Undrained sediment loading key to long-runout submarine mass movements : evidence from the Caribbean Volcanic Arc

Long undersea debris runout can be facilitated by a boundary layer formed by weak marine sediments under a moving slide mass. Undrained loading of such offshore sediment results in a profound drop of basal shear resistance, compared to subaerial shear resistance, enabling long undersea runout. Thus large long-runout submarine landslides are not truly enigmatic (Voight and Elsworth 1992, 1997), but are understandable in terms of conventional geotechnical principles. A corollary is that remoulded undrained strength, and not friction angle, should be used for basal resistance in numerical simulations. This hypothesis is testable via drilling and examining the structure at the soles of undersea debris avalanches for indications of incorporation of sheared marine sediments, by tests of soil properties, and by simulations. Such considerations of emplacement process are an aim of ongoing research in the Lesser Antilles (Caribbean Sea), where multiple offshore debris avalanche and dome-collapse debris deposits have been identified since 1999 on swath bathymetric surveys collected in five oceanographic cruises. This paper reviews the prehistoric and historic collapses that have occurred offshore of Antilles arc islands and summarizes ongoing research on emplacement processes.

Evidence for carbonate platform failure during rapid sea-level rise; ca 14 000 year old bioclastic flow deposits in the Lesser Antilles

Bioclastic flow deposits offshore from the Soufrie`re Hills volcano on Montserrat in the Lesser Antilles were deposited by the largest volume sediment flows near this active volcano in the last 26 kyr. The volume of these deposits exceeds that of the largest historic volcanic dome collapse in the world, which occurred on Montserrat in 2003. These flows were most probably generated by a large submarine slope failure of the carbonate shelf comprising the south west flank of Antigua or the east flank of Redonda; adjacent islands that are not volcanically active. The bioclastic flow deposits are relatively coarse-grained and either ungraded or poorly graded, and were deposited by non cohesive debris flow and high density turbidity currents. The bioclastic deposit often comprises multiple sub-units that cannot be correlated between core sites; some located just 2 km apart. Multiple sub-units in the bioclastic deposit result from either flow reflection, stacking of multiple debris flow lobes, and/or multi-stage collapse of the initial landslide. This study provides unusually precise constraints on the age of this mass flow event that occurred at ca 14 ka. Few large submarine landslides have been well dated, but the slope failures that have been dated are commonly associated with periods of rapid sea-level change.

Rough fuzzy control of SVC for power system stability enhancement

This paper presents a new approach to the design of a rough fuzzy controller for the control loop of the SVC (static VAR system) in a two area power system for stability enhancement with particular emphasis on providing effective damping for oscillatory instabilities. The performances of the rough fuzzy and the conventional fuzzy controller are compared with that of the conventional PI controller for a variety of transient disturbances, highlighting the effectiveness of the rough fuzzy controller in damping the inter-area oscillations. The effect of the rough fuzzy controller in improving the CCT (critical clearing time) of the two area system is elaborated in this paper as well.

Traffic-related fine and ultrafine particle exposures of professional drivers and illness : An opportunity to better link exposure science and epidemiology to address an occupational hazard?

Exposures to traffic-related air pollution (TRAP) can be particularly high in transport microenvironments (i.e. in and around vehicles) despite the short durations typically spent there. There is a mounting body of evidence that suggests that this is especially true for fine (b2.5 μm) and ultrafine (b100 nm, UF) particles. Professional drivers, who spend extended periods of time in transport microenvironments due to their job, may incur exposures markedly higher than already elevated non-occupational exposures. Numerous epidemiological studies have shown a raised incidence of adverse health outcomes among professional drivers, and exposure to TRAP has been suggested as one of the possible causal factors. Despite this, data describing the range and determinants of occupational exposures to fine and UF particles are largely conspicuous in their absence. Such information could strengthen attempts to define the aetiology of professional drivers' illnesses as it relates to traffic combustion-derived particles. In this article, we suggest that the drivers' occupational fine and UF particle exposures are an exemplar case where opportunities exist to better link exposure science and epidemiology in addressing questions of causality. The nature of the hazard is first introduced, followed by an overview of the health effects attributable to exposures typical of transport microenvironments. Basic determinants of exposure and reduction strategies are also described, and finally the state of knowledge is briefly summarised along with an outline of the main unanswered questions in the topic area.

