s predicted efficiency in carbon capture. In particular, we determine the minimum gas flow rate necessary to achieve 90% capture efficiency with 95% confidence.

Probabilistic Fatigue Life Prediction of Bridge Cables Based on Multiscaling and Mesoscopic Fracture Mechanics

Directory of Open Access Journals (Sweden)

Zhongxiang Liu

2016-04-01

Full Text Available Fatigue fracture of bridge stay-cables is usually a multiscale process as the crack grows from micro-scale to macro-scale. Such a process, however, is highly uncertain. In order to make a rational prediction of the residual life of bridge cables, a probabilistic fatigue approach is proposed, based on a comprehensive vehicle load model, finite element analysis and multiscaling and mesoscopic fracture mechanics. Uncertainties in both material properties and external loads are considered. The proposed method is demonstrated through the fatigue life prediction of cables of the Runyang Cable-Stayed Bridge in China, and it is found that cables along the bridge spans may have significantly different fatigue lives, and due to the variability, some of them may have shorter lives than those as expected from the design.

Evaluating the Predictive Value of Growth Prediction Models

Science.gov (United States)

Murphy, Daniel L.; Gaertner, Matthew N.

2014-01-01

This study evaluates four growth prediction models--projection, student growth percentile, trajectory, and transition table--commonly used to forecast (and give schools credit for) middle school students' future proficiency. Analyses focused on vertically scaled summative mathematics assessments, and two performance standards conditions (high…

Synchronized motion control and precision positioning compensation of a 3-DOFs macro-micro parallel manipulator fully actuated by piezoelectric actuators

Science.gov (United States)

Zhang, Quan; Li, Chaodong; Zhang, Jiantao; Zhang, Xu

2017-11-01

The macro-micro combined approach, as an effective way to realize trans-scale nano-precision positioning with multi-dimensions and high velocity, plays a significant role in integrated circuit manufacturing field. A 3-degree-of-freedoms (3-DOFs) macro-micro manipulator is designed and analyzed to compromise the conflictions among the large stroke, high precision and multi-DOFs. The macro manipulator is a 3-Prismatic-Revolute-Revolute (3-PRR) structure parallel manipulator which is driven by three linear ultrasonic motors. The dynamic model and the cross-coupling error based synchronized motion controller of the 3-PRR parallel manipulator are theoretical analyzed and experimental tested. To further improve the positioning accuracy, a 3-DOFs monolithic compliant manipulator actuated by three piezoelectric stack actuators is designed. Then a multilayer BP neural network based inverse kinematic model identifier is developed to perform the positioning control. Finally, by forming the macro-micro structure, the dual stage manipulator successfully achieved the positioning task from the point (2 mm, 2 mm, 0 rad) back to the original point (0 mm, 0 mm, 0 rad) with the translation errors in X and Y directions less than ±50 nm and the rotation error around Z axis less than ±1 μrad, respectively.

Regional Scale High Resolution δ18O Prediction in Precipitation Using MODIS EVI

Science.gov (United States)

Huang, Cho-Ying; Wang, Chung-Ho; Lin, Shou-De; Lo, Yi-Chen; Huang, Bo-Wen; Hatch, Kent A.; Shiu, Hau-Jie; You, Cheng-Feng; Chang, Yuan-Mou; Shen, Sheng-Feng

2012-01-01

The natural variation in stable water isotope ratio data, also known as water isoscape, is a spatiotemporal fingerprint and a powerful natural tracer that has been widely applied in disciplines as diverse as hydrology, paleoclimatology, ecology and forensic investigation. Although much effort has been devoted to developing a predictive water isoscape model, it remains a central challenge for scientists to generate high accuracy, fine scale spatiotemporal water isoscape prediction. Here we develop a novel approach of using the MODIS-EVI (the Moderate Resolution Imagining Spectroradiometer-Enhanced Vegetation Index), to predict δ18O in precipitation at the regional scale. Using a structural equation model, we show that the EVI and precipitated δ18O are highly correlated and thus the EVI is a good predictor of precipitated δ18O. We then test the predictability of our EVI-δ18O model and demonstrate that our approach can provide high accuracy with fine spatial (250×250 m) and temporal (16 days) scale δ18O predictions (annual and monthly predictabilities [r] are 0.96 and 0.80, respectively). We conclude the merging of the EVI and δ18O in precipitation can greatly extend the spatial and temporal data availability and thus enhance the applicability for both the EVI and water isoscape. PMID:23029053

Extending the reach of powder diffraction modelling by user defined macros

CERN Document Server

Scardi, Paolo

2010-01-01

The main focus of this special topic volume is the development and possibilities of the MACRO language within TOPAS, with a specific session dedicated to WPPM. The collection is presented here in the form of a ""macro tutorial"" for the benefit of the entire powder diffraction community. More than a collection of standard scientific papers, the contributions to this special issue provide methods, tutorials and practical suggestions and solutions for the proper use of TOPAS and WPPM in a number of applications; ranging from the most common to the most refined and specific cases.Readers will fin

Interconnecting Urban Planning with Multi-Scale Urban Quality : Review of Macro Scale Urban Redevelopment Project on Micro Scale Urban Quality in Shenzhen

NARCIS (Netherlands)

Deng, X.

2015-01-01

The Shenzhen planning system has been effective in promoting economic growth through the prodigious urbanization of land. It has given priority to the ‘macro-level’ planning goals of economic growth through physical development. Questions can be raised about the physical and social outcomes from the

LANDIS PRO: a landscape model that predicts forest composition and structure changes at regional scales

Science.gov (United States)

Wen J. Wang; Hong S. He; Jacob S. Fraser; Frank R. Thompson; Stephen R. Shifley; Martin A. Spetich

2014-01-01

LANDIS PRO predicts forest composition and structure changes incorporating species-, stand-, and landscape-scales processes at regional scales. Species-scale processes include tree growth, establishment, and mortality. Stand-scale processes contain density- and size-related resource competition that regulates self-thinning and seedling establishment. Landscapescale...

In-hospital risk prediction for post-stroke depression: development and validation of the Post-stroke Depression Prediction Scale.

Science.gov (United States)

de Man-van Ginkel, Janneke M; Hafsteinsdóttir, Thóra B; Lindeman, Eline; Ettema, Roelof G A; Grobbee, Diederick E; Schuurmans, Marieke J

2013-09-01

The timely detection of post-stroke depression is complicated by a decreasing length of hospital stay. Therefore, the Post-stroke Depression Prediction Scale was developed and validated. The Post-stroke Depression Prediction Scale is a clinical prediction model for the early identification of stroke patients at increased risk for post-stroke depression. The study included 410 consecutive stroke patients who were able to communicate adequately. Predictors were collected within the first week after stroke. Between 6 to 8 weeks after stroke, major depressive disorder was diagnosed using the Composite International Diagnostic Interview. Multivariable logistic regression models were fitted. A bootstrap-backward selection process resulted in a reduced model. Performance of the model was expressed by discrimination, calibration, and accuracy. The model included a medical history of depression or other psychiatric disorders, hypertension, angina pectoris, and the Barthel Index item dressing. The model had acceptable discrimination, based on an area under the receiver operating characteristic curve of 0.78 (0.72-0.85), and calibration (P value of the U-statistic, 0.96). Transforming the model to an easy-to-use risk-assessment table, the lowest risk category (sum score, depression, which increased to 82% in the highest category (sum score, >21). The clinical prediction model enables clinicians to estimate the degree of the depression risk for an individual patient within the first week after stroke.

Macro factors in oil futures returns

International Nuclear Information System (INIS)

Le Pen, Yannick; Sevi, Benoit

2012-01-01

We investigate the macro factors that can explain the monthly oil futures return for the NYMEX WTI futures contract for the time period 1993:11 to 2010:03. We build a new database of 187 real and nominal macro-economic variables from developed and emerging countries and resort to the large factor approximate model to extract 9 factors from this dataset. We then regress crude oil return on several combinations of these factors. Our best model explains around 38% of the variability of oil futures return. More interestingly, the factor which has the largest influence on crude oil price is related to real variables from emerging countries. This result confirms the latest finding in the literature that the recent evolution in oil price is attributable to change in supply and demand conditions and not to the large increase in trading activity from speculators. (authors)

An evaluation of string theory for the prediction of dynamic tire properties using scale model aircraft tires

Science.gov (United States)

Clark, S. K.; Dodge, R. N.; Nybakken, G. H.

1972-01-01

The string theory was evaluated for predicting lateral tire dynamic properties as obtained from scaled model tests. The experimental data and string theory predictions are in generally good agreement using lateral stiffness and relaxation length values obtained from the static or slowly rolling tire. The results indicate that lateral forces and self-aligning torques are linearly proportional to tire lateral stiffness and to the amplitude of either steer or lateral displacement. In addition, the results show that the ratio of input excitation frequency to road speed is the proper independent variable by which frequency should be measured.

Validated predictive modelling of the environmental resistome.

Science.gov (United States)

Amos, Gregory C A; Gozzard, Emma; Carter, Charlotte E; Mead, Andrew; Bowes, Mike J; Hawkey, Peter M; Zhang, Lihong; Singer, Andrew C; Gaze, William H; Wellington, Elizabeth M H

2015-06-01

Multi-drug-resistant bacteria pose a significant threat to public health. The role of the environment in the overall rise in antibiotic-resistant infections and risk to humans is largely unknown. This study aimed to evaluate drivers of antibiotic-resistance levels across the River Thames catchment, model key biotic, spatial and chemical variables and produce predictive models for future risk assessment. Sediment samples from 13 sites across the River Thames basin were taken at four time points across 2011 and 2012. Samples were analysed for class 1 integron prevalence and enumeration of third-generation cephalosporin-resistant bacteria. Class 1 integron prevalence was validated as a molecular marker of antibiotic resistance; levels of resistance showed significant geospatial and temporal variation. The main explanatory variables of resistance levels at each sample site were the number, proximity, size and type of surrounding wastewater-treatment plants. Model 1 revealed treatment plants accounted for 49.5% of the variance in resistance levels. Other contributing factors were extent of different surrounding land cover types (for example, Neutral Grassland), temporal patterns and prior rainfall; when modelling all variables the resulting model (Model 2) could explain 82.9% of variations in resistance levels in the whole catchment. Chemical analyses correlated with key indicators of treatment plant effluent and a model (Model 3) was generated based on water quality parameters (contaminant and macro- and micro-nutrient levels). Model 2 was beta tested on independent sites and explained over 78% of the variation in integron prevalence showing a significant predictive ability. We believe all models in this study are highly useful tools for informing and prioritising mitigation strategies to reduce the environmental resistome.

Attribution of Large-Scale Climate Patterns to Seasonal Peak-Flow and Prospects for Prediction Globally

Science.gov (United States)

Lee, Donghoon; Ward, Philip; Block, Paul

2018-02-01

Flood-related fatalities and impacts on society surpass those from all other natural disasters globally. While the inclusion of large-scale climate drivers in streamflow (or high-flow) prediction has been widely studied, an explicit link to global-scale long-lead prediction is lacking, which can lead to an improved understanding of potential flood propensity. Here we attribute seasonal peak-flow to large-scale climate patterns, including the El Niño Southern Oscillation (ENSO), Pacific Decadal Oscillation (PDO), North Atlantic Oscillation (NAO), and Atlantic Multidecadal Oscillation (AMO), using streamflow station observations and simulations from PCR-GLOBWB, a global-scale hydrologic model. Statistically significantly correlated climate patterns and streamflow autocorrelation are subsequently applied as predictors to build a global-scale season-ahead prediction model, with prediction performance evaluated by the mean squared error skill score (MSESS) and the categorical Gerrity skill score (GSS). Globally, fair-to-good prediction skill (20% ≤ MSESS and 0.2 ≤ GSS) is evident for a number of locations (28% of stations and 29% of land area), most notably in data-poor regions (e.g., West and Central Africa). The persistence of such relevant climate patterns can improve understanding of the propensity for floods at the seasonal scale. The prediction approach developed here lays the groundwork for further improving local-scale seasonal peak-flow prediction by identifying relevant global-scale climate patterns. This is especially attractive for regions with limited observations and or little capacity to develop flood early warning systems.

