Consistent floor response spectra for performance-based seismic design of nonstructural elements

The achievement of adequate performance objectives for buildings under increasing seismic intensities is not only related to the performance of structural members but also to the behavior of nonstructural elements. The need to properly design nonstructural elements for earthquakes has been largely demonstrated in the last few years and has become an important objective within the earthquake engineering community. A crucial aspect in the proper design of nonstructural elements is the definition of the seismic demand in terms of both absolute acceleration and relative displacement floor response spectra. In the first part of this study, relative displacement and absolute acceleration floor response spectra were computed for four reinforced concrete moment-resisting archetype frames via dynamic time-history analyses and were compared with floor response spectra predicted by means of two recent simplified methodologies available in the literature. It was observed that one of the existing methodologies is generally unable to predict consistent absolute acceleration and relative displacement floor response spectra. An improved procedure is developed for estimating consistent floor response spectra for building structures subjected to low and medium-high seismic intensities. This new procedure improves the predictions of a relative displacement floor response spectrum by constraining its ordinates at long nonstructural periods to the expected peak absolute displacement of the floor. The resulting acceleration and relative displacement response spectra are then consistently related by the well-known pseudo-spectral relationship over the entire nonstructural period range. The effectiveness of the proposed methodology was appraised against floor response spectra computed from nonlinear time-history analyses.     

Evaluating the performance of topobathymetric LiDAR to support multi-dimensional flow modelling in a gravel-bed mountain stream

Stream biophysical processes are commonly studied using multi-dimensional numerical modelling that quantifies flow hydraulics from which parameters such as habitat suitability, stream carrying capacity, and bed mobility are derived. These analyses would benefit from accurate high-resolution stream bathymetries spanning tens of kilometres of channel, especially in small streams or where navigation is difficult. Traditional ground-based survey methods are limited by survey time, dense vegetation and stream access, and are usually only feasible for short reaches. Conversely, airborne topobathymetric LiDAR surveys may overcome these limitations, although limited research is available on how errors in LiDAR-derived digital elevation models (DEMs) might propagate through flow models. This study investigated the performance of LiDAR-derived topobathymetry in support of multi-dimensional flow modelling and ecohydraulics calculations in two gravel-bedded reaches (approximately 200 m long), one morphologically complex and one morphologically simple, and at the segment scale (32 km-long stream segment) along a 15 m-wide river in central Idaho, USA. We compared metre and sub-metre-resolution DEMs generated from RTK-GPS ground and Experimental Advanced Airborne Research LiDAR-B (EAARL-B) surveys and water depths, velocities, shear stresses, habitat suitability, and bed mobility modelled with two-dimensional (2D) hydraulic models supported by LiDAR and ground-surveyed DEMs. Residual statistics, bias (B), and standard deviation (SD) of the residuals between depth and velocity predicted from the model supported by LiDAR and ground-survey topobathymetries were up to −0.04 (B) and 0.09 m (SD) for depth and −0.09 (B) and 0.20 m s⁻¹ (SD) for velocity. The accuracy (B = 0.05 m), precision (SD = 0.09 m), and point density (1 point m⁻²) of the LiDAR topobathymetric survey (regardless of reach complexity) were sufficient to support 2D hydrodynamic modelling and derivative stream habitat and process analyses, because these statistics were comparable to those of model calibration with B = 0 m and SD = 0.04 m for water surface elevation and B = 0.05 m s⁻¹ and SD = 0.22 m s⁻¹ for velocity in our investigation. © 2020 John Wiley & Sons, Ltd.     

