Strains at the myotendinous junction predicted by a micromechanical model.
Sharafi, Bahar; Ames, Elizabeth G; Holmes, Jeffrey W; Blemker, Silvia S
2011-11-10
The goal of this work was to create a finite element micromechanical model of the myotendinous junction (MTJ) to examine how the structure and mechanics of the MTJ affect the local micro-scale strains experienced by muscle fibers. We validated the model through comparisons with histological longitudinal sections of muscles fixed in slack and stretched positions. The model predicted deformations of the A-bands within the fiber near the MTJ that were similar to those measured from the histological sections. We then used the model to predict the dependence of local fiber strains on activation and the mechanical properties of the endomysium. The model predicted that peak micro-scale strains increase with activation and as the compliance of the endomysium decreases. Analysis of the models revealed that, in passive stretch, local fiber strains are governed by the difference of the mechanical properties between the fibers and the endomysium. In active stretch, strain distributions are governed by the difference in cross-sectional area along the length of the tapered region of the fiber near the MTJ. The endomysium provides passive resistance that balances the active forces and prevents the tapered region of the fiber from undergoing excessive strain. These model predictions lead to the following hypotheses: (i) the increased likelihood of injury during active lengthening of muscle fibers may be due to the increase in peak strain with activation and (ii) endomysium may play a role in protecting fibers from injury by reducing the strains within the fiber at the MTJ. Copyright Â© 2011 Elsevier Ltd. All rights reserved.
[Developing a predictive model for the caregiver strain index].
Álvarez-Tello, Margarita; Casado-Mejía, Rosa; Praena-Fernández, Juan Manuel; Ortega-Calvo, Manuel
Patient homecare with multiple morbidities is an increasingly common occurrence. The caregiver strain index is tool in the form of questionnaire that is designed to measure the perceived burden of those who care for their families. The aim of this study is to construct a diagnostic nomogram of informal caregiver burden using data from a predictive model. The model was drawn up using binary logistic regression and the questionnaire items as dichotomous factors. The dependent variable was the final score obtained with the questionnaire but categorised in accordance with that in the literature. Scores between 0 and 6 were labelled as "no" (no caregiver stress) and at or greater than 7 as "yes". The version 3.1.1R statistical software was used. To construct confidence intervals for the ROC curve 2000 boot strap replicates were used. A sample of 67 caregivers was obtained. A diagnosing nomogram was made up with its calibration graph (Brier scaled = 0.686, Nagelkerke R(2)=0.791), and the corresponding ROC curve (area under the curve=0.962). The predictive model generated using binary logistic regression and the nomogram contain four items (1, 4, 5 and 9) of the questionnaire. R plotting functions allow a very good solution for validating a model like this. The area under the ROC curve (0.96; 95% CI: 0.994-0.941) achieves a high discriminative value. Calibration also shows high goodness of fit values, suggesting that it may be clinically useful in community nursing and geriatric establishments. Copyright © 2015 SEGG. Publicado por Elsevier España, S.L.U. All rights reserved.
Haddag, Badis; ABED-MERAIM, Farid; BALAN, Tudor
2007-01-01
The aim of this work is to study the strain localization during the plastic deformation of sheets metals. This phenomenon is precursor for the fracture of drawing parts, thus its prediction using advanced behavior models is important in order to obtain safe final parts. Most often, an accurate prediction of localization during forming process requires damage to be included in the simulation. For this purpose, an advanced, anisotropic elastoplastic model, combining isotropic and kinematic hard...
Prediction of stress-strain behavior of ceramic matrix composites using unit cell model
Directory of Open Access Journals (Sweden)
Suzuki Takuya
2015-01-01
Full Text Available In this study, the elastic modulus and the stress-strain curve of ceramic matrix composites (CMCs were predicted by using the unit cell model that consists of fiber bundles and matrix. The unit cell model was developed based on the observation of cross sections of CMCs. The elastic modulus of CMCs was calculated from the results of finite element analysis using the developed model. The non-linear behavior of stress-strain curve of CMCs was also predicted by taking the degradation of the elastic modulus into consideration, where the degradation was related to the experimentally measured crack density in CMCs. The approach using the unit cell model was applied to two kinds of CMCs, and good agreement was obtained between the experimental and the calculated results.
Ji, Dongmei; Ren, Jianxing; Zhang, Lai-Chang
2016-09-01
A novel creep-fatigue life prediction model was deduced based on an expression of the strain energy density in this study. In order to obtain the expression of the strain energy density, the load-controlled creep-fatigue (CF) tests of P92 steel at 873 K were carried out. Cyclic strain of P92 steel under CF load was divided into elastic strain, applying and unloading plastic strain, creep strain, and anelastic strain. Analysis of cyclic strain indicates that the damage process of P92 steel under CF load consists of three stages, similar to pure creep. According to the characteristics of the strains above, an expression was defined to describe the strain energy density for each cycle. The strain energy density at stable stage is inversely proportional to the total strain energy density dissipated by P92 steel. However, the total strain energy densities under different test conditions are proportional to the fatigue life. Therefore, the expression of the strain energy density at stable stage was chosen to predict the fatigue life. The CF experimental data on P92 steel were employed to verify the rationality of the novel model. The model obtained from the load-controlled CF test of P92 steel with short holding time could predict the fatigue life of P92 steel with long holding time.
Ji, Dongmei; Ren, Jianxing; Zhang, Lai-Chang
2016-11-01
A novel creep-fatigue life prediction model was deduced based on an expression of the strain energy density in this study. In order to obtain the expression of the strain energy density, the load-controlled creep-fatigue (CF) tests of P92 steel at 873 K were carried out. Cyclic strain of P92 steel under CF load was divided into elastic strain, applying and unloading plastic strain, creep strain, and anelastic strain. Analysis of cyclic strain indicates that the damage process of P92 steel under CF load consists of three stages, similar to pure creep. According to the characteristics of the strains above, an expression was defined to describe the strain energy density for each cycle. The strain energy density at stable stage is inversely proportional to the total strain energy density dissipated by P92 steel. However, the total strain energy densities under different test conditions are proportional to the fatigue life. Therefore, the expression of the strain energy density at stable stage was chosen to predict the fatigue life. The CF experimental data on P92 steel were employed to verify the rationality of the novel model. The model obtained from the load-controlled CF test of P92 steel with short holding time could predict the fatigue life of P92 steel with long holding time.
Elsaadany, Mostafa; Yan, Karen Chang; Yildirim-Ayan, Eda
2017-01-16
Successful tissue engineering and regenerative therapy necessitate having extensive knowledge about mechanical milieu in engineered tissues and the resident cells. In this study, we have merged two powerful analysis tools, namely finite element analysis and stochastic analysis, to understand the mechanical strain within the tissue scaffold and residing cells and to predict the cell viability upon applying mechanical strains. A continuum-based multi-length scale finite element model (FEM) was created to simulate the physiologically relevant equiaxial strain exposure on cell-embedded tissue scaffold and to calculate strain transferred to the tissue scaffold (macro-scale) and residing cells (micro-scale) upon various equiaxial strains. The data from FEM were used to predict cell viability under various equiaxial strain magnitudes using stochastic damage criterion analysis. The model validation was conducted through mechanically straining the cardiomyocyte-encapsulated collagen constructs using a custom-built mechanical loading platform (EQUicycler). FEM quantified the strain gradients over the radial and longitudinal direction of the scaffolds and the cells residing in different areas of interest. With the use of the experimental viability data, stochastic damage criterion, and the average cellular strains obtained from multi-length scale models, cellular viability was predicted and successfully validated. This methodology can provide a great tool to characterize the mechanical stimulation of bioreactors used in tissue engineering applications in providing quantification of mechanical strain and predicting cellular viability variations due to applied mechanical strain.
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.
Energy Technology Data Exchange (ETDEWEB)
Cheng, Guang; Hu, Xiaohua; Choi, Kyoo Sil; Sun, Xin
2017-10-10
Ductile fracture is a local phenomenon, and it is well established that fracture strain levels depend on both stress triaxiality and the resolution (grid size) of strain measurements. Two-dimensional plane strain post-necking models with different representative volume element (RVE) sizes are used to predict the size-dependent fracture strain of a commercial dual-phase steel, DP980. The models are generated from the actual microstructures, and the individual phase flow properties and literature-based individual phase damage parameters for the Johnson-Cook model are used for ferrite and martensite. A monotonic relationship is predicted: the smaller the model size, the higher the fracture strain. Thus, a general framework is developed to quantify the size-dependent fracture strains for multiphase materials. In addition to the RVE sizes, the influences of intrinsic microstructure features, i.e., the flow curve and fracture strains of the two constituent phases, on the predicted fracture strains also are examined. Application of the derived fracture strain versus RVE size relationship is demonstrated with large clearance trimming simulations with different element sizes.
Prediction Models on Distribution of Inherent Strains in T Type Welding Structure
Institute of Scientific and Technical Information of China (English)
Peng HE; Jicai FENG; Jiecai HAN; Yiyu QIAN
2003-01-01
A fundamental theory for the analysis of residual welding stresses and deformation based on the inherent strain distribution along the welded joint is introduced. The method of predicting maximum hardness Hv(y, z) and maximum inherent strain gmax is given
A damage accumulation model for complex strain paths: Prediction of ductile failure in metals
Lapovok, Rimma; Hodgson, D.
2009-11-01
The characterisation of strain path with respect to the directionality of defect formation is discussed. The criterion of non-monotonic strain path is used in the scalar and tensor models for damage accumulation and recovery. Comparable analysis of models and their verification has been obtained by simulation of crack initiation in a two-stage metal forming operation consisting of wire drawing followed by constrained upsetting.
Directory of Open Access Journals (Sweden)
Amit Kumar Gupta
2014-10-01
Full Text Available In this paper, to predict flow stress of Austenitic Stainless Steel (ASS 304 at elevated temperatures the extended Rusinek–Klepaczko (RK model has been modified using an exponential strain dependent term for dynamic strain aging (DSA region. Isothermal tensile tests are conducted on ASS 304 for a temperature range of 323–923 K with an interval of 50 K and at strain rates of 0.0001 s−1, 0.001 s−1, 0.01 s−1 and 0.1 s−1. DSA phenomenon is observed from 623 to 923 K at 0.0001 s−1, 0.001 s−1 and 0.01 s−1. Material constants are calculated using data obtained from these tensile tests for non-DSA and DSA region separately. The predicted results from the RK model are compared with the experimental data to check the accuracy of the constitutive relation. It is observed that to find out the constants of this model, some initial assumptions are required, and these initial values affect the predicted values. Hence, Genetic Algorithm (GA is used to optimize the constants for RK model. Statistical measures such as the correlation coefficient, the average absolute error and standard deviation are used to measure the accuracy of the model. The resulting values of the correlation coefficient for ASS 304 for non-DSA and DSA region using modified extended RK model are 0.9828 and 0.9701. This modified, extended RK model is compared with Johnson–Cook (JC, Zerilli–Armstrong (ZA and Arrhenius models and it is observed that specifically in DSA region, the modified extended RK model gives highly accurate predictions.
Directory of Open Access Journals (Sweden)
Satish Kumar
2012-07-01
Full Text Available More than 200 different types of Human papillomavirus (HPV are identified, 40 transmit extensively through sexual contacts affecting the genital tract. HPV strains have been etiologically linked to vaginal, vulvar, penile, anal, oral and cervical cancer (99.7% as a result of mutations leading to cell transformations due to interference of E6 and E7 oncoproteins with p53 and pRB tumor suppressor genes respectively, besides other cellular proteins. As structures of E6 and E7 proteins are not available, the simultaneous structural analysis of E6 and E7 proteins of 50 different HPV strains was carried out in detail for prediction and validation, using bioinformatics tools. E6 and E7 proteins sequences were retrieved in FASTA format from NCBI and their structures predicted by comparative modeling using modeller9v6 software. Further, most of the HPV strains showed good stereochemistry results in most favored regions when subjected to PROCHECK analysis and subsequently each protein was validated using ProSA-web tool. The work carried out on comparing and exploring the structural variations in these oncogenic proteins might help in genome based drugs and vaccines designing, beyond their limitations.
Hussain, Mozammil; Natarajan, Raghu N; Chaudhary, Gulafsha; An, Howard S; Andersson, Gunnar B J
2011-05-01
Disc swelling pressure (P(swell)) facilitated by fixed charged density (FCD) of proteoglycans (P(fcd)) and strain-dependent permeability (P(strain)) are of critical significance in the physiological functioning of discs. FCD of proteoglycans prevents any excessive matrix deformation by tissue stiffening, whereas strain-dependent permeability limits the rate of stress transfer from fluid to solid skeleton. To date, studies involving the modeling of FCD of proteoglycans and strain-dependent permeability have not been reported for the cervical discs. The current study objective is to compare the relative contributions of strain-dependent permeability and FCD of proteoglycans in predicting cervical disc biomechanics. Three-dimensional finite element models of a C5-C6 segment with three different disc compositions were analyzed: an SPFP model (strain-dependent permeability and FCD of proteoglycans), an SP model (strain-dependent permeability alone), and an FP model (FCD of proteoglycans alone). The outcomes of the current study suggest that the relative contributions of strain-dependent permeability and FCD of proteoglycans were almost comparable in predicting the physiological behavior of the cervical discs under moment loads. However, under compression, strain-dependent permeability better predicted the in vivo disc response than that of the FCD of proteoglycans. Unlike the FP model (least stiff) in compression, motion behavior of the three models did not vary much from each other and agreed well within the standard deviations of the corresponding in vivo published data. Flexion was recorded with maximum P(fcd) and P(strain), whereas minimum values were found in extension. The study data enhance the understanding of the roles played by the FCD of proteoglycans and strain-dependent permeability and porosity in determining disc tissue swelling behavior. Degenerative changes involving strain-dependent permeability and/or loss of FCD of proteoglycans can further be
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
Prediction of swelling rocks strain in tunneling
Parsapour, D.; Fahimifar, A.
2016-05-01
Swelling deformations leading to convergence of tunnels may result in significant difficulties during the construction, in particular for long term use of tunnels. By extracting an experimental based explicit analytical solution for formulating swelling strains as a function of time and stress, swelling strains are predicted from the beginning of excavation and during the service life of tunnel. Results obtained from the analytical model show a proper agreement with experimental results. This closed-form solution has been implemented within a numerical program using the finite element method for predicting time-dependent swelling strain around tunnels. Evaluating effects of swelling parameters on time-dependent strains and tunnel shape on swelling behavior around the tunnel according to this analytical solution is considered. The ground-support interaction and consequent swelling effect on the induced forces in tunnel lining is considered too. Effect of delay in lining installation on swelling pressure which acting on the lining and its structural integrity, is also evaluated. A MATLAB code of " SRAP" is prepared and applied to calculate all swelling analysis around tunnels based on analytical solution.
Kosaki, Yutaka; Watanabe, Shigeru
2016-10-01
Autism-spectrum disorder (ASD) is a multi-aspect developmental disorder characterised by various social and non-social behavioural abnormalities. Using BTBR T+ tf mouse strain (BTBR), a promising animal model displaying a number of behavioural and neural characteristics associated with ASD, we tested the hypothesis that at the core of various symptoms of ASD lies a fundamental deficit in predictive learning between events. In five experiments, we conducted a variety of Pavlovian conditioning tasks, some requiring the establishment of associations between temporally phasic events and others involving static events. BTBR mice were impaired in the acquisition of conditioned magazine approach responses with an appetitive unconditioned stimulus (US) (Experiment 1) and conditioned freezing with an electric shock US (Experiment 2). Both of these tasks had temporally phasic conditioned stimuli (CSs). Conversely, these mice showed normal acquisition of conditioned place preference (CPP), whether the US was a systemic injection of methamphetamine (Experiment 3A) or the presence of food (Experiment 3B). Experiment 4 showed normal acquisition of conditioned taste aversion (CTA) to a flavour-taste compound CS, although BTBR mice still exhibited an abnormal stimulus selection when learning for each element of the compound CS was assessed separately. Experiment 5 revealed a weaker latent inhibition of CTA in BTBR mice. The BTBR mouse's impaired predictive learning between phasic events and intact associations between static events are discussed in terms of dysfunctional contingency-based, but not contiguity-based learning, which may accompany abnormal selective attention to relevant cues. We propose that such dysfunctional contingency learning mechanisms may underlie the development of various social and non-social symptoms of ASD.
Rowlinson, Steve; Jia, Yunyan Andrea
2014-04-01
Existing heat stress risk management guidelines recommended by international standards are not practical for the construction industry which needs site supervision staff to make instant managerial decisions to mitigate heat risks. The ability of the predicted heat strain (PHS) model [ISO 7933 (2004). Ergonomics of the thermal environment analytical determination and interpretation of heat stress using calculation of the predicted heat strain. Geneva: International Standard Organisation] to predict maximum allowable exposure time (D lim) has now enabled development of localized, action-triggering and threshold-based guidelines for implementation by lay frontline staff on construction sites. This article presents a protocol for development of two heat stress management tools by applying the PHS model to its full potential. One of the tools is developed to facilitate managerial decisions on an optimized work-rest regimen for paced work. The other tool is developed to enable workers' self-regulation during self-paced work.
Hashim, Z.; Fukusaki, E.
2016-06-01
The increased demand for clean, sustainable and renewable energy resources has driven the development of various microbial systems to produce biofuels. One of such systems is the ethanol-producing yeast. Although yeast produces ethanol naturally using its native pathways, production yield is low and requires improvement for commercial biofuel production. Moreover, ethanol is toxic to yeast and thus ethanol tolerance should be improved to further enhance ethanol production. In this study, we employed metabolomics-based strategy using 30 single-gene deleted yeast strains to construct multivariate models for ethanol tolerance and screen metabolites that relate to ethanol sensitivity/tolerance. The information obtained from this study can be used as an input for strain improvement via metabolic engineering.
Jürchott, Karsten; Schulz, Axel Ronald; Bozzetti, Cecilia; Pohlmann, Dominika; Stervbo, Ulrik; Warth, Sarah; Mälzer, Julia Nora; Waldner, Julian; Schweiger, Brunhilde; Olek, Sven; Grützkau, Andreas; Babel, Nina; Thiel, Andreas; Neumann, Avidan Uriel
2016-01-01
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 (H1N1)pdm09 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(H1N1)pdm09 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(H1N1)pdm09 with a high accuracy of 89% (p-value = 0.00002). An additional validation study (N = 43 vaccinees sero-negative to A(H1N1)pdm09) 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(H1N1)pdm09 influenza strain after seasonal multi-valent vaccination as a continuous function of age, NSSN and baseline CD4 count.
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
Bozzetti, Cecilia; Pohlmann, Dominika; Stervbo, Ulrik; Warth, Sarah; Mälzer, Julia Nora; Waldner, Julian; Schweiger, Brunhilde; Olek, Sven; Grützkau, Andreas
2016-01-01
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(H1N1)pdm09 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(H1N1)pdm09 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(H1N1)pdm09 with a high accuracy of 89% (p-value = 0.00002). An additional validation study (N = 43 vaccinees sero-negative to A(H1N1)pdm09) 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(H1N1)pdm09 influenza strain after seasonal multi-valent vaccination as a continuous
Energy Technology Data Exchange (ETDEWEB)
Ahmadi, Nabi; Nayebi, Ali [Shiraz University, Shiraz (Iran, Islamic Republic of)
2015-07-15
Yield surface distortion and its center movement were employed in a unified viscoplastic model to predict the ratcheting behavior of the 304 stainless steel. A combination of the Ohno-Wang model and the yield surface distortion model of Baltov and Sawczuk was used in uniaxial loading. Stress amplitude and the mean stress were varied in the tests to verify the model. Uniaxial loadings were simulated with and without consideration of yield surface distortion. Results from both simulations were compared. Yield surface distortion showed a significant effect on the simulation of the ratcheting responses.
Duc-Toan, Nguyen; Tien-Long, Banh; Young-Suk, Kim; Dong-Won, Jung
2011-08-01
In this study, a modified Johnson-Cook (J-C) model and an innovated method to determine (J-C) material parameters are proposed to predict more correctly stress-strain curve for tensile tests in elevated temperatures. A MATLAB tool is used to determine material parameters by fitting a curve to follow Ludwick's hardening law at various elevated temperatures. Those hardening law parameters are then utilized to determine modified (J-C) model material parameters. The modified (J-C) model shows the better prediction compared to the conventional one. As the first verification, an FEM tensile test simulation based on the isotropic hardening model for boron sheet steel at elevated temperatures was carried out via a user-material subroutine, using an explicit finite element code, and compared with the measurements. The temperature decrease of all elements due to the air cooling process was then calculated when considering the modified (J-C) model and coded to VUMAT subroutine for tensile test simulation of cooling process. The modified (J-C) model showed the good agreement between the simulation results and the corresponding experiments. The second investigation was applied for V-bending spring-back prediction of magnesium alloy sheets at elevated temperatures. Here, the combination of proposed J-C model with modified hardening law considering the unusual plastic behaviour for magnesium alloy sheet was adopted for FEM simulation of V-bending spring-back prediction and shown the good comparability with corresponding experiments.
Duc-Toan, Nguyen; Tien-Long, Banh; Dong-Won, Jung; Seung-Han, Yang; Young-Suk, Kim
2012-02-01
In order to predict correctly stress-strain curve for tensile tests at elevated and cooling temperatures, a modification of a Johnson-Cook (J-C) model and a new method to determine (J-C) material parameters are proposed. A MATLAB tool is used to determine material parameters by fitting a curve to follow Ludwick and Voce's hardening law at various elevated temperatures. Those hardening law parameters are then utilized to determine modified (J-C) model material parameters. The modified (J-C) model shows the better prediction compared to the conventional one. An FEM tensile test simulation based on the isotropic hardening model for metal sheet at elevated temperatures was carried out via a user-material subroutine, using an explicit finite element code. The simulation results at elevated temperatures were firstly presented and then compared with the measurements. The temperature decrease of all elements due to the air cooling process was then calculated when considering the modified (J-C) model and coded to VUMAT subroutine for tensile test simulation. The modified (J-C) model showed the good comparability between the simulation results and the corresponding experiments.
Kubota, H.; Kuwabara, K.; Hamada, Y.
2014-08-01
This paper applies the heat balance equation (HBE) for clothed subjects as a linear function of mean skin temperature ( t sk ) by a new sweating efficiency ( η sw ) and an approximation for the thermoregulatory sweat rate. The equation predicting t sk in steady state conditions was derived as the solution of the HBE and used for a predictive heat strain scale. The heat loss from the wet clothing (WCL) area was identified with a new variable of `virtual dripping sweat rate VDSR' ( S wdr ). This is a subject's un-evaporated sweat rate in dry clothing from the regional sweat rate exceeding the maximum evaporative capacity, and adds the moisture to the clothing, reducing the intrinsic clothing insulation. The S wdr allowed a mass balance analysis of the wet clothing area identified as clothing wetness ( w cl ). The w cl was derived by combining the HBE at the WCL surface from which the evaporation rate and skin heat loss from WCL region are given. Experimental results on eight young male subjects wearing typical summer clothing, T-shirt and trousers verified the model for predicting t sk with WCL thermal resistance ( R cl,w ) identified as 25 % of dry clothing ( R cl,d ).
Modelling to very high strains
Bons, P. D.; Jessell, M. W.; Griera, A.; Evans, L. A.; Wilson, C. J. L.
2009-04-01
Ductile strains in shear zones often reach extreme values, resulting in typical structures, such as winged porphyroclasts and several types of shear bands. The numerical simulation of the development of such structures has so far been inhibited by the low maximum strains that numerical models can normally achieve. Typical numerical models collapse at shear strains in the order of one to three. We have implemented a number of new functionalities in the numerical platform "Elle" (Jessell et al. 2001), which significantly increases the amount of strain that can be achieved and simultaneously reduces boundary effects that become increasingly disturbing at higher strain. Constant remeshing, while maintaining the polygonal phase regions, is the first step to avoid collapse of the finite-element grid required by finite-element solvers, such as Basil (Houseman et al. 2008). The second step is to apply a grain-growth routine to the boundaries of polygons that represent phase regions. This way, the development of sharp angles is avoided. A second advantage is that phase regions may merge or become separated (boudinage). Such topological changes are normally not possible in finite element deformation codes. The third step is the use of wrapping vertical model boundaries, with which optimal and unchanging model boundaries are maintained for the application of stress or velocity boundary conditions. The fourth step is to shift the model by a random amount in the vertical direction every time step. This way, the fixed horizontal boundary conditions are applied to different material points within the model every time step. Disturbing boundary effects are thus averaged out over the whole model and not localised to e.g. top and bottom of the model. Reduction of boundary effects has the additional advantage that model can be smaller and, therefore, numerically more efficient. Owing to the combination of these existing and new functionalities it is now possible to simulate the
Institute of Scientific and Technical Information of China (English)
Ravindranadh BOBBILI; B. RAMAKRISHNA; V. MADHU; A.K. GOGIA
2015-01-01
An artificial neural network (ANN) constitutive model and JohnsoneCook (JeC) model were developed for 7017 aluminium alloy based on high strain rate data generated from split Hopkinson pressure bar (SHPB) experiments at various temperatures. A neural network configuration consists of both training and validation, which is effectively employed to predict flow stress. Temperature, strain rate and strain are considered as inputs, whereas flow stress is taken as output of the neural network. A comparative study on JohnsoneCook (JeC) model and neural network model was performed. It was observed that the developed neural network model could predict flow stress under various strain rates and tem-peratures. The experimental stressestrain data obtained from high strain rate compression tests using SHPB over a range of temperatures (25?e300 ?C), strains (0.05e0.3) and strain rates (1500e4500 s?1) were employed to formulate JeC model to predict the flow stress behaviour of 7017 aluminium alloy under high strain rate loading. The JeC model and the back-propagation ANN model were developed to predict the flow stress of 7017 aluminium alloy under high strain rates, and their predictability was 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 0.8461 and 10.624%, respectively, while R and AARE for the ANN model are 0.9995 and 2.58%, respectively. The predictions of ANN model are observed to be in consistent with the experimental data for all strain rates and temperatures.
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.
Strain Rate Dependent Modeling of Polymer Matrix Composites
Goldberg, Robert K.; Stouffer, Donald C.
1999-01-01
A research program is in progress to develop strain rate dependent deformation and failure models for the analysis of polymer matrix composites subject to high strain rate impact loads. Strain rate dependent inelastic constitutive equations have been developed to model the polymer matrix, and have been incorporated into a micromechanics approach to analyze polymer matrix composites. The Hashin failure criterion has been implemented within the micromechanics results to predict ply failure strengths. The deformation model has been implemented within LS-DYNA, a commercially available transient dynamic finite element code. The deformation response and ply failure stresses for the representative polymer matrix composite AS4/PEEK have been predicted for a variety of fiber orientations and strain rates. The predicted results compare favorably to experimentally obtained values.
Multiplicative earthquake likelihood models incorporating strain rates
Rhoades, D. A.; Christophersen, A.; Gerstenberger, M. C.
2017-01-01
SUMMARYWe examine the potential for strain-rate variables to improve long-term earthquake likelihood models. We derive a set of multiplicative hybrid earthquake likelihood models in which cell rates in a spatially uniform baseline model are scaled using combinations of covariates derived from earthquake catalogue data, fault data, and strain-rates for the New Zealand region. Three components of the strain rate estimated from GPS data over the period 1991-2011 are considered: the shear, rotational and dilatational strain rates. The hybrid model parameters are optimised for earthquakes of M 5 and greater over the period 1987-2006 and tested on earthquakes from the period 2012-2015, which is independent of the strain rate estimates. The shear strain rate is overall the most informative individual covariate, as indicated by Molchan error diagrams as well as multiplicative modelling. Most models including strain rates are significantly more informative than the best models excluding strain rates in both the fitting and testing period. A hybrid that combines the shear and dilatational strain rates with a smoothed seismicity covariate is the most informative model in the fitting period, and a simpler model without the dilatational strain rate is the most informative in the testing period. These results have implications for probabilistic seismic hazard analysis and can be used to improve the background model component of medium-term and short-term earthquake forecasting models.
STRESS-STRAIN FINITE ELEMENT ANALYSIS AND FATIGUE LIFE PREDICTION FOR BOLTED CONNECTIONS
Institute of Scientific and Technical Information of China (English)
无
2002-01-01
A cyclic plasticity model is used into finite element (FE) method to obtain the details of elastic-plastic stress-strain in the bolts under cyclic axial loading. Two criteria in multiaxial fatigue are employed to predict fatigue lives of bolts. The predicted fatigue lives are in favorable agreement with the experimental results for machined bolts.
Cestari, Andrea
2013-01-01
Predictive modeling is emerging as an important knowledge-based technology in healthcare. The interest in the use of predictive modeling reflects advances on different fronts such as the availability of health information from increasingly complex databases and electronic health records, a better understanding of causal or statistical predictors of health, disease processes and multifactorial models of ill-health and developments in nonlinear computer models using artificial intelligence or neural networks. These new computer-based forms of modeling are increasingly able to establish technical credibility in clinical contexts. The current state of knowledge is still quite young in understanding the likely future direction of how this so-called 'machine intelligence' will evolve and therefore how current relatively sophisticated predictive models will evolve in response to improvements in technology, which is advancing along a wide front. Predictive models in urology are gaining progressive popularity not only for academic and scientific purposes but also into the clinical practice with the introduction of several nomograms dealing with the main fields of onco-urology.
Strained Si/SiGe MOS transistor model
Directory of Open Access Journals (Sweden)
Tatjana Pešić-Brđanin
2009-06-01
Full Text Available In this paper we describe a new model of surfacechannel strained-Si/SiGe MOSFET based on the extension of non-quasi-static (NQS circuit model previously derived for bulk-Si devices. Basic equations of the NQS model have been modified to account for the new physical parameters of strained-Si and relaxed-SiGe layers. From the comparisons with measurements, it is shown that a modified NQS MOS including steady-state self heating can accurately predict DC characteristics of Strained Silicon MOSFETs.
Predictive validity of the Strain Index in turkey processing.
Knox, K; Moore, J S
2001-05-01
The Strain Index is a job analysis method for determining if workers are exposed to increased risk of developing distal upper extremity disorders. Its predictive and external validity was initially demonstrated in a pork processing plant. The purpose of this study was to evaluate the predictive validity of the Strain Index in one turkey processing plant. While blinded to health outcomes, investigators analyzed the right and left sides of workers in 28 jobs using the Strain Index and classified them as "hazardous" or "safe" based on the Strain Index score. Subsequently, OSHA 200 logs were used to ascertain the occurrence of distal upper extremity disorders retrospectively. If at least one such disorder had occurred on the right or left side during the previous 3 years, that side was classified as "positive." If no such disorder was reported during the previous 3 years, that side was classified as "negative." When comparing sides, symmetry between morbidity and hazard classification was required. When comparing jobs, such symmetry was not required. Evidence of association between the hazard classifications and the morbidity classifications for the 56 sides and the 28 jobs was evaluated using 2 x 2 contingency tables. For the sides, the association between hazard classification and morbidity classification was statistically significant, with an odds ratio of 22.0. The sensitivity, specificity, positive predictive value, and negative predictive value were 0.86, 0.79, 0.92, and 0.65, respectively. Similar results were noted for the jobs--the odds ratio was 50.0, and the sensitivity, specificity, positive predictive value, and negative predictive value were 0.91, 0.83, 0.95, and 0.71. These results provide additional evidence of the external validity and predictive validity of the Strain Index.
Computer modelling of bone's adaptation: the role of normal strain, shear strain and fluid flow.
Tiwari, Abhishek Kumar; Prasad, Jitendra
2017-04-01
Bone loss is a serious health problem. In vivo studies have found that mechanical stimulation may inhibit bone loss as elevated strain in bone induces osteogenesis, i.e. new bone formation. However, the exact relationship between mechanical environment and osteogenesis is less clear. Normal strain is considered as a prime stimulus of osteogenic activity; however, there are some instances in the literature where osteogenesis is observed in the vicinity of minimal normal strain, specifically near the neutral axis of bending in long bones. It suggests that osteogenesis may also be induced by other or secondary components of mechanical environment such as shear strain or canalicular fluid flow. As it is evident from the literature, shear strain and fluid flow can be potent stimuli of osteogenesis. This study presents a computational model to investigate the roles of these stimuli in bone adaptation. The model assumes that bone formation rate is roughly proportional to the normal, shear and fluid shear strain energy density above their osteogenic thresholds. In vivo osteogenesis due to cyclic cantilever bending of a murine tibia has been simulated. The model predicts results close to experimental findings when normal strain, and shear strain or fluid shear were combined. This study also gives a new perspective on the relation between osteogenic potential of micro-level fluid shear and that of macro-level bending shear. Attempts to establish such relations among the components of mechanical environment and corresponding osteogenesis may ultimately aid in the development of effective approaches to mitigating bone loss.
MODEL PREDICTIVE CONTROL FUNDAMENTALS
African Journals Online (AJOL)
2012-07-02
Jul 2, 2012 ... paper, we will present an introduction to the theory and application of MPC with Matlab codes written to ... model predictive control, linear systems, discrete-time systems, ... and then compute very rapidly for this open-loop con-.
Predictive validity of the strain index in manufacturing facilities.
Rucker, Nathan; Moore, J Steven
2002-01-01
The Strain Index is a job analysis method for determining if workers are exposed to increased risk of developing distal upper extremity disorders. Its predictive and external validity was initially demonstrated in a pork processing plant. The purpose of this study was to evaluate its predictive validity in two manufacturing plants. While blinded to health outcomes, investigators analyzed the right and left sides of 28 single-task jobs using the Strain Index and classified them as "hazardous" or "safe" based on the Strain Index score. Subsequently, OSHA 200 logs were used to ascertain the occurrence of distal upper extremity disorders retrospectively. If at least one such disorder occurred on the right or left side during the prior three years, that side was classified as "positive." If no such disorder was reported during the prior three years, that side was classified as "negative." When comparing sides, symmetry between morbidity and hazard classification was required. When comparing jobs, such symmetry was not required. Evidence of association between the hazard classifications and the morbidity classifications for the 56 sides and the 28 jobs was evaluated using 2 x 2 contingency tables. For the sides, the association between hazard classification and morbidity classification was statistically significant with an empirical odds ratio of 73.2. The sensitivity, specificity, positive predictive value, and negative predictive value were 1.00, 0.84, 0.47, and 1.00. Similar results were noted for the jobs--the empirical odds ratio was 106.6, and the sensitivity, specificity, positive predictive value, and negative predictive value were 1.00, 0.91, 0.75, and 1.00. While these results provide additional evidence of the Strain Index's external validity and predictive validity, it should be noted that these jobs involved the performance of single tasks.
Nominal model predictive control
Grüne, Lars
2013-01-01
5 p., to appear in Encyclopedia of Systems and Control, Tariq Samad, John Baillieul (eds.); International audience; Model Predictive Control is a controller design method which synthesizes a sampled data feedback controller from the iterative solution of open loop optimal control problems.We describe the basic functionality of MPC controllers, their properties regarding feasibility, stability and performance and the assumptions needed in order to rigorously ensure these properties in a nomina...
Nominal Model Predictive Control
Grüne, Lars
2014-01-01
5 p., to appear in Encyclopedia of Systems and Control, Tariq Samad, John Baillieul (eds.); International audience; Model Predictive Control is a controller design method which synthesizes a sampled data feedback controller from the iterative solution of open loop optimal control problems.We describe the basic functionality of MPC controllers, their properties regarding feasibility, stability and performance and the assumptions needed in order to rigorously ensure these properties in a nomina...
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...... the possibilities w.r.t. different numerical weather predictions actually available to the project....
Five challenges in modelling interacting strain dynamics
DEFF Research Database (Denmark)
Wikramaratna, Paul S; Kurcharski, Adam; Gupta, Sunetra
2015-01-01
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...
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 CO_{2} 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.
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...
Prediction of forming limit strains of thin foils using shim
Joshi, Sanket Vivek; Bade, Rohit A.; Narasimhan, K.
2013-12-01
Thin foils of metallic alloys find utility in metallic thermal protection systems, such as honeycomb structures. Understanding the formability of these thin foils becomes imperative so as to design accurate tooling and also to ensure mechanical robustness of the honeycomb structures during service. It has been found that, obtaining the precise limit strains of these foils directly using the conventional limiting dome test tooling is difficult, because of the excessive draw in and wrinkling that occurs during the punch travel, resulting in erroneous measurement or prediction of limit strains. To address this issue, the blank over blank stacking methodology was developed, which helped keep the draw-in and wrinkling at negligible and thus acceptable levels. Although the blank over blank stacking methodology offers a way to predict and measure limit strains, the same may not be accurate enough due to the effect the substrate properties may impose on the thin foil. To avoid this effect, a different methodology has been proposed herein, which uses a shim stacked over the blank to avoid draw in of these foil blanks and thus help accurate clamping of the blank between the die and blank holder. It is thus understood that either a critical local or global increase in the thickness of the blank material in and around the draw bead is essential to obtain effective clamping of foil and to avoid draw-in and wrinkling. Although, miniaturized hemispherical dome tests may be beneficial for obtaining limit strains as far as foils are concerned, the methodologies proposed herein provide a route to obtaining the same using available equipment, thus saving resources and time involved in development of new miniaturized testing devices. The forming limit strains of thin foils of IN 718 (inconel) alloy having a thickness of 50μm, C263 (nimonic) alloy having a thickness of 100μm and CP Ti (commercially pure titanium) having a thickness of 200μm have been predicted using this methodology
A predictive fitness model for influenza
Łuksza, Marta; Lässig, Michael
2014-03-01
The seasonal human influenza A/H3N2 virus undergoes rapid evolution, which produces significant year-to-year sequence turnover in the population of circulating strains. Adaptive mutations respond to human immune challenge and occur primarily in antigenic epitopes, the antibody-binding domains of the viral surface protein haemagglutinin. Here we develop a fitness model for haemagglutinin that predicts the evolution of the viral population from one year to the next. Two factors are shown to determine the fitness of a strain: adaptive epitope changes and deleterious mutations outside the epitopes. We infer both fitness components for the strains circulating in a given year, using population-genetic data of all previous strains. From fitness and frequency of each strain, we predict the frequency of its descendent strains in the following year. This fitness model maps the adaptive history of influenza A and suggests a principled method for vaccine selection. Our results call for a more comprehensive epidemiology of influenza and other fast-evolving pathogens that integrates antigenic phenotypes with other viral functions coupled by genetic linkage.
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
Prediction of failure strain and burst pressure in high yield-to-tensile strength ratio linepipe
Energy Technology Data Exchange (ETDEWEB)
Law, M. [Institute of Materials and Engineering Science, Australian Nuclear Science and Technology Organisation (ANSTO), Lucas Heights, NSW (Australia)]. E-mail: mlx@ansto.gov.au; Bowie, G. [BlueScope Steel Ltd., Level 11, 120 Collins St, Melbourne, Victoria 3000 (Australia)
2007-08-15
Failure pressures and strains were predicted for a number of burst tests as part of a project to explore failure strain in high yield-to-tensile strength ratio linepipe. Twenty-three methods for predicting the burst pressure and six methods of predicting the failure strain are compared with test results. Several methods were identified which gave accurate and reliable estimates of burst pressure. No method of accurately predicting the failure strain was found, though the best was noted.
Predicting Offshore Swarm Rate Changes by Volumetric Strain Changes in Izu Peninsula, Japan
Kumazawa, T.; Ogata, Y.; Kimura, Y.; Maeda, K.; Kobayashi, A.
2014-12-01
The eastern offshore of Izu peninsula is one of the well known volcanic active regions in Japan, where magma intrusions have been observed several times since 1980s monitored by strain-meters located nearby. Major swarm activities have been synchronously associated with coseismic and preseismic significant sizes of a volumetric strain changes (Earthquake Research Committee, 2010). We investigated the background seismicity changes during these earthquake swarms using the nonstationary ETAS model (Kumazawa and Ogata, 2013), and have found the followings. The modified volumetric strain change data by removing the effect of earth tides and precipitation as well as removing coseismic jumps have much higher cross-correlations to the background rates of the ETAS model than to the whole seismicity rate change of the ETAS, and further the strain changes precede the background seismicity by lag of about a day. This relation suggests an enhanced prediction of earthquakes in this region using volumetric strain measurements. Thus we propose an extended ETAS model where the background seismicity rate is predicted by the time series of preceding volumetric strain changes. Our numerical results for Izu region show consistent outcomes throughout the major swarms in this region. References Earthquake Research Committee (2010). Report on "Prediction of seismic activity in the Izu Eastern Region" (in Japanese), http://www.jishin.go.jp/main/yosoku/izu/index.htm Kumazawa, T. and Ogata, Y. (2013). Quantitative description of induced seismic activity before and after the 2011 Tohoku-Oki earthquake by nonstationary ETAS model, J Geophys.Res. 118, 6165-6182.
Kuykendall, Katherine
2011-07-01
Constitutive laws commonly used to model friction stir welding have been evaluated, both qualitatively and quantitatively, and a new application of a constitutive law which can be extended to materials commonly used in FSW is presented. Existing constitutive laws have been classified as path-dependent or path-independent. Path-independent laws have been further classified according to the physical phenomena they capture: strain hardening, strain rate hardening, and/or thermal softening. Path-dependent laws can track gradients in temperature and strain rate characteristic to friction stir welding; however, path-independent laws cannot. None of the path-independent constitutive laws evaluated has been validated over the full range of strain, strain rate, and temperature in friction stir welding. Holding all parameters other than constitutive law constant in a friction stir weld model resulted in temperature differences of up to 21%. Varying locations for maximum temperature difference indicate that the constitutive laws resulted in different temperature profiles. The Sheppard and Wright law is capable of capturing saturation but incapable of capturing strain hardening with errors as large as 57% near yield. The Johnson-Cook law is capable of capturing strain hardening; however, its inability to capture saturation causes over-predictions of stress at large strains with errors as large as 37% near saturation. The Kocks and Mecking model is capable of capturing strain hardening and saturation with errors less than 5% over the entire range of plastic strain. The Sheppard and Wright and Johnson-Cook laws are incapable of capturing transients characteristic of material behavior under interrupted temperature or strain rate. The use of a state variable in the Kocks and Mecking law allows it to predict such transients. Constants for the Kocks and Mecking model for AA 5083, AA 3004, and Inconel 600 were determined from Atlas of Formability data. Constants for AA 5083 and AA
Computational prediction of vaccine strains for human influenza A (H3N2) viruses.
Steinbrück, L; Klingen, T R; McHardy, A C
2014-10-01
have developed a data-driven framework for vaccine strain prediction which facilitates the computational analysis of genetic and antigenic data and does not rely on explicit evolutionary models. Our computational decision procedure generated good matches of the vaccine strain to the circulating predominant strain for most seasons and could be used to support the expert-guided prediction made by the WHO; it thus may allow an increase in vaccine efficacy.
Estimation of respiratory heat flows in prediction of heat strain among Taiwanese steel workers
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.
Gurson's Model: ALE Formulation and Strain Localization
da Cunda, Luiz A. B.; Creus, Guillermo J.
2007-05-01
This paper presents a brief review of Gurson's damage model, employed to describes the strength degradation in ductile metals submitted to large plastic deformations. The damage model is applied using finite elements and an Arbitrary Lagrangian-Eulerian formulation (ALE), to ensure a better quality to the finite elements mesh. The study of the combined application of ALE and Gurson approach to damage modeling and strain localization is the object of this paper.
