WorldWideScience

Sample records for models predict strain

  1. A rate-dependent Hosford-Coulomb model for predicting ductile fracture at high strain rates

    Directory of Open Access Journals (Sweden)

    Marcadet Stephane J.

    2015-01-01

    Full Text Available The Hosford-Coulomb model incorporates the important effect of the Lode angle parameter in addition to the stress triaxiality to predict the initiation of ductile fracture. A strain-rate dependent extension of the Hosford-Coulomb model is presented to describe the results from low, intermediate and high strain rate fracture experiments on advanced high strength steels (DP590 and TRIP780. The model predictions agree well with the experimental observation of an increase in ductility as function of strain rate for stress states ranging from uniaxial to equi-biaxial tension.

  2. Ratchetting strain prediction

    International Nuclear Information System (INIS)

    Noban, Mohammad; Jahed, Hamid

    2007-01-01

    A time-efficient method for predicting ratchetting strain is proposed. The ratchetting strain at any cycle is determined by finding the ratchetting rate at only a few cycles. This determination is done by first defining the trajectory of the origin of stress in the deviatoric stress space and then incorporating this moving origin into a cyclic plasticity model. It is shown that at the beginning of the loading, the starting point of this trajectory coincides with the initial stress origin and approaches the mean stress, displaying a power-law relationship with the number of loading cycles. The method of obtaining this trajectory from a standard uniaxial asymmetric cyclic loading is presented. Ratchetting rates are calculated with the help of this trajectory and through the use of a constitutive cyclic plasticity model which incorporates deviatoric stresses and back stresses that are measured with respect to this moving frame. The proposed model is used to predict the ratchetting strain of two types of steels under single- and multi-step loadings. Results obtained agree well with the available experimental measurements

  3. Assessment of continuum mechanics models in predicting buckling strains of single-walled carbon nanotubes.

    Science.gov (United States)

    Zhang, Y Y; Wang, C M; Duan, W H; Xiang, Y; Zong, Z

    2009-09-30

    This paper presents an assessment of continuum mechanics (beam and cylindrical shell) models in the prediction of critical buckling strains of axially loaded single-walled carbon nanotubes (SWCNTs). Molecular dynamics (MD) simulation results for SWCNTs with various aspect (length-to-diameter) ratios and diameters will be used as the reference solutions for this assessment exercise. From MD simulations, two distinct buckling modes are observed, i.e. the shell-type buckling mode, when the aspect ratios are small, and the beam-type mode, when the aspect ratios are large. For moderate aspect ratios, the SWCNTs buckle in a mixed beam-shell mode. Therefore one chooses either the beam or the shell model depending on the aspect ratio of the carbon nanotubes (CNTs). It will be shown herein that for SWCNTs with long aspect ratios, the local Euler beam results are comparable to MD simulation results carried out at room temperature. However, when the SWCNTs have moderate aspect ratios, it is necessary to use the more refined nonlocal beam theory or the Timoshenko beam model for a better prediction of the critical strain. For short SWCNTs with large diameters, the nonlocal shell model with the appropriate small length scale parameter can provide critical strains that are in good agreement with MD results. However, for short SWCNTs with small diameters, more work has to be done to refine the nonlocal cylindrical shell model for better prediction of critical strains.

  4. Modeling Stress Strain Relationships and Predicting Failure Probabilities For Graphite Core Components

    Energy Technology Data Exchange (ETDEWEB)

    Duffy, Stephen [Cleveland State Univ., Cleveland, OH (United States)

    2013-09-09

    This project will implement inelastic constitutive models that will yield the requisite stress-strain information necessary for graphite component design. Accurate knowledge of stress states (both elastic and inelastic) is required to assess how close a nuclear core component is to failure. Strain states are needed to assess deformations in order to ascertain serviceability issues relating to failure, e.g., whether too much shrinkage has taken place for the core to function properly. Failure probabilities, as opposed to safety factors, are required in order to capture the bariability in failure strength in tensile regimes. The current stress state is used to predict the probability of failure. Stochastic failure models will be developed that can accommodate possible material anisotropy. This work will also model material damage (i.e., degradation of mechanical properties) due to radiation exposure. The team will design tools for components fabricated from nuclear graphite. These tools must readily interact with finite element software--in particular, COMSOL, the software algorithm currently being utilized by the Idaho National Laboratory. For the eleastic response of graphite, the team will adopt anisotropic stress-strain relationships available in COMSO. Data from the literature will be utilized to characterize the appropriate elastic material constants.

  5. Modeling Stress Strain Relationships and Predicting Failure Probabilities For Graphite Core Components

    International Nuclear Information System (INIS)

    Duffy, Stephen

    2013-01-01

    This project will implement inelastic constitutive models that will yield the requisite stress-strain information necessary for graphite component design. Accurate knowledge of stress states (both elastic and inelastic) is required to assess how close a nuclear core component is to failure. Strain states are needed to assess deformations in order to ascertain serviceability issues relating to failure, e.g., whether too much shrinkage has taken place for the core to function properly. Failure probabilities, as opposed to safety factors, are required in order to capture the bariability in failure strength in tensile regimes. The current stress state is used to predict the probability of failure. Stochastic failure models will be developed that can accommodate possible material anisotropy. This work will also model material damage (i.e., degradation of mechanical properties) due to radiation exposure. The team will design tools for components fabricated from nuclear graphite. These tools must readily interact with finite element software--in particular, COMSOL, the software algorithm currently being utilized by the Idaho National Laboratory. For the eleastic response of graphite, the team will adopt anisotropic stress-strain relationships available in COMSO. Data from the literature will be utilized to characterize the appropriate elastic material constants.

  6. Forming limit curves determined in high-speed Nakajima tests and predicted by a strain rate sensitive model

    Science.gov (United States)

    Weiß-Borkowski, Nathalie; Lian, Juhne; Marten, Thorsten; Tröster, Thomas; Münstermann, Sebastian; Bleck, Wolfgang

    2017-10-01

    Material characteristics such as yield strength and failure strain are affected by the loading speed. Even the start of instability and necking depends not only on the strain hardening coefficient but also on the strain rate sensitivity parameter. Therefore, the strain rate dependence of materials for both plasticity and the failure behavior is taken into account in crash simulations for strain rates up to 1,000 s-1. The current standard experiment for investigation of strain rate dependence is the high speed tensile test as described in a FAT guideline. Moreover, the need of material characterization at multi-axial loadings and high strain rates is pointed out in FAT guideline. Forming limit diagrams (FLD) can be used for the description of the material`s instability behavior at multi-axial loading. Usually, the FLD are determined quasi-statically at 1.5 mm/s. The usage of experimentally determined, quasi-static FLD also at high strain rates leads to great uncertainties and thus can be hardly used in crash simulations. A possibility for experimentally recording FLD at high forming rates > 100 s-1 offers the present described high speed Nakajima test. The results for the deep drawing steel DC01 illustrate the need of the determination of dynamic FLD. In this context, due to the strain rate dependence of the material behavior an extrapolation of quasi-static FLD is not feasible. Alternatively, the prediction of forming limit curves (FLC) at high strain rates is possible with the extended modified maximum force criterion. This new and extended model includes the strain rate dependence and therefore predicting forming limits at dynamic forming gets possible. The new approach is described and the accordance of experimental determined and predicted results for the begin of instability is presented.

  7. Analysis of Analytical Models Developed under the Uniaxial Strain Condition for Predicting Coal Permeability during Primary Depletion

    Directory of Open Access Journals (Sweden)

    Chuanming Li

    2017-11-01

    Full Text Available The stress-dependent permeability of coal during coalbed methane production has been extensively studied both experimentally and theoretically. However, how permeability changes as a function of stress variation is somewhat unclear to date, and currently used analytical models fail to accurately predict permeability evolution with gas depletion. Considering that the role played by changes in in situ stress in permeability evolution is critical, a comprehensive theoretical study was first conducted, through which it was found that coal permeability is determined by mean effective stress. Moreover, the influence of matrix shrinkage on cleat deformation and then coal permeability was overestimated by currently used models, leading to inaccuracy of the predicted permeability. By taking both mean effective stress and the influence of matrix shrinkage on cleat deformation into account, a new permeability model was developed under the uniaxial strain condition in order to precisely estimate permeability evolution during gas depletion. An in-depth investigation and comparison among four commonly-used permeability models, the Palmer and Mansoori (P&M model, Improved P&M model, Shi and Durucan (S&D model, and Cui and Bustin (C&B model, was then conducted. It was experimentally verified that a good match can be achieved between the lab data and the results predicted by the proposed model. Permeability variation of coalbed reservoirs associated with gas depletion is a consequence of two opposing effects: mechanical compaction and matrix shrinkage. In comparison, it was found that the coefficients of these two effects incorporated in those four models have a significant impact on permeability variation; and the accuracy of the values of initial cleat porosity and cleat compressibility, the bridges connecting permeability, and those two effects in analytical models, is extremely critical to permeability estimations. This study can shed light on improving the

  8. Demonstration of a multiscale modeling technique: prediction of the stress–strain response of light activated shape memory polymers

    International Nuclear Information System (INIS)

    Beblo, Richard V; Weiland, Lisa Mauck

    2010-01-01

    Presented is a multiscale modeling method applied to light activated shape memory polymers (LASMPs). LASMPs are a new class of shape memory polymer (SMPs) being developed for adaptive structures applications where a thermal stimulus is undesirable. LASMP developmental emphasis is placed on optical manipulation of Young's modulus. A multiscale modeling approach is employed to anticipate the soft and hard state moduli solely on the basis of a proposed molecular formulation. Employing such a model shows promise for expediting down-selection of favorable formulations for synthesis and testing, and subsequently accelerating LASMP development. An empirical adaptation of the model is also presented which has applications in system design once a formulation has been identified. The approach employs rotational isomeric state theory to build a molecular scale model of the polymer chain yielding a list of distances between the predicted crosslink locations, or r-values. The r-values are then fitted with Johnson probability density functions and used with Boltzmann statistical mechanics to predict stress as a function of the strain of the phantom polymer network. Empirical adaptation for design adds junction constraint theory to the modeling process. Junction constraint theory includes the effects of neighboring chain interactions. Empirical fitting results in numerically accurate Young's modulus predictions. The system is modular in nature and thus lends itself well to being adapted to other polymer systems and development applications

  9. Prediction of stress-strain state of municipal solid waste with application of soft soil creep model

    Directory of Open Access Journals (Sweden)

    Ofrikhter Vadim Grigor'evich

    Full Text Available The deformation of municipal solid waste is a complex process caused by the nature of MSW, the properties of which differ from the properties of common soils. The mass of municipal solid waste shows the mixed behaviour partially similar to granular soils, and partially - to cohesive. So, one of mechanical characteristics of MSW is the cohesion typical to cohesive soils, but at the same time the filtration coefficient of MSW has an order of 1 m/day that is characteristic for granular soils. It has been established that MSW massif can be simulated like the soil reinforced by randomly oriented fibers. Today a significant amount of the verified and well proved software products are available for numerical modelling of soils. The majority of them use finite element method (FEM. The soft soil creep model (SSC-model seems to be the most suitable for modelling of municipal solid waste, as it allows estimating the development of settlements in time with separation of primary and secondary consolidation. Unlike the soft soil, one of the factors of secondary consolidation of MSW is biological degradation, the influence of which is possible to consider at the definition of the modified parameters essential for soft soil model. Application of soft soil creep model allows carrying out the calculation of stress-strain state of waste from the beginning of landfill filling up to any moment of time both during the period of operation and in postclosure period. The comparative calculation presented in the paper is executed in Plaxis software using the soft-soil creep model in contrast to the calculation using the composite model of MSW. All the characteristics for SSC-model were derived from the composite model. The comparative results demonstrate the advantage of SSC-model for prediction of the development of MSW stress-strain state. As far as after the completion of the biodegradation processes MSW behaviour is similar to cohesion-like soils, the demonstrated

  10. Anisotropic finite element models for brain injury prediction: the sensitivity of axonal strain to white matter tract inter-subject variability.

    Science.gov (United States)

    Giordano, Chiara; Zappalà, Stefano; Kleiven, Svein

    2017-08-01

    Computational models incorporating anisotropic features of brain tissue have become a valuable tool for studying the occurrence of traumatic brain injury. The tissue deformation in the direction of white matter tracts (axonal strain) was repeatedly shown to be an appropriate mechanical parameter to predict injury. However, when assessing the reliability of axonal strain to predict injury in a population, it is important to consider the predictor sensitivity to the biological inter-subject variability of the human brain. The present study investigated the axonal strain response of 485 white matter subject-specific anisotropic finite element models of the head subjected to the same loading conditions. It was observed that the biological variability affected the orientation of the preferential directions (coefficient of variation of 39.41% for the elevation angle-coefficient of variation of 29.31% for the azimuth angle) and the determination of the mechanical fiber alignment parameter in the model (gray matter volume 55.55-70.75%). The magnitude of the maximum axonal strain showed coefficients of variation of 11.91%. On the contrary, the localization of the maximum axonal strain was consistent: the peak of strain was typically located in a 2 cm 3 volume of the brain. For a sport concussive event, the predictor was capable of discerning between non-injurious and concussed populations in several areas of the brain. It was concluded that, despite its sensitivity to biological variability, axonal strain is an appropriate mechanical parameter to predict traumatic brain injury.

  11. Maximum principal strain as a criterion for prediction of orthodontic mini-implants failure in subject-specific finite element models.

    Science.gov (United States)

    Albogha, Mhd Hassan; Kitahara, Toru; Todo, Mitsugu; Hyakutake, Hiroto; Takahashi, Ichiro

    2016-01-01

    To investigate the most reliable stress or strain parameters in subject-specific finite element (FE) models to predict success or failure of orthodontic mini-implants (OMIs). Subject-specific FE analysis was applied to 28 OMIs used for anchorage. Each model was developed using two computed tomography data sets, the first taken before OMI placement and the second taken immediately after placement. Of the 28 OMIs, 6 failed during the first 5 months, and 22 were successful. The bone compartment was divided into four zones in the FE models, and peak stress and strain parameters were calculated for each. Logistic regression of the failure (vs success) of OMIs on the stress and strain parameters in the models was conducted to verify the ability of these parameters to predict OMI failure. Failure was significantly dependent on principal strain parameters rather than stress parameters. Peak maximum principal strain in the bone 0.5 to 1 mm from the OMI surface was the best predictor of failure (R(2) = 0.8151). We propose the use of the maximum principal strain as a criterion for predicting OMI failure in FE models.

  12. Experimental tests of planar strain theory for predicting bone cross-sectional longitudinal and shear strains.

    Science.gov (United States)

    Verner, Kari A; Lehner, Michael; Lamas, Luis P; Main, Russell P

    2016-10-01

    Understanding of the diversity of skeletal loading regimes in vertebrate long bones during locomotion has been significantly enhanced by the application of planar strain theory (PST) to in vivo bone strain data. PST is used to model the distribution of longitudinal strains normal to the bone's transverse cross-section and the location of the neutral axis of bending. To our knowledge, the application of this theory to skeletal biomechanics has not been experimentally validated. We evaluated the accuracy of PST using strain measurements from emu tibiotarsi instrumented with four strain gauges and loaded in ex vivo four-point bending. Using measured strains from three-gauge combinations, PST was applied to predict strain values at a fourth gauge's location. Experimentally measured and predicted strain values correlated linearly with a slope near 1.0, suggesting that PST accurately predicts longitudinal strains. Additionally, we assessed the use of PST to extrapolate shear strains to locations on a bone not instrumented with rosette strain gauges. Guineafowl tibiotarsi were instrumented with rosette strain gauges and in vivo longitudinal and shear strains were measured during treadmill running. Individual-specific and sample-mean ratios between measured longitudinal strains from the medial and posterior bone surfaces were used to extrapolate posterior-site shear strain from shear strains measured on the medial surface. Measured and predicted shear strains at the posterior gauge site using either ratio showed trends for a positive correlation between measured and predicted strains, but the correlation did not equal 1.0 and had a non-zero intercept, suggesting that the use of PST should be carefully considered in the context of the goals of the study and the desired precision for the predicted shear strains. © 2016. Published by The Company of Biologists Ltd.

  13. Human responses in heat - comparison of the Predicted Heat Strain and the Fiala multi-node model for a case of intermittent work.

    Science.gov (United States)

    Lundgren-Kownacki, Karin; Martínez, Natividad; Johansson, Bo; Psikuta, Agnes; Annaheim, Simon; Kuklane, Kalev

    2017-12-01

    Two mathematical models of human thermal regulation include the rational Predicted Heat Strain (PHS) and the thermophysiological model by Fiala. The approaches of the models are different, however, they both aim at providing predictions of the thermophysiological responses to thermal environments of an average person. The aim of this study was to compare and analyze predictions of the two models against experimental data. The analysis also includes a gender comparison. The experimental data comprised of ten participants (5 males, 5 females, average anthropometric values were used as input) conducting an intermittent protocol of rotating tasks (cycling, stacking, stepping and arm crank) of moderate metabolic activities (134-291W/m 2 ) with breaks in-between in a controlled environmental condition (34°C, 60% RH). The validation consisted of the predictions' comparison against experimental data from 2.5h of data of rectal temperature and mean skin temperature based on contact thermometry from four body locations. The PHS model over-predicted rectal temperatures during the first activity for males and the cooling effectiveness of sweat in the recovery periods, for both males and females. As a result, the PHS simulation underestimated the thermal strain in this context. The Fiala model accurately predicted the rectal temperature throughout the exposure. The fluctuation of the experimental mean skin temperature was not reflected in any of the models. However, the PHS simulation model showed better agreement than the Fiala model. As both models predicted responses more accurately for males than females, we suggest that in future development of the models it is important to take this result into account. The paper further discusses possible sources of the observed discrepancies and concludes with some suggestions for modifications. Copyright © 2017 Elsevier Ltd. All rights reserved.

  14. Highly Predictive Model for a Protective Immune Response to the A(H1N1pdm2009 Influenza Strain after Seasonal Vaccination.

    Directory of Open Access Journals (Sweden)

    Karsten Jürchott

    Full Text Available Understanding the immune response after vaccination against new influenza strains is highly important in case of an imminent influenza pandemic and for optimization of seasonal vaccination strategies in high risk population groups, especially the elderly. Models predicting the best sero-conversion response among the three strains in the seasonal vaccine were recently suggested. However, these models use a large number of variables and/or information post- vaccination. Here in an exploratory pilot study, we analyzed the baseline immune status in young (<31 years, N = 17 versus elderly (≥50 years, N = 20 donors sero-negative to the newly emerged A(H1N1pdm09 influenza virus strain and correlated it with the serological response to that specific strain after seasonal influenza vaccination. Extensive multi-chromatic FACS analysis (36 lymphocyte sub-populations measured was used to quantitatively assess the cellular immune status before vaccination. We identified CD4+ T cells, and amongst them particularly naive CD4+ T cells, as the best correlates for a successful A(H1N1pdm09 immune response. Moreover, the number of influenza strains a donor was sero-negative to at baseline (NSSN in addition to age, as expected, were important predictive factors. Age, NSSN and CD4+ T cell count at baseline together predicted sero-protection (HAI≥40 to A(H1N1pdm09 with a high accuracy of 89% (p-value = 0.00002. An additional validation study (N = 43 vaccinees sero-negative to A(H1N1pdm09 has confirmed the predictive value of age, NSSN and baseline CD4+ counts (accuracy = 85%, p-value = 0.0000004. Furthermore, the inclusion of donors at ages 31-50 had shown that the age predictive function is not linear with age but rather a sigmoid with a midpoint at about 50 years. Using these results we suggest a clinically relevant prediction model that gives the probability for non-protection to A(H1N1pdm09 influenza strain after seasonal multi-valent vaccination as a

  15. One-Way Coupling of an Advanced CFD Multi-Physics Model to FEA for Predicting Stress-Strain in the Solidifying Shell during Continuous Casting of Steel

    Science.gov (United States)

    Svensson, Johan; Ramírez López, Pavel E.; Jalali, Pooria N.; Cervantes, Michel

    2015-06-01

    One of the main targets for Continuous Casting (CC) modelling is the actual prediction of defects during transient events. However, the majority of CC models are based on a statistical approach towards flow and powder performance, which is unable to capture the subtleties of small variations in casting conditions during real industrial operation or the combined effects of such changes leading eventually to defects. An advanced Computational Fluid Dynamics (CFD) model; which accounts for transient changes on lubrication during casting due to turbulent flow dynamics and mould oscillation has been presented on MCWASP XIV (Austria) to address these issues. The model has been successfully applied to the industrial environment to tackle typical problems such as lack of lubrication or unstable flows. However, a direct application to cracking had proven elusive. The present paper describes how results from this advanced CFD-CC model have been successfully coupled to structural Finite Element Analysis (FEA) for prediction of stress-strains as a function of irregular lubrication conditions in the mould. The main challenge for coupling was the extraction of the solidified shell from CFD calculations (carried out with a hybrid structured mesh) and creating a geometry by using iso-surfaces, re-meshing and mapping loads (e.g. temperature, pressure and external body forces), which served as input to mechanical stress-strain calculations. Preliminary results for CC of slabs show that the temperature distribution within the shell causes shrinkage and thermal deformation; which are in turn, the main source of stress. Results also show reasonable stress levels of 10-20 MPa in regions, where the shell is thin and exposed to large temperature gradients. Finally, predictions are in good agreement with prior works where stresses indicate compression at the slab surface, while tension is observed at the interior; generating a characteristic stress-strain state during solidification in CC.

  16. Haldane model under nonuniform strain

    Science.gov (United States)

    Ho, Yen-Hung; Castro, Eduardo V.; Cazalilla, Miguel A.

    2017-10-01

    We study the Haldane model under strain using a tight-binding approach, and compare the obtained results with the continuum-limit approximation. As in graphene, nonuniform strain leads to a time-reversal preserving pseudomagnetic field that induces (pseudo-)Landau levels. Unlike a real magnetic field, strain lifts the degeneracy of the zeroth pseudo-Landau levels at different valleys. Moreover, for the zigzag edge under uniaxial strain, strain removes the degeneracy within the pseudo-Landau levels by inducing a tilt in their energy dispersion. The latter arises from next-to-leading order corrections to the continuum-limit Hamiltonian, which are absent for a real magnetic field. We show that, for the lowest pseudo-Landau levels in the Haldane model, the dominant contribution to the tilt is different from graphene. In addition, although strain does not strongly modify the dispersion of the edge states, their interplay with the pseudo-Landau levels is different for the armchair and zigzag ribbons. Finally, we study the effect of strain in the band structure of the Haldane model at the critical point of the topological transition, thus shedding light on the interplay between nontrivial topology and strain in quantum anomalous Hall systems.

  17. Geomechanical Modeling of CO2 Injection Site to Predict Wellbore Stresses and Strains for the Design of Wellbore Seal Repair Materials

    Science.gov (United States)

    Sobolik, S. R.; Gomez, S. P.; Matteo, E. N.; Stormont, J.

    2015-12-01

    This paper will present the results of large-scale three-dimensional calculations simulating the hydrological-mechanical behavior of a CO2injection reservoir and the resulting effects on wellbore casings and sealant repair materials. A critical aspect of designing effective wellbore seal repair materials is predicting thermo-mechanical perturbations in local stress that can compromise seal integrity. The DOE-NETL project "Wellbore Seal Repair Using Nanocomposite Materials," is interested in the stress-strain history of abandoned wells, as well as changes in local pressure, stress, and temperature conditions that accompany carbon dioxide injection or brine extraction. Two distinct computational models comprise the current modeling effort. The first is a field scale model that uses the stratigraphy, material properties, and injection history from a pilot CO2injection operation in Cranfield, MS to develop a stress-strain history for wellbore locations from 100 to 400 meters from an injection well. The results from the field scale model are used as input to a more detailed model of a wellbore casing. The 3D wellbore model examines the impacts of various loading scenarios on a casing structure. This model has been developed in conjunction with bench-top experiments of an integrated seal system in an idealized scaled wellbore mock-up being used to test candidate seal repair materials. The results from these models will be used to estimate the necessary mechanical properties needed for a successful repair material. This material is based upon work supported by the US Department of Energy (DOE) National Energy Technology Laboratory (NETL) under Grant Number DE-FE0009562. This project is managed and administered by the Storage Division of the NETL and funded by DOE/NETL and cost-sharing partners. This work was funded in part by the Center for Frontiers of Subsurface Energy Security, an Energy Frontier Research Center funded by the US Department of Energy, Office of Science

  18. Cultural Resource Predictive Modeling

    Science.gov (United States)

    2017-10-01

    refining formal, inductive predictive models is the quality of the archaeological and environmental data. To build models efficiently, relevant...geomorphology, and historic information . Lessons Learned: The original model was focused on the identification of prehistoric resources. This...system but uses predictive modeling informally . For example, there is no probability for buried archaeological deposits on the Burton Mesa, but there is

  19. Predictive modeling of complications.

    Science.gov (United States)

    Osorio, Joseph A; Scheer, Justin K; Ames, Christopher P

    2016-09-01

    Predictive analytic algorithms are designed to identify patterns in the data that allow for accurate predictions without the need for a hypothesis. Therefore, predictive modeling can provide detailed and patient-specific information that can be readily applied when discussing the risks of surgery with a patient. There are few studies using predictive modeling techniques in the adult spine surgery literature. These types of studies represent the beginning of the use of predictive analytics in spine surgery outcomes. We will discuss the advancements in the field of spine surgery with respect to predictive analytics, the controversies surrounding the technique, and the future directions.

  20. Archaeological predictive model set.

    Science.gov (United States)

    2015-03-01

    This report is the documentation for Task 7 of the Statewide Archaeological Predictive Model Set. The goal of this project is to : develop a set of statewide predictive models to assist the planning of transportation projects. PennDOT is developing t...

  1. Wind power prediction models

    Science.gov (United States)

    Levy, R.; Mcginness, H.

    1976-01-01

    Investigations were performed to predict the power available from the wind at the Goldstone, California, antenna site complex. The background for power prediction was derived from a statistical evaluation of available wind speed data records at this location and at nearby locations similarly situated within the Mojave desert. In addition to a model for power prediction over relatively long periods of time, an interim simulation model that produces sample wind speeds is described. The interim model furnishes uncorrelated sample speeds at hourly intervals that reproduce the statistical wind distribution at Goldstone. A stochastic simulation model to provide speed samples representative of both the statistical speed distributions and correlations is also discussed.

  2. Zephyr - the prediction models

    DEFF Research Database (Denmark)

    Nielsen, Torben Skov; Madsen, Henrik; Nielsen, Henrik Aalborg

    2001-01-01

    utilities as partners and users. The new models are evaluated for five wind farms in Denmark as well as one wind farm in Spain. It is shown that the predictions based on conditional parametric models are superior to the predictions obatined by state-of-the-art parametric models.......This paper briefly describes new models and methods for predicationg the wind power output from wind farms. The system is being developed in a project which has the research organization Risø and the department of Informatics and Mathematical Modelling (IMM) as the modelling team and all the Danish...

  3. Strain histograms are equal to strain ratios in predicting malignancy in breast tumours

    Science.gov (United States)

    Ewertsen, Caroline; Sletting, Susanne; Talman, Maj-Lis; Vejborg, Ilse; Bachmann Nielsen, Michael

    2017-01-01

    Objectives To assess whether strain histograms are equal to strain ratios in predicting breast tumour malignancy and to see if either could be used to upgrade Breast Imaging Reporting and Data System (BI-RADS) 3 tumours for immediate biopsy. Methods Ninety-nine breast tumours were examined using B-mode BI-RADS scorings and strain elastography. Strain histograms and ratios were assessed, and areas- under-the-receiver-operating-characteristic-curve (AUROC) for each method calculated. In BI-RADS 3 tumours cut-offs for strain histogram and ratio values were calculated to see if some tumours could be upgraded for immediate biopsy. Linear regression was performed to evaluate the effect of tumour depth and size, and breast density on strain elastography. Results Forty-four of 99 (44.4%) tumours were malignant. AUROC of BI-RADS, strain histograms and strain ratios were 0.949, 0.830 and 0.794 respectively. There was no significant difference between AUROCs of strain histograms and strain ratios (P = 0.405), while they were both inferior to BI-RADS scoring (PBI-RADS 3 tumours were malignant. When cut-offs of 189 for strain histograms and 1.44 for strain ratios were used to upgrade BI-RADS 3 tumours, AUROCS were 0.961 (Strain histograms and BI-RADS) and 0.941 (Strain ratios and BI-RADS). None of them was significantly different from BI-RADS scoring alone (P = 0.249 and P = 0.414). Tumour size and depth, and breast density influenced neither strain histograms (P = 0.196, P = 0.115 and P = 0.321) nor strain ratios (P = 0.411, P = 0.596 and P = 0.321) Conclusion Strain histogram analyses are reliable and easy to do in breast cancer diagnosis and perform comparably to strain ratio analyses. No significant difference in AUROCs between BI-RADS scoring and elastography combined with BI-RADS scoring was found in this study. PMID:29073170

  4. Strain histograms are equal to strain ratios in predicting malignancy in breast tumours.

    Directory of Open Access Journals (Sweden)

    Jonathan Frederik Carlsen

    Full Text Available To assess whether strain histograms are equal to strain ratios in predicting breast tumour malignancy and to see if either could be used to upgrade Breast Imaging Reporting and Data System (BI-RADS 3 tumours for immediate biopsy.Ninety-nine breast tumours were examined using B-mode BI-RADS scorings and strain elastography. Strain histograms and ratios were assessed, and areas- under-the-receiver-operating-characteristic-curve (AUROC for each method calculated. In BI-RADS 3 tumours cut-offs for strain histogram and ratio values were calculated to see if some tumours could be upgraded for immediate biopsy. Linear regression was performed to evaluate the effect of tumour depth and size, and breast density on strain elastography.Forty-four of 99 (44.4% tumours were malignant. AUROC of BI-RADS, strain histograms and strain ratios were 0.949, 0.830 and 0.794 respectively. There was no significant difference between AUROCs of strain histograms and strain ratios (P = 0.405, while they were both inferior to BI-RADS scoring (P<0.001, P = 0.008. Four out of 26 BI-RADS 3 tumours were malignant. When cut-offs of 189 for strain histograms and 1.44 for strain ratios were used to upgrade BI-RADS 3 tumours, AUROCS were 0.961 (Strain histograms and BI-RADS and 0.941 (Strain ratios and BI-RADS. None of them was significantly different from BI-RADS scoring alone (P = 0.249 and P = 0.414. Tumour size and depth, and breast density influenced neither strain histograms (P = 0.196, P = 0.115 and P = 0.321 nor strain ratios (P = 0.411, P = 0.596 and P = 0.321.Strain histogram analyses are reliable and easy to do in breast cancer diagnosis and perform comparably to strain ratio analyses. No significant difference in AUROCs between BI-RADS scoring and elastography combined with BI-RADS scoring was found in this study.

  5. Inverse and Predictive Modeling

    Energy Technology Data Exchange (ETDEWEB)

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

    2017-09-27

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

  6. A strain-mediated corrosion model for bioabsorbable metallic stents.

    Science.gov (United States)

    Galvin, E; O'Brien, D; Cummins, C; Mac Donald, B J; Lally, C

    2017-06-01

    This paper presents a strain-mediated phenomenological corrosion model, based on the discrete finite element modelling method which was developed for use with the ANSYS Implicit finite element code. The corrosion model was calibrated from experimental data and used to simulate the corrosion performance of a WE43 magnesium alloy stent. The model was found to be capable of predicting the experimentally observed plastic strain-mediated mass loss profile. The non-linear plastic strain model, extrapolated from the experimental data, was also found to adequately capture the corrosion-induced reduction in the radial stiffness of the stent over time. The model developed will help direct future design efforts towards the minimisation of plastic strain during device manufacture, deployment and in-service, in order to reduce corrosion rates and prolong the mechanical integrity of magnesium devices. The need for corrosion models that explore the interaction of strain with corrosion damage has been recognised as one of the current challenges in degradable material modelling (Gastaldi et al., 2011). A finite element based plastic strain-mediated phenomenological corrosion model was developed in this work and was calibrated based on the results of the corrosion experiments. It was found to be capable of predicting the experimentally observed plastic strain-mediated mass loss profile and the corrosion-induced reduction in the radial stiffness of the stent over time. To the author's knowledge, the results presented here represent the first experimental calibration of a plastic strain-mediated corrosion model of a corroding magnesium stent. Copyright © 2017 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

  7. Five challenges in modelling interacting strain dynamics

    Directory of Open Access Journals (Sweden)

    Paul S. Wikramaratna

    2015-03-01

    Full Text Available Population epidemiological models where hosts can be infected sequentially by different strains have the potential to help us understand many important diseases. Researchers have in recent years started to develop and use such models, but the extra layer of complexity from multiple strains brings with it many technical challenges. It is therefore hard to build models which have realistic assumptions yet are tractable. Here we outline some of the main challenges in this area. First we begin with the fundamental question of how to translate from complex small-scale dynamics within a host to useful population models. Next we consider the nature of so-called “strain space”. We describe two key types of host heterogeneities, and explain how models could help generate a better understanding of their effects. Finally, for diseases with many strains, we consider the challenge of modelling how immunity accumulates over multiple exposures.

  8. Patient-Specific MRI-Based Right Ventricle Models Using Different Zero-Load Diastole and Systole Geometries for Better Cardiac Stress and Strain Calculations and Pulmonary Valve Replacement Surgical Outcome Predictions.

    Directory of Open Access Journals (Sweden)

    Dalin Tang

    Full Text Available Accurate calculation of ventricular stress and strain is critical for cardiovascular investigations. Sarcomere shortening in active contraction leads to change of ventricular zero-stress configurations during the cardiac cycle. A new model using different zero-load diastole and systole geometries was introduced to provide more accurate cardiac stress/strain calculations with potential to predict post pulmonary valve replacement (PVR surgical outcome.Cardiac magnetic resonance (CMR data were obtained from 16 patients with repaired tetralogy of Fallot prior to and 6 months after pulmonary valve replacement (8 male, 8 female, mean age 34.5 years. Patients were divided into Group 1 (n = 8 with better post PVR outcome and Group 2 (n = 8 with worse post PVR outcome based on their change in RV ejection fraction (EF. CMR-based patient-specific computational RV/LV models using one zero-load geometry (1G model and two zero-load geometries (diastole and systole, 2G model were constructed and RV wall thickness, volume, circumferential and longitudinal curvatures, mechanical stress and strain were obtained for analysis. Pairwise T-test and Linear Mixed Effect (LME model were used to determine if the differences from the 1G and 2G models were statistically significant, with the dependence of the pair-wise observations and the patient-slice clustering effects being taken into consideration. For group comparisons, continuous variables (RV volumes, WT, C- and L- curvatures, and stress and strain values were summarized as mean ± SD and compared between the outcome groups by using an unpaired Student t-test. Logistic regression analysis was used to identify potential morphological and mechanical predictors for post PVR surgical outcome.Based on results from the 16 patients, mean begin-ejection stress and strain from the 2G model were 28% and 40% higher than that from the 1G model, respectively. Using the 2G model results, RV EF changes correlated negatively with

  9. Femoral strain during walking predicted with muscle forces from static and dynamic optimization.

    Science.gov (United States)

    Edwards, W Brent; Miller, Ross H; Derrick, Timothy R

    2016-05-03

    Mechanical strain plays an important role in skeletal health, and the ability to accurately and noninvasively quantify bone strain in vivo may be used to develop preventive measures that improve bone quality and decrease fracture risk. A non-invasive estimation of bone strain requires combined musculoskeletal - finite element modeling, for which the applied muscle forces are usually obtained from static optimization (SO) methods. In this study, we compared finite element predicted femoral strains in walking using muscle forces obtained from SO to those obtained from forward dynamics (FD) simulation. The general trends in strain distributions were similar between FD and SO derived conditions and both agreed well with previously reported in vivo strain gage measurements. On the other hand, differences in peak maximum (εmax) and minimum (εmin) principal strain magnitudes were as high as 32% between FD (εmax/εmin=945/-1271με) and SO (εmax/εmin=752/-859με). These large differences in strain magnitudes were observed during the first half of stance, where SO predicted lower gluteal muscle forces and virtually no co-contraction of the hip adductors compared to FD. The importance of these results will likely depend on the purpose/application of the modeling procedure. If the goal is to obtain a generalized strain distribution for adaptive bone remodeling algorithms, then traditional SO is likely sufficient. In cases were strain magnitudes are critical, as is the case with fracture risk assessment, bone strain estimation may benefit by including muscle activation and contractile dynamics in SO, or by using FD when practical. Copyright © 2016 Elsevier Ltd. All rights reserved.

  10. Prediction of the origin of French Legionella pneumophila strains using a mixed-genome microarray.

    Science.gov (United States)

    Den Boer, Jeroen W; Euser, Sjoerd M; Nagelkerke, Nico J; Schuren, Frank; Jarraud, Sophie; Etienne, Jerome

    2013-07-01

    Legionella is a water and soil bacterium that can infect humans, causing a pneumonia known as Legionnaires' disease. The pneumonia is almost exclusively caused by the species L. pneumophila, of which serogroup 1 is responsible for 90% of patients. Within serogroup 1, large differences in prevalence in clinical isolates have been described. A recent study, using a Dutch Legionella strain collection, identified five virulence associated markers. In our study, we verify whether these five Dutch markers can predict the patient or environmental origin of a French Legionella strain collection. In addition, we identify new potential virulence markers and verify whether these can predict better. A total of 219 French patient isolates and environmental strains were compared using a mixed-genome micro-array. The micro-array data were analysed to identify predictive markers, using a Random Forest algorithm combined with a logistic regression model. The sequences of the identified markers were compared with eleven known Legionella genomes, using BlastN and BlastX; the functionality for each of the predictive markers was checked in the literature. The five Dutch markers insufficiently predicted the patient or environmental origin of the French Legionella strains. Subsequent analyses identified four predictive markers for the French collection that were used for the logistic regression model. This model showed a negative predictive value of 91%. Three of the French markers differed from the Dutch markers, one showed considerable overlap and was found in one of the Legionella genomes (Lorraine strain). This marker encodes for a structural toxin protein RtxA, described for L. pneumophila as a factor involved in virulence and entry in both human cells and amoebae. The combination of a mixed-genome micro-array and statistical analysis using a Random Forest algorithm has identified virulence markers in a consistent way. The Lorraine strain and related Dutch and French Legionella

  11. Novel Approach for Prediction of Localized Necking in Case of Nonlinear Strain Paths

    Science.gov (United States)

    Drotleff, K.; Liewald, M.

    2017-09-01

    Rising customer expectations regarding design complexity and weight reduction of sheet metal components alongside with further reduced time to market implicate increased demand for process validation using numerical forming simulation. Formability prediction though often is still based on the forming limit diagram first presented in the 1960s. Despite many drawbacks in case of nonlinear strain paths and major advances in research in the recent years, the forming limit curve (FLC) is still one of the most commonly used criteria for assessing formability of sheet metal materials. Especially when forming complex part geometries nonlinear strain paths may occur, which cannot be predicted using the conventional FLC-Concept. In this paper a novel approach for calculation of FLCs for nonlinear strain paths is presented. Combining an interesting approach for prediction of FLC using tensile test data and IFU-FLC-Criterion a model for prediction of localized necking for nonlinear strain paths can be derived. Presented model is purely based on experimental tensile test data making it easy to calibrate for any given material. Resulting prediction of localized necking is validated using an experimental deep drawing specimen made of AA6014 material having a sheet thickness of 1.04 mm. The results are compared to IFU-FLC-Criterion based on data of pre-stretched Nakajima specimen.

  12. Predictive Surface Complexation Modeling

    Energy Technology Data Exchange (ETDEWEB)

    Sverjensky, Dimitri A. [Johns Hopkins Univ., Baltimore, MD (United States). Dept. of Earth and Planetary Sciences

    2016-11-29

    Surface complexation plays an important role in the equilibria and kinetics of processes controlling the compositions of soilwaters and groundwaters, the fate of contaminants in groundwaters, and the subsurface storage of CO2 and nuclear waste. Over the last several decades, many dozens of individual experimental studies have addressed aspects of surface complexation that have contributed to an increased understanding of its role in natural systems. However, there has been no previous attempt to develop a model of surface complexation that can be used to link all the experimental studies in order to place them on a predictive basis. Overall, my research has successfully integrated the results of the work of many experimentalists published over several decades. For the first time in studies of the geochemistry of the mineral-water interface, a practical predictive capability for modeling has become available. The predictive correlations developed in my research now enable extrapolations of experimental studies to provide estimates of surface chemistry for systems not yet studied experimentally and for natural and anthropogenically perturbed systems.

  13. Computational modeling of dynamic mechanical properties of pure polycrystalline magnesium under high loading strain rates

    Directory of Open Access Journals (Sweden)

    Li Qizhen

    2015-01-01

    Full Text Available Computational simulations were performed to investigate the dynamic mechanical behavior of pure polycrystalline magnesium under different high loading strain rates with the values of 800, 1000, 2000, and 3600 s−1. The Johnson-Cook model was utilized in the simulations based on finite element modeling. The results showed that the simulations provided well-matched predictions of the material behavior such as the strain rate-time history, the stress-strain curve, and the temperature increase. Under high loading strain rates, the tested material experienced linear strain hardening at the early stage of plastic deformation, increased strain hardening at the intermediate plastic deformation region, and decreased strain hardening at the region before fracture. The strain hardening rates for the studied high loading strain rate cases do not vary much with the change of strain rates.

  14. High strain-rate compressive behavior and constitutive modeling of selected polymers

    Directory of Open Access Journals (Sweden)

    Yokoyama T.

    2012-08-01

    Full Text Available The present paper deals with constitutive modeling of the compressive stress-strain behavior of selected polymers at strain rates from 10−3 to 103/s using a modified Ramberg-Osgood equation. High strain-rate compressive stress-strain curves for four different commercially available extruded polymers are determined on the standard split Hopkinson pressure bar. The low and intermediate strain-rates compressive stress-strain relations are measured in an Instron testing machine. The five parameters for the modified Ramberg-Osgood equation are determined by fitting to the experimental compressive stress-strain data using a least-squares fit. The compressive stress-strain curves at three different strain rates derived from the modified Ramberg-Osgood models are compared with the experimental results. It is shown that the compressive stress-strain behavior during loading process can be successfully predicted by the modified Ramberg-Osgood equation.

  15. Brittle superconducting magnets: an equivilent strain model

    International Nuclear Information System (INIS)

    Barzi, E.; Danuso, M.

    2010-01-01

    To exceed fields of 10 T in accelerator magnets, brittle superconductors like A15 Nb 3 Sn and Nb 3 Al or ceramic High Temperature Superconductors have to be used. For such brittle superconductors it is not their maximum tensile yield stress that limits their structural resistance as much as strain values that provoke deformations in their delicate lattice, which in turn affect their superconducting properties. Work on the sensitivity of Nb 3 Sn cables to strain has been conducted in a number of stress states, including uniaxial and multi-axial, producing usually different results. This has made the need of a constituent design criterion imperative for magnet builders. In conventional structural problems an equivalent stress model is typically used to verify mechanical soundness. In the superconducting community a simple scalar equivalent strain to be used in place of an equivalent stress would be an extremely useful tool. As is well known in fundamental mechanics, there is not one single way to reduce a multiaxial strain state as represented by a 2nd order tensor to a scalar. The conceptual experiment proposed here will help determine the best scalar representation to use in the identification of an equivalent strain model.

  16. Brittle superconducting magnets: an equivilent strain model

    Energy Technology Data Exchange (ETDEWEB)

    Barzi, E.; /Fermilab; Danuso, M.

    2010-08-01

    To exceed fields of 10 T in accelerator magnets, brittle superconductors like A15 Nb{sub 3}Sn and Nb{sub 3}Al or ceramic High Temperature Superconductors have to be used. For such brittle superconductors it is not their maximum tensile yield stress that limits their structural resistance as much as strain values that provoke deformations in their delicate lattice, which in turn affect their superconducting properties. Work on the sensitivity of Nb{sub 3}Sn cables to strain has been conducted in a number of stress states, including uniaxial and multi-axial, producing usually different results. This has made the need of a constituent design criterion imperative for magnet builders. In conventional structural problems an equivalent stress model is typically used to verify mechanical soundness. In the superconducting community a simple scalar equivalent strain to be used in place of an equivalent stress would be an extremely useful tool. As is well known in fundamental mechanics, there is not one single way to reduce a multiaxial strain state as represented by a 2nd order tensor to a scalar. The conceptual experiment proposed here will help determine the best scalar representation to use in the identification of an equivalent strain model.

  17. Candidate Prediction Models and Methods

    DEFF Research Database (Denmark)

    Nielsen, Henrik Aalborg; Nielsen, Torben Skov; Madsen, Henrik

    2005-01-01

    This document lists candidate prediction models for Work Package 3 (WP3) of the PSO-project called ``Intelligent wind power prediction systems'' (FU4101). The main focus is on the models transforming numerical weather predictions into predictions of power production. The document also outlines...

  18. The emergence of the activity reduces conflict related strain (ARCAS) model: A test of a conditional mediation model of workplace conflict and employee strain

    NARCIS (Netherlands)

    Dijkstra, M.T.M.; Beersma, B.; Cornelissen, R. A. W. M.

    2012-01-01

    To test and extend the emerging Activity Reduces Conflict-Associated Strain (ARCAS) model, we predicted that the relationship between task conflict and employee strain would be weakened to the extent that people experience high organization-based self-esteem (OBSE). A survey among Dutch employees

  19. The emergence of the Activity Reduces Conflict Associated Strain (ARCAS) model: a test of a conditional mediation model of workplace conflict and employee strain

    NARCIS (Netherlands)

    Dijkstra, M.T.M.; Beersma, B.; Cornelissen, R.A.W.M.

    2012-01-01

    To test and extend the emerging Activity Reduces Conflict-Associated Strain (ARCAS) model, we predicted that the relationship between task conflict and employee strain would be weakened to the extent that people experience high organization-based self-esteem (OBSE). A survey among Dutch employees

  20. Melanoma risk prediction models

    Directory of Open Access Journals (Sweden)

    Nikolić Jelena

    2014-01-01

    Full Text Available Background/Aim. The lack of effective therapy for advanced stages of melanoma emphasizes the importance of preventive measures and screenings of population at risk. Identifying individuals at high risk should allow targeted screenings and follow-up involving those who would benefit most. The aim of this study was to identify most significant factors for melanoma prediction in our population and to create prognostic models for identification and differentiation of individuals at risk. Methods. This case-control study included 697 participants (341 patients and 356 controls that underwent extensive interview and skin examination in order to check risk factors for melanoma. Pairwise univariate statistical comparison was used for the coarse selection of the most significant risk factors. These factors were fed into logistic regression (LR and alternating decision trees (ADT prognostic models that were assessed for their usefulness in identification of patients at risk to develop melanoma. Validation of the LR model was done by Hosmer and Lemeshow test, whereas the ADT was validated by 10-fold cross-validation. The achieved sensitivity, specificity, accuracy and AUC for both models were calculated. The melanoma risk score (MRS based on the outcome of the LR model was presented. Results. The LR model showed that the following risk factors were associated with melanoma: sunbeds (OR = 4.018; 95% CI 1.724- 9.366 for those that sometimes used sunbeds, solar damage of the skin (OR = 8.274; 95% CI 2.661-25.730 for those with severe solar damage, hair color (OR = 3.222; 95% CI 1.984-5.231 for light brown/blond hair, the number of common naevi (over 100 naevi had OR = 3.57; 95% CI 1.427-8.931, the number of dysplastic naevi (from 1 to 10 dysplastic naevi OR was 2.672; 95% CI 1.572-4.540; for more than 10 naevi OR was 6.487; 95%; CI 1.993-21.119, Fitzpatricks phototype and the presence of congenital naevi. Red hair, phototype I and large congenital naevi were

  1. Prediction of thermal and mechanical stress-strain responses of TMC's subjected to complex TMF histories

    Science.gov (United States)

    Johnson, W. S.; Mirdamadi, M.

    1994-01-01

    This paper presents an experimental and analytical evaluation of cross-plied laminates of Ti-15V-3Cr-3Al-3Sn (Ti-15-3) matrix reinforced with continuous silicon-carbide fibers (SCS-6) subjected to a complex TMF loading profile. Thermomechanical fatigue test techniques were developed to conduct a simulation of a generic hypersonic flight profile. A micromechanical analysis was used. The analysis predicts the stress-strain response of the laminate and of the constituents in each ply during thermal and mechanical cycling by using only constituent properties as input. The fiber was modeled as elastic with transverse orthotropic and temperature-dependent properties. The matrix was modeled using a thermoviscoplastic constitutive relation. The fiber transverse modulus was reduced in the analysis to simulate the fiber-matrix interface failures. Excellent correlation was found between measured and predicted laminate stress-strain response due to generic hypersonic flight profile when fiber debonding was modeled.

  2. Estimation of respiratory heat flows in prediction of heat strain among Taiwanese steel workers.

    Science.gov (United States)

    Chen, Wang-Yi; Juang, Yow-Jer; Hsieh, Jung-Yu; Tsai, Perng-Jy; Chen, Chen-Peng

    2017-01-01

    International Organization for Standardization 7933 standard provides evaluation of required sweat rate (RSR) and predicted heat strain (PHS). This study examined and validated the approximations in these models estimating respiratory heat flows (RHFs) via convection (C res ) and evaporation (E res ) for application to Taiwanese foundry workers. The influence of change in RHF approximation to the validity of heat strain prediction in these models was also evaluated. The metabolic energy consumption and physiological quantities of these workers performing at different workloads under elevated wet-bulb globe temperature (30.3 ± 2.5 °C) were measured on-site and used in the calculation of RHFs and indices of heat strain. As the results show, the RSR model overestimated the C res for Taiwanese workers by approximately 3 % and underestimated the E res by 8 %. The C res approximation in the PHS model closely predicted the convective RHF, while the E res approximation over-predicted by 11 %. Linear regressions provided better fit in C res approximation (R 2  = 0.96) than in E res approximation (R 2  ≤ 0.85) in both models. The predicted C res deviated increasingly from the observed value when the WBGT reached 35 °C. The deviations of RHFs observed for the workers from those predicted using the RSR or PHS models did not significantly alter the heat loss via the skin, as the RHFs were in general of a level less than 5 % of the metabolic heat consumption. Validation of these approximations considering thermo-physiological responses of local workers is necessary for application in scenarios of significant heat exposure.

  3. Finite Element Modeling of the Behavior of Armor Materials Under High Strain Rates and Large Strains

    Science.gov (United States)

    Polyzois, Ioannis

    For years high strength steels and alloys have been widely used by the military for making armor plates. Advances in technology have led to the development of materials with improved resistance to penetration and deformation. Until recently, the behavior of these materials under high strain rates and large strains has been primarily based on laboratory testing using the Split Hopkinson Pressure Bar apparatus. With the advent of sophisticated computer programs, computer modeling and finite element simulations are being developed to predict the deformation behavior of these metals for a variety of conditions similar to those experienced during combat. In the present investigation, a modified direct impact Split Hopkinson Pressure Bar apparatus was modeled using the finite element software ABAQUS 6.8 for the purpose of simulating high strain rate compression of specimens of three armor materials: maraging steel 300, high hardness armor (HHA), and aluminum alloy 5083. These armor materials, provided by the Canadian Department of National Defence, were tested at the University of Manitoba by others. In this study, the empirical Johnson-Cook visco-plastic and damage models were used to simulate the deformation behavior obtained experimentally. A series of stress-time plots at various projectile impact momenta were produced and verified by comparison with experimental data. The impact momentum parameter was chosen rather than projectile velocity to normalize the initial conditions for each simulation. Phenomena such as the formation of adiabatic shear bands caused by deformation at high strains and strain rates were investigated through simulations. It was found that the Johnson-Cook model can accurately simulate the behavior of body-centered cubic (BCC) metals such as steels. The maximum shear stress was calculated for each simulation at various impact momenta. The finite element model showed that shear failure first occurred in the center of the cylindrical specimen and

  4. Prediction of the Strain Response of Poly-AlN/(100Si Surface Acoustic Wave Resonator and Experimental Analysis

    Directory of Open Access Journals (Sweden)

    Shuo Chen

    2016-04-01

    Full Text Available The strain sensitivity of the Aluminum Nitride (AlN/Silicon (Si surface acoustic wave resonator (SAWR is predicted based on a modeling method introduced in this work, and further compared with experimental results. The strain influence on both the period of the inter-digital transducer (IDT and the sound velocity is taken into consideration when modeling the strain response. From the modeling results, AlN and Si have opposite responses to strain; hence, for the AlN/Si-based SAWR, both a positive and a negative strain coefficient factor can be achieved by changing the thickness of the AlN layer, which is confirmed by strain response testing based on a silicon cantilever structure with two AlN configurations (1 μm and 3 μm in thickness, respectively.

  5. Prediction of the Strain Response of Poly-AlN/(100)Si Surface Acoustic Wave Resonator and Experimental Analysis.

    Science.gov (United States)

    Chen, Shuo; You, Zheng

    2016-04-27

    The strain sensitivity of the Aluminum Nitride (AlN)/Silicon (Si) surface acoustic wave resonator (SAWR) is predicted based on a modeling method introduced in this work, and further compared with experimental results. The strain influence on both the period of the inter-digital transducer (IDT) and the sound velocity is taken into consideration when modeling the strain response. From the modeling results, AlN and Si have opposite responses to strain; hence, for the AlN/Si-based SAWR, both a positive and a negative strain coefficient factor can be achieved by changing the thickness of the AlN layer, which is confirmed by strain response testing based on a silicon cantilever structure with two AlN configurations (1 μm and 3 μm in thickness, respectively).

  6. SPICE compatible analytical electron mobility model for biaxial strained-Si-MOSFETs

    International Nuclear Information System (INIS)

    Chaudhry, Amit; Sangwan, S.; Roy, J. N.

    2011-01-01

    This paper describes an analytical model for bulk electron mobility in strained-Si layers as a function of strain. Phonon scattering, columbic scattering and surface roughness scattering are included to analyze the full mobility model. Analytical explicit calculations of all of the parameters to accurately estimate the electron mobility have been made. The results predict an increase in the electron mobility with the application of biaxial strain as also predicted from the basic theory of strain physics of metal oxide semiconductor (MOS) devices. The results have also been compared with numerically reported results and show good agreement. (semiconductor devices)

  7. The MIDAS touch for Accurately Predicting the Stress-Strain Behavior of Tantalum

    Energy Technology Data Exchange (ETDEWEB)

    Jorgensen, S. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)

    2016-03-02

    Testing the behavior of metals in extreme environments is not always feasible, so material scientists use models to try and predict the behavior. To achieve accurate results it is necessary to use the appropriate model and material-specific parameters. This research evaluated the performance of six material models available in the MIDAS database [1] to determine at which temperatures and strain-rates they perform best, and to determine to which experimental data their parameters were optimized. Additionally, parameters were optimized for the Johnson-Cook model using experimental data from Lassila et al [2].

  8. Prediction of Ultimate Strain and Strength of FRP-Confined Concrete Cylinders Using Soft Computing Methods

    Directory of Open Access Journals (Sweden)

    Iman Mansouri

    2017-07-01

    Full Text Available This paper investigates the effectiveness of four different soft computing methods, namely radial basis neural network (RBNN, adaptive neuro fuzzy inference system (ANFIS with subtractive clustering (ANFIS-SC, ANFIS with fuzzy c-means clustering (ANFIS-FCM and M5 model tree (M5Tree, for predicting the ultimate strength and strain of concrete cylinders confined with fiber-reinforced polymer (FRP sheets. The models were compared according to the root mean square error (RMSE, mean absolute relative error (MARE and determination coefficient (R2 criteria. Similar accuracy was obtained by RBNN and ANFIS-FCM, and they provided better estimates in modeling ultimate strength of confined concrete. The ANFIS-SC, however, performed slightly better than the RBNN and ANFIS-FCM in estimating ultimate strain of confined concrete, and M5Tree provided the worst strength and strain estimates. Finally, the effects of strain ratio and the confinement stiffness ratio on strength and strain were investigated, and the confinement stiffness ratio was shown to be more effective.

  9. Experimental study of strain prediction on wave induced structures using modal decomposition and quasi static Ritz vectors

    DEFF Research Database (Denmark)

    Skafte, Anders; Kristoffersen, Julie; Vestermark, Jonas

    2017-01-01

    into two parts using complementary filters: Low frequency response caused by the quasi-static effect of the waves acting on the structure, and the high frequency response given by the modal properties of the structure. The high frequency response is then decomposed into modal coordinates using...... the experimental mode shapes. Strain histories are predicted by multiplying the modal coordinates with the expanded strain mode shapes. The low frequency response is decomposed using Ritz-vectors corresponding to the shapes that the structure vibrates with due to the wave loading. Strain Ritz......-vectors are then extracted from the finite element model by applying a load corresponding to a representative wave and the strain history for the low frequency response is found by multiplying the decomposed signal with the strain Ritz-vectors. Finally the combined strain history is found by adding the strain histories from...

  10. Confidence scores for prediction models

    DEFF Research Database (Denmark)

    Gerds, Thomas Alexander; van de Wiel, MA

    2011-01-01

    In medical statistics, many alternative strategies are available for building a prediction model based on training data. Prediction models are routinely compared by means of their prediction performance in independent validation data. If only one data set is available for training and validation......, then rival strategies can still be compared based on repeated bootstraps of the same data. Often, however, the overall performance of rival strategies is similar and it is thus difficult to decide for one model. Here, we investigate the variability of the prediction models that results when the same...... to distinguish rival prediction models with similar prediction performances. Furthermore, on the subject level a confidence score may provide useful supplementary information for new patients who want to base a medical decision on predicted risk. The ideas are illustrated and discussed using data from cancer...

  11. Assessment of Kinematic Brain Injury Metrics for Predicting Strain Responses in Diverse Automotive Impact Conditions.

    Science.gov (United States)

    Gabler, Lee F; Crandall, Jeff R; Panzer, Matthew B

    2016-12-01

    Numerous injury criteria have been developed to predict brain injury using the kinematic response of the head during impact. Each criterion utilizes a metric that is some mathematical combination of the velocity and/or acceleration components of translational and/or rotational head motion. Early metrics were based on linear acceleration of the head, but recent injury criteria have shifted towards rotational-based metrics. Currently, there is no universally accepted metric that is suitable for a diverse range of head impacts. In this study, we assessed the capability of fifteen existing kinematic-based metrics for predicting strain-based brain response using four different automotive impact conditions. Tissue-level strains were obtained through finite element model simulation of 660 head impacts including occupant and pedestrian crash tests, and pendulum head impacts. Correlations between head kinematic metrics and predicted brain strain-based metrics were evaluated. Correlations between brain strain and metrics based on angular velocity were highest among those evaluated, while metrics based on linear acceleration were least correlative. BrIC and RVCI were the kinematic metrics with the highest overall correlation; however, each metric had limitations in certain impact conditions. The results of this study suggest that rotational head kinematics are the most important parameters for brain injury criteria.

  12. Healthy work revisited: do changes in time strain predict well-being?

    Science.gov (United States)

    Moen, Phyllis; Kelly, Erin L; Lam, Jack

    2013-04-01

    Building on Karasek and Theorell (R. Karasek & T. Theorell, 1990, Healthy work: Stress, productivity, and the reconstruction of working life, New York, NY: Basic Books), we theorized and tested the relationship between time strain (work-time demands and control) and seven self-reported health outcomes. We drew on survey data from 550 employees fielded before and 6 months after the implementation of an organizational intervention, the results only work environment (ROWE) in a white-collar organization. Cross-sectional (wave 1) models showed psychological time demands and time control measures were related to health outcomes in expected directions. The ROWE intervention did not predict changes in psychological time demands by wave 2, but did predict increased time control (a sense of time adequacy and schedule control). Statistical models revealed increases in psychological time demands and time adequacy predicted changes in positive (energy, mastery, psychological well-being, self-assessed health) and negative (emotional exhaustion, somatic symptoms, psychological distress) outcomes in expected directions, net of job and home demands and covariates. This study demonstrates the value of including time strain in investigations of the health effects of job conditions. Results encourage longitudinal models of change in psychological time demands as well as time control, along with the development and testing of interventions aimed at reducing time strain in different populations of workers.

  13. Hot Deformation Behavior and Constitutive Modeling of Alloy 800H Considering Effectsof Strain

    Science.gov (United States)

    Luo, Rui; Zheng, Qi; Tang, Zhending; Yao, Yongquan; Xu, Guifang; Li, Dongsheng; Cheng, Xiaonong

    2017-05-01

    High-temperature single-pass compression experiments were conducted on alloy 800H using a Gleeble 3500 thermal-mechanical simulation testing machine, and hot deformation behaviors at temperatures of 1,000-1,150 °C and strain rates of 0.01-1 s-1 were investigated. The results revealed that dynamic recrystallization (DRX) behavior occurred more easily under deformation conditions with relatively low strain rates and high deformation temperatures. By taking the influence of strain on the hot deformation behavior into consideration, a strain-dependent hyperbolic sine constitutive model was constructed. Based on this revised constitutive model, flow stress during deformation was predicted. The linear relation between the predicted value and the experimental result was as high as 0.99648, and the absolute average relative error was 2.019 %. Thus, it was demonstrated that the strain-dependent analysis provided a constitutive model that was able to precisely predict flow stress under experimental conditions.

  14. Cracking monitoring by FBG strain sensor in the small scale dam model

    Science.gov (United States)

    Ren, Liang; Li, Hongnan; Li, Dongsheng

    2009-03-01

    Accurate measurement of strain variation and effective prediction of failure within models has been a major objective for strain sensors in dam model tests. In this paper, a FBG strain sensor with enhanced strain sensitivity and packaged by two gripper tubes is presented and applied in the seismic tests of a small scale dam model. This paper discusses the principle of enhanced sensitivity of the FBG strain sensor. Calibration experiments were conducted to evaluate the sensor's strain transferring characteristics on plates of different material. This paper also investigates the applicability of the FBG strain sensors in seismic tests of a dam model by conducting a comparison between the test measurements of FBG sensors and analytical predictions, monitoring the failure progress and predicting the cracking inside the dam model. Results of the dam model tests prove that this FBG strain sensor has the advantages of small size, high precision and embedability, demonstrate promising potential in cracking and failure monitoring and in identification of the dam model.

  15. Tantalum strength model incorporating temperature, strain rate and pressure

    Science.gov (United States)

    Lim, Hojun; Battaile, Corbett; Brown, Justin; Lane, Matt

    Tantalum is a body-centered-cubic (BCC) refractory metal that is widely used in many applications in high temperature, strain rate and pressure environments. In this work, we propose a physically-based strength model for tantalum that incorporates effects of temperature, strain rate and pressure. A constitutive model for single crystal tantalum is developed based on dislocation kink-pair theory, and calibrated to measurements on single crystal specimens. The model is then used to predict deformations of single- and polycrystalline tantalum. In addition, the proposed strength model is implemented into Sandia's ALEGRA solid dynamics code to predict plastic deformations of tantalum in engineering-scale applications at extreme conditions, e.g. Taylor impact tests and Z machine's high pressure ramp compression tests, and the results are compared with available experimental data. Sandia National Laboratories is a multi program laboratory managed and operated by Sandia Corporation, a wholly owned subsidiary of Lockheed Martin Corporation, for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-AC04-94AL85000.

  16. Bootstrap prediction and Bayesian prediction under misspecified models

    OpenAIRE

    Fushiki, Tadayoshi

    2005-01-01

    We consider a statistical prediction problem under misspecified models. In a sense, Bayesian prediction is an optimal prediction method when an assumed model is true. Bootstrap prediction is obtained by applying Breiman's `bagging' method to a plug-in prediction. Bootstrap prediction can be considered to be an approximation to the Bayesian prediction under the assumption that the model is true. However, in applications, there are frequently deviations from the assumed model. In this paper, bo...

