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Geopolymer concrete offers a favourable alternative to conventional Portland concrete due to its reduced embodied carbon dioxide (CO2) content. Engineering properties of geopolymer concrete, such as compressive strength, are commonly characterised based on experimental practices requiring large volumes of raw materials, time for sample preparation, and costly equipment. To help address this inefficiency, this study proposes machine learning-assisted numerical methods to predict compressive strength of fly ash-based geopolymer (FAGP) concrete. Methods assessed included artificial neural network (ANN), deep neural network (DNN), and deep residual network (ResNet), based on experimentally collected data. Performance of the proposed approaches were evaluated using various statistical measures including R-squared (R2), root mean square error (RMSE), and mean absolute percentage error (MAPE). Sensitivity analysis was carried out to identify effects of the following six input variables on the compressive strength of FAGP concrete: sodium hydroxide/sodium silicate ratio, fly ash/aggregate ratio, alkali activator/fly ash ratio, concentration of sodium hydroxide, curing time, and temperature. Fly ash/aggregate ratio was found to significantly affect compressive strength of FAGP concrete. Results obtained indicate that the proposed approaches offer reliable methods for FAGP design and optimisation. Of note was ResNet, which demonstrated the highest R2 and lowest RMSE and MAPE values.

Residue Fluid Catalytic Cracking (RFCC) is waste materials of petroleum industry, which contains Aluminium and Silicon ions. It could be used as source material for fabricating geopolymer materials. In this study, the properties of fly ash/RFCC based geopolymer concrete are investigated with the usage amount of RFCC in range from 20 to 100% by mass. The experimental results show that the higher usage amount of RFCC would provide higher content of alumino-silicate for geopolymerization. However, the ratios of SiO2/Al2O3 and Na2O/(SiO2 + Al2O3) are decreased. Also heat curing is required for fly ash/RFCC based geopolymer concrete. The slump of fresh geopolymer concrete is lower than 40% compared with fresh fly ash based geopolymer concrete. Besides, fly ash/RFCC based geopolymer concrete requires higher content of alkaline liquid to maintain the properties of fly ash based geopolymer on mix proportion.

The Cross-Laminated Timber (CLT) concrete composite floor can successfully address the issues of conventional wood product and become an attractive alternative material for conventional reinforced concrete floors in mid to high-rise building. The purpose of this research was to fully evaluate the capacity of this novel hybrid composite material under both dynamic and static conditions, before such this hybrid system becomes widely employed. This was achieved by performing a full-scale testing of five floor specimens. One specimen was designed according to Eurocode 5 to satisfy the design load for common office buildings, and four specimens were prepared with a concrete topping with different connector types, connector angles, and connector spacing. The test results illustrated that the CLT–concrete floor specimens had excellent structural performance in terms of strength capacity, 3 –5 times higher than the conventional CLT floor. The vibration performances of this composite floors were also enhanced, resulting in a remarkably effective use of this innovative materials.

Portland cement concrete is a major construction and building material used all over the world. It is a composite material comprising Portland cement, coarse aggregate, fine aggregate, and water. But its increased use in construction is exhausting natural resources used in its production, making it necessary to find alternative materials. One potential method is to use sea sand as fine aggregate to produce fly ash based geopolymer concrete. In this paper, the mechanical properties of geopolymer concrete prepared with sea sand as the fine aggregate, and the corrosion of steel bar embedded in the concrete subjected to accelerated corrosion tests, were investigated. The test data revealed that for sea sand based geopolymer concrete, the compressive strength reached high values at an alkaline to fly ash ratio of 0.35–0.45. The geopolymer concrete exhibited highcompressive strength with a low aggregate to fly ash ratio. Also, there was an increase in compressive strength when the Si/Al ratio changed from 1.16 to 1.67. Furthermore, very little difference was observed between the mechanical properties of geopolymer concrete using sea sand, and river sand. Measurements of the corrosion of steel bar using a half-cell potential survey indicated that the steel in geopolymer concrete with sea sand was attacked and corroded like normal concrete. However, the potential of steel bar in geopolymer concrete was higher than in Portland cement concrete.

