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INDONESIA
Civil Engineering Journal
Published by C.E.J Publishing Group
ISSN : 24763055     EISSN : 24763055     DOI : -
Core Subject : Engineering,
Civil Engineering, Building, Construction & Architecture
Civil Engineering Journal is a multidisciplinary, an open-access, internationally double-blind peer -reviewed journal concerned with all aspects of civil engineering, which include but are not necessarily restricted to: Building Materials and Structures, Coastal and Harbor Engineering, Constructions Technology, Constructions Management, Road and Bridge Engineering, Renovation of Buildings, Earthquake Engineering, Environmental Engineering, Geotechnical Engineering, Highway Engineering, Hydraulic and Hydraulic Structures, Structural Engineering, Surveying and Geo-Spatial Engineering, Transportation Engineering, Tunnel Engineering, Urban Engineering and Economy, Water Resources Engineering, Urban Drainage.
Arjuna Subject : -
Articles 1,848 Documents
 98   99   100   101   102 
High Strength Concrete Beams Reinforced with Hooked Steel Fibers under Pure Torsion Hussain, Haleem K.; Zewair, Mustafa Shareef; Ahmed, Mazin Abdulimam
Civil Engineering Journal Vol 8, No 1 (2022): January
Publisher : Salehan Institute of Higher Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/CEJ-2022-08-01-07

Abstract

A study of the behavior of fibers in high-strength reinforced concrete beams is presented in this paper. Twelve reinforced concrete beams were tested under a pure torsion load. Different compressive strengths (45.2, 64.7, and 84.8 MPa) and fiber volume fractions (0, 0.25, 0.5, and 0.75) with variable spacing between transverse reinforcements have been used. It was discovered that the maximum torque of a high-strength concrete beam is increased by about 20.3, 25.6, and 27.1% when the fractional volume of fiber is increased from 0 to 0.25, 0.5 and 0.75 respectively (when the compressive strength is 45.2 MPa and the transverse reinforcement spacing is 100 mm). The test results show that the ultimate torsional strength becomes higher when the concrete compressive strength increases, and this percentage increase becomes higher with increasing steel fiber volume fraction. When the spacing between transverse reinforcements decreases from 150 to 100 mm, the ultimate torque increases by 19.9%. When the spacing between transverse reinforcements decreases from 100 to 60 mm, the ultimate torque increases by 17.0%. In these beams, the fibers’ compressive strength and volume fraction were kept constant at 45.2 MPa and 0.75, respectively. Doi: 10.28991/CEJ-2022-08-01-07 Full Text: PDF
Fuzzy Analytical Hierarchy Processes for Damage State Assessment of Arch Masonry Bridge Mostefa Lallam; Abdelhamid Mammeri; Abdelkader Djebli
Civil Engineering Journal Vol 7, No 11 (2021): November
Publisher : Salehan Institute of Higher Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/cej-2021-03091770

Abstract

The present work proposes a fuzzy analytical hierarchy approach for decision making in the maintenance programming of masonry arch bridges. As a practical case, we propose to classify the degradation state of the Mohammadia masonry bridge. A large number of criteria and sub-criteria are combined to classify this type of bridges through visual inspections. The main criteria (level 1) considered in this work are the history of the bridge, the environmental conditions, the structural capacity and the professional involvement of the bridge. In addition, these criteria are subdivided into several sub-criteria (level 2) which are, in turn, subdivided into sub-criteria (level 3). Considering these criteria and sub-criteria, weights Wiare calculated by fuzzy geometric mean method of Buckley. Subsequently, expert scores were assigned to calculate the overall score CS reflecting the degradation of the considered infrastructure. Thereafter, the masonry arch bridges are classified respecting the French IQOA scoring system using the overall scores value CS. The proposed classification method gave similar results provided by an expert’s study realized previously as part of a national patrimony preservation policy. The obtained results are in good agreement, which makes this method an effective scientific tool for decision-making in view of prioritization of the maintenance after systematic inspection of masonry bridges such as the bridge studied in this work. Doi: 10.28991/cej-2021-03091770 Full Text: PDF
Maritime Climate in the Canary Islands and its Implications for the Construction of Coastal Infrastructures Jesica Rodríguez-Martín; Noelia Cruz-Pérez; Juan C. Santamarta
Civil Engineering Journal Vol 8, No 1 (2022): January
Publisher : Salehan Institute of Higher Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/CEJ-2022-08-01-02

