Linear Acoustic Exhaust System Simulation Using Source Data from Non Linear Simulation

2005 ◽  
Author(s):  
Robert Fairbrother ◽  
Hans Bodén ◽  
Ragnar Glav
Keyword(s):  
System Simulation ◽  
Exhaust System ◽  
Source Data ◽  
Non Linear

scholarly journals Relationship between Age and Value of Information for a Noisy Ornstein–Uhlenbeck Process

Entropy ◽  
2021 ◽  
Vol 23 (8) ◽  
pp. 940
Author(s):  
Zijing Wang ◽  
Mihai-Alin Badiu ◽  
Justin P. Coon
Keyword(s):  
Value Of Information ◽  
Markov Models ◽  
Upper Bounds ◽  
Distribution Functions ◽  
Lower And Upper Bounds ◽  
Uhlenbeck Process ◽  
Source Data ◽  
Non Linear ◽  
Queue Model ◽  
Selection Of

The age of information (AoI) has been widely used to quantify the information freshness in real-time status update systems. As the AoI is independent of the inherent property of the source data and the context, we introduce a mutual information-based value of information (VoI) framework for hidden Markov models. In this paper, we investigate the VoI and its relationship to the AoI for a noisy Ornstein–Uhlenbeck (OU) process. We explore the effects of correlation and noise on their relationship, and find logarithmic, exponential and linear dependencies between the two in three different regimes. This gives the formal justification for the selection of non-linear AoI functions previously reported in other works. Moreover, we study the statistical properties of the VoI in the example of a queue model, deriving its distribution functions and moments. The lower and upper bounds of the average VoI are also analysed, which can be used for the design and optimisation of freshness-aware networks. Numerical results are presented and further show that, compared with the traditional linear age and some basic non-linear age functions, the proposed VoI framework is more general and suitable for various contexts.

Exhaust System Evaluation and Design by Non-Linear Modeling

1992 ◽  
Author(s):  
Steve M. Sapsford ◽  
Vanessa C.M. Richards ◽  
Duane R. Amlee ◽  
Tom Morel ◽  
Mary T. Chappell
Keyword(s):  
Exhaust System ◽  
System Evaluation ◽  
Linear Modeling ◽  
Non Linear

THE EFFECT OF GEOMETRY ON FATIGUE LIFE FOR BELLOWS

2012 ◽  
Vol 06 ◽  
pp. 343-348
Author(s):  
JINBONG KIM
Keyword(s):  
Fatigue Life ◽  
System Design ◽  
Design Process ◽  
Linear Method ◽  
Exhaust System ◽  
Shell Element ◽  
Expansion Joints ◽  
Component Design ◽  
Non Linear ◽  
The Impact

A bellows is a component installed in the automobile exhaust system to reduce or prevent the impact from engine. Generally, the specifications on the bellows are determined in the system design process of exhaust system and the component design is carried out to meet the specifications such as stiffness. Consideration of fatigue is generally an important aspect of design on metallic bellows expansion joints. These components are subject to displacement loading which frequently results in cyclic strains. This study has been investigated to analyze the effect of geometry on fatigue life for automotive bellows. 8 node shell element and non-linear method is employed for the analysis. The optimized shapes of the bellows are expected to give good guidelines to the practical designs.

Exhaust System Simulation of a 2-Cylinder 2-Stroke Engine Including Heat Transfer Effects

2010 ◽  
Author(s):  
Dalibor Jajcevic ◽  
Matthias Fitl ◽  
Stephan Schmidt ◽  
Karl Glinsner ◽  
Raimund Almbauer
Keyword(s):  
Heat Transfer ◽  
System Simulation ◽  
Exhaust System ◽  
Transfer Effects ◽  
Heat Transfer Effects ◽  
Stroke Engine

scholarly journals A Learning-Based Image Fusion for High-Resolution SAR and Panchromatic Imagery

2020 ◽  
Vol 10 (9) ◽  
pp. 3298
Author(s):  
Dae Kyo Seo ◽  
Yang Dam Eo
Keyword(s):  
Image Fusion ◽  
Spatial Information ◽  
Sufficient Information ◽  
Random Forest Regression ◽  
Complementary Method ◽  
Linear Relationships ◽  
Source Data ◽  
Non Linear ◽  
Fusion Methods ◽  
Imaging Mechanisms

Image fusion is an effective complementary method to obtain information from multi-source data. In particular, the fusion of synthetic aperture radar (SAR) and panchromatic images contributes to the better visual perception of objects and compensates for spatial information. However, conventional fusion methods fail to address the differences in imaging mechanism and, therefore, they cannot fully consider all information. Thus, this paper proposes a novel fusion method that both considers the differences in imaging mechanisms and sufficiently provides spatial information. The proposed method is learning-based; it first selects data to be used for learning. Then, to reduce the complexity, classification is performed on the stacked image, and the learning is performed independently for each class. Subsequently, to consider sufficient information, various features are extracted from the SAR image. Learning is performed based on the model’s ability to establish non-linear relationships, minimizing the differences in imaging mechanisms. It uses a representative non-linear regression model, random forest regression. Finally, the performance of the proposed method is evaluated by comparison with conventional methods. The experimental results show that the proposed method is superior in terms of visual and quantitative aspects, thus verifying its applicability.

The Application of Non-Linear Boundary Conditions to a Linearly Elastic Model to Achieve Multi-State Structural Behavior in a Large-Displacement Mechanical System Simulation

1999 ◽  
Author(s):  
James B. McConville
Keyword(s):  
Boundary Conditions ◽  
Mechanical System ◽  
System Simulation ◽  
Linear Structure ◽  
Nonlinear Boundary Conditions ◽  
System Structure ◽  
Elastic Behavior ◽  
Elastic Model ◽  
Linear Elastic ◽  
Non Linear

Abstract Structural elasticity is increasingly perceived as vital to the fidelity of Mechanical System Simulation (MSS) analyses of complex systems under-going large motion. The use of modal elastic system components subject to non-linear loading has become commonplace. An additional use of nonlinear boundary conditions is that of altering the linear elastic behavior of the system structure(s) to achieve multi-state elastic behavior from a single, linear structure. The method is used in this paper to simulate with ADAMS® the effect of an aircraft experiencing a partial structural failure as a result of a hard landing.

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