WorldWideScience

Sample records for hierarchical fracture models

  1. Visualization and Hierarchical Analysis of Flow in Discrete Fracture Network Models

    Science.gov (United States)

    Aldrich, G. A.; Gable, C. W.; Painter, S. L.; Makedonska, N.; Hamann, B.; Woodring, J.

    2013-12-01

    Flow and transport in low permeability fractured rock is primary in interconnected fracture networks. Prediction and characterization of flow and transport in fractured rock has important implications in underground repositories for hazardous materials (eg. nuclear and chemical waste), contaminant migration and remediation, groundwater resource management, and hydrocarbon extraction. We have developed methods to explicitly model flow in discrete fracture networks and track flow paths using passive particle tracking algorithms. Visualization and analysis of particle trajectory through the fracture network is important to understanding fracture connectivity, flow patterns, potential contaminant pathways and fast paths through the network. However, occlusion due to the large number of highly tessellated and intersecting fracture polygons preclude the effective use of traditional visualization methods. We would also like quantitative analysis methods to characterize the trajectory of a large number of particle paths. We have solved these problems by defining a hierarchal flow network representing the topology of particle flow through the fracture network. This approach allows us to analyses the flow and the dynamics of the system as a whole. We are able to easily query the flow network, and use paint-and-link style framework to filter the fracture geometry and particle traces based on the flow analytics. This allows us to greatly reduce occlusion while emphasizing salient features such as the principal transport pathways. Examples are shown that demonstrate the methodology and highlight how use of this new method allows quantitative analysis and characterization of flow and transport in a number of representative fracture networks.

  2. Time to failure of hierarchical load-transfer models of fracture

    DEFF Research Database (Denmark)

    Vázquez-Prada, M; Gómez, J B; Moreno, Y

    1999-01-01

    The time to failure, T, of dynamical models of fracture for a hierarchical load-transfer geometry is studied. Using a probabilistic strategy and juxtaposing hierarchical structures of height n, we devise an exact method to compute T, for structures of height n+1. Bounding T, for large n, we are a...... are able to deduce that the time to failure tends to a nonzero value when n tends to infinity. This numerical conclusion is deduced for both power law and exponential breakdown rules....

  3. Flow and transport in hierarchically fractured systems

    International Nuclear Information System (INIS)

    Karasaki, K.

    1993-01-01

    Preliminary results indicate that flow in the saturated zone at Yucca Mountain is controlled by fractures. A current conceptual model assumes that the flow in the fracture system can be approximately by a three-dimensionally interconnected network of linear conduits. The overall flow system of rocks at Yucca Mountain is considered to consist of hierarchically structured heterogeneous fracture systems of multiple scales. A case study suggests that it is more appropriate to use the flow parameters of the large fracture system for predicting the first arrival time, rather than using the bulk average parameters of the total system

  4. Hierarchical multiscale modeling for flows in fractured media using generalized multiscale finite element method

    KAUST Repository

    Efendiev, Yalchin R.

    2015-06-05

    In this paper, we develop a multiscale finite element method for solving flows in fractured media. Our approach is based on generalized multiscale finite element method (GMsFEM), where we represent the fracture effects on a coarse grid via multiscale basis functions. These multiscale basis functions are constructed in the offline stage via local spectral problems following GMsFEM. To represent the fractures on the fine grid, we consider two approaches (1) discrete fracture model (DFM) (2) embedded fracture model (EFM) and their combination. In DFM, the fractures are resolved via the fine grid, while in EFM the fracture and the fine grid block interaction is represented as a source term. In the proposed multiscale method, additional multiscale basis functions are used to represent the long fractures, while short-size fractures are collectively represented by a single basis functions. The procedure is automatically done via local spectral problems. In this regard, our approach shares common concepts with several approaches proposed in the literature as we discuss. We would like to emphasize that our goal is not to compare DFM with EFM, but rather to develop GMsFEM framework which uses these (DFM or EFM) fine-grid discretization techniques. Numerical results are presented, where we demonstrate how one can adaptively add basis functions in the regions of interest based on error indicators. We also discuss the use of randomized snapshots (Calo et al. Randomized oversampling for generalized multiscale finite element methods, 2014), which reduces the offline computational cost.

  5. Stress generation and hierarchical fracturing in reactive systems

    Science.gov (United States)

    Jamtveit, B.; Iyer, K.; Royne, A.; Malthe-Sorenssen, A.; Mathiesen, J.; Feder, J.

    2007-12-01

    Hierarchical fracture patterns are the result of a slowly driven fracturing process that successively divides the rocks into smaller domains. In quasi-2D systems, such fracture patterns are characterized by four sided domains, and T-junctions where new fractures stop at right angles to pre-existing fractures. We describe fracturing of mm to dm thick enstatite layers in a dunite matrix from the Leka ophiolite complex in Norway. The fracturing process is driven by expansion of the dunite matrix during serpentinization. The cumulative distributions of fracture lengths show a scaling behavior that lies between a log - normal and power law (fractal) distribution. This is consistent with a simple fragmentation model in which domains are divided according to a 'top hat' distribution of new fracture positions within unfractured domains. Reaction-assisted hierarchical fracturing is also likely to be responsible for other (3-D) structures commonly observed in serpentinized ultramafic rocks, including the mesh-textures observed in individual olivine grains, and the high abundance of rectangular domains at a wide range of scales. Spectacular examples of 3-D hierarchical fracture patterns also form during the weathering of basaltic intrusions (dolerites). Incipient chemical weathering of dolerites in the Karoo Basin in South Africa occurs around water- filled fractures, originally produced by thermal contraction or by externally imposed stresses. This chemical weathering causes local expansion of the rock matrix and generates elastic stresses. On a mm to cm scale, these stresses lead to mechanical layer-by-layer spalling, producing the characteristic spheroidal weathering patterns. However, our field observations and computer simulations demonstrate that in confined environments, the spalling process alone is unable to relieve the elastic stresses. In such cases, chemical weathering drives a much larger scale hierarchical fracturing process in which fresh dolerite undergoes a

  6. Hierarchical species distribution models

    Science.gov (United States)

    Hefley, Trevor J.; Hooten, Mevin B.

    2016-01-01

    Determining the distribution pattern of a species is important to increase scientific knowledge, inform management decisions, and conserve biodiversity. To infer spatial and temporal patterns, species distribution models have been developed for use with many sampling designs and types of data. Recently, it has been shown that count, presence-absence, and presence-only data can be conceptualized as arising from a point process distribution. Therefore, it is important to understand properties of the point process distribution. We examine how the hierarchical species distribution modeling framework has been used to incorporate a wide array of regression and theory-based components while accounting for the data collection process and making use of auxiliary information. The hierarchical modeling framework allows us to demonstrate how several commonly used species distribution models can be derived from the point process distribution, highlight areas of potential overlap between different models, and suggest areas where further research is needed.

  7. Bayesian nonparametric hierarchical modeling.

    Science.gov (United States)

    Dunson, David B

    2009-04-01

    In biomedical research, hierarchical models are very widely used to accommodate dependence in multivariate and longitudinal data and for borrowing of information across data from different sources. A primary concern in hierarchical modeling is sensitivity to parametric assumptions, such as linearity and normality of the random effects. Parametric assumptions on latent variable distributions can be challenging to check and are typically unwarranted, given available prior knowledge. This article reviews some recent developments in Bayesian nonparametric methods motivated by complex, multivariate and functional data collected in biomedical studies. The author provides a brief review of flexible parametric approaches relying on finite mixtures and latent class modeling. Dirichlet process mixture models are motivated by the need to generalize these approaches to avoid assuming a fixed finite number of classes. Focusing on an epidemiology application, the author illustrates the practical utility and potential of nonparametric Bayes methods.

  8. Hierarchical Bass model

    International Nuclear Information System (INIS)

    Tashiro, Tohru

    2014-01-01

    We propose a new model about diffusion of a product which includes a memory of how many adopters or advertisements a non-adopter met, where (non-)adopters mean people (not) possessing the product. This effect is lacking in the Bass model. As an application, we utilize the model to fit the iPod sales data, and so the better agreement is obtained than the Bass model

  9. Hierarchical Bass model

    Science.gov (United States)

    Tashiro, Tohru

    2014-03-01

    We propose a new model about diffusion of a product which includes a memory of how many adopters or advertisements a non-adopter met, where (non-)adopters mean people (not) possessing the product. This effect is lacking in the Bass model. As an application, we utilize the model to fit the iPod sales data, and so the better agreement is obtained than the Bass model.

  10. Hierarchical Semantic Model of Geovideo

    Directory of Open Access Journals (Sweden)

    XIE Xiao

    2015-05-01

    Full Text Available The public security incidents were getting increasingly challenging with regard to their new features, including multi-scale mobility, multistage dynamic evolution, as well as spatiotemporal concurrency and uncertainty in the complex urban environment. However, the existing video models, which were used/designed for independent archive or local analysis of surveillance video, have seriously inhibited emergency response to the urgent requirements.Aiming at the explicit representation of change mechanism in video, the paper proposed a novel hierarchical geovideo semantic model using UML. This model was characterized by the hierarchical representation of both data structure and semantics based on the change-oriented three domains (feature domain, process domain and event domain instead of overall semantic description of video streaming; combining both geographical semantics and video content semantics, in support of global semantic association between multiple geovideo data. The public security incidents by video surveillance are inspected as an example to illustrate the validity of this model.

  11. Multicollinearity in hierarchical linear models.

    Science.gov (United States)

    Yu, Han; Jiang, Shanhe; Land, Kenneth C

    2015-09-01

    This study investigates an ill-posed problem (multicollinearity) in Hierarchical Linear Models from both the data and the model perspectives. We propose an intuitive, effective approach to diagnosing the presence of multicollinearity and its remedies in this class of models. A simulation study demonstrates the impacts of multicollinearity on coefficient estimates, associated standard errors, and variance components at various levels of multicollinearity for finite sample sizes typical in social science studies. We further investigate the role multicollinearity plays at each level for estimation of coefficient parameters in terms of shrinkage. Based on these analyses, we recommend a top-down method for assessing multicollinearity in HLMs that first examines the contextual predictors (Level-2 in a two-level model) and then the individual predictors (Level-1) and uses the results for data collection, research problem redefinition, model re-specification, variable selection and estimation of a final model. Copyright © 2015 Elsevier Inc. All rights reserved.

  12. Hierarchical modeling of active materials

    International Nuclear Information System (INIS)

    Taya, Minoru

    2003-01-01

    Intelligent (or smart) materials are increasingly becoming key materials for use in actuators and sensors. If an intelligent material is used as a sensor, it can be embedded in a variety of structure functioning as a health monitoring system to make their life longer with high reliability. If an intelligent material is used as an active material in an actuator, it plays a key role of making dynamic movement of the actuator under a set of stimuli. This talk intends to cover two different active materials in actuators, (1) piezoelectric laminate with FGM microstructure, (2) ferromagnetic shape memory alloy (FSMA). The advantage of using the FGM piezo laminate is to enhance its fatigue life while maintaining large bending displacement, while that of use in FSMA is its fast actuation while providing a large force and stroke capability. Use of hierarchical modeling of the above active materials is a key design step in optimizing its microstructure for enhancement of their performance. I will discuss briefly hierarchical modeling of the above two active materials. For FGM piezo laminate, we will use both micromechanical model and laminate theory, while for FSMA, the modeling interfacing nano-structure, microstructure and macro-behavior is discussed. (author)

  13. Bounds for the time to failure of hierarchical systems of fracture

    DEFF Research Database (Denmark)

    Gómez, J.B.; Vázquez-Prada, M.; Moreno, Y.

    1999-01-01

    an exact algebraic iterative method to compute the successive time intervals for individual breaking in systems of height n in terms of the information calculated in the previous height n - 1. As a byproduct of this method, rigorous lower and higher bounds for the time to failure of very large systems......For years limited Monte Carlo simulations have led to the suspicion that the time to failure of hierarchically organized load-transfer models of fracture is nonzero for sets of infinite size. This fact could have profound significance in engineering practice and also in geophysics. Here, we develop...

  14. Classification using Hierarchical Naive Bayes models

    DEFF Research Database (Denmark)

    Langseth, Helge; Dyhre Nielsen, Thomas

    2006-01-01

    Classification problems have a long history in the machine learning literature. One of the simplest, and yet most consistently well-performing set of classifiers is the Naïve Bayes models. However, an inherent problem with these classifiers is the assumption that all attributes used to describe......, termed Hierarchical Naïve Bayes models. Hierarchical Naïve Bayes models extend the modeling flexibility of Naïve Bayes models by introducing latent variables to relax some of the independence statements in these models. We propose a simple algorithm for learning Hierarchical Naïve Bayes models...

  15. Hierarchical modeling and analysis for spatial data

    CERN Document Server

    Banerjee, Sudipto; Gelfand, Alan E

    2003-01-01

    Among the many uses of hierarchical modeling, their application to the statistical analysis of spatial and spatio-temporal data from areas such as epidemiology And environmental science has proven particularly fruitful. Yet to date, the few books that address the subject have been either too narrowly focused on specific aspects of spatial analysis, or written at a level often inaccessible to those lacking a strong background in mathematical statistics.Hierarchical Modeling and Analysis for Spatial Data is the first accessible, self-contained treatment of hierarchical methods, modeling, and dat

  16. DEM Particle Fracture Model

    Energy Technology Data Exchange (ETDEWEB)

    Zhang, Boning [Univ. of Colorado, Boulder, CO (United States); Herbold, Eric B. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Homel, Michael A. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Regueiro, Richard A. [Univ. of Colorado, Boulder, CO (United States)

    2015-12-01

    An adaptive particle fracture model in poly-ellipsoidal Discrete Element Method is developed. The poly-ellipsoidal particle will break into several sub-poly-ellipsoids by Hoek-Brown fracture criterion based on continuum stress and the maximum tensile stress in contacts. Also Weibull theory is introduced to consider the statistics and size effects on particle strength. Finally, high strain-rate split Hopkinson pressure bar experiment of silica sand is simulated using this newly developed model. Comparisons with experiments show that our particle fracture model can capture the mechanical behavior of this experiment very well, both in stress-strain response and particle size redistribution. The effects of density and packings o the samples are also studied in numerical examples.

  17. Analysis hierarchical model for discrete event systems

    Science.gov (United States)

    Ciortea, E. M.

    2015-11-01

    The This paper presents the hierarchical model based on discrete event network for robotic systems. Based on the hierarchical approach, Petri network is analysed as a network of the highest conceptual level and the lowest level of local control. For modelling and control of complex robotic systems using extended Petri nets. Such a system is structured, controlled and analysed in this paper by using Visual Object Net ++ package that is relatively simple and easy to use, and the results are shown as representations easy to interpret. The hierarchical structure of the robotic system is implemented on computers analysed using specialized programs. Implementation of hierarchical model discrete event systems, as a real-time operating system on a computer network connected via a serial bus is possible, where each computer is dedicated to local and Petri model of a subsystem global robotic system. Since Petri models are simplified to apply general computers, analysis, modelling, complex manufacturing systems control can be achieved using Petri nets. Discrete event systems is a pragmatic tool for modelling industrial systems. For system modelling using Petri nets because we have our system where discrete event. To highlight the auxiliary time Petri model using transport stream divided into hierarchical levels and sections are analysed successively. Proposed robotic system simulation using timed Petri, offers the opportunity to view the robotic time. Application of goods or robotic and transmission times obtained by measuring spot is obtained graphics showing the average time for transport activity, using the parameters sets of finished products. individually.

  18. Computer model for ductile fracture

    International Nuclear Information System (INIS)

    Moran, B.; Reaugh, J. E.

    1979-01-01

    A computer model is described for predicting ductile fracture initiation and propagation. The computer fracture model is calibrated by simple and notched round-bar tension tests and a precracked compact tension test. The model is used to predict fracture initiation and propagation in a Charpy specimen and compare the results with experiments. The calibrated model provides a correlation between Charpy V-notch (CVN) fracture energy and any measure of fracture toughness, such as J/sub Ic/. A second simpler empirical correlation was obtained using the energy to initiate fracture in the Charpy specimen rather than total energy CVN, and compared the results with the empirical correlation of Rolfe and Novak

  19. Learning with hierarchical-deep models.

    Science.gov (United States)

    Salakhutdinov, Ruslan; Tenenbaum, Joshua B; Torralba, Antonio

    2013-08-01

    We introduce HD (or “Hierarchical-Deep”) models, a new compositional learning architecture that integrates deep learning models with structured hierarchical Bayesian (HB) models. Specifically, we show how we can learn a hierarchical Dirichlet process (HDP) prior over the activities of the top-level features in a deep Boltzmann machine (DBM). This compound HDP-DBM model learns to learn novel concepts from very few training example by learning low-level generic features, high-level features that capture correlations among low-level features, and a category hierarchy for sharing priors over the high-level features that are typical of different kinds of concepts. We present efficient learning and inference algorithms for the HDP-DBM model and show that it is able to learn new concepts from very few examples on CIFAR-100 object recognition, handwritten character recognition, and human motion capture datasets.

  20. Clinical fracture risk evaluated by hierarchical agglomerative clustering

    DEFF Research Database (Denmark)

    Kruse, C; Eiken, P; Vestergaard, P

    2017-01-01

    reimbursement, primary healthcare sector use and comorbidity of female subjects were combined. Standardized variable means, Euclidean distances and Ward's D2 method of hierarchical agglomerative clustering (HAC), were used to form the clustering object. K number of clusters was selected with the lowest cluster...

  1. A hierarchical model for ordinal matrix factorization

    DEFF Research Database (Denmark)

    Paquet, Ulrich; Thomson, Blaise; Winther, Ole

    2012-01-01

    This paper proposes a hierarchical probabilistic model for ordinal matrix factorization. Unlike previous approaches, we model the ordinal nature of the data and take a principled approach to incorporating priors for the hidden variables. Two algorithms are presented for inference, one based...

  2. Hierarchical Context Modeling for Video Event Recognition.

    Science.gov (United States)

    Wang, Xiaoyang; Ji, Qiang

    2016-10-11

    Current video event recognition research remains largely target-centered. For real-world surveillance videos, targetcentered event recognition faces great challenges due to large intra-class target variation, limited image resolution, and poor detection and tracking results. To mitigate these challenges, we introduced a context-augmented video event recognition approach. Specifically, we explicitly capture different types of contexts from three levels including image level, semantic level, and prior level. At the image level, we introduce two types of contextual features including the appearance context features and interaction context features to capture the appearance of context objects and their interactions with the target objects. At the semantic level, we propose a deep model based on deep Boltzmann machine to learn event object representations and their interactions. At the prior level, we utilize two types of prior-level contexts including scene priming and dynamic cueing. Finally, we introduce a hierarchical context model that systematically integrates the contextual information at different levels. Through the hierarchical context model, contexts at different levels jointly contribute to the event recognition. We evaluate the hierarchical context model for event recognition on benchmark surveillance video datasets. Results show that incorporating contexts in each level can improve event recognition performance, and jointly integrating three levels of contexts through our hierarchical model achieves the best performance.

  3. Challenges in Continuum Modelling of Intergranular Fracture

    DEFF Research Database (Denmark)

    Coffman, Valerie; Sethna, James P.; Ingraffea, A. R.

    2011-01-01

    of grain boundaries, but also in crucial ways on edges, corners and triple junctions of even greater geometrical complexity. To address the first two challenges, we explore the physical underpinnings for creating functional forms to capture the hierarchical commensurability structure in the grain boundary......Intergranular fracture in polycrystals is often simulated by finite elements coupled to a cohesive zone model for the interfaces, requiring cohesive laws for grain boundaries as a function of their geometry. We discuss three challenges in understanding intergranular fracture in polycrystals. First...... properties. To address the last challenge, we demonstrate a method for atomistically extracting the fracture properties of geometrically complex local regions on the fly from within a finite element simulation....

  4. Hierarchical Bayesian Models of Subtask Learning

    Science.gov (United States)

    Anglim, Jeromy; Wynton, Sarah K. A.

    2015-01-01

    The current study used Bayesian hierarchical methods to challenge and extend previous work on subtask learning consistency. A general model of individual-level subtask learning was proposed focusing on power and exponential functions with constraints to test for inconsistency. To study subtask learning, we developed a novel computer-based booking…

  5. Hierarchical models in the brain.

    Directory of Open Access Journals (Sweden)

    Karl Friston

    2008-11-01

    Full Text Available This paper describes a general model that subsumes many parametric models for continuous data. The model comprises hidden layers of state-space or dynamic causal models, arranged so that the output of one provides input to another. The ensuing hierarchy furnishes a model for many types of data, of arbitrary complexity. Special cases range from the general linear model for static data to generalised convolution models, with system noise, for nonlinear time-series analysis. Crucially, all of these models can be inverted using exactly the same scheme, namely, dynamic expectation maximization. This means that a single model and optimisation scheme can be used to invert a wide range of models. We present the model and a brief review of its inversion to disclose the relationships among, apparently, diverse generative models of empirical data. We then show that this inversion can be formulated as a simple neural network and may provide a useful metaphor for inference and learning in the brain.

  6. Topic Modeling of Hierarchical Corpora /

    OpenAIRE

    Kim, Do-kyum

    2014-01-01

    The sizes of modern digital libraries have grown beyond our capacity to comprehend manually. Thus we need new tools to help us in organizing and browsing large corpora of text that do not require manually examining each document. To this end, machine learning researchers have developed topic models, statistical learning algorithms for automatic comprehension of large collections of text. Topic models provide both global and local views of a corpus; they discover topics that run through the co...

  7. AN INTEGER PROGRAMMING MODEL FOR HIERARCHICAL WORKFORCE

    Directory of Open Access Journals (Sweden)

    BANU SUNGUR

    2013-06-01

    Full Text Available The model presented in this paper is based on the model developed by Billionnet for the hierarchical workforce problem. In Billionnet’s Model, while determining the workers’ weekly costs, weekly working hours of workers are not taken into consideration. In our model, the weekly costs per worker are reduced in proportion to the working hours per week. Our model is illustrated on the Billionnet’s Example. The models in question are compared and evaluated on the basis of the results obtained from the example problem. A reduction is achieved in the total cost by the proposed model.

  8. Mathematical modelling of fracture hydrology

    International Nuclear Information System (INIS)

    Herbert, A.W.; Hodgkinson, D.P.; Lever, D.A.; Robinson, P.C.; Rae, J.

    1985-06-01

    This report summarises the work performed between January 1983 and December 1984 for the CEC/DOE contract 'Mathematical Modelling of Fracture Hydrology', under the following headings: 1) Statistical fracture network modelling, 2) Continuum models of flow and transport, 3) Simplified models, 4) Analysis of laboratory experiments and 5) Analysis of field experiments. (author)

  9. Internet advertising effectiveness by using hierarchical model

    OpenAIRE

    RAHMANI, Samaneh

    2015-01-01

    Abstract. Present paper has been developed with the title of internet advertising effectiveness by using hierarchical model. Presenting the question: Today Internet is an important channel in marketing and advertising. The reason for this could be the ability of the Internet to reduce costs and people’s access to online services[1]. Also advertisers can easily access a multitude of users and communicate with them at low cost [9]. On the other hand, compared to traditional advertising, interne...

  10. A Hierarchical Agency Model of Deposit Insurance

    OpenAIRE

    Jonathan Carroll; Shino Takayama

    2010-01-01

    This paper develops a hierarchical agency model of deposit insurance. The main purpose is to undertake a game theoretic analysis of the consequences of deposit insurance schemes and their effects on monitoring incentives for banks. Using this simple framework, we analyze both risk- independent and risk-dependent premium schemes along with reserve requirement constraints. The results provide policymakers with not only a better understanding of the effects of deposit insurance on welfare and th...

  11. Hierarchic modeling of heat exchanger thermal hydraulics

    International Nuclear Information System (INIS)

    Horvat, A.; Koncar, B.

    2002-01-01

    Volume Averaging Technique (VAT) is employed in order to model the heat exchanger cross-flow as a porous media flow. As the averaging of the transport equations lead to a closure problem, separate relations are introduced to model interphase momentum and heat transfer between fluid flow and the solid structure. The hierarchic modeling is used to calculate the local drag coefficient C d as a function of Reynolds number Re h . For that purpose a separate model of REV is built and DNS of flow through REV is performed. The local values of heat transfer coefficient h are obtained from available literature. The geometry of the simulation domain and boundary conditions follow the geometry of the experimental test section used at U.C.L.A. The calculated temperature fields reveal that the geometry with denser pin-fins arrangement (HX1) heats fluid flow faster. The temperature field in the HX2 exhibits the formation of thermal boundary layer between pin-fins, which has a significant role in overall thermal performance of the heat exchanger. Although presented discrepancies of the whole-section drag coefficient C d are large, we believe that hierarchic modeling is an appropriate strategy for calculation of complex transport phenomena in heat exchanger geometries.(author)

  12. Galactic chemical evolution in hierarchical formation models

    Science.gov (United States)

    Arrigoni, Matias

    2010-10-01

    The chemical properties and abundance ratios of galaxies provide important information about their formation histories. Galactic chemical evolution has been modelled in detail within the monolithic collapse scenario. These models have successfully described the abundance distributions in our Galaxy and other spiral discs, as well as the trends of metallicity and abundance ratios observed in early-type galaxies. In the last three decades, however, the paradigm of hierarchical assembly in a Cold Dark Matter (CDM) cosmology has revised the picture of how structure in the Universe forms and evolves. In this scenario, galaxies form when gas radiatively cools and condenses inside dark matter haloes, which themselves follow dissipationless gravitational collapse. The CDM picture has been successful at predicting many observed properties of galaxies (for example, the luminosity and stellar mass function of galaxies, color-magnitude or star formation rate vs. stellar mass distributions, relative numbers of early and late-type galaxies, gas fractions and size distributions of spiral galaxies, and the global star formation history), though many potential problems and open questions remain. It is therefore interesting to see whether chemical evolution models, when implemented within this modern cosmological context, are able to correctly predict the observed chemical properties of galaxies. With the advent of more powerfull telescopes and detectors, precise observations of chemical abundances and abundance ratios in various phases (stellar, ISM, ICM) offer the opportunity to obtain strong constraints on galaxy formation histories and the physics that shapes them. However, in order to take advantage of these observations, it is necessary to implement detailed modeling of chemical evolution into a modern cosmological model of hierarchical assembly.

  13. Entrepreneurial intention modeling using hierarchical multiple regression

    Directory of Open Access Journals (Sweden)

    Marina Jeger

    2014-12-01

    Full Text Available The goal of this study is to identify the contribution of effectuation dimensions to the predictive power of the entrepreneurial intention model over and above that which can be accounted for by other predictors selected and confirmed in previous studies. As is often the case in social and behavioral studies, some variables are likely to be highly correlated with each other. Therefore, the relative amount of variance in the criterion variable explained by each of the predictors depends on several factors such as the order of variable entry and sample specifics. The results show the modest predictive power of two dimensions of effectuation prior to the introduction of the theory of planned behavior elements. The article highlights the main advantages of applying hierarchical regression in social sciences as well as in the specific context of entrepreneurial intention formation, and addresses some of the potential pitfalls that this type of analysis entails.

  14. Hierarchical Multinomial Processing Tree Models: A Latent-Trait Approach

    Science.gov (United States)

    Klauer, Karl Christoph

    2010-01-01

    Multinomial processing tree models are widely used in many areas of psychology. A hierarchical extension of the model class is proposed, using a multivariate normal distribution of person-level parameters with the mean and covariance matrix to be estimated from the data. The hierarchical model allows one to take variability between persons into…

  15. A hierarchical stochastic model for bistable perception.

    Directory of Open Access Journals (Sweden)

    Stefan Albert

    2017-11-01

    Full Text Available Viewing of ambiguous stimuli can lead to bistable perception alternating between the possible percepts. During continuous presentation of ambiguous stimuli, percept changes occur as single events, whereas during intermittent presentation of ambiguous stimuli, percept changes occur at more or less regular intervals either as single events or bursts. Response patterns can be highly variable and have been reported to show systematic differences between patients with schizophrenia and healthy controls. Existing models of bistable perception often use detailed assumptions and large parameter sets which make parameter estimation challenging. Here we propose a parsimonious stochastic model that provides a link between empirical data analysis of the observed response patterns and detailed models of underlying neuronal processes. Firstly, we use a Hidden Markov Model (HMM for the times between percept changes, which assumes one single state in continuous presentation and a stable and an unstable state in intermittent presentation. The HMM captures the observed differences between patients with schizophrenia and healthy controls, but remains descriptive. Therefore, we secondly propose a hierarchical Brownian model (HBM, which produces similar response patterns but also provides a relation to potential underlying mechanisms. The main idea is that neuronal activity is described as an activity difference between two competing neuronal populations reflected in Brownian motions with drift. This differential activity generates switching between the two conflicting percepts and between stable and unstable states with similar mechanisms on different neuronal levels. With only a small number of parameters, the HBM can be fitted closely to a high variety of response patterns and captures group differences between healthy controls and patients with schizophrenia. At the same time, it provides a link to mechanistic models of bistable perception, linking the group

  16. A hierarchical stochastic model for bistable perception.

    Science.gov (United States)

    Albert, Stefan; Schmack, Katharina; Sterzer, Philipp; Schneider, Gaby

    2017-11-01

    Viewing of ambiguous stimuli can lead to bistable perception alternating between the possible percepts. During continuous presentation of ambiguous stimuli, percept changes occur as single events, whereas during intermittent presentation of ambiguous stimuli, percept changes occur at more or less regular intervals either as single events or bursts. Response patterns can be highly variable and have been reported to show systematic differences between patients with schizophrenia and healthy controls. Existing models of bistable perception often use detailed assumptions and large parameter sets which make parameter estimation challenging. Here we propose a parsimonious stochastic model that provides a link between empirical data analysis of the observed response patterns and detailed models of underlying neuronal processes. Firstly, we use a Hidden Markov Model (HMM) for the times between percept changes, which assumes one single state in continuous presentation and a stable and an unstable state in intermittent presentation. The HMM captures the observed differences between patients with schizophrenia and healthy controls, but remains descriptive. Therefore, we secondly propose a hierarchical Brownian model (HBM), which produces similar response patterns but also provides a relation to potential underlying mechanisms. The main idea is that neuronal activity is described as an activity difference between two competing neuronal populations reflected in Brownian motions with drift. This differential activity generates switching between the two conflicting percepts and between stable and unstable states with similar mechanisms on different neuronal levels. With only a small number of parameters, the HBM can be fitted closely to a high variety of response patterns and captures group differences between healthy controls and patients with schizophrenia. At the same time, it provides a link to mechanistic models of bistable perception, linking the group differences to

  17. Constructive Epistemic Modeling: A Hierarchical Bayesian Model Averaging Method

    Science.gov (United States)

    Tsai, F. T. C.; Elshall, A. S.

    2014-12-01

    Constructive epistemic modeling is the idea that our understanding of a natural system through a scientific model is a mental construct that continually develops through learning about and from the model. Using the hierarchical Bayesian model averaging (HBMA) method [1], this study shows that segregating different uncertain model components through a BMA tree of posterior model probabilities, model prediction, within-model variance, between-model variance and total model variance serves as a learning tool [2]. First, the BMA tree of posterior model probabilities permits the comparative evaluation of the candidate propositions of each uncertain model component. Second, systemic model dissection is imperative for understanding the individual contribution of each uncertain model component to the model prediction and variance. Third, the hierarchical representation of the between-model variance facilitates the prioritization of the contribution of each uncertain model component to the overall model uncertainty. We illustrate these concepts using the groundwater modeling of a siliciclastic aquifer-fault system. The sources of uncertainty considered are from geological architecture, formation dip, boundary conditions and model parameters. The study shows that the HBMA analysis helps in advancing knowledge about the model rather than forcing the model to fit a particularly understanding or merely averaging several candidate models. [1] Tsai, F. T.-C., and A. S. Elshall (2013), Hierarchical Bayesian model averaging for hydrostratigraphic modeling: Uncertainty segregation and comparative evaluation. Water Resources Research, 49, 5520-5536, doi:10.1002/wrcr.20428. [2] Elshall, A.S., and F. T.-C. Tsai (2014). Constructive epistemic modeling of groundwater flow with geological architecture and boundary condition uncertainty under Bayesian paradigm, Journal of Hydrology, 517, 105-119, doi: 10.1016/j.jhydrol.2014.05.027.

  18. Bayesian hierarchical modelling of North Atlantic windiness

    Science.gov (United States)

    Vanem, E.; Breivik, O. N.

    2013-03-01

    Extreme weather conditions represent serious natural hazards to ship operations and may be the direct cause or contributing factor to maritime accidents. Such severe environmental conditions can be taken into account in ship design and operational windows can be defined that limits hazardous operations to less extreme conditions. Nevertheless, possible changes in the statistics of extreme weather conditions, possibly due to anthropogenic climate change, represent an additional hazard to ship operations that is less straightforward to account for in a consistent way. Obviously, there are large uncertainties as to how future climate change will affect the extreme weather conditions at sea and there is a need for stochastic models that can describe the variability in both space and time at various scales of the environmental conditions. Previously, Bayesian hierarchical space-time models have been developed to describe the variability and complex dependence structures of significant wave height in space and time. These models were found to perform reasonably well and provided some interesting results, in particular, pertaining to long-term trends in the wave climate. In this paper, a similar framework is applied to oceanic windiness and the spatial and temporal variability of the 10-m wind speed over an area in the North Atlantic ocean is investigated. When the results from the model for North Atlantic windiness is compared to the results for significant wave height over the same area, it is interesting to observe that whereas an increasing trend in significant wave height was identified, no statistically significant long-term trend was estimated in windiness. This may indicate that the increase in significant wave height is not due to an increase in locally generated wind waves, but rather to increased swell. This observation is also consistent with studies that have suggested a poleward shift of the main storm tracks.

  19. Bayesian hierarchical modelling of North Atlantic windiness

    Directory of Open Access Journals (Sweden)

    E. Vanem

    2013-03-01

    Full Text Available Extreme weather conditions represent serious natural hazards to ship operations and may be the direct cause or contributing factor to maritime accidents. Such severe environmental conditions can be taken into account in ship design and operational windows can be defined that limits hazardous operations to less extreme conditions. Nevertheless, possible changes in the statistics of extreme weather conditions, possibly due to anthropogenic climate change, represent an additional hazard to ship operations that is less straightforward to account for in a consistent way. Obviously, there are large uncertainties as to how future climate change will affect the extreme weather conditions at sea and there is a need for stochastic models that can describe the variability in both space and time at various scales of the environmental conditions. Previously, Bayesian hierarchical space-time models have been developed to describe the variability and complex dependence structures of significant wave height in space and time. These models were found to perform reasonably well and provided some interesting results, in particular, pertaining to long-term trends in the wave climate. In this paper, a similar framework is applied to oceanic windiness and the spatial and temporal variability of the 10-m wind speed over an area in the North Atlantic ocean is investigated. When the results from the model for North Atlantic windiness is compared to the results for significant wave height over the same area, it is interesting to observe that whereas an increasing trend in significant wave height was identified, no statistically significant long-term trend was estimated in windiness. This may indicate that the increase in significant wave height is not due to an increase in locally generated wind waves, but rather to increased swell. This observation is also consistent with studies that have suggested a poleward shift of the main storm tracks.

  20. Hydraulic fracture propagation modeling and data-based fracture identification

    Science.gov (United States)

    Zhou, Jing

    Successful shale gas and tight oil production is enabled by the engineering innovation of horizontal drilling and hydraulic fracturing. Hydraulically induced fractures will most likely deviate from the bi-wing planar pattern and generate complex fracture networks due to mechanical interactions and reservoir heterogeneity, both of which render the conventional fracture simulators insufficient to characterize the fractured reservoir. Moreover, in reservoirs with ultra-low permeability, the natural fractures are widely distributed, which will result in hydraulic fractures branching and merging at the interface and consequently lead to the creation of more complex fracture networks. Thus, developing a reliable hydraulic fracturing simulator, including both mechanical interaction and fluid flow, is critical in maximizing hydrocarbon recovery and optimizing fracture/well design and completion strategy in multistage horizontal wells. A novel fully coupled reservoir flow and geomechanics model based on the dual-lattice system is developed to simulate multiple nonplanar fractures' propagation in both homogeneous and heterogeneous reservoirs with or without pre-existing natural fractures. Initiation, growth, and coalescence of the microcracks will lead to the generation of macroscopic fractures, which is explicitly mimicked by failure and removal of bonds between particles from the discrete element network. This physics-based modeling approach leads to realistic fracture patterns without using the empirical rock failure and fracture propagation criteria required in conventional continuum methods. Based on this model, a sensitivity study is performed to investigate the effects of perforation spacing, in-situ stress anisotropy, rock properties (Young's modulus, Poisson's ratio, and compressive strength), fluid properties, and natural fracture properties on hydraulic fracture propagation. In addition, since reservoirs are buried thousands of feet below the surface, the

  1. Mathematical modelling of fracture hydrology

    International Nuclear Information System (INIS)

    Herbert, A.W.; Hodgkindon, D.P.; Lever, D.A.; Robinson, P.C.; Rae, J.

    1985-01-01

    This report reviews work carried out between January 1983 and December 1984 for the CEC/DOE contract 'Mathematical Modelling of Fracture Hydrology' which forms part of the CEC Mirage project (CEC 1984. Come 1985. Bourke et. al. 1983). It describes the development and use of a variety of mathematical models for the flow of water and transport of radionuclides in flowing groundwater. These models have an important role to play in assessing the long-term safety of radioactive waste burial, and in the planning and interpretation of associated experiments. The work is reported under five headings, namely 1) Statistical fracture network modelling, 2) Continuum models of flow and transport, 3) Simplified models, 4) Analysis of laboratory experiments, 5) Analysis of field experiments

  2. Mathematical modelling of fracture hydrology

    International Nuclear Information System (INIS)

    Rae, J.; Hodgkinson, D.P.; Robinson, P.C.; Herbert, A.W.

    1984-04-01

    This progress report contains notes on three aspects of hydrological modelling. Work on hydrodynamic dispersion in fractured media has been extended to transverse dispersion. Further work has been done on diffusion into the rock matrix and its effect on solute transport. The program NAMSOL has been used for the MIRAGE code comparison exercise being organised by Atkins R and D. (author)

  3. Fracture mechanics model of fragmentation

    International Nuclear Information System (INIS)

    Glenn, L.A.; Gommerstadt, B.Y.; Chudnovsky, A.

    1986-01-01

    A model of the fragmentation process is developed, based on the theory of linear elastic fracture mechanics, which predicts the average fragment size as a function of strain rate and material properties. This approach permits a unification of previous results, yielding Griffith's solution in the low-strain-rate limit and Grady's solution at high strain rates

  4. What are hierarchical models and how do we analyze them?

    Science.gov (United States)

    Royle, Andy

    2016-01-01

    In this chapter we provide a basic definition of hierarchical models and introduce the two canonical hierarchical models in this book: site occupancy and N-mixture models. The former is a hierarchical extension of logistic regression and the latter is a hierarchical extension of Poisson regression. We introduce basic concepts of probability modeling and statistical inference including likelihood and Bayesian perspectives. We go through the mechanics of maximizing the likelihood and characterizing the posterior distribution by Markov chain Monte Carlo (MCMC) methods. We give a general perspective on topics such as model selection and assessment of model fit, although we demonstrate these topics in practice in later chapters (especially Chapters 5, 6, 7, and 10 Chapter 5 Chapter 6 Chapter 7 Chapter 10)

  5. Hierarchical Neural Regression Models for Customer Churn Prediction

    Directory of Open Access Journals (Sweden)

    Golshan Mohammadi

    2013-01-01

    Full Text Available As customers are the main assets of each industry, customer churn prediction is becoming a major task for companies to remain in competition with competitors. In the literature, the better applicability and efficiency of hierarchical data mining techniques has been reported. This paper considers three hierarchical models by combining four different data mining techniques for churn prediction, which are backpropagation artificial neural networks (ANN, self-organizing maps (SOM, alpha-cut fuzzy c-means (α-FCM, and Cox proportional hazards regression model. The hierarchical models are ANN + ANN + Cox, SOM + ANN + Cox, and α-FCM + ANN + Cox. In particular, the first component of the models aims to cluster data in two churner and nonchurner groups and also filter out unrepresentative data or outliers. Then, the clustered data as the outputs are used to assign customers to churner and nonchurner groups by the second technique. Finally, the correctly classified data are used to create Cox proportional hazards model. To evaluate the performance of the hierarchical models, an Iranian mobile dataset is considered. The experimental results show that the hierarchical models outperform the single Cox regression baseline model in terms of prediction accuracy, Types I and II errors, RMSE, and MAD metrics. In addition, the α-FCM + ANN + Cox model significantly performs better than the two other hierarchical models.

  6. The Revised Hierarchical Model: A critical review and assessment

    OpenAIRE

    Kroll, Judith F.; van Hell, Janet G.; Tokowicz, Natasha; Green, David W.

    2010-01-01

    Brysbaert and Duyck (2009) suggest that it is time to abandon the Revised Hierarchical Model (Kroll and Stewart, 1994) in favor of connectionist models such as BIA+ (Dijkstra and Van Heuven, 2002) that more accurately account for the recent evidence on nonselective access in bilingual word recognition. In this brief response, we first review the history of the Revised Hierarchical Model (RHM), consider the set of issues that it was proposed to address, and then evaluate the evidence that supp...

  7. Hierarchical regression analysis in structural Equation Modeling

    NARCIS (Netherlands)

    de Jong, P.F.

    1999-01-01

    In a hierarchical or fixed-order regression analysis, the independent variables are entered into the regression equation in a prespecified order. Such an analysis is often performed when the extra amount of variance accounted for in a dependent variable by a specific independent variable is the main

  8. Slow logarithmic relaxation in models with hierarchically constrained dynamics

    OpenAIRE

    Brey, J. J.; Prados, A.

    2000-01-01

    A general kind of models with hierarchically constrained dynamics is shown to exhibit logarithmic anomalous relaxation, similarly to a variety of complex strongly interacting materials. The logarithmic behavior describes most of the decay of the response function.

  9. Bayesian disease mapping: hierarchical modeling in spatial epidemiology

    National Research Council Canada - National Science Library

    Lawson, Andrew

    2013-01-01

    .... Exploring these new developments, Bayesian Disease Mapping: Hierarchical Modeling in Spatial Epidemiology, Second Edition provides an up-to-date, cohesive account of the full range of Bayesian disease mapping methods and applications...

  10. Quantum Ising model on hierarchical structures

    International Nuclear Information System (INIS)

    Lin Zhifang; Tao Ruibao.

    1989-11-01

    A quantum Ising chain with both the exchange couplings and the transverse fields arranged in a hierarchical way is considered. Exact analytical results for the critical line and energy gap are obtained. It is shown that when R 1 not= R 2 , where R 1 and R 2 are the hierarchical parameters for the exchange couplings and the transverse fields, respectively, the system undergoes a phase transition in a different universality class from the pure quantum Ising chain with R 1 =R 2 =1. On the other hand, when R 1 =R 2 =R, there exists a critical value R c dependent on the furcating number of the hierarchy. In case of R > R c , the system is shown to exhibit as Ising-like critical point with the critical behaviour the same as in the pure case, while for R c the system belongs to another universality class. (author). 19 refs, 2 figs

  11. Road network safety evaluation using Bayesian hierarchical joint model.

    Science.gov (United States)

    Wang, Jie; Huang, Helai

    2016-05-01

    Safety and efficiency are commonly regarded as two significant performance indicators of transportation systems. In practice, road network planning has focused on road capacity and transport efficiency whereas the safety level of a road network has received little attention in the planning stage. This study develops a Bayesian hierarchical joint model for road network safety evaluation to help planners take traffic safety into account when planning a road network. The proposed model establishes relationships between road network risk and micro-level variables related to road entities and traffic volume, as well as socioeconomic, trip generation and network density variables at macro level which are generally used for long term transportation plans. In addition, network spatial correlation between intersections and their connected road segments is also considered in the model. A road network is elaborately selected in order to compare the proposed hierarchical joint model with a previous joint model and a negative binomial model. According to the results of the model comparison, the hierarchical joint model outperforms the joint model and negative binomial model in terms of the goodness-of-fit and predictive performance, which indicates the reasonableness of considering the hierarchical data structure in crash prediction and analysis. Moreover, both random effects at the TAZ level and the spatial correlation between intersections and their adjacent segments are found to be significant, supporting the employment of the hierarchical joint model as an alternative in road-network-level safety modeling as well. Copyright © 2016 Elsevier Ltd. All rights reserved.

  12. Advances in Applications of Hierarchical Bayesian Methods with Hydrological Models

    Science.gov (United States)

    Alexander, R. B.; Schwarz, G. E.; Boyer, E. W.

    2017-12-01

    Mechanistic and empirical watershed models are increasingly used to inform water resource decisions. Growing access to historical stream measurements and data from in-situ sensor technologies has increased the need for improved techniques for coupling models with hydrological measurements. Techniques that account for the intrinsic uncertainties of both models and measurements are especially needed. Hierarchical Bayesian methods provide an efficient modeling tool for quantifying model and prediction uncertainties, including those associated with measurements. Hierarchical methods can also be used to explore spatial and temporal variations in model parameters and uncertainties that are informed by hydrological measurements. We used hierarchical Bayesian methods to develop a hybrid (statistical-mechanistic) SPARROW (SPAtially Referenced Regression On Watershed attributes) model of long-term mean annual streamflow across diverse environmental and climatic drainages in 18 U.S. hydrological regions. Our application illustrates the use of a new generation of Bayesian methods that offer more advanced computational efficiencies than the prior generation. Evaluations of the effects of hierarchical (regional) variations in model coefficients and uncertainties on model accuracy indicates improved prediction accuracies (median of 10-50%) but primarily in humid eastern regions, where model uncertainties are one-third of those in arid western regions. Generally moderate regional variability is observed for most hierarchical coefficients. Accounting for measurement and structural uncertainties, using hierarchical state-space techniques, revealed the effects of spatially-heterogeneous, latent hydrological processes in the "localized" drainages between calibration sites; this improved model precision, with only minor changes in regional coefficients. Our study can inform advances in the use of hierarchical methods with hydrological models to improve their integration with stream

  13. Micromechanics modelling of ductile fracture

    CERN Document Server

    Chen, Zengtao

    2013-01-01

    This book summarizes research advances in micromechanics modelling of ductile fractures made in the past two decades. The ultimate goal of this book is to reach manufacturing frontline designers and materials engineers by providing a user-oriented, theoretical background of micromechanics modeling. Accordingly, the book is organized in a unique way and presents a vigorous damage percolation model developed by the authors over the last ten years. This model overcomes almost all difficulties of the existing models and can be used to completely accommodate ductile damage development within a single, measured microstructure frame. Related void damage criteria including nucleation, growth and coalescence are then discussed in detail: how they are improved, when and where they are used in the model, and how the model performs in comparison with the existing models. Sample forming simulations are provided to illustrate the model’s performance.

  14. Hierarchical Bayesian Modeling of Fluid-Induced Seismicity

    Science.gov (United States)

    Broccardo, M.; Mignan, A.; Wiemer, S.; Stojadinovic, B.; Giardini, D.

    2017-11-01

    In this study, we present a Bayesian hierarchical framework to model fluid-induced seismicity. The framework is based on a nonhomogeneous Poisson process with a fluid-induced seismicity rate proportional to the rate of injected fluid. The fluid-induced seismicity rate model depends upon a set of physically meaningful parameters and has been validated for six fluid-induced case studies. In line with the vision of hierarchical Bayesian modeling, the rate parameters are considered as random variables. We develop both the Bayesian inference and updating rules, which are used to develop a probabilistic forecasting model. We tested the Basel 2006 fluid-induced seismic case study to prove that the hierarchical Bayesian model offers a suitable framework to coherently encode both epistemic uncertainty and aleatory variability. Moreover, it provides a robust and consistent short-term seismic forecasting model suitable for online risk quantification and mitigation.

  15. Assessing alternative conceptual models of fracture flow

    International Nuclear Information System (INIS)

    Ho, C.K.

    1995-01-01

    The numerical code TOUGH2 was used to assess alternative conceptual models of fracture flow. The models that were considered included the equivalent continuum model (ECM) and the dual permeability (DK) model. A one-dimensional, layered, unsaturated domain was studied with a saturated bottom boundary and a constant infiltration at the top boundary. Two different infiltration rates were used in the studies. In addition, the connection areas between the fracture and matrix elements in the dual permeability model were varied. Results showed that the two conceptual models of fracture flow produced different saturation and velocity profiles-even under steady-state conditions. The magnitudes of the discrepancies were sensitive to two parameters that affected the flux between the fractures and matrix in the dual permeability model: (1) the fracture-matrix connection areas and (2) the capillary pressure gradients between the fracture and matrix elements

  16. Model of T-Type Fracture in Coal Fracturing and Analysis of Influence Factors of Fracture Morphology

    Directory of Open Access Journals (Sweden)

    Yuwei Li

    2018-05-01

    Full Text Available Special T-type fractures can be formed when coal is hydraulically fractured and there is currently no relevant theoretical model to calculate and describe them. This paper first establishes the height calculation model of vertical fractures in multi-layered formations and deduces the stress intensity factor (SIF at the upper and lower sides of the fracture in the process of vertical fracture extension. Combined with the fracture tip stress analysis method of fracture mechanics theory, the horizontal bedding is taken into account for tensile and shear failure, and the critical mechanical conditions for the formation of horizontal fracture in coal are obtained. Finally, the model of T-type fracture in coal fracturing is established, and it is verified by fracturing simulation experiments. The model calculation result shows that the increase of vertical fracture height facilitates the increase of horizontal fracture length. The fracture toughness of coal has a significant influence on the length of horizontal fracture and there is a threshold. When the fracture toughness is less than the threshold, the length of horizontal fracture remains unchanged, otherwise, the length of horizontal fracture increases rapidly with the increase of fracture toughness. When the shear strength of the interface between the coalbed and the interlayer increases, the length of the horizontal fracture of the T-type fracture rapidly decreases.

  17. Determining Predictor Importance in Hierarchical Linear Models Using Dominance Analysis

    Science.gov (United States)

    Luo, Wen; Azen, Razia

    2013-01-01

    Dominance analysis (DA) is a method used to evaluate the relative importance of predictors that was originally proposed for linear regression models. This article proposes an extension of DA that allows researchers to determine the relative importance of predictors in hierarchical linear models (HLM). Commonly used measures of model adequacy in…

  18. A hierarchical lattice spring model to simulate the mechanics of 2-D materials-based composites

    Directory of Open Access Journals (Sweden)

    Lucas eBrely

    2015-07-01

    Full Text Available In the field of engineering materials, strength and toughness are typically two mutually exclusive properties. Structural biological materials such as bone, tendon or dentin have resolved this conflict and show unprecedented damage tolerance, toughness and strength levels. The common feature of these materials is their hierarchical heterogeneous structure, which contributes to increased energy dissipation before failure occurring at different scale levels. These structural properties are the key to exceptional bioinspired material mechanical properties, in particular for nanocomposites. Here, we develop a numerical model in order to simulate the mechanisms involved in damage progression and energy dissipation at different size scales in nano- and macro-composites, which depend both on the heterogeneity of the material and on the type of hierarchical structure. Both these aspects have been incorporated into a 2-dimensional model based on a Lattice Spring Model, accounting for geometrical nonlinearities and including statistically-based fracture phenomena. The model has been validated by comparing numerical results to continuum and fracture mechanics results as well as finite elements simulations, and then employed to study how structural aspects impact on hierarchical composite material properties. Results obtained with the numerical code highlight the dependence of stress distributions on matrix properties and reinforcement dispersion, geometry and properties, and how failure of sacrificial elements is directly involved in the damage tolerance of the material. Thanks to the rapidly developing field of nanocomposite manufacture, it is already possible to artificially create materials with multi-scale hierarchical reinforcements. The developed code could be a valuable support in the design and optimization of these advanced materials, drawing inspiration and going beyond biological materials with exceptional mechanical properties.

  19. Multi-scale modeling of inter-granular fracture in UO2

    Energy Technology Data Exchange (ETDEWEB)

    Chakraborty, Pritam [Idaho National Lab. (INL), Idaho Falls, ID (United States); Zhang, Yongfeng [Idaho National Lab. (INL), Idaho Falls, ID (United States); Tonks, Michael R. [Idaho National Lab. (INL), Idaho Falls, ID (United States); Biner, S. Bulent [Idaho National Lab. (INL), Idaho Falls, ID (United States)

    2015-03-01

    A hierarchical multi-scale approach is pursued in this work to investigate the influence of porosity, pore and grain size on the intergranular brittle fracture in UO2. In this approach, molecular dynamics simulations are performed to obtain the fracture properties for different grain boundary types. A phase-field model is then utilized to perform intergranular fracture simulations of representative microstructures with different porosities, pore and grain sizes. In these simulations the grain boundary fracture properties obtained from molecular dynamics simulations are used. The responses from the phase-field fracture simulations are then fitted with a stress-based brittle fracture model usable at the engineering scale. This approach encapsulates three different length and time scales, and allows the development of microstructurally informed engineering scale model from properties evaluated at the atomistic scale.

  20. Hierarchical modeling of molecular energies using a deep neural network

    Science.gov (United States)

    Lubbers, Nicholas; Smith, Justin S.; Barros, Kipton

    2018-06-01

    We introduce the Hierarchically Interacting Particle Neural Network (HIP-NN) to model molecular properties from datasets of quantum calculations. Inspired by a many-body expansion, HIP-NN decomposes properties, such as energy, as a sum over hierarchical terms. These terms are generated from a neural network—a composition of many nonlinear transformations—acting on a representation of the molecule. HIP-NN achieves the state-of-the-art performance on a dataset of 131k ground state organic molecules and predicts energies with 0.26 kcal/mol mean absolute error. With minimal tuning, our model is also competitive on a dataset of molecular dynamics trajectories. In addition to enabling accurate energy predictions, the hierarchical structure of HIP-NN helps to identify regions of model uncertainty.

  1. Applying Hierarchical Model Calibration to Automatically Generated Items.

    Science.gov (United States)

    Williamson, David M.; Johnson, Matthew S.; Sinharay, Sandip; Bejar, Isaac I.

    This study explored the application of hierarchical model calibration as a means of reducing, if not eliminating, the need for pretesting of automatically generated items from a common item model prior to operational use. Ultimately the successful development of automatic item generation (AIG) systems capable of producing items with highly similar…

  2. A HIERARCHICAL SET OF MODELS FOR SPECIES RESPONSE ANALYSIS

    NARCIS (Netherlands)

    HUISMAN, J; OLFF, H; FRESCO, LFM

    Variation in the abundance of species in space and/or time can be caused by a wide range of underlying processes. Before such causes can be analysed we need simple mathematical models which can describe the observed response patterns. For this purpose a hierarchical set of models is presented. These

  3. A hierarchical set of models for species response analysis

    NARCIS (Netherlands)

    Huisman, J.; Olff, H.; Fresco, L.F.M.

    1993-01-01

    Variation in the abundance of species in space and/or time can be caused by a wide range of underlying processes. Before such causes can be analysed we need simple mathematical models which can describe the observed response patterns. For this purpose a hierarchical set of models is presented. These

  4. The Revised Hierarchical Model: A critical review and assessment

    NARCIS (Netherlands)

    Kroll, J.F.; Hell, J.G. van; Tokowicz, N.; Green, D.W.

    2010-01-01

    Brysbaert and Duyck (this issue) suggest that it is time to abandon the Revised Hierarchical Model (Kroll and Stewart, 1994) in favor of connectionist models such as BIA+ (Dijkstra and Van Heuven, 2002) that more accurately account for the recent evidence on non-selective access in bilingual word

  5. A hierarchical model exhibiting the Kosterlitz-Thouless fixed point

    International Nuclear Information System (INIS)

    Marchetti, D.H.U.; Perez, J.F.

    1985-01-01

    A hierarchical model for 2-d Coulomb gases displaying a line stable of fixed points describing the Kosterlitz-Thouless phase transition is constructed. For Coulomb gases corresponding to Z sub(N)- models these fixed points are stable for an intermediate temperature interval. (Author) [pt

  6. Hierarchical Multiple Markov Chain Model for Unsupervised Texture Segmentation

    Czech Academy of Sciences Publication Activity Database

    Scarpa, G.; Gaetano, R.; Haindl, Michal; Zerubia, J.

    2009-01-01

    Roč. 18, č. 8 (2009), s. 1830-1843 ISSN 1057-7149 R&D Projects: GA ČR GA102/08/0593 EU Projects: European Commission(XE) 507752 - MUSCLE Institutional research plan: CEZ:AV0Z10750506 Keywords : Classification * texture analysis * segmentation * hierarchical image models * Markov process Subject RIV: BD - Theory of Information Impact factor: 2.848, year: 2009 http://library.utia.cas.cz/separaty/2009/RO/haindl-hierarchical multiple markov chain model for unsupervised texture segmentation.pdf

  7. Hierarchical graphs for rule-based modeling of biochemical systems

    Directory of Open Access Journals (Sweden)

    Hu Bin

    2011-02-01

    Full Text Available Abstract Background In rule-based modeling, graphs are used to represent molecules: a colored vertex represents a component of a molecule, a vertex attribute represents the internal state of a component, and an edge represents a bond between components. Components of a molecule share the same color. Furthermore, graph-rewriting rules are used to represent molecular interactions. A rule that specifies addition (removal of an edge represents a class of association (dissociation reactions, and a rule that specifies a change of a vertex attribute represents a class of reactions that affect the internal state of a molecular component. A set of rules comprises an executable model that can be used to determine, through various means, the system-level dynamics of molecular interactions in a biochemical system. Results For purposes of model annotation, we propose the use of hierarchical graphs to represent structural relationships among components and subcomponents of molecules. We illustrate how hierarchical graphs can be used to naturally document the structural organization of the functional components and subcomponents of two proteins: the protein tyrosine kinase Lck and the T cell receptor (TCR complex. We also show that computational methods developed for regular graphs can be applied to hierarchical graphs. In particular, we describe a generalization of Nauty, a graph isomorphism and canonical labeling algorithm. The generalized version of the Nauty procedure, which we call HNauty, can be used to assign canonical labels to hierarchical graphs or more generally to graphs with multiple edge types. The difference between the Nauty and HNauty procedures is minor, but for completeness, we provide an explanation of the entire HNauty algorithm. Conclusions Hierarchical graphs provide more intuitive formal representations of proteins and other structured molecules with multiple functional components than do the regular graphs of current languages for

  8. A Hierarchal Risk Assessment Model Using the Evidential Reasoning Rule

    Directory of Open Access Journals (Sweden)

    Xiaoxiao Ji

    2017-02-01

    Full Text Available This paper aims to develop a hierarchical risk assessment model using the newly-developed evidential reasoning (ER rule, which constitutes a generic conjunctive probabilistic reasoning process. In this paper, we first provide a brief introduction to the basics of the ER rule and emphasize the strengths for representing and aggregating uncertain information from multiple experts and sources. Further, we discuss the key steps of developing the hierarchical risk assessment framework systematically, including (1 formulation of risk assessment hierarchy; (2 representation of both qualitative and quantitative information; (3 elicitation of attribute weights and information reliabilities; (4 aggregation of assessment information using the ER rule and (5 quantification and ranking of risks using utility-based transformation. The proposed hierarchical risk assessment framework can potentially be implemented to various complex and uncertain systems. A case study on the fire/explosion risk assessment of marine vessels demonstrates the applicability of the proposed risk assessment model.

  9. Comparing hierarchical models via the marginalized deviance information criterion.

    Science.gov (United States)

    Quintero, Adrian; Lesaffre, Emmanuel

    2018-07-20

    Hierarchical models are extensively used in pharmacokinetics and longitudinal studies. When the estimation is performed from a Bayesian approach, model comparison is often based on the deviance information criterion (DIC). In hierarchical models with latent variables, there are several versions of this statistic: the conditional DIC (cDIC) that incorporates the latent variables in the focus of the analysis and the marginalized DIC (mDIC) that integrates them out. Regardless of the asymptotic and coherency difficulties of cDIC, this alternative is usually used in Markov chain Monte Carlo (MCMC) methods for hierarchical models because of practical convenience. The mDIC criterion is more appropriate in most cases but requires integration of the likelihood, which is computationally demanding and not implemented in Bayesian software. Therefore, we consider a method to compute mDIC by generating replicate samples of the latent variables that need to be integrated out. This alternative can be easily conducted from the MCMC output of Bayesian packages and is widely applicable to hierarchical models in general. Additionally, we propose some approximations in order to reduce the computational complexity for large-sample situations. The method is illustrated with simulated data sets and 2 medical studies, evidencing that cDIC may be misleading whilst mDIC appears pertinent. Copyright © 2018 John Wiley & Sons, Ltd.

  10. Conceptual hierarchical modeling to describe wetland plant community organization

    Science.gov (United States)

    Little, A.M.; Guntenspergen, G.R.; Allen, T.F.H.

    2010-01-01

    Using multivariate analysis, we created a hierarchical modeling process that describes how differently-scaled environmental factors interact to affect wetland-scale plant community organization in a system of small, isolated wetlands on Mount Desert Island, Maine. We followed the procedure: 1) delineate wetland groups using cluster analysis, 2) identify differently scaled environmental gradients using non-metric multidimensional scaling, 3) order gradient hierarchical levels according to spatiotem-poral scale of fluctuation, and 4) assemble hierarchical model using group relationships with ordination axes and post-hoc tests of environmental differences. Using this process, we determined 1) large wetland size and poor surface water chemistry led to the development of shrub fen wetland vegetation, 2) Sphagnum and water chemistry differences affected fen vs. marsh / sedge meadows status within small wetlands, and 3) small-scale hydrologic differences explained transitions between forested vs. non-forested and marsh vs. sedge meadow vegetation. This hierarchical modeling process can help explain how upper level contextual processes constrain biotic community response to lower-level environmental changes. It creates models with more nuanced spatiotemporal complexity than classification and regression tree procedures. Using this process, wetland scientists will be able to generate more generalizable theories of plant community organization, and useful management models. ?? Society of Wetland Scientists 2009.

  11. Control of discrete event systems modeled as hierarchical state machines

    Science.gov (United States)

    Brave, Y.; Heymann, M.

    1991-01-01

    The authors examine a class of discrete event systems (DESs) modeled as asynchronous hierarchical state machines (AHSMs). For this class of DESs, they provide an efficient method for testing reachability, which is an essential step in many control synthesis procedures. This method utilizes the asynchronous nature and hierarchical structure of AHSMs, thereby illustrating the advantage of the AHSM representation as compared with its equivalent (flat) state machine representation. An application of the method is presented where an online minimally restrictive solution is proposed for the problem of maintaining a controlled AHSM within prescribed legal bounds.

  12. Hierarchical modelling for the environmental sciences statistical methods and applications

    CERN Document Server

    Clark, James S

    2006-01-01

    New statistical tools are changing the way in which scientists analyze and interpret data and models. Hierarchical Bayes and Markov Chain Monte Carlo methods for analysis provide a consistent framework for inference and prediction where information is heterogeneous and uncertain, processes are complicated, and responses depend on scale. Nowhere are these methods more promising than in the environmental sciences.

  13. Analysis of Error Propagation Within Hierarchical Air Combat Models

    Science.gov (United States)

    2016-06-01

    values alone are propagated through layers of combat models, the final results will likely be biased, and risk underestimated. An air-to-air...values alone are propagated through layers of combat models, the final results will likely be biased, and risk underestimated. An air-to-air engagement... PROPAGATION WITHIN HIERARCHICAL AIR COMBAT MODELS by Salih Ilaslan June 2016 Thesis Advisor: Thomas W. Lucas Second Reader: Jeffrey

  14. Modeling interfacial fracture in Sierra.

    Energy Technology Data Exchange (ETDEWEB)

    Brown, Arthur A.; Ohashi, Yuki; Lu, Wei-Yang; Nelson, Stacy A. C.; Foulk, James W.,; Reedy, Earl David,; Austin, Kevin N.; Margolis, Stephen B.

