Introduction

2018 ◽  
Author(s):  
Marcel Escudier
Keyword(s):  
Fluid Flow ◽  
Engineering Design ◽  
Ocean Waves ◽  
Basic Design ◽  
Natural Phenomena ◽  
Turbofan Engine ◽  
Expansion Waves ◽  
Supersonic Aircraft ◽  
Bodily Fluids ◽  
Design Calculations

In this chapter the wide array of engineering devices, from the kitchen tap (a valve) to supersonic aircraft, the basic design of which depends upon considerations of the flow of gases and liquids, is shown. Much the same is true of most natural phenomena from the atmosphere and our weather to ocean waves, and the movement of sperm and other bodily fluids. In this textbook a number of the concepts, principles, and procedures which underlie the analysis of any problem involving fluid flow or a fluid at rest are introduced. In this Introduction, examples have been selected for which, by the end of the book, the student should be in a position to make practically useful engineering-design calculations. These include a dam, a rocket motor, a supersonic aerofoil with shock and expansion waves, a turbojet engine, a turbofan engine, and the blading of a gas turbine.

The Use of the Fluid Flow Program Phoenics in Engineering Design

1985 ◽  
pp. 915-927
Author(s):  
N. Rhodes ◽  
S. A. Al-Sanea ◽  
K. A. Pericleous
Keyword(s):  
Fluid Flow ◽  
Engineering Design

How Finite Element Calculations Improve Hyper Compressor Performance and Lifetime

2013 ◽  
Author(s):  
Nicole Retz ◽  
Andreas Allenspach
Keyword(s):  
Finite Element ◽  
Manufacturing Processes ◽  
Basic Design ◽  
Finite Element Calculations ◽  
Compressor Performance ◽  
Design Calculations

The basic design of actual hyper compressor was performed around 40 years ago, in a time when the use of computers was limited and most of the design calculations were made by hand. In our days most parts are significantly improved with the support of finite element calculations. In this paper the benefits of such an optimization will be highlighted by several examples like the compressor central valve, the flexible rod coupling or even the overall compressor vibrations. In addition the modeling of some for hyper compressors typical manufacturing processes like autofrettage will be discussed.

scholarly journals Research of a High Thrust-to-Weight Ratio Small Turbofan Engine

1997 ◽  
Author(s):  
Masahiro Akagi ◽  
Masashi Shinomiya ◽  
Junichi Sakaki ◽  
Shunji Sugai
Keyword(s):  
Research And Development ◽  
Weight Ratio ◽  
Development Program ◽  
Engine Test ◽  
Test Results ◽  
Design Development ◽  
Turbofan Engine ◽  
Technical Research ◽  
Supersonic Aircraft ◽  
High Thrust

The 3rd Research Center of the Technical Research and Development Institute (TRDI) of Japan Defense Agency (JDA) and Ishikawajima-Harima Heavy Industries Co., Ltd. (IHI) developed and tested the demonstrator of a high thrust-to-weight ratio small turbofan engine with an afterburner called “XF3-400”, the purpose of which is to establish engine technologies for the future supersonic aircraft for JDA. The development program started in 1981 and the first engine test was carried out in 1992. All the engine tests planned completed in March 1995 successfully. This paper reports the design, development and test results of the XF3-400 engine above.

Sir George Gabriel Stokes in Skreen: how a childhood by the sea influenced a giant in fluid dynamics

2020 ◽  
Vol 378 (2174) ◽  
pp. 20190516
Author(s):  
Aoife Kearins
Keyword(s):  
Fluid Dynamics ◽  
Atlantic Ocean ◽  
Rural Area ◽  
Ocean Waves ◽  
Natural Phenomena ◽  
Theme Issue ◽  
University Of Cambridge ◽  
The University

George Gabriel Stokes spent most of his life at the University of Cambridge, where he undertook his undergraduate degree and later became Lucasian Professor of Mathematics and Master of Pembroke College. However, he spent the first 13 years of his life in Skreen, County Sligo, Ireland, a rural area right by the coastline, overlooking the Atlantic Ocean. As this paper will discuss, the time he spent there was short but its influence on him and his research was long reaching, with his childhood activities of walking by and bathing in the sea being credited for first piquing Stokes' interest in ocean waves, which he would go on to write papers about. More generally, it marked the beginning of an interest in fluid dynamics and a curious nature regarding natural phenomena in his surroundings. Stokes held a special affinity for the ocean for the rest of his life, constantly drawing inspiration for it in his mathematical and physical studies and referencing it in his correspondences. This commentary was written to celebrate Stokes' 200th birthday as part of the theme issue of Philosophical Transactions A . This article is part of the theme issue ‘Stokes at 200 (Part 1)’.

