Dynamic Model of a Vortex-Induced Energy Converter

2016 ◽  
Vol 138 (6) ◽  
Author(s):  
Giampaolo Manfrida ◽  
Mirko Rinchi ◽  
Guido Soldi
Keyword(s):  
Mathematical Formulation ◽  
Operating Conditions ◽  
Offshore Platforms ◽  
University Of Michigan ◽  
Design Variables ◽  
Harvesting Systems ◽  
An Array Of Cylinders ◽  
The Time Domain ◽  
Mechanical Optimization ◽  
Energy Converters

Vortex-induced energy converters (VIECs) are attracting the attention of researchers looking for energy-harvesting systems in the marine environment. These energy converters, while probably less efficient than many other specialized devices, have very few moving parts and are particularly suitable for operation in harsh environments, such as those encountered in the ocean and in offshore platforms. The principle of operation of VIECs is tapping the transverse vibration of a blunt slender body immersed in a stream, induced by unsteady flow separation (Von Karman vortex street). The simplest device is an array of cylinders: under specific conditions and with careful design, it is possible to work close to resonance and thereby to obtain large amplitudes of oscillation, which are converted into electricity by suitable devices (linear electrical generators or piezoelectric cells). The system was developed experimentally at University of Michigan, with several patents pending and scientific material published on preliminary tests. Numerical simulations of system dynamics allow to simulate more realistic operating conditions and to perform the mechanical optimization of the system in relation to a specific sea location. A model of the system was thus developed, resulting in a nonlinear dynamic mathematical formulation; this last is solved in the time domain using matlab/simulink programming. The sensitivity of the efficiency to the main design variables is investigated. The results demonstrate that the efficiency and power density are not attractive for the typical Mediterranean Sea conditions; however, as energy can be harvested over large surfaces, the system appears to deserve attention.

Improving Emission and Blow-Out Characteristics of Novel Natural Gas Low NOx Burners for Heavy Duty Gas Turbine

2019 ◽  
Author(s):  
Matteo Cerutti ◽  
Michele Roma ◽  
Alessio Picchi ◽  
Riccardo Becchi ◽  
Bruno Facchini
Keyword(s):  
Objective Function ◽  
Gas Turbine ◽  
Mathematical Formulation ◽  
Flame Stabilization ◽  
Operating Conditions ◽  
Design Parameters ◽  
Design Variables ◽  
Geometrical Features ◽  
Heavy Duty Gas Turbine ◽  
Operating Window

Abstract The development and the optimization of a novel dry low NOx burner may require several steps of improvement. The first step of the overall development process has been documented by authors in a previous paper and included an exhaustive experimental characterization of a set of novel geometries. The in-depth results analysis allowed to correlate the investigated design parameters to burner performances, discovering possible two-fold optimization paths. Recurrent verifications of the assumptions made to define prototypes design are considered a mandatory step to avoid significant deviation from the correct optimization path, which strongly depends on both objective function definition and selection of design variables. Concerning the objective function, a proper mathematical formulation was proposed in the previous work, which represented a balance between two apparently conflicting aspect like flame stability and low emissions. Concerning design variables, outcomes of the first test campaign have been used in the present work to define new burner geometries. Starting from a new baseline who has showed the widest low NOx operating window, additional geometrical features have been considered in this survey as potentially affecting flame stabilization. Thanks to the degree of freedom offered by DMLM technology, rapid prototyping of alternative geometries allowed to easily setup a new experimental plan for the second optimization step. Exploiting the same approach used in the first test campaign, new geometries have been tested in a single-cup test rig at gas turbine relevant operating conditions, showing Stable low-NOx operating windows have been evaluated throughout dedicated objective functions for all geometries and results showed lower NOx and CO emissions as a consequence of the newly introduced geometrical modifications. Moreover, the comparison with the estimates of the previous campaign proved the existence of the identified optimization path. Indeed, it furnished valid elements for further using of the proposed methodology for the improvement of emission and blow-out characteristics of novel burners and, more in general, for the development of a novel dry low NOx technology.

