Interaction between heavy vehicles and roads

This paper discusses road damage caused by heavy commercial vehicles. Chapter 1 presents some important terminology and a brief historical review of road construction and vehicle-road interaction, from ancient times to the present day. The main types of vehicle-generated road damage, and the methods that are used by pavement engineers to analyze them are discussed in Chapter 2. Attention is also given to the main features of the response of road surfaces to vehicle loads and mathematical models that have been developed to predict road response. Chapter 3 reviews the effects on road damage of vehicle features which can be studied without consideration of vehicle dynamics. These include gross vehicle weight, axle and tire configurations, tire contact conditions and static load sharing in axle group suspensions. The dynamic tire forces generated by heavy vehicles are examined in Chapter 4. The discussion includes their simulation and measurement, their principal characteristics, the effects of tires and suspension design on dynamic forces, and the potential benefits of using advanced suspensions for minimizing dynamic tire forces. Chapter 5 discusses methods for estimating the effects of dynamic tire forces on road damage. The two main approaches are either to examine the statistics of the forces themselves; or to calculate the response of a pavement model to the forces, and to calculate the resulting wear using a material damage model. The issues involved in assessing vehicles for 'road friendliness' are discussed in Chapter 6. Possible assessment methods include measuring strains in an instrumented pavement traversed by the vehicle, measuring dynamic tire forces, or measuring vehicle parameters such as the 'natural frequency' and 'damping ratio'. Each of these measurements involves different assumptions and analysis methods for converting the results into some measure of road damage. Chapter 7 includes a summary of the main conclusions of the paper and recommendations for tire and suspension design, road design and construction, and for vehicle regulations.

Kernelized log linear models for continuous speech recognition

Large margin criteria and discriminative models are two effective improvements for HMM-based speech recognition. This paper proposed a large margin trained log linear model with kernels for CSR. To avoid explicitly computing in the high dimensional feature space and to achieve the nonlinear decision boundaries, a kernel based training and decoding framework is proposed in this work. To make the system robust to noise a kernel adaptation scheme is also presented. Previous work in this area is extended in two directions. First, most kernels for CSR focus on measuring the similarity between two observation sequences. The proposed joint kernels defined a similarity between two observation-label sequence pairs on the sentence level. Second, this paper addresses how to efficiently employ kernels in large margin training and decoding with lattices. To the best of our knowledge, this is the first attempt at using large margin kernel-based log linear models for CSR. The model is evaluated on a noise corrupted continuous digit task: AURORA 2.0. © 2013 IEEE.

Discrete multicomponent model for biodiesel spray combustion simulation

An important first step in spray combustion simulation is an accurate determination of the fuel properties which affects the modelling of spray formation and reaction. In a practical combustion simulation, the implementation of a multicomponent model is important in capturing the relative volatility of different fuel components. A Discrete Multicomponent (DM) model is deemed to be an appropriate candidate to model a composite fuel like biodiesel which consists of four components of fatty acid methyl esters (FAME). In this paper, the DM model is compared with the traditional Continuous Thermodynamics (CTM) model for both diesel and biodiesel. The CTM model is formulated based on mixing rules that incorporate the physical and thermophysical properties of pure components into a single continuous surrogate for the composite fuel. The models are implemented within the open-source CFD code OpenFOAM, and a semi-quantitative comparison is made between the predicted spray-combustion characteristics and optical measurements of a swirl-stabilised flame of diesel and biodiesel. The DM model performs better than the CTM model in predicting a higher magnitude of heat release rate in the top flame brush region of the biodiesel flame compared to that of the diesel flame. Using both the DM and CTM models, the simulation successfully reproduces the droplet size, volume flux, and droplet density profiles of diesel and biodiesel. The DM model predicts a longer spray penetration length for biodiesel compared to that of diesel, as seen in the experimental data. Also, the DM model reproduces a segregated biodiesel fuel vapour field and spray in which the most abundant FAME component has the longest vapour penetration. In the biodiesel flame, the relative abundance of each fuel component is found to dominate over the relative volatility in terms of the vapour species distribution and vice versa in the liquid species distribution. © 2014 Elsevier Ltd. All rights reserved.

"Plateau"-related summary statistics are uninformative for comparing working memory models.