Heat curing in an oven is the traditional method to obtain mechanical properties of geopolymers. This characteristic has significantly affected operations in terms of construction and energy consumption. The target of this paper is proposing alternative curing methods namely self-cured technologies for fly ash based geopolymer materials that are cured in ambient conditions without use of a heat resource. Two alternative methods are to use three different mixing processes with preheated materials and to use two thermogenetic admixtures (hot pack material and quicklime). The results show that for the mixing processes, a larger amount of provided heat energy results in a higher compressive strength of the geopolymer mortar (GM). For the use of a thermogenetic admixture, the results from compressive strength testing, Scanning Electron Microscope (SEM), energy dispersive X-ray analysis (EDX) micrographs and X-ray diffraction (XRD) analysis confirm that quicklime is more efficient than hot pack material. In the case of using quicklime, the suggested amount is about 3–5% of fly ash by mass.

In this paper, evaluation of the mechanical properties of heat-cured low-calcium fly-ash geopolymer concrete and the behavior of geopolymer concrete beams are reported in detail. The mechanical properties are evaluated using the modulus elasticity, Poisson’s ratio, stress–strain relation, and indirect tensile strength. Behavior of the geopolymer beam is determined using a flexural test with four-point bending, elastic theory, and a finite element model (FEM). The measured modulus elasticity values of geopolymer concrete are lower than those calculated using current standards for normal concrete. The Poisson’s ratio is from 0.16 to 0.21, which is similar to the values of conventional concrete. The stress–strain relation in compression matches well with the formulation designed for Portland cement concrete. The indirect tensile strength is a fraction of the compressive strength but it is higher than the calculated value using an expression designed for normal concrete. The deflections at mid-span, and the crack patterns of the geopolymer concrete beam determined from FEM, are better matched with the experimental results than with the elastic theory results.

In this research, two different machine learning approaches are proposed for predicting the compressive strength of fly ash based geopolymer concrete. Experimental work with a total of 335 mix proportions were conducted to produce the data for training and validating processes. In the proposed models, the amount of fly ash, water glass solution, sodium hydroxide solution, coarse aggregate, fine aggregate, water, concentration of sodium hydroxide solution, curing time, and curing temperature were considered as nine input variables, while compressive strength was the output feature. The performance of the machine learning approaches was evaluated using a set of three metrics, including correlation coefficient (R), mean absolute error (MAE) and root mean square error (RMSE). Good correlation between machine learning models and experimental results was obtained. The proposed models can be employed to build a standard mix, and for designing the mix proportions of fly ash based geopolymer concrete.

This research investigates the design process of free-form architecture to understand the design strategy and changing factors during the development phase and the cause for them. It is aimed to foresee the changing factors from the design process and to reduce design changes. It analyzes the design changes of free-form architecture based on projects with finalized documentation or under construction in South Korea. Many free-form shapes of the free-form architectures have to be adjusted to rigid-form in order to satisfy function and be economical to build. The research finds three patterns in design changes. First, from the factors for design changes: function, constructability, design, program add/subtract, efficiency, circulation; Function and Constructability are the higher factors compared with the rest. The two are the design changes suitable for actual usage and cost savings. Second, each project has different predominant factors for design changes as the degree of free-form is different. Contrary to initial expectation, the greater the degrees of free-form of the competition scheme, the higher the rate of Function among the factors for design changes. Constructability is higher when the degree of the free-form is less than others. It means that the lower the degree of the free-form, the more properly planned the space of the building is. Last, Constructability of free-form architecture is considered during the earlier design phase than definite-form, one by which the design changes by comparing ‘Before fixed Space Program’ (BSP) and ‘After fixed Space Program’ (ASP) design changes. The research would be helpful as a reference for setting up competition guidelines to reduce trial and error during the design process.

Global warming has recently become a topical issue throughout the world, and the cement industry is widely seen as one of the prominent factors responsible for it. Therefore, the development of new...