Dahle, Geir Olav; Stangeland, Lodve; Moen, Christian Arvei; Salminen, Pirjo-Riitta; Haaverstad, Rune; Matre, Knut; Grong, Ketil
2016-05-15
Noninvasive measurements of myocardial strain and strain rate by speckle tracking echocardiography correlate to cardiac contractile state but also to load, which may weaken their value as indices of inotropy. In a porcine model, we investigated the influence of acute dynamic preload reductions on left ventricular strain and strain rate and their relation to the pressure-conductance catheter-derived preload recruitable stroke work (PRSW) and peak positive first derivative of left ventricular pressure (LV-dP/dtmax). Speckle tracking strain and strain rate in the longitudinal, circumferential, and radial directions were measured during acute dynamic reductions of end-diastolic volume during three different myocardial inotropic states. Both strain and strain rate were sensitive to unloading of the left ventricle (P speckle tracking echocardiography-derived strain rate is more robust to dynamic ventricular unloading than strain. Longitudinal and circumferential strain could not predict load-independent contractility. Strain rates, and especially in the radial direction, are good predictors of preload-independent inotropic markers derived from conductance catheter. Copyright © 2016 the American Physiological Society.
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].
Strain Elastography for Prediction of Malignancy in Soft Tissue Tumours--Preliminary Results
DEFF Research Database (Denmark)
Riishede, I; Ewertsen, C; Carlsen, J;
2015-01-01
PURPOSE: To evaluate the ability of strain elastography to predict malignancy in patients with soft tissue tumors, and to compare three evaluation methods of strain elastography: strain ratios, strain histograms and visual scoring. MATERIALS AND METHODS: 60 patients with 61 tumors were analyzed i...
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 de
Paiement, Jean-François; Grandvalet, Yves; Bengio, Samy
2008-01-01
Modeling long-term dependencies in time series has proved very difficult to achieve with traditional machine learning methods. This problem occurs when considering music data. In this paper, we introduce generative models for melodies. We decompose melodic modeling into two subtasks. We first propose a rhythm model based on the distributions of distances between subsequences. Then, we define a generative model for melodies given chords and rhythms based on modeling sequences of Narmour featur...
Zephyr - the prediction models
DEFF Research Database (Denmark)
Nielsen, Torben Skov; Madsen, Henrik; Nielsen, Henrik Aalborg
2001-01-01
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 Dani...
Ngoy, E. K.
2016-07-01
Prediction of environmental effects on fibre reinforced plastics habitually is made difficult due to the complex variability of the natural service environment. This paper suggests a method to predict thermal strain distribution over the material lifetime by discretisation of the exposure history. Laboratory results show a high correlation between predicted and experimentally measured strain distribution
Finite Element Modeling of the Behavior of Armor Materials Under High Strain Rates and Large Strains
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
Welding Distortion Prediction in 5A06 Aluminum Alloy Complex Structure via Inherent Strain Method
Directory of Open Access Journals (Sweden)
Zhi Zeng
2016-09-01
Full Text Available Finite element (FE simulation with inherent deformation is an ideal and practical computational approach for predicting welding stress and distortion in the production of complex aluminum alloy structures. In this study, based on the thermal elasto-plastic analysis, FE models of multi-pass butt welds and T-type fillet welds were investigated to obtain the inherent strain distribution in a 5A06 aluminum alloy cylindrical structure. The angular distortion of the T-type joint was used to investigate the corresponding inherent strain mechanism. Moreover, a custom-designed experimental system was applied to clarify the magnitude of inherent deformation. With the mechanism investigation of welding-induced buckling by FE analysis using inherent deformation, an application for predicting and mitigating the welding buckling in fabrication of complex aluminum alloy structure was developed.
Baqersad, Javad; Niezrecki, Christopher; Avitabile, Peter
2015-10-01
Health monitoring of rotating structures (e.g. wind turbines and helicopter blades) has historically been a challenge due to sensing and data transmission problems. Unfortunately mechanical failure in many structures initiates at components on or inside the structure where there is no sensor located to predict the failure. In this paper, a wind turbine was mounted with a semi-built-in configuration and was excited using a mechanical shaker. A series of optical targets was distributed along the blades and the fixture and the displacement of those targets during excitation was measured using a pair of high speed cameras. Measured displacements with three dimensional point tracking were transformed to all finite element degrees of freedom using a modal expansion algorithm. The expanded displacements were applied to the finite element model to predict the full-field dynamic strain on the surface of the structure as well as within the interior points. To validate the methodology of dynamic strain prediction, the predicted strain was compared to measured strain by using six mounted strain-gages. To verify if a simpler model of the turbine can be used for the expansion, the expansion process was performed both by using the modes of the entire turbine and modes of a single cantilever blade. The results indicate that the expansion approach can accurately predict the strain throughout the turbine blades from displacements measured by using stereophotogrammetry.
Directory of Open Access Journals (Sweden)
A. Tata
2009-01-01
Full Text Available This paper presents a nonlinear finite element modeling and analysis of rectangular normal-strength reinforced concrete columns confined with transverse steel under axial compressive loading. In this study, the columns were modeled as discrete elements using ANSYS nonlinear finite element software. Concrete was modeled with 8-noded SOLID65 elements that can translate either in the x-, y-, or z-axis directions from ANSYS element library. Longitudinal and transverse steels were modeled as discrete elements using 3D-LINK8 bar elements available in the ANSYS element library. The nonlinear constitutive law of each material was also implemented in the model. The results indicate that the stress-strain relationships obtained from the analytical model using ANSYS are in good agreement with the experimental data. This has been confirmed with the insignificant difference between the analytical and experimental, i.e. 5.65 and 2.80 percent for the peak stress and the strain at the peak stress, respectively. The comparison shows that the ANSYS nonlinear finite element program is capable of modeling and predicting the actual nonlinear behavior of confined concrete column under axial loading. The actual stress-strain relationship, the strength gain and ductility improvement have also been confirmed to be satisfactorily.
Confidence scores for prediction models
DEFF Research Database (Denmark)
Gerds, Thomas Alexander; van de Wiel, MA
2011-01-01
modelling strategy is applied to different training sets. For each modelling strategy we estimate a confidence score based on the same repeated bootstraps. A new decomposition of the expected Brier score is obtained, as well as the estimates of population average confidence scores. The latter can be used...... 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...
Modelling, controlling, predicting blackouts
Wang, Chengwei; Baptista, Murilo S
2016-01-01
The electric power system is one of the cornerstones of modern society. One of its most serious malfunctions is the blackout, a catastrophic event that may disrupt a substantial portion of the system, playing havoc to human life and causing great economic losses. Thus, understanding the mechanisms leading to blackouts and creating a reliable and resilient power grid has been a major issue, attracting the attention of scientists, engineers and stakeholders. In this paper, we study the blackout problem in power grids by considering a practical phase-oscillator model. This model allows one to simultaneously consider different types of power sources (e.g., traditional AC power plants and renewable power sources connected by DC/AC inverters) and different types of loads (e.g., consumers connected to distribution networks and consumers directly connected to power plants). We propose two new control strategies based on our model, one for traditional power grids, and another one for smart grids. The control strategie...
Melanoma Risk Prediction Models
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.
Predictive model for segmented poly(urea
Directory of Open Access Journals (Sweden)
Frankl P.
2012-08-01
Full Text Available Segmented poly(urea has been shown to be of significant benefit in protecting vehicles from blast and impact and there have been several experimental studies to determine the mechanisms by which this protective function might occur. One suggested route is by mechanical activation of the glass transition. In order to enable design of protective structures using this material a constitutive model and equation of state are needed for numerical simulation hydrocodes. Determination of such a predictive model may also help elucidate the beneficial mechanisms that occur in polyurea during high rate loading. The tool deployed to do this has been Group Interaction Modelling (GIM – a mean field technique that has been shown to predict the mechanical and physical properties of polymers from their structure alone. The structure of polyurea has been used to characterise the parameters in the GIM scheme without recourse to experimental data and the equation of state and constitutive model predicts response over a wide range of temperatures and strain rates. The shock Hugoniot has been predicted and validated against existing data. Mechanical response in tensile tests has also been predicted and validated.
Prediction models in complex terrain
DEFF Research Database (Denmark)
Marti, I.; Nielsen, Torben Skov; Madsen, Henrik
2001-01-01
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......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...... and HIRLAM predictions. The statistical models belong to the class of conditional parametric models. The models are estimated using local polynomial regression, but the estimation method is here extended to be adaptive in order to allow for slow changes in the system e.g. caused by the annual variations...
Pressure prediction model for compression garment design.
Leung, W Y; Yuen, D W; Ng, Sun Pui; Shi, S Q
2010-01-01
Based on the application of Laplace's law to compression garments, an equation for predicting garment pressure, incorporating the body circumference, the cross-sectional area of fabric, applied strain (as a function of reduction factor), and its corresponding Young's modulus, is developed. Design procedures are presented to predict garment pressure using the aforementioned parameters for clinical applications. Compression garments have been widely used in treating burning scars. Fabricating a compression garment with a required pressure is important in the healing process. A systematic and scientific design method can enable the occupational therapist and compression garments' manufacturer to custom-make a compression garment with a specific pressure. The objectives of this study are 1) to develop a pressure prediction model incorporating different design factors to estimate the pressure exerted by the compression garments before fabrication; and 2) to propose more design procedures in clinical applications. Three kinds of fabrics cut at different bias angles were tested under uniaxial tension, as were samples made in a double-layered structure. Sets of nonlinear force-extension data were obtained for calculating the predicted pressure. Using the value at 0° bias angle as reference, the Young's modulus can vary by as much as 29% for fabric type P11117, 43% for fabric type PN2170, and even 360% for fabric type AP85120 at a reduction factor of 20%. When comparing the predicted pressure calculated from the single-layered and double-layered fabrics, the double-layered construction provides a larger range of target pressure at a particular strain. The anisotropic and nonlinear behaviors of the fabrics have thus been determined. Compression garments can be methodically designed by the proposed analytical pressure prediction model.
Goldberg, Robert K.; Stouffer, Donald C.
1998-01-01
Recently applications have exposed polymer matrix composite materials to very high strain rate loading conditions, requiring an ability to understand and predict the material behavior under these extreme conditions. In this second paper of a two part report, a three-dimensional composite micromechanical model is described which allows for the analysis of the rate dependent, nonlinear deformation response of a polymer matrix composite. Strain rate dependent inelastic constitutive equations utilized to model the deformation response of a polymer are implemented within the micromechanics method. The deformation response of two representative laminated carbon fiber reinforced composite materials with varying fiber orientation has been predicted using the described technique. The predicted results compare favorably to both experimental values and the response predicted by the Generalized Method of Cells, a well-established micromechanics analysis method.
Williamson, Hannah C; Karney, Benjamin R; Bradbury, Thomas N
2013-02-01
Social-learning perspectives explicitly recognize the role of partners' personal histories and contexts as possible causes of couple communication behavior, but these assumptions are rarely tested directly, and operationalizations of context in behavioral research on couples rarely extend beyond the interacting dyad. To broaden our understanding of why couples differ in communication, the current study examined whether observed behaviors in marital interactions covary with individual experiences and contextual factors. Behaviors coded from in-home conversations of 414 ethnically diverse newlywed couples were examined simultaneously in relation to childhood and family-of-origin experiences, financial strain and stressful life events, depressive symptoms, and relationship satisfaction. A latent factor representing financial strain and stressful life events was the strongest correlate of negative communication, with higher levels of stress predicting more negativity. Relationship satisfaction was the strongest correlate of observed positivity, with higher levels of satisfaction predicting more positivity. Childhood and family experiences were unrelated to behaviors, whereas results for depressive symptoms were complex and counterintuitive. Because the negative behaviors highlighted in social-learning models of relationship functioning, and often targeted in educational interventions, covary reliably with the stresses and financial strains that couples experience, contextual factors merit greater emphasis in models designed to explain and prevent marital deterioration.
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...
Tantalum strength model incorporating temperature, strain rate and pressure
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.
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 (Tc) 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.
A mouse model for testing the pathogenicity of equine herpes virus-1 strains.
van Woensel, P A; Goovaerts, D; Markx, D; Visser, N
1995-07-01
A mouse model was developed for testing the pathogenicity of equine herpes virus-1 (EHV-1) strains. The model was validated with EHV-1 strains that are known to be of a low or high pathogenicity in horses. From all parameters tested, the safety index, which was calculated from the body weights of the mice after infection, proved to be the best predictive parameter. When this parameter was used, good and reliable correlations were found with the pathogenicity of the EHV-1 strains in horses. This method enabled the differentiation between the two experimental EHV-1 strains whose genetic backgrounds were supposedly equal.
Predictive models of forest dynamics.
Purves, Drew; Pacala, Stephen
2008-06-13
Dynamic global vegetation models (DGVMs) have shown that forest dynamics could dramatically alter the response of the global climate system to increased atmospheric carbon dioxide over the next century. But there is little agreement between different DGVMs, making forest dynamics one of the greatest sources of uncertainty in predicting future climate. DGVM predictions could be strengthened by integrating the ecological realities of biodiversity and height-structured competition for light, facilitated by recent advances in the mathematics of forest modeling, ecological understanding of diverse forest communities, and the availability of forest inventory data.
Using Predictions Based on Geostatistics to Monitor Trends in Aspergillus flavus Strain Composition.
Orum, T V; Bigelow, D M; Cotty, P J; Nelson, M R
1999-09-01
ABSTRACT Aspergillus flavus is a soil-inhabiting fungus that frequently produces aflatoxins, potent carcinogens, in cottonseed and other seed crops. A. flavus S strain isolates, characterized on the basis of sclerotial morphology, are highly toxigenic. Spatial and temporal characteristics of the percentage of the A. flavus isolates that are S strain (S strain incidence) were used to predict patterns across areas of more than 30 km(2). Spatial autocorrelation in S strain incidence in Yuma County, AZ, was shown to extend beyond field boundaries to adjacent fields. Variograms revealed both short-range (2 to 6 km) and long-range (20 to 30 km) spatial structure in S strain incidence. S strain incidence at 36 locations sampled in July 1997 was predicted with a high correlation between expected and observed values (R = 0.85, P = 0.0001) by kriging data from July 1995 and July 1996. S strain incidence at locations sampled in October 1997 and March 1998 was markedly less than predicted by kriging data from the same months in prior years. Temporal analysis of four locations repeatedly sampled from April 1995 through July 1998 also indicated a major reduction in S strain incidence in the Texas Hill area after July 1997. Surface maps generated by kriging point data indicated a similarity in the spatial pattern of S strain incidence among all sampling dates despite temporal changes in the overall S strain incidence. Geostatistics provided useful descriptions of variability in S strain incidence over space and time.
Deviatoric constitutive model: domain of strain rate validity
Energy Technology Data Exchange (ETDEWEB)
Zocher, Marvin A [Los Alamos National Laboratory
2009-01-01
A case is made for using an enhanced methodology in determining the parameters that appear in a deviatoric constitutive model. Predictability rests on our ability to solve a properly posed initial boundary value problem (IBVP), which incorporates an accurate reflection of material constitutive behavior. That reflection is provided through the constitutive model. Moreover, the constitutive model is required for mathematical closure of the IBVP. Common practice in the shock physics community is to divide the Cauchy tensor into spherical and deviatoric parts, and to develop separate models for spherical and deviatoric constitutive response. Our focus shall be on the Cauchy deviator and deviatoric constitutive behavior. Discussions related to the spherical part of the Cauchy tensor are reserved for another time. A number of deviatoric constitutive models have been developed for utilization in the solution of IBVPs that are of interest to those working in the field of shock physics, e.g. All of these models are phenomenological and contain a number of parameters that must be determined in light of experimental data. The methodology employed in determining these parameters dictates the loading regime over which the model can be expected to be accurate. The focus of this paper is the methodology employed in determining model parameters and the consequences of that methodology as it relates to the domain of strain rate validity. We shall begin by describing the methodology that is typically employed. We shall discuss limitations imposed upon predictive capability by the typically employed methodology. We shall propose a modification to the typically employed methodology that significantly extends the domain of strain rate validity.
Statistical assessment of predictive modeling uncertainty
Barzaghi, Riccardo; Marotta, Anna Maria
2017-04-01
When the results of geophysical models are compared with data, the uncertainties of the model are typically disregarded. We propose a method for defining the uncertainty of a geophysical model based on a numerical procedure that estimates the empirical auto and cross-covariances of model-estimated quantities. These empirical values are then fitted by proper covariance functions and used to compute the covariance matrix associated with the model predictions. The method is tested using a geophysical finite element model in the Mediterranean region. Using a novel χ2 analysis in which both data and model uncertainties are taken into account, the model's estimated tectonic strain pattern due to the Africa-Eurasia convergence in the area that extends from the Calabrian Arc to the Alpine domain is compared with that estimated from GPS velocities while taking into account the model uncertainty through its covariance structure and the covariance of the GPS estimates. The results indicate that including the estimated model covariance in the testing procedure leads to lower observed χ2 values that have better statistical significance and might help a sharper identification of the best-fitting geophysical models.
Comparative Analysis of Measured and Predicted Shrinkage Strain in Concrete
Directory of Open Access Journals (Sweden)
Kossakowski P. G.
2014-06-01
Full Text Available The article discusses the issues related to concrete shrinkage. The basic information on the phenomenon is presented as well as the factors that determine the contraction are pointed out and the stages of the process are described. The guidance for estimating the shrinkage strain is given according to Eurocode standard PN-EN 1992-1-1:2008. The results of studies of the samples shrinkage strain of concrete C25/30 are presented with a comparative analysis of the results estimated by the guidelines of the standard according to PN-EN 1992-1- 1:2008
Dijkstra, Maria T M; Beersma, Bianca; Cornelissen, Roosmarijn A W M
2012-07-01
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 demonstrated that, consistent with the model, the conflict-employee strain relationship was weaker the higher employees' OBSE and the more they engaged in active problem-solving conflict management. Our data also revealed that higher levels of OBSE were related to more problem-solving conflict management. Moreover, consistent with the ARCAS model, we could confirm a conditional mediation model in which organization-based self-esteem through its relationship with problem-solving conflict management weakened the relationship between task conflict and employee strain. Potential applications of the results are discussed.
Prediction of dynamic strains on a monopile offshore wind turbine using virtual sensors
Iliopoulos, A. N.; Weijtjens, W.; Van Hemelrijck, D.; Devriendt, C.
2015-07-01
The monitoring of the condition of the offshore wind turbine during its operational states offers the possibility of performing accurate assessments of the remaining life-time as well as supporting maintenance decisions during its entire life. The efficacy of structural monitoring in the case of the offshore wind turbine, though, is undermined by the practical limitations connected to the measurement system in terms of cost, weight and feasibility of sensor mounting (e.g. at muddline level 30m below the water level). This limitation is overcome by reconstructing the full-field response of the structure based on the limited number of measured accelerations and a calibrated Finite Element Model of the system. A modal decomposition and expansion approach is used for reconstructing the responses at all degrees of freedom of the finite element model. The paper will demonstrate the possibility to predict dynamic strains from acceleration measurements based on the aforementioned methodology. These virtual dynamic strains will then be evaluated and validated based on actual strain measurements obtained from a monitoring campaign on an offshore Vestas V90 3 MW wind turbine on a monopile foundation.
Ko, William L.; Fleischer, Van Tran
2012-01-01
In the formulations of earlier Displacement Transfer Functions for structure shape predictions, the surface strain distributions, along a strain-sensing line, were represented with piecewise linear functions. To improve the shape-prediction accuracies, Improved Displacement Transfer Functions were formulated using piecewise nonlinear strain representations. Through discretization of an embedded beam (depth-wise cross section of a structure along a strain-sensing line) into multiple small domains, piecewise nonlinear functions were used to describe the surface strain distributions along the discretized embedded beam. Such piecewise approach enabled the piecewise integrations of the embedded beam curvature equations to yield slope and deflection equations in recursive forms. The resulting Improved Displacement Transfer Functions, written in summation forms, were expressed in terms of beam geometrical parameters and surface strains along the strain-sensing line. By feeding the surface strains into the Improved Displacement Transfer Functions, structural deflections could be calculated at multiple points for mapping out the overall structural deformed shapes for visual display. The shape-prediction accuracies of the Improved Displacement Transfer Functions were then examined in view of finite-element-calculated deflections using different tapered cantilever tubular beams. It was found that by using the piecewise nonlinear strain representations, the shape-prediction accuracies could be greatly improved, especially for highly-tapered cantilever tubular beams.
In vivo bone strain and finite element modeling of the mandible of Alligator mississippiensis
Porro, Laura B; Metzger, Keith A; Iriarte-Diaz, Jose; Ross, Callum F
2013-01-01
Forces experienced during feeding are thought to strongly influence the morphology of the vertebrate mandible; in vivo strain data are the most direct evidence for deformation of the mandible induced by these loading regimes. Although many studies have documented bone strains in the mammalian mandible, no information is available on strain magnitudes, orientations or patterns in the sauropsid lower jaw during feeding. Furthermore, strain gage experiments record the mechanical response of bone at a few locations, not across the entire mandible. In this paper, we present bone strain data recorded at various sites on the lower jaw of Alligator mississippiensis during in vivo feeding experiments. These data are used to understand how changes in loading regime associated with changes in bite location are related to changes in strain regime on the working and balancing sides of the mandible. Our results suggest that the working side mandible is bent dorsoventrally and twisted about its long-axis during biting, and the balancing side experiences primarily dorsoventral bending. Strain orientations are more variable on the working side than on the balancing side with changes in bite point and between experiments; the balancing side exhibits higher strain magnitudes. In the second part of this paper, we use principal strain orientations and magnitudes recorded in vivo to evaluate a finite element model of the alligator mandible. Our comparison demonstrates that strain orientations and mandibular deformation predicted by the model closely match in vivo results; however, absolute strain magnitudes are lower in the finite element model. PMID:23855772
Assessment of the Uniqueness of Wind Tunnel Strain-Gage Balance Load Predictions
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.
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.
Fracture prediction using modified mohr coulomb theory for non-linear strain paths using AA3104-H19
Dick, Robert; Yoon, Jeong Whan
2016-08-01
Experiment results from uniaxial tensile tests, bi-axial bulge tests, and disk compression tests for a beverage can AA3104-H19 material are presented. The results from the experimental tests are used to determine material coefficients for both Yld2000 and Yld2004 models. Finite element simulations are developed to study the influence of materials model on the predicted earing profile. It is shown that only the YLD2004 model is capable of accurately predicting the earing profile as the YLD2000 model only predicts 4 ears. Excellent agreement with the experimental data for earing is achieved using the AA3104-H19 material data and the Yld2004 constitutive model. Mechanical tests are also conducted on the AA3104-H19 to generate fracture data under different stress triaxiality conditions. Tensile tests are performed on specimens with a central hole and notched specimens. Torsion of a double bridge specimen is conducted to generate points near pure shear conditions. The Nakajima test is utilized to produce points in bi-axial tension. The data from the experiments is used to develop the fracture locus in the principal strain space. Mapping from principal strain space to stress triaxiality space, principal stress space, and polar effective plastic strain space is accomplished using a generalized mapping technique. Finite element modeling is used to validate the Modified Mohr-Coulomb (MMC) fracture model in the polar space. Models of a hole expansion during cup drawing and a cup draw/reverse redraw/expand forming sequence demonstrate the robustness of the modified PEPS fracture theory for the condition with nonlinear forming paths and accurately predicts the onset of failure. The proposed methods can be widely used for predicting failure for the examples which undergo nonlinear strain path including rigid-packaging and automotive forming.
Quantifying strain variability in modeling growth of Listeria monocytogenes
Aryani, D.; Besten, den H.M.W.; Hazeleger, W.C.; Zwietering, M.H.
2015-01-01
Prediction of microbial growth kinetics can differ from the actual behavior of the target microorganisms. In the present study, the impact of strain variability on maximum specific growth rate (µmax) (h- 1) was quantified using twenty Listeria monocytogenes strains. The µmax was determined as functi
Bosi, Emanuele; Monk, Jonathan M; Aziz, Ramy K; Fondi, Marco; Nizet, Victor; Palsson, Bernhard Ø
2016-06-28
Staphylococcus aureus is a preeminent bacterial pathogen capable of colonizing diverse ecological niches within its human host. We describe here the pangenome of S. aureus based on analysis of genome sequences from 64 strains of S. aureus spanning a range of ecological niches, host types, and antibiotic resistance profiles. Based on this set, S. aureus is expected to have an open pangenome composed of 7,411 genes and a core genome composed of 1,441 genes. Metabolism was highly conserved in this core genome; however, differences were identified in amino acid and nucleotide biosynthesis pathways between the strains. Genome-scale models (GEMs) of metabolism were constructed for the 64 strains of S. aureus These GEMs enabled a systems approach to characterizing the core metabolic and panmetabolic capabilities of the S. aureus species. All models were predicted to be auxotrophic for the vitamins niacin (vitamin B3) and thiamin (vitamin B1), whereas strain-specific auxotrophies were predicted for riboflavin (vitamin B2), guanosine, leucine, methionine, and cysteine, among others. GEMs were used to systematically analyze growth capabilities in more than 300 different growth-supporting environments. The results identified metabolic capabilities linked to pathogenic traits and virulence acquisitions. Such traits can be used to differentiate strains responsible for mild vs. severe infections and preference for hosts (e.g., animals vs. humans). Genome-scale analysis of multiple strains of a species can thus be used to identify metabolic determinants of virulence and increase our understanding of why certain strains of this deadly pathogen have spread rapidly throughout the world.
Bosi, Emanuele; Monk, Jonathan M.; Aziz, Ramy K.; Fondi, Marco; Nizet, Victor; Palsson, Bernhard Ø.
2016-01-01
Staphylococcus aureus is a preeminent bacterial pathogen capable of colonizing diverse ecological niches within its human host. We describe here the pangenome of S. aureus based on analysis of genome sequences from 64 strains of S. aureus spanning a range of ecological niches, host types, and antibiotic resistance profiles. Based on this set, S. aureus is expected to have an open pangenome composed of 7,411 genes and a core genome composed of 1,441 genes. Metabolism was highly conserved in this core genome; however, differences were identified in amino acid and nucleotide biosynthesis pathways between the strains. Genome-scale models (GEMs) of metabolism were constructed for the 64 strains of S. aureus. These GEMs enabled a systems approach to characterizing the core metabolic and panmetabolic capabilities of the S. aureus species. All models were predicted to be auxotrophic for the vitamins niacin (vitamin B3) and thiamin (vitamin B1), whereas strain-specific auxotrophies were predicted for riboflavin (vitamin B2), guanosine, leucine, methionine, and cysteine, among others. GEMs were used to systematically analyze growth capabilities in more than 300 different growth-supporting environments. The results identified metabolic capabilities linked to pathogenic traits and virulence acquisitions. Such traits can be used to differentiate strains responsible for mild vs. severe infections and preference for hosts (e.g., animals vs. humans). Genome-scale analysis of multiple strains of a species can thus be used to identify metabolic determinants of virulence and increase our understanding of why certain strains of this deadly pathogen have spread rapidly throughout the world. PMID:27286824
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.
Modeling of a Surface Acoustic Wave Strain Sensor
Wilson, W. C.; Atkinson, Gary M.
2010-01-01
NASA Langley Research Center is investigating Surface Acoustic Wave (SAW) sensor technology for harsh environments aimed at aerospace applications. To aid in development of sensors a model of a SAW strain sensor has been developed. The new model extends the modified matrix method to include the response of Orthogonal Frequency Coded (OFC) reflectors and the response of SAW devices to strain. These results show that the model accurately captures the strain response of a SAW sensor on a Langasite substrate. The results of the model of a SAW Strain Sensor on Langasite are presented
Screening Three Strains of Pseudomonas aeruginosa: Prediction of Biosurfactant-Producer Strain
Directory of Open Access Journals (Sweden)
Gholamreza Dehghan-Noudeh
2009-01-01
Full Text Available Problem statement: The chemical surfactants have some disadvantages; especially, toxicity and no biodegradability. Approach: Biosurfactants were the structurally diverse group of surface-active molecules synthesize by micro-organisms. The microbial surfactants were interesting, because of the biodegradable and have many applications in industry, agriculture, medicine. Results: In the present study, the production of biosurfactant by three strains of Pseudomonas aeruginosa (PTCC 1074, 1310 and 1430 was investigated. The hemolytic and foam forming activity of different strains were studied and consequently, P. aeruginosa PTCC 1074 was selected as the suitable strain. P. aeruginosa PTCC 1074 was grown in the nutrient broth medium and biosurfactant production was evaluated every 24 h by emulsification index and surface tension for the best of production time. After that, in order to get maximum production of biosurfactant, the selected strain was grown with different additives in nutrient broth and the best culture medium was found. The biosurfactant was isolated from the supernatant and its amphipathic structure was confirmed by chemical methods. Conclusion: Biosurfactant produced by Pseudomonas aeruginosa PTCC 1074 would be considered as a suitable surfactant in industries due to its low toxicity.
Webster, Duncan; Schulte, Friederike A; Lambers, Floor M; Kuhn, Gisela; Müller, Ralph
2015-03-18
Huiskes et al. hypothesized that mechanical strains sensed by osteocytes residing in trabecular bone dictate the magnitude of load-induced bone formation. More recently, the mechanical environment in bone marrow has also been implicated in bone׳s response to mechanical stimulation. In this study, we hypothesize that trabecular load-induced bone formation can be predicted by mechanical signals derived from an integrative µFE model, incorporating a description of both the bone and marrow phase. Using the mouse tail loading model in combination with in vivo micro-computed tomography (µCT) we tracked load induced changes in the sixth caudal vertebrae of C57BL/6 mice to quantify the amount of newly mineralized and eroded bone volumes. To identify the mechanical signals responsible for adaptation, local morphometric changes were compared to micro-finite element (µFE) models of vertebrae prior to loading. The mechanical parameters calculated were strain energy density (SED) on trabeculae at bone forming and resorbing surfaces, SED in the marrow at the boundary between bone forming and resorbing surfaces, along with SED in the trabecular bone and marrow volumes. The gradients of each parameter were also calculated. Simple regression analysis showed mean SED gradients in the trabecular bone matrix to significantly correlate with newly mineralized and eroded bone volumes R(2)=0.57 and 0.41, respectively, pbone marrow plays a significant role in determining osteoblast and osteoclast activity.
High Strain-Rate Material Model Validation for Laser Peening Simulation
Directory of Open Access Journals (Sweden)
Kristina Langer
2015-09-01
Full Text Available Finite element modeling can be a powerful tool for predicting residual stresses induced by laser peening; however the sign and magnitude of the stress predictions depend strongly on how the material model captures the high strain rate response. Although a Johnson-Cook formulation is often employed, its suitability for modeling phenomena at very high strain rates has not been rigorously evaluated. In this paper, we address the effectiveness of the Johnson-Cook model, with parameters developed from lower strain rate material data (∼10^3 s^–1, to capture the higher strain rate response (∼10^5–10^6 s^–1 encountered during the laser peening process. Published Johnson-Cook parameters extracted from split Hopkinson bar testing were used to predict the shock response of aluminum samples during high-impact flyer plate tests. Additional quasi-static and split Hopkinson bar tests were also conducted to study the model response in the lower strain rate regime. The overall objective of the research was to ascertain whether a material model based on conventional test data (quasi-static compression testing and split Hopkinson bar measurements can credibly be used in FE simulations to predict laser peen-induced stresses.
Modeling temperature and strain rate history in effects in OFHU Cu
Tanner, Albert Buck
Accurate material behavior prediction during large deformations is essential. For the U.S. Army, explosively formed projectiles (EFP), penetrators, and vehicle armor are applications which will benefit from a better understanding of and ability to predict material behavior when subjected to high and varying strain rates and temperatures. Linking macro-scale material behavior with the evolution of microstructure has proven effective in obtaining an appropriate mathematical structure for constitutive relationships. Incorporation of strain rate, temperature, and deformation path history effects are especially critical to accurately predict material responses for arbitrary nonisothermal, variable strain rate conditions. Material constitutive equations contain numerous parameters which must be determined experimentally, and often are not fully optimized. The goal of this research was to develop more physically descriptive kinematics and kinetics models for large strain deformation based on internal state variable (ISV) evolution laws which include strain rate and temperature history dependence. A unique and comprehensive set of experiments involving sequences of different strain rates, temperatures, and deformation paths, as well as, constant strain rate, isothermal and experiments characterizing restoration processes, were conducted on OFHC Cu. Microstructural examinations found that recrystallization occurs and has a significant influence on the flow stress. The performance of various models, including state-of-the-art models such as the BCJ (Sandia), MTS (Los Alamos), and McDowell models were correlated and compared to experimental data. A novel hybrid optimization strategy was used to obtain the optimum parameter set possible corresponding to each model form. To account for the observed flow stress softening, an internal state variable representing the "softened" recrystallized state was incorporated into the hardening evolution equations in the BCJ and Mc
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.
Elías-Zúñiga, Alex; Baylón, Karen; Ferrer, Inés; Serenó, Lídia; Garcia-Romeu, Maria Luisa; Bagudanch, Isabel; Grabalosa, Jordi; Pérez-Recio, Tania; Martínez-Romero, Oscar; Ortega-Lara, Wendy; Elizalde, Luis Ernesto
2014-01-01
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. PMID:28788466
LS-DYNA Implementation of Polymer Matrix Composite Model Under High Strain Rate Impact
Zheng, Xia-Hua; Goldberg, Robert K.; Binienda, Wieslaw K.; Roberts, Gary D.
2003-01-01
A recently developed constitutive model is implemented into LS-DYNA as a user defined material model (UMAT) to characterize the nonlinear strain rate dependent behavior of polymers. By utilizing this model within a micromechanics technique based on a laminate analogy, an algorithm to analyze the strain rate dependent, nonlinear deformation of a fiber reinforced polymer matrix composite is then developed as a UMAT to simulate the response of these composites under high strain rate impact. The models are designed for shell elements in order to ensure computational efficiency. Experimental and numerical stress-strain curves are compared for two representative polymers and a representative polymer matrix composite, with the analytical model predicting the experimental response reasonably well.
A New Theoretical Model of a Carbon Nanotube Strain Sensor
Institute of Scientific and Technical Information of China (English)
QIU Wei; KANG Yi-Lan; LEI Zhen-Kun; QIN Qing-Hua; LI Qiu
2009-01-01
Carbon nanotubes (CNTs) are potential strain sensors due to their excellent mechanical and spectral properties.A new theoretical model of a CNT strain sensor is obtained by applying the polarized Raman properties of CNTs,which calculates the synthetic contributions of Raman spectra from the CNTs in random directions.By using this theoretical model,the analytic relationship between planar strain components and the Raman shift increment of uniformly dispersed CNTs is obtained,which is applicable for accurately characterizing the strain in random directions on the surface of a measured microsystem.
Giordano, Chiara; Kleiven, Svein
2014-11-01
Finite element (FE) models are often used to study the biomechanical effects of traumatic brain injury (TBI). Measures based on mechanical responses, such as principal strain or invariants of the strain tensor, are used as a metric to predict the risk of injury. However, the reliability of inferences drawn from these models depends on the correspondence between the mechanical measures and injury data, as well as the establishment of accurate thresholds of tissue injury. In the current study, a validated anisotropic FE model of the human head is used to evaluate the hypothesis that strain in the direction of fibers (axonal strain) is a better predictor of TBI than maximum principal strain (MPS), anisotropic equivalent strain (AESM) and cumulative strain damage measure (CSDM). An analysis of head kinematics-based metrics, such as head injury criterion (HIC) and brain injury criterion (BrIC), is also provided. Logistic regression analysis is employed to compare binary injury data (concussion/no concussion) with continuous strain/kinematics data. The threshold corresponding to 50% of injury probability is determined for each parameter. The predictive power (area under the ROC curve, AUC) is calculated from receiver operating characteristic (ROC) curve analysis. The measure with the highest AUC is considered to be the best predictor of mTBI. Logistic regression shows a statistical correlation between all the mechanical predictors and injury data for different regions of the brain. Peaks of axonal strain have the highest AUC and determine a strain threshold of 0.07 for corpus callosum and 0.15 for the brainstem, in agreement with previously experimentally derived injury thresholds for reversible axonal injury. For a data set of mild TBI from the national football league, the strain in the axonal direction is found to be a better injury predictor than MPS, AESM, CSDM, BrIC and HIC.
National Research Council Canada - National Science Library
Ravindranadh BOBBILI B. RAMAKRISHNA V. MADHU A.K. GOGIA
2015-01-01
An artificial neural network （ANN） constitutive model and Johnson-Cook （J-C） model were developed for 7017 aluminium alloy based on high strain rate data generated from split Hopkinson pressure bar （SHPB...
National Research Council Canada - National Science Library
Bobbili, Ravindranadh; Ramakrishna, B; Madhu, V; Gogia, A.K
2015-01-01
An artificial neural network (ANN) constitutive model and Johnson–Cook (J–C) model were developed for 7017 aluminium alloy based on high strain rate data generated from split Hopkinson pressure bar (SHPB...
PREDICT : model for prediction of survival in localized prostate cancer
Kerkmeijer, Linda G W; Monninkhof, Evelyn M.; van Oort, Inge M.; van der Poel, Henk G.; de Meerleer, Gert; van Vulpen, Marco
2016-01-01
Purpose: Current models for prediction of prostate cancer-specific survival do not incorporate all present-day interventions. In the present study, a pre-treatment prediction model for patients with localized prostate cancer was developed.Methods: From 1989 to 2008, 3383 patients were treated with I
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....
Predictive Modeling of Cardiac Ischemia
Anderson, Gary T.
1996-01-01
The goal of the Contextual Alarms Management System (CALMS) project is to develop sophisticated models to predict the onset of clinical cardiac ischemia before it occurs. The system will continuously monitor cardiac patients and set off an alarm when they appear about to suffer an ischemic episode. The models take as inputs information from patient history and combine it with continuously updated information extracted from blood pressure, oxygen saturation and ECG lines. Expert system, statistical, neural network and rough set methodologies are then used to forecast the onset of clinical ischemia before it transpires, thus allowing early intervention aimed at preventing morbid complications from occurring. The models will differ from previous attempts by including combinations of continuous and discrete inputs. A commercial medical instrumentation and software company has invested funds in the project with a goal of commercialization of the technology. The end product will be a system that analyzes physiologic parameters and produces an alarm when myocardial ischemia is present. If proven feasible, a CALMS-based system will be added to existing heart monitoring hardware.
Institute of Scientific and Technical Information of China (English)
Ravindranadh BOBBILI; V. MADHU; A.K. GOGIA
2014-01-01
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 JohnsoneCook (JeC) 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 stressestrain data obtained from high strain rate compression tests using SHPB, over a range of tempering temperatures (500e650 ?C), strains (0.05e0.2) and strain rates (1000e5500/s) are employed to formulate JeC 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 JeC 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.
Runciman, Amanda; Xu, David; Pelton, Alan R; Ritchie, Robert O
2011-08-01
Medical devices, particularly endovascular stents, manufactured from superelastic Nitinol, a near-equiatomic alloy of Ni and Ti, are subjected to complex mixed-mode loading conditions in vivo, including axial tension and compression, radial compression, pulsatile, bending and torsion. Fatigue lifetime prediction methodologies for Nitinol, however, are invariably based on uniaxial loading and thus fall short of accurately predicting the safe lifetime of stents under the complex multiaxial loading conditions experienced physiologically. While there is a considerable body of research documented on the cyclic fatigue of Nitinol in uniaxial tension or bending, there remains an almost total lack of comprehensive fatigue lifetime data for other loading conditions, such as torsion and tension/torsion. In this work, thin-walled Nitinol tubes were cycled in torsion at various mean and alternating strains to investigate the fatigue life behavior of Nitinol and results compared to equivalent fatigue data collected under uniaxial tensile/bending loads. Using these strain-life results for various loading modes and an equivalent referential (Lagrangian) strain approach, a strategy for normalizing these data is presented. Based on this strategy, a fatigue lifetime prediction model for the multiaxial loading of Nitinol is presented utilizing a modified Coffin-Manson approach where the number of cycles to failure is related to the equivalent alternating transformation strain.
Strain-Path Modeling for Geo-Materials.
1984-03-07
feasible to obtain by measurement the stress-strain curves needed for reliable prediction of se smic sources. A subset of the same curves also prevails on a...explosive events is eviden - tly open to criticism, and some of that appears below. However, the aim of this paper is not to carp, but to map a more...curves needed for accurate prediction of motion at a given site are obtained by measuring stress along the kinds of strain paths already known to
Models for elastic shells with incompatible strains
2012-01-01
The three-dimensional shapes of thin lamina such as leaves, flowers, feathers, wings etc, are driven by the differential strain induced by the relative growth. The growth takes place through variations in the Riemannian metric, given on the thin sheet as a function of location in the central plane and also across its thickness. The shape is then a consequence of elastic energy minimization on the frustrated geometrical object. Here we provide a rigorous derivation of the asymptotic theories f...
Numerical weather prediction model tuning via ensemble prediction system
Jarvinen, H.; Laine, M.; Ollinaho, P.; Solonen, A.; Haario, H.
2011-12-01
This paper discusses a novel approach to tune predictive skill of numerical weather prediction (NWP) models. NWP models contain tunable parameters which appear in parameterizations schemes of sub-grid scale physical processes. Currently, numerical values of these parameters are specified manually. In a recent dual manuscript (QJRMS, revised) we developed a new concept and method for on-line estimation of the NWP model parameters. The EPPES ("Ensemble prediction and parameter estimation system") method requires only minimal changes to the existing operational ensemble prediction infra-structure and it seems very cost-effective because practically no new computations are introduced. The approach provides an algorithmic decision making tool for model parameter optimization in operational NWP. In EPPES, statistical inference about the NWP model tunable parameters is made by (i) generating each member of the ensemble of predictions using different model parameter values, drawn from a proposal distribution, and (ii) feeding-back the relative merits of the parameter values to the proposal distribution, based on evaluation of a suitable likelihood function against verifying observations. In the presentation, the method is first illustrated in low-order numerical tests using a stochastic version of the Lorenz-95 model which effectively emulates the principal features of ensemble prediction systems. The EPPES method correctly detects the unknown and wrongly specified parameters values, and leads to an improved forecast skill. Second, results with an atmospheric general circulation model based ensemble prediction system show that the NWP model tuning capacity of EPPES scales up to realistic models and ensemble prediction systems. Finally, a global top-end NWP model tuning exercise with preliminary results is published.
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.
Modeling the electromechanical and strain response of carbon nanotube-based nanocomposites
Lee, Bo Mi; Loh, Kenneth J.; Burton, Andrew R.; Loyola, Bryan R.
