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

Purpose – Constant flow valves have been presented in industrial applications or academic studies, which compensate pressures of bearing recesses as load fluctuates. The flow rate of constant-flow valves (CFVs) can be constant in spite of the pressure changes in recesses. However, specific condition of design parameters must be satisfied. The paper aims to discuss these issues. Design/methodology/approach – This paper utilizes analytical method to study the static characteristics of CFVs, three types belong to traditional design of CFV are reviewed afresh. Moreover, an innovative design for constant flow is presented and studied. Findings – The review and study results reveal that appropriate relationships among design parameters for these types of CFVs. Originality/value – The numerical simulation is used to investigate the influence of design parameters on the change of flow rate when pressure ratio of recess is changed.

Investigations of constant-flow valves for hydrostatic bearings

The non-stationary signal features are averaged in correspondence with the length of analysis time, thus making it impossible to highlight the signal characteristics and caused the difficulties in identifying or diagnosing faults. In this paper, the wavelet order spectrum method using a combination of wavelet transform (WT) and speed frequency ordering. The feature order does not change with variations in speed, thus can effectively identify non-stationary faults in mechanical equipment. In addition, principal components analysis (PCA) is used to extract the main features of the wavelet order spectrum and reduce the volume of data. This is combined with self-organizing maps (SOM) to devise an artificial intelligence method for fault diagnosis in non-stationary states.

Machinery Fault Detection Using the Wavelet Order Spectrum

When influence coefficient (IC) method is used in rotor balancing, it is possible that serious errors could be resulted in unbalance determinations due to the contamination of measurements and IC matrix being ill-posed. In this study, the availability of least squares algorithm (LSA) and Tikhonov regularization (TR) is studied by error estimations of unbalance determination with considering measurement errors. Also, the influence of illness of the IC matrix equation on the change of balancing accuracy relative to the measurement error will be simulated. The finite element method is used to analyze unbalance responses of a rotor-bearing system and the analysis results of both TR and LSA are compared in case studies. Furthermore, the validations of both methods are realized by balancing experiments of a rotor kit.

Rotor Balancing with Considering Measurement Errors

This paper researches the influences of two recess geometry and restrictor dimensions on the flow patterns and pressure distribution of lubricant film, which are coupled effects of hybrid characteristics of a hydrostatic bearing, by using the numerical simulation method. Analyze the results to understand the characteristics and the reasons of flow patterns of recess and calculate the loading capacity. The research gets the design parameter of increasing the loading capacity.

Numerical Simulations via Navier-Stokes Equation for Estimating Effects of Recess Geometry, Restrictor Dimension and Surface Speed on Static Characteristics of Hybrid Bearing

Yuan Kang

Papers

Investigations of constant-flow valves for hydrostatic bearings

Machinery Fault Detection Using the Wavelet Order Spectrum

Rotor Balancing with Considering Measurement Errors

Numerical Simulations via Navier-Stokes Equation for Estimating Effects of Recess Geometry, Restrictor Dimension and Surface Speed on Static Characteristics of Hybrid Bearing

Influence of bearing damping on instability of asymmetric shafts, part IV: Effects of fluid-film bearings