Modelling interactions between multiple bridge deterioration mechanisms

Bridge asset managers are tasked with developing effective maintenance strategies by the stakeholders of transportation networks. Any presentation of maintenance strategies requires an estimate of the consequence on the Whole Life Cycle Cost (WLCC), which is contingent on an accurate deterioration model. Bridge deterioration has previously been demonstrated to exhibit non-constant behaviour in literature. However, commonly industrial data constrains deterioration models to use exponential distributions. In this study, a Dynamic Bayesian Network (DBN) is proposed to model bridge deterioration, which considers the initiation of different defect mechanisms and the interactions between the mechanisms. The model is parameterised using an exponential distribution, however through the consideration of defect interactions, non-constant deterioration behaviour can still be incorporated in the model. The deterioration of pointing, displacement of block work alongside the presence of spalling, hollowness and masonry cracking are the defect mechanisms considered, with masonry railway bridges in the United Kingdom serving as a case study

Multi-defect modelling of bridge deterioration using truncated inspection records

Bridge Management Systems (BMS) are decision support tools that have gained widespread use across the transportation infrastructure management industry. The Whole Life Cycle Cost (WLCC) modelling in a BMS is typically composed of two main components: a deterioration model and a decision model. An accurate deterioration model is fundamental to any quality decision output.There are examples of deterministic and stochastic models for predictive deterioration modelling in the literature, however the condition of a bridge in these models is considered as an ‘overall’ condition which is either the worst condition or some aggregation of all the defects present. This research proposes a predictive bridge deterioration model which computes deterioration profiles for several distinct deterioration mechanisms on a bridge.The predictive deterioration model is composed of multiple Markov Chains, estimated using a method of maximum likelihood applied to panel data. The data available for all the defects types at each inspection is incomplete. As such, the proposed method considers that only the most significant defects are recorded, and inference is required regarding the less severe defects. A portfolio of 9,726 masonry railway bridges, with an average of 2.47 inspections per bridge, in the United Kingdom is the case study considered

Analytical models of polymer nucleation

In this thesis we investigate and develop analytic models for polymer nucleation and other barrier crossing problems. Our most broadly appealing method for certain multi dimensional barrier crossing problems is a one-dimensional projection which includes a novel technique to extract rate kinetics from simulations [M J Hamer et al., Soft Matter, 2012, 8, 11396-11408]. The scenarios we expect our method to be potentially useful are situations where barrier crossings are rare, and the dominant mechanism is through a series of unlikely incremental steps. The rate kinetics extraction technique is also reliant on the equilibrium energy barrier being relevant to non-equilibrium system, but is not appropriate when strong kinetic contributions dominate the process, and enable crossings over highly unfavourable energetic pathways. We explore and significantly enhance the Graham-Olmsted (GO) polymer nucleation simulation [R S Graham and P D Olmsted, Phys. Rev. Lett., 2009, 103, 115702], producing a combinatorial calculation to obtain exact energy landscapes from it’s basic stochastic rules of monomer attachment [M J Hamer et al., J. Non-Newton. Fluid., 2010, 165, 1294-1301]. We apply our rate kinetics extraction technique to the GO model and find that for most flow rates in purely long chain melts, nuclei tend to grow along similar paths over energy landscapes. The technique reveals a clear signature when this pattern is disobeyed, as in the case of blends of long and short chain polymer melts, some of which display highly anisotropic growth. In addition, we design several one-dimensional barrier crossing models with distinct characteristics, predicting the average and the distribution of crossing times with great accuracy. That finally enables us to completely describe the GO simulation’s nucleation rates with analytic theory, by presenting a model of polymer nucleation featuring crystal rotation, which vastly impacts nucleation rates when polymer melts are subject to flow

Eccentric loading increases peak torque angle of the ankle plantar flexors in healthy volunteers

