Reliability Analysis of Type III Gas Storage Vessel Under Pressure Loading

Journal of Failure Analysis and Prevention - This work presents the suggestion of a model for the prediction of the reliability of type III gas storage vessel under pressure, considering the...     

Synthesis and characterization of a series of cross-linked polyamines for removal of Erichrome Black T from aqueous solution

A new series of polymers comprising four terpolymers was synthesized via Mannich polycondensation of benzene-1,4-diamine, formaldehyde and piperazine by varying the benzene-1,4-diamine and piperazine ratio. The new polyamines (labeled Dipip) were characterized using 13C solid-state NMR, FT-IR, TGA, DSC, XRD, SEM and EDX. The adsorptive performances of the synthesized polymers for Erichrome Black T (EBT) uptake from aqueous solution were investigated under batch process. Equilibrium, kinetic, and thermo-dynamic studies were conducted to determine the influence of different operational parameters of the adsorption process. The two most promising polymers among the series show an excellent EBT removal efficiency of～100％and～95％with high adsorption capacities of 775 mg·g- 1 and 917 mg·g- 1, respectively at a meager dosage of 5 mg. The sorption of EBT on the polymers was well described by Redlich-Peterson&Langmuir model while the kinetic studies indicate that pseudo-second order model was followed. For the thermodynamic studies, the negativeΔG and positiveΔH values obtained suggest a spontaneity of the sorption process which was endothermic in nature. The results of reusability test of the resins were promising even at the fourth cycle, showcasing the potentials of the new polymers in dyes contaminated water treatment.     

Development of optimized triaxially electrospun titania nanofiber-in-nanotube core-shell structure

One dimensional (1D) nanostructures and its derivatives can be manipulated to serve special functions like hollow structure, and higher surface area. 1D TiO₂ nanotube-in-nanofibers (NF@NT) are developed through triaxial electrospinning followed by a calcination process. A blended solution of polyvinyl pyrrolidone and tetra-butyl titanate is used in outer and inner layers of nanofibers, respectively, while paraffin oil is used in the middle layer. The optimized triaxial nanofibers of 669.4 ± 52.43 nm are developed at 7.5 w/w% concentration, 28 kV applied voltage, and 24 cm spinning distance. TiO₂ NF@NT structure is obtained through calcination of optimized triaxial nanofibers at 550°C. Subsequently, the morphology of TiO₂ NF@NT and its uniform diameter distribution is confirmed through scanning electron microscopy. Fourier-transform infrared spectroscopy results indicates the formation of TiO₂ NF@NT. X-Rays diffraction pattern peaks also reveals the presence of both anatase and rutile crystalline phases. The presence of only titanium (Ti) and oxygen (O) elements in the TiO₂ NF@NT is confirmed through energy dispersive X-ray spectroscopy. Brunauer–Emmett–Teller analysis indicates that TiO₂ NF@NT has a higher specific surface area of ~141.68 m²/g compared with the solid TiO₂ nanofiber (~75.31 m²/g). This study can be adopted to develop TiO₂ NF@NT for wide range of application.     

Robotics and manufacturing education and research— the New Mexico initiatives

Since the early 1980s, the University of New Mexico (UNM) has been increasingly active in the area of manufacturing engineering and robotics research and education. Six robotics and manufacturing laboratories devoted to research and instruction have been established. Many PhD and master's students use these facilities in their research, and instructional programs have been established at the undergraduate and graduate level in both the Mechanical Engineering and Electrical and Computer Engineering Departments.Notably, a master's level program was established in 1987 with participation from two universities, UNM and New Mexico State University. Active collaboration is the mode of operation between the College of Engineering and the Robert O. Anderson Schools of Management at UNM in the manufacturing program, a program in total quality management, and in the establishment of a computer-integrated manufacturing program and laboratory through IBM's CIM in Higher Education Alliance.This paper describes these programs in detail, and discusses some approaches and future plans.     

