Beihang University

About: Beihang University is a education organization based out in Beijing, China. It is known for research contribution in the topics: Computer science & Control theory. The organization has 67002 authors who have published 73507 publications receiving 975691 citations. The organization is also known as: Beijing University of Aeronautics and Astronautics.

Effect of heat treatment on microstructure, mechanical and corrosion properties of austenitic stainless steel 316 L using arc additive manufacturing

Abstract: The mechanical and corrosion properties of gas metal arc additive manufacturing (GMA-AM) 316L could be optimized by modifying the volume fractions of sigma (σ) and delta-ferrite (δ) phases through heat treatment. Results show that the heat treatment at 1000 °C to 1200 °C for one hour will not obvious influence the morphology of grains in steel but largely influence the contents of σ and δ phases. The heat treatment at 1000 °C effectively increases the amount of σ phase in steel, causing both increase of UTS and YS but decrease of El and RA. The heat treatment at 1100 °C to 1200 °C completely eliminates σ phase, leading to the decrease of UTS and YS but increase of El and RA. The σ phase has better strengthening effect than δ phase, but which may degrade ductility and increase the possibility for cracks generation in steel. Meanwhile, limiting the number of both σ and δ phases through heat treatment can improve the corrosion resistance of steel. And σ phase appears more detrimental impact on degradation the corrosion resistance of steel than δ phase.

Highly-Efficient Gating of Solid-State Nanochannels by DNA Supersandwich Structure Containing ATP Aptamers: A Nanofluidic IMPLICATION Logic Device

Abstract: Integrating biological components into artificial devices establishes an interface to understand and imitate the superior functionalities of the living systems. One challenge in developing biohybrid nanosystems mimicking the gating function of the biological ion channels is to enhance the gating efficiency of the man-made systems. Herein, we demonstrate a DNA supersandwich and ATP gated nanofluidic device that exhibits high ON–OFF ratios (up to 106) and a perfect electric seal at its closed state (∼GΩ). The ON–OFF ratio is distinctly higher than existing chemically modified nanofluidic gating systems. The gigaohm seal is comparable with that required in ion channel electrophysiological recording and some lipid bilayer-coated nanopore sensors. The gating function is implemented by self-assembling DNA supersandwich structures into solid-state nanochannels (open-to-closed) and their disassembly through ATP–DNA binding interactions (closed-to-open). On the basis of the reversible and all-or-none electrochemic...

An effective intrusion detection framework based on SVM with feature augmentation

Abstract: Network security is becoming increasingly important in our daily lives—not only for organizations but also for individuals. Intrusion detection systems have been widely used to prevent information from being compromised, and various machine-learning techniques have been proposed to enhance the performance of intrusion detection systems. However, higher-quality training data is an essential determinant that could improve detection performance. It is well known that the marginal density ratio is the most powerful univariate classifier. In this paper, we propose an effective intrusion detection framework based on a support vector machine (SVM) with augmented features. More specifically, we implement the logarithm marginal density ratios transformation to form the original features with the goal of obtaining new and better-quality transformed features that can greatly improve the detection capability of an SVM-based detection model. The NSL-KDD dataset is used to evaluate the proposed method, and the empirical results show that it achieves a better and more robust performance than existing methods in terms of accuracy, detection rate, false alarm rate and training speed.

Investigating behaviours of hydrogen in a tungsten grain boundary by first principles: from dissolution and diffusion to a trapping mechanism

Abstract: We have investigated the dissolution, segregation and diffusion of hydrogen (H) in a tungsten (W) grain boundary (GB) using a first-principles method in order to understand the GB trapping mechanism of H. Optimal charge density plays an essential role in such a GB trapping mechanism. Dissolution and segregation of H are directly associated with the optimal charge density, which can be reflected by the H solution and segregation energy sequence for the different interstitial sites. To occupy the optimal-charge-density site, H can be easily trapped by the W GB with the solution and segregation energy of −0.23 eV and −1.11 eV, respectively. Kinetically, such a trapping is easier to realize due to the much lower diffusion barrier of 0.13–0.16 eV from the bulk to the GB in comparison with the segregation energy, suggesting that it is quite difficult for the trapped H to escape out of the GB. However, the GB can hold no more than 2 H atoms because the isosurface of optimal charge density almost disappears with the second H atom in, leading to the conclusion that H2 molecule and thus H bubble cannot form in the W GB. Taking into account the lower vacancy formation energy in the GB as compared with the bulk, we propose that the experimentally observed H bubble formation in the W GB should be via a vacancy trapping mechanism.