scholarly journals Mutual Information and Meta-Heuristic Classifiers Applied to Bearing Fault Diagnosis in Three-Phase Induction Motors

2020 ◽  
Vol 11 (1) ◽  
pp. 314
Author(s):  
Gustavo Henrique Bazan ◽  
Alessandro Goedtel ◽  
Marcelo Favoretto Castoldi ◽  
Wagner Fontes Godoy ◽  
Oscar Duque-Perez ◽  
...  
Keyword(s):  
Fault Diagnosis ◽  
Mutual Information ◽  
Induction Motors ◽  
Operating Conditions ◽  
Industrial Systems ◽  
Bearing Fault Diagnosis ◽  
Bee Colony ◽  
Three Phase ◽  
C4.5 Decision Tree ◽  
The Time Domain

Three-phase induction motors are extensively used in industrial processes due to their robustness, adaptability to different operating conditions, and low operation and maintenance costs. Induction motor fault diagnosis has received special attention from industry since it can reduce process losses and ensure the reliable operation of industrial systems. Therefore, this paper presents a study on the use of meta-heuristic tools in the diagnosis of bearing failures in induction motors. The extraction of the fault characteristics is performed based on mutual information measurements between the stator current signals in the time domain. Then, the Artificial Bee Colony algorithm is used to select the relevant mutual information values and optimize the pattern classifier input data. To evaluate the classification accuracy under various levels of failure severity, the performance of two different pattern classifiers was compared: The C4.5 decision tree and the multi-layer artificial perceptron neural networks. The experimental results confirm the effectiveness of the proposed approach.

A Multiple Harmonic Open-Loop Controller for Hydro/Aerodynamic Force Measurements in Rotating Machinery Using Magnetic Bearings

2002 ◽  
Vol 124 (4) ◽  
pp. 827-834 ◽  
Author(s):  
D. O. Baun ◽  
E. H. Maslen ◽  
C. R. Knospe ◽  
R. D. Flack
Keyword(s):  
Frequency Domain ◽  
Time Domain ◽  
Open Loop ◽  
Rotating Machinery ◽  
Operating Conditions ◽  
Rotor Vibration ◽  
Aerodynamic Forces ◽  
Analog Input ◽  
Input And Output ◽  
The Time Domain

Inherent in the construction of many experimental apparatus designed to measure the hydro/aerodynamic forces of rotating machinery are features that contribute undesirable parasitic forces to the measured or test forces. Typically, these parasitic forces are due to seals, drive couplings, and hydraulic and/or inertial unbalance. To obtain accurate and sensitive measurement of the hydro/aerodynamic forces in these situations, it is necessary to subtract the parasitic forces from the test forces. In general, both the test forces and the parasitic forces will be dependent on the system operating conditions including the specific motion of the rotor. Therefore, to properly remove the parasitic forces the vibration orbits and operating conditions must be the same in tests for determining the hydro/aerodynamic forces and tests for determining the parasitic forces. This, in turn, necessitates a means by which the test rotor’s motion can be accurately controlled to an arbitrarily defined trajectory. Here in, an interrupt-driven multiple harmonic open-loop controller was developed and implemented on a laboratory centrifugal pump rotor supported in magnetic bearings (active load cells) for this purpose. This allowed the simultaneous control of subharmonic, synchronous, and superharmonic rotor vibration frequencies with each frequency independently forced to some user defined orbital path. The open-loop controller was implemented on a standard PC using commercially available analog input and output cards. All analog input and output functions, transformation of the position signals from the time domain to the frequency domain, and transformation of the open-loop control signals from the frequency domain to the time domain were performed in an interrupt service routine. Rotor vibration was attenuated to the noise floor, vibration amplitude ≈0.2 μm, or forced to a user specified orbital trajectory. Between the whirl frequencies of 14 and 2 times running speed, the orbit semi-major and semi-minor axis magnitudes were controlled to within 0.5% of the requested axis magnitudes. The ellipse angles and amplitude phase angles of the imposed orbits were within 0.3 deg and 1.0 deg, respectively, of their requested counterparts.

