Ultrasonic torsional guided wave sensor for flow front monitoring inside molds

Measuring the extent of flow of viscous fluids inside opaque molds has been a very important parameter in determining the quality of products in the manufacturing process such as injection molding and resin transfer molding. Hence, in this article, an ultrasonic torsional guided wave sensor has been discussed for monitoring the movement of flow front during filling of resins in opaque molds. A pair of piezoelectric normal shear transducers were used for generating and receiving the fundamental ultrasonic torsional guided wave mode in thin copper wires. The torsional mode was excited at one end of the wire, while the flowing viscous fluid progressively wet the other free end of the wire. The time of flight of the transient reflections of this fundamental mode from the air-fluid interface, where the wire enters the resin, was used to measure the position of the fluid flow front. Experiments were conducted on four fluids with different viscosity values. Two postprocessing algorithms were developed for enhancing the transient reflected signal and for suppressing the unwanted stationary signals. The algorithms were tested for cases where the reflected signals showed a poor signal to noise ratio.     

Quantification of compaction-induced crystallinity reduction of a pharmaceutical solid using 19F solid-state NMR and powder X-ray diffraction

¹⁹F solid-state nuclear magnetic resonance (NMR) was investigated as an analytical technique to quantify the amorphous phase in a fluorine-containing pharmaceutical candidate. The crystallinity of Compound 1 was calculated using two ¹⁹F T₁ relaxation-based methods. The first method employs both the pure amorphous and the crystalline reference standards while the second method is model independent and utilizes a single standard. The ¹⁹F solid-state NMR results were confirmed with powder X-ray diffraction methods. From X-ray diffraction data, two linear calibration curves were obtained from blends of crystalline and amorphous Compound 1: one is based on the total integrated intensity of selected diffraction peaks and the other on the total intensity of the amorphous halo at 2θ positions that have no interference from crystalline diffraction peaks. The crystallinity of Compound 1 after compaction calculated by both ¹⁹F solid-state NMR methods was in excellent agreement with the results from the X-ray calibration curves. ¹⁹F solid-state NMR was shown to be a powerful technique in determining the amount of amorphous phase present in a pharmaceutical solid.     

A survey on handling computationally expensive multiobjective optimization problems using surrogates: non-nature inspired methods

Computationally expensive multiobjective optimization problems arise, e.g. in many engineering applications, where several conflicting objectives are to be optimized simultaneously while satisfying constraints. In many cases, the lack of explicit mathematical formulas of the objectives and constraints may necessitate conducting computationally expensive and time-consuming experiments and/or simulations. As another challenge, these problems may have either convex or nonconvex or even disconnected Pareto frontier consisting of Pareto optimal solutions. Because of the existence of many such solutions, typically, a decision maker is required to select the most preferred one. In order to deal with the high computational cost, surrogate-based methods are commonly used in the literature. This paper surveys surrogate-based methods proposed in the literature, where the methods are independent of the underlying optimization algorithm and mitigate the computational burden to capture different types of Pareto frontiers. The methods considered are classified, discussed and then compared. These methods are divided into two frameworks: the sequential and the adaptive frameworks. Based on the comparison, we recommend the adaptive framework to tackle the aforementioned challenges.     

Mechanical and thermal properties,morphology and relaxation characteristics of poly(lactic acid) and soy flour/wood flour blends

Poly(lactic acid) (PLA) is a biodegradable polymer derived from sugar‐based materials, and its applications are varied. PLA blends are commonly employed to overcome certain disadvantages such as poor impact strength, low heat distortion temperature, poor processability and relatively high cost. In this study, blending PLA with soy flour (SF), wood flour (WF) and sodium bisulfite‐modified SF was used to improve the adhesion to PLA. In all cases, 0.5 wt% methylenediphenyl diisocyanate (MDI) was used as a coupling agent. Mechanical and thermal properties, morphology and relaxation characteristics of the blends were investigated. The results showed that MDI was an effective coupling agent for the WF/PLA system in improving tensile strength and elongation. Differential scanning calorimetry results indicated that SF and modified SF act as nucleation agents and facilitate the crystallization behavior of PLA by increasing the percentage crystallinity. From mechanical relaxation of the temperature‐variant system, we determined how the mechanical relaxation time evolves during the course of heating and obtained the Kohlrausch–Williams–Watts parameter and activation energy (ΔE). PLA and its blends exhibited highly homogeneous relaxational dynamics in their transition from glass to liquid, and ΔE of PLA and its blends is mainly affected by their densities and compositions. Copyright © 2010 Society of Chemical Industry     