Multi-Scale Multi-physics Methods Development for the Calculation of Hot-Spots in the NGNP

International Nuclear Information System (INIS)

Downar, Thomas; Seker, Volkan

2013-01-01

Radioactive gaseous fission products are released out of the fuel element at a significantly higher rate when the fuel temperature exceeds 1600°C in high-temperature gas-cooled reactors (HTGRs). Therefore, it is of paramount importance to accurately predict the peak fuel temperature during all operational and design-basis accident conditions. The current methods used to predict the peak fuel temperature in HTGRs, such as the Next-Generation Nuclear Plant (NGNP), estimate the average fuel temperature in a computational mesh modeling hundreds of fuel pebbles or a fuel assembly in a pebble-bed reactor (PBR) or prismatic block type reactor (PMR), respectively. Experiments conducted in operating HTGRs indicate considerable uncertainty in the current methods and correlations used to predict actual temperatures. The objective of this project is to improve the accuracy in the prediction of local 'hot' spots by developing multi-scale, multi-physics methods and implementing them within the framework of established codes used for NGNP analysis.The multi-scale approach which this project will implement begins with defining suitable scales for a physical and mathematical model and then deriving and applying the appropriate boundary conditions between scales. The macro scale is the greatest length that describes the entire reactor, whereas the meso scale models only a fuel block in a prismatic reactor and ten to hundreds of pebbles in a pebble bed reactor. The smallest scale is the micro scale--the level of a fuel kernel of the pebble in a PBR and fuel compact in a PMR--which needs to be resolved in order to calculate the peak temperature in a fuel kernel.

Multi-Scale Multi-physics Methods Development for the Calculation of Hot-Spots in the NGNP

Energy Technology Data Exchange (ETDEWEB)

Downar, Thomas [Univ. of Michigan, Ann Arbor, MI (United States); Seker, Volkan [Univ. of Michigan, Ann Arbor, MI (United States)

2013-04-30

Radioactive gaseous fission products are released out of the fuel element at a significantly higher rate when the fuel temperature exceeds 1600°C in high-temperature gas-cooled reactors (HTGRs). Therefore, it is of paramount importance to accurately predict the peak fuel temperature during all operational and design-basis accident conditions. The current methods used to predict the peak fuel temperature in HTGRs, such as the Next-Generation Nuclear Plant (NGNP), estimate the average fuel temperature in a computational mesh modeling hundreds of fuel pebbles or a fuel assembly in a pebble-bed reactor (PBR) or prismatic block type reactor (PMR), respectively. Experiments conducted in operating HTGRs indicate considerable uncertainty in the current methods and correlations used to predict actual temperatures. The objective of this project is to improve the accuracy in the prediction of local "hot" spots by developing multi-scale, multi-physics methods and implementing them within the framework of established codes used for NGNP analysis.The multi-scale approach which this project will implement begins with defining suitable scales for a physical and mathematical model and then deriving and applying the appropriate boundary conditions between scales. The macro scale is the greatest length that describes the entire reactor, whereas the meso scale models only a fuel block in a prismatic reactor and ten to hundreds of pebbles in a pebble bed reactor. The smallest scale is the micro scale--the level of a fuel kernel of the pebble in a PBR and fuel compact in a PMR--which needs to be resolved in order to calculate the peak temperature in a fuel kernel.

Large-scale ligand-based predictive modelling using support vector machines.

Science.gov (United States)

Alvarsson, Jonathan; Lampa, Samuel; Schaal, Wesley; Andersson, Claes; Wikberg, Jarl E S; Spjuth, Ola

2016-01-01

The increasing size of datasets in drug discovery makes it challenging to build robust and accurate predictive models within a reasonable amount of time. In order to investigate the effect of dataset sizes on predictive performance and modelling time, ligand-based regression models were trained on open datasets of varying sizes of up to 1.2 million chemical structures. For modelling, two implementations of support vector machines (SVM) were used. Chemical structures were described by the signatures molecular descriptor. Results showed that for the larger datasets, the LIBLINEAR SVM implementation performed on par with the well-established libsvm with a radial basis function kernel, but with dramatically less time for model building even on modest computer resources. Using a non-linear kernel proved to be infeasible for large data sizes, even with substantial computational resources on a computer cluster. To deploy the resulting models, we extended the Bioclipse decision support framework to support models from LIBLINEAR and made our models of logD and solubility available from within Bioclipse.

ZEUS - standardized macros for the TPA computer

International Nuclear Information System (INIS)

Winde, M.

1976-01-01

An existing cross-assembler with macro-option was modified to allow the usage of the ZEUS macros. The ZEUS macros are understood by the assembler without prior definition by the user. ZEUS macros allow the programmer, who is obliged to code his TPA (PDP-8) programs on the assembler level to formulate his program logic as in a higher level language. ZEUS macros offer all basic elements necessary for structured programming. (author)

Macro-Fiber Composite Based Transduction

Science.gov (United States)

2016-03-01

substrate Material properties of single crystal macro fiber composite actuators for active twist rotor blades Park, Jae-Sang (Seoul National...Passive Smart Structures and Integrated Systems 2007 Material properties of single crystal macro fiber composite actuators for active twist rotor ...19b. TELEPHONE NUMBER (Include area code) 10-03-20 16 Final Report 01 Jan 2013 - 31 Dec 2015 Macro-Fiber Composite Based Transduction N000-14-13-1-0212

Meso-Scale Modelling of Deformation, Damage and Failure in Dual Phase Steels

Science.gov (United States)

Sari Sarraf, Iman

Advanced high strength steels (AHSS), such as dual phase (DP) and transformation induced plasticity (TRIP) steels, offer high ductility, formability, and strength, as well as high strength-to-weight ratio and improved crash resistance. Dual phase steels belong to a family of high strength grades which consist of martensite, responsible for strengthening, distributed in a ductile ferrite matrix which accommodates the deformation throughout the forming process. It has been shown that the predominant damage mechanism and failure in DP steels depends on the ferrite and martensite grain sizes and their morphology, and can range from a mixture of brittle and ductile rupture to completely ductile rupture in a quasi-static uniaxial tension test. In this study, a hybrid finite element cellular automata model, initially proposed by Anton Shterenlikht (2003), was developed to evaluate the forming behaviour and predict the onset of instability and damage evolution in a dual phase steel. In this model, the finite element constitutive model is used to represent macro-level strain gradients and a damage variable, and two different cell arrays are designed to represent the ductile and brittle fracture modes in meso-scale. In the FE part of the model, a modified Rousselier ductile damage model is developed to account for nucleation, growth and coalescence of voids. Also, several rate-dependent hardening models were developed and evaluated to describe the work hardening flow curve of DP600. Based on statistical analysis and simulation results, a modified Johnson-Cook (JC) model and a multiplicative combination of the Voce-modified JC functions were found to be the most accurate hardening models. The developed models were then implemented in a user-defined material subroutine (VUMAT) for ABAQUS/Explicit finite element simulation software to simulate uniaxial tension tests at strain rates ranging from 0.001 1/s to 1000 1/s, Marciniak tests, and electrohydraulic free-forming (EHFF

Multi-scale individual-based model of microbial and bioconversion dynamics in aerobic granular sludge.

Science.gov (United States)

Xavier, Joao B; De Kreuk, Merle K; Picioreanu, Cristian; Van Loosdrecht, Mark C M

2007-09-15

Aerobic granular sludge is a novel compact biological wastewater treatment technology for integrated removal of COD (chemical oxygen demand), nitrogen, and phosphate charges. We present here a multiscale model of aerobic granular sludge sequencing batch reactors (GSBR) describing the complex dynamics of populations and nutrient removal. The macro scale describes bulk concentrations and effluent composition in six solutes (oxygen, acetate, ammonium, nitrite, nitrate, and phosphate). A finer scale, the scale of one granule (1.1 mm of diameter), describes the two-dimensional spatial arrangement of four bacterial groups--heterotrophs, ammonium oxidizers, nitrite oxidizers, and phosphate accumulating organisms (PAO)--using individual based modeling (IbM) with species-specific kinetic models. The model for PAO includes three internal storage compounds: polyhydroxyalkanoates (PHA), poly phosphate, and glycogen. Simulations of long-term reactor operation show how the microbial population and activity depends on the operating conditions. Short-term dynamics of solute bulk concentrations are also generated with results comparable to experimental data from lab scale reactors. Our results suggest that N-removal in GSBR occurs mostly via alternating nitrification/denitrification rather than simultaneous nitrification/denitrification, supporting an alternative strategy to improve N-removal in this promising wastewater treatment process.

Prediction of resource volumes at untested locations using simple local prediction models

Science.gov (United States)

Attanasi, E.D.; Coburn, T.C.; Freeman, P.A.

2006-01-01

This paper shows how local spatial nonparametric prediction models can be applied to estimate volumes of recoverable gas resources at individual undrilled sites, at multiple sites on a regional scale, and to compute confidence bounds for regional volumes based on the distribution of those estimates. An approach that combines cross-validation, the jackknife, and bootstrap procedures is used to accomplish this task. Simulation experiments show that cross-validation can be applied beneficially to select an appropriate prediction model. The cross-validation procedure worked well for a wide range of different states of nature and levels of information. Jackknife procedures are used to compute individual prediction estimation errors at undrilled locations. The jackknife replicates also are used with a bootstrap resampling procedure to compute confidence bounds for the total volume. The method was applied to data (partitioned into a training set and target set) from the Devonian Antrim Shale continuous-type gas play in the Michigan Basin in Otsego County, Michigan. The analysis showed that the model estimate of total recoverable volumes at prediction sites is within 4 percent of the total observed volume. The model predictions also provide frequency distributions of the cell volumes at the production unit scale. Such distributions are the basis for subsequent economic analyses. ?? Springer Science+Business Media, LLC 2007.

Multi-Scale Three-Dimensional Variational Data Assimilation System for Coastal Ocean Prediction

Science.gov (United States)

Li, Zhijin; Chao, Yi; Li, P. Peggy

2012-01-01

A multi-scale three-dimensional variational data assimilation system (MS-3DVAR) has been formulated and the associated software system has been developed for improving high-resolution coastal ocean prediction. This system helps improve coastal ocean prediction skill, and has been used in support of operational coastal ocean forecasting systems and field experiments. The system has been developed to improve the capability of data assimilation for assimilating, simultaneously and effectively, sparse vertical profiles and high-resolution remote sensing surface measurements into coastal ocean models, as well as constraining model biases. In this system, the cost function is decomposed into two separate units for the large- and small-scale components, respectively. As such, data assimilation is implemented sequentially from large to small scales, the background error covariance is constructed to be scale-dependent, and a scale-dependent dynamic balance is incorporated. This scheme then allows effective constraining large scales and model bias through assimilating sparse vertical profiles, and small scales through assimilating high-resolution surface measurements. This MS-3DVAR enhances the capability of the traditional 3DVAR for assimilating highly heterogeneously distributed observations, such as along-track satellite altimetry data, and particularly maximizing the extraction of information from limited numbers of vertical profile observations.

The relationship between venture capital investment and macro economic variables via statistical computation method

Science.gov (United States)

Aygunes, Gunes

2017-07-01

The objective of this paper is to survey and determine the macroeconomic factors affecting the level of venture capital (VC) investments in a country. The literary depends on venture capitalists' quality and countries' venture capital investments. The aim of this paper is to give relationship between venture capital investment and macro economic variables via statistical computation method. We investigate the countries and macro economic variables. By using statistical computation method, we derive correlation between venture capital investments and macro economic variables. According to method of logistic regression model (logit regression or logit model), macro economic variables are correlated with each other in three group. Venture capitalists regard correlations as a indicator. Finally, we give correlation matrix of our results.

