Ronald Sabo^1*, Aleksey Yermakov², Chiu Tai Law³, Rani Elhajjar⁴

Journal of Renewable Materials, Vol.4, No.5, pp. 297-312, 2016, DOI:10.7569/JRM.2016.634114

Abstract Cellulose nanomaterials have a number of interesting and unique properties that make them well-suited for use in electronics applications such as energy harvesting devices, actuators and sensors. Cellulose nanofibrils and nanocrystals have good mechanical properties, high transparency, and low coefficient of thermal expansion, among other properties that facilitate both active and inactive roles in electronics and related devices. For example, these nanomaterials have been demonstrated to operate as substrates for flexible electronics and displays, to improve the efficiency of photovoltaics, to work as a component of magnetostrictive composites and to act as a suitable lithium ion battery separator membrane. A… More >

Vinay Shimpi¹, Madappa V. R. Sivasubramanian^1,*, S. B. Singh²

Structural Durability & Health Monitoring, Vol.13, No.1, pp. 1-40, 2019, DOI:10.32604/sdhm.2019.05951

Abstract In this review article, the past investigations carried out on heritage structures using Ambient Vibration Test (AVT) and Operational Modal Analysis (OMA) for system identification (determination of dynamic properties like frequency, mode shape and damping ratios) and associated applications are summarized. A total of 68 major research studies on heritage structures around the world that are available in literature are surveyed for this purpose. At first, field investigations carried out on heritage structures prior to conducting AVT are explained in detail. Next, specifications of accelerometers, location of accelerometers and optimization of accelerometer networks have been elaborated with respect to the… More >

Mengyue He¹, Zhifang Zhang^1,*, Karthik Ram Ramakrishnan²

Structural Durability & Health Monitoring, Vol.12, No.4, pp. 213-256, 2018, DOI:10.32604/sdhm.2018.05122

Abstract Fibre reinforced polymer (FRP) composite laminates are now commonly used in many structural applications, especially in the aerospace industry, where margins of safety are kept low in order to minimise weight. Timely detection and assessment of damage (in particular delaminations) in composite laminates are therefore critical, as they can cause loss of structural integrity affecting the safe operation of the composite structures. The current trend is towards implementation of structural health monitoring (SHM) systems which can monitor the structures in situ without down time. In this paper, first, the current available SHM techniques for delamination detection in FRP composites are… More >

Kong Fah Tee ^1,*

Structural Durability & Health Monitoring, Vol.12, No.3, pp. 129-147, 2018, DOI: 10.3970/sdhm.2018.04316

Abstract Structural health monitoring (SHM) is a vast, interdisciplinary research field whose literature spans several decades with focusing on condition assessment of different types of structures including aerospace, mechanical and civil structures. The need for quantitative global damage detection methods that can be applied to complex structures has led to vibration-based inspection. Statistical time series methods for SHM form an important and rapidly evolving category within the broader vibration-based methods. In the literature on the structural damage detection, many time series-based methods have been proposed. When a considered time series model approximates the vibration response of a structure and model coefficients… More >

Roshan Kumar^1,*, Wei Zhao¹, Vikash Singh²

Structural Durability & Health Monitoring, Vol.12, No.2, pp. 65-83, 2018, DOI: 10.3970/sdhm.2018.02329

Abstract This paper presents an evaluation of time-frequency methods for the analysis of seismic signals. Background of the present work is to describe, how the frequency content of the signal is changing in time. The theoretical basis of short time Fourier transform, Gabor transform, wavelet transform, S-transform, Wigner distribution, Wigner-Ville distribution, Pseudo Wigner-Ville distribution, Smoothed Pseudo Wigner-Ville distribution, Choi-William distribution, Born-Jordan Distribution and cone shape distribution are presented. The strengths and weaknesses of each technique are verified by applying them to a particular synthetic seismic signal and recorded real time earthquake data. More >

A. Kroworz¹, A. Katunin^1,*

Structural Durability & Health Monitoring, Vol.12, No.1, pp. 1-18, 2018, DOI:10.3970/sdhm.2018.012.001