Abstract

Islands are isolated systems that depend on maritime trade for their subsistence. Efficient, durable and structurally reliable port infrastructures are essential for the economic and social development of islands. However, not all port infrastructures are designed in the same way. They can vary, depending on whether they are built on continental land, built on non-volcanic islands or built on volcanic oceanic islands (such as the Canary Islands, Spain). The latter islands are the subject of this study due to their specific features, construction difficulties and the importance of sound maritime infrastructures. The maritime climate of an area consists of the wave and storm regimes that affect it and, from these, the coastal dynamics and coastal formations of that area can be studied. For this reason, historical data were collated on significant directional wave heights from 1958 to 2015 from several WANA-SIMAR points in the virtual buoy network of State Ports of Spain located near the Canary Islands. These data have been studied to obtain the maximum directional wave heights (Hs) at each point. With this analysis, we have obtained useful summary tables to calculate wave height by a graphic method that transforms the distribution function into a line drawn on probabilistic paper, using reduced variables. This enables adjustments to be made by linear regression and minimum square methods to facilitate planning and design of maritime infrastructures in a reliable way. Doi: 10.28991/CEJ-2022-08-01-02 Full Text: PDF
Field Assessment of Non-nuclear Methods Used for Hot Mix Asphalt Density Measurement Zaman, Shah; Hussain, Jawad; Ahmad Zaidi, Syed Bilal; Ejaz, Naeem; Awan, Hammad Hussain
Civil Engineering Journal Vol 5, No 8 (2019): August
Publisher : Salehan Institute of Higher Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/cej-2019-03091374

Abstract

Destructive nature along with the associated higher cost of the traditional core method used for hot mix asphalt density measurement has convinced researchers switching to some non-destructive technique for this purpose which is cost efficient as well. Earlier, nuclear density gauges were introduced for this purpose which was non-destructive as well. Since such devices were associated with the use of gamma rays, therefore, leading to safety and health issues. Last decade observed a revolution in asphalt density measurement technique with the evolution of non-nuclear density gauges. This research work is carried out with the objective to determine the efficiency and accuracy of a newly developed non-nuclear density gauge i.e. PQI-380 for field conditions as it needs its thorough evaluation prior to future uses in many of the developing countries including Pakistan. Density data obtained using standard core method and non-nuclear density gauge for 195 location confirms the satisfactory performance of the instrument. Results obtained show that the coefficient of correlation is near to 0.9. which refers to a strong correlation between the density data. Moreover, performance criteria e.g. root mean square error and mean absolute error between the density data set is also very low confirming the good measuring abilities of the device. Instrument performed well for repeatability analysis giving maximum coefficient of variance less than 5 percent.
Manufacturing and Performance of an Economical 1-D Shake Table Aamar Danish; Naveed Ahmad; M. Usama Salim
Civil Engineering Journal Vol 5, No 9 (2019): September
Publisher : Salehan Institute of Higher Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/cej-2019-03091390

Abstract

The researchers and engineers encountered many problems to precisely replicate earthquake waves. Earthquakes are one of the nature's worst catastrophes and are still unpredictable. Statistical research has shown that the earthquakes have increased in frequency in recent years and have become a major concern for the world especially for those countries which are located on the fault lines such as Japan, Bangladesh and Pakistan. So, it was imperative to device a mechanism to check earthquake response and apply some necessary mitigations for the safety of humanity. After many years of research an indispensable testing apparatus was designed named as Shake Table. This apparatus is extensively used in earthquake research centers globally because it is the best available apparatus to replicate the earthquakes imposed dynamic effects on structures. A uni-axial shaking table was designed, manufactured and installed in University of Engineering & Technology Taxila, Pakistan which is operated on 3 HP servo motor coupled with encoder, motion controller and supported on HSB mechanical linear drive. The system was assembled in a simple way with care to endure sufficient replication of given (recorded) motion by shake table system. This paper focuses on the designing, manufacturing and performance of an economical analytical model of 1-D shake table incorporating conjunction of structural dynamics and linear control theory.
The Effect of Adding Steel Fibers and Graphite on Mechanical and Electrical Behaviors of Asphalt Concrete M. Messaoud; B. Glaoui; O. Abdelkhalek
Civil Engineering Journal Vol 8, No 2 (2022): February
Publisher : Salehan Institute of Higher Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/CEJ-2022-08-02-012

