931 resultados para Civil engineering|Engineering, Sanitary and Municipal|Petroleum engineering|Environmental science


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This paper presents the results of a real bridge field experiment, carried out on a fiber reinforced polymer (FRP) pedestrian truss bridge of which nodes are reinforced with stainless steel plates. The aim of this paper is to identify the dynamic parameters of this bridge by using both conventional techniques and a model updating algorithm. In the field experiment, the bridge was instrumented with accelerometers at a number of locations on the bridge deck, recording both vertical and transverse vibrations. It was excited via jump tests at particular locations along its span and the resulting acceleration signals are used to identify dynamic parameters, such as the bridge mode shape, natural frequency and damping constant. Pedestrianinduced vibrations are also measured and utilized to identify dynamic parameters of the bridge. For a complete analysis of the bridge, a numerical model of the FRP bridge is created whose properties are calibrated utilizing a model updating algorithm. Comparable frequencies and mode shapes to those from the experiment were obtained by the FE models considering the reinforcement by increasing elastic modulus at every node of the bridge by stainless steel plate. Moreover, considering boundary conditions at both ends as fixed in the model resulted in modal properties comparable/similar to those from the experiment. This study also demonstrated that the effect of reinforcement and boundary conditions must be properly considered in an FE model to analyze real behavior of the FRP bridge.

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In order to predict compressive strength of geopolymers prepared from alumina-silica natural products, based on the effect of Al 2 O 3 /SiO 2, Na 2 O/Al 2 O 3, Na 2 O/H 2 O, and Na/[Na+K], more than 50 pieces of data were gathered from the literature. The data was utilized to train and test a multilayer artificial neural network (ANN). Therefore a multilayer feedforward network was designed with chemical compositions of alumina silicate and alkali activators as inputs and compressive strength as output. In this study, a feedforward network with various numbers of hidden layers and neurons were tested to select the optimum network architecture. The developed three-layer neural network simulator model used the feedforward back propagation architecture, demonstrated its ability in training the given input/output patterns. The cross-validation data was used to show the validity and high prediction accuracy of the network. This leads to the optimum chemical composition and the best paste can be made from activated alumina-silica natural products using alkaline hydroxide, and alkaline silicate. The research results are in agreement with mechanism of geopolymerization.


Read More: http://ascelibrary.org/doi/abs/10.1061/(ASCE)MT.1943-5533.0000829

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This report studied the effect of crumb rubber in the asphalt mixture. The mixtures were also having limestone filler as a modifier. Mastic and mortar (mastic-fine aggregate system) mixture having different quantities of crumb rubber and limestone filler modifiers have been tested in order to find the best rutting resistance combination with an acceptable stiffness. The rheological tests on bituminous mastics and mortars have done in the laboratories in Nottingham Transport Engineering Centre (NTEC) and University of Bologna (DICAM). In the second chapter, an extensive literature review about the binders, additives, asphalt mixtures, various modelling and testing methods have been reviewed. In the third chapter, the physical and rheological properties of the binders have been investigated using both traditional devices and DSRs. The forth chapter is dedicated to finding the behaviour of the modified mastics (Binder-modifier system) with different combinations. Five different combinations of crumb rubber and limestone filler mastic tested with various methods using Dynamic Shear Rheometers. In the fifth chapter, in order to find the effect of the modifiers in the rheological properties of the complete asphalt mixture, the fine aggregates added to the same mastic combinations. In this phase, the behaviour of the system so-called mortar; binder, rubber, filler and fine aggregates) has been studied using the DSR device and the traditional tests. The results show that using fine crumb rubber reduces the thermo sensibility of the mastic (Binder Bitumen System) and improves its elasticity. Limestone filler in the other hand increases the mixture stiffness at high Frequencies. Another important outcome of this research was that the rheological properties of the mortars were following the same trend of the mastics, therefore study the rheological properties of the mastic gives an upright estimation of the mortar.

