About: Lanzhou Jiaotong University is a education organization based out in Lanzhou, China. It is known for research contribution in the topics: Ligand & Crystal structure. The organization has 7571 authors who have published 6220 publications receiving 53792 citations. The organization is also known as: Lanzhou Railway University.
Papers published on a yearly basis
TL;DR: In this article, a genetic algorithm is developed to solve the multi-station problem through a special binary coding method that indicates a train departure or cancellation at every possible time point, and a local improvement algorithm is presented to find optimal timetables for individual station cases.
Abstract: This article focuses on optimizing a passenger train timetable in a heavily congested urban rail corridor. When peak-hour demand temporally exceeds the maximum loading capacity of a train, passengers may not be able to board the next arrival train, and they may be forced to wait in queues for the following trains. A binary integer programming model incorporated with passenger loading and departure events is constructed to provide a theoretic description for the problem under consideration. Based on time-dependent, origin-to-destination trip records from an automatic fare collection system, a nonlinear optimization model is developed to solve the problem on practically sized corridors, subject to the available train-unit fleet. The latest arrival time of boarded passengers is introduced to analytically calculate effective passenger loading time periods and the resulting time-dependent waiting times under dynamic demand conditions. A by-product of the model is the passenger assignment with strict capacity constraints under oversaturated conditions. Using cumulative input–output diagrams, we present a local improvement algorithm to find optimal timetables for individual station cases. A genetic algorithm is developed to solve the multi-station problem through a special binary coding method that indicates a train departure or cancellation at every possible time point. The effectiveness of the proposed model and algorithm are evaluated using a real-world data set.
TL;DR: A unified quadratic integer programming model with linear constraints is developed to jointly synchronize effective passenger loading time windows and train arrival and departure times at each station.
Abstract: This paper focuses on how to minimize the total passenger waiting time at stations by computing and adjusting train timetables for a rail corridor with given time-varying origin-to-destination passenger demand matrices. Given predetermined train skip-stop patterns, a unified quadratic integer programming model with linear constraints is developed to jointly synchronize effective passenger loading time windows and train arrival and departure times at each station. A set of quadratic and quasi-quadratic objective functions are proposed to precisely formulate the total waiting time under both minute-dependent demand and hour-dependent demand volumes from different origin–destination pairs. We construct mathematically rigorous and algorithmically tractable nonlinear mixed integer programming models for both real-time scheduling and medium-term planning applications. The proposed models are implemented using general purpose high-level optimization solvers, and the model effectiveness is further examined through numerical experiments of real-world rail train timetabling test cases.
TL;DR: By using Bohnenblust-Karlin's fixed point theorem, a main existence theorem is obtained and two existence results are established when the multi-valued nonlinearity F has sub-linear or linear growth in the state variable y.
Abstract: This paper is mainly concerned with the existence of solutions for a certain class of fractional differential inclusions with boundary conditions. By using Bohnenblust-Karlin's fixed point theorem, a main existence theorem is obtained. As an application of this main theorem, we establish two existence results when the multi-valued nonlinearity F has sub-linear or linear growth in the state variable y. Our results are even new when applied to a corresponding single-valued problem.
TL;DR: In this article, the use of GNPs to strengthen the bulk Cu-matrix composites was reported, and the GNP reinforced composites were prepared by a combination of the ball milling and hot-pressing processing, and their mechanical properties were investigated.
Abstract: Graphene nanoplatelets (GNPs) exhibit ultra-high strength and elastic modulus. Therefore, they are potential ideal reinforcements in metal–matrix composites (MMCs). In this work, we report the use of GNPs to strengthen the bulk Cu-matrix composites. GNP reinforced Cu-matrix (GNP/Cu) composites were prepared by a combination of the ball milling and hot-pressing processing, and their mechanical properties were investigated. Microstructure studies indicated that the GNPs with 0–8 vol.% contents were well dispersed in the Cu matrix by ball milling. Compared to unreinforced Cu, the GNP/Cu composites showed a remarkable increase in yield strength and Young's modulus up to 114 and 37% at 8 vol.% GNP content, respectively. The extraordinary reinforcement is attributed to the homogeneous dispersion of GNPs and grain refinement. However, the mechanical improvement of GNP/Cu composites was still below the theoretical value. The possible reasons for this deviation were discussed and the methods for further mechanical improvement of GNP/Cu composites were proposed.
TL;DR: In this article, the authors provide an updated review on the available alternative to produce biochar from biomass, quantification and characterization of biochar, the adsorptive capacity for the adaption of contaminants, and the effect of addition to agricultural soils on contaminant bioavailability.
Abstract: This paper provides an updated review on the subjects, the available alternative to produce biochar from biomass, quantification and characterization of biochar, the adsorptive capacity for the adsorption of contaminants, and the effect of biochar addition to agricultural soils on contaminant bioavailability. The property of biochar produced is much dependent upon the composition and type of biomass and the conditions at which biomass is carbonized. The physical and chemical characterizations are necessary to identify the basic structure and property of biochar and to predict its potential in various environmental application. Biochar is a promising alternative to remedy the soils contaminated with heavy metals and organic compounds through adsorption and immobilization due to its large surface area, charged surface, and functional groups. Overall, the bioavailability of heavy metals and organic compounds decreases when biochar is amended into soils.
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