WinBUGSio: A SAS Macro for the Remote Execution of WinBUGS

Directory of Open Access Journals (Sweden)

Michael K. Smith

2007-09-01

Full Text Available This is a macro which facilitates remote execution of WinBUGS from within SAS. The macro pre-processes data for WinBUGS, writes the WinBUGS batch-script, executes this script and reads in output statistics from the WinBUGS log-file back into SAS native format. The user specifies the input and output file names and directory path as well as the statistics to be monitored in WinBUGS. The code works best for a model that has already been set up and checked for convergence diagnostics within WinBUGS. An obvious extension of the use of this macro is for running simulations where the input and output files all have the same name but all that differs between simulation iterations is the input dataset. The functionality and syntax of the macro call are described in this paper and illustrated using a simple linear regression model.

A full description of the Three-ME model: Multi-sector macro-economic Model for the Evaluation of Environmental and Energy policy

International Nuclear Information System (INIS)

Callonnec, Gael; Landa, Gissela; Malliet, Paul; Yeddir-Tamsamani, Yasser; Reynes, Frederic

2013-01-01

Since 2008, the ADEME and the OFCE are involved in a research convention to develop the model Three-ME. This document provides a full description of new version of the model. Three-ME is a new model of the French economy especially designed to evaluate the medium and long term impact of environmental and energy policies at the macro-economic and sector levels. To do so Three-ME combines two important features. Firstly, it has the main characteristics of neo-Keynesian models by assuming a slow adjustment of effective quantities and prices to their notional level, an endogenous money supply, a Taylor rule and a Philips curve. Compared to standard multi-sector CGEM, this has the advantage to allow for the existence of under-optimum equilibria such as the presence of involuntary unemployment. Secondly, Three-ME is a hybrid model in the sense that it combines the top-down approach of general equilibrium macro-economic models with elements of bottom-up models of energy models developed by engineers. As in bottom-up models, the amount of energy consumed is related to their use, that is the number of buildings or cars, and the energy class to which they belong. This hypothesis is more realistic compared to the assumption made in the majority of top-down models where energy consumption is usually directly related to income through a nested structure of utility function. (authors)

A micro-macro acceleration method for the Monte Carlo simulation of stochastic differential equations

DEFF Research Database (Denmark)

Debrabant, Kristian; Samaey, Giovanni; Zieliński, Przemysław

2017-01-01

We present and analyse a micro-macro acceleration method for the Monte Carlo simulation of stochastic differential equations with separation between the (fast) time-scale of individual trajectories and the (slow) time-scale of the macroscopic function of interest. The algorithm combines short...

Prediction and optimisation of Pb/Zn/Fe sulphide scales in gas production fields

Energy Technology Data Exchange (ETDEWEB)

Dyer, Sarah; Orski, Karine; Menezes, Carlos; Heath, Steve; MacPherson, Calum; Simpson, Caroline; Graham, Gordon

2006-03-15

limitations of current thermodynamic models at predicting the type of sulphide scale which may occur. (author) (tk)

From micro-correlations to macro-correlations

International Nuclear Information System (INIS)

Eliazar, Iddo

2016-01-01

Random vectors with a symmetric correlation structure share a common value of pair-wise correlation between their different components. The symmetric correlation structure appears in a multitude of settings, e.g. mixture models. In a mixture model the components of the random vector are drawn independently from a general probability distribution that is determined by an underlying parameter, and the parameter itself is randomized. In this paper we study the overall correlation of high-dimensional random vectors with a symmetric correlation structure. Considering such a random vector, and terming its pair-wise correlation “micro-correlation”, we use an asymptotic analysis to derive the random vector’s “macro-correlation” : a score that takes values in the unit interval, and that quantifies the random vector’s overall correlation. The method of obtaining macro-correlations from micro-correlations is then applied to a diverse collection of frameworks that demonstrate the method’s wide applicability.

Ground-water solute transport modeling using a three-dimensional scaled model

International Nuclear Information System (INIS)

Crider, S.S.

1987-01-01

Scaled models are used extensively in current hydraulic research on sediment transport and solute dispersion in free surface flows (rivers, estuaries), but are neglected in current ground-water model research. Thus, an investigation was conducted to test the efficacy of a three-dimensional scaled model of solute transport in ground water. No previous results from such a model have been reported. Experiments performed on uniform scaled models indicated that some historical problems (e.g., construction and scaling difficulties; disproportionate capillary rise in model) were partly overcome by using simple model materials (sand, cement and water), by restricting model application to selective classes of problems, and by physically controlling the effect of the model capillary zone. Results from these tests were compared with mathematical models. Model scaling laws were derived for ground-water solute transport and used to build a three-dimensional scaled model of a ground-water tritium plume in a prototype aquifer on the Savannah River Plant near Aiken, South Carolina. Model results compared favorably with field data and with a numerical model. Scaled models are recommended as a useful additional tool for prediction of ground-water solute transport

The evaluation/application of Hydrus-2D model for simulating macro-pores flow in loess soil

OpenAIRE

Xuexuan Xu; Shahmir Ali Kalhoro; Wen yuan Chen; Sajjad Raza

2017-01-01

Soil hydraulic properties were mainly governed by soil structures especially when the structures is full of the connected soil macro-pores. Therefore, the good hydrological models need to be well documented for revealing the process of soil water movement affected by soil medium. The Hydrus-2D model with double domain was recommended in simulating water movement in a heterogeneous medium of soil. To evaluate the performance of the double domain Hydrus-2D model in loess soil, the dynamic of so...

Performance prediction of industrial centrifuges using scale-down models.

Science.gov (United States)

Boychyn, M; Yim, S S S; Bulmer, M; More, J; Bracewell, D G; Hoare, M

2004-12-01

Computational fluid dynamics was used to model the high flow forces found in the feed zone of a multichamber-bowl centrifuge and reproduce these in a small, high-speed rotating disc device. Linking the device to scale-down centrifugation, permitted good estimation of the performance of various continuous-flow centrifuges (disc stack, multichamber bowl, CARR Powerfuge) for shear-sensitive protein precipitates. Critically, the ultra scale-down centrifugation process proved to be a much more accurate predictor of production multichamber-bowl performance than was the pilot centrifuge.

The effect of micro and macro stressors in the work environment on computer professionals' subjective health status and productive behavior in Japan.

Science.gov (United States)

Tominaga, Maki; Asakura, Takashi; Akiyama, Tsuyoshi

2007-06-01

To investigate the effect of micro and macro stressors in the work environment on the subjective health status and productive behavior of computer professionals, we conducted a web-based investigation with Japanese IT-related company employees in 53 company unions. The questionnaire consisted of individual attributes, employment characteristics, working hour characteristics, company size and profitability, personal characteristics (i.e., Growth Need Strength), micro and macro stressors scale, and four outcome scales concerning the subjective health status and productive behavior. We obtained 1,049 Japanese IT-related company employees' data (response rate: 66%), and analyzed the data of computer engineers (80%; n=871). The results of hierarchical multiple regressions showed that each full model explained 23% in psychological distress, 20% in cumulative fatigue, 44% in job dissatisfaction, and 35% in intentions to leave, respectively. In micro stressors, "quantitative and qualitative work overload" had the strongest influence on both the subjective health status and intentions to leave. Furthermore, in macro stressors, "career and future ambiguity" was the most important predictor of the subjective health status, and "insufficient evaluation systems" and "poor supervisor's support" were important predictors of productive behavior as well. These findings suggest that improving not only micro stressors but also macro stressors will enhance the subjective health status and increase the productive behavior of computer professionals in Japan.

Credit Spread Modeling: Macro-financial versus HOC Approach

Directory of Open Access Journals (Sweden)

Sanja Dudaković

2014-12-01

Full Text Available The aim of this paper is to throw light on the relationship between credit spread changes and past changes of U.S. macro-financial variables when invariants do not have Gaussian distribution. The first part presents the empirical analysis which is based on 10-year AAA corporate bond yields and 10-year Treasury bond yields. Explanatory variables include lagged U.S. leading index, Russell 2000 returns, BBB bond price changes interest rate swaps, exchange rates EUR/ USD, Repo rates, S& P 500 returns and S&P 500 volatility, Treasury bill changes, liquidity index-TRSW, LIBOR rates, Moody’s default rates; credit spread volatility and Treasury bills volatility. The proposed dynamical model explains 73% of the U.S. credit spread variance for the period 1999:07-2013:07. The second part of the article introduces the parameter estimation method based on higher order cumulants. It is demonstrated empirically that much of the information about variability of Credit Spread can be extracted from higher order cumulant function (85%.

3-D CFD modeling and experimental testing of thermal behavior of a Li-Ion battery

International Nuclear Information System (INIS)

Gümüşsu, Emre; Ekici, Özgür; Köksal, Murat

2017-01-01

Highlights: • A thermally fully predictive 3-D CFD model is developed for Li-Ion batteries. • Complete flow field around the battery and conduction inside the battery are solved. • Macro-scale thermophysical properties and the entropic term are investigated. • Discharge rate and usage history of the battery are systematically investigated. • Reliability of the model was tested through experimental measurements. - Abstract: In this study, a 3-D computational fluid dynamics model was developed for investigating the thermal behavior of lithium ion batteries under natural convection. The model solves the complete flow field around the battery as well as conduction inside the battery using the well-known heat generation model of Bernardi et al. (1985). The model is thermally fully predictive so it requires only electrical performance parameters of the battery to calculate its temperature during discharging. Using the model, detailed investigation of the effects of the variation of the macro-scale thermophysical properties and the entropic term of the heat generation model was carried out. Results show that specific heat is a critical property that has a significant impact on the simulation results whereas thermal conductivity has relatively minor importance. Moreover, the experimental data can be successfully predicted without taking the entropic term into account in the calculation of the heat generation. The difference between the experimental and predicted battery surface temperature was less than 3 °C for all discharge rates and regardless of the usage history of the battery. The developed model has the potential to be used for the investigation of the thermal behavior of Li-Ion batteries in different packaging configurations under natural and forced convection.

Why Macro Practice Matters

Science.gov (United States)

Reisch, Michael

2016-01-01

This article asserts that macro practice is increasingly important in today's rapidly changing and complex practice environment. It briefly explores the history of macro practice in U.S. social work, summarizes its major contributions to the profession and to U.S. society, and provides some suggestions for how social work programs can expand…

Improving Prediction of Large-scale Regime Transitions

Science.gov (United States)

Gyakum, J. R.; Roebber, P.; Bosart, L. F.; Honor, A.; Bunker, E.; Low, Y.; Hart, J.; Bliankinshtein, N.; Kolly, A.; Atallah, E.; Huang, Y.

