Highway accelerated loading instrument (HALI) testing on permanent deformation for concrete block pavement

Experiment concrete block pavements (CBP) are essential to study and assess the structural pavement performance. Accelerated loading testing is able to determine the pavement response and performance under a controlled, accelerated, accumulation of damage in a compressed time period. A test was performed in laboratory to investigate the permanent deformation development under Highway Accelerated Loading Instrument (HALI). A CBP model constructed from the bottom with hard neoprene, bedding sand and paving blocks filled with jointing sand was prepared and tested. Up to 2500 cycles load repetitions of a 1000 kg single wheel load were applied to the pavement model. The pavement deformation development was studied through its transverse deformation profile, mean rut depth in the wheel path, longitudinal rut depth profile and joint width between paving blocks. Test results indicated that the rut depth increase with increasing number of load repetitions and also the heaves at each side of the wheel path. It has also shown that the constant deformation, accelerating and braking sections of the pavement have been observed and determine

Permanent deformation of concrete block pavements under highway accelerated loading

Experiment concrete block pavements (CBP) are essential to study and assess the structural pavement performance. Accelerated loading testing is able to determine the pavement response and performance under a controlled, accelerated, accumulation of damage in a compressed time period. A test was performed in laboratory to investigate the permanent deformation development under Highway Accelerated Loading Instrument (HALI). A CBP model constructed from the bottom with hard neoprene, bedding sand and paving blocks filled with jointing sand was prepared and tested. Up to 2500 cycles load repetitions of a 1000 kg single wheel load were applied to the pavement model. The pavement deformation development was studied through its transverse deformation profile, mean rut depth in the wheel path, longitudinal rut depth profile and joint width between paving blocks. Test results indicated that the rut depth increase with increasing number of load repetitions and also the heaves at each side of the wheel path. It has also shown that the constant deformation, accelerating and braking sections of the pavement have been observed and determined

Urban flood depth estimate with a new calibrated curve number runoff prediction model

The 1954 Soil Conservation Services (SCS) runoff predictive model was adopted in engineering designs throughout the world. However, its runoff prediction reliability was under scrutiny by recent studies. The conventional curve number (CN) selection methodology is often very subjective and lacks scientific justification while nested soil group catchments complicate the issue with the risk of inappropriate curve number selection which produces unreliable runoff results. The SCS CN model was statistically invalid (α = 0.01 level) and over predicted runoff volume as much as 21% at the Sungai Kerayong catchment in Kuala Lumpur, Malaysia. Blind adoption of the model will commit a type II error. As such, this study presented a new method to calibrate and formulate an urban runoff model with inferential statistics and residual modelling technique to correct the runoff prediction results from the SCS CN model with a corrected equation. The new model out-performed the Asymptotic runoff model and SCS CN runoff model with low predictive model bias, reduced sum of squared errors by 32% and achieved high Nash-Sutcliffe efficiency value of 0.96. The derived urban curve number is 98.0 with 99% confidence interval ranging from 97.8 to 99.5 for Sungai Kerayong catchment. Twenty-five storms generated almost 29 million m3 runoff (11,548 Olympic size swimming pools) from the Sungai Kerayong catchment in this study. 75%-94% of the rain water became runoff from those storms and lost through the catchment, without efficient drainage infrastructure in place, the averaged flood depth reached 6.5 cm while the actual flood depth will be deeper at the flood ponding area near to the catchment outlet

Machine Learning Methods for Better Water Quality Prediction

In any aquatic system analysis, the modelling water quality parameters are of considerable significance. The traditional modelling methodologies are dependent on datasets that involve large amount of unknown or unspecified input data and generally consist of time-consuming processes. The implementation of artificial intelligence (AI) leads to a flexible mathematical structure that has the capability to identify non-linear and complex relationships between input and output data. There has been a major degradation of the Johor River Basin because of several developmental and human activities. Therefore, setting up of a water quality prediction model for better water resource management is of critical importance and will serve as a powerful tool. The different modelling approaches that have been implemented include: Adaptive Neuro-Fuzzy Inference System (ANFIS), Radial Basis Function Neural Networks (RBF-ANN), and Multi-Layer Perceptron Neural Networks (MLP-ANN). However, data obtained from monitoring stations and experiments are possibly polluted by noise signals as a result of random and systematic errors. Due to the presence of noise in the data, it is relatively difficult to make an accurate prediction. Hence, a Neuro-Fuzzy Inference System (WDT-ANFIS) based augmented wavelet de-noising technique has been recommended that depends on historical data of the water quality parameter. In the domain of interests, the water quality parameters primarily include ammoniacal nitrogen (AN), suspended solid (SS) and pH. In order to evaluate the impacts on the model, three evaluation techniques or assessment processes have been used. The first assessment process is dependent on the partitioning of the neural network connection weights that ascertains the significance of every input parameter in the network. On the other hand, the second and third assessment processes ascertain the most effectual input that has the potential to construct the models using a single and a combination of parameters, respectively. During these processes, two scenarios were introduced: Scenario 1 and Scenario 2. Scenario 1 constructs a prediction model for water quality parameters at every station, while Scenario 2 develops a prediction model on the basis of the value of the same parameter at the previous station (upstream). Both the scenarios are based on the value of the twelve input parameters. The field data from 2009 to 2010 was used to validate WDT-ANFIS. The WDT-ANFIS model exhibited a significant improvement in predicting accuracy for all the water quality parameters and outperformed all the recommended models. Also, the performance of Scenario 2 was observed to be more adequate than Scenario 1, with substantial improvement in the range of 0.5% to 5% for all the water quality parameters at all stations. On validating the recommended model, it was found that the model satisfactorily predicted all the water quality parameters (R2 values equal or bigger than 0.9). © 201