2014-04-01
Over the last few decades, carbon nanotube (CNT)-based thin films or nanocomposites have been widely investigated as a multifunctional material. The proposed applications extend beyond sensing, ultra-strong coatings, biomedical grafts, and energy harvesting, among others. In particular, thin films characterized by a percolated and random distribution of CNTs within a flexible polymeric matrix have been shown to change its electrical properties in response to applied strains. While a plethora of experimental work has been conducted, modeling their electromechanical response remains challenging. Furthermore, their design and optimization require the derivation of accurate electromechanical models that could predict thin film response to applied strains. Thus, the objective of this study is to implement a percolation-based piezoresistive model that could explain the underlying mechanisms for strain sensing. First, a percolation-based model with randomly distributed, straight CNTs was developed in MATLAB. Second, the number of CNTs within a unit area was varied to explore its influence on percolation probability. Then, to understand how the film's electrical properties respond to strain, two different models were implemented. Both models calculated the geometrical response of the film and CNTs due to applied uniaxial strains. The first model considered the fact that the electrical resistance of individual CNTs changed depending solely on its length between junctions. The other model further explored the idea of incorporating strain sensitivity of individual CNTs. The electromechanical responses and the strain sensitivities of the two models were compared by calculating how their bulk resistance varied due to applied tensile and compressive strains. The numerical model results were then qualitatively compared to experimental results reported in the literature.
Evaluation of burst pressure prediction models for line pipes
Energy Technology Data Exchange (ETDEWEB)
Zhu, Xian-Kui, E-mail: zhux@battelle.org [Battelle Memorial Institute, 505 King Avenue, Columbus, OH 43201 (United States); Leis, Brian N. [Battelle Memorial Institute, 505 King Avenue, Columbus, OH 43201 (United States)
2012-01-15
Accurate prediction of burst pressure plays a central role in engineering design and integrity assessment of oil and gas pipelines. Theoretical and empirical solutions for such prediction are evaluated in this paper relative to a burst pressure database comprising more than 100 tests covering a variety of pipeline steel grades and pipe sizes. Solutions considered include three based on plasticity theory for the end-capped, thin-walled, defect-free line pipe subjected to internal pressure in terms of the Tresca, von Mises, and ZL (or Zhu-Leis) criteria, one based on a cylindrical instability stress (CIS) concept, and a large group of analytical and empirical models previously evaluated by Law and Bowie (International Journal of Pressure Vessels and Piping, 84, 2007: 487-492). It is found that these models can be categorized into either a Tresca-family or a von Mises-family of solutions, except for those due to Margetson and Zhu-Leis models. The viability of predictions is measured via statistical analyses in terms of a mean error and its standard deviation. Consistent with an independent parallel evaluation using another large database, the Zhu-Leis solution is found best for predicting burst pressure, including consideration of strain hardening effects, while the Tresca strength solutions including Barlow, Maximum shear stress, Turner, and the ASME boiler code provide reasonably good predictions for the class of line-pipe steels with intermediate strain hardening response. - Highlights: Black-Right-Pointing-Pointer This paper evaluates different burst pressure prediction models for line pipes. Black-Right-Pointing-Pointer The existing models are categorized into two major groups of Tresca and von Mises solutions. Black-Right-Pointing-Pointer Prediction quality of each model is assessed statistically using a large full-scale burst test database. Black-Right-Pointing-Pointer The Zhu-Leis solution is identified as the best predictive model.
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...
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 co...... of friction in metal forming, where the material generally strain hardens. The extension of the model to cover strain hardening materials is validated by comparison to previously published experimental data.......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......-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...
Carozzi, N B; Kramer, V C; Warren, G W; Evola, S; Koziel, M G
1991-01-01
A rapid analysis of Bacillus thuringiensis strains predictive of insecticidal activity was established by using polymerase chain reaction (PCR) technology. Primers specific to regions of high homology within genes encoding three major classes of B. thuringiensis crystal proteins were used to generate a PCR product profile characteristic of each insecticidal class. Predictions of insecticidal activity were made on the basis of the electrophoretic patterns of the PCR products. Included in the s...
Predictive Model Assessment for Count Data
2007-09-05
critique count regression models for patent data, and assess the predictive performance of Bayesian age-period-cohort models for larynx cancer counts...the predictive performance of Bayesian age-period-cohort models for larynx cancer counts in Germany. We consider a recent suggestion by Baker and...Figure 5. Boxplots for various scores for patent data count regressions. 11 Table 1 Four predictive models for larynx cancer counts in Germany, 1998–2002
Competition, coinfection and strain replacement in models of Bordetella pertussis.
Nicoli, Emily J; Ayabina, Diepreye; Trotter, Caroline L; Turner, Katherine M E; Colijn, Caroline
2015-08-01
Pertussis, or whooping cough, is an important respiratory infection causing considerable infant mortality worldwide. Recently, incidence has risen in countries with strong vaccine programmes and there are concerns about antigenic shift resulting in vaccine evasion. Interactions between pertussis and non-vaccine-preventable strains will play an important role in the evolution and population dynamics of pertussis. In particular, if we are to understand the role strain replacement plays in vaccinated settings, it will be essential to understand how strains or variants of pertussis interact. Here we explore under what conditions we would expect strain replacement to be of concern in pertussis. We develop a dynamic transmission model that allows for coinfection between Bordetella pertussis (the main causative agent of pertussis) and a strain or variant unaffected by the vaccine. We incorporate both neutrality (in the sense of ecological/population genetic neutrality) and immunity into the model, leaving the specificity of the immune response flexible. We find that strain replacement may be considerable when immunity is non-specific. This is in contrast to previous findings where neutrality was not considered. We conclude that the extent to which models reflect ecological neutrality can have a large impact on conclusions regarding strain replacement. This will likely have onward consequences for estimates of vaccine efficacy and cost-effectiveness.
Canadinç, Demircan; Önal, Orkun; Özmenci, Cemre
2014-01-01
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 ten...
Mehdizadeh, Arash; Gardiner, Bruce S; Lavagnino, Michael; Smith, David W
2017-03-13
In this study, we propose a method for quantitative prediction of changes in concentrations of a number of key signaling, structural and effector molecules within the extracellular matrix of tendon. To achieve this, we introduce the notion of elementary cell responses (ECRs). An ECR defines a normal reference secretion profile of a molecule by a tenocyte in response to the tenocyte's local strain. ECRs are then coupled with a model for mechanical damage of tendon collagen fibers at different straining conditions of tendon and then scaled up to the tendon tissue level for comparison with experimental observations. Specifically, our model predicts relative changes in ECM concentrations of transforming growth factor beta, interleukin 1 beta, collagen type I, glycosaminoglycan, matrix metalloproteinase 1 and a disintegrin and metalloproteinase with thrombospondin motifs 5, with respect to tendon straining conditions that are consistent with the observations in the literature. In good agreement with a number of in vivo and in vitro observations, the model provides a logical and parsimonious explanation for how excessive mechanical loading of tendon can lead to under-stimulation of tenocytes and a degenerative tissue profile, which may well have bearing on a better understanding of tendon homeostasis and the origin of some tendinopathies.
Modeling of Stress- Strain Curves of Drained Triaxial Test on Sand
Directory of Open Access Journals (Sweden)
Awad A. Karni
2006-01-01
Full Text Available This paper presents a hyperbolic mathematical model to predict the complete stress-strain curve of drained triaxial tests on uniform dense sand. The model was formed in one equation with many parameters. The main parameters that are needed to run the model are the confining pressure, angle of friction and the relative density. The other parameters, initial and final slopes of the stress strain curve, the reference stress and the curve-shape parameter are determined as functions of the confining pressure, angle of friction and the relative density using best fitting curve technique from the experimental tests results. Drained triaxial tests were run on clean white uniform sand to utilize and verify this model. These tests were carried out at four levels of confining pressure of 100, 200, 300 and 400 kPa. This model was used to predict the stress-strain curves for drained triaxial tests on quartz sand at different relative density using the data of Kouner[1]. The model predictions were compared with the experimental results and showed good agreements of the predicted results with the experimental results at all levels of applied confining pressures and relative densities.
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.
Mechanical model for yield strength of nanocrystalline materials under high strain rate loading
Institute of Scientific and Technical Information of China (English)
朱荣涛; 周剑秋; 马璐; 张振忠
2008-01-01
To understand the high strain rate deformation mechanism and determine the grain size,strain rate and porosity dependent yield strength of nanocrystalline materials,a new mechanical model based on the deformation mechanism of nanocrystalline materials under high strain rate loading was developed.As a first step of the research,the yield behavior of the nanocrystalline materials under high strain rate loading was mainly concerned in the model and uniform deformation was assumed for simplification.Nanocrystalline materials were treated as composites consisting of grain interior phase and grain boundary phase,and grain interior and grain boundary deformation mechanisms under high strain rate loading were analyzed,then Voigt model was applied to coupling grain boundary constitutive relation with mechanical model for grain interior phase to describe the overall yield mechanical behavior of nanocrystalline materials.The predictions by the developed model on the yield strength of nanocrysatlline materials at high strain rates show good agreements with various experimental data.Further discussion was presented for calculation results and relative experimental observations.
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.
Nonlinear chaotic model for predicting storm surges
Directory of Open Access Journals (Sweden)
M. Siek
2010-09-01
Full Text Available This paper addresses the use of the methods of nonlinear dynamics and chaos theory for building a predictive chaotic model from time series. The chaotic model predictions are made by the adaptive local models based on the dynamical neighbors found in the reconstructed phase space of the observables. We implemented the univariate and multivariate chaotic models with direct and multi-steps prediction techniques and optimized these models using an exhaustive search method. The built models were tested for predicting storm surge dynamics for different stormy conditions in the North Sea, and are compared to neural network models. The results show that the chaotic models can generally provide reliable and accurate short-term storm surge predictions.
Nonlinear chaotic model for predicting storm surges
Siek, M.; Solomatine, D.P.
This paper addresses the use of the methods of nonlinear dynamics and chaos theory for building a predictive chaotic model from time series. The chaotic model predictions are made by the adaptive local models based on the dynamical neighbors found in the reconstructed phase space of the observables.
Geomechanical modeling of stress and strain evolution during contractional fault-related folding
Smart, Kevin J.; Ferrill, David A.; Morris, Alan P.; McGinnis, Ronald N.
2012-11-01
Understanding stress states and rock mass deformation deep underground is critical to a range of endeavors including oil and gas exploration and production, geothermal reservoir characterization and management, and subsurface disposal of CO2. Geomechanical modeling can predict the onset of failure and the type and abundance of deformation features along with the orientations and magnitudes of stresses. This approach enables development of forward models that incorporate realistic mechanical stratigraphy (e.g., including competence contrasts, bed thicknesses, and bedding planes), include faults and bedding-slip surfaces as frictional sliding interfaces, reproduce the overall geometry of the fold structures of interest, and allow tracking of stress and strain through the deformation history. Use of inelastic constitutive relationships (e.g., elastic-plastic behavior) allows permanent strains to develop in response to the applied loads. This ability to capture permanent deformation is superior to linear elastic models, which are often used for numerical convenience, but are incapable of modeling permanent deformation or predicting permanent deformation processes such as faulting, fracturing, and pore collapse. Finite element modeling results compared with field examples of a natural contractional fault-related fold show that well-designed geomechanical modeling can match overall fold geometries and be applied to stress, fracture, and subseismic fault prediction in geologic structures. Geomechanical modeling of this type allows stress and strain histories to be obtained throughout the model domain.
Peri-Implant Strain in an In Vitro Model.
Hussaini, Souheil; Vaidyanathan, Tritala K; Wadkar, Abhinav P; Quran, Firas A Al; Ehrenberg, David; Weiner, Saul
2015-10-01
An in vitro experimental model was designed and tested to determine the influence that peri-implant strain may have on the overall crestal bone. Strain gages were attached to polymethylmethacrylate (PMMA) models containing a screw-type root form implant at sites 1 mm from the resin-implant interface. Three different types of crown superstructures (cemented, 1-screw [UCLA] and 2-screw abutment types) were tested. Loading (1 Hz, 200 N load) was performed using a MTS Mechanical Test System. The strain gage data were stored and organized in a computer for statistical treatment. Strains for all abutment types did not exceed the physiological range for modeling and remodeling of cancellous bone, 200-2500 με (microstrain). For approximately one-quarter of the trials, the strain values were less than 200 με the zone for bone atrophy. The mean microstrain obtained was 517.7 με. In conclusion, the peri-implant strain in this in vitro model did not exceed the physiologic range of bone remodeling under axial occlusal loading.
EFFICIENT PREDICTIVE MODELLING FOR ARCHAEOLOGICAL RESEARCH
Balla, A.; Pavlogeorgatos, G.; Tsiafakis, D.; Pavlidis, G.
2014-01-01
The study presents a general methodology for designing, developing and implementing predictive modelling for identifying areas of archaeological interest. The methodology is based on documented archaeological data and geographical factors, geospatial analysis and predictive modelling, and has been applied to the identification of possible Macedonian tombs’ locations in Northern Greece. The model was tested extensively and the results were validated using a commonly used predictive gain,...
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
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...
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
Averaged hole mobility model of biaxially strained Si
Institute of Scientific and Technical Information of China (English)
Song Jianjun; Zhu He; Yang Jinyong; Zhang Heming; Xuan Rongxi; Hu Huiyong
2013-01-01
We aim to establisha model of the averaged hole mobility of strained Si grown on (001),(101),and (111) relaxed Si1-xGex substrates.The results obtained from our calculation show that their hole mobility values corresponding to strained Si (001),(101) and (111) increase by at most about three,two and one times,respectively,in comparison with the unstrained Si.The results can provide a valuable reference to the understanding and design of strained Si-based device physics.
Electric circuit model for strained-layer epitaxy
Kujofsa, Tedi; Ayers, John E.
2016-11-01
For the design and analysis of a strained-layer semiconductor device structure, the equilibrium strain profile may be determined numerically by energy minimization but this method is computationally intense and non-intuitive. Here we present an electric circuit model approach for the equilibrium analysis of an epitaxial stack, in which each sublayer may be represented by an analogous configuration involving a current source, a resistor, a voltage source, and an ideal diode. The resulting node voltages in the analogous electric circuit correspond to the equilibrium strains in the original epitaxial structure. This new approach enables analysis using widely accessible circuit simulators, and an intuitive understanding of electric circuits may be translated to the relaxation of strained-layer structures. In this paper, we describe the mathematical foundation of the electrical circuit model and demonstrate its application to epitaxial layers of Si1-x Ge x grown on a Si (001) substrate.
Safari, Keivan H.; Zamani, Jamal; Guedes, Rui M.; Ferreira, Fernando J.
2016-02-01
An adiabatic constitutive model is proposed for large strain deformation of polycarbonate (PC) at high strain rates. When the strain rate is sufficiently high such that the heat generated does not have time to transfer to the surroundings, temperature of material rises. The high strain rate deformation behavior of polymers is significantly affected by temperature-dependent constants and thermal softening. Based on the isothermal model which first was introduced by Mulliken and Boyce et al. (Int. J. Solids Struct. 43:1331-1356, 2006), an adiabatic model is proposed to predict the yield and post-yield behavior of glassy polymers at high strain rates. When calculating the heat generated and the temperature changes during the step by step simulation of the deformation, temperature-dependent elastic constants are incorporated to the constitutive equations. Moreover, better prediction of softening phenomena is achieved by the new definition for softening parameters of the proposed model. The constitutive model has been implemented numerically into a commercial finite element code through a user material subroutine (VUMAT). The experimental results, obtained using a split Hopkinson pressure bar, are supported by dynamic mechanical thermal analysis (DMTA) and Decompose/Shift/Reconstruct (DSR) method. Comparison of adiabatic model predictions with experimental data demonstrates the ability of the model to capture the characteristic features of stress-strain curve of the material at very high strain rates.
How to Establish Clinical Prediction Models
Directory of Open Access Journals (Sweden)
Yong-ho Lee
2016-03-01
Full Text Available A clinical prediction model can be applied to several challenging clinical scenarios: screening high-risk individuals for asymptomatic disease, predicting future events such as disease or death, and assisting medical decision-making and health education. Despite the impact of clinical prediction models on practice, prediction modeling is a complex process requiring careful statistical analyses and sound clinical judgement. Although there is no definite consensus on the best methodology for model development and validation, a few recommendations and checklists have been proposed. In this review, we summarize five steps for developing and validating a clinical prediction model: preparation for establishing clinical prediction models; dataset selection; handling variables; model generation; and model evaluation and validation. We also review several studies that detail methods for developing clinical prediction models with comparable examples from real practice. After model development and vigorous validation in relevant settings, possibly with evaluation of utility/usability and fine-tuning, good models can be ready for the use in practice. We anticipate that this framework will revitalize the use of predictive or prognostic research in endocrinology, leading to active applications in real clinical practice.
A 3-D Geodynamic Model of Strain Partitioning in Southern California
Ye, J.; Liu, M.; Lin, F.
2012-12-01
In southern California, strain resulting from the relative motion between the Pacific and the North American plates is partitioned in a complex system of transcurrent, transcompressional, and transtensional faults. High-precision GPS measurements in this region have enabled kinematic modeling of the present-day strain partitioning between major faults in southern California. However, geodynamic models are needed to understand the cause of strain partitioning and to determine strain in regions where faults are blind or diffuse. We have developed a regional-scale geodynamic model of strain partitioning in southern California. This 3-D viscoelasto-plastic finite element model incorporates first-order fault geometry of the major active faults in the region. The model domain includes an elastoplastic upper crust on top of a viscoelastic lower lithospheric layer. Deformation is driven by the relative motion between the Pacific and the North American plates, imposed as a displacement boundary condition. Plastic deformation both within the fault zones and in the unfaulted surrounding crust is calculated. Our results show that the Big Bend of the San Andreas Fault, and other geometric complexity of faults in southern California, plays a major role in strain partitioning. The observed variations of strain portioning in southern California can be explained by the geometric configuration of fault systems relative to the relative plate motion, without appealing to basal traction of a flowing lower lithosphere. The model predicts concentrated plastic strain under the reverse fault systems in the Transverse Ranges and the young and diffuse faults in the Eastern California Shear Zone across the Mojave Desert, where a number damaging earthquakes occurred in the past decades.
Comparison of Prediction-Error-Modelling Criteria
DEFF Research Database (Denmark)
Jørgensen, John Bagterp; Jørgensen, Sten Bay
2007-01-01
is a realization of a continuous-discrete multivariate stochastic transfer function model. The proposed prediction error-methods are demonstrated for a SISO system parameterized by the transfer functions with time delays of a continuous-discrete-time linear stochastic system. The simulations for this case suggest......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...... computational resources. The identification method is suitable for predictive control....
Atomistic modeling at experimental strain rates and timescales
Yan, Xin; Cao, Penghui; Tao, Weiwei; Sharma, Pradeep; Park, Harold S.
2016-12-01
Modeling physical phenomena with atomistic fidelity and at laboratory timescales is one of the holy grails of computational materials science. Conventional molecular dynamics (MD) simulations enable the elucidation of an astonishing array of phenomena inherent in the mechanical and chemical behavior of materials. However, conventional MD, with our current computational modalities, is incapable of resolving timescales longer than microseconds (at best). In this short review article, we briefly review a recently proposed approach—the so-called autonomous basin climbing (ABC) method—that in certain instances can provide valuable information on slow timescale processes. We provide a general summary of the principles underlying the ABC approach, with emphasis on recent methodological developments enabling the study of mechanically-driven processes at slow (experimental) strain rates and timescales. Specifically, we show that by combining a strong physical understanding of the underlying phenomena, kinetic Monte Carlo, transition state theory and minimum energy pathway methods, the ABC method has been found to be useful in a variety of mechanically-driven problems ranging from the prediction of creep-behavior in metals, constitutive laws for grain boundary sliding, void nucleation rates, diffusion in amorphous materials to protein unfolding. Aside from reviewing the basic ideas underlying this approach, we emphasize some of the key challenges encountered in our own personal research work and suggest future research avenues for exploration.
Research of the rapid pressure-strain correlation model in the rapid distortion limit
Institute of Scientific and Technical Information of China (English)
2008-01-01
Even though a number of rapid pressure-strain models have been suggested and successfully tested for different flow situations by various authors,the model proposals still exhibit some apparent deficiencies when subjected to the flows with rapid distortion. From Mansour’s relatively straightforward rapid distortion analysis,if an initially anisotropic flow undergoes a purely rapid rotation,the anisotropy measures will exhibit the behavior of the damped oscillations. Within the current framework of modeling the rapid pressure-strain correlation,i.e.,the models based on the assumption that the M-tensor for the rapid pressure-strain term is expand-able in the Reynolds-stress anisotropy tensor alone,all the model predictions fail to give the damped oscillations in the turbulence anisotropy. In the case of initially isotropic turbulence subjected to rapid distortion,Sj?gren and Johansson showed that all the existing rapid pressure-strain models would deliver the identical path in the anisotropy-invariant map for both homogeneous plane strain and shear flows. The rapid distortion analysis shows two distinct curves reflecting different flow physics. In this work,we try to present a possible way to create a system that can overcome these deficiencies with the aid of the rapid distortion theory (RDT).
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...
Evaluation of a dentoalveolar model for testing mouthguards: stress and strain analyses.
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.
Analytical Modeling of the High Strain Rate Deformation of Polymer Matrix Composites
Goldberg, Robert K.; Roberts, Gary D.; Gilat, Amos
2003-01-01
The results presented here are part of an ongoing research program to develop strain rate dependent deformation and failure models for the analysis of polymer matrix composites subject to high strain rate impact loads. State variable constitutive equations originally developed for metals have been modified in order to model the nonlinear, strain rate dependent deformation of polymeric matrix materials. To account for the effects of hydrostatic stresses, which are significant in polymers, the classical 5 plasticity theory definitions of effective stress and effective plastic strain are modified by applying variations of the Drucker-Prager yield criterion. To verify the revised formulation, the shear and tensile deformation of a representative toughened epoxy is analyzed across a wide range of strain rates (from quasi-static to high strain rates) and the results are compared to experimentally obtained values. For the analyzed polymers, both the tensile and shear stress-strain curves computed using the analytical model correlate well with values obtained through experimental tests. The polymer constitutive equations are implemented within a strength of materials based micromechanics method to predict the nonlinear, strain rate dependent deformation of polymer matrix composites. In the micromechanics, the unit cell is divided up into a number of independently analyzed slices, and laminate theory is then applied to obtain the effective deformation of the unit cell. The composite mechanics are verified by analyzing the deformation of a representative polymer matrix composite (composed using the representative polymer analyzed for the correlation of the polymer constitutive equations) for several fiber orientation angles across a variety of strain rates. The computed values compare favorably to experimentally obtained results.
Chen, Zhen; Wilmanns, Matthias; Zeng, An-Ping
2010-10-01
The future of industrial biotechnology requires efficient development of highly productive and robust strains of microorganisms. Present praxis of strain development cannot adequately fulfill this requirement, primarily owing to the inability to control reactions precisely at a molecular level, or to predict reliably the behavior of cells upon perturbation. Recent developments in two areas of biology are changing the situation rapidly: structural biology has revealed details about enzymes and associated bioreactions at an atomic level; and synthetic biology has provided tools to design and assemble precisely controllable modules for re-programming cellular metabolic circuitry. However, because of different emphases, to date, these two areas have developed separately. A linkage between them is desirable to harness their concerted potential. We therefore propose structural synthetic biotechnology as a new field in biotechnology, specifically for application to the development of industrial microbial strains. Copyright © 2010 Elsevier Ltd. All rights reserved.
Prawirodirdjo, Linette; Ben-Zion, Yehuda; Bock, Yehuda
2006-02-01
We suggest that strain in the elastic part of the Earth's crust induced by surface temperature variations is a significant contributor to the seasonal variations observed in the spatially filtered daily position time series of Southern California Integrated GPS Network (SCIGN) stations. We compute the predicted thermoelastic strain from the observed local atmospheric temperature record assuming an elastically decoupled layer over a uniform elastic half-space and compare the seasonal variations in thermoelastic strain to the horizontal GPS position time series. We consider three regions (Palmdale, 29 Palms, and Idyllwild), each with one temperature station and three to six GPS stations. The temperature time series is used to compute thermoelastic strain at each station on the basis of its relative location in the temperature field. For each region we assume a wavelength for the temperature field that is related to the local topography. The depth of the decoupled layer is inferred from the phase delay between the temperature record and the GPS time series. The relative amplitude of strain variation at each GPS station, calculated to be on the order of 0.1 μstrain, is related to the relative location of that station in the temperature field. The goodness of fit between model and data is evaluated from the relative amplitudes of the seasonal signals, as well as the appropriateness of the chosen temperature field wavelength and decoupled layer depth. The analysis shows a good fit between the predicted strains and the GPS time series. This suggests that the model captures the key first-order ingredients that determine the thermoelastic strain in a given area. The results can be used to improve the signal/noise ratio in GPS data.
Case studies in archaeological predictive modelling
Verhagen, Jacobus Wilhelmus Hermanus Philippus
2007-01-01
In this thesis, a collection of papers is put together dealing with various quantitative aspects of predictive modelling and archaeological prospection. Among the issues covered are the effects of survey bias on the archaeological data used for predictive modelling, and the complexities of testing p
Childhood asthma prediction models: a systematic review.
Smit, Henriette A; Pinart, Mariona; Antó, Josep M; Keil, Thomas; Bousquet, Jean; Carlsen, Kai H; Moons, Karel G M; Hooft, Lotty; Carlsen, Karin C Lødrup
2015-12-01
Early identification of children at risk of developing asthma at school age is crucial, but the usefulness of childhood asthma prediction models in clinical practice is still unclear. We systematically reviewed all existing prediction models to identify preschool children with asthma-like symptoms at risk of developing asthma at school age. Studies were included if they developed a new prediction model or updated an existing model in children aged 4 years or younger with asthma-like symptoms, with assessment of asthma done between 6 and 12 years of age. 12 prediction models were identified in four types of cohorts of preschool children: those with health-care visits, those with parent-reported symptoms, those at high risk of asthma, or children in the general population. Four basic models included non-invasive, easy-to-obtain predictors only, notably family history, allergic disease comorbidities or precursors of asthma, and severity of early symptoms. Eight extended models included additional clinical tests, mostly specific IgE determination. Some models could better predict asthma development and other models could better rule out asthma development, but the predictive performance of no single model stood out in both aspects simultaneously. This finding suggests that there is a large proportion of preschool children with wheeze for which prediction of asthma development is difficult.
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
Research on dynamic creep strain and settlement prediction under the subway vibration loading.
Luo, Junhui; Miao, Linchang
2016-01-01
This research aims to explore the dynamic characteristics and settlement prediction of soft soil. Accordingly, the dynamic shear modulus formula considering the vibration frequency was utilized and the dynamic triaxial test conducted to verify the validity of the formula. Subsequently, the formula was applied to the dynamic creep strain function, with the factors influencing the improved dynamic creep strain curve of soft soil being analyzed. Meanwhile, the variation law of dynamic stress with sampling depth was obtained through the finite element simulation of subway foundation. Furthermore, the improved dynamic creep strain curve of soil layer was determined based on the dynamic stress. Thereafter, it could to estimate the long-term settlement under subway vibration loading by norms. The results revealed that the dynamic shear modulus formula is straightforward and practical in terms of its application to the vibration frequency. The values predicted using the improved dynamic creep strain formula closed to the experimental values, whilst the estimating settlement closed to the measured values obtained in the field test.
Modeling and Prediction of Hot Deformation Flow Curves
Mirzadeh, Hamed; Cabrera, Jose Maria; Najafizadeh, Abbas
2012-01-01
The modeling of hot flow stress and prediction of flow curves for unseen deformation conditions are important in metal-forming processes because any feasible mathematical simulation needs accurate flow description. In the current work, in an attempt to summarize, generalize, and introduce efficient methods, the dynamic recrystallization (DRX) flow curves of a 17-4 PH martensitic precipitation hardening stainless steel, a medium carbon microalloyed steel, and a 304 H austenitic stainless steel were modeled and predicted using (1) a hyperbolic sine equation with strain dependent constants, (2) a developed constitutive equation in a simple normalized stress-normalized strain form and its modified version, and (3) a feed-forward artificial neural network (ANN). These methods were critically discussed, and the ANN technique was found to be the best for the modeling available flow curves; however, the developed constitutive equation showed slightly better performance than that of ANN and significantly better predicted values than those of the hyperbolic sine equation in prediction of flow curves for unseen deformation conditions.
Development of a Generic Creep-Fatigue Life Prediction Model
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.
Life prediction of thermal-mechanical fatigue using strain-range partitioning
Halford, G. R.; Manson, S. S.
1975-01-01
The applicability is described of the method of Strainrange Partitioning to the life prediction of thermal-mechanical strain-cycling fatigue. An in-phase test on 316 stainless steel is analyzed as an illustrative example. The observed life is in excellent agreement with the life predicted by the method using the recently proposed Step-Stress Method of experimental partitioning, the Interation Damage Rule, and the life relationships determined at an isothermal temperature of 705 C. Implications of the study are discussed relative to the general thermal fatigue problem.
Modeling elastic anisotropy in strained heteroepitaxy
Krishna Dixit, Gopal; Ranganathan, Madhav
2017-09-01
Using a continuum evolution equation, we model the growth and evolution of quantum dots in the heteroepitaxial Ge on Si(0 0 1) system in a molecular beam epitaxy unit. We formulate our model in terms of evolution due to deposition, and due to surface diffusion which is governed by a free energy. This free energy has contributions from surface energy, curvature, wetting effects and elastic energy due to lattice mismatch between the film and the substrate. In addition to anisotropy due to surface energy which favors facet formation, we also incorporate elastic anisotropy due to an underlying crystal lattice. The complicated elastic problem of the film-substrate system subjected to boundary conditions at the free surface, interface and the bulk substrate is solved by perturbation analysis using a small slope approximation. This permits an analysis of effects at different orders in the slope and sheds new light on the observed behavior. Linear stability analysis shows the early evolution of the instability towards dot formation. The elastic anisotropy causes a change in the alignment of dots in the linear regime, whereas the surface energy anisotropy changes the dot shapes at the nonlinear regime. Numerical simulation of the full nonlinear equations shows the evolution of the surface morphology. In particular, we show, for parameters of the Ge0.25 Si0.75 on Si(0 0 1), the surface energy anisotropy dominates the shapes of the quantum dots, whereas their alignment is influenced by the elastic energy anisotropy. The anisotropy in elasticity causes a further elongation of the islands whose coarsening is interrupted due to facets on the surface.
Modeling elastic anisotropy in strained heteroepitaxy.
Dixit, Gopal Krishna; Ranganathan, Madhav
2017-09-20
Using a continuum evolution equation, we model the growth and evolution of quantum dots in the heteroepitaxial Ge on Si(0 0 1) system in a molecular beam epitaxy unit. We formulate our model in terms of evolution due to deposition, and due to surface diffusion which is governed by a free energy. This free energy has contributions from surface energy, curvature, wetting effects and elastic energy due to lattice mismatch between the film and the substrate. In addition to anisotropy due to surface energy which favors facet formation, we also incorporate elastic anisotropy due to an underlying crystal lattice. The complicated elastic problem of the film-substrate system subjected to boundary conditions at the free surface, interface and the bulk substrate is solved by perturbation analysis using a small slope approximation. This permits an analysis of effects at different orders in the slope and sheds new light on the observed behavior. Linear stability analysis shows the early evolution of the instability towards dot formation. The elastic anisotropy causes a change in the alignment of dots in the linear regime, whereas the surface energy anisotropy changes the dot shapes at the nonlinear regime. Numerical simulation of the full nonlinear equations shows the evolution of the surface morphology. In particular, we show, for parameters of the [Formula: see text] [Formula: see text] on Si(0 0 1), the surface energy anisotropy dominates the shapes of the quantum dots, whereas their alignment is influenced by the elastic energy anisotropy. The anisotropy in elasticity causes a further elongation of the islands whose coarsening is interrupted due to [Formula: see text] facets on the surface.
Model predictive control classical, robust and stochastic
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...
Barocas, Victor H; Dorfman, Kevin D; Segal, Yoav
2012-08-01
A model is developed and analyzed for type IV collagen turnover in the kidney glomerular basement membrane (GBM), which is the primary structural element in the glomerular capillary wall. The model incorporates strain dependence in both deposition and removal of the GBM, leading to an equilibrium tissue strain at which deposition and removal are balanced. The GBM thickening decreases tissue strain per unit of transcapillary pressure drop according to the law of Laplace, but increases the transcapillary pressure drop required to maintain glomerular filtration. The model results are in agreement with the observed GBM alterations in Alport syndrome and thin basement membrane disease, and the model-predicted linear relation between the inverse capillary radius and inverse capillary thickness at equilibrium is consistent with published data on different mammals. In addition, the model predicts a minimum achievable strain in the GBM based on the geometry, properties, and mechanical environment; that is, an infinitely thick GBM would still experience a finite strain. Although the model assumptions would be invalid for an extremely thick GBM, the minimum achievable strain could be significant in diseases, such as Alport syndrome, characterized by focal GBM thickening. Finally, an examination of reasonable values for the model parameters suggests that the oncotic pressure drop-the osmotic pressure difference between the plasma and the filtrate due to large molecules-plays an important role in setting the GBM strain and, thus, leakage of protein into the urine may be protective against some GBM damage.
Laschinger, H K; Finegan, J; Shamian, J; Wilk, P
2001-05-01
In this study, we tested an expanded model of Kanter's structural empowerment, which specified the relationships among structural and psychological empowerment, job strain, and work satisfaction. Strategies proposed in Kanter's empowerment theory have the potential to reduce job strain and improve employee work satisfaction and performance in current restructured healthcare settings. The addition to the model of psychological empowerment as an outcome of structural empowerment provides an understanding of the intervening mechanisms between structural work conditions and important organizational outcomes. A predictive, nonexperimental design was used to test the model in a random sample of 404 Canadian staff nurses. The Conditions of Work Effectiveness Questionnaire, the Psychological Empowerment Questionnaire, the Job Content Questionnaire, and the Global Satisfaction Scale were used to measure the major study variables. Structural equation modelling analyses revealed a good fit of the hypothesized model to the data based on various fit indices (chi 2 = 1140, df = 545, chi 2/df ratio = 2.09, CFI = 0.986, RMSEA = 0.050). The amount of variance accounted for in the model was 58%. Staff nurses felt that structural empowerment in their workplace resulted in higher levels of psychological empowerment. These heightened feelings of psychological empowerment in turn strongly influenced job strain and work satisfaction. However, job strain did not have a direct effect on work satisfaction. These results provide initial support for an expanded model of organizational empowerment and offer a broader understanding of the empowerment process.
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...
Garion, C
2001-01-01
The 300-series stainless steels are metastable austenitic alloys: martensitic transformation occurs at low temperatures and/or when plastic strain fields develop in the structures. The transformation influences the mechanical properties of the material. The present note aims at proposing a set of constitutive equations describing the plastic strain induced martensitic transformation in the stainless steels at cryogenic temperatures. The constitutive modelling shall create a bridge between the material sciences and the structural analysis. For the structures developing and accumulating plastic deformations at sub-zero temperatures, it is of primary importance to be able to predict the intensity of martensitic transformation and its effect on the material properties. In particular, the constitutive model has been applied to predict the behaviour of the components of the LHC interconnections, the so-called bellows expansion joints (the LHC mechanical compensation system).
Massive Predictive Modeling using Oracle R Enterprise
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...
A Murine Hypertrophic Cardiomyopathy Model: The DBA/2J Strain.
Directory of Open Access Journals (Sweden)
Wenyuan Zhao
Full Text Available Familial hypertrophic cardiomyopathy (HCM is attributed to mutations in genes that encode for the sarcomere proteins, especially Mybpc3 and Myh7. Genotype-phenotype correlation studies show significant variability in HCM phenotypes among affected individuals with identical causal mutations. Morphological changes and clinical expression of HCM are the result of interactions with modifier genes. With the exceptions of angiotensin converting enzyme, these modifiers have not been identified. Although mouse models have been used to investigate the genetics of many complex diseases, natural murine models for HCM are still lacking. In this study we show that the DBA/2J (D2 strain of mouse has sequence variants in Mybpc3 and Myh7, relative to widely used C57BL/6J (B6 reference strain and the key features of human HCM. Four-month-old of male D2 mice exhibit hallmarks of HCM including increased heart weight and cardiomyocyte size relative to B6 mice, as well as elevated markers for cardiac hypertrophy including β-myosin heavy chain (MHC, atrial natriuretic peptide (ANP, brain natriuretic peptide (BNP, and skeletal muscle alpha actin (α1-actin. Furthermore, cardiac interstitial fibrosis, another feature of HCM, is also evident in the D2 strain, and is accompanied by up-regulation of type I collagen and α-smooth muscle actin (SMA-markers of fibrosis. Of great interest, blood pressure and cardiac function are within the normal range in the D2 strain, demonstrating that cardiac hypertrophy and fibrosis are not secondary to hypertension, myocardial infarction, or heart failure. Because D2 and B6 strains have been used to generate a large family of recombinant inbred strains, the BXD cohort, the D2 model can be effectively exploited for in-depth genetic analysis of HCM susceptibility and modifier screens.
Directory of Open Access Journals (Sweden)
Maria Carolina dos Santos Freitas
2013-04-01
Full Text Available In this work, the formability of a hot-dip galvanized interstitial-free (IF steel sheet was evaluated by means of uniaxial tensile and Forming Limit Curve (FLC tests. The FLC was defined using the flat-bottomed Marciniak's punch technique, where the strain analysis was made using a digital image correlation software. A plastic localization model was also proposed wherein the governing equations are solved with the help of the Newton's method. The investigated hot-dip galvanized IF steel sheet presented a very good formability level in the deep-drawing range consistent with the measured Lankford values. The predicted limit strains were found to be in good agreement with the experimental data of the hot-dip galvanized IF steel sheet owing to the definition of the localization model geometrical imperfection as a function of the experimental surface roughness evolution and, in particular, to the yield surface flattening near to the plane-strain stress state authorized by the adopted yield criterion.
Liver Cancer Risk Prediction Models
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.
Colorectal Cancer Risk Prediction Models
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.
Cervical Cancer Risk Prediction Models
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.
Prostate Cancer Risk Prediction Models
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.
Pancreatic Cancer Risk Prediction Models
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.
Colorectal Cancer Risk Prediction Models
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.
Bladder Cancer Risk Prediction Models
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.
Esophageal Cancer Risk Prediction Models
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.
Lung Cancer Risk Prediction Models
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.
Breast Cancer Risk Prediction Models
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.
Ovarian Cancer Risk Prediction Models
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.
Testicular Cancer Risk Prediction Models
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.
Fourth-order strain-gradient phase mixture model for nanocrystalline fcc materials
Klusemann, Benjamin; Bargmann, Swantje; Estrin, Yuri
2016-12-01
The proposed modeling approach for nanocrystalline materials is an extension of the local phase mixture model introduced by Kim et al (2000 Acta Mater. 48 493-504). Local models cannot account for any non-uniformities or strain patterns, i.e. such models describe the behavior correctly only as long as it is homogeneous. In order to capture heterogeneities, the phase mixture model is augmented with gradient terms of higher order, namely second and fourth order. Different deformation mechanisms are assumed to operate in grain interior and grain boundaries concurrently. The deformation mechanism in grain boundaries is associated with diffusional mass transport along the boundaries, while in the grain interior dislocation glide as well as diffusion controlled mechanisms are considered. In particular, the mechanical response of nanostructured polycrystals is investigated. The model is capable of correctly predicting the transition of flow stress from Hall-Petch behavior in conventional grain size range to an inverse Hall-Petch relation in the nanocrystalline grain size range. The consideration of second- and fourth-order strain gradients allows non-uniformities within the strain field to represent strain patterns in combination with a regularization effect. Details of the numerical implementation are provided.
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...
Posterior Predictive Model Checking in Bayesian Networks
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…
A Course in... Model Predictive Control.
Arkun, Yaman; And Others
1988-01-01
Describes a graduate engineering course which specializes in model predictive control. Lists course outline and scope. Discusses some specific topics and teaching methods. Suggests final projects for the students. (MVL)
Equivalency and unbiasedness of grey prediction models
Institute of Scientific and Technical Information of China (English)
Bo Zeng; Chuan Li; Guo Chen; Xianjun Long
2015-01-01
In order to deeply research the structure discrepancy and modeling mechanism among different grey prediction mo-dels, the equivalence and unbiasedness of grey prediction mo-dels are analyzed and verified. The results show that al the grey prediction models that are strictly derived from x(0)(k) +az(1)(k) = b have the identical model structure and simulation precision. Moreover, the unbiased simulation for the homoge-neous exponential sequence can be accomplished. However, the models derived from dx(1)/dt+ax(1) =b are only close to those derived from x(0)(k)+az(1)(k)=b provided that|a|has to satisfy|a| < 0.1; neither could the unbiased simulation for the homoge-neous exponential sequence be achieved. The above conclusions are proved and verified through some theorems and examples.
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.
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.
Prediction of Sinorhizobium meliloti sRNA genes and experimental detection in strain 2011
Directory of Open Access Journals (Sweden)
Becker Anke
2008-09-01
Full Text Available Abstract Background Small non-coding RNAs (sRNAs have emerged as ubiquitous regulatory elements in bacteria and other life domains. However, few sRNAs have been identified outside several well-studied species of gamma-proteobacteria and thus relatively little is known about the role of RNA-mediated regulation in most other bacterial genera. Here we have conducted a computational prediction of putative sRNA genes in intergenic regions (IgRs of the symbiotic α-proteobacterium S. meliloti 1021 and experimentally confirmed the expression of dozens of these candidate loci in the closely related strain S. meliloti 2011. Results Our first sRNA candidate compilation was based mainly on the output of the sRNAPredictHT algorithm. A thorough manual sequence analysis of the curated list rendered an initial set of 18 IgRs of interest, from which 14 candidates were detected in strain 2011 by Northern blot and/or microarray analysis. Interestingly, the intracellular transcript levels varied in response to various stress conditions. We developed an alternative computational method to more sensitively predict sRNA-encoding genes and score these predicted genes based on several features to allow identification of the strongest candidates. With this novel strategy, we predicted 60 chromosomal independent transcriptional units that, according to our annotation, represent strong candidates for sRNA-encoding genes, including most of the sRNAs experimentally verified in this work and in two other contemporary studies. Additionally, we predicted numerous candidate sRNA genes encoded in megaplasmids pSymA and pSymB. A significant proportion of the chromosomal- and megaplasmid-borne putative sRNA genes were validated by microarray analysis in strain 2011. Conclusion Our data extend the number of experimentally detected S. meliloti sRNAs and significantly expand the list of putative sRNA-encoding IgRs in this and closely related α-proteobacteria. In addition, we have
Hybrid modeling and prediction of dynamical systems
Lloyd, Alun L.; Flores, Kevin B.
2017-01-01
Scientific analysis often relies on the ability to make accurate predictions of a system’s dynamics. Mechanistic models, parameterized by a number of unknown parameters, are often used for this purpose. Accurate estimation of the model state and parameters prior to prediction is necessary, but may be complicated by issues such as noisy data and uncertainty in parameters and initial conditions. At the other end of the spectrum exist nonparametric methods, which rely solely on data to build their predictions. While these nonparametric methods do not require a model of the system, their performance is strongly influenced by the amount and noisiness of the data. In this article, we consider a hybrid approach to modeling and prediction which merges recent advancements in nonparametric analysis with standard parametric methods. The general idea is to replace a subset of a mechanistic model’s equations with their corresponding nonparametric representations, resulting in a hybrid modeling and prediction scheme. Overall, we find that this hybrid approach allows for more robust parameter estimation and improved short-term prediction in situations where there is a large uncertainty in model parameters. We demonstrate these advantages in the classical Lorenz-63 chaotic system and in networks of Hindmarsh-Rose neurons before application to experimentally collected structured population data. PMID:28692642
Risk terrain modeling predicts child maltreatment.
