Hasil untuk "Mechanics of engineering. Applied mechanics"

S. Pope

It was a pleasure to read this important book. To understand and predict the development of turbulent flows represents both a continuing scientific challenge and also a serious practical problem in many different fields. Professor Pope has based his book on graduate level lecture courses on turbulence that he has presented at MIT and at Cornell University. It is intended for students in engineering, applied mathematics, oceanography and atmospheric sciences, as well as researchers and practising engineers. The emphasis is on turbulent flows, rather than on the theory of homogeneous turbulence, and only constant-density, nonreacting flows are considered. The author states that his aim is to explain concepts and develop the necessary mathematical tools, rather than to provide a practical guide to turbulence modelling. The text is divided into two parts. Part I provides an introduction to turbulent flows and the fundamental physical processes involved. Topics discussed in separate chapters include: the equations of fluid motion, the statistical description of turbulent flows, the mean flow equations, free shear flows, scales of turbulent motion and wall flows. The chapter on statistical methods for turbulence is particularly good; together with the related appendices it represents a valuable and accessible introduction to the subject. Several approaches for modelling or simulating turbulent flows are then described in Part II, in which the various chapters describe direct numerical simulation (DNS), turbulent viscosity models such as the k-ε model, Reynolds stress and related second-moment models, probability density function (pdf) models and large-eddy simulation (LES) techniques. Finally, some necessary mathematical tools are summarized in ten Appendices dealing with a wide range of relevant topics including tensors, Dirac delta functions, Fourier transforms, random processes, derivation of pdf equations, characteristic functions and stochastic descriptions of diffusion processes. I particularly enjoyed the chapters on modelling and simulation of turbulent flows. A unified treatment of the different types of model has enabled the author to make valuable connections between them and to reach clear and logical conclusions about the strengths and weaknesses of each approach. Over many years Professor Pope has made very important contributions to the development and application of pdf methods for the prediction of nonreactive and also reactive turbulent flows. The chapter on this subject is an exceptionally clear description of these powerful and often under-utilized simulation methods. The final chapter, on LES, provides an excellent introduction, with valuable and novel insights into both the promise and the problems of this relatively new and rapidly developing approach. It should be compulsory reading for many LES practitioners. Each section of the book contains a number of exercises, which typically invite the reader either to derive an expression that is quoted in the text or to generalize an analysis set out in the text. These exercises are often divided into several stages, and contain appropriate instructions, so that a diligent student will find his or her way through them. An advantage of the extensive use of appendices and student exercises is that analytical clarity and physical understanding are not obscured by unnecessary algebraic detail or by the need to review basic mathematical tools. The result is an exceptionally clear presentation, together with an often penetrating critique of both classical methods and recent developments in the theory and modelling of turbulent flows. There is excellent cross-referencing between one section and another, and an extensive and up-to-date bibliography. I strongly recommend this book to advanced students of fluid mechanics, to their teachers and to all researchers, engineers and others with a professional interest in turbulent flows. K N C Bray

G. Molenberghs

A. Marowka

M. Sacks, R. Gleason

We are pleased to publish the second in a series of special ssues published in the Journal of Biomechanical Engineering that ocus in high-impact areas. The current issue grew out of a Symosium on the Mechanics of Growth and Remodeling in Native nd Engineered Tissues, which took place at the 2008 Summer ioengineering Conference, Marco Island, FL, June 25–29, 2008. The underlying impetus for this symposium was that, despite its arly success, tissue engineers have faced challenges in repairing r replacing tissues that serve a predominantly biomechanical unction. An evolving discipline called “functional tissue engieering” seeks to address these challenges. The principles of funcional tissue engineering address biomechanical considerations of issue engineering approaches to repair and replacements for loadearing structures. The long term in vivo fate of any engineered issue is currently unknown. Clearly, a complete understanding of he in vivo remodeling process requires multi-length scale aproaches. Further, the degree of cellular function and similarity to he native tissue has yet to be determined. The focus of this issue as thus to explore how state-of-the-art work in the Mechanics of rowth and Remodeling in native tissues can be applied to the evelopment of Engineered Tissues. Topics included in this special issue include the latest theoretial concepts and experimental applications to explore how these oncepts can be applied to native and engineered tissue developent, including

L. Pawłowski

Kai Guo, Zhenze Yang, Chi-Hua Yu et al.

