Recent developments in the extrusion of helical gears

With an improved die, a method for manufacturing gears by means of tube extrusion has been developed to a stage where, without noticeable wear of the die, 40,000 workpieces can be manufactured. The paper presents a numerical analysis of the stresses and deflection of the die, offering also a comparison between the modified and the conventional symmetric orifice. Based on the results obtained and using recent work on crack prediction for extrusion dies, the area most prone to rupture is determined. Moreover, a concept for the precorrection of the die is offered to improve the tooth quality of the gears.     

Adsorption and decomposition of H2S on Pd(1 1 1) surface: a first-principles study

Gradient-corrected density functional theory was used to investigate the adsorption of H₂S on Pd(1 1 1) surface. Molecular adsorption was found to be stable with H₂S binding preferentially at top sites. In addition, the adsorption of other S moieties (SH and S) was investigated. SH and S were found to be preferentially bind at the bridge and fcc sites, respectively. The reaction pathways and energy profiles for H₂S decomposition giving rise to adsorbed S and H were determined. Both H₂S_(ad) → SH_(ad) + H_(ad) and SH_(ad) → S_(ad) + H_(ad) reactions were found to have low barriers and high exothermicities. This reveals that the decomposition of H₂S on Pd(1 1 1) surface is a facile process.     

Biflavonoid-Induced Disruption of Hydrogen Bonds Leads to Amyloid-β Disaggregation

Deposition of amyloid β (Aβ) fibrils in the brain is a key pathologic hallmark of Alzheimer’s disease. A class of polyphenolic biflavonoids is known to have anti-amyloidogenic effects by inhibiting aggregation of Aβ and promoting disaggregation of Aβ fibrils. In the present study, we further sought to investigate the structural basis of the Aβ disaggregating activity of biflavonoids and their interactions at the atomic level. A thioflavin T (ThT) fluorescence assay revealed that amentoflavone-type biflavonoids promote disaggregation of Aβ fibrils with varying potency due to specific structural differences. The computational analysis herein provides the first atomistic details for the mechanism of Aβ disaggregation by biflavonoids. Molecular docking analysis showed that biflavonoids preferentially bind to the aromatic-rich, partially ordered N-termini of Aβ fibril via the π–π interactions. Moreover, docking scores correlate well with the ThT EC₅₀ values. Molecular dynamic simulations revealed that biflavonoids decrease the content of β-sheet in Aβ fibril in a structure-dependent manner. Hydrogen bond analysis further supported that the substitution of hydroxyl groups capable of hydrogen bond formation at two positions on the biflavonoid scaffold leads to significantly disaggregation of Aβ fibrils. Taken together, our data indicate that biflavonoids promote disaggregation of Aβ fibrils due to their ability to disrupt the fibril structure, suggesting biflavonoids as a lead class of compounds to develop a therapeutic agent for Alzheimer’s disease.     

CU++: an object oriented framework for computational fluid dynamics applications using graphics processing units

The application of graphics processing units (GPU) to solve partial differential equations is gaining popularity with the advent of improved computer hardware. Various lower level interfaces exist that allow the user to access GPU specific functions. One such interface is NVIDIA’s Compute Unified Device Architecture (CUDA) library. However, porting existing codes to run on the GPU requires the user to write kernels that execute on multiple cores, in the form of Single Instruction Multiple Data (SIMD). In the present work, a higher level framework, termed CU++, has been developed that uses object oriented programming techniques available in C++ such as polymorphism, operator overloading, and template meta programming. Using this approach, CUDA kernels can be generated automatically during compile time. Briefly, CU++ allows a code developer with just C/C++ knowledge to write computer programs that will execute on the GPU without any knowledge of specific programming techniques in CUDA. This approach is tremendously beneficial for Computational Fluid Dynamics (CFD) code development because it mitigates the necessity of creating hundreds of GPU kernels for various purposes. In its current form, CU++ provides a framework for parallel array arithmetic, simplified data structures to interface with the GPU, and smart array indexing. An implementation of heterogeneous parallelism, i.e., utilizing multiple GPUs to simultaneously process a partitioned grid system with communication at the interfaces using Message Passing Interface (MPI) has been developed and tested.     