2017-12-01

Cool season atmospheric predictability over the CONUS on subseasonal times scales (1-4 weeks) is critically dependent upon the structure, configuration, and evolution of the North Pacific jet stream (NPJ). The NPJ can be perturbed on its tropical side on synoptic time scales by recurving and transitioning tropical cyclones (TCs) and on subseasonal time scales by longitudinally varying convection associated with the Madden-Julian Oscillation (MJO). Likewise, the NPJ can be perturbed on its poleward side on synoptic time scales by midlatitude and polar disturbances that originate over the Asian continent. These midlatitude and polar disturbances can often trigger downstream Rossby wave propagation across the North Pacific, North America, and the North Atlantic. The project team is investigating the following multiscale processes and features: the spatiotemporal distribution of cyclone clustering over the Northern Hemisphere; cyclone clustering as influenced by atmospheric blocking and the phases and amplitudes of the major teleconnection indices, ENSO and the MJO; composite and case study analyses of representative cyclone clustering events to establish the governing dynamics; regime change predictability horizons associated with cyclone clustering events; Arctic air mass generation and modification; life cycles of the MJO; and poleward heat and moisture transports of subtropical air masses. A critical component of the study is weather regime classification. These classifications are defined through: the spatiotemporal clustering of surface cyclogenesis; a general circulation metric combining data at 500-hPa and the dynamic tropopause; Self Organizing Maps (SOM), constructed from dynamic tropopause and 850 hPa equivalent potential temperature data. The resultant lattice of nodes is used to categorize synoptic classes and their predictability, as well as to determine the robustness of the CFSv2 model climate relative to observations. Transition pathways between these

Distributed Model Predictive Control over Multiple Groups of Vehicles in Highway Intelligent Space for Large Scale System

Directory of Open Access Journals (Sweden)

Tang Xiaofeng

2014-01-01

Full Text Available The paper presents the three time warning distances for solving the large scale system of multiple groups of vehicles safety driving characteristics towards highway tunnel environment based on distributed model prediction control approach. Generally speaking, the system includes two parts. First, multiple vehicles are divided into multiple groups. Meanwhile, the distributed model predictive control approach is proposed to calculate the information framework of each group. Each group of optimization performance considers the local optimization and the neighboring subgroup of optimization characteristics, which could ensure the global optimization performance. Second, the three time warning distances are studied based on the basic principles used for highway intelligent space (HIS and the information framework concept is proposed according to the multiple groups of vehicles. The math model is built to avoid the chain avoidance of vehicles. The results demonstrate that the proposed highway intelligent space method could effectively ensure driving safety of multiple groups of vehicles under the environment of fog, rain, or snow.

Prediction of Hydraulic Performance of a Scaled-Down Model of SMART Reactor Coolant Pump

Energy Technology Data Exchange (ETDEWEB)

Kwon, Sun Guk; Park, Jin Seok; Yu, Je Yong; Lee, Won Jae [Korea Atomic Energy Research Institute, Daejeon (Korea, Republic of)

2010-08-15

An analysis was conducted to predict the hydraulic performance of a reactor coolant pump (RCP) of SMART at the off-design as well as design points. In order to reduce the analysis time efficiently, a single passage containing an impeller and a diffuser was considered as the computational domain. A stage scheme was used to perform a circumferential averaging of the flux on the impeller-diffuser interface. The pressure difference between the inlet and outlet of the pump was determined and was used to compute the head, efficiency, and break horse power (BHP) of a scaled-down model under conditions of steady-state incompressible flow. The predicted curves of the hydraulic performance of an RCP were similar to the typical characteristic curves of a conventional mixed-flow pump. The complex internal fluid flow of a pump, including the internal recirculation loss due to reverse flow, was observed at a low flow rate.

Plant interactions alter the predictions of metabolic scaling theory.

Directory of Open Access Journals (Sweden)

Yue Lin

Full Text Available Metabolic scaling theory (MST is an attempt to link physiological processes of individual organisms with macroecology. It predicts a power law relationship with an exponent of -4/3 between mean individual biomass and density during density-dependent mortality (self-thinning. Empirical tests have produced variable results, and the validity of MST is intensely debated. MST focuses on organisms' internal physiological mechanisms but we hypothesize that ecological interactions can be more important in determining plant mass-density relationships induced by density. We employ an individual-based model of plant stand development that includes three elements: a model of individual plant growth based on MST, different modes of local competition (size-symmetric vs. -asymmetric, and different resource levels. Our model is consistent with the observed variation in the slopes of self-thinning trajectories. Slopes were significantly shallower than -4/3 if competition was size-symmetric. We conclude that when the size of survivors is influenced by strong ecological interactions, these can override predictions of MST, whereas when surviving plants are less affected by interactions, individual-level metabolic processes can scale up to the population level. MST, like thermodynamics or biomechanics, sets limits within which organisms can live and function, but there may be stronger limits determined by ecological interactions. In such cases MST will not be predictive.

Coupling between cracking and permeability, a model for structure service life prediction

International Nuclear Information System (INIS)

Lasne, M.; Gerard, B.; Breysse, D.

1993-01-01

Many authors have chosen permeability coefficients (permeation, diffusion) as a reference for material durability and for structure service life prediction. When we look for designing engineered barriers for radioactive waste storage we find these macroscopic parameters very essential. In order to work with a predictive model of transfer properties evolution in a porous media (concrete, mortar, rock) we introduce a 'micro-macro' hierarchical model of permeability whose data are the total porosity and the pore size distribution. In spite of the simplicity of the model (very small CPU time consuming) comparative studies show predictive results for sound cement pastes, mortars and concretes. Associated to these works we apply a model of damage due to hydration processes at early ages to a container as a preliminary underproject for the definitive storage of Low Level radioactive Waste (LLW). Data are geometry, cement properties and damage measurement of concrete. This model takes into account the mechanical property of the concrete maturation (volumic variations during cement hydration can damage the structures). Some local microcracking can appear and affect the long term durability. Following these works we introduce our research program for the concrete cracking analysis. An experimental campaign is designed in order to determine damage-cracking-porosity-permeability coupling. (authors). 12 figs., 16 refs

Spreadsheet macros for coloring sequence alignments.

Science.gov (United States)

Haygood, M G

1993-12-01

This article describes a set of Microsoft Excel macros designed to color amino acid and nucleotide sequence alignments for review and preparation of visual aids. The colored alignments can then be modified to emphasize features of interest. Procedures for importing and coloring sequences are described. The macro file adds a new menu to the menu bar containing sequence-related commands to enable users unfamiliar with Excel to use the macros more readily. The macros were designed for use with Macintosh computers but will also run with the DOS version of Excel.

Multi-scale Modeling of Plasticity in Tantalum.

Energy Technology Data Exchange (ETDEWEB)

Lim, Hojun [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Battaile, Corbett Chandler. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Carroll, Jay [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Buchheit, Thomas E. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Boyce, Brad [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Weinberger, Christopher [Drexel Univ., Philadelphia, PA (United States)

2015-12-01

In this report, we present a multi-scale computational model to simulate plastic deformation of tantalum and validating experiments. In atomistic/ dislocation level, dislocation kink- pair theory is used to formulate temperature and strain rate dependent constitutive equations. The kink-pair theory is calibrated to available data from single crystal experiments to produce accurate and convenient constitutive laws. The model is then implemented into a BCC crystal plasticity finite element method (CP-FEM) model to predict temperature and strain rate dependent yield stresses of single and polycrystalline tantalum and compared with existing experimental data from the literature. Furthermore, classical continuum constitutive models describing temperature and strain rate dependent flow behaviors are fit to the yield stresses obtained from the CP-FEM polycrystal predictions. The model is then used to conduct hydro- dynamic simulations of Taylor cylinder impact test and compared with experiments. In order to validate the proposed tantalum CP-FEM model with experiments, we introduce a method for quantitative comparison of CP-FEM models with various experimental techniques. To mitigate the effects of unknown subsurface microstructure, tantalum tensile specimens with a pseudo-two-dimensional grain structure and grain sizes on the order of millimeters are used. A technique combining an electron back scatter diffraction (EBSD) and high resolution digital image correlation (HR-DIC) is used to measure the texture and sub-grain strain fields upon uniaxial tensile loading at various applied strains. Deformed specimens are also analyzed with optical profilometry measurements to obtain out-of- plane strain fields. These high resolution measurements are directly compared with large-scale CP-FEM predictions. This computational method directly links fundamental dislocation physics to plastic deformations in the grain-scale and to the engineering-scale applications. Furthermore, direct

Micro-flock patterns and macro-clusters in chiral active Brownian disks

Science.gov (United States)

Levis, Demian; Liebchen, Benno

2018-02-01

Chiral active particles (or self-propelled circle swimmers) feature a rich collective behavior, comprising rotating macro-clusters and micro-flock patterns which consist of phase-synchronized rotating clusters with a characteristic self-limited size. These patterns emerge from the competition of alignment interactions and rotations suggesting that they might occur generically in many chiral active matter systems. However, although excluded volume interactions occur naturally among typical circle swimmers, it is not yet clear if macro-clusters and micro-flock patterns survive their presence. The present work shows that both types of pattern do survive but feature strongly enhance fluctuations regarding the size and shape of the individual clusters. Despite these fluctuations, we find that the average micro-flock size still follows the same characteristic scaling law as in the absence of excluded volume interactions, i.e. micro-flock sizes scale linearly with the single-swimmer radius.

The Volatility of Indonesia Shari’ah Capital Market Stock Price Toward Macro Economics Variable

Directory of Open Access Journals (Sweden)

Helma Malini

2014-08-01

Full Text Available Shari’ah stock market is also affected by many highly interrelated economic, social, political andother factor, same as the conventional stock market, the interaction between macroeconomic variablesand Shari’ah stock market creating volatility in the stock price as a response towards severalshocks. The sensitivity of Shari’ah stock market towards shocks happened related with the futureexpectation of micro and macro factor in one country which can be predict or unpredictable.There are six macroeconomic variables that used in this research; inflation, exchange rate, interestrate, dow jones index, crude oil palm price, and FED rate. Using vector error correction model(VECM, the result shows that domestic macroeconomic variables that significantly affect IndonesiaShari’ah compliance for long term, while for international macroeconomic variables the selectedvariable such as FED rate and Dow Jones Index are not significantly affected Indonesia Shari’ahcompliance both in short term and long term. Keywords: Indonesia Shari’ah compliance, Macro Economic Indicators, Impulse Response Function,Stock Price Volatility

Scale Issues in the Assessment of Pesticide Leaching Vulnerability for Loamy Structured Soils in Denmark

DEFF Research Database (Denmark)

van der Keur, Peter; Iversen, Bo Vangsø; Hollis, John

type as derived by the European scale method and also derived from a neural network type PTF at the national high spatial resolution. Simulations of pesticide leaching by the one-dimensional numerical water flow and reactive solute transport model MACRO are performed for low and high values of near...... soil classes according to the first method 1 does not match the scale at a required finer scale for vulnerability mapping. Finally, the method employing a coupled MACRO-MIKE SHE catchment scale approach shows that climate change resulting in altered rainfall intensities and patterns as well as changed...

Joint Macro and Femto Field Performance and Interference Measurements

DEFF Research Database (Denmark)

Jørgensen, Niels T.K.; Isotalo, Tero; Pedersen, Klaus

2012-01-01

In this paper macro performance in a co-channel macro and femto setup is studied. Measurements are performed in a live Universal Mobile Telecommunication System (UMTS) network. It is concluded that femto interference does not affect macro downlink (DL) performance as long as the macro Received Si...... radius smaller than 5 meter – with realistic power settings. This makes co-channel femto deployment less promising in dense macro environments with good macro RSCP coverage.......In this paper macro performance in a co-channel macro and femto setup is studied. Measurements are performed in a live Universal Mobile Telecommunication System (UMTS) network. It is concluded that femto interference does not affect macro downlink (DL) performance as long as the macro Received...... Signal Code Power (RSCP) is stronger than femto RSCP. We also conclude that a macro escape carrier is a robust DL interference management solution. In uplink (UL) direction it is shown that a single femto UE close to macro cell potentially can cause a noise rise of 6 dB in the surrounding macro cell...

