Finite strains fully coupled analysis of a horizontal wellbore drilled through a porous rock formation

Wellbore instability, in particular in deep perforations, continues to be one of the major problem in the oil and gas industry, that can dramatically increase production costs. Eventual instabilities may be prevented supporting temporarily the wellbore with mud circulation. If instability may occur, the value of the mud pressure needs to be sufficiently high to prevent compressional failure, but it should also be lower than a critical value that would cause tensile failure and unintentional hydraulic fracturing. Predicting faithfully the stress distribution around a borehole, and moreover the yielding and failure zones, is a challenging but fundamental task, essential to estimate the correct mud pressure and hence to prevent instabilities and sand production. This study focuses on quantifying the pressure distribution, stress field and plastic zones around a horizontal borehole drilled at great depth through a highly porous rock formation. The perforation of a wellbore in a saturated porous material is a coupled problem, which involves deformations of the solid phase and simultaneous diffusion of the fluid phase. A fully coupled finite element method is adopted, considering both material non linearity (elastoplasticity) and geometric nonlinearity (finite deformations) in the solid matrix, resulting in a so called u−p formulation. The variation of porosity and permeability, as consequence of the finite deformations of the solid matrix, is taken into account. The model adopts an elastoplastic constitutive law characterized by two yield surfaces, that is able to capture the dilatant and compactant plastic mechanism. The simulations investigate the quasi-static transient phenomenon associated with the perforation, until the steady state condition is reached. The model describes the evolution of the stress and pressure distribution, and moreover the propagation of the plastic zones around the borehole. The work demonstrates the capability of the finite deformations coupled approach to simulate the whole process, giving an instrument to determine the stability and sand production of the wellbore

Contact-damage coupled modelling of FRP reinforcements under variable loading times

In the last years FRP (Fiber Reinforced Polymer) technology has been developed to repair damaged concrete structures. In this work it is proposed to investigate the complex mechanism of stress-strain evolution at the FRP interface, during different loading programs (short or long-time loadings), until complete debonding. This study has been performed by means of a fully threedimensional approach within the context of damage mechanics, to appropriately catch transversal effects as well as normal stresses, developing a realistic and comprehensive study of the delamination process. The adhesion properties have been reconstructed through a contact model incorporating an elastic-damage constitutive law, relating inter-laminar stresses acting in the sliding direction. A F.E. research code (FRPCON) has been developed, including a numerical procedure accounting for Mazars’s damage law inside the contact algorithm. The code is able to describe the delamination process considering the different surface preparation of the concrete part as well. The long-time behaviour of these composite structures has been studied by means of two visco-elastic formulations: i) Bazant’s B3 law has been considered for the concrete component, where creep effect is composed by three different terms, i.e. the elastic part, basic creep and drying creep; ii) for FRP’s fibres and matrix a micromechanical approach has been implemented. The experimental results of long-time bending tests have been used to calibrate and validate the numerical models

On exploiting Data Visualization and IoT for Increasing Sustainability and Safety in a Smart Campus

In a world that is getting increasingly digital and interconnected, and where more and more physical objects are integrated into the information network (Internet of Things, IoT), Data Visualization can facilitate the understanding of huge volumes of data. In this paper, we present the design and implementation of a testbed where IoT and Data Visualization have been exploited to increase the sustainability and safety of the Cesena (Smart) Campus. In particular, we detail the overall system architecture and the interactive dashboard that facilitates the management of the campus premises and the timetabling. Exploiting our system, we show how we can improve the campus sustainability (in terms of energy saving) and safety (considering the COVID-19 restrictions and regulations)

On supporting university communities in indoor wayfinding: An inclusive design approach

Mobility can be defined as the ability of people to move, live and interact with the space. In this context, indoor mobility, in terms of indoor localization and wayfinding, is a relevant topic due to the challenges it presents, in comparison with outdoor mobility, where GPS is hardly exploited. Knowing how to move in an indoor environment can be crucial for people with disabilities, and in particular for blind users, but it can provide several advantages also to any person who is moving in an unfamiliar place. Following this line of thought, we employed an inclusive by design approach to implement and deploy a system that comprises an Internet of Things infrastructure and an accessible mobile application to provide wayfinding functions, targeting the University community. As a real word case study, we considered the University of Bologna, designing a system able to be deployed in buildings with different configurations and settings, considering also historical buildings. The final system has been evaluated in three different scenarios, considering three different target audiences (18 users in total): i. students with disabilities (i.e., visual and mobility impairments); ii. campus students; and iii. visitors and tourists. Results reveal that all the participants enjoyed the provided functions and the indoor localization strategy was fine enough to provide a good wayfinding experience

