Effect of a drag-reducing polymer solution ejection on tip vortex cavitation

Experiments regarding the modification of the foil geometry and/or active or passive mass injection in the vortex core have been performed to investigate the possibility of inhibiting tip vortex cavitation. The ejection at very low flow rates of drag-reducing polymer solutions at the tip of hydrofoils and propeller blades has demonstrated effectiveness as a tip vortex cavitation inhibitor. This paper reports the results obtained with an elliptical hydrofoil, of 8cm maximum chord and 12cm haif-span, operating at Reynolds numbers, of =10⁶, much larger than those previously reported in the literature. Lift coefficients and critical cavitation numbers were determined for a variety of flow and polymer solution ejection conditions. Tangential and axial components of the mean velocity as well as velocity fluctuations along the vortex path were also measured. At 12.5 m/s free stream velocity and a variety of angles of attack, the ejection of a 500 ppm aqueous solution of a drag-reducing polymer at a flow rate of about 5 cm³/s leads to a decrease of up to 30% in the cavitation number. This occurs without modification of the lift coefficient and, hence, of the midspan bound circulation of the foil. Moreover, water injection does not cause any appreciable change in the cavitation numbers. The tangential velocity profiles along the vortex path during polymer ejection indicate that the potential region remains the same, while the viscous core dimension increases, and the maximum tangential velocity decreases substantially as compared to the no ejection or water ejection experiments. Thus, the pressure coefficients at the vortex axis are smaller than for the no ejection or water ejection cases and cause the reduction of the critical cavitation numbers. It is speculated that this inhibition effect is due only to swelling of the polymer solution when exiting the ejection orifice.List of symbols a core radius (distance to the vortex axis for maximum tangential velocity) - C ₁ lift coefficient - c _max maximum chord - Cp pressure coefficient at the vortex axis - Cp _min minimum pressure coefficient at the vortex axis - d _e diameter of the ejection port - m ejection flow rate - P reference pressure - P _v vapor pressure - V free stream velocity - V _a axial velocity - V _t tangential velocity - v _r radial component of the velocity resulting from jet swelling - x downstream distance from the tip of the foil - y, r distance to the vortex axis - angle of attack - r difference between the swollen jet and the ejection port radii - boundary layer thickness - tip vortex intensity - _d ( _de ) desinent cavitation number (with ejection) - _i ( _ie ) inception cavitation number (with ejection) - _ii normal stresses - viscosity - v kinematic viscosity - p specific mass     

Assimilation of altimetric data in the mid-latitude oceans using the Singular Evolutive Extended Kalman filter with an eddy-resolving, primitive equation model

A new data assimilation scheme has been elaborated for ocean circulation models based on the concept of an evolutive, reduced-order Kalman filter. The dimension of the assimilation problem is reduced by expressing the initial error covariance matrix as a truncated series of orthogonal perturbations. This error sub-space evolves during the assimilation so as to capture the growing modes of the estimation error. The algorithm has been formulated in quite a general fashion to make it tractable with a large variety of ocean models and measurement types. In the present paper, we have examined three possible strategies to compute the evolution of the error subspace in the so-called Singular Evolutive Extended Kalman (SEEK) filter: the steady filter considers a time-independent error sub-space, the apprentice filter progressively enriches the error sub-space with the information learned from the innovation vector after each analysis step, and the dynamical filter updates the error sub-space according to the model dynamics. The SEEK filter has been implemented to assimilate synthetic observations of the surface topography in a non-linear, primitive equation model that uses density as vertical coordinate. A simplified box configuration has been adopted to simulate a Gulf Stream-like current and its associated eddies and gyres with a resolution of 20 km in the horizontal, and 4 levels in the vertical. The concept of twin experiments is used to demonstrate that the conventional SEEK filter must be complemented by a learning mechanism in order to model the misrepresented tail of the error covariance matrix. An approach based on the vertical physics of the isopycnal model, is shown particularly robust to control the velocity field in deep layers with surface observations only. The cost of the method makes it a suitable candidate for large-size assimilation problems and operational applications.     

A Mathematical Model for Driver Steering Control, with Design, Tuning and Performance Results

A mathematical model for the steering control of an automobile is described. The structure of the model derives from linear optimal discrete time preview control theory but it is non-linear. Its parameter values are obtained by heuristic methods, using insight gained from the linear optimal control theory. The driver model is joined to a vehicle dynamics model and the path tracking performance is demonstrated, using moderate manoeuvring and racing speeds. The model is shown to be capable of excellent path following and to be robust against changes in the vehicle dynamics. Application to the simulation of manoeuvres specified by an ideal vehicle path and further development of the model to formalise the derivation of its parameter values and to put it to other uses are discussed.     

An Extended Adaptive Kalman Filter for Real-time State Estimation of Vehicle Handling Dynamics

This paper considers a method for estimating vehicle handling dynamic states in real-time, using a reduced sensor set; the information is essential for vehicle handling stability control and is also valuable in chassis design evaluation. An extended (nonlinear) Kalman filter is designed to estimate the rapidly varying handling state vector. This employs a low order (4 DOF) handling model which is augmented to include adaptive states (cornering stiffnesses) to compensate for tyre force nonlinearities. The adaptation is driven by steer-induced variations in the longitudinal vehicle acceleration. The observer is compared with an equivalent linear, model-invariant Kalman filter. Both filters are designed and tested against data from a high order source model which simulates six degrees of freedom for the vehicle body, and employs a combined-slip Pacejka tyre model. A performance comparison is presented, which shows promising results for the extended filter, given a sensor set comprising three accelerometers only. The study also presents an insight into the effect of correlated error sources in this application, and it concludes with a discussion of the new observer's practical viability.     

