Experimental Study of Ultra Shallow Floor Beams (USFB) with Perforated Steel Sections

ABSTRACT: In modern building construction design, floor spans are becoming longer. Hence, steel framed structures have become more competitive when compared with traditional reinforced concrete framed buildings. In order to minimise the structural section of the composite sections, and for economic reasons, steel perforated beams are designed to act compositely with the floor slab. When the concrete slab lies within the steel flanges, as in the Ultra Shallow Floor Beam (USFB), there is an additional benefit when considering fire resistance. The aim of this study is to investigate the contribution of the concrete in composite cellular beams in the case where the concrete slab lies between the beam flanges of a steel section, when resisting vertical shear forces. The concrete between the flanges enhances the load-carrying capacity by providing a load path to transfer the shear force. Four specimens of steel-concrete composite beams with web openings in the steel section were tested in this study. One bare steel section with web openings was also tested as a comparison. This is the first such investigation of the failure mode under shear resistance (Vierendeel action) of the Ultra Shallow Floor Beam. In the test specimens, the web opening diameter is 76% of the beam depth, which is the largest currently available. This represents the worst case in terms of Vierendeel bending forces generated in the vicinity of the web openings. The smaller the hole is, the easier it is for the trapped concrete between the flanges to transfer shear across the opening. The results from the composite beam tests show a significant increase in shear resistance. The percentage of the shear capacity improvement of the particular case is presented herein as well as the failure mode of the composite beams. The shear enhancement demonstrated in this study has been utilised software that is used in design practice

Regularization-independent study of renormalized non-perturbative quenched QED

A recently proposed regularization-independent method is used for the first time to solve the renormalized fermion Schwinger-Dyson equation numerically in quenched QED$_4$. The Curtis-Pennington vertex is used to illustrate the technique and to facilitate comparison with previous calculations which used the alternative regularization schemes of modified ultraviolet cut-off and dimensional regularization. Our new results are in excellent numerical agreement with these, and so we can now conclude with confidence that there is no residual regularization dependence in these results. Moreover, from a computational point of view the regularization independent method has enormous advantages, since all integrals are absolutely convergent by construction, and so do not mix small and arbitrarily large momentum scales. We analytically predict power law behaviour in the asymptotic region, which is confirmed numerically with high precision. The successful demonstration of this efficient new technique opens the way for studies of unquenched QED to be undertaken in the near future.Comment: 20 pages,5 figure

Tests of a Semi-Analytical Case 1 and Gelbstoff Case 2 SeaWiFS Algorithm with a Global Data Set

A semi-analytical algorithm was tested with a total of 733 points of either unpackaged or packaged-pigment data, with corresponding algorithm parameters for each data type. The 'unpackaged' type consisted of data sets that were generally consistent with the Case 1 CZCS algorithm and other well calibrated data sets. The 'packaged' type consisted of data sets apparently containing somewhat more packaged pigments, requiring modification of the absorption parameters of the model consistent with the CalCOFI study area. This resulted in two equally divided data sets. A more thorough scrutiny of these and other data sets using a semianalytical model requires improved knowledge of the phytoplankton and gelbstoff of the specific environment studied. Since the semi-analytical algorithm is dependent upon 4 spectral channels including the 412 nm channel, while most other algorithms are not, a means of testing data sets for consistency was sought. A numerical filter was developed to classify data sets into the above classes. The filter uses reflectance ratios, which can be determined from space. The sensitivity of such numerical filters to measurement resulting from atmospheric correction and sensor noise errors requires further study. The semi-analytical algorithm performed superbly on each of the data sets after classification, resulting in RMS1 errors of 0.107 and 0.121, respectively, for the unpackaged and packaged data-set classes, with little bias and slopes near 1.0. In combination, the RMS1 performance was 0.114. While these numbers appear rather sterling, one must bear in mind what mis-classification does to the results. Using an average or compromise parameterization on the modified global data set yielded an RMS1 error of 0.171, while using the unpackaged parameterization on the global evaluation data set yielded an RMS1 error of 0.284. So, without classification, the algorithm performs better globally using the average parameters than it does using the unpackaged parameters. Finally, the effects of even more extreme pigment packaging must be examined in order to improve algorithm performance at high latitudes. Note, however, that the North Sea and Mississippi River plume studies contributed data to the packaged and unpackaged classess, respectively, with little effect on algorithm performance. This suggests that gelbstoff-rich Case 2 waters do not seriously degrade performance of the semi-analytical algorithm

Comparative Life Cycle Assessment of Direct and Indirect Solar Water Disinfection Processes in Developing Countries

In July 2010, the UN General Assembly recognized the universal human right to sufficient water for health and sanitation (UN…, 2010). The reliable disinfection of this water plays a critical role in public health (Carter and Miller, 2005), and this study investigates the use of four ultraviolet (UV) disinfection methods for use in international development and disaster relief. The study focuses on the life cycle impacts of four direct and indirect solar ultraviolet disinfection systems. Direct solar disinfection refers to exposure of water to solar radiation, while indirect solar disinfection collects solar energy and uses this to power a UV lamp disinfection reactor. These four systems were compared to chlorine disinfection and automobile distribution as baseline methods. Existing literature was used to define a life cycle functional unit for each system, which quantified the material use, infrastructure required, and life cycle of the components of each system. The impact of each system was then defined in the Life Cycle Analysis software SimaPro. Analyses compared the use of each technology at “community, school, small group, and family” scales. Due to the significant impact that end-of-use of a system can have on rural communities, an end-of-life analysis was conducted in addition to the quantitative life cycle analysis. Life cycle analysis shows that both direct and indirect UV disinfection methods vary dramatically over several categories of impact assessment. End of life analysis and this variation highlight the extremely complicated process of designing the appropriate disinfection system for use in developing countries

Running coupling and fermion mass in strong coupling QED

Simple toy model is used in order to exhibit the technique of extracting the non-perturbative information about Green's functions in Minkowski space. The effective charge and the dynamical electron mass are calculated in strong coupling 3+1 QED by solving the coupled Dyson-Schwinger equations for electron and photon propagators. The minimal Ball-Chiu vertex was used for simplicity and we impose the Landau gauge fixing on QED action. The solution obtained separately in Euclidean and Minkowski space were compared, the latter one was extracted with the help of spectral technique.Comment: 23 pages, 4 figures, v4: revised and extended version, one introductory section adde

Short term traffic flow prediction with particle methods in the presence of sparse data

Traffic prediction approaches face challenges when presented with sparse or missing data. This can be caused by numerous factors such as: i) sensors not being operational; ii) communication issues; iii) cost prohibiting full monitoring of a road network. This present work adds to existing body of knowledge by proposing a particle based framework for dealing with these challenges. An expression of the likelihood function is derived for the case when the missing value is calculated based on Kriging interpolation. With the Kriging interpolation, the missing values of the measurements are predicted, which are subsequently used in the computation of likelihood terms in the particle filter algorithm. The results show 23% to 36.34% improvement in RMSE values for the synthetic data used