Evaluating stakeholder satisfaction during public participation in major infrastructure and construction projects : a fuzzy approach

Numerous different and sometimes discrepant interests can be affected, both positively and negatively, throughout the course of a major infrastructure and construction (MIC) project. Failing to address and meet the concerns and expectations of the stakeholders involved has resulted in many project failures. One way to address this issue is through a participatory approach to project decision making. Whether the participation mechanism is effective or not depends largely on the client/owner. This paper provides a means of systematically evaluating the effectiveness of the public participation exercise, or even the whole project, through the measurement of stakeholder satisfaction. Since the process of satisfaction measurement is complicated and uncertain, requiring approximate reasoning involving human intuition, a fuzzy approach is adopted. From this, a multi-factor hierarchical fuzzy comprehensive evaluation model is established to facilitate the evaluation of satisfaction in both single stakeholder group and overall MIC project stakeholders.

Increasing disaster resilience of people and property through fostering collaboration in coastal high hazard zones

As evidenced with the 2011 floods the state of Queensland in Australia is quite vulnerable to this kind of disaster. Climate change will increase the frequency and magnitude of such events and will have a variety of other impacts. To deal with these governments at all levels need to be prepared and work together. Since most of the population of the state is located in the coastal areas and these areas are more vulnerable to the impacts of climate change this paper examines climate change adaptation efforts in coastal Queensland. The paper is part of a more comprehensive project which looks at the critical linkages between land use and transport planning in coastal Queensland, especially in light of increased frequencies of cyclonic activity and other impacts associated with climate change. The aim is improving coordination between local and state government in addressing land use and transport planning in coastal high hazard areas. By increasing the ability of local governments and state agencies to coordinate planning activities, we can help adapt to impacts of climate change. Towards that end, we will look at the ways that these groups currently interact, especially with regard to issues involving uncertainty related to climate change impacts. Through surveys and interviews of Queensland coastal local governments and state level planning agencies on how they coordinate their planning activities at different levels as well as how much they take into account the linkage of transportation and land use we aim to identify the weaknesses of the current planning system in responding to the challenges of climate change adaptation. The project will identify opportunities for improving the ways we plan and coordinate planning, and make recommendations to improve resilience in advance of disasters so as to help speed up recovery when they occur.

Visual motion perception predicts driving hazard perception ability

PURPOSE: To examine the basis of previous findings of an association between indices of driving safety and visual motion sensitivity and to examine whether this association could be explained by low-level changes in visual function. METHODS: 36 visually normal participants (aged 19 – 80 years), completed a battery of standard vision tests including visual acuity, contrast sensitivity and automated visual fields. and two tests of motion perception including sensitivity for movement of a drifting Gabor stimulus, and sensitivity for displacement in a random-dot kinematogram (Dmin). Participants also completed a hazard perception test (HPT) which measured participants’ response times to hazards embedded in video recordings of real world driving which has been shown to be linked to crash risk. RESULTS: Dmin for the random-dot stimulus ranged from -0.88 to -0.12 log minutes of arc, and the minimum drift rate for the Gabor stimulus ranged from 0.01 to 0.35 cycles per second. Both measures of motion sensitivity significantly predicted response times on the HPT. In addition, while the relationship involving the HPT and motion sensitivity for the random-dot kinematogram was partially explained by the other visual function measures, the relationship with sensitivity for detection of the drifting Gabor stimulus remained significant even after controlling for these variables. CONCLUSION: These findings suggest that motion perception plays an important role in the visual perception of driving-relevant hazards independent of other areas of visual function and should be further explored as a predictive test of driving safety. Future research should explore the causes of reduced motion perception in order to develop better interventions to improve road safety.

