Predicting the digestible energy of corn determined with growing swine from nutrient composition and cross-species measurements.

PubMed

Smith, B; Hassen, A; Hinds, M; Rice, D; Jones, D; Sauber, T; Iiams, C; Sevenich, D; Allen, R; Owens, F; McNaughton, J; Parsons, C

2015-03-01

The DE values of corn grain for pigs will differ among corn sources. More accurate prediction of DE may improve diet formulation and reduce diet cost. Corn grain sources ( = 83) were assayed with growing swine (20 kg) in DE experiments with total collection of feces, with 3-wk-old broiler chick in nitrogen-corrected apparent ME (AME) trials and with cecectomized adult roosters in nitrogen-corrected true ME (TME) studies. Additional AME data for the corn grain source set was generated based on an existing near-infrared transmittance prediction model (near-infrared transmittance-predicted AME [NIT-AME]). Corn source nutrient composition was determined by wet chemistry methods. These data were then used to 1) test the accuracy of predicting swine DE of individual corn sources based on available literature equations and nutrient composition and 2) develop models for predicting DE of sources from nutrient composition and the cross-species information gathered above (AME, NIT-AME, and TME). The overall measured DE, AME, NIT-AME, and TME values were 4,105 ± 11, 4,006 ± 10, 4,004 ± 10, and 4,086 ± 12 kcal/kg DM, respectively. Prediction models were developed using 80% of the corn grain sources; the remaining 20% was reserved for validation of the developed prediction equation. Literature equations based on nutrient composition proved imprecise for predicting corn DE; the root mean square error of prediction ranged from 105 to 331 kcal/kg, an equivalent of 2.6 to 8.8% error. Yet among the corn composition traits, 4-variable models developed in the current study provided adequate prediction of DE (model ranging from 0.76 to 0.79 and root mean square error [RMSE] of 50 kcal/kg). When prediction equations were tested using the validation set, these models had a 1 to 1.2% error of prediction. Simple linear equations from AME, NIT-AME, or TME provided an accurate prediction of DE for individual sources ( ranged from 0.65 to 0.73 and RMSE ranged from 50 to 61 kcal/kg). Percentage error of prediction based on the validation data set was greater (1.4%) for the TME model than for the NIT-AME or AME models (1 and 1.2%, respectively), indicating that swine DE values could be accurately predicted by using AME or NIT-AME. In conclusion, regression equations developed from broiler measurements or from analyzed nutrient composition proved adequate to reliably predict the DE of commercially available corn hybrids for growing pigs.

Ridge regression for predicting elastic moduli and hardness of calcium aluminosilicate glasses

NASA Astrophysics Data System (ADS)

Deng, Yifan; Zeng, Huidan; Jiang, Yejia; Chen, Guorong; Chen, Jianding; Sun, Luyi

2018-03-01

It is of great significance to design glasses with satisfactory mechanical properties predictively through modeling. Among various modeling methods, data-driven modeling is such a reliable approach that can dramatically shorten research duration, cut research cost and accelerate the development of glass materials. In this work, the ridge regression (RR) analysis was used to construct regression models for predicting the compositional dependence of CaO-Al2O3-SiO2 glass elastic moduli (Shear, Bulk, and Young’s moduli) and hardness based on the ternary diagram of the compositions. The property prediction over a large glass composition space was accomplished with known experimental data of various compositions in the literature, and the simulated results are in good agreement with the measured ones. This regression model can serve as a facile and effective tool for studying the relationship between the compositions and the property, enabling high-efficient design of glasses to meet the requirements for specific elasticity and hardness.

Predicting seasonal diet in the yellow-bellied marmot: success and failure for the linear programming model.

PubMed

Edwards, G P

1997-10-01

Seasonal diet selection in the yellow-bellied marmot (Marmota flaviventris) was studied at two sites in Montana during 1991 and 1992. A linear programming model of optimal diet selection successfully predicted the composition of observed diets (monocot versus dicot) in eight out of ten cases early in the active season (April-June). During this period, adult, yearling and juvenile marmots selected diets consistent with the predicted goal of energy maximisation. However, late in the active season (July-August), the model predicted the diet composition in only one out of six cases. In all six late-season determinations, the model underestimated the amount of monocot in the diet. Possible reasons why the model failed to reliably predict diet composition late in the active season are discussed.

Experimental verification of a progressive damage model for composite laminates based on continuum damage mechanics. M.S. Thesis Final Report

NASA Technical Reports Server (NTRS)

Coats, Timothy William

1994-01-01

Progressive failure is a crucial concern when using laminated composites in structural design. Therefore the ability to model damage and predict the life of laminated composites is vital. The purpose of this research was to experimentally verify the application of the continuum damage model, a progressive failure theory utilizing continuum damage mechanics, to a toughened material system. Damage due to tension-tension fatigue was documented for the IM7/5260 composite laminates. Crack density and delamination surface area were used to calculate matrix cracking and delamination internal state variables, respectively, to predict stiffness loss. A damage dependent finite element code qualitatively predicted trends in transverse matrix cracking, axial splits and local stress-strain distributions for notched quasi-isotropic laminates. The predictions were similar to the experimental data and it was concluded that the continuum damage model provided a good prediction of stiffness loss while qualitatively predicting damage growth in notched laminates.

Modelling Behaviour of a Carbon Epoxy Composite Exposed to Fire: Part II—Comparison with Experimental Results

PubMed Central

Tranchard, Pauline; Samyn, Fabienne; Duquesne, Sophie; Estèbe, Bruno; Bourbigot, Serge

2017-01-01

Based on a phenomenological methodology, a three dimensional (3D) thermochemical model was developed to predict the temperature profile, the mass loss and the decomposition front of a carbon-reinforced epoxy composite laminate (T700/M21 composite) exposed to fire conditions. This 3D model takes into account the energy accumulation by the solid material, the anisotropic heat conduction, the thermal decomposition of the material, the gas mass flow into the composite, and the internal pressure. Thermophysical properties defined as temperature dependant properties were characterised using existing as well as innovative methodologies in order to use them as inputs into our physical model. The 3D thermochemical model accurately predicts the measured mass loss and observed decomposition front when the carbon fibre/epoxy composite is directly impacted by a propane flame. In short, the model shows its capability to predict the fire behaviour of a carbon fibre reinforced composite for fire safety engineering. PMID:28772836

Modelling Behaviour of a Carbon Epoxy Composite Exposed to Fire: Part II-Comparison with Experimental Results.

PubMed

Tranchard, Pauline; Samyn, Fabienne; Duquesne, Sophie; Estèbe, Bruno; Bourbigot, Serge

2017-04-28

Based on a phenomenological methodology, a three dimensional (3D) thermochemical model was developed to predict the temperature profile, the mass loss and the decomposition front of a carbon-reinforced epoxy composite laminate (T700/M21 composite) exposed to fire conditions. This 3D model takes into account the energy accumulation by the solid material, the anisotropic heat conduction, the thermal decomposition of the material, the gas mass flow into the composite, and the internal pressure. Thermophysical properties defined as temperature dependant properties were characterised using existing as well as innovative methodologies in order to use them as inputs into our physical model. The 3D thermochemical model accurately predicts the measured mass loss and observed decomposition front when the carbon fibre/epoxy composite is directly impacted by a propane flame. In short, the model shows its capability to predict the fire behaviour of a carbon fibre reinforced composite for fire safety engineering.

Probabilistic fatigue life prediction of metallic and composite materials

NASA Astrophysics Data System (ADS)

Xiang, Yibing

Fatigue is one of the most common failure modes for engineering structures, such as aircrafts, rotorcrafts and aviation transports. Both metallic materials and composite materials are widely used and affected by fatigue damage. Huge uncertainties arise from material properties, measurement noise, imperfect models, future anticipated loads and environmental conditions. These uncertainties are critical issues for accurate remaining useful life (RUL) prediction for engineering structures in service. Probabilistic fatigue prognosis considering various uncertainties is of great importance for structural safety. The objective of this study is to develop probabilistic fatigue life prediction models for metallic materials and composite materials. A fatigue model based on crack growth analysis and equivalent initial flaw size concept is proposed for metallic materials. Following this, the developed model is extended to include structural geometry effects (notch effect), environmental effects (corroded specimens) and manufacturing effects (shot peening effects). Due to the inhomogeneity and anisotropy, the fatigue model suitable for metallic materials cannot be directly applied to composite materials. A composite fatigue model life prediction is proposed based on a mixed-mode delamination growth model and a stiffness degradation law. After the development of deterministic fatigue models of metallic and composite materials, a general probabilistic life prediction methodology is developed. The proposed methodology combines an efficient Inverse First-Order Reliability Method (IFORM) for the uncertainty propogation in fatigue life prediction. An equivalent stresstransformation has been developed to enhance the computational efficiency under realistic random amplitude loading. A systematical reliability-based maintenance optimization framework is proposed for fatigue risk management and mitigation of engineering structures.

Strain Rate Dependent Deformation and Strength Modeling of a Polymer Matrix Composite Utilizing a Micromechanics Approach. Degree awarded by Cincinnati Univ.

NASA Technical Reports Server (NTRS)

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 compare reasonably well to experimental values, with some discrepancies. The discrepancies are at least partially caused by the method used to integrate the rate equations in the polymer constitutive model.

Predicting Jakarta composite index using hybrid of fuzzy time series and support vector regression models

NASA Astrophysics Data System (ADS)

Febrian Umbara, Rian; Tarwidi, Dede; Budi Setiawan, Erwin

2018-03-01

The paper discusses the prediction of Jakarta Composite Index (JCI) in Indonesia Stock Exchange. The study is based on JCI historical data for 1286 days to predict the value of JCI one day ahead. This paper proposes predictions done in two stages., The first stage using Fuzzy Time Series (FTS) to predict values of ten technical indicators, and the second stage using Support Vector Regression (SVR) to predict the value of JCI one day ahead, resulting in a hybrid prediction model FTS-SVR. The performance of this combined prediction model is compared with the performance of the single stage prediction model using SVR only. Ten technical indicators are used as input for each model.

Constitutive Modeling of Piezoelectric Polymer Composites

NASA Technical Reports Server (NTRS)

Odegard, Gregory M.; Gates, Tom (Technical Monitor)

2003-01-01

A new modeling approach is proposed for predicting the bulk electromechanical properties of piezoelectric composites. The proposed model offers the same level of convenience as the well-known Mori-Tanaka method. In addition, it is shown to yield predicted properties that are, in most cases, more accurate or equally as accurate as the Mori-Tanaka scheme. In particular, the proposed method is used to determine the electromechanical properties of four piezoelectric polymer composite materials as a function of inclusion volume fraction. The predicted properties are compared to those calculated using the Mori-Tanaka and finite element methods.

Diagnostic, Predictive and Compositional Modeling with Data Mining in Integrated Learning Environments

ERIC Educational Resources Information Center

Lee, Chien-Sing

2007-01-01

Models represent a set of generic patterns to test hypotheses. This paper presents the CogMoLab student model in the context of an integrated learning environment. Three aspects are discussed: diagnostic and predictive modeling with respect to the issues of credit assignment and scalability and compositional modeling of the student profile in the…

Modeling and Predicting the Stress Relaxation of Composites with Short and Randomly Oriented Fibers

PubMed Central

Obaid, Numaira; Sain, Mohini

2017-01-01

The addition of short fibers has been experimentally observed to slow the stress relaxation of viscoelastic polymers, producing a change in the relaxation time constant. Our recent study attributed this effect of fibers on stress relaxation behavior to the interfacial shear stress transfer at the fiber-matrix interface. This model explained the effect of fiber addition on stress relaxation without the need to postulate structural changes at the interface. In our previous study, we developed an analytical model for the effect of fully aligned short fibers, and the model predictions were successfully compared to finite element simulations. However, in most industrial applications of short-fiber composites, fibers are not aligned, and hence it is necessary to examine the time dependence of viscoelastic polymers containing randomly oriented short fibers. In this study, we propose an analytical model to predict the stress relaxation behavior of short-fiber composites where the fibers are randomly oriented. The model predictions were compared to results obtained from Monte Carlo finite element simulations, and good agreement between the two was observed. The analytical model provides an excellent tool to accurately predict the stress relaxation behavior of randomly oriented short-fiber composites. PMID:29053601

A mathematical model for regulating monomer composition of the microbially synthesized polyhydroxyalkanoate copolymers.

PubMed

Xu, Jun; Guo, Baohua; Zhang, Zengmin; Wu, Qiong; Zhou, Quan; Chen, Jinchun; Chen, Guoqiang; Li, Guodong

2005-06-30

A mathematical model is proposed for predicting the copolymer composition of the microbially synthesized polyhydroxyalkanoate (PHA) copolymers. Based on the biochemical reactions involved in the precursor formation and polymerization pathways, the model correlates the copolymer composition with the cultivation conditions, the enzyme levels and selectivity, and the metabolic pathways. It suggests the following points: (1) in the case of a sole carbon source, the copolymer composition depends mainly on the topology of the metabolic pathways and the selectivity of both the enzymes involved in the precursor formation and the polymerization route; (2) the copolymer composition can be varied in a wide range via alteration of the flux ratio of different types of monomers channeled from two or more independent and simultaneous pathways; (3) the enzymes which should be over-expressed or inhibited to obtain the desired copolymer composition can be predicted. For example, inhibition of the beta-oxidation pathway will increase the content of the monomer units with longer chain length. To test the model, various experiments were envisaged by varying cultivation time, concentration and chain length of the sole carbon source, and molar ratio of the cosubstrates. The predictions from the model agree well with the experimental results. Therefore, the proposed model will be useful in predicting the PHA copolymer composition under different biochemical reaction conditions. In other words, it can provide a guide for the synthesis of desired PHA copolymers.

A Theoretical Model for Predicting Fracture Strength and Critical Flaw Size of the ZrB2-ZrC Composites at High Temperatures

NASA Astrophysics Data System (ADS)

Wang, Ruzhuan; Li, Xiaobo; Wang, Jing; Jia, Bi; Li, Weiguo

2018-06-01

This work shows a new rational theoretical model for quantitatively predicting fracture strength and critical flaw size of the ZrB2-ZrC composites at different temperatures, which is based on a new proposed temperature dependent fracture surface energy model and the Griffith criterion. The fracture model takes into account the combined effects of temperature and damage terms (surface flaws and internal flaws) with no any fitting parameters. The predictions of fracture strength and critical flaw size of the ZrB2-ZrC composites at high temperatures agree well with experimental data. Then using the theoretical method, the improvement and design of materials are proposed. The proposed model can be used to predict the fracture strength, find the critical flaw and study the effects of microstructures on the fracture mechanism of the ZrB2-ZrC composites at high temperatures, which thus could become a potential convenient, practical and economical technical means for predicting fracture properties and material design.

Multiscale modeling of PVDF matrix carbon fiber composites

NASA Astrophysics Data System (ADS)

Greminger, Michael; Haghiashtiani, Ghazaleh

2017-06-01

Self-sensing carbon fiber reinforced composites have the potential to enable structural health monitoring that is inherent to the composite material rather than requiring external or embedded sensors. It has been demonstrated that a self-sensing carbon fiber reinforced polymer composite can be created by using the piezoelectric polymer polyvinylidene difluoride (PVDF) as the matrix material and using a Kevlar layer to separate two carbon fiber layers. In this configuration, the electrically conductive carbon fiber layers act as electrodes and the Kevlar layer acts as a dielectric to prevent the electrical shorting of the carbon fiber layers. This composite material has been characterized experimentally for its effective d 33 and d 31 piezoelectric coefficients. However, for design purposes, it is desirable to obtain a predictive model of the effective piezoelectric coefficients for the final smart composite material. Also, the inverse problem can be solved to determine the degree of polarization obtained in the PVDF material during polarization by comparing the effective d 33 and d 31 values obtained in experiment to those predicted by the finite element model. In this study, a multiscale micromechanics and coupled piezoelectric-mechanical finite element modeling approach is introduced to predict the mechanical and piezoelectric performance of a plain weave carbon fiber reinforced PVDF composite. The modeling results show good agreement with the experimental results for the mechanical and electrical properties of the composite. In addition, the degree of polarization of the PVDF component of the composite is predicted using this multiscale modeling approach and shows that there is opportunity to drastically improve the smart composite’s performance by improving the polarization procedure.

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

NASA Technical Reports Server (NTRS)

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 procedures and residual strain predications, and discusses pertinent experimental results from the validation studies.

An Integrated Approach Linking Process to Structural Modeling With Microstructural Characterization for Injections-Molded Long-Fiber Thermoplastics

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

Nguyen, Ba Nghiep; Bapanapalli, Satish K.; Smith, Mark T.

2008-09-01

The objective of our work is to enable the optimum design of lightweight automotive structural components using injection-molded long fiber thermoplastics (LFTs). To this end, an integrated approach that links process modeling to structural analysis with experimental microstructural characterization and validation is developed. First, process models for LFTs are developed and implemented into processing codes (e.g. ORIENT, Moldflow) to predict the microstructure of the as-formed composite (i.e. fiber length and orientation distributions). In parallel, characterization and testing methods are developed to obtain necessary microstructural data to validate process modeling predictions. Second, the predicted LFT composite microstructure is imported into amore » structural finite element analysis by ABAQUS to determine the response of the as-formed composite to given boundary conditions. At this stage, constitutive models accounting for the composite microstructure are developed to predict various types of behaviors (i.e. thermoelastic, viscoelastic, elastic-plastic, damage, fatigue, and impact) of LFTs. Experimental methods are also developed to determine material parameters and to validate constitutive models. Such a process-linked-structural modeling approach allows an LFT composite structure to be designed with confidence through numerical simulations. Some recent results of our collaborative research will be illustrated to show the usefulness and applications of this integrated approach.« less

Advanced numerical models and material characterisation techniques for composite materials subject to impact and shock wave loading

NASA Astrophysics Data System (ADS)

Clegg, R. A.; White, D. M.; Hayhurst, C.; Ridel, W.; Harwick, W.; Hiermaier, S.

2003-09-01

The development and validation of an advanced material model for orthotropic materials, such as fibre reinforced composites, is described. The model is specifically designed to facilitate the numerical simulation of impact and shock wave propagation through orthotropic materials and the prediction of subsequent material damage. Initial development of the model concentrated on correctly representing shock wave propagation in composite materials under high and hypervelocity impact conditions [1]. This work has now been extended to further concentrate on the development of improved numerical models and material characterisation techniques for the prediction of damage, including residual strength, in fibre reinforced composite materials. The work is focussed on Kevlar-epoxy however materials such as CFRP are also being considered. The paper describes our most recent activities in relation to the implementation of advanced material modelling options in this area. These enable refined non-liner directional characteristics of composite materials to be modelled, in addition to the correct thermodynamic response under shock wave loading. The numerical work is backed by an extensive experimental programme covering a wide range of static and dynamic tests to facilitate derivation of model input data and to validate the predicted material response. Finally, the capability of the developing composite material model is discussed in relation to a hypervelocity impact problem.

Predicting community composition from pairwise interactions

NASA Astrophysics Data System (ADS)

Friedman, Jonathan; Higgins, Logan; Gore, Jeff

The ability to predict the structure of complex, multispecies communities is crucial for understanding the impact of species extinction and invasion on natural communities, as well as for engineering novel, synthetic communities. Communities are often modeled using phenomenological models, such as the classical generalized Lotka-Volterra (gLV) model. While a lot of our intuition comes from such models, their predictive power has rarely been tested experimentally. To directly assess the predictive power of this approach, we constructed synthetic communities comprised of up to 8 soil bacteria. We measured the outcome of competition between all species pairs, and used these measurements to predict the composition of communities composed of more than 2 species. The pairwise competitions resulted in a diverse set of outcomes, including coexistence, exclusion, and bistability, and displayed evidence for both interference and facilitation. Most pair outcomes could be captured by the gLV framework, and the composition of multispecies communities could be predicted for communities composed solely of such pairs. Our results demonstrate the predictive ability and utility of simple phenomenology, which enables accurate predictions in the absence of mechanistic details.

Modeling heterogeneous (co)variances from adjacent-SNP groups improves genomic prediction for milk protein composition traits.

PubMed

Gebreyesus, Grum; Lund, Mogens S; Buitenhuis, Bart; Bovenhuis, Henk; Poulsen, Nina A; Janss, Luc G

2017-12-05

Accurate genomic prediction requires a large reference population, which is problematic for traits that are expensive to measure. Traits related to milk protein composition are not routinely recorded due to costly procedures and are considered to be controlled by a few quantitative trait loci of large effect. The amount of variation explained may vary between regions leading to heterogeneous (co)variance patterns across the genome. Genomic prediction models that can efficiently take such heterogeneity of (co)variances into account can result in improved prediction reliability. In this study, we developed and implemented novel univariate and bivariate Bayesian prediction models, based on estimates of heterogeneous (co)variances for genome segments (BayesAS). Available data consisted of milk protein composition traits measured on cows and de-regressed proofs of total protein yield derived for bulls. Single-nucleotide polymorphisms (SNPs), from 50K SNP arrays, were grouped into non-overlapping genome segments. A segment was defined as one SNP, or a group of 50, 100, or 200 adjacent SNPs, or one chromosome, or the whole genome. Traditional univariate and bivariate genomic best linear unbiased prediction (GBLUP) models were also run for comparison. Reliabilities were calculated through a resampling strategy and using deterministic formula. BayesAS models improved prediction reliability for most of the traits compared to GBLUP models and this gain depended on segment size and genetic architecture of the traits. The gain in prediction reliability was especially marked for the protein composition traits β-CN, κ-CN and β-LG, for which prediction reliabilities were improved by 49 percentage points on average using the MT-BayesAS model with a 100-SNP segment size compared to the bivariate GBLUP. Prediction reliabilities were highest with the BayesAS model that uses a 100-SNP segment size. The bivariate versions of our BayesAS models resulted in extra gains of up to 6% in prediction reliability compared to the univariate versions. Substantial improvement in prediction reliability was possible for most of the traits related to milk protein composition using our novel BayesAS models. Grouping adjacent SNPs into segments provided enhanced information to estimate parameters and allowing the segments to have different (co)variances helped disentangle heterogeneous (co)variances across the genome.

Prediction of composite fatigue life under variable amplitude loading using artificial neural network trained by genetic algorithm

NASA Astrophysics Data System (ADS)

Rohman, Muhamad Nur; Hidayat, Mas Irfan P.; Purniawan, Agung

2018-04-01

Neural networks (NN) have been widely used in application of fatigue life prediction. In the use of fatigue life prediction for polymeric-base composite, development of NN model is necessary with respect to the limited fatigue data and applicable to be used to predict the fatigue life under varying stress amplitudes in the different stress ratios. In the present paper, Multilayer-Perceptrons (MLP) model of neural network is developed, and Genetic Algorithm was employed to optimize the respective weights of NN for prediction of polymeric-base composite materials under variable amplitude loading. From the simulation result obtained with two different composite systems, named E-glass fabrics/epoxy (layups [(±45)/(0)2]S), and E-glass/polyester (layups [90/0/±45/0]S), NN model were trained with fatigue data from two different stress ratios, which represent limited fatigue data, can be used to predict another four and seven stress ratios respectively, with high accuracy of fatigue life prediction. The accuracy of NN prediction were quantified with the small value of mean square error (MSE). When using 33% from the total fatigue data for training, the NN model able to produce high accuracy for all stress ratios. When using less fatigue data during training (22% from the total fatigue data), the NN model still able to produce high coefficient of determination between the prediction result compared with obtained by experiment.

Modelling and simulation of the consolidation behavior during thermoplastic prepreg composites forming process

NASA Astrophysics Data System (ADS)

Xiong, H.; Hamila, N.; Boisse, P.

2017-10-01

Pre-impregnated thermoplastic composites have recently attached increasing interest in the automotive industry for their excellent mechanical properties and their rapid cycle manufacturing process, modelling and numerical simulations of forming processes for composites parts with complex geometry is necessary to predict and optimize manufacturing practices, especially for the consolidation effects. A viscoelastic relaxation model is proposed to characterize the consolidation behavior of thermoplastic prepregs based on compaction tests with a range of temperatures. The intimate contact model is employed to predict the evolution of the consolidation which permits the microstructure prediction of void presented through the prepreg. Within a hyperelastic framework, several simulation tests are launched by combining a new developed solid shell finite element and the consolidation models.

The prediction of the flash point for binary aqueous-organic solutions.

PubMed

Liaw, Horng-Jang; Chiu, Yi-Yu

2003-07-18

A mathematical model, which may be used for predicting the flash point of aqueous-organic solutions, has been proposed and subsequently verified by experimentally-derived data. The results reveal that this model is able to precisely predict the flash point over the entire composition range of binary aqueous-organic solutions by way of utilizing the flash point data pertaining to the flammable component. The derivative of flash point with respect to composition (solution composition effect upon flash point) can be applied to process safety design/operation in order to identify as to whether the dilution of a flammable liquid solution with water is effective in reducing the fire and explosion hazard of the solution at a specified composition. Such a derivative equation was thus derived based upon the flash point prediction model referred to above and then verified by the application of experimentally-derived data.

Comparison Of Models Of Metal-Matrix Composites

NASA Technical Reports Server (NTRS)

Bigelow, C. A.; Johnson, W. S.; Naik, R. A.

1994-01-01

Report presents comparative review of four mathematical models of micromechanical behaviors of fiber/metal-matrix composite materials. Models differ in various details, all based on properties of fiber and matrix constituent materials, all involve square arrays of fibers continuous and parallel and all assume complete bonding between constituents. Computer programs implementing models used to predict properties and stress-vs.-strain behaviors of unidirectional- and cross-ply laminated composites made of boron fibers in aluminum matrices and silicon carbide fibers in titanium matrices. Stresses in fiber and matrix constituent materials also predicted.

A model for predicting high-temperature fatigue failure of a W/Cu composite

NASA Technical Reports Server (NTRS)

Verrilli, M. J.; Kim, Y.-S.; Gabb, T. P.

1991-01-01

The material studied, a tungsten-fiber-reinforced, copper-matrix composite, is a candidate material for rocket nozzle liner applications. It was shown that at high temperatures, fatigue cracks initiate and propagate inside the copper matrix through a process of initiation, growth, and coalescence of grain boundary cavities. The ductile tungsten fibers neck and rupture locally after the surrounding matrix fails, and complete failure of the composite then ensues. A simple fatigue life prediction model is presented for the tungsten/copper composite system.

Network model for thermal conductivities of unidirectional fiber-reinforced composites

NASA Astrophysics Data System (ADS)

Wang, Yang; Peng, Chaoyi; Zhang, Weihua

2014-12-01

An empirical network model has been developed to predict the in-plane thermal conductivities along arbitrary directions for unidirectional fiber-reinforced composites lamina. Measurements of thermal conductivities along different orientations were carried out. Good agreement was observed between values predicted by the network model and the experimental data; compared with the established analytical models, the newly proposed network model could give values with higher precision. Therefore, this network model is helpful to get a wider and more comprehensive understanding of heat transmission characteristics of fiber-reinforced composites and can be utilized as guidance to design and fabricate laminated composites with specific directional or specific locational thermal conductivities for structures that simultaneously perform mechanical and thermal functions, i.e. multifunctional structures (MFS).

Composite Stress Rupture: A New Reliability Model Based on Strength Decay

NASA Technical Reports Server (NTRS)

Reeder, James R.

2012-01-01

A model is proposed to estimate reliability for stress rupture of composite overwrap pressure vessels (COPVs) and similar composite structures. This new reliability model is generated by assuming a strength degradation (or decay) over time. The model suggests that most of the strength decay occurs late in life. The strength decay model will be shown to predict a response similar to that predicted by a traditional reliability model for stress rupture based on tests at a single stress level. In addition, the model predicts that even though there is strength decay due to proof loading, a significant overall increase in reliability is gained by eliminating any weak vessels, which would fail early. The model predicts that there should be significant periods of safe life following proof loading, because time is required for the strength to decay from the proof stress level to the subsequent loading level. Suggestions for testing the strength decay reliability model have been made. If the strength decay reliability model predictions are shown through testing to be accurate, COPVs may be designed to carry a higher level of stress than is currently allowed, which will enable the production of lighter structures

Deformation, Failure, and Fatigue Life of SiC/Ti-15-3 Laminates Accurately Predicted by MAC/GMC

NASA Technical Reports Server (NTRS)

Bednarcyk, Brett A.; Arnold, Steven M.

2002-01-01

NASA Glenn Research Center's Micromechanics Analysis Code with Generalized Method of Cells (MAC/GMC) (ref.1) has been extended to enable fully coupled macro-micro deformation, failure, and fatigue life predictions for advanced metal matrix, ceramic matrix, and polymer matrix composites. Because of the multiaxial nature of the code's underlying micromechanics model, GMC--which allows the incorporation of complex local inelastic constitutive models--MAC/GMC finds its most important application in metal matrix composites, like the SiC/Ti-15-3 composite examined here. Furthermore, since GMC predicts the microscale fields within each constituent of the composite material, submodels for local effects such as fiber breakage, interfacial debonding, and matrix fatigue damage can and have been built into MAC/GMC. The present application of MAC/GMC highlights the combination of these features, which has enabled the accurate modeling of the deformation, failure, and life of titanium matrix composites.

Prediction of the true digestible amino acid contents from the chemical composition of sorghum grain for poultry.

PubMed

Ebadi, M R; Sedghi, M; Golian, A; Ahmadi, H

2011-10-01

Accurate knowledge of true digestible amino acid (TDAA) contents of feedstuffs is necessary to accurately formulate poultry diets for profitable production. Several experimental approaches that are highly expensive and time consuming have been used to determine available amino acids. Prediction of the nutritive value of a feed ingredient from its chemical composition via regression methodology has been attempted for many years. The artificial neural network (ANN) model is a powerful method that may describe the relationship between digestible amino acid contents and chemical composition. Therefore, multiple linear regressions (MLR) and ANN models were developed for predicting the TDAA contents of sorghum grain based on chemical composition. A precision-fed assay trial using cecectomized roosters was performed to determine the TDAA contents in 48 sorghum samples from 12 sorghum varieties differing in chemical composition. The input variables for both MLR and ANN models were CP, ash, crude fiber, ether extract, and total phenols whereas the output variable was each individual TDAA for every sample. The results of this study revealed that it is possible to satisfactorily estimate the TDAA of sorghum grain through its chemical composition. The chemical composition of sorghum grain seems to highly influence the TDAA contents when considering components such as CP, crude fiber, ether extract, ash and total phenols. It is also possible to estimate the TDAA contents through multiple regression equations with reasonable accuracy depending on composition. However, a more satisfactory prediction may be achieved via ANN for all amino acids. The R(2) values for the ANN model corresponding to testing and training parameters showed a higher accuracy of prediction than equations established by the MLR method. In addition, the current data confirmed that chemical composition, often considered in total amino acid prediction, could be also a useful predictor of true digestible values of selected amino acids for poultry.

Biochemical methane potential prediction of plant biomasses: Comparing chemical composition versus near infrared methods and linear versus non-linear models.

PubMed

Godin, Bruno; Mayer, Frédéric; Agneessens, Richard; Gerin, Patrick; Dardenne, Pierre; Delfosse, Philippe; Delcarte, Jérôme

2015-01-01

The reliability of different models to predict the biochemical methane potential (BMP) of various plant biomasses using a multispecies dataset was compared. The most reliable prediction models of the BMP were those based on the near infrared (NIR) spectrum compared to those based on the chemical composition. The NIR predictions of local (specific regression and non-linear) models were able to estimate quantitatively, rapidly, cheaply and easily the BMP. Such a model could be further used for biomethanation plant management and optimization. The predictions of non-linear models were more reliable compared to those of linear models. The presentation form (green-dried, silage-dried and silage-wet form) of biomasses to the NIR spectrometer did not influence the performances of the NIR prediction models. The accuracy of the BMP method should be improved to enhance further the BMP prediction models. Copyright © 2014 Elsevier Ltd. All rights reserved.

Navy Fuel Composition and Screening Tool (FCAST) v2.8

DTIC Science & Technology

2016-05-10

allowed us to develop partial least squares (PLS) models based on gas chromatography–mass spectrometry (GC-MS) data that predict fuel properties. The...Chemometric property modeling Partial least squares PLS Compositional profiler Naval Air Systems Command Air-4.4.5 Patuxent River Naval Air Station Patuxent...Cumulative predicted residual error sum of squares DiEGME Diethylene glycol monomethyl ether FCAST Fuel Composition and Screening Tool FFP Fit for

Modeling of short fiber reinforced injection moulded composite

NASA Astrophysics Data System (ADS)

Kulkarni, A.; Aswini, N.; Dandekar, C. R.; Makhe, S.

2012-09-01

A micromechanics based finite element model (FEM) is developed to facilitate the design of a new production quality fiber reinforced plastic injection molded part. The composite part under study is composed of a polyetheretherketone (PEEK) matrix reinforced with 30% by volume fraction of short carbon fibers. The constitutive material models are obtained by using micromechanics based homogenization theories. The analysis is carried out by successfully coupling two commercial codes, Moldflow and ANSYS. Moldflow software is used to predict the fiber orientation by considering the flow kinetics and molding parameters. Material models are inputted into the commercial software ANSYS as per the predicted fiber orientation and the structural analysis is carried out. Thus in the present approach a coupling between two commercial codes namely Moldflow and ANSYS has been established to enable the analysis of the short fiber reinforced injection moulded composite parts. The load-deflection curve is obtained based on three constitutive material model namely an isotropy, transversely isotropy and orthotropy. Average values of the predicted quantities are compared to experimental results, obtaining a good correlation. In this manner, the coupled Moldflow-ANSYS model successfully predicts the load deflection curve of a composite injection molded part.

Modeling the Tensile Behavior of Cross-Ply C/SiC Ceramic-Matrix Composites

NASA Astrophysics Data System (ADS)

Li, L. B.; Song, Y. D.; Sun, Y. C.

2015-07-01

The tensile behavior of cross-ply C/SiC ceramic-matrix composites (CMCs) at room temperature has been investigated. Under tensile loading, the damage evolution process was observed with an optical microscope. A micromechanical approach was developed to predict the tensile stress-strain curve, which considers the damage mechanisms of transverse multicracking, matrix multicracking, fiber/matrix interface debonding, and fiber fracture. The shear-lag model was used to describe the microstress field of the damaged composite. By combining the shear-lag model with different damage models, the tensile stress-strain curve of cross-ply CMCs corresponding to each damage stage was modeled. The predicted tensile stress-strain curves of cross-ply C/SiC composites agreed with experimental data.

Properties predictive modeling through the concept of a hybrid interphase existing between phases in contact

NASA Astrophysics Data System (ADS)

Portan, D. V.; Papanicolaou, G. C.

2018-02-01

From practical point of view, predictive modeling based on the physics of composite material behavior is wealth generating; by guiding material system selection and process choices, by cutting down on experimentation and associated costs; and by speeding up the time frame from the research stage to the market place. The presence of areas with different properties and the existence of an interphase between them have a pronounced influence on the behavior of a composite system. The Viscoelastic Hybrid Interphase Model (VHIM), considers the existence of a non-homogeneous viscoelastic and anisotropic interphase having properties depended on the degree of adhesion between the two phases in contact. The model applies for any physical/mechanical property (e.g. mechanical, thermal, electrical and/or biomechanical). Knowing the interphasial variation of a specific property one can predict the corresponding macroscopic behavior of the composite. Moreover, the model acts as an algorithm and a two-way approach can be used: (i) phases in contact may be chosen to get the desired properties of the final composite system or (ii) the initial phases in contact determine the final behavior of the composite system, that can be approximately predicted. The VHIM has been proven, amongst others, to be extremely useful in biomaterial designing for improved contact with human tissues.

Prediction of mitochondrial proteins of malaria parasite using split amino acid composition and PSSM profile.

PubMed

Verma, Ruchi; Varshney, Grish C; Raghava, G P S

2010-06-01

The rate of human death due to malaria is increasing day-by-day. Thus the malaria causing parasite Plasmodium falciparum (PF) remains the cause of concern. With the wealth of data now available, it is imperative to understand protein localization in order to gain deeper insight into their functional roles. In this manuscript, an attempt has been made to develop prediction method for the localization of mitochondrial proteins. In this study, we describe a method for predicting mitochondrial proteins of malaria parasite using machine-learning technique. All models were trained and tested on 175 proteins (40 mitochondrial and 135 non-mitochondrial proteins) and evaluated using five-fold cross validation. We developed a Support Vector Machine (SVM) model for predicting mitochondrial proteins of P. falciparum, using amino acids and dipeptides composition and achieved maximum MCC 0.38 and 0.51, respectively. In this study, split amino acid composition (SAAC) is used where composition of N-termini, C-termini, and rest of protein is computed separately. The performance of SVM model improved significantly from MCC 0.38 to 0.73 when SAAC instead of simple amino acid composition was used as input. In addition, SVM model has been developed using composition of PSSM profile with MCC 0.75 and accuracy 91.38%. We achieved maximum MCC 0.81 with accuracy 92% using a hybrid model, which combines PSSM profile and SAAC. When evaluated on an independent dataset our method performs better than existing methods. A web server PFMpred has been developed for predicting mitochondrial proteins of malaria parasites ( http://www.imtech.res.in/raghava/pfmpred/).

Time prediction of failure a type of lamps by using general composite hazard rate model

NASA Astrophysics Data System (ADS)

Riaman; Lesmana, E.; Subartini, B.; Supian, S.

2018-03-01

This paper discusses the basic survival model estimates to obtain the average predictive value of lamp failure time. This estimate is for the parametric model, General Composite Hazard Level Model. The random time variable model used is the exponential distribution model, as the basis, which has a constant hazard function. In this case, we discuss an example of survival model estimation for a composite hazard function, using an exponential model as its basis. To estimate this model is done by estimating model parameters, through the construction of survival function and empirical cumulative function. The model obtained, will then be used to predict the average failure time of the model, for the type of lamp. By grouping the data into several intervals and the average value of failure at each interval, then calculate the average failure time of a model based on each interval, the p value obtained from the tes result is 0.3296.

Experimental Verification of a Progressive Damage Model for IM7/5260 Laminates Subjected to Tension-Tension Fatigue

NASA Technical Reports Server (NTRS)

Coats, Timothy W.; Harris, Charles E.

1995-01-01

The durability and damage tolerance of laminated composites are critical design considerations for airframe composite structures. Therefore, the ability to model damage initiation and growth and predict the life of laminated composites is necessary to achieve structurally efficient and economical designs. The purpose of this research is to experimentally verify the application of a continuum damage model to predict progressive damage development in a toughened material system. Damage due to monotonic and tension-tension fatigue was documented for IM7/5260 graphite/bismaleimide laminates. Crack density and delamination surface area were used to calculate matrix cracking and delamination internal state variables to predict stiffness loss in unnotched laminates. A damage dependent finite element code predicted the stiffness loss for notched laminates with good agreement to experimental data. It was concluded that the continuum damage model can adequately predict matrix damage progression in notched and unnotched laminates as a function of loading history and laminate stacking sequence.

Composite Overwrapped Pressure Vessel (COPV) Stress Rupture Testing

NASA Technical Reports Server (NTRS)

Greene, Nathanael J.; Saulsberry, Regor L.; Leifeste, Mark R.; Yoder, Tommy B.; Keddy, Chris P.; Forth, Scott C.; Russell, Rick W.

2010-01-01

This paper reports stress rupture testing of Kevlar(TradeMark) composite overwrapped pressure vessels (COPVs) at NASA White Sands Test Facility. This 6-year test program was part of the larger effort to predict and extend the lifetime of flight vessels. Tests were performed to characterize control parameters for stress rupture testing, and vessel life was predicted by statistical modeling. One highly instrumented 102-cm (40-in.) diameter Kevlar(TradeMark) COPV was tested to failure (burst) as a single-point model verification. Significant data were generated that will enhance development of improved NDE methods and predictive modeling techniques, and thus better address stress rupture and other composite durability concerns that affect pressure vessel safety, reliability and mission assurance.

Application of the Refined Zigzag Theory to the Modeling of Delaminations in Laminated Composites

NASA Technical Reports Server (NTRS)

Groh, Rainer M. J.; Weaver, Paul M.; Tessler, Alexander

2015-01-01

The Refined Zigzag Theory is applied to the modeling of delaminations in laminated composites. The commonly used cohesive zone approach is adapted for use within a continuum mechanics model, and then used to predict the onset and propagation of delamination in five cross-ply composite beams. The resin-rich area between individual composite plies is modeled explicitly using thin, discrete layers with isotropic material properties. A damage model is applied to these resin-rich layers to enable tracking of delamination propagation. The displacement jump across the damaged interfacial resin layer is captured using the zigzag function of the Refined Zigzag Theory. The overall model predicts the initiation of delamination to within 8% compared to experimental results and the load drop after propagation is represented accurately.

Congruence in demersal fish, macroinvertebrate, and macroalgal community turnover on shallow temperate reefs.

PubMed

Thomson, Russell J; Hill, Nicole A; Leaper, Rebecca; Ellis, Nick; Pitcher, C Roland; Barrett, Neville S; Edgar, Graham J

2014-03-01

To support coastal planning through improved understanding of patterns of biotic and abiotic surrogacy at broad scales, we used gradient forest modeling (GFM) to analyze and predict spatial patterns of compositional turnover of demersal fishes, macroinvertebrates, and macroalgae on shallow, temperate Australian reefs. Predictive models were first developed using environmental surrogates with estimates of prediction uncertainty, and then the efficacy of the three assemblages as biosurrogates for each other was assessed. Data from underwater visual surveys of subtidal rocky reefs were collected from the southeastern coastline of continental Australia (including South Australia and Victoria) and the northern coastline of Tasmania. These data were combined with 0.01 degree-resolution gridded environmental variables to develop statistical models of compositional turnover (beta diversity) using GFM. GFM extends the machine learning, ensemble tree-based method of random forests (RF), to allow the simultaneous modeling of multiple taxa. The models were used to generate predictions of compositional turnover for each of the three assemblages within unsurveyed areas across the 6600 km of coastline in the region of interest. The most important predictor for all three assemblages was variability in sea surface temperature (measured as standard deviation from measures taken interannually). Spatial predictions of compositional turnover within unsurveyed areas across the region of interest were remarkably congruent across the three taxa. However, the greatest uncertainty in these predictions varied in location among the different assemblages. Pairwise congruency comparisons of observed and predicted turnover among the three assemblages showed that invertebrate and macroalgal biodiversity were most similar, followed by fishes and macroalgae, and lastly fishes and invertebrate biodiversity, suggesting that of the three assemblages, macroalgae would make the best biosurrogate for both invertebrate and fish compositional turnover.

Review on failure prediction techniques of composite single lap joint

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

Ab Ghani, A.F., E-mail: ahmadfuad@utem.edu.my; Rivai, Ahmad, E-mail: ahmadrivai@utem.edu.my

2016-03-29

Adhesive bonding is the most appropriate joining method in construction of composite structures. The use of reliable design and prediction technique will produce better performance of bonded joints. Several papers from recent papers and journals have been reviewed and synthesized to understand the current state of the art in this area. It is done by studying the most relevant analytical solutions for composite adherends with start of reviewing the most fundamental ones involving beam/plate theory. It is then extended to review single lap joint non linearity and failure prediction and finally on the failure prediction on composite single lap joint.more » The review also encompasses the finite element modelling part as tool to predict the elastic response of composite single lap joint and failure prediction numerically.« less

Modeling and Testing of the Viscoelastic Properties of a Graphite Nanoplatelet/Epoxy Composite

NASA Technical Reports Server (NTRS)

Odegard, Gregory M.; Gates, Thomas S.

2005-01-01

In order to facilitate the interpretation of experimental data, a micromechanical modeling procedure is developed to predict the viscoelastic properties of a graphite nanoplatelet/epoxy composite as a function of volume fraction and nanoplatelet diameter. The predicted storage and loss moduli for the composite are compared to measured values from the same material using three test methods; Dynamical Mechanical Analysis, nanoindentation, and quasi-static tensile tests. In most cases, the model and experiments indicate that for increasing volume fractions of nanoplatelets, both the storage and loss moduli increase. Also, the results indicate that for nanoplatelet sizes above 15 microns, nanoindentation is capable of measuring properties of individual constituents of a composite system. Comparison of the predicted values to the measured data helps illustrate the relative similarities and differences between the bulk and local measurement techniques.

Evaluation and prediction of long-term environmental effects of nonmetallic materials

NASA Technical Reports Server (NTRS)

Papazian, H.

1985-01-01

The properties of a number of nonmetallic materials were evaluated experimentally in simulated space environments in order to develop models for accelerated test methods useful for predicting such behavioral changes. Graphite-epoxy composites were exposed to thermal cycling. Adhesive foam tapes were subjected to a vacuum environment. Metal-matrix composites were tested for baseline data. Predictive modeling designed to include strength and aging effects on composites, polymeric films, and metals under such space conditions (including the atomic oxygen environment) is discussed. The Korel 8031-00 high strength adhesive foam tape was shown to be superior to the other two tested.

Creep of plain weave polymer matrix composites

NASA Astrophysics Data System (ADS)

Gupta, Abhishek

Polymer matrix composites are increasingly used in various industrial sectors to reduce structural weight and improve performance. Woven (also known as textile) composites are one class of polymer matrix composites with increasing market share mostly due to their lightweight, their flexibility to form into desired shape, their mechanical properties and toughness. Due to the viscoelasticity of the polymer matrix, time-dependent degradation in modulus (creep) and strength (creep rupture) are two of the major mechanical properties required by engineers to design a structure reliably when using these materials. Unfortunately, creep and creep rupture of woven composites have received little attention by the research community and thus, there is a dire need to generate additional knowledge and prediction models, given the increasing market share of woven composites in load bearing structural applications. Currently, available creep models are limited in scope and have not been validated for any loading orientation and time period beyond the experimental time window. In this thesis, an analytical creep model, namely the Modified Equivalent Laminate Model (MELM), was developed to predict tensile creep of plain weave composites for any orientation of the load with respect to the orientation of the fill and warp fibers, using creep of unidirectional composites. The ability of the model to predict creep for any orientation of the load is a "first" in this area. The model was validated using an extensive experimental involving the tensile creep of plain weave composites under varying loading orientation and service conditions. Plain weave epoxy (F263)/ carbon fiber (T300) composite, currently used in aerospace applications, was procured as fabrics from Hexcel Corporation. Creep tests were conducted under two loading conditions: on-axis loading (0°) and off-axis loading (45°). Constant load creep, in the temperature range of 80-240°C and stress range of 1-70% UTS of the composites, was experimentally evaluated for time periods ranging from 1--120 hours under both loading conditions. The composite showed increase in creep with increase in temperature and stress. Creep of composite increased with increase in angle of loading, from 1% under on-axis loading to 31% under off-axis loading, within the tested time window. The experimental creep data for plain weave composites were superposed using TTSP (Time Temperature Superposition Principle) to obtain a master curve of experimental data extending to several years and was compared with model predictions to validate the model. The experimental and model results were found in good agreement within an error range of +/-1-3% under both loading conditions. A parametric study was also conducted to understand the effect of microstructure of plain weave composites on its on-axis and off-axis creep. Generation of knowledge in this area is also "first". Additionally, this thesis generated knowledge on time-dependent damage m woven composites and its effect on creep and tensile properties and their prediction.

Single and double production of the Higgs boson at hadron and lepton colliders in minimal composite Higgs models

NASA Astrophysics Data System (ADS)

Kanemura, Shinya; Kaneta, Kunio; Machida, Naoki; Odori, Shinya; Shindou, Tetsuo

2016-07-01

In the composite Higgs models, originally proposed by Georgi and Kaplan, the Higgs boson is a pseudo Nambu-Goldstone boson (pNGB) of spontaneous breaking of a global symmetry. In the minimal version of such models, global SO(5) symmetry is spontaneously broken to SO(4), and the pNGBs form an isospin doublet field, which corresponds to the Higgs doublet in the Standard Model (SM). Predicted coupling constants of the Higgs boson can in general deviate from the SM predictions, depending on the compositeness parameter. The deviation pattern is determined also by the detail of the matter sector. We comprehensively study how the model can be tested via measuring single and double production processes of the Higgs boson at the LHC and future electron-positron colliders. The possibility to distinguish the matter sector among the minimal composite Higgs models is also discussed. In addition, we point out differences in the cross section of double Higgs boson production from the prediction in other new physics models.

High-Fidelity Microstructural Characterization and Performance Modeling of Aluminized Composite Propellant

DOE PAGES

Kosiba, Graham D.; Wixom, Ryan R.; Oehlschlaeger, Matthew A.

2017-10-27

Image processing and stereological techniques were used to characterize the heterogeneity of composite propellant and inform a predictive burn rate model. Composite propellant samples made up of ammonium perchlorate (AP), hydroxyl-terminated polybutadiene (HTPB), and aluminum (Al) were faced with an ion mill and imaged with a scanning electron microscope (SEM) and x-ray tomography (micro-CT). Properties of both the bulk and individual components of the composite propellant were determined from a variety of image processing tools. An algebraic model, based on the improved Beckstead-Derr-Price model developed by Cohen and Strand, was used to predict the steady-state burning of the aluminized compositemore » propellant. In the presented model the presence of aluminum particles within the propellant was introduced. The thermal effects of aluminum particles are accounted for at the solid-gas propellant surface interface and aluminum combustion is considered in the gas phase using a single global reaction. In conclusion, properties derived from image processing were used directly as model inputs, leading to a sample-specific predictive combustion model.« less

High-Fidelity Microstructural Characterization and Performance Modeling of Aluminized Composite Propellant

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

Kosiba, Graham D.; Wixom, Ryan R.; Oehlschlaeger, Matthew A.

Image processing and stereological techniques were used to characterize the heterogeneity of composite propellant and inform a predictive burn rate model. Composite propellant samples made up of ammonium perchlorate (AP), hydroxyl-terminated polybutadiene (HTPB), and aluminum (Al) were faced with an ion mill and imaged with a scanning electron microscope (SEM) and x-ray tomography (micro-CT). Properties of both the bulk and individual components of the composite propellant were determined from a variety of image processing tools. An algebraic model, based on the improved Beckstead-Derr-Price model developed by Cohen and Strand, was used to predict the steady-state burning of the aluminized compositemore » propellant. In the presented model the presence of aluminum particles within the propellant was introduced. The thermal effects of aluminum particles are accounted for at the solid-gas propellant surface interface and aluminum combustion is considered in the gas phase using a single global reaction. In conclusion, properties derived from image processing were used directly as model inputs, leading to a sample-specific predictive combustion model.« less

Prediction of frozen food properties during freezing using product composition.

PubMed

Boonsupthip, W; Heldman, D R

2007-06-01

Frozen water fraction (FWF), as a function of temperature, is an important parameter for use in the design of food freezing processes. An FWF-prediction model, based on concentrations and molecular weights of specific product components, has been developed. Published food composition data were used to determine the identity and composition of key components. The model proposed in this investigation had been verified using published experimental FWF data and initial freezing temperature data, and by comparison to outputs from previously published models. It was found that specific food components with significant influence on freezing temperature depression of food products included low molecular weight water-soluble compounds with molality of 50 micromol per 100 g food or higher. Based on an analysis of 200 high-moisture food products, nearly 45% of the experimental initial freezing temperature data were within an absolute difference (AD) of +/- 0.15 degrees C and standard error (SE) of +/- 0.65 degrees C when compared to values predicted by the proposed model. The predicted relationship between temperature and FWF for all analyzed food products provided close agreements with experimental data (+/- 0.06 SE). The proposed model provided similar prediction capability for high- and intermediate-moisture food products. In addition, the proposed model provided statistically better prediction of initial freezing temperature and FWF than previous published models.

Micro-mechanics modelling of smart materials

NASA Astrophysics Data System (ADS)

Shah, Syed Asim Ali

Metal Matrix ceramic-reinforced composites are rapidly becoming strong candidates as structural materials for many high temperature and engineering applications. Metal matrix composites (MMC) combine the ductile properties of the matrix with a brittle phase of the reinforcement, leading to high stiffness and strength with a reduction in structural weight. The main objective of using a metal matrix composite system is to increase service temperature or improve specific mechanical properties of structural components by replacing existing super alloys.The purpose of the study is to investigate, develop and implement second phase reinforcement alloy strengthening empirical model with SiCp reinforced A359 aluminium alloy composites on the particle-matrix interface and the overall mechanical properties of the material.To predict the interfacial fracture strength of aluminium, in the presence of silicon segregation, an empirical model has been modified. This model considers the interfacial energy caused by segregation of impurities at the interface and uses Griffith crack type arguments to predict the formation energies of impurities at the interface. Based on this, model simulations were conducted at nano scale specifically at the interface and the interfacial strengthening behaviour of reinforced aluminium alloy system was expressed in terms of elastic modulus.The numerical model shows success in making prediction possible of trends in relation to segregation and interfacial fracture strength behaviour in SiC particle-reinforced aluminium matrix composites. The simulation models using various micro scale modelling techniques to the aluminum alloy matrix composite, strengthenedwith varying amounts of silicon carbide particulate were done to predict the material state at critical points with properties of Al-SiC which had been heat treated.In this study an algorithm is developed to model a hard ceramic particle in a soft matrix with a clear distinct interface and a strain based relationship has been proposed for the strengthening behaviour of the MMC at the interface rather than stress based, by successfully completing the numerical modelling of particulate reinforced metal matrix composites.

Validation of Material Models For Automotive Carbon Fiber Composite Structures Via Physical And Crash Testing (VMM Composites Project)

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

Coppola, Anthony; Faruque, Omar; Truskin, James F

As automotive fuel economy requirements increase, the push for reducing overall vehicle weight will likely include the consideration of materials that have not previously been part of mainstream vehicle design and manufacturing, including carbon fiber composites. Vehicle manufacturers currently rely on computer-aided engineering (CAE) methods as part of the design and development process, so going forward, the ability to accurately and predictably model carbon fiber composites will be necessary. If composites are to be used for structural components, this need applies to both, crash and quasi-static modeling. This final report covers the results of a five-year, $6.89M, 50% cost-shared researchmore » project between Department of Energy (DOE) and the US Advanced Materials Partnership (USAMP) under Cooperative Agreement DE-EE-0005661 known as “Validation of Material Models for Automotive Carbon Fiber Composite Structures Via Physical and Crash Testing (VMM).” The objective of the VMM Composites Project was to validate and assess the ability of physics-based material models to predict crash performance of automotive primary load-carrying carbon fiber composite structures. Simulation material models that were evaluated included micro-mechanics based meso-scale models developed by the University of Michigan (UM) and micro-plane models by Northwestern University (NWU) under previous collaborations with the DOE and Automotive Composites Consortium/USAMP, as well as five commercial crash codes: LS-DYNA, RADIOSS, VPS/PAM-CRASH, Abaqus, and GENOA-MCQ. CAE predictions obtained from seven organizations were compared with experimental results from quasi-static testing and dynamic crash testing of a thermoset carbon fiber composite front-bumper and crush-can (FBCC) system gathered under multiple loading conditions. This FBCC design was developed to demonstrate progressive crush, virtual simulation, tooling, fabrication, assembly, non-destructive evaluation and crash testing advances in order to assess the correlation of the predicted results to the physical tests. The FBCC was developed to meet a goal of 30-35% mass reduction while aiming for equivalent energy absorption as a steel component for which baseline experimental results were obtained from testing in the same crash modes. The project also evaluated crash performance of thermoplastic composite structures fabricated from commercial prepreg materials and low cost carbon fiber sourced from Oak Ridge National Laboratory. The VMM Project determined that no set of predictions from a CAE supplier were found to be universally accurate among all the six crash modes evaluated. In general, crash modes that were most dependent on the properties of the prepreg were more accurate than those that were dependent on the behavior of the joints. The project found that current CAE modeling methods or best practices for carbon fiber composites have not achieved standardization, and accuracy of CAE is highly reliant on the experience of its users. Coupon tests alone are not sufficient to develop an accurate material model, but it is necessary to bridge the gap between the coupon data and performance of the actual structure with a series of subcomponent level tests. Much of the unreliability of the predictions can be attributed to shortcomings in our ability to mathematically link the effects of manufacturing and material variability into the material models. This is a subject of ongoing research in the industry. The final report is organized by key technical tasks to describe how the validation project developed, modeled and compared crash data obtained on the composite FBCC to the multiple sets of CAE predictions. Highlights of the report include a discussion of the quantitative comparison between predictions and experimental data, as well as an in-depth discussion of remaining technological gaps that exist in the industry, which are intended to spur innovations and improvements in CAE technology.« less

Evaluation of Lightning Induced Effects in a Graphite Composite Fairing Structure. Parts 1 and 2

NASA Technical Reports Server (NTRS)

Trout, Dawn H.; Stanley, James E.; Wahid, Parveen F.

2011-01-01

Defining the electromagnetic environment inside a graphite composite fairing due to lightning is of interest to spacecraft developers. This paper is the first in a two part series and studies the shielding effectiveness of a graphite composite model fairing using derived equivalent properties. A frequency domain Method of Moments (MoM) model is developed and comparisons are made with shielding test results obtained using a vehicle-like composite fairing. The comparison results show that the analytical models can adequately predict the test results. Both measured and model data indicate that graphite composite fairings provide significant attenuation to magnetic fields as frequency increases. Diffusion effects are also discussed. Part 2 examines the time domain based effects through the development of a loop based induced field testing and a Transmission-Line-Matrix (TLM) model is developed in the time domain to study how the composite fairing affects lightning induced magnetic fields. Comparisons are made with shielding test results obtained using a vehicle-like composite fairing in the time domain. The comparison results show that the analytical models can adequately predict the test and industry results.

The EST Model for Predicting Progressive Damage and Failure of Open Hole Bending Specimens

NASA Technical Reports Server (NTRS)

Joseph, Ashith P. K.; Waas, Anthony M.; Pineda, Evan J.

2016-01-01

Progressive damage and failure in open hole composite laminate coupons subjected to flexural loading is modeled using Enhanced Schapery Theory (EST). Previous studies have demonstrated that EST can accurately predict the strength of open hole coupons under remote tensile and compressive loading states. This homogenized modeling approach uses single composite shell elements to represent the entire laminate in the thickness direction and significantly reduces computational cost. Therefore, when delaminations are not of concern or are active in the post-peak regime, the version of EST presented here is a good engineering tool for predicting deformation response. Standard coupon level tests provides all the input data needed for the model and they are interpreted in conjunction with finite element (FE) based simulations. Open hole bending test results of three different IM7/8552 carbon fiber composite layups agree well with EST predictions. The model is able to accurately capture the curvature change and deformation localization in the specimen at and during the post catastrophic load drop event.

Evaluation of indoor air composition time variation in air-tight occupied spaces during night periods

NASA Astrophysics Data System (ADS)

Markov, Detelin

2012-11-01

This paper presents an easy-to-understand procedure for prediction of indoor air composition time variation in air-tight occupied spaces during the night periods. The mathematical model is based on the assumptions for homogeneity and perfect mixing of the indoor air, the ideal gas model for non-reacting gas mixtures, mass conservation equations for the entire system and for each species, a model for prediction of basal metabolic rate of humans as well as a model for prediction of O2 consumption rate and both CO2 and H2O generation rates by breathing. Time variation of indoor air composition is predicted at constant indoor air temperature for three scenarios based on the analytical solution of the mathematical model. The results achieved reveal both the most probable scenario for indoor air time variation in air-tight occupied spaces as well as the cause for morning tiredness after having a sleep in a modern energy efficient space.

Damage and strength of composite materials: Trends, predictions, and challenges

NASA Technical Reports Server (NTRS)

Obrien, T. Kevin

1994-01-01

Research on damage mechanisms and ultimate strength of composite materials relevant to scaling issues will be addressed in this viewgraph presentation. The use of fracture mechanics and Weibull statistics to predict scaling effects for the onset of isolated damage mechanisms will be highlighted. The ability of simple fracture mechanics models to predict trends that are useful in parametric or preliminary designs studies will be reviewed. The limitations of these simple models for complex loading conditions will also be noted. The difficulty in developing generic criteria for the growth of these mechanisms needed in progressive damage models to predict strength will be addressed. A specific example for a problem where failure is a direct consequence of progressive delamination will be explored. A damage threshold/fail-safety concept for addressing composite damage tolerance will be discussed.

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

Matyas, Josef; Cooley, Scott K.; Sundaram, S. K.

Slags of low viscosity readily penetrate the refractory lining in slagging gasifiers, causing rapid and severe corrosion called spalling. In addition, a low-viscosity slag that flows down the gasifier wall forms a relatively thin layer of slag on the refractory surface, allowing the corrosive gases in the gasifier to participate in the chemical reactions between the refractory and the slag. In contrast, a slag viscosity of <25 Pa•s at 1400°C is necessary to minimize the possibility of plugging the slag tap. There is a need to predict and optimize slag viscosity so slagging gasifiers can operate continuously at temperatures rangingmore » from 1300 to 1650°C. The approach adopted in this work was to statistically design and prepare simulated slags, measure the viscosity as a function of temperature, and develop a model to predict slag viscosity based on slag composition and temperature. Statistical design software was used to select compositions from a candidate set of all possible vertices that will optimally represent the composition space for 10 main components. A total of 21 slag compositions were generated, including 5 actual coal slag compositions. The Arrhenius equation was applied to measured viscosity versus temperature data of tested slags, and the Arrhenius coefficients (A and B in ln(vis) = A + B/T) were expressed as linear functions of the slag composition. The viscosity model was validated using 1) data splitting approach, and 2) viscosity/temperature data of selected slag compositions from the literature that were formulated and melted at Pacific Northwest National Laboratory. The capability of the model to predict the viscosity of coal slags was compared with the model developed by Browning et al. because this model can predict the viscosity of slags from coal ash better than the most commonly used empirical models found in the literature.« less

Micromechanics of metal matrix composites using the Generalized Method of Cells model (GMC) user's guide

NASA Technical Reports Server (NTRS)

Aboudi, Jacob; Pindera, Marek-Jerzy

1992-01-01

A user's guide for the program gmc.f is presented. The program is based on the generalized method of cells model (GMC) which is capable via a micromechanical analysis, of predicting the overall, inelastic behavior of unidirectional, multi-phase composites from the knowledge of the properties of the viscoplastic constituents. In particular, the program is sufficiently general to predict the response of unidirectional composites having variable fiber shapes and arrays.

Simple model for piezoelectric ceramic/polymer 1-3 composites used in ultrasonic transducer applications.

PubMed

Chan, H W; Unsworth, J

1989-01-01

A theoretical model is presented for combining parameters of 1-3 ultrasonic composite materials in order to predict ultrasonic characteristics such as velocity, acoustic impedance, electromechanical coupling factor, and piezoelectric coefficients. Hence, the model allows the estimation of resonance frequencies of 1-3 composite transducers. This model has been extended to cover more material parameters, and they are compared to experimental results up to PZT volume fraction nu of 0.8. The model covers calculation of piezoelectric charge constants d(33) and d(31). Values are found to be in good agreement with experimental results obtained for PZT 7A/Araldite D 1-3 composites. The acoustic velocity, acoustic impedance, and electromechanical coupling factor are predicted and found to be close to the values determined experimentally.

Micromechanical Modeling of Woven Metal Matrix Composites

NASA Technical Reports Server (NTRS)

Bednarcyk, Brett A.; Pindera, Marek-Jerzy

1997-01-01

This report presents the results of an extensive micromechanical modeling effort for woven metal matrix composites. The model is employed to predict the mechanical response of 8-harness (8H) satin weave carbon/copper (C/Cu) composites. Experimental mechanical results for this novel high thermal conductivity material were recently reported by Bednarcyk et al. along with preliminary model results. The micromechanics model developed herein is based on an embedded approach. A micromechanics model for the local (micro-scale) behavior of the woven composite, the original method of cells (Aboudi), is embedded in a global (macro-scale) micromechanics model (the three-dimensional generalized method of cells (GMC-3D) (Aboudi). This approach allows representation of true repeating unit cells for woven metal matrix composites via GMC-3D, and representation of local effects, such as matrix plasticity, yarn porosity, and imperfect fiber-matrix bonding. In addition, the equations of GMC-3D were reformulated to significantly reduce the number of unknown quantities that characterize the deformation fields at the microlevel in order to make possible the analysis of actual microstructures of woven composites. The resulting micromechanical model (WCGMC) provides an intermediate level of geometric representation, versatility, and computational efficiency with respect to previous analytical and numerical models for woven composites, but surpasses all previous modeling work by allowing the mechanical response of a woven metal matrix composite, with an elastoplastic matrix, to be examined for the first time. WCGMC is employed to examine the effects of composite microstructure, porosity, residual stresses, and imperfect fiber-matrix bonding on the predicted mechanical response of 8H satin C/Cu. The previously reported experimental results are summarized, and the model predictions are compared to monotonic and cyclic tensile and shear test data. By considering appropriate levels of porosity, residual stresses, and imperfect fiber-matrix debonding, reasonably good qualitative and quantitative correlation is achieved between model and experiment.

Flexural creep behaviour of jute polypropylene composites

NASA Astrophysics Data System (ADS)

Chandekar, Harichandra; Chaudhari, Vikas

2016-09-01

Present study is about the flexural creep behaviour of jute fabric reinforced polypropylene (Jute-PP) composites. The PP sheet and alkali treated jute fabric is stacked alternately and hot pressed in compression molding machine to get Jute-PP composite laminate. The flexural creep study is carried out on dynamic mechanical analyzer. The creep behaviour of the composite is modeled using four-parameter Burgers model. Short-term accelerated creep testing is conducted which is later used to predict long term creep behaviour. The feasibility of the construction of a master curve using the time-temperature superposition (TTS) principle to predict long term creep behavior of unreinforced PP and Jute-PP composite is investigated.

A stochastic model for optimizing composite predictors based on gene expression profiles.

PubMed

Ramanathan, Murali

2003-07-01

This project was done to develop a mathematical model for optimizing composite predictors based on gene expression profiles from DNA arrays and proteomics. The problem was amenable to a formulation and solution analogous to the portfolio optimization problem in mathematical finance: it requires the optimization of a quadratic function subject to linear constraints. The performance of the approach was compared to that of neighborhood analysis using a data set containing cDNA array-derived gene expression profiles from 14 multiple sclerosis patients receiving intramuscular inteferon-beta1a. The Markowitz portfolio model predicts that the covariance between genes can be exploited to construct an efficient composite. The model predicts that a composite is not needed for maximizing the mean value of a treatment effect: only a single gene is needed, but the usefulness of the effect measure may be compromised by high variability. The model optimized the composite to yield the highest mean for a given level of variability or the least variability for a given mean level. The choices that meet this optimization criteria lie on a curve of composite mean vs. composite variability plot referred to as the "efficient frontier." When a composite is constructed using the model, it outperforms the composite constructed using the neighborhood analysis method. The Markowitz portfolio model may find potential applications in constructing composite biomarkers and in the pharmacogenomic modeling of treatment effects derived from gene expression endpoints.

Melts of garnet lherzolite: experiments, models and comparison to melts of pyroxenite and carbonated lherzolite

USGS Publications Warehouse

Grove, Timothy L.; Holbig, Eva S.; Barr, Jay A.; Till, Christy B.; Krawczynski, Michael J.

2013-01-01

Phase equilibrium experiments on a compositionally modified olivine leucitite from the Tibetan plateau have been carried out from 2.2 to 2.8 GPa and 1,380–1,480 °C. The experiments-produced liquids multiply saturated with spinel and garnet lherzolite phase assemblages (olivine, orthopyroxene, clinopyroxene and spinel ± garnet) under nominally anhydrous conditions. These SiO2-undersaturated liquids and published experimental data are utilized to develop a predictive model for garnet lherzolite melting of compositionally variable mantle under anhydrous conditions over the pressure range of 1.9–6 GPa. The model estimates the major element compositions of garnet-saturated melts for a range of mantle lherzolite compositions and predicts the conditions of the spinel to garnet lherzolite phase transition for natural peridotite compositions at above-solidus temperatures and pressures. We compare our predicted garnet lherzolite melts to those of pyroxenite and carbonated lherzolite and develop criteria for distinguishing among melts of these different source types. We also use the model in conjunction with a published predictive model for plagioclase and spinel lherzolite to characterize the differences in major element composition for melts in the plagioclase, spinel and garnet facies and develop tests to distinguish between melts of these three lherzolite facies based on major elements. The model is applied to understand the source materials and conditions of melting for high-K lavas erupted in the Tibetan plateau, basanite–nephelinite lavas erupted early in the evolution of Kilauea volcano, Hawaii, as well as younger tholeiitic to alkali lavas from Kilauea.

Analytical design model for a piezo-composite unimorph actuator and its verification using lightweight piezo-composite curved actuators

NASA Astrophysics Data System (ADS)

Yoon, K. J.; Park, K. H.; Lee, S. K.; Goo, N. S.; Park, H. C.

2004-06-01

This paper describes an analytical design model for a layered piezo-composite unimorph actuator and its numerical and experimental verification using a LIPCA (lightweight piezo-composite curved actuator) that is lighter than other conventional piezo-composite type actuators. The LIPCA is composed of top fiber composite layers with high modulus and low CTE (coefficient of thermal expansion), a middle PZT ceramic wafer, and base layers with low modulus and high CTE. The advantages of the LIPCA design are to replace the heavy metal layer of THUNDER by lightweight fiber-reinforced plastic layers without compromising the generation of high force and large displacement and to have design flexibility by selecting the fiber direction and the number of prepreg layers. In addition to the lightweight advantage and design flexibility, the proposed device can be manufactured without adhesive layers when we use a resin prepreg system. A piezo-actuation model for a laminate with piezo-electric material layers and fiber composite layers is proposed to predict the curvature and residual stress of the LIPCA. To predict the actuation displacement of the LIPCA with curvature, a finite element analysis method using the proposed piezo-actuation model is introduced. The predicted deformations are in good agreement with the experimental ones.

Local Debonding and Fiber Breakage in Composite Materials Modeled Accurately

NASA Technical Reports Server (NTRS)

Bednarcyk, Brett A.; Arnold, Steven M.

2001-01-01

A prerequisite for full utilization of composite materials in aerospace components is accurate design and life prediction tools that enable the assessment of component performance and reliability. Such tools assist both structural analysts, who design and optimize structures composed of composite materials, and materials scientists who design and optimize the composite materials themselves. NASA Glenn Research Center's Micromechanics Analysis Code with Generalized Method of Cells (MAC/GMC) software package (http://www.grc.nasa.gov/WWW/LPB/mac) addresses this need for composite design and life prediction tools by providing a widely applicable and accurate approach to modeling composite materials. Furthermore, MAC/GMC serves as a platform for incorporating new local models and capabilities that are under development at NASA, thus enabling these new capabilities to progress rapidly to a stage in which they can be employed by the code's end users.