Fully Parametric High-Fidelity CFD Model for the Design Optimisation of the Cyclic Stagger Pattern of a Set of Fan Outlet Guide Vanes

2009 ◽  
Author(s):  
Andrea Milli ◽  
Olivier Bron
Keyword(s):  
Complex Geometry ◽  
Single Point ◽  
Sensitivity Study ◽  
Operating Conditions ◽  
High Fidelity ◽  
Cfd Model ◽  
Design Optimisation ◽  
Guide Vanes ◽  
High Loss ◽  
Design Variables

The present paper deals with the redesign of cyclic variation of a set of fan outlet guide vanes by means of high-fidelity full-annulus CFD. The necessity for the aerodynamic redesign originated from a change to the original project requirement, when the customer requested an increase in specific thrust above the original engine specification. The main objectives of this paper are: 1) make use of 3D CFD simulations to accurately model the flow field and identify high-loss regions; 2) elaborate an effective optimisation strategy using engineering judgement in order to define realistic objectives, constraints and design variables; 3) emphasise the importance of parametric geometry modelling and meshing for automatic design optimisation of complex turbomachinery configurations; 4) illustrate that the combination of advanced optimisation algorithms and aerodynamic expertise can lead to successful optimisations of complex turbomachinery components within practical time and costs constrains. The current design optimisation exercise was carried out using an in-house set of software tools to mesh, resolve, analyse and optimise turbomachinery components by means of Reynolds-averaged Navier-Stokes simulations. The original configuration was analysed using the 3D CFD model and thereafter assessed against experimental data and flow visualisations. The main objective of this phase was to acquire a deep insight of the aerodynamics and the loss mechanisms. This was important to appropriately limit the design scope and to drive the optimisation in the desirable direction with a limited number of design variables. A mesh sensitivity study was performed in order to minimise computational costs. Partially converged CFD solutions with restart and response surface models were used to speed up the optimisation loop. Finally, the single-point optimised circumferential stagger pattern was manually adjusted to increase the robustness of the design at other flight operating conditions. Overall, the optimisation resulted in a major loss reduction and increased operating range. Most important, it provided the project with an alternative and improved design within the time schedule requested and demonstrated that CFD tools can be used effectively not only for the analysis but also to provide new design solutions as a matter of routine even for very complex geometry configurations.

Improvement of the Static and Dynamic Characteristics of Magnetic Head Sliders by Optimum Design

1999 ◽  
Vol 122 (1) ◽  
pp. 280-287 ◽  
Author(s):  
Hiromu Hashimoto ◽  
Yasuhisa Hattori
Keyword(s):  
Objective Function ◽  
Optimum Design ◽  
Amplitude Ratio ◽  
Optimization Technique ◽  
Hard Disk Drives ◽  
Maximum Amplitude ◽  
Disk Surface ◽  
Operating Conditions ◽  
Magnetic Head ◽  
Design Variables

The aim of this paper is to develop a general methodology for the optimum design of magnetic head sliders in improving the spacing characteristics between a slider and disk surface under static and dynamic operating conditions of hard disk drives and to present an application of the methodology to the IBM 3380-type slider design. To generate the optimal design variables, the objective function is defined as the weighted sum of the minimum spacing, the maximum difference in the spacing due to variation of the radial location of the head, and the maximum amplitude ratio of the slider motion. Slider rail width, taper length, taper angle, suspension position, and preload are selected as the design variables. Before the optimization of the head, the effects of these five design variables on the objective function are examined by a parametric study, and then the optimum design variables are determined by applying the hybrid optimization technique, combining the direct search method and successive quadratic programming. From the obtained results, the effectiveness of optimum design on the spacing characteristics of magnetic heads is clarified. [S0742-4787(00)03701-2]

scholarly journals Hardware-in-the-loop simulation of wave energy converters based on dielectric elastomer generators

