Analyses of Non-Uniform Rational B-spline (NURB) curve by varying weights at its nodal points and projection ratio produce several kinetically plausible symmetric and asymmetric fold morphologies in 2D promptly and efficiently with varied overall geometries, curvature of limbs, sharpness/bluntness of hinges, extent of hinge zone, tightness/interlimb angles, etc. Some of these folds are new geometries what other approaches, such as those with Bézier curve, did not produce so far. Natural fold profiles can be matched with NURB curves from photographs. 相似文献
Surat city of India, situated 100 km downstream of Ukai Dam and 19.4 km upstream from the mouth of River Tapi, has experienced the largest flood in 2006. The peak discharge of about 25,770 m3 s?1 released from the Ukai Dam was responsible for a disaster. To assess the flood and find inundation in low-lying areas, simulation work is carried out under the 1D/2D couple hydrodynamic modeling. Two hundred ninety-nine cross sections, two hydraulic structures and five major bridges across the river are considered for 1D modeling, whereas a topographic map at 0.5 m contour interval was used to produce a 5 m grid, and SRTM (30 and 90 m) grid has been considered for Surat and the Lower Tapi Basin. The tidal level at the river mouth and the release from the Ukai Dam during 2006 flood are considered as the downstream and upstream boundaries, respectively. The model is simulated under the unsteady flow condition and validated for the year 2006. The simulated result shows that 9th August was the worst day in terms of flooding for Surat city and a maximum 75–77% area was under inundation. Out of seven zones, the west zone had the deepest flood and inundated under 4–5 m. Furthermore, inundation is simulated under the bank protection work (i.e., levees, retaining wall) constructed after the 2006 flood. The simulated results show that the major zones are safe against the inundation under 14,430 m3 s?1 water releases from Ukai Dam except for the west zone. The study shows the 2D capability of new HEC-RAS 5 for flood inundation mapping and management studies. 相似文献
We have studied the synthesis of26Al during combined hydrogen and helium-burning processes in high temperature and density conditions. The possible sites for these processes are believed to be the neutron star surfaces where the density ranges from =104–107 g cm–3 and temperature range from 108–8×108 K. The screening effect which leads to an enhancement of nuclear reaction rates is taken into account whenever necessary. A detailed calculation of the abundances of26Al and27Al isotopes is presented here. Finite amounts of26Al is found to be produced atT=2×108 K and =108 g cm–3 due to these combined reactions. This situation is likely to be realized during the -ray burst events on neutron star surface. The amount of material processed in the burst sources is very little compared to the amount of material processed in Novae or Supernovae. Thus it is suggested that rather than contributing to the overall amount of26Al, -ray bursts are likely to contribute more significantly to the inhomogeneity of26Al distribution in interstellar medium. 相似文献
The expected growth in the demand for passenger and freight services exacerbates the challenges of reducing transport GHG emissions, especially as commercial low-carbon alternatives to petroleum fuels are limited for shipping, air and long-distance road travel. Biofuels can offer a pathway to significantly reduce emissions from these sectors, as they can easily substitute for conventional liquid fuels in internal combustion engines. In this paper, we assess the potential of bioenergy to reduce transport GHG emissions through an analysis leveraging various integrated assessment models and scenarios, as part of the 33rd Energy Modeling Forum study (EMF-33). We find that bioenergy can contribute a significant, albeit not dominant, proportion of energy supply to the future transport sector: in scenarios aiming to keep the temperature increase below 2 °C by the end of the twenty-first century, models project that in 2100 bioenergy can provide on average 42 EJ/yr (ranging from 5 to 85 EJ/yr) for transport (compared to 3.7 EJ in 2018), mainly through lignocellulosic fuels. This makes up 9–62% of final transport energy use. Only a small amount of bioenergy is projected to be used in transport through electricity and hydrogen pathways, with a larger role for biofuels in road passenger transport than in freight. The association of carbon capture and storage (CCS) with bioenergy technologies (BECCS) is a key determinant in the role of biofuels in transport, because of the competition for biomass feedstock to provide other final energy carriers along with carbon removal. Among models that consider CCS in the biofuel conversion process the average market share of biofuels is 21% in 2100 (ranging from 2 to 44%), compared to 10% (0–30%) for models that do not. Cumulative direct emissions from the transport sector account for half of the emission budget (from 306 to 776 out of 1,000 GtCO2). However, the carbon intensity of transport decreases as much as other energy sectors in 2100 when accounting for process emissions, including carbon removal from BECCS. Lignocellulosic fuels become more attractive for transport decarbonization if BECCS is not feasible for any energy sectors. Since global transport service demand increases and biomass supply is limited, its allocation to and within the transport sector is uncertain and sensitive to assumptions about political as well as technological and socioeconomic factors.
