Output-only identification of the modal and physical properties of structures using free vibration response

The viability of a complete structural characterization of civil structures is explored and discussed. In particular, the identification of modal (i.e. natural frequencies, damping ratios and modal shapes) and physical properties (i.e. mass and stiffness) using only the structure’s free decay response is studied. To accomplish this, modal analysis from free vibration response only (MAFVRO) and mass modification (MM) methodologies are engaged along with Wavelet based techniques for optimal signal processing and modal reconstruction. The methodologies are evaluated using simulated and experimental data. The simulated data are extracted from a simple elastic model of a 5 story shear building and from a more realistic nonlinear model of a RC frame structure. The experimental data are gathered from shake table test of a 2-story scaled shear building. Guidelines for the reconstruction procedure from the data are proposed as the quality of the identified properties is shown to be governed by adequate selection of the frequency bands and optimal modal shape reconstruction. Moreover, in cases where the structure has undergone damage, the proposed identification scheme can also be applied for preliminary assessment of structural health.     

A contrast of two typical LUCC processes and their driving forces in oases of arid areas: A case study of Sangong River Watershed at the northern foot of Tianshan Mountains

Aerial photographs taken in 1978 and 1987, Landsat TM images in 1998 as well as soil, hydrology and socio-economic data for the oases in Sangong River Watershed were processed by Remote Sensing (RS) and Geographic Information System (GIS). There are two typical agricultural land uses in oases, Farm-based Land Use with large-scale intensified agricultural activities (FLU) and Household Responsibility-based Land Use with small-scale activities (HRLU). The Index Model of Land Use/Land Cover Change (LUCC), Weighted Index Sum (WIS) and logistic stepwise regression model were established to contrast the two typical LUCC processes and their driving forces. The land use patterns were dominated by cropland and grassland for the entire region, and cropland, residential and industrial land were increasing stably. In the HRLU areas, woodland and grassland declined dramatically, but in the FLU areas, grassland decreased only by 12.0%, whereas woodland increased by 13.7%. LUCC was stronger in the earlier stage (1978–1987) than in the later stage (1987–1998) for the entire region. LUCC was more intense in the HRLU areas than in the FLU areas during the entire period (1978–1998). Policy was a key factor in the land use change, and water resources were a precondition in land use. Under the control of policy and water resources, the main human driving factors included population and economy, and the main natural restrictions were soil fertility and groundwater depth. Human driving factors controlled the land change in the HRLU areas, but natural restriction factors dominated in the FLU areas. In the mean time, intensification of LUCC in the region had some spatiotemporal implications with a fluctuation of impact factors.     

Simplification and Validation of a Spectral-Tensor Model for Turbulence Including Atmospheric Stability

A spectral-tensor model of non-neutral, atmospheric-boundary-layer turbulence is evaluated using Eulerian statistics from single-point measurements of the wind speed and temperature at heights up to 100 m, assuming constant vertical gradients of mean wind speed and temperature. The model has been previously described in terms of the dissipation rate \(\epsilon \), the length scale of energy-containing eddies \(\mathcal {L}\), a turbulence anisotropy parameter \(\varGamma \), the Richardson number Ri, and the normalized rate of destruction of temperature variance \(\eta _\theta \equiv \epsilon _\theta /\epsilon \). Here, the latter two parameters are collapsed into a single atmospheric stability parameter z / L using Monin–Obukhov similarity theory, where z is the height above the Earth’s surface, and L is the Obukhov length corresponding to \(\{Ri,\eta _\theta \}\). Model outputs of the one-dimensional velocity spectra, as well as cospectra of the streamwise and/or vertical velocity components, and/or temperature, and cross-spectra for the spatial separation of all three velocity components and temperature, are compared with measurements. As a function of the four model parameters, spectra and cospectra are reproduced quite well, but horizontal temperature fluxes are slightly underestimated in stable conditions. In moderately unstable stratification, our model reproduces spectra only up to a scale \(\sim \) 1 km. The model also overestimates coherences for vertical separations, but is less severe in unstable than in stable cases.     

Magnetic Fields of Neutron Stars

This article briefly reviews our current understanding of the evolution of magnetic fields in neutron stars, which basically defines the evolutionary pathways between different observational classes of neutron stars. The emphasis here is on the evolution in binary systems and the newly emergent classes of millisecond pulsars.     