A Unit-Cell Model for Predicting the Elastic Constants of 3D Four Directional Cylindrical Braided Composite Shafts

NASA Astrophysics Data System (ADS)

Hao, Wenfeng; Liu, Ye; Huang, Xinrong; Liu, Yinghua; Zhu, Jianguo

2018-06-01

In this work, the elastic constants of 3D four directional cylindrical braided composite shafts were predicted using analytical and numerical methods. First, the motion rule of yarn carrier of 3D four directional cylindrical braided composite shafts was analyzed, and the horizontal projection of yarn motion trajectory was obtained. Then, the geometry models of unit-cells with different braiding angles and fiber volume contents were built up, and the meso-scale models of 3D cylindrical braided composite shafts were obtained. Finally, the effects of braiding angles and fiber volume contents on the elastic constants of 3D braided composite shafts were analyzed theoretically and numerically. These results play a crucial role in investigating the mechanical properties of 3D 4-directional braided composites shafts.

Experimental and Numerical Analysis of Triaxially Braided Composites Utilizing a Modified Subcell Modeling Approach

NASA Technical Reports Server (NTRS)

Cater, Christopher; Xiao, Xinran; Goldberg, Robert K.; Kohlman, Lee W.

2015-01-01

A combined experimental and analytical approach was performed for characterizing and modeling triaxially braided composites with a modified subcell modeling strategy. Tensile coupon tests were conducted on a [0deg/60deg/-60deg] braided composite at angles of 0deg, 30deg, 45deg, 60deg and 90deg relative to the axial tow of the braid. It was found that measured coupon strength varied significantly with the angle of the applied load and each coupon direction exhibited unique final failures. The subcell modeling approach implemented into the finite element software LS-DYNA was used to simulate the various tensile coupon test angles. The modeling approach was successful in predicting both the coupon strength and reported failure mode for the 0deg, 30deg and 60deg loading directions. The model over-predicted the strength in the 90deg direction; however, the experimental results show a strong influence of free edge effects on damage initiation and failure. In the absence of these local free edge effects, the subcell modeling approach showed promise as a viable and computationally efficient analysis tool for triaxially braided composite structures. Future work will focus on validation of the approach for predicting the impact response of the braided composite against flat panel impact tests.

Experimental and Numerical Analysis of Triaxially Braided Composites Utilizing a Modified Subcell Modeling Approach

NASA Technical Reports Server (NTRS)

Cater, Christopher; Xiao, Xinran; Goldberg, Robert K.; Kohlman, Lee W.

2015-01-01

A combined experimental and analytical approach was performed for characterizing and modeling triaxially braided composites with a modified subcell modeling strategy. Tensile coupon tests were conducted on a [0deg/60deg/-60deg] braided composite at angles [0deg, 30deg, 45deg, 60deg and 90deg] relative to the axial tow of the braid. It was found that measured coupon strength varied significantly with the angle of the applied load and each coupon direction exhibited unique final failures. The subcell modeling approach implemented into the finite element software LS-DYNA was used to simulate the various tensile coupon test angles. The modeling approach was successful in predicting both the coupon strength and reported failure mode for the 0deg, 30deg and 60deg loading directions. The model over-predicted the strength in the 90deg direction; however, the experimental results show a strong influence of free edge effects on damage initiation and failure. In the absence of these local free edge effects, the subcell modeling approach showed promise as a viable and computationally efficient analysis tool for triaxially braided composite structures. Future work will focus on validation of the approach for predicting the impact response of the braided composite against flat panel impact tests.

Model Determined for Predicting Fatigue Lives of Metal Matrix Composites Under Mean Stresses

NASA Technical Reports Server (NTRS)

Lerch, Bradley

1997-01-01

Aircraft engine components invariably are subjected to mean stresses over and above the cyclic loads. In monolithic materials, it has been observed that tensile mean stresses are detrimental and compressive mean stresses are beneficial to fatigue life in comparison to a base of zero mean stress. Several mean stress models exist for monolithic metals, but each differ quantitatively in the extent to which detrimental or beneficial effects are ascribed. There have been limited attempts to apply these models to metal matrix composites. At the NASA Lewis Research Center, several mean stress models--the Smith-Watson- Topper, Walker, Normalized Goodman, and Soderberg models--were examined for applicability to this class of composite materials. The Soderberg approach, which normalizes the mean stress to a 0.02-percent yield strength, was shown to best represent the effect of mean stresses over the range covered. The other models varied significantly in their predictability and often failed to predict the composite behavior at very high tensile mean stresses. This work is the first to systematically demonstrate the influence of mean stresses on metal matrix composites and model their effects. Attention also was given to fatigue-cracking mechanisms in the Ti-15-3 matrix and to micromechanics analyses of mean stress effects.

Prediction of microalgae hydrothermal liquefaction products from feedstock biochemical composition

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

Leow, Shijie; Witter, John R.; Vardon, Derek R.

Hydrothermal liquefaction (HTL) uses water under elevated temperatures and pressures (200–350 °C, 5–20 MPa) to convert biomass into liquid “biocrude” oil. Despite extensive reports on factors influencing microalgae cell composition during cultivation and separate reports on HTL products linked to cell composition, the field still lacks a quantitative model to predict HTL conversion product yield and qualities from feedstock biochemical composition; the tailoring of microalgae feedstock for downstream conversion is a unique and critical aspect of microalgae biofuels that must be leveraged upon for optimization of the whole process. This study developed predictive relationships for HTL biocrude yield and othermore » conversion product characteristics based on HTL of Nannochloropsis oculata batches harvested with a wide range of compositions (23–59% dw lipids, 58–17% dw proteins, 12–22% dw carbohydrates) and a defatted batch (0% dw lipids, 75% dw proteins, 19% dw carbohydrates). HTL biocrude yield (33–68% dw) and carbon distribution (49–83%) increased in proportion to the fatty acid (FA) content. A component additivity model (predicting biocrude yield from lipid, protein, and carbohydrates) was more accurate predicting literature yields for diverse microalgae species than previous additivity models derived from model compounds. FA profiling of the biocrude product showed strong links to the initial feedstock FA profile of the lipid component, demonstrating that HTL acts as a water-based extraction process for FAs; the remainder non-FA structural components could be represented using the defatted batch. These findings were used to introduce a new FA-based model that predicts biocrude oil yields along with other critical parameters, and is capable of adjusting for the wide variations in HTL methodology and microalgae species through the defatted batch. Lastly, the FA model was linked to an upstream cultivation model (Phototrophic Process Model), providing for the first time an integrated modeling framework to overcome a critical barrier to microalgae-derived HTL biofuels and enable predictive analysis of the overall microalgal-to-biofuel process.« less

Prediction of microalgae hydrothermal liquefaction products from feedstock biochemical composition

DOE PAGES

Leow, Shijie; Witter, John R.; Vardon, Derek R.; ...

2015-05-11

Hydrothermal liquefaction (HTL) uses water under elevated temperatures and pressures (200–350 °C, 5–20 MPa) to convert biomass into liquid “biocrude” oil. Despite extensive reports on factors influencing microalgae cell composition during cultivation and separate reports on HTL products linked to cell composition, the field still lacks a quantitative model to predict HTL conversion product yield and qualities from feedstock biochemical composition; the tailoring of microalgae feedstock for downstream conversion is a unique and critical aspect of microalgae biofuels that must be leveraged upon for optimization of the whole process. This study developed predictive relationships for HTL biocrude yield and othermore » conversion product characteristics based on HTL of Nannochloropsis oculata batches harvested with a wide range of compositions (23–59% dw lipids, 58–17% dw proteins, 12–22% dw carbohydrates) and a defatted batch (0% dw lipids, 75% dw proteins, 19% dw carbohydrates). HTL biocrude yield (33–68% dw) and carbon distribution (49–83%) increased in proportion to the fatty acid (FA) content. A component additivity model (predicting biocrude yield from lipid, protein, and carbohydrates) was more accurate predicting literature yields for diverse microalgae species than previous additivity models derived from model compounds. FA profiling of the biocrude product showed strong links to the initial feedstock FA profile of the lipid component, demonstrating that HTL acts as a water-based extraction process for FAs; the remainder non-FA structural components could be represented using the defatted batch. These findings were used to introduce a new FA-based model that predicts biocrude oil yields along with other critical parameters, and is capable of adjusting for the wide variations in HTL methodology and microalgae species through the defatted batch. Lastly, the FA model was linked to an upstream cultivation model (Phototrophic Process Model), providing for the first time an integrated modeling framework to overcome a critical barrier to microalgae-derived HTL biofuels and enable predictive analysis of the overall microalgal-to-biofuel process.« less

Glass Transition Temperature- and Specific Volume- Composition Models for Tellurite Glasses

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

Riley, Brian J.; Vienna, John D.

This report provides models for predicting composition-properties for tellurite glasses, namely specific gravity and glass transition temperature. Included are the partial specific coefficients for each model, the component validity ranges, and model fit parameters.

Improvement of Progressive Damage Model to Predicting Crashworthy Composite Corrugated Plate

NASA Astrophysics Data System (ADS)

Ren, Yiru; Jiang, Hongyong; Ji, Wenyuan; Zhang, Hanyu; Xiang, Jinwu; Yuan, Fuh-Gwo

2018-02-01

To predict the crashworthy composite corrugated plate, different single and stacked shell models are evaluated and compared, and a stacked shell progressive damage model combined with continuum damage mechanics is proposed and investigated. To simulate and predict the failure behavior, both of the intra- and inter- laminar failure behavior are considered. The tiebreak contact method, 1D spot weld element and cohesive element are adopted in stacked shell model, and a surface-based cohesive behavior is used to capture delamination in the proposed model. The impact load and failure behavior of purposed and conventional progressive damage models are demonstrated. Results show that the single shell could simulate the impact load curve without the delamination simulation ability. The general stacked shell model could simulate the interlaminar failure behavior. The improved stacked shell model with continuum damage mechanics and cohesive element not only agree well with the impact load, but also capture the fiber, matrix debonding, and interlaminar failure of composite structure.

Prediction of protein-protein interactions based on PseAA composition and hybrid feature selection.

PubMed

Liu, Liang; Cai, Yudong; Lu, Wencong; Feng, Kaiyan; Peng, Chunrong; Niu, Bing

2009-03-06

Based on pseudo amino acid (PseAA) composition and a novel hybrid feature selection frame, this paper presents a computational system to predict the PPIs (protein-protein interactions) using 8796 protein pairs. These pairs are coded by PseAA composition, resulting in 114 features. A hybrid feature selection system, mRMR-KNNs-wrapper, is applied to obtain an optimized feature set by excluding poor-performed and/or redundant features, resulting in 103 remaining features. Using the optimized 103-feature subset, a prediction model is trained and tested in the k-nearest neighbors (KNNs) learning system. This prediction model achieves an overall accurate prediction rate of 76.18%, evaluated by 10-fold cross-validation test, which is 1.46% higher than using the initial 114 features and is 6.51% higher than the 20 features, coded by amino acid compositions. The PPIs predictor, developed for this research, is available for public use at http://chemdata.shu.edu.cn/ppi.

An improved null model for assessing the net effects of multiple stressors on communities.

PubMed

Thompson, Patrick L; MacLennan, Megan M; Vinebrooke, Rolf D

2018-01-01

Ecological stressors (i.e., environmental factors outside their normal range of variation) can mediate each other through their interactions, leading to unexpected combined effects on communities. Determining whether the net effect of stressors is ecologically surprising requires comparing their cumulative impact to a null model that represents the linear combination of their individual effects (i.e., an additive expectation). However, we show that standard additive and multiplicative null models that base their predictions on the effects of single stressors on community properties (e.g., species richness or biomass) do not provide this linear expectation, leading to incorrect interpretations of antagonistic and synergistic responses by communities. We present an alternative, the compositional null model, which instead bases its predictions on the effects of stressors on individual species, and then aggregates them to the community level. Simulations demonstrate the improved ability of the compositional null model to accurately provide a linear expectation of the net effect of stressors. We simulate the response of communities to paired stressors that affect species in a purely additive fashion and compare the relative abilities of the compositional null model and two standard community property null models (additive and multiplicative) to predict these linear changes in species richness and community biomass across different combinations (both positive, negative, or opposite) and intensities of stressors. The compositional model predicts the linear effects of multiple stressors under almost all scenarios, allowing for proper classification of net effects, whereas the standard null models do not. Our findings suggest that current estimates of the prevalence of ecological surprises on communities based on community property null models are unreliable, and should be improved by integrating the responses of individual species to the community level as does our compositional null model. © 2017 John Wiley & Sons Ltd.

Prediction of progressive damage and strength of plain weave composites using the finite element method

NASA Astrophysics Data System (ADS)

Srirengan, Kanthikannan

The overall objective of this research was to develop the finite element code required to efficiently predict the strength of plain weave composite structures. Towards which, three-dimensional conventional progressive damage analysis was implemented to predict the strength of plain weave composites subjected to periodic boundary conditions. Also, modal technique for three-dimensional global/local stress analysis was developed to predict the failure initiation in plain weave composite structures. The progressive damage analysis was used to study the effect of quadrature order, mesh refinement and degradation models on the predicted damage and strength of plain weave composites subjected to uniaxial tension in the warp tow direction. A 1/32sp{nd} part of the representative volume element of a symmetrically stacked configuration was analyzed. The tow geometry was assumed to be sinusoidal. Graphite/Epoxy system was used. Maximum stress criteria and combined stress criteria were used to predict failure in the tows and maximum principal stress criterion was used to predict failure in the matrix. Degradation models based on logical reasoning, micromechanics idealization and experimental comparisons were used to calculate the effective material properties with of damage. Modified Newton-Raphson method was used to determine the incremental solution for each applied strain level. Using a refined mesh and the discount method based on experimental comparisons, the progressive damage and the strength of plain weave composites of waviness ratios 1/3 and 1/6 subjected to uniaxial tension in the warp direction have been characterized. Plain weave composites exhibit a brittle response in uniaxial tension. The strength decreases significantly with the increase in waviness ratio. Damage initiation and collapse were caused dominantly due to intra-tow cracking and inter-tow debonding respectively. The predicted strength of plain weave composites of racetrack geometry and waviness ratio 1/25.7 was compared with analytical predictions and experimental findings and was found to match well. To evaluate the performance of the modal technique, failure initiation in a short woven composite cantilevered plate subjected to end moment and transverse end load was predicted. The global/local predictions were found to reasonably match well with the conventional finite element predictions.

Surface complexation modeling of Cd(II) sorption to montmorillonite, bacteria, and their composite

NASA Astrophysics Data System (ADS)

Wang, Ning; Du, Huihui; Huang, Qiaoyun; Cai, Peng; Rong, Xingmin; Feng, Xionghan; Chen, Wenli

2016-10-01

Surface complexation modeling (SCM) has emerged as a powerful tool for simulating heavy metal adsorption processes on the surface of soil solid components under different geochemical conditions. The component additivity (CA) approach is one of the strategies that have been widely used in multicomponent systems. In this study, potentiometric titration, isothermal adsorption, zeta potential measurement, and extended X-ray absorption fine-structure (EXAFS) spectra analysis were conducted to investigate Cd adsorption on 2 : 1 clay mineral montmorillonite, on Gram-positive bacteria Bacillus subtilis, and their mineral-organic composite. We developed constant capacitance models of Cd adsorption on montmorillonite, bacterial cells, and mineral-organic composite. The adsorption behavior of Cd on the surface of the composite was well explained by CA-SCM. Some deviations were observed from the model simulations at pH < 5, where the values predicted by the model were lower than the experimental results. The Cd complexes of X2Cd, SOCd+, R-COOCd+, and R-POCd+ were the predominant species on the composite surface over the pH range of 3 to 8. The distribution ratio of the adsorbed Cd between montmorillonite and bacterial fractions in the composite as predicted by CA-SCM closely coincided with the estimated value of EXAFS at pH 6. The model could be useful for the prediction of heavy metal distribution at the interface of multicomponents and their risk evaluation in soils and associated environments.

Infiltration/cure modeling of resin transfer molded composite materials using advanced fiber architectures

NASA Technical Reports Server (NTRS)

Loos, Alfred C.; Weideman, Mark H.; Long, Edward R., Jr.; Kranbuehl, David E.; Kinsley, Philip J.; Hart, Sean M.

1991-01-01

A model was developed which can be used to simulate infiltration and cure of textile composites by resin transfer molding. Fabric preforms were resin infiltrated and cured using model generated optimized one-step infiltration/cure protocols. Frequency dependent electromagnetic sensing (FDEMS) was used to monitor in situ resin infiltration and cure during processing. FDEMS measurements of infiltration time, resin viscosity, and resin degree of cure agreed well with values predicted by the simulation model. Textile composites fabricated using a one-step infiltration/cure procedure were uniformly resin impregnated and void free. Fiber volume fraction measurements by the resin digestion method compared well with values predicted using the model.

Local stresses in metal matrix composites subjected to thermal and mechanical loading

NASA Technical Reports Server (NTRS)

Highsmith, Alton L.; Shin, Donghee; Naik, Rajiv A.

1990-01-01

An elasticity solution has been used to analyze matrix stresses near the fiber/matrix interface in continuous fiber-reinforced metal-matrix composites, modeling the micromechanics in question in terms of a cylindrical fiber and cylindrical matrix sheath which is embedded in an orthotropic medium representing the composite. The model's predictions for lamina thermal and mechanical properties are applied to a laminate analysis determining ply-level stresses due to thermomechanical loading. A comparison is made between these results, which assume cylindrical symmetry, and the predictions yielded by a FEM model in which the fibers are arranged in a square array.

Modelling scenarios on feed-to-fillet transfer of dioxins and dioxin-like PCBs in future feeds to farmed Atlantic salmon (Salmo salar).

PubMed

Berntssen, Marc H G; Sanden, Monica; Hove, Helge; Lie, Øyvind

2016-11-01

The salmon feed composition has changed the last decade with a replacement of traditionally use of fish oil and fishmeal diets with vegetable ingredients and the use decontaminated fish oils, causing reduced concentrations of dioxins and dioxin-like PCBs in farmed Norwegian Atlantic salmon. The development of novel salmon feeds has prompted the need for prediction on dioxins and dl-PCB concentrations in future farmed salmon. Prediction on fillet dioxins and dl-PCB concentrations from different feed composition scenarios are made using a simple one-compartmental transfer model based on earlier established dioxin and dl-PCB congener specific uptake and elimination kinetics rates. The model is validated with two independent feeding trials, with a significant linear correlation (r(2) = 0.96, y = 1.0x, p < 0.0001, n = 116) between observed and predicted values. Model fillet predictions are made for the following four scenarios; (1) general feed composition of 1999, (2) feed composition of 2013, (3) future feed composition with high fish oil and meal replacement, (4) future feed composition with high fish oil and meal replacement and decontaminated fish oil. Model predictions of fillet dioxin and dl-PCB concentrations from 1999 (1.05 ng WHO2005-TEQs kg(-1)ww) and 2013 (0.57 ng WHO2005-TEQs kg(-1)ww) are in line with the data observed in national surveillance programs of those years (1.1 and 0.52 ng WHO2005-TEQs kg(-1)ww, respectively). Future use of high replacement and decontaminated oils feeds gave predicted fillet concentrations of 0.27 ng WHO2005-TEQs kg(-1)ww, which is near the limit of quantification. Copyright © 2016 Elsevier Ltd. All rights reserved.

Micromechanical Prediction of the Effective Coefficients of Thermo-Piezoelectric Multiphase Composites

NASA Technical Reports Server (NTRS)

Aboudi, Jacob

1998-01-01

The micromechanical generalized method of cells model is employed for the prediction of the effective elastic, piezoelectric, dielectric, pyroelectric and thermal-expansion constants of multiphase composites with embedded piezoelectric materials. The predicted effective constants are compared with other micromechanical methods available in the literature and good agreements are obtained.

Literature Review on the Design of Composite Mechanically Fastened Joints (Revue de la Documentation sur la Conception des Joints a Liaison Mecanique en Composites),

DTIC Science & Technology

1986-02-01

mechanics Eisenmann (32) established a bolted joint static strength prediction model based on fracture mechanics for composite materials. The failure...34 Composite Materials, Volume 2, Academic Press, 1974, pp. 353-431. 32. Eisenmann , J.R., "Bolted Joint Static Strength Model for Composite Materials," NASA

Time dependent micromechanics in continuous graphite fiber/epoxy composites with fiber breaks

NASA Astrophysics Data System (ADS)

Zhou, Chao Hui

Time dependent micromechanics in graphite fiber/epoxy composites around fiber breaks was investigated with micro Raman spectroscopy (MRS) and two shear-lag based composite models, a multi-fiber model (VBI) and a single fiber model (SFM), which aim at predicting the strain/stress evolutions in the composite from the matrix creep behavior and fiber strength statistics. This work is motivated by the need to understand the micromechanics and predict the creep-rupture of the composites. Creep of the unfilled epoxy was characterized under different stress levels and at temperatures up to 80°C, with two power law functions, which provided the modeling parameters used as input for the composite models. Both the VBI and the SFM models showed good agreement with the experimental data obtained with MRS, when inelasticity (interfacial debonding and/or matrix yielding) was not significant. The maximum shear stress near a fiber break relaxed at t-alpha/2 (or as (1+ talpha)-1/2) and the load recovery length increased at talpha/2(or (1+ talpha)1/2) following the model predictions. When the inelastic zone became non-negligible, the viscoelastic VBI model lost its competence, while the SFM with inelasticity showed good agreement with the MRS measurements. Instead of using the real fiber spacing, an effective fiber spacing was used in model predictions, taking into account of the radial decay of the interfacial shear stress from the fiber surface. The comparisons between MRS data and the SFM showed that inelastic zone would initiate when the shear strain at the fiber end exceeds a critical value gammac which was determined to be 5% for this composite system at room temperature and possibly a smaller value at elevated temperatures. The stress concentrations in neighboring intact fibers played important roles in the subsequent fiber failure and damage growth. The VBI model predicts a constant stress concentration factor, 1.33, for the 1st nearest intact fiber, which is in good agreement with MRS measurements for most cases except for those with severely debonded interfaces. However, the VBI model usually gives a stress concentration profile narrower than the measured one due to the inelasticity near the fiber break. The low average fiber volume fraction in the model composites caused small relaxation in the stress concentration, which became more obvious at elevated temperatures, especially for large fiber spacing cases. When new break(s) occurred in the original intact neighboring fibers within an effective distance from the original break, the inelastic zones grew at a faster rate due to the strong interactions. Results on the creep-rupture of the bulk composites showed that the failure probability depends on the stress level and the loading time. The time dependent failure probability data could be fitted to a power law function, which suggested a link between the matrix creep, composite short-term strength and the composite creep-rupture.

Structural behavior of composites with progressive fracture

NASA Technical Reports Server (NTRS)

Minnetyan, L.; Murthy, P. L. N.; Chamis, C. C.

1989-01-01

The objective of the study is to unify several computational tools developed for the prediction of progressive damage and fracture with efforts for the prediction of the overall response of damaged composite structures. In particular, a computational finite element model for the damaged structure is developed using a computer program as a byproduct of the analysis of progressive damage and fracture. Thus, a single computational investigation can predict progressive fracture and the resulting variation in structural properties of angleplied composites.

Modeling approaches for the simulation of ultrasonic inspections of anisotropic composite structures in the CIVA software platform

NASA Astrophysics Data System (ADS)

Jezzine, Karim; Imperiale, Alexandre; Demaldent, Edouard; Le Bourdais, Florian; Calmon, Pierre; Dominguez, Nicolas

2018-04-01

Models for the simulation of ultrasonic inspections of flat and curved plate-like composite structures, as well as stiffeners, are available in the CIVA-COMPOSITE module released in 2016. A first modelling approach using a ray-based model is able to predict the ultrasonic propagation in an anisotropic effective medium obtained after having homogenized the composite laminate. Fast 3D computations can be performed on configurations featuring delaminations, flat bottom holes or inclusions for example. In addition, computations on ply waviness using this model will be available in CIVA 2017. Another approach is proposed in the CIVA-COMPOSITE module. It is based on the coupling of CIVA ray-based model and a finite difference scheme in time domain (FDTD) developed by AIRBUS. The ray model handles the ultrasonic propagation between the transducer and the FDTD computation zone that surrounds the composite part. In this way, the computational efficiency is preserved and the ultrasound scattering by the composite structure can be predicted. Alternatively, a high order finite element approach is currently developed at CEA but not yet integrated in CIVA. The advantages of this approach will be discussed and first simulation results on Carbon Fiber Reinforced Polymers (CFRP) will be shown. Finally, the application of these modelling tools to the construction of metamodels is discussed.

A procedure for utilization of a damage-dependent constitutive model for laminated composites

NASA Technical Reports Server (NTRS)

Lo, David C.; Allen, David H.; Harris, Charles E.

1992-01-01

Described here is the procedure for utilizing a damage constitutive model to predict progressive damage growth in laminated composites. In this model, the effects of the internal damage are represented by strain-like second order tensorial damage variables and enter the analysis through damage dependent ply level and laminate level constitutive equations. The growth of matrix cracks due to fatigue loading is predicted by an experimentally based damage evolutionary relationship. This model is incorporated into a computer code called FLAMSTR. This code is capable of predicting the constitutive response and matrix crack damage accumulation in fatigue loaded laminated composites. The structure and usage of FLAMSTR are presented along with sample input and output files to assist the code user. As an example problem, an analysis of crossply laminates subjected to two stage fatigue loading was conducted and the resulting damage accumulation and stress redistribution were examined to determine the effect of variations in fatigue load amplitude applied during the first stage of the load history. It was found that the model predicts a significant loading history effect on damage evolution.

Fatigue damage prognosis of internal delamination in composite plates under cyclic compression loadings using affine arithmetic as uncertainty propagation tool

NASA Astrophysics Data System (ADS)

Gbaguidi, Audrey J.-M.

Structural health monitoring (SHM) has become indispensable for reducing maintenance costs and increasing the in-service capacity of a structure. The increased use of lightweight composite materials in aircraft structures drastically increased the effects of fatigue induced damage on their critical structural components and thus the necessity to predict the remaining life of those components. Damage prognosis, one of the least investigated fields in SHM, uses the current damage state of the system to forecast its future performance by estimating the expected loading environments. A successful damage prediction model requires the integration of technologies in areas like measurements, materials science, mechanics of materials, and probability theories, but most importantly the quantification of uncertainty in all these areas. In this study, Affine Arithmetic is used as a method for incorporating the uncertainties due to the material properties into the fatigue life prognosis of composite plates subjected to cyclic compressive loadings. When loadings are compressive in nature, the composite plates undergo repeated buckling-unloading of the delaminated layer which induces mixed modes I and II states of stress at the tip of the delamination in the plates. The Kardomateas model-based prediction law is used to predict the growth of the delamination, while the integration of the effects of the uncertainties for modes I and II coefficients in the fatigue life prediction model is handled using Affine arithmetic. The Mode I and Mode II interlaminar fracture toughness and fatigue characterization of the composite plates are first experimentally studied to obtain the material coefficients and fracture toughness, respectively. Next, these obtained coefficients are used in the Kardomateas law to predict the delamination lengths in the composite plates while using Affine Arithmetic to handle their uncertainties. At last, the fatigue characterization of the composite plates during compressive-buckling loadings is experimentally studied, and the delamination lengths obtained are compared with the predicted values to check the performance of Affine Arithmetic as an uncertainty propagation tool.

Predicting the influence of liposomal lipid composition on liposome size, zeta potential and liposome-induced dendritic cell maturation using a design of experiments approach.

PubMed

Soema, Peter C; Willems, Geert-Jan; Jiskoot, Wim; Amorij, Jean-Pierre; Kersten, Gideon F

2015-08-01

In this study, the effect of liposomal lipid composition on the physicochemical characteristics and adjuvanticity of liposomes was investigated. Using a design of experiments (DoE) approach, peptide-containing liposomes containing various lipids (EPC, DOPE, DOTAP and DC-Chol) and peptide concentrations were formulated. Liposome size and zeta potential were determined for each formulation. Moreover, the adjuvanticity of the liposomes was assessed in an in vitro dendritic cell (DC) model, by quantifying the expression of DC maturation markers CD40, CD80, CD83 and CD86. The acquired data of these liposome characteristics were successfully fitted with regression models, and response contour plots were generated for each response factor. These models were applied to predict a lipid composition that resulted in a liposome with a target zeta potential. Subsequently, the expression of the DC maturation factors for this lipid composition was predicted and tested in vitro; the acquired maturation responses corresponded well with the predicted ones. These results show that a DoE approach can be used to screen various lipids and lipid compositions, and to predict their impact on liposome size, charge and adjuvanticity. Using such an approach may accelerate the formulation development of liposomal vaccine adjuvants. Copyright © 2015 The Authors. Published by Elsevier B.V. All rights reserved.

VARTM Process Modeling of Aerospace Composite Structures

NASA Technical Reports Server (NTRS)

Song, Xiao-Lan; Grimsley, Brian W.; Hubert, Pascal; Cano, Roberto J.; Loos, Alfred C.

2003-01-01

A three-dimensional model was developed to simulate the VARTM composite manufacturing process. The model considers the two important mechanisms that occur during the process: resin flow, and compaction and relaxation of the preform. The model was used to simulate infiltration of a carbon preform with an epoxy resin by the VARTM process. The model predicted flow patterns and preform thickness changes agreed qualitatively with the measured values. However, the predicted total infiltration times were much longer than measured most likely due to the inaccurate preform permeability values used in the simulation.

Prediction of the partitioning behaviour of proteins in aqueous two-phase systems using only their amino acid composition.

PubMed

Salgado, J Cristian; Andrews, Barbara A; Ortuzar, Maria Fernanda; Asenjo, Juan A

2008-01-18

The prediction of the partition behaviour of proteins in aqueous two-phase systems (ATPS) using mathematical models based on their amino acid composition was investigated. The predictive models are based on the average surface hydrophobicity (ASH). The ASH was estimated by means of models that use the three-dimensional structure of proteins and by models that use only the amino acid composition of proteins. These models were evaluated for a set of 11 proteins with known experimental partition coefficient in four-phase systems: polyethylene glycol (PEG) 4000/phosphate, sulfate, citrate and dextran and considering three levels of NaCl concentration (0.0% w/w, 0.6% w/w and 8.8% w/w). The results indicate that such prediction is feasible even though the quality of the prediction depends strongly on the ATPS and its operational conditions such as the NaCl concentration. The ATPS 0 model which use the three-dimensional structure obtains similar results to those given by previous models based on variables measured in the laboratory. In addition it maintains the main characteristics of the hydrophobic resolution and intrinsic hydrophobicity reported before. Three mathematical models, ATPS I-III, based only on the amino acid composition were evaluated. The best results were obtained by the ATPS I model which assumes that all of the amino acids are completely exposed. The performance of the ATPS I model follows the behaviour reported previously, i.e. its correlation coefficients improve as the NaCl concentration increases in the system and, therefore, the effect of the protein hydrophobicity prevails over other effects such as charge or size. Its best predictive performance was obtained for the PEG/dextran system at high NaCl concentration. An increase in the predictive capacity of at least 54.4% with respect to the models which use the three-dimensional structure of the protein was obtained for that system. In addition, the ATPS I model exhibits high correlation coefficients in that system being higher than 0.88 on average. The ATPS I model exhibited correlation coefficients higher than 0.67 for the rest of the ATPS at high NaCl concentration. Finally, we tested our best model, the ATPS I model, on the prediction of the partition coefficient of the protein invertase. We found that the predictive capacities of the ATPS I model are better in PEG/dextran systems, where the relative error of the prediction with respect to the experimental value is 15.6%.

A dislocation-based, strain–gradient–plasticity strengthening model for deformation processed metal–metal composites

DOE PAGES

Tian, Liang; Russell, Alan; Anderson, Iver

2014-01-03

Deformation processed metal–metal composites (DMMCs) are high-strength, high-electrical conductivity composites developed by severe plastic deformation of two ductile metal phases. The extraordinarily high strength of DMMCs is underestimated using the rule of mixture (or volumetric weighted average) of conventionally work-hardened metals. A dislocation-density-based, strain–gradient–plasticity model is proposed to relate the strain-gradient effect with the geometrically necessary dislocations emanating from the interface to better predict the strength of DMMCs. The model prediction was compared with our experimental findings of Cu–Nb, Cu–Ta, and Al–Ti DMMC systems to verify the applicability of the new model. The results show that this model predicts themore » strength of DMMCs better than the rule-of-mixture model. The strain-gradient effect, responsible for the exceptionally high strength of heavily cold worked DMMCs, is dominant at large deformation strain since its characteristic microstructure length is comparable with the intrinsic material length.« less

Modeling Woven Polymer Matrix Composites with MAC/GMC

NASA Technical Reports Server (NTRS)

Bednarcyk, Brett A.; Arnold, Steven M. (Technical Monitor)

2000-01-01

NASA's Micromechanics Analysis Code with Generalized Method of Cells (MAC/GMC) is used to predict the elastic properties of plain weave polymer matrix composites (PMCs). The traditional one step three-dimensional homogertization procedure that has been used in conjunction with MAC/GMC for modeling woven composites in the past is inaccurate due to the lack of shear coupling inherent to the model. However, by performing a two step homogenization procedure in which the woven composite repeating unit cell is homogenized independently in the through-thickness direction prior to homogenization in the plane of the weave, MAC/GMC can now accurately model woven PMCs. This two step procedure is outlined and implemented, and predictions are compared with results from the traditional one step approach and other models and experiments from the literature. Full coupling of this two step technique with MAC/ GMC will result in a widely applicable, efficient, and accurate tool for the design and analysis of woven composite materials and structures.

Modeling and Simulation of Voids in Composite Tape Winding Process Based on Domain Superposition Technique

NASA Astrophysics Data System (ADS)

Deng, Bo; Shi, Yaoyao

2017-11-01

The tape winding technology is an effective way to fabricate rotationally composite materials. Nevertheless, some inevitable defects will seriously influence the performance of winding products. One of the crucial ways to identify the quality of fiber-reinforced composite material products is examining its void content. Significant improvement in products' mechanical properties can be achieved by minimizing the void defect. Two methods were applied in this study, finite element analysis and experimental testing, respectively, to investigate the mechanism of how void forming in composite tape winding processing. Based on the theories of interlayer intimate contact and Domain Superposition Technique (DST), a three-dimensional model of prepreg tape void with SolidWorks has been modeled in this paper. Whereafter, ABAQUS simulation software was used to simulate the void content change with pressure and temperature. Finally, a series of experiments were performed to determine the accuracy of the model-based predictions. The results showed that the model is effective for predicting the void content in the composite tape winding process.

Modified creep and shrinkage prediction model B3 for serviceability limit state analysis of composite slabs

NASA Astrophysics Data System (ADS)

Gholamhoseini, Alireza

2016-03-01

Relatively little research has been reported on the time-dependent in-service behavior of composite concrete slabs with profiled steel decking as permanent formwork and little guidance is available for calculating long-term deflections. The drying shrinkage profile through the thickness of a composite slab is greatly affected by the impermeable steel deck at the slab soffit, and this has only recently been quantified. This paper presents the results of long-term laboratory tests on composite slabs subjected to both drying shrinkage and sustained loads. Based on laboratory measurements, a design model for the shrinkage strain profile through the thickness of a slab is proposed. The design model is based on some modifications to an existing creep and shrinkage prediction model B3. In addition, an analytical model is developed to calculate the time-dependent deflection of composite slabs taking into account the time-dependent effects of creep and shrinkage. The calculated deflections are shown to be in good agreement with the experimental measurements.

Modeling and life prediction methodology for Titanium Matrix Composites subjected to mission profiles

NASA Technical Reports Server (NTRS)

Mirdamadi, M.; Johnson, W. S.

1994-01-01

Titanium matrix composites (TMC) are being evaluated as structural materials for elevated temperature applications in future generation hypersonic vehicles. In such applications, TMC components are subjected to complex thermomechanical loading profiles at various elevated temperatures. Therefore, thermomechanical fatigue (TMF) testing, using a simulated mission profile, is essential for evaluation and development of life prediction methodologies. The objective of the research presented in this paper was to evaluate the TMF response of the (0/90)2s SCS-6/Timetal-21S subjected to a generic hypersonic flight profile and its portions with a temperature ranging from -130 C to 816 C. It was found that the composite modulus, prior to rapid degradation, had consistent values for all the profiles tested. A micromechanics based analysis was used to predict the stress-strain response of the laminate and of the constituents in each ply during thermomechanical loading conditions by using only constituent properties as input. The fiber was modeled as elastic with transverse orthotropic and temperature dependent properties. The matrix was modeled using a thermoviscoplastic constitutive relation. In the analysis, the composite modulus degradation was assumed to result from matrix cracking and was modeled by reducing the matrix modulus. Fatigue lives of the composite subjected to the complex generic hypersonic flight profile were well correlated using the predicted stress in 0 degree fibers.

Investigation of the Thermomechanical Response of Shape Memory Alloy Hybrid Composite Beams

NASA Technical Reports Server (NTRS)

Davis, Brian A.

2005-01-01

Previous work at NASA Langley Research Center (LaRC) involved fabrication and testing of composite beams with embedded, pre-strained shape memory alloy (SMA) ribbons. That study also provided comparison of experimental results with numerical predictions from a research code making use of a new thermoelastic model for shape memory alloy hybrid composite (SMAHC) structures. The previous work showed qualitative validation of the numerical model. However, deficiencies in the experimental-numerical correlation were noted and hypotheses for the discrepancies were given for further investigation. The goal of this work is to refine the experimental measurement and numerical modeling approaches in order to better understand the discrepancies, improve the correlation between prediction and measurement, and provide rigorous quantitative validation of the numerical model. Thermal buckling, post-buckling, and random responses to thermal and inertial (base acceleration) loads are studied. Excellent agreement is achieved between the predicted and measured results, thereby quantitatively validating the numerical tool.

Hydrogen and Oxygen Isotope Ratios in Body Water and Hair: Modeling Isotope Dynamics in Nonhuman Primates

PubMed Central

O’Grady, Shannon P.; Valenzuela, Luciano O.; Remien, Christopher H.; Enright, Lindsey E.; Jorgensen, Matthew J.; Kaplan, Jay R.; Wagner, Janice D.; Cerling, Thure E.; Ehleringer, James R.

2012-01-01

The stable isotopic composition of drinking water, diet, and atmospheric oxygen influence the isotopic composition of body water (2H/1H, 18O/16O expressed as δ2H and δ18O). In turn, body water influences the isotopic composition of organic matter in tissues, such as hair and teeth, which are often used to reconstruct historical dietary and movement patterns of animals and humans. Here, we used a nonhuman primate system (Macaca fascicularis) to test the robustness of two different mechanistic stable isotope models: a model to predict the δ2H and δ18O values of body water and a second model to predict the δ2H and δ18O values of hair. In contrast to previous human-based studies, use of nonhuman primates fed controlled diets allowed us to further constrain model parameter values and evaluate model predictions. Both models reliably predicted the δ2H and δ18O values of body water and of hair. Moreover, the isotope data allowed us to better quantify values for two critical variables in the models: the δ2H and δ18O values of gut water and the 18O isotope fractionation associated with a carbonyl oxygen-water interaction in the gut (αow). Our modeling efforts indicated that better predictions for body water and hair isotope values were achieved by making the isotopic composition of gut water approached that of body water. Additionally, the value of αow was 1.0164, in close agreement with the only other previously measured observation (microbial spore cell walls), suggesting robustness of this fractionation factor across different biological systems. PMID:22553163

Hydrogen and oxygen isotope ratios in body water and hair: modeling isotope dynamics in nonhuman primates.

PubMed

O'Grady, Shannon P; Valenzuela, Luciano O; Remien, Christopher H; Enright, Lindsey E; Jorgensen, Matthew J; Kaplan, Jay R; Wagner, Janice D; Cerling, Thure E; Ehleringer, James R

2012-07-01

The stable isotopic composition of drinking water, diet, and atmospheric oxygen influence the isotopic composition of body water ((2)H/(1)H, (18)O/(16)O expressed as δ(2) H and δ(18)O). In turn, body water influences the isotopic composition of organic matter in tissues, such as hair and teeth, which are often used to reconstruct historical dietary and movement patterns of animals and humans. Here, we used a nonhuman primate system (Macaca fascicularis) to test the robustness of two different mechanistic stable isotope models: a model to predict the δ(2)H and δ(18)O values of body water and a second model to predict the δ(2)H and δ(18)O values of hair. In contrast to previous human-based studies, use of nonhuman primates fed controlled diets allowed us to further constrain model parameter values and evaluate model predictions. Both models reliably predicted the δ(2)H and δ(18)O values of body water and of hair. Moreover, the isotope data allowed us to better quantify values for two critical variables in the models: the δ(2)H and δ(18)O values of gut water and the (18)O isotope fractionation associated with a carbonyl oxygen-water interaction in the gut (α(ow)). Our modeling efforts indicated that better predictions for body water and hair isotope values were achieved by making the isotopic composition of gut water approached that of body water. Additionally, the value of α(ow) was 1.0164, in close agreement with the only other previously measured observation (microbial spore cell walls), suggesting robustness of this fractionation factor across different biological systems. © 2012 Wiley Periodicals, Inc.

A Deep Learning Approach to LIBS Spectroscopy for Planetary Applications

NASA Astrophysics Data System (ADS)

Mullen, T. H.; Parente, M.; Gemp, I.; Dyar, M. D.

2017-12-01

The ChemCam instrument on the Curiousity rover has collected >440,000 laser-induced breakdown spectra (LIBS) from 1500 different geological targets since 2012. The team is using a pipeline of preprocessing and partial least squares techniques to predict compositions of surface materials [1]. Unfortunately, such multivariate techniques are plagued by hard-to-meet assumptions involving constant hyperparameter tuning to specific elements and the amount of training data available; if the whole distribution of data is not seen, the method will overfit to the training data and generalizability will suffer. The rover only has 10 calibration targets on-board that represent a small subset of the geochemical samples the rover is expected to investigate. Deep neural networks have been used to bypass these issues in other fields. Semi-supervised techniques allow researchers to utilized small labeled datasets and vast amounts of unlabeled data. One example is the variational autoencoder model, a semi-supervised generative model in the form of a deep neural network. The autoencoder assumes that LIBS spectra are generated from a distribution conditioned on the elemental compositions in the sample and some nuisance. The system is broken into two models: one that predicts elemental composition from the spectra and one that generates spectra from compositions that may or may not be seen in the training set. The synthesized spectra show strong agreement with geochemical conventions to express specific compositions. The predictions of composition show improved generalizability to PLS. Deep neural networks have also been used to transfer knowledge from one dataset to another to solve unlabeled data problems. Given that vast amounts of laboratry LIBS spectra have been obtained in the past few years, it is now feasible train a deep net to predict elemental composition from lab spectra. Transfer learning (manifold alignment or calibration transfer) [2] is then used to fine-tune the model from terrestrial lab data to Martian field data. Neural networks and generative models provide the flexibility need for elemental composition prediction and unseen spectra synthesis. [1] Clegg S. et al. (2016) Spectrochim. Acta B, 129, 64-85. [2] Boucher T. et al. (2017) J. Chemom., 31, e2877.

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

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

Nguyen, Ba Nghiep; Kunc, Vlastimil; Jin, Xiaoshi

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. Predictedmore » stress-strain responses up to failure and damage accumulations are compared to the experimental results to validate the model.« less

Numerical simulation of elasto-plastic deformation of composites: evolution of stress microfields and implications for homogenization models

NASA Astrophysics Data System (ADS)

González, C.; Segurado, J.; LLorca, J.

2004-07-01

The deformation of a composite made up of a random and homogeneous dispersion of elastic spheres in an elasto-plastic matrix was simulated by the finite element analysis of three-dimensional multiparticle cubic cells with periodic boundary conditions. "Exact" results (to a few percent) in tension and shear were determined by averaging 12 stress-strain curves obtained from cells containing 30 spheres, and they were compared with the predictions of secant homogenization models. In addition, the numerical simulations supplied detailed information of the stress microfields, which was used to ascertain the accuracy and the limitations of the homogenization models to include the nonlinear deformation of the matrix. It was found that secant approximations based on the volume-averaged second-order moment of the matrix stress tensor, combined with a highly accurate linear homogenization model, provided excellent predictions of the composite response when the matrix strain hardening rate was high. This was not the case, however, in composites which exhibited marked plastic strain localization in the matrix. The analysis of the evolution of the matrix stresses revealed that better predictions of the composite behavior can be obtained with new homogenization models which capture the essential differences in the stress carried by the elastic and plastic regions in the matrix at the onset of plastic deformation.

Predicting animal δ18O: Accounting for diet and physiological adaptation

NASA Astrophysics Data System (ADS)

Kohn, Matthew J.

1996-12-01

Theoretical predictions and measured isotope variations indicate that diet and physiological adaptation have a significant impact on animals δ18O and cannot be ignored. A generalized model is therefore developed for the prediction of animal body water and phosphate δ18O to incorporate these factors quantitatively. Application of the model reproduces most published compositions and compositional trends for mammals and birds. A moderate dependence of animal δ18O on humidity is predicted for drought-tolerant animals, and the correlation between humidity and North American deer bone composition as corrected for local meteoric water is predicted within the scatter of the data. In contrast to an observed strong correlation between kangaroo δ18O and humidity (Δδ18O/Δh ∼ 2.5± 0.4‰/10%r.h.), the predicted humidity dependence is only 1.3 - 1.7‰/10% r.h., and it is inferred that drinking water in hot dry areas of Australia is enriched in 18O over rainwater. Differences in physiology and water turnover readily explain the observed differences in δ18O for several herbivore genera in East Africa, excepting antelopes. Antelope models are more sensitive to biological fractionations, and adjustments to the flux of transcutaneous water vapor within experimentally measured ranges allows their δ18O values to be matched. Models of the seasonal changes of forage composition for two regions with dissimilar climates show that significant seasonal variations in animal isotope composition are expected, and that animals with different physiologies and diets track climate differently. Analysis of different genera with disparate sensitivities to surface water and humidity will allow the most accurate quantification of past climate changes.

Circular Functions Based Comprehensive Analysis of Plastic Creep Deformations in the Fiber Reinforced Composites

NASA Astrophysics Data System (ADS)

Monfared, Vahid

2016-12-01

Analytically based model is presented for behavioral analysis of the plastic deformations in the reinforced materials using the circular (trigonometric) functions. The analytical method is proposed to predict creep behavior of the fibrous composites based on basic and constitutive equations under a tensile axial stress. New insight of the work is to predict some important behaviors of the creeping matrix. In the present model, the prediction of the behaviors is simpler than the available methods. Principal creep strain rate behaviors are very noteworthy for designing the fibrous composites in the creeping composites. Analysis of the mentioned parameter behavior in the reinforced materials is necessary to analyze failure, fracture, and fatigue studies in the creep of the short fiber composites. Shuttles, spaceships, turbine blades and discs, and nozzle guide vanes are commonly subjected to the creep effects. Also, predicting the creep behavior is significant to design the optoelectronic and photonic advanced composites with optical fibers. As a result, the uniform behavior with constant gradient is seen in the principal creep strain rate behavior, and also creep rupture may happen at the fiber end. Finally, good agreements are found through comparing the obtained analytical and FEM results.

Comprehensive model for predicting elemental composition of coal pyrolysis products

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

Ricahrds, Andrew P.; Shutt, Tim; Fletcher, Thomas H.

Large-scale coal combustion simulations depend highly on the accuracy and utility of the physical submodels used to describe the various physical behaviors of the system. Coal combustion simulations depend on the particle physics to predict product compositions, temperatures, energy outputs, and other useful information. The focus of this paper is to improve the accuracy of devolatilization submodels, to be used in conjunction with other particle physics models. Many large simulations today rely on inaccurate assumptions about particle compositions, including that the volatiles that are released during pyrolysis are of the same elemental composition as the char particle. Another common assumptionmore » is that the char particle can be approximated by pure carbon. These assumptions will lead to inaccuracies in the overall simulation. There are many factors that influence pyrolysis product composition, including parent coal composition, pyrolysis conditions (including particle temperature history and heating rate), and others. All of these factors are incorporated into the correlations to predict the elemental composition of the major pyrolysis products, including coal tar, char, and light gases.« less

Comparison of model predictions for the composition of the ionosphere of Mars to MAVEN NGIMS data

NASA Astrophysics Data System (ADS)

Withers, Paul; Vogt, Marissa; Mayyasi, Majd; Mahaffy, Paul; Benna, Mehdi; Elrod, Meredith; Bougher, Stephen; Dong, Chuanfei; Chaufray, Jean-Yves; Ma, Yingjuan; Jakosky, Bruce

2015-11-01

Prior to the arrival of the Mars Atmosphere and Volatile EvolutioN (MAVEN) spacecraft at Mars, the only available measurements of the composition of the planet's ionosphere were those acquired by the two Viking Landers during their atmospheric entries. Many numerical models of the composition of the ionosphere of Mars have been developed, but these have only been validated for species, altitudes, and conditions for which Viking data exist. Here we compare the ionospheric composition and structure predicted by 10 ionospheric models at solar zenith angles of 45-60° against ion density measurements acquired by the MAVEN Neutral Gas and Ion Mass Spectrometer (NGIMS). The most successful models included three-dimensional plasma transport driven by interactions with the surrounding space environment but had relatively simple ionospheric chemistry.

Evaluating the environmental fate of short-chain chlorinated paraffins (SCCPs) in the Nordic environment using a dynamic multimedia model.

PubMed

Krogseth, Ingjerd S; Breivik, Knut; Arnot, Jon A; Wania, Frank; Borgen, Anders R; Schlabach, Martin

2013-12-01

Short chain chlorinated paraffins (SCCPs) raise concerns due to their potential for persistence, bioaccumulation, long-range transport and adverse effects. An understanding of their environmental fate remains limited, partly due to the complexity of the mixture. The purpose of this study was to evaluate whether a mechanistic, integrated, dynamic environmental fate and bioaccumulation multimedia model (CoZMoMAN) can reconcile what is known about environmental emissions and human exposure of SCCPs in the Nordic environment. Realistic SCCP emission scenarios, resolved by formula group, were estimated and used to predict the composition and concentrations of SCCPs in the environment and the human food chain. Emissions at the upper end of the estimated range resulted in predicted total concentrations that were often within a factor of 6 of observations. Similar model performance for a complex group of organic contaminants as for the well-known polychlorinated biphenyls strengthens the confidence in the CoZMoMAN model and implies a relatively good mechanistic understanding of the environmental fate of SCCPs. However, the degree of chlorination predicted for SCCPs in sediments, fish, and humans was higher than observed and poorly established environmental half-lives and biotransformation rate constants contributed to the uncertainties in the predicted composition and ∑SCCP concentrations. Improving prediction of the SCCP composition will also require better constrained estimates of the composition of SCCP emissions. There is, however, also large uncertainty and lack of coherence in the existing observations, and better model-measurement agreement will require improved analytical methods and more strategic sampling. More measurements of SCCP levels and compositions in samples from background regions are particularly important.

Validation of an interior noise prediction model for a composite cylinder

NASA Technical Reports Server (NTRS)

Beyer, Todd B.; Grosveld, Ferdinand W.

1987-01-01

An acoustic modal analysis has been performed in the cavity of a composite cylinder model of an aircraft fuselage. The filament wound, composite shell is 12 feet long and 5.5 feet in diameter. A one-half-in. thick plywood floor is attached to the shell 69 deg from the vertical centerline through the bottom of the shell. The acoustic modal frequencies were obtained from a sound pressure level and phase survey conducted throughout the interior volume bounded by the floor, endcaps and stiffened shell, while being excited by white noise from a loudspeaker source. The measured acoustic resonance frequencies and mode shapes compare well with analytical predictions from the Propeller Aircraft Interior Noise (PAIN) model. Details of the theory and derivation of the acoustic characteristics have been included. Reverberation time measurements, using the integrated impulse technique, have been performed to determine acoustic loss factors. These measured loss factors have been input to the PAIN program in order to more accurately predict the space-averaged interior noise of the composite cylinder.

Predicting properties of gas and solid streams by intrinsic kinetics of fast pyrolysis of wood

DOE PAGES

Klinger, Jordan; Bar-Ziv, Ezra; Shonnard, David; ...

2015-12-12

Pyrolysis has the potential to create a biocrude oil from biomass sources that can be used as fuel or as feedstock for subsequent upgrading to hydrocarbon fuels or other chemicals. The product distribution/composition, however, is linked to the biomass source. This work investigates the products formed from pyrolysis of woody biomass with a previously developed chemical kinetics model. Different woody feedstocks reported in prior literature are placed on a common basis (moisture, ash, fixed carbon free) and normalized by initial elemental composition through ultimate analysis. Observed product distributions over the full devolatilization range are explored, reconstructed by the model, andmore » verified with independent experimental data collected with a microwave-assisted pyrolysis system. These trends include production of permanent gas (CO, CO 2), char, and condensable (oil, water) species. Elementary compositions of these streams are also investigated. As a result, close agreement between literature data, model predictions, and independent experimental data indicate that the proposed model/method is able to predict the ideal distribution from fast pyrolysis given reaction temperature, residence time, and feedstock composition.« less

Prediction of mechanical properties of composites of HDPE/HA/EAA.

PubMed

Albano, C; Perera, R; Cataño, L; Karam, A; González, G

2011-04-01

In this investigation, the behavior of the mechanical properties of composites of high-density polyethylene/hydroxyapatite (HDPE/HA) with and without ethylene-acrylic acid copolymer (EAA) as possible compatibilizer, was studied. Different mathematical models were used to predict their Young's modulus, tensile strength and elongation at break. A comparison with the experimental results shows that the theoretical models of Guth and Kerner modified can be used to predict the Young's modulus. On the other hand, the values obtained by the Verbeek model do not show a good agreement with the experimental data, since different factors that influence the mechanical properties are considered in this model such as: aspect ratio of the reinforcement, interfacial adhesion, porosity and binder content. TEM analysis confirms the discrepancies obtained between the experimental Young's modulus values and those predicted by the Verbeek model. The values of "P", "a" and "σ(A)" suggest that an interaction among the carboxylic groups of the copolymer and the hydroxyl groups of hydroxyapatite might be present. In composites with 20 and 30 wt% of filler, this interaction does not improve the Young's modulus values, since the deviations of the Verbeek model are significant. Copyright © 2010 Elsevier Ltd. All rights reserved.

Micromechanics analysis of space simulated thermal deformations and stresses in continuous fiber reinforced composites

NASA Technical Reports Server (NTRS)

Bowles, David E.

1990-01-01

Space simulated thermally induced deformations and stresses in continuous fiber reinforced composites were investigated with a micromechanics analysis. The investigation focused on two primary areas. First, available explicit expressions for predicting the effective coefficients of thermal expansion (CTEs) for a composite were compared with each other, and with a finite element (FE) analysis, developed specifically for this study. Analytical comparisons were made for a wide range of fiber/matrix systems, and predicted values were compared with experimental data. The second area of investigation focused on the determination of thermally induced stress fields in the individual constituents. Stresses predicted from the FE analysis were compared to those predicted from a closed-form solution to the composite cylinder (CC) model, for two carbon fiber/epoxy composites. A global-local formulation, combining laminated plate theory and FE analysis, was used to determine the stresses in multidirectional laminates. Thermally induced damage initiation predictions were also made.

Thermo-hydroforming of a fiber-reinforced thermoplastic composites considering fiber orientations

NASA Astrophysics Data System (ADS)

Ahn, Hyunchul; Kuuttila, Nicholas Eric; Pourboghrat, Farhang

2018-05-01

The Thermoplastic woven composites were formed using a composite thermal hydroforming process, utilizing heated and pressurized fluid, similar to sheet metal forming. This study focuses on the modification of 300-ton pressure formation and predicts its behavior. Spectra Shield SR-3136 is used in this study and material properties are measured by experiments. The behavior of fiber-reinforced thermoplastic polymer composites (FRTP) was modeled using the Preferred Fiber Orientation (PFO) model and validated by comparing numerical analysis with experimental results. The thermo-hydroforming process has shown good results in the ability to form deep drawn parts with reduced wrinkles. Numerical analysis was performed using the PFO model and implemented as commercial finite element software ABAQUS / Explicit. The user subroutine (VUMAT) was used for the material properties of the thermoplastic composite layer. This model is suitable for working with multiple layers of composite laminates. Model parameters have been updated to work with cohesive zone model to calculate the interfacial properties between each composite layer. The results of the numerical modeling showed a good correlation with the molding experiment on the forming shape. Numerical results were also compared with experimental results on punch force-displacement curves for deformed geometry and forming processes of the composite layer. Overall, the shape of the deformed FRTP, including the distribution of wrinkles, was accurately predicted as shown in this study.

Distillation-based Droplet Modeling of Non-Ideal Oxygenated Gasoline Blends: Investigating the Role of Droplet Evaporation on PM Emissions

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

Burke, Stephen C.; Ratcliff, Matthew; McCormick, Robert

In some studies, a relationship has been observed between increasing ethanol content in gasoline and increased particulate matter (PM) emissions from vehicles equipped with spark ignition engines. The fundamental cause of the PM increase seen for moderate ethanol concentrations is not well understood. Ethanol features a greater heat of vaporization (HOV) than gasoline and also influences vaporization by altering the liquid and vapor composition throughout the distillation process. A droplet vaporization model was developed to explore ethanol's effect on the evaporation of aromatic compounds known to be PM precursors. The evolving droplet composition is modeled as a distillation process, withmore » non-ideal interactions between oxygenates and hydrocarbons accounted for using UNIFAC group contribution theory. Predicted composition and distillation curves were validated by experiments. Detailed hydrocarbon analysis was applied to fuel samples and to distillate fractions, and used as input for the initial droplet composition. With composition calculated throughout the distillation, the changing HOV and other physical properties can be found using reference data. The droplet can thus be modeled in terms of energy transfer, which in turn provides the transient mass transfer, droplet temperature, and droplet diameter. Model predictions suggest that non-ideal vapor-liquid equilibrium along with an increase in HOV can alter the droplet composition evolution. Results predict that the presence of ethanol causes enrichment of the higher boiling fractions (T90+) in the aromatic components as well as lengthens the droplet lifetime. A simulation of the evaporation process in a transient environment as experienced within an engine cylinder predicts a decrease in mixing time of the heaviest fractions of the fuel prior to spark initiation, possibly explaining observations linking ethanol to PM.« less

Distillation-based Droplet Modeling of Non-Ideal Oxygenated Gasoline Blends: Investigating the Role of Droplet Evaporation on PM Emissions

DOE PAGES

Burke, Stephen C.; Ratcliff, Matthew; McCormick, Robert; ...

2017-03-28

In some studies, a relationship has been observed between increasing ethanol content in gasoline and increased particulate matter (PM) emissions from vehicles equipped with spark ignition engines. The fundamental cause of the PM increase seen for moderate ethanol concentrations is not well understood. Ethanol features a greater heat of vaporization (HOV) than gasoline and also influences vaporization by altering the liquid and vapor composition throughout the distillation process. A droplet vaporization model was developed to explore ethanol's effect on the evaporation of aromatic compounds known to be PM precursors. The evolving droplet composition is modeled as a distillation process, withmore » non-ideal interactions between oxygenates and hydrocarbons accounted for using UNIFAC group contribution theory. Predicted composition and distillation curves were validated by experiments. Detailed hydrocarbon analysis was applied to fuel samples and to distillate fractions, and used as input for the initial droplet composition. With composition calculated throughout the distillation, the changing HOV and other physical properties can be found using reference data. The droplet can thus be modeled in terms of energy transfer, which in turn provides the transient mass transfer, droplet temperature, and droplet diameter. Model predictions suggest that non-ideal vapor-liquid equilibrium along with an increase in HOV can alter the droplet composition evolution. Results predict that the presence of ethanol causes enrichment of the higher boiling fractions (T90+) in the aromatic components as well as lengthens the droplet lifetime. A simulation of the evaporation process in a transient environment as experienced within an engine cylinder predicts a decrease in mixing time of the heaviest fractions of the fuel prior to spark initiation, possibly explaining observations linking ethanol to PM.« less

Effect of saline absorption on the flexural stress relaxation behavior of epoxy/cotton composite materials for orthopedics applications

NASA Astrophysics Data System (ADS)

Kontaxis, L. C.; Pavlou, C.; Portan, D. V.; Papanicolaou, G. C.

2018-02-01

In the present study, a composite material consisting of a polymeric epoxy resin matrix, reinforced with forty layers of non-woven cotton fiber fabric was manufactured. The method used to manufacture the composite was the Resin Vacuum Infusion technique. This is a technique widely used for high-performance, defect-free, composite materials. Composites and neat polymers are subjected to stresses during their function, while at the same time being influenced by environmental conditions, such as temperature and humidity. The main goal of this study was the investigation of the degradation of composite's viscoelastic behavior, after saline absorption. At this point, it should be mentioned, that this material could be used in biomedical applications. Therefore, a sealed container full of saline was used for the immer s ion of the specimens manufactured, and was placed in a bath at 37°C (body temperature). The specimens remained there for five different immersion periods (24, 72, 144, 216, 336 hours). The viscoelastic behavior of the composite material was determined through stress relaxation under flexure conditions, and the effect of immersion time and amount of saline absorption was studied. It was observed that after 24 hours of immersion a 42% decrease in stress was observed, which in the sequence remained almost constant. The stress relaxation experimental results were predicted by using the Residua l Property Model (RPM), a model developed by Papanicolaou et al. The same model has been successfully applied in the past, to many different materials previously subjected to various types of damage, in order to predict their residual behavior. For its application, the RPM predictive model needs only two experimental points. It was found that in all cases, predictions were in good agreement with experimental findings. Furthermore, the comparison between experimental values and theoretical predictions formed the basis of useful observations and conclusions.

Application of finite element substructuring to composite micromechanics. M.S. Thesis - Akron Univ., May 1984

NASA Technical Reports Server (NTRS)

Caruso, J. J.

1984-01-01

Finite element substructuring is used to predict unidirectional fiber composite hygral (moisture), thermal, and mechanical properties. COSMIC NASTRAN and MSC/NASTRAN are used to perform the finite element analysis. The results obtained from the finite element model are compared with those obtained from the simplified composite micromechanics equations. A unidirectional composite structure made of boron/HM-epoxy, S-glass/IMHS-epoxy and AS/IMHS-epoxy are studied. The finite element analysis is performed using three dimensional isoparametric brick elements and two distinct models. The first model consists of a single cell (one fiber surrounded by matrix) to form a square. The second model uses the single cell and substructuring to form a nine cell square array. To compare computer time and results with the nine cell superelement model, another nine cell model is constructed using conventional mesh generation techniques. An independent computer program consisting of the simplified micromechanics equation is developed to predict the hygral, thermal, and mechanical properties for this comparison. The results indicate that advanced techniques can be used advantageously for fiber composite micromechanics.

Comparison of models for predicting the changes in phytoplankton community composition in the receiving water system of an inter-basin water transfer project.

PubMed

Zeng, Qinghui; Liu, Yi; Zhao, Hongtao; Sun, Mingdong; Li, Xuyong

2017-04-01

Inter-basin water transfer projects might cause complex hydro-chemical and biological variation in the receiving aquatic ecosystems. Whether machine learning models can be used to predict changes in phytoplankton community composition caused by water transfer projects have rarely been studied. In the present study, we used machine learning models to predict the total algal cell densities and changes in phytoplankton community composition in Miyun reservoir caused by the middle route of the South-to-North Water Transfer Project (SNWTP). The model performances of four machine learning models, including regression trees (RT), random forest (RF), support vector machine (SVM), and artificial neural network (ANN) were evaluated and the best model was selected for further prediction. The results showed that the predictive accuracies (Pearson's correlation coefficient) of the models were RF (0.974), ANN (0.951), SVM (0.860), and RT (0.817) in the training step and RF (0.806), ANN (0.734), SVM (0.730), and RT (0.692) in the testing step. Therefore, the RF model was the best method for estimating total algal cell densities. Furthermore, the predicted accuracies of the RF model for dominant phytoplankton phyla (Cyanophyta, Chlorophyta, and Bacillariophyta) in Miyun reservoir ranged from 0.824 to 0.869 in the testing step. The predicted proportions with water transfer of the different phytoplankton phyla ranged from -8.88% to 9.93%, and the predicted dominant phyla with water transfer in each season remained unchanged compared to the phytoplankton succession without water transfer. The results of the present study provide a useful tool for predicting the changes in phytoplankton community caused by water transfer. The method is transferrable to other locations via establishment of models with relevant data to a particular area. Our findings help better understanding the possible changes in aquatic ecosystems influenced by inter-basin water transfer. Copyright © 2017 Elsevier Ltd. All rights reserved.

NOAA's National Air Quality Predictions and Development of Aerosol and Atmospheric Composition Prediction Components for the Next Generation Global Prediction System

NASA Astrophysics Data System (ADS)

Stajner, I.; Hou, Y. T.; McQueen, J.; Lee, P.; Stein, A. F.; Tong, D.; Pan, L.; Huang, J.; Huang, H. C.; Upadhayay, S.

2016-12-01

NOAA provides operational air quality predictions using the National Air Quality Forecast Capability (NAQFC): ozone and wildfire smoke for the United States and airborne dust for the contiguous 48 states at http://airquality.weather.gov. NOAA's predictions of fine particulate matter (PM2.5) became publicly available in February 2016. Ozone and PM2.5 predictions are produced using a system that operationally links the Community Multiscale Air Quality (CMAQ) model with meteorological inputs from the North American mesoscale forecast Model (NAM). Smoke and dust predictions are provided using the Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) model. Current NAQFC focus is on updating CMAQ to version 5.0.2, improving PM2.5 predictions, and updating emissions estimates, especially for NOx using recently observed trends. Wildfire smoke emissions from a newer version of the USFS BlueSky system are being included in a new configuration of the NAQFC NAM-CMAQ system, which is re-run for the previous 24 hours when the wildfires were observed from satellites, to better represent wildfire emissions prior to initiating predictions for the next 48 hours. In addition, NOAA is developing the Next Generation Global Prediction System (NGGPS) to represent the earth system for extended weather prediction. NGGPS will include a representation of atmospheric dynamics, physics, aerosols and atmospheric composition as well as coupling with ocean, wave, ice and land components. NGGPS is being developed with a broad community involvement, including community developed components and academic research to develop and test potential improvements for potentially inclusion in NGGPS. Several investigators at NOAA's research laboratories and in academia are working to improve the aerosol and gaseous chemistry representation for NGGPS, to develop and evaluate the representation of atmospheric composition, and to establish and improve the coupling with radiation and microphysics. Additional efforts may include the improved use of predicted atmospheric composition in assimilation of observations and the linkage of full global atmospheric composition predictions with national air quality predictions.

Nonlinear Visco-Elastic Response of Composites via Micro-Mechanical Models

NASA Technical Reports Server (NTRS)

Gates, Thomas S.; Sridharan, Srinivasan

2005-01-01

Micro-mechanical models for a study of nonlinear visco-elastic response of composite laminae are developed and their performance compared. A single integral constitutive law proposed by Schapery and subsequently generalized to multi-axial states of stress is utilized in the study for the matrix material. This is used in conjunction with a computationally facile scheme in which hereditary strains are computed using a recursive relation suggested by Henriksen. Composite response is studied using two competing micro-models, viz. a simplified Square Cell Model (SSCM) and a Finite Element based self-consistent Cylindrical Model (FECM). The algorithm is developed assuming that the material response computations are carried out in a module attached to a general purpose finite element program used for composite structural analysis. It is shown that the SSCM as used in investigations of material nonlinearity can involve significant errors in the prediction of transverse Young's modulus and shear modulus. The errors in the elastic strains thus predicted are of the same order of magnitude as the creep strains accruing due to visco-elasticity. The FECM on the other hand does appear to perform better both in the prediction of elastic constants and the study of creep response.

Micromechanical Prediction of the Effective Behavior of Fully Coupled Electro-Magneto-Thermo-Elastic Multiphase Composites

NASA Technical Reports Server (NTRS)

Aboudi, Jacob

2000-01-01

The micromechanical generalized method of cells model is employed for the prediction of the effective moduli of electro-magneto-thermo-elastic composites. These include the effective elastic, piezoelectric, piezomagnetic, dielectric, magnetic permeability, electromagnetic coupling moduli, as well as the effective thermal expansion coefficients and the associated pyroelectric and pyromagnetic constants. Results are given for fibrous and periodically bilaminated composites.

Prediction of Composite Pressure Vessel Failure Location using Fiber Bragg Grating Sensors

NASA Technical Reports Server (NTRS)

Kreger, Steven T.; Taylor, F. Tad; Ortyl, Nicholas E.; Grant, Joseph

2006-01-01

Ten composite pressure vessels were instrumented with fiber Bragg grating sensors in order to assess the strain levels of the vessel under various loading conditions. This paper and presentation will discuss the testing methodology, the test results, compare the testing results to the analytical model, and present a possible methodology for predicting the failure location and strain level of composite pressure vessels.

Experimental Characterization and Micromechanical Modeling of Woven Carbon/Copper Composites

NASA Technical Reports Server (NTRS)

Bednarcyk, Brett A.; Pauly, Christopher C.; Pindera, Marek-Jerzy

1997-01-01

The results of an extensive experimental characterization and a preliminary analytical modeling effort for the elastoplastic mechanical behavior of 8-harness satin weave carbon/copper (C/Cu) composites are presented. Previous experimental and modeling investigations of woven composites are discussed, as is the evolution of, and motivation for, the continuing research on C/Cu composites. Experimental results of monotonic and cyclic tension, compression, and Iosipescu shear tests, and combined tension-compression tests, are presented. With regard to the test results, emphasis is placed on the effect of strain gauge size and placement, the effect of alloying the copper matrix to improve fiber-matrix bonding, yield surface characterization, and failure mechanisms. The analytical methodology used in this investigation consists of an extension of the three-dimensional generalized method of cells (GMC-3D) micromechanics model, developed by Aboudi (1994), to include inhomogeneity and plasticity effects on the subcell level. The extension of the model allows prediction of the elastoplastic mechanical response of woven composites, as represented by a true repeating unit cell for the woven composite. The model is used to examine the effects of refining the representative geometry of the composite, altering the composite overall fiber volume fraction, changing the size and placement of the strain gauge with respect to the composite's reinforcement weave, and including porosity within the infiltrated fiber yarns on the in-plane elastoplastic tensile, compressive, and shear response of 8-harness satin C/Cu. The model predictions are also compared with the appropriate monotonic experimental results.