  17. Spallation model for the high strain rates range

    Science.gov (United States)

    Dekel, E.; Eliezer, S.; Henis, Z.; Moshe, E.; Ludmirsky, A.; Goldberg, I. B.

    1998-11-01

    Measurements of the dynamic spall strength in aluminum and copper shocked by a high power laser to pressures of hundreds of kbars show a rapid increase in the spall strength with the strain rate at values of about 107 s-1. We suggest that this behavior is a result of a change in the spall mechanism. At low strain rates the spall is caused by the motion and coalescence of material's initial flaws. At high strain rates there is not enough time for the flaws to move and the spall is produced by the formation and coalescence of additional cavities where the interatomic forces become dominant. Material under tensile stress is in a metastable condition and cavities of a critical radius are formed in it due to thermal fluctuations. These cavities grow due to the tension. The total volume of the voids grow until the material disintegrates at the spall plane. Simplified calculations based on this model, describing the metal as a viscous liquid, give results in fairly good agreement with the experimental data and predict the increase in spall strength at high strain rates.

  18. Predictive validation of an influenza spread model.

    Directory of Open Access Journals (Sweden)

    Ayaz Hyder

    Full Text Available BACKGROUND: Modeling plays a critical role in mitigating impacts of seasonal influenza epidemics. Complex simulation models are currently at the forefront of evaluating optimal mitigation strategies at multiple scales and levels of organization. Given their evaluative role, these models remain limited in their ability to predict and forecast future epidemics leading some researchers and public-health practitioners to question their usefulness. The objective of this study is to evaluate the predictive ability of an existing complex simulation model of influenza spread. METHODS AND FINDINGS: We used extensive data on past epidemics to demonstrate the process of predictive validation. This involved generalizing an individual-based model for influenza spread and fitting it to laboratory-confirmed influenza infection data from a single observed epidemic (1998-1999. Next, we used the fitted model and modified two of its parameters based on data on real-world perturbations (vaccination coverage by age group and strain type. Simulating epidemics under these changes allowed us to estimate the deviation/error between the expected epidemic curve under perturbation and observed epidemics taking place from 1999 to 2006. Our model was able to forecast absolute intensity and epidemic peak week several weeks earlier with reasonable reliability and depended on the method of forecasting-static or dynamic. CONCLUSIONS: Good predictive ability of influenza epidemics is critical for implementing mitigation strategies in an effective and timely manner. Through the process of predictive validation applied to a current complex simulation model of influenza spread, we provided users of the model (e.g. public-health officials and policy-makers with quantitative metrics and practical recommendations on mitigating impacts of seasonal influenza epidemics. This methodology may be applied to other models of communicable infectious diseases to test and potentially improve

  19. Predictive Validation of an Influenza Spread Model

    Science.gov (United States)

    Hyder, Ayaz; Buckeridge, David L.; Leung, Brian

    2013-01-01

    Background Modeling plays a critical role in mitigating impacts of seasonal influenza epidemics. Complex simulation models are currently at the forefront of evaluating optimal mitigation strategies at multiple scales and levels of organization. Given their evaluative role, these models remain limited in their ability to predict and forecast future epidemics leading some researchers and public-health practitioners to question their usefulness. The objective of this study is to evaluate the predictive ability of an existing complex simulation model of influenza spread. Methods and Findings We used extensive data on past epidemics to demonstrate the process of predictive validation. This involved generalizing an individual-based model for influenza spread and fitting it to laboratory-confirmed influenza infection data from a single observed epidemic (1998–1999). Next, we used the fitted model and modified two of its parameters based on data on real-world perturbations (vaccination coverage by age group and strain type). Simulating epidemics under these changes allowed us to estimate the deviation/error between the expected epidemic curve under perturbation and observed epidemics taking place from 1999 to 2006. Our model was able to forecast absolute intensity and epidemic peak week several weeks earlier with reasonable reliability and depended on the method of forecasting-static or dynamic. Conclusions Good predictive ability of influenza epidemics is critical for implementing mitigation strategies in an effective and timely manner. Through the process of predictive validation applied to a current complex simulation model of influenza spread, we provided users of the model (e.g. public-health officials and policy-makers) with quantitative metrics and practical recommendations on mitigating impacts of seasonal influenza epidemics. This methodology may be applied to other models of communicable infectious diseases to test and potentially improve their predictive

  20. Prediction models in complex terrain

    DEFF Research Database (Denmark)

    Marti, I.; Nielsen, Torben Skov; Madsen, Henrik

    2001-01-01

    The objective of the work is to investigatethe performance of HIRLAM in complex terrain when used as input to energy production forecasting models, and to develop a statistical model to adapt HIRLAM prediction to the wind farm. The features of the terrain, specially the topography, influence...... the performance of HIRLAM in particular with respect to wind predictions. To estimate the performance of the model two spatial resolutions (0,5 Deg. and 0.2 Deg.) and different sets of HIRLAM variables were used to predict wind speed and energy production. The predictions of energy production for the wind farms...... are calculated using on-line measurements of power production as well as HIRLAM predictions as input thus taking advantage of the auto-correlation, which is present in the power production for shorter pediction horizons. Statistical models are used to discribe the relationship between observed energy production...

  1. MODEL PREDICTIVE CONTROL FUNDAMENTALS

    African Journals Online (AJOL)

    2012-07-02

    Jul 2, 2012 ... Linear MPC. 1. Uses linear model: ˙x = Ax + Bu. 2. Quadratic cost function: F = xT Qx + uT Ru. 3. Linear constraints: Hx + Gu < 0. 4. Quadratic program. Nonlinear MPC. 1. Nonlinear model: ˙x = f(x, u). 2. Cost function can be nonquadratic: F = (x, u). 3. Nonlinear constraints: h(x, u) < 0. 4. Nonlinear program.

  2. Predictive capabilities of various constitutive models for arterial tissue.

    Science.gov (United States)

    Schroeder, Florian; Polzer, Stanislav; Slažanský, Martin; Man, Vojtěch; Skácel, Pavel

    2018-02-01

    Aim of this study is to validate some constitutive models by assessing their capabilities in describing and predicting uniaxial and biaxial behavior of porcine aortic tissue. 14 samples from porcine aortas were used to perform 2 uniaxial and 5 biaxial tensile tests. Transversal strains were furthermore stored for uniaxial data. The experimental data were fitted by four constitutive models: Holzapfel-Gasser-Ogden model (HGO), model based on generalized structure tensor (GST), Four-Fiber-Family model (FFF) and Microfiber model. Fitting was performed to uniaxial and biaxial data sets separately and descriptive capabilities of the models were compared. Their predictive capabilities were assessed in two ways. Firstly each model was fitted to biaxial data and its accuracy (in term of R 2 and NRMSE) in prediction of both uniaxial responses was evaluated. Then this procedure was performed conversely: each model was fitted to both uniaxial tests and its accuracy in prediction of 5 biaxial responses was observed. Descriptive capabilities of all models were excellent. In predicting uniaxial response from biaxial data, microfiber model was the most accurate while the other models showed also reasonable accuracy. Microfiber and FFF models were capable to reasonably predict biaxial responses from uniaxial data while HGO and GST models failed completely in this task. HGO and GST models are not capable to predict biaxial arterial wall behavior while FFF model is the most robust of the investigated constitutive models. Knowledge of transversal strains in uniaxial tests improves robustness of constitutive models. Copyright © 2017 Elsevier Ltd. All rights reserved.

  3. Strain histograms are equal to strain ratios in predicting malignancy in breast tumours

    DEFF Research Database (Denmark)

    Carlsen, Jonathan Frederik; Ewertsen, Caroline; Sletting, Susanne

    2017-01-01

    could be upgraded for immediate biopsy. Linear regression was performed to evaluate the effect of tumour depth and size, and breast density on strain elastography. Results: Forty-four of 99 (44.4%) tumours were malignant. AUROC of BI-RADS, strain histograms and strain ratios were 0.949, 0.830 and 0.......794 respectively. There was no significant difference between AUROCs of strain histograms and strain ratios (P = 0.405), while they were both inferior to BI-RADS scoring (P0.001, P = 0.008). Four out of 26 BI-RADS 3 tumours were malignant. When cut-offs of 189 for strain histograms and 1.44 for strain ratios were...... used to upgrade BI-RADS 3 tumours, AUROCS were 0.961 (Strain histograms and BIRADS) and 0.941 (Strain ratios and BI-RADS). None of them was significantly different from BI-RADS scoring alone (P = 0.249 and P = 0.414). Tumour size and depth, and breast density influenced neither strain histograms (P = 0...

  4. Modelling bankruptcy prediction models in Slovak companies

    Directory of Open Access Journals (Sweden)

    Kovacova Maria

    2017-01-01

    Full Text Available An intensive research from academics and practitioners has been provided regarding models for bankruptcy prediction and credit risk management. In spite of numerous researches focusing on forecasting bankruptcy using traditional statistics techniques (e.g. discriminant analysis and logistic regression and early artificial intelligence models (e.g. artificial neural networks, there is a trend for transition to machine learning models (support vector machines, bagging, boosting, and random forest to predict bankruptcy one year prior to the event. Comparing the performance of this with unconventional approach with results obtained by discriminant analysis, logistic regression, and neural networks application, it has been found that bagging, boosting, and random forest models outperform the others techniques, and that all prediction accuracy in the testing sample improves when the additional variables are included. On the other side the prediction accuracy of old and well known bankruptcy prediction models is quiet high. Therefore, we aim to analyse these in some way old models on the dataset of Slovak companies to validate their prediction ability in specific conditions. Furthermore, these models will be modelled according to new trends by calculating the influence of elimination of selected variables on the overall prediction ability of these models.

  5. Melanoma Risk Prediction Models

    Science.gov (United States)

    Developing statistical models that estimate the probability of developing melanoma cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

  6. Predictive models of moth development

    Science.gov (United States)

    Degree-day models link ambient temperature to insect life-stages, making such models valuable tools in integrated pest management. These models increase management efficacy by predicting pest phenology. In Wisconsin, the top insect pest of cranberry production is the cranberry fruitworm, Acrobasis v...

  7. Predictive Models and Computational Embryology

    Science.gov (United States)

    EPA’s ‘virtual embryo’ project is building an integrative systems biology framework for predictive models of developmental toxicity. One schema involves a knowledge-driven adverse outcome pathway (AOP) framework utilizing information from public databases, standardized ontologies...

  8. Mathematical prediction of core body temperature from environment, activity, and clothing: The heat strain decision aid (HSDA).

    Science.gov (United States)

    Potter, Adam W; Blanchard, Laurie A; Friedl, Karl E; Cadarette, Bruce S; Hoyt, Reed W

    2017-02-01

    Physiological models provide useful summaries of complex interrelated regulatory functions. These can often be reduced to simple input requirements and simple predictions for pragmatic applications. This paper demonstrates this modeling efficiency by tracing the development of one such simple model, the Heat Strain Decision Aid (HSDA), originally developed to address Army needs. The HSDA, which derives from the Givoni-Goldman equilibrium body core temperature prediction model, uses 16 inputs from four elements: individual characteristics, physical activity, clothing biophysics, and environmental conditions. These inputs are used to mathematically predict core temperature (T c ) rise over time and can estimate water turnover from sweat loss. Based on a history of military applications such as derivation of training and mission planning tools, we conclude that the HSDA model is a robust integration of physiological rules that can guide a variety of useful predictions. The HSDA model is limited to generalized predictions of thermal strain and does not provide individualized predictions that could be obtained from physiological sensor data-driven predictive models. This fully transparent physiological model should be improved and extended with new findings and new challenging scenarios. Published by Elsevier Ltd.

  9. Second Generation Models for Strain-Based Design

    Science.gov (United States)

    2011-08-30

    This project covers the development of tensile strain design models which form a key part of the strain-based design of pipelines. The strain-based design includes at least two limit states, tensile rupture, and compressive buckling. The tensile stra...

  10. Predictions models with neural nets

    Directory of Open Access Journals (Sweden)

    Vladimír Konečný

    2008-01-01

    Full Text Available The contribution is oriented to basic problem trends solution of economic pointers, using neural networks. Problems include choice of the suitable model and consequently configuration of neural nets, choice computational function of neurons and the way prediction learning. The contribution contains two basic models that use structure of multilayer neural nets and way of determination their configuration. It is postulate a simple rule for teaching period of neural net, to get most credible prediction.Experiments are executed with really data evolution of exchange rate Kč/Euro. The main reason of choice this time series is their availability for sufficient long period. In carry out of experiments the both given basic kind of prediction models with most frequent use functions of neurons are verified. Achieve prediction results are presented as in numerical and so in graphical forms.

  11. A Constitutive Model for Strain-Controlled Strength Degradation of Rockmasses (SDR)

    Science.gov (United States)

    Kalos, A.; Kavvadas, M.

    2017-11-01

    The paper describes a continuum, rate-independent, incremental plasticity constitutive model applicable in weak rocks and heavily fractured rockmasses, where mechanical behaviour is controlled by rockmass strength rather than structural features (discontinuities). The model describes rockmass structure by a generalised Hoek-Brown Structure Envelope (SE) in the stress space. Stress paths inside the SE are nonlinear and irreversible to better simulate behaviour at strains up to peak strength and under stress reversals. Stress paths on the SE have user-controlled volume dilatancy (gradually reducing to zero at large shear strains) and can model post-peak strain softening of brittle rockmasses via a structure degradation (damage) mechanism triggered by accumulated plastic shear strains. As the SE may strain harden with plastic strains, ductile behaviour can also be modelled. The model was implemented in the Finite Element Code Simulia ABAQUS and was applied in plane strain (2D) excavation of a cylindrical cavity (tunnel) to predict convergence-confinement curves. It is shown that small-strain nonlinearity, variable volume dilatancy and post-peak hardening/softening strongly affect the predicted curves, resulting in corresponding differences of lining pressures in real tunnel excavations.

  12. Investigation of stress–strain models for confined high strength ...

    Indian Academy of Sciences (India)

    The ascending branch of stress–strain curves depended on the ratio of confinement reinforcement was similar to the modified Kent–Park model and the descending branch similar to the Nagashima model. Keywords. High strength concrete; confined concrete; stress–strain models; ductility toughness. 1. Introduction.

  13. A thermovisco-hyperelastic constitutive model of HTPB propellant with damage at intermediate strain rates

    Science.gov (United States)

    Wang, Zhejun; Qiang, Hongfu; Wang, Tiejun; Wang, Guang; Hou, Xiao

    2017-08-01

    The uniaxial compressive tests at different temperatures (223-298 K) and strain rates ( 0.40-63 s^{-1}) are reported to study the properties of hydroxyl-terminated polybutadiene (HTPB) propellant at intermediate strain rates, using a new INSTRON testing machine. The experimental results indicate that the compressive properties (mechanical properties and damage) of HTPB propellant are remarkably affected by temperature and strain rate and display significant nonlinear material behaviors at large strains under all the test conditions. Continuously decreasing temperature and increasing strain rate, the characteristics of stress-strain curves and damage for HTPB propellant are more complex and are significantly different from that at room temperature or at lower strain rates. A new constitutive model was developed to describe the compressive behaviors of HTPB propellant at room temperature and intermediate strain rates by simply coupling the effect of strain rate into the conventional hyperelastic model. Based on the compressive behaviors of HTPB propellant and the nonlinear viscoelastic constitutive theories, a new thermovisco-hyperelastic constitutive model with damage was proposed to predict the stress responses of the propellant at low temperatures and intermediate strain rates. In this new model, the damage is related to the viscoelastic properties of the propellant. Meanwhile, the effect of temperature on the hyperelastic properties, viscoelastic properties and damage are all considered by the macroscopical method. The constitutive parameters in the proposed constitutive models were identified by the genetic algorithm (GA)-based optimization method. By comparing the predicted and experimental results, it can be found that the developed constitutive models can correctly describe the uniaxial compressive behaviors of HTPB propellant at intermediate strain rates and different temperatures.

  14. Parameters Identification of Interface Friction Model for Ceramic Matrix Composites Based on Stress-Strain Response

    Science.gov (United States)

    Han, Xiao; Gao, Xiguang; Song, Yingdong

    2017-10-01

    An approach to identify parameters of interface friction model for Ceramic Matrix composites based on stress-strain response was developed. The stress distribution of fibers in the interface slip region and intact region of the damaged composite was determined by adopting the interface friction model. The relation between maximum strain, secant moduli of hysteresis loop and interface shear stress, interface de-bonding stress was established respectively with the method of symbolic-graphic combination. By comparing the experimental strain, secant moduli of hysteresis loop with computation values, the interface shear stress and interface de-bonding stress corresponding to first cycle were identified. Substituting the identification of parameters into interface friction model, the stress-strain curves were predicted and the predicted results fit experiments well. Besides, the influence of number of data points on identifying the value of interface parameters was discussed. And the approach was compared with the method based on the area of hysteresis loop.

  15. Finite Element Analysis of Cross Rolling on AISI 304 Stainless Steel: Prediction of Stress and Strain Fields

    Science.gov (United States)

    Rout, Matruprasad; Pal, Surjya Kanta; Singh, Shiv Brat

    2017-02-01

    Studies on the effect of strain path during rolling has been carried out for a long time, but the same has not been done using Finite Element Analysis (FEA). Change in strain path affects the state variables in the rolled plate like stress, strain, temperature etc. In the current work, Finite Element Analysis for cross rolling of AISI 304 austenitic stainless steel has been carried out by rotating the plate by 90° in between the passes. To analyze stress and strain fields in the material for cross rolling, a full 3D model of work-roll and plate has been developed using rigid-viscoplastic finite element method. The stress and strain fields, considering von-Mises yield criteria, are calculated by using updated Lagrangian method. In addition to these, the model also calculates the normal pressure and strain rate distribution in the plate during cross rolling. The nature of the variations of stress and strain fields in the plate, predicted by the model, is in good agreement with the previously published works for unidirectional rolling.

  16. Predictive ability of boiler production models | Ogundu | Animal ...

    African Journals Online (AJOL)

    The weekly body weight measurements of a growing strain of Ross broiler were used to compare the of ability of three mathematical models (the multi, linear, quadratic and Exponential) to predict 8 week body weight from early body measurements at weeks I, II, III, IV, V, VI and VII. The results suggest that the three models ...

  17. Strain Concentration at Structural Discontinuities and Its Prediction Based on Characteristics of Compliance Change in Structures

    Science.gov (United States)

    Kasahara, Naoto

    Elevated temperature structural design codes pay attention to strain concentration at structural discontinuities due to creep and plasticity, since it causes an increase in creep-fatigue damage of materials. One of the difficulties in predicting strain concentration is its dependence on the magnitude of loading, the constitutive equations, and the duration of loading. In this study, the author investigated the fundamental mechanism of strain concentration and its main factors. The results revealed that strain concentration is caused by strain redistribution between elastic and inelastic regions, which can be quantified by the characteristics of structural compliance. The characteristics of structural compliance are controlled by elastic region in structures and are insensitive to constitutive equations. It means that inelastic analysis can be easily applied to obtain compliance characteristics. By utilizing this fact, a simplified inelastic analysis method was proposed based on the characteristics of compliance change for the prediction of strain concentration.

  18. Assessment of the Uniqueness of Wind Tunnel Strain-Gage Balance Load Predictions

    Science.gov (United States)

    Ulbrich, N.

    2016-01-01

    A new test was developed to assess the uniqueness of wind tunnel strain-gage balance load predictions that are obtained from regression models of calibration data. The test helps balance users to gain confidence in load predictions of non-traditional balance designs. It also makes it possible to better evaluate load predictions of traditional balances that are not used as originally intended. The test works for both the Iterative and Non-Iterative Methods that are used in the aerospace testing community for the prediction of balance loads. It is based on the hypothesis that the total number of independently applied balance load components must always match the total number of independently measured bridge outputs or bridge output combinations. This hypothesis is supported by a control volume analysis of the inputs and outputs of a strain-gage balance. It is concluded from the control volume analysis that the loads and bridge outputs of a balance calibration data set must separately be tested for linear independence because it cannot always be guaranteed that a linearly independent load component set will result in linearly independent bridge output measurements. Simple linear math models for the loads and bridge outputs in combination with the variance inflation factor are used to test for linear independence. A highly unique and reversible mapping between the applied load component set and the measured bridge output set is guaranteed to exist if the maximum variance inflation factor of both sets is less than the literature recommended threshold of five. Data from the calibration of a six{component force balance is used to illustrate the application of the new test to real-world data.

  19. What do saliency models predict?

    Science.gov (United States)

    Koehler, Kathryn; Guo, Fei; Zhang, Sheng; Eckstein, Miguel P.

    2014-01-01

    Saliency models have been frequently used to predict eye movements made during image viewing without a specified task (free viewing). Use of a single image set to systematically compare free viewing to other tasks has never been performed. We investigated the effect of task differences on the ability of three models of saliency to predict the performance of humans viewing a novel database of 800 natural images. We introduced a novel task where 100 observers made explicit perceptual judgments about the most salient image region. Other groups of observers performed a free viewing task, saliency search task, or cued object search task. Behavior on the popular free viewing task was not best predicted by standard saliency models. Instead, the models most accurately predicted the explicit saliency selections and eye movements made while performing saliency judgments. Observers' fixations varied similarly across images for the saliency and free viewing tasks, suggesting that these two tasks are related. The variability of observers' eye movements was modulated by the task (lowest for the object search task and greatest for the free viewing and saliency search tasks) as well as the clutter content of the images. Eye movement variability in saliency search and free viewing might be also limited by inherent variation of what observers consider salient. Our results contribute to understanding the tasks and behavioral measures for which saliency models are best suited as predictors of human behavior, the relationship across various perceptual tasks, and the factors contributing to observer variability in fixational eye movements. PMID:24618107

  20. Large-strain time-temperature equivalence in high density polyethylene for prediction of extreme deformation and damage

    Directory of Open Access Journals (Sweden)

    Gray G.T.

    2012-08-01

    Full Text Available Time-temperature equivalence is a widely recognized property of many time-dependent material systems, where there is a clear predictive link relating the deformation response at a nominal temperature and a high strain-rate to an equivalent response at a depressed temperature and nominal strain-rate. It has been found that high-density polyethylene (HDPE obeys a linear empirical formulation relating test temperature and strain-rate. This observation was extended to continuous stress-strain curves, such that material response measured in a load frame at large strains and low strain-rates (at depressed temperatures could be translated into a temperature-dependent response at high strain-rates and validated against Taylor impact results. Time-temperature equivalence was used in conjuction with jump-rate compression tests to investigate isothermal response at high strain-rate while exluding adiabatic heating. The validated constitutive response was then applied to the analysis of Dynamic-Tensile-Extrusion of HDPE, a tensile analog to Taylor impact developed at LANL. The Dyn-Ten-Ext test results and FEA found that HDPE deformed smoothly after exiting the die, and after substantial drawing appeared to undergo a pressure-dependent shear damage mechanism at intermediate velocities, while it fragmented at high velocities. Dynamic-Tensile-Extrusion, properly coupled with a validated constitutive model, can successfully probe extreme tensile deformation and damage of polymers.

  1. Numerical method for a 2D drift diffusion model arising in strained n ...

    Indian Academy of Sciences (India)

    carrier mobility dependence on the lateral and vertical electric field model is especially considered in the formulation. By using the .... effects of electric field on mobility, we use a simplified mobility model [19], see eq. (16). The effects of the .... Our simulator predicted that the drive current of strained MOSFET is higher than.

  2. Neural network modeling to evaluate the dynamic flow stress of high strength armor steels under high strain rate compression

    Directory of Open Access Journals (Sweden)

    Ravindranadh Bobbili

    2014-12-01

    Full Text Available An artificial neural network (ANN constitutive model is developed for high strength armor steel tempered at 500 °C, 600 °C and 650 °C based on high strain rate data generated from split Hopkinson pressure bar (SHPB experiments. A new neural network configuration consisting of both training and validation is effectively employed to predict flow stress. Tempering temperature, strain rate and strain are considered as inputs, whereas flow stress is taken as output of the neural network. A comparative study on Johnson–Cook (J–C model and neural network model is performed. It was observed that the developed neural network model could predict flow stress under various strain rates and tempering temperatures. The experimental stress–strain data obtained from high strain rate compression tests using SHPB, over a range of tempering temperatures (500–650 °C, strains (0.05–0.2 and strain rates (1000–5500/s are employed to formulate J–C model to predict the high strain rate deformation behavior of high strength armor steels. The J-C model and the back-propagation ANN model were developed to predict the high strain rate deformation behavior of high strength armor steel and their predictability is evaluated in terms of correlation coefficient (R and average absolute relative error (AARE. R and AARE for the J–C model are found to be 0.7461 and 27.624%, respectively, while R and AARE for the ANN model are 0.9995 and 2.58%, respectively. It was observed that the predictions by ANN model are in consistence with the experimental data for all tempering temperatures.

  3. Childhood economic strains in predicting substance use in emerging adulthood: mediation effects of youth self-control and parenting practices.

    Science.gov (United States)

    Lee, Chien-Ti; McClernon, F Joseph; Kollins, Scott H; Prybol, Kevin; Fuemmeler, Bernard F

    2013-11-01

    To examine the influence of childhood economic strains on substance use in young adulthood and to assess the mediating roles of self-control as well as positive parenting during adolescence in a nationally representative longitudinal cohort. The study included data from participants (n = 1,285) in the Panel Study of Income Dynamics, Child Development Supplement, and Transition to Adult. Structural equation modeling was used to evaluate the associations among risk factors during childhood and adolescence that predicted substance use in early adulthood. Conditions of economic strains, especially poverty, during childhood were associated with an increased likelihood of regular smoking in adulthood, which was partially mediated by poorer self-control during adolescence. Self-control is negatively affected by economic strains and serves as a mediator between poverty and risk of regular smoking. Additional research is needed to better understand how economic strains effect the development of self-control.

  4. Computational studies of a strain-based deformation shape prediction algorithm for control and monitoring applications

    Science.gov (United States)

    Derkevorkian, Armen; Alvarenga, Jessica; Masri, Sami F.; Boussalis, Helen; Richards, W. Lance

    2012-04-01

    A modal approach is investigated for real-time deformation shape prediction of lightweight unmanned flying aerospace structures, for the purposes of Structural Health Monitoring (SHM) and condition assessment. The deformation prediction algorithm depends on the modal properties of the structure and uses high-resolution fiber-optic sensors to obtain strain data from a representative aerospace structure (e.g., flying wing) in order to predict the associated real-time deflection shape. The method is based on the use of fiber-optic sensors such as optical Fiber Bragg Gratings (FBGs) which are known for their accuracy and light weight. In this study, the modal method is examined through computational models involving Finite-Element Analysis (FEA). Furthermore, sensitivity analyses are performed to investigate the effects of several external factors such as sensor locations and noise pollution on the performance of the algorithm. This work analyzes the numerous complications and difficulties that might potentially arise from combining the state-of-the-art advancements in sensing technology, deformation shape prediction, and structural health monitoring, to achieve a robust way of monitoring ultra lightweight flying wings or next-generation commercial airplanes.

  5. On the Rule of Mixtures for Predicting Stress-Softening and Residual Strain Effects in Biological Tissues and Biocompatible Materials

    Directory of Open Access Journals (Sweden)

    Alex Elías-Zúñiga

    2014-01-01

    Full Text Available In this work, we use the rule of mixtures to develop an equivalent material model in which the total strain energy density is split into the isotropic part related to the matrix component and the anisotropic energy contribution related to the fiber effects. For the isotropic energy part, we select the amended non-Gaussian strain energy density model, while the energy fiber effects are added by considering the equivalent anisotropic volumetric fraction contribution, as well as the isotropized representation form of the eight-chain energy model that accounts for the material anisotropic effects. Furthermore, our proposed material model uses a phenomenological non-monotonous softening function that predicts stress softening effects and has an energy term, derived from the pseudo-elasticity theory, that accounts for residual strain deformations. The model’s theoretical predictions are compared with experimental data collected from human vaginal tissues, mice skin, poly(glycolide-co-caprolactone (PGC25 3-0 and polypropylene suture materials and tracheal and brain human tissues. In all cases examined here, our equivalent material model closely follows stress-softening and residual strain effects exhibited by experimental data.

  6. Prediction of strain values in reinforcements and concrete of a RC frame using neural networks

    Science.gov (United States)

    Vafaei, Mohammadreza; Alih, Sophia C.; Shad, Hossein; Falah, Ali; Halim, Nur Hajarul Falahi Abdul

    2018-01-01

    The level of strain in structural elements is an important indicator for the presence of damage and its intensity. Considering this fact, often structural health monitoring systems employ strain gauges to measure strains in critical elements. However, because of their sensitivity to the magnetic fields, inadequate long-term durability especially in harsh environments, difficulties in installation on existing structures, and maintenance cost, installation of strain gauges is not always possible for all structural components. Therefore, a reliable method that can accurately estimate strain values in critical structural elements is necessary for damage identification. In this study, a full-scale test was conducted on a planar RC frame to investigate the capability of neural networks for predicting the strain values. Two neural networks each of which having a single hidden layer was trained to relate the measured rotations and vertical displacements of the frame to the strain values measured at different locations of the frame. Results of trained neural networks indicated that they accurately estimated the strain values both in reinforcements and concrete. In addition, the trained neural networks were capable of predicting strains for the unseen input data set.

  7. Prediction of strain values in reinforcements and concrete of a RC frame using neural networks

    Science.gov (United States)

    Vafaei, Mohammadreza; Alih, Sophia C.; Shad, Hossein; Falah, Ali; Halim, Nur Hajarul Falahi Abdul

    2018-03-01

    The level of strain in structural elements is an important indicator for the presence of damage and its intensity. Considering this fact, often structural health monitoring systems employ strain gauges to measure strains in critical elements. However, because of their sensitivity to the magnetic fields, inadequate long-term durability especially in harsh environments, difficulties in installation on existing structures, and maintenance cost, installation of strain gauges is not always possible for all structural components. Therefore, a reliable method that can accurately estimate strain values in critical structural elements is necessary for damage identification. In this study, a full-scale test was conducted on a planar RC frame to investigate the capability of neural networks for predicting the strain values. Two neural networks each of which having a single hidden layer was trained to relate the measured rotations and vertical displacements of the frame to the strain values measured at different locations of the frame. Results of trained neural networks indicated that they accurately estimated the strain values both in reinforcements and concrete. In addition, the trained neural networks were capable of predicting strains for the unseen input data set.

  8. Dynamic model updating based on strain mode shape and natural frequency using hybrid pattern search technique

    Science.gov (United States)

    Guo, Ning; Yang, Zhichun; Wang, Le; Ouyang, Yan; Zhang, Xinping

    2018-05-01

    Aiming at providing a precise dynamic structural finite element (FE) model for dynamic strength evaluation in addition to dynamic analysis. A dynamic FE model updating method is presented to correct the uncertain parameters of the FE model of a structure using strain mode shapes and natural frequencies. The strain mode shape, which is sensitive to local changes in structure, is used instead of the displacement mode for enhancing model updating. The coordinate strain modal assurance criterion is developed to evaluate the correlation level at each coordinate over the experimental and the analytical strain mode shapes. Moreover, the natural frequencies which provide the global information of the structure are used to guarantee the accuracy of modal properties of the global model. Then, the weighted summation of the natural frequency residual and the coordinate strain modal assurance criterion residual is used as the objective function in the proposed dynamic FE model updating procedure. The hybrid genetic/pattern-search optimization algorithm is adopted to perform the dynamic FE model updating procedure. Numerical simulation and model updating experiment for a clamped-clamped beam are performed to validate the feasibility and effectiveness of the present method. The results show that the proposed method can be used to update the uncertain parameters with good robustness. And the updated dynamic FE model of the beam structure, which can correctly predict both the natural frequencies and the local dynamic strains, is reliable for the following dynamic analysis and dynamic strength evaluation.

  9. 3D Strain Modelling of Tear Fault Analogues

    Science.gov (United States)

    Hindle, D.; Vietor, T.

    2005-12-01

    Tear faults can be described as vertical discontinuities, with near fault parallel displacements terminating on some sort of shallow detachment. As such, they are difficult to study in "cross section" i.e. 2 dimensions as is often the case for fold-thrust systems. Hence, little attempt has been made to model the evolution of strain around tear faults and the processes of strain localisation in such structures due to the necessity of describing these systems in 3 dimensions and the problems this poses for both numerical and analogue modelling. Field studies suggest that strain in such regions can be distributed across broad zones on minor tear systems, which are often not easily mappable. Such strain is probably assumed to be due to distributed strain and to displacement gradients which are themselves necessary for the initiation of the tear itself. We present a numerical study of the effects of a sharp, basal discontinutiy parallel to the transport direction in a shortening wedge of material. The discontinuity is represented by two adjacent basal surfaces with strongly contrasting (0.5 and 0.05) friction coefficient. The material is modelled using PFC3D distinct element software for simulating granular material, whose properties are chosen to simulate upper crustal, sedimentary rock. The model geometry is a rectangular bounding box, 2km x 1km, and 0.35-0.5km deep, with a single, driving wall of constant velocity. We show the evolution of strain in the model in horizontal and vertical sections, and interpret strain localization as showing the spontaneous development of tear fault like features. The strain field in the model is asymmetrical, rotated towards the strong side of the model. Strain increments seem to oscillate in time, suggesting achievement of a steady state. We also note that our model cannot be treated as a critical wedge, since the 3rd dimension and the lateral variations of strength rule out this type of 2D approximation.

  10. Cutoffs of isokinetic strength ratio and hamstring strain prediction in professional soccer players.

    Science.gov (United States)

    Dauty, M; Menu, P; Fouasson-Chailloux, A

    2018-01-01

    Hamstring strain injuries frequently occur during professional soccer practice. Low hamstring strength represents an intrinsic modifiable risk factor but cutoffs of isokinetic knee strength ratios are controversial to predict hamstring strain in professional soccer players. We aimed to predict hamstring strain in accordance with cutoffs of isokinetic knee strength ratios. Bilateral, conventional, and functional isokinetic strength ratios were calculated in 194 professional soccer players at the beginning of 15 consecutive seasons. 36 soccer players presented a moderate hamstring strain and 158 were not injured. The different calculated isokinetic ratios were compared with the right and left limb of the uninjured population. Different usual cutoffs were tested: at 0.85 and 0.90 for the bilateral concentric and eccentric hamstring-to-hamstring ratio, at 0.60 and 0.47 for the conventional hamstring-to-quadriceps ratio and at 0.80 and 1 for the mixed hamstring-to-quadriceps ratio. The specific ratios for the studied population were also determined by the 10th percentile and then tested. Hamstring strain prediction was established in terms of odds ratios. No cutoff with bilateral, conventional, or functional isokinetic strength ratio was predictive of hamstring strain after univariate analysis. Specific cutoffs determined from the studied population were not more predictive. Very few injured soccer players presented values under the cutoffs at 0.47 for the conventional ratio and at 0.80 for the mixed ratio. Regardless of their values, cutoffs of isokinetic strength ratios were not predictive of hamstring injuries. The use of isokinetic cutoffs is not recommended to predict hamstring muscle strain in professional soccer players. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

  11. Predictive ability of egg production models | Oni | Nigerian Journal of ...

    African Journals Online (AJOL)

    The monthly egg production data of a strain of Rhode Island chickens were used to compare three mathematical models (the Parabolic exponential, Wood's Gamma and modified Gamma by McNally) on their ability to predict 52 week total egg production from part-production at 16, 20, and 24 weeks, on a hen-housed basis.

  12. Modeling of Strain Effects in Multi-component Semiconductors

    Science.gov (United States)

    Arjmand, Mehrdad

    Strain affects the properties of crystalline material by changing the atomic symmetry. Controlling the strain in semiconductors helps to tune properties of material and design new material. For instance, strained semiconductor heterostructures have improved the efficiency of traditional solar cells remarkably. Another example of strain application is in electronic devices. Strained heterostructure nanowires provide a better control on electronic properties of gates used in transistors. Gate-all-around nanowires are promising candidates to power microprocessors in future. Strain is also used to make quantum dot structures from semiconductors. These quantum dots are used in quantum computing, diode lasers and sensors. Once the stored strain in a structure reaches a critical limit, it relaxes by triggering different phenomena in the structure. For instance, strain causes morphology change, plastic deformation, phase separation and intermixing, fracture, buckling, bulging and peeling. In order to use these strained structures for design purposes, it is critical to understand these different relaxation phenomena and be able to control them. Modeling provides a powerful framework to understand different relaxation mechanisms and provide guidance to control these strain induced phenomena. In this thesis, I have developed a continuum based model called "phase field" to study morphology change, plastic deformation and phase separation in multi-component semiconductors during growth and annealing processes. The advantage of phase field approach compared to some other modeling techniques is that it includes the effects of both thermodynamics and kinetics. Also, I have developed a continuum based elasto-plasticity model to study the effects of plastic relaxation in semiconductor nanowires. This model can particularly be useful for piezoelectric and surface stability analysis of nanowires.

  13. Metabolic Modeling of Common Escherichia coli Strains in Human Gut Microbiome

    Directory of Open Access Journals (Sweden)

    Yue-Dong Gao

    2014-01-01

    Full Text Available The recent high-throughput sequencing has enabled the composition of Escherichia coli strains in the human microbial community to be profiled en masse. However, there are two challenges to address: (1 exploring the genetic differences between E. coli strains in human gut and (2 dynamic responses of E. coli to diverse stress conditions. As a result, we investigated the E. coli strains in human gut microbiome using deep sequencing data and reconstructed genome-wide metabolic networks for the three most common E. coli strains, including E. coli HS, UTI89, and CFT073. The metabolic models show obvious strain-specific characteristics, both in network contents and in behaviors. We predicted optimal biomass production for three models on four different carbon sources (acetate, ethanol, glucose, and succinate and found that these stress-associated genes were involved in host-microbial interactions and increased in human obesity. Besides, it shows that the growth rates are similar among the models, but the flux distributions are different, even in E. coli core reactions. The correlations between human diabetes-associated metabolic reactions in the E. coli models were also predicted. The study provides a systems perspective on E. coli strains in human gut microbiome and will be helpful in integrating diverse data sources in the following study.

  14. Interaction of rate- and size-effect using a dislocation density based strain gradient viscoplasticity model

    Science.gov (United States)

    Nguyen, Trung N.; Siegmund, Thomas; Tomar, Vikas; Kruzic, Jamie J.

    2017-12-01

    Size effects occur in non-uniform plastically deformed metals confined in a volume on the scale of micrometer or sub-micrometer. Such problems have been well studied using strain gradient rate-independent plasticity theories. Yet, plasticity theories describing the time-dependent behavior of metals in the presence of size effects are presently limited, and there is no consensus about how the size effects vary with strain rates or whether there is an interaction between them. This paper introduces a constitutive model which enables the analysis of complex load scenarios, including loading rate sensitivity, creep, relaxation and interactions thereof under the consideration of plastic strain gradient effects. A strain gradient viscoplasticity constitutive model based on the Kocks-Mecking theory of dislocation evolution, namely the strain gradient Kocks-Mecking (SG-KM) model, is established and allows one to capture both rate and size effects, and their interaction. A formulation of the model in the finite element analysis framework is derived. Numerical examples are presented. In a special virtual creep test with the presence of plastic strain gradients, creep rates are found to diminish with the specimen size, and are also found to depend on the loading rate in an initial ramp loading step. Stress relaxation in a solid medium containing cylindrical microvoids is predicted to increase with decreasing void radius and strain rate in a prior ramp loading step.

  15. Design and application of a fiber Bragg grating strain sensor with enhanced sensitivity in the small-scale dam model

    Science.gov (United States)

    Ren, Liang; Chen, Jianyun; Li, Hong-Nan; Song, Gangbing; Ji, Xueheng

    2009-03-01

    Accurate measurement of strain variation and effective prediction of failure within models have been major objectives for strain sensors in dam model tests. In this paper, a fiber Bragg grating (FBG) strain sensor with enhanced strain sensitivity that is packaged by two gripper tubes is presented and applied in the seismic tests of a small-scale dam model. This paper discusses the principle of enhanced sensitivity of the FBG strain sensor. Calibration experiments and reliability tests were conducted to evaluate the sensor's strain transferring characteristics on plates of different material. This paper also investigates the applicability of the FBG strain sensors in seismic tests of a dam model by conducting a comparison between the test measurements of FBG sensors and analytical predictions, monitoring the failure progress and predicting the cracking inside the dam model. Results of the dam model tests prove that the FBG strain sensor has the advantages of small size, high precision, and embeddability. It has a promising potential in the cracking and failure monitoring and identification of the dam model.

  16. Simple regional strain pattern analysis to predict response to cardiac resynchronization therapy

    DEFF Research Database (Denmark)

    Risum, Niels; Jons, Christian; Olsen, Niels T

    2012-01-01

    A classical strain pattern of early contraction in one wall and prestretching of the opposing wall followed by late contraction has previously been associated with left bundle branch block (LBBB) activation and short-term response to cardiac resynchronization therapy (CRT). Aims of this study were...... to establish the long-term predictive value of an LBBB-related strain pattern and to identify changes in contraction patterns during short-term and long-term CRT....

  17. An improved Armstrong-Frederick-Type Plasticity Model for Stable Cyclic Stress-Strain Responses Considering Nonproportional Hardening

    Science.gov (United States)

    Li, Jing; Zhang, Zhong-ping; Li, Chun-wang

    2018-03-01

    This paper modified an Armstrong-Frederick-type plasticity model for investigating the stable cyclic deformation behavior of metallic materials with different sensitivity to nonproportional loadings. In the modified model, the nonproportionality factor and nonproportional cyclic hardening coefficient coupled with the Jiang-Sehitoglu incremental plasticity model were used to estimate the stable stress-strain responses of the two materials (1045HR steel and 304 stainless steel) under various tension-torsion strain paths. A new equation was proposed to calculate the nonproportionality factor on the basis of the minimum normal strain range. Procedures to determine the minimum normal strain range were presented for general multiaxial loadings. Then, the modified model requires only the cyclic strain hardening exponent and cyclic strength coefficient to determine the material constants. It is convenient for predicting the stable stress-strain responses of materials in engineering application. Comparisons showed that the modified model can reflect the effect of nonproportional cyclic hardening well.

  18. COMPUTER MODELING OF STRAINS ON PHASE BOUNDARIES IN DUCTILE CAST IRON AT HOT EXTRUSION

    Directory of Open Access Journals (Sweden)

    A. I. Pokrovsky

    2017-01-01

    Full Text Available The computer modeling of the strain distribution in the structure of ductile iron with ferrite-pearlite matrix and inclusions of spherical graphite dependence on increasing degree of deformation during direct hot extrusion was researched. Using a software system of finite-element analysis ANSYS the numerical values of the strains at the phase boundaries: ferrite-perlite, graphiteferrite and also inside the graphite inclusions were defined. The analysis of the strain distribution in the investigated structures was performed and local zones of increased strains were discovered. The results of modeling are compared with metallographic analysis and fracture patterns. The obtained results could be used in the prediction of fracture zones in the cast iron products. 

  19. Demonstrating the improvement of predictive maturity of a computational model

    Energy Technology Data Exchange (ETDEWEB)

    Hemez, Francois M [Los Alamos National Laboratory; Unal, Cetin [Los Alamos National Laboratory; Atamturktur, Huriye S [CLEMSON UNIV.

    2010-01-01

    We demonstrate an improvement of predictive capability brought to a non-linear material model using a combination of test data, sensitivity analysis, uncertainty quantification, and calibration. A model that captures increasingly complicated phenomena, such as plasticity, temperature and strain rate effects, is analyzed. Predictive maturity is defined, here, as the accuracy of the model to predict multiple Hopkinson bar experiments. A statistical discrepancy quantifies the systematic disagreement (bias) between measurements and predictions. Our hypothesis is that improving the predictive capability of a model should translate into better agreement between measurements and predictions. This agreement, in turn, should lead to a smaller discrepancy. We have recently proposed to use discrepancy and coverage, that is, the extent to which the physical experiments used for calibration populate the regime of applicability of the model, as basis to define a Predictive Maturity Index (PMI). It was shown that predictive maturity could be improved when additional physical tests are made available to increase coverage of the regime of applicability. This contribution illustrates how the PMI changes as 'better' physics are implemented in the model. The application is the non-linear Preston-Tonks-Wallace (PTW) strength model applied to Beryllium metal. We demonstrate that our framework tracks the evolution of maturity of the PTW model. Robustness of the PMI with respect to the selection of coefficients needed in its definition is also studied.

  20. A study of fatigue life prediction for automotive spot weldment using local strain approach

    International Nuclear Information System (INIS)

    Lee, Song In; Yu, Hyo Sun; Na, Sung Hun; Na, Eui Gyun

    2000-01-01

    The fatigue crack initiation life is studied on automotive spot weldment made from cold rolled carbon steel(SPC) sheet by using DCPDM and local strain approach. It can be found that the fatigue crack initiation behavior in spot weldment can be definitely detected by DCPDM system. The local stresses and strains are estimated by elastic-plastic FEM analysis and the alternative approximate method based on Neuber's rule were applied to predict the fatigue life of spot weldment. A satisfactory correlation between the predicted life and experimental life can be found in spot weldment within a factor of 4

  1. Micromechanical modeling of stress-induced strain in polycrystalline Ni–Mn–Ga by directional solidification

    Energy Technology Data Exchange (ETDEWEB)

    Zhu, Yuping, E-mail: zhuyuping@126.com [Seismic Observation and Geophysical Imaging Laboratory, Institute of Geophysics, China Earthquake Administration, Beijing 100081 (China); Shi, Tao; Teng, Yao [Faculty of Civil Engineering and Mechanics, Jiangsu University, Zhenjiang 212013 (China)

    2015-10-05

    Highlights: • A micromechanical model of directional solidification Ni–Mn–Ga is developed. • The stress–strain curves in different directions are tested. • The martensite Young’s moduli in different directions are predicted. • The macro reorientation strains in different directions are investigated. - Abstract: Polycrystalline ferromagnetic shape memory alloy Ni–Mn–Ga produced by directional solidification possess unique properties. Its compressive stress–strain behaviors in loading–unloading cycle show nonlinear and anisotropic. Based on the self-consistent theory and thermodynamics principle, a micromechanical constitutive model of polycrystalline Ni–Mn–Ga by directional solidification is developed considering the generating mechanism of the macroscopic strain and anisotropy. Then, the stress induced strains at different angles to solidification direction are calculated, and the results agree well with the experimental data. The predictive curves of martensite Young’s modulus and macro reorientation strain in different directions are investigated. It may provide theoretical guidance for the design and use of ferromagnetic shape memory alloy.

  2. Micromechanical modeling of stress-induced strain in polycrystalline Ni–Mn–Ga by directional solidification

    International Nuclear Information System (INIS)

    Zhu, Yuping; Shi, Tao; Teng, Yao

    2015-01-01

    Highlights: • A micromechanical model of directional solidification Ni–Mn–Ga is developed. • The stress–strain curves in different directions are tested. • The martensite Young’s moduli in different directions are predicted. • The macro reorientation strains in different directions are investigated. - Abstract: Polycrystalline ferromagnetic shape memory alloy Ni–Mn–Ga produced by directional solidification possess unique properties. Its compressive stress–strain behaviors in loading–unloading cycle show nonlinear and anisotropic. Based on the self-consistent theory and thermodynamics principle, a micromechanical constitutive model of polycrystalline Ni–Mn–Ga by directional solidification is developed considering the generating mechanism of the macroscopic strain and anisotropy. Then, the stress induced strains at different angles to solidification direction are calculated, and the results agree well with the experimental data. The predictive curves of martensite Young’s modulus and macro reorientation strain in different directions are investigated. It may provide theoretical guidance for the design and use of ferromagnetic shape memory alloy

  3. Comparison of physically based constitutive models characterizing armor steel over wide temperature and strain rate ranges

    International Nuclear Information System (INIS)

    Xu, Zejian; Huang, Fenglei

    2012-01-01

    Both descriptive and predictive capabilities of five physically based constitutive models (PB, NNL, ZA, VA, and RK) are investigated and compared systematically, in characterizing plastic behavior of the 603 steel at temperatures ranging from 288 to 873 K, and strain rates ranging from 0.001 to 4500 s −1 . Determination of the constitutive parameters is introduced in detail for each model. Validities of the established models are checked by strain rate jump tests performed under different loading conditions. The results show that the RK and NNL models have better performance in the description of material behavior, especially the work-hardening effect, while the PB and VA models predict better. The inconsistency that is observed between the capabilities of description and prediction of the models indicates the existence of the minimum number of required fitting data, reflecting the degree of a model's requirement for basic data in parameter calibration. It is also found that the description capability of a model is dependent to a large extent on both its form and the number of its constitutive parameters, while the precision of prediction relies largely on the performance of description. In the selection of constitutive models, the experimental data and the constitutive models should be considered synthetically to obtain a better efficiency in material behavior characterization

  4. Comparison of physically based constitutive models characterizing armor steel over wide temperature and strain rate ranges

    Science.gov (United States)

    Xu, Zejian; Huang, Fenglei

    2012-01-01

    Both descriptive and predictive capabilities of five physically based constitutive models (PB, NNL, ZA, VA, and RK) are investigated and compared systematically, in characterizing plastic behavior of the 603 steel at temperatures ranging from 288 to 873 K, and strain rates ranging from 0.001 to 4500 s-1. Determination of the constitutive parameters is introduced in detail for each model. Validities of the established models are checked by strain rate jump tests performed under different loading conditions. The results show that the RK and NNL models have better performance in the description of material behavior, especially the work-hardening effect, while the PB and VA models predict better. The inconsistency that is observed between the capabilities of description and prediction of the models indicates the existence of the minimum number of required fitting data, reflecting the degree of a model's requirement for basic data in parameter calibration. It is also found that the description capability of a model is dependent to a large extent on both its form and the number of its constitutive parameters, while the precision of prediction relies largely on the performance of description. In the selection of constitutive models, the experimental data and the constitutive models should be considered synthetically to obtain a better efficiency in material behavior characterization.

  5. Computational model of 18650 lithium-ion battery with coupled strain rate and SOC dependencies

    International Nuclear Information System (INIS)

    Xu, Jun; Liu, Binghe; Wang, Xinyi; Hu, Dayong

    2016-01-01

    Highlights: • An anisotropic model to describe mechanical behaviors of LIB is established. • SOC dependency is included in the mechanical model of the jellyroll. • Dynamic effect is considered in the model for LIB. - Abstract: Highly nonlinear structures and constituent materials and hazardous experiment situations have resulted in a pressing need for a numerical mechanical model for lithium-ion battery (LIB). However, such a model is still not well established. In this paper, an anisotropic homogeneous model describing the jellyroll and the battery shell is established and validated through compression, indentation, and bending tests at quasi-static loadings. In this model, state-of-charge (SOC) dependency of the LIB is further included through an analogy with the strain-rate effect. Moreover, with consideration of the inertia and strain-rate effects, the anisotropic homogeneous model is extended into the dynamic regime and proven capable of predicting the dynamic response of the LIB using the drop-weight test. The established model may help to predict extreme cases with high SOCs and crashing speeds with an over 135% improved accuracy compared to traditional models. The established coupled strain rate and SOC dependencies of the numerical mechanical model for the LIB aims to provide a solid step toward unraveling and quantifying the complicated problems for research on LIB mechanical integrity.

  6. Combination of the electrocardiographic strain pattern and albuminuria for the prediction of new-onset heart failure in hypertensive patients: the LIFE study

    DEFF Research Database (Denmark)

    Okin, Peter M; Wachtell, Kristian; Devereux, Richard B

    2008-01-01

    Although albuminuria and the electrocardiographic (ECG) strain pattern each predict development of heart failure (HF), whether combining albuminuria and strain improves prediction of new HF is unclear.......Although albuminuria and the electrocardiographic (ECG) strain pattern each predict development of heart failure (HF), whether combining albuminuria and strain improves prediction of new HF is unclear....

  7. Predicted strain coverage of a meningococcal multicomponent vaccine (4CMenB) in Portugal.

    Science.gov (United States)

    Simões, Maria João; Bettencourt, Célia; De Paola, Rosita; Giuliani, Maria; Pizza, Mariagrazia; Moschioni, Monica; Machado, Jorge

    2017-01-01

    Although the incidence of meningococcal disease has been declining over the past decade in Portugal MenB meningococci is still an important cause of meningitis and sepsis. The aim of this study was to estimate the strain coverage of the 4CMenB vaccine in Portugal in order to support health policies for prevention and control of meningococcal disease. Since 2002 the clinical and laboratory notification of meningococcal disease is mandatory in Portugal. National database includes since then all confirmed cases notified to the reference laboratory or to the Directorate of Health. Strains included in this study were all the invasive MenB isolated from the 1st July 2011 to the 30th June 2015, sent to the reference laboratory. To predict the vaccine strain coverage of the 4CMenB the expression and cross-reactivity of the surface antigens fHbp, NadA, NHBA were assessed by the Meningococcal Antigen Typing System (MATS) whereas PorA typing was performed by sequencing. The presence of at least one antigen with a Relative Potency (RP) greater than its MATS-positive bactericidal threshold RP value or the presence of PorA VR2 = 4 was considered to be predictive for a strain to be covered by the 4CMenB vaccine. The estimated 4CMenB strain coverage in Portugal was 67.9%. The percentage of strain coverage in each of the four epidemiological years ranged from 63.9% to 73.7%. Strains covered by one antigen represent 32.1% of the total of isolates, 29.2% of strains were covered by two antigens and 6.6% by three antigens. No strain had all the four antigens. Antigens that most contributed for coverage were NHBA and fHbp. Data from Portugal is in accordance with the MATS predicted strain coverage in five European countries (England and Wales, France, Germany, Italy and Norway) that pointed to 78% coverage for strains collected in the epidemiological year 2007-2008.

  8. General Friction Model Extended by the Effect of Strain Hardening

    DEFF Research Database (Denmark)

    Nielsen, Chris V.; Martins, Paulo A.F.; Bay, Niels

    2016-01-01

    An extension to the general friction model proposed by Wanheim and Bay [1] to include the effect of strain hardening is proposed. The friction model relates the friction stress to the fraction of real contact area by a friction factor under steady state sliding. The original model for the real...... contact area as function of the normalized contact pressure is based on slip-line analysis and hence on the assumption of rigid-ideally plastic material behavior. In the present work, a general finite element model is established to, firstly, reproduce the original model under the assumption of rigid......-ideally plastic material, and secondly, to extend the solution by the influence of material strain hardening. This corresponds to adding a new variable and, therefore, a new axis to the general friction model. The resulting model is presented in a combined function suitable for e.g. finite element modeling...

  9. Analysis of an asymmetric two-strain dengue model.

    NARCIS (Netherlands)

    Kooi, B.W.; Aguiar, M.; Stollenwerk, N.

    2014-01-01

    In this paper we analyse a two-strain compartmental dengue fever model that allows us to study the behaviour of a Dengue fever epidemic. Dengue fever is the most common mosquito-borne viral disease of humans that in recent years has become a major international public health concern. The model is an

  10. Strain in the mesoscale kinetic Monte Carlo model for sintering

    DEFF Research Database (Denmark)

    Bjørk, Rasmus; Frandsen, Henrik Lund; Tikare, V.

    2014-01-01

    Shrinkage strains measured from microstructural simulations using the mesoscale kinetic Monte Carlo (kMC) model for solid state sintering are discussed. This model represents the microstructure using digitized discrete sites that are either grain or pore sites. The algorithm used to simulate dens...

  11. Prediction of material creep behaviour for strain based life assessment applications

    Energy Technology Data Exchange (ETDEWEB)

    Rantala, J.H.; Hurst, R.C. [EC JRC IAM, Petten (Netherlands); Bregani, F. [ENEL, Milan (Italy)

    1998-12-31

    In this work the idea of using constant load uniaxial creep test results instead of constant stress results for developing a CDM creep model for the P92 material is demonstrated. Due to limited availability of creep test results this work is based on incomplete test data and a general stress rupture line. In spite of these limitations a material creep model was developed for use in a FE analysis. Using P91 material as an example, a method is proposed to account for differences in strain evolution as a function of stress which normally manifests itself as lower strain values at low stresses in a normalised time-strain plot. This allows the CDM model to be used both in FE analysis and in strain-based life assessment engineering calculations. (orig.) 3 refs.

  12. Experimental Determination and Numerical Modelling of Process Induced Strains and Residual Stresses in Thick Glass/Epoxy Laminate

    DEFF Research Database (Denmark)

    Nielsen, Michael Wenani; Hattel, Jesper Henri; Løgstrup Andersen, Tom

    2012-01-01

    In this work, a cure hardening instantaneous linear elastic (CHILE) model and a path dependent (PD) constitutive approach are compared, for the case of modelling strain build-up during curing of a thick composite laminate part. The PD approach is a limiting case of viscoelasticity with path...... dependency on temperature and cure degree. Model predictions are compared to experimentally determined in-situ strains, determined using FBG sensors. It was found that both models offer good approximations of internal strain build-up. A general shortcoming is the lack of capturing rate-dependent effects...

  13. An analytical coal permeability model for tri-axial strain and stress conditions

    Energy Technology Data Exchange (ETDEWEB)

    Connell, Luke D.; Lu, Meng; Pan, Zhejun [Unconventional Gas Reservoirs, CSIRO Petroleum Resources, Ian Wark Laboratory, Bayview Avenue, Clayton, Vic 3168 (Australia)

    2010-11-01

    Coal permeability is sensitive to the effective stress and is therefore coupled to the geomechanical behaviour of the seam during gas migration. As coal shrinks with gas desorption and swells with adsorption, understanding this coupling to geomechanical behaviour is central to interpreting coal permeability. Existing coal permeability models, such as those proposed by Shi and Durucan (2004) and Palmer and Mansoori (1996), simplify the geomechanical processes by assuming uni-axial strain and constant vertical stress. However it is difficult to replicate these conditions in laboratory tri-axial permeability testing and during laboratory core flooding tests for enhanced coal bed methane. Often laboratory tests involve a hydrostatic stress state where the pressure in the confining fluid within the tri-axial cell is uniformly applied to the sample exterior. In this experimental arrangement the sample is allowed to undergo tri-axial strain. This paper presents two new analytical permeability model representations, derived from the general linear poroelastic constitutive law, that include the effects of tri-axial strain and stress for coal undergoing gas adsorption induced swelling. A novel approach is presented to the representation of the effect of coal sorption strain on cleat porosity and thus permeability. This involves distinguishing between the sorption strain of the coal matrix, the pores (or cleats) and the bulk coal. The developed model representations are applied to the results from a series of laboratory tests and it is shown that the models can predict the laboratory permeability data. As part of this characterisation the various sorption strains are identified and it is shown that the pore strain is significantly larger than (approximately 50 times) the bulk sorption strain. The models also provide further insight into how coal permeability varies with coal shrinkage and swelling and how the permeability rebound pressure depends upon the effective stress

  14. Evaluation of a dentoalveolar model for testing mouthguards: stress and strain analyses.

    Science.gov (United States)

    Verissimo, Crisnicaw; Costa, Paulo Victor Moura; Santos-Filho, Paulo César Freitas; Fernandes-Neto, Alfredo Júlio; Tantbirojn, Daranee; Versluis, Antheunis; Soares, Carlos José

    2016-02-01

    Custom-fitted mouthguards are devices used to decrease the likelihood of dental trauma. The aim of this study was to develop an experimental bovine dentoalveolar model with periodontal ligament to evaluate mouthguard shock absorption, and impact strain and stress behavior. A pendulum impact device was developed to perform the impact tests with two different impact materials (steel ball and baseball). Five bovine jaws were selected with standard age and dimensions. Six-mm mouthguards were made for the impact tests. The jaws were fixed in a pendulum device and impacts were performed from 90, 60, and 45° angles, with and without mouthguard. Strain gauges were attached at the palatal surface of the impacted tooth. The strain and shock absorption of the mouthguards was calculated and data were analyzed with 3-way anova and Tukey's test (α = 0.05). Two-dimensional finite element models were created based on the cross-section of the bovine dentoalveolar model used in the experiment. A nonlinear dynamic impact analysis was performed to evaluate the strain and stress distributions. Without mouthguards, the increase in impact angulation significantly increased strains and stresses. Mouthguards reduced strain and stress values. Impact velocity, impact object (steel ball or baseball), and mouthguard presence affected the impact stresses and strains in a bovine dentoalveolar model. Experimental strain measurements and finite element models predicted similar behavior; therefore, both methodologies are suitable for evaluating the biomechanical performance of mouthguards. © 2015 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

  15. Deformation modeling and the strain transient dip test

    International Nuclear Information System (INIS)

    Jones, W.B.; Rohde, R.W.; Swearengen, J.C.

    1980-01-01

    Recent efforts in material deformation modeling reveal a trend toward unifying creep and plasticity with a single rate-dependent formulation. While such models can describe actual material deformation, most require a number of different experiments to generate model parameter information. Recently, however, a new model has been proposed in which most of the requisite constants may be found by examining creep transients brought about through abrupt changes in creep stress (strain transient dip test). The critical measurement in this test is the absence of a resolvable creep rate after a stress drop. As a consequence, the result is extraordinarily sensitive to strain resolution as well as machine mechanical response. This paper presents the design of a machine in which these spurious effects have been minimized and discusses the nature of the strain transient dip test using the example of aluminum. It is concluded that the strain transient dip test is not useful as the primary test for verifying any micromechanical model of deformation. Nevertheless, if a model can be developed which is verifiable by other experimentts, data from a dip test machine may be used to generate model parameters

  16. Neural Network Prediction of Failure of Damaged Composite Pressure Vessels from Strain Field Data Acquired by a Computer Vision Method

    Science.gov (United States)

    Russell, Samuel S.; Lansing, Matthew D.

    1997-01-01

    This effort used a new and novel method of acquiring strains called Sub-pixel Digital Video Image Correlation (SDVIC) on impact damaged Kevlar/epoxy filament wound pressure vessels during a proof test. To predict the burst pressure, the hoop strain field distribution around the impact location from three vessels was used to train a neural network. The network was then tested on additional pressure vessels. Several variations on the network were tried. The best results were obtained using a single hidden layer. SDVIC is a fill-field non-contact computer vision technique which provides in-plane deformation and strain data over a load differential. This method was used to determine hoop and axial displacements, hoop and axial linear strains, the in-plane shear strains and rotations in the regions surrounding impact sites in filament wound pressure vessels (FWPV) during proof loading by internal pressurization. The relationship between these deformation measurement values and the remaining life of the pressure vessels, however, requires a complex theoretical model or numerical simulation. Both of these techniques are time consuming and complicated. Previous results using neural network methods had been successful in predicting the burst pressure for graphite/epoxy pressure vessels based upon acoustic emission (AE) measurements in similar tests. The neural network associates the character of the AE amplitude distribution, which depends upon the extent of impact damage, with the burst pressure. Similarly, higher amounts of impact damage are theorized to cause a higher amount of strain concentration in the damage effected zone at a given pressure and result in lower burst pressures. This relationship suggests that a neural network might be able to find an empirical relationship between the SDVIC strain field data and the burst pressure, analogous to the AE method, with greater speed and simplicity than theoretical or finite element modeling. The process of testing SDVIC

  17. Prediction of core and lower extremity strains and sprains in collegiate football players: a preliminary study.

    Science.gov (United States)

    Wilkerson, Gary B; Giles, Jessica L; Seibel, Dustin K

    2012-01-01

    Poor core stability is believed to increase vulnerability to uncontrolled joint displacements throughout the kinetic chain between the foot and the lumbar spine. To assess the value of preparticipation measurements as predictors of core or lower extremity strains or sprains in collegiate football players. Cohort study. National Collegiate Athletic Association Division I Football Championship Subdivision football program. All team members who were present for a mandatory physical examination on the day before preseason practice sessions began (n = 83). Preparticipation administration of surveys to assess low back, knee, and ankle function; documentation of knee and ankle injury history; determination of body mass index; 4 different assessments of core muscle endurance; and measurement of step-test recovery heart rate. All injuries were documented throughout the preseason practice period and 11-game season. Receiver operating characteristic analysis and logistic regression analysis were used to identify dichotomized predictive factors that best discriminated injured from uninjured status. The 75th and 50th percentiles were evaluated as alternative cutpoints for dichotomization of injury predictors. Players with ≥2 of 3 potentially modifiable risk factors related to core function had 2 times greater risk for injury than those with <2 factors (95% confidence interval = 1.27, 4.22), and adding a high level of exposure to game conditions increased the injury risk to 3 times greater (95% confidence interval = 1.95, 4.98). Prediction models that used the 75th and 50th percentile cutpoints yielded results that were very similar to those for the model that used receiver operating characteristic-derived cutpoints. Low back dysfunction and suboptimal endurance of the core musculature appear to be important modifiable football injury risk factors that can be identified on preparticipation screening. These predictors need to be assessed in a prospective manner with a larger

  18. Composite Cure Process Modeling and Simulations using COMPRO(Registered Trademark) and Validation of Residual Strains using Fiber Optics Sensors

    Science.gov (United States)

    Sreekantamurthy, Thammaiah; Hudson, Tyler B.; Hou, Tan-Hung; Grimsley, Brian W.

