Nano/microcharacterization on mechanical properties and structures of geopolymeric matrices and interfacial transition zones

University of Technology Sydney. Faculty of Engineering and Information Technology.This study aims to promote the fundamental understanding of fly ash-based geopolymer through micro and nanoscale mechanical and structural characterization. Geopolymer concrete is studied from two aspects of paste and interfacial transition zone (ITZ). In addition to properties investigation and related mechanism analysis, new insights and methods are provided for the nano/micromechanical testing and analysis of highly heterogeneous materials. Prior to research, several typical nanomechanical testing techniques are introduced and compared. The review provides the current research trend, advantages/disadvantages and suitable application of these techniques in cement-based materials. Then, based on the study of geopolymer paste, some critical questions of the statistical nanoindentation technique (SNT) are discussed. The study reveals the disadvantages of using the least-square estimation (LSE) for deconvolution of data in some highly heterogeneous materials such as geopolymers and proposes a "compromise approach" using maximum likelihood estimation (MLE) for deconvolution. Correlation and difference of different statistical techniques are analyzed to clarify the rationality of the proposed method. Thereafter, the effects of the general design parameters such as silica modulus, alkali concentration, and curing condition on the properties of N-A-S-H gel and its association with the performance of geopolymer are investigated and discussed. The properties of geopolymer are further modified by nano-SiO₂ and nano-TiO₂. The effects of different nanoparticles on microstructure, gel proportion and gel micromechanical properties are discussed to reveal the macro-strength reinforcement mechanism. For ITZ research, a method based on modelled ITZ samples is proposed to facilitate comparison research and nanomechanical testing. This part starts with the comparison of ITZ in geopolymer concrete and Portland cement (PC) concrete. The mechanism of the better ITZ performance in geopolymer than PC is revealed. Afterwards, scratch technique coupled with Gaussian mixture model (GMM) is introduced on the modelled ITZ samples as a quick method for interfacial properties evaluation. The statistical results indicate that silica modulus is an important factor governing the interfacial properties of geopolymer. In the last section of ITZ research, the heterogeneity of ITZ in section concrete is categorized into three levels. The study promotes the heterogeneity of the investigated ITZ to the second level for a deeper understanding of ITZ in geopolymer. Echoing the beginning of the thesis, scratch and indentation techniques are combined used, which clearly shows some of their different advantages for nanomechanical properties investigation. Strategies are proposed to overcome the higher level of heterogeneity to realize ITZ properties investigation with feasible workload and accuracy

Second-Harmonic Generation and Spectrum Modulation by Active Nonlinear Metamaterial

The nonlinear properties of a metamaterial sample composed of double-layer metallic patterns and voltage controllable diodes are experimentally investigated. Second harmonics and spectrum modulations are clearly observed in a wide band of microwave frequencies, showing that this kind of metamaterial is not only tunable by low DC bias voltage, but also behaves strong nonlinear property under a small power incidence. These properties are difficult to be found in normal, naturally occurring materials.Comment: 14 pages, 4 figure

Dynamics Study of the OH + O3 Atmospheric Reaction with Both Reactants Vibrationally Excited

The dynamics of the title five-atom atmospheric reaction is studied by the quasiclassical trajectory method for vibrational states of OH over the range 2 ≤ v ≤ 9 and initial vibrational energies of O3 between 9 and 21 kcal mol-1 using a previously reported double many-body expansion potential energy surface for HO4(2A). The results show that the reaction is controlled by both capture- and barrier-type mechanisms, with the rate constants depending strongly on the reactants' internal energy content. Also suggested from the magnitude of the calculated rate coefficients is that the title processes may not be ignorable when studying the stratospheric ozone budget

Towards Efficient Visual Adaption via Structural Re-parameterization

Parameter-efficient transfer learning (PETL) is an emerging research spot aimed at inexpensively adapting large-scale pre-trained models to downstream tasks. Recent advances have achieved great success in saving storage costs for various vision tasks by updating or injecting a small number of parameters instead of full fine-tuning. However, we notice that most existing PETL methods still incur non-negligible latency during inference. In this paper, we propose a parameter-efficient and computationally friendly adapter for giant vision models, called RepAdapter. Specifically, we prove that the adaption modules, even with a complex structure, can be seamlessly integrated into most giant vision models via structural re-parameterization. This property makes RepAdapter zero-cost during inference. In addition to computation efficiency, RepAdapter is more effective and lightweight than existing PETL methods due to its sparse structure and our careful deployment. To validate RepAdapter, we conduct extensive experiments on 27 benchmark datasets of three vision tasks, i.e., image and video classifications and semantic segmentation. Experimental results show the superior performance and efficiency of RepAdapter than the state-of-the-art PETL methods. For instance, by updating only 0.6% parameters, we can improve the performance of ViT from 38.8 to 55.1 on Sun397. Its generalizability is also well validated by a bunch of vision models, i.e., ViT, CLIP, Swin-Transformer and ConvNeXt. Our source code is released at https://github.com/luogen1996/RepAdapter

