Spatial landslide hazard assessment along the Jelapang Corridor of the North-South Expressway in Malaysia using high resolution airborne LiDAR data

Mapping landslide-prone regions are crucial in natural hazard management and urban development activities in hilly and tropical regions. This research aimed to delineate a spatial prediction of landslide hazard areas along the Jelapang Corridor of the North-South Expressway in Malaysia by using two statistical models, namely, logistic regression (LR) and evidential belief function (EBF). Landslides result in high economic and social loses in Malaysia, particularly to highway concessionaries such as PLUS Expressways Berhad. LR and EBF determine the correlation between conditioning factors and landslide occurrence. EBF can also be applied in bivariate statistical analysis. Thus, EBF can be used to assess the effect of each class of conditioning factors on landslide occurrence. A landslide inventory map with 26 landslide sites was recorded using field measurements. Subsequently, the landslide inventory was randomly divided into two data sets. Approximately 70 % of the data were used for training the models, and 30 % were used for validating the results. Eight landslide conditioning factors were prepared for landslide susceptibility analysis: altitude, slope, aspect, curvature, stream power index, topographic wetness index, terrain roughness index, and distance from river. The landslide probability index was derived from both methods and subsequently classified into five susceptible classes by using the quantile method. The resultant landslide susceptibility maps were evaluated using the area under the curve technique. Results revealed the proficiency of the LR method in landslide susceptibility mapping. The achieved success and prediction rates for LR were 90 and 88 %, respectively. However, EBF was not successful in providing reasonable accurate results. The acquired success and prediction rates for EBF were 53 and 50 %, respectively. Hence, the LR technique can be utilized in landslide hazard studies for land use management and planning

Investigation Of The Mechanical Properties Of Standard Malaysian Rubber With Constant Viscosity And Epoxidised Natural Rubber Using Nano-Indentation Test

The usage of natural rubber (NR) in the development of laminated rubber-metal spring (LR-MS) for automotive applications has led to the investigation on its mechanical properties. This paper describes the use of nano-indentation test to investigate the mechanical properties of standard Malaysian rubber (SMR) with constant viscosity and epoxidised natural rubber (ENR). The mechanical properties of SMR Constant Viscosity 60 (SMR CV-60) and 25 mole % ENR (ENR 25) reinforced with 0, 20, 40 and 60 phr of carbon black (CB) was investigated. The nano-indentation test was carried out using Berkovich tips at constant load of 2 mN with holding times of 0, 5, 10, 15, and 20 s. It was found that the SMR CV-60 and ENR 25 compounds with 60 phr CB loading recorded the highest hardness and elastic modulus values, and also had the lowest penetration depth. The test also revealed that the hardness and penetration depth were independent to the holding times. In contrast, the indentation elastic modulus was found to be highly affected by the holding tim

Mathematical Modelling Of Passive Discrete Lumped Parameter System Using Standard Malaysian Rubber Constant Viscosity

This paper represents the basic and circular vibration isolator in High Frequencies using Malaysian natural rubber. Rubber material is chosen because it has very high damping to ensure the sufficient dissipation of vibration energy from the seismic wave. They are two methods involve in this paper, which are lumped parameter and wave propagation techniques. The lumped parameter system is developed to represent the baseline model of laminated rubber-metal spring. Wave propagation model is developed using non- dispersive rod. The mathematical modeling of laminated rubber-metal spring has been developed based on the internal resonance, lumped parameter and finite rod model, respectively. For a conclusion, the mathematical modeling of a prediction of basic and circular vibration isolator can be as a tool to predict the new trial-error method for developing new compounding of the vibration isolator in future, respectively

Prediction Of Basic And Circular Vibration Isolator In High Frequencies Using Malaysian Natural Rubber For Highway C2L Machine

This paper represents the basic and circular vibration isolator in High Frequencies using Malaysian natural rubber. Rubber material is chosen because it has very high damping to ensure the sufficient dissipation of vibration energy from the seismic wave. They are two methods involve in this paper, which are lumped parameter and wave propagation techniques. The lumped parameter system is developed to represent the baseline model of laminated rubber-metal spring. Wave propagation model is developed using non-dispersive rod. The mathematical modeling of laminated rubber-metal spring has been developed based on the internal resonance, lumped parameter and finite rod model, respectively. For a conclusion, the mathematical modeling of a prediction of basic and circular vibration isolator can be as a tool to predict the new trial-error method for developing new compounding of the vibration isolator in future, respectively