    2013-09-01

    This report summarizes computational efforts to model interfacial fracture using cohesive zone models in the SIERRA/SolidMechanics (SIERRA/SM) finite element code. Cohesive surface elements were used to model crack initiation and propagation along predefined paths. Mesh convergence was observed with SIERRA/SM for numerous geometries. As the funding for this project came from the Advanced Simulation and Computing Verification and Validation (ASC V&V) focus area, considerable effort was spent performing verification and validation. Code verification was performed to compare code predictions to analytical solutions for simple three-element simulations as well as a higher-fidelity simulation of a double-cantilever beam. Parameter identification was conducted with Dakota using experimental results on asymmetric double-cantilever beam (ADCB) and end-notched-flexure (ENF) experiments conducted under Campaign-6 funding. Discretization convergence studies were also performed with respect to mesh size and time step and an optimization study was completed for mode II delamination using the ENF geometry. Throughout this verification process, numerous SIERRA/SM bugs were found and reported, all of which have been fixed, leading to over a 10-fold increase in convergence rates. Finally, mixed-mode flexure experiments were performed for validation. One of the unexplained issues encountered was material property variability for ostensibly the same composite material. Since the variability is not fully understood, it is difficult to accurately assess uncertainty when performing predictions.

  15. Metastable states in the hierarchical Dyson model drive parallel processing in the hierarchical Hopfield network

    International Nuclear Information System (INIS)

    Agliari, Elena; Barra, Adriano; Guerra, Francesco; Galluzzi, Andrea; Tantari, Daniele; Tavani, Flavia

    2015-01-01

    In this paper, we introduce and investigate the statistical mechanics of hierarchical neural networks. First, we approach these systems à la Mattis, by thinking of the Dyson model as a single-pattern hierarchical neural network. We also discuss the stability of different retrievable states as predicted by the related self-consistencies obtained both from a mean-field bound and from a bound that bypasses the mean-field limitation. The latter is worked out by properly reabsorbing the magnetization fluctuations related to higher levels of the hierarchy into effective fields for the lower levels. Remarkably, mixing Amit's ansatz technique for selecting candidate-retrievable states with the interpolation procedure for solving for the free energy of these states, we prove that, due to gauge symmetry, the Dyson model accomplishes both serial and parallel processing. We extend this scenario to multiple stored patterns by implementing the Hebb prescription for learning within the couplings. This results in Hopfield-like networks constrained on a hierarchical topology, for which, by restricting to the low-storage regime where the number of patterns grows at its most logarithmical with the amount of neurons, we prove the existence of the thermodynamic limit for the free energy, and we give an explicit expression of its mean-field bound and of its related improved bound. We studied the resulting self-consistencies for the Mattis magnetizations, which act as order parameters, are studied and the stability of solutions is analyzed to get a picture of the overall retrieval capabilities of the system according to both mean-field and non-mean-field scenarios. Our main finding is that embedding the Hebbian rule on a hierarchical topology allows the network to accomplish both serial and parallel processing. By tuning the level of fast noise affecting it or triggering the decay of the interactions with the distance among neurons, the system may switch from sequential retrieval to

  16. Hierarchical material models for fragmentation modeling in NIF-ALE-AMR

    International Nuclear Information System (INIS)

    Fisher, A C; Masters, N D; Koniges, A E; Anderson, R W; Gunney, B T N; Wang, P; Becker, R; Dixit, P; Benson, D J

    2008-01-01

    Fragmentation is a fundamental process that naturally spans micro to macroscopic scales. Recent advances in algorithms, computer simulations, and hardware enable us to connect the continuum to microstructural regimes in a real simulation through a heterogeneous multiscale mathematical model. We apply this model to the problem of predicting how targets in the NIF chamber dismantle, so that optics and diagnostics can be protected from damage. The mechanics of the initial material fracture depend on the microscopic grain structure. In order to effectively simulate the fragmentation, this process must be modeled at the subgrain level with computationally expensive crystal plasticity models. However, there are not enough computational resources to model the entire NIF target at this microscopic scale. In order to accomplish these calculations, a hierarchical material model (HMM) is being developed. The HMM will allow fine-scale modeling of the initial fragmentation using computationally expensive crystal plasticity, while the elements at the mesoscale can use polycrystal models, and the macroscopic elements use analytical flow stress models. The HMM framework is built upon an adaptive mesh refinement (AMR) capability. We present progress in implementing the HMM in the NIF-ALE-AMR code. Additionally, we present test simulations relevant to NIF targets

  17. Hierarchical material models for fragmentation modeling in NIF-ALE-AMR

    Energy Technology Data Exchange (ETDEWEB)

    Fisher, A C; Masters, N D; Koniges, A E; Anderson, R W; Gunney, B T N; Wang, P; Becker, R [Lawrence Livermore National Laboratory, PO Box 808, Livermore, CA 94551 (United States); Dixit, P; Benson, D J [University of California San Diego, 9500 Gilman Dr., La Jolla. CA 92093 (United States)], E-mail: fisher47@llnl.gov

    2008-05-15

    Fragmentation is a fundamental process that naturally spans micro to macroscopic scales. Recent advances in algorithms, computer simulations, and hardware enable us to connect the continuum to microstructural regimes in a real simulation through a heterogeneous multiscale mathematical model. We apply this model to the problem of predicting how targets in the NIF chamber dismantle, so that optics and diagnostics can be protected from damage. The mechanics of the initial material fracture depend on the microscopic grain structure. In order to effectively simulate the fragmentation, this process must be modeled at the subgrain level with computationally expensive crystal plasticity models. However, there are not enough computational resources to model the entire NIF target at this microscopic scale. In order to accomplish these calculations, a hierarchical material model (HMM) is being developed. The HMM will allow fine-scale modeling of the initial fragmentation using computationally expensive crystal plasticity, while the elements at the mesoscale can use polycrystal models, and the macroscopic elements use analytical flow stress models. The HMM framework is built upon an adaptive mesh refinement (AMR) capability. We present progress in implementing the HMM in the NIF-ALE-AMR code. Additionally, we present test simulations relevant to NIF targets.

  18. Hierarchical Models of the Nearshore Complex System

    National Research Council Canada - National Science Library

    Werner, Brad

    2004-01-01

    .... This grant was termination funding for the Werner group, specifically aimed at finishing up and publishing research related to synoptic imaging of near shore bathymetry, testing models for beach cusp...

  19. Hierarchical and coupling model of factors influencing vessel traffic flow.

    Directory of Open Access Journals (Sweden)

    Zhao Liu

    Full Text Available Understanding the characteristics of vessel traffic flow is crucial in maintaining navigation safety, efficiency, and overall waterway transportation management. Factors influencing vessel traffic flow possess diverse features such as hierarchy, uncertainty, nonlinearity, complexity, and interdependency. To reveal the impact mechanism of the factors influencing vessel traffic flow, a hierarchical model and a coupling model are proposed in this study based on the interpretative structural modeling method. The hierarchical model explains the hierarchies and relationships of the factors using a graph. The coupling model provides a quantitative method that explores interaction effects of factors using a coupling coefficient. The coupling coefficient is obtained by determining the quantitative indicators of the factors and their weights. Thereafter, the data obtained from Port of Tianjin is used to verify the proposed coupling model. The results show that the hierarchical model of the factors influencing vessel traffic flow can explain the level, structure, and interaction effect of the factors; the coupling model is efficient in analyzing factors influencing traffic volumes. The proposed method can be used for analyzing increases in vessel traffic flow in waterway transportation system.

  20. Hierarchical and coupling model of factors influencing vessel traffic flow.

    Science.gov (United States)

    Liu, Zhao; Liu, Jingxian; Li, Huanhuan; Li, Zongzhi; Tan, Zhirong; Liu, Ryan Wen; Liu, Yi

    2017-01-01

    Understanding the characteristics of vessel traffic flow is crucial in maintaining navigation safety, efficiency, and overall waterway transportation management. Factors influencing vessel traffic flow possess diverse features such as hierarchy, uncertainty, nonlinearity, complexity, and interdependency. To reveal the impact mechanism of the factors influencing vessel traffic flow, a hierarchical model and a coupling model are proposed in this study based on the interpretative structural modeling method. The hierarchical model explains the hierarchies and relationships of the factors using a graph. The coupling model provides a quantitative method that explores interaction effects of factors using a coupling coefficient. The coupling coefficient is obtained by determining the quantitative indicators of the factors and their weights. Thereafter, the data obtained from Port of Tianjin is used to verify the proposed coupling model. The results show that the hierarchical model of the factors influencing vessel traffic flow can explain the level, structure, and interaction effect of the factors; the coupling model is efficient in analyzing factors influencing traffic volumes. The proposed method can be used for analyzing increases in vessel traffic flow in waterway transportation system.

  1. Multiphase flow models for hydraulic fracturing technology

    Science.gov (United States)

    Osiptsov, Andrei A.

    2017-10-01

    The technology of hydraulic fracturing of a hydrocarbon-bearing formation is based on pumping a fluid with particles into a well to create fractures in porous medium. After the end of pumping, the fractures filled with closely packed proppant particles create highly conductive channels for hydrocarbon flow from far-field reservoir to the well to surface. The design of the hydraulic fracturing treatment is carried out with a simulator. Those simulators are based on mathematical models, which need to be accurate and close to physical reality. The entire process of fracture placement and flowback/cleanup can be conventionally split into the following four stages: (i) quasi-steady state effectively single-phase suspension flow down the wellbore, (ii) particle transport in an open vertical fracture, (iii) displacement of fracturing fluid by hydrocarbons from the closed fracture filled with a random close pack of proppant particles, and, finally, (iv) highly transient gas-liquid flow in a well during cleanup. The stage (i) is relatively well described by the existing hydralics models, while the models for the other three stages of the process need revisiting and considerable improvement, which was the focus of the author’s research presented in this review paper. For stage (ii), we consider the derivation of a multi-fluid model for suspension flow in a narrow vertical hydraulic fracture at moderate Re on the scale of fracture height and length and also the migration of particles across the flow on the scale of fracture width. At the stage of fracture cleanaup (iii), a novel multi-continua model for suspension filtration is developed. To provide closure relationships for permeability of proppant packings to be used in this model, a 3D direct numerical simulation of single phase flow is carried out using the lattice-Boltzmann method. For wellbore cleanup (iv), we present a combined 1D model for highly-transient gas-liquid flow based on the combination of multi-fluid and

  2. Petascale Hierarchical Modeling VIA Parallel Execution

    Energy Technology Data Exchange (ETDEWEB)

    Gelman, Andrew [Principal Investigator

    2014-04-14

    The research allows more effective model building. By allowing researchers to fit complex models to large datasets in a scalable manner, our algorithms and software enable more effective scientific research. In the new area of “big data,” it is often necessary to fit “big models” to adjust for systematic differences between sample and population. For this task, scalable and efficient model-fitting tools are needed, and these have been achieved with our new Hamiltonian Monte Carlo algorithm, the no-U-turn sampler, and our new C++ program, Stan. In layman’s terms, our research enables researchers to create improved mathematical modes for large and complex systems.

  3. Hierarchical Modelling of Flood Risk for Engineering Decision Analysis

    DEFF Research Database (Denmark)

    Custer, Rocco

    protection structures in the hierarchical flood protection system - is identified. To optimise the design of protection structures, fragility and vulnerability models must allow for consideration of decision alternatives. While such vulnerability models are available for large protection structures (e...... systems, as well as the implementation of the flood risk analysis methodology and the vulnerability modelling approach are illustrated with an example application. In summary, the present thesis provides a characterisation of hierarchical flood protection systems as well as several methodologies to model...... and robust. Traditional risk management solutions, e.g. dike construction, are not particularly flexible, as they are difficult to adapt to changing risk. Conversely, the recent concept of integrated flood risk management, entailing a combination of several structural and non-structural risk management...

  4. A Hierarchical Visualization Analysis Model of Power Big Data

    Science.gov (United States)

    Li, Yongjie; Wang, Zheng; Hao, Yang

    2018-01-01

    Based on the conception of integrating VR scene and power big data analysis, a hierarchical visualization analysis model of power big data is proposed, in which levels are designed, targeting at different abstract modules like transaction, engine, computation, control and store. The regularly departed modules of power data storing, data mining and analysis, data visualization are integrated into one platform by this model. It provides a visual analysis solution for the power big data.

  5. Fully probabilistic design of hierarchical Bayesian models

    Czech Academy of Sciences Publication Activity Database

    Quinn, A.; Kárný, Miroslav; Guy, Tatiana Valentine

    2016-01-01

    Roč. 369, č. 1 (2016), s. 532-547 ISSN 0020-0255 R&D Projects: GA ČR GA13-13502S Institutional support: RVO:67985556 Keywords : Fully probabilistic design * Ideal distribution * Minimum cross-entropy principle * Bayesian conditioning * Kullback-Leibler divergence * Bayesian nonparametric modelling Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 4.832, year: 2016 http://library.utia.cas.cz/separaty/2016/AS/karny-0463052.pdf

  6. Hierarchical Model Predictive Control for Resource Distribution

    DEFF Research Database (Denmark)

    Bendtsen, Jan Dimon; Trangbæk, K; Stoustrup, Jakob

    2010-01-01

    units. The approach is inspired by smart-grid electric power production and consumption systems, where the flexibility of a large number of power producing and/or power consuming units can be exploited in a smart-grid solution. The objective is to accommodate the load variation on the grid, arising......This paper deals with hierarchichal model predictive control (MPC) of distributed systems. A three level hierachical approach is proposed, consisting of a high level MPC controller, a second level of so-called aggregators, controlled by an online MPC-like algorithm, and a lower level of autonomous...... on one hand from varying consumption, on the other hand by natural variations in power production e.g. from wind turbines. The approach presented is based on quadratic optimization and possess the properties of low algorithmic complexity and of scalability. In particular, the proposed design methodology...

  7. Introduction to Hierarchical Bayesian Modeling for Ecological Data

    CERN Document Server

    Parent, Eric

    2012-01-01

    Making statistical modeling and inference more accessible to ecologists and related scientists, Introduction to Hierarchical Bayesian Modeling for Ecological Data gives readers a flexible and effective framework to learn about complex ecological processes from various sources of data. It also helps readers get started on building their own statistical models. The text begins with simple models that progressively become more complex and realistic through explanatory covariates and intermediate hidden states variables. When fitting the models to data, the authors gradually present the concepts a

  8. A hierarchical spatiotemporal analog forecasting model for count data.

    Science.gov (United States)

    McDermott, Patrick L; Wikle, Christopher K; Millspaugh, Joshua

    2018-01-01

    Analog forecasting is a mechanism-free nonlinear method that forecasts a system forward in time by examining how past states deemed similar to the current state moved forward. Previous applications of analog forecasting has been successful at producing robust forecasts for a variety of ecological and physical processes, but it has typically been presented in an empirical or heuristic procedure, rather than as a formal statistical model. The methodology presented here extends the model-based analog method of McDermott and Wikle (Environmetrics, 27, 2016, 70) by placing analog forecasting within a fully hierarchical statistical framework that can accommodate count observations. Using a Bayesian approach, the hierarchical analog model is able to quantify rigorously the uncertainty associated with forecasts. Forecasting waterfowl settling patterns in the northwestern United States and Canada is conducted by applying the hierarchical analog model to a breeding population survey dataset. Sea surface temperature (SST) in the Pacific Ocean is used to help identify potential analogs for the waterfowl settling patterns.

  9. Bayesian hierarchical model for large-scale covariance matrix estimation.

    Science.gov (United States)

    Zhu, Dongxiao; Hero, Alfred O

    2007-12-01

    Many bioinformatics problems implicitly depend on estimating large-scale covariance matrix. The traditional approaches tend to give rise to high variance and low accuracy due to "overfitting." We cast the large-scale covariance matrix estimation problem into the Bayesian hierarchical model framework, and introduce dependency between covariance parameters. We demonstrate the advantages of our approaches over the traditional approaches using simulations and OMICS data analysis.

  10. Inclusion-initiated fracture model for ceramics

    International Nuclear Information System (INIS)

    Sung, J.; Nicholson, P.S.

    1990-01-01

    The fracture of ceramics initiating from a typical inclusion is analyzed. The inclusion is considered to have a thermal expansion coefficient and fracture toughness lower than those of the matrix and a Young's modulus higher than that of the matrix. Inclusion-initiated fracture is modeled for a spherical inclusion using a weight function method to compute the residual stress intensity factor for a part-through elliptical crack. The results are applied to an α-Al 2 O 3 inclusion embedded in a tetragonal ZrO 2 ceramic. The strength predictions agree well with experimental data

  11. Hierarchical composites: Analysis of damage evolution based on fiber bundle model

    DEFF Research Database (Denmark)

    Mishnaevsky, Leon

    2011-01-01

    A computational model of multiscale composites is developed on the basis of the fiber bundle model with the hierarchical load sharing rule, and employed to study the effect of the microstructures of hierarchical composites on their damage resistance. Two types of hierarchical materials were consi...

  12. Hierarchical modeling of cluster size in wildlife surveys

    Science.gov (United States)

    Royle, J. Andrew

    2008-01-01

    Clusters or groups of individuals are the fundamental unit of observation in many wildlife sampling problems, including aerial surveys of waterfowl, marine mammals, and ungulates. Explicit accounting of cluster size in models for estimating abundance is necessary because detection of individuals within clusters is not independent and detectability of clusters is likely to increase with cluster size. This induces a cluster size bias in which the average cluster size in the sample is larger than in the population at large. Thus, failure to account for the relationship between delectability and cluster size will tend to yield a positive bias in estimates of abundance or density. I describe a hierarchical modeling framework for accounting for cluster-size bias in animal sampling. The hierarchical model consists of models for the observation process conditional on the cluster size distribution and the cluster size distribution conditional on the total number of clusters. Optionally, a spatial model can be specified that describes variation in the total number of clusters per sample unit. Parameter estimation, model selection, and criticism may be carried out using conventional likelihood-based methods. An extension of the model is described for the situation where measurable covariates at the level of the sample unit are available. Several candidate models within the proposed class are evaluated for aerial survey data on mallard ducks (Anas platyrhynchos).

  13. A hierarchical community occurrence model for North Carolina stream fish

    Science.gov (United States)

    Midway, S.R.; Wagner, Tyler; Tracy, B.H.

    2016-01-01

    The southeastern USA is home to one of the richest—and most imperiled and threatened—freshwater fish assemblages in North America. For many of these rare and threatened species, conservation efforts are often limited by a lack of data. Drawing on a unique and extensive data set spanning over 20 years, we modeled occurrence probabilities of 126 stream fish species sampled throughout North Carolina, many of which occur more broadly in the southeastern USA. Specifically, we developed species-specific occurrence probabilities from hierarchical Bayesian multispecies models that were based on common land use and land cover covariates. We also used index of biotic integrity tolerance classifications as a second level in the model hierarchy; we identify this level as informative for our work, but it is flexible for future model applications. Based on the partial-pooling property of the models, we were able to generate occurrence probabilities for many imperiled and data-poor species in addition to highlighting a considerable amount of occurrence heterogeneity that supports species-specific investigations whenever possible. Our results provide critical species-level information on many threatened and imperiled species as well as information that may assist with re-evaluation of existing management strategies, such as the use of surrogate species. Finally, we highlight the use of a relatively simple hierarchical model that can easily be generalized for similar situations in which conventional models fail to provide reliable estimates for data-poor groups.

  14. RECENT ADVANCES IN NATURALLY FRACTURED RESERVOIR MODELING

    OpenAIRE

    ORDOÑEZ, A; PEÑUELA, G; IDROBO, E. A; MEDINA, C. E

    2001-01-01

    Large amounts of oil reserves are contained in naturally fractured reservoirs. Most of these hydrocarbon volumes have been left behind because of the poor knowledge and/or description methodology of those reservoirs. This lack of knowledge has lead to the nonexistence of good quantitative models for this complicated type of reservoirs. The complexity of naturally fractured reservoirs causes the need for integration of all existing information at all scales (drilling, well logging, seismic, we...

  15. Hierarchical Bayesian spatial models for multispecies conservation planning and monitoring.

    Science.gov (United States)

    Carroll, Carlos; Johnson, Devin S; Dunk, Jeffrey R; Zielinski, William J

    2010-12-01

    Biologists who develop and apply habitat models are often familiar with the statistical challenges posed by their data's spatial structure but are unsure of whether the use of complex spatial models will increase the utility of model results in planning. We compared the relative performance of nonspatial and hierarchical Bayesian spatial models for three vertebrate and invertebrate taxa of conservation concern (Church's sideband snails [Monadenia churchi], red tree voles [Arborimus longicaudus], and Pacific fishers [Martes pennanti pacifica]) that provide examples of a range of distributional extents and dispersal abilities. We used presence-absence data derived from regional monitoring programs to develop models with both landscape and site-level environmental covariates. We used Markov chain Monte Carlo algorithms and a conditional autoregressive or intrinsic conditional autoregressive model framework to fit spatial models. The fit of Bayesian spatial models was between 35 and 55% better than the fit of nonspatial analogue models. Bayesian spatial models outperformed analogous models developed with maximum entropy (Maxent) methods. Although the best spatial and nonspatial models included similar environmental variables, spatial models provided estimates of residual spatial effects that suggested how ecological processes might structure distribution patterns. Spatial models built from presence-absence data improved fit most for localized endemic species with ranges constrained by poorly known biogeographic factors and for widely distributed species suspected to be strongly affected by unmeasured environmental variables or population processes. By treating spatial effects as a variable of interest rather than a nuisance, hierarchical Bayesian spatial models, especially when they are based on a common broad-scale spatial lattice (here the national Forest Inventory and Analysis grid of 24 km(2) hexagons), can increase the relevance of habitat models to multispecies

  16. Modeling contaminant plumes in fractured limestone aquifers

    DEFF Research Database (Denmark)

    Mosthaf, Klaus; Brauns, Bentje; Fjordbøge, Annika Sidelmann

    Determining the fate and transport of contaminant plumes from contaminated sites in limestone aquifers is important because they are a major drinking water resource. This is challenging because they are often heavily fractured and contain chert layers and nodules, resulting in a complex transport...... model. The paper concludes with recommendations on how to identify and employ suitable models to advance the conceptual understanding and as decision support tools for risk assessment and the planning of remedial actions....... behavior. Improved conceptual models are needed for this type of site. Here conceptual models are developed by combining numerical models with field data. Several types of fracture flow and transport models are available for the modeling of contaminant transport in fractured media. These include...... the established approaches of the equivalent porous medium, discrete fracture and dual continuum models. However, these modeling concepts are not well tested for contaminant plume migration in limestone geologies. Our goal was to develop and evaluate approaches for modeling the transport of dissolved contaminant...

  17. Linguistic steganography on Twitter: hierarchical language modeling with manual interaction

    Science.gov (United States)

    Wilson, Alex; Blunsom, Phil; Ker, Andrew D.

    2014-02-01

    This work proposes a natural language stegosystem for Twitter, modifying tweets as they are written to hide 4 bits of payload per tweet, which is a greater payload than previous systems have achieved. The system, CoverTweet, includes novel components, as well as some already developed in the literature. We believe that the task of transforming covers during embedding is equivalent to unilingual machine translation (paraphrasing), and we use this equivalence to de ne a distortion measure based on statistical machine translation methods. The system incorporates this measure of distortion to rank possible tweet paraphrases, using a hierarchical language model; we use human interaction as a second distortion measure to pick the best. The hierarchical language model is designed to model the speci c language of the covers, which in this setting is the language of the Twitter user who is embedding. This is a change from previous work, where general-purpose language models have been used. We evaluate our system by testing the output against human judges, and show that humans are unable to distinguish stego tweets from cover tweets any better than random guessing.

  18. Hierarchical Swarm Model: A New Approach to Optimization

    Directory of Open Access Journals (Sweden)

    Hanning Chen

    2010-01-01

    Full Text Available This paper presents a novel optimization model called hierarchical swarm optimization (HSO, which simulates the natural hierarchical complex system from where more complex intelligence can emerge for complex problems solving. This proposed model is intended to suggest ways that the performance of HSO-based algorithms on complex optimization problems can be significantly improved. This performance improvement is obtained by constructing the HSO hierarchies, which means that an agent in a higher level swarm can be composed of swarms of other agents from lower level and different swarms of different levels evolve on different spatiotemporal scale. A novel optimization algorithm (named PS2O, based on the HSO model, is instantiated and tested to illustrate the ideas of HSO model clearly. Experiments were conducted on a set of 17 benchmark optimization problems including both continuous and discrete cases. The results demonstrate remarkable performance of the PS2O algorithm on all chosen benchmark functions when compared to several successful swarm intelligence and evolutionary algorithms.

  19. An Efficient Two-Scale Hybrid Embedded Fracture Model for Shale Gas Simulation

    KAUST Repository

    Amir, Sahar Z.

    2016-12-27

    Natural and hydraulic fractures existence and state differs on a reservoir-by-reservoir or even on a well-by-well basis leading to the necessity of exploring the flow regimes variations with respect to the diverse fracture-network shapes forged. Conventional Dual-Porosity Dual-Permeability (DPDP) schemes are not adequate to model such complex fracture-network systems. To overcome this difficulty, in this paper, an iterative Hybrid Embedded multiscale (two-scale) Fracture model (HEF) is applied on a derived fit-for-purpose shale gas model. The HEF model involves splitting the fracture computations into two scales: 1) fine-scale solves for the flux exchange parameter within each grid cell; 2) coarse-scale solves for the pressure applied to the domain grid cells using the flux exchange parameter computed at each grid cell from the fine-scale. After that, the D dimensions matrix pressure and the (D-1) lower dimensional fracture pressure are solved as a system to apply the matrix-fracture coupling. HEF model combines the DPDP overlapping continua concept, the DFN lower dimensional fractures concept, the HFN hierarchical fracture concept, and the CCFD model simplicity. As for the fit-for-purpose shale gas model, various fit-for-purpose shale gas models can be derived using any set of selected properties plugged in one of the most popularly used proposed literature models as shown in the appendix. Also, this paper shows that shale extreme low permeability cause flow behavior to be dominated by the structure and magnitude of high permeability fractures.

  20. An Efficient Two-Scale Hybrid Embedded Fracture Model for Shale Gas Simulation

    KAUST Repository

    Amir, Sahar Z.; Sun, Shuyu

    2016-01-01

    Natural and hydraulic fractures existence and state differs on a reservoir-by-reservoir or even on a well-by-well basis leading to the necessity of exploring the flow regimes variations with respect to the diverse fracture-network shapes forged. Conventional Dual-Porosity Dual-Permeability (DPDP) schemes are not adequate to model such complex fracture-network systems. To overcome this difficulty, in this paper, an iterative Hybrid Embedded multiscale (two-scale) Fracture model (HEF) is applied on a derived fit-for-purpose shale gas model. The HEF model involves splitting the fracture computations into two scales: 1) fine-scale solves for the flux exchange parameter within each grid cell; 2) coarse-scale solves for the pressure applied to the domain grid cells using the flux exchange parameter computed at each grid cell from the fine-scale. After that, the D dimensions matrix pressure and the (D-1) lower dimensional fracture pressure are solved as a system to apply the matrix-fracture coupling. HEF model combines the DPDP overlapping continua concept, the DFN lower dimensional fractures concept, the HFN hierarchical fracture concept, and the CCFD model simplicity. As for the fit-for-purpose shale gas model, various fit-for-purpose shale gas models can be derived using any set of selected properties plugged in one of the most popularly used proposed literature models as shown in the appendix. Also, this paper shows that shale extreme low permeability cause flow behavior to be dominated by the structure and magnitude of high permeability fractures.

  1. Reduced Fracture Finite Element Model Analysis of an Efficient Two-Scale Hybrid Embedded Fracture Model

    KAUST Repository

    Amir, Sahar Z.

    2017-06-09

    A Hybrid Embedded Fracture (HEF) model was developed to reduce various computational costs while maintaining physical accuracy (Amir and Sun, 2016). HEF splits the computations into fine scale and coarse scale. Fine scale solves analytically for the matrix-fracture flux exchange parameter. Coarse scale solves for the properties of the entire system. In literature, fractures were assumed to be either vertical or horizontal for simplification (Warren and Root, 1963). Matrix-fracture flux exchange parameter was given few equations built on that assumption (Kazemi, 1968; Lemonnier and Bourbiaux, 2010). However, such simplified cases do not apply directly for actual random fracture shapes, directions, orientations …etc. This paper shows that the HEF fine scale analytic solution (Amir and Sun, 2016) generates the flux exchange parameter found in literature for vertical and horizontal fracture cases. For other fracture cases, the flux exchange parameter changes according to the angle, slop, direction, … etc. This conclusion rises from the analysis of both: the Discrete Fracture Network (DFN) and the HEF schemes. The behavior of both schemes is analyzed with exactly similar fracture conditions and the results are shown and discussed. Then, a generalization is illustrated for any slightly compressible single-phase fluid within fractured porous media and its results are discussed.

  2. Reduced Fracture Finite Element Model Analysis of an Efficient Two-Scale Hybrid Embedded Fracture Model

    KAUST Repository

    Amir, Sahar Z.; Chen, Huangxin; Sun, Shuyu

    2017-01-01

    A Hybrid Embedded Fracture (HEF) model was developed to reduce various computational costs while maintaining physical accuracy (Amir and Sun, 2016). HEF splits the computations into fine scale and coarse scale. Fine scale solves analytically for the matrix-fracture flux exchange parameter. Coarse scale solves for the properties of the entire system. In literature, fractures were assumed to be either vertical or horizontal for simplification (Warren and Root, 1963). Matrix-fracture flux exchange parameter was given few equations built on that assumption (Kazemi, 1968; Lemonnier and Bourbiaux, 2010). However, such simplified cases do not apply directly for actual random fracture shapes, directions, orientations …etc. This paper shows that the HEF fine scale analytic solution (Amir and Sun, 2016) generates the flux exchange parameter found in literature for vertical and horizontal fracture cases. For other fracture cases, the flux exchange parameter changes according to the angle, slop, direction, … etc. This conclusion rises from the analysis of both: the Discrete Fracture Network (DFN) and the HEF schemes. The behavior of both schemes is analyzed with exactly similar fracture conditions and the results are shown and discussed. Then, a generalization is illustrated for any slightly compressible single-phase fluid within fractured porous media and its results are discussed.

  3. The Realized Hierarchical Archimedean Copula in Risk Modelling

    Directory of Open Access Journals (Sweden)

    Ostap Okhrin

    2017-06-01

    Full Text Available This paper introduces the concept of the realized hierarchical Archimedean copula (rHAC. The proposed approach inherits the ability of the copula to capture the dependencies among financial time series, and combines it with additional information contained in high-frequency data. The considered model does not suffer from the curse of dimensionality, and is able to accurately predict high-dimensional distributions. This flexibility is obtained by using a hierarchical structure in the copula. The time variability of the model is provided by daily forecasts of the realized correlation matrix, which is used to estimate the structure and the parameters of the rHAC. Extensive simulation studies show the validity of the estimator based on this realized correlation matrix, and its performance, in comparison to the benchmark models. The application of the estimator to one-day-ahead Value at Risk (VaR prediction using high-frequency data exhibits good forecasting properties for a multivariate portfolio.

  4. Learning Hierarchical User Interest Models from Web Pages

    Institute of Scientific and Technical Information of China (English)

    2006-01-01

    We propose an algorithm for learning hierarchical user interest models according to the Web pages users have browsed. In this algorithm, the interests of a user are represented into a tree which is called a user interest tree, the content and the structure of which can change simultaneously to adapt to the changes in a user's interests. This expression represents a user's specific and general interests as a continuum. In some sense, specific interests correspond to short-term interests, while general interests correspond to long-term interests. So this representation more really reflects the users' interests. The algorithm can automatically model a user's multiple interest domains, dynamically generate the interest models and prune a user interest tree when the number of the nodes in it exceeds given value. Finally, we show the experiment results in a Chinese Web Site.

  5. Modeling evolutionary dynamics of epigenetic mutations in hierarchically organized tumors.

    Directory of Open Access Journals (Sweden)

    Andrea Sottoriva

    2011-05-01

    Full Text Available The cancer stem cell (CSC concept is a highly debated topic in cancer research. While experimental evidence in favor of the cancer stem cell theory is apparently abundant, the results are often criticized as being difficult to interpret. An important reason for this is that most experimental data that support this model rely on transplantation studies. In this study we use a novel cellular Potts model to elucidate the dynamics of established malignancies that are driven by a small subset of CSCs. Our results demonstrate that epigenetic mutations that occur during mitosis display highly altered dynamics in CSC-driven malignancies compared to a classical, non-hierarchical model of growth. In particular, the heterogeneity observed in CSC-driven tumors is considerably higher. We speculate that this feature could be used in combination with epigenetic (methylation sequencing studies of human malignancies to prove or refute the CSC hypothesis in established tumors without the need for transplantation. Moreover our tumor growth simulations indicate that CSC-driven tumors display evolutionary features that can be considered beneficial during tumor progression. Besides an increased heterogeneity they also exhibit properties that allow the escape of clones from local fitness peaks. This leads to more aggressive phenotypes in the long run and makes the neoplasm more adaptable to stringent selective forces such as cancer treatment. Indeed when therapy is applied the clone landscape of the regrown tumor is more aggressive with respect to the primary tumor, whereas the classical model demonstrated similar patterns before and after therapy. Understanding these often counter-intuitive fundamental properties of (non-hierarchically organized malignancies is a crucial step in validating the CSC concept as well as providing insight into the therapeutical consequences of this model.

  6. Tractography segmentation using a hierarchical Dirichlet processes mixture model.

    Science.gov (United States)

    Wang, Xiaogang; Grimson, W Eric L; Westin, Carl-Fredrik

    2011-01-01

    In this paper, we propose a new nonparametric Bayesian framework to cluster white matter fiber tracts into bundles using a hierarchical Dirichlet processes mixture (HDPM) model. The number of clusters is automatically learned driven by data with a Dirichlet process (DP) prior instead of being manually specified. After the models of bundles have been learned from training data without supervision, they can be used as priors to cluster/classify fibers of new subjects for comparison across subjects. When clustering fibers of new subjects, new clusters can be created for structures not observed in the training data. Our approach does not require computing pairwise distances between fibers and can cluster a huge set of fibers across multiple subjects. We present results on several data sets, the largest of which has more than 120,000 fibers. Copyright © 2010 Elsevier Inc. All rights reserved.

  7. Hierarchical decision modeling essays in honor of Dundar F. Kocaoglu

    CERN Document Server

    2016-01-01

    This volume, developed in honor of Dr. Dundar F. Kocaoglu, aims to demonstrate the applications of the Hierarchical Decision Model (HDM) in different sectors and its capacity in decision analysis. It is comprised of essays from noted scholars, academics and researchers of engineering and technology management around the world. This book is organized into four parts: Technology Assessment, Strategic Planning, National Technology Planning and Decision Making Tools. Dr. Dundar F. Kocaoglu is one of the pioneers of multiple decision models using hierarchies, and creator of the HDM in decision analysis. HDM is a mission-oriented method for evaluation and/or selection among alternatives. A wide range of alternatives can be considered, including but not limited to, different technologies, projects, markets, jobs, products, cities to live in, houses to buy, apartments to rent, and schools to attend. Dr. Kocaoglu’s approach has been adopted for decision problems in many industrial sectors, including electronics rese...

  8. Compartmentalization analysis using discrete fracture network models

    Energy Technology Data Exchange (ETDEWEB)

    La Pointe, P.R.; Eiben, T.; Dershowitz, W. [Golder Associates, Redmond, VA (United States); Wadleigh, E. [Marathon Oil Co., Midland, TX (United States)

    1997-08-01

    This paper illustrates how Discrete Fracture Network (DFN) technology can serve as a basis for the calculation of reservoir engineering parameters for the development of fractured reservoirs. It describes the development of quantitative techniques for defining the geometry and volume of structurally controlled compartments. These techniques are based on a combination of stochastic geometry, computational geometry, and graph the theory. The parameters addressed are compartment size, matrix block size and tributary drainage volume. The concept of DFN models is explained and methodologies to compute these parameters are demonstrated.

  9. Regulator Loss Functions and Hierarchical Modeling for Safety Decision Making.

    Science.gov (United States)

    Hatfield, Laura A; Baugh, Christine M; Azzone, Vanessa; Normand, Sharon-Lise T

    2017-07-01

    Regulators must act to protect the public when evidence indicates safety problems with medical devices. This requires complex tradeoffs among risks and benefits, which conventional safety surveillance methods do not incorporate. To combine explicit regulator loss functions with statistical evidence on medical device safety signals to improve decision making. In the Hospital Cost and Utilization Project National Inpatient Sample, we select pediatric inpatient admissions and identify adverse medical device events (AMDEs). We fit hierarchical Bayesian models to the annual hospital-level AMDE rates, accounting for patient and hospital characteristics. These models produce expected AMDE rates (a safety target), against which we compare the observed rates in a test year to compute a safety signal. We specify a set of loss functions that quantify the costs and benefits of each action as a function of the safety signal. We integrate the loss functions over the posterior distribution of the safety signal to obtain the posterior (Bayes) risk; the preferred action has the smallest Bayes risk. Using simulation and an analysis of AMDE data, we compare our minimum-risk decisions to a conventional Z score approach for classifying safety signals. The 2 rules produced different actions for nearly half of hospitals (45%). In the simulation, decisions that minimize Bayes risk outperform Z score-based decisions, even when the loss functions or hierarchical models are misspecified. Our method is sensitive to the choice of loss functions; eliciting quantitative inputs to the loss functions from regulators is challenging. A decision-theoretic approach to acting on safety signals is potentially promising but requires careful specification of loss functions in consultation with subject matter experts.

  10. Discrete fracture modelling for the Stripa tracer validation experiment predictions

    International Nuclear Information System (INIS)

    Dershowitz, W.; Wallmann, P.

    1992-02-01

    Groundwater flow and transport through three-dimensional networks of discrete fractures was modeled to predict the recovery of tracer from tracer injection experiments conducted during phase 3 of the Stripa site characterization and validation protect. Predictions were made on the basis of an updated version of the site scale discrete fracture conceptual model used for flow predictions and preliminary transport modelling. In this model, individual fractures were treated as stochastic features described by probability distributions of geometric and hydrologic properties. Fractures were divided into three populations: Fractures in fracture zones near the drift, non-fracture zone fractures within 31 m of the drift, and fractures in fracture zones over 31 meters from the drift axis. Fractures outside fracture zones are not modelled beyond 31 meters from the drift axis. Transport predictions were produced using the FracMan discrete fracture modelling package for each of five tracer experiments. Output was produced in the seven formats specified by the Stripa task force on fracture flow modelling. (au)

  11. Characterizing the course of back pain after osteoporotic vertebral fracture: a hierarchical cluster analysis of a prospective cohort study.

    Science.gov (United States)

    Toyoda, Hiromitsu; Takahashi, Shinji; Hoshino, Masatoshi; Takayama, Kazushi; Iseki, Kazumichi; Sasaoka, Ryuichi; Tsujio, Tadao; Yasuda, Hiroyuki; Sasaki, Takeharu; Kanematsu, Fumiaki; Kono, Hiroshi; Nakamura, Hiroaki

    2017-09-23

    This study demonstrated four distinct patterns in the course of back pain after osteoporotic vertebral fracture (OVF). Greater angular instability in the first 6 months after the baseline was one factor affecting back pain after OVF. Understanding the natural course of symptomatic acute OVF is important in deciding the optimal treatment strategy. We used latent class analysis to classify the course of back pain after OVF and identify the risk factors associated with persistent pain. This multicenter cohort study included 218 consecutive patients with ≤ 2-week-old OVFs who were enrolled at 11 institutions. Dynamic x-rays and back pain assessment with a visual analog scale (VAS) were obtained at enrollment and at 1-, 3-, and 6-month follow-ups. The VAS scores were used to characterize patient groups, using hierarchical cluster analysis. VAS for 128 patients was used for hierarchical cluster analysis. Analysis yielded four clusters representing different patterns of back pain progression. Cluster 1 patients (50.8%) had stable, mild pain. Cluster 2 patients (21.1%) started with moderate pain and progressed quickly to very low pain. Patients in cluster 3 (10.9%) had moderate pain that initially improved but worsened after 3 months. Cluster 4 patients (17.2%) had persistent severe pain. Patients in cluster 4 showed significant high baseline pain intensity, higher degree of angular instability, and higher number of previous OVFs, and tended to lack regular exercise. In contrast, patients in cluster 2 had significantly lower baseline VAS and less angular instability. We identified four distinct groups of OVF patients with different patterns of back pain progression. Understanding the course of back pain after OVF may help in its management and contribute to future treatment trials.

  12. Modeling of flow in faulted and fractured media

    Energy Technology Data Exchange (ETDEWEB)

    Oeian, Erlend

    2004-03-01

    . Thus, the main purpose of this chapter is to go into more details on the various parameters and derivations compared to the papers. Details of the ATHENA simulator is presented in Chapt. 3, including both earlier and recent additions. The main focus of this chapter is on code development issues like platform portability, 'safe' parallel programming and general improvements. Due to the code specific details, the content of this paper is for the most part not covered in the Part II papers. Chapt. 4 includes the domain decomposition framework and details on the parallel implementation. Based on the fault modeling aspects introduced in Chapt. 1, a brief review of existing numerical fracture flow techniques are given in Chapt. 5. Also, a hierarchical approach for including fractures at different scales within the ATHENA simulator is given here. This includes both discretization issues and methods for up scaling. After summary and conclusions in Chapt. 6, Part I ends with Chapt. 7 including suggestions on further work within the ATHENA simulator framework in particular and on numerical techniques for fractured porous media flow in general.

  13. Modeling of flow in faulted and fractured media

    Energy Technology Data Exchange (ETDEWEB)

    Oeian, Erlend

    2004-03-01

    . Thus, the main purpose of this chapter is to go into more details on the various parameters and derivations compared to the papers. Details of the ATHENA simulator is presented in Chapt. 3, including both earlier and recent additions. The main focus of this chapter is on code development issues like platform portability, 'safe' parallel programming and general improvements. Due to the code specific details, the content of this paper is for the most part not covered in the Part II papers. Chapt. 4 includes the domain decomposition framework and details on the parallel implementation. Based on the fault modeling aspects introduced in Chapt. 1, a brief review of existing numerical fracture flow techniques are given in Chapt. 5. Also, a hierarchical approach for including fractures at different scales within the ATHENA simulator is given here. This includes both discretization issues and methods for up scaling. After summary and conclusions in Chapt. 6, Part I ends with Chapt. 7 including suggestions on further work within the ATHENA simulator framework in particular and on numerical techniques for fractured porous media flow in general.

  14. GSMNet: A Hierarchical Graph Model for Moving Objects in Networks

    Directory of Open Access Journals (Sweden)

    Hengcai Zhang

    2017-03-01

    Full Text Available Existing data models for moving objects in networks are often limited by flexibly controlling the granularity of representing networks and the cost of location updates and do not encompass semantic information, such as traffic states, traffic restrictions and social relationships. In this paper, we aim to fill the gap of traditional network-constrained models and propose a hierarchical graph model called the Geo-Social-Moving model for moving objects in Networks (GSMNet that adopts four graph structures, RouteGraph, SegmentGraph, ObjectGraph and MoveGraph, to represent the underlying networks, trajectories and semantic information in an integrated manner. The bulk of user-defined data types and corresponding operators is proposed to handle moving objects and answer a new class of queries supporting three kinds of conditions: spatial, temporal and semantic information. Then, we develop a prototype system with the native graph database system Neo4Jto implement the proposed GSMNet model. In the experiment, we conduct the performance evaluation using simulated trajectories generated from the BerlinMOD (Berlin Moving Objects Database benchmark and compare with the mature MOD system Secondo. The results of 17 benchmark queries demonstrate that our proposed GSMNet model has strong potential to reduce time-consuming table join operations an d shows remarkable advantages with regard to representing semantic information and controlling the cost of location updates.

  15. Evaluation of scale effects on hydraulic characteristics of fractured rock using fracture network model

    International Nuclear Information System (INIS)

    Ijiri, Yuji; Sawada, Atsushi; Uchida, Masahiro; Ishiguro, Katsuhiko; Umeki, Hiroyuki; Sakamoto, Kazuhiko; Ohnishi, Yuzo

    2001-01-01

    It is important to take into account scale effects on fracture geometry if the modeling scale is much larger than the in-situ observation scale. The scale effect on fracture trace length, which is the most scale dependent parameter, is investigated using fracture maps obtained at various scales in tunnel and dam sites. We found that the distribution of fracture trace length follows negative power law distribution in regardless of locations and rock types. The hydraulic characteristics of fractured rock is also investigated by numerical analysis of discrete fracture network (DFN) model where power law distribution of fracture radius is adopted. We found that as the exponent of power law distribution become larger, the hydraulic conductivity of DFN model increases and the travel time in DFN model decreases. (author)

  16. An XFEM Model for Hydraulic Fracturing in Partially Saturated Rocks

    Directory of Open Access Journals (Sweden)

    Salimzadeh Saeed

    2016-01-01

    Full Text Available Hydraulic fracturing is a complex multi-physics phenomenon. Numerous analytical and numerical models of hydraulic fracturing processes have been proposed. Analytical solutions commonly are able to model the growth of a single hydraulic fracture into an initially intact, homogeneous rock mass. Numerical models are able to analyse complex problems such as multiple hydraulic fractures and fracturing in heterogeneous media. However, majority of available models are restricted to single-phase flow through fracture and permeable porous rock. This is not compatible with actual field conditions where the injected fluid does not have similar properties as the host fluid. In this study we present a fully coupled hydro-poroelastic model which incorporates two fluids i.e. fracturing fluid and host fluid. Flow through fracture is defined based on lubrication assumption, while flow through matrix is defined as Darcy flow. The fracture discontinuity in the mechanical model is captured using eXtended Finite Element Method (XFEM while the fracture propagation criterion is defined through cohesive fracture model. The discontinuous matrix fluid velocity across fracture is modelled using leak-off loading which couples fracture flow and matrix flow. The proposed model has been discretised using standard Galerkin method, implemented in Matlab and verified against several published solutions. Multiple hydraulic fracturing simulations are performed to show the model robustness and to illustrate how problem parameters such as injection rate and rock permeability affect the hydraulic fracturing variables i.e. injection pressure, fracture aperture and fracture length. The results show the impact of partial saturation on leak-off and the fact that single-phase models may underestimate the leak-off.

  17. Application of hierarchical genetic models to Raven and WAIS subtests: a Dutch twin study

    NARCIS (Netherlands)

    Rijsdijk, F.V.; Vernon, P.A.; Boomsma, D.I.

    2002-01-01

    Hierarchical models of intelligence are highly informative and widely accepted. Application of these models to twin data, however, is sparse. This paper addresses the question of how a genetic hierarchical model fits the Wechsler Adult Intelligence Scale (WAIS) subtests and the Raven Standard

  18. MODELING THE RED SEQUENCE: HIERARCHICAL GROWTH YET SLOW LUMINOSITY EVOLUTION

    International Nuclear Information System (INIS)

    Skelton, Rosalind E.; Bell, Eric F.; Somerville, Rachel S.

    2012-01-01

    We explore the effects of mergers on the evolution of massive early-type galaxies by modeling the evolution of their stellar populations in a hierarchical context. We investigate how a realistic red sequence population set up by z ∼ 1 evolves under different assumptions for the merger and star formation histories, comparing changes in color, luminosity, and mass. The purely passive fading of existing red sequence galaxies, with no further mergers or star formation, results in dramatic changes at the bright end of the luminosity function and color-magnitude relation. Without mergers there is too much evolution in luminosity at a fixed space density compared to observations. The change in color and magnitude at a fixed mass resembles that of a passively evolving population that formed relatively recently, at z ∼ 2. Mergers among the red sequence population ('dry mergers') occurring after z = 1 build up mass, counteracting the fading of the existing stellar populations to give smaller changes in both color and luminosity for massive galaxies. By allowing some galaxies to migrate from the blue cloud onto the red sequence after z = 1 through gas-rich mergers, younger stellar populations are added to the red sequence. This manifestation of the progenitor bias increases the scatter in age and results in even smaller changes in color and luminosity between z = 1 and z = 0 at a fixed mass. The resultant evolution appears much slower, resembling the passive evolution of a population that formed at high redshift (z ∼ 3-5), and is in closer agreement with observations. We conclude that measurements of the luminosity and color evolution alone are not sufficient to distinguish between the purely passive evolution of an old population and cosmologically motivated hierarchical growth, although these scenarios have very different implications for the mass growth of early-type galaxies over the last half of cosmic history.

  19. Hierarchical modeling and its numerical implementation for layered thin elastic structures

    Energy Technology Data Exchange (ETDEWEB)

    Cho, Jin-Rae [Hongik University, Sejong (Korea, Republic of)

    2017-05-15

    Thin elastic structures such as beam- and plate-like structures and laminates are characterized by the small thickness, which lead to classical plate and laminate theories in which the displacement fields through the thickness are assumed linear or higher-order polynomials. These classical theories are either insufficient to represent the complex stress variation through the thickness or may encounter the accuracy-computational cost dilemma. In order to overcome the inherent problem of classical theories, the concept of hierarchical modeling has been emerged. In the hierarchical modeling, the hierarchical models with different model levels are selected and combined within a structure domain, in order to make the modeling error be distributed as uniformly as possible throughout the problem domain. The purpose of current study is to explore the potential of hierarchical modeling for the effective numerical analysis of layered structures such as laminated composite. For this goal, the hierarchical models are constructed and the hierarchical modeling is implemented by selectively adjusting the level of hierarchical models. As well, the major characteristics of hierarchical models are investigated through the numerical experiments.

  20. a Fractal Network Model for Fractured Porous Media

    Science.gov (United States)

    Xu, Peng; Li, Cuihong; Qiu, Shuxia; Sasmito, Agus Pulung

    2016-04-01

    The transport properties and mechanisms of fractured porous media are very important for oil and gas reservoir engineering, hydraulics, environmental science, chemical engineering, etc. In this paper, a fractal dual-porosity model is developed to estimate the equivalent hydraulic properties of fractured porous media, where a fractal tree-like network model is used to characterize the fracture system according to its fractal scaling laws and topological structures. The analytical expressions for the effective permeability of fracture system and fractured porous media, tortuosity, fracture density and fraction are derived. The proposed fractal model has been validated by comparisons with available experimental data and numerical simulation. It has been shown that fractal dimensions for fracture length and aperture have significant effect on the equivalent hydraulic properties of fractured porous media. The effective permeability of fracture system can be increased with the increase of fractal dimensions for fracture length and aperture, while it can be remarkably lowered by introducing tortuosity at large branching angle. Also, a scaling law between the fracture density and fractal dimension for fracture length has been found, where the scaling exponent depends on the fracture number. The present fractal dual-porosity model may shed light on the transport physics of fractured porous media and provide theoretical basis for oil and gas exploitation, underground water, nuclear waste disposal and geothermal energy extraction as well as chemical engineering, etc.

  1. Bayesian Hierarchical Random Effects Models in Forensic Science

    Directory of Open Access Journals (Sweden)

    Colin G. G. Aitken

    2018-04-01

    Full Text Available Statistical modeling of the evaluation of evidence with the use of the likelihood ratio has a long history. It dates from the Dreyfus case at the end of the nineteenth century through the work at Bletchley Park in the Second World War to the present day. The development received a significant boost in 1977 with a seminal work by Dennis Lindley which introduced a Bayesian hierarchical random effects model for the evaluation of evidence with an example of refractive index measurements on fragments of glass. Many models have been developed since then. The methods have now been sufficiently well-developed and have become so widespread that it is timely to try and provide a software package to assist in their implementation. With that in mind, a project (SAILR: Software for the Analysis and Implementation of Likelihood Ratios was funded by the European Network of Forensic Science Institutes through their Monopoly programme to develop a software package for use by forensic scientists world-wide that would assist in the statistical analysis and implementation of the approach based on likelihood ratios. It is the purpose of this document to provide a short review of a small part of this history. The review also provides a background, or landscape, for the development of some of the models within the SAILR package and references to SAILR as made as appropriate.

  2. Bayesian Hierarchical Random Effects Models in Forensic Science.

    Science.gov (United States)

    Aitken, Colin G G

    2018-01-01

    Statistical modeling of the evaluation of evidence with the use of the likelihood ratio has a long history. It dates from the Dreyfus case at the end of the nineteenth century through the work at Bletchley Park in the Second World War to the present day. The development received a significant boost in 1977 with a seminal work by Dennis Lindley which introduced a Bayesian hierarchical random effects model for the evaluation of evidence with an example of refractive index measurements on fragments of glass. Many models have been developed since then. The methods have now been sufficiently well-developed and have become so widespread that it is timely to try and provide a software package to assist in their implementation. With that in mind, a project (SAILR: Software for the Analysis and Implementation of Likelihood Ratios) was funded by the European Network of Forensic Science Institutes through their Monopoly programme to develop a software package for use by forensic scientists world-wide that would assist in the statistical analysis and implementation of the approach based on likelihood ratios. It is the purpose of this document to provide a short review of a small part of this history. The review also provides a background, or landscape, for the development of some of the models within the SAILR package and references to SAILR as made as appropriate.

  3. Renormalization group analysis of a simple hierarchical fermion model

    International Nuclear Information System (INIS)

    Dorlas, T.C.

    1991-01-01

    A simple hierarchical fermion model is constructed which gives rise to an exact renormalization transformation in a 2-dimensional parameter space. The behaviour of this transformation is studied. It has two hyperbolic fixed points for which the existence of a global critical line is proven. The asymptotic behaviour of the transformation is used to prove the existence of the thermodynamic limit in a certain domain in parameter space. Also the existence of a continuum limit for these theories is investigated using information about the asymptotic renormalization behaviour. It turns out that the 'trivial' fixed point gives rise to a two-parameter family of continuum limits corresponding to that part of parameter space where the renormalization trajectories originate at this fixed point. Although the model is not very realistic it serves as a simple example of the appliclation of the renormalization group to proving the existence of the thermodynamic limit and the continuum limit of lattice models. Moreover, it illustrates possible complications that can arise in global renormalization group behaviour, and that might also be present in other models where no global analysis of the renormalization transformation has yet been achieved. (orig.)

  4. Testing adaptive toolbox models: a Bayesian hierarchical approach.

    Science.gov (United States)

    Scheibehenne, Benjamin; Rieskamp, Jörg; Wagenmakers, Eric-Jan

    2013-01-01

    Many theories of human cognition postulate that people are equipped with a repertoire of strategies to solve the tasks they face. This theoretical framework of a cognitive toolbox provides a plausible account of intra- and interindividual differences in human behavior. Unfortunately, it is often unclear how to rigorously test the toolbox framework. How can a toolbox model be quantitatively specified? How can the number of toolbox strategies be limited to prevent uncontrolled strategy sprawl? How can a toolbox model be formally tested against alternative theories? The authors show how these challenges can be met by using Bayesian inference techniques. By means of parameter recovery simulations and the analysis of empirical data across a variety of domains (i.e., judgment and decision making, children's cognitive development, function learning, and perceptual categorization), the authors illustrate how Bayesian inference techniques allow toolbox models to be quantitatively specified, strategy sprawl to be contained, and toolbox models to be rigorously tested against competing theories. The authors demonstrate that their approach applies at the individual level but can also be generalized to the group level with hierarchical Bayesian procedures. The suggested Bayesian inference techniques represent a theoretical and methodological advancement for toolbox theories of cognition and behavior.

  5. Application of Hierarchical Linear Models/Linear Mixed-Effects Models in School Effectiveness Research

    Science.gov (United States)

    Ker, H. W.

    2014-01-01

    Multilevel data are very common in educational research. Hierarchical linear models/linear mixed-effects models (HLMs/LMEs) are often utilized to analyze multilevel data nowadays. This paper discusses the problems of utilizing ordinary regressions for modeling multilevel educational data, compare the data analytic results from three regression…

  6. Hierarchical Bayesian modelling of mobility metrics for hazard model input calibration

    Science.gov (United States)

    Calder, Eliza; Ogburn, Sarah; Spiller, Elaine; Rutarindwa, Regis; Berger, Jim

    2015-04-01

    In this work we present a method to constrain flow mobility input parameters for pyroclastic flow models using hierarchical Bayes modeling of standard mobility metrics such as H/L and flow volume etc. The advantage of hierarchical modeling is that it can leverage the information in global dataset for a particular mobility metric in order to reduce the uncertainty in modeling of an individual volcano, especially important where individual volcanoes have only sparse datasets. We use compiled pyroclastic flow runout data from Colima, Merapi, Soufriere Hills, Unzen and Semeru volcanoes, presented in an open-source database FlowDat (https://vhub.org/groups/massflowdatabase). While the exact relationship between flow volume and friction varies somewhat between volcanoes, dome collapse flows originating from the same volcano exhibit similar mobility relationships. Instead of fitting separate regression models for each volcano dataset, we use a variation of the hierarchical linear model (Kass and Steffey, 1989). The model presents a hierarchical structure with two levels; all dome collapse flows and dome collapse flows at specific volcanoes. The hierarchical model allows us to assume that the flows at specific volcanoes share a common distribution of regression slopes, then solves for that distribution. We present comparisons of the 95% confidence intervals on the individual regression lines for the data set from each volcano as well as those obtained from the hierarchical model. The results clearly demonstrate the advantage of considering global datasets using this technique. The technique developed is demonstrated here for mobility metrics, but can be applied to many other global datasets of volcanic parameters. In particular, such methods can provide a means to better contain parameters for volcanoes for which we only have sparse data, a ubiquitous problem in volcanology.

  7. A hierarchical network modeling method for railway tunnels safety assessment

    Science.gov (United States)

    Zhou, Jin; Xu, Weixiang; Guo, Xin; Liu, Xumin

    2017-02-01

    Using network theory to model risk-related knowledge on accidents is regarded as potential very helpful in risk management. A large amount of defects detection data for railway tunnels is collected in autumn every year in China. It is extremely important to discover the regularities knowledge in database. In this paper, based on network theories and by using data mining techniques, a new method is proposed for mining risk-related regularities to support risk management in railway tunnel projects. A hierarchical network (HN) model which takes into account the tunnel structures, tunnel defects, potential failures and accidents is established. An improved Apriori algorithm is designed to rapidly and effectively mine correlations between tunnel structures and tunnel defects. Then an algorithm is presented in order to mine the risk-related regularities table (RRT) from the frequent patterns. At last, a safety assessment method is proposed by consideration of actual defects and possible risks of defects gained from the RRT. This method cannot only generate the quantitative risk results but also reveal the key defects and critical risks of defects. This paper is further development on accident causation network modeling methods which can provide guidance for specific maintenance measure.

  8. Production optimisation in the petrochemical industry by hierarchical multivariate modelling

    Energy Technology Data Exchange (ETDEWEB)

    Andersson, Magnus; Furusjoe, Erik; Jansson, Aasa

    2004-06-01

    This project demonstrates the advantages of applying hierarchical multivariate modelling in the petrochemical industry in order to increase knowledge of the total process. The models indicate possible ways to optimise the process regarding the use of energy and raw material, which is directly linked to the environmental impact of the process. The refinery of Nynaes Refining AB (Goeteborg, Sweden) has acted as a demonstration site in this project. The models developed for the demonstration site resulted in: Detection of an unknown process disturbance and suggestions of possible causes; Indications on how to increase the yield in combination with energy savings; The possibility to predict product quality from on-line process measurements, making the results available at a higher frequency than customary laboratory analysis; Quantification of the gradually lowered efficiency of heat transfer in the furnace and increased fuel consumption as an effect of soot build-up on the furnace coils; Increased knowledge of the relation between production rate and the efficiency of the heat exchangers. This report is one of two reports from the project. It contains a technical discussion of the result with some degree of detail. A shorter and more easily accessible report is also available, see IVL report B1586-A.

  9. Fracture modelling of a high performance armour steel

    Science.gov (United States)

    Skoglund, P.; Nilsson, M.; Tjernberg, A.

    2006-08-01

    The fracture characteristics of the high performance armour steel Armox 500T is investigated. Tensile mechanical experiments using samples with different notch geometries are used to investigate the effect of multi-axial stress states on the strain to fracture. The experiments are numerically simulated and from the simulation the stress at the point of fracture initiation is determined as a function of strain and these data are then used to extract parameters for fracture models. A fracture model based on quasi-static experiments is suggested and the model is tested against independent experiments done at both static and dynamic loading. The result show that the fracture model give reasonable good agreement between simulations and experiments at both static and dynamic loading condition. This indicates that multi-axial loading is more important to the strain to fracture than the deformation rate in the investigated loading range. However on-going work will further characterise the fracture behaviour of Armox 500T.

  10. Cohesive fracture model for functionally graded fiber reinforced concrete

    International Nuclear Information System (INIS)

    Park, Kyoungsoo; Paulino, Glaucio H.; Roesler, Jeffery

    2010-01-01

    A simple, effective, and practical constitutive model for cohesive fracture of fiber reinforced concrete is proposed by differentiating the aggregate bridging zone and the fiber bridging zone. The aggregate bridging zone is related to the total fracture energy of plain concrete, while the fiber bridging zone is associated with the difference between the total fracture energy of fiber reinforced concrete and the total fracture energy of plain concrete. The cohesive fracture model is defined by experimental fracture parameters, which are obtained through three-point bending and split tensile tests. As expected, the model describes fracture behavior of plain concrete beams. In addition, it predicts the fracture behavior of either fiber reinforced concrete beams or a combination of plain and fiber reinforced concrete functionally layered in a single beam specimen. The validated model is also applied to investigate continuously, functionally graded fiber reinforced concrete composites.

  11. Ongoing Model Development Analyzing Glass Fracture

    DEFF Research Database (Denmark)

    Molnar, G.; Bojtar, I.; Nielsen, Jens Henrik

    2013-01-01

    Present subject deals with an ongoing experimental and numerical analysis of inplane loaded glass plates. The main goal of the investigation is to develop a hybrid – discrete and finite element – model which could follow the fracture process in annealed and in tempered glass. Measurements of the ...... an overview of the structure of the research and a summary of current status archived so far.......Present subject deals with an ongoing experimental and numerical analysis of inplane loaded glass plates. The main goal of the investigation is to develop a hybrid – discrete and finite element – model which could follow the fracture process in annealed and in tempered glass. Measurements...... of the residual stress state before failure and high-speed camera recordings of the failure are being performed in order to verify the numerical model. The primary goal of this research is to follow the overall fracture of a structural element – e.g. beam – loaded inplane. Present paper would like to give...

  12. Colloid transport in model fracture filling materials

    Science.gov (United States)

    Wold, S.; Garcia-Garcia, S.; Jonsson, M.

    2010-12-01

    Colloid transport in model fracture filling materials Susanna Wold*, Sandra García-García and Mats Jonsson KTH Chemical Science and Engineering Royal Institute of Technology, SE-100 44 Stockholm, Sweden *Corresponding author: E-mail: wold@kth.se Phone: +46 8 790 6295 In colloid transport in water-bearing fractures, the retardation depends on interactions with the fracture surface by sorption or filtration. These mechanisms are difficult to separate. A rougher surface will give a larger area available for sorption, and also when a particle is physically hindered, it approaches the surface and enables further sorption. Sorption can be explained by electrostatics were the strongest sorption on minerals always is observed at pH below pHpzc (Filby et al., 2008). The adhesion of colloids to mineral surfaces is related to the surface roughness according to a recent study (Darbha et al., 2010). There is a large variation in the characteristics of water-bearing fractures in bedrock in terms of aperture distribution, flow velocity, surface roughness, mineral distributions, presence of fracture filling material, and biological and organic material, which is hard to implement in modeling. The aim of this work was to study the transport of negatively charged colloids in model fracture filling material in relation to flow, porosity, mineral type, colloid size, and surface charge distribution. In addition, the impact on transport of colloids of mixing model fracture filling materials with different retention and immobilization capacities, determined by batch sorption experiments, was investigated. The transport of Na-montmorillonite colloids and well-defined negatively charged latex microspheres of 50, 100, and 200 nm diameter were studied in either columns containing quartz or quartz mixed with biotite. The ionic strength in the solution was exclusively 0.001 and pH 6 or 8.5. The flow rates used were 0.002, 0.03, and 0.6 mL min-1. Sorption of the colloids on the model fracture

  13. AN ACTIVE FRACTURE MODEL FOR UNSATURATED FLOW AND TRANSPORT

    International Nuclear Information System (INIS)

    HUI-HAI LIU, GUDMUNDUR S. BODVARSSON AND CHRISTINE DOUGHTY

    1999-01-01

    Fracture/matrix (F/M) interaction is a key factor affecting flow and transport in unsaturated fractured rocks. In classic continuum approaches (Warren and Root, 1963), it is assumed that flow occurs through all the connected fractures and is uniformly distributed over the entire fracture area, which generally gives a relatively large F/M interaction. However, fractures seem to have limited interaction with the surrounding matrix at Yucca Mountain, Nevada, as suggested by geochemical nonequilibrium between the perched water (resulting mainly from fracture flow) and pore water in the rock matrix. Because of the importance of the F/M interaction and related issues, there is a critical need to develop new approaches to accurately consider the interaction reduction inferred from field data at the Yucca Mountain site. Motivated by this consideration, they have developed an active fracture model based on the hypothesis that not all connected fractures actively conduct water in unsaturated fractured rocks

  14. A joint model for multivariate hierarchical semicontinuous data with replications.

    Science.gov (United States)

    Kassahun-Yimer, Wondwosen; Albert, Paul S; Lipsky, Leah M; Nansel, Tonja R; Liu, Aiyi

    2017-01-01

    Longitudinal data are often collected in biomedical applications in such a way that measurements on more than one response are taken from a given subject repeatedly overtime. For some problems, these multiple profiles need to be modeled jointly to get insight on the joint evolution and/or association of these responses over time. In practice, such longitudinal outcomes may have many zeros that need to be accounted for in the analysis. For example, in dietary intake studies, as we focus on in this paper, some food components are eaten daily by almost all subjects, while others are consumed episodically, where individuals have time periods where they do not eat these components followed by periods where they do. These episodically consumed foods need to be adequately modeled to account for the many zeros that are encountered. In this paper, we propose a joint model to analyze multivariate hierarchical semicontinuous data characterized by many zeros and more than one replicate observations at each measurement occasion. This approach allows for different probability mechanisms for describing the zero behavior as compared with the mean intake given that the individual consumes the food. To deal with the potentially large number of multivariate profiles, we use a pairwise model fitting approach that was developed in the context of multivariate Gaussian random effects models with large number of multivariate components. The novelty of the proposed approach is that it incorporates: (1) multivariate, possibly correlated, response variables; (2) within subject correlation resulting from repeated measurements taken from each subject; (3) many zero observations; (4) overdispersion; and (5) replicate measurements at each visit time.