Performance on visual working memory tasks decreases as more items need to be remembered. Over the past decade, a debate has unfolded between proponents of slot models and slotless models of this phenomenon (Ma, Husain, Bays (Nature Neuroscience 17, 347-356, 2014). Zhang and Luck (Nature 453, (7192), 233-235, 2008) and Anderson, Vogel, and Awh (Attention, Perception, Psychophys 74, (5), 891-910, 2011) noticed that as more items need to be remembered, "memory noise" seems to first increase and then reach a "stable plateau." They argued that three summary statistics characterizing this plateau are consistent with slot models, but not with slotless models. Here, we assess the validity of their methods. We generated synthetic data both from a leading slot model and from a recent slotless model and quantified model evidence using log Bayes factors. We found that the summary statistics provided at most 0.15 % of the expected model evidence in the raw data. In a model recovery analysis, a total of more than a million trials were required to achieve 99 % correct recovery when models were compared on the basis of summary statistics, whereas fewer than 1,000 trials were sufficient when raw data were used. Therefore, at realistic numbers of trials, plateau-related summary statistics are highly unreliable for model comparison. Applying the same analyses to subject data from Anderson et al. (Attention, Perception, Psychophys 74, (5), 891-910, 2011), we found that the evidence in the summary statistics was at most 0.12 % of the evidence in the raw data and far too weak to warrant any conclusions. The evidence in the raw data, in fact, strongly favored the slotless model. These findings call into question claims about working memory that are based on summary statistics.

Comparison of moment-curvature models for fiber-reinforced polymer plate-end debonding studies using global energy balance approach

This paper compares a number of different moment-curvature models for cracked concrete sections that contain both steel and external fiber-reinforced polymer (FRP) reinforcement. The question of whether to use a whole-section analysis or one that considers the FRP separately is discussed. Five existing and three new models are compared with test data for moment-curvature or load deflection behavior, and five models are compared with test results for plate-end debonding using a global energy balance approach (GEBA). A proposal is made for the use of one of the simplified models. The availability of a simplified model opens the way to the production of design aids so that the GEBA can be made available to practicing engineers through design guides and parametric studies. Copyright © 2014, American Concrete Institute.

High-level scene structure using visibility and occlusion

We demonstrate a new method for extracting high-level scene information from the type of data available from simultaneous localisation and mapping systems. We model the scene with a collection of primitives (such as bounded planes), and make explicit use of both visible and occluded points in order to refine the model. Since our formulation allows for different kinds of primitives and an arbitrary number of each, we use Bayesian model evidence to compare very different models on an even footing. Additionally, by making use of Bayesian techniques we can also avoid explicitly finding the optimal assignment of map landmarks to primitives. The results show that explicit reasoning about occlusion improves model accuracy and yields models which are suitable for aiding data association. © 2011. The copyright of this document resides with its authors.

Gastropods on submersed macrophytes in Yangtze lakes: Community characteristics and empirical modelling

Epiphytic gastropods in Yangtze lakes have suffered from large-scale declines of submersed macrophytes during past decades. To better understand what controls gastropod community, monthly investigations were carried out in four Yangtze lakes during December, 2001-March, 2003. Composed of 23 species belonging to Pulmonata and Prosobranchia, the community is characterized by the constitution of small individuals. The average density and biomass were 417 +/- 160 ind/m(2) and 18.05 +/- 7.43 g/m(2), with maxima a-round August. Submersed macrophyte biomass is shown to be the key factor affecting species number, density, and biomass of gastropods. Accordingly, a series of annual and seasonal models yielding high predictive powers were generated. Preference analyses demonstrated that pulmonates and prosobranchs with different respiratory organs prefer different macrophyte functional groups.

Fracture Properties of LPCVD Silicon Nitride and Thermally Grown Silicon Oxide Thin Films From the Load-Deflection of Long Si3N4 and SiO2/Si3N4 Diaphragms