Performance enhancement of permeable asphalt mixtures with recycled aggregate for concrete pavement application

The incorporation of recycled concrete aggregate (RCA) in permeable asphalt mixtures (PAMs) is an efficient method of utilizing construction demolished waste. It not only conforms to the trend of building sponge cities, but also alleviates the problem of overexploitation of natural aggregate resources. As the performance of PAM containing recycled aggregate is not comparable to natural aggregate, modification treatments and the addition of hybrid fibers are adopted as two enhancement methods to improve the performance of PAM with RAC in this study. It is found that replacing natural aggregate with recycled aggregate increases the optimum asphalt content (OAC) but decreases the residual stability. The OAC is increased by 45% when the RCA ratio is 100%, whereas applying silicone resin can give a 16.2% decrease in the OAC. Enhancing RCA with silicone resin can increase the water stability to be comparable with natural aggregate. Moreover, with modification treatment using calcium hydroxide solution, the mechanical strength of PAM is enhanced to even higher than that of natural coarse aggregate mixture alone. Improvements in both mechanical strength and water stability are also achieved by strengthening recycled aggregate with cement slurry, although the performance is less effective than using silicone resin. With the increase in the content of RCA, the permeability coefficients of PAM first decrease and then exhibit an increasing trend. The results indicate that the PAM with RCA and modification treatments can perform satisfactorily as a pavement material in practice. Applying probable modification, PAM incorporating RCA meets the criteria for use in concrete pavement applications

Unconfounded Propensity Estimation for Unbiased Ranking

The goal of unbiased learning to rank (ULTR) is to leverage implicit user feedback for optimizing learning-to-rank systems. Among existing solutions, automatic ULTR algorithms that jointly learn user bias models (i.e., propensity models) with unbiased rankers have received a lot of attention due to their superior performance and low deployment cost in practice. Despite their theoretical soundness, the effectiveness is usually justified under a weak logging policy, where the ranking model can barely rank documents according to their relevance to the query. However, when the logging policy is strong, e.g., an industry-deployed ranking policy, the reported effectiveness cannot be reproduced. In this paper, we first investigate ULTR from a causal perspective and uncover a negative result: existing ULTR algorithms fail to address the issue of propensity overestimation caused by the query-document relevance confounder. Then, we propose a new learning objective based on backdoor adjustment and highlight its differences from conventional propensity models, which reveal the prevalence of propensity overestimation. On top of that, we introduce a novel propensity model called Logging-Policy-aware Propensity (LPP) model and its distinctive two-step optimization strategy, which allows for the joint learning of LPP and ranking models within the automatic ULTR framework, and actualize the unconfounded propensity estimation for ULTR. Extensive experiments on two benchmarks demonstrate the effectiveness and generalizability of the proposed method.Comment: 11 pages, 5 figure

Construction Technology of Precast Pier Foundation Filled with Demolished Concrete Lumps

Applying of demolished concrete lumps (DCLs) in the pier foundation is an effective way to improve the efficiency of construction waste resource utilization. Fifty-two cylindrical specimens with the size of ∅ 250 mm × 500 mm were fabricated by mixing of DCLs with the fresh concrete (FC) and used to investigate the influence of two key factors, the gradation of the DCLs and the height setting of layered “steel mesh,” on the uniaxial compression and flexural strength properties of the compound concrete specimens. Results indicate that the layered “steel mesh” in the specimens can restrain the settlement and segregation of the DCLs and improve the compressive and flexural strength of the specimens significantly. Normally, there are two types of failure damage mode of the test pieces, the failure of the interface between DCLs and the FC and the fracture failure of the DCLs. When the stress level is below 0.5, the test piece is in the elastic stage. Crack development occurs when stress level further increase to 0.7–0.9. The pieces with the layered pouring height of H2 and the DCLs of R3 present the optimum compressive strength and flexural strength and also best construction effect

Falling weight impact test of a new-type flexible rock-shed

A new concept of a flexible rock-shed is presented for protection of the railway from falling rocks. The flexible rock-shed is made of flexible nets connected by specific spring spacer bars to an array of reinforced concrete portable frames which are linked by a longitudinal steel tube truss. To evaluate the performance of the flexible rock-shed, experimental and numerical studies are carried out in the present study. Impact tests are conducted on a full-scale partial model of the prototype structure when it is subjected to a falling block of 340 kg. The impact time interval, maximum deflection of the flexible net, tensile forces in the supporting ropes, and axial strains of spring spacer bars are recorded. To further examine the dynamic behavior of the flexible rock-shed, numerical simulations are also carried out by using the explicit finite element code ANSYS/LS-DYNA. It is found that the numerical results coincide well with the experimental data and both the numerical and experimental studies reveal that the structure can withstand impact energy of 50 kJ with all the materials working in the elastic range. The structural details are improved and the basis for the design and construction of similar structures in the future is provided