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This thesis evaluates the rheological behaviour of asphalt mixtures and the corresponding extracted binders from the mixtures containing different amounts of Reclaimed Asphalt (RA). Generally, the use of RA is limited to certain amounts. The study materials are Stone Mastic Asphalts including a control sample with 0% RA, and other samples with RA rates of 30%, 60% and 100%. Another set of studied mixtures are Asphalt Concretes (AC) types with again a control mix having 0% RA rate and the other mixtures designs containing 30%, 60% and 90% of reclaimed asphalt which also contain additives. In addition to the bitumen samples extracted from asphalt mixes, there are bitumen samples directly extracted from the original RA. To characterize the viscoelastic behaviour of the binders, Dynamic Shear Rheometer (DSR) tests were conducted on bitumen specimens. The resulting influence of the RA content in the bituminous binders are illustrated through master curves, black diagrams and Cole-Cole plots with regressing these experimental data by the application of the analogical 2S2P1D and the analytical CA model. The advantage of the CA model is in its limited number of parameters and thus is a simple model to use. The 2S2P1D model is an analogical rheological model for the prediction of the linear viscoelastic properties of both asphalt binders and mixtures. In order to study the influence of RA on mixtures, the Indirect Tensile Test (ITT) has been conducted. The master curves of different mixture samples are evaluated by regressing the test data points to a sigmoidal function and subsequently by comparing the master curves, the influence of RA materials is studied. The thesis also focusses on the applicability and also differences of CA model and 2S2P1D model for bitumen samples and the sigmoid function for the mixtures and presents the influence of the RA rate on the investigated model parameters.

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One of the biggest challenges that contaminant hydrogeology is facing, is how to adequately address the uncertainty associated with model predictions. Uncertainty arise from multiple sources, such as: interpretative error, calibration accuracy, parameter sensitivity and variability. This critical issue needs to be properly addressed in order to support environmental decision-making processes. In this study, we perform Global Sensitivity Analysis (GSA) on a contaminant transport model for the assessment of hydrocarbon concentration in groundwater. We provide a quantification of the environmental impact and, given the incomplete knowledge of hydrogeological parameters, we evaluate which are the most influential, requiring greater accuracy in the calibration process. Parameters are treated as random variables and a variance-based GSA is performed in a optimized numerical Monte Carlo framework. The Sobol indices are adopted as sensitivity measures and they are computed by employing meta-models to characterize the migration process, while reducing the computational cost of the analysis. The proposed methodology allows us to: extend the number of Monte Carlo iterations, identify the influence of uncertain parameters and lead to considerable saving computational time obtaining an acceptable accuracy.

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Thesis (Ph.D.)--University of Washington, 2016-08

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Thesis (Master's)--University of Washington, 2016-08

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Thesis (Ph.D.)--University of Washington, 2016-08

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According to the U.S. National Environmental Policy Act of 1969 (NEPA), federal action to manipulate habitat for species conservation requires an environmental impact statement, which should integrate natural, physical, economic, and social sciences in planning and decision making. Nonetheless, most impact assessments focus disproportionately on physical or ecological impacts rather than integrating ecological and socioeconomic components. We developed a participatory social-ecological impact assessment (SEIA) that addresses the requirements of NEPA and integrates social and ecological concepts for impact assessments. We cooperated with the Bureau of Land Management in Idaho, USA on a project designed to restore habitat for the Greater Sage-Grouse (Centrocercus urophasianus). We employed questionnaires, workshop dialogue, and participatory mapping exercises with stakeholders to identify potential environmental changes and subsequent impacts expected to result from the removal of western juniper (Juniperus occidentalis). Via questionnaires and workshop dialogue, stakeholders identified 46 environmental changes and associated positive or negative impacts to people and communities in Owyhee County, Idaho. Results of the participatory mapping exercises showed that the spatial distribution of social, economic, and ecological values throughout Owyhee County are highly associated with the two main watersheds, wilderness areas, and the historic town of Silver City. Altogether, the SEIA process revealed that perceptions of project scale varied among participants, highlighting the need for specificity about spatial and temporal scales. Overall, the SEIA generated substantial information concerning potential impacts associated with habitat treatments for Greater Sage-Grouse. The SEIA is transferable to other land management and conservation contexts because it supports holistic understanding and framing of connections between humans and ecosystems. By applying this SEIA framework, land managers and affected people have an opportunity to fulfill NEPA requirements and develop more comprehensive management plans that better reflect the linkages of social-ecological systems.