Meccanica ◽  
2021 ◽  
Vol 56 (5) ◽  
pp. 1223-1237
Author(s):  
Giacomo Moretti ◽  
Andrea Scialò ◽  
Giovanni Malara ◽  
Giovanni Gerardo Muscolo ◽  
Felice Arena ◽  
...  
Keyword(s):  
Wave Energy ◽  
Large Scale ◽  
Low Cost ◽  
Test Site ◽  
Dielectric Elastomer ◽  
Operating Conditions ◽  
Polymer Materials ◽  
Hardware In The Loop ◽  
Wave Energy Converters ◽  
Energy Converters

AbstractDielectric elastomer generators (DEGs) are soft electrostatic generators based on low-cost electroactive polymer materials. These devices have attracted the attention of the marine energy community as a promising solution to implement economically viable wave energy converters (WECs). This paper introduces a hardware-in-the-loop (HIL) simulation framework for a class of WECs that combines the concept of the oscillating water columns (OWCs) with the DEGs. The proposed HIL system replicates in a laboratory environment the realistic operating conditions of an OWC/DEG plant, while drastically reducing the experimental burden compared to wave tank or sea tests. The HIL simulator is driven by a closed-loop real-time hydrodynamic model that is based on a novel coupling criterion which allows rendering a realistic dynamic response for a diversity of scenarios, including large scale DEG plants, whose dimensions and topologies are largely different from those available in the HIL setup. A case study is also introduced, which simulates the application of DEGs on an OWC plant installed in a mild real sea laboratory test-site. Comparisons with available real sea-test data demonstrated the ability of the HIL setup to effectively replicate a realistic operating scenario. The insights gathered on the promising performance of the analysed OWC/DEG systems pave the way to pursue further sea trials in the future.

Evaluation of Fuel Preparation Systems for Lean Premixing-Prevaporizing Combustors

1986 ◽  
Vol 108 (2) ◽  
pp. 391-395
Author(s):  
W. J. Dodds ◽  
E. E. Ekstedt
Keyword(s):  
System Design ◽  
Large Scale ◽  
Fuel Injection ◽  
Operating Conditions ◽  
Turbine Engine ◽  
Fuel Injectors ◽  
Design Concepts ◽  
Mixture Preparation ◽  
Design Variables ◽  
System Length

A series of tests was conducted to provide data for the design of premixing-prevaporizing fuel-air mixture preparation systems for aircraft gas turbine engine combustors. Fifteen configurations of four different fuel-air mixture preparation system design concepts were evaluated to determine fuel-air mixture uniformity at the system exit over a range of conditions representative of cruise operation for a modern commercial turbofan engine. Operating conditions, including pressure, temperature, fuel-air ratio, and velocity had no clear effect on mixture uniformity in systems which used low-pressure fuel injectors. However, performance of systems using pressure atomizing fuel nozzles and large-scale mixing devices was shown to be sensitive to operating conditions. Variations in system design variables were also evaluated and correlated. Mixture uniformity improved with increased system length, pressure drop, and number of fuel injection points per unit area. A premixing system compatible with the combustor envelope of a typical combustion system and capable of providing mixture nonuniformity (standard deviation/mean) below 15% over a typical range of cruise operating conditions was demonstrated.

A Deep Neural Network Model for Learning Runtime Frequency Response Function Using Sensor Measurements

2021 ◽  
Author(s):  
Yongzhi Qu ◽  
Gregory W. Vogl ◽  
Zechao Wang
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Fourier Transform ◽  
Time Domain ◽  
Frequency Response Function ◽  
Frequency Component ◽  
Operating Conditions ◽  
Input Output ◽  
The Fourier Transform ◽  
The Time Domain