    2016-01-01

    Composite cure process induced residual strains and warping deformations in composite components present significant challenges in the manufacturing of advanced composite structure. As a part of the Manufacturing Process and Simulation initiative of the NASA Advanced Composite Project (ACP), research is being conducted on the composite cure process by developing an understanding of the fundamental mechanisms by which the process induced factors influence the residual responses. In this regard, analytical studies have been conducted on the cure process modeling of composite structural parts with varied physical, thermal, and resin flow process characteristics. The cure process simulation results were analyzed to interpret the cure response predictions based on the underlying physics incorporated into the modeling tool. In the cure-kinetic analysis, the model predictions on the degree of cure, resin viscosity and modulus were interpreted with reference to the temperature distribution in the composite panel part and tool setup during autoclave or hot-press curing cycles. In the fiber-bed compaction simulation, the pore pressure and resin flow velocity in the porous media models, and the compaction strain responses under applied pressure were studied to interpret the fiber volume fraction distribution predictions. In the structural simulation, the effect of temperature on the resin and ply modulus, and thermal coefficient changes during curing on predicted mechanical strains and chemical cure shrinkage strains were studied to understand the residual strains and stress response predictions. In addition to computational analysis, experimental studies were conducted to measure strains during the curing of laminated panels by means of optical fiber Bragg grating sensors (FBGs) embedded in the resin impregnated panels. The residual strain measurements from laboratory tests were then compared with the analytical model predictions. The paper describes the cure process

  19. Probabilistic predictive modelling of carbon nanocomposites for medical implants design.

    Science.gov (United States)

    Chua, Matthew; Chui, Chee-Kong

    2015-04-01

    Modelling of the mechanical properties of carbon nanocomposites based on input variables like percentage weight of Carbon Nanotubes (CNT) inclusions is important for the design of medical implants and other structural scaffolds. Current constitutive models for the mechanical properties of nanocomposites may not predict well due to differences in conditions, fabrication techniques and inconsistencies in reagents properties used across industries and laboratories. Furthermore, the mechanical properties of the designed products are not deterministic, but exist as a probabilistic range. A predictive model based on a modified probabilistic surface response algorithm is proposed in this paper to address this issue. Tensile testing of three groups of different CNT weight fractions of carbon nanocomposite samples displays scattered stress-strain curves, with the instantaneous stresses assumed to vary according to a normal distribution at a specific strain. From the probabilistic density function of the experimental data, a two factors Central Composite Design (CCD) experimental matrix based on strain and CNT weight fraction input with their corresponding stress distribution was established. Monte Carlo simulation was carried out on this design matrix to generate a predictive probabilistic polynomial equation. The equation and method was subsequently validated with more tensile experiments and Finite Element (FE) studies. The method was subsequently demonstrated in the design of an artificial tracheal implant. Our algorithm provides an effective way to accurately model the mechanical properties in implants of various compositions based on experimental data of samples. Copyright © 2015 Elsevier Ltd. All rights reserved.

  20. Modelling high strain rate phenomena in metal cutting simulation

    International Nuclear Information System (INIS)

    Wedberg, Dan; Svoboda, Ales; Lindgren, Lars-Erik

    2012-01-01

    Chip formation in metal cutting is associated with large strains and high strain rates, concentrated locally to deformation zones in front of the tool and beneath the cutting edge. Furthermore, dissipative plastic work and friction work generate high local temperatures. These phenomena together with numerical complications make modelling of metal cutting difficult. Material models, which are crucial in metal cutting simulations, are usually calibrated based on data from material testing. Nevertheless, the magnitude of strains and strain rates involved in metal cutting are several orders higher than those generated from conventional material testing. A highly desirable feature is therefore a material model that can be extrapolated outside the calibration range. In this study, two variants of a flow stress model based on dislocation density and vacancy concentration are used to simulate orthogonal metal cutting of AISI 316L stainless steel. It is found that the addition of phonon drag improves the results somewhat but the addition of this phenomenon still does not make it possible to extrapolate the constitutive model reliably outside its calibration range. (paper)

  1. Iowa calibration of MEPDG performance prediction models.

    Science.gov (United States)

    2013-06-01

    This study aims to improve the accuracy of AASHTO Mechanistic-Empirical Pavement Design Guide (MEPDG) pavement : performance predictions for Iowa pavement systems through local calibration of MEPDG prediction models. A total of 130 : representative p...

  2. Separation and prediction of irrecoverable strain components of concrete during the first thermal cycle

    International Nuclear Information System (INIS)

    Khoury, G.A.

    1993-01-01

    Strains of three AGR type concretes were measured during the first heat cycle and their relative thermal stability determined. It was possible to isolate for the first time the shrinkage and creep components for the period during heating-up. Predictions of the residual strains for the loaded specimens can be made by simple superposition of creep and shrinkage components up to a certain critical temperature, which for basalt concrete is about 500 deg. C and limestone concrete is about 200-300 deg. C. Above the critical temperature, it is necessary to add a 'cracking component'. (author)

  3. A Micro-Mechanically Based Continuum Model for Strain-Induced Crystallization in Natural Rubber

    Science.gov (United States)

    Mistry, Sunny Jigger

    Recent experimental results show that strain-induced crystallization can substantially improve the crack growth resistance of natural rubber. While this might suggest superior designs of tires or other industrial applications where elastomers are used, a more thorough understanding of the underlying physics of strain-induced crystallization in natural rubber has to be developed before any design process can be started. The objective of this work is to develop a computationally-accessible micro-mechanically based continuum model, which is able to predict the macroscopic behavior of strain crystallizing natural rubber. While several researchers have developed micro-mechanical models of partially crystallized polymer chains, their results mainly give qualitative agreement with experimental data due to a lack of good micro-macro transition theories or the lack of computational power. However, recent developments in multiscale modeling in polymers provide new tools to continue this early work. In this thesis, a new model is proposed to model strain-induced crystallization in natural rubber. To this end, a micro-mechanical model of a constrained partially crystallized polymer chain with an extended-chain crystal is derived and connected to the macroscopic level using the non-affine micro-sphere model. On the macroscopic level, a thermodynamically consistent framework for strain-crystallizing materials is developed, and a description of the crystallization kinetics is introduced. For that matter, an evolution law for crystallization based on the gradient of the macroscopic Helmholtz free energy function (chemical potential) in combination with a simple threshold function is used. A numerical implementation of the model is proposed and its predictive performance assessed using published data.

  4. Model complexity control for hydrologic prediction

    NARCIS (Netherlands)

    Schoups, G.; Van de Giesen, N.C.; Savenije, H.H.G.

    2008-01-01

    A common concern in hydrologic modeling is overparameterization of complex models given limited and noisy data. This leads to problems of parameter nonuniqueness and equifinality, which may negatively affect prediction uncertainties. A systematic way of controlling model complexity is therefore

  5. Crystal plasticity based finite element modelling of large strain deformation in AM30 magnesium alloy

    Science.gov (United States)

    Izadbakhsh, Adel; Inal, Kaan; Mishra, Raja K.

    2012-04-01

    In this paper, the finite strain plastic deformation of AM30 magnesium alloy has been simulated using the crystal plasticity finite element method. The simulations have been carried out using a rate-dependent elastic-viscoplastic crystal plasticity constitutive model implemented in a user defined material subroutine (UMAT) in the commercial software LS-DYNA. The plastic deformation mechanisms accounted for in the model are the slip systems in the matrix (parent grain), extension twinning systems and the slip systems inside the extension twinned regions. The parameters of the constitutive model have been calibrated using the experimental data. The calibrated model has then been used to predict the deformation of AM30 magnesium alloy in bending and simple shear. For the bending strain path, the effects of texture on the strain accommodated by the deformation mechanisms and bending moment have been investigated. For simple shear, the effects of texture on the relative activity of deformation mechanisms, shear stress and texture evolution have been investigated. Also, the effect of twinning on shear stress and texture evolution has been studied. The numerical analyses predicted a more uniform strain distribution during bending and simple shear for rolled texture compared with extruded texture.

  6. A Modified Johnson-Cook Model for Flow Behavior of Alloy 800H at Intermediate Strain Rates and High Temperatures

    Science.gov (United States)

    Shokry, Abdallah

    2017-12-01

    A modified Johnson-Cook model for the flow behavior of alloy 800H at intermediate strain rates and high temperatures is presented. The modification is based on a study of the relation between strain hardening and both strain rate and softening parameters. The predicted stresses obtained using the modified model are compared to those obtained using the original Johnson-Cook model. The parameters constitute the two models are determined using the inverse method, Kalman filter. The results show that the modified model fits the experimental data very well for different combinations of strain rates and temperatures, with a mean value of R-squared regression of 0.90 for the modified model and 0.74 for the original Johnson-Cook model.

  7. Staying Power of Churn Prediction Models

    NARCIS (Netherlands)

    Risselada, Hans; Verhoef, Peter C.; Bijmolt, Tammo H. A.

    In this paper, we study the staying power of various churn prediction models. Staying power is defined as the predictive performance of a model in a number of periods after the estimation period. We examine two methods, logit models and classification trees, both with and without applying a bagging

  8. Strain gradient plasticity-based modeling of hydrogen environment assisted cracking

    DEFF Research Database (Denmark)

    Martínez Pañeda, Emilio; Niordson, Christian Frithiof; P. Gangloff, Richard

    2016-01-01

    to predict hydrogen environment assisted crack growth properties. SGP elevates crack tip geometrically necessary dislocation density and flow stress, with enhancement declining with increasing alloy strength. Elevated hydrostatic stress promotes high-trapped H concentration for crack tip damage......Finite element analysis of stress about a blunt crack tip, emphasizing finite strain and phenomenologicaland mechanism-based strain gradient plasticity (SGP) formulations, is integrated with electrochemical assessment of occluded-crack tip hydrogen (H) solubility and two H-decohesion models......; it is imperative to account for SGP in H cracking models. Predictions of the threshold stress intensity factor and H-diffusion limited Stage II crack growth rate agree with experimental data for a high strength austenitic Ni-Cusuperalloy (Monel®K-500) and two modern ultra-high strength martensitic steels (Aer...

  9. The importance of the strain rate and creep on the stress corrosion cracking mechanisms and models

    International Nuclear Information System (INIS)

    Aly, Omar F.; Mattar Neto, Miguel; Schvartzman, Monica M.A.M.

    2011-01-01

    Stress corrosion cracking is a nuclear, power, petrochemical, and other industries equipment and components (like pressure vessels, nozzles, tubes, accessories) life degradation mode, involving fragile fracture. The stress corrosion cracking failures can produce serious accidents, and incidents which can put on risk the safety, reliability, and efficiency of many plants. These failures are of very complex prediction. The stress corrosion cracking mechanisms are based on three kinds of factors: microstructural, mechanical and environmental. Concerning the mechanical factors, various authors prefer to consider the crack tip strain rate rather than stress, as a decisive factor which contributes to the process: this parameter is directly influenced by the creep strain rate of the material. Based on two KAPL-Knolls Atomic Power Laboratory experimental studies in SSRT (slow strain rate test) and CL (constant load) test, for prediction of primary water stress corrosion cracking in nickel based alloys, it has done a data compilation of the film rupture mechanism parameters, for modeling PWSCC of Alloy 600 and discussed the importance of the strain rate and the creep on the stress corrosion cracking mechanisms and models. As derived from this study, a simple theoretical model is proposed, and it is showed that the crack growth rate estimated with Brazilian tests results with Alloy 600 in SSRT, are according with the KAPL ones and other published literature. (author)

  10. On the evolution and modelling of lattice strains during the cyclic loading of TWIP steel

    International Nuclear Information System (INIS)

    Saleh, Ahmed A.; Pereloma, Elena V.; Clausen, Bjørn; Brown, Donald W.; Tomé, Carlos N.; Gazder, Azdiar A.

    2013-01-01

    The evolution of lattice strains in fully annealed Fe–24Mn–3Al–2Si–1Ni–0.06C twinning-induced plasticity (TWIP) steel is investigated via in situ neutron diffraction during cyclic (tension–compression) loading between strain limits of ±1%. The pronounced Bauschinger effect observed upon load reversal is accounted for by a combination of the intergranular residual stresses and the intragranular sources of back stress, such as dislocation pile-ups at the intersection of stacking faults. The recently modified elasto-plastic self-consistent (EPSC) model which empirically accounts for both intergranular and intragranular back stresses has been successfully used to simulate the macroscopic stress–strain response and the evolution of the lattice strains. The EPSC model captures the experimentally observed tension–compression asymmetry as it accounts for the directionality of twinning as well as Schmid factor considerations. For the strain limits used in this study, the EPSC model also predicts that the lower flow stress on reverse shear loading reported in earlier Bauschinger-type experiments on TWIP steel is a geometrical or loading path effect

  11. Comparison of Prediction-Error-Modelling Criteria

    DEFF Research Database (Denmark)

    Jørgensen, John Bagterp; Jørgensen, Sten Bay

    2007-01-01

    Single and multi-step prediction-error-methods based on the maximum likelihood and least squares criteria are compared. The prediction-error methods studied are based on predictions using the Kalman filter and Kalman predictors for a linear discrete-time stochastic state space model, which is a r...

  12. Calibration of PMIS pavement performance prediction models.

    Science.gov (United States)

    2012-02-01

    Improve the accuracy of TxDOTs existing pavement performance prediction models through calibrating these models using actual field data obtained from the Pavement Management Information System (PMIS). : Ensure logical performance superiority patte...

  13. Predictive Model Assessment for Count Data

    National Research Council Canada - National Science Library

    Czado, Claudia; Gneiting, Tilmann; Held, Leonhard

    2007-01-01

    .... In case studies, we critique count regression models for patent data, and assess the predictive performance of Bayesian age-period-cohort models for larynx cancer counts in Germany. Key words: Calibration...

  14. Modeling and Prediction Using Stochastic Differential Equations

    DEFF Research Database (Denmark)

    Juhl, Rune; Møller, Jan Kloppenborg; Jørgensen, John Bagterp

    2016-01-01

    deterministic and can predict the future perfectly. A more realistic approach would be to allow for randomness in the model due to e.g., the model be too simple or errors in input. We describe a modeling and prediction setup which better reflects reality and suggests stochastic differential equations (SDEs......) for modeling and forecasting. It is argued that this gives models and predictions which better reflect reality. The SDE approach also offers a more adequate framework for modeling and a number of efficient tools for model building. A software package (CTSM-R) for SDE-based modeling is briefly described....... that describes the variation between subjects. The ODE setup implies that the variation for a single subject is described by a single parameter (or vector), namely the variance (covariance) of the residuals. Furthermore the prediction of the states is given as the solution to the ODEs and hence assumed...

  15. Sequence-based prediction for vaccine strain selection and identification of antigenic variability in foot-and-mouth disease virus.

    Directory of Open Access Journals (Sweden)

    Richard Reeve

    2010-12-01

    Full Text Available Identifying when past exposure to an infectious disease will protect against newly emerging strains is central to understanding the spread and the severity of epidemics, but the prediction of viral cross-protection remains an important unsolved problem. For foot-and-mouth disease virus (FMDV research in particular, improved methods for predicting this cross-protection are critical for predicting the severity of outbreaks within endemic settings where multiple serotypes and subtypes commonly co-circulate, as well as for deciding whether appropriate vaccine(s exist and how much they could mitigate the effects of any outbreak. To identify antigenic relationships and their predictors, we used linear mixed effects models to account for variation in pairwise cross-neutralization titres using only viral sequences and structural data. We identified those substitutions in surface-exposed structural proteins that are correlates of loss of cross-reactivity. These allowed prediction of both the best vaccine match for any single virus and the breadth of coverage of new vaccine candidates from their capsid sequences as effectively as or better than serology. Sub-sequences chosen by the model-building process all contained sites that are known epitopes on other serotypes. Furthermore, for the SAT1 serotype, for which epitopes have never previously been identified, we provide strong evidence--by controlling for phylogenetic structure--for the presence of three epitopes across a panel of viruses and quantify the relative significance of some individual residues in determining cross-neutralization. Identifying and quantifying the importance of sites that predict viral strain cross-reactivity not just for single viruses but across entire serotypes can help in the design of vaccines with better targeting and broader coverage. These techniques can be generalized to any infectious agents where cross-reactivity assays have been carried out. As the parameterization

  16. Constitutive Behavior Modelling of AA1100-O AT Large Strain and High Strain Rates

    Science.gov (United States)

    Testa, Gabriel; Iannitti, Gianluca; Ruggiero, Andrew; Gentile, Domenico; Bonora, Nicola

    2017-06-01

    Constitutive behavior of AA1100-O, provided as extruded bar, was investigated. Microscopic observation showed that the cross-section has a peculiar microstructure consisting in the inner core with a large grain size surrounded by an external annulus with finer grains. Low and high strain rates tensile tests were carried out at different temperature ranging from -190 ° C to 100 ° C. Constitutive behavior was modelled using a modified version of Rusinek & Klepaczko model. Parameters were calibrated on tensile test results. Tests and numerical simulations of symmetric Taylor (RoR) and dynamic tensile extrusion (DTE) tests at different impact velocities were carried out in order to validate the model under complex deformation paths.

  17. Predicting target displacements using ultrasound elastography and finite element modeling.

    Science.gov (United States)

    op den Buijs, Jorn; Hansen, Hendrik H G; Lopata, Richard G P; de Korte, Chris L; Misra, Sarthak

    2011-11-01

    Soft tissue displacements during minimally invasive surgical procedures may cause target motion and subsequent misplacement of the surgical tool. A technique is presented to predict target displacements using a combination of ultrasound elastography and finite element (FE) modeling. A cubic gelatin/agar phantom with stiff targets was manufactured to obtain pre- and post-loading ultrasound radio frequency (RF) data from a linear array transducer. The RF data were used to compute displacement and strain images, from which the distribution of elasticity was reconstructed using an inverse FE-based approach. The FE model was subsequently used to predict target displacements upon application of different boundary and loading conditions to the phantom. The influence of geometry was investigated by application of the technique to a breast-shaped phantom. The distribution of elasticity in the phantoms as determined from the strain distribution agreed well with results from mechanical testing. Upon application of different boundary and loading conditions to the cubic phantom, the FE model-predicted target motion were consistent with ultrasound measurements. The FE-based approach could also accurately predict the displacement of the target upon compression and indentation of the breast-shaped phantom. This study provides experimental evidence that organ geometry and boundary conditions surrounding the organ are important factors influencing target motion. In future work, the technique presented in this paper could be used for preoperative planning of minimally invasive surgical interventions.

  18. Development of a Generic Creep-Fatigue Life Prediction Model

    Science.gov (United States)

    Goswami, Tarun

    2002-01-01

    The objective of this research proposal is to further compile creep-fatigue data of steel alloys and superalloys used in military aircraft engines and/or rocket engines and to develop a statistical multivariate equation. The newly derived model will be a probabilistic fit to all the data compiled from various sources. Attempts will be made to procure the creep-fatigue data from NASA Glenn Research Center and other sources to further develop life prediction models for specific alloy groups. In a previous effort [1-3], a bank of creep-fatigue data has been compiled and tabulated under a range of known test parameters. These test parameters are called independent variables, namely; total strain range, strain rate, hold time, and temperature. The present research attempts to use these variables to develop a multivariate equation, which will be a probabilistic equation fitting a large database. The data predicted by the new model will be analyzed using the normal distribution fits, the closer the predicted lives are with the experimental lives (normal line 1 to 1 fit) the better the prediction. This will be evaluated in terms of a coefficient of correlation, R 2 as well. A multivariate equation developed earlier [3] has the following form, where S, R, T, and H have specific meaning discussed later.

  19. Predictive models for arteriovenous fistula maturation.

    Science.gov (United States)

    Al Shakarchi, Julien; McGrogan, Damian; Van der Veer, Sabine; Sperrin, Matthew; Inston, Nicholas

    2016-05-07

    Haemodialysis (HD) is a lifeline therapy for patients with end-stage renal disease (ESRD). A critical factor in the survival of renal dialysis patients is the surgical creation of vascular access, and international guidelines recommend arteriovenous fistulas (AVF) as the gold standard of vascular access for haemodialysis. Despite this, AVFs have been associated with high failure rates. Although risk factors for AVF failure have been identified, their utility for predicting AVF failure through predictive models remains unclear. The objectives of this review are to systematically and critically assess the methodology and reporting of studies developing prognostic predictive models for AVF outcomes and assess them for suitability in clinical practice. Electronic databases were searched for studies reporting prognostic predictive models for AVF outcomes. Dual review was conducted to identify studies that reported on the development or validation of a model constructed to predict AVF outcome following creation. Data were extracted on study characteristics, risk predictors, statistical methodology, model type, as well as validation process. We included four different studies reporting five different predictive models. Parameters identified that were common to all scoring system were age and cardiovascular disease. This review has found a small number of predictive models in vascular access. The disparity between each study limits the development of a unified predictive model.

  20. Model Predictive Control Fundamentals | Orukpe | Nigerian Journal ...

    African Journals Online (AJOL)

    Model Predictive Control (MPC) has developed considerably over the last two decades, both within the research control community and in industries. MPC strategy involves the optimization of a performance index with respect to some future control sequence, using predictions of the output signal based on a process model, ...

  1. Unreachable Setpoints in Model Predictive Control

    DEFF Research Database (Denmark)

    Rawlings, James B.; Bonné, Dennis; Jørgensen, John Bagterp

    2008-01-01

    In this work, a new model predictive controller is developed that handles unreachable setpoints better than traditional model predictive control methods. The new controller induces an interesting fast/slow asymmetry in the tracking response of the system. Nominal asymptotic stability of the optim...

  2. Modeling of the Strain Rate Dependency of Polycarbonate’s Yield Stress: Evaluation of Four Constitutive Equations

    Directory of Open Access Journals (Sweden)

    Abdullah A. Al-Juaid

    2016-01-01

    Full Text Available The main focus of this paper is in evaluating four constitutive relations which model the strain rate dependency of polymers yield stress. Namely, the two-term power-law, the Ree-Eyring, the cooperative, and the newly modified-Eyring equations are used to fit tensile and compression yield stresses of polycarbonate, which are obtained from the literature. The four equations give good agreement with the experimental data. Despite using only three material constants, the modified-Eyring equation, which considers a strain rate-dependent activation volume, gives slightly worse fit than the three other equations. The two-term power-law and the cooperative equation predict a progressive increase in the strain rate sensitivity of the yield stress. Oppositely, the Ree-Eyring and the modified-Eyring equations show a clear transition between the low and high strain rate ranges. Namely, they predict a linear dependency of the yield stress in terms of the strain rate at the low strain rate range. Crossing a threshold strain rate, the yield stress sensitivity sharply increases as the strain rate increases. Hence, two different behaviors were observed though the four equations fit well the experimental data. More experimental data, mainly at the intermediate strain rate range, are needed to conclude which, of the two behaviors, is more appropriate for polymers.

  3. Clinical Prediction Models for Cardiovascular Disease: Tufts Predictive Analytics and Comparative Effectiveness Clinical Prediction Model Database.

    Science.gov (United States)

    Wessler, Benjamin S; Lai Yh, Lana; Kramer, Whitney; Cangelosi, Michael; Raman, Gowri; Lutz, Jennifer S; Kent, David M

    2015-07-01

    Clinical prediction models (CPMs) estimate the probability of clinical outcomes and hold the potential to improve decision making and individualize care. For patients with cardiovascular disease, there are numerous CPMs available although the extent of this literature is not well described. We conducted a systematic review for articles containing CPMs for cardiovascular disease published between January 1990 and May 2012. Cardiovascular disease includes coronary heart disease, heart failure, arrhythmias, stroke, venous thromboembolism, and peripheral vascular disease. We created a novel database and characterized CPMs based on the stage of development, population under study, performance, covariates, and predicted outcomes. There are 796 models included in this database. The number of CPMs published each year is increasing steadily over time. Seven hundred seventeen (90%) are de novo CPMs, 21 (3%) are CPM recalibrations, and 58 (7%) are CPM adaptations. This database contains CPMs for 31 index conditions, including 215 CPMs for patients with coronary artery disease, 168 CPMs for population samples, and 79 models for patients with heart failure. There are 77 distinct index/outcome pairings. Of the de novo models in this database, 450 (63%) report a c-statistic and 259 (36%) report some information on calibration. There is an abundance of CPMs available for a wide assortment of cardiovascular disease conditions, with substantial redundancy in the literature. The comparative performance of these models, the consistency of effects and risk estimates across models and the actual and potential clinical impact of this body of literature is poorly understood. © 2015 American Heart Association, Inc.

  4. Strain Rate Dependent Behavior and Modeling for Compression Response of Hybrid Fiber Reinforced Concrete

    Directory of Open Access Journals (Sweden)

    S.M. Ibrahim

    Full Text Available Abstract This paper investigates the stress-strain characteristics of Hybrid fiber reinforced concrete (HFRC composites under dynamic compression using Split Hopkinson Pressure Bar (SHPB for strain rates in the range of 25 to 125 s-1. Three types of fibers - hooked ended steel fibers, monofilament crimped polypropylene fibers and staple Kevlar fibers were used in the production of HFRC composites. The influence of different fibers in HFRC composites on the failure mode, dynamic increase factor (DIF of strength, toughness and strain are also studied. Degree of fragmentation of HFRC composite specimens increases with increase in the strain rate. Although the use of high percentage of steel fibers leads to the best performance but among the hybrid fiber combinations studied, HFRC composites with relatively higher percentage of steel fibers and smaller percentage of polypropylene and Kevlar fibers seem to reflect the equally good synergistic effects of fibers under dynamic compression. A rate dependent analytical model is proposed for predicting complete stress-strain curves of HFRC composites. The model is based on a comprehensive fiber reinforcing index and complements well with the experimental results.

  5. A model for recovery kinetics of aluminum after large strain

    DEFF Research Database (Denmark)

    Yu, Tianbo; Hansen, Niels

    2012-01-01

    A model is suggested to analyze recovery kinetics of heavily deformed aluminum. The model is based on the hardness of isothermal annealed samples before recrystallization takes place, and it can be extrapolated to longer annealing times to factor out the recrystallization component of the hardness...... for conditions where recovery and recrystallization overlap. The model is applied to the isothermal recovery at temperatures between 140 and 220°C of commercial purity aluminum deformed to true strain 5.5. EBSD measurements have been carried out to detect the onset of discontinuous recrystallization. Furthermore...

  6. Two Strain Dengue Model with Temporary Cross Immunity and Seasonality

    International Nuclear Information System (INIS)

    Aguiar, Maira; Ballesteros, Sebastien; Stollenwerk, Nico

    2010-01-01

    Models on dengue fever epidemiology have previously shown critical fluctuations with power law distributions and also deterministic chaos in some parameter regions due to the multi-strain structure of the disease pathogen. In our first model including well known biological features, we found a rich dynamical structure including limit cycles, symmetry breaking bifurcations, torus bifurcations, coexisting attractors including isola solutions and deterministic chaos (as indicated by positive Lyapunov exponents) in a much larger parameter region, which is also biologically more plausible than the previous results of other researches. Based on these findings we will investigate the model structures further including seasonality.

  7. Hybrid approaches to physiologic modeling and prediction

    Science.gov (United States)

    Olengü, Nicholas O.; Reifman, Jaques

    2005-05-01

    This paper explores how the accuracy of a first-principles physiological model can be enhanced by integrating data-driven, "black-box" models with the original model to form a "hybrid" model system. Both linear (autoregressive) and nonlinear (neural network) data-driven techniques are separately combined with a first-principles model to predict human body core temperature. Rectal core temperature data from nine volunteers, subject to four 30/10-minute cycles of moderate exercise/rest regimen in both CONTROL and HUMID environmental conditions, are used to develop and test the approach. The results show significant improvements in prediction accuracy, with average improvements of up to 30% for prediction horizons of 20 minutes. The models developed from one subject's data are also used in the prediction of another subject's core temperature. Initial results for this approach for a 20-minute horizon show no significant improvement over the first-principles model by itself.

  8. Self-consistent modelling of lattice strains during the in-situ tensile loading of twinning induced plasticity steel

    International Nuclear Information System (INIS)

    Saleh, Ahmed A.; Pereloma, Elena V.; Clausen, Bjørn; Brown, Donald W.; Tomé, Carlos N.; Gazder, Azdiar A.

    2014-01-01

    The evolution of lattice strains in a fully recrystallised Fe–24Mn–3Al–2Si–1Ni–0.06C TWinning Induced Plasticity (TWIP) steel subjected to uniaxial tensile loading up to a true strain of ∼35% was investigated via in-situ neutron diffraction. Typical of fcc elastic and plastic anisotropy, the {111} and {200} grain families record the lowest and highest lattice strains, respectively. Using modelling cases with and without latent hardening, the recently extended Elasto-Plastic Self-Consistent model successfully predicted the macroscopic stress–strain response, the evolution of lattice strains and the development of crystallographic texture. Compared to the isotropic hardening case, latent hardening did not have a significant effect on lattice strains and returned a relatively faster development of a stronger 〈111〉 and a weaker 〈100〉 double fibre parallel to the tensile axis. Close correspondence between the experimental lattice strains and those predicted using particular orientations embedded within a random aggregate was obtained. The result suggests that the exact orientations of the surrounding aggregate have a weak influence on the lattice strain evolution

  9. Anisotropic Constitutive Model of Strain-Induced Phenomena in Stainless Steels at Cryogenic Temperatures

    International Nuclear Information System (INIS)

    Garion, C.; Skoczen, B.

    2004-01-01

    A majority of the thin-walled components subjected to intensive plastic straining at cryogenic temperatures are made of stainless steels. The examples of such components can be found in the interconnections of particle accelerators, containing the superconducting magnets, where the thermal contraction is absorbed by thin-walled, axisymmetric shells called bellows expansion joints. The stainless steels show three main phenomena induced by plastic strains at cryogenic temperatures: serrated (discontinuous) yielding, γ→α' phase transformation and anisotropic ductile damage. In the present paper, a coupled constitutive model of γ→α' phase transformation and orthotropic ductile damage is presented. A kinetic law of phase transformation, and a kinetic law of evolution of orthotropic damage are presented. The model is extended to anisotropic plasticity comprising a constant anisotropy (texture effect), which can be classically taken into account by the Hill yield surface, and plastic strain induced anisotropy. For such a model the shape of the yield surface in the stress space varies as a function of the plastic strains. The constitutive model creates a bridge between material science (experiments) and structural analysis. It has been used to predict the response of beam vacuum and cryogenic bellows to monotonic and cyclic loads developed in the interconnections of the Large Hadron Collider at CERN

  10. Diagnostic Value of Knee Arthrometry in the Prediction of Anterior Cruciate Ligament Strain During Landing

    Science.gov (United States)

    Kiapour, Ata M.; Wordeman, Samuel C.; Paterno, Mark V.; Quatman, Carmen E.; Levine, Jason W.; Goel, Vijay K.; Demetropoulos, Constantine K.; Hewett, Timothy E.

    2014-01-01

    of applied anterior shear load produced a mean peak anterior tibial translation of 3.1 ± 1.1 mm and a mean peak ACL strain of 4.9% ± 4.3%. Anterior shear load was a significant determinant of anterior tibial translation (P anterior tibial translation and ACL strain. Cadaveric simulations of landing produced a mean axial impact load of 4070 ± 732 N. Simulated landing significantly increased the mean peak anterior tibial translation to 10.4 ± 3.5 mm and the mean peak ACL strain to 6.8% ± 2.8% (P anterior tibial translation quantified by knee arthrometry. Conclusion Our first hypothesis is supported by a significant correlation between arthrometry displacement collected during laxity tests and concurrent ACL strain calculated from DVRT measurements. Experimental findings also support our second hypothesis that instrumented measures of anterior knee laxity predict peak ACL strain during landing, while specimens with greater knee laxity demonstrated higher levels of peak ACL strain during landing. Clinical Relevance The current findings highlight the importance of instrumented anterior knee laxity assessments as a potential indicator of the risk of ACL injuries in addition to its clinical utility in the evaluation of ACL integrity. PMID:24275863

  11. Comparison of the immunomodulatory properties of three probiotic strains of Lactobacilli using complex culture systems: prediction for in vivo efficacy.

    Directory of Open Access Journals (Sweden)

    Erika Mileti

    Full Text Available BACKGROUND: While the use of probiotics to treat or prevent inflammatory bowel disease (IBD has been proposed, to this point the clinical benefits have been limited. In this report we analyzed the immunological activity of three strains of Lactobacillus to predict their in vivo efficacy in protecting against experimental colitis. METHODOLOGY/PRINCIPAL FINDINGS: We compared the immunological properties of Lactobacillus plantarum NCIMB8826, L. rhamnosus GG (LGG, L. paracasei B21060 and pathogenic Salmonella typhimurium (SL1344. We studied the stimulatory effects of these different strains upon dendritic cells (DCs either directly by co-culture or indirectly via conditioning of an epithelial intermediary. Furthermore, we characterized the effects of these strains in vivo using a Dextran sulphate sodium (DSS model of colitis. We found that the three strains exhibited different abilities to induce inflammatory cytokine production by DCs with L. plantarum being the most effective followed by LGG and L. paracasei. L. paracasei minimally induced the release of cytokines, while it also inhibited the potential of DCs to both produce inflammatory cytokines (IL-12 and TNF-alpha and to drive Th1 T cells in response to Salmonella. This effect on DCs was found under both direct and indirect stimulatory conditions - i.e. mediated by epithelial cells - and was dependent upon an as yet unidentified soluble mediator. When tested in vivo, L. plantarum and LGG exacerbated the development of DSS-induced colitis and caused the death of treated mice, while, conversely L. paracasei was protective. CONCLUSIONS: We describe a new property of probiotics to either directly or indirectly inhibit DC activation by inflammatory bacteria. Moreover, some immunostimulatory probiotics not only failed to protect against colitis, they actually amplified the disease progression. In conclusion, caution must be exercised when choosing a probiotic strain to treat IBD.

  12. Evaluating the Predictive Value of Growth Prediction Models

    Science.gov (United States)

    Murphy, Daniel L.; Gaertner, Matthew N.

    2014-01-01

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

  13. Model predictive control classical, robust and stochastic

    CERN Document Server

    Kouvaritakis, Basil

    2016-01-01

    For the first time, a textbook that brings together classical predictive control with treatment of up-to-date robust and stochastic techniques. Model Predictive Control describes the development of tractable algorithms for uncertain, stochastic, constrained systems. The starting point is classical predictive control and the appropriate formulation of performance objectives and constraints to provide guarantees of closed-loop stability and performance. Moving on to robust predictive control, the text explains how similar guarantees may be obtained for cases in which the model describing the system dynamics is subject to additive disturbances and parametric uncertainties. Open- and closed-loop optimization are considered and the state of the art in computationally tractable methods based on uncertainty tubes presented for systems with additive model uncertainty. Finally, the tube framework is also applied to model predictive control problems involving hard or probabilistic constraints for the cases of multiplic...

  14. Experimental Study and Modelling of Poly (Methyl Methacrylate) and Polycarbonate Compressive Behavior from Low to High Strain Rates

    Science.gov (United States)

    El-Qoubaa, Z.; Colard, L.; Matadi Boumbimba, R.; Rusinek, A.

    2018-03-01

    This paper concerns an experimental investigation of Polycarbonate and Poly (methyl methacrylate) compressive behavior from low to high strain rates. Experiments were conducted from 0.001/s to ≈ 5000/s for PC and from 0.001/s to ≈ 2000/s for PMMA. The true strain-stress behavior is established and analyzed at various stain rates. Both PC and PMMA mechanical behavior appears as known, to be strain rate and temperature dependent. The DSGZ model is selected for modelling the strain-stress curves while the yield stress is reproduced using the cooperative model and a modified Eyring equation based on Eyring first process theory. All the three models predictions are in agreement with experiments performed on PC and PMMA.

  15. Sustained involvement in youth sports activities predicts reduced chronic job strain in early midlife.

    Science.gov (United States)

    Yang, X; Telama, R; Hirvensalo, M; Hintsanen, M; Hintsa, T; Pulkki-Råback, L; Mansikkaniemi, K; Viikari, J S A; Keltikangas-Järvinen, L; Raitakari, O T

    2010-12-01

    We examined the long-term effects of youth leisure time physical activity (LTPA) and sports participation on the prevalence of chronic work stress in adulthood. Participants (326 men and 338 women) aged 9 to 18 years were initially enrolled in 1980 and followed until 2007. Data were collected using questionnaires and bicycle ergometry in a subgroup. High youth LTPA and sports participation predicted lower chronic job strain in both sexes. The association was mediated by type A leadership. Participation and persistence in organized youth sports followed a similar pattern. In the subgroup, adult physical fitness only partly accounted for the association. Sustained involvement in youth physical activity and sport lasting at least 3 years is associated with reduced chronic job strain in adulthood. The association was partially explained by type A leadership and physical fitness.

  16. A Global Model for Bankruptcy Prediction.

    Science.gov (United States)

    Alaminos, David; Del Castillo, Agustín; Fernández, Manuel Ángel

    2016-01-01

    The recent world financial crisis has increased the number of bankruptcies in numerous countries and has resulted in a new area of research which responds to the need to predict this phenomenon, not only at the level of individual countries, but also at a global level, offering explanations of the common characteristics shared by the affected companies. Nevertheless, few studies focus on the prediction of bankruptcies globally. In order to compensate for this lack of empirical literature, this study has used a methodological framework of logistic regression to construct predictive bankruptcy models for Asia, Europe and America, and other global models for the whole world. The objective is to construct a global model with a high capacity for predicting bankruptcy in any region of the world. The results obtained have allowed us to confirm the superiority of the global model in comparison to regional models over periods of up to three years prior to bankruptcy.

  17. A thermomechanical constitutive model for superelastic SMA wire with strain-rate dependence

    Science.gov (United States)

    Zhu, Songye; Zhang, Yunfeng

    2007-10-01

    The recent increased use of shape memory alloys (SMAs) for civil engineering applications manifests the need for a high-fidelity constitutive model which considers the material's strong dependence on the loading rate. This paper presents an improved thermomechanical constitutive model with strain-rate dependence for predicting the uniaxial superelastic behavior of shape memory alloys. The proposed constitutive model, which is formulated within a thermomechanical framework, is comprised of three principal parts: a mechanical law, an energy balance equation, and a transformation kinetics rule. The analytical derivation of the model and experimental test results for superelastic NiTi wires are described in this paper. The prediction made by this phenomenological model shows good agreement with experimental data for superelastic NiTi wires at various loading rates. Through a comparison with experimental results, the proposed constitutive model was evaluated for several key characteristics of superelastic behavior such as reduction of hysteresis area, increase of transformation plateau, and temperature change with strain rate. The proposed constitutive model offers a useful tool for the design and simulation of superelastic SMA-based devices in civil engineering applications.

  18. A STRAINED EUROPEAN MODEL. IS EASTERN ENLARGEMENT TO BLAME?

    Directory of Open Access Journals (Sweden)

    Daniel Daianu

    2007-04-01

    Full Text Available As anticipated, the recent enlargement has put considerable pressure on the European construction, as most of the EU15 member countries are economically and socially strained and policy-makers have a very hard time in devising proper answers to society’s ills. The paper examines various factors which have strained the European Social Model and which, arguably, make this period of Euro-pessimism quite peculiar. It looks at the race for competitiveness in today’s world and the economic rise of Asia; it looks at some inner dynamics in the European societies (demographics, the crisis of the welfare state, a sort of decadence and it tries to explore what lies ahead, including policy options. An underlying thesis herein is that eastern enlargement is not the culprit for the current pains of the EU member countries, though it may have accentuated some.

  19. Fingerprint verification prediction model in hand dermatitis.

    Science.gov (United States)

    Lee, Chew K; Chang, Choong C; Johor, Asmah; Othman, Puwira; Baba, Roshidah

    2015-07-01

    Hand dermatitis associated fingerprint changes is a significant problem and affects fingerprint verification processes. This study was done to develop a clinically useful prediction model for fingerprint verification in patients with hand dermatitis. A case-control study involving 100 patients with hand dermatitis. All patients verified their thumbprints against their identity card. Registered fingerprints were randomized into a model derivation and model validation group. Predictive model was derived using multiple logistic regression. Validation was done using the goodness-of-fit test. The fingerprint verification prediction model consists of a major criterion (fingerprint dystrophy area of ≥ 25%) and two minor criteria (long horizontal lines and long vertical lines). The presence of the major criterion predicts it will almost always fail verification, while presence of both minor criteria and presence of one minor criterion predict high and low risk of fingerprint verification failure, respectively. When none of the criteria are met, the fingerprint almost always passes the verification. The area under the receiver operating characteristic curve was 0.937, and the goodness-of-fit test showed agreement between the observed and expected number (P = 0.26). The derived fingerprint verification failure prediction model is validated and highly discriminatory in predicting risk of fingerprint verification in patients with hand dermatitis. © 2014 The International Society of Dermatology.

  20. Massive Predictive Modeling using Oracle R Enterprise

    CERN Multimedia

    CERN. Geneva

    2014-01-01

    R is fast becoming the lingua franca for analyzing data via statistics, visualization, and predictive analytics. For enterprise-scale data, R users have three main concerns: scalability, performance, and production deployment. Oracle's R-based technologies - Oracle R Distribution, Oracle R Enterprise, Oracle R Connector for Hadoop, and the R package ROracle - address these concerns. In this talk, we introduce Oracle's R technologies, highlighting how each enables R users to achieve scalability and performance while making production deployment of R results a natural outcome of the data analyst/scientist efforts. The focus then turns to Oracle R Enterprise with code examples using the transparency layer and embedded R execution, targeting massive predictive modeling. One goal behind massive predictive modeling is to build models per entity, such as customers, zip codes, simulations, in an effort to understand behavior and tailor predictions at the entity level. Predictions...

  1. Modeling mechanical signals on the surface of µCT and CAD based rapid prototype scaffold models to predict (early stage) tissue development

    NARCIS (Netherlands)

    Hendrikson, W.J.; van Blitterswijk, Clemens; Verdonschot, Nicolaas Jacobus Joseph; Moroni, Lorenzo; Rouwkema, Jeroen

    2014-01-01

    In the field of tissue engineering, mechano-regulation theories have been applied to help predict tissue development in tissue engineering scaffolds in the past. For this, finite element models (FEMs) were used to predict the distribution of strains within a scaffold. However, the strains reported

  2. Modeling mechanical signals on the surface of microCT and CAD based rapid prototype scaffold models to predict (early stage) tissue development

    NARCIS (Netherlands)

    Hendrikson, W.J.; Blitterswijk, C.A. van; Verdonschot, N.J.; Moroni, L.; Rouwkema, J.

    2014-01-01

    In the field of tissue engineering, mechano-regulation theories have been applied to help predict tissue development in tissue engineering scaffolds in the past. For this, finite element models (FEMs) were used to predict the distribution of strains within a scaffold. However, the strains reported

  3. Predictive Model of Systemic Toxicity (SOT)

    Science.gov (United States)

    In an effort to ensure chemical safety in light of regulatory advances away from reliance on animal testing, USEPA and L’Oréal have collaborated to develop a quantitative systemic toxicity prediction model. Prediction of human systemic toxicity has proved difficult and remains a ...

  4. Testicular Cancer Risk Prediction Models

    Science.gov (United States)

    Developing statistical models that estimate the probability of testicular cervical cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

  5. Pancreatic Cancer Risk Prediction Models

    Science.gov (United States)

    Developing statistical models that estimate the probability of developing pancreatic cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

  6. Colorectal Cancer Risk Prediction Models

    Science.gov (United States)

    Developing statistical models that estimate the probability of developing colorectal cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

  7. Prostate Cancer Risk Prediction Models

    Science.gov (United States)

    Developing statistical models that estimate the probability of developing prostate cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

  8. Bladder Cancer Risk Prediction Models

    Science.gov (United States)

    Developing statistical models that estimate the probability of developing bladder cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

  9. Esophageal Cancer Risk Prediction Models

    Science.gov (United States)

    Developing statistical models that estimate the probability of developing esophageal cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

  10. Cervical Cancer Risk Prediction Models

    Science.gov (United States)

    Developing statistical models that estimate the probability of developing cervical cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

  11. Breast Cancer Risk Prediction Models

    Science.gov (United States)

    Developing statistical models that estimate the probability of developing breast cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

  12. Lung Cancer Risk Prediction Models

    Science.gov (United States)

    Developing statistical models that estimate the probability of developing lung cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

  13. Liver Cancer Risk Prediction Models

    Science.gov (United States)

    Developing statistical models that estimate the probability of developing liver cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

  14. Ovarian Cancer Risk Prediction Models

    Science.gov (United States)

    Developing statistical models that estimate the probability of developing ovarian cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

  15. Behaviour and modelling of aluminium alloy AA6060 subjected to a wide range of strain rates and temperatures

    Directory of Open Access Journals (Sweden)

    Vilamosa Vincent

    2015-01-01

    Full Text Available The thermo-mechanical behaviour in tension of an as-cast and homogenized AA6060 alloy was investigated at a wide range of strains (the entire deformation process up to fracture, strain rates (0.01–750 s−1 and temperatures (20–350 ∘C. The tests at strain rates up to 1 s−1 were performed in a universal testing machine, while a split-Hopkinson tension bar (SHTB system was used for strain rates from 350 to 750 s−1. The samples were heated with an induction-based heating system. A typical feature of aluminium alloys at high temperatures is that necking occurs at a rather early stage of the deformation process. In order to determine the true stress-strain curve also after the onset of necking, all tests were instrumented with a digital camera. The experimental tests reveal that the AA6060 material has negligible strain-rate sensitivity (SRS for temperatures lower than 200 ∘C, while both yielding and work hardening exhibit a strong positive SRS at higher temperatures. The coupled strain-rate and temperature sensitivity is challenging to capture with most existing constitutive models. The paper presents an outline of a new semi-physical model that expresses the flow stress in terms of plastic strain, plastic strain rate and temperature. The parameters of the model were determined from the tests, and the stress-strain curves from the tests were compared with the predictions of the model. Good agreement was obtained over the entire strain rate and temperature range.

  16. Posterior Predictive Model Checking in Bayesian Networks

    Science.gov (United States)

    Crawford, Aaron

    2014-01-01

    This simulation study compared the utility of various discrepancy measures within a posterior predictive model checking (PPMC) framework for detecting different types of data-model misfit in multidimensional Bayesian network (BN) models. The investigated conditions were motivated by an applied research program utilizing an operational complex…

  17. On the prediction of ductile fracture by void coalescence and strain localization

    Science.gov (United States)

    Luo, Tuo; Gao, Xiaosheng

    2018-04-01

    This paper presents a unit cell model based on the observation that ductile fracture occurs when plastic flow is localized in a band. The unit cell consists of three void containing material units stacked in the direction normal to the localization plane. Localization takes place in the middle material unit while the two outer units undergo elastic recovery after failure occurs. Thus a failure criterion is established as when the macroscopic effective strain of the outer material units reaches the maximum value. Analyses are conducted to demonstrate the effect of the voids existing outside the localization band. Comparisons of the present model with several previous models suggest that the present model is not only easy to implement in finite element analysis but also more suitable to robustly determine the failure strain. A series of unit cell analyses are conducted for various macroscopic stress triaxialities and Lode parameters. The analysis results confirm that for a fixed Lode parameter, the failure strain decreases exponentially with the stress triaxiality and for a given stress triaxiality, it increases as the stress state approaches the generalized tension and generalized compression. The analysis results also reveal the effect of the stress state on the deformed void shape within and near the localization band.

  18. Strain Rate Dependant Material Model for Orthotropic Metals

    Science.gov (United States)

    Vignjevic, Rade

    2016-08-01

    In manufacturing processes anisotropic metals are often exposed to the loading with high strain rates in the range from 102 s-1 to 106 s-1 (e.g. stamping, cold spraying and explosive forming). These types of loading often involve generation and propagation of shock waves within the material. The material behaviour under such a complex loading needs to be accurately modelled, in order to optimise the manufacturing process and achieve appropriate properties of the manufactured component. The presented research is related to development and validation of a thermodynamically consistent physically based constitutive model for metals under high rate loading. The model is capable of modelling damage, failure and formation and propagation of shock waves in anisotropic metals. The model has two main parts: the strength part which defines the material response to shear deformation and an equation of state (EOS) which defines the material response to isotropic volumetric deformation [1]. The constitutive model was implemented into the transient nonlinear finite element code DYNA3D [2] and our in house SPH code. Limited model validation was performed by simulating a number of high velocity material characterisation and validation impact tests. The new damage model was developed in the framework of configurational continuum mechanics and irreversible thermodynamics with internal state variables. The use of the multiplicative decomposition of deformation gradient makes the model applicable to arbitrary plastic and damage deformations. To account for the physical mechanisms of failure, the concept of thermally activated damage initially proposed by Tuller and Bucher [3], Klepaczko [4] was adopted as the basis for the new damage evolution model. This makes the proposed damage/failure model compatible with the Mechanical Threshold Strength (MTS) model Follansbee and Kocks [5], 1988; Chen and Gray [6] which was used to control evolution of flow stress during plastic deformation. In

  19. Predicting and Modeling RNA Architecture

    Science.gov (United States)

    Westhof, Eric; Masquida, Benoît; Jossinet, Fabrice

    2011-01-01

    SUMMARY A general approach for modeling the architecture of large and structured RNA molecules is described. The method exploits the modularity and the hierarchical folding of RNA architecture that is viewed as the assembly of preformed double-stranded helices defined by Watson-Crick base pairs and RNA modules maintained by non-Watson-Crick base pairs. Despite the extensive molecular neutrality observed in RNA structures, specificity in RNA folding is achieved through global constraints like lengths of helices, coaxiality of helical stacks, and structures adopted at the junctions of helices. The Assemble integrated suite of computer tools allows for sequence and structure analysis as well as interactive modeling by homology or ab initio assembly with possibilities for fitting within electronic density maps. The local key role of non-Watson-Crick pairs guides RNA architecture formation and offers metrics for assessing the accuracy of three-dimensional models in a more useful way than usual root mean square deviation (RMSD) values. PMID:20504963

  20. Multiple Steps Prediction with Nonlinear ARX Models

    OpenAIRE

    Zhang, Qinghua; Ljung, Lennart

    2007-01-01

    NLARX (NonLinear AutoRegressive with eXogenous inputs) models are frequently used in black-box nonlinear system identication. Though it is easy to make one step ahead prediction with such models, multiple steps prediction is far from trivial. The main difficulty is that in general there is no easy way to compute the mathematical expectation of an output conditioned by past measurements. An optimal solution would require intensive numerical computations related to nonlinear filltering. The pur...

  1. Predictability of extreme values in geophysical models

    Directory of Open Access Journals (Sweden)

    A. E. Sterk

    2012-09-01

    Full Text Available Extreme value theory in deterministic systems is concerned with unlikely large (or small values of an observable evaluated along evolutions of the system. In this paper we study the finite-time predictability of extreme values, such as convection, energy, and wind speeds, in three geophysical models. We study whether finite-time Lyapunov exponents are larger or smaller for initial conditions leading to extremes. General statements on whether extreme values are better or less predictable are not possible: the predictability of extreme values depends on the observable, the attractor of the system, and the prediction lead time.

  2. Kinetic characteristics and modelling of growth and substrate removal by Alcaligenes faecalis strain NR.

    Science.gov (United States)

    Chen, Jie; Zhao, Bin; An, Qiang; Wang, Xia; Zhang, Yi Xin

    2016-04-01

    Alcaligenes faecalis strain NR has the capability of simultaneous ammonium and organic carbon removal under sole aerobic conditions. The growth and substrate removal characteristics of A. faecalis strain NR were studied and appropriate kinetic models were developed. The maximum substrate removal rate of NH4 (+)-N and TOC were determined as 2.27 mg NH4 (+)-N/L/h and 30.00 mg TOC/L/h, respectively with initial NH4 (+)-N = 80 mg/L and TOC = 800 mg/L. Single-substrate models and double-substrate models based on Monod, Contois, Moser and Teissier were employed to describe the bioprocess kinetic coefficients. As a result, two double-substrate models, Teissier-Contois and Contois-Contois, were considered to be appropriate to model growth kinetics with both NH4 (+)-N and TOC as limiting substrates. The kinetic constants of maximum growth rate (μ max) and half-saturation constant (K S and B S) were obtained by solving multiple equations with regression. This work can be used to further understand and predict the performance of heterotrophic nitrifiers, and thus provides specific guidance of these functional strains in practical wastewater treatment process.

  3. Model complexity control for hydrologic prediction

    Science.gov (United States)

    Schoups, G.; van de Giesen, N. C.; Savenije, H. H. G.

    2008-12-01

    A common concern in hydrologic modeling is overparameterization of complex models given limited and noisy data. This leads to problems of parameter nonuniqueness and equifinality, which may negatively affect prediction uncertainties. A systematic way of controlling model complexity is therefore needed. We compare three model complexity control methods for hydrologic prediction, namely, cross validation (CV), Akaike's information criterion (AIC), and structural risk minimization (SRM). Results show that simulation of water flow using non-physically-based models (polynomials in this case) leads to increasingly better calibration fits as the model complexity (polynomial order) increases. However, prediction uncertainty worsens for complex non-physically-based models because of overfitting of noisy data. Incorporation of physically based constraints into the model (e.g., storage-discharge relationship) effectively bounds prediction uncertainty, even as the number of parameters increases. The conclusion is that overparameterization and equifinality do not lead to a continued increase in prediction uncertainty, as long as models are constrained by such physical principles. Complexity control of hydrologic models reduces parameter equifinality and identifies the simplest model that adequately explains the data, thereby providing a means of hydrologic generalization and classification. SRM is a promising technique for this purpose, as it (1) provides analytic upper bounds on prediction uncertainty, hence avoiding the computational burden of CV, and (2) extends the applicability of classic methods such as AIC to finite data. The main hurdle in applying SRM is the need for an a priori estimation of the complexity of the hydrologic model, as measured by its Vapnik-Chernovenkis (VC) dimension. Further research is needed in this area.

  4. Predictions of localized plastic flow conditions in irradiated zircaloy using a unified phenomenological model

    International Nuclear Information System (INIS)

    Miller, A.K.

    1977-01-01

    A general-purpose constitutive model for the non-elastic deformation of metals and alloys has recently been developed. This model is aimed at improved analysis of high-temperature structures in general and light-water reactor cladding in particular. Accordingly, detailed work has been undertaken to apply the model to the in-reactor behavior of zircaloy, and to verify that the model does, in fact, simulate the deformation of zircaloy in a realistic manner. It is the purpose of this paper to present some of these results, especially as regards strain softening and localized plastic flow. The model is phenomenological in that it is formulated at the macroscopic level and thus predicts the interrelationship of macroscopic variables such as stress, strain rate, temperature, and history but the overall format of the model is based on the microscopic dislocation mechanisms underlying non-elastic deformation. The equations simulate a wide variety of phenomena such as transient and steady-state creep; short-time plasticity; cyclic hardening, softening, and saturation; static and dynamic recovery; dynamic strain aging effects; complex stress, strain rate, and temperature histories; and interactions of all of these. The effects of fluence, cold work, and post-irradiation strain rate have been examined analytically. For annealed material, with increasing fluence (1) the simulated yield strength increases (up to saturation), (2) the magnitude of the stress drop during strain softening increases, and (3) the strain at which the stress goes through a minimum increases. Prior cold work tends to suppress the simulated strain softening in irradiated material. Unirradiated, cold-worked material having a yield strength level equal to that of annealed, irradiated material does not show strain softening in the simulations. With increasing strain rate, the strain-softening portion of the stress-strain curve takes a larger amount of strain

  5. Quantifying predictive accuracy in survival models.

    Science.gov (United States)

    Lirette, Seth T; Aban, Inmaculada

    2017-12-01

    For time-to-event outcomes in medical research, survival models are the most appropriate to use. Unlike logistic regression models, quantifying the predictive accuracy of these models is not a trivial task. We present the classes of concordance (C) statistics and R 2 statistics often used to assess the predictive ability of these models. The discussion focuses on Harrell's C, Kent and O'Quigley's R 2 , and Royston and Sauerbrei's R 2 . We present similarities and differences between the statistics, discuss the software options from the most widely used statistical analysis packages, and give a practical example using the Worcester Heart Attack Study dataset.

  6. Predictive power of nuclear-mass models

    Directory of Open Access Journals (Sweden)

    Yu. A. Litvinov

    2013-12-01

    Full Text Available Ten different theoretical models are tested for their predictive power in the description of nuclear masses. Two sets of experimental masses are used for the test: the older set of 2003 and the newer one of 2011. The predictive power is studied in two regions of nuclei: the global region (Z, N ≥ 8 and the heavy-nuclei region (Z ≥ 82, N ≥ 126. No clear correlation is found between the predictive power of a model and the accuracy of its description of the masses.

  7. Return Predictability, Model Uncertainty, and Robust Investment

    DEFF Research Database (Denmark)

    Lukas, Manuel

    Stock return predictability is subject to great uncertainty. In this paper we use the model confidence set approach to quantify uncertainty about expected utility from investment, accounting for potential return predictability. For monthly US data and six representative return prediction models, we...... find that confidence sets are very wide, change significantly with the predictor variables, and frequently include expected utilities for which the investor prefers not to invest. The latter motivates a robust investment strategy maximizing the minimal element of the confidence set. The robust investor...... allocates a much lower share of wealth to stocks compared to a standard investor....

  8. Heat strain imposed by personal protective ensembles: quantitative analysis using a thermoregulation model

    Science.gov (United States)

    Xu, Xiaojiang; Gonzalez, Julio A.; Santee, William R.; Blanchard, Laurie A.; Hoyt, Reed W.

    2016-07-01

    The objective of this paper is to study the effects of personal protective equipment (PPE) and specific PPE layers, defined as thermal/evaporative resistances and the mass, on heat strain during physical activity. A stepwise thermal manikin testing and modeling approach was used to analyze a PPE ensemble with four layers: uniform, ballistic protection, chemical protective clothing, and mask and gloves. The PPE was tested on a thermal manikin, starting with the uniform, then adding an additional layer in each step. Wearing PPE increases the metabolic rates (dot{M}) , thus dot{M} were adjusted according to the mass of each of four configurations. A human thermoregulatory model was used to predict endurance time for each configuration at fixed dot{M} and at its mass adjusted dot{M} . Reductions in endurance time due to resistances, and due to mass, were separately determined using predicted results. Fractional contributions of PPE's thermal/evaporative resistances by layer show that the ballistic protection and the chemical protective clothing layers contribute about 20 %, respectively. Wearing the ballistic protection over the uniform reduced endurance time from 146 to 75 min, with 31 min of the decrement due to the additional resistances of the ballistic protection, and 40 min due to increased dot{M} associated with the additional mass. Effects of mass on heat strain are of a similar magnitude relative to effects of increased resistances. Reducing resistances and mass can both significantly alleviate heat strain.

  9. Spatial Economics Model Predicting Transport Volume

    Directory of Open Access Journals (Sweden)

    Lu Bo

    2016-10-01

    Full Text Available It is extremely important to predict the logistics requirements in a scientific and rational way. However, in recent years, the improvement effect on the prediction method is not very significant and the traditional statistical prediction method has the defects of low precision and poor interpretation of the prediction model, which cannot only guarantee the generalization ability of the prediction model theoretically, but also cannot explain the models effectively. Therefore, in combination with the theories of the spatial economics, industrial economics, and neo-classical economics, taking city of Zhuanghe as the research object, the study identifies the leading industry that can produce a large number of cargoes, and further predicts the static logistics generation of the Zhuanghe and hinterlands. By integrating various factors that can affect the regional logistics requirements, this study established a logistics requirements potential model from the aspect of spatial economic principles, and expanded the way of logistics requirements prediction from the single statistical principles to an new area of special and regional economics.

  10. Accuracy assessment of landslide prediction models

    International Nuclear Information System (INIS)

    Othman, A N; Mohd, W M N W; Noraini, S

    2014-01-01

    The increasing population and expansion of settlements over hilly areas has greatly increased the impact of natural disasters such as landslide. Therefore, it is important to developed models which could accurately predict landslide hazard zones. Over the years, various techniques and models have been developed to predict landslide hazard zones. The aim of this paper is to access the accuracy of landslide prediction models developed by the authors. The methodology involved the selection of study area, data acquisition, data processing and model development and also data analysis. The development of these models are based on nine different landslide inducing parameters i.e. slope, land use, lithology, soil properties, geomorphology, flow accumulation, aspect, proximity to river and proximity to road. Rank sum, rating, pairwise comparison and AHP techniques are used to determine the weights for each of the parameters used. Four (4) different models which consider different parameter combinations are developed by the authors. Results obtained are compared to landslide history and accuracies for Model 1, Model 2, Model 3 and Model 4 are 66.7, 66.7%, 60% and 22.9% respectively. From the results, rank sum, rating and pairwise comparison can be useful techniques to predict landslide hazard zones

  11. Modeling the Stress Strain Behavior of Woven Ceramic Matrix Composites

    Science.gov (United States)

    Morscher, Gregory N.

    2006-01-01

    Woven SiC fiber reinforced SiC matrix composites represent one of the most mature composite systems to date. Future components fabricated out of these woven ceramic matrix composites are expected to vary in shape, curvature, architecture, and thickness. The design of future components using woven ceramic matrix composites necessitates a modeling approach that can account for these variations which are physically controlled by local constituent contents and architecture. Research over the years supported primarily by NASA Glenn Research Center has led to the development of simple mechanistic-based models that can describe the entire stress-strain curve for composite systems fabricated with chemical vapor infiltrated matrices and melt-infiltrated matrices for a wide range of constituent content and architecture. Several examples will be presented that demonstrate the approach to modeling which incorporates a thorough understanding of the stress-dependent matrix cracking properties of the composite system.

  12. Psychosocial job strain and productivity in human service workers: A test of the demand-control-support model.

    NARCIS (Netherlands)

    Dollard, M.F.; Winefield, H.R.; Winefield, A.H.; Jonge, J. de

    2000-01-01

    The aim of the study was to test the main and interactive effects of the key dimensions of the demand-control-support model in predicting levels of strain (specifically emotional exhaustion, depersonalization and job dissatisfaction) and feelings of productivity and competency (personal

  13. Left ventricular global longitudinal strain predicts major adverse cardiac events and all-cause mortality in heart transplant patients.

