[신간의 별자리x] 우리/미술, 그리고 ‘슬픔의 박물관’

The American Society for Testing and Materials (ASTM) is an independent organization devoted to the development of standards.

American Society for Testing and Materials

Nature And Properties Of Soils

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A User’s Guide

Learning incorporates a broad range of complex procedures. Machine learning (ML) is a subdivision of artificial intelligence based on the biological learning process. The ML approach deals with the design of algorithms to learn from machine readable data. ML covers main domains such as data mining, difficult-to-program applications, and software applications. It is a collection of a variety of algorithms (e.g. neural networks, support vector machines, self-organizing map, decision trees, random forests, case-based reasoning, genetic programming, etc.) that can provide multivariate, nonlinear, nonparametric regression or classification. The modeling capabilities of the ML-based methods have resulted in their extensive applications in science and engineering. Herein, the role of ML as an effective approach for solving problems in geosciences and remote sensing will be highlighted. The unique features of some of the ML techniques will be outlined with a specific attention to genetic programming paradigm. Furthermore, nonparametric regression and classification illustrative examples are presented to demonstrate the efficiency of ML for tackling the geosciences and remote sensing problems.

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Machine learning in geosciences and remote sensing

Evaluation of liquefaction induced lateral displacements using genetic programming

Intrusion of seawater into coastal aquifers is considered one of the most important processes that degrade water-quality by raising the salinity to levels exceeding acceptable drinking standards. Therefore saltwater intrusion should be prevented or at least controlled to protect groundwater resources. This paper presents a cost-effective method to control seawater intrusion in coastal aquifers. This methodology ADR (Abstraction, Desalination and Recharge) includes; abstraction of saline water and recharge to the aquifer after desalination. A coupled transient density-dependent finite element model is developed for simulation of fluid flow and solute transport and used to simulate seawater intrusion. The simulation model has been integrated with an optimization model to examine three scenarios to control seawater intrusion including; abstraction, recharge and a combination system, ADR. The main objectives of the models are to determine the optimal depths, locations and abstraction/recharge rates for the wells to minimize the total costs for construction and operation as well as salt concentrations in the aquifer. A comparison between the combined system (ADR) and the individual abstraction or recharge system is made in terms of total cost and total salt concentration in the aquifer and the amount of repulsion of seawater achieved. The results show that the proposed ADR system performs significantly better than using abstraction or recharge wells alone as it gives the least cost and least salt concentration in the aquifer. ADR is considered an effective tool to control seawater intrusion and can be applied in areas where there is a risk of seawater intrusion.

A Cost-Effective Method to Control Seawater Intrusion in Coastal Aquifers

In this paper, a new genetic programming (GP) approach for predicting settlement of shallow foundations is presented. The GP model is developed and verified using a large database of standard penet...

A new genetic programming model for predicting settlement of shallow foundations

A series of experiments were carried out to investigate the behavior of cement-stabilized fiber-reinforced clay with different cement and fiber contents. Three groups of tests were conducted, on: (1) reinforced samples with four different fiber contents (0.5%, 0.75%, 1% and 1.25%); (2) cement-stabilized samples with three different cement contents (5%, 8% and 10%); and (3) cement-stabilized, fiber-reinforced samples with the same fiber contents as the uncemented reinforced samples. Unconfined compression tests (UCT) were carried out on the uncemented samples. These UCT tests were also conducted on the cement-stabilized samples with and without fiber inclusions after 3, 7, 14 and 28 days of curing time. The results indicated that the inclusion of fibers within uncemented and cement-stabilized soil caused an increase in the unconfined compressive strength and axial strain at failure, and changed the brittle behavior of the cement-stabilized soil to a more ductile behavior. It was also shown that t...

Akbar A. Javadi

Papers

Evaluation of liquefaction induced lateral displacements using genetic programming

A Cost-Effective Method to Control Seawater Intrusion in Coastal Aquifers

A new genetic programming model for predicting settlement of shallow foundations

Behavior of cement-stabilized clay reinforced with nylon fiber

Triaxial tests of sand reinforced with 3D inclusions