  15. XFEM modeling of hydraulic fracture in porous rocks with natural fractures

    Science.gov (United States)

    Wang, Tao; Liu, ZhanLi; Zeng, QingLei; Gao, Yue; Zhuang, Zhuo

    2017-08-01

    Hydraulic fracture (HF) in porous rocks is a complex multi-physics coupling process which involves fluid flow, diffusion and solid deformation. In this paper, the extended finite element method (XFEM) coupling with Biot theory is developed to study the HF in permeable rocks with natural fractures (NFs). In the recent XFEM based computational HF models, the fluid flow in fractures and interstitials of the porous media are mostly solved separately, which brings difficulties in dealing with complex fracture morphology. In our new model the fluid flow is solved in a unified framework by considering the fractures as a kind of special porous media and introducing Poiseuille-type flow inside them instead of Darcy-type flow. The most advantage is that it is very convenient to deal with fluid flow inside the complex fracture network, which is important in shale gas extraction. The weak formulation for the new coupled model is derived based on virtual work principle, which includes the XFEM formulation for multiple fractures and fractures intersection in porous media and finite element formulation for the unified fluid flow. Then the plane strain Kristianovic-Geertsma-de Klerk (KGD) model and the fluid flow inside the fracture network are simulated to validate the accuracy and applicability of this method. The numerical results show that large injection rate, low rock permeability and isotropic in-situ stresses tend to lead to a more uniform and productive fracture network.

  16. Adaptive hierarchical grid model of water-borne pollutant dispersion

    Science.gov (United States)

    Borthwick, A. G. L.; Marchant, R. D.; Copeland, G. J. M.

    Water pollution by industrial and agricultural waste is an increasingly major public health issue. It is therefore important for water engineers and managers to be able to predict accurately the local behaviour of water-borne pollutants. This paper describes the novel and efficient coupling of dynamically adaptive hierarchical grids with standard solvers of the advection-diffusion equation. Adaptive quadtree grids are able to focus on regions of interest such as pollutant fronts, while retaining economy in the total number of grid elements through selective grid refinement. Advection is treated using Lagrangian particle tracking. Diffusion is solved separately using two grid-based methods; one is by explicit finite differences, the other a diffusion-velocity approach. Results are given in two dimensions for pure diffusion of an initially Gaussian plume, advection-diffusion of the Gaussian plume in the rotating flow field of a forced vortex, and the transport of species in a rectangular channel with side wall boundary layers. Close agreement is achieved with analytical solutions of the advection-diffusion equation and simulations from a Lagrangian random walk model. An application to Sepetiba Bay, Brazil is included to demonstrate the method with complex flows and topography.

  17. Hierarchical statistical modeling of xylem vulnerability to cavitation.

    Science.gov (United States)

    Ogle, Kiona; Barber, Jarrett J; Willson, Cynthia; Thompson, Brenda

    2009-01-01

    Cavitation of xylem elements diminishes the water transport capacity of plants, and quantifying xylem vulnerability to cavitation is important to understanding plant function. Current approaches to analyzing hydraulic conductivity (K) data to infer vulnerability to cavitation suffer from problems such as the use of potentially unrealistic vulnerability curves, difficulty interpreting parameters in these curves, a statistical framework that ignores sampling design, and an overly simplistic view of uncertainty. This study illustrates how two common curves (exponential-sigmoid and Weibull) can be reparameterized in terms of meaningful parameters: maximum conductivity (k(sat)), water potential (-P) at which percentage loss of conductivity (PLC) =X% (P(X)), and the slope of the PLC curve at P(X) (S(X)), a 'sensitivity' index. We provide a hierarchical Bayesian method for fitting the reparameterized curves to K(H) data. We illustrate the method using data for roots and stems of two populations of Juniperus scopulorum and test for differences in k(sat), P(X), and S(X) between different groups. Two important results emerge from this study. First, the Weibull model is preferred because it produces biologically realistic estimates of PLC near P = 0 MPa. Second, stochastic embolisms contribute an important source of uncertainty that should be included in such analyses.

  18. Scale of association: hierarchical linear models and the measurement of ecological systems

    Science.gov (United States)

    Sean M. McMahon; Jeffrey M. Diez

    2007-01-01

    A fundamental challenge to understanding patterns in ecological systems lies in employing methods that can analyse, test and draw inference from measured associations between variables across scales. Hierarchical linear models (HLM) use advanced estimation algorithms to measure regression relationships and variance-covariance parameters in hierarchically structured...

  19. A novel Bayesian hierarchical model for road safety hotspot prediction.

    Science.gov (United States)

    Fawcett, Lee; Thorpe, Neil; Matthews, Joseph; Kremer, Karsten

    2017-02-01

    In this paper, we propose a Bayesian hierarchical model for predicting accident counts in future years at sites within a pool of potential road safety hotspots. The aim is to inform road safety practitioners of the location of likely future hotspots to enable a proactive, rather than reactive, approach to road safety scheme implementation. A feature of our model is the ability to rank sites according to their potential to exceed, in some future time period, a threshold accident count which may be used as a criterion for scheme implementation. Our model specification enables the classical empirical Bayes formulation - commonly used in before-and-after studies, wherein accident counts from a single before period are used to estimate counterfactual counts in the after period - to be extended to incorporate counts from multiple time periods. This allows site-specific variations in historical accident counts (e.g. locally-observed trends) to offset estimates of safety generated by a global accident prediction model (APM), which itself is used to help account for the effects of global trend and regression-to-mean (RTM). The Bayesian posterior predictive distribution is exploited to formulate predictions and to properly quantify our uncertainty in these predictions. The main contributions of our model include (i) the ability to allow accident counts from multiple time-points to inform predictions, with counts in more recent years lending more weight to predictions than counts from time-points further in the past; (ii) where appropriate, the ability to offset global estimates of trend by variations in accident counts observed locally, at a site-specific level; and (iii) the ability to account for unknown/unobserved site-specific factors which may affect accident counts. We illustrate our model with an application to accident counts at 734 potential hotspots in the German city of Halle; we also propose some simple diagnostics to validate the predictive capability of our

  20. Metamodeling Techniques to Aid in the Aggregation Process of Large Hierarchical Simulation Models

    National Research Council Canada - National Science Library

    Rodriguez, June F

    2008-01-01

    .... More specifically, investigating how to accurately aggregate hierarchical lower-level (higher resolution) models into the next higher-level in order to reduce the complexity of the overall simulation model...

  1. A Hierarchical Modeling for Reactive Power Optimization With Joint Transmission and Distribution Networks by Curve Fitting

    DEFF Research Database (Denmark)

    Ding, Tao; Li, Cheng; Huang, Can

    2018-01-01

    –slave structure and improves traditional centralized modeling methods by alleviating the big data problem in a control center. Specifically, the transmission-distribution-network coordination issue of the hierarchical modeling method is investigated. First, a curve-fitting approach is developed to provide a cost......In order to solve the reactive power optimization with joint transmission and distribution networks, a hierarchical modeling method is proposed in this paper. It allows the reactive power optimization of transmission and distribution networks to be performed separately, leading to a master...... optimality. Numerical results on two test systems verify the effectiveness of the proposed hierarchical modeling and curve-fitting methods....

  2. An Embedded 3D Fracture Modeling Approach for Simulating Fracture-Dominated Fluid Flow and Heat Transfer in Geothermal Reservoirs

    Energy Technology Data Exchange (ETDEWEB)

    Johnston, Henry [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Wang, Cong [Colorado School of Mines; Winterfeld, Philip [Colorado School of Mines; Wu, Yu-Shu [Colorado School of Mines

    2018-02-14

    An efficient modeling approach is described for incorporating arbitrary 3D, discrete fractures, such as hydraulic fractures or faults, into modeling fracture-dominated fluid flow and heat transfer in fractured geothermal reservoirs. This technique allows 3D discrete fractures to be discretized independently from surrounding rock volume and inserted explicitly into a primary fracture/matrix grid, generated without including 3D discrete fractures in prior. An effective computational algorithm is developed to discretize these 3D discrete fractures and construct local connections between 3D fractures and fracture/matrix grid blocks of representing the surrounding rock volume. The constructed gridding information on 3D fractures is then added to the primary grid. This embedded fracture modeling approach can be directly implemented into a developed geothermal reservoir simulator via the integral finite difference (IFD) method or with TOUGH2 technology This embedded fracture modeling approach is very promising and computationally efficient to handle realistic 3D discrete fractures with complicated geometries, connections, and spatial distributions. Compared with other fracture modeling approaches, it avoids cumbersome 3D unstructured, local refining procedures, and increases computational efficiency by simplifying Jacobian matrix size and sparsity, while keeps sufficient accuracy. Several numeral simulations are present to demonstrate the utility and robustness of the proposed technique. Our numerical experiments show that this approach captures all the key patterns about fluid flow and heat transfer dominated by fractures in these cases. Thus, this approach is readily available to simulation of fractured geothermal reservoirs with both artificial and natural fractures.

  3. A Bayesian hierarchical model for demand curve analysis.

    Science.gov (United States)

    Ho, Yen-Yi; Nhu Vo, Tien; Chu, Haitao; Luo, Xianghua; Le, Chap T

    2018-07-01

    Drug self-administration experiments are a frequently used approach to assessing the abuse liability and reinforcing property of a compound. It has been used to assess the abuse liabilities of various substances such as psychomotor stimulants and hallucinogens, food, nicotine, and alcohol. The demand curve generated from a self-administration study describes how demand of a drug or non-drug reinforcer varies as a function of price. With the approval of the 2009 Family Smoking Prevention and Tobacco Control Act, demand curve analysis provides crucial evidence to inform the US Food and Drug Administration's policy on tobacco regulation, because it produces several important quantitative measurements to assess the reinforcing strength of nicotine. The conventional approach popularly used to analyze the demand curve data is individual-specific non-linear least square regression. The non-linear least square approach sets out to minimize the residual sum of squares for each subject in the dataset; however, this one-subject-at-a-time approach does not allow for the estimation of between- and within-subject variability in a unified model framework. In this paper, we review the existing approaches to analyze the demand curve data, non-linear least square regression, and the mixed effects regression and propose a new Bayesian hierarchical model. We conduct simulation analyses to compare the performance of these three approaches and illustrate the proposed approaches in a case study of nicotine self-administration in rats. We present simulation results and discuss the benefits of using the proposed approaches.

  4. Synthesis of industrial applications of local approach to fracture models

    International Nuclear Information System (INIS)

    Eripret, C.

    1993-03-01

    This report gathers different applications of local approach to fracture models to various industrial configurations, such as nuclear pressure vessel steel, cast duplex stainless steels, or primary circuit welds such as bimetallic welds. As soon as models are developed on the basis of microstructural observations, damage mechanisms analyses, and fracture process, the local approach to fracture proves to solve problems where classical fracture mechanics concepts fail. Therefore, local approach appears to be a powerful tool, which completes the standard fracture criteria used in nuclear industry by exhibiting where and why those classical concepts become unvalid. (author). 1 tab., 18 figs., 25 refs

  5. Modelling of Local Necking and Fracture in Aluminium Alloys

    International Nuclear Information System (INIS)

    Achani, D.; Eriksson, M.; Hopperstad, O. S.; Lademo, O.-G.

    2007-01-01

    Non-linear Finite Element simulations are extensively used in forming and crashworthiness studies of automotive components and structures in which fracture need to be controlled. For thin-walled ductile materials, the fracture-related phenomena that must be properly represented are thinning instability, ductile fracture and through-thickness shear instability. Proper representation of the fracture process relies on the accuracy of constitutive and fracture models and their parameters that need to be calibrated through well defined experiments. The present study focuses on local necking and fracture which is of high industrial importance, and uses a phenomenological criterion for modelling fracture in aluminium alloys. As an accurate description of plastic anisotropy is important, advanced phenomenological constitutive equations based on the yield criterion YLD2000/YLD2003 are used. Uniaxial tensile tests and disc compression tests are performed for identification of the constitutive model parameters. Ductile fracture is described by the Cockcroft-Latham fracture criterion and an in-plane shear tests is performed to identify the fracture parameter. The reason is that in a well designed in-plane shear test no thinning instability should occur and it thus gives more direct information about the phenomenon of ductile fracture. Numerical simulations have been performed using a user-defined material model implemented in the general-purpose non-linear FE code LS-DYNA. The applicability of the model is demonstrated by correlating the predicted and experimental response in the in-plane shear tests and additional plane strain tension tests

  6. Statistical modelling of railway track geometry degradation using Hierarchical Bayesian models

    International Nuclear Information System (INIS)

    Andrade, A.R.; Teixeira, P.F.

    2015-01-01

    Railway maintenance planners require a predictive model that can assess the railway track geometry degradation. The present paper uses a Hierarchical Bayesian model as a tool to model the main two quality indicators related to railway track geometry degradation: the standard deviation of longitudinal level defects and the standard deviation of horizontal alignment defects. Hierarchical Bayesian Models (HBM) are flexible statistical models that allow specifying different spatially correlated components between consecutive track sections, namely for the deterioration rates and the initial qualities parameters. HBM are developed for both quality indicators, conducting an extensive comparison between candidate models and a sensitivity analysis on prior distributions. HBM is applied to provide an overall assessment of the degradation of railway track geometry, for the main Portuguese railway line Lisbon–Oporto. - Highlights: • Rail track geometry degradation is analysed using Hierarchical Bayesian models. • A Gibbs sampling strategy is put forward to estimate the HBM. • Model comparison and sensitivity analysis find the most suitable model. • We applied the most suitable model to all the segments of the main Portuguese line. • Tackling spatial correlations using CAR structures lead to a better model fit

  7. Numerical modelling in non linear fracture mechanics

    Directory of Open Access Journals (Sweden)

    Viggo Tvergaard

    2007-07-01

    Full Text Available Some numerical studies of crack propagation are based on using constitutive models that accountfor damage evolution in the material. When a critical damage value has been reached in a materialpoint, it is natural to assume that this point has no more carrying capacity, as is done numerically in the elementvanish technique. In the present review this procedure is illustrated for micromechanically based materialmodels, such as a ductile failure model that accounts for the nucleation and growth of voids to coalescence, and a model for intergranular creep failure with diffusive growth of grain boundary cavities leading to micro-crack formation. The procedure is also illustrated for low cycle fatigue, based on continuum damage mechanics. In addition, the possibility of crack growth predictions for elastic-plastic solids using cohesive zone models to represent the fracture process is discussed.

  8. Simulation of counter-current imbibition in water-wet fractured reservoirs based on discrete-fracture model

    Directory of Open Access Journals (Sweden)

    Wang Yueying

    2017-08-01

    Full Text Available Isolated fractures usually exist in fractured media systems, where the capillary pressure in the fracture is lower than that of the matrix, causing the discrepancy in oil recoveries between fractured and non-fractured porous media. Experiments, analytical solutions and conventional simulation methods based on the continuum model approach are incompetent or insufficient in describing media containing isolated fractures. In this paper, the simulation of the counter-current imbibition in fractured media is based on the discrete-fracture model (DFM. The interlocking or arrangement of matrix and fracture system within the model resembles the traditional discrete fracture network model and the hybrid-mixed-finite-element method is employed to solve the associated equations. The Behbahani experimental data validates our simulation solution for consistency. The simulation results of the fractured media show that the isolated-fractures affect the imbibition in the matrix block. Moreover, the isolated fracture parameters such as fracture length and fracture location influence the trend of the recovery curves. Thus, the counter-current imbibition behavior of media with isolated fractures can be predicted using this method based on the discrete-fracture model.

  9. Linking advanced fracture models to structural analysis

    Energy Technology Data Exchange (ETDEWEB)

    Chiesa, Matteo

    2001-07-01

    Shell structures with defects occur in many situations. The defects are usually introduced during the welding process necessary for joining different parts of the structure. Higher utilization of structural materials leads to a need for accurate numerical tools for reliable prediction of structural response. The direct discretization of the cracked shell structure with solid finite elements in order to perform an integrity assessment of the structure in question leads to large size problems, and makes such analysis infeasible in structural application. In this study a link between local material models and structural analysis is outlined. An ''ad hoc'' element formulation is used in order to connect complex material models to the finite element framework used for structural analysis. An improved elasto-plastic line spring finite element formulation, used in order to take cracks into account, is linked to shell elements which are further linked to beam elements. In this way one obtain a global model of the shell structure that also accounts for local flexibilities and fractures due to defects. An important advantage with such an approach is a direct fracture mechanics assessment e.g. via computed J-integral or CTOD. A recent development in this approach is the notion of two-parameter fracture assessment. This means that the crack tip stress tri-axiality (constraint) is employed in determining the corresponding fracture toughness, giving a much more realistic capacity of cracked structures. The present thesis is organized in six research articles and an introductory chapter that reviews important background literature related to this work. Paper I and II address the performance of shell and line spring finite elements as a cost effective tool for performing the numerical calculation needed to perform a fracture assessment. In Paper II a failure assessment, based on the testing of a constraint-corrected fracture mechanics specimen under tension, is

  10. Modelling deformation and fracture in confectionery wafers

    Energy Technology Data Exchange (ETDEWEB)

    Mohammed, Idris K.; Charalambides, Maria N.; Williams, J. Gordon; Rasburn, John [Mechanical Engineering Department, Imperial College London, South Kensington, London, SW7 2AZ, United Kingdom and Nestec York Ltd., Nestlé Product Technology Centre, Haxby Road, PO Box 204, York YO91 1XY (United Kingdom)

    2015-01-22

    The aim of this research is to model the deformation and fracture behaviour of brittle wafers often used in chocolate confectionary products. Three point bending and compression experiments were performed on beam and circular disc samples respectively to determine the 'apparent' stress-strain curves in bending and compression. The deformation of the wafer for both these testing types was observed in-situ within an SEM. The wafer is modeled analytically and numerically as a composite material with a core which is more porous than the skins. X-ray tomography was used to generate a three dimensional volume of the wafer microstructure which was then meshed and used for quantitative analysis. A linear elastic material model, with a damage function and element deletion, was used and the XMT generated architecture was loaded in compression. The output from the FE simulations correlates closely to the load-deflection deformation observed experimentally.

  11. Specimen-specific modeling of hip fracture pattern and repair.

    Science.gov (United States)

    Ali, Azhar A; Cristofolini, Luca; Schileo, Enrico; Hu, Haixiang; Taddei, Fulvia; Kim, Raymond H; Rullkoetter, Paul J; Laz, Peter J

    2014-01-22

    Hip fracture remains a major health problem for the elderly. Clinical studies have assessed fracture risk based on bone quality in the aging population and cadaveric testing has quantified bone strength and fracture loads. Prior modeling has primarily focused on quantifying the strain distribution in bone as an indicator of fracture risk. Recent advances in the extended finite element method (XFEM) enable prediction of the initiation and propagation of cracks without requiring a priori knowledge of the crack path. Accordingly, the objectives of this study were to predict femoral fracture in specimen-specific models using the XFEM approach, to perform one-to-one comparisons of predicted and in vitro fracture patterns, and to develop a framework to assess the mechanics and load transfer in the fractured femur when it is repaired with an osteosynthesis implant. Five specimen-specific femur models were developed from in vitro experiments under a simulated stance loading condition. Predicted fracture patterns closely matched the in vitro patterns; however, predictions of fracture load differed by approximately 50% due to sensitivity to local material properties. Specimen-specific intertrochanteric fractures were induced by subjecting the femur models to a sideways fall and repaired with a contemporary implant. Under a post-surgical stance loading, model-predicted load sharing between the implant and bone across the fracture surface varied from 59%:41% to 89%:11%, underscoring the importance of considering anatomic and fracture variability in the evaluation of implants. XFEM modeling shows potential as a macro-level analysis enabling fracture investigations of clinical cohorts, including at-risk groups, and the design of robust implants. © 2013 Published by Elsevier Ltd.

  12. A multiscale model of distributed fracture and permeability in solids in all-round compression

    Science.gov (United States)

    De Bellis, Maria Laura; Della Vecchia, Gabriele; Ortiz, Michael; Pandolfi, Anna

    2017-07-01

    We present a microstructural model of permeability in fractured solids, where the fractures are described in terms of recursive families of parallel, equidistant cohesive faults. Faults originate upon the attainment of tensile or shear strength in the undamaged material. Secondary faults may form in a hierarchical organization, creating a complex network of connected fractures that modify the permeability of the solid. The undamaged solid may possess initial porosity and permeability. The particular geometry of the superposed micro-faults lends itself to an explicit analytical quantification of the porosity and permeability of the damaged material. The model is the finite kinematics version of a recently proposed porous material model, applied with success to the simulation of laboratory tests and excavation problems [De Bellis, M. L., Della Vecchia, G., Ortiz, M., Pandolfi, A., 2016. A linearized porous brittle damage material model with distributed frictional-cohesive faults. Engineering Geology 215, 10-24. Cited By 0. 10.1016/j.enggeo.2016.10.010]. The extension adds over and above the linearized kinematics version for problems characterized by large deformations localized in narrow zones, while the remainder of the solid undergoes small deformations, as typically observed in soil and rock mechanics problems. The approach is particularly appealing as a means of modeling a wide scope of engineering problems, ranging from the prevention of water or gas outburst into underground mines, to the prediction of the integrity of reservoirs for CO2 sequestration or hazardous waste storage, to hydraulic fracturing processes.

  13. Hierarchical functional model for automobile development; Jidosha kaihatsu no tame no kaisogata kino model

    Energy Technology Data Exchange (ETDEWEB)

    Sumida, S [U-shin Ltd., Tokyo (Japan); Nagamatsu, M; Maruyama, K [Hokkaido Institute of Technology, Sapporo (Japan); Hiramatsu, S [Mazda Motor Corp., Hiroshima (Japan)

    1997-10-01

    A new approach on modeling is put forward in order to compose the virtual prototype which is indispensable for fully computer integrated concurrent development of automobile product. A basic concept of the hierarchical functional model is proposed as the concrete form of this new modeling technology. This model is used mainly for explaining and simulating functions and efficiencies of both the parts and the total product of automobile. All engineers who engage themselves in design and development of automobile can collaborate with one another using this model. Some application examples are shown, and usefulness of this model is demonstrated. 5 refs., 5 figs.

  14. A new computer code for discrete fracture network modelling

    Science.gov (United States)

    Xu, Chaoshui; Dowd, Peter

    2010-03-01

    The authors describe a comprehensive software package for two- and three-dimensional stochastic rock fracture simulation using marked point processes. Fracture locations can be modelled by a Poisson, a non-homogeneous, a cluster or a Cox point process; fracture geometries and properties are modelled by their respective probability distributions. Virtual sampling tools such as plane, window and scanline sampling are included in the software together with a comprehensive set of statistical tools including histogram analysis, probability plots, rose diagrams and hemispherical projections. The paper describes in detail the theoretical basis of the implementation and provides a case study in rock fracture modelling to demonstrate the application of the software.

  15. Recognizing Chinese characters in digital ink from non-native language writers using hierarchical models

    Science.gov (United States)

    Bai, Hao; Zhang, Xi-wen

    2017-06-01

    While Chinese is learned as a second language, its characters are taught step by step from their strokes to components, radicals to components, and their complex relations. Chinese Characters in digital ink from non-native language writers are deformed seriously, thus the global recognition approaches are poorer. So a progressive approach from bottom to top is presented based on hierarchical models. Hierarchical information includes strokes and hierarchical components. Each Chinese character is modeled as a hierarchical tree. Strokes in one Chinese characters in digital ink are classified with Hidden Markov Models and concatenated to the stroke symbol sequence. And then the structure of components in one ink character is extracted. According to the extraction result and the stroke symbol sequence, candidate characters are traversed and scored. Finally, the recognition candidate results are listed by descending. The method of this paper is validated by testing 19815 copies of the handwriting Chinese characters written by foreign students.

  16. New aerial survey and hierarchical model to estimate manatee abundance

    Science.gov (United States)

    Langimm, Cahterine A.; Dorazio, Robert M.; Stith, Bradley M.; Doyle, Terry J.

    2011-01-01

    Monitoring the response of endangered and protected species to hydrological restoration is a major component of the adaptive management framework of the Comprehensive Everglades Restoration Plan. The endangered Florida manatee (Trichechus manatus latirostris) lives at the marine-freshwater interface in southwest Florida and is likely to be affected by hydrologic restoration. To provide managers with prerestoration information on distribution and abundance for postrestoration comparison, we developed and implemented a new aerial survey design and hierarchical statistical model to estimate and map abundance of manatees as a function of patch-specific habitat characteristics, indicative of manatee requirements for offshore forage (seagrass), inland fresh drinking water, and warm-water winter refuge. We estimated the number of groups of manatees from dual-observer counts and estimated the number of individuals within groups by removal sampling. Our model is unique in that we jointly analyzed group and individual counts using assumptions that allow probabilities of group detection to depend on group size. Ours is the first analysis of manatee aerial surveys to model spatial and temporal abundance of manatees in association with habitat type while accounting for imperfect detection. We conducted the study in the Ten Thousand Islands area of southwestern Florida, USA, which was expected to be affected by the Picayune Strand Restoration Project to restore hydrology altered for a failed real-estate development. We conducted 11 surveys in 2006, spanning the cold, dry season and warm, wet season. To examine short-term and seasonal changes in distribution we flew paired surveys 1–2 days apart within a given month during the year. Manatees were sparsely distributed across the landscape in small groups. Probability of detection of a group increased with group size; the magnitude of the relationship between group size and detection probability varied among surveys. Probability

  17. Hydromechanical modeling of clay rock including fracture damage

    Science.gov (United States)

    Asahina, D.; Houseworth, J. E.; Birkholzer, J. T.

    2012-12-01

    Argillaceous rock typically acts as a flow barrier, but under certain conditions significant and potentially conductive fractures may be present. Fracture formation is well-known to occur in the vicinity of underground excavations in a region known as the excavation disturbed zone. Such problems are of particular importance for low-permeability, mechanically weak rock such as clays and shales because fractures can be relatively transient as a result of fracture self-sealing processes. Perhaps not as well appreciated is the fact that natural fractures can form in argillaceous rock as a result of hydraulic overpressure caused by phenomena such as disequlibrium compaction, changes in tectonic stress, and mineral dehydration. Overpressure conditions can cause hydraulic fracturing if the fluid pressure leads to tensile effective stresses that exceed the tensile strength of the material. Quantitative modeling of this type of process requires coupling between hydrogeologic processes and geomechanical processes including fracture initiation and propagation. Here we present a computational method for three-dimensional, hydromechanical coupled processes including fracture damage. Fractures are represented as discrete features in a fracture network that interact with a porous rock matrix. Fracture configurations are mapped onto an unstructured, three-dimensonal, Voronoi grid, which is based on a random set of spatial points. Discrete fracture networks (DFN) are represented by the connections of the edges of a Voronoi cells. This methodology has the advantage that fractures can be more easily introduced in response to coupled hydro-mechanical processes and generally eliminates several potential issues associated with the geometry of DFN and numerical gridding. A geomechanical and fracture-damage model is developed here using the Rigid-Body-Spring-Network (RBSN) numerical method. The hydrogelogic and geomechanical models share the same geometrical information from a 3D Voronoi

  18. Modeling of flow through fractured tuff at Fran Ridge

    International Nuclear Information System (INIS)

    Eaton, R.R.; Ho, C.K.; Glass, R.J.; Nicholl, M.J.; Arnold, B.W.

    1996-01-01

    Numerical studies have modeled an infiltration experiment at Fran Ridge, using the TOUGH2 code, to aid in the selection of computational models for waste repository performance assessment. This study investigates the capabilities of TOUGH2 to simulate transient flows through highly fractured tuff, and provides a possible means of calibrating hydrologic parameters such as effective fracture aperture and fracture-matrix connectivity. Two distinctly different conceptual models were used in the TOUGH2 code, the dual permeability model and the equivalent continuum model. The field experiments involved the infiltration of dyed ponded water in highly fractured tuff. The infiltration observed in the experiment was subsequently modeled using Fran Ridge fracture frequencies, obtained during post-experiment site excavation. Comparison of the TOUGH2 results obtained using the two conceptual models gives insight into their relative strengths and weaknesses

  19. Streaming potential modeling in fractured rock: Insights into the identification of hydraulically active fractures

    Science.gov (United States)

    Roubinet, D.; Linde, N.; Jougnot, D.; Irving, J.

    2016-05-01

    Numerous field experiments suggest that the self-potential (SP) geophysical method may allow for the detection of hydraulically active fractures and provide information about fracture properties. However, a lack of suitable numerical tools for modeling streaming potentials in fractured media prevents quantitative interpretation and limits our understanding of how the SP method can be used in this regard. To address this issue, we present a highly efficient two-dimensional discrete-dual-porosity approach for solving the fluid flow and associated self-potential problems in fractured rock. Our approach is specifically designed for complex fracture networks that cannot be investigated using standard numerical methods. We then simulate SP signals associated with pumping conditions for a number of examples to show that (i) accounting for matrix fluid flow is essential for accurate SP modeling and (ii) the sensitivity of SP to hydraulically active fractures is intimately linked with fracture-matrix fluid interactions. This implies that fractures associated with strong SP amplitudes are likely to be hydraulically conductive, attracting fluid flow from the surrounding matrix.

  20. Discrete fracture modelling of the Finnsjoen rock mass: Phase 2

    International Nuclear Information System (INIS)

    Geier, J.E.; Axelsson, C.L.; Haessler, L.; Benabderrahmane, A.

    1992-04-01

    A discrete fracture network (DFN) model of the Finnsjoen site was derived from field data, and used to predict block-scale flow and transport properties. The DFN model was based on a compound Poisson process, with stochastic fracture zones, and individual fracture concentrated around the fracture zones. This formulation was used to represent the multitude of fracture zones at the site which could be observed on lineament maps and in boreholes, but were not the focus of detailed characterization efforts. Due to a shortage of data for fracture geometry at depth, distributions of fracture orientation and size were assumed to be uniform throughout the site. Transmissivity within individual fracture planes was assumed to vary according to a fractal model. Constant-head packer tests were simulated with the model, and the observed transient responses were compared with actual tests in terms of distributions of interpreted transmissivity and flow dimension, to partially validate the model. Both simulated and actual tests showed a range of flow dimension from sublinear to spherical, indicating local variations in the connectivity of the fracture population. A methodology was developed for estimation of an effective stochastic continuum from the DFN model, but this was only partly demonstrated. Directional conductivities for 40 m block were estimated using the DFN model. These show extremely poor correlation with results of multiple packer tests in the same blocks, indicating possible limitation of small-scale packer tests for predicting block-scale properties. Estimates are given of effective flow porosity and flow wetted surface, based on the block-scale flow fields calculated by the DFN model, and probabilistic models for the relationships among local fracture transmissivity, void space, and specific surface. The database for constructing these models is extremely limited. A review is given of the existing database for single fracture hydrologic properties. (127 refs

  1. A mechanical model of biomimetic adhesive pads with tilted and hierarchical structures.

    Science.gov (United States)

    Schargott, M

    2009-06-01

    A 3D model for hierarchical biomimetic adhesive pads is constructed. It is based on the main principles of the adhesive pads of the Tokay gecko and consists of hierarchical layers of vertical or tilted beams, where each layer is constructed in such a way that no cohesion between adjacent beams can occur. The elastic and adhesive properties are calculated analytically and numerically. For the adhesive contact on stochastically rough surfaces, the maximum adhesion force increases with increasing number of hierarchical layers. Additional calculations show that the adhesion force also depends on the height spectrum of the rough surface.

  2. A mechanical model of biomimetic adhesive pads with tilted and hierarchical structures

    Energy Technology Data Exchange (ETDEWEB)

    Schargott, M [Institute of Mechanics, Technische Universitaet Berlin, Strd 17 Juni 135, 10623 Berlin (Germany)], E-mail: martin.schargott@tu-berlin.de

    2009-06-01

    A 3D model for hierarchical biomimetic adhesive pads is constructed. It is based on the main principles of the adhesive pads of the Tokay gecko and consists of hierarchical layers of vertical or tilted beams, where each layer is constructed in such a way that no cohesion between adjacent beams can occur. The elastic and adhesive properties are calculated analytically and numerically. For the adhesive contact on stochastically rough surfaces, the maximum adhesion force increases with increasing number of hierarchical layers. Additional calculations show that the adhesion force also depends on the height spectrum of the rough surface.

  3. A mechanical model of biomimetic adhesive pads with tilted and hierarchical structures

    International Nuclear Information System (INIS)

    Schargott, M

    2009-01-01

    A 3D model for hierarchical biomimetic adhesive pads is constructed. It is based on the main principles of the adhesive pads of the Tokay gecko and consists of hierarchical layers of vertical or tilted beams, where each layer is constructed in such a way that no cohesion between adjacent beams can occur. The elastic and adhesive properties are calculated analytically and numerically. For the adhesive contact on stochastically rough surfaces, the maximum adhesion force increases with increasing number of hierarchical layers. Additional calculations show that the adhesion force also depends on the height spectrum of the rough surface

  4. Modeling Dynamic Fracture of Cryogenic Pellets

    Energy Technology Data Exchange (ETDEWEB)

    Parks, Paul [General Atomics, San Diego, CA (United States)

    2016-06-30

    This work is part of an investigation with the long-range objective of predicting the size distribution function and velocity dispersion of shattered pellet fragments after a large cryogenic pellet impacts a solid surface at high velocity. The study is vitally important for the shattered pellet injection (SPI) technique, one of the leading technologies being implemented at ORNL for the mitigation of disruption damage on current tokamaks and ITER. The report contains three parts that are somewhat interwoven. In Part I we formulated a self-similar model for the expansion dynamics and velocity dispersion of the debris cloud following pellet impact against a thick (rigid) target plate. Also presented in Part I is an analytical fracture model that predicts the nominal or mean size of the fragments in the debris cloud and agrees well with known SPI data. The aim of Part II is to gain an understanding of the pellet fracturing process when a pellet is shattered inside a miter tube with a sharp bend. Because miter tubes have a thin stainless steel (SS) wall a permanent deformation (dishing) of the wall is produced at the site of the impact. A review of the literature indicates that most projectile impact on thin plates are those for which the target is deformed and the projectile is perfectly rigid. Such impacts result in “projectile embedding” where the projectile speed is reduced to zero during the interaction so that all the kinetic energy (KE) of the projectile goes into the energy stored in plastic deformation. Much of the literature deals with perforation of the target. The problem here is quite different; the softer pellet easily undergoes complete material failure causing only a small transfer of KE to stored energy of wall deformation. For the real miter tube, we derived a strain energy function for the wall deflection using a non-linear (plastic) stress-strain relation for 304 SS. Using a dishing profile identical to the linear Kirchkoff-Love profile (for lack

  5. Anisotropic composite human skull model and skull fracture validation against temporo-parietal skull fracture.

    Science.gov (United States)

    Sahoo, Debasis; Deck, Caroline; Yoganandan, Narayan; Willinger, Rémy

    2013-12-01

    A composite material model for skull, taking into account damage is implemented in the Strasbourg University finite element head model (SUFEHM) in order to enhance the existing skull mechanical constitutive law. The skull behavior is validated in terms of fracture patterns and contact forces by reconstructing 15 experimental cases. The new SUFEHM skull model is capable of reproducing skull fracture precisely. The composite skull model is validated not only for maximum forces, but also for lateral impact against actual force time curves from PMHS for the first time. Skull strain energy is found to be a pertinent parameter to predict the skull fracture and based on statistical (binary logistical regression) analysis it is observed that 50% risk of skull fracture occurred at skull strain energy of 544.0mJ. © 2013 Elsevier Ltd. All rights reserved.

  6. A fractal model for intergranular fractures in nanocrystals

    International Nuclear Information System (INIS)

    Lung, C.W.; Xiong, L.Y.; Zhou, X.Z.

    1993-09-01

    A fractal model for intergranular fractures in nanocrystals is proposed to explain the dependence of fracture toughness with grain size in this range of scale. Based on positron annihilation and internal friction experimental results, we point out that the assumption of a constant grain boundary thickness in previous models is too simplified to be true. (author). 7 refs, 6 figs

  7. Usability Prediction & Ranking of SDLC Models Using Fuzzy Hierarchical Usability Model

    Science.gov (United States)

    Gupta, Deepak; Ahlawat, Anil K.; Sagar, Kalpna

    2017-06-01

    Evaluation of software quality is an important aspect for controlling and managing the software. By such evaluation, improvements in software process can be made. The software quality is significantly dependent on software usability. Many researchers have proposed numbers of usability models. Each model considers a set of usability factors but do not cover all the usability aspects. Practical implementation of these models is still missing, as there is a lack of precise definition of usability. Also, it is very difficult to integrate these models into current software engineering practices. In order to overcome these challenges, this paper aims to define the term `usability' using the proposed hierarchical usability model with its detailed taxonomy. The taxonomy considers generic evaluation criteria for identifying the quality components, which brings together factors, attributes and characteristics defined in various HCI and software models. For the first time, the usability model is also implemented to predict more accurate usability values. The proposed system is named as fuzzy hierarchical usability model that can be easily integrated into the current software engineering practices. In order to validate the work, a dataset of six software development life cycle models is created and employed. These models are ranked according to their predicted usability values. This research also focuses on the detailed comparison of proposed model with the existing usability models.

  8. Lean business model and implementation of a geriatric fracture center.

    Science.gov (United States)

    Kates, Stephen L

    2014-05-01

    Geriatric hip fracture is a common event associated with high costs of care and often with suboptimal outcomes for the patients. Ideally, a new care model to manage geriatric hip fractures would address both quality and safety of patient care as well as the need for reduced costs of care. The geriatric fracture center model of care is one such model reported to improve both outcomes and quality of care. It is a lean business model applied to medicine. This article describes basic lean business concepts applied to geriatric fracture care and information needed to successfully implement a geriatric fracture center. It is written to assist physicians and surgeons in their efforts to implement an improved care model for their patients. Copyright © 2014 Elsevier Inc. All rights reserved.

  9. Bottom-up learning of hierarchical models in a class of deterministic POMDP environments

    Directory of Open Access Journals (Sweden)

    Itoh Hideaki

    2015-09-01

    Full Text Available The theory of partially observable Markov decision processes (POMDPs is a useful tool for developing various intelligent agents, and learning hierarchical POMDP models is one of the key approaches for building such agents when the environments of the agents are unknown and large. To learn hierarchical models, bottom-up learning methods in which learning takes place in a layer-by-layer manner from the lowest to the highest layer are already extensively used in some research fields such as hidden Markov models and neural networks. However, little attention has been paid to bottom-up approaches for learning POMDP models. In this paper, we present a novel bottom-up learning algorithm for hierarchical POMDP models and prove that, by using this algorithm, a perfect model (i.e., a model that can perfectly predict future observations can be learned at least in a class of deterministic POMDP environments

  10. Automatic thoracic anatomy segmentation on CT images using hierarchical fuzzy models and registration

    Science.gov (United States)

    Sun, Kaioqiong; Udupa, Jayaram K.; Odhner, Dewey; Tong, Yubing; Torigian, Drew A.

    2014-03-01

    This paper proposes a thoracic anatomy segmentation method based on hierarchical recognition and delineation guided by a built fuzzy model. Labeled binary samples for each organ are registered and aligned into a 3D fuzzy set representing the fuzzy shape model for the organ. The gray intensity distributions of the corresponding regions of the organ in the original image are recorded in the model. The hierarchical relation and mean location relation between different organs are also captured in the model. Following the hierarchical structure and location relation, the fuzzy shape model of different organs is registered to the given target image to achieve object recognition. A fuzzy connected delineation method is then used to obtain the final segmentation result of organs with seed points provided by recognition. The hierarchical structure and location relation integrated in the model provide the initial parameters for registration and make the recognition efficient and robust. The 3D fuzzy model combined with hierarchical affine registration ensures that accurate recognition can be obtained for both non-sparse and sparse organs. The results on real images are presented and shown to be better than a recently reported fuzzy model-based anatomy recognition strategy.

  11. Hierarchical modeling and inference in ecology: The analysis of data from populations, metapopulations and communities

    Science.gov (United States)

    Royle, J. Andrew; Dorazio, Robert M.

    2008-01-01

    A guide to data collection, modeling and inference strategies for biological survey data using Bayesian and classical statistical methods. This book describes a general and flexible framework for modeling and inference in ecological systems based on hierarchical models, with a strict focus on the use of probability models and parametric inference. Hierarchical models represent a paradigm shift in the application of statistics to ecological inference problems because they combine explicit models of ecological system structure or dynamics with models of how ecological systems are observed. The principles of hierarchical modeling are developed and applied to problems in population, metapopulation, community, and metacommunity systems. The book provides the first synthetic treatment of many recent methodological advances in ecological modeling and unifies disparate methods and procedures. The authors apply principles of hierarchical modeling to ecological problems, including * occurrence or occupancy models for estimating species distribution * abundance models based on many sampling protocols, including distance sampling * capture-recapture models with individual effects * spatial capture-recapture models based on camera trapping and related methods * population and metapopulation dynamic models * models of biodiversity, community structure and dynamics.

  12. Modelling Laccoliths: Fluid-Driven Fracturing in the Lab

    Science.gov (United States)

    Ball, T. V.; Neufeld, J. A.

    2017-12-01

    Current modelling of the formation of laccoliths neglects the necessity to fracture rock layers for propagation to occur [1]. In magmatic intrusions at depth the idea of fracture toughness is used to characterise fracturing, however an analogue for near surface intrusions has yet to be explored [2]. We propose an analytical model for laccolith emplacement that accounts for the energy required to fracture at the tip of an intrusion. For realistic physical parameters we find that a lag region exists between the fluid magma front and the crack tip where large negative pressures in the tip cause volatiles to exsolve from the magma. Crucially, the dynamics of this tip region controls the spreading due to the competition between viscous forces and fracture energy. We conduct a series of complementary experiments to investigate fluid-driven fracturing of adhered layers and confirm the existence of two regimes: viscosity dominant spreading, controlled by the pressure in the lag region, and fracture energy dominant spreading, controlled by the energy required to fracture layers. Our experiments provide the first observations, and evolution, of a vapour tip. These experiments and our simplified model provide insight into the key physical processes in near surface magmatic intrusions with applications to fluid-driven fracturing more generally. Michaut J. Geophys. Res. 116(B5), B05205. Bunger & Cruden J. Geophys. Res. 116(B2), B02203.

  13. Modelling of ductile and cleavage fracture by local approach

    International Nuclear Information System (INIS)

    Samal, M.K.; Dutta, B.K.; Kushwaha, H.S.

    2000-08-01

    This report describes the modelling of ductile and cleavage fracture processes by local approach. It is now well known that the conventional fracture mechanics method based on single parameter criteria is not adequate to model the fracture processes. It is because of the existence of effect of size and geometry of flaw, loading type and rate on the fracture resistance behaviour of any structure. Hence, it is questionable to use same fracture resistance curves as determined from standard tests in the analysis of real life components because of existence of all the above effects. So, there is need to have a method in which the parameters used for the analysis will be true material properties, i.e. independent of geometry and size. One of the solutions to the above problem is the use of local approaches. These approaches have been extensively studied and applied to different materials (including SA33 Gr.6) in this report. Each method has been studied and reported in a separate section. This report has been divided into five sections. Section-I gives a brief review of the fundamentals of fracture process. Section-II deals with modelling of ductile fracture by locally uncoupled type of models. In this section, the critical cavity growth parameters of the different models have been determined for the primary heat transport (PHT) piping material of Indian pressurised heavy water reactor (PHWR). A comparative study has been done among different models. The dependency of the critical parameters on stress triaxiality factor has also been studied. It is observed that Rice and Tracey's model is the most suitable one. But, its parameters are not fully independent of triaxiality factor. For this purpose, a modification to Rice and Tracery's model is suggested in Section-III. Section-IV deals with modelling of ductile fracture process by locally coupled type of models. Section-V deals with the modelling of cleavage fracture process by Beremins model, which is based on Weibulls

  14. Ranking of Business Process Simulation Software Tools with DEX/QQ Hierarchical Decision Model.

    Science.gov (United States)

    Damij, Nadja; Boškoski, Pavle; Bohanec, Marko; Mileva Boshkoska, Biljana

    2016-01-01

    The omnipresent need for optimisation requires constant improvements of companies' business processes (BPs). Minimising the risk of inappropriate BP being implemented is usually performed by simulating the newly developed BP under various initial conditions and "what-if" scenarios. An effectual business process simulations software (BPSS) is a prerequisite for accurate analysis of an BP. Characterisation of an BPSS tool is a challenging task due to the complex selection criteria that includes quality of visual aspects, simulation capabilities, statistical facilities, quality reporting etc. Under such circumstances, making an optimal decision is challenging. Therefore, various decision support models are employed aiding the BPSS tool selection. The currently established decision support models are either proprietary or comprise only a limited subset of criteria, which affects their accuracy. Addressing this issue, this paper proposes a new hierarchical decision support model for ranking of BPSS based on their technical characteristics by employing DEX and qualitative to quantitative (QQ) methodology. Consequently, the decision expert feeds the required information in a systematic and user friendly manner. There are three significant contributions of the proposed approach. Firstly, the proposed hierarchical model is easily extendible for adding new criteria in the hierarchical structure. Secondly, a fully operational decision support system (DSS) tool that implements the proposed hierarchical model is presented. Finally, the effectiveness of the proposed hierarchical model is assessed by comparing the resulting rankings of BPSS with respect to currently available results.

  15. Robust Real-Time Music Transcription with a Compositional Hierarchical Model.

    Science.gov (United States)

    Pesek, Matevž; Leonardis, Aleš; Marolt, Matija

    2017-01-01

    The paper presents a new compositional hierarchical model for robust music transcription. Its main features are unsupervised learning of a hierarchical representation of input data, transparency, which enables insights into the learned representation, as well as robustness and speed which make it suitable for real-world and real-time use. The model consists of multiple layers, each composed of a number of parts. The hierarchical nature of the model corresponds well to hierarchical structures in music. The parts in lower layers correspond to low-level concepts (e.g. tone partials), while the parts in higher layers combine lower-level representations into more complex concepts (tones, chords). The layers are learned in an unsupervised manner from music signals. Parts in each layer are compositions of parts from previous layers based on statistical co-occurrences as the driving force of the learning process. In the paper, we present the model's structure and compare it to other hierarchical approaches in the field of music information retrieval. We evaluate the model's performance for the multiple fundamental frequency estimation. Finally, we elaborate on extensions of the model towards other music information retrieval tasks.

  16. A generalized linear factor model approach to the hierarchical framework for responses and response times.

    Science.gov (United States)

    Molenaar, Dylan; Tuerlinckx, Francis; van der Maas, Han L J

    2015-05-01

    We show how the hierarchical model for responses and response times as developed by van der Linden (2007), Fox, Klein Entink, and van der Linden (2007), Klein Entink, Fox, and van der Linden (2009), and Glas and van der Linden (2010) can be simplified to a generalized linear factor model with only the mild restriction that there is no hierarchical model at the item side. This result is valuable as it enables all well-developed modelling tools and extensions that come with these methods. We show that the restriction we impose on the hierarchical model does not influence parameter recovery under realistic circumstances. In addition, we present two illustrative real data analyses to demonstrate the practical benefits of our approach. © 2014 The British Psychological Society.

  17. Development of Reservoir Characterization Techniques and Production Models for Exploiting Naturally Fractured Reservoirs

    Energy Technology Data Exchange (ETDEWEB)

    Wiggins, Michael L.; Brown, Raymon L.; Civan, Frauk; Hughes, Richard G.

    2001-08-15

    Research continues on characterizing and modeling the behavior of naturally fractured reservoir systems. Work has progressed on developing techniques for estimating fracture properties from seismic and well log data, developing naturally fractured wellbore models, and developing a model to characterize the transfer of fluid from the matrix to the fracture system for use in the naturally fractured reservoir simulator.

  18. Simulated evolution of fractures and fracture networks subject to thermal cooling: A coupled discrete element and heat conduction model

    Energy Technology Data Exchange (ETDEWEB)

    Huang, Hai; Plummer, Mitchell; Podgorney, Robert

    2013-02-01

    Advancement of EGS requires improved prediction of fracture development and growth during reservoir stimulation and long-term operation. This, in turn, requires better understanding of the dynamics of the strongly coupled thermo-hydro-mechanical (THM) processes within fractured rocks. We have developed a physically based rock deformation and fracture propagation simulator by using a quasi-static discrete element model (DEM) to model mechanical rock deformation and fracture propagation induced by thermal stress and fluid pressure changes. We also developed a network model to simulate fluid flow and heat transport in both fractures and porous rock. In this paper, we describe results of simulations in which the DEM model and network flow & heat transport model are coupled together to provide realistic simulation of the changes of apertures and permeability of fractures and fracture networks induced by thermal cooling and fluid pressure changes within fractures. Various processes, such as Stokes flow in low velocity pores, convection-dominated heat transport in fractures, heat exchange between fluid-filled fractures and solid rock, heat conduction through low-permeability matrices and associated mechanical deformations are all incorporated into the coupled model. The effects of confining stresses, developing thermal stress and injection pressure on the permeability evolution of fracture and fracture networks are systematically investigated. Results are summarized in terms of implications for the development and evolution of fracture distribution during hydrofracturing and thermal stimulation for EGS.

  19. Three-Dimensional Modeling of Fracture Clusters in Geothermal Reservoirs

    Energy Technology Data Exchange (ETDEWEB)

    Ghassemi, Ahmad [Univ. of Oklahoma, Norman, OK (United States)

    2017-08-11

    The objective of this is to develop a 3-D numerical model for simulating mode I, II, and III (tensile, shear, and out-of-plane) propagation of multiple fractures and fracture clusters to accurately predict geothermal reservoir stimulation using the virtual multi-dimensional internal bond (VMIB). Effective development of enhanced geothermal systems can significantly benefit from improved modeling of hydraulic fracturing. In geothermal reservoirs, where the temperature can reach or exceed 350oC, thermal and poro-mechanical processes play an important role in fracture initiation and propagation. In this project hydraulic fracturing of hot subsurface rock mass will be numerically modeled by extending the virtual multiple internal bond theory and implementing it in a finite element code, WARP3D, a three-dimensional finite element code for solid mechanics. The new constitutive model along with the poro-thermoelastic computational algorithms will allow modeling the initiation and propagation of clusters of fractures, and extension of pre-existing fractures. The work will enable the industry to realistically model stimulation of geothermal reservoirs. The project addresses the Geothermal Technologies Office objective of accurately predicting geothermal reservoir stimulation (GTO technology priority item). The project goal will be attained by: (i) development of the VMIB method for application to 3D analysis of fracture clusters; (ii) development of poro- and thermoelastic material sub-routines for use in 3D finite element code WARP3D; (iii) implementation of VMIB and the new material routines in WARP3D to enable simulation of clusters of fractures while accounting for the effects of the pore pressure, thermal stress and inelastic deformation; (iv) simulation of 3D fracture propagation and coalescence and formation of clusters, and comparison with laboratory compression tests; and (v) application of the model to interpretation of injection experiments (planned by our

  20. Optimization of flow modeling in fractured media with discrete fracture network via percolation theory

    Science.gov (United States)

    Donado-Garzon, L. D.; Pardo, Y.

    2013-12-01

    Fractured media are very heterogeneous systems where occur complex physical and chemical processes to model. One of the possible approaches to conceptualize this type of massifs is the Discrete Fracture Network (DFN). Donado et al., modeled flow and transport in a granitic batholith based on this approach and found good fitting with hydraulic and tracer tests, but the computational cost was excessive due to a gigantic amount of elements to model. We present in this work a methodology based on percolation theory for reducing the number of elements and in consequence, to reduce the bandwidth of the conductance matrix and the execution time of each network. DFN poses as an excellent representation of all the set of fractures of the media, but not all the fractures of the media are part of the conductive network. Percolation theory is used to identify which nodes or fractures are not conductive, based on the occupation probability or percolation threshold. In a fractured system, connectivity determines the flow pattern in the fractured rock mass. This volume of fluid is driven through connection paths formed by the fractures, when the permeability of the rock is negligible compared to the fractures. In a population of distributed fractures, each of this that has no intersection with any connected fracture do not contribute to generate a flow field. This algorithm also permits us to erase these elements however they are water conducting and hence, refine even more the backbone of the network. We used 100 different generations of DFN that were optimized in this study using percolation theory. In each of the networks calibrate hydrodynamic parameters as hydraulic conductivity and specific storage coefficient, for each of the five families of fractures, yielding a total of 10 parameters to estimate, at each generation. Since the effects of the distribution of fault orientation changes the value of the percolation threshold, but not the universal laws of classical

  1. Predicting Longitudinal Change in Language Production and Comprehension in Individuals with Down Syndrome: Hierarchical Linear Modeling.

    Science.gov (United States)

    Chapman, Robin S.; Hesketh, Linda J.; Kistler, Doris J.

    2002-01-01

    Longitudinal change in syntax comprehension and production skill, measured over six years, was modeled in 31 individuals (ages 5-20) with Down syndrome. The best fitting Hierarchical Linear Modeling model of comprehension uses age and visual and auditory short-term memory as predictors of initial status, and age for growth trajectory. (Contains…

  2. Measuring Teacher Effectiveness through Hierarchical Linear Models: Exploring Predictors of Student Achievement and Truancy

    Science.gov (United States)

    Subedi, Bidya Raj; Reese, Nancy; Powell, Randy

    2015-01-01

    This study explored significant predictors of student's Grade Point Average (GPA) and truancy (days absent), and also determined teacher effectiveness based on proportion of variance explained at teacher level model. We employed a two-level hierarchical linear model (HLM) with student and teacher data at level-1 and level-2 models, respectively.…

  3. Heuristics for Hierarchical Partitioning with Application to Model Checking

    DEFF Research Database (Denmark)

    Möller, Michael Oliver; Alur, Rajeev

    2001-01-01

    Given a collection of connected components, it is often desired to cluster together parts of strong correspondence, yielding a hierarchical structure. We address the automation of this process and apply heuristics to battle the combinatorial and computational complexity. We define a cost function...... that captures the quality of a structure relative to the connections and favors shallow structures with a low degree of branching. Finding a structure with minimal cost is NP-complete. We present a greedy polynomial-time algorithm that approximates good solutions incrementally by local evaluation of a heuristic...... function. We argue for a heuristic function based on four criteria: the number of enclosed connections, the number of components, the number of touched connections and the depth of the structure. We report on an application in the context of formal verification, where our algorithm serves as a preprocessor...

  4. Connectivity, flow and transport in network models of fractured media

    International Nuclear Information System (INIS)

    Robinson, P.C.

    1984-10-01

    In order to evaluate the safety of radioactive waste disposal underground it is important to understand the way in which radioactive material is transported through the rock to the surface. If the rock is fractured the usual models may not be applicable. In this work we look at three aspects of fracture networks: connectivity, flow and transport. These are studied numerically by generating fracture networks in a computer and modelling the processes which occur. Connectivity relates to percolation theory, and critical densities for fracture systems are found in two and three dimensions. The permeability of two-dimensional networks is studied. The way that permeability depends on fracture density, network size and spread of fracture length can be predicted using a cut lattice model. Transport through the fracture network by convection through the fractures and mixing at the intersections is studied. The Fickian dispersion equation does not describe the resulting hydrodynamic dispersion. Extensions to the techniques to three dimensions and to include other processes are discussed. (author)

  5. The hydro-mechanical modeling of the fractured media; Modelisation hydromecanique des milieux fractures

    Energy Technology Data Exchange (ETDEWEB)

    Kadiri, I

    2002-10-15

    The hydro-mechanical modeling of the fractured media is quite complex. Simplifications are necessary for the modeling of such media, but, not always justified, Only permeable fractures are often considered. The rest of the network is approximated by an equivalent continuous medium. Even if we suppose that this approach is validated, the hydraulic and mechanical properties of the fractures and of the continuous medium are seldom known. Calibrations are necessary for the determination of these properties. Until now, one does not know very well the nature of measurements which must be carried out in order to carry on a modeling in discontinuous medium, nor elements of enough robust validation for this kind of modeling. For a better understanding of the hydro-mechanical phenomena in fractured media, two different sites have been selected for the work. The first is the site of Grimsel in Switzerland in which an underground laboratory is located at approximately 400 m of depth. The FEBEX experiment aims at the in-situ study of the consecutive phenomena due to the installation of a heat source representative of radioactive waste in the last 17 meters of the FEBEX tunnel in the laboratory of Grimsel. Only, the modeling of the hydro-mechanical of the excavation was model. The modeling of the Febex enabled us to establish a methodology of calibration of the hydraulic properties in the discontinuous media. However, this kind of study on such complex sites does not make possible to answer all the questions which arise on the hydro-mechanical behavior of the fractured media. We thus carried out modeling on an other site, smaller than the fist one and more accessible. The experimental site of Coaraze, in the Maritime Alps, is mainly constituted of limestone and fractures. Then the variation of water pressure along fractures is governed by the opening/closure sequence of a water gate. Normal displacement as well as the pore pressure along these fractures are recorded, and then

  6. The Hierarchical Trend Model for property valuation and local price indices

    NARCIS (Netherlands)

    Francke, M.K.; Vos, G.A.

    2002-01-01

    This paper presents a hierarchical trend model (HTM) for selling prices of houses, addressing three main problems: the spatial and temporal dependence of selling prices and the dependency of price index changes on housing quality. In this model the general price trend, cluster-level price trends,

  7. Measuring Service Quality in Higher Education: Development of a Hierarchical Model (HESQUAL)

    Science.gov (United States)

    Teeroovengadum, Viraiyan; Kamalanabhan, T. J.; Seebaluck, Ashley Keshwar

    2016-01-01

    Purpose: This paper aims to develop and empirically test a hierarchical model for measuring service quality in higher education. Design/methodology/approach: The first phase of the study consisted of qualitative research methods and a comprehensive literature review, which allowed the development of a conceptual model comprising 53 service quality…

  8. Avoiding Boundary Estimates in Hierarchical Linear Models through Weakly Informative Priors

    Science.gov (United States)

    Chung, Yeojin; Rabe-Hesketh, Sophia; Gelman, Andrew; Dorie, Vincent; Liu, Jinchen

    2012-01-01

    Hierarchical or multilevel linear models are widely used for longitudinal or cross-sectional data on students nested in classes and schools, and are particularly important for estimating treatment effects in cluster-randomized trials, multi-site trials, and meta-analyses. The models can allow for variation in treatment effects, as well as…

  9. LiDAR based prediction of forest biomass using hierarchical models with spatially varying coefficients

    Science.gov (United States)

    Chad Babcock; Andrew O. Finley; John B. Bradford; Randy Kolka; Richard Birdsey; Michael G. Ryan

    2015-01-01

    Many studies and production inventory systems have shown the utility of coupling covariates derived from Light Detection and Ranging (LiDAR) data with forest variables measured on georeferenced inventory plots through regression models. The objective of this study was to propose and assess the use of a Bayesian hierarchical modeling framework that accommodates both...

  10. A Hierarchical Linear Model for Estimating Gender-Based Earnings Differentials.

    Science.gov (United States)

    Haberfield, Yitchak; Semyonov, Moshe; Addi, Audrey

    1998-01-01

    Estimates of gender earnings inequality in data from 116,431 Jewish workers were compared using a hierarchical linear model (HLM) and ordinary least squares model. The HLM allows estimation of the extent to which earnings inequality depends on occupational characteristics. (SK)

  11. Galactic chemical evolution in hierarchical formation models - I. Early-type galaxies in the local Universe

    NARCIS (Netherlands)

    Arrigoni, Matías; Trager, Scott C.; Somerville, Rachel S.; Gibson, Brad K.

    We study the metallicities and abundance ratios of early-type galaxies in cosmological semi-analytic models (SAMs) within the hierarchical galaxy formation paradigm. To achieve this we implemented a detailed galactic chemical evolution model and can now predict abundances of individual elements for

  12. Galactic chemical evolution in hierarchical formation models : I. Early-type galaxies in the local Universe

    NARCIS (Netherlands)

    Arrigoni, Matias; Trager, Scott C.; Somerville, Rachel S.; Gibson, Brad K.

    2010-01-01

    We study the metallicities and abundance ratios of early-type galaxies in cosmological semi-analytic models (SAMs) within the hierarchical galaxy formation paradigm. To achieve this we implemented a detailed galactic chemical evolution model and can now predict abundances of individual elements for

  13. Hierarchical Bayesian modeling of the space - time diffusion patterns of cholera epidemic in Kumasi, Ghana

    NARCIS (Netherlands)

    Osei, Frank B.; Osei, F.B.; Duker, Alfred A.; Stein, A.

    2011-01-01

    This study analyses the joint effects of the two transmission routes of cholera on the space-time diffusion dynamics. Statistical models are developed and presented to investigate the transmission network routes of cholera diffusion. A hierarchical Bayesian modelling approach is employed for a joint

  14. A Hybrid PO - Higher-Order Hierarchical MoM Formulation using Curvilinear Geometry Modeling

    DEFF Research Database (Denmark)

    Jørgensen, E.; Meincke, Peter; Breinbjerg, Olav

    2003-01-01

    which implies a very modest memory requirement. Nevertheless, the hierarchical feature of the basis functions maintains the ability to treat small geometrical details efficiently. In addition, the scatterer is modelled with higher-order curved patches which allows accurate modelling of curved surfaces...

  15. Soft tissue deformation using a Hierarchical Finite Element Model.

    Science.gov (United States)

    Faraci, Alessandro; Bello, Fernando; Darzi, Ara

    2004-01-01

    Simulating soft tissue deformation in real-time has become increasingly important in order to provide a realistic virtual environment for training surgical skills. Several methods have been proposed with the aim of rendering in real-time the mechanical and physiological behaviour of human organs, one of the most popular being Finite Element Method (FEM). In this paper we present a new approach to the solution of the FEM problem introducing the concept of parent and child mesh within the development of a hierarchical FEM. The online selection of the child mesh is presented with the purpose to adapt the mesh hierarchy in real-time. This permits further refinement of the child mesh increasing the detail of the deformation without slowing down the simulation and giving the possibility of integrating force feedback. The results presented demonstrate the application of our proposed framework using a desktop virtual reality (VR) system that incorporates stereo vision with integrated haptics co-location via a desktop Phantom force feedback device.

  16. Modeling CO2 Storage in Fractured Reservoirs: Fracture-Matrix Interactions of Free-Phase and Dissolved CO2

    Science.gov (United States)

    Oldenburg, C. M.; Zhou, Q.; Birkholzer, J. T.

    2017-12-01

    The injection of supercritical CO2 (scCO2) in fractured reservoirs has been conducted at several storage sites. However, no site-specific dual-continuum modeling for fractured reservoirs has been reported and modeling studies have generally underestimated the fracture-matrix interactions. We developed a conceptual model for enhanced CO2 storage to take into account global scCO2 migration in the fracture continuum, local storage of scCO2 and dissolved CO2 (dsCO2) in the matrix continuum, and driving forces for scCO2 invasion and dsCO2 diffusion from fractures. High-resolution discrete fracture-matrix models were developed for a column of idealized matrix blocks bounded by vertical and horizontal fractures and for a km-scale fractured reservoir. The column-scale simulation results show that equilibrium storage efficiency strongly depends on matrix entry capillary pressure and matrix-matrix connectivity while the time scale to reach equilibrium is sensitive to fracture spacing and matrix flow properties. The reservoir-scale modeling results shows that the preferential migration of scCO2 through fractures is coupled with bulk storage in the rock matrix that in turn retards the fracture scCO2 plume. We also developed unified-form diffusive flux equations to account for dsCO2 storage in brine-filled matrix blocks and found solubility trapping is significant in fractured reservoirs with low-permeability matrix.

