Optimization and integration of ground vehicle systems

This article deals with the optimal design of ground vehicles and their subsystems, with particular reference to 'active' safety and comfort. A review of state-of-the-art optimization methods for solving vehicle system design problems, including the integration of electronic controls, is given, thus further encouraging the use of such methods as standard tools for automotive engineers. Particular attention is devoted to the class of methods pertaining to complex system design optimization, as well as approaches for the optimal design of complex systems under uncertainty. Some examples of design optimizations are given in the fields of vehicle system dynamics, powertrain/internal combustion engine design, active safety and ride comfort, vehicle system design and lightweight structures, advanced automotive electronics, and smart vehicles.     

Sliding mode observers for vehicle mode detection

This paper explores the use of sliding mode observers to detect the onset of potentially dangerous vehicle modes such as oversteer, understeer or split-μ braking. Provided these modes can be detected quickly enough, existing stability controllers can be engaged to ensure safe performance of the vehicle. It is shown that the equivalent output error injection signals associated with the sliding mode observer have distinctive signatures depending on the particular mode encountered. Appropriate thresholds on these signals can be set so the scheme ignores variations which arise during normal driving, but can detect and isolate different undesirable vehicle modes within 0.3 seconds of their onset.     

Lateral Dynamics of an Offroad Motorcycle by System Identification

An instrumented offroad motorcycle was run at a range of speeds in approximately straight lines whilst the rider excited its lateral dynamics by shaking the steering. Autoregressive models were fitted to the resulting multiple output time series data using system identification. The method allowed statistical estimation of state space models to represent the dynamics of an unstable or marginally stable vehicle under manual control. A symbolic algebra computer package was used to derive an analytical state space model to describe the lateral dynamics of the motorcycle. Results from the experiments and analysis compared well with respect to frequency, damping and modal shape of weave and wobble modes, frequency response and model order.     

Seasonal productivity dynamics in the pelagic central Benguela System inferred from the flux of carbonate and silicate organisms

Flux of bulk components, carbonate- and silicate-bearing skeleton organisms, and the δ¹⁵N-isotopic signal were investigated on a 1-year time-series sediment trap deployed at the pelagic NU mooring site (Namibia Upwelling, ca. 29°S, 13°E) in the central Benguela System. The flux of bulk components mostly shows bimodal seasonality with major peaks in austral summer and winter, and moderate to low export in austral fall and spring. The calcium carbonate fraction dominates the export of particulates throughout the year, followed by lithogenic and biogenic opal. Planktonic foraminifera and coccolithophorids are major components of the carbonate fraction, while diatoms clearly dominate the biogenic opal fraction. Bulk δ¹⁵N isotopic composition of particulate matter is positively correlated with the total mass flux during summer and fall, while negatively correlated during winter and spring. Seasonal changes in the intensity of the main oceanographic processes affecting the NU site are inferred from variations in bulk component flux, and in the flux and diversity patterns of individual species or group of species. Influence from the Namaqua (Hondeklip) upwelling cell through offshore migration of chlorophyll filaments is stronger in summer, while the winter flux maximum seems to reflect mainly in situ production, with less influence from the coastal and shelf upwelling areas. On a yearly basis, dominant microorganisms correspond well with the flora and fauna of tropical/subtropical waters, with minor contribution of near-shore organisms. The simultaneous occurrence of species with different ecological affinities mirrors the fact that the mooring site was located in a transitional region with large hydrographic variability over short-time intervals.     

Variability of snow and ice thermal, physical and optical properties pertinent to sea ice algae biomass during spring

Changes in the thermal, physical and optical properties of the snow–sea ice system and feedbacks between various temporal and spatial scales affect accumulation of microalgae at the sea ice bottom and are the focus of this research. During the spring transition period, May 4 to June 9, 2002, we closely monitored atmospheric conditions and properties of the snow–sea ice system, including thermal, physical and optical properties of the snow cover (e.g., temperature, grain size, light attenuation), ice thickness and salinity, and biomass of bottom ice algae. Results show that snowdrift size averaged 31.2 by 10.6 m with a depth range of 2 to 45 cm. Snowpacks also varied in age, distinguished by coincident peaks of snow salinity and grain size and a lower PAR extinction coefficient. Spatial variability of the snowpack was superimposed by temporal variability associated with seasonal snow–ice melt and wind redistribution of snow. Maximum biomass of ice algae was observed under intermediate snow covers. Under thin snow covers, algae biomass declined steadily coincident with seasonal warming and desalination of the ice cover. Under thick snow covers, algae biomass was negatively correlated with snow depth. These results suggest that thin snow covers were associated with a thermal effect causing sloughing of algae, whereas under deep snow, algae were still light limited and thermally insulated from the warming atmosphere. Our results highlight the importance of snow cover history on the sea ice system operating below. Furthermore, in the context of current climate change scenarios, shifts in snow depth would result in decreases of ice algae biomass.     