Abstract The frequency response function (FRF), defined as the ratio between the Fourier transform of the time-domain output and the Fourier transform of the time-domain input, is a common tool to analyze the relationships between inputs and outputs of a mechanical system. Learning the FRF for mechanical systems can facilitate system identification, condition-based health monitoring, and improve performance metrics, by providing an input-output model that describes the system dynamics. Existing FRF identification assumes there is a one-to-one mapping between each input frequency component and output frequency component. However, during dynamic operations, the FRF can present complex dependencies with frequency cross-correlations due to modulation effects, nonlinearities, and mechanical noise. Furthermore, existing FRFs assume linearity between input-output spectrums with varying mechanical loads, while in practice FRFs can depend on the operating conditions and show high nonlinearities. Outputs of existing neural networks are typically low-dimensional labels rather than real-time high-dimensional measurements. This paper proposes a vector regression method based on deep neural networks for the learning of runtime FRFs from measurement data under different operating conditions. More specifically, a neural network based on an encoder-decoder with a symmetric compression structure is proposed. The deep encoder-decoder network features simultaneous learning of the regression relationship between input and output embeddings, as well as a discriminative model for output spectrum classification under different operating conditions. The learning model is validated using experimental data from a high-pressure hydraulic test rig. The results show that the proposed model can learn the FRF between sensor measurements under different operating conditions with high accuracy and denoising capability. The learned FRF model provides an estimation for sensor measurements when a physical sensor is not feasible and can be used for operating condition recognition.

Floating Body Equilibrium by Potential-Energy Minimization

1991 ◽  
Vol 28 (03) ◽  
pp. 153-162
Author(s):  
Antonio Campanile
Keyword(s):  
Potential Energy ◽  
Energy Minimization ◽  
Stable Equilibrium ◽  
Mathematical Formulation ◽  
Floating Body ◽  
Offshore Platforms ◽  
Equilibrium Equations ◽  
Hull Form ◽  
Computer Based ◽  
Marine Vehicle

The paper presents a computer-based approach aiming to solve the equilibrium equations of a floating body by means of potential-energy minimization. After a brief and general discussion, the principle that the potential energy of the system must be at a minimum is adopted as the condition for identifying the stable equilibrium positions of a marine vehicle. A consistent mathematical formulation is then developed. The problem is solved, therefore, by searching for the minimum of a function of three variables using a simple and efficient iterative method. This makes it possible for the equilibrium positions to be determined directly, unlike the classic methods-that is, without any previously constructed table of hydrostatic data and regardless of the magnitude of waterplane rotation compared with the initial orientation. No restriction is stipulated on hull form. Some study cases relating to a prismatic barge and a jacket-type platform are presented and analyzed. Relevant numerical results allow the procedure to be optimized so as to improve convergence. Finally, peculiar features of the proposed method are discussed, with particular reference to jacket-type offshore platforms, and further valuable applications are indicated.

scholarly journals Ecodesign of Batch Processes: Optimal Design Strategies for Economic and Ecological Bioprocesses

2007 ◽  
Vol 5 (1) ◽  
Author(s):  
Adrian Dietz ◽  
Catherine Azzaro Pantel ◽  
Luc Guy Pibouleau ◽  
Serge Domenech
Keyword(s):  
Genetic Algorithm ◽  
Discrete Event ◽  
Operating Conditions ◽  
Batch Processes ◽  
Stochastic Algorithm ◽  
Plant Design ◽  
Environment Design ◽  
Design Strategies ◽  
Design Variables ◽  
Batch Plant

This work deals with the multicriteria cost-environment design of multiproduct batch plants, where the design variables are the equipment item sizes as well as the operating conditions. The case study is a multiproduct batch plant for the production of four recombinant proteins. Given the important combinatorial aspect of the problem, the approach used consists in coupling a stochastic algorithm, indeed a Genetic Algorithm (GA) with a Discrete Event Simulator (DES). To take into account the conflicting situations that may be encountered at the earliest stage of batch plant design, i.e. compromise situations between cost and environmental consideration, a Multicriteria Genetic Algorithm (MUGA) was developed with a Pareto optimal ranking method. The results show how the methodology can be used to find a range of trade-off solutions for optimizing batch plant design.

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