Chemistry and sulfur isotopic composition of precipitation at Bologna, Italy

Individual and monthly precipitation samples from the polluted atmosphere of Bologna (Emilia-Romagna province) were collected during March 1996 to May 1997 and analyzed for major ions in solution and S isotopes in dissolved SO₄.Weighted mean enrichment factors relative to seawater are found to be 1.0 for Na, 15.2 for K, 105 for Ca, 3.3 for Mg, 17.3 for SO₄ and 663 for HCO⁻₃. Very good positive correlations are observed for the Ca²⁺–Mg²⁺–HCO⁻₃–SO²⁻₄–NO⁻₃ system, indicating that dissolution of Ca (±Mg)-carbonate particles by H₂SO₄ and HNO₃ from combustion of oil and gas is a major process controlling the chemical composition of rain and snow. Na⁺ and Cl⁻ in monthly precipitation derive essentially from sea spray, but the contribution of Na⁺ from continental sources is appreciable in a number of individual rains. NH⁺₄ appears to be on average more abundant in spring and summer precipitation, its main sources being microbial activity in soils and application of fertilizers. K⁺ is probably of continental origin from soil dust.The S isotopic composition of SO₄ is systematically positive, with mean δ³⁴S values of +3.2±1.6‰ (n=40) in individual precipitation and +2.8±1.4‰ (n=12) in monthly precipitation. These isotopic compositions are interpreted in terms of a dominant contribution of S from anthropogenic emissions and subordinate contributions from biogenic and marine sources. Pollutant SO₄ is estimated to have a δ³⁴S value in the range +2.5 to +4.5‰, whereas a distinctive δ³⁴S of −4.5‰ or lower indicates SO₄ from oxidation of biogenic gases.The isotopic and chemical compositions of SO₄ do not depend on wind direction, thus testifying to a mostly local source for pollutant S in the Bologna atmosphere.     

Hydrological and biogeochemical features of the Northern Adriatic Sea in the period 2003–2006

This paper reports on the main biogeochemical properties of the Northern Adriatic Sea in the period May 2003–November 2006 within the framework of the European program INTERREG III Italy‐Slovenia. Spatial and temporal distributions of water density, dissolved oxygen, nutrients (nitrogen, phosphorous and silicon) and chlorophyll a are presented. Multivariate methods such as fuzzy k‐means, self‐organising maps and cluster analysis were used to identify the different water masses and to characterise the temporal and spatial variability of the main biogeochemical features present in the area. The results confirm that the Po River outflows and the meteorological forcing factors are the main components triggering the alternation of stratification and mixing of the water column and that strongly affect the trophic state of the basin. In general, oligotrophic conditions dominate, and were more pronounced offshore, but mesotrophy occurred episodically in May 2004 and July 2005, when phytoplankton blooms were observed concomitant with vertical stability of the water column. A marked interannual variability was also observed, supporting the importance of maintaining long‐term observations of the basin.     

Diffusion of osmium in pyrrhotite and pyrite: implications for closure of the Re–Os isotopic system

In order to better constrain the extent to which common sulfide minerals will retain their osmium isotopic composition subsequent to crystallization, we have conducted experiments to quantify the diffusion behavior of osmium in pyrite and pyrrhotite. Experiments consisted of either (1) isothermal soaking of diffusion couples consisting of natural pyrite or pyrrhotite crystals packed against powdered Os-bearing Fe-sulfide or (2) ‘relaxation’ of initially high near-surface osmium concentrations produced in the latter experiments (pyrite only). Osmium penetration into samples was characterized by depth profiling using Rutherford backscattering spectroscopy (RBS) (pyrite) or electron microprobe analyses across sectioned run products (pyrrhotite). Results of the first type of diffusion experiment involving pyrite show only limited osmium penetration into sample surfaces, with the extent of penetration uncorrelated with run duration. Images of pyrite samples using atomic force microscopy show roughening of initially smooth surfaces as a consequence of step formation and suggest that osmium incorporation into the near-surface occurred by solute uptake during step growth and not by volume diffusion. Prolonged (1000⁺ h) ‘relaxation’ experiments revealed no additional osmium penetration into pyrite surfaces and based on the depth resolution for RBS, a maximum diffusion coefficient of 2.5×10⁻²³ m²/s at 500°C was calculated. Experiments involving pyrrhotite over the temperature range of 950–1100°C showed extensive osmium uptake and osmium concentration gradients that conform with Fickian diffusion behavior. We found that pyrrhotite Fe/S could be varied by changes in the composition of the starting material and osmium source and over the range of Fe/S produced in experiments (molar Fe/S=0.83–0.90), we observed no systematic variation in the osmium diffusion coefficient. Diffusion coefficients measured parallel to the a crystallographic axis were on average 1.4× higher than values measured parallel to c and regression of the c-axis data yielded the Arrhenius relation:

