Identifying short-term variation of dynamic friction by means of its frequency response function

A challenging case study of dynamic friction was presented in a previous study (A. Cabboi, J. Woodhouse, Validation of a constitutive law for friction-induced vibration under different wear conditions, Wear 396–397 (2018) 107–125), concerning tests performed with a Polycarbonate pin sliding on a steel disc. Identifying and modelling the frictional frequency response for this system turned out to be rarely possible, since the measurements were affected by significant wear and by intermittent squeal occurrence. To shed light on the observed “capricious” behaviour, an “instantaneous” estimation of the frequency response of dynamic friction was developed, allowing the dynamic friction behaviour to be captured and tracked before, and for few cases during, squeal events. Each “instantaneous” frequency response of dynamic friction was fitted by a rate-and-state model, and variations of the model parameters for different sliding speeds, changing normal forces and at different wear stages were tracked. With direct relevance to squeal predictions, the model parameters identified through the proposed processing and fitting methodology could detect rapid transitions between velocity-strengthening and weakening behaviour. These transitions may occur at different sliding speeds, but they also occur during measurements carried out at a constant sliding speed. Based on the identified model parameters, a first qualitative attempt to predict squeal events by means of rate-and-state models is presented, and shown to give promising correlation with experimental results

The frequency response of dynamic friction: Enhanced rate-and-state models

The prediction and control of friction-induced vibration requires a sufficiently accurate constitutive law for dynamic friction at the sliding interface: for linearised stability analysis, this requirement takes the form of a frictional frequency response function. Systematic measurements of this frictional frequency response function are presented for small samples of nylon and polycarbonate sliding against a glass disc. Previous efforts to explain such measurements from a theoretical model have failed, but an enhanced rate-and-state model is presented which is shown to match the measurements remarkably well. The tested parameter space covers a range of normal forces (10–50 N), of sliding speeds (1–10 mm/s) and frequencies (100–2000 Hz). The key new ingredient in the model is the inclusion of contact stiffness to take into account elastic deformations near the interface. A systematic methodology is presented to discriminate among possible variants of the model, and then to identify the model parameter values.Alessandro Cabboi and Thibaut Putelat both acknowledge support from the EPSRC programme grant “Engineering Nonlinearity” (ref. EP/K003836/1).This is the final version of the article. It first appeared from Elsevier via https://doi.org10.1016/j.jmps.2016.03.02

Validation of a constitutive law for friction-induced vibration under different wear conditions

Recent work (A. Cabboi, T. Putelat, J. Woodhouse, The frequency response of dynamic friction: Enhanced rate- and-state models, Journal of the Mechanics and Physics of Solids 92 (2016) 210–236) has shown promising agreement between measurements and theoretical modelling of high-frequency dynamic sliding friction. This paper confirms and extends this agreement by presenting results for a wide selection of contacting materials. Additional measurement tech- niques are also introduced, to give independent confirmation of parameter identification and improve the robustness of the identification process. The results show that virtually every individual measurement can be fitted accurately by the pro- posed theoretical model, and that in all cases where rapid wear of the contacting materials was not an issue it was possible to achieve a good global fit to sets of tests at different normal loads and sliding speeds. The evidence suggests that this measurement procedure is able to characterise the dynamic behaviour at a frictional interface up to kiloHertz frequencies, and consequently provide the means to discriminate among, and calibrate, proposed dynamic friction models. Identifying a reliable model could significantly improve the prediction accuracy for friction-induced vibration such as vehicle brake squeal.Financial support was provided by the EPSRC programme grant “Engineering Nonlinearity” (ref. EP/K003836/1 — www.engineeringnonlinearity.ac.uk)

Automated modal identification and tracking: Application to an iron arch bridge

Challenges concerning the automation of modal identification and tracking procedures in permanent monitoring systems for Structural Health Monitoring purposes are discussed. In this context, an automated procedure based on parametric identification methods that involve the interpretation of stabilization diagrams is proposed. The methodology comprehends two key points: (i) automatic analysis of stabilization diagrams, performed through a first check of reasonable damping ratio, a subsequent modal complexity check and a final clustering of structural modes; (ii) automated tracking of the evolution in time of the identified modal properties. The proposed modal clustering and tracking steps exploit the introduction of self-adaptable dynamic thresholds, that do not require any a priori manual tuning for the different recorded data set. Finally, the proposed approach was successfully validated using real data collected on a historic iron arch bridge.This is the author accepted manuscript. The final version is available from Wiley via https://doi.org/10.1002/stc.185

No evidence of neural adaptations following chronic unilateral isometric training of the intrinsic muscles of the hand: a randomized controlled study

Purpose: To test whether long-term cortical adaptations occur bilaterally following chronic unilateral training with a simple motor task. / Methods: Participants (n = 34) were randomly allocated to a training or control groups. Only the former completed a 4-week maximal-intensity isometric training of the right first dorsal interosseus muscle through key pinching. Maximal strength was assessed bilaterally in four different movements progressively less similar to the training task: key, tip and tripod pinches, and handgrip. Transcranial magnetic stimulation was used to probe, in the left and right primary hand motor cortices, a number of standard tests of cortical excitability, including thresholds, intra-cortical inhibition and facilitation, transcallosal inhibition, and sensory-motor integration. / Results: Training increased strength in the trained hand, but only for the tasks specifically involving the trained muscle (key +8.5 %; p < 0.0005; tip +7.2 %; p = 0.02). However, the effect size was small and below the cutoff for meaningful change. Handgrip and tripod pinch were instead unaffected. There was a similar improvement in strength in the untrained hand, i.e., a cross-education effect (key +6.4 %; p = 0.02; tip +4.7 %; p = 0.007). Despite these changes in strength, no significant variation was observed in any of the neurophysiological parameters describing cortico-spinal and intra-cortical excitability, inter-hemispheric inhibition, and cortical sensory-motor integration. / Conclusions: A 4-week maximal-intensity unilateral training induced bilaterally spatial- and task-specific strength gains, which were not associated to direct or crossed cortical adaptations. The observed long-term stability of neurophysiological parameters might result from homeostatic plasticity phenomena, aimed at restoring the physiological inter-hemispheric balance of neural activity levels perturbed by the exercise. / Trial registration number: ClinicalTrials.gov identifier NCT02010398

