Development of a hybrid simulation controller for full‐scale experimental investigation of seismic retrofits for soft‐story woodframe buildings

Hybrid simulations of a full‐scale soft‐story woodframe building specimen with various retrofits were carried out as part of the Network for Earthquake Engineering Simulation Research project – NEES‐Soft: seismic risk reduction for soft‐story woodframe buildings. The test structure in the hybrid simulation was a three‐story woodframe building that was divided into a numerical substructure of the first story with various retrofits and a full‐scale physical substructure of the upper two stories. Four long‐stroke actuators, two at the second floor and two at the roof diaphragm, were attached to the physical substructure to impose the simulated seismic responses including both translation and in‐plane rotation. Challenges associated with this first implementation of a full‐scale hybrid simulation on a woodframe building were identified. This paper presents the development and validation of a scalable and robust hybrid simulation controller for efficient test site deployment. The development consisted of three incremental validation phases ranging from small‐scale, mid‐scale, to full‐scale tests conducted at three laboratories. Experimental setup, procedure, and results of each phase of the controller development are discussed, demonstrating the effectiveness and efficiency of the incremental controller development approach for large‐scale hybrid simulation programs with complex test setup. Copyright © 2016 John Wiley & Sons, Ltd.     

Silicate‐oxide mineral chemistry of mafic–ultramafic rocks as an indicator of the roots of an island arc: The Chilas Complex,Kohistan (Pakistan)

The Chilas Complex is a major lower crustal component of the Cretaceous Kohistan island arc and one of the largest exposed slices of arc magma chamber in the world. Covering more than 8000 km², it reaches a current tectonic width of around 40 km. It was emplaced at 85 Ma during rifting of the arc soon after the collision of the arc with the Karakoram plate. Over 85% of the Complex comprises homogeneous, olivine‐free gabbronorite and subordinate orthopyroxene–quartz diorite association (MGNA), which contains bodies of up to 30 km² of ultramafic–mafic–anorthositic association (UMAA) rocks. Primary cumulate textures, igneous layering, and sedimentary structures are well preserved in layered parts of the UMAA in spite of pervasive granulite facies metamorphism. Mineral analyses show that the UMAA is characterized by more magnesian and more aluminous pyroxene and more calcic plagioclase than those in the MGNA. High modal abundances of orthopyroxene, magnetite and ilmenite (in MGNA), general Mg–Fe–Al spatial variations, and an MFA plot of whole‐rock analyses suggest a calc‐alkaline origin for the Complex. Projection of the pyroxene compositions on the Wo–En–Fs face is akin to those of pyroxenes from island arcs gabbros. The presence of highly calcic plagioclase and hornblende in UMAA is indicative of hydrous parental arc magma. The complex may be a product of two‐stage partial melting of a rising mantle diaper. The MGNA rocks represent the earlier phase melting, whereas the UMAA magma resulted from the melting of the same source depleted by the extraction of the earlier melt phase. Some of the massive peridotites in the UMAA may either be cumulates or represent metasomatized and remobilized upper mantle. The Chilas Complex shows similarities with many other (supra)subduction‐related mafic–ultramafic complexes worldwide.     

Impact of draining hilly lands on runoff and on‐site erosion: a case study from humid Ethiopia

The use of drainage ditches on farmland has an impact on erosion processes both on‐site and off‐site, though their environmental impacts are not unequivocal. Here we study the runoff response and related rill erosion after installing drainage ditches and assess the effects of stone bunds in north Ethiopia. Three different land management systems were studied in 10 cropland catchments around Wanzaye during the rainy season of 2013: (1) the exclusive use of drainage ditches (locally called feses), (2) the exclusive use of stone bunds, and (3) a mixture of both systems. Stone bunds are an effective soil and water conservation technique, making the land more resistant against on‐site erosion, and allowing feses to be installed at a larger angle with the contour. The mean rill volumes for the 10 studied cropland catchments during the rainy season of 2013 was 3.73 ± 4.20 m³ ha^?1 corresponding to a soil loss of 5.72 ± 6.30 ton ha^?1. The establishment of feses causes larger rill volumes (R = 0.59, N = 10), although feses are perceived as the best way to avoid soil erosion when no stone bunds are present. The use of feses increases event‐based runoff coefficients (RCs) on cropland from c. 5% to values up to 39%. Also, a combination of low stone bund density and high feses density results in a higher RC, whereas catchments with a high stone bund density and low feses density have a lower RC. Peak runoff discharges decrease when stone bund density increases, whereas feses density is positively related to the peak runoff discharge. A multiple linear relation in which both feses and stone bund densities are used as explanatory variable, performs best in explaining runoff hydrograph peakedness (R² = 83%). Copyright © 2015 John Wiley & Sons, Ltd.     

