MRC Laboratory of Molecular Biology
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Ground-source heat pump systems: The effects of variable trench separations and pipe configurations in horizontal ground heat exchangers
No full textGround-source heat pump systems are renewable and highly efficient HVAC systems that utilise the ground to exchange heat via ground heat exchangers (GHEs). This study developed a detailed 3D finite element model for horizontal GHEs by using COMSOL Multiphysics and vali-dated it against a fully instrumented system under the loading conditions of rural industries in NSW, Australia. First, the yearly performance evaluation of the horizontal straight GHEs showed an adequate initial design under the unique loads. This study then evaluated the effects of variable trench separations, GHE configurations, and effective thermal conductivity. Different trench separations that varied between 1.2 and 3.5 m were selected and analysed while considering three different horizontal loop configurations, i.e., the horizontal straight, slinky, and dense slinky loop con-figurations. These configurations had the same length of pipe in one trench, and the first two had the same trench length as well. The results revealed that when the trench separation became smaller, there was a minor increasing trend (0.5 °C) in the carrier fluid temperature. As for the configuration, the dense slinky loop showed an average that was 1.5 °C lower than those of the horizontal straight and slinky loop (which were about the same). This indicates that, when land is limited, compro-mises on the trench separation should be made first in lieu of changes in the loop configuration. Lastly, the results showed that although the effective thermal conductivity had an impact on the carrier fluid temperature, this impact was much lower compared to that for the GHE configurations and trench separations
Machine learning and structural health monitoring overview with emerging technology and high-dimensional data source highlights
No full textConventional damage detection techniques are gradually being replaced by state-of-the-art smart monitoring and decision-making solutions. Near real-time and online damage assessment in structural health monitoring (SHM) systems is a promising transition toward bridging the gaps between the past’s applicative inefficiencies and the emerging technologies of the future. In the age of the smart city, Internet of Things (IoT), and big data analytics, the complex nature of data-driven civil infrastructures monitoring frameworks has not been fully matured. Machine learning (ML) algorithms are thus providing the necessary tools to augment the capabilities of SHM systems and provide intelligent solutions for the challenges of the past. This article aims to clarify and review the ML frontiers involved in modern SHM systems. A detailed analysis of the ML pipelines is provided, and the in-demand methods and algorithms are summarized in augmentative tables and figures. Connecting the ubiquitous sensing and big data processing of critical information in infrastructures through the IoT paradigm is the future of SHM systems. In line with these digital advancements, considering the next-generation SHM and ML combinations, recent breakthroughs in (1) mobile device-assisted, (2) unmanned aerial vehicles, (3) virtual/augmented reality, and (4) digital twins are discussed at length. Finally, the current and future challenges and open research issues in SHM-ML conjunction are examined. The roadmap of utilizing emerging technologies within ML-engaged SHM is still in its infancy; thus, the article offers an outlook on the future of monitoring systems in assessing civil infrastructure integrity
Modelling COVID-19 dynamics and potential for herd immunity by vaccination in Austria, Luxembourg and Sweden.
No full textAgainst the COVID-19 pandemic, non-pharmaceutical interventions have been widely applied and vaccinations have taken off. The upcoming question is how the interplay between vaccinations and social measures will shape infections and hospitalizations. Hence, we extend the Susceptible-Exposed-Infectious-Removed (SEIR) model including these elements. We calibrate it to data of Luxembourg, Austria and Sweden until 15th December 2020. Sweden results having the highest fraction of undetected, Luxembourg of infected and all three being far from herd immunity in December. We quantify the level of social interaction, showing that a level around 1/3 of before the pandemic was still required in December to keep the effective reproduction number Refft below 1, for all three countries. Aiming to vaccinate the whole population within 1 year at constant rate would require on average 1,700 fully vaccinated people/day in Luxembourg, 24,000 in Austria and 28,000 in Sweden, and could lead to herd immunity only by mid summer. Herd immunity might not be reached in 2021 if too slow vaccines rollout speeds are employed. The model thus estimates which vaccination rates are too low to allow reaching herd immunity in 2021, depending on social interaction. Vaccination will considerably, but not immediately, help to curb the infection; thus limiting social interactions remains crucial for the months to come
Direct laser writing of graded-index SiGe waveguides via phase segregation
No full textWe report direct laser writing of graded-index optical waveguides via phase segregation in initially homogenous silicongermanium (SiGe) thin films epitaxially-grown on silicon substrates. We used a continuous wave (CW) laser operating at a wavelength of 532 nm. The laser beam was focused to a 5 μm diameter spot on the surface of SiGe films with a thickness of 575 nm and a Ge concentration of %50. Compositional separation of a SiGe film was induced by melting the surface, and the composition profile was tailored by controlling the scan speed of the laser-induced molten zone in a range of 0.1-200 mm/s. At high scan speeds, scanning the laser beam produces a travelling Ge-rich molten zone, where a build-up of Ge content occurs at the trailing edge because of insufficient diffusion-limited Ge transport. Material characterizations have revealed that the laser-processed SiGe microstripes consist of Ge-rich strip cores (> 70% Ge) surrounded by Si-rich under-claddings (<30% Ge). Scan-speed dependent phase segregation allows for fabrication of graded-index SiGe waveguides with tunable compositional profiles, which were characterized by optical transmission measurements, and modal analysis using simulations. Our method could also be applied to pseudo-binary alloys of ternary semiconductors (AlGaAs), which have equilibrium phase diagrams similar to that of SiGe alloys
Filtration of viral aerosols via a hybrid carbon nanotube active filter