Aggregate behaviour in concrete materials under high temperature conditions

Concrete under high temperature conditions is a topic of wide interest for applications in several engineering fields, from nuclear to civil as well as building engineering

Designing human-centric software artifacts with future users: a case study

The quality and quantity of participation supplied by human beings during the different phases of the design and development of a software artifact are central to studies in human-centered computing. With this paper, we have investigated on what kind of experienced people should be engaged to design a new computational artifact, when a participatory approach is adopted. We compared two approaches: the former including only future users (i.e., novices) in the design process, and the latter enlarging the community to expert users. We experimented with the design of a large software artifact, in use at the University of Bologna, engaging almost 1500 users. Statistical methodologies were employed to validate our findings. Our analysis has provided mounting evidence that expert users have contributed to the design of the artifact only by a small amount. Instead, most of the innovative initiatives have come from future users, thus surpassing some traditional limitations that tend to exclude future users from this kind of processes. We here challenge the traditional opinion that expert users provide typically a more reliable contribution in a participatory software design process, demonstrating instead that future users would be often better suited. Along this line of sense, this is the first paper, in the field of human-centric computing, that discusses the relevant question to offer to future users a larger design space, intended as a higher level of freedom given in a software design situation, demarcated by precise design constraints. In this sense, the outcome has been positiv

Numerical modelling of ellipsoidal inclusions

Within the framework of numerical algorithms for the threedimensional random packing of granular materials this work presents an innovative formulation for polydispersed ellipsoidal particles, including an overlapping detection algorithm for an optimized simulation of the mesostructure of geomaterials, particularly concrete. Granular composite cement-based materials can be so reconstructed with adequate precision in terms of grain size distribution. Specifically, the algorithm performance towards the assumed inclusion shape (ellipsoidal or spheric) and degree of regularity (round or irregular) is here discussed. Examples on real grading curves prove that this approach is effective. The advantages of the proposed method for computational mechanics purposes are also disclosed when properly interfaced with visualization CAD (Computer Aided Design) tools

Variability of three-dimensional forces increase during experimental knee pain

Knee pain is a common symptom of different knee pathologies, affecting muscle strength and force generation. Although the control of precise three-dimensional forces is essential for the performance of functional tasks, current evidence of pain effects in force variability is limited to single-directional assessments of contractions at moderate force levels. This study assessed the effects of experimental knee joint pain in the three-dimensional force variability during isometric knee extensions at a wide range of target forces (2.5-80 % of maximal voluntary contraction, MVC). Fifteen healthy subjects performed contractions before, immediately following, and after injections of hypertonic (painful) or isotonic (control) saline into the infrapatellar fat pad. Pain intensity was measured on a 10-cm visual analogue scale. Force magnitude, direction, and variability were assessed using a six-axis force sensor while activity of quadriceps and hamstring muscles was recorded by surface electromyography. Significant correlation was found between tangential force displacements and variability of quadriceps muscle activity. Experimental knee pain increased the variability of the task-related force component at all force levels, while variability of tangential force components increased at low forces (≤5 % of MVC). The mean quadriceps activity decreased during painful contractions only at 80 % of MVC. Pain adaptations underlying increased force variability at low contraction levels probably involve heterogeneous reorganization of muscle activity, which could not be detected by surface electrodes. These findings indicate a less efficient motor strategy during knee joint pain, suggesting that pain relief may enhance training for the control of smooth forces by knee pain patients

On combining Big Data and machine learning to support eco-driving behaviours

A conscious use of the battery is one of the key elements to consider while driving an electric vehicle. Hence, supporting the drivers, with information about it, can be strategic in letting them drive in a better way, with the purpose of optimizing the energy consumption. In the context of electric vehicles, equipped with regenerative brakes, the driver\u2019s braking style can make a significant difference. In this paper, we propose an approach which is based on the combination of big data and machine learning techniques, with the aim of enhancing the driver\u2019s braking style through visual elements (displayed in the vehicle dashboard, as a Human\u2013Machine Interface), actuating eco-driving behaviours. We have designed and developed a system prototype, by exploiting big data coming from an electric vehicle and a machine learning algorithm. Then, we have conducted a set of tests, with simulated and real data, and here we discuss the results we have obtained that can open interesting discussions about the use of big data, together with machine learning, so as to improve drivers\u2019 awareness of eco-behaviours