The aerodynamic effects of wing rotation and a revised quasi-steady model of flapping flight

We used a dynamically scaled model insect to measure the rotational forces produced by a flapping insect wing. A steadily translating wing was rotated at a range of constant angular velocities, and the resulting aerodynamic forces were measured using a sensor attached to the base of the wing. These instantaneous forces were compared with quasi-steady estimates based on translational force coefficients. Because translational and rotational velocities were constant, the wing inertia was negligible, and any difference between measured forces and estimates based on translational force coefficients could be attributed to the aerodynamic effects of wing rotation. By factoring out the geometry and kinematics of the wings from the rotational forces, we determined rotational force coefficients for a range of angular velocities and different axes of rotation. The measured coefficients were compared with a mathematical model developed for two-dimensional motions in inviscid fluids, which we adapted to the three-dimensional case using blade element theory. As predicted by theory, the rotational coefficient varied linearly with the position of the rotational axis for all angular velocities measured. The coefficient also, however, varied with angular velocity, in contrast to theoretical predictions. Using the measured rotational coefficients, we modified a standard quasi-steady model of insect flight to include rotational forces, translational forces and the added mass inertia. The revised model predicts the time course of force generation for several different patterns of flapping kinematics more accurately than a model based solely on translational force coefficients. By subtracting the improved quasi-steady estimates from the measured forces, we isolated the aerodynamic forces due to wake capture

Optimal Flood Control

A mathematical model for optimal control of the water levels in a chain of reservoirs is studied. Some remarks regarding sensitivity with respect to the time horizon, terminal cost and forecast of inflow are made

The aerodynamic effects of wing–wing interaction in flapping insect wings

We employed a dynamically scaled mechanical model of the small fruit fly Drosophila melanogaster (Reynolds number 100–200) to investigate force enhancement due to contralateral wing interactions during stroke reversal (the 'clap-and-fling'). The results suggest that lift enhancement during clap-and-fling requires an angular separation between the two wings of no more than 10–12°. Within the limitations of the robotic apparatus, the clap-and-fling augmented total lift production by up to 17%, but depended strongly on stroke kinematics. The time course of the interaction between the wings was quite complex. For example, wing interaction attenuated total force during the initial part of the wing clap, but slightly enhanced force at the end of the clap phase. We measured two temporally transient peaks of both lift and drag enhancement during the fling phase: a prominent peak during the initial phase of the fling motion, which accounts for most of the benefit in lift production, and a smaller peak of force enhancement at the end fling when the wings started to move apart. A detailed digital particle image velocimetry (DPIV) analysis during clap-and-fling showed that the most obvious effect of the bilateral 'image' wing on flow occurs during the early phase of the fling, due to a strong fluid influx between the wings as they separate. The DPIV analysis revealed, moreover, that circulation induced by a leading edge vortex (LEV) during the early fling phase was smaller than predicted by inviscid two-dimensional analytical models, whereas circulation of LEV nearly matched the predictions of Weis-Fogh's inviscid model at late fling phase. In addition, the presence of the image wing presumably causes subtle modifications in both the wake capture and viscous forces. Collectively, these effects explain some of the changes in total force and lift production during the fling. Quite surprisingly, the effect of clap-and-fling is not restricted to the dorsal part of the stroke cycle but extends to the beginning of upstroke, suggesting that the presence of the image wing distorts the gross wake structure throughout the stroke cycle

EVOLUTION OF IR-SELECTED GALAXIES IN Z~0.4 CLUSTERS

Wide-field optical and near--IR ($JHK$) imaging is presented for two rich galaxy clusters: Abell~370 at $z=0.374$ and Abell~851 (Cl0939+47) at $z=0.407$. Galaxy catalogs selected from the near--IR images are 90\% complete to approximately 1.5 mag below $K^\ast$ resulting in samples with $\sim$100 probable member galaxies per cluster in the central $\sim$2 Mpc. Comparison with $HST$ WFPC images yields subsamples of $\sim$70 galaxies in each cluster with morphological types. Analysis of the complete samples and the $HST$ subsamples shows that the $z\sim 0.4$ E/S0s are bluer than those in the Bower et al.\ (1992) Coma sample in the optical$-K$ color by $0.13$~mag for Abell~370 and by $0.18$~mag for Abell~851. If real, the bluing of the E/S0 populations at moderate redshift is consistent with that calculated from the Bruzual and Charlot (1993) models of passive elliptical galaxy evolution. In both clusters the intrinsic scatter of the known E/S0s about their optical$-K$ color--mag relation is small ($\sim 0.06$ mag) and not significantly different from that of Coma E/S0s as given by Bower et al.\ (1992), indicating that the galaxies within each cluster formed at the same time at an early epoch.Comment: uuencoded gzipped tar file containing latex files of manuscript (42 pages) plus tables (9 pages); figures available by anonymous ftp at ftp://ipac.caltech.edu//pub/pickup/sed ; accepted for publication in the Ap

Sources of Unreliable Testimony from Children

We distilled research findings on sources of unreliable testimony from children into four principles that capture how the field of forensic developmental psychology conceptualizes this topic. The studies selected to illustrate these principles address three major questions: (a) how do young children perform in eyewitness studies, (b) why are some children less accurate than others, and (c) what phenomena generate unreliable testimony? Throughout our research, our focus is on factors other than lying that produce inaccurate or seemingly inconsistent autobiographical reports.Collectively, this research has shown that (a) children’s eyewitness accuracy is highly dependent on context, (b) neurological immaturity makes children vulnerable to errors under some circumstances, and (c) some children are more swayed by external influences than others. Finally, the diversity of factors that can influence the reliability of children’s testimony dictates that (d) analyzing children’s testimony as if they were adults (i.e., with adult abilities, sensibilities, and motivations) will lead to frequent misunderstandings. It takes considerable knowledge of development—including information about developmental psycholinguistics, memory development, and the gradual emergence of cognitive control—to work with child witnesses and to analyze cases as there are many sources of unreliable testimony

Human behavioural analysis with self-organizing map for ambient assisted living

This paper presents a system for automatically classifying the resting location of a moving object in an indoor environment. The system uses an unsupervised neural network (Self Organising Feature Map) fully implemented on a low-cost, low-power automated home-based surveillance system, capable of monitoring activity level of elders living alone independently. The proposed system runs on an embedded platform with a specialised ceiling-mounted video sensor for intelligent activity monitoring. The system has the ability to learn resting locations, to measure overall activity levels and to detect specific events such as potential falls. First order motion information, including first order moving average smoothing, is generated from the 2D image coordinates (trajectories). A novel edge-based object detection algorithm capable of running at a reasonable speed on the embedded platform has been developed. The classification is dynamic and achieved in real-time. The dynamic classifier is achieved using a SOFM and a probabilistic model. Experimental results show less than 20% classification error, showing the robustness of our approach over others in literature with minimal power consumption. The head location of the subject is also estimated by a novel approach capable of running on any resource limited platform with power constraints

A computer vision approach to classification of birds in flight from video sequences

Bird populations are an important bio-indicator; so collecting reliable data is useful for ecologists helping conserve and manage fragile ecosystems. However, existing manual monitoring methods are labour-intensive, time-consuming, and error-prone. The aim of our work is to develop a reliable system, capable of automatically classifying individual bird species in flight from videos. This is challenging, but appropriate for use in the field, since there is often a requirement to identify in flight, rather than when stationary. We present our work in progress, which uses combined appearance and motion features to classify and present experimental results across seven species using Normal Bayes classifier with majority voting and achieving a classification rate of 86%