Pusat Pengajian Kejuruteraan Awam - Tesis

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Characterisation of quaternary deposit in Seberang Perai Selatan, Pulau Pinang using combine shear wave velocity (VS).
(2019-02)
Ariffin, Julianiza
Soft quaternary deposit are widely found in Seberang Prai Selatan, Penang which consist of marine clay, silt and few thin layers of sand. But its characteristic and data was scarcely found. Due to active development on the area laid by quaternary deposit, construction the soft ground is becoming unavoidable despite its problematic character. Since soil characterisation are most essential for preliminary assessment before substructure design, adequate information of the subsurface condition is essential. Seismic soil investigation had been done to provide a reliable characterization of the soft marine deposits using in-situ Multichannel Analysis of Surface Wave consist of Active MASW, Passive MASW, Hybrid MASW and Seismic Cone Penetration Test (SCPT) to developed for site specific data of quaternary deposits of Penang. One dimensional in-situ shear wave velocity profiling described a heterogeneous layer of clay material ranged in 20 m/s to 180m/s from top layer until 15m depth and sandy soil layer with Vs ranged in 180m/s to 360 m/s at 15m to 30m depth. The shear wave velocity were used to determine the soil material had been compared with borehole lithology and SPT-N value. The values is consistent with the lithology and SPT-N value from bore log. Therefore, the range of shear wave velocity are valid and applicable for Seberang Prai Selatan quaternary deposit. Relationship between proposed 4 methods developed where Active MASW and SCPT method show weak relationship while Passive MASW and Hybrid MASW show strongest relationship. Hybrid MASW, a combination of Active and Passive MASW, show clear advantage for characterisation at deeper region compared to SCPT methods due to SCPT limited ability to penetrate hard soil. Active MASW captured high frequency noise which is limited to shallow region only. Therefore, it can be concluded that Hybrid and SCPT are reliable method for characterisation. Based on Vs30 from Hybrid MASW, Seberang Prai Selatan soil are classified as Site D and E. Combined shear wave velocity of Hybrid MASW and SCPT were used to determine the dynamic properties of Seberang Prai Selatan. The initial small strain stiffness or initial shear modulus described to be in range of 20 MPa to 50 MPa for clay soil at top to 15m depth and 50 MPa to 200 MPa for sandy soil at 15m to 30m depth. The elastic modulus ranged in 10 MPa to 40 MPa for the clayey soil and 20 MPa to 200 MPa for the sandy soil
Influence Of Palm Oil Fuel Ash As A Supplementary Binder On Properties Of Self-Compacting Concrete
(2014-03)
Zainul, Zainurul
Palm oil fuel ash (pofa) obtained from a palm oil mill was subjected to treatment process via sieving, grinding and heat treatment in order to improve its particles size and its potential reactivity as pozzolanic material in self-compacting concrete (sec). The treated pofa was then utilized as partial cement replacement in the production of see with pofa contents of 0%, 20%, 40% and 60% by mass of ordinary portland cement (opc). The properties of fresh scc mixes were explored through slump flow, slump flow t5oo, l-box, sieve stability as well as proctor penetration tests where the inclusion of pofa at replacement of 60% gave excellent results which satisfied the stipulated requirement for scc. On contrary, the hardened properties of see was evaluated through compressive strength, porosity, initial surface absorption (i sat), gas permeability, water permeability, rapid chloride permeability (rept) and rapid chloride migration (rmt) tests. The results obtained indicated significant improvement in the hardened scc properties with the inclusion of pofa. Sce with 40% pofa exhibits the greatest compressive strength value which exceeded the targeted strength of 50 mpa. [n term of durability related properties, all pofa-scc mixes showed better properties than the opc-sec, where the mix containing 60 % pofa exhibiting the greatest improvement at 180 days of water-curing period for all tests.
