CSDL Bài trích Báo - Tạp chí
chủ đề: Civil engineering
1 Applications of Google OR-Tools in solving construction management linear optimization problems = Ứng dụng công cụ Google OR-Tools trong giải các bài toán tối ưu hóa tuyến tính trong quản lý dự án xây dựng / Hoang Nhat Duc, Nguyen Quoc Lam // .- 2021 .- Số 06(49) .- P. 3-7 .- 692
This study demonstrates the application of Google OR-Tools as a powerful, easy-to-use, and open source software suite in tackling linear programs. Herein, this open source tool has been integrated with Visual C# programming and the optimization models are formulated in Microsoft Visual Studio. Two optimization case studies are used in this study to illustrate the implementation of the Google OR-Tools.
2 Experimental study on influence of rice husk ash on mortar compressive strength at different temperatures = Nghiên cứu thực nghiệm ảnh hưởng của tro trấu tới cường độ của vữa ở các nhiệt độ khác nhau / Tran Thu Hien // .- 2022 .- Số 03(52) .- P. 51-59 .- 624
An experimental study on compressive strength of mortar mixes containing different amounts of rice husk ash (5, 10, 20%) has been investigated. The impact of different elevated temperatures (150, 300, 450, 750oC) on mortar strength is also examined. The experiments found that RHA can be used in its untreated form up to 10% as cementitious replacement without detriment of mortar compressive strength.
3 Influence of rice husk ash on mortar compressive strength at different temperatures : machine learning based modelling = Ảnh hưởng của tro trấu tới cường độ của vữa ở các nhiệt độ khác nhau : mô hình hóa bằng máy học / Tran Thu Hien, Hoang Nhat Duc // .- 2022 .- Số 05(54) .- P. 27-36 .- 624
This research is dedicated to the extension of the body of knowledge by proposing the application of three machine learning models for predicting compressive strength of mortar mixtures containing RHA. The Artificial Neural Network (ANN), Least Squares Support Vector Regression (LS-SVR) and Multivariate Adaptive Regression Splines (MARS) models were selected.
4 A review of metaheuristic optimized machine learning regression with applications in construction engineering = Khảo sát các mô hình học máy được tối ưu hóa bởi các thuật toán tìm kiếm với ứng dụng cho phân tích hồi quy trong ngành xây dựng / Hoang Nhat Duc, Nguyen Quoc Lama, Tran Van Duc // .- 2022 .- Số 05(54) .- P. 43-49 .- 624
This article aims at reviewing state-of-the-art research works involving the use of metaheuristic optimized machine learning regression models. Recent research articles published in the time period of 2019-2021 are surveyed.
5 Strand breakage detection in prestressed multi-strand anchorage structures using PZT interface technique = Chẩn đoán sự hư hỏng tao cáp dự ứng lực trong vùng neo cáp sử dụng hiệu trở kháng / Phan Ngoc Tuong Vy, Dang Ngoc Loi // .- 2023 .- Số 01(56) .- P. 27-35 .- 624
In this paper, the implementation of the PZT interface technique for monitoring strand breakage in a prestressed concrete anchorage zone is presented. First, the fundamental of the PZT interface for impedance monitoring is briefly reviewed. Second, a FE (finite element) analysis of a multi-strand concrete anchorage equipped with an array of PZT interfaces is analyzed to obtain impedance signatures under a series of strand breakage events. Last, variations in impedance responses of the PZT array are quantified using root-mean-square-deviation (RMSD), and the linear tomography analysis of impedance’s RMSD indices is utilized to localize damage strands.
6 Kernel regression models developed with Visual C# .NET for data analysis in construction engineering = Các mô hình hồi quy dựa vào hàm nhân được phát triển với ngôn ngữ Visual C# .NET và ứng dụng cho phân tích dữ liệu trong ngành xây dựng / Hoang Nhat Duc, Nguyen Quoc Lam // .- 2023 .- Số 01(56) .- P. 47-53 .- 624
This research work relies on kernel regression methods for constructing nonlinear regression models. These models can be used to solve function approximation tasks in construction engineering. The newly developed software program was developed with the Visual C# .NET. The program has been tested with the task of estimating the punching shear strength of steel fibre reinforced concrete slab.
7 Study on using rice husk ash from ceramic kiln as a partial alternative for cement in mortar = Nghiên cứu sử dụng tro trấu từ lò nung gốm để thay thế một phần xi măng trong vữa / Le Hoai Bao, Ngo Van Thuc, Nguyen Van Xuan, Tran Quang Huy // .- 2025 .- No. 03 .- P. 82-85 .- 690
This paper presents the use of rice husk ash that is recovered from burning rice husks in a local ceramic kiln. In this study, rice husk ash is used as a replacement for cement in different dosages of 0%, 5%, 10%, 15%, and 20%. The strength of the specimens was assessed at 7, 28, and 56 days of age. According to the results, rice husk ash added in amounts ranging from 5% to 15% performed equivalent to ordinary mortar in compressive strength.
8 Influence of rice husk ash on mortar compressive strength at different temperatures: Machine learning based modelling / Tran Thu Hien, Hoang Nhat Duc // Khoa học & Công nghệ Đại học Duy Tân .- 2022 .- Số 5(54) .- P. 27-36 .- 624
The impact of different rice husk ash contents (5, 10, 20%) on mortar strength is examined at different elevated temperatures (150, 300, 450, 750oC). Based on a 45 experimental result data set, three machine learning algorithms including the Artificial Neural Network (ANN), the Least Squares Support Vector Regression (LS-SVR) and the Multivariate Adaptive Regression Splines (MARS) have been used to model the functional relationship between the mixture components and the compressive strength. As a result, it is shown that LS-SVR consists in the most capable approach for modeling mortar strength with a good value of coefficient of determination (R2) = 0.80. Accordingly, this machine learning approach is potential to be used in RHA contained mix design by construction engineers.
9 Image processing-based automatic gradation of stone aggregates / Hoang Nhat Duc, Nguyen Quoc Lam, Pham Quang Nhat // Khoa học & Công nghệ Đại học Duy Tân .- 2022 .- Số 5(54) .- P. 37-42 .- 624
Gradation strongly influences the mechanical properties of stone materials. This paper aims to employ image processing methods to develop a simple tool for automatic gradation of stone aggregates. The methods of image thresholding, Gaussian filtering, median filtering, morphological closing, and contour analysis are employed. The output of the newly constructed system is the plots demonstrating particle size distribution. These plots can be used for further inspection of aggregate gradation. The system has been developed in Python and with the help of the OpenCV library.
10 A review of metaheuristic optimized machine learning regression with applications in construction engineering / Hoang Nhat Duc, Nguyen Quoc Lam, Tran Van Duc // Khoa học & Công nghệ Đại học Duy Tân .- 2022 .- Số 5(54) .- P. 43-49 .- 624
Regression analysis is an essential task in construction engineering. This article aims at reviewing state-of-the-art research works involving the use of metaheuristic optimized machine learning regression models. Recent research articles published in the time period of 2019-2021 are surveyed. Research areas of construction material, construction management, structural engineering, geotechnical engineering, hydraulic engineering, and structural health monitoring are taken into account. It is expected that the present review would enhance interest among the new users in the application of metaheuristic optimized machine learning regression approaches.