    Science.gov (United States)

    Clemmensen, Tor Skibsted; Eiskjær, Hans; Løgstrup, Brian Bridal; Ilkjær, Lars Bo; Poulsen, Steen Hvitfeldt

    2017-05-01

    Left ventricular global longitudinal strain (LVGLS) is a robust longitudinal myocardial deformation marker that is strongly affected by cardiac allograft vasculopathy (CAV), microvascular dysfunction, and acute cellular rejection (ACR). We evaluated graft deformation for risk stratification in long-term heart transplant (HTx) patients. The study included 196 patients who underwent HTx between 2011 and 2013. Patients underwent comprehensive echocardiography and coronary angiography. Previous rejection burden was assessed, and ACR grades were calculated. Patients were prospectively followed until February 24, 2016. Major adverse cardiac events (MACE), including coronary event, heart failure, treated rejection, and cardiovascular death, and all-cause mortality were recorded. During follow-up, 57 patients experienced MACE. Median follow-up was 1,035 (interquartile range [IQR] 856-1,124) days. Median time to first event was 534 (IQR 276-763) days. LVGLS was a strong predictor of MACE (hazard ratio [HR] 4.9, 95% confidence interval [CI] 2.7-8.9, p transplantation. Measurement of LVGLS strongly predicts MACE and mortality in long-term HTx patients. Predictive ability was seen in patients with and without CAV. A combined model of left ventricular systolic deformation by LVGLS and diastolic graft performance by LVFP was a stronger model for prediction of MACE and all-cause mortality. Copyright © 2017 International Society for Heart and Lung Transplantation. Published by Elsevier Inc. All rights reserved.

  14. Succinate overproduction: A case study of computational strain design using a comprehensive Escherichia coli kinetic model

    Directory of Open Access Journals (Sweden)

    Ali eKhodayari

    2015-01-01

    Full Text Available Computational strain design prediction accuracy has been the focus for many recent efforts through the selective integration of kinetic information into metabolic models. In general, kinetic model prediction quality is determined by the range and scope of genetic and/or environmental perturbations used during parameterization. In this effort, we apply the k-OptForce procedure on a kinetic model of E. coli core metabolism constructed using the Ensemble Modeling (EM method and parameterized using multiple mutant strains data under aerobic respiration with glucose as the carbon source. Minimal interventions are identified that improve succinate yield under both aerobic and anaerobic conditions to test the fidelity of model predictions under both genetic and environmental perturbations. Under aerobic condition, k-OptForce identifies interventions that match existing experimental strategies pointing at a number of unexplored flux redirections such as routing glyoxylate flux through the glycerate metabolism to improve succinate yield. Many of the identified interventions rely on the kinetic descriptions and would not be discoverable by a purely stoichiometric description. In contrast, under fermentative (anaerobic conditions, k-OptForce fails to identify key interventions including up-regulation of anaplerotic reactions and elimination of competitive fermentative products. This is due to the fact that the pathways activated under anaerobic conditions were not properly parameterized as only aerobic flux data were used in the model construction. This study shed light on the importance of condition-specific model parameterization and provides insight onto how to augment kinetic models so as to correctly respond to multiple environmental perturbations.

  15. Multi-scale Modeling of the Impact Response of a Strain Rate Sensitive High-Manganese Austenitic Steel

    Directory of Open Access Journals (Sweden)

    Orkun eÖnal

    2014-09-01

    Full Text Available A multi-scale modeling approach was applied to predict the impact response of a strain rate sensitive high-manganese austenitic steel. The roles of texture, geometry and strain rate sensitivity were successfully taken into account all at once by coupling crystal plasticity and finite element (FE analysis. Specifically, crystal plasticity was utilized to obtain the multi-axial flow rule at different strain rates based on the experimental deformation response under uniaxial tensile loading. The equivalent stress – equivalent strain response was then incorporated into the FE model for the sake of a more representative hardening rule under impact loading. The current results demonstrate that reliable predictions can be obtained by proper coupling of crystal plasticity and FE analysis even if the experimental flow rule of the material is acquired under uniaxial loading and at moderate strain rates that are significantly slower than those attained during impact loading. Furthermore, the current findings also demonstrate the need for an experiment-based multi-scale modeling approach for the sake of reliable predictions of the impact response.

  16. Posterior predictive checking of multiple imputation models.

    Science.gov (United States)

    Nguyen, Cattram D; Lee, Katherine J; Carlin, John B

    2015-07-01

    Multiple imputation is gaining popularity as a strategy for handling missing data, but there is a scarcity of tools for checking imputation models, a critical step in model fitting. Posterior predictive checking (PPC) has been recommended as an imputation diagnostic. PPC involves simulating "replicated" data from the posterior predictive distribution of the model under scrutiny. Model fit is assessed by examining whether the analysis from the observed data appears typical of results obtained from the replicates produced by the model. A proposed diagnostic measure is the posterior predictive "p-value", an extreme value of which (i.e., a value close to 0 or 1) suggests a misfit between the model and the data. The aim of this study was to evaluate the performance of the posterior predictive p-value as an imputation diagnostic. Using simulation methods, we deliberately misspecified imputation models to determine whether posterior predictive p-values were effective in identifying these problems. When estimating the regression parameter of interest, we found that more extreme p-values were associated with poorer imputation model performance, although the results highlighted that traditional thresholds for classical p-values do not apply in this context. A shortcoming of the PPC method was its reduced ability to detect misspecified models with increasing amounts of missing data. Despite the limitations of posterior predictive p-values, they appear to have a valuable place in the imputer's toolkit. In addition to automated checking using p-values, we recommend imputers perform graphical checks and examine other summaries of the test quantity distribution. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  17. The Finite Strain Johnson Cook Plasticity and Damage Constitutive Model in ALEGRA.

    Energy Technology Data Exchange (ETDEWEB)

    Sanchez, Jason James [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

    2018-02-01

    A finite strain formulation of the Johnson Cook plasticity and damage model and it's numerical implementation into the ALEGRA code is presented. The goal of this work is to improve the predictive material failure capability of the Johnson Cook model. The new implementation consists of a coupling of damage and the stored elastic energy as well as the minimum failure strain criteria for spall included in the original model development. This effort establishes the necessary foundation for a thermodynamically consistent and complete continuum solid material model, for which all intensive properties derive from a common energy. The motivation for developing such a model is to improve upon ALEGRA's present combined model framework. Several applications of the new Johnson Cook implementation are presented. Deformation driven loading paths demonstrate the basic features of the new model formulation. Use of the model produces good comparisons with experimental Taylor impact data. Localized deformation leading to fragmentation is produced for expanding ring and exploding cylinder applications.

  18. Predicting Protein Secondary Structure with Markov Models

    DEFF Research Database (Denmark)

    Fischer, Paul; Larsen, Simon; Thomsen, Claus

    2004-01-01

    we are considering here, is to predict the secondary structure from the primary one. To this end we train a Markov model on training data and then use it to classify parts of unknown protein sequences as sheets, helices or coils. We show how to exploit the directional information contained...... in the Markov model for this task. Classifications that are purely based on statistical models might not always be biologically meaningful. We present combinatorial methods to incorporate biological background knowledge to enhance the prediction performance....

  19. Energy approach to brittle fracture in strain-gradient modelling

    Science.gov (United States)

    Placidi, Luca; Barchiesi, Emilio

    2018-02-01

    In this paper, we exploit some results in the theory of irreversible phenomena to address the study of quasi-static brittle fracture propagation in a two-dimensional isotropic continuum. The elastic strain energy density of the body has been assumed to be geometrically nonlinear and to depend on the strain gradient. Such generalized continua often arise in the description of microstructured media. These materials possess an intrinsic length scale, which determines the size of internal boundary layers. In particular, the non-locality conferred by this internal length scale avoids the concentration of deformations, which is usually observed when dealing with local models and which leads to mesh dependency. A scalar Lagrangian damage field, ranging from zero to one, is introduced to describe the internal state of structural degradation of the material. Standard Lamé and second-gradient elastic coefficients are all assumed to decrease as damage increases and to be locally zero if the value attained by damage is one. This last situation is associated with crack formation and/or propagation. Numerical solutions of the model are provided in the case of an obliquely notched rectangular specimen subjected to monotonous tensile and shear loading tests, and brittle fracture propagation is discussed.

  20. Energy based prediction models for building acoustics

    DEFF Research Database (Denmark)

    Brunskog, Jonas

    2012-01-01

    In order to reach robust and simplified yet accurate prediction models, energy based principle are commonly used in many fields of acoustics, especially in building acoustics. This includes simple energy flow models, the framework of statistical energy analysis (SEA) as well as more elaborated...... principles as, e.g., wave intensity analysis (WIA). The European standards for building acoustic predictions, the EN 12354 series, are based on energy flow and SEA principles. In the present paper, different energy based prediction models are discussed and critically reviewed. Special attention is placed...... on underlying basic assumptions, such as diffuse fields, high modal overlap, resonant field being dominant, etc., and the consequences of these in terms of limitations in the theory and in the practical use of the models....

  1. Comparative Study of Bancruptcy Prediction Models

    Directory of Open Access Journals (Sweden)

    Isye Arieshanti

    2013-09-01

    Full Text Available Early indication of bancruptcy is important for a company. If companies aware of  potency of their bancruptcy, they can take a preventive action to anticipate the bancruptcy. In order to detect the potency of a bancruptcy, a company can utilize a a model of bancruptcy prediction. The prediction model can be built using a machine learning methods. However, the choice of machine learning methods should be performed carefully. Because the suitability of a model depends on the problem specifically. Therefore, in this paper we perform a comparative study of several machine leaning methods for bancruptcy prediction. According to the comparative study, the performance of several models that based on machine learning methods (k-NN, fuzzy k-NN, SVM, Bagging Nearest Neighbour SVM, Multilayer Perceptron(MLP, Hybrid of MLP + Multiple Linear Regression, it can be showed that fuzzy k-NN method achieve the best performance with accuracy 77.5%

  2. Modeling fracture in the context of a strain-limiting theory of elasticity: a single anti-plane shear crack

    KAUST Repository

    Rajagopal, K. R.

    2011-01-06

    This paper is the first part of an extended program to develop a theory of fracture in the context of strain-limiting theories of elasticity. This program exploits a novel approach to modeling the mechanical response of elastic, that is non-dissipative, materials through implicit constitutive relations. The particular class of models studied here can also be viewed as arising from an explicit theory in which the displacement gradient is specified to be a nonlinear function of stress. This modeling construct generalizes the classical Cauchy and Green theories of elasticity which are included as special cases. It was conjectured that special forms of these implicit theories that limit strains to physically realistic maximum levels even for arbitrarily large stresses would be ideal for modeling fracture by offering a modeling paradigm that avoids the crack-tip strain singularities characteristic of classical fracture theories. The simplest fracture setting in which to explore this conjecture is anti-plane shear. It is demonstrated herein that for a specific choice of strain-limiting elasticity theory, crack-tip strains do indeed remain bounded. Moreover, the theory predicts a bounded stress field in the neighborhood of a crack-tip and a cusp-shaped opening displacement. The results confirm the conjecture that use of a strain limiting explicit theory in which the displacement gradient is given as a function of stress for modeling the bulk constitutive behavior obviates the necessity of introducing ad hoc modeling constructs such as crack-tip cohesive or process zones in order to correct the unphysical stress and strain singularities predicted by classical linear elastic fracture mechanics. © 2011 Springer Science+Business Media B.V.

  3. Prediction Models for Dynamic Demand Response

    Energy Technology Data Exchange (ETDEWEB)

    Aman, Saima; Frincu, Marc; Chelmis, Charalampos; Noor, Muhammad; Simmhan, Yogesh; Prasanna, Viktor K.

    2015-11-02

    As Smart Grids move closer to dynamic curtailment programs, Demand Response (DR) events will become necessary not only on fixed time intervals and weekdays predetermined by static policies, but also during changing decision periods and weekends to react to real-time demand signals. Unique challenges arise in this context vis-a-vis demand prediction and curtailment estimation and the transformation of such tasks into an automated, efficient dynamic demand response (D2R) process. While existing work has concentrated on increasing the accuracy of prediction models for DR, there is a lack of studies for prediction models for D2R, which we address in this paper. Our first contribution is the formal definition of D2R, and the description of its challenges and requirements. Our second contribution is a feasibility analysis of very-short-term prediction of electricity consumption for D2R over a diverse, large-scale dataset that includes both small residential customers and large buildings. Our third, and major contribution is a set of insights into the predictability of electricity consumption in the context of D2R. Specifically, we focus on prediction models that can operate at a very small data granularity (here 15-min intervals), for both weekdays and weekends - all conditions that characterize scenarios for D2R. We find that short-term time series and simple averaging models used by Independent Service Operators and utilities achieve superior prediction accuracy. We also observe that workdays are more predictable than weekends and holiday. Also, smaller customers have large variation in consumption and are less predictable than larger buildings. Key implications of our findings are that better models are required for small customers and for non-workdays, both of which are critical for D2R. Also, prediction models require just few days’ worth of data indicating that small amounts of

  4. Injection-Molded Long-Fiber Thermoplastic Composites: From Process Modeling to Prediction of Mechanical Properties

    Energy Technology Data Exchange (ETDEWEB)

    Nguyen, Ba Nghiep; Kunc, Vlastimil; Jin, Xiaoshi; Tucker III, Charles L.; Costa, Franco

    2013-12-18

    This article illustrates the predictive capabilities for long-fiber thermoplastic (LFT) composites that first simulate the injection molding of LFT structures by Autodesk® Simulation Moldflow® Insight (ASMI) to accurately predict fiber orientation and length distributions in these structures. After validating fiber orientation and length predictions against the experimental data, the predicted results are used by ASMI to compute distributions of elastic properties in the molded structures. In addition, local stress-strain responses and damage accumulation under tensile loading are predicted by an elastic-plastic damage model of EMTA-NLA, a nonlinear analysis tool implemented in ABAQUS® via user-subroutines using an incremental Eshelby-Mori-Tanaka approach. Predicted stress-strain responses up to failure and damage accumulations are compared to the experimental results to validate the model.

  5. Are animal models predictive for humans?

    Directory of Open Access Journals (Sweden)

    Greek Ray

    2009-01-01

    Full Text Available Abstract It is one of the central aims of the philosophy of science to elucidate the meanings of scientific terms and also to think critically about their application. The focus of this essay is the scientific term predict and whether there is credible evidence that animal models, especially in toxicology and pathophysiology, can be used to predict human outcomes. Whether animals can be used to predict human response to drugs and other chemicals is apparently a contentious issue. However, when one empirically analyzes animal models using scientific tools they fall far short of being able to predict human responses. This is not surprising considering what we have learned from fields such evolutionary and developmental biology, gene regulation and expression, epigenetics, complexity theory, and comparative genomics.

  6. Evaluation of CASP8 model quality predictions

    KAUST Repository

    Cozzetto, Domenico

    2009-01-01

    The model quality assessment problem consists in the a priori estimation of the overall and per-residue accuracy of protein structure predictions. Over the past years, a number of methods have been developed to address this issue and CASP established a prediction category to evaluate their performance in 2006. In 2008 the experiment was repeated and its results are reported here. Participants were invited to infer the correctness of the protein models submitted by the registered automatic servers. Estimates could apply to both whole models and individual amino acids. Groups involved in the tertiary structure prediction categories were also asked to assign local error estimates to each predicted residue in their own models and their results are also discussed here. The correlation between the predicted and observed correctness measures was the basis of the assessment of the results. We observe that consensus-based methods still perform significantly better than those accepting single models, similarly to what was concluded in the previous edition of the experiment. © 2009 WILEY-LISS, INC.

  7. Optimal decolorization and kinetic modeling of synthetic dyes by Pseudomonas strains.

    Science.gov (United States)

    Yu, J; Wang, X; Yue, P L

    2001-10-01

    Pseudomonas spp were isolated from an anaerobic-aerobic dyeing house wastewater treatment facility as the most active azo-dye degraders. Decolorization of azo dyes and non-azo dyes including anthraquinone, metal complex and indigo was compared with individual strains and a bacterial consortium consisting of the individual strain and municipal sludge (50 50wt). The consortium showed a significant improvement on decolorization of two recalcitrant non-azo dyes, but little effect on the dyes that the individual strains could degrade to a great or moderate extent. Decolorization of Acid violet 7 (monoazo) by a Pseudomonas strain GM3 was studied in detail under various conditions. The optimum decolorization activity was observed in a narrow pH range (7-8), a narrow temperature range (35-40 degrees C), and at the presence of organic and ammonium nitrogen. Nitrate had a severe inhibitory effect on azo dye decolorization: 10 mg/L led to 50% drop in decolorization activity and 1000 mg/L to complete activity depression. A kinetic model is established giving the dependence of decolorization rate on cell mass concentration (first-order) and dye concentration (half order). The rate increased with temperature from 10 to 35 C, which can be predicted by Arrhenius equation with the activation energy of 16.87 kcal/mol and the frequency factor of 1.49 x 10(11) (mg L)1/2/g DCM min.

  8. Model predictive controller design of hydrocracker reactors

    OpenAIRE

    GÖKÇE, Dila

    2014-01-01

    This study summarizes the design of a Model Predictive Controller (MPC) in Tüpraş, İzmit Refinery Hydrocracker Unit Reactors. Hydrocracking process, in which heavy vacuum gasoil is converted into lighter and valuable products at high temperature and pressure is described briefly. Controller design description, identification and modeling studies are examined and the model variables are presented. WABT (Weighted Average Bed Temperature) equalization and conversion increase are simulate...

  9. Prediction of dissolution profiles by non-destructive near infrared spectroscopy in tablets subjected to different levels of strain.

    Science.gov (United States)

    Hernandez, Eduardo; Pawar, Pallavi; Keyvan, Golshid; Wang, Yifan; Velez, Natasha; Callegari, Gerardo; Cuitino, Alberto; Michniak-Kohn, Bozena; Muzzio, Fernando J; Romañach, Rodolfo J

    2016-01-05

    This study describes how the strain on formulation components affects dissolution and how near infrared spectroscopy can be used to predict dissolution. Strain (exposure to shear stress) applied during powder mixing affects the interaction between formulation components. Particles experience shear strain when they move relative to each other in a process affecting the properties of the final product. This stress affects the dissolution of oral solid dosages forms. However, dissolution testing destroys the entire tablet, making it impossible to further evaluate tablet properties when an out of specification result is obtained. Thus, a nondestructive technique such as near infrared spectroscopy is desirable to predict dissolution. The aim of this study was to predict dissolution on tablets with different levels of strain (shear) using near infrared spectroscopy in combination with multivariate data analysis. Shear was induced using a modified Couette cell on the powder mixture and tablets from these mixtures were produced using a tablet press emulator. Tablets produced with different strain levels were measured using near infrared spectroscopy. Spectra were obtained in diffuse reflectance mode and pretreated with baseline correction to maintain the physical and chemical information of the tablets. Dissolution profiles were obtained using USP Apparatus 2 as a reference method. Principal component analysis was used to study the sources of variation in the spectra obtained. Partial least squares 2 was used to predict dissolution on tablets with different levels of strain.

  10. Multi-Model Ensemble Wake Vortex Prediction

    Science.gov (United States)

    Koerner, Stephan; Holzaepfel, Frank; Ahmad, Nash'at N.

    2015-01-01

    Several multi-model ensemble methods are investigated for predicting wake vortex transport and decay. This study is a joint effort between National Aeronautics and Space Administration and Deutsches Zentrum fuer Luft- und Raumfahrt to develop a multi-model ensemble capability using their wake models. An overview of different multi-model ensemble methods and their feasibility for wake applications is presented. The methods include Reliability Ensemble Averaging, Bayesian Model Averaging, and Monte Carlo Simulations. The methodologies are evaluated using data from wake vortex field experiments.

  11. An over-nonlocal implicit gradient-enhanced damage-plastic model for trabecular bone under large compressive strains.

    Science.gov (United States)

    Hosseini, Hadi S; Horák, Martin; Zysset, Philippe K; Jirásek, Milan

    2015-11-01

    Investigation of trabecular bone strength and compaction is important for fracture risk prediction. At 1-2% compressive strain, trabecular bone undergoes strain softening, which may lead to numerical instabilities and mesh dependency in classical local damage-plastic models. The aim of this work is to improve our continuum damage-plastic model of bone by reducing the influence of finite element mesh size under large compression. This spurious numerical phenomenon may be circumvented by incorporating the nonlocal effect of cumulated plastic strain into the constitutive law. To this end, an over-nonlocal implicit gradient model of bone is developed and implemented into the finite element software ABAQUS using a user element subroutine. The ability of the model to detect the regions of bone failure is tested against experimental stepwise loading data of 16 human trabecular bone biopsies. The numerical outcomes of the nonlocal model revealed reduction of finite element mesh dependency compared with the local damage-plastic model. Furthermore, it helped reduce the computational costs of large-strain compression simulations. To the best of our knowledge, the proposed model is the first to predict the failure and densification of trabecular bone up to large compression independently of finite element mesh size. The current development enables the analysis of trabecular bone compaction as in osteoporotic fractures and implant migration, where large deformation of bone plays a key role. Copyright © 2015 John Wiley & Sons, Ltd.

  12. Modeling actuation forces and strains in nastic structures

    Science.gov (United States)

    Matthews, Luke A.; Giurgiutiu, Victor

    2006-03-01

    Nastic structures are capable of three dimensional shape change using biological principles borrowed from plant motion. The plant motor cells increase or decrease in size through a change in osmotic pressure. When nonuniform cell swelling occurs, it causes the plant tissue to warp and change shape, resulting it net movement, known as nastic motion, which is the same phenomena that causes plants to angle their broad leaf and flower surfaces to face light sources. The nastic structures considered in this paper are composed of a bilayer of microactuator arrays with a fluid reservoir in between the two layers. The actuators are housed in a thin plate and expand when water from the fluid reservoir is pumped into the actuation chamber through a phospholipid bilayer with embedded active transport proteins, which move the water from the low pressure fluid reservoir into a high pressure actuation chamber. Increasing water pressure inside the actuator causes lateral expansion and axial bulging, and the non-uniform net volume change of actuators throughout the nastic structure results in twisting or bending shape change. Modifying the actuation displacement allows controlled volume change. This paper presents an analytical model of the driving and blocking forces involved in actuation, as well as stress and strain that occurs due to the pressure changes. Actuation is driven by increasing osmotic pressure, and blocking forces are taken into consideration to plan actuator response so that outside forces do not counteract the displacement of actuation. Nastic structures are designed with use in unmanned aerial vehicles in mind, so blocking forces are modeled to be similar to in-flight conditions. Stress in the system is modeled so that any residual strain or lasting deformation can be determined, as well as a lifespan before failure from repeated actuation. The long-term aim of our work is to determine the power and energy efficiency of nastic structures actuation mechanism.

  13. Thermodynamic modeling of activity coefficient and prediction of solubility: Part 1. Predictive models.

    Science.gov (United States)

    Mirmehrabi, Mahmoud; Rohani, Sohrab; Perry, Luisa

    2006-04-01

    A new activity coefficient model was developed from excess Gibbs free energy in the form G(ex) = cA(a) x(1)(b)...x(n)(b). The constants of the proposed model were considered to be function of solute and solvent dielectric constants, Hildebrand solubility parameters and specific volumes of solute and solvent molecules. The proposed model obeys the Gibbs-Duhem condition for activity coefficient models. To generalize the model and make it as a purely predictive model without any adjustable parameters, its constants were found using the experimental activity coefficient and physical properties of 20 vapor-liquid systems. The predictive capability of the proposed model was tested by calculating the activity coefficients of 41 binary vapor-liquid equilibrium systems and showed good agreement with the experimental data in comparison with two other predictive models, the UNIFAC and Hildebrand models. The only data used for the prediction of activity coefficients, were dielectric constants, Hildebrand solubility parameters, and specific volumes of the solute and solvent molecules. Furthermore, the proposed model was used to predict the activity coefficient of an organic compound, stearic acid, whose physical properties were available in methanol and 2-butanone. The predicted activity coefficient along with the thermal properties of the stearic acid were used to calculate the solubility of stearic acid in these two solvents and resulted in a better agreement with the experimental data compared to the UNIFAC and Hildebrand predictive models.

  14. PREDICTIVE CAPACITY OF ARCH FAMILY MODELS

    Directory of Open Access Journals (Sweden)

    Raphael Silveira Amaro

    2016-03-01

    Full Text Available In the last decades, a remarkable number of models, variants from the Autoregressive Conditional Heteroscedastic family, have been developed and empirically tested, making extremely complex the process of choosing a particular model. This research aim to compare the predictive capacity, using the Model Confidence Set procedure, than five conditional heteroskedasticity models, considering eight different statistical probability distributions. The financial series which were used refers to the log-return series of the Bovespa index and the Dow Jones Industrial Index in the period between 27 October 2008 and 30 December 2014. The empirical evidences showed that, in general, competing models have a great homogeneity to make predictions, either for a stock market of a developed country or for a stock market of a developing country. An equivalent result can be inferred for the statistical probability distributions that were used.

  15. Left Ventricular global longitudinal strain predicts heart failure readmission in acute decompensated heart failure.

    Science.gov (United States)

    Romano, Simone; Mansour, Ibrahim N; Kansal, Mayank; Gheith, Hana; Dowdy, Zachary; Dickens, Carolyn A; Buto-Colletti, Cassandra; Chae, June M; Saleh, Hussam H; Stamos, Thomas D

    2017-03-15

    The goal of this study was to determine if left ventricular (LV) global longitudinal strain (GLS) predicts heart failure (HF) readmission in patients with acute decompensated heart failure. Two hundred ninety one patients were enrolled at the time of admission for acute decompensated heart failure between January 2011 and September 2013. Left ventricle global longitudinal strain (LV GLS) by velocity vector imaging averaged from 2, 3 and 4-chamber views could be assessed in 204 out of 291 (70%) patients. Mean age was 63.8 ± 15.2 years, 42% of the patients were males and 78% were African American or Hispanic. Patients were followed until the first HF hospital readmission up to 44 months. Patients were grouped into quartiles on the basis of LV GLS. Kaplan-Meier curves showed significantly higher readmission rates in patients with worse LV GLS (log-rank p heart disease, dementia, New York Heart Association class, LV ejection fraction, use of angiotensin converting enzyme inhibitors or angiotensin receptor blockers, systolic and diastolic blood pressure on admission and sodium level on admission, worse LV GLS was the strongest predictor of recurrent HF readmission (p heart failure with a higher risk of readmission in case of progressive worsening of LV GLS, independent of the ejection fraction.

  16. Prediction of Local Ultimate Strain and Toughness of Trabecular Bone Tissue by Raman Material Composition Analysis

    Directory of Open Access Journals (Sweden)

    Roberto Carretta

    2015-01-01

    Full Text Available Clinical studies indicate that bone mineral density correlates with fracture risk at the population level but does not correlate with individual fracture risk well. Current research aims to better understand the failure mechanism of bone and to identify key determinants of bone quality, thus improving fracture risk prediction. To get a better understanding of bone strength, it is important to analyze tissue-level properties not influenced by macro- or microarchitectural factors. The aim of this pilot study was to identify whether and to what extent material properties are correlated with mechanical properties at the tissue level. The influence of macro- or microarchitectural factors was excluded by testing individual trabeculae. Previously reported data of mechanical parameters measured in single trabeculae under tension and bending and its compositional properties measured by Raman spectroscopy was evaluated. Linear and multivariate regressions show that bone matrix quality but not quantity was significantly and independently correlated with the tissue-level ultimate strain and postyield work (r=0.65–0.94. Principal component analysis extracted three independent components explaining 86% of the total variance, representing elastic, yield, and ultimate components according to the included mechanical parameters. Some matrix parameters were both included in the ultimate component, indicating that the variation in ultimate strain and postyield work could be largely explained by Raman-derived compositional parameters.

  17. Prediction of local ultimate strain and toughness of trabecular bone tissue by Raman material composition analysis.

    Science.gov (United States)

    Carretta, Roberto; Stüssi, Edgar; Müller, Ralph; Lorenzetti, Silvio

    2015-01-01

    Clinical studies indicate that bone mineral density correlates with fracture risk at the population level but does not correlate with individual fracture risk well. Current research aims to better understand the failure mechanism of bone and to identify key determinants of bone quality, thus improving fracture risk prediction. To get a better understanding of bone strength, it is important to analyze tissue-level properties not influenced by macro- or microarchitectural factors. The aim of this pilot study was to identify whether and to what extent material properties are correlated with mechanical properties at the tissue level. The influence of macro- or microarchitectural factors was excluded by testing individual trabeculae. Previously reported data of mechanical parameters measured in single trabeculae under tension and bending and its compositional properties measured by Raman spectroscopy was evaluated. Linear and multivariate regressions show that bone matrix quality but not quantity was significantly and independently correlated with the tissue-level ultimate strain and postyield work (r = 0.65-0.94). Principal component analysis extracted three independent components explaining 86% of the total variance, representing elastic, yield, and ultimate components according to the included mechanical parameters. Some matrix parameters were both included in the ultimate component, indicating that the variation in ultimate strain and postyield work could be largely explained by Raman-derived compositional parameters.

  18. A revised prediction model for natural conception.

    Science.gov (United States)

    Bensdorp, Alexandra J; van der Steeg, Jan Willem; Steures, Pieternel; Habbema, J Dik F; Hompes, Peter G A; Bossuyt, Patrick M M; van der Veen, Fulco; Mol, Ben W J; Eijkemans, Marinus J C

    2017-06-01

    One of the aims in reproductive medicine is to differentiate between couples that have favourable chances of conceiving naturally and those that do not. Since the development of the prediction model of Hunault, characteristics of the subfertile population have changed. The objective of this analysis was to assess whether additional predictors can refine the Hunault model and extend its applicability. Consecutive subfertile couples with unexplained and mild male subfertility presenting in fertility clinics were asked to participate in a prospective cohort study. We constructed a multivariable prediction model with the predictors from the Hunault model and new potential predictors. The primary outcome, natural conception leading to an ongoing pregnancy, was observed in 1053 women of the 5184 included couples (20%). All predictors of the Hunault model were selected into the revised model plus an additional seven (woman's body mass index, cycle length, basal FSH levels, tubal status,history of previous pregnancies in the current relationship (ongoing pregnancies after natural conception, fertility treatment or miscarriages), semen volume, and semen morphology. Predictions from the revised model seem to concur better with observed pregnancy rates compared with the Hunault model; c-statistic of 0.71 (95% CI 0.69 to 0.73) compared with 0.59 (95% CI 0.57 to 0.61). Copyright © 2017. Published by Elsevier Ltd.

  19. Soil Stress-Strain Behavior: Measurement, Modeling and Analysis

    CERN Document Server

    Ling, Hoe I; Leshchinsky, Dov; Koseki, Junichi; A Collection of Papers of the Geotechnical Symposium in Rome

    2007-01-01

    This book is an outgrowth of the proceedings for the Geotechnical Symposium in Roma, which was held on March 16 and 17, 2006 in Rome, Italy. The Symposium was organized to celebrate the 60th birthday of Prof. Tatsuoka as well as honoring his research achievement. The publications are focused on the recent developments in the stress-strain behavior of geomaterials, with an emphasis on laboratory measurements, soil constitutive modeling and behavior of soil structures (such as reinforced soils, piles and slopes). The latest advancement in the field, such as the rate effect and dynamic behavior of both clay and sand, behavior of modified soils and soil mixtures, and soil liquefaction are addressed. A special keynote paper by Prof. Tatsuoka is included with three other keynote papers (presented by Prof. Lo Presti, Prof. Di Benedetto, and Prof. Shibuya).

  20. Modelling the predictive performance of credit scoring

    Directory of Open Access Journals (Sweden)

    Shi-Wei Shen

    2013-07-01

    Research purpose: The purpose of this empirical paper was to examine the predictive performance of credit scoring systems in Taiwan. Motivation for the study: Corporate lending remains a major business line for financial institutions. However, in light of the recent global financial crises, it has become extremely important for financial institutions to implement rigorous means of assessing clients seeking access to credit facilities. Research design, approach and method: Using a data sample of 10 349 observations drawn between 1992 and 2010, logistic regression models were utilised to examine the predictive performance of credit scoring systems. Main findings: A test of Goodness of fit demonstrated that credit scoring models that incorporated the Taiwan Corporate Credit Risk Index (TCRI, micro- and also macroeconomic variables possessed greater predictive power. This suggests that macroeconomic variables do have explanatory power for default credit risk. Practical/managerial implications: The originality in the study was that three models were developed to predict corporate firms’ defaults based on different microeconomic and macroeconomic factors such as the TCRI, asset growth rates, stock index and gross domestic product. Contribution/value-add: The study utilises different goodness of fits and receiver operator characteristics during the examination of the robustness of the predictive power of these factors.

  1. Modelling language evolution: Examples and predictions

    Science.gov (United States)

    Gong, Tao; Shuai, Lan; Zhang, Menghan

    2014-06-01

    We survey recent computer modelling research of language evolution, focusing on a rule-based model simulating the lexicon-syntax coevolution and an equation-based model quantifying the language competition dynamics. We discuss four predictions of these models: (a) correlation between domain-general abilities (e.g. sequential learning) and language-specific mechanisms (e.g. word order processing); (b) coevolution of language and relevant competences (e.g. joint attention); (c) effects of cultural transmission and social structure on linguistic understandability; and (d) commonalities between linguistic, biological, and physical phenomena. All these contribute significantly to our understanding of the evolutions of language structures, individual learning mechanisms, and relevant biological and socio-cultural factors. We conclude the survey by highlighting three future directions of modelling studies of language evolution: (a) adopting experimental approaches for model evaluation; (b) consolidating empirical foundations of models; and (c) multi-disciplinary collaboration among modelling, linguistics, and other relevant disciplines.

  2. Model Predictive Control of Sewer Networks

    DEFF Research Database (Denmark)

    Pedersen, Einar B.; Herbertsson, Hannes R.; Niemann, Henrik

    2016-01-01

    The developments in solutions for management of urban drainage are of vital importance, as the amount of sewer water from urban areas continues to increase due to the increase of the world’s population and the change in the climate conditions. How a sewer network is structured, monitored and cont...... benchmark model. Due to the inherent constraints the applied approach is based on Model Predictive Control....... and controlled have thus become essential factors for efficient performance of waste water treatment plants. This paper examines methods for simplified modelling and controlling a sewer network. A practical approach to the problem is used by analysing simplified design model, which is based on the Barcelona...

  3. Bayesian Predictive Models for Rayleigh Wind Speed

    DEFF Research Database (Denmark)

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

    2017-01-01

    predictive model of the wind speed aggregates the non-homogeneous distributions into a single continuous distribution. Therefore, the result is able to capture the variation among the probability distributions of the wind speeds at the turbines’ locations in a wind farm. More specifically, instead of using...... a wind speed distribution whose parameters are known or estimated, the parameters are considered as random whose variations are according to probability distributions. The Bayesian predictive model for a Rayleigh which only has a single model scale parameter has been proposed. Also closed-form posterior......One of the major challenges with the increase in wind power generation is the uncertain nature of wind speed. So far the uncertainty about wind speed has been presented through probability distributions. Also the existing models that consider the uncertainty of the wind speed primarily view...

  4. Comparison of two ordinal prediction models

    DEFF Research Database (Denmark)

    Kattan, Michael W; Gerds, Thomas A

    2015-01-01

    system (i.e. old or new), such as the level of evidence for one or more factors included in the system or the general opinions of expert clinicians. However, given the major objective of estimating prognosis on an ordinal scale, we argue that the rival staging system candidates should be compared...... on their ability to predict outcome. We sought to outline an algorithm that would compare two rival ordinal systems on their predictive ability. RESULTS: We devised an algorithm based largely on the concordance index, which is appropriate for comparing two models in their ability to rank observations. We...... demonstrate our algorithm with a prostate cancer staging system example. CONCLUSION: We have provided an algorithm for selecting the preferred staging system based on prognostic accuracy. It appears to be useful for the purpose of selecting between two ordinal prediction models....

  5. Genetic organisation, mobility and predicted functions of genes on integrated, mobile genetic elements in sequenced strains of Clostridium difficile.

    Directory of Open Access Journals (Sweden)

    Michael S M Brouwer

    Full Text Available Clostridium difficile is the leading cause of hospital-associated diarrhoea in the US and Europe. Recently the incidence of C. difficile-associated disease has risen dramatically and concomitantly with the emergence of 'hypervirulent' strains associated with more severe disease and increased mortality. C. difficile contains numerous mobile genetic elements, resulting in the potential for a highly plastic genome. In the first sequenced strain, 630, there is one proven conjugative transposon (CTn, Tn5397, and six putative CTns (CTn1, CTn2 and CTn4-7, of which, CTn4 and CTn5 were capable of excision. In the second sequenced strain, R20291, two further CTns were described.CTn1, CTn2 CTn4, CTn5 and CTn7 were shown to excise from the genome of strain 630 and transfer to strain CD37. A putative CTn from R20291, misleadingly termed a phage island previously, was shown to excise and to contain three putative mobilisable transposons, one of which was capable of excision. In silico probing of C. difficile genome sequences with recombinase gene fragments identified new putative conjugative and mobilisable transposons related to the elements in strains 630 and R20291. CTn5-like elements were described occupying different insertion sites in different strains, CTn1-like elements that have lost the ability to excise in some ribotype 027 strains were described and one strain was shown to contain CTn5-like and CTn7-like elements arranged in tandem. Additionally, using bioinformatics, we updated previous gene annotations and predicted novel functions for the accessory gene products on these new elements.The genomes of the C. difficile strains examined contain highly related CTns suggesting recent horizontal gene transfer. Several elements were capable of excision and conjugative transfer. The presence of antibiotic resistance genes and genes predicted to promote adaptation to the intestinal environment suggests that CTns play a role in the interaction of C

  6. Predictive analytics can support the ACO model.

    Science.gov (United States)

    Bradley, Paul

    2012-04-01

    Predictive analytics can be used to rapidly spot hard-to-identify opportunities to better manage care--a key tool in accountable care. When considering analytics models, healthcare providers should: Make value-based care a priority and act on information from analytics models. Create a road map that includes achievable steps, rather than major endeavors. Set long-term expectations and recognize that the effectiveness of an analytics program takes time, unlike revenue cycle initiatives that may show a quick return.

  7. Predictive modeling in homogeneous catalysis: a tutorial

    NARCIS (Netherlands)

    Maldonado, A.G.; Rothenberg, G.

    2010-01-01

    Predictive modeling has become a practical research tool in homogeneous catalysis. It can help to pinpoint ‘good regions’ in the catalyst space, narrowing the search for the optimal catalyst for a given reaction. Just like any other new idea, in silico catalyst optimization is accepted by some

  8. Model predictive control of smart microgrids

    DEFF Research Database (Denmark)

    Hu, Jiefeng; Zhu, Jianguo; Guerrero, Josep M.

    2014-01-01

    required to realise high-performance of distributed generations and will realise innovative control techniques utilising model predictive control (MPC) to assist in coordinating the plethora of generation and load combinations, thus enable the effective exploitation of the clean renewable energy sources...

  9. Feedback model predictive control by randomized algorithms

    NARCIS (Netherlands)

    Batina, Ivo; Stoorvogel, Antonie Arij; Weiland, Siep

    2001-01-01

    In this paper we present a further development of an algorithm for stochastic disturbance rejection in model predictive control with input constraints based on randomized algorithms. The algorithm presented in our work can solve the problem of stochastic disturbance rejection approximately but with

  10. A Robustly Stabilizing Model Predictive Control Algorithm

    Science.gov (United States)

    Ackmece, A. Behcet; Carson, John M., III

    2007-01-01

    A model predictive control (MPC) algorithm that differs from prior MPC algorithms has been developed for controlling an uncertain nonlinear system. This algorithm guarantees the resolvability of an associated finite-horizon optimal-control problem in a receding-horizon implementation.

  11. Hierarchical Model Predictive Control for Resource Distribution

    DEFF Research Database (Denmark)

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

    2010-01-01

    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...

  12. Model Predictive Control based on Finite Impulse Response Models

    DEFF Research Database (Denmark)

    Prasath, Guru; Jørgensen, John Bagterp

    2008-01-01

    We develop a regularized l2 finite impulse response (FIR) predictive controller with input and input-rate constraints. Feedback is based on a simple constant output disturbance filter. The performance of the predictive controller in the face of plant-model mismatch is investigated by simulations ...

  13. Modeling two strains of disease via aggregate-level infectivity curves.

    Science.gov (United States)

    Romanescu, Razvan; Deardon, Rob

    2016-04-01

    Well formulated models of disease spread, and efficient methods to fit them to observed data, are powerful tools for aiding the surveillance and control of infectious diseases. Our project considers the problem of the simultaneous spread of two related strains of disease in a context where spatial location is the key driver of disease spread. We start our modeling work with the individual level models (ILMs) of disease transmission, and extend these models to accommodate the competing spread of the pathogens in a two-tier hierarchical population (whose levels we refer to as 'farm' and 'animal'). The postulated interference mechanism between the two strains is a period of cross-immunity following infection. We also present a framework for speeding up the computationally intensive process of fitting the ILM to data, typically done using Markov chain Monte Carlo (MCMC) in a Bayesian framework, by turning the inference into a two-stage process. First, we approximate the number of animals infected on a farm over time by infectivity curves. These curves are fit to data sampled from farms, using maximum likelihood estimation, then, conditional on the fitted curves, Bayesian MCMC inference proceeds for the remaining parameters. Finally, we use posterior predictive distributions of salient epidemic summary statistics, in order to assess the model fitted.

  14. Disease prediction models and operational readiness.

    Directory of Open Access Journals (Sweden)

    Courtney D Corley

    Full Text Available The objective of this manuscript is to present a systematic review of biosurveillance models that operate on select agents and can forecast the occurrence of a disease event. We define a disease event to be a biological event with focus on the One Health paradigm. These events are characterized by evidence of infection and or disease condition. We reviewed models that attempted to predict a disease event, not merely its transmission dynamics and we considered models involving pathogens of concern as determined by the US National Select Agent Registry (as of June 2011. We searched commercial and government databases and harvested Google search results for eligible models, using terms and phrases provided by public health analysts relating to biosurveillance, remote sensing, risk assessments, spatial epidemiology, and ecological niche modeling. After removal of duplications and extraneous material, a core collection of 6,524 items was established, and these publications along with their abstracts are presented in a semantic wiki at http://BioCat.pnnl.gov. As a result, we systematically reviewed 44 papers, and the results are presented in this analysis. We identified 44 models, classified as one or more of the following: event prediction (4, spatial (26, ecological niche (28, diagnostic or clinical (6, spread or response (9, and reviews (3. The model parameters (e.g., etiology, climatic, spatial, cultural and data sources (e.g., remote sensing, non-governmental organizations, expert opinion, epidemiological were recorded and reviewed. A component of this review is the identification of verification and validation (V&V methods applied to each model, if any V&V method was reported. All models were classified as either having undergone Some Verification or Validation method, or No Verification or Validation. We close by outlining an initial set of operational readiness level guidelines for disease prediction models based upon established Technology

  15. Caries risk assessment models in caries prediction

    Directory of Open Access Journals (Sweden)

    Amila Zukanović

    2013-11-01

    Full Text Available Objective. The aim of this research was to assess the efficiency of different multifactor models in caries prediction. Material and methods. Data from the questionnaire and objective examination of 109 examinees was entered into the Cariogram, Previser and Caries-Risk Assessment Tool (CAT multifactor risk assessment models. Caries risk was assessed with the help of all three models for each patient, classifying them as low, medium or high-risk patients. The development of new caries lesions over a period of three years [Decay Missing Filled Tooth (DMFT increment = difference between Decay Missing Filled Tooth Surface (DMFTS index at baseline and follow up], provided for examination of the predictive capacity concerning different multifactor models. Results. The data gathered showed that different multifactor risk assessment models give significantly different results (Friedman test: Chi square = 100.073, p=0.000. Cariogram is the model which identified the majority of examinees as medium risk patients (70%. The other two models were more radical in risk assessment, giving more unfavorable risk –profiles for patients. In only 12% of the patients did the three multifactor models assess the risk in the same way. Previser and CAT gave the same results in 63% of cases – the Wilcoxon test showed that there is no statistically significant difference in caries risk assessment between these two models (Z = -1.805, p=0.071. Conclusions. Evaluation of three different multifactor caries risk assessment models (Cariogram, PreViser and CAT showed that only the Cariogram can successfully predict new caries development in 12-year-old Bosnian children.

  16. Link Prediction via Sparse Gaussian Graphical Model

    Directory of Open Access Journals (Sweden)

    Liangliang Zhang

    2016-01-01

    Full Text Available Link prediction is an important task in complex network analysis. Traditional link prediction methods are limited by network topology and lack of node property information, which makes predicting links challenging. In this study, we address link prediction using a sparse Gaussian graphical model and demonstrate its theoretical and practical effectiveness. In theory, link prediction is executed by estimating the inverse covariance matrix of samples to overcome information limits. The proposed method was evaluated with four small and four large real-world datasets. The experimental results show that the area under the curve (AUC value obtained by the proposed method improved by an average of 3% and 12.5% compared to 13 mainstream similarity methods, respectively. This method outperforms the baseline method, and the prediction accuracy is superior to mainstream methods when using only 80% of the training set. The method also provides significantly higher AUC values when using only 60% in Dolphin and Taro datasets. Furthermore, the error rate of the proposed method demonstrates superior performance with all datasets compared to mainstream methods.

  17. Electrostatic ion thrusters - towards predictive modeling

    Energy Technology Data Exchange (ETDEWEB)

    Kalentev, O.; Matyash, K.; Duras, J.; Lueskow, K.F.; Schneider, R. [Ernst-Moritz-Arndt Universitaet Greifswald, D-17489 (Germany); Koch, N. [Technische Hochschule Nuernberg Georg Simon Ohm, Kesslerplatz 12, D-90489 Nuernberg (Germany); Schirra, M. [Thales Electronic Systems GmbH, Soeflinger Strasse 100, D-89077 Ulm (Germany)

    2014-02-15

    The development of electrostatic ion thrusters so far has mainly been based on empirical and qualitative know-how, and on evolutionary iteration steps. This resulted in considerable effort regarding prototype design, construction and testing and therefore in significant development and qualification costs and high time demands. For future developments it is anticipated to implement simulation tools which allow for quantitative prediction of ion thruster performance, long-term behavior and space craft interaction prior to hardware design and construction. Based on integrated numerical models combining self-consistent kinetic plasma models with plasma-wall interaction modules a new quality in the description of electrostatic thrusters can be reached. These open the perspective for predictive modeling in this field. This paper reviews the application of a set of predictive numerical modeling tools on an ion thruster model of the HEMP-T (High Efficiency Multi-stage Plasma Thruster) type patented by Thales Electron Devices GmbH. (copyright 2014 WILEY-VCH Verlag GmbH and Co. KGaA, Weinheim) (orig.)

  18. Characterizing Attention with Predictive Network Models.

    Science.gov (United States)

    Rosenberg, M D; Finn, E S; Scheinost, D; Constable, R T; Chun, M M

    2017-04-01

    Recent work shows that models based on functional connectivity in large-scale brain networks can predict individuals' attentional abilities. While being some of the first generalizable neuromarkers of cognitive function, these models also inform our basic understanding of attention, providing empirical evidence that: (i) attention is a network property of brain computation; (ii) the functional architecture that underlies attention can be measured while people are not engaged in any explicit task; and (iii) this architecture supports a general attentional ability that is common to several laboratory-based tasks and is impaired in attention deficit hyperactivity disorder (ADHD). Looking ahead, connectivity-based predictive models of attention and other cognitive abilities and behaviors may potentially improve the assessment, diagnosis, and treatment of clinical dysfunction. Copyright © 2017 Elsevier Ltd. All rights reserved.

  19. Genetic models of homosexuality: generating testable predictions

    Science.gov (United States)

    Gavrilets, Sergey; Rice, William R

    2006-01-01

    Homosexuality is a common occurrence in humans and other species, yet its genetic and evolutionary basis is poorly understood. Here, we formulate and study a series of simple mathematical models for the purpose of predicting empirical patterns that can be used to determine the form of selection that leads to polymorphism of genes influencing homosexuality. Specifically, we develop theory to make contrasting predictions about the genetic characteristics of genes influencing homosexuality including: (i) chromosomal location, (ii) dominance among segregating alleles and (iii) effect sizes that distinguish between the two major models for their polymorphism: the overdominance and sexual antagonism models. We conclude that the measurement of the genetic characteristics of quantitative trait loci (QTLs) found in genomic screens for genes influencing homosexuality can be highly informative in resolving the form of natural selection maintaining their polymorphism. PMID:17015344

  20. Numerical predictions of heat transfer and pressure tube/calandria tube deformation during Calandria-tube Strain Contact Boiling (CSCB) tests

    Energy Technology Data Exchange (ETDEWEB)

    Tanase, A.; Szymanski, J.; El-Hawary, M.; Delja, A., E-mail: aurelian.tanase@cnsc-ccsn.gc.ca [Canadian Nuclear Safety Commission, Ottawa, ON (Canada)

    2015-07-01

    The assessment of fuel channel integrity during large break LOCA requires adequate prediction of the thermal-mechanical behaviour of the fuel channel following pressure tube ballooning into contact with the calandria tube. Analytical models developed for this purpose need to be calibrated and validated against experimental data. A new series of contact boiling tests was initiated by CNSC to provide additional data on calandria tube straining behaviour after PT/CT contact. This paper presents selected results of the first of these tests and their comparisons with predictions using analytical methodology developed by CNSC staff. (author)

  1. A statistical model for predicting muscle performance

    Science.gov (United States)

    Byerly, Diane Leslie De Caix

    The objective of these studies was to develop a capability for predicting muscle performance and fatigue to be utilized for both space- and ground-based applications. To develop this predictive model, healthy test subjects performed a defined, repetitive dynamic exercise to failure using a Lordex spinal machine. Throughout the exercise, surface electromyography (SEMG) data were collected from the erector spinae using a Mega Electronics ME3000 muscle tester and surface electrodes placed on both sides of the back muscle. These data were analyzed using a 5th order Autoregressive (AR) model and statistical regression analysis. It was determined that an AR derived parameter, the mean average magnitude of AR poles, significantly correlated with the maximum number of repetitions (designated Rmax) that a test subject was able to perform. Using the mean average magnitude of AR poles, a test subject's performance to failure could be predicted as early as the sixth repetition of the exercise. This predictive model has the potential to provide a basis for improving post-space flight recovery, monitoring muscle atrophy in astronauts and assessing the effectiveness of countermeasures, monitoring astronaut performance and fatigue during Extravehicular Activity (EVA) operations, providing pre-flight assessment of the ability of an EVA crewmember to perform a given task, improving the design of training protocols and simulations for strenuous International Space Station assembly EVA, and enabling EVA work task sequences to be planned enhancing astronaut performance and safety. Potential ground-based, medical applications of the predictive model include monitoring muscle deterioration and performance resulting from illness, establishing safety guidelines in the industry for repetitive tasks, monitoring the stages of rehabilitation for muscle-related injuries sustained in sports and accidents, and enhancing athletic performance through improved training protocols while reducing

  2. Prediction models : the right tool for the right problem

    NARCIS (Netherlands)

    Kappen, Teus H.; Peelen, Linda M.

    2016-01-01

    PURPOSE OF REVIEW: Perioperative prediction models can help to improve personalized patient care by providing individual risk predictions to both patients and providers. However, the scientific literature on prediction model development and validation can be quite technical and challenging to

  3. In silico strain optimization by adding reactions to metabolic models.

    Science.gov (United States)

    Correia, Sara; Rocha, Miguel

    2012-07-24

    Nowadays, the concerns about the environment and the needs to increase the productivity at low costs, demand for the search of new ways to produce compounds with industrial interest. Based on the increasing knowledge of biological processes, through genome sequencing projects, and high-throughput experimental techniques as well as the available computational tools, the use of microorganisms has been considered as an approach to produce desirable compounds. However, this usually requires to manipulate these organisms by genetic engineering and/ or changing the enviromental conditions to make the production of these compounds possible. In many cases, it is necessary to enrich the genetic material of those microbes with hereologous pathways from other species and consequently adding the potential to produce novel compounds. This paper introduces a new plug-in for the OptFlux Metabolic Engineering platform, aimed at finding suitable sets of reactions to add to the genomes of selected microbes (wild type strain), as well as finding complementary sets of deletions, so that the mutant becomes able to overproduce compounds with industrial interest, while preserving their viability. The necessity of adding reactions to the metabolic model arises from existing gaps in the original model or motivated by the productions of new compounds by the organism. The optimization methods used are metaheuristics such as Evolutionary Algorithms and Simulated Annealing. The usefulness of this plug-in is demonstrated by a case study, regarding the production of vanillin by the bacterium E. coli.

  4. Assessment of Bactericidal Drug Activity and Treatment Outcome in a Mouse Tuberculosis Model Using a Clinical Beijing Strain.

    Science.gov (United States)

    Mourik, Bas C; de Knegt, Gerjo J; Verbon, Annelies; Mouton, Johan W; Bax, Hannelore I; de Steenwinkel, Jurriaan E M

    2017-10-01

    Mycobacterium tuberculosis Beijing strains are associated with lower treatment success rates in tuberculosis (TB) patients. In contrast, laboratory strains such as H37Rv are often used in preclinical tuberculosis models. Therefore, we explored the impact of using a clinical Beijing strain on treatment outcome in our mouse tuberculosis model. Additionally, the predictive value of bactericidal activity on treatment outcome was assessed. BALB/c mice were infected with a Beijing strain and treated with one of 10 different combinations of conventional anti-TB drugs. Bactericidal activity was assessed by determining reductions in mycobacterial load after 7, 14, and 28 days and after 2, 3, and 6 months of treatment. Treatment outcome was evaluated after a 6-month treatment course and was based on lung culture status 3 months posttreatment. None of the anti-TB drug regimens tested could achieve 100% treatment success. Treatment outcome depended critically on rifampin. Four non-rifampin-containing regimens showed 0% treatment success compared to success rates between 81 and 95% for six rifampin-containing regimens. Bactericidal activity was predictive only for treatment outcome after 3 months of treatment. Our data advocate the use of multiple mycobacterial strains, including a Beijing strain, to increase the translational value of mouse TB models evaluating treatment outcome. Additionally, our findings support the notion that bactericidal activity in the first 2 months of treatment, as measured in clinical phase IIa/b trials, has limited predictive value for tuberculosis treatment outcome, thus emphasizing the need for better parameters to guide future phase IIII trials. Copyright © 2017 American Society for Microbiology.

  5. A 3D finite strain phenomenological constitutive model for shape memory alloys considering martensite reorientation

    Science.gov (United States)

    Arghavani, J.; Auricchio, F.; Naghdabadi, R.; Reali, A.; Sohrabpour, S.

    2010-06-01

    Most devices based on shape memory alloys experience both finite deformations and non-proportional loading conditions in engineering applications. This motivates the development of constitutive models considering finite strain as well as martensite variant reorientation. To this end, in the present article, based on the principles of continuum thermodynamics with internal variables, a three-dimensional finite strain phenomenological constitutive model is proposed taking its basis from the recent model in the small strain regime proposed by Panico and Brinson (J Mech Phys Solids 55:2491-2511, 2007). In the finite strain constitutive model derivation, a multiplicative decomposition of the deformation gradient into elastic and inelastic parts, together with an additive decomposition of the inelastic strain rate tensor into transformation and reorientation parts is adopted. Moreover, it is shown that, when linearized, the proposed model reduces exactly to the original small strain model.

  6. Computed-tomography-based finite-element models of long bones can accurately capture strain response to bending and torsion.

    Science.gov (United States)

    Varghese, Bino; Short, David; Penmetsa, Ravi; Goswami, Tarun; Hangartner, Thomas

    2011-04-29

    Finite element (FE) models of long bones constructed from computed-tomography (CT) data are emerging as an invaluable tool in the field of bone biomechanics. However, the performance of such FE models is highly dependent on the accurate capture of geometry and appropriate assignment of material properties. In this study, a combined numerical-experimental study is performed comparing FE-predicted surface strains with strain-gauge measurements. Thirty-six major, cadaveric, long bones (humerus, radius, femur and tibia), which cover a wide range of bone sizes, were tested under three-point bending and torsion. The FE models were constructed from trans-axial volumetric CT scans, and the segmented bone images were corrected for partial-volume effects. The material properties (Young's modulus for cortex, density-modulus relationship for trabecular bone and Poisson's ratio) were calibrated by minimizing the error between experiments and simulations among all bones. The R(2) values of the measured strains versus load under three-point bending and torsion were 0.96-0.99 and 0.61-0.99, respectively, for all bones in our dataset. The errors of the calculated FE strains in comparison to those measured using strain gauges in the mechanical tests ranged from -6% to 7% under bending and from -37% to 19% under torsion. The observation of comparatively low errors and high correlations between the FE-predicted strains and the experimental strains, across the various types of bones and loading conditions (bending and torsion), validates our approach to bone segmentation and our choice of material properties. Copyright © 2011 Elsevier Ltd. All rights reserved.

  7. Small strain multiphase-field model accounting for configurational forces and mechanical jump conditions

    Science.gov (United States)

    Schneider, Daniel; Schoof, Ephraim; Tschukin, Oleg; Reiter, Andreas; Herrmann, Christoph; Schwab, Felix; Selzer, Michael; Nestler, Britta

    2017-08-01

    Computational models based on the phase-field method have become an essential tool in material science and physics in order to investigate materials with complex microstructures. The models typically operate on a mesoscopic length scale resolving structural changes of the material and provide valuable information about the evolution of microstructures and mechanical property relations. For many interesting and important phenomena, such as martensitic phase transformation, mechanical driving forces play an important role in the evolution of microstructures. In order to investigate such physical processes, an accurate calculation of the stresses and the strain energy in the transition region is indispensable. We recall a multiphase-field elasticity model based on the force balance and the Hadamard jump condition at the interface. We show the quantitative characteristics of the model by comparing the stresses, strains and configurational forces with theoretical predictions in two-phase cases and with results from sharp interface calculations in a multiphase case. As an application, we choose the martensitic phase transformation process in multigrain systems and demonstrate the influence of the local homogenization scheme within the transition regions on the resulting microstructures.

  8. Autonomy and social norms in a three factor grief model predicting perinatal grief in India.

    Science.gov (United States)

    Roberts, Lisa R; Lee, Jerry W

    2014-01-01

    Perinatal grief following stillbirth is a significant social and mental health burden. We examined associations among the following latent variables: autonomy, social norms, self-despair, strained coping, and acute grief-among poor, rural women in India who experienced stillbirth. A structural equation model was built and tested using quantitative data from 347 women of reproductive age in Chhattisgarh. Maternal acceptance of traditional social norms worsens self-despair and strained coping, and increases the autonomy granted to women. Greater autonomy increases acute grief. Greater despair and acute grief increase strained coping. Social and cultural factors were found to predict perinatal grief in India.

  9. Neuro-fuzzy modeling in bankruptcy prediction

    Directory of Open Access Journals (Sweden)

    Vlachos D.

    2003-01-01

    Full Text Available For the past 30 years the problem of bankruptcy prediction had been thoroughly studied. From the paper of Altman in 1968 to the recent papers in the '90s, the progress of prediction accuracy was not satisfactory. This paper investigates an alternative modeling of the system (firm, combining neural networks and fuzzy controllers, i.e. using neuro-fuzzy models. Classical modeling is based on mathematical models that describe the behavior of the firm under consideration. The main idea of fuzzy control, on the other hand, is to build a model of a human control expert who is capable of controlling the process without thinking in a mathematical model. This control expert specifies his control action in the form of linguistic rules. These control rules are translated into the framework of fuzzy set theory providing a calculus, which can stimulate the behavior of the control expert and enhance its performance. The accuracy of the model is studied using datasets from previous research papers.

  10. Robust human body model injury prediction in simulated side impact crashes.

    Science.gov (United States)

    Golman, Adam J; Danelson, Kerry A; Stitzel, Joel D

    2016-01-01

    This study developed a parametric methodology to robustly predict occupant injuries sustained in real-world crashes using a finite element (FE) human body model (HBM). One hundred and twenty near-side impact motor vehicle crashes were simulated over a range of parameters using a Toyota RAV4 (bullet vehicle), Ford Taurus (struck vehicle) FE models and a validated human body model (HBM) Total HUman Model for Safety (THUMS). Three bullet vehicle crash parameters (speed, location and angle) and two occupant parameters (seat position and age) were varied using a Latin hypercube design of Experiments. Four injury metrics (head injury criterion, half deflection, thoracic trauma index and pelvic force) were used to calculate injury risk. Rib fracture prediction and lung strain metrics were also analysed. As hypothesized, bullet speed had the greatest effect on each injury measure. Injury risk was reduced when bullet location was further from the B-pillar or when the bullet angle was more oblique. Age had strong correlation to rib fractures frequency and lung strain severity. The injuries from a real-world crash were predicted using two different methods by (1) subsampling the injury predictors from the 12 best crush profile matching simulations and (2) using regression models. Both injury prediction methods successfully predicted the case occupant's low risk for pelvic injury, high risk for thoracic injury, rib fractures and high lung strains with tight confidence intervals. This parametric methodology was successfully used to explore crash parameter interactions and to robustly predict real-world injuries.

  11. The Exometabolome of Two Model Strains of the Roseobacter Group: A Marketplace of Microbial Metabolites

    Directory of Open Access Journals (Sweden)

    Gerrit Wienhausen

    2017-10-01

    Full Text Available Recent studies applying Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR-MS showed that the exometabolome of marine bacteria is composed of a surprisingly high molecular diversity. To shed more light on how this diversity is generated we examined the exometabolome of two model strains of the Roseobacter group, Phaeobacter inhibens and Dinoroseobacter shibae, grown on glutamate, glucose, acetate or succinate by FT-ICR-MS. We detected 2,767 and 3,354 molecular formulas in the exometabolome of each strain and 67 and 84 matched genome-predicted metabolites of P. inhibens and D. shibae, respectively. The annotated compounds include late precursors of biosynthetic pathways of vitamins B1, B2, B5, B6, B7, B12, amino acids, quorum sensing-related compounds, indole acetic acid and methyl-(indole-3-yl acetic acid. Several formulas were also found in phytoplankton blooms. To shed more light on the effects of some of the precursors we supplemented two B1 prototrophic diatoms with the detected precursor of vitamin B1 HET (4-methyl-5-(β-hydroxyethylthiazole and HMP (4-amino-5-hydroxymethyl-2-methylpyrimidine and found that their growth was stimulated. Our findings indicate that both strains and other bacteria excreting a similar wealth of metabolites may function as important helpers to auxotrophic and prototrophic marine microbes by supplying growth factors and biosynthetic precursors.

  12. Role of Right Ventricular Global Longitudinal Strain in Predicting Early and Long-Term Mortality in Cardiac Resynchronization Therapy Patients.

    Directory of Open Access Journals (Sweden)

    Vivien Klaudia Nagy

    Full Text Available Right ventricular (RV dysfunction has been associated with poor prognosis in chronic heart failure (HF. However, less data is available about the role of RV dysfunction in patients with cardiac resynchronization therapy (CRT. We aimed to investigate if RV dysfunction would predict outcome in CRT.We enrolled prospectively ninety-three consecutive HF patients in this single center observational study. All patients underwent clinical evaluation and echocardiography before CRT and 6 months after implantation. We assessed RV geometry and function by using speckle tracking imaging and calculated strain parameters. We performed multivariable Cox regression models to test mortality at 6 months and at 24 months.RV dysfunction, characterized by decreased RVGLS (RV global longitudinal strain [10.2 (7.0-12.8 vs. 19.5 (15.0-23.9 %, p<0.0001] and RVFWS (RV free wall strain [15.6 (10.0-19.3 vs. 17.4 (10.5-22.2 %, p = 0.04], improved 6 months after CRT implantation. Increasing baseline RVGLS and RVFWS predicted survival independent of other parameters at 6 months [hazard ratio (HR = 0.37 (0.15-0.90, p = 0.02 and HR = 0.42 (0.19-0.89, p = 0.02; per 1 standard deviation increase, respectively]. RVGLS proved to be a significant independent predictor of mortality at 24 months [HR = 0.53 (0.32-0.86, p = 0.01], and RVFWS showed a strong tendency [HR = 0.64 (0.40-1.00, p = 0.05]. The 24-month survival was significantly impaired in patients with RVGLS below 10.04% before CRT implantation [area under the curve = 0.72 (0.60-0.84, p = 0.002, log-rank p = 0.0008; HR = 5.23 (1.76-15.48, p = 0.003].Our findings indicate that baseline RV dysfunction is associated with poor short-term and long-term prognosis after CRT implantation.

