Ultrasonic wave characteristics of nanorods via nonlocal strain gradient models

This paper studies an ultrasonic wave dispersion characteristics of a nanorod. Nonlocal strain gradient models (both second and fourth order) are introduced to analyze the ultrasonic wave behavior in nanorod. Explicit expressions are derived for wave numbers and the wave speeds of the nanorod. The analysis shows that the fourth order strain gradient model gives approximate results over the second order strain gradient model for dynamic analysis. The second order strain gradient model gives a critical wave number at certain wave frequency, where the wave speeds are zero. A relation among the number of waves along the nanorod, the nonlocal scaling parameter (e(0)a), and the length of the nanorod is obtained from the nonlocal second order strain gradient model. The ultrasonic wave characteristics of the nanorod obtained from the nonlocal strain gradient models are compared with the classical continuum model. The dynamic response behavior of nanorods is explained from both the strain gradient models. The effect of e(0)a on the ultrasonic wave behavior of the nanorods is also observed. (C) 2010 American Institute of Physics.

Foaming of slags under dynamic conditions

Slag foaming under dynamic conditions has been studied in laboratory scale to examine the influence of properties commonly used to describe the foaminess and foam stability of slags under steady-state conditions. Synthetically produced slags with compositions relevant to tool steel and stainless steel production were studied through X-ray equipment in measurements simulating the dynamic conditions found in real processes. It is found that the dynamic systems display a more complex behavior than systems Under steady state. Traditional theories for foaming do not seem to be valid for slag foaming under dynamic conditions. The foam displays a fluctuating behavior, which the presently available models are not able to take into account. The concept of a foaming index does not seem to be applicable, resulting in the need for alternative models.

Models for spin-state transitions in solids

The model for spin-state transitions described by Bari and Sivardiere (1972) is static and can be solved exactly even when the dynamics of the lattice are included; the dynamic model does not, however, show any phase transition. A coupling between the octahedra, on the other hand, leads to a phase transition in the dynamical two-sublattice displacement model. A coupling of the spin states to the cube of the sublattice displacement leads to a first-order phase transition. The most reasonable model appears to be a two-phonon model in which an ion-cage mode mixes the spin states, while a breathing mode couples to the spin states without mixing. This model explains the non-zero population of high-spin states at low temperatures, temperature-dependent variations in the inverse susceptibility and the spin-state population ratio, as well as the structural phase transitions accompanying spin-state transitions found in some systems.

Dynamic Behavior of Poly(2-vinylpyridine) in Solution Studied by 13C Nuclear Magnetic Relaxation

Abstract: The dynamics of poly(2-vinylpyridine) in chloroform solution has been examined by C-13 spin-lattice relaxation time and NOE measurements as a function of temperature. The experiments were performed at 50.3 and 100.6 MHz. The backbone carbon relaxation data have been analyzed in terms of six motional models. Among these models, the models which consider conformational transitions and bond librations for the backbone were found to be more successful. Pyridyl ring motion has been modeled as a restricted rotation with the rotational amplitude varying with temperature. The activation energy parameters obtained from the relaxation data of the pyridyl ring carbon have been compared with the energy barrier for ring rotation estimated from conformational energy calculations using the AM1 semiempirical quantum chemical method. The results of the conformational energy calculations support the description of pyridyl ring motion as a restricted rotation.

Voltage and Temperature Scalable Standard Cell Leakage Models Based on Stacks for Statistical Leakage Characterization

With extensive use of dynamic voltage scaling (DVS) there is increasing need for voltage scalable models. Similarly, leakage being very sensitive to temperature motivates the need for a temperature scalable model as well. We characterize standard cell libraries for statistical leakage analysis based on models for transistor stacks. Modeling stacks has the advantage of using a single model across many gates there by reducing the number of models that need to be characterized. Our experiments on 15 different gates show that we needed only 23 models to predict the leakage across 126 input vector combinations. We investigate the use of neural networks for the combined PVT model, for the stacks, which can capture the effect of inter die, intra gate variations, supply voltage(0.6-1.2 V) and temperature (0 - 100degC) on leakage. Results show that neural network based stack models can predict the PDF of leakage current across supply voltage and temperature accurately with the average error in mean being less than 2% and that in standard deviation being less than 5% across a range of voltage, temperature.