Eccentric loading of the ankle plantar Flexor’s (PF) has demonstrated clinical efficacy in the conservative treatment of Achilles tendinopathy, however, its mechanism of therapeutic benefit remains unclear. The purpose of this study was to examine the effects of PF eccentric loading on PF angle to peak torque (AtPT), peak torque (PT) and lower limb vertical stiffness. Thirty healthy volunteers were randomised to an eccentric (n=15) or concentric (n=13) exercise group. A 10-week loading programme of the ankle plantar flexors was completed. AtPT, PT and vertical stiffness were compared within and between groups before and after the interventions. AtPT increased in the eccentric group by 3.2° dorsiflexion (p=0.001) and decreased by 0.7° dorsiflexion (p=0.528) for the concentric group with significant post-intervention group differences (p\u3c0.001). PT levels were unchanged following the interventions for both groups (p\u3e0.2); however, post-intervention the eccentric group showed a greater PT than the concentric group (p\u3e0.05). Between group comparison showed no significant difference in vertical stiffness (p\u3e0.5). However, the concentric group demonstrated a vertical stiffness increase of 765kNm-¹ (p ≥ 0.05). This study demonstrates that a clinically derived eccentric loading programme can produce an adaptive shift in AtPT of the ankle plantar flexors in a healthy population. These results support the theory that in part, eccentric loading derives its therapeutic benefit from mechanisms that influence plantar flexor motor performance

Do associations of physical activity and sedentary behaviour with cardiovascular disease and mortality differ across socioeconomic groups? A prospective analysis of device-measured and self-reported UK Biobank data

OBJECTIVE: To examine if individual-level and area-level socioeconomic status (SES) modifies the association of moderate-to-vigorous physical activity (MVPA), domain-specific physical activity and sedentary behaviour with all-cause mortality (ACM) and incident cardiovascular disease (CVD). METHODS: We used self-reported (International Physical Activity Questionnaire short form) and accelerometer-measured physical activity and sedentary behaviour data from the UK Biobank. We created an individual-level composite SES index using latent class analysis of household income, education and employment status. The Townsend Index was the measure of area-level SES. Cox proportional hazards regression models stratified across SES were used. RESULTS: In 328 228 participants (mean age 55.9 (SD 8.1) years, 45% men) with an average follow-up of 12.1 (1.4) years, 18 033 deaths and 98 922 incident CVD events occurred. We found an increased ACM risk of low physical activity and high sedentary behaviour and an increased incident CVD risk of low accelerometer-measured moderate-to-vigorous physical activity (ACCEL_MVPA) and high sitting time. We observed statistically significant interactions for all exposures in ACM analyses by individual-level SES (p<0.05) but only for screen time in area-level SES–ACM analysis (p<0.001). Compared with high self-reported moderate-to-vigorous physical activity (IPAQ_MVPA), adjusted ACM HRs for low IPAQ_MVPA were 1.14 (95% CI 1.05 to .25), 1.15 (95% CI 1.06 to 1.24) and 1.22 (95% CI 1.13 to 1.31) in high, medium and low individual-level SES, respectively. There were higher detrimental associations of low ACCEL_MVPA with decreasing area-level SES for both outcomes and of high screen time with ACM in low area-level SES. CONCLUSION: We found modest evidence suggesting that the detrimental associations of low MVPA and high screen time with ACM and incident CVD are accentuated in low SES groups

A standardised sampling protocol for robust assessment of reach-scale fish community diversity in wadeable New Zealand streams

The New Zealand fish fauna contains species that are affected not only by river system connectivity, but also by catchment and local-scale changes in landcover, water quality and habitat quality. Consequently, native fish have potential as multi-scale bioindicators of human pressure on stream ecosystems, yet no standardised, repeatable and scientifically defensible methods currently exist for effectively quantifying their abundance or diversity in New Zealand stream reaches. Here we report on the testing of a back-pack electrofishing method, modified from that used by the United States Environmental Protection Agency, on a wide variety of wadeable stream reaches throughout New Zealand. Seventy-three first- to third-order stream reaches were fished with a single pass over 150-345 m length. Time taken to sample a reach using single-pass electrofishing ranged from 1-8 h. Species accumulation curves indicated that, irrespective of location, continuous sampling of 150 stream metres is required to accurately describe reach-scale fish species richness using this approach. Additional species detection beyond 150 m was rare (<10%) with a single additional species detected at only two out of the 17 reaches sampled beyond this distance. A positive relationship was also evident between species detection and area fished, although stream length rather than area appeared to be the better predictor. The method tested provides a standardised and repeatable approach for regional and/or national reporting on the state of New Zealand's freshwater fish communities and trends in richness and abundance over time