The integrated evaluation of the macro environment of companies providing transport services

Directory of Open Access Journals (Sweden)

A. Žvirblis

2008-09-01

Full Text Available The article presents the main principles of the integrated evaluation of macro environment components and factors influencing the performance of transport companies as well as providing the validated quantitative evaluation models and results obtained in evaluating the macro environment of Lithuanian companies providing transport services. Since quantitative evaluation is growing in importance, the process of developing the principles and methods of business macro environment quantitative evaluation is becoming relevant from both theoretical and practical perspectives. The created methodology is based on the concept of macro environment as an integrated whole of components, formalization and the principle of three-stage quantitative evaluation. The methodology suggested involves the quantitative evaluation of primary factors and macro environment components as an integral dimension (expressed in points. On the basis of this principle, an integrated macro environment evaluation parameter is established as its level index. The methodology integrates the identification of significant factors, building scenarios, a primary analysis of factors, expert evaluation, the quantitative evaluation of macro environment components and their whole. The application of the multi-criteria Simple Additive Weighting (SAW method is validated. The integrated evaluation of the macro environment of Lithuanian freight transportation companies was conducted. As a result, the level indices of all components as well as the level index of macro environment considered as a whole of components were identified. The latter reflects the extent of deviation from an average level of a favourable macro environment. This is important for developing strategic marketing decisions and expanding a strategic area.

Time to death and the forecasting of macro-level health care expenditures: some further considerations.

Science.gov (United States)

van Baal, Pieter H; Wong, Albert

2012-12-01

Although the effect of time to death (TTD) on health care expenditures (HCE) has been investigated using individual level data, the most profound implications of TTD have been for the forecasting of macro-level HCE. Here we estimate the TTD model using macro-level data from the Netherlands consisting of mortality rates and age- and gender-specific per capita health expenditures for the years 1981-2007. Forecasts for the years 2008-2020 of this macro-level TTD model were compared to forecasts that excluded TTD. Results revealed that the effect of TTD on HCE in our macro model was similar to those found in micro-econometric studies. As the inclusion of TTD pushed growth rate estimates from unidentified causes upwards, however, the two models' forecasts of HCE for the 2008-2020 were similar. We argue that including TTD, if modeled correctly, does not lower forecasts of HCE. Copyright © 2012 Elsevier B.V. All rights reserved.

An integrated analysis of micro- and macro-habitat features as a tool to detect weather-driven constraints: A case study with cavity nesters.

Directory of Open Access Journals (Sweden)

D Campobello

Full Text Available The effects of climate change on animal populations may be shaped by habitat characteristics at both micro- and macro-habitat level, however, empirical studies integrating these two scales of observation are lacking. As analyses of the effects of climate change commonly rely on data from a much larger scale than the microhabitat level organisms are affected at, this mismatch risks hampering progress in developing understanding of the details of the ecological and evolutionary responses of organisms and, ultimately, effective actions to preserve their populations. Cavity nesters, often with a conservation status of concern, are an ideal model because the cavity is a microenvironment potentially different from the macroenvironment but nonetheless inevitably interacting with it. The lesser kestrel (Falco naumanni is a cavity nester which was until recently classified by as Vulnerable species. Since 2004, for nine years, we collected detailed biotic and abiotic data at both micro- and macro-scales of observation in a kestrel population breeding in the Gela Plain (Italy, a Mediterranean area where high temperatures may reach lethal values for the nest content. We show that macroclimatic features needed to be integrated with both abiotic and biotic factors recorded at a microscale before reliably predicting nest temperatures. Among the nest types used by lesser kestrels, we detected a preferential occupation of the cooler nest types, roof tiles, by early breeders whereas, paradoxically, late breeders nesting with hotter temperatures occupied the overheated nest holes. Not consistent with such a suggested nest selection, the coolest nest type did not host a higher reproductive success than the overheated nests. We discussed our findings in the light of cavity temperatures and nest types deployed within conservation actions assessed by integrating selected factors at different observation scales.

An integrated analysis of micro- and macro-habitat features as a tool to detect weather-driven constraints: A case study with cavity nesters.

Science.gov (United States)

Campobello, D; Lindström, J; Di Maggio, R; Sarà, M

2017-01-01

The effects of climate change on animal populations may be shaped by habitat characteristics at both micro- and macro-habitat level, however, empirical studies integrating these two scales of observation are lacking. As analyses of the effects of climate change commonly rely on data from a much larger scale than the microhabitat level organisms are affected at, this mismatch risks hampering progress in developing understanding of the details of the ecological and evolutionary responses of organisms and, ultimately, effective actions to preserve their populations. Cavity nesters, often with a conservation status of concern, are an ideal model because the cavity is a microenvironment potentially different from the macroenvironment but nonetheless inevitably interacting with it. The lesser kestrel (Falco naumanni) is a cavity nester which was until recently classified by as Vulnerable species. Since 2004, for nine years, we collected detailed biotic and abiotic data at both micro- and macro-scales of observation in a kestrel population breeding in the Gela Plain (Italy), a Mediterranean area where high temperatures may reach lethal values for the nest content. We show that macroclimatic features needed to be integrated with both abiotic and biotic factors recorded at a microscale before reliably predicting nest temperatures. Among the nest types used by lesser kestrels, we detected a preferential occupation of the cooler nest types, roof tiles, by early breeders whereas, paradoxically, late breeders nesting with hotter temperatures occupied the overheated nest holes. Not consistent with such a suggested nest selection, the coolest nest type did not host a higher reproductive success than the overheated nests. We discussed our findings in the light of cavity temperatures and nest types deployed within conservation actions assessed by integrating selected factors at different observation scales.

Evaluation of performance of seasonal precipitation prediction at regional scale over India

Science.gov (United States)

Mohanty, U. C.; Nageswararao, M. M.; Sinha, P.; Nair, A.; Singh, A.; Rai, R. K.; Kar, S. C.; Ramesh, K. J.; Singh, K. K.; Ghosh, K.; Rathore, L. S.; Sharma, R.; Kumar, A.; Dhekale, B. S.; Maurya, R. K. S.; Sahoo, R. K.; Dash, G. P.

2018-03-01

The seasonal scale precipitation amount is an important ingredient in planning most of the agricultural practices (such as a type of crops, and showing and harvesting schedules). India being an agroeconomic country, the seasonal scale prediction of precipitation is directly linked to the socioeconomic growth of the nation. At present, seasonal precipitation prediction at regional scale is a challenging task for the scientific community. In the present study, an attempt is made to develop multi-model dynamical-statistical approach for seasonal precipitation prediction at the regional scale (meteorological subdivisions) over India for four prominent seasons which are winter (from December to February; DJF), pre-monsoon (from March to May; MAM), summer monsoon (from June to September; JJAS), and post-monsoon (from October to December; OND). The present prediction approach is referred as extended range forecast system (ERFS). For this purpose, precipitation predictions from ten general circulation models (GCMs) are used along with the India Meteorological Department (IMD) rainfall analysis data from 1982 to 2008 for evaluation of the performance of the GCMs, bias correction of the model results, and development of the ERFS. An extensive evaluation of the performance of the ERFS is carried out with dependent data (1982-2008) as well as independent predictions for the period 2009-2014. In general, the skill of the ERFS is reasonably better and consistent for all the seasons and different regions over India as compared to the GCMs and their simple mean. The GCM products failed to explain the extreme precipitation years, whereas the bias-corrected GCM mean and the ERFS improved the prediction and well represented the extremes in the hindcast period. The peak intensity, as well as regions of maximum precipitation, is better represented by the ERFS than the individual GCMs. The study highlights the improvement of forecast skill of the ERFS over 34 meteorological subdivisions

Preparing the Model for Prediction Across Scales (MPAS) for global retrospective air quality modeling

Science.gov (United States)

The US EPA has a plan to leverage recent advances in meteorological modeling to develop a "Next-Generation" air quality modeling system that will allow consistent modeling of problems from global to local scale. The meteorological model of choice is the Model for Predic...

Macro-SICM: A Scanning Ion Conductance Microscope for Large-Range Imaging.

Science.gov (United States)

Schierbaum, Nicolas; Hack, Martin; Betz, Oliver; Schäffer, Tilman E

2018-04-17

The scanning ion conductance microscope (SICM) is a versatile, high-resolution imaging technique that uses an electrolyte-filled nanopipet as a probe. Its noncontact imaging principle makes the SICM uniquely suited for the investigation of soft and delicate surface structures in a liquid environment. The SICM has found an ever-increasing number of applications in chemistry, physics, and biology. However, a drawback of conventional SICMs is their relatively small scan range (typically 100 μm × 100 μm in the lateral and 10 μm in the vertical direction). We have developed a Macro-SICM with an exceedingly large scan range of 25 mm × 25 mm in the lateral and 0.25 mm in the vertical direction. We demonstrate the high versatility of the Macro-SICM by imaging at different length scales: from centimeters (fingerprint, coin) to millimeters (bovine tongue tissue, insect wing) to micrometers (cellular extensions). We applied the Macro-SICM to the study of collective cell migration in epithelial wound healing.

Modelling the transport and decay processes of microbial tracers in a macro-tidal estuary.

Science.gov (United States)

Abu-Bakar, Amyrhul; Ahmadian, Reza; Falconer, Roger A

2017-10-15

The Loughor Estuary is a macro-tidal coastal basin, located along the Bristol Channel, in the South West of the U.K. The maximum spring tidal range in the estuary is up to 7.5 m, near Burry Port Harbour. This estuarine region can experience severe coastal flooding during high spring tides, including extreme flooding of the intertidal saltmarshes at Llanrhidian, as well as the lower industrial and residential areas at Llanelli and Gowerton. The water quality of this estuarine basin needs to comply with the designated standards for safe recreational bathing and shellfish harvesting industries. The waterbody however, potentially receives overloading of bacterial inputs that enter the estuarine system from both point and diffuse sources. Therefore, a microbial tracer study was carried out to get a better understanding of the faecal bacteria sources and to enable a hydro-environmental model to be refined and calibrated for both advection and dispersion transport. A two-dimensional hydro-environmental model has been refined and extended to predict the highest water level covering the intertidal floodplains of the Loughor Estuary. The validated hydrodynamic model for both water levels and currents, was included with the injected mass of microbial tracer, i.e. MS2 coliphage from upstream of the estuary, and modelled as a non-conservative tracer over several tidal cycles through the system. The calibration and validation of the transport and decay of microbial tracer was undertaken, by comparing the model results and the measured data at two different sampling locations. The refined model developed as a part of this study, was used to acquire a better understanding of the water quality processes and the potential sources of bacterial pollution in the estuary. Copyright © 2017 Elsevier Ltd. All rights reserved.

A neuro-fuzzy model to predict the inflow to the guardialfiera multipurpose dam (Southern Italy at medium-long time scales

Directory of Open Access Journals (Sweden)

L.F. Termite

2013-09-01

Full Text Available Intelligent computing tools based on fuzzy logic and artificial neural networks have been successfully applied in various problems with superior performances. A new approach of combining these two powerful tools, known as neuro-fuzzy systems, has increasingly attracted scientists in different fields. Few studies have been undertaken to evaluate their performances in hydrologic modeling. Specifically are available rainfall-runoff modeling typically at very short time scales (hourly, daily or event for the real-time forecasting of floods with in input precipitation and past runoff (i.e. inflow rate and in few cases models for the prediction of the monthly inflows to a dam using the past inflows as input. This study presents an application of an Adaptive Network-based Fuzzy Inference System (ANFIS, as a neuro-fuzzy-computational technique, in the forecasting of the inflow to the Guardialfiera multipurpose dam (CB, Italy at the weekly and monthly time scale. The latter has been performed both directly at monthly scale (monthly input data and iterating the weekly model. Twenty-nine years of rainfall, temperature, water level in the reservoir and releases to the different uses were available. In all simulations meteorological input data were used and in some cases also the past inflows. The performance of the defined ANFIS models were established by different efficiency and correlation indices. The results at the weekly time scale can be considered good, with a Nash- Sutcliffe efficiency index E = 0.724 in the testing phase. At the monthly time scale, satisfactory results were obtained with the iteration of the weekly model for the prediction of the incoming volume up to 3 weeks ahead (E = 0.574, while the direct simulation of monthly inflows gave barely satisfactory results (E = 0.502. The greatest difficulties encountered in the analysis were related to the reliability of the available data. The results of this study demonstrate the promising

Loading Intensity Prediction by Velocity and the OMNI-RES 0-10 Scale in Bench Press.

