Добірка наукової літератури з теми "Oncoming wave algorithm"

A potential-flow numerical model is described for time-simulation of motions of two-dimensional floating bodies subjected to an oncoming wave train. The model is fully nonlinear in that no assumptions of smallness either in wave steepness or in body motions are made. The basic algorithm is based on a boundary integral formulation and time-stepping of the nonlinear free-surface constraints in an Eulerian frame of reference. Simple techniques are devised to overcome numerical instability problems that are encountered in the proposed method. The simulation time can be extended over several periods of steady-state oscillations depending on the size of the computational domain. Several illustrative results simulating large heave and roll motions as well as drifting of a rectangular body are presented and discussed. The numerical predictions are also evaluated against model tests which include several nonnegligible nonlinear phenomena, and the agreement is encouraging.

Fish in schooling formations navigate complex flow fields replete with mechanical energy in the vortex wakes of their companions. Their schooling behavior has been associated with evolutionary advantages including energy savings, yet the underlying physical mechanisms remain unknown. We show that fish can improve their sustained propulsive efficiency by placing themselves in appropriate locations in the wake of other swimmers and intercepting judiciously their shed vortices. This swimming strategy leads to collective energy savings and is revealed through a combination of high-fidelity flow simulations with a deep reinforcement learning (RL) algorithm. The RL algorithm relies on a policy defined by deep, recurrent neural nets, with long–short-term memory cells, that are essential for capturing the unsteadiness of the two-way interactions between the fish and the vortical flow field. Surprisingly, we find that swimming in-line with a leader is not associated with energetic benefits for the follower. Instead, “smart swimmer(s)” place themselves at off-center positions, with respect to the axis of the leader(s) and deform their body to synchronize with the momentum of the oncoming vortices, thus enhancing their swimming efficiency at no cost to the leader(s). The results confirm that fish may harvest energy deposited in vortices and support the conjecture that swimming in formation is energetically advantageous. Moreover, this study demonstrates that deep RL can produce navigation algorithms for complex unsteady and vortical flow fields, with promising implications for energy savings in autonomous robotic swarms.

More than 65 million people live with epilepsy. The unpredictable nature of epileptic seizures drastically increases the risk of injury, especially in daily activities such as walking or driving. The purpose of this project is to develop an accurate prediction device that utilizes raw EEG data for the prediction of epileptic seizures to alert patients of an oncoming seizure beforehand to escape dangerous situations. Using the raw EEG data, features were extracted by computing the average power spectral density of different brain waves after applying the Fast Fourier Transform. These features were used as the input dataset to the machine learning algorithms. Each model is tested with new unseen data using various metrics such as accuracy, precision, recall, and F1 score. The highest performing algorithm, Random Forest (RF) produced a prediction accuracy of 99.0% and a precision of 99.3%. Channel importance is calculated for the RF algorithm. This analysis helped to reduce the number of channels from 22 before feature importance to only 7 channels without significant hits to performance metrics. Using the RF algorithm, an embedded program is developed to run on a portable, low-power hardware device to predict the onset of a seizure. The hardware includes BeagleBone Black microcontroller running open-source software and a Bluetooth transmitter-receiver to transmit the prediction to smartphone devices. By reducing the number of EEG channels to 7 channels, the system is more convenient for a future wearable device. Hardware with the ability to predict epileptic seizures can save many patients from potentially dangerous situations such as driving or swimming. It can help many patients in their daily lives by removing the uncertainty and improving their quality of life.

An extended pattern search approach is presented for the optimization of the placement of wind turbines on a wind farm. Problem-specific extensions infuse stochastic characteristics into the deterministic pattern search, inhibiting convergence on local optima and yielding better results than pattern search alone. The optimal layout for a wind farm is considered here to be one that maximizes the power generation of the farm while minimizing the farm cost. To estimate the power output, an established wake model is used to account for the aerodynamic effects of turbine blades on downstream wind speed, as the oncoming wind speed for any turbine is proportional to the amount of power the turbine can produce. As turbines on a wind farm are in close proximity, the interaction of turbulent wakes developed by the turbines can have a significant effect on the power development capability of the farm. The farm cost is estimated using an accepted simplified model that is a function of the number of turbines. The algorithm develops a two-dimensional layout for a given number of turbines, performing local turbine movement while applying global evaluation. Three test cases are presented: (a) constant, unidirectional wind, (b) constant, multidirectional wind, and (c) varying, multidirectional wind. The purpose of this work is to explore the ability of an extended pattern search (EPS) algorithm to solve the wind farm layout problem, as EPS has been shown to be particularly effective in solving multimodal layout problems. It is also intended to show that the inclusion of extensions into the algorithm can better inform the search than algorithms that have been previously presented in the literature. Resulting layouts created by this extended pattern search algorithm develop more power than previously explored algorithms using the same evaluation models and objective functions. In addition, the algorithm’s resulting layouts motivate a heuristic that aids in the manual development of the best layout found to date. The results of this work validate the application of an extended pattern search algorithm to the wind farm layout problem, and that its performance is enhanced by the use of problem-specific extensions that aid in developing results that are superior to those developed by previous algorithms.