Frame-rate stereopsis using non-parametric transforms and programmable logic

A frame-rate stereo vision system, based on non-parametric matching metrics, is described. Traditional metrics, such as normalized cross-correlation, are expensive in terms of logic. Non-parametric measures require only simple, parallelizable, functions such as comparators, counters and exclusive-or, and are thus very well suited to implementation in reprogrammable logic.

Motorcycle Safety Research Project Interim Summary Report 3 : Training and Licensing Interventions for Risk Taking and Hazard Perception for Motorcyclists

Motorcycle trauma is a serious road safety issue in Queensland and throughout Australia. In 2009, Queensland Transport (later Transport and Main Roads or TMR) appointed CARRS-Q to provide a three-year program of Road Safety Research Services for Motorcycle Rider Safety. Funding for this research originated from the Motor Accident Insurance Commission. This program of research was undertaken to produce knowledge to assist TMR to improve motorcycle safety by further strengthening the licensing and training system to make learner riders safer by developing a pre-learner package (Deliverable 1), and by evaluating the QRide CAP program to ensure that it is maximally effective and contributes to the best possible training for new riders (Deliverable 2). The focus of this report is Deliverable 3 of the overall program of research. It identifies potential new licensing components that will reduce the incidence of risky riding and improve higher-order cognitive skills in new riders.

Asset health prediction using the explicit hazard model

The ability to estimate the asset reliability and the probability of failure is critical to reducing maintenance costs, operation downtime, and safety hazards. Predicting the survival time and the probability of failure in future time is an indispensable requirement in prognostics and asset health management. In traditional reliability models, the lifetime of an asset is estimated using failure event data, alone; however, statistically sufficient failure event data are often difficult to attain in real-life situations due to poor data management, effective preventive maintenance, and the small population of identical assets in use. Condition indicators and operating environment indicators are two types of covariate data that are normally obtained in addition to failure event and suspended data. These data contain significant information about the state and health of an asset. Condition indicators reflect the level of degradation of assets while operating environment indicators accelerate or decelerate the lifetime of assets. When these data are available, an alternative approach to the traditional reliability analysis is the modelling of condition indicators and operating environment indicators and their failure-generating mechanisms using a covariate-based hazard model. The literature review indicates that a number of covariate-based hazard models have been developed. All of these existing covariate-based hazard models were developed based on the principle theory of the Proportional Hazard Model (PHM). However, most of these models have not attracted much attention in the field of machinery prognostics. Moreover, due to the prominence of PHM, attempts at developing alternative models, to some extent, have been stifled, although a number of alternative models to PHM have been suggested. The existing covariate-based hazard models neglect to fully utilise three types of asset health information (including failure event data (i.e. observed and/or suspended), condition data, and operating environment data) into a model to have more effective hazard and reliability predictions. In addition, current research shows that condition indicators and operating environment indicators have different characteristics and they are non-homogeneous covariate data. Condition indicators act as response variables (or dependent variables) whereas operating environment indicators act as explanatory variables (or independent variables). However, these non-homogenous covariate data were modelled in the same way for hazard prediction in the existing covariate-based hazard models. The related and yet more imperative question is how both of these indicators should be effectively modelled and integrated into the covariate-based hazard model. This work presents a new approach for addressing the aforementioned challenges. The new covariate-based hazard model, which termed as Explicit Hazard Model (EHM), explicitly and effectively incorporates all three available asset health information into the modelling of hazard and reliability predictions and also drives the relationship between actual asset health and condition measurements as well as operating environment measurements. The theoretical development of the model and its parameter estimation method are demonstrated in this work. EHM assumes that the baseline hazard is a function of the both time and condition indicators. Condition indicators provide information about the health condition of an asset; therefore they update and reform the baseline hazard of EHM according to the health state of asset at given time t. Some examples of condition indicators are the vibration of rotating machinery, the level of metal particles in engine oil analysis, and wear in a component, to name but a few. Operating environment indicators in this model are failure accelerators and/or decelerators that are included in the covariate function of EHM and may increase or decrease the value of the hazard from the baseline hazard. These indicators caused by the environment in which an asset operates, and that have not been explicitly identified by the condition indicators (e.g. Loads, environmental stresses, and other dynamically changing environment factors). While the effects of operating environment indicators could be nought in EHM; condition indicators could emerge because these indicators are observed and measured as long as an asset is operational and survived. EHM has several advantages over the existing covariate-based hazard models. One is this model utilises three different sources of asset health data (i.e. population characteristics, condition indicators, and operating environment indicators) to effectively predict hazard and reliability. Another is that EHM explicitly investigates the relationship between condition and operating environment indicators associated with the hazard of an asset. Furthermore, the proportionality assumption, which most of the covariate-based hazard models suffer from it, does not exist in EHM. According to the sample size of failure/suspension times, EHM is extended into two forms: semi-parametric and non-parametric. The semi-parametric EHM assumes a specified lifetime distribution (i.e. Weibull distribution) in the form of the baseline hazard. However, for more industry applications, due to sparse failure event data of assets, the analysis of such data often involves complex distributional shapes about which little is known. Therefore, to avoid the restrictive assumption of the semi-parametric EHM about assuming a specified lifetime distribution for failure event histories, the non-parametric EHM, which is a distribution free model, has been developed. The development of EHM into two forms is another merit of the model. A case study was conducted using laboratory experiment data to validate the practicality of the both semi-parametric and non-parametric EHMs. The performance of the newly-developed models is appraised using the comparison amongst the estimated results of these models and the other existing covariate-based hazard models. The comparison results demonstrated that both the semi-parametric and non-parametric EHMs outperform the existing covariate-based hazard models. Future research directions regarding to the new parameter estimation method in the case of time-dependent effects of covariates and missing data, application of EHM in both repairable and non-repairable systems using field data, and a decision support model in which linked to the estimated reliability results, are also identified.

