Correlation of creep rate with microstructural changes during high temperature creep

Creep tests were conducted on Haynes 188 cobalt-base alloy and alpha titanium. The tests on Haynes 188 were conducted at 1600 F and 1800 F for stresses from 3 to 20 ksi, and the as-received, mill-annealed results were compared to specimens given 5%, 10%, and 15% room temperature prestrains and then annealed one hour at 1800 F. The tests on alpha titanium were performed at 7,250 and 10,000 psi at 500 C. One creep test was done at 527 C and 10,000 psi to provide information on kinetics. Results for annealed titanium were compared to specimens given 10% and 20% room temperature prestrains followed by 100 hours recovery at 550 C. Electron microscopy was used to relate dislocation and precipitate structure to the creep behavior of the two materials. The results on Haynes 188 alloy reveal that the time to reach 0.5% creep strain at 1600 F increases with increasing prestrain for exposure times less than 1,000 hours, the increase at 15% prestrain being more than a factor of ten

Variation in Establishment Success for American Mistletoe [\u3ci\u3ePhoradendron leucarpum\u3c/i\u3e (Raf.) Reveal & M.C. Johnst. (Viscaceae)] Appears Most Likely to Predict its Distribution in Virginia and North Carolina, United States

Dispersal limitation and variation in habitat suitability may determine an association of American mistletoe [Phoradendron leucarpum (Raf.) Reveal & M.C. Johnst. (Viscaceae)] with forested wetlands in Virginia and North Carolina, United States. Here, we first tested the alternative hypothesis that variation in host availability drives this habitat relationship. We used a generalized linear model to show a positive effect of forested wetland habitat on American mistletoe occurrence after accounting for both variation in host availability and differences among regions in host use. We then used seed sowing experiments to quantify how light availability and flood regime determine the viability of American mistletoe, allowing us to evaluate the potential for establishment limitation to determine this habitat relationship. Light availability predicted establishment rates but % canopy openness did not predict seed germination rates. Thus, variation in the ability for American mistletoe to establish across forested habitat types with different local light availabilities is a potentially important mechanism in determining its distribution

Synaptic Scaling Balances Learning in a Spiking Model of Neocortex

Learning in the brain requires complementary mechanisms: potentiation and activity-dependent homeostatic scaling. We introduce synaptic scaling to a biologically-realistic spiking model of neocortex which can learn changes in oscillatory rhythms using STDP, and show that scaling is necessary to balance both positive and negative changes in input from potentiation and atrophy. We discuss some of the issues that arise when considering synaptic scaling in such a model, and show that scaling regulates activity whilst allowing learning to remain unaltered.Comment: 10 page

Modeling Stress-Dependent Anisotropic Elastoplastic Unbound Granular Base in Flexible Pavements

Unbound granular base (UGB) has a cross-anisotropic and nonlinear (stress-dependent) modulus with a plastic behavior. Existing UGB models address nonlinear cross-anisotropy and plasticity separately. It is unknown how the two characteristics are coupled into a finite element model (FEM) and how this will affect the pavement responses. This study presents a coupled nonlinear cross-anisotropic elastoplastic (NAEP) constitutive model for the UGB and implements it in a weak form equation-based FEM. No material subroutine is needed to address the circular dependence between the stress-dependent anisotropic modulus, structural stress responses, and elastoplastic deformation. The NAEP model was calibrated by triaxial resilient modulus and strength tests and validated using laboratory measurements in a large-scale soil-tank pavement structural test. It is found that the NAEP model is valid and effective in predicting the UGB responses in flexible pavements. The model predicted less horizontal tensile stresses at the base bottom and introduced compressive stresses in the middle and top of the base course. This is caused by an increasing confinement resulting from a horizontal plastic dilation in the base course, which cannot be modeled without considering plasticity. The stress-dependent modulus for the UGB material decreases with depth and the distance from loading centerline. Compared with a nonlinear anisotropic elastic model, the NAEP model predicted the same tensile strain at asphalt layer bottom, a higher base modulus, and a higher subgrade compressive strain. Thus, the nonlinear anisotropic elastic UGB model results in the same fatigue life as the NAEP model but may riskily under-predict rutting damage

