Thermal degradation kinetics of poly(trimethylol propane triacrylate)/poly(hexane diol diacrylate) interpenetrating polymer network

Interpenetrating polymer networks (IPNs) of trimethylol propane triacrylate (TMPTA) and 1,6-hexane diol diacrylate (HDDA) at different weight ratios were synthesized. Temperature modulated differential scanning calorimetry (TMDSC) was used to determine whether the formation resulted in a copolymer or interpenetrating polymer network (IPN). These polymers are used as binders for microstereolithography (MSL) based ceramic microfabrication. The kinetics of thermal degradation of these polymers are important to optimize the debinding process for fabricating 3D shaped ceramic objects by MSL based rapid prototyping technique. Therefore, thermal and thermo-oxidative degradation of these IPNs have been studied by dynamic and isothermal thermogravimetry (TGA). Non-isothermal model-free kinetic methods have been adopted (isoconversional differential and KAS) to calculate the apparent activation energy (E a) as a function of conversion (α) in N 2 and air. The degradation of these polymers in N 2 atmosphere occurs via two mechanisms. Chain end scission plays a dominant role at lower temperature while the kinetics is governed by random chain scission at higher temperature. Oxidative degradation shows multiple degradation steps having higher activation energy than in N 2. Isothermal degradation was also carried out to predict the reaction model which is found to be decelerating. It was shown that the degradation of PTMPTA follows a contracting sphere reaction model in N 2. However, as the HDDA content increases in the IPNs, the degradation reaction follows Avrami-Erofeev model and diffusion governed mechanisms. The intermediate IPN compositions show both type of mechanism. Based on the above study, debinding strategy for MSL based microfabricated ceramic structure has been proposed. © 2012 Elsevier B.V.

Effect of side confining walls on the growth rate of compressible mixing layers

Model free simulations are performed to study the effect of the presence of side wall in compressible mixing of two parallel dissimilar gaseous streams with significant temperature difference. The turbulence statistics shows the three dimensional nature of the flow with and without the presence of side walls. The presence of side wall neither makes the flow field two dimensional, nor suppresses three dimensional disturbances. However, the comparison of shear layer growth rate and wall pressures reveal a better match with the two dimensional simulation results. This better match is explained on the basis of formation of oblique structures due to the presence of side walls which also suppress the distribution of momentum in third direction making the pressures to be higher as compared with the case without side walls. (C) 2013 Elsevier Ltd. All rights reserved.

Exploration of supersonic confined mixing layer: Effect of dissimilar gases at different temperatures

The growth rate of high-speed mixing layer between two dissimilar gases is explored through the model free simulation results. To analyse the cause for the higher mixing layer growth rate in comparison to the existing values reported in literature, the results were compared with the model free simulations of mixing of two high-speed streams of nitrogen (similar gas) at matched temperature and density. The analysis indicates that pressure and density fluctuations no longer remain correlated completely for the mixing layer formed between two dissimilar gases at different temperatures in contrast to the complete pressure density correlation for similar gases. It has been observed that the correlation between temperature and density fluctuations is near -1.0 for dissimilar gases in the mixing layer region and is much higher than for similar gases. It is concluded that mixing layer of similar gases shows a decrease in growth rate due to compressibility effect, while that of dissimilar gases shows a decrease due to dominant temperature effect on density.

Behaviour of turbulent Prandtl/Schmidt number in compressible mixing layer

The behaviour of turbulent Prandtl/Schmidt number is explored through the model-free simulation results. It has been observed that compressibility affects the Reynolds scalar flux vectors. Reduced peak values are also observed for compressible convective Mach number mixing layer as compared with the incompressible convective Mach number counterpart, indicating a reduction in the mixing of enthalpy and species. Pr-t and Sc-t variations also indicate a reduction in mixing. It is observed that unlike the incompressible case, it is difficult to assign a constant value to these numbers due to their continuous variation in space. Modelling of Pr-t and Sc-t would be necessary to cater for this continuous spatial variation. However, the turbulent Lewis number is evaluated to be near unity for the compressible case, making it necessary to model only one of the Pr-t and Sc-t..