Artificial intelligence, especially machine learning (ML) and deep learning (DL) algorithms, is becoming an important tool in the fields of materials and mechanical engineering, attributed to its power to predict materials properties, design de novo materials and discover new mechanisms beyond intuitions. As the structural complexity of novel materials soars, the material design problem to optimize mechanical behaviors can involve massive design spaces that are intractable for conventional methods. Addressing this challenge, ML models trained from large material datasets that relate structure, properties and function at multiple hierarchical levels have offered new avenues for fast exploration of the design spaces. The performance of a ML-based materials design approach relies on the collection or generation of a large dataset that is properly preprocessed using the domain knowledge of materials science underlying chemical and physical concepts, and a suitable selection of the applied ML model. Recent breakthroughs in ML techniques have created vast opportunities for not only overcoming long-standing mechanics problems but also for developing unprecedented materials design strategies. In this review, we first present a brief introduction of state-of-the-art ML models, algorithms and structures. Then, we discuss the importance of data collection, generation and preprocessing. The applications in mechanical property prediction, materials design and computational methods using ML-based approaches are summarized, followed by perspectives on opportunities and open challenges in this emerging and exciting field.

Thomas Benz, S. Nordal

I. Kovacic, R. Rand, S. Sah

Azam Ahmad Bakir, Mohd Jamil Mohamed Mokhtarudin, Nasrul Hadi Johari

Aneurysms are vascular diseases with a low survival rate. Studying blood flow characteristics is essential to understand the disease, which would require experimentation on an anatomical phantom structure for simulating and measuring blood flow under controlled conditions. Conventional phantom fabrication often relies on single-use moulds, which are economically ineffective and time-consuming especially when replication is needed. In this study, we developed a method for fabricating an aneurysmal vascular phantom using a 3D-printed semi-reusable mould. The novelty lies in the reusable outer mould cope that was 3D-printed using polylactic acid (PLA), while the inner core was 3D-printed using water-soluble polyvinyl alcohol (PVA). A silicone-based elastomer, Sylgard 184 was used to create the vascular phantom because it approximates the mechanical properties of actual blood vessels. The silicone was injected onto the mould and the PVA core was dissolved in hot water to create a hollow structure. The resulting phantom is elastic and translucent, suitable for macro-scale flow visualization. It is also fabricated at a lower cost than those reported in previous studies. The semi-reusable mould concept enhances scalability by being low-cost and enables repeatable phantom production, offering an efficient way for research, training, and medical device testing.

Shavindra Wickramathilaka, John Grundy, Kashumi Madampe et al.

The use of diverse mobile applications among senior users is becoming increasingly widespread. However, many of these apps contain accessibility problems that result in negative user experiences for seniors. A key reason is that software practitioners often lack the time or resources to address the broad spectrum of age-related accessibility and personalisation needs. As current developer tools and practices encourage one-size-fits-all interfaces with limited potential to address the diversity of senior needs, there is a growing demand for approaches that support the systematic creation of adaptive, accessible app experiences. To this end, we present AdaptForge, a novel model-driven engineering (MDE) approach that enables advanced design-time adaptations of mobile application interfaces and behaviours tailored to the accessibility needs of senior users. AdaptForge uses two domain-specific languages (DSLs) to address age-related accessibility needs. The first model defines users' context-of-use parameters, while the second defines conditional accessibility scenarios and corresponding UI adaptation rules. These rules are interpreted by an MDE workflow to transform an app's original source code into personalised instances. We also report evaluations with professional software developers and senior end-users, demonstrating the feasibility and practical utility of AdaptForge.

J. Ajayi, E. Adetiba, A. Ifijeh et al.

Abstract A drastic decline in the number of students that are enrolled for Engineering is now being experienced in developed as well as developing countries. Learning is becoming boring as a generation brought up on technology is losing the ability to pay attention in traditional classes for a long stretch of time. This has led to the idea that other teaching methods do exist and can be applied in teaching/learning. This work leveraged the use of Digital Game-Based Learning (DGBL) in Engineering classrooms to develop a serious game named LogicHouse Version 1 (LogicHouse-V1 or LogicHouse for short). The game, is a web-based serious game prototype that targets selected topics in Digital Electronics course. This course is a core component of undergraduate curriculum in Electrical & Electronics Engineering, Computer Engineering, Information Technology, Communication Engineering, Computer Science and other related Science Technology Engineering and Mathematics (STEM) courses. LogicHouse involves a virtual broken house where the player has to play the various levels to fix the house and gain points along the way. This game was designed based on the Learning Mechanics-Game Mechanics (LM-GM) model and the Unified Modeling Language (UML). Furthermore, the design was implemented using Adobe Illustrator, Procreate, Unity Engine, C#, Microsoft Azure Playfab and deployed on itch.io. Preliminary evaluation results indicate that students are interested in the game and its application. Based on this, there is a prospect of improved performance in any course in which the game is implemented.

