Pullout Response of Uniaxial Geogrid in Tire Shred–Sand Mixtures

Use of tire shred–soil mixtures as backfill materials in mechanically stabilized earth walls has several advantages over other backfill materials: (1) good drainage, (2) high shear strength, and (3) low compacted unit weight. This paper presents the results of laboratory pullout tests performed on uniaxial geogrid embedded in tire shred–sand mixtures. The effects of tire shred size, tire shred–sand mixing ratio and confining pressure on the interaction between the geogrid and tire shred–sand mixtures are evaluated. Three sizes of tire shreds are considered: tire chips (with 9.5 mm nominal size), tire shreds 50-to-100 mm long and tire shreds 100-to-200 mm in length, with mixing ratios of 0, 12, 25 and 100 % of tire shreds in the mixtures (by weight). Based on compaction testing of a number of mixtures, the optimal mixing proportion of tire shreds and sand was found to lie between 25/75 and 30/70 (by weight of tire shred and sand); this is equivalent to approximately 40/60 and 50/50, respectively, by volume of tire shreds and sand. The pullout resistance of a geogrid embedded in tire shred–sand mixtures is significantly higher than that of the same geogrid embedded in tire shreds only. The size of the tire shreds has negligible effect on the pullout resistance of a geogrid embedded in mixtures prepared with either low (12/88 mix) or high (100/0 mix) tire shred content. However, when the 25/75 mixture is used, greater geogrid pullout resistance was obtained for the geogrid embedded in tire chip–sand mixtures than in tire shred–sand mixtures.     

A GNSS interference identification using an adaptive cascading IIR notch filter

A low-complexity time-domain approach for global navigation satellite systems is proposed to detect and identify single-tone, multi-tone, swept continuous wave interference (CWI) and band-limited white Gaussian noise (BLWN). An adaptive notch filter and adaptive cascading filter structure are employed to identify the type of interference signals. The number of the cascading stages is selected by comparing the total power in receiver bandpass, and after, passing the adaptive notch filter. For this reason, the proposed filter structure is more efficient in identifying and mitigating interference signals than the conventional filter structure. In addition, the automatic gain control gain is used to detect the existence of continuous wave interference. The performance of the interference detection and identification method is evaluated for the cases of GPS signal in the presence of single-tone, multi-tone, swept CWI and BLWN.     

Graded-Density Reservoirs for Accessing High Stress Low Temperature Material States

In recently developed laser-driven shockless compression experiments an ablatively driven shock in a primary target is transformed into a ramp compression wave in a secondary target via unloading followed by stagnation across an intermediate vacuum gap. Current limitations on the achievable peak longitudinal stresses are limited by the ability of shaping the temporal profile of the ramp compression pulse. We report on new techniques using graded density reservoirs for shaping the loading profile and extending these techniques to high peak pressures.     

Assessment of future runoff trends under multiple climate change scenarios in the Willamette River Basin,Oregon, USA

We investigated trends in future seasonal runoff components in the Willamette River Basin (WRB) of Oregon for the twenty‐first century. Statistically downscaled climate projections by Climate Impacts Group (CIG), eight different global climate model (GCM) simulations with two different greenhouse gas (GHG) emission scenarios, (A1B and B1), were used as inputs for the US Geological Survey's Precipitation Runoff Modelling System. Ensemble mean results show negative trends in spring (March, April and May) and summer (June, July and August) runoff and positive trends in fall (September, October and November) and winter (December, January and February) runoff for 2000–2099. This is a result of temperature controls on the snowpack and declining summer and increasing winter precipitation. With temperature increases throughout the basin, snow water equivalent (SWE) is projected to decline consistently for all seasons. The decreases in the centre of timing and 7‐day low flows and increases in the top 5% flow are caused by the earlier snowmelt in spring, decreases in summer runoff and increases in fall and winter runoff, respectively. Winter runoff changes are more pronounced in higher elevations than in low elevations in winter. Seasonal runoff trends are associated with the complex interactions of climatic and topographic variables. While SWE is the most important explanatory variable for spring and winter runoff trends, precipitation has the strongest influence on fall runoff. Spatial error regression models that incorporate spatial dependence better explain the variations of runoff trends than ordinary least‐squares (OLS) multiple regression models. Our results show that long‐term trends of water balance components in the WRB could be highly affected by anthropogenic climate change, but the direction and magnitude of such changes are highly dependent on the interactions between climate change and land surface hydrology. This suggests a need for spatially explicit adaptive water resource management within the WRB under climate change. Copyright © 2010 John Wiley & Sons, Ltd.     