  17. Transformation of renormalization groups in 2N-component fermion hierarchical model

    International Nuclear Information System (INIS)

    Stepanov, R.G.

    2006-01-01

    The 2N-component fermion model on the hierarchical lattice is studied. The explicit formulae for renormalization groups transformation in the space of coefficients setting the Grassmannian-significant density of the free measure are presented. The inverse transformation of the renormalization group is calculated. The definition of immovable points of renormalization groups is reduced to solving the set of algebraic equations. The interesting connection between renormalization group transformations in boson and fermion hierarchical models is found out. It is shown that one transformation is obtained from other one by the substitution of N on -N [ru

  18. Fuzzy hierarchical model for risk assessment principles, concepts, and practical applications

    CERN Document Server

    Chan, Hing Kai

    2013-01-01

    Risk management is often complicated by situational uncertainties and the subjective preferences of decision makers. Fuzzy Hierarchical Model for Risk Assessment introduces a fuzzy-based hierarchical approach to solve risk management problems considering both qualitative and quantitative criteria to tackle imprecise information.   This approach is illustrated through number of case studies using examples from the food, fashion and electronics sectors to cover a range of applications including supply chain management, green product design and green initiatives. These practical examples explore how this method can be adapted and fine tuned to fit other industries as well.   Supported by an extensive literature review, Fuzzy Hierarchical Model for Risk Assessment  comprehensively introduces a new method for project managers across all industries as well as researchers in risk management.

  19. Modeling Flow in Naturally Fractured Reservoirs : Effect of Fracture Aperture Distribution on Critical Sub-Network for Flow

    NARCIS (Netherlands)

    Gong, J.; Rossen, W.R.

    2014-01-01

    Fracture network connectivity and aperture (or conductivity) distribution are two crucial features controlling the flow behavior of fractured formations. The effect of connectivity on flow properties is well documented. We focus here on the influence of fracture aperture distribution. We model a

  20. Modeling flow and transport in fracture networks using graphs

    Science.gov (United States)

    Karra, S.; O'Malley, D.; Hyman, J. D.; Viswanathan, H. S.; Srinivasan, G.

    2018-03-01

    Fractures form the main pathways for flow in the subsurface within low-permeability rock. For this reason, accurately predicting flow and transport in fractured systems is vital for improving the performance of subsurface applications. Fracture sizes in these systems can range from millimeters to kilometers. Although modeling flow and transport using the discrete fracture network (DFN) approach is known to be more accurate due to incorporation of the detailed fracture network structure over continuum-based methods, capturing the flow and transport in such a wide range of scales is still computationally intractable. Furthermore, if one has to quantify uncertainty, hundreds of realizations of these DFN models have to be run. To reduce the computational burden, we solve flow and transport on a graph representation of a DFN. We study the accuracy of the graph approach by comparing breakthrough times and tracer particle statistical data between the graph-based and the high-fidelity DFN approaches, for fracture networks with varying number of fractures and degree of heterogeneity. Due to our recent developments in capabilities to perform DFN high-fidelity simulations on fracture networks with large number of fractures, we are in a unique position to perform such a comparison. We show that the graph approach shows a consistent bias with up to an order of magnitude slower breakthrough when compared to the DFN approach. We show that this is due to graph algorithm's underprediction of the pressure gradients across intersections on a given fracture, leading to slower tracer particle speeds between intersections and longer travel times. We present a bias correction methodology to the graph algorithm that reduces the discrepancy between the DFN and graph predictions. We show that with this bias correction, the graph algorithm predictions significantly improve and the results are very accurate. The good accuracy and the low computational cost, with O (104) times lower times than

  1. Experiments in Error Propagation within Hierarchal Combat Models

    Science.gov (United States)

    2015-09-01

    stochastic Lanchester campaign model that contains 18 Blue and 25 Red submarines. The outputs of the campaign models are analyzed statistically. The...sampled in a variety of ways, including just the mean, and used to calculate the attrition coefficients for a stochastic Lanchester campaign model...9 2. Lanchester Models .............................................................................10 III. SCENARIO AND MODEL DEVELOPMENT

  2. Measuring and Modeling Flow in Welded Fractured Tuffs

    International Nuclear Information System (INIS)

    R. Salve; C. Doughty; J.S. Wang

    2001-01-01

    We have carried out a series of in situ liquid-release experiments in conjunction with a numerical modeling study to examine the effect of the rock matrix on liquid flow and transport occurring primarily through the fracture network. Field experiments were conducted in the highly fractured Topopah Spring welded tuff at a site accessed from the Exploratory Studies Facility (ESFS), an underground laboratory in the unsaturated zone at Yucca Mountain, Nevada. During the experiment, wetting-front movement, flow-field evolution, and drainage of fracture flow paths were evaluated. Modeling was used to aid in experimental design, predict experimental results, and study the physical processes accompanying liquid flow through unsaturated fractured welded tuff. Field experiments and modeling suggest that it may not be sufficient to conceptualize the fractured tuff as consisting of a single network of high-permeability fractures embedded in a low-permeability matrix. The need to include a secondary fracture network is demonstrated by comparison to the liquid flow observed in the field

  3. INFOGRAPHIC MODELING OF THE HIERARCHICAL STRUCTURE OF THE MANAGEMENT SYSTEM EXPOSED TO AN INNOVATIVE CONFLICT

    Directory of Open Access Journals (Sweden)

    Chulkov Vitaliy Olegovich

    2012-12-01

    Full Text Available This article deals with the infographic modeling of hierarchical management systems exposed to innovative conflicts. The authors analyze the facts that serve as conflict drivers in the construction management environment. The reasons for innovative conflicts include changes in hierarchical structures of management systems, adjustment of workers to new management conditions, changes in the ideology, etc. Conflicts under consideration may involve contradictions between requests placed by customers and the legislation, any risks that may originate from the above contradiction, conflicts arising from any failure to comply with any accepted standards of conduct, etc. One of the main objectives of the theory of hierarchical structures is to develop a model capable of projecting potential innovative conflicts. Models described in the paper reflect dynamic changes in patterns of external impacts within the conflict area. The simplest model element is a monad, or an indivisible set of characteristics of participants at the pre-set level. Interaction between two monads forms a diad. Modeling of situations that involve a different number of monads, diads, resources and impacts can improve methods used to control and manage hierarchical structures in the construction industry. However, in the absence of any mathematical models employed to simulate conflict-related events, processes and situations, any research into, projection and management of interpersonal and group-to-group conflicts are to be performed in the legal environment

  4. Adaptive Multiscale Modeling of Geochemical Impacts on Fracture Evolution

    Science.gov (United States)

    Molins, S.; Trebotich, D.; Steefel, C. I.; Deng, H.

    2016-12-01

    Understanding fracture evolution is essential for many subsurface energy applications, including subsurface storage, shale gas production, fracking, CO2 sequestration, and geothermal energy extraction. Geochemical processes in particular play a significant role in the evolution of fractures through dissolution-driven widening, fines migration, and/or fracture sealing due to precipitation. One obstacle to understanding and exploiting geochemical fracture evolution is that it is a multiscale process. However, current geochemical modeling of fractures cannot capture this multi-scale nature of geochemical and mechanical impacts on fracture evolution, and is limited to either a continuum or pore-scale representation. Conventional continuum-scale models treat fractures as preferential flow paths, with their permeability evolving as a function (often, a cubic law) of the fracture aperture. This approach has the limitation that it oversimplifies flow within the fracture in its omission of pore scale effects while also assuming well-mixed conditions. More recently, pore-scale models along with advanced characterization techniques have allowed for accurate simulations of flow and reactive transport within the pore space (Molins et al., 2014, 2015). However, these models, even with high performance computing, are currently limited in their ability to treat tractable domain sizes (Steefel et al., 2013). Thus, there is a critical need to develop an adaptive modeling capability that can account for separate properties and processes, emergent and otherwise, in the fracture and the rock matrix at different spatial scales. Here we present an adaptive modeling capability that treats geochemical impacts on fracture evolution within a single multiscale framework. Model development makes use of the high performance simulation capability, Chombo-Crunch, leveraged by high resolution characterization and experiments. The modeling framework is based on the adaptive capability in Chombo

  5. Radon transport in fractured soil. Laboratory experiments and modelling

    International Nuclear Information System (INIS)

    Hoff, A.

    1997-10-01

    Radon (Rn-222) transport in fractured soil has been investigated by laboratory experiments and by modelling. Radon transport experiments have been performed with two sand columns (homogeneous and inhomogeneous) and one undisturbed clayey till column containing a net of preferential flow paths (root holes). A numerical model (the finite-element model FRACTRAN) and an analytic model (a pinhole model) have been applied in simulations if soil gas and radon transport in fractured soil. Experiments and model calculations are included in a discussion of radon entry rates into houses placed on fractured soil. The main conclusion is, that fractures does not in general alter transport of internally generated radon out of soil, when the pressure and flow conditions in the soil is comparable to the conditions prevailing under a house. This indicates the important result, that fractures in soil have no impact on radon entry into a house beyond that of an increased gas permeability, but a more thorough investigation of this subject is needed. Only in the case where the soil is exposed to large pressure gradients, relative to gradients induced by a house, may it be possible to observe effects of radon exchange between fractures and matrix. (au) 52 tabs., 60 ill., 5 refs

  6. Radon transport in fractured soil. Laboratory experiments and modelling

    Energy Technology Data Exchange (ETDEWEB)

    Hoff, A

    1997-10-01

    Radon (Rn-222) transport in fractured soil has been investigated by laboratory experiments and by modelling. Radon transport experiments have been performed with two sand columns (homogeneous and inhomogeneous) and one undisturbed clayey till column containing a net of preferential flow paths (root holes). A numerical model (the finite-element model FRACTRAN) and an analytic model (a pinhole model) have been applied in simulations if soil gas and radon transport in fractured soil. Experiments and model calculations are included in a discussion of radon entry rates into houses placed on fractured soil. The main conclusion is, that fractures does not in general alter transport of internally generated radon out of soil, when the pressure and flow conditions in the soil is comparable to the conditions prevailing under a house. This indicates the important result, that fractures in soil have no impact on radon entry into a house beyond that of an increased gas permeability, but a more thorough investigation of this subject is needed. Only in the case where the soil is exposed to large pressure gradients, relative to gradients induced by a house, may it be possible to observe effects of radon exchange between fractures and matrix. (au) 52 tabs., 60 ill., 5 refs.

  7. Modelling tracer transport in fractured rock at Stripa

    International Nuclear Information System (INIS)

    Herbert, A.

    1992-01-01

    We present the results of a modelling study, making predictions for tracer transport experiments carried out within the H-zone feature in the Stripa mine. We use a direct fracture network approach to represent the system of interconnected flow-conducting fractures comprising this zone. It is a highly fractured granite, and our fracture-network models include up to 60000 fractures. We have had to develop efficient algorithms to calculate the flow and transport through these networks; these techniques are described and justified. The first stage of modelling addressed two saline injection experiments. The results of these were known to us and so in addition to 'predicting' the results of these experiments, we used them to calibrate a flow model of the experimental site. This model was then used to make true 'blind' predictions for a set of tracer experiments carried out in the natural head-field, caused by an open drift. Where our flow model was good, our predictions were found to be very accurate, explaining the dispersion in the tracer breakthrough in terms of the fracture network geometry. Discrepancies for experiments in less well characterised regions of the H-zone are presented, and we suggest that the errors in these predictions are a consequence of the inaccuracies of the flow-field. We have demonstrated the use of large-scale fracture network modelling. It has proved very successful, and made very accurate predictions of field experiments carried out at the Stripa mine. The measured dispersion of tracers can be accounted for by the geometry of the fracture network flow system. (14 refs.) (au)

  8. Slug flow model for infiltration into fractured porous media

    International Nuclear Information System (INIS)

    Martinez, M.J.

    1999-01-01

    A model for transient infiltration into a periodically fractured porous layer is presented. The fracture is treated as a permeable-walled slot and the moisture distribution is in the form of a slug being an advancing meniscus. The wicking of moisture from the fracture to the unsaturated porous matrix is a nonlinear diffusion process and is approximately by self-similar solutions. The resulting model is a nonlinear Volterra integral equation with a weakly singular kernel. Numerical analysis provides solutions over a wide range of the parameter space and reveals the asymptotic forms of the penetration of this slug in terms of dimensionless variables arising in the model. The numerical solutions corroborate asymptotic results given earlier by Nitao and Buscheck (1991), and by Martinez (1988). Some implications for the transport of liquid in fractured rock are discussed

  9. Application of hierarchical genetic models to Raven and WAIS subtests: a Dutch twin study.

    Science.gov (United States)

    Rijsdijk, Frühling V; Vernon, P A; Boomsma, Dorret I

    2002-05-01

    Hierarchical models of intelligence are highly informative and widely accepted. Application of these models to twin data, however, is sparse. This paper addresses the question of how a genetic hierarchical model fits the Wechsler Adult Intelligence Scale (WAIS) subtests and the Raven Standard Progressive test score, collected in 194 18-year-old Dutch twin pairs. We investigated whether first-order group factors possess genetic and environmental variance independent of the higher-order general factor and whether the hierarchical structure is significant for all sources of variance. A hierarchical model with the 3 Cohen group-factors (verbal comprehension, perceptual organisation and freedom-from-distractibility) and a higher-order g factor showed the best fit to the phenotypic data and to additive genetic influences (A), whereas the unique environmental source of variance (E) could be modeled by a single general factor and specifics. There was no evidence for common environmental influences. The covariation among the WAIS group factors and the covariation between the group factors and the Raven is predominantly influenced by a second-order genetic factor and strongly support the notion of a biological basis of g.

  10. A Hierarchical Bayesian Model to Predict Self-Thinning Line for Chinese Fir in Southern China.

    Directory of Open Access Journals (Sweden)

    Xiongqing Zhang

    Full Text Available Self-thinning is a dynamic equilibrium between forest growth and mortality at full site occupancy. Parameters of the self-thinning lines are often confounded by differences across various stand and site conditions. For overcoming the problem of hierarchical and repeated measures, we used hierarchical Bayesian method to estimate the self-thinning line. The results showed that the self-thinning line for Chinese fir (Cunninghamia lanceolata (Lamb.Hook. plantations was not sensitive to the initial planting density. The uncertainty of model predictions was mostly due to within-subject variability. The simulation precision of hierarchical Bayesian method was better than that of stochastic frontier function (SFF. Hierarchical Bayesian method provided a reasonable explanation of the impact of other variables (site quality, soil type, aspect, etc. on self-thinning line, which gave us the posterior distribution of parameters of self-thinning line. The research of self-thinning relationship could be benefit from the use of hierarchical Bayesian method.

  11. Fictitious Crack Model of Concrete Fracture

    DEFF Research Database (Denmark)

    Brincker, Rune; Dahl, H.

    1989-01-01

    The substructure method introduced by Petersson is reformulated for the three-point bending specimen in order to obtain complete load-displacement relations without significant truncation. The problem of instability caused by the linearization of the softening in the fracture zone is discussed, a...

  12. Groundwater degassing in fractured rock: Modelling and data comparison

    Energy Technology Data Exchange (ETDEWEB)

    Jarsjoe, J.; Destouni, G. [Royal Inst. of Tech., Stockholm (Sweden). Water Resources Engineering

    1998-11-01

    Dissolved gas may be released from deep groundwater in the vicinity of open boreholes and drifts, where the water pressures are relatively low. Degassing of groundwater may influence observations of hydraulic conditions made in drifts, interpretation of experiments performed close to drifts, and buffer mass and backfill performance, particularly during emplacement and repository closure. Under certain conditions, considerable fracture inflow and transmissivity reductions have been observed during degassing experiments in the field and in the laboratory; such reductions affect the outcome and interpretation of both hydraulic and tracer tests. We develop models for the estimation of the resulting degree of fracture gas saturation and the associated transmissivity reduction due to groundwater degassing in fractured rock. Derived expressions for bubble trapping probability show that fracture aperture variability and correlation length influence the conditions for capillary bubble trapping and gas accumulation. The laboratory observations of bubble trapping in an Aespoe fracture replica are consistent with the prediction of a relatively high probability of bubble trapping in this fracture. The prediction was based on the measured aperture distribution of the Aespoe fracture and the applied hydraulic gradient. Results also show that the conceptualisation of gas and water occupancy in a fracture greatly influences model predictions of gas saturation and relative transmissivity. Images from laboratory degassing experiments indicate that tight apertures are completely filled with water, whereas both gas and water exist in wider apertures under degassing conditions; implementation of this relation in our model resulted in the best agreement between predictions and laboratory observations. Model predictions for conditions similar to those prevailing in field for single fractures at great depths indicate that degassing effects in boreholes should generally be small, unless the

  13. From Playability to a Hierarchical Game Usability Model

    OpenAIRE

    Nacke, Lennart E.

    2010-01-01

    This paper presents a brief review of current game usability models. This leads to the conception of a high-level game development-centered usability model that integrates current usability approaches in game industry and game research.

  14. Evaluation of Validity and Reliability for Hierarchical Scales Using Latent Variable Modeling

    Science.gov (United States)

    Raykov, Tenko; Marcoulides, George A.

    2012-01-01

    A latent variable modeling method is outlined, which accomplishes estimation of criterion validity and reliability for a multicomponent measuring instrument with hierarchical structure. The approach provides point and interval estimates for the scale criterion validity and reliability coefficients, and can also be used for testing composite or…

  15. Predicting Examination Performance Using an Expanded Integrated Hierarchical Model of Test Emotions and Achievement Goals

    Science.gov (United States)

    Putwain, Dave; Deveney, Carolyn

    2009-01-01

    The aim of this study was to examine an expanded integrative hierarchical model of test emotions and achievement goal orientations in predicting the examination performance of undergraduate students. Achievement goals were theorised as mediating the relationship between test emotions and performance. 120 undergraduate students completed…

  16. Using Hierarchical Linear Modelling to Examine Factors Predicting English Language Students' Reading Achievement

    Science.gov (United States)

    Fung, Karen; ElAtia, Samira

    2015-01-01

    Using Hierarchical Linear Modelling (HLM), this study aimed to identify factors such as ESL/ELL/EAL status that would predict students' reading performance in an English language arts exam taken across Canada. Using data from the 2007 administration of the Pan-Canadian Assessment Program (PCAP) along with the accompanying surveys for students and…

  17. The Hierarchical Factor Model of ADHD: Invariant across Age and National Groupings?

    Science.gov (United States)

    Toplak, Maggie E.; Sorge, Geoff B.; Flora, David B.; Chen, Wai; Banaschewski, Tobias; Buitelaar, Jan; Ebstein, Richard; Eisenberg, Jacques; Franke, Barbara; Gill, Michael; Miranda, Ana; Oades, Robert D.; Roeyers, Herbert; Rothenberger, Aribert; Sergeant, Joseph; Sonuga-Barke, Edmund; Steinhausen, Hans-Christoph; Thompson, Margaret; Tannock, Rosemary; Asherson, Philip; Faraone, Stephen V.

    2012-01-01

    Objective: To examine the factor structure of attention-deficit/hyperactivity disorder (ADHD) in a clinical sample of 1,373 children and adolescents with ADHD and their 1,772 unselected siblings recruited from different countries across a large age range. Hierarchical and correlated factor analytic models were compared separately in the ADHD and…

  18. Symptom structure of PTSD: support for a hierarchical model separating core PTSD symptoms from dysphoria

    NARCIS (Netherlands)

    Rademaker, Arthur R.; van Minnen, Agnes; Ebberink, Freek; van Zuiden, Mirjam; Hagenaars, Muriel A.; Geuze, Elbert

    2012-01-01

    As of yet, no collective agreement has been reached regarding the precise factor structure of posttraumatic stress disorder (PTSD). Several alternative factor-models have been proposed in the last decades. The current study examined the fit of a hierarchical adaptation of the Simms et al. (2002)

  19. Hierarchical models for informing general biomass equations with felled tree data

    Science.gov (United States)

    Brian J. Clough; Matthew B. Russell; Christopher W. Woodall; Grant M. Domke; Philip J. Radtke

    2015-01-01

    We present a hierarchical framework that uses a large multispecies felled tree database to inform a set of general models for predicting tree foliage biomass, with accompanying uncertainty, within the FIA database. Results suggest significant prediction uncertainty for individual trees and reveal higher errors when predicting foliage biomass for larger trees and for...

  20. Perfect observables for the hierarchical non-linear O(N)-invariant σ-model

    International Nuclear Information System (INIS)

    Wieczerkowski, C.; Xylander, Y.

    1995-05-01

    We compute moving eigenvalues and the eigenvectors of the linear renormalization group transformation for observables along the renormalized trajectory of the hierarchical non-linear O(N)-invariant σ-model by means of perturbation theory in the running coupling constant. Moving eigenvectors are defined as solutions to a Callan-Symanzik type equation. (orig.)

  1. Intraclass Correlation Coefficients in Hierarchical Designs: Evaluation Using Latent Variable Modeling

    Science.gov (United States)

    Raykov, Tenko

    2011-01-01

    Interval estimation of intraclass correlation coefficients in hierarchical designs is discussed within a latent variable modeling framework. A method accomplishing this aim is outlined, which is applicable in two-level studies where participants (or generally lower-order units) are clustered within higher-order units. The procedure can also be…

  2. Mass transport in fracture media: impact of the random function model assumed for fractures conductivity

    International Nuclear Information System (INIS)

    Capilla, J. E.; Rodrigo, J.; Gomez Hernandez, J. J.

    2003-01-01

    Characterizing the uncertainty of flow and mass transport models requires the definition of stochastic models to describe hydrodynamic parameters. Porosity and hydraulic conductivity (K) are two of these parameters that exhibit a high degree of spatial variability. K is usually the parameter whose variability influence to a more extended degree solutes movement. In fracture media, it is critical to properly characterize K in the most altered zones where flow and solutes migration tends to be concentrated. However, K measurements use to be scarce and sparse. This fact calls to consider stochastic models that allow quantifying the uncertainty of flow and mass transport predictions. This paper presents a convective transport problem solved in a 3D block of fractured crystalline rock. the case study is defined based on data from a real geological formation. As the scarcity of K data in fractures does not allow supporting classical multi Gaussian assumptions for K in fractures, the non multi Gaussian hypothesis has been explored, comparing mass transport results for alternative Gaussian and non-Gaussian assumptions. The latter hypothesis allows reproducing high spatial connectivity for extreme values of K. This feature is present in nature, might lead to reproduce faster solute pathways, and therefore should be modeled in order to obtain reasonably safe prediction of contaminants migration in a geological formation. The results obtained for the two alternative hypotheses show a remarkable impact of the K random function model in solutes movement. (Author) 9 refs

  3. Relating Cohesive Zone Model to Linear Elastic Fracture Mechanics

    Science.gov (United States)

    Wang, John T.

    2010-01-01

    The conditions required for a cohesive zone model (CZM) to predict a failure load of a cracked structure similar to that obtained by a linear elastic fracture mechanics (LEFM) analysis are investigated in this paper. This study clarifies why many different phenomenological cohesive laws can produce similar fracture predictions. Analytical results for five cohesive zone models are obtained, using five different cohesive laws that have the same cohesive work rate (CWR-area under the traction-separation curve) but different maximum tractions. The effect of the maximum traction on the predicted cohesive zone length and the remote applied load at fracture is presented. Similar to the small scale yielding condition for an LEFM analysis to be valid. the cohesive zone length also needs to be much smaller than the crack length. This is a necessary condition for a CZM to obtain a fracture prediction equivalent to an LEFM result.

  4. Modeling biogechemical reactive transport in a fracture zone

    Energy Technology Data Exchange (ETDEWEB)

    Molinero, Jorge; Samper, Javier; Yang, Chan Bing, and Zhang, Guoxiang; Guoxiang, Zhang

    2005-01-14

    A coupled model of groundwater flow, reactive solute transport and microbial processes for a fracture zone of the Aspo site at Sweden is presented. This is the model of the so-called Redox Zone Experiment aimed at evaluating the effects of tunnel construction on the geochemical conditions prevailing in a fracture granite. It is found that a model accounting for microbially-mediated geochemical processes is able to reproduce the unexpected measured increasing trends of dissolved sulfate and bicarbonate. The model is also useful for testing hypotheses regarding the role of microbial processes and evaluating the sensitivity of model results to changes in biochemical parameters.

  5. Modeling biogeochemical reactive transport in a fracture zone

    International Nuclear Information System (INIS)

    Molinero, Jorge; Samper, Javier; Yang, Chan Bing; Zhang, Guoxiang; Guoxiang, Zhang

    2005-01-01

    A coupled model of groundwater flow, reactive solute transport and microbial processes for a fracture zone of the Aspo site at Sweden is presented. This is the model of the so-called Redox Zone Experiment aimed at evaluating the effects of tunnel construction on the geochemical conditions prevailing in a fracture granite. It is found that a model accounting for microbially-mediated geochemical processes is able to reproduce the unexpected measured increasing trends of dissolved sulfate and bicarbonate. The model is also useful for testing hypotheses regarding the role of microbial processes and evaluating the sensitivity of model results to changes in biochemical parameters

  6. An Analysis of Turkey's PISA 2015 Results Using Two-Level Hierarchical Linear Modelling

    Science.gov (United States)

    Atas, Dogu; Karadag, Özge

    2017-01-01

    In the field of education, most of the data collected are multi-level structured. Cities, city based schools, school based classes and finally students in the classrooms constitute a hierarchical structure. Hierarchical linear models give more accurate results compared to standard models when the data set has a structure going far as individuals,…

  7. Investigating Some Technical Issues on Cohesive Zone Modeling of Fracture

    Science.gov (United States)

    Wang, John T.

    2011-01-01

    This study investigates some technical issues related to the use of cohesive zone models (CZMs) in modeling fracture processes. These issues include: why cohesive laws of different shapes can produce similar fracture predictions; under what conditions CZM predictions have a high degree of agreement with linear elastic fracture mechanics (LEFM) analysis results; when the shape of cohesive laws becomes important in the fracture predictions; and why the opening profile along the cohesive zone length needs to be accurately predicted. Two cohesive models were used in this study to address these technical issues. They are the linear softening cohesive model and the Dugdale perfectly plastic cohesive model. Each cohesive model constitutes five cohesive laws of different maximum tractions. All cohesive laws have the same cohesive work rate (CWR) which is defined by the area under the traction-separation curve. The effects of the maximum traction on the cohesive zone length and the critical remote applied stress are investigated for both models. For a CZM to predict a fracture load similar to that obtained by an LEFM analysis, the cohesive zone length needs to be much smaller than the crack length, which reflects the small scale yielding condition requirement for LEFM analysis to be valid. For large-scale cohesive zone cases, the predicted critical remote applied stresses depend on the shape of cohesive models used and can significantly deviate from LEFM results. Furthermore, this study also reveals the importance of accurately predicting the cohesive zone profile in determining the critical remote applied load.

  8. Technical Note: Probabilistically constraining proxy age–depth models within a Bayesian hierarchical reconstruction model

    Directory of Open Access Journals (Sweden)

    J. P. Werner

    2015-03-01

    Full Text Available Reconstructions of the late-Holocene climate rely heavily upon proxies that are assumed to be accurately dated by layer counting, such as measurements of tree rings, ice cores, and varved lake sediments. Considerable advances could be achieved if time-uncertain proxies were able to be included within these multiproxy reconstructions, and if time uncertainties were recognized and correctly modeled for proxies commonly treated as free of age model errors. Current approaches for accounting for time uncertainty are generally limited to repeating the reconstruction using each one of an ensemble of age models, thereby inflating the final estimated uncertainty – in effect, each possible age model is given equal weighting. Uncertainties can be reduced by exploiting the inferred space–time covariance structure of the climate to re-weight the possible age models. Here, we demonstrate how Bayesian hierarchical climate reconstruction models can be augmented to account for time-uncertain proxies. Critically, although a priori all age models are given equal probability of being correct, the probabilities associated with the age models are formally updated within the Bayesian framework, thereby reducing uncertainties. Numerical experiments show that updating the age model probabilities decreases uncertainty in the resulting reconstructions, as compared with the current de facto standard of sampling over all age models, provided there is sufficient information from other data sources in the spatial region of the time-uncertain proxy. This approach can readily be generalized to non-layer-counted proxies, such as those derived from marine sediments.

  9. Sensitivity Analysis of the Bone Fracture Risk Model

    Science.gov (United States)

    Lewandowski, Beth; Myers, Jerry; Sibonga, Jean Diane

    2017-01-01

    Introduction: The probability of bone fracture during and after spaceflight is quantified to aid in mission planning, to determine required astronaut fitness standards and training requirements and to inform countermeasure research and design. Probability is quantified with a probabilistic modeling approach where distributions of model parameter values, instead of single deterministic values, capture the parameter variability within the astronaut population and fracture predictions are probability distributions with a mean value and an associated uncertainty. Because of this uncertainty, the model in its current state cannot discern an effect of countermeasures on fracture probability, for example between use and non-use of bisphosphonates or between spaceflight exercise performed with the Advanced Resistive Exercise Device (ARED) or on devices prior to installation of ARED on the International Space Station. This is thought to be due to the inability to measure key contributors to bone strength, for example, geometry and volumetric distributions of bone mass, with areal bone mineral density (BMD) measurement techniques. To further the applicability of model, we performed a parameter sensitivity study aimed at identifying those parameter uncertainties that most effect the model forecasts in order to determine what areas of the model needed enhancements for reducing uncertainty. Methods: The bone fracture risk model (BFxRM), originally published in (Nelson et al) is a probabilistic model that can assess the risk of astronaut bone fracture. This is accomplished by utilizing biomechanical models to assess the applied loads; utilizing models of spaceflight BMD loss in at-risk skeletal locations; quantifying bone strength through a relationship between areal BMD and bone failure load; and relating fracture risk index (FRI), the ratio of applied load to bone strength, to fracture probability. There are many factors associated with these calculations including

  10. A hierarchical causal modeling for large industrial plants supervision

    International Nuclear Information System (INIS)

    Dziopa, P.; Leyval, L.

    1994-01-01

    A supervision system has to analyse the process current state and the way it will evolve after a modification of the inputs or disturbance. It is proposed to base this analysis on a hierarchy of models, witch differ by the number of involved variables and the abstraction level used to describe their temporal evolution. In a first step, special attention is paid to causal models building, from the most abstract one. Once the hierarchy of models has been build, the most detailed model parameters are estimated. Several models of different abstraction levels can be used for on line prediction. These methods have been applied to a nuclear reprocessing plant. The abstraction level could be chosen on line by the operator. Moreover when an abnormal process behaviour is detected a more detailed model is automatically triggered in order to focus the operator attention on the suspected subsystem. (authors). 11 refs., 11 figs

  11. Sparse Event Modeling with Hierarchical Bayesian Kernel Methods

    Science.gov (United States)

    2016-01-05

    SECURITY CLASSIFICATION OF: The research objective of this proposal was to develop a predictive Bayesian kernel approach to model count data based on...several predictive variables. Such an approach, which we refer to as the Poisson Bayesian kernel model, is able to model the rate of occurrence of... kernel methods made use of: (i) the Bayesian property of improving predictive accuracy as data are dynamically obtained, and (ii) the kernel function

  12. Hierarchical modelling of line commutated power systems used in particle accelerators using Saber

    International Nuclear Information System (INIS)

    Reimund, J.A.

    1993-01-01

    This paper discusses the use of hierarchical simulation models using the program Saber trademark for the prediction of magnet ripple currents generated by the power supply/output filter combination. Modeling of an entire power system connected to output filters and particle accelerator ring magnets will be presented. Special emphasis is made on the modeling of power source imbalances caused by transformer impedance imbalances and utility variances. The affect that these imbalances have on the harmonic content of ripple current is also investigated

  13. A test of the hierarchical model of litter decomposition

    DEFF Research Database (Denmark)

    Bradford, Mark A.; Veen, G. F.; Bonis, Anne

    2017-01-01

    Our basic understanding of plant litter decomposition informs the assumptions underlying widely applied soil biogeochemical models, including those embedded in Earth system models. Confidence in projected carbon cycle-climate feedbacks therefore depends on accurate knowledge about the controls...... regulating the rate at which plant biomass is decomposed into products such as CO2. Here we test underlying assumptions of the dominant conceptual model of litter decomposition. The model posits that a primary control on the rate of decomposition at regional to global scales is climate (temperature...

  14. A Multiscale Time-Splitting Discrete Fracture Model of Nanoparticles Transport in Fractured Porous Media

    KAUST Repository

    El-Amin, Mohamed F.; Kou, Jisheng; Sun, Shuyu

    2017-01-01

    Recently, applications of nanoparticles have been considered in many branches of petroleum engineering, especially, enhanced oil recovery. The current paper is devoted to investigate the problem of nanoparticles transport in fractured porous media, numerically. We employed the discrete-fracture model (DFM) to represent the flow and transport in the fractured formations. The system of the governing equations consists of the mass conservation law, Darcy's law, nanoparticles concentration in water, deposited nanoparticles concentration on the pore-wall, and entrapped nanoparticles concentration in the pore-throat. The variation of porosity and permeability due to the nanoparticles deposition/entrapment on/in the pores is also considered. We employ the multiscale time-splitting strategy to control different time-step sizes for different physics, such as pressure and concentration. The cell-centered finite difference (CCFD) method is used for the spatial discretization. Numerical examples are provided to demonstrate the efficiency of the proposed multiscale time splitting approach.

  15. A Multiscale Time-Splitting Discrete Fracture Model of Nanoparticles Transport in Fractured Porous Media

    KAUST Repository

    El-Amin, Mohamed F.

    2017-06-06

    Recently, applications of nanoparticles have been considered in many branches of petroleum engineering, especially, enhanced oil recovery. The current paper is devoted to investigate the problem of nanoparticles transport in fractured porous media, numerically. We employed the discrete-fracture model (DFM) to represent the flow and transport in the fractured formations. The system of the governing equations consists of the mass conservation law, Darcy\\'s law, nanoparticles concentration in water, deposited nanoparticles concentration on the pore-wall, and entrapped nanoparticles concentration in the pore-throat. The variation of porosity and permeability due to the nanoparticles deposition/entrapment on/in the pores is also considered. We employ the multiscale time-splitting strategy to control different time-step sizes for different physics, such as pressure and concentration. The cell-centered finite difference (CCFD) method is used for the spatial discretization. Numerical examples are provided to demonstrate the efficiency of the proposed multiscale time splitting approach.

  16. Simulating individual-based models of epidemics in hierarchical networks

    NARCIS (Netherlands)

    Quax, R.; Bader, D.A.; Sloot, P.M.A.

    2009-01-01

    Current mathematical modeling methods for the spreading of infectious diseases are too simplified and do not scale well. We present the Simulator of Epidemic Evolution in Complex Networks (SEECN), an efficient simulator of detailed individual-based models by parameterizing separate dynamics

  17. A three-component, hierarchical model of executive attention

    OpenAIRE

    Whittle, Sarah; Pantelis, Christos; Testa, Renee; Tiego, Jeggan; Bellgrove, Mark

    2017-01-01

    Executive attention refers to the goal-directed control of attention. Existing models of executive attention distinguish between three correlated, but empirically dissociable, factors related to selectively attending to task-relevant stimuli (Selective Attention), inhibiting task-irrelevant responses (Response Inhibition), and actively maintaining goal-relevant information (Working Memory Capacity). In these models, Selective Attention and Response Inhibition are moderately strongly correlate...

  18. An open-population hierarchical distance sampling model

    Science.gov (United States)

    Sollmann, Rachel; Beth Gardner,; Richard B Chandler,; Royle, J. Andrew; T Scott Sillett,

    2015-01-01

    Modeling population dynamics while accounting for imperfect detection is essential to monitoring programs. Distance sampling allows estimating population size while accounting for imperfect detection, but existing methods do not allow for direct estimation of demographic parameters. We develop a model that uses temporal correlation in abundance arising from underlying population dynamics to estimate demographic parameters from repeated distance sampling surveys. Using a simulation study motivated by designing a monitoring program for island scrub-jays (Aphelocoma insularis), we investigated the power of this model to detect population trends. We generated temporally autocorrelated abundance and distance sampling data over six surveys, using population rates of change of 0.95 and 0.90. We fit the data generating Markovian model and a mis-specified model with a log-linear time effect on abundance, and derived post hoc trend estimates from a model estimating abundance for each survey separately. We performed these analyses for varying number of survey points. Power to detect population changes was consistently greater under the Markov model than under the alternatives, particularly for reduced numbers of survey points. The model can readily be extended to more complex demographic processes than considered in our simulations. This novel framework can be widely adopted for wildlife population monitoring.

  19. An open-population hierarchical distance sampling model.

    Science.gov (United States)

    Sollmann, Rahel; Gardner, Beth; Chandler, Richard B; Royle, J Andrew; Sillett, T Scott

    2015-02-01

    Modeling population dynamics while accounting for imperfect detection is essential to monitoring programs. Distance sampling allows estimating population size while accounting for imperfect detection, but existing methods do not allow for estimation of demographic parameters. We develop a model that uses temporal correlation in abundance arising from underlying population dynamics to estimate demographic parameters from repeated distance sampling surveys. Using a simulation study motivated by designing a monitoring program for Island Scrub-Jays (Aphelocoma insularis), we investigated the power of this model to detect population trends. We generated temporally autocorrelated abundance and distance sampling data over six surveys, using population rates of change of 0.95 and 0.90. We fit the data generating Markovian model and a mis-specified model with a log-linear time effect on abundance, and derived post hoc trend estimates from a model estimating abundance for each survey separately. We performed these analyses for varying numbers of survey points. Power to detect population changes was consistently greater under the Markov model than under the alternatives, particularly for reduced numbers of survey points. The model can readily be extended to more complex demographic processes than considered in our simulations. This novel framework can be widely adopted for wildlife population monitoring.

  20. Multi-Scale Modelling of Deformation and Fracture in a Biomimetic Apatite-Protein Composite: Molecular-Scale Processes Lead to Resilience at the μm-Scale.

    Directory of Open Access Journals (Sweden)

    Dirk Zahn

    Full Text Available Fracture mechanisms of an enamel-like hydroxyapatite-collagen composite model are elaborated by means of molecular and coarse-grained dynamics simulation. Using fully atomistic models, we uncover molecular-scale plastic deformation and fracture processes initiated at the organic-inorganic interface. Furthermore, coarse-grained models are developed to investigate fracture patterns at the μm-scale. At the meso-scale, micro-fractures are shown to reduce local stress and thus prevent material failure after loading beyond the elastic limit. On the basis of our multi-scale simulation approach, we provide a molecular scale rationalization of this phenomenon, which seems key to the resilience of hierarchical biominerals, including teeth and bone.

  1. Comparing the performance of flat and hierarchical Habitat/Land-Cover classification models in a NATURA 2000 site

    Science.gov (United States)

    Gavish, Yoni; O'Connell, Jerome; Marsh, Charles J.; Tarantino, Cristina; Blonda, Palma; Tomaselli, Valeria; Kunin, William E.

    2018-02-01

    The increasing need for high quality Habitat/Land-Cover (H/LC) maps has triggered considerable research into novel machine-learning based classification models. In many cases, H/LC classes follow pre-defined hierarchical classification schemes (e.g., CORINE), in which fine H/LC categories are thematically nested within more general categories. However, none of the existing machine-learning algorithms account for this pre-defined hierarchical structure. Here we introduce a novel Random Forest (RF) based application of hierarchical classification, which fits a separate local classification model in every branching point of the thematic tree, and then integrates all the different local models to a single global prediction. We applied the hierarchal RF approach in a NATURA 2000 site in Italy, using two land-cover (CORINE, FAO-LCCS) and one habitat classification scheme (EUNIS) that differ from one another in the shape of the class hierarchy. For all 3 classification schemes, both the hierarchical model and a flat model alternative provided accurate predictions, with kappa values mostly above 0.9 (despite using only 2.2-3.2% of the study area as training cells). The flat approach slightly outperformed the hierarchical models when the hierarchy was relatively simple, while the hierarchical model worked better under more complex thematic hierarchies. Most misclassifications came from habitat pairs that are thematically distant yet spectrally similar. In 2 out of 3 classification schemes, the additional constraints of the hierarchical model resulted with fewer such serious misclassifications relative to the flat model. The hierarchical model also provided valuable information on variable importance which can shed light into "black-box" based machine learning algorithms like RF. We suggest various ways by which hierarchical classification models can increase the accuracy and interpretability of H/LC classification maps.

  2. Numerical simulation on ferrofluid flow in fractured porous media based on discrete-fracture model

    Science.gov (United States)

    Huang, Tao; Yao, Jun; Huang, Zhaoqin; Yin, Xiaolong; Xie, Haojun; Zhang, Jianguang

    2017-06-01

    Water flooding is an efficient approach to maintain reservoir pressure and has been widely used to enhance oil recovery. However, preferential water pathways such as fractures can significantly decrease the sweep efficiency. Therefore, the utilization ratio of injected water is seriously affected. How to develop new flooding technology to further improve the oil recovery in this situation is a pressing problem. For the past few years, controllable ferrofluid has caused the extensive concern in oil industry as a new functional material. In the presence of a gradient in the magnetic field strength, a magnetic body force is produced on the ferrofluid so that the attractive magnetic forces allow the ferrofluid to be manipulated to flow in any desired direction through the control of the external magnetic field. In view of these properties, the potential application of using the ferrofluid as a new kind of displacing fluid for flooding in fractured porous media is been studied in this paper for the first time. Considering the physical process of the mobilization of ferrofluid through porous media by arrangement of strong external magnetic fields, the magnetic body force was introduced into the Darcy equation and deals with fractures based on the discrete-fracture model. The fully implicit finite volume method is used to solve mathematical model and the validity and accuracy of numerical simulation, which is demonstrated through an experiment with ferrofluid flowing in a single fractured oil-saturated sand in a 2-D horizontal cell. At last, the water flooding and ferrofluid flooding in a complex fractured porous media have been studied. The results showed that the ferrofluid can be manipulated to flow in desired direction through control of the external magnetic field, so that using ferrofluid for flooding can raise the scope of the whole displacement. As a consequence, the oil recovery has been greatly improved in comparison to water flooding. Thus, the ferrofluid

  3. An efficient hydro-mechanical model for coupled multi-porosity and discrete fracture porous media

    Science.gov (United States)

    Yan, Xia; Huang, Zhaoqin; Yao, Jun; Li, Yang; Fan, Dongyan; Zhang, Kai

    2018-02-01

    In this paper, a numerical model is developed for coupled analysis of deforming fractured porous media with multiscale fractures. In this model, the macro-fractures are modeled explicitly by the embedded discrete fracture model, and the supporting effects of fluid and fillings in these fractures are represented explicitly in the geomechanics model. On the other hand, matrix and micro-fractures are modeled by a multi-porosity model, which aims to accurately describe the transient matrix-fracture fluid exchange process. A stabilized extended finite element method scheme is developed based on the polynomial pressure projection technique to address the displacement oscillation along macro-fracture boundaries. After that, the mixed space discretization and modified fixed stress sequential implicit methods based on non-matching grids are applied to solve the coupling model. Finally, we demonstrate the accuracy and application of the proposed method to capture the coupled hydro-mechanical impacts of multiscale fractures on fractured porous media.

  4. The application of a hierarchical Bayesian spatiotemporal model for ...

    Indian Academy of Sciences (India)

    Process (GP) model by using the Gibbs sampling method. The result for ... good indicator of the HBST method. The statistical ... summary and discussion of future works are given .... spatiotemporal package in R language (R core team. 2013).

  5. Bayesian disease mapping: hierarchical modeling in spatial epidemiology

    National Research Council Canada - National Science Library

    Lawson, Andrew

    2013-01-01

    Since the publication of the first edition, many new Bayesian tools and methods have been developed for space-time data analysis, the predictive modeling of health outcomes, and other spatial biostatistical areas...

  6. Hierarchical models and iterative optimization of hybrid systems

    Energy Technology Data Exchange (ETDEWEB)

    Rasina, Irina V. [Ailamazyan Program Systems Institute, Russian Academy of Sciences, Peter One str. 4a, Pereslavl-Zalessky, 152021 (Russian Federation); Baturina, Olga V. [Trapeznikov Control Sciences Institute, Russian Academy of Sciences, Profsoyuznaya str. 65, 117997, Moscow (Russian Federation); Nasatueva, Soelma N. [Buryat State University, Smolina str.24a, Ulan-Ude, 670000 (Russian Federation)

    2016-06-08

    A class of hybrid control systems on the base of two-level discrete-continuous model is considered. The concept of this model was proposed and developed in preceding works as a concretization of the general multi-step system with related optimality conditions. A new iterative optimization procedure for such systems is developed on the base of localization of the global optimality conditions via contraction the control set.

  7. Trans-dimensional matched-field geoacoustic inversion with hierarchical error models and interacting Markov chains.

    Science.gov (United States)

    Dettmer, Jan; Dosso, Stan E

    2012-10-01

    This paper develops a trans-dimensional approach to matched-field geoacoustic inversion, including interacting Markov chains to improve efficiency and an autoregressive model to account for correlated errors. The trans-dimensional approach and hierarchical seabed model allows inversion without assuming any particular parametrization by relaxing model specification to a range of plausible seabed models (e.g., in this case, the number of sediment layers is an unknown parameter). Data errors are addressed by sampling statistical error-distribution parameters, including correlated errors (covariance), by applying a hierarchical autoregressive error model. The well-known difficulty of low acceptance rates for trans-dimensional jumps is addressed with interacting Markov chains, resulting in a substantial increase in efficiency. The trans-dimensional seabed model and the hierarchical error model relax the degree of prior assumptions required in the inversion, resulting in substantially improved (more realistic) uncertainty estimates and a more automated algorithm. In particular, the approach gives seabed parameter uncertainty estimates that account for uncertainty due to prior model choice (layering and data error statistics). The approach is applied to data measured on a vertical array in the Mediterranean Sea.

  8. A hybrid deterministic-probabilistic approach to model the mechanical response of helically arranged hierarchical strands

    Science.gov (United States)

    Fraldi, M.; Perrella, G.; Ciervo, M.; Bosia, F.; Pugno, N. M.

    2017-09-01

    Very recently, a Weibull-based probabilistic strategy has been successfully applied to bundles of wires to determine their overall stress-strain behaviour, also capturing previously unpredicted nonlinear and post-elastic features of hierarchical strands. This approach is based on the so-called "Equal Load Sharing (ELS)" hypothesis by virtue of which, when a wire breaks, the load acting on the strand is homogeneously redistributed among the surviving wires. Despite the overall effectiveness of the method, some discrepancies between theoretical predictions and in silico Finite Element-based simulations or experimental findings might arise when more complex structures are analysed, e.g. helically arranged bundles. To overcome these limitations, an enhanced hybrid approach is proposed in which the probability of rupture is combined with a deterministic mechanical model of a strand constituted by helically-arranged and hierarchically-organized wires. The analytical model is validated comparing its predictions with both Finite Element simulations and experimental tests. The results show that generalized stress-strain responses - incorporating tension/torsion coupling - are naturally found and, once one or more elements break, the competition between geometry and mechanics of the strand microstructure, i.e. the different cross sections and helical angles of the wires in the different hierarchical levels of the strand, determines the no longer homogeneous stress redistribution among the surviving wires whose fate is hence governed by a "Hierarchical Load Sharing" criterion.

  9. A hierarchical stress release model for synthetic seismicity

    Science.gov (United States)

    Bebbington, Mark

    1997-06-01

    We construct a stochastic dynamic model for synthetic seismicity involving stochastic stress input, release, and transfer in an environment of heterogeneous strength and interacting segments. The model is not fault-specific, having a number of adjustable parameters with physical interpretation, namely, stress relaxation, stress transfer, stress dissipation, segment structure, strength, and strength heterogeneity, which affect the seismicity in various ways. Local parameters are chosen to be consistent with large historical events, other parameters to reproduce bulk seismicity statistics for the fault as a whole. The one-dimensional fault is divided into a number of segments, each comprising a varying number of nodes. Stress input occurs at each node in a simple random process, representing the slow buildup due to tectonic plate movements. Events are initiated, subject to a stochastic hazard function, when the stress on a node exceeds the local strength. An event begins with the transfer of excess stress to neighboring nodes, which may in turn transfer their excess stress to the next neighbor. If the event grows to include the entire segment, then most of the stress on the segment is transferred to neighboring segments (or dissipated) in a characteristic event. These large events may themselves spread to other segments. We use the Middle America Trench to demonstrate that this model, using simple stochastic stress input and triggering mechanisms, can produce behavior consistent with the historical record over five units of magnitude. We also investigate the effects of perturbing various parameters in order to show how the model might be tailored to a specific fault structure. The strength of the model lies in this ability to reproduce the behavior of a general linear fault system through the choice of a relatively small number of parameters. It remains to develop a procedure for estimating the internal state of the model from the historical observations in order to

  10. The hydro-mechanical modeling of the fractured media

    International Nuclear Information System (INIS)

    Kadiri, I.

    2002-10-01

    The hydro-mechanical modeling of the fractured media is quite complex. Simplifications are necessary for the modeling of such media, but, not always justified, Only permeable fractures are often considered. The rest of the network is approximated by an equivalent continuous medium. Even if we suppose that this approach is validated, the hydraulic and mechanical properties of the fractures and of the continuous medium are seldom known. Calibrations are necessary for the determination of these properties. Until now, one does not know very well the nature of measurements which must be carried out in order to carry on a modeling in discontinuous medium, nor elements of enough robust validation for this kind of modeling. For a better understanding of the hydro-mechanical phenomena in fractured media, two different sites have been selected for the work. The first is the site of Grimsel in Switzerland in which an underground laboratory is located at approximately 400 m of depth. The FEBEX experiment aims at the in-situ study of the consecutive phenomena due to the installation of a heat source representative of radioactive waste in the last 17 meters of the FEBEX tunnel in the laboratory of Grimsel. Only, the modeling of the hydro-mechanical of the excavation was model. The modeling of the Febex enabled us to establish a methodology of calibration of the hydraulic properties in the discontinuous media. However, this kind of study on such complex sites does not make possible to answer all the questions which arise on the hydro-mechanical behavior of the fractured media. We thus carried out modeling on an other site, smaller than the fist one and more accessible. The experimental site of Coaraze, in the Maritime Alps, is mainly constituted of limestone and fractures. Then the variation of water pressure along fractures is governed by the opening/closure sequence of a water gate. Normal displacement as well as the pore pressure along these fractures are recorded, and then

  11. Calibration of Automatically Generated Items Using Bayesian Hierarchical Modeling.

    Science.gov (United States)

    Johnson, Matthew S.; Sinharay, Sandip

    For complex educational assessments, there is an increasing use of "item families," which are groups of related items. However, calibration or scoring for such an assessment requires fitting models that take into account the dependence structure inherent among the items that belong to the same item family. C. Glas and W. van der Linden…

  12. A hierarchical modeling of information seeking behavior of school ...

    African Journals Online (AJOL)

    The aim of this study was to investigate the information seeking behavior of school teachers in the public primary schools of rural areas of Nigeria and to draw up a model of their information-seeking behavior. A Cross-sectional survey design research was employed to carry out the research. Findings showed that the ...

  13. Generic Database Cost Models for Hierarchical Memory Systems

    NARCIS (Netherlands)

    S. Manegold (Stefan); P.A. Boncz (Peter); M.L. Kersten (Martin)

    2002-01-01

    textabstractAccurate prediction of operator execution time is a prerequisite for database query optimization. Although extensively studied for conventional disk-based DBMSs, cost modeling in main-memory DBMSs is still an open issue. Recent database research has demonstrated that memory access is

  14. Generic database cost models for hierarchical memory systems

    NARCIS (Netherlands)

    S. Manegold (Stefan); P.A. Boncz (Peter); M.L. Kersten (Martin)

    2002-01-01

    textabstractAccurate prediction of operator execution time is a prerequisite fordatabase query optimization. Although extensively studied for conventionaldisk-based DBMSs, cost modeling in main-memory DBMSs is still an openissue. Recent database research has demonstrated that memory access ismore

  15. Modeling the Fracture of Ice Sheets on Parallel Computers

    Energy Technology Data Exchange (ETDEWEB)

    Waisman, Haim [Columbia Univ., New York, NY (United States); Tuminaro, Ray [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

    2013-10-10

    The objective of this project was to investigate the complex fracture of ice and understand its role within larger ice sheet simulations and global climate change. This objective was achieved by developing novel physics based models for ice, novel numerical tools to enable the modeling of the physics and by collaboration with the ice community experts. At the present time, ice fracture is not explicitly considered within ice sheet models due in part to large computational costs associated with the accurate modeling of this complex phenomena. However, fracture not only plays an extremely important role in regional behavior but also influences ice dynamics over much larger zones in ways that are currently not well understood. To this end, our research findings through this project offers significant advancement to the field and closes a large gap of knowledge in understanding and modeling the fracture of ice sheets in the polar regions. Thus, we believe that our objective has been achieved and our research accomplishments are significant. This is corroborated through a set of published papers, posters and presentations at technical conferences in the field. In particular significant progress has been made in the mechanics of ice, fracture of ice sheets and ice shelves in polar regions and sophisticated numerical methods that enable the solution of the physics in an efficient way.

  16. Bayesian Hierarchical Distributed Lag Models for Summer Ozone Exposure and Cardio-Respiratory Mortality

    OpenAIRE

    Yi Huang; Francesca Dominici; Michelle Bell

    2004-01-01

    In this paper, we develop Bayesian hierarchical distributed lag models for estimating associations between daily variations in summer ozone levels and daily variations in cardiovascular and respiratory (CVDRESP) mortality counts for 19 U.S. large cities included in the National Morbidity Mortality Air Pollution Study (NMMAPS) for the period 1987 - 1994. At the first stage, we define a semi-parametric distributed lag Poisson regression model to estimate city-specific relative rates of CVDRESP ...

  17. Transport modeling of sorbing tracers in artificial fractures

    International Nuclear Information System (INIS)

    Keum, Dong Kwon; Baik, Min Hoon; Park, Chung Kyun; Cho, Young Hwan; Hahn, Phil Soo.

    1998-02-01

    This study was performed as part of a fifty-man year attachment program between AECL (Atomic Energy Canada Limited) and KAERI. Three kinds of computer code, HDD, POMKAP and VAMKAP, were developed to predict transport of contaminants in fractured rock. MDDM was to calculate the mass transport of contaminants in a single fracture using a simple hydrodynamic dispersion diffusion model. POMKAP was to predict the mass transport of contaminants by a two-dimensional variable aperture model. In parallel with modeling, the validation of models was also performed through the analysis of the migration experimental data obtained in acrylic plastic and granite artificial fracture system at the Whiteshell laboratories, AECL, Canada. (author). 34 refs., 11 tabs., 76 figs

  18. Transport modeling of sorbing tracers in artificial fractures

    Energy Technology Data Exchange (ETDEWEB)

    Keum, Dong Kwon; Baik, Min Hoon; Park, Chung Kyun; Cho, Young Hwan; Hahn, Phil Soo

    1998-02-01

    This study was performed as part of a fifty-man year attachment program between AECL (Atomic Energy Canada Limited) and KAERI. Three kinds of computer code, HDD, POMKAP and VAMKAP, were developed to predict transport of contaminants in fractured rock. MDDM was to calculate the mass transport of contaminants in a single fracture using a simple hydrodynamic dispersion diffusion model. POMKAP was to predict the mass transport of contaminants by a two-dimensional variable aperture model. In parallel with modeling, the validation of models was also performed through the analysis of the migration experimental data obtained in acrylic plastic and granite artificial fracture system at the Whiteshell laboratories, AECL, Canada. (author). 34 refs., 11 tabs., 76 figs.

  19. Hydraulic Fracture Growth in a Layered Formation based on Fracturing Experiments and Discrete Element Modeling

    Science.gov (United States)

    Yushi, Zou; Xinfang, Ma; Tong, Zhou; Ning, Li; Ming, Chen; Sihai, Li; Yinuo, Zhang; Han, Li

    2017-09-01

    Hydraulic fracture (HF) height containment tends to occur in layered formations, and it significantly influences the entire HF geometry or the stimulated reservoir volume. This study aims to explore the influence of preexisting bedding planes (BPs) on the HF height growth in layered formations. Laboratory fracturing experiments were performed to confirm the occurrence of HF height containment in natural shale that contains multiple weak and high-permeability BPs under triaxial stresses. Numerical simulations were then conducted to further illustrate the manner in which vertical stress, BP permeability, BP density(or spacing), pump rate, and fluid viscosity control HF height growth using a 3D discrete element method-based fracturing model. In this model, the rock matrix was considered transversely isotropic and multiple BPs can be explicitly represented. Experimental and numerical results show that the vertically growing HF tends to be limited by multi-high-permeability BPs, even under higher vertical stress. When the vertically growing HF intersects with the multi-high-permeability BPs, the injection pressure will be sharply reduced. If a low pumping rate or a low-viscosity fluid is used, the excess fracturing fluid leak-off into the BPs obviously decreases the rate of pressure build up, which will then limit the growth of HF. Otherwise, a higher pumping rate and/or a higher viscosity will reduce the leak-off time and fluid volume, but increase the injection pressure to drive the HF to grow and to penetrate through the BPs.

  20. A hierarchical analysis of terrestrial ecosystem model Biome-BGC: Equilibrium analysis and model calibration

    Energy Technology Data Exchange (ETDEWEB)

    Thornton, Peter E [ORNL; Wang, Weile [ORNL; Law, Beverly E. [Oregon State University; Nemani, Ramakrishna R [NASA Ames Research Center

    2009-01-01

    The increasing complexity of ecosystem models represents a major difficulty in tuning model parameters and analyzing simulated results. To address this problem, this study develops a hierarchical scheme that simplifies the Biome-BGC model into three functionally cascaded tiers and analyzes them sequentially. The first-tier model focuses on leaf-level ecophysiological processes; it simulates evapotranspiration and photosynthesis with prescribed leaf area index (LAI). The restriction on LAI is then lifted in the following two model tiers, which analyze how carbon and nitrogen is cycled at the whole-plant level (the second tier) and in all litter/soil pools (the third tier) to dynamically support the prescribed canopy. In particular, this study analyzes the steady state of these two model tiers by a set of equilibrium equations that are derived from Biome-BGC algorithms and are based on the principle of mass balance. Instead of spinning-up the model for thousands of climate years, these equations are able to estimate carbon/nitrogen stocks and fluxes of the target (steady-state) ecosystem directly from the results obtained by the first-tier model. The model hierarchy is examined with model experiments at four AmeriFlux sites. The results indicate that the proposed scheme can effectively calibrate Biome-BGC to simulate observed fluxes of evapotranspiration and photosynthesis; and the carbon/nitrogen stocks estimated by the equilibrium analysis approach are highly consistent with the results of model simulations. Therefore, the scheme developed in this study may serve as a practical guide to calibrate/analyze Biome-BGC; it also provides an efficient way to solve the problem of model spin-up, especially for applications over large regions. The same methodology may help analyze other similar ecosystem models as well.

  1. Generic Database Cost Models for Hierarchical Memory Systems

    OpenAIRE

    Manegold, Stefan; Boncz, Peter; Kersten, Martin

    2002-01-01

    textabstractAccurate prediction of operator execution time is a prerequisite for database query optimization. Although extensively studied for conventional disk-based DBMSs, cost modeling in main-memory DBMSs is still an open issue. Recent database research has demonstrated that memory access is more and more becoming a significant---if not the major---cost component of database operations. If used properly, fast but small cache memories---usually organized in cascading hierarchy between CPU ...

  2. Probabilistic Inference: Task Dependency and Individual Differences of Probability Weighting Revealed by Hierarchical Bayesian Modeling.

    Science.gov (United States)

    Boos, Moritz; Seer, Caroline; Lange, Florian; Kopp, Bruno

    2016-01-01

    Cognitive determinants of probabilistic inference were examined using hierarchical Bayesian modeling techniques. A classic urn-ball paradigm served as experimental strategy, involving a factorial two (prior probabilities) by two (likelihoods) design. Five computational models of cognitive processes were compared with the observed behavior. Parameter-free Bayesian posterior probabilities and parameter-free base rate neglect provided inadequate models of probabilistic inference. The introduction of distorted subjective probabilities yielded more robust and generalizable results. A general class of (inverted) S-shaped probability weighting functions had been proposed; however, the possibility of large differences in probability distortions not only across experimental conditions, but also across individuals, seems critical for the model's success. It also seems advantageous to consider individual differences in parameters of probability weighting as being sampled from weakly informative prior distributions of individual parameter values. Thus, the results from hierarchical Bayesian modeling converge with previous results in revealing that probability weighting parameters show considerable task dependency and individual differences. Methodologically, this work exemplifies the usefulness of hierarchical Bayesian modeling techniques for cognitive psychology. Theoretically, human probabilistic inference might be best described as the application of individualized strategic policies for Bayesian belief revision.

  3. Statistical shear lag model - unraveling the size effect in hierarchical composites.

    Science.gov (United States)

    Wei, Xiaoding; Filleter, Tobin; Espinosa, Horacio D

    2015-05-01

    Numerous experimental and computational studies have established that the hierarchical structures encountered in natural materials, such as the brick-and-mortar structure observed in sea shells, are essential for achieving defect tolerance. Due to this hierarchy, the mechanical properties of natural materials have a different size dependence compared to that of typical engineered materials. This study aimed to explore size effects on the strength of bio-inspired staggered hierarchical composites and to define the influence of the geometry of constituents in their outstanding defect tolerance capability. A statistical shear lag model is derived by extending the classical shear lag model to account for the statistics of the constituents' strength. A general solution emerges from rigorous mathematical derivations, unifying the various empirical formulations for the fundamental link length used in previous statistical models. The model shows that the staggered arrangement of constituents grants composites a unique size effect on mechanical strength in contrast to homogenous continuous materials. The model is applied to hierarchical yarns consisting of double-walled carbon nanotube bundles to assess its predictive capabilities for novel synthetic materials. Interestingly, the model predicts that yarn gauge length does not significantly influence the yarn strength, in close agreement with experimental observations. Copyright © 2015 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

  4. Accounting for uncertainty in ecological analysis: the strengths and limitations of hierarchical statistical modeling.

    Science.gov (United States)

    Cressie, Noel; Calder, Catherine A; Clark, James S; Ver Hoef, Jay M; Wikle, Christopher K

    2009-04-01

    Analyses of ecological data should account for the uncertainty in the process(es) that generated the data. However, accounting for these uncertainties is a difficult task, since ecology is known for its complexity. Measurement and/or process errors are often the only sources of uncertainty modeled when addressing complex ecological problems, yet analyses should also account for uncertainty in sampling design, in model specification, in parameters governing the specified model, and in initial and boundary conditions. Only then can we be confident in the scientific inferences and forecasts made from an analysis. Probability and statistics provide a framework that accounts for multiple sources of uncertainty. Given the complexities of ecological studies, the hierarchical statistical model is an invaluable tool. This approach is not new in ecology, and there are many examples (both Bayesian and non-Bayesian) in the literature illustrating the benefits of this approach. In this article, we provide a baseline for concepts, notation, and methods, from which discussion on hierarchical statistical modeling in ecology can proceed. We have also planted some seeds for discussion and tried to show where the practical difficulties lie. Our thesis is that hierarchical statistical modeling is a powerful way of approaching ecological analysis in the presence of inevitable but quantifiable uncertainties, even if practical issues sometimes require pragmatic compromises.

  5. Multi-subject hierarchical inverse covariance modelling improves estimation of functional brain networks.

    Science.gov (United States)

    Colclough, Giles L; Woolrich, Mark W; Harrison, Samuel J; Rojas López, Pedro A; Valdes-Sosa, Pedro A; Smith, Stephen M

    2018-05-07

    A Bayesian model for sparse, hierarchical inverse covariance estimation is presented, and applied to multi-subject functional connectivity estimation in the human brain. It enables simultaneous inference of the strength of connectivity between brain regions at both subject and population level, and is applicable to fmri, meg and eeg data. Two versions of the model can encourage sparse connectivity, either using continuous priors to suppress irrelevant connections, or using an explicit description of the network structure to estimate the connection probability between each pair of regions. A large evaluation of this model, and thirteen methods that represent the state of the art of inverse covariance modelling, is conducted using both simulated and resting-state functional imaging datasets. Our novel Bayesian approach has similar performance to the best extant alternative, Ng et al.'s Sparse Group Gaussian Graphical Model algorithm, which also is based on a hierarchical structure. Using data from the Human Connectome Project, we show that these hierarchical models are able to reduce the measurement error in meg beta-band functional networks by 10%, producing concomitant increases in estimates of the genetic influence on functional connectivity. Copyright © 2018. Published by Elsevier Inc.