Evaluation Of Mechanical Properties On Vulcanized SMRCV-60 And ENR-25 Of Flexible-Rigid Body Vibration Isolator

This paper presents the evaluation of tensile test results on mechanical properties of local natural rubber called the standard Malaysian rubber constant viscosity-60 and the epoxidized natural rubber 25% with different carbon loadings for vibration isolators. The tensile test was carried out to determine the breaking point for both specimens. Based on the results, the lowest recorded tensile strength was identified in rubber compound containing 0 phr carbon, and the maximum tensile strength values were evaluated with higher phr carbon. The results also showed that the carbon reinforcement was proportion with the values of the tensile strength. The recorded Young’s Modulus and the values of the modulus depend on the values of carbon content in the rubber compound. By increasing the percentage of carbon, the modulus also increased. The pattern of the stress-elongation curve was also significantly changed by increasing the tensile strength. The deformation of the secondary bonding within rubber and fillers was also evaluated and the bonding became stronger by increasing the carbon. In conclusion, it is found that by increasing the carbon percentage in both types of rubber compound contributes to higher mechanical properties of the samples

Development of landslide risk maps using high resolution airborne LiDAR data

Landslides are one of the catastrophic that often cause severe property damages, economic loss, and high maintenance costs. Slope failures are a result of multiple triggering parameters, including anthropogenic activities, intense earthquakes, and intense rainfall, and physical properties of unstable surface materials related to geology, land cover, slope geometry, moisture content, and vegetation. This thesis presents a set of novel GIS-based statistical approaches developed for the hazard mapping of rainfall-induced landslides using LiDAR derived data and parameters especially along the highway corridor. These approaches were tested in two areas along the PLUS Expressways Berhad in Perak, Malaysia: (1) Jelapang area (2) Gua Tempurung area. The objective of this research is firstly aims to identify optimized landslide conditioning parameters that influence the characteristic of landslides and optimise a spatial prediction of landslide hazard areas along the Jelapang and Gua Tempurung area of the North-South Expressway in Malaysia by using two statistical models, namely, logistic regression (LR) and evidential belief function (EBF). The second objective is to design and implement probabilistic (EBF) and statistical (LR) based analysis. LR and EBF determine the correlation between conditioning parameters and landslide occurrence. EBF can also be applied in bivariate statistical analysis. Thus, EBF can be used to assess the effect of each class of conditioning parameters on landslide occurrence. A landslide inventory map with historical landslide locations were recorded using field measurements for both study areas. Subsequently, the landslide inventory was randomly divided into two data sets. Approximately 70 % of the data were used for training the models, and 30 % were used for validating the results. Eight landslide conditioning parameters were prepared for landslide susceptibility analysis: altitude, slope, aspect, curvature, stream power index, topographic wetness index, terrain roughness index, and distance from river. The landslide probability index was derived using both methods (i.e. LR and EBF) and subsequently classified into five susceptible classes by using the quantile method. The resultant landslide susceptibility maps were evaluated using the area under the curve technique. The success rates of the EBF and LR models in Gua Tempurung were 73.93% and 84.91%, respectively while for Jelapang were 53.95% and 90.12%, respectively. The predicted accuracy rates of EBF and LR models in Gua Tempurung were 67.73% and 83.00%, respectively while Jelapang were 50.1% and 88.78%, respectively. Results revealed the proficiency of the LR method in landslide susceptibility mapping. The third objective of this research is to produce landslide hazard and vulnerability maps and implement landslide risk assessment which determines the expected degree of loss due to a landslide and the expected number of lives lost, people injured, damage to property and disruption of economic activity. To achieve this objective, the landslide susceptibility maps were transformed into a hazard map considering the main landslide triggering parameter (rainfall) recorded in the landslide inventory database in both study areas. Vulnerability to landslides is also regarded as another main parameter for risk analysis. In order to determine landslide risk in the study areas, the quantitative approach was used. For this purpose, the obtained landslide hazard and vulnerability maps were multiplied to produce risk map and a final landslide risk index map was obtained. Finally, after obtaining risk map through quantitative approach (i.e. LR), a comparison was carried out with risk maps derived from the “TEMAN” for both of study areas. The comparison of the results from TEMAN and LR method for the category of high risk slopes alone for Gua Tempurung and Jelapamg areas have been reduced to 96.2 % and 79%, respectively. The results proved that the method can be significantly effective for an accurate risk assessment for both study areas. Consequently, produced maps in this research may be helpful for planners, decision makers at PLUS, and government agencies in landslide management and planning in the study area

