Field validation of controlled Monte Carlo data generation for statistical damage identification employing Mahalanobis squared distance

This article presents the field applications and validations for the controlled Monte Carlo data generation scheme. This scheme was previously derived to assist the Mahalanobis squared distance–based damage identification method to cope with data-shortage problems which often cause inadequate data multinormality and unreliable identification outcome. To do so, real-vibration datasets from two actual civil engineering structures with such data (and identification) problems are selected as the test objects which are then shown to be in need of enhancement to consolidate their conditions. By utilizing the robust probability measures of the data condition indices in controlled Monte Carlo data generation and statistical sensitivity analysis of the Mahalanobis squared distance computational system, well-conditioned synthetic data generated by an optimal controlled Monte Carlo data generation configurations can be unbiasedly evaluated against those generated by other set-ups and against the original data. The analysis results reconfirm that controlled Monte Carlo data generation is able to overcome the shortage of observations, improve the data multinormality and enhance the reliability of the Mahalanobis squared distance–based damage identification method particularly with respect to false-positive errors. The results also highlight the dynamic structure of controlled Monte Carlo data generation that makes this scheme well adaptive to any type of input data with any (original) distributional condition.

Synthesis, mechanical and electrical properties of carbon microcoils and nanocoils

The results on the synthesis, mechanical and electrical properties of carbon microcoils and nanocoils (CMCs, CNCs) synthesized using catalytic CVD and Ni-P and Co-P catalyst alloys, respectively, are reported. SEM analysis reveals that the CMCs and CNCs have unique helical morphologies, and diameters of 5.0-9.0 μm and 450-550 nm, respectively. Moreover, CMCs with flat cross-section can be stretched to 3 times their original coil lengths. Current-voltage characteristics of a single microcoil have also been obtained. It is found that the CMCs have the electrical conductivity between 100 and 160 S/cm, whereas the electrical resistance increases by about 20% during the coil extension. Besides, the microcoils can produce light in vacuum when the test voltage reaches 10 V. The emission intensity increases as the voltage increases. The mechanical and electrical properties of CMCs and CNC make them potentially useful in many applications in micromagnetic sensors, mechanical microsprings and optoelectronics.

Mechanical model and superelastic properties of carbon microcoils with circular cross-section

Here we report on an unconventional Ni-P alloy-catalyzed, high-throughput, highly reproducible chemical vapor deposition of ultralong carbon microcoils using acetylene precursor in the temperature range 700-750 °C. Scanning electron microscopy analysis reveals that the carbon microcoils have a unique double-helix structure and a uniform circular cross-section. It is shown that double-helix carbon microcoils have outstanding superelastic properties. The microcoils can be extended up to 10-20 times of their original coil length, and quickly recover the original state after releasing the force. A mechanical model of the carbon coils with a large spring index is developed to describe their extension and contraction. Given the initial coil parameters, this mechanical model can successfully account for the geometric nonlinearity of the spring constants for carbon micro- and nanocoils, and is found in a good agreement with the experimental data in the whole stretching process.

Supporting process model validation through natural language generation

The design and development of process-aware information systems is often supported by specifying requirements as business process models. Although this approach is generally accepted as an effective strategy, it remains a fundamental challenge to adequately validate these models given the diverging skill set of domain experts and system analysts. As domain experts often do not feel confident in judging the correctness and completeness of process models that system analysts create, the validation often has to regress to a discourse using natural language. In order to support such a discourse appropriately, so-called verbalization techniques have been defined for different types of conceptual models. However, there is currently no sophisticated technique available that is capable of generating natural-looking text from process models. In this paper, we address this research gap and propose a technique for generating natural language texts from business process models. A comparison with manually created process descriptions demonstrates that the generated texts are superior in terms of completeness, structure, and linguistic complexity. An evaluation with users further demonstrates that the texts are very understandable and effectively allow the reader to infer the process model semantics. Hence, the generated texts represent a useful input for process model validation.

Diagnostics of rolling element bearings for the traction system of high speed trains : experimental evidences

Monitoring of the integrity of rolling element bearings in the traction system of high speed trains is a fundamental operation in order to avoid catastrophic failures and to implement effective condition-based maintenance strategies. Diagnostics of rolling element bearings is usually based on vibration signal analysis by means of suitable signal processing techniques. The experimental validation of such techniques has been traditionally performed by means of laboratory tests on artificially damaged bearings, while their actual effectiveness in industrial applications, particularly in the field of rail transport, remains scarcely investigated. This paper will address the diagnostics of bearings taken from the service after a long term operation on a high speed train. These worn bearings have been installed on a test-rig, consisting of a complete full-scale traction system of a high speed train, able to reproduce the effects of wheel-track interaction and bogie-wheelset dynamics. The results of the experimental campaign show that suitable signal processing techniques are able to diagnose bearing failures even in this harsh and noisy application. Moreover, the most suitable location of the sensors on the traction system is also proposed.