Fractal complexity of daily physical activity and cognitive function in a midlife cohort

High stability of fluctuation in physiological patterns across fixed time periods suggest healthy fractal complexity, while greater randomness in fluctuation patterns may indicate underlying disease processes. The importance of fractal stability in mid-life remains unexplored. We quantified fractal regulation patterns in 24-h accelerometer data and examined associations with cognitive function in midlife. Data from 5097 individuals (aged 46) from the 1970 British Cohort Study were analyzed. Participants wore thigh-mounted accelerometers for seven days and completed cognitive tests (verbal fluency, memory, processing speed; derived composite z-score). Detrended fluctuation analysis (DFA) was used to examine temporal correlations of acceleration magnitude across 25 time scales (range: 1 min-10 h). Linear regression examined associations between DFA scaling exponents (DFAe) and each standardised cognitive outcome. DFAe was normally distributed (mean ± SD: 0.90 ± 0.06; range: 0.72-1.25). In males, a 0.10 increase in DFAe was associated with a 0.30 (95% Confidence Interval: 0.14, 0.47) increase in composite cognitive z-score in unadjusted models; associations were strongest for verbal fluency (0.10 [0.04, 0.16]). Associations remained in fully-adjusted models for verbal fluency only (0.06 [0.00, 0.12]). There was no association between DFA and cognition in females. Greater fractal stability in men was associated with better cognitive function. This could indicate mechanisms through which fractal complexity may scale up to and contribute to cognitive clinical endpoints

Optical second harmonic generation in encapsulated single-layer InSe

We report the observation of optical second harmonic generation (SHG) in single-layer indium selenide (InSe). We measure a second harmonic signal of $>10^3$ $\textrm{cts/s}$ under nonresonant excitation using a home-built confocal microscope and a standard pulsed pico-second laser. We demonstrate that polarization-resolved SHG serves as a fast, non-invasive tool to determine the crystal axes in single-layer InSe and to relate the sharp edges of the flake to the armchair and zigzag edges of the crystal structure. Our experiment determines these angles to an accuracy better than $\pm$ $0.2^{\circ}$. Treating the two-dimensional material as a nonlinear polarizable sheet, we determine a second-order nonlinear sheet polarizability $| \chi_{\textrm{sheet}}^{(2)}|=(17.9 \pm 11.0)\times 10^{-20}$ $\textrm{m}^2 \textrm{V}^{-1}$ for single-layer InSe, corresponding to an effective nonlinear susceptibility value of $| \chi_\textrm{eff}^{(2)}| \approx (223 \pm 138) \times 10^{-12}$ $\textrm{m} \textrm{V}^{-1}$ accounting for the sheet thickness ($\textrm{d} \approx 0.8$ $\textrm{nm}$). We demonstrate that the SHG technique can also be applied to encapsulated samples to probe their crystal orientations. The method is therefore suitable for creating high quality van der Waals heterostructures with control over the crystal directions

Incorporating defect specific condition indicators in a bridge life cycle analysis

Bridges are critical assets for the safe, reliable and functional operation of transportation networks. Infrastructure asset managers are responsible for ensuring that these bridges adhere to rigorous safety standards using the finite resources available to transportation agencies. To facilitate strategy development and to present decisions to stakeholders, a life cycle analysis is commonly performed. Many bridge owners use stochastic models that are calibrated using condition records from visual examinations, however condition records typically report bridge condition on a single condition scale. In this study, defect specific condition scales are utilised to implement multiple defect specific condition indicators in the modelling of deterioration. These additional indicators enable the modelling of the interactions between defects during deterioration. Moreover, the indicators are used in the modelling of different defect specific maintenance interventions providing the scope to quantitatively assess the effects of strategies that favour early intervention. A multiple defect deterioration model is presented as a dynamic Bayesian network, which is calibrated using records for metallic girders from railway bridges in the United Kingdom. A Petri net model is then used to perform a life cycle analysis, which incorporates a novel dynamic conditional approach for Petri net modelling to utilise the multiple condition indicators