Civil Engineering

Oil palm is one of the major economic crops in many countries. Malaysia alone produces about 47% of the world's palm oil supply and can be considered as the world's largest producer and exporter of palm oil. Malaysia also generates huge quantity of oil palm biomass including oil palm trunks, oil palm fronds, empty fruit bunches (EFB), shells and fibers as waste from palm oil fruit harvest and oil extraction processing. At present there is a continuously increasing interest in the utilization of oil palm biomass as a source of clean energy. One of the major interests is hydrogen from oil palm biomass. Hydrogen from biomass is a clean and efficient energy source and is expected to take a significant role in future energy demand due to the raw material availability.

A study on gasification of empty fruit bunch (EFB), a waste of the palm oil industry, was investigated. The composition and particle size distribution of feedstock were determined and the thermal degradation behaviour was analysed by a thermogravimetric analysis (TGA). Then fluidized bed bench scale gasification unit was used to investigate the effect of the operating parameters on EFB air gasification namely reactor temperature in the range of 700-1000°C, feedstock particle size in the range of 0.3-1.0 mm and equivalence ratio (ER) in the range of 0.15-0.35. The main gas species generated, as identified by a gas chromatography (GC), were H 2 , CO, CO 2 and CH 4 . With temperature increasing from 700°C to 1000°C, the total gas yield was enhanced greatly and reached the maximum value ($92 wt.%, on the raw biomass sample basis) at 1000°C with big portions of H 2 (38.02 vol.%) and CO (36.36 vol.%). Feedstock particle size showed an influence on the upgrading of H 2 , CO and CH 4 yields. The feedstock particle size of 0.3-0.5 mm, was found to obtain a higher H 2 yield (33.93 vol.%), and higher LHV of gas product (15.26 MJ/m 3 ). Equivalence ratio (ER) showed a significant influence on the upgrading of hydrogen production and product distribution. The optimum ER (0.25) was found to attain a higher H 2 yield (27.31 vol.%) at 850°C. Due to the low efficiency of bench scale gasification unit the system needs to be scaling-up. The cost analysis for scale-up EFB gasification unit showed that the hydrogen supply cost is RM 6.70/kg EFB ($2.11/kg = $0.18/Nm 3 ).

Soil deformation is one of the major interests with regard to the stability analysis of the foundations. The deformations are signified for both vertical and lateral soil deformation; which the former plays vital role in designing a good foundation. As the stability of the foundation affect the stability of the entire structure, instrumentation and monitoring play an important roles in order to monitor the performances of the geotechnical structures. Until now the design of a foundation soil system is relied on the quantification of soil bearing capacity and foundation structural capacity and then followed by conventional monitoring system to observe the settlement so that within the allowable values. Therefore, this study focuses on the newly usage of distributed optical fibre sensing application to monitor strain distribution within a soil mass due to surcharge loading. It is expected to observe the strain distribution goes proportionally to vertical stress distribution concept; w...

For almost two decades, distributed optical fibre sensors are well-known for an alternative to conventional instrumentation in geotechnical engineering applications. However, the technology is yet to be fully implemented due to uncertainties of attachment method or the best way to deploy optical fibre for geo-structure health monitoring. Thus, a project of a 1g model of soil slope was intiated and was constructed with three layers of optical fibre that were horizontally embedded in the soil slope mass in order to observe strain development due to a surcharge load. The strain mobilizations were measured by using Brillouin Optical Time-Domain Analysis (BOTDA) sensing system during the incremental loading on the slope crest until a failure feature had been initiated. The aim of study is to evaluate the development of horizontal strains from Brillouin-based optical fibre sensor subjected to soil slope deformation which lead to slope failures. The results showed that the measurands of op...

