Quasi-two-dimensional flow on the polar β-plane: Laboratory experiments

Geophysical turbulence is strongly affected by the variation of the Coriolis parameter with latitude. This variation results in the so-called β-effect, which forces energy from small-scales to be transferred preferentially into zonal motions. This effect results in the formation of narrow jet-like zonal flows that dominate the dynamics and act as transport barriers. Here, laboratory experiments are used to reproduce this effect in decaying turbulent flows. An electromagnetic cell is used to generate an initial field of vorticity in a rotating tank. Under conditions of quasi-geostrophic flow, the β-effect is produced by depth variation of the flow instead of variation of the Coriolis parameter. The effects of changing the container geometry and the overall fluid depth on the production of jets are investigated. The results suggest that this laboratory configuration can be used to model jet formation in the oceans and that increasing fluid depth is a practical way to decrease viscous effects.     

单向复合材料高应变率下材料特性的研究

在船舶领域,复合材料及夹芯复合材料板梁结构已大量应用在舰船结构中,尤其游艇及复合材料高速艇上.在运行过程中,这些结构有时很可能会受到如砰击、碰撞等动态载荷或高速冲击载荷.然而到目前为止,大多数的结构设计所用到的材料特性仍基于低应变率情况下的准静态测试结果.该文研究了高速艇等结构中的纤维增强复合材料高应变率情况下的材料特性,通过引入一种粘弹性模型来模拟并分析研究对象.并在世界先进的INSTRON高应变率材料试验机上设计并完成了相关试验,验证了该枯弹性模型、确定了模型中的材料参数.该粘弹性模型然后被用来研究分析应变率对单向复合材料机械特性的影响.     

Nutrient cycling and primary production in the marine systems of the Arctic and Antarctic

Primary production events in both the Arctic and the Antarctic are highly localized. Carbon-14 incubations that did not account for this caused antarctic primary production estimates to be revised too far downwards from the historic view of high productivity. The primary production regime in the Arctic is even more heterogeneous than in the Antarctic. Arctic primary production rates are in the process of being revised upwards because of a better spatial and temporal distribution of incubation experiments and a re-awakening of interest in estimating new production from the distribution of chemical variables. Similarly, recent examination of temporal changes in nitrate concentrations and recognition of the importance of ice-edge blooms has caused antarctic primary productivity to be revised upwards. In both the Arctic and the Antarctic, the ratio of “new” to total primary production is high, and neglect of this fact can lead to an underestimation of the potential that these regions have for influencing global cycles of bioactive chemicals. Some recent data on temporal changes in nitrate from Fram Strait emphasize the poor state of our knowledge by suggesting an unexpectedly high “new” production rate of 1 g C m⁻² d⁻¹ for a 35 day experiment that encountered an early Phaeocystis bloom. Chemical distributions suggest that new production over the shelf seas that border the Polar Basin is about 50 g Cm⁻² yr⁻¹.The shelves in the Arctic Ocean's marginal and adjacent seas comprise 25% of the total global continental shelf. These extensive shallow regions have much higher rates of primary production than the Polar Basin and may be globally significant sites of denitrification. Globally significant silica deposition could occur on these shelves or on the adjacent slopes.Because of the differences in geomorphology and stratification, global warming is likely to increase primary production in the Arctic and will probably decrease antarctic primary production.In addition to sharing high ratios of “new” to total primary production, high ammonium concentrations occur in the Arctic and Antarctic. It is possible that these accumulations arise from a strong repression of nitrification at low temperatures.     

Application of a 3-D variational inverse model to the analysis of ecohydrodynamic data in the Northern Bering and Southern Chukchi Seas

In the scope of the Inner SHelf Transfer And Recycling Program, extensive oceanographic surveys were conducted in the Northern Bering and Southern Chukchi Seas. A vast amount of hydrographic, chemical and biological data were collected in order to increase the information available on the system and to test if biological observations are indeed compatible with the dominant hydrographic regimes. An original model, based on the variational inverse method, was developed with the aim of reconstructing realistic three-dimensional fields of the variables of interest and giving an interpretation of the observations consistent with the physics of the general circulation. The basic formulation of the model is quite general and provides a very helpful tool in the context of interdisciplinary studies. In a first stage, the vertical and horizontal structures of physical variables are reproduced and discussed. Secondly, a sketch is proposed to explain the driving mechanisms of the primary productivity in the Northern Bering Sea. In particular, one shows that the hydrodynamic regimes strongly condition the behaviour of the ecosystem and are mainly responsible for the very fertile environment that characterizes the Southern Chukchi Sea.     

Full vehicle simulation using thermomechanically coupled hybrid neural network shock absorber model

In the case of full vehicle models, the technique of multi-body simulation (MBS) is frequently used to study their highly non-linear dynamic behaviour. Many non-linearities in vehicle models are induced by force elements like springs, shock absorbers, bushings and tires. Commonly, spline functions are used to represent the force responses of these components. If the non-linear relationships are more complicated, the spline approximations are no more accurate. An alternative approach is based on empirical neural networks which are based on the mathematical approximation of measured data. It is well known that neural networks are able to represent and predict complex component responses accurately. The aim of this paper is to perform a dynamic full vehicle simulation using a thermomechanically coupled hybrid neural network shock absorber model. In this shock absorber model, the spline approach is combined with a temperature-dependent neural network. Based on a displacement-controlled excitation on a four post test rig in the ADAMS/Car MBS software, a rugged test track is simulated. In this way, the front and rear shock absorbers are dynamically loaded with comfort-relevant frequencies in the range of 0.75-30 Hz and velocity amplitudes up to 2 m/s. By the simulation, stability of the hybrid neural network model is demonstrated. Furthermore, the damping force, the vertical acceleration of the chassis and the required simulation times are compared. The standard spline approach is used as a reference.     

Empirical approaches to combining revealed and stated preference data: Some recent developments with reference to urban mode choice

This paper replaces the nested logit ‘trick’ used in estimation of a modal choice model, when stated preference (SP) and revealed preference (RP) data are pooled, with an error component mixed logit model that can (i) relax the IID condition attached to subsets of alternatives in nested logit models, (ii) accommodate correlated observations, and (iii) reveal the relevant scale parameter for subsets of alternatives. Such a model can also incorporate state dependence between data types and preference heterogeneity on observed attributes. An example of choice among bus, train and car modes illustrates the difference in empirical evidence, especially elasticity outputs.     

Use of a probabilistic particle tracking model to simulate the Prestige oil spill

A probabilistic particle tracking model is used to simulate the oil dispersion after the Prestige wreckage. This oil spill constitutes a suitable benchmark to analyze the capabilities of a probabilistic model, since the time elapsed from wreckage to oil landing (12 days) is much longer than the reliability time associated with forecast winds, usually on the order of 3–4 days. The particle model can be run in two different modes: real time mode (when existing reliable wind fields for the event under scope) and in probabilistic mode (in absence of reliable wind fields but with historical fields corresponding to a similar period). The validity of the particle model is first evaluated in a hindcast way, running the Prestige case with the wind fields corresponding to the period November 19 to November 30, 2002, which were not available at the moment of the wreckage. Calculations show the accuracy of the model to provide the right impact point and timing. The probabilistic model is then used to simulate the same event by means of historical data. The region where the oil landed is shown to be the area with the highest probability to be impacted.