310 research outputs found
Interfacial liquid control to realize superior comprehensive properties of microwelded NiTi-stainless steel joints for multifunctional biomedical device fabrication
No full textDissimilar joining of NiTi and stainless steel (SS) is important in biomedical applications but poses significant challenges due to brittle intermetallic compounds (IMCs) formation in the welds. Replacing harmful phases in fusion welding cannot fully eliminate brittle IMCs and may introduce toxic elements, while the mixing restriction in solid-state welding increases the process complexity and results in large plastic deformation that degrades NiTi functional properties. In this work, we present a novel methodology that achieves a solid-state joined interface in NiTi-SS fusion welding (i.e., resistance microwelding) through in-situ interfacial liquid control. By combining the advantages of both welding techniques, the current method produced NiTi-SS joints with superior strength, superelasticity and biocompatibility compared to NiTi joints or base metal. The ultrathin reaction layer at the solid-state joined interface contributedto a strong metallurgical bonding, while Joule heating effects and interfacial reactions enhanced superelasticity and biocompatibility of the joint. By demonstrating complete superelasticity on NiTi side, flexible deformation capacity on SS side, superior resistance to hydrogen embrittlement and electrochemical corrosion, and reduced Ni ion release and cytotoxicity, the welded joint shows great potential for the fabrication of multifunctional biomedical devices. Our work not only provides a comprehensive study ofNiTi-SS joining under the biomedical background, but also introduces a new strategy for controlling material interface and dissimilar-metal welding process
The Optimal Sequence for Reset Controllers
No full textThe PID controller is one of the most used controllers in the industry. However, fundamental limitations due to linearity restrict its performances when higher bandwidth, stability, and precision are required simultaneously in today’s high-tech industry. Reset control is a promising nonlinear control strategy which can overcome these limitations. But it also brings new problems.High order harmonics are introduced into the system because of non-linearity which lead to unwanted dynamics and deterioration of performances. So it is necessary to reduce them as much as possible. It is found that the sequence of different parts of a reset controller has effects on the magnitude of high order harmonics. Through high order sinusoidal input describing functions (HOSIDOFs) tool, the optimal sequence of the open loop in which the magnitude of high order harmonics is minimum is achieved for a general reset controller. The superiority of the suggested sequence in the closed-loop system is validated through both simulation and experiments at a Lorentz-actuated precision positioning stage.Mechanical Engineering | Mechatronic System Design (MSD
Secure Control for Cyber-Physical Systems under Malicious Attacks
No full textThis article investigates the secure control problem for cyber-physical systems when the malicious data are injected into the cyber realm, which directly connects to the actuators. Based on moving target defense (MTD) and reinforcement learning, we propose a novel proactive and reactive defense control scheme. First, the system (A,B) is modeled as a switching system consisting of several controllable pairs (A,Bl) to facilitate the construction of the MTD control scheme. The controllable pairs (A,Bl) can be altered to update system dynamics under certain unpredictable switching probabilities for each subsystem, which can prevent the adversaries from effective attacks. Second, both attack detection and isolation schemes are designed to accurately locate and exclude the compromised actuators from a switching sequence. Third, a reinforcement learning algorithm based on the zero-sum game theory is proposed to design the defense control scheme when there exist no controllable subsystems to switch. To demonstrate the effectiveness of the defense control scheme, a three-tank system under unknown cyber attacks is illustrated.Accepted Author ManuscriptRobot Dynamic
Somatostatin and Octreotide on the Treatment of Acute Pancreatitis - Basic and Clinical Studies for Three Decades
No full textDiscovering Lin-Kernighan-Helsgaun heuristic for routing optimization using self-supervised reinforcement learning
No full textVehicle routing optimization is a crucial responsibility of transportation service providers, which can significantly reduce operating expenses and improve client satisfaction. Learning to tackle routing optimization problems automatically can be the next significant step forward in optimization technology. Despite recent advancements in automatically learned heuristics for routing optimization problems, state-of-the-art traditional methods such as Lin-Kernighan-Helsgaun (LKH) still outperform machine learning-based approaches. To narrow this gap, we propose a novel technique called self-supervised reinforcement learning (SSRL), which combines self-supervised learning with the LKH heuristic. We provide a node decoder and an edge decoder corresponding to reinforcement learning and self-supervised learning for learning node penalties and edge scores, respectively. The self-supervised part with cross-entropy loss offers strong gradient signals for parameter updates. At the same time, the reinforcement learning component functions as a regularizer to drive the supervised part, which focuses on particular rewards. SSRL learns and replicates all of the LKH’s significant components, improving the original LKH’s generalization and performance. Through experiments on multiple vehicle routing problems, SSRL has demonstrated superior accuracy and efficiency compared to existing methods. Our results provide empirical evidence of SSRL’s effectiveness and potential as a promising solution for optimizing complex routing problems
Carbon nanosphere adsorbents for removal of arsenate and selenate from water
No full textabstract: Porous carbon nanospheres prepared using spray pyrolysis were evaluated as adsorbents for removal of arsenate and selenate in de-ionized (DI), canal, and well waters. The carbon nanospheres displayed good binding to both metals in DI water and outperformed commercial activated carbons for arsenate removal in pH > 8, likely due to the presence of basic surface functional groups, high surface-to-volume ratio, and suitable micropores formed during the synthesis.View the article on the publisher's website at http://pubs.rsc.org.ezproxy1.lib.asu.edu/en/content/articlelanding/2015/en/c4en00204
- …