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Compaction control using lightweight deflectometers (LWD) is currently being evaluated in several states and countries and fully implemented for pavement construction quality assurance (QA) by a few. Broader implementation has been hampered by the lack of a widely recognized standard for interpreting the load and deflection data obtained during construction QA testing. More specifically, reliable and practical procedures are required for relating these measurements to the fundamental material property—modulus—used in pavement design. This study presents a unique set of data and analyses for three different LWDs on a large-scale controlled-condition experiment. Three 4.5x4.5 m2 test pits were designed and constructed at target moisture and density conditions simulating acceptable and unacceptable construction quality. LWD testing was performed on the constructed layers along with static plate loading testing, conventional nuclear gauge moisture-density testing, and non-nuclear gravimetric and volumetric water content measurements. Additional material was collected for routine and exploratory tests in the laboratory. These included grain size distributions, soil classification, moisture-density relations, resilient modulus testing at optimum and field conditions, and an advanced experiment of LWD testing on top of the Proctor compaction mold. This unique large-scale controlled-condition experiment provides an excellent high quality resource of data that can be used by future researchers to find a rigorous, theoretically sound, and straightforward technique for standardizing LWD determination of modulus and construction QA for unbound pavement materials.

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Design of geotechnical systems is often challenging as it requires the understanding of complex soil behaviour and its influence on field-scale performance of geo-structures. To advance the scientific knowledge and the technological development in geotechnical engineering, a Scottish academic community, named Scottish Universities Geotechnics Network (SUGN), was established in 2001, composing of eight higher education institutions. The network gathers geotechnics researchers, including experimentalists as well as centrifuge, constitutive, and numerical modellers, to generate multiple synergies for building larger collaboration and wider research dissemination in and beyond Scotland. The paper will highlight the research excellence and leading work undertaken in SUGN emphasising some of the contribution to the geotechnical research community and some of the significant research outcomes.

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This paper presents the results of 3D DEM simulations of granular materials subject to cyclic loading. While both the drained and undrained conditions are considered, the effects of depositional history and consolidation stress history on the stress-strain response are specifically evaluated. It is demonstrated that the different stress histories have a significant effect on soil response and that such effects can be attributed to differences in the initial particle arrangement (fabric).

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Different methods to study the evolution of fabric anisotropy are presented. DEM simulations on assemblies of spheres subjected to different stress paths using a three-dimensional periodic cell are used for the analysis of these methods. The links between soil fabric and macro-scale behaviour are also discussed.

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Happier employees are more productive. Organizations across industry, no doubt, try to improve their employees’ happiness with the objective to achieve higher profitability and company value. While this issue has drawn increasing attention in high tech and other industries, little is known about the happiness of project management professionals. More research is needed to explore the current situation of workplace happiness of project management professionals and the driving factors behind it. This thesis explores the workplace happiness (subjective well-being) of project management professionals based on the exploratory statistical analysis of a survey 225 professionals in the state of Maryland, conducted in October 2014. The thesis applies Structural Equation Modeling and multiple regression analysis to the dataset and shows no significant impact of gender, age, work experience, and some other demographic traits on workplace happiness, also named well-being. Statistically significant factors for workplace happiness include: creating pleasant work environment, promoting open organization and well-managed team, and good organization to work for. With respect to the reliability of self-reporting, the study finds that the comprehensive appraisal tool designed by Happiness Works and New Economics Foundation can give a more reliable happiness evaluation. Two key factors, i.e. career perspectives and free to be self, can help alleviate the overconfidence of workplace happiness.