The application of these diffusion data to simple models of diffusive exchange during static or polythermal time–temperature histories is used to assess the conditions under which radiogenic osmium will be retained. During isothermal annealing, calculations indicate that the cores of millimeter-sized spherical pyrrhotite crystals undergoing diffusive exchange with an external osmium reservoir will have their initial compositions perturbed in ≤0.5 Ma at temperatures exceeding 400°C. Pyrite undergoing the same process at 500°C requires in excess of 10 Ma before crystal cores are affected. The relatively short ‘core retention’ time-scales for pyrrhotite indicates that this mineral may be prone to isotopic resetting following relatively brief crustal thermal events, thus possibly accounting for the scatter that commonly occurs in Re–Os isochrons generated from massive sulfide samples. Calculated closure temperatures (T_c) for osmium exchange in pyrrhotite yielded values of 300–400°C for grain sizes ranging from 10 to 1000 μm. These values of T_c are similar to those calculated for Ar retention in biotite, and considerably lower than for Sr in apatite and plagioclase, for example. Such low closure temperatures for pyrrhotite suggest this mineral will date the final stage in the cooling of a magmatic system and possibly be susceptible to open system osmium exchange in the presence of late-stage hydrothermal fluids. This latter result infers that caution be applied when interpreting elevated initial osmium isotopic ratios as a product of crustal assimilation at the magmatic stage.     

On the role of spatial resolution on snow estimates using a process‐based snow model across a range of climatology and elevation

Hydrological processes in mountainous settings depend on snow distribution, whose prediction accuracy is a function of model spatial scale. Although model accuracy is expected to improve with finer spatial resolution, an increase in resolution comes with modelling costs related to increased computational time and greater input data and parameter information. This computational and data collection expense is still a limiting factor for many large watersheds. Thus, this work's main objective is to question which physical processes lead to loss in model accuracy with regard to input spatial resolution under different climatic conditions and elevation ranges. To address this objective, a spatially distributed snow model, iSnobal, was run with inputs distributed at 50‐m—our benchmark for comparison—and 100‐m resolutions and with aggregated (averaged from the fine to the large resolution) inputs from the 50‐m model to 100‐, 250‐, 500‐, and 750‐m resolution for wet, average, and dry years over the Upper Boise River Basin (6,963 km²), which spans four elevation bands: rain dominated, rain–snow transition, and snow dominated below treeline and above treeline. Residuals, defined as differences between values quantified with high resolution (>50 m) models minus the benchmark model (50 m), of simulated snow‐covered area (SCA) and snow water equivalent (SWE) were generally slight in the aggregated scenarios. This was due to transferring the effects of topography on meteorological variables from the 50‐m model to the coarser scales through aggregation. Residuals in SCA and SWE in the distributed 100‐m simulation were greater than those of the aggregated 750 m. Topographic features such as slope and aspect were simplified, and their gradient was reduced due to coarsening the topography from the 50‐ to 100‐m resolution. Therefore, solar radiation was overestimated, and snow drifting was modified and caused substantial SCA and SWE underestimation in the distributed 100‐m model relative to the 50‐m model. Large residuals were observed in the wet year and at the highest elevation band when and where snow mass was large. These results support that model accuracy is substantially reduced with model scales coarser than 50 m.     