Formation Mechanism Of Lamellar Chips During Machining Of Bulk Metallic Glass

The uniqThe unique lamellar chips formed in turning–machining of a Vit 1 bulk metallic glass (BMG) are found to be due to repeated shearband formation in the primary shear zone (PSZ). A coupled thermomechanical orthogonal cutting model, taking into account force, free volume and energy balance in the PSZ, is developed to quantitatively characterize lamellar chip formation. Its onset criterion is revealed through a linear perturbation analysis. Lamellar chip formation is understood as a self-sustained limit-cycle phenomenon: there is autonomous feedback in stress, free volume and temperature in the PSZ. The underlying mechanism is the symmetry breaking of free volume flow and source, rather than thermal instability. These results are fundamentally useful for machining BMGs and even for understanding the physical nature of inhomogeneous flow in BMGs.ue lamellar chips formed in turning–machining of a Vit 1 bulk metallic glass (BMG) are found to be due to repeated shearband.

Neural and computational representations of decision variables

These studies explore how, where, and when representations of variables critical to decision-making are represented in the brain. In order to produce a decision, humans must first determine the relevant stimuli, actions, and possible outcomes before applying an algorithm that will select an action from those available. When choosing amongst alternative stimuli, the framework of value-based decision-making proposes that values are assigned to the stimuli and that these values are then compared in an abstract “value space” in order to produce a decision. Despite much progress, in particular regarding the pinpointing of ventromedial prefrontal cortex (vmPFC) as a region that encodes the value, many basic questions remain. In Chapter 2, I show that distributed BOLD signaling in vmPFC represents the value of stimuli under consideration in a manner that is independent of the type of stimulus it is. Thus the open question of whether value is represented in abstraction, a key tenet of value-based decision-making, is confirmed. However, I also show that stimulus-dependent value representations are also present in the brain during decision-making and suggest a potential neural pathway for stimulus-to-value transformations that integrates these two results.

More broadly speaking, there is both neural and behavioral evidence that two distinct control systems are at work during action selection. These two systems compose the “goal-directed system”, which selects actions based on an internal model of the environment, and the “habitual” system, which generates responses based on antecedent stimuli only. Computational characterizations of these two systems imply that they have different informational requirements in terms of input stimuli, actions, and possible outcomes. Associative learning theory predicts that the habitual system should utilize stimulus and action information only, while goal-directed behavior requires that outcomes as well as stimuli and actions be processed. In Chapter 3, I test whether areas of the brain hypothesized to be involved in habitual versus goal-directed control represent the corresponding theorized variables.

The question of whether one or both of these neural systems drives Pavlovian conditioning is less well-studied. Chapter 4 describes an experiment in which subjects were scanned while engaged in a Pavlovian task with a simple non-trivial structure. After comparing a variety of model-based and model-free learning algorithms (thought to underpin goal-directed and habitual decision-making, respectively), it was found that subjects’ reaction times were better explained by a model-based system. In addition, neural signaling of precision, a variable based on a representation of a world model, was found in the amygdala. These data indicate that the influence of model-based representations of the environment can extend even to the most basic learning processes.

Knowledge of the state of hidden variables in an environment is required for optimal inference regarding the abstract decision structure of a given environment and therefore can be crucial to decision-making in a wide range of situations. Inferring the state of an abstract variable requires the generation and manipulation of an internal representation of beliefs over the values of the hidden variable. In Chapter 5, I describe behavioral and neural results regarding the learning strategies employed by human subjects in a hierarchical state-estimation task. In particular, a comprehensive model fit and comparison process pointed to the use of "belief thresholding". This implies that subjects tended to eliminate low-probability hypotheses regarding the state of the environment from their internal model and ceased to update the corresponding variables. Thus, in concert with incremental Bayesian learning, humans explicitly manipulate their internal model of the generative process during hierarchical inference consistent with a serial hypothesis testing strategy.

