1,721,043 research outputs found
Viscosity Variability Impact on 2D Laminar and Turbulent Poiseuille Velocity Profiles; Characteristic-Based Split (CBS) Stabilization
No full textThe erosion of riverbeds and riverbanks depends, among other causes, both on the velocity fields and on their gradient near their boundaries, with the generation of shear stresses. The presence of sediments modifies the viscosity and, accordingly, modifies the profiles, particularly near the edges right where they are generated. Therefore, in this work, the distortion of the velocity profiles due to an imposed spatial variability of viscosity, was studied applying the Computational Fluid Dynamics (CFD). In particular, as test cases, laminar and turbulent Plane Poiseuille flows, were selected. For simplicity, it was assumed that the sediment distribution and therefore the viscosity distribution was not influenced by the mixing due to velocity field. That is, the equilibrium configuration was determined as a consequence of a spatially variable distribution of viscosity. The 2D Navier-Stokes equations, in steady state conditions, were numerically solved exploiting a research software developed and discussed by the author [1]. The turbulence was considered through the RANS (Reynolds Averaged Navier Stokes) approach. The two equations k − models were employed. The turbulence phenomena near solid boundaries was simulated by the means of Wall-Functions. Spatial discretization was carried out using the Finite Element Method (FEM). A structured meshing with h like adaptability was developed. Then, in order to avoid velocities and pressure instabilities, the Characteristic-based split algorithm (CBS) was applied, while, in order to correctly consider incompressibility, by a numerical point of view, the Method of Artificial Compressibility (AC) was selected. Accordingly, the related CBS-AC three steps algorithm was implemented [1]. Then, some parametric numerical experiments were performed, considering a semi-implicit, approach. As was to be expected, the velocity profiles, for both laminar and turbulent were influenced by the viscosity distribution. The discussion of the overall results points out the sensitivity of the algorithms not only to the meshes size, to their distribution and to the number of iterations, but also to some intrinsic “experimental numerical dials” (safe coefficients, explicit vs implicit ratio), specific of the selected approach. Moreover, suggestions have emerged for more complex and more complete simulations which, necessarily, would use methods based on iterations internal to each time-ste
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Parametric Analysis of Urban Flood Risk Based on 'Shallow Water' Model; A Real Case at Small Scale
No full textIn this paper, we examined the increased risk of urban flooding due to incorrect or insufficient maintenance of small hydrological basins. In particular, the effects of a peak rainfall event on a water drainage canal near to a town in central Italy were considered. By means of the RiverFlow2D commercial computational software, the Shallow water technique was chosen, which is based on the Finite Volume Element and on the Godunov-Riemann technique. We also experimented with parallel computing, by performing the same calculations with GPUs (Graphics Processing Units) and we were able to significantly reduce the total time by 80 times. The study area is located in Pianello di Ostra district (Ancona, Marche, Italy). The peak rain data, which is publicly available, were recorded by the Corinaldo pluviometric station (9.1 km from the area) between April 26th and May 2nd 2014 and it caused a subsequent flooding event lasting two days. We integrated pluviometric data with available cartography, a rigorous site inspection, interviews with inhabitants and a high-resolution topographic survey (30 x 30 cm) acquired with a drone. To process rainfall data, we selected the Curve-Number (CN) empirical method, developed by the USDA Natural Resources Conservation Service (SCS). The parametric simulations on Fosso della Trocca basin were performed considering both pre-flooding maintenance state, with obstructions of the channel and the presence of a small bridge, and optimal maintenance state, with no obstructions and no bridge. The computer-simulated depth of the flooding water was compatible with what was observed during the real flood. Thus, the effects of increasingly intense rainfall events were estimated. However, we found that threshold values exist above which no ordinary maintenance is sufficient to avoid flooding phenomena
Statistical approach to compute a surrogate input for building physics CFD simulations through experimental measurements
No full textComputational Fluid Dynamics (CFD) simulations are sensitive to input uncertainties and human errors. Using real-world data as an input for CFD simulations is not rare for building physics simulations and it is still an open topic. In most cases, computer simulations using CFD are for design purposes and they aim to represent the situations occur in the real-world. The real-world parameters are commonly set based on experimental measurements. However, it is known that experimental measurements are affected by uncertainties; hence the experimental values have to be processed to calibrate numerical simulations. This paper investigates the CFD simulation calibration through experimental measurements. In particular, a statistical approach is employed to study the experimental data of inlet-outlet velocities for ten non successive days in a test-room with the purpose of assuming a surrogate day input that is the most significant of the dataset. Moreover, five different input methods on the boundary conditions of inlet velocity obtained from the experimental measurements are implemented and the accuracy of the predicted results through CFD simulations is presented. For the first input, the actual measurements of one particular day were chosen among the ten available days. For the other four, the numerical input relating to each second of the synthetic day was constructed by means of a statistical assessment of the actual measures obtained at each corresponding second of the ten actual days. The Hermite polynomial chaos expansion was selected for the last approach. Results have shown a significant variability of airflow for both experimentally measured input and output signals. By using the experimental signal expansion through Hermite polynomials the experimental and numerical values give satisfactory results
Surface Water Flow Balance of a River Basin Using a Shallow Water Approach and GPU Parallel Computing—Pescara River (Italy) as Test Case
Full text linkThe analysis and prevention of hydrogeological risks plays a very important role and, currently, much attention is paid to advanced numerical models that correspond more to physical reality and whose aim is to reproduce complex environmental phenomena even for long times and on large spatial scales. Within this context, the feasibility of performing an effective balance of surface water flow relating to several months was explored, based on accurate hydraulic and mathematical-numerical models applied to a system at the scale of a hydrographic basin. To pursue this target, a 2D Riemann–Godunov shallow-water approach, solved in parallel on a graphical processing unit (GPU), able to drastically reduce calculation time, and implemented into the RiverFlow2D code (2017 version), was selected. Infiltration and evapotranspiration were included but in a simplified way, in order to face the calibration and validation simulations and because, despite the parallel approach, it is very demanding even for the computer time requirement. As a test case the Pescara river basin, located in Abruzzo, Central Italy, covering an area of 813 km2 and well representative of a typical medium-sized basin, was selected. The topography was described by a 10 × 10 m digital terrain model (DTM), covered by about 1,700,000 triangular elements, equipped with 11 rain gauges, distributed over the entire area, with some hydrometers and some fluviometric stations. Calibration, and validation were performed considering the flow data measured at a station located in close proximity to the mouth of the river. The comparison between the numerical and measured data, and also from a statistical point of view, was quite satisfactory. A further important outcome was the capability to highlight any differences between the numerical flow-rate balance carried out on the basis of the contributions of all known sources and the values actually measured. This characteristic of the applied modeling allows better calibration and verification not only of the effectiveness of much more simplified approaches, but also the entire network of measurement stations and could suggest the need for a more in-depth exploration of the territory in question. It would also enable the eventual identification of further hidden supplies of water inventory from underground sources and, accordingly, to enlarge the hydrographic and hydrogeological border of the basin under study. Moreover, the parallel computing platform would also allow the development of effective early warning systems, for example, of floods
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