Generation of a short fibre biocomposite representative volume element

One of the greatest challenge in working with natural fibre composites is the large variation in mechanical properties that result from the geometric inconsistency amongst fibres. Traditional design tools and models are unable to accurately incorporate this non-homogeneity to predict the resulting local behaviour of biocomposite materials. The following paper presents a methodology to generate a representative volume element (RVE) to simulate the material microstructure of short fibre composites, with the intent of modelling the popular class of short fibre biocomposites materials. The capabilities of a range of particle packing algorithms used in literature are compared in terms of the maximum volume fraction they have been able to achieve and for what fibre length to diameter aspect ratio. The methodology is able to account for the characteristics of fibre geometry samples, according to their probability density functions (PDFs). The RVE generation strategy imposes periodic boundary conditions and fibres are declared invalid if an intersection between fibres is detected. The effect of different PDFs on the resulting RVE are discussed. An RVE populated with data following a Weibull distribution is compared to that from normally distributed data with an equal mean but varied standard deviations. Using a Weibull distribution to simulate the characteristics of an RVE requires a significantly higher number of fibres than any comparable normal distribution, due to the skewness of the data towards large values at low probabilities. The highest volume fraction achieved was 40% for an RVE containing fibres with lengths distributed according to a Weibull distribution and aspect ratios of 15. The future intent of this work is to perform finite element analysis on RVE samples with a range of varied microstructure characteristics to determine the effect on overall composite properties, which will provide new insights on how best to formulate short fibre compounds

Learning to diagnose accurately through virtual patients: do reflection phases have an added benefit?

BACKGROUND Simulation-based learning with virtual patients is a highly effective method that could potentially be further enhanced by including reflection phases. The effectiveness of reflection phases for learning to diagnose has mainly been demonstrated for problem-centered instruction with text-based cases, not for simulation-based learning. To close this research gap, we conducted a study on learning history-taking using virtual patients. In this study, we examined the added benefit of including reflection phases on learning to diagnose accurately, the associations between knowledge and learning, and the diagnostic process. METHODS A sample of N = 121 medical students completed a three-group experiment with a control group and pre- and posttests. The pretest consisted of a conceptual and strategic knowledge test and virtual patients to be diagnosed. In the learning phase, two intervention groups worked with virtual patients and completed different types of reflection phases, while the control group learned with virtual patients but without reflection phases. The posttest again involved virtual patients. For all virtual patients, diagnostic accuracy was assessed as the primary outcome. Current hypotheses were tracked during reflection phases and in simulation-based learning to measure diagnostic process. RESULTS Regarding the added benefit of reflection phases, an ANCOVA controlling for pretest performance found no difference in diagnostic accuracy at posttest between the three conditions, F(2, 114) = 0.93, p = .398. Concerning knowledge and learning, both pretest conceptual knowledge and strategic knowledge were not associated with learning to diagnose accurately through reflection phases. Learners' diagnostic process improved during simulation-based learning and the reflection phases. CONCLUSIONS Reflection phases did not have an added benefit for learning to diagnose accurately in virtual patients. This finding indicates that reflection phases may not be as effective in simulation-based learning as in problem-centered instruction with text-based cases and can be explained with two contextual differences. First, information processing in simulation-based learning uses the verbal channel and the visual channel, while text-based learning only draws on the verbal channel. Second, in simulation-based learning, serial cue cases are used to gather information step-wise, whereas, in text-based learning, whole cases are used that present all data at once

The variable magnetic field of V889 Her and the challenge of detecting exoplanets around young Suns using Gaussian process regression

Discovering exoplanets orbiting young Suns can provide insight into the formation and early evolution of our own solar system, but the extreme magnetic activity of young stars obfuscates exoplanet detection. Here we monitor the long-term magnetic field and chromospheric activity variability of the young solar analogue V889 Her, model the activity-induced radial velocity variations and evaluate the impacts of extreme magnetism on exoplanet detection thresholds. We map the magnetic field and surface brightness for 14 epochs between 2004 and 2019. Our results show potential 3-4 yr variations of the magnetic field which evolves from weak and simple during chromospheric activity minima to strong and complex during activity maxima but without any polarity reversals. A persistent, temporally-varying polar spot coexists with weaker, short-lived lower-latitude spots. Due to their different decay time-scales, significant differential rotation and the limited temporal coverage of our legacy data, we were unable to reliably model the activity-induced radial velocity using Gaussian Process regression. Doppler Imaging can be a useful method for modelling the magnetic activity jitter of extremely active stars using data with large phase gaps. Given our data and using Doppler Imaging to filter activity jitter, we estimate that we could detect Jupiter-mass planets with orbital periods of $\sim$3 d. A longer baseline of continuous observations is the best observing strategy for the detection of exoplanets orbiting highly active stars.Comment: Accepted by MNRA