A deformation-formulated micromechanics model of the effective Young's modulus and strength of laminated composites containing local ply curvature

NASA Technical Reports Server (NTRS)

Lee, Jong-Won; Harris, Charles E.

1990-01-01

A mathematical model based on the Euler-Bermoulli beam theory is proposed for predicting the effective Young's moduli of piecewise isotropic composite laminates with local ply curvatures in the main load-carrying layers. Strains in corrugated layers, in-phase layers, and out-of-phase layers are predicted for various geometries and material configurations by assuming matrix layers as elastic foundations of different spring constants. The effective Young's moduli measured from corrugated aluminum specimens and aluminum/epoxy specimens with in-phase and out-of-phase wavy patterns coincide very well with the model predictions. Moire fringe analysis of an in-phase specimen and an out-of-phase specimen are also presented, confirming the main assumption of the model related to the elastic constraint due to the matrix layers. The present model is also compared with the experimental results and other models, including the microbuckling models, published in the literature. The results of the present study show that even a very small-scale local ply curvature produces a noticeable effect on the mechanical constitutive behavior of a laminated composite.

Elevated carbon dioxide is predicted to promote coexistence among competing species in a trait-based model

DOE PAGES

Ali, Ashehad A.; Medlyn, Belinda E.; Aubier, Thomas G.; ...

2015-10-06

Differential species responses to atmospheric CO 2 concentration (C a) could lead to quantitative changes in competition among species and community composition, with flow-on effects for ecosystem function. However, there has been little theoretical analysis of how elevated C a (eC a) will affect plant competition, or how composition of plant communities might change. Such theoretical analysis is needed for developing testable hypotheses to frame experimental research. Here, we investigated theoretically how plant competition might change under eC a by implementing two alternative competition theories, resource use theory and resource capture theory, in a plant carbon and nitrogen cycling model.more » The model makes several novel predictions for the impact of eC a on plant community composition. Using resource use theory, the model predicts that eC a is unlikely to change species dominance in competition, but is likely to increase coexistence among species. Using resource capture theory, the model predicts that eC a may increase community evenness. Collectively, both theories suggest that eC a will favor coexistence and hence that species diversity should increase with eC a. Our theoretical analysis leads to a novel hypothesis for the impact of eC a on plant community composition. In this study, the hypothesis has potential to help guide the design and interpretation of eC a experiments.« less

A comparison of life prediction methodologies for titanium matrix composites subjected to thermomechanical fatigue

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

Calcaterra, J.R.; Johnson, W.S.; Neu, R.W.

1997-12-31

Several methodologies have been developed to predict the lives of titanium matrix composites (TMCs) subjected to thermomechanical fatigue (TMF). This paper reviews and compares five life prediction models developed at NASA-LaRC. Wright Laboratories, based on a dingle parameter, the fiber stress in the load-carrying, or 0{degree}, direction. The two other models, both developed at Wright Labs. are multi-parameter models. These can account for long-term damage, which is beyond the scope of the single-parameter models, but this benefit is offset by the additional complexity of the methodologies. Each of the methodologies was used to model data generated at NASA-LeRC. Wright Labs.more » and Georgia Tech for the SCS-6/Timetal 21-S material system. VISCOPLY, a micromechanical stress analysis code, was used to determine the constituent stress state for each test and was used for each model to maintain consistency. The predictive capabilities of the models are compared, and the ability of each model to accurately predict the responses of tests dominated by differing damage mechanisms is addressed.« less

PNNL Technical Support to The Implementation of EMTA and EMTA-NLA Models in Autodesk® Moldflow® Packages

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

Nguyen, Ba Nghiep; Wang, Jin

2012-12-01

Under the Predictive Engineering effort, PNNL developed linear and nonlinear property prediction models for long-fiber thermoplastics (LFTs). These models were implemented in PNNL’s EMTA and EMTA-NLA codes. While EMTA is a standalone software for the computation of the composites thermoelastic properties, EMTA-NLA presents a series of nonlinear models implemented in ABAQUS® via user subroutines for structural analyses. In all these models, it is assumed that the fibers are linear elastic while the matrix material can exhibit a linear or typical nonlinear behavior depending on the loading prescribed to the composite. The key idea is to model the constitutive behavior ofmore » the matrix material and then to use an Eshelby-Mori-Tanaka approach (EMTA) combined with numerical techniques for fiber length and orientation distributions to determine the behavior of the as-formed composite. The basic property prediction models of EMTA and EMTA-NLA have been subject for implementation in the Autodesk® Moldflow® software packages. These models are the elastic stiffness model accounting for fiber length and orientation distributions, the fiber/matrix interface debonding model, and the elastic-plastic models. The PNNL elastic-plastic models for LFTs describes the composite nonlinear stress-strain response up to failure by an elastic-plastic formulation associated with either a micromechanical criterion to predict failure or a continuum damage mechanics formulation coupling damage to plasticity. All the models account for fiber length and orientation distributions as well as fiber/matrix debonding that can occur at any stage of loading. In an effort to transfer the technologies developed under the Predictive Engineering project to the American automotive and plastics industries, PNNL has obtained the approval of the DOE Office of Vehicle Technologies to provide Autodesk, Inc. with the technical support for the implementation of the basic property prediction models of EMTA and EMTA-NLA in the Autodesk® Moldflow® packages. This report summarizes the recent results from Autodesk Simulation Moldlow Insight (ASMI) analyses using the EMTA models and EMTA-NLA/ABAQUS® analyses for further assessment of the EMTA-NLA models to support their implementation in Autodesk Moldflow Structural Alliance (AMSA). PNNL’s technical support to Autodesk, Inc. included (i) providing the theoretical property prediction models as described in published journal articles and reports, (ii) providing explanations of these models and computational procedure, (iii) providing the necessary LFT data for process simulations and property predictions, and (iv) performing ABAQUS/EMTA-NLA analyses to further assess and illustrate the models for selected LFT materials.« less

Modeling and Characterization of a Graphite Nanoplatelet/Epoxy Composite

NASA Technical Reports Server (NTRS)

Odegard, Gregory M.; Chasiotis, I.; Chen, Q.; Gates, T. S.

2004-01-01

A micromechanical modeling procedure is developed to predict the viscoelastic properties of a graphite nanoplatelet/epoxy composite as a function of volume fraction and nanoplatelet diameter. The predicted storage and loss moduli from the model are compared to measured values from the same material using Dynamical Mechanical Analysis, nanoindentation, and tensile tests. In most cases, the model and experiments indicate that for increasing volume fractions of nanoplatelets, both the storage and loss moduli increase. Also, in most cases, the model and experiments indicate that as the nanoplatelet diameter is increased, the storage and loss moduli decrease and increase, respectively.

Modeling of robotic fish propelled by an ionic polymer-metal composite caudal fin

NASA Astrophysics Data System (ADS)

Chen, Zheng; Shatara, Stephan; Tan, Xiaobo

2009-03-01

In this paper, a model is proposed for a biomimetic robotic fish propelled by an ionic polymer metal composite (IPMC) actuator with a rigid passive fin at the end. The model incorporates both IPMC actuation dynamics and the hydrodynamics, and predicts the steady-state speed of the robot under a periodic actuation voltage. Experimental results have shown that the proposed model can predict the fish motion for different tail dimensions. Since its parameters are expressed in terms of physical properties and geometric dimensions, the model is expected to be instrumental in optimal design of the robotic fish.

Unified Viscoplastic Behavior of Metal Matrix Composites

NASA Technical Reports Server (NTRS)

Arnold, S. M.; Robinson, D. N.; Bartolotta, P. A.

1992-01-01

The need for unified constitutive models was recognized more than a decade ago in the results of phenomenological tests on monolithic metals that exhibited strong creep-plasticity interaction. Recently, metallic alloys have been combined to form high-temperature ductile/ductile composite materials, raising the natural question of whether these metallic composites exhibit the same phenomenological features as their monolithic constituents. This question is addressed in the context of a limited, yet definite (to illustrate creep/plasticity interaction) set of experimental data on the model metal matrix composite (MMC) system W/Kanthal. Furthermore, it is demonstrated that a unified viscoplastic representation, extended for unidirectional composites and correlated to W/Kanthal, can accurately predict the observed longitudinal composite creep/plasticity interaction response and strain rate dependency. Finally, the predicted influence of fiber orientation on the creep response of W/Kanthal is illustrated.

An experimental investigation of agglutinate melting mechanisms - Shocked mixtures of sodium and potassium feldspars

NASA Technical Reports Server (NTRS)

Simon, S. B.; Papike, J. J.; Horz, F.; See, T. H.

1985-01-01

The results of an experiment designed to test the validity of the model for agglutinate formation involving fusion of the finest fraction or F3 are reported. Impact glasses were formed from various mixes of orthoclase and albite powders, which were used as analogs for soils with chemically constrasting coarse and fine fractions. The results showed that the single most important factor displacing the composition of a small-scale impact melt from the bulk composition of the source regolith is the fractionated composition of the finest soil fraction. Volatile loss and the amount of melting, which in turn are determined by the degree of shock, are also important. As predicted by the model, the lower pressure melts are the most fractionated, and higher pressure is accompanied by increased melting causing glass compositions to approach the bulk. In general, the systematics predicted by the model are observed; the model appears to be valid.

Damage evolution and mechanical response of cross-ply ceramic composite laminates

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

Weitsman, Y.; Yu, N.; Zhu, H.

1995-12-31

A mechanistic model for the damage evolution and mechanical response of cross-ply ceramic composite laminates under monotonically increasing uniaxial tension is presented. The model accounts for a variety of damage mechanisms evolving in cross-ply ceramic composite laminates, such as fiber-bridged matrix cracks in 0{degrees}-plies, transversely oriented matrix cracks in 90{degrees}-plies, and slips at 0{degrees}/90{degrees} ply interfaces as well as at the fiber/matrix interfaces. Energy criteria are developed to determine the creation and progression of matrix cracks and slip zones. The model predicts that the crack density in 0{degrees}-plies becomes higher than that within the 90{degrees}-plies as the applied load ismore » incrementally increased, which agrees with the experimental observation. It is also shown that the model provides a reasonable prediction for the nonlinear stress-strain behavior of crossply SiC/CAS ceramic composites.« less

[Application of near infrared reflectance spectroscopy to predict meat chemical compositions: a review].

PubMed

Tao, Lin-Li; Yang, Xiu-Juan; Deng, Jun-Ming; Zhang, Xi

2013-11-01

In contrast to conventional methods for the determination of meat chemical composition, near infrared reflectance spectroscopy enables rapid, simple, secure and simultaneous assessment of numerous meat properties. The present review focuses on the use of near infrared reflectance spectroscopy to predict meat chemical compositions. The potential of near infrared reflectance spectroscopy to predict crude protein, intramuscular fat, fatty acid, moisture, ash, myoglobin and collagen of beef, pork, chicken and lamb is reviewed. This paper discusses existing questions and reasons in the current research. According to the published results, although published results vary considerably, they suggest that near-infrared reflectance spectroscopy shows a great potential to replace the expensive and time-consuming chemical analysis of meat composition. In particular, under commercial conditions where simultaneous measurements of different chemical components are required, near infrared reflectance spectroscopy is expected to be the method of choice. The majority of studies selected feature-related wavelengths using principal components regression, developed the calibration model using partial least squares and modified partial least squares, and estimated the prediction accuracy by means of cross-validation using the same sample set previously used for the calibration. Meat fatty acid composition predicted by near-infrared spectroscopy and non-destructive prediction and visualization of chemical composition in meat using near-infrared hyperspectral imaging and multivariate regression are the hot studying field now. On the other hand, near infrared reflectance spectroscopy shows great difference for predicting different attributes of meat quality which are closely related to the selection of calibration sample set, preprocessing of near-infrared spectroscopy and modeling approach. Sample preparation also has an important effect on the reliability of NIR prediction; in particular, lack of homogeneity of the meat samples influenced the accuracy of estimation of chemical components. In general the predicting results of intramuscular fat, fatty acid and moisture are best, the predicting results of crude protein and myoglobin are better, while the predicting results of ash and collagen are less accurate.

Testing the Predictive Capability of the High-Fidelity Generalized Method of Cells Using an Efficient Reformulation

NASA Technical Reports Server (NTRS)

Arnold, Steven M. (Technical Monitor); Bansal, Yogesh; Pindera, Marek-Jerzy

2004-01-01

The High-Fidelity Generalized Method of Cells is a new micromechanics model for unidirectionally reinforced periodic multiphase materials that was developed to overcome the original model's shortcomings. The high-fidelity version predicts the local stress and strain fields with dramatically greater accuracy relative to the original model through the use of a better displacement field representation. Herein, we test the high-fidelity model's predictive capability in estimating the elastic moduli of periodic composites characterized by repeating unit cells obtained by rotation of an infinite square fiber array through an angle about the fiber axis. Such repeating unit cells may contain a few or many fibers, depending on the rotation angle. In order to analyze such multi-inclusion repeating unit cells efficiently, the high-fidelity micromechanics model's framework is reformulated using the local/global stiffness matrix approach. The excellent agreement with the corresponding results obtained from the standard transformation equations confirms the new model's predictive capability for periodic composites characterized by multi-inclusion repeating unit cells lacking planes of material symmetry. Comparison of the effective moduli and local stress fields with the corresponding results obtained from the original Generalized Method of Cells dramatically highlights the original model's shortcomings for certain classes of unidirectional composites.

Experimental Validation of a Thermoelastic Model for SMA Hybrid Composites

NASA Technical Reports Server (NTRS)

Turner, Travis L.

2001-01-01

This study presents results from experimental validation of a recently developed model for predicting the thermomechanical behavior of shape memory alloy hybrid composite (SMAHC) structures, composite structures with an embedded SMA constituent. The model captures the material nonlinearity of the material system with temperature and is capable of modeling constrained, restrained, or free recovery behavior from experimental measurement of fundamental engineering properties. A brief description of the model and analysis procedures is given, followed by an overview of a parallel effort to fabricate and characterize the material system of SMAHC specimens. Static and dynamic experimental configurations for the SMAHC specimens are described and experimental results for thermal post-buckling and random response are presented. Excellent agreement is achieved between the measured and predicted results, fully validating the theoretical model for constrained recovery behavior of SMAHC structures.

Analysis of linear elasticity and non-linearity due to plasticity and material damage in woven and biaxial braided composites

NASA Astrophysics Data System (ADS)

Goyal, Deepak

Textile composites have a wide variety of applications in the aerospace, sports, automobile, marine and medical industries. Due to the availability of a variety of textile architectures and numerous parameters associated with each, optimal design through extensive experimental testing is not practical. Predictive tools are needed to perform virtual experiments of various options. The focus of this research is to develop a better understanding of linear elastic response, plasticity and material damage induced nonlinear behavior and mechanics of load flow in textile composites. Textile composites exhibit multiple scales of complexity. The various textile behaviors are analyzed using a two-scale finite element modeling. A framework to allow use of a wide variety of damage initiation and growth models is proposed. Plasticity induced non-linear behavior of 2x2 braided composites is investigated using a modeling approach based on Hill's yield function for orthotropic materials. The mechanics of load flow in textile composites is demonstrated using special non-standard postprocessing techniques that not only highlight the important details, but also transform the extensive amount of output data into comprehensible modes of behavior. The investigations show that the damage models differ from each other in terms of amount of degradation as well as the properties to be degraded under a particular failure mode. When compared with experimental data, predictions of some models match well for glass/epoxy composite whereas other's match well for carbon/epoxy composites. However, all the models predicted very similar response when damage factors were made similar, which shows that the magnitude of damage factors are very important. Full 3D as well as equivalent tape laminate predictions lie within the range of the experimental data for a wide variety of braided composites with different material systems, which validated the plasticity analysis. Conclusions about the effect of fiber type on the degree of plasticity induced non-linearity in a +/-25° braid depend on the measure of non-linearity. Investigations about the mechanics of load flow in textile composites bring new insights about the textile behavior. For example, the reasons for existence of transverse shear stress under uni-axial loading and occurrence of stress concentrations at certain locations were explained.

Verification and Validation of a Three-Dimensional Generalized Composite Material Model

NASA Technical Reports Server (NTRS)

Hoffarth, Canio; Harrington, Joseph; Subramaniam, D. Rajan; Goldberg, Robert K.; Carney, Kelly S.; DuBois, Paul; Blankenhorn, Gunther

2014-01-01

A general purpose orthotropic elasto-plastic computational constitutive material model has been developed to improve predictions of the response of composites subjected to high velocity impact. The three-dimensional orthotropic elasto-plastic composite material model is being implemented initially for solid elements in LS-DYNA as MAT213. In order to accurately represent the response of a composite, experimental stress-strain curves are utilized as input, allowing for a more general material model that can be used on a variety of composite applications. The theoretical details are discussed in a companion paper. This paper documents the implementation, verification and qualitative validation of the material model using the T800- F3900 fiber/resin composite material.

Verification and Validation of a Three-Dimensional Generalized Composite Material Model

NASA Technical Reports Server (NTRS)

Hoffarth, Canio; Harrington, Joseph; Rajan, Subramaniam D.; Goldberg, Robert K.; Carney, Kelly S.; DuBois, Paul; Blankenhorn, Gunther

2015-01-01

A general purpose orthotropic elasto-plastic computational constitutive material model has been developed to improve predictions of the response of composites subjected to high velocity impact. The three-dimensional orthotropic elasto-plastic composite material model is being implemented initially for solid elements in LS-DYNA as MAT213. In order to accurately represent the response of a composite, experimental stress-strain curves are utilized as input, allowing for a more general material model that can be used on a variety of composite applications. The theoretical details are discussed in a companion paper. This paper documents the implementation, verification and qualitative validation of the material model using the T800-F3900 fiber/resin composite material

Impact damage of composite plates

NASA Technical Reports Server (NTRS)

Lal, K. M.; Goglia, G. L.

1983-01-01

A simple model to study low velocity transverse impact of thin plates made of fiber-reinforced composite material, in particular T300/5208 graphite-epoxy was discussed. This model predicts the coefficient of restitution, which is a measure of the energy absorbed by the target during an impact event. The model is constructed on the assumption that the plate is inextensible in the fiber direction and that the material is incompressible in the z-direction. Such a plate essentially deforms by shear, hence this model neglects bending deformations of the plate. The coefficient of restitution is predicted to increase with large interlaminar shear strength and low transverse shear modulus of the laminate. Predictions are compared with the test results of impacted circular and rectangular clamped plates. Experimentally measured values of the coefficient of restitution are found to agree with the predicted values within a reasonable error.

Composite fermion theory for bosonic quantum Hall states on lattices.

PubMed

Möller, G; Cooper, N R

2009-09-04

We study the ground states of the Bose-Hubbard model in a uniform magnetic field, motivated by the physics of cold atomic gases on lattices at high vortex density. Mapping the bosons to composite fermions (CF) leads to the prediction of quantum Hall fluids that have no counterpart in the continuum. We construct trial states for these phases and test numerically the predictions of the CF model. We establish the existence of strongly correlated phases beyond those in the continuum limit and provide evidence for a wider scope of the composite fermion approach beyond its application to the lowest Landau level.

Evaluation of Material Models within LS-DYNA(Registered TradeMark) for a Kevlar/Epoxy Composite Honeycomb

NASA Technical Reports Server (NTRS)

Polanco, Michael A.; Kellas, Sotiris; Jackson, Karen

2009-01-01

The performance of material models to simulate a novel composite honeycomb Deployable Energy Absorber (DEA) was evaluated using the nonlinear explicit dynamic finite element code LS-DYNA(Registered TradeMark). Prototypes of the DEA concept were manufactured using a Kevlar/Epoxy composite material in which the fibers are oriented at +/-45 degrees with respect to the loading axis. The development of the DEA has included laboratory tests at subcomponent and component levels such as three-point bend testing of single hexagonal cells, dynamic crush testing of single multi-cell components, and impact testing of a full-scale fuselage section fitted with a system of DEA components onto multi-terrain environments. Due to the thin nature of the cell walls, the DEA was modeled using shell elements. In an attempt to simulate the dynamic response of the DEA, it was first represented using *MAT_LAMINATED_COMPOSITE_FABRIC, or *MAT_58, in LS-DYNA. Values for each parameter within the material model were generated such that an in-plane isotropic configuration for the DEA material was assumed. Analytical predictions showed that the load-deflection behavior of a single-cell during three-point bending was within the range of test data, but predicted the DEA crush response to be very stiff. In addition, a *MAT_PIECEWISE_LINEAR_PLASTICITY, or *MAT_24, material model in LS-DYNA was developed, which represented the Kevlar/Epoxy composite as an isotropic elastic-plastic material with input from +/-45 degrees tensile coupon data. The predicted crush response matched that of the test and localized folding patterns of the DEA were captured under compression, but the model failed to predict the single-cell three-point bending response.

Evaluation of a Progressive Failure Analysis Methodology for Laminated Composite Structures

NASA Technical Reports Server (NTRS)

Sleight, David W.; Knight, Norman F., Jr.; Wang, John T.

1997-01-01

A progressive failure analysis methodology has been developed for predicting the nonlinear response and failure of laminated composite structures. The progressive failure analysis uses C plate and shell elements based on classical lamination theory to calculate the in-plane stresses. Several failure criteria, including the maximum strain criterion, Hashin's criterion, and Christensen's criterion, are used to predict the failure mechanisms. The progressive failure analysis model is implemented into a general purpose finite element code and can predict the damage and response of laminated composite structures from initial loading to final failure.

TiC growth in C fiber/Ti alloy composites during liquid infiltration

NASA Technical Reports Server (NTRS)

Warrier, S. G.; Lin, R. Y.

1993-01-01

A cylindrical model is developed for predicting the reaction zone thickness of carbon fiber-reinforced Ti-matrix composites, and good agreement is obtained between its predicted values and experimental results. The reaction-rate constant for TiC formation is estimated to be 1.5 x 10 exp -9 sq cm/sec. The model is extended to evaluate the relationship between C-coating thicknesses on SiC fibers and processing times.

Simple Elasticity Modeling and Failure Prediction for Composite Flexbeams

NASA Technical Reports Server (NTRS)

Makeev, Andrew; Armanios, Erian; OBrien, T. Kevin (Technical Monitor)

2001-01-01

A simple 2D boundary element analysis, suitable for developing cost effective models for tapered composite laminates, is presented. Constant stress and displacement elements are used. Closed-form fundamental solutions are derived. Numerical results are provided for several configurations to illustrate the accuracy of the model.

Multiscale Fatigue Life Prediction for Composite Panels

NASA Technical Reports Server (NTRS)

Bednarcyk, Brett A.; Yarrington, Phillip W.; Arnold, Steven M.

2012-01-01

Fatigue life prediction capabilities have been incorporated into the HyperSizer Composite Analysis and Structural Sizing Software. The fatigue damage model is introduced at the fiber/matrix constituent scale through HyperSizer s coupling with NASA s MAC/GMC micromechanics software. This enables prediction of the micro scale damage progression throughout stiffened and sandwich panels as a function of cycles leading ultimately to simulated panel failure. The fatigue model implementation uses a cycle jumping technique such that, rather than applying a specified number of additional cycles, a specified local damage increment is specified and the number of additional cycles to reach this damage increment is calculated. In this way, the effect of stress redistribution due to damage-induced stiffness change is captured, but the fatigue simulations remain computationally efficient. The model is compared to experimental fatigue life data for two composite facesheet/foam core sandwich panels, demonstrating very good agreement.

Predicting the chromatographic retention of polymers: application of the polymer model to poly(styrene/ethylacrylate)copolymers.

PubMed

Bashir, Mubasher A; Radke, Wolfgang

2012-02-17

The retention behavior of a range of statistical poly(styrene/ethylacrylate) copolymers is investigated, in order to determine the possibility to predict retention volumes of these copolymers based on a suitable chromatographic retention model. It was found that the composition of elution in gradient chromatography of the copolymers is closely related to the eluent composition at which, in isocratic chromatography, the transition from elution in adsorption to exclusion mode occurs. For homopolymers this transition takes place at a critical eluent composition at which the molar mass dependence of elution volume vanishes. Thus, similar critical eluent compositions can be defined for statistical copolymers. The existence of a critical eluent composition is further supported by the narrower peak width, indicating that the broad molar mass distribution of the samples does not contribute to the retention volume. It is shown that the existing retention model for homopolymers allows for correct quantitative predictions of retention volumes based on only three appropriate initial experiments. The selection of these initial experiments involves a gradient run and two isocratic experiments, one at the composition of elution calculated from first gradient run and second at a slightly higher eluent strength. Copyright © 2011 Elsevier B.V. All rights reserved.

Iron and nickel isotope compositions of presolar silicon carbide grains from supernovae

NASA Astrophysics Data System (ADS)

Kodolányi, János; Stephan, Thomas; Trappitsch, Reto; Hoppe, Peter; Pignatari, Marco; Davis, Andrew M.; Pellin, Michael J.

2018-01-01

We report the carbon, silicon, iron, and nickel isotope compositions of twenty-five presolar SiC grains of mostly supernova (SN) origin. The iron and nickel isotope compositions were measured with the new Chicago Instrument for Laser Ionization, CHILI, which allows the analysis of all iron and nickel isotopes without the isobaric interferences that plagued previous measurements with the NanoSIMS. Despite terrestrial iron and nickel contamination, significant isotopic anomalies in 54Fe/56Fe, 57Fe/56Fe, 60Ni/58Ni, 61Ni/58Ni, 62Ni/58Ni, and 64Ni/58Ni were detected in nine SN grains (of type X). Combined multi-isotope data of three grains with the largest nickel isotope anomalies (>100‰ or <-100‰ in at least one isotope ratio, when expressed as deviation from the solar value) are compared with the predictions of two SN models, one with and one without hydrogen ingestion in the He shell prior to SN explosion. One grain's carbon-silicon-iron-nickel isotope composition is consistent with the prediction of the model without hydrogen ingestion, whereas the other two grains' isotope anomalies could not be reproduced using either SN models. The discrepancies between the measured isotope compositions and model predictions may indicate element fractionation in the SN ejecta prior to or during grain condensation, and reiterate the need for three-dimensional SN models.

Empirically Based Composite Fracture Prediction Model From the Global Longitudinal Study of Osteoporosis in Postmenopausal Women (GLOW)

PubMed Central

Compston, Juliet E.; Chapurlat, Roland D.; Pfeilschifter, Johannes; Cooper, Cyrus; Hosmer, David W.; Adachi, Jonathan D.; Anderson, Frederick A.; Díez-Pérez, Adolfo; Greenspan, Susan L.; Netelenbos, J. Coen; Nieves, Jeri W.; Rossini, Maurizio; Watts, Nelson B.; Hooven, Frederick H.; LaCroix, Andrea Z.; March, Lyn; Roux, Christian; Saag, Kenneth G.; Siris, Ethel S.; Silverman, Stuart; Gehlbach, Stephen H.

2014-01-01

Context: Several fracture prediction models that combine fractures at different sites into a composite outcome are in current use. However, to the extent individual fracture sites have differing risk factor profiles, model discrimination is impaired. Objective: The objective of the study was to improve model discrimination by developing a 5-year composite fracture prediction model for fracture sites that display similar risk profiles. Design: This was a prospective, observational cohort study. Setting: The study was conducted at primary care practices in 10 countries. Patients: Women aged 55 years or older participated in the study. Intervention: Self-administered questionnaires collected data on patient characteristics, fracture risk factors, and previous fractures. Main Outcome Measure: The main outcome is time to first clinical fracture of hip, pelvis, upper leg, clavicle, or spine, each of which exhibits a strong association with advanced age. Results: Of four composite fracture models considered, model discrimination (c index) is highest for an age-related fracture model (c index of 0.75, 47 066 women), and lowest for Fracture Risk Assessment Tool (FRAX) major fracture and a 10-site model (c indices of 0.67 and 0.65). The unadjusted increase in fracture risk for an additional 10 years of age ranges from 80% to 180% for the individual bones in the age-associated model. Five other fracture sites not considered for the age-associated model (upper arm/shoulder, rib, wrist, lower leg, and ankle) have age associations for an additional 10 years of age from a 10% decrease to a 60% increase. Conclusions: After examining results for 10 different bone fracture sites, advanced age appeared the single best possibility for uniting several different sites, resulting in an empirically based composite fracture risk model. PMID:24423345

Shape control of NITINOL-reinforced composite beams

NASA Astrophysics Data System (ADS)

Baz, Amr M.; Chen, Tung-Huei; Ro, Jeng-Jong

1994-05-01

The shape of composite beams is controlled by sets of flat strips of a shape memory nickel-titanium alloy (NITINOL). A mathematical model is developed to describe the behavior of this class of SMART composites. The model describes the interaction between the elastic characteristics of the composite beams and the thermally- induced shape memory effect of the NITINOL strips. The effect of various activation strategies of the NITINOL strips on the shape of the composite beams is determined. The theoretical predictions of the model are validated experimentally using a fiberglass composite beam made of 8 plies of unidirectional BASF 5216 prepregs which are 9.75-cm wide and 21.20 cm long. The beams are provided with four NITINOL-55 strips which are 1.2 mm thick and 1.25 cm wide. The time response characteristics of the beam are monitored and compared with the corresponding theoretical characteristics. Close agreement is obtained between the theoretical predictions and the experimental results. The obtained results suggest the potential of the NITINOL strips in controlling the shape of composite beams without compromising their structural stiffness.

Validation of the Registry to Evaluate Early and Long-Term Pulmonary Arterial Hypertension Disease Management (REVEAL) pulmonary hypertension prediction model in a unique population and utility in the prediction of long-term survival.

PubMed

Cogswell, Rebecca; Kobashigawa, Erin; McGlothlin, Dana; Shaw, Robin; De Marco, Teresa

2012-11-01

The Registry to Evaluate Early and Long-Term Pulmonary Arterial (PAH) Hypertension Disease Management (REVEAL) model was designed to predict 1-year survival in patients with PAH. Multivariate prediction models need to be evaluated in cohorts distinct from the derivation set to determine external validity. In addition, limited data exist on the utility of this model in the prediction of long-term survival. REVEAL model performance was assessed to predict 1-year and 5-year outcomes, defined as survival or composite survival or freedom from lung transplant, in 140 patients with PAH. The validation cohort had a higher proportion of human immunodeficiency virus (7.9% vs 1.9%, p < 0.0001), methamphetamine use (19.3% vs 4.9%, p < 0.0001), and portal hypertension PAH (16.4% vs 5.1%, p < 0.0001) compared with the development cohort. The C-index of the model to predict survival was 0.765 at 1 year and 0.712 at 5 years of follow-up. The C-index of the model to predict composite survival or freedom from lung transplant was 0.805 and 0.724 at 1 and 5 years of follow-up, respectively. Prediction by the model, however, was weakest among patients with intermediate-risk predicted survival. The REVEAL model had adequate discrimination to predict 1-year survival in this small but clinically distinct validation cohort. Although the model also had predictive ability out to 5 years, prediction was limited among patients of intermediate risk, suggesting our prediction methods can still be improved. Copyright © 2012. Published by Elsevier Inc.

Numerical Modeling, Thermomechanical Testing, and NDE Procedures for Prediction of Microcracking Induced Permeability of Cryogenic Composites

NASA Technical Reports Server (NTRS)

Noh, Jae; Whitcomb, John; Oh, Bongtaek; Lagoudas, Dimitris; Maslov, Konstatin; Ganpatyre, Atul; Kinra, Vikram

2003-01-01

Reusable Space Vehicles will include light cryogenic composite fuel tanks that must not leak excessively even after multiple launches. Damage in cryogenic composite fuel tanks induced during manufacturing and advanced by thermomechanical cycling can accelerate leakage of the propellant. Whether the leakage exceeds tolerable levels depends on many factors, including pressure gradients, microcrack density, other damage such as delamination, connectivity of the cracks, residual stresses from manufacture, service-induced stresses from thermal and mechanical loads, and composite lay-up. Although it is critical to experimentally characterize permeability during various thermal and mechanical load histories, optimal design depends on having analytical models that can predict the effect of various parameters on performance. Our broad goal is to develop such models that are experimentally validated by destructive and non-destructive evaluation means.

Multi-physics modeling of multifunctional composite materials for damage detection

NASA Astrophysics Data System (ADS)

Sujidkul, Thanyawalai

This study presents a modeling of multifunction composite materials for damage detection with its verification and validation to mechanical behavior predictions of Carbon Fibre Reinforced Polymer composites (CFRPs), CFRPs laminated composites, and woven SiC/SiC matrix composites that are subjected to fracture damage. Advantages of those materials are low cost, low density, high strength-to-weight ratio, and comparable specific tensile properties, the special of SiC/SiC is good environmental stability at high temperature. Resulting in, the composite has been used for many important structures such as helicopter rotors, aerojet engines, gas turbines, hot control surfaces, sporting goods, and windmill blades. Damage or material defect detection in a mechanical component can provide vital information for the prediction of remaining useful life, which will result in the prevention of catastrophic failures. Thus the understanding of the mechanical behavior have been challenge to the prevent damage and failure of composites in different scales. The damage detection methods in composites have been investigated widely in recent years. Non-destructive techniques are the traditional methods to detect the damage such as X-ray, acoustic emission and thermography. However, due to the invisible damage in composite can be occurred, to prevent the failure in composites. The developments of damage detection methods have been considered. Due to carbon fibers are conductive materials, in resulting CFRPs can be self-sensing to detect damage. As is well known, the electrical resistance has been shown to be a sensitive measure of internal damage, and also this work study in thermal resistance can detect damage in composites. However, there is a few number of different micromechanical modeling schemes has been proposed in the published literature for various types of composites. This works will provide with a numerical, analytical, and theoretical failure models in different damages to predict the mechanical damage behavior with electrical properties and thermal properties.

Methods of Predicting Solid Waste Characteristics.

ERIC Educational Resources Information Center

Boyd, Gail B.; Hawkins, Myron B.

The project summarized by this report involved a preliminary design of a model for estimating and predicting the quantity and composition of solid waste and a determination of its feasibility. The novelty of the prediction model is that it estimates and predicts on the basis of knowledge of materials and quantities before they become a part of the…

Fatigue Life Prediction of 2D Woven Ceramic-Matrix Composites at Room and Elevated Temperatures

NASA Astrophysics Data System (ADS)

Longbiao, Li

2017-03-01

In this paper, the fatigue life of 2D woven ceramic-matrix composites, i.e., SiC/SiC, SiC/Si-N-C, SiC/Si-B4C, and Nextel 610™/Aluminosilicate, at room and elevated temperatures has been predicted using the micromechanics approach. An effective coefficient of the fiber volume fraction along the loading direction (ECFL) was introduced to describe the fiber architecture of preforms. The Budiansky-Hutchinson-Evans shear-lag model was used to describe the microstress field of the damaged composite considering fibers failure. The statistical matrix multicracking model and fracture mechanics interface debonding criterion were used to determine the matrix crack spacing and interface debonded length. The interface shear stress and fibers strength degradation model and oxidation region propagation model have been adopted to analyze the fatigue and oxidation effects on fatigue life of the composite, which is controlled by interface frictional slip and diffusion of oxygen gas through matrix multicrackings. Under cyclic fatigue loading, the fibers broken fraction was determined by combining the interface/fiber oxidation model, interface wear model and fibers statistical failure model at elevated temperatures, based on the assumption that the fiber strength is subjected to two-parameter Weibull distribution and the load carried by broken and intact fibers satisfy the Global Load Sharing (GLS) criterion. When the broken fibers fraction approaches to the critical value, the composites fatigue fractures. The fatigue life S- N curves of 2D SiC/SiC, SiC/Si-N-C, SiC/Si-B4C, and Nextel 610™/Aluminosilicate composites at room temperature and 800, 1000 and 1200 °C in air and steam have been predicted.

Predicting Plywood Properties with Wood-based Composite Models

Treesearch

Christopher Adam Senalik; Robert J. Ross

2015-01-01

Previous research revealed that stress wave nondestructive testing techniques could be used to evaluate the tensile and flexural properties of wood-based composite materials. Regression models were developed that related stress wave transmission characteristics (velocity and attenuation) to modulus of elasticity and strength. The developed regression models accounted...

Pyrolysis Model Development for a Multilayer Floor Covering

PubMed Central

McKinnon, Mark B.; Stoliarov, Stanislav I.

2015-01-01

Comprehensive pyrolysis models that are integral to computational fire codes have improved significantly over the past decade as the demand for improved predictive capabilities has increased. High fidelity pyrolysis models may improve the design of engineered materials for better fire response, the design of the built environment, and may be used in forensic investigations of fire events. A major limitation to widespread use of comprehensive pyrolysis models is the large number of parameters required to fully define a material and the lack of effective methodologies for measurement of these parameters, especially for complex materials. The work presented here details a methodology used to characterize the pyrolysis of a low-pile carpet tile, an engineered composite material that is common in commercial and institutional occupancies. The studied material includes three distinct layers of varying composition and physical structure. The methodology utilized a comprehensive pyrolysis model (ThermaKin) to conduct inverse analyses on data collected through several experimental techniques. Each layer of the composite was individually parameterized to identify its contribution to the overall response of the composite. The set of properties measured to define the carpet composite were validated against mass loss rate curves collected at conditions outside the range of calibration conditions to demonstrate the predictive capabilities of the model. The mean error between the predicted curve and the mean experimental mass loss rate curve was calculated as approximately 20% on average for heat fluxes ranging from 30 to 70 kW·m−2, which is within the mean experimental uncertainty. PMID:28793556

Nonlinear analysis of AS4/PEEK thermoplastic composite laminate using a one parameter plasticity model

NASA Technical Reports Server (NTRS)

Sun, C. T.; Yoon, K. J.

1990-01-01

A one-parameter plasticity model was shown to adequately describe the orthotropic plastic deformation of AS4/PEEK (APC-2) unidirectional thermoplastic composite. This model was verified further for unidirectional and laminated composite panels with and without a hole. The nonlinear stress-strain relations were measured and compared with those predicted by the finite element analysis using the one-parameter elastic-plastic constitutive model. The results show that the one-parameter orthotropic plasticity model is suitable for the analysis of elastic-plastic deformation of AS4/PEEK composite laminates.

Elastic-plastic analysis of AS4/PEEK composite laminate using a one-parameter plasticity model

NASA Technical Reports Server (NTRS)

Sun, C. T.; Yoon, K. J.

1992-01-01

A one-parameter plasticity model was shown to adequately describe the plastic deformation of AS4/PEEK (APC-2) unidirectional thermoplastic composite. This model was verified further for unidirectional and laminated composite panels with and without a hole. The elastic-plastic stress-strain relations of coupon specimens were measured and compared with those predicted by the finite element analysis using the one-parameter plasticity model. The results show that the one-parameter plasticity model is suitable for the analysis of elastic-plastic deformation of AS4/PEEK composite laminates.

A micromechanics-based strength prediction methodology for notched metal matrix composites

NASA Technical Reports Server (NTRS)

Bigelow, C. A.

1992-01-01

An analytical micromechanics based strength prediction methodology was developed to predict failure of notched metal matrix composites. The stress-strain behavior and notched strength of two metal matrix composites, boron/aluminum (B/Al) and silicon-carbide/titanium (SCS-6/Ti-15-3), were predicted. The prediction methodology combines analytical techniques ranging from a three dimensional finite element analysis of a notched specimen to a micromechanical model of a single fiber. In the B/Al laminates, a fiber failure criteria based on the axial and shear stress in the fiber accurately predicted laminate failure for a variety of layups and notch-length to specimen-width ratios with both circular holes and sharp notches when matrix plasticity was included in the analysis. For the SCS-6/Ti-15-3 laminates, a fiber failure based on the axial stress in the fiber correlated well with experimental results for static and post fatigue residual strengths when fiber matrix debonding and matrix cracking were included in the analysis. The micromechanics based strength prediction methodology offers a direct approach to strength prediction by modeling behavior and damage on a constituent level, thus, explicitly including matrix nonlinearity, fiber matrix debonding, and matrix cracking.

A micromechanics-based strength prediction methodology for notched metal-matrix composites

NASA Technical Reports Server (NTRS)

Bigelow, C. A.

1993-01-01

An analytical micromechanics-based strength prediction methodology was developed to predict failure of notched metal matrix composites. The stress-strain behavior and notched strength of two metal matrix composites, boron/aluminum (B/Al) and silicon-carbide/titanium (SCS-6/Ti-15-3), were predicted. The prediction methodology combines analytical techniques ranging from a three-dimensional finite element analysis of a notched specimen to a micromechanical model of a single fiber. In the B/Al laminates, a fiber failure criteria based on the axial and shear stress in the fiber accurately predicted laminate failure for a variety of layups and notch-length to specimen-width ratios with both circular holes and sharp notches when matrix plasticity was included in the analysis. For the SCS-6/Ti-15-3 laminates, a fiber failure based on the axial stress in the fiber correlated well with experimental results for static and postfatigue residual strengths when fiber matrix debonding and matrix cracking were included in the analysis. The micromechanics-based strength prediction methodology offers a direct approach to strength prediction by modeling behavior and damage on a constituent level, thus, explicitly including matrix nonlinearity, fiber matrix debonding, and matrix cracking.

Outgassing and dimensional changes of polymer matrix composites in space

NASA Technical Reports Server (NTRS)

Tennyson, R. C.; Matthews, R.

1993-01-01

A thermal-vacuum outgassing model and test protocol for predicting outgassing times and dimensional changes for polymer matrix composites is described. Experimental results derived from a 'control' sample are used to provide the basis for analytical predictions to compare with the outgassing response of Long Duration Exposure Facility (LDEF) flight samples.

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

Treesearch

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

2014-01-01

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

Prediction of long-term transverse creep compliance in high-temperature IM7/LaRC-RP46 composites

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

Yuan, F.G.; Potter, B.D.

1994-12-31

An experimental study is performed which predicts long-term tensile transverse creep compliance of high-temperature IM7/LaRC-RP46 composites from short-term creep and recovery tests. The short-term tests were conducted for various stress levels at various fixed temperatures. Predictive nonlinear viscoelastic model developed by Schapery and experimental procedure were used to predict the long-term results in terms of master curve extrapolated from short-term tests.

Prediction protein structural classes with pseudo-amino acid composition: approximate entropy and hydrophobicity pattern.

PubMed

Zhang, Tong-Liang; Ding, Yong-Sheng; Chou, Kuo-Chen

2008-01-07

Compared with the conventional amino acid (AA) composition, the pseudo-amino acid (PseAA) composition as originally introduced for protein subcellular location prediction can incorporate much more information of a protein sequence, so as to remarkably enhance the power of using a discrete model to predict various attributes of a protein. In this study, based on the concept of PseAA composition, the approximate entropy and hydrophobicity pattern of a protein sequence are used to characterize the PseAA components. Also, the immune genetic algorithm (IGA) is applied to search the optimal weight factors in generating the PseAA composition. Thus, for a given protein sequence sample, a 27-D (dimensional) PseAA composition is generated as its descriptor. The fuzzy K nearest neighbors (FKNN) classifier is adopted as the prediction engine. The results thus obtained in predicting protein structural classification are quite encouraging, indicating that the current approach may also be used to improve the prediction quality of other protein attributes, or at least can play a complimentary role to the existing methods in the relevant areas. Our algorithm is written in Matlab that is available by contacting the corresponding author.

The validation of a human force model to predict dynamic forces resulting from multi-joint motions

NASA Technical Reports Server (NTRS)

Pandya, Abhilash K.; Maida, James C.; Aldridge, Ann M.; Hasson, Scott M.; Woolford, Barbara J.

1992-01-01

The development and validation is examined of a dynamic strength model for humans. This model is based on empirical data. The shoulder, elbow, and wrist joints were characterized in terms of maximum isolated torque, or position and velocity, in all rotational planes. This data was reduced by a least squares regression technique into a table of single variable second degree polynomial equations determining torque as a function of position and velocity. The isolated joint torque equations were then used to compute forces resulting from a composite motion, in this case, a ratchet wrench push and pull operation. A comparison of the predicted results of the model with the actual measured values for the composite motion indicates that forces derived from a composite motion of joints (ratcheting) can be predicted from isolated joint measures. Calculated T values comparing model versus measured values for 14 subjects were well within the statistically acceptable limits and regression analysis revealed coefficient of variation between actual and measured to be within 0.72 and 0.80.

Reliability prediction of ontology-based service compositions using Petri net and time series models.

PubMed

Li, Jia; Xia, Yunni; Luo, Xin

2014-01-01

OWL-S, one of the most important Semantic Web service ontologies proposed to date, provides a core ontological framework and guidelines for describing the properties and capabilities of their web services in an unambiguous, computer interpretable form. Predicting the reliability of composite service processes specified in OWL-S allows service users to decide whether the process meets the quantitative quality requirement. In this study, we consider the runtime quality of services to be fluctuating and introduce a dynamic framework to predict the runtime reliability of services specified in OWL-S, employing the Non-Markovian stochastic Petri net (NMSPN) and the time series model. The framework includes the following steps: obtaining the historical response times series of individual service components; fitting these series with a autoregressive-moving-average-model (ARMA for short) and predicting the future firing rates of service components; mapping the OWL-S process into a NMSPN model; employing the predicted firing rates as the model input of NMSPN and calculating the normal completion probability as the reliability estimate. In the case study, a comparison between the static model and our approach based on experimental data is presented and it is shown that our approach achieves higher prediction accuracy.

Predicting invertebrate assemblage composition from harvesting pressure and environmental characteristics on tropical reef flats

NASA Astrophysics Data System (ADS)

Jimenez, H.; Dumas, P.; Ponton, D.; Ferraris, J.

2012-03-01

Invertebrates represent an essential component of coral reef ecosystems; they are ecologically important and a major resource, but their assemblages remain largely unknown, particularly on Pacific islands. Understanding their distribution and building predictive models of community composition as a function of environmental variables therefore constitutes a key issue for resource management. The goal of this study was to define and classify the main environmental factors influencing tropical invertebrate distributions in New Caledonian reef flats and to test the resulting predictive model. Invertebrate assemblages were sampled by visual counting during 2 years and 2 seasons, then coupled to different environmental conditions (habitat composition, hydrodynamics and sediment characteristics) and harvesting status (MPA vs. non-MPA and islets vs. coastal flats). Environmental conditions were described by a principal component analysis (PCA), and contributing variables were selected. Permutational analysis of variance (PERMANOVA) was used to test the effects of different factors (status, flat, year and season) on the invertebrate assemblage composition. Multivariate regression trees (MRT) were then used to hierarchically classify the effects of environmental and harvesting variables. MRT model explained at least 60% of the variation in structure of invertebrate communities. Results highlighted the influence of status (MPA vs. non-MPA) and location (islet vs. coastal flat), followed by habitat composition, organic matter content, hydrodynamics and sampling year. Predicted assemblages defined by indicator families were very different for each environment-exploitation scenario and correctly matched a calibration data matrix. Predictions from MRT including both environmental variables and harvesting pressure can be useful for management of invertebrates in coral reef environments.

Relationship between body composition and postural control in prepubertal overweight/obese children: A cross-sectional study.

PubMed

Villarrasa-Sapiña, Israel; Álvarez-Pitti, Julio; Cabeza-Ruiz, Ruth; Redón, Pau; Lurbe, Empar; García-Massó, Xavier

2018-02-01

Excess body weight during childhood causes reduced motor functionality and problems in postural control, a negative influence which has been reported in the literature. Nevertheless, no information regarding the effect of body composition on the postural control of overweight and obese children is available. The objective of this study was therefore to establish these relationships. A cross-sectional design was used to establish relationships between body composition and postural control variables obtained in bipedal eyes-open and eyes-closed conditions in twenty-two children. Centre of pressure signals were analysed in the temporal and frequency domains. Pearson correlations were applied to establish relationships between variables. Principal component analysis was applied to the body composition variables to avoid potential multicollinearity in the regression models. These principal components were used to perform a multiple linear regression analysis, from which regression models were obtained to predict postural control. Height and leg mass were the body composition variables that showed the highest correlation with postural control. Multiple regression models were also obtained and several of these models showed a higher correlation coefficient in predicting postural control than simple correlations. These models revealed that leg and trunk mass were good predictors of postural control. More equations were found in the eyes-open than eyes-closed condition. Body weight and height are negatively correlated with postural control. However, leg and trunk mass are better postural control predictors than arm or body mass. Finally, body composition variables are more useful in predicting postural control when the eyes are open. Copyright © 2017 Elsevier Ltd. All rights reserved.

A Large-scale Finite Element Model on Micromechanical Damage and Failure of Carbon Fiber/Epoxy Composites Including Thermal Residual Stress

NASA Astrophysics Data System (ADS)

Liu, P. F.; Li, X. K.

2018-06-01

The purpose of this paper is to study micromechanical progressive failure properties of carbon fiber/epoxy composites with thermal residual stress by finite element analysis (FEA). Composite microstructures with hexagonal fiber distribution are used for the representative volume element (RVE), where an initial fiber breakage is assumed. Fiber breakage with random fiber strength is predicted using Monte Carlo simulation, progressive matrix damage is predicted by proposing a continuum damage mechanics model and interface failure is simulated using Xu and Needleman's cohesive model. Temperature dependent thermal expansion coefficients for epoxy matrix are used. FEA by developing numerical codes using ANSYS finite element software is divided into two steps: 1. Thermal residual stresses due to mismatch between fiber and matrix are calculated; 2. Longitudinal tensile load is further exerted on the RVE to perform progressive failure analysis of carbon fiber/epoxy composites. Numerical convergence is solved by introducing the viscous damping effect properly. The extended Mori-Tanaka method that considers interface debonding is used to get homogenized mechanical responses of composites. Three main results by FEA are obtained: 1. the real-time matrix cracking, fiber breakage and interface debonding with increasing tensile strain is simulated. 2. the stress concentration coefficients on neighbouring fibers near the initial broken fiber and the axial fiber stress distribution along the broken fiber are predicted, compared with the results using the global and local load-sharing models based on the shear-lag theory. 3. the tensile strength of composite by FEA is compared with those by the shear-lag theory and experiments. Finally, the tensile stress-strain curve of composites by FEA is applied to the progressive failure analysis of composite pressure vessel.

A Large-scale Finite Element Model on Micromechanical Damage and Failure of Carbon Fiber/Epoxy Composites Including Thermal Residual Stress

NASA Astrophysics Data System (ADS)

Liu, P. F.; Li, X. K.

2017-09-01

The purpose of this paper is to study micromechanical progressive failure properties of carbon fiber/epoxy composites with thermal residual stress by finite element analysis (FEA). Composite microstructures with hexagonal fiber distribution are used for the representative volume element (RVE), where an initial fiber breakage is assumed. Fiber breakage with random fiber strength is predicted using Monte Carlo simulation, progressive matrix damage is predicted by proposing a continuum damage mechanics model and interface failure is simulated using Xu and Needleman's cohesive model. Temperature dependent thermal expansion coefficients for epoxy matrix are used. FEA by developing numerical codes using ANSYS finite element software is divided into two steps: 1. Thermal residual stresses due to mismatch between fiber and matrix are calculated; 2. Longitudinal tensile load is further exerted on the RVE to perform progressive failure analysis of carbon fiber/epoxy composites. Numerical convergence is solved by introducing the viscous damping effect properly. The extended Mori-Tanaka method that considers interface debonding is used to get homogenized mechanical responses of composites. Three main results by FEA are obtained: 1. the real-time matrix cracking, fiber breakage and interface debonding with increasing tensile strain is simulated. 2. the stress concentration coefficients on neighbouring fibers near the initial broken fiber and the axial fiber stress distribution along the broken fiber are predicted, compared with the results using the global and local load-sharing models based on the shear-lag theory. 3. the tensile strength of composite by FEA is compared with those by the shear-lag theory and experiments. Finally, the tensile stress-strain curve of composites by FEA is applied to the progressive failure analysis of composite pressure vessel.

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

PubMed

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

2016-03-01

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

A new fracture mechanics model for multiple matrix cracks of SiC fiber reinforced brittle-matrix composites

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

Okabe, T.; Takeda, N.; Komotori, J.

1999-11-26

A new model is proposed for multiple matrix cracking in order to take into account the role of matrix-rich regions in the cross section in initiating crack growth. The model is used to predict the matrix cracking stress and the total number of matrix cracks. The model converts the matrix-rich regions into equivalent penny shape crack sizes and predicts the matrix cracking stress with a fracture mechanics crack-bridging model. The estimated distribution of matrix cracking stresses is used as statistical input to predict the number of matrix cracks. The results show good agreement with the experimental results by replica observations.more » Therefore, it is found that the matrix cracking behavior mainly depends on the distribution of matrix-rich regions in the composite.« less

Artificial Intelligence Based Optimization for the Se(IV) Removal from Aqueous Solution by Reduced Graphene Oxide-Supported Nanoscale Zero-Valent Iron Composites

PubMed Central

Cao, Rensheng; Ruan, Wenqian; Wu, Xianliang; Wei, Xionghui

2018-01-01

Highly promising artificial intelligence tools, including neural network (ANN), genetic algorithm (GA) and particle swarm optimization (PSO), were applied in the present study to develop an approach for the evaluation of Se(IV) removal from aqueous solutions by reduced graphene oxide-supported nanoscale zero-valent iron (nZVI/rGO) composites. Both GA and PSO were used to optimize the parameters of ANN. The effect of operational parameters (i.e., initial pH, temperature, contact time and initial Se(IV) concentration) on the removal efficiency was examined using response surface methodology (RSM), which was also utilized to obtain a dataset for the ANN training. The ANN-GA model results (with a prediction error of 2.88%) showed a better agreement with the experimental data than the ANN-PSO model results (with a prediction error of 4.63%) and the RSM model results (with a prediction error of 5.56%), thus the ANN-GA model was an ideal choice for modeling and optimizing the Se(IV) removal by the nZVI/rGO composites due to its low prediction error. The analysis of the experimental data illustrates that the removal process of Se(IV) obeyed the Langmuir isotherm and the pseudo-second-order kinetic model. Furthermore, the Se 3d and 3p peaks found in XPS spectra for the nZVI/rGO composites after removing treatment illustrates that the removal of Se(IV) was mainly through the adsorption and reduction mechanisms. PMID:29543753

Artificial Intelligence Based Optimization for the Se(IV) Removal from Aqueous Solution by Reduced Graphene Oxide-Supported Nanoscale Zero-Valent Iron Composites.

PubMed

Cao, Rensheng; Fan, Mingyi; Hu, Jiwei; Ruan, Wenqian; Wu, Xianliang; Wei, Xionghui

2018-03-15

Highly promising artificial intelligence tools, including neural network (ANN), genetic algorithm (GA) and particle swarm optimization (PSO), were applied in the present study to develop an approach for the evaluation of Se(IV) removal from aqueous solutions by reduced graphene oxide-supported nanoscale zero-valent iron (nZVI/rGO) composites. Both GA and PSO were used to optimize the parameters of ANN. The effect of operational parameters (i.e., initial pH, temperature, contact time and initial Se(IV) concentration) on the removal efficiency was examined using response surface methodology (RSM), which was also utilized to obtain a dataset for the ANN training. The ANN-GA model results (with a prediction error of 2.88%) showed a better agreement with the experimental data than the ANN-PSO model results (with a prediction error of 4.63%) and the RSM model results (with a prediction error of 5.56%), thus the ANN-GA model was an ideal choice for modeling and optimizing the Se(IV) removal by the nZVI/rGO composites due to its low prediction error. The analysis of the experimental data illustrates that the removal process of Se(IV) obeyed the Langmuir isotherm and the pseudo-second-order kinetic model. Furthermore, the Se 3d and 3p peaks found in XPS spectra for the nZVI/rGO composites after removing treatment illustrates that the removal of Se(IV) was mainly through the adsorption and reduction mechanisms.

Vibroacoustic Model Validation for a Curved Honeycomb Composite Panel

NASA Technical Reports Server (NTRS)

Buehrle, Ralph D.; Robinson, Jay H.; Grosveld, Ferdinand W.

2001-01-01

Finite element and boundary element models are developed to investigate the vibroacoustic response of a curved honeycomb composite sidewall panel. Results from vibroacoustic tests conducted in the NASA Langley Structural Acoustic Loads and Transmission facility are used to validate the numerical predictions. The sidewall panel is constructed from a flexible honeycomb core sandwiched between carbon fiber reinforced composite laminate face sheets. This type of construction is being used in the development of an all-composite aircraft fuselage. In contrast to conventional rib-stiffened aircraft fuselage structures, the composite panel has nominally uniform thickness resulting in a uniform distribution of mass and stiffness. Due to differences in the mass and stiffness distribution, the noise transmission mechanisms for the composite panel are expected to be substantially different from those of a conventional rib-stiffened structure. The development of accurate vibroacoustic models will aide in the understanding of the dominant noise transmission mechanisms and enable optimization studies to be performed that will determine the most beneficial noise control treatments. Finite element and boundary element models of the sidewall panel are described. Vibroacoustic response predictions are presented for forced vibration input and the results are compared with experimental data.

Supersymmetry with a pNGB Higgs and partial compositeness

NASA Astrophysics Data System (ADS)

Marzocca, David; Parolini, Alberto; Serone, Marco

2014-03-01

We study the consequences of combining SUSY with a pseudo Nambu-Goldstone boson Higgs coming from an SO(5)/SO(4) coset and "partial compositeness". In particular, we focus on how electroweak symmetry breaking and the Higgs mass are reproduced in models where the symmetry SO(5) is linearly realized. The global symmetry forbids tree-level contributions to the Higgs potential coming from D-terms, differently from what happens in most of the SUSY little-Higgs constructions. While the stops are generally heavy, light fermion top partners below 1 TeV are predicted. In contrast to what happens in non-SUSY composite Higgs models, they are necessary to reproduce the correct top, rather than Higgs, mass. En passant, we point out that, independently of SUSY, models where t R is fully composite and embedded in the 5 of SO(5) generally predict a too light Higgs.

Prediction of crosslink density of solid propellant binders. [curing of elastomers

NASA Technical Reports Server (NTRS)

Marsh, H. E., Jr.

1976-01-01

A quantitative theory is outlined which allows calculation of crosslink density of solid propellant binders from a small number of predetermined parameters such as the binder composition, the functionality distributions of the ingredients, and the extent of the curing reaction. The parameter which is partly dependent on process conditions is the extent of reaction. The proposed theoretical model is verified by independent measurement of effective chain concentration and sol and gel fractions in simple compositions prepared from model compounds. The model is shown to correlate tensile data with composition in the case of urethane-cured polyether and certain solid propellants. A formula for the branching coefficient is provided according to which if one knows the functionality distributions of the ingredients and the corresponding equivalent weights and can measure or predict the extent of reaction, he can calculate the branching coefficient of such a system for any desired composition.

Prediction of fat-free body mass from bioelectrical impedance and anthropometry among 3-year-old children using DXA

PubMed Central

Ejlerskov, Katrine T.; Jensen, Signe M.; Christensen, Line B.; Ritz, Christian; Michaelsen, Kim F.; Mølgaard, Christian

2014-01-01

For 3-year-old children suitable methods to estimate body composition are sparse. We aimed to develop predictive equations for estimating fat-free mass (FFM) from bioelectrical impedance (BIA) and anthropometry using dual-energy X-ray absorptiometry (DXA) as reference method using data from 99 healthy 3-year-old Danish children. Predictive equations were derived from two multiple linear regression models, a comprehensive model (height2/resistance (RI), six anthropometric measurements) and a simple model (RI, height, weight). Their uncertainty was quantified by means of 10-fold cross-validation approach. Prediction error of FFM was 3.0% for both equations (root mean square error: 360 and 356 g, respectively). The derived equations produced BIA-based prediction of FFM and FM near DXA scan results. We suggest that the predictive equations can be applied in similar population samples aged 2–4 years. The derived equations may prove useful for studies linking body composition to early risk factors and early onset of obesity. PMID:24463487

Prediction of fat-free body mass from bioelectrical impedance and anthropometry among 3-year-old children using DXA.

PubMed

Ejlerskov, Katrine T; Jensen, Signe M; Christensen, Line B; Ritz, Christian; Michaelsen, Kim F; Mølgaard, Christian

2014-01-27

For 3-year-old children suitable methods to estimate body composition are sparse. We aimed to develop predictive equations for estimating fat-free mass (FFM) from bioelectrical impedance (BIA) and anthropometry using dual-energy X-ray absorptiometry (DXA) as reference method using data from 99 healthy 3-year-old Danish children. Predictive equations were derived from two multiple linear regression models, a comprehensive model (height(2)/resistance (RI), six anthropometric measurements) and a simple model (RI, height, weight). Their uncertainty was quantified by means of 10-fold cross-validation approach. Prediction error of FFM was 3.0% for both equations (root mean square error: 360 and 356 g, respectively). The derived equations produced BIA-based prediction of FFM and FM near DXA scan results. We suggest that the predictive equations can be applied in similar population samples aged 2-4 years. The derived equations may prove useful for studies linking body composition to early risk factors and early onset of obesity.

First-harmonic nonlinearities can predict unseen third-harmonics in medium-amplitude oscillatory shear (MAOS)

NASA Astrophysics Data System (ADS)

Carey-De La Torre, Olivia; Ewoldt, Randy H.

2018-02-01

We use first-harmonic MAOS nonlinearities from G 1' and G 1″ to test a predictive structure-rheology model for a transient polymer network. Using experiments with PVA-Borax (polyvinyl alcohol cross-linked by sodium tetraborate (borax)) at 11 different compositions, the model is calibrated to first-harmonic MAOS data on a torque-controlled rheometer at a fixed frequency, and used to predict third-harmonic MAOS on a displacement controlled rheometer at a different frequency three times larger. The prediction matches experiments for decomposed MAOS measures [ e 3] and [ v 3] with median disagreement of 13% and 25%, respectively, across all 11 compositions tested. This supports the validity of this model, and demonstrates the value of using all four MAOS signatures to understand and test structure-rheology relations for complex fluids.

Micromechanics Analysis Code (MAC) User Guide: Version 1.0

NASA Technical Reports Server (NTRS)

Wilt, T. E.; Arnold, S. M.

1994-01-01

The ability to accurately predict the thermomechanical deformation response of advanced composite materials continues to play an important role in the development of these strategic materials. Analytical models that predict the effective behavior of composites are used not only by engineers performing structural analysis of large-scale composite components but also by material scientists in developing new material systems. For an analytical model to fulfill these two distinct functions it must be based on a micromechanics approach which utilizes physically based deformation and life constitutive models and allows one to generate the average (macro) response of a composite material given the properties of the individual constituents and their geometric arrangement. Here the user guide for the recently developed, computationally efficient and comprehensive micromechanics analysis code, MAC, who's predictive capability rests entirely upon the fully analytical generalized method of cells, GMC, micromechanics model is described. MAC is a versatile form of research software that 'drives' the double or triple ply periodic micromechanics constitutive models based upon GMC. MAC enhances the basic capabilities of GMC by providing a modular framework wherein (1) various thermal, mechanical (stress or strain control), and thermomechanical load histories can be imposed; (2) different integration algorithms may be selected; (3) a variety of constituent constitutive models may be utilized and/or implemented; and (4) a variety of fiber architectures may be easily accessed through their corresponding representative volume elements.

Micromechanics Analysis Code (MAC). User Guide: Version 2.0

NASA Technical Reports Server (NTRS)

Wilt, T. E.; Arnold, S. M.

1996-01-01

The ability to accurately predict the thermomechanical deformation response of advanced composite materials continues to play an important role in the development of these strategic materials. Analytical models that predict the effective behavior of composites are used not only by engineers performing structural analysis of large-scale composite components but also by material scientists in developing new material systems. For an analytical model to fulfill these two distinct functions it must be based on a micromechanics approach which utilizes physically based deformation and life constitutive models and allows one to generate the average (macro) response of a composite material given the properties of the individual constituents and their geometric arrangement. Here the user guide for the recently developed, computationally efficient and comprehensive micromechanics analysis code's (MAC) who's predictive capability rests entirely upon the fully analytical generalized method of cells (GMC), micromechanics model is described. MAC is a versatile form of research software that 'drives' the double or triply periodic micromechanics constitutive models based upon GMC. MAC enhances the basic capabilities of GMC by providing a modular framework wherein (1) various thermal, mechanical (stress or strain control) and thermomechanical load histories can be imposed, (2) different integration algorithms may be selected, (3) a variety of constituent constitutive models may be utilized and/or implemented, and (4) a variety of fiber and laminate architectures may be easily accessed through their corresponding representative volume elements.

Handbook of Analytical Methods for Textile Composites

NASA Technical Reports Server (NTRS)

Cox, Brian N.; Flanagan, Gerry

1997-01-01

The purpose of this handbook is to introduce models and computer codes for predicting the properties of textile composites. The handbook includes several models for predicting the stress-strain response all the way to ultimate failure; methods for assessing work of fracture and notch sensitivity; and design rules for avoiding certain critical mechanisms of failure, such as delamination, by proper textile design. The following textiles received some treatment: 2D woven, braided, and knitted/stitched laminates and 3D interlock weaves, and braids.

Translating landfill methane generation parameters among first-order decay models.

PubMed

Krause, Max J; Chickering, Giles W; Townsend, Timothy G

2016-11-01

Landfill gas (LFG) generation is predicted by a first-order decay (FOD) equation that incorporates two parameters: a methane generation potential (L 0 ) and a methane generation rate (k). Because non-hazardous waste landfills may accept many types of waste streams, multiphase models have been developed in an attempt to more accurately predict methane generation from heterogeneous waste streams. The ability of a single-phase FOD model to predict methane generation using weighted-average methane generation parameters and tonnages translated from multiphase models was assessed in two exercises. In the first exercise, waste composition from four Danish landfills represented by low-biodegradable waste streams was modeled in the Afvalzorg Multiphase Model and methane generation was compared to the single-phase Intergovernmental Panel on Climate Change (IPCC) Waste Model and LandGEM. In the second exercise, waste composition represented by IPCC waste components was modeled in the multiphase IPCC and compared to single-phase LandGEM and Australia's Solid Waste Calculator (SWC). In both cases, weight-averaging of methane generation parameters from waste composition data in single-phase models was effective in predicting cumulative methane generation from -7% to +6% of the multiphase models. The results underscore the understanding that multiphase models will not necessarily improve LFG generation prediction because the uncertainty of the method rests largely within the input parameters. A unique method of calculating the methane generation rate constant by mass of anaerobically degradable carbon was presented (k c ) and compared to existing methods, providing a better fit in 3 of 8 scenarios. Generally, single phase models with weighted-average inputs can accurately predict methane generation from multiple waste streams with varied characteristics; weighted averages should therefore be used instead of regional default values when comparing models. Translating multiphase first-order decay model input parameters by weighted average shows that single-phase models can predict cumulative methane generation within the level of uncertainty of many of the input parameters as defined by the Intergovernmental Panel on Climate Change (IPCC), which indicates that decreasing the uncertainty of the input parameters will make the model more accurate rather than adding multiple phases or input parameters.

Compositional variations in sands of the Bagnold Dunes, Gale Crater, Mars, from visible-shortwave infrared spectroscopy and comparison with ground truth from the Curiosity Rover

USGS Publications Warehouse

Lapotre, Mathieu G.A.; Ehlmann, B. L.; Minson, Sarah E.; Arvidson, R. E.; Ayoub, F.; Fraeman, A. A.; Ewing, R. C.; Bridges, N. T.

2017-01-01

During its ascent up Mount Sharp, the Mars Science Laboratory Curiosity rover traversed the Bagnold Dune Field. We model sand modal mineralogy and grain size at four locations near the rover traverse, using orbital shortwave infrared single scattering albedo spectra and a Markov-Chain Monte Carlo implementation of Hapke's radiative transfer theory to fully constrain uncertainties and permitted solutions. These predictions, evaluated against in situ measurements at one site from the Curiosity rover, show that XRD-measured mineralogy of the basaltic sands is within the 95% confidence interval of model predictions. However, predictions are relatively insensitive to grain size and are non-unique, especially when modeling the composition of minerals with solid solutions. We find an overall basaltic mineralogy and show subtle spatial variations in composition in and around the Bagnold dunes, consistent with a mafic enrichment of sands with cumulative transport distance by sorting of olivine, pyroxene, and plagioclase grains during aeolian saltation. Furthermore, the large variations in Fe and Mg abundances (~20 wt%) at the Bagnold Dunes suggest that compositional variability induced by wind sorting may be enhanced by local mixing with proximal sand sources. Our estimates demonstrate a method for orbital quantification of composition with rigorous uncertainty determination and provide key constraints for interpreting in situ measurements of compositional variability within martian aeolian sandstones.

Scale effects in the response and failure of fiber reinforced composite laminates loaded in tension and in flexure

NASA Technical Reports Server (NTRS)

Jackson, Karen E.; Kellas, Sotiris; Morton, John

1992-01-01

The feasibility of using scale model testing for predicting the full-scale behavior of flat composite coupons loaded in tension and beam-columns loaded in flexure is examined. Classical laws of similitude are applied to fabricate and test replica model specimens to identify scaling effects in the load response, strength, and mode of failure. Experiments were performed on graphite-epoxy composite specimens having different laminate stacking sequences and a range of scaled sizes. From the experiments it was deduced that the elastic response of scaled composite specimens was independent of size. However, a significant scale effect in strength was observed. In addition, a transition in failure mode was observed among scaled specimens of certain laminate stacking sequences. A Weibull statistical model and a fracture mechanics based model were applied to predict the strength scale effect since standard failure criteria cannot account for the influence of absolute specimen size on strength.

Characterization of Metal Matrix Composites

NASA Technical Reports Server (NTRS)

Daniel, I. M.; Chun, H. J.; Karalekas, D.

1994-01-01

Experimental methods were developed, adapted, and applied to the characterization of a metal matrix composite system, namely, silicon carbide/aluminim (SCS-2/6061 Al), and its constituents. The silicon carbide fiber was characterized by determining its modulus, strength, and coefficient of thermal expansion. The aluminum matrix was characterized thermomechanically up to 399 C (750 F) at two strain rates. The unidirectional SiC/Al composite was characterized mechanically under longitudinal, transverse, and in-plane shear loading up to 399 C (750 F). Isothermal and non-isothermal creep behavior was also measured. The applicability of a proposed set of multifactor thermoviscoplastic nonlinear constitutive relations and a computer code was investigated. Agreement between predictions and experimental results was shown in a few cases. The elastoplastic thermomechanical behavior of the composite was also described by a number of new analytical models developed or adapted for the material system studied. These models include the rule of mixtures, composite cylinder model with various thermoelastoplastic analyses and a model based on average field theory. In most cases satisfactory agreement was demonstrated between analytical predictions and experimental results for the cases of stress-strain behavior and thermal deformation behavior at different temperatures. In addition, some models yielded detailed three-dimensional stress distributions in the constituents within the composite.