  13. Predictive Models for Carcinogenicity and Mutagenicity ...

    Science.gov (United States)

    Mutagenicity and carcinogenicity are endpoints of major environmental and regulatory concern. These endpoints are also important targets for development of alternative methods for screening and prediction due to the large number of chemicals of potential concern and the tremendous cost (in time, money, animals) of rodent carcinogenicity bioassays. Both mutagenicity and carcinogenicity involve complex, cellular processes that are only partially understood. Advances in technologies and generation of new data will permit a much deeper understanding. In silico methods for predicting mutagenicity and rodent carcinogenicity based on chemical structural features, along with current mutagenicity and carcinogenicity data sets, have performed well for local prediction (i.e., within specific chemical classes), but are less successful for global prediction (i.e., for a broad range of chemicals). The predictivity of in silico methods can be improved by improving the quality of the data base and endpoints used for modelling. In particular, in vitro assays for clastogenicity need to be improved to reduce false positives (relative to rodent carcinogenicity) and to detect compounds that do not interact directly with DNA or have epigenetic activities. New assays emerging to complement or replace some of the standard assays include VitotoxTM, GreenScreenGC, and RadarScreen. The needs of industry and regulators to assess thousands of compounds necessitate the development of high-t

  14. Disease Prediction Models and Operational Readiness

    Energy Technology Data Exchange (ETDEWEB)

    Corley, Courtney D.; Pullum, Laura L.; Hartley, David M.; Benedum, Corey M.; Noonan, Christine F.; Rabinowitz, Peter M.; Lancaster, Mary J.

    2014-03-19

    INTRODUCTION: The objective of this manuscript is to present a systematic review of biosurveillance models that operate on select agents and can forecast the occurrence of a disease event. One of the primary goals of this research was to characterize the viability of biosurveillance models to provide operationally relevant information for decision makers to identify areas for future research. Two critical characteristics differentiate this work from other infectious disease modeling reviews. First, we reviewed models that attempted to predict the disease event, not merely its transmission dynamics. Second, we considered models involving pathogens of concern as determined by the US National Select Agent Registry (as of June 2011). Methods: We searched dozens of commercial and government databases and harvested Google search results for eligible models utilizing terms and phrases provided by public health analysts relating to biosurveillance, remote sensing, risk assessments, spatial epidemiology, and ecological niche-modeling, The publication date of search results returned are bound by the dates of coverage of each database and the date in which the search was performed, however all searching was completed by December 31, 2010. This returned 13,767 webpages and 12,152 citations. After de-duplication and removal of extraneous material, a core collection of 6,503 items was established and these publications along with their abstracts are presented in a semantic wiki at http://BioCat.pnnl.gov. Next, PNNL’s IN-SPIRE visual analytics software was used to cross-correlate these publications with the definition for a biosurveillance model resulting in the selection of 54 documents that matched the criteria resulting Ten of these documents, However, dealt purely with disease spread models, inactivation of bacteria, or the modeling of human immune system responses to pathogens rather than predicting disease events. As a result, we systematically reviewed 44 papers and the

  15. Micro-Structural Evolution and Size-Effects in Plastically Deformed Single Crystals: Strain Gradient Continuum Modeling

    DEFF Research Database (Denmark)

    El-Naaman, Salim Abdallah

    An extensive amount of research has been devoted to the development of micro-mechanics based gradient plasticity continuum theories, which are necessary for modeling micron-scale plasticity when large spatial gradients of plastic strain appear. While many models have proven successful in capturing...... the macroscopic effects related to strain gradients, most predict smooth micro-structures. The evolution of dislocation micro-structures, during plastic straining of ductile crystalline materials, is highly complex and nonuniform. Published experimental measurements on deformed metal crystals show distinct......, to focus on their ability to capture realistic micro-structural evolution. This challenge is the main focus of the present thesis, which takes as starting point a non-work conjugate type back stress based higher order crystal plasticity theory. Within this framework, several possibilities for the back...

  16. Nonlinear model predictive control theory and algorithms

    CERN Document Server

    Grüne, Lars

    2017-01-01

    This book offers readers a thorough and rigorous introduction to nonlinear model predictive control (NMPC) for discrete-time and sampled-data systems. NMPC schemes with and without stabilizing terminal constraints are detailed, and intuitive examples illustrate the performance of different NMPC variants. NMPC is interpreted as an approximation of infinite-horizon optimal control so that important properties like closed-loop stability, inverse optimality and suboptimality can be derived in a uniform manner. These results are complemented by discussions of feasibility and robustness. An introduction to nonlinear optimal control algorithms yields essential insights into how the nonlinear optimization routine—the core of any nonlinear model predictive controller—works. Accompanying software in MATLAB® and C++ (downloadable from extras.springer.com/), together with an explanatory appendix in the book itself, enables readers to perform computer experiments exploring the possibilities and limitations of NMPC. T...

  17. A predictive model for dimensional errors in fused deposition modeling

    DEFF Research Database (Denmark)

    Stolfi, A.

    2015-01-01

    values of L (0.254 mm, 0.330 mm) was produced by comparing predicted values with external face-to-face measurements. After removing outliers, the results show that the developed two-parameter model can serve as tool for modeling the FDM dimensional behavior in a wide range of deposition angles....

  18. A predictive model for dimensional errors in fused deposition modeling

    DEFF Research Database (Denmark)

    Stolfi, A.

    2015-01-01

    This work concerns the effect of deposition angle (a) and layer thickness (L) on the dimensional performance of FDM parts using a predictive model based on the geometrical description of the FDM filament profile. An experimental validation over the whole a range from 0° to 177° at 3° steps and two...... values of L (0.254 mm, 0.330 mm) was produced by comparing predicted values with external face-to-face measurements. After removing outliers, the results show that the developed two-parameter model can serve as tool for modeling the FDM dimensional behavior in a wide range of deposition angles....

  19. Predictive Modeling in Actinide Chemistry and Catalysis

    Energy Technology Data Exchange (ETDEWEB)

    Yang, Ping [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

    2016-05-16

    These are slides from a presentation on predictive modeling in actinide chemistry and catalysis. The following topics are covered in these slides: Structures, bonding, and reactivity (bonding can be quantified by optical probes and theory, and electronic structures and reaction mechanisms of actinide complexes); Magnetic resonance properties (transition metal catalysts with multi-nuclear centers, and NMR/EPR parameters); Moving to more complex systems (surface chemistry of nanomaterials, and interactions of ligands with nanoparticles); Path forward and conclusions.

  20. Predictive modelling of evidence informed teaching

    OpenAIRE

    Zhang, Dell; Brown, C.

    2017-01-01

    In this paper, we analyse the questionnaire survey data collected from 79 English primary schools about the situation of evidence informed teaching, where the evidences could come from research journals or conferences. Specifically, we build a predictive model to see what external factors could help to close the gap between teachers’ belief and behaviour in evidence informed teaching, which is the first of its kind to our knowledge. The major challenge, from the data mining perspective, is th...

  1. A Predictive Model for Cognitive Radio

    Science.gov (United States)

    2006-09-14

    response in a given situation. Vadde et al. interest and produce a model for prediction of the response. have applied response surface methodology and...34 2000. [3] K. K. Vadde and V. R. Syrotiuk, "Factor interaction on service configurations to those that best meet our communication delivery in mobile ad...resulting set of configurations randomly or apply additional 2004. screening criteria. [4] K. K. Vadde , M.-V. R. Syrotiuk, and D. C. Montgomery

  2. Tectonic predictions with mantle convection models

    Science.gov (United States)

    Coltice, Nicolas; Shephard, Grace E.

    2018-04-01

    Over the past 15 yr, numerical models of convection in Earth's mantle have made a leap forward: they can now produce self-consistent plate-like behaviour at the surface together with deep mantle circulation. These digital tools provide a new window into the intimate connections between plate tectonics and mantle dynamics, and can therefore be used for tectonic predictions, in principle. This contribution explores this assumption. First, initial conditions at 30, 20, 10 and 0 Ma are generated by driving a convective flow with imposed plate velocities at the surface. We then compute instantaneous mantle flows in response to the guessed temperature fields without imposing any boundary conditions. Plate boundaries self-consistently emerge at correct locations with respect to reconstructions, except for small plates close to subduction zones. As already observed for other types of instantaneous flow calculations, the structure of the top boundary layer and upper-mantle slab is the dominant character that leads to accurate predictions of surface velocities. Perturbations of the rheological parameters have little impact on the resulting surface velocities. We then compute fully dynamic model evolution from 30 and 10 to 0 Ma, without imposing plate boundaries or plate velocities. Contrary to instantaneous calculations, errors in kinematic predictions are substantial, although the plate layout and kinematics in several areas remain consistent with the expectations for the Earth. For these calculations, varying the rheological parameters makes a difference for plate boundary evolution. Also, identified errors in initial conditions contribute to first-order kinematic errors. This experiment shows that the tectonic predictions of dynamic models over 10 My are highly sensitive to uncertainties of rheological parameters and initial temperature field in comparison to instantaneous flow calculations. Indeed, the initial conditions and the rheological parameters can be good enough

  3. Predictive Modeling of Influenza Shows the Promise of Applied Evolutionary Biology.

    Science.gov (United States)

    Morris, Dylan H; Gostic, Katelyn M; Pompei, Simone; Bedford, Trevor; Łuksza, Marta; Neher, Richard A; Grenfell, Bryan T; Lässig, Michael; McCauley, John W

    2018-02-01

    Seasonal influenza is controlled through vaccination campaigns. Evolution of influenza virus antigens means that vaccines must be updated to match novel strains, and vaccine effectiveness depends on the ability of scientists to predict nearly a year in advance which influenza variants will dominate in upcoming seasons. In this review, we highlight a promising new surveillance tool: predictive models. Based on data-sharing and close collaboration between the World Health Organization and academic scientists, these models use surveillance data to make quantitative predictions regarding influenza evolution. Predictive models demonstrate the potential of applied evolutionary biology to improve public health and disease control. We review the state of influenza predictive modeling and discuss next steps and recommendations to ensure that these models deliver upon their considerable biomedical promise. Copyright © 2017 Elsevier Ltd. All rights reserved.

  4. Strain dyssynchrony index determined by three-dimensional speckle area tracking can predict response to cardiac resynchronization therapy

    Directory of Open Access Journals (Sweden)

    Onishi Tetsuari

    2011-04-01

    Full Text Available Abstract Background We have previously reported strain dyssynchrony index assessed by two-dimensional speckle tracking strain, and a marker of both dyssynchrony and residual myocardial contractility, can predict response to cardiac resynchronization therapy (CRT. A newly developed three-dimensional (3-D speckle tracking system can quantify endocardial area change ratio (area strain, which coupled with the factors of both longitudinal and circumferential strain, from all 16 standard left ventricular (LV segments using complete 3-D pyramidal datasets. Our objective was to test the hypothesis that strain dyssynchrony index using area tracking (ASDI can quantify dyssynchrony and predict response to CRT. Methods We studied 14 heart failure patients with ejection fraction of 27 ± 7% (all≤35% and QRS duration of 172 ± 30 ms (all≥120 ms who underwent CRT. Echocardiography was performed before and 6-month after CRT. ASDI was calculated as the average difference between peak and end-systolic area strain of LV endocardium obtained from 3-D speckle tracking imaging using 16 segments. Conventional dyssynchrony measures were assessed by interventricular mechanical delay, Yu Index, and two-dimensional radial dyssynchrony by speckle-tracking strain. Response was defined as a ≥15% decrease in LV end-systolic volume 6-month after CRT. Results ASDI ≥ 3.8% was the best predictor of response to CRT with a sensitivity of 78%, specificity of 100% and area under the curve (AUC of 0.93 (p Conclusions ASDI can predict responders and LV reverse remodeling following CRT. This novel index using the 3-D speckle tracking system, which shows circumferential and longitudinal LV dyssynchrony and residual endocardial contractility, may thus have clinical significance for CRT patients.

  5. EXPERIMENTAL TESTS OF VANADIUM STRENGTH MODELS AT HIGH PRESSURES AND STRAIN RATES

    Energy Technology Data Exchange (ETDEWEB)

    Park, H; Barton, N R; Becker, R C; Bernier, J V; Cavallo, R M; Lorenz, K T; Pollaine, S M; Remington, B A; Rudd, R E

    2010-03-02

    Experimental results showing significant reductions from classical in the Rayleigh-Taylor (RT) instability growth rate due to high pressure material strength or effective lattice viscosity in metal foils are presented. On the Omega Laser in the Laboratory for Laser Energetics, University of Rochester, target samples of polycrystalline vanadium are compressed and accelerated quasi-isentropically at {approx}1 Mbar pressures, while maintaining the samples in the solid-state. Comparison of the results with constitutive models for solid state strength under these conditions show that the measured RT growth is substantially lower than predictions using existing models that work well at low pressures and long time scales. High pressure, high strain rate data can be explained by the enhanced strength due to a phonon drag mechanism, creating a high effective lattice viscosity.

  6. Predictive Modeling of the CDRA 4BMS

    Science.gov (United States)

    Coker, Robert F.; Knox, James C.

    2016-01-01

    As part of NASA's Advanced Exploration Systems (AES) program and the Life Support Systems Project (LSSP), fully predictive models of the Four Bed Molecular Sieve (4BMS) of the Carbon Dioxide Removal Assembly (CDRA) on the International Space Station (ISS) are being developed. This virtual laboratory will be used to help reduce mass, power, and volume requirements for future missions. In this paper we describe current and planned modeling developments in the area of carbon dioxide removal to support future crewed Mars missions as well as the resolution of anomalies observed in the ISS CDRA.

  7. Negative emotionality, activity, and sociability temperaments predicting long-term job strain and effort-reward imbalance: a 15-year prospective follow-up study.

    Science.gov (United States)

    Hintsanen, Mirka; Hintsa, Taina; Widell, Anna; Kivimäki, Mika; Raitakari, Olli T; Keltkangas-Järvinen, Liisa

    2011-08-01

    This study examined a longitudinal association between innate temperament and perceptions of long-term work stressors. The sample consisted of 276 men and 345 women (aged 30-45 years in 2007) participating in the prospective population-based Cardiovascular Risk in Young Finns study. In 1992, temperament was self-assessed with the EAS questionnaire that assesses three temperamental traits: negative emotionality, activity, and sociability. Perceived work stressors were measured in 2001 and in 2007 using two models: Karasek's demand/control-model in which a combination of high demands and low control results in job strain, and Siegrist's Effort-reward imbalance (ERI) model. The results showed that higher negative emotionality and lower sociability systematically predicted higher perceived job strain and ERI (Ppredicted higher perceived ERI (Ppredict perceived job strain, as it was related to both higher perceived demands and higher control. The results suggest that temperament may be a predisposing factor to the experiences of work stressors in adulthood. Although self-reported job strain and ERI are measures of job characteristics, they are affected by individual temperament. Copyright © 2011 Elsevier Inc. All rights reserved.

  8. Modification of a thermomechanical model to predict constitutive behavior of Al-Mg-Si alloys

    NARCIS (Netherlands)

    Van de Langkruis, J.; Kool, W.H.; Van der Zwaag, S.

    2006-01-01

    A previously developed constitutive model for quantification of the effect of the condition of Mg and Si in AA6xxx alloys was used for the prediction of the flow stresses measured by plane strain compression (PSC) tests. As an extension of earlier work, two AA6xxx alloys were subjected to different

  9. Predictive Modeling by the Cerebellum Improves Proprioception

    Science.gov (United States)

    Bhanpuri, Nasir H.; Okamura, Allison M.

    2013-01-01

    Because sensation is delayed, real-time movement control requires not just sensing, but also predicting limb position, a function hypothesized for the cerebellum. Such cerebellar predictions could contribute to perception of limb position (i.e., proprioception), particularly when a person actively moves the limb. Here we show that human cerebellar patients have proprioceptive deficits compared with controls during active movement, but not when the arm is moved passively. Furthermore, when healthy subjects move in a force field with unpredictable dynamics, they have active proprioceptive deficits similar to cerebellar patients. Therefore, muscle activity alone is likely insufficient to enhance proprioception and predictability (i.e., an internal model of the body and environment) is important for active movement to benefit proprioception. We conclude that cerebellar patients have an active proprioceptive deficit consistent with disrupted movement prediction rather than an inability to generally enhance peripheral proprioceptive signals during action and suggest that active proprioceptive deficits should be considered a fundamental cerebellar impairment of clinical importance. PMID:24005283

  10. Prediction of Chemical Function: Model Development and ...

    Science.gov (United States)

    The United States Environmental Protection Agency’s Exposure Forecaster (ExpoCast) project is developing both statistical and mechanism-based computational models for predicting exposures to thousands of chemicals, including those in consumer products. The high-throughput (HT) screening-level exposures developed under ExpoCast can be combined with HT screening (HTS) bioactivity data for the risk-based prioritization of chemicals for further evaluation. The functional role (e.g. solvent, plasticizer, fragrance) that a chemical performs can drive both the types of products in which it is found and the concentration in which it is present and therefore impacting exposure potential. However, critical chemical use information (including functional role) is lacking for the majority of commercial chemicals for which exposure estimates are needed. A suite of machine-learning based models for classifying chemicals in terms of their likely functional roles in products based on structure were developed. This effort required collection, curation, and harmonization of publically-available data sources of chemical functional use information from government and industry bodies. Physicochemical and structure descriptor data were generated for chemicals with function data. Machine-learning classifier models for function were then built in a cross-validated manner from the descriptor/function data using the method of random forests. The models were applied to: 1) predict chemi

  11. Gamma-Ray Pulsars Models and Predictions

    CERN Document Server

    Harding, A K

    2001-01-01

    Pulsed emission from gamma-ray pulsars originates inside the magnetosphere, from radiation by charged particles accelerated near the magnetic poles or in the outer gaps. In polar cap models, the high energy spectrum is cut off by magnetic pair production above an energy that is dependent on the local magnetic field strength. While most young pulsars with surface fields in the range B = 10^{12} - 10^{13} G are expected to have high energy cutoffs around several GeV, the gamma-ray spectra of old pulsars having lower surface fields may extend to 50 GeV. Although the gamma-ray emission of older pulsars is weaker, detecting pulsed emission at high energies from nearby sources would be an important confirmation of polar cap models. Outer gap models predict more gradual high-energy turnovers at around 10 GeV, but also predict an inverse Compton component extending to TeV energies. Detection of pulsed TeV emission, which would not survive attenuation at the polar caps, is thus an important test of outer gap models. N...

  12. A prediction model for Clostridium difficile recurrence

    Directory of Open Access Journals (Sweden)

    Francis D. LaBarbera

    2015-02-01

    Full Text Available Background: Clostridium difficile infection (CDI is a growing problem in the community and hospital setting. Its incidence has been on the rise over the past two decades, and it is quickly becoming a major concern for the health care system. High rate of recurrence is one of the major hurdles in the successful treatment of C. difficile infection. There have been few studies that have looked at patterns of recurrence. The studies currently available have shown a number of risk factors associated with C. difficile recurrence (CDR; however, there is little consensus on the impact of most of the identified risk factors. Methods: Our study was a retrospective chart review of 198 patients diagnosed with CDI via Polymerase Chain Reaction (PCR from February 2009 to Jun 2013. In our study, we decided to use a machine learning algorithm called the Random Forest (RF to analyze all of the factors proposed to be associated with CDR. This model is capable of making predictions based on a large number of variables, and has outperformed numerous other models and statistical methods. Results: We came up with a model that was able to accurately predict the CDR with a sensitivity of 83.3%, specificity of 63.1%, and area under curve of 82.6%. Like other similar studies that have used the RF model, we also had very impressive results. Conclusions: We hope that in the future, machine learning algorithms, such as the RF, will see a wider application.

  13. Artificial Neural Network Model for Predicting Compressive

    Directory of Open Access Journals (Sweden)

    Salim T. Yousif

    2013-05-01

    Full Text Available   Compressive strength of concrete is a commonly used criterion in evaluating concrete. Although testing of the compressive strength of concrete specimens is done routinely, it is performed on the 28th day after concrete placement. Therefore, strength estimation of concrete at early time is highly desirable. This study presents the effort in applying neural network-based system identification techniques to predict the compressive strength of concrete based on concrete mix proportions, maximum aggregate size (MAS, and slump of fresh concrete. Back-propagation neural networks model is successively developed, trained, and tested using actual data sets of concrete mix proportions gathered from literature.    The test of the model by un-used data within the range of input parameters shows that the maximum absolute error for model is about 20% and 88% of the output results has absolute errors less than 10%. The parametric study shows that water/cement ratio (w/c is the most significant factor  affecting the output of the model.     The results showed that neural networks has strong potential as a feasible tool for predicting compressive strength of concrete.

  14. Evaluating predictive models of software quality

    International Nuclear Information System (INIS)

    Ciaschini, V; Canaparo, M; Ronchieri, E; Salomoni, D

    2014-01-01

    Applications from High Energy Physics scientific community are constantly growing and implemented by a large number of developers. This implies a strong churn on the code and an associated risk of faults, which is unavoidable as long as the software undergoes active evolution. However, the necessities of production systems run counter to this. Stability and predictability are of paramount importance; in addition, a short turn-around time for the defect discovery-correction-deployment cycle is required. A way to reconcile these opposite foci is to use a software quality model to obtain an approximation of the risk before releasing a program to only deliver software with a risk lower than an agreed threshold. In this article we evaluated two quality predictive models to identify the operational risk and the quality of some software products. We applied these models to the development history of several EMI packages with intent to discover the risk factor of each product and compare it with its real history. We attempted to determine if the models reasonably maps reality for the applications under evaluation, and finally we concluded suggesting directions for further studies.

  15. A generative model for predicting terrorist incidents

    Science.gov (United States)

    Verma, Dinesh C.; Verma, Archit; Felmlee, Diane; Pearson, Gavin; Whitaker, Roger

    2017-05-01

    A major concern in coalition peace-support operations is the incidence of terrorist activity. In this paper, we propose a generative model for the occurrence of the terrorist incidents, and illustrate that an increase in diversity, as measured by the number of different social groups to which that an individual belongs, is inversely correlated with the likelihood of a terrorist incident in the society. A generative model is one that can predict the likelihood of events in new contexts, as opposed to statistical models which are used to predict the future incidents based on the history of the incidents in an existing context. Generative models can be useful in planning for persistent Information Surveillance and Reconnaissance (ISR) since they allow an estimation of regions in the theater of operation where terrorist incidents may arise, and thus can be used to better allocate the assignment and deployment of ISR assets. In this paper, we present a taxonomy of terrorist incidents, identify factors related to occurrence of terrorist incidents, and provide a mathematical analysis calculating the likelihood of occurrence of terrorist incidents in three common real-life scenarios arising in peace-keeping operations

  16. PREDICTION MODELS OF GRAIN YIELD AND CHARACTERIZATION

    Directory of Open Access Journals (Sweden)

    Narciso Ysac Avila Serrano

    2009-06-01

    Full Text Available With the objective to characterize the grain yield of five cowpea cultivars and to find linear regression models to predict it, a study was developed in La Paz, Baja California Sur, Mexico. A complete randomized blocks design was used. Simple and multivariate analyses of variance were carried out using the canonical variables to characterize the cultivars. The variables cluster per plant, pods per plant, pods per cluster, seeds weight per plant, seeds hectoliter weight, 100-seed weight, seeds length, seeds wide, seeds thickness, pods length, pods wide, pods weight, seeds per pods, and seeds weight per pods, showed significant differences (P≤ 0.05 among cultivars. Paceño and IT90K-277-2 cultivars showed the higher seeds weight per plant. The linear regression models showed correlation coefficients ≥0.92. In these models, the seeds weight per plant, pods per cluster, pods per plant, cluster per plant and pods length showed significant correlations (P≤ 0.05. In conclusion, the results showed that grain yield differ among cultivars and for its estimation, the prediction models showed determination coefficients highly dependable.

  17. Analytical modeling of subthreshold current and subthreshold swing of Gaussian-doped strained-Si-on-insulator MOSFETs

    International Nuclear Information System (INIS)

    Rawat, Gopal; Kumar, Sanjay; Goel, Ekta; Kumar, Mirgender; Jit, S.; Dubey, Sarvesh

    2014-01-01

    This paper presents the analytical modeling of subthreshold current and subthreshold swing of short-channel fully-depleted (FD) strained-Si-on-insulator (SSOI) MOSFETs having vertical Gaussian-like doping profile in the channel. The subthreshold current and subthreshold swing have been derived using the parabolic approximation method. In addition to the effect of strain on silicon layer, various other device parameters such as channel length (L), gate-oxide thickness (t ox ), strained-Si channel thickness (t s-Si ), peak doping concentration (N P ), project range (R p ) and straggle (σ p ) of the Gaussian profile have been considered while predicting the device characteristics. The present work may help to overcome the degradation in subthreshold characteristics with strain engineering. These subthreshold current and swing models provide valuable information for strained-Si MOSFET design. Accuracy of the proposed models is verified using the commercially available ATLAS™, a two-dimensional (2D) device simulator from SILVACO. (semiconductor devices)

  18. Global analysis of multi-strains SIS, SIR and MSIR epidemic models

    OpenAIRE

    Bichara , Derdei; Iggidr , Abderrahman; Sallet , Gauthier

    2014-01-01

    International audience; We consider SIS, SIR and MSIR models with standard mass action and varying population, with $n$ different pathogen strains of an infectious disease. We also consider the same models with vertical transmission. We prove that under generic conditions a competitive exclusion principle holds. To each strain a basic reproduction ratio can be associated. It corresponds to the case where only this strain exists. The basic reproduction ratio of the complete system is the maxim...

  19. Competitive exclusion principle for SIS and SIR models with n strains

    OpenAIRE

    Bichara , Derdei; Iggidr , Abderrahman; Sallet , Gauthier

    2012-01-01

    We consider SIS and SIR models with standard mass action and varying population, with $n$ different pathogen strains of an infectious disease. We also consider the same models with vertical transmission. We prove that under generic conditions a competitive exclusion principle holds. To each strain a basic reproduction ratio can be associated. It corresponds to the case where only this strain exists. The basic reproduction ratio of the complete system is the maximum of each individual basic re...

  20. Predictive Models for Normal Fetal Cardiac Structures.

    Science.gov (United States)

    Krishnan, Anita; Pike, Jodi I; McCarter, Robert; Fulgium, Amanda L; Wilson, Emmanuel; Donofrio, Mary T; Sable, Craig A

    2016-12-01

    Clinicians rely on age- and size-specific measures of cardiac structures to diagnose cardiac disease. No universally accepted normative data exist for fetal cardiac structures, and most fetal cardiac centers do not use the same standards. The aim of this study was to derive predictive models for Z scores for 13 commonly evaluated fetal cardiac structures using a large heterogeneous population of fetuses without structural cardiac defects. The study used archived normal fetal echocardiograms in representative fetuses aged 12 to 39 weeks. Thirteen cardiac dimensions were remeasured by a blinded echocardiographer from digitally stored clips. Studies with inadequate imaging views were excluded. Regression models were developed to relate each dimension to estimated gestational age (EGA) by dates, biparietal diameter, femur length, and estimated fetal weight by the Hadlock formula. Dimension outcomes were transformed (e.g., using the logarithm or square root) as necessary to meet the normality assumption. Higher order terms, quadratic or cubic, were added as needed to improve model fit. Information criteria and adjusted R 2 values were used to guide final model selection. Each Z-score equation is based on measurements derived from 296 to 414 unique fetuses. EGA yielded the best predictive model for the majority of dimensions; adjusted R 2 values ranged from 0.72 to 0.893. However, each of the other highly correlated (r > 0.94) biometric parameters was an acceptable surrogate for EGA. In most cases, the best fitting model included squared and cubic terms to introduce curvilinearity. For each dimension, models based on EGA provided the best fit for determining normal measurements of fetal cardiac structures. Nevertheless, other biometric parameters, including femur length, biparietal diameter, and estimated fetal weight provided results that were nearly as good. Comprehensive Z-score results are available on the basis of highly predictive models derived from gestational

  1. Processing plant persistent strains of Listeria monocytogenes appear to have a lower virulence potential than clinical strains in selected virulence models

    DEFF Research Database (Denmark)

    Jensen, Anne; Thomsen, L.E.; Jørgensen, R.L.

    2008-01-01

    cell line, Caco-2; time to death in a nematode model, Caenorhabditis elegans and in a fruit fly model, Drosophila melanogaster and fecal shedding in a guinea pig model. All strains adhered to and grew in Caco-2 cells in similar levels. When exposed to 10(6) CFU/ml, two strains representing......Listeria monocytogenes is an important foodborne bacterial pathogen that can colonize food processing equipment. One group of genetically similar L. monocytogenes strains (RAPID type 9) was recently shown to reside in several independent fish processing plants. Persistent strains are likely...... the persistent RAPD type 9 invaded Caco-2 cells in lower numbers (10(2)-10(3) CFU/ml) as compared to the four other strains (10(4)-10(6) CFU/ml), including food and human clinical strains. In the D. melanogaster model, the two RAPD type 9 strains were among the slowest to kill. Similarly, the time to reach 50...

  2. An analytical model for climatic predictions

    International Nuclear Information System (INIS)

    Njau, E.C.

    1990-12-01

    A climatic model based upon analytical expressions is presented. This model is capable of making long-range predictions of heat energy variations on regional or global scales. These variations can then be transformed into corresponding variations of some other key climatic parameters since weather and climatic changes are basically driven by differential heating and cooling around the earth. On the basis of the mathematical expressions upon which the model is based, it is shown that the global heat energy structure (and hence the associated climatic system) are characterized by zonally as well as latitudinally propagating fluctuations at frequencies downward of 0.5 day -1 . We have calculated the propagation speeds for those particular frequencies that are well documented in the literature. The calculated speeds are in excellent agreement with the measured speeds. (author). 13 refs

  3. An Anisotropic Hardening Model for Springback Prediction

    International Nuclear Information System (INIS)

    Zeng, Danielle; Xia, Z. Cedric

    2005-01-01

    As more Advanced High-Strength Steels (AHSS) are heavily used for automotive body structures and closures panels, accurate springback prediction for these components becomes more challenging because of their rapid hardening characteristics and ability to sustain even higher stresses. In this paper, a modified Mroz hardening model is proposed to capture realistic Bauschinger effect at reverse loading, such as when material passes through die radii or drawbead during sheet metal forming process. This model accounts for material anisotropic yield surface and nonlinear isotropic/kinematic hardening behavior. Material tension/compression test data are used to accurately represent Bauschinger effect. The effectiveness of the model is demonstrated by comparison of numerical and experimental springback results for a DP600 straight U-channel test

  4. Finite strain formulation of viscoelastic damage model for simulation of fabric reinforced polymers under dynamic loading

    Directory of Open Access Journals (Sweden)

    Treutenaere S.

    2015-01-01

    Full Text Available The use of fabric reinforced polymers in the automotive industry is growing significantly. The high specific stiffness and strength, the ease of shaping as well as the great impact performance of these materials widely encourage their diffusion. The present model increases the predictability of explicit finite element analysis and push the boundaries of the ongoing phenomenological model. Carbon fibre composites made up various preforms were tested by applying different mechanical load up to dynamic loading. This experimental campaign highlighted the physical mechanisms affecting the initial mechanical properties, namely intra- and interlaminar matrix damage, viscoelasticty and fibre failure. The intralaminar behaviour model is based on the explicit formulation of the matrix damage model developed by the ONERA as the given damage formulation correlates with the experimental observation. Coupling with a Maxwell-Wiechert model, the viscoelasticity is included without losing the direct explicit formulation. Additionally, the model is formulated under a total Lagrangian scheme in order to maintain consistency for finite strain. Thus, the material frame-indifference as well as anisotropy are ensured. This allows reorientation of fibres to be taken into account particularly for in-plane shear loading. Moreover, fall within the framework of the total Lagrangian scheme greatly makes the parameter identification easier, as based on the initial configuration. This intralaminar model thus relies upon a physical description of the behaviour of fabric composites and the numerical simulations show a good correlation with the experimental results.

  5. Constitutive modelling of the large inelastic deformation behaviour of rubber-toughened poly(methyl methacrylate): effects of strain rate, temperature and rubber-phase volume fraction

    Science.gov (United States)

    Zaïri, F.; Naït-Abdelaziz, M.; Gloaguen, J. M.; Lefebvre, J. M.

    2010-07-01

    A combined approach including experimental investigation and constitutive modelling was followed in this work to study the stress-strain behaviour of rubber-toughened glassy polymers. The large inelastic deformation response of rubber-toughened poly(methyl methacrylate) (RT-PMMA) was experimentally studied under uniaxial compression tests at different strain rates and temperatures. The studied composite system consists of spherical core-shell (PMMA hard shell and soft rubber core) particles embedded in a PMMA matrix. The influence of particle concentration (ranging from 0% to 45%) on the macroscopic behaviour was also investigated from small to large strain. The physically based hyperelastic-viscoplastic constitutive model of Boyce-Socrate-Llana was extended to describe the stress-strain behaviour of rubber-toughened glassy polymers. The model accounts for the effective contribution of the two polymeric phases to the overall composite macroscopic behaviour, by including in the original model the hyperelastic deformation of rubber particles. The capabilities of the model to describe the rate-dependent yield and post-yield behaviour of PMMA over a wide range of temperatures and strain rates are pointed out. The model is able to successfully capture the significant features of the stress-strain behaviour including the initial linear elasticity, the gradual rollover to yield, the strain softening after yield (when it exists) followed by the strain hardening. Its predictive capabilities are further tested by comparison with compression data on RT-PMMA for different rubber contents.

  6. A constitutive framework for modelling thin incompressible viscoelastic materials under plane stress in the finite strain regime

    Science.gov (United States)

    Kroon, M.

    2011-11-01

    Rubbers and soft biological tissues may undergo large deformations and are also viscoelastic. The formulation of constitutive models for these materials poses special challenges. In several applications, especially in biomechanics, these materials are also relatively thin, implying that in-plane stresses dominate and that plane stress may therefore be assumed. In the present paper, a constitutive model for viscoelastic materials in the finite strain regime and under the assumption of plane stress is proposed. It is assumed that the relaxation behaviour in the direction of plane stress can be treated separately, which makes it possible to formulate evolution laws for the plastic strains on explicit form at the same time as incompressibility is fulfilled. Experimental results from biomechanics (dynamic inflation of dog aorta) and rubber mechanics (biaxial stretching of rubber sheets) were used to assess the proposed model. The assessment clearly indicates that the model is fully able to predict the experimental outcome for these types of material.

  7. Finite element prediction of elastic strains in beryllium compact tension specimens

    International Nuclear Information System (INIS)

    Guerra, F.; Varma, R.; Bourke, M.

    1997-01-01

    Three-dimensional finite element (FE) calculations using ABAQUS version 5.5.9 were compared to neutron diffraction measurements of a loaded, pre-cracked beryllium compact tension (CT) specimens. The objective was to validate the FE results with the experimental open-quotes elastic strainclose quotes measurements. Then the FE calculations could be used to study residual stress and other aspects of these problems in the unloaded state and the crack tip stress in the loaded state which is hard to measure experimentally. A graded FE mesh was focused on the regions containing high strain gradients, the smallest elements were approximately 0.5 mm x 0.5 mm x 0.4 mm. A standard 20-node brick element model was complemented by a model with 1/4-point elements at the crack tip. Since the neutron diffraction measurements provided a volume average of approximately a cube of edge 3.0 mm, various averaging (or integrating) techniques were used on the FE results. Several integration schemes showed good agreement with the experimental results

  8. Micromechanical modeling of damage in periodic composites using strain gradient plasticity

    DEFF Research Database (Denmark)

    Azizi, Reza

    2012-01-01

    model for the fiber–matrix interface. For the micro structure, free energy holds both elastic strains and plastic strain gradients. Due to the gradient theory, higher order boundary conditions must be considered. A unit cell with a circular elastic fiber is studied by the numerical finite element cell......Damage evolution at the fiber matrix interface in Metal Matrix Composites (MMCs) is studied using strain gradient theory of plasticity. The study includes the rate independent formulation of energetic strain gradient plasticity for the matrix, purely elastic model for the fiber and cohesive zone...... model under simple shear and transverse uniaxial tension using plane strain and periodic boundary conditions. The result of the overall response curve, effective plastic strain, effective stress and higher order stress distributions are shown. The effect of the material length scale, maximum stress...

  9. The dynamic compressive behavior and constitutive modeling of D1 railway wheel steel over a wide range of strain rates and temperatures

    Directory of Open Access Journals (Sweden)

    Lin Jing

    Full Text Available The dynamic compressive behavior of D1 railway wheel steel at high strain rates was investigated using a split Hopkinson pressure bar (SHPB apparatus. Three types of specimens, which were derived from the different positions (i.e., the rim, web and hub of a railway wheel, were tested over a wide range of strain rates from 10−3 s−1 to 2.4 × 103 s−1 and temperatures from 213 K to 973 K. Influences of the strain rate and temperature on flow stress were discussed, and rate- and temperature-dependent constitutive relationships were assessed by the Cowper-Symonds model, Johnson-Cook model and a physically-based model, respectively. The experimental results show that the compressive true stress versus true strain response of D1 wheel steel is strain rate-dependent, and the strain hardening rate during the plastic flow stage decreases with the elevation of strain rate. Besides, the D1 wheel steel displays obvious temperature-dependence, and the third-type strain aging (3rd SA is occurred at the temperature region of 673–973 K at a strain rate of ∼1500 s−1. Comparisons of experimental results with theoretical predictions indicate that the physically-based model has a better prediction capability for the 3rd SA characteristic of the tested D1 wheel steel. Keywords: Railway wheel steel, SHPB, Strain rate, Temperature effect, Strain aging

  10. Web tools for predictive toxicology model building.

    Science.gov (United States)

    Jeliazkova, Nina

    2012-07-01

    The development and use of web tools in chemistry has accumulated more than 15 years of history already. Powered by the advances in the Internet technologies, the current generation of web systems are starting to expand into areas, traditional for desktop applications. The web platforms integrate data storage, cheminformatics and data analysis tools. The ease of use and the collaborative potential of the web is compelling, despite the challenges. The topic of this review is a set of recently published web tools that facilitate predictive toxicology model building. The focus is on software platforms, offering web access to chemical structure-based methods, although some of the frameworks could also provide bioinformatics or hybrid data analysis functionalities. A number of historical and current developments are cited. In order to provide comparable assessment, the following characteristics are considered: support for workflows, descriptor calculations, visualization, modeling algorithms, data management and data sharing capabilities, availability of GUI or programmatic access and implementation details. The success of the Web is largely due to its highly decentralized, yet sufficiently interoperable model for information access. The expected future convergence between cheminformatics and bioinformatics databases provides new challenges toward management and analysis of large data sets. The web tools in predictive toxicology will likely continue to evolve toward the right mix of flexibility, performance, scalability, interoperability, sets of unique features offered, friendly user interfaces, programmatic access for advanced users, platform independence, results reproducibility, curation and crowdsourcing utilities, collaborative sharing and secure access.

  11. [Endometrial cancer: Predictive models and clinical impact].

    Science.gov (United States)

    Bendifallah, Sofiane; Ballester, Marcos; Daraï, Emile

    2017-12-01

    In France, in 2015, endometrial cancer (CE) is the first gynecological cancer in terms of incidence and the fourth cause of cancer of the woman. About 8151 new cases and nearly 2179 deaths have been reported. Treatments (surgery, external radiotherapy, brachytherapy and chemotherapy) are currently delivered on the basis of an estimation of the recurrence risk, an estimation of lymph node metastasis or an estimate of survival probability. This risk is determined on the basis of prognostic factors (clinical, histological, imaging, biological) taken alone or grouped together in the form of classification systems, which are currently insufficient to account for the evolutionary and prognostic heterogeneity of endometrial cancer. For endometrial cancer, the concept of mathematical modeling and its application to prediction have developed in recent years. These biomathematical tools have opened a new era of care oriented towards the promotion of targeted therapies and personalized treatments. Many predictive models have been published to estimate the risk of recurrence and lymph node metastasis, but a tiny fraction of them is sufficiently relevant and of clinical utility. The optimization tracks are multiple and varied, suggesting the possibility in the near future of a place for these mathematical models. The development of high-throughput genomics is likely to offer a more detailed molecular characterization of the disease and its heterogeneity. Copyright © 2017 Société Française du Cancer. Published by Elsevier Masson SAS. All rights reserved.

  12. Predictive Capability Maturity Model for computational modeling and simulation.

    Energy Technology Data Exchange (ETDEWEB)

    Oberkampf, William Louis; Trucano, Timothy Guy; Pilch, Martin M.

    2007-10-01

    The Predictive Capability Maturity Model (PCMM) is a new model that can be used to assess the level of maturity of computational modeling and simulation (M&S) efforts. The development of the model is based on both the authors experience and their analysis of similar investigations in the past. The perspective taken in this report is one of judging the usefulness of a predictive capability that relies on the numerical solution to partial differential equations to better inform and improve decision making. The review of past investigations, such as the Software Engineering Institute's Capability Maturity Model Integration and the National Aeronautics and Space Administration and Department of Defense Technology Readiness Levels, indicates that a more restricted, more interpretable method is needed to assess the maturity of an M&S effort. The PCMM addresses six contributing elements to M&S: (1) representation and geometric fidelity, (2) physics and material model fidelity, (3) code verification, (4) solution verification, (5) model validation, and (6) uncertainty quantification and sensitivity analysis. For each of these elements, attributes are identified that characterize four increasing levels of maturity. Importantly, the PCMM is a structured method for assessing the maturity of an M&S effort that is directed toward an engineering application of interest. The PCMM does not assess whether the M&S effort, the accuracy of the predictions, or the performance of the engineering system satisfies or does not satisfy specified application requirements.

  13. Report on an Assessment of the Application of EPP Results from the Strain Limit Evaluation Procedure to the Prediction of Cyclic Life Based on the SMT Methodology

    Energy Technology Data Exchange (ETDEWEB)

    Jetter, R. I. [R. I. Jetter Consulting, Pebble Beach, CA (United States); Messner, M. C. [Argonne National Lab. (ANL), Argonne, IL (United States); Sham, T. -L. [Argonne National Lab. (ANL), Argonne, IL (United States); Wang, Y. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)

    2017-08-01

    The goal of the proposed integrated Elastic Perfectly-Plastic (EPP) and Simplified Model Test (SMT) methodology is to incorporate an SMT data based approach for creep-fatigue damage evaluation into the EPP methodology to avoid the separate evaluation of creep and fatigue damage and eliminate the requirement for stress classification in current methods; thus greatly simplifying evaluation of elevated temperature cyclic service. This methodology should minimize over-conservatism while properly accounting for localized defects and stress risers. To support the implementation of the proposed methodology and to verify the applicability of the code rules, analytical studies and evaluation of thermomechanical test results continued in FY17. This report presents the results of those studies. An EPP strain limits methodology assessment was based on recent two-bar thermal ratcheting test results on 316H stainless steel in the temperature range of 405 to 7050C. Strain range predictions from the EPP evaluation of the two-bar tests were also evaluated and compared with the experimental results. The role of sustained primary loading on cyclic life was assessed using the results of pressurized SMT data from tests on Alloy 617 at 9500C. A viscoplastic material model was used in an analytic simulation of two-bar tests to compare with EPP strain limits assessments using isochronous stress strain curves that are consistent with the viscoplastic material model. A finite element model of a prior 304H stainless steel Oak Ridge National Laboratory (ORNL) nozzle-to-sphere test was developed and used for an EPP strain limits and creep-fatigue code case damage evaluations. A theoretical treatment of a recurring issue with convergence criteria for plastic shakedown illustrated the role of computer machine precision in EPP calculations.

  14. Predictions of models for environmental radiological assessment

    International Nuclear Information System (INIS)

    Peres, Sueli da Silva; Lauria, Dejanira da Costa; Mahler, Claudio Fernando

    2011-01-01

    In the field of environmental impact assessment, models are used for estimating source term, environmental dispersion and transfer of radionuclides, exposure pathway, radiation dose and the risk for human beings Although it is recognized that the specific information of local data are important to improve the quality of the dose assessment results, in fact obtaining it can be very difficult and expensive. Sources of uncertainties are numerous, among which we can cite: the subjectivity of modelers, exposure scenarios and pathways, used codes and general parameters. The various models available utilize different mathematical approaches with different complexities that can result in different predictions. Thus, for the same inputs different models can produce very different outputs. This paper presents briefly the main advances in the field of environmental radiological assessment that aim to improve the reliability of the models used in the assessment of environmental radiological impact. The intercomparison exercise of model supplied incompatible results for 137 Cs and 60 Co, enhancing the need for developing reference methodologies for environmental radiological assessment that allow to confront dose estimations in a common comparison base. The results of the intercomparison exercise are present briefly. (author)

  15. Modelling Sporangiospore-yeast transformation of Dimorphomyces strain.

    Science.gov (United States)

    Omoifo, C O

    1996-01-01

    Two types of buffered media, strictly defined-Ammonium sulphate-basal salts and complex Peptone-basal salts, were used for the cultivation of Dimorphomyces pleomorphis, one of two dimorphic fungi isolated from fermenting juice of soursop fruit, Annona muricata L. The growth count was taken every twenty-four hours. Transient morphologies were observed to change from sporangiospores through enlarged globose cells, to granular particles and eventually, polar budding yeast cells in the strictly defined medium at 15 degrees, 20 degrees, or 37 degrees C, but the complex medium casually terminally induced polar budding yeast cells and multipolar budding yeast like cells in between the growth phases, at 15 degrees and 20 degrees C, while mainly multipolar budding yeastlike morphology was observed at elevated temperature. There was obvious influence of nutritional factor or morphological expression (p < 0.01). After analysis of variance, the growth data could not fit into predictive quadratic polynomial model because the organism's response curves were incongruent with basic assumptions of the model. Furthermore, a stepwise regression analysis gave very low coefficients of determination, r2, for the interactive combinations. They were therefore, considered unfit for the data. Construction of the pII-profiles led to inference being drawn from the chemiosmotic theory, polyelectrolyte theory to account for the behaviour in the buffered multiionic media. It was also thought that inherent cellular mitotic division and glycolytic activity led to a prelogarithmic growth response.

  16. Strain Echocardiography Improves Risk Prediction of Ventricular Arrhythmias After Myocardial Infarction

    DEFF Research Database (Denmark)

    Haugaa, Kristina H; Grenne, Bjørnar L; Eek, Christian H

    2013-01-01

    The aim of this study was to test the hypothesis that strain echocardiography might improve arrhythmic risk stratification in patients after myocardial infarction (MI).......The aim of this study was to test the hypothesis that strain echocardiography might improve arrhythmic risk stratification in patients after myocardial infarction (MI)....

  17. Effect on Prediction when Modeling Covariates in Bayesian Nonparametric Models.

    Science.gov (United States)

    Cruz-Marcelo, Alejandro; Rosner, Gary L; Müller, Peter; Stewart, Clinton F

    2013-04-01

    In biomedical research, it is often of interest to characterize biologic processes giving rise to observations and to make predictions of future observations. Bayesian nonparametric methods provide a means for carrying out Bayesian inference making as few assumptions about restrictive parametric models as possible. There are several proposals in the literature for extending Bayesian nonparametric models to include dependence on covariates. Limited attention, however, has been directed to the following two aspects. In this article, we examine the effect on fitting and predictive performance of incorporating covariates in a class of Bayesian nonparametric models by one of two primary ways: either in the weights or in the locations of a discrete random probability measure. We show that different strategies for incorporating continuous covariates in Bayesian nonparametric models can result in big differences when used for prediction, even though they lead to otherwise similar posterior inferences. When one needs the predictive density, as in optimal design, and this density is a mixture, it is better to make the weights depend on the covariates. We demonstrate these points via a simulated data example and in an application in which one wants to determine the optimal dose of an anticancer drug used in pediatric oncology.

  18. Stress/strain Modelling of Casting Processes in the Framework of the Control-Volume Method

    DEFF Research Database (Denmark)

    Hattel, Jesper Henri; Thorborg, Jesper; Andersen, Søren

    1998-01-01

    Realistic computer simulations of casting processes call for the solution of both thermal, fluid-flow and stress/strain related problems. The multitude of the influencing parameters, and their non-linear, transient and temperature dependent nature, make the calculations complex. Therefore the need......, the present model is based on the mainly decoupled representation of the thermal, mechanical and microstructural processes. Examples of industrial applications, such as predicting residual deformations in castings and stress levels in die casting dies, are presented...... domain, which is highly convenient. The basis of the method is the control volume finite difference approach on structured meshes. The basic assumptions of the method are shortly reviewed and discussed. As for other methods which aim at application oriented analysis of casting deformations and stresses...

  19. Combining GPS measurements and IRI model predictions

    International Nuclear Information System (INIS)

    Hernandez-Pajares, M.; Juan, J.M.; Sanz, J.; Bilitza, D.

    2002-01-01

    The free electrons distributed in the ionosphere (between one hundred and thousands of km in height) produce a frequency-dependent effect on Global Positioning System (GPS) signals: a delay in the pseudo-orange and an advance in the carrier phase. These effects are proportional to the columnar electron density between the satellite and receiver, i.e. the integrated electron density along the ray path. Global ionospheric TEC (total electron content) maps can be obtained with GPS data from a network of ground IGS (international GPS service) reference stations with an accuracy of few TEC units. The comparison with the TOPEX TEC, mainly measured over the oceans far from the IGS stations, shows a mean bias and standard deviation of about 2 and 5 TECUs respectively. The discrepancies between the STEC predictions and the observed values show an RMS typically below 5 TECUs (which also includes the alignment code noise). he existence of a growing database 2-hourly global TEC maps and with resolution of 5x2.5 degrees in longitude and latitude can be used to improve the IRI prediction capability of the TEC. When the IRI predictions and the GPS estimations are compared for a three month period around the Solar Maximum, they are in good agreement for middle latitudes. An over-determination of IRI TEC has been found at the extreme latitudes, the IRI predictions being, typically two times higher than the GPS estimations. Finally, local fits of the IRI model can be done by tuning the SSN from STEC GPS observations

  20. Mathematical models for indoor radon prediction

    International Nuclear Information System (INIS)

    Malanca, A.; Pessina, V.; Dallara, G.

    1995-01-01

    It is known that the indoor radon (Rn) concentration can be predicted by means of mathematical models. The simplest model relies on two variables only: the Rn source strength and the air exchange rate. In the Lawrence Berkeley Laboratory (LBL) model several environmental parameters are combined into a complex equation; besides, a correlation between the ventilation rate and the Rn entry rate from the soil is admitted. The measurements were carried out using activated carbon canisters. Seventy-five measurements of Rn concentrations were made inside two rooms placed on the second floor of a building block. One of the rooms had a single-glazed window whereas the other room had a double pane window. During three different experimental protocols, the mean Rn concentration was always higher into the room with a double-glazed window. That behavior can be accounted for by the simplest model. A further set of 450 Rn measurements was collected inside a ground-floor room with a grounding well in it. This trend maybe accounted for by the LBL model

  1. A Predictive Maintenance Model for Railway Tracks

    DEFF Research Database (Denmark)

    Li, Rui; Wen, Min; Salling, Kim Bang

    2015-01-01

    presents a mathematical model based on Mixed Integer Programming (MIP) which is designed to optimize the predictive railway tamping activities for ballasted track for the time horizon up to four years. The objective function is setup to minimize the actual costs for the tamping machine (measured by time......). Five technical and economic aspects are taken into account to schedule tamping: (1) track degradation of the standard deviation of the longitudinal level over time; (2) track geometrical alignment; (3) track quality thresholds based on the train speed limits; (4) the dependency of the track quality...... recovery on the track quality after tamping operation and (5) Tamping machine operation factors. A Danish railway track between Odense and Fredericia with 57.2 km of length is applied for a time period of two to four years in the proposed maintenance model. The total cost can be reduced with up to 50...

  2. Accelerating early anti-tuberculosis drug discovery by creating mycobacterial indicator strains that predict mode of action

    KAUST Repository

    Boot, Maikel

    2018-04-13

    Due to the rise of drug resistant forms of tuberculosis there is an urgent need for novel antibiotics to effectively combat these cases and shorten treatment regimens. Recently, drug screens using whole cell analyses have been shown to be successful. However, current high-throughput screens focus mostly on stricto sensu life-death screening that give little qualitative information. In doing so, promising compound scaffolds or non-optimized compounds that fail to reach inhibitory concentrations are missed. To accelerate early TB drug discovery, we performed RNA sequencing on Mycobacterium tuberculosis and Mycobacterium marinum to map the stress responses that follow upon exposure to sub-inhibitory concentrations of antibiotics with known targets: ciprofloxacin, ethambutol, isoniazid, streptomycin and rifampicin. The resulting dataset comprises the first overview of transcriptional stress responses of mycobacteria to different antibiotics. We show that antibiotics can be distinguished based on their specific transcriptional stress fingerprint. Notably, this fingerprint was more distinctive in M. marinum. We decided to use this to our advantage and continue with this model organism. A selection of diverse antibiotic stress genes was used to construct stress reporters. In total, three functional reporters were constructed to respond to DNA damage, cell wall damage and ribosomal inhibition. Subsequently, these reporter strains were used to screen a small anti-TB compound library to predict the mode of action. In doing so, we could identify the putative mode of action for three novel compounds, which confirms our approach.

  3. An Operational Model for the Prediction of Jet Blast

    Science.gov (United States)

    2012-01-09

    This paper presents an operational model for the prediction of jet blast. The model was : developed based upon three modules including a jet exhaust model, jet centerline decay : model and aircraft motion model. The final analysis was compared with d...

  4. Continuous-Discrete Time Prediction-Error Identification Relevant for Linear Model Predictive Control

    DEFF Research Database (Denmark)

    Jørgensen, John Bagterp; Jørgensen, Sten Bay

    2007-01-01

    A Prediction-error-method tailored for model based predictive control is presented. The prediction-error method studied are based on predictions using the Kalman filter and Kalman predictors for a linear discrete-time stochastic state space model. The linear discrete-time stochastic state space...... model is realized from a continuous-discrete-time linear stochastic system specified using transfer functions with time-delays. It is argued that the prediction-error criterion should be selected such that it is compatible with the objective function of the predictive controller in which the model...

  5. A Continuum Damage Mechanics Model to Predict Kink-Band Propagation Using Deformation Gradient Tensor Decomposition

    Science.gov (United States)

    Bergan, Andrew C.; Leone, Frank A., Jr.

    2016-01-01

    A new model is proposed that represents the kinematics of kink-band formation and propagation within the framework of a mesoscale continuum damage mechanics (CDM) model. The model uses the recently proposed deformation gradient decomposition approach to represent a kink band as a displacement jump via a cohesive interface that is embedded in an elastic bulk material. The model is capable of representing the combination of matrix failure in the frame of a misaligned fiber and instability due to shear nonlinearity. In contrast to conventional linear or bilinear strain softening laws used in most mesoscale CDM models for longitudinal compression, the constitutive response of the proposed model includes features predicted by detailed micromechanical models. These features include: 1) the rotational kinematics of the kink band, 2) an instability when the peak load is reached, and 3) a nonzero plateau stress under large strains.

  6. Effect of large elastic strains on cavitation instability predictions for elastic-plastic solids

    DEFF Research Database (Denmark)

    Tvergaard, Viggo

    1999-01-01

    For an infinite solid containing a void, the cavitation instability limit is defined as the remote stress-and strain state, at which the void grows without bound, driven by the elastic energy stored in the surrounding material. Such cavitation limits have been analysed by a number of authors...... hydrostatic tension as well as for more general axisymmetric remote stress field, with an initially spherical void. Different levels of strain hardening are considered. (C) 1998 Elsevier Science Ltd. All rights reserved....

  7. Predictive modeling: potential application in prevention services.

    Science.gov (United States)

    Wilson, Moira L; Tumen, Sarah; Ota, Rissa; Simmers, Anthony G

    2015-05-01

    In 2012, the New Zealand Government announced a proposal to introduce predictive risk models (PRMs) to help professionals identify and assess children at risk of abuse or neglect as part of a preventive early intervention strategy, subject to further feasibility study and trialing. The purpose of this study is to examine technical feasibility and predictive validity of the proposal, focusing on a PRM that would draw on population-wide linked administrative data to identify newborn children who are at high priority for intensive preventive services. Data analysis was conducted in 2013 based on data collected in 2000-2012. A PRM was developed using data for children born in 2010 and externally validated for children born in 2007, examining outcomes to age 5 years. Performance of the PRM in predicting administratively recorded substantiations of maltreatment was good compared to the performance of other tools reviewed in the literature, both overall, and for indigenous Māori children. Some, but not all, of the children who go on to have recorded substantiations of maltreatment could be identified early using PRMs. PRMs should be considered as a potential complement to, rather than a replacement for, professional judgment. Trials are needed to establish whether risks can be mitigated and PRMs can make a positive contribution to frontline practice, engagement in preventive services, and outcomes for children. Deciding whether to proceed to trial requires balancing a range of considerations, including ethical and privacy risks and the risk of compounding surveillance bias. Crown Copyright © 2015. Published by Elsevier Inc. All rights reserved.

  8. Prediction of crack growth direction by Strain Energy Sih's Theory on specimens SEN under tension-compression biaxial loading employing Genetic Algorithms

    International Nuclear Information System (INIS)

    Rodriguez-MartInez R; Lugo-Gonzalez E; Urriolagoitia-Calderon G; Urriolagoitia-Sosa G; Hernandez-Gomez L H; Romero-Angeles B; Torres-San Miguel Ch

    2011-01-01

    Crack growth direction has been studied in many ways. Particularly Sih's strain energy theory predicts that a fracture under a three-dimensional state of stress spreads in direction of the minimum strain energy density. In this work a study for angle of fracture growth was made, considering a biaxial stress state at the crack tip on SEN specimens. The stress state applied on a tension-compression SEN specimen is biaxial one on crack tip, as it can observed in figure 1. A solution method proposed to obtain a mathematical model considering genetic algorithms, which have demonstrated great capacity for the solution of many engineering problems. From the model given by Sih one can deduce the density of strain energy stored for unit of volume at the crack tip as dW = [1/2E(σ 2 x + σ 2 y ) - ν/E(σ x σy)]dV (1). From equation (1) a mathematical deduction to solve in terms of θ of this case was developed employing Genetic Algorithms, where θ is a crack propagation direction in plane x-y. Steel and aluminium mechanical properties to modelled specimens were employed, because they are two of materials but used in engineering design. Obtained results show stable zones of fracture propagation but only in a range of applied loading.

  9. Heuristic Modeling for TRMM Lifetime Predictions

    Science.gov (United States)

    Jordan, P. S.; Sharer, P. J.; DeFazio, R. L.

    1996-01-01

    Analysis time for computing the expected mission lifetimes of proposed frequently maneuvering, tightly altitude constrained, Earth orbiting spacecraft have been significantly reduced by means of a heuristic modeling method implemented in a commercial-off-the-shelf spreadsheet product (QuattroPro) running on a personal computer (PC). The method uses a look-up table to estimate the maneuver frequency per month as a function of the spacecraft ballistic coefficient and the solar flux index, then computes the associated fuel use by a simple engine model. Maneuver frequency data points are produced by means of a single 1-month run of traditional mission analysis software for each of the 12 to 25 data points required for the table. As the data point computations are required only a mission design start-up and on the occasion of significant mission redesigns, the dependence on time consuming traditional modeling methods is dramatically reduced. Results to date have agreed with traditional methods to within 1 to 1.5 percent. The spreadsheet approach is applicable to a wide variety of Earth orbiting spacecraft with tight altitude constraints. It will be particularly useful to such missions as the Tropical Rainfall Measurement Mission scheduled for launch in 1997, whose mission lifetime calculations are heavily dependent on frequently revised solar flux predictions.

  10. A Computational Model for Predicting Gas Breakdown

    Science.gov (United States)

    Gill, Zachary

    2017-10-01

    Pulsed-inductive discharges are a common method of producing a plasma. They provide a mechanism for quickly and efficiently generating a large volume of plasma for rapid use and are seen in applications including propulsion, fusion power, and high-power lasers. However, some common designs see a delayed response time due to the plasma forming when the magnitude of the magnetic field in the thruster is at a minimum. New designs are difficult to evaluate due to the amount of time needed to construct a new geometry and the high monetary cost of changing the power generation circuit. To more quickly evaluate new designs and better understand the shortcomings of existing designs, a computational model is developed. This model uses a modified single-electron model as the basis for a Mathematica code to determine how the energy distribution in a system changes with regards to time and location. By analyzing this energy distribution, the approximate time and location of initial plasma breakdown can be predicted. The results from this code are then compared to existing data to show its validity and shortcomings. Missouri S&T APLab.

  11. Distributed model predictive control made easy

    CERN Document Server

    Negenborn, Rudy

    2014-01-01

    The rapid evolution of computer science, communication, and information technology has enabled the application of control techniques to systems beyond the possibilities of control theory just a decade ago. Critical infrastructures such as electricity, water, traffic and intermodal transport networks are now in the scope of control engineers. The sheer size of such large-scale systems requires the adoption of advanced distributed control approaches. Distributed model predictive control (MPC) is one of the promising control methodologies for control of such systems.   This book provides a state-of-the-art overview of distributed MPC approaches, while at the same time making clear directions of research that deserve more attention. The core and rationale of 35 approaches are carefully explained. Moreover, detailed step-by-step algorithmic descriptions of each approach are provided. These features make the book a comprehensive guide both for those seeking an introduction to distributed MPC as well as for those ...

  12. Numerical method for a 2D drift diffusion model arising in strained n ...

    Indian Academy of Sciences (India)

    This paper reports the calculation of electron transport in metal oxide semiconductor field effects transistors (MOSFETs) with biaxially tensile strained silicon channel. The calculation is formulated based on two-dimensional drift diffusion model (DDM) including strain effects. The carrier mobility dependence on the lateral and ...

  13. Modelling plastic deformation of metals over a wide range of strain rates using irreversible thermodynamics

    NARCIS (Netherlands)

    Huang, M.; Rivera-Diaz-del-Castillo, P.E.J.; Bouaziz, O.; Van der Zwaag, S.

    2009-01-01

    Based on the theory of irreversible thermodynamics, the present work proposes a dislocation-based model to describe the plastic deformation of FCC metals over wide ranges of strain rates. The stress-strain behaviour and the evolution of the average dislocation density are derived. It is found that

  14. Consistent stress-strain ductile fracture model as applied to two grades of beryllium

    International Nuclear Information System (INIS)

    Priddy, T.G.; Benzley, S.E.; Ford, L.M.

    1980-01-01

    Published yield and ultimate biaxial stress and strain data for two grades of beryllium are correlated with a more complete method of characterizing macroscopic strain at fracture initiation in ductile materials. Results are compared with those obtained from an exponential, mean stress dependent, model. Simple statistical methods are employed to illustrate the degree of correlation for each method with the experimental data

  15. Which method predicts recidivism best?: A comparison of statistical, machine learning, and data mining predictive models

    OpenAIRE

    Tollenaar, N.; van der Heijden, P.G.M.