Daley, Dyann; Bachmann, Michael; Bachmann, Brittany A; Pedigo, Christian; Bui, Minh-Thuy; Coffman, Jamye
2016-12-01
As indicated by research on the long-term effects of adverse childhood experiences (ACEs), maltreatment has far-reaching consequences for affected children. Effective prevention measures have been elusive, partly due to difficulty in identifying vulnerable children before they are harmed. This study employs Risk Terrain Modeling (RTM), an analysis of the cumulative effect of environmental factors thought to be conducive for child maltreatment, to create a highly accurate prediction model for future substantiated child maltreatment cases in the City of Fort Worth, Texas. The model is superior to commonly used hotspot predictions and more beneficial in aiding prevention efforts in a number of ways: 1) it identifies the highest risk areas for future instances of child maltreatment with improved precision and accuracy; 2) it aids the prioritization of risk-mitigating efforts by informing about the relative importance of the most significant contributing risk factors; 3) since predictions are modeled as a function of easily obtainable data, practitioners do not have to undergo the difficult process of obtaining official child maltreatment data to apply it; 4) the inclusion of a multitude of environmental risk factors creates a more robust model with higher predictive validity; and, 5) the model does not rely on a retrospective examination of past instances of child maltreatment, but adapts predictions to changing environmental conditions. The present study introduces and examines the predictive power of this new tool to aid prevention efforts seeking to improve the safety, health, and wellbeing of vulnerable children.
Property predictions using microstructural modeling
Energy Technology Data Exchange (ETDEWEB)
Wang, K.G. [Department of Materials Science and Engineering, Rensselaer Polytechnic Institute, CII 9219, 110 8th Street, Troy, NY 12180-3590 (United States)]. E-mail: wangk2@rpi.edu; Guo, Z. [Sente Software Ltd., Surrey Technology Centre, 40 Occam Road, Guildford GU2 7YG (United Kingdom); Sha, W. [Metals Research Group, School of Civil Engineering, Architecture and Planning, The Queen' s University of Belfast, Belfast BT7 1NN (United Kingdom); Glicksman, M.E. [Department of Materials Science and Engineering, Rensselaer Polytechnic Institute, CII 9219, 110 8th Street, Troy, NY 12180-3590 (United States); Rajan, K. [Department of Materials Science and Engineering, Rensselaer Polytechnic Institute, CII 9219, 110 8th Street, Troy, NY 12180-3590 (United States)
2005-07-15
Precipitation hardening in an Fe-12Ni-6Mn maraging steel during overaging is quantified. First, applying our recent kinetic model of coarsening [Phys. Rev. E, 69 (2004) 061507], and incorporating the Ashby-Orowan relationship, we link quantifiable aspects of the microstructures of these steels to their mechanical properties, including especially the hardness. Specifically, hardness measurements allow calculation of the precipitate size as a function of time and temperature through the Ashby-Orowan relationship. Second, calculated precipitate sizes and thermodynamic data determined with Thermo-Calc[copyright] are used with our recent kinetic coarsening model to extract diffusion coefficients during overaging from hardness measurements. Finally, employing more accurate diffusion parameters, we determined the hardness of these alloys independently from theory, and found agreement with experimental hardness data. Diffusion coefficients determined during overaging of these steels are notably higher than those found during the aging - an observation suggesting that precipitate growth during aging and precipitate coarsening during overaging are not controlled by the same diffusion mechanism.
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.
Modeling Strain Rate Effect for Heterogeneous Brittle Materials
Institute of Scientific and Technical Information of China (English)
MA Guowei; DONG Aiai; LI Jianchun
2006-01-01
Rocks are heterogeneous from the point of microstructure which is of significance to their dynamic failure behavior.Both the compressive and tensile strength of rock-like materials is regarded different from the static strength.The present study adopts smoothed particle hydrodynamics (SPH) which is a virtual particle based meshfree method to investigate strain rate effect for heterogeneous brittle materials.The SPH method is capable of simulating rock fracture,free of the mesh constraint of the traditional FEM and FDM models.A pressure dependent J-H constitutive model involving heterogeneity is employed in the numerical modeling.The results show the compressive strength increases with the increase of strain rate as well as the tensile strength,which is important to the engineering design.
Evaluation of creep-fatigue life-prediction models for the solar central receiver
Hyzak, J. M.; Hughes, D. A.
1981-09-01
The applicability of several creep fatigue models to life prediction of boiler tubes in a solar central receiver (SCR) was evaluated. The SCR boiler tubes will experience compressive strain dwell loading with hold times up to 6 to 8 hours at temperatures where time dependent deformation will occur. The evaluation criteria include the ability of the model to account for mean stress effects and to be practical in the long life, small strain range regime. A correlation between maximum tensile stress and fatigue life is presented. Using this correlation, compressive dwell behavior is predicted based on continuous cycling data. The limits of this predictive scheme are addressed.
Institute of Scientific and Technical Information of China (English)
吴志荣; 胡绪腾; 宋迎东
2013-01-01
工程中的大多构件承受着复杂的载荷形式,将单轴疲劳模型应用到多轴载荷情况已不能满足工程精度的要求,多轴载荷下的疲劳寿命计算日益引起人们的重视.基于临界平面的思想,结合Fatemi-Socie(FS)模型和Smith-Watson-Topper(SWT)参数各自的优点,提出一种新的多轴疲劳寿命预测模型.该模型以最大切应变幅与最大切应变幅平面上修正SWT参数的和作为多轴疲劳损伤控制参量,此参量可以同时考虑非比例附加循环硬化和平均应力对材料多轴疲劳寿命的影响,能同时适用于比例和非比例加载下的多轴疲劳问题.采用纯钛Ti、BT9钛合金、304不锈钢、S45C钢和1045HR钢5种材料多轴疲劳试验数据对提出的模型进行评估和验证,对几种材料比例和非比例加载下的多轴疲劳寿命预测结果大都分布在试验结果的2倍分散带之内,结果表明提出的多轴疲劳寿命模型具有较高的预测精度.%The most components of engineering structures are usually subjected to a complex loading. It is unable to meet the requirements of engineering precision if a uniaxial fatigue model is used under multi-axial loading. The calculation of fatigue life prediction under multiaxial loading causes people's attention more and more. A new multiaxial fatigue life prediction model is proposed based on the critical plane criteria. The model integrates the respective advantages of Fatemi-Socie(FS) model and Smith-Watson-Topper(SWT) parameter. The damage parameter in this model takes the sum of the maximum shear strain amplitude and the modified SWT parameter on the maximum shear strain amplitude plain. It can consider the effects of additional cyclic hardening due to non-proportional loading and mean stress on the multi-axial fatigue life of material. The proposed model can be applied to proportional and non-proportional loading. The model is evaluated by the multiaxial fatigue test data of pure titanium, BT9
Energy Technology Data Exchange (ETDEWEB)
Yu, Xinghua [ORNL; Wang, Yanli [ORNL; Crooker, Paul [Electric Power Research Institute (EPRI); Feng, Zhili [ORNL
2015-01-01
Weld residual stress is one of the primary driving forces for primary water stress corrosion cracking in dissimilar metal welds (DMWs). To mitigate tensile residual stress in DMWs, it is critical to understand residual stress distribution by modeling techniques. Recent studies have shown that weld residual stress prediction using today s DMW residual stress models strongly depends on the strain-hardening constitutive model chosen. The commonly used strain-hardening models (isotropic, kinematic, and mixed) are all time-independent and inadequate to account for the time-dependent (viscous) plastic deformation at the elevated temperatures experienced during welding. For materials with profound strain-hardening, such as stainless steels and nickel-based alloys that are widely used in nuclear reactor and piping systems, the equivalent plastic strain the determinate factor of the flow stress can be highly dependent on the recovery and recrystallization processes. These processes are in turn a strong function of temperature, time, and deformation rate. Recently, the authors proposed a new temperature- and time-dependent strain-hardening constitutive model: the dynamic strain-hardening constitutive model. The application of such a model has resulted in improved weld residual stress prediction compared to the residual stress measurement results from the contour and deep-hole drilling methods. In this study, the dynamic strain-hardening behavior of Type 304 stainless steel and Alloy 82 used in pressure vessel nozzle DMWs is experimentally determined. The kinetics of the recovery and recrystallization of flow stress are derived from experiments, resulting in a semi-empirical equation as a function of pre-strain, time, and temperature that can be used for weld residual stress modeling. The method used in this work also provides an approach to study the kinetics of recovery and recrystallization of other materials with significant strain-hardening.
Modeling and Prediction Using Stochastic Differential Equations
DEFF Research Database (Denmark)
Juhl, Rune; Møller, Jan Kloppenborg; Jørgensen, John Bagterp
2016-01-01
Pharmacokinetic/pharmakodynamic (PK/PD) modeling for a single subject is most often performed using nonlinear models based on deterministic ordinary differential equations (ODEs), and the variation between subjects in a population of subjects is described using a population (mixed effects) setup...... 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...... 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...
Precision Plate Plan View Pattern Predictive Model
Institute of Scientific and Technical Information of China (English)
ZHAO Yang; YANG Quan; HE An-rui; WANG Xiao-chen; ZHANG Yun
2011-01-01
According to the rolling features of plate mill, a 3D elastic-plastic FEM （finite element model） based on full restart method of ANSYS/LS-DYNA was established to study the inhomogeneous plastic deformation of multipass plate rolling. By analyzing the simulation results, the difference of head and tail ends predictive models was found and modified. According to the numerical simulation results of 120 different kinds of conditions, precision plate plan view pattern predictive model was established. Based on these models, the sizing MAS （mizushima automatic plan view pattern control system） method was designed and used on a 2 800 mm plate mill. Comparing the rolled plates with and without PVPP （plan view pattern predictive） model, the reduced width deviation indicates that the olate !olan view Dattern predictive model is preeise.
NBC Hazard Prediction Model Capability Analysis
1999-09-01
Puff( SCIPUFF ) Model Verification and Evaluation Study, Air Resources Laboratory, NOAA, May 1998. Based on the NOAA review, the VLSTRACK developers...TO SUBSTANTIAL DIFFERENCES IN PREDICTIONS HPAC uses a transport and dispersion (T&D) model called SCIPUFF and an associated mean wind field model... SCIPUFF is a model for atmospheric dispersion that uses the Gaussian puff method - an arbitrary time-dependent concentration field is represented
Goldberg, Robert K.; Stouffer, Donald C.
1998-01-01
Recently applications have exposed polymer matrix composite materials to very high strain rate loading conditions, requiring an ability to understand and predict the material behavior under these extreme conditions. In this first paper of a two part report, background information is presented, along with the constitutive equations which will be used to model the rate dependent nonlinear deformation response of the polymer matrix. Strain rate dependent inelastic constitutive models which were originally developed to model the viscoplastic deformation of metals have been adapted to model the nonlinear viscoelastic deformation of polymers. The modified equations were correlated by analyzing the tensile/ compressive response of both 977-2 toughened epoxy matrix and PEEK thermoplastic matrix over a variety of strain rates. For the cases examined, the modified constitutive equations appear to do an adequate job of modeling the polymer deformation response. A second follow-up paper will describe the implementation of the polymer deformation model into a composite micromechanical model, to allow for the modeling of the nonlinear, rate dependent deformation response of polymer matrix composites.
Yang, Lin; Ding, He; Zhang, Xin; Qiao, Li
2017-03-01
A semi-analytical modeling framework on the microscopic basis is proposed in this paper to predict the low-temperature transport properties of strained Nb3Sn superconductors. The theoretical predictions agree well with experimental observations, which indicate that the competitions between the strain state-dependent variations in the phonon spectrum and the electron density of states (DOS) are an important consideration in interpreting the coupled low temperature-strain sensitivity of resistivity in superconducting Nb3Sn. The model is helpful for identifying the scaling law describing the anomalies in the strain dependence of superconducting critical properties of Nb3Sn conductors.
Two Strain Dengue Model with Temporary Cross Immunity and Seasonality
Aguiar, Maíra; Ballesteros, Sebastien; Stollenwerk, Nico
2010-09-01
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.
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...
Constitutive modeling of shape memory alloys at finite strain
Energy Technology Data Exchange (ETDEWEB)
Pethoe, A. [Technical Univ. Budapest (Hungary). Dept. of Applied Mechanics
2001-07-01
A new model which is able to reproduce the basic responses of shape memory materials on both micro- and macrostructural aspects is presented. The model is based on a local finite strain continuum description and uses a multiplicative decomposition of the total deformation gradient which involves elastic, plastic and microstructurally given phase transitional parts. For the elastic behavior of the material a coupled hyper-hypoelastic model is used based on a recently developed logarithmic rate. A complex constitutive equation is presented which consists of the kinetics of phase change process given by thermodynamical basis. Finally a simple one dimensional example is also shown. (orig.)
Formability prediction for AHSS materials using damage models
Amaral, R.; Santos, Abel D.; José, César de Sá; Miranda, Sara
2017-05-01
Advanced high strength steels (AHSS) are seeing an increased use, mostly due to lightweight design in automobile industry and strict regulations on safety and greenhouse gases emissions. However, the use of these materials, characterized by a high strength to weight ratio, stiffness and high work hardening at early stages of plastic deformation, have imposed many challenges in sheet metal industry, mainly their low formability and different behaviour, when compared to traditional steels, which may represent a defying task, both to obtain a successful component and also when using numerical simulation to predict material behaviour and its fracture limits. Although numerical prediction of critical strains in sheet metal forming processes is still very often based on the classic forming limit diagrams, alternative approaches can use damage models, which are based on stress states to predict failure during the forming process and they can be classified as empirical, physics based and phenomenological models. In the present paper a comparative analysis of different ductile damage models is carried out, in order numerically evaluate two isotropic coupled damage models proposed by Johnson-Cook and Gurson-Tvergaard-Needleman (GTN), each of them corresponding to the first two previous group classification. Finite element analysis is used considering these damage mechanics approaches and the obtained results are compared with experimental Nakajima tests, thus being possible to evaluate and validate the ability to predict damage and formability limits for previous defined approaches.
Corporate prediction models, ratios or regression analysis?
Bijnen, E.J.; Wijn, M.F.C.M.
1994-01-01
The models developed in the literature with respect to the prediction of a company s failure are based on ratios. It has been shown before that these models should be rejected on theoretical grounds. Our study of industrial companies in the Netherlands shows that the ratios which are used in
Modelling Chemical Reasoning to Predict Reactions
Segler, Marwin H S
2016-01-01
The ability to reason beyond established knowledge allows Organic Chemists to solve synthetic problems and to invent novel transformations. Here, we propose a model which mimics chemical reasoning and formalises reaction prediction as finding missing links in a knowledge graph. We have constructed a knowledge graph containing 14.4 million molecules and 8.2 million binary reactions, which represents the bulk of all chemical reactions ever published in the scientific literature. Our model outperforms a rule-based expert system in the reaction prediction task for 180,000 randomly selected binary reactions. We show that our data-driven model generalises even beyond known reaction types, and is thus capable of effectively (re-) discovering novel transformations (even including transition-metal catalysed reactions). Our model enables computers to infer hypotheses about reactivity and reactions by only considering the intrinsic local structure of the graph, and because each single reaction prediction is typically ac...
A phase-field model for ductile fracture at finite strains and its experimental verification
Ambati, Marreddy; Kruse, Roland; De Lorenzis, Laura
2016-01-01
In this paper, a phase-field model for ductile fracture previously proposed in the kinematically linear regime is extended to the three-dimensional finite strain setting, and its predictions are qualitatively and quantitatively compared with several experimental results, both from ad-hoc tests carried out by the authors and from the available literature. The proposed model is based on the physical assumption that fracture occurs when a scalar measure of the accumulated plastic strain reaches a critical value, and such assumption is introduced through the dependency of the phase-field degradation function on this scalar measure. The proposed model is able to capture the experimentally observed sequence of elasto-plastic deformation, necking and fracture phenomena in flat specimens; the occurrence of cup-and-cone fracture patterns in axisymmetric specimens; the role played by notches and by their size on the measured displacement at fracture; and the sequence of distinct cracking events observed in more complex specimens.
Modeling and strain gauging of eddy current repulsion deicing systems
Smith, Samuel O.
1993-01-01
Work described in this paper confirms and extends work done by Zumwalt, et al., on a variety of in-flight deicing systems that use eddy current repulsion for repelling ice. Two such systems are known as electro-impulse deicing (EIDI) and the eddy current repulsion deicing strip (EDS). Mathematical models for these systems are discussed for their capabilities and limitations. The author duplicates a particular model of the EDS. Theoretical voltage, current, and force results are compared directly to experimental results. Dynamic strain measurements results are presented for the EDS system. Dynamic strain measurements near EDS or EIDI coils are complicated by the high magnetic fields in the vicinity of the coils. High magnetic fields induce false voltage signals out of the gages.
Tracking Strains in the Microbiome: Insights from Metagenomics and Models.
Brito, Ilana L; Alm, Eric J
2016-01-01
Transmission usually refers to the movement of pathogenic organisms. Yet, commensal microbes that inhabit the human body also move between individuals and environments. Surprisingly little is known about the transmission of these endogenous microbes, despite increasing realizations of their importance for human health. The health impacts arising from the transmission of commensal bacteria range widely, from the prevention of autoimmune disorders to the spread of antibiotic resistance genes. Despite this importance, there are outstanding basic questions: what is the fraction of the microbiome that is transmissible? What are the primary mechanisms of transmission? Which organisms are the most highly transmissible? Higher resolution genomic data is required to accurately link microbial sources (such as environmental reservoirs or other individuals) with sinks (such as a single person's microbiome). New computational advances enable strain-level resolution of organisms from shotgun metagenomic data, allowing the transmission of strains to be followed over time and after discrete exposure events. Here, we highlight the latest techniques that reveal strain-level resolution from raw metagenomic reads and new studies that are tracking strains across people and environments. We also propose how models of pathogenic transmission may be applied to study the movement of commensals between microbial communities.
Evaluation of CASP8 model quality predictions
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.
Xia, Mingjun; Ghafouri-Shiraz, H
2016-03-01
This paper reports a new model for strained quantum well lasers, which are based on the quantum well transmission line modeling method where effects of both carrier transport and carrier heating have been included. We have applied this new model and studied the effect of carrier transport on the output waveform of a strained quantum well laser both in time and frequency domains. It has been found that the carrier transport increases the turn-on, turn-off delay times and damping of the quantum well laser transient response. Also, analysis in the frequency domain indicates that the carrier transport causes the output spectrum of the quantum well laser in steady state to exhibit a redshift which has a narrower bandwidth and lower magnitude. The simulation results of turning-on transients obtained by the proposed model are compared with those obtained by the rate equation laser model. The new model has also been used to study the effects of pump current spikes on the laser output waveforms properties, and it was found that the presence of current spikes causes (i) wavelength blueshift, (ii) larger bandwidth, and (iii) reduces the magnitude and decreases the side-lobe suppression ratio of the laser output spectrum. Analysis in both frequency and time domains confirms that the new proposed model can accurately predict the temporal and spectral behaviors of strained quantum well lasers.
Genetic models of homosexuality: generating testable predictions
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 inclu...
Identification of Strain-Softening Properties and Computational Predictions of Localized Fracture.
1984-03-01
OFFICE SYMBOL I de .4 a Code) LAWRENCE D. HOKANSON, Lt. Col. USAF (202) 767-4935 AFOSR/NA DO FORM 1473, 83 APR EDITION OF I JAN 73 IS OBSOLETE...crack band approach of Bazant and co-wor- kers [9] who interpreted the fictitious crack model of Hillerborg et al [10] within a crack band of finite...shear bands within linear bifurcation studies [13], [14]. In fact, Bazant offered some elementary strain-softening interpretation of concrete in
Wind farm production prediction - The Zephyr model
Energy Technology Data Exchange (ETDEWEB)
Landberg, L. [Risoe National Lab., Wind Energy Dept., Roskilde (Denmark); Giebel, G. [Risoe National Lab., Wind Energy Dept., Roskilde (Denmark); Madsen, H. [IMM (DTU), Kgs. Lyngby (Denmark); Nielsen, T.S. [IMM (DTU), Kgs. Lyngby (Denmark); Joergensen, J.U. [Danish Meteorologisk Inst., Copenhagen (Denmark); Lauersen, L. [Danish Meteorologisk Inst., Copenhagen (Denmark); Toefting, J. [Elsam, Fredericia (DK); Christensen, H.S. [Eltra, Fredericia (Denmark); Bjerge, C. [SEAS, Haslev (Denmark)
2002-06-01
This report describes a project - funded by the Danish Ministry of Energy and the Environment - which developed a next generation prediction system called Zephyr. The Zephyr system is a merging between two state-of-the-art prediction systems: Prediktor of Risoe National Laboratory and WPPT of IMM at the Danish Technical University. The numerical weather predictions were generated by DMI's HIRLAM model. Due to technical difficulties programming the system, only the computational core and a very simple version of the originally very complex system were developed. The project partners were: Risoe, DMU, DMI, Elsam, Eltra, Elkraft System, SEAS and E2. (au)
Ko, William L.; Fleischer, Van Tran
2015-01-01
Variable-Domain Displacement Transfer Functions were formulated for shape predictions of complex wing structures, for which surface strain-sensing stations must be properly distributed to avoid jointed junctures, and must be increased in the high strain gradient region. Each embedded beam (depth-wise cross section of structure along a surface strain-sensing line) was discretized into small variable domains. Thus, the surface strain distribution can be described with a piecewise linear or a piecewise nonlinear function. Through discretization, the embedded beam curvature equation can be piece-wisely integrated to obtain the Variable-Domain Displacement Transfer Functions (for each embedded beam), which are expressed in terms of geometrical parameters of the embedded beam and the surface strains along the strain-sensing line. By inputting the surface strain data into the Displacement Transfer Functions, slopes and deflections along each embedded beam can be calculated for mapping out overall structural deformed shapes. A long tapered cantilever tubular beam was chosen for shape prediction analysis. The input surface strains were analytically generated from finite-element analysis. The shape prediction accuracies of the Variable- Domain Displacement Transfer Functions were then determined in light of the finite-element generated slopes and deflections, and were fofound to be comparable to the accuracies of the constant-domain Displacement Transfer Functions
A Simple Model for Yielding and Strain Hardening in Glassy Polymers
Larson, Ron
2013-03-01
Strain hardening has long been an observed feature of polymer glasses in extension; explanations to date have often been phenomenological. Ediger and coworkers (Lee et al. Science 323, 231, 2009) have shown in experiments on PMMA glasses that, in addition to strain hardening, polymeric glasses show a remarkable non-monotonicity in the segmental relaxation time both in loading and unloading of stress. Here, we develop a simple constitutive equation that combines recent theories for yielding in simple glasses (Brader et al. PNAS, 106, 15186, 2009) to represent local segmental modes in the polymer, with a dumbbell model for the slow polymer relaxation modes. For a polymer glass under uniaxial loading, the model predicts that the liquefaction of the segmental modes permits strain hardening of the polymer modes to emerge, and once this emerges, it slows the deformation of the material under constant load enough to partially re-vitrify the segmental modes even though the sample remains under stress. In this way, the observed non-monotonicity in the segmental relaxation modes is produced. We show the extension of the work to simple shearing flows, and make (as yet) untested predictions about segmental relaxation rates in shear flows. We also show how to extend the model to include Rouse chain dynamics in place of the over-simplified dumbbell.
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.
Transferable tight binding model for strained group IV and III-V heterostructures
Tan, Yaohua; Povolotskyi, Micheal; Kubis, Tillmann; Boykin, Timothy; Klimeck, Gerhard
Modern semiconductor devices have reached critical device dimensions in the range of several nanometers. For reliable prediction of device performance, it is critical to have a numerical efficient model that are transferable to material interfaces. In this work, we present an empirical tight binding (ETB) model with transferable parameters for strained IV and III-V group semiconductors. The ETB model is numerically highly efficient as it make use of an orthogonal sp3d5s* basis set with nearest neighbor inter-atomic interactions. The ETB parameters are generated from HSE06 hybrid functional calculations. Band structures of strained group IV and III-V materials by ETB model are in good agreement with corresponding HSE06 calculations. Furthermore, the ETB model is applied to strained superlattices which consist of group IV and III-V elements. The ETB model turns out to be transferable to nano-scale hetero-structure. The ETB band structures agree with the corresponding HSE06 results in the whole Brillouin zone. The ETB band gaps of superlattices with common cations or common anions have discrepancies within 0.05eV.
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.
Predictive QSAR modeling of phosphodiesterase 4 inhibitors.
Kovalishyn, Vasyl; Tanchuk, Vsevolod; Charochkina, Larisa; Semenuta, Ivan; Prokopenko, Volodymyr
2012-02-01
A series of diverse organic compounds, phosphodiesterase type 4 (PDE-4) inhibitors, have been modeled using a QSAR-based approach. 48 QSAR models were compared by following the same procedure with different combinations of descriptors and machine learning methods. QSAR methodologies used random forests and associative neural networks. The predictive ability of the models was tested through leave-one-out cross-validation, giving a Q² = 0.66-0.78 for regression models and total accuracies Ac=0.85-0.91 for classification models. Predictions for the external evaluation sets obtained accuracies in the range of 0.82-0.88 (for active/inactive classifications) and Q² = 0.62-0.76 for regressions. The method showed itself to be a potential tool for estimation of IC₅₀ of new drug-like candidates at early stages of drug development. Copyright © 2011 Elsevier Inc. All rights reserved.
Energy Technology Data Exchange (ETDEWEB)
Christ, H J [Institut fuer Werkstofftechnik, Universitaet Siegen, D-57068 Siegen (Germany); Bauer, V, E-mail: hans-juergen.christ@uni-siegen.d [Wieland Werke AG, Graf-Arco Str. 36, D-89072 Ulm (Germany)
2010-07-01
The cyclic stress-strain behaviour of metals and alloys in cyclic saturation can reasonably be described by means of simple multi-component models, such as the model based on a parallel arrangement of elastic-perfectly plastic elements, which was originally proposed by Masing already in 1923. This model concept was applied to thermomechanical fatigue loading of two metallic engineering materials which were found to be rather oppositional with respect to cyclic plastic deformation. One material is an austenitic stainless steel of type AISI304L which shows dynamic strain aging (DSA) and serves as an example for a rather ductile alloy. A dislocation arrangement was found after TMF testing deviating characteristically from the corresponding isothermal microstructures. The second material is a third-generation near-gamma TiAl alloy which is characterized by a very pronounced ductile-to-brittle transition (DBT) within the temperature range of TMF cycling. Isothermal fatigue testing at temperatures below the DBT temperature leads to cyclic hardening, while cyclic softening was found to occur above DBT. The combined effect under TMF leads to a continuously developing mean stress. The experimental observations regarding isothermal and non-isothermal stress-strain behaviour and the correlation to the underlying microstructural processes was used to further develop the TMF multi-composite model in order to accurately predict the TMF stress-strain response by taking the alloy-specific features into account.
Wang, Qinghua; Ri, Shien; Tsuda, Hiroshi; Koyama, Motomichi; Tsuzaki, Kaneaki
2017-06-12
Aimed at the low accuracy problem of shear strain measurement in Moiré methods, a two-dimensional (2D) Moiré phase analysis method is proposed for full-field deformation measurement with high accuracy. A grid image is first processed by the spatial phase-shifting sampling Moiré technique to get the Moiré phases in two directions, which are then conjointly analyzed for measuring 2D displacement and strain distributions. The strain especially the shear strain measurement accuracy is remarkably improved, and dynamic deformation is measurable from automatic batch processing of single-shot grid images. As an application, the 2D microscale strain distributions of a titanium alloy were measured, and the crack occurrence location was successfully predicted from strain concentration.
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.
Modelling the predictive performance of credit scoring
Directory of Open Access Journals (Sweden)
Shi-Wei Shen
2013-02-01
Full Text Available Orientation: The article discussed the importance of rigour in credit risk assessment.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.
Calibrated predictions for multivariate competing risks models.
Gorfine, Malka; Hsu, Li; Zucker, David M; Parmigiani, Giovanni
2014-04-01
Prediction models for time-to-event data play a prominent role in assessing the individual risk of a disease, such as cancer. Accurate disease prediction models provide an efficient tool for identifying individuals at high risk, and provide the groundwork for estimating the population burden and cost of disease and for developing patient care guidelines. We focus on risk prediction of a disease in which family history is an important risk factor that reflects inherited genetic susceptibility, shared environment, and common behavior patterns. In this work family history is accommodated using frailty models, with the main novel feature being allowing for competing risks, such as other diseases or mortality. We show through a simulation study that naively treating competing risks as independent right censoring events results in non-calibrated predictions, with the expected number of events overestimated. Discrimination performance is not affected by ignoring competing risks. Our proposed prediction methodologies correctly account for competing events, are very well calibrated, and easy to implement.
Lagrangian and Eulerian biventricular strains from anatomical NURBS models using tagged MRI
Tustison, Nicholas J.; Amini, Amir A.
2005-04-01
We present current research in which both left and right ventricular deformation is estimated from tagged cardiac magnetic resonance imaging using volumetric deformable models constructed from nonuniform rational B-splines (NURBS). The four model types considered include Cartesian-based NURBS models with both a cylindrical and prolate-spheroidal parameterization, prolate spheroidal-based NURBS models with a prolate-spheroidal parameterization, and cylindrical-based NURBS models with a cylindrical parameterization. For each frame subsequent to end-diastole, a NURBS model is constructed by fitting two surfaces with the same parameterization to the corresponding set of epicardial and endocardial contours from which a volumetric model is created. Using normal displacements of the three sets of orthogonal tag planes as well as displacements of contour/tag line intersection points and tag plane intersection points, one can solve for the optimal homogeneous coordinates, in a weighted least squares sense, of the control points of the deformed NURBS model at end-diastole using quadratic programming. This allows for subsequent forward displacement fitting from end-diastole to all later time frames. After fitting to all time points of data, lofting the NURBS model at each time point creates a comprehensive 4-D NURBS model. From this model, we can extract 3-D myocardial deformation fields and corresponding strain maps which are local measures of non-rigid deformation. The results show that, in the case of simulated data, the quadratic Cartesian-based NURBS model outperformed its counterparts in predicting normal strain. This model was used to then calculate normal Lagrangian and Eulerian strains in canine data.
Modelling language evolution: Examples and predictions.
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.
Modelling language evolution: Examples and predictions
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.
Global Solar Dynamo Models: Simulations and Predictions
Indian Academy of Sciences (India)
Mausumi Dikpati; Peter A. Gilman
2008-03-01
Flux-transport type solar dynamos have achieved considerable success in correctly simulating many solar cycle features, and are now being used for prediction of solar cycle timing and amplitude.We first define flux-transport dynamos and demonstrate how they work. The essential added ingredient in this class of models is meridional circulation, which governs the dynamo period and also plays a crucial role in determining the Sun’s memory about its past magnetic fields.We show that flux-transport dynamo models can explain many key features of solar cycles. Then we show that a predictive tool can be built from this class of dynamo that can be used to predict mean solar cycle features by assimilating magnetic field data from previous cycles.
Constitutive modeling and computational implementation for finite strain plasticity
Reed, K. W.; Atluri, S. N.
1985-01-01
This paper describes a simple alternate approach to the difficult problem of modeling material behavior. Starting from a general representation for a rate-tpe constitutive equation, it is shown by example how sets of test data may be used to derive restrictions on the scalar functions appearing in the representation. It is not possible to determine these functions from experimental data, but the aforementioned restrictions serve as a guide in their eventual definition. The implications are examined for hypo-elastic, isotropically hardening plastic, and kinematically hardening plastic materials. A simple model for the evolution of the 'back-stress,' in a kinematic-hardening plasticity theory, that is entirely analogous to a hypoelastic stress-strain relation is postulated and examined in detail in modeling finitely plastic tension-torsion test. The implementation of rate-type material models in finite element algorithms is also discussed.
Model Predictive Control of Sewer Networks
Pedersen, Einar B.; Herbertsson, Hannes R.; Niemann, Henrik; Poulsen, Niels K.; Falk, Anne K. V.
2017-01-01
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 controlled have thus become essential factors for effcient 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 benchmark model. Due to the inherent constraints the applied approach is based on Model Predictive Control.
Strain Rate Dependant Material Model for Orthotropic Metals
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
DKIST Polarization Modeling and Performance Predictions
Harrington, David
2016-05-01
Calibrating the Mueller matrices of large aperture telescopes and associated coude instrumentation requires astronomical sources and several modeling assumptions to predict the behavior of the system polarization with field of view, altitude, azimuth and wavelength. The Daniel K Inouye Solar Telescope (DKIST) polarimetric instrumentation requires very high accuracy calibration of a complex coude path with an off-axis f/2 primary mirror, time dependent optical configurations and substantial field of view. Polarization predictions across a diversity of optical configurations, tracking scenarios, slit geometries and vendor coating formulations are critical to both construction and contined operations efforts. Recent daytime sky based polarization calibrations of the 4m AEOS telescope and HiVIS spectropolarimeter on Haleakala have provided system Mueller matrices over full telescope articulation for a 15-reflection coude system. AEOS and HiVIS are a DKIST analog with a many-fold coude optical feed and similar mirror coatings creating 100% polarization cross-talk with altitude, azimuth and wavelength. Polarization modeling predictions using Zemax have successfully matched the altitude-azimuth-wavelength dependence on HiVIS with the few percent amplitude limitations of several instrument artifacts. Polarization predictions for coude beam paths depend greatly on modeling the angle-of-incidence dependences in powered optics and the mirror coating formulations. A 6 month HiVIS daytime sky calibration plan has been analyzed for accuracy under a wide range of sky conditions and data analysis algorithms. Predictions of polarimetric performance for the DKIST first-light instrumentation suite have been created under a range of configurations. These new modeling tools and polarization predictions have substantial impact for the design, fabrication and calibration process in the presence of manufacturing issues, science use-case requirements and ultimate system calibration
Directory of Open Access Journals (Sweden)
Alex Elías-Zúñiga
2013-01-01
Full Text Available This work focuses on the formulation of a constitutive equation to predict Mullins and residual strain effects of buna-N, silicone, and neoprene rubber strings subjected to small transverse vibrations. The nonmonotone behavior exhibited by experimental data is captured by the proposed material model through the inclusion of a phenomenological non-monotonous softening function that depends on the strain intensity between loading and unloading cycles. It is shown that theoretical predictions compare well with uniaxial experimental data collected from transverse vibration tests.
Modelling Chemical Reasoning to Predict Reactions
Segler, Marwin H. S.; Waller, Mark P.
2016-01-01
The ability to reason beyond established knowledge allows Organic Chemists to solve synthetic problems and to invent novel transformations. Here, we propose a model which mimics chemical reasoning and formalises reaction prediction as finding missing links in a knowledge graph. We have constructed a knowledge graph containing 14.4 million molecules and 8.2 million binary reactions, which represents the bulk of all chemical reactions ever published in the scientific literature. Our model outpe...
Predictive Modeling of the CDRA 4BMS
Coker, Robert; Knox, James
2016-01-01
Fully predictive models of the Four Bed Molecular Sieve of the Carbon Dioxide Removal Assembly on the International Space Station 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.
Raman Model Predicting Hardness of Covalent Crystals
Zhou, Xiang-Feng; Qian, Quang-Rui; Sun, Jian; Tian, Yongjun; Wang, Hui-Tian
2009-01-01
Based on the fact that both hardness and vibrational Raman spectrum depend on the intrinsic property of chemical bonds, we propose a new theoretical model for predicting hardness of a covalent crystal. The quantitative relationship between hardness and vibrational Raman frequencies deduced from the typical zincblende covalent crystals is validated to be also applicable for the complex multicomponent crystals. This model enables us to nondestructively and indirectly characterize the hardness o...
Predictive Modelling of Mycotoxins in Cereals
Fels, van der H.J.; Liu, C.
2015-01-01
In dit artikel worden de samenvattingen van de presentaties tijdens de 30e bijeenkomst van de Werkgroep Fusarium weergegeven. De onderwerpen zijn: Predictive Modelling of Mycotoxins in Cereals.; Microbial degradation of DON.; Exposure to green leaf volatiles primes wheat against FHB but boosts
Unreachable Setpoints in Model Predictive Control
DEFF Research Database (Denmark)
Rawlings, James B.; Bonné, Dennis; Jørgensen, John Bagterp
2008-01-01
steady state is established for terminal constraint model predictive control (MPC). The region of attraction is the steerable set. Existing analysis methods for closed-loop properties of MPC are not applicable to this new formulation, and a new analysis method is developed. It is shown how to extend...
Predictive Modelling of Mycotoxins in Cereals
Fels, van der H.J.; Liu, C.
2015-01-01
In dit artikel worden de samenvattingen van de presentaties tijdens de 30e bijeenkomst van de Werkgroep Fusarium weergegeven. De onderwerpen zijn: Predictive Modelling of Mycotoxins in Cereals.; Microbial degradation of DON.; Exposure to green leaf volatiles primes wheat against FHB but boosts produ
Prediction modelling for population conviction data
Tollenaar, N.
2017-01-01
In this thesis, the possibilities of using prediction models for judicial penal case data are investigated. The development and refinement of a risk taxation scale based on these data is discussed. When false positives are weighted equally severe as false negatives, 70% can be classified correctly.
A Predictive Model for MSSW Student Success
Napier, Angela Michele
2011-01-01
This study tested a hypothetical model for predicting both graduate GPA and graduation of University of Louisville Kent School of Social Work Master of Science in Social Work (MSSW) students entering the program during the 2001-2005 school years. The preexisting characteristics of demographics, academic preparedness and culture shock along with…
Predictability of extreme values in geophysical models
Sterk, A.E.; Holland, M.P.; Rabassa, P.; Broer, H.W.; Vitolo, R.
2012-01-01
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 model
A revised prediction model for natural conception
Bensdorp, A.J.; Steeg, J.W. van der; Steures, P.; Habbema, J.D.; Hompes, P.G.; Bossuyt, P.M.; Veen, F. van der; Mol, B.W.; Eijkemans, M.J.; Kremer, J.A.M.; et al.,
2017-01-01
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
Distributed Model Predictive Control via Dual Decomposition
DEFF Research Database (Denmark)
Biegel, Benjamin; Stoustrup, Jakob; Andersen, Palle
2014-01-01
This chapter presents dual decomposition as a means to coordinate a number of subsystems coupled by state and input constraints. Each subsystem is equipped with a local model predictive controller while a centralized entity manages the subsystems via prices associated with the coupling constraints...
Predictive Modelling of Mycotoxins in Cereals
Fels, van der H.J.; Liu, C.
2015-01-01
In dit artikel worden de samenvattingen van de presentaties tijdens de 30e bijeenkomst van de Werkgroep Fusarium weergegeven. De onderwerpen zijn: Predictive Modelling of Mycotoxins in Cereals.; Microbial degradation of DON.; Exposure to green leaf volatiles primes wheat against FHB but boosts produ
Leptogenesis in minimal predictive seesaw models
Björkeroth, Fredrik; Varzielas, Ivo de Medeiros; King, Stephen F
2015-01-01
We estimate the Baryon Asymmetry of the Universe (BAU) arising from leptogenesis within a class of minimal predictive seesaw models involving two right-handed neutrinos and simple Yukawa structures with one texture zero. The two right-handed neutrinos are dominantly responsible for the "atmospheric" and "solar" neutrino masses with Yukawa couplings to $(\
Park, Sei Jin; Zhao, Hangbo; Kim, Sanha; De Volder, Michael; John Hart, A
2016-08-01
High-throughput fabrication of microstructured surfaces with multi-directional, re-entrant, or otherwise curved features is becoming increasingly important for applications such as phase change heat transfer, adhesive gripping, and control of electromagnetic waves. Toward this goal, curved microstructures of aligned carbon nanotubes (CNTs) can be fabricated by engineered variation of the CNT growth rate within each microstructure, for example by patterning of the CNT growth catalyst partially upon a layer which retards the CNT growth rate. This study develops a finite-element simulation framework for predictive synthesis of complex CNT microarchitectures by this strain-engineered growth process. The simulation is informed by parametric measurements of the CNT growth kinetics, and the anisotropic mechanical properties of the CNTs, and predicts the shape of CNT microstructures with impressive fidelity. Moreover, the simulation calculates the internal stress distribution that results from extreme deformation of the CNT structures during growth, and shows that delamination of the interface between the differentially growing segments occurs at a critical shear stress. Guided by these insights, experiments are performed to study the time- and geometry-depended stress development, and it is demonstrated that corrugating the interface between the segments of each microstructure mitigates the interface failure. This study presents a methodology for 3D microstructure design based on "pixels" that prescribe directionality to the resulting microstructure, and show that this framework enables the predictive synthesis of more complex architectures including twisted and truss-like forms.
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.
Harnessing Intra-Host Strain Competition to Limit Antibiotic Resistance: Mathematical Model Results.
Beams, Alexander B; Toth, Damon J A; Khader, Karim; Adler, Frederick R
2016-09-01
Antibiotic overuse has promoted the spread of antibiotic resistance. To compound the issue, treating individuals dually infected with antibiotic-resistant and antibiotic-vulnerable strains can make their infections completely resistant through competitive release. We formulate mathematical models of transmission dynamics accounting for dual infections and extensions accounting for lag times between infection and treatment or between cure and ending treatment. Analysis using the Next-Generation Matrix reveals how competition within hosts and the costs of resistance determine whether vulnerable and resistant strains persist, coexist, or drive each other to extinction. Invasion analysis predicts that treatment of dually infected cases will promote resistance. By varying antibiotic strength, the models suggest that physicians have two ways to achieve a particular resistance target: prescribe relatively weak antibiotics to everyone infected with an antibiotic-vulnerable strain or give more potent prescriptions to only those patients singly infected with the vulnerable strain after ruling out the possibility of them being dually infected with resistance. Through selectivity and moderation in antibiotic prescription, resistance might be limited.
Hernandez, Eduardo; Pawar, Pallavi; Keyvan, Golshid; Wang, Yifan; Velez, Natasha; Callegari, Gerardo; Cuitino, Alberto; Michniak-Kohn, Bozena; Muzzio, Fernando J; Romañach, Rodolfo J
2016-01-01
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.
Specialized Language Models using Dialogue Predictions
Popovici, C; Popovici, Cosmin; Baggia, Paolo
1996-01-01
This paper analyses language modeling in spoken dialogue systems for accessing a database. The use of several language models obtained by exploiting dialogue predictions gives better results than the use of a single model for the whole dialogue interaction. For this reason several models have been created, each one for a specific system question, such as the request or the confirmation of a parameter. The use of dialogue-dependent language models increases the performance both at the recognition and at the understanding level, especially on answers to system requests. Moreover other methods to increase performance, like automatic clustering of vocabulary words or the use of better acoustic models during recognition, does not affect the improvements given by dialogue-dependent language models. The system used in our experiments is Dialogos, the Italian spoken dialogue system used for accessing railway timetable information over the telephone. The experiments were carried out on a large corpus of dialogues coll...
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.
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
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...
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.
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.