  6. Latent Variable Regression 4-Level Hierarchical Model Using Multisite Multiple-Cohorts Longitudinal Data. CRESST Report 801

    Science.gov (United States)

    Choi, Kilchan

    2011-01-01

    This report explores a new latent variable regression 4-level hierarchical model for monitoring school performance over time using multisite multiple-cohorts longitudinal data. This kind of data set has a 4-level hierarchical structure: time-series observation nested within students who are nested within different cohorts of students. These…

  7. Principal-subordinate hierarchical multi-objective programming model of initial water rights allocation

    Directory of Open Access Journals (Sweden)

    Dan Wu

    2009-06-01

    Full Text Available The principal-subordinate hierarchical multi-objective programming model of initial water rights allocation was developed based on the principle of coordinated and sustainable development of different regions and water sectors within a basin. With the precondition of strictly controlling maximum emissions rights, initial water rights were allocated between the first and the second levels of the hierarchy in order to promote fair and coordinated development across different regions of the basin and coordinated and efficient water use across different water sectors, realize the maximum comprehensive benefits to the basin, promote the unity of quantity and quality of initial water rights allocation, and eliminate water conflict across different regions and water sectors. According to interactive decision-making theory, a principal-subordinate hierarchical interactive iterative algorithm based on the satisfaction degree was developed and used to solve the initial water rights allocation model. A case study verified the validity of the model.

  8. Use of a Bayesian hierarchical model to study the allometric scaling of the fetoplacental weight ratio

    Directory of Open Access Journals (Sweden)

    Fidel Ernesto Castro Morales

    2016-03-01

    Full Text Available Abstract Objectives: to propose the use of a Bayesian hierarchical model to study the allometric scaling of the fetoplacental weight ratio, including possible confounders. Methods: data from 26 singleton pregnancies with gestational age at birth between 37 and 42 weeks were analyzed. The placentas were collected immediately after delivery and stored under refrigeration until the time of analysis, which occurred within up to 12 hours. Maternal data were collected from medical records. A Bayesian hierarchical model was proposed and Markov chain Monte Carlo simulation methods were used to obtain samples from distribution a posteriori. Results: the model developed showed a reasonable fit, even allowing for the incorporation of variables and a priori information on the parameters used. Conclusions: new variables can be added to the modelfrom the available code, allowing many possibilities for data analysis and indicating the potential for use in research on the subject.

  9. Hierarchic stochastic modelling applied to intracellular Ca(2+ signals.

    Directory of Open Access Journals (Sweden)

    Gregor Moenke

    Full Text Available Important biological processes like cell signalling and gene expression have noisy components and are very complex at the same time. Mathematical analysis of such systems has often been limited to the study of isolated subsystems, or approximations are used that are difficult to justify. Here we extend a recently published method (Thurley and Falcke, PNAS 2011 which is formulated in observable system configurations instead of molecular transitions. This reduces the number of system states by several orders of magnitude and avoids fitting of kinetic parameters. The method is applied to Ca(2+ signalling. Ca(2+ is a ubiquitous second messenger transmitting information by stochastic sequences of concentration spikes, which arise by coupling of subcellular Ca(2+ release events (puffs. We derive analytical expressions for a mechanistic Ca(2+ model, based on recent data from live cell imaging, and calculate Ca(2+ spike statistics in dependence on cellular parameters like stimulus strength or number of Ca(2+ channels. The new approach substantiates a generic Ca(2+ model, which is a very convenient way to simulate Ca(2+ spike sequences with correct spiking statistics.

  10. Probabilistic inference: Task dependency and individual differences of probability weighting revealed by hierarchical Bayesian modelling

    Directory of Open Access Journals (Sweden)

    Moritz eBoos

    2016-05-01

    Full Text Available Cognitive determinants of probabilistic inference were examined using hierarchical Bayesian modelling techniques. A classic urn-ball paradigm served as experimental strategy, involving a factorial two (prior probabilities by two (likelihoods design. Five computational models of cognitive processes were compared with the observed behaviour. Parameter-free Bayesian posterior probabilities and parameter-free base rate neglect provided inadequate models of probabilistic inference. The introduction of distorted subjective probabilities yielded more robust and generalizable results. A general class of (inverted S-shaped probability weighting functions had been proposed; however, the possibility of large differences in probability distortions not only across experimental conditions, but also across individuals, seems critical for the model’s success. It also seems advantageous to consider individual differences in parameters of probability weighting as being sampled from weakly informative prior distributions of individual parameter values. Thus, the results from hierarchical Bayesian modelling converge with previous results in revealing that probability weighting parameters show considerable task dependency and individual differences. Methodologically, this work exemplifies the usefulness of hierarchical Bayesian modelling techniques for cognitive psychology. Theoretically, human probabilistic inference might be best described as the application of individualized strategic policies for Bayesian belief revision.

  11. An approach to ductile fracture resistance modelling in pipeline steels

    Energy Technology Data Exchange (ETDEWEB)

    Pussegoda, L.N.; Fredj, A. [BMT Fleet Technology Ltd., Kanata (Canada)

    2009-07-01

    Ductile fracture resistance studies of high grade steels in the pipeline industry often included analyses of the crack tip opening angle (CTOA) parameter using 3-point bend steel specimens. The CTOA is a function of specimen ligament size in high grade materials. Other resistance measurements may include steady state fracture propagation energy, critical fracture strain, and the adoption of damage mechanisms. Modelling approaches for crack propagation were discussed in this abstract. Tension tests were used to calibrate damage model parameters. Results from the tests were then applied to the crack propagation in a 3-point bend specimen using modern 1980 vintage steels. Limitations and approaches to overcome the difficulties associated with crack propagation modelling were discussed.

  12. Modeling of Hydrodynamic Chromatography for Colloid Migration in Fractured Rock

    International Nuclear Information System (INIS)

    Li Shihhai; Jen, C.-P.

    2001-01-01

    The role of colloids in the migration of radionuclides in the geosphere has been emphasized in the performance assessment of high-level radioactive waste disposal. The literature indicates that the colloid velocity may not be equal to the velocity of groundwater owing to hydrodynamic chromatography. A theoretical model for hydrodynamic chromatography of colloid migration in the fracture is proposed in the present work. In this model, the colloids are treated as nonreactive and the external forces acting on colloidal particles are considered including the inertial force, the van der Waals attractive force, and the electrical double-layer repulsive force, as well as the gravitational force. A fully developed concentration profile for colloids is obtained to elucidate migration behavior for colloids in the fracture. The effects of parameters governing these forces and the aperture of the fracture are determined using a theoretical model

  13. Numerical modelling of flow and transport in rough fractures

    Directory of Open Access Journals (Sweden)

    Scott Briggs

    2014-12-01

    Full Text Available Simulation of flow and transport through rough walled rock fractures is investigated using the lattice Boltzmann method (LBM and random walk (RW, respectively. The numerical implementation is developed and validated on general purpose graphic processing units (GPGPUs. Both the LBM and RW method are well suited to parallel implementation on GPGPUs because they require only next-neighbour communication and thus can reduce expenses. The LBM model is an order of magnitude faster on GPGPUs than published results for LBM simulations run on modern CPUs. The fluid model is verified for parallel plate flow, backward facing step and single fracture flow; and the RW model is verified for point-source diffusion, Taylor-Aris dispersion and breakthrough behaviour in a single fracture. Both algorithms place limitations on the discrete displacement of fluid or particle transport per time step to minimise the numerical error that must be considered during implementation.

  14. Modeling when people quit: Bayesian censored geometric models with hierarchical and latent-mixture extensions.

    Science.gov (United States)

    Okada, Kensuke; Vandekerckhove, Joachim; Lee, Michael D

    2018-02-01

    People often interact with environments that can provide only a finite number of items as resources. Eventually a book contains no more chapters, there are no more albums available from a band, and every Pokémon has been caught. When interacting with these sorts of environments, people either actively choose to quit collecting new items, or they are forced to quit when the items are exhausted. Modeling the distribution of how many items people collect before they quit involves untangling these two possibilities, We propose that censored geometric models are a useful basic technique for modeling the quitting distribution, and, show how, by implementing these models in a hierarchical and latent-mixture framework through Bayesian methods, they can be extended to capture the additional features of specific situations. We demonstrate this approach by developing and testing a series of models in two case studies involving real-world data. One case study deals with people choosing jokes from a recommender system, and the other deals with people completing items in a personality survey.

  15. Multiscale model reduction for shale gas transport in fractured media

    KAUST Repository

    Akkutlu, I. Y.

    2016-05-18

    In this paper, we develop a multiscale model reduction technique that describes shale gas transport in fractured media. Due to the pore-scale heterogeneities and processes, we use upscaled models to describe the matrix. We follow our previous work (Akkutlu et al. Transp. Porous Media 107(1), 235–260, 2015), where we derived an upscaled model in the form of generalized nonlinear diffusion model to describe the effects of kerogen. To model the interaction between the matrix and the fractures, we use Generalized Multiscale Finite Element Method (Efendiev et al. J. Comput. Phys. 251, 116–135, 2013, 2015). In this approach, the matrix and the fracture interaction is modeled via local multiscale basis functions. In Efendiev et al. (2015), we developed the GMsFEM and applied for linear flows with horizontal or vertical fracture orientations aligned with a Cartesian fine grid. The approach in Efendiev et al. (2015) does not allow handling arbitrary fracture distributions. In this paper, we (1) consider arbitrary fracture distributions on an unstructured grid; (2) develop GMsFEM for nonlinear flows; and (3) develop online basis function strategies to adaptively improve the convergence. The number of multiscale basis functions in each coarse region represents the degrees of freedom needed to achieve a certain error threshold. Our approach is adaptive in a sense that the multiscale basis functions can be added in the regions of interest. Numerical results for two-dimensional problem are presented to demonstrate the efficiency of proposed approach. © 2016 Springer International Publishing Switzerland

  16. The Case for A Hierarchal System Model for Linux Clusters

    Energy Technology Data Exchange (ETDEWEB)

    Seager, M; Gorda, B

    2009-06-05

    The computer industry today is no longer driven, as it was in the 40s, 50s and 60s, by High-performance computing requirements. Rather, HPC systems, especially Leadership class systems, sit on top of a pyramid investment mode. Figure 1 shows a representative pyramid investment model for systems hardware. At the base of the pyramid is the huge investment (order 10s of Billions of US Dollars per year) in semiconductor fabrication and process technologies. These costs, which are approximately doubling with every generation, are funded from investments multiple markets: enterprise, desktops, games, embedded and specialized devices. Over and above these base technology investments are investments for critical technology elements such as microprocessor, chipsets and memory ASIC components. Investments for these components are spread across the same markets as the base semiconductor processes investments. These second tier investments are approximately half the size of the lower level of the pyramid. The next technology investment layer up, tier 3, is more focused on scalable computing systems such as those needed for HPC and other markets. These tier 3 technology elements include networking (SAN, WAN and LAN), interconnects and large scalable SMP designs. Above these is tier 4 are relatively small investments necessary to build very large, scalable systems high-end or Leadership class systems. Primary among these are the specialized network designs of vertically integrated systems, etc.

  17. Modelling of 3D fractured geological systems - technique and application

    Science.gov (United States)

    Cacace, M.; Scheck-Wenderoth, M.; Cherubini, Y.; Kaiser, B. O.; Bloecher, G.

    2011-12-01

    All rocks in the earth's crust are fractured to some extent. Faults and fractures are important in different scientific and industry fields comprising engineering, geotechnical and hydrogeological applications. Many petroleum, gas and geothermal and water supply reservoirs form in faulted and fractured geological systems. Additionally, faults and fractures may control the transport of chemical contaminants into and through the subsurface. Depending on their origin and orientation with respect to the recent and palaeo stress field as well as on the overall kinematics of chemical processes occurring within them, faults and fractures can act either as hydraulic conductors providing preferential pathways for fluid to flow or as barriers preventing flow across them. The main challenge in modelling processes occurring in fractured rocks is related to the way of describing the heterogeneities of such geological systems. Flow paths are controlled by the geometry of faults and their open void space. To correctly simulate these processes an adequate 3D mesh is a basic requirement. Unfortunately, the representation of realistic 3D geological environments is limited by the complexity of embedded fracture networks often resulting in oversimplified models of the natural system. A technical description of an improved method to integrate generic dipping structures (representing faults and fractures) into a 3D porous medium is out forward. The automated mesh generation algorithm is composed of various existing routines from computational geometry (e.g. 2D-3D projection, interpolation, intersection, convex hull calculation) and meshing (e.g. triangulation in 2D and tetrahedralization in 3D). All routines have been combined in an automated software framework and the robustness of the approach has been tested and verified. These techniques and methods can be applied for fractured porous media including fault systems and therefore found wide applications in different geo-energy related

  18. Emotional intelligence is a second-stratum factor of intelligence: evidence from hierarchical and bifactor models.

    Science.gov (United States)

    MacCann, Carolyn; Joseph, Dana L; Newman, Daniel A; Roberts, Richard D

    2014-04-01

    This article examines the status of emotional intelligence (EI) within the structure of human cognitive abilities. To evaluate whether EI is a 2nd-stratum factor of intelligence, data were fit to a series of structural models involving 3 indicators each for fluid intelligence, crystallized intelligence, quantitative reasoning, visual processing, and broad retrieval ability, as well as 2 indicators each for emotion perception, emotion understanding, and emotion management. Unidimensional, multidimensional, hierarchical, and bifactor solutions were estimated in a sample of 688 college and community college students. Results suggest adequate fit for 2 models: (a) an oblique 8-factor model (with 5 traditional cognitive ability factors and 3 EI factors) and (b) a hierarchical solution (with cognitive g at the highest level and EI representing a 2nd-stratum factor that loads onto g at λ = .80). The acceptable relative fit of the hierarchical model confirms the notion that EI is a group factor of cognitive ability, marking the expression of intelligence in the emotion domain. The discussion proposes a possible expansion of Cattell-Horn-Carroll theory to include EI as a 2nd-stratum factor of similar standing to factors such as fluid intelligence and visual processing.

  19. Action detection by double hierarchical multi-structure space-time statistical matching model

    Science.gov (United States)

    Han, Jing; Zhu, Junwei; Cui, Yiyin; Bai, Lianfa; Yue, Jiang

    2018-03-01

    Aimed at the complex information in videos and low detection efficiency, an actions detection model based on neighboring Gaussian structure and 3D LARK features is put forward. We exploit a double hierarchical multi-structure space-time statistical matching model (DMSM) in temporal action localization. First, a neighboring Gaussian structure is presented to describe the multi-scale structural relationship. Then, a space-time statistical matching method is proposed to achieve two similarity matrices on both large and small scales, which combines double hierarchical structural constraints in model by both the neighboring Gaussian structure and the 3D LARK local structure. Finally, the double hierarchical similarity is fused and analyzed to detect actions. Besides, the multi-scale composite template extends the model application into multi-view. Experimental results of DMSM on the complex visual tracker benchmark data sets and THUMOS 2014 data sets show the promising performance. Compared with other state-of-the-art algorithm, DMSM achieves superior performances.

  20. Oscillatory Critical Amplitudes in Hierarchical Models and the Harris Function of Branching Processes

    Science.gov (United States)

    Costin, Ovidiu; Giacomin, Giambattista

    2013-02-01

    Oscillatory critical amplitudes have been repeatedly observed in hierarchical models and, in the cases that have been taken into consideration, these oscillations are so small to be hardly detectable. Hierarchical models are tightly related to iteration of maps and, in fact, very similar phenomena have been repeatedly reported in many fields of mathematics, like combinatorial evaluations and discrete branching processes. It is precisely in the context of branching processes with bounded off-spring that T. Harris, in 1948, first set forth the possibility that the logarithm of the moment generating function of the rescaled population size, in the super-critical regime, does not grow near infinity as a power, but it has an oscillatory prefactor (the Harris function). These oscillations have been observed numerically only much later and, while the origin is clearly tied to the discrete character of the iteration, the amplitude size is not so well understood. The purpose of this note is to reconsider the issue for hierarchical models and in what is arguably the most elementary setting—the pinning model—that actually just boils down to iteration of polynomial maps (and, notably, quadratic maps). In this note we show that the oscillatory critical amplitude for pinning models and the Harris function coincide. Moreover we make explicit the link between these oscillatory functions and the geometry of the Julia set of the map, making thus rigorous and quantitative some ideas set forth in Derrida et al. (Commun. Math. Phys. 94:115-132, 1984).

  1. On hierarchical models for visual recognition and learning of objects, scenes, and activities

    CERN Document Server

    Spehr, Jens

    2015-01-01

    In many computer vision applications, objects have to be learned and recognized in images or image sequences. This book presents new probabilistic hierarchical models that allow an efficient representation of multiple objects of different categories, scales, rotations, and views. The idea is to exploit similarities between objects and object parts in order to share calculations and avoid redundant information. Furthermore inference approaches for fast and robust detection are presented. These new approaches combine the idea of compositional and similarity hierarchies and overcome limitations of previous methods. Besides classical object recognition the book shows the use for detection of human poses in a project for gait analysis. The use of activity detection is presented for the design of environments for ageing, to identify activities and behavior patterns in smart homes. In a presented project for parking spot detection using an intelligent vehicle, the proposed approaches are used to hierarchically model...

  2. An Improved Rate-Transient Analysis Model of Multi-Fractured Horizontal Wells with Non-Uniform Hydraulic Fracture Properties

    Directory of Open Access Journals (Sweden)

    Youwei He

    2018-02-01

    Full Text Available Although technical advances in hydraulically fracturing and drilling enable commercial production from tight reservoirs, oil/gas recovery remains at a low level. Due to the technical and economic limitations of well-testing operations in tight reservoirs, rate-transient analysis (RTA has become a more attractive option. However, current RTA models hardly consider the effect of the non-uniform production on rate decline behaviors. In fact, PLT results demonstrate that production profile is non-uniform. To fill this gap, this paper presents an improved RTA model of multi-fractured horizontal wells (MFHWs to investigate the effects of non-uniform properties of hydraulic fractures (production of fractures, fracture half-length, number of fractures, fracture conductivity, and vertical permeability on rate transient behaviors through the diagnostic type curves. Results indicate obvious differences on the rate decline curves among the type curves of uniform properties of fractures (UPF and non-uniform properties of fractures (NPF. The use of dimensionless production integral derivative curve magnifies the differences so that we can diagnose the phenomenon of non-uniform production. Therefore, it’s significant to incorporate the effects of NPF into the RDA models of MFHWs, and the model proposed in this paper enables us to better evaluate well performance based on long-term production data.

  3. Fracture flow modelling. Proof of evidence

    International Nuclear Information System (INIS)

    Hencher, S.R.

    1996-01-01

    Proof of Evidence by an expert witness is presented in support of the case by Friends of the Earth (FOE) against the proposed construction by UK Nirex Ltd of an underground Rock Characterisation Facility (RCF) at a site in the Sellafield area. The RCF is part of an investigation by Nirex into a suitable site for an underground repository for the disposal of radioactive waste. The objections were raised at a Planning Inquiry in 1995. The evidence points out that current understanding of the factors which control flow through a network of interconnecting fractures, such as that at the Sellafield site, is at a very early stage of development. Neither are the methods of investigation and analysis required for a post-closure performance assessment (PCPA) for a repository well developed. These issues are being investigated in international underground research laboratories but the proposed RCF is intended to be confirmatory rather than experimental. (23 references). (UK)

  4. Loss Performance Modeling for Hierarchical Heterogeneous Wireless Networks With Speed-Sensitive Call Admission Control

    DEFF Research Database (Denmark)

    Huang, Qian; Huang, Yue-Cai; Ko, King-Tim

    2011-01-01

    . This approach avoids unnecessary and frequent handoff between cells and reduces signaling overheads. An approximation model with guaranteed accuracy and low computational complexity is presented for the loss performance of multiservice traffic. The accuracy of numerical results is validated by comparing......A hierarchical overlay structure is an alternative solution that integrates existing and future heterogeneous wireless networks to provide subscribers with better mobile broadband services. Traffic loss performance in such integrated heterogeneous networks is necessary for an operator's network...

  5. Bayesian Poisson hierarchical models for crash data analysis: Investigating the impact of model choice on site-specific predictions.

    Science.gov (United States)

    Khazraee, S Hadi; Johnson, Valen; Lord, Dominique

    2018-08-01

    The Poisson-gamma (PG) and Poisson-lognormal (PLN) regression models are among the most popular means for motor vehicle crash data analysis. Both models belong to the Poisson-hierarchical family of models. While numerous studies have compared the overall performance of alternative Bayesian Poisson-hierarchical models, little research has addressed the impact of model choice on the expected crash frequency prediction at individual sites. This paper sought to examine whether there are any trends among candidate models predictions e.g., that an alternative model's prediction for sites with certain conditions tends to be higher (or lower) than that from another model. In addition to the PG and PLN models, this research formulated a new member of the Poisson-hierarchical family of models: the Poisson-inverse gamma (PIGam). Three field datasets (from Texas, Michigan and Indiana) covering a wide range of over-dispersion characteristics were selected for analysis. This study demonstrated that the model choice can be critical when the calibrated models are used for prediction at new sites, especially when the data are highly over-dispersed. For all three datasets, the PIGam model would predict higher expected crash frequencies than would the PLN and PG models, in order, indicating a clear link between the models predictions and the shape of their mixing distributions (i.e., gamma, lognormal, and inverse gamma, respectively). The thicker tail of the PIGam and PLN models (in order) may provide an advantage when the data are highly over-dispersed. The analysis results also illustrated a major deficiency of the Deviance Information Criterion (DIC) in comparing the goodness-of-fit of hierarchical models; models with drastically different set of coefficients (and thus predictions for new sites) may yield similar DIC values, because the DIC only accounts for the parameters in the lowest (observation) level of the hierarchy and ignores the higher levels (regression coefficients

  6. A Lateral Tensile Fracturing Model for Listric Fault

    Science.gov (United States)

    Qiu, Z.

    2007-12-01

    The new discovery of a major seismic fault of the great 1976 Tangshan earthquake suggests a lateral tensile fracturing process at the seismic source. The fault is in listric shape but can not be explained with the prevailing model of listric fault. A double-couple of forces without moment is demonstrated to be applicable to simulate the source mechanism. Based on fracture mechanics, laboratory experiments as well as numerical simulations, the model is against the assumption of stick-slip on existing fault as the cause of the earthquake but not in conflict with seismological observations. Global statistics of CMT solutions of great earthquakes raises significant support to the idea that lateral tensile fracturing might account for not only the Tangshan earthquake but also others.

  7. Coupled models in porous media: reactive transport and fractures

    International Nuclear Information System (INIS)

    Amir, L.

    2008-12-01

    This thesis deals with numerical simulation of coupled models for flow and transport in porous media. We present a new method for coupling chemical reactions and transport by using a Newton-Krylov method, and we also present a model of flow in fractured media, based on a domain decomposition method that takes into account the case of intersecting fractures. This study is composed of three parts: the first part contains an analysis, and implementation, of various numerical methods for discretizing advection-diffusion problems, in particular by using operator splitting methods. The second part is concerned with a fully coupled method for modeling transport and chemistry problems. The coupled transport-chemistry model is described, after discretization in time, by a system of nonlinear equations. The size of the system, namely the number of grid points times the number a chemical species, precludes a direct solution of the linear system. To alleviate this difficulty, we solve the system by a Newton-Krylov method, so as to avoid forming and factoring the Jacobian matrix. In the last part, we present a model of flow in 3D for intersecting fractures, by using a domain decomposition method. The fractures are treated as interfaces between sub-domains. We show existence and uniqueness of the solution, and we validate the model by numerical tests. (author)

  8. The brush model - a new approach to numerical modeling of matrix diffusion in fractured clay stone

    International Nuclear Information System (INIS)

    Lege, T.; Shao, H.

    1998-01-01

    A special approach for numerical modeling of contaminant transport in fractured clay stone is presented. The rock matrix and the fractures are simulated with individual formulations for FE grids and transport, coupled into a single model. The capacity of the rock matrix to take up contaminants is taken into consideration with a discrete simulation of matrix diffusion. Thus, the natural process of retardation due to matrix diffusion can be better simulated than by a standard introduction of an empirical parameter into the transport equation. Transport in groundwater in fractured clay stone can be simulated using a model called a 'brush model'. The 'brush handle' is discretized by 2-D finite elements. Advective-dispersive transport in groundwater in the fractures is assumed. The contaminant diffuses into 1D finite elements perpendicular to the fractures, i.e., the 'bristles of the brush'. The conclusion is drawn that matrix diffusion is an important property of fractured clay stone for contaminant retardation. (author)

  9. Numerical modeling of thermal conductive heating in fractured bedrock.

    Science.gov (United States)

    Baston, Daniel P; Falta, Ronald W; Kueper, Bernard H

    2010-01-01

    Numerical modeling was employed to study the performance of thermal conductive heating (TCH) in fractured shale under a variety of hydrogeological conditions. Model results show that groundwater flow in fractures does not significantly affect the minimum treatment zone temperature, except near the beginning of heating or when groundwater influx is high. However, fracture and rock matrix properties can significantly influence the time necessary to remove all liquid water (i.e., reach superheated steam conditions) in the treatment area. Low matrix permeability, high matrix porosity, and wide fracture spacing can contribute to boiling point elevation in the rock matrix. Consequently, knowledge of these properties is important for the estimation of treatment times. Because of the variability in boiling point throughout a fractured rock treatment zone and the absence of a well-defined constant temperature boiling plateau in the rock matrix, it may be difficult to monitor the progress of thermal treatment using temperature measurements alone. Copyright © 2010 The Author(s). Journal compilation © 2010 National Ground Water Association.

  10. A sow replacement model using Bayesian updating in a three-level hierarchic Markov process. II. Optimization model

    DEFF Research Database (Denmark)

    Kristensen, Anders Ringgaard; Søllested, Thomas Algot

    2004-01-01

    improvements. The biological model of the replacement model is described in a previous paper and in this paper the optimization model is described. The model is developed as a prototype for use under practical conditions. The application of the model is demonstrated using data from two commercial Danish sow......Recent methodological improvements in replacement models comprising multi-level hierarchical Markov processes and Bayesian updating have hardly been implemented in any replacement model and the aim of this study is to present a sow replacement model that really uses these methodological...... herds. It is concluded that the Bayesian updating technique and the hierarchical structure decrease the size of the state space dramatically. Since parameter estimates vary considerably among herds it is concluded that decision support concerning sow replacement only makes sense with parameters...

  11. Topics in Computational Bayesian Statistics With Applications to Hierarchical Models in Astronomy and Sociology

    Science.gov (United States)

    Sahai, Swupnil

    This thesis includes three parts. The overarching theme is how to analyze structured hierarchical data, with applications to astronomy and sociology. The first part discusses how expectation propagation can be used to parallelize the computation when fitting big hierarchical bayesian models. This methodology is then used to fit a novel, nonlinear mixture model to ultraviolet radiation from various regions of the observable universe. The second part discusses how the Stan probabilistic programming language can be used to numerically integrate terms in a hierarchical bayesian model. This technique is demonstrated on supernovae data to significantly speed up convergence to the posterior distribution compared to a previous study that used a Gibbs-type sampler. The third part builds a formal latent kernel representation for aggregate relational data as a way to more robustly estimate the mixing characteristics of agents in a network. In particular, the framework is applied to sociology surveys to estimate, as a function of ego age, the age and sex composition of the personal networks of individuals in the United States.

  12. Microstructure oriented modelling of hierarchically perfused porous media for cerebral blood flow evaluation

    Czech Academy of Sciences Publication Activity Database

    Tonar, Z.; Kochová, P.; Cimrman, R.; Witter, K.; Janáček, Jiří; Rohan, V.

    2011-01-01

    Roč. 465, č. 2011 (2011), s. 286-289 ISSN 1013-9826. [International Conference on Materials Structure & Micromechanics of Fracture /6./. Brno, 28.06.2010-30.06.2010] Institutional research plan: CEZ:AV0Z50110509 Keywords : brain * perfusion * morphometry * microvessels * stereology * modelling Subject RIV: EA - Cell Biology

  13. A Two-Scale Reduced Model for Darcy Flow in Fractured Porous Media

    KAUST Repository

    Chen, Huangxin; Sun, Shuyu

    2016-01-01

    scale, and the effect of fractures on each coarse scale grid cell intersecting with fractures is represented by the discrete fracture model (DFM) on the fine scale. In the DFM used on the fine scale, the matrix-fracture system are resolved

  14. Exploring Neural Network Models with Hierarchical Memories and Their Use in Modeling Biological Systems

    Science.gov (United States)

    Pusuluri, Sai Teja

    Energy landscapes are often used as metaphors for phenomena in biology, social sciences and finance. Different methods have been implemented in the past for the construction of energy landscapes. Neural network models based on spin glass physics provide an excellent mathematical framework for the construction of energy landscapes. This framework uses a minimal number of parameters and constructs the landscape using data from the actual phenomena. In the past neural network models were used to mimic the storage and retrieval process of memories (patterns) in the brain. With advances in the field now, these models are being used in machine learning, deep learning and modeling of complex phenomena. Most of the past literature focuses on increasing the storage capacity and stability of stored patterns in the network but does not study these models from a modeling perspective or an energy landscape perspective. This dissertation focuses on neural network models both from a modeling perspective and from an energy landscape perspective. I firstly show how the cellular interconversion phenomenon can be modeled as a transition between attractor states on an epigenetic landscape constructed using neural network models. The model allows the identification of a reaction coordinate of cellular interconversion by analyzing experimental and simulation time course data. Monte Carlo simulations of the model show that the initial phase of cellular interconversion is a Poisson process and the later phase of cellular interconversion is a deterministic process. Secondly, I explore the static features of landscapes generated using neural network models, such as sizes of basins of attraction and densities of metastable states. The simulation results show that the static landscape features are strongly dependent on the correlation strength and correlation structure between patterns. Using different hierarchical structures of the correlation between patterns affects the landscape features

  15. Fracture initiation associated with chemical degradation: observation and modeling

    Energy Technology Data Exchange (ETDEWEB)

    Byoungho Choi; Zhenwen Zhou; Chudnovsky, Alexander [Illinois Univ., Dept. of Civil and Materials Engineering (M/C 246), Chicago, IL (United States); Stivala, Salvatore S. [Stevens Inst. of Technology, Dept. of Chemistry and Chemical Biology, Hoboken, NJ (United States); Sehanobish, Kalyan; Bosnyak, Clive P. [Dow Chemical Co., Freeport, TX (United States)

    2005-01-01

    The fracture initiation in engineering thermoplastics resulting from chemical degradation is usually observed in the form of a microcrack network within a surface layer of degraded polymer exposed to a combined action of mechanical stresses and chemically aggressive environment. Degradation of polymers is usually manifested in a reduction of molecular weight, increase of crystallinity in semi crystalline polymers, increase of material density, a subtle increase in yield strength, and a dramatic reduction in toughness. An increase in material density, i.e., shrinkage of the degraded layer is constrained by adjacent unchanged material results in a buildup of tensile stress within the degraded layer and compressive stress in the adjacent unchanged material due to increasing incompatibility between the two. These stresses are an addition to preexisting manufacturing and service stresses. At a certain level of degradation, a combination of toughness reduction and increase of tensile stress result in fracture initiation. A quantitative model of the described above processes is presented in these work. For specificity, the internally pressurized plastic pipes that transport a fluid containing a chemically aggressive (oxidizing) agent is used as the model of fracture initiation. Experimental observations of material density and toughness dependence on degradation reported elsewhere are employed in the model. An equation for determination of a critical level of degradation corresponding to the offset of fracture is constructed. The critical level of degradation for fracture initiation depends on the rates of toughness deterioration and build-up of the degradation related stresses as well as on the manufacturing and service stresses. A method for evaluation of the time interval prior to fracture initiation is also formulated. (Author)

  16. Mineral Precipitation in Fractures: Multiscale Imaging and Geochemical Modeling

    Science.gov (United States)

    Hajirezaie, S.; Peters, C. A.; Swift, A.; Sheets, J. M.; Cole, D. R.; Crandall, D.; Cheshire, M.; Stack, A. G.; Anovitz, L. M.

    2017-12-01

    For subsurface energy technologies such as geologic carbon sequestration, fractures are potential pathways for fluid migration from target formations. Highly permeable fractures may become sealed by mineral precipitation. In this study, we examined shale specimens with existing cemented fractures as natural analogues, using an array of imaging methods to characterize mineralogy and porosity at several spatial scales. In addition, we used reactive transport modeling to investigate geochemical conditions that can lead to extensive mineral precipitation and to simulate the impacts on fracture hydraulic properties. The naturally-cemented fractured rock specimens were from the Upper Wolfcamp formation in Texas, at 10,000 ft depth. The specimens were scanned using x-ray computed tomography (xCT) at resolution of 13 microns. The xCT images revealed an original fracture aperture of 1.9 mm filled with several distinct mineral phases and vuggy void regions, and the mineral phase volumes and surface areas were quantified and mapped in 3D. Specimens were thin-sectioned and examined at micron- and submicron-scales using petrographic microscopy (PM), scanning electron microscopy (SEM), energy dispersive X-ray spectroscopy (EDX), and small angle X-ray scattering (SAXS). Collectively these methods revealed crystals of dolomite as large as 900 microns in length overlain with a heterogeneous mixture of carbonate minerals including calcite, dolomite, and Fe-rich dolomite, interspersed at spatial scales as small as 5 microns. In addition, secondary precipitation of SiO2 was found to fill some of the void space. This multiscale imaging was used to inform the reactive transport modeling employed to examine the conditions that can cause the observed mineral precipitation in fractures at a larger scale. Two brines containing solutions that when mixed would lead to precipitation of various carbonate minerals were simulated as injectants into a fracture domain. In particular, the competing

  17. Hierarchical Model Predictive Control for Plug-and-Play Resource Distribution

    DEFF Research Database (Denmark)

    Bendtsen, Jan Dimon; Trangbæk, K; Stoustrup, Jakob

    2012-01-01

    of autonomous units. The approach is inspired by smart-grid electric power production and consumption systems, where the flexibility of a large number of power producing and/or power consuming units can be exploited in a smart-grid solution. The objective is to accommodate the load variation on the grid......This chapter deals with hierarchical model predictive control (MPC) of distributed systems. A three level hierarchical approach is proposed, consisting of a high level MPC controller, a second level of so-called aggregators, controlled by an online MPC-like algorithm, and a lower level......, arising on one hand from varying consumption, on the other hand by natural variations in power production e.g. from wind turbines. The proposed method can also be applied to supply chain management systems, where the challenge is to balance demand and supply, using a number of storages each with a maximal...

  18. Market Competitiveness Evaluation of Mechanical Equipment with a Pairwise Comparisons Hierarchical Model.

    Science.gov (United States)

    Hou, Fujun

    2016-01-01

    This paper provides a description of how market competitiveness evaluations concerning mechanical equipment can be made in the context of multi-criteria decision environments. It is assumed that, when we are evaluating the market competitiveness, there are limited number of candidates with some required qualifications, and the alternatives will be pairwise compared on a ratio scale. The qualifications are depicted as criteria in hierarchical structure. A hierarchical decision model called PCbHDM was used in this study based on an analysis of its desirable traits. Illustration and comparison shows that the PCbHDM provides a convenient and effective tool for evaluating the market competitiveness of mechanical equipment. The researchers and practitioners might use findings of this paper in application of PCbHDM.

  19. Hierarchical relaxation dynamics in a tilted two-band Bose-Hubbard model

    Science.gov (United States)

    Cosme, Jayson G.

    2018-04-01

    We numerically examine slow and hierarchical relaxation dynamics of interacting bosons described by a tilted two-band Bose-Hubbard model. The system is found to exhibit signatures of quantum chaos within the spectrum and the validity of the eigenstate thermalization hypothesis for relevant physical observables is demonstrated for certain parameter regimes. Using the truncated Wigner representation in the semiclassical limit of the system, dynamics of relevant observables reveal hierarchical relaxation and the appearance of prethermalized states is studied from the perspective of statistics of the underlying mean-field trajectories. The observed prethermalization scenario can be attributed to different stages of glassy dynamics in the mode-time configuration space due to dynamical phase transition between ergodic and nonergodic trajectories.

  20. Hierarchical Bayesian nonparametric mixture models for clustering with variable relevance determination.

    Science.gov (United States)

    Yau, Christopher; Holmes, Chris

    2011-07-01

    We propose a hierarchical Bayesian nonparametric mixture model for clustering when some of the covariates are assumed to be of varying relevance to the clustering problem. This can be thought of as an issue in variable selection for unsupervised learning. We demonstrate that by defining a hierarchical population based nonparametric prior on the cluster locations scaled by the inverse covariance matrices of the likelihood we arrive at a 'sparsity prior' representation which admits a conditionally conjugate prior. This allows us to perform full Gibbs sampling to obtain posterior distributions over parameters of interest including an explicit measure of each covariate's relevance and a distribution over the number of potential clusters present in the data. This also allows for individual cluster specific variable selection. We demonstrate improved inference on a number of canonical problems.

  1. Improving Hierarchical Models Using Historical Data with Applications in High-Throughput Genomics Data Analysis.

    Science.gov (United States)

    Li, Ben; Li, Yunxiao; Qin, Zhaohui S

    2017-06-01

    Modern high-throughput biotechnologies such as microarray and next generation sequencing produce a massive amount of information for each sample assayed. However, in a typical high-throughput experiment, only limited amount of data are observed for each individual feature, thus the classical 'large p , small n ' problem. Bayesian hierarchical model, capable of borrowing strength across features within the same dataset, has been recognized as an effective tool in analyzing such data. However, the shrinkage effect, the most prominent feature of hierarchical features, can lead to undesirable over-correction for some features. In this work, we discuss possible causes of the over-correction problem and propose several alternative solutions. Our strategy is rooted in the fact that in the Big Data era, large amount of historical data are available which should be taken advantage of. Our strategy presents a new framework to enhance the Bayesian hierarchical model. Through simulation and real data analysis, we demonstrated superior performance of the proposed strategy. Our new strategy also enables borrowing information across different platforms which could be extremely useful with emergence of new technologies and accumulation of data from different platforms in the Big Data era. Our method has been implemented in R package "adaptiveHM", which is freely available from https://github.com/benliemory/adaptiveHM.

  2. Hierarchical modelling of temperature and habitat size effects on population dynamics of North Atlantic cod

    DEFF Research Database (Denmark)

    Mantzouni, Irene; Sørensen, Helle; O'Hara, Robert B.

    2010-01-01

    and Beverton and Holt stock–recruitment (SR) models were extended by applying hierarchical methods, mixed-effects models, and Bayesian inference to incorporate the influence of these ecosystem factors on model parameters representing cod maximum reproductive rate and carrying capacity. We identified......Understanding how temperature affects cod (Gadus morhua) ecology is important for forecasting how populations will develop as climate changes in future. The effects of spawning-season temperature and habitat size on cod recruitment dynamics have been investigated across the North Atlantic. Ricker...

  3. Stabilization of multiple rib fractures in a canine model.

    Science.gov (United States)

    Huang, Ke-Nan; Xu, Zhi-Fei; Sun, Ju-Xian; Ding, Xin-Yu; Wu, Bin; Li, Wei; Qin, Xiong; Tang, Hua

    2014-12-01

    Operative stabilization is frequently used in the clinical treatment of multiple rib fractures (MRF); however, no ideal material exists for use in this fixation. This study investigates a newly developed biodegradable plate system for the stabilization of MRF. Silk fiber-reinforced polycaprolactone (SF/PCL) plates were developed for rib fracture stabilization and studied using a canine flail chest model. Adult mongrel dogs were divided into three groups: one group received the SF/PCL plates, one group received standard clinical steel plates, and the final group did not undergo operative fracture stabilization (n = 6 for each group). Radiographic, mechanical, and histologic examination was performed to evaluate the effectiveness of the biodegradable material for the stabilization of the rib fractures. No nonunion and no infections were found when using SF-PCL plates. The fracture sites collapsed in the untreated control group, leading to obvious chest wall deformity not encountered in the two groups that underwent operative stabilization. Our experimental study shows that the SF/PCL plate has the biocompatibility and mechanical strength suitable for fixation of MRF and is potentially ideal for the treatment of these injuries. Copyright © 2014 Elsevier Inc. All rights reserved.

  4. Numerical modeling of ductile tearing effects on cleavage fracture toughness

    International Nuclear Information System (INIS)

    Dodds, R.H. Jr.; Tang, M.; Anderson, T.L.

    1994-05-01

    Experimental studies demonstrate a significant effect of specimen size, a/W ratio and prior ductile tearing on cleavage fracture toughness values (J c ) measured in the ductile-to-brittle transition region of ferritic materials. In the lower-transition region, cleavage fracture often occurs under conditions of large-scale yielding but without prior ductile crack extension. The increased toughness develops when plastic zones formed at the crack tip interact with nearby specimen surfaces which relaxes crack-tip constraint (stress triaxiality). In the mid-to-upper transition region, small amounts of ductile crack extension (often c -values. Previous work by the authors described a micromechanics fracture model to correct measured J c -values for the mechanistic effects of large-scale yielding. This new work extends the model to also include the influence of ductile crack extension prior to cleavage. The paper explores development of the new model, provides necessary graphs and procedures for its application and demonstrates the effects of the model on fracture data sets for two pressure vessel steels (A533B and A515)

  5. Modeling of 1D Anomalous Diffusion in Fractured Nanoporous Media

    Directory of Open Access Journals (Sweden)

    Albinali Ali

    2016-07-01

    Full Text Available Fractured nanoporous reservoirs include multi-scale and discontinuous fractures coupled with a complex nanoporous matrix. Such systems cannot be described by the conventional dual-porosity (or multi-porosity idealizations due to the presence of different flow mechanisms at multiple scales. More detailed modeling approaches, such as Discrete Fracture Network (DFN models, similarly suffer from the extensive data requirements dictated by the intricacy of the flow scales, which eventually deter the utility of these models. This paper discusses the utility and construction of 1D analytical and numerical anomalous diffusion models for heterogeneous, nanoporous media, which is commonly encountered in oil and gas production from tight, unconventional reservoirs with fractured horizontal wells. A fractional form of Darcy’s law, which incorporates the non-local and hereditary nature of flow, is coupled with the classical mass conservation equation to derive a fractional diffusion equation in space and time. Results show excellent agreement with established solutions under asymptotic conditions and are consistent with the physical intuitions.

  6. Modeling for mechanical response of CICC by hierarchical approach and ABAQUS simulation

    Energy Technology Data Exchange (ETDEWEB)

    Li, Y.X.; Wang, X.; Gao, Y.W., E-mail: ywgao@lzu.edu.cn; Zhou, Y.H.

    2013-11-15

    Highlights: • We develop an analytical model based on the hierarchical approach of classical wire rope theory. • The numerical model is set up through ABAQUS to verify and enhance the theoretical model. • We calculate two concerned mechanical response: global displacement–load curve and local axial strain distribution. • Elastic–plasticity is the main character in loading curve, and the friction between adjacent strands plays a significant role in the distribution map. -- Abstract: An unexpected degradation frequently occurs in superconducting cable (CICC) due to the mechanical response (deformation) when suffering from electromagnetic load and thermal load during operation. Because of the cable's hierarchical twisted configuration, it is difficult to quantitatively model the mechanical response. In addition, the local mechanical characteristics such as strain distribution could be hardly monitored via experimental method. To address this issue, we develop an analytical model based on the hierarchical approach of classical wire rope theory. This approach follows the algorithm advancing successively from n + 1 stage (e.g. 3 × 3 × 5 subcable) to n stage (e.g. 3 × 3 subcable). There are no complicated numerical procedures required in this model. Meanwhile, the numerical model is set up through ABAQUS to verify and enhance the theoretical model. Subsequently, we calculate two concerned mechanical responses: global displacement–load curve and local axial strain distribution. We find that in the global displacement–load curve, the elastic–plasticity is the main character, and the higher-level cable shows enhanced nonlinear characteristics. As for the local distribution, the friction among adjacent strands plays a significant role in this map. The magnitude of friction strongly influences the regularity of the distribution at different twisted stages. More detailed results are presented in this paper.

  7. Modeling for mechanical response of CICC by hierarchical approach and ABAQUS simulation

    International Nuclear Information System (INIS)

    Li, Y.X.; Wang, X.; Gao, Y.W.; Zhou, Y.H.

    2013-01-01

    Highlights: • We develop an analytical model based on the hierarchical approach of classical wire rope theory. • The numerical model is set up through ABAQUS to verify and enhance the theoretical model. • We calculate two concerned mechanical response: global displacement–load curve and local axial strain distribution. • Elastic–plasticity is the main character in loading curve, and the friction between adjacent strands plays a significant role in the distribution map. -- Abstract: An unexpected degradation frequently occurs in superconducting cable (CICC) due to the mechanical response (deformation) when suffering from electromagnetic load and thermal load during operation. Because of the cable's hierarchical twisted configuration, it is difficult to quantitatively model the mechanical response. In addition, the local mechanical characteristics such as strain distribution could be hardly monitored via experimental method. To address this issue, we develop an analytical model based on the hierarchical approach of classical wire rope theory. This approach follows the algorithm advancing successively from n + 1 stage (e.g. 3 × 3 × 5 subcable) to n stage (e.g. 3 × 3 subcable). There are no complicated numerical procedures required in this model. Meanwhile, the numerical model is set up through ABAQUS to verify and enhance the theoretical model. Subsequently, we calculate two concerned mechanical responses: global displacement–load curve and local axial strain distribution. We find that in the global displacement–load curve, the elastic–plasticity is the main character, and the higher-level cable shows enhanced nonlinear characteristics. As for the local distribution, the friction among adjacent strands plays a significant role in this map. The magnitude of friction strongly influences the regularity of the distribution at different twisted stages. More detailed results are presented in this paper

  8. A sow replacement model using Bayesian updating in a three-level hierarchic Markov process. I. Biological model

    DEFF Research Database (Denmark)

    Kristensen, Anders Ringgaard; Søllested, Thomas Algot

    2004-01-01

    that really uses all these methodological improvements. In this paper, the biological model describing the performance and feed intake of sows is presented. In particular, estimation of herd specific parameters is emphasized. The optimization model is described in a subsequent paper......Several replacement models have been presented in literature. In other applicational areas like dairy cow replacement, various methodological improvements like hierarchical Markov processes and Bayesian updating have been implemented, but not in sow models. Furthermore, there are methodological...... improvements like multi-level hierarchical Markov processes with decisions on multiple time scales, efficient methods for parameter estimations at herd level and standard software that has been hardly implemented at all in any replacement model. The aim of this study is to present a sow replacement model...

  9. A hierarchical modeling methodology for the definition and selection of requirements

    Science.gov (United States)

    Dufresne, Stephane

    This dissertation describes the development of a requirements analysis methodology that takes into account the concept of operations and the hierarchical decomposition of aerospace systems. At the core of the methodology, the Analytic Network Process (ANP) is used to ensure the traceability between the qualitative and quantitative information present in the hierarchical model. The proposed methodology is implemented to the requirements definition of a hurricane tracker Unmanned Aerial Vehicle. Three research objectives are identified in this work; (1) improve the requirements mapping process by matching the stakeholder expectations with the concept of operations, systems and available resources; (2) reduce the epistemic uncertainty surrounding the requirements and requirements mapping; and (3) improve the requirements down-selection process by taking into account the level of importance of the criteria and the available resources. Several challenges are associated with the identification and definition of requirements. The complexity of the system implies that a large number of requirements are needed to define the systems. These requirements are defined early in the conceptual design, where the level of knowledge is relatively low and the level of uncertainty is large. The proposed methodology intends to increase the level of knowledge and reduce the level of uncertainty by guiding the design team through a structured process. To address these challenges, a new methodology is created to flow-down the requirements from the stakeholder expectations to the systems alternatives. A taxonomy of requirements is created to classify the information gathered during the problem definition. Subsequently, the operational and systems functions and measures of effectiveness are integrated to a hierarchical model to allow the traceability of the information. Monte Carlo methods are used to evaluate the variations of the hierarchical model elements and consequently reduce the

  10. Hydraulic Fracturing and Production Optimization in Eagle Ford Shale Using Coupled Geomechanics and Fluid Flow Model

    Science.gov (United States)

    Suppachoknirun, Theerapat; Tutuncu, Azra N.

    2017-12-01

    With increasing production from shale gas and tight oil reservoirs, horizontal drilling and multistage hydraulic fracturing processes have become a routine procedure in unconventional field development efforts. Natural fractures play a critical role in hydraulic fracture growth, subsequently affecting stimulated reservoir volume and the production efficiency. Moreover, the existing fractures can also contribute to the pressure-dependent fluid leak-off during the operations. Hence, a reliable identification of the discrete fracture network covering the zone of interest prior to the hydraulic fracturing design needs to be incorporated into the hydraulic fracturing and reservoir simulations for realistic representation of the in situ reservoir conditions. In this research study, an integrated 3-D fracture and fluid flow model have been developed using a new approach to simulate the fluid flow and deliver reliable production forecasting in naturally fractured and hydraulically stimulated tight reservoirs. The model was created with three key modules. A complex 3-D discrete fracture network model introduces realistic natural fracture geometry with the associated fractured reservoir characteristics. A hydraulic fracturing model is created utilizing the discrete fracture network for simulation of the hydraulic fracture and flow in the complex discrete fracture network. Finally, a reservoir model with the production grid system is used allowing the user to efficiently perform the fluid flow simulation in tight formations with complex fracture networks. The complex discrete natural fracture model, the integrated discrete fracture model for the hydraulic fracturing, the fluid flow model, and the input dataset have been validated against microseismic fracture mapping and commingled production data obtained from a well pad with three horizontal production wells located in the Eagle Ford oil window in south Texas. Two other fracturing geometries were also evaluated to optimize

  11. Hierarchical model generation for architecture reconstruction using laser-scanned point clouds

    Science.gov (United States)

    Ning, Xiaojuan; Wang, Yinghui; Zhang, Xiaopeng

    2014-06-01

    Architecture reconstruction using terrestrial laser scanner is a prevalent and challenging research topic. We introduce an automatic, hierarchical architecture generation framework to produce full geometry of architecture based on a novel combination of facade structures detection, detailed windows propagation, and hierarchical model consolidation. Our method highlights the generation of geometric models automatically fitting the design information of the architecture from sparse, incomplete, and noisy point clouds. First, the planar regions detected in raw point clouds are interpreted as three-dimensional clusters. Then, the boundary of each region extracted by projecting the points into its corresponding two-dimensional plane is classified to obtain detailed shape structure elements (e.g., windows and doors). Finally, a polyhedron model is generated by calculating the proposed local structure model, consolidated structure model, and detailed window model. Experiments on modeling the scanned real-life buildings demonstrate the advantages of our method, in which the reconstructed models not only correspond to the information of architectural design accurately, but also satisfy the requirements for visualization and analysis.

  12. Hierarchical Agent-Based Integrated Modelling Approach for Microgrids with Adoption of EVs and HRES

    Directory of Open Access Journals (Sweden)

    Peng Han

    2014-01-01

    Full Text Available The large adoption of electric vehicles (EVs, hybrid renewable energy systems (HRESs, and the increasing of the loads shall bring significant challenges to the microgrid. The methodology to model microgrid with high EVs and HRESs penetrations is the key to EVs adoption assessment and optimized HRESs deployment. However, considering the complex interactions of the microgrid containing massive EVs and HRESs, any previous single modelling approaches are insufficient. Therefore in this paper, the methodology named Hierarchical Agent-based Integrated Modelling Approach (HAIMA is proposed. With the effective integration of the agent-based modelling with other advanced modelling approaches, the proposed approach theoretically contributes to a new microgrid model hierarchically constituted by microgrid management layer, component layer, and event layer. Then the HAIMA further links the key parameters and interconnects them to achieve the interactions of the whole model. Furthermore, HAIMA practically contributes to a comprehensive microgrid operation system, through which the assessment of the proposed model and the impact of the EVs adoption are achieved. Simulations show that the proposed HAIMA methodology will be beneficial for the microgrid study and EV’s operation assessment and shall be further utilized for the energy management, electricity consumption prediction, the EV scheduling control, and HRES deployment optimization.

  13. An adaptive sampling method for variable-fidelity surrogate models using improved hierarchical kriging

    Science.gov (United States)

    Hu, Jiexiang; Zhou, Qi; Jiang, Ping; Shao, Xinyu; Xie, Tingli

    2018-01-01

    Variable-fidelity (VF) modelling methods have been widely used in complex engineering system design to mitigate the computational burden. Building a VF model generally includes two parts: design of experiments and metamodel construction. In this article, an adaptive sampling method based on improved hierarchical kriging (ASM-IHK) is proposed to refine the improved VF model. First, an improved hierarchical kriging model is developed as the metamodel, in which the low-fidelity model is varied through a polynomial response surface function to capture the characteristics of a high-fidelity model. Secondly, to reduce local approximation errors, an active learning strategy based on a sequential sampling method is introduced to make full use of the already required information on the current sampling points and to guide the sampling process of the high-fidelity model. Finally, two numerical examples and the modelling of the aerodynamic coefficient for an aircraft are provided to demonstrate the approximation capability of the proposed approach, as well as three other metamodelling methods and two sequential sampling methods. The results show that ASM-IHK provides a more accurate metamodel at the same simulation cost, which is very important in metamodel-based engineering design problems.

  14. Numerical research of two-phase flow in fractured-porous media based on discrete fracture fetwork model

    Science.gov (United States)

    Pyatkov, A. A.; Kosyakov, V. P.; Rodionov, S. P.; Botalov, A. Y.

    2018-03-01

    In this work was the study of the processes of isothermal and non-isothermal flow of high viscosity oil in a fractured-porous reservoir. The numerical experiment was done using our own reservoir simulator with the possibility of modeling of fluid motion in conditions of non-isothermal processes and long fractures in the formation.

  15. Dynamic classification of fetal heart rates by hierarchical Dirichlet process mixture models.

    Directory of Open Access Journals (Sweden)

    Kezi Yu

    Full Text Available In this paper, we propose an application of non-parametric Bayesian (NPB models for classification of fetal heart rate (FHR recordings. More specifically, we propose models that are used to differentiate between FHR recordings that are from fetuses with or without adverse outcomes. In our work, we rely on models based on hierarchical Dirichlet processes (HDP and the Chinese restaurant process with finite capacity (CRFC. Two mixture models were inferred from real recordings, one that represents healthy and another, non-healthy fetuses. The models were then used to classify new recordings and provide the probability of the fetus being healthy. First, we compared the classification performance of the HDP models with that of support vector machines on real data and concluded that the HDP models achieved better performance. Then we demonstrated the use of mixture models based on CRFC for dynamic classification of the performance of (FHR recordings in a real-time setting.

  16. HDDM: Hierarchical Bayesian estimation of the Drift-Diffusion Model in Python.

    Science.gov (United States)

    Wiecki, Thomas V; Sofer, Imri; Frank, Michael J

    2013-01-01

    The diffusion model is a commonly used tool to infer latent psychological processes underlying decision-making, and to link them to neural mechanisms based on response times. Although efficient open source software has been made available to quantitatively fit the model to data, current estimation methods require an abundance of response time measurements to recover meaningful parameters, and only provide point estimates of each parameter. In contrast, hierarchical Bayesian parameter estimation methods are useful for enhancing statistical power, allowing for simultaneous estimation of individual subject parameters and the group distribution that they are drawn from, while also providing measures of uncertainty in these parameters in the posterior distribution. Here, we present a novel Python-based toolbox called HDDM (hierarchical drift diffusion model), which allows fast and flexible estimation of the the drift-diffusion model and the related linear ballistic accumulator model. HDDM requires fewer data per subject/condition than non-hierarchical methods, allows for full Bayesian data analysis, and can handle outliers in the data. Finally, HDDM supports the estimation of how trial-by-trial measurements (e.g., fMRI) influence decision-making parameters. This paper will first describe the theoretical background of the drift diffusion model and Bayesian inference. We then illustrate usage of the toolbox on a real-world data set from our lab. Finally, parameter recovery studies show that HDDM beats alternative fitting methods like the χ(2)-quantile method as well as maximum likelihood estimation. The software and documentation can be downloaded at: http://ski.clps.brown.edu/hddm_docs/

  17. HDDM: Hierarchical Bayesian estimation of the Drift-Diffusion Model in Python

    Directory of Open Access Journals (Sweden)

    Thomas V Wiecki

    2013-08-01

    Full Text Available The diffusion model is a commonly used tool to infer latent psychological processes underlying decision making, and to link them to neural mechanisms based on reaction times. Although efficient open source software has been made available to quantitatively fit the model to data, current estimation methods require an abundance of reaction time measurements to recover meaningful parameters, and only provide point estimates of each parameter. In contrast, hierarchical Bayesian parameter estimation methods are useful for enhancing statistical power, allowing for simultaneous estimation of individual subject parameters and the group distribution that they are drawn from, while also providing measures of uncertainty in these parameters in the posterior distribution. Here, we present a novel Python-based toolbox called HDDM (hierarchical drift diffusion model, which allows fast and flexible estimation of the the drift-diffusion model and the related linear ballistic accumulator model. HDDM requires fewer data per subject / condition than non-hierarchical method, allows for full Bayesian data analysis, and can handle outliers in the data. Finally, HDDM supports the estimation of how trial-by-trial measurements (e.g. fMRI influence decision making parameters. This paper will first describe the theoretical background of drift-diffusion model and Bayesian inference. We then illustrate usage of the toolbox on a real-world data set from our lab. Finally, parameter recovery studies show that HDDM beats alternative fitting methods like the chi-quantile method as well as maximum likelihood estimation. The software and documentation can be downloaded at: http://ski.clps.brown.edu/hddm_docs

  18. Modeling of the fracture behavior of spot welds using advanced micro-mechanical damage models

    International Nuclear Information System (INIS)

    Sommer, Silke

    2010-01-01

    This paper presents the modeling of deformation and fracture behavior of resistance spot welded joints in DP600 steel sheets. Spot welding is still the most commonly used joining technique in automotive engineering. In overloading situations like crash joints are often the weakest link in a structure. For those reasons, crash simulations need reliable and applicable tools to predict the load bearing capacity of spot welded components. Two series of component tests with different spot weld diameters have shown that the diameter of the weld nugget is the main influencing factor affecting fracture mode (interfacial or pull-out fracture), load bearing capacity and energy absorption. In order to find a correlation between nugget diameter, load bearing capacity and fracture mode, the spot welds are simulated with detailed finite element models containing base metal, heat affected zone and weld metal in lap-shear loading conditions. The change in fracture mode from interfacial to pull-out or peel-out fracture with growing nugget diameter under lap-shear loading was successfully modeled using the Gologanu-Leblond model in combination with the fracture criteria of Thomason and Embury. A small nugget diameter is identified to be the main cause for interfacial fracture. In good agreement with experimental observations, the calculated pull-out fracture initiates in the base metal at the boundary to the heat affected zone.

  19. Pipe fracture evaluations for leak-rate detection: Probabilistic models

    International Nuclear Information System (INIS)

    Rahman, S.; Wilkowski, G.; Ghadiali, N.

    1993-01-01

    This is the second in series of three papers generated from studies on nuclear pipe fracture evaluations for leak-rate detection. This paper focuses on the development of novel probabilistic models for stochastic performance evaluation of degraded nuclear piping systems. It was accomplished here in three distinct stages. First, a statistical analysis was conducted to characterize various input variables for thermo-hydraulic analysis and elastic-plastic fracture mechanics, such as material properties of pipe, crack morphology variables, and location of cracks found in nuclear piping. Second, a new stochastic model was developed to evaluate performance of degraded piping systems. It is based on accurate deterministic models for thermo-hydraulic and fracture mechanics analyses described in the first paper, statistical characterization of various input variables, and state-of-the-art methods of modem structural reliability theory. From this model. the conditional probability of failure as a function of leak-rate detection capability of the piping systems can be predicted. Third, a numerical example was presented to illustrate the proposed model for piping reliability analyses. Results clearly showed that the model provides satisfactory estimates of conditional failure probability with much less computational effort when compared with those obtained from Monte Carlo simulation. The probabilistic model developed in this paper will be applied to various piping in boiling water reactor and pressurized water reactor plants for leak-rate detection applications

  20. Hierarchical modeling for rare event detection and cell subset alignment across flow cytometry samples.

    Directory of Open Access Journals (Sweden)

    Andrew Cron

    Full Text Available Flow cytometry is the prototypical assay for multi-parameter single cell analysis, and is essential in vaccine and biomarker research for the enumeration of antigen-specific lymphocytes that are often found in extremely low frequencies (0.1% or less. Standard analysis of flow cytometry data relies on visual identification of cell subsets by experts, a process that is subjective and often difficult to reproduce. An alternative and more objective approach is the use of statistical models to identify cell subsets of interest in an automated fashion. Two specific challenges for automated analysis are to detect extremely low frequency event subsets without biasing the estimate by pre-processing enrichment, and the ability to align cell subsets across multiple data samples for comparative analysis. In this manuscript, we develop hierarchical modeling extensions to the Dirichlet Process Gaussian Mixture Model (DPGMM approach we have previously described for cell subset identification, and show that the hierarchical DPGMM (HDPGMM naturally generates an aligned data model that captures both commonalities and variations across multiple samples. HDPGMM also increases the sensitivity to extremely low frequency events by sharing information across multiple samples analyzed simultaneously. We validate the accuracy and reproducibility of HDPGMM estimates of antigen-specific T cells on clinically relevant reference peripheral blood mononuclear cell (PBMC samples with known frequencies of antigen-specific T cells. These cell samples take advantage of retrovirally TCR-transduced T cells spiked into autologous PBMC samples to give a defined number of antigen-specific T cells detectable by HLA-peptide multimer binding. We provide open source software that can take advantage of both multiple processors and GPU-acceleration to perform the numerically-demanding computations. We show that hierarchical modeling is a useful probabilistic approach that can provide a

  1. Hierarchical Models for Type Ia Supernova Light Curves in the Optical and Near Infrared

    Science.gov (United States)

    Mandel, Kaisey; Narayan, G.; Kirshner, R. P.

    2011-01-01

    I have constructed a comprehensive statistical model for Type Ia supernova optical and near infrared light curves. Since the near infrared light curves are excellent standard candles and are less sensitive to dust extinction and reddening, the combination of near infrared and optical data better constrains the host galaxy extinction and improves the precision of distance predictions to SN Ia. A hierarchical probabilistic model coherently accounts for multiple random and uncertain effects, including photometric error, intrinsic supernova light curve variations and correlations across phase and wavelength, dust extinction and reddening, peculiar velocity dispersion and distances. An improved BayeSN MCMC code is implemented for computing probabilistic inferences for individual supernovae and the SN Ia and host galaxy dust populations. I use this hierarchical model to analyze nearby Type Ia supernovae with optical and near infared data from the PAIRITEL, CfA3, and CSP samples and the literature. Using cross-validation to test the robustness of the model predictions, I find that the rms Hubble diagram scatter of predicted distance moduli is 0.11 mag for SN with optical and near infrared data versus 0.15 mag for SN with only optical data. Accounting for the dispersion expected from random peculiar velocities, the rms intrinsic prediction error is 0.08-0.10 mag for SN with both optical and near infrared light curves. I discuss results for the inferred intrinsic correlation structures of the optical-NIR SN Ia light curves and the host galaxy dust distribution captured by the hierarchical model. The continued observation and analysis of Type Ia SN in the optical and near infrared is important for improving their utility as precise and accurate cosmological distance indicators.

  2. A conceptual modeling framework for discrete event simulation using hierarchical control structures.

    Science.gov (United States)

    Furian, N; O'Sullivan, M; Walker, C; Vössner, S; Neubacher, D

    2015-08-01

    Conceptual Modeling (CM) is a fundamental step in a simulation project. Nevertheless, it is only recently that structured approaches towards the definition and formulation of conceptual models have gained importance in the Discrete Event Simulation (DES) community. As a consequence, frameworks and guidelines for applying CM to DES have emerged and discussion of CM for DES is increasing. However, both the organization of model-components and the identification of behavior and system control from standard CM approaches have shortcomings that limit CM's applicability to DES. Therefore, we discuss the different aspects of previous CM frameworks and identify their limitations. Further, we present the Hierarchical Control Conceptual Modeling framework that pays more attention to the identification of a models' system behavior, control policies and dispatching routines and their structured representation within a conceptual model. The framework guides the user step-by-step through the modeling process and is illustrated by a worked example.