Experimental evidences in bearing diagnostics for traction system of high speed trains

Rolling element bearings are the most critical components in the traction system of high speed trains. Monitoring their integrity is a fundamental operation in order to avoid catastrophic failures and to implement effective condition based maintenance strategies. Generally, diagnostics of rolling element bearings is usually performed by analyzing vibration signals measured by accelerometers placed in the proximity of the bearing under investigation. Several papers have been published on this subject in the last two decades, mainly devoted to the development and assessment of signal processing techniques for diagnostics. The experimental validation of such techniques has been traditionally performed by means of laboratory tests on artificially damaged bearings, while their actual effectiveness in specific industrial applications, particularly in rail industry, remains scarcely investigated. This paper is aimed at filling this knowledge gap, by addressing the diagnostics of bearings taken from the service after a long term operation on the traction system of a high speed train. Moreover, in order to test the effectiveness of the diagnostic procedures in the environmental conditions peculiar to the rail application, a specific test-rig has been built, consisting of a complete full-scale train traction system, able to reproduce the effects of wheeltrack interaction and bogie-wheelset dynamics. The results of the experimental campaign show that suitable signal processing techniques are able to diagnose bearing failures even in this harsh and noisy application. Moreover, the most suitable location of the sensors on the traction system is proposed, in order to limit their number.

Determination of strain-rate-dependent mechanical behavior of living and fixed osteocytes and chondrocytes using atomic force microscopy and inverse finite element analysis

The aim of this paper is to determine the strain-rate-dependent mechanical behavior of living and fixed osteocytes and chondrocytes, in vitro. Firstly, Atomic Force Microscopy (AFM) was used to obtain the force-indentation curves of these single cells at four different strain-rates. These results were then employed in inverse finite element analysis (FEA) using Modified Standard neo-Hookean Solid (MSnHS) idealization of these cells to determine their mechanical properties. In addition, a FEA model with a newly developed spring element was employed to accurately simulate AFM evaluation in this study. We report that both cytoskeleton (CSK) and intracellular fluid govern the strain-rate-dependent mechanical property of living cells whereas intracellular fluid plays a predominant role on fixed cells’ behavior. In addition, through the comparisons, it can be concluded that osteocytes are stiffer than chondrocytes at all strain-rates tested indicating that the cells could be the biomarker of their tissue origin. Finally, we report that MSnHS is able to capture the strain-rate-dependent mechanical behavior of osteocyte and chondrocyte for both living and fixed cells. Therefore, we concluded that the MSnHS is a good model for exploration of mechanical deformation responses of single osteocytes and chondrocytes. This study could open a new avenue for analysis of mechanical behavior of osteocytes and chondrocytes as well as other similar types of cells.

Measuring, modelling and understanding the mechanical behavior of bagasse

In the Australian sugar industry, sugar cane is smashed into a straw like material by hammers before being squeezed between large rollers to extract the sugar juice. The straw like material is initially called prepared cane and then bagasse as it passes through successive roller milling units. The sugar cane materials are highly compressible, have high moisture content, are fibrous, and they resemble some peat soils in both appearance and mechanical behaviour. A promising avenue to improve the performance of milling units for increased throughput and juice extraction, and to reduce costs is by modelling of the crushing process. To achieve this, it is believed necessary that milling models should be able to reproduce measured bagasse behaviour. This investigation sought to measure the mechanical (compression, shear, and volume) behaviour of prepared cane and bagasse, to identify limitations in currently used material models, and to progress towards a material model that can predict bagasse behaviour adequately. Tests were carried out using a modified direct shear test equipment and procedure at most of the large range of pressures occurring in the crushing process. The investigation included an assessment of the performance of the direct shear test for measuring bagasse behaviour. The assessment was carried out using finite element modelling. It was shown that prepared cane and bagasse exhibited critical state behavior similar to that of soils and the magnitudes of material parameters were determined. The measurements were used to identify desirable features for a bagasse material model. It was shown that currently used material models had major limitations for reproducing bagasse behaviour. A model from the soil mechanics literature was modified and shown to achieve improved reproduction while using magnitudes of material parameters that better reflected the measured values. Finally, a typical three roller mill pressure feeder configuration was modelled. The predictions and limitations were assessed by comparison to measured data from a sugar factory.

