Effect of steam environment on severe core damage behaviour for VVER-1000 with the ASTEC V1 code

Severe accident studies for very low frequency events for VVER-1000 (V320) are carried out to estimate in-vessel damage progression under steam-rich and starved conditions. The analyses with code ASTEC, jointly developed by IRSN (France) and GRS, Germany), have shown the influence of steam environment on core heat-up followed by material relocation, hydrogen production, vessel failure and aerosol generation along with release to containment. Hydro-accumulator injection for studied transients also gives rise to a steam-rich environment enhancing the material oxidation depending on the injection time and period. The generated information along with PSA-Level 2 is helpful to decide Plant Damage State (PDS) and fruitfully develop accident management strategies for the plant.     

Thermoelectric cold-chain chests for storing/transporting vaccines in remote regions

The cold chain is one of the key elements of the preventive health-care delivery system. Vaccines have to be carried long distances, stored in remote places and during this period the temperature has to be maintained within certain specified values. Realizing the needs of such requirements, the Department of Science & Technology, New Delhi (Govt. of India) assigned a project to the R&D Division of MECON, Ranchi for development of Thermoelectric Cold-Chain Chest operated by 12 V DC vehicular battery. The resulting portable thermoelectric (i.e. Peltier effect) Cold-Chain Chest (TCC) operated successfully even in an ambient environment of 45 °C, mainly for preserving and transporting life-saving medicines for urban as well as rural areas.     

Synthesis of Flexible Graphene/Polymer Composites for Supercapacitor Applications

In this paper, the graphene was synthesized using biocompatible cellulosic component from onions. Onion epidermal cells were chosen as raw material. During heating at high temperature, the bonding among atoms in material was rearranged and forms two-dimensional hexagonal carbon layer (graphene). The characterization of synthesized graphene was done by x-ray diffractometer, Raman spectrometer and field emission scanning electron microscopy, respectively. An attempt has been taken to form the capacitors with two different current collector electrodes, anticipating the performance of the supercapacitors. The observed capacitance values as-obtained for Al and Au current collector were 1.3 μF and 6.08 μF, respectively. However, when thermally exfoliated graphene was used as an electrode on Al and Au current collector, the capacitance value was drastically increased and found to be 1.6 and 41.25 μF, respectively.     

Analytic solution for planar indeterminate impact problems using an energy constraint

This work proposes an analytic method for resolving planar multi-point indeterminate impact problems for rigid-body systems. An event-based approach is used to detect impact events, and constraints consistent with the rigid-body assumption are used to resolve the indeterminacy associated with multi-point impact analysis. The work-energy relation is utilized to determine post-impact velocities based on an energetic coefficient of restitution to model energy dissipation, thereby yielding an energetically consistent set of post-impact velocities based on Stronge’s energetic coefficient of restitution for the treatment of rigid impacts. The effect of stick–slip transition is analyzed based on Coulomb friction. This paper also discusses the transition from impact to contact. This analysis is essential for considering the rocking block problem that is used as an example herein. The predictions of the model for the rocking block problem are compared to experimental results published in the literature. An example of a planar ball undergoing two-point impact is also presented.     

Intermetallic Precipitation in Low-Density Steel

Metallurgical and Materials Transactions A - Low-density steels (LDS) represent a relatively new class of material that contains a large concentration of aluminum. In the present work, we studied...     

An automated patient monitoring using discrete‐time wireless sensor networks

In recent years, Internet of Things (IoT) devices are used for remote health monitoring. For remotely monitoring a patient, only the health information at different time points are not sufficient; predicted values of biomarkers (for some future time points) are also important. In this article, we propose a powerful statistical model for an efficient dynamic patient monitoring using wireless sensor nodes through Bayesian Learning (BL). We consider the setting where a set of correlated biomarkers are measured from a patient through wireless sensors, but the sensors only report the ordinal outcomes (say, good, fair, high, or very high) to the sink based on some prefixed thresholds. The challenge is to use the ordinal outcomes for monitoring and predicting the health status of the patient under consideration. We propose a linear mixed model where interbiomarker correlations and intrabiomarker dependence are modeled simultaneously. The estimated and the predicted values of the biomarkers are transferred over the internet so that health care providers and the family members of the patient can remotely monitor the patient. Extensive simulation studies are performed to assess practical usefulness of our proposed joint model, and the performance of the proposed joint model is compared to that of some other traditional models used in the literature.     

Identification of monofloral honey using voltammetric electronic tongue

Quality assessment of honey is often related to its floral origin which is a complex task to evaluate. Traditional technique of floral assessment is made by melissopalynological method. However, this method is quite time consuming and also often operator dependent. Thus, the fallout is a large range of error in interpretation of the result and hence there is considerable demand for instrumental methods to assess the identification of pollen in honey. In this pursuit, an electronic tongue based on cyclic voltammetry is developed to discriminate honey samples based on their floral types and is described in this paper. The technique has been investigated using platinum as the working electrode and the resultant current from the potentiostat has been considered for data analysis. The use of principal component analysis (PCA) and linear discriminate analysis (LDA) proves to be useful in clustering honey samples. Finally, classification performances are investigated using back-propagation multilayer perceptron (BP-MLP) and radial basis function (RBF) neural network models for identification of different floral origin of honey.     

An inhomogeneous thermal block model of man for the electromagnetic environment

An inhomogeneous thermal block model of man with 476 cubical cells has been developed. It incorporates inhomogeneous blood flow rates, metabolic heat production, specific heats, and thermal conductivities, obtained by volume-weighted averaging of the values for eleven different tissue types which constitute the human body. The transient heat conduction equation for the thermal model includes the effects of internal metabolic heat generation, electromagnetic energy deposition, heat conduction through the tissues, convective heat transfer by blood, evaporative heat dissipation by sweating and insensible perspiration, respiratory heat loss, and heat transfer to the environment by radiation and convection. The standard implicit finite difference technique has been utilized to solve the three-dimensional heat conduction equation.     

Quarterwave microstrip antenna on a ferrimagnetic substrate

Experiment conducted on a microstrip quarterwave antenna structure on a typical ferrite substrate reveals reduction in size, interesting radiation characteristics and a broadband nature over a wide range of frequencies in the lower UHF region.     

BIST/Digital-Compatible Testing of RF Devices Using Distortion Model Fitting

Testing of Radio Frequency (RF) circuits for nonlinearity specifications generally requires the use of multiple test measurements thereby contributing to increased test cost. Prior RF test methods have suffered from significant test calibration effort (training for supervised learners) when using compact tests or from increased test time due to direct specification measurement. On the other hand, due to aggressive technology scaling, there are plenty of digital transistors available that can be used to simplify testing of Analog/Mixed-Signal (AMS) and RF devices. In this paper, an RF test methodology is developed that: (a) allows RF devices to be tested for several distortion specifications using distortion model fitting algorithms in test time comparable to what can be achieved using supervised learning techniques while retaining the accuracy of direct specification measurement, (b) allows multiple RF specifications to be determined concurrently from a single data acquisition and (c) allows digital-compatible testing/BIST to be performed using digital testers or on-chip built in self-test (BIST) circuitry. With regard to (a), a key benefit is that no training of supervised learning algorithm is necessary. The proposed method based on distortion model fitting is shown to give excellent results across common RF performance metrics while providing ~10× improvements in test time compared to previous methods.