Science.gov (United States)

Naclerio, Fernando; Larumbe-Zabala, Eneko

2017-02-01

Naclerio, F and Larumbe-Zabala, E. Loading intensity prediction by velocity and the OMNI-RES 0-10 scale in bench press. J Strength Cond Res 32(1): 323-329, 2017-This study examined the possibility of using movement velocity and the perceived exertion as indicators of relative load in the bench press (BP) exercise. A total of 308 young, healthy, resistance trained athletes (242 men and 66 women) performed a progressive strength test up to the one repetition maximum for the individual determination of the full load-velocity and load-exertion relationships. Longitudinal regression models were used to predict the relative load from the average velocity (AV) and the OMNI-Resistance Exercise Scales (OMNI-RES 0-10 scale), considering sets as the time-related variable. Load associated with the AV and the OMNI-RES 0-10 scale value expressed after performing a set of 1-3 repetitions were used to construct 2 adjusted predictive equations: Relative load = 107.75 - 62.97 × average velocity; and Relative load = 29.03 + 7.26 × OMNI-RES 0-10 scale value. The 2 models were capable of estimating the relative load with an accuracy of 84 and 93%, respectively. These findings confirm the ability of the 2 calculated regression models, using load-velocity and load-exertion from the OMNI-RES 0-10 scale, to accurately predict strength performance in BP.

Scaling Effects on Materials Tribology: From Macro to Micro Scale.

Science.gov (United States)

Stoyanov, Pantcho; Chromik, Richard R

2017-05-18

The tribological study of materials inherently involves the interaction of surface asperities at the micro to nanoscopic length scales. This is the case for large scale engineering applications with sliding contacts, where the real area of contact is made up of small contacting asperities that make up only a fraction of the apparent area of contact. This is why researchers have sought to create idealized experiments of single asperity contacts in the field of nanotribology. At the same time, small scale engineering structures known as micro- and nano-electromechanical systems (MEMS and NEMS) have been developed, where the apparent area of contact approaches the length scale of the asperities, meaning the real area of contact for these devices may be only a few asperities. This is essentially the field of microtribology, where the contact size and/or forces involved have pushed the nature of the interaction between two surfaces towards the regime where the scale of the interaction approaches that of the natural length scale of the features on the surface. This paper provides a review of microtribology with the purpose to understand how tribological processes are different at the smaller length scales compared to macrotribology. Studies of the interfacial phenomena at the macroscopic length scales (e.g., using in situ tribometry) will be discussed and correlated with new findings and methodologies at the micro-length scale.

Drift-Scale Coupled Processes (DST and THC Seepage) Models

International Nuclear Information System (INIS)

Dixon, P.

2004-01-01

The purpose of this Model Report (REV02) is to document the unsaturated zone (UZ) models used to evaluate the potential effects of coupled thermal-hydrological-chemical (THC) processes on UZ flow and transport. This Model Report has been developed in accordance with the ''Technical Work Plan for: Performance Assessment Unsaturated Zone'' (Bechtel SAIC Company, LLC (BSC) 2002 [160819]). The technical work plan (TWP) describes planning information pertaining to the technical scope, content, and management of this Model Report in Section 1.12, Work Package AUZM08, ''Coupled Effects on Flow and Seepage''. The plan for validation of the models documented in this Model Report is given in Attachment I, Model Validation Plans, Section I-3-4, of the TWP. Except for variations in acceptance criteria (Section 4.2), there were no deviations from this TWP. This report was developed in accordance with AP-SIII.10Q, ''Models''. This Model Report documents the THC Seepage Model and the Drift Scale Test (DST) THC Model. The THC Seepage Model is a drift-scale process model for predicting the composition of gas and water that could enter waste emplacement drifts and the effects of mineral alteration on flow in rocks surrounding drifts. The DST THC model is a drift-scale process model relying on the same conceptual model and much of the same input data (i.e., physical, hydrological, thermodynamic, and kinetic) as the THC Seepage Model. The DST THC Model is the primary method for validating the THC Seepage Model. The DST THC Model compares predicted water and gas compositions, as well as mineral alteration patterns, with observed data from the DST. These models provide the framework to evaluate THC coupled processes at the drift scale, predict flow and transport behavior for specified thermal-loading conditions, and predict the evolution of mineral alteration and fluid chemistry around potential waste emplacement drifts. The DST THC Model is used solely for the validation of the THC

Flexible non-linear predictive models for large-scale wind turbine diagnostics

DEFF Research Database (Denmark)

Bach-Andersen, Martin; Rømer-Odgaard, Bo; Winther, Ole

2017-01-01

We demonstrate how flexible non-linear models can provide accurate and robust predictions on turbine component temperature sensor data using data-driven principles and only a minimum of system modeling. The merits of different model architectures are evaluated using data from a large set...... of turbines operating under diverse conditions. We then go on to test the predictive models in a diagnostic setting, where the output of the models are used to detect mechanical faults in rotor bearings. Using retrospective data from 22 actual rotor bearing failures, the fault detection performance...... of the models are quantified using a structured framework that provides the metrics required for evaluating the performance in a fleet wide monitoring setup. It is demonstrated that faults are identified with high accuracy up to 45 days before a warning from the hard-threshold warning system....

Modeling heat efficiency, flow and scale-up in the corotating disc scraped surface heat exchanger

DEFF Research Database (Denmark)

Friis, Alan; Szabo, Peter; Karlson, Torben

2002-01-01

A comparison of two different scale corotating disc scraped surface heat exchangers (CDHE) was performed experimentally. The findings were compared to predictions from a finite element model. We find that the model predicts well the flow pattern of the two CDHE's investigated. The heat transfer...... performance predicted by the model agrees well with experimental observations for the laboratory scale CDHE whereas the overall heat transfer in the scaled-up version was not in equally good agreement. The lack of the model to predict the heat transfer performance in scale-up leads us to identify the key...

Implementation of the ANNs ensembles in macro-BIM cost estimates of buildings' floor structural frames

Science.gov (United States)

Juszczyk, Michał

2018-04-01

This paper reports some results of the studies on the use of artificial intelligence tools for the purposes of cost estimation based on building information models. A problem of the cost estimates based on the building information models on a macro level supported by the ensembles of artificial neural networks is concisely discussed. In the course of the research a regression model has been built for the purposes of cost estimation of buildings' floor structural frames, as higher level elements. Building information models are supposed to serve as a repository of data used for the purposes of cost estimation. The core of the model is the ensemble of neural networks. The developed model allows the prediction of cost estimates with satisfactory accuracy.

Quantitative Missense Variant Effect Prediction Using Large-Scale Mutagenesis Data.

Science.gov (United States)

Gray, Vanessa E; Hause, Ronald J; Luebeck, Jens; Shendure, Jay; Fowler, Douglas M

2018-01-24

Large datasets describing the quantitative effects of mutations on protein function are becoming increasingly available. Here, we leverage these datasets to develop Envision, which predicts the magnitude of a missense variant's molecular effect. Envision combines 21,026 variant effect measurements from nine large-scale experimental mutagenesis datasets, a hitherto untapped training resource, with a supervised, stochastic gradient boosting learning algorithm. Envision outperforms other missense variant effect predictors both on large-scale mutagenesis data and on an independent test dataset comprising 2,312 TP53 variants whose effects were measured using a low-throughput approach. This dataset was never used for hyperparameter tuning or model training and thus serves as an independent validation set. Envision prediction accuracy is also more consistent across amino acids than other predictors. Finally, we demonstrate that Envision's performance improves as more large-scale mutagenesis data are incorporated. We precompute Envision predictions for every possible single amino acid variant in human, mouse, frog, zebrafish, fruit fly, worm, and yeast proteomes (https://envision.gs.washington.edu/). Copyright © 2017 Elsevier Inc. All rights reserved.

A unified algorithm for predicting partition coefficients for PBPK modeling of drugs and environmental chemicals

International Nuclear Information System (INIS)

Peyret, Thomas; Poulin, Patrick; Krishnan, Kannan

2010-01-01

The algorithms in the literature focusing to predict tissue:blood PC (P tb ) for environmental chemicals and tissue:plasma PC based on total (K p ) or unbound concentration (K pu ) for drugs differ in their consideration of binding to hemoglobin, plasma proteins and charged phospholipids. The objective of the present study was to develop a unified algorithm such that P tb , K p and K pu for both drugs and environmental chemicals could be predicted. The development of the unified algorithm was accomplished by integrating all mechanistic algorithms previously published to compute the PCs. Furthermore, the algorithm was structured in such a way as to facilitate predictions of the distribution of organic compounds at the macro (i.e. whole tissue) and micro (i.e. cells and fluids) levels. The resulting unified algorithm was applied to compute the rat P tb , K p or K pu of muscle (n = 174), liver (n = 139) and adipose tissue (n = 141) for acidic, neutral, zwitterionic and basic drugs as well as ketones, acetate esters, alcohols, aliphatic hydrocarbons, aromatic hydrocarbons and ethers. The unified algorithm reproduced adequately the values predicted previously by the published algorithms for a total of 142 drugs and chemicals. The sensitivity analysis demonstrated the relative importance of the various compound properties reflective of specific mechanistic determinants relevant to prediction of PC values of drugs and environmental chemicals. Overall, the present unified algorithm uniquely facilitates the computation of macro and micro level PCs for developing organ and cellular-level PBPK models for both chemicals and drugs.

The Effects of Exurbanization on Bird and Macro invertebrate Communities in Deciduous Forests on the Cumberland Plateau, Tennessee

International Nuclear Information System (INIS)

Casey, J.M.; Wilson, M.E.; Haskell, D.G.; Hollingshead, N.

2009-01-01

To investigate the potential causes of changes to bird communities in exurban areas, we examined the relationship between bird and macro invertebrate communities in exurbanized forest. We randomly located sampling points across a gradient of exurbanization. We used point counts to quantify bird communities and sweep netting, soil cores, pitfalls, and frass collectors to quantify macro invertebrates. Bird communities had higher richness and abundance in exurban areas compared to undeveloped forests, and lost some species of conservation concern but gained others. The macro invertebrate community was slightly more abundant in exurban areas, with a slight shift in taxonomic composition. The abundance of macro invertebrates in soil cores (but not pitfalls) predicted the abundance of ground-foraging birds. The abundance of macro invertebrates in sweep nets was not associated with the abundance of aerial insectivore birds. Exurbanization therefore appears to change bird and macro invertebrate communities, but to a lesser extent than agricultural forest fragmentation or intensive urbanization.

Investigations of the Gas-Liquid Multiphase System Involving Macro-Instability in a Baffled Stirred Tank Reactor

Directory of Open Access Journals (Sweden)

Shuo Zhang

2016-01-01

Full Text Available Bubble Sauter Mean Diameter (SMD in gas-liquid multiphase system is of particular interest and the quantification of gas characteristics is still a challenge today. In this contribution, multiphase Computational Fluid Dynamic (CFD simulations are combined with Population Balance Model (PBM to investigate the bubble SMD in baffled stirred tank reactor (STR. Hereby, special attention is given to the phenomenon known as the fluid macro-instability (MI, which is a large-scale low-frequency fluid velocity variation in baffled STRs, since the fluid MIs have a dominating influence on the bubble breakage and coalescence processes. The simulations, regarding the fluid velocity, are validated with Laser Doppler Anemometry (LDA experiments, in which the instant radial velocity is analyzed through Fast Fourier Transform (FFT spectrum. The frequency peaks of the fluid MIs are found both in the simulation and in the experiment with a high degree of accuracy. After the validation, quantitative predictions of overall bubble SMD with and without MIs are carried out. Due to the accurate prediction of the fluid field, the influence of the fluid MI to bubble SMD is presented. This result provides more adequate information for engineers working in the field of estimating bubble SMDs in baffled STRs.