Values and actions in aversion

Model-based and model-free controllers can, in principle, learn arbitrary actions to optimize their behavior, at least those actions that can be expressed and explored. Indeed, these are often referred to as instrumental controllers because their choices are learned to be instrumental for the delivery of desired outcomes. Although this flexibility is very powerful, it comes with an attendant cost of learning. Evolution appears to have endowed everything from the simplest organisms to us with powerful, pre-specified, but inflexible alternatives. These responses are termed Pavlovian, after the famous Russian physiologist and psychologist Pavlov. The responses of the Pavlovian controller are determined by evolutionary (phylogenetic) considerations rather than (ontogenetic) aspects of the contingent development or learning of an individual. These responses directly interact with instrumental choices arising from goal-directed and habitual controllers. This interaction has been studied in a wealth of animal paradigms, and can be helpful, neutral, or harmful, according to circumstance. Although there has been less careful or analytical study of it in humans, it can be interpreted as underpinning a wealth of behavioral aberrations. © 2009 Elsevier Inc. All rights reserved.

Does temporal discounting explain unhealthy behavior? A systematic review and reinforcement learning perspective.

The tendency to make unhealthy choices is hypothesized to be related to an individual's temporal discount rate, the theoretical rate at which they devalue delayed rewards. Furthermore, a particular form of temporal discounting, hyperbolic discounting, has been proposed to explain why unhealthy behavior can occur despite healthy intentions. We examine these two hypotheses in turn. We first systematically review studies which investigate whether discount rates can predict unhealthy behavior. These studies reveal that high discount rates for money (and in some instances food or drug rewards) are associated with several unhealthy behaviors and markers of health status, establishing discounting as a promising predictive measure. We secondly examine whether intention-incongruent unhealthy actions are consistent with hyperbolic discounting. We conclude that intention-incongruent actions are often triggered by environmental cues or changes in motivational state, whose effects are not parameterized by hyperbolic discounting. We propose a framework for understanding these state-based effects in terms of the interplay of two distinct reinforcement learning mechanisms: a "model-based" (or goal-directed) system and a "model-free" (or habitual) system. Under this framework, while discounting of delayed health may contribute to the initiation of unhealthy behavior, with repetition, many unhealthy behaviors become habitual; if health goals then change, habitual behavior can still arise in response to environmental cues. We propose that the burgeoning development of computational models of these processes will permit further identification of health decision-making phenotypes.

Finding resonance: Adaptive frequency oscillators for dynamic legged locomotion

There is much to gain from providing walking machines with passive dynamics, e.g. by including compliant elements in the structure. These elements can offer interesting properties such as self-stabilization, energy efficiency and simplified control. However, there is still no general design strategy for such robots and their controllers. In particular, the calibration of control parameters is often complicated because of the highly nonlinear behavior of the interactions between passive components and the environment. In this article, we propose an approach in which the calibration of a key parameter of a walking controller, namely its intrinsic frequency, is done automatically. The approach uses adaptive frequency oscillators to automatically tune the intrinsic frequency of the oscillators to the resonant frequency of a compliant quadruped robot The tuning goes beyond simple synchronization and the learned frequency stays in the controller when the robot is put to halt. The controller is model free, robust and simple. Results are presented illustrating how the controller can robustly tune itself to the robot, as well as readapt when the mass of the robot is changed. We also provide an analysis of the convergence of the frequency adaptation for a linearized plant, and show how that analysis is useful for determining which type of sensory feedback must be used for stable convergence. This approach is expected to explain some aspects of developmental processes in biological and artificial adaptive systems that "develop" through the embodied system-environment interactions. © 2006 IEEE.

Correcting the errors: Volatility forecast evaluation using high-frequency data and realized volatilities

We develop general model-free adjustment procedures for the calculation of unbiased volatility loss functions based on practically feasible realized volatility benchmarks. The procedures, which exploit recent nonparametric asymptotic distributional results, are both easy-to-implement and highly accurate in empirically realistic situations. We also illustrate that properly accounting for the measurement errors in the volatility forecast evaluations reported in the existing literature can result in markedly higher estimates for the true degree of return volatility predictability.