No full textExposure to expired particles and droplets carrying infectious viruses is a primary transmission pathway for respiratory diseases. Removal of particles and droplets via filtration from a volume can drastically reduce the exposure to viruses, but viruses may remain active on filtration surfaces as potential resuspension or fomite risks. Here, we report the development of macroscopic carbon nanotube air filters synthesized using ultra-thin carbon nanotube electrically conductive membranes, mechanically supported by a porous polyester backing. Filtration efficiencies were measured up to 99.999%, while ultra-thin materials with low areal density (0.1 g m─2) exhibited pressure drops comparable to commercial High-Efficiency Particulate Air (HEPA) filters. These electrically conductive filters are actively self-sanitized by thermal flashes via resistive heating to temperatures above 80 °C within seconds or less. Such temperatures were proven to achieve full deactivation of a betacoronavirus and an adeno-associated virus retained on filter surfaces. A filtration unit prototype equipped with a CNT filter module (∼1.2 m2) was shown to achieve air purification of 99% of a room within 10 min at 26 air changes per hour
Effect of glass fiber sheet in adhesive on the bond and galvanic corrosion behaviours of CFRP-Steel bonded system
No full textSteel structures strengthened with CFRP composite may have potential galvanic corrosion issue. It was recommended that a layer of glass fiber sheet (GFS) be embedded in the adhesive layer to protect the CFRP-steel bonded system against galvanic corrosion. But the inclusion of GFS in the adhesive may negatively affect the bond behaviour between steel and CFRP. This paper investigated the effects of GFS on the corrosion behaviour and bond characteristics between steel and CFRP. Three types of experimental testing on CFRP-steel double strap joints with/without GFS were conducted, including accelerated corrosion testing, static and fatigue testing. Accelerated corrosion testing was carried out to justify the effectiveness of GFS in preventing galvanic corrosion of CFRP-steel bonded system. Static tension testing and fatigue testing were carried out to quantify the effect of GFS on the static and fatigue bond behaviour between steel and CFRP. The effects of GFS on the corrosion rate, failure mode, joint capacity and fatigue life were reported. Experimental results suggested that GFS may reduce the fatigue performance of the bond between steel and CFRP, although GFS may slightly improve the static bond behaviour. It is recommended that GFS can be included in the adhesive layer as an additional protection against the galvanic corrosion hazard in the CFRP-steel bonded system, provided that the system has no concern of fatigue loading
Thermal and Mechanical Analyses of Compliant Thermoelectric Coils for Flexible and Bio-Integrated Devices
No full textThree-dimensional coil structures assembled by mechanically guided compressive buckling have shown potential in enabling efficient thermal impedance matching of thermoelectric devices at a small characteristic scale, which increases the efficiency of power conversion, and has the potential to supply electric power to flexible bio-integrated devices. The unconventional heat dissipation behavior at the side surfaces of the thin-film coil, which serves as a "heat pump," is strongly dependent on the geometry and the material of the encapsulating dissipation layer (e.g., polyimide). The low heat transfer coefficient of the encapsulation layer, which may damp the heat transfer for a conventional thermoelectric device, usually limits the heat transfer efficiency. However, the unconventional geometry of the coil can take advantage of the low heat transfer coefficient to increase its hot-To-cold temperature difference, and this requires further thermal analysis of the coil in order to improve its power conversion efficiency. Another challenge for the coil is that the active thin-film thermoelectric materials employed (e.g., heavily doped Silicon) are usually very brittle, with the fracture strain less than 0.1% in general while the overall device may undergo large deformation (e.g., stretched 100%). Mechanical analysis is therefore necessary to avoid failure/fracture of the thermoelectric material. In this work, we study the effect of coil geometry on both thermal and mechanical behaviors by using numerical and analytical approaches, and optimize the coil geometry to improve the device performance, and to guide its design for future applications
Agent-Based Simulation of General Contractor-Subcontractor Interactions in a Multiproject Environment
No full textThe behavioral dynamics of general contractors and subcontractors in bidding, construction planning, and production control influence the outcomes of construction projects. To date, researchers have modeled these interactions in the context of stand-alone projects. While much has been learned, questions arise concerning the validity of these models, because projects are not islands - they are affected by the markets in which general contractors compete for subcontractor resources. LeapconX is a marketwide simulation that can model an unlimited number of construction projects, subcontractors, and residential building projects in any given market region. It enables testing of production system innovations, revealing the impacts not only on companies implementing the innovations, but also on companies that do not. The system was validated through simulation using data for the Newark, New Jersey metropolitan area. Three production control innovations were tested at three levels of market penetration. Comparison of the results with those of single-project simulations for the same innovations confirms that market dynamics moderate outcomes. LeapconX enables both construction management researchers and practitioners to predict the likely outcomes of a wide variety of procedural and technological innovations, with little cost and no risk to actual projects
Dynamic network reconstruction from heterogeneous datasets
No full textPerforming multiple experiments is common when learning internal mechanisms of complex systems. These experiments can include perturbations of parameters or external disturbances. A challenging problem is to efficiently incorporate all collected data simultaneously to infer the underlying dynamic network. This paper addresses the reconstruction of dynamic networks from heterogeneous datasets under the assumption that the underlying networks share the same Boolean structure across all experiments. Parametric models are derived for dynamical structure functions, which describe causal interactions between measured variables. Multiple datasets are integrated into one regression problem with additional demands on group sparsity to assure network sparsity and structure consistency. To acquire structured group sparsity, we propose a sampling-based method, together with extended versions of l1-methods and sparse Bayesian learning. The performance of the proposed methods is benchmarked in numerical simulation. In summary, this paper presents efficient methods on network reconstruction from multiple experiments, and reveals practical experience that could guide applications