Pore-scale study on flow and heat transfer in 3D reconstructed porous media using micro-tomography images

International Nuclear Information System (INIS)

Liu, Zhenyu; Wu, Huiying

2016-01-01

Highlights: • The complex porous domain has been reconstructed with the micro CT scan images. • Pore-scale numerical model based on LB method has been established. • The correlations for flow and heat transfer were derived from the predictions. • The numerical approach developed in this work is suitable for complex porous media. - Abstract: This paper presents the numerical study on fluid flow and heat transfer in reconstructed porous media at the pore-scale with the double-population thermal lattice Boltzmann (LB) method. The porous geometry was reconstructed using micro-tomography images from micro-CT scanner. The thermal LB model was numerically tested before simulation and a good agreement was achieved by compared with the existing results. The detailed distributions of velocity and temperature in complex pore spaces were obtained from the pore-scale simulation. The correlations for flow and heat transfer in the specific porous media sample were derived based on the numerical results. The numerical method established in this work provides a promising approach to predict pore-scale flow and heat transfer characteristics in reconstructed porous domain with real geometrical effect, which can be extended for the continuum modeling of the transport process in porous media at macro-scale.

Macro-economic and energy scenarios for Japan through the long-term

International Nuclear Information System (INIS)

Mankin, Shuichi

1986-03-01

As one of studies and systems analyses on the role of VHTR and process heat utilization in future energy systems, long-term macro economic and energy scenarios of Japan until the year 2030 have been generated. This paper presents,; 1) the outline of the long-term macro econometric model and the energy system dynamics model by which these scenarios were generated, 2) back grounds and prospects on future societies of Japan and exogeneous assumptions for calculations, and 3) macro energy and economic scenarios generated. Reflecting the present economic prospects, these scenarios are seemed to be of extremely low-growth type, however, the role of VHTR and its energy systems could be prospected clealy to play a large and important role within these scenario regions. Basic philosophies of scenario generations are also mentioned in this paper. (author)

Bridging scales with thermodynamics: from nano to macro

International Nuclear Information System (INIS)

Kjelstrup, Signe; Bedeaux, Dick; Trinh, Thuat; Schnell, Sondre K; Vlugt, Thijs J H; Simon, Jean-Marc; Bardow, Andre

2014-01-01

We have recently developed a method to calculate thermodynamic properties of macroscopic systems by extrapolating properties of systems of molecular dimensions. Appropriate scaling laws for small systems were derived using the method for small systems thermodynamics of Hill, considering surface and nook energies in small systems of varying sizes. Given certain conditions, Hill's method provides the same systematic basis for small systems as conventional thermodynamics does for large systems. We show how the method can be used to compute thermodynamic data for the macroscopic limit from knowledge of fluctuations in the small system. The rapid and precise method offers an alternative to current more difficult computations of thermodynamic factors from Kirkwood–Buff integrals. When multiplied with computed Maxwell–Stefan diffusivities, agreement is found between computed predictions and experiments of the Fick diffusion coefficients for several binary systems. Diffusion coefficients were obtained by linking the Green–Kubo formulae to the Onsager coefficients. The formulae were used to improve/disprove empirical formulae for diffusion coefficients. (review)

Incorporating uncertainty in predictive species distribution modelling.

Science.gov (United States)

Beale, Colin M; Lennon, Jack J

2012-01-19

Motivated by the need to solve ecological problems (climate change, habitat fragmentation and biological invasions), there has been increasing interest in species distribution models (SDMs). Predictions from these models inform conservation policy, invasive species management and disease-control measures. However, predictions are subject to uncertainty, the degree and source of which is often unrecognized. Here, we review the SDM literature in the context of uncertainty, focusing on three main classes of SDM: niche-based models, demographic models and process-based models. We identify sources of uncertainty for each class and discuss how uncertainty can be minimized or included in the modelling process to give realistic measures of confidence around predictions. Because this has typically not been performed, we conclude that uncertainty in SDMs has often been underestimated and a false precision assigned to predictions of geographical distribution. We identify areas where development of new statistical tools will improve predictions from distribution models, notably the development of hierarchical models that link different types of distribution model and their attendant uncertainties across spatial scales. Finally, we discuss the need to develop more defensible methods for assessing predictive performance, quantifying model goodness-of-fit and for assessing the significance of model covariates.

Preparing for Exascale: Towards convection-permitting, global atmospheric simulations with the Model for Prediction Across Scales (MPAS)

Science.gov (United States)

Heinzeller, Dominikus; Duda, Michael G.; Kunstmann, Harald

2017-04-01

With strong financial and political support from national and international initiatives, exascale computing is projected for the end of this decade. Energy requirements and physical limitations imply the use of accelerators and the scaling out to orders of magnitudes larger numbers of cores then today to achieve this milestone. In order to fully exploit the capabilities of these Exascale computing systems, existing applications need to undergo significant development. The Model for Prediction Across Scales (MPAS) is a novel set of Earth system simulation components and consists of an atmospheric core, an ocean core, a land-ice core and a sea-ice core. Its distinct features are the use of unstructured Voronoi meshes and C-grid discretisation to address shortcomings of global models on regular grids and the use of limited area models nested in a forcing data set, with respect to parallel scalability, numerical accuracy and physical consistency. Here, we present work towards the application of the atmospheric core (MPAS-A) on current and future high performance computing systems for problems at extreme scale. In particular, we address the issue of massively parallel I/O by extending the model to support the highly scalable SIONlib library. Using global uniform meshes with a convection-permitting resolution of 2-3km, we demonstrate the ability of MPAS-A to scale out to half a million cores while maintaining a high parallel efficiency. We also demonstrate the potential benefit of a hybrid parallelisation of the code (MPI/OpenMP) on the latest generation of Intel's Many Integrated Core Architecture, the Intel Xeon Phi Knights Landing.

Automated a complex computer aided design concept generated using macros programming

Science.gov (United States)

Rizal Ramly, Mohammad; Asrokin, Azharrudin; Abd Rahman, Safura; Zulkifly, Nurul Ain Md

2013-12-01

Changing a complex Computer Aided design profile such as car and aircraft surfaces has always been difficult and challenging. The capability of CAD software such as AutoCAD and CATIA show that a simple configuration of a CAD design can be easily modified without hassle, but it is not the case with complex design configuration. Design changes help users to test and explore various configurations of the design concept before the production of a model. The purpose of this study is to look into macros programming as parametric method of the commercial aircraft design. Macros programming is a method where the configurations of the design are done by recording a script of commands, editing the data value and adding a certain new command line to create an element of parametric design. The steps and the procedure to create a macro programming are discussed, besides looking into some difficulties during the process of creation and advantage of its usage. Generally, the advantages of macros programming as a method of parametric design are; allowing flexibility for design exploration, increasing the usability of the design solution, allowing proper contained by the model while restricting others and real time feedback changes.

Automated a complex computer aided design concept generated using macros programming

International Nuclear Information System (INIS)

Ramly, Mohammad Rizal; Asrokin, Azharrudin; Rahman, Safura Abd; Zulkifly, Nurul Ain Md

2013-01-01

Changing a complex Computer Aided design profile such as car and aircraft surfaces has always been difficult and challenging. The capability of CAD software such as AutoCAD and CATIA show that a simple configuration of a CAD design can be easily modified without hassle, but it is not the case with complex design configuration. Design changes help users to test and explore various configurations of the design concept before the production of a model. The purpose of this study is to look into macros programming as parametric method of the commercial aircraft design. Macros programming is a method where the configurations of the design are done by recording a script of commands, editing the data value and adding a certain new command line to create an element of parametric design. The steps and the procedure to create a macro programming are discussed, besides looking into some difficulties during the process of creation and advantage of its usage. Generally, the advantages of macros programming as a method of parametric design are; allowing flexibility for design exploration, increasing the usability of the design solution, allowing proper contained by the model while restricting others and real time feedback changes

Recursive macro generator for the TAS-86 language. First part: the macro generator language. Second part: system internal logics

International Nuclear Information System (INIS)

Zraick, Samir

1970-01-01

A macro-generator is a translator which is able to interpret and translate a programme written in a macro-language. After a first part presenting the main notions and proposing a brief description of the TAS-86 language, the second part of this research thesis reports the development of the macro-generator language, and notably presents the additional functionalities provided by the macro generator. The development is illustrated by logical flowcharts and programming listings

Multi-scale predictions of massive conifer mortality due to chronic temperature rise

Science.gov (United States)

McDowell, N. G.; Williams, A. P.; Xu, C.; Pockman, W. T.; Dickman, L. T.; Sevanto, S.; Pangle, R.; Limousin, J.; Plaut, J.; Mackay, D. S.; Ogee, J.; Domec, J. C.; Allen, C. D.; Fisher, R. A.; Jiang, X.; Muss, J. D.; Breshears, D. D.; Rauscher, S. A.; Koven, C.

2016-03-01

Global temperature rise and extremes accompanying drought threaten forests and their associated climatic feedbacks. Our ability to accurately simulate drought-induced forest impacts remains highly uncertain in part owing to our failure to integrate physiological measurements, regional-scale models, and dynamic global vegetation models (DGVMs). Here we show consistent predictions of widespread mortality of needleleaf evergreen trees (NET) within Southwest USA by 2100 using state-of-the-art models evaluated against empirical data sets. Experimentally, dominant Southwest USA NET species died when they fell below predawn water potential (Ψpd) thresholds (April-August mean) beyond which photosynthesis, hydraulic and stomatal conductance, and carbohydrate availability approached zero. The evaluated regional models accurately predicted NET Ψpd, and 91% of predictions (10 out of 11) exceeded mortality thresholds within the twenty-first century due to temperature rise. The independent DGVMs predicted >=50% loss of Northern Hemisphere NET by 2100, consistent with the NET findings for Southwest USA. Notably, the global models underestimated future mortality within Southwest USA, highlighting that predictions of future mortality within global models may be underestimates. Taken together, the validated regional predictions and the global simulations predict widespread conifer loss in coming decades under projected global warming.

Multi-scale predictions of coniferous forest mortality in the northern hemisphere

Science.gov (United States)

McDowell, N. G.

2015-12-01

Global temperature rise and extremes accompanying drought threaten forests and their associated climatic feedbacks. Our incomplete understanding of the fundamental physiological thresholds of vegetation mortality during drought limits our ability to accurately simulate future vegetation distributions and associated climate feedbacks. Here we integrate experimental evidence with models to show potential widespread loss of needleleaf evergreen trees (NET; ~ conifers) within the Southwest USA by 2100; with rising temperature being the primary cause of mortality. Experimentally, dominant Southwest USA NET species died when they fell below predawn water potential (Ypd) thresholds (April-August mean) beyond which photosynthesis, stomatal and hydraulic conductance, and carbohydrate availability approached zero. Empirical and mechanistic models accurately predicted NET Ypd, and 91% of predictions (10/11) exceeded mortality thresholds within the 21st century due to temperature rise. Completely independent global models predicted >50% loss of northern hemisphere NET by 2100, consistent with the findings for Southwest USA. The global models disagreed with the ecosystem process models in regards to future mortality in Southwest USA, however, highlighting the potential underestimates of future NET mortality as simulated by the global models and signifying the importance of improving regional predictions. Taken together, these results from the validated regional predictions and the global simulations predict global-scale conifer loss in coming decades under projected global warming.

Linking Resilience and Transformation as Micro- and Macro Adaptation

Science.gov (United States)

Friedman, E.; Breitzer, R.; Solecki, W. D.