  3. Efficient Actor-Critic Algorithm with Hierarchical Model Learning and Planning

    Science.gov (United States)

    Fu, QiMing

    2016-01-01

    To improve the convergence rate and the sample efficiency, two efficient learning methods AC-HMLP and RAC-HMLP (AC-HMLP with ℓ 2-regularization) are proposed by combining actor-critic algorithm with hierarchical model learning and planning. The hierarchical models consisting of the local and the global models, which are learned at the same time during learning of the value function and the policy, are approximated by local linear regression (LLR) and linear function approximation (LFA), respectively. Both the local model and the global model are applied to generate samples for planning; the former is used only if the state-prediction error does not surpass the threshold at each time step, while the latter is utilized at the end of each episode. The purpose of taking both models is to improve the sample efficiency and accelerate the convergence rate of the whole algorithm through fully utilizing the local and global information. Experimentally, AC-HMLP and RAC-HMLP are compared with three representative algorithms on two Reinforcement Learning (RL) benchmark problems. The results demonstrate that they perform best in terms of convergence rate and sample efficiency. PMID:27795704

  4. Computational models of the hydrodynamics of fractured-porous media

    International Nuclear Information System (INIS)

    Grandi, G.M.

    1989-01-01

    The prediction of the flow pattern in fractured-porous media has great importance in the assessment of the local thermohydrological effects of the siting of a nuclear waste repository, among many other technological applications. Computational models must be used due to the complexity of the different phenomena involved which restricts the use of analytical techniques. A new numerical method, based on the boundary-fitted finite-difference technique, is presented in this thesis. The boundaries are external (the boundary of the physical domain), and internal (which correspond to the fracture network). The inclusion of the discrete fracture representation in the volume that represents the porous medium is the difference between the usual approach and the present one. The numerical model has been used in the prediction of the flow pattern in several internationally recognized verification cases and to hypothetical problems of our interest. The results obtained proved that the numerical approach considered gives accurate and reliable predictions of the hydrodynamics of fractured-porous media, allowing its use for the above mentioned studies. (Author) [es

  5. Fracture network modeling and GoldSim simulation support

    International Nuclear Information System (INIS)

    Sugita, Kenichirou; Dershowitz, W.

    2005-01-01

    During Heisei-16, Golder Associates provided support for JNC Tokai through discrete fracture network data analysis and simulation of the Mizunami Underground Research Laboratory (MIU), participation in Task 6 of the AEspoe Task Force on Modeling of Groundwater Flow and Transport, and development of methodologies for analysis of repository site characterization strategies and safety assessment. MIU support during H-16 involved updating the H-15 FracMan discrete fracture network (DFN) models for the MIU shaft region, and developing improved simulation procedures. Updates to the conceptual model included incorporation of 'Step2' (2004) versions of the deterministic structures, and revision of background fractures to be consistent with conductive structure data from the DH-2 borehole. Golder developed improved simulation procedures for these models through the use of hybrid discrete fracture network (DFN), equivalent porous medium (EPM), and nested DFN/EPM approaches. For each of these models, procedures were documented for the entire modeling process including model implementation, MMP simulation, and shaft grouting simulation. Golder supported JNC participation in Task 6AB, 6D and 6E of the AEspoe Task Force on Modeling of Groundwater Flow and Transport during H-16. For Task 6AB, Golder developed a new technique to evaluate the role of grout in performance assessment time-scale transport. For Task 6D, Golder submitted a report of H-15 simulations to SKB. For Task 6E, Golder carried out safety assessment time-scale simulations at the block scale, using the Laplace Transform Galerkin method. During H-16, Golder supported JNC's Total System Performance Assessment (TSPA) strategy by developing technologies for the analysis of the use site characterization data in safety assessment. This approach will aid in the understanding of the use of site characterization to progressively reduce site characterization uncertainty. (author)

  6. Modeling climate effects on hip fracture rate by the multivariate GARCH model in Montreal region, Canada

    Science.gov (United States)

    Modarres, Reza; Ouarda, Taha B. M. J.; Vanasse, Alain; Orzanco, Maria Gabriela; Gosselin, Pierre

    2014-07-01

    Changes in extreme meteorological variables and the demographic shift towards an older population have made it important to investigate the association of climate variables and hip fracture by advanced methods in order to determine the climate variables that most affect hip fracture incidence. The nonlinear autoregressive moving average with exogenous variable-generalized autoregressive conditional heteroscedasticity (ARMA X-GARCH) and multivariate GARCH (MGARCH) time series approaches were applied to investigate the nonlinear association between hip fracture rate in female and male patients aged 40-74 and 75+ years and climate variables in the period of 1993-2004, in Montreal, Canada. The models describe 50-56 % of daily variation in hip fracture rate and identify snow depth, air temperature, day length and air pressure as the influencing variables on the time-varying mean and variance of the hip fracture rate. The conditional covariance between climate variables and hip fracture rate is increasing exponentially, showing that the effect of climate variables on hip fracture rate is most acute when rates are high and climate conditions are at their worst. In Montreal, climate variables, particularly snow depth and air temperature, appear to be important predictors of hip fracture incidence. The association of climate variables and hip fracture does not seem to change linearly with time, but increases exponentially under harsh climate conditions. The results of this study can be used to provide an adaptive climate-related public health program and ti guide allocation of services for avoiding hip fracture risk.

  7. Using outcrop data for geological well test modelling in fractured reservoirs

    NARCIS (Netherlands)

    Aljuboori, F.; Corbett, P.; Bisdom, K.; Bertotti, G.; Geiger, S.

    2015-01-01

    Outcrop fracture data sets can now be acquired with ever more accuracy using drone technology augmented by field observations. These models can be used to form realistic, deterministic models of fractured reservoirs. Fractured well test models are traditionally seen to be finite or infinite

  8. Hierarchical Self Assembly of Patterns from the Robinson Tilings: DNA Tile Design in an Enhanced Tile Assembly Model.

    Science.gov (United States)

    Padilla, Jennifer E; Liu, Wenyan; Seeman, Nadrian C

    2012-06-01

    We introduce a hierarchical self assembly algorithm that produces the quasiperiodic patterns found in the Robinson tilings and suggest a practical implementation of this algorithm using DNA origami tiles. We modify the abstract Tile Assembly Model, (aTAM), to include active signaling and glue activation in response to signals to coordinate the hierarchical assembly of Robinson patterns of arbitrary size from a small set of tiles according to the tile substitution algorithm that generates them. Enabling coordinated hierarchical assembly in the aTAM makes possible the efficient encoding of the recursive process of tile substitution.

  9. TYPE Ia SUPERNOVA LIGHT CURVE INFERENCE: HIERARCHICAL MODELS IN THE OPTICAL AND NEAR-INFRARED

    International Nuclear Information System (INIS)

    Mandel, Kaisey S.; Narayan, Gautham; Kirshner, Robert P.

    2011-01-01

    We have constructed a comprehensive statistical model for Type Ia supernova (SN Ia) light curves spanning optical through near-infrared (NIR) data. A hierarchical framework coherently models multiple random and uncertain effects, including intrinsic supernova (SN) light curve covariances, dust extinction and reddening, and distances. An improved BAYESN Markov Chain Monte Carlo code computes probabilistic inferences for the hierarchical model by sampling the global probability density of parameters describing individual SNe and the population. We have applied this hierarchical model to optical and NIR data of 127 SNe Ia from PAIRITEL, CfA3, Carnegie Supernova Project, and the literature. We find an apparent population correlation between the host galaxy extinction A V and the ratio of total-to-selective dust absorption R V . For SNe with low dust extinction, A V ∼ V ∼ 2.5-2.9, while at high extinctions, A V ∼> 1, low values of R V < 2 are favored. The NIR luminosities are excellent standard candles and are less sensitive to dust extinction. They exhibit low correlation with optical peak luminosities, and thus provide independent information on distances. The combination of NIR and optical data constrains the dust extinction and improves the predictive precision of individual SN Ia distances by about 60%. Using cross-validation, we estimate an rms distance modulus prediction error of 0.11 mag for SNe with optical and NIR data versus 0.15 mag for SNe with optical data alone. Continued study of SNe Ia in the NIR is important for improving their utility as precise and accurate cosmological distance indicators.

  10. Fracture Mechanical Markov Chain Crack Growth Model

    DEFF Research Database (Denmark)

    Gansted, L.; Brincker, Rune; Hansen, Lars Pilegaard

    1991-01-01

    propagation process can be described by a discrete space Markov theory. The model is applicable to deterministic as well as to random loading. Once the model parameters for a given material have been determined, the results can be used for any structure as soon as the geometrical function is known....

  11. Process-based modelling of tree and stand growth: towards a hierarchical treatment of multiscale processes

    International Nuclear Information System (INIS)

    Makela, A.

    2003-01-01

    A generally accepted method has not emerged for managing the different temporal and spatial scales in a forest ecosystem. This paper reviews a hierarchical-modular modelling tradition, with the main focus on individual tree growth throughout the rotation. At this scale, model performance requires (i) realistic long-term dynamic properties, (ii) realistic responses of growth and mortality of competing individuals, and (iii) realistic responses to ecophysio-logical inputs. Model development and validation are illustrated through allocation patterns, height growth, and size-related feedbacks. Empirical work to test the approach is reviewed. In this approach, finer scale effects are embedded in parameters calculated using more detailed, interacting modules. This is exemplified by (i) the within-year effect of weather on annual photosynthesis, (ii) the effects of fast soil processes on carbon allocation and photosynthesis, and (iii) the utilization of detailed stem structure to predict wood quality. Prevailing management paradigms are reflected in growth modelling. A shift of emphasis has occurred from productivity in homogeneous canopies towards, e.g., wood quality versus total yield, spatially more explicit models, and growth decline in old-growth forests. The new problems emphasize the hierarchy of the system and interscale interactions, suggesting that the hierarchical-modular approach could prove constructive. (author)

  12. Hierarchical modeling and robust synthesis for the preliminary design of large scale complex systems

    Science.gov (United States)

    Koch, Patrick Nathan

    Large-scale complex systems are characterized by multiple interacting subsystems and the analysis of multiple disciplines. The design and development of such systems inevitably requires the resolution of multiple conflicting objectives. The size of complex systems, however, prohibits the development of comprehensive system models, and thus these systems must be partitioned into their constituent parts. Because simultaneous solution of individual subsystem models is often not manageable iteration is inevitable and often excessive. In this dissertation these issues are addressed through the development of a method for hierarchical robust preliminary design exploration to facilitate concurrent system and subsystem design exploration, for the concurrent generation of robust system and subsystem specifications for the preliminary design of multi-level, multi-objective, large-scale complex systems. This method is developed through the integration and expansion of current design techniques: (1) Hierarchical partitioning and modeling techniques for partitioning large-scale complex systems into more tractable parts, and allowing integration of subproblems for system synthesis, (2) Statistical experimentation and approximation techniques for increasing both the efficiency and the comprehensiveness of preliminary design exploration, and (3) Noise modeling techniques for implementing robust preliminary design when approximate models are employed. The method developed and associated approaches are illustrated through their application to the preliminary design of a commercial turbofan turbine propulsion system; the turbofan system-level problem is partitioned into engine cycle and configuration design and a compressor module is integrated for more detailed subsystem-level design exploration, improving system evaluation.

  13. A Hierarchical Feature Extraction Model for Multi-Label Mechanical Patent Classification

    Directory of Open Access Journals (Sweden)

    Jie Hu

    2018-01-01

    Full Text Available Various studies have focused on feature extraction methods for automatic patent classification in recent years. However, most of these approaches are based on the knowledge from experts in related domains. Here we propose a hierarchical feature extraction model (HFEM for multi-label mechanical patent classification, which is able to capture both local features of phrases as well as global and temporal semantics. First, a n-gram feature extractor based on convolutional neural networks (CNNs is designed to extract salient local lexical-level features. Next, a long dependency feature extraction model based on the bidirectional long–short-term memory (BiLSTM neural network model is proposed to capture sequential correlations from higher-level sequence representations. Then the HFEM algorithm and its hierarchical feature extraction architecture are detailed. We establish the training, validation and test datasets, containing 72,532, 18,133, and 2679 mechanical patent documents, respectively, and then check the performance of HFEMs. Finally, we compared the results of the proposed HFEM and three other single neural network models, namely CNN, long–short-term memory (LSTM, and BiLSTM. The experimental results indicate that our proposed HFEM outperforms the other compared models in both precision and recall.

  14. A hierarchical bayesian model to quantify uncertainty of stream water temperature forecasts.

    Directory of Open Access Journals (Sweden)

    Guillaume Bal

    Full Text Available Providing generic and cost effective modelling approaches to reconstruct and forecast freshwater temperature using predictors as air temperature and water discharge is a prerequisite to understanding ecological processes underlying the impact of water temperature and of global warming on continental aquatic ecosystems. Using air temperature as a simple linear predictor of water temperature can lead to significant bias in forecasts as it does not disentangle seasonality and long term trends in the signal. Here, we develop an alternative approach based on hierarchical Bayesian statistical time series modelling of water temperature, air temperature and water discharge using seasonal sinusoidal periodic signals and time varying means and amplitudes. Fitting and forecasting performances of this approach are compared with that of simple linear regression between water and air temperatures using i an emotive simulated example, ii application to three French coastal streams with contrasting bio-geographical conditions and sizes. The time series modelling approach better fit data and does not exhibit forecasting bias in long term trends contrary to the linear regression. This new model also allows for more accurate forecasts of water temperature than linear regression together with a fair assessment of the uncertainty around forecasting. Warming of water temperature forecast by our hierarchical Bayesian model was slower and more uncertain than that expected with the classical regression approach. These new forecasts are in a form that is readily usable in further ecological analyses and will allow weighting of outcomes from different scenarios to manage climate change impacts on freshwater wildlife.

  15. A conceptual modeling framework for discrete event simulation using hierarchical control structures

    Science.gov (United States)

    Furian, N.; O’Sullivan, M.; Walker, C.; Vössner, S.; Neubacher, D.

    2015-01-01

    Conceptual Modeling (CM) is a fundamental step in a simulation project. Nevertheless, it is only recently that structured approaches towards the definition and formulation of conceptual models have gained importance in the Discrete Event Simulation (DES) community. As a consequence, frameworks and guidelines for applying CM to DES have emerged and discussion of CM for DES is increasing. However, both the organization of model-components and the identification of behavior and system control from standard CM approaches have shortcomings that limit CM’s applicability to DES. Therefore, we discuss the different aspects of previous CM frameworks and identify their limitations. Further, we present the Hierarchical Control Conceptual Modeling framework that pays more attention to the identification of a models’ system behavior, control policies and dispatching routines and their structured representation within a conceptual model. The framework guides the user step-by-step through the modeling process and is illustrated by a worked example. PMID:26778940

  16. Fracture network modelling: an integrated approach for realisation of complex fracture network geometries

    International Nuclear Information System (INIS)

    Srivastava, R.M.

    2007-01-01

    In its efforts to improve geological support of the safety case, Ontario Power Generation's Deep Geologic Repository Technology Programme (DGRTP) has developed a procedure (Srivastava, 2002) for creating realistic 3-D fracture network models (FNMs) that honor information typically available at the time of preliminary site characterisation: By accommodating all of the these various pieces of 'hard' and 'soft' data, these FNMs provide a single, coherent and consistent model that can serve the needs of many preliminary site characterisation studies. The detailed, complex and realistic models of 3-D fracture geometry produced by this method can serve as the basis for developing rock property models to be used in flow and transport studies. They can also be used for exploring the suitability of a proposed site by providing quantitative assessments of the probability that a proposed repository with a specified geometry will be intersected by fractures. When integrated with state-of-the-art scientific visualisation, these models can also help in the planning of additional data gathering activities by identifying critical fractures that merit further detailed investigation. Finally, these FNMs can serve as one of the central elements of the presentation and explanation of the Descriptive Conceptual Geosphere Model (DCM) to other interested parties, including non-technical audiences. In addition to being ideally suited to preliminary site characterisation, the approach also readily incorporates field data that may become available during subsequent site investigations, including ground reconnaissance, borehole programmes and other subsurface studies. A single approach can therefore serve the needs of the site characterisation from its inception through several years of data collection and more detailed site-specific investigations, accommodating new data as they become available and updating the FNMs accordingly. The FNMs from this method are probabilistic in the sense that

  17. A microstructurally based fracture model for nuclear graphite

    International Nuclear Information System (INIS)

    Burchell, T.D.

    1991-01-01

    This paper reports the physical basis of, and assumptions behind, a fracture model for nuclear graphites. Microstructurally related inputs, such as filler particle size, filler particle fracture toughness (K Ic ), density, pore size distribution, number of pores and specimen geometry (size and volume), are utilized in the model. The model has been applied to two graphites, Great Lakes Carbon Corporation grade H-451 and Toyo Tanso grade IG-110. For each graphite, the predicted tensile failure probabilities are compared with experimental data generated using ASTM Standard C-749 tensile test specimens. The predicted failure probabilities are in close agreement with the experimental data, particularly in the case of the H-451. The model is also shown to qualitatively predict the influence on the failure probabilities of changes in filler particle size, density, pore size, pore size distribution, number of pores and specimen geometry (stressed volume). The good performance is attributed to the sound physical basis of the model, which recognizes the dominant role of porosity in controlling crack initiation and propagation during graphite fracture. 8 refs., 12 figs., 1 tab

  18. Hierarchical modeling of plasma and transport phenomena in a dielectric barrier discharge reactor

    Science.gov (United States)

    Bali, N.; Aggelopoulos, C. A.; Skouras, E. D.; Tsakiroglou, C. D.; Burganos, V. N.

    2017-12-01

    A novel dual-time hierarchical approach is developed to link the plasma process to macroscopic transport phenomena in the interior of a dielectric barrier discharge (DBD) reactor that has been used for soil remediation (Aggelopoulos et al 2016 Chem. Eng. J. 301 353-61). The generation of active species by plasma reactions is simulated at the microseconds (µs) timescale, whereas convection and thermal conduction are simulated at the macroscopic (minutes) timescale. This hierarchical model is implemented in order to investigate the influence of the plasma DBD process on the transport and reaction mechanisms during remediation of polluted soil. In the microscopic model, the variables of interest include the plasma-induced reactive concentrations, while in the macroscopic approach, the temperature distribution, and the velocity field both inside the discharge gap and within the polluted soil material as well. For the latter model, the Navier-Stokes and Darcy Brinkman equations for the transport phenomena in the porous domain are solved numerically using a FEM software. The effective medium theory is employed to provide estimates of the effective time-evolving and three-phase transport properties in the soil sample. Model predictions considering the temporal evolution of the plasma remediation process are presented and compared with corresponding experimental data.

  19. A model of shape memory materials with hierarchical twinning: statics and dynamics

    International Nuclear Information System (INIS)

    Saxena, A.; Bishop, A.R.; Wu, Y.; Lookman, T.

    1995-01-01

    We consider a model of shape memory materials in which hierarchical twinning near the habit plane (austenite-martensite interface) is a new and crucial ingredient. The model includes (1) a triple-well potential (φ 6 model) in local shear strain, (2) strain gradient terms up to second order in strain and fourth order in gradient, and (3) all symmetry allowed compositional fluctuation-induced strain gradient terms. The last term favors hierarchy which enables communication between macroscopic (cm) and microscopic (A) regions essential for shape memory. Hierarchy also stabilizes tweed formation (criss-cross patterns of twins). External stress or pressure modulates (''patterns'') the spacing of domain walls. Therefore the ''pattern'' is encoded in the modulated hierarchical variation of the depth and width of the twins. This hierarchy of length scales provides a related hierarchy of time scales and thus the possibility of non-exponential decay. The four processes of the complete shape memory cycle-write, record, erase and recall-are explained within this model. Preliminary results based on 2D molecular dynamics are shown for tweed and hierarchy formation. (orig.)

  20. Relating Memory To Functional Performance In Normal Aging to Dementia Using Hierarchical Bayesian Cognitive Processing Models

    Science.gov (United States)

    Shankle, William R.; Pooley, James P.; Steyvers, Mark; Hara, Junko; Mangrola, Tushar; Reisberg, Barry; Lee, Michael D.

    2012-01-01

    Determining how cognition affects functional abilities is important in Alzheimer’s disease and related disorders (ADRD). 280 patients (normal or ADRD) received a total of 1,514 assessments using the Functional Assessment Staging Test (FAST) procedure and the MCI Screen (MCIS). A hierarchical Bayesian cognitive processing (HBCP) model was created by embedding a signal detection theory (SDT) model of the MCIS delayed recognition memory task into a hierarchical Bayesian framework. The SDT model used latent parameters of discriminability (memory process) and response bias (executive function) to predict, simultaneously, recognition memory performance for each patient and each FAST severity group. The observed recognition memory data did not distinguish the six FAST severity stages, but the latent parameters completely separated them. The latent parameters were also used successfully to transform the ordinal FAST measure into a continuous measure reflecting the underlying continuum of functional severity. HBCP models applied to recognition memory data from clinical practice settings accurately translated a latent measure of cognition to a continuous measure of functional severity for both individuals and FAST groups. Such a translation links two levels of brain information processing, and may enable more accurate correlations with other levels, such as those characterized by biomarkers. PMID:22407225

  1. Hierarchical Bayesian Markov switching models with application to predicting spawning success of shovelnose sturgeon

    Science.gov (United States)

    Holan, S.H.; Davis, G.M.; Wildhaber, M.L.; DeLonay, A.J.; Papoulias, D.M.

    2009-01-01

    The timing of spawning in fish is tightly linked to environmental factors; however, these factors are not very well understood for many species. Specifically, little information is available to guide recruitment efforts for endangered species such as the sturgeon. Therefore, we propose a Bayesian hierarchical model for predicting the success of spawning of the shovelnose sturgeon which uses both biological and behavioural (longitudinal) data. In particular, we use data that were produced from a tracking study that was conducted in the Lower Missouri River. The data that were produced from this study consist of biological variables associated with readiness to spawn along with longitudinal behavioural data collected by using telemetry and archival data storage tags. These high frequency data are complex both biologically and in the underlying behavioural process. To accommodate such complexity we developed a hierarchical linear regression model that uses an eigenvalue predictor, derived from the transition probability matrix of a two-state Markov switching model with generalized auto-regressive conditional heteroscedastic dynamics. Finally, to minimize the computational burden that is associated with estimation of this model, a parallel computing approach is proposed. ?? Journal compilation 2009 Royal Statistical Society.

  2. Hierarchical Bayesian modelling of gene expression time series across irregularly sampled replicates and clusters.

    Science.gov (United States)

    Hensman, James; Lawrence, Neil D; Rattray, Magnus

    2013-08-20

    Time course data from microarrays and high-throughput sequencing experiments require simple, computationally efficient and powerful statistical models to extract meaningful biological signal, and for tasks such as data fusion and clustering. Existing methodologies fail to capture either the temporal or replicated nature of the experiments, and often impose constraints on the data collection process, such as regularly spaced samples, or similar sampling schema across replications. We propose hierarchical Gaussian processes as a general model of gene expression time-series, with application to a variety of problems. In particular, we illustrate the method's capacity for missing data imputation, data fusion and clustering.The method can impute data which is missing both systematically and at random: in a hold-out test on real data, performance is significantly better than commonly used imputation methods. The method's ability to model inter- and intra-cluster variance leads to more biologically meaningful clusters. The approach removes the necessity for evenly spaced samples, an advantage illustrated on a developmental Drosophila dataset with irregular replications. The hierarchical Gaussian process model provides an excellent statistical basis for several gene-expression time-series tasks. It has only a few additional parameters over a regular GP, has negligible additional complexity, is easily implemented and can be integrated into several existing algorithms. Our experiments were implemented in python, and are available from the authors' website: http://staffwww.dcs.shef.ac.uk/people/J.Hensman/.

  3. Diagnostics for generalized linear hierarchical models in network meta-analysis.

    Science.gov (United States)

    Zhao, Hong; Hodges, James S; Carlin, Bradley P

    2017-09-01

    Network meta-analysis (NMA) combines direct and indirect evidence comparing more than 2 treatments. Inconsistency arises when these 2 information sources differ. Previous work focuses on inconsistency detection, but little has been done on how to proceed after identifying inconsistency. The key issue is whether inconsistency changes an NMA's substantive conclusions. In this paper, we examine such discrepancies from a diagnostic point of view. Our methods seek to detect influential and outlying observations in NMA at a trial-by-arm level. These observations may have a large effect on the parameter estimates in NMA, or they may deviate markedly from other observations. We develop formal diagnostics for a Bayesian hierarchical model to check the effect of deleting any observation. Diagnostics are specified for generalized linear hierarchical NMA models and investigated for both published and simulated datasets. Results from our example dataset using either contrast- or arm-based models and from the simulated datasets indicate that the sources of inconsistency in NMA tend not to be influential, though results from the example dataset suggest that they are likely to be outliers. This mimics a familiar result from linear model theory, in which outliers with low leverage are not influential. Future extensions include incorporating baseline covariates and individual-level patient data. Copyright © 2017 John Wiley & Sons, Ltd.

  4. Hierarchical spatial models for predicting pygmy rabbit distribution and relative abundance

    Science.gov (United States)

    Wilson, T.L.; Odei, J.B.; Hooten, M.B.; Edwards, T.C.

    2010-01-01

    Conservationists routinely use species distribution models to plan conservation, restoration and development actions, while ecologists use them to infer process from pattern. These models tend to work well for common or easily observable species, but are of limited utility for rare and cryptic species. This may be because honest accounting of known observation bias and spatial autocorrelation are rarely included, thereby limiting statistical inference of resulting distribution maps. We specified and implemented a spatially explicit Bayesian hierarchical model for a cryptic mammal species (pygmy rabbit Brachylagus idahoensis). Our approach used two levels of indirect sign that are naturally hierarchical (burrows and faecal pellets) to build a model that allows for inference on regression coefficients as well as spatially explicit model parameters. We also produced maps of rabbit distribution (occupied burrows) and relative abundance (number of burrows expected to be occupied by pygmy rabbits). The model demonstrated statistically rigorous spatial prediction by including spatial autocorrelation and measurement uncertainty. We demonstrated flexibility of our modelling framework by depicting probabilistic distribution predictions using different assumptions of pygmy rabbit habitat requirements. Spatial representations of the variance of posterior predictive distributions were obtained to evaluate heterogeneity in model fit across the spatial domain. Leave-one-out cross-validation was conducted to evaluate the overall model fit. Synthesis and applications. Our method draws on the strengths of previous work, thereby bridging and extending two active areas of ecological research: species distribution models and multi-state occupancy modelling. Our framework can be extended to encompass both larger extents and other species for which direct estimation of abundance is difficult. ?? 2010 The Authors. Journal compilation ?? 2010 British Ecological Society.

  5. A three-dimensional coupled thermo-hydro-mechanical model for deformable fractured geothermal systems

    DEFF Research Database (Denmark)

    Salimzadeh, Saeed; Paluszny, Adriana; Nick, Hamidreza M.

    2018-01-01

    A fully coupled thermal-hydraulic-mechanical (THM) finite element model is presented for fractured geothermal reservoirs. Fractures are modelled as surface discontinuities within a three-dimensional matrix. Non-isothermal flow through the rock matrix and fractures are defined and coupled to a mec......A fully coupled thermal-hydraulic-mechanical (THM) finite element model is presented for fractured geothermal reservoirs. Fractures are modelled as surface discontinuities within a three-dimensional matrix. Non-isothermal flow through the rock matrix and fractures are defined and coupled....... The model has been validated against several analytical solutions, and applied to study the effects of the deformable fractures on the injection of cold water in fractured geothermal systems. Results show that the creation of flow channelling due to the thermal volumetric contraction of the rock matrix...

  6. Estimating effectiveness in HIV prevention trials with a Bayesian hierarchical compound Poisson frailty model

    Science.gov (United States)

    Coley, Rebecca Yates; Browna, Elizabeth R.

    2016-01-01

    Inconsistent results in recent HIV prevention trials of pre-exposure prophylactic interventions may be due to heterogeneity in risk among study participants. Intervention effectiveness is most commonly estimated with the Cox model, which compares event times between populations. When heterogeneity is present, this population-level measure underestimates intervention effectiveness for individuals who are at risk. We propose a likelihood-based Bayesian hierarchical model that estimates the individual-level effectiveness of candidate interventions by accounting for heterogeneity in risk with a compound Poisson-distributed frailty term. This model reflects the mechanisms of HIV risk and allows that some participants are not exposed to HIV and, therefore, have no risk of seroconversion during the study. We assess model performance via simulation and apply the model to data from an HIV prevention trial. PMID:26869051

  7. Hierarchical competition models with the Allee effect II: the case of immigration.

    Science.gov (United States)

    Assas, Laila; Dennis, Brian; Elaydi, Saber; Kwessi, Eddy; Livadiotis, George

    2015-01-01

    This is part II of an earlier paper that dealt with hierarchical models with the Allee effect but with no immigration. In this paper, we greatly simplify the proofs in part I and provide a proof of the global dynamics of the non-hyperbolic cases that were previously conjectured. Then, we show how immigration to one of the species or to both would, drastically, change the dynamics of the system. It is shown that if the level of immigration to one or to both species is above a specified level, then there will be no extinction region where both species go to extinction.

  8. High-accuracy critical exponents for O(N) hierarchical 3D sigma models

    International Nuclear Information System (INIS)

    Godina, J. J.; Li, L.; Meurice, Y.; Oktay, M. B.

    2006-01-01

    The critical exponent γ and its subleading exponent Δ in the 3D O(N) Dyson's hierarchical model for N up to 20 are calculated with high accuracy. We calculate the critical temperatures for the measure δ(φ-vector.φ-vector-1). We extract the first coefficients of the 1/N expansion from our numerical data. We show that the leading and subleading exponents agree with Polchinski equation and the equivalent Litim equation, in the local potential approximation, with at least 4 significant digits

  9. A hierarchical Markov decision process modeling feeding and marketing decisions of growing pigs

    DEFF Research Database (Denmark)

    Pourmoayed, Reza; Nielsen, Lars Relund; Kristensen, Anders Ringgaard

    2016-01-01

    Feeding is the most important cost in the production of growing pigs and has a direct impact on the marketing decisions, growth and the final quality of the meat. In this paper, we address the sequential decision problem of when to change the feed-mix within a finisher pig pen and when to pick pigs...... for marketing. We formulate a hierarchical Markov decision process with three levels representing the decision process. The model considers decisions related to feeding and marketing and finds the optimal decision given the current state of the pen. The state of the system is based on information from on...

  10. An Efficient Upscaling Procedure Based on Stokes-Brinkman Model and Discrete Fracture Network Method for Naturally Fractured Carbonate Karst Reservoirs

    KAUST Repository

    Qin, Guan; Bi, Linfeng; Popov, Peter; Efendiev, Yalchin; Espedal, Magne

    2010-01-01

    , fractures and their interconnectivities in coarse-scale simulation models. In this paper, we present a procedure based on our previously proposed Stokes-Brinkman model (SPE 125593) and the discrete fracture network method for accurate and efficient upscaling

  11. Geological discrete fracture network model for the Laxemar site. Site Descriptive Modelling. SDM-Site Laxemar

    Energy Technology Data Exchange (ETDEWEB)

    La Pointe, Paul; Fox, Aaron (Golder Associates Inc (United States)); Hermanson, Jan; Oehman, Johan (Golder Associates AB, Stockholm (Sweden))

    2008-12-15

    The Swedish Nuclear Fuel and Waste Management Company (SKB) is performing site characterization at two different locations, Forsmark and Laxemar, in order to locate a site for a final geologic repository for spent nuclear fuel. The program is built upon the development of Site Descriptive Models (SDMs) at specific timed data freezes. Each SDM is formed from discipline-specific reports from across the scientific spectrum. This report describes the methods, analyses, and conclusions of the modelling team in the production of the SDM-Site Laxemar geological discrete-fracture network (DFN) model. The DFN builds upon the work of other geological models, including the deformation zone and rock domain models. The geological DFN is a statistical model for stochastically simulating rock fractures and minor deformation zones at a scale of less than 1,000 m (the lower cut-off of the DZ models). The geological DFN is valid within six distinct fracture domains inside the Laxemar local model subarea: FSM{sub C}, FSM{sub E}W007, FSM{sub N}, FSM{sub N}E005, FSM{sub S}, and FSM{sub W}. The models are built using data from detailed surface outcrop maps, geophysical lineament maps, and the cored borehole record at Laxemar. The conceptual model for the SDM-Site Laxemar geological DFN model revolves around the identification of fracture domains based on relative fracture set intensities, orientation clustering, and the regional tectonic framework (including deformation zones). A single coupled fracture size/fracture intensity concept (the Base Model) based on a Pareto (power-law) distribution for fracture sizes was chosen as the recommended parameterisation. A slew of alternative size-intensity models were also carried through the fracture analyses and into the uncertainty and model verification analyses. Uncertainty is modelled by analysing the effects on fracture intensity (P32) that alternative model cases can have. Uncertainty is parameterised as a ratio between the P32 of the

  12. Geological discrete fracture network model for the Laxemar site. Site Descriptive Modelling. SDM-Site Laxemar

    International Nuclear Information System (INIS)

    La Pointe, Paul; Fox, Aaron; Hermanson, Jan; Oehman, Johan

    2008-10-01

    The Swedish Nuclear Fuel and Waste Management Company (SKB) is performing site characterization at two different locations, Forsmark and Laxemar, in order to locate a site for a final geologic repository for spent nuclear fuel. The program is built upon the development of Site Descriptive Models (SDMs) at specific timed data freezes. Each SDM is formed from discipline-specific reports from across the scientific spectrum. This report describes the methods, analyses, and conclusions of the modelling team in the production of the SDM-Site Laxemar geological discrete-fracture network (DFN) model. The DFN builds upon the work of other geological models, including the deformation zone and rock domain models. The geological DFN is a statistical model for stochastically simulating rock fractures and minor deformation zones at a scale of less than 1,000 m (the lower cut-off of the DZ models). The geological DFN is valid within six distinct fracture domains inside the Laxemar local model subarea: FSM C , FSM E W007, FSM N , FSM N E005, FSM S , and FSM W . The models are built using data from detailed surface outcrop maps, geophysical lineament maps, and the cored borehole record at Laxemar. The conceptual model for the SDM-Site Laxemar geological DFN model revolves around the identification of fracture domains based on relative fracture set intensities, orientation clustering, and the regional tectonic framework (including deformation zones). A single coupled fracture size/fracture intensity concept (the Base Model) based on a Pareto (power-law) distribution for fracture sizes was chosen as the recommended parameterisation. A slew of alternative size-intensity models were also carried through the fracture analyses and into the uncertainty and model verification analyses. Uncertainty is modelled by analysing the effects on fracture intensity (P32) that alternative model cases can have. Uncertainty is parameterised as a ratio between the P32 of the alternative model and the P

  13. A nonequilibrium model for reactive contaminant transport through fractured porous media: Model development and semianalytical solution

    Science.gov (United States)

    Joshi, Nitin; Ojha, C. S. P.; Sharma, P. K.

    2012-10-01

    In this study a conceptual model that accounts for the effects of nonequilibrium contaminant transport in a fractured porous media is developed. Present model accounts for both physical and sorption nonequilibrium. Analytical solution was developed using the Laplace transform technique, which was then numerically inverted to obtain solute concentration in the fracture matrix system. The semianalytical solution developed here can incorporate both semi-infinite and finite fracture matrix extent. In addition, the model can account for flexible boundary conditions and nonzero initial condition in the fracture matrix system. The present semianalytical solution was validated against the existing analytical solutions for the fracture matrix system. In order to differentiate between various sorption/transport mechanism different cases of sorption and mass transfer were analyzed by comparing the breakthrough curves and temporal moments. It was found that significant differences in the signature of sorption and mass transfer exists. Applicability of the developed model was evaluated by simulating the published experimental data of Calcium and Strontium transport in a single fracture. The present model simulated the experimental data reasonably well in comparison to the model based on equilibrium sorption assumption in fracture matrix system, and multi rate mass transfer model.

  14. Mesoscale Characterization of Fracture Properties of Steel Fiber-Reinforced Concrete Using a Lattice–Particle Model

    Directory of Open Access Journals (Sweden)

    Francisco Montero-Chacón

    2017-02-01

    Full Text Available This work presents a lattice–particle model for the analysis of steel fiber-reinforced concrete (SFRC. In this approach, fibers are explicitly modeled and connected to the concrete matrix lattice via interface elements. The interface behavior was calibrated by means of pullout tests and a range for the bond properties is proposed. The model was validated with analytical and experimental results under uniaxial tension and compression, demonstrating the ability of the model to correctly describe the effect of fiber volume fraction and distribution on fracture properties of SFRC. The lattice–particle model was integrated into a hierarchical homogenization-based scheme in which macroscopic material parameters are obtained from mesoscale simulations. Moreover, a representative volume element (RVE analysis was carried out and the results shows that such an RVE does exist in the post-peak regime and until localization takes place. Finally, the multiscale upscaling strategy was successfully validated with three-point bending tests.

  15. Mesoscale Characterization of Fracture Properties of Steel Fiber-Reinforced Concrete Using a Lattice-Particle Model.

    Science.gov (United States)

    Montero-Chacón, Francisco; Cifuentes, Héctor; Medina, Fernando

    2017-02-21

    This work presents a lattice-particle model for the analysis of steel fiber-reinforced concrete (SFRC). In this approach, fibers are explicitly modeled and connected to the concrete matrix lattice via interface elements. The interface behavior was calibrated by means of pullout tests and a range for the bond properties is proposed. The model was validated with analytical and experimental results under uniaxial tension and compression, demonstrating the ability of the model to correctly describe the effect of fiber volume fraction and distribution on fracture properties of SFRC. The lattice-particle model was integrated into a hierarchical homogenization-based scheme in which macroscopic material parameters are obtained from mesoscale simulations. Moreover, a representative volume element (RVE) analysis was carried out and the results shows that such an RVE does exist in the post-peak regime and until localization takes place. Finally, the multiscale upscaling strategy was successfully validated with three-point bending tests.

  16. Mesoscale Characterization of Fracture Properties of Steel Fiber-Reinforced Concrete Using a Lattice–Particle Model

    Science.gov (United States)

    Montero-Chacón, Francisco; Cifuentes, Héctor; Medina, Fernando

    2017-01-01

    This work presents a lattice–particle model for the analysis of steel fiber-reinforced concrete (SFRC). In this approach, fibers are explicitly modeled and connected to the concrete matrix lattice via interface elements. The interface behavior was calibrated by means of pullout tests and a range for the bond properties is proposed. The model was validated with analytical and experimental results under uniaxial tension and compression, demonstrating the ability of the model to correctly describe the effect of fiber volume fraction and distribution on fracture properties of SFRC. The lattice–particle model was integrated into a hierarchical homogenization-based scheme in which macroscopic material parameters are obtained from mesoscale simulations. Moreover, a representative volume element (RVE) analysis was carried out and the results shows that such an RVE does exist in the post-peak regime and until localization takes place. Finally, the multiscale upscaling strategy was successfully validated with three-point bending tests. PMID:28772568

  17. Fracture network modeling and GoldSim simulation support

    International Nuclear Information System (INIS)

    Sugita, Kenichiro; Dershowitz, William

    2003-01-01

    During Heisei-14, Golder Associates provided support for JNC Tokai through data analysis and simulation of the MIU Underground Rock Laboratory, participation in Task 6 of the Aespoe Task Force on Modelling of Groundwater Flow and Transport, and analysis of repository safety assessment technologies including cell networks for evaluation of the disturbed rock zone (DRZ) and total systems performance assessment (TSPA). MIU Underground Rock Laboratory support during H-14 involved discrete fracture network (DFN) modelling in support of the Multiple Modelling Project (MMP) and the Long Term Pumping Test (LPT). Golder developed updated DFN models for the MIU site, reflecting updated analyses of fracture data. Golder also developed scripts to support JNC simulations of flow and transport pathways within the MMP. Golder supported JNC participation in Task 6 of the Aespoe Task Force on Modelling of Groundwater Flow and Transport during H-14. Task 6A and 6B compared safety assessment (PA) and experimental time scale simulations along a pipe transport pathway. Task 6B2 extended Task 6B simulations from 1-D to 2-D. For Task 6B2, Golder carried out single fracture transport simulations on a wide variety of generic heterogeneous 2D fractures using both experimental and safety assessment boundary conditions. The heterogeneous 2D fractures were implemented according to a variety of in plane heterogeneity patterns. Multiple immobile zones were considered including stagnant zones, infillings, altered wall rock, and intact rock. During H-14, JNC carried out extensive studies of the distributed rock zone (DRZ) surrounding repository tunnels and drifts. Golder supported this activity be evaluating the calculation time necessary for simulating a reference heterogeneous DRZ cell network for a range of computational strategies. To support the development of JNC's total system performance assessment (TSPA) strategy, Golder carried out a review of the US DOE Yucca Mountain Project TSPA. This

  18. Large-scale model of flow in heterogeneous and hierarchical porous media

    Science.gov (United States)

    Chabanon, Morgan; Valdés-Parada, Francisco J.; Ochoa-Tapia, J. Alberto; Goyeau, Benoît

    2017-11-01

    Heterogeneous porous structures are very often encountered in natural environments, bioremediation processes among many others. Reliable models for momentum transport are crucial whenever mass transport or convective heat occurs in these systems. In this work, we derive a large-scale average model for incompressible single-phase flow in heterogeneous and hierarchical soil porous media composed of two distinct porous regions embedding a solid impermeable structure. The model, based on the local mechanical equilibrium assumption between the porous regions, results in a unique momentum transport equation where the global effective permeability naturally depends on the permeabilities at the intermediate mesoscopic scales and therefore includes the complex hierarchical structure of the soil. The associated closure problem is numerically solved for various configurations and properties of the heterogeneous medium. The results clearly show that the effective permeability increases with the volume fraction of the most permeable porous region. It is also shown that the effective permeability is sensitive to the dimensionality spatial arrangement of the porous regions and in particular depends on the contact between the impermeable solid and the two porous regions.

  19. Evolutionary-Hierarchical Bases of the Formation of Cluster Model of Innovation Economic Development

    Directory of Open Access Journals (Sweden)

    Yuliya Vladimirovna Dubrovskaya

    2016-10-01

    Full Text Available The functioning of a modern economic system is based on the interaction of objects of different hierarchical levels. Thus, the problem of the study of innovation processes taking into account the mutual influence of the activities of these economic actors becomes important. The paper dwells evolutionary basis for the formation of models of innovation development on the basis of micro and macroeconomic analysis. Most of the concepts recognized that despite a big number of diverse models, the coordination of the relations between economic agents is of crucial importance for the successful innovation development. According to the results of the evolutionary-hierarchical analysis, the authors reveal key phases of the development of forms of business cooperation, science and government in the domestic economy. It has become the starting point of the conception of the characteristics of the interaction in the cluster models of innovation development of the economy. Considerable expectancies on improvement of the national innovative system are connected with the development of cluster and network structures. The main objective of government authorities is the formation of mechanisms and institutions that will foster cooperation between members of the clusters. The article explains that the clusters cannot become the factors in the growth of the national economy, not being an effective tool for interaction between the actors of the regional innovative systems.

  20. Bayesian hierarchical model for variations in earthquake peak ground acceleration within small-aperture arrays

    KAUST Repository

    Rahpeyma, Sahar; Halldorsson, Benedikt; Hrafnkelsson, Birgir; Jonsson, Sigurjon

    2018-01-01

    Knowledge of the characteristics of earthquake ground motion is fundamental for earthquake hazard assessments. Over small distances, relative to the source–site distance, where uniform site conditions are expected, the ground motion variability is also expected to be insignificant. However, despite being located on what has been characterized as a uniform lava‐rock site condition, considerable peak ground acceleration (PGA) variations were observed on stations of a small‐aperture array (covering approximately 1 km2) of accelerographs in Southwest Iceland during the Ölfus earthquake of magnitude 6.3 on May 29, 2008 and its sequence of aftershocks. We propose a novel Bayesian hierarchical model for the PGA variations accounting separately for earthquake event effects, station effects, and event‐station effects. An efficient posterior inference scheme based on Markov chain Monte Carlo (MCMC) simulations is proposed for the new model. The variance of the station effect is certainly different from zero according to the posterior density, indicating that individual station effects are different from one another. The Bayesian hierarchical model thus captures the observed PGA variations and quantifies to what extent the source and recording sites contribute to the overall variation in ground motions over relatively small distances on the lava‐rock site condition.

  1. Bayesian hierarchical model for variations in earthquake peak ground acceleration within small-aperture arrays

    KAUST Repository

    Rahpeyma, Sahar

    2018-04-17

    Knowledge of the characteristics of earthquake ground motion is fundamental for earthquake hazard assessments. Over small distances, relative to the source–site distance, where uniform site conditions are expected, the ground motion variability is also expected to be insignificant. However, despite being located on what has been characterized as a uniform lava‐rock site condition, considerable peak ground acceleration (PGA) variations were observed on stations of a small‐aperture array (covering approximately 1 km2) of accelerographs in Southwest Iceland during the Ölfus earthquake of magnitude 6.3 on May 29, 2008 and its sequence of aftershocks. We propose a novel Bayesian hierarchical model for the PGA variations accounting separately for earthquake event effects, station effects, and event‐station effects. An efficient posterior inference scheme based on Markov chain Monte Carlo (MCMC) simulations is proposed for the new model. The variance of the station effect is certainly different from zero according to the posterior density, indicating that individual station effects are different from one another. The Bayesian hierarchical model thus captures the observed PGA variations and quantifies to what extent the source and recording sites contribute to the overall variation in ground motions over relatively small distances on the lava‐rock site condition.

  2. A hierarchical probabilistic model for rapid object categorization in natural scenes.

    Directory of Open Access Journals (Sweden)

    Xiaofu He

    Full Text Available Humans can categorize objects in complex natural scenes within 100-150 ms. This amazing ability of rapid categorization has motivated many computational models. Most of these models require extensive training to obtain a decision boundary in a very high dimensional (e.g., ∼6,000 in a leading model feature space and often categorize objects in natural scenes by categorizing the context that co-occurs with objects when objects do not occupy large portions of the scenes. It is thus unclear how humans achieve rapid scene categorization.To address this issue, we developed a hierarchical probabilistic model for rapid object categorization in natural scenes. In this model, a natural object category is represented by a coarse hierarchical probability distribution (PD, which includes PDs of object geometry and spatial configuration of object parts. Object parts are encoded by PDs of a set of natural object structures, each of which is a concatenation of local object features. Rapid categorization is performed as statistical inference. Since the model uses a very small number (∼100 of structures for even complex object categories such as animals and cars, it requires little training and is robust in the presence of large variations within object categories and in their occurrences in natural scenes. Remarkably, we found that the model categorized animals in natural scenes and cars in street scenes with a near human-level performance. We also found that the model located animals and cars in natural scenes, thus overcoming a flaw in many other models which is to categorize objects in natural context by categorizing contextual features. These results suggest that coarse PDs of object categories based on natural object structures and statistical operations on these PDs may underlie the human ability to rapidly categorize scenes.

  3. Formation of shatter cones by symmetric fracture bifurcation: Phenomenological modeling and validation

    Science.gov (United States)

    Kenkmann, Thomas; Hergarten, Stefan; Kuhn, Thomas; Wilk, Jakob

    2016-08-01

    Several models of shatter cone formation require a heterogeneity at the cone apex of high impedance mismatch to the surrounding bulk rock. This heterogeneity is the source of spherically expanding waves that interact with the planar shock front or the following release wave. While these models are capable of explaining the overall conical shape of shatter cones, they are not capable of explaining the subcone structure and the diverging and branching striations that characterize the surface of shatter cones and lead to the so-called horse-tailing effect. Here, we use the hierarchical arrangement of subcone ridges of shatter cone surfaces as key for understanding their formation. Tracing a single subcone ridge from its apex downward reveals that each ridge branches after some distance into two symmetrically equivalent subcone ridges. This pattern is repeated to form new branches. We propose that subcone ridges represent convex-curved fracture surfaces and their intersection corresponds to the bifurcation axis. The characteristic diverging striations are interpreted as the intersection lineations delimiting each subcone. Multiple symmetric crack branching is the result of rapid fracture propagation that may approach the Raleigh wave speed. We present a phenomenological model that fully constructs the shatter cone geometry to any order. The overall cone geometry including apex angle of the enveloping cone and the degree of concavity (horse-tailing) is largely governed by the convexity of the subcone ridges. Straight cones of various apical angles, constant slope, and constant bifurcation angles form if the subcone convexity is low (30°). Increasing subcone convexity leads to a stronger horse-tailing effect and the bifurcation angles increase with increasing distance from the enveloping cone apex. The model predicts possible triples of enveloping cone angle, bifurcation angle, and subcone angle. Measurements of these quantities on four shatter cones from different

  4. Internal fracture heterogeneity in discrete fracture network modelling: Effect of correlation length and textures with connected and disconnected permeability field

    Science.gov (United States)

    Frampton, A.; Hyman, J.; Zou, L.

    2017-12-01

    Analysing flow and transport in sparsely fractured media is important for understanding how crystalline bedrock environments function as barriers to transport of contaminants, with important applications towards subsurface repositories for storage of spent nuclear fuel. Crystalline bedrocks are particularly favourable due to their geological stability, low advective flow and strong hydrogeochemical retention properties, which can delay transport of radionuclides, allowing decay to limit release to the biosphere. There are however many challenges involved in quantifying and modelling subsurface flow and transport in fractured media, largely due to geological complexity and heterogeneity, where the interplay between advective and dispersive flow strongly impacts both inert and reactive transport. A key to modelling transport in a Lagrangian framework involves quantifying pathway travel times and the hydrodynamic control of retention, and both these quantities strongly depend on heterogeneity of the fracture network at different scales. In this contribution, we present recent analysis of flow and transport considering fracture networks with single-fracture heterogeneity described by different multivariate normal distributions. A coherent triad of fields with identical correlation length and variance are created but which greatly differ in structure, corresponding to textures with well-connected low, medium and high permeability structures. Through numerical modelling of multiple scales in a stochastic setting we quantify the relative impact of texture type and correlation length against network topological measures, and identify key thresholds for cases where flow dispersion is controlled by single-fracture heterogeneity versus network-scale heterogeneity. This is achieved by using a recently developed novel numerical discrete fracture network model. Furthermore, we highlight enhanced flow channelling for cases where correlation structure continues across

  5. New model for surface fracture induced by dynamical stress

    OpenAIRE

    Andersen, J. V.; Lewis, L. J.

    1997-01-01

    We introduce a model where an isotropic, dynamically-imposed stress induces fracture in a thin film. Using molecular dynamics simulations, we study how the integrated fragment distribution function depends on the rate of change and magnitude of the imposed stress, as well as on temperature. A mean-field argument shows that the system becomes unstable for a critical value of the stress. We find a striking invariance of the distribution of fragments for fixed ratio of temperature and rate of ch...

  6. A dust spectral energy distribution model with hierarchical Bayesian inference - I. Formalism and benchmarking

    Science.gov (United States)

    Galliano, Frédéric

    2018-05-01

    This article presents a new dust spectral energy distribution (SED) model, named HerBIE, aimed at eliminating the noise-induced correlations and large scatter obtained when performing least-squares fits. The originality of this code is to apply the hierarchical Bayesian approach to full dust models, including realistic optical properties, stochastic heating, and the mixing of physical conditions in the observed regions. We test the performances of our model by applying it to synthetic observations. We explore the impact on the recovered parameters of several effects: signal-to-noise ratio, SED shape, sample size, the presence of intrinsic correlations, the wavelength coverage, and the use of different SED model components. We show that this method is very efficient: the recovered parameters are consistently distributed around their true values. We do not find any clear bias, even for the most degenerate parameters, or with extreme signal-to-noise ratios.

  7. Merging information from multi-model flood projections in a hierarchical Bayesian framework

    Science.gov (United States)

    Le Vine, Nataliya

    2016-04-01

    Multi-model ensembles are becoming widely accepted for flood frequency change analysis. The use of multiple models results in large uncertainty around estimates of flood magnitudes, due to both uncertainty in model selection and natural variability of river flow. The challenge is therefore to extract the most meaningful signal from the multi-model predictions, accounting for both model quality and uncertainties in individual model estimates. The study demonstrates the potential of a recently proposed hierarchical Bayesian approach to combine information from multiple models. The approach facilitates explicit treatment of shared multi-model discrepancy as well as the probabilistic nature of the flood estimates, by treating the available models as a sample from a hypothetical complete (but unobserved) set of models. The advantages of the approach are: 1) to insure an adequate 'baseline' conditions with which to compare future changes; 2) to reduce flood estimate uncertainty; 3) to maximize use of statistical information in circumstances where multiple weak predictions individually lack power, but collectively provide meaningful information; 4) to adjust multi-model consistency criteria when model biases are large; and 5) to explicitly consider the influence of the (model performance) stationarity assumption. Moreover, the analysis indicates that reducing shared model discrepancy is the key to further reduction of uncertainty in the flood frequency analysis. The findings are of value regarding how conclusions about changing exposure to flooding are drawn, and to flood frequency change attribution studies.

  8. Implicit fracture modelling in FLAC3D: Assessing the behaviour of fractured shales, carbonates and other fractured rock types

    NARCIS (Netherlands)

    Osinga, S.; Pizzocolo, F.; Veer, E.F. van der; Heege, J.H. ter

    2016-01-01

    Fractured rocks play an important role in many types of petroleum and geo-energy operations. From fractured limestone reservoirs to unconventionals, understanding the geomechanical behaviour and the dynamically coupled (dual) permeability system is paramount for optimal development of these systems.

  9. Groundwater modelling for fractured and porous media: HYDROCOIN Level 1

    International Nuclear Information System (INIS)

    Noy, D.J.

    1986-01-01

    The report describes work carried out as part of the 'Hydrocoin' project to verify some of the models used by the British Geological Survey on its radioactive waste disposal programme. The author's work on Hydrocoin Level 1 concerned groundwater modelling for fractured and porous media. The overall conclusions arising from the work were: a) pressure fields in saturated media can be reliably calculated by existing programmes, b) three techniques for deriving the flow fields are described, and c) severe practical limitations exist as to the ability of current programs to model variably saturated conditions over moderate distances. (U.K.)

  10. Fracture network modeling and GoldSim simulation support

    International Nuclear Information System (INIS)

    Sugita, Kenichiro; Dershowitz, William

    2004-01-01

    During Heisei-15, Golder Associates provided support for JNC Tokai through discrete fracture network data analysis and simulation of the MIU Underground Rock Laboratory, participation in Task 6 of the Aespoe Task Force on Modelling of Groundwater Flow and Transport, and development of methodologies for analysis of repository site characterization strategies and safety assessment. MIU Underground Rock Laboratory support during H-15 involved development of new discrete fracture network (DFN) models for the MIU Shoba-sama Site, in the region of shaft development. Golder developed three DFN models for the site using discrete fracture network, equivalent porous medium (EPM), and nested DFN/EPM approaches. Each of these models were compared based upon criteria established for the multiple modeling project (MMP). Golder supported JNC participation in Task 6AB, 6D and 6E of the Aespoe Task Force on Modelling of Groundwater Flow and Transport during H-15. For Task 6AB, Golder implemented an updated microstructural model in GoldSim, and used this updated model to simulate the propagation of uncertainty from experimental to safety assessment time scales, for 5 m scale transport path lengths. Task 6D and 6E compared safety assessment (PA) and experimental time scale simulations in a 200 m scale discrete fracture network. For Task 6D, Golder implemented a DFN model using FracMan/PA Works, and determined the sensitivity of solute transport to a range of material property and geometric assumptions. For Task 6E, Golder carried out demonstration FracMan/PA Works transport calculations at a 1 million year time scale, to ensure that task specifications are realistic. The majority of work for Task 6E will be carried out during H-16. During H-15, Golder supported JNC's Total System Performance Assessment (TSPO) strategy by developing technologies for the analysis of precipitant concentration. These approaches were based on the GoldSim precipitant data management features, and were

  11. Dislocation-free zone model of fracture comparison with experiments

    International Nuclear Information System (INIS)

    Ohr, S.M.; Chang, S.

    1982-01-01

    The dislocation-free zone (DFZ) model of fracture has been extended to study the relationship between the stress intensity factor, extent of plastic deformation, and crack tip geometry of an elastic-plastic crack as a function of applied stress. The results show that the stress intensity factor K decreases from the elastic value at first slowly, then goes rapidly to zero as the number of dislocations in the plastic zone increases. The crack with a zero stress intensity factor has its crack tip stress field completely relaxed by plastic deformation and hence is called a plastic crack. Between the elastic and plastic cracks, a wide range of elastic-plastic cracks having both a stress singularity and a plastic zone are possible. These elastic-plastic cracks with a DFZ are predicted if there is a critical stress intensity factor K/sub g/ required for the generation of dislocations at the crack tip. The expression for K/sub g/ is obtained from the crack tip dislocation nucleation model of Rice and Thomson. In most metals, the magnitude of K/sub g/ is less than the critical stress intensity factor for brittle fracture K/sub c/. The values of K are determined from electron microscope fracture experiments for various metals and they are found to be in good agreement with the K/sub g/ predicted from the model. It is concluded that for most ductile and semibrittle metals, the mechanism of dislocation generation is more important than the fracture surface energy in determining the stress intensity factor at the crack tip

  12. Hierarchical neural network model of the visual system determining figure/ground relation

    Science.gov (United States)

    Kikuchi, Masayuki

    2017-07-01

    One of the most important functions of the visual perception in the brain is figure/ground interpretation from input images. Figural region in 2D image corresponding to object in 3D space are distinguished from background region extended behind the object. Previously the author proposed a neural network model of figure/ground separation constructed on the standpoint that local geometric features such as curvatures and outer angles at corners are extracted and propagated along input contour in a single layer network (Kikuchi & Akashi, 2001). However, such a processing principle has the defect that signal propagation requires manyiterations despite the fact that actual visual system determines figure/ground relation within the short period (Zhou et al., 2000). In order to attain speed-up for determining figure/ground, this study incorporates hierarchical architecture into the previous model. This study confirmed the effect of the hierarchization as for the computation time by simulation. As the number of layers increased, the required computation time reduced. However, such speed-up effect was saturatedas the layers increased to some extent. This study attempted to explain this saturation effect by the notion of average distance between vertices in the area of complex network, and succeeded to mimic the saturation effect by computer simulation.

  13. Toward combining thematic information with hierarchical multiscale segmentations using tree Markov random field model

    Science.gov (United States)

    Zhang, Xueliang; Xiao, Pengfeng; Feng, Xuezhi

    2017-09-01

    It has been a common idea to produce multiscale segmentations to represent the various geographic objects in high-spatial resolution remote sensing (HR) images. However, it remains a great challenge to automatically select the proper segmentation scale(s) just according to the image information. In this study, we propose a novel way of information fusion at object level by combining hierarchical multiscale segmentations with existed thematic information produced by classification or recognition. The tree Markov random field (T-MRF) model is designed for the multiscale combination framework, through which the object type is determined as close as the existed thematic information. At the same time, the object boundary is jointly determined by the thematic labels and the multiscale segments through the minimization of the energy function. The benefits of the proposed T-MRF combination model include: (1) reducing the dependence of segmentation scale selection when utilizing multiscale segmentations; (2) exploring the hierarchical context naturally imbedded in the multiscale segmentations. The HR images in both urban and rural areas are used in the experiments to show the effectiveness of the proposed combination framework on these two aspects.

  14. Empirical Bayes ranking and selection methods via semiparametric hierarchical mixture models in microarray studies.

    Science.gov (United States)

    Noma, Hisashi; Matsui, Shigeyuki

    2013-05-20

    The main purpose of microarray studies is screening of differentially expressed genes as candidates for further investigation. Because of limited resources in this stage, prioritizing genes are relevant statistical tasks in microarray studies. For effective gene selections, parametric empirical Bayes methods for ranking and selection of genes with largest effect sizes have been proposed (Noma et al., 2010; Biostatistics 11: 281-289). The hierarchical mixture model incorporates the differential and non-differential components and allows information borrowing across differential genes with separation from nuisance, non-differential genes. In this article, we develop empirical Bayes ranking methods via a semiparametric hierarchical mixture model. A nonparametric prior distribution, rather than parametric prior distributions, for effect sizes is specified and estimated using the "smoothing by roughening" approach of Laird and Louis (1991; Computational statistics and data analysis 12: 27-37). We present applications to childhood and infant leukemia clinical studies with microarrays for exploring genes related to prognosis or disease progression. Copyright © 2012 John Wiley & Sons, Ltd.

  15. Hierarchical modeling of genome-wide Short Tandem Repeat (STR) markers infers native American prehistory.

    Science.gov (United States)

    Lewis, Cecil M

    2010-02-01

    This study examines a genome-wide dataset of 678 Short Tandem Repeat loci characterized in 444 individuals representing 29 Native American populations as well as the Tundra Netsi and Yakut populations from Siberia. Using these data, the study tests four current hypotheses regarding the hierarchical distribution of neutral genetic variation in native South American populations: (1) the western region of South America harbors more variation than the eastern region of South America, (2) Central American and western South American populations cluster exclusively, (3) populations speaking the Chibchan-Paezan and Equatorial-Tucanoan language stock emerge as a group within an otherwise South American clade, (4) Chibchan-Paezan populations in Central America emerge together at the tips of the Chibchan-Paezan cluster. This study finds that hierarchical models with the best fit place Central American populations, and populations speaking the Chibchan-Paezan language stock, at a basal position or separated from the South American group, which is more consistent with a serial founder effect into South America than that previously described. Western (Andean) South America is found to harbor similar levels of variation as eastern (Equatorial-Tucanoan and Ge-Pano-Carib) South America, which is inconsistent with an initial west coast migration into South America. Moreover, in all relevant models, the estimates of genetic diversity within geographic regions suggest a major bottleneck or founder effect occurring within the North American subcontinent, before the peopling of Central and South America. 2009 Wiley-Liss, Inc.

  16. An approach based on Hierarchical Bayesian Graphical Models for measurement interpretation under uncertainty

    Science.gov (United States)

    Skataric, Maja; Bose, Sandip; Zeroug, Smaine; Tilke, Peter

    2017-02-01

    It is not uncommon in the field of non-destructive evaluation that multiple measurements encompassing a variety of modalities are available for analysis and interpretation for determining the underlying states of nature of the materials or parts being tested. Despite and sometimes due to the richness of data, significant challenges arise in the interpretation manifested as ambiguities and inconsistencies due to various uncertain factors in the physical properties (inputs), environment, measurement device properties, human errors, and the measurement data (outputs). Most of these uncertainties cannot be described by any rigorous mathematical means, and modeling of all possibilities is usually infeasible for many real time applications. In this work, we will discuss an approach based on Hierarchical Bayesian Graphical Models (HBGM) for the improved interpretation of complex (multi-dimensional) problems with parametric uncertainties that lack usable physical models. In this setting, the input space of the physical properties is specified through prior distributions based on domain knowledge and expertise, which are represented as Gaussian mixtures to model the various possible scenarios of interest for non-destructive testing applications. Forward models are then used offline to generate the expected distribution of the proposed measurements which are used to train a hierarchical Bayesian network. In Bayesian analysis, all model parameters are treated as random variables, and inference of the parameters is made on the basis of posterior distribution given the observed data. Learned parameters of the posterior distribution obtained after the training can therefore be used to build an efficient classifier for differentiating new observed data in real time on the basis of pre-trained models. We will illustrate the implementation of the HBGM approach to ultrasonic measurements used for cement evaluation of cased wells in the oil industry.

  17. Fractured reservoir discrete feature network technologies. Final report, March 7, 1996 to September 30, 1998

    Energy Technology Data Exchange (ETDEWEB)

    Dershowitz, William S.; Einstein, Herbert H.; LaPoint, Paul R.; Eiben, Thorsten; Wadleigh, Eugene; Ivanova, Violeta

    1998-12-01

    This report summarizes research conducted for the Fractured Reservoir Discrete Feature Network Technologies Project. The five areas studied are development of hierarchical fracture models; fractured reservoir compartmentalization, block size, and tributary volume analysis; development and demonstration of fractured reservoir discrete feature data analysis tools; development of tools for data integration and reservoir simulation through application of discrete feature network technologies for tertiary oil production; quantitative evaluation of the economic value of this analysis approach.