Rainfall is inevitably one of the main factors that trigger landslides. However, not much study has been conducted on the impact of groundwater rise on slope stability. Thus, this study is intended to focus on the rise of the groundwater level from the bottom of the slope which would lead to landslides due to pore pressure development by eliminating other landslide-triggering factors (i.e., infiltration and surface runoff). Saturated sand was used for slope modeling, and sand densities of 1523 kg/m3, 1562 kg/m3, and 1592 kg/m3 were tested with a constant slope angle of 45°. Another set of experiments was also performed on slopes having angles of 25°, 45°, and 60° and with a maintained density of sand at 1562 kg/m3. Through observation, failure was initiated first at the toe of the slope before minor and major slips or total collapse occurs. Dimensions of slip surfaces were measured and included in SLOPE/W for the computation of the safety factor. In conclusion, safety factors are fo...

Rainfall infiltration is well-known as one of the important factors that lead to slope failure in tropical areas such Malaysia because it’s significant fluctuation of pore water pressure due to monsoon seasons. In this paper, a distributed sensing optical fibre system named Brillouin Optical Time Domain Analysis (BOTDA) is used to monitor the strain development of a laboratory soil slope model. The aim of study is to determine the plane failure of a residual soil slope under rainfall infiltration and subsequent loading impact using BOTDA technology. A soil slope model was constructed from Malaysian residual soil slope and tested under various rainfall infiltration patterns and sequential loadings. A continuous ribbon optical fibre has been directly embedded in the soil slope to measure the soil strain. The paper only presented on soil strain response due to rainfall infiltration and relations to the pore pressure development within the finite slope. From the experiments, it has been...

This handbook is a reference for the faculty, academic and administrative staff on the process and procedures involved in preparing and obtaining accreditation. This handbook also serves as a valuable guide for the faculty to develop an assessment plan in the process of future accreditation

Bitumen merupakan bahan perekat dalam turapan jalan raya yang sering digunakan di Malaysia. Penggunaan bitumen lebih meluas berbanding tar kerana tar diperolehi daripada proses penyulingan musnah terhadap arang batu. Di Malaysia arang batu tidak dihasilkan dan disebabkan itu penggunaan tar menjadi terhad.

On a macroscale, the effect of installing prefabricated vertical drains (PVDs) in a subsoil is to increase the mass hydraulic conductivity of the subsoil in the vertical direction. Based on this concept, a simple method for modeling PVD improved subsoils is proposed, in which an equivalent vertical hydraulic conductivity k v e for the PVD improved subsoil is explicitly derived. With the proposed simple method, analysis of PVD improved subsoil is the same as that of the unimproved case. The theoretical verification of the simple method was made under 1D condition. The calculated average degree of consolidation and excess pore pressure distribution in the vertical direction using the simple method are compared with existing theoretical solutions (combination of Terzaghi's consolidation theory and Hansbo's solution for PVD consolidation). It has been proved theoretically that, in terms of average degree of consolidation, in the case of one layer and ignoring the vertical drainage of natural subsoil, the maximum error of the proposed method is 10% compared with Hansbo's solution.

Malaysia has recorded a steady increase in the number of road traffic accidents from year to year at an alarming rate of 5%. Serious injuries due to the accidents, which could lead to permanent disability, might cause a long-term problem to the nation economy-wise. Predicting the number of serious injury cases in the future is important in understanding the trend of road traffic accidents to help policy-makers in proposing a countermeasure. Time-series model has been employed to predict the occurrence of road traffic crashes including fatalities. Nonetheless, the prediction of serious injury cases, which should not be taken lightly due to its potential impact, has not been proposed especially with regards to Malaysian road traffic accident data. This study attempts to employ Artificial Neural Networks (ANN), a machine learning algorithm, to predict the number of serious injury cases in Malaysia based on the road traffic accident data of the past 20 years. Ma-chine learning has incre...

Traffic mortality rate is the baseline through which road safety plans of a country could be evaluated. A reliable and reasonable analysis of road traffic related injuries and their leading causes is vital to the road safety investigation, evaluation as well as policymaking. Malaysia has the third highest fatality rate from road traffic accidents in Asia as well as in South East Asia. Although many researchers have attempted to provide predictive models of road traffic mortality (RTM) in the country, the predictions are found to be rather unsatisfactory in forecasting the causes as well as the future road fatality. It is hypothesized that the inability of the previous models to provide a good prediction of the RTM might be attributed to the complicated and non-linear data relationship of the underlying causes of road traffic accidents. A Support Vector Machine (SVM) is demonstrated to be effective in solving both classifications as well as regression problems owing to its efficacy t...