The bulge test is successfully extended to the determination of the fracture properties of silicon nitride and oxide thin films. This is achieved by using long diaphragms made of silicon nitride single layers and oxide/nitride bilayers, and applying comprehensive mechanical model that describes the mechanical response of the diaphragms under uniform differential pressure. The model is valid for thin films with arbitrary z-dependent plane-strain modulus and prestress, where z denotes the coordinate perpendicular to the diaphragm. It takes into account the bending rigidity and stretching stiffness of the layered materials and the compliance of the supporting edges. This enables the accurate computation of the load-deflection response and stress distribution throughout the composite diaphragm as a function of the load, in particular at the critical pressure leading to the fracture of the diaphragms. The method is applied to diaphragms made of single layers of 300-nm-thick silicon nitride deposited by low-pressure chemical vapor deposition and composite diaphragms of silicon nitride grown on top of thermal silicon oxide films produced by wet thermal oxidation at 950 degrees C and 1050 degrees C with target thicknesses of 500, 750, and 1000 mn. All films characterized have an amorphous structure. Plane-strain moduli E-ps and prestress levels sigma(0) of 304.8 +/- 12.2 GPa and 1132.3 +/- 34.4 MPa, respectively, are extracted for Si3N4, whereas E-ps = 49.1 +/- 7.4 GPa and sigma(0) = -258.6 +/- 23.1 MPa are obtained for SiO2 films. The fracture data are analyzed using the standardized form of the Weibull distribution. The Si3N4 films present relatively high values of maximum stress at fracture and Weibull moduli, i.e., sigma(max) = 7.89 +/- 0.23 GPa and m = 50.0 +/- 3.6, respectively, when compared to the thermal oxides (sigma(max) = 0.89 +/- 0.07 GPa and m = 12.1 +/- 0.5 for 507-nm-thick 950 degrees C layers). A marginal decrease of sigma(max) with thickness is observed for SiO2, with no significant differences between the films grown at 950 degrees C and 1050 degrees C. Weibull moduli of oxide thin films are found to lie between 4.5 +/- 1.2 and 19.8 +/- 4.2, depending on the oxidation temperature and film thickness.

Atomic configurations of dislocation core and twin boundaries in 3C-SiC studied by high-resolution electron microscopy

The defects in 3C-SiC film grown on (001) plane of Si substrate were studied using a 200 kV high-resolution electron microscope with point resolution of 0.2 nm. A posterior image processing technique, the image deconvolution, was utilized in combination with the image contrast analysis to distinguish atoms of Si from C distant from each other by 0.109 nm in the [110] projected image. The principle of the image processing technique utilized and the related image contrast theory is briefly presented. The procedures of transforming an experimental image that does not reflect the crystal structure intuitively into the structure map and of identifying Si and C atoms from the map are described. The atomic configurations for a 30 degrees partial dislocation and a microtwin have been derived at atomic level. It has been determined that the 30 degrees partial dislocation terminates in C atom and the segment of microtwin is sandwiched between two 180 degrees rotation twins. The corresponding stacking sequences are derived and atomic models are constructed according to the restored structure maps for both the 30 degrees partial dislocation and microtwin. Images were simulated based on the two models to affirm the above-mentioned results.

A new development on ANN in China - Biomimetic pattern recognition and multi weight vector neurons

A new model of pattern recognition principles-Biomimetic Pattern Recognition, which is based on "matter cognition" instead of "matter classification", has been proposed. As a important means realizing Biomimetic Pattern Recognition, the mathematical model and analyzing method of ANN get breakthrough: a novel all-purpose mathematical model has been advanced, which can simulate all kinds of neuron architecture, including RBF and BP models. As the same time this model has been realized using hardware; the high-dimension space geometry method, a new means to analyzing ANN, has been researched.

Biomimetic (topological) pattern recognition - A new model of pattern recognition theory and its application

A new theoretical model of Pattern Recognition principles was proposed, which is based on "matter cognition" instead of "matter classification" in traditional statistical Pattern Recognition. This new model is closer to the function of human being, rather than traditional statistical Pattern Recognition using "optimal separating" as its main principle. So the new model of Pattern Recognition is called the Biomimetic Pattern Recognition (BPR)(1). Its mathematical basis is placed on topological analysis of the sample set in the high dimensional feature space. Therefore, it is also called the Topological Pattern Recognition (TPR). The fundamental idea of this model is based on the fact of the continuity in the feature space of any one of the certain kinds of samples. We experimented with the Biomimetic Pattern Recognition (BPR) by using artificial neural networks, which act through covering the high dimensional geometrical distribution of the sample set in the feature space. Onmidirectionally cognitive tests were done on various kinds of animal and vehicle models of rather similar shapes. For the total 8800 tests, the correct recognition rate is 99.87%. The rejection rate is 0.13% and on the condition of zero error rates, the correct rate of BPR was much better than that of RBF-SVM.

