Swelling behaviour of compacted Maryland clay under different boundary conditions

This paper presents an experimental study on the swelling response of compacted Maryland clay specimens subjected to hydration under a range of boundary conditions. The research is multi-scale with swelling tests complemented by comprehensive mercury intrusion porosimetry analyses. The objective of the experimental programme is to establish the locus of final swollen states (in terms of void ratio and swelling pressure) and assess its robustness by testing a range of boundary conditions or combinations thereof. Five initial soil conditions were tested and swelling was generated by flooding or incremental suction reduction by way of the osmotic technique. The paper shows that, for a given soil condition, there is no influence of the stress–volume path on the final swollen state. This observation was corroborated at the microscopic level by the mercury intrusion porosimetry. It was concluded that the effect of different stiffness can actually be analysed in terms of the maximum stress applied to the specimen. In particular, a clear correlation was identified between the macroscopic strains and the confinement applied during the test, regardless of the boundary conditions. Also, the conceptual model relating the water ratio and micro void ratio proposed by E. Romero and co-workers in 2011 was found to prevail, regardless of the boundary conditions.Peer ReviewedPostprint (author's final draft

User quality of experience of mulsemedia applications

User Quality of Experience (QoE) is of fundamental importance in multimedia applications and has been extensively studied for decades. However, user QoE in the context of the emerging multiple-sensorial media (mulsemedia) services, which involve different media components than the traditional multimedia applications, have not been comprehensively studied. This article presents the results of subjective tests which have investigated user perception of mulsemedia content. In particular, the impact of intensity of certain mulsemedia components including haptic and airflow on user-perceived experience are studied. Results demonstrate that by making use of mulsemedia the overall user enjoyment levels increased by up to 77%

Augmented reality-assisted cloud additive manufacturing with digital twin technology for multi-stakeholder value Co-creation in product innovation

Industry 4.0, boosting the integration of sophisticated computational and manufacturing technologies, has profoundly reshaped the way to deal with market dynamics. It increases the capabilities of multi-stakeholders to engage in value co-creation for product innovation. Nonetheless, it also poses challenges to operation efficiency, i.e., surged requirements meeting expedited delivery times, in account of stakeholders’ diverse backgrounds and goals. To respond, by applying the technology of Digital Twin (DT), this study proposes an Augmented Reality-assisted Cloud Additive Manufacturing (AR-CAM) framework, establishing a sophisticated cyber-physical interface to cater to various coordinating interactions. By this means, it attempts to give a consistent understanding to multi-background stakeholders. A case study involving the fabrication of a speed rear derailleur is applied, thereby underscoring the validity of the AR-CAM framework

Response of different osmotic membranes and calibration of a coupled model capturing the temperature effect for the osmotic method

Reliable suction control is of paramount importance for experimental unsaturated soil mechanics. The osmotic method, based on polyethylene glycol (PEG) and semi-permeable membranes, is one of the possible methods to control suction. Although this method is quite simple to implement, reliable results can only be obtained with adequate calibration curves linking suction and PEG concentration, and a good understanding of the factors influencing the method. Several studies have investigated different aspects of this method, including the osmotic potential generated by given PEG concentrations, but the effect of temperature is not yet fully captured. This paper presents the results of a comprehensive study of the osmotic method looking at the long-term response of three different types of membranes, the effect of temperature, PEG molecular weight (MW) and the combination of different MW cut off (MWCO) on the calibration curves. Finally the data were used to calibrate a model capturing the temperature effect, in a coupled manner, in order to provide a robust calibration

Development and Validation of a New Near-Infrared Sensor to Measure Polyethylene Glycol (PEG) Concentration in Water

A near-infrared absorption based laser sensor has been designed and validated for the real-time measurement of polyethylene glycol (PEG) concentration. The wavelength was selected after the determination of the absorption spectrum of deionised water and PEG solutions using a Varian Cary 6000i spectrophotometer, in order to limit the influence of PEG molecular mass on the absorption measurement. With this new sensor, the water is treated as the attenuating species and the addition of PEG in water reduces the absorbance of the medium. The concept was validated using three different PEG types (PEG 6,000, 20,000, and 35,000) and it was found that the results follow Beer Lambert’s law. The influence of temperature was assessed by testing the PEG 20,000 at four different temperatures that could be encountered in a laboratory environment. The data show a slight temperature influence (increase of absorbance by 8% when the temperature rises from about 20 to about 29 degrees). Following the validation phase conducted ex situ, a prototype of an immersible sensor was built and calibrated for in situ measurements

Response of different osmotic membranes and calibration of a coupled model capturing the temperature effect for the osmotic method

Reliable suction control is of paramount importance for experimental unsaturated soil mechanics. The osmotic method, based on polyethylene glycol (PEG) and semi-permeable membranes, is one of the possible methods to control suction. Although this method is quite simple to implement, reliable results can only be obtained with adequate calibration curves linking suction and PEG concentration, and a good understanding of the factors influencing the method. Several studies have investigated different aspects of this method, including the osmotic potential generated by given PEG concentrations, but the effect of temperature is not yet fully captured. This paper presents the results of a comprehensive study of the osmotic method looking at the long-term response of three different types of membranes, the effect of temperature, PEG molecular weight (MW) and the combination of different MW cut off (MWCO) on the calibration curves. Finally the data were used to calibrate a model capturing the temperature effect, in a coupled manner, in order to provide a robust calibration

Characterization of the secondary swelling of compacted Maryland clay

This paper presents the result of a multi-scale experimental investigation on the phenomenon of secondary swelling. Specimens of compacted Maryland clay were prepared under different initial conditions (void ratio and water content), loaded at different levels of vertical stress and inundated until secondary swelling was observed. One test was also performed with suction control and incremental swelling. These tests were complemented by micro structural analyses via mercury intrusion porosimetry. The coefficient of secondary swelling, defined as the gradient of the evolution of void ratio with logarithm of time was calculated and correlated to the macro scale strain. Several trends were observed and it was showed that, under low confinement, the secondary swelling mostly takes place in the macro pores

Insights on Crash Injury Severity Control from Novice and Experienced Drivers: A Bivariate Random-Effects Probit Analysis

This study intended to investigate the crash injury severity from the insights of the novice and experienced drivers. To achieve this objective, a bivariate panel data probit model was initially proposed to account for the correlation between both time-specific and individual-specific error terms. The geocrash data of Las Vegas metropolitan area from 2014 to 2017 were collected. In order to estimate two (seemingly unrelated) nonlinear processes and to control for interrelations between the unobservables, the bivariate random-effects probit model was built up, in which injury severity levels of novice and experienced drivers were addressed by bivariate (seemingly unrelated) probit simultaneously, and the interrelations between the unobservables (i.e., heterogeneity issue) were accommodated by bivariate random-effects model. Results revealed that crash types, vehicle types of minor responsibility, pedestrians, and motorcyclists were potentially significant factors of injury severity for novice drivers, while crash types, driver condition of minor responsibility, first harm, and highway factor were significant for experienced drivers. The findings provide useful insights for practitioners to improve traffic safety levels of novice and experienced drivers