A cellular automaton for the factor of safety field in landslides modeling

Landslide inventories show that the statistical distribution of the area of recorded events is well described by a power law over a range of decades. To understand these distributions, we consider a cellular automaton to model a time and position dependent factor of safety. The model is able to reproduce the complex structure of landslide distribution, as experimentally reported. In particular, we investigate the role of the rate of change of the system dynamical variables, induced by an external drive, on landslide modeling and its implications on hazard assessment. As the rate is increased, the model has a crossover from a critical regime with power-laws to non power-law behaviors. We suggest that the detection of patterns of correlated domains in monitored regions can be crucial to identify the response of the system to perturbations, i.e., for hazard assessment.Comment: 4 pages, 3 figure

Development of predicting model for safety behaviour based on safety psychology and working environment

The increasing trend of occupational accident due to unsafe act and unsafe condition especially in construction site suggests the need for more proactive safety assessment model. Therefore this research aimed to establish a prediction model of safety behaviour based on safety psychology and working environment factors in construction site. Theory of Planned Behaviour (TpB) was adapted to examine on the prediction model of safety behaviour among construction workers using safety psychology representing unsafe act and working environment factors representing unsafe condition. A modified perception questionnaire named Safety Psychometric Model (SPM) was proposed based on TpB questionnaire and safety attitude questionnaire (SQA). Previously, the approach has successfully applied in health care and manufacturing sector. The questionnaire has been validated by three industrial and academic experts. A total of 554 respondents among 92 construction site were selected as the subjects for analysis. Structural Equation Modelling (SEM) and Statistical Package for the Social Science (SPSS) was use for analysis purpose which involve correlation, regression and structural equation analysis. The results demonstrated that safety psychology and work environment factor was related positively with safety behaviour intention. The elements of workers’ attitude, subjective norm and perceived control that form the safety psychology context found to be significantly has the ability to predict safety behaviour. The demographics variances of personal and education background, working experiences and training background also determine as the factors of safety behaviour of the construction workers. The research also successfully established a safety behaviour prediction model that named Safety Psychometric Model. The model can be benefited by safety practitioners, organizations and researchers to explore the safety behaviour prediction. It also enhanced the knowledge in the area of employee behaviour prediction and modelling

Tokamak MHD equilibria with reversed magnetic shear and sheared flow

Analytic solutions of the magnetohydrodynamic equilibrium equations for a cylindrically symmetric magnetically confined plasma with reversed magnetic shear, s < 0, and sheared flow are constructed by prescribing the safety factor-, poloidal velocity- and axial velocity- profiles consistently with experimental ones

A study of stability analysis of pyroclastic covers based on electrical resistivity measurements

Usually, the degree of stability of a slope is quantified by the Factor of Safety whose values depend on physical and mechanical soil properties analyzed on samples of much reduced sizes or referring to very small soil volumes around porous probes. To overcome the limit of punctual information, we propose a semi-empirical approach based on the use of geophysical methods and the employment of a geophysical Factor of Safety recently introduced by the authors in terms of local resistivities and slope angles. In this paper, we show an application of our proposal on a test area of about 2000 m2 on Sarno Mountains (Campania Region - Southern Italy), where shallow landslides involving pyroclastic soils periodically occur triggered by critical rainfall events. Starting from two resistivity tomography surveys performed on the test area in autumn and spring, we obtained maps of the geophysical Factor of Safety at different depths for the two seasons. We also estimated the values of the Factor of Safety by using the infinite slope model in the dry and saturated scenario. A comparison between the values of the geophysical and geotechnical Factor of Safety shows advantages and disadvantages of our approach.Comment: 16 pages, 5 figure