Abstract

Conductive asphalt concrete can satisfy different and multifunctional applications such as heating roads to get rid of snow and ice and assure auto-detection, auto-cure, and energy recovery. This research aims to evaluate the performance of asphalt concrete with additives like steel fibers and graphite powder. This work is based on destructive tests (direct tensile test FENIX) and non-destructive tests (electrical resistivity measures). The obtained results indicate that the tensile resistance, dissipated energy, and ductility module of asphalt concrete increased with the increasing steel fiber percentage. Direct tensile strength, cracking resistance, and dissipated energy increased as graphite percentage increased, while the ductility module decreased. Electrical resistivity decreased when it added steel fibers and graphite. Therefore, it found that tensile strength increased reversibly with electrical resistance. When adding steel fibers or graphite powder, the dissipated energy of asphalt concrete is increased while electrical resistivity is decreased. The dissipated energy of conductive asphalt concrete with steel fibers is higher than that with graphite powder. Electrical resistivity decreased significantly with increasing steel fibers, compared to electrical resistivity with graphite. The obtained results indicate that asphalt concrete cracking resistance is higher with the optimal percentage of steel fibers added at 1% and better mechanical performance. Doi: 10.28991/CEJ-2022-08-02-012 Full Text: PDF
Heterogeneity based Mode Choice Behaviour for Introduction of Sustainable Intermediate Public Transport (IPT) Modes Saurabh Kumar; Sanjeev Sinha
Civil Engineering Journal Vol 8, No 3 (2022): March
Publisher : Salehan Institute of Higher Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/CEJ-2022-08-03-09

Abstract

Intermediate public transport (IPT) supplements the public transport system by providing first and last-mile connectivity to commuters. A feeder service based on sustainable intermediate public transportation can be made attractive by improving its mobility, accessibility, convenience, and comfort for its users. Sustainable IPT modes have a lower impact on the environment and can cater to the current and future needs of transportation. In this study, commuters' choice responses were collected using a stated preference survey instrument, and the database was analyzed using a Random Parameter Logit (RPL) model. Face-to-face interviews were conducted with respondents who were approached at random. A different combination of values from the levels of attributes was used to create choice scenarios for each IPT mode. Different types of IPT modes were identified in the study act as feeder services, which was used to find their utility functions using a random parameter logit model. The random parameter logit model with heterogeneity was used to evaluate the impacts of different socioeconomic and trip features on mean estimations. The utility function was used to find willingness to pay (WTP) for different attributes of an IPT mode to assess the relative value of these attributes. It was observed that WTP values also varied between different levels, which were based on their "monthly income level", "trip purpose", and "fare". "High income level" commuters have a higher WTP for travel time, frequency, and comfort improvements. On the other hand, the "work trip" and "high travel fare" levels of commuters have higher WTP for travel time, frequency, and safety improvements. According to the findings of the study, sustainable IPT modes with high quality of service are recommended because of commuters' willingness to pay for improved safety and comfort. The results so obtained can also be used for a better understanding of the travel behaviour analysis of various IPT modes. Doi: 10.28991/CEJ-2022-08-03-09 Full Text: PDF
Investigating the Effect of Gradation, Temperature and Loading Duration on the Resilient Modulus of Asphalt Concrete Muhammad Junaid; Muhammad Zafar Ali Shah; Ghulam Yaseen; Hammad Hussain Awan; Daud Khan; Muhammad Jawad
Civil Engineering Journal Vol 8, No 2 (2022): February
Publisher : Salehan Institute of Higher Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/CEJ-2022-08-02-07

Abstract

This research was carried out to assess the effect of aggregate skeleton, temperature variation, and loading duration on the resilient modulus of asphalt concrete mixtures. Two different gradation methods, i.e., the conventional method of gradation and the Bailey method of gradation, were adopted to design the aggregate skeleton. The effect of these gradation methods, with temperature and loading duration, on the resilient modulus of asphalt concrete has not been previously investigated. The Modified Marshall Test was used to determine optimum binder content against 4% air voids, and then volumetric and strength parameters were calculated against optimum binder content. For performance tests, specimens were prepared at optimum binder content using a Superpave gyratory compactor. An indirect tensile strength test on both types of mixtures was conducted, and a 20% value of indirect tensile strength was kept for peak load, whereas 10% was kept for seating load for conducting resilient modulus tests. The tests were conducted at 100 and 300 ms duration loads under two different temperatures, i.e., 25 oC and 40 oC. The results declared that aggregate skeleton, temperature, and loading duration have a prominent effect on the resilient modulus of asphalt concrete mixtures. Bailey gradation mixtures disclosed higher resilient modulus values than conventional gradation mixtures. Higher values of resilient modulus were observed for both gradation mixtures at low temperatures and under small duration loads than at high temperatures and large duration loads. The results of the two-way factorial design also confirmed the above findings. Doi: 10.28991/CEJ-2022-08-02-07 Full Text: PDF
A Statistical Model to Predict the Strength Development of Geopolymer Concrete Based on SiO2/Al2O3 Ratio Variation Ali A. Ali; Tareq S. Al-Attar; Waleed A. Abbas
Civil Engineering Journal Vol 8, No 3 (2022): March
Publisher : Salehan Institute of Higher Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/CEJ-2022-08-03-04

