Moving bottlenecks are moving capacity restrictions that affect traffic flows, and they can be used to describe the effects of buses and trucks in transportation networks. The computation of solutions associated with ...
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Moving bottlenecks are moving capacity restrictions that affect traffic flows, and they can be used to describe the effects of buses and trucks in transportation networks. The computation of solutions associated with the presence of moving bottlenecks is complex, since they both influence and are influenced by surrounding traffic. In this study, we propose a fast numerical scheme that can efficiently compute the solutions to an arbitrary number of moving (and fixed) bottlenecks, for a stretch of road modeled by the Lighthil-lWhitham-Richards (LWR) model. Several different moving bottlenecks can be simulated endogenously all together by means of an algorithm based on a semi-analytic Lax-Hopf formula. Since the numerical scheme is semi-analytic and requires a very low number of operations, it can be employed for traffic estimation problems where fast and accurate solutions are required. We demonstrate the capabilities of the method by implementing two alternative traffic management strategies designed to minimize the negative impacts of trucks and buses in urban environments. (C) 2017 Elsevier Ltd. All rights reserved.
For boundary element analysis of the orthotropic potential problems in thin structures, the higher order elements are expected to discretize the boundary. However, the use of the higher order elements leads to more co...
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For boundary element analysis of the orthotropic potential problems in thin structures, the higher order elements are expected to discretize the boundary. However, the use of the higher order elements leads to more complex forms of the integrands in boundary integral equations. The resulting nearly singular integrals on the higher order elements are difficult to be evaluated when the source point is very close to the integral element. In this paper, a semi-analytic algorithm is presented to evaluate the nearly singular integrals on the quadratic elements in two dimensional (2-D) orthotropic potential problems. By constructing the approximate singular integral kernels, the nearly singular integrals through subtraction technique are transformed into the sum of regular parts and singular parts. Then, the former are calculated by the conventional Gaussian quadrature and the latter are calculated by the analytical integral formulas. Numerical examples demonstrate that the present semi-analytic algorithm is efficient and accurate to calculate the nearly singular integrals on the quadratic elements. Especially, the BEM with the present semi-analytic algorithm is successfully applied to analyzing 2-D orthotropic potential problems in very thin structures.
While satellite remote sensing has become a very useful tool contributing to assessments of sea surface partial pressure of carbon dioxide (pCO(2)) that subsequently allow quantification of air-sea CO2 flux, the appli...
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While satellite remote sensing has become a very useful tool contributing to assessments of sea surface partial pressure of carbon dioxide (pCO(2)) that subsequently allow quantification of air-sea CO2 flux, the application of empirical approaches in coastal oceans has proven challenging owing to the interaction of multiple controlling factors. We propose a mechanistic semi-analytic algorithm (MeSAA) to estimate sea surface pCO(2) in river-dominated coastal oceans using satellite data. Observed pCO(2) can be analytically expressed as the sum of individual components controlled by major factors such as thermodynamics (or temperature), mixing, and biology. With marine carbonate system calculations, temperature and mixing effects can be predicted using thermodynamic principles and by assuming conservative two end-member mixing of total dissolved inorganic carbon and total alkalinity (e.g., the Changjiang River and Kuroshio water in the East China Sea, ECS). Next, an integral expression for pCO(2) drawdown due to biological effects can be parameterized using the chlorophyll a concentration (chla). We demonstrate the validity and applicability of the algorithm in the ECS during summertime. Sensitivity analysis shows that errors in empirical coefficients and three input satellite parameters (salinity, SST, chla) have limited influence on the algorithm, and satellite-derived pCO(2) is consistent with underway data, even though no in situ pCO(2) data from the ECS shelves was used to train the algorithm. Our algorithm has more physical and biogeochemical mechanistic meaning than empirical methods, and should be applicable to other similar systems.
With the rapid development of the economy in recent years, massive algal (blue-green algae in particular) blooms have often observed in Chinese eutrophic lakes. The concentration of the cyanobacterial pigment phycocya...