Understanding hydrological processes in glacierized catchments: Evidence and implications of highly variable isotopic and electrical conductivity data

The spatial and temporal characterization of geochemical tracers over Alpine glacierized catchments is particularly difficult, but fundamental to quantify groundwater, glacier melt, and rain water contribution to stream runoff. In this study, we analysed the spatial and temporal variability of δ²H and electrical conductivity (EC) in various water sources during three ablation seasons in an 8.4‐km² glacierized catchment in the Italian Alps, in relation to snow cover and hydro‐meteorological conditions. Variations in the daily streamflow range due to melt‐induced runoff events were controlled by maximum daily air temperature and snow covered area in the catchment. Maximum daily streamflow decreased with increasing snow cover, and a threshold relation was found between maximum daily temperature and daily streamflow range. During melt‐induced runoff events, stream water EC decreased due to the contribution of glacier melt water to stream runoff. In this catchment, EC could be used to distinguish the contribution of subglacial flow (identified as an end member, enriched in EC) from glacier melt water to stream runoff, whereas spring water in the study area could not be considered as an end member. The isotopic composition of snow, glacier ice, and melt water was not significantly correlated with the sampling point elevation, and the spatial variability was more likely affected by postdepositional processes. The high spatial and temporal variability in the tracer signature of the end members (subglacial flow, rain water, glacier melt water, and residual winter snow), together with small daily variability in stream water δ²H dynamics, are problematic for the quantification of the contribution of the identified end members to stream runoff, and call for further research, possibly integrated with other natural or artificial tracers.     

The 2-D lattice theory of Flower Constellations

The 2-D lattice theory of Flower Constellations, generalizing Harmonic Flower Constellations (the symmetric subset of Flower Constellations) as well as the Walker/ Mozhaev constellations, is presented here. This theory is a new general framework to design symmetric constellations using a $2\times 2$ 2 × 2 lattice matrix of integers or by its minimal representation, the Hermite normal form. From a geometrical point of view, the phasing of satellites is represented by a regular pattern (lattice) on a two-Dimensional torus. The 2-D lattice theory of Flower Constellations does not require any compatibility condition and uses a minimum set of integer parameters whose meaning are explored throughout the paper. This general minimum-parametrization framework allows us to obtain all symmetric distribution of satellites. Due to the $J_2$ J 2 effect this design framework is meant for circular orbits and for elliptical orbits at critical inclination, or to design elliptical constellations for the unperturbed Keplerian case.     

The 3-D lattice theory of Flower Constellations

Flower Constellations (FCs) have been extensively studied for use in optimal constellation design. The Harmonic FCs (HFCs) subset, representing the symmetric configurations, have recently been reformulated into 2-D Lattice Flower Constellations (2D-LFCs), encompassing the complete set of HFCs. Elliptic orbits are generally avoided due to the deleterious effects of Earth’s oblateness on the constellation, but here we present a novel concept for avoiding this problem and enabling more effective global coverage utilizing elliptic orbits. This new 3D Lattice Flower Constellations (3D-LFCs) framework generalizes the 2D-LFCs, Walker constellations, elliptical Walker constellations, and many of Draim’s global coverage constellations. Previous studies have shown FCs can provide improved performance in global navigation over existing Global Navigation Satellite Systems (GNSS). We found a 3D-LFC design that improved the average positioning accuracy by 3.5 % while reducing launch $\varDelta v$ Δ v requirements when compared to the existing Galileo GNSS constellation.     

Improving crop type determination using satellite imagery: A study for the Regione del Veneto,Italy

The Regione del Veneto (Italy) is cooperating with the University of California, Santa Barbara and other researchers in Italy and the U.S.A. to develop a system of econometric crop production modeling. Five crops are to be included in this project: small grains (wheat and barley), corn, sugar beets, soybeans, orchards and vineyards. A critical part of the crop yield modeling process is the identification of crops using multispectral satellite data. This paper explores two strategies to improve crop classification accuracies: (1) use of ancillary data stored in digital format and (2) use of multitemporal data. Ancillary information stored on digital files were used in this research to remove (mask) non‐agricultural areas from satellite image data. Comparison between the classification of masked and unmasked images showed that improvement ranged from 3% to 26% depending on crop type. The multidate classification was performed by compiling an image of transformed spectral bands and three TM‐5 bands. The transformed bands were TM band 4 over TM band 3. Based on the work conducted in this study it is clear that crop type determination from satellite imagery is possible for small field agricultural areas such as those found in Italy.