Hydrogen production by Chlamydomonas reinhardtii under light driven sulfur deprived condition

This article explores the possibility of demonstrating sustainable photohydrogen production using Chlamydomonas reinhardtii when grown in sulfur deprived photoautotrophic condition. The hydrogen evolving capability of the algal species was monitored based on alternating light and dark period. Investigation was carried out during the day time in order to exploit the solar energy for meeting the demand of the light period. The results showed that when the reactor was operated at varying photoperiod namely 2, 3 and 4 h of alternating light and dark period, the gas generation was found to be 32 ± 4, 63 ± 7 and 52 ± 5 mL/h, while the corresponding hydrogen content was 47, 86 and 87% respectively. Functional components of hydrogen generation reaction centers were also analyzed, which showed that the PS(I) reaction centers were involved in hydrogen production pathway, as the light absorption by PS(I) was prerequisite for hydrogen generation under sulfur deprived photoautotrophic condition. The findings showed a higher gas yield and hydrogen content under dark period, whereas under light period the gas content was below detectable level for hydrogen due to the reversible hydrogenase reaction.     

Dielectric and pyroelectric anisotropy in the melt-quenched barium bismuth niobate ceramics

BaBi₂Nb₂O₉ textured ceramics were fabricated via melt-quenching followed by high temperature (800–1000 °C) sintering process. The resulting ceramics possessed a {00l} texture with the a–b plane of the grains oriented parallel to the major face of the quenched plate. The influence of the sintering temperature on the orientation factor (f) and microstructure was evaluated via X-ray powder diffraction (XRD) and Scanning electron microscopy (SEM). The orientation factor was found to increase with increase in the sintering temperature and reached a maximum value of 0.47 for the samples sintered at 1000 °C for 10 h. Relative density and the grain-size of the ceramics were found to increase with increase in the sintering temperatures. The effect of texture on the dielectric and pyroelectric properties was evaluated. The measurements performed along the direction perpendicular to the pressing axis exhibited superior values than that of the direction parallel to the pressing axis. The observed anisotropy in the physical properties was attributed to the increased contribution from the highly polarizable a–b planes which are oriented in the direction perpendicular the pressing axis.     

BER evaluation and rate matching attribute selection for QoS support on the UMTS downlink

In UMTS technology, Coded Composite Transport Channels (CCTrCh-s) are used to carry multiple Transport Channels (TrCh-s) in parallel on (usually) one physical layer connection. Rate Matching Attributes (RMA-s) are used to share the CCTrCh resources among the transport channels. We consider I transport channels on the downlink of a UMTS network, with RMA values RMA ₁,RMA ₂,…,RMA _I . The QoS experienced by the multiplexed connections depends on the RMA values used. We derive analytical expressions for the Bit Error Probabilities (BER-s) seen by each uncoded TrCh in the multiplex when transmitted over an AWGN and a multipath channel. Simulations indicate that the expressions are very accurate. Next, we derive analytical expressions for bounds on the per-channel bit error probabilities seen when convolutional coding is employed by each channel and the multiplex is transmitted over an AWGN and a multipath channel, respectively. The derivation of these analytical expressions is the main contribution of this paper. Further, we use the expressions to obtain simple procedures that provide the RMA values required to achieve a target set of BER-s for a specified signal-to-noise ratio. The results of this paper indicate how differentiated QoS may be provided while maintaining high spectral efficiency. R. M. Karthik is currently a Ph.D. candidate in the Centre for Electronics Design and Technology, Indian Institute of Science, Bangalore, India. He received his B. E. (Electronics and Communication Engineering) from Government College of Technology, Coimbatore, India in 1998 and M. E. (Applied Electronics) from College of Engineering, Guindy, Anna University, India in 2000. His current research interests include communication networks and QoS in UMTS Networks. Joy Kuri has a B.E. in Electronics and Telecommunication engineering from Jadavpur University, Kolkata. After a year in the industry, he joined the M.E. program in the Department of Electrical Communication Engineering at the Indian Institute of Science. He went on to receive a Ph.D. from the same department at IISc in 1995. Subsequently, he spent two years at Ecole Polytechnique, University of Montreal, Canada and one and a half years in INRS-Telecommunications, University of Quebec, Canada as a Research Associate. Since 1999 he has been with the Centre for Electronics Design and Technology, Indian Institute of Science, where he is currently Associate Professor. His research and teaching interests are in the areas of modelling, analysis and control of communication networks and stochastic systems. He is co-author of the book Communication Networking: An Analytical Approach by Kumar, Manjunath and Kuri, published by Morgan Kaufman/Elsevier.     

