Airborne dust distribution in longwall faces

Summary The generation and transportation of airborne dust is governed mainly by the velocity and the movement pattern of the ventilation air in longwall faces. Generally speaking, the higher the air velocity, the more airborne dust will be generated and the further dust of a given size will be carried away from the source. In order to effectively prevent or reduce the production and spread of the airborne dust, the airborne dust concentration distribution at a longwall face must be known in advance. This paper presents the measurement methodology, data analyses and dust distributions in five longwall faces.     

Variation of initial Th/Th and limits of high precision U-Th dating of shallow-water corals

One hundred eighty U-Th data, including 23 isochrons on 24 pristine modern and Holocene corals and 33 seawater samples, were analyzed using sector-field mass spectrometry to understand the variability of initial ²³⁰Th/²³²Th (²³⁰Th/²³²Th₀). This dataset allows us to further assess the accuracy and precision of coral ²³⁰Th dating method. By applying quality control, including careful sampling and subsampling protocols and the use of contamination-free storage and workbench spaces, the resulting low procedural blanks give an equivalent uncertainty in age of only ±0.2-0.3 yr for 1-2 g of coral sample. Using site-specific ²³⁰Th/²³²Th₀ values or isochron techniques, our study demonstrates that corals with an age less than 100 yrs can be ²³⁰Th-dated with precisions of ±1 yr. Six living subtidal coral samples were collected from two continental shelf sites, Nanwan off southern Taiwan in the western Pacific and Son Tra off central Vietnam in the South China Sea; one coral core was drilled from an open-ocean site, Santo Island, Vanuatu, in the western tropical Pacific; and modern and fossil intertidal coral slabs, 17 in total, were cut from six sites around the islands of Simeulue, Lago, North Pagai and South Pagai of Sumatra in the eastern Indian Ocean. The results indicate that the main source of thorium is the dissolved phase of seawater, with variation of ²³⁰Th/²³²Th₀ depending on local hydrology. With intense input of terrestrial material, low ²³⁰Th/²³²Th₀ atomic ratios of 4.9 × 10⁻⁶ and 3.2 × 10⁻⁶ with a 10% variation are observed in Nanwan and Son Tra, respectively. At the Santo site, we find a value of 5.6 × 10⁻⁶ at 4 horizons and one high value of 24 × 10⁻⁶ in a sample from AD 1974.6 ± 0.5, likely due to the upwelling of cold water during a La Niña event between AD 1973 and 1976. The natural dynamics of ²³⁰Th/²³²Th₀ recorded in the intertidal corals at sites in the Sumatran islands are complicated so that this value varies significantly from 3.0 to 9.4 × 10⁻⁶. Three of the 141 modern coral ²³⁰Th ages differ from their true ages by −23 to +4, indicating the presence of detrital material with anomalous ²³⁰Th/²³²Th values. Duplicate measurement of coeval subsamples is therefore recommended to verify the age accuracy. This improved high precision coral ²³⁰Th dating method raises the prospects of refining the age models for band-counted and tracer-tuned chronologies and of advancing coral paleoclimate research.     

An intelligent and autonomous MEMS IMU/GPS integration scheme for low cost land navigation applications

An intelligent scheme to integrate inertial navigation system/global positioning system (GPS) is proposed using a constructive neural network (CNN) to overcome the limitations of current schemes, namely Kalman filtering (KF). The proposed CNN technique does not require prior knowledge or empirical trials to implement the proposed architecture since it is able to construct its architecture “on the fly,” based on the complexity of the vehicle dynamic variations. The proposed scheme is implemented and tested using Micro-electro-mechanical systems inertial measurement unit data collected in a land-vehicle environment. The performance of the proposed scheme is then compared with the multi-layer feed-forward neural networks (MFNN) and KF- based schemes in terms of positioning accuracy during GPS signal outages. The results are then analyzed and discussed in terms of positioning accuracy and learning time. The preliminary results presented in this article indicate that the positioning accuracy were improved by more than 55% when the MFNN and CNN-based schemes were implemented. In addition, the proposed CNN was able to construct the topology by itself autonomously on the fly and achieve similar prediction performance with less hidden neurons compared to MFNN-based schemes.     

An advanced analytical model for high damping rubber bearings

Base‐isolation technologies have been developed over the years in attempts to mitigate the effects of earthquakes on structures and potentially vulnerable contents in earthquake prone areas of the world. The high damping rubber bearing (HDRB) is a relatively recent and evolving technology of this kind. The isolator shifts the fundamental period of the base‐isolated structure to a value beyond the range of the plentiful energy‐containing periods of earthquake motions and supplies significant damping to dissipate energy caused by motions. Nevertheless, the highly non‐linear mechanical behaviour of the HDRB is so complex, especially at large strains, that it is difficult to model it analytically. In this paper, an extensive study of experimental tests for identifying the mechanical characteristics of the HDRB is presented. By modifying the Wen's model to include the rate‐dependent effects, an advanced analytical model in an incremental form for the HDRB is also proposed. A very good agreement between the analytical and experimental results has been obtained. It is illustrated that the proposed mathematical model can predict well the mechanical behaviour of HDRB bearings, even at large shear strain. Copyright © 2003 John Wiley & Sons, Ltd.     

