In-situ Micro-CT Tests, Meso-modelling and Fibre Optimization of Ultra-HighPerformance Fibre Reinforced Concrete (UHPFRC)

The ultra high performance fibre reinforced concrete (UHPFRC) is a relatively newcementitious composite material without coarse aggregates. It has superior mechanical propertiesand durability to the normal-strength concrete (NSC). However, the UHPFRC is not widely used,mainly because of its 5-10 times higher material cost than the NSC, much of which comes fromthe large number of high-strength steel fibres randomly embedded in the UHPC mortar, as wellas the high content of cement. This study is aimed to reduce the material cost of UHPFRC forwider engineering applicability, by developing meso-scale simulation-based fibre optimizationalgorithms and partly replacing the mortar by coarse ceramsite lightweight aggregates (LWAs),so as to achieve a balance between the desired mechanical properties and the cost-effectivenessof this material.Firstly, a meso-scale finite element (FE) modelling approach was developed to simulate thecomplicated nonlinear fracture and damage behaviour of UHPFRC (without coarse aggregates)beams reinforced with steel bars and stirrups. In the meso-scale models, the steel fibres wererandomly generated and explicitly simulated. The continuum damage plasticity model was usedas the constitutive law for the UHPC matrix, and cohesive elements were used to simulate thesoftening bond-slip behaviour on the steel bar-matrix and fibre-matrix interfaces. Both the steelfibres and bars were modelled by elastoplastic beam elements. As such, all the potential failuremodes, including matrix cracking and crushing, yielding and breakage of steel bars and fibres,and debonding of interfaces, could be simulated. Three beams, under three or four-point bending,with or without stirrups, were simulated to validate the modelling approach. The results werecompared well with experiments in terms of crack patterns, failure processes, and loaddisplacement curves. Monte Carlo simulations were further carried out to quantify the effects of the fibre volume fraction, the shear span versus beam depth ratio, the bar reinforcement ratio, andthe stirrup spacing. Based on the results, an improved design equation of shear strength of barreinforced UHPFRC beams was proposed.Secondly, the above-developed meso-scale modelling approach was combined with twooptimization algorithms to optimize the fibre orientation and distribution in reinforced UHPFRCbeams, with a view to significantly reduce the usage of fibres and thus the material cost. In thefirst optimization algorithm, the fibres were only placed in the beam’s lower part under hightensile stress and the diagonal strips with major shear cracks, with fibre orientations parallel tothe maximum principal stresses, whereas no fibres were used in compression-dominant regionsbecause the compressive strength of UHPFRC is not sensitive to fibres of usual volume fractions5 (1%-5%). Simulations of typical beams indicated that the fibre number could be reduced up to60% without sacrificing the load-carrying capacity. In the second optimization algorithm, thebeam was first optimized by topological optimization techniques (BESO and SIMP methods) asthe strut-tie models, and the steel fibres were only added longitudinally in the tensile ties. Fortypical beam examples, the simulations showed that the volume of the UHPC matrix and thenumber of fibres could be reduced up to 50% and 60%, respectively.Thirdly, both in-situ micro X-ray computed tomography (μXCT) tests and conventional labtests were conducted on small UHPFRC specimens with various LWAs’ contents underprogressive 3-point bending to analyse the effects of LWAs and fibres on damage evolution andmechanical properties. 3D μXCT images with a voxel resolution of 34.74µm at different loadswere obtained, reconstructed and analysed, and the internal structures and statistical data of poresand fibres, and the failure modes, including matrix cracking and spalling, fibre bridging and pullout, and failure of LWAs, were clearly visualised and characterised. It was found that a highercontent of LWAs resulted in higher porosity and lower density in the material, and lower loadcarrying capacity of the UHPFRC specimens, especially as the LWAs’ content was over 15%.Finally, 2D mesoscale FE models were developed to simulate the fracture behaviour of testedUHPFRC beams with various LWAs’ contents. The LWAs were modelled as polygons of arbitraryshape with the grading curve obtained from the μXCT images. The LWA-matrix interfaces weremodelled by the cohesive elements, while the matrix, the fibres and the fibre-matrix interfaceswere modelled in the same way as for the UHPFRC without coarse aggregates. The simulatedresults agree well with the experimental results of the in-situ μXCT beam bending tests in termsof the crack patterns, the failure processes, and the load-displacement curves. The fracture ofLWAs and the fibre bridging effect were well captured by the developed models

Intelligent Computational Transportation

Transportation is commonplace around our world. Numerous researchers dedicate great efforts to vast transportation research topics. The purpose of this dissertation is to investigate and address a couple of transportation problems with respect to geographic discretization, pavement surface automatic examination, and traffic ow simulation, using advanced computational technologies. Many applications require a discretized 2D geographic map such that local information can be accessed efficiently. For example, map matching, which aligns a sequence of observed positions to a real-world road network, needs to find all the nearby road segments to the individual positions. To this end, the map is discretized by cells and each cell retains a list of road segments coincident with this cell. An efficient method is proposed to form such lists for the cells without costly overlapping tests. Furthermore, the method can be easily extended to 3D scenarios for fast triangle mesh voxelization. Pavement surface distress conditions are critical inputs for quantifying roadway infrastructure serviceability. Existing computer-aided automatic examination techniques are mainly based on 2D image analysis or 3D georeferenced data set. The disadvantage of information losses or extremely high costs impedes their effectiveness iv and applicability. In this study, a cost-effective Kinect-based approach is proposed for 3D pavement surface reconstruction and cracking recognition. Various cracking measurements such as alligator cracking, traverse cracking, longitudinal cracking, etc., are identified and recognized for their severity examinations based on associated geometrical features. Smart transportation is one of the core components in modern urbanization processes. Under this context, the Connected Autonomous Vehicle (CAV) system presents a promising solution towards the enhanced traffic safety and mobility through state-of-the-art wireless communications and autonomous driving techniques. Due to the different nature between the CAVs and the conventional Human- Driven-Vehicles (HDVs), it is believed that CAV-enabled transportation systems will revolutionize the existing understanding of network-wide traffic operations and re-establish traffic ow theory. This study presents a new continuum dynamics model for the future CAV-enabled traffic system, realized by encapsulating mutually-coupled vehicle interactions using virtual internal and external forces. A Smoothed Particle Hydrodynamics (SPH)-based numerical simulation and an interactive traffic visualization framework are also developed

A Study of the Allan Variance for Constant-Mean Non-Stationary Processes

The Allan Variance (AV) is a widely used quantity in areas focusing on error measurement as well as in the general analysis of variance for autocorrelated processes in domains such as engineering and, more specifically, metrology. The form of this quantity is widely used to detect noise patterns and indications of stability within signals. However, the properties of this quantity are not known for commonly occurring processes whose covariance structure is non-stationary and, in these cases, an erroneous interpretation of the AV could lead to misleading conclusions. This paper generalizes the theoretical form of the AV to some non-stationary processes while at the same time being valid also for weakly stationary processes. Some simulation examples show how this new form can help to understand the processes for which the AV is able to distinguish these from the stationary cases and hence allow for a better interpretation of this quantity in applied cases