Membrane degumming of crude rice bran oil: Pilot plant study

The procedure for the classical chemical refining of vegetable oils consists of degumming, alkali neutralization, bleaching, and deodorization. Conventional refining of rice bran oil using alkali gives oil of acceptable quality, but the refining losses are very high. A critical work has been carried out to study the application of membrane technology in the pretreatment of crude rice bran oil. Oils intended for physical refining should have a low phosphorus content, and this is not readily achievable by the conventional acid/water degumming process. The application of membrane technology for the pretreatment of rice bran oil has been investigated. The process has already been successfully applied to other vegetable oils. Ceramic membranes, which are important from the commercial point of view, were examined for this purpose. The results showed that the membrane‐filtered oils met the requirements of physical refining, with a substantial reduction in color. It was observed that most of the waxy material was also rejected. Experiments were carried out to establish the relationship between permeate flux and rejection with membrane pore size, trans‐membrane pressure and micellar solute concentration.     

Multiple process parameter optimization of wire electrical discharge machining on Inconel 825 using Taguchi grey relational analysis

In this paper, an effective approach, Taguchi grey relational analysis, has been applied to experimental results of wire cut electrical discharge machining (WEDM) on Inconel 825 with consideration of multiple response measures. The approach combines the orthogonal array design of experiment with grey relational analysis. The main objective of this study is to obtain improved material removal rate, surface roughness, and spark gap. Grey relational theory is adopted to determine the best process parameters that optimize the response measures. The experiment has been done by using Taguchi’s orthogonal array L36 (2¹?×?3⁷). Each experiment was conducted under different conditions of input parameters. The response table and the grey relational grade for each level of the machining parameters have been established. From 36 experiments, the best combination of parameters was found. The experimental results confirm that the proposed method in this study effectively improves the machining performance of WEDM process.     

A Technique for Optimal Sequential Maintenance Scheduling

This paper presents the mathematical development of, and a simple solution technique for, an optimal sequential maintenance scheduling problem. The model is shown to satisfy the Kuhn-Tucker conditions, the necessary and sufficient conditions for the existence of an optimal solution. Real-world systems consisting of mixtures of constant and increasing failure rate devices are considered in the model. Sequential preventive maintenance schedules are developed for groups of identical items with increasing failure rates. Provision is made for the corrective maintenance of these groups if failures occur in between the preventive maintenance schedules. Also, constant failure rate devices are accorded corrective maintenance when failures occur. Optimality is achieved by minimizing the total annual maintenance cost, subject to constraints on the system availability, number of maintenance personnel and intervals of preventive maintenance. The model is applied to a coal mine power system example.     

Experimental investigation on the effects of process parameters of GMAW and transient thermal analysis of AISI321 steel

Gas metal arc welding (GMAW) develops an arc by controlling the metal from the wire rod and the input process parameters. The deposited metal forms a weld bead and themechanical properties depend upon the quality of the weld bead. Proper control of the process parameters which affect the bead geometry, the microstructures of the weldments and the mechanical properties like hardness, is necessary. This experimental study aims at developing mathematical models for bead height (HB), bead width (WB) and bead penetration (PB) and investigating the effects of four process parameters
viz: welding voltage, welding speed, wire feed rate and gas flow rate on bead geometry, hardness and microstructure of AISI321 steel with 10 mm thickness. The transient thermal analysis shows temperature and residual stress distributions at different conduction and convection conditions.     

Cellular Mechanisms of Enhanced Osteoblasts Functions via Phase‐Reversion Induced Nano/Submicron‐Grained Structure in a Low‐Ni Austenitic Stainless Steel

We elucidate here the fundamental principles underlying the modulation of osteoblasts functions in stainless steel biomedical devices achieved by nanoscale/submicron grain structure obtained through the novel concept of phase reversion in a low Ni bearing 15Cr–9Mn–1.7Cu steel. Interestingly, a comparative investigation of nano/submicron (N‐SM) and coarse‐grained (CG) structure under identical conditions indicated that cell attachment, proliferation, and viability are favorably enhanced in N‐SM grained structure and significantly different from the CG structure. These observations were further confirmed by expression levels of vinculin and associated actin cytoskeleton. Computational analysis of immunofluorescence micrographs suggested increased vinculin concentration associated with actin stress fibers in the outer regions of the cells and cellular extensions, implying enhanced cell–substrate interactions on the N‐SM grained substrate. The favorable enhancement of osteoblasts functions and cellular attachment on N‐SM grained surface is attributed to ultrafine grain size, i.e., the availability of greater open lattice in the position of high angle grain boundaries, and high hydrophilicity. The integration of cellular and molecular biology with material science and engineering as described here provides a route to modulate cellular and molecular reactions in promoting osteoinductive signaling of surface adherent cells. The end outcome of the study is that stainless steels with low Ni contents in comparison to the conventionally used bioimplant with 10–13 wt%Ni, as specially processed, exhibit desired, enhanced cell functions, and bulk properties.     