Road Network Vulnerability Based on Diversion Routes to Reconnect Disrupted Road Segments

The reliance on roads to provide fluent mobilization has raised great concern when facing functional degradation. Disruption of the critical segments of a road network may significantly increase the distance traveled by a community. This paper proposes a method for measuring road network vulnerability when facing disruption by assessing all road segments within a network. The assessment is based on two of the shortest disjointed diversion routes from one end of the segment to the other, supporting the strategy of reaching equilibrium flow in an emergency condition. To generate diversion routes for the purpose of reconnecting a disrupted segment, the shortest path patterns are generated through the formation of adjacent polygons using GIS. Accordingly, this paper proposes a segment vulnerability index based on the support of diversion routes. Additionally, the model introduces supporting vulnerability, a parameter for measuring the potential of a road segment becoming a supporting diversion route when its surrounding segments are disrupted. By adopting the Malaysian Peninsular road network as a case study, the developed index can assist transportation agencies in planning and maintaining road assets while prioritizing vulnerable road segments relative to the entire road network

Road Network Vulnerability Based on Diversion Routes to Reconnect Disrupted Road Segments

The reliance on roads to provide fluent mobilization has raised great concern when facing functional degradation. Disruption of the critical segments of a road network may significantly increase the distance traveled by a community. This paper proposes a method for measuring road network vulnerability when facing disruption by assessing all road segments within a network. The assessment is based on two of the shortest disjointed diversion routes from one end of the segment to the other, supporting the strategy of reaching equilibrium flow in an emergency condition. To generate diversion routes for the purpose of reconnecting a disrupted segment, the shortest path patterns are generated through the formation of adjacent polygons using GIS. Accordingly, this paper proposes a segment vulnerability index based on the support of diversion routes. Additionally, the model introduces supporting vulnerability, a parameter for measuring the potential of a road segment becoming a supporting diversion route when its surrounding segments are disrupted. By adopting the Malaysian Peninsular road network as a case study, the developed index can assist transportation agencies in planning and maintaining road assets while prioritizing vulnerable road segments relative to the entire road network

Modelling and estimation on vibration and noise level of the dynamic wiper system using input shaping strategy

During wiping operation to wipe rain and dirt out from the windscreen, the wiper generates unwanted noise and vibration. This may cause dissatisfaction to the automotive vehicles due to annoying sounds and perhaps leads to poor visibility to the driver. Therefore, this paper proposes an approach to reduce and eliminate noise and vibration in a windscreen automotive vehicles wiper system. A two-dimensional mathematical model available in the open literature is adopted and integrated with a proposed control scheme, i.e. input shaping. Firstly, analysis is performed based on an original model, i.e. without input shaping in order to determine the noise (frequency) and vibration (amplitude) levels. Comparison is also made between the prediction results with finite element results. It is found that the correlation is reasonably close. The next stage is to introduce the two-impulse input shaping scheme. It is found that the input shaping could reduce certain amount of vibration level. Finally, parametric studies are also performed to examine the effectiveness of the proposed approach

Modelling And Estimation On Vibration And Noise Level Of The Dynamic Wiper System Using Input Shaping Strategy

During wiping operation to wipe rain and dirt out from the windscreen, the wiper generates unwanted noise and vibration. This may cause dissatisfaction to the automotive vehicles due to annoying sounds and perhaps leads to poor visibility to the driver. Therefore, this paper proposes an approach to reduce and eliminate noise and vibration in a windscreen automotive vehicles wiper system. A two-dimensional mathematical model available in the open literature is adopted and integrated with a proposed control scheme, i.e. input shaping. Firstly, analysis is performed based on an original model, i.e. without input shaping in order to determine the noise (frequency) and vibration (amplitude) levels. Comparison is also made between the prediction results with finite element results. It is found that the correlation is reasonably close. The next stage is to introduce the two-impulse input shaping scheme. It is found that the input shaping could reduce certain amount of vibration level. Finally, parametric studies are also performed to examine the effectiveness of the proposed approach