Parametric study of the behaviour of reinforced concrete columns in fire

The research is concerned with the application of the computer simulation technique to study the performance of reinforced concrete columns in a fire environment. The effect of three different concrete constitutive models incorporated in the computer simulation on the structural response of reinforced concrete columns exposed to fire is investigated. The material models differed mainly in respect to the formulation of the mechanical properties of concrete. The results from the simulation have clearly illustrated that a more realistic response of a reinforced concrete column exposed to fire is given by a constitutive model with transient creep or appropriate strain effect The assessment of the relative effect of the three concrete material models is considered from the analysis by adopting the approach of a parametric study, carried out using the results from a series of analyses on columns heated on three sides which produce substantial thermal gradients. Three different loading conditions were used on the column; axial loading and eccentric loading both to induce moments in the same sense and opposite sense to those induced by the thermal gradient. An axially loaded column heated on four sides was also considered. The computer modelling technique adopted separated the thermal and structural responses into two distinct computer programs. A finite element heat transfer analysis was used to determine the thermal response of the reinforced concrete columns when exposed to the ISO 834 furnace environment. The temperature distribution histories obtained were then used in conjunction with a structural response program. The effect of the occurrence of spalling on the structural behaviour of reinforced concrete column is also investigated. There is general recognition of the potential problems of spalling but no real investigation into what effect spalling has on the fire resistance of reinforced concrete members. In an attempt to address the situation, a method has been developed to model concrete columns exposed to fire which incorporates the effect of spalling. A total of 224 computer simulations were undertaken by varying the amounts of concrete lost during a specified period of exposure to fire. An array of six percentages of spalling were chosen for one range of simulation while a two stage progressive spalling regime was used for a second range. The quantification of the reduction in fire resistance of the columns against the amount of spalling, heating and loading patterns, and the time at which the concrete spalls appears to indicate that it is the amount of spalling which is the most significant variable in the reduction of fire resistance

Figures of merit and constraints from testing General Relativity using the latest cosmological data sets including refined COSMOS 3D weak lensing

We use cosmological constraints from current data sets and a figure of merit (FoM) approach to probe any deviations from general relativity (GR) at cosmological scales. The FoM approach is used to study the constraining power of various combinations of data sets on modified gravity (MG) parameters. We use recently refined HST-COSMOS weak-lensing tomography data, ISW-galaxy cross correlations from 2MASS and SDSS LRG surveys, matter power spectrum from SDSS-DR7 (MPK), WMAP7 temperature and polarization spectra, BAO from 2DF and SDSS-DR7, and Union2 compilation of supernovae, in addition to other bounds from H_0 measurements and BBN. We use 3 parametrizations of MG parameters that enter the perturbed field equations. In order to allow for variations with redshift and scale, the first 2 parametrizations use recently suggested functional forms while the third is based on binning methods. Using the first parametrization, we find that CMB + ISW + WL provides the strongest constraints on MG parameters followed by CMB+WL or CMB+MPK+ISW. Using the second parametrization or binning methods, CMB+MPK+ISW consistently provides some of the strongest constraints. This shows that the constraints are parametrization dependent. We find that adding up current data sets does not improve consistently uncertainties on MG parameters due to tensions between best-fit MG parameters preferred by different data sets. Furthermore, some functional forms imposed by the parametrizations can lead to an exacerbation of these tensions. Next, unlike some studies that used the CFHTLS lensing data, we do not find any deviation from GR using the refined HST-COSMOS data, confirming previous claims in those studies that their result may have been due to some systematic effect. Finally, we find in all cases that the values corresponding to GR are within the 95% confidence level contours for all data set combinations. (abridged)Comment: 18 pages, 6 figures, matches version published in PR

Alternative Methods of Describing Structure Formation in the Lemaitre-Tolman Model

We describe several new ways of specifying the behaviour of Lemaitre-Tolman (LT) models, in each case presenting the method for obtaining the LT arbitrary functions from the given data, and the conditions for existence of such solutions. In addition to our previously considered `boundary conditions', the new ones include: a simultaneous big bang, a homogeneous density or velocity distribution in the asymptotic future, a simultaneous big crunch, a simultaneous time of maximal expansion, a chosen density or velocity distribution in the asymptotic future, only growing or only decaying fluctuations. Since these conditions are combined in pairs to specify a particular model, this considerably increases the possible ways of designing LT models with desired properties.Comment: Accepted by Phys Rev D. RevTeX 4, 13 pages, no figures. Part of a series: gr-qc/0106096, gr-qc/0303016, gr-qc/0309119. Replacement contains very minor correction