Abstract Non-destructive testing (NDT) of structures is one of the most important tasks of the proper maintenance and diagnosis of machines and constructions structural condition. NDT methods contribute to the damage tolerance philosophy used in the aircraft design methodology as well as many other operation and maintenance programs of machinery and constructions. The following study is focusing on overviewing an important group of NDT methods: the optical and other ones, which found broad applicability in scientific and industrial studies nowadays. The paper discusses the selected most widely applicable methods, namely, visual testing, ultrasonic testing, radiographic testing, infrared thermography as well as… More >

Alamelu Manghai T.M.¹, Jegadeeshwaran R², Sugumaran V.³

Structural Durability & Health Monitoring, Vol.11, No.1, pp. 43-67, 2017, DOI:10.3970/sdhm.2017.012.043

Abstract Diagnosis is the recognition of the nature and cause of a certain phenomenon. It is generally used to determine cause and effect of a problem. Machine fault diagnosis is a field of finding faults arising in machines. To identify the most probable faults leading to failure, many methods are used for data collection, including vibration monitoring, thermal imaging, oil particle analysis, etc. Then these data are processed using methods like spectral analysis, wavelet analysis, wavelet transform, short-term Fourier transform, high-resolution spectral analysis, waveform analysis, etc., The results of this analysis are used in a root cause failure analysis in order… More >

Tong Li^∗, Prasad KDV Yarlagadda^∗, Adekunle Oloyede^∗, Namal Thibbotuwawa^∗, YuanTong Gu^∗,†

Molecular & Cellular Biomechanics, Vol.12, No.1, pp. 17-35, 2015, DOI:10.3970/mcb.2015.012.017

Abstract Living cells are the functional unit of organs that controls reactions to their exterior. However, the mechanics of living cells can be difficult to characterize due to the crypticity of their microscale structures and associated dynamic cellular processes. Fortunately, multiscale modelling provides a powerful simulation tool that can be used to study the mechanical properties of these soft hierarchical, biological systems. This paper reviews recent developments in hierarchical multiscale modeling technique that aimed at understanding cytoskeleton mechanics. Discussions are expanded with respects to cytoskeletal components including: intermediate filaments, microtubules and microfilament networks. The mechanical performance of difference cytoskeleton components are… More >

Lai Yee Leung^*, Pamela J. VandeVord^∗,†, Alessandra Leonardi Dal Cengio^*, Cynthia Bir^*, King H. Yang^*, Albert I. King^*

Molecular & Cellular Biomechanics, Vol.5, No.3, pp. 155-168, 2008, DOI:10.3970/mcb.2008.005.155

Abstract Historically, blast overpressure is known to affect primarily gas-containing organs such as the lung and ear. More recent interests focus on its ability to cause damage to solid organs such as the brain, resulting in neurological disorders. Returning veterans exposed to blast but without external injuries are being diagnosed with mild traumatic brain injury (Warden 2006) and with cortical dysfunction (Cernak et al 1999). Decades of studies have been conducted to elucidate the effects of primary blast wave on the central nervous system. These studies were mostly concerned with systemic effects (Saljo et al 2000-2003; Kaur et al 1995-1997, 1999;… More >

Hao Wu¹, Qi Liu^{2, 3, *}, Xiaodong Liu⁴

CMC-Computers, Materials & Continua, Vol.60, No.2, pp. 575-597, 2019, DOI:10.32604/cmc.2019.03595

Abstract Deep learning technology has brought great impetus to artificial intelligence, especially in the fields of image processing, pattern and object recognition in recent years. Present proposed artificial neural networks and optimization skills have effectively achieved large-scale deep learnt neural networks showing better performance with deeper depth and wider width of networks. With the efforts in the present deep learning approaches, factors, e.g., network structures, training methods and training data sets are playing critical roles in improving the performance of networks. In this paper, deep learning models in recent years are summarized and compared with detailed discussion of several typical networks… More >