Development of spark plasma sintered conductive SiC–TiB2 composites for electrical discharge machining applications

Highly dense electrically conductive silicon carbide (SiC)–(0, 10, 20, and 30 vol%) titanium boride (TiB₂) composites with 10 vol% of Y₂O₃–AlN additives were fabricated at a relatively low temperature of 1800°C by spark plasma sintering in nitrogen atmosphere. Phase analysis of sintered composites reveals suppressed β→α phase transformation due to low sintering temperature, nitride additives, and nitrogen sintering atmosphere. With increase in TiB₂ content, hardness increased from 20.6 to 23.7 GPa and fracture toughness increased from 3.6 to 5.5 MPa m^1/2. The electrical conductivity increased to a remarkable 2.72 × 10³ (Ω cm)^–1 for SiC–30 vol% TiB₂ composites due to large amount of conductive reinforcement, additive composition, and sintering in nitrogen atmosphere. The successful electrical discharge machining illustrates potential of the sintered SiC–TiB₂ composites toward extending the application regime of conventional SiC-based ceramics.     

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.     

Synergistic interaction of biocatalyst with bio-anode as a function of electrode materials

Comprehensive study was performed to understand the synergistic interaction between the biocatalyst and anode in terms of electron discharge (ED) pattern and microbial growth by varying electrode (bio-anode) materials viz., graphite, aluminum, brass, copper, nickel and stainless steel. Experiments were performed in bio-electrochemical cell consisting of three electrodes (bio-anode as working electrode, carbon rod as counter electrode and Ag/AgCl(S) as reference electrode) employing anaerobic mixed culture as anodic biocatalyst. Voltammetric and chronoamperometric analysis were used to enumerate the ED and redox reactions. Presence of higher microbial population and dominance of Gram positive bacteria with higher ED supported graphite function as a good bio-anode material. Nickel and stainless steel showed higher ED after graphite associated with dominance of Gram positive bacterial population. Although higher ED was noticed with brass, metal oxidation and decrement in ED with time doesn’t support its function as bio-anode. In spite of higher ED than nickel and stainless steel, aluminum and copper showed significant metal oxidation leading to change in both physical and electrochemical properties along with dominant growth of Gram negative bacteria. This study gives a comprehensive idea on biocatalyst interaction with anode in extracellular electron transfer which is important in improving the anode performance. Juxtaposing the results, it can be deduced that the outcome of the present study can be extended to all bio-electrochemical systems including microbial fuel cell (MFC).     

Systemic inflammatory load in humans is suppressed by consumption of two formulations of dried,encapsulated juice concentrate

Chronic inflammation contributes to an increased risk for developing chronic conditions such as cardiovascular disease, diabetes, and cancer. A high “inflammatory load” is defined as elevated inflammation markers in blood or other tissues. We evaluated several markers of systemic inflammation from healthy adults and tested the hypothesis that two formulations of encapsulated fruit and vegetable juice powder concentrate with added berry powders (FVB) or without (FV) could impact markers of inflammatory load. Using a double‐blind, placebo‐controlled approach, 117 subjects were randomly assigned to receive placebo, FV, or FVB capsules. Blood was drawn at baseline and after 60 d of capsule consumption. We measured inflammatory markers (high sensitivity C‐Reactive Protein, Monocyte Chemotactic Protein‐1, Macrophage Inflammatory Protein 1‐β, and Regulated upon Activation, Normal T cell Expressed and Secreted), superoxide dismutase, and micronutrients (β‐carotene, vitamin C, and vitamin E). Results showed Monocyte Chemotactic Protein‐1, Macrophage Inflammatory Protein 1‐β, and RANTES levels were significantly reduced and superoxide dismutase and micronutrient levels were significantly increased in subjects consuming both FV and FVB, relative to placebo. Data suggest a potential health benefit by consuming either formulation of the encapsulated juice concentrates through their anti‐inflammatory properties.     

Monthly Rainfall Prediction Using Wavelet Neural Network Analysis

Rainfall is one of the most significant parameters in a hydrological model. Several models have been developed to analyze and predict the rainfall forecast. In recent years, wavelet techniques have been widely applied to various water resources research because of their time-frequency representation. In this paper an attempt has been made to find an alternative method for rainfall prediction by combining the wavelet technique with Artificial Neural Network (ANN). The wavelet and ANN models have been applied to monthly rainfall data of Darjeeling rain gauge station. The calibration and validation performance of the models is evaluated with appropriate statistical methods. The results of monthly rainfall series modeling indicate that the performances of wavelet neural network models are more effective than the ANN models.     

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.     

Microstructure and residual stress distribution of similar and dissimilar electron beam welds – Maraging steel to medium alloy medium carbon steel

The influence of parent metal heat treatment condition on the residual stress distribution in dissimilar metal welds of maraging steel to quenched and tempered medium alloy medium carbon steel has been investigated. It has been observed that the residual stress distribution would be more compressive if the maraging steel is in soft condition. This is attributed to stress absorbing nature of highly yielding soft maraging steel.     

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.     

Degradation of chlorpyrifos contaminated soil by bioslurry reactor operated in sequencing batch mode: bioprocess monitoring

Bioslurry reactor (SS-SBR) was studied for the degradation of chlorpyrifos contaminated soil using native mixed microflora, by adopting sequencing batch mode (anoxic-aerobic-anoxic) operation. Reactor operation was monitored for a total cycle period of 72 h consisting of 3 h of FILL, 64 h REACT, 2 h of SETTLE, and 3 h of DECANT with chlorpyrifos concentrations of 3000 micrpg/g, 6000 microg/g and 12000 microg/g. At 3000 microg/g of chlorpyrifos concentration, 91% was degraded after 72 h of the cycle period, whereas in the case of 6000 microg/g of chlorpyrifos, 82.5% was degraded. However, for 12000 microg/g of chlorpyrifos, only 14.5% degradation was observed. The degradation rate was rapid at lower substrate concentration and 12000 microg/g of substrate concentration was found to be inhibitory. Chlorpyrifos removal rate was slow during the initial phase of the sequence operation. Half-life of chlorpyrifos degradation (t0.5) was estimated to be 6.3 h for 3000 microg/g of substrate, 17.5 h for 6000 microg/g and 732.2 h for 12000 microg/g. Process performance was assessed by monitoring chlorpyrifos concentration and biochemical process parameters viz., pH, oxidation and reduction potential (ORP), dissolved oxygen (DO), oxygen consumption rate (OCR) and microbial count (CFU) during sequence operation. From the experimental data obtained it can be concluded that the rate-limiting step with the bioslurry phase reactor in the process of chlorpyrifos degradation may be attributed to the concentration of substrate present in either soil or liquid phase. Periodic operations (SBR) by varying individual components of substrate with time in each process step place micro-organisms under nutritional changes from feast to famine and maintains a wide distribution in the population of micro-organisms resulting in high uptake of the substrate in the bioslurry reactor.     

Bias voltage dependence properties of cadmium oxide films deposited by d.c. reactive magnetron sputtering

Cadmium oxide films were grown on glass substrates using d.c. reactive magnetron sputtering technique by sputtering from a metallic cadmium target in an oxygen partial pressure of 1×10^–3 mbar under various substrate bias voltages. The substrate bias voltage significantly influences the crystallographic structure of the deposited films. The influence of substrate bias voltage on the electrical and optical properties of the films was systematically studied. The films formed at a substrate temperature of 473 K and bias voltage of –80 V showed an electrical resistivity of 1×10^–3 cm, optical transmittance of 86%, optical band gap of 2.47 eV and a figure of merit of 7×10^{–3 –1}.