Estimation of the Roll Hydrodynamic Moment Model of a Ship by Using the System Identification Method and the Free Running Model Test

When a fast container ship or a naval vessel turns, accompanying roll motions occur. This roll effect must be considered in the horizontal equations of the motion of the ship to predict the maneuverability of the ship properly. In this paper, a new method for determining a model structure of the hydrodynamic roll moment acting on a ship and for estimating the hydrodynamic coefficients is proposed. The method utilizes a system identification technique with the data from sea trial tests or from free running model (FRM) tests. To obtain motion data that is applied to the proposed algorithm, an FRM of a large container ship was developed. Using this model ship, standard maneuvering tests were carried out on a small body of water out of doors. A hydrodynamic roll moment model was constructed utilizing the data from turning circle tests and a 20-20 zig-zag test. This was then confirmed through a 10-10 zig-zag test. It was concluded that a model structure of the hydrodynamic roll moment model could be established without difficulty through a system identification method and FRM tests.     

Aquifer Characterization Using Fiber Bragg Grating Multi-Level Monitoring System

Groundwater responses measured from multiple wells at different depths are essential for delineating the aquifer heterogeneity using hydraulic tomography (HT). In general, conducting HT requires many wells because traditional well monitoring is usually partially open at a specific depth interval or is fully penetrating. Accordingly, conducting an HT survey is typically costly and time-consuming. To tackle these issues, a new multi-level monitoring system (MLMS) for the HT survey was developed using the fiber Bragg grating (FBG) technique. This FBG MLMS could collect the depth-discrete groundwater observations from a fully penetrated 2-inch well. Three field campaigns were conducted to validate the capability of the FBG MLMS for HT surveys. The results show that the accuracy and stability of this MLMS are reliable and that FBG MLMS is beneficial for conducting an HT survey. Specifically, compared to the traditional monitoring well in an injection event, this FBG MLMS can concurrently cause an increase in the number of cross-hole tests several times and collect many more head observations than the standard methods, resulting in the observed flow fields efficiently reaching ergodic conditions and effectively improving the accuracy of the estimated hydraulic heterogeneity. Therefore, the FBG MLMS could be an alternative MLMS for efficiently and economically conducting an HT survey.     

On a novel approach to forecast sparse rare events: applications to Parkfield earthquake prediction

Natural Hazards - Rare events are plentiful in nature and most of them have devastating consequences on human lives and property. Modeling such events is intrinsically challenging due to their very...     

Potential impacts of northeastern Eurasian snow cover on generation of dust storms in northwestern China during spring

The effects of the northeastern Eurasian snow cover on the frequency of spring dust storms in northwestern China have been examined for the period 1979–2007. Averaged over all 43 stations in northwestern China, a statistically significant relationship has been found between dust-storm frequency (DSF) and Eurasian snow-water equivalent (SWE) during spring: mean DSF of 7.4 and 3.3 days for years of high- and low SWE, respectively. Further analyses reveal that positive SWE anomalies enhance the meridional gradients of the lower tropospheric temperatures and geopotential heights, thereby strengthening westerly jets and zonal wind shear over northwestern China and western Inner Mongolia of China, the regions of major dust sources. The anomalous atmospheric circulation corresponding to the Eurasian SWE anomalies either reinforces or weakens atmospheric baroclinicity and cyclogenesis, according to the sign of the anomaly, to affect the spring DSF. This study suggests that Eurasian SWE anomalies can be an influential factor of spring DSF in northwestern China and western Inner Mongolia of China.     