Abstract

Geopolymer Concrete (GPC) is a new class of concrete that presents a vital improvement in sustainability and the environment, particularly in recycling and alternative construction methods. Geopolymers offer a sustainable, low energy consumption, low carbon footprint, and a 100% substitute for the Portland cement binder for civil infrastructure applications. Furthermore, many aluminosilicate materials can be obtained as by-products of other processes, such as coal combustion or the thermal pulping of wood. In addition, slag and fly ash are necessary to source materials for geopolymer. Therefore, geopolymer is considered a solution for waste management that can minimize greenhouse gas emissions. In this statistical study, the present experimental work and found experimental data were collected from local and international literature and were used to build and validate the statistical models to predict the strength development of Geopolymer concrete with binary and ternary systems of source materials. The main independent variable was R, representing the ratio of SiO2/Al2O3by weight in the source material. The investigated range of R was 1.42–3.6. Nine concrete geopolymer mixes with R in the above range represent the experimental part carried out. The targeted properties were compressive, splitting, and flexural strengths. The experimental results showed that the R ratio significantly influences the mechanical performance of the final product. The compressive strength improved by 82, 86, 93, and 95%, when metakaolin content was partially replaced by fly ash and GGBS by percentages of 30, 70, 72, 90, and 95% for mixes 2, 3, 5, 7, and 8 respectively. Also, when GGBS partially replaced fly ash content by 36% and 100% for mixes 6 and 9, compressive strength improved by 10.6% and 41.8%, respectively, compared to mix4. Furthermore, the statistical study revealed that the R ratio might be utilized to determine geopolymer strength with reasonable accuracy. The built models were developed by linear and non-linear regression analysis using SPSS software, version 25. Doi: 10.28991/CEJ-2022-08-03-04 Full Text: PDF
Landslide Susceptibility Mapping using Machine Learning Algorithm Muhammad Afaq Hussain; Zhanlong Chen; Run Wang; Safeer Ullah Shah; Muhammad Shoaib; Nafees Ali; Daozhu Xu; Chao Ma
Civil Engineering Journal Vol 8, No 2 (2022): February
Publisher : Salehan Institute of Higher Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/CEJ-2022-08-02-02

Abstract

Landslides are natural disasters that have resulted in the loss of economies and lives over the years. The landslides caused by the 2005 Muzaffarabad earthquake heavily impacted the area, and slopes in the region have become unstable. This research was carried out to find out which areas, as in Muzaffarabad district, are sensitive to landslides and to define the relationship between landslides and geo-environmental factors using three tree-based classifiers, namely, Extreme Gradient Boosting (XGBoost), Random Forest (RF), and k-Nearest Neighbors (KNN). These machine learning models are innovative and can assess environmental problems and hazards for any given area on a regional scale. The research consists of three steps: Firstly, for training and validation, 94 historical landslides were randomly split into a proportion of 7/3. Secondly, topographical and geological data as well as satellite imagery were gathered, analyzed, and built into a spatial database using GIS Environment. Nine layers of landslide-conditioning factors were developed, including Aspect, Elevation, Slope, NDVI, Curvature, SPI, TWI, Lithology, and Landcover. Finally, the receiver operating characteristic (ROC) curve and the area under the ROC curve (AUC) value were used to estimate the model's efficiency. The area under the curve values for the RF, XGBoost, and KNN models are 0.895 (89.5%), 0.893 (89.3%), and 0.790 (79.0%), respectively. Based on the three machine learning techniques, the innovative outputs show that the performance of the Random Forest model has a maximum AUC value of 0.895, and it is more efficient than the other tree-based classifiers. Elevation and Slope were determined as the most important factors affecting landslides in this research area. The landslide susceptibility maps were classified into four classes: low, moderate, high, and very high susceptibility. The result maps are useful for future generalized construction operations, such as selecting and conserving new urban and infrastructural areas. Doi: 10.28991/CEJ-2022-08-02-02 Full Text: PDF

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