Experimental evidence of flow destabilization in a 2D bidisperse foam

Liquid foam flows in a Hele-Shaw cell were investigated. The plug flow obtained for a monodisperse foam is strongly perturbed in the presence of bubbles whose size is larger than the average bubble size by an order of magnitude at least. The large bubbles migrate faster than the mean flow above a velocity threshold which depends on its size. We evidence experimentally this new instability and, in case of a single large bubble, we compare the large bubble velocity with the prediction deduced from scaling arguments. In case of a bidisperse foam, an attractive interaction between large bubbles induces segregation and the large bubbles organize themselves in columns oriented along the flow. These results allow to identify the main ingredients governing 2D polydisperse foam flows

Managerial decisions to recover from Covid-19 disruption: A multi-objective optimization approach applied to public transport operators

The resilience of transport systems, facing natural or man-made disruptions, has been widely discussed in literature in terms of recovery capabilities concerning infrastructures, suggesting solutions to provide users an acceptable level of service along the interrupted network. However, in the context of the Covid-19 outbreak, the disruption has stressed the resilience of transport systems not on the supply side but rather at organizational level for transport service providers. Indeed, the sudden and drastic decrease in users due to the restrictions imposed by governments to limit the pandemic spread has implicated severe economic consequences in the running of transport companies. In this paper, attention has been focused on the public transport sector to analyse the effects of different initiatives, which companies could undertake in response to the demand shock caused by the Covid-19 emergency. Notably, an optimization procedure has been developed with the aim of determining feasible Pareto-front solutions, which correspond to trade-off conditions for the concurrent maximization of the company profit and the minimization of outsourcing services. The time span necessary to implement the examined recovery measures has been considered together with the limitation to appropriate threshold values for the main cost and income items influencing the company operations management. The proposed approach has been applied to the case study of an Italian public transport company to appraise different post-Covid-19 resilience strategies

A New Multi-objective Solution Approach Using ModeFRONTIER and OpenTrack for Energy-Efficient Train Timetabling Problem

Trains move along the railway infrastructure according to specific timetables. The timetables are based on the running time calculation and they are usually calculated without considering explicitly energy consumption. Since green transportation is becoming more and more important from environmental perspectives, energy consumption minimization could be considered also in timetable calculation. In particular, the Energy-Efficient Train Timetabling Problem (EETTP) consists in the energy-efficient timetable calculation considering the trade-off between energy efficiency and running times. In this work, a solution approach to solve a multi-objective EETTP is described in which the two objectives are the minimization of both energy consumption and the total travel time. The approach finds the schedules to guarantee that the train speed profiles minimize the objectives. It is based on modeFRONTIER and OpenTrack that are integrated by using the OpenTrack Application Programming Interface in a modeFRONTIER workflow. In particular, the optimization is made by modeFRONTIER, while the calculation of the train speed profiles, energy consumption and total travel time is made by OpenTrack. The approach is used with Multi-objective Genetic Algorithm-II and the Non-dominating Sorting Genetic-II, which are two genetic algorithms available in modeFRONTIER. The solution approach is tested on a case study that represents a real situation of metro line in Turkey. For both algorithms, a Pareto Front of solution which are a good trade-off between the objectives are reported. The results show significant reduction of both energy consumption and total travel time with respect to the existing timetable

Computational modeling: valuable tool or math exercise?

ABSTRACT Optimization techniques have been used in engineering design for decades maximizing a specific performance metric, ultimately cost of a product for a given performance. As a matter of fact most accepted theories of market efficiency for the past half century have focused on the single objective of maximizing the profit. The well known concept of Pareto Frontier has been used mainly to explain that at high risk corresponds a high reward and therefore any \u201cnon dominated\u201d solution is equivalent. More recently it has become widely accepted that a multi-objective approach is necessary for a more efficient decision making process about product development with sustainability in mind. However a number of numerical technologies commonly grouped under the term \u201cdesign optimization\u201d can be used not only for product design but also to improve the quality in the modeling cof complex phenomena. The design practice has therefore become an iterative process where decision making is performed on the basis of the compromise solutions quantitatively determined or estimated and the optimization methods are used for building the model, design a component or with high ambition face the product design at system level. Through the description of practical examples the use of optimization for model calibration, for component design and finally for product design will be illustrated

Towards Automatic Crack Size Estimation with iFEM for Structural Health Monitoring

The inverse finite element method (iFEM) is a model-based technique to compute the displacement (and then the strain) field of a structure from strain measurements and a geometrical discretization of the same. Different literature works exploit the error between the numerically reconstructed strains and the experimental measurements to perform damage identification in a structural health monitoring framework. However, only damage detection and localization are performed, without attempting a proper damage size estimation. The latter could be based on machine learning techniques; however, an a priori definition of the damage conditions would be required. To overcome these limitations, the present work proposes a new approach in which the damage is systematically introduced in the iFEM model to minimize its discrepancy with respect to the physical structure. This is performed with a maximum likelihood estimation framework, where the most accurate damage scenario is selected among a series of different models. The proposed approach was experimentally verified on an aluminum plate subjected to fatigue crack propagation, which enables the creation of a digital twin of the structure itself. The strain field fed to the iFEM routine was experimentally measured with an optical backscatter reflectometry fiber and the methodology was validated with independent observations of lasers and the digital image correlation

Service Engagement: Psychopathology, Recovery Style and Treatments

The aim of the present study is to evaluate how recovery style, a set of strategies used by patients to interact with services and therapists, and the severity of psychotic symptoms affect the quality/continuity of taking charge of each patient. 156 psychotic patients at different stages of illness were enrolled. Sociodemographic and clinical data were collected and integration/sealing-Over Scale, Recovery Style Questionnaire and Positive and Negative Syndrome Scale were administered. Patients were distinguished into four groups according to the type of treatment received: clinical package, hospital package, day-care package, and residential package. A positive correlation between the cost of psychiatric performance and psychopathological severity (measured with PANSS scores) was identified. No association emerged between ISOS/RSQ total scores and costs. The sanitary expenditure appears to be linked to positive psychotic symptoms while lower performances are given for the treatment of patients with predominant negative symptoms. Recovery style itself has not a direct influence on the quantity/quality of psychiatric services

Digital Technologies for Transport and Mobility: Challenges, Trends and Perspectives

This white paper aims at presenting the ideas emerging from the different fields pertaining to transport and mobility, to describe the capacities of current state-of-the-art digital technologies and the perspectives that are expected to shape the future of transport and mobility

Robust design optimisation of dynamical space systems

In this paper we present a novel approach to the optimisation of complex systems affected by epistemic uncertainty when system and uncertainty evolve dynamically with time; we propose a new modelling approach that uses Evidence Theory to capture epistemic uncertainty A system is considered which is affected by the time during the operational life (failure rate, performance degradation, function degradation, etc.). The goal is to obtain a resilient design: robust with respect to performance variability and reliable against possible partial failures of one or more components. We propose to enhance the Evidence Network Model (ENM) with time-dependent reliability functions and decompose the problem into subproblems of smaller complexity. Through this decomposition uncertainty quantification of complex systems becomes affordable for a range of real-world applications. The method is here applied to a simple resource allocation problem where the goal is to optimally position subsystems within a spacecraft [1