Nonlinearity and Strain-Rate Dependence in the Deformation Response of Polymer Matrix Composites Modeled

NASA Technical Reports Server (NTRS)

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.

A Multiscale Modeling Approach to Analyze Filament-Wound Composite Pressure Vessels

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

Nguyen, Ba Nghiep; Simmons, Kevin L.

2013-07-22

A multiscale modeling approach to analyze filament-wound composite pressure vessels is developed in this article. The approach, which extends the Nguyen et al. model [J. Comp. Mater. 43 (2009) 217] developed for discontinuous fiber composites to continuous fiber ones, spans three modeling scales. The microscale considers the unidirectional elastic fibers embedded in an elastic-plastic matrix obeying the Ramberg-Osgood relation and J2 deformation theory of plasticity. The mesoscale behavior representing the composite lamina is obtained through an incremental Mori-Tanaka type model and the Eshelby equivalent inclusion method [Proc. Roy. Soc. Lond. A241 (1957) 376]. The implementation of the micro-meso constitutive relationsmore » in the ABAQUS® finite element package (via user subroutines) allows the analysis of a filament-wound composite pressure vessel (macroscale) to be performed. Failure of the composite lamina is predicted by a criterion that accounts for the strengths of the fibers and of the matrix as well as of their interface. The developed approach is demonstrated in the analysis of a filament-wound pressure vessel to study the effect of the lamina thickness on the burst pressure. The predictions are favorably compared to the numerical and experimental results by Lifshitz and Dayan [Comp. Struct. 32 (1995) 313].« less

A model for the progressive failure of laminated composite structural components

NASA Technical Reports Server (NTRS)

Allen, D. H.; Lo, D. C.

1991-01-01

Laminated continuous fiber polymeric composites are capable of sustaining substantial load induced microstructural damage prior to component failure. Because this damage eventually leads to catastrophic failure, it is essential to capture the mechanics of progressive damage in any cogent life prediction model. For the past several years the authors have been developing one solution approach to this problem. In this approach the mechanics of matrix cracking and delamination are accounted for via locally averaged internal variables which account for the kinematics of microcracking. Damage progression is predicted by using phenomenologically based damage evolution laws which depend on the load history. The result is a nonlinear and path dependent constitutive model which has previously been implemented to a finite element computer code for analysis of structural components. Using an appropriate failure model, this algorithm can be used to predict component life. In this paper the model will be utilized to demonstrate the ability to predict the load path dependence of the damage and stresses in plates subjected to fatigue loading.

Modelling of Damage Evolution in Braided Composites: Recent Developments

NASA Astrophysics Data System (ADS)

Wang, Chen; Roy, Anish; Silberschmidt, Vadim V.; Chen, Zhong

2017-12-01

Composites reinforced with woven or braided textiles exhibit high structural stability and excellent damage tolerance thanks to yarn interlacing. With their high stiffness-to-weight and strength-to-weight ratios, braided composites are attractive for aerospace and automotive components as well as sports protective equipment. In these potential applications, components are typically subjected to multi-directional static, impact and fatigue loadings. To enhance material analysis and design for such applications, understanding mechanical behaviour of braided composites and development of predictive capabilities becomes crucial. Significant progress has been made in recent years in development of new modelling techniques allowing elucidation of static and dynamic responses of braided composites. However, because of their unique interlacing geometric structure and complicated failure modes, prediction of damage initiation and its evolution in components is still a challenge. Therefore, a comprehensive literature analysis is presented in this work focused on a review of the state-of-the-art progressive damage analysis of braided composites with finite-element simulations. Recently models employed in the studies on mechanical behaviour, impact response and fatigue analyses of braided composites are presented systematically. This review highlights the importance, advantages and limitations of as-applied failure criteria and damage evolution laws for yarns and composite unit cells. In addition, this work provides a good reference for future research on FE simulations of braided composites.

Gamma Prime Precipitate Evolution During Aging of a Model Nickel-Based Superalloy

NASA Astrophysics Data System (ADS)

Goodfellow, A. J.; Galindo-Nava, E. I.; Christofidou, K. A.; Jones, N. G.; Martin, T.; Bagot, P. A. J.; Boyer, C. D.; Hardy, M. C.; Stone, H. J.

2018-03-01

The microstructural stability of nickel-based superalloys is critical for maintaining alloy performance during service in gas turbine engines. In this study, the precipitate evolution in a model polycrystalline Ni-based superalloy during aging to 1000 hours has been studied via transmission electron microscopy, atom probe tomography, and neutron diffraction. Variations in phase composition and precipitate morphology, size, and volume fraction were observed during aging, while the constrained lattice misfit remained constant at approximately zero. The experimental composition of the γ matrix phase was consistent with thermodynamic equilibrium predictions, while significant differences were identified between the experimental and predicted results from the γ' phase. These results have implications for the evolution of mechanical properties in service and their prediction using modeling methods.

Analytical Modelling of Transverse Matrix Cracking of [plus or minus Theta/90(sub n)](sub s) Composite Laminates Under Multiaxial Loading

NASA Technical Reports Server (NTRS)

Mayugo, J A.; Camanho, P. P.; Maimi, P.; Davila, C. G.

2010-01-01

An analytical model based on the analysis of a cracked unit cell of a composite laminate subjected to multiaxial loads is proposed to predict the onset and accumulation of transverse matrix cracks in the 90(sub n) plies of uniformly stressed [plus or minus Theta/90(sub n)](sub s) laminates. The model predicts the effect of matrix cracks on the stiffness of the laminate, as well as the ultimate failure of the laminate, and it accounts for the effect of the ply thickness on the ply strength. Several examples describing the predictions of laminate response, from damage onset up to final failure under both uniaxial and multiaxial loads, are presented.

A Numerical Method for Simulating the Microscopic Damage Evolution in Composites Under Uniaxial Transverse Tension

NASA Astrophysics Data System (ADS)

Zhi, Jie; Zhao, Libin; Zhang, Jianyu; Liu, Zhanli

2016-06-01

In this paper, a new numerical method that combines a surface-based cohesive model and extended finite element method (XFEM) without predefining the crack paths is presented to simulate the microscopic damage evolution in composites under uniaxial transverse tension. The proposed method is verified to accurately capture the crack kinking into the matrix after fiber/matrix debonding. A statistical representative volume element (SRVE) under periodic boundary conditions is used to approximate the microstructure of the composites. The interface parameters of the cohesive models are investigated, in which the initial interface stiffness has a great effect on the predictions of the fiber/matrix debonding. The detailed debonding states of SRVE with strong and weak interfaces are compared based on the surface-based and element-based cohesive models. The mechanism of damage in composites under transverse tension is described as the appearance of the interface cracks and their induced matrix micro-cracking, both of which coalesce into transversal macro-cracks. Good agreement is found between the predictions of the model and the in situ experimental observations, demonstrating the efficiency of the presented model for simulating the microscopic damage evolution in composites.

Effect of water flow and chemical environment on microbiota growth and composition in the human colon.

PubMed

Cremer, Jonas; Arnoldini, Markus; Hwa, Terence

2017-06-20

The human gut harbors a dynamic microbial community whose composition bears great importance for the health of the host. Here, we investigate how colonic physiology impacts bacterial growth, which ultimately dictates microbiota composition. Combining measurements of bacterial physiology with analysis of published data on human physiology into a quantitative, comprehensive modeling framework, we show how water flow in the colon, in concert with other physiological factors, determine the abundances of the major bacterial phyla. Mechanistically, our model shows that local pH values in the lumen, which differentially affect the growth of different bacteria, drive changes in microbiota composition. It identifies key factors influencing the delicate regulation of colonic pH, including epithelial water absorption, nutrient inflow, and luminal buffering capacity, and generates testable predictions on their effects. Our findings show that a predictive and mechanistic understanding of microbial ecology in the gut is possible. Such predictive understanding is needed for the rational design of intervention strategies to actively control the microbiota.

Effect of water flow and chemical environment on microbiota growth and composition in the human colon

PubMed Central

Cremer, Jonas; Arnoldini, Markus; Hwa, Terence

2017-01-01

The human gut harbors a dynamic microbial community whose composition bears great importance for the health of the host. Here, we investigate how colonic physiology impacts bacterial growth, which ultimately dictates microbiota composition. Combining measurements of bacterial physiology with analysis of published data on human physiology into a quantitative, comprehensive modeling framework, we show how water flow in the colon, in concert with other physiological factors, determine the abundances of the major bacterial phyla. Mechanistically, our model shows that local pH values in the lumen, which differentially affect the growth of different bacteria, drive changes in microbiota composition. It identifies key factors influencing the delicate regulation of colonic pH, including epithelial water absorption, nutrient inflow, and luminal buffering capacity, and generates testable predictions on their effects. Our findings show that a predictive and mechanistic understanding of microbial ecology in the gut is possible. Such predictive understanding is needed for the rational design of intervention strategies to actively control the microbiota. PMID:28588144

Assessment of Fecal Near-infrared Spectroscopy to Predict Feces Chemical Composition and Apparent Total Tract Digestibility of Nutrients in Pigs.

PubMed

Nirea, K G; Pérez de Nanclares, M; Skugor, A; Afseth, N K; Meuwissen, T H E; Hansen, J Ø; Mydland, L T; Øverland, M

2018-05-08

Apparent total tract digestibility (ATTD) of nutrients could be an alternative measure of feed efficiency when breeding for robust animals that are fed fiber-rich diets. Apparent total tract digestibility of nutrients requires measuring individual feed intake of a large number of animals which is expensive and complex. Alternatively, ATTD of nutrients and feces chemical composition can be predicted using fecal near-infrared spectroscopy (FNIRS). The objective of this study was to assess if the feces chemical composition and ATTD of nutrients can be predicted using FNIRS that originate from various pig experimental datasets. Fecal samples together with detailed information on the feces chemical composition and ATTD of nutrients were obtained from four different pig experiments. Feces near-infrared spectroscopy were analyzed from fecal samples of a complete dataset. The model was calibrated using the FNIRS and reference samples of feces chemical composition and ATTD of nutrients. The robustness and predictability of the model was evaluated by the r2 and the closeness between SE of calibration (SEC) and SE of cross-validation (SECV). Prediction of the feces chemical components and ATTD of nutrients was successful as SEC and SECV were equivalent. Calibration model was developed to estimate the ATTD of nutrients and fecal chemical composition from the FNIRS and worked well for OM (r2 = 0.94; SEC = 48.5; SECV = 56.6), CP ( r2 = 0.89; SEC = 18.1; SECV = 18.8), GE ( r2 = 0.92; SEC = 1.2; SECV = 1.4), NDF (r2 = 0.94 ; SEC = 55; SECV = 60.2), OM digestibility (r2 = 0.94; SEC = 5.5; SECV = 6.7), GE digestibility (r2 = 0.88; SEC = 2.3; SECV = 2.6) and fat digestibility (r2 = 0.79 ; SEC = 6, SECV = 6.8). However, the SE of prediction was slightly higher than what has been reported in another study. The prediction of feces chemical composition for fat (r2 = 0.69; SEC = 11.7, SECV = 12.3), CP digestibility (r2 = 0.63; SEC = 2.3; SECV = 2.7) and NDF digestibility (r2 = 0.64, SEC = 7.7, SECV = 8.8) was moderate. We conclude that the FNIRS accurately predicts the chemical composition of feces and ATTD of nutrients for OM, CP and GE. The approach of FNIRS is a cost-effective method for measuring digestibility and feed efficiency in a large-scale pig breeding programs.

Textile composite processing science

NASA Technical Reports Server (NTRS)

Loos, Alfred C.; Hammond, Vincent H.; Kranbuehl, David E.; Hasko, Gregory H.

1993-01-01

A multi-dimensional model of the Resin Transfer Molding (RTM) process was developed for the prediction of the infiltration behavior of a resin into an anisotropic fiber preform. Frequency dependent electromagnetic sensing (FDEMS) was developed for in-situ monitoring of the RTM process. Flow visualization and mold filling experiments were conducted to verify sensor measurements and model predictions. Test results indicated good agreement between model predictions, sensor readings, and experimental data.

Developing a predictive model for the chemical composition of soot nanoparticles

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

Violi, Angela; Michelsen, Hope; Hansen, Nils

In order to provide the scientific foundation to enable technology breakthroughs in transportation fuel, it is important to develop a combustion modeling capability to optimize the operation and design of evolving fuels in advanced engines for transportation applications. The goal of this proposal is to develop a validated predictive model to describe the chemical composition of soot nanoparticles in premixed and diffusion flames. Atomistic studies in conjunction with state-of-the-art experiments are the distinguishing characteristics of this unique interdisciplinary effort. The modeling effort has been conducted at the University of Michigan by Prof. A. Violi. The experimental work has entailed amore » series of studies using different techniques to analyze gas-phase soot precursor chemistry and soot particle production in premixed and diffusion flames. Measurements have provided spatial distributions of polycyclic aromatic hydrocarbons and other gas-phase species and size and composition of incipient soot nanoparticles for comparison with model results. The experimental team includes Dr. N. Hansen and H. Michelsen at Sandia National Labs' Combustion Research Facility, and Dr. K. Wilson as collaborator at Lawrence Berkeley National Lab's Advanced Light Source. Our results show that the chemical and physical properties of nanoparticles affect the coagulation behavior in soot formation, and our results on an experimentally validated, predictive model for the chemical composition of soot nanoparticles will not only enhance our understanding of soot formation since but will also allow the prediction of particle size distributions under combustion conditions. These results provide a novel description of soot formation based on physical and chemical properties of the particles for use in the next generation of soot models and an enhanced capability for facilitating the design of alternative fuels and the engines they will power.« less

An effective simplified model of composite compression struts for partially-restrained steel frame with reinforced concrete infill walls

NASA Astrophysics Data System (ADS)

Sun, Guohua; Chuang-Sheng, Walter Yang; Gu, Qiang; DesRoches, Reginald

2018-04-01

To resolve the issue regarding inaccurate prediction of the hysteretic behavior by micro-based numerical analysis for partially-restrained (PR) steel frames with solid reinforced concrete (RC) infill walls, an innovative simplified model of composite compression struts is proposed on the basis of experimental observation on the cracking distribution, load transferring mechanism, and failure modes of RC infill walls filled in PR steel frame. The proposed composite compression struts model for the solid RC infill walls is composed of α inclined struts and main diagonal struts. The α inclined struts are used to reflect the part of the lateral force resisted by shear connectors along the frame-wall interface, while the main diagonal struts are introduced to take into account the rest of the lateral force transferred along the diagonal direction due to the complicated interaction between the steel frame and RC infill walls. This study derives appropriate formulas for the effective widths of the α inclined strut and main diagonal strut, respectively. An example of PR steel frame with RC infill walls simulating simulated by the composite inclined compression struts model is illustrated. The maximum lateral strength and the hysteresis curve shape obtained from the proposed composite strut model are in good agreement with those from the test results, and the backbone curve of a PR steel frame with RC infill walls can be predicted precisely when the inter-story drift is within 1%. This simplified model can also predict the structural stiffness and the equivalent viscous damping ratio well when the inter-story drift ratio exceeds 0.5%.

A numerical approach to model and predict the energy absorption and crush mechanics within a long-fiber composite crush tube

NASA Astrophysics Data System (ADS)

Pickett, Leon, Jr.

Past research has conclusively shown that long fiber structural composites possess superior specific energy absorption characteristics as compared to steel and aluminum structures. However, destructive physical testing of composites is very costly and time consuming. As a result, numerical solutions are desirable as an alternative to experimental testing. Up until this point, very little numerical work has been successful in predicting the energy absorption of composite crush structures. This research investigates the ability to use commercially available numerical modeling tools to approximate the energy absorption capability of long-fiber composite crush tubes. This study is significant because it provides a preliminary analysis of the suitability of LS-DYNA to numerically characterize the crushing behavior of a dynamic axial impact crushing event. Composite crushing theory suggests that there are several crushing mechanisms occurring during a composite crush event. This research evaluates the capability and suitability of employing, LS-DYNA, to simulate the dynamic crush event of an E-glass/epoxy cylindrical tube. The model employed is the composite "progressive failure model", a much more limited failure model when compared to the experimental failure events which naturally occur. This numerical model employs (1) matrix cracking, (2) compression, and (3) fiber breakage failure modes only. The motivation for the work comes from the need to reduce the significant cost associated with experimental trials. This research chronicles some preliminary efforts to better understand the mechanics essential in pursuit of this goal. The immediate goal is to begin to provide deeper understanding of a composite crush event and ultimately create a viable alternative to destructive testing of composite crush tubes.

Numerical Analysis of the Elastic Properties of 3D Needled Carbon/Carbon Composites

NASA Astrophysics Data System (ADS)

Tan, Y.; Yan, Y.; Li, X.; Guo, F.

2017-09-01

Based on the observation of microstructures of 3D needled carbon/carbon (C/C) composites, a model of their representative volume element (RVE) considering the true distribution of fibers is established. Using the theories of mesoscopic mechanics and introducing periodic boundary conditions for displacements, their elastic properties, with account of porosity, are determined by finite-element methods. Quasi-static tensile tests were carried out, and the numerical predictions were found to be in good agreement with test results. This means that the RVE model of 3D needled C/C composites can predict their elastic properties efficiently. The effects of needling density, radius of needled fibers, and thickness ratio of a short-cut fiber web and a weftless ply on the elastic constants of the composites are analyzed.

Empirical Model Development for Predicting Shock Response on Composite Materials Subjected to Pyroshock Loading

NASA Technical Reports Server (NTRS)

Gentz, Steven J.; Ordway, David O; Parsons, David S.; Garrison, Craig M.; Rodgers, C. Steven; Collins, Brian W.

2015-01-01

The NASA Engineering and Safety Center (NESC) received a request to develop an analysis model based on both frequency response and wave propagation analyses for predicting shock response spectrum (SRS) on composite materials subjected to pyroshock loading. The model would account for near-field environment (approx. 9 inches from the source) dominated by direct wave propagation, mid-field environment (approx. 2 feet from the source) characterized by wave propagation and structural resonances, and far-field environment dominated by lower frequency bending waves in the structure. This report documents the outcome of the assessment.

Empirical Model Development for Predicting Shock Response on Composite Materials Subjected to Pyroshock Loading. [Appendices

NASA Technical Reports Server (NTRS)

Gentz, Steven J.; Ordway, David O.; Parsons, David S.; Garrison, Craig M.; Rodgers, C. Steven; Collins, Brian W.

2015-01-01

The NASA Engineering and Safety Center (NESC) received a request to develop an analysis model based on both frequency response and wave propagation analyses for predicting shock response spectrum (SRS) on composite materials subjected to pyroshock loading. The model would account for near-field environment (9 inches from the source) dominated by direct wave propagation, mid-field environment (approximately 2 feet from the source) characterized by wave propagation and structural resonances, and far-field environment dominated by lower frequency bending waves in the structure. This document contains appendices to the Volume I report.

Empirical Model Development for Predicting Shock Response on Composite Materials Subjected to Pyroshock Loading: Appendices

NASA Technical Reports Server (NTRS)

Gentz, Steven J.; Ordway, David O.; Parsons, David S.; Garrison, Craig M.; Rodgers, C. Steven; Collins, Brian W.

2015-01-01

The NASA Engineering and Safety Center (NESC) received a request to develop an analysis model based on both frequency response and wave propagation analyses for predicting shock response spectrum (SRS) on composite materials subjected to pyroshock loading. The model would account for near-field environment (approx. 9 inches from the source) dominated by direct wave propagation, mid-field environment (approx. 2 feet from the source) characterized by wave propagation and structural resonances, and far-field environment dominated by lower frequency bending waves in the structure. This document contains appendices to the Volume I report.

When relationships estimated in the past cannot be used to predict the future: using mechanistic models to predict landscape ecological dynamics in a changing world

Treesearch

Eric J. Gustafson

2013-01-01

Researchers and natural resource managers need predictions of how multiple global changes (e.g., climate change, rising levels of air pollutants, exotic invasions) will affect landscape composition and ecosystem function. Ecological predictive models used for this purpose are constructed using either a mechanistic (process-based) or a phenomenological (empirical)...

Space can substitute for time in predicting climate-change effects on biodiversity

USGS Publications Warehouse

Blois, Jessica L.; Williams, John W.; Fitzpatrick, Matthew C.; Jackson, Stephen T.; Ferrier, Simon

2013-01-01

“Space-for-time” substitution is widely used in biodiversity modeling to infer past or future trajectories of ecological systems from contemporary spatial patterns. However, the foundational assumption—that drivers of spatial gradients of species composition also drive temporal changes in diversity—rarely is tested. Here, we empirically test the space-for-time assumption by constructing orthogonal datasets of compositional turnover of plant taxa and climatic dissimilarity through time and across space from Late Quaternary pollen records in eastern North America, then modeling climate-driven compositional turnover. Predictions relying on space-for-time substitution were ∼72% as accurate as “time-for-time” predictions. However, space-for-time substitution performed poorly during the Holocene when temporal variation in climate was small relative to spatial variation and required subsampling to match the extent of spatial and temporal climatic gradients. Despite this caution, our results generally support the judicious use of space-for-time substitution in modeling community responses to climate change.

Space can substitute for time in predicting climate-change effects on biodiversity.

PubMed

Blois, Jessica L; Williams, John W; Fitzpatrick, Matthew C; Jackson, Stephen T; Ferrier, Simon

2013-06-04

"Space-for-time" substitution is widely used in biodiversity modeling to infer past or future trajectories of ecological systems from contemporary spatial patterns. However, the foundational assumption--that drivers of spatial gradients of species composition also drive temporal changes in diversity--rarely is tested. Here, we empirically test the space-for-time assumption by constructing orthogonal datasets of compositional turnover of plant taxa and climatic dissimilarity through time and across space from Late Quaternary pollen records in eastern North America, then modeling climate-driven compositional turnover. Predictions relying on space-for-time substitution were ∼72% as accurate as "time-for-time" predictions. However, space-for-time substitution performed poorly during the Holocene when temporal variation in climate was small relative to spatial variation and required subsampling to match the extent of spatial and temporal climatic gradients. Despite this caution, our results generally support the judicious use of space-for-time substitution in modeling community responses to climate change.

Effects of climate change and shifts in forest composition on forest net primary production

Treesearch

Jyh-Min Chiang; Louts [Louis] R. Iverson; Anantha Prasad; Kim J. Brown

2008-01-01

Forests are dynamic in both structure and species composition, and these dynamics are strongly influenced by climate. However, the net effects of future tree species composition on net primary production (NPP) are not well understood. The objective of this work was to model the potential range shifts of tree species (DISTRIB Model) and predict their impacts on NPP (...

Finite element modeling of small-scale tapered wood-laminated composite poles with biomimicry features

Treesearch

Cheng Piao; Todd F. Shupe; R.C. Tang; Chung Y. Hse

2008-01-01

Tapered composite poles with biomimicry features as in bamboo are a new generation of wood laminated composite poles that may some day be considered as an alternative to solid wood poles that are widely used in the transmission and telecommunication fields. Five finite element models were developed with ANSYS to predict and assess the performance of five types of...

Development of a Composite Delamination Fatigue Life Prediction Methodology

NASA Technical Reports Server (NTRS)

OBrien, Thomas K.

2009-01-01

Delamination is one of the most significant and unique failure modes in composite structures. Because of a lack of understanding of the consequences of delamination and the inability to predict delamination onset and growth, many composite parts are unnecessarily rejected upon inspection, both immediately after manufacture and while in service. NASA Langley is leading the efforts in the U.S. to develop a fatigue life prediction methodology for composite delamination using fracture mechanics. Research being performed to this end will be reviewed. Emphasis will be placed on the development of test standards for delamination characterization, incorporation of approaches for modeling delamination in commercial finite element codes, and efforts to mature the technology for use in design handbooks and certification documents.

Measured effects of surface cloth impressions on polar backscatter and comparison with a reflection grating model

NASA Technical Reports Server (NTRS)

Madaras, Eric I.; Brush, Edwin F., III; Bridal, S. L.; Holland, Mark R.; Miller, James G.

1992-01-01

This paper focuses on the nature of a typical composite surface and its effects on scattering. Utilizing epoxy typical of that in composites and standard composite fabrication methods, a sample with release cloth impressions on its surface is produced. A simple model for the scattering from the surface impressions of this sample is constructed and then polar backscatter measurements are made on the sample and compared with the model predictions.

Quantitative Model to Predict Melts on the Ol-Opx Saturation Boundary during Mantle Melting: The Role of H2O

NASA Astrophysics Data System (ADS)

Andrews, A. L.; Grove, T. L.

2014-12-01

Two quantitative, empirical models are presented that predict mantle melt compositions in equilibrium with olivine (ol) + orthopyroxene (opx) ± spinel (sp) as a function of variable pressure and H2O content. The models consist of multiple linear regressions calibrated using new data from H2O-undersaturated primitive and depleted mantle lherzolite melting experiments as well as experimental literature data. The models investigate the roles of H2O, Pressure, 1-Mg# (1-[XMg/(XMg+XFe)]), NaK# ((Na2O+K2O)/(Na2O+K2O+CaO)), TiO2, and Cr2O3 on mantle melt compositions. Melts are represented by the pseudoternary endmembers Clinopyroxene (Cpx), Olivine (Ol), Plagioclase (Plag), and Quartz (Qz) of Tormey et al. (1987). Model A returns predictive equations for the four endmembers with identical predictor variables, whereas Model B chooses predictor variables for the four compositional endmember equations and temperature independently. We employ the use of Akaike Information Criteria (Akaike, 1974) to determine the best predictor variables from initial variables chosen through thermodynamic reasoning and by previous models. In both Models A and B, the coefficients for H2O show that increasing H2O drives the melt to more Qz normative space, as the Qz component increases by +0.012(3) per 1 wt.% H2O. The other endmember components decrease and are all three times less affected by H2O (Ol: -0.004(2); Cpx: -0.004(2); Plag: -0.004(3)). Consistent with previous models and experimental data, increasing pressure moves melt compositions to more Ol normative space at the expense of the Qz component. The models presented quantitatively determine the influence of H2O, Pressure, 1-Mg#, NaK#, TiO2, and Cr2O3 on mantle melts in equilibrium with ol+opx±sp; the equations presented can be used to predict melts of known mantle source compositions saturated in ol+opx±sp. References Tormey, Grove, & Bryan (1987), doi: 10.1007/BF00375227. Akaike (1974), doi: 10.1109/TAC.1974.1100705.

Effects of elevated temperature on the viscoplastic modeling of graphite/polymeric composites

NASA Technical Reports Server (NTRS)

Gates, Thomas S.

1991-01-01

To support the development of new materials for the design of next generation supersonic transports, a research program is underway at NASA to assess the long term durability of advanced polymer matrix composites (PMC's). One of main objectives of the program was to explore the effects of elevated temperature (23 to 200 C) on the constitutive model's material parameters. To achieve this goal, test data on the observed nonlinear, stress-strain behavior of IM7/5260 and IM7/8320 composites under tension and compression loading were collected and correlated against temperature. These tests, conducted under isothermal conditions using variable strain rates, included such phenomena as stress relaxation and short term creep. The second major goal was the verification of the model by comparison of analytical predictions and test results for off axis and angle ply laminates. Correlation between test and predicted behavior was performed for specimens of both material systems over a range of temperatures. Results indicated that the model provided reasonable predictions of material behavior in load or strain controlled tests. Periods of loading, unloading, stress relaxation, and creep were accounted for.

Case study on prediction of remaining methane potential of landfilled municipal solid waste by statistical analysis of waste composition data.

PubMed

Sel, İlker; Çakmakcı, Mehmet; Özkaya, Bestamin; Suphi Altan, H

2016-10-01

Main objective of this study was to develop a statistical model for easier and faster Biochemical Methane Potential (BMP) prediction of landfilled municipal solid waste by analyzing waste composition of excavated samples from 12 sampling points and three waste depths representing different landfilling ages of closed and active sections of a sanitary landfill site located in İstanbul, Turkey. Results of Principal Component Analysis (PCA) were used as a decision support tool to evaluation and describe the waste composition variables. Four principal component were extracted describing 76% of data set variance. The most effective components were determined as PCB, PO, T, D, W, FM, moisture and BMP for the data set. Multiple Linear Regression (MLR) models were built by original compositional data and transformed data to determine differences. It was observed that even residual plots were better for transformed data the R(2) and Adjusted R(2) values were not improved significantly. The best preliminary BMP prediction models consisted of D, W, T and FM waste fractions for both versions of regressions. Adjusted R(2) values of the raw and transformed models were determined as 0.69 and 0.57, respectively. Copyright © 2016 Elsevier Ltd. All rights reserved.

Ply cracking in composite laminates

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

Han, Youngmyong.

1989-01-01

Ply cracking behavior and accompanying stiffness changes in thermoset as well as thermoplastic matrix composites under various loading conditions are investigated. Specific topics addressed are: analytical model development for property degradations due to ply cracking under general in-plane loading; crack initiation and multiplication under static loading; and crack multiplication under cyclic loading. A model was developed to calculate the energy released due to ply cracking in a composite laminate subjected to general in-plane loading. The method is based on the use of a second order polynomial to represent the crack opening displacement and the concept of a through-the-thickness inherent flaw.more » The model is then used in conjunction with linear elastic fracture mechanics to predict the progressive ply cracking as well as first ply cracking. A resistance curve for crack multiplication is proposed as a means of characterizing the resistance to ply cracking in composite laminates. A methodology of utilizing the resistance curve to assess the crack density or overloading is also discussed. The method was applied to the graphite/thermoplastic polyimide composite to predict progressive ply cracking. However, unlike the thermoset matrix composites, a strength model is found to fit the experimental results better than the fracture mechanics based model. A set of closed form equations is also developed to calculate the accompanying stiffness changes due to the ply cracking. The effect of thermal residual stress is included in the analysis. A new method is proposed to characterize transverse ply cracking of symmetric balanced laminates under cyclic loading. The method is based on the concept of a through-the-thickness inherent flaw, the Paris law, and the resistance curve. Only two constants are needed to predict the crack density as a function of fatigue cycles.« less

Mesh Convergence Requirements for Composite Damage Models

NASA Technical Reports Server (NTRS)

Davila, Carlos G.

2016-01-01

The ability of the finite element method to accurately represent the response of objects with intricate geometry and loading renders the finite element method as an extremely versatile analysis technique for structural analysis. Finite element analysis is routinely used in industry to calculate deflections, stress concentrations, natural frequencies, buckling loads, and much more. The method works by discretizing complex problems into smaller, simpler approximations that are valid over small uniform domains. For common analyses, the maximum size of the elements that can be used is often be determined by experience. However, to verify the quality of a solution, analyses with several levels of mesh refinement should be performed to ensure that the solution has converged. In recent years, the finite element method has been used to calculate the resistance of structures, and in particular that of composite structures. A number of techniques such as cohesive zone modeling, the virtual crack closure technique, and continuum damage modeling have emerged that can be used to predict cracking, delaminations, fiber failure, and other composite damage modes that lead to structural collapse. However, damage models present mesh refinement requirements that are not well understood. In this presentation, we examine different mesh refinement issues related to the representation of damage in composite materials. Damage process zone sizes and their corresponding mesh requirements will be discussed. The difficulties of modeling discontinuities and the associated need for regularization techniques will be illustrated, and some unexpected element size constraints will be presented. Finally, some of the difficulties in constructing models of composite structures capable of predicting transverse matrix cracking will be discussed. It will be shown that to predict the initiation and propagation of transverse matrix cracks, their density, and their saturation may require models that are significantly more refined than those that have been contemplated in the past.

A New Local Debonding Model with Application to the Transverse Tensile and Creep Behavior of Continuously Reinforced Titanium Composites

NASA Technical Reports Server (NTRS)

Bednarcyk, Brett A.; Arnold, Steven M.

2000-01-01

A new, widely applicable model for local interfacial debonding in composite materials is presented. Unlike its direct predecessors, the new model allows debonding to progress via unloading of interfacial stresses even as global loading of the composite continues. Previous debonding models employed for analysis of titanium matrix composites are surpassed by the accuracy, simplicity, and efficiency demonstrated by the new model. The new model was designed to operate seamlessly within NASA Glenn's Micromechanics Analysis Code with Generalized Method of Cells (MAC/GMC), which was employed to simulate the time- and rate-dependent (viscoplastic) transverse tensile and creep behavior of SiC/Ti composites. MAC/GMC's ability to simulate the transverse behavior of titanium matrix composites has been significantly improved by the new debonding model. Further, results indicate the need for a more accurate constitutive representation of the titanium matrix behavior in order to enable predictions of the composite transverse response, without resorting to recalibration of the debonding model parameters.

METCAN: The metal matrix composite analyzer

NASA Technical Reports Server (NTRS)

Hopkins, Dale A.; Murthy, Pappu L. N.

1988-01-01

Metal matrix composites (MMC) are the subject of intensive study and are receiving serious consideration for critical structural applications in advanced aerospace systems. MMC structural analysis and design methodologies are studied. Predicting the mechanical and thermal behavior and the structural response of components fabricated from MMC requires the use of a variety of mathematical models. These models relate stresses to applied forces, stress intensities at the tips of cracks to nominal stresses, buckling resistance to applied force, or vibration response to excitation forces. The extensive research in computational mechanics methods for predicting the nonlinear behavior of MMC are described. This research has culminated in the development of the METCAN (METal Matrix Composite ANalyzer) computer code.

Investigation into the propagation of Omega very low frequency signals and techniques for improvement of navigation accuracy including differential and composite omega

NASA Technical Reports Server (NTRS)

1973-01-01

An analysis of Very Low Frequency propagation in the atmosphere in the 10-14 kHz range leads to a discussion of some of the more significant causes of phase perturbation. The method of generating sky-wave corrections to predict the Omega phase is discussed. Composite Omega is considered as a means of lane identification and of reducing Omega navigation error. A simple technique for generating trapezoidal model (T-model) phase prediction is presented and compared with the Navy predictions and actual phase measurements. The T-model prediction analysis illustrates the ability to account for the major phase shift created by the diurnal effects on the lower ionosphere. An analysis of the Navy sky-wave correction table is used to provide information about spatial and temporal correlation of phase correction relative to the differential mode of operation.

Predicting protein-binding regions in RNA using nucleotide profiles and compositions.

PubMed

Choi, Daesik; Park, Byungkyu; Chae, Hanju; Lee, Wook; Han, Kyungsook

2017-03-14

Motivated by the increased amount of data on protein-RNA interactions and the availability of complete genome sequences of several organisms, many computational methods have been proposed to predict binding sites in protein-RNA interactions. However, most computational methods are limited to finding RNA-binding sites in proteins instead of protein-binding sites in RNAs. Predicting protein-binding sites in RNA is more challenging than predicting RNA-binding sites in proteins. Recent computational methods for finding protein-binding sites in RNAs have several drawbacks for practical use. We developed a new support vector machine (SVM) model for predicting protein-binding regions in mRNA sequences. The model uses sequence profiles constructed from log-odds scores of mono- and di-nucleotides and nucleotide compositions. The model was evaluated by standard 10-fold cross validation, leave-one-protein-out (LOPO) cross validation and independent testing. Since actual mRNA sequences have more non-binding regions than protein-binding regions, we tested the model on several datasets with different ratios of protein-binding regions to non-binding regions. The best performance of the model was obtained in a balanced dataset of positive and negative instances. 10-fold cross validation with a balanced dataset achieved a sensitivity of 91.6%, a specificity of 92.4%, an accuracy of 92.0%, a positive predictive value (PPV) of 91.7%, a negative predictive value (NPV) of 92.3% and a Matthews correlation coefficient (MCC) of 0.840. LOPO cross validation showed a lower performance than the 10-fold cross validation, but the performance remains high (87.6% accuracy and 0.752 MCC). In testing the model on independent datasets, it achieved an accuracy of 82.2% and an MCC of 0.656. Testing of our model and other state-of-the-art methods on a same dataset showed that our model is better than the others. Sequence profiles of log-odds scores of mono- and di-nucleotides were much more powerful features than nucleotide compositions in finding protein-binding regions in RNA sequences. But, a slight performance gain was obtained when using the sequence profiles along with nucleotide compositions. These are preliminary results of ongoing research, but demonstrate the potential of our approach as a powerful predictor of protein-binding regions in RNA. The program and supporting data are available at http://bclab.inha.ac.kr/RBPbinding .

Evaluation of DeNitrification DeComposition model for estimating ammonia fluxes from chemical fertilizer application

USDA-ARS?s Scientific Manuscript database

DeNitrification DeComposition (DNDC) model predictions of NH3 fluxes following chemical fertilizer application were evaluated by comparison to relaxed eddy accumulation (REA) measurements, in Central Illinois, United States, over the 2014 growing season of corn. Practical issues for evaluating closu...

Chondritic Models of 4 Vesta: Comparison of Data from the Dawn Mission with Predicted Internal Structure and Surface Composition/Mineralogy

NASA Technical Reports Server (NTRS)

Toplis, M. J.; Mizzon, H.; Forni, O.; Monnereau, M.; Barrat, J-A.; Prettyman, T. H.; McSween, H. Y.; McCoy, T. J.; Mittlefehldt, D. W.; De Sanctis, M. C.;

Design of two-way reversible bending actuator based on a shape memory alloy/shape memory polymer composite

NASA Astrophysics Data System (ADS)

Taya, Minoru; Liang, Yuanchang; Namli, Onur C.; Tamagawa, Hirohisa; Howie, Tucker

2013-10-01

The design of a reversible bending actuator based on a SMA/SMP composite is presented. The SMA/SMP composite is made of SMA NiTi wires with a bent ‘U’-shape in the austenite phase embedded in an epoxy SMP matrix which has a memorized flat shape. The bending motion is caused by heating the composite above TAf to activate the NiTi recovery. Upon cooling, the softening from the austenite to R-phase transformation results in a relaxation of the composite towards its original flat shape. In the three-point bending measurement the composite was able to exhibit a reversible deflection of 1.3 mm on a support with a 10 mm span. In addition, a material model for predicting the composite’s deflection is presented and predicts the experimental results reasonably well. The model also estimates the in-plane internal force and the degree of the SMA phase transformation.

Reliability Prediction of Ontology-Based Service Compositions Using Petri Net and Time Series Models

PubMed Central

Li, Jia; Xia, Yunni; Luo, Xin

2014-01-01

OWL-S, one of the most important Semantic Web service ontologies proposed to date, provides a core ontological framework and guidelines for describing the properties and capabilities of their web services in an unambiguous, computer interpretable form. Predicting the reliability of composite service processes specified in OWL-S allows service users to decide whether the process meets the quantitative quality requirement. In this study, we consider the runtime quality of services to be fluctuating and introduce a dynamic framework to predict the runtime reliability of services specified in OWL-S, employing the Non-Markovian stochastic Petri net (NMSPN) and the time series model. The framework includes the following steps: obtaining the historical response times series of individual service components; fitting these series with a autoregressive-moving-average-model (ARMA for short) and predicting the future firing rates of service components; mapping the OWL-S process into a NMSPN model; employing the predicted firing rates as the model input of NMSPN and calculating the normal completion probability as the reliability estimate. In the case study, a comparison between the static model and our approach based on experimental data is presented and it is shown that our approach achieves higher prediction accuracy. PMID:24688429

Development of an engineering analysis of progressive damage in composites during low velocity impact

NASA Technical Reports Server (NTRS)

Humphreys, E. A.

1981-01-01

A computerized, analytical methodology was developed to study damage accumulation during low velocity lateral impact of layered composite plates. The impact event was modeled as perfectly plastic with complete momentum transfer to the plate structure. A transient dynamic finite element approach was selected to predict the displacement time response of the plate structure. Composite ply and interlaminar stresses were computed at selected time intervals and subsequently evaluated to predict layer and interlaminar damage. The effects of damage on elemental stiffness were then incorporated back into the analysis for subsequent time steps. Damage predicted included fiber failure, matrix ply failure and interlaminar delamination.

A unified approach for composite cost reporting and prediction in the ACT program

NASA Technical Reports Server (NTRS)

Freeman, W. Tom; Vosteen, Louis F.; Siddiqi, Shahid

1991-01-01

The Structures Technology Program Office (STPO) at NASA Langley Research Center has held two workshops with representatives from the commercial airframe companies to establish a plan for development of a standard cost reporting format and a cost prediction tool for conceptual and preliminary designers. This paper reviews the findings of the workshop representatives with a plan for implementation of their recommendations. The recommendations of the cost tracking and reporting committee will be implemented by reinstituting the collection of composite part fabrication data in a format similar to the DoD/NASA Structural Composites Fabrication Guide. The process of data collection will be automated by taking advantage of current technology with user friendly computer interfaces and electronic data transmission. Development of a conceptual and preliminary designers' cost prediction model will be initiated. The model will provide a technically sound method for evaluating the relative cost of different composite structural designs, fabrication processes, and assembly methods that can be compared to equivalent metallic parts or assemblies. The feasibility of developing cost prediction software in a modular form for interfacing with state of the art preliminary design tools and computer aided design (CAD) programs is assessed.

Impact of MODIS High-Resolution Sea-Surface Temperatures on WRF Forecasts at NWS Miami, FL

NASA Technical Reports Server (NTRS)

Case, Jonathan L.; LaCasse, Katherine M.; Dembek, Scott R.; Santos, Pablo; Lapenta, William M.

2007-01-01

Over the past few years,studies at the Short-term Prediction Research and Transition (SPoRT) Center have suggested that the use of Moderate Resolution Imaging Spectroradiometer (MODIS) composite sea-surface temperature (SST) products in regional weather forecast models can have a significant positive impact on short-term numerical weather prediction in coastal regions. The recent paper by LaCasse et al. (2007, Monthly Weather Review) highlights lower atmospheric differences in regional numerical simulations over the Florida offshore waters using 2-km SST composites derived from the MODIS instrument aboard the polar-orbiting Aqua and Terra Earth Observing System satellites. To help quantify the value of this impact on NWS Weather Forecast Offices (WFOs), the SPoRT Center and the NWS WFO at Miami, FL (MIA) are collaborating on a project to investigate the impact of using the high-resolution MODIS SST fields within the Weather Research and Forecasting (WRF) prediction system. The scientific hypothesis being tested is: More accurate specification of the lower-boundary forcing within WRF will result in improved land/sea fluxes and hence, more accurate evolution of coastal mesoscale circulations and the associated sensible weather elements. The NWS MIA is currently running the WRF system in real-time to support daily forecast operations, using the National Centers for Environmental Prediction Nonhydrostatic Mesoscale Model dynamical core within the NWS Science and Training Resource Center's Environmental Modeling System (EMS) software; The EMS is a standalone modeling system capable of downloading the necessary daily datasets, and initializing, running and displaying WRF forecasts in the NWS Advanced Weather Interactive Processing System (AWIPS) with little intervention required by forecasters. Twenty-seven hour forecasts are run daily with start times of 0300,0900, 1500, and 2100 UTC on a domain with 4-km grid spacing covering the southern half of Florida and the far western portions of the Bahamas, the Florida Keys, the Straights of Florida, and adjacent waters of the Gulf of Mexico and Atlantic Ocean. Each model run is initialized using the Local Analysis and Prediction System (LAPS) analyses available in AWIPS, invoking the diabatic. "hot-start" capability. In this WRF model "hot-start", the LAPS-analyzed cloud and precipitation features are converted into model microphysics fields with enhanced vertical velocity profiles, effectively reducing the model spin-up time required to predict precipitation systems. The SSTs are initialized with the NCEP Real-Time Global (RTG) analyses at l/12 degree resolution (approx. 9 km); however, the RTG product does not exhibit fine-scale details consistent with its grid resolution. SPoRT is conducting parallel WRF EMS runs identical to the operational runs at NWS MIA in every respect except for the use of MODIS SST composites in place of the RTG product as the initial and boundary conditions over water. The MODIS SST composites for initializing the SPoRT WRF runs are generated on a 2-km grid four times daily at 0400, 0700, 1600, and 1900 UTC, based on the times of the overhead passes of the Aqua and Terra satellites. The incorporation of the MODIS SST composites into the SPoRTWRF runs is staggered such that the 0400UTC composite initializes the 0900 UTC WRF, the 0700 UTC composite initializes the 1500 UTC WRF, the 1600 UTC composite initializes the 2100 UTC WRF, and the 1900 UTC composite initializes the 0300 UTC WRF. A comparison of the SPoRT and Miami forecasts is underway in 2007, and includes quantitative verification of near-surface temperature, dewpoint, and wind forecasts at surface observation locations. In addition, particular days of interest are being analyzed to determine the impact of the MODIS SST data on the development and evolution of predicted sea/land-breeze circulations, clouds, and precipitation. This paper will present verification results comparing the NWS MIA forecasts the SPoRT experimental WRF forecasts, and highlight any substantial differences noted in the predicted mesoscale phenomena.

A comparison of analysis tools for predicting the inelastic cyclic response of cross-ply titanium matrix composites

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

Kroupa, J.L.; Coker, D.; Neu, R.W.

1996-12-31

Several micromechanical models that are currently being used for predicting the thermal and mechanical behavior of a cross-ply, [0/90], titanium matrix composite are evaluated. Six computer programs or methods are compared: (1) VISCOPLY; (2) METCAN; (3) FIDEP, an enhanced concentric cylinder model; (4) LISOL, a modified method of cells approach; (5) an elementary approach where the [90] ply is assumed to have the same properties as the matrix; and (6) a finite element method. Comparisons are made for the thermal residual stresses at room temperature resulting from processing, as well as for stresses and strains in two isothermal and twomore » thermomechanical fatigue test cases. For each case, the laminate response of the models is compared to experimental behavior, while the responses of the constituents are compared among the models. The capability of each model to predict frequency effects, inelastic cyclic strain (hysteresis) behavior, and strain ratchetting with cycling is shown. The basis of formulation for the micromechanical models, the constitutive relationships used for the matrix and fiber, and the modeling technique of the [90] ply are all found to be important factors for determining the accurate behavior of the [0/90] composite.« less

Analytical model for force prediction when machining metal matrix composites

NASA Astrophysics Data System (ADS)

Sikder, Snahungshu

Metal Matrix Composites (MMC) offer several thermo-mechanical advantages over standard materials and alloys which make them better candidates in different applications. Their light weight, high stiffness, and strength have attracted several industries such as automotive, aerospace, and defence for their wide range of products. However, the wide spread application of Meal Matrix Composites is still a challenge for industry. The hard and abrasive nature of the reinforcement particles is responsible for rapid tool wear and high machining costs. Fracture and debonding of the abrasive reinforcement particles are the considerable damage modes that directly influence the tool performance. It is very important to find highly effective way to machine MMCs. So, it is important to predict forces when machining Metal Matrix Composites because this will help to choose perfect tools for machining and ultimately save both money and time. This research presents an analytical force model for predicting the forces generated during machining of Metal Matrix Composites. In estimating the generated forces, several aspects of cutting mechanics were considered including: shearing force, ploughing force, and particle fracture force. Chip formation force was obtained by classical orthogonal metal cutting mechanics and the Johnson-Cook Equation. The ploughing force was formulated while the fracture force was calculated from the slip line field theory and the Griffith theory of failure. The predicted results were compared with previously measured data. The results showed very good agreement between the theoretically predicted and experimentally measured cutting forces.

Evaluation of a Mathematical Model of Rat Body Weight Regulation in Application to Caloric Restriction and Drug Treatment Studies.

PubMed

Selimkhanov, Jangir; Thompson, W Clayton; Patterson, Terrell A; Hadcock, John R; Scott, Dennis O; Maurer, Tristan S; Musante, Cynthia J

2016-01-01

The purpose of this work is to develop a mathematical model of energy balance and body weight regulation that can predict species-specific response to common pre-clinical interventions. To this end, we evaluate the ability of a previously published mathematical model of mouse metabolism to describe changes in body weight and body composition in rats in response to two short-term interventions. First, we adapt the model to describe body weight and composition changes in Sprague-Dawley rats by fitting to data previously collected from a 26-day caloric restriction study. The calibrated model is subsequently used to describe changes in rat body weight and composition in a 23-day cannabinoid receptor 1 antagonist (CB1Ra) study. While the model describes body weight data well, it fails to replicate body composition changes with CB1Ra treatment. Evaluation of a key model assumption about deposition of fat and fat-free masses shows a limitation of the model in short-term studies due to the constraint placed on the relative change in body composition components. We demonstrate that the model can be modified to overcome this limitation, and propose additional measurements to further test the proposed model predictions. These findings illustrate how mathematical models can be used to support drug discovery and development by identifying key knowledge gaps and aiding in the design of additional experiments to further our understanding of disease-relevant and species-specific physiology.

Evaluation of a Mathematical Model of Rat Body Weight Regulation in Application to Caloric Restriction and Drug Treatment Studies

PubMed Central

Selimkhanov, Jangir; Patterson, Terrell A.; Scott, Dennis O.; Maurer, Tristan S.; Musante, Cynthia J.

2016-01-01

The purpose of this work is to develop a mathematical model of energy balance and body weight regulation that can predict species-specific response to common pre-clinical interventions. To this end, we evaluate the ability of a previously published mathematical model of mouse metabolism to describe changes in body weight and body composition in rats in response to two short-term interventions. First, we adapt the model to describe body weight and composition changes in Sprague-Dawley rats by fitting to data previously collected from a 26-day caloric restriction study. The calibrated model is subsequently used to describe changes in rat body weight and composition in a 23-day cannabinoid receptor 1 antagonist (CB1Ra) study. While the model describes body weight data well, it fails to replicate body composition changes with CB1Ra treatment. Evaluation of a key model assumption about deposition of fat and fat-free masses shows a limitation of the model in short-term studies due to the constraint placed on the relative change in body composition components. We demonstrate that the model can be modified to overcome this limitation, and propose additional measurements to further test the proposed model predictions. These findings illustrate how mathematical models can be used to support drug discovery and development by identifying key knowledge gaps and aiding in the design of additional experiments to further our understanding of disease-relevant and species-specific physiology. PMID:27227543

In Situ Strength Model for Continuous Fibers and Multi-Scale Modeling the Fracture of C/SiC Composites

NASA Astrophysics Data System (ADS)

Zhang, Sheng; Gao, Xiguang; Song, Yingdong

2018-04-01

A new in situ strength model of carbon fibers was developed based on the distribution of defects to predict the stress-strain response and the strength of C/SiC composites. Different levels of defects in the fibers were considered in this model. The defects in the fibers were classified by their effects on the strength of the fiber. The strength of each defect and the probability that the defect appears were obtained from the tensile test of single fibers. The strength model of carbon fibers was combined with the shear-lag model to predict the stress-strain responses and the strengths of fiber bundles and C/SiC minicomposites. To verify the strength model, tensile tests were performed on fiber bundles and C/SiC minicomposites. The predicted and experimental results were in good agreement. Effects of the fiber length, the fiber number and the heat treatment on the final strengths of fiber bundles and C/SiC minicomposites were also discussed.

Modeling the shape and composition of the human body using dual energy X-ray absorptiometry images

PubMed Central

Shepherd, John A.; Fan, Bo; Schwartz, Ann V.; Cawthon, Peggy; Cummings, Steven R.; Kritchevsky, Stephen; Nevitt, Michael; Santanasto, Adam; Cootes, Timothy F.

2017-01-01

There is growing evidence that body shape and regional body composition are strong indicators of metabolic health. The purpose of this study was to develop statistical models that accurately describe holistic body shape, thickness, and leanness. We hypothesized that there are unique body shape features that are predictive of mortality beyond standard clinical measures. We developed algorithms to process whole-body dual-energy X-ray absorptiometry (DXA) scans into body thickness and leanness images. We performed statistical appearance modeling (SAM) and principal component analysis (PCA) to efficiently encode the variance of body shape, leanness, and thickness across sample of 400 older Americans from the Health ABC study. The sample included 200 cases and 200 controls based on 6-year mortality status, matched on sex, race and BMI. The final model contained 52 points outlining the torso, upper arms, thighs, and bony landmarks. Correlation analyses were performed on the PCA parameters to identify body shape features that vary across groups and with metabolic risk. Stepwise logistic regression was performed to identify sex and race, and predict mortality risk as a function of body shape parameters. These parameters are novel body composition features that uniquely identify body phenotypes of different groups and predict mortality risk. Three parameters from a SAM of body leanness and thickness accurately identified sex (training AUC = 0.99) and six accurately identified race (training AUC = 0.91) in the sample dataset. Three parameters from a SAM of only body thickness predicted mortality (training AUC = 0.66, validation AUC = 0.62). Further study is warranted to identify specific shape/composition features that predict other health outcomes. PMID:28423041

Durability and Damage Tolerance of High Temperature Polymeric Composites

NASA Technical Reports Server (NTRS)

Case, Scott W.; Reifsnider, Kenneth L.

1996-01-01

Modern durability and damage tolerance predictions for composite material systems rely on accurate estimates of the local stress and material states for each of the constituents, as well as the manner in which the constituents interact. In this work, an number of approaches to estimating the stress states and interactions are developed. First, an elasticity solution is presented for the problem of a penny-shaped crack in an N-phase composite material system opened by a prescribed normal pressure. The stress state around such a crack is then used to estimate the stress concentrations due to adjacent fiber fractures in composite materials. The resulting stress concentrations are then used to estimate the tensile strength of the composite. The predicted results are compared with experimental values. In addition, a cumulative damage model for fatigue is presented. Modifications to the model are made to include the effects of variable amplitude loading. These modifications are based upon the use of remaining strength as a damage metric and the definition of an equivalent generalized time. The model is initially validated using results from the literature. Also, experimental data from APC-2 laminates and IM7/K3B laminates are used in the model. The use of such data for notched laminates requires the use of an effective hole size, which is calculated based upon strain distribution measurements. Measured remaining strengths after fatigue loading are compared with the predicted values for specimens fatigued at room temperature and 350 F (177 C).

Equivalent parameter model of 1-3 piezocomposite with a sandwich polymer

NASA Astrophysics Data System (ADS)

Zhang, Yanjun; Wang, Likun; Qin, Lei

2018-06-01

A theoretical model was developed to investigate the performance of 1-3 piezoelectric composites with a sandwich polymer. Effective parameters, such as the electromechanical coupling factor, longitudinal velocity, and characteristic acoustic impedance of the piezocomposite, were predicted using the developed model. The influences of volume fractions and components of the polymer phase on the effective parameters of the piezoelectric composite were studied. The theoretical model was verified experimentally. The proposed model can reproduce the effective parameters of 1-3 piezoelectric composites with a sandwich polymer in the thickness mode. The measured electromechanical coupling factor was improved by more than 9.8% over the PZT/resin 1-3 piezoelectric composite.

A life prediction model for laminated composite structural components

NASA Technical Reports Server (NTRS)

Allen, David H.

1990-01-01

A life prediction methodology for laminated continuous fiber composites subjected to fatigue loading conditions was developed. A summary is presented of research completed. A phenomenological damage evolution law was formulated for matrix cracking which is independent of stacking sequence. Mechanistic and physical support was developed for the phenomenological evolution law proposed above. The damage evolution law proposed above was implemented to a finite element computer program. And preliminary predictions were obtained for a structural component undergoing fatigue loading induced damage.

FIBER ORIENTATION IN INJECTION MOLDED LONG CARBON FIBER THERMOPLASTIC COMPOSITES

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

Wang, Jin; Nguyen, Ba Nghiep; Mathur, Raj N.

2015-03-23

A set of edge-gated and center-gated plaques were injection molded with long carbon fiber-reinforced thermoplastic composites, and the fiber orientation was measured at different locations of the plaques. Autodesk Simulation Moldflow Insight (ASMI) software was used to simulate the injection molding of these plaques and to predict the fiber orientation, using the anisotropic rotary diffusion and the reduced strain closure models. The phenomenological parameters of the orientation models were carefully identified by fitting to the measured orientation data. The fiber orientation predictions show very good agreement with the experimental data.

Comparative study of solvation parameter models accounting the effects of mobile phase composition in reversed-phase liquid chromatography.

PubMed

Torres-Lapasió, J R; Ruiz-Angel, M J; García-Alvarez-Coque, M C

2007-09-28

Solvation parameter models relate linearly compound properties with five fundamental solute descriptors (excess molar refraction, dipolarity/polarizability, effective hydrogen-bond acidity and basicity, and McGowan volume). These models are widely used, due to the availability of protocols to obtain the descriptors, good performance, and general applicability. Several approaches to predict retention in reversed-phase liquid chromatography (RPLC) as a function of these descriptors and mobile phase composition are compared, assaying the performance with a set of 146 organic compounds of diverse nature, eluted with acetonitrile and methanol. The approaches are classified in two groups: those that only allow predictions of retention for the mobile phases used to build the models, and those valid at any other mobile phase composition. The first group includes the use of ratios between the regressed coefficients of the solvation models that are assumed to be characteristic for a column/solvent system, and the application of offsets to transfer the retention from a reference mobile phase to any other. Maximal accuracy in predictions corresponded, however, to the approaches in the second group, which were based on models that describe the retention as a function of mobile phase composition (expressed as the solvent volume fraction or a normalised polarity measurement), where the coefficients were made dependent on the solvent descriptors. The study revealed the properties that influence the retention and distinguish the particular behaviour of acetonitrile and methanol in RPLC.

Interactions of elevation, aspect, and slope in models of forest species composition and productivity

Treesearch

Albert R. Stage; Christian Salas

2007-01-01

We present a linear model for the interacting effects of elevation, aspect, and slope for use in predicting forest productivity or species composition. The model formulation we propose integrates interactions of these three factors in a mathematical expression representing their combined effect in terms of a cosine function of aspect with a phase shift and amplitude...

Metabolic Model-Based Integration of Microbiome Taxonomic and Metabolomic Profiles Elucidates Mechanistic Links between Ecological and Metabolic Variation.

PubMed

Noecker, Cecilia; Eng, Alexander; Srinivasan, Sujatha; Theriot, Casey M; Young, Vincent B; Jansson, Janet K; Fredricks, David N; Borenstein, Elhanan

2016-01-01

Multiple molecular assays now enable high-throughput profiling of the ecology, metabolic capacity, and activity of the human microbiome. However, to date, analyses of such multi-omic data typically focus on statistical associations, often ignoring extensive prior knowledge of the mechanisms linking these various facets of the microbiome. Here, we introduce a comprehensive framework to systematically link variation in metabolomic data with community composition by utilizing taxonomic, genomic, and metabolic information. Specifically, we integrate available and inferred genomic data, metabolic network modeling, and a method for predicting community-wide metabolite turnover to estimate the biosynthetic and degradation potential of a given community. Our framework then compares variation in predicted metabolic potential with variation in measured metabolites' abundances to evaluate whether community composition can explain observed shifts in the community metabolome, and to identify key taxa and genes contributing to the shifts. Focusing on two independent vaginal microbiome data sets, each pairing 16S community profiling with large-scale metabolomics, we demonstrate that our framework successfully recapitulates observed variation in 37% of metabolites. Well-predicted metabolite variation tends to result from disease-associated metabolism. We further identify several disease-enriched species that contribute significantly to these predictions. Interestingly, our analysis also detects metabolites for which the predicted variation negatively correlates with the measured variation, suggesting environmental control points of community metabolism. Applying this framework to gut microbiome data sets reveals similar trends, including prediction of bile acid metabolite shifts. This framework is an important first step toward a system-level multi-omic integration and an improved mechanistic understanding of the microbiome activity and dynamics in health and disease. Studies characterizing both the taxonomic composition and metabolic profile of various microbial communities are becoming increasingly common, yet new computational methods are needed to integrate and interpret these data in terms of known biological mechanisms. Here, we introduce an analytical framework to link species composition and metabolite measurements, using a simple model to predict the effects of community ecology on metabolite concentrations and evaluating whether these predictions agree with measured metabolomic profiles. We find that a surprisingly large proportion of metabolite variation in the vaginal microbiome can be predicted based on species composition (including dramatic shifts associated with disease), identify putative mechanisms underlying these predictions, and evaluate the roles of individual bacterial species and genes. Analysis of gut microbiome data using this framework recovers similar community metabolic trends. This framework lays the foundation for model-based multi-omic integrative studies, ultimately improving our understanding of microbial community metabolism.

Metabolic Model-Based Integration of Microbiome Taxonomic and Metabolomic Profiles Elucidates Mechanistic Links between Ecological and Metabolic Variation

PubMed Central

Noecker, Cecilia; Eng, Alexander; Srinivasan, Sujatha; Theriot, Casey M.; Young, Vincent B.; Jansson, Janet K.; Fredricks, David N.

2016-01-01

ABSTRACT Multiple molecular assays now enable high-throughput profiling of the ecology, metabolic capacity, and activity of the human microbiome. However, to date, analyses of such multi-omic data typically focus on statistical associations, often ignoring extensive prior knowledge of the mechanisms linking these various facets of the microbiome. Here, we introduce a comprehensive framework to systematically link variation in metabolomic data with community composition by utilizing taxonomic, genomic, and metabolic information. Specifically, we integrate available and inferred genomic data, metabolic network modeling, and a method for predicting community-wide metabolite turnover to estimate the biosynthetic and degradation potential of a given community. Our framework then compares variation in predicted metabolic potential with variation in measured metabolites’ abundances to evaluate whether community composition can explain observed shifts in the community metabolome, and to identify key taxa and genes contributing to the shifts. Focusing on two independent vaginal microbiome data sets, each pairing 16S community profiling with large-scale metabolomics, we demonstrate that our framework successfully recapitulates observed variation in 37% of metabolites. Well-predicted metabolite variation tends to result from disease-associated metabolism. We further identify several disease-enriched species that contribute significantly to these predictions. Interestingly, our analysis also detects metabolites for which the predicted variation negatively correlates with the measured variation, suggesting environmental control points of community metabolism. Applying this framework to gut microbiome data sets reveals similar trends, including prediction of bile acid metabolite shifts. This framework is an important first step toward a system-level multi-omic integration and an improved mechanistic understanding of the microbiome activity and dynamics in health and disease. IMPORTANCE Studies characterizing both the taxonomic composition and metabolic profile of various microbial communities are becoming increasingly common, yet new computational methods are needed to integrate and interpret these data in terms of known biological mechanisms. Here, we introduce an analytical framework to link species composition and metabolite measurements, using a simple model to predict the effects of community ecology on metabolite concentrations and evaluating whether these predictions agree with measured metabolomic profiles. We find that a surprisingly large proportion of metabolite variation in the vaginal microbiome can be predicted based on species composition (including dramatic shifts associated with disease), identify putative mechanisms underlying these predictions, and evaluate the roles of individual bacterial species and genes. Analysis of gut microbiome data using this framework recovers similar community metabolic trends. This framework lays the foundation for model-based multi-omic integrative studies, ultimately improving our understanding of microbial community metabolism. PMID:27239563

Relationships between nutrient composition of flowers and fruit quality in orange trees grown in calcareous soil.

PubMed

Pestana, Maribela; Beja, Pedro; Correia, Pedro José; de Varennes, Amarilis; Faria, Eugénio Araújo

2005-06-01

To determine if flower nutrient composition can be used to predict fruit quality, a field experiment was conducted over three seasons (1996-1999) in a commercial orange orchard (Citrus sinensis (L.) Osbeck cv. 'Valencia Late', budded on Troyer citrange rootstock) established on a calcareous soil in southern Portugal. Flowers were collected from 20 trees during full bloom in April and their nutrient composition determined, and fruits were harvested the following March and their quality evaluated. Patterns of covariation in flower nutrient concentrations and in fruit quality variables were evaluated by principal component analysis. Regression models relating fruit quality variables to flower nutrient composition were developed by stepwise selection procedures. The predictive power of the regression models was evaluated with an independent data set. Nutrient composition of flowers at full bloom could be used to predict the fruit quality variables fresh fruit mass and maturation index in the following year. Magnesium, Ca and Zn concentrations measured in flowers were related to fruit fresh mass estimations and N, P, Mg and Fe concentrations were related to fruit maturation index. We also established reference values for the nutrient composition of flowers based on measurements made in trees that produced large (> 76 mm in diameter) fruit.

Dynamic modelling of solids in a full-scale activated sludge plant preceded by CEPT as a preliminary step for micropollutant removal modelling.

PubMed

Baalbaki, Zeina; Torfs, Elena; Maere, Thomas; Yargeau, Viviane; Vanrolleghem, Peter A

2017-04-01

The presence of micropollutants in the environment has triggered research on quantifying and predicting their fate in wastewater treatment plants (WWTPs). Since the removal of micropollutants is highly related to conventional pollutant removal and affected by hydraulics, aeration, biomass composition and solids concentration, the fate of these conventional pollutants and characteristics must be well predicted before tackling models to predict the fate of micropollutants. In light of this, the current paper presents the dynamic modelling of conventional pollutants undergoing activated sludge treatment using a limited set of additional daily composite data besides the routine data collected at a WWTP over one year. Results showed that as a basis for modelling, the removal of micropollutants, the Bürger-Diehl settler model was found to capture the actual effluent total suspended solids (TSS) concentrations more efficiently than the Takács model by explicitly modelling the overflow boundary. Results also demonstrated that particular attention must be given to characterizing incoming TSS to obtain a representative solids balance in the presence of a chemically enhanced primary treatment, which is key to predict the fate of micropollutants.

A Bayesian Performance Prediction Model for Mathematics Education: A Prototypical Approach for Effective Group Composition

ERIC Educational Resources Information Center

Bekele, Rahel; McPherson, Maggie

2011-01-01

This research work presents a Bayesian Performance Prediction Model that was created in order to determine the strength of personality traits in predicting the level of mathematics performance of high school students in Addis Ababa. It is an automated tool that can be used to collect information from students for the purpose of effective group…

Large-Scale Aerosol Modeling and Analysis

DTIC Science & Technology

2008-09-30

novel method of simultaneous real- time measurements of ice-nucleating particle concentrations and size- resolved chemical composition of individual...is to develop a practical predictive capability for visibility and weather effects of aerosol particles for the entire globe for timely use in...prediction follows that used in numerical weather prediction, namely real- time assessment for initialization of first-principles models. The Naval

The Inclusion of Arbitrary Load Histories in the Strength Decay Model for Stress Rupture

NASA Technical Reports Server (NTRS)

Reeder, James R.

2014-01-01

Stress rupture is a failure mechanism where failures can occur after a period of time, even though the material has seen no increase in load. Carbon/epoxy composite materials have demonstrated the stress rupture failure mechanism. In a previous work, a model was proposed for stress rupture of composite overwrap pressure vessels (COPVs) and similar composite structures based on strength degradation. However, the original model was limited to constant load periods (holds) at constant load. The model was expanded in this paper to address arbitrary loading histories and specifically the inclusions of ramp loadings up to holds and back down. The broadening of the model allows for failures on loading to be treated as any other failure that may occur during testing instead of having to be treated as a special case. The inclusion of ramps can also influence the length of the "safe period" following proof loading that was previously predicted by the model. No stress rupture failures are predicted in a safe period because time is required for strength to decay from above the proof level to the lower level of loading. Although the model can predict failures during the ramp periods, no closed-form solution for the failure times could be derived. Therefore, two suggested solution techniques were proposed. Finally, the model was used to design an experiment that could detect the difference between the strength decay model and a commonly used model for stress rupture. Although these types of models are necessary to help guide experiments for stress rupture, only experimental evidence will determine how well the model may predict actual material response. If the model can be shown to be accurate, current proof loading requirements may result in predicted safe periods as long as 10(13) years. COPVs design requirements for stress rupture may then be relaxed, allowing more efficient designs, while still maintaining an acceptable level of safety.

Mapping Plant Diversity and Composition Across North Carolina Piedmont Forest Landscapes Using Lidar-Hyperspectral Remote Sensing

NASA Astrophysics Data System (ADS)

Hakkenberg, Christopher R.

Forest modification, from local stress to global change, has given rise to efforts to model, map, and monitor critical properties of forest communities like structure, composition, and diversity. Predictive models based on data from spatially-nested field plots and LiDAR-hyperspectral remote sensing systems are one particularly effective means towards the otherwise prohibitively resource-intensive task of consistently characterizing forest community dynamics at landscape scales. However, to date, most predictive models fail to account for actual (rather than idealized) species and community distributions, are unsuccessful in predicting understory components in structurally and taxonomically heterogeneous forests, and may suffer from diminished predictive accuracy due to incongruity in scale and precision between field plot samples, remotely-sensed data, and target biota of varying size and density. This three-part study addresses these and other concerns in the modeling and mapping of emergent properties of forest communities by shifting the scope of prediction from the individual or taxon to the whole stand or community. It is, after all, at the stand scale where emergent properties like functional processes, biodiversity, and habitat aggregate and manifest. In the first study, I explore the relationship between forest structure (a proxy for successional demographics and resource competition) and tree species diversity in the North Carolina Piedmont, highlighting the empirical basis and potential for utilizing forest structure from LiDAR in predictive models of tree species diversity. I then extend these conclusions to map landscape pattern in multi-scale vascular plant diversity as well as turnover in community-continua at varying compositional resolutions in a North Carolina Piedmont landscape using remotely-sensed LiDAR-hyperspectral estimates of topography, canopy structure, and foliar biochemistry. Recognizing that the distinction between correlation and causation mirrors that between knowledge and understanding, all three studies distinguish between prediction of pattern and inference of process. Thus, in addition to advancing mapping methodologies relevant to a range of forest ecosystem management and monitoring applications, all three studies are noteworthy for assessing the ecological relationship between environmental predictors and emergent landscape patterns in plant composition and diversity in North Carolina Piedmont forests.

A Non-Arrhenian Viscosity Model for Natural Silicate Melts with Applications to Volcanology

NASA Astrophysics Data System (ADS)

Russell, J. K.; Giordano, D.; Dingwell, D. B.