A Physics-driven Neural Networks-based Simulation System (PhyNNeSS) for multimodal interactive virtual environments involving nonlinear deformable objects

BACKGROUND: While an update rate of 30 Hz is considered adequate for real time graphics, a much higher update rate of about 1 kHz is necessary for haptics. Physics-based modeling of deformable objects, especially when large nonlinear deformations and complex nonlinear material properties are involved, at these very high rates is one of the most challenging tasks in the development of real time simulation systems. While some specialized solutions exist, there is no general solution for arbitrary nonlinearities. METHODS: In this work we present PhyNNeSS - a Physics-driven Neural Networks-based Simulation System - to address this long-standing technical challenge. The first step is an off-line pre-computation step in which a database is generated by applying carefully prescribed displacements to each node of the finite element models of the deformable objects. In the next step, the data is condensed into a set of coefficients describing neurons of a Radial Basis Function network (RBFN). During real-time computation, these neural networks are used to reconstruct the deformation fields as well as the interaction forces. RESULTS: We present realistic simulation examples from interactive surgical simulation with real time force feedback. As an example, we have developed a deformable human stomach model and a Penrose-drain model used in the Fundamentals of Laparoscopic Surgery (FLS) training tool box. CONCLUSIONS: A unique computational modeling system has been developed that is capable of simulating the response of nonlinear deformable objects in real time. The method distinguishes itself from previous efforts in that a systematic physics-based pre-computational step allows training of neural networks which may be used in real time simulations. We show, through careful error analysis, that the scheme is scalable, with the accuracy being controlled by the number of neurons used in the simulation. PhyNNeSS has been integrated into SoFMIS (Software Framework for Multimodal Interactive Simulation) for general use.     

Erosion behavior of SiC–WC composites

Dense silicon carbide (SiC) ceramics were prepared with 0, 10, 30 or 50 wt% WC particles by hot pressing powder mixtures of SiC, WC and oxide additives at 1800 °C for 1 h under a pressure of 40 MPa in an Ar atmosphere. Effects of alumina or SiC erodent particles and the WC content on the erosion performance of sintered SiC–WC composites were assessed. Microstructures of the sintered composites consisted of WC particles distributed in the equi-axed grain structure of SiC. Fracture surfaces showed a mixed mode of fracture, with a large extent of transgranular fracture observed in SiC ceramics prepared with 30 wt% WC. Crack bridging by WC enhanced toughening of the SiC ceramics. A maximum fracture toughness of 6.7 MPa*m^1/2 was observed for the SiC ceramics with 50 wt% WC, whereas a high hardness of 26 GPa was obtained for the SiC ceramics with 30 wt% WC. When eroded at normal incidence, two orders of magnitude less erosion occurred when SiC–WC composites were eroded by alumina particles than that eroded by SiC particles. The erosion rate of the composites increased with increasing angle of SiC particle impingement from 30° to 90°, and decreased with WC reinforcement up to 30 wt%. A minimum erosion wear rate of 6.6 mm³/kg was obtained for SiC–30 wt% WC composites. Effects of mechanical properties and microstructure on erosion of the sintered SiC–WC composites are discussed, and the dominant wear mechanisms are also elucidated.     

Finite element analysis of the bending behavior of a workpiece in equal channel angular pressing

For the first time, a detailed and systematic finite element study was carried to identify the parameters which cause the bending of the workpiece in equal channel angular pressing. These simulations were carried out by using commercial finite element code Abaqus with different materials behavior, processing parameters, and die geometries. The results showed that the optimal ways to reduce the bending of strain rate sensitive materials in ECAP without varying the strain homogeneity are the usage of lower processing speed and the increase in length of the die exit-channel.     

Optimal design of \overline {\text{X}} -control chart with Pareto in-control times

Economic control chart models usually assume that the time to occurrence of an assignable cause follows an exponential or Weibull distribution. This paper extends that to the Pareto distribution in order to investigate, in general, the effect on the economic control chart parameters like sample size, time between two successive samples, and the cost per unit time of the distributional assumption. The Pareto distribution arises as a limiting distribution of the waiting time for the number of new observations needed to obtain a value exceeding the greatest among “n” observations. It was found that the economic design of $ \overline {\text{X}} $ chart is greatly influenced by the distributional assumption. Using the cost model, the sensitivity analysis of the statistical economic design of the $ \overline {\text{X}} $ chart with respect to the parameters and costs is studied.