Modification of CaO by Organic Alumina Precursor for Enhancing Cyclic Capture of CO2 Greenhouse Gas

The modification of CaO sorbent with organic alumina precursor to enhance the sorption capacity during cyclic capture is demonstrated in this study. The results indicate that during the 10?min sorption time for each cycle, the CO2 sorption capacity of original CaO sorbent is significantly decreased from 0.27 to 0.19 and 0.12?g CO2/g sorbent after 5 and 60?cycles, respectively. On the other hand, the organic alumina modified CaO has a fresh capacity of 0.22?g CO2/g sorbent, it increases to 0.24?g CO2/g sorbent after 5?cycles, and then decreases to around 0.15?g CO2/g sorbent after 60?cycles. When increasing the sorption time to 60?min at the 66th cycle, the sorption capacity of original CaO is 0.2, whereas it is 0.26?g CO2/g sorbent for organic alumina modified CaO. The results demonstrate that by adding only 5% by weight of Ca12Al14O33 species into the CaO sorbent, the CO2 sorption capacity can be enhanced up to ～ 27% by weight.     

Experimental and theoretical studies of a two-stage pulse tube cryocooler operating down to 3 K

The development of a two-stage Pulse Tube Cryocooler (PTC) which produces a no-load temperature of ～3 K and delivers a refrigeration power of ～250 mW at 5 K is reported in this work. The system uses stainless steel meshes along with lead (Pb) granules and combinations of Pb, Er₃Ni and HoCu₂ in layered structures as the first and second stage regenerator materials respectively. With Helium as a working fluid, the pressure oscillations are generated using a 6 kW water-cooled Helium compressor along with an indigenous rotary valve. Different configurations of pulse tube systems have been experimentally studied, by both varying the dimensions of pulse tubes and regenerators as well as the second stage regenerator material composition. The pulse tube Cryocooler has been numerically analyzed by using both the isothermal model and the model based on solving the energy equations. The predicted refrigeration powers as well as the temperature profiles have been compared with the experimental results for specific pulse tube configurations.     

Sarcastic user behavior classification and prediction from social media data using firebug swarm optimization-based long short-term memory

Sarcasm is a type of speech where people use positive words to convey a negative message. Recently, only a few research have been presented that focus on the entire spectrum of sarcasm in order to identify sarcastic sentiments present in both the image and the text. This work presents a novel firebug swarm optimization-based long short-term memory (FSO-LSTM) architecture to identify the sarcastic sentiments present in tweets. To identify the facial expressions of the users, the proposed FSO-based LSTM architecture is trained using the CK?+?dataset. The FSO algorithm is used to optimize the weighting factors of the LSTM architecture and also minimize the root-mean-square error (RMSE) and mean absolute error. The proposed method primarily attempts to address two challenging issues in sarcasm detection: the high number of false negatives and the fact that polite tweets often go undetected. The user's mood changes (sarcastic) such as rude, polite, furious, and impassive can be identified using the proposed model. Hence, the proposed classifier is capable of analyzing the behavior change of the user by collecting the past twitter account history. The efficiency of the proposed methodology is evaluated using different performance metrics such as accuracy, RMSE, confusion matrix, and loss. The proposed methodology offers an average classification accuracy of 97.25% classification accuracy when compared to the state-of-the-art approaches.