Showing papers in "Ksce Journal of Civil Engineering in 2022"

Optimization of Sand-Bentonite Mixture for the Stable Engineered Barriers using Desirability Optimization Methodology: A Macro-Micro-Evaluation

Abstract: In this paper, Desirability Optimization Methodology (DOM) is employed to achieve optimum sand bentonite mixture (SBM) based on multiple antagonist macro-geotechnical responses of the compacted SBM prepared using poorly graded sand with the mean grain size around 0.2 mm and bentonite with plasticity index around 157% for the stable engineered barriers (EBs). For this purpose, varying mix designs of SBM compacted at compaction energy of 2,700 kN-m/m3 are initially tested to determine their mechanical properties, volumetric-change behavior, and hydraulic conductivity. The unconfined compressive strength, cohesion, angle of internal fiction, swell pressure, compression index, and hydraulic conductivity are taken as the geotechnical design parameters for the SBM. Mathematical models are developed and statistically validated for these design parameters using sand content (SC) and bentonite content (BC) as the predictors. In addition, models are also developed to predict compression curves for compacted SBMs. Moreover, microstructural evaluation is conducted through scanning electron microscope (SEM) analysis to determine the SBM having a desirable microstructure for stable EB. It is observed that a major shift in the microstructure from medium pores to micro-pores occurs for the BC between 20% and 30%. Afterward, optimization of SBM is carried out by integrating developed models for the geotechnical design parameters in a desirability function (D) algorithm, which is subsequently simulated by setting maximization of strength and minimization of swell pressure, compressibility and hydraulic conductivity of compacted SBM as the goals. A reasonably high D-value is achieved for the SBMs having SC:BC in a range of 74:26 to 78:22 with the highest at 75.63:24.37 against the set goals. This study manifests an effective and pragmatic strategy for designing the SBM for a stable EB considering its antagonist hydraulic, volumetric change, and mechanical responses.

Estimation of Route Choice Behaviors of Bike-Sharing Users as First- and Last-mile Trips for Introduction of Mobility-as-a-Service (MaaS)

Abstract: Bicycling has been considered the sustainable alternatives of first- and last-mile trips for Mobility-as-a-Service (MaaS) in integrated transport systems. This study aims to analyze the route choice behaviors of bike-sharing users for the first- and last-mile trips in MaaS, incorporating the connectivity to the subway stations. The observed GPS data is employed to generate the route travels of bike-sharing users, and the choice set generation algorithm, i.e., the k-medoids clustering method, is applied to extract the representative alternatives in route choice models. This study analyzes the path-size logit model to compare the route choice behaviors incorporating peak periods, and access and egress trips. The bike-sharing use at the evening-peak period is more frequent than the other periods. Also, the bike-sharing users are found to be positively associated with the ratio of bike lanes for the access and egress trips to the subway stations, whereas they are reluctant to detour for their trips. The finding of this research is that the extension of bike facilities on access and egress to the subway stations is necessary to improve the bike-sharing use for the first- and last-mile trips in MaaS.