多形体筛查

开发一种药物并将其推入市场并不是一件容易的事情，尤其是我们当前所处的环境是在西方的生产标准之下。法律环境和公众意念都对制造业有了很强烈的要求。很少有其它的行业，在被要求快速无误工作的同时，还要面对如此详细的审查和规章制度。那些因操作程序或设计不精确导致后期药物研发终止或临床试验冗余的公司，面临着艰巨的增加上市产品、树立和维持投资者信心的挑战。     

Numerical Model of a Tilting Body Railway Vehicle Compared With Rig and on Track Tests

The aim of the paper is to describe and verify a numerical model for the simulation of the dynamic behaviour of a tilting body railway vehicle, with particular attention to the curve negotiation conditions. In the model the dynamics of the tilting active control devices are reproduced, combining the numerical mechanical model of the vehicle with the control software used on the real vehicle. In order to validate the numerical simulation model, numerical results and experimental ones, from both a test rig and out-door tests, were compared.     

Wind-triggered events of phytoplankton downward flux in the Northeast Water Polynya

Phytoplankton carbon fluxes were studied in the Northeast Water (NEW) Polynya, off the eastern coast of Greenland (79° to 81°N, 6° to 17°W), during summer 1993. The downward flux of organic particles was determined during 54 days using a sediment trap moored at a fixed location, below the pycnocline (130 m). The hypothesis of the present study is that wind events were ultimately responsible for the events of diatoms downward flux recorded in the trap.Wind conditions can influence the vertical transport of phytoplankton by affecting (1) the environmental conditions (e.g. hydrostatic pressure, nutrient concentrations, and irradiance) encountered by phytoplankton during their vertical excursion, and (2) the aggregation and disaggregation of phytoplankton flocs. The first mechanism affects the physiological regulation of buoyancy, whereas the second one affects the size and shape of settling particles.Using field data (wind velocity, density profiles and phytoplankton abundance), we assessed the potential aggregation and the vertical excursion of phytoplankton in surface waters. The results show that, upstream from the trap, wind and hydrodynamic conditions were sometimes favourable to the downward export of phytoplankton. Lag-correlation between time series of wind and phytoplankton downward flux shows that flux events lagged wind events by ca. 16 days. Given that the average current velocity in the top 100 m was ca. 10 cm s⁻¹, a lag of 16 days corresponded to a lateral transport of ca. 130 km, upstream from the sediment trap, where phytoplankton production was lower than at the location of the trap. According to that scenario, 21% to 60% of primary production was exported to depth during wind events. If we had assumed instead a tight spatial coupling between the material collected in the trap and the relatively high phytoplankton production at the location of the trap, we would have concluded that <7% of primary production was exported to depth. The difference between the two scenarios has great implications for the fate of phytoplankton. Our results stress the importance of investigating the spatial coupling between surface and trap data before assessing the pathways of phytoplankton carbon cycling.     

Construction of a stochastic model of track geometry irregularities and validation through experimental measurements of dynamic loading

This paper describes the construction of a stochastic model of urban railway track geometry irregularities, based on experimental data. The considered irregularities are track gauge, superelevation, horizontal and vertical curvatures. They are modelled as random fields whose statistical properties are extracted from a large set of on-track measurements of the geometry of an urban railway network. About 300–1000 terms are used in the Karhunen–Loève/Polynomial Chaos expansions to represent the random fields with appropriate accuracy. The construction of the random fields is then validated by comparing on-track measurements of the contact forces and numerical dynamics simulations for different operational conditions (train velocity and car load) and horizontal layouts (alignment, curve). The dynamics simulations are performed both with and without randomly generated geometrical irregularities for the track. The power spectrum densities obtained from the dynamics simulations with the model of geometrical irregularities compare extremely well with those obtained from the experimental contact forces. Without irregularities, the spectrum is 10–50?dB too low.     

Analysis and optimisation of objective vehicle dynamics testing in winter conditions

Objective testing of vehicle handling in winter conditions has not been implemented yet because of its low repeatability and its low signal-to-noise ratio. Enabling this testing, by identifying robust manoeuvres and metrics, was the aim of this study. This has been achieved by using both experimental data, gathered with steering-robot tests on ice, and simulation models of different complexities. Simple bicycle models with brush and MF-tyre models were built, both optimally parameterised against the experimental data. The brush model presented a better balance in complexity performance. This model was also implemented in a Kalman filter to reduce measurement noise; however, a simpler low-pass filter showed almost similar results at lower cost. A more advanced full vehicle model was built in VI-CarRealTime, based on kinematics and compliance data, damper measurements, and real tyre measurements in winter conditions. This model offered better results and was therefore chosen to optimise the initial manoeuvres through test design and simulations. A sensitivity analysis (ANOVA) of the experimental data allowed one to classify the robustness of the metrics. Finally, to validate the results, the proposed and the initial manoeuvres were tested back to back in a new winter campaign.