Khodayari, Ali; Chowdhury, Anupam; Maranas, Costas D
2014-01-01
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 while pointing at a number of unexplored flux re-directions such as routing glyoxylate flux through the glycerate metabolism to improve succinate yield. Many of the identified interventions rely on the kinetic descriptions that would not be discoverable by a purely stoichiometric description. In contrast, under fermentative (anaerobic) condition, 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 condition 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 on how to augment kinetic models so as to correctly respond to multiple environmental perturbations.
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.
ENSO Prediction using Vector Autoregressive Models
Chapman, D. R.; Cane, M. A.; Henderson, N.; Lee, D.; Chen, C.
2013-12-01
A recent comparison (Barnston et al, 2012 BAMS) shows the ENSO forecasting skill of dynamical models now exceeds that of statistical models, but the best statistical models are comparable to all but the very best dynamical models. In this comparison the leading statistical model is the one based on the Empirical Model Reduction (EMR) method. Here we report on experiments with multilevel Vector Autoregressive models using only sea surface temperatures (SSTs) as predictors. VAR(L) models generalizes Linear Inverse Models (LIM), which are a VAR(1) method, as well as multilevel univariate autoregressive models. Optimal forecast skill is achieved using 12 to 14 months of prior state information (i.e 12-14 levels), which allows SSTs alone to capture the effects of other variables such as heat content as well as seasonality. The use of multiple levels allows the model advancing one month at a time to perform at least as well for a 6 month forecast as a model constructed to explicitly forecast 6 months ahead. We infer that the multilevel model has fully captured the linear dynamics (cf. Penland and Magorian, 1993 J. Climate). Finally, while VAR(L) is equivalent to L-level EMR, we show in a 150 year cross validated assessment that we can increase forecast skill by improving on the EMR initialization procedure. The greatest benefit of this change is in allowing the prediction to make effective use of information over many more months.
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.)
Modeling the Stress Strain Behavior of Woven Ceramic Matrix Composites
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.
Gas explosion prediction using CFD models
Energy Technology Data Exchange (ETDEWEB)
Niemann-Delius, C.; Okafor, E. [RWTH Aachen Univ. (Germany); Buhrow, C. [TU Bergakademie Freiberg Univ. (Germany)
2006-07-15
A number of CFD models are currently available to model gaseous explosions in complex geometries. Some of these tools allow the representation of complex environments within hydrocarbon production plants. In certain explosion scenarios, a correction is usually made for the presence of buildings and other complexities by using crude approximations to obtain realistic estimates of explosion behaviour as can be found when predicting the strength of blast waves resulting from initial explosions. With the advance of computational technology, and greater availability of computing power, computational fluid dynamics (CFD) tools are becoming increasingly available for solving such a wide range of explosion problems. A CFD-based explosion code - FLACS can, for instance, be confidently used to understand the impact of blast overpressures in a plant environment consisting of obstacles such as buildings, structures, and pipes. With its porosity concept representing geometry details smaller than the grid, FLACS can represent geometry well, even when using coarse grid resolutions. The performance of FLACS has been evaluated using a wide range of field data. In the present paper, the concept of computational fluid dynamics (CFD) and its application to gas explosion prediction is presented. Furthermore, the predictive capabilities of CFD-based gaseous explosion simulators are demonstrated using FLACS. Details about the FLACS-code, some extensions made to FLACS, model validation exercises, application, and some results from blast load prediction within an industrial facility are presented. (orig.)
Genetic models of homosexuality: generating testable predictions.
Gavrilets, Sergey; Rice, William R
2006-12-22
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.
Characterizing Attention with Predictive Network Models.
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.
A Study On Distributed Model Predictive Consensus
Keviczky, Tamas
2008-01-01
We investigate convergence properties of a proposed distributed model predictive control (DMPC) scheme, where agents negotiate to compute an optimal consensus point using an incremental subgradient method based on primal decomposition as described in Johansson et al. [2006, 2007]. The objective of the distributed control strategy is to agree upon and achieve an optimal common output value for a group of agents in the presence of constraints on the agent dynamics using local predictive controllers. Stability analysis using a receding horizon implementation of the distributed optimal consensus scheme is performed. Conditions are given under which convergence can be obtained even if the negotiations do not reach full consensus.
A Universal Tare Load Prediction Algorithm for Strain-Gage Balance Calibration Data Analysis
Ulbrich, N.
2011-01-01
An algorithm is discussed that may be used to estimate tare loads of wind tunnel strain-gage balance calibration data. The algorithm was originally developed by R. Galway of IAR/NRC Canada and has been described in the literature for the iterative analysis technique. Basic ideas of Galway's algorithm, however, are universally applicable and work for both the iterative and the non-iterative analysis technique. A recent modification of Galway's algorithm is presented that improves the convergence behavior of the tare load prediction process if it is used in combination with the non-iterative analysis technique. The modified algorithm allows an analyst to use an alternate method for the calculation of intermediate non-linear tare load estimates whenever Galway's original approach does not lead to a convergence of the tare load iterations. It is also shown in detail how Galway's algorithm may be applied to the non-iterative analysis technique. Hand load data from the calibration of a six-component force balance is used to illustrate the application of the original and modified tare load prediction method. During the analysis of the data both the iterative and the non-iterative analysis technique were applied. Overall, predicted tare loads for combinations of the two tare load prediction methods and the two balance data analysis techniques showed excellent agreement as long as the tare load iterations converged. The modified algorithm, however, appears to have an advantage over the original algorithm when absolute voltage measurements of gage outputs are processed using the non-iterative analysis technique. In these situations only the modified algorithm converged because it uses an exact solution of the intermediate non-linear tare load estimate for the tare load iteration.
NONLINEAR MODEL PREDICTIVE CONTROL OF CHEMICAL PROCESSES
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R. G. SILVA
1999-03-01
Full Text Available A new algorithm for model predictive control is presented. The algorithm utilizes a simultaneous solution and optimization strategy to solve the model's differential equations. The equations are discretized by equidistant collocation, and along with the algebraic model equations are included as constraints in a nonlinear programming (NLP problem. This algorithm is compared with the algorithm that uses orthogonal collocation on finite elements. The equidistant collocation algorithm results in simpler equations, providing a decrease in computation time for the control moves. Simulation results are presented and show a satisfactory performance of this algorithm.
Directory of Open Access Journals (Sweden)
Baumann Gert
2008-06-01
Full Text Available Abstract Background Cardiac Resynchronization Therapy (CRT leads to hemodynamic and clinical improvement in heart failure patients. The established methods to evaluate myocardial asynchrony analyze longitudinal and radial myocardial function. This study evaluates the new method of circumferential 2D-strain imaging in the prediction of the long-term response to CRT. Methods and results 38 heart failure patients (NYHA II-III, QRS > 120 ms, LVEF Conclusion There is a significant decrease in the circumferential 2D-strain derived delays after CRT, indicating that resynchronization induces improvement in all three dimensions of myocardial contraction. However, the resulting predictive values of 2D strain delays are not superior to longitudinal and radial 2D-strain or TDI delays.
Left ventricular 12 segmental strain imaging predicts response to cardiac resynchronization therapy
Institute of Scientific and Technical Information of China (English)
DONG Ying-xue; Jae K.Oh; YANG Yan-zong; Yong-mei Cha
2013-01-01
Background The number of non-responders to cardiac resynchronization therapy (CRT) exposes the need for better patient selection criteria for CRT.This study aimed to identify echocardiographic parameters that would predict the response to CRT.Methods Forty-five consecutive patients receiving CRT-D implantation for heart failure (HF) were included in this prospective study.New York Heart Association (NYHA) class,6-minute walk distance,electrograph character,and multi echocardiographic parameters,especially in strain patterns,were measured and compared before and six months after CRT in the responder and non-responder groups.Response to CRT was defined as a decrease in left ventricular endsystolic volume (LVESV) of 15％ or more at 6-month follow up.Results Twenty-two (48.9％) patients demonstrated a response to CRT at 6-month follow-up.Significant improvement in NYHA class (P ＜0.01),left ventricular end-diastolic volume (LVEDV) (P ＜0.01),and 6-minute walk distance (P ＜0.01) was shown in this group.Although there was an interventricular mechanical delay determined by the difference between left and right ventricular pre-ejection intervals ((42.87±19.64) ms vs.(29.43±18.19) ms,P=0.02),the standard deviation of time to peak myocardial strain among 12 basal,mid and apical segments (Tε-SD) ((119.97±43.32) ms vs.(86.62±36.86) ms,P=0.01) and the non-ischemic etiology (P=0.03) were significantly higher in responders than non-responders,only the Tε-SD (OR=1.02,95％ Cl=1.01-1.04,P=0.02) proved to be a favorable predictor of CRT response after multivariate Logistic regression analysis.Conclusion The left ventricular 12 segmental strain imaging is a promising echocardiographic parameter for predicting CRT response.
In vitro strain measurements in cerebral aneurysm models for cyber-physical diagnosis.
Shi, Chaoyang; Kojima, Masahiro; Anzai, Hitomi; Tercero, Carlos; Ikeda, Seiichi; Ohta, Makoto; Fukuda, Toshio; Arai, Fumihito; Najdovski, Zoran; Negoro, Makoto; Irie, Keiko
2013-06-01
The development of new diagnostic technologies for cerebrovascular diseases requires an understanding of the mechanism behind the growth and rupture of cerebral aneurysms. To provide a comprehensive diagnosis and prognosis of this disease, it is desirable to evaluate wall shear stress, pressure, deformation and strain in the aneurysm region, based on information provided by medical imaging technologies. In this research, we propose a new cyber-physical system composed of in vitro dynamic strain experimental measurements and computational fluid dynamics (CFD) simulation for the diagnosis of cerebral aneurysms. A CFD simulation and a scaled-up membranous silicone model of a cerebral aneurysm were completed, based on patient-specific data recorded in August 2008. In vitro blood flow simulation was realized with the use of a specialized pump. A vision system was also developed to measure the strain at different regions on the model by way of pulsating blood flow circulating inside the model. Experimental results show that distance and area strain maxima were larger near the aneurysm neck (0.042 and 0.052), followed by the aneurysm dome (0.023 and 0.04) and finally the main blood vessel section (0.01 and 0.014). These results were complemented by a CFD simulation for the addition of wall shear stress, oscillatory shear index and aneurysm formation index. Diagnosis results using imaging obtained in August 2008 are consistent with the monitored aneurysm growth in 2011. The presented study demonstrates a new experimental platform for measuring dynamic strain within cerebral aneurysms. This platform is also complemented by a CFD simulation for advanced diagnosis and prediction of the growth tendency of an aneurysm in endovascular surgery. Copyright © 2013 John Wiley & Sons, Ltd.
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.
Performance model to predict overall defect density
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J Venkatesh
2012-08-01
Full Text Available Management by metrics is the expectation from the IT service providers to stay as a differentiator. Given a project, the associated parameters and dynamics, the behaviour and outcome need to be predicted. There is lot of focus on the end state and in minimizing defect leakage as much as possible. In most of the cases, the actions taken are re-active. It is too late in the life cycle. Root cause analysis and corrective actions can be implemented only to the benefit of the next project. The focus has to shift left, towards the execution phase than waiting for lessons to be learnt post the implementation. How do we pro-actively predict defect metrics and have a preventive action plan in place. This paper illustrates the process performance model to predict overall defect density based on data from projects in an organization.
Neuro-fuzzy modeling in bankruptcy prediction
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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.
Goldberg, Robert K.
2000-01-01
There has been no accurate procedure for modeling the high-speed impact of composite materials, but such an analytical capability will be required in designing reliable lightweight engine-containment systems. The majority of the models in use assume a linear elastic material response that does not vary with strain rate. However, for containment systems, polymer matrix composites incorporating ductile polymers are likely to be used. For such a material, the deformation response is likely to be nonlinear and to vary with strain rate. An analytical model has been developed at the NASA Glenn Research Center at Lewis Field that incorporates both of these features. A set of constitutive equations that was originally developed to analyze the viscoplastic deformation of metals (Ramaswamy-Stouffer equations) was modified to simulate the nonlinear, rate-dependent deformation of polymers. Specifically, the effects of hydrostatic stresses on the inelastic response, which can be significant in polymers, were accounted for by a modification of the definition of the effective stress. The constitutive equations were then incorporated into a composite micromechanics model based on the mechanics of materials theory. This theory predicts the deformation response of a composite material from the properties and behavior of the individual constituents. In this manner, the nonlinear, rate-dependent deformation response of a polymer matrix composite can be predicted.
Seasonal Predictability in a Model Atmosphere.
Lin, Hai
2001-07-01
The predictability of atmospheric mean-seasonal conditions in the absence of externally varying forcing is examined. A perfect-model approach is adopted, in which a global T21 three-level quasigeostrophic atmospheric model is integrated over 21 000 days to obtain a reference atmospheric orbit. The model is driven by a time-independent forcing, so that the only source of time variability is the internal dynamics. The forcing is set to perpetual winter conditions in the Northern Hemisphere (NH) and perpetual summer in the Southern Hemisphere.A significant temporal variability in the NH 90-day mean states is observed. The component of that variability associated with the higher-frequency motions, or climate noise, is estimated using a method developed by Madden. In the polar region, and to a lesser extent in the midlatitudes, the temporal variance of the winter means is significantly greater than the climate noise, suggesting some potential predictability in those regions.Forecast experiments are performed to see whether the presence of variance in the 90-day mean states that is in excess of the climate noise leads to some skill in the prediction of these states. Ensemble forecast experiments with nine members starting from slightly different initial conditions are performed for 200 different 90-day means along the reference atmospheric orbit. The serial correlation between the ensemble means and the reference orbit shows that there is skill in the 90-day mean predictions. The skill is concentrated in those regions of the NH that have the largest variance in excess of the climate noise. An EOF analysis shows that nearly all the predictive skill in the seasonal means is associated with one mode of variability with a strong axisymmetric component.
Directory of Open Access Journals (Sweden)
Michael S M Brouwer
Full Text Available BACKGROUND: 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. RESULTS: 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. CONCLUSIONS: 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
A kinetic model for predicting biodegradation.
Dimitrov, S; Pavlov, T; Nedelcheva, D; Reuschenbach, P; Silvani, M; Bias, R; Comber, M; Low, L; Lee, C; Parkerton, T; Mekenyan, O
2007-01-01
Biodegradation plays a key role in the environmental risk assessment of organic chemicals. The need to assess biodegradability of a chemical for regulatory purposes supports the development of a model for predicting the extent of biodegradation at different time frames, in particular the extent of ultimate biodegradation within a '10 day window' criterion as well as estimating biodegradation half-lives. Conceptually this implies expressing the rate of catabolic transformations as a function of time. An attempt to correlate the kinetics of biodegradation with molecular structure of chemicals is presented. A simplified biodegradation kinetic model was formulated by combining the probabilistic approach of the original formulation of the CATABOL model with the assumption of first order kinetics of catabolic transformations. Nonlinear regression analysis was used to fit the model parameters to OECD 301F biodegradation kinetic data for a set of 208 chemicals. The new model allows the prediction of biodegradation multi-pathways, primary and ultimate half-lives and simulation of related kinetic biodegradation parameters such as biological oxygen demand (BOD), carbon dioxide production, and the nature and amount of metabolites as a function of time. The model may also be used for evaluating the OECD ready biodegradability potential of a chemical within the '10-day window' criterion.
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
Paul, Surajit Kumar
2014-09-01
This paper has presented a life prediction model in the field of multiaxial low-cycle fatigue. The proposed model is generally applied for constant amplitude multiaxial proportional and non-proportional loading. Depending upon applied strain path the equivalent strain varies within a cycle. Equivalent average strain amplitude is considered as fatigue damage parameter in the proposed model. The model has requirement of only two material constants and no other tuning parameters. The model is examined by the proportional and non-proportional low-cycle fatigue life experimental data for eight different types of materials. The model is successfully correlated with multiaxial fatigue lives of eight different materials.
Mosser, Thomas; Talagrand-Reboul, Emilie; Colston, Sophie M.; Graf, Joerg; Figueras, Maria J.; Jumas-Bilak, Estelle; Lamy, Brigitte
2015-01-01
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, we studied the virulence of aeromonads recovered from human mixed infections. We tested them individually and in association with other strains with the aim of improving our understanding of aeromonosis. Twelve strains that were recovered in pairs from six mixed infections were tested in a virulence model of the worm Caenorhabditis elegans. Nine isolates were weak worm killers (median time to death, TD50, ≥7 days) when administered alone. Two pairs showed enhanced virulence, as indicated by a significantly shortened TD50 after co-infection vs. infection with a single strain. Enhanced virulence was also observed for five of the 14 additional experimental pairs, and each of these pairs included one strain from a natural synergistic pair. These experiments indicated that synergistic effects were frequent and were limited to pairs that were composed of strains belonging to different species. The genome content of virulence-associated genes failed to explain virulence synergy, although some virulence-associated genes that were present in some strains were absent from their companion strain (e.g., T3SS). The synergy observed in virulence when two Aeromonas isolates were co-infected stresses the idea that consideration should be given to the fact that infection does not depend only on single strain virulence but is instead the result of a more complex interaction between the microbes involved, the host and the environment. These results are of interest for other diseases in which mixed infections are likely and in particular for water-borne diseases (e.g., legionellosis, vibriosis), in which pathogens may display enhanced virulence in the presence of the right partner. This
Nonlinear model predictive control theory and algorithms
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...
Robust human body model injury prediction in simulated side impact crashes.
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.
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.
Autonomy and social norms in a three factor grief model predicting perinatal grief in India.
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.
Reynolds-stress model prediction of 3-D duct flows
Gerolymos, G A
2014-01-01
The paper examines the impact of different modelling choices in second-moment closures by assessing model performance in predicting 3-D duct flows. The test-cases (developing flow in a square duct [Gessner F.B., Emery A.F.: {\\em ASME J. Fluids Eng.} {\\bf 103} (1981) 445--455], circular-to-rectangular transition-duct [Davis D.O., Gessner F.B.: {\\em AIAA J.} {\\bf 30} (1992) 367--375], and \\tsn{S}-duct with large separation [Wellborn S.R., Reichert B.A., Okiishi T.H.: {\\em J. Prop. Power} {\\bf 10} (1994) 668--675]) include progressively more complex strains. Comparison of experimental data with selected 7-equation models (6 Reynolds-stress-transport and 1 scale-determining equations), which differ in the closure of the velocity/pressure-gradient tensor $\\Pi_{ij}$, suggests that rapid redistribution controls separation and secondary-flow prediction, whereas, inclusion of pressure-diffusion modelling improves reattachment and relaxation behaviour.
Probabilistic prediction models for aggregate quarry siting
Robinson, G.R.; Larkins, P.M.
2007-01-01
Weights-of-evidence (WofE) and logistic regression techniques were used in a GIS framework to predict the spatial likelihood (prospectivity) of crushed-stone aggregate quarry development. The joint conditional probability models, based on geology, transportation network, and population density variables, were defined using quarry location and time of development data for the New England States, North Carolina, and South Carolina, USA. The Quarry Operation models describe the distribution of active aggregate quarries, independent of the date of opening. The New Quarry models describe the distribution of aggregate quarries when they open. Because of the small number of new quarries developed in the study areas during the last decade, independent New Quarry models have low parameter estimate reliability. The performance of parameter estimates derived for Quarry Operation models, defined by a larger number of active quarries in the study areas, were tested and evaluated to predict the spatial likelihood of new quarry development. Population density conditions at the time of new quarry development were used to modify the population density variable in the Quarry Operation models to apply to new quarry development sites. The Quarry Operation parameters derived for the New England study area, Carolina study area, and the combined New England and Carolina study areas were all similar in magnitude and relative strength. The Quarry Operation model parameters, using the modified population density variables, were found to be a good predictor of new quarry locations. Both the aggregate industry and the land management community can use the model approach to target areas for more detailed site evaluation for quarry location. The models can be revised easily to reflect actual or anticipated changes in transportation and population features. ?? International Association for Mathematical Geology 2007.
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 s...... as it pinpoints which decisions to be concerned about when the goal is to predict footbridge response. The studies involve estimating footbridge responses using Monte-Carlo simulations and focus is on estimating vertical structural response to single person loading....
Nonconvex Model Predictive Control for Commercial Refrigeration
DEFF Research Database (Denmark)
Hovgaard, Tobias Gybel; Larsen, Lars F.S.; Jørgensen, John Bagterp
2013-01-01
is to minimize the total energy cost, using real-time electricity prices, while obeying temperature constraints on the zones. We propose a variation on model predictive control to achieve this goal. When the right variables are used, the dynamics of the system are linear, and the constraints are convex. The cost...... the iterations, which is more than fast enough to run in real-time. We demonstrate our method on a realistic model, with a full year simulation and 15 minute time periods, using historical electricity prices and weather data, as well as random variations in thermal load. These simulations show substantial cost...
Energy Technology Data Exchange (ETDEWEB)
Ong, P.V., E-mail: phuongvu.ong@csun.edu; Kioussis, Nicholas, E-mail: nick.kioussis@csun.edu
2016-02-15
Employing ab initio electronic structure calculations we have investigated the magnetostrictive properties and the effect of epitaxial strain on the magnetic anisotropy (MA) of Au/FeCo/MgO heterostructure. Under small expansive strain on the FeCo layer the system exhibits an in-plane MA. The calculations reveal that the strain dependence of the MA is nonlinear and that the FeCo film undergoes a spin reorientation at a critical strain between 2 and 4%. The underlying mechanism is the strain-induced shift of the spin–orbit coupled d-states of the Fe atoms. We predict a giant magnetostriction coefficient of about 420×10{sup −6} in the heterostructure. - Highlights: • Nonlinear strain dependence of magnetic anisotropy. • The FeCo film undergoes a spin reorientation at a critical strain between 2 and 4%. • The underlying mechanism is the strain-induced shift of the spin–orbit coupled d-states of the Fe atoms. • Giant magnetostriction coefficient of about 420×10{sup -6} in the heterostructure.
Predictive In Vivo Models for Oncology.
Behrens, Diana; Rolff, Jana; Hoffmann, Jens
2016-01-01
Experimental oncology research and preclinical drug development both substantially require specific, clinically relevant in vitro and in vivo tumor models. The increasing knowledge about the heterogeneity of cancer requested a substantial restructuring of the test systems for the different stages of development. To be able to cope with the complexity of the disease, larger panels of patient-derived tumor models have to be implemented and extensively characterized. Together with individual genetically engineered tumor models and supported by core functions for expression profiling and data analysis, an integrated discovery process has been generated for predictive and personalized drug development.Improved “humanized” mouse models should help to overcome current limitations given by xenogeneic barrier between humans and mice. Establishment of a functional human immune system and a corresponding human microenvironment in laboratory animals will strongly support further research.Drug discovery, systems biology, and translational research are moving closer together to address all the new hallmarks of cancer, increase the success rate of drug development, and increase the predictive value of preclinical models.
Constructing predictive models of human running.
Maus, Horst-Moritz; Revzen, Shai; Guckenheimer, John; Ludwig, Christian; Reger, Johann; Seyfarth, Andre
2015-02-06
Running is an essential mode of human locomotion, during which ballistic aerial phases alternate with phases when a single foot contacts the ground. The spring-loaded inverted pendulum (SLIP) provides a starting point for modelling running, and generates ground reaction forces that resemble those of the centre of mass (CoM) of a human runner. Here, we show that while SLIP reproduces within-step kinematics of the CoM in three dimensions, it fails to reproduce stability and predict future motions. We construct SLIP control models using data-driven Floquet analysis, and show how these models may be used to obtain predictive models of human running with six additional states comprising the position and velocity of the swing-leg ankle. Our methods are general, and may be applied to any rhythmic physical system. We provide an approach for identifying an event-driven linear controller that approximates an observed stabilization strategy, and for producing a reduced-state model which closely recovers the observed dynamics. © 2014 The Author(s) Published by the Royal Society. All rights reserved.
Statistical Seasonal Sea Surface based Prediction Model
Suarez, Roberto; Rodriguez-Fonseca, Belen; Diouf, Ibrahima
2014-05-01
The interannual variability of the sea surface temperature (SST) plays a key role in the strongly seasonal rainfall regime on the West African region. The predictability of the seasonal cycle of rainfall is a field widely discussed by the scientific community, with results that fail to be satisfactory due to the difficulty of dynamical models to reproduce the behavior of the Inter Tropical Convergence Zone (ITCZ). To tackle this problem, a statistical model based on oceanic predictors has been developed at the Universidad Complutense of Madrid (UCM) with the aim to complement and enhance the predictability of the West African Monsoon (WAM) as an alternative to the coupled models. The model, called S4CAST (SST-based Statistical Seasonal Forecast) is based on discriminant analysis techniques, specifically the Maximum Covariance Analysis (MCA) and Canonical Correlation Analysis (CCA). Beyond the application of the model to the prediciton of rainfall in West Africa, its use extends to a range of different oceanic, atmospheric and helth related parameters influenced by the temperature of the sea surface as a defining factor of variability.
2011-01-01
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 speckle-tracking strain was also predictive of response to CRT with an AUC of 0.82 (p speckle tracking system, which shows circumferential and longitudinal LV dyssynchrony and residual endocardial contractility, may thus have clinical significance for CRT patients. PMID:21466687
Polzer, Stanislav; Bursa, Jiri; Gasser, T Christian; Staffa, Robert; Vlachovsky, Robert
2013-07-01
Wall stress analysis of abdominal aortic aneurysm (AAA) is a promising method of identifying AAAs at high risk of rupture. However, neglecting residual strains (RS) in the load-free configuration of patient-specific finite element analysis models is a sever limitation that strongly affects the computed wall stresses. Although several methods for including RS have been proposed, they cannot be directly applied to patient-specific AAA simulations. RS in the AAA wall are predicted through volumetric tissue growth that aims at satisfying the homogeneous stress hypothesis at mean arterial pressure load. Tissue growth is interpolated linearly across the wall thickness and aneurysm tissues are described by isotropic constitutive formulations. The total deformation is multiplicatively split into elastic and growth contributions, and a staggered schema is used to solve the field variables. The algorithm is validated qualitatively at a cylindrical artery model and then applied to patient-specific AAAs (n = 5). The induced RS state is fully three-dimensional and in qualitative agreement with experimental observations, i.e., wall strips that were excised from the load-free wall showed stress-releasing-deformations that are typically seen in laboratory experiments. Compared to RS-free simulations, the proposed algorithm reduced the von Mises stress gradient across the wall by a tenfold. Accounting for RS leads to homogenized wall stresses, which apart from reducing the peak wall stress (PWS) also shifted its location in some cases. The present study demonstrated that the homogeneous stress hypothesis can be effectively used to predict RS in the load-free configuration of the vascular wall. The proposed algorithm leads to a fast and robust prediction of RS, which is fully capable for a patient-specific AAA rupture risk assessment. Neglecting RS leads to non-realistic wall stress values that severely overestimate the PWS.
Heterogeneity Confounds Establishment of "a" Model Microbial Strain.
Keller, Nancy P
2017-02-21
Aspergillus fumigatus is a ubiquitous environmental mold and the leading cause of diverse human diseases ranging from allergenic bronchopulmonary aspergillosis (ABPA) to invasive pulmonary aspergillosis (IPA). Experimental investigations of the biology and virulence of this opportunistic pathogen have historically used a few type strains; however, it is increasingly observed with this fungus that heterogeneity among isolates potentially confounds the use of these reference isolates. Illustrating this point, Kowalski et al. (mBio 7:e01515-16, 2016, https://doi.org/10.1128/mBio.01515-16) demonstrated that variation in 16 environmental and clinical isolates of A. fumigatus correlated virulence with fitness in low oxygen, whereas Fuller et al. (mBio 7:e01517-16, 2016, https://doi.org/10.1128/mBio.01517-16) showed wide variation in light responses at a physiological and protein functionality level in 15 A. fumigatus isolates. In both studies, two commonly used type strains, Af293 and CEA10, displayed significant differences in physiological responses to abiotic stimuli and virulence in a murine model of IPA.
Evaluation Study of Pressure-Strain Correlation Models in Compressible Flow
Directory of Open Access Journals (Sweden)
Aicha Hanafi
2016-01-01
Full Text Available This paper is devoted to the second-order closure for compressible turbulent flows with special attention paid to modeling the pressure-strain correlation appearing in the Reynolds stress equation. This term appears as the main one responsible for the changes of the turbulence structures that arise from structural compressibility effects. The structure of the gradient Mach number is similar to that of turbulence, therefore this parameter may be appropriate to study the changes in turbulence structures that arise from structural compressibility effects. Thus, the incompressible model (LRR of the pressure-strain correlation and its corrected form by using the turbulent Mach number, fail to correctly evaluate the compressibility effects at high shear flow. An extension of the widely used incompressible model (LRR on compressible homogeneous shear flow is the major aim of the present work. From this extension the standard coefficients Ci became a function of the compressibility parameters (the turbulent Mach number and the gradient Mach number. Application of the model on compressible homogeneous shear flow by considering various initial conditions shows reasonable agreement with the DNS results of Sarkar. The ability of the models to predict the equilibrium states for the flow in cases A1 and A4 from DNS results of Sarkar is examined, the results appear to be very encouraging. Thus, both parameters Mt and Mg should be used to model significant structural compressibility effects at high-speed shear flow.
Predictive modeling by the cerebellum improves proprioception.
Bhanpuri, Nasir H; Okamura, Allison M; Bastian, Amy J
2013-09-04
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.
Institute of Scientific and Technical Information of China (English)
无
2000-01-01
Based on study of strain distribution in whisker reinforced metal matrix composites, an explicit precise stiffness tensor is derived. In the present theory, the effect of whisker orientation on the macro property of composites is considered, but the effect of random whisker position and the complicated strain field at whisker ends are averaged. The derived formula is able to predict the stiffness modulus of composites with arbitrary whisker orientation under any loading condition. Compared with the models of micro-mechanics, the present theory is competent for modulus prediction of actual engineering composites. The verification and application of the present theory are given in a subsequent paper published in the same issue.
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.
Gamma-Ray Pulsars Models and Predictions
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...
Artificial Neural Network Model for Predicting Compressive
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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.
Ground Motion Prediction Models for Caucasus Region
Jorjiashvili, Nato; Godoladze, Tea; Tvaradze, Nino; Tumanova, Nino
2016-04-01
Ground motion prediction models (GMPMs) relate ground motion intensity measures to variables describing earthquake source, path, and site effects. Estimation of expected ground motion is a fundamental earthquake hazard assessment. The most commonly used parameter for attenuation relation is peak ground acceleration or spectral acceleration because this parameter gives useful information for Seismic Hazard Assessment. Since 2003 development of Georgian Digital Seismic Network has started. In this study new GMP models are obtained based on new data from Georgian seismic network and also from neighboring countries. Estimation of models is obtained by classical, statistical way, regression analysis. In this study site ground conditions are additionally considered because the same earthquake recorded at the same distance may cause different damage according to ground conditions. Empirical ground-motion prediction models (GMPMs) require adjustment to make them appropriate for site-specific scenarios. However, the process of making such adjustments remains a challenge. This work presents a holistic framework for the development of a peak ground acceleration (PGA) or spectral acceleration (SA) GMPE that is easily adjustable to different seismological conditions and does not suffer from the practical problems associated with adjustments in the response spectral domain.
Modeling and Prediction of Krueger Device Noise
Guo, Yueping; Burley, Casey L.; Thomas, Russell H.
2016-01-01
This paper presents the development of a noise prediction model for aircraft Krueger flap devices that are considered as alternatives to leading edge slotted slats. The prediction model decomposes the total Krueger noise into four components, generated by the unsteady flows, respectively, in the cove under the pressure side surface of the Krueger, in the gap between the Krueger trailing edge and the main wing, around the brackets supporting the Krueger device, and around the cavity on the lower side of the main wing. For each noise component, the modeling follows a physics-based approach that aims at capturing the dominant noise-generating features in the flow and developing correlations between the noise and the flow parameters that control the noise generation processes. The far field noise is modeled using each of the four noise component's respective spectral functions, far field directivities, Mach number dependencies, component amplitudes, and other parametric trends. Preliminary validations are carried out by using small scale experimental data, and two applications are discussed; one for conventional aircraft and the other for advanced configurations. The former focuses on the parametric trends of Krueger noise on design parameters, while the latter reveals its importance in relation to other airframe noise components.
A generative model for predicting terrorist incidents
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
Two-strain Tuberculosis Transmission Model under Three Control Strategies
Rayhan, S. N.; Bakhtiar, T.; Jaharuddin
2017-03-01
In 1997, Castillo-Chavez and Feng developed a two-strain tuberculosis (TB) model, which is typical TB and resistant TB. Castillo-Chavez and Feng’s model was then subsequently developed by Jung et al. (2002) by adding two control variables. In this work, Jung et al.’s model was modified by introducing a new control variable so that there are three controls, namely chemoprophylaxis and two treatment strategies, with the application of three different scenarios related to the objective functional form and control application. Pontryagin maximum principle was applied to derive the differential equations system as a condition that must be satisfied by the optimal control variables. Furthermore, the fourth-order Runge-Kutta method was exploited to determine the numerical solution of the optimal control problem. In this numerical solution, it is shown that the controls treated on TB transmission model provide a good effect because latent and infected individuals are decreasing, and the number of individuals that is treated effectively is increasing.
Modelling the physiological strain and physical burden of chemical protective coveralls.
Wen, ShuQin; Petersen, Stewart; McQueen, Rachel; Batcheller, Jane
2015-01-01
This study determined the impact of selected chemical protective coveralls (CPC) on physiological responses and comfort sensations. Fifteen males exercised at approximately 6 METS in three CPC (Tyvek®, Gulf and Tychem®) and a control garment. Physiological strain was characterised by core and skin temperatures, heart rate, V̇O2, perceived exertion, hotness and wetness. Physical burden was characterised by restriction to movement, V̇O2 and RPE. The highest levels of physiological strain and physical burden were found in Tychem®, and the lowest in control. Seven statistical regression models were developed through correlation and multiple regression analyses between the human responses and the results from previously conducted fabric and garment property testing. These models showed that physical burden was increased by adding weight and/or restricting movement. Oxygen consumption was best predicted by clothing weight and fabric bending hysteresis. Fabric evaporative resistance and thickness were the two best predictors of physiological and perceptual responses. Practitioner Summary: Traditional evaluation of chemical protective coveralls (CPC) involves testing at the fabric and garment levels and rarely is based on human trials. This study integrates information from fabric, garment and human trials to better understand physiological strain and physical comfort during prolonged exercise in CPC.
Modification of a thermomechanical model to predict constitutive behavior of Al-Mg-Si alloys
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
Constructing A Small Strain Potential for Multi-Scale Modeling
Mallik, A; Cheng, H P; Dufty, J W; Mallik, Aditi; Runge, Keith; Cheng, Hai-Ping; Dufty, James W.; Mallik, Aditi; Runge, Keith; Cheng, Hai-Ping; Dufty, James W.
2005-01-01
For problems relating to fracture, a consistent embedding of a quantum (QM) domain in its classical (CM) environment requires that the classical system should yield the same structure and elastic properties as the QM domain for states near equilibrium. It is proposed that an appropriate classical potential can be constructed using ab initio data on the equilibrium and weakly strained configurations calculated from the quantum description, rather than the more usual approach of fitting to a wide range of empirical data. The scheme is illustrated in detail for a model system, silica nanorod that has the proper stiochiometric ratio of Si:O as observed in real silica. The potential is chosen to be pairwise additive, with the same pair potential functional form as familiar phenomenological TTAM potential. Here, the parameters are determined using a genetic algorithm with force data obtained directly from a quantum calculation. The resulting potential gives excellent agreement with properties of the reference quant...
Soil Stress-Strain Behavior: Measurement, Modeling and Analysis
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).
Optimal feedback scheduling of model predictive controllers
Institute of Scientific and Technical Information of China (English)
Pingfang ZHOU; Jianying XIE; Xiaolong DENG
2006-01-01
Model predictive control (MPC) could not be reliably applied to real-time control systems because its computation time is not well defined. Implemented as anytime algorithm, MPC task allows computation time to be traded for control performance, thus obtaining the predictability in time. Optimal feedback scheduling (FS-CBS) of a set of MPC tasks is presented to maximize the global control performance subject to limited processor time. Each MPC task is assigned with a constant bandwidth server (CBS), whose reserved processor time is adjusted dynamically. The constraints in the FSCBS guarantee scheduler of the total task set and stability of each component. The FS-CBS is shown robust against the variation of execution time of MPC tasks at runtime. Simulation results illustrate its effectiveness.
Objective calibration of numerical weather prediction models
Voudouri, A.; Khain, P.; Carmona, I.; Bellprat, O.; Grazzini, F.; Avgoustoglou, E.; Bettems, J. M.; Kaufmann, P.
2017-07-01
Numerical weather prediction (NWP) and climate models use parameterization schemes for physical processes, which often include free or poorly confined parameters. Model developers normally calibrate the values of these parameters subjectively to improve the agreement of forecasts with available observations, a procedure referred as expert tuning. A practicable objective multi-variate calibration method build on a quadratic meta-model (MM), that has been applied for a regional climate model (RCM) has shown to be at least as good as expert tuning. Based on these results, an approach to implement the methodology to an NWP model is presented in this study. Challenges in transferring the methodology from RCM to NWP are not only restricted to the use of higher resolution and different time scales. The sensitivity of the NWP model quality with respect to the model parameter space has to be clarified, as well as optimize the overall procedure, in terms of required amount of computing resources for the calibration of an NWP model. Three free model parameters affecting mainly turbulence parameterization schemes were originally selected with respect to their influence on the variables associated to daily forecasts such as daily minimum and maximum 2 m temperature as well as 24 h accumulated precipitation. Preliminary results indicate that it is both affordable in terms of computer resources and meaningful in terms of improved forecast quality. In addition, the proposed methodology has the advantage of being a replicable procedure that can be applied when an updated model version is launched and/or customize the same model implementation over different climatological areas.
Prediction models from CAD models of 3D objects
Camps, Octavia I.
1992-11-01
In this paper we present a probabilistic prediction based approach for CAD-based object recognition. Given a CAD model of an object, the PREMIO system combines techniques of analytic graphics and physical models of lights and sensors to predict how features of the object will appear in images. In nearly 4,000 experiments on analytically-generated and real images, we show that in a semi-controlled environment, predicting the detectability of features of the image can successfully guide a search procedure to make informed choices of model and image features in its search for correspondences that can be used to hypothesize the pose of the object. Furthermore, we provide a rigorous experimental protocol that can be used to determine the optimal number of correspondences to seek so that the probability of failing to find a pose and of finding an inaccurate pose are minimized.
Model predictive control of MSMPR crystallizers
Moldoványi, Nóra; Lakatos, Béla G.; Szeifert, Ferenc
2005-02-01
A multi-input-multi-output (MIMO) control problem of isothermal continuous crystallizers is addressed in order to create an adequate model-based control system. The moment equation model of mixed suspension, mixed product removal (MSMPR) crystallizers that forms a dynamical system is used, the state of which is represented by the vector of six variables: the first four leading moments of the crystal size, solute concentration and solvent concentration. Hence, the time evolution of the system occurs in a bounded region of the six-dimensional phase space. The controlled variables are the mean size of the grain; the crystal size-distribution and the manipulated variables are the input concentration of the solute and the flow rate. The controllability and observability as well as the coupling between the inputs and the outputs was analyzed by simulation using the linearized model. It is shown that the crystallizer is a nonlinear MIMO system with strong coupling between the state variables. Considering the possibilities of the model reduction, a third-order model was found quite adequate for the model estimation in model predictive control (MPC). The mean crystal size and the variance of the size distribution can be nearly separately controlled by the residence time and the inlet solute concentration, respectively. By seeding, the controllability of the crystallizer increases significantly, and the overshoots and the oscillations become smaller. The results of the controlling study have shown that the linear MPC is an adaptable and feasible controller of continuous crystallizers.
Modelling of pressure-strain correlation in compressible turbulent flow
Institute of Scientific and Technical Information of China (English)
Siyuan Huang; Song Fu
2008-01-01
Previous studies carried out in the early 1990s conjectured that the main compressible effects could be associated with the dilatational effects of velocity fluctuation.Later,it was shown that the main compressibility effect came from the reduced pressure-strain term due to reduced pressure fluctuations.Although better understanding of the compressible turbulence is generally achieved with the increased DNS and experimental research effort,there are still some discrepancies among these recent findings.Analysis of the DNS and experimental data suggests that some of the discrepancies are apparent if the compressible effect is related to the turbulent Mach number,Mt.From the comparison of two classes of compressible flow,homogenous shear flow and inhomogeneous shear flow(mixing layer),we found that the effect of compressibility on both classes of shear flow can be characterized in three categories corresponding to three regions of turbulent Mach numbers:the low-Mt,the moderate-Mt and high-Mt regions.In these three regions the effect of compressibility on the growth rate of the turbulent mixing layer thickness is rather different.A simple approach to the reduced pressure-strain effect may not necessarily reduce the mixing-layer growth rate,and may even cause an increase in the growth rate.The present work develops a new second-moment model for the compressible turbulence through the introduction of some blending functions of Mt to account for the compressibility effects on the flow.The model has been successfully applied to the compressible mixing layers.
An Anisotropic Hardening Model for Springback Prediction
Zeng, Danielle; Xia, Z. Cedric
2005-08-01
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.
Job stress models for predicting burnout syndrome: a review.
Chirico, Francesco
2016-01-01
In Europe, the Council Directive 89/391 for improvement of workers' safety and health has emphasized the importance of addressing all occupational risk factors, and hence also psychosocial and organizational risk factors. Nevertheless, the construct of "work-related stress" elaborated from EU-OSHA is not totally corresponding with the "psychosocial" risk, that is a broader category of risk, comprising various and different psychosocial risk factors. The term "burnout", without any binding definition, tries to integrate symptoms as well as cause of the burnout process. In Europe, the most important methods developed for the work related stress risk assessment are based on the Cox's transactional model of job stress. Nevertheless, there are more specific models for predicting burnout syndrome. This literature review provides an overview of job burnout, highlighting the most important models of job burnout, such as the Job Strain, the Effort/Reward Imbalance and the Job Demands-Resources models. The difference between these models and the Cox's model of job stress is explored.
Prediction of the bending behavior after pre-strain of an aluminum alloy
Pradeau, A.; Thuillier, S.; Yoon, J. W.
2016-10-01
The present work is focused on the modeling of sheet metal mechanical behavior up to rupture, including anisotropy and hardening. The mechanical behavior of an AA6016 alloy was characterized at room temperature in tension, simple shear and hydraulic bulging. The initial anisotropy was described with the Yld2004-18p yield criterion coupled to a mixed hardening law. Concerning rupture, an uncoupled phenomenological criterion of Mohr-Coulomb type will be used. For the material parameter identification, an inverse methodology was used with the objective of reducing the gap between experimental and numerical data. Finally, validation of the results was performed on bending tests with different amplitudes of tension pre-strain in order to reach or not rupture in the bent area.
Markov chain modeling of evolution of strains in reinforced concrete flexural beams
Directory of Open Access Journals (Sweden)
Anoop, M. B.
