Approximate deconvolution boundary conditions for large eddy simulation

AbstractWe introduce new boundary conditions for large eddy simulation. These boundary conditions are based on an approximate deconvolution approach. They are computationally efficient and general, which makes them appropriate for the numerical simulation of turbulent flows with time-dependent boundary conditions. Numerical results are presented to demonstrate the new boundary conditions in a simplified linear setting

An Optimal Control Approach to Sensor / Actuator Placement for Optimal Control of High Performance Buildings

In this paper we consider the problem of best sensor location for optimal state estimation for real time energy efficient optimal control. Although the basic idea can be applied to the joint sensor / actuator location problem, we focus on the sensor placement because of its immediate application to retrofits where sensors can easily relocated while the location of control inputs (diffusers, vents, etc.) are less movable. It is important to note that this approach does not require “time accurate high fidelity simulations” and has been successful in other disciplines such as structural control, control of chemical processes and fluid flow control. We show how these techniques can be applied to high performance building design and control. We present the theoretical basis for the method, discuss the computational requirements and use simple models to illustrate the ideas and numerical methods for solution. We then apply the method results to a multi-zone hospital suite problem

An Improved Continuous Sensitivity Equation Method for Optimal Shape Design in Mixed Convection

International audienceThis paper presents an optimal shape design methodology for mixed convection problems. The Navier-Stokes equations and the Continuous Sensitivity Equations (CSE) are solved using an adaptive finite-element method to obtain flow and sensitivity fields. A new procedure is presented to extract accurate values of the flow derivatives at the boundary, appearing in the CSE boundary conditions for shape parameters. Flow and sensitivity information are then employed to calculate the value and gradient of a design objective function. A BFGS optimization algorithm is used to find optimal shape parameter values. The proposed approach is first verified on a problem with a closed form solution, obtained by the method of manufactured solutions. The method is then applied to determine the optimal shape of a model cooling system

Order reduction approaches for the algebraic Riccati equation and the LQR problem

We explore order reduction techniques for solving the algebraic Riccati equation (ARE), and investigating the numerical solution of the linear-quadratic regulator problem (LQR). A classical approach is to build a surrogate low dimensional model of the dynamical system, for instance by means of balanced truncation, and then solve the corresponding ARE. Alternatively, iterative methods can be used to directly solve the ARE and use its approximate solution to estimate quantities associated with the LQR. We propose a class of Petrov-Galerkin strategies that simultaneously reduce the dynamical system while approximately solving the ARE by projection. This methodology significantly generalizes a recently developed Galerkin method by using a pair of projection spaces, as it is often done in model order reduction of dynamical systems. Numerical experiments illustrate the advantages of the new class of methods over classical approaches when dealing with large matrices

Approximation of Parametric Derivatives by the Empirical Interpolation Method

We introduce a general a priori convergence result for the approximation of parametric derivatives of parametrized functions. We consider the best approximations to parametric derivatives in a sequence of approximation spaces generated by a general approximation scheme, and we show that these approximations are convergent provided that the best approximation to the function itself is convergent. We also provide estimates for the convergence rates. We present numerical results with spaces generated by a particular approximation scheme—the Empirical Interpolation Method—to confirm the validity of the general theory

Fast Approximated POD for a Flat Plate Benchmark with a Time Varying Angle of Attack

An approximate POD algorithm provides an empirical Galerkin approximation with guaranteed a priori lower bound on the required resolution. The snapshot ensemble is partitioned into several sub-ensembles. Cross correlations between these sub-ensembles are approximated in terms of a far smaller correlation matrix. Computational speedup is nearly linear in the number of partitions, up to a saturation that can be estimated a priori. The algorithm is particularly suitable for analyzing long transient trajectories of high dimensional simulations, but can be applied also for spatial partitioning and parallel processing of very high spatial dimension data. The algorithm is demonstrated using transient data from two simulations. First, a two dimensional simulation of the flow over a flat plate, as it transitions from AOA = 30° to a horizontal position and back. Second, a three dimensional simulation of a flat plate with aspect ratio two as it transitions from a horizontal position to AOA = 30°

A Review of River Herring Science in Support of Species Conservation and Ecosystem Restoration

River herring—a collective name for the Alewife Alosa pseudoharengus and Blueback Herring A. aestivalis—play a crucial role in freshwater and marine ecosystems along the Eastern Seaboard of North America. River herring are anadromous and return to freshwater habitats in the tens to hundreds of millions to spawn, supplying food to many species and providing nutrients to freshwater ecosystems. After two and a half centuries of habitat loss, habitat degradation, and overfishing, river herring are at historic lows. In 2013, National Oceanic and Atmospheric Administration Fisheries established the Technical Expert Working Group (TEWG) to synthesize information about river herring and to provide recommendations to advance the science related to their restoration. This paper was composed largely by the chairs of the TEWG subgroups and represents a review of the current state of knowledge of river herring, with an emphasis on identification of threats and discussion of recent research and management actions related to understanding and reducing these threats. Important research needs are then identified and discussed. Finally, current knowledge is synthesized, considering the relative importance of different threats. This synthesis identifies dam removal and increased stream connectivity as critical to river herring restoration. Better understanding and accounting for predation, climate change, and fisheries are also important for restoration. Finally, there is recent evidence that the effects of human development and contamination on habitat quality may be more important threats than previously recognized. Given the range of threats, an ecosystem approach is needed to be successful with river herring restoration. To facilitate this ecosystem approach, collaborative forums such as the TEWG (renamed the Atlantic Coast River Herring Collaborative Forum in 2020) are needed to share and synthesize information among river herring managers, researchers, and community groups from across the species’ range