Malaysia has recorded a steady increase in the number of road traffic accidents from year to year at an alarming rate of 5%. Serious injuries due to the accidents, which could lead to permanent disability, might cause a longterm problem to the nation economy-wise. Predicting the number of serious injury cases in the future is important in understanding the trend of road traffic accidents to help policymakers in proposing a countermeasure. Time-series model has been employed to predict the occurrence of road traffic crashes including fatalities. Nonetheless, the prediction of serious injury cases, which should not be taken lightly due to its potential impact, has not been proposed especially with regards to Malaysian road traffic accident data. This study attempts to employ Artificial Neural Networks (ANN), a machine learning algorithm, to predict the number of serious injury cases in Malaysia based on the road traffic accident data of the past 20 years. Machine learning has increasingly been adopted in recent years owing to its ability to predict as well as catering for the non-linear behaviour of the data examined. A single-hidden ANN model was developed based on seven features, namely the number of registered vehicles, population, length of federal road, length of FELDA road, length of federal institutional road, length of federal territory road, and length of the expressway in order to predict the number of serious injuries. It was established from the present investigation that the developed ANN model is capable to predict the number of serious injuries from 1997 until 2017 with a mean absolute percentage error of only 3%. This demonstrates the capability of the developed machine learning in road traffic accident prediction, and it could be useful in outlining an action plan to mitigate the number of serious injuries in Malaysia.

Reckless driving behavior might result in a higher risk of an accident. Many factors are known to be the cause of this driving behavior. One of the factors is the socio-demographic background of the driver. This study aims to review currently available literature that investigates the relationship between driving behavior and any known socio-demographic characteristics. The review also focuses on the method used in the data collection as well as the tools used to perform the analysis to correlate the driving behavior and socio-demographic background. The review found that the influence of socio-demographic background on driving behavior study has not been explored in detail especially from the ethnicity point of view. With regards to the data collection, most of the study utilised the self- report survey, in which the targeted respondents are young adults. There are also studies covering all age groups that made use of the Driving Behaviour Questionnaire, data of traffic accidents o...

Many road traffic accidents occur in Malaysia every year. Road fatalities has been one of the main causes of death in Malaysia. More than half of these fatalities were among motorcyclists. An accident between a passenger car and a motorcycle might be caused by the blind spot of the car driver, in which the driver was unable to notice an incoming motorcycle from behind or the side. Blind spot monitoring system has been developed using recent technology. However, this active blind spot monitoring system is expensive and only available in luxury cars. Another type of blind spot monitoring is known as passive blind spot monitoring by means of a convex mirror. Many convex blind mirrors are being sold nationwide that come in various shapes. Nonetheless, the effectiveness of this convex mirror has never been quantified. This study aims to experimentally quantify the effectiveness of this mirror by using a spotlight, projecting a direct light to the side mirror. A circular convex mirror was...

Road traffic fatality is a burden towards low- and middle-income countries including Malaysia. Seeing that Selangor has the highest number of road traffic fatalities in Malaysia for the year 2019, therefore the state is selected as a case study. The aim of the article is 1) to understand the road traffic crash pattern and road traffic fatality pattern in Selangor 2) to determine the ability of 16 road traffic features in classifying road traffic fatality occurrence. The preliminary data screening shows that road traffic crash patterns and road traffic fatality patterns in Selangor have many similarities. However, both of them also have few dissimilarities such as crash time of occurrence, day of occurrence, number of vehicles involved in a crash, and type of vehicle first hit for the crash. Supervised machine learning algorithm in Orange data mining software was considered in this analysis. The analysed algorithms among others are neural network, random forest, decision tree, logist...