TS-fuzzy controlled DFIG based wind energy conversion system

This paper focuses on the implementation of the TS (Tagaki-Sugino) fuzzy controller for the active power and the DC capacitor voltage control of the Doubly Fed Induction Generator (DFIG) based wind generator. DFIG system is represented by a third-order model where electromagnetic transients of the stator are neglected. The effectiveness of the TS-fuzzy controller on the rotor speed oscillations and the DC capacitor voltage variations of the DFIG damping controller on converter ratings of the DFIG system is also investigated. The results of the time domain simulation studies are presented to elucidate the effectiveness of the TS-fuzzy controller compared with conventional PI controller in the DFIG system. The proposed TS-fuzzy controller can improve the fault ride through capability of DFIG compared to the conventional PI controller

Hazard based models for freeway traffic incident duration

Assessing and prioritising cost-effective strategies to mitigate the impacts of traffic incidents and accidents on non-recurrent congestion on major roads represents a significant challenge for road network managers. This research examines the influence of numerous factors associated with incidents of various types on their duration. It presents a comprehensive traffic incident data mining and analysis by developing an incident duration model based on twelve months of incident data obtained from the Australian freeway network. Parametric accelerated failure time (AFT) survival models of incident duration were developed, including log-logistic, lognormal, and Weibul-considering both fixed and random parameters, as well as a Weibull model with gamma heterogeneity. The Weibull AFT models with random parameters were appropriate for modelling incident duration arising from crashes and hazards. A Weibull model with gamma heterogeneity was most suitable for modelling incident duration of stationary vehicles. Significant variables affecting incident duration include characteristics of the incidents (severity, type, towing requirements, etc.), and location, time of day, and traffic characteristics of the incident. Moreover, the findings reveal no significant effects of infrastructure and weather on incident duration. A significant and unique contribution of this paper is that the durations of each type of incident are uniquely different and respond to different factors. The results of this study are useful for traffic incident management agencies to implement strategies to reduce incident duration, leading to reduced congestion, secondary incidents, and the associated human and economic losses.

