Optimal yield level of bilinear seismic isolation devices

The yield level of an insulator is one of the important parameters which are related to responses and absorbing energy under seismic input energy in isolated structures. The purpose of this paper is to determine the optimal ratios of yield force of the isolator (Q_y) to the total weight of the structures (W). To obtain the optimal ratio, 1044 two-degree-of-freedom isolated bridge models, which have bilinear isolators, were selected. These 2-DOF isolated bridge models with superstructure isolation can consider pier flexibility and various parameters of the isolator. Two formulas for determining the optimal yield ratio are proposed and compared with the previous researches. RAE (the ratio of absorbed energy by the isolator to the total input energy) is related directly to structural responses, and Optimal Yield Ratio (OYR), defined as a yield ratio at maximum RAE, can be obtained from the relationship between RAE and Q_y/W. Here, we found that RAE is a reliable factor to evaluate OYR, and it is proportional to earthquake amplitudes under the same kinds of earthquake loadings. Using the proposed formulas, OYR is determined and the optimal yield force of the isolator can be obtained easily and reliably at a seismic isolation design stage. Copyright © 1999 John Wiley & Sons, Ltd.     

Comparison of abstraction scenarios simulated by SWAT and SWAT-MODFLOW

In hydrological modelling of catchments, wherein streams are groundwater-fed, an accurate representation of groundwater processes and their interaction with surface water is crucial. With this purpose, a coupled model was recently developed linking SWAT (Soil and Water Assessment Tool) with the fully-distributed groundwater model MODFLOW (Modular Groundwater Flow). In this study, SWAT and SWAT-MODFLOW were applied to a Danish groundwater-dominant catchment, simulating groundwater abstraction scenarios and assessing the benefits and drawbacks of SWAT-MODFLOW. Both models demonstrated good performance. However, SWAT-MODFLOW provided more realistic outputs when simulating abstraction: the decrease in streamflow was similar to the volume of water abstracted, while in SWAT the impact was negligible. SWAT also showed impacts on streamflow only when abstractions were taken from the shallow aquifer, not from the deep aquifer. Overall, SWAT-MODFLOW demonstrated wider possibilities for groundwater analysis, providing more insights than SWAT in supporting decision making in relation to environmental assessment.     

Impact of sensor measurement error on sensor positioning in water quality monitoring networks

This paper studies the impact of sensor measurement error on designing a water quality monitoring network for a river system, and shows that robust sensor locations can be obtained when an optimization algorithm is combined with a statistical process control (SPC) method. Specifically, we develop a possible probabilistic model of sensor measurement error and the measurement error model is embedded into a simulation model of a river system. An optimization algorithm is used to find the optimal sensor locations that minimize the expected time until a spill detection in the presence of a constraint on the probability of detecting a spill. The experimental results show that the optimal sensor locations are highly sensitive to the variability of measurement error and false alarm rates are often unacceptably high. An SPC method is useful in finding thresholds that guarantee a false alarm rate no more than a pre-specified target level, and an optimization algorithm combined with the thresholds finds a robust sensor network.     

Effects of fluid displacement pattern on complex electrical impedance in Berea sandstone over frequency range 104–106 Hz

To better understand the effect of fluid distribution on the electric response of rocks saturated with oil and brine, we conducted experimental studies on the complex electrical impedance in a Berea sandstone, together with in situ acquisitions of oil distribution images employing a high‐resolution medical X‐ray computed tomography. We performed two tests of brine displacement by oil under high (10 MPa) and low (5 MPa) pressures, which were accompanied by fingering and stable displacement patterns, respectively. The measured complex impedance data were fitted to the Cole model to obtain the resistance, capacitance, peak frequency of the imaginary impedance, and the exponent α of the rock–fluid system. With increasing oil saturation, the resistance showed an increasing trend, whereas the other three parameters decreased. The fingering displacement exhibited lower resistance and capacitance than the stable displacement. The analysis of the resistance changes using a simple parallel connection model indicates that there are more components of residual brine in parallel connections in the fingering pattern than in the stable displacement pattern at the same saturation. We also interpreted the normalised changes in the capacitance (or apparent dielectric constant) with respect to the oil saturation via an analysis of the shape factor of fluid distribution based on the Maxwell–Wagner–Brugermann–Hanai model. The changes in the shape factor suggest that the pinch‐off of the brine in parallel connection by the oil is a dominant mechanism reducing the capacitance. In the stable displacement, most of the connections in the brine phase are immediately pinched off by oil displacement front at a local oil saturation of 65%. Conversely, in the fingering displacement, there is a transition from the bulk or layered brine to the pinched‐off at a local oil saturation below 60%. The analyses indicate that the difference in the fluid distribution under different fluid conditions is responsible for the non‐Archie behaviour.     

