Experimental Investigation of the Effect of Purge Flow and Main Flow Interaction in a Low-Speed Turbine Cascade Passage

In order to protect the vulnerable turbine components from extreme high temperature, coolant flow is introduced from the compressor to the disk cavity, inevitably interacting with the main flow. This paper describes an experimental investigation of the interaction between the main flow and the purge flow in a low-speed turbine cascade with three purge flow rates, Cm = 0, Cm = 1%, and Cm = 2%. In order to study the effect of the interaction between the main flow and the purge flow on the secondary flows, a Rortex method developed by Liu Chaoquan is introduced to identify the vortex in the flow field. In the meantime, a method to calculate the mean entropy production rate based on the particle image velocimetry (PIV) result is adopted to investigate the flow loss. The PIV result indicates that the purge flow has a prominent impact on the flow field of the cascade passage, changing the velocity distribution that induces a local blockage area. The results of vortex identification show that the purge flow promotes the generation of the passage vortex near the suction side. In addition, the purge flow makes the passage vortex migrate to the tip wall direction, enlarging the region affected by the secondary flow. The mean entropy production (MEP) result shows that the flow loss is mainly caused by the passage vortex. The coincidence of the high-MEP region and the location of the passage vortex indicates that the purge flow increases the secondary flow loss by affecting the formation and the migration of the passage vortex.     

Detectability conditions for output-only subspace identification

ABSTRACT

The scope of output-only/blind identification is restricted to stochastic/statistical processes, but for the first time in this study, the detectability conditions for general output-only subspace identification are investigated. This aids the range of input sources to be extended in a much realistic manner, beyond the only stochastic inputs. For this purpose, the subspace framework is assigned to make a connection between the output signal contents and the LTI system order. A few substantial hypotheses and algebraic statements are propounded affirming the sufficiency of the genuine output sequences for the identification purpose. This can be perceived as the cornerstone of state-space model reconstruction. In order to consolidate the notions according to reality, several examples are studied and examined for different input classes with stochastic disturbance.     

Identification of a fault zone ahead of the tunnel excavation face using the extended Kalman filter

Simulation of mechanized tunneling and on-site excavation require very good knowledge of the geomechanical and material properties. Identification of the material must be fast and continuously performed during tunnel excavation for the best possible strategies for advancing the tunnel boring machine. We present in this work the use of the extended Kalman filter (EKF) for identification of the inclined fault zone ahead of the face. The EKF showed fast and stable convergence of the model parameters under study. In comparison with the particle swarm optimization technique applied to the same back analysis problem, faster convergence of the identified parameters as well as high robustness with respect to the choice of the initial parameter values have been observed.     

Encapsulation of nanocrystals with responsive gels for spatial optical identification

A tripeptide (β-AspFF) gelator was designed and synthesised using solid-phase peptide synthesis. The as-prepared gelator formed a stable and clear multi-responsive gel in toluene solution. Encapsulating the quantum dots with β-AspFF effectively increased stability and antioxidisation ability which are beneficial for optical identification.     

Unsupervised cell identification on multidimensional X‐ray fluorescence datasets

A novel approach to locate, identify and refine positions and whole areas of cell structures based on elemental contents measured by X‐ray fluorescence microscopy is introduced. It is shown that, by initializing with only a handful of prototypical cell regions, this approach can obtain consistent identification of whole cells, even when cells are overlapping, without training by explicit annotation. It is robust both to different measurements on the same sample and to different initializations. This effort provides a versatile framework to identify targeted cellular structures from datasets too complex for manual analysis, like most X‐ray fluorescence microscopy data. Possible future extensions are also discussed.     

Comment on: “Topology identification and adaptive synchronization of uncertain complex networks with adaptive double scaling functions” [Commun Nonlinear Sci Numer Simul 2011;16:3337-43]

In this comment letter we point out that the main result of the recent paper [Xu Y, Zhou W, Fang J, Sun W. Topology identification and adaptive synchronization of uncertain complex networks with adaptive double scaling functions. Commun Nonlinear Sci Numer Simul 2011;16(18):3337-43] has certain errors. The mistakes are corrected and a correct version is presented in this letter. We further indicate that a sufficient condition has been neglected in a series of articles discussing the same topic of network topology identification; hence we hope this letter can help clarify some unclear concepts about this topic.     

Rapid and Efficient Proteolysis for Protein Analysis by an Aptamer-Based Immobilized Chymotrypsin Microreactor

Efficient protein digestion is a key step for successful mass spectrometry identification. However, traditional in-solution digestion suffers some drawbacks, such as autolysis of protease, long analysis times and lack of control. Recently, specific single-stranded nucleic acids, aptamers, screened from random sequence pools, have been performed high affinity for targets. In this paper, we have developed a novel enzyme reactor, which immobilized chymotrypsin based on aptamer-grafted silica beads. Mixed proteins, which consist of bovine serum albumin, myoglobin, and cytochrome c, were used as samples, to evaluate the digestion performance of the enzymatic reactor. With the use of this novel tool, proteins were digested in 40 min to an extent similar to that achieved with soluble enzyme at 37°C after 16 h. Moreover, enzymatic reactor regeneration was carried out through chymotrypsin elution and re-immobilization. The advanced characteristics of the aptamer-based chymotrypsin reactor demonstrated that aptamers could serve as novel materials for rapid and efficient enzyme immobilization and application in protein studies.