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With the rapid development of the economy in recent years, massive algal (blue-green algae in particular) blooms have often observed in Chinese eutrophic lakes. The concentration of the cyanobacterial pigment phycocyanin (PC), an accessory pigment unique to freshwater blue-green algae, is often used as a quantitative indicator of blue-green algae in eutrophic inland waters. The purpose of this study was to evaluate the semi-analytic PC retrieval algorithm proposed by Simis et al. and to explore the potential to improve this PC algorithm so that it is more suitable for eutrophic lakes, such as Taihu Lake: In this paper, we recalculated the correction coefficients gamma and delta to calculate the absorptions of chlorophyll-a at 665 nm and the absorptions of phycocyanin at 620 nm in terms of in situ measurements and observed that the values of these coefficients differed from the values used by Simis et al. and Randolph et al. The two coefficients are site dependent due to the different bio-optical properties of lakes. We also observed that the specific PC absorption at 620 nm a(pc)*(620) decreases exponentially with an increase in PC concentrations. Therefore, a non-linear power-function of a(pc)*(620), instead of a constant value of a(pc)*(620) as used by Simis et at, was proposed for our improved PC retrieval algorithm in Taihu Lake, yielding a squared correlation coefficient (R-2) of 0.55 and a root mean square error (RMSE) of 58.89 mu g/L. Compared with the original PC retrieval algorithm by Simis et al., the improved retrieval algorithm has generally superior performance. In evaluating the limitation of the PC retrieval algorithms, we observed that the ratio of the total suspended solids to phycocyanin can be used as a primary measure for retrieval performance. Validation in Dianchi Lake and an error analysis proved that the improved PC algorithm has a better universality and is more suitable for eutrophic lakes with higher PC concentrations. (C) 2013 Elsevier B.
Knowledge of the concentration of total suspended sediment (TSS) in coastal waters is of significance to marine environmental monitoring agencies to determine the turbidity of water that serve as a proxy to estimate t...
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Knowledge of the concentration of total suspended sediment (TSS) in coastal waters is of significance to marine environmental monitoring agencies to determine the turbidity of water that serve as a proxy to estimate the availability of light at depth for benthic habitats. TSS models applicable to data collected by satellite sensors can be used to determine TSS with reasonable accuracy and of adequate spatial and temporal resolution to be of use for coastal water quality monitoring. Thus, a study is presented here where we develop a semi-analytic sediment model (SASM) applicable to any sensor with red and near infrared (NIR) bands. The calibration and validation of the SASM using bootstrap and cross-validation methods showed that the SASM applied to Moderate Resolution Imaging Spectroradiometer (MODIS)-Aqua band 1 data retrieved TSS with a root mean square error (RMSE) and mean averaged relative error (MARE) of 5.75 mg/L and 33.33% respectively. The application of the SASM over our study region using MODIS-Aqua band 1 data showed that the SASM can be used to monitor the on-going, post and pre-dredging activities and identify daily TSS anomalies that are caused by natural and anthropogenic processes in coastal waters of northern Western Australia.
Remote sensing of suspended particulate matter, SPM, from space has long been used to assess its spatio-temporal variability in various coastal areas. The associated algorithms were generally site specific or develope...
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Remote sensing of suspended particulate matter, SPM, from space has long been used to assess its spatio-temporal variability in various coastal areas. The associated algorithms were generally site specific or developed over a relatively narrow range of concentration, which make them inappropriate for global applications (or at least over broad SPM range). In the frame of the GlobCoast project, a large in situ data set of SPM and remote sensing reflectance, R-rs(lambda), has been built gathering together measurements from various coastal areas around Europe, French Guiana, North Canada, Vietnam, and China. This data set covers various contrasting coastal environments diversely affected by different biogeochemical and physical processes such as sediment resuspension, phytoplankton bloom events, and rivers discharges (Amazon, Mekong, Yellow river, MacKenzie, etc.). The SPM concentration spans about four orders of magnitude, from 0.15 to 2626 g center dot m(-3). Different empirical and semi-analytical approaches developed to assess SPM from R-rs(lambda) were tested over this in situ data set. As none of them provides satisfactory results over the whole SPM range, a generic semi-analytical approach has been developed. This algorithm is based on two standard semi-analytical equations calibrated for low-to-medium and highly turbid waters, respectively. A mixing law has also been developed for intermediate environments. Sources of uncertainties in SPM retrieval such as the bio-optical variability, atmospheric correction errors, and spectral bandwidth have been evaluated. The coefficients involved in these different algorithms have been calculated for ocean color (SeaWiFS, MODIS-A/T, MERIS/OLCI, VIIRS) and high spatial resolution (LandSat8-OLI, and Sentinel2-MSI) sensors. The performance of the proposed algorithm varies only slightly from one sensor to another demonstrating the great potential applicability of the proposed approach over global and contrasting coastal waters.
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