Nonlinear modeling of the seismic response of masonry structures: critical review and open issues towards engineering practice

Bulletin of Earthquake Engineering - This paper provides a comphrensive review of the critical aspects of nonlinear modeling for evaluating the seismic response of masonry structures, emphasizing...     

The RUSLE erosion index as a proxy indicator for debris flow susceptibility

Debris flows represent dangerous occurrences in many parts of the world. Several disasters are documented due to this type of fast-moving landslides; therefore, natural-hazard assessment of debris flows is crucial for safety of life and property. To this aim, much current work is being directed toward developing geotechnical-hydraulic models for the evaluation of debris flow susceptibility. A common base for such current models is parameterization of background predisposing and triggering factors such as inherent characteristics of geo-materials, topography, landscape and vegetation cover, rainfall regime, human activities, etc. which influence the occurrence of these processes on slopes. The same factors are also taken into account in soil erosion prediction models. Consequently, it seems worth investigating the effectiveness of the soil erosion index as debris flows susceptibility indicator. To this aim, a logistic regression analysis was carried out between the erosion index assessed by means of the Revised Universal Soil Loss Equation (RUSLE) model and the inventory of debris flows that have occurred in an area in Sicily (Southern Italy). Model assumptions were verified and validated by means of a series of statistical tools. Different possible scenarios were also evaluated by considering hypothetical changes in soil erosion rate under different rain erosivity conditions. Notwithstanding the rough approximations in model data collection, the outcomes appear encouraging.     

Geophysical surveys integrated with rainfall data analysis for the study of soil piping phenomena occurred in a densely urbanized area in eastern Sicily

Natural Hazards - The occurrence of strong and abrupt rainfall, together with a wrong land use planning and an uncontrolled urban development, can constitute a risk for infrastructure and...     

The influence of petrography,mineralogy and chemistry on burnability and reactivity of quicklime produced in Twin Shaft Regenerative (TSR) kilns from Neoarchean limestone (Transvaal Supergroup,South Africa)

Mineralogy and Petrology - This study evaluates the influence of chemical, mineralogical and petrographic features of the Neoarchean limestone from the Ouplaas Mine (Griqualand West, South Africa)...     

Estimation of radar-rainfall error spatial correlation

The study presents a theoretical framework for estimating the radar-rainfall error spatial correlation (ESC) using data from relatively dense rain gauge networks. The error is defined as the difference between the radar estimate and the corresponding true areal rainfall. The method is analogous to the error variance separation that corrects the error variance of a radar-rainfall product for gauge representativeness errors. The study demonstrates the necessity to consider the area–point uncertainties while estimating the spatial correlation structure in the radar-rainfall errors. To validate the method, the authors conduct a Monte Carlo simulation experiment with synthetic fields with known error spatial correlation structure. These tests reveal that the proposed method, which accounts for the area–point distortions in the estimation of radar-rainfall ESC, performs very effectively. The authors then apply the method to estimate the ESC of the National Weather Service’s standard hourly radar-rainfall products, known as digital precipitation arrays (DPA). Data from the Oklahoma Micronet rain gauge network (with the grid step of about 5 km) are used as the ground reference for the DPAs. This application shows that the radar-rainfall errors are spatially correlated with a correlation distance of about 20 km. The results also demonstrate that the spatial correlations of radar–gauge differences are considerably underestimated, especially at small distances, as the area–point uncertainties are ignored.     

Head-wave parametric rolling of a surface combatant

Complementary CFD, towing tank EFD, and nonlinear dynamics approach study of parametric roll for the ONR Tumblehome surface combatant both with and without bilge keels is presented. The investigations without bilge keels include a wide range of conditions. CFD closely agrees with EFD for resistance, sinkage, and trim except for Fr>0.5 which may be due to free surface and/or turbulence modeling. CFD shows fairly close agreement with EFD for forward-speed roll decay in calm water, although damping is over/under predicted for largest/smaller GM. Most importantly CFD shows remarkably close agreement with EFD for forward-speed parametric roll in head waves for GM=0.038 and 0.033 m, although CFD predicts larger instability zones at high and low Fr, respectively. The CFD and EFD results are analyzed with consideration ship motion theory and compared with Mathieu equation and nonlinear dynamics approaches. Nonlinear dynamics approaches are in qualitative agreement with CFD and EFD. The CFD and nonlinear dynamics approach results were blind in that the actual EFD radius of gyration k_xx was not known a priori.     