Scalability of parallel spatial direct numerical simulations on intel hypercube and IBM SP1 and SP2

The implementation and performance of a parallel spatial direct numerical simulation (PSDNS) approach on the Intel iPSC/860 hypercube and IBM SP1 and SP2 parallel computers is documented. Spatially evolving disturbances associated with laminar-to-turbulent transition in boundary-layer flows are computed with the PSDNS code. The feasibility of using the PSDNS to perform transition studies on these computers is examined. The results indicate that PSDNS approach can effectively be parallelized on a distributed-memory parallel machine by remapping the distributed data structure during the course of the calculation. Scalability information is provided to estimate computational costs to match the actual costs relative to changes in the number of grid points. By increasing the number of processors, slower than linear speedups are achieved with optimized (machine-dependent library) routines. This slower than linear speedup results because the computational cost is dominated by FFT routine, which yields less than ideal speedups. By using appropriate compile options and optimized library routines on the SP1, the serial code achieves 52–56 Mflops on a single node of the SP1 (45 percent of theoretical peak performance). The actual performance of the PSDNS code on the SP1 is evaluated with a real world simulation that consists of 1.7 million grid points. One time step of this simulation is calculated on eight nodes of the SP1 in the same time as required by a Cray Y/MP supercomputer. For the same simulation, 32-nodes of the SP1 and SP2 are required to reach the performance of a Cray C-90. A 32 node SP1 (SP2) configuration is 2.9 (4.6) times faster than a Cray Y/MP for this simulation, while the hypercube is roughly 2 times slower than the Y/MP for this application.     

An efficient deep learning technique for facial emotion recognition

Emotion recognition from facial images is considered as a challenging task due to the varying nature of facial expressions. The prior studies on emotion classification from facial images using deep learning models have focused on emotion recognition from facial images but face the issue of performance degradation due to poor selection of layers in the convolutional neural network model.To address this issue, we propose an efficient deep learning technique using a convolutional neural network model for classifying emotions from facial images and detecting age and gender from the facial expressions efficiently. Experimental results show that the proposed model outperformed baseline works by achieving an accuracy of 95.65% for emotion recognition, 98.5% for age recognition, and 99.14% for gender recognition.

     

Contextual Text Mining Framework for Unstructured Textual Judicial Corpora through Ontologies

Digitalization has changed the way of information processing, and new techniques of legal data processing are evolving. Text mining helps to analyze and search different court cases available in the form of digital text documents to extract case reasoning and related data. This sort of case processing helps professionals and researchers to refer the previous case with more accuracy in reduced time. The rapid development of judicial ontologies seems to deliver interesting problem solving to legal knowledge formalization. Mining context information through ontologies from corpora is a challenging and interesting field. This research paper presents a three tier contextual text mining framework through ontologies for judicial corpora. This framework comprises on the judicial corpus, text mining processing resources and ontologies for mining contextual text from corpora to make text and data mining more reliable and fast. A top-down ontology construction approach has been adopted in this paper. The judicial corpus has been selected with a sufficient dataset to process and evaluate the results. The experimental results and evaluations show significant improvements in comparison with the available techniques.     

On inverse kinematics with inequality constraints: new insights into minimum jerk trajectory generation

The problem of inverse kinematics is revisited in the present paper. The paper is focusing on the problem of solving the inverse kinematics problem while minimizing the jerk of the joint trajectories. Even though the conventional inverse kinematics algorithms have been proven to be efficient in many applications, it has been proven that constraints on the accelerations or the jerk cannot be guaranteed, and even yields to divergence or makes the problem unsolvable. The proposed algorithm yields smooth velocity and acceleration trajectories, which are highly desired features for industrial robots. The algorithm uses the joint jerk as the control parameter instead of the classical use of the joint velocity as result constraints on the jerk function can be easily incorporated. To validate the proposed approach, we have conducted several simulations scenarios. The simulation results have revealed that the proposed method can efficiently solve the inverse kinematics problem while considering constraints on the joint acceleration and jerk.