    2012-01-01

    Using criminal population conviction histories of recent offenders, prediction mod els are developed that predict three types of criminal recidivism: general recidivism, violent recidivism and sexual recidivism. The research question is whether prediction techniques from modern statistics, data mining and machine learning provide an improvement in predictive performance over classical statistical methods, namely logistic regression and linear discrim inant analysis. These models are compared ...

  16. Strain analysis in the Orijärvi triangle, southwestern Finland; in perspective of tectonic models

    Directory of Open Access Journals (Sweden)

    Stel, H.

    1999-12-01

    Full Text Available Finite strain analyses were performed in metavolcanic rocks (agglomerates and pillowed metabasalts from the Orijärvi area, southwestern Finland. In this area, tight folding (F1 of layered metasedimentary rocks and development of a penetrative axial plane schistosity (S1 took place during an early stage in the Svecofennian orogeny. Within the domain, there is no evidence of older deformational structures or of a later deformation phase; except in narrow, late-stage shear zones that bound the Orijärvi triangle. During the orogenic evolution, a pervasive attenuation of the fabric in metavolcanic rocks has taken place. In order to quantify strain intensity and to investigate the relation of strain in metavolcanics and folding in metasediments, strain analyses were performed by the Rf/φ method on (subelliptical markers. Metavolcanic rocks demonstrate relatively homogeneous strain values on the outcrop scale, but strain parameters vary strongly on the scale of the study area. This variation in strain correlates with variation in rock composition; felsic metavolcanics demonstrate consistently lower strain intensities than mafic ones. Finite strain ellipsoids are prolate, indicating that the rocks underwent apparent constriction. X axes of strain are(subparallel to the regional fold axis. Constriction in the Orijärvi triangle is not in conflict with any of the current tectonic models. However, given the local structural setting, the most straightforward interpretation is that of progressive constriction by plutonic diapirism.

  17. A Model for High-Strain-Rate Deformation of Uranium-Niobium Alloys

    Energy Technology Data Exchange (ETDEWEB)

    F.L.Addessio; Q.H.Zuo; T.A.Mason; L.C.Brinson

    2003-05-01

    A thermodynamic approach is used to develop a framework for modeling uranium-niobium alloys under the conditions of high strain rate. Using this framework, a three-dimensional phenomenological model, which includes nonlinear elasticity (equation of state), phase transformation, crystal reorientation, rate-dependent plasticity, and porosity growth is presented. An implicit numerical technique is used to solve the evolution equations for the material state. Comparisons are made between the model and data for low-strain-rate loading and unloading as well as for heating and cooling experiments. Comparisons of the model and data also are made for low- and high-strain-rate uniaxial stress and uniaxial strain experiments. A uranium-6 weight percent niobium alloy is used in the comparisons of model and experiment.

  18. Predictive value of cardiac magnetic resonance imaging-derived myocardial strain for poor outcomes in patients with acute myocarditis

    Energy Technology Data Exchange (ETDEWEB)

    Lee, Ji Won; Jeong, Yeon Joo; Lee, Gee Won; Lee, Nam Kyung; Lee, Hye Won; Kim, Jin You [Pusan National University School of Medicine and Medical Research Institute, Pusan National University Hospital, Busan (Korea, Republic of); Choi, Bum Sung; Choo, Ki Seok [Pusan National University Yangsan Hospital, Yangsan (Korea, Republic of)

    2017-08-01

    To evaluate the utility of cardiovascular magnetic resonance (CMR)-derived myocardial strain measurement for the prediction of poor outcomes in patients with acute myocarditis We retrospectively analyzed data from 37 patients with acute myocarditis who underwent CMR. Left ventricular (LV) size, LV mass index, ejection fraction and presence of myocardial late gadolinium enhancement (LGE) were analyzed. LV circumferential strain (EccSAX), radial strain (ErrSAX) from mid-ventricular level short-axis cine views and LV longitudinal strain (EllLV), radial strain (ErrLax) measurements from 2-chamber long-axis views were obtained. In total, 31 of 37 patients (83.8%) underwent follow-up echocardiography. The primary outcome was major adverse cardiovascular event (MACE). Incomplete LV functional recovery was a secondary outcome. During an average follow-up of 41 months, 11 of 37 patients (29.7%) experienced MACE. Multivariable Cox proportional hazard regression analysis, which included LV mass index, LV ejection fraction, the presence of LGE, EccSAX, ErrSAX, EllLV, and ErrLax values, indicated that the presence of LGE (hazard ratio, 42.88; p = 0.014), together with ErrLax (hazard ratio, 0.77 per 1%, p = 0.004), was a significant predictor of MACE. Kaplan-Meier analysis demonstrated worse outcomes in patient with LGE and an ErrLax value ≤ 9.48%. Multivariable backward regression analysis revealed that ErrLax values were the only significant predictors of LV functional recovery (hazard ratio, 0.54 per 1%; p = 0.042). CMR-derived ErrLax values can predict poor outcomes, both MACE and incomplete LV functional recovery, in patients with acute myocarditis, while LGE is only a predictor of MACE.

  19. Modeling mechanical signals on the surface of µCT and CAD based rapid prototype scaffold models to predict (early stage) tissue development.

    Science.gov (United States)

    Hendrikson, W J; van Blitterswijk, C A; Verdonschot, N; Moroni, L; Rouwkema, J

    2014-09-01

    In the field of tissue engineering, mechano-regulation theories have been applied to help predict tissue development in tissue engineering scaffolds in the past. For this, finite element models (FEMs) were used to predict the distribution of strains within a scaffold. However, the strains reported in these studies are volumetric strains of the material or strains developed in the extracellular matrix occupying the pore space. The initial phase of cell attachment and growth on the biomaterial surface has thus far been neglected. In this study, we present a model that determines the magnitude of biomechanical signals on the biomaterial surface, enabling us to predict cell differentiation stimulus values at this initial stage. Results showed that magnitudes of the 2D strain--termed surface strain--were lower when compared to the 3D volumetric strain or the conventional octahedral shear strain as used in current mechano-regulation theories. Results of both µCT and CAD derived FEMs from the same scaffold were compared. Strain and fluid shear stress distributions, and subsequently the cell differentiation stimulus, were highly dependent on the pore shape. CAD models were not able to capture the distributions seen in the µCT FEM. The calculated mechanical stimuli could be combined with current mechanobiological models resulting in a tool to predict cell differentiation in the initial phase of tissue engineering. Although experimental data is still necessary to properly link mechanical signals to cell behavior in this specific setting, this model is an important step towards optimizing scaffold architecture and/or stimulation regimes. © 2014 Wiley Periodicals, Inc.

  20. Fuzzy predictive filtering in nonlinear economic model predictive control for demand response

    DEFF Research Database (Denmark)

    Santos, Rui Mirra; Zong, Yi; Sousa, Joao M. C.

    2016-01-01

    The performance of a model predictive controller (MPC) is highly correlated with the model's accuracy. This paper introduces an economic model predictive control (EMPC) scheme based on a nonlinear model, which uses a branch-and-bound tree search for solving the inherent non-convex optimization...

  1. Experimentally derived model to predict permeability behavior of mudstones

    Science.gov (United States)

    Schneider, J.; Flemings, P. B.; Day-Stirrat, R.; Germaine, J. T.

    2010-12-01

    We use uniaxial consolidation experiments to analyze the permeability evolution during consolidation for mudstones with varying composition to develop a predictive permeability model for mudstones. We admixed silt-sized silica to dry, natural Boston Blue Clay (BBC) powder in five different mass ratios. The result is mixtures of silty clay and clayey silt with percentages of clay-sized particles varying between 36 % and 57 %. To recreate natural conditions yet remove variability and soil disturbance, we resedimented all mixtures to a total stress of 100 kPa. We then loaded them to a vertical effective stress of 2.4 MPa in an uniaxial, constant-rate-of-strain consolidation device. We show that vertical permeability increases exponentially with void ratio and decreasing clay content. There is an order of magnitude difference in permeability at a given void ratio for clay contents varying from 36 % to 57 % (by mass). We developed a model that predicts the permeability of silt-clay mixtures based on knowledge of the composition and void ratio alone. The model assumes that flow occurs through the clay-matrix. Thus, the effective permeability is controlled by the void ratio of the clay fraction. At a given stress level, the clay void ratio increases with silt content: large pores are preserved in silty samples due to stress-bridging which does not allow the clay particles to consolidate. Mudstones are important to practical and fundamental programs. They are a key cap rock for subsurface hydrocarbons and geologic storage of CO2. Over the last decade, large amounts of natural gas have been produced from mudstone (shale) gas fields.

  2. Theoretical prediction and experimental verification of protein-coding genes in plant pathogen genome Agrobacterium tumefaciens strain C58.

    Science.gov (United States)

    Wang, Qian; Lei, Yang; Xu, Xiwen; Wang, Gejiao; Chen, Ling-Ling

    2012-01-01

    Agrobacterium tumefaciens strain C58 is a Gram-negative soil bacterium capable of inducing tumors (crown galls) on many dicotyledonous plants. The genome of A. tumefaciens strain C58 was re-annotated based on the Z-curve method. First, all the 'hypothetical genes' were re-identified, and 29 originally annotated 'hypothetical genes' were recognized to be non-coding open reading frames (ORFs). Theoretical evidence obtained from principal component analysis, clusters of orthologous groups of proteins occupation, and average length distribution showed that these non-coding ORFs were highly unlikely to encode proteins. Results from the reverse transcription-polymerase chain reaction (RT-PCR) experiments on three different growth stages of A. tumefaciens C58 confirmed that 23 (79%) of the identified non-coding ORFs have no transcripts in these growth stages. In addition, using theoretical prediction, 19 potential protein-coding genes were predicted to be new protein-coding genes. Fifteen (79%) of these genes were verified with RT-PCR experiments. The RT-PCR experimental results confirmed the reliability of our theoretical prediction, indicating that false-positive prediction and missing genes always exist in the annotation of A. tumefaciens C58 genome. The improved annotation will serve as a valuable resource for the research of the lifestyle, metabolism, and pathogenicity of A. tumefaciens C58. The re-annotation of A. tumefaciens C58 can be obtained from http://211.69.128.148/Atum/.

  3. Theoretical prediction and experimental verification of protein-coding genes in plant pathogen genome Agrobacterium tumefaciens strain C58.

    Directory of Open Access Journals (Sweden)

    Qian Wang

    Full Text Available Agrobacterium tumefaciens strain C58 is a Gram-negative soil bacterium capable of inducing tumors (crown galls on many dicotyledonous plants. The genome of A. tumefaciens strain C58 was re-annotated based on the Z-curve method. First, all the 'hypothetical genes' were re-identified, and 29 originally annotated 'hypothetical genes' were recognized to be non-coding open reading frames (ORFs. Theoretical evidence obtained from principal component analysis, clusters of orthologous groups of proteins occupation, and average length distribution showed that these non-coding ORFs were highly unlikely to encode proteins. Results from the reverse transcription-polymerase chain reaction (RT-PCR experiments on three different growth stages of A. tumefaciens C58 confirmed that 23 (79% of the identified non-coding ORFs have no transcripts in these growth stages. In addition, using theoretical prediction, 19 potential protein-coding genes were predicted to be new protein-coding genes. Fifteen (79% of these genes were verified with RT-PCR experiments. The RT-PCR experimental results confirmed the reliability of our theoretical prediction, indicating that false-positive prediction and missing genes always exist in the annotation of A. tumefaciens C58 genome. The improved annotation will serve as a valuable resource for the research of the lifestyle, metabolism, and pathogenicity of A. tumefaciens C58. The re-annotation of A. tumefaciens C58 can be obtained from http://211.69.128.148/Atum/.

  4. Investigation of Stress-Strain History Modeling at Stress Risers

    Science.gov (United States)

    1977-06-01

    4 v.FtIoOD COVEE~ tD (INVESTIGATION OF STRESS STRAIN HISM4rYI I a,.5..1 eW 96 - ,v MODEiLINGi AT STRESS RISERS, ______~ .- ,-* . - ’ LG77ERM33 - h...spacmn F 0’r of ZOY-76’ i Iyr FodIM hxrtwv.rtrjj ’ti~n Iri of o.(.1)2. morn A; 2 C0.02 ni 7,4 from F~ifuri.l /6 1i I1 17.4-0.135 for thu first CYGIa

  5. Family Members Affected by a Close Relative's Addiction: The Stress-Strain-Coping-Support Model

    Science.gov (United States)

    Orford, Jim; Copello, Alex; Velleman, Richard; Templeton, Lorna

    2010-01-01

    This article outlines the stress-strain-coping-support (SSCS) model which underpins the whole programme of work described in this supplement. The need for such a model is explained: previous models of substance misuse and the family have attributed dysfunction or deficiency to families or family members. In contrast, the SSCS model assumes that…

  6. Model for predicting mountain wave field uncertainties

    Science.gov (United States)

    Damiens, Florentin; Lott, François; Millet, Christophe; Plougonven, Riwal

    2017-04-01

    Studying the propagation of acoustic waves throughout troposphere requires knowledge of wind speed and temperature gradients from the ground up to about 10-20 km. Typical planetary boundary layers flows are known to present vertical low level shears that can interact with mountain waves, thereby triggering small-scale disturbances. Resolving these fluctuations for long-range propagation problems is, however, not feasible because of computer memory/time restrictions and thus, they need to be parameterized. When the disturbances are small enough, these fluctuations can be described by linear equations. Previous works by co-authors have shown that the critical layer dynamics that occur near the ground produces large horizontal flows and buoyancy disturbances that result in intense downslope winds and gravity wave breaking. While these phenomena manifest almost systematically for high Richardson numbers and when the boundary layer depth is relatively small compare to the mountain height, the process by which static stability affects downslope winds remains unclear. In the present work, new linear mountain gravity wave solutions are tested against numerical predictions obtained with the Weather Research and Forecasting (WRF) model. For Richardson numbers typically larger than unity, the mesoscale model is used to quantify the effect of neglected nonlinear terms on downslope winds and mountain wave patterns. At these regimes, the large downslope winds transport warm air, a so called "Foehn" effect than can impact sound propagation properties. The sensitivity of small-scale disturbances to Richardson number is quantified using two-dimensional spectral analysis. It is shown through a pilot study of subgrid scale fluctuations of boundary layer flows over realistic mountains that the cross-spectrum of mountain wave field is made up of the same components found in WRF simulations. The impact of each individual component on acoustic wave propagation is discussed in terms of

  7. Avian-Pathogenic Escherichia coli Strains Are Similar to Neonatal Meningitis E. coli Strains and Are Able To Cause Meningitis in the Rat Model of Human Disease ▿

    Science.gov (United States)

    Tivendale, Kelly A.; Logue, Catherine M.; Kariyawasam, Subhashinie; Jordan, Dianna; Hussein, Ashraf; Li, Ganwu; Wannemuehler, Yvonne; Nolan, Lisa K.

    2010-01-01

    Escherichia coli strains causing avian colibacillosis and human neonatal meningitis, urinary tract infections, and septicemia are collectively known as extraintestinal pathogenic E. coli (ExPEC). Characterization of ExPEC strains using various typing techniques has shown that they harbor many similarities, despite their isolation from different host species, leading to the hypothesis that ExPEC may have zoonotic potential. The present study examined a subset of ExPEC strains: neonatal meningitis E. coli (NMEC) strains and avian-pathogenic E. coli (APEC) strains belonging to the O18 serogroup. The study found that they were not easily differentiated on the basis of multilocus sequence typing, phylogenetic typing, or carriage of large virulence plasmids. Among the APEC strains examined, one strain was found to be an outlier, based on the results of these typing methods, and demonstrated reduced virulence in murine and avian pathogenicity models. Some of the APEC strains tested in a rat model of human neonatal meningitis were able to cause meningitis, demonstrating APEC's ability to cause disease in mammals, lending support to the hypothesis that APEC strains have zoonotic potential. In addition, some NMEC strains were able to cause avian colisepticemia, providing further support for this hypothesis. However, not all of the NMEC and APEC strains tested were able to cause disease in avian and murine hosts, despite the apparent similarities in their known virulence attributes. Thus, it appears that a subset of NMEC and APEC strains harbors zoonotic potential, while other strains do not, suggesting that unknown mechanisms underlie host specificity in some ExPEC strains. PMID:20515929

  8. Left and right ventricular dyssynchrony and strains from cardiovascular magnetic resonance feature tracking do not predict deterioration of ventricular function in patients with repaired tetralogy of Fallot.

    Science.gov (United States)

    Jing, Linyuan; Wehner, Gregory J; Suever, Jonathan D; Charnigo, Richard J; Alhadad, Sudad; Stearns, Evan; Mojsejenko, Dimitri; Haggerty, Christopher M; Hickey, Kelsey; Valente, Anne Marie; Geva, Tal; Powell, Andrew J; Fornwalt, Brandon K

    2016-08-22

    Patients with repaired tetralogy of Fallot (rTOF) suffer from progressive ventricular dysfunction decades after their surgical repair. We hypothesized that measures of ventricular strain and dyssynchrony would predict deterioration of ventricular function in patients with rTOF. A database search identified all patients at a single institution with rTOF who underwent cardiovascular magnetic resonance (CMR) at least twice, >6 months apart, without intervening surgical or catheter procedures. Seven primary predictors were derived from the first CMR using a custom feature tracking algorithm: left (LV), right (RV) and inter-ventricular dyssynchrony, LV and RV peak global circumferential strains, and LV and RV peak global longitudinal strains. Three outcomes were defined, whose changes were assessed over time: RV end-diastolic volume, and RV and LV ejection fraction. Multivariate linear mixed models were fit to investigate relationships of outcomes to predictors and ten potential baseline confounders. One hundred fifty-three patients with rTOF (23 ± 14 years, 50 % male) were included. The mean follow-up duration between the first and last CMR was 2.9 ± 1.3 years. After adjustment for confounders, none of the 7 primary predictors were significantly associated with change over time in the 3 outcome variables. Only 1-17 % of the variability in the change over time in the outcome variables was explained by the baseline predictors and potential confounders. In patients with repaired tetralogy of Fallot, ventricular dyssynchrony and global strain derived from cine CMR were not significantly related to changes in ventricular size and function over time. The ability to predict deterioration in ventricular function in patients with rTOF using current methods is limited.

  9. How fault evolution changes strain partitioning and fault slip rates in Southern California: Results from geodynamic modeling

    Science.gov (United States)

    Ye, Jiyang; Liu, Mian

    2017-08-01

    In Southern California, the Pacific-North America relative plate motion is accommodated by the complex southern San Andreas Fault system that includes many young faults (faults and their impact on strain partitioning and fault slip rates are important for understanding the evolution of this plate boundary zone and assessing earthquake hazard in Southern California. Using a three-dimensional viscoelastoplastic finite element model, we have investigated how this plate boundary fault system has evolved to accommodate the relative plate motion in Southern California. Our results show that when the plate boundary faults are not optimally configured to accommodate the relative plate motion, strain is localized in places where new faults would initiate to improve the mechanical efficiency of the fault system. In particular, the Eastern California Shear Zone, the San Jacinto Fault, the Elsinore Fault, and the offshore dextral faults all developed in places of highly localized strain. These younger faults compensate for the reduced fault slip on the San Andreas Fault proper because of the Big Bend, a major restraining bend. The evolution of the fault system changes the apportionment of fault slip rates over time, which may explain some of the slip rate discrepancy between geological and geodetic measurements in Southern California. For the present fault configuration, our model predicts localized strain in western Transverse Ranges and along the dextral faults across the Mojave Desert, where numerous damaging earthquakes occurred in recent years.

  10. Dual-phase steel sheets under cyclic tension-compression to large strains: Experiments and crystal plasticity modeling

    Science.gov (United States)

    Zecevic, Milovan; Korkolis, Yannis P.; Kuwabara, Toshihiko; Knezevic, Marko

    2016-11-01

    In this work, we develop a physically-based crystal plasticity model for the prediction of cyclic tension-compression deformation of multi-phase materials, specifically dual-phase (DP) steels. The model is elasto-plastic in nature and integrates a hardening law based on statistically stored dislocation density, localized hardening due to geometrically necessary dislocations (GNDs), slip-system-level kinematic backstresses, and annihilation of dislocations. The model further features a two level homogenization scheme where the first level is the overall response of a two-phase polycrystalline aggregate and the second level is the homogenized response of the martensite polycrystalline regions. The model is applied to simulate a cyclic tension-compression-tension deformation behavior of DP590 steel sheets. From experiments, we observe that the material exhibits a typical decreasing hardening rate during forward loading, followed by a linear and then a non-linear unloading upon the load reversal, the Bauschinger effect, and changes in hardening rate during strain reversals. To predict these effects, we identify the model parameters using a portion of the measured data and validate and verify them using the remaining data. The developed model is capable of predicting all the particular features of the cyclic deformation of DP590 steel, with great accuracy. From the predictions, we infer and discuss the effects of GNDs, the backstresses, dislocation annihilation, and the two-level homogenization scheme on capturing the cyclic deformation behavior of the material.

  11. An elasto-plastic self-consistent model with hardening based on dislocation density, twinning and de-twinning: Application to strain path changes in HCP metals

    Energy Technology Data Exchange (ETDEWEB)

    Zecevic, Milovan [Department of Mechanical Engineering, University of New Hampshire, Durham, NH 03824 (United States); Knezevic, Marko, E-mail: marko.knezevic@unh.edu [Department of Mechanical Engineering, University of New Hampshire, Durham, NH 03824 (United States); Beyerlein, Irene J. [Theoretical Division, Los Alamos National Laboratory, Los Alamos, NM 87545 (United States); Tomé, Carlos N. [Materials Science and Technology Division, Los Alamos National Laboratory, Los Alamos, NM 87545 (United States)

    2015-06-25

    In this work, we develop a polycrystal mean-field constitutive model based on an elastic–plastic self-consistent (EPSC) framework. In this model, we incorporate recently developed subgrain models for dislocation density evolution with thermally activated slip, twin activation via statistical stress fluctuations, reoriented twin domains within the grain and associated stress relaxation, twin boundary hardening, and de-twinning. The model is applied to a systematic set of strain path change tests on pure beryllium (Be). Under the applied deformation conditions, Be deforms by multiple slip modes and deformation twinning and thereby provides a challenging test for model validation. With a single set of material parameters, determined using the flow-stress vs. strain responses during monotonic testing, the model predicts well the evolution of texture, lattice strains, and twinning. With further analysis, we demonstrate the significant influence of internal residual stresses on (1) the flow stress drop when reloading from one path to another, (2) deformation twin activation, (3) de-twinning during a reversal strain path change, and (4) the formation of additional twin variants during a cross-loading sequence. The model presented here can, in principle, be applied to other metals, deforming by multiple slip and twinning modes under a wide range of temperature, strain rate, and strain path conditions.

  12. Computational prediction of over-annotated protein-coding genes in the genome of Agrobacterium tumefaciens strain C58

    Science.gov (United States)

    Yu, Jia-Feng; Sui, Tian-Xiang; Wang, Hong-Mei; Wang, Chun-Ling; Jing, Li; Wang, Ji-Hua

    2015-12-01

    Agrobacterium tumefaciens strain C58 is a type of pathogen that can cause tumors in some dicotyledonous plants. Ever since the genome of A. tumefaciens strain C58 was sequenced, the quality of annotation of its protein-coding genes has been queried continually, because the annotation varies greatly among different databases. In this paper, the questionable hypothetical genes were re-predicted by integrating the TN curve and Z curve methods. As a result, 30 genes originally annotated as “hypothetical” were discriminated as being non-coding sequences. By testing the re-prediction program 10 times on data sets composed of the function-known genes, the mean accuracy of 99.99% and mean Matthews correlation coefficient value of 0.9999 were obtained. Further sequence analysis and COG analysis showed that the re-annotation results were very reliable. This work can provide an efficient tool and data resources for future studies of A. tumefaciens strain C58. Project supported by the National Natural Science Foundation of China (Grant Nos. 61302186 and 61271378) and the Funding from the State Key Laboratory of Bioelectronics of Southeast University.

  13. Computational prediction of over-annotated protein-coding genes in the genome of Agrobacterium tumefaciens strain C58

    International Nuclear Information System (INIS)

    Yu Jia-Feng; Sui Tian-Xiang; Wang Ji-Hua; Wang Hong-Mei; Wang Chun-Ling; Jing Li

    2015-01-01

    Agrobacterium tumefaciens strain C58 is a type of pathogen that can cause tumors in some dicotyledonous plants. Ever since the genome of A. tumefaciens strain C58 was sequenced, the quality of annotation of its protein-coding genes has been queried continually, because the annotation varies greatly among different databases. In this paper, the questionable hypothetical genes were re-predicted by integrating the TN curve and Z curve methods. As a result, 30 genes originally annotated as “hypothetical” were discriminated as being non-coding sequences. By testing the re-prediction program 10 times on data sets composed of the function-known genes, the mean accuracy of 99.99% and mean Matthews correlation coefficient value of 0.9999 were obtained. Further sequence analysis and COG analysis showed that the re-annotation results were very reliable. This work can provide an efficient tool and data resources for future studies of A. tumefaciens strain C58. (special topic)

  14. Theoretical Prediction of an Antimony-Silicon Monolayer (penta-Sb2Si): Band Gap Engineering by Strain Effect

    Science.gov (United States)

    Morshedi, Hosein; Naseri, Mosayeb; Hantehzadeh, Mohammad Reza; Elahi, Seyed Mohammad

    2018-04-01

    In this paper, using a first principles calculation, a two-dimensional structure of silicon-antimony named penta-Sb2Si is predicted. The structural, kinetic, and thermal stabilities of the predicted monolayer are confirmed by the cohesive energy calculation, phonon dispersion analysis, and first principles molecular dynamic simulation, respectively. The electronic properties investigation shows that the pentagonal Sb2Si monolayer is a semiconductor with an indirect band gap of about 1.53 eV (2.1 eV) from GGA-PBE (PBE0 hybrid functional) calculations which can be effectively engineered by employing external biaxial compressive and tensile strain. Furthermore, the optical characteristics calculation indicates that the predicted monolayer has considerable optical absorption and reflectivity in the ultraviolet region. The results suggest that a Sb2Si monolayer has very good potential applications in new nano-optoelectronic devices.

  15. Model Predictive Control for an Industrial SAG Mill

    DEFF Research Database (Denmark)

    Ohan, Valeriu; Steinke, Florian; Metzger, Michael

    2012-01-01

    We discuss Model Predictive Control (MPC) based on ARX models and a simple lower order disturbance model. The advantage of this MPC formulation is that it has few tuning parameters and is based on an ARX prediction model that can readily be identied using standard technologies from system identic...

  16. Uncertainties in spatially aggregated predictions from a logistic regression model

    NARCIS (Netherlands)

    Horssen, P.W. van; Pebesma, E.J.; Schot, P.P.

    2002-01-01

    This paper presents a method to assess the uncertainty of an ecological spatial prediction model which is based on logistic regression models, using data from the interpolation of explanatory predictor variables. The spatial predictions are presented as approximate 95% prediction intervals. The

  17. Dealing with missing predictor values when applying clinical prediction models.

    NARCIS (Netherlands)

    Janssen, K.J.; Vergouwe, Y.; Donders, A.R.T.; Harrell Jr, F.E.; Chen, Q.; Grobbee, D.E.; Moons, K.G.

    2009-01-01

    BACKGROUND: Prediction models combine patient characteristics and test results to predict the presence of a disease or the occurrence of an event in the future. In the event that test results (predictor) are unavailable, a strategy is needed to help users applying a prediction model to deal with

  18. A viscoelastic, viscoplastic model of cortical bone valid at low and high strain rates.

    Science.gov (United States)

    Johnson, T P M; Socrate, S; Boyce, M C

    2010-10-01

    The stress-strain behavior of cortical bone is well known to be strain-rate dependent, exhibiting both viscoelastic and viscoplastic behavior. Viscoelasticity has been demonstrated in literature data with initial modulus increasing by more than a factor of 2 as applied strain rate is increased from 0.001 to 1500 s(-1). A strong dependence of yield on strain rate has also been reported in the literature, with the yield stress at 250 s(-1) having been observed to be more than twice that at 0.001 s(-1), demonstrating the material viscoplasticity. Constitutive models which capture this rate-dependent behavior from very low to very high strain rates are required in order to model and simulate the full range of loading conditions which may be experienced in vivo; particularly those involving impact, ballistic and blast events. This paper proposes a new viscoelastic, viscoplastic constitutive model which has been developed to meet these requirements. The model is fitted to three sets of stress-strain measurements from the literature and shown to be valid at strain rates ranging over seven orders of magnitude. 2010 Acta Materialia Inc. All rights reserved.

  19. Global longitudinal strain predicts incident atrial fibrillation and stroke occurrence after acute myocardial infarction

    DEFF Research Database (Denmark)

    Olsen, Flemming Javier; Pedersen, Sune; Jensen, Jan Skov

    2016-01-01

    .12, 95% confidence interval 1.00; 1.25, P = 0.042, per 1% decrease) after multivariable adjustment for baseline predictors (age, sex, diabetes, hypertension, diastolic dysfunction, and LVEF) using Cox regression. Furthermore, global longitudinal strain resulted in significantly higher c...

  20. Continuous borehole strain and pore pressure in the near field of the 28 September 2004 M 6.0 parkfield, California, earthquake: Implications for nucleation, fault response, earthquake prediction and tremor

    Science.gov (United States)

    Johnston, M.J.S.; Borcherdt, R.D.; Linde, A.T.; Gladwin, M.T.

    2006-01-01

    Near-field observations of high-precision borehole strain and pore pressure, show no indication of coherent accelerating strain or pore pressure during the weeks to seconds before the 28 September 2004 M 6.0 Parkfield earthquake. Minor changes in strain rate did occur at a few sites during the last 24 hr before the earthquake but these changes are neither significant nor have the form expected for strain during slip coalescence initiating fault failure. Seconds before the event, strain is stable at the 10-11 level. Final prerupture nucleation slip in the hypocentral region is constrained to have a moment less than 2 ?? 1012 N m (M 2.2) and a source size less than 30 m. Ground displacement data indicate similar constraints. Localized rupture nucleation and runaway precludes useful prediction of damaging earthquakes. Coseismic dynamic strains of about 10 microstrain peak-to-peak were superimposed on volumetric strain offsets of about 0.5 microstrain to the northwest of the epicenter and about 0.2 microstrain to the southeast of the epicenter, consistent with right lateral slip. Observed strain and Global Positioning System (GPS) offsets can be simply fit with 20 cm of slip between 4 and 10 km on a 20-km segment of the fault north of Gold Hill (M0 = 7 ?? 1017 N m). Variable slip inversion models using GPS data and seismic data indicate similar moments. Observed postseismic strain is 60% to 300% of the coseismic strain, indicating incomplete release of accumulated strain. No measurable change in fault zone compliance preceding or following the earthquake is indicated by stable earth tidal response. No indications of strain change accompany nonvolcanic tremor events reported prior to and following the earthquake.

  1. Neural Fuzzy Inference System-Based Weather Prediction Model and Its Precipitation Predicting Experiment

    Directory of Open Access Journals (Sweden)

    Jing Lu

    2014-11-01

    Full Text Available We propose a weather prediction model in this article based on neural network and fuzzy inference system (NFIS-WPM, and then apply it to predict daily fuzzy precipitation given meteorological premises for testing. The model consists of two parts: the first part is the “fuzzy rule-based neural network”, which simulates sequential relations among fuzzy sets using artificial neural network; and the second part is the “neural fuzzy inference system”, which is based on the first part, but could learn new fuzzy rules from the previous ones according to the algorithm we proposed. NFIS-WPM (High Pro and NFIS-WPM (Ave are improved versions of this model. It is well known that the need for accurate weather prediction is apparent when considering the benefits. However, the excessive pursuit of accuracy in weather prediction makes some of the “accurate” prediction results meaningless and the numerical prediction model is often complex and time-consuming. By adapting this novel model to a precipitation prediction problem, we make the predicted outcomes of precipitation more accurate and the prediction methods simpler than by using the complex numerical forecasting model that would occupy large computation resources, be time-consuming and which has a low predictive accuracy rate. Accordingly, we achieve more accurate predictive precipitation results than by using traditional artificial neural networks that have low predictive accuracy.

  2. Foundation Settlement Prediction Based on a Novel NGM Model

    Directory of Open Access Journals (Sweden)

    Peng-Yu Chen

    2014-01-01

    Full Text Available Prediction of foundation or subgrade settlement is very important during engineering construction. According to the fact that there are lots of settlement-time sequences with a nonhomogeneous index trend, a novel grey forecasting model called NGM (1,1,k,c model is proposed in this paper. With an optimized whitenization differential equation, the proposed NGM (1,1,k,c model has the property of white exponential law coincidence and can predict a pure nonhomogeneous index sequence precisely. We used two case studies to verify the predictive effect of NGM (1,1,k,c model for settlement prediction. The results show that this model can achieve excellent prediction accuracy; thus, the model is quite suitable for simulation and prediction of approximate nonhomogeneous index sequence and has excellent application value in settlement prediction.

  3. Usefulness of right ventricular free wall strain to predict quality of life in "repaired" tetralogy of Fallot.

    Science.gov (United States)

    Lu, Jimmy C; Ghadimi Mahani, Maryam; Agarwal, Prachi P; Cotts, Timothy B; Dorfman, Adam L

    2013-06-01

    After repair of tetralogy of Fallot, the left ventricular ejection fraction and the right ventricular ejection fraction are associated with clinical status and outcomes, but the relation of strain, a potentially earlier marker of dysfunction, to quality of life has not been evaluated. In 58 patients with tetralogy of Fallot (median age 29 years, interquartile range 20 to 41) who underwent cardiovascular magnetic resonance imaging and completed the Short Form 36, Version 2 (a validated quality-of-life assessment), left ventricular global circumferential strain, left ventricular global longitudinal strain, and right ventricular free wall longitudinal strain (RVLSFW) were measured from cine images using feature-tracking software. Age-adjusted z score ≤-1 for the physical component summary or subscales of physical functioning, role-physical, and general health was considered a clinically significant decrease in quality of life. Patients with RVLSFW less than the median had increased odds of decreased physical functioning (odds ratio [OR] 5.4, p = 0.01) and general health (OR 3.5, p = 0.04) subscale scores, which remained significant in patients with right ventricular ejection fractions ≥45% (physical functioning: OR 9.5, p = 0.03; general health: OR 5.9, p = 0.04). Left ventricular global circumferential strain and left ventricular global longitudinal strain did not predict decreased quality of life in this population. Intraobserver and interobserver variability was acceptable for left ventricular global circumferential strain (coefficients of variation 9.5% and 10.0%, respectively) but lower for left ventricular global longitudinal strain (coefficients of variation 17.2% and 16.8%, respectively) and poor for RVLSFW (coefficients of variation 19.9% and 28.8%, respectively). In conclusion, RVLSFW appears to have discriminative ability in this population for decreased quality of life and may yield incremental prognostic value beyond global right ventricular

  4. Comparing National Water Model Inundation Predictions with Hydrodynamic Modeling

    Science.gov (United States)

    Egbert, R. J.; Shastry, A.; Aristizabal, F.; Luo, C.

    2017-12-01

    The National Water Model (NWM) simulates the hydrologic cycle and produces streamflow forecasts, runoff, and other variables for 2.7 million reaches along the National Hydrography Dataset for the continental United States. NWM applies Muskingum-Cunge channel routing which is based on the continuity equation. However, the momentum equation also needs to be considered to obtain better estimates of streamflow and stage in rivers especially for applications such as flood inundation mapping. Simulation Program for River NeTworks (SPRNT) is a fully dynamic model for large scale river networks that solves the full nonlinear Saint-Venant equations for 1D flow and stage height in river channel networks with non-uniform bathymetry. For the current work, the steady-state version of the SPRNT model was leveraged. An evaluation on SPRNT's and NWM's abilities to predict inundation was conducted for the record flood of Hurricane Matthew in October 2016 along the Neuse River in North Carolina. This event was known to have been influenced by backwater effects from the Hurricane's storm surge. Retrospective NWM discharge predictions were converted to stage using synthetic rating curves. The stages from both models were utilized to produce flood inundation maps using the Height Above Nearest Drainage (HAND) method which uses the local relative heights to provide a spatial representation of inundation depths. In order to validate the inundation produced by the models, Sentinel-1A synthetic aperture radar data in the VV and VH polarizations along with auxiliary data was used to produce a reference inundation map. A preliminary, binary comparison of the inundation maps to the reference, limited to the five HUC-12 areas of Goldsboro, NC, yielded that the flood inundation accuracies for NWM and SPRNT were 74.68% and 78.37%, respectively. The differences for all the relevant test statistics including accuracy, true positive rate, true negative rate, and positive predictive value were found

  5. Development of a New Gradient Based Strain-Criterion for Prediction of Bendability in Quality Assurance and FEA

    Science.gov (United States)

    Denninger, Ralf; Liewald, Mathias; Sindel, Manfred

    2011-08-01

    Numerical simulation systems are more and more used in process development of car bodies. Nowadays, also the hemming process is optimised in FEA. Thus, the analysing of process robustness calls for a failure criterion for the specific bending and hemming load condition. For that purpose the experimental determination of bendability under various pre-load conditions that occur in real production, e.g. during deep drawing in press shop, is content of this contribution. Using these experimental results, a new approach for a strain-gradient based failure criterion for bending operations is presented to optimise bendability prediction. The bending-strain-gradient approach can be used both in production related departments of quality assurance as well as for simulative process design or process validation for vehicle manufacturing planning.

  6. Predictive models for moving contact line flows

    Science.gov (United States)

    Rame, Enrique; Garoff, Stephen

    2003-01-01

    Modeling flows with moving contact lines poses the formidable challenge that the usual assumptions of Newtonian fluid and no-slip condition give rise to a well-known singularity. This singularity prevents one from satisfying the contact angle condition to compute the shape of the fluid-fluid interface, a crucial calculation without which design parameters such as the pressure drop needed to move an immiscible 2-fluid system through a solid matrix cannot be evaluated. Some progress has been made for low Capillary number spreading flows. Combining experimental measurements of fluid-fluid interfaces very near the moving contact line with an analytical expression for the interface shape, we can determine a parameter that forms a boundary condition for the macroscopic interface shape when Ca much les than l. This parameter, which plays the role of an "apparent" or macroscopic dynamic contact angle, is shown by the theory to depend on the system geometry through the macroscopic length scale. This theoretically established dependence on geometry allows this parameter to be "transferable" from the geometry of the measurement to any other geometry involving the same material system. Unfortunately this prediction of the theory cannot be tested on Earth.

  7. Full-range stress–strain behaviour of contemporary pipeline steels: Part I. Model description

    International Nuclear Information System (INIS)

    Hertelé, Stijn; De Waele, Wim; Denys, Rudi; Verstraete, Matthias

    2012-01-01

    The stress–strain relationship of contemporary pipeline steels is often approximated by the relatively simple Ramberg–Osgood equation. However, these steels often show a more complex post-yield behaviour, which can result in significant errors. To address this limitation for cases where an accurate full-range description is needed, the authors developed a new ‘UGent’ stress–strain model which has two independent strain-hardening exponents. This paper compares the UGent model with the Ramberg–Osgood model for a wide range of experimental data, by means of least-squares curve fitting. A significant improvement is observed for contemporary pipeline steels with a yield-to-tensile ratio above 0.80. These steels typically exhibit two distinct stages of strain hardening. In contrast to the Ramberg–Osgood model, both stages are successfully described by the UGent model. A companion paper (Part II) discusses how to find appropriate model parameter values for the UGent model. - Highlights: ► Contemporary pipeline steels often show two strain-hardening stages. ► This phenomenon is progressively apparent as Y/T exceeds 0.80. ► Both stages cannot be simultaneously described by the Ramberg–Osgood model. ► A new “UGent” model provides significantly better descriptions. ► The improvement becomes more pronounced as Y/T increases.

  8. A constitutive model for particulate-reinforced titanium matrix composites subjected to high strain rates and high temperatures

    Directory of Open Access Journals (Sweden)

    Song Wei-Dong

    2013-01-01

    Full Text Available Quasi-static and dynamic tension tests were conducted to study the mechanical properties of particulate-reinforced titanium matrix composites at strain rates ranging from 0.0001/s to 1000/s and at temperatures ranging from 20 °C to 650 °C Based on the experimental results, a constitutive model, which considers the effects of strain rate and temperature on hot deformation behavior, was proposed for particulate-reinforced titanium matrix composites subjected to high strain rates and high temperatures by using Zener-Hollomon equations including Arrhenius terms. All the material constants used in the model were identified by fitting Zener-Hollomon equations against the experimental results. By comparison of theoretical predictions presented by the model with experimental results, a good agreement was achieved, which indicates that this constitutive model can give an accurate and precise estimate for high temperature flow stress for the studied titanium matrix composites and can be used for numerical simulations of hot deformation behavior of the composites.

  9. Developmental prediction model for early alcohol initiation in Dutch adolescents

    NARCIS (Netherlands)

    Geels, L.M.; Vink, J.M.; Beijsterveldt, C.E.M. van; Bartels, M.; Boomsma, D.I.

    2013-01-01

    Objective: Multiple factors predict early alcohol initiation in teenagers. Among these are genetic risk factors, childhood behavioral problems, life events, lifestyle, and family environment. We constructed a developmental prediction model for alcohol initiation below the Dutch legal drinking age

  10. Exposure to pairs of Aeromonas strains enhances virulence in the Caenorhabditis elegans infection model

    Science.gov (United States)

    Aeromonad virulence remains poorly understood, and is difficult to predict from strain characteristics. In addition, infections are often polymicrobial (i.e., are mixed infections), and 5 -10% of such infections include two distinct aeromonads, which has an unknown impact on virulence. In this work,...

  11. Seasonal predictability of Kiremt rainfall in coupled general circulation models

    Science.gov (United States)

    Gleixner, Stephanie; Keenlyside, Noel S.; Demissie, Teferi D.; Counillon, François; Wang, Yiguo; Viste, Ellen

    2017-11-01

    The Ethiopian economy and population is strongly dependent on rainfall. Operational seasonal predictions for the main rainy season (Kiremt, June-September) are based on statistical approaches with Pacific sea surface temperatures (SST) as the main predictor. Here we analyse dynamical predictions from 11 coupled general circulation models for the Kiremt seasons from 1985-2005 with the forecasts starting from the beginning of May. We find skillful predictions from three of the 11 models, but no model beats a simple linear prediction model based on the predicted Niño3.4 indices. The skill of the individual models for dynamically predicting Kiremt rainfall depends on the strength of the teleconnection between Kiremt rainfall and concurrent Pacific SST in the models. Models that do not simulate this teleconnection fail to capture the observed relationship between Kiremt rainfall and the large-scale Walker circulation.

  12. MODELLING OF DYNAMIC SPEED LIMITS USING THE MODEL PREDICTIVE CONTROL

    Directory of Open Access Journals (Sweden)

    Andrey Borisovich Nikolaev

    2017-09-01

    Full Text Available The article considers the issues of traffic management using intelligent system “Car-Road” (IVHS, which consist of interacting intelligent vehicles (IV and intelligent roadside controllers. Vehicles are organized in convoy with small distances between them. All vehicles are assumed to be fully automated (throttle control, braking, steering. Proposed approaches for determining speed limits for traffic cars on the motorway using a model predictive control (MPC. The article proposes an approach to dynamic speed limit to minimize the downtime of vehicles in traffic.

  13. Prediction of mean skin temperature for use as a heat strain scale by introducing an equation for sweating efficiency

    Science.gov (United States)

    Kubota, H.; Kuwabara, K.; Hamada, Y.

    2014-09-01

    The present paper made the heat balance equation (HBE) for nude or minimally clad subjects a linear function of mean skin temperature ( t sk) by applying new equations for sweating efficiency ( η sw) and thermoregulatory sweat rate ( S wR). As the solution of the HBE, the equation predicting t sk was derived and used for a heat strain scale of subjects. The η sw was proportional to the reciprocal of S w/ E max ( S w, sweat rate; E max maximum evaporative capacity) and the S wR was proportional to t sk with a parameter of the sweating capacity of the subject. The errors of predicted t sk from observations due to the approximation of η sw were examined based on experimental data conducted on eight young male subjects. The value of errors of t sk was -0.10 ± 0.42 °C (mean ± sample standard deviation (SSD)). We aim to apply the predicted t sk of a subject at a level of sweating capacity as a heat strain scale of a function of four environmental factors (dry- and wet-bulb temperatures, radiation, and air velocity) and three human factors (metabolic rate, sweating capacity, and clothing (≤0.2clo)).

  14. Ductile Tearing of Thin Aluminum Plates Under Blast Loading. Predictions with Fully Coupled Models and Biaxial Material Response Characterization

    Energy Technology Data Exchange (ETDEWEB)

    Corona, Edmundo [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Gullerud, Arne S. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Haulenbeek, Kimberly K. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Reu, Phillip L. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

    2015-06-01

    The work presented in this report concerns the response and failure of thin 2024- T3 aluminum alloy circular plates to a blast load produced by the detonation of a nearby spherical charge. The plates were fully clamped around the circumference and the explosive charge was located centrally with respect to the plate. The principal objective was to conduct a numerical model validation study by comparing the results of predictions to experimental measurements of plate deformation and failure for charges with masses in the vicinity of the threshold between no tearing and tearing of the plates. Stereo digital image correlation data was acquired for all tests to measure the deflection and strains in the plates. The size of the virtual strain gage in the measurements, however, was relatively large, so the strain measurements have to be interpreted accordingly as lower bounds of the actual strains in the plate and of the severity of the strain gradients. A fully coupled interaction model between the blast and the deflection of the structure was considered. The results of the validation exercise indicated that the model predicted the deflection of the plates reasonably accurately as well as the distribution of strain on the plate. The estimation of the threshold charge based on a critical value of equivalent plastic strain measured in a bulge test, however, was not accurate. This in spite of efforts to determine the failure strain of the aluminum sheet under biaxial stress conditions. Further work is needed to be able to predict plate tearing with some degree of confidence. Given the current technology, at least one test under the actual blast conditions where the plate tears is needed to calibrate the value of equivalent plastic strain when failure occurs in the numerical model. Once that has been determined, the question of the explosive mass value at the threshold could be addressed with more confidence.

  15. Strain Sensor of Carbon Nanotubes in Microscale: From Model to Metrology

    Directory of Open Access Journals (Sweden)

    Wei Qiu

    2014-01-01

    Full Text Available A strain sensor composed of carbon nanotubes with Raman spectroscopy can achieve measurement of the three in-plane strain components in microscale. Based on previous work on the mathematic model of carbon nanotube strain sensors, this paper presents a detailed study on the optimization, diversification, and standardization of a CNT strain sensor from the viewpoint of metrology. A new miniaccessory for polarization control is designed, and two different preparing methods for CNT films as sensing media are introduced to provide diversified choices for applications. Then, the standard procedure of creating CNT strain sensors is proposed. Application experiments confirmed the effectiveness of the above improvement, which is helpful in developing this method for convenient metrology.

  16. Modeling of strain effects on the device behaviors of ferroelectric memory field-effect transistors

    International Nuclear Information System (INIS)

    Yang, Feng; Hu, Guangda; Wu, Weibing; Yang, Changhong; Wu, Haitao; Tang, Minghua

    2013-01-01

    The influence of strains on the channel current–gate voltage behaviors and memory windows of ferroelectric memory field-effect transistors (FeMFETs) were studied using an improved model based on the Landau–Devonshire theory. ‘Channel potential–gate voltage’ ferroelectric polarization and silicon surface potential diagrams were constructed for strained single-domain BaTiO 3 FeMFETs. The compressive strains can increase (or decrease) the amplitude of transistor currents and enlarge memory windows. However, tensile strains only decrease the maximum value of transistor currents and compress memory windows. Mismatch strains were found to have a significant influence on the electrical behaviors of the devices, therefore, they must be considered in FeMFET device designing. (fast track communication)

  17. Identification of strain-rate and thermal sensitive material model with an inverse method

    CERN Document Server

    Peroni, L; Peroni, M

    2010-01-01

    This paper describes a numerical inverse method to extract material strength parameters from the experimental data obtained via mechanical tests at different strain-rates and temperatures. It will be shown that this procedure is particularly useful to analyse experimental results when the stress-strain fields in the specimen cannot be correctly described via analytical models. This commonly happens in specimens with no regular shape, in specimens with a regular shape when some instability phenomena occur (for example the necking phenomena in tensile tests that create a strongly heterogeneous stress-strain fields) or in dynamic tests (where the strain-rate field is not constant due to wave propagation phenomena). Furthermore the developed procedure is useful to take into account thermal phenomena generally affecting high strain-rate tests due to the adiabatic overheating related to the conversion of plastic work. The method presented requires strong effort both from experimental and numerical point of view, an...

  18. Strain Sensor of Carbon Nanotubes in Microscale: From Model to Metrology

    Science.gov (United States)

    Qiu, Wei; Li, Shi-Lei; Deng, Wei-lin; Gao, Di; Kang, Yi-Lan

    2014-01-01

    A strain sensor composed of carbon nanotubes with Raman spectroscopy can achieve measurement of the three in-plane strain components in microscale. Based on previous work on the mathematic model of carbon nanotube strain sensors, this paper presents a detailed study on the optimization, diversification, and standardization of a CNT strain sensor from the viewpoint of metrology. A new miniaccessory for polarization control is designed, and two different preparing methods for CNT films as sensing media are introduced to provide diversified choices for applications. Then, the standard procedure of creating CNT strain sensors is proposed. Application experiments confirmed the effectiveness of the above improvement, which is helpful in developing this method for convenient metrology. PMID:24683338

  19. An Analytical Model for Predicting the Stress Distributions within Single-Lap Adhesively Bonded Beams

    Directory of Open Access Journals (Sweden)

    Xiaocong He

    2014-01-01

    Full Text Available An analytical model for predicting the stress distributions within single-lap adhesively bonded beams under tension is presented in this paper. By combining the governing equations of each adherend with the joint kinematics, the overall system of governing equations can be obtained. Both the adherends and the adhesive are assumed to be under plane strain condition. With suitable boundary conditions, the stress distribution of the adhesive in the longitudinal direction is determined.

  20. Healthy Work Revisited: Do Changes in Time Strain Predict Well-Being?

    OpenAIRE

    Moen, Phyllis; Kelly, Erin L.; Lam, Jack

    2013-01-01

    Building on Karasek and Theorell (R. Karasek & T. Theorell, 1990, Healthy work: Stress, productivity, and the reconstruction of working life, New York, NY: Basic Books), we theorized and tested the relationship between time strain (work-time demands and control) and seven self-reported health outcomes. We drew on survey data from 550 employees fielded before and 6 months after the implementation of an organizational intervention, the Results Only Work Environment (ROWE) in a white-collar orga...

  1. Novel bioinformatics strategies for prediction of directional sequence changes in influenza virus genomes and for surveillance of potentially hazardous strains.

    Science.gov (United States)

    Iwasaki, Yuki; Abe, Takashi; Wada, Yoshiko; Wada, Kennosuke; Ikemura, Toshimichi

    2013-08-21

    With the remarkable increase of microbial and viral sequence data obtained from high-throughput DNA sequencers, novel tools are needed for comprehensive analysis of the big sequence data. We have developed "Batch-Learning Self-Organizing Map (BLSOM)" which can characterize very many, even millions of, genomic sequences on one plane. Influenza virus is one of zoonotic viruses and shows clear host tropism. Important issues for bioinformatics studies of influenza viruses are prediction of genomic sequence changes in the near future and surveillance of potentially hazardous strains. To characterize sequence changes in influenza virus genomes after invasion into humans from other animal hosts, we applied BLSOMs to analyses of mono-, di-, tri-, and tetranucleotide compositions in all genome sequences of influenza A and B viruses and found clear host-dependent clustering (self-organization) of the sequences. Viruses isolated from humans and birds differed in mononucleotide composition from each other. In addition, host-dependent oligonucleotide compositions that could not be explained with the host-dependent mononucleotide composition were revealed by oligonucleotide BLSOMs. Retrospective time-dependent directional changes of mono- and oligonucleotide compositions, which were visualized for human strains on BLSOMs, could provide predictive information about sequence changes in newly invaded viruses from other animal hosts (e.g. the swine-derived pandemic H1N1/09). Basing on the host-dependent oligonucleotide composition, we proposed a strategy for prediction of directional changes of virus sequences and for surveillance of potentially hazardous strains when introduced into human populations from non-human sources. Millions of genomic sequences from infectious microbes and viruses have become available because of their medical and social importance, and BLSOM can characterize the big data and support efficient knowledge discovery.

  2. Ischemic heart disease and early diagnosis. Study on the predictive value of 2D strain.

    Science.gov (United States)

    Dattilo, G; Imbalzano, E; Lamari, A; Casale, M; Paunovic, N; Busacca, P; Di Bella, G

    2016-07-15

    Two-dimensional strain echocardiography (2D-SE) quantifies left ventricular global longitudinal strain (GLS) and global circumferential strain (GCS). Our aim was to test 2D-SE during dipyridamole stress echocardiography (Dipy-Stress) in patients with non-diagnostic result, checking by way of coronary CT angiography (CCTA) the possible presence of coronary artery disease (CAD). Over twenty-four months 65 consecutive patients with non-diagnostic Dipy-Stress were studied by 2D-SE and by CCTA. GCS and GLS at rest and after stress were compared according to data derived from CCTA. CAD was graded as significant (stenosis ≥50%), mild (stenosis between 15 and 50%) or absent (stenosis stress was similar in CCTA-positive (26±5% and 27±5% respectively) and CCTA-negative groups (27±3% and 28±3% respectively). GLS at rest was significantly reduced (Pstress was lower (Pstress was found in positive-CCTA group. ΔGLS showed a significant decrease (PStress allows, in case of non-diagnostic test, identification of mild-CAD with high sensitivity and specificity. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

  3. Predictability in models of the atmospheric circulation

    NARCIS (Netherlands)

    Houtekamer, P.L.

    1992-01-01

    It will be clear from the above discussions that skill forecasts are still in their infancy. Operational skill predictions do not exist. One is still struggling to prove that skill predictions, at any range, have any quality at all. It is not clear what the statistics of the analysis error

  4. Modeling of failure mode in knee ligaments depending on the strain rate

    Directory of Open Access Journals (Sweden)

    Hyman William

    2002-01-01

    Full Text Available Abstract Background The failure mechanism of the knee ligament (bone-ligament-bone complex at different strain rates is an important subject in the biomechanics of the knee. This study reviews and summarizes the literature describing ligament injury as a function of stain rate, which has been published during the last 30 years. Methods Three modes of injury are presented as a function of strain rate, and they are used to analyze the published cases. The number of avulsions is larger than that of ligament tearing in mode I. There is no significant difference between the number of avulsions and ligament tearing in mode II. Ligament tearing happens more frequently than avulsion in mode III. Results When the strain rate increases, the order of mode is mode I, II, III, I, and II. Analytical models of ligament behavior as a function of strain rate are also presented and used to provide an integrated framework for describing all of the failure regimes. In addition, this study showed the failure mechanisms with different specimens, ages, and strain rates. Conclusion There have been several a numbers of studies of ligament failure under various conditions including widely varying strain rates. One issue in these studies is whether ligament failure occurs mid-ligament or at the bone attachment point, with assertions that this is a function of the strain rate. However, over the range of strain rates and other conditions reported, there has appeared to be discrepancies in the conclusions on the effect of strain rate. The analysis and model presented here provides a unifying assessment of the previous disparities, emphasizing the differential effect of strain rate on the relative strengths of the ligament and the attachment.

  5. Required Collaborative Work in Online Courses: A Predictive Modeling Approach

    Science.gov (United States)

    Smith, Marlene A.; Kellogg, Deborah L.

    2015-01-01

    This article describes a predictive model that assesses whether a student will have greater perceived learning in group assignments or in individual work. The model produces correct classifications 87.5% of the time. The research is notable in that it is the first in the education literature to adopt a predictive modeling methodology using data…

  6. Models for predicting compressive strength and water absorption of ...

    African Journals Online (AJOL)

    This work presents a mathematical model for predicting the compressive strength and water absorption of laterite-quarry dust cement block using augmented Scheffe's simplex lattice design. The statistical models developed can predict the mix proportion that will yield the desired property. The models were tested for lack of ...

  7. Strain rate-dependent viscohyperelastic constitutive modeling of bovine liver tissue.

    Science.gov (United States)

    Roan, Esra; Vemaganti, Kumar

    2011-04-01

    The mechanical response of most soft tissue is considered to be viscohyperelastic, making the development of accurate constitutive models a challenging task. In this article, we present a constitutive model for bovine liver tissue that utilizes a viscous dissipation potential, and use it to model the response of bovine liver tissue at strain rates ranging from 0.001 to 0.04 s(-1). On the material modeling front of this study, the free energy is assumed to depend on the right Cauchy-Green deformation tensor, whereas a separate rate-dependent viscous potential is posited to characterize viscoelasticity. This viscous dissipation component is a function of the time rate of change of the right Cauchy-Green deformation tensor. On the experimental front, no-slip uniaxial compression experiments are conducted on bovine liver tissue at various strain rates. A numerical correction approach is used to account for the no-slip edge conditions, and the constitutive model is fit to the resulting corrected stress-strain data. The complete derivation of the material model, its implementation in the finite element software package ABAQUS, and a validation study are presented in this article. The results show that bovine liver tissue exhibits a strong strain-rate dependence even at the low strain rates considered here and that the proposed constitutive model is able to accurately describe this response.

  8. A Simplified Micromechanical Modeling Approach to Predict the Tensile Flow Curve Behavior of Dual-Phase Steels

    Science.gov (United States)

    Nanda, Tarun; Kumar, B. Ravi; Singh, Vishal

    2017-11-01

    Micromechanical modeling is used to predict material's tensile flow curve behavior based on microstructural characteristics. This research develops a simplified micromechanical modeling approach for predicting flow curve behavior of dual-phase steels. The existing literature reports on two broad approaches for determining tensile flow curve of these steels. The modeling approach developed in this work attempts to overcome specific limitations of the existing two approaches. This approach combines dislocation-based strain-hardening method with rule of mixtures. In the first step of modeling, `dislocation-based strain-hardening method' was employed to predict tensile behavior of individual phases of ferrite and martensite. In the second step, the individual flow curves were combined using `rule of mixtures,' to obtain the composite dual-phase flow behavior. To check accuracy of proposed model, four distinct dual-phase microstructures comprising of different ferrite grain size, martensite fraction, and carbon content in martensite were processed by annealing experiments. The true stress-strain curves for various microstructures were predicted with the newly developed micromechanical model. The results of micromechanical model matched closely with those of actual tensile tests. Thus, this micromechanical modeling approach can be used to predict and optimize the tensile flow behavior of dual-phase steels.

  9. Estimating Risks of Heat Strain by Age and Sex: A Population-Level Simulation Model

    Directory of Open Access Journals (Sweden)

    Kathryn Glass

    2015-05-01

    Full Text Available Individuals living in hot climates face health risks from hyperthermia due to excessive heat. Heat strain is influenced by weather exposure and by individual characteristics such as age, sex, body size, and occupation. To explore the population-level drivers of heat strain, we developed a simulation model that scales up individual risks of heat storage (estimated using Myrup and Morgan’s man model “MANMO” to a large population. Using Australian weather data, we identify high-risk weather conditions together with individual characteristics that increase the risk of heat stress under these conditions. The model identifies elevated risks in children and the elderly, with females aged 75 and older those most likely to experience heat strain. Risk of heat strain in males does not increase as rapidly with age, but is greatest on hot days with high solar radiation. Although cloudy days are less dangerous for the wider population, older women still have an elevated risk of heat strain on hot cloudy days or when indoors during high temperatures. Simulation models provide a valuable method for exploring population level risks of heat strain, and a tool for evaluating public health and other government policy interventions.

  10. A Geodetic Strain Rate Model for the East African Rift System.

    Science.gov (United States)

    Stamps, D S; Saria, E; Kreemer, C

    2018-01-15

    Here we describe the new Sub-Saharan Africa Geodetic Strain Rate Model v.1.0 (SSA-GSRM v.1.0), which provides fundamental constraints on long-term tectonic deformation in the region and an improved seismic hazards assessment in Sub-Saharan Africa. Sub-Saharan Africa encompasses the East African Rift System, the active divergent plate boundary between the Nubian and Somalian plates, where strain is largely accommodated along the boundaries of three subplates. We develop an improved geodetic strain rate field for sub-Saharan Africa that incorporates 1) an expanded geodetic velocity field, 2) redefined regions of deforming zones guided by seismicity distribution, and 3) updated constraints on block rotations. SSA-GSRM v.1.0 spans longitudes 22° to 55.5° and latitudes -52° to 20° with 0.25° (longitude) by 0.2° (latitude) spacing. For plates/sub-plates, we assign rigid block rotations as constraints on the strain rate calculation that is determined by fitting bicubic Bessel splines to a new geodetic velocity solution for an interpolated velocity gradient tensor field. We derive strain rates, velocities, and vorticity rates from the velocity gradient tensor field. A comparison with the Global Geodetic Strain Rate model v2.1 reveals regions of previously unresolved spatial heterogeneities in geodetic strain rate distribution, which indicates zones of elevated seismic risk.

  11. A Constitutive Model for Superelastic Shape Memory Alloys Considering the Influence of Strain Rate

    Directory of Open Access Journals (Sweden)

    Hui Qian

    2013-01-01

    Full Text Available Shape memory alloys (SMAs are a relatively new class of functional materials, exhibiting special thermomechanical behaviors, such as shape memory effect and superelasticity, which enable their applications in seismic engineering as energy dissipation devices. This paper investigates the properties of superelastic NiTi shape memory alloys, emphasizing the influence of strain rate on superelastic behavior under various strain amplitudes by cyclic tensile tests. A novel constitutive equation based on Graesser and Cozzarelli’s model is proposed to describe the strain-rate-dependent hysteretic behavior of superelastic SMAs at different strain levels. A stress variable including the influence of strain rate is introduced into Graesser and Cozzarelli’s model. To verify the effectiveness of the proposed constitutive equation, experiments on superelastic NiTi wires with different strain rates and strain levels are conducted. Numerical simulation results based on the proposed constitutive equation and experimental results are in good agreement. The findings in this paper will assist the future design of superelastic SMA-based energy dissipation devices for seismic protection of structures.

  12. Sands subjected to repetitive vertical loading under zero lateral strain: accumulation models, terminal densities, and settlement

    KAUST Repository

    Chong, Song Hun

    2016-08-09

    Geosystems often experience numerous loading cycles. Plastic strain accumulation during repetitive mechanical loads can lead to shear shakedown or continued shear ratcheting; in all cases, volumetric strains diminish as the specimen evolves towards terminal density. Previously suggested models and new functions are identified to fit plastic strain accumulation data. All accumulation models are formulated to capture terminal density (volumetric strain) and either shakedown or ratcheting (shear strain). Repetitive vertical loading tests under zero lateral strain conditions are conducted using three different sands packed at initially low and high densities. Test results show that plastic strain accumulation for all sands and density conditions can be captured in the same dimensionless plot defined in terms of the initial relative density, terminal density, and ratio between the amplitude of the repetitive load and the initial static load. This observation allows us to advance a simple but robust procedure to estimate the maximum one-dimensional settlement that a foundation could experience if subjected to repetitive loads. © 2016, Canadian Science Publishing. All rights reserved.

  13. On the importance of retaining stresses and strains in repositioning computational biomechanical models of the cervical spine.