An attempt is made in this study to develop a model to forecast the cyclonic depressions leading to cyclonic storms over North Indian Ocean (NIO) with 3 days lead time. A multilayer perceptron (MLP) model is developed for the purpose and the forecast quality of the model is compared with other neural network and multiple linear regression models to assess the forecast skill and performances of the MLP model. The input matrix of the model is prepared with the data of cloud coverage, cloud top temperature, cloud top pressure, cloud optical depth, cloud water path collected from remotely sensed moderate resolution imaging spectro-radiometer (MODIS), and sea surface temperature. The input data are collected 3 days before the cyclogenesis over NIO. The target output is the central pressure, pressure drop, wind speed, and sea surface temperature associated with cyclogenesis over NIO. The models are trained with the data and records from 1998 to 2008. The result of the study reveals that the forecast error with MLP model varies between 0 and 7.2 % for target outputs. The errors with MLP are less than radial basis function network, generalized regression neural network, linear neural network where the errors vary between 0 and 8.4 %, 0.3 and 24.8 %, and 0.3 and 32.4 %, respectively. The forecast with conventional statistical multiple linear regression model, on the other hand, generates error values between 15.9 and 32.4 %. The performances of the models are validated for the cyclonic storms of 2009, 2010, and 2011. The forecast errors with MLP model during validation are also observed to be minimum. 相似文献
The current generations of climate models are in substantial disagreement as to the projected patterns of sea surface temperatures (SSTs) in the Tropics over the next several decades. We show that the spatial patterns of tropical ocean temperature trends have a strong influence on global mean temperature and precipitation and on global mean radiative forcing. We identify the SST patterns with the greatest influence on the global mean climate and find very different, and often opposing, sensitivities to SST changes in the tropical Indian and West Pacific Oceans. Our work stresses the need to reduce climate model biases in these sensitive regions, as they not only affect the regional climates of the nearby densely populated continents, but also have a disproportionately large effect on the global climate.
Joseph J. BarsugliEmail: Phone: +1-303-4976042Fax: +1-303-4976449
The characteristic features of Indian summer monsoon (ISM) and monsoon intraseasonal oscillations (MISO) are analyzed in the 25 year simulation by the superparameterized Community Climate System Model (SP-CCSM). The observations indicate the low frequency oscillation with a period of 30–60 day to have the highest power with a dominant northward propagation, while the faster mode of MISO with a period of 10–20 day shows a stationary pattern with no northward propagation. SP-CCSM simulates two dominant quasi-periodic oscillations with periods 15–30 day and 40–70 day indicating a systematic low frequency bias in simulating the observed modes. Further, contrary to the observation, the SP-CCSM 15–30 day mode has a significant northward propagation; while the 40–70 day mode does not show prominent northward propagation. The inability of the SP-CCSM to reproduce the observed modes correctly is shown to be linked with inability of the cloud resolving model (CRM) to reproduce the characteristic heating associated with the barotropic and baroclinic vertical structures of the high-frequency and the low-frequency modes. It appears that the superparameterization in the General Circulation Model (GCM) certainly improves seasonal mean model bias significantly. There is a need to improve the CRM through which the barotropic and baroclinic modes are simulated with proper space and time distribution. 相似文献
