Acoustic Performance of a Periodically Voided Viscoelastic Medium With Uncertainty in Design Parameters

2020 ◽  
Vol 142 (6) ◽  
Author(s):  
Gyani Shankar Sharma ◽  
Beatrice Faverjon ◽  
David Dureisseix ◽  
Alex Skvortsov ◽  
Ian MacGillivray ◽  
...  
Keyword(s):  
Resonance Frequency ◽  
Stochastic Models ◽  
Sound Transmission ◽  
Geometric Parameters ◽  
Design Parameters ◽  
Computationally Efficient ◽  
Acoustic Performance ◽  
Material Parameters ◽  
The Mean ◽  
Uncertainty In Design

Abstract The effect of uncertainties in material and geometric parameters on the acoustic performance of a viscoelastic coating is investigated. The model of the coating comprises a structure conventionally used in underwater applications, namely a soft elastic matrix embedded with periodic arrangements of voids. To investigate the effect of uncertainties on the acoustic performance of the coating, stochastic models based on the non-intrusive polynomial chaos expansion (PCE) method and Monte Carlo (MC) simulations are developed. The same analytical formulation of the acoustic coating is employed in both stochastic models. In the PCE method, the analytical model is transformed into a computationally efficient surrogate model using stochastic collocation. The effect of uncertainty in an individual geometric or material parameter on the acoustic performance of the coating is investigated by examining the mean, envelopes, and probability distribution of the monopole resonance frequency and sound transmission through the coating. The effect of variation in combinations of geometric and material parameters is then examined. Uncertainty in the geometric parameters is observed to have greater impact on the resonance frequency of the voids and sound transmission through the coating compared to uncertainty in the material properties.

Preliminary Experimental Study of SMA Knitted Actuation Architectures

Aerospace ◽  
2006 ◽  
Author(s):  
Julianna Evans ◽  
Diann Brei ◽  
Jonathan Luntz
Keyword(s):  
Experimental Study ◽  
Smart Materials ◽  
Material Properties ◽  
Geometric Parameters ◽  
Design Parameters ◽  
Static Force ◽  
Vast Array ◽  
Material Parameters ◽  
Wide Range ◽  
And Control

Nature builds an immense set of materials exhibiting a wide range of behaviors using only a small number of basic compounds. The range of materials comes about through architecture, giving functional structure to the basic materials. Analogously, a new genre of actuators can be derived from existing smart materials through architecture. This paper presents a preliminary experimental study of knitted actuation architectures that yield high strains (up to 73%) with moderate forces (tens of Newtons or more) from basic contracting smart material fibers. By different combinations of the two primary knit loops – purl and knit – a variety of behaviors can be achieved including contraction, rolling, spirals, accordions, arching, and any combination of these across the fabric. This paper catalogs several basic knit stitches and their actuated form: garter, stockinette, seed, rib and I-cord. These knitted architectures provide performance tailorability (force, strain, stiffness, and motion) by manipulation of key design parameters such as the material properties of the wire, the geometric parameters (wire diameter, loop size, and gauge), and architectural parameters (stitch type and orientation). This is demonstrated via a quasi-static force-deflection experimental study with several shape memory alloy garter prototypes with varying geometric parameters. While the basic architecture of a knit is simple, it affords a vast array of architectural combinations and control of geometrical and material parameters that generate a myriad of gross motion capabilities beyond that of current day actuation strategies.

Die Molekülstruktur des N-Chlorsdiwefeloxiddifluoridimids ClNSOF2 / The Molecular Structure of ClNSOF2

1974 ◽  
Vol 29 (6) ◽  
pp. 901-904 ◽  
Author(s):  
O. Oberhammer ◽  
O. Glemser ◽  
H. Klüver
Keyword(s):  
Molecular Structure ◽  
Electron Diffraction ◽  
Geometric Parameters ◽  
Mean Square ◽  
The Mean

The molecular structure of ClNSOF2 was determined by electron diffraction of gases. The following geometric parameters were obtained:Cl-N=1.715(5), S=N=1.484(7), S=O=1.394(3), S-F=1.548(3) Å, ∢ ClNS=114.7 (8), ∢ FSF=92.6(.8), ∢ NSF=111.8(.9) ∢ NSO=117.4 (3.1) and ∢ OSF=108.6 (.8)°. The results for the mean square amplitudes of vibration are given in the paper and an attempt is made to explain differences in corresponding parameters of some related molecules.