We address a challenge of active flow control: the optimization of many actuation parameters guaranteeing fast convergence and avoiding suboptimal local minima. This challenge is addressed by a new optimizer, called the explorative gradient method (EGM). EGM alternatively performs one exploitive downhill simplex step and an explorative Latin hypercube sampling iteration. Thus, the convergence rate of a gradient based method is guaranteed while, at the same time, better minima are explored. For an analytical multi-modal test function, EGM is shown to significantly outperform the downhill simplex method, the random restart simplex, Latin hypercube sampling, Monte Carlo sampling and the genetic algorithm. EGM is applied to minimize the net drag power of the two-dimensional fluidic pinball benchmark with three cylinder rotations as actuation parameters. The net drag power is reduced by 29 % employing direct numerical simulations at a Reynolds number of $100$ based on the cylinder diameter. This optimal actuation leads to 52 % drag reduction employing Coanda forcing for boat tailing and partial stabilization of vortex shedding. The price is an actuation energy corresponding to 23 % of the unforced parasitic drag power. EGM is also used to minimize drag of the $35^\circ$ slanted Ahmed body employing distributed steady blowing with 10 inputs. 17 % drag reduction are achieved using Reynolds-averaged Navier–Stokes simulations at the Reynolds number $Re_H=1.9 \times 10^5$ based on the height of the Ahmed body. The wake is controlled with seven local jet-slot actuators at all trailing edges. Symmetric operation corresponds to five independent actuator groups at top, middle, bottom, top sides and bottom sides. Each slot actuator produces a uniform jet with the velocity and angle as free parameters, yielding 10 actuation parameters as free inputs. The optimal actuation emulates boat tailing by inward-directed blowing with velocities which are comparable to the oncoming velocity. We expect that EGM will be employed as efficient optimizer in many future active flow control plants as alternative or augmentation to pure gradient search or explorative methods.

Багатошляхова маршрутизація характеризується великою часовою складністю пошуку множини шляхів, що не перетинаються. Часова складність знаходження найкоротшого шляху по алгоритму Дейкстри представляє собою величину O(kN2). При знаходженні k-шляхів часова складність збільшується відповідно в k раз. В зв’язку з цим, для пошуку множини шляхів, що не перетинаються, в рамках цієї роботи був запропонований модифікований метод «гілок та границь». Це досягається за рахунок виключення операцій перебору варіантів формування кожного шляху. В процесі роботи алгоритму у відповідності з методом «гілок та границь» будується дерево рішень, коренем якого є початкова вершина, а листями є вершини, суміжні з кінцевою вершиною.

Abstract Wave forces can form a serious threat to offshore platforms and ships. The damage produced by these forces of nature jeopardizes their operability as well as the well-being of their crews. Similar remarks apply to coastal defense systems. To develop the knowledge needed to safely design these constructions, in close cooperation with MARIN and the offshore industry the numerical simulation method ComFLOW is being developed. So far, its development was focussed on predicting wave loads (green water, slamming) on fixed structures, and for those applications the method is already being used successfully by the offshore industry. Often, the investigated object (ship, floating platform) is dynamically moving under the influence of these wave forces, and its hydrodynamic loading depends upon the position of the object with respect to the oncoming waves. Predicting the position (and deformation) of the body is an integral part of the (scientific and engineering) problem. The paper will give an overview of the algorithmic developments necessary to describe the above-mentioned physical phenomena. In particular attention will be paid to fluid-solid body and fluid-structure interaction and non-reflecting outflow boundary conditions. Several illustrations including validation, will demonstrate the prediction capabilities of the simulation method.

Abstract Flow-induced vibrations (FIV) of a flexibly-mounted harbor seal whisker module, allowed to oscillate in the cross-flow direction, placed in tandem arrangement with an upstream circular cylinder is studied, experimentally. The FIV response of the whisker module in terms of amplitudes and frequencies of oscillation are studied for a reduced velocity range of U* = 3.2–24.2, corresponding to a Reynolds number range of Re = 279–2,077. Flow-induced vibration response is studied and characterized for a wide range of separation distances between the upstream cylinder and the whisker module, as well as the angle at which the whisker faces the oncoming flow (angle of attack). Instantaneous volumetric flow field behind the whisker model was measured using Volumetric Particle Tracking Velocimetry (PTV) data processed by the “Shake The Box” (STB) algorithm that allowed for the time resolved, three dimensional (3D) 3 components (3C) measurement of flow field in the wake of the whisker module. The wake dynamics of the tandem pair of the whisker module and the upstream cylinder were studied at different angles of attack of the whisker module. Our results show while the whisker module was placed at 0° angle of attack, it did not experience any flow-induced vibration. However, when an upstream cylinder was placed in tandem with the whisker module, the whisker experienced large amplitude oscillations over a wide range of flow velocities. The whisker module picked up the “footprints” left behind the upstream cylinder for center-to center distance up to 25 times the whisker’s diameter. No oscillation was observed when the upstream cylinder was placed at relatively large distance of 50 times the whisker diameter. When the whisker was placed at 90° angle of attack, both for the standalone configuration of the whisker, as well as the tandem arrangement with the upstream cylinder, large amplitude oscillation were observed over a wide, but limited range of reduced velocities. This type of large-amplitude oscillation over a limited range of the flow velocity, while the frequency of oscillation stayed around the natural frequency of the system resembled those classic vortex-induced vibration response observed in the case of an elastically-mounted circular cylinder. Volumetric flow field measurements revealed highly three-dimensional vortex shedding patterns in the wake of the whisker module, which were attributed to the undulatory spanwise structure of the whisker. When the gap size between the upstream cylinder and the downstream whisker module was small, the wake in the gap region was characterized by the presence of two shear layers that were reattached to downstream whisker module. As the gap size increased, well-developed, highly three-dimensional vortical structures were observed in the gap region.