Railway bridge structural health monitoring and fault detection: state-of-the-art methods and future challenges

Railway importance in the transportation industry is increasing continuously, due to the growing demand of both passenger travel and transportation of goods. However, more than 35% of the 300,000 railway bridges across Europe are over 100-years old, and their reliability directly impacts the reliability of the railway network. This increased demand may lead to higher risk associated with their unexpected failures, resulting safety hazards to passengers and increased whole life cycle cost of the asset. Consequently, one of the most important aspects of evaluation of the reliability of the overall railway transport system is bridge structural health monitoring, which can monitor the health state of the bridge by allowing an early detection of failures. Therefore, a fast, safe and cost-effective recovery of the optimal health state of the bridge, where the levels of element degradation or failure are maintained efficiently, can be achieved. In this article, after an introduction to the desired features of structural health monitoring, a review of the most commonly adopted bridge fault detection methods is presented. Mainly, the analysis focuses on model-based finite element updating strategies, non-model-based (data-driven) fault detection methods, such as artificial neural network, and Bayesian belief network–based structural health monitoring methods. A comparative study, which aims to discuss and compare the performance of the reviewed types of structural health monitoring methods, is then presented by analysing a short-span steel structure of a railway bridge. Opportunities and future challenges of the fault detection methods of railway bridges are highlighted

DMTs and Covid-19 severity in MS: a pooled analysis from Italy and France

We evaluated the effect of DMTs on Covid-19 severity in patients with MS, with a pooled-analysis of two large cohorts from Italy and France. The association of baseline characteristics and DMTs with Covid-19 severity was assessed by multivariate ordinal-logistic models and pooled by a fixed-effect meta-analysis. 1066 patients with MS from Italy and 721 from France were included. In the multivariate model, anti-CD20 therapies were significantly associated (OR&nbsp;=&nbsp;2.05, 95%CI&nbsp;=&nbsp;1.39–3.02, p&nbsp;&lt;&nbsp;0.001) with Covid-19 severity, whereas interferon indicated a decreased risk (OR&nbsp;=&nbsp;0.42, 95%CI&nbsp;=&nbsp;0.18–0.99, p&nbsp;=&nbsp;0.047). This pooled-analysis confirms an increased risk of severe Covid-19 in patients on anti-CD20 therapies and supports the protective role of interferon

Identifying short-term variation of dynamic friction by means of its frequency response function

A challenging case study of dynamic friction was presented in a previous study (A. Cabboi, J. Woodhouse, Validation of a constitutive law for friction-induced vibration under different wear conditions, Wear 396–397 (2018) 107–125), concerning tests performed with a Polycarbonate pin sliding on a steel disc. Identifying and modelling the frictional frequency response for this system turned out to be rarely possible, since the measurements were affected by significant wear and by intermittent squeal occurrence. To shed light on the observed “capricious” behaviour, an “instantaneous” estimation of the frequency response of dynamic friction was developed, allowing the dynamic friction behaviour to be captured and tracked before, and for few cases during, squeal events. Each “instantaneous” frequency response of dynamic friction was fitted by a rate-and-state model, and variations of the model parameters for different sliding speeds, changing normal forces and at different wear stages were tracked. With direct relevance to squeal predictions, the model parameters identified through the proposed processing and fitting methodology could detect rapid transitions between velocity-strengthening and weakening behaviour. These transitions may occur at different sliding speeds, but they also occur during measurements carried out at a constant sliding speed. Based on the identified model parameters, a first qualitative attempt to predict squeal events by means of rate-and-state models is presented, and shown to give promising correlation with experimental results

Vibration-based structural health monitoring of stay cables by microwave remote sensing

Microwave remote sensing is probably the most recent experimental technique suitable to the non-contact measurement of deflections on large structures, in static or dynamic conditions. In the first part of the paper, the main techniques adopted in microwave remote sensing are described, so that advantages and potential issues of these techniques are presented and discussed. Subsequently, the paper addresses the application of the radar technology to the measurement of the vibration response on the stay cables of two cable-stayed bridges. The dynamic tests were performed in operational conditions (i.e. with the excitation being mainly provided by micro-tremors, wind and traffic) and the maximum deflections of the cables were generally lower than 5.0 mm. The investigation clearly highlights: (a) the safe and simple use of the radar on site and its effectiveness to simultaneously measure the dynamic response of all the stay cables of an array; (b) the negligible effects of the typical issues and uncertainties that might affect the radar measurements; (c) the accuracy of the results provided by the microwave remote sensing in terms of natural frequencies and tension forces of the stay cables; (d) the suitability of microwave interferometry to the repeated application within Structural Health Monitoring programmes