Characteristics of pegmatoidal granite exposed near Bayalan,Ajmer district,Rajasthan

The study involves the characterization of pegmatoidal granite, southeast of Beawar, Ajmer district, Rajasthan. Earlier researchers had described this granite as part of the BGC, basement to the Bhim Group of the Delhi Super Group rocks. However, the present study indicates that it is younger than the rocks of Bhim Group of South Delhi Fold Belt, into which it is intrusive. The intrusion is structurally controlled and the outcrop pattern is phacolithic. The granite had intruded post-D₂ deformation of the Delhi orogeny along the axial planes of D₂ folds. The intrusion has also resulted in the formation of a contact aureole about the calc gneisses.     

Eutrophication,health risk assessment and spatial analysis of water quality in Gucheng Lake,China

The water characteristics of the Gucheng Lake, such as eutrophication, health and spatial distribution, were investigated. On the basis of the trophic state index (TSI) and entropy weight, a synthesized trophic state index (STSI) model was established to assess lake eutrophication condition through calculating STSI, choosing TP, TN, COD, BOD and NH₃-N as trophic variables. The STSI ranged from 50.58 to 62.44, which showed that the water has been between eutrophic and supereutrophic. A histogram was applied to health risk assessment which was analyzed from carcinogenic substances (Cr⁺⁶, As and Cd) and non-carcinogenic substances (hydroxybenzene, Pb, Hg, CN⁻ and NH₃), and the results showed that the former was much greater than the latter for effect. The total risk for each resident caused by all pollutants ranged from 5.18E-05 to 8.34E-05, which is far higher than the standard, recommended by Sweden Bureau of Environment Protection and Holland Ministry of Building and Environment Protection (1.0E-05). Cluster analysis was used to detect similarities and dissimilarities among the seven sampling sites and explain the observed clustering in terms of affected conditions. Twenty-one variables were used to divide seven sampling sites into three groups, namely, north lake, south lake and lake center.     

Microstructure characteristics and forming environment of late Quaternary Period loess in the Loess Plateau of China

Since the late Quaternary Period, the rapid rising of the northeastern Qinghai-Tibetan Plateau has greatly changed the East Asian climate and formed different regional monsoon climates. Various microstructures of the loess in northern China have formed under a variety of climatic conditions. The scanning electron microscope (SEM) and energy spectrum analysis are used in this paper to study the relationship between the indexes of loess microstructures and the forming climates, and the indexes include the diameter of sand grains, Ca/Fe value and the characteristic shapes of the loess from SEM microstructures pictures. In terms of their respective climatic circumstances, the major microstructures of regional loess may be classified into nine categories according to their forms and particle sizes, such as loess formed in near-sand source, loess of granule sand dropping, and loess formed in hot and rainy places, i.e. with the loess SEM pictures, climates of about 15 ka b.p. in different places may be evaluated. In conclusion, the clear and distinguishable loess microstructures and their indexes in the Loess Plateau of China can also deduce the evolution of climate, such as warm or cold and wet or dry, and even sandstorm activities when the loess is deposited.     

Stochastic evaluation of simple pairing approaches to reconstruct incomplete rainfall time series

Two-station pairing approaches are routinely used to infill missing information in incomplete rainfall databases. We evaluated the performance of three simple methodologies to reconstruct incomplete time series in presence of variable nonlinear correlation between data pairs. Nonlinearity stems from the statistics describing the marginal peak-over-threshold (POT) values of rainfall events. A Monte Carlo analysis was developed to quantitatively assess expected errors from the use of chronological pairing (CP) with linear and nonlinear regression and frequency pairing (FP). CP is based on a priori selection of regression functions, while FP is based on matching the probability of non-exceedance of an event from one time series with the probability of non-exceedance of a similar event from another time series. We adopted a generalized Pareto (GP) model to describe POT events, and a t-copula algorithm to generate reference nonlinearly correlated pairs of random temporal distributions distributed according with the GP model. The results suggest that the optimal methodology strongly depends on GP statistics. In general, CP seems to provide the lowest errors when GP statistics were similar and correlation became linear; we found that a power-2 function performs well for the selected statistics when the number of missing points is limited. FP outperforms the other methods when POT statistics are different and variables are markedly nonlinearly correlated. Ensemble-based results seem to be supported by the analysis of observed precipitation at two real-world gauge stations.