Sze Dai Pang

Smart multifunctional cement mortar containing graphite nanoplatelet

The piezoresistivity-based strain sensing ability of cementitious composites containing graphite nanoplatelet (GNP) is investigated in this paper. GNP offers the advantages of ease of processing, excellent mechanical and electrical properties at a very low cost compared to carbon nanotubes and carbon nano-fibers. Cement mortar with 0%, 1.2%, 2.4%, 3.6% and 4.8% of GNP (by volume of composite) were cast. The electrical resistance of the specimens was measured by both the two- and four-probe methods using direct current (DC). The effect of polarization was characterized and the percolation threshold was experimentally found to be between 2.4% and 3.6% of GNP based on both accelerated and normal drying specimens. The assumption of Ohmic material was tested with varying current and found to be valid for current < 0.01mA and 0.5mA for four- and two-probe methods respectively. The piezoresistive effect was demonstrated by comparing the gage factors of mortars with GNP vs plain mortar under cyclic loading in compression at 3 strain levels. At low strains, the high gage factor is believed to stem from both the effect of the imperfect interfaces around the GNP and the piezoresistivity of the GNP; at higher strains, the gage factor is likely to be attributed to the piezoresistivity of the GNP and it is still 1-2 orders of magnitude larger than the gage factor arising from geometric changes.

Strain and damage self-sensing cement composites with conductive graphene nanoplatelet

A novel cement composite containing graphene nanoplatelet (GNP) which can sense its own strain and damage is introduced in this paper. Piezoresistive strain sensing was investigated for mortar specimens with GNP under both cyclic and monotonically increasing compressive and tensile strain. Under compression, the electrical resistance decreased with increasing strain and the normalized resistance can be described by a bilinear curve with a kink at about 400 microstrain. At low strain, a high gauge factor exceeding 103 in magnitude was obtained and it increased almost linearly with the GNP content. This can be attributed primarily to the reducing interfacial distance and forming of better contacts between GNP and cement paste when the composite was initially loaded. At higher compressive strain beyond 400 microstrain, the gauge factor is consistently about 102 for GNP content exceeding the percolation threshold. A different response was observed for specimens under tension due to the formation and propagation of microcracks even at low tensile strain due to the brittleness of the material. The initial gauge factor is of the order 102 for tensile strain up to 100 microstrain and it increases exponentially beyond that. The damage self-sensing capability of this conductive cement composites is explored using electric potential method. Closed form expression for the assessment of damage are derived based on the mathematical analogy between the electrostatic field and the elastostatic field under anti-plane shear loading. The derived expression provide a quick and accurate assessment of the damage of this conductive material which is characterized by its change in compliance.

Effects of Interphase Regions of Particulate-Reinforced Metal Matrix Nanocomposites Using a Discrete Dislocation Plasticity Model

AbstractMetal matrix nanocomposites (MMNCs) show significant promise for use as structural and/or functional materials. In recent years, discrete dislocation simulations have been used to perform a numerical analysis on MMNCs. Although the trend of increasing flow stress and degree of hardening with a larger particle volume fraction and decreasing particle size were captured by existing simulations, the effects of these parameters on the mechanical behavior of MMNCs shown in these analyses were not as substantial as those reported in experiments. Meanwhile, the presence of thermally induced dislocations and chemical reactions between the matrix and inclusions suggest that interphase regions should be accounted for in the simulation. By using a level set in the extended FEM (XFEM), interphase regions are introduced into the numerical model. The effects of elastic properties, thickness of the interphase regions, and resistance to dislocation motion within the interphase regions are examined in this study.

Use of online assessments to monitor learning outcomes in higher level engineering courses

The use of online systems for assessments has become increasingly popular over the past decade. There is a general consensus that these systems have tremendous potential for enhancing teaching and learning even at the tertiary level. Nevertheless, most past studies on the use of online assessments have been focused on lower level or foundational courses that have larger class sizes while the adoption rate in higher level courses is relatively smaller. Moreover, online assessments are generally well suited for building lower order cognitive skills that are commonly engaged in foundational courses. On the other hand, higher level courses tend to require students to exercise higher order cognitive skills. Thus, it is still an open question whether online assessments can be as effective in promoting higher order cognitive skills as lower order ones, even though they can also be potentially used to enhance teaching and learning in higher level courses. Therefore, in this study online assessments were adopted as a means for students and instructors to monitor the learning progress and outcomes of students in a higher level engineering course, in order determine whether (a) the online assessments helped to improve the general level of proficiency of the students in this course, and (b) there were clear links between the levels of cognitive skills engaged in the online assessments with the examination results and final grades. The key features of the online assessments used in this study were (a) each set of assessment questions consisted of questions with different levels of difficulty and marks, and (b) students were allowed to attempt any combination of questions to get a pre-determined maximum score. The results obtained in this study show that the online assessments seemed to be rather effective in enhancing the learning experience of the students and achieving their intended outcome of helping students monitor their own learning progress and level of achievement. Moreover, there was apparently a significant correlation between the level of achievement attained by a student for the difficult online assessment questions, which required the use of higher order cognitive skills, and the subsequent performance in the end-of-semester examination as well as the final grade obtained by the student.

Parameter Sensitivity in Numerical Modelling of Ice-Structure Interaction With Cohesive Element Method

The increasing marine activities in the Arctic has resulted in a growing demand for reliable structural designs in this region. Ice loads are a major concern to the designer of a marine structure in the arctic, and are often the principal factor that governs the structural design [Palmer and Croasdale, 2013]. With the rapid advancement in computational power, numerical method is becoming a useful tool for design of offshore structures subjected to ice actions.Cohesive element method (CEM), a method which has been widely utilized to simulate fracture in various materials ranging from metals to ceramics and composites as well as bi-material systems, has been recently applied to predict ice-structure interactions. Although it shows promising future for further applications, there are also some challenging issues like high mesh dependency, large variation in cohesive properties etc., yet to be resolved.In this study, a 3D finite element model with the use of CEM was developed in LS-DYNA for simulating ice-structure interaction. The stability of the model was investigated and a parameter sensitivity analysis was carried out for a better understanding of how each material parameter affects the simulation results.Copyright