Extracting Knowledge of Concrete Shear Strength from Artificial Neural Networks

This article introduces an artificial neural network (ANN) to estimate the shear strength of reinforced concrete beams. Current methods for calculating shear strength use a model that is based on engineering mechanics and empirical values determined though testing of a beam failing due to shear. The current methods are intended to provide a conservative lower bound on the strength needed to prevent a shear failure. A database containing the results of over 1200 laboratory shear strength tests was used to train an ANN. The database contained the geometric and material property data from the test specimens and the recorded failure load. The ANN presented in this paper was able to predict the shear strength of reinforced concrete beams more accurately than the current approach. The ANN provides additional insight on the parameters that are most significant in estimating concrete shear strength, which may lead to a better understanding of the mechanism of shear failure

Kinetic Monte Carlo Study of the Atomic Layer Deposition of Zinc Oxide

Atomic layer deposition (ALD) has emerged as an important technique for thin film deposition in the last two decades. Zinc oxide thin films, usually grown via DEZ/H2O-process, have seen much interest both in application and in theoretical research. The surface processes related to the growth of the thin film are not entirely understood and the conceptual picture of the ALD process has been contradicted by recent experiments where ligands from the zinc pulse persist on the surface even after extended water pulse exposures. In this work, we investigate the overall growth of the zinc oxide thin films grown via DEZ/H2O-process by modelling the surface chemistry using first principles kinetic Monte Carlo for the first time. The kinetic Monte Carlo allows us to implement density functional theory calculations conducted on zinc oxide (100) surface into a kinetic model and extract data directly comparable to experimental measurements. The temperature dependent growth profile obtained from our model is in good qualitative agreement with the experimental data. The onset of thin film growth is offset from the experimentally data due to the underestimation of the reaction barriers within density functional theory. The growth per cycle of the deposited film is overestimated by 18% in the kinetic model. Mass-gain during an ALD cycle is in qualitative agreement with experimental quartz-crystal microbalance data. The main mass-gain within an ALD cycle is obtained during the DEZ pulse and mass-change during the water pulse negligible. The cause of low film growth at low temperatures is due to the high reaction barriers for ethyl-elimination during the water pulse. This kinetic barrier results in low film growth as no new DEZ can adsorb to the ethyl-saturated surface. At elevated temperatures ethyl-elimination becomes accessible, resulting in the ideal layer-by-layer growth of the film. However, a large fraction of ethyl-ligands persist on the surface after each ALD cycle even at high temperatures. This results in ethyl-ligands being encapsulated into the film lattice. This is likely due to an incomplete set of reaction pathways and it is likely that some yet unidentified process is responsible for the elimination of the ethyl-ligands from the surface as the deposition process progresses.Peer reviewe

CFD investigation of balcony spill plumes in atria

Smoke management in buildings during fire events often uses mechanical ventilation systems to maintainsmoke layer elevation above a safe evacuation path. Design of these systems requires accuratecorrelations for the smoke production rate of the buoyant fire plume. One design issue is the smokeproduction rate of fire plumes which spill out from a fire compartment, under a balcony and up through anatrium or other large volume. Current engineering correlations for these balcony spill plumes are basedon a combination of one-tenth scale test data and theoretical analysis. Questions have arisen over thesuitability of these correlations for real-scale designs. A combined program of full-scale experimentationand CFD modeling is being conducted to analyze the accuracy of these correlations.Dans la gestion de la fum\ue9e dans les \ue9difices o\uf9 \ue9clate un incendie, c'est souvent un syst\ue8me d'extraction m\ue9canique qui sert \ue0 maintenir les couches de fum\ue9e \ue0 un niveau plus haut qu'une voie d'\ue9vacuation s\ue9curitaire donn\ue9e. La conception de tels syst\ue8mes requiert que soient \ue9tablies des corr\ue9lations pr\ue9cises relativement au taux de production de fum\ue9e du panache de flammes flottant. Le taux de production de fum\ue9e des panaches que d\ue9gage un compartiment o\uf9 un feu a \ue9clat\ue9 et qui l\ue8chent le dessous d'un balcon pour s'\ue9lever \ue0 l'int\ue9rieur d'un atrium ou autre espace \ue0 fort volume constitue un probl\ue8me pour la conception. Les corr\ue9lations d'ing\ue9nierie actuelles pour ces panaches d\ue9gag\ue9s sous les balcons sont fond\ue9es sur une utilisation combin\ue9e de donn\ue9es d'essais \ue0 l'\ue9chelle d'un dixi\ue8me et d'analyses th\ue9oriques. La pertinence de telles corr\ue9lations pour des conceptions en vraie grandeur a soulev\ue9 des questions. On dirige actuellement un programme mixte d'exp\ue9rimentation en vraie grandeur et de mod\ue9lisation de m\ue9canique des fluides computationnelle (CFD) dans le but d'analyser le degr\ue9 de pr\ue9cision de ces corr\ue9lations.Peer reviewed: YesNRC publication: Ye