Using Physics-Informed Generative Adversarial Networks to Perform Super-Resolution for Multiphase Fluid Simulations

2021 ◽  
Author(s):  
Matthew Li ◽  
Christopher McComb
Keyword(s):  
Machine Learning ◽  
Fluid Flow ◽  
Engineering Design ◽  
Computational Cost ◽  
Super Resolution ◽  
Generative Adversarial Networks ◽  
Generative Adversarial Network ◽  
Turbulent Fluid Flow ◽  
Turbulent Fluid ◽  
Multiphase Fluid

Abstract Computational Fluid Dynamics (CFD) simulations are useful to the field of engineering design as they provide deep insights on product or system performance without the need to construct and test physical prototypes. However, they can be very computationally intensive to run. Machine learning methods have been shown to reconstruct high-resolution single-phase turbulent fluid flow simulations from low-resolution inputs. This offers a potential avenue towards alleviating computational cost in iterative engineering design applications. However, little work thus far has explored the application of machine learning image super-resolution methods to multiphase fluid flow (which is important for important for emerging fields such as marine hydrokinetic energy conversion). In this work, we apply a modified version of the Super-Resolution Generative Adversarial Network (SRGAN) model to a multiphase turbulent fluid flow problem, specifically to reconstruct fluid phase fraction at a higher resolution. Two models were created in this work, one with a simple physics-constrained loss function and one without, and the results are discussed and analyzed. We found that both models were able to significantly outperform non-machine learning upsampling methods and can preserve an impressive amount of detail and nuance, showing the versatility of the SRGAN model for upsampling fluid simulations. However, the difference in accuracy between the two models is quite minimal. This indicates that, for these contexts studied here, the additional complexity of a physics-informed approach may not be justified.

An Analytical Model for the Basic Design Calculations of Journal Bearings

2010 ◽  
Vol 132 (2) ◽  
Author(s):  
R. K. Naffin ◽  
L. Chang
Keyword(s):  
Analytical Model ◽  
Numerical Solutions ◽  
Journal Bearings ◽  
Basic Design ◽  
Reasonable Accuracy ◽  
Design Calculations

This paper presents an analytical model for the basic design calculations of plain journal bearings. The model yields reasonable accuracy as compared with published numerical solutions under the same conditions. The principles and procedures of the formulations are presented along with accuracy analyses.

Basic design guideline for the preliminary engineering design of PIE facilities in IFMIF/EVEDA

2011 ◽  
Vol 86 (12) ◽  
pp. 2904-2907 ◽  
Author(s):  
Takafumi Kogawara ◽  
Eiichi Wakai ◽  
Takayuki Kikuchi ◽  
Michiyoshi Yamamoto ◽  
Joaquin Molla
Keyword(s):  
Engineering Design ◽  
Basic Design ◽  
Design Guideline

Engineering design calculations with fuzzy parameters

1992 ◽  
Vol 52 (1) ◽  
pp. 1-20 ◽  
Author(s):  
Kristin L. Wood ◽  
Kevin N. Otto ◽  
Erik K. Antonsson
Keyword(s):  
Engineering Design ◽  
Design Calculations ◽  
Fuzzy Parameters

Comparing Fuzzy and Probability Calculus for Representing Imprecision in Preliminary Engineering Design

1989 ◽  
Author(s):  
K. L. Wood ◽  
E. K. Antonsson ◽  
J. L. Beck
Keyword(s):  
Fuzzy Sets ◽  
Engineering Design ◽  
Stochastic Uncertainty ◽  
Probability Calculus ◽  
Fuzzy Calculus ◽  
Design Calculations

Abstract A technique to perform design calculations on imprecise representations of parameters using the calculus of fuzzy sets has been previously developed [17]. An analogous approach to representing and manipulating uncertainty in choosing among alternatives (imprecision) using probability calculus is presented and compared with the fuzzy calculus technique. We find that the fuzzy calculus is well suited to representing and manipulating the imprecision aspect of uncertainty, and probability is best used to represent stochastic uncertainty.

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