• International Journal of Highway Engineering
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• v.7 no.3 s.25
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• pp.71-78
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• 2005

This study focuses on finding out engineering characteristics of asphalt concrete mixtures using mineral fillers with recycled waste lime, which is a by-product in the Soda Ash(Na2CO3) production course. The materials tested in this study were made with 25%, 50%, 75% and 100% of mixing ratio based on the conventional mineral filler ratio to analyze the recycle possibility of the waste lime. The asphalt concrete mixtures with recycled waste lime and hydrated lime, and conventional asphalt concrete mixtures were evaluated through their fundamental engineering properties such as Marshall stability, indirect tensile strength, resilient modulus, permanent deformation characteristics, moisture susceptibility and fatigue resistance. The results indicate that the application of recycled waste lime as mineral filler improves the permanent deformation characteristics, stiffness and fatigue endurance of asphalt concrete mixtures at the wide range of temperatures. It is also found that the mixtures with recycled waste lime show higher resistance against stripping than conventional asphalt concrete mixtures. It is concluded from various test results that the waste lime can be used as mineral fillers and especially can greatly improve resistance to permanent deformation of asphalt concrete mixtures at high temperatures.

• Journal of the Korean Recycled Construction Resources Institute
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• v.9 no.1
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• pp.109-116
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• 2021

In order to replace mineral aggregate used as road pavement materials with steel slag aggregate, this present study evaluated mechanical properties of SMA Concrete mixtures using steel slag aggregate as oxidized slag from electric furnace in iron works. The variables of this experiment are the aggregate type of mineral and steel slag and the sieve sized of 10mm and 13mm. The physical properties inclu ding the specific gravity and absorption rate etc. of the slag aggregate mixtu res satisfied the KS standard as asphalt mixtu re. As a resu lt of evalu ating the mechanical properties of the asphalt mixtures, the optimum asphalt content of the slag aggregate mixtures were lower than that of the mineral aggregate mixtures, but other quality standards were all satisfied. In the deformation strength evaluation, the slag aggregate mixtures were measu red slightly higher than that of the mineral aggregate mixtu res, and the dynamic stability test satisfied the 2,000pass/mm standard value in all specimens. And, the moduli of resilient of the slag aggregate mixtures showed an improved value compared with the mineral aggregate mixtures. Therefore, as the resilient rate of the slag aggregate mixtures improved, it is speculated that there will be an effect of improving public performance according to the repeated traffic load of the vehicle.

• Journal of Soil and Groundwater Environment
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• v.14 no.5
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• pp.18-28
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• 2009

Both feasibility and accuracy of lumped approach to group 12 organic compounds in mixtures into a fewer number of pseudocompounds in sorption processes were evaluated using mixtures containing organic compounds with various physicochemical properties and low-surface-area mineral sorbents. The lumped approach for sorption to simulated mineral sorbents was developed by cluster analysis from statistics. Using the lumped approach, the sorption estimated from both reduced number of pseudocompounds and their sorption parameters (i.e., $K_f$, n) can approximate sorption behavior of complex organic mixtures. Additionally, the pseudocompounds for various mixtures to different types of low-surface-area mineral sorbents can be estimated a priori from the physicochemical properties of organic compound (i.e., ${\gamma_w}^{sat}$). Therefore, the lumped approach may help to simplify the complex fate and transport model of organic contaminant mixtures, reduce experimental efforts, and yet provide results that are statistically identical for practical purposes. Further research is warranted to enhance the accuracy of lumped approach using the multiple regression analysis considering the H-bonding capacity, site concentrations, functional groups for mineral sorbents.