Hydrocarbon condensation modelling to mitigate fluid coker cyclone fouling

FLUID COKING is a continuous process that thermally converts heavy hydrocarbons, such as oil sands bitumen, to lighter and higher‐value products by horizontal spray injection onto a fluidized bed of hot coke particles. The cyclone sections of commercial fluid coker reactors experience fouling during typical operation, which limits unit run lengths. The main objective of this work is to improve fluid coker reliability by proposing cyclone fouling mitigation strategies based on practical operation modifications. This study developed a process simulation in Aspen Plus to establish the combined impact of vapour‐liquid equilibrium, endothermic thermal cracking reactions, pressure changes, and overall fluid dynamics in the selected fluid coker control volumes. The hydrocarbon composition was defined by applying an assay characterization of distillation data for representative hydrocarbon streams. Case studies were performed to determine the sensitivity of the predicted temperatures and hydrocarbon condensate flow rates for: (a) the burner‐to‐fluid coker transfer line temperature; (b) the hot coke flow rate; (c) hot coke entrainment from the freeboard region; and (d) scouring coke flow rate in the horn chamber. The scouring coke flow rate was identified as the most promising process lever to mitigate fluid coker cyclone fouling.     

Isolation and characterization of cellulose nanowhiskers from Acacia caesia plant

Acacia caesia (L.) Willd (soap bark) fiber is an abundant natural resource, that is rich in cellulose. The study reports the effective utilization of underutilized Acacia caesia fiber for the isolation of nanocellulose whiskers. The nanocellulose whiskers were isolated successfully from Acacia caesia fibers by following alkali, bleaching, and sulfuric acid treatment. The obtained nanocellulose whiskers were carefully investigated for its chemical composition, structure, morphology, crystallinity, and thermal stability. The chemical composition and Fourier transform infrared spectra of nanocellulose whiskers showed the elimination of the non-cellulosic parts present in the raw Acacia caesia fibers. The X-ray diffraction analysis showed an upsurge in the crystallinity of the cellulose fibers after the chemical treatments. The isolation of nanocellulose whiskers from Acacia caesia raw fiber was confirmed by electron microscopy analysis. The thermogravimetric analysis showed remarkably high char residue for the nanocellulose whiskers compared to raw fibers. Based on the properties of nanocellulose whiskers, it can be concluded that the nanocellulose whiskers produced from Acacia caesia raw fibers are potential reinforcing material for developing high-performance green composites.     

Building Trust and Cooperation through Technology Adaptation in Virtual Teams: Empirical Field Evidence

Abstract

This article reports findings of a study of how leaders of virtual information systems development teams improve team trust and cooperation by managing adaptation of information and communications tools. Results indicate how Theory X (command and control) and Theory Y (facilitate and support) styles of leadership enable and hinder effective outcomes.     

Energy sector planning using multiple-index pinch analysis

Pinch analysis was initially developed as a methodology for optimizing energy efficiency in process plants. Applications of pinch analysis applications are based on common principles of using stream quantity and quality to determine optimal system targets. This initial targeting step identifies the pinch point, which then allows complex problems to be decomposed for the subsequent design of an optimal network using insights drawn from the targeting stage. One important class of pinch analysis problems is energy planning with footprint constraints, which began with the development of carbon emissions pinch analysis; in such problems, energy sources and demands are characterized by carbon footprint as the quality index. This methodology has been extended by using alternative quality indexes that measure different sustainability dimensions, such as water footprint, land footprint, emergy transformity, inoperability risk, energy return on investment and human fatalities. Pinch analysis variants still have the limitation of being able to use one quality index at a time, while previous attempts to develop pinch analysis methods using multiple indices have only been partially successful for special cases. In this work, a multiple-index pinch analysis method is developed by using an aggregate quality index, based on a weighted linear function of different quality indexes normally used in energy planning. The weights used to compute the aggregate index are determined via the analytic hierarchy process. A case study for Indian power sector is solved to illustrate how this approach allows multiple sustainability dimensions to be accounted for in energy planning.     

The Mediating Role of Self-Efficacy in the Development of Entrepreneurial Intentions.

The purpose of this study was to investigate the mediating role of self-efficacy in the development of students' intentions to become entrepreneurs. The authors used structural equation modeling with a sample of 265 master of business administration students across 5 universities to test their hypotheses. The results showed that the effects of perceived learning from entrepreneurship-related courses, previous entrepreneurial experience, and risk propensity on entrepreneurial intentions were fully mediated by entrepreneurial self-efficacy. Contrary to expectations, gender was not mediated by self-efficacy but had a direct effect such that women reported lower entrepreneurial career intentions. The authors discuss practical implications and directions for future research. (PsycINFO Database Record (c) 2010 APA, all rights reserved)