Fatigue Laws Via Functional Equations

In routine industrial design, fatigue life estimation is largely based on S-N curves and ad hoc cycle counting algorithms used with Miner's rule for predicting life under complex loading. However, there are well known deficiencies of the conventional approach. Of the many cumulative damage rules that have been proposed, Manson's Double Linear Damage Rule (DLDR) has been the most successful. Here we follow up, through comparisons with experimental data from many sources, on a new approach to empirical fatigue life estimation (A Constructive Empirical Theory for Metal Fatigue Under Block Cyclic Loading', Proceedings of the Royal Society A, in press). The basic modeling approach is first described: it depends on enforcing mathematical consistency between predictions of simple empirical models that include indeterminate functional forms, and published fatigue data from handbooks. This consistency is enforced through setting up and (with luck) solving a functional equation with three independent variables and six unknown functions. The model, after eliminating or identifying various parameters, retains three fitted parameters; for the experimental data available, one of these may be set to zero. On comparison against data from several different sources, with two fitted parameters, we find that our model works about as well as the DLDR and much better than Miner's rule. We finally discuss some ways in which the model might be used, beyond the scope of the DLDR.

Numerical prediction of load-displacement behaviors of adhesively bonded joints at different extension rates and temperatures

The present work focuses on simulation of nonlinear mechanical behaviors of adhesively bonded DLS (double lap shear) joints for variable extension rates and temperatures using the implicit ABAQUS solver. Load-displacement curves of DLS joints at nine combinations of extension rates and environmental temperatures are initially obtained by conducting tensile tests in a UTM. The joint specimens are made from dual phase (DP) steel coupons bonded with a rubber-toughened adhesive. It is shown that the shell-solid model of a DLS joint, in which substrates are modeled with shell elements and adhesive with solid elements, can effectively predict the mechanical behavior of the joint. Exponent Drucker-Prager or Von Mises yield criterion together with nonlinear isotropic hardening is used for the simulation of DLS joint tests. It has been found that at a low temperature (-20 degrees C), both Von Mises and exponent Drucker-Prager criteria give close prediction of experimental load-extension curves. However. at a high temperature (82 degrees C), Von Mises condition tends to yield a perceptibly softer joint behavior, while the corresponding response obtained using exponent Drucker-Prager criterion is much closer to the experimental load-displacement curve.

Consolidation Behavior of Soils

Based on Terzaghi's consolidation theory, percent of consolidation, U, versus the time factor, T, relationship for constant/linear excess pore water pressure distribution, it is possible to generate theoretical log10(H2/t) versus U curves where H is the length of the drainage path of a consolidating layer, and t is the time for different known values of the coefficient of consolidation, cν. A method has been developed wherein both the theoretical and experimental behavior of soils during consolidation can be simultaneously compared and studied on the same plot. The experimental log10(H2/t) versus U curves have been compared with the theoretical curves. The deviations of the experimental behavior from the theory are explained in terms of initial compression and secondary compression. Analysis of results indicates that the secondary compression essentially starts from about 60% consolidation. A simple procedure is presented for calculating the value of cv from the δ-t data using log10(H2/t) versus U plot.

Melanopsin mediated post-illumination pupil response in early age-related macular degeneration