Streamflow prediction for sungai kulim, malaysia using random forest (rf) and support vector regression (svr) models
(2024-05-01)
Yeoh, Kai Lun
Short-term streamflow prediction is important for managing immediate risks associated with extreme and unpredictable weather events. Despite numerical models showing great capabilities in streamflow prediction, they require extensive data, fundamentals of hydrology, and calibration efforts. Conversely, data-driven models are relatively quick to model and can capture the non-linearity in the streamflow time series, without requiring knowledge about the natural catchment mechanism, thus gaining traction in recent years amidst digital evolutions. In this study, two machine learning (ML) models, namely random forest (RF) and support vector regression (SVR) were introduced for multi-step ahead streamflow predictions in the Sungai Kulim catchment which has undergone speedy urban development. The models with six different input combinations were developed and assessed, using 14 years of hydrological datasets. The results revealed that the performance of the non-parametric RF algorithm was high depending on the size of terminal nodes and input configurations. Increasing the terminal node’s size improved the accuracy of the RF model. The maximum relative improvements in RMSE and NSE were 36.9% and 60.6% respectively, considering lead time up to three hours. Introducing more correlated variables into the input makes the RF algorithm capture the dynamics in time series, resulting in higher generalization to new and unseen data. Conversely, the performance of the SVR algorithm was more dependent on the selection of kernel functions and its hyperparameters, rather than the input combinations. Next, the RF model (Nash-Sutcliffe Efficiency (NSE):0.392-0.963; root mean square error (RMSE):1.485 m3/s-5.720 m3/s) performed better than the SVR model (NSE:0.190-0.830; RMSE:3.020 m3/s-6.598 m3/s) during both validation and verification stages. Although the peak streamflow was underpredicted by both RF and SVR models at all lead times, the RF model still resulted in very good predictions (PBIAS < 10%). However, the predictions by the SVR models were unsatisfactory (PBIAS > 25%), except for the one-hour-ahead streamflow (PBIAS=5.28%). The hydrographs reproduced by the RF model had smoother crest segments, rising and recession limbs as well as closer peak values, compared with the SVR model. In brief, the overall accuracy of the ML models decreased with the increasing lead-time length. The findings of this research provide insight into the use of ML algorithms for short-term streamflow prediction in Malaysia. This supports the goals of the Sendai Framework and Sustainable Development Goals by issuing flood warnings, informing risk reduction strategies, and enhancing disaster preparedness. It fosters resilient communities, safeguards human health, promotes sustainable water management, and addresses climate change impacts, contributing to safer and more sustainable development.
Wildland fire risk classification of various tree species based on ignition characteristics, heat flux, and moisture content in China
(2024-07-01)
Yang, Wenxu
Firebrands are a major source of ignition for wildland fires. In the study of predicting firebrand behavior in forest fires, existing studies of firebrands formation have been performed on the effect of limited moisture content and heating condition resulting in debatable and insufficient data in laboratory-scale or computer simulation model. Aim of this study is to investigate pyrolysis and flammability of selected wildland fuels in typical regions of China, together with other necessary parameters. Based on previous findings, seven flammable wildland fuels with high fire potential were selected. The pyrolysis and flammability performance of selected wildland fuels at different heating condition and with different moisture content was determined using thermal gravimetric analyzer and cone calorimeter respectively. Result found that: 1. Fuel property: the thickness and area were strongly affected by moisture content level; 2. Pyrolysis property: the heat conductivity coefficient increased with moisture content; 3. Flammability property: peak of heat release rate increased with moisture content, time to ignition decreased with heat flux, mass loss rate increased with heat flux, heat flux had little effect on efficient heat of combustion value. Fire risk classification was established for wildland fire prediction, specimen A and specimen B possess high risk for wildland fire compared to specimen C, D, E, F, G.
Effective control measures to minimize cost overrun during construction phase of high-rise residential building projects in Chongqing, China
(2024-03-01)
Wang, Yue
Cost overrun during construction is a common issue in construction projects around the world, including in Chongqing, China. At present, there are few studies related to cost overrun at construction stage of high-rise residential building projects (HRBPs) in Chongqing. The aim of this research is to develop effective control measures from the contractor's perspective to minimize cost overrun during construction phase of HRBPs in Chongqing. Firstly, 65 cost overrun risk factors (CORFs) in construction projects were identified with literature reviews and semistructured interviews. All the risk factors have been prioritized through the analytic hierarchy process (AHP) based on their importance to project cost. Out of the 65 CORFs identified, 12 were classified as the critical ones that have a great potential to instigate a cost overrun during construction to take place in the real project. There were four risk factors which had the biggest impact on cost overruns, and their weights were 0.04 or above, including “low bid”, “force majeure”, “undetailed/inaccurate geological survey data”, and “increased loan interest rates”. Finally, control measures were developed for these four critical cost overrun risk factors (CCORFs). In order to control "low bid", firstly, strong comprehensive strength and a reasonable enterprise quota can improve the probability of winning the bid of the construction enterprise which is the construction enterprise needs to work hard all the time. Secondly, detailed records in the bidding process can help to develop measures after winning the bid. Finally, after winning the bid, the solution measures for the low-priced list items are essential. In view of “force majeure”, this study formulated measures to control largescale infectious diseases. In response to the epidemic, preventive measures and material guarantees need to be taken beforehand. If epidemic patients are discovered in the project, they must be managed and controlled as soon as possible. In addition, it is also important to retain relevant information and reduce the pressure on corporate funds. In order to control “undetailed/inaccurate geological survey data”, measures were formulated for the bidding stage and the construction stage. In view of "increased loan interest rates", the control measures were mainly formulated from both internal and external aspects of construction enterprises. The measures developed provided a guideline to control the risk of cost overruns and clear control key points to help contractors to minimize cost overruns in the construction phase of HRBPs.

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