In this paper, we present a novel visualization approach for the quantitative analysis of knee movement patterns in time-varying data sets. The presented approach has been developed for the analysis of patellofemoral instability, which is a common knee problem, caused by the abnormal movement of the patella (kneecap). Manual kinematic parameter calculations across time steps in a dynamic volumetric data set are time-consuming and prone to errors as well as inconsistencies. To overcome these limitations, the proposed approach supports automatic tracking of identified features of interest (FOIs) in the time domain and, thus, facilitates quantitative analysis processes in a semiautomatic manner. Moreover, it allows us to visualize the movement of the patella in the femoral groove during an active flexion and extension movement, which is essential to assess kinematics with respect to knee flexions. To further support quantitative analysis, we propose kinematic plots and time-angle profiles, which enable comparative dynamics visualization. As a result, our proposed visualization approach facilitates better understanding of the effects of surgical interventions by quantifying and comparing the dynamics before and after the operations. We demonstrate our approach using clinical time-varying patellofemoral data, discuss its benefits with respect to quantification as well as medical reporting, and describe how to generalize it to other complex joint movements.

Construction materials have been greatly improved in recent years and reinforced concrete is no exception. However, corrosion inside reinforced concrete continues to be a primary problem in the con...

The advents of technologies have led to tremendous increases in the diversity and size of the available data. In the field of medicine, the advancements in medical imaging technologies have dramati ...

Multiple sequence alignment (MSA) is essential as an initial step in studying molecular phylogeny as well as during the identification of genomic rearrangements. Recent advances in sequencing techniques have led to a tremendous increase in the number of sequences to be analyzed. As a result, a greater demand is being placed on visualization techniques, as they have the potential to reveal the underlying information in large-scale MSAs. In this work, we present a novel visualization technique for conveying the patterns in large-scale MSAs. By applying gradient vector flow analysis to the MSA data, we can extract and visually emphasize conservations and other patterns that are relevant during the MSA exploration process. In contrast to the traditional visual representation of MSAs, which exploits color-coded tables, the proposed visual metaphor allows us to provide an overview of large MSAs as well as to highlight global patterns, outliers, and data distributions. We will motivate and describe the proposed algorithm, and further demonstrate its application to large-scale MSAs.

Diffusion Tensor Imaging DTI in combination with fiber tracking algorithms enables visualization and characterization of white matter structures in the brain. However, the low spatial resolution associated with the inherently low signal-to-noise ratio of DTI has raised concerns regarding the reliability of the obtained fiber bundles. Therefore, recent advancements in fiber tracking algorithms address the accuracy of the reconstructed fibers. In this paper, we propose a novel approach for analyzing and reducing the uncertainty of densely sampled 3D DTI fibers in biological specimens. To achieve this goal, we derive the uncertainty in the reconstructed fiber tracts using different deterministic and stochastic fiber tracking algorithms. Through a unified representation of the derived uncertainty, we generate a new set of reconstructed fiber tracts that has a lower level of uncertainty. We will discuss our approach in detail and present the results we could achieve when applying it to several use cases.

Geopolymer concrete is known as an alternative to Portland cement, with low carbon dioxide emissions compared with the conventional building materials. In this research, the influence of curing conditions and alkali hydroxide were investigated, using curing temperatures between 40 to 100℃, curing times from 4 to 12 hours, and various types of hydroxide and concentrations of sodium hydroxide solution. Geopolymerization needs energy and time to occur, and higher curing temperatures resulted in larger compressive strength, while longer curing times resulted in higher compressive strength. At the same curing temperature, longer curing time resulted in a higher compressive strength because the longer curing time extends the chemical reaction. For geopolymer concrete, sodium hydroxide is a better property than potassium hydroxide, because the atomic size of sodium anion is smaller than potassium. Further, the strength of concrete increased when the concentration of sodium hydroxide increased. In conclusion, geopolymer concrete is suitable for traditional building materials. Finding renewable materials to satisfy the increasing demand for building structures will be the primary challenge in future.