New and Old Waters Separation using Isotopic Approaches for Oil Palm and Regenerated Forest Catchments in Sarawak, Malaysia

Forest conversion has potentially affecting the hydrological processes within the catchment area especially in tropical countries due to the frequent and intense rainfall. Thus, the aims of this study are:-i) to evaluate the water flow pattern for oil palm plantation and regenerated forest catchments; and ii) to compute the new and old water contributions to stream discharge from these two types of catchments during storm events. Isotopic (Oxygen-18 (δ 18 O)) approach was applied to perform two-component hydrograph separation for the monitored five storm events. Our results showed that new water was ranging between 51 to 59% under regenerated forest catchment and 63 to 69% under oil palm plantation catchment, respectively. This implies that more new water was generated in the overland flow from oil palm canopies due to limited infiltration (soil compaction) within oil palm catchment. Our results also discovered that new water has dominated the runoff volume during peak flow. It is evidenced that rainfall has become the main source of supplying new water in both catchments due to overland flow or rapid subsurface delivery of storm water. Detailed study on the long term flow regime is necessary to formulate an effective management strategy for protecting water resources in the tropic

Preface

2021 International Conference on Environmental Engineering and Energy (ICEEE 2021) was held online in Wuhan, China, on November 20, 2021. ICEEE 2021 is co-sponsored by Modern International Green Culture Communication Association (MIGCCA), and the conference proceeding is published by IOP Publishing. ICEEE 2021 provides an excellent international forum for sharing knowledge and results in theory, methodology and applications of environmental engineering and energy. The conference looks for significant contributions to all major fields of environmental engineering and energy in theoretical and application aspects. The aim of the conference is to provide a platform to the global researchers and practitioners from both academia as well as industry to meet and share cutting-edge development in the fields.The ICEEE 2021 proceedings tend to collect the up-to-date, comprehensive and worldwide state-of-art knowledge on environmental engineering and energy. All of accepted papers were subjected to strict peer-reviewing by 2–5 expert reviewers. The papers have been selected for this volume because of quality and the relevance to the conference. We hope this book will not only provide the readers a broad overview of the latest research results, but also provide the readers a valuable summary and reference in these fields.COVID-19 cases were found in difference provinces, which were cluster of infection. In order to avoid virus' spreading, the organiser switched the conference to a virtual one. It was held online on November 20, 2021 via Tencent Meeting. The virtual conference consisted of Opening Speech (10 mins), Keynote Speeches (40 mins presentation + 10 mins Q&A), and Oral Presentation (15-20 mins presentation + 10 mins Q&A) and Concluding Remarks (5 mins). The number of attendees are more than expectation

HYDROLOGICAL PERFORMANCE OF NATIVE PLANT SPECIES WITHIN EXTENSIVE GREEN ROOF SYSTEM IN MALAYSIA

ABSTRACT Little is known about the hydrological performances of different native plant species within extensive green roof system in Malaysia. Thus, this research focused on the runoff retention efficiency within extensive green roof system with respect to different native plant species in Malaysia. A total of six green roofs were constructed with five being vegetated and one left unvegetated. Four test beds were vegetated with Nephrolepis bisserata (fern), Axonopus compressus (cow grass), portulaca grandiflora cultivars (sedum) and Zoysia matrella (Manila grass). The fifth test bed was a combination of all species and the six test bed with bare soil acted as control. The runoff volume was measured volumetrically through connected to an surface runoff harvesting tank under the test beds. Water retention was calculated from the difference between the depth of rainfall and the depth of runoff from each test bed. Results showed that mixture of plant species was the most effective vegetation at reducing runoff water. The monoculture of portulaca grandiflora cultivars (sedum) performed the best runoff water retention efficiency for single plant species

An International Collaborative Consensus Statement on En Bloc Resection of Bladder Tumour Incorporating Two Systematic Reviews, a Two-round Delphi Survey and a Consensus Meeting

Funding/Support and role of the sponsor: This study was supported by the General Research Fund/Early Career Scheme of the Research Grants Council, Hong Kong, China (reference no. 24116518).Peer reviewedPostprin

Highway accelerated loading instrument (HALI) for concrete block pavement

Pavement damage and axle load are very much related. Even though there are many studies evaluating this relationship, not many of them used a full scale experiment especially in concrete block pavement. This study is to develop on equipment which is named as Highway Accelerated Loading Instrument (HALI) to simulate the normal road axle load. This instrument is able to generalize different axle loads on the full-scale road pavements. Pavements constructed in this machine have been fully instrumented for the measurement of stress, strain and deformation. The tested pavement is restricted to repetitions of specific axle loads applied by this mechanically guided test wheel. However, the machine has the limitation on temperature control for the pavement under accelerated trafficking test. This paper will describe the development of HALI and its application to the studies on behavior and performance of concrete block pavement