Purpose To determine whether melanopsin expressing intrinsically photosensitive Retinal Ganglion Cell (ipRGC) inputs to the pupil light reflex (PLR) are affected in early age-related macular degeneration (AMD). Methods The PLR was measured in 40 participants (20 early AMD and 20 age-matched controls) using a custom-built Maxwellian-view pupillometer. Sinusoidal stimuli (0.5 Hz, 11.9 s duration, 35.6° diameter) were presented to the study eye and the consensual pupil response was measured for stimuli with high melanopsin excitation (464nm; blue) and with low melanopsin excitation (638 nm; red) that biased activation to the outer retina. Two melanopsin PLR metrics were quantified: the Phase Amplitude Percentage (PAP) during the sinusoidal stimulus presentation and the Post-Illumination Pupil Response (PIPR). The PLR during stimulus presentation was analyzed using latency to constriction, transient pupil response and maximum pupil constriction metrics. Diagnostic accuracy was evaluated using receiver operating characteristic (ROC) curves. Results The blue PIPR was significantly less sustained in the early AMD group (p<0.001). The red PIPR was not significantly different between groups (p>0.05). The PAP and blue stimulus constriction amplitude were significantly lower in the early AMD group (p < 0.05). There was no significant difference between groups in the latency or transient amplitude for both stimuli (p>0.05). ROC analysis showed excellent diagnostic accuracy for the blue PIPR metrics (AUC>0.9). Conclusions This is the initial report that the melanopsin controlled PIPR is dysfunctional in early AMD. The non-invasive, objective measurement of the ipRGC controlled PIPR has excellent diagnostic accuracy for early AMD.

Ion beam processing of oriented CuO films deposited on (100) YSZ by laser ablation

A systematic study of Ar ion implantation in cupric oxide films has been reported. Oriented CuO films were deposited by pulsed excimer laser ablation technique on (1 0 0) YSZ substrates. X-ray diffraction (XRD) spectra showed the highly oriented nature of the deposited CuO films. The films were subjected to ion bombardment for studies of damage formation, Implantations were carried out using 100 keV Arf over a dose range between 5 x 10(12) and 5 x 10(15) ions/cm(2). The as-deposited and ion beam processed samples were characterized by XRD technique and resistance versus temperature (R-T) measurements. The activation energies for electrical conduction were found from In [R] versus 1/T curves. Defects play an important role in the conduction mechanism in the implanted samples. The conductivity of the film increases, and the corresponding activation energy decreases with respect to the dose value.

Miniature cone tip resistance of sand with fly ash using triaxial setup

In a continuation of the authors' recent work, the ultimate tip resistance of a miniature cone using triaxial equipment was determined for samples of dry sand mixed with dry fly ash. The effect of (i) the proportion of fly ash, (ii) the relative density of samples, and (iii) the vertical overburden pressure was examined. It was noted that an addition of fly ash in sand for the same range of relative density leads to a significant reduction in the ultimate tip resistance of the cone (q(cu)). This occurs due to a decrease in the friction angle (phi) of the sample with an increase in the fly ash content for a given relative density. For phi greater than about 30 degrees, two widely used correlation curves from published literature, providing the relationships between q(cu) and phi for cohesionless soils, were found to provide satisfactory predictions, even for sand - fly ash mixtures. As was expected, the values of qcu increase continuously with an increase in the relative density of the soil mass and the vertical effective ( overburden) stress on the sample.

An experimental study on anisotropic mechanical properties of porcine thoracic aorta

Objective: To study the anisotropic mechanical properties of the thoracic aorta in porcine. Methods: Twenty-one porcine thoracic aortas were collected and categorized into three groups. The aortas were then cut through in their axial directions and expanded into two-dimensional planes. Then, by setting the length direction of the planar aortas (i.e., axial directions of the aortas) as 0°, each planar aorta was counterclockwisely cut into 8 samples with orientation of 30°, 45°, 60°, 90°, 120°, 135°, 150° and 180°, respectively. Finally, the uniaxial tensile tests were applied on three groups of samples at the loading rates of 1, 5 and 10 mm/min, respectively, to obtain the elastic modulus and ultimate stress of the aorta in different directions and at different loading rates. Results: The stress-strain curves exhibited different viscoelastic behaviors. With the increase of sample orientations, the elastic modulus gradually increased from 30°, reached the maximum value at 90°, and then gradually decreased till 180°. The variation trend of ultimate stress was similar to that of elastic modulus. Moreover, different loading rates showed a significant influence on the results of elastic modulus and ultimate stress, but a weak influence on the anisotropic degree. Conclusions: The porcine thoracic aorta is highly anisotropic. This research finding provides parameter references for assignment of material properties in finite element modeling, and is significant for understanding biomechanical properties of the arteries.