A generalized transformation approach for simulating steady-state variably-saturated subsurface flow

A numerical method is proposed to accurately and efficiently compute a direct steady-state solution of the nonlinear Richards equation. In the proposed method, the Kirchhoff integral transformation and a complementary transformation are applied to the governing equation in order to separate the nonlinear hyperbolic characteristic from the linear parabolic part. The separation allows the transformed governing equation to be applied to partially- to fully-saturated systems with arbitrary constitutive relations between primary (pressure head) and secondary variables (relative permeability). The transformed governing equation is then discretized with control volume finite difference/finite element approximations, followed by inverse transformation. The approach is compared to analytical and other numerical approaches for variably-saturated flow in 1-D and 3-D domains. The results clearly demonstrate that the approach is not only more computationally efficient but also more accurate than traditional numerical solutions. The approach is also applied to an example flow problem involving a regional-scale variably-saturated heterogeneous system, where the vadose zone is up to 1 km thick. The performance, stability, and effectiveness of the transform approach is exemplified for this complex heterogeneous example, which is typical of many problems encountered in the field. It is shown that computational performance can be enhanced by several orders of magnitude with the described integral transformation approach.     

Modeling a major source of economic resilience to disasters: recapturing lost production

Terrorist attacks and natural disasters have potentially severe economic consequences in terms of property damage and business interruption. However, experience from the September 11 World Trade Center attack and other disasters indicates that the economy has a great deal of resilience. This refers to the ability to dampen the maximum potential economic output (business interruption) loss. One of the most prominent sources of resilience is the ability of businesses to reschedule, or recapture, lost production after the event. Although there have been applications of a fixed parameter recapture factor for each of several aggregated sectors of the economy, there has been little formal analysis of this resilience action. This study offers a theoretic framework for analyzing production rescheduling. It distinguishes the major conditions influencing two aspects that have previously been neglected: (1) the maximum time span over which the rescheduling can take place and (2) the likely decline of the maximum recapture as the business interruption increases. We divide the relevant time path into two periods after recovery. One is a function of a recaptured output path after recovery to the status of normal production. The other is a function for the maximum recaptured production, based on the recaptured output path. The recaptured output path function is assumed to follow a normal distribution function, and hence, total recaptured output follows the cumulative normal distribution function over time after productive capacity is restored. Also, we develop a new cumulative normal distribution function for interruption time duration, which is symmetric with respect to the output axis. This recapture function has unknown parameters. Empirical data on the recaptured amounts following an actual disaster can be used to estimate the parameters of this function using simulation methods.     

Ecosystem responses to climate change in a large on-river reservoir, Lake Paldang, Korea

The impact of climate change on a large river reservoir ecosystem was investigated. Long-term meteorological data showed that recent climate change, including warmer winters, increased precipitation intensity and extended dry periods, may have influenced the basin of Lake Paldang, the most downstream reservoir of a series of on-river reservoirs. Extreme hydrologic events and climate warming, acting independently and in combination, appear to be related to changes in the Lake Paldang ecosystem. A significant increase in chlorophyll a concentrations in early spring corresponded to the timing of ice break-up. An increase in winter temperatures, which resulted in a shorter time period of ice-cover and earlier ice break-up, appears to have stimulated phytoplankton growth in winter and early spring. Repeated intensive and extended influxes of turbid water, associated with more frequent extreme rainfall events, have increased concentration of suspended solids and may have influenced the biotic community structure of Lake Paldang. In the mid-2000s, the area vegetated by submerged hydrophytes, the abundance and biomass of the phylum Mollusca, as well as the abundance of fish from the subfamily Acheilognathinae, which spawn in the body of bivalve molluscs, was all smaller than in the late 1980s and early 1990s. Together, these results suggest that climate change may have contributed directly and indirectly to changes in each trophic level of the Lake Paldang ecosystem.     

Ensemble-based landslide susceptibility maps in Jinbu area, Korea

Ensemble techniques were developed, applied and validated for the analysis of landslide susceptibility in Jinbu area, Korea using the geographic information system (GIS). Landslide-occurrence areas were detected in the study by interpreting aerial photographs and field survey data. Landslide locations were randomly selected in a 70/30 ratio for training and validation of the models, respectively. Topography, geology, soil and forest databases were also constructed. Maps relevant to landslide occurrence were assembled in a spatial database. Using the constructed spatial database, 17 landslide-related factors were extracted. The relationships between the detected landslide locations and the factors were identified and quantified by frequency ratio, weight of evidence, logistic regression and artificial neural network models and their ensemble models. The relationships were used as factor ratings in the overlay analysis to create landslide susceptibility indexes and maps. Then, the four landslide susceptibility maps were used as new input factors and integrated using the frequency ratio, weight of evidence, logistic regression and artificial neural network models as ensemble methods to make better susceptibility maps. All of the susceptibility maps were validated by comparison with known landslide locations that were not used directly in the analysis. As the result, the ensemble-based landslide susceptibility map that used the new landslide-related input factor maps showed better accuracy (87.11% in frequency ratio, 83.14% in weight of evidence, 87.79% in logistic regression and 84.54% in artificial neural network) than the individual landslide susceptibility maps (84.94% in frequency ratio, 82.82% in weight of evidence, 87.72% in logistic regression and 81.44% in artificial neural network). All accuracy assessments showed overall satisfactory agreement of more than 80%. The ensemble model was found to be more effective in terms of prediction accuracy than the individual model.