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Inspired by nature, oscillating foils offer viable options as alternate energy resources to harness energy from wind and water. Here, we propose a proper orthogonal decomposition (POD)-based reduced-order model (ROM) of power generation by flapping airfoils in conjunction with deep neural networks. Numerical simulations are performed for incompressible flow past a flapping NACA-0012 airfoil at a Reynolds number of 1100 using the Arbitrary Lagrangian–Eulerian approach. The snapshots of the pressure field around the flapping foil are then utilized to construct the pressure POD modes of each case, which serve as the reduced basis to span the solution space. The novelty of the current research relates to the identification, development, and employment of long-short-term neural network (LSTM) models to predict temporal coefficients of the pressure modes. These coefficients, in turn, are used to reconstruct hydrodynamic forces and moment, leading to computations of power. The proposed model takes the known temporal coefficients as inputs and predicts the future temporal coefficients followed by previously estimated temporal coefficients, very similar to traditional ROM. Through the new trained model, we can predict the temporal coefficients for a long time duration that can be far beyond the training time intervals more accurately. It may not be attained by traditional ROMs that lead to erroneous results. Consequently, the flow physics including the forces and moment exerted by fluids can be reconstructed accurately using POD modes as the basis set. [ABSTRACT FROM AUTHOR]

In this article, we introduce a machine learning–based reduced-order modeling (ML-ROM) framework through the integration of proper orthogonal decomposition (POD) and deep neural networks (DNNs), in addition to long short-term memory (LSTM) networks. The DNN is utilized to upscale POD temporal coefficients and their respective spatial modes to account for the dynamics represented by the truncated modes. In the second part of the algorithm, temporal evolution of the POD coefficients is obtained by recursively predicting their future states using an LSTM network. The proposed model (ML-ROM) is tested for flow past a circular cylinder characterized by the Navier–Stokes equations. We perform pressure mode decomposition analysis on the flow data using both POD and ML-ROM to predict hydrodynamic forces and demonstrate the accuracy of the proposed strategy for modeling lift and drag coefficients. [ABSTRACT FROM AUTHOR]

In this paper, an artificial neural network (ANN)-based reduced order model (ROM) is developed for the hydrodynamics forces on an airfoil immersed in the flow field at different angles of attack. The proper orthogonal decomposition (POD) of the flow field data is employed to obtain pressure modes and the temporal coefficients. These temporal pressure coefficients are used to train the ANN using data from three different angles of attack. The trained network then takes the value of angle of attack (AOA) and past POD coefficients as an input and predicts the future temporal coefficients. We also decompose the surface pressure modes into lift and drag components. These surface pressure modes are then employed to calculate the pressure component of lift CLp and drag CDp coefficients. The train model is then tested on the in-sample data and out-of-sample data. The results show good agreement with the true numerical data, thus validating the neural network based model. [ABSTRACT FROM AUTHOR]

An efficient parallel scheme based on the nodal discontinuous Galerkin finite element method (nodal-DGFEM) for the numerical solution of the partial differential equations governing fluid flow phenomena is discussed. The flow solver is demonstrated to perform numerical simulation of two-dimensional flow regimes on unstructured triangular grids. The parallel implementation serves to fulfill the requisition of the numerical method regarding high-performance computing resources. The distributed memory programming model with the domain decomposition approach is adopted. The message passing interface library is used for communication among the parallel processes, which are assigned domain-decomposed subproblems. The presented parallelization strategy accurately and efficiently tackles the communication of multi-node data on the element edges between the neighboring parallel processes. The efficacy and efficiency of the parallel solver are demonstrated through solving the well-known problem of non-viscous isentropic convecting vortex flow on parallel systems. The parallelization would extend the scope of the DGFEM by producing solutions in reasonable time frames. [ABSTRACT FROM AUTHOR]

This article concerns heat transfer analysis in pulsating flow in a channel with walls having multiple symmetric constrictions. The flow is influenced by Lorentz force and thermal radiation. The unsteady governing equations, simplified for low conducting fluids, are solved by the finite difference method using the stream–vorticity function formulation. The effects of the emerging parameters, including the magnetic field parameter (Hartman number), Reynolds number, Prandtl number, and radiation parameter on various flow profiles, are studied. The profiles of dimensionless axial velocity, temperature, wall shear stress (WSS), skin friction coefficient, and local Nusselt number are discussed graphically. The profiles are examined at various prominent axial locations and time instants of the pulse cycle. The WSS has a direct relation with the Hartmann and Strouhal numbers. The WSS generated at the first constriction is higher than that at the second constriction. The WSS increases with an increase in the Strouhal number in the accelerating phase and decreases in the decelerating phase on both the constrictions. The temperature decreases with an increase in the Hartman and Prandtl numbers at the constricted portion of the channel. The radiation parameter directly affects the temperature and inversely affects the Nusselt number at the constricted part of the channel. However, in general, the flow profiles exhibit irregular patterns downstream of the constriction. The Nusselt profiles are higher at the first encountered constriction bump than that at the next bumps. [ABSTRACT FROM AUTHOR]

