Nanofluids, the fluid suspensions of nanomaterials, have shown many interesting properties, and the distinctive features offer unprecedented potential for many applications. This paper summarizes the recent progress on the study of nanofluids, such as the preparation methods, the evaluation methods for the stability of nanofluids, and the ways to enhance the stability for nanofluids, the stability mechanisms of nanofluids, and presents the broad range of current and future applications in various fields including energy and mechanical and biomedical fields. At last, the paper identifies the opportunities for future research.

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A review on nanofluids: preparation, stability mechanisms, and applications

The special mechanical properties of nanoparticles allow for novel applications in many fields, e.g., surface engineering, tribology and nanomanufacturing/nanofabrication. In this review, the basic physics of the relevant interfacial forces to nanoparticles and the main measuring techniques are briefly introduced first. Then, the theories and important results of the mechanical properties between nanoparticles or the nanoparticles acting on a surface, e.g., hardness, elastic modulus, adhesion and friction, as well as movement laws are surveyed. Afterwards, several of the main applications of nanoparticles as a result of their special mechanical properties, including lubricant additives, nanoparticles in nanomanufacturing and nanoparticle reinforced composite coating, are introduced. A brief summary and the future outlook are also given in the final part. (Some figures may appear in colour only in the online journal)

https://iopscience.iop.org/article/10.1088/0022-3727/47/1/013001/pdf

Mechanical properties of nanoparticles: basics and applications

This book equips the reader to understand every important aspect of the dynamics of rotating machines. Will the vibration be large? What influences machine stability? How can the vibration be reduced? Which sorts of rotor vibration are the worst? The book develops this understanding initially using extremely simple models for each phenomenon, in which (at most) four equations capture the behavior. More detailed models are then developed based on finite element analysis, to enable the accurate simulation of the relevant phenomena for real machines. Analysis software (in MATLAB) is associated with this book, and novices to rotordynamics can expect to make good predictions of critical speeds and rotating mode shapes within days. The book is structured more as a learning guide than as a reference tome and provides readers with more than 100 worked examples and more than 100 problems and solutions.

/pdf/dynamics-of-rotating-machines-499re2kizd.pdf

Dynamics of rotating machines

The prediction of chaotic time series with neural networks is a traditional practical problem of dynamic systems. This paper is not intended for proposing a new model or a new methodology, but to study carefully and thoroughly several aspects of a model on which there are no enough communicated experimental data, as well as to derive conclusions that would be of interest. The recurrent neural networks (RNN) models are not only important for the forecasting of time series but also generally for the control of the dynamical system. A RNN with a sufficiently large number of neurons is a nonlinear autoregressive and moving average (NARMA) model, with "moving average" referring to the inputs. The prediction can be assimilated to identification of dynamic process. An architectural approach of RNN with embedded memory, "Nonlinear Autoregressive model process with eXogenous input" (NARX), showing promising qualities for dynamic system applications, is analyzed in this paper. The performances of the NARX model are verified for several types of chaotic or fractal time series applied as input for neural network, in relation with the number of neurons, the training algorithms and the dimensions of his embedded memory. In addition, this work has attempted to identify a way to use the classic statistical methodologies (R/S Rescaled Range analysis and Hurst exponent) to obtain new methods of improving the process efficiency of the prediction chaotic time series with NARX.

/pdf/the-use-of-narx-neural-networks-to-predict-chaotic-time-31hso0ise7.pdf

The use of NARX neural networks to predict chaotic time series

A necessary condition for double scroll attractor existence in fractional-order systems

Instability analysis of unsymmetrical rotor-bearing systems using the transfer matrix method

Fault detection in gear train system is important in order to transmitting power effectively The artificial intelligent such as neural network is widely used in fault diagnosis and substituted for traditional methods In rotary machinery, the symptoms of vibration signals in frequency domain have been used as inputs to the neural network and diagnosis results are obtained by network computation However, in gear or rolling bearing system, it is difficult to extract the symptoms from vibration signals in frequency domain which have shock vibration signals The diagnosis results are not satisfied by using artificial neural network, if the training samples are not enough The Bayesian networks (BN) is an effective method for uncertain knowledge and less information in faults diagnosis In order to classify the instantaneous shock of vibration signals in gear train system, the statistical parameters of vibration signals in time-domain are used in this study These statistical parameters include kurtosis, crest, skewness factors etc There, based on the statistical parameters of vibration signals in time-domain, the fault diagnosis is implemented by using BN and compared with two methods back-propagation neural network (BPNN) and probabilistic neural network (PNN) in gear train system

Gear Fault Diagnosis in Time Domains by Using Bayesian Networks

Purpose – This paper is the third part of a serial studies for constant and variable compensations of the closed-type hydrostatic thrust bearings which has face-to-face recesses couple. The static stiffness of closed-type hydrostatic thrust bearings can then be obtained from the differentiation of recess pressure with respect to worktable displacement. The paper aims to discuss these issues. Design/methodology/approach – In this paper, the double-action restrictors of cylindrical-spool-type and tapered-spool-type are taken into consideration for variable compensation of hydrostatic bearings. Findings – The static stiffness in thrust direction of hydrostatic bearing is determined by the flow continuity equations that are formulated by film flow and compensation flow for each recess, respectively. The type selection and parameter determination of the double-action spool-type restrictors can be obtained from finding results of this study for maximum stiffness in design of hydrostatic bearings. Originality/va...

Design for static stiffness of hydrostatic bearings: double-action variable compensation of spool-type restrictors

Influence of bearing damping on instability of asymmetric shafts—Part I. Stabilizing and destabilizing effects

Purpose – This paper seeks to modify the determinations of flow rate and fluid resistance, which can be realized and confident from the measurements of flow rates in experiments.Design/methodology/approach – According to coupled physics of solid membrane and lubrication fluid, finite element method is used simultaneously to determine membrane deflection and film thickness. Several cases are simulated by traditional method, finite element method and compared with experimental method for the flow rates and fluid resistances to present the modification of determination results.Findings – The FEM results for the fixed eight‐section are approximated to actual flow rate and are consistent with the modified determination of the flow rates, and so the modified determinations of the flow rates are verified. When a computer of P4 with 1.8 GHz CPU and 512 MB RAM is utilized, time needed for traditional method or modified formula is fewer than one second. However, more than 4 h is required for FEM by using the same c...

Yuan Kang

Papers

Instability analysis of unsymmetrical rotor-bearing systems using the transfer matrix method

Gear Fault Diagnosis in Time Domains by Using Bayesian Networks

Design for static stiffness of hydrostatic bearings: double-action variable compensation of spool-type restrictors

Influence of bearing damping on instability of asymmetric shafts—Part I. Stabilizing and destabilizing effects

Modified determination of fluid resistance for membrane‐type restrictors