Statistical decadal predictions for sea surface temperatures: a benchmark for dynamical GCM predictions

Accurate decadal climate predictions could be used to inform adaptation actions to a changing climate. The skill of such predictions from initialised dynamical global climate models (GCMs) may be assessed by comparing with predictions from statistical models which are based solely on historical observations. This paper presents two benchmark statistical models for predicting both the radiatively forced trend and internal variability of annual mean sea surface temperatures (SSTs) on a decadal timescale based on the gridded observation data set HadISST. For both statistical models, the trend related to radiative forcing is modelled using a linear regression of SST time series at each grid box on the time series of equivalent global mean atmospheric CO₂ concentration. The residual internal variability is then modelled by (1) a first-order autoregressive model (AR1) and (2) a constructed analogue model (CA). From the verification of 46 retrospective forecasts with start years from 1960 to 2005, the correlation coefficient for anomaly forecasts using trend with AR1 is greater than 0.7 over parts of extra-tropical North Atlantic, the Indian Ocean and western Pacific. This is primarily related to the prediction of the forced trend. More importantly, both CA and AR1 give skillful predictions of the internal variability of SSTs in the subpolar gyre region over the far North Atlantic for lead time of 2–5 years, with correlation coefficients greater than 0.5. For the subpolar gyre and parts of the South Atlantic, CA is superior to AR1 for lead time of 6–9 years. These statistical forecasts are also compared with ensemble mean retrospective forecasts by DePreSys, an initialised GCM. DePreSys is found to outperform the statistical models over large parts of North Atlantic for lead times of 2–5 years and 6–9 years, however trend with AR1 is generally superior to DePreSys in the North Atlantic Current region, while trend with CA is superior to DePreSys in parts of South Atlantic for lead time of 6–9 years. These findings encourage further development of benchmark statistical decadal prediction models, and methods to combine different predictions.     

Real-time multi-model decadal climate predictions

We present the first climate prediction of the coming decade made with multiple models, initialized with prior observations. This prediction accrues from an international activity to exchange decadal predictions in near real-time, in order to assess differences and similarities, provide a consensus view to prevent over-confidence in forecasts from any single model, and establish current collective capability. We stress that the forecast is experimental, since the skill of the multi-model system is as yet unknown. Nevertheless, the forecast systems used here are based on models that have undergone rigorous evaluation and individually have been evaluated for forecast skill. Moreover, it is important to publish forecasts to enable open evaluation, and to provide a focus on climate change in the coming decade. Initialized forecasts of the year 2011 agree well with observations, with a pattern correlation of 0.62 compared to 0.31 for uninitialized projections. In particular, the forecast correctly predicted La Niña in the Pacific, and warm conditions in the north Atlantic and USA. A similar pattern is predicted for 2012 but with a weaker La Niña. Indices of Atlantic multi-decadal variability and Pacific decadal variability show no signal beyond climatology after 2015, while temperature in the Niño3 region is predicted to warm slightly by about 0.5 °C over the coming decade. However, uncertainties are large for individual years and initialization has little impact beyond the first 4 years in most regions. Relative to uninitialized forecasts, initialized forecasts are significantly warmer in the north Atlantic sub-polar gyre and cooler in the north Pacific throughout the decade. They are also significantly cooler in the global average and over most land and ocean regions out to several years ahead. However, in the absence of volcanic eruptions, global temperature is predicted to continue to rise, with each year from 2013 onwards having a 50 % chance of exceeding the current observed record. Verification of these forecasts will provide an important opportunity to test the performance of models and our understanding and knowledge of the drivers of climate change.