Sustainable Engineering

A Review on Utilising Combined Agricultural Waste Adsorbents for Ammonia Nitrogen Removal: Insights into Bamboo Biochar and Empty Fruit Bunch

2024-07-17T12:28:20+08:00

This review highlights the effectiveness of bamboo biochar and empty fruit bunch (EFB) fibres as low-cost adsorbents for ammonia nitrogen removal from wastewater. Both materials are highlighted for their abundant availability and substantial adsorption capabilities. Bamboo biochar, derived from pyrolysed bamboo, benefits from its high surface area and porosity, enhanced further through chemical activation that increases its functional groups and pore structure. This modification significantly improves its efficiency in adsorbing ammonia nitrogen. Similarly, EFB, a by-product of palm oil production, is treated through carbonisation and activation, which enhances its adsorption properties. The review also discusses the potential for combining bamboo biochar and EFB, as their complementary properties could offer a more effective solution for wastewater treatment. The paper emphasises the advantages of these materials in addressing environmental challenges and highlights the need for further research into their combined use, as well as their potential for reuse and regeneration to promote sustainability. This review provides insights into optimising adsorbent modifications and exploring practical applications in wastewater treatment.

Keywords: Bamboo biochar; Modified empty fruit bunch; Combined adsorbent; Ammonia nitrogen Adsorption; Wastewater

Oil extraction from rice bran using conventional and bio-based solvents

2024-06-16T16:42:34+08:00

Rice bran is the outer layer of the rice grain, rich in essential nutrients and bioactive compounds. It is a valuable by-product used for various purposes, including the extraction of rice bran oil (RBO) known for its health benefits. This study focused on extracting oil from the nutritious rice bran using both conventional solvent (n-hexane) and bio-based solvent (isopropanol) for comparison under diverse conditions. The RBO yields were analysed at different temperatures of 40^oC, 50^oC, and 60^oC, with bran-to-solvent ratios of 1:3, 1:5, and 1:7, and extraction times of 2, 4, and 6 hours. The highest yields achieved were 12.4% for n-hexane at 60^oC, 1:7 ratio, and 6 hours, and 9.76% for isopropanol at 60^oC, 1:7 ratio, and 4 hours. The extracted oil underwent comprehensive physical analysis, including density, acid value, free fatty acid, and iodine value test. The physical analysis revealed density values of 0.867 g/mL for n-hexane and 0.866 g/mL for isopropanol. Acid values were 21.48 mg KOH/g (n-hexane) and 26.90 mg KOH/g (isopropanol). Free fatty acid percentages were 10.74% (n-hexane) and 13.45% (isopropanol). Iodine values were 65.48 mg (n-hexane) and 60.40 mg (isopropanol). The collected data were analysed using response surface methodology (RSM) to optimize the extraction condition, predicting the highest yield at 60^oC, with a bran-to-oil ratio of 1:5 parts solvent, and an extraction time of 6 hours. Statistical analysis confirmed the significance of the optimization model (p < 0.05). Overall, this study provided valuable insights, advancing more efficient and effective RBO production methods.

Keywords: rice bran; extraction; n-hexane; iso-propanol

Evaluation of Linear Elastic Dynamic Analysis Behavior on RC Buildings in Sabah Subjected to Moderate PGA

2024-07-18T15:26:17+08:00

Seismic performance of existing buildings in Southeast Sabah needs further examination, as there has been limited research. It is significant to explore the buildings respond to linear elastic dynamic analysis, especially considering that most reinforced concrete (RC) buildings insufficient earthquake-resistant technology. The current study aims to establish the correlation between peak ground acceleration (PGA) and the performance point of buildings under moderate PGA of 0.12g, 0.14g, and 0.16g, and then to assess the expected performance level of three RC buildings. The selection of three buildings within a 10 km radius from the active faults area. The buildings undergo an analytical method that necessitates the utilization of computational techniques to determine their capacity curve, demand curve, and performance point through the application of pushover analysis under the different of PGA. The performance point of buildings is determined by the intersection between capacity and demand curves, indicating Life Safety (LS) in inelastic range. This study critically evaluates the performance point of buildings that indicates inelastic displacement of the roof according to the intersection between capacity and demand curves under the various PGA.

Keywords: Performance point; RC buildings; Acceleration

Review of cost estimation practices for building projects using BIM

2024-07-04T15:16:13+08:00

Cost management remains one of the key challenges in architectural, engineering and construction (AEC) projects. Building information modeling (BIM) has gained popularity amongst AEC industry professionals due to its better visualization and clash detection abilities. The present study therefore attempts to review the cost estimation practices for building projects using BIM. The objective of the present study is to find answers to the research questions viz., 1) What are the various methodologies adopted for estimating building cost using BIM? and 2) Is BIM popular tool amongst cost management professionals? The literature review is divided into four parts. The first part of the literature review deals with general observations addressing issues and challenges of using BIM for cost estimation. The second part of the literature review covers different types of models and framework developed by researchers for estimating cost of building projects using BIM. The third part of the review investigates the key observations by various associated stakeholders on the usage of BIM for estimating building cost. The interpretation through various case studies is discussed in the last part of the literature review.

Keywords: Cost estimation; Cost management; BIM

A Review of Artificial Neural Networks (ANNs) as a Potential Predictive Tool for the Performance of Scissor-Type Deployable Bridges

2024-07-04T15:35:49+08:00

After a severe disaster, some places may be unreachable for rescue operations due to bridge destruction. A scissor-type deployable bridge is a novel rescue technology that enables a lifeline to be quickly recovered during a catastrophic event. Several structural analysis approaches were used to predict the structural behavior of deployable bridges. Yet none of the prior studies used Artificial Neural Networks (ANNs) to predict the structural behavior of scissor-type deployable bridges. This research explores the potentiality of Artificial Neural Networks (ANNs) to predict the performance of a scissor-type deployable bridge. The study aims to leverage the capabilities of ANNs in modeling complex relationships to forecast key parameters related to the bridge's functionality. ANNs can assist engineers in optimizing the design parameters of scissor-type deployable bridges by predicting how different configurations affect total deformation and stress levels. The analysis involves training the neural network with relevant data to enable it to learn and generalize patterns, enabling more informed predictions for diverse scenarios. Lastly, the application of ANNs in simulating bridge behavior contributes to advancing research in structural engineering, particularly in the field of deployable structures, by providing insights into complex structural responses that are challenging to model analytically.

Keywords: Deployable Bridge, Mobile Bridge, Scissor-Type Bridge, Aluminum Alloy, Artificial Neural Networks (ANNs), MATLAB