Modelling of the mechanical behaviour of heavily over-consolidated bagasse

A better understanding of the behaviour of prepared cane and bagasse, and the ability to model the mechanical behaviour of bagasse as it is squeezed in a milling unit to extract juice, would help identify how to improve the current process, for example to reduce final bagasse moisture. Previous investigations have proven that juice flow through bagasse obeys Darcy’s permeability law, that the grip of the rough surface of the grooves on the bagasse can be represented by the Mohr-Coulomb failure criterion for soils, and that the internal mechanical behaviour of the bagasse is critical state behaviour similar to that for sand and clay. Current Finite Element Models (FEM) available in commercial software have adequate permeability models. However, no commercially available software seems to contain an adequate mechanical model for bagasse. The same software contains a few material models for soil and other materials, while the coding of hundreds of developed models for soil and other materials remains confidential at universities and government research centres. Progress has been made in the last ten years towards implementing a mechanical model for bagasse in finite element software code. This paper builds on that progress and carries out a further step towards obtaining an adequate material model. The fifth and final loading condition outlined previously, shearing of heavily over-consolidated bagasse, is outlined.

Preparation of graphene oxide/epoxy nanocomposites with significantly improved mechanical properties

The effect of graphene oxide (GO) on the mechanical properties and the curing reaction of Diglycidyl Ether of Bisphenol A/F and Triethylenetetramine epoxy system was investigated. GO was prepared by oxidation of graphite flakes and characterized by spectroscopic and microscopic techniques. Epoxy nanocomposites were fabricated with different GO loading by solution mixing technique. It was found that incorporation of small amount of GO into the epoxy matrix significantly enhanced the mechanical properties of the epoxy. In particular, model I fracture toughness was increased by nearly 50% with the addition of 0.1 wt. % GO to epoxy. The toughening mechanism was understood by fractography analysis of the tested samples. The more irregular, coarse, and multi-plane fracture surfaces of the epoxy/GO nanocomposites were observed. This implies that the two-dimensional GO sheets effectively disturbed and deflected the crack propagation. At 0.5 wt. % GO, elastic modulus was ~35% greater than neat epoxy. Differential scanning calorimetry (DSC) results showed that GO addition moderately affect the glass transition temperature (Tg) of epoxy. The maximum decrease of Tg by ~7 oC was shown for the nanocomposite with 0.5 wt. % GO. DSC results further revealed that GO significantly hindered the cure reaction in the epoxy system.

Experimental investigation of post-fire mechanical properties of cold-formed steels

Cold-formed steel members are widely used in residential, industrial and commercial buildings as primary load-bearing elements. During fire events, they will be exposed to elevated temperatures. If the general appearance of the structure is satisfactory after a fire event then the question that has to be answered is how the load bearing capacity of cold-formed steel members in these buildings has been affected. Hence after such fire events there is a need to evaluate the residual strength of these members. However, the post-fire behaviour of cold-formed steel members has not been investigated in the past. This means conservative decisions are likely to be made in relation to fire exposed cold-formed steel buildings. Therefore an experimental study was undertaken to investigate the post-fire mechanical properties of cold-formed steels. Tensile coupons taken from cold-formed steel sheets of three different steel grades and thicknesses were exposed to different elevated temperatures up to 800 oC, and were then allowed to cool down to ambient temperature before they were tested to failure. Tensile coupon tests were conducted to obtain their post-fire stress-strain curves and associated mechanical properties (yield stress, Young’s modulus, ultimate strength and ductility). It was found that the post-fire mechanical properties of cold-formed steels are reduced below the original ambient temperature mechanical properties if they had been exposed to temperatures exceeding 300 oC. Hence a new set of equations is proposed to predict the post-fire mechanical properties of cold-formed steels. Such post-fire mechanical property assessments allow structural and fire engineers to make an accurate prediction of the safety of fire exposed cold-formed steel buildings. This paper presents the details of this experimental study and the results of post-fire mechanical properties of cold-formed steels. It also includes the results of a post-fire evaluation of cold-formed steel walls.

Bridging experiments, models and simulations : an integrative approach to validation in computational cardiac electrophysiology

Computational models in physiology often integrate functional and structural information from a large range of spatio-temporal scales from the ionic to the whole organ level. Their sophistication raises both expectations and scepticism concerning how computational methods can improve our understanding of living organisms and also how they can reduce, replace and refine animal experiments. A fundamental requirement to fulfil these expectations and achieve the full potential of computational physiology is a clear understanding of what models represent and how they can be validated. The present study aims at informing strategies for validation by elucidating the complex interrelations between experiments, models and simulations in cardiac electrophysiology. We describe the processes, data and knowledge involved in the construction of whole ventricular multiscale models of cardiac electrophysiology. Our analysis reveals that models, simulations, and experiments are intertwined, in an assemblage that is a system itself, namely the model-simulation-experiment (MSE) system. Validation must therefore take into account the complex interplay between models, simulations and experiments. Key points for developing strategies for validation are: 1) understanding sources of bio-variability is crucial to the comparison between simulation and experimental results; 2) robustness of techniques and tools is a pre-requisite to conducting physiological investigations using the MSE system; 3) definition and adoption of standards facilitates interoperability of experiments, models and simulations; 4) physiological validation must be understood as an iterative process that defines the specific aspects of electrophysiology the MSE system targets, and is driven by advancements in experimental and computational methods and the combination of both.

