Damage evolution behavior of CFRP laminates under post-impact fatigue with water absorption environment

In this study, the damage evolution behavior was evaluated considering the effect of the textile structure and water absorption. Damage observation was conducted by the integration of non-destructive and direct observation methods. Candidate textile reinforcements were T300-3k plain woven fabric (PW) and T700S-12k multi-axial knitted fabric (MA). The effect of water absorption on the performances of compression after impact (CAI) and PIF were small in PW CFRP laminates. Conversely, PIF properties of water-absorbed MA CFRP laminates drastically decreased than that of dry ones. CAI strength was not affected by water absorption. PIF performance of dry MA CFRP was fairly higher than that of the others. From the precise observation, some evidences of interfacial deterioration caused by water absorption were confirmed in both PW and MA CFRP laminates.     

Production of Lacto-N-biose I Using Crude Extracts of Bifidobacterial Cells

Lacto-N-biose I (LNB) is supposed to represent the bifidus factor in human milk oligosaccharides, and can be practically produced from sucrose and GlcNAc using four bifidobacterial enzymes, 1,3-β-galactosyl-N-acetylhexosamine phosphorylase, sucrose phosphorylase, UDP-glucose-hexose 1-phosphate uridylyltransferase, and UDP-glucose 4-epimerase, recombinantly produced by Escherichia coli. Here the production of LNB by the same enzymatic method without using genetically modified enzymes to consider the use of LNB for a food ingredient was reported. All four enzymes were produced as the intracellular enzymes of Bifidobacterium strains. The mixture of the crude extracts contained all four enzymes, with other enzymes interfering with the LNB production, namely, phosphoglucomutase, fructose 6-phosphate phosphoketolase, and glycogen phosphorylase. The first two interfering enzymes were selectively inactivated by heat treatment at 47 °C for 1 h in the presence of pancreatin, and glycogen phosphorylase was disabled by hydrolyzing its possible acceptor molecules using glucoamylase. Finally, 91 % of GlcNAc was converted into LNB in the 100-mL reaction mixture containing 300 mM GlcNAc.     

Computational cavitation flows at inception and light stages on an axial-flow pump blade and in a cage-guided control valve

Cavitation flows induced around an axial-flow pump blade and inside a high pressure cage-type valve are simu-lated by a two-dimensional unsteady Navier-Stokes analysis with the simplest treatment of bubble dynamics.Thefluid is assumed as a continuum of homogeneous dispersed mixture of water and vapor nuclei.The analysis isaimed to capture transient stages with high amplitude pressure change during the birth and collapse of the bubbleespecially at the stage of cavitation inception.By the pump blade analysis,in which the field pressure is moderate,cavitation number of the inception and locations of developed cavitation are found to agree with experimental re-suits in a wide flow range between high incidence and negative incidence.In the valve flow analysis,in which thewater pressure of 5MPa is reduced to 2MPa,pressure change responding to the bubble collapse between the vaporpressure lower than 1 KPa and the extreme pressure of higher than 10~4 KPa is captured through a stable computa-tion.Location of the inception bubble and pressure force to the valve plug is found agree well with the respectiveexperimental features.     

Locomotion Control of MEMS Microrobot Using Pulse‐Type Hardware Neural Networks

This paper presents the locomotion control of a microelectromechanical system (MEMS) microrobot. The MEMS microrobot demonstrates locomotion control by pulse‐type hardware neural networks (P‐HNN). P‐HNN generate oscillatory patterns of electrical activity like those of living organisms. The basic component of P‐HNN is a pulse‐type hardware neuron model (P‐HNM). The P‐HNM has the same basic features as biological neurons, such as the threshold, the refractory period, and spatiotemporal summation characteristics, and allows the generation of continuous action potentials. P‐HNN has been constructed with MOSFETs and can be integrated by CMOS technology. Like living organisms, P‐HNN has realized robot control without using software programs or A/D converters. The size of the microrobot fabricated by MEMS technology was 4 × 4 × 3.5 mm. The frame of the robot was made of a silicon wafer, equipped with rotary actuators, link mechanisms, and six legs. The MEMS microrobot emulated the locomotion method and the neural networks of an insect by rotary actuators, link mechanisms, and the P‐HNN. We show that the P‐HNN can control the forward and backward locomotion of the fabricated MEMS microrobot, and that it is possible to switch its direction by inputting an external trigger pulse. The locomotion speed was 19.5 mm/min and the step size was 1.3 mm. © 2013 Wiley Periodicals, Inc. Electr Eng Jpn, 186(3): 43–50, 2014; Published online in Wiley Online Library ( wileyonlinelibrary.com ). DOI 10.1002/eej.22473     

