Effect of mean stress on multiaxial ratcheting life: a simplified life prediction model based on average equivalent stress amplitude

This article proposes a model to predict uniaxial and multiaxial ratcheting life by addressing the three primary parameters that influence failure life: fatigue damage, ratcheting damage and the multiaxial loading path. These three factors are addressed in the present model by (a) the stress amplitude for fatigue damage, (b) mean stress-dependent Goodman equation for ratcheting damage and (c) an inherent weight factor based on average equivalent stress to account for the multiaxial loading. The proposed model requires only two material constants which can be easily determined from uniaxial symmetric stress-controlled fatigue tests. Experimental ratcheting life data collected from the literature for 1025 and 42CrMo steel under multiaxial proportional and nonproportional constant amplitude loading ratcheting with triangular sinusoidal and trapezoidal waveform (i.e. linear, rhombic, circular, elliptical and square stress paths) have shown good agreement with the proposed model.

An overview of new progresses in understanding pipeline corrosion

An approach to achieving the ambitious goal of cost effectively extending the safe operation life of energy pipeline to 100 years is the application of health monitoring and life prediction tools that are able to provide both long-term remnant pipeline life prediction and in-situ pipeline condition monitoring. A critical step is the enhancement of technological capabilities that are required for understanding and quantifying the effects of key factors influencing buried steel pipeline corrosion and environmentally assisted materials degradation, and the development of condition monitoring technologies that are able to provide in-situ monitoring and site-specific warning of pipeline damage. This paper provides an overview of our current research aimed at developing new sensors and electrochemical cells for monitoring, categorising and quantifying the level and nature of external pipeline and coating damages under the combined effects of various inter-related variables and processes such as localised corrosion, coating cracking and disbondment, cathodic shielding, transit loss of cathodic protection.

Structural health monitoring: a practical approach to achieving in-situ and site-specific warning of pipeline corrosion and coating failure

An approach to achieving the ambitious goal of cost effectively extending the safe operation life of energy pipelines to, for instance, 100 years is the application of structural health monitoring and life prediction tools that are able to provide long-term remnant pipeline life prediction and in-situ pipeline condition monitoring. A critical step in pipeline structural health monitoring is the enhancement of technological capabilities that are required for quantifying the effects of key factors influencing buried pipeline corrosion and environmentally assisted materials degradation, and the development of condition monitoring technologies that are able to provide in-situ monitoring and site-specific warning of pipeline damage. This paper provides an overview of our current research aimed at developing new sensors for monitoring, categorising and quantifying the level and nature of external pipeline and coating damages under the combined effects of various inter-related variables and processes such as localised corrosion, coating damage and disbondment, cathodic shielding. The concept of in-situ monitoring and site-specific warning of pipeline corrosion is illustrated by a case of monitoring localised corrosion under disbonded coatings using a new corrosion monitoring probe. A basic principle that underpins the use of sensors to monitor localised corrosion has been presented: Localised corrosion and coating failure are not an accidental occurrence, it occurs as the result of fundamental thermodynamic instability of a metal exposed to a specific environment. Therefore corrosion and coating disbondment occurring on a pipeline will also occur on a sensor made of the same material and exposed to the same pipeline condition. Although the exact location of localised corrosion or coating disbondment could be difficult to pinpoint along the length of a buried pipeline, the ‘worst-case scenario’ and high risk pipeline sections and sites are predictable. Sensors can be embedded at these strategic sites to collect data that contain ‘predictor features’ signifying the occurrence of localised corrosion, CP failure, coating disbondment and degradation. Information from these sensors will enable pipeline owners to prioritise site survey and inspection operations, and to develop maintenance strategy to manage aged pipelines, rather than replace them.

Considerations associated with the testing of external pipeline coatings

Reliable testing methodologies for the assessment of protective coatings are critical for ensuring the integrity and durability of pipeline coatings (such as field joint coatings) and the mitigation of pipeline corrosion. Currently the failure of joint coatings is one of the major concerns in corrosion protection of pipelines, although they represent only approximately 5% of the coated area in a pipeline system. This paper presents an overview of major testing methodologies currently used in the pipeline industry for the selection, testing, and life prediction of coatings, in particular field joint coatings. Particular focus is on the discussion of difficulties and limitations in testing methods for assessing pipeline coating cracking, cathodic disbondment and loss of adhesion. It is shown that there are limitations in current methodologies in evaluating the coating flexibility - a key parameter for avoiding coatings cracking during hydrostatic testing, cyclic pressure operation and field bending. Methodologies for assessing the effect of holidays in coatings on the cathodic disbondment of pipeline coating under excessively negative cathodic protection (CP) voltages also require improvement. Furthermore, methods for understanding the effects of coating wet adhesion on pipeline coating, cracking and disbondment also need attention. Some preliminary results for addressing some of these issues are also presented in this paper.