Towards a better understanding of fire performance assessment of façade systems: Current situation and a proposed new assessment framework

This manuscript presents tools and data that serve to enable an evaluation of the risk associated with vertical fire spread on buildings. A highly detailed context to cladding fires is described to unveil the complexity and magnitude of the problem and to identify gaps of information. An engineering framework is then developed which delivers required information that fills some of those gaps and that needs to be used towards achieving quantified fire performance. The data itself has been published as a publicly available database, entitled the Cladding Materials Library (www.claddingmaterialslibrary.com.au). This data can be used to support building fire risk assessments or as the basis for more in-depth research into façade fires. This paper presents the context of the data together with the competency framework necessary for upskilling building professionals to have the capacity to implement the engineering framework

Behavior of FRP confined ultra-high strength concrete columns under compression: An experimental study

Ultra High-Strength Concrete (UHSC) have become increasingly popular within the civil engineering community. While many studies exist on structural members made using UHSC, research works on the behavior of Fiber Reinforced Polymer (FRP) confined UHSC columns are scarce. Existing theoretical models for predicting the behavior of FRP-confined normal strength and high strength concrete found to be inadequate for FRP-confined UHSC with silica fume. Due to inconstancies of existing limited experimental results on FRP-confined UHSC columns, effect of silica fume cannot be clearly identified. This paper presents an experimental study on the compressive performance of twelve FRP-confined UHSC columns under axial compression. The variables investigated include unconfined concrete strength (two different mix designs with different silica fume content) and number of GFRP plies. While GFRP confinement significantly enhance both compressive strength and ultimate strain, effectiveness of GFRP confinement was found to be largely effected by the concrete mix design

The variable magnetic field of V889 Her and the challenge of detecting exoplanets around young Suns using Gaussian process regression

Discovering exoplanets orbiting young Suns can provide insight into the formation and early evolution of our own solar system, but the extreme magnetic activity of young stars obfuscates exoplanet detection. Here we monitor the long-term magnetic field and chromospheric activity variability of the young solar analogue V889 Her, model the activity-induced radial velocity variations and evaluate the impacts of extreme magnetism on exoplanet detection thresholds. We map the magnetic field and surface brightness for 14 epochs between 2004 and 2019. Our results show potential 3-4 yr variations of the magnetic field which evolves from weak and simple during chromospheric activity minima to strong and complex during activity maxima but without any polarity reversals. A persistent, temporally-varying polar spot coexists with weaker, short-lived lower-latitude spots. Due to their different decay time-scales, significant differential rotation and the limited temporal coverage of our legacy data, we were unable to reliably model the activity-induced radial velocity using Gaussian Process regression. Doppler Imaging can be a useful method for modelling the magnetic activity jitter of extremely active stars using data with large phase gaps. Given our data and using Doppler Imaging to filter activity jitter, we estimate that we could detect Jupiter-mass planets with orbital periods of ∼3 d. A longer baseline of continuous observations is the best observing strategy for the detection of exoplanets orbiting highly active stars

Towards a better understanding of fire performance assessment of façade systems: current situation and a proposed new assessment framework

This manuscript presents tools and data that serve to enable an evaluation of the risk associated with vertical fire spread on buildings. A highly detailed context to cladding fires is described to unveil the complexity and magnitude of the problem and to identify gaps of information. An engineering framework is then developed which delivers required information that fills some of those gaps and that needs to be used towards achieving quantified fire performance. The data itself has been published as a publicly available database, entitled the Cladding Materials Library (www.claddingmaterialslibrary.com.au). This data can be used to support building fire risk assessments or as the basis for more in-depth research into façade fires. This paper presents the context of the data together with the competency framework necessary for upskilling building professionals to have the capacity to implement the engineering framework