A new development on ANN in China - Biomimetic pattern recognition and multi weight vector neurons

A new model of pattern recognition principles-Biomimetic Pattern Recognition, which is based on "matter cognition" instead of "matter classification", has been proposed. As a important means realizing Biomimetic Pattern Recognition, the mathematical model and analyzing method of ANN get breakthrough: a novel all-purpose mathematical model has been advanced, which can simulate all kinds of neuron architecture, including RBF and BP models. As the same time this model has been realized using hardware; the high-dimension space geometry method, a new means to analyzing ANN, has been researched.

Cure processing modeling and cure cycle simulation of epoxy-terminated poly(phenylene ether ketone) .2. Chemorheological modeling

Chemorheology and corresponding models for an epoxy-terminated poly(phenylene ether ketone) (E-PEK) and 4,4'-diaminodiphenyl sulfone (DDS) system were investigated using a differential scanning calorimeter (DSC) and a cone-and-plate rheometer. For this system, the reported four-parameter chemorheological model and modified WLF chemorheological model can only be used in an isothermal or nonisothermal process, respectively. In order to predict the resin viscosity variation during a stepwise temperature cure cycle actually used, a new model based on the combination of the four-parameter model and the modified WLF model was developed. The combined model can predict the resin viscosity variation during a stepwise temperature cure cycle more accurately than the above two models. In order to simplify the establishment of this model, a new five-parameter chemorheological model was then developed. The parameters in this five-parameter model can be determined through very few rheology and DSC experiments. This model is practicable to describe the resin viscosity variation for isothermal, nonisothermal, or stepwise temperature cure cycles accurately. The five-parameter chemorheological model has also successfully been used in the E-PEK systems with two other curing agents, i.e., the diamine curing agent with the addition of a boron trifluride monoethylamine (BF3-MEA) accelerator and an anhydride curing agent (hexahydrophthalic acid anhydride). (C) 1997 John Wiley & Sons, Inc.

An estimate of divergence time of parazoa and eumetazoa and that of cephalochordata and vertebrata by aldolase and triose phosphate isomerase clocks

Previously we suggested that four proteins including aldolase and triose phosphate isomerase (TPI) evolved with approximately constant rates over long periods covering the whole animal phyla. The constant rates of aldolase and TPI evolution were reexamined based on three different models for estimating evolutionary distances, It was shown that the evolutionary rates remain essentially unchanged in comparisons not only between different classes of vertebrates but also between vertebrates and arthropods and even between animals and plants, irrespective of the models used, Thus these enzymes might be useful molecular clocks for inferring divergence times of animal phyla, To know the divergence time of Parazoa and Eumetazoa and that of Cephalochordata and Vertebrata, the aldolase cDNAs from Ephydatia fluviatilis, a freshwater sponge, and the TPI cDNAs from Ephydatia fluviatilis and Branchiostoma belcheri an amphioxus, have been cloned and sequenced, Comparisons of the deduced amino acid sequences of aldolase and TPI from the freshwater sponge with known sequences revealed that the Parazoa-Eumetazoa split occurred about 940 million years ago (Ma) as determined by the average of two proteins and three models, Similarly, the aldolase and TPI clocks suggest that vertebrates and amphioxus last shared a common ancestor around 700 Ma and they possibly diverged shortly after the divergence of deuterostomes and protostomes.

Variations in the eastern Indian Ocean warm pool and its relation to the dipole in the tropical Indian Ocean

Based on the monthly average SST and 850 hPa monthly average wind data, the seasonal, interannual and long-term variations in the eastern Indian Ocean warm pool (EIWP) and its relationship to the Indian Ocean Dipole (IOD), and its response to the wind over the Indian Ocean are analyzed in this study. The results show that the distribution range, boundary and area of the EIWP exhibited obviously seasonal and interannual variations associated with the ENSO cycles. Further analysis suggests that the EIWP had obvious long-term trend in its bound edge and area, which indicated the EIWP migrated westwards by about 14 longitudes for its west edge, southwards by about 5 latitudes for its south edge and increased by 3.52x10(6) km(2) for its area, respectively, from 1950 to 2002. The correlation and composite analyses show that the anomalous westward and northward displacements of the EIWP caused by the easterly wind anomaly and the southerly wind anomaly over the eastern equatorial Indian Ocean played an important and direct role in the formation of the IOD.