Prediction of non-proportional cyclic hardening and multiaxial fatigue life for FCC and BCC metals under constant amplitude of strain cycling

The fatigue lives are reduced accompanying an additional cyclic hardening under strain controlled non-proportional cyclic loading in which principal directions of stress and strain are altered within a cycle. This study predicts non-proportional cyclic hardening and multiaxial fatigue life for several BCC and FCC metals under constant amplitude strain cycling. A novel procedure to determine non-proportional cyclic hardening form uniaxial tensile properties has discussed in this study. Standard plastic strain energy density based fatigue criteria with considering the non-proportional cyclic hardening effect successfully predicts multiaxial fatigue lives. The predictions of non-proportional cyclic hardening and multiaxial fatigue life through models are validated by experimental results of various BCC and FCC metals which are collected from literatures.

Frequency, severity and effect of life of physical symptoms experienced during pregnancy

This study aimed to: 1) describe the number, frequency, severity of discomfort and effect of symptoms on life of 29 physical symptoms women experienced at 15 to 25 weeks of gestation; 2) explore whether experiencing this group of physical symptoms more frequently and intensely was associated with a higher score of depressive symptoms and lower self-esteem; (3) examine whether discomfort and effect ratings aided prediction of well being over and above symptom frequency; and (4) investigate which individual physical symptoms contributed most to predicting depressive symptoms and self-esteem. Pregnant women (n = 215) completed the Beck Depression Inventory, Rosenberg Self-Esteem Scale, and a physical symptoms questionnaire. Frequency, discomfort, and the effect of physical symptoms all consistently correlated with higher scores for depressive symptoms, but less consistently with lower self-esteem. Discomfort and the effect of symptoms predicted variance in depressive symptoms after accounting for symptom frequency. Higher frequency, more discomfort, and the effect of fatigue and effect of flatulence were related to depressive symptoms. Relationships between pregnancy-related physical symptoms, depressive symptoms, and low self-esteem suggest that when women report any of these constellation of factors, further screening is indicated. A comprehensive assessment of physical symptoms includes frequency, discomfort, and effect on life.

Modified life cycle inventory of aluminium die casting

Aluminium die casting is a process used to transform molten aluminium material into automotive gearbox housings, wheels and electronic components, among many other uses. It is used because it is a very efficient method of achieving near net shape with the required mechanical properties. Life Cycle Assessment (LCA) is a technique used to determine the environmental impacts of a product or process. The Life Cycle Inventory (LCI) is the initial phase of an LCA and describes which emissions will occur and which raw materials are used during the life of a product or during a process. This study has improved the LCI technique by adding in manufacturing and other costs to the ISO standardised methods. Although this is not new, the novel application and allocation methods have been developed independently. The improved technique has then been applied to Aluminium High Pressure Die Casting. In applying the improved LCI to this process, the cost in monetary terms and environmental emissions have been determined for a particular component manufactured by this process. A model has been developed in association with an industry partner so this technique can be repeatedly applied and used in the prediction of costs and emissions. This has been tested with two different products. Following this, specialised LCA software modelling of the aluminium high pressure die casting process was conducted. The variations in the process have shown that each particular component will have different costs and emissions and it is not possible to generalise the process by modelling only one component. This study has concentrated on one process within die casting but the techniques developed can be used across any variations in the die casting process.