This article presents a numerical investigation of the pulsatile flow of non-Newtonian Casson fluid through a rectangular channel with symmetrical local constriction on the walls. The objective is to study the heat transfer characteristics of the said fluid flow under an applied magnetic field and thermal radiation. Such a study may find its application in devising treatments for stenosis in blood arteries, designing biomechanical devices, and controlling industrial processes with flow pulsation. Using the finite difference approach, the mathematical model is solved and is converted into the vorticity-stream function form. The impacts of the Hartman number, Strouhal number, Casson fluid parameter, porosity parameter, Prandtl number, and thermal radiation parameter on the flow profiles are argued. The effects on the axial velocity and temperature profiles are observed and argued. Some plots of the streamlines, vorticity, and temperature distribution are also shown. On increasing the values of the magnetic field parameter, the axial flow velocity increases, whereas the temperature decreases. The flow profiles for the Casson fluid parameter have a similar trend, and the profiles for the porosity parameter have an opposite trend to the flow profiles for the magnetic field parameter. The temperature decreases with an increase in the Prandtl number. The temperature increases with an increase in the thermal radiation parameter. The profile patterns are not perfectly uniform downstream of the constriction. [ABSTRACT FROM AUTHOR]

High-order numerical schemes implemented on high-performance parallel computers are of special interest for contemporary numerical simulations, especially in computational fluid dynamics. In this study, first, a high-order parallel flow solver is presented for some test cases of aerodynamic simulations. The flow solver is based on a discontinuous Galerkin finite element method on arbitrary grids with different orders of polynomial approximation for solving the compressible flow model. Second, the distributed-memory parallel implementation of the flow solver is benchmarked on a shared-memory multicore system. A distributed-memory parallel application can be executed on shared-memory architectures by assuming that each of the parallel processes assumes separate memory address space, although all are present in a common memory bank. This approach can offer an effective measure to address several issues related to limited resources, especially for uninterrupted electric supply. The scalability of the parallel application is analyzed by varying the problem workload per process for the test cases. For some test cases in the present study, over 90% parallel efficiency per process is also observed. The performance of the distributed-memory program on the shared-memory architecture establishes suitability and robustness of the approach for small to medium scale problems, at least. [ABSTRACT FROM AUTHOR]

This study numerically investigates two-dimensional incompressible flows over elastically mounted foils, undergoing semi-passive and fully passive motion. In our strongly coupled numerical models, we employ linear and cubic stiffness and damping terms in order to examine their highly nonlinear response. The undamped model of the fully passive system exhibits various responses from periodic to chaotic and then to flip-over for the reduced velocity, ranging from 1 to 10. However, introducing the cubic damping terms causes a significant decrease in the magnitude of plunging and pitching amplitudes without affecting the onset point of bifurcation. Also, plunging and pitching amplitudes are altered significantly after the point of onset. Furthermore, the performance metrics of each passive system are computed for power generation applications to demonstrate that semi-passive system attain efficiency up to 20% for a pitching amplitude of 50° with the excitation frequency in the narrow range of 0.15 to 0.20. On the other hand for a fully passive system, the efficiency of around 34% is obtained near the onset point of a bifurcation with a low mass ratio and linear damping terms. However, introducing cubic damping terms causes degradation in efficiency to bring it down to 14 − 20 % for a wide range of reduced velocity. • Nonlinear dynamical models are strongly coupled with an in-house CFD-based solver. • Nonlinear damping and stiffness are introduced in the computational models. • For the semi-passive dynamical system, an efficiency of 20% is attained. • The fully passive system leads to an efficiency of up to 17% for low mass ratios. • Introducing cubic damping degrades the efficiency to 8%–9% for fully-passive foils. [ABSTRACT FROM AUTHOR]

Micro-power generators are increasingly becoming popular to meet the power requirements of micro-electromechanical systems, such as small sensors. One such resource of harnessing energy is through exploiting flow instabilities found in vortex-induced vibrations, flutter, etc. In this work, we numerically investigate the hydrodynamic performance of fully forced flapping foils with the goal to exploit their underlying physical mechanisms for the development of micro-power generators. We consider prescribed combination of plunging and pitching motions imposed to a NACA-0012 airfoil. We conduct a parametric study by varying the Strouhal number and the amplitude of the pitching angle to identify two operational flow regimes: power generation and thrust-producing propulsion using the feathering criterion. In the latter regime, the foil performs positive work on the surrounding fluid and therefore, the positive propulsive efficiency can be attained as long as the horizontal hydrodynamic force remains negative. For the power generation regime, the product of the lift force and plunging velocity is found mostly positive over the oscillating cycle, which indicates that the flowing fluid carries out work on the foil. The parametric study reveals that the foil can reach up to 42% power generation efficiency when setting the pitching amplitude in the range of 60° to 70°. For foils operating in the power generation regime, we present a piezoelectric energy harvester that can efficiently harness usable electric power from high fluid pressure regions. We identify two core locations based on the pressure field at which the attachment of piezoelectric patches can lead to significant energy harvesting. As such, the present study provides guidance for the design enhancement of micro-power generators relying on the interactions of flapping foils with the surrounding fluid. • Develop a computational model to simulate incompressible flows over moving bodies. • Analyze the hydrodynamic characteristics and propulsive efficiency of flapping foils. • Identify the flow regimes of flapping foils: power generation and thrust-producing propulsion. • Propose a design of a piezoelectric energy harvester. [ABSTRACT FROM AUTHOR]