2012-09-01
Full Text Available From the analysis of experimentally observed variations in surface strains with loading in reinforced concrete beams, it is noted that there is a need to consider the evolution of strains (with loading as a stochastic process. Use of Markov Chains for modeling stochastic evolution of strains with loading in reinforced concrete flexural beams is studied in this paper. A simple, yet practically useful, bi-level homogeneous Gaussian Markov Chain (BLHGMC model is proposed for determining the state of strain in reinforced concrete beams. The BLHGMC model will be useful for predicting behavior/response of reinforced concrete beams leading to more rational design.A través del análisis de la evolución de la deformación superficial observada experimentalmente en vigas de hormigón armado al entrar en carga, se constata que dicho proceso debe considerarse estocástico. En este trabajo se estudia la utilización de cadenas de Markov para modelizar la evolución estocástica de la deformación de vigas flexotraccionadas. Se propone, para establecer el estado de deformación de estas, un modelo con distribución gaussiana tipo cadena de Markov homogénea de dos niveles (BLHGMC por sus siglas en inglés, cuyo empleo resulta sencillo y práctico. Se comprueba la utilidad del modelo BLHGMC para prever el comportamiento de estos elementos, lo que determina a su vez una mayor racionalidad a la hora de su cálculo y diseño
Tatsumi, Kazuhiro; Tanaka, Hidekazu; Yamawaki, Kouhei; Ryo, Keiko; Omar, Alaa Mabrouk Salem; Fukuda, Yuko; Norisada, Kazuko; Matsumoto, Kensuke; Onishi, Tetsuari; Gorcsan, John; Yoshida, Akihiro; Kawai, Hiroya; Hirata, Ken-ichi
2011-02-01
The strain delay index is reportedly a marker of dyssynchrony and residual myocardial contractility. The aim of this study was to test the hypothesis that a relatively simple version of the strain dyssynchrony index (SDI) can predict response to cardiac resynchronization therapy (CRT) and that combining assessment of radial, circumferential, and longitudinal SDI can further improve the prediction of responders. A total of 52 patients who underwent CRT were studied. The SDI was calculated as the average difference between peak and end-systolic strain from 6 segments for radial and circumferential SDI and 18 segments for longitudinal SDI. Conventional dyssynchrony measures were assessed by interventricular mechanical delay, the Yu index, and radial dyssynchrony by speckle tracking strain. Response was defined as a ≥15% decrease in end-systolic volume after 3 months. Of the individual parameters, radial SDI ≥6.5% was the best predictor of response to CRT, with sensitivity of 81%, specificity of 81%, and an area under the curve of 0.87 (p SDIs was 100%. In contrast, rates in patients with either 1 or no positive SDIs were 42% and 22%, respectively (p SDIs). In conclusion, the SDI can successfully predict response to CRT, and the combined approach leads to more accurate prediction than using individual parameters.
Paul, Shirshendu; Katiyar, Amit; Sarkar, Kausik; Chatterjee, Dhiman; Shi, William T; Forsberg, Flemming
2010-06-01
Two nonlinear interfacial elasticity models--interfacial elasticity decreasing linearly and exponentially with area fraction--are developed for the encapsulation of contrast microbubbles. The strain softening (decreasing elasticity) results from the decreasing association between the constitutive molecules of the encapsulation. The models are used to find the characteristic properties (surface tension, interfacial elasticity, interfacial viscosity and nonlinear elasticity parameters) for a commercial contrast agent. Properties are found using the ultrasound attenuation measured through a suspension of contrast agent. Dynamics of the resulting models are simulated, compared with other existing models and discussed. Imposing non-negativity on the effective surface tension (the encapsulation experiences no net compressive stress) shows "compression-only" behavior. The exponential and the quadratic (linearly varying elasticity) models result in similar behaviors. The validity of the models is investigated by comparing their predictions of the scattered nonlinear response for the contrast agent at higher excitations against experimental measurement. All models predict well the scattered fundamental response. The nonlinear strain softening included in the proposed elastic models of the encapsulation improves their ability to predict subharmonic response. They predict the threshold excitation for the initiation of subharmonic response and its subsequent saturation.
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.
Predictive modelling of ferroelectric tunnel junctions
Velev, Julian P.; Burton, John D.; Zhuravlev, Mikhail Ye; Tsymbal, Evgeny Y.
2016-05-01
Ferroelectric tunnel junctions combine the phenomena of quantum-mechanical tunnelling and switchable spontaneous polarisation of a nanometre-thick ferroelectric film into novel device functionality. Switching the ferroelectric barrier polarisation direction produces a sizable change in resistance of the junction—a phenomenon known as the tunnelling electroresistance effect. From a fundamental perspective, ferroelectric tunnel junctions and their version with ferromagnetic electrodes, i.e., multiferroic tunnel junctions, are testbeds for studying the underlying mechanisms of tunnelling electroresistance as well as the interplay between electric and magnetic degrees of freedom and their effect on transport. From a practical perspective, ferroelectric tunnel junctions hold promise for disruptive device applications. In a very short time, they have traversed the path from basic model predictions to prototypes for novel non-volatile ferroelectric random access memories with non-destructive readout. This remarkable progress is to a large extent driven by a productive cycle of predictive modelling and innovative experimental effort. In this review article, we outline the development of the ferroelectric tunnel junction concept and the role of theoretical modelling in guiding experimental work. We discuss a wide range of physical phenomena that control the functional properties of ferroelectric tunnel junctions and summarise the state-of-the-art achievements in the field.
Simple predictions from multifield inflationary models.
Easther, Richard; Frazer, Jonathan; Peiris, Hiranya V; Price, Layne C
2014-04-25
We explore whether multifield inflationary models make unambiguous predictions for fundamental cosmological observables. Focusing on N-quadratic inflation, we numerically evaluate the full perturbation equations for models with 2, 3, and O(100) fields, using several distinct methods for specifying the initial values of the background fields. All scenarios are highly predictive, with the probability distribution functions of the cosmological observables becoming more sharply peaked as N increases. For N=100 fields, 95% of our Monte Carlo samples fall in the ranges ns∈(0.9455,0.9534), α∈(-9.741,-7.047)×10-4, r∈(0.1445,0.1449), and riso∈(0.02137,3.510)×10-3 for the spectral index, running, tensor-to-scalar ratio, and isocurvature-to-adiabatic ratio, respectively. The expected amplitude of isocurvature perturbations grows with N, raising the possibility that many-field models may be sensitive to postinflationary physics and suggesting new avenues for testing these scenarios.
Directory of Open Access Journals (Sweden)
Key Christopher T.
2015-01-01
Full Text Available This study details and demonstrates a strain-based criterion for the prediction of polymer matrix composite material damage and failure under shock loading conditions. Shock loading conditions are characterized by high-speed impacts or explosive events that result in very high pressures in the materials involved. These material pressures can reach hundreds of kbar and often exceed the material strengths by several orders of magnitude. Researchers have shown that under these high pressures, composites exhibit significant increases in stiffness and strength. In this work we summarize modifications to a previous stress based interactive failure criterion based on the model initially proposed by Hashin, to include strain dependence. The failure criterion is combined with the multi-constituent composite constitutive model (MCM within a shock physics hydrocode. The constitutive model allows for decomposition of the composite stress and strain fields into the individual phase averaged constituent level stress and strain fields, which are then applied to the failure criterion. Numerical simulations of a metallic sphere impacting carbon/epoxy composite plates at velocities up to 1000 m/s are performed using both the stress and strain based criterion. These simulation results are compared to experimental tests to illustrate the advantages of a strain-based criterion in the shock environment.
Key, Christopher T.; Schumacher, Shane C.; Alexander, C. Scott
2015-09-01
This study details and demonstrates a strain-based criterion for the prediction of polymer matrix composite material damage and failure under shock loading conditions. Shock loading conditions are characterized by high-speed impacts or explosive events that result in very high pressures in the materials involved. These material pressures can reach hundreds of kbar and often exceed the material strengths by several orders of magnitude. Researchers have shown that under these high pressures, composites exhibit significant increases in stiffness and strength. In this work we summarize modifications to a previous stress based interactive failure criterion based on the model initially proposed by Hashin, to include strain dependence. The failure criterion is combined with the multi-constituent composite constitutive model (MCM) within a shock physics hydrocode. The constitutive model allows for decomposition of the composite stress and strain fields into the individual phase averaged constituent level stress and strain fields, which are then applied to the failure criterion. Numerical simulations of a metallic sphere impacting carbon/epoxy composite plates at velocities up to 1000 m/s are performed using both the stress and strain based criterion. These simulation results are compared to experimental tests to illustrate the advantages of a strain-based criterion in the shock environment.
Predictions of models for environmental radiological assessment
Energy Technology Data Exchange (ETDEWEB)
Peres, Sueli da Silva; Lauria, Dejanira da Costa, E-mail: suelip@ird.gov.br, E-mail: dejanira@irg.gov.br [Instituto de Radioprotecao e Dosimetria (IRD/CNEN-RJ), Servico de Avaliacao de Impacto Ambiental, Rio de Janeiro, RJ (Brazil); Mahler, Claudio Fernando [Coppe. Instituto Alberto Luiz Coimbra de Pos-Graduacao e Pesquisa de Engenharia, Universidade Federal do Rio de Janeiro (UFRJ) - Programa de Engenharia Civil, RJ (Brazil)
2011-07-01
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 {sup 137}Cs and {sup 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)
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......The primary structure of a protein is the sequence of its amino acids. The secondary structure describes structural properties of the molecule such as which parts of it form sheets, helices or coils. Spacial and other properties are described by the higher order structures. The classification task...
A Modified Model Predictive Control Scheme
Institute of Scientific and Technical Information of China (English)
Xiao-Bing Hu; Wen-Hua Chen
2005-01-01
In implementations of MPC (Model Predictive Control) schemes, two issues need to be addressed. One is how to enlarge the stability region as much as possible. The other is how to guarantee stability when a computational time limitation exists. In this paper, a modified MPC scheme for constrained linear systems is described. An offline LMI-based iteration process is introduced to expand the stability region. At the same time, a database of feasible control sequences is generated offline so that stability can still be guaranteed in the case of computational time limitations. Simulation results illustrate the effectiveness of this new approach.
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...... facilitates plug-and-play addition of subsystems without redesign of any controllers. The method is supported by a number of simulations featuring a three-level smart-grid power control system for a small isolated power grid....
Explicit model predictive control accuracy analysis
Knyazev, Andrew; Zhu, Peizhen; Di Cairano, Stefano
2015-01-01
Model Predictive Control (MPC) can efficiently control constrained systems in real-time applications. MPC feedback law for a linear system with linear inequality constraints can be explicitly computed off-line, which results in an off-line partition of the state space into non-overlapped convex regions, with affine control laws associated to each region of the partition. An actual implementation of this explicit MPC in low cost micro-controllers requires the data to be "quantized", i.e. repre...
Critical conceptualism in environmental modeling and prediction.
Christakos, G
2003-10-15
Many important problems in environmental science and engineering are of a conceptual nature. Research and development, however, often becomes so preoccupied with technical issues, which are themselves fascinating, that it neglects essential methodological elements of conceptual reasoning and theoretical inquiry. This work suggests that valuable insight into environmental modeling can be gained by means of critical conceptualism which focuses on the software of human reason and, in practical terms, leads to a powerful methodological framework of space-time modeling and prediction. A knowledge synthesis system develops the rational means for the epistemic integration of various physical knowledge bases relevant to the natural system of interest in order to obtain a realistic representation of the system, provide a rigorous assessment of the uncertainty sources, generate meaningful predictions of environmental processes in space-time, and produce science-based decisions. No restriction is imposed on the shape of the distribution model or the form of the predictor (non-Gaussian distributions, multiple-point statistics, and nonlinear models are automatically incorporated). The scientific reasoning structure underlying knowledge synthesis involves teleologic criteria and stochastic logic principles which have important advantages over the reasoning method of conventional space-time techniques. Insight is gained in terms of real world applications, including the following: the study of global ozone patterns in the atmosphere using data sets generated by instruments on board the Nimbus 7 satellite and secondary information in terms of total ozone-tropopause pressure models; the mapping of arsenic concentrations in the Bangladesh drinking water by assimilating hard and soft data from an extensive network of monitoring wells; and the dynamic imaging of probability distributions of pollutants across the Kalamazoo river.
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.
Reeves, E A; Barton, D C; FitzPatrick, D P; Fisher, J
1998-01-01
As new methods of sterilization of the ultra-high molecular weight polyethylene (UHMWPE) component in knee replacements are introduced, reported incidents of delamination will decrease. The prediction of plastic strain accumulation and associated failure mechanisms will then become more important in knee replacement design. The finite element analysis reported in this paper aims to advance the modelling of strain accumulation in UHMWPE over repeated gait cycles and seeks to determine the effects of the knee replacement design variables of geometry and kinematics. Material testing was performed under cyclic and creep conditions to generate the elastic, viscoplastic material model that has been used in this time-dependent analysis. Non-conforming geometries were found to accumulate plastic strains at higher rates than conforming geometries. The anatomical motion known as rollback initially produced lower strain rates, but predictions of the long-term response indicated that designs which allow rollback may produce higher strains than static designs after only about a week of loading for a knee replacement patient.
A Predictive Maintenance Model for Railway Tracks
DEFF Research Database (Denmark)
Li, Rui; Wen, Min; Salling, Kim Bang
2015-01-01
For the modern railways, maintenance is critical for ensuring safety, train punctuality and overall capacity utilization. The cost of railway maintenance in Europe is high, on average between 30,000 – 100,000 Euro per km per year [1]. Aiming to reduce such maintenance expenditure, this paper...... 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...... 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...
Bar-Kochba, Eyal; Scimone, Mark T; Estrada, Jonathan B; Franck, Christian
2016-08-02
In the United States over 1.7 million cases of traumatic brain injury are reported yearly, but predictive correlation of cellular injury to impact tissue strain is still lacking, particularly for neuronal injury resulting from compression. Given the prevalence of compressive deformations in most blunt head trauma, this information is critically important for the development of future mitigation and diagnosis strategies. Using a 3D in vitro neuronal compression model, we investigated the role of impact strain and strain rate on neuronal lifetime, viability, and pathomorphology. We find that strain magnitude and rate have profound, yet distinctively different effects on the injury pathology. While strain magnitude affects the time of neuronal death, strain rate influences the pathomorphology and extent of population injury. Cellular injury is not initiated through localized deformation of the cytoskeleton but rather driven by excess strain on the entire cell. Furthermore we find that, mechanoporation, one of the key pathological trigger mechanisms in stretch and shear neuronal injuries, was not observed under compression.
Bar-Kochba, Eyal; Scimone, Mark T.; Estrada, Jonathan B.; Franck, Christian
2016-08-01
In the United States over 1.7 million cases of traumatic brain injury are reported yearly, but predictive correlation of cellular injury to impact tissue strain is still lacking, particularly for neuronal injury resulting from compression. Given the prevalence of compressive deformations in most blunt head trauma, this information is critically important for the development of future mitigation and diagnosis strategies. Using a 3D in vitro neuronal compression model, we investigated the role of impact strain and strain rate on neuronal lifetime, viability, and pathomorphology. We find that strain magnitude and rate have profound, yet distinctively different effects on the injury pathology. While strain magnitude affects the time of neuronal death, strain rate influences the pathomorphology and extent of population injury. Cellular injury is not initiated through localized deformation of the cytoskeleton but rather driven by excess strain on the entire cell. Furthermore we find that, mechanoporation, one of the key pathological trigger mechanisms in stretch and shear neuronal injuries, was not observed under compression.
Theoretical model for forming limit diagram predictions without initial inhomogeneity
Gologanu, Mihai; Comsa, Dan Sorin; Banabic, Dorel
2013-05-01
the plane-strain case the limit-analysis model predicts almost instantaneous necking but in the next step the virtual band hardens enough to deactivate the localization condition. In this case we apply a supplementary condition for incipient necking similar to the one used in Hill's model for the second quadrant. We show that this condition is precisely the one for incipient bifurcation inside the virtual (and weaker) band. Finally we discuss some limitations, extensions and possible applications of the new necking model based on limit analysis.
Predictive Model of Radiative Neutrino Masses
Babu, K S
2013-01-01
We present a simple and predictive model of radiative neutrino masses. It is a special case of the Zee model which introduces two Higgs doublets and a charged singlet. We impose a family-dependent Z_4 symmetry acting on the leptons, which reduces the number of parameters describing neutrino oscillations to four. A variety of predictions follow: The hierarchy of neutrino masses must be inverted; the lightest neutrino mass is extremely small and calculable; one of the neutrino mixing angles is determined in terms of the other two; the phase parameters take CP-conserving values with \\delta_{CP} = \\pi; and the effective mass in neutrinoless double beta decay lies in a narrow range, m_{\\beta \\beta} = (17.6 - 18.5) meV. The ratio of vacuum expectation values of the two Higgs doublets, tan\\beta, is determined to be either 1.9 or 0.19 from neutrino oscillation data. Flavor-conserving and flavor-changing couplings of the Higgs doublets are also determined from neutrino data. The non-standard neutral Higgs bosons, if t...
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...
Effect on Prediction when Modeling Covariates in Bayesian Nonparametric Models.
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.
DEFF Research Database (Denmark)
Jørgensen, John Bagterp; Jørgensen, Sten Bay
2007-01-01
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......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...
Rubino, Cristina; Perry, Sara Jansen; Milam, Alex C; Spitzmueller, Christiane; Zapf, Dieter
2012-10-01
We propose an expanded stressor-strain model that explicitly incorporates person characteristics, the Demand-Control-Person model. This model integrates Karasek's traditional Demand-Control model with Hobfoll's (1989) Conservation of Resources theory. With participants from two organizations, we tested the moderating role of emotional stability in conjunction with two job demands (i.e., uncertainty and time pressure) and control (i.e., decision latitude) in predicting two forms of strain (i.e., job dissatisfaction and disengagement). Our findings support the expanded Demand-Control-Person model, such that a significant three-way interaction emerged for uncertainty and time pressure. As predicted, the traditional Demand-Control model only held among individuals high in emotional stability, such that low-emotional stability individuals did either not benefit as readily from decision latitude or were more susceptible to job demands when they had decision latitude. Thus, the Demand-Control-Person model may provide a more comprehensive model and consistent prediction of the effect of stressors on strain as determined by individual characteristics.
DEFF Research Database (Denmark)
El-Naaman, Salim Abdallah
, 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......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...
Two criteria for evaluating risk prediction models.
Pfeiffer, R M; Gail, M H
2011-09-01
We propose and study two criteria to assess the usefulness of models that predict risk of disease incidence for screening and prevention, or the usefulness of prognostic models for management following disease diagnosis. The first criterion, the proportion of cases followed PCF (q), is the proportion of individuals who will develop disease who are included in the proportion q of individuals in the population at highest risk. The second criterion is the proportion needed to follow-up, PNF (p), namely the proportion of the general population at highest risk that one needs to follow in order that a proportion p of those destined to become cases will be followed. PCF (q) assesses the effectiveness of a program that follows 100q% of the population at highest risk. PNF (p) assess the feasibility of covering 100p% of cases by indicating how much of the population at highest risk must be followed. We show the relationship of those two criteria to the Lorenz curve and its inverse, and present distribution theory for estimates of PCF and PNF. We develop new methods, based on influence functions, for inference for a single risk model, and also for comparing the PCFs and PNFs of two risk models, both of which were evaluated in the same validation data.
Methods for Handling Missing Variables in Risk Prediction Models
Held, Ulrike; Kessels, Alfons; Aymerich, Judith Garcia; Basagana, Xavier; ter Riet, Gerben; Moons, Karel G. M.; Puhan, Milo A.
2016-01-01
Prediction models should be externally validated before being used in clinical practice. Many published prediction models have never been validated. Uncollected predictor variables in otherwise suitable validation cohorts are the main factor precluding external validation.We used individual patient
Numerical models for the prediction of failure for multilayer fusion Al-alloy sheets
Energy Technology Data Exchange (ETDEWEB)
Gorji, Maysam; Berisha, Bekim; Hora, Pavel [ETH Zurich, Institute of Virtual Manufacturing, Zurich (Switzerland); Timm, Jürgen [Novelis Switzerland SA, 3960 Sierre (Switzerland)
2013-12-16
Initiation and propagation of cracks in monolithic and multi-layer aluminum alloys, called “Fusion”, is investigated. 2D plane strain finite element simulations are performed to model deformation due to bending and to predict failure. For this purpose, fracture strains are measured based on microscopic pictures of Nakajima specimens. In addition to, micro-structure of materials is taken into account by introducing a random grain distribution over the sheet thickness as well as a random distribution of the measured yield curve. It is shown that the performed experiments and the introduced FE-Model are appropriate methods to highlight the advantages of the Fusion material, especially for bending processes.
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.
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)....
Estimating the magnitude of prediction uncertainties for the APLE model
Models are often used to predict phosphorus (P) loss from agricultural fields. While it is commonly recognized that model predictions are inherently uncertain, few studies have addressed prediction uncertainties using P loss models. In this study, we conduct an uncertainty analysis for the Annual P ...
Prediction of Catastrophes: an experimental model
Peters, Randall D; Pomeau, Yves
2012-01-01
Catastrophes of all kinds can be roughly defined as short duration-large amplitude events following and followed by long periods of "ripening". Major earthquakes surely belong to the class of 'catastrophic' events. Because of the space-time scales involved, an experimental approach is often difficult, not to say impossible, however desirable it could be. Described in this article is a "laboratory" setup that yields data of a type that is amenable to theoretical methods of prediction. Observations are made of a critical slowing down in the noisy signal of a solder wire creeping under constant stress. This effect is shown to be a fair signal of the forthcoming catastrophe in both of two dynamical models. The first is an "abstract" model in which a time dependent quantity drifts slowly but makes quick jumps from time to time. The second is a realistic physical model for the collective motion of dislocations (the Ananthakrishna set of equations for creep). Hope thus exists that similar changes in the response to ...
Predictive modeling of low solubility semiconductor alloys
Rodriguez, Garrett V.; Millunchick, Joanna M.
2016-09-01
GaAsBi is of great interest for applications in high efficiency optoelectronic devices due to its highly tunable bandgap. However, the experimental growth of high Bi content films has proven difficult. Here, we model GaAsBi film growth using a kinetic Monte Carlo simulation that explicitly takes cation and anion reactions into account. The unique behavior of Bi droplets is explored, and a sharp decrease in Bi content upon Bi droplet formation is demonstrated. The high mobility of simulated Bi droplets on GaAsBi surfaces is shown to produce phase separated Ga-Bi droplets as well as depressions on the film surface. A phase diagram for a range of growth rates that predicts both Bi content and droplet formation is presented to guide the experimental growth of high Bi content GaAsBi films.
Distributed model predictive control made easy
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 ...
Leptogenesis in minimal predictive seesaw models
Björkeroth, Fredrik; de Anda, Francisco J.; de Medeiros Varzielas, Ivo; King, Stephen F.
2015-10-01
We estimate the Baryon Asymmetry of the Universe (BAU) arising from leptogenesis within a class of minimal predictive seesaw models involving two right-handed neutrinos and simple Yukawa structures with one texture zero. The two right-handed neutrinos are dominantly responsible for the "atmospheric" and "solar" neutrino masses with Yukawa couplings to ( ν e , ν μ , ν τ ) proportional to (0, 1, 1) and (1, n, n - 2), respectively, where n is a positive integer. The neutrino Yukawa matrix is therefore characterised by two proportionality constants with their relative phase providing a leptogenesis-PMNS link, enabling the lightest right-handed neutrino mass to be determined from neutrino data and the observed BAU. We discuss an SU(5) SUSY GUT example, where A 4 vacuum alignment provides the required Yukawa structures with n = 3, while a {{Z}}_9 symmetry fixes the relatives phase to be a ninth root of unity.
Measuring and modelling straining of Escherichia coli in saturated porous media.
Foppen, Jan Willem; van Herwerden, Manon; Schijven, Jack
2007-08-15
Though coliform bacteria are used worldwide to indicate fecal pollution of groundwater, the parameters determining the transport of Escherichia coli in aquifers are relatively unknown. We evaluated the occurrence of both straining and attachment of E. coli ATCC25922 in columns of ultra-pure, angular, saturated quartz sand. The column experiments were conducted over a wide range of porous medium sizes, column heights, input concentrations, and pore water flow velocities. Straining and attachment were examined by modelling the breakthrough curves (with HYDRUS 1D). In addition, model output was compared with measured strained and attached bacteria via column extrusion experiments (in which sand was extruded from the column and placed in excess water) and flow reversal experiments (in which the pore water flow direction was reversed, thereby dislodging strained bacteria). Our model consisted of an attachment rate coefficient and a straining rate coefficient; both of these decreased with transport distance. The straining rate coefficient also decreased in a Langmuirian way, in response to the filling of available pore space, which in turn depended on influent bacteria concentration, quartz grain diameter, and transport distance. The maximum strained fraction was 25-30% of total bacteria mass applied to the column; the maximum attached fraction was 30-35%. The fit between modelled and measured (strained and attached) bacteria masses was acceptable, as was the sensitivity of the model output to fitted parameter values. Our results lead to a new description for the time-dependent mass balance of strained bacteria, which entails using three fitting parameters. The results also imply that column experiments in combination with retention profiles (or various column lengths) are not enough to explain the retention processes in a column. Column extrusion and flow reversal experiments provide vital additional information on the occurrence and magnitude of straining. Our
Anisotropy-resolving models for predicting separation in 3--D asymmetric diffusers
Jeyapaul, Elbert; Durbin, Paul
2011-11-01
All linear eddy-viscosity models are qualitatively incorrect in predicting separation in 3-D asymmetric diffusers. The failure to predict normal stress and shear stress anisotropy at high production-dissipation ratios is the cause. The Explicit algebraic Reynolds stress model (Wallin and Johansson, 2000) predicts the mean flow field in the diffuser accurately, but not the wall pressure and Reynolds stresses. Recalibrating the coefficients of the rapid part of pressure-strain model improves the wall pressure prediction. Including the convective, diffusive, streamline curvature effects on anisotropy has not been beneficial. The model has been tested using a family of diffusers having the same nominal streamwise pressure gradient, LES data is used as a reference. Professor
Constitutive modeling of polycarbonate over a wide range of strain rates and temperatures
Wang, Haitao; Zhou, Huamin; Huang, Zhigao; Zhang, Yun; Zhao, Xiaoxuan
2016-06-01
The mechanical behavior of polycarbonate was experimentally investigated over a wide range of strain rates ( 10^{-4} to 5× 103 s^{-1}) and temperatures (293 to 353 K). Compression tests under these conditions were performed using a SHIMADZU universal testing machine and a split Hopkinson pressure bar. Falling weight impact testing was carried out on an Instron Dynatup 9200 drop tower system. The rate- and temperature-dependent deformation behavior of polycarbonate was discussed in detail. Dynamic mechanical analysis (DMA) tests were utilized to observe the glass ( α ) transition and the secondary ( β ) transition of polycarbonate. The DMA results indicate that the α and β transitions have a dramatic influence on the mechanical behavior of polycarbonate. The decompose/shift/reconstruct (DSR) method was utilized to decompose the storage modulus into the α and β components and extrapolate the entire modulus, the α-component modulus and the β-component modulus. Based on three previous models, namely, Mulliken-Boyce, G'Sell-Jonas and DSGZ, an adiabatic model is proposed to predict the mechanical behavior of polycarbonate. The model considers the contributions of both the α and β transitions to the mechanical behavior, and it has been implemented in ABAQUS/Explicit through a user material subroutine VUMAT. The model predictions are proven to essentially coincide with the experimental results during compression testing and falling weight impact testing.
Constitutive modeling of polycarbonate over a wide range of strain rates and temperatures
Wang, Haitao; Zhou, Huamin; Huang, Zhigao; Zhang, Yun; Zhao, Xiaoxuan
2017-02-01
The mechanical behavior of polycarbonate was experimentally investigated over a wide range of strain rates (10^{-4} to 5× 103 s^{-1}) and temperatures (293 to 353 K). Compression tests under these conditions were performed using a SHIMADZU universal testing machine and a split Hopkinson pressure bar. Falling weight impact testing was carried out on an Instron Dynatup 9200 drop tower system. The rate- and temperature-dependent deformation behavior of polycarbonate was discussed in detail. Dynamic mechanical analysis (DMA) tests were utilized to observe the glass (α ) transition and the secondary (β ) transition of polycarbonate. The DMA results indicate that the α and β transitions have a dramatic influence on the mechanical behavior of polycarbonate. The decompose/shift/reconstruct (DSR) method was utilized to decompose the storage modulus into the α and β components and extrapolate the entire modulus, the α-component modulus and the β-component modulus. Based on three previous models, namely, Mulliken-Boyce, G'Sell-Jonas and DSGZ, an adiabatic model is proposed to predict the mechanical behavior of polycarbonate. The model considers the contributions of both the α and β transitions to the mechanical behavior, and it has been implemented in ABAQUS/Explicit through a user material subroutine VUMAT. The model predictions are proven to essentially coincide with the experimental results during compression testing and falling weight impact testing.
The effects of aponeurosis geometry on strain injury susceptibility explored with a 3D muscle model.
Rehorn, Michael R; Blemker, Silvia S
2010-09-17
In the musculoskeletal system, some muscles are injured more frequently than others. For example, the biceps femoris longhead (BFLH) is the most commonly injured hamstring muscle. It is thought that acute injuries result from large strains within the muscle tissue, but the mechanism behind this type of strain injury is still poorly understood. The purpose of this study was to build computational models to analyze the stretch distributions within the BFLH muscle and to explore the effects of aponeurosis geometry on the magnitude and location of peak stretches within the model. We created a three-dimensional finite element (FE) model of the BFLH based on magnetic resonance (MR) images. We also created a series of simplified models with a similar geometry to the MR-based model. We analyzed the stretches predicted by the MR-based model during lengthening contractions to determine the region of peak local fiber stretch. The peak along-fiber stretch was 1.64 and was located adjacent to the proximal myotendinous junction (MTJ). In contrast, the average along-fiber stretch across all the muscle tissue was 0.95. By analyzing the simple models, we found that varying the dimensions of the aponeuroses (width, length, and thickness) had a substantial impact on the location and magnitude of peak stretches within the muscle. Specifically, the difference in widths between the proximal and distal aponeurosis in the BFLH contributed most to the location and magnitude of peak stretch, as decreasing the proximal aponeurosis width by 80% increased peak average stretches along the proximal MTJ by greater than 60% while slightly decreasing stretches along the distal MTJ. These results suggest that the aponeurosis morphology of the BFLH plays a significant role in determining stretch distributions throughout the muscle. Furthermore, this study introduces the new hypothesis that aponeurosis widths may be important in determining muscle injury susceptibility.
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.
Neural network modeling for the prediction of texture evolution of hot deformed aluminum alloys
Barat, P.; Withers, P. J.
2003-12-01
Commercial aluminum rolling mills operate under very restricted thermomechanical conditions determined from experience and plant trials. In this paper we report results for four-stand tandem mill rolling simulations within and beyond the thermomechanical conditions typical of a rolling mill by plane strain compression (PSC) testing to assess the effect of deformed conditions on the texture of the hot deformed aluminum strip after annealing. A neural network modeling study was then initiated to find a predictive relationship between the observed texture and the thermomechanical parameters of strain, strain rate, and temperature. The model suggested that temperature is the prime variable that influences texture. Such models can be used to evaluate optimal strategies for the control of process parameters of a four-stand tandem mill.
Comparing model predictions for ecosystem-based management
DEFF Research Database (Denmark)
Jacobsen, Nis Sand; Essington, Timothy E.; Andersen, Ken Haste
2016-01-01
Ecosystem modeling is becoming an integral part of fisheries management, but there is a need to identify differences between predictions derived from models employed for scientific and management purposes. Here, we compared two models: a biomass-based food-web model (Ecopath with Ecosim (Ew......E)) and a size-structured fish community model. The models were compared with respect to predicted ecological consequences of fishing to identify commonalities and differences in model predictions for the California Current fish community. We compared the models regarding direct and indirect responses to fishing...... on one or more species. The size-based model predicted a higher fishing mortality needed to reach maximum sustainable yield than EwE for most species. The size-based model also predicted stronger top-down effects of predator removals than EwE. In contrast, EwE predicted stronger bottom-up effects...
SEMICONDUCTOR DEVICES Nanoscale strained-Si MOSFET physics and modeling approaches: a review
Chaudhry, Amit; Roy, J. N.; Joshi, Garima
2010-10-01
An attempt has been made to give a detailed review of strained silicon technology. Various device models have been studied that consider the effect of strain on the devices, and comparisons have been drawn. A review of some modeling issues in strained silicon technology has also been outlined. The review indicates that this technology is very much required in nanoscale MOSFETs due to its several potential benefits, and there is a strong need for an analytical model which describes the complete physics of the strain technology.
Measurement and Modeling of Sorption-Induced Strain and Permeability Changes in Coal
Energy Technology Data Exchange (ETDEWEB)
Eric P. Robertson
2005-10-01
Strain caused by the adsorption of gases was measured in samples of subbituminous coal from the Powder River basin of Wyoming, U.S.A., and high-volatile bituminous coal from the Uinta-Piceance basin of Utah, U.S.A. using a newly developed strain measurement apparatus. The apparatus can be used to measure strain on multiple small coal samples based on the optical detection of the longitudinal strain. The swelling and shrinkage (strain) in the coal samples resulting from the adsorption of carbon dioxide, nitrogen, methane, helium, and a mixture of gases was measured. Sorption-induced strain processes were shown to be reversible and easily modeled with a Langmuir-type equation. Extended Langmuir theory was applied to satisfactorily model strain caused by the adsorption of gas mixtures using the pure gas Langmuir strain constants. The amount of time required to obtain accurate strain data was greatly reduced compared to other strain measurement methods. Sorption-induced changes in permeability were also measured as a function of pres-sure. Cleat compressibility was found to be variable, not constant. Calculated variable cleat-compressibility constants were found to correlate well with previously published data for other coals. During permeability tests, sorption-induced matrix shrinkage was clearly demonstrated by higher permeability values at lower pore pressures while holding overburden pressure constant. Measured permeability data were modeled using three dif-ferent permeability models from the open literature that take into account sorption-induced matrix strain. All three models poorly matched the measured permeability data because they overestimated the impact of measured sorption-induced strain on permeabil-ity. However, by applying an experimentally derived expression to the measured strain data that accounts for the confining overburden pressure, pore pressure, coal type, and gas type, the permeability models were significantly improved.
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.
Remaining Useful Lifetime (RUL - Probabilistic Predictive Model
Directory of Open Access Journals (Sweden)
Ephraim Suhir
2011-01-01
Full Text Available Reliability evaluations and assurances cannot be delayed until the device (system is fabricated and put into operation. Reliability of an electronic product should be conceived at the early stages of its design; implemented during manufacturing; evaluated (considering customer requirements and the existing specifications, by electrical, optical and mechanical measurements and testing; checked (screened during manufacturing (fabrication; and, if necessary and appropriate, maintained in the field during the product’s operation Simple and physically meaningful probabilistic predictive model is suggested for the evaluation of the remaining useful lifetime (RUL of an electronic device (system after an appreciable deviation from its normal operation conditions has been detected, and the increase in the failure rate and the change in the configuration of the wear-out portion of the bathtub has been assessed. The general concepts are illustrated by numerical examples. The model can be employed, along with other PHM forecasting and interfering tools and means, to evaluate and to maintain the high level of the reliability (probability of non-failure of a device (system at the operation stage of its lifetime.
A Predictive Model of Geosynchronous Magnetopause Crossings
Dmitriev, A; Chao, J -K
2013-01-01
We have developed a model predicting whether or not the magnetopause crosses geosynchronous orbit at given location for given solar wind pressure Psw, Bz component of interplanetary magnetic field (IMF) and geomagnetic conditions characterized by 1-min SYM-H index. The model is based on more than 300 geosynchronous magnetopause crossings (GMCs) and about 6000 minutes when geosynchronous satellites of GOES and LANL series are located in the magnetosheath (so-called MSh intervals) in 1994 to 2001. Minimizing of the Psw required for GMCs and MSh intervals at various locations, Bz and SYM-H allows describing both an effect of magnetopause dawn-dusk asymmetry and saturation of Bz influence for very large southward IMF. The asymmetry is strong for large negative Bz and almost disappears when Bz is positive. We found that the larger amplitude of negative SYM-H the lower solar wind pressure is required for GMCs. We attribute this effect to a depletion of the dayside magnetic field by a storm-time intensification of t...
Predictive modeling for EBPC in EBDW
Zimmermann, Rainer; Schulz, Martin; Hoppe, Wolfgang; Stock, Hans-Jürgen; Demmerle, Wolfgang; Zepka, Alex; Isoyan, Artak; Bomholt, Lars; Manakli, Serdar; Pain, Laurent
2009-10-01
We demonstrate a flow for e-beam proximity correction (EBPC) to e-beam direct write (EBDW) wafer manufacturing processes, demonstrating a solution that covers all steps from the generation of a test pattern for (experimental or virtual) measurement data creation, over e-beam model fitting, proximity effect correction (PEC), and verification of the results. We base our approach on a predictive, physical e-beam simulation tool, with the possibility to complement this with experimental data, and the goal of preparing the EBPC methods for the advent of high-volume EBDW tools. As an example, we apply and compare dose correction and geometric correction for low and high electron energies on 1D and 2D test patterns. In particular, we show some results of model-based geometric correction as it is typical for the optical case, but enhanced for the particularities of e-beam technology. The results are used to discuss PEC strategies, with respect to short and long range effects.
Lebert, I; Robles-Olvera, V; Lebert, A
2000-10-01
Three models for one rapid and one slow growing strain of Pseudomonas fragi and one slow growing strain of P. fluorescens were developed in a meat broth; they were designed to take account of variations in growth and to provide a growth response interval. These models, and another for Listeria monocytogenes (Lm14 model), were used to predict the growth of spoilage Pseudomonas spp. and pathogenic Listeria in meat products. The Pseudomonas and Listeria models provided satisfactory predictions concerning inoculated strains grown in decontaminated beef meat. It was also possible to use the Pseudomonas models to predict the growth of the natural flora (mainly Pseudomonas spp.) of refrigerated meat stored under aerobic conditions. In experiments with mixed populations, three situations were observed: (1) in decontaminated meat, L. monocytogenes inoculated alone grew well at 6 degrees C, and this result was correctly predicted by the model; (2) in decontaminated meat inoculated with Listeria and Pseudomonas strains, L. innocua grew well and was not affected by the presence of Pseudomonas, and the growth of both organisms was correctly predicted by the models; (3) in naturally contaminated meat inoculated with Listeria, the strain did not grow until Pseudomonas had reached the stationary phase. The models satisfactorily predicted the growth of Pseudomonas spp. but not that of Listeria. In conclusion, the Lm14 model cannot be used for refrigerated meat stored aerobically as the results suggest a 'fail-safe' level which may be too high: meat had already reached a spoilage state even though no increase in the level of Listeria was observed. The Pseudomonas models accurately predicted the growth of naturally occurring Pseudomonas spp.
Institute of Scientific and Technical Information of China (English)
Aizhao Zhou; Tinghao Lu
2009-01-01
The behavior of soil-structure interface plays a major role in the definition of soil-structure interaction. In this paper a bi-potential surface elasto-plastic model for soil-structure interface is proposed in order to describe the interface deformation behavior, including strain softening and normal dilatancy. The model is formulated in the framework of generalized potential theory, in which the soil-structure interface problem is regard as a two-dimensional mathematical problem in stress field, and plastic state equations are used to replace the traditional field surface. The relation curves of shear stress and tangential strain are fitted by a piecewise function composed by hyperbolic functions and hyperbolic secant functions, while the relation curves of normal strain and tangential strain are fitted by another piecewise function composed by quadratic functions and hyperbolic secant functions. The approach proposed has the advantage of deriving an elasto-plastic constitutive matrix without postulating the plastic potential functions and yield surface. Moreover, the mathematical principle is clear, and the entire model parameters can be identified by experimental tests. Finally, the predictions of the model have been compared with experimental results obtained from simple shear tests under normal stresses, and results show the model is reasonable and practical.
Microstructurally Based Prediction of High Strain Failure Modes in Crystalline Solids
2016-07-05
Investigation of the High Strain-Rate Behavior of High Strength Aluminum Alloys, The Metals Society, Orlando, FL, March, 2012 (c) Presentations ...Number of Presentations : Non Peer-Reviewed Conference Proceeding publications (other than abstracts): Received Paper TOTAL: Received Paper TOTAL: Number of...subjected to extreme changes in temperature, pressure , and strain-rates. A special focus is on high strength aluminum and titanium alloys due to
Model for predicting mountain wave field uncertainties
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
Introduction to Displacements, Strains and Stresses in a 1D CVM-model
DEFF Research Database (Denmark)
Frandsen, Jens Ole
This lecture note contains an introduction to displacements, strains and stresses in an one-dimensional sg-FVM model of a tensile test bar.......This lecture note contains an introduction to displacements, strains and stresses in an one-dimensional sg-FVM model of a tensile test bar....
A work-hardening and softening constitutive model for sand: modified plastic strain energy approach
Institute of Scientific and Technical Information of China (English)
Fangle Peng; M.S.A. Siddiquee; Shaoming Liao
2005-01-01
The paper describes an energy-based constitutive model for sand, which is modified based on the modified plastic strain energy approach, represented by a unique relationship between the modified plastic strain energy and a stress parameter, independent of stress history. The modified plastic strain energy approach was developed based on results from a series of drained plastic strain compression tests along various stress paths on saturated dense Toyoura sand with accurate stress and strain measurements. The proposed model is coupled with an isotropically work-hardening and softening, non-associtated, elasto-plastic material description. The constitutive model concerns the inherent and stress systeminduced cross-anisotropic elastic deformation properties of sand. It is capable of simulating the deformation characteristics of stress history and stress path, the effects of pressure level, anisotropic strength and void ratio, and the strain localization.
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.
Energy Technology Data Exchange (ETDEWEB)
Rodriguez-MartInez R; Lugo-Gonzalez E; Urriolagoitia-Calderon G; Urriolagoitia-Sosa G; Hernandez-Gomez L H; Romero-Angeles B; Torres-San Miguel Ch, E-mail: rrodriguezm@ipn.mx, E-mail: urrio332@hotmail.com, E-mail: guiurri@hotmail.com, E-mail: luishector56@hotmail.com, E-mail: romerobeatriz98@hotmail.com, E-mail: napor@hotmail.com [INSTITUTO POLITECNICO NACIONAL Seccion de Estudios de Posgrado e Investigacion (SEPI), Escuela Superior de Ingenieria Mecanica y Electrica (ESIME), Edificio 5. 2do Piso, Unidad Profesional Adolfo Lopez Mateos ' Zacatenco' Col. Lindavista, C.P. 07738, Mexico, D.F. (Mexico)
2011-07-19
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({sigma}{sup 2}{sub x} + {sigma}{sup 2}{sub y}) - {nu}/E({sigma}{sub x}{sigma}{sub y})]dV (1). From equation (1) a mathematical deduction to solve in terms of {theta} of this case was developed employing Genetic Algorithms, where {theta} 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.