Measurement method of plasma current and density in atmospheric pressure plasma jet

We present a measurement method of the plasma current and density in an atmospheric‐pressure plasma generated using a quartz tube, helium gas, and copper foil electrode by applying a high RF voltage. The plasma in the form of a bullet is released as a plume or jet into the atmosphere. To study the characteristics of the atmospheric‐pressure plasma, the plasma current is measured using a current probe, and the drift velocity of plasma plume is measured using a photodetector. The current of the plasma plume is estimated by subtracting the ground line current from the power line current in the circuit. The density of plasma plume n is estimated from the plasma plume current I and the drift velocity v as I = envS, where S is the cross section of plasma plume. The density of the released plasma into the atmosphere is estimated as ∼10¹⁸ m⁻³ by the method. © 2015 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.     

Processing and 3D printing of SiCN polymer-derived ceramics

Preceramic polymer resins are attractive for the 3D printing of net-shaped ceramic components. Recently various processes have been demonstrated for 3D printing of polymer-derived ceramics (PDCs). Ultimately in these processes, the process outcomes strongly depend on the process parameters. In particular, for PDCs the ceramic density, and ceramic yield are affected by the catalyst concentration and cross-linking duration. Here, we use thermal analysis and FTIR to quantify the interrelation of the process parameters on the process outcome for polysilazanes and demonstrate 3D printing of PDC components based on the best-identified process parameters. The results of this work can be used as guidelines for future additive manufacturing of PDCs.     

Application of Near-Infrared Spectroscopy for Evaluation of Drying Stress on Lumber Surface: A Comparison of Artificial Neural Networks and Partial Least Squares Regression

This study aimed to examine the feasibility of evaluating the stress level at the surface of lumber during drying using near-infrared (NIR) spectroscopy combined with artificial neural networks (ANNs). Sugi (Cryptomeria japonica D. Don) lumber with an initial moisture content ranging from 41.1 to 85.8% was dried using a commercial drying schedule. An ANN model for predicting surface-released strain (SRS) was developed based on NIR spectra collected from the lumber during drying. The predictive ability of the ANN model was compared with a partial least squares (PLS) regression model.

The ANN model showed good correlation between laboratory-measured SRS and predicted SRS with an R ² of 0.79, a root mean square error of prediction (RMSEP) of 0.0009, and a ratio of performance to deviation (RPD) of 1.81. The PLS regression model gave a lower R ² of 0.69, a higher RMSEP of 0.0010, and a lower RPD of 1.38 than the ANN model, suggesting that the predictive performance of the ANN model was superior to the PLS regression model. The SRS evolution during drying as predicted by the models showed a similar trend to the laboratory-measured one. The predicted elapsed times to reach maximum tensile SRS and stress reversal roughly coincided with the laboratory-measured times. These results suggest that NIR spectroscopy combined with multivariate analysis has the potential to predict the drying stress level on the lumber surface and the critical periods during drying, such as the points of maximum tensile stress and stress reversal.     

Lewis Acid‐Catalyzed or Base‐Promoted Regioselective Cycloisomerization of N‐Imidoyl‐o‐alkynylanilines for Synthesis of N‐Imidoyl‐(1 H)‐indoles and 4‐Alkylidene‐3,4‐dihydroquinazolines

Product selectivity control for the synthesis of imidoylindoles and 4‐alkylidenedihydroquinazolines from N‐imidoyl‐o‐alkynylanilines via silver triflate‐catalyzed cycloisomerization or tetrabutylammonium fluoride‐promoted cyclization is described. The product selectivity depends mainly on the catalyst/promoter used, and on the substituents on the alkyne and amidine functions of the substrates.