2005-12-01

Silicate melt viscosity is the most important physical property in volcanic systems. It governs styles and rates of flow, velocity distributions in flowing magma, rates of vesiculation, and, ultimately, sets limits on coherent(vs. fragmented or disrupted) flow. The prediction of melt viscosity over the range of conditions found on terrestrial planets remains a challenge. However, the extraordinary increase in number and quality of published measurements of melt viscosity suggests the possibility of new models. Here we review the attributes of previous models for silicate melt viscosity and, then, present a new predictive model natural silicate melts. The importance of silicate melt viscosity was recognized early [1] and culminated in 2 models for predicting silicate melt viscosity [2,3]. These models used an Arrhenian T-dependence; they were limited by a limited experimental database dominated by high-T measurements. Subsequent models have aimed to: i) extend the compositional range of Arrhenian T-dependent models [4,5]; ii) to develop non-Arrhenian models for limited ranges of composition [6,7,8], iii) to develop new strategies for modelling the composition and T-dependence of viscosity [9,10,11], and, finally, to create chemical models for the non-Arrhenian T-dependence of natural melts [12]. We present a multicomponent model for the compositional and T dependence of silicate melt viscosity based on data spanning a wide range of anhydrous melt compositions. The experimental data include micropenetration and concentric cylinder viscometry measurements covering a viscosity range of 10-1 to 1012 Pa s and a T-range from 700 to 1650°C. These published data provide a high- quality database comprising ~ 800 experimental data on 44 well-characterized melt compositions. Our model uses the Adam-Gibbs equation to capture T-dependence: log η = A + B/[T · log (T/C)] where A, B, and C are adjustable parameters that vary for different melt compositions. We assume that all silicate melts converge to a common, but unknown, high-T limit (e.g., A) and that all compositional dependence is accommodated for by B and C. We adopt a linear compositional dependence for B and C: B = σi=1..n [xi βi] C = σi=1..n [xi γi] where xi's are the mole fractions of oxide components (n=8) and βi and γi are adjustable parameters. The model, therefore, comprises 2 · n+1 adjustable parameters which are optimized for against the experimental database including a common value of A and compositional coefficeints for B and C. The new model reproduces the original database to within experimental uncertainty and can predict the viscosity of silicate melts across the full range of conditions found in Nature. References Cited: [1] Friedman et al., 1963. J Geophys Res 68, 6523-6535. [2] Bottinga Y & Weill D 1972. Am J Sci 272, 438- 475. [3] Shaw HR 1972. Am J Sci 272, 438- 475. [4] Persikov ES 1991. Adv Phys Geochem 9, 1-40. [5] Prusevich AA 1988. Geol Geofiz 29, 67-69. [6] Baker DR 1996. Am Min 81, 126-134. [7] Hess KU & Dingwell DB 1996. Am Min 81, 1297- 1300. [8] Zhang, et al. 2003. Am min 88, 1741- 1752. [9] Russell et al. 2002. Eur J Min 14, 417-428. [10] Russell et al. 2003. Am Min 8, 1390- 1394. [11] Russell JK & Giordano D In Press. Geochim Cosmochim Acta. [12] Giordano D & Dingwell DB 2003. Earth Planet. Sci. Lett. 208, 337-349.

Nonlinear and progressive failure aspects of transport composite fuselage damage tolerance

NASA Technical Reports Server (NTRS)

Walker, Tom; Ilcewicz, L.; Murphy, Dan; Dopker, Bernhard

1993-01-01

The purpose is to provide an end-user's perspective on the state of the art in life prediction and failure analysis by focusing on subsonic transport fuselage issues being addressed in the NASA/Boeing Advanced Technology Composite Aircraft Structure (ATCAS) contract and a related task-order contract. First, some discrepancies between the ATCAS tension-fracture test database and classical prediction methods is discussed, followed by an overview of material modeling work aimed at explaining some of these discrepancies. Finally, analysis efforts associated with a pressure-box test fixture are addressed, as an illustration of modeling complexities required to model and interpret tests.

Empirical Model Development for Predicting Shock Response on Composite Materials Subjected to Pyroshock Loading. Volume 2, Part 1; Appendices

NASA Technical Reports Server (NTRS)

Gentz, Steven J.; Ordway, David O.; Parsons, David S.; Garrison, Craig M.; Rodgers, C. Steven; Collins, Brian W.

2015-01-01

The NASA Engineering and Safety Center (NESC) received a request to develop an analysis model based on both frequency response and wave propagation analyses for predicting shock response spectrum (SRS) on composite materials subjected to pyroshock loading. The model would account for near-field environment (approximately 9 inches from the source) dominated by direct wave propagation, mid-field environment (approximately 2 feet from the source) characterized by wave propagation and structural resonances, and far-field environment dominated by lower frequency bending waves in the structure. This document contains appendices to the Volume I report.

Fully Coupled Micro/Macro Deformation, Damage, and Failure Prediction for SiC/Ti-15-3 Laminates

NASA Technical Reports Server (NTRS)

Bednarcyk, Brett A.; Arnold, Steven M.; Lerch, Brad A.

2001-01-01

The deformation, failure, and low cycle fatigue life of SCS-6/Ti-15-3 composites are predicted using a coupled deformation and damage approach in the context of the analytical generalized method of cells (GMC) micromechanics model. The local effects of inelastic deformation, fiber breakage, fiber-matrix interfacial debonding, and fatigue damage are included as sub-models that operate on the micro scale for the individual composite phases. For the laminate analysis, lamination theory is employed as the global or structural scale model, while GMC is embedded to operate on the meso scale to simulate the behavior of the composite material within each laminate layer. While the analysis approach is quite complex and multifaceted, it is shown, through comparison with experimental data, to be quite accurate and realistic while remaining extremely efficient.

Prediction of stock markets by the evolutionary mix-game model

NASA Astrophysics Data System (ADS)

Chen, Fang; Gou, Chengling; Guo, Xiaoqian; Gao, Jieping

2008-06-01

This paper presents the efforts of using the evolutionary mix-game model, which is a modified form of the agent-based mix-game model, to predict financial time series. Here, we have carried out three methods to improve the original mix-game model by adding the abilities of strategy evolution to agents, and then applying the new model referred to as the evolutionary mix-game model to forecast the Shanghai Stock Exchange Composite Index. The results show that these modifications can improve the accuracy of prediction greatly when proper parameters are chosen.

A New Local Failure Model with Application to the Longitudinal Tensile Behavior of Continuously Reinforced Titanium Composites

NASA Technical Reports Server (NTRS)

Bednarcyk, Brett A.; Arnold, Steven M.

2000-01-01

A new model for local fiber failures in composite materials loaded longitudinally is presented. In developing the model, the goal was to account for the effects of fiber breakage on the global response of a composite in a relatively simple and efficient manner. Towards this end, the model includes the important feature of local stress unloading, even as global loading of the composite continues. The model has been incorporated into NASA Glenn's Micromechanics Analysis Code with Generalized Method of Cells (MAC/GMC) and was employed to simulate the longitudinal tensile deformation and failure behavior of several silicon carbide fiber/titanium matrix (SiC/Ti) composites. The model is shown to be quite realistic and capable of accurate predictions for various temperatures, fiber volume fractions, and fiber diameters. Further- more, the new model compares favorably to Curtin's (1993) effective fiber breakage model, which has also been incorporated into MAC/GMC.

LS-DYNA Implementation of Polymer Matrix Composite Model Under High Strain Rate Impact

NASA Technical Reports Server (NTRS)

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.

On Complexities of Impact Simulation of Fiber Reinforced Polymer Composites: A Simplified Modeling Framework

PubMed Central

Alemi-Ardakani, M.; Milani, A. S.; Yannacopoulos, S.

2014-01-01

Impact modeling of fiber reinforced polymer composites is a complex and challenging task, in particular for practitioners with less experience in advanced coding and user-defined subroutines. Different numerical algorithms have been developed over the past decades for impact modeling of composites, yet a considerable gap often exists between predicted and experimental observations. In this paper, after a review of reported sources of complexities in impact modeling of fiber reinforced polymer composites, two simplified approaches are presented for fast simulation of out-of-plane impact response of these materials considering four main effects: (a) strain rate dependency of the mechanical properties, (b) difference between tensile and flexural bending responses, (c) delamination, and (d) the geometry of fixture (clamping conditions). In the first approach, it is shown that by applying correction factors to the quasistatic material properties, which are often readily available from material datasheets, the role of these four sources in modeling impact response of a given composite may be accounted for. As a result a rough estimation of the dynamic force response of the composite can be attained. To show the application of the approach, a twill woven polypropylene/glass reinforced thermoplastic composite laminate has been tested under 200 J impact energy and was modeled in Abaqus/Explicit via the built-in Hashin damage criteria. X-ray microtomography was used to investigate the presence of delamination inside the impacted sample. Finally, as a second and much simpler modeling approach it is shown that applying only a single correction factor over all material properties at once can still yield a reasonable prediction. Both advantages and limitations of the simplified modeling framework are addressed in the performed case study. PMID:25431787

Thermoplastic matrix composite processing model

NASA Technical Reports Server (NTRS)

Dara, P. H.; Loos, A. C.

1985-01-01

The effects the processing parameters pressure, temperature, and time have on the quality of continuous graphite fiber reinforced thermoplastic matrix composites were quantitatively accessed by defining the extent to which intimate contact and bond formation has occurred at successive ply interfaces. Two models are presented predicting the extents to which the ply interfaces have achieved intimate contact and cohesive strength. The models are based on experimental observation of compression molded laminates and neat resin conditions, respectively. Identified as the mechanism explaining the phenomenon by which the plies bond to themselves is the theory of autohesion (or self diffusion). Theoretical predictions from the Reptation Theory between autohesive strength and contact time are used to explain the effects of the processing parameters on the observed experimental strengths. The application of a time-temperature relationship for autohesive strength predictions is evaluated. A viscoelastic compression molding model of a tow was developed to explain the phenomenon by which the prepreg ply interfaces develop intimate contact.

Georgia Tech Vertical Lift Research Center of Excellence

DTIC Science & Technology

2017-12-14

Technical Project Summaries Task 1.1 (GT-1): Next Generation VABS for More Realistic Modeling of Composite Blades ...Methodology for the Prediction of Rotor Blade Ice Formation and Shedding ..................................................................... 20...software disclosures and technology transfer efforts. Task 1.1 (GT-1): Next Generation VABS for More Realistic Modeling of Composite Blades PIs

Competition for Resources: A Reexamination of Sibship Composition Models of Parental Investment

ERIC Educational Resources Information Center

Lee, Kristen Schultz

2009-01-01

The predictions of resource dilution and sibship gender composition models of educational investment are tested using the Japanese Nationwide Survey on Families (N = 6,985). Japan is an important case because of its postindustrial economy, coupled with high levels of dependence on parental investment to attend a university and persisting gender…

Using Indigenous Materials for Construction

DTIC Science & Technology

2015-07-01

Theoretical models were devised for prediction of the structural attributes of indigenous ferrocement sheets and sandwich composite panels comprising the...indigenous ferrocement skins and aerated concrete core. Structural designs were developed for these indigenous sandwich composite panels in typical...indigenous materials and building systems developed in the project were evaluated. Numerical modeling capabilities were developed for structural

Creep and stress relaxation modeling of polycrystalline ceramic fibers

NASA Technical Reports Server (NTRS)

Dicarlo, James A.; Morscher, Gregory N.

1994-01-01

A variety of high performance polycrystalline ceramic fibers are currently being considered as reinforcement for high temperature ceramic matrix composites. However, under mechanical loading about 800 C, these fibers display creep related instabilities which can result in detrimental changes in composite dimensions, strength, and internal stress distributions. As a first step toward understanding these effects, this study examines the validity of a mechanism-based empirical model which describes primary stage tensile creep and stress relaxation of polycrystalline ceramic fibers as independent functions of time, temperature, and applied stress or strain. To verify these functional dependencies, a simple bend test is used to measure stress relaxation for four types of commercial ceramic fibers for which direct tensile creep data are available. These fibers include both nonoxide (SCS-6, Nicalon) and oxide (PRD-166, FP) compositions. The results of the Bend Stress Relaxation (BSR) test not only confirm the stress, time, and temperature dependencies predicted by the model, but also allow measurement of model empirical parameters for the four fiber types. In addition, comparison of model tensile creep predictions based on the BSR test results with the literature data show good agreement, supporting both the predictive capability of the model and the use of the BSR text as a simple method for parameter determination for other fibers.

Creep and stress relaxation modeling of polycrystalline ceramic fibers

NASA Technical Reports Server (NTRS)

Dicarlo, James A.; Morscher, Gregory N.

1991-01-01

A variety of high performance polycrystalline ceramic fibers are currently being considered as reinforcement for high temperature ceramic matrix composites. However, under mechanical loading above 800 C, these fibers display creep-related instabilities which can result in detrimental changes in composite dimensions, strength, and internal stress distributions. As a first step toward understanding these effects, this study examines the validity of mechanistic-based empirical model which describes primary stage tensile creep and stress relaxation of polycrystalline ceramic fibers as independent functions of time, temperature, and applied stress or strain. To verify these functional dependencies, a simple bend test is used to measure stress relaxation for four types of commercial ceramic fibers for which direct tensile creep data are available. These fibers include both nonoxide (SCS-6, Nicalon) and oxide (PRD-166, FP) compositions. The results of the bend stress relaxation (BSR) test not only confirm the stress, time, and temperature dependencies predicted by the model but also allow measurement of model empirical parameters for the four fiber types. In addition, comparison of model predictions and BSR test results with the literature tensile creep data show good agreement, supporting both the predictive capability of the model and the use of the BSR test as a simple method for parameter determination for other fibers.

Distillation time as tool for improved antimalarial activity and differential oil composition of cumin seed oil

USDA-ARS?s Scientific Manuscript database

A steam distillation extraction kinetics experiment was conducted to estimate essential oil yield, composition, antimalarial, and antioxidant capacity of cumin (Cuminum cyminum L.) seed (fruits). Furthermore, regression models were developed to predict essential oil yield and composition for a given...

High-Temperature Cast Aluminum for Efficient Engines

NASA Astrophysics Data System (ADS)

Bobel, Andrew C.

Accurate thermodynamic databases are the foundation of predictive microstructure and property models. An initial assessment of the commercially available Thermo-Calc TCAL2 database and the proprietary aluminum database of QuesTek demonstrated a large degree of deviation with respect to equilibrium precipitate phase prediction in the compositional region of interest when compared to 3-D atom probe tomography (3DAPT) and transmission electron microscopy (TEM) experimental results. New compositional measurements of the Q-phase (Al-Cu-Mg-Si phase) led to a remodeling of the Q-phase thermodynamic description in the CALPHAD databases which has produced significant improvements in the phase prediction capabilities of the thermodynamic model. Due to the unique morphologies of strengthening precipitate phases commonly utilized in high-strength cast aluminum alloys, the development of new microstructural evolution models to describe both rod and plate particle growth was critical for accurate mechanistic strength models which rely heavily on precipitate size and shape. Particle size measurements through both 3DAPT and TEM experiments were used in conjunction with literature results of many alloy compositions to develop a physical growth model for the independent prediction of rod radii and rod length evolution. In addition a machine learning (ML) model was developed for the independent prediction of plate thickness and plate diameter evolution as a function of alloy composition, aging temperature, and aging time. The developed models are then compared with physical growth laws developed for spheres and modified for ellipsoidal morphology effects. Analysis of the effect of particle morphology on strength enhancement has been undertaken by modification of the Orowan-Ashby equation for 〈110〉 alpha-Al oriented finite rods in addition to an appropriate version for similarly oriented plates. A mechanistic strengthening model was developed for cast aluminum alloys containing both rod and plate-like precipitates. The model accurately accounts for the temperature dependence of particle nucleation and growth, solid solution strengthening, Si eutectic strength, and base aluminum yield strength. Strengthening model predictions of tensile yield strength are in excellent agreement with experimental observations over a wide range of aluminum alloy systems, aging temperatures, and test conditions. The developed models enable the prediction of the required particle morphology and volume fraction necessary to achieve target property goals in the design of future aluminum alloys. The effect of partitioning elements to the Q-phase was also considered for the potential to control the nucleation rate, reduce coarsening, and control the evolution of particle morphology. Elements were selected based on density functional theory (DFT) calculations showing the prevalence of certain elements to partition to the Q-phase. 3DAPT experiments were performed on Q-phase containing wrought alloys with these additions and show segregation of certain elements to the Q-phase with relative agreement to DFT predictions.

Development of NIRS models to predict protein and amylose content of brown rice and proximate compositions of rice bran.

PubMed

Bagchi, Torit Baran; Sharma, Srigopal; Chattopadhyay, Krishnendu

2016-01-15

With the escalating persuasion of economic and nutritional importance of rice grain protein and nutritional components of rice bran (RB), NIRS can be an effective tool for high throughput screening in rice breeding programme. Optimization of NIRS is prerequisite for accurate prediction of grain quality parameters. In the present study, 173 brown rice (BR) and 86 RB samples with a wide range of values were used to compare the calibration models generated by different chemometrics for grain protein (GPC) and amylose content (AC) of BR and proximate compositions (protein, crude oil, moisture, ash and fiber content) of RB. Various modified partial least square (mPLSs) models corresponding with the best mathematical treatments were identified for all components. Another set of 29 genotypes derived from the breeding programme were employed for the external validation of these calibration models. High accuracy of all these calibration and prediction models was ensured through pair t-test and correlation regression analysis between reference and predicted values. Copyright © 2015 Elsevier Ltd. All rights reserved.

Fatigue damage characterization of braided and woven fiber reinforced polymer matrix composites at room and elevated temperatures

NASA Astrophysics Data System (ADS)

Montesano, John

The use of polymer matrix composites (PMC) for manufacturing primary load-bearing structural components has significantly increased in many industrial applications. Specifically in the aerospace industry, PMCs are also being considered for elevated temperature applications. Current aerospace-grade composite components subjected to fatigue loading are over-designed due to insufficient understanding of the material failure processes, and due to the lack of available generic fatigue prediction models. A comprehensive literature survey reveals that there are few fatigue studies conducted on woven and braided fabric reinforced PMC materials, and even fewer at elevated temperatures. It is therefore the objective of this study to characterize and subsequently model the elevated temperature fatigue behaviour of a triaxial braided PMC, and to investigate the elevated temperature fatigue properties of two additional woven PMCs. An extensive experimental program is conducted using a unique test protocol on the braided and woven composites, which consists of static and fatigue testing at various test temperatures. The development of mechanically-induced damage is monitored using a combination of non-destructive techniques which included infrared thermography, fiber optic sensors and edge replication. The observed microscopic damage development is quantified and correlated to the exhibited macroscopic material behaviour at all test temperatures. The fiber-dominated PMC materials considered in this study did not exhibit notable time- or temperature-dependent static properties. However, fatigue tests reveal that the local damage development is in fact notably influenced by temperature. The elevated temperature environment increases the toughness of the thermosetting polymers, which results in consistently slower fatigue crack propagation rates for the respective composite materials. This has a direct impact on the stiffness degradation rate and the fatigue lives for the braided and woven composites under investigation. The developed analytical fatigue damage prediction model, which is based on actual observed damage mechanisms, accurately predicted the development of damage and the corresponding stiffness degradation for the braided PMC, for all test temperatures. An excellent correlation was found between the experimental and the predicted results to within a 2% accuracy. The prediction model adequately captured the local temperature-induced phenomenon exhibited by the braided PMC material. The results presented in this study are novel for a braided composite material subjected to elevated temperature fatigue.

Modeling the effects of free-living marine bacterial community composition on heterotrophic remineralization rates and biogeochemical carbon cycling

NASA Astrophysics Data System (ADS)

Teel, E.; Liu, X.; Cram, J. A.; Sachdeva, R.; Fuhrman, J. A.; Levine, N. M.

2016-12-01

Global oceanic ecosystem models either disregard fluctuations in heterotrophic bacterial remineralization or vary remineralization as a simple function of temperature, available carbon, and nutrient limitation. Most of these models were developed before molecular techniques allowed for the description of microbial community composition and functional diversity. Here we investigate the impact of a dynamic heterotrophic community and variable remineralization rates on biogeochemical cycling. Specifically, we integrated variable microbial remineralization into an ecosystem model by utilizing molecular community composition data, association network analysis, and biogeochemical rate data from the San Pedro Ocean Time-series (SPOT) station. Fluctuations in free-living bacterial community function and composition were examined using monthly environmental and biological data collected at SPOT between 2000 and 2011. On average, the bacterial community showed predictable seasonal changes in community composition and peaked in abundance in the spring with a one-month lag from peak chlorophyll concentrations. Bacterial growth efficiency (BGE), estimated from bacterial production, was found to vary widely at the site (5% to 40%). In a multivariate analysis, 47.6% of BGE variability was predicted using primary production, bacterial community composition, and temperature. A classic Nutrient-Phytoplankton-Zooplankton-Detritus model was expanded to include a heterotroph module that captured the observed relationships at the SPOT site. Results show that the inclusion of dynamic bacterial remineralization into larger oceanic ecosystem models can significantly impact microzooplankton grazing, the duration of surface phytoplankton blooms, and picophytoplankton primary production rates.

Thermal-mechanical behavior of high precision composite mirrors

NASA Technical Reports Server (NTRS)

Kuo, C. P.; Lou, M. C.; Rapp, D.

1993-01-01

Composite mirror panels were designed, constructed, analyzed, and tested in the framework of a NASA precision segmented reflector task. The deformations of the reflector surface during the exposure to space enviroments were predicted using a finite element model. The composite mirror panels have graphite-epoxy or graphite-cyanate facesheets, separated by an aluminum or a composite honeycomb core. It is pointed out that in order to carry out detailed modeling of composite mirrors with high accuracy, it is necessary to have temperature dependent properties of the materials involved and the type and magnitude of manufacturing errors and material nonuniformities. The structural modeling and analysis efforts addressed the impact of key design and materials parameters on the performance of mirrors.

On the competition among aerosol number, size and composition in predicting CCN variability: a multi-annual field study in an urbanized desert.

PubMed

Crosbie, E; Youn, J-S; Balch, B; Wonaschütz, A; Shingler, T; Wang, Z; Conant, W C; Betterton, E A; Sorooshian, A

2015-02-10

A 2-year data set of measured CCN (cloud condensation nuclei) concentrations at 0.2 % supersaturation is combined with aerosol size distribution and aerosol composition data to probe the effects of aerosol number concentrations, size distribution and composition on CCN patterns. Data were collected over a period of 2 years (2012-2014) in central Tucson, Arizona: a significant urban area surrounded by a sparsely populated desert. Average CCN concentrations are typically lowest in spring (233 cm -3 ), highest in winter (430 cm -3 ) and have a secondary peak during the North American monsoon season (July to September; 372 cm -3 ). There is significant variability outside of seasonal patterns, with extreme concentrations (1 and 99 % levels) ranging from 56 to 1945 cm -3 as measured during the winter, the season with highest variability. Modeled CCN concentrations based on fixed chemical composition achieve better closure in winter, with size and number alone able to predict 82% of the variance in CCN concentration. Changes in aerosol chemical composition are typically aligned with changes in size and aerosol number, such that hygroscopicity can be parameterized even though it is still variable. In summer, models based on fixed chemical composition explain at best only 41% (pre-monsoon) and 36% (monsoon) of the variance. This is attributed to the effects of secondary organic aerosol (SOA) production, the competition between new particle formation and condensational growth, the complex interaction of meteorology, regional and local emissions and multi-phase chemistry during the North American monsoon. Chemical composition is found to be an important factor for improving predictability in spring and on longer timescales in winter. Parameterized models typically exhibit improved predictive skill when there are strong relationships between CCN concentrations and the prevailing meteorology and dominant aerosol physicochemical processes, suggesting that similar findings could be possible in other locations with comparable climates and geography.

Disturbance observer based model predictive control for accurate atmospheric entry of spacecraft

NASA Astrophysics Data System (ADS)

Wu, Chao; Yang, Jun; Li, Shihua; Li, Qi; Guo, Lei

2018-05-01

Facing the complex aerodynamic environment of Mars atmosphere, a composite atmospheric entry trajectory tracking strategy is investigated in this paper. External disturbances, initial states uncertainties and aerodynamic parameters uncertainties are the main problems. The composite strategy is designed to solve these problems and improve the accuracy of Mars atmospheric entry. This strategy includes a model predictive control for optimized trajectory tracking performance, as well as a disturbance observer based feedforward compensation for external disturbances and uncertainties attenuation. 500-run Monte Carlo simulations show that the proposed composite control scheme achieves more precise Mars atmospheric entry (3.8 km parachute deployment point distribution error) than the baseline control scheme (8.4 km) and integral control scheme (5.8 km).

Numerical, micro-mechanical prediction of crack growth resistance in a fibre-reinforced/brittle matrix composite

NASA Technical Reports Server (NTRS)

Jenkins, Michael G.; Ghosh, Asish; Salem, Jonathan A.

1990-01-01

Micromechanics fracture models are incorporated into three distinct fracture process zones which contribute to the crack growth resistance of fibrous composites. The frontal process zone includes microcracking, fiber debonding, and some fiber failure. The elastic process zone is related only to the linear elastic creation of new matrix and fiber fracture surfaces. The wake process zone includes fiber bridging, fiber pullout, and fiber breakage. The R-curve predictions of the model compare well with empirical results for a unidirectional, continuous fiber C/C composite. Separating the contributions of each process zone reveals the wake region to contain the dominant crack growth resistance mechanisms. Fractography showed the effects of the micromechanisms on the macroscopic fracture behavior.

Impacts of Process and Prediction Uncertainties on Projected Hanford Waste Glass Amount

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

Gervasio, Vivianaluxa; Vienna, John D.; Kim, Dong-Sang

Analyses were performed to evaluate the impacts of using the advanced glass models, constraints (Vienna et al. 2016), and uncertainty descriptions on projected Hanford glass mass. The maximum allowable WOL was estimated for waste compositions while simultaneously satisfying all applicable glass property and composition constraints with sufficient confidence. Different components of prediction and composition/process uncertainties were systematically included in the calculations to evaluate their impacts on glass mass. The analyses estimated the production of 23,360 MT of IHLW glass when no uncertainties were taken into accound. Accounting for prediction and composition/process uncertainties resulted in 5.01 relative percent increase in estimatedmore » glass mass 24,531 MT. Roughly equal impacts were found for prediction uncertainties (2.58 RPD) and composition/process uncertainties (2.43 RPD). ILAW mass was predicted to be 282,350 MT without uncertainty and with weaste loading “line” rules in place. Accounting for prediction and composition/process uncertainties resulted in only 0.08 relative percent increase in estimated glass mass of 282,562 MTG. Without application of line rules the glass mass decreases by 10.6 relative percent (252,490 MT) for the case with no uncertainties. Addition of prediction uncertainties increases glass mass by 1.32 relative percent and the addition of composition/process uncertainties increase glass mass by an additional 7.73 relative percent (9.06 relative percent increase combined). The glass mass estimate without line rules (275,359 MT) was 2.55 relative percent lower than that with the line rules (282,562 MT), after accounting for all applicable uncertainties.« less

Modeling plant composition as community continua in a forest landscape with LiDAR and hyperspectral remote sensing.

PubMed

Hakkenberg, C R; Peet, R K; Urban, D L; Song, C

2018-01-01

In light of the need to operationalize the mapping of forest composition at landscape scales, this study uses multi-scale nested vegetation sampling in conjunction with LiDAR-hyperspectral remotely sensed data from the G-LiHT airborne sensor to map vascular plant compositional turnover in a compositionally and structurally complex North Carolina Piedmont forest. Reflecting a shift in emphasis from remotely sensing individual crowns to detecting aggregate optical-structural properties of forest stands, predictive maps reflect the composition of entire vascular plant communities, inclusive of those species smaller than the resolution of the remotely sensed imagery, intertwined with proximate taxa, or otherwise obscured from optical sensors by dense upper canopies. Stand-scale vascular plant composition is modeled as community continua: where discrete community-unit classes at different compositional resolutions provide interpretable context for continuous gradient maps that depict n-dimensional compositional complexity as a single, consistent RGB color combination. In total, derived remotely sensed predictors explain 71%, 54%, and 48% of the variation in the first three components of vascular plant composition, respectively. Among all remotely sensed environmental gradients, topography derived from LiDAR ground returns, forest structure estimated from LiDAR all returns, and morphological-biochemical traits determined from hyperspectral imagery each significantly correspond to the three primary axes of floristic composition in the study site. Results confirm the complementarity of LiDAR and hyperspectral sensors for modeling the environmental gradients constraining landscape turnover in vascular plant composition and hold promise for predictive mapping applications spanning local land management to global ecosystem modeling. © 2017 by the Ecological Society of America.

How preschool executive functioning predicts several aspects of math achievement in Grades 1 and 3: A longitudinal study.

PubMed

Viterbori, Paola; Usai, M Carmen; Traverso, Laura; De Franchis, Valentina

2015-12-01

This longitudinal study analyzes whether selected components of executive function (EF) measured during the preschool period predict several indices of math achievement in primary school. Six EF measures were assessed in a sample of 5-year-old children (N = 175). The math achievement of the same children was then tested in Grades 1 and 3 using both a composite math score and three single indices of written calculation, arithmetical facts, and problem solving. Using previous results obtained from the same sample of children, a confirmatory factor analysis examining the latent EF structure in kindergarten indicated that a two-factor model provided the best fit for the data. In this model, inhibition and working memory (WM)-flexibility were separate dimensions. A full structural equation model was then used to test the hypothesis that math achievement (the composite math score and single math scores) in Grades 1 and 3 could be explained by the two EF components comprising the kindergarten model. The results indicate that the WM-flexibility component measured during the preschool period substantially predicts mathematical achievement, especially in Grade 3. The math composite scores were predicted by the WM-flexibility factor at both grade levels. In Grade 3, both problem solving and arithmetical facts were predicted by the WM-flexibility component. The results empirically support interventions that target EF as an important component of early childhood mathematics education. Copyright © 2015 Elsevier Inc. All rights reserved.

Probabilistic micromechanics for metal matrix composites

NASA Astrophysics Data System (ADS)

Engelstad, S. P.; Reddy, J. N.; Hopkins, Dale A.

A probabilistic micromechanics-based nonlinear analysis procedure is developed to predict and quantify the variability in the properties of high temperature metal matrix composites. Monte Carlo simulation is used to model the probabilistic distributions of the constituent level properties including fiber, matrix, and interphase properties, volume and void ratios, strengths, fiber misalignment, and nonlinear empirical parameters. The procedure predicts the resultant ply properties and quantifies their statistical scatter. Graphite copper and Silicon Carbide Titanlum Aluminide (SCS-6 TI15) unidirectional plies are considered to demonstrate the predictive capabilities. The procedure is believed to have a high potential for use in material characterization and selection to precede and assist in experimental studies of new high temperature metal matrix composites.

Analysis of Discrete-Source Damage Progression in a Tensile Stiffened Composite Panel

NASA Technical Reports Server (NTRS)

Wang, John T.; Lotts, Christine G.; Sleight, David W.

1999-01-01

This paper demonstrates the progressive failure analysis capability in NASA Langley s COMET-AR finite element analysis code on a large-scale built-up composite structure. A large-scale five stringer composite panel with a 7-in. long discrete source damage was analyzed from initial loading to final failure including the geometric and material nonlinearities. Predictions using different mesh sizes, different saw cut modeling approaches, and different failure criteria were performed and assessed. All failure predictions have a reasonably good correlation with the test result.

An assessment model for atmospheric composition

NASA Technical Reports Server (NTRS)

Prather, Michael J. (Editor)

1988-01-01

Predicting future perturbations to global air quality and climate requires, as a prerequisite, prognostic models for the composition of the Earth's atmosphere. Such assessment models are needed to evaluate the impact on our environment of different social choices that affect emissions of the photochemically and radiatively important trace gases. Our presentation here of a prototype assessment model is intended to encourage public scientific discussions of the necessary components of the model and their interactions, with the recognition that models similar to this will likely be used by the Environmental Protection Agency and other regulatory agencies in order to assess the effect of changes in atmospheric composition on climate over the next century.

Incorporation of lysosomal sequestration in the mechanistic model for prediction of tissue distribution of basic drugs.

PubMed

Assmus, Frauke; Houston, J Brian; Galetin, Aleksandra

2017-11-15

The prediction of tissue-to-plasma water partition coefficients (Kpu) from in vitro and in silico data using the tissue-composition based model (Rodgers & Rowland, J Pharm Sci. 2005, 94(6):1237-48.) is well established. However, distribution of basic drugs, in particular into lysosome-rich lung tissue, tends to be under-predicted by this approach. The aim of this study was to develop an extended mechanistic model for the prediction of Kpu which accounts for lysosomal sequestration and the contribution of different cell types in the tissue of interest. The extended model is based on compound-specific physicochemical properties and tissue composition data to describe drug ionization, distribution into tissue water and drug binding to neutral lipids, neutral phospholipids and acidic phospholipids in tissues, including lysosomes. Physiological data on the types of cells contributing to lung, kidney and liver, their lysosomal content and lysosomal pH were collated from the literature. The predictive power of the extended mechanistic model was evaluated using a dataset of 28 basic drugs (pK a ≥7.8, 17 β-blockers, 11 structurally diverse drugs) for which experimentally determined Kpu data in rat tissue have been reported. Accounting for the lysosomal sequestration in the extended mechanistic model improved the accuracy of Kpu predictions in lung compared to the original Rodgers model (56% drugs within 2-fold or 88% within 3-fold of observed values). Reduction in the extent of Kpu under-prediction was also evident in liver and kidney. However, consideration of lysosomal sequestration increased the occurrence of over-predictions, yielding overall comparable model performances for kidney and liver, with 68% and 54% of Kpu values within 2-fold error, respectively. High lysosomal concentration ratios relative to cytosol (>1000-fold) were predicted for the drugs investigated; the extent differed depending on the lysosomal pH and concentration of acidic phospholipids among cell types. Despite this extensive lysosomal sequestration in the individual cells types, the maximal change in the overall predicted tissue Kpu was <3-fold for lysosome-rich tissues investigated here. Accounting for the variability in cellular physiological model input parameters, in particular lysosomal pH and fraction of the cellular volume occupied by the lysosomes, only partially explained discrepancies between observed and predicted Kpu data in the lung. Improved understanding of the system properties, e.g., cell/organelle composition is required to support further development of mechanistic equations for the prediction of drug tissue distribution. Application of this revised mechanistic model is recommended for prediction of Kpu in lysosome-rich tissue to facilitate the advancement of physiologically-based prediction of volume of distribution and drug exposure in the tissues. Copyright © 2017 Elsevier B.V. All rights reserved.

Wave propagation modeling in composites reinforced by randomly oriented fibers

NASA Astrophysics Data System (ADS)

Kudela, Pawel; Radzienski, Maciej; Ostachowicz, Wieslaw

2018-02-01

A new method for prediction of elastic constants in randomly oriented fiber composites is proposed. It is based on mechanics of composites, the rule of mixtures and total mass balance tailored to the spectral element mesh composed of 3D brick elements. Selected elastic properties predicted by the proposed method are compared with values obtained by another theoretical method. The proposed method is applied for simulation of Lamb waves in glass-epoxy composite plate reinforced by randomly oriented fibers. Full wavefield measurements conducted by the scanning laser Doppler vibrometer are in good agreement with simulations performed by using the time domain spectral element method.

A Comparison of Various Stress Rupture Life Models for Orbiter Composite Pressure Vessels and Confidence Intervals

NASA Technical Reports Server (NTRS)

Grimes-Ledesma, Lorie; Murthy, Pappu L. N.; Phoenix, S. Leigh; Glaser, Ronald

2007-01-01

In conjunction with a recent NASA Engineering and Safety Center (NESC) investigation of flight worthiness of Kevlar Overwrapped Composite Pressure Vessels (COPVs) on board the Orbiter, two stress rupture life prediction models were proposed independently by Phoenix and by Glaser. In this paper, the use of these models to determine the system reliability of 24 COPVs currently in service on board the Orbiter is discussed. The models are briefly described, compared to each other, and model parameters and parameter uncertainties are also reviewed to understand confidence in reliability estimation as well as the sensitivities of these parameters in influencing overall predicted reliability levels. Differences and similarities in the various models will be compared via stress rupture reliability curves (stress ratio vs. lifetime plots). Also outlined will be the differences in the underlying model premises, and predictive outcomes. Sources of error and sensitivities in the models will be examined and discussed based on sensitivity analysis and confidence interval determination. Confidence interval results and their implications will be discussed for the models by Phoenix and Glaser.

Design for inadvertent damage in composite laminates

NASA Technical Reports Server (NTRS)

Singhal, Surendra N.; Chamis, Christos C.

1992-01-01

Simplified predictive methods and models to computationally simulate durability and damage in polymer matrix composite materials/structures are described. The models include (1) progressive fracture, (2) progressively damaged structural behavior, (3) progressive fracture in aggressive environments, (4) stress concentrations, and (5) impact resistance. Several examples are included to illustrate applications of the models and to identify significant parameters and sensitivities. Comparisons with limited experimental data are made.

Explicit Pore Pressure Material Model in Carbon-Cloth Phenolic

NASA Technical Reports Server (NTRS)

Gutierrez-Lemini, Danton; Ehle, Curt

2003-01-01

An explicit material model that uses predicted pressure in the pores of a carbon-cloth phenolic (CCP) composite has been developed. This model is intended to be used within a finite-element model to predict phenomena specific to CCP components of solid-fuel-rocket nozzles subjected to high operating temperatures and to mechanical stresses that can be great enough to cause structural failures. Phenomena that can be predicted with the help of this model include failures of specimens in restrained-thermal-growth (RTG) tests, pocketing erosion, and ply lifting

Unsupervised classification of petroleum Certified Reference Materials and other fuels by chemometric analysis of gas chromatography-mass spectrometry data

PubMed Central

de Carvalho Rocha, Werickson Fortunato; Schantz, Michele M.; Sheen, David A.; Chu, Pamela M.; Lippa, Katrice A.

2017-01-01

As feedstocks transition from conventional oil to unconventional petroleum sources and biomass, it will be necessary to determine whether a particular fuel or fuel blend is suitable for use in engines. Certifying a fuel as safe for use is time-consuming and expensive and must be performed for each new fuel. In principle, suitability of a fuel should be completely determined by its chemical composition. This composition can be probed through use of detailed analytical techniques such as gas chromatography-mass spectroscopy (GC-MS). In traditional analysis, chromatograms would be used to determine the details of the composition. In the approach taken in this paper, the chromatogram is assumed to be entirely representative of the composition of a fuel, and is used directly as the input to an algorithm in order to develop a model that is predictive of a fuel's suitability. When a new fuel is proposed for service, its suitability for any application could then be ascertained by using this model to compare its chromatogram with those of the fuels already known to be suitable for that application. In this paper, we lay the mathematical and informatics groundwork for a predictive model of hydrocarbon properties. The objective of this work was to develop a reliable model for unsupervised classification of the hydrocarbons as a prelude to developing a predictive model of their engine-relevant physical and chemical properties. A set of hydrocarbons including biodiesel fuels, gasoline, highway and marine diesel fuels, and crude oils was collected and GC-MS profiles obtained. These profiles were then analyzed using multi-way principal components analysis (MPCA), principal factors analysis (PARAFAC), and a self-organizing map (SOM), which is a kind of artificial neural network. It was found that, while MPCA and PARAFAC were able to recover descriptive models of the fuels, their linear nature obscured some of the finer physical details due to the widely varying composition of the fuels. The SOM was able to find a descriptive classification model which has the potential for practical recognition and perhaps prediction of fuel properties. PMID:28603295

Ecosystem composition changes over the past millennium: model simulations and comparison with paleoecological observations

NASA Astrophysics Data System (ADS)

Liu, Y.; Rollinson, C.; Dietze, M.; McLachlan, J. S.; Poulter, B.; Quaife, T. L.; Raiho, A.; Ricciuto, D. M.; Schaefer, K. M.; Steinkamp, J.; Moore, D. J.

2015-12-01

Over multi-decadal to multi-centennial timescales, ecosystem function and carbon storage is largely influenced by vegetation composition. The predictability of ecosystem responses to climate change thus depends on the understanding of long-term community dynamics. Our study aims to quantify the influence of the most relevant ecological factors that control plant distribution and abundance, in contemporary terrestrial biosphere models and in paleo-records, and constrain the model processes and parameters with paleoecological data. We simulated vegetation changes at 6 sites in the northeastern United States over the past 1160 years using 7 terrestrial biosphere models and variations (CLM4.5-CN, ED2, ED2-LU, JULES-TRIFFID, LINKAGES, LPJ-GUESS, LPJ-wsl) driven by common paleoclimatic drivers. We examined plant growth, recruitment, and mortality (including other carbon turnover) of the plant functional types (PFTs) in the models, attributed the responses to three major factors (climate, competition, and disturbance), and estimated the relative effect of each factor. We assessed the model responses against plant-community theories (bioclimatic limits, niche difference, temporal variation and storage effect, and disturbance). We found that vegetation composition were sensitive to realized niche differences (e.g. differential growth response) among PFTs. Because many models assume unlimited dispersal and sometimes recruitment, the "storage effect" constantly affects community composition. Fire was important in determining the ecosystem composition, yet the vegetation to fire feedback was weak in the models. We also found that vegetation-composition changes in the simulations were driven to a much greater degree by growth as opposed to by turnover/mortality, when compared with those in paleoecological records. Our work suggest that 1) for forecasting slow changes in vegetation composition, we can use paleo-data to better quantify the realized niches of PFTs and associated uncertainties, and 2) for predicting abrupt changes in vegetation composition, we need to better implement processes of dynamic turnover and fire in current ecosystem models.

Prediction of peak shape in hydro-organic and micellar-organic liquid chromatography as a function of mobile phase composition.

PubMed

Baeza-Baeza, J J; Ruiz-Angel, M J; García-Alvarez-Coque, M C

2007-09-07

A simple model is proposed that relates the parameters describing the peak width with the retention time, which can be easily predicted as a function of mobile phase composition. This allows the further prediction of peak shape with global errors below 5%, using a modified Gaussian model with a parabolic variance. The model is useful in the optimisation of chromatographic resolution to assess an eventual overlapping of close peaks. The dependence of peak shape with mobile phase composition was studied for mobile phases containing acetonitrile in the presence and absence of micellised surfactant (micellar-organic and hydro-organic reversed-phase liquid chromatography, RPLC). In micellar RPLC, both modifiers (surfactant and acetonitrile) were observed to decrease or improve the efficiencies in the same percentage, at least in the studied concentration ranges. The study also revealed that the problem of achieving smaller efficiencies in this chromatographic mode, compared to hydro-organic RPLC, is not only related to the presence of surfactant covering the stationary phase, but also to the smaller concentration of organic solvent in the mobile phase.

Time-dependent deformation of titanium metal matrix composites

NASA Technical Reports Server (NTRS)

Bigelow, C. A.; Bahei-El-din, Y. A.; Mirdamadi, M.

1995-01-01

A three-dimensional finite element program called VISCOPAC was developed and used to conduct a micromechanics analysis of titanium metal matrix composites. The VISCOPAC program uses a modified Eisenberg-Yen thermo-viscoplastic constitutive model to predict matrix behavior under thermomechanical fatigue loading. The analysis incorporated temperature-dependent elastic properties in the fiber and temperature-dependent viscoplastic properties in the matrix. The material model was described and the necessary material constants were determined experimentally. Fiber-matrix interfacial behavior was analyzed using a discrete fiber-matrix model. The thermal residual stresses due to the fabrication cycle were predicted with a failed interface, The failed interface resulted in lower thermal residual stresses in the matrix and fiber. Stresses due to a uniform transverse load were calculated at two temperatures, room temperature and an elevated temperature of 650 C. At both temperatures, a large stress concentration was calculated when the interface had failed. The results indicate the importance of accuracy accounting for fiber-matrix interface failure and the need for a micromechanics-based analytical technique to understand and predict the behavior of titanium metal matrix composites.

Development of Design Analysis Methods for C/SiC Composite Structures

NASA Technical Reports Server (NTRS)

Sullivan, Roy M.; Mital, Subodh K.; Murthy, Pappu L. N.; Palko, Joseph L.; Cueno, Jacques C.; Koenig, John R.

2006-01-01

The stress-strain behavior at room temperature and at 1100 C (2000 F) was measured for two carbon-fiber-reinforced silicon carbide (C/SiC) composite materials: a two-dimensional plain-weave quasi-isotropic laminate and a three-dimensional angle-interlock woven composite. Micromechanics-based material models were developed for predicting the response properties of these two materials. The micromechanics based material models were calibrated by correlating the predicted material property values with the measured values. Four-point beam bending sub-element specimens were fabricated with these two fiber architectures and four-point bending tests were performed at room temperature and at 1100 C. Displacements and strains were measured at various locations along the beam and recorded as a function of load magnitude. The calibrated material models were used in concert with a nonlinear finite element solution to simulate the structural response of these two materials in the four-point beam bending tests. The structural response predicted by the nonlinear analysis method compares favorably with the measured response for both materials and for both test temperatures. Results show that the material models scale up fairly well from coupon to subcomponent level.

Comprehensive Micromechanics-Analysis Code - Version 4.0

NASA Technical Reports Server (NTRS)

Arnold, S. M.; Bednarcyk, B. A.

2005-01-01

Version 4.0 of the Micromechanics Analysis Code With Generalized Method of Cells (MAC/GMC) has been developed as an improved means of computational simulation of advanced composite materials. The previous version of MAC/GMC was described in "Comprehensive Micromechanics-Analysis Code" (LEW-16870), NASA Tech Briefs, Vol. 24, No. 6 (June 2000), page 38. To recapitulate: MAC/GMC is a computer program that predicts the elastic and inelastic thermomechanical responses of continuous and discontinuous composite materials with arbitrary internal microstructures and reinforcement shapes. The predictive capability of MAC/GMC rests on a model known as the generalized method of cells (GMC) - a continuum-based model of micromechanics that provides closed-form expressions for the macroscopic response of a composite material in terms of the properties, sizes, shapes, and responses of the individual constituents or phases that make up the material. Enhancements in version 4.0 include a capability for modeling thermomechanically and electromagnetically coupled ("smart") materials; a more-accurate (high-fidelity) version of the GMC; a capability to simulate discontinuous plies within a laminate; additional constitutive models of materials; expanded yield-surface-analysis capabilities; and expanded failure-analysis and life-prediction capabilities on both the microscopic and macroscopic scales.

Text Comprehension Mediates Morphological Awareness, Syntactic Processing, and Working Memory in Predicting Chinese Written Composition Performance

PubMed Central

Guan, Connie Qun; Ye, Feifei; Wagner, Richard K.; Meng, Wanjin; Leong, Che Kan

2014-01-01

The goal of the present study was to test opposing views about four issues concerning predictors of individual differences in Chinese written composition: (a) Whether morphological awareness, syntactic processing, and working memory represent distinct and measureable constructs in Chinese or are just manifestations of general language ability; (b) whether they are important predictors of Chinese written composition, and if so, the relative magnitudes and independence of their predictive relations; (c) whether observed predictive relations are mediated by text comprehension; and (d) whether these relations vary or are developmentally invariant across three years of writing development. Based on analyses of the performance of students in grades 4 (n = 246), 5 (n = 242) and 6 (n = 261), the results supported morphological awareness, syntactic processing, and working memory as distinct yet correlated abilities that made independent contributions to predicting Chinese written composition, with working memory as the strongest predictor. However, predictive relations were mediated by text comprehension. The final model accounted for approximately 75 percent of the variance in Chinese written composition. The results were largely developmentally invariant across the three grades from which participants were drawn. PMID:25530630

An analytical solution for the elastoplastic response of a continuous fiber composite under uniaxial loading

NASA Technical Reports Server (NTRS)

Lee, Jong-Won; Allen, David H.

1990-01-01

A continuous fiber composite is modelled by a two-element composite cylinder in order to predict the elastoplastic response of the composite under a monotonically increasing tensile loading parallel to fibers. The fibers and matrix are assumed to be elastic-perfectly plastic materials obeying Hill's and Tresca's yield criteria, respectively. Here, the composite behavior when the fibers yield prior to the matrix is investigated.

Hybrid ray-FDTD model for the simulation of the ultrasonic inspection of CFRP parts

NASA Astrophysics Data System (ADS)

Jezzine, Karim; Ségur, Damien; Ecault, Romain; Dominguez, Nicolas; Calmon, Pierre

2017-02-01

Carbon Fiber Reinforced Polymers (CFRP) are commonly used in structural parts in the aeronautic industry, to reduce the weight of aircraft while maintaining high mechanical performances. Simulation of the ultrasonic inspections of these parts has to face the highly heterogeneous and anisotropic characteristics of these materials. To model the propagation of ultrasound in these composite structures, we propose two complementary approaches. The first one is based on a ray model predicting the propagation of the ultrasound in an anisotropic effective medium obtained from a homogenization of the material. The ray model is designed to deal with possibly curved parts and subsequent continuously varying anisotropic orientations. The second approach is based on the coupling of the ray model, and a finite difference scheme in time domain (FDTD). The ray model handles the ultrasonic propagation between the transducer and the FDTD computation zone that surrounds the composite part. In this way, the computational efficiency is preserved and the ultrasound scattering by the composite structure can be predicted. Inspections of flat or curved composite panels, as well as stiffeners can be performed. The models have been implemented in the CIVA software platform and compared to experiments. We also present an application of the simulation to the performance demonstration of the adaptive inspection technique SAUL (Surface Adaptive Ultrasound).

A New Scheme to Characterize and Identify Protein Ubiquitination Sites.

PubMed

Nguyen, Van-Nui; Huang, Kai-Yao; Huang, Chien-Hsun; Lai, K Robert; Lee, Tzong-Yi

2017-01-01

Protein ubiquitination, involving the conjugation of ubiquitin on lysine residue, serves as an important modulator of many cellular functions in eukaryotes. Recent advancements in proteomic technology have stimulated increasing interest in identifying ubiquitination sites. However, most computational tools for predicting ubiquitination sites are focused on small-scale data. With an increasing number of experimentally verified ubiquitination sites, we were motivated to design a predictive model for identifying lysine ubiquitination sites for large-scale proteome dataset. This work assessed not only single features, such as amino acid composition (AAC), amino acid pair composition (AAPC) and evolutionary information, but also the effectiveness of incorporating two or more features into a hybrid approach to model construction. The support vector machine (SVM) was applied to generate the prediction models for ubiquitination site identification. Evaluation by five-fold cross-validation showed that the SVM models learned from the combination of hybrid features delivered a better prediction performance. Additionally, a motif discovery tool, MDDLogo, was adopted to characterize the potential substrate motifs of ubiquitination sites. The SVM models integrating the MDDLogo-identified substrate motifs could yield an average accuracy of 68.70 percent. Furthermore, the independent testing result showed that the MDDLogo-clustered SVM models could provide a promising accuracy (78.50 percent) and perform better than other prediction tools. Two cases have demonstrated the effective prediction of ubiquitination sites with corresponding substrate motifs.

Basic failure mechanisms in advanced composites

NASA Technical Reports Server (NTRS)

Mullin, J. V.; Mazzio, V. F.; Mehan, R. L.

1972-01-01

Failure mechanisms in carbon-epoxy composites are identified as a basis for more reliable prediction of the performance of these materials. The approach involves both the study of local fracture events in model specimens containing small groups of filaments and fractographic examination of high fiber content engineering composites. Emphasis is placed on the correlation of model specimen observations with gross fracture modes. The effects of fiber surface treatment, resin modification and fiber content are studied and acoustic emission methods are applied. Some effort is devoted to analysis of the failure process in composite/metal specimens.

Model of the non-linear stress-strain behavior of a 2D-SiC/SiC ceramic matrix composite (CMC)

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

Guillaumat, L; Lamon, J.

The non-linear stress-strain behaviour of a 2D-SiC/SiC composite reinforced with fabrics of fiber bundles was predicted from properties of major constituents. A finite element analysis was employed for stress computation. The different steps of matrix damage identified experimentally were duplicated in the mesh. Predictions compared satisfactorily with experimental data.

A generalized methodology to characterize composite materials for pyrolysis models

NASA Astrophysics Data System (ADS)

McKinnon, Mark B.

The predictive capabilities of computational fire models have improved in recent years such that models have become an integral part of many research efforts. Models improve the understanding of the fire risk of materials and may decrease the number of expensive experiments required to assess the fire hazard of a specific material or designed space. A critical component of a predictive fire model is the pyrolysis sub-model that provides a mathematical representation of the rate of gaseous fuel production from condensed phase fuels given a heat flux incident to the material surface. The modern, comprehensive pyrolysis sub-models that are common today require the definition of many model parameters to accurately represent the physical description of materials that are ubiquitous in the built environment. Coupled with the increase in the number of parameters required to accurately represent the pyrolysis of materials is the increasing prevalence in the built environment of engineered composite materials that have never been measured or modeled. The motivation behind this project is to develop a systematic, generalized methodology to determine the requisite parameters to generate pyrolysis models with predictive capabilities for layered composite materials that are common in industrial and commercial applications. This methodology has been applied to four common composites in this work that exhibit a range of material structures and component materials. The methodology utilizes a multi-scale experimental approach in which each test is designed to isolate and determine a specific subset of the parameters required to define a material in the model. Data collected in simultaneous thermogravimetry and differential scanning calorimetry experiments were analyzed to determine the reaction kinetics, thermodynamic properties, and energetics of decomposition for each component of the composite. Data collected in microscale combustion calorimetry experiments were analyzed to determine the heats of complete combustion of the volatiles produced in each reaction. Inverse analyses were conducted on sample temperature data collected in bench-scale tests to determine the thermal transport parameters of each component through degradation. Simulations of quasi-one-dimensional bench-scale gasification tests generated from the resultant models using the ThermaKin modeling environment were compared to experimental data to independently validate the models.

Mass Conservation in Modeling Moisture Diffusion in Multi-Layer Carbon Composite Structures

NASA Technical Reports Server (NTRS)

Nurge, Mark A.; Youngquist, Robert C.; Starr, Stanley O.

2009-01-01

Moisture diffusion in multi-layer carbon composite structures is difficult to model using finite difference methods due to the discontinuity in concentrations between adjacent layers of differing materials. Applying a mass conserving approach at these boundaries proved to be effective at accurately predicting moisture uptake for a sample exposed to a fixed temperature and relative humidity. Details of the model developed are presented and compared with actual moisture uptake data gathered over 130 days from a graphite epoxy composite sandwich coupon with a Rohacell foam core.

The viscosity of magmatic silicate liquids: A model for calculation

NASA Technical Reports Server (NTRS)

Bottinga, Y.; Weill, D. F.

1971-01-01

A simple model has been designed to allow reasonably accurate calculations of viscosity as a function of temperature and composition. The problem of predicting viscosities of anhydrous silicate liquids has been investigated since such viscosity numbers are applicable to many extrusive melts and to nearly dry magmatic liquids in general. The fluidizing action of water dissolved in silicate melts is well recognized and it is now possible to predict the effect of water content on viscosity in a semiquantitative way. Water was not incorporated directly into the model. Viscosities of anhydrous compositions were calculated, and, where necessary, the effect of added water and estimated. The model can be easily modified to incorporate the effect of water whenever sufficient additional data are accumulated.

Aspects of porosity prediction using multivariate linear regression

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

Byrnes, A.P.; Wilson, M.D.

1991-03-01

Highly accurate multiple linear regression models have been developed for sandstones of diverse compositions. Porosity reduction or enhancement processes are controlled by the fundamental variables, Pressure (P), Temperature (T), Time (t), and Composition (X), where composition includes mineralogy, size, sorting, fluid composition, etc. The multiple linear regression equation, of which all linear porosity prediction models are subsets, takes the generalized form: Porosity = C{sub 0} + C{sub 1}(P) + C{sub 2}(T) + C{sub 3}(X) + C{sub 4}(t) + C{sub 5}(PT) + C{sub 6}(PX) + C{sub 7}(Pt) + C{sub 8}(TX) + C{sub 9}(Tt) + C{sub 10}(Xt) + C{sub 11}(PTX) + C{submore » 12}(PXt) + C{sub 13}(PTt) + C{sub 14}(TXt) + C{sub 15}(PTXt). The first four primary variables are often interactive, thus requiring terms involving two or more primary variables (the form shown implies interaction and not necessarily multiplication). The final terms used may also involve simple mathematic transforms such as log X, e{sup T}, X{sup 2}, or more complex transformations such as the Time-Temperature Index (TTI). The X term in the equation above represents a suite of compositional variable and, therefore, a fully expanded equation may include a series of terms incorporating these variables. Numerous published bivariate porosity prediction models involving P (or depth) or Tt (TTI) are effective to a degree, largely because of the high degree of colinearity between p and TTI. However, all such bivariate models ignore the unique contributions of P and Tt, as well as various X terms. These simpler models become poor predictors in regions where colinear relations change, were important variables have been ignored, or where the database does not include a sufficient range or weight distribution for the critical variables.« less

Monitoring and modeling of long-term settlements of an experimental landfill in Brazil.

PubMed

Simões, Gustavo Ferreira; Catapreta, Cícero Antônio Antunes

2013-02-01

Settlement evaluation in sanitary landfills is a complex process, due to the waste heterogeneity, time-varying properties and influencing factors and mechanisms, such as mechanical compression due to load application and creep, and physical-chemical and biological processes caused by the wastes decomposition. Many empirical models for the analysis of long-term settlement in landfills are reported in the literature. This paper presents the results of a settlement monitoring program carried out during 6 years in Belo Horizonte experimental landfill. Different sets of field data were used to calibrate three long-term settlement prediction models (rheological, hyperbolic and composite). The parameters obtained in the calibration were used to predict the settlements and to compare with actual field data. During the monitoring period of 6 years, significant vertical strains were observed (of up to 31%) in relation to the initial height of the experimental landfill. The results for the long-term settlement prediction obtained by the hyperbolic and rheological models significantly underestimate the settlements, regardless the period of data used in the calibration. The best fits were obtained with the composite model, except when 1 year field data were used in the calibration. The results of the composite model indicate settlements stabilization at larger times and with larger final settlements when compared to the hyperbolic and rheological models. Copyright © 2012 Elsevier Ltd. All rights reserved.

A method to adapt thoracic impedance based on chest geometry and composition to assess congestion in heart failure patients.

PubMed

Cuba-Gyllensten, Illapha; Gastelurrutia, Paloma; Bonomi, Alberto G; Riistama, Jarno; Bayes-Genis, Antoni; Aarts, Ronald M

2016-04-14

Multi-frequency trans-thoracic bioimpedance (TTI) could be used to track fluid changes and congestion of the lungs, however, patient specific characteristics may impact the measurements. We investigated the effects of thoracic geometry and composition on measurements of TTI and developed an equation to calculate a personalized fluid index. Simulations of TTI measurements for varying levels of chest circumference, fat and muscle proportion were used to derive parameters for a model predicting expected values of TTI. This model was then adapted to measurements from a control group of 36 healthy volunteers to predict TTI and lung fluids (fluid index). Twenty heart failure (HF) patients treated for acute HF were then used to compare the changes in the personalized fluid index to symptoms of HF and predicted TTI to measurements at hospital discharge. All the derived body characteristics affected the TTI measurements in healthy volunteers and together the model predicted the measured TTI with 8.9% mean absolute error. In HF patients the estimated TTI correlated well with the discharged TTI (r=0.73,p <0.001) and the personalized fluid index followed changes in symptom levels during treatment. However, 37% (n=7) of the patients were discharged well below the model expected value. Accounting for chest geometry and composition might help in interpreting TTI measurements. Copyright © 2016 IPEM. Published by Elsevier Ltd. All rights reserved.

A Model for Dissolution of Lime in Steelmaking Slags

NASA Astrophysics Data System (ADS)

Sarkar, Rahul; Roy, Ushasi; Ghosh, Dinabandhu

2016-08-01

In a previous study by Sarkar et al. (Metall. Mater. Trans. B 46B:961 2015), a dynamic model of the LD steelmaking was developed. The prediction of the previous model (Sarkar et al. in Metall. Mater. Trans. B 46B:961 2015) for the bath (metal) composition matched well with the plant data (Cicutti et al. in Proceedings of 6th International Conference on Molten Slags, Fluxes and Salts, Stockholm City, 2000). However, with respect to the slag composition, the prediction was not satisfactory. The current study aims to improve upon the previous model Sarkar et al. (Metall. Mater. Trans. B 46B:961 2015) by incorporating a lime dissolution submodel into the earlier one. From the industrial point of view, the understanding of the lime dissolution kinetics is important to meet the ever-increasing demand of producing low-P steel at a low basicity. In the current study, three-step kinetics for the lime dissolution is hypothesized on the assumption that a solid layer of 2CaO·SiO2 should form around the unreacted core of the lime. From the available experimental data, it seems improbable that the observed kinetics should be controlled singly by any one kinetic step. Accordingly, a general, mixed control model has been proposed to calculate the dissolution rate of the lime under varying slag compositions and temperatures. First, the rate equation for each of the three rate-controlling steps has been derived, for three different lime geometries. Next, the rate equation for the mixed control kinetics has been derived and solved to find the dissolution rate. The model predictions have been validated by means of the experimental data available in the literature. In addition, the effects of the process conditions on the dissolution rate have been studied, and compared with the experimental results wherever possible. Incorporation of this submodel into the earlier global model (Sarkar et al. in Metall. Mater. Trans. B 46B:961 2015) enables the prediction of the lime dissolution rate in the dynamic system of LD steelmaking. In addition, with the inclusion of this submodel, significant improvement in the prediction of the slag composition during the main blow period has been observed.

Application of Interface Technology in Progressive Failure Analysis of Composite Panels

NASA Technical Reports Server (NTRS)

Sleight, D. W.; Lotts, C. G.

2002-01-01

A progressive failure analysis capability using interface technology is presented. The capability has been implemented in the COMET-AR finite element analysis code developed at the NASA Langley Research Center and is demonstrated on composite panels. The composite panels are analyzed for damage initiation and propagation from initial loading to final failure using a progressive failure analysis capability that includes both geometric and material nonlinearities. Progressive failure analyses are performed on conventional models and interface technology models of the composite panels. Analytical results and the computational effort of the analyses are compared for the conventional models and interface technology models. The analytical results predicted with the interface technology models are in good correlation with the analytical results using the conventional models, while significantly reducing the computational effort.

Interactions of changing climate and shifts in forest composition on stand carbon balance

Treesearch

Chiang Jyh-Min; Louis Iverson; Anantha Prasad; Kim Brown

2006-01-01

Given that climate influences forest biogeographic distribution, many researchers have created models predicting shifts in tree species range with future climate change scenarios. The objective of this study is to investigate the forest carbon consequences of shifts in stand species composition with current and future climate scenarios using such a model.

Nonlinear Analysis and Scaling Laws for Noncircular Composite Structures Subjected to Combined Loads

NASA Technical Reports Server (NTRS)

Hilburger, Mark W.; Rose, Cheryl A.; Starnes, James H., Jr.

2001-01-01

Results from an analytical study of the response of a built-up, multi-cell noncircular composite structure subjected to combined internal pressure and mechanical loads are presented. Nondimensional parameters and scaling laws based on a first-order shear-deformation plate theory are derived for this noncircular composite structure. The scaling laws are used to design sub-scale structural models for predicting the structural response of a full-scale structure representative of a portion of a blended-wing-body transport aircraft. Because of the complexity of the full-scale structure, some of the similitude conditions are relaxed for the sub-scale structural models. Results from a systematic parametric study are used to determine the effects of relaxing selected similitude conditions on the sensitivity of the effectiveness of using the sub-scale structural model response characteristics for predicting the full-scale structure response characteristics.

Cool Bottom Processing on the AGB and Presolar Grain Compositions

NASA Technical Reports Server (NTRS)

Nollett, Kenneth M.; Busso, M.; Wasserburg, G. J.

2002-01-01

We describe results from a model of cool bottom processing (CBP) in AGB (asymptotic giant branch) stars. We predict O, Al, C and N isotopic compositions of circumstellar grains. Measured compositions of mainstream SiC grains and many oxide grains are consistent with CBP. Additional information is contained in the original extended abstract.

Development of a Risk Prediction Model and Clinical Risk Score for Isolated Tricuspid Valve Surgery.

PubMed

LaPar, Damien J; Likosky, Donald S; Zhang, Min; Theurer, Patty; Fonner, C Edwin; Kern, John A; Bolling, Stephen F; Drake, Daniel H; Speir, Alan M; Rich, Jeffrey B; Kron, Irving L; Prager, Richard L; Ailawadi, Gorav

2018-02-01

While tricuspid valve (TV) operations remain associated with high mortality (∼8-10%), no robust prediction models exist to support clinical decision-making. We developed a preoperative clinical risk model with an easily calculable clinical risk score (CRS) to predict mortality and major morbidity after isolated TV surgery. Multi-state Society of Thoracic Surgeons database records were evaluated for 2,050 isolated TV repair and replacement operations for any etiology performed at 50 hospitals (2002-2014). Parsimonious preoperative risk prediction models were developed using multi-level mixed effects regression to estimate mortality and composite major morbidity risk. Model results were utilized to establish a novel CRS for patients undergoing TV operations. Models were evaluated for discrimination and calibration. Operative mortality and composite major morbidity rates were 9% and 42%, respectively. Final regression models performed well (both P<0.001, AUC = 0.74 and 0.76) and included preoperative factors: age, gender, stroke, hemodialysis, ejection fraction, lung disease, NYHA class, reoperation and urgent or emergency status (all P<0.05). A simple CRS from 0-10+ was highly associated (P<0.001) with incremental increases in predicted mortality and major morbidity. Predicted mortality risk ranged from 2%-34% across CRS categories, while predicted major morbidity risk ranged from 13%-71%. Mortality and major morbidity after isolated TV surgery can be predicted using preoperative patient data from the STS Adult Cardiac Database. A simple clinical risk score predicts mortality and major morbidity after isolated TV surgery. This score may facilitate perioperative counseling and identification of suitable patients for TV surgery. Copyright © 2018 The Society of Thoracic Surgeons. Published by Elsevier Inc. All rights reserved.

Modeling the VARTM Composite Manufacturing Process

NASA Technical Reports Server (NTRS)

Song, Xiao-Lan; Loos, Alfred C.; Grimsley, Brian W.; Cano, Roberto J.; Hubert, Pascal

2004-01-01

A comprehensive simulation model of the Vacuum Assisted Resin Transfer Modeling (VARTM) composite manufacturing process has been developed. For isothermal resin infiltration, the model incorporates submodels which describe cure of the resin and changes in resin viscosity due to cure, resin flow through the reinforcement preform and distribution medium and compaction of the preform during the infiltration. The accuracy of the model was validated by measuring the flow patterns during resin infiltration of flat preforms. The modeling software was used to evaluate the effects of the distribution medium on resin infiltration of a flat preform. Different distribution medium configurations were examined using the model and the results were compared with data collected during resin infiltration of a carbon fabric preform. The results of the simulations show that the approach used to model the distribution medium can significantly effect the predicted resin infiltration times. Resin infiltration into the preform can be accurately predicted only when the distribution medium is modeled correctly.

Updraft Fixed Bed Gasification Aspen Plus Model

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

2007-09-27

The updraft fixed bed gasification model provides predictive modeling capabilities for updraft fixed bed gasifiers, when devolatilization data is available. The fixed bed model is constructed using Aspen Plus, process modeling software, coupled with a FORTRAN user kinetic subroutine. Current updraft gasification models created in Aspen Plus have limited predictive capabilities and must be "tuned" to reflect a generalized gas composition as specified in literature or by the gasifier manufacturer. This limits the applicability of the process model.

Statistical characterization of the fatigue behavior of composite lamina

NASA Technical Reports Server (NTRS)

Yang, J. N.; Jones, D. L.

1979-01-01

A theoretical model was developed to predict statistically the effects of constant and variable amplitude fatigue loadings on the residual strength and fatigue life of composite lamina. The parameters in the model were established from the results of a series of static tensile tests and a fatigue scan and a number of verification tests were performed. Abstracts for two other papers on the effect of load sequence on the statistical fatigue of composites are also presented.

Dynamics of nanoparticle-protein corona complex formation: analytical results from population balance equations.

PubMed

Darabi Sahneh, Faryad; Scoglio, Caterina; Riviere, Jim

2013-01-01

Nanoparticle-protein corona complex formation involves absorption of protein molecules onto nanoparticle surfaces in a physiological environment. Understanding the corona formation process is crucial in predicting nanoparticle behavior in biological systems, including applications of nanotoxicology and development of nano drug delivery platforms. This paper extends the modeling work in to derive a mathematical model describing the dynamics of nanoparticle corona complex formation from population balance equations. We apply nonlinear dynamics techniques to derive analytical results for the composition of nanoparticle-protein corona complex, and validate our results through numerical simulations. The model presented in this paper exhibits two phases of corona complex dynamics. In the first phase, proteins rapidly bind to the free surface of nanoparticles, leading to a metastable composition. During the second phase, continuous association and dissociation of protein molecules with nanoparticles slowly changes the composition of the corona complex. Given sufficient time, composition of the corona complex reaches an equilibrium state of stable composition. We find analytical approximate formulae for metastable and stable compositions of corona complex. Our formulae are very well-structured to clearly identify important parameters determining corona composition. The dynamics of biocorona formation constitute vital aspect of interactions between nanoparticles and living organisms. Our results further understanding of these dynamics through quantitation of experimental conditions, modeling results for in vitro systems to better predict behavior for in vivo systems. One potential application would involve a single cell culture medium related to a complex protein medium, such as blood or tissue fluid.

Predictive model for the Dutch post-consumer plastic packaging recycling system and implications for the circular economy.

PubMed

Brouwer, Marieke T; Thoden van Velzen, Eggo U; Augustinus, Antje; Soethoudt, Han; De Meester, Steven; Ragaert, Kim

2018-01-01

The Dutch post-consumer plastic packaging recycling network has been described in detail (both on the level of packaging types and of materials) from the household potential to the polymeric composition of the recycled milled goods. The compositional analyses of 173 different samples of post-consumer plastic packaging from different locations in the network were combined to indicatively describe the complete network with material flow analysis, data reconciliation techniques and process technological parameters. The derived potential of post-consumer plastic packages in the Netherlands in 2014 amounted to 341 Gg net (or 20.2 kg net.cap -1 .a -1 ). The complete recycling network produced 75.2 Gg milled goods, 28.1 Gg side products and 16.7 Gg process waste. Hence the net recycling chain yield for post-consumer plastic packages equalled 30%. The end-of-life fates for 35 different plastic packaging types were resolved. Additionally, the polymeric compositions of the milled goods and the recovered masses were derived with this model. These compositions were compared with experimentally determined polymeric compositions of recycled milled goods, which confirmed that the model predicts these compositions reasonably well. Also the modelled recovered masses corresponded reasonably well with those measured experimentally. The model clarified the origin of polymeric contaminants in recycled plastics, either sorting faults or packaging components, which gives directions for future improvement measures. Copyright © 2017 Elsevier Ltd. All rights reserved.