Distinct patterns of interaction between vegetation and morphodynamics

Dynamic interaction between river morphodynamics and vegetation affects river channel patterns and populations of riparian species. A range of numerical models exists to investigate the interaction between vegetation and morphodynamics. However, many of these models oversimplify either the morphodynamics or the vegetation dynamics, which hampers the development of predictive models for river management. We have developed a model coupling advanced morphodynamics and dynamic vegetation, which is innovative because it includes dynamic ecological processes and progressing vegetation characteristics as opposed to commonly used static vegetation without growth and mortality. Our objective is to understand and quantify the effects of vegetation‐type dependent settling, growth and mortality on the river pattern and morphodynamics of a meandering river. We compared several dynamic vegetation scenarios with different functional trait sets to reference scenarios without vegetation and with static vegetation without growth and mortality. We find distinct differences in morphodynamics and river morphology. The default dynamic vegetation scenario, based on two Salicaceae species, shows an active meandering behaviour, while the static vegetation scenario develops into a static, vegetation‐dominated state. The diverse vegetation patterns in the dynamic scenario reduce lateral migration, increase meander migration rate and create a smoother floodplain compared to the static scenario. Dynamic vegetation results in typical vegetation patterns, vegetation age distribution and river patterns as observed in the field. We show a quantitative interaction between vegetation and morphodynamics, where increasing vegetation cover decreases sediment transport rates. Furthermore, differences in vegetation colonization, density and survival create distinct patterns in river morphology, showing that vegetation properties and dynamics drive the formation of different river morphologies. Our model demonstrates the high sensitivity of channel morphodynamics to various species traits, an understanding which is required for floodplain and stream restoration and more realistic modelling of long‐term river development. Copyright © 2015 John Wiley & Sons, Ltd.     

The role of long‐term human impact on avulsion and fan development

This study aims to understand (mainly qualitatively) the long‐term role of human impact on avulsion processes and the development of fluvial (mega‐) fans in semi‐arid environments. In this paper we refer to human impact as the direct influences of actions on the river's hydraulics (i.e. flow regulation, flow diversion and channel engineering). In five case‐studies drawn from the Khuzestan plains in southwest Iran we have analysed the setup and triggering conditions of specific avulsions that occurred in the past (timescale of millennia) and identified the role of human interference in their causation. Our analysis is based on the integration of historical, archaeological, geomorphological and geological data. Through this study we demonstrate that avulsions in the Khuzestan plains are the result of long‐term and complex interplay between multiple human‐induced and natural causes. In similar ways human‐induced actions may play important roles during different phases of avulsion development. The ‘success‘ of an avulsion in the post‐triggering phase may be defined by human‐induced setup causes as well as morphodynamic processes. We suggest that present‐day flood events may be partly inherited from long‐term human alterations of the natural processes. These finding could have implications for any fluvial system (e.g. distributive fluvial systems, deltas) where avulsion plays a major role in their development and research tends to emphasize on natural mechanisms. Copyright © 2016 John Wiley & Sons, Ltd.     

Application of wavelet-artificial intelligence hybrid models for water quality prediction: a case study in Aji-Chay River,Iran

The accuracy of Artificial Neural Network (ANN), Adaptive Neuro-Fuzzy Inference System (ANFIS), wavelet-ANN and wavelet-ANFIS in predicting monthly water salinity levels of northwest Iran’s Aji-Chay River was assessed. The models were calibrated, validated and tested using different subsets of monthly records (October 1983 to September 2011) of individual solute (Ca²⁺, Mg²⁺, Na⁺, SO₄ ^2? and Cl^?) concentrations (input parameters, meq L^?1), and electrical conductivity-based salinity levels (output parameter, µS cm^?1), collected by the East Azarbaijan regional water authority. Based on the statistical criteria of coefficient of determination (R²), normalized root mean square error (NRMSE), Nash–Sutcliffe efficiency coefficient (NSC) and threshold statistics (TS) the ANFIS model was found to outperform the ANN model. To develop coupled wavelet-AI models, the original observed data series was decomposed into sub-time series using Daubechies, Symlet or Haar mother wavelets of different lengths (order), each implemented at three levels. To predict salinity input parameter series were used as input variables in different wavelet order/level-AI model combinations. Hybrid wavelet-ANFIS (R² = 0.9967, NRMSE = 2.9 × 10^?5 and NSC = 0.9951) and wavelet-ANN (R² = 0.996, NRMSE = 3.77 × 10^?5 and NSC = 0.9946) models implementing the db4 mother wavelet decomposition outperformed the ANFIS (R² = 0.9954, NRMSE = 3.77 × 10^?5 and NSC = 0.9914) and ANN (R² = 0.9936, NRMSE = 3.99 × 10^?5 and NSC = 0.9903) models.     

Uncertainty propagation of arbitrary probability density functions applied to upscaling of transmissivities

In many fields of study, and certainly in hydrogeology, uncertainty propagation is a recurring subject. Usually, parametrized probability density functions (PDFs) are used to represent data uncertainty, which limits their use to particular distributions. Often, this problem is solved by Monte Carlo simulation, with the disadvantage that one needs a large number of calculations to achieve reliable results. In this paper, a method is proposed based on a piecewise linear approximation of PDFs. The uncertainty propagation with these discretized PDFs is distribution independent. The method is applied to the upscaling of transmissivity data, and carried out in two steps: the vertical upscaling of conductivity values from borehole data to aquifer scale, and the spatial interpolation of the transmissivities. The results of this first step are complete PDFs of the transmissivities at borehole locations reflecting the uncertainties of the conductivities and the layer thicknesses. The second step results in a spatially distributed transmissivity field with a complete PDF at every grid cell. We argue that the proposed method is applicable to a wide range of uncertainty propagation problems.