Energy Requirements of a Passive and an Electromechanical Active Suspension System

Passive suspensions are designed to dissipate the energy otherwise transferred to a vehicle's body through interactions with a roadway or terrain. A bond graph representation of an independent suspension design was developed to study the energy flow through a vehicle. The bond graph model was tuned and validated through experimental tests and was found to produce suitable results. Examining the bond graph reveals that the dissipated energy associated with vertical and transverse coordinates generally originates from the longitudinal motion of the vehicle and is transferred through the tire-ground contact patch. Additionally, since the longitudinal energy originates from the vehicle's engine, the energy dissipated via the suspension shock absorber as well as other components (e.g., mechanical joints, etc.) essentially dissipate some engine energy. The plots presented in the paper support this theory by showing that upon traveling a rough terrain, the vehicle's longitudinal velocity drops more when vertical vibrations increase. Results show that a vehicle equipped with a passive suspension experiences a larger velocity drop compared to one with an active suspension traversing the same rough terrain. The paper compares the results of simulation of an analytical bond graph model of an active suspension system with experimental results and finds good agreement between the two. Other simulations show that relative to passive suspensions, not only do active suspensions yield substantial improvement in ride quality, they can also result in substantial energy savings. This paper concludes that if electromechanical actuators are supplemented by passive springs to support the vehicle static weight, the amount of energy required for operation of actuators is significantly less than the amount dissipated by conventional shock absorbers.     

Optimization for Vehicle Suspension II: Frequency Domain

The objective of this study is optimizing the components design of a vehicle suspension system under excitation due to road roughness. The vehicle is modelled as a dynamic system made of masses interconnected by, linear, springs and dampers. The optimizing code provides values corresponding to the caracteristics of masses, dampers and springs which, within a range, minimize the objective function for a defined excitation. This objective function auantifies the vehicle comfort level.

The optimization method used is the sequential linear programming by iteratively applying the Simplex algorithm. The model response is obtained in frequency domain and the vehicle excitation can be either random or deterministic.

The exact nature of the optimization problem, objective function and restrictions, depend on the type of excitation considered.

In succeeding paragraphs, the problem formulation together with a comparison with other authors is presented.     

Impacts of Terrestrial and Shoreline Stressors on Eelgrass in Puget Sound: An Expert Elicitation

We used expert elicitation to examine potential responses of eelgrass to several restoration strategies in Puget Sound. Restoration strategies included shoreline armor removal and modification, removal and modification of overwater structures, and efforts to improve water clarity via reductions in anthropogenic nutrient and sediment loadings. Expert responses indicated a general belief that reducing stressors would increase eelgrass cover; however, responses varied greatly among stressors. Our analyses revealed that removal of overwater structures, nutrient loading and shoreline armoring will have significantly larger effects on eelgrass recovery than would removal of sediment loading, with removal of overwater structures having the largest effect. We then used a probabilistic model to estimate what actions, singularly or in combination, could yield a large increase in eelgrass cover. Reducing single stressors could, in theory, result in recovery of eelgrass in Puget Sound; however, the magnitude of actions required would be so great that it is likely not practical. In contrast, we identified combinations of smaller reductions of stressors that could achieve significant eelgrass recovery. For example, a 40% reduction in overwater structures, combined with 20% reductions in shoreline armor, and nutrient and sediment loadings, was predicted to be one of the more feasible combinations of actions for meeting the target. The importance of eelgrass to Puget requires prompt input of scientific advice, and this work fills an important knowledge gap in the face of rapidly approaching legislative deadlines. While coded expert opinion of the sort we use here is a weak substitute for data, our work clarifies the current extent of scientific uncertainty that can guide management action in the near term and scientific research in the long term.     

Integrated Environmental Modeling and Assessment of Coastal Ecosystems: Application for Aquaculture Management

This article presents an approach that couples coastal ecosystem modeling with integrated environmental assessment methodologies to support coastal management. The focus is to support the development of an ecosystem approach to aquaculture management including interactions with watershed substance loading. A Chinese bay, with intense aquaculture and multiple catchment uses, and where significant modeling efforts were undertaken is used as a case study. The ecosystem model developed for this bay is used to run scenarios that test the local management strategy for nutrient reduction. The corresponding ecological and economic impacts of the managers’ scenarios are analyzed by means of the Differential Drivers-Pressure-State-Impact-Response (ΔDPSIR) analysis. Emphasis is given to the analysis of the eutrophication process in the bay including present eutrophic condition and the expected changes due to the simulated scenarios. For this purpose, the Assessment of Estuarine Trophic Status (ASSETS) screening model is a valuable tool to interpret and classify the data and model outputs regarding eutrophication condition and to evaluate the manageable level of the nutrient loading entering in the bay.     

Air quality impact assessment of NOx and PM due to diesel vehicles in Delhi

The impact of diesel vehicles on NO_x and PM emissions at various locations in Delhi is assessed using two line source models; the California line source version 4 and the Indian Institute of Technology Line Source. The models offer comparable results but both under predicting the observed values with the Indian Institute of Technology model predictions being slightly better. The analysis also identifies hotspots due to concentrations of NO_x and PM and their diurnal variations is found to be greater in at night hours.