Engineering the mechanical properties of graphene nanotube hybrid structures through structural modulation

The excellent multi-functional properties of carbon nanotube (CNT) and graphene have enabled them as appealing building blocks to construct 3D carbon-based nanomaterials or nanostructures. The recently reported graphene nanotube hybrid structure (GNHS) is one of the representatives of such nanostructures. This work investigated the relationships between the mechanical properties of the GNHS and its structure basing on large-scale molecular dynamics simulations. It is found that increasing the length of the constituent CNTs, the GNHS will have a higher Young’s modulus and yield strength. Whereas, no strong correlation is found between the number of graphene layers and Young’s modulus and yield strength, though more graphene layers intends to lead to a higher yield strain. In the meanwhile, the presences of multi-wall CNTs are found to greatly strengthen the hybrid structure. Generally, the hybrid structures exhibit a brittle behavior and the failure initiates from the connecting regions between CNT and graphene. More interestingly, affluent formations of monoatomic chains and rings are found at the fracture region. This study provides an in-depth understanding of the mechanical performance of the GNHSs while varying their structures, which will shed lights on the design and also the applications of the carbon-based nanostructures.

Cross cultural adaptation and validation of a Spanish version of the lower limb functional index

Background: The Lower Limb Functional Index (LLFI) is a relatively recently published regional outcome measure. The development article showed the LLFI had robust and valid clinimetric properties with sound psychometric and practical characteristics when compared to the Lower Limb Extremity Scale (LEFS) criterion standard. Objective: The purpose of this study was cross cultural adaptation and validation of the LLFI Spanish-version (LLFI-Sp) in a Spanish population. Methods: A two stage observational study was conducted. The LLFI was initially cross-culturally adapted to Spanish through double forward and single backward translation; then subsequently validated for the psychometric characteristics of validity, internal consistency, reliability, error score and factor structure. Participants (n = 136) with various lower limb conditions of >12 weeks duration completed the LLFI-Sp, Western Ontario and McMaster University Osteoarthritis Index (WOMAC) and the Euroqol Health Questionnaire 5 Dimensions (EQ-5D-3 L). The full sample was employed to determine internal consistency, concurrent criterion validity, construct validity and factor structure; a subgroup (n = 45) determined reliability at seven days concurrently completing a global rating of change scale. Results: The LLFI-Sp demonstrated high but not excessive internal consistency (α = 0.91) and high reliability (ICC = 0.96). The factor structure was one-dimensional which supported the construct validity. Criterion validity with the WOMAC was strong (r = 0.77) and with the EQ-5D-3 L fair and inversely correlated (r = -0.62). The study limitations included the lack of longitudinal data and the determination of responsiveness. Conclusions: The LLFI-Sp supports the findings of the original English version as being a valid lower limb regional outcome measure. It demonstrated similar psychometric properties for internal consistency, validity, reliability, error score and factor structure.

Comparison of eight published static finite element models of the intact lumbar spine : predictive power of models improves when combined together

Finite element (FE) model studies have made important contributions to our understanding of functional biomechanics of the lumbar spine. However, if a model is used to answer clinical and biomechanical questions over a certain population, their inherently large inter-subject variability has to be considered. Current FE model studies, however, generally account only for a single distinct spinal geometry with one set of material properties. This raises questions concerning their predictive power, their range of results and on their agreement with in vitro and in vivo values. Eight well-established FE models of the lumbar spine (L1-5) of different research centres around the globe were subjected to pure and combined loading modes and compared to in vitro and in vivo measurements for intervertebral rotations, disc pressures and facet joint forces. Under pure moment loading, the predicted L1-5 rotations of almost all models fell within the reported in vitro ranges, and their median values differed on average by only 2° for flexion-extension, 1° for lateral bending and 5° for axial rotation. Predicted median facet joint forces and disc pressures were also in good agreement with published median in vitro values. However, the ranges of predictions were larger and exceeded those reported in vitro, especially for the facet joint forces. For all combined loading modes, except for flexion, predicted median segmental intervertebral rotations and disc pressures were in good agreement with measured in vivo values. In light of high inter-subject variability, the generalization of results of a single model to a population remains a concern. This study demonstrated that the pooled median of individual model results, similar to a probabilistic approach, can be used as an improved predictive tool in order to estimate the response of the lumbar spine.