A pilot study in different unstable designs on the biomechanical effect of gait characteristics

The purpose of this study was to compare kinematics and kinetics during walking for healthy subjects using unstable shoes with different designs. Ten subjects participated in this study, and foot biomechanical data during walking were quantified using motion analysis system and a force plate. Data were collected for unstable shoes condition after accommodation period of one week. With soft material added in the heel region, the peak impact force was effectively reduced when compared among similar shapes. In addition, the soft material added in the rocker bottom showed more to be in dorsiflexed position during the initial stance. The shoe with three rocker curves design reduced the contact area in the heel strike, which may result in increasing human body forward speed. Further studies shall be carried out after adapting to long periods of wearing unstable shoes.

On optimum stratification with proportional allocation for a class of pareto distributions

Cum ./LSTA_A_8828879_O_XML_IMAGES/LSTA_A_8828879_O_ILM0001.gif rule [Singh (1975)] has been suggested in the literature for finding approximately optimum strata boundaries for proportional allocation, when the stratification is done on the study variable. This paper shows that for the class of density functions arising from the Wang and Aggarwal (1984) representation of the Lorenz Curve (or DBV curves in case of inventory theory), the cum ./LSTA_A_8828879_O_XML_IMAGES/LSTA_A_8828879_O_ILM0002.gif rule in place of giving approximately optimum strata boundaries, yields exactly optimum boundaries. It is also shown that the conjecture of Mahalanobis (1952) “. . .an optimum or nearly optimum solutions will be obtained when the expected contribution of each stratum to the total aggregate value of Y is made equal for all strata” yields exactly optimum strata boundaries for the case considered in the paper.

Massive black-hole binary inspirals: results from the LISA parameter estimation taskforce

The LISA Parameter Estimation Taskforce was formed in September 2007 to provide the LISA Project with vetted codes, source distribution models and results related to parameter estimation. The Taskforce's goal is to be able to quickly calculate the impact of any mission design changes on LISA's science capabilities, based on reasonable estimates of the distribution of astrophysical sources in the universe. This paper describes our Taskforce's work on massive black-hole binaries (MBHBs). Given present uncertainties in the formation history of MBHBs, we adopt four different population models, based on (i) whether the initial black-hole seeds are small or large and (ii) whether accretion is efficient or inefficient at spinning up the holes. We compare four largely independent codes for calculating LISA's parameter-estimation capabilities. All codes are based on the Fisher-matrix approximation, but in the past they used somewhat different signal models, source parametrizations and noise curves. We show that once these differences are removed, the four codes give results in extremely close agreement with each other. Using a code that includes both spin precession and higher harmonics in the gravitational-wave signal, we carry out Monte Carlo simulations and determine the number of events that can be detected and accurately localized in our four population models.

On Visual Detection of Highly-occluded Objects for Harvesting Automation in Horticulture

Developing accurate and reliable crop detection algorithms is an important step for harvesting automation in horticulture. This paper presents a novel approach to visual detection of highly-occluded fruits. We use a conditional random field (CRF) on multi-spectral image data (colour and Near-Infrared Reflectance, NIR) to model two classes: crop and background. To describe these two classes, we explore a range of visual-texture features including local binary pattern, histogram of oriented gradients, and learn auto-encoder features. The pro-posed methods are evaluated using hand-labelled images from a dataset captured on a commercial capsicum farm. Experimental results are presented, and performance is evaluated in terms of the Area Under the Curve (AUC) of the precision-recall curves.Our current results achieve a maximum performance of 0.81AUC when combining all of the texture features in conjunction with colour information.

