Self-healing Feature Research Articles

Power Distribution Self-Healing System Based on Intuitionistic Uncertainty-Rough Sets

General concern and numerous studies of smart grid make it explicit that self-healing feature is an essential condition of power system intellectualization. Existing self-healing system based on traditional intelligence algorithms can't simultaneously achieve satisfied effect and efficiency. To deal with the uncertainty factors and mass redundant data in the power system, rough set theory and intuitionistic fuzzy set theory are employed in this paper. And considering the excellent function of MAS which is a distributed and coupled network with different kinds of agents that can work together for a global goal, a multiagent self-healing system based on intuitionistic uncertainty-rough sets is proposed in this paper. The proposed method can enhance the control accuracy and simultaneously improve the decision-making efficiency. And the simulation result of a distribution system shows the excellent effect.

Thermal-responsive self-healing hydrogel based on hydrophobically modified chitosan and vesicle

High-performance polymer materials with stimulus-responsive, self-healing and controllable features are expected to have diverse applications. In this paper, we report a novel, thermal-switchable self-healing hydrogel which can be obtained simply by mixing the hydrophobically modified chitosan (hm-chitosan) with the thermal-responsive vesicle composed of 5-methyl salicylic acid (5mS) and dodecyltrimethylammonium bromide (DTAB). Temperature stimuli points to a sol–gel phase transition in the supramolecular hydrogel and such transition can be reversibly performed for several cycles. In particular, the gelation temperature can be easily controlled by varying the ratio of DTAB to 5mS. Aside from the temperature responsive ability, the original feature highlighted in this work is that such a vesicle-based hydrogel exhibits interesting self-healing feature in a matter of seconds through the autonomic reconstruction without the use of healing agent. Thus, hydrogels based on hm-chitosan and functional vesicle may have potential application in a wide range of areas.

Study of geometric stability and structural integrity of self-healing glass seal system used in solid oxide fuel cells

A self-healing glass seal has the potential to restore its mechanical properties upon being reheated to the solid oxide fuel cell (SOFC) stack operating temperature. Such a self-healing feature is desirable for achieving high seal reliability during thermal cycling. Self-healing glass is also characterized by its low mechanical stiffness and high creep rate at SOFC operating temperatures. Therefore, the geometric stability and structural integrity of the glass seal system are critical to its successful application in SOFCs. This paper describes studies of the geometric stability and structural integrity of the self-healing glass seal system and the influence of various interfacial conditions during the operating and cooling-down processes using finite element analyses. For this purpose, the test cell used in the leakage tests for compliant glass seals, conducted at Pacific Northwest National Laboratory (PNNL), was taken as the initial modeling geometry. The effect of the ceramic stopper on the geometric stability of the self-healing glass sealants was studied first. Two interfacial conditions of the ceramic stopper and glass seals, i.e., bonded (strong) or unbonded (weak), were considered. Then the influences of interfacial strengths at various interfaces, i.e., stopper/glass, stopper/PEN, as well as stopper/IC plate, on the geometric stability and reliability of glass during the operating and cooling processes were examined.

E-Span and LPT for data aggregation in wireless sensor networks

In wireless sensor networks (WSNs), when a stimulus or event is detected within a particular region, data reports from the neighboring sensor nodes (sources) are sent to the sink (destination). Data from these sources are usually aggregated along their way to the sink. The data aggregation via in-network processing reduce communication cost and improves energy efficiency. In this paper, we propose two different tree structures to facilitate data aggregation. We first propose E-Span, which is an energy-aware spanning tree algorithm. In E-span, the source node which has the highest residual energy is chosen as the root. Other source nodes choose their corresponding parent node among their neighbors based on the information of the residual energy and distance to the root. We also propose the Lifetime-Preserving Tree ( LPT). In LPT, nodes which have higher residual energy are chosen as the aggregating parents. LPT also includes a self-healing feature by which the tree will be re-constructed again whenever a node is no longer functional or a broken link is detected. By choosing Directed Diffusion [C. Intanagonwiwat, R. Govindan, D. Estrin, Directed diffusion: a scalable and robust communication paradigm for sensor networks, in: Proc. of ACM MobiCom’00, Boston, MA, Aug. 2000, pp. 56–67.] as the underlying routing platform, simulation results show that in a WSN with 250 sensor nodes, the lifetime of sources can be extended significantly when data are aggregated by using either E-Span or LPT algorithms.