Wireless Communication in Process Control Loop: Requirements Analysis, Industry Practices and Experimental Evaluation

Wireless communication is already used in process automation for process monitoring. The next stage of implementation of wireless technology in industrial applications is for process control. The need for wireless networked control systems has evolved because of the necessity for extensibility, mobility, modularity, fast deployment, and reduced installation and maintenance cost. These benefits are only applicable given that the wireless network of choice can meet the strict requirements of process control applications, such as latency. In this regard, this paper is an effort towards identifying current industry practices related to implementing process control over a wireless link and evaluates the suitability of ISA100.11a network for use in process control through experiments

Time-resolved Adaptive Direct FEM Simulation of High-lift Aircraft Configurations

Our simulation methodology is referred to as Direct FEM Simulation (DFS), or General Galerkin (G2) and uses a finite element method (FEM) with piecewise linear approximation in space and time, and with numerical stabilization in the form of a weighted least squares method based on the residual. The incompressible Navier-Stokes Equations (NSE) are discretized directly, without applying any filter. Thus, the method does not result in Large Eddy Simulation (LES) filtered solutions, but is instead an approximation of a weak solution satisfying the weak form of the NSE. In G2 we have a posteriori error estimates for quantities of interest that can be expressed as functionals of a weak solution. These a posteriori error estimates, which form the basis for our adaptive mesh refinement algorithm, are based on the solution of an associated adjoint problem with a goal quantity (the aerodynamic forces in this work) as data, similarly to an optimal control problem. We provide references to related work below. The methodology and software have been previously validated for a number of turbulent flow benchmark problems, including one of the HiLiftPW-2 high Reynolds number cases. The DFS method is implemented in the Unicorn solver, which uses the open source software framework FEniCS-HPC, designed for automated solution of partial differential equations on massively parallel architectures using the FEM. In this chapter we present adaptive results from the Third AIAA High Lift Prediction Workshop in Denver, Colorado based on our DFS methodology and Unicorn/FEniCS-HPC software. We show that the methodology quantitavely and qualitatively captures the main features of the experiment - aerodynamic forces and the stall mechanism with a novel numerical tripping, with a much coarser mesh resolution and cheaper computational cost than the standard in the field

Polygons on a Rotating Fluid Surface

We report a novel and spectacular instability of a fluid surface in a rotating system. In a flow driven by rotating the bottom plate of a partially filled, stationary cylindrical container, the shape of the free surface can spontaneously break the axial symmetry and assume the form of a polygon rotating rigidly with a speed different from that of the plate. With water we have observed polygons with up to 6 corners. It has been known for many years that such flows are prone to symmetry breaking, but apparently the polygonal surface shapes have never been observed. The creation of rotating internal waves in a similar setup was observed for much lower rotation rates, where the free surface remains essentially flat. We speculate that the instability is caused by the strong azimuthal shear due to the stationary walls and that it is triggered by minute wobbling of the rotating plate. The slight asymmetry induces a tendency for mode-locking between the plate and the polygon, where the polygon rotates by one corner for each complete rotation of the plate

Computability and Adaptivity in CFD

We give a brief introduction to research on adaptive computational methods for laminar compressible and incompressible flow, and then focus on computability and adaptivity for turbulent incompressible flow, where we present a framework for adaptive finite element methods with duality- based a posteriori error control for chosen output quantities of interest. We show in concrete examples that outputs such as mean values in time of drag and lift of a bluff body in a turbulent flow are computable to a tolerance of a few percent, for a simple geometry using some hundred thousand mesh points, and for complex geometries some million mesh points

Deconvolving Instrumental and Intrinsic Broadening in Excited State X-ray Spectroscopies

Intrinsic and experimental mechanisms frequently lead to broadening of spectral features in excited-state spectroscopies. For example, intrinsic broadening occurs in x-ray absorption spectroscopy (XAS) measurements of heavy elements where the core-hole lifetime is very short. On the other hand, nonresonant x-ray Raman scattering (XRS) and other energy loss measurements are more limited by instrumental resolution. Here, we demonstrate that the Richardson-Lucy (RL) iterative algorithm provides a robust method for deconvolving instrumental and intrinsic resolutions from typical XAS and XRS data. For the K-edge XAS of Ag, we find nearly complete removal of ~9.3 eV FWHM broadening from the combined effects of the short core-hole lifetime and instrumental resolution. We are also able to remove nearly all instrumental broadening in an XRS measurement of diamond, with the resulting improved spectrum comparing favorably with prior soft x-ray XAS measurements. We present a practical methodology for implementing the RL algorithm to these problems, emphasizing the importance of testing for stability of the deconvolution process against noise amplification, perturbations in the initial spectra, and uncertainties in the core-hole lifetime.Comment: 35 pages, 13 figure

Quasi-Optimal Filtering in Inverse Problems

A way of constructing a nonlinear filter close to the optimal Kolmogorov - Wiener filter is proposed within the framework of the statistical approach to inverse problems. Quasi-optimal filtering, which has no Bayesian assumptions, produces stable and efficient solutions by relying solely on the internal resources of the inverse theory. The exact representation is given of the Feasible Region for inverse solutions that follows from the statistical consideration.Comment: 9 pages, 240 K

FEniCS-HPC: Automated predictive high-performance finite element computing with applications in aerodynamics

Developing multiphysics finite element methods (FEM) and scalable HPC implementations can be very challenging in terms of software complexity and performance, even more so with the addition of goal-oriented adaptive mesh refinement. To manage the complexity we in this work present general adaptive stabilized methods with automated implementation in the FEniCS-HPC automated open source software framework. This allows taking the weak form of a partial differential equation (PDE) as input in near-mathematical notation and automatically generating the low-level implementation source code and auxiliary equations and quantities necessary for the adaptivity. We demonstrate new optimal strong scaling results for the whole adaptive framework applied to turbulent flow on massively parallel architectures down to 25000 vertices per core with ca. 5000 cores with the MPI-based PETSc backend and for assembly down to 500 vertices per core with ca. 20000 cores with the PGAS-based JANPACK backend. As a demonstration of the power of the combination of the scalability together with the adaptive methodology allowing prediction of gross quantities in turbulent flow we present an application in aerodynamics of a full DLR-F11 aircraft in connection with the HiLift-PW2 benchmarking workshop with good match to experiments

Singing voice separation with deep U-Net convolutional networks

The decomposition of a music audio signal into its vocal and backing track components is analogous to image-to-image translation, where a mixed spectrogram is transformed into its constituent sources. We propose a novel application of the U-Net architecture — initially developed for medical imaging — for the task of source separation, given its proven capacity for recreating the fine, low-level detail required for high-quality audio reproduction. Through both quantitative evaluation and subjective assessment, experiments demonstrate that the proposed algorithm achieves state-of-the-art performance