    Science.gov (United States)

    Boakye-Yiadom, Solomon; Cronin, Duane S

    2018-01-01

    Human body models are created in a specific posture and often repositioned and analyzed without retaining stresses that result from repositioning. For example, repositioning a human neck model within the physiological range of motion to a head-turned posture prior to an impact results in initial stresses within the tissues distracted from their neutral position. The aim of this study was to investigate the effect of repositioning on the subsequent kinetics, kinematics, and failure modes, of a lower cervical spine motion segment, to support future research at the full neck level. Repositioning was investigated for 3 modes (tension, flexion, and extension) and 3 load cases. The model was repositioned and loaded to failure in one continuous load history (case 1), or repositioned then restarted with retained stresses and loaded to failure (case 2). In case 3, the model was repositioned and then restarted in a stress-free state, representing current repositioning methods. Not retaining the repositioning stresses and strains resulted in different kinetics, kinematics, or failure modes, depending on the mode of loading. For the motion segment model, the differences were associated with the intervertebral disc fiber reorientation and load distribution, because the disc underwent the largest deformation during repositioning. This study demonstrated that repositioning led to altered response and tissue failure, which is critical for computational models intended to predict injury at the tissue level. It is recommended that stresses and strains be included and retained for subsequent analysis when repositioning a human computational neck model. Copyright © 2017 John Wiley & Sons, Ltd.

  14. Prognostic value of strain and strain rate in the prediction of postoperative atrial fibrillation in patients undergoing coronary artery bypass grafting: a systematic literature review

    Directory of Open Access Journals (Sweden)

    Leila Bigdelu

    2016-03-01

    Full Text Available Introduction: Atrial fibrillation (AF is a common dysrhythmia postoperatively after coronary artery bypass grafting (CABG. Myocardial strain and strain-rate imaging is used for the assessment of postoperative atrial fibrillation (POAF as a new echocardiographic method. Methods: PubMed and Scopus were searched thoroughly using the following search terms: (strain and strain rate AND (atrial fibrillation OR AF on March 2015 to find English articles in which the strain and strain-rate echocardiographic imaging had been used for the evaluation of AF in patients undergone CABG. Full text of the relevant papers was fully reviewed for data extraction.Result: Of overall 6 articles found in PubMed, 10 records found in Scopus and 4 articles found through reference list search, only 6 papers fully met the inclusion criteria for further assessment and data extraction. The results of strain and strain-rate assessment showed that in total of 542 patients undergoing CABG, POAF occurred in 106 patients. Studies showed that the reduction of left atrial (LA strain rate is correlated with AF. Consistently, the results of present review showed that LA strain and strain-rate in patients who developed AF postoperatively after CABG are significantly reduced, suggesting that strain and strain-rate could be a predictor of POAF.Conclusion: Based on the obtained results, strain and strain-rate is a suitable and accurate echocardiographic technique in the assessment of left atrial function , and it might be helpful to detect the patients who are at high risk of POAF.

  15. Finite Element Modeling of Strain Distribution through Sheet Thickness during Cold Rolling with Grooved Rolls

    Directory of Open Access Journals (Sweden)

    Pesin A.

    2015-01-01

    Full Text Available Plastic strain control of aluminum alloys are of importance for improvement of sheet microstructure and properties. The paper presents a numerical analysis of the strain distribution through pure Al sheet thickness during cold rolling with flat and grooved rolls. FEM simulations were carried out with using software DEFORM 3D. For verification of the numeric modeling results, the experimental analysis was carried out. The influence of the roll shape on strain distribution through Al sheet thickness was studied. It was shown that the strain effective increases from 0.9 to 1.5 during cold rolling with grooved rolls, when depth of indentation of grooved rolls in sheet increases from 0.25 to 0.50 mm. FE model can be used to optimize the cold rolling process to improve microstructure and mechanical properties of aluminum sheets.

  16. Repeated Strains, Social Control, Social Learning, and Delinquency: Testing an Integrated Model of General Strain Theory in China

    Science.gov (United States)

    Bao, Wan-Ning; Haas, Ain; Chen, Xiaojin; Pi, Yijun

    2014-01-01

    In Agnew's general strain theory, repeated strains can generate crime and delinquency by reducing social control and fostering social learning of crime. Using a sample of 615 middle-and high-school students in China, this study examines how social control and social learning variables mediate the effect of repeated strains in school and at home on…

  17. Multistrain models predict sequential multidrug treatment strategies to result in less antimicrobial resistance than combination treatment

    DEFF Research Database (Denmark)

    Ahmad, Amais; Zachariasen, Camilla; Christiansen, Lasse Engbo

    2016-01-01

    generated by a mathematical model of the competitive growth of multiple strains of Escherichia coli.Results: Simulation studies showed that sequential use of tetracycline and ampicillin reduced the level of double resistance, when compared to the combination treatment. The effect of the cycling frequency...... (how frequently antibiotics are alternated in a sequential treatment) of the two drugs was dependent upon the order in which the two drugs were used.Conclusion: Sequential treatment was more effective in preventing the growth of resistant strains when compared to the combination treatment. The cycling...... frequency did not play a role in suppressing the growth of resistant strains, but the specific order of the two antimicrobials did. Predictions made from the study could be used to redesign multidrug treatment strategies not only for intramuscular treatment in pigs, but also for other dosing routes....

  18. Viscoplastic behavior of zirconium alloys in the temperatures range 20 deg C - 400 deg C: characterization and modeling of strain ageing phenomena

    International Nuclear Information System (INIS)

    Graff, St.

    2006-10-01

    The anomalous strain rate sensitivity of zirconium alloys over the temperatures range 20-600 C has been widely reported in the literature. This unconventional behavior is related to the existence of strain ageing phenomenon which results from the combined action of thermally activated diffusion of foreign atoms to and along dislocation cores and the long range of dislocations interactions. The important role of interstitial and substitutional atoms in zirconium alloys, responsible for strain ageing and the lack of information about the domain where strain ageing is active have not been yet adequately characterized because of the multiplicity of alloying elements and chemical impurities. The aim of this work is to characterize experimentally the range of temperatures and strain rates where strain ageing is active on the macroscopic and mesoscopic scales. We propose also a predictive approach of the strain ageing effects, using the macroscopic strain ageing model suggested by McCormick (McCormick, 1988; Zhang et al., 2000). Specific zirconium alloys were elaborated starting from a crystal bar of zirconium with 2.2 wt% hafnium and very low oxygen content (80 wt ppm), called ZrHf. Another substitutional atom was added to the solid solution under the form of 1 wt% niobium. Some zirconium alloys were doped with oxygen, others were not. All of them were characterized by various mechanical tests (standard tensile tests, tensile tests with strain rate changes, relaxation tests with unloading). The experimental results were compared with those for the standard oxygen doped zirconium alloy (1300 wt ppm) studied by Pujol (Pujol, 1994) and called Zr702. The following experimental evidences of the age-hardening phenomena were collected and then modeled: 1) low and/or negative strain rate sensitivity around 200-300 C, 2) creep arrest at 200 C, 3) relaxation arrest at 200 C and 300 C, 4) plastic strain heterogeneities observed in laser extensometry on the millimeter scale

  19. Viscoplastic behavior of zirconium alloys in the temperatures range 20 deg C - 400 deg C: characterization and modeling of strain ageing phenomena

    Energy Technology Data Exchange (ETDEWEB)

    Graff, St

    2006-10-15

    The anomalous strain rate sensitivity of zirconium alloys over the temperatures range 20-600 C has been widely reported in the literature. This unconventional behavior is related to the existence of strain ageing phenomenon which results from the combined action of thermally activated diffusion of foreign atoms to and along dislocation cores and the long range of dislocations interactions. The important role of interstitial and substitutional atoms in zirconium alloys, responsible for strain ageing and the lack of information about the domain where strain ageing is active have not been yet adequately characterized because of the multiplicity of alloying elements and chemical impurities. The aim of this work is to characterize experimentally the range of temperatures and strain rates where strain ageing is active on the macroscopic and mesoscopic scales. We propose also a predictive approach of the strain ageing effects, using the macroscopic strain ageing model suggested by McCormick (McCormick, 1988; Zhang et al., 2000). Specific zirconium alloys were elaborated starting from a crystal bar of zirconium with 2.2 wt% hafnium and very low oxygen content (80 wt ppm), called ZrHf. Another substitutional atom was added to the solid solution under the form of 1 wt% niobium. Some zirconium alloys were doped with oxygen, others were not. All of them were characterized by various mechanical tests (standard tensile tests, tensile tests with strain rate changes, relaxation tests with unloading). The experimental results were compared with those for the standard oxygen doped zirconium alloy (1300 wt ppm) studied by Pujol (Pujol, 1994) and called Zr702. The following experimental evidences of the age-hardening phenomena were collected and then modeled: 1) low and/or negative strain rate sensitivity around 200-300 C, 2) creep arrest at 200 C, 3) relaxation arrest at 200 C and 300 C, 4) plastic strain heterogeneities observed in laser extensometry on the millimeter scale

  20. Regression models for predicting anthropometric measurements of ...

    African Journals Online (AJOL)

    measure anthropometric dimensions to predict difficult-to-measure dimensions required for ergonomic design of school furniture. A total of 143 students aged between 16 and 18 years from eight public secondary schools in Ogbomoso, Nigeria ...

  1. FINITE ELEMENT MODEL FOR PREDICTING RESIDUAL ...

    African Journals Online (AJOL)

    direction (σx) had a maximum value of 375MPa (tensile) and minimum value of ... These results shows that the residual stresses obtained by prediction from the finite element method are in fair agreement with the experimental results.

  2. Probabilistic Modeling and Visualization for Bankruptcy Prediction

    DEFF Research Database (Denmark)

    Antunes, Francisco; Ribeiro, Bernardete; Pereira, Francisco Camara

    2017-01-01

    In accounting and finance domains, bankruptcy prediction is of great utility for all of the economic stakeholders. The challenge of accurate assessment of business failure prediction, specially under scenarios of financial crisis, is known to be complicated. Although there have been many successful......). Using real-world bankruptcy data, an in-depth analysis is conducted showing that, in addition to a probabilistic interpretation, the GP can effectively improve the bankruptcy prediction performance with high accuracy when compared to the other approaches. We additionally generate a complete graphical...... visualization to improve our understanding of the different attained performances, effectively compiling all the conducted experiments in a meaningful way. We complete our study with an entropy-based analysis that highlights the uncertainty handling properties provided by the GP, crucial for prediction tasks...

  3. Prediction for Major Adverse Outcomes in Cardiac Surgery: Comparison of Three Prediction Models

    Directory of Open Access Journals (Sweden)

    Cheng-Hung Hsieh

    2007-09-01

    Conclusion: The Parsonnet score performed as well as the logistic regression models in predicting major adverse outcomes. The Parsonnet score appears to be a very suitable model for clinicians to use in risk stratification of cardiac surgery.

  4. A numerical framework for modeling flexoelectricity and Maxwell stress in soft dielectrics at finite strains

    OpenAIRE

    Yvonnet, Julien; Liu, Liping

    2017-01-01

    International audience; In the present work, a numerical finite element framework is introduced to model and solve the response of nonlinear soft dielectrics, including the effects of Maxwell stress and flexoelectricity at finite strains. Weak forms, finite element discretizations and constistent linearizations, able to handle strain gradient in the context of flexo-electricity are introduced. Numerical algorithms for the treatment of a soft dielectric in a surrounding medium are presented, m...

  5. Appropriate models for estimating stresses and strains in asphalt layers

    CSIR Research Space (South Africa)

    Jooste, FJ

    1998-09-01

    Full Text Available The broad objective is to make recommendations for appropriate modelling procedures to be used in the structural design of asphalt layers. Findings of this investigation are intended to be used in refining and validating existing asphalt pavement...

  6. From Predictive Models to Instructional Policies

    Science.gov (United States)

    Rollinson, Joseph; Brunskill, Emma

    2015-01-01

    At their core, Intelligent Tutoring Systems consist of a student model and a policy. The student model captures the state of the student and the policy uses the student model to individualize instruction. Policies require different properties from the student model. For example, a mastery threshold policy requires the student model to have a way…

  7. An improved model to predict nonuniform deformation of Zr-2.5 Nb pressure tubes

    International Nuclear Information System (INIS)

    Lei, Q.M.; Fan, H.Z.

    1997-01-01

    Present circular pressure-tube ballooning models in most fuel channel codes assume that the pressure tube remains circular during ballooning. This model provides adequate predictions of pressure-tube ballooning behaviour when the pressure tube (PT) and the calandria tube (CT) are concentric and when a small (<100 degrees C) top-to-bottom circumferential temperature gradient is present on the pressure tube. However, nonconcentric ballooning is expected to occur under certain postulated CANDU (CANada Deuterium Uranium) accident conditions. This circular geometry assumption prevents the model from accurately predicting nonuniform pressure-tube straining and local PT/CT contact when the pressure tube is subjected to a large circumferential temperature gradient and consequently deforms in a noncircular pattern. This paper describes an improved model that predicts noncircular pressure-tube deformation. Use of this model (once fully validated) will reduce uncertainties in the prediction of pressure-tube ballooning during a postulated loss-of-coolant accident (LOCA) in a CANDU reactor. The noncircular deformation model considers a ring or cross-section of a pressure tube with unit axial length to calculate deformation in the radial and circumferential directions. The model keeps track of the thinning of the pressure-tube wall as well as the shape deviation from a reference circle. Such deviation is expressed in a cosine Fourier series for the lateral symmetry case. The coefficients of the series for the first m terms are calculated by solving a set of algebraic equations at each time step. The model also takes into account the effects of pressure-tube sag or bow on ballooning, using an input value of the offset distance between the centre of the calandria tube and the initial centre of the pressure tube for determining the position radius of the pressure tube. One significant improvement realized in using the noncircular deformation model is a more accurate prediction in

  8. A finite-strain homogenization model for viscoplastic porous single crystals: II - Applications

    Science.gov (United States)

    Song, Dawei; Ponte Castañeda, P.

    2017-10-01

    In part I of this work (Song and Ponte Castañeda, 2017a), a new homogenization-based constitutive model was developed for the finite-strain, macroscopic response of porous viscoplastic single crystals. In this second part, the new model is first used to investigate the instantaneous response and the evolution of the microstructure for porous FCC single crystals for a wide range of loading conditions. The loading orientation, Lode angle and stress triaxiality are found to have significant effects on the evolution of porosity and average void shape, which play crucial roles in determining the overall hardening/softening behavior of porous single crystals. The predictions of the model are found to be in fairly good agreement with numerical simulations available from the literature for all loadings considered, especially for low triaxiality conditions. The model is then used to investigate the strong effect of crystal anisotropy on the instantaneous response and the evolution of the microstructure for porous HCP single crystals. For uniaxial tension and compression, the overall hardening/softening behavior of porous HCP crystals is found to be controlled mostly by the evolution of void shape, and not so much by the evolution of porosity. In particular, porous HCP crystals exhibit overall hardening behavior with increasing porosity, while they exhibit overall softening behavior with decreasing porosity. This interesting behavior is consistent with corresponding results for porous FCC crystals, but is found to be more significant for porous HCP crystals with large anisotropy, such as porous ice, where the non-basal slip systems are much harder than the basal systems.

  9. Comparisons of Faulting-Based Pavement Performance Prediction Models

    Directory of Open Access Journals (Sweden)

    Weina Wang

    2017-01-01

    Full Text Available Faulting prediction is the core of concrete pavement maintenance and design. Highway agencies are always faced with the problem of lower accuracy for the prediction which causes costly maintenance. Although many researchers have developed some performance prediction models, the accuracy of prediction has remained a challenge. This paper reviews performance prediction models and JPCP faulting models that have been used in past research. Then three models including multivariate nonlinear regression (MNLR model, artificial neural network (ANN model, and Markov Chain (MC model are tested and compared using a set of actual pavement survey data taken on interstate highway with varying design features, traffic, and climate data. It is found that MNLR model needs further recalibration, while the ANN model needs more data for training the network. MC model seems a good tool for pavement performance prediction when the data is limited, but it is based on visual inspections and not explicitly related to quantitative physical parameters. This paper then suggests that the further direction for developing the performance prediction model is incorporating the advantages and disadvantages of different models to obtain better accuracy.

  10. Determination of the strain generated in InAs/InP quantum wires: prediction of nucleation sites

    International Nuclear Information System (INIS)

    Molina, S I; Ben, T; Sales, D L; Pizarro, J; Galindo, P L; Varela, M; Pennycook, S J; Fuster, D; Gonzalez, Y; Gonzalez, L

    2006-01-01

    The compositional distribution in a self-assembled InAs(P) quantum wire grown by molecular beam epitaxy on an InP(001) substrate has been determined by electron energy loss spectrum imaging. We have determined the strain and stress fields generated in and around this wire capped with a 5 nm InP layer by finite element calculations using as input the compositional map experimentally obtained. Preferential sites for nucleation of wires grown on the surface of this InP capping layer are predicted, based on chemical potential minimization, from the determined strain and stress fields on this surface. The determined preferential sites for wire nucleation agree with their experimentally measured locations. The method used in this paper, which combines electron energy loss spectroscopy, high-resolution Z contrast imaging, and elastic theory finite element calculations, is believed to be a valuable technique of wide applicability for predicting the preferential nucleation sites of epitaxial self-assembled nano-objects

  11. Determination of the strain generated in InAs/InP quantum wires: prediction of nucleation sites

    Energy Technology Data Exchange (ETDEWEB)

    Molina, S I [Departamento de Ciencia de los Materiales e I.M. y Q.I., Facultad de Ciencias, Universidad de Cadiz, Campus RIo San Pedro, s/n, 11510 Puerto Real, Cadiz (Spain); Ben, T [Departamento de Ciencia de los Materiales e I.M. y Q.I., Facultad de Ciencias, Universidad de Cadiz, Campus RIo San Pedro, s/n, 11510 Puerto Real, Cadiz (Spain); Sales, D L [Departamento de Ciencia de los Materiales e I.M. y Q.I., Facultad de Ciencias, Universidad de Cadiz, Campus RIo San Pedro, s/n, 11510 Puerto Real, Cadiz (Spain); Pizarro, J [Departamento de Lenguajes y Sistemas Informaticos, CASEM, Universidad de Cadiz, Campus RIo San Pedro, s/n, 11510 Puerto Real, Cadiz (Spain); Galindo, P L [Departamento de Lenguajes y Sistemas Informaticos, CASEM, Universidad de Cadiz, Campus RIo San Pedro, s/n, 11510 Puerto Real, Cadiz (Spain); Varela, M [Condensed Matter Sciences Division, Oak Ridge National Laboratory, Oak Ridge, TN 37831 (United States); Pennycook, S J [Condensed Matter Sciences Division, Oak Ridge National Laboratory, Oak Ridge, TN 37831 (United States); Fuster, D [Instituto de Microelectronica de Madrid (CNM, CSIC), Isaac Newton 8, 28760 Tres Cantos, Madrid (Spain); Gonzalez, Y [Instituto de Microelectronica de Madrid (CNM, CSIC), Isaac Newton 8, 28760 Tres Cantos, Madrid (Spain); Gonzalez, L [Instituto de Microelectronica de Madrid (CNM, CSIC), Isaac Newton 8, 28760 Tres Cantos, Madrid (Spain)

    2006-11-28

    The compositional distribution in a self-assembled InAs(P) quantum wire grown by molecular beam epitaxy on an InP(001) substrate has been determined by electron energy loss spectrum imaging. We have determined the strain and stress fields generated in and around this wire capped with a 5 nm InP layer by finite element calculations using as input the compositional map experimentally obtained. Preferential sites for nucleation of wires grown on the surface of this InP capping layer are predicted, based on chemical potential minimization, from the determined strain and stress fields on this surface. The determined preferential sites for wire nucleation agree with their experimentally measured locations. The method used in this paper, which combines electron energy loss spectroscopy, high-resolution Z contrast imaging, and elastic theory finite element calculations, is believed to be a valuable technique of wide applicability for predicting the preferential nucleation sites of epitaxial self-assembled nano-objects.

  12. A model to predict the beginning of the pollen season

    DEFF Research Database (Denmark)

    Toldam-Andersen, Torben Bo

    1991-01-01

    In order to predict the beginning of the pollen season, a model comprising the Utah phenoclirnatography Chill Unit (CU) and ASYMCUR-Growing Degree Hour (GDH) submodels were used to predict the first bloom in Alms, Ulttirrs and Berirln. The model relates environmental temperatures to rest completion...... and bud development. As phenologic parameter 14 years of pollen counts were used. The observed datcs for the beginning of the pollen seasons were defined from the pollen counts and compared with the model prediction. The CU and GDH submodels were used as: 1. A fixed day model, using only the GDH model...... for fruit trees are generally applicable, and give a reasonable description of the growth processes of other trees. This type of model can therefore be of value in predicting the start of the pollen season. The predicted dates were generally within 3-5 days of the observed. Finally the possibility of frost...

  13. Risk prediction model: Statistical and artificial neural network approach

    Science.gov (United States)

    Paiman, Nuur Azreen; Hariri, Azian; Masood, Ibrahim

    2017-04-01

    Prediction models are increasingly gaining popularity and had been used in numerous areas of studies to complement and fulfilled clinical reasoning and decision making nowadays. The adoption of such models assist physician's decision making, individual's behavior, and consequently improve individual outcomes and the cost-effectiveness of care. The objective of this paper is to reviewed articles related to risk prediction model in order to understand the suitable approach, development and the validation process of risk prediction model. A qualitative review of the aims, methods and significant main outcomes of the nineteen published articles that developed risk prediction models from numerous fields were done. This paper also reviewed on how researchers develop and validate the risk prediction models based on statistical and artificial neural network approach. From the review done, some methodological recommendation in developing and validating the prediction model were highlighted. According to studies that had been done, artificial neural network approached in developing the prediction model were more accurate compared to statistical approach. However currently, only limited published literature discussed on which approach is more accurate for risk prediction model development.

  14. Software-engineering-based model for mitigating Repetitive Strain ...

    African Journals Online (AJOL)

    The incorporation of Information and Communication Technology (ICT) in virtually all facets of human endeavours has fostered the use of computers. This has induced Repetitive Stress Injury (RSI) for continuous and persistent computer users. Proposing a software engineering model capable of enacted RSI force break ...

  15. Evaluation of the US Army fallout prediction model

    International Nuclear Information System (INIS)

    Pernick, A.; Levanon, I.

    1987-01-01

    The US Army fallout prediction method was evaluated against an advanced fallout prediction model--SIMFIC (Simplified Fallout Interpretive Code). The danger zone areas of the US Army method were found to be significantly greater (up to a factor of 8) than the areas of corresponding radiation hazard as predicted by SIMFIC. Nonetheless, because the US Army's method predicts danger zone lengths that are commonly shorter than the corresponding hot line distances of SIMFIC, the US Army's method is not reliably conservative

  16. MM99.70 - MODELS FOR FRICTION AND MATERIAL STRESS STRAIN HARDENING IN COLD FORMING

    DEFF Research Database (Denmark)

    Eriksen, Morten

    1999-01-01

    The purpose of the present documentation is to provide the necessary information for numerical simulation of cold forging operations applying the new friction model based on simulative testing as described in /1/..The documentation describes how the friction stress depends on the surface pressure...... into three main groups: friction modelling, stress/strain curves and other input data for numerical simulation....

  17. Biomechanical Strain Exacerbates Inflammation on a Progeria-on-a-Chip Model

    NARCIS (Netherlands)

    Ribas, J.; Zhang, Y.S.; Pitrez, P.R.; Leijten, Jeroen Christianus Hermanus; Miscuglio, M.; Rouwkema, Jeroen; Dokmeci, M.R.; Nissan, X.; Ferreira, L.; Khademhosseini, A.

    2017-01-01

    A progeria-on-a-chip model is engineered to recapitulate the biomechanical dynamics of vascular disease and aging. The model shows an exacerbated injury response to strain and is rescued by pharmacological treatments. The progeria-on-a-chip is expected to drive the discovery of new drugs and to

  18. Comparative Evaluation of Some Crop Yield Prediction Models ...

    African Journals Online (AJOL)

    A computer program was adopted from the work of Hill et al. (1982) to calibrate and test three of the existing yield prediction models using tropical cowpea yieldÐweather data. The models tested were Hanks Model (first and second versions). Stewart Model (first and second versions) and HallÐButcher Model. Three sets of ...

  19. Comparative Evaluation of Some Crop Yield Prediction Models ...

    African Journals Online (AJOL)

    (1982) to calibrate and test three of the existing yield prediction models using tropical cowpea yieldÐweather data. The models tested were Hanks Model (first and second versions). Stewart Model (first and second versions) and HallÐButcher Model. Three sets of cowpea yield-water use and weather data were collected.

  20. Prediction of speech intelligibility based on an auditory preprocessing model

    DEFF Research Database (Denmark)

    Christiansen, Claus Forup Corlin; Pedersen, Michael Syskind; Dau, Torsten

    2010-01-01

    Classical speech intelligibility models, such as the speech transmission index (STI) and the speech intelligibility index (SII) are based on calculations on the physical acoustic signals. The present study predicts speech intelligibility by combining a psychoacoustically validated model of auditory...

  1. Modelling microbial interactions and food structure in predictive microbiology

    NARCIS (Netherlands)

    Malakar, P.K.

    2002-01-01

    Keywords: modelling, dynamic models, microbial interactions, diffusion, microgradients, colony growth, predictive microbiology.

    Growth response of microorganisms in foods is a complex process. Innovations in food production and preservation techniques have resulted in adoption of

  2. Ocean wave prediction using numerical and neural network models

    Digital Repository Service at National Institute of Oceanography (India)

    Mandal, S.; Prabaharan, N.

    This paper presents an overview of the development of the numerical wave prediction models and recently used neural networks for ocean wave hindcasting and forecasting. The numerical wave models express the physical concepts of the phenomena...

  3. A Prediction Model of the Capillary Pressure J-Function.

    Directory of Open Access Journals (Sweden)

    W S Xu

    Full Text Available The capillary pressure J-function is a dimensionless measure of the capillary pressure of a fluid in a porous medium. The function was derived based on a capillary bundle model. However, the dependence of the J-function on the saturation Sw is not well understood. A prediction model for it is presented based on capillary pressure model, and the J-function prediction model is a power function instead of an exponential or polynomial function. Relative permeability is calculated with the J-function prediction model, resulting in an easier calculation and results that are more representative.

  4. Rock Fracture Toughness Under Mode II Loading: A Theoretical Model Based on Local Strain Energy Density

    Science.gov (United States)

    Rashidi Moghaddam, M.; Ayatollahi, M. R.; Berto, F.

    2018-01-01

    The values of mode II fracture toughness reported in the literature for several rocks are studied theoretically by using a modified criterion based on strain energy density averaged over a control volume around the crack tip. The modified criterion takes into account the effect of T-stress in addition to the singular terms of stresses/strains. The experimental results are related to mode II fracture tests performed on the semicircular bend and Brazilian disk specimens. There are good agreements between theoretical predictions using the generalized averaged strain energy density criterion and the experimental results. The theoretical results reveal that the value of mode II fracture toughness is affected by the size of control volume around the crack tip and also the magnitude and sign of T-stress.

  5. Substructure based modeling of nickel single crystals cycled at low plastic strain amplitudes

    Science.gov (United States)

    Zhou, Dong

    In this dissertation a meso-scale, substructure-based, composite single crystal model is fully developed from the simple uniaxial model to the 3-D finite element method (FEM) model with explicit substructures and further with substructure evolution parameters, to simulate the completely reversed, strain controlled, low plastic strain amplitude cyclic deformation of nickel single crystals. Rate-dependent viscoplasticity and Armstrong-Frederick type kinematic hardening rules are applied to substructures on slip systems in the model to describe the kinematic hardening behavior of crystals. Three explicit substructure components are assumed in the composite single crystal model, namely "loop patches" and "channels" which are aligned in parallel in a "vein matrix," and persistent slip bands (PSBs) connected in series with the vein matrix. A magnetic domain rotation model is presented to describe the reverse magnetostriction of single crystal nickel. Kinematic hardening parameters are obtained by fitting responses to experimental data in the uniaxial model, and the validity of uniaxial assumption is verified in the 3-D FEM model with explicit substructures. With information gathered from experiments, all control parameters in the model including hardening parameters, volume fraction of loop patches and PSBs, and variation of Young's modulus etc. are correlated to cumulative plastic strain and/or plastic strain amplitude; and the whole cyclic deformation history of single crystal nickel at low plastic strain amplitudes is simulated in the uniaxial model. Then these parameters are implanted in the 3-D FEM model to simulate the formation of PSB bands. A resolved shear stress criterion is set to trigger the formation of PSBs, and stress perturbation in the specimen is obtained by several elements assigned with PSB material properties a priori. Displacement increment, plastic strain amplitude control and overall stress-strain monitor and output are carried out in the user

  6. Computational modelling of traumatic brain injury predicts the location of chronic traumatic encephalopathy pathology.

    Science.gov (United States)

    Ghajari, Mazdak; Hellyer, Peter J; Sharp, David J

    2017-02-01

    Traumatic brain injury can lead to the neurodegenerative disease chronic traumatic encephalopathy. This condition has a clear neuropathological definition but the relationship between the initial head impact and the pattern of progressive brain pathology is poorly understood. We test the hypothesis that mechanical strain and strain rate are greatest in sulci, where neuropathology is prominently seen in chronic traumatic encephalopathy, and whether human neuroimaging observations converge with computational predictions. Three distinct types of injury were simulated. Chronic traumatic encephalopathy can occur after sporting injuries, so we studied a helmet-to-helmet impact in an American football game. In addition, we investigated an occipital head impact due to a fall from ground level and a helmeted head impact in a road traffic accident involving a motorcycle and a car. A high fidelity 3D computational model of brain injury biomechanics was developed and the contours of strain and strain rate at the grey matter-white matter boundary were mapped. Diffusion tensor imaging abnormalities in a cohort of 97 traumatic brain injury patients were also mapped at the grey matter-white matter boundary. Fifty-one healthy subjects served as controls. The computational models predicted large strain most prominent at the depths of sulci. The volume fraction of sulcal regions exceeding brain injury thresholds were significantly larger than that of gyral regions. Strain and strain rates were highest for the road traffic accident and sporting injury. Strain was greater in the sulci for all injury types, but strain rate was greater only in the road traffic and sporting injuries. Diffusion tensor imaging showed converging imaging abnormalities within sulcal regions with a significant decrease in fractional anisotropy in the patient group compared to controls within the sulci. Our results show that brain tissue deformation induced by head impact loading is greatest in sulcal locations

  7. Statistical model based gender prediction for targeted NGS clinical panels

    Directory of Open Access Journals (Sweden)

    Palani Kannan Kandavel

    2017-12-01

    The reference test dataset are being used to test the model. The sensitivity on predicting the gender has been increased from the current “genotype composition in ChrX” based approach. In addition, the prediction score given by the model can be used to evaluate the quality of clinical dataset. The higher prediction score towards its respective gender indicates the higher quality of sequenced data.

  8. Comparative analysis and modeling of the severity of steatohepatitis in DDC-treated mouse strains.

    Directory of Open Access Journals (Sweden)

    Vikash Pandey

    Full Text Available BACKGROUND: Non-alcoholic fatty liver disease (NAFLD has a broad spectrum of disease states ranging from mild steatosis characterized by an abnormal retention of lipids within liver cells to steatohepatitis (NASH showing fat accumulation, inflammation, ballooning and degradation of hepatocytes, and fibrosis. Ultimately, steatohepatitis can result in liver cirrhosis and hepatocellular carcinoma. METHODOLOGY AND RESULTS: In this study we have analyzed three different mouse strains, A/J, C57BL/6J, and PWD/PhJ, that show different degrees of steatohepatitis when administered a 3,5-diethoxycarbonyl-1,4-dihydrocollidine (DDC containing diet. RNA-Seq gene expression analysis, protein analysis and metabolic profiling were applied to identify differentially expressed genes/proteins and perturbed metabolite levels of mouse liver samples upon DDC-treatment. Pathway analysis revealed alteration of arachidonic acid (AA and S-adenosylmethionine (SAMe metabolism upon other pathways. To understand metabolic changes of arachidonic acid metabolism in the light of disease expression profiles a kinetic model of this pathway was developed and optimized according to metabolite levels. Subsequently, the model was used to study in silico effects of potential drug targets for steatohepatitis. CONCLUSIONS: We identified AA/eicosanoid metabolism as highly perturbed in DDC-induced mice using a combination of an experimental and in silico approach. Our analysis of the AA/eicosanoid metabolic pathway suggests that 5-hydroxyeicosatetraenoic acid (5-HETE, 15-hydroxyeicosatetraenoic acid (15-HETE and prostaglandin D2 (PGD2 are perturbed in DDC mice. We further demonstrate that a dynamic model can be used for qualitative prediction of metabolic changes based on transcriptomics data in a disease-related context. Furthermore, SAMe metabolism was identified as being perturbed due to DDC treatment. Several genes as well as some metabolites of this module show differences between A

  9. comparative analysis of two mathematical models for prediction

    African Journals Online (AJOL)

    Abstract. A mathematical modeling for prediction of compressive strength of sandcrete blocks was performed using statistical analysis for the sandcrete block data ob- tained from experimental work done in this study. The models used are Scheffes and Osadebes optimization theories to predict the compressive strength of ...

  10. Comparison of predictive models for the early diagnosis of diabetes

    NARCIS (Netherlands)

    M. Jahani (Meysam); M. Mahdavi (Mahdi)

    2016-01-01

    textabstractObjectives: This study develops neural network models to improve the prediction of diabetes using clinical and lifestyle characteristics. Prediction models were developed using a combination of approaches and concepts. Methods: We used memetic algorithms to update weights and to improve

  11. Testing and analysis of internal hardwood log defect prediction models

    Science.gov (United States)

    R. Edward. Thomas

    2011-01-01

    The severity and location of internal defects determine the quality and value of lumber sawn from hardwood logs. Models have been developed to predict the size and position of internal defects based on external defect indicator measurements. These models were shown to predict approximately 80% of all internal knots based on external knot indicators. However, the size...

  12. Hidden Markov Model for quantitative prediction of snowfall

    Indian Academy of Sciences (India)

    A Hidden Markov Model (HMM) has been developed for prediction of quantitative snowfall in Pir-Panjal and Great Himalayan mountain ranges of Indian Himalaya. The model predicts snowfall for two days in advance using daily recorded nine meteorological variables of past 20 winters from 1992–2012. There are six ...

  13. Bayesian variable order Markov models: Towards Bayesian predictive state representations

    NARCIS (Netherlands)

    Dimitrakakis, C.

    2009-01-01

    We present a Bayesian variable order Markov model that shares many similarities with predictive state representations. The resulting models are compact and much easier to specify and learn than classical predictive state representations. Moreover, we show that they significantly outperform a more

  14. Refining the Committee Approach and Uncertainty Prediction in Hydrological Modelling

    NARCIS (Netherlands)

    Kayastha, N.

    2014-01-01

    Due to the complexity of hydrological systems a single model may be unable to capture the full range of a catchment response and accurately predict the streamflows. The multi modelling approach opens up possibilities for handling such difficulties and allows improve the predictive capability of

  15. Refining the committee approach and uncertainty prediction in hydrological modelling

    NARCIS (Netherlands)

    Kayastha, N.

    2014-01-01

    Due to the complexity of hydrological systems a single model may be unable to capture the full range of a catchment response and accurately predict the streamflows. The multi modelling approach opens up possibilities for handling such difficulties and allows improve the predictive capability of

  16. Wind turbine control and model predictive control for uncertain systems

    DEFF Research Database (Denmark)

    Thomsen, Sven Creutz

    as disturbance models for controller design. The theoretical study deals with Model Predictive Control (MPC). MPC is an optimal control method which is characterized by the use of a receding prediction horizon. MPC has risen in popularity due to its inherent ability to systematically account for time...

  17. Hidden Markov Model for quantitative prediction of snowfall and ...

    Indian Academy of Sciences (India)

    A Hidden Markov Model (HMM) has been developed for prediction of quantitative snowfall in Pir-Panjal and Great Himalayan mountain ranges of Indian Himalaya. The model predicts snowfall for two days in advance using daily recorded nine meteorological variables of past 20 winters from 1992–2012. There are six ...

  18. Model predictive control of a 3-DOF helicopter system using ...

    African Journals Online (AJOL)

    ... by simulation, and its performance is compared with that achieved by linear model predictive control (LMPC). Keywords: nonlinear systems, helicopter dynamics, MIMO systems, model predictive control, successive linearization. International Journal of Engineering, Science and Technology, Vol. 2, No. 10, 2010, pp. 9-19 ...

  19. Models for predicting fuel consumption in sagebrush-dominated ecosystems

    Science.gov (United States)

    Clinton S. Wright

    2013-01-01

    Fuel consumption predictions are necessary to accurately estimate or model fire effects, including pollutant emissions during wildland fires. Fuel and environmental measurements on a series of operational prescribed fires were used to develop empirical models for predicting fuel consumption in big sagebrush (Artemisia tridentate Nutt.) ecosystems....

  20. Comparative Analysis of Two Mathematical Models for Prediction of ...

    African Journals Online (AJOL)

    A mathematical modeling for prediction of compressive strength of sandcrete blocks was performed using statistical analysis for the sandcrete block data obtained from experimental work done in this study. The models used are Scheffe's and Osadebe's optimization theories to predict the compressive strength of sandcrete ...

  1. Modeling the pressure-strain correlation of turbulence: An invariant dynamical systems approach

    Science.gov (United States)

    Speziale, Charles G.; Sarkar, Sutanu; Gatski, Thomas B.

    1990-01-01

    The modeling of the pressure-strain correlation of turbulence is examined from a basic theoretical standpoint with a view toward developing improved second-order closure models. Invariance considerations along with elementary dynamical systems theory are used in the analysis of the standard hierarchy of closure models. In these commonly used models, the pressure-strain correlation is assumed to be a linear function of the mean velocity gradients with coefficients that depend algebraically on the anisotropy tensor. It is proven that for plane homogeneous turbulent flows the equilibrium structure of this hierarchy of models is encapsulated by a relatively simple model which is only quadratically nonlinear in the anisotropy tensor. This new quadratic model - the SSG model - is shown to outperform the Launder, Reece, and Rodi model (as well as more recent models that have a considerably more complex nonlinear structure) in a variety of homogeneous turbulent flows. Some deficiencies still remain for the description of rotating turbulent shear flows that are intrinsic to this general hierarchy of models and, hence, cannot be overcome by the mere introduction of more complex nonlinearities. It is thus argued that the recent trend of adding substantially more complex nonlinear terms containing the anisotropy tensor may be of questionable value in the modeling of the pressure-strain correlation. Possible alternative approaches are discussed briefly.

  2. Modelling the pressure-strain correlation of turbulence - An invariant dynamical systems approach

    Science.gov (United States)

    Speziale, Charles G.; Sarkar, Sutanu; Gatski, Thomas B.

    1991-01-01

    The modeling of the pressure-strain correlation of turbulence is examined from a basic theoretical standpoint with a view toward developing improved second-order closure models. Invariance considerations along with elementary dynamical systems theory are used in the analysis of the standard hierarchy of closure models. In these commonly used models, the pressure-strain correlation is assumed to be a linear function of the mean velocity gradients with coefficients that depend algebraically on the anisotropy tensor. It is proven that for plane homogeneous turbulent flows the equilibrium structure of this hierarchy of models is encapsulated by a relatively simple model which is only quadratically nonlinear in the anisotropy tensor. This new quadratic model - the SSG model - is shown to outperform the Launder, Reece, and Rodi model (as well as more recent models that have a considerably more complex nonlinear structure) in a variety of homogeneous turbulent flows. Some deficiencies still remain for the description of rotating turbulent shear flows that are intrinsic to this general hierarchy of models and, hence, cannot be overcome by the mere introduction of more complex nonlinearities. It is thus argued that the recent trend of adding substantially more complex nonlinear terms containing the anisotropy tensor may be of questionable value in the modeling of the pressure-strain correlation. Possible alternative approaches are discussed briefly.

  3. A mathematical model for predicting earthquake occurrence ...

    African Journals Online (AJOL)

    We consider the continental crust under damage. We use the observed results of microseism in many seismic stations of the world which was established to study the time series of the activities of the continental crust with a view to predicting possible time of occurrence of earthquake. We consider microseism time series ...

  4. Model for predicting the injury severity score.

    Science.gov (United States)

    Hagiwara, Shuichi; Oshima, Kiyohiro; Murata, Masato; Kaneko, Minoru; Aoki, Makoto; Kanbe, Masahiko; Nakamura, Takuro; Ohyama, Yoshio; Tamura, Jun'ichi

    2015-07-01

    To determine the formula that predicts the injury severity score from parameters that are obtained in the emergency department at arrival. We reviewed the medical records of trauma patients who were transferred to the emergency department of Gunma University Hospital between January 2010 and December 2010. The injury severity score, age, mean blood pressure, heart rate, Glasgow coma scale, hemoglobin, hematocrit, red blood cell count, platelet count, fibrinogen, international normalized ratio of prothrombin time, activated partial thromboplastin time, and fibrin degradation products, were examined in those patients on arrival. To determine the formula that predicts the injury severity score, multiple linear regression analysis was carried out. The injury severity score was set as the dependent variable, and the other parameters were set as candidate objective variables. IBM spss Statistics 20 was used for the statistical analysis. Statistical significance was set at P  Watson ratio was 2.200. A formula for predicting the injury severity score in trauma patients was developed with ordinary parameters such as fibrin degradation products and mean blood pressure. This formula is useful because we can predict the injury severity score easily in the emergency department.

  5. Devising Strain Hardening Models Using Kocks–Mecking Plots—A Comparison of Model Development for Titanium Aluminides and Case Hardening Steel

    Directory of Open Access Journals (Sweden)

    Markus Bambach

    2016-08-01

    Full Text Available The present study focuses on the development of strain hardening models taking into account the peculiarities of titanium aluminides. In comparison to steels, whose behavior has been studied extensively in the past, titanium aluminides possess a much larger initial work hardening rate, a sharp peak stress and pronounced softening. The work hardening behavior of a TNB-V4 (Ti–44.5Al–6.25Nb–0.8Mo–0.1B alloy is studied using isothermal hot compression tests conducted on a Gleeble 3500 simulator, and compared to the typical case hardening steel 25MoCrS4. The behavior is analyzed with the help of the Kocks-Mecking plots. In contrast to steel the TNB-V4 alloy shows a non-linear course of θ (i.e., no stage-III hardening initially and exhibits neither a plateau (stage IV hardening nor an inflection point at all deformation conditions. The present paper describes the development and application of a methodology for the design of strain hardening models for the TNB-V4 alloy and the 25CrMoS4 steel by taking the course of the Kocks-Mecking plots into account. Both models use different approaches for the hardening and softening mechanisms and accurately predict the flow stress over a wide range of deformation conditions. The methodology may hence assist in further developments of more sophisticated physically-based strain hardening models for TiAl-alloys.

  6. Radiative and non-radiative recombinations in tensile strained Ge microstrips: Photoluminescence experiments and modeling

    Energy Technology Data Exchange (ETDEWEB)

    Virgilio, M., E-mail: virgilio@df.unipi.it [Dip. di Fisica “E. Fermi,” Università di Pisa, Largo Pontecorvo 3, 56127 Pisa (Italy); NEST, Istituto Nanoscienze-CNR, P.za San Silvestro 12, 56127 Pisa (Italy); Schroeder, T.; Yamamoto, Y. [IHP, Im Technologiepark 25, 15236 Frankfurt (Oder) (Germany); Capellini, G. [IHP, Im Technologiepark 25, 15236 Frankfurt (Oder) (Germany); Dip. di scienze, Università Roma Tre, viale G. Marconi 446, 00146 Roma (Italy)

    2015-12-21

    Tensile germanium microstrips are candidate as gain material in Si-based light emitting devices due to the beneficial effect of the strain field on the radiative recombination rate. In this work, we thoroughly investigate their radiative recombination spectra by means of micro-photoluminescence experiments at different temperatures and excitation powers carried out on samples featuring different tensile strain values. For sake of comparison, bulk Ge(001) photoluminescence is also discussed. The experimental findings are interpreted in light of a numerical modeling based on a multi-valley effective mass approach, taking in to account the depth dependence of the photo-induced carrier density and of the self-absorption effect. The theoretical modeling allowed us to quantitatively describe the observed increase of the photoluminescence intensity for increasing values of strain, excitation power, and temperature. The temperature dependence of the non-radiative recombination time in this material has been inferred thanks to the model calibration procedure.

  7. Analysis of structures based on a characteristic-strain model of creep

    International Nuclear Information System (INIS)

    Bolton, J.

    2008-01-01

    A companion paper [Bolton J. In: A characteristic-strain model for creep, ECCC/I.Mech.E. conference on creep and fracture in high-temperature components, London, September 2005] describes a creep model based on a constant 'characteristic strain' at any temperature. The present paper discusses the application of such a model, first to simple structures and then to engineering components of general form under steady loading. A basis is proposed for identifying the stress within a structure, or within the critical part of a structure, which can be considered to govern both its overall and local deformations. The concept is similar to skeletal-point stress but is more readily applied to components of any shape. The implementation of the concept of 'structural stress' is discussed in the context of finite-element creep calculations. Consideration is given to the analysis of cracked structures, where very high strains at the crack tip must be accommodated

  8. Econometric models for predicting confusion crop ratios

    Science.gov (United States)

    Umberger, D. E.; Proctor, M. H.; Clark, J. E.; Eisgruber, L. M.; Braschler, C. B. (Principal Investigator)

    1979-01-01

    Results for both the United States and Canada show that econometric models can provide estimates of confusion crop ratios that are more accurate than historical ratios. Whether these models can support the LACIE 90/90 accuracy criterion is uncertain. In the United States, experimenting with additional model formulations could provide improved methods models in some CRD's, particularly in winter wheat. Improved models may also be possible for the Canadian CD's. The more aggressive province/state models outperformed individual CD/CRD models. This result was expected partly because acreage statistics are based on sampling procedures, and the sampling precision declines from the province/state to the CD/CRD level. Declining sampling precision and the need to substitute province/state data for the CD/CRD data introduced measurement error into the CD/CRD models.

  9. Fixed recurrence and slip models better predict earthquake behavior than the time- and slip-predictable models 1: repeating earthquakes

    Science.gov (United States)

    Rubinstein, Justin L.; Ellsworth, William L.; Chen, Kate Huihsuan; Uchida, Naoki

    2012-01-01

    The behavior of individual events in repeating earthquake sequences in California, Taiwan and Japan is better predicted by a model with fixed inter-event time or fixed slip than it is by the time- and slip-predictable models for earthquake occurrence. Given that repeating earthquakes are highly regular in both inter-event time and seismic moment, the time- and slip-predictable models seem ideally suited to explain their behavior. Taken together with evidence from the companion manuscript that shows similar results for laboratory experiments we conclude that the short-term predictions of the time- and slip-predictable models should be rejected in favor of earthquake models that assume either fixed slip or fixed recurrence interval. This implies that the elastic rebound model underlying the time- and slip-predictable models offers no additional value in describing earthquake behavior in an event-to-event sense, but its value in a long-term sense cannot be determined. These models likely fail because they rely on assumptions that oversimplify the earthquake cycle. We note that the time and slip of these events is predicted quite well by fixed slip and fixed recurrence models, so in some sense they are time- and slip-predictable. While fixed recurrence and slip models better predict repeating earthquake behavior than the time- and slip-predictable models, we observe a correlation between slip and the preceding recurrence time for many repeating earthquake sequences in Parkfield, California. This correlation is not found in other regions, and the sequences with the correlative slip-predictable behavior are not distinguishable from nearby earthquake sequences that do not exhibit this behavior.

  10. Adding propensity scores to pure prediction models fails to improve predictive performance

    Directory of Open Access Journals (Sweden)

    Amy S. Nowacki

    2013-08-01

    Full Text Available Background. Propensity score usage seems to be growing in popularity leading researchers to question the possible role of propensity scores in prediction modeling, despite the lack of a theoretical rationale. It is suspected that such requests are due to the lack of differentiation regarding the goals of predictive modeling versus causal inference modeling. Therefore, the purpose of this study is to formally examine the effect of propensity scores on predictive performance. Our hypothesis is that a multivariable regression model that adjusts for all covariates will perform as well as or better than those models utilizing propensity scores with respect to model discrimination and calibration.Methods. The most commonly encountered statistical scenarios for medical prediction (logistic and proportional hazards regression were used to investigate this research question. Random cross-validation was performed 500 times to correct for optimism. The multivariable regression models adjusting for all covariates were compared with models that included adjustment for or weighting with the propensity scores. The methods were compared based on three predictive performance measures: (1 concordance indices; (2 Brier scores; and (3 calibration curves.Results. Multivariable models adjusting for all covariates had the highest average concordance index, the lowest average Brier score, and the best calibration. Propensity score adjustment and inverse probability weighting models without adjustment for all covariates performed worse than full models and failed to improve predictive performance with full covariate adjustment.Conclusion. Propensity score techniques did not improve prediction performance measures beyond multivariable adjustment. Propensity scores are not recommended if the analytical goal is pure prediction modeling.

  11. PEEX Modelling Platform for Seamless Environmental Prediction

    Science.gov (United States)

    Baklanov, Alexander; Mahura, Alexander; Arnold, Stephen; Makkonen, Risto; Petäjä, Tuukka; Kerminen, Veli-Matti; Lappalainen, Hanna K.; Ezau, Igor; Nuterman, Roman; Zhang, Wen; Penenko, Alexey; Gordov, Evgeny; Zilitinkevich, Sergej; Kulmala, Markku

    2017-04-01

    The Pan-Eurasian EXperiment (PEEX) is a multidisciplinary, multi-scale research programme stared in 2012 and aimed at resolving the major uncertainties in Earth System Science and global sustainability issues concerning the Arctic and boreal Northern Eurasian regions and in China. Such challenges include climate change, air quality, biodiversity loss, chemicalization, food supply, and the use of natural resources by mining, industry, energy production and transport. The research infrastructure introduces the current state of the art modeling platform and observation systems in the Pan-Eurasian region and presents the future baselines for the coherent and coordinated research infrastructures in the PEEX domain. The PEEX modeling Platform is characterized by a complex seamless integrated Earth System Modeling (ESM) approach, in combination with specific models of different processes and elements of the system, acting on different temporal and spatial scales. The ensemble approach is taken to the integration of modeling results from different models, participants and countries. PEEX utilizes the full potential of a hierarchy of models: scenario analysis, inverse modeling, and modeling based on measurement needs and processes. The models are validated and constrained by available in-situ and remote sensing data of various spatial and temporal scales using data assimilation and top-down modeling. The analyses of the anticipated large volumes of data produced by available models and sensors will be supported by a dedicated virtual research environment developed for these purposes.

  12. Prediction of Local Ultimate Strain and Toughness of Trabecular Bone Tissue by Raman Material Composition Analysis

    OpenAIRE

    Carretta, Roberto; Stüssi, Edgar; Müller, Ralph; Lorenzetti, Silvio

    2015-01-01

    Clinical studies indicate that bone mineral density correlates with fracture risk at the population level but does not correlate with individual fracture risk well. Current research aims to better understand the failure mechanism of bone and to identify key determinants of bone quality, thus improving fracture risk prediction. To get a better understanding of bone strength, it is important to analyze tissue-level properties not influenced by macro- or microarchitectural factors. The aim of th...

  13. Direct construction of predictive models for describing growth Salmonella enteritidis in liquid eggs – a one-step approach

    Science.gov (United States)

    The objective of this study was to develop a new approach using a one-step approach to directly construct predictive models for describing the growth of Salmonella Enteritidis (SE) in liquid egg white (LEW) and egg yolk (LEY). A five-strain cocktail of SE, induced to resist rifampicin at 100 mg/L, ...

  14. Analysis of the dengue disease model with two virus strains

    Science.gov (United States)

    Adi-Kusumo, F.; Aini, A. N.; Ridwan, M.

    2014-02-01

    Dengue fever (DF) and dengue haemorrhagic fever (DHF) are the disease caused by the dengue virus which is transmitted to the human by infected female mosquitoes. The disease is endemic in more than 100 countries over the world. Dengue virus has four distinct serotypes which are closely related to each other antigenically. A person who infected by the dengue virus will never be infected again by the same serotype, but he looses immunity from the three other serotypes. Infection with one serotype does not provide cross-protective immunity against to others. Here we assume that there are two serotypes exist in the population. Someone who has recovered from one serotype become susceptible to the other serotype and can be reinfected. In this paper we analyze the model of dengue fever with two infections from the different serotype by linear analysis. Then we study the effect of vaccination to the model. In numerical simulation, we use Runge-Kutta order 4 to integrate the solution of the system.

  15. Modeling the kinematic effect of horizontal strain rates on firn depth-density profiles

    Science.gov (United States)

    Horlings, A. N.; Stevens, C. M.; Holschuh, N.; Christianson, K. A.; Waddington, E. D.

    2017-12-01

    Firn compaction must be considered in interpretation of satellite repeat-altimetry measurements for ice-sheet mass balance estimates that are used to determine land-ice contribution to sea-level change. Firn compaction models remain the largest source of uncertainty in determining ice-sheet mass balance from repeat altimetry because the physical processes responsible for firn compaction are not fully understood. Most commonly used firn compaction models are 1-D, empirical or semi-empirical, and built on steady-state assumptions. These assumptions may be inappropriate in some regions, particularly areas of dynamic flow. In many of these regions, the horizontal strain rate due to dynamic ice flow can be similar in magnitude to the vertical strain rate from firn compaction. Therefore, horizontal stresses are important to consider in calculating firn depth-density profiles, yet are not represented in the current generation of firn compaction models. Here, we incorporate the kinematic effect of longitudinal strain on firn depth-density profiles in the dry snow zone. In every time step, the firn first densifies and consequently thins via a firn densification model; then, the firn stretches (thins) as stipulated by an imposed longitudinal strain rate without further density changes. Idealized tests show that the kinematic effect for longitudinal strain rates larger than 10-4 yr-1 can significantly decrease the depth-integrated porosity (> 0.5m) for climatic conditions representative of northeast Greenland. For conditions common on Thwaites Glacier, West Antarctica, results indicate that the kinematic effect on the firn column can shallow the bubble close-off depth by 20m and decrease the depth-integrated porosity by 7m. These results suggest that incorporating horizontal stresses into firn compaction models is essential to accurately model firn depth-density profiles in regions of ice sheets with high horizontal strain rates.

  16. Models Predicting Success of Infertility Treatment: A Systematic Review

    Science.gov (United States)

    Zarinara, Alireza; Zeraati, Hojjat; Kamali, Koorosh; Mohammad, Kazem; Shahnazari, Parisa; Akhondi, Mohammad Mehdi

    2016-01-01

    Background: Infertile couples are faced with problems that affect their marital life. Infertility treatment is expensive and time consuming and occasionally isn’t simply possible. Prediction models for infertility treatment have been proposed and prediction of treatment success is a new field in infertility treatment. Because prediction of treatment success is a new need for infertile couples, this paper reviewed previous studies for catching a general concept in applicability of the models. Methods: This study was conducted as a systematic review at Avicenna Research Institute in 2015. Six data bases were searched based on WHO definitions and MESH key words. Papers about prediction models in infertility were evaluated. Results: Eighty one papers were eligible for the study. Papers covered years after 1986 and studies were designed retrospectively and prospectively. IVF prediction models have more shares in papers. Most common predictors were age, duration of infertility, ovarian and tubal problems. Conclusion: Prediction model can be clinically applied if the model can be statistically evaluated and has a good validation for treatment success. To achieve better results, the physician and the couples’ needs estimation for treatment success rate were based on history, the examination and clinical tests. Models must be checked for theoretical approach and appropriate validation. The privileges for applying the prediction models are the decrease in the cost and time, avoiding painful treatment of patients, assessment of treatment approach for physicians and decision making for health managers. The selection of the approach for designing and using these models is inevitable. PMID:27141461

  17. Towards a generalized energy prediction model for machine tools.

    Science.gov (United States)

    Bhinge, Raunak; Park, Jinkyoo; Law, Kincho H; Dornfeld, David A; Helu, Moneer; Rachuri, Sudarsan

    2017-04-01

    Energy prediction of machine tools can deliver many advantages to a manufacturing enterprise, ranging from energy-efficient process planning to machine tool monitoring. Physics-based, energy prediction models have been proposed in the past to understand the energy usage pattern of a machine tool. However, uncertainties in both the machine and the operating environment make it difficult to predict the energy consumption of the target machine reliably. Taking advantage of the opportunity to collect extensive, contextual, energy-consumption data, we discuss a data-driven approach to develop an energy prediction model of a machine tool in this paper. First, we present a methodology that can efficiently and effectively collect and process data extracted from a machine tool and its sensors. We then present a data-driven model that can be used to predict the energy consumption of the machine tool for machining a generic part. Specifically, we use Gaussian Process (GP) Regression, a non-parametric machine-learning technique, to develop the prediction model. The energy prediction model is then generalized over multiple process parameters and operations. Finally, we apply this generalized model with a method to assess uncertainty intervals to predict the energy consumed to machine any part using a Mori Seiki NVD1500 machine tool. Furthermore, the same model can be used during process planning to optimize the energy-efficiency of a machining process.

  18. Poisson Mixture Regression Models for Heart Disease Prediction

    Science.gov (United States)

    Erol, Hamza

    2016-01-01

    Early heart disease control can be achieved by high disease prediction and diagnosis efficiency. This paper focuses on the use of model based clustering techniques to predict and diagnose heart disease via Poisson mixture regression models. Analysis and application of Poisson mixture regression models is here addressed under two different classes: standard and concomitant variable mixture regression models. Results show that a two-component concomitant variable Poisson mixture regression model predicts heart disease better than both the standard Poisson mixture regression model and the ordinary general linear Poisson regression model due to its low Bayesian Information Criteria value. Furthermore, a Zero Inflated Poisson Mixture Regression model turned out to be the best model for heart prediction over all models as it both clusters individuals into high or low risk category and predicts rate to heart disease componentwise given clusters available. It is deduced that heart disease prediction can be effectively done by identifying the major risks componentwise using Poisson mixture regression model. PMID:27999611

  19. Comparison of Predictive Models for the Early Diagnosis of Diabetes.

    Science.gov (United States)

    Jahani, Meysam; Mahdavi, Mahdi

    2016-04-01

    This study develops neural network models to improve the prediction of diabetes using clinical and lifestyle characteristics. Prediction models were developed using a combination of approaches and concepts. We used memetic algorithms to update weights and to improve prediction accuracy of models. In the first step, the optimum amount for neural network parameters such as momentum rate, transfer function, and error function were obtained through trial and error and based on the results of previous studies. In the second step, optimum parameters were applied to memetic algorithms in order to improve the accuracy of prediction. This preliminary analysis showed that the accuracy of neural networks is 88%. In the third step, the accuracy of neural network models was improved using a memetic algorithm and resulted model was compared with a logistic regression model using a confusion matrix and receiver operating characteristic curve (ROC). The memetic algorithm improved the accuracy from 88.0% to 93.2%. We also found that memetic algorithm had a higher accuracy than the model from the genetic algorithm and a regression model. Among models, the regression model has the least accuracy. For the memetic algorithm model the amount of sensitivity, specificity, positive predictive value, negative predictive value, and ROC are 96.2, 95.3, 93.8, 92.4, and 0.958 respectively. The results of this study provide a basis to design a Decision Support System for risk management and planning of care for individuals at risk of diabetes.

  20. Prediction of the Stress-Strain Behavior of Open-Cell Aluminum Foam under Compressive Loading and the Effects of Various RVE Boundary Conditions

    Science.gov (United States)

    Hamidi Ghaleh Jigh, Behrang; Farsi, Mohammad Ali; Hosseini Toudeshky, Hossein

    2018-04-01

    The prediction of the mechanical behavior of metallic foams with realistic microstructure and the effects of various boundary conditions on the mechanical behavior is an important and challenging issue in modeling representative volume elements (RVEs). A numerical investigation is conducted to determine the effects of various boundary conditions and cell wall cross sections on the compressive mechanical properties of aluminum foam, including the stiffness, plateau stress and onset strain of densification. The open-cell AA6101-T6 aluminum foam Duocel is used in the analyses in this study. Geometrical characteristics including the cell size, foam relative density, and cross-sectional shape and thickness of the cell walls are extracted from images of the foam. Then, the obtained foam microstructure is analyzed as a 2D model. The ligaments are modeled as shear deformable beams with elastic-plastic material behavior. To prevent interpenetration of the nodes and walls inside the cells with large deformations, self-contact-type frictionless interaction is stipulated between the internal surfaces. Sensitivity analyses are performed using several boundary conditions and cells wall cross-sectional shapes. The predicted results from the finite element analyses are compared with the experimental results. Finally, the most appropriate boundary conditions, leading to more consistent results with the experimental data, are introduced.

  1. A CONSTITUTIVE MODEL FOR STRAIN RATES FROM 10-4 TO 106 s-1

    OpenAIRE

    Steinberg, D.; Lund, C.

    1988-01-01

    We have developed an addition to the Steinberg-Guinan high strainrate constitutive model that extends its validity to strain rates as low as 10-4 s-1. With this new model, we have successfully reproduced a number of rate-dependent, shock-induced phenomena in tantalum, such as precursor on reshock, precursor decay, and shock smearing. We have also successfully calculated a plate-impact experiment at a loading stress of 230 GPa as well as extensive date for yield strength vs strain-rate at room...

  2. Applications of modeling in polymer-property prediction

    Science.gov (United States)

    Case, F. H.

    1996-08-01

    A number of molecular modeling techniques have been applied for the prediction of polymer properties and behavior. Five examples illustrate the range of methodologies used. A simple atomistic simulation of small polymer fragments is used to estimate drug compatibility with a polymer matrix. The analysis of molecular dynamics results from a more complex model of a swollen hydrogel system is used to study gas diffusion in contact lenses. Statistical mechanics are used to predict conformation dependent properties — an example is the prediction of liquid-crystal formation. The effect of the molecular weight distribution on phase separation in polyalkanes is predicted using thermodynamic models. In some cases, the properties of interest cannot be directly predicted using simulation methods or polymer theory. Correlation methods may be used to bridge the gap between molecular structure and macroscopic properties. The final example shows how connectivity-indices-based quantitative structure-property relationships were used to predict properties for candidate polyimids in an electronics application.

  3. Artificial Neural Network Model for Predicting Compressive

    OpenAIRE

    Salim T. Yousif; Salwa M. Abdullah

    2013-01-01

      Compressive strength of concrete is a commonly used criterion in evaluating concrete. Although testing of the compressive strength of concrete specimens is done routinely, it is performed on the 28th day after concrete placement. Therefore, strength estimation of concrete at early time is highly desirable. This study presents the effort in applying neural network-based system identification techniques to predict the compressive strength of concrete based on concrete mix proportions, maximum...

  4. Prediction of hourly solar radiation with multi-model framework

    International Nuclear Information System (INIS)

    Wu, Ji; Chan, Chee Keong

    2013-01-01

    Highlights: • A novel approach to predict solar radiation through the use of clustering paradigms. • Development of prediction models based on the intrinsic pattern observed in each cluster. • Prediction based on proper clustering and selection of model on current time provides better results than other methods. • Experiments were conducted on actual solar radiation data obtained from a weather station in Singapore. - Abstract: In this paper, a novel multi-model prediction framework for prediction of solar radiation is proposed. The framework started with the assumption that there are several patterns embedded in the solar radiation series. To extract the underlying pattern, the solar radiation series is first segmented into smaller subsequences, and the subsequences are further grouped into different clusters. For each cluster, an appropriate prediction model is trained. Hence a procedure for pattern identification is developed to identify the proper pattern that fits the current period. Based on this pattern, the corresponding prediction model is applied to obtain the prediction value. The prediction result of the proposed framework is then compared to other techniques. It is shown that the proposed framework provides superior performance as compared to others

  5. Influence of Different Yield Loci on Failure Prediction with Damage Models

    Science.gov (United States)

    Heibel, S.; Nester, W.; Clausmeyer, T.; Tekkaya, A. E.