• International Journal of Concrete Structures and Materials
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• v.6 no.1
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• pp.31-40
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• 2012

Self-consolidating concrete (SCC) is a recently developed innovative construction material. SCC fills in a formwork without any vibrating consolidation, which allows us to eventually achieve robust casting. However, high formwork lateral pressure exerted by SCC is a critical issue regarding its application as cast-in-place concrete. In order to control the risk caused by high formwork pressure, a comprehensive prediction model for the pressure was previously proposed, investigated, and validated with various SCC mixtures. The model was originally designed to simulate the intrinsic pressure response of SCC mixtures while excluding other extrinsic influencing factors such as friction and flexibility of the formwork. The model was then extended to consider extrinsic factors such as friction between SCC mixtures and formwork. In addition, other interesting topics for peak formwork pressure and mineral admixture effects were summarized in the paper.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.402-404
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• 2003

We present two methods for the automatic selection of the threshold values in unsupervised change detection. Both methods consist of the same two procedures: 1) to determine the parameters of Gaussian mixtures from a difference image or ratio image, 2) to determine threshold values using the Bayesian rule for minimum error. In the first method, the Expectation-Maximization algorithm is applied for estimating the parameters of the Gaussian mixtures. The second method is based on the iterative thresholding that successively employs thresholding and estimation of the model parameters. The effectiveness and applicability of the methods proposed here are illustrated by an experiment on the multi-temporal KOMPAT-1 EOC images.

• Proceedings of the Korean Society of Soil and Groundwater Environment Conference
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• 2005.10a
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• pp.77-77
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• 2005

• Magazine of the Korean Society of Agricultural Engineers
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• v.21 no.1
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• pp.63-77
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• 1979

Six kinds of weathered granite soils whose degree of weathering and mineral compo- sitions are different, were tested in order to improve the soil-cement. by performing compression test, durability (freezing-thawing) test and mesurement of shrinkage are made. From result of the tests as mentioned above, the following conclusions are drawn. The unconfined compressive strength of seondary additives containing soil-cement mixtures and their resistance against freezeing-thawing are more increased and shrinkage is more decreased than soil-cement mixtures only in case opitimun quantity of additives are added to soil-cement mixtures, and according as types of soils.

• Proceedings of the Korean Institute of Resources Recycling Conference
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• 1993.03a
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• pp.7.1-7
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• 1993

• Journal of the Mineralogical Society of Korea
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• v.26 no.1
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• pp.27-34
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• 2013

X-ray powder diffraction is one of the most powerful techniques for qualitative and quantitative analysis of crystalline compounds. Thus, there exist a number of different methods for quantifying mineral mixtures using X-ray diffraction pattern. We present here the use of Rietveld and PONKCS (partial or no known crystal structure) methods for quantification of amorphous and crystallized mineral phases in synthetic mixtures of standard minerals (amorphous silica, quartz, mullite and corundum). Pawley phase model of amorphous silica was successfully built from the pattern of 100 wt% amorphous silica and internal standard-spiked samples by PONKCS approach. The average of absolute bias for quantities of amorphous silica was 1.85 wt%. The larger bias observed for lower quantities of amorphous silica is probably explained by low intensities of diffraction pattern. Averages of absolute bias for minerals were 0.53 wt% for quartz, 0.87 wt% for mullite and 0.57 wt% for corundum, respectively. The PONKCS approach achieved improved quantitative results compared with classical Rietveld method by using an internal standard.

• Journal of the Korean Geosynthetics Society
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• v.23 no.1
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• pp.17-25
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• 2024

The Voids in the Mineral Aggregate (VMA) within asphalt mixtures play a crucial role in defining the mixture's structural integrity, durability, and resistance to environmental factors. Accurate prediction and optimization of VMA are essential for enhancing the performance and longevity of asphalt pavements, particularly in varying climatic and environmental conditions. This study introduces a novel machine learning framework leveraging ensemble machine learning model for predicting VMA in asphalt mixtures. By analyzing a comprehensive set of variables, including aggregate size distribution, binder content, and compaction levels, our framework offers a more precise prediction of VMA than traditional single-model approaches. The use of advanced machine learning techniques not only surpasses the accuracy of conventional empirical methods but also significantly reduces the reliance on extensive laboratory testing. Our findings highlight the effectiveness of a data-driven approach in the field of asphalt mixture design, showcasing a path toward more efficient and sustainable pavement engineering practices. This research contributes to the advancement of predictive modeling in construction materials, offering valuable insights for the design and optimization of asphalt mixtures with optimal void characteristics.