Failure Investigation of a Fill Slope in Putrajaya, Malaysia

On 6th of January 2001, a fill slope collapsed in Putrajaya, Malaysia. The failed slope was 25m in height. The failure caused the slope to pushed two reinforced earth walls and the recently completed jetty and boat docking facilities to collapse. The depth of the failure scar was about 2m with a failure length of about 50m. A failure investigation was then carried out to determine the causes of failure. A total of thirteen new boreholes, fifteen Mackintosh probes and three hand augers were carried out to determine the soil profile. A desk study of existing information and records, site reconnaissance and mapping of the failure area was also carried out to determine the causes and the extent of the failure. Some of the findings of the failure investigation are there were no pile slab found at reinforced earth wall W2 as stated in the drawings and the groundwater table has risen as a result of the filling of the lake, which was carried out after the construction of the fill slope. The groundwater table at failure was found to be much higher than those measured during the site investigation works. Seepages of water were also seen from the failed area

Probing Cosmic Acceleration Beyond the Equation of State: Distinguishing between Dark Energy and Modified Gravity Models

If general relativity is the correct theory of physics on large scales, then there is a differential equation that relates the Hubble expansion function, inferred from measurements of angular diameter distance and luminosity distance, to the growth rate of large scale structure. For a dark energy fluid without couplings or an unusual sound speed, deviations from this consistency relationship could be the signature of modified gravity on cosmological scales. We propose a procedure based on this consistency relation in order to distinguish between some dark energy models and modified gravity models. The procedure uses different combinations of cosmological observations and is able to find inconsistencies when present. As an example, we apply the procedure to a universe described by a recently proposed 5-dimensional modified gravity model. We show that this leads to an inconsistency within the dark energy parameter space detectable by future experiments.Comment: 8 pages, 7 figures; expanded paper; matches PRD accepted version; corrected growth rate formula; main results and conclusion unchange

Large scale structure simulations of inhomogeneous LTB void models

We perform numerical simulations of large scale structure evolution in an inhomogeneous Lemaitre-Tolman-Bondi (LTB) model of the Universe. We follow the gravitational collapse of a large underdense region (a void) in an otherwise flat matter-dominated Einstein-deSitter model. We observe how the (background) density contrast at the centre of the void grows to be of order one, and show that the density and velocity profiles follow the exact non-linear LTB solution to the full Einstein equations for all but the most extreme voids. This result seems to contradict previous claims that fully relativistic codes are needed to properly handle the non-linear evolution of large scale structures, and that local Newtonian dynamics with an explicit expansion term is not adequate. We also find that the (local) matter density contrast grows with the scale factor in a way analogous to that of an open universe with a value of the matter density OmegaM(r) corresponding to the appropriate location within the void.Comment: 7 pages, 6 figures, published in Physical Review

Compact structure representation in discovering frequent patterns for association rules

Frequent pattern mining is a key problem in important data mining applications, such as the discovery of association rules, strong rules and episodes. Structure used in typical algorithms for solving this problem operate in several database scans and a large number of candidate generation. This paper presents a compact structure representation called Flex-tree in discovering frequent patterns for association rules. Flex-tree structure is a lexicographic tree which finds frequent patterns by using depth first search strategy. Efficiency of mining is achieved with one scan of database instead of repeated database passes done in other methods and avoid the costly generation of large numbers of candidate sets, which dramatically reduces the search space