Direct Sensitivity Analysis of Multibody Systems: A Vehicle Dynamics Benchmark

2019 ◽  
Vol 14 (2) ◽  
Author(s):  
Alfonso Callejo ◽  
Daniel Dopico
Keyword(s):  
Sensitivity Analysis ◽  
Multibody Systems ◽  
Automatic Differentiation ◽  
Time Integration ◽  
General Purpose ◽  
Contact Forces ◽  
Design Parameters ◽  
Computational Techniques ◽  
Computationally Efficient ◽  
Integration Algorithm

Algorithms for the sensitivity analysis of multibody systems are quickly maturing as computational and software resources grow. Indeed, the area has made substantial progress since the first academic methods and examples were developed. Today, sensitivity analysis tools aimed at gradient-based design optimization are required to be as computationally efficient and scalable as possible. This paper presents extensive verification of one of the most popular sensitivity analysis techniques, namely the direct differentiation method (DDM). Usage of such method is recommended when the number of design parameters relative to the number of outputs is small and when the time integration algorithm is sensitive to accumulation errors. Verification is hereby accomplished through two radically different computational techniques, namely manual differentiation and automatic differentiation, which are used to compute the necessary partial derivatives. Experiments are conducted on an 18-degree-of-freedom, 366-dependent-coordinate bus model with realistic geometry and tire contact forces, which constitutes an unusually large system within general-purpose sensitivity analysis of multibody systems. The results are in good agreement; the manual technique provides shorter runtimes, whereas the automatic differentiation technique is easier to implement. The presented results highlight the potential of manual and automatic differentiation approaches within general-purpose simulation packages, and the importance of formulation benchmarking.

Design on Parameterized Drafting System of Centrifugal Fan

2010 ◽  
Vol 34-35 ◽  
pp. 192-196
Author(s):  
Jiang Zhu ◽  
Limin Chen ◽  
Ping Yuan Xi
Keyword(s):  
Aerodynamic Force ◽  
Geometric Parameters ◽  
Rapid Response ◽  
Design Parameters ◽  
Centrifugal Fan ◽  
Aerodynamic Design ◽  
Key Factors ◽  
Fan Speed ◽  
Force Calculation

The impeller is the important pneumatic part of centrifugal fan, and its structure performances are key factors which affect the whole performances of fan. The CAD module of centrifugal fan can realize the automation of aerodynamic force calculation. According to demands, computer can automatically complete aerodynamic force calculation and further determine major geometric parameters of impeller of fan. Speed coefficient and diametral quotient are two important parameters reflecting the character of ventilating fan. The relation curve between the speed coefficient and diametral quotient of various fans is plotted in this paper. The CAD module of impeller of centrifugal fan can realize such functions as aerodynamic design and parameterization drawing of impeller, and can accomplish rapid response from receiving design parameters to profiled impeller of fan, so that it can improve the quality of drawing.

scholarly journals Variability in Pavement Design

2015 ◽  
Vol 16 (2) ◽  
pp. 50-67 ◽  
Author(s):  
Paola Dalla Valle ◽  
Nick Thom
Keyword(s):  
Pavement Design ◽  
Pavement Performance ◽  
Design Parameters ◽  
Probability Density Distribution ◽  
Analysis And Design ◽  
The Subject ◽  
The Mean ◽  
Subgrade Modulus ◽  
Input Variables ◽  
The Uk