Using NEURON for Reaction-Diffusion Modeling of Extracellular Dynamics

Development of credible clinically-relevant brain simulations has been slowed due to a focus on electrophysiology in computational neuroscience, neglecting the multiscale whole-tissue modeling approach used for simulation in most other organ systems. We have now begun to extend the NEURON simulation platform in this direction by adding extracellular modeling. The extracellular medium of neural tissue is an active medium of neuromodulators, ions, inflammatory cells, oxygen, NO and other gases, with additional physiological, pharmacological and pathological agents. These extracellular agents influence, and are influenced by, cellular electrophysiology, and cellular chemophysiology—the complex internal cellular milieu of second-messenger signaling and cascades. NEURON's extracellular reaction-diffusion is supported by an intuitive Python-based where/who/what command sequence, derived from that used for intracellular reaction diffusion, to support coarse-grained macroscopic extracellular models. This simulation specification separates the expression of the conceptual model and parameters from the underlying numerical methods. In the volume-averaging approach used, the macroscopic model of tissue is characterized by free volume fraction—the proportion of space in which species are able to diffuse, and tortuosity—the average increase in path length due to obstacles. These tissue characteristics can be defined within particular spatial regions, enabling the modeler to account for regional differences, due either to intrinsic organization, particularly gray vs. white matter, or to pathology such as edema. We illustrate simulation development using spreading depression, a pathological phenomenon thought to play roles in migraine, epilepsy and stroke. Simulation results were verified against analytic results and against the extracellular portion of the simulation run under FiPy. The creation of this NEURON interface provides a pathway for interoperability that can be used to automatically export this class of models into complex intracellular/extracellular simulations and future cross-simulator standardization

Characteristics of damaged asphalt mixtures in tension and compression

This paper addresses the measurement and modelling of the damaged properties of asphalt mixtures including the fracture, healing and viscoplastic deformation of the asphalt mixtures in both tensile and compressive loading as being affected by their composition and conditioning with ageing and exposure to temperature and moisture. An energy-based mechanics is applied to obtain the material fundamental properties such as surface energies, bond energies, anisotropy, yield functions and plastic potential functions that are valid for actual asphalt mixtures, viscoelastic crack growth criteria under both tensile and compressive loading, a simple mechanics-based method of determining the fatigue endurance limit, and the measurement and prediction of healing in restoring the damage done by fracture. Healing is anti-fracture and cracking is the net result of the interplay of these two complimentary mechanisms. Because fracture in asphalt mixtures is not the growth of a single crack but the simultaneous growth of multiple cracks that start out as air voids, this fact leads to the use of the growth of damage density to characterise fracture in an asphalt mixture. It was discovered that the form of Paris’ law applies to the growth of damage density of asphalt mixtures in both tensile and compressive loadings. The importance of this fact lies in many developments from this discovery, e.g. compressive monotonic loading of cylindrical test samples permits a direct determination of the Paris’ Law coefficient and exponent. In all cases, measured material properties are presented as they vary with mixture composition and with conditioning such as moisture and ageing, both in the lab and in the field. The measurements of these properties are made simply, quickly and accurately by the use of mechanics so that an entire characterisation of the properties of an asphalt mixture in tension and compression can be completed in the space of one day. The net effect is to reduce the efforts expended in the lab and the systematic error due to the assumptions made by the existing models and simultaneously to increase the efficiency and cost-effectiveness of materials testing and raise the reliability of the design of mixtures, pavement structures and specifications and the prediction of the life cycles in as-built pavements

Viscoelasticplastic-Fracture modeling of asphalt mixtures under monotonic and repeated loads

Rutting and cracking occur simultaneously in asphalt mixtures as observed in the field and in the laboratory. Existing mechanical models have not properly addressed viscoelastic and viscoplastic deformation together with cracking attributable to model deficiencies, parameter calibration, and numerical inefficiency. This study developed viscoelasticplastic-fracture (VEPF) models for the characterization of viscoelasticity by Prony model and viscoplasticity by Perzyna's flow rule with a generalized Drucker-Prager yield surface and a nonassociated plastic potential. Viscofracture damage was modeled by a viscoelastic Griffith criterion and a pseudo J-integral Paris's law for crack initiation and propagation, respectively. The VEPF models were implemented in a finite element program by using a weak form partial differential equation modeling technique without the need for programming user-defined material subroutines. Model parameters were derived from fundamental material properties by using dynamic modulus, strength, and repeated load tests. Simulations indicated that the viscoelastic-viscoplastic-viscofracture characteristics were effectively modeled by the VEPF models for asphalt mixtures at different confinements and temperatures. An asphalt mixture under monotonic compressive loads exhibited a sequenced process including a pure viscoelastic deformation stage, a coupled viscoelastic-viscoplastic deformation stage, a viscoelastic-viscoplastic deformation coupled with a viscofracture initiation and a propagation stage, and then a viscoelastic-viscofracture rupture stage with saturated viscoplastic deformation. The asphalt mixture under repeated loads yielded an increasing viscoplastic strain at an increasing rate during the first half of the haversine load, while the increment of the viscoplastic strain (per load cycle) decreased with load cycles. The finite element program, which is based on a partial differential equation, effectively modeled the coupled viscoelastic-viscoplastic-viscofracture behaviors of the asphalt mixtures

