Prediction of Fatigue Life in Plain Concrete Using Entropy Production

An energy approach within the framework of thermodynamics is used to model the fatigue process in plain concrete. Fatigue crack growth is an irreversible process associated with an irreversible entropy gain. A closed-form expression for entropy generated during fatigue in terms of energy dissipated is derived using principles of dimensional analysis and self-similarity. An increase in compliance is considered as a measure of damage accumulated during fatigue. The entropy at final fatigue failure is shown to be independent of loading and geometry and is proposed as a material property. A relationship between energy dissipated and number of cycles of fatigue loading is obtained. (C) 2015 American Society of Civil Engineers.

Probabilistic Prediction based Scheduling for Delay Sensitive Traffic in Internet of Things

This paper proposes a probabilistic prediction based approach for providing Quality of Service (QoS) to delay sensitive traffic for Internet of Things (IoT). A joint packet scheduling and dynamic bandwidth allocation scheme is proposed to provide service differentiation and preferential treatment to delay sensitive traffic. The scheduler focuses on reducing the waiting time of high priority delay sensitive services in the queue and simultaneously keeping the waiting time of other services within tolerable limits. The scheme uses the difference in probability of average queue length of high priority packets at previous cycle and current cycle to determine the probability of average weight required in the current cycle. This offers optimized bandwidth allocation to all the services by avoiding distribution of excess resources for high priority services and yet guaranteeing the services for it. The performance of the algorithm is investigated using MPEG-4 traffic traces under different system loading. The results show the improved performance with respect to waiting time for scheduling high priority packets and simultaneously keeping tolerable limits for waiting time and packet loss for other services. Crown Copyright (C) 2015 Published by Elsevier B.V.

PREDICTION OF TRANSITIONAL AND SEPARATED BOUNDARY LAYERS IN A COMPRESSOR CASCADE

Numerical simulations were performed of experiments from a cascade of stator blades at three low Reynolds numbers representative of flight conditions. Solutions were assessed by comparing blade surface pressures, velocity and turbulence intensity along blade normals at several stations along the suction surface and in the wake. At Re = 210,000 and 380,000 the laminar boundary layer over the suction surface separates and reattaches with significant turbulence fluctuations. A new 3-equation transition model, the k-k(L)-omega model, was used to simulate this flow. Predicted locations of the separation bubble, and profiles of velocity and turbulence fluctuations on blade-normal lines at various stations along the blade were found to be quite close to measurements. Suction surface pressure distributions were not as close at the lower Re. The solution with the standard k-omega SST model showed significant differences in all quantities. At Re = 640,000 transition occurs earlier and it is a turbulent boundary layer that separates near the trailing edge. The solution with the Reynolds stress model was found to be quite close to the experiment in the separated region also, unlike the k-omega SST solution. Three-dimensional computations were performed at Re = 380,000 and 640,000. In both cases there were no significant differences between the midspan solution from 3D computations and the 2D solutions. However, the 3D solutions exhibited flow features observed in the experiments the nearly 2D structure of the flow over most of the span at 380,000 and the spanwise growth of corner vortices from the endwall at 640,000.

Comprehensive evaluation of multisatellite precipitation estimates over India using gridded rainfall data

This study presents a comprehensive evaluation of five widely used multisatellite precipitation estimates (MPEs) against 1 degrees x 1 degrees gridded rain gauge data set as ground truth over India. One decade observations are used to assess the performance of various MPEs (Climate Prediction Center (CPC)-South Asia data set, CPC Morphing Technique (CMORPH), Precipitation Estimation From Remotely Sensed Information Using Artificial Neural Networks, Tropical Rainfall Measuring Mission's Multisatellite Precipitation Analysis (TMPA-3B42), and Global Precipitation Climatology Project). All MPEs have high detection skills of rain with larger probability of detection (POD) and smaller ``missing'' values. However, the detection sensitivity differs from one product (and also one region) to the other. While the CMORPH has the lowest sensitivity of detecting rain, CPC shows highest sensitivity and often overdetects rain, as evidenced by large POD and false alarm ratio and small missing values. All MPEs show higher rain sensitivity over eastern India than western India. These differential sensitivities are found to alter the biases in rain amount differently. All MPEs show similar spatial patterns of seasonal rain bias and root-mean-square error, but their spatial variability across India is complex and pronounced. The MPEs overestimate the rainfall over the dry regions (northwest and southeast India) and severely underestimate over mountainous regions (west coast and northeast India), whereas the bias is relatively small over the core monsoon zone. Higher occurrence of virga rain due to subcloud evaporation and possible missing of small-scale convective events by gauges over the dry regions are the main reasons for the observed overestimation of rain by MPEs. The decomposed components of total bias show that the major part of overestimation is due to false precipitation. The severe underestimation of rain along the west coast is attributed to the predominant occurrence of shallow rain and underestimation of moderate to heavy rain by MPEs. The decomposed components suggest that the missed precipitation and hit bias are the leading error sources for the total bias along the west coast. All evaluation metrics are found to be nearly equal in two contrasting monsoon seasons (southwest and northeast), indicating that the performance of MPEs does not change with the season, at least over southeast India. Among various MPEs, the performance of TMPA is found to be better than others, as it reproduced most of the spatial variability exhibited by the reference.