15N NMR relaxation data reveal significant chemical exchange broadening in the alpha-domain of human α-lactalbumin

Human alpha-lactalbumin (alpha-LA), a 123-residue calcium-binding protein, has been studied using (15)N NMR relaxation methods in order to characterize backbone dynamics of the native state at the level of individual residues. Relaxation data were collected at three magnetic field strengths and analyzed using the model-free formalism of Lipari and Szabo. The order parameters derived from this analysis are generally high, indicating a rigid backbone. A total of 46 residues required an exchange contribution to T(2); 43 of these residues are located in the alpha-domain of the protein. The largest exchange contributions are observed in the A-, B-, D-, and C-terminal 3(10)-helices of the alpha-domain; these residues have been shown previously to form a highly stable core in the alpha-LA molten globule. The observed exchange broadening, along with previous hydrogen/deuterium amide exchange data, suggests that this part of the alpha-domain may undergo a local structural transition between the well-ordered native structure and a less-ordered molten-globule-like structure.

Three primary kinetic characteristics observed in a pulse-response TAP experiment

The state-by-state transient screening approach based on a pulse-response thin-zone TAP experiment is further developed whereby single-pulse kinetic tests are treated as small perturbations to catalyst compositions and analyzed using integral method of moments. Results on three primary kinetic characteristics, termed basic kinetic coefficients, are presented. These three coefficients were introduced as main observables from experimentally measured TAP-responses in a kinetic-model-free manner. Each was analytically determined from moments of responses with no assumption about the detailed kinetic model. In this paper, the inverse question of how well these coefficients represent the time evolution of the observed responses is addressed. Sets of three basic kinetic coefficients are calculated from model and experimental responses and these calculated values are used to generate 3-coefficient curves in a kinetic-model-free manner. The comparison of these 3-coefficient curves with original responses shows that three basic kinetic coefficients can be sufficient to describe the observed kinetics of exit flow time dependencies with no assumption regarding the detailed kinetic model.

Second-Order Training of Adaptive Critics for Online Process Control

A new algorithm for training of nonlinear optimal neuro-controllers (in the form of the model-free, action-dependent, adaptive critic paradigm). Overcomes problems with existing stochastic backpropagation training: need for data storage, parameter shadowing and poor convergence, offering significant benefits for online applications.

Theoretical considerations of electrochemical phase formation for an ideal Frank-van der Merwe system - Ag on Au(111) and Au(100)

: Static calculation and preliminary kinetic Monte Carlo simulation studies are undertaken for the nucleation and growth on a model system which follows a Frank-van der Merwe mechanism. In the present case, we consider the deposition of Ag on Au(100) and Au(111) surfaces. The interactions were calculated using the embedded atom model. The kinetics of formation and growth of 2D Ag structures on Au(100) and Au(111) is investigated and the influence of surface steps on this phenomenon is studied. Very different time scales are predicted for Ag diffusion on Au(100) and Au(111), thus rendering very different regimes for the nucleation and growth of the related 2D phases. These observations are drawn from the application of a model free of any adjustable parameter.

Monitoring and repair of an impact damaged prestressed bridge

This paper details the monitoring and repair of an impact damaged prestressed concrete bridge. The repair was required following an impact from a low-loader carrying an excavator while passing underneath the bridge. The repair was carried out by preloading the bridge in the vicinity of the damage to relieve some prestressing. This preload was removed following the hardening and considerable strength gain of the repair material. The true behaviour of damaged prestressed concrete bridges during repair is difficult to estimate theoretically due to lack of benchmarking and inadequacy of assumed damage models. A network of strain gauges at locations of interest was thus installed during the entire period of repair. Effects of various activities were qualitatively and quantitatively observed. The interaction and rapid, model-free calibration of damaged and undamaged beams, including identification of damaged gauges were also probed. This full scale experiment is expected to be of interest and benefit to the practising engineer and the researcher alike.