    2017-09-01

    Advanced high strength steels are widely used in the automotive industry to simultaneously improve crash performance and reduce the car body weight. A drawback of these multiphase steels is their sensitivity to damage effects and thus the reduction of ductility. For that reason the Forming Limit Curve is only partially suitable for this class of steels. An improvement in failure prediction can be obtained by using damage mechanics. The objective of this paper is to comparatively review the phenomenological damage model GISSMO and the Enhanced Lemaitre Damage Model. GISSMO is combined with three different yield loci, namely von Mises, Hill48 and Barlat2000 to investigate the influence of the choice of the plasticity description on damage modelling. The Enhanced Lemaitre Model is used with Hill48. An inverse parameter identification strategy for a DP1000 based on stress-strain curves and optical strain measurements of shear, uniaxial, notch and (equi-)biaxial tension tests is applied to calibrate the models. A strong dependency of fracture strains on the choice of yield locus can be observed. The identified models are validated on a cross-die cup showing ductile fracture with slight necking.

  6. Investigating the conformational stability of prion strains through a kinetic replication model.

    Directory of Open Access Journals (Sweden)

    Mattia Zampieri

    2009-07-01

    Full Text Available Prion proteins are known to misfold into a range of different aggregated forms, showing different phenotypic and pathological states. Understanding strain specificities is an important problem in the field of prion disease. Little is known about which PrP(Sc structural properties and molecular mechanisms determine prion replication, disease progression and strain phenotype. The aim of this work is to investigate, through a mathematical model, how the structural stability of different aggregated forms can influence the kinetics of prion replication. The model-based results suggest that prion strains with different conformational stability undergoing in vivo replication are characterizable in primis by means of different rates of breakage. A further role seems to be played by the aggregation rate (i.e. the rate at which a prion fibril grows. The kinetic variability introduced in the model by these two parameters allows us to reproduce the different characteristic features of the various strains (e.g., fibrils' mean length and is coherent with all experimental observations concerning strain-specific behavior.

  7. A processing plant persistent strain of Listeria monocytogenes crosses the fetoplacental barrier in a pregnant guinea pig model

    DEFF Research Database (Denmark)

    Jensen, Anne; Williams, D.; Irving, E. A.

    2008-01-01

    independent fish processing plants. The purpose of the present study was to determine the virulence potential of one RAPD type 9 strain (La111), one human clinical strain (Scott A), and one monkey clinical strain (12443) in a pregnant guinea pig model. Animals were orally exposed to 10(8) CFU of L...

  8. PREDICTION OF MAXIMUM CREEP STRAIN OF HIGH PERFORMANCE STEEL FIBER REINFORCED CONCRETE

    Directory of Open Access Journals (Sweden)

    Mishina Alexandra Vasil'evna

    2012-12-01

    Full Text Available The strongest research potential is demonstrated by the areas of application of high performance steel fiber reinforced concrete (HPSFRC. The research of its rheological characteristics is very important for the purposes of understanding its behaviour. This article is an overview of an experimental study of UHSSFRC. The study was carried out in the form of lasting creep tests of HPSFRC prism specimen, loaded by stresses of varied intensity. The loading was performed at different ages: 7, 14, 28 and 90 days after concreting. The stress intensity was 0.3 and 0.6 Rb; it was identified on the basis of short-term crush tests of similar prism-shaped specimen, performed on the same day. As a result, values of ultimate creep strains and ultimate specific creep of HPSFRC were identified. The data was used to construct an experimental diagramme of the ultimate specific creep on the basis of the HPSFRC loading age if exposed to various stresses. The research has resulted in the identification of a theoretical relationship that may serve as the basis for the high-precision projection of the pattern of changes in the ultimate specific creep of HPSFRC, depending on the age of loading and the stress intensity.

  9. Application of strain-controlled fatigue concepts to the prediction of weldment fatigue life

    International Nuclear Information System (INIS)

    Lawrence, F.V. Jr.; Mazumdar, P.K.; Illinois Univ., Urbana

    1979-01-01

    The total fatigue life of weldments has been estimated for butt welds using strain controlled fatigue and fatigue crack propagation concepts. Key developments which facilitated these estimates were the assumption of Ksub(f max) conditions (the largest value of Ksub(f) possible for a given weld shape). The total fatigue life was estimated as the sum of a fatigue crack initiation period (cycles to obtain a 0.25 mm fatigue crack) and the fatigue crack propagation period. Mean stress relaxation effects and the fatigue properties of the actual weld zone materials were considered. Influence of welding residual stresses and material strength level were also investigated. The initiation life was found to be very sensitive to changes in Ksub(f) but not too sensitive to strength level. The importance of residual stresses and mean stress varied with material as did the fraction of total life devoted to crack initiation. Mild steels, quenched and tempered high strength low alloy steels, and aluminium alloy welds were considered. (orig.) 891 RW/orig. 892 RKD [de

  10. The fitness landscape of HIV-1 gag: advanced modeling approaches and validation of model predictions by in vitro testing.

    Directory of Open Access Journals (Sweden)

    Jaclyn K Mann

    2014-08-01

    Full Text Available Viral immune evasion by sequence variation is a major hindrance to HIV-1 vaccine design. To address this challenge, our group has developed a computational model, rooted in physics, that aims to predict the fitness landscape of HIV-1 proteins in order to design vaccine immunogens that lead to impaired viral fitness, thus blocking viable escape routes. Here, we advance the computational models to address previous limitations, and directly test model predictions against in vitro fitness measurements of HIV-1 strains containing multiple Gag mutations. We incorporated regularization into the model fitting procedure to address finite sampling. Further, we developed a model that accounts for the specific identity of mutant amino acids (Potts model, generalizing our previous approach (Ising model that is unable to distinguish between different mutant amino acids. Gag mutation combinations (17 pairs, 1 triple and 25 single mutations within these predicted to be either harmful to HIV-1 viability or fitness-neutral were introduced into HIV-1 NL4-3 by site-directed mutagenesis and replication capacities of these mutants were assayed in vitro. The predicted and measured fitness of the corresponding mutants for the original Ising model (r = -0.74, p = 3.6×10-6 are strongly correlated, and this was further strengthened in the regularized Ising model (r = -0.83, p = 3.7×10-12. Performance of the Potts model (r = -0.73, p = 9.7×10-9 was similar to that of the Ising model, indicating that the binary approximation is sufficient for capturing fitness effects of common mutants at sites of low amino acid diversity. However, we show that the Potts model is expected to improve predictive power for more variable proteins. Overall, our results support the ability of the computational models to robustly predict the relative fitness of mutant viral strains, and indicate the potential value of this approach for understanding viral immune evasion

  11. The fitness landscape of HIV-1 gag: advanced modeling approaches and validation of model predictions by in vitro testing.

    Science.gov (United States)

    Mann, Jaclyn K; Barton, John P; Ferguson, Andrew L; Omarjee, Saleha; Walker, Bruce D; Chakraborty, Arup; Ndung'u, Thumbi

    2014-08-01

    Viral immune evasion by sequence variation is a major hindrance to HIV-1 vaccine design. To address this challenge, our group has developed a computational model, rooted in physics, that aims to predict the fitness landscape of HIV-1 proteins in order to design vaccine immunogens that lead to impaired viral fitness, thus blocking viable escape routes. Here, we advance the computational models to address previous limitations, and directly test model predictions against in vitro fitness measurements of HIV-1 strains containing multiple Gag mutations. We incorporated regularization into the model fitting procedure to address finite sampling. Further, we developed a model that accounts for the specific identity of mutant amino acids (Potts model), generalizing our previous approach (Ising model) that is unable to distinguish between different mutant amino acids. Gag mutation combinations (17 pairs, 1 triple and 25 single mutations within these) predicted to be either harmful to HIV-1 viability or fitness-neutral were introduced into HIV-1 NL4-3 by site-directed mutagenesis and replication capacities of these mutants were assayed in vitro. The predicted and measured fitness of the corresponding mutants for the original Ising model (r = -0.74, p = 3.6×10-6) are strongly correlated, and this was further strengthened in the regularized Ising model (r = -0.83, p = 3.7×10-12). Performance of the Potts model (r = -0.73, p = 9.7×10-9) was similar to that of the Ising model, indicating that the binary approximation is sufficient for capturing fitness effects of common mutants at sites of low amino acid diversity. However, we show that the Potts model is expected to improve predictive power for more variable proteins. Overall, our results support the ability of the computational models to robustly predict the relative fitness of mutant viral strains, and indicate the potential value of this approach for understanding viral immune evasion, and

  12. Posterior Predictive Model Checking for Multidimensionality in Item Response Theory

    Science.gov (United States)

    Levy, Roy; Mislevy, Robert J.; Sinharay, Sandip

    2009-01-01

    If data exhibit multidimensionality, key conditional independence assumptions of unidimensional models do not hold. The current work pursues posterior predictive model checking, a flexible family of model-checking procedures, as a tool for criticizing models due to unaccounted for dimensions in the context of item response theory. Factors…

  13. Model predictive control of a crude oil distillation column

    Directory of Open Access Journals (Sweden)

    Morten Hovd

    1999-04-01

    Full Text Available The project of designing and implementing model based predictive control on the vacuum distillation column at the Nynäshamn Refinery of Nynäs AB is described in this paper. The paper describes in detail the modeling for the model based control, covers the controller implementation, and documents the benefits gained from the model based controller.

  14. Enhancing Flood Prediction Reliability Using Bayesian Model Averaging

    Science.gov (United States)

    Liu, Z.; Merwade, V.

    2017-12-01

    Uncertainty analysis is an indispensable part of modeling the hydrology and hydrodynamics of non-idealized environmental systems. Compared to reliance on prediction from one model simulation, using on ensemble of predictions that consider uncertainty from different sources is more reliable. In this study, Bayesian model averaging (BMA) is applied to Black River watershed in Arkansas and Missouri by combining multi-model simulations to get reliable deterministic water stage and probabilistic inundation extent predictions. The simulation ensemble is generated from 81 LISFLOOD-FP subgrid model configurations that include uncertainty from channel shape, channel width, channel roughness and discharge. Model simulation outputs are trained with observed water stage data during one flood event, and BMA prediction ability is validated for another flood event. Results from this study indicate that BMA does not always outperform all members in the ensemble, but it provides relatively robust deterministic flood stage predictions across the basin. Station based BMA (BMA_S) water stage prediction has better performance than global based BMA (BMA_G) prediction which is superior to the ensemble mean prediction. Additionally, high-frequency flood inundation extent (probability greater than 60%) in BMA_G probabilistic map is more accurate than the probabilistic flood inundation extent based on equal weights.

  15. A longitudinal examination of the Adaptation to Poverty-Related Stress Model: predicting child and adolescent adjustment over time.

    Science.gov (United States)

    Wadsworth, Martha E; Rindlaub, Laura; Hurwich-Reiss, Eliana; Rienks, Shauna; Bianco, Hannah; Markman, Howard J

    2013-01-01

    This study tests key tenets of the Adaptation to Poverty-related Stress Model. This model (Wadsworth, Raviv, Santiago, & Etter, 2011 ) builds on Conger and Elder's family stress model by proposing that primary control coping and secondary control coping can help reduce the negative effects of economic strain on parental behaviors central to the family stress model, namely, parental depressive symptoms and parent-child interactions, which together can decrease child internalizing and externalizing problems. Two hundred seventy-five co-parenting couples with children between the ages of 1 and 18 participated in an evaluation of a brief family strengthening intervention, aimed at preventing economic strain's negative cascade of influence on parents, and ultimately their children. The longitudinal path model, analyzed at the couple dyad level with mothers and fathers nested within couple, showed very good fit, and was not moderated by child gender or ethnicity. Analyses revealed direct positive effects of primary control coping and secondary control coping on mothers' and fathers' depressive symptoms. Decreased economic strain predicted more positive father-child interactions, whereas increased secondary control coping predicted less negative mother-child interactions. Positive parent-child interactions, along with decreased parent depression and economic strain, predicted child internalizing and externalizing over the course of 18 months. Multiple-group models analyzed separately by parent gender revealed, however, that child age moderated father effects. Findings provide support for the adaptation to poverty-related stress model and suggest that prevention and clinical interventions for families affected by poverty-related stress may be strengthened by including modules that address economic strain and efficacious strategies for coping with strain.

  16. Genomic prediction of complex human traits: relatedness, trait architecture and predictive meta-models

    Science.gov (United States)

    Spiliopoulou, Athina; Nagy, Reka; Bermingham, Mairead L.; Huffman, Jennifer E.; Hayward, Caroline; Vitart, Veronique; Rudan, Igor; Campbell, Harry; Wright, Alan F.; Wilson, James F.; Pong-Wong, Ricardo; Agakov, Felix; Navarro, Pau; Haley, Chris S.

    2015-01-01

    We explore the prediction of individuals' phenotypes for complex traits using genomic data. We compare several widely used prediction models, including Ridge Regression, LASSO and Elastic Nets estimated from cohort data, and polygenic risk scores constructed using published summary statistics from genome-wide association meta-analyses (GWAMA). We evaluate the interplay between relatedness, trait architecture and optimal marker density, by predicting height, body mass index (BMI) and high-density lipoprotein level (HDL) in two data cohorts, originating from Croatia and Scotland. We empirically demonstrate that dense models are better when all genetic effects are small (height and BMI) and target individuals are related to the training samples, while sparse models predict better in unrelated individuals and when some effects have moderate size (HDL). For HDL sparse models achieved good across-cohort prediction, performing similarly to the GWAMA risk score and to models trained within the same cohort, which indicates that, for predicting traits with moderately sized effects, large sample sizes and familial structure become less important, though still potentially useful. Finally, we propose a novel ensemble of whole-genome predictors with GWAMA risk scores and demonstrate that the resulting meta-model achieves higher prediction accuracy than either model on its own. We conclude that although current genomic predictors are not accurate enough for diagnostic purposes, performance can be improved without requiring access to large-scale individual-level data. Our methodologically simple meta-model is a means of performing predictive meta-analysis for optimizing genomic predictions and can be easily extended to incorporate multiple population-level summary statistics or other domain knowledge. PMID:25918167

  17. Immune Modulating Capability of Two Exopolysaccharide-Producing Bifidobacterium Strains in a Wistar Rat Model

    Directory of Open Access Journals (Sweden)

    Nuria Salazar

    2014-01-01

    Full Text Available Fermented dairy products are the usual carriers for the delivery of probiotics to humans, Bifidobacterium and Lactobacillus being the most frequently used bacteria. In this work, the strains Bifidobacterium animalis subsp. lactis IPLA R1 and Bifidobacterium longum IPLA E44 were tested for their capability to modulate immune response and the insulin-dependent glucose homeostasis using male Wistar rats fed with a standard diet. Three intervention groups were fed daily for 24 days with 10% skimmed milk, or with 109 cfu of the corresponding strain suspended in the same vehicle. A significant increase of the suppressor-regulatory TGF-β cytokine occurred with both strains in comparison with a control (no intervention group of rats; the highest levels were reached in rats fed IPLA R1. This strain presented an immune protective profile, as it was able to reduce the production of the proinflammatory IL-6. Moreover, phosphorylated Akt kinase decreased in gastroctemius muscle of rats fed the strain IPLA R1, without affecting the glucose, insulin, and HOMA index in blood, or levels of Glut-4 located in the membrane of muscle and adipose tissue cells. Therefore, the strain B. animalis subsp. lactis IPLA R1 is a probiotic candidate to be tested in mild grade inflammation animal models.

  18. Strain-specific virulence phenotypes of Streptococcus pneumoniae assessed using the Chinchilla laniger model of otitis media.

    OpenAIRE

    Michael L Forbes; Edward Horsey; N Luisa Hiller; Farrel J Buchinsky; Jay D Hayes; James M Compliment; Todd Hillman; Suzanne Ezzo; Kai Shen; Randy Keefe; Karen Barbadora; J Christopher Post; Fen Ze Hu; Garth D Ehrlich

    2008-01-01

    Background Streptococcus pneumoniae [Sp] infection is associated with local and systemic disease. Our current understanding of the differential contributions of genetic strain variation, serotype, and host response to disease phenotype is incomplete. Using the chinchilla model of otitis media [OM] we investigated the disease phenotype generated by the laboratory strain TIGR4 and each of thirteen clinical strains (BS68-75, BS290, BS291, BS293, BS436 and BS437); eleven of the thirteen strains h...

  19. Predictive models for acute kidney injury following cardiac surgery.

    Science.gov (United States)

    Demirjian, Sevag; Schold, Jesse D; Navia, Jose; Mastracci, Tara M; Paganini, Emil P; Yared, Jean-Pierre; Bashour, Charles A

    2012-03-01

    Accurate prediction of cardiac surgery-associated acute kidney injury (AKI) would improve clinical decision making and facilitate timely diagnosis and treatment. The aim of the study was to develop predictive models for cardiac surgery-associated AKI using presurgical and combined pre- and intrasurgical variables. Prospective observational cohort. 25,898 patients who underwent cardiac surgery at Cleveland Clinic in 2000-2008. Presurgical and combined pre- and intrasurgical variables were used to develop predictive models. Dialysis therapy and a composite of doubling of serum creatinine level or dialysis therapy within 2 weeks (or discharge if sooner) after cardiac surgery. Incidences of dialysis therapy and the composite of doubling of serum creatinine level or dialysis therapy were 1.7% and 4.3%, respectively. Kidney function parameters were strong independent predictors in all 4 models. Surgical complexity reflected by type and history of previous cardiac surgery were robust predictors in models based on presurgical variables. However, the inclusion of intrasurgical variables accounted for all explained variance by procedure-related information. Models predictive of dialysis therapy showed good calibration and superb discrimination; a combined (pre- and intrasurgical) model performed better than the presurgical model alone (C statistics, 0.910 and 0.875, respectively). Models predictive of the composite end point also had excellent discrimination with both presurgical and combined (pre- and intrasurgical) variables (C statistics, 0.797 and 0.825, respectively). However, the presurgical model predictive of the composite end point showed suboptimal calibration (P predictive models in other cohorts is required before wide-scale application. We developed and internally validated 4 new models that accurately predict cardiac surgery-associated AKI. These models are based on readily available clinical information and can be used for patient counseling, clinical

  20. Modeling number of claims and prediction of total claim amount

    Science.gov (United States)

    Acar, Aslıhan Şentürk; Karabey, Uǧur

    2017-07-01

    In this study we focus on annual number of claims of a private health insurance data set which belongs to a local insurance company in Turkey. In addition to Poisson model and negative binomial model, zero-inflated Poisson model and zero-inflated negative binomial model are used to model the number of claims in order to take into account excess zeros. To investigate the impact of different distributional assumptions for the number of claims on the prediction of total claim amount, predictive performances of candidate models are compared by using root mean square error (RMSE) and mean absolute error (MAE) criteria.

  1. Analyzing Reaction Rates with the Distortion/Interaction‐Activation Strain Model

    Science.gov (United States)

    2017-01-01

    Abstract The activation strain or distortion/interaction model is a tool to analyze activation barriers that determine reaction rates. For bimolecular reactions, the activation energies are the sum of the energies to distort the reactants into geometries they have in transition states plus the interaction energies between the two distorted molecules. The energy required to distort the molecules is called the activation strain or distortion energy. This energy is the principal contributor to the activation barrier. The transition state occurs when this activation strain is overcome by the stabilizing interaction energy. Following the changes in these energies along the reaction coordinate gives insights into the factors controlling reactivity. This model has been applied to reactions of all types in both organic and inorganic chemistry, including substitutions and eliminations, cycloadditions, and several types of organometallic reactions. PMID:28447369

  2. Analyzing Reaction Rates with the Distortion/Interaction-Activation Strain Model.

    Science.gov (United States)

    Bickelhaupt, F Matthias; Houk, Kendall N

    2017-08-14

    The activation strain or distortion/interaction model is a tool to analyze activation barriers that determine reaction rates. For bimolecular reactions, the activation energies are the sum of the energies to distort the reactants into geometries they have in transition states plus the interaction energies between the two distorted molecules. The energy required to distort the molecules is called the activation strain or distortion energy. This energy is the principal contributor to the activation barrier. The transition state occurs when this activation strain is overcome by the stabilizing interaction energy. Following the changes in these energies along the reaction coordinate gives insights into the factors controlling reactivity. This model has been applied to reactions of all types in both organic and inorganic chemistry, including substitutions and eliminations, cycloadditions, and several types of organometallic reactions. © 2017 The Authors. Published by Wiley-VCH Verlag GmbH & Co. KGaA.

  3. Assessment of performance of survival prediction models for cancer prognosis

    Directory of Open Access Journals (Sweden)

    Chen Hung-Chia

    2012-07-01

    Full Text Available Abstract Background Cancer survival studies are commonly analyzed using survival-time prediction models for cancer prognosis. A number of different performance metrics are used to ascertain the concordance between the predicted risk score of each patient and the actual survival time, but these metrics can sometimes conflict. Alternatively, patients are sometimes divided into two classes according to a survival-time threshold, and binary classifiers are applied to predict each patient’s class. Although this approach has several drawbacks, it does provide natural performance metrics such as positive and negative predictive values to enable unambiguous assessments. Methods We compare the survival-time prediction and survival-time threshold approaches to analyzing cancer survival studies. We review and compare common performance metrics for the two approaches. We present new randomization tests and cross-validation methods to enable unambiguous statistical inferences for several performance metrics used with the survival-time prediction approach. We consider five survival prediction models consisting of one clinical model, two gene expression models, and two models from combinations of clinical and gene expression models. Results A public breast cancer dataset was used to compare several performance metrics using five prediction models. 1 For some prediction models, the hazard ratio from fitting a Cox proportional hazards model was significant, but the two-group comparison was insignificant, and vice versa. 2 The randomization test and cross-validation were generally consistent with the p-values obtained from the standard performance metrics. 3 Binary classifiers highly depended on how the risk groups were defined; a slight change of the survival threshold for assignment of classes led to very different prediction results. Conclusions 1 Different performance metrics for evaluation of a survival prediction model may give different conclusions in

  4. An affine microsphere approach to modeling strain-induced crystallization in rubbery polymers

    Science.gov (United States)

    Nateghi, A.; Dal, H.; Keip, M.-A.; Miehe, C.

    2018-01-01

    Upon stretching a natural rubber sample, polymer chains orient themselves in the direction of the applied load and form crystalline regions. When the sample is retracted, the original amorphous state of the network is restored. Due to crystallization, properties of rubber change considerably. The reinforcing effect of the crystallites stiffens the rubber and increases the crack growth resistance. It is of great importance to understand the mechanism leading to strain-induced crystallization. However, limited theoretical work has been done on the investigation of the associated kinetics. A key characteristic observed in the stress-strain diagram of crystallizing rubber is the hysteresis, which is entirely attributed to strain-induced crystallization. In this work, we propose a micromechanically motivated material model for strain-induced crystallization in rubbers. Our point of departure is constructing a micromechanical model for a single crystallizing polymer chain. Subsequently, a thermodynamically consistent evolution law describing the kinetics of crystallization on the chain level is proposed. This chain model is then incorporated into the affine microsphere model. Finally, the model is numerically implemented and its performance is compared to experimental data.

  5. Model-based uncertainty in species range prediction

    DEFF Research Database (Denmark)

    Pearson, R. G.; Thuiller, Wilfried; Bastos Araujo, Miguel

    2006-01-01

    algorithm when extrapolating beyond the range of data used to build the model. The effects of these factors should be carefully considered when using this modelling approach to predict species ranges. Main conclusions We highlight an important source of uncertainty in assessments of the impacts of climate......Aim Many attempts to predict the potential range of species rely on environmental niche (or 'bioclimate envelope') modelling, yet the effects of using different niche-based methodologies require further investigation. Here we investigate the impact that the choice of model can have on predictions......, identify key reasons why model output may differ and discuss the implications that model uncertainty has for policy-guiding applications. Location The Western Cape of South Africa. Methods We applied nine of the most widely used modelling techniques to model potential distributions under current...

  6. Prediction Model for Gastric Cancer Incidence in Korean Population.

    Science.gov (United States)

    Eom, Bang Wool; Joo, Jungnam; Kim, Sohee; Shin, Aesun; Yang, Hye-Ryung; Park, Junghyun; Choi, Il Ju; Kim, Young-Woo; Kim, Jeongseon; Nam, Byung-Ho

    2015-01-01

    Predicting high risk groups for gastric cancer and motivating these groups to receive regular checkups is required for the early detection of gastric cancer. The aim of this study is was to develop a prediction model for gastric cancer incidence based on a large population-based cohort in Korea. Based on the National Health Insurance Corporation data, we analyzed 10 major risk factors for gastric cancer. The Cox proportional hazards model was used to develop gender specific prediction models for gastric cancer development, and the performance of the developed model in terms of discrimination and calibration was also validated using an independent cohort. Discrimination ability was evaluated using Harrell's C-statistics, and the calibration was evaluated using a calibration plot and slope. During a median of 11.4 years of follow-up, 19,465 (1.4%) and 5,579 (0.7%) newly developed gastric cancer cases were observed among 1,372,424 men and 804,077 women, respectively. The prediction models included age, BMI, family history, meal regularity, salt preference, alcohol consumption, smoking and physical activity for men, and age, BMI, family history, salt preference, alcohol consumption, and smoking for women. This prediction model showed good accuracy and predictability in both the developing and validation cohorts (C-statistics: 0.764 for men, 0.706 for women). In this study, a prediction model for gastric cancer incidence was developed that displayed a good performance.

  7. AN EFFICIENT PATIENT INFLOW PREDICTION MODEL FOR HOSPITAL RESOURCE MANAGEMENT

    Directory of Open Access Journals (Sweden)

    Kottalanka Srikanth

    2017-07-01

    Full Text Available There has been increasing demand in improving service provisioning in hospital resources management. Hospital industries work with strict budget constraint at the same time assures quality care. To achieve quality care with budget constraint an efficient prediction model is required. Recently there has been various time series based prediction model has been proposed to manage hospital resources such ambulance monitoring, emergency care and so on. These models are not efficient as they do not consider the nature of scenario such climate condition etc. To address this artificial intelligence is adopted. The issues with existing prediction are that the training suffers from local optima error. This induces overhead and affects the accuracy in prediction. To overcome the local minima error, this work presents a patient inflow prediction model by adopting resilient backpropagation neural network. Experiment are conducted to evaluate the performance of proposed model inter of RMSE and MAPE. The outcome shows the proposed model reduces RMSE and MAPE over existing back propagation based artificial neural network. The overall outcomes show the proposed prediction model improves the accuracy of prediction which aid in improving the quality of health care management.

  8. Risk Prediction Model for Severe Postoperative Complication in Bariatric Surgery.

    Science.gov (United States)

    Stenberg, Erik; Cao, Yang; Szabo, Eva; Näslund, Erik; Näslund, Ingmar; Ottosson, Johan

    2018-01-12

    Factors associated with risk for adverse outcome are important considerations in the preoperative assessment of patients for bariatric surgery. As yet, prediction models based on preoperative risk factors have not been able to predict adverse outcome sufficiently. This study aimed to identify preoperative risk factors and to construct a risk prediction model based on these. Patients who underwent a bariatric surgical procedure in Sweden between 2010 and 2014 were identified from the Scandinavian Obesity Surgery Registry (SOReg). Associations between preoperative potential risk factors and severe postoperative complications were analysed using a logistic regression model. A multivariate model for risk prediction was created and validated in the SOReg for patients who underwent bariatric surgery in Sweden, 2015. Revision surgery (standardized OR 1.19, 95% confidence interval (CI) 1.14-0.24, p prediction model. Despite high specificity, the sensitivity of the model was low. Revision surgery, high age, low BMI, large waist circumference, and dyspepsia/GERD were associated with an increased risk for severe postoperative complication. The prediction model based on these factors, however, had a sensitivity that was too low to predict risk in the individual patient case.

  9. Prediction Model for Gastric Cancer Incidence in Korean Population.

    Directory of Open Access Journals (Sweden)

    Bang Wool Eom

    Full Text Available Predicting high risk groups for gastric cancer and motivating these groups to receive regular checkups is required for the early detection of gastric cancer. The aim of this study is was to develop a prediction model for gastric cancer incidence based on a large population-based cohort in Korea.Based on the National Health Insurance Corporation data, we analyzed 10 major risk factors for gastric cancer. The Cox proportional hazards model was used to develop gender specific prediction models for gastric cancer development, and the performance of the developed model in terms of discrimination and calibration was also validated using an independent cohort. Discrimination ability was evaluated using Harrell's C-statistics, and the calibration was evaluated using a calibration plot and slope.During a median of 11.4 years of follow-up, 19,465 (1.4% and 5,579 (0.7% newly developed gastric cancer cases were observed among 1,372,424 men and 804,077 women, respectively. The prediction models included age, BMI, family history, meal regularity, salt preference, alcohol consumption, smoking and physical activity for men, and age, BMI, family history, salt preference, alcohol consumption, and smoking for women. This prediction model showed good accuracy and predictability in both the developing and validation cohorts (C-statistics: 0.764 for men, 0.706 for women.In this study, a prediction model for gastric cancer incidence was developed that displayed a good performance.

  10. Stage-specific predictive models for breast cancer survivability.

    Science.gov (United States)

    Kate, Rohit J; Nadig, Ramya

    2017-01-01

    Survivability rates vary widely among various stages of breast cancer. Although machine learning models built in past to predict breast cancer survivability were given stage as one of the features, they were not trained or evaluated separately for each stage. To investigate whether there are differences in performance of machine learning models trained and evaluated across different stages for predicting breast cancer survivability. Using three different machine learning methods we built models to predict breast cancer survivability separately for each stage and compared them with the traditional joint models built for all the stages. We also evaluated the models separately for each stage and together for all the stages. Our results show that the most suitable model to predict survivability for a specific stage is the model trained for that particular stage. In our experiments, using additional examples of other stages during training did not help, in fact, it made it worse in some cases. The most important features for predicting survivability were also found to be different for different stages. By evaluating the models separately on different stages we found that the performance widely varied across them. We also demonstrate that evaluating predictive models for survivability on all the stages together, as was done in the past, is misleading because it overestimates performance. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

  11. Image processing of full-field strain data and its use in model updating

    Energy Technology Data Exchange (ETDEWEB)

    Wang, W; Mottershead, J E [Centre for Engineering Dynamics, School of Engineering, University of Liverpool, UK, L69 3GH (United Kingdom); Sebastian, C M; Patterson, E A, E-mail: wangweizhuo@gmail.com [Composite Vehicle Research Center, Michigan State University, Lansing, MI (United States)

    2011-07-19

    Finite element model updating is an inverse problem based on measured structural outputs, typically natural frequencies. Full-field responses such as static stress/strain patterns and vibration mode shapes contain valuable information for model updating but within large volumes of highly-redundant data. Pattern recognition and image processing provide feasible techniques to extract effective and efficient information, often known as shape features, from this data. For instance, the Zernike polynomials having the properties of orthogonality and rotational invariance are powerful decomposition kernels for a shape defined within a unit circle. In this paper, full field strain patterns for a specimen, in the form of a square plate with a circular hole, under a tensile load are considered. Effective shape features can be constructed by a set of modified Zernike polynomials. The modification includes the application of a weighting function to the Zernike polynomials so that high strain magnitudes around the hole are well represented. The Gram-Schmidt process is then used to ensure orthogonality for the obtained decomposition kernels over the domain of the specimen. The difference between full-field strain patterns measured by digital image correlation (DIC) and reconstructed using 15 shape features (Zernike moment descriptors, ZMDs) at different steps in the elasto-plastic deformation of the specimen is found to be very small. It is significant that only a very small number of shape features are necessary and sufficient to represent the full-field data. Model updating of nonlinear elasto-plastic material properties is carried out by adjusting the parameters of a FE model until the FE strain pattern converges upon the measured strains as determined using ZMDs.

  12. Strain localisation in mechanically layered rocks beneath detachment zones: insights from numerical modelling

    Directory of Open Access Journals (Sweden)

    L. Le Pourhiet

    2013-04-01

    Full Text Available We have designed a series of fully dynamic numerical simulations aimed at assessing how the orientation of mechanical layering in rocks controls the orientation of shear bands and the depth of penetration of strain in the footwall of detachment zones. Two parametric studies are presented. In the first one, the influence of stratification orientation on the occurrence and mode of strain localisation is tested by varying initial dip of inherited layering in the footwall with regard to the orientation of simple shear applied at the rigid boundary simulating a rigid hanging wall, all scaling and rheological parameter kept constant. It appears that when Mohr–Coulomb plasticity is being used, shear bands are found to localise only when the layering is being stretched. This corresponds to early deformational stages for inital layering dipping in the same direction as the shear is applied, and to later stages for intial layering dipping towards the opposite direction of shear. In all the cases, localisation of the strain after only γ=1 requires plastic yielding to be activated in the strong layer. The second parametric study shows that results are length-scale independent and that orientation of shear bands is not sensitive to the viscosity contrast or the strain rate. However, decreasing or increasing strain rate is shown to reduce the capacity of the shear zone to localise strain. In the later case, the strain pattern resembles a mylonitic band but the rheology is shown to be effectively linear. Based on the results, a conceptual model for strain localisation under detachment faults is presented. In the early stages, strain localisation occurs at slow rates by viscous shear instabilities but as the layered media is exhumed, the temperature drops and the strong layers start yielding plastically, forming shear bands and localising strain at the top of the shear zone. Once strain localisation has occured, the deformation in the shear band becomes

  13. Evaluation of wave runup predictions from numerical and parametric models

    Science.gov (United States)

    Stockdon, Hilary F.; Thompson, David M.; Plant, Nathaniel G.; Long, Joseph W.

    2014-01-01

    Wave runup during storms is a primary driver of coastal evolution, including shoreline and dune erosion and barrier island overwash. Runup and its components, setup and swash, can be predicted from a parameterized model that was developed by comparing runup observations to offshore wave height, wave period, and local beach slope. Because observations during extreme storms are often unavailable, a numerical model is used to simulate the storm-driven runup to compare to the parameterized model and then develop an approach to improve the accuracy of the parameterization. Numerically simulated and parameterized runup were compared to observations to evaluate model accuracies. The analysis demonstrated that setup was accurately predicted by both the parameterized model and numerical simulations. Infragravity swash heights were most accurately predicted by the parameterized model. The numerical model suffered from bias and gain errors that depended on whether a one-dimensional or two-dimensional spatial domain was used. Nonetheless, all of the predictions were significantly correlated to the observations, implying that the systematic errors can be corrected. The numerical simulations did not resolve the incident-band swash motions, as expected, and the parameterized model performed best at predicting incident-band swash heights. An assimilated prediction using a weighted average of the parameterized model and the numerical simulations resulted in a reduction in prediction error variance. Finally, the numerical simulations were extended to include storm conditions that have not been previously observed. These results indicated that the parameterized predictions of setup may need modification for extreme conditions; numerical simulations can be used to extend the validity of the parameterized predictions of infragravity swash; and numerical simulations systematically underpredict incident swash, which is relatively unimportant under extreme conditions.

  14. Finite-Element Modeling of Viscoelastic Cells During High-Frequency Cyclic Strain

    Directory of Open Access Journals (Sweden)

    David W. Holdsworth

    2012-03-01

    Full Text Available Mechanotransduction refers to the mechanisms by which cells sense and respond to local loads and forces. The process of mechanotransduction plays an important role both in maintaining tissue viability and in remodeling to repair damage; moreover, it may be involved in the initiation and progression of diseases such as osteoarthritis and osteoporosis. An understanding of the mechanisms by which cells respond to surrounding tissue matrices or artificial biomaterials is crucial in regenerative medicine and in influencing cellular differentiation. Recent studies have shown that some cells may be most sensitive to low-amplitude, high-frequency (i.e., 1–100 Hz mechanical stimulation. Advances in finite-element modeling have made it possible to simulate high-frequency mechanical loading of cells. We have developed a viscoelastic finite-element model of an osteoblastic cell (including cytoskeletal actin stress fibers, attached to an elastomeric membrane undergoing cyclic isotropic radial strain with a peak value of 1,000 µstrain. The results indicate that cells experience significant stress and strain amplification when undergoing high-frequency strain, with peak values of cytoplasmic strain five times higher at 45 Hz than at 1 Hz, and peak Von Mises stress in the nucleus increased by a factor of two. Focal stress and strain amplification in cells undergoing high-frequency mechanical stimulation may play an important role in mechanotransduction.

  15. Identification of strain-rate and thermal sensitive material model with an inverse method

    Directory of Open Access Journals (Sweden)

    Peroni M.

    2010-06-01

    Full Text Available This paper describes a numerical inverse method to extract material strength parameters from the experimental data obtained via mechanical tests at different strainrates and temperatures. It will be shown that this procedure is particularly useful to analyse experimental results when the stress-strain fields in the specimen cannot be correctly described via analytical models. This commonly happens in specimens with no regular shape, in specimens with a regular shape when some instability phenomena occur (for example the necking phenomena in tensile tests that create a strongly heterogeneous stress-strain fields or in dynamic tests (where the strain-rate field is not constant due to wave propagation phenomena. Furthermore the developed procedure is useful to take into account thermal phenomena generally affecting high strain-rate tests due to the adiabatic overheating related to the conversion of plastic work. The method presented requires strong effort both from experimental and numerical point of view, anyway it allows to precisely identify the parameters of different material models. This could provide great advantages when high reliability of the material behaviour is necessary. Applicability of this method is particularly indicated for special applications in the field of aerospace engineering, ballistic, crashworthiness studies or particle accelerator technologies, where materials could be submitted to strong plastic deformations at high-strain rate in a wide range of temperature. Thermal softening effect has been investigated in a temperature range between 20°C and 1000°C.

  16. Identification of strain-rate and thermal sensitive material model with an inverse method

    Science.gov (United States)

    Peroni, L.; Scapin, M.; Peroni, M.

    2010-06-01

    This paper describes a numerical inverse method to extract material strength parameters from the experimental data obtained via mechanical tests at different strainrates and temperatures. It will be shown that this procedure is particularly useful to analyse experimental results when the stress-strain fields in the specimen cannot be correctly described via analytical models. This commonly happens in specimens with no regular shape, in specimens with a regular shape when some instability phenomena occur (for example the necking phenomena in tensile tests that create a strongly heterogeneous stress-strain fields) or in dynamic tests (where the strain-rate field is not constant due to wave propagation phenomena). Furthermore the developed procedure is useful to take into account thermal phenomena generally affecting high strain-rate tests due to the adiabatic overheating related to the conversion of plastic work. The method presented requires strong effort both from experimental and numerical point of view, anyway it allows to precisely identify the parameters of different material models. This could provide great advantages when high reliability of the material behaviour is necessary. Applicability of this method is particularly indicated for special applications in the field of aerospace engineering, ballistic, crashworthiness studies or particle accelerator technologies, where materials could be submitted to strong plastic deformations at high-strain rate in a wide range of temperature. Thermal softening effect has been investigated in a temperature range between 20°C and 1000°C.

  17. Damage based constitutive model for predicting the performance degradation of concrete

    Directory of Open Access Journals (Sweden)

    Zhi Wang

    Full Text Available An anisotropic elastic-damage coupled constitutive model for plain concrete is developed, which describes the concrete performance degradation. The damage variable, related to the surface density of micro-cracks and micro-voids, and represented by a second order tensor, is governed by the principal tension strain components. For adequately describing the partial crack opening/closure effect under tension and compression for concrete, a new suitable thermodynamic potential is proposed to express the state equations for modeling the mechanical behaviors. Within the frame-work of thermodynamic potential, concrete strain mechanisms are identified in the proposed anisotropic damage model while each state variable is physically explained and justified. The strain equivalence hypothesis is used for deriving the constitutive equations, which leads to the development of a decoupled algorithm for effective stress computation and damage evolution. Additionally, a detailed numerical algorithm is described and the simulations are shown for uni-axial compression, tension and multi-axial loadings. For verifying the numerical results, a series of experiments on concrete were carried out. Reasonably good agreement between experimental results and the predicted values was observed. The proposed constitutive model can be used to accurately model the concrete behaviors under uni-axial compression, tension and multi-axial loadings. Additionally, the presented work is expected to be very useful in the nonlinear finite element analysis of large-scale concrete structures.

  18. Femtocells Sharing Management using mobility prediction model

    OpenAIRE

    Barth, Dominique; Choutri, Amira; Kloul, Leila; Marcé, Olivier

    2013-01-01

    Bandwidth sharing paradigm constitutes an incentive solution for the serious capacity management problem faced by operators as femtocells owners are able to offer a QoS guaranteed network access to mobile users in their femtocell coverage. In this paper, we consider a technico-economic bandwidth sharing model based on a reinforcement learning algorithm. Because such a model does not allow the convergence of the learning algorithm, due to the small size of the femtocells, the mobile users velo...

  19. Validating predictions from climate envelope models

    Science.gov (United States)

    Watling, J.; Bucklin, D.; Speroterra, C.; Brandt, L.; Cabal, C.; Romañach, Stephanie S.; Mazzotti, Frank J.

    2013-01-01

    Climate envelope models are a potentially important conservation tool, but their ability to accurately forecast species’ distributional shifts using independent survey data has not been fully evaluated. We created climate envelope models for 12 species of North American breeding birds previously shown to have experienced poleward range shifts. For each species, we evaluated three different approaches to climate envelope modeling that differed in the way they treated climate-induced range expansion and contraction, using random forests and maximum entropy modeling algorithms. All models were calibrated using occurrence data from 1967–1971 (t1) and evaluated using occurrence data from 1998–2002 (t2). Model sensitivity (the ability to correctly classify species presences) was greater using the maximum entropy algorithm than the random forest algorithm. Although sensitivity did not differ significantly among approaches, for many species, sensitivity was maximized using a hybrid approach that assumed range expansion, but not contraction, in t2. Species for which the hybrid approach resulted in the greatest improvement in sensitivity have been reported from more land cover types than species for which there was little difference in sensitivity between hybrid and dynamic approaches, suggesting that habitat generalists may be buffered somewhat against climate-induced range contractions. Specificity (the ability to correctly classify species absences) was maximized using the random forest algorithm and was lowest using the hybrid approach. Overall, our results suggest cautious optimism for the use of climate envelope models to forecast range shifts, but also underscore the importance of considering non-climate drivers of species range limits. The use of alternative climate envelope models that make different assumptions about range expansion and contraction is a new and potentially useful way to help inform our understanding of climate change effects on species.

  20. Validating predictions from climate envelope models.

    Directory of Open Access Journals (Sweden)

    James I Watling

    Full Text Available Climate envelope models are a potentially important conservation tool, but their ability to accurately forecast species' distributional shifts using independent survey data has not been fully evaluated. We created climate envelope models for 12 species of North American breeding birds previously shown to have experienced poleward range shifts. For each species, we evaluated three different approaches to climate envelope modeling that differed in the way they treated climate-induced range expansion and contraction, using random forests and maximum entropy modeling algorithms. All models were calibrated using occurrence data from 1967-1971 (t1 and evaluated using occurrence data from 1998-2002 (t2. Model sensitivity (the ability to correctly classify species presences was greater using the maximum entropy algorithm than the random forest algorithm. Although sensitivity did not differ significantly among approaches, for many species, sensitivity was maximized using a hybrid approach that assumed range expansion, but not contraction, in t2. Species for which the hybrid approach resulted in the greatest improvement in sensitivity have been reported from more land cover types than species for which there was little difference in sensitivity between hybrid and dynamic approaches, suggesting that habitat generalists may be buffered somewhat against climate-induced range contractions. Specificity (the ability to correctly classify species absences was maximized using the random forest algorithm and was lowest using the hybrid approach. Overall, our results suggest cautious optimism for the use of climate envelope models to forecast range shifts, but also underscore the importance of considering non-climate drivers of species range limits. The use of alternative climate envelope models that make different assumptions about range expansion and contraction is a new and potentially useful way to help inform our understanding of climate change effects on

  1. Strain effects on three-dimensional, two-dimensional, and one-dimensional silicon logic devices: Predicting the future of strained silicon

    Science.gov (United States)

    Baykan, Mehmet O.; Thompson, Scott E.; Nishida, Toshikazu

    2010-11-01

    Using a classification scheme based on carrier confinement type (electrostatic and spatial) and the degrees of freedom of the mobile carriers (3DOF, 2DOF, and 1DOF), strain effects on 3DOF to 1DOF silicon logic devices are compared from quantum confinement and device geometry perspectives. For these varied device geometries and types, the effects of strain-induced band splitting and band warping on the modification of the average conductivity effective mass and carrier scattering rates are evaluated. It is shown that the beneficial effects of strain-induced band splitting are the most effective for devices with little or no initial band splitting and become less so for devices with already large built-in band splitting. For these devices with large splitting energy, the potential for strain-induced carrier conductivity mass reduction through repopulation of lower energy bands and the suppression of optical intervalley phonon scattering are limited. On the other hand, for all devices without spatial confinement, a comparable amount of effective mass reduction occurs through favorable strain-induced band warping. Under spatial carrier confinement, much higher strain levels with respect to unconfined or electrically confined devices are required to observe strain-induced band warping in the band structure, with larger strain requirements as the confinement dimension decreases. In electrically confined volume-inversion devices, the favorable strain type required for carrier mass reduction results in increased surface scattering by bringing the carrier centroid closer to gate surfaces. However, for spatially confined volume-inversion devices, the favorable mechanical strain does not alter the carrier distribution in the device cross section. Consequently, strain is expected to be more effective in modification of low field carrier transport in electrically confined volume-inversion devices and less for spatially confined devices, with respect to conventional 2DOF planar

  2. North Atlantic climate model bias influence on multiyear predictability

    Science.gov (United States)

    Wu, Y.; Park, T.; Park, W.; Latif, M.

    2018-01-01

    The influences of North Atlantic biases on multiyear predictability of unforced surface air temperature (SAT) variability are examined in the Kiel Climate Model (KCM). By employing a freshwater flux correction over the North Atlantic to the model, which strongly alleviates both North Atlantic sea surface salinity (SSS) and sea surface temperature (SST) biases, the freshwater flux-corrected integration depicts significantly enhanced multiyear SAT predictability in the North Atlantic sector in comparison to the uncorrected one. The enhanced SAT predictability in the corrected integration is due to a stronger and more variable Atlantic Meridional Overturning Circulation (AMOC) and its enhanced influence on North Atlantic SST. Results obtained from preindustrial control integrations of models participating in the Coupled Model Intercomparison Project Phase 5 (CMIP5) support the findings obtained from the KCM: models with large North Atlantic biases tend to have a weak AMOC influence on SAT and exhibit a smaller SAT predictability over the North Atlantic sector.

  3. Climate predictability and prediction skill on seasonal time scales over South America from CHFP models

    Science.gov (United States)

    Osman, Marisol; Vera, C. S.

    2017-10-01

    This work presents an assessment of the predictability and skill of climate anomalies over South America. The study was made considering a multi-model ensemble of seasonal forecasts for surface air temperature, precipitation and regional circulation, from coupled global circulation models included in the Climate Historical Forecast Project. Predictability was evaluated through the estimation of the signal-to-total variance ratio while prediction skill was assessed computing anomaly correlation coefficients. Both indicators present over the continent higher values at the tropics than at the extratropics for both, surface air temperature and precipitation. Moreover, predictability and prediction skill for temperature are slightly higher in DJF than in JJA while for precipitation they exhibit similar levels in both seasons. The largest values of predictability and skill for both variables and seasons are found over northwestern South America while modest but still significant values for extratropical precipitation at southeastern South America and the extratropical Andes. The predictability levels in ENSO years of both variables are slightly higher, although with the same spatial distribution, than that obtained considering all years. Nevertheless, predictability at the tropics for both variables and seasons diminishes in both warm and cold ENSO years respect to that in all years. The latter can be attributed to changes in signal rather than in the noise. Predictability and prediction skill for low-level winds and upper-level zonal winds over South America was also assessed. Maximum levels of predictability for low-level winds were found were maximum mean values are observed, i.e. the regions associated with the equatorial trade winds, the midlatitudes westerlies and the South American Low-Level Jet. Predictability maxima for upper-level zonal winds locate where the subtropical jet peaks. Seasonal changes in wind predictability are observed that seem to be related to

  4. Prediction skill of rainstorm events over India in the TIGGE weather prediction models

    Science.gov (United States)

    Karuna Sagar, S.; Rajeevan, M.; Vijaya Bhaskara Rao, S.; Mitra, A. K.

    2017-12-01

    Extreme rainfall events pose a serious threat of leading to severe floods in many countries worldwide. Therefore, advance prediction of its occurrence and spatial distribution is very essential. In this paper, an analysis has been made to assess the skill of numerical weather prediction models in predicting rainstorms over India. Using gridded daily rainfall data set and objective criteria, 15 rainstorms were identified during the monsoon season (June to September). The analysis was made using three TIGGE (THe Observing System Research and Predictability Experiment (THORPEX) Interactive Grand Global Ensemble) models. The models considered are the European Centre for Medium-Range Weather Forecasts (ECMWF), National Centre for Environmental Prediction (NCEP) and the UK Met Office (UKMO). Verification of the TIGGE models for 43 observed rainstorm days from 15 rainstorm events has been made for the period 2007-2015. The comparison reveals that rainstorm events are predictable up to 5 days in advance, however with a bias in spatial distribution and intensity. The statistical parameters like mean error (ME) or Bias, root mean square error (RMSE) and correlation coefficient (CC) have been computed over the rainstorm region using the multi-model ensemble (MME) mean. The study reveals that the spread is large in ECMWF and UKMO followed by the NCEP model. Though the ensemble spread is quite small in NCEP, the ensemble member averages are not well predicted. The rank histograms suggest that the forecasts are under prediction. The modified Contiguous Rain Area (CRA) technique was used to verify the spatial as well as the quantitative skill of the TIGGE models. Overall, the contribution from the displacement and pattern errors to the total RMSE is found to be more in magnitude. The volume error increases from 24 hr forecast to 48 hr forecast in all the three models.

  5. Fracture criteria under creep with strain history taken into account, and long-term strength modelling

    Science.gov (United States)

    Khokhlov, A. V.

    2009-08-01

    In the present paper, we continue to study the nonlinear constitutive relation (CR) between the stress and strain proposed in [1] to describe one-dimensional isothermal rheological processes in the case of monotone variation of the strain (in particular, relaxation, creep, plasticity, and superplasticity). We show that this CR together with the strain fracture criterion (FC) leads to theoretical long-term strength curves (LSC) with the same qualitative properties as the typical experimental LSC of viscoelastoplastic materials. We propose two parametric families of fracture criteria in the case of monotone uniaxial strain, which are related to the strain fracture criterion (SFC) but take into account the strain increase history and the dependence of the critical strain on the stress. Instead of the current strain, they use other measures of damage related to the strain history by time-dependent integral operators. For any values of the material parameters, analytic studies of these criteria allowed us to find several useful properties, which confirm that they can be used to describe the creep fracture of different materials. In particular, we prove that, together with the proposed constitutive relations, these FC lead to theoretical long-term strength curves (TLSC) with the same qualitative properties as the experimental LSC. It is important that each of the constructed families of FC forms a monotone and continuous scale of criteria (monotonously and continuously depending on a real parameter) that contains the SFC as the limit case. Moreover, the criteria in the first family always provide the fracture time greater than that given by the SFC, the criteria in the second family always provide a smaller fracture time, and the difference can be made arbitrarily small by choosing the values of the control parameter near the scale end. This property is very useful in finding a more accurate adjustment of the model to the existing experimental data describing the

  6. Micro-mechanical studies on graphite strength prediction models

    Science.gov (United States)

    Kanse, Deepak; Khan, I. A.; Bhasin, V.; Vaze, K. K.

    2013-06-01

    The influence of type of loading and size-effects on the failure strength of graphite were studied using Weibull model. It was observed that this model over-predicts size effect in tension. However, incorporation of grain size effect in Weibull model, allows a more realistic simulation of size effects. Numerical prediction of strength of four-point bend specimen was made using the Weibull parameters obtained from tensile test data. Effective volume calculations were carried out and subsequently predicted strength was compared with experimental data. It was found that Weibull model can predict mean flexural strength with reasonable accuracy even when grain size effect was not incorporated. In addition, the effects of microstructural parameters on failure strength were analyzed using Rose and Tucker model. Uni-axial tensile, three-point bend and four-point bend strengths were predicted using this model and compared with the experimental data. It was found that this model predicts flexural strength within 10%. For uni-axial tensile strength, difference was 22% which can be attributed to less number of tests on tensile specimens. In order to develop failure surface of graphite under multi-axial state of stress, an open ended hollow tube of graphite was subjected to internal pressure and axial load and Batdorf model was employed to calculate failure probability of the tube. Bi-axial failure surface was generated in the first and fourth quadrant for 50% failure probability by varying both internal pressure and axial load.

  7. Strain Differences in Antioxidants in Rat Models of Cardiovascular Disease Exposed to Ozone

    Science.gov (United States)

    We examined the hypothesis that antioxidant substances and enzymes in lung, heart and in bronchoalveolar lavage fluid (BALF) are altered in response to 03 in cardiovascular disease and/or metabolic syndrome (CVD)-prone rat models. CVD strains [spontaneously hypertensive (SH), SH ...

  8. Deeper Insight into the Diels-Alder Reaction through the Activation Strain Model

    NARCIS (Netherlands)

    Fernandez, I.; Bickelhaupt, F.M.

    2016-01-01

    The Diels–Alder (DA) cycloaddition reaction has the ability to significantly increase molecular complexity regioselectively and stereospecifically in a single synthetic step. In this review it is discussed how the activation strain model of chemical reactivity reveals the physical factors that

  9. Model for muscle regeneration around fibrotic lesions in recurrent strain injuries.

    NARCIS (Netherlands)

    Grefte, S.; Kuijpers-Jagtman, A.M.; Torensma, R.; Hoff, J.W. Von den

    2010-01-01

    PURPOSE: The purpose of this study was to establish an in vivo model for muscle regeneration after strain injury in the presence of a fibrotic discontinuity. METHODS: The musculus soleus of 5-wk-old male rats was exposed, completely lacerated, and sutured together with or without a collagen scaffold

  10. Recovery Kinetics in Commercial Purity Aluminum Deformed to Ultrahigh Strain: Model and Experiment

    DEFF Research Database (Denmark)

    Yu, Tianbo; Hansen, Niels

    2016-01-01

    A new approach to analyze recovery kinetics is developed from a recent model, and microstructural observations are introduced to supplement hardness measurements. The approach involves two steps of data fitting, and the second step of fitting enables an estimation of the apparent activation energ...... of nanostructured materials produced by high strain deformation....

  11. Finite-Strain Fractional-Order Viscoelastic (FOV) Material Models and Numerical Methods for Solving Them

    Science.gov (United States)

    Freed, Alan D.; Diethelm, Kai; Gray, Hugh R. (Technical Monitor)

    2002-01-01

    Fraction-order viscoelastic (FOV) material models have been proposed and studied in 1D since the 1930's, and were extended into three dimensions in the 1970's under the assumption of infinitesimal straining. It was not until 1997 that Drozdov introduced the first finite-strain FOV constitutive equations. In our presentation, we shall continue in this tradition by extending the standard, FOV, fluid and solid, material models introduced in 1971 by Caputo and Mainardi into 3D constitutive formula applicable for finite-strain analyses. To achieve this, we generalize both the convected and co-rotational derivatives of tensor fields to fractional order. This is accomplished by defining them first as body tensor fields and then mapping them into space as objective Cartesian tensor fields. Constitutive equations are constructed using both variants for fractional rate, and their responses are contrasted in simple shear. After five years of research and development, we now possess a basic suite of numerical tools necessary to study finite-strain FOV constitutive equations and their iterative refinement into a mature collection of material models. Numerical methods still need to be developed for efficiently solving fraction al-order integrals, derivatives, and differential equations in a finite element setting where such constitutive formulae would need to be solved at each Gauss point in each element of a finite model, which can number into the millions in today's analysis.

  12. New Approaches for Channel Prediction Based on Sinusoidal Modeling

    Directory of Open Access Journals (Sweden)

    Ekman Torbjörn

    2007-01-01

    Full Text Available Long-range channel prediction is considered to be one of the most important enabling technologies to future wireless communication systems. The prediction of Rayleigh fading channels is studied in the frame of sinusoidal modeling in this paper. A stochastic sinusoidal model to represent a Rayleigh fading channel is proposed. Three different predictors based on the statistical sinusoidal model are proposed. These methods outperform the standard linear predictor (LP in Monte Carlo simulations, but underperform with real measurement data, probably due to nonstationary model parameters. To mitigate these modeling errors, a joint moving average and sinusoidal (JMAS prediction model and the associated joint least-squares (LS predictor are proposed. It combines the sinusoidal model with an LP to handle unmodeled dynamics in the signal. The joint LS predictor outperforms all the other sinusoidal LMMSE predictors in suburban environments, but still performs slightly worse than the standard LP in urban environments.

  13. Bayesian Age-Period-Cohort Modeling and Prediction - BAMP

    Directory of Open Access Journals (Sweden)

    Volker J. Schmid

    2007-10-01

    Full Text Available The software package BAMP provides a method of analyzing incidence or mortality data on the Lexis diagram, using a Bayesian version of an age-period-cohort model. A hierarchical model is assumed with a binomial model in the first-stage. As smoothing priors for the age, period and cohort parameters random walks of first and second order, with and without an additional unstructured component are available. Unstructured heterogeneity can also be included in the model. In order to evaluate the model fit, posterior deviance, DIC and predictive deviances are computed. By projecting the random walk prior into the future, future death rates can be predicted.

  14. Modeling for prediction of restrained shrinkage effect in concrete repair

    International Nuclear Information System (INIS)

    Yuan Yingshu; Li Guo; Cai Yue

    2003-01-01

    A general model of autogenous shrinkage caused by chemical reaction (chemical shrinkage) is developed by means of Arrhenius' law and a degree of chemical reaction. Models of tensile creep and relaxation modulus are built based on a viscoelastic, three-element model. Tests of free shrinkage and tensile creep were carried out to determine some coefficients in the models. Two-dimensional FEM analysis based on the models and other constitutions can predict the development of tensile strength and cracking. Three groups of patch-repaired beams were designed for analysis and testing. The prediction from the analysis shows agreement with the test results. The cracking mechanism after repair is discussed

  15. A stochastic model correctly predicts changes in budding yeast cell cycle dynamics upon periodic expression of CLN2.

    Directory of Open Access Journals (Sweden)

    Cihan Oguz

    Full Text Available In this study, we focus on a recent stochastic budding yeast cell cycle model. First, we estimate the model parameters using extensive data sets: phenotypes of 110 genetic strains, single cell statistics of wild type and cln3 strains. Optimization of stochastic model parameters is achieved by an automated algorithm we recently used for a deterministic cell cycle model. Next, in order to test the predictive ability of the stochastic model, we focus on a recent experimental study in which forced periodic expression of CLN2 cyclin (driven by MET3 promoter in cln3 background has been used to synchronize budding yeast cell colonies. We demonstrate that the model correctly predicts the experimentally observed synchronization levels and cell cycle statistics of mother and daughter cells under various experimental conditions (numerical data that is not enforced in parameter optimization, in addition to correctly predicting the qualitative changes in size control due to forced CLN2 expression. Our model also generates a novel prediction: under frequent CLN2 expression pulses, G1 phase duration is bimodal among small-born cells. These cells originate from daughters with extended budded periods due to size control during the budded period. This novel prediction and the experimental trends captured by the model illustrate the interplay between cell cycle dynamics, synchronization of cell colonies, and size control in budding yeast.

  16. Predicting Footbridge Response using Stochastic Load Models

    DEFF Research Database (Denmark)

    Pedersen, Lars; Frier, Christian

    2013-01-01

    Walking parameters such as step frequency, pedestrian mass, dynamic load factor, etc. are basically stochastic, although it is quite common to adapt deterministic models for these parameters. The present paper considers a stochastic approach to modeling the action of pedestrians, but when doing so...... decisions need to be made in terms of statistical distributions of walking parameters and in terms of the parameters describing the statistical distributions. The paper explores how sensitive computations of bridge response are to some of the decisions to be made in this respect. This is useful...

  17. Phase field modeling of brittle fracture for enhanced assumed strain shells at large deformations: formulation and finite element implementation

    Science.gov (United States)

    Reinoso, J.; Paggi, M.; Linder, C.

    2017-06-01

    Fracture of technological thin-walled components can notably limit the performance of their corresponding engineering systems. With the aim of achieving reliable fracture predictions of thin structures, this work presents a new phase field model of brittle fracture for large deformation analysis of shells relying on a mixed enhanced assumed strain (EAS) formulation. The kinematic description of the shell body is constructed according to the solid shell concept. This enables the use of fully three-dimensional constitutive models for the material. The proposed phase field formulation integrates the use of the (EAS) method to alleviate locking pathologies, especially Poisson thickness and volumetric locking. This technique is further combined with the assumed natural strain method to efficiently derive a locking-free solid shell element. On the computational side, a fully coupled monolithic framework is consistently formulated. Specific details regarding the corresponding finite element formulation and the main aspects associated with its implementation in the general purpose packages FEAP and ABAQUS are addressed. Finally, the applicability of the current strategy is demonstrated through several numerical examples involving different loading conditions, and including linear and nonlinear hyperelastic constitutive models.

  18. Uncertainties in model-based outcome predictions for treatment planning

    International Nuclear Information System (INIS)

    Deasy, Joseph O.; Chao, K.S. Clifford; Markman, Jerry

    2001-01-01

    Purpose: Model-based treatment-plan-specific outcome predictions (such as normal tissue complication probability [NTCP] or the relative reduction in salivary function) are typically presented without reference to underlying uncertainties. We provide a method to assess the reliability of treatment-plan-specific dose-volume outcome model predictions. Methods and Materials: A practical method is proposed for evaluating model prediction based on the original input data together with bootstrap-based estimates of parameter uncertainties. The general framework is applicable to continuous variable predictions (e.g., prediction of long-term salivary function) and dichotomous variable predictions (e.g., tumor control probability [TCP] or NTCP). Using bootstrap resampling, a histogram of the likelihood of alternative parameter values is generated. For a given patient and treatment plan we generate a histogram of alternative model results by computing the model predicted outcome for each parameter set in the bootstrap list. Residual uncertainty ('noise') is accounted for by adding a random component to the computed outcome values. The residual noise distribution is estimated from the original fit between model predictions and patient data. Results: The method is demonstrated using a continuous-endpoint model to predict long-term salivary function for head-and-neck cancer patients. Histograms represent the probabilities for the level of posttreatment salivary function based on the input clinical data, the salivary function model, and the three-dimensional dose distribution. For some patients there is significant uncertainty in the prediction of xerostomia, whereas for other patients the predictions are expected to be more reliable. In contrast, TCP and NTCP endpoints are dichotomous, and parameter uncertainties should be folded directly into the estimated probabilities, thereby improving the accuracy of the estimates. Using bootstrap parameter estimates, competing treatment

  19. Validation of a tuber blight (Phytophthora infestans) prediction model

    Science.gov (United States)

    Potato tuber blight caused by Phytophthora infestans accounts for significant losses in storage. There is limited published quantitative data on predicting tuber blight. We validated a tuber blight prediction model developed in New York with cultivars Allegany, NY 101, and Katahdin using independent...

  20. Geospatial application of the Water Erosion Prediction Project (WEPP) Model

    Science.gov (United States)

    D. C. Flanagan; J. R. Frankenberger; T. A. Cochrane; C. S. Renschler; W. J. Elliot

    2011-01-01

    The Water Erosion Prediction Project (WEPP) model is a process-based technology for prediction of soil erosion by water at hillslope profile, field, and small watershed scales. In particular, WEPP utilizes observed or generated daily climate inputs to drive the surface hydrology processes (infiltration, runoff, ET) component, which subsequently impacts the rest of the...