Comparison of static-feedforward and dynamic-feedback neural networks for rainfall–runoff modeling

A systematic comparison of two basic types of neural network, static and dynamic, is presented in this study. Two back-propagation (BP) learning optimization algorithms, the standard BP and conjugate gradient (CG) method, are used for the static network, and the real-time recurrent learning (RTRL) algorithm is used for the dynamic-feedback network. Twenty-three storm-events, about 1632 rainfall and runoff data sets, of the Lan-Yang River in Taiwan are used to demonstrate the efficiency and practicability of the neural networks for one hour ahead streamflow forecasting. In a comparison of searching algorithms for a static network, the results show that the CG method is superior to the standard BP method in terms of the efficiency and effectiveness of the constructed network's performance. For a comparison of the static neural network using the CG algorithm with the dynamic neural network using RTRL, the results show that (1) the static-feedforward neural network could produce satisfactory results only when there is a sufficient and adequate training data set, (2) the dynamic neural network generally could produce better and more stable flow forecasting than the static network, and (3) the RTRL algorithm helps to continually update the dynamic network for learning—this feature is especially important for the extraordinary time-varying characteristics of rainfall–runoff processes.     

The assessment of high recharge areas using DO indicators and recharge potential analysis: a case study of Taiwan’s Pingtung plain

Identifying high groundwater recharge areas is important for the conservation of groundwater quality and quantity. A common practice used by previous studies is to estimate groundwater recharge potential (GRP) using recharge potential analysis (RPA) under different environments. These studies use the estimated GRP to identify the high potential groundwater recharge sites. However, the RPA parameters are subjectively defined for these previous studies. To remove the supposition, this study proposes a systematic approach that defines the RPA parameter values based on the theory of parameter identification. This study uses dissolved oxygen (DO) indicators to calibrate the RPA parameters. This calibration improves the correlation coefficient between the DO indicators and computed GRP values from 0.63 to 0.87. By comparing the initial values, these results indicate that the estimated RPA parameters better represent the field infiltration characteristic. This result also indicates that defining the RPA parameter values based on DO indicators is necessary and important for accuracy. These calibrated parameters are used to estimate the GRP distribution of Taiwan’s Pingtung Plain. The GRP values are delineated into five levels. High and excellent GRP areas are defined as high recharge areas, which compose about 26.74 % of the study area. Based on the proposed method, the estimated GRP distribution can accurately represent the study area’s field recharge characteristics. These study results can be a good reference for groundwater recharge analyses, specifically if well data is limited or difficult to obtain.     

The impact of the Changjiang River plume extension on the nanoflagellate community in the East China Sea

Variation in the summer nanoflagellate community on the continental shelf ecosystem of East China Sea (ECS) is closely coupled with environmental variation due to extension of the Changjiang River plume. Spatial patterns of nanoflagellate abundance were studied in June and August 2003, June 2006 and July 2007 over the ECS shelf. The Changjiang River plume was smaller during the August 2003 and July 2007 cruises than during the rest other 2 cruises. Total nanoflagellates densities varied between 1 and 120 × 10² cells ml⁻¹ with the highest abundances occurring within the Changjiang River plume during large plume periods. In the small plume periods, the range of nanoflagellates abundance was 3–33 × 10² cells ml⁻¹ and the highest abundances were observed during these periods either within the Changjiang River plume or the Yellow Sea Coastal Water (YSCW). During large plume periods, nanoflagellate abundance closely related to changes in salinity and during the small period, abundance was most related to water temperature. The pigmented nanoflagellate community (PNF) within Changjiang River plume, especially in the <3 μm size class, appears to increase in response to terrestrial or anthropogenic inorganic nutrient loading in the discharge of fresh water from the Changjiang River. The PNF abundance pronounced increase caused the variation of nanoflagellate community of ECS in summer. We suggest that the discharge of fresh water from Changjiang River has significant ecological impacts on spatial variations in nanoflagellate community in the ECS.     

Evaluating the contribution of multi-model combination to streamflow hindcasting by empirical and conceptual models

The contribution of multi-model combination to daily streamflow hindcasting was evaluated through the HBV (Hydrologiska Byråns Vattenbalansavdelning) and RNN (recurrent neural networks) models with 100 ensemble members generated with different initial conditions for both. In the calibration phase, the analysis showed that the HBV and RNN models with 20 members have better accuracy and require less calibration time. The combination of two models, however, did not provide significant improvements when 80 more members were added in the combination. In the validation phase, the results indicated that both HBV and RNN models with 20 members not only accurately produce reliable and stable streamflow hindcasting, but also effectively simulate the timing and the value of peak flows. From the consistency of calibration and validation results, the study provides an important contribution, namely, that ensemble size is not sensitive to the type of hydrological model in terms of streamflow hindcasting.