Modeling wrap faced reinforced soil retaining walls subjected to dynamic excitation

This paper describes some of the physical and numerical model tests of reinforced soil retaining walls subjected to dynamic excitation through uni-axial shaking tests. Models of retaining walls are constructed in a perspex box with geotextile reinforcement using the wrap around technique with dry sand backfill and instrumented with displacement sensors, accelerometers and soil pressure sensors. Numerical modelling of these shaking table tests is carried using FLAC. Numerical model is validated by comparing physical model results. Responses of wrap faced walls with different number of reinforcement layers are discussed from both the physical and numerical model tests. Results showed that the displacements are decreasing with the increase in number of reinforcement layers while acceleration amplifications are not affected significantly.

Reinforcement learning applications in dynamic pricing of retail markets

In this paper, we investigate the use of reinforcement learning (RL) techniques to the problem of determining dynamic prices in an electronic retail market. As representative models, we consider a single seller market and a two seller market, and formulate the dynamic pricing problem in a setting that easily generalizes to markets with more than two sellers. We first formulate the single seller dynamic pricing problem in the RL framework and solve the problem using the Q-learning algorithm through simulation. Next we model the two seller dynamic pricing problem as a Markovian game and formulate the problem in the RL framework. We solve this problem using actor-critic algorithms through simulation. We believe our approach to solving these problems is a promising way of setting dynamic prices in multi-agent environments. We illustrate the methodology with two illustrative examples of typical retail markets.

Analysis of Conformational Variation in Macromolecular Structural Models

Experimental conditions or the presence of interacting components can lead to variations in the structural models of macromolecules. However, the role of these factors in conformational selection is often omitted by in silico methods to extract dynamic information from protein structural models. Structures of small peptides, considered building blocks for larger macromolecular structural models, can substantially differ in the context of a larger protein. This limitation is more evident in the case of modeling large multi-subunit macromolecular complexes using structures of the individual protein components. Here we report an analysis of variations in structural models of proteins with high sequence similarity. These models were analyzed for sequence features of the protein, the role of scaffolding segments including interacting proteins or affinity tags and the chemical components in the experimental conditions. Conformational features in these structural models could be rationalized by conformational selection events, perhaps induced by experimental conditions. This analysis was performed on a non-redundant dataset of protein structures from different SCOP classes. The sequence-conformation correlations that we note here suggest additional features that could be incorporated by in silico methods to extract dynamic information from protein structural models.

On the dynamic contact angle in simulation of impinging droplets with sharp interface methods

Effects of dynamic contact angle models on the flow dynamics of an impinging droplet in sharp interface simulations are presented in this article. In the considered finite element scheme, the free surface is tracked using the arbitrary Lagrangian-Eulerian approach. The contact angle is incorporated into the model by replacing the curvature with the Laplace-Beltrami operator and integration by parts. Further, the Navier-slip with friction boundary condition is used to avoid stress singularities at the contact line. Our study demonstrates that the contact angle models have almost no influence on the flow dynamics of the non-wetting droplets. In computations of the wetting and partially wetting droplets, different contact angle models induce different flow dynamics, especially during recoiling. It is shown that a large value for the slip number has to be used in computations of the wetting and partially wetting droplets in order to reduce the effects of the contact angle models. Among all models, the equilibrium model is simple and easy to implement. Further, the equilibrium model also incorporates the contact angle hysteresis. Thus, the equilibrium contact angle model is preferred in sharp interface numerical schemes.