The impact of legislation on divorce : a hazard function approach

The paper examines the impact of the introduction of no-fault divorce legislation in Australia. The approach used is rather novel, a hazard model of the divorce rate is estimated with the role of legislation captured via a time-varying covariate. The paper concludes that contrary to US empirical evidence, no-fault divorce legislation appears to have had a positive impact upon the divorce rate in Australia.

Video-based road commentary training improves hazard perception of young drivers in a dual task

This study used a video-based hazard perception dual task to compare the hazard perception skills of young drivers with middle aged, more experienced drivers and to determine if these skills can be improved with video-based road commentary training. The primary task required the participants to detect and verbally identify immediate hazard on video-based traffic scenarios while concurrently performing a secondary tracking task, simulating the steering of real driving. The results showed that the young drivers perceived fewer immediate hazards (mean = 75.2%, n = 24, 19 females) than the more experienced drivers (mean = 87.5%, n = 8, all females), and had longer hazard perception times, but performed better in the secondary tracking task. After the road commentary training, the mean percentage of hazards detected and identified by the young drivers improved to the level of the experienced drivers and was significantly higher than that of an age and driving experience matched control group. The results will be discussed in the context of psychological theories of hazard perception and in relation to road commentary as an evidence-based training intervention that seems to improve many aspects of unsafe driving behaviour in young drivers.

Community response to disasters in Indonesia : Gotong Royong; a double edged-sword

Indonesia is a country spread across wide-ranging archipelago, located in South East Asia between two oceans, the Indian and the Pacific. Indonesia is well known as an active tectonic region because it lies on top of three major active tectonic plates: the Eurasian in the North, the Indian Ocean-Australian in the South, and the Pacific plate in the East. The southern and eastern part of the country features a range of volcanic arcs, volcanic mountains, and lowlands with 500 young volcanoes, of which 128 are active and thus representing 15% of the world’s active volcanoes. In the period 2002-2007, approximately 1782 disasters occurred, with hundreds of thousands of lives lost and billions of rupiah in losses incurred: (Floods - 1183 instances, cyclones - 272 instances, and landslides - 252 instances). Of these, the 2004 Aceh tsunami and the 2006 central Java earthquake (impacting predominantly city and suburbs of Yogyakarta) were the most significant. Even so, disaster management experts believe lessons learnt from the two major natural disasters needs to be formalised into laws and institutions before another disaster occurs, regardless of the type of natural disaster – i.e. Volcano eruption or landslide; as opposed to tsunami or earthquake. Following in the wake of disasters occurring in Yogyakarta, many of its community members responded by banding together as one, with the determination of rebuilding its villages and cities through the spirit of ‘gotong royong’. The idea of social interaction; in particular as a collective, consensual, and cooperative nation; has predominantly formed the ideological basis of Indonesia’s societal nature. Many Indonesian terms cohere to this ideology, such as: ‘koperasi” (cooperatives as the basis of economic interactions), ‘musyawarah’ (consensual nature in decision making), and ‘gotong royong’ (mutual assistance). ‘Gotong royong’ has become a key cultural operator in Indonesia, in particular In Jogjakarta. Appropriately so as ‘gotong royong’ is depicted from the traditional Javanese village, where labour is accomplished through reciprocal exchange and the villagers are motivated by a general ethos of selfishness and concern for the common good. The culture of ‘gotong royong’ promotes positive values such as social harmony and mutual reciprocation in disaster-affected areas provides the necessary spirit needed to endure the hardships and for all involved. While gotong royong emphasises the positive notions of mutual family support and deep community level activity there is a potential for contrast against government lead disaster response and recovery management activities especially in settings where sporadic governance mechanisms exist and transparency and accountability in the recovery process of public infrastructure assets have been questioned. This paper thus questions whether Gotong Royong is a double-edged sword, and explores the potential marriage of community values and governance mechanisms for future disaster management planning and practice.