جستجوی مقالات مرتبط با کلیدواژه « Trip » در نشریات گروه « فنی و مهندسی »

The aim of this study is to propose a comprehensive approach for handling the crew scheduling problem in the railway systems. In this approach, the information of different railway trips are considered as input and the problem is divided to three separated phases. In phase I, we generate all feasible sequences of the trips, which are named as the pairings. A depth-first search algorithm is developed to implement this phase. In phase II, the pairings constituting the optimal solution are to be obtained. Both mentioned phases are handled in a centralized decision-making system for the entire railway network. Phase III aims to locally assign the crew groups to the optimal pairings. To solve the problem in phase III, a new mathematical model is developed in this paper. The model can determine the minimum required crew groups, and optimally assign the crew groups to the selected pairings of each home depot. In order to evaluate the developed algorithm and model, the Iranian railway network is evaluated by consideration of all passenger trips of the network. The results show that the proposed approach is capable of efficiently generating the optimal schedules for the railway crew groups in a reasonable computation time.

The dynamic behavior of three high manganese steels with very different stacking fault
energy (SFE) values (4-30 mJ/m2) were studied using high strain rate torsional tests. The hotrolled microstructure of the steel with the lowest SFE of 4 mJ/m2 consisted of a duplex mixture of austenite and ε-martensite, but those of the other two steels were fully austenitic. The deformed microstructures were studied by optical and electron microscopy. The quasi-static deformation of the low-SFE steel was accompanied with profuse martensitic transformation. However, when this steel was deformed at high strain rates (> 500 /s), martensite formation was reduced due to the adiabatic temperature rise and the increased SFE of the steel. The deformation of the steel with
moderate SFE of 18 mJ/m2 at all the tested strain rates was mainly controlled by the formation of mechanical twins that was leading to an excellent ductility of about 55% even at the highest strain rate of ~1700 /s. In contrast, dynamic deformation of the steel with the highest SFE of 30 mJ/m2 led to the appearance of some shear bands. This was ascribed to the decreased twinning and work hardening rate in this steel. Finally, the topographic studies showed that the fracture surface of the low-SFE steel contained relatively larger cleavage areas and smaller dimples suggesting a relatively more brittle fracture. This was related to the presence of brittle ε and α` martensite phases in this steel.

In this work, dynamic mechanical properties of three high-manganese steels with TRIP/TWIP or fully TWIP characteristics are studied. High strain rate experiments in the range of true strain rates between ~500 and 1800 /s are conducted using a dynamic torsional testing setup. All the three steels show a positive strain rate sensitivity in the intermediate range of strain rates (up to 500 /s). But, they behave differently as the strain rate is further increased. The steel with the lowest carbon content shows a strain rate softening behavior, while the other two exhibit strain rate hardening. The adiabatic temperature rise of the material greatly influences its stacking fault energy during the high rate dynamic deformation. Thus, unlike the quasi-static experiments, the dominant deformation mechanism of the steel during a dynamic test changes as the deformation progresses. In this regard, the variations of the stacking fault energy during the deformation are calculated for the three steels.

One of the most important issues in urban planning is developing sustainable public transportation. The basic condition for this purpose is analyzing current condition especially based on data. Data mining is a set of new techniques that are beyond statistical data analyzing. Clustering techniques is a subset of it that one of it’s techniques used for analyzing passengers’ trip. The result of this research shows relations and similarities in different segments that its usage is from strategic to tactical and operational areas. The approach in transportation is completely novel in the part of trip patterns and a novel process is proposed that can be implemented in highway analysis. Also this method can be applied in traffic and vehicle treats that need automatic number plate recognition (ANPR) for data gathering. A real case study has been studied here by developed process.