Prediction and validation of gold nanoparticles (GNPs) on plant growth promoting rhizobacteria (PGPR): a step toward development of nano-biofertilizers

Several soil microbes are present in the rhizosphere zone, especially plant growth promoting rhizobacteria (PGPR), which are best known for their plant growth promoting activities. The present study reflects the effect of gold nanoparticles (GNPs) at various concentrations on the growth of PGPR. GNPs were synthesized chemically, by reduction of HAuCl 4, and further characterized by UV-Vis spectroscopy, X-ray diffraction technique (XRD), and transmission electron microscopy (TEM), etc. The impact of GNPs on PGPR was investigated by Clinical Laboratory Standards Institute (CLSI) recommended Broth-Microdilution technique against four selected PGPR viz., Pseudomonas fluorescens, Bacillus subtilis, Paenibacillus elgii, and Pseudomonas putida. Neither accelerating nor reducing impact was observed in P. putida due to GNPs. On the contrary, significant increase was observed in the case of P. fluorescens, P. elgii, and B. subtilis, and hence, GNPs can be exploited as nano-biofertilizers.

A fast algorithm for speech polarity detection using long-term linear prediction

Speech polarity detection is a crucial first step in many speech processing techniques. In this paper, an algorithm is proposed that improvises the existing technique using the skewness of the voice source (VS) signal. Here, the integrated linear prediction residual (ILPR) is used as the VS estimate, which is obtained using linear prediction on long-term frames of the low-pass filtered speech signal. This excludes the unvoiced regions from analysis and also reduces the computation. Further, a modified skewness measure is proposed for decision, which also considers the magnitude of the skewness of the ILPR along with its sign. With the detection error rate (DER) as the performance metric, the algorithm is tested on 8 large databases and its performance (DER=0.20%) is found to be comparable to that of the best technique (DER=0.06%) on both clean and noisy speech. Further, the proposed method is found to be ten times faster than the best technique.

Prediction of electronically nonadiabatic decomposition mechanisms of isolated gas phase nitrogen-rich energetic salt: Guanidium-triazolate

Electronically nonadiabatic decomposition pathways of guanidium triazolate are explored theoretically. Nonadiabatically coupled potential energy surfaces are explored at the complete active space self-consistent field (CASSCF) level of theory. For better estimation of energies complete active space second order perturbation theories (CASPT2 and CASMP2) are also employed. Density functional theory (DFT) with B3LYP functional and MP2 level of theory are used to explore subsequent ground state decomposition pathways. In comparison with all possible stable decomposition products (such as, N-2, NH3, HNC, HCN, NH2CN and CH3NC), only NH3 (with NH2CN) and N-2 are predicted to be energetically most accessible initial decomposition products. Furthermore, different conical intersections between the S-1 and S-0 surfaces, which are computed at the CASSCF(14,10)/6-31G(d) level of theory, are found to play an essential role in the excited state deactivation process of guanidium triazolate. This is the first report on the electronically nonadiabatic decomposition mechanisms of isolated guanidium triazolate salt. (C) 2015 Elsevier B.V. All rights reserved.

Numerical prediction of nozzle flow separation: Issue of turbulence modeling

Numerical simulation of separated flows in rocket nozzles is challenging because existing turbulence models are unable to predict it correctly. This paper addresses this issue with the Spalart-Allmaras and Shear Stress Transport (SST) eddy-viscosity models, which predict flow separation with moderate success. Their performances have been compared against experimental data for a conical and two contoured subscale nozzles. It is found that they fail to predict the separation location correctly, exhibiting sensitivity to the nozzle pressure ratio (NPR) and nozzle type. A careful assessment indicated how the model had to be tuned for better, consistent prediction. It is learnt that SST model's failure is caused by limiting of the shear stress inside boundary layer according to Bradshaw's assumption, and by over prediction of jet spreading rate. Accordingly, SST's coefficients were empirically modified to match the experimental wall pressure data. Results confirm that accurate RANS prediction of separation depends on the correct capture of the jet spreading rate, and that it is feasible over a wide range of NPRs by modified values of the diffusion coefficients in the turbulence model. (C) 2015 Elsevier Masson SAS. All rights reserved.