CFD investigation of balcony spill plumes in atria

This paper demonstrates an integrated method for using experimental data and computational fluid dynamics modeling to design smoke management for atriums and other large building volumes. By means of full-scale experimentation and computational fluid dynamics modeling, the research correlated the combination of one-tenth scale experimental data and theoretical analysis used for simulating fire conditions to full-scale designs.Dans ce rapport, on d\ue9crit une m\ue9thode int\ue9gr\ue9e permettant d'utiliser les donn\ue9es exp\ue9rimentales et la mod\ue9lisation de la dynamique des fluides computationnelle pour g\ue9rer la fum\ue9e dans les atriums et d'autres grands volumes de b\ue2timents. \uc0 partir d'exp\ue9riences en vraie grandeur et d'une mod\ue9lisation de dynamique des fluides computationnelle, les chercheurs ont \ue9tabli une corr\ue9lation entre les donn\ue9es exp\ue9rimentales \ue0 l'\ue9chelle 1 : 10 combin\ue9es \ue0 l'analyse th\ue9orique utilis\ue9e pour simuler les conditions d'incendie et les mod\ue8les en vraie grandeur.Peer reviewed: YesNRC publication: Ye

FEDSM2002-31171 VECTOR POSTIONING FOR CROSS CORRELATION PIV

ABSTRACT Continuing advances in digital imaging technology stimulate greater interest in applying particle image velocimetry (PIV) over increasingly larger fields of view. Unfortunately when larger fields of view are analyzed, velocity gradients in the image become more localized. In addition, non-uniformities in image illumination and particle number density become more prevalent. These factors, coupled with the requirement that large areas of interest (AOIs) must be employed to measure the full range of velocity, cause degradation of correlation results (i.e. broadening and/or splintering of the cross correlation peak) which leads to positional bias errors in the measured velocity field. More advanced super resolution strategies that employ an iterative AOI reduction process inherently reduce positional bias in PIV results but these strategies can break down in complex flows where velocity gradients are steep and particle dispersion does not remain uniformly random. To mitigate these problems a simple but effective technique is presented that enables individual velocity vectors to be placed within an AOI at locations toward which the cross correlation plane is biased. The method involves analysis of the correlation plane to extract the dominant features that are matched in two successive AOIs. To demonstrate the utility of the methodology results obtained from synthetic images are compared against results obtained using the conventional PIV approach

CO Oxidation on the Au₁₅Cu₁₅ Cluster and the Role of Vacancies in the MgO(100) Support

A comprehensive theoretical study of a Au₁₅Cu₁₅ cluster on MgO(100) supports and its catalytic activity for CO oxidation has been performed based on the density functional theory and microkinetic modeling. Molecular adsorption and different reaction paths based on the Langmuir–Hinshelwood (LH) and Eley–Rideal (ER) mechanisms have been explored by tuning the location of vacancies in MgO(100). The charge states of the Au₁₅Cu₁₅ cluster are negative on all supports, defect-free, O-vacancy (F-center), and Mg-vacancy (V-center), and the effect is significantly amplified on the F-center. In each case, the O₂ molecule can be effectively activated upon adsorption and dissociated to 2 × O atoms easily, and the reaction modeling takes into account also the reaction paths with adsorbed O atoms. Overall, CO oxidation has lower reaction barriers on the cluster on the F-center. The microkinetic modeling analysis reveals that CO oxidation is very sensitive to the CO partial pressure, as the relatively strong CO binding leads readily to CO poisoning of the cluster surface sites and hinders CO₂ formation. For low CO partial pressures, the catalytic reaction takes place already at 150 K for the cluster on the F-center. The CO₂ production rates are much lower for the defect-free and V-center supports which display similar increased activity at elevated temperatures. In all cases, the right combination of CO and O₂ partial pressures is instrumental for CO₂ production