2017-12-01

The concept of resiliency within climate adaptation planning and practice is widespread, but in some ways it has begun to suffer from its own success. While resiliency provides a valuable frame for understanding the conditions and opportunities for localized responses to increasing climate risks, the concept's ubiquitous use leads to it being applied to often conflicting policy agendas, which can mask or limit the capacity to connect efforts focused on near term risk to longer term and emergent climate threats in communities. These challenges are particularly evident in the context of extreme events and in the post extreme event policy windows. To overcome these issues and take advantage of the post-event policy window, the NOAA RISA Climate Change Risk in the Urban Northeast (CCRUN) project has been developing two specific, "boutique", policy tools. These include the PELT (Post-event learning toolkit) and MART (Macro-adaptation Resilience toolkit) toolkits. Embedded in these toolkits are two approaches to small scale strategies often associated with near term action (i.e., micro-adaptation) and large scale strategies associated with broad longer term needs (i.e., macro-adaptation). In this paper, these two approaches - micro and macro adaptation - are theoretically defined and presented in practice through the beta-testing of the PELT and MART toolkits. Most importantly, we illustrate how the theoretical links between resiliency and transformation can be operationalized through the use of these approaches, and how these approaches can be implemented in everyday risk management practice. We present our work through selected case studies in the Northeast US region, specifically in Jamaica Bay, New York, and Eastwick neighborhood in Philadelphia.

Long-term relationships of major macro-variables in a resource-related economic model of Australia

International Nuclear Information System (INIS)

Harvie, Charles; Hoa, T. van

1993-01-01

The paper reports the results of a simple cointegration analysis applied to bivariate causality models using data on resource output, oil prices, terms of trade, current account and output growth to investigate the long-term relationships among these major macroeconomic aggregates in a resource-related economic model of Australia. For the period 1960-1990, the empirical evidence indicates that these five macro-variables, as formulated in our model, are not random walks. In addition, resource production and oil prices are significantly cointegrated, and they are also significantly cointegrated with the current account, terms of trade and economic growth. These findings provide support to the long-term adjustments foundation of our resource-related model. (author)

A global high-resolution model experiment on the predictability of the atmosphere

Science.gov (United States)

Judt, F.

2016-12-01

Forecasting high-impact weather phenomena is one of the most important aspects of numerical weather prediction (NWP). Over the last couple of years, a tremendous increase in computing power has facilitated the advent of global convection-resolving NWP models, which allow for the seamless prediction of weather from local to planetary scales. Unfortunately, the predictability of specific meteorological phenomena in these models is not very well known. This raises questions about which forecast problems are potentially tractable, and what is the value of global convection-resolving model predictions for the end user. To address this issue, we use the Yellowstone supercomputer to conduct a global high-resolution predictability experiment with the recently developed Model for Prediction Across Scales (MPAS). The computing power of Yellowstone enables the model to run at a globally uniform resolution of 4 km with 55 vertical levels (>2 billion grid cells). These simulations, which require 3 million core-hours for the entire experiment, allow for the explicit treatment of organized deep moist convection (i.e., thunderstorm systems). Resolving organized deep moist convection alleviates grave limitations of previous predictability studies, which either used high-resolution limited-area models or global simulations with coarser grids and cumulus parameterization. By computing the error growth characteristics in a set of "identical twin" model runs, the experiment will clarify the intrinsic predictability limits of atmospheric phenomena on a wide range of scales, from severe thunderstorms to global-scale wind patterns that affect the distribution of tropical rainfall. Although a major task by itself, this study is intended to be exploratory work for a future predictability experiment going beyond of what has so far been feasible. We hope to use CISL's new Cheyenne supercomputer to conduct a similar predictability experiments on a global mesh with 1-2 km resolution. This

Remote sensing applied to numerical modelling. [water resources pollution

Science.gov (United States)

Sengupta, S.; Lee, S. S.; Veziroglu, T. N.; Bland, R.

1975-01-01

Progress and remaining difficulties in the construction of predictive mathematical models of large bodies of water as ecosystems are reviewed. Surface temperature is at present the only variable than can be measured accurately and reliably by remote sensing techniques, but satellite infrared data are of sufficient resolution for macro-scale modeling of oceans and large lakes, and airborne radiometers are useful in meso-scale analysis (of lakes, bays, and thermal plumes). Finite-element and finite-difference techniques applied to the solution of relevant coupled time-dependent nonlinear partial differential equations are compared, and the specific problem of the Biscayne Bay and environs ecosystem is tackled in a finite-differences treatment using the rigid-lid model and a rigid-line grid system.

A framework for evaluating forest landscape model predictions using empirical data and knowledge

Science.gov (United States)

Wen J. Wang; Hong S. He; Martin A. Spetich; Stephen R. Shifley; Frank R. Thompson; William D. Dijak; Qia. Wang

2014-01-01

Evaluation of forest landscape model (FLM) predictions is indispensable to establish the credibility of predictions. We present a framework that evaluates short- and long-term FLM predictions at site and landscape scales. Site-scale evaluation is conducted through comparing raster cell-level predictions with inventory plot data whereas landscape-scale evaluation is...

MACRO1: a code to test a methodology for analyzing nuclear-waste management systems

International Nuclear Information System (INIS)

Edwards, L.L.

1979-01-01

The code is primarily a manager of probabilistic data and deterministic mathematical models. The user determines the desired aggregation of the available models into a composite model of a physical system. MACRO1 then propagates the finite probability distributions of the inputs to the model to finite probability distributions over the outputs. MACRO1 has been applied to a sample analysis of a nuclear-waste repository, and its results compared satisfactorily with previously obtained Monte Carlo statistics

Multi Scale Models for Flexure Deformation in Sheet Metal Forming

Directory of Open Access Journals (Sweden)

Di Pasquale Edmondo

2016-01-01

Full Text Available This paper presents the application of multi scale techniques to the simulation of sheet metal forming using the one-step method. When a blank flows over the die radius, it undergoes a complex cycle of bending and unbending. First, we describe an original model for the prediction of residual plastic deformation and stresses in the blank section. This model, working on a scale about one hundred times smaller than the element size, has been implemented in SIMEX, one-step sheet metal forming simulation code. The utilisation of this multi-scale modeling technique improves greatly the accuracy of the solution. Finally, we discuss the implications of this analysis on the prediction of springback in metal forming.

Bayesian Predictive Models for Rayleigh Wind Speed

DEFF Research Database (Denmark)

Shahirinia, Amir; Hajizadeh, Amin; Yu, David C

2017-01-01

predictive model of the wind speed aggregates the non-homogeneous distributions into a single continuous distribution. Therefore, the result is able to capture the variation among the probability distributions of the wind speeds at the turbines’ locations in a wind farm. More specifically, instead of using...... a wind speed distribution whose parameters are known or estimated, the parameters are considered as random whose variations are according to probability distributions. The Bayesian predictive model for a Rayleigh which only has a single model scale parameter has been proposed. Also closed-form posterior...... and predictive inferences under different reasonable choices of prior distribution in sensitivity analysis have been presented....

The dynamical integrity concept for interpreting/ predicting experimental behaviour: from macro- to nano-mechanics.

Science.gov (United States)

Lenci, Stefano; Rega, Giuseppe; Ruzziconi, Laura

2013-06-28

The dynamical integrity, a new concept proposed by J.M.T. Thompson, and developed by the authors, is used to interpret experimental results. After reviewing the main issues involved in this analysis, including the proposal of a new integrity measure able to capture in an easy way the safe part of basins, attention is dedicated to two experiments, a rotating pendulum and a micro-electro-mechanical system, where the theoretical predictions are not fulfilled. These mechanical systems, the former at the macro-scale and the latter at the micro-scale, permit a comparative analysis of different mechanical and dynamical behaviours. The fact that in both cases the dynamical integrity permits one to justify the difference between experimental and theoretical results, which is the main achievement of this paper, shows the effectiveness of this new approach and suggests its use in practical situations. The men of experiment are like the ant, they only collect and use; the reasoners resemble spiders, who make cobwebs out of their own substance. But the bee takes the middle course: it gathers its material from the flowers of the garden and field, but transforms and digests it by a power of its own. Not unlike this is the true business of philosophy (science); for it neither relies solely or chiefly on the powers of the mind, nor does it take the matter which it gathers from natural history and mechanical experiments and lay up in the memory whole, as it finds it, but lays it up in the understanding altered and digested. Therefore, from a closer and purer league between these two faculties, the experimental and the rational (such as has never been made), much may be hoped. (Francis Bacon 1561-1626) But are we sure of our observational facts? Scientific men are rather fond of saying pontifically that one ought to be quite sure of one's observational facts before embarking on theory. Fortunately those who give this advice do not practice what they preach. Observation and theory get

Sensitivity analysis of the STICS-MACRO model to identify cropping practices reducing pesticides losses.

Science.gov (United States)

Lammoglia, Sabine-Karen; Makowski, David; Moeys, Julien; Justes, Eric; Barriuso, Enrique; Mamy, Laure

2017-02-15

STICS-MACRO is a process-based model simulating the fate of pesticides in the soil-plant system as a function of agricultural practices and pedoclimatic conditions. The objective of this work was to evaluate the influence of crop management practices on water and pesticide flows in contrasted environmental conditions. We used the Morris screening sensitivity analysis method to identify the most influential cropping practices. Crop residues management and tillage practices were shown to have strong effects on water percolation and pesticide leaching. In particular, the amount of organic residues added to soil was found to be the most influential input. The presence of a mulch could increase soil water content so water percolation and pesticide leaching. Conventional tillage was also found to decrease pesticide leaching, compared to no-till, which is consistent with many field observations. The effects of the soil, crop and climate conditions tested in this work were less important than those of cropping practices. STICS-MACRO allows an ex ante evaluation of cropping systems and agricultural practices, and of the related pesticides environmental impacts. Copyright © 2016 Elsevier B.V. All rights reserved.

Assessing flood risk at the global scale: model setup, results, and sensitivity

International Nuclear Information System (INIS)

Ward, Philip J; Jongman, Brenden; Weiland, Frederiek Sperna; Winsemius, Hessel C; Bouwman, Arno; Ligtvoet, Willem; Van Beek, Rens; Bierkens, Marc F P

2013-01-01

Globally, economic losses from flooding exceeded $19 billion in 2012, and are rising rapidly. Hence, there is an increasing need for global-scale flood risk assessments, also within the context of integrated global assessments. We have developed and validated a model cascade for producing global flood risk maps, based on numerous flood return-periods. Validation results indicate that the model simulates interannual fluctuations in flood impacts well. The cascade involves: hydrological and hydraulic modelling; extreme value statistics; inundation modelling; flood impact modelling; and estimating annual expected impacts. The initial results estimate global impacts for several indicators, for example annual expected exposed population (169 million); and annual expected exposed GDP ($1383 billion). These results are relatively insensitive to the extreme value distribution employed to estimate low frequency flood volumes. However, they are extremely sensitive to the assumed flood protection standard; developing a database of such standards should be a research priority. Also, results are sensitive to the use of two different climate forcing datasets. The impact model can easily accommodate new, user-defined, impact indicators. We envisage several applications, for example: identifying risk hotspots; calculating macro-scale risk for the insurance industry and large companies; and assessing potential benefits (and costs) of adaptation measures. (letter)

Macro- and micro-chaotic structures in the Hindmarsh-Rose model of bursting neurons

Energy Technology Data Exchange (ETDEWEB)

Barrio, Roberto, E-mail: rbarrio@unizar.es; Serrano, Sergio [Computational Dynamics Group, Departamento de Matemática Aplicada, GME and IUMA, Universidad de Zaragoza, E-50009 Zaragoza (Spain); Angeles Martínez, M. [Computational Dynamics Group, GME, Universidad de Zaragoza, E-50009 Zaragoza (Spain); Shilnikov, Andrey [Neuroscience Institute and Department of Mathematics and Statistics, Georgia State University, Atlanta, Georgia 30078 (United States); Department of Computational Mathematics and Cybernetics, Lobachevsky State University of Nizhni Novgorod, 603950 Nizhni Novgorod (Russian Federation)

2014-06-01