Optimizing Low-Concentration Mercury Removal from Aqueous Solutions by Reduced Graphene Oxide-Supported Fe3O4 Composites with the Aid of an Artificial Neural Network and Genetic Algorithm

PubMed Central

Cao, Rensheng; Hu, Jiwei; Ruan, Wenqian; Xiong, Kangning; Wei, Xionghui

2017-01-01

Reduced graphene oxide-supported Fe3O4 (Fe3O4/rGO) composites were applied in this study to remove low-concentration mercury from aqueous solutions with the aid of an artificial neural network (ANN) modeling and genetic algorithm (GA) optimization. The Fe3O4/rGO composites were prepared by the solvothermal method and characterized by X-ray diffraction (XRD), transmission electron microscopy (TEM), atomic force microscopy (AFM), N2-sorption, X-ray photoelectron spectroscopy (XPS), Fourier transform infrared spectroscopy (FTIR) and superconduction quantum interference device (SQUID). Response surface methodology (RSM) and ANN were employed to model the effects of different operating conditions (temperature, initial pH, initial Hg ion concentration and contact time) on the removal of the low-concentration mercury from aqueous solutions by the Fe3O4/rGO composites. The ANN-GA model results (with a prediction error below 5%) show better agreement with the experimental data than the RSM model results (with a prediction error below 10%). The removal process of the low-concentration mercury obeyed the Freudlich isotherm and the pseudo-second-order kinetic model. In addition, a regeneration experiment of the Fe3O4/rGO composites demonstrated that these composites can be reused for the removal of low-concentration mercury from aqueous solutions. PMID:29112141

The effect of weak interface on transverse properties of a ceramic matrix composite

NASA Technical Reports Server (NTRS)

Shimansky, R. A.; Hahn, H. T.; Salamon, N. J.

1990-01-01

Experimental studies conducted at NASA Lewis on SiC reaction-bonded Si3N4 composite system showed that transverse stiffness and strength were much lower than those predicted from existing analytical models based on good interfacial bonding. It was believed that weakened interfaces were responsible for the decrease in tranverse properties. To support this claim, a two-dimensional FEM analysis was performed for a transverse representative volume element. Specifically, the effect of fiber/matrix displacement compatibility at the interface was studied under both tensile and compressive transverse loadings. Interface debonding was represented using active gap elements connecting the fiber and matrix. The analyses show that the transverse tensile strength and stiffness are best predicted when a debonded interface is assumed for the composite. In fact, the measured properties can be predicted by simply replacing the fibers by voids. Thus, it is found that little or no interfacial bonding exists in the composite, and that an elastic analysis can predict the transverse stiffness and strength.

Molecular Modeling of Aerospace Polymer Matrices Including Carbon Nanotube-Enhanced Epoxy

NASA Astrophysics Data System (ADS)

Radue, Matthew S.

Carbon fiber (CF) composites are increasingly replacing metals used in major structural parts of aircraft, spacecraft, and automobiles. The current limitations of carbon fiber composites are addressed through computational material design by modeling the salient aerospace matrix materials. Molecular Dynamics (MD) models of epoxies with and without carbon nanotube (CNT) reinforcement and models of pure bismaleimides (BMIs) were developed to elucidate structure-property relationships for improved selection and tailoring of matrices. The influence of monomer functionality on the mechanical properties of epoxies is studied using the Reax Force Field (ReaxFF). From deformation simulations, the Young's modulus, yield point, and Poisson's ratio are calculated and analyzed. The results demonstrate an increase in stiffness and yield strength with increasing resin functionality. Comparison between the network structures of distinct epoxies is further advanced by the Monomeric Degree Index (MDI). Experimental validation demonstrates the MD results correctly predict the relationship in Young's moduli for all epoxies modeled. Therefore, the ReaxFF is confirmed to be a useful tool for studying the mechanical behavior of epoxies. While epoxies have been well-studied using MD, there has been no concerted effort to model cured BMI polymers due to the complexity of the network-forming reactions. A novel, adaptable crosslinking framework is developed for implementing 5 distinct cure reactions of Matrimid-5292 (a BMI resin) and investigating the network structure using MD simulations. The influence of different cure reactions and extent of curing are analyzed on the several thermo-mechanical properties such as mass density, glass transition temperature, coefficient of thermal expansion, elastic moduli, and thermal conductivity. The developed crosslinked models correctly predict experimentally observed trends for various properties. Finally, the epoxies modeled (di-, tri-, and tetra-functionalresins) are simulated with embedded CNT to understand how the affinity to nanoparticles affects the mechanical response. Multiscale modeling techniques are then employed to translate the molecular phenomena observed to predict the behavior of realistic composites. The effective stiffness of hybrid composites are predicted for CNT/epoxy composites with randomly oriented CNTs, for CF/CNT/epoxy systems with aligned CFs and randomly oriented CNTs, and for woven CF/CNT/epoxy fabric with randomly oriented CNTs. The results indicate that in the CNT/epoxy systems the epoxy type has a significant influence on the elastic properties. For the CF/CNT/epoxy hybrid composites, the axial modulus is highly influenced by CF concentration, while the transverse modulus is primarily affected by the CNT weight fraction.

Predicting the composition of red wine blends using an array of multicomponent Peptide-based sensors.

PubMed

Ghanem, Eman; Hopfer, Helene; Navarro, Andrea; Ritzer, Maxwell S; Mahmood, Lina; Fredell, Morgan; Cubley, Ashley; Bolen, Jessica; Fattah, Rabia; Teasdale, Katherine; Lieu, Linh; Chua, Tedmund; Marini, Federico; Heymann, Hildegarde; Anslyn, Eric V

2015-05-20

Differential sensing using synthetic receptors as mimics of the mammalian senses of taste and smell is a powerful approach for the analysis of complex mixtures. Herein, we report on the effectiveness of a cross-reactive, supramolecular, peptide-based sensing array in differentiating and predicting the composition of red wine blends. Fifteen blends of Cabernet Sauvignon, Merlot and Cabernet Franc, in addition to the mono varietals, were used in this investigation. Linear Discriminant Analysis (LDA) showed a clear differentiation of blends based on tannin concentration and composition where certain mono varietals like Cabernet Sauvignon seemed to contribute less to the overall characteristics of the blend. Partial Least Squares (PLS) Regression and cross validation were used to build a predictive model for the responses of the receptors to eleven binary blends and the three mono varietals. The optimized model was later used to predict the percentage of each mono varietal in an independent test set composted of four tri-blends with a 15% average error. A partial least square regression model using the mouth-feel and taste descriptive sensory attributes of the wine blends revealed a strong correlation of the receptors to perceived astringency, which is indicative of selective binding to polyphenols in wine.

Micromechanics Fatigue Damage Analysis Modeling for Fabric Reinforced Ceramic Matrix Composites

NASA Technical Reports Server (NTRS)

Min, J. B.; Xue, D.; Shi, Y.

2013-01-01

A micromechanics analysis modeling method was developed to analyze the damage progression and fatigue failure of fabric reinforced composite structures, especially for the brittle ceramic matrix material composites. A repeating unit cell concept of fabric reinforced composites was used to represent the global composite structure. The thermal and mechanical properties of the repeating unit cell were considered as the same as those of the global composite structure. The three-phase micromechanics, the shear-lag, and the continuum fracture mechanics models were integrated with a statistical model in the repeating unit cell to predict the progressive damages and fatigue life of the composite structures. The global structure failure was defined as the loss of loading capability of the repeating unit cell, which depends on the stiffness reduction due to material slice failures and nonlinear material properties in the repeating unit cell. The present methodology is demonstrated with the analysis results evaluated through the experimental test performed with carbon fiber reinforced silicon carbide matrix plain weave composite specimens.

Fatigue Life Prediction of Fiber-Reinforced Ceramic-Matrix Composites with Different Fiber Preforms at Room and Elevated Temperatures

PubMed Central

Li, Longbiao

2016-01-01

In this paper, the fatigue life of fiber-reinforced ceramic-matrix composites (CMCs) with different fiber preforms, i.e., unidirectional, cross-ply, 2D (two dimensional), 2.5D and 3D CMCs at room and elevated temperatures in air and oxidative environments, has been predicted using the micromechanics approach. An effective coefficient of the fiber volume fraction along the loading direction (ECFL) was introduced to describe the fiber architecture of preforms. The statistical matrix multicracking model and fracture mechanics interface debonding criterion were used to determine the matrix crack spacing and interface debonded length. Under cyclic fatigue loading, the fiber broken fraction was determined by combining the interface wear model and fiber statistical failure model at room temperature, and interface/fiber oxidation model, interface wear model and fiber statistical failure model at elevated temperatures, based on the assumption that the fiber strength is subjected to two-parameter Weibull distribution and the load carried by broken and intact fibers satisfies the Global Load Sharing (GLS) criterion. When the broken fiber fraction approaches the critical value, the composites fatigue fracture. PMID:28773332

Electrical Resistance of SiC/SiC Ceramic Matrix Composites for Damage Detection and Life-Prediction

NASA Technical Reports Server (NTRS)

Smith, Craig; Morscher, Gregory; Xia, Zhenhai

2009-01-01

Ceramic matrix composites (CMC) are suitable for high temperature structural applications such as turbine airfoils and hypersonic thermal protection systems due to their low density high thermal conductivity. The employment of these materials in such applications is limited by the ability to accurately monitor and predict damage evolution. Current nondestructive methods such as ultrasound, x-ray, and thermal imaging are limited in their ability to quantify small scale, transverse, in-plane, matrix cracks developed over long-time creep and fatigue conditions. CMC is a multifunctional material in which the damage is coupled with the material s electrical resistance, providing the possibility of real-time information about the damage state through monitoring of resistance. Here, resistance measurement of SiC/SiC composites under mechanical load at both room temperature monotonic and high temperature creep conditions, coupled with a modal acoustic emission technique, can relate the effects of temperature, strain, matrix cracks, fiber breaks, and oxidation to the change in electrical resistance. A multiscale model can in turn be developed for life prediction of in-service composites, based on electrical resistance methods. Results of tensile mechanical testing of SiC/SiC composites at room and high temperatures will be discussed. Data relating electrical resistivity to composite constituent content, fiber architecture, temperature, matrix crack formation, and oxidation will be explained, along with progress in modeling such properties.

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

NASA Astrophysics Data System (ADS)

Han, Xiao; Gao, Xiguang; Song, Yingdong

2017-10-01

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

A Model for Fiber Length Attrition in Injection-Molded Long-Fiber Composites

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

TuckerIII, Charles L.; Phelps, Jay H; El-Rahman, Ahmed Abd

2013-01-01

Long-fiber thermoplastic (LFT) composites consist of an engineering thermoplastic matrix with glass or carbon reinforcing fibers that are initially 10 to 13 mm long. When an LFT is injection molded, flow during mold filling orients the fibers and degrades the fiber length. Fiber orientation models for injection molding are well developed, and special orientation models for LFTs have been developed. Here we present a detailed quantitative model for fiber length attrition in a flowing fiber suspension. The model tracks a discrete fiber length distribution (FLD) at each spatial node. Key equations are a conservation equation for total fiber length, andmore » a breakage rate equation. The breakage rate is based on buckling of fibers due to hydrodynamic forces, when the fibers are in unfavorable orientations. The FLD model is combined with a mold filling simulation to predict spatial and temporal variations in fiber length distribution in a mold cavity during filling. The predictions compare well to experiments on a glassfiber/ PP LFT molding. Fiber length distributions predicted by the model are easily incorporated into micromechanics models to predict the stress-strain behavior of molded LFT materials. Author to whom correspondence should be addressed; electronic mail: ctucker@illinois.edu 1« less

Modeling homeorhetic trajectories of milk component yields, body composition and dry-matter intake in dairy cows: Influence of parity, milk production potential and breed.

PubMed

Daniel, J B; Friggens, N C; van Laar, H; Ingvartsen, K L; Sauvant, D

2018-06-01

The control of nutrient partitioning is complex and affected by many factors, among them physiological state and production potential. Therefore, the current model aims to provide for dairy cows a dynamic framework to predict a consistent set of reference performance patterns (milk component yields, body composition change, dry-matter intake) sensitive to physiological status across a range of milk production potentials (within and between breeds). Flows and partition of net energy toward maintenance, growth, gestation, body reserves and milk components are described in the model. The structure of the model is characterized by two sub-models, a regulating sub-model of homeorhetic control which sets dynamic partitioning rules along the lactation, and an operating sub-model that translates this into animal performance. The regulating sub-model describes lactation as the result of three driving forces: (1) use of previously acquired resources through mobilization, (2) acquisition of new resources with a priority of partition towards milk and (3) subsequent use of resources towards body reserves gain. The dynamics of these three driving forces were adjusted separately for fat (milk and body), protein (milk and body) and lactose (milk). Milk yield is predicted from lactose and protein yields with an empirical equation developed from literature data. The model predicts desired dry-matter intake as an outcome of net energy requirements for a given dietary net energy content. The parameters controlling milk component yields and body composition changes were calibrated using two data sets in which the diet was the same for all animals. Weekly data from Holstein dairy cows was used to calibrate the model within-breed across milk production potentials. A second data set was used to evaluate the model and to calibrate it for breed differences (Holstein, Danish Red and Jersey) on the mobilization/reconstitution of body composition and on the yield of individual milk components. These calibrations showed that the model framework was able to adequately simulate milk yield, milk component yields, body composition changes and dry-matter intake throughout lactation for primiparous and multiparous cows differing in their production level.

An inverse modeling strategy and a computer program to model garnet growth and resorption

NASA Astrophysics Data System (ADS)

Lanari, Pierre; Giuntoli, Francesco

2017-04-01

GrtMod is a computer program that allows numerical simulation of the pressure-temperature (P-T) evolution of garnet porphyroblasts based on the composition of successive growth zones preserved in natural samples. For each garnet growth stage, a new reactive bulk composition is optimized, allowing for resorption and/or fractionation of the previously crystalized garnet. The successive minimizations are performed using a heuristic search method and an objective function that quantify the amount by which the predicted garnet composition deviates from the measured values. The automated strategy of GrtMod includes a two stages optimization and one refinement stage. In this contribution, we will present several application examples. The new strategy provides quantitative estimates of the optimal P-T conditions whereas it was generally derived in a qualitatively way by using garnet isopleth intersections in equilibrium phase diagrams. GrtMod can also be used to model the evolution of the reactive bulk composition along any P-T trajectories. The results for typical MORB and metapelite compositions demonstrate that fractional crystallization models are required to derive accurate P-T information from garnet compositional zoning. GrtMod can also be used to retrieve complex garnet histories involving several stages of resorption. For instance, it has been used to model the P-T condition of garnet growth in grains from the Sesia Zone (Western Alps). The compositional variability of successive growth zones is characterized using standardized X-ray maps and the program XMapTools. Permian garnet cores crystalized under granulite facies conditions (T > 800°C and P = 6 kbar), whereas Alpine garnet rims grew at eclogite facies conditions (650°C and 16 kbar) involving several successive episodes of resorption. The model predicts that up to 50 vol% of garnet was dissolved before a new episode of garnet growth.

Fast classification and compositional analysis of cornstover fractions using Fourier transform near-infrared techniques.

PubMed

Philip Ye, X; Liu, Lu; Hayes, Douglas; Womac, Alvin; Hong, Kunlun; Sokhansanj, Shahab

2008-10-01

The objectives of this research were to determine the variation of chemical composition across botanical fractions of cornstover, and to probe the potential of Fourier transform near-infrared (FT-NIR) techniques in qualitatively classifying separated cornstover fractions and in quantitatively analyzing chemical compositions of cornstover by developing calibration models to predict chemical compositions of cornstover based on FT-NIR spectra. Large variations of cornstover chemical composition for wide calibration ranges, which is required by a reliable calibration model, were achieved by manually separating the cornstover samples into six botanical fractions, and their chemical compositions were determined by conventional wet chemical analyses, which proved that chemical composition varies significantly among different botanical fractions of cornstover. Different botanic fractions, having total saccharide content in descending order, are husk, sheath, pith, rind, leaf, and node. Based on FT-NIR spectra acquired on the biomass, classification by Soft Independent Modeling of Class Analogy (SIMCA) was employed to conduct qualitative classification of cornstover fractions, and partial least square (PLS) regression was used for quantitative chemical composition analysis. SIMCA was successfully demonstrated in classifying botanical fractions of cornstover. The developed PLS model yielded root mean square error of prediction (RMSEP %w/w) of 0.92, 1.03, 0.17, 0.27, 0.21, 1.12, and 0.57 for glucan, xylan, galactan, arabinan, mannan, lignin, and ash, respectively. The results showed the potential of FT-NIR techniques in combination with multivariate analysis to be utilized by biomass feedstock suppliers, bioethanol manufacturers, and bio-power producers in order to better manage bioenergy feedstocks and enhance bioconversion.

Investigation of Micro-Scale Architectural Effects on Damage of Composites

NASA Technical Reports Server (NTRS)

Stier, Bertram; Bednarcyk, Brett A.; Simon, Jaan W.; Reese, Stefanie

2015-01-01

This paper presents a three-dimensional, energy based, anisotropic, stiffness reduction, progressive damage model for composite materials and composite material constituents. The model has been implemented as a user-defined constitutive model within the Abaqus finite element software package and applied to simulate the nonlinear behavior of a damaging epoxy matrix within a unidirectional composite material. Three different composite microstructures were considered as finite element repeating unit cells, with appropriate periodicity conditions applied at the boundaries. Results representing predicted transverse tensile, longitudinal shear, and transverse shear stress-strain curves are presented, along with plots of the local fields indicating the damage progression within the microstructure. It is demonstrated that the damage model functions appropriately at the matrix scale, enabling localization of the damage to simulate failure of the composite material. The influence of the repeating unit cell geometry and the effect of the directionality of the applied loading are investigated and discussed.

Enhanced production of medicinal polysaccharide by submerged fermentation of Lingzhi or Reishi medicinal mushroom Ganoderma lucidium (W.Curt.:Fr.) P. Karst. Using statistical and evolutionary optimization methods.

PubMed

Baskar, Gurunathan; Sathya, Shree Rajesh K

2011-01-01

Statistical and evolutionary optimization of media composition was employed for the production of medicinal exopolysaccharide (EPS) by Lingzhi or Reishi medicinal mushroom Ganoderma lucidium MTCC 1039 using soya bean meal flour as low-cost substrate. Soya bean meal flour, ammonium chloride, glucose, and pH were identified as the most important variables for EPS yield using the two-level Plackett-Burman design and further optimized using the central composite design (CCD) and the artificial neural network (ANN)-linked genetic algorithm (GA). The high value of coefficient of determination of ANN (R² = 0.982) indicates that the ANN model was more accurate than the second-order polynomial model of CCD (R² = 0.91) for representing the effect of media composition on EPS yield. The predicted optimum media composition using ANN-linked GA was soybean meal flour 2.98%, glucose 3.26%, ammonium chloride 0.25%, and initial pH 7.5 for the maximum predicted EPS yield of 1005.55 mg/L. The experimental EPS yield obtained using the predicted optimum media composition was 1012.36 mg/L, which validates the high degree of accuracy of evolutionary optimization for enhanced production of EPS by submerged fermentation of G. lucidium.

Prediction of functional aerobic capacity without exercise testing

NASA Technical Reports Server (NTRS)

Jackson, A. S.; Blair, S. N.; Mahar, M. T.; Wier, L. T.; Ross, R. M.; Stuteville, J. E.

1990-01-01

The purpose of this study was to develop functional aerobic capacity prediction models without using exercise tests (N-Ex) and to compare the accuracy with Astrand single-stage submaximal prediction methods. The data of 2,009 subjects (9.7% female) were randomly divided into validation (N = 1,543) and cross-validation (N = 466) samples. The validation sample was used to develop two N-Ex models to estimate VO2peak. Gender, age, body composition, and self-report activity were used to develop two N-Ex prediction models. One model estimated percent fat from skinfolds (N-Ex %fat) and the other used body mass index (N-Ex BMI) to represent body composition. The multiple correlations for the developed models were R = 0.81 (SE = 5.3 ml.kg-1.min-1) and R = 0.78 (SE = 5.6 ml.kg-1.min-1). This accuracy was confirmed when applied to the cross-validation sample. The N-Ex models were more accurate than what was obtained from VO2peak estimated from the Astrand prediction models. The SEs of the Astrand models ranged from 5.5-9.7 ml.kg-1.min-1. The N-Ex models were cross-validated on 59 men on hypertensive medication and 71 men who were found to have a positive exercise ECG. The SEs of the N-Ex models ranged from 4.6-5.4 ml.kg-1.min-1 with these subjects.(ABSTRACT TRUNCATED AT 250 WORDS).

Predicting biomass of hyperdiverse and structurally complex central Amazonian forests - a virtual approach using extensive field data

DOE PAGES

Magnabosco Marra, Daniel; Higuchi, Niro; Trumbore, Susan E.; ...

2016-03-11

Notice on corrigendum: This paper has a corresponding corrigendum published. Please read the corrigendum first. Old-growth forests are subject to substantial changes in structure and species composition due to the intensification of human activities, gradual climate change and extreme weather events. Trees store ca. 90 % of the total aboveground biomass (AGB) in tropical forests and precise tree biomass estimation models are crucial for management and conservation. In the central Amazon, predicting AGB at large spatial scales is a challenging task due to the heterogeneity of successional stages, high tree species diversity and inherent variations in tree allometry and architecture.more » We parameterized generic AGB estimation models applicable across species and a wide range of structural and compositional variation related to species sorting into height layers as well as frequent natural disturbances. We used 727 trees (diameter at breast height ≥ 5 cm) from 101 genera and at least 135 species harvested in a contiguous forest near Manaus, Brazil. Sampling from this data set we assembled six scenarios designed to span existing gradients in floristic composition and size distribution in order to select models that best predict AGB at the landscape level across successional gradients. We found that good individual tree model fits do not necessarily translate into reliable predictions of AGB at the landscape level. When predicting AGB (dry mass) over scenarios using our different models and an available pantropical model, we observed systematic biases ranging from -31 % (pantropical) to +39 %, with root-mean-square error (RMSE) values of up to 130 Mg ha -1 (pantropical). Our first and second best models had both low mean biases (0.8 and 3.9 %, respectively) and RMSE (9.4 and 18.6 Mg ha -1) when applied over scenarios. Predicting biomass correctly at the landscape level in hyperdiverse and structurally complex tropical forests, especially allowing good performance at the margins of data availability for model construction/calibration, requires the inclusion of predictors that express inherent variations in species architecture. The model of interest should comprise the floristic composition and size-distribution variability of the target forest, implying that even generic global or pantropical biomass estimation models can lead to strong biases. Reliable biomass assessments for the Amazon basin (i.e., secondary forests) still depend on the collection of allometric data at the local/regional scale and forest inventories including species-specific attributes, which are often unavailable or estimated imprecisely in most regions.« less

Corrigendum to "Predicting biomass of hyperdiverse and structurally complex central Amazonian forests — a virtual approach using extensive field data" Published in Biogeosciences, 13, 1553-1570, 2016

DOE PAGES

Magnabosco Marra, Daniel; Higuchi, Niro; Trumbore, Susan E.; ...

2016-04-27

Old-growth forests are subject to substantial changes in structure and species composition due to the intensification of human activities, gradual climate change and extreme weather events. Trees store ca. 90% of the total aboveground biomass (AGB) in tropical forests and precise tree biomass estimation models are crucial for management and conservation. In the central Amazon, predicting AGB at large spatial scales is a challenging task due to the heterogeneity of successional stages, high tree species diversity and inherent variations in tree allometry and architecture. We parameterized generic AGB estimation models applicable across species and a wide range of structural andmore » compositional variation related to species sorting into height layers as well as frequent natural disturbances. We used 727 trees (diameter at breast height ≥5 cm) from 101 genera and at least 135 species harvested in a contiguous forest near Manaus, Brazil. Sampling from this data set we assembled six scenarios designed to span existing gradients in floristic composition and size distribution in order to select models that best predict AGB at the landscape level across successional gradients. We found that good individual tree model fits do not necessarily translate into reliable predictions of AGB at the landscape level. We observed systematic biases ranging from -31% (pantropical) to +39 %, with root-mean-square error (RMSE) values of up to 130-Mg ha -1 (pantropical), when predicting AGB (dry mass) over scenarios using our different models and an available pantropical model. Our first and second best models had both low mean biases (0.8 and 3.9 %, respectively) and RMSE (9.4 and 18.6 Mg ha -1) when applied over scenarios. Predicting biomass correctly at the landscape level in hyperdiverse and structurally complex tropical forests, especially allowing good performance at the margins of data availability for model construction/calibration, requires the inclusion of predictors that express inherent variations in species architecture. Furthermore, the model of interest should comprise the floristic composition and size-distribution variability of the target forest, implying that even generic global or pantropical biomass estimation models can lead to strong biases. Reliable biomass assessments for the Amazon basin (i.e., secondary forests) still depend on the collection of allometric data at the local/regional scale and forest inventories including species-specific attributes, which are often unavailable or estimated imprecisely in most regions.« less

Corrigendum to "Predicting biomass of hyperdiverse and structurally complex central Amazonian forests — a virtual approach using extensive field data" Published in Biogeosciences, 13, 1553-1570, 2016

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

Magnabosco Marra, Daniel; Higuchi, Niro; Trumbore, Susan E.

Old-growth forests are subject to substantial changes in structure and species composition due to the intensification of human activities, gradual climate change and extreme weather events. Trees store ca. 90% of the total aboveground biomass (AGB) in tropical forests and precise tree biomass estimation models are crucial for management and conservation. In the central Amazon, predicting AGB at large spatial scales is a challenging task due to the heterogeneity of successional stages, high tree species diversity and inherent variations in tree allometry and architecture. We parameterized generic AGB estimation models applicable across species and a wide range of structural andmore » compositional variation related to species sorting into height layers as well as frequent natural disturbances. We used 727 trees (diameter at breast height ≥5 cm) from 101 genera and at least 135 species harvested in a contiguous forest near Manaus, Brazil. Sampling from this data set we assembled six scenarios designed to span existing gradients in floristic composition and size distribution in order to select models that best predict AGB at the landscape level across successional gradients. We found that good individual tree model fits do not necessarily translate into reliable predictions of AGB at the landscape level. We observed systematic biases ranging from -31% (pantropical) to +39 %, with root-mean-square error (RMSE) values of up to 130-Mg ha -1 (pantropical), when predicting AGB (dry mass) over scenarios using our different models and an available pantropical model. Our first and second best models had both low mean biases (0.8 and 3.9 %, respectively) and RMSE (9.4 and 18.6 Mg ha -1) when applied over scenarios. Predicting biomass correctly at the landscape level in hyperdiverse and structurally complex tropical forests, especially allowing good performance at the margins of data availability for model construction/calibration, requires the inclusion of predictors that express inherent variations in species architecture. Furthermore, the model of interest should comprise the floristic composition and size-distribution variability of the target forest, implying that even generic global or pantropical biomass estimation models can lead to strong biases. Reliable biomass assessments for the Amazon basin (i.e., secondary forests) still depend on the collection of allometric data at the local/regional scale and forest inventories including species-specific attributes, which are often unavailable or estimated imprecisely in most regions.« less

Impacts of Process and Prediction Uncertainties on Projected Hanford Waste Glass Amount

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

Gervasio, V.; Kim, D. S.; Vienna, J. D.

Analyses were performed to evaluate the impacts of using the advanced glass models, constraints, and uncertainty descriptions on projected Hanford glass mass. The maximum allowable waste oxide loading (WOL) was estimated for waste compositions while simultaneously satisfying all applicable glass property and composition constraints with sufficient confidence. Different components of prediction and composition/process uncertainties were systematically included in the calculations to evaluate their impacts on glass mass. The analyses estimated the production of 23,360 MT of immobilized high-level waste (IHLW) glass when no uncertainties were taken into account. Accounting for prediction and composition/process uncertainties resulted in 5.01 relative percent increasemore » in estimated glass mass of 24,531 MT. Roughly equal impacts were found for prediction uncertainties (2.58 RPD) and composition/process uncertainties (2.43 RPD). The immobilized low-activity waste (ILAW) mass was predicted to be 282,350 MT without uncertainty and with waste loading “line” rules in place. Accounting for prediction and composition/process uncertainties resulted in only 0.08 relative percent increase in estimated glass mass of 282,562 MT. Without application of line rules the glass mass decreases by 10.6 relative percent (252,490 MT) for the case with no uncertainties. Addition of prediction uncertainties increases glass mass by 1.32 relative percent and the addition of composition/process uncertainties increase glass mass by an additional 7.73 relative percent (9.06 relative percent increase combined). The glass mass estimate without line rules (275,359 MT) was 2.55 relative percent lower than that with the line rules (282,562 MT), after accounting for all applicable uncertainties.« less

Predicting fiber refractive index from a measured preform index profile

NASA Astrophysics Data System (ADS)

Kiiveri, P.; Koponen, J.; Harra, J.; Novotny, S.; Husu, H.; Ihalainen, H.; Kokki, T.; Aallos, V.; Kimmelma, O.; Paul, J.

2018-02-01

When producing fiber lasers and amplifiers, silica glass compositions consisting of three to six different materials are needed. Due to the varying needs of different applications, substantial number of different glass compositions are used in the active fiber structures. Often it is not possible to find material parameters for theoretical models to estimate thermal and mechanical properties of those glass compositions. This makes it challenging to predict accurately fiber core refractive index values, even if the preform index profile is measured. Usually the desired fiber refractive index value is achieved experimentally, which is expensive. To overcome this problem, we analyzed statistically the changes between the measured preform and fiber index values. We searched for correlations that would help to predict the Δn-value change from preform to fiber in a situation where we don't know the values of the glass material parameters that define the change. Our index change models were built using the data collected from preforms and fibers made by the Direct Nanoparticle Deposition (DND) technology.

Long-term monitoring and prediction for settlement and composition of refuse in Shanghai Laogang Municipal Landfill.

PubMed

Jiangying, Liu; Dimin, Xu; Youcai, Zhao; Shaowei, Chen; Guojian, Li; Qi, Zhou

2004-09-01

Parameters about composition of refuse such as mass percentage of biodegradable matter, volatile solid, organic carbon, cellulose, total sugar, and settlement were monitored and analyzed in a large-scale experimental unit. The empirical formulas between composition and refuse age were established in terms of the data obtained from the experimental unit and verified by comparing with the corresponding parameters of refuse in the closed landfill units from 1991 until 1994 in the Shanghai Laogang Municipal Landfill. Furthermore, the long-term prediction for the composition of refuse was made, and it was predicted that the half-life is 7 to 11 years for biodegradable matter, 9 to 12 years for organic carbon or volatile solid, 7 to 16 years for cellulose, and 4 to 6 years for total sugar. In addition, a mathematical model, based on the mechanism of refuse biodegradation in the landfill, was developed to simulate the relationship between the settlement and the refuse age and manifests the secondary settlement potential. The mathematical model was proved not only to be reliable but also should be accurate for predicting the settlement of the landfill. The secondary settlement, which mainly results from the slow and gradual biodegradation of refuse, is linear with respect to the exponent of refuse age. Finally, according to the settlement model and empirical biodegradation formulas, it may be predicted that, 79.4% of biodegradable matter, 92.9% of total sugar, 72.7% of volatile solid and organic carbon, and 73.1% of cellulose will be biodegraded and that 79% of the maximum secondary settlement potential will occur before the Shanghai Laogang Municipal Landfill is in a high stabilization situation, i.e., approximately 21 years after final closure.

Thermo-mechanical response predictions for metal matrix composite laminates

NASA Technical Reports Server (NTRS)

Aboudi, J.; Hidde, J. S.; Herakovich, C. T.

1991-01-01

An analytical micromechanical model is employed for prediction of the stress-strain response of metal matrix composite laminates subjected to thermomechanical loading. The predicted behavior of laminates is based upon knowledge of the thermomechanical response of the transversely isotropic, elastic fibers and the elastic-viscoplastic, work-hardening matrix. The method is applied to study the behavior of silicon carbide/titanium metal matrix composite laminates. The response of laminates is compared with that of unidirectional lamina. The results demonstrate the effect of cooling from a stress-free temperature and the mismatch of thermal and mechanical properties of the constituent phases on the laminate's subsequent mechanical response. Typical results are presented for a variety of laminates subjected to monotonic tension, monotonic shear and cyclic tensile/compressive loadings.

Dielectric properties of CaCu3Ti4O12-silicone resin composites

NASA Astrophysics Data System (ADS)

Babu, Sanjesh; Singh, Kirti; Govindan, Anil

2012-06-01

CaCu3Ti4O12 (CCTO)-silicone resin composites with various CCTO volume fractions were prepared. Relatively high dielectric constant ( ɛ=119) and low loss (tan δ=0.35) of the composites with CCTO volume fraction of 0.9 were observed. Two theoretical models were employed to predict the dielectric constant of these composites; the dielectric constant obtained via the Maxwell-Garnett model was in close agreement with the experimental data. The dielectric constant of CCTO-silicone resin composites showed a weak frequency dependence at the measuring frequency range and the loss tangent apparently decreases with increase in frequency.

Chemometric compositional analysis of phenolic compounds in fermenting samples and wines using different infrared spectroscopy techniques.

PubMed

Aleixandre-Tudo, Jose Luis; Nieuwoudt, Helene; Aleixandre, Jose Luis; du Toit, Wessel

2018-01-01

The wine industry requires reliable methods for the quantification of phenolic compounds during the winemaking process. Infrared spectroscopy appears as a suitable technique for process control and monitoring. The ability of Fourier transform near infrared (FT-NIR), attenuated total reflectance mid infrared (ATR-MIR) and Fourier transform infrared (FT-IR) spectroscopies to predict compositional phenolic levels during red wine fermentation and aging was investigated. Prediction models containing a large number of samples collected over two vintages from several industrial fermenting tanks as well as wine samples covering a varying number of vintages were validated. FT-NIR appeared as the most accurate technique to predict the phenolic content. Although slightly less accurate models were observed, ATR-MIR and FT-IR can also be used for the prediction of the majority of phenolic measurements. Additionally, the slope and intercept test indicated a systematic error for the three spectroscopies which seems to be slightly more pronounced for HPLC generated phenolics data than for the spectrophotometric parameters. However, the results also showed that the predictions made with the three instruments are statistically comparable. The robustness of the prediction models was also investigated and discussed. Copyright © 2017 Elsevier B.V. All rights reserved.

Two cation exchange models for direct and inverse modelling of solution major cation composition in equilibrium with illite surfaces

NASA Astrophysics Data System (ADS)

Tournassat, Christophe; Gailhanou, Hélène; Crouzet, Catherine; Braibant, Gilles; Gautier, Anne; Lassin, Arnault; Blanc, Philippe; Gaucher, Eric C.

2007-03-01

Na/K, Na/Ca and Na/Mg exchange isotherms were performed on the fine fraction (<2 μm) of Imt-2 illite samples at a total normality of about 0.005 mol/L in anionic chloride medium. The derived selectivity coefficients for Na/K, Na/Ca and Na/Mg were found to vary as a function of the exchanger composition and compared well with the data collected in the literature for similar experimental conditions. Two models were built to reproduce the data: the first was a multi(2)-site model with constant Gaines and Thomas selectivity coefficients; the second was a one-site model taking into account surface species activity coefficients. The results of the models were in rather good agreement with both our data and literature data. The multi-site model proved to be efficient in predicting the exchanger composition as a function of the Na/Ca/Mg/K concentrations in solution, whereas the one-site model proved to be a better approach to derive the Na/Ca/Mg/K concentrations in solution based on the knowledge of the exchanger composition and the total normality of the solution. The interest of this approach is illustrated by the need for major cation solute concentration predictions in compacted clay for the characterization of nuclear deep disposal host rock repositories.

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

Nelson, Stacy; English, Shawn; Briggs, Timothy

Fiber-reinforced composite materials offer light-weight solutions to many structural challenges. In the development of high-performance composite structures, a thorough understanding is required of the composite materials themselves as well as methods for the analysis and failure prediction of the relevant composite structures. However, the mechanical properties required for the complete constitutive definition of a composite material can be difficult to determine through experimentation. Therefore, efficient methods are necessary that can be used to determine which properties are relevant to the analysis of a specific structure and to establish a structure's response to a material parameter that can only be definedmore » through estimation. The objectives of this paper deal with demonstrating the potential value of sensitivity and uncertainty quantification techniques during the failure analysis of loaded composite structures; and the proposed methods are applied to the simulation of the four-point flexural characterization of a carbon fiber composite material. Utilizing a recently implemented, phenomenological orthotropic material model that is capable of predicting progressive composite damage and failure, a sensitivity analysis is completed to establish which material parameters are truly relevant to a simulation's outcome. Then, a parameter study is completed to determine the effect of the relevant material properties' expected variations on the simulated four-point flexural behavior as well as to determine the value of an unknown material property. This process demonstrates the ability to formulate accurate predictions in the absence of a rigorous material characterization effort. Finally, the presented results indicate that a sensitivity analysis and parameter study can be used to streamline the material definition process as the described flexural characterization was used for model validation.« less

Modification of a Macromechanical Finite-Element Based Model for Impact Analysis of Triaxially-Braided Composites

NASA Technical Reports Server (NTRS)

Goldberg, Robert K.; Blinzler, Brina J.; Binienda, Wieslaw K.

2010-01-01

A macro level finite element-based model has been developed to simulate the mechanical and impact response of triaxially-braided polymer matrix composites. In the analytical model, the triaxial braid architecture is simulated by using four parallel shell elements, each of which is modeled as a laminated composite. For the current analytical approach, each shell element is considered to be a smeared homogeneous material. The commercial transient dynamic finite element code LS-DYNA is used to conduct the simulations, and a continuum damage mechanics model internal to LS-DYNA is used as the material constitutive model. The constitutive model requires stiffness and strength properties of an equivalent unidirectional composite. Simplified micromechanics methods are used to determine the equivalent stiffness properties, and results from coupon level tests on the braided composite are utilized to back out the required strength properties. Simulations of quasi-static coupon tests of several representative braided composites are conducted to demonstrate the correlation of the model. Impact simulations of a represented braided composites are conducted to demonstrate the capability of the model to predict the penetration velocity and damage patterns obtained experimentally.

Investigation of a Macromechanical Approach to Analyzing Triaxially-Braided Polymer Composites

NASA Technical Reports Server (NTRS)

Goldberg, Robert K.; Blinzler, Brina J.; Binienda, Wieslaw K.

2010-01-01

A macro level finite element-based model has been developed to simulate the mechanical and impact response of triaxially-braided polymer matrix composites. In the analytical model, the triaxial braid architecture is simulated by using four parallel shell elements, each of which is modeled as a laminated composite. The commercial transient dynamic finite element code LS-DYNA is used to conduct the simulations, and a continuum damage mechanics model internal to LS-DYNA is used as the material constitutive model. The material stiffness and strength values required for the constitutive model are determined based on coupon level tests on the braided composite. Simulations of quasi-static coupon tests of a representative braided composite are conducted. Varying the strength values that are input to the material model is found to have a significant influence on the effective material response predicted by the finite element analysis, sometimes in ways that at first glance appear non-intuitive. A parametric study involving the input strength parameters provides guidance on how the analysis model can be improved.

A Simple Analytical Model for Magnetization and Coercivity of Hard/Soft Nanocomposite Magnets

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

Park, Jihoon; Hong, Yang-Ki; Lee, Woncheol

Here, we present a simple analytical model to estimate the magnetization (σ s) and intrinsic coercivity (Hci) of a hard/soft nanocomposite magnet using the mass fraction. Previously proposed models are based on the volume fraction of the hard phase of the composite. But, it is difficult to measure the volume of the hard or soft phase material of a composite. We synthesized Sm 2Co 7/Fe-Co, MnAl/Fe-Co, MnBi/Fe-Co, and BaFe 12O 19/Fe-Co composites for characterization of their σs and Hci. The experimental results are in good agreement with the present model. Therefore, this analytical model can be extended to predict themore » maximum energy product (BH) max of hard/soft composite.« less

A Simple Analytical Model for Magnetization and Coercivity of Hard/Soft Nanocomposite Magnets

DOE PAGES

Park, Jihoon; Hong, Yang-Ki; Lee, Woncheol; ...

2017-07-10

Here, we present a simple analytical model to estimate the magnetization (σ s) and intrinsic coercivity (Hci) of a hard/soft nanocomposite magnet using the mass fraction. Previously proposed models are based on the volume fraction of the hard phase of the composite. But, it is difficult to measure the volume of the hard or soft phase material of a composite. We synthesized Sm 2Co 7/Fe-Co, MnAl/Fe-Co, MnBi/Fe-Co, and BaFe 12O 19/Fe-Co composites for characterization of their σs and Hci. The experimental results are in good agreement with the present model. Therefore, this analytical model can be extended to predict themore » maximum energy product (BH) max of hard/soft composite.« less

Effects of a thermal perturbation on mineralogy and pore water composition in a clay-rock: An experimental and modeling study

NASA Astrophysics Data System (ADS)

Gailhanou, H.; Lerouge, C.; Debure, M.; Gaboreau, S.; Gaucher, E. C.; Grangeon, S.; Grenèche, J.-M.; Kars, M.; Madé, B.; Marty, N. C. M.; Warmont, F.; Tournassat, C.

2017-01-01

The physical and chemical properties of clay-rocks are, at least partly, controlled by the chemical composition of their pore water. In evaluating the concept of disposing of radioactive waste in clay-rock formations, determining pore water composition is an important step in predicting how a clay-rock will behave over time and as a function of external forces, such as chemical and thermal perturbations. This study aimed to assess experimental and modeling methodology to calculate pore water composition in a clay-rock as a function of temperature (up to 80 °C). Hydrothermal alteration experiments were carried out on clay-rock samples. We conducted comprehensive chemical and mineralogical characterization of the material before and after reaction, and monitored how the chemical parameters in the liquid and gas phases changed. We compared the experimental results with the a priori predictions made by various models that differed in their hypotheses on the reactivity of the minerals present in the system. Thermodynamic equilibrium could not be assessed unequivocally in these experiments and most of the predicted mineralogy changes were too subtle to be tracked quantitatively. However, from observing the neo-formation of minerals such as goethite we were able to assess the prominent role of Fe-bearing phases in the outcome of the experiments, especially for the measured pH and pCO2 values. After calibrating the amount of reacting Fe-bearing phases with our data, we proposed a thermodynamic model that was capable of predicting the chemical evolution of the systems under investigation as well as the evolution of other systems already published in the literature, with the same clay-rock material but with significant differences in experimental conditions.

Matrix Synthesis and Characterization

NASA Technical Reports Server (NTRS)

1984-01-01

The role of NASA in the area of composite material synthesis; evaluation techniques; prediction analysis techniques; solvent-resistant tough composite matrix; resistance to paint strippers; acceptable processing temperature and pressure for thermoplastics; and the role of computer modeling and fiber interface improvement were discussed.

Ternary isocratic mobile phase optimization utilizing resolution Design Space based on retention time and peak width modeling.

PubMed

Kawabe, Takefumi; Tomitsuka, Toshiaki; Kajiro, Toshi; Kishi, Naoyuki; Toyo'oka, Toshimasa

2013-01-18

An optimization procedure of ternary isocratic mobile phase composition in the HPLC method using a statistical prediction model and visualization technique is described. In this report, two prediction models were first evaluated to obtain reliable prediction results. The retention time prediction model was constructed by modification from past respectable knowledge of retention modeling against ternary solvent strength changes. An excellent correlation between observed and predicted retention time was given in various kinds of pharmaceutical compounds by the multiple regression modeling of solvent strength parameters. The peak width of half height prediction model employed polynomial fitting of the retention time, because a linear relationship between the peak width of half height and the retention time was not obtained even after taking into account the contribution of the extra-column effect based on a moment method. Accurate prediction results were able to be obtained by such model, showing mostly over 0.99 value of correlation coefficient between observed and predicted peak width of half height. Then, a procedure to visualize a resolution Design Space was tried as the secondary challenge. An artificial neural network method was performed to link directly between ternary solvent strength parameters and predicted resolution, which were determined by accurate prediction results of retention time and a peak width of half height, and to visualize appropriate ternary mobile phase compositions as a range of resolution over 1.5 on the contour profile. By using mixtures of similar pharmaceutical compounds in case studies, we verified a possibility of prediction to find the optimal range of condition. Observed chromatographic results on the optimal condition mostly matched with the prediction and the average of difference between observed and predicted resolution were approximately 0.3. This means that enough accuracy for prediction could be achieved by the proposed procedure. Consequently, the procedure to search the optimal range of ternary solvent strength achieving an appropriate separation is provided by using the resolution Design Space based on accurate prediction. Copyright © 2012 Elsevier B.V. All rights reserved.

Impacts of the mixing state and chemical composition on the cloud condensation nuclei (CCN) activity in Beijing during winter, 2016

NASA Astrophysics Data System (ADS)

Ren, J.; Zhang, F.

2017-12-01

Abstract.Understanding aerosol chemical composition and mixing state on CCN activity in polluted urban area is crucial to determine NCCN accurately and thus to quantify aerosol indirect effects. Aerosol hrgroscopicity, size-resolved cloud condensation nuclei (CCN) concentration and chemical composition are measured under polluted and background conditions in Beijing based on the Air Pollution and Human Health (APHH) field campaign in winter 2016. The CCN number concentration (NCCN) is predicted by using κ-Köhler theory from the PNSD and five simplified of the mixing state and chemical composition. The assumption of EIS (sulfate, nitrate and SOA internally mixed, and POA and BC externally mixed with size-resolved chemical composition) shows the best closure to predict NCCN with the ratio of predicted to measured NCCN of 0.96-1.12 both in POL and BG conditions. Under BG conditions, IB (internal mixture with bulk chemical composition) scheme achieves the best CCN closure during any periods of a day. In polluted days, EIS and IS (internal mixture with size-resolved chemical composition) scheme may achieve better closure than IB scheme due to the heterogeneity in particles composition across different size. ES (external mixture with size-resolved chemical composition) and EB (external mixture with bulk chemical composition) scheme markedly underestimate the NCCN with the ratio of predicted to measured NCCN of 0.6-0.8. In addition, we note that assumptions of size-resolved composition (IS or ES) show very limited promotes by comparing with the assumptions of bulk composition (IB or EB), furthermore, the prediction becomes worse by using size-resolved assumption in clean days. The predicted NCCN during eve-rush periods shows the most sensitivity to the five different assumptions, with ratios of the predicted and measured NCCN ranging from 0.5 to 1.4, reflecting great impacts from evening traffic and cooking sources. The result from the sensitivity examination of predict NCCN to particles mixing state and organic volume fractions with the aging of organic particles suggests that the mixing state of particles plays a minor role when the κorg exceeds 0.1. Our study could provide new dataset to evaluate the CCN parameterization in models in those heavily polluted regions with large fraction of POA and BC.

Silkworm cocoons inspire models for random fiber and particulate composites

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

Chen Fujia; Porter, David; Vollrath, Fritz

The bioengineering design principles evolved in silkworm cocoons make them ideal natural prototypes and models for structural composites. Cocoons depend for their stiffness and strength on the connectivity of bonding between their constituent materials of silk fibers and sericin binder. Strain-activated mechanisms for loss of bonding connectivity in cocoons can be translated directly into a surprisingly simple yet universal set of physically realistic as well as predictive quantitative structure-property relations for a wide range of technologically important fiber and particulate composite materials.

Silkworm cocoons inspire models for random fiber and particulate composites

NASA Astrophysics Data System (ADS)

Chen, Fujia; Porter, David; Vollrath, Fritz

2010-10-01

The bioengineering design principles evolved in silkworm cocoons make them ideal natural prototypes and models for structural composites. Cocoons depend for their stiffness and strength on the connectivity of bonding between their constituent materials of silk fibers and sericin binder. Strain-activated mechanisms for loss of bonding connectivity in cocoons can be translated directly into a surprisingly simple yet universal set of physically realistic as well as predictive quantitative structure-property relations for a wide range of technologically important fiber and particulate composite materials.

Local-global analysis of crack growth in continuously reinfoced ceramic matrix composites

NASA Technical Reports Server (NTRS)

Ballarini, Roberto; Ahmed, Shamim

1989-01-01

This paper describes the development of a mathematical model for predicting the strength and micromechanical failure characteristics of continuously reinforced ceramic matrix composites. The local-global analysis models the vicinity of a propagating crack tip as a local heterogeneous region (LHR) consisting of spring-like representation of the matrix, fibers and interfaces. Parametric studies are conducted to investigate the effects of LHR size, component properties, and interface conditions on the strength and sequence of the failure processes in the unidirectional composite system.

An evaluation of the hardwood regeneration model (REGEN) 16 years post-harvest of a regenerated stand in East Tennessee

Treesearch

Wayne K. Clatterbuck

2015-01-01

The REGEN model (developed by USDA Forest Service, Southern Research Station, Bent Creek Experimental Forest) was used prior to harvest to predict species composition of hardwoods at crown closure. This study evaluates whether the predictive ability of the model was effective by using post-harvest information after 16 years. Regeneration data were collected prior to...

Numerical Investigation of Desulfurization Kinetics in Gas-Stirred Ladles by a Quick Modeling Analysis Approach

NASA Astrophysics Data System (ADS)

Cao, Qing; Nastac, Laurentiu; Pitts-Baggett, April; Yu, Qiulin

2018-03-01

A quick modeling analysis approach for predicting the slag-steel reaction and desulfurization kinetics in argon gas-stirred ladles has been developed in this study. The model consists of two uncoupled components: (i) a computational fluid dynamics (CFD) model for predicting the fluid flow and the characteristics of slag-steel interface, and (ii) a multicomponent reaction kinetics model for calculating the desulfurization evolution. The steel-slag interfacial area and mass transfer coefficients predicted by the CFD simulation are used as the processing data for the reaction model. Since the desulfurization predictions are uncoupled from the CFD simulation, the computational time of this uncoupled predictive approach is decreased by at least 100 times for each case study when compared with the CFD-reaction kinetics fully coupled model. The uncoupled modeling approach was validated by comparing the evolution of steel and slag compositions with the experimentally measured data during ladle metallurgical furnace (LMF) processing at Nucor Steel Tuscaloosa, Inc. Then, the validated approach was applied to investigate the effects of the initial steel and slag compositions, as well as different types of additions during the refining process on the desulfurization efficiency. The results revealed that the sulfur distribution ratio and the desulfurization reaction can be promoted by making Al and CaO additions during the refining process. It was also shown that by increasing the initial Al content in liquid steel, both Al oxidation and desulfurization rates rapidly increase. In addition, it was found that the variation of the initial Si content in steel has no significant influence on the desulfurization rate. Lastly, if the initial CaO content in slag is increased or the initial Al2O3 content is decreased in the fluid-slag compositional range, the desulfurization rate can be improved significantly during the LMF process.

Numerical Investigation of Desulfurization Kinetics in Gas-Stirred Ladles by a Quick Modeling Analysis Approach

NASA Astrophysics Data System (ADS)

Cao, Qing; Nastac, Laurentiu; Pitts-Baggett, April; Yu, Qiulin

2018-06-01

A quick modeling analysis approach for predicting the slag-steel reaction and desulfurization kinetics in argon gas-stirred ladles has been developed in this study. The model consists of two uncoupled components: (i) a computational fluid dynamics (CFD) model for predicting the fluid flow and the characteristics of slag-steel interface, and (ii) a multicomponent reaction kinetics model for calculating the desulfurization evolution. The steel-slag interfacial area and mass transfer coefficients predicted by the CFD simulation are used as the processing data for the reaction model. Since the desulfurization predictions are uncoupled from the CFD simulation, the computational time of this uncoupled predictive approach is decreased by at least 100 times for each case study when compared with the CFD-reaction kinetics fully coupled model. The uncoupled modeling approach was validated by comparing the evolution of steel and slag compositions with the experimentally measured data during ladle metallurgical furnace (LMF) processing at Nucor Steel Tuscaloosa, Inc. Then, the validated approach was applied to investigate the effects of the initial steel and slag compositions, as well as different types of additions during the refining process on the desulfurization efficiency. The results revealed that the sulfur distribution ratio and the desulfurization reaction can be promoted by making Al and CaO additions during the refining process. It was also shown that by increasing the initial Al content in liquid steel, both Al oxidation and desulfurization rates rapidly increase. In addition, it was found that the variation of the initial Si content in steel has no significant influence on the desulfurization rate. Lastly, if the initial CaO content in slag is increased or the initial Al2O3 content is decreased in the fluid-slag compositional range, the desulfurization rate can be improved significantly during the LMF process.

Predicting major element mineral/melt equilibria - A statistical approach

NASA Technical Reports Server (NTRS)

Hostetler, C. J.; Drake, M. J.

1980-01-01

Empirical equations have been developed for calculating the mole fractions of NaO0.5, MgO, AlO1.5, SiO2, KO0.5, CaO, TiO2, and FeO in a solid phase of initially unknown identity given only the composition of the coexisting silicate melt. The approach involves a linear multivariate regression analysis in which solid composition is expressed as a Taylor series expansion of the liquid compositions. An internally consistent precision of approximately 0.94 is obtained, that is, the nature of the liquidus phase in the input data set can be correctly predicted for approximately 94% of the entries. The composition of the liquidus phase may be calculated to better than 5 mol % absolute. An important feature of this 'generalized solid' model is its reversibility; that is, the dependent and independent variables in the linear multivariate regression may be inverted to permit prediction of the composition of a silicate liquid produced by equilibrium partial melting of a polymineralic source assemblage.

Importance of succession, harvest, and climate change in determining future composition in US Central Hardwood Forests

Treesearch

Wen J. Wang; Hong S. He; Frank R. Thompson; Jacob S. Fraser; Brice B. Hanberry; William D. Dijak

2015-01-01

Most temperate forests in U.S. are recovering from heavy exploitation and are in intermediate successional stages where partial tree harvest is the primary disturbance. Changes in regional forest composition in response to climate change are often predicted for plant functional types using biophysical process models. These models usually simplify the simulation of...

Predicting relative species composition within mixed conifer forest pixels using zero‐inflated models and Landsat imagery

Treesearch

Shannon L. Savage; Rick L. Lawrence; John R. Squires

2015-01-01

Ecological and land management applications would often benefit from maps of relative canopy cover of each species present within a pixel, instead of traditional remote-sensing based maps of either dominant species or percent canopy cover without regard to species composition. Widely used statistical models for remote sensing, such as randomForest (RF),...

Thermo-mechanical characterization of a thermoplastic composite and prediction of the residual stresses and lamina curvature during cooling

NASA Astrophysics Data System (ADS)

Péron, Mael; Jacquemin, Frédéric; Casari, Pascal; Orange, Gilles; Bailleul, Jean-Luc; Boyard, Nicolas

2017-10-01

The prediction of process induced stresses during the cooling of thermoplastic composites still represents a challenge for the scientific community. However, a precise determination of these stresses is necessary in order to optimize the process conditions and thus lower the stresses effects on the final part health. A model is presented here, that permits the estimation of residual stresses during cooling. It relies on the nonlinear laminate theory, which has been adapted to arbitrary layup sequences. The developed model takes into account the heat transfers through the thickness of the laminate, together with the crystallization kinetics. The development of the composite mechanical properties during cooling is addressed by an incremental linear elastic constitutive law, which also considers thermal and crystallization strains. In order to feed the aforementioned model, a glass fiber and PA6.6 matrix unidirectional (UD) composite has been characterized. This work finally focuses on the identification of the material and process related parameters that lower the residual stresses level, including the ply sequence, the fiber volume fraction and the cooling rate.

Finite Elements Analysis of a Composite Semi-Span Test Article With and Without Discrete Damage

NASA Technical Reports Server (NTRS)

Lovejoy, Andrew E.; Jegley, Dawn C. (Technical Monitor)

2000-01-01

AS&M Inc. performed finite element analysis, with and without discrete damage, of a composite semi-span test article that represents the Boeing 220-passenger transport aircraft composite semi-span test article. A NASTRAN bulk data file and drawings of the test mount fixtures and semi-span components were utilized to generate the baseline finite element model. In this model, the stringer blades are represented by shell elements, and the stringer flanges are combined with the skin. Numerous modeling modifications and discrete source damage scenarios were applied to the test article model throughout the course of the study. This report details the analysis method and results obtained from the composite semi-span study. Analyses were carried out for three load cases: Braked Roll, LOG Down-Bending and 2.5G Up-Bending. These analyses included linear and nonlinear static response, as well as linear and nonlinear buckling response. Results are presented in the form of stress and strain plots. factors of safety for failed elements, buckling loads and modes, deflection prediction tables and plots, and strainage prediction tables and plots. The collected results are presented within this report for comparison to test results.

Spatiotemporal microbiota dynamics from quantitative in vitro and in silico models of the gut

NASA Astrophysics Data System (ADS)

Hwa, Terence

The human gut harbors a dynamic microbial community whose composition bears great importance for the health of the host. Here, we investigate how colonic physiology impacts bacterial growth behaviors, which ultimately dictate the gut microbiota composition. Combining measurements of bacterial growth physiology with analysis of published data on human physiology into a quantitative modeling framework, we show how hydrodynamic forces in the colon, in concert with other physiological factors, determine the abundances of the major bacterial phyla in the gut. Our model quantitatively explains the observed variation of microbiota composition among healthy adults, and predicts colonic water absorption (manifested as stool consistency) and nutrient intake to be two key factors determining this composition. The model further reveals that both factors, which have been identified in recent correlative studies, exert their effects through the same mechanism: changes in colonic pH that differentially affect the growth of different bacteria. Our findings show that a predictive and mechanistic understanding of microbial ecology in the human gut is possible, and offer the hope for the rational design of intervention strategies to actively control the microbiota. This work is supported by the Bill and Melinda Gates Foundation.

Failure analysis of single-bolted joint for lightweight composite laminates and metal plate

NASA Astrophysics Data System (ADS)

Li, Linjie; Qu, Junli; Liu, Xiangdong

2018-01-01

A three-dimensional progressive damage model was developed in ANSYS to predict the damage accumulation of single bolted joint in composite laminates under in-plane tensile loading. First, we describe the formulation and algorithm of this model. Second, we calculate the failure loads of the joint in fibre reinforced epoxy laminated composite plates and compare it with the experiment results, which validates that our model can appropriately simulate the ultimate tensile strength of the joints and the whole process of failure of structure. Finally, this model is applied to study the failure process of the light-weight composite material (USN125). The study also has a great potential to provide a strong basis for bolted joints design in composite Laminates as well as a simple tool for comparing different laminate geometries and bolt arrangements.

New Approach to Synthesis of Powder and Composite Materials by Electron Beam. Part 1. Technological Features of the Process

NASA Astrophysics Data System (ADS)

Rudskoy, A. I.; Kondrat'ev, S. Yu.; Sokolov, Yu. A.

2016-05-01

Possibilities of electron beam synthesis of structural and tool composite materials are considered. It is shown that a novel process involving mathematical modeling of each individual operation makes it possible to create materials with programmable structure and predictable properties from granules of various specified chemical compositions and sizes.

A model for prediction of fume formation rate in gas metal arc welding (GMAW), globular and spray modes, DC electrode positive.

PubMed

Dennis, J H; Hewitt, P J; Redding, C A; Workman, A D

2001-03-01

Prediction of fume formation rate during metal arc welding and the composition of the fume are of interest to occupational hygienists concerned with risk assessment and to manufacturers of welding consumables. A model for GMAW (DC electrode positive) is described based on the welder determined process parameters (current, wire feed rate and wire composition), on the surface area of molten metal in the arc and on the partial vapour pressures of the component metals of the alloy wire. The model is applicable to globular and spray welding transfer modes but not to dip mode. Metal evaporation from a droplet is evaluated for short time increments and total evaporation obtained by summation over the life of the droplet. The contribution of fume derived from the weld pool and spatter (particles of metal ejected from the arc) is discussed, as are limitations of the model. Calculated droplet temperatures are similar to values determined by other workers. A degree of relationship between predicted and measured fume formation rates is demonstrated but the model does not at this stage provide a reliable predictive tool.

A methodology to predict damage initiation, damage growth and residual strength in titanium matrix composites

NASA Technical Reports Server (NTRS)

Bakuckas, J. G., Jr.; Johnson, W. S.

1994-01-01

In this research, a methodology to predict damage initiation, damage growth, fatigue life, and residual strength in titanium matrix composites (TMC) is outlined. Emphasis was placed on micromechanics-based engineering approaches. Damage initiation was predicted using a local effective strain approach. A finite element analysis verified the prevailing assumptions made in the formulation of this model. Damage growth, namely, fiber-bridged matrix crack growth, was evaluated using a fiber bridging (FB) model which accounts for thermal residual stresses. This model combines continuum fracture mechanics and micromechanics analyses yielding stress-intensity factor solutions for fiber-bridged matrix cracks. It is assumed in the FB model that fibers in the wake of the matrix crack are idealized as a closure pressure, and an unknown constant frictional shear stress is assumed to act along the debond length of the bridging fibers. This frictional shear stress was used as a curve fitting parameter to the available experimental data. Fatigue life and post-fatigue residual strength were predicted based on the axial stress in the first intact 0 degree fiber calculated using the FB model and a three-dimensional finite element analysis.

Fracture mechanisms and fracture control in composite structures

NASA Astrophysics Data System (ADS)

Kim, Wone-Chul

Four basic failure modes--delamination, delamination buckling of composite sandwich panels, first-ply failure in cross-ply laminates, and compression failure--are analyzed using linear elastic fracture mechanics (LEFM) and the J-integral method. Structural failures, including those at the micromechanical level, are investigated with the aid of the models developed, and the critical strains for crack propagation for each mode are obtained. In the structural fracture analyses area, the fracture control schemes for delamination in a composite rib stiffener and delamination buckling in composite sandwich panels subjected to in-plane compression are determined. The critical fracture strains were predicted with the aid of LEFM for delamination and the J-integral method for delamination buckling. The use of toughened matrix systems has been recommended for improved damage tolerant design for delamination crack propagation. An experimental study was conducted to determine the onset of delamination buckling in composite sandwich panel containing flaws. The critical fracture loads computed using the proposed theoretical model and a numerical computational scheme closely followed the experimental measurements made on sandwich panel specimens of graphite/epoxy faceskins and aluminum honeycomb core with varying faceskin thicknesses and core sizes. Micromechanical models of fracture in composites are explored to predict transverse cracking of cross-ply laminates and compression fracture of unidirectional composites. A modified shear lag model which takes into account the important role of interlaminar shear zones between the 0 degree and 90 degree piles in cross-ply laminate is proposed and criteria for transverse cracking have been developed. For compressive failure of unidirectional composites, pre-existing defects play an important role. Using anisotropic elasticity, the stress state around a defect under a remotely applied compressive load is obtained. The experimentally observed complex compressive failure modes, such as shear crippling and pure compressive fiber failure of fibers are explained by the predicted stress distributions calculated in this work. These fracture analyses can be damage tolerant design methodology for composite structures. The proposed fracture criteria and the corresponding critical fracture strains provide the designer with quantitative guidelines for safe-life design. These have been incorporated into a fracture control plan for composite structures, which is also described. Currently, fracture control plans do not exist for composite structures; the proposed plan is a first step towards establishing fracture control and damage tolerant design methodology for this important class of materials.

Utility of a routine urinalysis in children who require clean intermittent catheterization.

PubMed

Forster, C S; Haslam, D B; Jackson, E; Goldstein, S L

2017-10-01

Children who require clean intermittent catheterization (CIC) frequently have positive urine cultures. However, diagnosing a urinary tract infection (UTI) can be difficult, as there are no standardized criteria. Routine urinalysis (UA) has good predictive accuracy for UTI in the general pediatric population, but data are limited on the utility of routine UA in the population of children who require CIC. To determine the utility of UA parameters (e.g. leukocyte esterase, nitrites, and pyuria) to predict UTI in children who require CIC, and identify a composite UA that has maximal predictive accuracy for UTI. A cross-sectional study of 133 children who required CIC, and had a UA and urine culture sent as part of standard of care. Patients in the no-UTI group all had UA and urine cultures sent as part of routine urodynamics, and were asymptomatic. Patients included in the UTI group had growth of ≥50,000 colony-forming units/ml of a known uropathogen on urine culture, in addition to two or more of the following symptoms: fever, abdominal pain, back pain, foul-smelling urine, new or worse incontinence, and pain with catheterization. Categorical data were compared using Chi-squared test, and continuous data were compared with Student's t-test. Sensitivity, specificity, and positive and negative predictive values were calculated for individual UA parameters, as well as the composite UA. Logistic regression was performed on potential composite UA models to identify the model that best fit the data. There was a higher proportion of patients in the no-UTI group with negative leukocyte esterase compared with the UTI group. There was a higher proportion of patients with UTI who had large leukocyte esterase and positive nitrites compared with the no-UTI group (Summary Figure). There was no between-group difference in urinary white blood cells. Positive nitrites were the most specific (84.4%) for UTI. None of the parameters had a high positive predictive value, while all had high negative predictive values. The composite model with the best Akaike information criterion was >10 urinary white blood cells and either moderate or large leukocyte esterase, which had a positive predictive value of 33.3 and a negative predictive value of 90.4. Routine UA had limited sensitivity, but moderate specificity, in predicting UTI in children who required CIC. The composite UA and moderate or large leukocyte esterase both had good negative predictive values for the outcome of UTI. Copyright © 2017 Journal of Pediatric Urology Company. Published by Elsevier Ltd. All rights reserved.

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

Noecker, Cecilia; Eng, Alexander; Srinivasan, Sujatha

ABSTRACT Multiple molecular assays now enable high-throughput profiling of the ecology, metabolic capacity, and activity of the human microbiome. However, to date, analyses of such multi-omic data typically focus on statistical associations, often ignoring extensive prior knowledge of the mechanisms linking these various facets of the microbiome. Here, we introduce a comprehensive framework to systematically link variation in metabolomic data with community composition by utilizing taxonomic, genomic, and metabolic information. Specifically, we integrate available and inferred genomic data, metabolic network modeling, and a method for predicting community-wide metabolite turnover to estimate the biosynthetic and degradation potential of a given community.more » Our framework then compares variation in predicted metabolic potential with variation in measured metabolites’ abundances to evaluate whether community composition can explain observed shifts in the community metabolome, and to identify key taxa and genes contributing to the shifts. Focusing on two independent vaginal microbiome data sets, each pairing 16S community profiling with large-scale metabolomics, we demonstrate that our framework successfully recapitulates observed variation in 37% of metabolites. Well-predicted metabolite variation tends to result from disease-associated metabolism. We further identify several disease-enriched species that contribute significantly to these predictions. Interestingly, our analysis also detects metabolites for which the predicted variation negatively correlates with the measured variation, suggesting environmental control points of community metabolism. Applying this framework to gut microbiome data sets reveals similar trends, including prediction of bile acid metabolite shifts. This framework is an important first step toward a system-level multi-omic integration and an improved mechanistic understanding of the microbiome activity and dynamics in health and disease. IMPORTANCEStudies characterizing both the taxonomic composition and metabolic profile of various microbial communities are becoming increasingly common, yet new computational methods are needed to integrate and interpret these data in terms of known biological mechanisms. Here, we introduce an analytical framework to link species composition and metabolite measurements, using a simple model to predict the effects of community ecology on metabolite concentrations and evaluating whether these predictions agree with measured metabolomic profiles. We find that a surprisingly large proportion of metabolite variation in the vaginal microbiome can be predicted based on species composition (including dramatic shifts associated with disease), identify putative mechanisms underlying these predictions, and evaluate the roles of individual bacterial species and genes. Analysis of gut microbiome data using this framework recovers similar community metabolic trends. This framework lays the foundation for model-based multi-omic integrative studies, ultimately improving our understanding of microbial community metabolism.« less

Meso-Scale Progressive Damage Behavior Characterization of Triaxial Braided Composites under Quasi-Static Tensile Load

NASA Astrophysics Data System (ADS)

Ren, Yiru; Zhang, Songjun; Jiang, Hongyong; Xiang, Jinwu

2018-04-01

Based on continuum damage mechanics (CDM), a sophisticated 3D meso-scale finite element (FE) model is proposed to characterize the progressive damage behavior of 2D Triaxial Braided Composites (2DTBC) with 60° braiding angle under quasi-static tensile load. The modified Von Mises strength criterion and 3D Hashin failure criterion are used to predict the damage initiation of the pure matrix and fiber tows. A combining interface damage and friction constitutive model is applied to predict the interface damage behavior. Murakami-Ohno stiffness degradation scheme is employed to predict the damage evolution process of each constituent. Coupling with the ordinary and translational symmetry boundary conditions, the tensile elastic response including tensile strength and failure strain of 2DTBC are in good agreement with the available experiment data. The numerical results show that the main failure modes of the composites under axial tensile load are pure matrix cracking, fiber and matrix tension failure in bias fiber tows, matrix tension failure in axial fiber tows and interface debonding; the main failure modes of the composites subjected to transverse tensile load are free-edge effect, matrix tension failure in bias fiber tows and interface debonding.

Composite laminate failure parameter optimization through four-point flexure experimentation and analysis

DOE PAGES

Nelson, Stacy; English, Shawn; Briggs, Timothy

2016-05-06

Fiber-reinforced composite materials offer light-weight solutions to many structural challenges. In the development of high-performance composite structures, a thorough understanding is required of the composite materials themselves as well as methods for the analysis and failure prediction of the relevant composite structures. However, the mechanical properties required for the complete constitutive definition of a composite material can be difficult to determine through experimentation. Therefore, efficient methods are necessary that can be used to determine which properties are relevant to the analysis of a specific structure and to establish a structure's response to a material parameter that can only be definedmore » through estimation. The objectives of this paper deal with demonstrating the potential value of sensitivity and uncertainty quantification techniques during the failure analysis of loaded composite structures; and the proposed methods are applied to the simulation of the four-point flexural characterization of a carbon fiber composite material. Utilizing a recently implemented, phenomenological orthotropic material model that is capable of predicting progressive composite damage and failure, a sensitivity analysis is completed to establish which material parameters are truly relevant to a simulation's outcome. Then, a parameter study is completed to determine the effect of the relevant material properties' expected variations on the simulated four-point flexural behavior as well as to determine the value of an unknown material property. This process demonstrates the ability to formulate accurate predictions in the absence of a rigorous material characterization effort. Finally, the presented results indicate that a sensitivity analysis and parameter study can be used to streamline the material definition process as the described flexural characterization was used for model validation.« less

Progressive Damage Modeling of Notched Composites

NASA Technical Reports Server (NTRS)

Aitharaju, Venkat; Aashat, Satvir; Kia, Hamid; Satyanarayana, Arunkumar; Bogert, Philip

2016-01-01

There is an increased interest in using non-crimp fabric reinforced composites for primary and secondary structural weight savings in high performance automobile applications. However, one of the main challenges in implementing these composites is the lack of understanding of damage progression under a wide variety of loading conditions for general configurations. Towards that end, researchers at GM and NASA are developing new damage models to predict accurately the progressive failure of these composites. In this investigation, the developed progressive failure analysis model was applied to study damage progression in center-notched and open-hole tension specimens for various laminate schemes. The results of a detailed study with respect to the effect of element size on the analysis outcome are presented.

