Northeastern University (China)

About: Northeastern University (China) is a education organization based out in Shenyang, China. It is known for research contribution in the topics: Control theory & Microstructure. The organization has 36087 authors who have published 36125 publications receiving 426807 citations. The organization is also known as: Dōngběi Dàxué & Northeastern University (东北大学).

An Effective Artificial Bee Colony Algorithm for a Real-World Hybrid Flowshop Problem in Steelmaking Process

Abstract: This paper aims to provide a solution method for the real-world hybrid flowshop scheduling problem resulting from a steelmaking process, which has important applications in modern iron and steel industry. We first present a mixed integer mathematic model based on a comprehensive investigation. Then, we develop a heuristic method and two improvement procedures for a given schedule based on the problem-specific characteristics. Finally, we propose an effective artificial bee colony (ABC) algorithm with the job-permutation-based representation for solving the scheduling problem. The proposed ABC algorithm incorporates the heuristic and improvement procedures as well as new characteristics including a neighboring solution generation method and two enhanced strategies. To evaluate the proposed algorithm, we present several adaptations of other well-known and recent metaheuristics to the problem and conduct a serial of experiments with the instances generated according to real-world production process. The results show that the proposed ABC algorithm is more effective than all other adaptations after comprehensive computational comparisons and statistical analysis.

Probing interaction and spatial curvature in the holographic dark energy model

Abstract: In this paper we place observational constraints on the interaction and spatial curvature in the holographic dark energy model. We consider three kinds of phenomenological interactions between holographic dark energy and matter, i.e., the interaction term Q is proportional to the energy densities of dark energy (rho(A)), matter (p(m)), and matter plus dark energy (p(m) + p(A)). For probing the interaction and spatial curvature in the holographic dark energy model, we use the latest observational data including the type la supernovae (SNIa) Constitution data, the shift parameter of the cosmic microwave background (CMB) given by the five-year Wilkinson Microwave Anisotropy Probe (WMAP5) observations, and the baryon acoustic oscillation (BAO) measurement, from the Sloan Digital Sky Survey (SDSS). Our results show that, the interaction and spatial curvature in the holographic dark energy model are both rather small. Besides, it is interesting to find that there exists significant degeneracy between the phenomenological interaction and the spatial curvature in the holographic dark energy model.

Encapsulation of CH3NH3PbBr3 Perovskite Quantum Dots in MOF-5 Microcrystals as a Stable Platform for Temperature and Aqueous Heavy Metal Ion Detection.

Abstract: The stability issue of organometallic halide perovskites remains a great challenge for future research as to their applicability in different functional material fields. Herein, a novel and facile two-step synthesis procedure is reported for encapsulation of CH3NH3PbBr3 perovskite quantum dots (QDs) in MOF-5 microcrystals, where PbBr2 and CH3NH3Br precursors are added stepwise to fabricate stable CH3NH3PbBr3@MOF-5 composites. In comparison to CH3NH3PbBr3 QDs, CH3NH3PbBr3@MOF-5 composites exhibited highly improved water resistance and thermal stability, as well as better pH adaptability over a wide range. Luminescent investigations demonstrate that CH3NH3PbBr3@MOF-5 composites not only featured excellent sensing properties with respect to temperature changes from 30 to 230 °C but also exhibited significant selective luminescent response to several different metal ions in aqueous solution. These outstanding characteristics indicate that the stable CH3NH3PbBr3@MOF-5 composites are potentially interesting for...

Energy-Efficient Multi-Constraint Routing Algorithm With Load Balancing for Smart City Applications

Abstract: Many researches show that the power consumption of network devices of ICT is nearly 10% of total global consumption. While the redundant deployment of network equipment makes the network utilization is relatively low, which leads to a very low energy efficiency of networks. With the dynamic and high quality demands of users, how to improve network energy efficiency becomes a focus under the premise of ensuring network performance and customer service quality. For this reason, we propose an energy consumption model based on link loads, and use the network’s bit energy consumption parameter to measure the network energy efficiency. This paper is to minimize the network’s bit energy consumption parameter, and then we propose the energy-efficient minimum criticality routing algorithm, which includes energy efficiency routing and load balancing. To further improve network energy efficiency, this paper proposes an energy-efficient multi-constraint rerouting (E2MR2) algorithm. E2MR2 uses the energy consumption model to set up the link weight for maximum energy efficiency and exploits rerouting strategy to ensure network QoS and maximum delay constraints. The simulation uses synthetic traffic data in the real network topology to analyze the performance of our method. Simulation results that our approach is feasible and promising.

Effects of retained austenite volume fraction, morphology, and carbon content on strength and ductility of nanostructured TRIP-assisted steels

Abstract: With a suite of multi-modal and multi-scale characterization techniques, the present study unambiguously proves that a substantially-improved combination of ultrahigh strength and good ductility can be achieved by tailoring the volume fraction, morphology, and carbon content of the retained austenite (RA) in a transformation-induced-plasticity (TRIP) steel with the nominal chemical composition of 0.19C–0.30Si–1.76Mn–1.52Al (weight percent, wt%). After intercritical annealing and bainitic holding, a combination of ultimate tensile strength (UTS) of 1100 MPa and true strain of 50% has been obtained, as a result of the ultrafine RA lamellae, which are alternately arranged in the bainitic ferrite around junction regions of ferrite grains. For reference, specimens with a blocky RA, prepared without the bainitic holding, yield a low ductility (35%) and a low UTS (800 MPa). The volume fraction, morphology, and carbon content of RA have been characterized using various techniques, including the magnetic probing, scanning electron microscopy (SEM), electron-backscatter-diffraction (EBSD), and transmission electron microscopy (TEM). Interrupted tensile tests, mapped using EBSD in conjunction with the kernel average misorientation (KAM) analysis, reveal that the lamellar RA is the governing microstructure component responsible for the higher mechanical stability, compared to the blocky one. By coupling these various techniques, we quantitatively demonstrate that in addition to the RA volume fraction, its morphology and carbon content are equally important in optimizing the strength and ductility of TRIP-assisted steels.