RFI modeling and prediction approach for SATOP applications: RFI prediction models
Nguyen, Tien M.; Tran, Hien T.; Wang, Zhonghai; Coons, Amanda; Nguyen, Charles C.; Lane, Steven A.; Pham, Khanh D.; Chen, Genshe; Wang, Gang
2016-05-01
This paper describes a technical approach for the development of RFI prediction models using carrier synchronization loop when calculating Bit or Carrier SNR degradation due to interferences for (i) detecting narrow-band and wideband RFI signals, and (ii) estimating and predicting the behavior of the RFI signals. The paper presents analytical and simulation models and provides both analytical and simulation results on the performance of USB (Unified S-Band) waveforms in the presence of narrow-band and wideband RFI signals. The models presented in this paper will allow the future USB command systems to detect the RFI presence, estimate the RFI characteristics and predict the RFI behavior in real-time for accurate assessment of the impacts of RFI on the command Bit Error Rate (BER) performance. The command BER degradation model presented in this paper also allows the ground system operator to estimate the optimum transmitted SNR to maintain a required command BER level in the presence of both friendly and un-friendly RFI sources.
Prediction models : the right tool for the right problem
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 unders
A new model for the life prediction of GH4133 under TMF conditions
Institute of Scientific and Technical Information of China (English)
无
2002-01-01
Thermal mechanical cyclic strain tests were carried out under in-phase and out-of-phase conditions on a Nickel-base Superalloy GH4133 in the temperature range of 571-823℃. Based on analyzing the present models of TMF (thermal mechanical fatigue) life prediction, a new model for predicting nickel-base superalloy TMF lifetime was proposed.TMF life of superalloy GH4133 was calculated accurately based on the new model. Experimental TMF life has been compared with the calculatedresults and all results fall in the scatter band of 1.5. The calculating results show that the new model is not only simple, but also precise. This model will play great roles in life prediction of the metal materials and the engineering components subjected to non-isothermal service conditions.
Regression Model Term Selection for the Analysis of Strain-Gage Balance Calibration Data
Ulbrich, Norbert Manfred; Volden, Thomas R.
2010-01-01
The paper discusses the selection of regression model terms for the analysis of wind tunnel strain-gage balance calibration data. Different function class combinations are presented that may be used to analyze calibration data using either a non-iterative or an iterative method. The role of the intercept term in a regression model of calibration data is reviewed. In addition, useful algorithms and metrics originating from linear algebra and statistics are recommended that will help an analyst (i) to identify and avoid both linear and near-linear dependencies between regression model terms and (ii) to make sure that the selected regression model of the calibration data uses only statistically significant terms. Three different tests are suggested that may be used to objectively assess the predictive capability of the final regression model of the calibration data. These tests use both the original data points and regression model independent confirmation points. Finally, data from a simplified manual calibration of the Ames MK40 balance is used to illustrate the application of some of the metrics and tests to a realistic calibration data set.
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.
Predictability of the Indian Ocean Dipole in the coupled models
Liu, Huafeng; Tang, Youmin; Chen, Dake; Lian, Tao
2017-03-01
In this study, the Indian Ocean Dipole (IOD) predictability, measured by the Indian Dipole Mode Index (DMI), is comprehensively examined at the seasonal time scale, including its actual prediction skill and potential predictability, using the ENSEMBLES multiple model ensembles and the recently developed information-based theoretical framework of predictability. It was found that all model predictions have useful skill, which is normally defined by the anomaly correlation coefficient larger than 0.5, only at around 2-3 month leads. This is mainly because there are more false alarms in predictions as leading time increases. The DMI predictability has significant seasonal variation, and the predictions whose target seasons are boreal summer (JJA) and autumn (SON) are more reliable than that for other seasons. All of models fail to predict the IOD onset before May and suffer from the winter (DJF) predictability barrier. The potential predictability study indicates that, with the model development and initialization improvement, the prediction of IOD onset is likely to be improved but the winter barrier cannot be overcome. The IOD predictability also has decadal variation, with a high skill during the 1960s and the early 1990s, and a low skill during the early 1970s and early 1980s, which is very consistent with the potential predictability. The main factors controlling the IOD predictability, including its seasonal and decadal variations, are also analyzed in this study.
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.
Micromechanical modeling of damage in periodic composites using strain gradient plasticity
DEFF Research Database (Denmark)
Azizi, Reza
2012-01-01
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...
Nonconvex model predictive control for commercial refrigeration
Gybel Hovgaard, Tobias; Boyd, Stephen; Larsen, Lars F. S.; Bagterp Jørgensen, John
2013-08-01
We consider the control of a commercial multi-zone refrigeration system, consisting of several cooling units that share a common compressor, and is used to cool multiple areas or rooms. In each time period we choose cooling capacity to each unit and a common evaporation temperature. The goal is to minimise the total energy cost, using real-time electricity prices, while obeying temperature constraints on the zones. We propose a variation on model predictive control to achieve this goal. When the right variables are used, the dynamics of the system are linear, and the constraints are convex. The cost function, however, is nonconvex due to the temperature dependence of thermodynamic efficiency. To handle this nonconvexity we propose a sequential convex optimisation method, which typically converges in fewer than 5 or so iterations. We employ a fast convex quadratic programming solver to carry out the iterations, which is more than fast enough to run in real time. We demonstrate our method on a realistic model, with a full year simulation and 15-minute time periods, using historical electricity prices and weather data, as well as random variations in thermal load. These simulations show substantial cost savings, on the order of 30%, compared to a standard thermostat-based control system. Perhaps more important, we see that the method exhibits sophisticated response to real-time variations in electricity prices. This demand response is critical to help balance real-time uncertainties in generation capacity associated with large penetration of intermittent renewable energy sources in a future smart grid.
Leptogenesis in minimal predictive seesaw models
Energy Technology Data Exchange (ETDEWEB)
Björkeroth, Fredrik [School of Physics and Astronomy, University of Southampton,Southampton, SO17 1BJ (United Kingdom); Anda, Francisco J. de [Departamento de Física, CUCEI, Universidad de Guadalajara,Guadalajara (Mexico); Varzielas, Ivo de Medeiros; King, Stephen F. [School of Physics and Astronomy, University of Southampton,Southampton, SO17 1BJ (United Kingdom)
2015-10-15
We estimate the Baryon Asymmetry of the Universe (BAU) arising from leptogenesis within a class of minimal predictive seesaw models involving two right-handed neutrinos and simple Yukawa structures with one texture zero. The two right-handed neutrinos are dominantly responsible for the “atmospheric” and “solar” neutrino masses with Yukawa couplings to (ν{sub e},ν{sub μ},ν{sub τ}) proportional to (0,1,1) and (1,n,n−2), respectively, where n is a positive integer. The neutrino Yukawa matrix is therefore characterised by two proportionality constants with their relative phase providing a leptogenesis-PMNS link, enabling the lightest right-handed neutrino mass to be determined from neutrino data and the observed BAU. We discuss an SU(5) SUSY GUT example, where A{sub 4} vacuum alignment provides the required Yukawa structures with n=3, while a ℤ{sub 9} symmetry fixes the relatives phase to be a ninth root of unity.
QSPR Models for Octane Number Prediction
Directory of Open Access Journals (Sweden)
Jabir H. Al-Fahemi
2014-01-01
Full Text Available Quantitative structure-property relationship (QSPR is performed as a means to predict octane number of hydrocarbons via correlating properties to parameters calculated from molecular structure; such parameters are molecular mass M, hydration energy EH, boiling point BP, octanol/water distribution coefficient logP, molar refractivity MR, critical pressure CP, critical volume CV, and critical temperature CT. Principal component analysis (PCA and multiple linear regression technique (MLR were performed to examine the relationship between multiple variables of the above parameters and the octane number of hydrocarbons. The results of PCA explain the interrelationships between octane number and different variables. Correlation coefficients were calculated using M.S. Excel to examine the relationship between multiple variables of the above parameters and the octane number of hydrocarbons. The data set was split into training of 40 hydrocarbons and validation set of 25 hydrocarbons. The linear relationship between the selected descriptors and the octane number has coefficient of determination (R2=0.932, statistical significance (F=53.21, and standard errors (s =7.7. The obtained QSPR model was applied on the validation set of octane number for hydrocarbons giving RCV2=0.942 and s=6.328.
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.
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...
Webber, Judith B; Noonan, Mike; Pasco, Neil F; Hay, Joanne M
2011-01-01
The measured response of rapid biochemical oxygen demand (BOD) biosensors is often not identical to those measured using the conventional 5-day BOD assay. This paper highlights the efficacy of using both glucose-glutamic acid (GGA) and Organisation for Economic Cooperation and Development (OECD) BOD standards as a rapid screen for microorganisms most likely to reliably predict real effluent BODs when used in rapid BOD devices. Using these two synthetic BOD standards, a microorganism was identified that produced comparable BOD response profiles for two assays, the MICREDOX® assay and the conventional 5-day BOD(5) test. A factorial experimental design systematically evaluated the impact of four factors (microbial strain, growth media composition, media strength, and microbial growth phase) on the BOD response profiles using GGA and OECD synthetic standard substrates. An outlier was identified that showed an improved correlation between the MICREDOX® BOD (BOD(sens)) and BOD(5) assays for both the synthetic standards and for real wastewater samples. Microbial strain was the dominant factor influencing BOD(sens) values, with Arthrobacter globiformis single cultures clearly demonstrating superior rapid BOD(sens) response profiles for both synthetic and real waste samples. It was the only microorganism to approach the BOD(5) response for the OECD substrate (171 mg O(2)L(-1)), and also reported BOD values for real waste samples that were comparable to those produced by the BOD(5) test, including discriminating between filtered and unfiltered samples.
Kusunose, Kenya; Torii, Yuta; Yamada, Hirotsugu; Nishio, Susumu; Hirata, Yukina; Seno, Hiromitsu; Saijo, Yoshihito; Ise, Takayuki; Yamaguchi, Koji; Tobiume, Takeshi; Yagi, Shusuke; Soeki, Takeshi; Wakatsuki, Tetsuzo; Sata, Masataka
2017-02-01
This study sought to assess the time course of presumptive tachycardia-induced cardiomyopathy and the predictors of left ventricular (LV) functional recovery in such patients. Tachycardia-induced cardiomyopathy is a potentially reversible cardiomyopathy with effective treatment of the tachyarrhythmia. However, cases without improvement of LV systolic function were found occasionally. The diagnosis of tachycardia-induced cardiomyopathy can be challenging, and the role of echocardiographic imaging in the prediction of LV functional recovery is limited. LV segmental longitudinal strains (LS) were evaluated by 2-dimensional speckle tracking in 71 consecutive patients (65 ± 16 years; 61% men) with tachyarrhythmia and reduced left ventricular ejection fraction (LVEF) without any other known cardiovascular disease, and 30 age and sex-matched control subjects. Relative apical LS ratio (RALSR) was defined using the equation: average apical LS / (average basal LS + average mid LS) as a marker of strain distribution. Compared with control subjects, patients with tachyarrhythmia had significantly lower global LS. Improvement in LVEF within 6 months after treatment of index arrhythmia was observed in 41 patients, and LVEF did not improve in 30 patients. In univariate analysis, lower LVEF at baseline (hazard ratio: 0.59 per 1 SD; p = 0.04) and higher RALSR (hazard ratio: 11.2 per 1 SD; p < 0.001) were associated with no recovery in LVEF during follow-up. In a multivariate logistic regression model, the significant predictor of LV systolic functional recovery was RALSR (hazard ratio: 22.9 per 1 SD; p = 0.001). A RALSR of 0.61 was sensitive (71%) and specific (90%) in differentiating LV systolic functional recovery (area under the curve: 0.88). The RALSR was associated with LV systolic functional recovery. This information might be useful for clinical evaluation and follow-up in patients with reduced LVEF. Copyright © 2017 American College of Cardiology Foundation
Experimentation and Modeling of the Tension Behavior of Polycarbonate at High Strain Rates
Directory of Open Access Journals (Sweden)
Yingjie Xu
2016-02-01
Full Text Available A comprehensive understanding of the mechanical behavior of polycarbonate (PC under high-rate loadings is essential for better design of PC products. In this work, the mechanical behavior of PC is studied during tensile loading at high strain rates, using a split Hopkinson tension bar (SHTB. A modified experimental technique based on the SHTB is proposed to perform the tension testing on PC at rates exceeding 1000 s−1. The effect of strain rates on the tension stress–strain law of PC is investigated over a wide range of strain rates (0.0005–4500 s−1. Based on the experiments, a physically based constitutive model is developed to describe the strain rate dependent tensile stress–strain law. The high rate tensile deformation mechanics of PC are further studied via finite element simulations using the LSDYNA code together with the developed constitutive model.
Energy Technology Data Exchange (ETDEWEB)
Kao, Kuo-Hsing; Meyer, Kristin De [imec, Kapeldreef 75, 3001 Leuven (Belgium); Department of Electrical Engineering, KU Leuven, Leuven (Belgium); Verhulst, Anne S.; Rooyackers, Rita; Douhard, Bastien; Delmotte, Joris; Bender, Hugo; Richard, Olivier; Vandervorst, Wilfried; Simoen, Eddy; Hikavyy, Andriy; Loo, Roger; Arstila, Kai; Collaert, Nadine; Thean, Aaron; Heyns, Marc M. [imec, Kapeldreef 75, 3001 Leuven (Belgium)
2014-12-07
Band-to-band tunneling parameters of strained indirect bandgap materials are not well-known, hampering the reliability of performance predictions of tunneling devices based on these materials. The nonlocal band-to-band tunneling model for compressively strained SiGe is calibrated based on a comparison of strained SiGe p-i-n tunneling diode measurements and doping-profile-based diode simulations. Dopant and Ge profiles of the diodes are determined by secondary ion mass spectrometry and capacitance-voltage measurements. Theoretical parameters of the band-to-band tunneling model are calculated based on strain-dependent properties such as bandgap, phonon energy, deformation-potential-based electron-phonon coupling, and hole effective masses of strained SiGe. The latter is determined with a 6-band k·p model. The calibration indicates an underestimation of the theoretical electron-phonon coupling with nearly an order of magnitude. Prospects of compressively strained SiGe tunneling transistors are made by simulations with the calibrated model.
Cano-García, Liliana; Rivera-Jiménez, Silvia; Belloch, Carmela; Flores, Mónica
2014-05-15
The ability of seven Debaryomyces hansenii strains to generate aroma compounds in a fermented sausage model system was evaluated. The presence of the yeast, in the inoculated models, was confirmed by PCR amplification of M13 minisatellite. Volatile compounds production was analysed using Solid Phase Micro-Extraction and gas chromatography/mass spectrometry. Forty volatile compounds were detected, quantified and their odour activity values (OAVs) calculated. All volatile compounds increased during time in the inoculated models although significant differences were found amongst them. Ester and sulphur production was strongly dependent on the strain inoculated. D. hansenii P2 and M6 strains were the highest producers of sulphur compounds where dimethyl disulphide and dimethyl trisulfide were the most prominent aroma components identified by their OAVs whereas, M4 showed the highest OAVs for ester compounds followed by the P2 strain. The meat model system has been useful to show the real ability of yeast strains to produce aroma compounds.
Anisotropic Behaviour of Sand in the Small Strain Domain. Experimental Measurements and Modelling
Ezaoui, A.; Di Benedetto, H.; Van Bang, D.
This paper deals with the initial and loading path induced anisotropy for a sub angular granular material, Hostun sand. The "quasi" elastic properties observed in the small strain domain (hypoelastic model, called DBGS model, which takes into account the stress induced anisotropy, is firstly described. This model is not sufficient to properly describe experimental results at isotropic stress state as well as thus obtained during deviatoric stress path for medium and large strain. Then, an extension of the model is proposed, called DBGSP model, where strain induced anisotropy is taken into account. The concept of virtual strain induced anisotropy is introduced in this rheological hypoelastic model developed at ENTPE, and the ability of the model to foresee experimental behaviour is checked.
Predictability in models of the atmospheric circulation.
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 are. The
Constitutive Model for Multiaxial Ratcheting Predictions of Cyclic Softening Weld Metal
Institute of Scientific and Technical Information of China (English)
GAO Hong; CHEN Xu; JIAO Rong
2005-01-01
A series of fully reversed axial, torsional strain-controlled cyclic tests and two multiaxial ratcheting tests were conducted on weld metal specimens using an Instron8521 tension-torsional servo-controlled testing machine. The weld metal showed clear cyclic softening under axial, torsional and multiaxial loading. A modified kinematic hardening rule was proposed in which a multiaxial-loading-dependent parameter incorporated the radial evanescence term of the Burlet-Cailletaud mode with the Ohno-Wang kinematic hardening rule to predict the multiaxial ratcheting effects. The introduction of yield stress evolved with accumulated plasticity strain enables the model to predict cyclic plasticity behavior of cyclic softening or cyclic hardening materials. Thus modified model considers the isotropic hardening as well as kinematic hardening of yield surface, and it can present description of plasticity behavior and ratcheting of cyclic softening and cyclic hardening materials well under multiaxial loading.
Allostasis: a model of predictive regulation.
Sterling, Peter
2012-04-12
The premise of the standard regulatory model, "homeostasis", is flawed: the goal of regulation is not to preserve constancy of the internal milieu. Rather, it is to continually adjust the milieu to promote survival and reproduction. Regulatory mechanisms need to be efficient, but homeostasis (error-correction by feedback) is inherently inefficient. Thus, although feedbacks are certainly ubiquitous, they could not possibly serve as the primary regulatory mechanism. A newer model, "allostasis", proposes that efficient regulation requires anticipating needs and preparing to satisfy them before they arise. The advantages: (i) errors are reduced in magnitude and frequency; (ii) response capacities of different components are matched -- to prevent bottlenecks and reduce safety factors; (iii) resources are shared between systems to minimize reserve capacities; (iv) errors are remembered and used to reduce future errors. This regulatory strategy requires a dedicated organ, the brain. The brain tracks multitudinous variables and integrates their values with prior knowledge to predict needs and set priorities. The brain coordinates effectors to mobilize resources from modest bodily stores and enforces a system of flexible trade-offs: from each organ according to its ability, to each organ according to its need. The brain also helps regulate the internal milieu by governing anticipatory behavior. Thus, an animal conserves energy by moving to a warmer place - before it cools, and it conserves salt and water by moving to a cooler one before it sweats. The behavioral strategy requires continuously updating a set of specific "shopping lists" that document the growing need for each key component (warmth, food, salt, water). These appetites funnel into a common pathway that employs a "stick" to drive the organism toward filling the need, plus a "carrot" to relax the organism when the need is satisfied. The stick corresponds broadly to the sense of anxiety, and the carrot broadly to
Candan, Ozkan; Ozdemir, Nihal; Aung, Soe Moe; Dogan, Cem; Karabay, Can Yucel; Gecmen, Cetin; Omaygenç, Onur; Güler, Ahmet
2013-10-01
Postoperative atrial fibrillation (POAF) is common after cardiac surgery and is associated with increased morbidity, mortality, and prolonged hospital stay. Speckle tracking echocardiography (STE) has been applied recently for evaluation of LA function. The purpose of this study was to examine whether left atrial longitudinal strain measured by STE is a predictor for the development of POAF following mitral valve surgery for severe mitral regurgitation. We studied 53 patients undergoing mitral valve surgery in sinus rhythm at the time of surgery. Echocardiography with evaluation of LA strain by STE was performed. Detection of POAF was based on documentation of AF episodes by continuous telemetry throughout hospitalization. Patients who did not develop POAF were taken as group 1 and those who had POAF constituted group 2. The echocardiographic and clinical predictors of POAF were investigated. POAF occurred in 28.3% of subjects. Mean age, LAVi and BNP were found higher in group 2 while peak atrial longitudinal strain (PALS) (13.9 ± 3.8% vs. 24.8 ± 7.3%; P longitudinal strain was found to predict POAF in patients undergoing mitral valve surgery. It could be used to better identify patients at greater risk of developing POAF, and thus to guide in risk stratification and to take appropriate intensive prophylactic therapy.
Ko, William L.; Fleischer, Van Tran
2012-01-01
New first- and second-order displacement transfer functions have been developed for deformed shape calculations of nonuniform cross-sectional beam structures such as aircraft wings. The displacement transfer functions are expressed explicitly in terms of beam geometrical parameters and surface strains (uniaxial bending strains) obtained at equally spaced strain stations along the surface of the beam structure. By inputting the measured or analytically calculated surface strains into the displacement transfer functions, one could calculate local slopes, deflections, and cross-sectional twist angles of the nonuniform beam structure for mapping the overall structural deformed shapes for visual display. The accuracy of deformed shape calculations by the first- and second-order displacement transfer functions are determined by comparing these values to the analytically predicted values obtained from finite element analyses. This comparison shows that the new displacement transfer functions could quite accurately calculate the deformed shapes of tapered cantilever tubular beams with different tapered angles. The accuracy of the present displacement transfer functions also are compared to those of the previously developed displacement transfer functions.
Biocomputational prediction of non-coding RNAs in model cyanobacteria
Directory of Open Access Journals (Sweden)
Ude Susanne
2009-03-01
Full Text Available Abstract Background In bacteria, non-coding RNAs (ncRNA are crucial regulators of gene expression, controlling various stress responses, virulence, and motility. Previous work revealed a relatively high number of ncRNAs in some marine cyanobacteria. However, for efficient genetic and biochemical analysis it would be desirable to identify a set of ncRNA candidate genes in model cyanobacteria that are easy to manipulate and for which extended mutant, transcriptomic and proteomic data sets are available. Results Here we have used comparative genome analysis for the biocomputational prediction of ncRNA genes and other sequence/structure-conserved elements in intergenic regions of the three unicellular model cyanobacteria Synechocystis PCC6803, Synechococcus elongatus PCC6301 and Thermosynechococcus elongatus BP1 plus the toxic Microcystis aeruginosa NIES843. The unfiltered numbers of predicted elements in these strains is 383, 168, 168, and 809, respectively, combined into 443 sequence clusters, whereas the numbers of individual elements with high support are 94, 56, 64, and 406, respectively. Removing also transposon-associated repeats, finally 78, 53, 42 and 168 sequences, respectively, are left belonging to 109 different clusters in the data set. Experimental analysis of selected ncRNA candidates in Synechocystis PCC6803 validated new ncRNAs originating from the fabF-hoxH and apcC-prmA intergenic spacers and three highly expressed ncRNAs belonging to the Yfr2 family of ncRNAs. Yfr2a promoter-luxAB fusions confirmed a very strong activity of this promoter and indicated a stimulation of expression if the cultures were exposed to elevated light intensities. Conclusion Comparison to entries in Rfam and experimental testing of selected ncRNA candidates in Synechocystis PCC6803 indicate a high reliability of the current prediction, despite some contamination by the high number of repetitive sequences in some of these species. In particular, we
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...
Required Collaborative Work in Online Courses: A Predictive Modeling Approach
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…
A prediction model for assessing residential radon concentration in Switzerland
Hauri, D.D.; Huss, A.; Zimmermann, F.; Kuehni, C.E.; Roosli, M.
2012-01-01
Indoor radon is regularly measured in Switzerland. However, a nationwide model to predict residential radon levels has not been developed. The aim of this study was to develop a prediction model to assess indoor radon concentrations in Switzerland. The model was based on 44,631 measurements from the
Institute of Scientific and Technical Information of China (English)
杨柳; 罗迎社
2008-01-01
The basic factors relating to the rheological stress in the constitutive equations were introduced.Carbon constructional quality steels were regarded as a kind of elastic-viscoplastic materials under high temperature and the elastic-viscoplastic constitutive models were summarized.A series of tension experiments under the same temperature and different strain rates,and the same strain rate and different temperatures were done on 20 steel,35 steel and 45 steel.52 groups of rheological stress-strain curves were obtained.The experimental results were analyzed theoretically.The rheological stress constitutive models of carbon steels were built combining the strong points of the Perzyna model and Johnson-Cook model.Comparing the calculation results conducted from the model with the experiment results,the results proves that the model can reflect the temperature effect and strain rate effect of carbon constructional quality steels better.
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.
Distributional Analysis for Model Predictive Deferrable Load Control
Chen, Niangjun; Gan, Lingwen; Low, Steven H.; Wierman, Adam
2014-01-01
Deferrable load control is essential for handling the uncertainties associated with the increasing penetration of renewable generation. Model predictive control has emerged as an effective approach for deferrable load control, and has received considerable attention. In particular, previous work has analyzed the average-case performance of model predictive deferrable load control. However, to this point, distributional analysis of model predictive deferrable load control has been elusive. In ...
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.
On hydrological model complexity, its geometrical interpretations and prediction uncertainty
Arkesteijn, E.C.M.M.; Pande, S.
2013-01-01
Knowledge of hydrological model complexity can aid selection of an optimal prediction model out of a set of available models. Optimal model selection is formalized as selection of the least complex model out of a subset of models that have lower empirical risk. This may be considered equivalent to
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.
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...... studies on bankruptcy detection, seldom probabilistic approaches were carried out. In this paper we assume a probabilistic point-of-view by applying Gaussian Processes (GP) in the context of bankruptcy prediction, comparing it against the Support Vector Machines (SVM) and the Logistic Regression (LR......). 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...
Predictive modeling of dental pain using neural network.
Kim, Eun Yeob; Lim, Kun Ok; Rhee, Hyun Sill
2009-01-01
The mouth is a part of the body for ingesting food that is the most basic foundation and important part. The dental pain predicted by the neural network model. As a result of making a predictive modeling, the fitness of the predictive modeling of dental pain factors was 80.0%. As for the people who are likely to experience dental pain predicted by the neural network model, preventive measures including proper eating habits, education on oral hygiene, and stress release must precede any dental treatment.
Poluektov, M.; van Dommelen, J. A. W.; Govaert, L. E.; Yakimets, I.; Geers, M. G. D.
2013-12-01
A micromechanically based model is used to describe the mechanical behaviour of polyethylene terephthalate (PET) under uniaxial compression up to large strains and at different temperatures. The creep behaviour of isotropic PET is simulated and compared to experimental data to demonstrate the applicability of the model to describe the long-term response. The material is modelled as an aggregate of two-phase layered domains, where different constitutive laws are used for the phases. A hybrid interaction law between the domains is adopted. The crystalline phase is modelled with crystal plasticity and the amorphous phase with the Eindhoven Glassy Polymer model, taking into account material ageing effects. Model parameters for the selected constitutive laws of the phases are identified from uniaxial compression tests for fully amorphous material and semicrystalline material. Texture evolution during the deformation predicted by the model adequately matches previously observed texture evolution.
Prediction of shear bands in sand based on granular flow model and two-phase equilibrium
Institute of Scientific and Technical Information of China (English)
张义同; 齐德瑄; 杜如虚; 任述光
2008-01-01
In contrast to the traditional interpretation of shear bands in sand as a bifurcation problem in continuum mechanics,shear bands in sand are considered as high-strain phase(plastic phase) of sand and the materials outside the bands are still in low-strain phase(elastic phase),namely,the two phases of sand can coexist under certain condition.As a one-dimensional example,the results show that,for materials with strain-softening behavior,the two-phase solution is a stable branch of solutions,but the method to find two-phase solutions is very different from the one for bifurcation analysis.The theory of multi-phase equilibrium and the slow plastic flow model are applied to predict the formation and patterns of shear bands in sand specimens,discontinuity of deformation gradient and stress across interfaces between shear bands and other regions is considered,the continuity of displacements and traction across interfaces is imposed,and the Maxwell relation is satisfied.The governing equations are deduced.The critical stress for the formation of a shear band,both the stresses and strains inside the band and outside the band,and the inclination angle of the band can all be predicted.The predicted results are consistent with experimental measurements.
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 t
Single chain stochastic polymer modeling at high strain rates.
Energy Technology Data Exchange (ETDEWEB)
Harstad, E. N. (Eric N.); Harlow, Francis Harvey,; Schreyer, H. L.
2001-01-01
Our goal is to develop constitutive relations for the behavior of a solid polymer during high-strain-rate deformations. In contrast to the classic thermodynamic techniques for deriving stress-strain response in static (equilibrium) circumstances, we employ a statistical-mechanics approach, in which we evolve a probability distribution function (PDF) for the velocity fluctuations of the repeating units of the chain. We use a Langevin description for the dynamics of a single repeating unit and a Lioville equation to describe the variations of the PDF. Moments of the PDF give the conservation equations for a single polymer chain embedded in other similar chains. To extract single-chain analytical constitutive relations these equations have been solved for representative loading paths. By this process we discover that a measure of nonuniform chain link displacement serves this purpose very well. We then derive an evolution equation for the descriptor function, with the result being a history-dependent constitutive relation.
The effects of strain heating in lithospheric stretching models
Stanton, M.; Hodge, D.; Cozzarelli, F.
1985-01-01
The deformation by stretching of a continental type lithosphere has been formulated so that the problem can be solved by a continuum mechanical approach. The deformation, stress state, and temperature distribution are constrained to satisfy the physical laws of conservation of mass, energy, momentum, and an experimentally defined rheological response. The conservation of energy equation including a term of strain energy dissipation is given. The continental lithosphere is assumed to have the rheology of an isotropic, incompressible, nonlinear viscous, two layered solid.
Mathematical Model of Load Pass and Prediction of Fatigue Life on Bolt Threads with Reduced Lead
Asayama, Yukiteru
A mathematical model is proposed in order to elucidate the mechanism that the fatigue strength of external threads increases by reducing the lead on a thread system such as a bolt and nut. The model is constructed from the concept that a local strain proportional to the reducing degree of the lead, although the local strain is at first produced in the bolt thread farthest from the bearing surface of the nut, is induced in each thread root with an increase of applied load. The fatigue life predicted from the mathematical model shows good agreement with the experimental fatigue life of cadmium-plated external threads with the reduced lead on the material having strength as high as 1270MPa. The model can provide useful suggestions for the design of fasteners for aerospace, which are required to satisfy severe requirements of fatigue strengths and dimensions.
Strain estimation in 3D by fitting linear and planar data to the March model
Mulchrone, Kieran F.; Talbot, Christopher J.
2016-08-01
The probability density function associated with the March model is derived and used in a maximum likelihood method to estimate the best fit distribution and 3D strain parameters for a given set of linear or planar data. Typically it is assumed that in the initial state (pre-strain) linear or planar data are uniformly distributed on the sphere which means the number of strain parameters estimated needs to be reduced so that the numerical technique succeeds. Essentially this requires that the data are rotated into a suitable reference frame prior to analysis. The method has been applied to a suitable example from the Dalradian of SW Scotland and results obtained are consistent with those from an independent method of strain analysis. Despite March theory having been incorporated deep into the fabric of geological strain analysis, its full potential as a simple direct 3D strain analytical tool has not been achieved. The method developed here may help remedy this situation.
Impact of animal strain on gene expression in a rat model of acute cardiac rejection
Directory of Open Access Journals (Sweden)
Norsworthy Kelly J
2009-06-01
Full Text Available Abstract Background The expression levels of many genes show wide natural variation among strains or populations. This study investigated the potential for animal strain-related genotypic differences to confound gene expression profiles in acute cellular rejection (ACR. Using a rat heart transplant model and 2 different rat strains (Dark Agouti, and Brown Norway, microarrays were performed on native hearts, transplanted hearts, and peripheral blood mononuclear cells (PBMC. Results In heart tissue, strain alone affected the expression of only 33 probesets while rejection affected the expression of 1368 probesets (FDR 10% and FC ≥ 3. Only 13 genes were affected by both strain and rejection, which was Conclusion In ACR, genetic background has a large impact on the transcriptome of immune cells, but not heart tissue. Gene expression studies of ACR should avoid study designs that require cross strain comparisons between leukocytes.
Cyprych, D.; Brune, S.; Piazolo, S.; Quinteros, J.
2016-09-01
We use a centimeter-scale 2-D numerical model to investigate the effect of the presence of a second phase with various volume percent, shape, and orientation on strain localization in a viscoelastic matrix. In addition, the evolution of bulk rheological behavior of aggregates during uniaxial compression is analyzed. The rheological effect of dynamic recrystallization processes in the matrix is reproduced by viscous strain softening. We show that the presence of hard particles strengthens the aggregate, but also causes strain localization and the formation of ductile shear zones in the matrix. The presence of soft particles weakens the aggregate, while strain localizes within the particles and matrix between particles. The shape and the orientation of second phases control the orientation, geometry, and connectivity of ductile shear zones. We propose an analytical scaling method that translates the bulk stress measurements of our 2-D simulations to 3-D experiments. Comparing our model to the laboratory uniaxial compression experiments on ice cylinders with hard second phases allows the analysis of transient and steady-state strain distribution in ice matrix, and strain partitioning between ice and second phases through empirical calibration of viscous softening parameters. We find that the ice matrix in two-phase aggregates accommodates more strain than the applied bulk strain, while at faster strain rates some of the load is transferred into hard particles. Our study illustrates that dynamic recrystallization processes in the matrix are markedly influenced by the presence of a second phase.
Prediction of peptide bonding affinity: kernel methods for nonlinear modeling
Bergeron, Charles; Sundling, C Matthew; Krein, Michael; Katt, Bill; Sukumar, Nagamani; Breneman, Curt M; Bennett, Kristin P
2011-01-01
This paper presents regression models obtained from a process of blind prediction of peptide binding affinity from provided descriptors for several distinct datasets as part of the 2006 Comparative Evaluation of Prediction Algorithms (COEPRA) contest. This paper finds that kernel partial least squares, a nonlinear partial least squares (PLS) algorithm, outperforms PLS, and that the incorporation of transferable atom equivalent features improves predictive capability.
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.
DEFF Research Database (Denmark)
Olsen, Flemming Javier; Pedersen, Sune; Jensen, Jan Skov
2016-01-01
Patients with acute myocardial infarction are at increased risk of developing atrial fibrillation. We aimed to evaluate whether speckle tracking echocardiography improves risk stratification for atrial fibrillation in these patients.The study comprised of 373 patients with ST-segment elevation...... myocardial infarction (STEMI) treated with primary percutaneous coronary intervention. Patients had an echocardiogram performed at a median of 2 days after their STEMI. The echocardiograms consisted of conventional measurements and myocardial strain analysis by speckle tracking from 3 apical projections...
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.
Proteochemometric model for predicting the inhibition of penicillin-binding proteins
Nabu, Sunanta; Nantasenamat, Chanin; Owasirikul, Wiwat; Lawung, Ratana; Isarankura-Na-Ayudhya, Chartchalerm; Lapins, Maris; Wikberg, Jarl E. S.; Prachayasittikul, Virapong
2015-02-01
Neisseria gonorrhoeae infection threatens to become an untreatable sexually transmitted disease in the near future owing to the increasing emergence of N. gonorrhoeae strains with reduced susceptibility and resistance to the extended-spectrum cephalosporins (ESCs), i.e. ceftriaxone and cefixime, which are the last remaining option for first-line treatment of gonorrhea. Alteration of the penA gene, encoding penicillin-binding protein 2 (PBP2), is the main mechanism conferring penicillin resistance including reduced susceptibility and resistance to ESCs. To predict and investigate putative amino acid mutations causing β-lactam resistance particularly for ESCs, we applied proteochemometric modeling to generalize N. gonorrhoeae susceptibility data for predicting the interaction of PBP2 with therapeutic β-lactam antibiotics. This was afforded by correlating publicly available data on antimicrobial susceptibility of wild-type and mutant N. gonorrhoeae strains for penicillin-G, cefixime and ceftriaxone with 50 PBP2 protein sequence data using partial least-squares projections to latent structures. The generated model revealed excellent predictability ( R 2 = 0.91, Q 2 = 0.77, Q Ext 2 = 0.78). Moreover, our model identified amino acid mutations in PBP2 with the highest impact on antimicrobial susceptibility and provided information on physicochemical properties of amino acid mutations affecting antimicrobial susceptibility. Our model thus provided insight into the physicochemical basis for resistance development in PBP2 suggesting its use for predicting and monitoring novel PBP2 mutations that may emerge in the future.
Prediction using patient comparison vs. modeling: a case study for mortality prediction.
Hoogendoorn, Mark; El Hassouni, Ali; Mok, Kwongyen; Ghassemi, Marzyeh; Szolovits, Peter
2016-08-01
Information in Electronic Medical Records (EMRs) can be used to generate accurate predictions for the occurrence of a variety of health states, which can contribute to more pro-active interventions. The very nature of EMRs does make the application of off-the-shelf machine learning techniques difficult. In this paper, we study two approaches to making predictions that have hardly been compared in the past: (1) extracting high-level (temporal) features from EMRs and building a predictive model, and (2) defining a patient similarity metric and predicting based on the outcome observed for similar patients. We analyze and compare both approaches on the MIMIC-II ICU dataset to predict patient mortality and find that the patient similarity approach does not scale well and results in a less accurate model (AUC of 0.68) compared to the modeling approach (0.84). We also show that mortality can be predicted within a median of 72 hours.
DEFF Research Database (Denmark)
Ahmad, Amais; Zachariasen, Camilla; Christiansen, Lasse Engbo;
2016-01-01
Background: Combination treatment is increasingly used to fight infections caused by bacteria resistant to two or more antimicrobials. While multiple studies have evaluated treatment strategies to minimize the emergence of resistant strains for single antimicrobial treatment, fewer studies have...... 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...... 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....
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...... problem. Moreover, to reduce the computation time and improve the controller's performance, a fuzzy predictive filter is introduced. With the purpose of testing the developed EMPC, a simulation controlling the temperature levels of an intelligent office building (PowerFlexHouse), with and without fuzzy...
DEFF Research Database (Denmark)
King, Zachary A.; O'Brien, Edward J.; Feist, Adam M.;
2017-01-01
The metabolic byproducts secreted by growing cells can be easily measured and provide a window into the state of a cell; they have been essential to the development of microbiology, cancer biology, and biotechnology. Progress in computational modeling of cells has made it possible to predict...... metabolic byproduct secretion with bottom-up reconstructions of metabolic networks. However, owing to a lack of data, it has not been possible to validate these predictions across a wide range of strains and conditions. Through literature mining, we were able to generate a database of Escherichia coli...
Abdelgawwad, Ihab M; Al Hawary, Ahmed A; Kamal, Hanan M; Al Maghawry, Layla M
2017-01-13
The aim of the study was to assess the ability of tissue Doppler (TD) deformation analysis at rest to predict left ventricular contractile recovery in patients undergoing percutaneous coronary intervention (PCI). This prospective cohort enrolled 67 patients with segmental wall motion abnormality. Assessment of each segment was performed at rest and during low dose Dobutamine stress echocardiography (DSE) using a 4 point scoring system, TD peak systolic strain (PSS) and peak systolic strain rate (PSSR). The study followed up the patients for contractile improvement after 6 months of successful PCI by echocardiography. Of a 319 dysfunctional segments, 155 (49%) showed contractile recovery and 164 (51%) did not. PSS and PSSR at rest were significantly higher in recovered segments compared to segments without recovery (PSS: -7.27 ± 0.8 Vs. -6.14 ± 0.7%, PSSR: -0.34 ± 0.13 Vs. -0.24 ± 0.1/s. p recovery group at follow up (p 0.001). Resting PSSR as well as PSS and PSSR during DSE were significant independent predictors of contractile recovery (p recovery, resting PSSR with a -0.31/s cut-off point had 76% sensitivity and 59% specificity (AUC 0.74), DSE qualitative viability assessment had a sensitivity of 75% and specificity of 77%, DSE PSS with a cut-off point of -9.1% had 74% sensitivity and 63% specificity (AUC 0.77) and DSE PSSR with a cut-off point of -0.72/s had 78% sensitivity and 77% specificity (AUC 0.81). Resting PSSR is a modest predictor of segmental contractile recovery after PCI while PSSR during DSE has a comparable diagnostic performance to subjective wall motion scoring. Recovered segments show improvement of deformation parameters after PCI.
Predictive modeling and reducing cyclic variability in autoignition engines
Energy Technology Data Exchange (ETDEWEB)
Hellstrom, Erik; Stefanopoulou, Anna; Jiang, Li; Larimore, Jacob
2016-08-30
Methods and systems are provided for controlling a vehicle engine to reduce cycle-to-cycle combustion variation. A predictive model is applied to predict cycle-to-cycle combustion behavior of an engine based on observed engine performance variables. Conditions are identified, based on the predicted cycle-to-cycle combustion behavior, that indicate high cycle-to-cycle combustion variation. Corrective measures are then applied to prevent the predicted high cycle-to-cycle combustion variation.
Intelligent predictive model of ventilating capacity of imperial smelt furnace
Institute of Scientific and Technical Information of China (English)
唐朝晖; 胡燕瑜; 桂卫华; 吴敏
2003-01-01
In order to know the ventilating capacity of imperial smelt furnace (ISF), and increase the output of plumbum, an intelligent modeling method based on gray theory and artificial neural networks(ANN) is proposed, in which the weight values in the integrated model can be adjusted automatically. An intelligent predictive model of the ventilating capacity of the ISF is established and analyzed by the method. The simulation results and industrial applications demonstrate that the predictive model is close to the real plant, the relative predictive error is 0.72%, which is 50% less than the single model, leading to a notable increase of the output of plumbum.
A Prediction Model of the Capillary Pressure J-Function
Xu, W. S.; Luo, P. Y.; Sun, L.; Lin, N.
2016-01-01
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. PMID:27603701
Adaptation of Predictive Models to PDA Hand-Held Devices
Directory of Open Access Journals (Sweden)
Lin, Edward J
2008-01-01
Full Text Available Prediction models using multiple logistic regression are appearing with increasing frequency in the medical literature. Problems associated with these models include the complexity of computations when applied in their pure form, and lack of availability at the bedside. Personal digital assistant (PDA hand-held devices equipped with spreadsheet software offer the clinician a readily available and easily applied means of applying predictive models at the bedside. The purposes of this article are to briefly review regression as a means of creating predictive models and to describe a method of choosing and adapting logistic regression models to emergency department (ED clinical practice.
A model to predict the power output from wind farms
Energy Technology Data Exchange (ETDEWEB)
Landberg, L. [Riso National Lab., Roskilde (Denmark)
1997-12-31
This paper will describe a model that can predict the power output from wind farms. To give examples of input the model is applied to a wind farm in Texas. The predictions are generated from forecasts from the NGM model of NCEP. These predictions are made valid at individual sites (wind farms) by applying a matrix calculated by the sub-models of WASP (Wind Atlas Application and Analysis Program). The actual wind farm production is calculated using the Riso PARK model. Because of the preliminary nature of the results, they will not be given. However, similar results from Europe will be given.
Modelling microbial interactions and food structure in predictive microbiology
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
Modelling microbial interactions and food structure in predictive microbiology
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 new technologies
Estimating Model Prediction Error: Should You Treat Predictions as Fixed or Random?
Wallach, Daniel; Thorburn, Peter; Asseng, Senthold; Challinor, Andrew J.; Ewert, Frank; Jones, James W.; Rotter, Reimund; Ruane, Alexander
2016-01-01
Crop models are important tools for impact assessment of climate change, as well as for exploring management options under current climate. It is essential to evaluate the uncertainty associated with predictions of these models. We compare two criteria of prediction error; MSEP fixed, which evaluates mean squared error of prediction for a model with fixed structure, parameters and inputs, and MSEP uncertain( X), which evaluates mean squared error averaged over the distributions of model structure, inputs and parameters. Comparison of model outputs with data can be used to estimate the former. The latter has a squared bias term, which can be estimated using hindcasts, and a model variance term, which can be estimated from a simulation experiment. The separate contributions to MSEP uncertain (X) can be estimated using a random effects ANOVA. It is argued that MSEP uncertain (X) is the more informative uncertainty criterion, because it is specific to each prediction situation.