  18. Bayesian hierarchical models for smoothing in two-phase studies, with application to small area estimation.

    Science.gov (United States)

    Ross, Michelle; Wakefield, Jon

    2015-10-01

    Two-phase study designs are appealing since they allow for the oversampling of rare sub-populations which improves efficiency. In this paper we describe a Bayesian hierarchical model for the analysis of two-phase data. Such a model is particularly appealing in a spatial setting in which random effects are introduced to model between-area variability. In such a situation, one may be interested in estimating regression coefficients or, in the context of small area estimation, in reconstructing the population totals by strata. The efficiency gains of the two-phase sampling scheme are compared to standard approaches using 2011 birth data from the research triangle area of North Carolina. We show that the proposed method can overcome small sample difficulties and improve on existing techniques. We conclude that the two-phase design is an attractive approach for small area estimation.

  19. A Bayesian Hierarchical Model for Relating Multiple SNPs within Multiple Genes to Disease Risk

    Directory of Open Access Journals (Sweden)

    Lewei Duan

    2013-01-01

    Full Text Available A variety of methods have been proposed for studying the association of multiple genes thought to be involved in a common pathway for a particular disease. Here, we present an extension of a Bayesian hierarchical modeling strategy that allows for multiple SNPs within each gene, with external prior information at either the SNP or gene level. The model involves variable selection at the SNP level through latent indicator variables and Bayesian shrinkage at the gene level towards a prior mean vector and covariance matrix that depend on external information. The entire model is fitted using Markov chain Monte Carlo methods. Simulation studies show that the approach is capable of recovering many of the truly causal SNPs and genes, depending upon their frequency and size of their effects. The method is applied to data on 504 SNPs in 38 candidate genes involved in DNA damage response in the WECARE study of second breast cancers in relation to radiotherapy exposure.

  20. Parallel Motion Simulation of Large-Scale Real-Time Crowd in a Hierarchical Environmental Model

    Directory of Open Access Journals (Sweden)

    Xin Wang

    2012-01-01

    Full Text Available This paper presents a parallel real-time crowd simulation method based on a hierarchical environmental model. A dynamical model of the complex environment should be constructed to simulate the state transition and propagation of individual motions. By modeling of a virtual environment where virtual crowds reside, we employ different parallel methods on a topological layer, a path layer and a perceptual layer. We propose a parallel motion path matching method based on the path layer and a parallel crowd simulation method based on the perceptual layer. The large-scale real-time crowd simulation becomes possible with these methods. Numerical experiments are carried out to demonstrate the methods and results.

  1. Statistical methodology for discrete fracture model - including fracture size, orientation uncertainty together with intensity uncertainty and variability

    International Nuclear Information System (INIS)

    Darcel, C.; Davy, P.; Le Goc, R.; Dreuzy, J.R. de; Bour, O.

    2009-11-01

    Investigations led for several years at Laxemar and Forsmark reveal the large heterogeneity of geological formations and associated fracturing. This project aims at reinforcing the statistical DFN modeling framework adapted to a site scale. This leads therefore to develop quantitative methods of characterization adapted to the nature of fracturing and data availability. We start with the hypothesis that the maximum likelihood DFN model is a power-law model with a density term depending on orientations. This is supported both by literature and specifically here by former analyses of the SKB data. This assumption is nevertheless thoroughly tested by analyzing the fracture trace and lineament maps. Fracture traces range roughly between 0.5 m and 10 m - i e the usual extension of the sample outcrops. Between the raw data and final data used to compute the fracture size distribution from which the size distribution model will arise, several steps are necessary, in order to correct data from finite-size, topographical and sampling effects. More precisely, a particular attention is paid to fracture segmentation status and fracture linkage consistent with the DFN model expected. The fracture scaling trend observed over both sites displays finally a shape parameter k t close to 1.2 with a density term (α 2d ) between 1.4 and 1.8. Only two outcrops clearly display a different trend with k t close to 3 and a density term (α 2d ) between 2 and 3.5. The fracture lineaments spread over the range between 100 meters and a few kilometers. When compared with fracture trace maps, these datasets are already interpreted and the linkage process developed previously has not to be done. Except for the subregional lineament map from Forsmark, lineaments display a clear power-law trend with a shape parameter k t equal to 3 and a density term between 2 and 4.5. The apparent variation in scaling exponent, from the outcrop scale (k t = 1.2) on one side, to the lineament scale (k t = 2) on

  2. Linking landscape characteristics to local grizzly bear abundance using multiple detection methods in a hierarchical model

    Science.gov (United States)

    Graves, T.A.; Kendall, Katherine C.; Royle, J. Andrew; Stetz, J.B.; Macleod, A.C.

    2011-01-01

    Few studies link habitat to grizzly bear Ursus arctos abundance and these have not accounted for the variation in detection or spatial autocorrelation. We collected and genotyped bear hair in and around Glacier National Park in northwestern Montana during the summer of 2000. We developed a hierarchical Markov chain Monte Carlo model that extends the existing occupancy and count models by accounting for (1) spatially explicit variables that we hypothesized might influence abundance; (2) separate sub-models of detection probability for two distinct sampling methods (hair traps and rub trees) targeting different segments of the population; (3) covariates to explain variation in each sub-model of detection; (4) a conditional autoregressive term to account for spatial autocorrelation; (5) weights to identify most important variables. Road density and per cent mesic habitat best explained variation in female grizzly bear abundance; spatial autocorrelation was not supported. More female bears were predicted in places with lower road density and with more mesic habitat. Detection rates of females increased with rub tree sampling effort. Road density best explained variation in male grizzly bear abundance and spatial autocorrelation was supported. More male bears were predicted in areas of low road density. Detection rates of males increased with rub tree and hair trap sampling effort and decreased over the sampling period. We provide a new method to (1) incorporate multiple detection methods into hierarchical models of abundance; (2) determine whether spatial autocorrelation should be included in final models. Our results suggest that the influence of landscape variables is consistent between habitat selection and abundance in this system.

  3. Hybrid-dimensional modelling of two-phase flow through fractured porous media with enhanced matrix fracture transmission conditions

    Science.gov (United States)

    Brenner, Konstantin; Hennicker, Julian; Masson, Roland; Samier, Pierre

    2018-03-01

    In this work, we extend, to two-phase flow, the single-phase Darcy flow model proposed in [26], [12] in which the (d - 1)-dimensional flow in the fractures is coupled with the d-dimensional flow in the matrix. Three types of so called hybrid-dimensional two-phase Darcy flow models are proposed. They all account for fractures acting either as drains or as barriers, since they allow pressure jumps at the matrix-fracture interfaces. The models also permit to treat gravity dominated flow as well as discontinuous capillary pressure at the material interfaces. The three models differ by their transmission conditions at matrix fracture interfaces: while the first model accounts for the nonlinear two-phase Darcy flux conservations, the second and third ones are based on the linear single phase Darcy flux conservations combined with different approximations of the mobilities. We adapt the Vertex Approximate Gradient (VAG) scheme to this problem, in order to account for anisotropy and heterogeneity aspects as well as for applicability on general meshes. Several test cases are presented to compare our hybrid-dimensional models to the generic equi-dimensional model, in which fractures have the same dimension as the matrix, leading to deep insight about the quality of the proposed reduced models.

  4. How does aging affect recognition-based inference? A hierarchical Bayesian modeling approach.

    Science.gov (United States)

    Horn, Sebastian S; Pachur, Thorsten; Mata, Rui

    2015-01-01

    The recognition heuristic (RH) is a simple strategy for probabilistic inference according to which recognized objects are judged to score higher on a criterion than unrecognized objects. In this article, a hierarchical Bayesian extension of the multinomial r-model is applied to measure use of the RH on the individual participant level and to re-evaluate differences between younger and older adults' strategy reliance across environments. Further, it is explored how individual r-model parameters relate to alternative measures of the use of recognition and other knowledge, such as adherence rates and indices from signal-detection theory (SDT). Both younger and older adults used the RH substantially more often in an environment with high than low recognition validity, reflecting adaptivity in strategy use across environments. In extension of previous analyses (based on adherence rates), hierarchical modeling revealed that in an environment with low recognition validity, (a) older adults had a stronger tendency than younger adults to rely on the RH and (b) variability in RH use between individuals was larger than in an environment with high recognition validity; variability did not differ between age groups. Further, the r-model parameters correlated moderately with an SDT measure expressing how well people can discriminate cases where the RH leads to a correct vs. incorrect inference; this suggests that the r-model and the SDT measures may offer complementary insights into the use of recognition in decision making. In conclusion, younger and older adults are largely adaptive in their application of the RH, but cognitive aging may be associated with an increased tendency to rely on this strategy. Copyright © 2014 Elsevier B.V. All rights reserved.

  5. Hierarchical Colored Petri Nets for Modeling and Analysis of Transit Signal Priority Control Systems

    Directory of Open Access Journals (Sweden)

    Yisheng An

    2018-01-01

    Full Text Available In this paper, we consider the problem of developing a model for traffic signal control with transit priority using Hierarchical Colored Petri nets (HCPN. Petri nets (PN are useful for state analysis of discrete event systems due to their powerful modeling capability and mathematical formalism. This paper focuses on their use to formalize the transit signal priority (TSP control model. In a four-phase traffic signal control model, the transit detection and two kinds of transit priority strategies are integrated to obtain the HCPN-based TSP control models. One of the advantages to use these models is the clear presentation of traffic light behaviors in terms of conditions and events that cause the detection of a priority request by a transit vehicle. Another advantage of the resulting models is that the correctness and reliability of the proposed strategies are easily analyzed. After their full reachable states are generated, the boundness, liveness, and fairness of the proposed models are verified. Experimental results show that the proposed control model provides transit vehicles with better effectiveness at intersections. This work helps advance the state of the art in the design of signal control models related to the intersection of roadways.

  6. Prion Amplification and Hierarchical Bayesian Modeling Refine Detection of Prion Infection

    Science.gov (United States)

    Wyckoff, A. Christy; Galloway, Nathan; Meyerett-Reid, Crystal; Powers, Jenny; Spraker, Terry; Monello, Ryan J.; Pulford, Bruce; Wild, Margaret; Antolin, Michael; Vercauteren, Kurt; Zabel, Mark

    2015-02-01

    Prions are unique infectious agents that replicate without a genome and cause neurodegenerative diseases that include chronic wasting disease (CWD) of cervids. Immunohistochemistry (IHC) is currently considered the gold standard for diagnosis of a prion infection but may be insensitive to early or sub-clinical CWD that are important to understanding CWD transmission and ecology. We assessed the potential of serial protein misfolding cyclic amplification (sPMCA) to improve detection of CWD prior to the onset of clinical signs. We analyzed tissue samples from free-ranging Rocky Mountain elk (Cervus elaphus nelsoni) and used hierarchical Bayesian analysis to estimate the specificity and sensitivity of IHC and sPMCA conditional on simultaneously estimated disease states. Sensitivity estimates were higher for sPMCA (99.51%, credible interval (CI) 97.15-100%) than IHC of obex (brain stem, 76.56%, CI 57.00-91.46%) or retropharyngeal lymph node (90.06%, CI 74.13-98.70%) tissues, or both (98.99%, CI 90.01-100%). Our hierarchical Bayesian model predicts the prevalence of prion infection in this elk population to be 18.90% (CI 15.50-32.72%), compared to previous estimates of 12.90%. Our data reveal a previously unidentified sub-clinical prion-positive portion of the elk population that could represent silent carriers capable of significantly impacting CWD ecology.

  7. Prion amplification and hierarchical Bayesian modeling refine detection of prion infection.

    Science.gov (United States)

    Wyckoff, A Christy; Galloway, Nathan; Meyerett-Reid, Crystal; Powers, Jenny; Spraker, Terry; Monello, Ryan J; Pulford, Bruce; Wild, Margaret; Antolin, Michael; VerCauteren, Kurt; Zabel, Mark

    2015-02-10

    Prions are unique infectious agents that replicate without a genome and cause neurodegenerative diseases that include chronic wasting disease (CWD) of cervids. Immunohistochemistry (IHC) is currently considered the gold standard for diagnosis of a prion infection but may be insensitive to early or sub-clinical CWD that are important to understanding CWD transmission and ecology. We assessed the potential of serial protein misfolding cyclic amplification (sPMCA) to improve detection of CWD prior to the onset of clinical signs. We analyzed tissue samples from free-ranging Rocky Mountain elk (Cervus elaphus nelsoni) and used hierarchical Bayesian analysis to estimate the specificity and sensitivity of IHC and sPMCA conditional on simultaneously estimated disease states. Sensitivity estimates were higher for sPMCA (99.51%, credible interval (CI) 97.15-100%) than IHC of obex (brain stem, 76.56%, CI 57.00-91.46%) or retropharyngeal lymph node (90.06%, CI 74.13-98.70%) tissues, or both (98.99%, CI 90.01-100%). Our hierarchical Bayesian model predicts the prevalence of prion infection in this elk population to be 18.90% (CI 15.50-32.72%), compared to previous estimates of 12.90%. Our data reveal a previously unidentified sub-clinical prion-positive portion of the elk population that could represent silent carriers capable of significantly impacting CWD ecology.

  8. Multilevel Hierarchical Modeling of Benthic Macroinvertebrate Responses to Urbanization in Nine Metropolitan Regions across the Conterminous United States

    Science.gov (United States)

    Kashuba, Roxolana; Cha, YoonKyung; Alameddine, Ibrahim; Lee, Boknam; Cuffney, Thomas F.

    2010-01-01

    Multilevel hierarchical modeling methodology has been developed for use in ecological data analysis. The effect of urbanization on stream macroinvertebrate communities was measured across a gradient of basins in each of nine metropolitan regions across the conterminous United States. The hierarchical nature of this dataset was harnessed in a multi-tiered model structure, predicting both invertebrate response at the basin scale and differences in invertebrate response at the region scale. Ordination site scores, total taxa richness, Ephemeroptera, Plecoptera, Trichoptera (EPT) taxa richness, and richness-weighted mean tolerance of organisms at a site were used to describe invertebrate responses. Percentage of urban land cover was used as a basin-level predictor variable. Regional mean precipitation, air temperature, and antecedent agriculture were used as region-level predictor variables. Multilevel hierarchical models were fit to both levels of data simultaneously, borrowing statistical strength from the complete dataset to reduce uncertainty in regional coefficient estimates. Additionally, whereas non-hierarchical regressions were only able to show differing relations between invertebrate responses and urban intensity separately for each region, the multilevel hierarchical regressions were able to explain and quantify those differences within a single model. In this way, this modeling approach directly establishes the importance of antecedent agricultural conditions in masking the response of invertebrates to urbanization in metropolitan regions such as Milwaukee-Green Bay, Wisconsin; Denver, Colorado; and Dallas-Fort Worth, Texas. Also, these models show that regions with high precipitation, such as Atlanta, Georgia; Birmingham, Alabama; and Portland, Oregon, start out with better regional background conditions of invertebrates prior to urbanization but experience faster negative rates of change with urbanization. Ultimately, this urbanization

  9. Computational Modelling of Fracture Propagation in Rocks Using a Coupled Elastic-Plasticity-Damage Model

    Directory of Open Access Journals (Sweden)

    Isa Kolo

    2016-01-01

    Full Text Available A coupled elastic-plasticity-damage constitutive model, AK Model, is applied to predict fracture propagation in rocks. The quasi-brittle material model captures anisotropic effects and the distinct behavior of rocks in tension and compression. Calibration of the constitutive model is realized using experimental data for Carrara marble. Through the Weibull distribution function, heterogeneity effect is captured by spatially varying the elastic properties of the rock. Favorable comparison between model predictions and experiments for single-flawed specimens reveal that the AK Model is reliable and accurate for modelling fracture propagation in rocks.

  10. Epigenetic change detection and pattern recognition via Bayesian hierarchical hidden Markov models.

    Science.gov (United States)

    Wang, Xinlei; Zang, Miao; Xiao, Guanghua

    2013-06-15

    Epigenetics is the study of changes to the genome that can switch genes on or off and determine which proteins are transcribed without altering the DNA sequence. Recently, epigenetic changes have been linked to the development and progression of disease such as psychiatric disorders. High-throughput epigenetic experiments have enabled researchers to measure genome-wide epigenetic profiles and yield data consisting of intensity ratios of immunoprecipitation versus reference samples. The intensity ratios can provide a view of genomic regions where protein binding occur under one experimental condition and further allow us to detect epigenetic alterations through comparison between two different conditions. However, such experiments can be expensive, with only a few replicates available. Moreover, epigenetic data are often spatially correlated with high noise levels. In this paper, we develop a Bayesian hierarchical model, combined with hidden Markov processes with four states for modeling spatial dependence, to detect genomic sites with epigenetic changes from two-sample experiments with paired internal control. One attractive feature of the proposed method is that the four states of the hidden Markov process have well-defined biological meanings and allow us to directly call the change patterns based on the corresponding posterior probabilities. In contrast, none of existing methods can offer this advantage. In addition, the proposed method offers great power in statistical inference by spatial smoothing (via hidden Markov modeling) and information pooling (via hierarchical modeling). Both simulation studies and real data analysis in a cocaine addiction study illustrate the reliability and success of this method. Copyright © 2012 John Wiley & Sons, Ltd.

  11. Investigation of translaminar fracture in fibrereinforced composite laminates---applicability of linear elastic fracture mechanics and cohesive-zone model

    Science.gov (United States)

    Hou, Fang

    With the extensive application of fiber-reinforced composite laminates in industry, research on the fracture mechanisms of this type of materials have drawn more and more attentions. A variety of fracture theories and models have been developed. Among them, the linear elastic fracture mechanics (LEFM) and cohesive-zone model (CZM) are two widely-accepted fracture models, which have already shown applicability in the fracture analysis of fiber-reinforced composite laminates. However, there remain challenges which prevent further applications of the two fracture models, such as the experimental measurement of fracture resistance. This dissertation primarily focused on the study of the applicability of LEFM and CZM for the fracture analysis of translaminar fracture in fibre-reinforced composite laminates. The research for each fracture model consisted of two sections: the analytical characterization of crack-tip fields and the experimental measurement of fracture resistance parameters. In the study of LEFM, an experimental investigation based on full-field crack-tip displacement measurements was carried out as a way to characterize the subcritical and steady-state crack advances in translaminar fracture of fiber-reinforced composite laminates. Here, the fiber-reinforced composite laminates were approximated as anisotropic solids. The experimental investigation relied on the LEFM theory with a modification with respect to the material anisotropy. Firstly, the full-field crack-tip displacement fields were measured by Digital Image Correlation (DIC). Then two methods, separately based on the stress intensity approach and the energy approach, were developed to measure the crack-tip field parameters from crack-tip displacement fields. The studied crack-tip field parameters included the stress intensity factor, energy release rate and effective crack length. Moreover, the crack-growth resistance curves (R-curves) were constructed with the measured crack-tip field parameters

  12. Hierarchical modeling of bycatch rates of sea turtles in the western North Atlantic

    Science.gov (United States)

    Gardner, B.; Sullivan, P.J.; Epperly, S.; Morreale, S.J.

    2008-01-01

    Previous studies indicate that the locations of the endangered loggerhead Caretta caretta and critically endangered leatherback Dermochelys coriacea sea turtles are influenced by water temperatures, and that incidental catch rates in the pelagic longline fishery vary by region. We present a Bayesian hierarchical model to examine the effects of environmental variables, including water temperature, on the number of sea turtles captured in the US pelagic longline fishery in the western North Atlantic. The modeling structure is highly flexible, utilizes a Bayesian model selection technique, and is fully implemented in the software program WinBUGS. The number of sea turtles captured is modeled as a zero-inflated Poisson distribution and the model incorporates fixed effects to examine region-specific differences in the parameter estimates. Results indicate that water temperature, region, bottom depth, and target species are all significant predictors of the number of loggerhead sea turtles captured. For leatherback sea turtles, the model with only target species had the most posterior model weight, though a re-parameterization of the model indicates that temperature influences the zero-inflation parameter. The relationship between the number of sea turtles captured and the variables of interest all varied by region. This suggests that management decisions aimed at reducing sea turtle bycatch may be more effective if they are spatially explicit. ?? Inter-Research 2008.

  13. A hierarchical updating method for finite element model of airbag buffer system under landing impact

    Directory of Open Access Journals (Sweden)

    He Huan

    2015-12-01

    Full Text Available In this paper, we propose an impact finite element (FE model for an airbag landing buffer system. First, an impact FE model has been formulated for a typical airbag landing buffer system. We use the independence of the structure FE model from the full impact FE model to develop a hierarchical updating scheme for the recovery module FE model and the airbag system FE model. Second, we define impact responses at key points to compare the computational and experimental results to resolve the inconsistency between the experimental data sampling frequency and experimental triggering. To determine the typical characteristics of the impact dynamics response of the airbag landing buffer system, we present the impact response confidence factors (IRCFs to evaluate how consistent the computational and experiment results are. An error function is defined between the experimental and computational results at key points of the impact response (KPIR to serve as a modified objective function. A radial basis function (RBF is introduced to construct updating variables for a surrogate model for updating the objective function, thereby converting the FE model updating problem to a soluble optimization problem. Finally, the developed method has been validated using an experimental and computational study on the impact dynamics of a classic airbag landing buffer system.

  14. Parameterization of aquatic ecosystem functioning and its natural variation: Hierarchical Bayesian modelling of plankton food web dynamics

    Science.gov (United States)

    Norros, Veera; Laine, Marko; Lignell, Risto; Thingstad, Frede

    2017-10-01

    Methods for extracting empirically and theoretically sound parameter values are urgently needed in aquatic ecosystem modelling to describe key flows and their variation in the system. Here, we compare three Bayesian formulations for mechanistic model parameterization that differ in their assumptions about the variation in parameter values between various datasets: 1) global analysis - no variation, 2) separate analysis - independent variation and 3) hierarchical analysis - variation arising from a shared distribution defined by hyperparameters. We tested these methods, using computer-generated and empirical data, coupled with simplified and reasonably realistic plankton food web models, respectively. While all methods were adequate, the simulated example demonstrated that a well-designed hierarchical analysis can result in the most accurate and precise parameter estimates and predictions, due to its ability to combine information across datasets. However, our results also highlighted sensitivity to hyperparameter prior distributions as an important caveat of hierarchical analysis. In the more complex empirical example, hierarchical analysis was able to combine precise identification of parameter values with reasonably good predictive performance, although the ranking of the methods was less straightforward. We conclude that hierarchical Bayesian analysis is a promising tool for identifying key ecosystem-functioning parameters and their variation from empirical datasets.

  15. Geological discrete-fracture network model (version 1) for the Olkiluoto site, Finland

    International Nuclear Information System (INIS)

    Fox, A.; Buoro, A.; Dahlbo, K.; Wiren, L.

    2009-10-01

    This report describes the methods, analyses, and conclusions of the modelling team in the production of a discrete-fracture network (DFN) model for the Olkiluoto Site in Finland. The geological DFN is a statistical model for stochastically simulating rock fractures and minor faults at a scale ranging from approximately 0.05 m to approximately 500 m; an upper scale limit is not expressly defined, but the DFN model explicitly excludes structures at deformation-zone scales (∼ 500 m) and larger. The DFN model is presented as a series of tables summarizing probability distributions for several parameters necessary for fracture modelling: fracture orientation, fracture size, fracture intensity, and associated spatial constraints. The geological DFN is built from data collected during site characterization (SC) activities at Olkiluoto, which is currently planned to function as a final deep geological repository for spent fuel and nuclear waste from the Finnish nuclear power program. Data used in the DFN analyses include fracture maps from surface outcrops and trenches (as of July 2007), geological and structural data from cored boreholes (as of July 2007), and fracture information collected during the construction of the main tunnels and shafts at the ONKALO laboratory (January 2008). The modelling results suggest that the rock volume at Olkiluoto surrounding the ONKALO tunnel can be separated into three distinct volumes (fracture domains): an upper block, an intermediate block, and a lower block. The three fracture domains are bounded horizontally and vertically by large deformation zones. Fracture properties, such as fracture orientation and relative orientation set intensity, vary between fracture domains. The rock volume at Olkiluoto is dominated by three distinct fracture sets: subhorizontally-dipping fractures striking north-northeast and dipping to the east, a subvertically-dipping fracture set striking roughly north-south, and a subverticallydipping fracture set

  16. Using hierarchical linear growth models to evaluate protective mechanisms that mediate science achievement

    Science.gov (United States)

    von Secker, Clare Elaine

    The study of students at risk is a major topic of science education policy and discussion. Much research has focused on describing conditions and problems associated with the statistical risk of low science achievement among individuals who are members of groups characterized by problems such as poverty and social disadvantage. But outcomes attributed to these factors do not explain the nature and extent of mechanisms that account for differences in performance among individuals at risk. There is ample theoretical and empirical evidence that demographic differences should be conceptualized as social contexts, or collections of variables, that alter the psychological significance and social demands of life events, and affect subsequent relationships between risk and resilience. The hierarchical linear growth models used in this dissertation provide greater specification of the role of social context and the protective effects of attitude, expectations, parenting practices, peer influences, and learning opportunities on science achievement. While the individual influences of these protective factors on science achievement were small, their cumulative effect was substantial. Meta-analysis conducted on the effects associated with psychological and environmental processes that mediate risk mechanisms in sixteen social contexts revealed twenty-two significant differences between groups of students. Positive attitudes, high expectations, and more intense science course-taking had positive effects on achievement of all students, although these factors were not equally protective in all social contexts. In general, effects associated with authoritative parenting and peer influences were negative, regardless of social context. An evaluation comparing the performance and stability of hierarchical linear growth models with traditional repeated measures models is included as well.

  17. An Integrated Risk Index Model Based on Hierarchical Fuzzy Logic for Underground Risk Assessment

    Directory of Open Access Journals (Sweden)

    Muhammad Fayaz

    2017-10-01

    Full Text Available Available space in congested cities is getting scarce due to growing urbanization in the recent past. The utilization of underground space is considered as a solution to the limited space in smart cities. The numbers of underground facilities are growing day by day in the developing world. Typical underground facilities include the transit subway, parking lots, electric lines, water supply and sewer lines. The likelihood of the occurrence of accidents due to underground facilities is a random phenomenon. To avoid any accidental loss, a risk assessment method is required to conduct the continuous risk assessment and report any abnormality before it happens. In this paper, we have proposed a hierarchical fuzzy inference based model for under-ground risk assessment. The proposed hierarchical fuzzy inference architecture reduces the total number of rules from the rule base. Rule reduction is important because the curse of dimensionality damages the transparency and interpretation as it is very tough to understand and justify hundreds or thousands of fuzzy rules. The computation time also increases as rules increase. The proposed model takes 175 rules having eight input parameters to compute the risk index, and the conventional fuzzy logic requires 390,625 rules, having the same number of input parameters to compute risk index. Hence, the proposed model significantly reduces the curse of dimensionality. Rule design for fuzzy logic is also a tedious task. In this paper, we have also introduced new rule schemes, namely maximum rule-based and average rule-based; both schemes can be used interchangeably according to the logic needed for rule design. The experimental results show that the proposed method is a virtuous choice for risk index calculation where the numbers of variables are greater.

  18. Spatial patterns of breeding success of grizzly bears derived from hierarchical multistate models.

    Science.gov (United States)

    Fisher, Jason T; Wheatley, Matthew; Mackenzie, Darryl

    2014-10-01

    Conservation programs often manage populations indirectly through the landscapes in which they live. Empirically, linking reproductive success with landscape structure and anthropogenic change is a first step in understanding and managing the spatial mechanisms that affect reproduction, but this link is not sufficiently informed by data. Hierarchical multistate occupancy models can forge these links by estimating spatial patterns of reproductive success across landscapes. To illustrate, we surveyed the occurrence of grizzly bears (Ursus arctos) in the Canadian Rocky Mountains Alberta, Canada. We deployed camera traps for 6 weeks at 54 surveys sites in different types of land cover. We used hierarchical multistate occupancy models to estimate probability of detection, grizzly bear occupancy, and probability of reproductive success at each site. Grizzly bear occupancy varied among cover types and was greater in herbaceous alpine ecotones than in low-elevation wetlands or mid-elevation conifer forests. The conditional probability of reproductive success given grizzly bear occupancy was 30% (SE = 0.14). Grizzly bears with cubs had a higher probability of detection than grizzly bears without cubs, but sites were correctly classified as being occupied by breeding females 49% of the time based on raw data and thus would have been underestimated by half. Repeated surveys and multistate modeling reduced the probability of misclassifying sites occupied by breeders as unoccupied to <2%. The probability of breeding grizzly bear occupancy varied across the landscape. Those patches with highest probabilities of breeding occupancy-herbaceous alpine ecotones-were small and highly dispersed and are projected to shrink as treelines advance due to climate warming. Understanding spatial correlates in breeding distribution is a key requirement for species conservation in the face of climate change and can help identify priorities for landscape management and protection. © 2014 Society

  19. A new equi-dimensional fracture model using polyhedral cells for microseismic data sets

    KAUST Repository

    Al-Hinai, Omar

    2017-04-09

    We present a method for modeling flow in porous media in the presence of complex fracture networks. The approach utilizes the Mimetic Finite Difference (MFD) method. We employ a novel equi-dimensional approach for meshing fractures. By using polyhedral cells we avoid the common challenge in equi-dimensional fracture modeling of creating small cells at the intersection point. We also demonstrate how polyhedra can mesh complex fractures without introducing a large number of cells. We use polyhedra and the MFD method a second time for embedding fracture boundaries in the matrix domain using a “cut-cell” paradigm. The embedding approach has the advantage of being simple and localizes irregular cells to the area around the fractures. It also circumvents the need for conventional mesh generation, which can be challenging when applied to complex fracture geometries. We present numerical results confirming the validity of our approach for complex fracture networks and for different flow models. In our first example, we compare our method to the popular dual-porosity technique. Our second example compares our method with directly meshed fractures (single-porosity) for two-phase flow. The third example demonstrates two-phase flow for the case of intersecting ellipsoid fractures in three-dimensions, which are typical in microseismic analysis of fractures. Finally, we demonstrate our method on a two-dimensional fracture network produced from microseismic field data.

  20. A new equi-dimensional fracture model using polyhedral cells for microseismic data sets

    KAUST Repository

    Al-Hinai, Omar; Dong, Rencheng; Srinivasan, Sanjay; Wheeler, Mary F.

    2017-01-01

    We present a method for modeling flow in porous media in the presence of complex fracture networks. The approach utilizes the Mimetic Finite Difference (MFD) method. We employ a novel equi-dimensional approach for meshing fractures. By using polyhedral cells we avoid the common challenge in equi-dimensional fracture modeling of creating small cells at the intersection point. We also demonstrate how polyhedra can mesh complex fractures without introducing a large number of cells. We use polyhedra and the MFD method a second time for embedding fracture boundaries in the matrix domain using a “cut-cell” paradigm. The embedding approach has the advantage of being simple and localizes irregular cells to the area around the fractures. It also circumvents the need for conventional mesh generation, which can be challenging when applied to complex fracture geometries. We present numerical results confirming the validity of our approach for complex fracture networks and for different flow models. In our first example, we compare our method to the popular dual-porosity technique. Our second example compares our method with directly meshed fractures (single-porosity) for two-phase flow. The third example demonstrates two-phase flow for the case of intersecting ellipsoid fractures in three-dimensions, which are typical in microseismic analysis of fractures. Finally, we demonstrate our method on a two-dimensional fracture network produced from microseismic field data.

  1. Continuous and Discontinuous Modelling of Fracture in Concrete Using FEM

    CERN Document Server

    Tejchman, Jacek

    2013-01-01

    The book analyzes a quasi-static fracture process in concrete and reinforced concrete by means of constitutive models formulated within continuum mechanics. A continuous and discontinuous modelling approach was used. Using a continuous approach, numerical analyses were performed using a finite element method and three different enhanced continuum models: isotropic elasto-plastic, isotropic damage and anisotropic smeared crack one. The models were equipped with a characteristic length of micro-structure by means of a non-local and a second-gradient theory. So they could properly describe the formation of localized zones with a certain thickness and spacing and a related deterministic size effect. Using a discontinuous FE approach, numerical results of cracks using a cohesive crack model and XFEM were presented which were also properly regularized. Finite element analyses were performed with concrete elements under monotonic uniaxial compression, uniaxial tension, bending and shear-extension. Concrete beams un...

  2. Research program to develop and validate conceptual models for flow and transport through unsaturated, fractured rock

    International Nuclear Information System (INIS)

    Glass, R.J.; Tidwell, V.C.

    1991-09-01

    As part of the Yucca Mountain Project, our research program to develop and validate conceptual models for flow and transport through unsaturated fractured rock integrates fundamental physical experimentation with conceptual model formulation and mathematical modeling. Our research is directed toward developing and validating macroscopic, continuum-based models and supporting effective property models because of their widespread utility within the context of this project. Success relative to the development and validation of effective property models is predicted on a firm understanding of the basic physics governing flow through fractured media, specifically in the areas of unsaturated flow and transport in a single fracture and fracture-matrix interaction

  3. Research program to develop and validate conceptual models for flow and transport through unsaturated, fractured rock

    International Nuclear Information System (INIS)

    Glass, R.J.; Tidwell, V.C.

    1991-01-01

    As part of the Yucca Mountain Project, our research program to develop and validate conceptual models for flow and transport through unsaturated fractured rock integrates fundamental physical experimentation with conceptual model formulation and mathematical modeling. Our research is directed toward developing and validating macroscopic, continuum-based models and supporting effective property models because of their widespread utility within the context of this project. Success relative to the development and validation of effective property models is predicated on a firm understanding of the basic physics governing flow through fractured media, specifically in the areas of unsaturated flow and transport in a single fracture and fracture-matrix interaction. 43 refs

  4. Research program to develop and validate conceptual models for flow and transport through unsaturated, fractured rock

    International Nuclear Information System (INIS)

    Glass, R.J.; Tidwell, V.C.

    1991-01-01

    As part of the Yucca Mountain Project, our research program to develop and validate conceptual models for flow and transport through unsaturated fractured rock integrates fundamental physical experimentation with conceptual model formulation and mathematical modeling. Our research is directed toward developing and validating macroscopic, continuum-based models and supporting effective property models because of their widespread utility within the context of this project. Success relative to the development and validation of effective property models is predicted on a firm understanding of the basic physics governing flow through fractured media, specifically in the areas of unsaturated flow and transport in a single fracture and fracture-matrix interaction

  5. Reduced Rank Mixed Effects Models for Spatially Correlated Hierarchical Functional Data

    KAUST Repository

    Zhou, Lan

    2010-03-01

    Hierarchical functional data are widely seen in complex studies where sub-units are nested within units, which in turn are nested within treatment groups. We propose a general framework of functional mixed effects model for such data: within unit and within sub-unit variations are modeled through two separate sets of principal components; the sub-unit level functions are allowed to be correlated. Penalized splines are used to model both the mean functions and the principal components functions, where roughness penalties are used to regularize the spline fit. An EM algorithm is developed to fit the model, while the specific covariance structure of the model is utilized for computational efficiency to avoid storage and inversion of large matrices. Our dimension reduction with principal components provides an effective solution to the difficult tasks of modeling the covariance kernel of a random function and modeling the correlation between functions. The proposed methodology is illustrated using simulations and an empirical data set from a colon carcinogenesis study. Supplemental materials are available online.

  6. A Hierarchical Poisson Log-Normal Model for Network Inference from RNA Sequencing Data

    Science.gov (United States)

    Gallopin, Mélina; Rau, Andrea; Jaffrézic, Florence

    2013-01-01

    Gene network inference from transcriptomic data is an important methodological challenge and a key aspect of systems biology. Although several methods have been proposed to infer networks from microarray data, there is a need for inference methods able to model RNA-seq data, which are count-based and highly variable. In this work we propose a hierarchical Poisson log-normal model with a Lasso penalty to infer gene networks from RNA-seq data; this model has the advantage of directly modelling discrete data and accounting for inter-sample variance larger than the sample mean. Using real microRNA-seq data from breast cancer tumors and simulations, we compare this method to a regularized Gaussian graphical model on log-transformed data, and a Poisson log-linear graphical model with a Lasso penalty on power-transformed data. For data simulated with large inter-sample dispersion, the proposed model performs better than the other methods in terms of sensitivity, specificity and area under the ROC curve. These results show the necessity of methods specifically designed for gene network inference from RNA-seq data. PMID:24147011

  7. A Bayesian Approach to Model Selection in Hierarchical Mixtures-of-Experts Architectures.

    Science.gov (United States)

    Tanner, Martin A.; Peng, Fengchun; Jacobs, Robert A.

    1997-03-01

    There does not exist a statistical model that shows good performance on all tasks. Consequently, the model selection problem is unavoidable; investigators must decide which model is best at summarizing the data for each task of interest. This article presents an approach to the model selection problem in hierarchical mixtures-of-experts architectures. These architectures combine aspects of generalized linear models with those of finite mixture models in order to perform tasks via a recursive "divide-and-conquer" strategy. Markov chain Monte Carlo methodology is used to estimate the distribution of the architectures' parameters. One part of our approach to model selection attempts to estimate the worth of each component of an architecture so that relatively unused components can be pruned from the architecture's structure. A second part of this approach uses a Bayesian hypothesis testing procedure in order to differentiate inputs that carry useful information from nuisance inputs. Simulation results suggest that the approach presented here adheres to the dictum of Occam's razor; simple architectures that are adequate for summarizing the data are favored over more complex structures. Copyright 1997 Elsevier Science Ltd. All Rights Reserved.

  8. Bayesian Hierarchical Scale Mixtures of Log-Normal Models for Inference in Reliability with Stochastic Constraint

    Directory of Open Access Journals (Sweden)

    Hea-Jung Kim

    2017-06-01

    Full Text Available This paper develops Bayesian inference in reliability of a class of scale mixtures of log-normal failure time (SMLNFT models with stochastic (or uncertain constraint in their reliability measures. The class is comprehensive and includes existing failure time (FT models (such as log-normal, log-Cauchy, and log-logistic FT models as well as new models that are robust in terms of heavy-tailed FT observations. Since classical frequency approaches to reliability analysis based on the SMLNFT model with stochastic constraint are intractable, the Bayesian method is pursued utilizing a Markov chain Monte Carlo (MCMC sampling based approach. This paper introduces a two-stage maximum entropy (MaxEnt prior, which elicits a priori uncertain constraint and develops Bayesian hierarchical SMLNFT model by using the prior. The paper also proposes an MCMC method for Bayesian inference in the SMLNFT model reliability and calls attention to properties of the MaxEnt prior that are useful for method development. Finally, two data sets are used to illustrate how the proposed methodology works.

  9. Deformation Behavior between Hydraulic and Natural Fractures Using Fully Coupled Hydromechanical Model with XFEM

    Directory of Open Access Journals (Sweden)

    Fei Liu

    2017-01-01

    Full Text Available There has been a growing consensus that preexisting natural fractures play an important role during stimulation. A novel fully coupled hydromechanical model using extended finite element method is proposed. This directly coupled scheme avoids the cumbersome process during calculating the fluid pressure in complicated fracture networks and translating into an equivalent nodal force. Numerical examples are presented to simulate the hydraulic fracture propagation paths for simultaneous multifracture treatments with properly using the stress shadow effects for horizontal wells and to reveal the deformation response and interaction mechanism between hydraulic induced fracture and nonintersected natural fractures at orthotropic and nonorthotropic angles. With the stress shadow effects, the induced hydraulic flexural fracture deflecting to wellbore rather than transverse fracture would be formed during the progress of simultaneous fracturing for a horizontal well. The coupled hydromechanical simulation reveals that the adjacent section to the intersection is opened and the others are closed for orthogonal natural fracture, while the nonorthogonal natural fracture is activated near the intersection firstly and along the whole section with increasing perturbed stresses. The results imply that the induced hydraulic fracture tends to cross orthotropic natural fracture, while it is prior to being arrested by the nonorthotropic natural fracture.

  10. Statistical methodology for discrete fracture model - including fracture size, orientation uncertainty together with intensity uncertainty and variability

    Energy Technology Data Exchange (ETDEWEB)

    Darcel, C. (Itasca Consultants SAS (France)); Davy, P.; Le Goc, R.; Dreuzy, J.R. de; Bour, O. (Geosciences Rennes, UMR 6118 CNRS, Univ. def Rennes, Rennes (France))

    2009-11-15

    Investigations led for several years at Laxemar and Forsmark reveal the large heterogeneity of geological formations and associated fracturing. This project aims at reinforcing the statistical DFN modeling framework adapted to a site scale. This leads therefore to develop quantitative methods of characterization adapted to the nature of fracturing and data availability. We start with the hypothesis that the maximum likelihood DFN model is a power-law model with a density term depending on orientations. This is supported both by literature and specifically here by former analyses of the SKB data. This assumption is nevertheless thoroughly tested by analyzing the fracture trace and lineament maps. Fracture traces range roughly between 0.5 m and 10 m - i e the usual extension of the sample outcrops. Between the raw data and final data used to compute the fracture size distribution from which the size distribution model will arise, several steps are necessary, in order to correct data from finite-size, topographical and sampling effects. More precisely, a particular attention is paid to fracture segmentation status and fracture linkage consistent with the DFN model expected. The fracture scaling trend observed over both sites displays finally a shape parameter k{sub t} close to 1.2 with a density term (alpha{sub 2d}) between 1.4 and 1.8. Only two outcrops clearly display a different trend with k{sub t} close to 3 and a density term (alpha{sub 2d}) between 2 and 3.5. The fracture lineaments spread over the range between 100 meters and a few kilometers. When compared with fracture trace maps, these datasets are already interpreted and the linkage process developed previously has not to be done. Except for the subregional lineament map from Forsmark, lineaments display a clear power-law trend with a shape parameter k{sub t} equal to 3 and a density term between 2 and 4.5. The apparent variation in scaling exponent, from the outcrop scale (k{sub t} = 1.2) on one side, to

  11. Class hierarchical test case generation algorithm based on expanded EMDPN model

    Institute of Scientific and Technical Information of China (English)

    LI Jun-yi; GONG Hong-fang; HU Ji-ping; ZOU Bei-ji; SUN Jia-guang

    2006-01-01

    A new model of event and message driven Petri network(EMDPN) based on the characteristic of class interaction for messages passing between two objects was extended. Using EMDPN interaction graph, a class hierarchical test-case generation algorithm with cooperated paths (copaths) was proposed, which can be used to solve the problems resulting from the class inheritance mechanism encountered in object-oriented software testing such as oracle, message transfer errors, and unreachable statement. Finally, the testing sufficiency was analyzed with the ordered sequence testing criterion(OSC). The results indicate that the test cases stemmed from newly proposed automatic algorithm of copaths generation satisfies synchronization message sequences testing criteria, therefore the proposed new algorithm of copaths generation has a good coverage rate.

  12. LIMO EEG: a toolbox for hierarchical LInear MOdeling of ElectroEncephaloGraphic data.

    Science.gov (United States)

    Pernet, Cyril R; Chauveau, Nicolas; Gaspar, Carl; Rousselet, Guillaume A

    2011-01-01

    Magnetic- and electric-evoked brain responses have traditionally been analyzed by comparing the peaks or mean amplitudes of signals from selected channels and averaged across trials. More recently, tools have been developed to investigate single trial response variability (e.g., EEGLAB) and to test differences between averaged evoked responses over the entire scalp and time dimensions (e.g., SPM, Fieldtrip). LIMO EEG is a Matlab toolbox (EEGLAB compatible) to analyse evoked responses over all space and time dimensions, while accounting for single trial variability using a simple hierarchical linear modelling of the data. In addition, LIMO EEG provides robust parametric tests, therefore providing a new and complementary tool in the analysis of neural evoked responses.

  13. Multi-pathway model of nuclide transport in fractured media and its application

    International Nuclear Information System (INIS)

    Li Xun; Yang Zeping; Li Jinxuan

    2010-01-01

    In order to know the law of nuclide transport in fracture system, the basic differential equations of nuclide transport in fracture and matrix were obtained based on the dual media theory, and the general analytic solutions of nuclide transport in single fractured media with exponential attenuation source in fracture were deduced by Laplace transform, and one-dimensional multi-pathway model of nuclide transport was proposed based on dual media theory and stochastic distribution of fracture parameters. The transport of Th-229, Cs-135 and Se-79 were simulated with this model, the relative concentration of these nuclides in fracture system were predicted. Further more, it was deduced that aperture and velocity can distinctly influence transport of nuclide by comparing with the results which were simulated by single fracture model. (authors)

  14. (Environmental and geophysical modeling, fracture mechanics, and boundary element methods)

    Energy Technology Data Exchange (ETDEWEB)

    Gray, L.J.

    1990-11-09

    Technical discussions at the various sites visited centered on application of boundary integral methods for environmental modeling, seismic analysis, and computational fracture mechanics in composite and smart'' materials. The traveler also attended the International Association for Boundary Element Methods Conference at Rome, Italy. While many aspects of boundary element theory and applications were discussed in the papers, the dominant topic was the analysis and application of hypersingular equations. This has been the focus of recent work by the author, and thus the conference was highly relevant to research at ORNL.

  15. Experimental Fracture Model versus Osteotomy Model in Metacarpal Bone Plate Fixation

    Directory of Open Access Journals (Sweden)

    S. Ochman

    2011-01-01

    Full Text Available Introduction. Osteotomy or fracture models can be used to evaluate mechanical properties of fixation techniques of the hand skeleton in vitro. Although many studies make use of osteotomy models, fracture models simulate the clinical situation more realistically. This study investigates monocortical and bicortical plate fixation on metacarpal bones considering both aforementioned models to decide which method is best suited to test fixation techniques. Methods. Porcine metacarpal bones (=40 were randomized into 4 groups. In groups I and II bones were fractured with a modified 3-point bending test. The intact bones represented a further control group to which the other groups after fixation were compared. In groups III and IV a standard osteotomy was carried out. Bones were fixated with plates monocortically (group I, III and bicortically (group II, IV and tested for failure. Results. Bones fractured at a mean maximum load of 482.8 N ± 104.8 N with a relative standard deviation (RSD of 21.7%, mean stiffness was 122.3 ± 35 N/mm. In the fracture model, there was a significant difference (=0.01 for maximum load of monocortically and bicortically fixed bones in contrast to the osteotomy model (=0.9. Discussion. In the fracture model, because one can use the same bone for both measurements in the intact state and the bone-plate construct states, the impact of inter-individual differences is reduced. In contrast to the osteotomy model there are differences between monocortical and bicortical fixations in the fracture model. Thus simulation of the in vivo situation is better and seems to be suitable for the evaluation of mechanical properties of fixation techniques on metacarpals.

  16. Modelisation of transport in fractured media with a smeared fractures modeling approach: special focus on matrix diffusion process.

    Science.gov (United States)

    Fourno, A.; Grenier, C.; Benabderrahmane, H.

    2003-04-01

    Modeling flow and transport in natural fractured media is a difficult issue due among others to the complexity of the system, the particularities of the geometrical features, the strong parameter value contrasts between the fracture zones (flow zones) and the matrix zones (no flow zones). This lead to the development of dedicated tools like for instance discrete fracture network models (DFN). We follow here another line applicable for classical continuous modeling codes. The fracture network is not meshed here but presence of fractures is taken into account by means of continuous heterogeneous fields (permeability, porosity, head, velocity, concentration ...). This line, followed by different authors, is referred as smeared fracture approach and presents the following advantages: the approach is very versatile because no dedicated spatial discretization effort is required (we use a basic regular mesh, simulations can be done on a rough mesh saving computer time). This makes this kind of approach very promising for taking heterogeneity of properties as well as uncertainties into account within a Monte Carlo framework for instance. Furthermore, the geometry of the matrix blocks where transfers proceed by diffusion is fully taken into account contrary to classical simplified 1D approach for instance. Nevertheless continuous heterogeneous field representation of a fractured medium requires a homogenization process at the scale of the mesh considered. Literature proves that this step of homogenization for transport is still a challenging task. Consequently, the level precision of the results has to be estimated. We precedently proposed a new approach dedicated to Mixed and Hybrid Finite Element approach. This numerical scheme is very interesting for such highly heterogeneous media and in particular guaranties exact conservation of mass flow for each mesh leading to good transport results. We developed a smeared fractures approach to model flow and transport limited to

  17. Probabilistic daily ILI syndromic surveillance with a spatio-temporal Bayesian hierarchical model.

    Directory of Open Access Journals (Sweden)

    Ta-Chien Chan

    Full Text Available BACKGROUND: For daily syndromic surveillance to be effective, an efficient and sensible algorithm would be expected to detect aberrations in influenza illness, and alert public health workers prior to any impending epidemic. This detection or alert surely contains uncertainty, and thus should be evaluated with a proper probabilistic measure. However, traditional monitoring mechanisms simply provide a binary alert, failing to adequately address this uncertainty. METHODS AND FINDINGS: Based on the Bayesian posterior probability of influenza-like illness (ILI visits, the intensity of outbreak can be directly assessed. The numbers of daily emergency room ILI visits at five community hospitals in Taipei City during 2006-2007 were collected and fitted with a Bayesian hierarchical model containing meteorological factors such as temperature and vapor pressure, spatial interaction with conditional autoregressive structure, weekend and holiday effects, seasonality factors, and previous ILI visits. The proposed algorithm recommends an alert for action if the posterior probability is larger than 70%. External data from January to February of 2008 were retained for validation. The decision rule detects successfully the peak in the validation period. When comparing the posterior probability evaluation with the modified Cusum method, results show that the proposed method is able to detect the signals 1-2 days prior to the rise of ILI visits. CONCLUSIONS: This Bayesian hierarchical model not only constitutes a dynamic surveillance system but also constructs a stochastic evaluation of the need to call for alert. The monitoring mechanism provides earlier detection as well as a complementary tool for current surveillance programs.

  18. Interneuronal Mechanism for Tinbergen’s Hierarchical Model of Behavioral Choice

    Science.gov (United States)

    Pirger, Zsolt; Crossley, Michael; László, Zita; Naskar, Souvik; Kemenes, György; O’Shea, Michael; Benjamin, Paul R.; Kemenes, Ildikó

    2014-01-01

    Summary Recent studies of behavioral choice support the notion that the decision to carry out one behavior rather than another depends on the reconfiguration of shared interneuronal networks [1]. We investigated another decision-making strategy, derived from the classical ethological literature [2, 3], which proposes that behavioral choice depends on competition between autonomous networks. According to this model, behavioral choice depends on inhibitory interactions between incompatible hierarchically organized behaviors. We provide evidence for this by investigating the interneuronal mechanisms mediating behavioral choice between two autonomous circuits that underlie whole-body withdrawal [4, 5] and feeding [6] in the pond snail Lymnaea. Whole-body withdrawal is a defensive reflex that is initiated by tactile contact with predators. As predicted by the hierarchical model, tactile stimuli that evoke whole-body withdrawal responses also inhibit ongoing feeding in the presence of feeding stimuli. By recording neurons from the feeding and withdrawal networks, we found no direct synaptic connections between the interneuronal and motoneuronal elements that generate the two behaviors. Instead, we discovered that behavioral choice depends on the interaction between two unique types of interneurons with asymmetrical synaptic connectivity that allows withdrawal to override feeding. One type of interneuron, the Pleuro-Buccal (PlB), is an extrinsic modulatory neuron of the feeding network that completely inhibits feeding when excited by touch-induced monosynaptic input from the second type of interneuron, Pedal-Dorsal12 (PeD12). PeD12 plays a critical role in behavioral choice by providing a synaptic pathway joining the two behavioral networks that underlies the competitive dominance of whole-body withdrawal over feeding. PMID:25155505

  19. Hierarchical Bayesian Spatio Temporal Model Comparison on the Earth Trapped Particle Forecast

    International Nuclear Information System (INIS)

    Suparta, Wayan; Gusrizal

    2014-01-01

    We compared two hierarchical Bayesian spatio temporal (HBST) results, Gaussian process (GP) and autoregressive (AR) models, on the Earth trapped particle forecast. Two models were employed on the South Atlantic Anomaly (SAA) region. Electron of >30 keV (mep0e1) from National Oceanic and Atmospheric Administration (NOAA) 15-18 satellites data was chosen as the particle modeled. We used two weeks data to perform the model fitting on a 5°x5° grid of longitude and latitude, and 31 August 2007 was set as the date of forecast. Three statistical validations were performed on the data, i.e. the root mean square error (RMSE), mean absolute percentage error (MAPE) and bias (BIAS). The statistical analysis showed that GP model performed better than AR with the average of RMSE = 0.38 and 0.63, MAPE = 11.98 and 17.30, and BIAS = 0.32 and 0.24, for GP and AR, respectively. Visual validation on both models with the NOAA map's also confirmed the superior of the GP than the AR. The variance of log flux minimum = 0.09 and 1.09, log flux maximum = 1.15 and 1.35, and in successively represents GP and AR

  20. A hierarchical model for estimating density in camera-trap studies

    Science.gov (United States)

    Royle, J. Andrew; Nichols, James D.; Karanth, K.Ullas; Gopalaswamy, Arjun M.

    2009-01-01

    Estimating animal density using capture–recapture data from arrays of detection devices such as camera traps has been problematic due to the movement of individuals and heterogeneity in capture probability among them induced by differential exposure to trapping.We develop a spatial capture–recapture model for estimating density from camera-trapping data which contains explicit models for the spatial point process governing the distribution of individuals and their exposure to and detection by traps.We adopt a Bayesian approach to analysis of the hierarchical model using the technique of data augmentation.The model is applied to photographic capture–recapture data on tigers Panthera tigris in Nagarahole reserve, India. Using this model, we estimate the density of tigers to be 14·3 animals per 100 km2 during 2004.Synthesis and applications. Our modelling framework largely overcomes several weaknesses in conventional approaches to the estimation of animal density from trap arrays. It effectively deals with key problems such as individual heterogeneity in capture probabilities, movement of traps, presence of potential ‘holes’ in the array and ad hoc estimation of sample area. The formulation, thus, greatly enhances flexibility in the conduct of field surveys as well as in the analysis of data, from studies that may involve physical, photographic or DNA-based ‘captures’ of individual animals.

  1. Automatic relative RPC image model bias compensation through hierarchical image matching for improving DEM quality

    Science.gov (United States)

    Noh, Myoung-Jong; Howat, Ian M.

    2018-02-01

    The quality and efficiency of automated Digital Elevation Model (DEM) extraction from stereoscopic satellite imagery is critically dependent on the accuracy of the sensor model used for co-locating pixels between stereo-pair images. In the absence of ground control or manual tie point selection, errors in the sensor models must be compensated with increased matching search-spaces, increasing both the computation time and the likelihood of spurious matches. Here we present an algorithm for automatically determining and compensating the relative bias in Rational Polynomial Coefficients (RPCs) between stereo-pairs utilizing hierarchical, sub-pixel image matching in object space. We demonstrate the algorithm using a suite of image stereo-pairs from multiple satellites over a range stereo-photogrammetrically challenging polar terrains. Besides providing a validation of the effectiveness of the algorithm for improving DEM quality, experiments with prescribed sensor model errors yield insight into the dependence of DEM characteristics and quality on relative sensor model bias. This algorithm is included in the Surface Extraction through TIN-based Search-space Minimization (SETSM) DEM extraction software package, which is the primary software used for the U.S. National Science Foundation ArcticDEM and Reference Elevation Model of Antarctica (REMA) products.

  2. Estimating the Term Structure With a Semiparametric Bayesian Hierarchical Model: An Application to Corporate Bonds1

    Science.gov (United States)

    Cruz-Marcelo, Alejandro; Ensor, Katherine B.; Rosner, Gary L.

    2011-01-01

    The term structure of interest rates is used to price defaultable bonds and credit derivatives, as well as to infer the quality of bonds for risk management purposes. We introduce a model that jointly estimates term structures by means of a Bayesian hierarchical model with a prior probability model based on Dirichlet process mixtures. The modeling methodology borrows strength across term structures for purposes of estimation. The main advantage of our framework is its ability to produce reliable estimators at the company level even when there are only a few bonds per company. After describing the proposed model, we discuss an empirical application in which the term structure of 197 individual companies is estimated. The sample of 197 consists of 143 companies with only one or two bonds. In-sample and out-of-sample tests are used to quantify the improvement in accuracy that results from approximating the term structure of corporate bonds with estimators by company rather than by credit rating, the latter being a popular choice in the financial literature. A complete description of a Markov chain Monte Carlo (MCMC) scheme for the proposed model is available as Supplementary Material. PMID:21765566

  3. Detection of Natural Fractures from Observed Surface Seismic Data Based on a Linear-Slip Model

    Science.gov (United States)

    Chen, Huaizhen; Zhang, Guangzhi

    2018-03-01

    Natural fractures play an important role in migration of hydrocarbon fluids. Based on a rock physics effective model, the linear-slip model, which defines fracture parameters (fracture compliances) for quantitatively characterizing the effects of fractures on rock total compliance, we propose a method to detect natural fractures from observed seismic data via inversion for the fracture compliances. We first derive an approximate PP-wave reflection coefficient in terms of fracture compliances. Using the approximate reflection coefficient, we derive azimuthal elastic impedance as a function of fracture compliances. An inversion method to estimate fracture compliances from seismic data is presented based on a Bayesian framework and azimuthal elastic impedance, which is implemented in a two-step procedure: a least-squares inversion for azimuthal elastic impedance and an iterative inversion for fracture compliances. We apply the inversion method to synthetic and real data to verify its stability and reasonability. Synthetic tests confirm that the method can make a stable estimation of fracture compliances in the case of seismic data containing a moderate signal-to-noise ratio for Gaussian noise, and the test on real data reveals that reasonable fracture compliances are obtained using the proposed method.

  4. Statistical geological discrete fracture network model. Forsmark modelling stage 2.2

    International Nuclear Information System (INIS)

    Fox, Aaron; La Pointe, Paul; Simeonov, Assen; Hermanson, Jan; Oehman, Johan

    2007-11-01

    The Swedish Nuclear Fuel and Waste Management Company (SKB) is performing site characterization at two different locations, Forsmark and Laxemar, in order to locate a site for a final geologic repository for spent nuclear fuel. The program is built upon the development of Site Descriptive Models (SDMs) at specific timed data freezes. Each SDM is formed from discipline-specific reports from across the scientific spectrum. This report describes the methods, analyses, and conclusions of the geological modeling team with respect to a geological and statistical model of fractures and minor deformation zones (henceforth referred to as the geological DFN), version 2.2, at the Forsmark site. The geological DFN builds upon the work of other geological modelers, including the deformation zone (DZ), rock domain (RD), and fracture domain (FD) models. The geological DFN is a statistical model for stochastically simulating rock fractures and minor deformation zones as a scale of less than 1,000 m (the lower cut-off of the DZ models). The geological DFN is valid within four specific fracture domains inside the local model region, and encompassing the candidate volume at Forsmark: FFM01, FFM02, FFM03, and FFM06. The models are build using data from detailed surface outcrop maps and the cored borehole record at Forsmark. The conceptual model for the Forsmark 2.2 geological revolves around the concept of orientation sets; for each fracture domain, other model parameters such as size and intensity are tied to the orientation sets. Two classes of orientation sets were described; Global sets, which are encountered everywhere in the model region, and Local sets, which represent highly localized stress environments. Orientation sets were described in terms of their general cardinal direction (NE, NW, etc). Two alternatives are presented for fracture size modeling: - the tectonic continuum approach (TCM, TCMF) described by coupled size-intensity scaling following power law distributions

  5. Statistical geological discrete fracture network model. Forsmark modelling stage 2.2

    Energy Technology Data Exchange (ETDEWEB)

    Fox, Aaron; La Pointe, Paul [Golder Associates Inc (United States); Simeonov, Assen [Swedish Nuclear Fuel and Waste Management Co., Stockholm (Sweden); Hermanson, Jan; Oehman, Johan [Golder Associates AB, Stockholm (Sweden)

    2007-11-15

    The Swedish Nuclear Fuel and Waste Management Company (SKB) is performing site characterization at two different locations, Forsmark and Laxemar, in order to locate a site for a final geologic repository for spent nuclear fuel. The program is built upon the development of Site Descriptive Models (SDMs) at specific timed data freezes. Each SDM is formed from discipline-specific reports from across the scientific spectrum. This report describes the methods, analyses, and conclusions of the geological modeling team with respect to a geological and statistical model of fractures and minor deformation zones (henceforth referred to as the geological DFN), version 2.2, at the Forsmark site. The geological DFN builds upon the work of other geological modelers, including the deformation zone (DZ), rock domain (RD), and fracture domain (FD) models. The geological DFN is a statistical model for stochastically simulating rock fractures and minor deformation zones as a scale of less than 1,000 m (the lower cut-off of the DZ models). The geological DFN is valid within four specific fracture domains inside the local model region, and encompassing the candidate volume at Forsmark: FFM01, FFM02, FFM03, and FFM06. The models are build using data from detailed surface outcrop maps and the cored borehole record at Forsmark. The conceptual model for the Forsmark 2.2 geological revolves around the concept of orientation sets; for each fracture domain, other model parameters such as size and intensity are tied to the orientation sets. Two classes of orientation sets were described; Global sets, which are encountered everywhere in the model region, and Local sets, which represent highly localized stress environments. Orientation sets were described in terms of their general cardinal direction (NE, NW, etc). Two alternatives are presented for fracture size modeling: - the tectonic continuum approach (TCM, TCMF) described by coupled size-intensity scaling following power law distributions

  6. A Two-Scale Reduced Model for Darcy Flow in Fractured Porous Media

    KAUST Repository

    Chen, Huangxin

    2016-06-01

    In this paper, we develop a two-scale reduced model for simulating the Darcy flow in two-dimensional porous media with conductive fractures. We apply the approach motivated by the embedded fracture model (EFM) to simulate the flow on the coarse scale, and the effect of fractures on each coarse scale grid cell intersecting with fractures is represented by the discrete fracture model (DFM) on the fine scale. In the DFM used on the fine scale, the matrix-fracture system are resolved on unstructured grid which represents the fractures accurately, while in the EFM used on the coarse scale, the flux interaction between fractures and matrix are dealt with as a source term, and the matrix-fracture system can be resolved on structured grid. The Raviart-Thomas mixed finite element methods are used for the solution of the coupled flows in the matrix and the fractures on both fine and coarse scales. Numerical results are presented to demonstrate the efficiency of the proposed model for simulation of flow in fractured porous media.

  7. A fracture-controlled path-following technique for phase-field modeling of brittle fracture

    NARCIS (Netherlands)

    Singh, N.; Verhoosel, C.V.; De Borst, R.; Van Brummelen, E.H.

    2016-01-01

    In the phase-field description of brittle fracture, the fracture-surface area can be expressed as a functional of the phase field (or damage field). In this work we study the applicability of this explicit expression as a (non-linear) path-following constraint to robustly track the equilibrium path

  8. Effective media models for unsaturated fractured rock: A field experiment

    International Nuclear Information System (INIS)

    Nicholl, M.J.; Glass, R.J.

    1995-01-01

    A thick unsaturated rock mass at Yucca Mountain is currently under consideration as a potential repository site for disposal of high level radioactive waste. In accordance with standard industry and scientific practices, abstract numerical models will be used to evaluate the potential for radionuclide release through the groundwater system. At this time, currently available conceptual models used to develop effective media properties are based primarily on simplistic considerations. The work presented here is part of an integrated effort to develop effective media models at the intermediate block scale (approximately 8-125m) through a combination of physical observations, numerical simulations and theoretical considerations. A multi-purpose field experiment designed and conducted as part of this integrated effort is described. Specific goals of this experimental investigation were to: (1) obtain fracture network data from Topopah Spring Tuff for use in block scale simulations; (2) identity positions of the network conducting flow under three different boundary conditions; (3) visualize preferential flow paths and small-scale flow structures; (4) collect samples for subsequent hydraulic testing and use in block-scale simulations; and (5) demonstrate the ability of Electrical Resistance Tomography (ERT) to delineate fluid distribution within fractured rock

  9. Correcting underestimation of optimal fracture length by modeling proppant conductivity variations in hydraulically fractured gas/condensate reservoirs

    Energy Technology Data Exchange (ETDEWEB)

    Akram, A.H.; Samad, A. [Society of Petroleum Engineers, Richardson, TX (United States)]|[Schlumberger, Houston, TX (United States)

    2006-07-01

    A study was conducted in which a newly developed numerical simulator was used to forecast the productivity of a hydraulically fractured well in a retrograde gas-condensate sandstone reservoir. The effect of condensate dropout was modeled in both the reservoir and the proppant pack. The type of proppant and the stress applied to it are among the factors that determine proppant conductivity in a single-phase flow. Other factors include the high velocity of gas and the presence of liquid in the proppant pack. It was concluded that apparent proppant permeability in a gas condensate reservoir varies along the length of the hydraulic fracture and depends on the distance from the wellbore. It will increase towards the tip of the fracture where liquid ratio and velocity are lower. Apparent proppant permeability also changes with time. Forecasting is most accurate when these conditions are considered in the simulation. There are 2 problems associated with the use of a constant proppant permeability in a gas condensate reservoir. The first relates to the fact that it is impossible to obtain a correct single number that will mimic the drawdown of the real fracture at a particular rate without going through the process of determining the proppant permeability profile in a numerical simulator. The second problem relates to the fact that constant proppant permeability yields an optimal fracture length that is too short. Analytical modeling does not account for these complexities. It was determined that the only way to accurately simulate the behaviour of a hydraulic fracture in a high rate well, is by advanced numerical modeling that considers varying apparent proppant permeability in terms of time and distance along the fracture length. 10 refs., 2 tabs., 16 figs., 1 appendix.