Environmental Mechanics Research in China

By recalling mankind's path during past 50 years in the present article, we mainly highlight the significance of environmental issues today. In particular, two major factors leading to environment deterioration in China such as water resources and coal burning are stressed on. Present-day environmental issues are obviously interdisciplinary, of multiple scales and multi-composition in nature. Therefore, a process-based approach for environment research is absolutely necessarily. A series of sub-processes, either physical, chemical or biological, are subsequently analyzed in order to established reasonable parameterization scheme and credible comprehensive model. And we are now in a position to answer questions still open to us, improve existing somewhat empirical engineering approaches and enhance quantitative accuracy in prediction. To illustrate this process-based research approach, three typical examples associated with the Yangtze River Estuary, Loess Plateau and Tenggeli Desert environments have been dealt with respectively. A theoretical model of vertical flow field accounting for runoff and tide interaction has been established to delineate salinity and sediment motion which are responsible for the formation of mouth bar at the outlet and the ecological evolution there. A kinematic wave theory combined with the revised Green-Ampt infiltration formula is applied to the prediction of runoff generation and erosion in three types of erosion region on the Loess Plateau. Three approaches describing water motion in SPAC system in arid areas at different levels have been improved by introducing vegetation sub-models. However, we have found that the formation of a dry sandy layer and biological crust skin are additional primary causes leading to deterioration of water supply and succession of ecological system.

State Vector: A New Approach to Prediction of the Failure of Brittle Heterogeneous Media and Large Earthquakes

The concept of state vector stems from statistical physics, where it is usually used to describe activity patterns of a physical field in its manner of coarsegrain. In this paper, we propose an approach by which the state vector was applied to describe quantitatively the damage evolution of the brittle heterogeneous systems, and some interesting results are presented, i.e., prior to the macro-fracture of rock specimens and occurrence of a strong earthquake, evolutions of the four relevant scalars time series derived from the state vectors changed anomalously. As retrospective studies, some prominent large earthquakes occurred in the Chinese Mainland (e.g., the M 7.4 Haicheng earthquake on February 4, 1975, and the M 7.8 Tangshan earthquake on July 28, 1976, etc) were investigated. Results show considerable promise that the time-dependent state vectors could serve as a kind of precursor to predict earthquakes.

Characteristics and Sub-Characteristics of Two-Dimensional Parabolized Stability Equations

特征分析表明：对原始扰动量的抛物化稳定性方程组(PSE),它在亚超音速区分别具有椭圆和抛物特性,给出PSE特征对马赫数的依赖关系,阐明PSE仅把信息对流-扩散传播特性抛物化,而保留了信息对流-扰动传播特性,因此PSE应称为扩散抛物化稳定性方程(DPSE)。

Load-Unload Response Ratio and Accelerating Moment/Energy Release Critical Region Scaling and Earthquake Prediction

The main idea of the Load-Unload Response Ratio (LURR) is that when a system is stable, its response to loading corresponds to its response to unloading, whereas when the system is approaching an unstable state, the response to loading and unloading becomes quite different. High LURR values and observations of Accelerating Moment/Energy Release (AMR/AER) prior to large earthquakes have led different research groups to suggest intermediate-term earthquake prediction is possible and imply that the LURR and AMR/AER observations may have a similar physical origin. To study this possibility, we conducted a retrospective examination of several Australian and Chinese earthquakes with magnitudes ranging from 5.0 to 7.9, including Australia's deadly Newcastle earthquake and the devastating Tangshan earthquake. Both LURR values and best-fit power-law time-to-failure functions were computed using data within a range of distances from the epicenter. Like the best-fit power-law fits in AMR/AER, the LURR value was optimal using data within a certain epicentral distance implying a critical region for LURR. Furthermore, LURR critical region size scales with mainshock magnitude and is similar to the AMR/AER critical region size. These results suggest a common physical origin for both the AMR/AER and LURR observations. Further research may provide clues that yield an understanding of this mechanism and help lead to a solid foundation for intermediate-term earthquake prediction.