Modeling the dynamic response of wrap-faced reinforced soil retaining walls

This paper describes the development of a numerical model for simulating the shaking table tests on wrap-faced reinforced soil retaining walls. Some of the physical model tests carried out on reinforced soil retaining walls subjected to dynamic excitation through uniaxial shaking tests are briefly discussed. Models of retaining walls are constructed in a perspex box with geotextile reinforcement using the wraparound technique with dry sand backfill and instrumented with displacement sensors, accelerometers, and soil pressure sensors. Results showed that the displacements decrease with the increase in number of reinforcement layers, whereas acceleration amplifications were not affected significantly. Numerical modeling of these shaking table tests is carried out using the Fast Lagrangian Analysis of Continua program. The numerical model is validated by comparing the results with experiments on physical models. Responses of wrap-faced walls with varying numbers of reinforcement layers are compared. Sensitivity analysis performed on the numerical models showed that the friction and dilation angle of backfill material and stiffness properties of the geotextile-soil interface are the most affecting parameters for the model response.

Dynamic multi-relational Chinese restaurant process for analyzing influences on users in social media

We study the problem of analyzing influence of various factors affecting individual messages posted in social media. The problem is challenging because of various types of influences propagating through the social media network that act simultaneously on any user. Additionally, the topic composition of the influencing factors and the susceptibility of users to these influences evolve over time. This problem has not been studied before, and off-the-shelf models are unsuitable for this purpose. To capture the complex interplay of these various factors, we propose a new non-parametric model called the Dynamic Multi-Relational Chinese Restaurant Process. This accounts for the user network for data generation and also allows the parameters to evolve over time. Designing inference algorithms for this model suited for large scale social-media data is another challenge. To this end, we propose a scalable and multi-threaded inference algorithm based on online Gibbs Sampling. Extensive evaluations on large-scale Twitter and Face book data show that the extracted topics when applied to authorship and commenting prediction outperform state-of-the-art baselines. More importantly, our model produces valuable insights on topic trends and user personality trends beyond the capability of existing approaches.

Study of dynamic behaviour of recession curves

Since Brutsaert and Neiber (1977), recession curves are widely used to analyse subsurface systems of river basins by expressing -dQ/dt as a function of Q, which typically take a power law form: -dQ/dt=kQ, where Q is the discharge at a basin outlet at time t. Traditionally recession flows are modelled by single reservoir models that assume a unique relationship between -dQ/dt and Q for a basin. However, recent observations indicate that -dQ/dt-Q relationship of a basin varies greatly across recession events, indicating the limitation of such models. In this study, the dynamic relationship between -dQ/dt and Q of a basin is investigated through the geomorphological recession flow model which models recession flows by considering the temporal evolution of its active drainage network (the part of the stream network of the basin draining water at time t). Two primary factors responsible for the dynamic relationship are identified: (i) degree of aquifer recharge (ii) spatial variation of rainfall. Degree of aquifer recharge, which is likely to be controlled by (effective) rainfall patterns, influences the power law coefficient, k. It is found that k has correlation with past average streamflow, which confirms the notion that dynamic -dQ/dt-Q relationship is caused by the degree of aquifer recharge. Spatial variation of rainfall is found to have control on both the exponent, , and the power law coefficient, k. It is noticed that that even with same and k, recession curves can be different, possibly due to their different (recession) peak values. This may also happen due to spatial variation of rainfall. Copyright (c) 2012 John Wiley & Sons, Ltd.

Experimental and theoretical studies on static and dynamic pressure-concentration isotherms of MmNi(5-x)Al(x) (x=0, 0.3, 0.5 and 0.8) hydrides

The static and dynamic pressure concentration isotherms (PCIs) of MmNi(5-x)Al(x). (x = 0, 0.3, 0.5 and 0.8) hydrides were measured at different temperatures using volumetric method. The effect of Al substitution on PCI and thermodynamic properties were studied. The plateau pressure and maximum hydrogen storage capacity decreased with Al content whereas reaction enthalpy increased. The plateau pressure, plateau slope and hysteresis effect was observed more for dynamic PCIs compared to static PCIs. Different mathematical models used for metal hydride-based thermodynamic devices simulation are compared to select suitable model for static and dynamic PCI simulation of MmNi(5)-based hydrides. Few important physical coefficients (partial molar volume, reaction enthalpy, reaction entropy, etc.) useful for development of thermodynamic devices were estimated. A relation has been proposed to correlate aluminium content and physical coefficients for the prediction of unknown PCI. The simulated and experimental PCIs were found matching closely for both static and dynamic conditions. Copyright (C) 2014, Hydrogen Energy Publications, LLC. Published by Elsevier Ltd. All rights reserved.