  10. Scaling local species-habitat relations to the larger landscape with a hierarchical spatial count model

    Science.gov (United States)

    Thogmartin, W.E.; Knutson, M.G.

    2007-01-01

    Much of what is known about avian species-habitat relations has been derived from studies of birds at local scales. It is entirely unclear whether the relations observed at these scales translate to the larger landscape in a predictable linear fashion. We derived habitat models and mapped predicted abundances for three forest bird species of eastern North America using bird counts, environmental variables, and hierarchical models applied at three spatial scales. Our purpose was to understand habitat associations at multiple spatial scales and create predictive abundance maps for purposes of conservation planning at a landscape scale given the constraint that the variables used in this exercise were derived from local-level studies. Our models indicated a substantial influence of landscape context for all species, many of which were counter to reported associations at finer spatial extents. We found land cover composition provided the greatest contribution to the relative explained variance in counts for all three species; spatial structure was second in importance. No single spatial scale dominated any model, indicating that these species are responding to factors at multiple spatial scales. For purposes of conservation planning, areas of predicted high abundance should be investigated to evaluate the conservation potential of the landscape in their general vicinity. In addition, the models and spatial patterns of abundance among species suggest locations where conservation actions may benefit more than one species. ?? 2006 Springer Science+Business Media B.V.

  11. Hierarchical Kinematic Modelling and Optimal Design of a Novel Hexapod Robot with Integrated Limb Mechanism

    Directory of Open Access Journals (Sweden)

    Guiyang Xin

    2015-09-01

    Full Text Available This paper presents a novel hexapod robot, hereafter named PH-Robot, with three degrees of freedom (3-DOF parallel leg mechanisms based on the concept of an integrated limb mechanism (ILM for the integration of legged locomotion and arm manipulation. The kinematic model plays an important role in the parametric optimal design and motion planning of robots. However, models of parallel mechanisms are often difficult to obtain because of the implicit relationship between the motions of actuated joints and the motion of a moving platform. In order to derive the kinematic equations of the proposed hexapod robot, an extended hierarchical kinematic modelling method is proposed. According to the kinematic model, the geometrical parameters of the leg are optimized utilizing a comprehensive objective function that considers both dexterity and payload. PH-Robot has distinct advantages in accuracy and load ability over a robot with serial leg mechanisms through the former's comparison of performance indices. The reachable workspace of the leg verifies its ability to walk and manipulate. The results of the trajectory tracking experiment demonstrate the correctness of the kinematic model of the hexapod robot.

  12. Calibrating the sqHIMMELI v1.0 wetland methane emission model with hierarchical modeling and adaptive MCMC

    Science.gov (United States)

    Susiluoto, Jouni; Raivonen, Maarit; Backman, Leif; Laine, Marko; Makela, Jarmo; Peltola, Olli; Vesala, Timo; Aalto, Tuula

    2018-03-01

    Estimating methane (CH4) emissions from natural wetlands is complex, and the estimates contain large uncertainties. The models used for the task are typically heavily parameterized and the parameter values are not well known. In this study, we perform a Bayesian model calibration for a new wetland CH4 emission model to improve the quality of the predictions and to understand the limitations of such models.The detailed process model that we analyze contains descriptions for CH4 production from anaerobic respiration, CH4 oxidation, and gas transportation by diffusion, ebullition, and the aerenchyma cells of vascular plants. The processes are controlled by several tunable parameters. We use a hierarchical statistical model to describe the parameters and obtain the posterior distributions of the parameters and uncertainties in the processes with adaptive Markov chain Monte Carlo (MCMC), importance resampling, and time series analysis techniques. For the estimation, the analysis utilizes measurement data from the Siikaneva flux measurement site in southern Finland. The uncertainties related to the parameters and the modeled processes are described quantitatively. At the process level, the flux measurement data are able to constrain the CH4 production processes, methane oxidation, and the different gas transport processes. The posterior covariance structures explain how the parameters and the processes are related. Additionally, the flux and flux component uncertainties are analyzed both at the annual and daily levels. The parameter posterior densities obtained provide information regarding importance of the different processes, which is also useful for development of wetland methane emission models other than the square root HelsinkI Model of MEthane buiLd-up and emIssion for peatlands (sqHIMMELI). The hierarchical modeling allows us to assess the effects of some of the parameters on an annual basis. The results of the calibration and the cross validation suggest that

  13. LiDAR based prediction of forest biomass using hierarchical models with spatially varying coefficients

    Science.gov (United States)

    Babcock, Chad; Finley, Andrew O.; Bradford, John B.; Kolka, Randall K.; Birdsey, Richard A.; Ryan, Michael G.

    2015-01-01

    Many studies and production inventory systems have shown the utility of coupling covariates derived from Light Detection and Ranging (LiDAR) data with forest variables measured on georeferenced inventory plots through regression models. The objective of this study was to propose and assess the use of a Bayesian hierarchical modeling framework that accommodates both residual spatial dependence and non-stationarity of model covariates through the introduction of spatial random effects. We explored this objective using four forest inventory datasets that are part of the North American Carbon Program, each comprising point-referenced measures of above-ground forest biomass and discrete LiDAR. For each dataset, we considered at least five regression model specifications of varying complexity. Models were assessed based on goodness of fit criteria and predictive performance using a 10-fold cross-validation procedure. Results showed that the addition of spatial random effects to the regression model intercept improved fit and predictive performance in the presence of substantial residual spatial dependence. Additionally, in some cases, allowing either some or all regression slope parameters to vary spatially, via the addition of spatial random effects, further improved model fit and predictive performance. In other instances, models showed improved fit but decreased predictive performance—indicating over-fitting and underscoring the need for cross-validation to assess predictive ability. The proposed Bayesian modeling framework provided access to pixel-level posterior predictive distributions that were useful for uncertainty mapping, diagnosing spatial extrapolation issues, revealing missing model covariates, and discovering locally significant parameters.

  14. Modeling fractures as interfaces for flow and transport in porous media

    International Nuclear Information System (INIS)

    Serres, Ch.; Alboin, C.; Jaffre, J.; Roberts, J.

    2002-05-01

    We are concerned with flow and transport in a fractured porous medium at a scale where the fractures can be modelled individually. The fractures themselves are porous media with large permeability in comparison with that in the surrounding rock. Contrarily to many studies in which the contrast in permeabilities is of such an order that the flow outside of the fracture is neglected, the purpose of this work is to consider the case where the exchange between the fractures and the surrounding rock is significant. Then it is necessary to take into account this interaction because it has a profound effect on the flow and the transport of a solute. The main idea for this work is to treat fractures as interfaces. Then it will not be necessary to use mesh refinements around the fractures, which is an important drawback of most models. Treating fractures as interfaces leads to non-overlapping domain decomposition methods, using the natural domain decomposition suggested by the fracture network. This paper is organized as follows. In Section 2, we present the model, and in Section 3, we show that the corresponding problem has a unique solution. In Section 4, we reduce the approximate problem to a problem with unknowns on the interface. Numerical results are given in Section 5 for the simple case of a domain divided into two sub-domains by one fracture. In Section 6 we extend the formulation to the case of intersecting fractures and in Section 7 to that of a solute transport. (authors)

  15. Fracture network model of the groundwater flow in the Romuvaara site

    International Nuclear Information System (INIS)

    Poteri, A.; Laitinen, M.

    1997-01-01

    In the study, computer codes are employed to analyse the groundwater flow patterns in the sparcely fractured intact rock at the Romuvaara site. The new fracture data gathered during the detailed site characterisation phase demonstrated that the characteristic properties of fractures can be estimated quite reliably from few boreholes and outcrops. Results obtained by employing new methods, like the use of borehole-TV, changed the fracture intensity of the potential water conducting fractures compared to the earlier model. In the preliminary site investigation phase only the orientated fractures were used to derive the parameters of the intact rock. In the present model all the fractures outside the known fracture zones are used. The hydraulic conductivity tensor of the intact rock was estimated with the fracture network model. The flow simulations were calculated for a 16 x 16 x 16 m 3 rock volume and about 2000 fractures. The flow rate distribution through the cross sectional area of the disposal canisters was calculated for a set of ten realisations and a large number of different canister positions. The total number of canister positions simulated was 2200. The flow distribution in larger volume was studied using a method that searched the flow routes of highest conductance. The flow routes were examined into north-south, east-west and vertical directions. Flow routes along homogeneous and heterogeneous fractures were compared. (21 refs.)

  16. Numerical modeling of the effects of roughness on flow and eddy formation in fractures

    Directory of Open Access Journals (Sweden)

    Scott Briggs

    2017-02-01

    Full Text Available The effect of roughness on flow in fractures was investigated using lattice Boltzmann method (LBM. Simulations were conducted for both statistically generated hypothetical fractures and a natural dolomite fracture. The effect of increasing roughness on effective hydraulic aperture, Izbash and Forchheimer parameters with increasing Reynolds number (Re ranging from 0.01 to 500 was examined. The growth of complex flow features, such as eddies arising near the fracture surface, was directly associated with changes in surface roughness. Rapid eddy growth above Re values of 1, followed by less rapid growth at higher Re values, suggested a three-zone nonlinear model for flow in rough fractures. This three-zone model, relating effective hydraulic conductivity to Re, was also found to be appropriate for the simulation of water flow in the natural dolomite fracture. Increasing fracture roughness led to greater eddy volumes and lower effective hydraulic conductivities for the same Re values.

  17. Hierarchical Bayesian models to assess between- and within-batch variability of pathogen contamination in food.

    Science.gov (United States)

    Commeau, Natalie; Cornu, Marie; Albert, Isabelle; Denis, Jean-Baptiste; Parent, Eric

    2012-03-01

    Assessing within-batch and between-batch variability is of major interest for risk assessors and risk managers in the context of microbiological contamination of food. For example, the ratio between the within-batch variability and the between-batch variability has a large impact on the results of a sampling plan. Here, we designed hierarchical Bayesian models to represent such variability. Compatible priors were built mathematically to obtain sound model comparisons. A numeric criterion is proposed to assess the contamination structure comparing the ability of the models to replicate grouped data at the batch level using a posterior predictive loss approach. Models were applied to two case studies: contamination by Listeria monocytogenes of pork breast used to produce diced bacon and contamination by the same microorganism on cold smoked salmon at the end of the process. In the first case study, a contamination structure clearly exists and is located at the batch level, that is, between batches variability is relatively strong, whereas in the second a structure also exists but is less marked. © 2012 Society for Risk Analysis.

  18. Bayesian Uncertainty Quantification for Subsurface Inversion Using a Multiscale Hierarchical Model

    KAUST Repository

    Mondal, Anirban

    2014-07-03

    We consider a Bayesian approach to nonlinear inverse problems in which the unknown quantity is a random field (spatial or temporal). The Bayesian approach contains a natural mechanism for regularization in the form of prior information, can incorporate information from heterogeneous sources and provide a quantitative assessment of uncertainty in the inverse solution. The Bayesian setting casts the inverse solution as a posterior probability distribution over the model parameters. The Karhunen-Loeve expansion is used for dimension reduction of the random field. Furthermore, we use a hierarchical Bayes model to inject multiscale data in the modeling framework. In this Bayesian framework, we show that this inverse problem is well-posed by proving that the posterior measure is Lipschitz continuous with respect to the data in total variation norm. Computational challenges in this construction arise from the need for repeated evaluations of the forward model (e.g., in the context of MCMC) and are compounded by high dimensionality of the posterior. We develop two-stage reversible jump MCMC that has the ability to screen the bad proposals in the first inexpensive stage. Numerical results are presented by analyzing simulated as well as real data from hydrocarbon reservoir. This article has supplementary material available online. © 2014 American Statistical Association and the American Society for Quality.

  19. Comparison of Extreme Precipitation Return Levels using Spatial Bayesian Hierarchical Modeling versus Regional Frequency Analysis

    Science.gov (United States)

    Love, C. A.; Skahill, B. E.; AghaKouchak, A.; Karlovits, G. S.; England, J. F.; Duren, A. M.

    2017-12-01

    We compare gridded extreme precipitation return levels obtained using spatial Bayesian hierarchical modeling (BHM) with their respective counterparts from a traditional regional frequency analysis (RFA) using the same set of extreme precipitation data. Our study area is the 11,478 square mile Willamette River basin (WRB) located in northwestern Oregon, a major tributary of the Columbia River whose 187 miles long main stem, the Willamette River, flows northward between the Coastal and Cascade Ranges. The WRB contains approximately two ­thirds of Oregon's population and 20 of the 25 most populous cities in the state. The U.S. Army Corps of Engineers (USACE) Portland District operates thirteen dams and extreme precipitation estimates are required to support risk­ informed hydrologic analyses as part of the USACE Dam Safety Program. Our intent is to profile for the USACE an alternate methodology to an RFA that was developed in 2008 due to the lack of an official NOAA Atlas 14 update for the state of Oregon. We analyze 24-hour annual precipitation maxima data for the WRB utilizing the spatial BHM R package "spatial.gev.bma", which has been shown to be efficient in developing coherent maps of extreme precipitation by return level. Our BHM modeling analysis involved application of leave-one-out cross validation (LOO-CV), which not only supported model selection but also a comprehensive assessment of location specific model performance. The LOO-CV results will provide a basis for the BHM RFA comparison.

  20. TOPICAL REVIEW: Nonlinear aspects of the renormalization group flows of Dyson's hierarchical model

    Science.gov (United States)

    Meurice, Y.

    2007-06-01

    We review recent results concerning the renormalization group (RG) transformation of Dyson's hierarchical model (HM). This model can be seen as an approximation of a scalar field theory on a lattice. We introduce the HM and show that its large group of symmetry simplifies drastically the blockspinning procedure. Several equivalent forms of the recursion formula are presented with unified notations. Rigourous and numerical results concerning the recursion formula are summarized. It is pointed out that the recursion formula of the HM is inequivalent to both Wilson's approximate recursion formula and Polchinski's equation in the local potential approximation (despite the very small difference with the exponents of the latter). We draw a comparison between the RG of the HM and functional RG equations in the local potential approximation. The construction of the linear and nonlinear scaling variables is discussed in an operational way. We describe the calculation of non-universal critical amplitudes in terms of the scaling variables of two fixed points. This question appears as a problem of interpolation between these fixed points. Universal amplitude ratios are calculated. We discuss the large-N limit and the complex singularities of the critical potential calculable in this limit. The interpolation between the HM and more conventional lattice models is presented as a symmetry breaking problem. We briefly introduce models with an approximate supersymmetry. One important goal of this review is to present a configuration space counterpart, suitable for lattice formulations, of functional RG equations formulated in momentum space (often called exact RG equations and abbreviated ERGE).

  1. A Hierarchical Building Segmentation in Digital Surface Models for 3D Reconstruction

    Directory of Open Access Journals (Sweden)

    Yiming Yan

    2017-01-01

    Full Text Available In this study, a hierarchical method for segmenting buildings in a digital surface model (DSM, which is used in a novel framework for 3D reconstruction, is proposed. Most 3D reconstructions of buildings are model-based. However, the limitations of these methods are overreliance on completeness of the offline-constructed models of buildings, and the completeness is not easily guaranteed since in modern cities buildings can be of a variety of types. Therefore, a model-free framework using high precision DSM and texture-images buildings was introduced. There are two key problems with this framework. The first one is how to accurately extract the buildings from the DSM. Most segmentation methods are limited by either the terrain factors or the difficult choice of parameter-settings. A level-set method are employed to roughly find the building regions in the DSM, and then a recently proposed ‘occlusions of random textures model’ are used to enhance the local segmentation of the buildings. The second problem is how to generate the facades of buildings. Synergizing with the corresponding texture-images, we propose a roof-contour guided interpolation of building facades. The 3D reconstruction results achieved by airborne-like images and satellites are compared. Experiments show that the segmentation method has good performance, and 3D reconstruction is easily performed by our framework, and better visualization results can be obtained by airborne-like images, which can be further replaced by UAV images.

  2. A hierarchical model for structure learning based on the physiological characteristics of neurons

    Institute of Scientific and Technical Information of China (English)

    WEI Hui

    2007-01-01

    Almost all applications of Artificial Neural Networks (ANNs) depend mainly on their memory ability.The characteristics of typical ANN models are fixed connections,with evolved weights,globalized representations,and globalized optimizations,all based on a mathematical approach.This makes those models to be deficient in robustness,efficiency of learning,capacity,anti-jamming between training sets,and correlativity of samples,etc.In this paper,we attempt to address these problems by adopting the characteristics of biological neurons in morphology and signal processing.A hierarchical neural network was designed and realized to implement structure learning and representations based on connected structures.The basic characteristics of this model are localized and random connections,field limitations of neuron fan-in and fan-out,dynamic behavior of neurons,and samples represented through different sub-circuits of neurons specialized into different response patterns.At the end of this paper,some important aspects of error correction,capacity,learning efficiency,and soundness of structural representation are analyzed theoretically.This paper has demonstrated the feasibility and advantages of structure learning and representation.This model can serve as a fundamental element of cognitive systems such as perception and associative memory.Key-words structure learning,representation,associative memory,computational neuroscience

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

    Science.gov (United States)

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

    2014-06-01

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

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

    Science.gov (United States)

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

    2014-01-01

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

  5. Benefits of Applying Hierarchical Models to the Empirical Green's Function Approach

    Science.gov (United States)

    Denolle, M.; Van Houtte, C.

    2017-12-01

    Stress drops calculated from source spectral studies currently show larger variability than what is implied by empirical ground motion models. One of the potential origins of the inflated variability is the simplified model-fitting techniques used in most source spectral studies. This study improves upon these existing methods, and shows that the fitting method may explain some of the discrepancy. In particular, Bayesian hierarchical modelling is shown to be a method that can reduce bias, better quantify uncertainties and allow additional effects to be resolved. The method is applied to the Mw7.1 Kumamoto, Japan earthquake, and other global, moderate-magnitude, strike-slip earthquakes between Mw5 and Mw7.5. It is shown that the variation of the corner frequency, fc, and the falloff rate, n, across the focal sphere can be reliably retrieved without overfitting the data. Additionally, it is shown that methods commonly used to calculate corner frequencies can give substantial biases. In particular, if fc were calculated for the Kumamoto earthquake using a model with a falloff rate fixed at 2 instead of the best fit 1.6, the obtained fc would be as large as twice its realistic value. The reliable retrieval of the falloff rate allows deeper examination of this parameter for a suite of global, strike-slip earthquakes, and its scaling with magnitude. The earthquake sequences considered in this study are from Japan, New Zealand, Haiti and California.

  6. A Bayesian hierarchical model with novel prior specifications for estimating HIV testing rates.

    Science.gov (United States)

    An, Qian; Kang, Jian; Song, Ruiguang; Hall, H Irene

    2016-04-30

    Human immunodeficiency virus (HIV) infection is a severe infectious disease actively spreading globally, and acquired immunodeficiency syndrome (AIDS) is an advanced stage of HIV infection. The HIV testing rate, that is, the probability that an AIDS-free HIV infected person seeks a test for HIV during a particular time interval, given no previous positive test has been obtained prior to the start of the time, is an important parameter for public health. In this paper, we propose a Bayesian hierarchical model with two levels of hierarchy to estimate the HIV testing rate using annual AIDS and AIDS-free HIV diagnoses data. At level one, we model the latent number of HIV infections for each year using a Poisson distribution with the intensity parameter representing the HIV incidence rate. At level two, the annual numbers of AIDS and AIDS-free HIV diagnosed cases and all undiagnosed cases stratified by the HIV infections at different years are modeled using a multinomial distribution with parameters including the HIV testing rate. We propose a new class of priors for the HIV incidence rate and HIV testing rate taking into account the temporal dependence of these parameters to improve the estimation accuracy. We develop an efficient posterior computation algorithm based on the adaptive rejection metropolis sampling technique. We demonstrate our model using simulation studies and the analysis of the national HIV surveillance data in the USA. Copyright © 2015 John Wiley & Sons, Ltd.

  7. Exploring the Effects of Congruence and Holland's Personality Codes on Job Satisfaction: An Application of Hierarchical Linear Modeling Techniques

    Science.gov (United States)

    Ishitani, Terry T.

    2010-01-01

    This study applied hierarchical linear modeling to investigate the effect of congruence on intrinsic and extrinsic aspects of job satisfaction. Particular focus was given to differences in job satisfaction by gender and by Holland's first-letter codes. The study sample included nationally represented 1462 female and 1280 male college graduates who…

  8. a Predictive Model of Permeability for Fractal-Based Rough Rock Fractures during Shear

    Science.gov (United States)

    Huang, Na; Jiang, Yujing; Liu, Richeng; Li, Bo; Zhang, Zhenyu

    This study investigates the roles of fracture roughness, normal stress and shear displacement on the fluid flow characteristics through three-dimensional (3D) self-affine fractal rock fractures, whose surfaces are generated using the modified successive random additions (SRA) algorithm. A series of numerical shear-flow tests under different normal stresses were conducted on rough rock fractures to calculate the evolutions of fracture aperture and permeability. The results show that the rough surfaces of fractal-based fractures can be described using the scaling parameter Hurst exponent (H), in which H = 3 - Df, where Df is the fractal dimension of 3D single fractures. The joint roughness coefficient (JRC) distribution of fracture profiles follows a Gauss function with a negative linear relationship between H and average JRC. The frequency curves of aperture distributions change from sharp to flat with increasing shear displacement, indicating a more anisotropic and heterogeneous flow pattern. Both the mean aperture and permeability of fracture increase with the increment of surface roughness and decrement of normal stress. At the beginning of shear, the permeability increases remarkably and then gradually becomes steady. A predictive model of permeability using the mean mechanical aperture is proposed and the validity is verified by comparisons with the experimental results reported in literature. The proposed model provides a simple method to approximate permeability of fractal-based rough rock fractures during shear using fracture aperture distribution that can be easily obtained from digitized fracture surface information.

  9. The three-zone composite productivity model for a multi-fractured horizontal shale gas well

    Science.gov (United States)

    Qi, Qian; Zhu, Weiyao

    2018-02-01

    Due to the nano-micro pore structures and the massive multi-stage multi-cluster hydraulic fracturing in shale gas reservoirs, the multi-scale seepage flows are much more complicated than in most other conventional reservoirs, and are crucial for the economic development of shale gas. In this study, a new multi-scale non-linear flow model was established and simplified, based on different diffusion and slip correction coefficients. Due to the fact that different flow laws existed between the fracture network and matrix zone, a three-zone composite model was proposed. Then, according to the conformal transformation combined with the law of equivalent percolation resistance, the productivity equation of a horizontal fractured well, with consideration given to diffusion, slip, desorption, and absorption, was built. Also, an analytic solution was derived, and the interference of the multi-cluster fractures was analyzed. The results indicated that the diffusion of the shale gas was mainly in the transition and Fick diffusion regions. The matrix permeability was found to be influenced by slippage and diffusion, which was determined by the pore pressure and diameter according to the Knudsen number. It was determined that, with the increased half-lengths of the fracture clusters, flow conductivity of the fractures, and permeability of the fracture network, the productivity of the fractured well also increased. Meanwhile, with the increased number of fractures, the distance between the fractures decreased, and the productivity slowly increased due to the mutual interfere of the fractures.

  10. Factors associated with leisure time physical inactivity in black individuals: hierarchical model

    Directory of Open Access Journals (Sweden)

    Francisco José Gondim Pitanga

    2014-09-01

    Full Text Available Background. A number of studies have shown that the black population exhibits higher levels of leisure-time physical inactivity (LTPI, but few have investigated the factors associated with this behavior.Objective. The aim of this study was to analyze associated factors and the explanatory model proposed for LTPI in black adults.Methods. The design was cross-sectional with a sample of 2,305 adults from 20–96 years of age, 902 (39.1% men, living in the city of Salvador, Brazil. LTPI was analyzed using the International Physical Activity Questionnaire (IPAQ. A hierarchical model was built with the possible factors associated with LTPI, distributed in distal (age and sex, intermediate 1 (socioeconomic status, educational level and marital status, intermediate 2 (perception of safety/violence in the neighborhood, racial discrimination in private settings and physical activity at work and proximal blocks (smoking and participation in Carnival block rehearsals. We estimated crude and adjusted odds ratio (OR using logistic regression.Results. The variables inversely associated with LTPI were male gender, socioeconomic status and secondary/university education, although the proposed model explains only 4.2% of LTPI.Conclusions. We conclude that male gender, higher education and socioeconomic status can reduce LTPI in black adults.

  11. An Integrated Model Based on a Hierarchical Indices System for Monitoring and Evaluating Urban Sustainability

    Directory of Open Access Journals (Sweden)

    Xulin Guo

    2013-02-01

    Full Text Available Over 50% of world’s population presently resides in cities, and this number is expected to rise to ~70% by 2050. Increasing urbanization problems including population growth, urban sprawl, land use change, unemployment, and environmental degradation, have markedly impacted urban residents’ Quality of Life (QOL. Therefore, urban sustainability and its measurement have gained increasing attention from administrators, urban planners, and scientific communities throughout the world with respect to improving urban development and human well-being. The widely accepted definition of urban sustainability emphasizes the balancing development of three primary domains (urban economy, society, and environment. This article attempts to improve the aforementioned definition of urban sustainability by incorporating a human well-being dimension. Major problems identified in existing urban sustainability indicator (USI models include a weak integration of potential indicators, poor measurement and quantification, and insufficient spatial-temporal analysis. To tackle these challenges an integrated USI model based on a hierarchical indices system was established for monitoring and evaluating urban sustainability. This model can be performed by quantifying indicators using both traditional statistical approaches and advanced geomatic techniques based on satellite imagery and census data, which aims to provide a theoretical basis for a comprehensive assessment of urban sustainability from a spatial-temporal perspective.

  12. A bayesian hierarchical model for classification with selection of functional predictors.

    Science.gov (United States)

    Zhu, Hongxiao; Vannucci, Marina; Cox, Dennis D

    2010-06-01

    In functional data classification, functional observations are often contaminated by various systematic effects, such as random batch effects caused by device artifacts, or fixed effects caused by sample-related factors. These effects may lead to classification bias and thus should not be neglected. Another issue of concern is the selection of functions when predictors consist of multiple functions, some of which may be redundant. The above issues arise in a real data application where we use fluorescence spectroscopy to detect cervical precancer. In this article, we propose a Bayesian hierarchical model that takes into account random batch effects and selects effective functions among multiple functional predictors. Fixed effects or predictors in nonfunctional form are also included in the model. The dimension of the functional data is reduced through orthonormal basis expansion or functional principal components. For posterior sampling, we use a hybrid Metropolis-Hastings/Gibbs sampler, which suffers slow mixing. An evolutionary Monte Carlo algorithm is applied to improve the mixing. Simulation and real data application show that the proposed model provides accurate selection of functional predictors as well as good classification.

  13. Teacher characteristics and student performance: An analysis using hierarchical linear modelling

    Directory of Open Access Journals (Sweden)

    Paula Armstrong

    2015-12-01

    Full Text Available This research makes use of hierarchical linear modelling to investigate which teacher characteristics are significantly associated with student performance. Using data from the SACMEQ III study of 2007, an interesting and potentially important finding is that younger teachers are better able to improve the mean mathematics performance of their students. Furthermore, younger teachers themselves perform better on subject tests than do their older counterparts. Identical models are run for Sub Saharan countries bordering on South Africa, as well for Kenya and the strong relationship between teacher age and student performance is not observed. Similarly, the model is run for South Africa using data from SACMEQ II (conducted in 2002 and the relationship between teacher age and student performance is also not observed. It must be noted that South African teachers were not tested in SACMEQ II so it was not possible to observe differences in subject knowledge amongst teachers in different cohorts and it was not possible to control for teachers’ level of subject knowledge when observing the relationship between teacher age and student performance. Changes in teacher education in the late 1990s and early 2000s may explain the differences in the performance of younger teachers relative to their older counterparts observed in the later dataset.

  14. [Establishment of Schatzker classification digital models of tibial plateau fractures and its application on virtual surgery].

    Science.gov (United States)

    Liu, Yong-gang; Zuo, Li-xin; Pei, Guo-xian; Dai, Ke; Sang, Jing-wei

    2013-08-20

    To explore the establishment of Schatzker classification digital model of tibial plateau fractures and its application in virtual surgery. Proximal tibial of one healthy male volunteer was examined with 64-slice spiral computed tomography (CT). The data were processed by software Mimics 10.01 and a model of proximal tibia was reconstructed. According to the Schatzker classification criteria of tibial plateau fractures, each type of fracture model was simulated.Screen-captures of fracture model were saved from different directions.Each type of fracture model was exported as video mode.Fracture model was imported into FreeForm modeling system.With a force feedback device, a surgeon could conduct virtual fracture operation simulation.Utilizing the GHOST of FreeForm modeling system, the software of virtual cutting, fracture reduction and fixation was developed.With a force feedback device PHANTOM, a surgeon could manipulate virtual surgical instruments and fracture classification model and simulate surgical actions such as assembly of surgical instruments, drilling, implantation of screw, reduction of fracture, bone grafting and fracture fixation, etc. The digital fracture model was intuitive, three-dimensional and realistic and it had excellent visual effect.Fracture could be observed and charted from optional direction and angle.Fracture model could rotate 360 ° in the corresponding video mode. The virtual surgical environment had a strong sense of reality, immersion and telepresence as well as good interaction and force feedback function in the FreeForm modeling system. The user could make the corresponding decisions about surgical method and choice of internal fixation according to the specific type of tibial plateau fracture as well as repeated operational practice in virtual surgery system. The digital fracture model of Schatzker classification is intuitive, three-dimensional, realistic and dynamic. The virtual surgery systems of Schatzker classifications make

  15. A Bayesian Hierarchical Modeling Approach to Predicting Flow in Ungauged Basins

    Science.gov (United States)

    Gronewold, A.; Alameddine, I.; Anderson, R. M.

    2009-12-01

    Recent innovative approaches to identifying and applying regression-based relationships between land use patterns (such as increasing impervious surface area and decreasing vegetative cover) and rainfall-runoff model parameters represent novel and promising improvements to predicting flow from ungauged basins. In particular, these approaches allow for predicting flows under uncertain and potentially variable future conditions due to rapid land cover changes, variable climate conditions, and other factors. Despite the broad range of literature on estimating rainfall-runoff model parameters, however, the absence of a robust set of modeling tools for identifying and quantifying uncertainties in (and correlation between) rainfall-runoff model parameters represents a significant gap in current hydrological modeling research. Here, we build upon a series of recent publications promoting novel Bayesian and probabilistic modeling strategies for quantifying rainfall-runoff model parameter estimation uncertainty. Our approach applies alternative measures of rainfall-runoff model parameter joint likelihood (including Nash-Sutcliffe efficiency, among others) to simulate samples from the joint parameter posterior probability density function. We then use these correlated samples as response variables in a Bayesian hierarchical model with land use coverage data as predictor variables in order to develop a robust land use-based tool for forecasting flow in ungauged basins while accounting for, and explicitly acknowledging, parameter estimation uncertainty. We apply this modeling strategy to low-relief coastal watersheds of Eastern North Carolina, an area representative of coastal resource waters throughout the world because of its sensitive embayments and because of the abundant (but currently threatened) natural resources it hosts. Consequently, this area is the subject of several ongoing studies and large-scale planning initiatives, including those conducted through the United

  16. Fear of Failure, 2x2 Achievement Goal and Self-Handicapping: An Examination of the Hierarchical Model of Achievement Motivation in Physical Education

    Science.gov (United States)

    Chen, Lung Hung; Wu, Chia-Huei; Kee, Ying Hwa; Lin, Meng-Shyan; Shui, Shang-Hsueh

    2009-01-01

    In this study, the hierarchical model of achievement motivation [Elliot, A. J. (1997). Integrating the "classic" and "contemporary" approaches to achievement motivation: A hierarchical model of approach and avoidance achievement motivation. In P. Pintrich & M. Maehr (Eds.), "Advances in motivation and achievement"…

  17. Development of tools and models for computational fracture assessment

    International Nuclear Information System (INIS)

    Talja, H.; Santaoja, K.

    1998-01-01

    The aim of the work presented in this paper has been to develop and test new computational tools and theoretically more sound methods for fracture mechanical analysis. The applicability of the engineering integrity assessment system MASI for evaluation of piping components has been extended. The most important motivation for the theoretical development have been the well-known fundamental limitations in the validity of J-integral, which limits its applicability in many important practical safety assessment cases. Examples are extensive plastic deformation, multimaterial structures and ascending loading paths (especially warm prestress, WPS). Further, the micromechanical Gurson model has been applied to several reactor pressure vessel materials. Special attention is paid to the transferability of Gurson model parameters from tensile test results to prediction of ductile failure behaviour of cracked structures. (author)

  18. Application of hierarchical Bayesian unmixing models in river sediment source apportionment

    Science.gov (United States)

    Blake, Will; Smith, Hugh; Navas, Ana; Bodé, Samuel; Goddard, Rupert; Zou Kuzyk, Zou; Lennard, Amy; Lobb, David; Owens, Phil; Palazon, Leticia; Petticrew, Ellen; Gaspar, Leticia; Stock, Brian; Boeckx, Pacsal; Semmens, Brice

    2016-04-01

    Fingerprinting and unmixing concepts are used widely across environmental disciplines for forensic evaluation of pollutant sources. In aquatic and marine systems, this includes tracking the source of organic and inorganic pollutants in water and linking problem sediment to soil erosion and land use sources. It is, however, the particular complexity of ecological systems that has driven creation of the most sophisticated mixing models, primarily to (i) evaluate diet composition in complex ecological food webs, (ii) inform population structure and (iii) explore animal movement. In the context of the new hierarchical Bayesian unmixing model, MIXSIAR, developed to characterise intra-population niche variation in ecological systems, we evaluate the linkage between ecological 'prey' and 'consumer' concepts and river basin sediment 'source' and sediment 'mixtures' to exemplify the value of ecological modelling tools to river basin science. Recent studies have outlined advantages presented by Bayesian unmixing approaches in handling complex source and mixture datasets while dealing appropriately with uncertainty in parameter probability distributions. MixSIAR is unique in that it allows individual fixed and random effects associated with mixture hierarchy, i.e. factors that might exert an influence on model outcome for mixture groups, to be explored within the source-receptor framework. This offers new and powerful ways of interpreting river basin apportionment data. In this contribution, key components of the model are evaluated in the context of common experimental designs for sediment fingerprinting studies namely simple, nested and distributed catchment sampling programmes. Illustrative examples using geochemical and compound specific stable isotope datasets are presented and used to discuss best practice with specific attention to (1) the tracer selection process, (2) incorporation of fixed effects relating to sample timeframe and sediment type in the modelling

  19. Validation of fracture flow models in the Stripa project

    International Nuclear Information System (INIS)

    Herbert, A.; Dershowitz, W.; Long, J.; Hodgkinson, D.

    1991-01-01

    One of the objectives of Phase III of the Stripa Project is to develop and evaluate approaches for the prediction of groundwater flow and nuclide transport in a specific unexplored volume of the Stripa granite and make a comparison with data from field measurements. During the first stage of the project, a prediction of inflow to the D-holes, an array of six parallel closely spaced 100m boreholes, was made based on data from six other boreholes. This data included fracture geometry, stress, single borehole geophysical logging, crosshole and reflection radar and seismic tomogram, head monitoring and single hole packer test measurements. Maps of fracture traces on the drift walls have also been made. The D-holes are located along a future Validation Drift which will be excavated. The water inflow to the D-holes has been measured in an experiment called the Simulated Drift Experiment. The paper reviews the Simulated Drift Experiment validation exercise. Following a discussion of the approach to validation, the characterization data and its preliminary interpretation are summarised and commented upon. That work has proved feasible to carry through all the complex and interconnected tasks associated with the gathering and interpretation of characterization data, the development and application of complex models, and the comparison with measured inflows. This exercise has provided detailed feed-back to the experimental and theoretical work required for measurements and predictions of flow into the Validation Drift. Computer codes used: CHANGE, FRACMAN, MAFIC, NAPSAC and TRINET. 2 figs., 2 tabs., 19 refs

  20. Hierarchical Model for the Similarity Measurement of a Complex Holed-Region Entity Scene

    Directory of Open Access Journals (Sweden)

    Zhanlong Chen

    2017-11-01

    Full Text Available Complex multi-holed-region entity scenes (i.e., sets of random region with holes are common in spatial database systems, spatial query languages, and the Geographic Information System (GIS. A multi-holed-region (region with an arbitrary number of holes is an abstraction of the real world that primarily represents geographic objects that have more than one interior boundary, such as areas that contain several lakes or lakes that contain islands. When the similarity of the two complex holed-region entity scenes is measured, the number of regions in the scenes and the number of holes in the regions are usually different between the two scenes, which complicates the matching relationships of holed-regions and holes. The aim of this research is to develop several holed-region similarity metrics and propose a hierarchical model to measure comprehensively the similarity between two complex holed-region entity scenes. The procedure first divides a complex entity scene into three layers: a complex scene, a micro-spatial-scene, and a simple entity (hole. The relationships between the adjacent layers are considered to be sets of relationships, and each level of similarity measurements is nested with the adjacent one. Next, entity matching is performed from top to bottom, while the similarity results are calculated from local to global. In addition, we utilize position graphs to describe the distribution of the holed-regions and subsequently describe the directions between the holes using a feature matrix. A case study that uses the Great Lakes in North America in 1986 and 2015 as experimental data illustrates the entire similarity measurement process between two complex holed-region entity scenes. The experimental results show that the hierarchical model accounts for the relationships of the different layers in the entire complex holed-region entity scene. The model can effectively calculate the similarity of complex holed-region entity scenes, even if the

  1. Determination of rock fracture parameters from crack models for failure in compression

    International Nuclear Information System (INIS)

    Kemeny, J.M.; Cook, N.G.W.

    1987-01-01

    Micromechanical models for axial splitting and for shear faulting are used to investigate parameters associated with rock fracture under compressive stresses. The fracture energies to create splitting fractures and shear faults are calculated using laboratory triaxial data. These energies are compared with the fracture energies for the propagation of microcracks that coalesce to form the larger scale fractures. It is found that for Westerly granite, the energies to create splitting fractures and shear faults are about three orders of magnitude greater than the energy needed to drive the tensile microcracks, due to the large amount of subsidiary crack surface area created in forming the larger scale fractures. A similar scale effect can be expected when extrapolating the laboratory results to field scale problems

  2. Effects of fracture surface roughness and shear displacement on geometrical and hydraulic properties of three-dimensional crossed rock fracture models

    Science.gov (United States)

    Huang, Na; Liu, Richeng; Jiang, Yujing; Li, Bo; Yu, Liyuan

    2018-03-01

    While shear-flow behavior through fractured media has been so far studied at single fracture scale, a numerical analysis of the shear effect on the hydraulic response of 3D crossed fracture model is presented. The analysis was based on a series of crossed fracture models, in which the effects of fracture surface roughness and shear displacement were considered. The rough fracture surfaces were generated using the modified successive random additions (SRA) algorithm. The shear displacement was applied on one fracture, and at the same time another fracture shifted along with the upper and lower surfaces of the sheared fracture. The simulation results reveal the development and variation of preferential flow paths through the model during the shear, accompanied by the change of the flow rate ratios between two flow planes at the outlet boundary. The average contact area accounts for approximately 5-27% of the fracture planes during shear, but the actual calculated flow area is about 38-55% of the fracture planes, which is much smaller than the noncontact area. The equivalent permeability will either increase or decrease as shear displacement increases from 0 to 4 mm, depending on the aperture distribution of intersection part between two fractures. When the shear displacement continuously increases by up to 20 mm, the equivalent permeability increases sharply first, and then keeps increasing with a lower gradient. The equivalent permeability of rough fractured model is about 26-80% of that calculated from the parallel plate model, and the equivalent permeability in the direction perpendicular to shear direction is approximately 1.31-3.67 times larger than that in the direction parallel to shear direction. These results can provide a fundamental understanding of fluid flow through crossed fracture model under shear.

  3. Quantifying Fracture Heterogeneity in Different Domains of Folded Carbonate Rocks to Improve Fractured Reservoir Analog Fluid Flow Models

    NARCIS (Netherlands)

    Bisdom, K.; Bertotti, G.; Gauthier, B.D.M.; Hardebol, N.J.

    2013-01-01

    Fluid flow in carbonate reservoirs is largely controlled by multiscale fracture networks. Significant variations of fracture network porosity and permeability are caused by the 3D heterogeneity of the fracture network characteristics, such as intensity, orientation and size. Characterizing fracture

  4. Developing a Hierarchical Decision Model to Evaluate Nuclear Power Plant Alternative Siting Technologies

    Science.gov (United States)

    Lingga, Marwan Mossa

    A strong trend of returning to nuclear power is evident in different places in the world. Forty-five countries are planning to add nuclear power to their grids and more than 66 nuclear power plants are under construction. Nuclear power plants that generate electricity and steam need to improve safety to become more acceptable to governments and the public. One novel practical solution to increase nuclear power plants' safety factor is to build them away from urban areas, such as offshore or underground. To date, Land-Based siting is the dominant option for siting all commercial operational nuclear power plants. However, the literature reveals several options for building nuclear power plants in safer sitings than Land-Based sitings. The alternatives are several and each has advantages and disadvantages, and it is difficult to distinguish among them and choose the best for a specific project. In this research, we recall the old idea of using the alternatives of offshore and underground sitings for new nuclear power plants and propose a tool to help in choosing the best siting technology. This research involved the development of a decision model for evaluating several potential nuclear power plant siting technologies, both those that are currently available and future ones. The decision model was developed based on the Hierarchical Decision Modeling (HDM) methodology. The model considers five major dimensions, social, technical, economic, environmental, and political (STEEP), and their related criteria and sub-criteria. The model was designed and developed by the author, and its elements' validation and evaluation were done by a large number of experts in the field of nuclear energy. The decision model was applied in evaluating five potential siting technologies and ranked the Natural Island as the best in comparison to Land-Based, Floating Plant, Artificial Island, and Semi-Embedded plant.

  5. Micromechanics of hierarchical materials

    DEFF Research Database (Denmark)

    Mishnaevsky, Leon, Jr.

    2012-01-01

    A short overview of micromechanical models of hierarchical materials (hybrid composites, biomaterials, fractal materials, etc.) is given. Several examples of the modeling of strength and damage in hierarchical materials are summarized, among them, 3D FE model of hybrid composites...... with nanoengineered matrix, fiber bundle model of UD composites with hierarchically clustered fibers and 3D multilevel model of wood considered as a gradient, cellular material with layered composite cell walls. The main areas of research in micromechanics of hierarchical materials are identified, among them......, the investigations of the effects of load redistribution between reinforcing elements at different scale levels, of the possibilities to control different material properties and to ensure synergy of strengthening effects at different scale levels and using the nanoreinforcement effects. The main future directions...

  6. Evaluation of Different Modeling Approaches to Simulate Contaminant Transport in a Fractured Limestone Aquifer

    Science.gov (United States)

    Mosthaf, K.; Rosenberg, L.; Balbarini, N.; Broholm, M. M.; Bjerg, P. L.; Binning, P. J.

    2014-12-01

    It is important to understand the fate and transport of contaminants in limestone aquifers because they are a major drinking water resource. This is challenging because they are highly heterogeneous; with micro-porous grains, flint inclusions, and being heavily fractured. Several modeling approaches have been developed to describe contaminant transport in fractured media, such as the discrete fracture (with various fracture geometries), equivalent porous media (with and without anisotropy), and dual porosity models. However, these modeling concepts are not well tested for limestone geologies. Given available field data and model purpose, this paper therefore aims to develop, examine and compare modeling approaches for transport of contaminants in fractured limestone aquifers. The model comparison was conducted for a contaminated site in Denmark, where a plume of a dissolved contaminant (PCE) has migrated through a fractured limestone aquifer. Multilevel monitoring wells have been installed at the site and available data includes information on spill history, extent of contamination, geology and hydrogeology. To describe the geology and fracture network, data from borehole logs was combined with an analysis of heterogeneities and fractures from a nearby excavation (analog site). Methods for translating the geological information and fracture mapping into each of the model concepts were examined. Each model was compared with available field data, considering both model fit and measures of model suitability. An analysis of model parameter identifiability and sensitivity is presented. Results show that there is considerable difference between modeling approaches, and that it is important to identify the right one for the actual scale and model purpose. A challenge in the use of field data is the determination of relevant hydraulic properties and interpretation of aqueous and solid phase contaminant concentration sampling data. Traditional water sampling has a bias

  7. Enriching the hierarchical model of achievement motivation: autonomous and controlling reasons underlying achievement goals.

    Science.gov (United States)

    Michou, Aikaterini; Vansteenkiste, Maarten; Mouratidis, Athanasios; Lens, Willy

    2014-12-01

    The hierarchical model of achievement motivation presumes that achievement goals channel the achievement motives of need for achievement and fear of failure towards motivational outcomes. Yet, less is known whether autonomous and controlling reasons underlying the pursuit of achievement goals can serve as additional pathways between achievement motives and outcomes. We tested whether mastery approach, performance approach, and performance avoidance goals and their underlying autonomous and controlling reasons would jointly explain the relation between achievement motives (i.e., fear of failure and need for achievement) and learning strategies (Study 1). Additionally, we examined whether the autonomous and controlling reasons underlying learners' dominant achievement goal would account for the link between achievement motives and the educational outcomes of learning strategies and cheating (Study 2). Six hundred and six Greek adolescent students (Mage = 15.05, SD = 1.43) and 435 university students (Mage M = 20.51, SD = 2.80) participated in studies 1 and 2, respectively. In both studies, a correlational design was used and the hypotheses were tested via path modelling. Autonomous and controlling reasons underlying the pursuit of achievement goals mediated, respectively, the relation of need for achievement and fear of failure to aspects of learning outcomes. Autonomous and controlling reasons underlying achievement goals could further explain learners' functioning in achievement settings. © 2014 The British Psychological Society.

  8. The SIS Model of Epidemic Spreading in a Hierarchical Social Network

    International Nuclear Information System (INIS)

    Grabowski, A.; Kosinski, R.A.

    2005-01-01

    The phenomenon of epidemic spreading in a population with a hierarchical structure of interpersonal interactions is described and investigated numerically. The SIS model with temporal immunity to a disease and a time of incubation is used. In our model spatial localization of individuals belonging to different social groups, effectiveness of different interpersonal interactions and the mobility of a contemporary community are taken into account. The structure of interpersonal connections is based on a scale-free network. The influence of the structure of the social network on typical relations characterizing the spreading process, like a range of epidemic and epidemic curves, is discussed. The probability that endemic state occurs is also calculated. Surprisingly it occurs, that less contagious diseases has greater chance to survive. The influence of preventive vaccinations on the spreading process is investigated and critical range of vaccinations that is sufficient for the suppression of an epidemic is calculated. Our results of numerical calculations are compared with the solutions of the master equation for the spreading process, and good agreement is found. (author)

  9. Fracture of Carbon Nanotube - Amorphous Carbon Composites: Molecular Modeling

    Science.gov (United States)

    Jensen, Benjamin D.; Wise, Kristopher E.; Odegard, Gregory M.

    2015-01-01

    Carbon nanotubes (CNTs) are promising candidates for use as reinforcements in next generation structural composite materials because of their extremely high specific stiffness and strength. They cannot, however, be viewed as simple replacements for carbon fibers because there are key differences between these materials in areas such as handling, processing, and matrix design. It is impossible to know for certain that CNT composites will represent a significant advance over carbon fiber composites before these various factors have been optimized, which is an extremely costly and time intensive process. This work attempts to place an upper bound on CNT composite mechanical properties by performing molecular dynamics simulations on idealized model systems with a reactive forcefield that permits modeling of both elastic deformations and fracture. Amorphous carbon (AC) was chosen for the matrix material in this work because of its structural simplicity and physical compatibility with the CNT fillers. It is also much stiffer and stronger than typical engineering polymer matrices. Three different arrangements of CNTs in the simulation cell have been investigated: a single-wall nanotube (SWNT) array, a multi-wall nanotube (MWNT) array, and a SWNT bundle system. The SWNT and MWNT array systems are clearly idealizations, but the SWNT bundle system is a step closer to real systems in which individual tubes aggregate into large assemblies. The effect of chemical crosslinking on composite properties is modeled by adding bonds between the CNTs and AC. The balance between weakening the CNTs and improving fiber-matrix load transfer is explored by systematically varying the extent of crosslinking. It is, of course, impossible to capture the full range of deformation and fracture processes that occur in real materials with even the largest atomistic molecular dynamics simulations. With this limitation in mind, the simulation results reported here provide a plausible upper limit on

  10. Motivation, Classroom Environment, and Learning in Introductory Geology: A Hierarchical Linear Model

    Science.gov (United States)

    Gilbert, L. A.; Hilpert, J. C.; Van Der Hoeven Kraft, K.; Budd, D.; Jones, M. H.; Matheney, R.; Mcconnell, D. A.; Perkins, D.; Stempien, J. A.; Wirth, K. R.

    2013-12-01

    Prior research has indicated that highly motivated students perform better and that learning increases in innovative, reformed classrooms, but untangling the student effects from the instructor effects is essential to understanding how to best support student learning. Using a hierarchical linear model, we examine these effects separately and jointly. We use data from nearly 2,000 undergraduate students surveyed by the NSF-funded GARNET (Geoscience Affective Research NETwork) project in 65 different introductory geology classes at research universities, public masters-granting universities, liberal arts colleges and community colleges across the US. Student level effects were measured as increases in expectancy and self-regulation using the Motivated Strategies for Learning Questionnaire (MSLQ; Pintrich et al., 1991). Instructor level effects were measured using the Reformed Teaching Observation Protocol, (RTOP; Sawada et al., 2000), with higher RTOP scores indicating a more reformed, student-centered classroom environment. Learning was measured by learning gains on a Geology Concept Inventory (GCI; Libarkin and Anderson, 2005) and normalized final course grade. The hierarchical linear model yielded significant results at several levels. At the student level, increases in expectancy and self-regulation are significantly and positively related to higher grades regardless of instructor; the higher the increase, the higher the grade. At the instructor level, RTOP scores are positively related to normalized average GCI learning gains. The higher the RTOP score, the higher the average class GCI learning gains. Across both levels, average class GCI learning gains are significantly and positively related to student grades; the higher the GCI learning gain, the higher the grade. Further, the RTOP scores are significantly and negatively related to the relationship between expectancy and course grade. The lower the RTOP score, the higher the correlation between change in

  11. Numerical modelling of fracture displacements due to thermal load from a KBS-3 repository

    Energy Technology Data Exchange (ETDEWEB)

    Hakami, Eva; Olofsson, Stig-Olof [Itasca Geomekanik AB, Stockholm (Sweden)

    2002-01-01

    The objective of the project has been to estimate the largest shear displacements that could be expected on a pre-existing fracture located in the repository area, due to the heat release from the deposited waste. Two-dimensional numerical analyses using the 'Universal Distinct Element Code' (UDEC) have been performed. The UDEC models represent a vertical cross section of a KBS-3 type repository with a large planar fracture intersecting a deposition hole at the repository centre. The extension, dip and mechanical properties of the fracture were changed in different models to evaluate the influence of these parameters on fracture shear displacements. The fracture was modelled using a Coulomb slip criterion with no cohesion and no dilation. The rock mass surrounding the fracture was modelled as a homogeneous, isotropic and elastic material, with a Young's modulus of 40 GPa. The initial heat release per unit repository area was assumed to be 8W/m{sup 2} (total power/total repository area). The shear displacements occur due to the thermal expansion of the rock surrounding the heat generating canisters. The rock mass is almost free to expand vertically, but is constrained horizontally, which gives a temperature-induced addition of shear stresses in the plane of the fracture. The shear movement of the fracture therefore follows the temperature development in the surrounding rock and the maximum shear displacement develops about 200 years after the waste deposition. Altogether, twenty cases are analysed. The maximum shear displacement, which occurs at the fracture centre, amounts to 0.2-13.8 cm depending on the fracture parameters. Among the analysed cases, the largest shear values, about 13 cm, was calculated for the cases with about 700 m long fractures with a shear stiffness of 0.005 GPa/m. Also, for large fractures with a higher shear stiffness of 5 GPa/m, but with a low friction angle (15 deg), the shear displacement reaches similar magnitudes, about

  12. Hierarchical modeling of systems with similar components: A framework for adaptive monitoring and control

    International Nuclear Information System (INIS)

    Memarzadeh, Milad; Pozzi, Matteo; Kolter, J. Zico

    2016-01-01

    System management includes the selection of maintenance actions depending on the available observations: when a system is made up by components known to be similar, data collected on one is also relevant for the management of others. This is typically the case of wind farms, which are made up by similar turbines. Optimal management of wind farms is an important task due to high cost of turbines' operation and maintenance: in this context, we recently proposed a method for planning and learning at system-level, called PLUS, built upon the Partially Observable Markov Decision Process (POMDP) framework, which treats transition and emission probabilities as random variables, and is therefore suitable for including model uncertainty. PLUS models the components as independent or identical. In this paper, we extend that formulation, allowing for a weaker similarity among components. The proposed approach, called Multiple Uncertain POMDP (MU-POMDP), models the components as POMDPs, and assumes the corresponding parameters as dependent random variables. Through this framework, we can calibrate specific degradation and emission models for each component while, at the same time, process observations at system-level. We compare the performance of the proposed MU-POMDP with PLUS, and discuss its potential and computational complexity. - Highlights: • A computational framework is proposed for adaptive monitoring and control. • It adopts a scheme based on Markov Chain Monte Carlo for inference and learning. • Hierarchical Bayesian modeling is used to allow a system-level flow of information. • Results show potential of significant savings in management of wind farms.

  13. Distinct Element Method modelling of fold-related fractures in a multilayer sequence

    Science.gov (United States)

    Kaserer, Klemens; Schöpfer, Martin P. J.; Grasemann, Bernhard

    2017-04-01

    Natural fractures have a significant impact on the performance of hydrocarbon systems/reservoirs. In a multilayer sequence, both the fracture density within the individual layers and the type of fracture intersection with bedding contacts are key parameters controlling fluid pathways. In the present study the influence of layer stacking and interlayer friction on fracture density and connectivity within a folded sequence is systematically investigated using 2D Distinct Element Method modelling. Our numerical approach permits forward modelling of both fracture nucleation/propagation/arrest and (contemporaneous) frictional slip along bedding planes in a robust and mechanically sound manner. Folding of the multilayer sequence is achieved by enforcing constant curvature folding by means of a velocity boundary condition at the model base, while a constant overburden pressure is maintained at the model top. The modelling reveals that with high bedding plane friction the multilayer stack behaves mechanically as a single layer so that the neutral surface develops in centre of the sequence and fracture spacing is controlled by the total thickness of the folded sequence. In contrast, low bedding plane friction leads to decoupling of the individual layers (flexural slip folding) so that a neutral surface develops in the centre of each layer and fracture spacing is controlled by the thickness of the individual layers. The low interfacial friction models illustrate that stepping of fractures across bedding planes is a common process, which can however have two contrasting origins: The mechanical properties of the interface cause fracture stepping during fracture propagation. Originally through-going fractures are later offset by interfacial slip during folding. A combination of these two different origins may lead to (apparently) inconsistent fracture offsets across bedding planes within a flexural slip fold.

  14. Discrete Dual Porosity Modeling of Electrical Current Flow in Fractured Media

    Science.gov (United States)

    Roubinet, D.; Irving, J.

    2013-12-01

    The study of fractured rocks is highly important in a variety of research fields and applications such as hydrogeology, geothermal energy, hydrocarbon extraction, and the long-term storage of toxic waste. Fractured media are characterized by a large contrast in permeability between the fractures and the rock matrix. For hydrocarbon extraction, the presence of highly conductive fractures is an advantage as they allow for quick and easy access to the resource. For toxic waste storage, however, the fractures represent a significant drawback as there is an increased risk of leakage and migration of pollutants deep into the subsurface. In both cases, the identification of fracture network characteristics is a critical, challenging, and required step. A number of previous studies have indicated that the presence of fractures in geological materials can have a significant impact on geophysical electrical resistivity measurements. It thus appears that, in some cases, geoelectrical surveys might be used to obtain useful information regarding fracture network characteristics. However, existing geoelectrical modeling tools and inversion methods are not properly adapted to deal with the specific challenges of fractured media. This prevents us from fully exploring the potential of the method to characterize fracture network properties. We thus require, as a first step, the development of accurate and efficient numerical modeling tools specifically designed for fractured domains. Building on the discrete fracture network (DFN) approach that has been widely used for modeling groundwater flow in fractured rocks, we have developed a discrete dual-porosity model for electrical current flow in fractured media. Our novel approach combines an explicit representation of the fractures with fracture-matrix electrical flow exchange at the block-scale. Tests in two dimensions show the ability of our method to deal with highly heterogeneous fracture networks in a highly computationally

  15. Use of hierarchical models to analyze European trends in congenital anomaly prevalence

    DEFF Research Database (Denmark)

    Cavadino, Alana; Prieto-Merino, David; Addor, Marie-Claude

    2016-01-01

    BACKGROUND: Surveillance of congenital anomalies is important to identify potential teratogens. Despite known associations between different anomalies, current surveillance methods examine trends within each subgroup separately. We aimed to evaluate whether hierarchical statistical methods that c...

  16. A Discrete Fracture Network Model with Stress-Driven Nucleation and Growth

    Science.gov (United States)

    Lavoine, E.; Darcel, C.; Munier, R.; Davy, P.

    2017-12-01

    The realism of Discrete Fracture Network (DFN) models, beyond the bulk statistical properties, relies on the spatial organization of fractures, which is not issued by purely stochastic DFN models. The realism can be improved by injecting prior information in DFN from a better knowledge of the geological fracturing processes. We first develop a model using simple kinematic rules for mimicking the growth of fractures from nucleation to arrest, in order to evaluate the consequences of the DFN structure on the network connectivity and flow properties. The model generates fracture networks with power-law scaling distributions and a percentage of T-intersections that are consistent with field observations. Nevertheless, a larger complexity relying on the spatial variability of natural fractures positions cannot be explained by the random nucleation process. We propose to introduce a stress-driven nucleation in the timewise process of this kinematic model to study the correlations between nucleation, growth and existing fracture patterns. The method uses the stress field generated by existing fractures and remote stress as an input for a Monte-Carlo sampling of nuclei centers at each time step. Networks so generated are found to have correlations over a large range of scales, with a correlation dimension that varies with time and with the function that relates the nucleation probability to stress. A sensibility analysis of input parameters has been performed in 3D to quantify the influence of fractures and remote stress field orientations.

  17. A GIS-Enabled, Michigan-Specific, Hierarchical Groundwater Modeling and Visualization System

    Science.gov (United States)

    Liu, Q.; Li, S.; Mandle, R.; Simard, A.; Fisher, B.; Brown, E.; Ross, S.

    2005-12-01

    Efficient management of groundwater resources relies on a comprehensive database that represents the characteristics of the natural groundwater system as well as analysis and modeling tools to describe the impacts of decision alternatives. Many agencies in Michigan have spent several years compiling expensive and comprehensive surface water and groundwater inventories and other related spatial data that describe their respective areas of responsibility. However, most often this wealth of descriptive data has only been utilized for basic mapping purposes. The benefits from analyzing these data, using GIS analysis functions or externally developed analysis models or programs, has yet to be systematically realized. In this talk, we present a comprehensive software environment that allows Michigan groundwater resources managers and frontline professionals to make more effective use of the available data and improve their ability to manage and protect groundwater resources, address potential conflicts, design cleanup schemes, and prioritize investigation activities. In particular, we take advantage of the Interactive Ground Water (IGW) modeling system and convert it to a customized software environment specifically for analyzing, modeling, and visualizing the Michigan statewide groundwater database. The resulting Michigan IGW modeling system (IGW-M) is completely window-based, fully interactive, and seamlessly integrated with a GIS mapping engine. The system operates in real-time (on the fly) providing dynamic, hierarchical mapping, modeling, spatial analysis, and visualization. Specifically, IGW-M allows water resources and environmental professionals in Michigan to: * Access and utilize the extensive data from the statewide groundwater database, interactively manipulate GIS objects, and display and query the associated data and attributes; * Analyze and model the statewide groundwater database, interactively convert GIS objects into numerical model features

  18. Hierarchical mixture of experts and diagnostic modeling approach to reduce hydrologic model structural uncertainty: STRUCTURAL UNCERTAINTY DIAGNOSTICS

    Energy Technology Data Exchange (ETDEWEB)

    Moges, Edom [Civil and Environmental Engineering Department, Washington State University, Richland Washington USA; Demissie, Yonas [Civil and Environmental Engineering Department, Washington State University, Richland Washington USA; Li, Hong-Yi [Hydrology Group, Pacific Northwest National Laboratory, Richland Washington USA

    2016-04-01

    In most water resources applications, a single model structure might be inadequate to capture the dynamic multi-scale interactions among different hydrological processes. Calibrating single models for dynamic catchments, where multiple dominant processes exist, can result in displacement of errors from structure to parameters, which in turn leads to over-correction and biased predictions. An alternative to a single model structure is to develop local expert structures that are effective in representing the dominant components of the hydrologic process and adaptively integrate them based on an indicator variable. In this study, the Hierarchical Mixture of Experts (HME) framework is applied to integrate expert model structures representing the different components of the hydrologic process. Various signature diagnostic analyses are used to assess the presence of multiple dominant processes and the adequacy of a single model, as well as to identify the structures of the expert models. The approaches are applied for two distinct catchments, the Guadalupe River (Texas) and the French Broad River (North Carolina) from the Model Parameter Estimation Experiment (MOPEX), using different structures of the HBV model. The results show that the HME approach has a better performance over the single model for the Guadalupe catchment, where multiple dominant processes are witnessed through diagnostic measures. Whereas, the diagnostics and aggregated performance measures prove that French Broad has a homogeneous catchment response, making the single model adequate to capture the response.

  19. Modeling of fracture of protective concrete structures under impact loads

    Energy Technology Data Exchange (ETDEWEB)

    Radchenko, P. A., E-mail: radchenko@live.ru; Batuev, S. P.; Radchenko, A. V.; Plevkov, V. S. [Tomsk State University of Architecture and Building, Tomsk, 634003 (Russian Federation)

    2015-10-27

    This paper presents results of numerical simulation of interaction between a Boeing 747-400 aircraft and the protective shell of a nuclear power plant. The shell is presented as a complex multilayered cellular structure consisting of layers of concrete and fiber concrete bonded with steel trusses. Numerical simulation was performed three-dimensionally using the original algorithm and software taking into account algorithms for building grids of complex geometric objects and parallel computations. Dynamics of the stress-strain state and fracture of the structure were studied. Destruction is described using a two-stage model that allows taking into account anisotropy of elastic and strength properties of concrete and fiber concrete. It is shown that wave processes initiate destruction of the cellular shell structure; cells start to destruct in an unloading wave originating after the compression wave arrival at free cell surfaces.

  20. Modeling of fracture of protective concrete structures under impact loads

    Science.gov (United States)

    Radchenko, P. A.; Batuev, S. P.; Radchenko, A. V.; Plevkov, V. S.

    2015-10-01

    This paper presents results of numerical simulation of interaction between a Boeing 747-400 aircraft and the protective shell of a nuclear power plant. The shell is presented as a complex multilayered cellular structure consisting of layers of concrete and fiber concrete bonded with steel trusses. Numerical simulation was performed three-dimensionally using the original algorithm and software taking into account algorithms for building grids of complex geometric objects and parallel computations. Dynamics of the stress-strain state and fracture of the structure were studied. Destruction is described using a two-stage model that allows taking into account anisotropy of elastic and strength properties of concrete and fiber concrete. It is shown that wave processes initiate destruction of the cellular shell structure; cells start to destruct in an unloading wave originating after the compression wave arrival at free cell surfaces.