A multilevel approach to modeling of porous bioceramics

NASA Astrophysics Data System (ADS)

Mikushina, Valentina A.; Sidorenko, Yury N.

2015-10-01

The paper is devoted to discussion of multiscale models of heterogeneous materials using principles. The specificity of approach considered is the using of geometrical model of composites representative volume, which must be generated with taking the materials reinforcement structure into account. In framework of such model may be considered different physical processes which have influence on the effective mechanical properties of composite, in particular, the process of damage accumulation. It is shown that such approach can be used to prediction the value of composite macroscopic ultimate strength. As an example discussed the particular problem of the study the mechanical properties of biocomposite representing porous ceramics matrix filled with cortical bones tissue.

Dependence of particle volume fraction on sound velocity and attenuation of EPDM composites.

PubMed

Kim, K S; Lee, K I; Kim, H Y; Yoon, S W; Hong, S H

2007-05-01

The sound velocity and the attenuation coefficient of EPDM (Ethylene-propylene Diene Monomer) composites incorporated with Silicon Carbide particles (SiCp's) of various volume fractions (0-40%) were experimentally and theoretically investigated. For the experiment a through-transmission technique was used. For the theoretical prediction, some mechanical property models such as Reuss model and Coherent Potential Approximation (CPA) model etc. were employed. The experimental results showed that the sound velocity decreased with the increase of the SiCp volume fraction up to 30% and then increased with the 40 vol% specimen. The attenuation coefficient was increased with the increasing SiCp volume fractions. The modified Reuss model with a longitudinal elastic modulus predicted most well the experimental sound velocity and elastic modulus results.

Intelligent processing for thick composites

NASA Astrophysics Data System (ADS)

Shin, Daniel Dong-Ok

2000-10-01

Manufacturing thick composite parts are associated with adverse curing conditions such as large in-plane temperature gradient and exotherms. The condition is further aggravated because the manufacturer's cycle and the existing cure control systems do not adequately counter such affects. In response, the forecast-based thermal control system is developed to have better cure control for thick composites. Accurate cure kinetic model is crucial for correctly identifying the amount of heat generated for composite process simulation. A new technique for identifying cure parameters for Hercules AS4/3502 prepreg is presented by normalizing the DSC data. The cure kinetics is based on an autocatalytic model for the proposed method, which uses dynamic and isothermal DSC data to determine its parameters. Existing models are also used to determine kinetic parameters but rendered inadequate because of the material's temperature dependent final degree of cure. The model predictions determined from the new technique showed good agreement to both isothermal and dynamic DSC data. The final degree of cure was also in good agreement with experimental data. A realistic cure simulation model including bleeder ply analysis and compaction is validated with Hercules AS4/3501-6 based laminates. The nonsymmetrical temperature distribution resulting from the presence of bleeder plies agreed well to the model prediction. Some of the discrepancies in the predicted compaction behavior were attributed to inaccurate viscosity and permeability models. The temperature prediction was quite good for the 3cm laminate. The validated process simulation model along with cure kinetics model for AS4/3502 prepreg were integrated into the thermal control system. The 3cm Hercules AS4/3501-6 and AS4/3502 laminate were fabricated. The resulting cure cycles satisfied all imposed requirements by minimizing exotherms and temperature gradient. Although the duration of the cure cycles increased, such phenomena was inevitable since longer time was required to maintain acceptable temperature gradient. The derived cure cycles were slightly different than what was anticipated by the offline simulation. Nevertheless, the system adapted to unanticipated events to satisfy the cure requirements.

High Density Polyethylene Composites Reinforced with Hybrid Inorganic Fillers: Morphology, Mechanical and Thermal Expansion Performance

PubMed Central

Huang, Runzhou; Xu, Xinwu; Lee, Sunyoung; Zhang, Yang; Kim, Birm-June; Wu, Qinglin

2013-01-01

The effect of individual and combined talc and glass fibers (GFs) on mechanical and thermal expansion performance of the filled high density polyethylene (HDPE) composites was studied. Several published models were adapted to fit the measured tensile modulus and strength of various composite systems. It was shown that the use of silane-modified GFs had a much larger effect in improving mechanical properties and in reducing linear coefficient of thermal expansion (LCTE) values of filled composites, compared with the use of un-modified talc particles due to enhanced bonding to the matrix, larger aspect ratio, and fiber alignment for GFs. Mechanical properties and LCTE values of composites with combined talc and GF fillers varied with talc and GF ratio at a given total filler loading level. The use of a larger portion of GFs in the mix can lead to better composite performance, while the use of talc can help lower the composite costs and increase its recyclability. The use of 30 wt % combined filler seems necessary to control LCTE values of filled HDPE in the data value range generally reported for commercial wood plastic composites. Tensile modulus for talc-filled composite can be predicted with rule of mixture, while a PPA-based model can be used to predict the modulus and strength of GF-filled composites. PMID:28788322

Constitutive modelling of composite biopolymer networks.

PubMed

Fallqvist, B; Kroon, M

2016-04-21

The mechanical behaviour of biopolymer networks is to a large extent determined at a microstructural level where the characteristics of individual filaments and the interactions between them determine the response at a macroscopic level. Phenomena such as viscoelasticity and strain-hardening followed by strain-softening are observed experimentally in these networks, often due to microstructural changes (such as filament sliding, rupture and cross-link debonding). Further, composite structures can also be formed with vastly different mechanical properties as compared to the individual networks. In this present paper, we present a constitutive model presented in a continuum framework aimed at capturing these effects. Special care is taken to formulate thermodynamically consistent evolution laws for dissipative effects. This model, incorporating possible anisotropic network properties, is based on a strain energy function, split into an isochoric and a volumetric part. Generalisation to three dimensions is performed by numerical integration over the unit sphere. Model predictions indicate that the constitutive model is well able to predict the elastic and viscoelastic response of biological networks, and to an extent also composite structures. Copyright © 2016 Elsevier Ltd. All rights reserved.

The effect of interface properties on nickel base alloy composites

NASA Technical Reports Server (NTRS)

Groves, M.; Grossman, T.; Senemeier, M.; Wright, K.

1995-01-01

This program was performed to assess the extent to which mechanical behavior models can predict the properties of sapphire fiber/nickel aluminide matrix composites and help guide their development by defining improved combinations of matrix and interface coating. The program consisted of four tasks: 1) selection of the matrices and interface coating constituents using a modeling-based approach; 2) fabrication of the selected materials; 3) testing and evaluation of the materials; and 4) evaluation of the behavior models to develop recommendations. Ni-50Al and Ni-20AI-30Fe (a/o) matrices were selected which gave brittle and ductile behavior, respectively, and an interface coating of PVD YSZ was selected which provided strong bonding to the sapphire fiber. Significant fiber damage and strength loss was observed in the composites which made straightforward comparison of properties with models difficult. Nevertheless, the models selected generally provided property predictions which agreed well with results when fiber degradation was incorporated. The presence of a strong interface bond was felt to be detrimental in the NiAI MMC system where low toughness and low strength were observed.

A Generalized Orthotropic Elasto-Plastic Material Model for Impact Analysis

NASA Astrophysics Data System (ADS)

Hoffarth, Canio

Composite materials are now beginning to provide uses hitherto reserved for metals in structural systems such as airframes and engine containment systems, wraps for repair and rehabilitation, and ballistic/blast mitigation systems. These structural systems are often subjected to impact loads and there is a pressing need for accurate prediction of deformation, damage and failure. There are numerous material models that have been developed to analyze the dynamic impact response of polymer matrix composites. However, there are key features that are missing in those models that prevent them from providing accurate predictive capabilities. In this dissertation, a general purpose orthotropic elasto-plastic computational constitutive material model has been developed to predict the response of composites subjected to high velocity impacts. The constitutive model is divided into three components - deformation model, damage model and failure model, with failure to be added at a later date. The deformation model generalizes the Tsai-Wu failure criteria and extends it using a strain-hardening-based orthotropic yield function with a non-associative flow rule. A strain equivalent formulation is utilized in the damage model that permits plastic and damage calculations to be uncoupled and capture the nonlinear unloading and local softening of the stress-strain response. A diagonal damage tensor is defined to account for the directionally dependent variation of damage. However, in composites it has been found that loading in one direction can lead to damage in multiple coordinate directions. To account for this phenomena, the terms in the damage matrix are semi-coupled such that the damage in a particular coordinate direction is a function of the stresses and plastic strains in all of the coordinate directions. The overall framework is driven by experimental tabulated temperature and rate-dependent stress-strain data as well as data that characterizes the damage matrix and failure. The developed theory has been implemented in a commercial explicit finite element analysis code, LS-DYNARTM, as MAT213. Several verification and validation tests using a commonly available carbon-fiber composite, Toyobo's T800/F3900, have been carried and the results show that the theory and implementation are efficient, robust and accurate.

Modeling of crack bridging in a unidirectional metal matrix composite

NASA Technical Reports Server (NTRS)

Ghosn, Louis J.; Kantzos, Pete; Telesman, Jack

1991-01-01

The effective fatigue crack driving force and crack opening profiles were determined analytically for fatigue tested unidirectional composite specimens exhibiting fiber bridging. The crack closure pressure due to bridging was modeled using two approaches; the fiber pressure model and the shear lag model. For both closure models, the Bueckner weight function method and the finite element method were used to calculate crack opening displacements and the crack driving force. The predicted near crack tip opening profile agreed well with the experimentally measured profiles for single edge notch SCS-6/Ti-15-3 metal matrix composite specimens. The numerically determined effective crack driving force, Delta K(sup eff), was calculated using both models to correlate the measure crack growth rate in the composite. The calculated Delta K(sup eff) from both models accounted for the crack bridging by showing a good agreement between the measured fatigue crack growth rates of the bridged composite and that of unreinforced, unbridged titanium matrix alloy specimens.

Modeling of crack bridging in a unidirectional metal matrix composite

NASA Technical Reports Server (NTRS)

Ghosn, Louis J.; Kantzos, Pete; Telesman, Jack

1992-01-01

The effective fatigue crack driving force and crack opening profiles were determined analytically for fatigue tested unidirectional composite specimens exhibiting fiber bridging. The crack closure pressure due to bridging was modeled using two approaches: the fiber pressure model and the shear lag model. For both closure models, the Bueckner weight function method and the finite element method were used to calculate crack opening displacements and the crack driving force. The predicted near crack tip opening profile agreed well with the experimentally measured profiles for single edge notch SCS-6/Ti-15-3 metal matrix composite specimens. The numerically determined effective crack driving force, Delta K(eff), was calculated using both models to correlate the measure crack growth rate in the composite. The calculated Delta K(eff) from both models accounted for the crack bridging by showing a good agreement between the measured fatigue crack growth rates of the bridged composite and that of unreinforced, unbridged titanium matrix alloy specimens.

Using Digital Terrain Modeling to Predict Ecological Types in the Balsam Mountains of Western North Carolina

Treesearch

Richard H. Odom; W. Henry McNab

2000-01-01

Relationships between overstory composition and topographic conditions were studied in high-elevation (>1300 meters) forests in the Balsam Mountains of western North Carolina to determine whether models could be developed to predict the occurrence of number vegetative communities in relation to topographic variables (elevation, landscape position, surface geometry,...

Mapping ecological systems with a random foret model: tradeoffs between errors and bias

Treesearch

Emilie Grossmann; Janet Ohmann; James Kagan; Heather May; Matthew Gregory

2010-01-01

New methods for predictive vegetation mapping allow improved estimations of plant community composition across large regions. Random Forest (RF) models limit over-fitting problems of other methods, and are known for making accurate classification predictions from noisy, nonnormal data, but can be biased when plot samples are unbalanced. We developed two contrasting...

Glass viscosity calculation based on a global statistical modelling approach

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

Fluegel, Alex

2007-02-01

A global statistical glass viscosity model was developed for predicting the complete viscosity curve, based on more than 2200 composition-property data of silicate glasses from the scientific literature, including soda-lime-silica container and float glasses, TV panel glasses, borosilicate fiber wool and E type glasses, low expansion borosilicate glasses, glasses for nuclear waste vitrification, lead crystal glasses, binary alkali silicates, and various further compositions from over half a century. It is shown that within a measurement series from a specific laboratory the reported viscosity values are often over-estimated at higher temperatures due to alkali and boron oxide evaporation during the measurementmore » and glass preparation, including data by Lakatos et al. (1972) and the recently published High temperature glass melt property database for process modeling by Seward et al. (2005). Similarly, in the glass transition range many experimental data of borosilicate glasses are reported too high due to phase separation effects. The developed global model corrects those errors. The model standard error was 9-17°C, with R^2 = 0.985-0.989. The prediction 95% confidence interval for glass in mass production largely depends on the glass composition of interest, the composition uncertainty, and the viscosity level. New insights in the mixed-alkali effect are provided.« less

Silicon in Mars' Core: A Prediction Based on Mars Model Using Nitrogen and Oxygen Isotopes in SNC Meteorites

NASA Technical Reports Server (NTRS)

Mohapatra, R. K.; Murty, S. V. S.

2002-01-01

Chemical and (oxygen) isotopic compositions of SNC meteorites have been used by a number of workers to infer the nature of precursor materials for the accretion of Mars. The idea that chondritic materials played a key role in the formation of Mars has been the central assumption in these works. Wanke and Dreibus have proposed a mixture of two types of chondritic materials, differing in oxygen fugacity but having CI type bulk chemical composition for the nonvolatile elements, for Mars' precursor. But a number of studies based on high pressure and temperature melting experiments do not favor a CI type bulk planet composition for Mars, as it predicts a bulk planet Fe/Si ratio much higher than that reported from the recent Pathfinder data. Oxygen forms the bulk of Mars (approximately 40% by wt.) and might provide clues to the type of materials that formed Mars. But models based on the oxygen isotopic compositions of SNC meteorites predict three different mixtures of precursor materials for Mars: 90% H + 10% CM, 85% H + 11% CV + 4% CI and 45% EH + 55% H. As each of these models has been shown to be consistent with the bulk geophysical properties (such as mean density, and moment of inertia factor) of Mars, the nature of the material that accreted to form Mars remains ambiguous.

Computational Design and Discovery of Ni-Based Alloys and Coatings: Thermodynamic Approaches Validated by Experiments

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

Liu, Zi-Kui; Gleeson, Brian; Shang, Shunli

This project developed computational tools that can complement and support experimental efforts in order to enable discovery and more efficient development of Ni-base structural materials and coatings. The project goal was reached through an integrated computation-predictive and experimental-validation approach, including first-principles calculations, thermodynamic CALPHAD (CALculation of PHAse Diagram), and experimental investigations on compositions relevant to Ni-base superalloys and coatings in terms of oxide layer growth and microstructure stabilities. The developed description included composition ranges typical for coating alloys and, hence, allow for prediction of thermodynamic properties for these material systems. The calculation of phase compositions, phase fraction, and phase stabilities,more » which are directly related to properties such as ductility and strength, was a valuable contribution, along with the collection of computational tools that are required to meet the increasing demands for strong, ductile and environmentally-protective coatings. Specifically, a suitable thermodynamic description for the Ni-Al-Cr-Co-Si-Hf-Y system was developed for bulk alloy and coating compositions. Experiments were performed to validate and refine the thermodynamics from the CALPHAD modeling approach. Additionally, alloys produced using predictions from the current computational models were studied in terms of their oxidation performance. Finally, results obtained from experiments aided in the development of a thermodynamic modeling automation tool called ESPEI/pycalphad - for more rapid discovery and development of new materials.« less

Prediction of as-cast grain size of inoculated aluminum alloys melt solidified under non-isothermal conditions

NASA Astrophysics Data System (ADS)

Du, Qiang; Li, Yanjun

2015-06-01

In this paper, a multi-scale as-cast grain size prediction model is proposed to predict as-cast grain size of inoculated aluminum alloys melt solidified under non-isothermal condition, i.e., the existence of temperature gradient. Given melt composition, inoculation and heat extraction boundary conditions, the model is able to predict maximum nucleation undercooling, cooling curve, primary phase solidification path and final as-cast grain size of binary alloys. The proposed model has been applied to two Al-Mg alloys, and comparison with laboratory and industrial solidification experimental results have been carried out. The preliminary conclusion is that the proposed model is a promising suitable microscopic model used within the multi-scale casting simulation modelling framework.

Experimental Verification of Computational Models for Laminated Composites

NASA Technical Reports Server (NTRS)

Harris, Charles E.; Coats, Timothy W.; Glaessgen, Edward H.

1999-01-01

The objective of the research reported herein is to develop a progressive damage methodology capable of predicting the residual strength of continuous fiber-reinforced, laminated, polymer matrix composites with through-penetration damage. The fracture behavior of center-notch tension panels with thin crack-like slits was studied. Since fibers are the major load-carrying constituent in polymer matrix composites, predicting the residual strength of a laminate requires a criterion for fiber fracture. The effects on fiber strain due to other damage mechanisms such as matrix cracking and delaminations must also be modeled. Therefore, the research herein examines the damage mechanisms involved in translaminate fracture and identifies the toughening mechanisms responsible for damage growth resistance in brittle epoxy matrix systems. The mechanics of matrix cracking and fiber fracture are discussed as is the mathematical framework for the progressive damage model developed by the authors. The progressive damage analysis algorithms have been implemented into a general purpose finite element code developed by NASA, the Computational Structural Mechanics Testbed (COMET). Damage growth is numerically simulated and the analytical residual strength predictions are compared to experimental results for a variety of notched panel configurations and materials systems.

Cutting the Composite Gordian Knot: Untangling the AGN-Starburst Threads in Single Aperture Spectra

NASA Astrophysics Data System (ADS)

Flury, Sophia; Moran, Edward C.

2018-01-01

Standard emission line diagnostics are able to segregate star-forming galaxies and Seyfert nuclei, and it is often assumed that ambiguous emission-line galaxies falling between these two populations are “composite” objects exhibiting both types of photoionization. We have developed a method that predicts the most probable H II and AGN components that could plausibly explain the “composite” classed objects solely on the basis of their SDSS spectra. The majority of our analysis is driven by empirical relationships revealed by SDSS data rather than theoretical models founded in assumptions. To verify our method, we have compared the predictions of our model with publicly released IFU data from the S7 survey and find that composite objects are not in fact a simple linear combination of the two types of emission. The data reveal a key component in the mixing sequence: geometric dilution of the ionizing radiation which powers the NLR of the active nucleus. When accounting for this effect, our model is successful when applied to several composite-class galaxies. Some objects, however, appear to be at variance with the predicted results, suggesting they may not be powered by black hole accretion.

Competitive and demographic leverage points of community shifts under climate warming

PubMed Central

Sorte, Cascade J. B.; White, J. Wilson

2013-01-01

Accelerating rates of climate change and a paucity of whole-community studies of climate impacts limit our ability to forecast shifts in ecosystem structure and dynamics, particularly because climate change can lead to idiosyncratic responses via both demographic effects and altered species interactions. We used a multispecies model to predict which processes and species' responses are likely to drive shifts in the composition of a space-limited benthic marine community. Our model was parametrized from experimental manipulations of the community. Model simulations indicated shifts in species dominance patterns as temperatures increase, with projected shifts in composition primarily owing to the temperature dependence of growth, mortality and competition for three critical species. By contrast, warming impacts on two other species (rendering them weaker competitors for space) and recruitment rates of all species were of lesser importance in determining projected community changes. Our analysis reveals the importance of temperature-dependent competitive interactions for predicting effects of changing climate on such communities. Furthermore, by identifying processes and species that could disproportionately leverage shifts in community composition, our results contribute to a mechanistic understanding of climate change impacts, thereby allowing more insightful predictions of future biodiversity patterns. PMID:23658199

Assessment and prediction of drying shrinkage cracking in bonded mortar overlays

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

Beushausen, Hans, E-mail: hans.beushausen@uct.ac.za; Chilwesa, Masuzyo

2013-11-15

Restrained drying shrinkage cracking was investigated on composite beams consisting of substrate concrete and bonded mortar overlays, and compared to the performance of the same mortars when subjected to the ring test. Stress development and cracking in the composite specimens were analytically modeled and predicted based on the measurement of relevant time-dependent material properties such as drying shrinkage, elastic modulus, tensile relaxation and tensile strength. Overlay cracking in the composite beams could be very well predicted with the analytical model. The ring test provided a useful qualitative comparison of the cracking performance of the mortars. The duration of curing wasmore » found to only have a minor influence on crack development. This was ascribed to the fact that prolonged curing has a beneficial effect on tensile strength at the onset of stress development, but is in the same time not beneficial to the values of tensile relaxation and elastic modulus. -- Highlights: •Parameter study on material characteristics influencing overlay cracking. •Analytical model gives good quantitative indication of overlay cracking. •Ring test presents good qualitative indication of overlay cracking. •Curing duration has little effect on overlay cracking.« less

Modeling the Thermostructural Stability of Melt-infiltrated Sic/sic Composites

NASA Technical Reports Server (NTRS)

DiCarlo, James A.; Bhatt, Ramakrishna T.; McCue, Terry R.

2003-01-01

SiC/SiC composites developed by NASA with Sylramic-iBN fibers and melt-infiltrated (MI) SiC-Si matrices have demonstrated 1000-hour rupture life in air at 100 MPa and 1315OC. Recently it has been determined that a major factor controlling the long-term rupture life of these composites is not environment or stress, but an intrinsic microstructural and strength instability caused by a thermally-induced silicon attack of the Sic fibers. The objective of this paper is to present a simple diffusion-based analytical model which predicts well the observed effects of stress-free thermal exposure on the residual tensile strength of Sylramic-iBN/SiC-Si composites. The practical implications of the model for SiC/SiC composites with MI matrices are discussed.

Micromechanics Analysis Code With Generalized Method of Cells (MAC/GMC): User Guide. Version 3

NASA Technical Reports Server (NTRS)

Arnold, S. M.; Bednarcyk, B. A.; Wilt, T. E.; Trowbridge, D.

1999-01-01

The ability to accurately predict the thermomechanical deformation response of advanced composite materials continues to play an important role in the development of these strategic materials. Analytical models that predict the effective behavior of composites are used not only by engineers performing structural analysis of large-scale composite components but also by material scientists in developing new material systems. For an analytical model to fulfill these two distinct functions it must be based on a micromechanics approach which utilizes physically based deformation and life constitutive models and allows one to generate the average (macro) response of a composite material given the properties of the individual constituents and their geometric arrangement. Here the user guide for the recently developed, computationally efficient and comprehensive micromechanics analysis code, MAC, who's predictive capability rests entirely upon the fully analytical generalized method of cells, GMC, micromechanics model is described. MAC/ GMC is a versatile form of research software that "drives" the double or triply periodic micromechanics constitutive models based upon GMC. MAC/GMC enhances the basic capabilities of GMC by providing a modular framework wherein 1) various thermal, mechanical (stress or strain control) and thermomechanical load histories can be imposed, 2) different integration algorithms may be selected, 3) a variety of material constitutive models (both deformation and life) may be utilized and/or implemented, and 4) a variety of fiber architectures (both unidirectional, laminate and woven) may be easily accessed through their corresponding representative volume elements contained within the supplied library of RVEs or input directly by the user, and 5) graphical post processing of the macro and/or micro field quantities is made available.

Evaluating Ice Nucleating Particle Concentrations From Prognostic Dust Minerals in an Earth System Model

NASA Astrophysics Data System (ADS)

Perlwitz, J. P.; Knopf, D. A.; Fridlind, A. M.; Miller, R. L.; Pérez García-Pando, C.; DeMott, P. J.

2016-12-01

The effect of aerosol particles on the radiative properties of clouds, the so-called, indirect effect of aerosols, is recognized as one of the largest sources of uncertainty in climate prediction. The distribution of water vapor, precipitation, and ice cloud formation are influenced by the atmospheric ice formation, thereby modulating cloud albedo and thus climate. It is well known that different particle types possess different ice formation propensities with mineral dust being a superior ice nucleating particle (INP) compared to soot particles. Furthermore, some dust mineral types are more proficient INP than others, depending on temperature and relative humidity.In recent work, we have presented an improved dust aerosol module in the NASA GISS Earth System ModelE2 with prognostic mineral composition of the dust aerosols. Thus, there are regional variations in dust composition. We evaluated the predicted mineral fractions of dust aerosols by comparing them to measurements from a compilation of about 60 published literature references. Additionally, the capability of the model to reproduce the elemental composition of the simulated dusthas been tested at Izana Observatory at Tenerife, Canary Islands, which is located off-shore of Africa and where frequent dust events are observed. We have been able to show that the new approach delivers a robust improvement of the predicted mineral fractions and elemental composition of dust.In the current study, we use three-dimensional dust mineral fields and thermodynamic conditions, which are simulated using GISS ModelE, to calculate offline the INP concentrations derived using different ice nucleation parameterizations that are currently discussed. We evaluate the calculated INP concentrations from the different parameterizations by comparing them to INP concentrations from field measurements.

Factors Influencing Progressive Failure Analysis Predictions for Laminated Composite Structure

NASA Technical Reports Server (NTRS)

Knight, Norman F., Jr.

2008-01-01

Progressive failure material modeling methods used for structural analysis including failure initiation and material degradation are presented. Different failure initiation criteria and material degradation models are described that define progressive failure formulations. These progressive failure formulations are implemented in a user-defined material model for use with a nonlinear finite element analysis tool. The failure initiation criteria include the maximum stress criteria, maximum strain criteria, the Tsai-Wu failure polynomial, and the Hashin criteria. The material degradation model is based on the ply-discounting approach where the local material constitutive coefficients are degraded. Applications and extensions of the progressive failure analysis material model address two-dimensional plate and shell finite elements and three-dimensional solid finite elements. Implementation details are described in the present paper. Parametric studies for laminated composite structures are discussed to illustrate the features of the progressive failure modeling methods that have been implemented and to demonstrate their influence on progressive failure analysis predictions.

Compositional Effects on Nickel-Base Superalloy Single Crystal Microstructures

NASA Technical Reports Server (NTRS)

MacKay, Rebecca A.; Gabb, Timothy P.; Garg,Anita; Rogers, Richard B.; Nathal, Michael V.

2012-01-01

Fourteen nickel-base superalloy single crystals containing 0 to 5 wt% chromium (Cr), 0 to 11 wt% cobalt (Co), 6 to 12 wt% molybdenum (Mo), 0 to 4 wt% rhenium (Re), and fixed amounts of aluminum (Al) and tantalum (Ta) were examined to determine the effect of bulk composition on basic microstructural parameters, including gamma' solvus, gamma' volume fraction, volume fraction of topologically close-packed (TCP) phases, phase chemistries, and gamma - gamma'. lattice mismatch. Regression models were developed to describe the influence of bulk alloy composition on the microstructural parameters and were compared to predictions by a commercially available software tool that used computational thermodynamics. Co produced the largest change in gamma' solvus over the wide compositional range used in this study, and Mo produced the largest effect on the gamma lattice parameter and the gamma - gamma' lattice mismatch over its compositional range, although Re had a very potent influence on all microstructural parameters investigated. Changing the Cr, Co, Mo, and Re contents in the bulk alloy had a significant impact on their concentrations in the gamma matrix and, to a smaller extent, in the gamma' phase. The gamma phase chemistries exhibited strong temperature dependencies that were influenced by the gamma and gamma' volume fractions. A computational thermodynamic modeling tool significantly underpredicted gamma' solvus temperatures and grossly overpredicted the amount of TCP phase at 982 C. Furthermore, the predictions by the software tool for the gamma - gamma' lattice mismatch were typically of the wrong sign and magnitude, but predictions could be improved if TCP formation was suspended within the software program. However, the statistical regression models provided excellent estimations of the microstructural parameters based on bulk alloy composition, thereby demonstrating their usefulness.

Measurement and prediction of the thermomechanical response of shape memory alloy hybrid composite beams

NASA Astrophysics Data System (ADS)

Davis, Brian; Turner, Travis L.; Seelecke, Stefan

2005-05-01

Previous work at NASA Langley Research Center (LaRC) involved fabrication and testing of composite beams with embedded, pre-strained shape memory alloy (SMA) ribbons within the beam structures. That study also provided comparison of experimental results with numerical predictions from a research code making use of a new thermoelastic model for shape memory alloy hybrid composite (SMAHC) structures. The previous work showed qualitative validation of the numerical model. However, deficiencies in the experimental-numerical correlation were noted and hypotheses for the discrepancies were given for further investigation. The goal of this work is to refine the experimental measurement and numerical modeling approaches in order to better understand the discrepancies, improve the correlation between prediction and measurement, and provide rigorous quantitative validation of the numerical analysis/design tool. The experimental investigation is refined by a more thorough test procedure and incorporation of higher fidelity measurements such as infrared thermography and projection moire interferometry. The numerical results are produced by a recently commercialized version of the constitutive model as implemented in ABAQUS and are refined by incorporation of additional measured parameters such as geometric imperfection. Thermal buckling, post-buckling, and random responses to thermal and inertial (base acceleration) loads are studied. The results demonstrate the effectiveness of SMAHC structures in controlling static and dynamic responses by adaptive stiffening. Excellent agreement is achieved between the predicted and measured results of the static and dynamic thermomechanical response, thereby providing quantitative validation of the numerical tool.

Measurement and Prediction of the Thermomechanical Response of Shape Memory Alloy Hybrid Composite Beams

NASA Technical Reports Server (NTRS)

Davis, Brian; Turner, Travis L.; Seelecke, Stefan

2005-01-01

Previous work at NASA Langley Research Center (LaRC) involved fabrication and testing of composite beams with embedded, pre-strained shape memory alloy (SMA) ribbons within the beam structures. That study also provided comparison of experimental results with numerical predictions from a research code making use of a new thermoelastic model for shape memory alloy hybrid composite (SMAHC) structures. The previous work showed qualitative validation of the numerical model. However, deficiencies in the experimental-numerical correlation were noted and hypotheses for the discrepancies were given for further investigation. The goal of this work is to refine the experimental measurement and numerical modeling approaches in order to better understand the discrepancies, improve the correlation between prediction and measurement, and provide rigorous quantitative validation of the numerical analysis/design tool. The experimental investigation is refined by a more thorough test procedure and incorporation of higher fidelity measurements such as infrared thermography and projection moire interferometry. The numerical results are produced by a recently commercialized version of the constitutive model as implemented in ABAQUS and are refined by incorporation of additional measured parameters such as geometric imperfection. Thermal buckling, post-buckling, and random responses to thermal and inertial (base acceleration) loads are studied. The results demonstrate the effectiveness of SMAHC structures in controlling static and dynamic responses by adaptive stiffening. Excellent agreement is achieved between the predicted and measured results of the static and dynamic thermomechanical response, thereby providing quantitative validation of the numerical tool.

Dynamics of Nanoparticle-Protein Corona Complex Formation: Analytical Results from Population Balance Equations

PubMed Central

Darabi Sahneh, Faryad; Scoglio, Caterina; Riviere, Jim

2013-01-01

Background Nanoparticle-protein corona complex formation involves absorption of protein molecules onto nanoparticle surfaces in a physiological environment. Understanding the corona formation process is crucial in predicting nanoparticle behavior in biological systems, including applications of nanotoxicology and development of nano drug delivery platforms. Method This paper extends the modeling work in to derive a mathematical model describing the dynamics of nanoparticle corona complex formation from population balance equations. We apply nonlinear dynamics techniques to derive analytical results for the composition of nanoparticle-protein corona complex, and validate our results through numerical simulations. Results The model presented in this paper exhibits two phases of corona complex dynamics. In the first phase, proteins rapidly bind to the free surface of nanoparticles, leading to a metastable composition. During the second phase, continuous association and dissociation of protein molecules with nanoparticles slowly changes the composition of the corona complex. Given sufficient time, composition of the corona complex reaches an equilibrium state of stable composition. We find analytical approximate formulae for metastable and stable compositions of corona complex. Our formulae are very well-structured to clearly identify important parameters determining corona composition. Conclusion The dynamics of biocorona formation constitute vital aspect of interactions between nanoparticles and living organisms. Our results further understanding of these dynamics through quantitation of experimental conditions, modeling results for in vitro systems to better predict behavior for in vivo systems. One potential application would involve a single cell culture medium related to a complex protein medium, such as blood or tissue fluid. PMID:23741371

Detection of superlattice domain formation in ternary lipid mixtures using fluorescence spectroscopy

NASA Astrophysics Data System (ADS)

Mutlu, Burcin; Lopez, Stephanie; Vaughn, Mark; Huang, Juyang; Cheng, K.

2011-10-01

Multicomponent lipid bilayers represent an important model system for studying the structures and functions of cell membranes. At present, the lateral organization of lipid components, particularly the formation of regular distribution, in lipid membranes containing charged lipid, e.g., phosphatidylserine, is not clear. Using a ternary phosphatidylcholine/phosphatidylserine/cholesterol lipid bilayer system, the presence of ordered domain formation was examined by measuring the fluorescence anisotropy of the embedded fluorescent probe, 22-(N-(7-nitrobenz-2-oxa-1,3-diazol- 4-yl)amino)-23,24-bisnor-5-cholen-3β- ol (NBD-CHOL), with structure similar to that of a cholesterol, as a function of phospatidylserine composition. The plot of the anisotropy vs. phosphatidylserine revealed abrupt changes at certain critical compositions of phosphatidylserine. Some of these critical compositions agree favorably with those predicted by the headgroup superlattice model suggesting that the charged phosphatidylserine lipid molecules adopt a superlattice-like distribution in the lipid bilayer at some predicted compositions. The ordered distribution of charged lipids may play an important role in the regulation of the composition of the biological membranes.

Fatigue of notched fiber composite laminates. Part 1: Analytical model

NASA Technical Reports Server (NTRS)

Mclaughlin, P. V., Jr.; Kulkarni, S. V.; Huang, S. N.; Rosen, B. W.

1975-01-01

A description is given of a semi-empirical, deterministic analysis for prediction and correlation of fatigue crack growth, residual strength, and fatigue lifetime for fiber composite laminates containing notches (holes). The failure model used for the analysis is based upon composite heterogeneous behavior and experimentally observed failure modes under both static and fatigue loading. The analysis is consistent with the wearout philosophy. Axial cracking and transverse cracking failure modes are treated together in the analysis. Cracking off-axis is handled by making a modification to the axial cracking analysis. The analysis predicts notched laminate failure from unidirectional material fatique properties using constant strain laminate analysis techniques. For multidirectional laminates, it is necessary to know lamina fatique behavior under axial normal stress, transverse normal stress and axial shear stress. Examples of the analysis method are given.

Variations on a theme - the evolution of hydrocarbon solids. I. Compositional and spectral modelling - the eRCN and DG models

NASA Astrophysics Data System (ADS)

Jones, A. P.

2012-04-01

Context. The compositional properties of hydrogenated amorphous carbons are known to evolve in response to the local conditions. Aims: We present a model for low-temperature, amorphous hydrocarbon solids, based on the microphysical properties of random and defected networks of carbon and hydrogen atoms, that can be used to study and predict the evolution of their properties in the interstellar medium. Methods: We adopt an adaptable and prescriptive approach to model these materials, which is based on a random covalent network (RCN) model, extended here to a full compositional derivation (the eRCN model), and a defective graphite (DG) model for the hydrogen poorer materials where the eRCN model is no longer valid. Results: We provide simple expressions that enable the determination of the structural, infrared and spectral properties of amorphous hydrocarbon grains as a function of the hydrogen atomic fraction, XH. Structural annealing, resulting from hydrogen atom loss, results in a transition from H-rich, aliphatic-rich to H-poor, aromatic-rich materials. Conclusions: The model predicts changes in the optical properties of hydrogenated amorphous carbon dust in response to the likely UV photon-driven and/or thermal annealing processes resulting, principally, from the radiation field in the environment. We show how this dust component will evolve, compositionally and structurally in the interstellar medium in response to the local conditions. Appendices A and B are available in electronic form at http://www.aanda.org

Comparative hazard analysis and toxicological modeling of diverse nanomaterials using the embryonic zebrafish (EZ) metric of toxicity

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

Harper, Bryan; Thomas, Dennis G.; Chikkagoudar, Satish

The integration of rapid assays, large data sets, informatics and modeling can overcome current barriers in understanding nanomaterial structure-toxicity relationships by providing a weight-of-the-evidence mechanism to generate hazard rankings for nanomaterials. Here we present the use of a rapid, low-cost assay to perform screening-level toxicity evaluations of nanomaterials in vivo. Calculated EZ Metric scores, a combined measure of morbidity and mortality, were established at realistic exposure levels and used to develop a predictive model of nanomaterial toxicity. Hazard ranking and clustering analysis of 68 diverse nanomaterials revealed distinct patterns of toxicity related to both core composition and outermost surface chemistrymore » of nanomaterials. The resulting clusters guided the development of a predictive model of gold nanoparticle toxicity to embryonic zebrafish. In addition, our findings suggest that risk assessments based on the size and core composition of nanomaterials alone may be wholly inappropriate, especially when considering complex engineered nanomaterials. These findings reveal the need to expeditiously increase the availability of quantitative measures of nanomaterial hazard and broaden the sharing of that data and knowledge to support predictive modeling. In addition, research should continue to focus on methodologies for developing predictive models of nanomaterial hazard based on sub-lethal responses to low dose exposures.« less

Comparative hazard analysis and toxicological modeling of diverse nanomaterials using the embryonic zebrafish (EZ) metric of toxicity

DOE PAGES

Harper, Bryan; Thomas, Dennis G.; Chikkagoudar, Satish; ...

2015-06-04

The integration of rapid assays, large data sets, informatics and modeling can overcome current barriers in understanding nanomaterial structure-toxicity relationships by providing a weight-of-the-evidence mechanism to generate hazard rankings for nanomaterials. Here we present the use of a rapid, low-cost assay to perform screening-level toxicity evaluations of nanomaterials in vivo. Calculated EZ Metric scores, a combined measure of morbidity and mortality, were established at realistic exposure levels and used to develop a predictive model of nanomaterial toxicity. Hazard ranking and clustering analysis of 68 diverse nanomaterials revealed distinct patterns of toxicity related to both core composition and outermost surface chemistrymore » of nanomaterials. The resulting clusters guided the development of a predictive model of gold nanoparticle toxicity to embryonic zebrafish. In addition, our findings suggest that risk assessments based on the size and core composition of nanomaterials alone may be wholly inappropriate, especially when considering complex engineered nanomaterials. These findings reveal the need to expeditiously increase the availability of quantitative measures of nanomaterial hazard and broaden the sharing of that data and knowledge to support predictive modeling. In addition, research should continue to focus on methodologies for developing predictive models of nanomaterial hazard based on sub-lethal responses to low dose exposures.« less

Predictions of the electro-mechanical response of conductive CNT-polymer composites

NASA Astrophysics Data System (ADS)

Matos, Miguel A. S.; Tagarielli, Vito L.; Baiz-Villafranca, Pedro M.; Pinho, Silvestre T.

2018-05-01

We present finite element simulations to predict the conductivity, elastic response and strain-sensing capability of conductive composites comprising a polymeric matrix and carbon nanotubes. Realistic representative volume elements (RVE) of the microstructure are generated and both constituents are modelled as linear elastic solids, with resistivity independent of strain; the electrical contact between nanotubes is represented by a new element which accounts for quantum tunnelling effects and captures the sensitivity of conductivity to separation. Monte Carlo simulations are conducted and the sensitivity of the predictions to RVE size is explored. Predictions of modulus and conductivity are found in good agreement with published results. The strain-sensing capability of the material is explored for multiaxial strain states.

Integration of Immune Cell Populations, mRNA-Seq, and CpG Methylation to Better Predict Humoral Immunity to Influenza Vaccination: Dependence of mRNA-Seq/CpG Methylation on Immune Cell Populations

PubMed Central

Zimmermann, Michael T.; Kennedy, Richard B.; Grill, Diane E.; Oberg, Ann L.; Goergen, Krista M.; Ovsyannikova, Inna G.; Haralambieva, Iana H.; Poland, Gregory A.

2017-01-01

The development of a humoral immune response to influenza vaccines occurs on a multisystems level. Due to the orchestration required for robust immune responses when multiple genes and their regulatory components across multiple cell types are involved, we examined an influenza vaccination cohort using multiple high-throughput technologies. In this study, we sought a more thorough understanding of how immune cell composition and gene expression relate to each other and contribute to interindividual variation in response to influenza vaccination. We first hypothesized that many of the differentially expressed (DE) genes observed after influenza vaccination result from changes in the composition of participants’ peripheral blood mononuclear cells (PBMCs), which were assessed using flow cytometry. We demonstrated that DE genes in our study are correlated with changes in PBMC composition. We gathered DE genes from 128 other publically available PBMC-based vaccine studies and identified that an average of 57% correlated with specific cell subset levels in our study (permutation used to control false discovery), suggesting that the associations we have identified are likely general features of PBMC-based transcriptomics. Second, we hypothesized that more robust models of vaccine response could be generated by accounting for the interplay between PBMC composition, gene expression, and gene regulation. We employed machine learning to generate predictive models of B-cell ELISPOT response outcomes and hemagglutination inhibition (HAI) antibody titers. The top HAI and B-cell ELISPOT model achieved an area under the receiver operating curve (AUC) of 0.64 and 0.79, respectively, with linear model coefficients of determination of 0.08 and 0.28. For the B-cell ELISPOT outcomes, CpG methylation had the greatest predictive ability, highlighting potentially novel regulatory features important for immune response. B-cell ELISOT models using only PBMC composition had lower performance (AUC = 0.67), but highlighted well-known mechanisms. Our analysis demonstrated that each of the three data sets (cell composition, mRNA-Seq, and DNA methylation) may provide distinct information for the prediction of humoral immune response outcomes. We believe that these findings are important for the interpretation of current omics-based studies and set the stage for a more thorough understanding of interindividual immune responses to influenza vaccination. PMID:28484452

Application of inorganic element ratios to chemometrics for determination of the geographic origin of welsh onions.

PubMed

Ariyama, Kaoru; Horita, Hiroshi; Yasui, Akemi

2004-09-22

The composition of concentration ratios of 19 inorganic elements to Mg (hereinafter referred to as 19-element/Mg composition) was applied to chemometric techniques to determine the geographic origin (Japan or China) of Welsh onions (Allium fistulosum L.). Using a composition of element ratios has the advantage of simplified sample preparation, and it was possible to determine the geographic origin of a Welsh onion within 2 days. The classical technique based on 20 element concentrations was also used along with the new simpler one based on 19 elements/Mg in order to validate the new technique. Twenty elements, Na, P, K, Ca, Mg, Mn, Fe, Cu, Zn, Sr, Ba, Co, Ni, Rb, Mo, Cd, Cs, La, Ce, and Tl, in 244 Welsh onion samples were analyzed by flame atomic absorption spectroscopy, inductively coupled plasma atomic emission spectrometry, and inductively coupled plasma mass spectrometry. Linear discriminant analysis (LDA) on 20-element concentrations and 19-element/Mg composition was applied to these analytical data, and soft independent modeling of class analogy (SIMCA) on 19-element/Mg composition was applied to these analytical data. The results showed that techniques based on 19-element/Mg composition were effective. LDA, based on 19-element/Mg composition for classification of samples from Japan and from Shandong, Shanghai, and Fujian in China, classified 101 samples used for modeling 97% correctly and predicted another 119 samples excluding 24 nonauthentic samples 93% correctly. In discriminations by 10 times of SIMCA based on 19-element/Mg composition modeled using 101 samples, 220 samples from known production areas including samples used for modeling and excluding 24 nonauthentic samples were predicted 92% correctly.

Viscoplastic deformations and compressive damage in an A359/SiC{sub p} metal-matrix composite

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

Li, Y.; Ramesh, K.T.; Chin, E.S.C.

2000-04-19

Recent work by the authors has examined the high-strain-rate compression of a metal-matrix composite consisting of an A359 Al alloy matrix reinforced by 20 vol.% of silicon carbide particulates (SiC{sub p}). The work-hardening that is observed in the experiments is much lower than that predicted by analytical and computational models which assume perfect particle-matrix interfaces and undamaged particles. In this work, the authors show that the discrepancy is a result of particle damage that develops within the A359/SiC{sub p} composite under compression. The evolution of particle damage has been characterized using quantitative microscopy, and is shown to be a functionmore » of the applied strain. A simple analytical model that incorporates evolving damage within the composite is proposed, and it is shown that the analytical predictions are consistent with the experimental observations over a wide range of strain rates.« less

An experimental study on the manufacture and characterization of in-plane fibre-waviness defects in composites.

PubMed

Christian, W J R; DiazDelaO, F A; Atherton, K; Patterson, E A

2018-05-01

A new method has been developed for creating localized in-plane fibre waviness in composite coupons and used to create a large batch of specimens. This method could be used by manufacturers to experimentally explore the effect of fibre waviness on composite structures both directly and indirectly to develop and validate computational models. The specimens were assessed using ultrasound, digital image correlation and a novel inspection technique capable of measuring residual strain fields. To explore how the defect affects the performance of composite structures, the specimens were then loaded to failure. Predictions of remnant strength were made using a simple ultrasound damage metric and a new residual strain-based damage metric. The predictions made using residual strain measurements were found to be substantially more effective at characterizing ultimate strength than ultrasound measurements. This suggests that residual strains have a significant effect on the failure of laminates containing fibre waviness and that these strains could be incorporated into computational models to improve their ability to simulate the defect.

Using Imaging Spectrometry measurements of Ecosystem Composition to constrain Regional Predictions of Carbon, Water and Energy Fluxes

NASA Astrophysics Data System (ADS)

Anderson, C.; Bond-Lamberty, B. P.; Huang, M.; Xu, Y.; Stegen, J.

2016-12-01

Ecosystem composition is a key attribute of terrestrial ecosystems, influencing the fluxes of carbon, water, and energy between the land surface and the atmosphere. The description of current ecosystem composition has traditionally come from relatively few ground-based inventories of the plant canopy, but are spatially limited and do not provide a comprehensive picture of ecosystem composition at regional or global scales. In this analysis, imaging spectrometry measurements, collected as part of the HyspIRI Preparatory Mission, are used to provide spatially-resolved estimates of plant functional type composition providing an important constraint on terrestrial biosphere model predictions of carbon, water and energy fluxes across the heterogeneous landscapes of the Californian Sierras. These landscapes include oak savannas, mid-elevation mixed pines, fir-cedar forests, and high elevation pines. Our results show that imaging spectrometry measurements can be successfully used to estimate regional-scale variation in ecosystem composition and resulting spatial heterogeneity in patterns of carbon, water and energy fluxes and ecosystem dynamics. Simulations at four flux tower sites within the study region yield patterns of seasonal and inter-annual variation in carbon and water fluxes that have comparable accuracy to simulations initialized from ground-based inventory measurements. Finally, results indicate that during the 2012-2015 Californian drought, regional net carbon fluxes fell by 84%, evaporation and transpiration fluxes fell by 53% and 33% respectively, and sensible heat increase by 51%. This study provides a framework for assimilating near-future global satellite imagery estimates of ecosystem composition with terrestrial biosphere models, constraining and improving their predictions of large-scale ecosystem dynamics and functioning.

Using Imaging Spectrometry measurements of Ecosystem Composition to constrain Regional Predictions of Carbon, Water and Energy Fluxes

NASA Astrophysics Data System (ADS)

Antonarakis, A. S.; Bogan, S.; Moorcroft, P. R.

2017-12-01

Ecosystem composition is a key attribute of terrestrial ecosystems, influencing the fluxes of carbon, water, and energy between the land surface and the atmosphere. The description of current ecosystem composition has traditionally come from relatively few ground-based inventories of the plant canopy, but are spatially limited and do not provide a comprehensive picture of ecosystem composition at regional or global scales. In this analysis, imaging spectrometry measurements, collected as part of the HyspIRI Preparatory Mission, are used to provide spatially-resolved estimates of plant functional type composition providing an important constraint on terrestrial biosphere model predictions of carbon, water and energy fluxes across the heterogeneous landscapes of the Californian Sierras. These landscapes include oak savannas, mid-elevation mixed pines, fir-cedar forests, and high elevation pines. Our results show that imaging spectrometry measurements can be successfully used to estimate regional-scale variation in ecosystem composition and resulting spatial heterogeneity in patterns of carbon, water and energy fluxes and ecosystem dynamics. Simulations at four flux tower sites within the study region yield patterns of seasonal and inter-annual variation in carbon and water fluxes that have comparable accuracy to simulations initialized from ground-based inventory measurements. Finally, results indicate that during the 2012-2015 Californian drought, regional net carbon fluxes fell by 84%, evaporation and transpiration fluxes fell by 53% and 33% respectively, and sensible heat increase by 51%. This study provides a framework for assimilating near-future global satellite imagery estimates of ecosystem composition with terrestrial biosphere models, constraining and improving their predictions of large-scale ecosystem dynamics and functioning.

Thermodynamic and kinetic modeling of Mn-Ni-Si precipitates in low-Cu reactor pressure vessel steels

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

Ke, Huibin; Wells, Peter; Edmondson, Philip D.

Formation of large volume fractions of Mn-Ni-Si precipitates (MNSPs) causes excess irradiation embrittlement of reactor pressure vessel (RPV) steels at high, extended-life fluences. Thus, a new and unique, semi-empirical cluster dynamics model was developed to study the evolution of MNSPs in low-Cu RPV steels. The model is based on CALPHAD thermodynamics and radiation enhanced diffusion kinetics. The thermodynamics dictates the compositional and temperature dependence of the free energy reductions that drive precipitation. The model treats both homogeneous and heterogeneous nucleation, where the latter occurs on cascade damage, like dislocation loops. The model has only four adjustable parameters that were fitmore » to an atom probe tomography (APT) database. The model predictions are in semi-quantitative agreement with systematic Mn, Ni and Si composition variations in alloys characterized by APT, including a sensitivity to local tip-to-tip variations even in the same steel. The model predicts that heterogeneous nucleation plays a critical role in MNSP formation in lower alloy Ni contents. Single variable assessments of compositional effects show that Ni plays a dominant role, while even small variations in irradiation temperature can have a large effect on the MNSP evolution. Within typical RPV steel ranges, Mn and Si have smaller effects. Furthermore, the delayed but then rapid growth of MNSPs to large volume fractions at high fluence is well predicted by the model. For purposes of illustration, the effect of MNSPs on transition temperature shifts are presented based on well-established microstructure-property and property-property models.« less

Thermodynamic and kinetic modeling of Mn-Ni-Si precipitates in low-Cu reactor pressure vessel steels

DOE PAGES

Ke, Huibin; Wells, Peter; Edmondson, Philip D.; ...

2017-07-12

Formation of large volume fractions of Mn-Ni-Si precipitates (MNSPs) causes excess irradiation embrittlement of reactor pressure vessel (RPV) steels at high, extended-life fluences. Thus, a new and unique, semi-empirical cluster dynamics model was developed to study the evolution of MNSPs in low-Cu RPV steels. The model is based on CALPHAD thermodynamics and radiation enhanced diffusion kinetics. The thermodynamics dictates the compositional and temperature dependence of the free energy reductions that drive precipitation. The model treats both homogeneous and heterogeneous nucleation, where the latter occurs on cascade damage, like dislocation loops. The model has only four adjustable parameters that were fitmore » to an atom probe tomography (APT) database. The model predictions are in semi-quantitative agreement with systematic Mn, Ni and Si composition variations in alloys characterized by APT, including a sensitivity to local tip-to-tip variations even in the same steel. The model predicts that heterogeneous nucleation plays a critical role in MNSP formation in lower alloy Ni contents. Single variable assessments of compositional effects show that Ni plays a dominant role, while even small variations in irradiation temperature can have a large effect on the MNSP evolution. Within typical RPV steel ranges, Mn and Si have smaller effects. Furthermore, the delayed but then rapid growth of MNSPs to large volume fractions at high fluence is well predicted by the model. For purposes of illustration, the effect of MNSPs on transition temperature shifts are presented based on well-established microstructure-property and property-property models.« less

Computational model of in vivo human energy metabolism during semi-starvation and re-feeding

PubMed Central

Hall, Kevin D.

2008-01-01

Changes of body weight and composition are the result of complex interactions among metabolic fluxes contributing to macronutrient balances. To better understand these interactions, a mathematical model was constructed that used the measured dietary macronutrient intake during semi-starvation and re-feeding as model inputs and computed whole-body energy expenditure, de novo lipogenesis, gluconeogenesis, as well as turnover and oxidation of carbohydrate, fat and protein. Published in vivo human data provided the basis for the model components which were integrated by fitting a few unknown parameters to the classic Minnesota human starvation experiment. The model simulated the measured body weight and fat mass changes during semi-starvation and re-feeding and predicted the unmeasured metabolic fluxes underlying the body composition changes. The resting metabolic rate matched the experimental measurements and required a model of adaptive thermogenesis. Re-feeding caused an elevation of de novo lipogenesis which, along with increased fat intake, resulted in a rapid repletion and overshoot of body fat. By continuing the computer simulation with the pre-starvation diet and physical activity, the original body weight and composition was eventually restored, but body fat mass was predicted to take more than one additional year to return to within 5% of its original value. The model was validated by simulating a recently published short-term caloric restriction experiment without changing the model parameters. The predicted changes of body weight, fat mass, resting metabolic rate, and nitrogen balance matched the experimental measurements thereby providing support for the validity of the model. PMID:16449298

Mechanistic model to predict colostrum intake based on deuterium oxide dilution technique data and impact of gestation and prefarrowing diets on piglet intake and sow yield of colostrum.

PubMed

Theil, P K; Flummer, C; Hurley, W L; Kristensen, N B; Labouriau, R L; Sørensen, M T

2014-12-01

The aims of the present study were to quantify colostrum intake (CI) of piglets using the D2O dilution technique, to develop a mechanistic model to predict CI, to compare these data with CI predicted by a previous empirical predictive model developed for bottle-fed piglets, and to study how composition of diets fed to gestating sows affected piglet CI, sow colostrum yield (CY), and colostrum composition. In total, 240 piglets from 40 litters were enriched with D2O. The CI measured by D2O from birth until 24 h after the birth of first-born piglet was on average 443 g (SD 151). Based on measured CI, a mechanistic model to predict CI was developed using piglet characteristics (24-h weight gain [WG; g], BW at birth [BWB; kg], and duration of CI [D; min]: CI, g=-106+2.26 WG+200 BWB+0.111 D-1,414 WG/D+0.0182 WG/BWB (R2=0.944). This model was used to predict the CI for all colostrum suckling piglets within the 40 litters (n=500, mean=437 g, SD=153 g) and was compared with the CI predicted by a previous empirical predictive model (mean=305 g, SD=140 g). The previous empirical model underestimated the CI by 30% compared with that obtained by the new mechanistic model. The sows were fed 1 of 4 gestation diets (n=10 per diet) based on different fiber sources (low fiber [17%] or potato pulp, pectin residue, or sugarbeet pulp [32 to 40%]) from mating until d 108 of gestation. From d 108 of gestation until parturition, sows were fed 1 of 5 prefarrowing diets (n=8 per diet) varying in supplemented fat (3% animal fat, 8% coconut oil, 8% sunflower oil, 8% fish oil, or 4% fish oil+4% octanoic acid). Sows fed diets with pectin residue or sugarbeet pulp during gestation produced colostrum with lower protein, fat, DM, and energy concentrations and higher lactose concentrations, and their piglets had greater CI as compared with sows fed potato pulp or the low-fiber diet (P<0.05), and sows fed pectin residue had a greater CY than potato pulp-fed sows (P<0.05). Prefarrowing diets affected neither CI nor CY, but the prefarrowing diet with coconut oil decreased lactose and increased DM concentrations of colostrum compared with other prefarrowing diets (P<0.05). In conclusion, the new mechanistic predictive model for CI suggests that the previous empirical predictive model underestimates CI of sow-reared piglets by 30%. It was also concluded that nutrition of sows during gestation affected CY and colostrum composition.

Progressive fracture of fiber composites

NASA Technical Reports Server (NTRS)

Irvin, T. B.; Ginty, C. A.

1983-01-01

Refined models and procedures are described for determining progressive composite fracture in graphite/epoxy angleplied laminates. Lewis Research Center capabilities are utilized including the Real Time Ultrasonic C Scan (RUSCAN) experimental facility and the Composite Durability Structural Analysis (CODSTRAN) computer code. The CODSTRAN computer code is used to predict the fracture progression based on composite mechanics, finite element stress analysis, and fracture criteria modules. The RUSCAN facility, CODSTRAN computer code, and scanning electron microscope are used to determine durability and identify failure mechanisms in graphite/epoxy composites.

Development and Evaluation of Models for the Relationship between Tree Height and Diameter at Breast Height for Chinese-Fir Plantations in Subtropical China.

PubMed

Li, Yan-qiong; Deng, Xiang-wen; Huang, Zhi-hong; Xiang, Wen-hua; Yan, Wen-de; Lei, Pi-feng; Zhou, Xiao-lu; Peng, Chang-hui

2015-01-01

Tree diameter at breast height (dbh) and height are the most important variables used in forest inventory and management as well as forest carbon-stock estimation. In order to identify the key stand variables that influence the tree height-dbh relationship and to develop and validate a suit of models for predicting tree height, data from 5961 tree samples aged from 6 years to 53 years and collected from 80 Chinese-fir plantation plots were used to fit 39 models, including 33 nonlinear models and 6 linear models, were developed and evaluated into two groups. The results showed that composite models performed better in height estimate than one-independent-variable models. Nonlinear composite Model 34 and linear composite Model 6 were recommended for predicting tree height in Chinese fir plantations with a dbh range between 4 cm and 40 cm when the dbh data for each tree and the quadratic mean dbh of the stand (Dq) and mean height of the stand (Hm) were available. Moreover, Hm could be estimated by using the formula Hm = 11.707 × l n(Dq)-18.032. Clearly, Dq was the primary stand variable that influenced the height-dbh relationship. The parameters of the models varied according to stand age and site. The inappropriate application of provincial or regional height-dbh models for predicting small tree height at local scale may result in larger uncertainties. The method and the recommended models developed in this study were statistically reliable for applications in growth and yield estimation for even-aged Chinese-fir plantation in Huitong and Changsha. The models could be extended to other regions and to other tree species only after verification in subtropical China.

Development and Evaluation of Models for the Relationship between Tree Height and Diameter at Breast Height for Chinese-Fir Plantations in Subtropical China

PubMed Central

Li, Yan-qiong; Deng, Xiang-wen; Huang, Zhi-hong; Xiang, Wen-hua; Yan, Wen-de; Lei, Pi-feng; Zhou, Xiao-lu; Peng, Chang-hui

2015-01-01

Tree diameter at breast height (dbh) and height are the most important variables used in forest inventory and management as well as forest carbon-stock estimation. In order to identify the key stand variables that influence the tree height-dbh relationship and to develop and validate a suit of models for predicting tree height, data from 5961 tree samples aged from 6 years to 53 years and collected from 80 Chinese-fir plantation plots were used to fit 39 models, including 33 nonlinear models and 6 linear models, were developed and evaluated into two groups. The results showed that composite models performed better in height estimate than one-independent-variable models. Nonlinear composite Model 34 and linear composite Model 6 were recommended for predicting tree height in Chinese fir plantations with a dbh range between 4 cm and 40 cm when the dbh data for each tree and the quadratic mean dbh of the stand (Dq) and mean height of the stand (Hm) were available. Moreover, Hm could be estimated by using the formula Hm=11.707×ln(Dq)-18.032. Clearly, Dq was the primary stand variable that influenced the height-dbh relationship. The parameters of the models varied according to stand age and site. The inappropriate application of provincial or regional height-dbh models for predicting small tree height at local scale may result in larger uncertainties. The method and the recommended models developed in this study were statistically reliable for applications in growth and yield estimation for even-aged Chinese-fir plantation in Huitong and Changsha. The models could be extended to other regions and to other tree species only after verification in subtropical China. PMID:25905458

A Progressive Damage Model for Predicting Permanent Indentation and Impact Damage in Composite Laminates

NASA Astrophysics Data System (ADS)

Ji, Zhaojie; Guan, Zhidong; Li, Zengshan

2017-10-01

In this paper, a progressive damage model was established on the basis of ABAQUS software for predicting permanent indentation and impact damage in composite laminates. Intralaminar and interlaminar damage was modelled based on the continuum damage mechanics (CDM) in the finite element model. For the verification of the model, low-velocity impact tests of quasi-isotropic laminates with material system of T300/5228A were conducted. Permanent indentation and impact damage of the laminates were simulated and the numerical results agree well with the experiments. It can be concluded that an obvious knee point can be identified on the curve of the indentation depth versus impact energy. Matrix cracking and delamination develops rapidly with the increasing impact energy, while considerable amount of fiber breakage only occurs when the impact energy exceeds the energy corresponding to the knee point. Predicted indentation depth after the knee point is very sensitive to the parameter μ which is proposed in this paper, and the acceptable value of this parameter is in range from 0.9 to 1.0.

Evaluation of a black-footed ferret resource utilization function model

USGS Publications Warehouse

Eads, D.A.; Millspaugh, J.J.; Biggins, D.E.; Jachowski, D.S.; Livieri, T.M.

2011-01-01

Resource utilization function (RUF) models permit evaluation of potential habitat for endangered species; ideally such models should be evaluated before use in management decision-making. We evaluated the predictive capabilities of a previously developed black-footed ferret (Mustela nigripes) RUF. Using the population-level RUF, generated from ferret observations at an adjacent yet distinct colony, we predicted the distribution of ferrets within a black-tailed prairie dog (Cynomys ludovicianus) colony in the Conata Basin, South Dakota, USA. We evaluated model performance, using data collected during post-breeding spotlight surveys (2007-2008) by assessing model agreement via weighted compositional analysis and count-metrics. Compositional analysis of home range use and colony-level availability, and core area use and home range availability, demonstrated ferret selection of the predicted Very high and High occurrence categories in 2007 and 2008. Simple count-metrics corroborated these findings and suggested selection of the Very high category in 2007 and the Very high and High categories in 2008. Collectively, these results suggested that the RUF was useful in predicting occurrence and intensity of space use of ferrets at our study site, the 2 objectives of the RUF. Application of this validated RUF would increase the resolution of habitat evaluations, permitting prediction of the distribution of ferrets within distinct colonies. Additional model evaluation at other sites, on other black-tailed prairie dog colonies of varying resource configuration and size, would increase understanding of influences upon model performance and the general utility of the RUF. ?? 2011 The Wildlife Society.

Grain-Size Based Additivity Models for Scaling Multi-rate Uranyl Surface Complexation in Subsurface Sediments

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

Zhang, Xiaoying; Liu, Chongxuan; Hu, Bill X.

The additivity model assumed that field-scale reaction properties in a sediment including surface area, reactive site concentration, and reaction rate can be predicted from field-scale grain-size distribution by linearly adding reaction properties estimated in laboratory for individual grain-size fractions. This study evaluated the additivity model in scaling mass transfer-limited, multi-rate uranyl (U(VI)) surface complexation reactions in a contaminated sediment. Experimental data of rate-limited U(VI) desorption in a stirred flow-cell reactor were used to estimate the statistical properties of the rate constants for individual grain-size fractions, which were then used to predict rate-limited U(VI) desorption in the composite sediment. The resultmore » indicated that the additivity model with respect to the rate of U(VI) desorption provided a good prediction of U(VI) desorption in the composite sediment. However, the rate constants were not directly scalable using the additivity model. An approximate additivity model for directly scaling rate constants was subsequently proposed and evaluated. The result found that the approximate model provided a good prediction of the experimental results within statistical uncertainty. This study also found that a gravel-size fraction (2 to 8 mm), which is often ignored in modeling U(VI) sorption and desorption, is statistically significant to the U(VI) desorption in the sediment.« less

Using the concept of Chou's pseudo amino acid composition to predict apoptosis proteins subcellular location: an approach by approximate entropy.

PubMed

Jiang, Xiaoying; Wei, Rong; Zhang, Tongliang; Gu, Quan

2008-01-01

The function of protein is closely correlated with it subcellular location. Prediction of subcellular location of apoptosis proteins is an important research area in post-genetic era because the knowledge of apoptosis proteins is useful to understand the mechanism of programmed cell death. Compared with the conventional amino acid composition (AAC), the Pseudo Amino Acid composition (PseAA) as originally introduced by Chou can incorporate much more information of a protein sequence so as to remarkably enhance the power of using a discrete model to predict various attributes of a protein. In this study, a novel approach is presented to predict apoptosis protein solely from sequence based on the concept of Chou's PseAA composition. The concept of approximate entropy (ApEn), which is a parameter denoting complexity of time series, is used to construct PseAA composition as additional features. Fuzzy K-nearest neighbor (FKNN) classifier is selected as prediction engine. Particle swarm optimization (PSO) algorithm is adopted for optimizing the weight factors which are important in PseAA composition. Two datasets are used to validate the performance of the proposed approach, which incorporate six subcellular location and four subcellular locations, respectively. The results obtained by jackknife test are quite encouraging. It indicates that the ApEn of protein sequence could represent effectively the information of apoptosis proteins subcellular locations. It can at least play a complimentary role to many of the existing methods, and might become potentially useful tool for protein function prediction. The software in Matlab is available freely by contacting the corresponding author.

On-line consolidation of thermoplastic composites

NASA Astrophysics Data System (ADS)

Shih, Po-Jen

An on-line consolidation system, which includes a computer-controlled filament winding machine and a consolidation head assembly, has been designed and constructed to fabricate composite parts from thermoplastic towpregs. A statistical approach was used to determine the significant processing parameters and their effect on the mechanical and physical properties of composite cylinders fabricated by on-line consolidation. A central composite experimental design was used to select the processing conditions for manufacturing the composite cylinders. The thickness, density, void content, degree of crystallinity and interlaminar shear strength (ILSS) were measured for each composite cylinder. Micrographs showed that complete intimate contact and uniform fiber-matrix distribution were achieved. The degree of crystallinity of the cylinders was found to be in the range of 25-30%. Under optimum processing conditions, an ILSS of 58 MPa and a void content of <1% were achieved for APC-2 (PEEK/Carbon fiber) composite cylinders. An in-situ measurement system which uses a slip ring assembly and a computer data acquisition system was developed to obtain temperature data during winding. Composite cylinders were manufactured with eight K-type thermocouples installed in various locations inside the cylinder. The temperature distribution inside the composite cylinder during winding was measured for different processing conditions. ABAQUS finite element models of the different processes that occur during on-line consolidation were constructed. The first model was used to determine the convective heat transfer coefficient for the hot-air heat source. A convective heat transfer coefficient of 260 w/msp{2°}K was obtained by matching the calculated temperature history to the in-situ measurement data. To predict temperature distribution during winding an ABAQUS winding simulation model was developed. The winding speed was modeled by incrementally moving the convective boundary conditions around the outer surface of the composite cylinder. A towpreg heating model was constructed to predict the temperature distribution on the cross section of the incoming towpreg. For the process-induced thermal stresses analysis, a thermoelastic finite element model was constructed. Using the temperature history obtained from thermal analysis as the initial conditions, the thermal stresses during winding and cooling were investigated.

Synergistic Effects of Temperature and Oxidation on Matrix Cracking in Fiber-Reinforced Ceramic-Matrix Composites

NASA Astrophysics Data System (ADS)

Longbiao, Li

2017-06-01

In this paper, the synergistic effects of temperatrue and oxidation on matrix cracking in fiber-reinforced ceramic-matrix composites (CMCs) has been investigated using energy balance approach. The shear-lag model cooperated with damage models, i.e., the interface oxidation model, interface debonding model, fiber strength degradation model and fiber failure model, has been adopted to analyze microstress field in the composite. The relationships between matrix cracking stress, interface debonding and slipping, fiber fracture, oxidation temperatures and time have been established. The effects of fiber volume fraction, interface properties, fiber strength and oxidation temperatures on the evolution of matrix cracking stress versus oxidation time have been analyzed. The matrix cracking stresses of C/SiC composite with strong and weak interface bonding after unstressed oxidation at an elevated temperature of 700 °C in air condition have been predicted for different oxidation time.

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

Delmau, L.H.; Haverlock, T.J.; Sloop, F.V., Jr.

This report presents the work that followed the CSSX model development completed in FY2002. The developed cesium and potassium extraction model was based on extraction data obtained from simple aqueous media. It was tested to ensure the validity of the prediction for the cesium extraction from actual waste. Compositions of the actual tank waste were obtained from the Savannah River Site personnel and were used to prepare defined simulants and to predict cesium distribution ratios using the model. It was therefore possible to compare the cesium distribution ratios obtained from the actual waste, the simulant, and the predicted values. Itmore » was determined that the predicted values agree with the measured values for the simulants. Predicted values also agreed, with three exceptions, with measured values for the tank wastes. Discrepancies were attributed in part to the uncertainty in the cation/anion balance in the actual waste composition, but likely more so to the uncertainty in the potassium concentration in the waste, given the demonstrated large competing effect of this metal on cesium extraction. It was demonstrated that the upper limit for the potassium concentration in the feed ought to not exceed 0.05 M in order to maintain suitable cesium distribution ratios.« less

Nanofibre distribution in composites manufactured with epoxy reinforced with nanofibrillated cellulose: model prediction and verification

NASA Astrophysics Data System (ADS)

Aitomäki, Yvonne; Westin, Mikael; Korpimäki, Jani; Oksman, Kristiina

2016-07-01

In this study a model based on simple scattering is developed and used to predict the distribution of nanofibrillated cellulose in composites manufactured by resin transfer moulding (RTM) where the resin contains nanofibres. The model is a Monte Carlo based simulation where nanofibres are randomly chosen from probability density functions for length, diameter and orientation. Their movements are then tracked as they advance through a random arrangement of fibres in defined fibre bundles. The results of the model show that the fabric filters the nanofibres within the first 20 µm unless clear inter-bundle channels are available. The volume fraction of the fabric fibres, flow velocity and size of nanofibre influence this to some extent. To verify the model, an epoxy with 0.5 wt.% Kraft Birch nanofibres was made through a solvent exchange route and stained with a colouring agent. This was infused into a glass fibre fabric using an RTM process. The experimental results confirmed the filtering of the nanofibres by the fibre bundles and their penetration in the fabric via the inter-bundle channels. Hence, the model is a useful tool for visualising the distribution of the nanofibres in composites in this manufacturing process.