Predicting Career Advancement with Structural Equation Modelling
Heimler, Ronald; Rosenberg, Stuart; Morote, Elsa-Sofia
2012-01-01
Purpose: The purpose of this paper is to use the authors' prior findings concerning basic employability skills in order to determine which skills best predict career advancement potential. Design/methodology/approach: Utilizing survey responses of human resource managers, the employability skills showing the largest relationships to career…
Predicting Career Advancement with Structural Equation Modelling
Heimler, Ronald; Rosenberg, Stuart; Morote, Elsa-Sofia
2012-01-01
Purpose: The purpose of this paper is to use the authors' prior findings concerning basic employability skills in order to determine which skills best predict career advancement potential. Design/methodology/approach: Utilizing survey responses of human resource managers, the employability skills showing the largest relationships to career…
Modeling and prediction of surgical procedure times
P.S. Stepaniak (Pieter); C. Heij (Christiaan); G. de Vries (Guus)
2009-01-01
textabstractAccurate prediction of medical operation times is of crucial importance for cost efficient operation room planning in hospitals. This paper investigates the possible dependence of procedure times on surgeon factors like age, experience, gender, and team composition. The effect of these f
Prediction Model of Sewing Technical Condition by Grey Neural Network
Institute of Scientific and Technical Information of China (English)
DONG Ying; FANG Fang; ZHANG Wei-yuan
2007-01-01
The grey system theory and the artificial neural network technology were applied to predict the sewing technical condition. The representative parameters, such as needle, stitch, were selected. Prediction model was established based on the different fabrics' mechanical properties that measured by KES instrument. Grey relevant degree analysis was applied to choose the input parameters of the neural network. The result showed that prediction model has good precision. The average relative error was 4.08% for needle and 4.25% for stitch.
Active diagnosis of hybrid systems - A model predictive approach
2009-01-01
A method for active diagnosis of hybrid systems is proposed. The main idea is to predict the future output of both normal and faulty model of the system; then at each time step an optimization problem is solved with the objective of maximizing the difference between the predicted normal and faulty outputs constrained by tolerable performance requirements. As in standard model predictive control, the first element of the optimal input is applied to the system and the whole procedure is repeate...
Evaluation of Fast-Time Wake Vortex Prediction Models
Proctor, Fred H.; Hamilton, David W.
2009-01-01
Current fast-time wake models are reviewed and three basic types are defined. Predictions from several of the fast-time models are compared. Previous statistical evaluations of the APA-Sarpkaya and D2P fast-time models are discussed. Root Mean Square errors between fast-time model predictions and Lidar wake measurements are examined for a 24 hr period at Denver International Airport. Shortcomings in current methodology for evaluating wake errors are also discussed.
Inverse modeling of InSAR and ground leveling data for 3D volumetric strain distribution
Gallardo, L. A.; Glowacka, E.; Sarychikhina, O.
2015-12-01
Wide availability of modern Interferometric Synthetic aperture Radar (InSAR) data have made possible the extensive observation of differential surface displacements and are becoming an efficient tool for the detailed monitoring of terrain subsidence associated to reservoir dynamics, volcanic deformation and active tectonism. Unfortunately, this increasing popularity has not been matched by the availability of automated codes to estimate underground deformation, since many of them still rely on trial-error subsurface model building strategies. We posit that an efficient algorithm for the volumetric modeling of differential surface displacements should match the availability of current leveling and InSAR data and have developed an algorithm for the joint inversion of ground leveling and dInSAR data in 3D. We assume the ground displacements are originated by a stress free-volume strain distribution in a homogeneous elastic media and determined the displacement field associated to an ensemble of rectangular prisms. This formulation is then used to develop a 3D conjugate gradient inversion code that searches for the three-dimensional distribution of the volumetric strains that predict InSAR and leveling surface displacements simultaneously. The algorithm is regularized applying discontinuos first and zero order Thikonov constraints. For efficiency, the resulting computational code takes advantage of the resulting convolution integral associated to the deformation field and some basic tools for multithreading parallelization. We extensively test our algorithm on leveling and InSAR test and field data of the Northwest of Mexico and compare to some feasible geological scenarios of underground deformation.
Comparison of Simple Versus Performance-Based Fall Prediction Models
Directory of Open Access Journals (Sweden)
Shekhar K. Gadkaree BS
2015-05-01
Full Text Available Objective: To compare the predictive ability of standard falls prediction models based on physical performance assessments with more parsimonious prediction models based on self-reported data. Design: We developed a series of fall prediction models progressing in complexity and compared area under the receiver operating characteristic curve (AUC across models. Setting: National Health and Aging Trends Study (NHATS, which surveyed a nationally representative sample of Medicare enrollees (age ≥65 at baseline (Round 1: 2011-2012 and 1-year follow-up (Round 2: 2012-2013. Participants: In all, 6,056 community-dwelling individuals participated in Rounds 1 and 2 of NHATS. Measurements: Primary outcomes were 1-year incidence of “any fall” and “recurrent falls.” Prediction models were compared and validated in development and validation sets, respectively. Results: A prediction model that included demographic information, self-reported problems with balance and coordination, and previous fall history was the most parsimonious model that optimized AUC for both any fall (AUC = 0.69, 95% confidence interval [CI] = [0.67, 0.71] and recurrent falls (AUC = 0.77, 95% CI = [0.74, 0.79] in the development set. Physical performance testing provided a marginal additional predictive value. Conclusion: A simple clinical prediction model that does not include physical performance testing could facilitate routine, widespread falls risk screening in the ambulatory care setting.
Testing and analysis of internal hardwood log defect prediction models
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...
Comparison of Simple Versus Performance-Based Fall Prediction Models
Directory of Open Access Journals (Sweden)
Shekhar K. Gadkaree BS
2015-05-01
Full Text Available Objective: To compare the predictive ability of standard falls prediction models based on physical performance assessments with more parsimonious prediction models based on self-reported data. Design: We developed a series of fall prediction models progressing in complexity and compared area under the receiver operating characteristic curve (AUC across models. Setting: National Health and Aging Trends Study (NHATS, which surveyed a nationally representative sample of Medicare enrollees (age ≥65 at baseline (Round 1: 2011-2012 and 1-year follow-up (Round 2: 2012-2013. Participants: In all, 6,056 community-dwelling individuals participated in Rounds 1 and 2 of NHATS. Measurements: Primary outcomes were 1-year incidence of “ any fall ” and “ recurrent falls .” Prediction models were compared and validated in development and validation sets, respectively. Results: A prediction model that included demographic information, self-reported problems with balance and coordination, and previous fall history was the most parsimonious model that optimized AUC for both any fall (AUC = 0.69, 95% confidence interval [CI] = [0.67, 0.71] and recurrent falls (AUC = 0.77, 95% CI = [0.74, 0.79] in the development set. Physical performance testing provided a marginal additional predictive value. Conclusion: A simple clinical prediction model that does not include physical performance testing could facilitate routine, widespread falls risk screening in the ambulatory care setting.
Refining the Committee Approach and Uncertainty Prediction in Hydrological Modelling
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 mode
Refining the committee approach and uncertainty prediction in hydrological modelling
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 mode
Refining the Committee Approach and Uncertainty Prediction in Hydrological Modelling
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 mode
Refining the committee approach and uncertainty prediction in hydrological modelling
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 mode
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.
Goldberg, Robert K.
1999-01-01
Potential gas turbine applications will expose polymer matrix composites to very high strain rate loading conditions, requiring an ability to understand and predict the material behavior under extreme conditions. Specifically, analytical methods designed for these applications must have the capability of properly capturing the strain rate sensitivities and nonlinearities that are present in the material response. The Ramaswamy-Stouffer constitutive equations, originally developed to analyze the viscoplastic deformation of metals, have been modified to simulate the nonlinear deformation response of ductile, crystalline polymers. The constitutive model is characterized and correlated for two representative ductile polymers. Fiberite 977-2 and PEEK, and the computed results correlate well with experimental values. The polymer constitutive equations are implemented in a mechanics of materials based composite micromechanics model to predict the nonlinear, rate dependent deformation response of a composite ply. Uniform stress and uniform strain assumptions are applied to compute the effective stresses of a composite unit cell from the applied strains. The micromechanics equations are successfully verified for two polymer matrix composites. IM7/977-2 and AS4/PEEK. The ultimate strength of a composite ply is predicted with the Hashin failure criteria that were implemented in the composite micromechanics model. The failure stresses of the two composite material systems are accurately predicted for a variety of fiber orientations and strain rates. The composite deformation model is implemented in LS-DYNA, a commercially available transient dynamic explicit finite element code. The matrix constitutive equations are converted into an incremental form, and the model is implemented into LS-DYNA through the use of a user defined material subroutine. The deformation response of a bulk polymer and a polymer matrix composite are predicted by finite element analyses. The results
Bi-variable damage model for fatigue life prediction of metal components
Institute of Scientific and Technical Information of China (English)
Miao Zhang; Qing-Chun Meng; Xing Zhang; Wei-Ping Hu
2011-01-01
Based on the theory of continuum damage mechanics, a bi-variable damage mechanics model is developed, which, according to thermodynamics, is accessible to derivation of damage driving force, damage evolution equation and damage evolution criteria. Furthermore, damage evolution equations of time rate are established by the generalized Drucker's postulate. The damage evolution equation of cycle rate is obtained by integrating the time damage evolution equations, and the fatigue life prediction method for smooth specimens under repeated loading with constant strain amplitude is constructed. Likewise, for notched specimens under the repeated loading with constant strain amplitude, the fatigue life prediction method is obtained on the ground of the theory of conservative integral in damage mechanics. Thus, the material parameters in the damage evolution equation can be obtained by reference to the fatigue test results of standard specimens with stress concentration factor equal to 1, 2 and 3.
Prediction of Maximum Strain in Finocyl Port Case-bonded Solid Propellants under Pressure Loading
Directory of Open Access Journals (Sweden)
Himanshu Shekhar
2006-07-01
Full Text Available Finite element analysis of case-bonded solid propellants in finocyl port configuration hasbeen carried out using finite element method. The parametric studies have also been conductedfor loading conditions, material properties, and geometrical configurations. The results arepresented in the form of a universal power law, which can be utilised for primary assessmentof peak strain in any finocyl port propellant configuration without using finite element software.This eliminates dependence on finite element software for structural integrity analysis of solidpropellants in finocyl port configuration under port pressurisation. The results obtained by finiteelement analysis and power law are in close agreement.
Impact of modellers' decisions on hydrological a priori predictions
Holländer, H. M.; Bormann, H.; Blume, T.; Buytaert, W.; Chirico, G. B.; Exbrayat, J.-F.; Gustafsson, D.; Hölzel, H.; Krauße, T.; Kraft, P.; Stoll, S.; Blöschl, G.; Flühler, H.
2014-06-01
In practice, the catchment hydrologist is often confronted with the task of predicting discharge without having the needed records for calibration. Here, we report the discharge predictions of 10 modellers - using the model of their choice - for the man-made Chicken Creek catchment (6 ha, northeast Germany, Gerwin et al., 2009b) and we analyse how well they improved their prediction in three steps based on adding information prior to each following step. The modellers predicted the catchment's hydrological response in its initial phase without having access to the observed records. They used conceptually different physically based models and their modelling experience differed largely. Hence, they encountered two problems: (i) to simulate discharge for an ungauged catchment and (ii) using models that were developed for catchments, which are not in a state of landscape transformation. The prediction exercise was organized in three steps: (1) for the first prediction the modellers received a basic data set describing the catchment to a degree somewhat more complete than usually available for a priori predictions of ungauged catchments; they did not obtain information on stream flow, soil moisture, nor groundwater response and had therefore to guess the initial conditions; (2) before the second prediction they inspected the catchment on-site and discussed their first prediction attempt; (3) for their third prediction they were offered additional data by charging them pro forma with the costs for obtaining this additional information. Holländer et al. (2009) discussed the range of predictions obtained in step (1). Here, we detail the modeller's assumptions and decisions in accounting for the various processes. We document the prediction progress as well as the learning process resulting from the availability of added information. For the second and third steps, the progress in prediction quality is evaluated in relation to individual modelling experience and costs of
Econometric models for predicting confusion crop ratios
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.
FINITE ELEMENT METHOD AS A BASIS FOR THE MODELING OF ROAD SURFACE STRESS-STRAIN STATE
2011-01-01
Problem statement. Despite the fact that rigid roads with asphalt concrete pavement widespread,their design and calculation provide for approximate data with some number of hidden factors. Thepresent paper proposes to use finite element method to model stress-strain state of rigid roads withasphalt concrete pavement.Results. The use of the finite element method enables one to construct the precise model ofstress-strain state of road pavement. The calculations performed on the basis of the mod...
Design of Strain-Compensated Epitaxial Layers Using an Electrical Circuit Model
Kujofsa, Tedi; Ayers, John E.
2017-08-01
The design of heterostructures that exhibit desired strain characteristics is critical for the realization of semiconductor devices with improved performance and reliability. The control of strain and dislocation dynamics requires an understanding of the relaxation processes associated with mismatched epitaxy, and the starting point for this analysis is the equilibrium strain profile, because the difference between the actual strain and the equilibrium value determines the driving force for dislocation glide and relaxation. Previously, we developed an electrical circuit model approach for the equilibrium analysis of semiconductor heterostructures, in which an epitaxial layer may be represented by a stack of subcircuits, each of which involves an independent current source, a resistor, an independent voltage source, and an ideal diode. In this work, we have applied the electrical circuit model to study the strain compensation mechanism and show that, for a given compositionally uniform device layer with fixed mismatch and layer thickness, a buffer layer may be designed (in terms of thickness and mismatch) to tailor the strain in the device layer. A special case is that in which the device layer will exhibit zero residual strain in equilibrium (complete strain compensation). In addition, the application of the electrical circuit analogy enables the determination of exact expressions for the residual strain characteristics of both the buffer and device layers in the general case where the device layer may exhibit partial strain compensation. On the basis of this framework, it is possible to develop design equations for the tailoring of the strain in a device layer grown on a uniform composition buffer.
PEEX Modelling Platform for Seamless Environmental Prediction
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.
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.
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,...
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.
Prediction and in vitro verification of potential CTL epitopes conserved among PRRSV-2 strains
DEFF Research Database (Denmark)
Welner, Simon; Nielsen, Morten; Rasmussen, Michael
2017-01-01
mutation rate, has hampered the development of safe and broadly protective vaccines. Aiming at a vaccine inducing an effective cytotoxic T cell response, a bioinformatics approach was taken to identify conserved PRRSV-derived peptides predicted to react broadly with common swine leukocyte antigen (SLA......) class I alleles. Briefly, all possible 9- and 10-mer peptides were generated from 104 complete PRRSV type 2 genomes of confirmed high quality, and peptides with high binding affinity to five common SLAs were identified combining the NetMHCpan and positional scanning combinatorial peptide libraries...... binding predictions. Predicted binders were prioritized according to genomic conservation and SLA coverage using the PopCover algorithm. From this, 53 peptides were acquired for further analysis. Binding affinity and stability of a subset of 101 peptide-SLA combinations were validated in vitro for 4...
Simulation of Healing Threshold in Strain-Induced Inflammation through a Discrete Informatics Model.
Ibrahim, Israr; Oruganti, Sanjay Venkata; Pidaparti, Ramana
2017-02-15
Respiratory diseases such as asthma and acute respiratory distress syndrome as well as acute lung injury involve inflammation at the cellular level. The inflammation process is very complex and is characterized by the emergence of cytokines along with other changes in cellular processes. Due to the complexity of the various constituents that makes up the inflammation dynamics, it is necessary to develop models that can complement experiments to fully understand inflammatory diseases. In this study, we developed a discrete informatics model based on cellular automata (CA) approach to investigate the influence of elastic field (stretch/strain) on the dynamics of inflammation and account for probabilistic adaptation based on statistical interpretation of existing experimental data. Our simulation model investigated the effects of low, medium and high strain conditions on inflammation dynamics. Results suggest that the model is able to indicate the threshold of innate healing of tissue as a response to strain experienced by the tissue. When strain is under the threshold, the tissue is still capable of adapting its structure to heal the damaged part. However, there exists a strain threshold where healing capability breaks down. The results obtained demonstrate that the developed discrete informatics based CA model is capable of modeling and giving insights into inflammation dynamics parameters under various mechanical strain/stretch environments.
Models Predicting Success of Infertility Treatment: A Systematic Review
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
MULTI MODEL DATA MINING APPROACH FOR HEART FAILURE PREDICTION
Directory of Open Access Journals (Sweden)
Priyanka H U
2016-09-01
Full Text Available Developing predictive modelling solutions for risk estimation is extremely challenging in health-care informatics. Risk estimation involves integration of heterogeneous clinical sources having different representation from different health-care provider making the task increasingly complex. Such sources are typically voluminous, diverse, and significantly change over the time. Therefore, distributed and parallel computing tools collectively termed big data tools are in need which can synthesize and assist the physician to make right clinical decisions. In this work we propose multi-model predictive architecture, a novel approach for combining the predictive ability of multiple models for better prediction accuracy. We demonstrate the effectiveness and efficiency of the proposed work on data from Framingham Heart study. Results show that the proposed multi-model predictive architecture is able to provide better accuracy than best model approach. By modelling the error of predictive models we are able to choose sub set of models which yields accurate results. More information was modelled into system by multi-level mining which has resulted in enhanced predictive accuracy.
The regional prediction model of PM10 concentrations for Turkey
Güler, Nevin; Güneri İşçi, Öznur
2016-11-01
This study is aimed to predict a regional model for weekly PM10 concentrations measured air pollution monitoring stations in Turkey. There are seven geographical regions in Turkey and numerous monitoring stations at each region. Predicting a model conventionally for each monitoring station requires a lot of labor and time and it may lead to degradation in quality of prediction when the number of measurements obtained from any õmonitoring station is small. Besides, prediction models obtained by this way only reflect the air pollutant behavior of a small area. This study uses Fuzzy C-Auto Regressive Model (FCARM) in order to find a prediction model to be reflected the regional behavior of weekly PM10 concentrations. The superiority of FCARM is to have the ability of considering simultaneously PM10 concentrations measured monitoring stations in the specified region. Besides, it also works even if the number of measurements obtained from the monitoring stations is different or small. In order to evaluate the performance of FCARM, FCARM is executed for all regions in Turkey and prediction results are compared to statistical Autoregressive (AR) Models predicted for each station separately. According to Mean Absolute Percentage Error (MAPE) criteria, it is observed that FCARM provides the better predictions with a less number of models.
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.
Gaussian mixture models as flux prediction method for central receivers
Grobler, Annemarie; Gauché, Paul; Smit, Willie
2016-05-01
Flux prediction methods are crucial to the design and operation of central receiver systems. Current methods such as the circular and elliptical (bivariate) Gaussian prediction methods are often used in field layout design and aiming strategies. For experimental or small central receiver systems, the flux profile of a single heliostat often deviates significantly from the circular and elliptical Gaussian models. Therefore a novel method of flux prediction was developed by incorporating the fitting of Gaussian mixture models onto flux profiles produced by flux measurement or ray tracing. A method was also developed to predict the Gaussian mixture model parameters of a single heliostat for a given time using image processing. Recording the predicted parameters in a database ensures that more accurate predictions are made in a shorter time frame.
Xu, Lin; Huang, Xiaomin; Ma, Jun; Huang, Jiangming; Fan, Yongwang; Li, Huidi; Qiu, Jian; Zhang, Heye; Huang, Wenhua
2017-02-01
This study was to evaluate the value of multi-directional strain parameters derived from three-dimensional (3D) speckle tracking echocardiography (STE) for predicting left ventricular (LV) remodeling after ST-elevation myocardial infarction (STEMI) treated with primary percutaneous coronary intervention (PCI) compared with that of two-dimensional (2D) global longitudinal strain (GLS). A total of 110 patients (mean age, 54 ± 9 years) after STEMI treated with primary PCI were enrolled in our study. At baseline (within 24 h after PCI), standard 2D echocardiography, 2D STE and 3D STE were performed to acquire the conventional echocardiographic parameters and strain parameters. At 3-month follow-up, standard 2D echocardiography was repeated to all the patients to determine LV remodeling, which was defined as a 20% increase in LV end-diastolic volume. At 3-month follow-up, LV remodeling occurred in 26 patients (24%). Compared with patients without LV remodeling, patients with remodeling had significantly reduced 2D GLS (-12.5 ± 3.2% vs -15.0 ± 3.1%, p remodeling. However, receiver-operating characteristic curve analysis showed that the area under the curve of 3D GLS (0.82) for predicting LV remodeling was significantly higher than that of 2D GLS (0.72, p = 0.034), 3D GAS (0.68, p remodeling and 3D GLS is the most powerful predictor among them.
Nonlinear model predictive control of a packed distillation column
Energy Technology Data Exchange (ETDEWEB)
Patwardhan, A.A.; Edgar, T.F. (Univ. of Texas, Austin, TX (United States). Dept. of Chemical Engineering)
1993-10-01
A rigorous dynamic model based on fundamental chemical engineering principles was formulated for a packed distillation column separating a mixture of cyclohexane and n-heptane. This model was simplified to a form suitable for use in on-line model predictive control calculations. A packed distillation column was operated at several operating conditions to estimate two unknown model parameters in the rigorous and simplified models. The actual column response to step changes in the feed rate, distillate rate, and reboiler duty agreed well with dynamic model predictions. One unusual characteristic observed was that the packed column exhibited gain-sign changes, which are very difficult to treat using conventional linear feedback control. Nonlinear model predictive control was used to control the distillation column at an operating condition where the process gain changed sign. An on-line, nonlinear model-based scheme was used to estimate unknown/time-varying model parameters.
Finite Element Modeling of Plane Strain Toughness for 7085 Aluminum Alloy
Karabin, M. E.; Barlat, F.; Shuey, R. T.
2009-02-01
In this work, the constitutive model for 7085-T7X (overaged) aluminum alloy plate samples with controlled microstructures was developed. Different lengths of 2nd step aging times produced samples with similar microstructure but different stress-strain curves ( i.e., different nanostructure). A conventional phenomenological strain-hardening law with no strain gradient effects was proposed to capture the peculiar hardening behavior of the material samples investigated in this work. The classical Gurson-Tvergaard potential, which includes the influence of void volume fraction (VVF) on the plastic flow behavior, as well as an extension proposed by Leblond et al.,[3] were considered. Unlike the former, the latter is able to account for the influence of strain hardening on the VVF growth. All the constitutive coefficients used in this work were based on experimental stress-strain curves obtained in uniaxial tension and on micromechanical modeling results of a void embedded in a matrix. These material models were used in finite element (FE) simulations of a compact tension (CT) specimen. An engineering criterion based on the instability of plastic flow at a crack tip was used for the determination of plane strain toughness K Ic . The influence of the microstructure was lumped into a single state variable, the initial void volume fraction. The simulation results showed that the strain-hardening behavior has a significant influence on K Ic .
Application of Nonlinear Predictive Control Based on RBF Network Predictive Model in MCFC Plant
Institute of Scientific and Technical Information of China (English)
CHEN Yue-hua; CAO Guang-yi; ZHU Xin-jian
2007-01-01
This paper described a nonlinear model predictive controller for regulating a molten carbonate fuel cell (MCFC). A detailed mechanism model of output voltage of a MCFC was presented at first. However, this model was too complicated to be used in a control system. Consequently, an off line radial basis function (RBF) network was introduced to build a nonlinear predictive model. And then, the optimal control sequences were obtained by applying golden mean method. The models and controller have been realized in the MATLAB environment. Simulation results indicate the proposed algorithm exhibits satisfying control effect even when the current densities vary largely.
Directory of Open Access Journals (Sweden)
Dan Liu
Full Text Available Since diastolic abnormalities are typical findings of cardiac amyloidosis (CA, we hypothesized that speckle-tracking-imaging (STI derived longitudinal early diastolic strain rate (LSRdias could predict outcome in CA patients with preserved left ventricular ejection fraction (LVEF >50%.Diastolic abnormalities including altered early filling are typical findings and are related to outcome in CA patients. Reduced longitudinal systolic strain (LSsys assessed by STI predicts increased mortality in CA patients. It remains unknown if LSRdias also related to outcome in these patients.Conventional echocardiography and STI were performed in 41 CA patients with preserved LVEF (25 male; mean age 65±9 years. Global and segmental LSsys and LSRdias were obtained in six LV segments from apical 4-chamber views.Nineteen (46% out of 41 CA patients died during a median of 16 months (quartiles 5-35 months follow-up. Baseline mitral annular plane systolic excursion (MAPSE, 6 ± 2 vs. 8 ± 3 mm, global LSRdias and basal-septal LSRdias were significantly lower in non-survivors than in survivors (all p < 0.05. NYHA class, number of non-cardiac organs involved, MAPSE, mid-septal LSsys, global LSRdias, basal-septal LSRdias and E/LSRdias were the univariable predictors of all-cause death. Multivariable analysis showed that number of non-cardiac organs involved (hazard ratio [HR] = 1.96, 95% confidence interval [CI] 1.17-3.26, P = 0.010, global LSRdias (HR = 7.30, 95% CI 2.08-25.65, P = 0.002, and E/LSRdias (HR = 2.98, 95% CI 1.54-5.79, P = 0.001 remained independently predictive of increased mortality risk. The prognostic performance of global LSRdias was optimal at a cutoff value of 0.85 S-1 (sensitivity 68%, specificity 67%. Global LSRdias < 0.85 S-1 predicted a 4-fold increased mortality in CA patients with preserved LVEF.STI-derived early diastolic strain rate is a powerful independent predictor of survival in CA patients with preserved LVEF.
A burnout prediction model based around char morphology
Energy Technology Data Exchange (ETDEWEB)
T. Wu; E. Lester; M. Cloke [University of Nottingham, Nottingham (United Kingdom). Nottingham Energy and Fuel Centre
2005-07-01
Poor burnout in a coal-fired power plant has marked penalties in the form of reduced energy efficiency and elevated waste material that can not be utilized. The prediction of coal combustion behaviour in a furnace is of great significance in providing valuable information not only for process optimization but also for coal buyers in the international market. Coal combustion models have been developed that can make predictions about burnout behaviour and burnout potential. Most of these kinetic models require standard parameters such as volatile content, particle size and assumed char porosity in order to make a burnout prediction. This paper presents a new model called the Char Burnout Model (ChB) that also uses detailed information about char morphology in its prediction. The model can use data input from one of two sources. Both sources are derived from image analysis techniques. The first from individual analysis and characterization of real char types using an automated program. The second from predicted char types based on data collected during the automated image analysis of coal particles. Modelling results were compared with a different carbon burnout kinetic model and burnout data from re-firing the chars in a drop tube furnace operating at 1300{sup o}C, 5% oxygen across several residence times. An improved agreement between ChB model and DTF experimental data proved that the inclusion of char morphology in combustion models can improve model predictions. 27 refs., 4 figs., 4 tabs.
Dynamics of a stochastic multi-strain SIS epidemic model driven by Lévy noise
Chen, Can; Kang, Yanmei
2017-01-01
A stochastic multi-strain SIS epidemic model is formulated by introducing Lévy noise into the disease transmission rate of each strain. First, we prove that the stochastic model admits a unique global positive solution, and, by the comparison theorem, we show that the solution remains within a positively invariant set almost surely. Next we investigate stochastic stability of the disease-free equilibrium, including stability in probability and pth moment asymptotic stability. Then sufficient conditions for persistence in the mean of the disease are established. Finally, based on an Euler scheme for Lévy-driven stochastic differential equations, numerical simulations for a stochastic two-strain model are carried out to verify the theoretical results. Moreover, numerical comparison results of the stochastic two-strain model and the deterministic version are also given. Lévy noise can cause the two strains to become extinct almost surely, even though there is a dominant strain that persists in the deterministic model. It can be concluded that the introduction of Lévy noise reduces the disease extinction threshold, which indicates that Lévy noise may suppress the disease outbreak.
Laser-Driven Ramp Compression to Investigate and Model Dynamic Response of Iron at High Strain Rates
Directory of Open Access Journals (Sweden)
Nourou Amadou
2016-12-01
Full Text Available Efficient laser shock processing of materials requires a good characterization of their dynamic response to pulsed compression, and predictive numerical models to simulate the thermomechanical processes governing this response. Due to the extremely high strain rates involved, the kinetics of these processes should be accounted for. In this paper, we present an experimental investigation of the dynamic behavior of iron under laser driven ramp loading, then we compare the results to the predictions of a constitutive model including viscoplasticity and a thermodynamically consistent description of the bcc to hcp phase transformation expected near 13 GPa. Both processes are shown to affect wave propagation and pressure decay, and the influence of the kinetics of the phase transformation on the velocity records is discussed in details.
Identification of strain-rate and thermal sensitive material model with an inverse method
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...
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.
Strain sensor of carbon nanotubes in microscale: from model to metrology.
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.
Application of Tube-Packaged FBG Strain Sensor in Vibration Experiment of Submarine Pipeline Model
Institute of Scientific and Technical Information of China (English)
无
2006-01-01
Optical fiber sensors have received increasing attention in the fields of aeronautic and civil engineering for their superior ability to stand explosion, immunity to electromagnetic interference and high accuracy, especially fit for measurement applications in harsh environment. In this study, a novel FBG (fiber Bragg grating) strain sensor, which is packaged in a 1.2 mm stainless steel tube with epoxy resin, is developed. Experiments are conducted on the universal material testing machine to calibrate its strain transferring characteristics. The sensor has the advantages of small size, high precision and flexible use, and exhibits promising potentials. Five tube-packaged strain FBG sensors have been applied to the vibration experiment of a submarine pipeline model. The strain measured with the FBG sensor agrees well with that measured with the electric resistance strain sensor.
Model-based uncertainty in species range prediction
DEFF Research Database (Denmark)
Pearson, R. G.; Thuiller, Wilfried; Bastos Araujo, Miguel;
2006-01-01
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...... day (using the area under the receiver operating characteristic curve (AUC) and kappa statistics) and by assessing consistency in predictions of range size changes under future climate (using cluster analysis). Results Our analyses show significant differences between predictions from different models......, with predicted changes in range size by 2030 differing in both magnitude and direction (e.g. from 92% loss to 322% gain). We explain differences with reference to two characteristics of the modelling techniques: data input requirements (presence/absence vs. presence-only approaches) and assumptions made by each...
A new ensemble model for short term wind power prediction
DEFF Research Database (Denmark)
Madsen, Henrik; Albu, Razvan-Daniel; Felea, Ioan;
2012-01-01
As the objective of this study, a non-linear ensemble system is used to develop a new model for predicting wind speed in short-term time scale. Short-term wind power prediction becomes an extremely important field of research for the energy sector. Regardless of the recent advancements in the re......-search of prediction models, it was observed that different models have different capabilities and also no single model is suitable under all situations. The idea behind EPS (ensemble prediction systems) is to take advantage of the unique features of each subsystem to detain diverse patterns that exist in the dataset....... The conferred results show that the prediction errors can be decreased, while the computation time is reduced....
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, ...
Energy Technology Data Exchange (ETDEWEB)
Munson, D.E.; Fossum, A.F.; Senseny, P.E. (Sandia National Labs., Albuquerque, NM (USA); Southwest Research Inst., San Antonio, TX (USA); RE/SPEC, Inc., Rapid City, SD (USA))
1989-08-01
The discrepancies between predicted and measured WIPP in situ Room D closures are markedly reduced through the use of a Tresca flow potential, an improved small strain constitutive model, an improved set of material parameters, and a modified stratigraphy. 12 refs., 5 figs., 1 tab.
Energy Technology Data Exchange (ETDEWEB)
Munson, D.E.; Fossum, A.F.; Senseny, P.E.
1989-01-01
The discrepancies between predicted and measured WIPP in situ Room D closures are markedly reduced through the use of a Tresca flow potential, an improved small strain constitutive model, an improved set of material parameters, and a modified stratigraphy. 17 refs., 8 figs., 1 tab.
Energy Technology Data Exchange (ETDEWEB)
Munson, D.E.; Fossum, A.F.; Senseny, P.E. (Sandia National Labs., Albuquerque, NM (USA))
1990-01-01
The discrepancies between predicted and measured Waste Isolation Pilot Plant (WIPP) in-situ Room D closures are markedly reduced through the use of a Tresca flow potential, an improved small strain constitutive model, an improved set of material parameters, and a modified stratigraphy. (author).
Improving Environmental Model Calibration and Prediction
2011-01-18
groundwater model calibration. Adv. Water Resour., 29(4):605–623, 2006. [9] B.E. Skahill, J.S. Baggett, S. Frankenstein , and C.W. Downer. More efficient...of Hydrology, Environmental Modelling & Software, or Water Resources Research). Skahill, B., Baggett, J., Frankenstein , S., and Downer, C.W. (2009
Model Predictive Control for Smart Energy Systems
DEFF Research Database (Denmark)
Halvgaard, Rasmus
load shifting capabilities of the units that adapts to the given price predictions. We furthermore evaluated control performance in terms of economic savings for different control strategies and forecasts. Chapter 5 describes and compares the proposed large-scale Aggregator control strategies....... Aggregators are assumed to play an important role in the future Smart Grid and coordinate a large portfolio of units. The developed economic MPC controllers interfaces each unit directly to an Aggregator. We developed several MPC-based aggregation strategies that coordinates the global behavior of a portfolio...
Using Google Earth to Explore Strain Rate Models of Southern California
Richard, G. A.; Bell, E. A.; Holt, W. E.
2007-12-01
A series of strain rate models for the Transverse Ranges of southern California were developed based on Quaternary fault slip data and geodetic data from high precision GPS stations in southern California. Pacific-North America velocity boundary conditions are applied for all models. Topography changes are calculated using the model dilatation rates, which predict crustal thickness changes under the assumption of Airy isostasy and a specified rate of crustal volume loss through erosion. The models were designed to produce graphical and numerical output representing the configuration of the region from 3 million years ago to 3 million years into the future at intervals of 50 thousand years. Using a North American reference frame, graphical output for the topography and faults and numerical output for locations of faults and points on the crust marked by the locations on cities were used to create data in KML format that can be used in Google Earth to represent time intervals of 50 thousand years. As markers familiar to students, the cities provide a geographic context that can be used to quantify crustal movement, using the Google Earth ruler tool. By comparing distances that markers for selected cities have moved in various parts of the region, students discover that the greatest amount of crustal deformation has occurred in the vicinity of the boundary between the North American and Pacific plates. Students can also identify areas of compression or extension by finding pairs of city markers that have converged or diverged, respectively, over time. The Google Earth layers also reveal that faults that are not parallel to the plate boundary have tended to rotate clockwise due to the right lateral motion along the plate boundary zone. KML TimeSpan markup was added to two versions of the model, enabling the layers to be displayed in an automatic sequenced loop for a movie effect. The data is also available as QuickTime (.mov) and Graphics Interchange Format (.gif
Combining logistic regression and neural networks to create predictive models.
Spackman, K. A.
1992-01-01
Neural networks are being used widely in medicine and other areas to create predictive models from data. The statistical method that most closely parallels neural networks is logistic regression. This paper outlines some ways in which neural networks and logistic regression are similar, shows how a small modification of logistic regression can be used in the training of neural network models, and illustrates the use of this modification for variable selection and predictive model building wit...
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
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.
A thermodynamic model to predict wax formation in petroleum fluids
Energy Technology Data Exchange (ETDEWEB)
Coutinho, J.A.P. [Universidade de Aveiro (Portugal). Dept. de Quimica. Centro de Investigacao em Quimica]. E-mail: jcoutinho@dq.ua.pt; Pauly, J.; Daridon, J.L. [Universite de Pau et des Pays de l' Adour, Pau (France). Lab. des Fluides Complexes
2001-12-01
Some years ago the authors proposed a model for the non-ideality of the solid phase, based on the Predictive Local Composition concept. This was first applied to the Wilson equation and latter extended to NRTL and UNIQUAC models. Predictive UNIQUAC proved to be extraordinarily successful in predicting the behaviour of both model and real hydrocarbon fluids at low temperatures. This work illustrates the ability of Predictive UNIQUAC in the description of the low temperature behaviour of petroleum fluids. It will be shown that using Predictive UNIQUAC in the description of the solid phase non-ideality a complete prediction of the low temperature behaviour of synthetic paraffin solutions, fuels and crude oils is achieved. The composition of both liquid and solid phases, the amount of crystals formed and the cloud points are predicted within the accuracy of the experimental data. The extension of Predictive UNIQUAC to high pressures, by coupling it with an EOS/G{sup E} model based on the SRK EOS used with the LCVM mixing rule, is proposed and predictions of phase envelopes for live oils are compared with experimental data. (author)
A THERMODYNAMIC MODEL TO PREDICT WAX FORMATION IN PETROLEUM FLUIDS
Directory of Open Access Journals (Sweden)
J.A.P. Coutinho
2001-12-01
Full Text Available Some years ago the authors proposed a model for the non-ideality of the solid phase, based on the Predictive Local Composition concept. This was first applied to the Wilson equation and latter extended to NRTL and UNIQUAC models. Predictive UNIQUAC proved to be extraordinarily successful in predicting the behaviour of both model and real hydrocarbon fluids at low temperatures. This work illustrates the ability of Predictive UNIQUAC in the description of the low temperature behaviour of petroleum fluids. It will be shown that using Predictive UNIQUAC in the description of the solid phase non-ideality a complete prediction of the low temperature behaviour of synthetic paraffin solutions, fuels and crude oils is achieved. The composition of both liquid and solid phases, the amount of crystals formed and the cloud points are predicted within the accuracy of the experimental data. The extension of Predictive UNIQUAC to high pressures, by coupling it with an EOS/G E model based on the SRK EOS used with the LCVM mixing rule, is proposed and predictions of phase envelopes for live oils are compared with experimental data.
A Boolean model of the Pseudomonas syringae hrp regulon predicts a tightly regulated system.
Directory of Open Access Journals (Sweden)
Daniel MacLean
Full Text Available The Type III secretion system (TTSS is a protein secretion machinery used by certain gram-negative bacterial pathogens of plants and animals to deliver effector molecules to the host and is at the core of the ability to cause disease. Extensive molecular and biochemical study has revealed the components and their interactions within this system but reductive approaches do not consider the dynamical properties of the system as a whole. In order to gain a better understanding of these dynamical behaviours and to create a basis for the refinement of the experimentally derived knowledge we created a Boolean model of the regulatory interactions within the hrp regulon of Pseudomonas syringae pathovar tomato strain DC3000 Pseudomonas syringae. We compared simulations of the model with experimental data and found them to be largely in accordance, though the hrpV node shows some differences in state changes to that expected. Our simulations also revealed interesting dynamical properties not previously predicted. The model predicts that the hrp regulon is a biologically stable two-state system, with each of the stable states being strongly attractive, a feature indicative of selection for a tightly regulated and responsive system. The model predicts that the state of the GacS/GacA node confers control, a prediction that is consistent with experimental observations that the protein has a role as master regulator. Simulated gene "knock out" experiments with the model predict that HrpL is a central information processing point within the network.
Comparison of ACL strain estimated via a data-driven model with in vitro measurements.
Weinhandl, Joshua T; Hoch, Matthew C; Bawab, Sebastian Y; Ringleb, Stacie I
2016-11-01
Computer modeling and simulation techniques have been increasingly used to investigate anterior cruciate ligament (ACL) loading during dynamic activities in an attempt to improve our understanding of injury mechanisms and development of injury prevention programs. However, the accuracy of many of these models remains unknown and thus the purpose of this study was to compare estimates of ACL strain from a previously developed three-dimensional, data-driven model with those obtained via in vitro measurements. ACL strain was measured as the knee was cycled from approximately 10° to 120° of flexion at 20 deg s(-1) with static loads of 100, 50, and 50 N applied to the quadriceps, biceps femoris and medial hamstrings (semimembranosus and semitendinosus) tendons, respectively. A two segment, five-degree-of-freedom musculoskeletal knee model was then scaled to match the cadaver's anthropometry and in silico ACL strains were then determined based on the knee joint kinematics and moments of force. Maximum and minimum ACL strains estimated in silico were within 0.2 and 0.42% of that measured in vitro, respectively. Additionally, the model estimated ACL strain with a bias (mean difference) of -0.03% and dynamic accuracy (rms error) of 0.36% across the flexion-extension cycle. These preliminary results suggest that the proposed model was capable of estimating ACL strains during a simple flexion-extension cycle. Future studies should validate the model under more dynamic conditions with variable muscle loading. This model could then be used to estimate ACL strains during dynamic sporting activities where ACL injuries are more common.
A systematic review of predictive modeling for bronchiolitis.
Luo, Gang; Nkoy, Flory L; Gesteland, Per H; Glasgow, Tiffany S; Stone, Bryan L
2014-10-01
Bronchiolitis is the most common cause of illness leading to hospitalization in young children. At present, many bronchiolitis management decisions are made subjectively, leading to significant practice variation among hospitals and physicians caring for children with bronchiolitis. To standardize care for bronchiolitis, researchers have proposed various models to predict the disease course to help determine a proper management plan. This paper reviews the existing state of the art of predictive modeling for bronchiolitis. Predictive modeling for respiratory syncytial virus (RSV) infection is covered whenever appropriate, as RSV accounts for about 70% of bronchiolitis cases. A systematic review was conducted through a PubMed search up to April 25, 2014. The literature on predictive modeling for bronchiolitis was retrieved using a comprehensive search query, which was developed through an iterative process. Search results were limited to human subjects, the English language, and children (birth to 18 years). The literature search returned 2312 references in total. After manual review, 168 of these references were determined to be relevant and are discussed in this paper. We identify several limitations and open problems in predictive modeling for bronchiolitis, and provide some preliminary thoughts on how to address them, with the hope to stimulate future research in this domain. Many problems remain open in predictive modeling for bronchiolitis. Future studies will need to address them to achieve optimal predictive models. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.
Osman, Marisol; Vera, C. S.
2016-11-01
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
Predicting and Modelling of Survival Data when Cox's Regression Model does not hold
DEFF Research Database (Denmark)
Scheike, Thomas H.; Zhang, Mei-Jie
2002-01-01
Aalen model; additive risk model; counting processes; competing risk; Cox regression; flexible modeling; goodness of fit; prediction of survival; survival analysis; time-varying effects......Aalen model; additive risk model; counting processes; competing risk; Cox regression; flexible modeling; goodness of fit; prediction of survival; survival analysis; time-varying effects...
Two-dimensional analytical models for asymmetric fully depleted double-gate strained silicon MOSFETs
Institute of Scientific and Technical Information of China (English)
Liu Hong-Xia; Li Jin; Li Bin; Cao Lei; Yuan Bo
2011-01-01
This paper develops the simple and accurate two-dimensional analytical models for new asymmetric double-gate fully depleted strained-Si MOSFET. The models mainly include the analytical equations of the surface potential, surface electric field and threshold voltage, which are derived by solving two dimensional Poisson equation in strained-Si layer.The models are verified by numerical simulation. Besides offering the physical insight into device physics in the model,the new structure also provides the basic designing guidance for further immunity of short channel effect and drain-induced barrier-lowering of CMOS-based devices in nanometre scale.