Characterization of the cavity nucleation factor for life prediction under creep-fatigue interaction

It is understood that grain boundary cavitation is one of the detrimental processes for the degradation of materials that reduces the creep-fatigue life at high temperatures. In a previous investigation, a model for life prediction under creep-fatigue conditions was proposed in terms of cavity nucleation and growth. In that model, the cavity nucleation factor (P) was introduced to correlate between the number of cavities and the plastic strain range from which athermal vacancies are generated. It was considered to be a material specific constant which was independent of the experimental conditions. However, in this study, it is found that the cavity nucleation factor is a function of the plastic strain range but is independent of the testing temperature at near 0.5 T _m. In the light of this dependency, a new cavity nucleation factor (P'), is introduced. Using this new cavity nucleation factor (P'), a modified equation for life prediction is proposed, and it is shown that there is good agreement between predicted and experimental lives. Additionally, an interesting approach has been made to find the physical meaning of the new cavity nucleation factor (P'). According to this study, it is suggested that the new cavity nucleation factor, which is regarded as a material specific constant, is found to be strongly related to the density of the grain boundary precipitates with a linear relationship existing between them.     

Application of the recurrent multilayer perceptron in modelingcomplex process dynamics

A nonlinear dynamic model is developed for a process system, namely a heat exchanger, using the recurrent multilayer perceptron network as the underlying model structure. The perceptron is a dynamic neural network, which appears effective in the input-output modeling of complex process systems. Dynamic gradient descent learning is used to train the recurrent multilayer perceptron, resulting in an order of magnitude improvement in convergence speed over a static learning algorithm used to train the same network. In developing the empirical process model the effects of actuator, process, and sensor noise on the training and testing sets are investigated. Learning and prediction both appear very effective, despite the presence of training and testing set noise, respectively. The recurrent multilayer perceptron appears to learn the deterministic part of a stochastic training set, and it predicts approximately a moving average response of various testing sets. Extensive model validation studies with signals that are encountered in the operation of the process system modeled, that is steps and ramps, indicate that the empirical model can substantially generalize operational transients, including accurate prediction of instabilities not in the training set. However, the accuracy of the model beyond these operational transients has not been investigated. Furthermore, online learning is necessary during some transients and for tracking slowly varying process dynamics. Neural networks based empirical models in some cases appear to provide a serious alternative to first principles models.     

Photocatalytic degradation of methyl orange using heteropolytungstic acid-encapsulated TiSBA-15

Heteropolyphosphotungstic acid (H₃PW₁₂O₄₀) (HPA)-encapsulated titanium-supported SBA15 nanoporous materials (HPA-TiSBA-15) were synthesized as a new photocatalyst, and they were characterized by FT-IR and ³¹P NMR MAS spectroscopic methods. Their photocatalytic effects on degradation of methyl orange in water were investigated under natural conditions, and it was found that a 4-fold increase in the photodegradation rate is observed in the presence of HPA-TiSBA-15 as compared to the rate observed in the presence of titanium-supported SBA15 nanoporous materials (TiSBA-15) without HPA.     

Minimum-Energy Translational Trajectory Generation for Differential-Driven Wheeled Mobile Robots

Mobile robots can be used in many applications, such as exploration, search and rescue, reconnaissance, security, and cleaning. Mobile robots usually carry batteries as their energy source and their operational time is restricted by the finite energy available from the batteries. Therefore, energy constraints are critical to the service time of mobile robots. This paper investigates the minimum-energy control problem for translational trajectory generation, which minimizes the energy drawn from the batteries. Optimal control theory is used to find the optimal velocity trajectory in analytic form. To demonstrate energy efficiency obtainable, we performed simulations of minimum-energy velocity control and compared the results with loss-minimization control and energy-optimal trapezoidal velocity profiles. Simulation results showed that significant energy savings can be achieved, of up to 9% compared with loss-minimization control and up to 10% compared with energy-optimal trapezoidal velocity profile. We also performed an actual robot experiment using Pioneer 3-AT platform to show the validity of the proposed minimum-energy velocity control. The experimental results revealed that the proposed minimum-energy velocity control can save the battery energy up to 10% compared with loss-minimization control. Categories (3): Robot control, (5): RobotMotion Planning     

An accurate and practical buffer allocation model for the buffer cache based on marginal gains

A new dynamic buffer allocation strategy based on the notion of marginal gains is presented for the buffer cache that is used by the operating system to store frequently accessed disk blocks in main memory, and the performance of the proposed strategy is compared with those of previous allocation strategies. In the proposed strategy, marginal gain values are predicted by exploiting functions that approximate the expected number of buffer hits per unit time. Experimental results from both trace-driven simulation and an actual implementation in the FreeBSD operating system show that the proposed strategy accurately predicts the marginal gain values for various workloads resulting in significantly improved buffer hit ratios.     

Category Norms as a Function of Culture and Age: Comparisons of Item Responses to 105 Categories by American and Chinese Adults.

Understanding how aging influences cognition across different cultures has been hindered by a lack of standardized, cross-referenced verbal stimuli. This study introduces a database of such item-level stimuli for both younger and older adults, in China and the United States, and makes 3 distinct contributions. First, the authors specify which item categories generalize across age and/or cultural groups, rigorously quantifying differences among them. Second, they introduce novel, powerful methods to measure between-group differences in freely generated ranked data, the rank-ordered logit model and Hellinger Affinity. Finally, a broad archive of tested, cross-linguistic stimuli is now freely available to researchers: data, similarity measures, and all stimulus materials for 105 categories and 4 culture-by-age groups, comprising over 10,000 fully translated unique item responses. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

An Area Optimization Method for Digital Filter Design

In this paper, we propose an efficient design method for area optimization in a digital filter. The conventional methods to reduce the number of adders in a filter have the problem of a long critical path delay caused by the deep logic depth of the filter due to adder sharing. Furthermore, there is such a disadvantage that they use the transposed direct form (TDF) filter which needs more registers than those of the direct form (DF) filter. In this paper, we present a hybrid structure of a TDF and DF based on the flattened coefficients method so that it can reduce the number of flip‐flops and full‐adders without additional critical path delay. We also propose a resource sharing method and sharing‐pattern searching algorithm to reduce the number of adders without deepening the logic depth. Simulation results show that the proposed structure can save the number of adders and registers by 22 and 26%, respectively, compared to the best one used in the past.     

Surface structural change of ZnO-coated LiNi0.5Mn1.5O4 spinel as 5 V cathode materials at elevated temperatures

LiNi_0.5Mn_1.5O₄ powder was synthesized via sol-gel method and coated with ZnO in order to test the electrochemical cyclability of the material as a cathode for the secondary Li battery in the 5 V range at 55 °C. The ZnO-coated LiNi_0.5Mn_1.5O₄ powder nearly maintained its initial capacity of 137 mA h g⁻¹ after 50 cycles whereas the uncoated powder was able to retain no more than 10% of the initial capacity after 30 cycles. TEM analysis of the cycled cathodes suggests that the formation of the graphitic surface phase, hindering the Li migration, may be responsible for the rapid capacity loss of the uncoated material while no such phase was observed on the surface of the ZnO coated LiNi_0.5Mn_1.5O₄ powder.     

Robust Space Time Receiver for CDMA-based Antenna Arrays

In this paper, we propose a new robust code division multiple access (CDMA) receiver of which weight vector is obtained by projecting the effective spatio-temporal signature waveform onto the signal subspace of the data covariance matrix. We verified our proposed algorithm by the field measured data obtained with a custom-built wideband CDMA test-bed. It will be shown that the proposed algorithm is robust to the signal mismatch.