Impact of Auditory Affect on Urgent Behaviors on a Car Simulator

Emotional content abounds the driver in different forms from billboard signs to in-vehicle devices to roadside situations. Such emotional scenes can result in unsafe driving behaviors and lead to collisions due to their ability to attract attentional resources and change driving goals to irrelevant ones (Megías et al. 2011b; Briggs et al, 2011). Recent studies have looked at the way auditory and visual emotional stimuli can impact individual’s decision under Evaluative and Urgent road environment behaviors. Evaluative behaviors are known as a categorization in which people judge a scene as risky or not, whereas Urgent behaviors are time sensitive, requiring a person to quickly respond to the scene in order to avoid negative consequences (Megias et al, 2011a). Previous research has examined the way visual emotional stimuli affects driving performance; however, relatively little is known about the effects of auditory emotional stimuli (Chan, & Singhal, 2014). Among studies that examined both types of behaviors while participants viewed images depicting a driving scenario, auditory emotional stimuli served to speed Evaluative judging (judge whether the scene is risky or not), but not under Urgent judging (judge whether to brake or not) (Serrano, et al, 2013). It was also found that negative sounds lead to more performance errors in driving (Chan, & Singhal, 2014). The current study is designed to further examine a number of task features using a medium fidelity (GE Patrol SIM) driving simulator. Urgent behaviors related to a risky driving scenario and auditory sounds will be used. Using the motivational model of emotion looking at evolutionary flight-and-fight mechanisms (Bradley et al., 2001; Lang et al. 2008), we would, in contrast to previous studies of urgent behaviors, expect to find a difference under emotional content when participants drive a car simulator. A car simulator is able to mimic a real driving environment than looking at a static picture done in Serrano et al (2013). This study aims to empirically examine the effects of driver urgent behavior and time pressure on driver’s hazard perception in a controlled driving simulation. In this experiment, a car following scene with sudden car decelerations will measure participant’s braking, steering, and speed behavior. Participants will drive while listening to emotionally charged auditory sounds that vary in valence and arousal. Valence is how pleasant to unpleasant a stimulus is, whereas arousal is how stimulating to unstimulating a stimulus is. Emotional sounds will be instigated before a braking event occurs and will be randomized. Based on theoretical principles of the motivation model of emotion, it is hypothesized that highly arousing unpleasant sounds would have a higher impact on driving performance than pleasant and neutral sounds. Theoretical and practical implications will also be discussed

Obtaining the spacetime metric from cosmological observations

Recent galaxy redshift surveys have brought in a large amount of accurate cosmological data out to redshift 0.3, and future surveys are expected to achieve a high degree of completeness out to a redshift exceeding 1. Consequently, a numerical programme for determining the metric of the universe from observational data will soon become practical; and thereby realise the ultimate application of Einstein's equations. Apart from detailing the cosmic geometry, this would allow us to verify and quantify homogeneity, rather than assuming it, as has been necessary up to now, and to do that on a metric level, and not merely at the mass distribution level. This paper is the beginning of a project aimed at such a numerical implementation. The primary observational data from our past light cone consists of galaxy redshifts, apparent luminosities, angular diameters and number densities, together with source evolution functions, absolute luminosities, true diameters and masses of sources. Here we start with the simplest case, that of spherical symmetry and a dust equation of state, and execute an algorithm that determines the unknown metric functions from this data. We discuss the challenges of turning the theoretical algorithm into a workable numerical procedure, particularly addressing the origin and the maximum in the area distance. Our numerical method is tested with several artificial data sets for homogeneous and inhomogeneous models, successfully reproducing the original models. This demonstrates the basic viability of such a scheme. Although current surveys don't have sufficient completeness or accuracy, we expect this situation to change in the near future, and in the meantime there are many refinements and generalisations to be added.Comment: 26 pages, 10 figures. Minor changes to match the published versio

Wavelet-based short-term load forecasting using optimized anfis

This paper focuses on forecasting electric load consumption using optimized Adaptive Neuro-Fuzzy inference System (ANFIS). It employs the use of Particle Swarm Optimization (PSO) to optimize ANFIS, with aim of improving its speed and accuracy. It determines the minimum error from the ANFIS error function and thus propagates it to the premise part. Wavelet transform was used to decompose the input variables using Daubechies 2 (db2). The purpose is to reduce outliers as small as possible in the forecasting data. The data was decomposed in to one approximation coefficients and three details coefficients. The combined Wavelet-PSO-ANFIS model was tested using weather and load data of Nova Scotia province. It was found that the model can perform more than Genetic Algorithm (GA) optimized ANFIS and traditional ANFIS, which is been optimized by Gradient Decent (GD). Mean Absolute Percentage Error (MAPE) was used to measure the accuracy of the model. The model gives lower MAPE than the other two models, and is faster in terms of speed of convergence