A Comparison of Tension and Compression Creep in a Polymeric Composite and the Effects of Physical Aging on Creep Behavior

NASA Technical Reports Server (NTRS)

Gates, Thomas S.; Veazie, David R.; Brinson, L. Catherine

1996-01-01

Experimental and analytical methods were used to investigate the similarities and differences of the effects of physical aging on creep compliance of IM7/K3B composite loaded in tension and compression. Two matrix dominated loading modes, shear and transverse, were investigated for two load cases, tension and compression. The tests, run over a range of sub-glass transition temperatures, provided material constants, material master curves and aging related parameters. Comparing results from the short-term data indicated that although trends in the data with respect to aging time and aging temperature are similar, differences exist due to load direction and mode. The analytical model used for predicting long-term behavior using short-term data as input worked equally as well for the tension or compression loaded cases. Comparison of the loading modes indicated that the predictive model provided more accurate long term predictions for the shear mode as compared to the transverse mode. Parametric studies showed the usefulness of the predictive model as a tool for investigating long-term performance and compliance acceleration due to temperature.

Protein and oil composition predictions of single soybeans by transmission Raman spectroscopy.

PubMed

Schulmerich, Matthew V; Walsh, Michael J; Gelber, Matthew K; Kong, Rong; Kole, Matthew R; Harrison, Sandra K; McKinney, John; Thompson, Dennis; Kull, Linda S; Bhargava, Rohit

2012-08-22

The soybean industry requires rapid, accurate, and precise technologies for the analyses of seed/grain constituents. While the current gold standard for nondestructive quantification of economically and nutritionally important soybean components is near-infrared spectroscopy (NIRS), emerging technology may provide viable alternatives and lead to next generation instrumentation for grain compositional analysis. In principle, Raman spectroscopy provides the necessary chemical information to generate models for predicting the concentration of soybean constituents. In this communication, we explore the use of transmission Raman spectroscopy (TRS) for nondestructive soybean measurements. We show that TRS uses the light scattering properties of soybeans to effectively homogenize the heterogeneous bulk of a soybean for representative sampling. Working with over 1000 individual intact soybean seeds, we developed a simple partial least-squares model for predicting oil and protein content nondestructively. We find TRS to have a root-mean-standard error of prediction (RMSEP) of 0.89% for oil measurements and 0.92% for protein measurements. In both calibration and validation sets, the predicative capabilities of the model were similar to the error in the reference methods.

Experiments Using a Ground-Based Electrostatic Levitator and Numerical Modeling of Melt Convection for the Iron-Cobalt System in Support of Space Experiments

NASA Astrophysics Data System (ADS)

Lee, Jonghyun; SanSoucie, Michael P.

2017-08-01

Materials research is being conducted using an electromagnetic levitator installed in the International Space Station. Various metallic alloys were tested to elucidate unknown links among the structures, processes, and properties. To accomplish the mission of these space experiments, several ground-based activities have been carried out. This article presents some of our ground-based supporting experiments and numerical modeling efforts. Mass evaporation of Fe50Co50, one of flight compositions, was predicted numerically and validated by the tests using an electrostatic levitator (ESL). The density of various compositions within the Fe-Co system was measured with ESL. These results are being served as reference data for the space experiments. The convection inside a electromagnetically-levitated droplet was also modeled to predict the flow status, shear rate, and convection velocity under various process parameters, which is essential information for designing and analyzing the space experiments of some flight compositions influenced by convection.

Composite prognostic models across the non-alcoholic fatty liver disease spectrum: Clinical application in developing countries

PubMed Central

Lückhoff, Hilmar K; Kruger, Frederik C; Kotze, Maritha J

2015-01-01

Heterogeneity in clinical presentation, histological severity, prognosis and therapeutic outcomes characteristic of non-alcoholic fatty liver disease (NAFLD) necessitates the development of scientifically sound classification schemes to assist clinicians in stratifying patients into meaningful prognostic subgroups. The need for replacement of invasive liver biopsies as the standard method whereby NAFLD is diagnosed, graded and staged with biomarkers of histological severity injury led to the development of composite prognostic models as potentially viable surrogate alternatives. In the present article, we review existing scoring systems used to (1) confirm the presence of undiagnosed hepatosteatosis; (2) distinguish between simple steatosis and NASH; and (3) predict advanced hepatic fibrosis, with particular emphasis on the role of NAFLD as an independent cardio-metabolic risk factor. In addition, the incorporation of functional genomic markers and application of emerging imaging technologies are discussed as a means to improve the diagnostic accuracy and predictive performance of promising composite models found to be most appropriate for widespread clinical adoption. PMID:26019735

Prediction of Size Effects in Notched Laminates Using Continuum Damage Mechanics

NASA Technical Reports Server (NTRS)

Camanho, D. P.; Maimi, P.; Davila, C. G.

2007-01-01

This paper examines the use of a continuum damage model to predict strength and size effects in notched carbon-epoxy laminates. The effects of size and the development of a fracture process zone before final failure are identified in an experimental program. The continuum damage model is described and the resulting predictions of size effects are compared with alternative approaches: the point stress and the inherent flaw models, the Linear-Elastic Fracture Mechanics approach, and the strength of materials approach. The results indicate that the continuum damage model is the most accurate technique to predict size effects in composites. Furthermore, the continuum damage model does not require any calibration and it is applicable to general geometries and boundary conditions.

Thermal-vacuum response of polymer matrix composites in space

NASA Technical Reports Server (NTRS)

Tennyson, R. C.; Matthews, R.

1993-01-01

This report describes a thermal-vacuum outgassing model and test protocol for predicting outgassing times and dimensional changes for polymer matrix composites. Experimental results derived from 'control' samples are used to provide the basis for analytical predictions to compare with the outgassing response of Long Duration Exposure Facility (LDEF) flight samples. Coefficient of thermal expansion (CTE) data are also presented. In addition, an example is given illustrating the dimensional change of a 'zero' CTE laminate due to moisture outgassing.

Analysis of Hydrogen Generation through Thermochemical Gasification of Coconut Shell Using Thermodynamic Equilibrium Model Considering Char and Tar

PubMed Central

Rupesh, Shanmughom; Muraleedharan, Chandrasekharan; Arun, Palatel

2014-01-01

This work investigates the potential of coconut shell for air-steam gasification using thermodynamic equilibrium model. A thermodynamic equilibrium model considering tar and realistic char conversion was developed using MATLAB software to predict the product gas composition. After comparing it with experimental results the prediction capability of the model is enhanced by multiplying equilibrium constants with suitable coefficients. The modified model is used to study the effect of key process parameters like temperature, steam to biomass ratio, and equivalence ratio on product gas yield, composition, and heating value of syngas along with gasification efficiency. For a steam to biomass ratio of unity, the maximum mole fraction of hydrogen in the product gas is found to be 36.14% with a lower heating value of 7.49 MJ/Nm3 at a gasification temperature of 1500 K and equivalence ratio of 0.15. PMID:27433487

Analysis of Hydrogen Generation through Thermochemical Gasification of Coconut Shell Using Thermodynamic Equilibrium Model Considering Char and Tar.

PubMed

Rupesh, Shanmughom; Muraleedharan, Chandrasekharan; Arun, Palatel

2014-01-01

This work investigates the potential of coconut shell for air-steam gasification using thermodynamic equilibrium model. A thermodynamic equilibrium model considering tar and realistic char conversion was developed using MATLAB software to predict the product gas composition. After comparing it with experimental results the prediction capability of the model is enhanced by multiplying equilibrium constants with suitable coefficients. The modified model is used to study the effect of key process parameters like temperature, steam to biomass ratio, and equivalence ratio on product gas yield, composition, and heating value of syngas along with gasification efficiency. For a steam to biomass ratio of unity, the maximum mole fraction of hydrogen in the product gas is found to be 36.14% with a lower heating value of 7.49 MJ/Nm(3) at a gasification temperature of 1500 K and equivalence ratio of 0.15.

New NIR Calibration Models Speed Biomass Composition and Reactivity Characterization

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

2015-09-01

Obtaining accurate chemical composition and reactivity (measures of carbohydrate release and yield) information for biomass feedstocks in a timely manner is necessary for the commercialization of biofuels. This highlight describes NREL's work to use near-infrared (NIR) spectroscopy and partial least squares multivariate analysis to develop calibration models to predict the feedstock composition and the release and yield of soluble carbohydrates generated by a bench-scale dilute acid pretreatment and enzymatic hydrolysis assay. This highlight is being developed for the September 2015 Alliance S&T Board meeting.

Prediction of impact force and duration during low velocity impact on circular composite laminates

NASA Technical Reports Server (NTRS)

Shivakumar, K. N.; Elber, W.; Illg, W.

1983-01-01

Two simple and improved models--energy-balance and spring-mass--were developed to calculate impact force and duration during low velocity impact of circular composite plates. Both models include the contact deformation of the plate and the impactor as well as bending, transverse shear, and membrane deformations of the plate. The plate was transversely isotropic graphite/epoxy composite laminate and the impactor was a steel sphere. Calculated impact forces from the two analyses agreed with each other. The analyses were verified by comparing the results with reported test data.

Orthotropic elasto-plastic behavior of AS4/APC-2 thermoplastic composite in compression

NASA Technical Reports Server (NTRS)

Sun, C. T.; Rui, Y.

1989-01-01

Uniaxial compression tests were performed on off-axis coupon specimens of unidirectional AS4/APC-2 thermoplastic composite at various temperatures. The elasto-plastic and strength properties of AS4/APC-2 composite were characterized with respect to temperature variation by using a one-parameter orthotropic plasticity model and a one-parameter failure criterion. Experimental results show that the orthotropic plastic behavior can be characterized quite well using the plasticity model, and the matrix-dominant compressive strengths can be predicted very accurately by the one-parameter failure criterion.

A nondestructive technique for predicting the strength remaining in filament wound composites subjected to low-level impact

NASA Technical Reports Server (NTRS)

Madaras, E. I.; Poe, C. C.; Heyman, J. S.

1987-01-01

A model for predicting the fracture strength of homogeneous materials is proposed. Impacted FWC samples were evaluated using ultrasonic testing and an X-ray dye penetration method. The ability of the model to measure fracture strength was also examined. The relation between attenuation and velocity measurements is studied. It is observed that the X-ray method is not useful for predicting fracture strength because the dye could not penetrate the matrix. It is noted that fracture strength predictions derived from the fracture mechanical model and the ultrasonic measurements correlate well with actual measured fracture strengths.

Full-scale testing and progressive damage modeling of sandwich composite aircraft fuselage structure

NASA Astrophysics Data System (ADS)

Leone, Frank A., Jr.

A comprehensive experimental and computational investigation was conducted to characterize the fracture behavior and structural response of large sandwich composite aircraft fuselage panels containing artificial damage in the form of holes and notches. Full-scale tests were conducted where panels were subjected to quasi-static combined pressure, hoop, and axial loading up to failure. The panels were constructed using plain-weave carbon/epoxy prepreg face sheets and a Nomex honeycomb core. Panel deformation and notch tip damage development were monitored during the tests using several techniques, including optical observations, strain gages, digital image correlation (DIC), acoustic emission (AE), and frequency response (FR). Additional pretest and posttest inspections were performed via thermography, computer-aided tap tests, ultrasound, x-radiography, and scanning electron microscopy. The framework to simulate damage progression and to predict residual strength through use of the finite element (FE) method was developed. The DIC provided local and full-field strain fields corresponding to changes in the state-of-damage and identified the strain components driving damage progression. AE was monitored during loading of all panels and data analysis methodologies were developed to enable real-time determination of damage initiation, progression, and severity in large composite structures. The FR technique has been developed, evaluating its potential as a real-time nondestructive inspection technique applicable to large composite structures. Due to the large disparity in scale between the fuselage panels and the artificial damage, a global/local analysis was performed. The global FE models fully represented the specific geometries, composite lay-ups, and loading mechanisms of the full-scale tests. A progressive damage model was implemented in the local FE models, allowing the gradual failure of elements in the vicinity of the artificial damage. A set of modifications to the definitions of the local FE model boundary conditions is proposed and developed to address several issues related to the scalability of progressive damage modeling concepts, especially in regards to full-scale fuselage structures. Notable improvements were observed in the ability of the FE models to predict the strength of damaged composite fuselage structures. Excellent agreement has been established between the FE model predictions and the experimental results recorded by DIC, AE, FR, and visual observations.

Calibration transfer of a Raman spectroscopic quantification method from at-line to in-line assessment of liquid detergent compositions.

PubMed

Brouckaert, D; Uyttersprot, J-S; Broeckx, W; De Beer, T

2017-06-08

The industrial production of liquid detergent compositions entails delicate balance of ingredients and process steps. In order to assure high quality and productivity in the manufacturing line, process analytical technology tools such as Raman spectroscopy are to be implemented. Marked chemical specificity, negligible water interference and high robustness are ascribed to this process analytical technique. Previously, at-line calibration models have been developed for determining the concentration levels of the being studied liquid detergents main ingredients from Raman spectra. A strategy is now proposed to transfer such at-line developed regression models to an in-line set-up, allowing real-time dosing control of the liquid detergent composition under production. To mimic in-line manufacturing conditions, liquid detergent compositions are created in a five-liter vessel with an overhead mixer. Raman spectra are continuously acquired by pumping the detergent under production via plastic tubing towards a Raman superhead probe, which is incorporated into a metal frame with a sapphire window facing the detergent fluid. Two at-line developed partial least squares (PLS) models are aimed at transferring, predicting the concentration of surfactant 1 and polymer 2 in the examined liquid detergent composition. A univariate slope/bias correction (SBC) is investigated, next to three well-acknowledged multivariate transformation methods: direct, piecewise and double-window piecewise direct standardization. Transfer is considered successful when the magnitude of the validation sets root mean square error of prediction (RMSEP) is similar to or smaller than the corresponding at-line prediction error. The transferred model offering the most promising outcome is further subjected to an exhaustive statistical evaluation, in order to appraise the applicability of the suggested calibration transfer method. Interval hypothesis tests are thereby performed for method comparison. It is illustrated that the investigated transfer approach yields satisfactory results, provided that the original at-line calibration model is thoroughly validated. Both SBC transfer models return lower RMSEP values than their corresponding original models. The surfactant 1 assay met all relevant evaluation criteria, demonstrating successful transfer to the in-line set-up. The in-line quantification of polymer 2 levels in the liquid detergent composition could not be statistically validated, due to the poorer performance of the at-line model. Copyright © 2017 Elsevier B.V. All rights reserved.

Metal Ion Speciation and Dissolved Organic Matter Composition in Soil Solutions

NASA Astrophysics Data System (ADS)

Benedetti, M. F.; Ren, Z. L.; Bravin, M.; Tella, M.; Dai, J.

2014-12-01

Knowledge of the speciation of heavy metals and the role of dissolved organic matter (DOM) in soil solution is a key to understand metal mobility and ecotoxicity. In this study, soil column-Donnan membrane technique (SC-DMT) was used to measure metal speciation of Cd, Cu, Ni, Pb, and Zn in eighteen soil solutions, covering a wide range of metal sources and concentrations. DOM composition in these soil solutions was also determined. Our results show that in soil solution Pb and Cu are dominant in complex form, whereas Cd, Ni and Zn mainly exist as free ions; for the whole range of soil solutions, only 26.2% of DOM is reactive and consists mainly of fulvic acid (FA). The metal speciation measured by SC-DMT was compared to the predicted ones obtained via the NICA-Donnan model using the measured FA concentrations. The free ion concentrations predicted by speciation modelling were in good agreement with the measurements. Diffusive gradients in thin-films gels (DGT) were also performed to quantify the labile metal species in the fluxes from solid phase to solution in fourteen soils. The concentrations of metal species detected by DGT were compared with the free ion concentrations measured by DMT and the maximum concentrations calculated based on the predicted metal speciation in SC-DMT soil solutions. It is concluded that both inorganic species and a fraction of FA bound species account for the amount of labile metals measured by DGT, consistent with the dynamic features of this technique. The comparisons between measurements using analytical techniques and mechanistic model predictions provided mutual validation in their performance. Moreover, we show that to make accurate modelling of metal speciation in soil solutions, the knowledge of DOM composition is the crucial information, especially for Cu; like in previous studies the modelling of Pb speciation is not optimal and an updated of Pb generic binding parameters is required to reduce model prediction uncertainties.

Mechanics of damping for fiber composite laminates including hygro-thermal effects

NASA Technical Reports Server (NTRS)

Saravanos, D. A.; Chamis, C. C.

1989-01-01

An integrated mechanics theory has been developed for the modeling of composite damping from the micromechanics to the laminate level. Simplified, design oriented equations based on hysteretic damping are presented for on-axis plies, off-axis plies, and laminates including the effect of temperature, moisture, and interply hysteretic damping. The temperature rise within vibrating composite laminates resulting from strain energy dissipation is also modeled, and their coupled hygro-thermo-mechanical response is predicted. The method correlates well with reported damping measurements. Application examples illustrate the effect of various ply, laminate, and hygro-thermal parameters on the overall damping performance of composite laminates.

Mechanics of damping for fiber composite laminates including hygro-thermal effects

NASA Technical Reports Server (NTRS)

Saravanos, D. A.; Chamis, Christos C.

1989-01-01

An integrated mechanics theory was developed for the modeling of composite damping from the micromechanics to the laminate level. Simplified, design oriented equations based on hysteretic damping are presented for on-axis plies, off-axis plies, and laminates including the effect of temperature, moisture, and interply hysteretic damping. The temperature rise within vibrating composite laminates resulting from strain energy dissipation is also modeled, and their coupled hygro-thermo-mechanical response is predicted. The method correlates well with reported damping measurements. Application examples illustrate the effect of various ply, laminate, and hygro-thermal parameters on the overall damping performance of composite laminates.

Impact and damage of an armor composite

NASA Astrophysics Data System (ADS)

Resnyansky, A. D.; Parry, S.; Bourne, N. K.; Townsend, D.; James, B. J.

2015-06-01

The use of carbon fiber composites under shock and impact loading in aerospace, defense and automotive applications is increasingly important. Therefore prediction of the composite behavior and damage in these conditions is critical. Influence of anisotropy, fiber orientation and the rate of loading during the impact is considered in the present study and validated by comparison with experiments. The experiments deal with the plane, ballistic and Taylor impacts accompanied by high-speed photography observations and tomography of recovered samples. The CTH hydrocode is employed as the modeling platform with an advanced rate sensitive material model used for description of the deformation and damage of the transversely isotropic composite material.

Dynamic mechanical properties of a Ti-based metallic glass matrix composite

NASA Astrophysics Data System (ADS)

Li, Jinshan; Cui, Jing; Qiao, Jichao; Bai, Jie; Kou, Hongchao; Wang, Jun

2015-04-01

Dynamic mechanical behavior of a Ti50Zr20Nb12Cu5Be13 bulk metallic glass composite was investigated using mechanical spectroscopy in both temperature and frequency domains. Storage modulus G' and loss modulus G″ are determined by temperature, and three distinct regions corresponding to different states in the bulk metallic glass composite are characterized. Physical parameters, such as atomic mobility and correlation factor χ, are introduced to analyze dynamic mechanical behavior of the bulk metallic glass composite in the framework of quasi-point defects (QPD) model. The experimental results are in good agreement with the prediction of QPD model.

Dynamic mechanical properties of a Ti-based metallic glass matrix composite

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

Li, Jinshan, E-mail: ljsh@nwpu.edu.cn; Cui, Jing; Bai, Jie

2015-04-21

Dynamic mechanical behavior of a Ti{sub 50}Zr{sub 20}Nb{sub 12}Cu{sub 5}Be{sub 13} bulk metallic glass composite was investigated using mechanical spectroscopy in both temperature and frequency domains. Storage modulus G′ and loss modulus G″ are determined by temperature, and three distinct regions corresponding to different states in the bulk metallic glass composite are characterized. Physical parameters, such as atomic mobility and correlation factor χ, are introduced to analyze dynamic mechanical behavior of the bulk metallic glass composite in the framework of quasi-point defects (QPD) model. The experimental results are in good agreement with the prediction of QPD model.

A Damage Model for the Simulation of Delamination in Advanced Composites under Variable-Mode Loading

NASA Technical Reports Server (NTRS)

Turon, A.; Camanho, P. P.; Costa, J.; Davila, C. G.

2006-01-01

A thermodynamically consistent damage model is proposed for the simulation of progressive delamination in composite materials under variable-mode ratio. The model is formulated in the context of Damage Mechanics. A novel constitutive equation is developed to model the initiation and propagation of delamination. A delamination initiation criterion is proposed to assure that the formulation can account for changes in the loading mode in a thermodynamically consistent way. The formulation accounts for crack closure effects to avoid interfacial penetration of two adjacent layers after complete decohesion. The model is implemented in a finite element formulation, and the numerical predictions are compared with experimental results obtained in both composite test specimens and structural components.

The Effect of Chemical Functionalization on Mechanical Properties of Nanotube/Polymer Composites

NASA Technical Reports Server (NTRS)

Odegard, G. M.; Frankland, S. J. V.; Gates, T. S.

2003-01-01

The effects of the chemical functionalization of a carbon nanotube embedded in a nanotube/polyethylene composite on the bulk elastic properties are presented. Constitutive equations are established for both functionalized and non-functionalized nanotube composites systems by using an equivalent-continuum modeling technique. The elastic properties of both composites systems are predicted for various nanotube lengths, volume fractions, and orientations. The results indicate that for the specific composite material considered in this study, most of the elastic stiffness constants of the functionalized composite are either less than or equal to those of the non-functionalized composite.

Fatigue Life Methodology for Bonded Composite Skin/Stringer Configurations

NASA Technical Reports Server (NTRS)

Krueger, Ronald; Paris, Isabelle L.; OBrien, T. Kevin; Minguet, Pierre J.

2001-01-01

A methodology is presented for determining the fatigue life of composite structures based on fatigue characterization data and geometric nonlinear finite element (FE) analyses. To demonstrate the approach, predicted results were compared to fatigue tests performed on specimens which represented a tapered composite flange bonded onto a composite skin. In a first step, tension tests were performed to evaluate the debonding mechanisms between the flange and the skin. In a second step, a 2D FE model was developed to analyze the tests. To predict matrix cracking onset, the relationship between the tension load and the maximum principal stresses transverse to the fiber direction was determined through FE analysis. Transverse tension fatigue life data were used to -enerate an onset fatigue life P-N curve for matrix cracking. The resulting prediction was in good agreement with data from the fatigue tests. In a third step, a fracture mechanics approach based on FE analysis was used to determine the relationship between the tension load and the critical energy release rate. Mixed mode energy release rate fatigue life data were used to create a fatigue life onset G-N curve for delamination. The resulting prediction was in good agreement with data from the fatigue tests. Further, the prediction curve for cumulative life to failure was generated from the previous onset fatigue life curves. The results showed that the methodology offers a significant potential to Predict cumulative fatigue life of composite structures.

Effect of stacking sequence and surface treatment on the thermal conductivity of multilayered hybrid nano-composites

NASA Astrophysics Data System (ADS)

Papanicolaou, G. C.; Pappa, E. J.; Portan, D. V.; Kotrotsos, A.; Kollia, E.

2018-02-01

The aim of the present investigation was to study the effect of both the stacking sequence and surface treatment on the thermal conductivity of multilayered hybrid nano-composites. Four types of multilayered hybrid nanocomposites were manufactured and tested: Nitinol- CNTs (carbon nanotubes)- Acrylic resin; Nitinol- Acrylic resin- CNTs; Surface treated Nitinol- CNTs- Acrylic resin and Surface treated Nitinol- Acrylic resin- CNTs. Surface treatment of Nitinol plies was realized by means of the electrochemical anodization. Surface topography of the anodized nitinol sheets was investigated through Scanning Electron Microscopy (SEM). It was found that the overall thermal response of the manufactured multilayered nano-composites was greatly influenced by both the anodization and the stacking sequence. A theoretical model for the prediction of the overall thermal conductivity has been developed considering the nature of the different layers, their stacking sequence as well as the interfacial thermal resistance. Thermal conductivity and Differential Scanning Calorimetry (DSC) measurements were conducted, to verify the predicted by the model overall thermal conductivities. In all cases, a good agreement between theoretical predictions and experimental results was found.

Dynamic optimization of metabolic networks coupled with gene expression.

PubMed

Waldherr, Steffen; Oyarzún, Diego A; Bockmayr, Alexander

2015-01-21

The regulation of metabolic activity by tuning enzyme expression levels is crucial to sustain cellular growth in changing environments. Metabolic networks are often studied at steady state using constraint-based models and optimization techniques. However, metabolic adaptations driven by changes in gene expression cannot be analyzed by steady state models, as these do not account for temporal changes in biomass composition. Here we present a dynamic optimization framework that integrates the metabolic network with the dynamics of biomass production and composition. An approximation by a timescale separation leads to a coupled model of quasi-steady state constraints on the metabolic reactions, and differential equations for the substrate concentrations and biomass composition. We propose a dynamic optimization approach to determine reaction fluxes for this model, explicitly taking into account enzyme production costs and enzymatic capacity. In contrast to the established dynamic flux balance analysis, our approach allows predicting dynamic changes in both the metabolic fluxes and the biomass composition during metabolic adaptations. Discretization of the optimization problems leads to a linear program that can be efficiently solved. We applied our algorithm in two case studies: a minimal nutrient uptake network, and an abstraction of core metabolic processes in bacteria. In the minimal model, we show that the optimized uptake rates reproduce the empirical Monod growth for bacterial cultures. For the network of core metabolic processes, the dynamic optimization algorithm predicted commonly observed metabolic adaptations, such as a diauxic switch with a preference ranking for different nutrients, re-utilization of waste products after depletion of the original substrate, and metabolic adaptation to an impending nutrient depletion. These examples illustrate how dynamic adaptations of enzyme expression can be predicted solely from an optimization principle. Copyright © 2014 Elsevier Ltd. All rights reserved.

Process-time Optimization of Vacuum Degassing Using a Genetic Alloy Design Approach

PubMed Central

Dilner, David; Lu, Qi; Mao, Huahai; Xu, Wei; van der Zwaag, Sybrand; Selleby, Malin

2014-01-01

This paper demonstrates the use of a new model consisting of a genetic algorithm in combination with thermodynamic calculations and analytical process models to minimize the processing time during a vacuum degassing treatment of liquid steel. The model sets multiple simultaneous targets for final S, N, O, Si and Al levels and uses the total slag mass, the slag composition, the steel composition and the start temperature as optimization variables. The predicted optimal conditions agree well with industrial practice. For those conditions leading to the shortest process time the target compositions for S, N and O are reached almost simultaneously. PMID:28788286

Modeling the mechanical behavior of ceramic and heterophase structures manufactured using selective laser sintering and spark plasma sintering

NASA Astrophysics Data System (ADS)

Skripnyak, Vladimir A.; Skripnyak, Evgeniya G.; Skripnyak, Vladimir V.; Vaganova, Irina K.

A model for predicting mechanical properties of ultra-high temperature ceramics and composites manufactured by selective laser sintering (SLS) and spark plasma sintering (SPS) under shock loading is presented. The model takes into account the porous structure, the specific volume and average sizes of phases, and the temperature of sintering. Residual stresses in ceramic composites reinforced with particles of refractory borides, carbides and nitrides after SLS or SPS were calculated. It is shown that the spall strength of diboride-zirconium matrix composites can be increased by the decreasing of porosity and the introduction of inclusions of specially selected refractory strengthening phases.

Developing strategies to initialize landscape-scale vegetation maps from FIA data to enhance resolution of individual species-size cohort representation in the landscape disturbance model SIMPPLLE

Treesearch

Jacob John Muller

2014-01-01

The ability of forest resource managers to understand and anticipate landscape-scale change in composition and structure relies upon an adequate characterization of the current forest composition and structure of various patches (or stands), along with the capacity of forest landscape models (FLMs) to predict patterns of growth, succession, and disturbance at multiple...

Predicting the viscosity of solids using steady-state creep behavior of the fibrous composites semi-theoretically

NASA Astrophysics Data System (ADS)

Monfared, Vahid

A semi-analytical formulation is presented for obtaining the viscosity of solids (such as metals) using the steady state creep model of the short-fiber composites. For achieving this aim, fluid mechanics theory is used for determining the viscosity. Sometimes, obtaining the viscosity is experimentally difficult and intricate. So, the present model may be beneficial to obtain the viscosity of metals.

Histologic and biochemical alterations predict pulmonary mechanical dysfunction in aging mice with chronic lung inflammation

PubMed Central

Laskin, Debra L.; Gow, Andrew J.

2017-01-01

Both aging and chronic inflammation produce complex structural and biochemical alterations to the lung known to impact work of breathing. Mice deficient in surfactant protein D (Sftpd) develop progressive age-related lung pathology characterized by tissue destruction/remodeling, accumulation of foamy macrophages and alteration in surfactant composition. This study proposes to relate changes in tissue structure seen in normal aging and in chronic inflammation to altered lung mechanics using a computational model. Alterations in lung function in aging and Sftpd -/- mice have been inferred from fitting simple mechanical models to respiratory impedance data (Zrs), however interpretation has been confounded by the simultaneous presence of multiple coexisting pathophysiologic processes. In contrast to the inverse modeling approach, this study uses simulation from experimental measurements to recapitulate how aging and inflammation alter Zrs. Histologic and mechanical measurements were made in C57BL6/J mice and congenic Sftpd-/- mice at 8, 27 and 80 weeks of age (n = 8/group). An anatomic computational model based on published airway morphometry was developed and Zrs was simulated between 0.5 and 20 Hz. End expiratory pressure dependent changes in airway caliber and recruitment were estimated from mechanical measurements. Tissue elements were simulated using the constant phase model of viscoelasticity. Baseline elastance distribution was estimated in 8-week-old wild type mice, and stochastically varied for each condition based on experimentally measured alteration in elastic fiber composition, alveolar geometry and surfactant composition. Weighing reduction in model error against increasing model complexity allowed for identification of essential features underlying mechanical pathology and their contribution to Zrs. Using a maximum likelihood approach, alteration in lung recruitment and diminished elastic fiber density were shown predictive of mechanical alteration at airway opening, to a greater extent than overt acinar wall destruction. Model-predicted deficits in PEEP-dependent lung recruitment correlate with altered lung lining fluid composition independent of age or genotype. PMID:28837561

Histologic and biochemical alterations predict pulmonary mechanical dysfunction in aging mice with chronic lung inflammation.

PubMed

Massa, Christopher B; Groves, Angela M; Jaggernauth, Smita U; Laskin, Debra L; Gow, Andrew J

2017-08-01

Both aging and chronic inflammation produce complex structural and biochemical alterations to the lung known to impact work of breathing. Mice deficient in surfactant protein D (Sftpd) develop progressive age-related lung pathology characterized by tissue destruction/remodeling, accumulation of foamy macrophages and alteration in surfactant composition. This study proposes to relate changes in tissue structure seen in normal aging and in chronic inflammation to altered lung mechanics using a computational model. Alterations in lung function in aging and Sftpd -/- mice have been inferred from fitting simple mechanical models to respiratory impedance data (Zrs), however interpretation has been confounded by the simultaneous presence of multiple coexisting pathophysiologic processes. In contrast to the inverse modeling approach, this study uses simulation from experimental measurements to recapitulate how aging and inflammation alter Zrs. Histologic and mechanical measurements were made in C57BL6/J mice and congenic Sftpd-/- mice at 8, 27 and 80 weeks of age (n = 8/group). An anatomic computational model based on published airway morphometry was developed and Zrs was simulated between 0.5 and 20 Hz. End expiratory pressure dependent changes in airway caliber and recruitment were estimated from mechanical measurements. Tissue elements were simulated using the constant phase model of viscoelasticity. Baseline elastance distribution was estimated in 8-week-old wild type mice, and stochastically varied for each condition based on experimentally measured alteration in elastic fiber composition, alveolar geometry and surfactant composition. Weighing reduction in model error against increasing model complexity allowed for identification of essential features underlying mechanical pathology and their contribution to Zrs. Using a maximum likelihood approach, alteration in lung recruitment and diminished elastic fiber density were shown predictive of mechanical alteration at airway opening, to a greater extent than overt acinar wall destruction. Model-predicted deficits in PEEP-dependent lung recruitment correlate with altered lung lining fluid composition independent of age or genotype.

Continuous fiber ceramic matrix composites for heat engine components

NASA Technical Reports Server (NTRS)

Tripp, David E.

1988-01-01

High strength at elevated temperatures, low density, resistance to wear, and abundance of nonstrategic raw materials make structural ceramics attractive for advanced heat engine applications. Unfortunately, ceramics have a low fracture toughness and fail catastrophically because of overload, impact, and contact stresses. Ceramic matrix composites provide the means to achieve improved fracture toughness while retaining desirable characteristics, such as high strength and low density. Materials scientists and engineers are trying to develop the ideal fibers and matrices to achieve the optimum ceramic matrix composite properties. A need exists for the development of failure models for the design of ceramic matrix composite heat engine components. Phenomenological failure models are currently the most frequently used in industry, but they are deterministic and do not adequately describe ceramic matrix composite behavior. Semi-empirical models were proposed, which relate the failure of notched composite laminates to the stress a characteristic distance away from the notch. Shear lag models describe composite failure modes at the micromechanics level. The enhanced matrix cracking stress occurs at the same applied stress level predicted by the two models of steady state cracking. Finally, statistical models take into consideration the distribution in composite failure strength. The intent is to develop these models into computer algorithms for the failure analysis of ceramic matrix composites under monotonically increasing loads. The algorithms will be included in a postprocessor to general purpose finite element programs.

Water Uptake Behavior and Young Modulus Prediction of Composites Based on Treated Sisal Fibers and Poly(Lactic Acid)

PubMed Central

Orue, Ander; Eceiza, Arantxa; Peña-Rodriguez, Cristina; Arbelaiz, Aitor

2016-01-01

The main aim of this work was to study the effect of sisal fiber surface treatments on water uptake behavior of composites based on untreated and treated fibers. For this purpose, sisal fibers were treated with different chemical treatments. All surface treatments delayed the water absorption of fibers only for a short time of period. No significant differences were observed in water uptake profiles of composites based on fibers with different surface treatments. After water uptake period, tensile strength and Young modulus values of sisal fiber/poly(lactic acid) (PLA) composites were decreased. On the other hand, composites based on NaOH + silane treated fibers showed the lowest diffusion coefficient values, suggesting that this treatment seemed to be the most effective treatment to reduce water diffusion rate into the composites. Finally, Young modulus values of composites, before water uptake period, were predicted using different micromechanical models and were compared with experimental data. PMID:28773524

Predicting the mineral composition of dust aerosols: Insights from elemental composition measured at the Izaña Observatory

NASA Astrophysics Data System (ADS)

Pérez García-Pando, Carlos; Miller, Ron L.; Perlwitz, Jan P.; Rodríguez, Sergio; Prospero, Joseph M.

2016-10-01

Regional variations of dust mineral composition are fundamental to climate impacts but generally neglected in climate models. A challenge for models is that atlases of soil composition are derived from measurements following wet sieving, which destroys the aggregates potentially emitted from the soil. Aggregates are crucial to simulating the observed size distribution of emitted soil particles. We use an extension of brittle fragmentation theory in a global dust model to account for these aggregates. Our method reproduces the size-resolved dust concentration along with the approximately size-invariant fractional abundance of elements like Fe and Al in the decade-long aerosol record from the Izaña Observatory, off the coast of West Africa. By distinguishing between Fe in structural and free forms, we can attribute improved model behavior to aggregation of Fe and Al-rich clay particles. We also demonstrate the importance of size-resolved measurements along with elemental composition analysis to constrain models.

Damage Simulation in Non-Crimp Fabric Composite Plates Subjected to Impact Loads

NASA Technical Reports Server (NTRS)

Satyanarayana, Arunkumar; Bogert, Philip B.; Aitharaju, Venkat; Aashat, Satvir; Kia, Hamid

2014-01-01

Progressive failure analysis (PFA) of non-crimp fabric (NCF) composite laminates subjected to low velocity impact loads was performed using the COmplete STress Reduction (COSTR) damage model implemented through VUMAT and UMAT41 user subroutines in the frame works of the commercial finite element programs ABAQUS/Explicit and LS-DYNA, respectively. To validate the model, low velocity experiments were conducted and detailed correlations between the predictions and measurements for both intra-laminar and inter-laminar failures were made. The developed material and damage model predicts the peak impact load and duration very close with the experimental results. Also, the simulation results of delamination damage between the ply interfaces, in-plane matrix damages and fiber damages were all in good agreement with the measurements from the non-destructive evaluation data.

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

Siranosian, Antranik Antonio; Schembri, Philip Edward; Luscher, Darby Jon

The Los Alamos National Laboratory's Weapon Systems Engineering division's Advanced Engineering Analysis group employs material constitutive models of composites for use in simulations of components and assemblies of interest. Experimental characterization, modeling and prediction of the macro-scale (i.e. continuum) behaviors of these composite materials is generally difficult because they exhibit nonlinear behaviors on the meso- (e.g. micro-) and macro-scales. Furthermore, it can be difficult to measure and model the mechanical responses of the individual constituents and constituent interactions in the composites of interest. Current efforts to model such composite materials rely on semi-empirical models in which meso-scale properties are inferredmore » from continuum level testing and modeling. The proposed approach involves removing the difficulties of interrogating and characterizing micro-scale behaviors by scaling-up the problem to work with macro-scale composites, with the intention of developing testing and modeling capabilities that will be applicable to the mesoscale. This approach assumes that the physical mechanisms governing the responses of the composites on the meso-scale are reproducible on the macro-scale. Working on the macro-scale simplifies the quantification of composite constituents and constituent interactions so that efforts can be focused on developing material models and the testing techniques needed for calibration and validation. Other benefits to working with macro-scale composites include the ability to engineer and manufacture—potentially using additive manufacturing techniques—composites that will support the application of advanced measurement techniques such as digital volume correlation and three-dimensional computed tomography imaging, which would aid in observing and quantifying complex behaviors that are exhibited in the macro-scale composites of interest. Ultimately, the goal of this new approach is to develop a meso-scale composite modeling framework, applicable to many composite materials, and the corresponding macroscale testing and test data interrogation techniques to support model calibration.« less

WRF-TMH: predicting transmembrane helix by fusing composition index and physicochemical properties of amino acids.

PubMed

Hayat, Maqsood; Khan, Asifullah

2013-05-01

Membrane protein is the prime constituent of a cell, which performs a role of mediator between intra and extracellular processes. The prediction of transmembrane (TM) helix and its topology provides essential information regarding the function and structure of membrane proteins. However, prediction of TM helix and its topology is a challenging issue in bioinformatics and computational biology due to experimental complexities and lack of its established structures. Therefore, the location and orientation of TM helix segments are predicted from topogenic sequences. In this regard, we propose WRF-TMH model for effectively predicting TM helix segments. In this model, information is extracted from membrane protein sequences using compositional index and physicochemical properties. The redundant and irrelevant features are eliminated through singular value decomposition. The selected features provided by these feature extraction strategies are then fused to develop a hybrid model. Weighted random forest is adopted as a classification approach. We have used two benchmark datasets including low and high-resolution datasets. tenfold cross validation is employed to assess the performance of WRF-TMH model at different levels including per protein, per segment, and per residue. The success rates of WRF-TMH model are quite promising and are the best reported so far on the same datasets. It is observed that WRF-TMH model might play a substantial role, and will provide essential information for further structural and functional studies on membrane proteins. The accompanied web predictor is accessible at http://111.68.99.218/WRF-TMH/ .

Analytical and numerical techniques for predicting the interfacial stresses of wavy carbon nanotube/polymer composites

NASA Astrophysics Data System (ADS)

Yazdchi, K.; Salehi, M.; Shokrieh, M. M.

2009-03-01

By introducing a new simplified 3D representative volume element for wavy carbon nanotubes, an analytical model is developed to study the stress transfer in single-walled carbon nanotube-reinforced polymer composites. Based on the pull-out modeling technique, the effects of waviness, aspect ratio, and Poisson ratio on the axial and interfacial shear stresses are analyzed in detail. The results of the present analytical model are in a good agreement with corresponding results for straight nanotubes.

Modeling Composite Laminate Crushing for Crash Analysis

NASA Technical Reports Server (NTRS)

Fleming, David C.; Jones, Lisa (Technical Monitor)

2002-01-01

Crash modeling of composite structures remains limited in application and has not been effectively demonstrated as a predictive tool. While the global response of composite structures may be well modeled, when composite structures act as energy-absorbing members through direct laminate crushing the modeling accuracy is greatly reduced. The most efficient composite energy absorbing structures, in terms of energy absorbed per unit mass, are those that absorb energy through a complex progressive crushing response in which fiber and matrix fractures on a small scale dominate the behavior. Such failure modes simultaneously include delamination of plies, failure of the matrix to produce fiber bundles, and subsequent failure of fiber bundles either in bending or in shear. In addition, the response may include the significant action of friction, both internally (between delaminated plies or fiber bundles) or externally (between the laminate and the crushing surface). A figure shows the crushing damage observed in a fiberglass composite tube specimen, illustrating the complexity of the response. To achieve a finite element model of such complex behavior is an extremely challenging problem. A practical crushing model based on detailed modeling of the physical mechanisms of crushing behavior is not expected in the foreseeable future. The present research describes attempts to model composite crushing behavior using a novel hybrid modeling procedure. Experimental testing is done is support of the modeling efforts, and a test specimen is developed to provide data for validating laminate crushing models.

Mechanical characterization and modeling of sponge-reinforced hydrogel composites under compression.

PubMed

Wu, Lei; Mao, Guoyong; Nian, Guodong; Xiang, Yuhai; Qian, Jin; Qu, Shaoxing

2018-05-30

Load-bearing applications of hydrogels call for materials with excellent mechanical properties. Despite the considerable progress in developing tough hydrogels, there is still a requirement to prepare high-performance hydrogels using simple strategies. In this paper, a sponge-reinforced hydrogel composite is synthesized by combining poly(acrylamide) (PAAm) hydrogel and polyurethane (PU) sponge. Uniaxial compressive testing of the hydrogel composites reveals that both the compressive modulus and the strength of the hydrogel composites are much higher than those of the PAAm hydrogel or sponge. In order to predict the compressive modulus of the hydrogel composite, we develop a theoretical model that is validated by experiments and numerical simulations. The present work may guide the design and manufacture of hydrogel-based composite materials, especially for biomaterial scaffolds and soft transducers.

The converse magnetoelectric coupling in asymmetric granule/matrix composite film with Ni/PZT component

NASA Astrophysics Data System (ADS)

Chen, Bo; Su, Ning-Ning; Cui, Wen-Li; Yan, Shi-Nong

2018-04-01

In this work, a type of asymmetric granule/matrix composite film is designed, where the Ni granule is dispersed in PZT matrix, meanwhile the top and bottom electrode is constituted by Au and SRO respectively. Predicted through the electrostatic screening model and mean field approximation, considerable electrostatic charge is induced on Ni granule surface by ferroelectric PZT polarization. Predicted through the spin splitting model and spherical shell approximation, both the magnetization and magnetic anisotropy of Ni granule are modulated by ferroelectric PZT polarization. As the volume fraction of Ni granule is increased, the electric modulation of magnetization and magnetic anisotropy is reduced and enhanced respectively. As the dimension of granule/matrix composite is varied, such modulation is retained. Due to the large area-volume ratio of nano-granule, this work benefits to realize the converse magnetoelectric coupling in nanoscale.

A general mixture theory. I. Mixtures of spherical molecules

NASA Astrophysics Data System (ADS)

Hamad, Esam Z.

1996-08-01

We present a new general theory for obtaining mixture properties from the pure species equations of state. The theory addresses the composition and the unlike interactions dependence of mixture equation of state. The density expansion of the mixture equation gives the exact composition dependence of all virial coefficients. The theory introduces multiple-index parameters that can be calculated from binary unlike interaction parameters. In this first part of the work, details are presented for the first and second levels of approximations for spherical molecules. The second order model is simple and very accurate. It predicts the compressibility factor of additive hard spheres within simulation uncertainty (equimolar with size ratio of three). For nonadditive hard spheres, comparison with compressibility factor simulation data over a wide range of density, composition, and nonadditivity parameter, gave an average error of 2%. For mixtures of Lennard-Jones molecules, the model predictions are better than the Weeks-Chandler-Anderson perturbation theory.

Aerospace Materials and Process Technology Reinvestment Workshop Held in Dayton, Ohio on 18-19 May 1993.

DTIC Science & Technology

1993-05-19

The Laboratories Theory, Modeling and Simulation , • ATP Characterization J Education and Human Resources • MTC Facilities -- NBSR and CNRF MISSION...34 Automiated System for Composite Analysis (ASCA).Y -Basis for usefri(eadly numerical methods to describe composite laminates and predict ?heir response

Constitutive Modeling of Nanotube/Polymer Composites with Various Nanotube Orientations

NASA Technical Reports Server (NTRS)

Odegard, Gregory M.; Gates, Thomas S.

2002-01-01

In this study, a technique has been proposed for developing constitutive models for polymer composite systems reinforced with single-walled carbon nanotubes (SWNT) with various orientations with respect to the bulk material coordinates. A nanotube, the local polymer adjacent to the nanotube, and the nanotube/polymer interface have been modeled as an equivalent-continuum fiber by using an equivalent-continuum modeling method. The equivalent-continuum fiber accounts for the local molecular structure and bonding information and serves as a means for incorporating micromechanical analyses for the prediction of bulk mechanical properties of SWNT/polymer composite. As an example, the proposed approach is used for the constitutive modeling of a SWNT/LaRC-SI (with a PmPV interface) composite system, with aligned nanotubes, three-dimensionally randomly oriented nanotubes, and nanotubes oriented with varying degrees of axisymmetry. It is shown that the Young s modulus is highly dependent on the SWNT orientation distribution.

A new aeroelastic model for composite rotor blades with straight and swept tips

NASA Technical Reports Server (NTRS)

Yuan, Kuo-An; Friedmann, Peretz P.; Venkatesan, Comandur

1992-01-01

An analytical model for predicting the aeroelastic behavior of composite rotor blades with straight and swept tips is presented. The blade is modeled by beam type finite elements along the elastic axis. A single finite element is used to model the swept tip. The nonlinear equations of motion for the finite element model are derived using Hamilton's principle and based on a moderate deflection theory and accounts for: arbitrary cross-sectional shape, pretwist, generally anisotropic material behavior, transverse shears and out-of-plane warping. Numerical results illustrating the effects of tip sweep, anhedral and composite ply orientation on blade aeroelastic behavior are presented. Tip sweep can induce aeroelastic instability by flap-twist coupling. Tip anhedral causes lag-torsion and flap-axial couplings, however, its effects on blade stability is less pronounced than the effect due to sweep. Composite ply orientation has a substantial effect on blade stability.

Gaussian processes with optimal kernel construction for neuro-degenerative clinical onset prediction

NASA Astrophysics Data System (ADS)

Canas, Liane S.; Yvernault, Benjamin; Cash, David M.; Molteni, Erika; Veale, Tom; Benzinger, Tammie; Ourselin, Sébastien; Mead, Simon; Modat, Marc

2018-02-01

Gaussian Processes (GP) are a powerful tool to capture the complex time-variations of a dataset. In the context of medical imaging analysis, they allow a robust modelling even in case of highly uncertain or incomplete datasets. Predictions from GP are dependent of the covariance kernel function selected to explain the data variance. To overcome this limitation, we propose a framework to identify the optimal covariance kernel function to model the data.The optimal kernel is defined as a composition of base kernel functions used to identify correlation patterns between data points. Our approach includes a modified version of the Compositional Kernel Learning (CKL) algorithm, in which we score the kernel families using a new energy function that depends both the Bayesian Information Criterion (BIC) and the explained variance score. We applied the proposed framework to model the progression of neurodegenerative diseases over time, in particular the progression of autosomal dominantly-inherited Alzheimer's disease, and use it to predict the time to clinical onset of subjects carrying genetic mutation.

Cost Models for MMC Manufacturing Processes

NASA Technical Reports Server (NTRS)

Elzey, Dana M.; Wadley, Haydn N. G.

1996-01-01

Processes for the manufacture of advanced metal matrix composites are rapidly approaching maturity in the research laboratory and there is growing interest in their transition to industrial production. However, research conducted to date has almost exclusively focused on overcoming the technical barriers to producing high-quality material and little attention has been given to the economical feasibility of these laboratory approaches and process cost issues. A quantitative cost modeling (QCM) approach was developed to address these issues. QCM are cost analysis tools based on predictive process models relating process conditions to the attributes of the final product. An important attribute, of the QCM approach is the ability to predict the sensitivity of material production costs to product quality and to quantitatively explore trade-offs between cost and quality. Applications of the cost models allow more efficient direction of future MMC process technology development and a more accurate assessment of MMC market potential. Cost models were developed for two state-of-the art metal matrix composite (MMC) manufacturing processes: tape casting and plasma spray deposition. Quality and Cost models are presented for both processes and the resulting predicted quality-cost curves are presented and discussed.

Study on effective thermal conductivity of silicone/phosphor composite and its size effect by Lattice Boltzmann method

NASA Astrophysics Data System (ADS)

Li, Lan; Zheng, Huai; Yuan, Chao; Hu, Run; Luo, Xiaobing

2016-12-01

The silicone/phosphor composite is widely used in light emitting diode (LED) packaging. The composite thermal properties, especially the effective thermal conductivity, strongly influence the LED performance. In this paper, a lattice Boltzmann model was presented to predict the silicone/phosphor composite effective thermal conductivity. Based on the present lattice Boltzmann model, a random generation method was established to describe the phosphor particle distribution in composite. Benchmarks were conducted by comparing the simulation results with theoretical solutions for simple cases. Then the model was applied to analyze the effective thermal conductivity of the silicone/phosphor composite and its size effect. The deviations between simulation and experimental results are <7 %, when the phosphor volume fraction varies from 0.038 to 0.45. The simulation results also indicate that effective thermal conductivity of the composite with larger particles is higher than that with small particles at the same volume fraction. While mixing these two sizes of phosphor particles provides an extra enhancement for the effective thermal conductivity.

Using MELTS to understand the evolution of silicic magmas: Challenges and successes in modeling the Highland Range Volcanic Sequence (NV)

NASA Astrophysics Data System (ADS)

Vaum, R. C.; Gualda, G. A.; Ghiorso, M. S.; Miller, C. F.; Colombini, L. L.

2009-12-01

The Highland Range near Searchlight, Nevada is comprised of mid-Miocene, intermediate to silicic volcanic rocks. This study focuses on the most silicic portion of the eruptive sequence (16.0-16.5 Ma). The first eruptions during this interval were effusive and produced trachydacite (66-70 wt% SiO2), but later the eruptive style shifted to explosive and compositions were more evolved (70-78 wt% SiO2). Glass compositions in rocks saturated in both quartz and sanidine align along the 150 MPa quartz+sanidine saturation surface, suggesting that the Highland Range magmas equilibrated in a single reservoir at that pressure. We are interested in better understanding this transition in eruptive style from effusive to eruptive, and our approach is based on modeling melt evolution using MELTS thermodynamic modeling software. We selected representative samples from key stratigraphic units, and focused on samples for which whole-rock and glass compositions, as well as mineral abundances, are available. This allows for direct comparison of simulation results with existing data. Initial simulations showed that MELTS predicts unrealistic paths of evolution when compared to the glass compositions and to the phase relations in the Qz-Ab-Or ternary. In particular, the stability field of quartz predicted by MELTS is much too small, causing melts to become exceedingly silicic (>80 wt% SiO2). Sanidine, on the other hand, has fairly sodic compositions and crystallizes too early in the sequence; therefore, simulated melt compositions are never as potassic as the analyzed glasses. Similar results are obtained when modeling the evolution of the Bishop and Campanian magmas, showing that these are systematic problems in MELTS calibration. Accordingly, we have adjusted the enthalpy of quartz and potassium end-member of the feldspar solid solution in MELTS so that the quartz-sanidine saturation surface is correctly predicted. We find that this modified version of MELTS much better models the evolution of silicic magmas. Sanidine begins to crystallize at lower temperatures, causing evolved melts to become significantly more potassic. Also, MELTS prediction of quartz saturation is in agreement with the position of the experimentally determined 150 MPa quartz+sanidine saturation surface. Importantly, the melt evolution that this modified version of MELTS predicts is very consistent with whole-rock data, glass chemistry, and mineral abundances in samples from the Highland Range. Simulations using the modified version of MELTS show that it works remarkably well, at least for relatively low degrees of crystallization. But a more reliable model to simulate the evolution of silicic magmas is necessary to more properly simulate the evolution of silicic systems, in particular at high degrees of crystallinity. We are currently working to create gMELTS, an associated solution model of the haplogranitic system, which, once completed, will be optimized to simulate the evolution of silicic systems.

Radial Mixing and Ru-Mo Isotope Systematics Under Different Accretion Scenarios

NASA Astrophysics Data System (ADS)

Fischer, R. A.; Nimmo, F.; O'Brien, D. P.

2017-12-01

The Ru-Mo isotopic compositions of inner Solar System bodies may reflect the provenance of accreted material and how it evolved with time, both of which are controlled by the accretion scenario these bodies experienced. Here we use a total of 116 N-body simulations of terrestrial planet accretion, run in the Eccentric Jupiter and Saturn (EJS), Circular Jupiter and Saturn (CJS), and Grand Tack scenarios, to model the Ru-Mo anomalies of Earth, Mars, and Theia analogues. This model starts by applying an initial step function in Ru-Mo isotopic composition, with compositions reflecting those in meteorites, and traces compositional evolution as planets accrete. The mass-weighted provenance of the resulting planets reveals more radial mixing in Grand Tack simulations than in EJS/CJS simulations, and more efficient mixing among late-accreted material than during the main phase of accretion in EJS/CJS simulations. We find that an extensive homogenous inner disk region is required to reproduce Earth's observed Ru-Mo composition. EJS/CJS simulations require a homogeneous reservoir in the inner disk extending to ≥3-4 AU (≥74-98% of initial mass) to reproduce Earth's composition, while Grand Tack simulations require a homogeneous reservoir extending to ≥3-10 AU (≥97-99% of initial mass), and likely to ≥7-10 AU. In the Grand Tack model, Jupiter's initial location (the most likely location for a discontinuity in isotopic composition) is 3.5 AU; however, this step location has only a 33% likelihood of producing an Earth with the correct Ru-Mo isotopic signature for the most plausible model conditions. Our results give the testable predictions that Mars has zero Ru anomaly and small or zero Mo anomaly, and the Moon has zero Mo anomaly. These predictions are insensitive to wide variations in parameter choices.

Noise reduction of a composite cylinder subjected to random acoustic excitation

NASA Technical Reports Server (NTRS)

Grosveld, Ferdinand W.; Beyer, T.

1989-01-01

Interior and exterior noise measurements were conducted on a stiffened composite floor-equipped cylinder, with and without an interior trim installed. Noise reduction was obtained for the case of random acoustic excitation in a diffuse field; the frequency range of interest was 100-800-Hz one-third octave bands. The measured data were compared with noise reduction predictions from the Propeller Aircraft Interior Noise (PAIN) program and from a statistical energy analysis. Structural model parameters were not predicted well by the PAIN program for the given input parameters; this resulted in incorrect noise reduction predictions for the lower one-third octave bands where the power flow into the interior of the cylinder was predicted on a mode-per-mode basis.

Simulation of Degraded Properties of 2D plain Woven C/SiC Composites under Preloading Oxidation Atmosphere

NASA Astrophysics Data System (ADS)

Chen, Xihui; Sun, Zhigang; Sun, Jianfen; Song, Yingdong

2017-12-01

In this paper, a numerical model which incorporates the oxidation damage model and the finite element model of 2D plain woven composites is presented for simulation of the oxidation behaviors of 2D plain woven C/SiC composite under preloading oxidation atmosphere. The equal proportional reduction method is firstly proposed to calculate the residual moduli and strength of unidirectional C/SiC composite. The multi-scale method is developed to simulate the residual elastic moduli and strength of 2D plain woven C/SiC composite. The multi-scale method is able to accurately predict the residual elastic modulus and strength of the composite. Besides, the simulated residual elastic moduli and strength of 2D plain woven C/SiC composites under preloading oxidation atmosphere show good agreements with experimental results. Furthermore, the preload, oxidation time, temperature and fiber volume fractions of the composite are investigated to show their influences upon the residual elastic modulus and strength of 2D plain woven C/SiC composites.

A Thermodynamic Model to Estimate the Formation of Complex Nitrides of Al x Mg(1- x)N in Silicon Steel

NASA Astrophysics Data System (ADS)

Luo, Yan; Zhang, Lifeng; Li, Ming; Sridhar, Seetharaman

2018-06-01

A complex nitride of Al x Mg(1- x)N was observed in silicon steels. A thermodynamic model was developed to predict the ferrite/nitride equilibrium in the Fe-Al-Mg-N alloy system, using published binary solubility products for stoichiometric phases. The model was used to estimate the solubility product of nitride compound, equilibrium ferrite, and nitride compositions, and the amounts of each phase, as a function of steel composition and temperature. In the current model, the molar ratio Al/(Al + Mg) in the complex nitride was great due to the low dissolved magnesium in steel. For a steel containing 0.52 wt pct Als, 10 ppm T.Mg., and 20 ppm T.N. at 1100 K (827 °C), the complex nitride was expressed by Al0.99496Mg0.00504N and the solubility product of this complex nitride was 2.95 × 10-7. In addition, the solution temperature of the complex nitride increased with increasing the nitrogen and aluminum in steel. The good agreement between the prediction and the detected precipitate compositions validated the current model.

Compositional control of continuously graded anode functional layer

NASA Astrophysics Data System (ADS)

McCoppin, J.; Barney, I.; Mukhopadhyay, S.; Miller, R.; Reitz, T.; Young, D.

2012-10-01

In this work, solid oxide fuel cells (SOFC's) are fabricated with linear-compositionally graded anode functional layers (CGAFL) using a computer-controlled compound aerosol deposition (CCAD) system. Cells with different CGAFL thicknesses (30 um and 50 um) are prepared with a continuous compositionally graded interface deposited between the electrolyte and anode support current collecting regions. The compositional profile was characterized using energy dispersive X-ray spectroscopic mapping. An analytical model of the compound aerosol deposition was developed. The model predicted compositional profiles for both samples that closely matched the measured profiles, suggesting that aerosol-based deposition methods are capable of creating functional gradation on length scales suitable for solid oxide fuel cell structures. The electrochemical performances of the two cells are analyzed using electrochemical impedance spectroscopy (EIS).

A higher-order theory for geometrically nonlinear analysis of composite laminates

NASA Technical Reports Server (NTRS)

Reddy, J. N.; Liu, C. F.

1987-01-01

A third-order shear deformation theory of laminated composite plates and shells is developed, the Navier solutions are derived, and its finite element models are developed. The theory allows parabolic description of the transverse shear stresses, and therefore the shear correction factors of the usual shear deformation theory are not required in the present theory. The theory also accounts for the von Karman nonlinear strains. Closed-form solutions of the theory for rectangular cross-ply and angle-ply plates and cross-ply shells are developed. The finite element model is based on independent approximations of the displacements and bending moments (i.e., mixed finite element model), and therefore, only C sup o -approximation is required. The finite element model is used to analyze cross-ply and angle-ply laminated plates and shells for bending and natural vibration. Many of the numerical results presented here should serve as references for future investigations. Three major conclusions resulted from the research: First, for thick laminates, shear deformation theories predict deflections, stresses and vibration frequencies significantly different from those predicted by classical theories. Second, even for thin laminates, shear deformation effects are significant in dynamic and geometrically nonlinear analyses. Third, the present third-order theory is more accurate compared to the classical and firt-order theories in predicting static and dynamic response of laminated plates and shells made of high-modulus composite materials.

Constitutive Behavior and Finite Element Analysis of FRP Composite and Concrete Members.

PubMed

Ann, Ki Yong; Cho, Chang-Geun

2013-09-10

The present study concerns compressive and flexural constitutive models incorporated into an isoparametric beam finite element scheme for fiber reinforced polymer (FRP) and concrete composites, using their multi-axial constitutive behavior. The constitutive behavior of concrete was treated in triaxial stress states as an orthotropic hypoelasticity-based formulation to determine the confinement effect of concrete from a three-dimensional failure surface in triaxial stress states. The constitutive behavior of the FRP composite was formulated from the two-dimensional classical lamination theory. To predict the flexural behavior of circular cross-section with FRP sheet and concrete composite, a layered discretization of cross-sections was incorporated into nonlinear isoparametric beam finite elements. The predicted constitutive behavior was validated by a comparison to available experimental results in the compressive and flexural beam loading test.

Modeling of Melt-Infiltrated SiC/SiC Composite Properties

NASA Technical Reports Server (NTRS)

Mital, Subodh K.; Bednarcyk, Brett A.; Arnold, Steven M.; Lang, Jerry

2009-01-01

The elastic properties of a two-dimensional five-harness melt-infiltrated silicon carbide fiber reinforced silicon carbide matrix (MI SiC/SiC) ceramic matrix composite (CMC) were predicted using several methods. Methods used in this analysis are multiscale laminate analysis, micromechanics-based woven composite analysis, a hybrid woven composite analysis, and two- and three-dimensional finite element analyses. The elastic properties predicted are in good agreement with each other as well as with the available measured data. However, the various methods differ from each other in three key areas: (1) the fidelity provided, (2) the efforts required for input data preparation, and (3) the computational resources required. Results also indicate that efficient methods are also able to provide a reasonable estimate of local stress fields.

A physically-based continuum damage mechanics model for numerical prediction of damage growth in laminated composite plates

NASA Astrophysics Data System (ADS)

Williams, Kevin Vaughan

Rapid growth in use of composite materials in structural applications drives the need for a more detailed understanding of damage tolerant and damage resistant design. Current analytical techniques provide sufficient understanding and predictive capabilities for application in preliminary design, but current numerical models applicable to composites are few and far between and their development into well tested, rigorous material models is currently one of the most challenging fields in composite materials. The present work focuses on the development, implementation, and verification of a plane-stress continuum damage mechanics based model for composite materials. A physical treatment of damage growth based on the extensive body of experimental literature on the subject is combined with the mathematical rigour of a continuum damage mechanics description to form the foundation of the model. The model has been implemented in the LS-DYNA3D commercial finite element hydrocode and the results of the application of the model are shown to be physically meaningful and accurate. Furthermore it is demonstrated that the material characterization parameters can be extracted from the results of standard test methodologies for which a large body of published data already exists for many materials. Two case studies are undertaken to verify the model by comparison with measured experimental data. The first series of analyses demonstrate the ability of the model to predict the extent and growth of damage in T800/3900-2 carbon fibre reinforced polymer (CFRP) plates subjected to normal impacts over a range of impact energy levels. The predicted force-time and force-displacement response of the panels compare well with experimental measurements. The damage growth and stiffness reduction properties of the T800/3900-2 CFRP are derived using published data from a variety of sources without the need for parametric studies. To further demonstrate the physical nature of the model, a IM6/937 CFRP with a more brittle matrix system than 3900-2 is also analysed. Results of analyses performed under the same impact conditions do not compare as well quantitatively with measurements but the results are still promising and qualitative differences between the T800/3900-2 and IM6/937 are accurately captured. Finally, to further demonstrate the capability of the model, the response of a notched CFRP plate under quasi-static tensile loading is simulated and compared to experimental measurements. Of particular significance is the fact that the experimental test modelled in this case is uniquely suited to the characterization of the strain softening phenomenon observed in FRP laminates. Results of this virtual experiment compare very favourably with the measured damage growth and force-displacement curves.

Influence of fiber architecture on the elastic an d inelastic response of metal matrix composites

NASA Technical Reports Server (NTRS)

Arnold, Steven M.; Pindera, Marek-Jerzy; Wilt, Thomas E.

1995-01-01

This three part paper focuses on the effect of fiber architecture (i.e., shape and distribution) on the elastic and inelastic response of metal matrix composites. The first part provides an annotative survey of the literature, presented as a historical perspective, dealing with the effects of fiber shape and distribution on the response of advanced polymeric matrix and metal matrix composites. Previous investigations dealing with both continuously and discontinuously reinforced composites are included. A summary of the state-of-the-art will assist in defining new directions in this quickly reviving area of research. The second part outlines a recently developed analytical micromechanics model that is particularly well suited for studying the influence of these effects on the response of metal matrix composites. This micromechanics model, referred to as the generalized method of cells (GMC), is capable of predicting the overall, inelastic behavior of unidirectional, multi-phased composites given the properties of the constituents. In particular, the model is sufficiently general to predict the response of unidirectional composites reinforced by either continuous or discontinuous fibers with different inclusion shapes and spatial arrangements in the presence of either perfect or imperfect interfaces and/or interfacial layers. Recent developments regarding this promising model, as well as directions for future enhancements of the model's predictive capability, are included. Finally, the third pan provides qualitative results generated using GMC for a representative titanium matix composite system, SCS-6/TlMETAL 21S. Results are presented that correctly demonstrate the relative effects of fiber arrangement and shape on the longitudinal and transverse stress-strain and creep response, with both strong and weak fiber/matrix interfacial bonds. The fiber arrangements include square, square diagonal, hexagonal and rectangular periodic arrays, as well as a random array. The fiber shapes include circular, square and cross-shaped cross sections. The effect of fiber volume fraction on the observed stress-strain response is also discussed, as the thus-far poorly documented strain rate sensitivity effect. In addition to the well documented features of architecture dependent response of continuously reinforced two-phase MMC's, new results involving continuous multi-phase internal architectures are presented. Specifically, stress strain and creep response of composites with different size fibers having different internal arrangements and bond strengths are investigated with the aim of determining the feasibility of using this approach to enhance the transverse toughness and creep resistance of TMC's.

Trace Elements in Basalts From the Siqueiros Fracture Zone: Implications for Melt Migration Models

NASA Astrophysics Data System (ADS)

Pickle, R. C.; Forsyth, D. W.; Saal, A. E.; Nagle, A. N.; Perfit, M. R.

2008-12-01

Incompatible trace element (ITE) ratios in MORB from a variety of locations may provide insights into the melt migration process by constraining aggregated melt compositions predicted by mantle melting and flow models. By using actual plate geometries to create a 3-D thermodynamic mantle model, melt volumes and compositions at all depths and locations may be calculated and binned into cubes using the pHMELTS algorithm [Asimow et al., 2004]. These melts can be traced from each cube to the surface assuming several migration models, including a simplified pressure gradient model and one in which melt is guided upwards by a low permeability compacted layer. The ITE ratios of all melts arriving at the surface are summed, averaged, and compared to those of the actual sample compositions from the various MOR locales. The Siqueiros fracture zone at 8° 20' N on the East Pacific Rise (EPR) comprises 4 intra-transform spreading centers (ITSCs) across 140 km of offset between two longer spreading ridges, and is an excellent study region for several reasons. First, an abundance of MORB data is readily available, and the samples retrieved from ITSCs are unlikely to be aggregated in a long-lived magma chamber or affected by along-axis transport, so they represent melts extracted locally from the mantle. Additionally, samples at Siqueiros span a compositional range from depleted to normal MORB within the fracture zone yet have similar isotopic compositions to samples collected from the 9-10° EPR. This minimizes the effect of assuming a uniform source composition in our melting model despite a heterogeneous mantle, allowing us to consistently compare the actual lava composition with that predicted by our model. Finally, it has been demonstrated with preliminary migration models that incipient melts generated directly below an ITSC may not necessarily erupt at that ITSC but migrate laterally towards a nearby ridge due to enhanced pressure gradients. The close proximity of the ITSCs at Siqueiros to the large ridges bounding the fracture zone provide a good opportunity to model this phenomenon and may help explain the variable ITE ratios found between samples collected within the transform and those near the ridges.

Thermal conductivity of the sideledge in aluminium electrolysis cells: Experiments and numerical modelling

NASA Astrophysics Data System (ADS)

Gheribi, Aïmen E.; Poncsák, Sándor; Guérard, Sébastien; Bilodeau, Jean-François; Kiss, László; Chartrand, Patrice

2017-03-01

During aluminium electrolysis, a ledge of frozen electrolytes is generally formed, attached to the sides of the cells. This ledge acts as a protective layer, preventing erosion and chemical attacks of both the electrolyte melt and the liquid aluminium on the side wall materials. The control of the sideledge thickness is thus essential in ensuring a reasonable lifetime for the cells. The key property for modelling and predicting the sideledge thickness as a function of temperature and electrolyte composition is the thermal conductivity. Unfortunately, almost no data is available on the thermal conductivity of the sideledge. The aim of this work is to alleviate this lack of data. For seven different samples of sideledge microstructures, recovered from post-mortem industrial electrolysis cells, the thermal diffusivity, the density, and the phase compositions were measured in the temperature range of 423 K to 873 K. The thermal diffusivity was measured with a laser flash technique and the average phase compositions by X-ray diffraction analysis. The thermal conductivity of the sideledge is deduced from the present experimental thermal diffusivity and density, and the thermodynamically assessed heat capacity. In addition to the present experimental work, a theoretical model for the prediction of the effective thermal transport properties of the sideledge microstructure is also proposed. The proposed model considers an equivalent microstructure and depends on phase fractions, porosity, and temperature. The strength of the model lies in the fact that only a few key physical properties are required for its parametrization and they can be predicted with a good accuracy via first principles calculations. It is shown that the theoretical predictions are in a good agreement with the present experimental measurements.

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

PubMed

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

2015-05-01

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

Consumer product chemical weight fractions from ingredient lists.

PubMed

Isaacs, Kristin K; Phillips, Katherine A; Biryol, Derya; Dionisio, Kathie L; Price, Paul S

2018-05-01

Assessing human exposures to chemicals in consumer products requires composition information. However, comprehensive composition data for products in commerce are not generally available. Many consumer products have reported ingredient lists that are constructed using specific guidelines. A probabilistic model was developed to estimate quantitative weight fraction (WF) values that are consistent with the rank of an ingredient in the list, the number of reported ingredients, and labeling rules. The model provides the mean, median, and 95% upper and lower confidence limit WFs for ingredients of any rank in lists of any length. WFs predicted by the model compared favorably with those reported on Material Safety Data Sheets. Predictions for chemicals known to provide specific functions in products were also found to reasonably agree with reported WFs. The model was applied to a selection of publicly available ingredient lists, thereby estimating WFs for 1293 unique ingredients in 1123 products in 81 product categories. Predicted WFs, although less precise than reported values, can be estimated for large numbers of product-chemical combinations and thus provide a useful source of data for high-throughput or screening-level exposure assessments.