Abstract This paper presents the results of a review on variability of key pavement design input variables (asphalt modulus and thickness, subgrade modulus) and assesses effects on pavement performance (fatigue and deformation life). Variability is described by statistical terms such as mean and standard deviation and by its probability density distribution. The subject of reliability in pavement design has pushed many highway organisations around the world to review their design methodologies, mainly empirical, to move towards mechanistic-empirical analysis and design which provide the tools for the designer to evaluate the effect of variations in materials on pavement performance. This research has reinforced this need for understanding how the variability of design parameters affects the pavement performance. This study has only considered flexible pavements. The sites considered for the analysis, all in the UK (including Northern Ireland), were mainly motorways or major trunk roads. Pavement survey data analysed were for Lane 1, the most heavily trafficked lane. Sections 1km long were considered wherever possible. Statistical characterisation of the variation of layer thickness, asphalt stiffness and subgrade stiffness is addressed. A sensitivity analysis is then carried out to assess which parameter(s) have the greater influence on the pavement life. The research shows that, combining the effect of all the parameters considered, the maximum range of 15th and 85th percentiles (as percentages of the mean) was found to be 64% to 558% for the fatigue life and 94% to 808% for the deformation life.

An Optimum-Curved Die-Profile for Investment Casting of Turbo Blades

2011 ◽  
Vol 314-316 ◽  
pp. 630-633
Author(s):  
Yi Wei Dong ◽  
Ding Hua Zhang ◽  
Kun Bu ◽  
Yang Qing Dou
Keyword(s):  
Numerical Simulation ◽  
Investment Casting ◽  
Geometric Parameters ◽  
Iteration Algorithm ◽  
Inverse Iteration ◽  
Simulation Data ◽  
Parameterized Modeling ◽  
Dimension Precision ◽  
Die Profile ◽  
The Mean

In order to avoid tremendous modifications of the die cavity for investment casting of turbo blades, this paper proposed an inverse iterative compensation method that adjusts certain geometric parameters to establish the die-profile. The parameterized modeling is achieved by identifying geometric parameters describing the mean camber line; the optimum-curve die-profile can be obtained based on the inverse iteration algorithm. As a result, the dimension precision of turbo blades can be guaranteed. The applicability of this method is validated using numerical simulation data.

Development and validation of a novel quasi-dimensional combustion model for un-scavenged prechamber gas engines with numerical simulations and engine experiments

2020 ◽  
pp. 146808742095133 ◽  
Author(s):  
Konstantinos Bardis ◽  
Panagiotis Kyrtatos ◽  
Guoqing Xu ◽  
Christophe Barro ◽  
Yuri Martin Wright ◽  
...  
Keyword(s):  
Numerical Simulations ◽  
Three Dimensional ◽  
Operating Conditions ◽  
Design Parameters ◽  
Combustion Model ◽  
Experimental Investigations ◽  
Computationally Efficient ◽  
Lean Burn ◽  
Dimensional Models ◽  
Three Dimensional Models

Lean-burn gas engines equipped with an un-scavenged prechamber have proven to reduce nitrogen oxides (NOx) emissions and fuel consumption, while mitigating combustion cycle-to-cycle fluctuations and unburned hydrocarbon (UHC) emissions. However, the performance of a prechamber gas engine is largely dependent on the prechamber design, which has to be optimised for the particular main chamber geometry and the foreseen engine operating conditions. Optimisation of such complex engine components relies partly on computationally efficient simulation tools, such as quasi and zero-dimensional models, since extensive experimental investigations can be costly and time-consuming. This article presents a newly developed quasi-dimensional (Q-D) combustion model for un-scavenged prechamber gas engines, which is motivated by the need for reliable low order models to optimise the principle design parameters of the prechamber. Our fundamental aim is to enhance the predictability and robustness of the proposed model with the inclusion of the following: (i) Formal derivation of the combustion and flow submodels via reduction of the corresponding three-dimensional models. (ii) Individual validation of the various submodels. (iii) Combined use of numerical simulations and experiments for the model validation. The resulting model shows very good agreement with the numerical simulations and the experiments from two different engines with various prechamber geometries using a set of fixed calibration parameters.