An associative memory of Hodgkin-Huxley neuron networks with Willshaw-type synaptic couplings

An associative memory has been discussed of neural networks consisting of spiking N (=100) Hodgkin-Huxley (HH) neurons with time-delayed couplings, which memorize P patterns in their synaptic weights. In addition to excitatory synapses whose strengths are modified after the Willshaw-type learning rule with the 0/1 code for quiescent/active states, the network includes uniform inhibitory synapses which are introduced to reduce cross-talk noises. Our simulations of the HH neuron network for the noise-free state have shown to yield a fairly good performance with the storage capacity of $\alpha_c = P_{\rm max}/N \sim 0.4 - 2.4$ for the low neuron activity of $f \sim 0.04-0.10$. This storage capacity of our temporal-code network is comparable to that of the rate-code model with the Willshaw-type synapses. Our HH neuron network is realized not to be vulnerable to the distribution of time delays in couplings. The variability of interspace interval (ISI) of output spike trains in the process of retrieving stored patterns is also discussed.Comment: 15 pages, 3 figures, changed Titl

NetPyNE, a tool for data-driven multiscale modeling of brain circuits

Biophysical modeling of neuronal networks helps to integrate and interpret rapidly growing and disparate experimental datasets at multiple scales. The NetPyNE tool (www.netpyne.org) provides both programmatic and graphical interfaces to develop data-driven multiscale network models in NEURON. NetPyNE clearly separates model parameters from implementation code. Users provide specifications at a high level via a standardized declarative language, for example connectivity rules, to create millions of cell-to-cell connections. NetPyNE then enables users to generate the NEURON network, run efficiently parallelized simulations, optimize and explore network parameters through automated batch runs, and use built-in functions for visualization and analysis – connectivity matrices, voltage traces, spike raster plots, local field potentials, and information theoretic measures. NetPyNE also facilitates model sharing by exporting and importing standardized formats (NeuroML and SONATA). NetPyNE is already being used to teach computational neuroscience students and by modelers to investigate brain regions and phenomena

Surface Science of DNA Adsorption onto Citrate-Capped Gold Nanoparticles

This document is the Accepted Manuscript version of a Published Work that appeared in final form in Langmuir copyright © American Chemical Society after peer review and technical editing by publisher. To access the final edited and published work see Zhang, X., Servos, M. R., & Liu, J. (2012). Surface Science of DNA Adsorption onto Citrate-Capped Gold Nanoparticles. Langmuir, 28(8), 3896–3902. https://doi.org/10.1021/la205036pSingle-stranded DNA can be adsorbed by citrate capped gold nanoparticles (AuNPs), resulting in increased AuNP stability, which forms the basis of a number of biochemical and analytical applications, but the fundamental interaction of this adsorption reaction remains unclear. In this study, we measured DNA adsorption kinetics, capacity, and isotherms, demonstrating that the adsorption process is governed by electrostatic forces. The charge repulsion among DNA strands and between DNA and AuNPs can be reduced by adding salt, reducing pH or by using noncharged peptide nucleic acid (PNA). Langmuir adsorption isotherms are obtained, indicating the presence of both adsorption and desorption of DNA from AuNPs. While increasing salt concentration facilitates DNA adsorption, the desorption rate is also enhanced in higher salt due to DNA compaction. DNA adsorption capacity is determined by DNA oligomer length, DNA concentration, and salt. Previous studies indicated faster adsorption of short DNA oligomers by AuNPs, we find that once adsorbed, longer DNAs are much more effective in protecting AuNPs from aggregation. DNA adsorption is also facilitated by using low pH buffers and high alcohol concentrations. A model based on electrostatic repulsion on AuNPs is proposed to rationalize the DNA adsorption/desorption behavior.University of Waterloo || Canadian Foundation for Innovation || Ontario Ministry of Research & Innovation || Canadian Institutes of Health Research || Natural Sciences and Engineering Research Council |