Dominique Levesque, Nicolas Sourlas

One of the important questions in statistical mechanics is how irreversibility (time's arrow) occurs when Newton equations of motion are time reversal invariant. One objection to irreversibility is based on Poincaré's recursion theorem: a classical hamiltonian confined system returns after some time, so-called Poincaré recurrence time (PRT), close to its initial configuration. Boltzmann's reply was that for a $N \sim 10^{23} $ macroscopic number of particles, PRT is very large and exceeds the age of the universe. In this paper we compute for the first time, using molecular dynamics, a typical recurrence time $ T(N)$ for a realistic case of a gas of $N$ particles. We find that $T(N) \sim N^z \exp (y N) $ and determine the exponents $y$ and $z$ for different values of the particle density and temperature. We also compute $y$ analytically using Boltzmann's hypotheses. We find an excellent agreement with the numerical results. This agreement validates Boltzmann's hypotheses which are not yet mathematically proven. We establish that that $T(N) $ exceeds the age of the Universe for a relatively small number of particles, much smaller than $ 10^{23} $.

Shuang Dang, J. Bi, Yu Zhao et al.

Yvonne Frühling, Timo Claßen, Mohammad Mobarak et al.

In the presented research, the use and technical realization of CO2 gas hydrate (GH) as a novel baking agent is investigated. GH are ice-like structures where one mole of hydrate typically consists of about 85% water and 15% gas. Hydrates were formed in a lab-scale 1.1 L stirred tank reactor at 1-2 °C and 3.5 MPa, and transferred into a temperature-controlled, gas-tight measuring cell. The leavening effect of gas hydrates was assessed by measuring the CO2 release rates. Storage stability at -20 to 0 °C and stability above 0 °C were investigated experimentally and a coupled thermodynamic and kinetic decay model implemented. At -10 °C, gas release was highest in the first minutes and stopped completely after 5 days. After 21 days storage at -10 °C, the GH still contained 20 % of the initial gas content. Above 0 °C, dissociation rates were highly temperature dependent, and half value times ranged from 30 min (3 °C) to 4 min (20 - 30 °C). Above 10 °C, ambient temperature had only a minor effect on the dissociation rates. Results from the kinetic decay model, applied for a 21 mm particle, showed similar dissociation behavior as a particle from experiments. Applying the model for a 3 mm particle, showed full dissociation after approximately 15 min. Stability and baking tests showed that CO2 hydrate is in principle suitable as a leavening agent. However, GH production still needs to be optimized and recipes for GH application require further development.

Kelsey M. Kennedy, A. Bhaw‐Luximon, D. Jhurry

Sreenivasulu Sunkara, M. Sreenivasa Reddy

Gold is one of the valuable metals and an important asset class for investors. People in India are emotionally attached to gold. Thousands of tonnes of idle gold are lying with Indian temples, trusts, and individuals. Investors consider capital appreciation; interest income and safety are major factors that influence buying of gold [1][4][7]. India is one of the biggest importers of gold every year. The government of India has introduced a few gold-related schemes to reduce gold imports. Sovereign gold bond [2] scheme and Re-vamped gold deposit scheme are introduced in the year 2015 under the Swarna Bharath initiative [9]. The present study is an attempt to find the association between awareness of investors and demographic factors towards gold ETFs, gold bonds, and gold deposits. The results reveal that there is a significant association at a 5% significance level between awareness of investors and all demographic factors used in the study except the gender of the respondent.

Sága Milan, Vaško Milan, Ságová Zuzanka et al.

The paper deals with implementation of the optimizing process into multi-axial rainflow analysis and cumulative damage calculation. It’s presented computational program FEA_FAT compiled in MATLAB. Stress analysis is realized by finite element procedure and the cumulative damage can be calculated by using two fundamental ways – critical plane approach and so called integral approach. Testing example presents random stress analysis and damage prediction of a simple FE model with non-proportional loading.

C. Mallor, S. Calvo, J.L. N��ez et al.

Different options that rely on fracture mechanics are currently used in engineering during the design and assessment of components. One of the most important aspects is the time taken for a crack to extend to its critical size. If this time is known and it is sufficiently large, a design concept based on inspection intervals can be applied in a viable way, as is it the case of a railway axle component. To define inspection intervals that ensure the continuous and safe operation of a damage-tolerant railway axle, a reliable estimation of its fatigue crack growth life is required. Due to the uncertainties involved in the fatigue process, inspections must be devised not only considering the uncertainties in the performance of the inspection technique, but also based on a probabilistic lifespan prediction. From this premise, this paper presents a procedure for determination of inspection intervals that uses a conservative fatigue crack growth life estimation based on the lifespan probability distribution. A practical example to illustrate the reliability-based inspection planning methodology in a railway axle under random bending loading is given. The inspection intervals are further assessed in terms of overall probability of detecting cracks in successive inspections and in terms of probability of failure, considering the probability of detection curve of the non-destructive testing technique. The procedure developed provides recommendation for the definition of inspection intervals and associated inspection techniques.

Qiao Huang, Jean-Claude Zambrini

We are describing relations between Schrödinger's variational problem and Onsager's approach to nonequilibrium statistical mechanics. Although the second work on reciprocal relations and detailed balance has been published in the same year (1931) as the first one, the impact of Schrödinger's idea has not yet been considered in the classical context of Onsager.