Spring thermal resources for grapevine in Kőszeg (Hungary) deduced from a very long pictorial time series (1740–2009)

Since 1740 until now, the Book of Vine Branches encompasses beautiful pictorial representations of shoots and sprouts, collected every year on April 24th in the vineyards of the Hungarian town of K?szeg. A long time series (1740–2009) of sprouts phenological development coded with the BBCH scale is obtained through paintings visual inspection. Consequently, a model relating sprouts development with thermal resources accumulation is developed on the base of Wien daily air temperature series for the 1857–2009 period. Thermal resources is obtained with the Normal Heat Hours approach, a response curve method that takes into account the nonlinear response of phenological development to temperature. The model, calibrated and validated on the 1930–2009 period, shows an overestimation of thermal resources when applied to the 1857–1929, due to the more advanced phenology of that phase. Since this advance can be ascribed to genetics and management instead of more favorable thermal conditions, model outputs previous to 1930 are decreased by a constant factor. Finally, the 1740–2009 time series of grapevine spring thermal resources is obtained applying the model to the complete phenological time series. The analysis of the series highlights a first phase (1740–1780) characterized by high and stable availability of thermal resources during the 1740–1780, a second phase (1781–1820) with the lowest level of resources, a phase of intermediate availability (1821–1929) and a final present phase (1930–2009) with renewed high availability. The adopted method overcomes the lack of correlation for the post 1960 period shown by previous works.     

Hydrothermal dolomitization of the carbonate Jurassic succession in the Provençal and Subbriançonnais Domains (Maritime Alps,North-Western Italy)

The present article illustrates a straightforward case of hydrothermal dolomitization, affecting Jurassic platform limestones of the Provençal and Subbriançonnais Domains (Maritime Alps, North-Western Italy). Dolomitized bodies are randomly distributed within the host limestone, and are commonly associated with dolomite vein networks and tabular bodies of dolomite-cemented breccias discordant with respect to bedding. Main dolomite types are a finely to medium-crystalline replacive dolomite and a coarsely-crystalline saddle dolomite occurring both as replacive and as cement. Stratigraphic constraints indicate that dolomitization occurred during the Cretaceous, in a shallow burial context, and was due to the circulation of hot fluids (temperature about 200 °C, as indicated by fluid inclusion microthermometry) through faults and related fracture networks. Hydrothermal dolomitization therefore indirectly documents a Cretaceous fault activity in the Maritime Alps segment of the European Tethyan passive margin.     

Review of the Different Sources of Uncertainty in Single Polarization Radar-Based Estimates of Rainfall

It is well acknowledged that there are large uncertainties associated with radar-based estimates of rainfall. Numerous sources of these errors are due to parameter estimation, the observational system and measurement principles, and not fully understood physical processes. Propagation of these uncertainties through all models for which radar-rainfall are used as input (e.g., hydrologic models) or as initial conditions (e.g., weather forecasting models) is necessary to enhance the understanding and interpretation of the obtained results. The aim of this paper is to provide an extensive literature review of the principal sources of error affecting single polarization radar-based rainfall estimates. These include radar miscalibration, attenuation, ground clutter and anomalous propagation, beam blockage, variability of the Z–R relation, range degradation, vertical variability of the precipitation system, vertical air motion and precipitation drift, and temporal sampling errors. Finally, the authors report some recent results from empirically-based modeling of the total radar-rainfall uncertainties. The bibliography comprises over 200 peer reviewed journal articles.     

Nonstationary modeling of a long record of rainfall and temperature over Rome

A long record (1862–2004) of seasonal rainfall and temperature from the Rome observatory of Collegio Romano are modeled in a nonstationary framework by means of the Generalized Additive Models in Location, Scale and Shape (GAMLSS). Modeling analyses are used to characterize nonstationarities in rainfall and related climate variables. It is shown that the GAMLSS models are able to represent the magnitude and spread in the seasonal time series with parameters which are a smooth function of time. Covariate analyses highlight the role of seasonal and interannual variability of large-scale climate forcing, as reflected in three teleconnection indexes (Atlantic Multidecadal Oscillation, North Atlantic Oscillation, and Mediterranean Index), for modeling seasonal rainfall and temperature over Rome. In particular, the North Atlantic Oscillation is a significant predictor during the winter, while the Mediterranean Index is a significant predictor for almost all seasons.