Microbial Biomass and Organic Nutrients in the Deep-Sea Sediments of the Central Indian Ocean Basin

In order to assess the impact of deep-sea mining on the in situ benthic life, we measured the microbial standing stock and concentration of organic nutrients in the deep-sea sediments of the Central Indian Ocean Basin in the Indian pioneer area. Sediments were collected using box core and grab samples during September 1996. The total bacterial numbers ranged from 10 10 -10 11 cells per g -1 dry weight sediment. There was a marginal decrease in the number of bacteria from surface to 30 cm depth, though the subsurface section registered a higher number than did the surface. The highest numbers were encountered at depths of 4-8 cm. The retrievable number of bacteria were two orders less in comparison with the direct total counts of bacteria. An almost homogeneous distribution of bacteria, total organic carbon, living biomass, and lipids throughout the depth of cores indicates active microbial and benthic processes in the deep sea sediments. On the other hand, a uniform distribution of total counts of bacteria, carbohydrates, and total organic carbon in all the cores indicates their stable nature and suggests that they can serve as useful parameters for long-term monitoring of the area after the benthic disturbance. Further studies on temporal variability in this region would not only verify the observed norms of distribution of these variables but would also help to understand restabilization processes after the simulated benthic disturbance.     

海上大直径钢管桩打桩过程中桩周土强度弱化研究

海上大直径钢管桩打桩过程中,桩周土体受到强烈扰动而发生强度弱化,掌握桩周土体强度弱化规律对于准确预测打桩过程、保证工程安全具有重要意义。为研究土体强度弱化规律,开展了环剪试验模拟打桩对桩周土体的扰动,测试土体强度随剪切速率的变化规律,建立了描述土体强度弱化规律的拟合公式,引入到打桩分析软件中。研究结果表明：土体的强度折减程度不仅与土体本身的性质有关还受到土体的埋深和剪切速率的影响,埋深越深土体强度折减程度越低,剪切速率越高土体强度折减越高,在打桩分析中可采用这里推荐的线性折减方法来模拟不同深度处土体强度的折减规律。     

Geoacoustic Inversion via Genetic Algorithm and Its Application to Manganese Sediment Identification

An acoustic inversion method using a wide-band signal and two near field receivers is proposed and applied to multiple layered seabed models including a manganese sediment. The inversion problem can be formulated into a probabilistic model comprised of signals, a forward model, and additive noise. The forward model simulates wide-band signals, such as chirp signals, and is chosen to be the source-waveletconvolution plane wave modeling method. The wavelet matching technique, using weighted least-squares fitting, estimates the sediment sound-speed and thickness on which determination of the possible numerical ranges for a priori uniform distribution is based. The genetic algorithm is applied to a global optimization problem to find a maximum a posteriori solution for determined a priori search space. Here the object function is defined by an L 2 norm of the difference between measured and modeled signals. Not only the marginal pdf but also its statistics are calculated by numerical evaluation of integrals using the samples selected during importance sampling process of the genetic algorithm.