Statistical modelling and power analysis for detecting trends in total suspended sediment loads

The export of sediments from coastal catchments can have detrimental impacts on estuaries and near shore reef ecosystems such as the Great Barrier Reef. Catchment management approaches aimed at reducing sediment loads require monitoring to evaluate their effectiveness in reducing loads over time. However, load estimation is not a trivial task due to the complex behaviour of constituents in natural streams, the variability of water flows and often a limited amount of data. Regression is commonly used for load estimation and provides a fundamental tool for trend estimation by standardising the other time specific covariates such as flow. This study investigates whether load estimates and resultant power to detect trends can be enhanced by (i) modelling the error structure so that temporal correlation can be better quantified, (ii) making use of predictive variables, and (iii) by identifying an efficient and feasible sampling strategy that may be used to reduce sampling error. To achieve this, we propose a new regression model that includes an innovative compounding errors model structure and uses two additional predictive variables (average discounted flow and turbidity). By combining this modelling approach with a new, regularly optimised, sampling strategy, which adds uniformity to the event sampling strategy, the predictive power was increased to 90%. Using the enhanced regression model proposed here, it was possible to detect a trend of 20% over 20 years. This result is in stark contrast to previous conclusions presented in the literature. (C) 2014 Elsevier B.V. All rights reserved.

Generalised growth models for aquatic species with an application to blacklip abalone (Haliotis rubra)

This paper presents a maximum likelihood method for estimating growth parameters for an aquatic species that incorporates growth covariates, and takes into consideration multiple tag-recapture data. Individual variability in asymptotic length, age-at-tagging, and measurement error are also considered in the model structure. Using distribution theory, the log-likelihood function is derived under a generalised framework for the von Bertalanffy and Gompertz growth models. Due to the generality of the derivation, covariate effects can be included for both models with seasonality and tagging effects investigated. Method robustness is established via comparison with the Fabens, improved Fabens, James and a non-linear mixed-effects growth models, with the maximum likelihood method performing the best. The method is illustrated further with an application to blacklip abalone (Haliotis rubra) for which a strong growth-retarding tagging effect that persisted for several months was detected

Sediment concentration prediction and statistical evaluation for annual load estimation

We consider the development of statistical models for prediction of constituent concentration of riverine pollutants, which is a key step in load estimation from frequent flow rate data and less frequently collected concentration data. We consider how to capture the impacts of past flow patterns via the average discounted flow (ADF) which discounts the past flux based on the time lapsed - more recent fluxes are given more weight. However, the effectiveness of ADF depends critically on the choice of the discount factor which reflects the unknown environmental cumulating process of the concentration compounds. We propose to choose the discount factor by maximizing the adjusted R-2 values or the Nash-Sutcliffe model efficiency coefficient. The R2 values are also adjusted to take account of the number of parameters in the model fit. The resulting optimal discount factor can be interpreted as a measure of constituent exhaustion rate during flood events. To evaluate the performance of the proposed regression estimators, we examine two different sampling scenarios by resampling fortnightly and opportunistically from two real daily datasets, which come from two United States Geological Survey (USGS) gaging stations located in Des Plaines River and Illinois River basin. The generalized rating-curve approach produces biased estimates of the total sediment loads by -30% to 83%, whereas the new approaches produce relatively much lower biases, ranging from -24% to 35%. This substantial improvement in the estimates of the total load is due to the fact that predictability of concentration is greatly improved by the additional predictors.

A simple Bayesian decision-theoretic design for dose-finding trials

A flexible and simple Bayesian decision-theoretic design for dose-finding trials is proposed in this paper. In order to reduce the computational burden, we adopt a working model with conjugate priors, which is flexible to fit all monotonic dose-toxicity curves and produces analytic posterior distributions. We also discuss how to use a proper utility function to reflect the interest of the trial. Patients are allocated based on not only the utility function but also the chosen dose selection rule. The most popular dose selection rule is the one-step-look-ahead (OSLA), which selects the best-so-far dose. A more complicated rule, such as the two-step-look-ahead, is theoretically more efficient than the OSLA only when the required distributional assumptions are met, which is, however, often not the case in practice. We carried out extensive simulation studies to evaluate these two dose selection rules and found that OSLA was often more efficient than two-step-look-ahead under the proposed Bayesian structure. Moreover, our simulation results show that the proposed Bayesian method's performance is superior to several popular Bayesian methods and that the negative impact of prior misspecification can be managed in the design stage.