Numerical investigation of the performance of engineered barriers in controlling stormwater runoff

In this paper, 2-dimensional, hydro-mechanically coupled finite element analyses are conducted to assess the performance of an engineered barrier, constructed from natural geomaterials, aimed at reducing flood risk in urban environments. The barrier consists of an unsaturated compacted soil layer with water holding properties and a drainage layer of a coarse granular material, that acts as a capillary break, and is constructed on top of the natural soil, in this case London clay. The barrier is vegetated so that its water storage capacity is renewed after each rainfall event. Sophisticated boundary conditions are used to simulate the effect of precipitation and evapotranspiration. The evolution of the rainfall infiltration and runoff rate is simulated both for a treated soil column with an engineered barrier and an untreated one consisting solely of in-situ London Clay. The percolation rate of rainfall water from the bottom of the barrier is also estimated. This comparison highlights the effectiveness of the engineered barrier in reducing the risk of fast flooding, in preventing excessive deformations and in protecting underground infrastructure during wetting and drying cycles. The effect of the hydraulic properties and geometry of the barrier is investigated by means of an extensive parametric analysis. Finally, recommendations for the design of barrier systems are made

‘Challenging’ doesn’t sum it up: Exploring probation practitioners’ experiences managing high-risk individuals during the COVID-19 pandemic

The COVID-19 pandemic has been, and still is, a worldwide health crisis. Despite the surge of literature on this phenomenon, little research has been conducted with the Probation Service during this time. The aim of this research was to explore Probation Practitioners’ (PPs’) experiences of the COVID-19 restrictions with a specific focus on those who access the Psychologically Informed Consultation Service (PICS). Further, to explore the experiences of key aspects of the COVID-19 pandemic through the lens of the Community Offender Personality Disorder Service. Semi-structured interviews were conducted with 9 PPs who represented a broad cross-section in terms of age and years of experience in the role. Interpretative Phenomenological Analysis was used to explore the experiences of PPs and revealed 5 main themes: unmet support needs, problematic working environments, an emotionally distressing time, the use of PICS, and a silver lining. These findings are discussed with implications for further research

A particle swarm optimization based memetic algorithm for dynamic optimization problems

Copyright @ Springer Science + Business Media B.V. 2010.Recently, there has been an increasing concern from the evolutionary computation community on dynamic optimization problems since many real-world optimization problems are dynamic. This paper investigates a particle swarm optimization (PSO) based memetic algorithm that hybridizes PSO with a local search technique for dynamic optimization problems. Within the framework of the proposed algorithm, a local version of PSO with a ring-shape topology structure is used as the global search operator and a fuzzy cognition local search method is proposed as the local search technique. In addition, a self-organized random immigrants scheme is extended into our proposed algorithm in order to further enhance its exploration capacity for new peaks in the search space. Experimental study over the moving peaks benchmark problem shows that the proposed PSO-based memetic algorithm is robust and adaptable in dynamic environments.This work was supported by the National Nature Science Foundation of China (NSFC) under Grant No. 70431003 and Grant No. 70671020, the National Innovation Research Community Science Foundation of China under Grant No. 60521003, the National Support Plan of China under Grant No. 2006BAH02A09 and the Ministry of Education, science, and Technology in Korea through the Second-Phase of Brain Korea 21 Project in 2009, the Engineering and Physical Sciences Research Council (EPSRC) of UK under Grant EP/E060722/01 and the Hong Kong Polytechnic University Research Grants under Grant G-YH60

Sibling relationships and family functioning in siblings of early adolescents, adolescents and young adults with autism spectrum disorder

The purpose of the study was to investigate how family functioning (defined as the ability that family members hold to manage stressful events, and intimate and social relationships), the degree to which family members feel happy and fulfilled with each other (called family satisfaction), and the demographical characteristics of siblings (age and gender) impacted on sibling relationships. The Circumplex Model of Marital and Family Systems and Behavioral Systems constituted the theoretical frameworks that guided our study. Eighty-six typically developing adolescents and young adults having a sister or a brother with autism spectrum disorder were enrolled. Results indicated that the youngest age group (early adolescents) reported to engage more frequently in negative behaviors with their siblings with ASD than the two older age groups (middle adolescents and young adults). No significant differences were found among the three age groups regarding behaviors derived from attachment, caregiving and affiliative systems. Family satisfaction and age significantly predicted behaviors during sibling interactions. Suggestions on prevention and intervention programs were discussed in order to prevent parentification among typically developing siblings and decrease episodes of quarrels and overt conflicts between brothers and sisters with and without AS

Understanding offender managers’ views and experiences of psychological consultations

Few studies have investigated the effectiveness of the psychological consultation process specifically for offender managers. This study involves a total of 23 offender managers’ views and perceptions of the consultation process within four areas of the North West of England. Within each location, a focus group was conducted involving between four and eight participants and interpretative phenomenological analysis was used to analyse the responses. The analysis revealed four main themes: validation of thoughts, feelings and practice; professional support; a personal touch; and room for improvement. These findings are discussed along with implications for further research

Comparison of two-phase pipe flow in openFOAM with a mechanistic model

Two-phase pipe flow is a common occurrence in many industrial applications such as power generation and oil and gas transportation. Accurate prediction of liquid holdup and pressure drop is of vast importance to ensure effective design and operation of fluid transport systems. In this paper, a Computational Fluid Dynamics (CFD) study of a two-phase flow of air and water is performed using OpenFOAM. The two-phase solver, interFoam is used to identify flow patterns and generate values of liquid holdup and pressure drop, which are compared to results obtained from a two-phase mechanistic model developed by Petalas and Aziz (2002). A total of 60 simulations have been performed at three separate pipe inclinations of 0°, +10° and -10° respectively. A three dimensional, 0.052m diameter pipe of 4m length is used with the Shear Stress Transport (SST) k - turbulence model to solve the turbulent mixtures of air and water. Results show that the flow pattern behaviour and numerical values of liquid holdup and pressure drop compare reasonably well to the mechanistic model

Feasibility and dominance rules in the electromagnetism-like algorithm for constrained global optimization

This paper presents the use of a constraint-handling technique, known as feasibility and dominance rules, in a electromagnetismlike (ELM) mechanism for solving constrained global optimization problems. Since the original ELM algorithm is specifically designed for solving bound constrained problems, only the inequality and equality constraints violation together with the objective function value are used to select points and to progress towards feasibility and optimality. Numerical experiments are presented, including a comparison with other methods recently reported in the literature

An artificial fish swarm filter-based Method for constrained global optimization

Ana Maria A.C. Rocha, M. Fernanda P. Costa and Edite M.G.P. Fernandes, An Artificial Fish Swarm Filter-Based Method for Constrained Global Optimization, B. Murgante, O. Gervasi, S. Mirsa, N. Nedjah, A.M. Rocha, D. Taniar, B. Apduhan (Eds.), Lecture Notes in Computer Science, Part III, LNCS 7335, pp. 57–71, Springer, Heidelberg, 2012.An artificial fish swarm algorithm based on a filter methodology for trial solutions acceptance is analyzed for general constrained global optimization problems. The new method uses the filter set concept to accept, at each iteration, a population of trial solutions whenever they improve constraint violation or objective function, relative to the current solutions. The preliminary numerical experiments with a wellknown benchmark set of engineering design problems show the effectiveness of the proposed method.Fundação para a Ciência e a Tecnologia (FCT