Assessing impact of material transition and thermal comfort models on embodied and operational energy in vernacular dwellings (India)

Vernacular dwellings are well-suited climate-responsive designs that adopt local materials and skills to support comfortable indoor environments in response to local climatic conditions. These naturally-ventilated passive dwellings have enabled civilizations to sustain even in extreme climatic conditions. The design and physiological resilience of the inhabitants have coevolved to be attuned to local climatic and environmental conditions. Such adaptations have perplexed modern theories in human thermal-comfort that have evolved in the era of electricity and air-conditioned buildings. Vernacular local building elements like rubble walls and mud roofs are given way to burnt brick walls and reinforced cement concrete tin roofs. Over 60% of Indian population is rural, and implications of such transitions on thermal comfort and energy in buildings are crucial to understand. Types of energy use associated with a buildings life cycle include its embodied energy, operational and maintenance energy, demolition and disposal energy. Embodied Energy (EE) represents total energy consumption for construction of building, i.e., embodied energy of building materials, material transportation energy and building construction energy. Embodied energy of building materials forms major contribution to embodied energy in buildings. Operational energy (OE) in buildings mainly contributed by space conditioning and lighting requirements, depends on the climatic conditions of the region and comfort requirements of the building occupants. Less energy intensive natural materials are used for traditional buildings and the EE of traditional buildings is low. Transition in use of materials causes significant impact on embodied energy of vernacular dwellings. Use of manufactured, energy intensive materials like brick, cement, steel, glass etc. contributes to high embodied energy in these dwellings. This paper studies the increase in EE of the dwelling attributed to change in wall materials. Climatic location significantly influences operational energy in dwellings. Buildings located in regions experiencing extreme climatic conditions would require more operational energy to satisfy the heating and cooling energy demands throughout the year. Traditional buildings adopt passive techniques or non-mechanical methods for space conditioning to overcome the vagaries of extreme climatic variations and hence less operational energy. This study assesses operational energy in traditional dwelling with regard to change in wall material and climatic location. OE in the dwellings has been assessed for hot-dry, warm humid and moderate climatic zones. Choice of thermal comfort models is yet another factor which greatly influences operational energy assessment in buildings. The paper adopts two popular thermal-comfort models, viz., ASHRAE comfort standards and TSI by Sharma and Ali to investigate thermal comfort aspects and impact of these comfort models on OE assessment in traditional dwellings. A naturally ventilated vernacular dwelling in Sugganahalli, a village close to Bangalore (India), set in warm - humid climate is considered for present investigations on impact of transition in building materials, change in climatic location and choice of thermal comfort models on energy in buildings. The study includes a rigorous real time monitoring of the thermal performance of the dwelling. Dynamic simulation models validated by measured data have also been adopted to determine the impact of the transition from vernacular to modern material-configurations. Results of the study and appraisal for appropriate thermal comfort standards for computing operational energy has been presented and discussed in this paper. (c) 2014 K.I. Praseeda. Published by Elsevier Ltd.

Optimal control analysis of the dynamic growth behavior of microorganisms

Understanding the growth behavior of microorganisms using modeling and optimization techniques is an active area of research in the fields of biochemical engineering and systems biology. In this paper, we propose a general modeling framework, based on Monad model, to model the growth of microorganisms. Utilizing the general framework, we formulate an optimal control problem with the objective of maximizing a long-term cellular goal and solve it analytically under various constraints for the growth of microorganisms in a two substrate batch environment. We investigate the relation between long term and short term cellular goals and show that the objective of maximizing cellular concentration at a fixed final time is equivalent to maximization of instantaneous growth rate. We then establish the mathematical connection between the generalized framework and optimal and cybernetic modeling frameworks and derive generalized governing dynamic equations for optimal and cybernetic models. We finally illustrate the influence of various constraints in the cybernetic modeling framework on the optimal growth behavior of microorganisms by solving several dynamic optimization problems using genetic algorithms. (C) 2014 Published by Elsevier Inc.