Quality of life assessment in the community-dwelling elderly : validation of the Assessment of Quality of Life (AQoL) instrument and comparison with the SF-36

Measurement of Health-Related Quality of Life (HRQoL) of the elderly requires instruments with demonstrated sensitivity, reliability, and validity, particularly with the increasing proportion of older people entering the health care system. This article reports the psychometric properties of the 12-item Assessment of Quality of Life (AQoL) instrument in chronically ill community-dwelling elderly people with an 18-month follow-up. Comparator instruments included the SF-36 and the OARS. Construct validity of the AQoL was strong when examined via factor analysis and convergent and divergent validity against other scales. Receiver Operator Characteristic (ROC) curve analyses and relative efficiency estimates indicated the AQoL is sensitive, responsive, and had the strongest predicative validity for nursing home entry. It was also sensitive to economic prediction over the follow-up. Given these robust psychometric properties and the brevity of the scale, AQoL appears to be a suitable instrument for epidemiologic studies where HRQoL and utility data are required from elderly populations.

Predictors of quality of life in carers for people with a progressive neurological illness: a longitudinal study

Purpose The aim of the present research was to determine the predictors of quality of life (QOL) among carers for people living with a chronic degenerative neurological illness, with comparisons of the differences in significant predictors of QOL between illness groups.
Methods Psychosocial and economic variables were examined among 192 carers for people living at home with motor neurone disease, Huntington’s disease, multiple sclerosis, and Parkinson’s, over a twelve-month period, to determine their contribution to the prediction of carer QOL.
Results Mood was the only consistent predictor of carer QOL across groups; however, marital relationship satisfaction, social support satisfaction, income, and economic pressure significantly predicted carer QOL for at least one of the illness groups, in addition to mood.
Conclusions The findings highlight the importance of recognising the varying roles that psychosocial and economic variables play on the prediction of carer QOL within each of these illness groups.

Insectivore life histories: further evidence against an optimum body size for mammals

1. This study tests a model of the relationship of body mass to reproductive power (the rate of conversion of energy from the environment to an organism’s offspring). Specifically tested is the prediction that the regression of life-history variables on body size will change slope and sign about an ‘optimum’ body mass of 100 g.
2. Life-history data from the mammalian order Insectivora have been collated and analysed using a phylogenetic comparative method to test this prediction.
3. The analyses showed little evidence for significant changes in slope or sign around 100 g body mass, or other possible optimal body masses, contradicting the predictions of the model. These findings agree with those of similar analyses on life-history variables of bats.

Hybrid prediction method for solar power using different computational intelligence algorithms

Computational Intelligence (CI) holds the key to the development of smart grid to overcome the challenges of planning and optimization through accurate prediction of Renewable Energy Sources (RES). This paper presents an architectural framework for the construction of hybrid intelligent predictor for solar power. This research investigates the applicabil- ity of heterogeneous regression algorithms for 6 hour ahead solar power availability forecasting using historical data from Rockhampton, Australia. Real life solar radiation data is collected across six years with hourly resolution from 2005 to 2010. We observe that the hybrid prediction method is suitable for a reliable smart grid energy management. Prediction reliability of the proposed hybrid prediction method is carried out in terms of prediction error performance based on statistical and graphical methods. The experimental results show that the proposed hybrid method achieved acceptable prediction accuracy. This potential hybrid model is applicable as a local predictor for any proposed hybrid method in real life application for 6 hours in advance prediction to ensure constant solar power supply in the smart grid operation.

Predicting psychological and subjective well-being from personality: incremental prediction from 30 facets over the Big 5

This study investigated the relationship between the Big 5, measured at factor and facet levels, and dimensions of both psychological and subjective well-being. Three hundred and thirty-seven participants completed the 30 Facet International Personality Item Pool Scale, Satisfaction with Life Scale, Positive and Negative Affectivity Schedule, and Ryff’s Scales of Psychological Well-Being. Cross-correlation decomposition presented a parsimonious picture of how well-being is related to personality factors. Incremental facet prediction was examined using double-adjusted r2 confidence intervals and semi-partial correlations. Incremental prediction by facets over factors ranged from almost nothing to a third more variance explained, suggesting a more modest incremental prediction than presented in the literature previously. Examination of semi-partial correlations controlling for factors revealed a small number of important facet-well-being correlations. All data and R analysis scripts are made available in an online repository.

Machine-learning prediction of cancer survival: a retrospective study using electronic administrative records and a cancer registry

Using the prediction of cancer outcome as a model, we have tested the hypothesis that through analysing routinely collected digital data contained in an electronic administrative record (EAR), using machine-learning techniques, we could enhance conventional methods in predicting clinical outcomes.