An adaptive sparse polynomial-chaos technique based on anisotropic indices

2020 ◽  
Vol 39 (3) ◽  
pp. 691-707
Author(s):  
Christos Salis ◽  
Nikolaos V. Kantartzis ◽  
Theodoros Zygiridis
Keyword(s):  
Polynomial Chaos ◽  
Computational Cost ◽  
Uncertainty Assessment ◽  
Design Parameters ◽  
Test Problems ◽  
Content Type ◽  
Sparse Polynomial ◽  
Index Sets ◽  
The Mean ◽  
Expansion Coefficients

Purpose The fabrication of electromagnetic (EM) components may induce randomness in several design parameters. In such cases, an uncertainty assessment is of high importance, as simulating the performance of those devices via deterministic approaches may lead to a misinterpretation of the extracted outcomes. This paper aims to present a novel heuristic for the sparse representation of the polynomial chaos (PC) expansion of the output of interest, aiming at calculating the involved coefficients with a small computational cost. Design/methodology/approach This paper presents a novel heuristic that aims to develop a sparse PC technique based on anisotropic index sets. Specifically, this study’s approach generates those indices by using the mean elementary effect of each input. Accurate outcomes are extracted in low computational times, by constructing design of experiments (DoE) which satisfy the D-optimality criterion. Findings The method proposed in this study is tested on three test problems; the first one involves a transmission line that exhibits several random dielectrics, while the second and the third cases examine the effects of various random design parameters to the transmission coefficient of microwave filters. Comparisons with the Monte Carlo technique and other PC approaches prove that accurate outcomes are obtained in a smaller computational cost, thus the efficiency of the PC scheme is enhanced. Originality/value This paper introduces a new sparse PC technique based on anisotropic indices. The proposed method manages to accurately extract the expansion coefficients by locating D-optimal DoE.

ARMA Model for Turbine and Compressor Clearance Forecasting

2010 ◽  
Author(s):  
Huageng Luo ◽  
George Ghanime ◽  
Liping Wang
Keyword(s):  
Arma Model ◽  
Design Parameters ◽  
Computationally Efficient ◽  
Detailed Model ◽  
Reduced Order ◽  
Operational Conditions ◽  
Turbine Efficiency ◽  
Modeling And Prediction ◽  
Efficiency And Effectiveness ◽  
Arma Modeling

In turbo machinery, clearance (the distance between the turbine or compressor blade tip to the casing) at high-pressure stages is one of the key design parameters to measure the turbine efficiency and effectiveness. Thus, appropriate modeling and prediction of the clearance under operational conditions is very important. If the clearance can be actively controlled, the turbine manufacturers get even more competitive advantages. For turbine design purpose, detailed physics based model is usually available. However, this kind of detailed model is not suitable for on-line prediction due to heavy computational requirements. Instead, a reduced order model based on the first order physics is used. Usually, the available reduced order models are computationally efficient, but they can hardly reach the accuracy desired by control engineers. In this paper, we applied an ARMA modeling technique for the reduced order clearance modeling and prediction. Typical turbine cycle operation data were used to build the ARMA model first. The built model is then used to predict other operations of the same unit, as well as other units of the same family.

scholarly journals Possibilities of Using Kalman Filters in Indoor Localization

Mathematics ◽  
2020 ◽  
Vol 8 (9) ◽  
pp. 1564
Author(s):  
Katerina Fronckova ◽  
Pavel Prazak
Keyword(s):  
Object Tracking ◽  
Stochastic Models ◽  
Kalman Filters ◽  
Indoor Environment ◽  
Moving Objects ◽  
Indoor Localization ◽  
Low Energy ◽  
Localization Error ◽  
Energy Data ◽  
The Mean

Kalman filters are a set of algorithms based on the idea of a filter described by Rudolf Emil Kalman in 1960. Kalman filters are used in various application domains, including localization, object tracking, and navigation. The text provides an overview and discussion of the possibilities of using Kalman filters in indoor localization. The problems of static localization and localization of dynamically moving objects are investigated, and corresponding stochastic models are created. Three algorithms for static localization and one algorithm for dynamic localization are described and demonstrated. All algorithms are implemented in the MATLAB software, and then their performance is tested on Bluetooth Low Energy data from a real indoor environment. The results show that by using Kalman filters, the mean localization error of two meters can be achieved, which is one meter less than in the case of using the standard fingerprinting technique. In general, the presented principles of Kalman filters are applicable in connection with various technologies and data of various nature.

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