Effect of holmium substitution on structural and electrical properties of barium zirconate titanate ferroelectric ceramics

The holmium substituted Ba_1−3x/2Ho_xZr_0.025Ti_0.975O₃ (x=0.01, 0.02, 0.025, 0.05) compositions were synthesized by the solid state reaction technique. The synthesized specimens were characterized for their structural and electrical properties using X-ray diffractometer, scanning electron microscopy, impedance analyzer and loop tracer. Phase analysis shows the formation of secondary phase Ho₂Ti₂O₇ for Ho≥2.5 mol% substitution. The microstructural investigation shows that the holmium substitution significantly reduces the grain size. The substitution of holmium increases the Curie temperature for x≤0.02 whereas Curie temperature decreases for x≥0.025. The maximum dielectric constant at transition temperature is observed for x=0.02. The solubility limit is 2 mol% and for x≥0.025 some of the holmium atoms enter B-sites and forms the secondary phase. An increase is observed in the coercive field of the specimens with the increasing holmium content.     

Enhancement of properties of recycled coarse aggregate concrete using bacteria

Due to rapid construction, necessity for raw materials of concrete, especially coarse aggregate, tends to increase the danger of early exhaustion of the natural resources. An alternative source of raw materials would perhaps delay the advent of this early exhaustion. Recycled coarse aggregate (RCA) plays a great role as an alternative raw material that can replace the natural coarse aggregate (NCA) for concrete. Previous studies show that the properties of RCA concrete are inferior in quality compared to NCA concrete. This article attempts to study the improvement of properties of RCA concrete with the addition of bacteria named as Bacillus subtilis. The experimental investigation was carried out to evaluate the improvement of the compressive strength, capillary water absorption, and drying shrinkage of RCA concrete incorporating bacteria. The compressive strength of RCA concrete is found to be increased by about 20% when the cell concentration of B. subtilis is 10⁶ cells/ml. The capillary water absorption as well as drying shrinkage of RCA are reduced when bacteria is incorporated. The improvement of RCA concrete is confirmed to be due to the calcium carbonate precipitation as observed from the microstructure studies carried out on it such as EDX, SEM, and XRD.     

Adaptive Linear Quadratic Regulator for Continuous-Time Systems With Uncertain Dynamics

In this paper, adaptive linear quadratic regulator (LQR) is proposed for continuous-time systems with uncertain dynamics. The dynamic state-feedback controller uses input-output data along the system trajectory to continuously adapt and converge to the optimal controller. The result differs from previous results in that the adaptive optimal controller is designed without the knowledge of the system dynamics and an initial stabilizing policy. Further, the controller is updated continuously using input-output data, as opposed to the commonly used switched/intermittent updates which can potentially lead to stability issues. An online state derivative estimator facilitates the design of a model-free controller. Gradient-based update laws are developed for online estimation of the optimal gain. Uniform exponential stability of the closed-loop system is established using the Lyapunov-based analysis, and a simulation example is provided to validate the theoretical contribution.      

Partitioned encoding schemes for algorithm-based fault tolerance inmassively parallel systems

Considers the applicability of algorithm based fault tolerance (ABET) to massively parallel scientific computation. Existing ABET schemes can provide effective fault tolerance at a low cost For computation on matrices of moderate size; however, the methods do not scale well to floating-point operations on large systems. This short note proposes the use of a partitioned linear encoding scheme to provide scalability. Matrix algorithms employing this scheme are presented and compared to current ABET schemes. It is shown that the partitioned scheme provides scalable linear codes with improved numerical properties with only a small increase in hardware and time overhead     

A Component Selection Framework of Cohesion and Coupling Metrics

Component-based software engineering is concerned with the development of software that can satisfy the customer prerequisites through reuse or independent development. Coupling and cohesion measurements are primarily used to analyse the better software design quality, increase the reliability and reduced system software complexity. The complexity measurement of cohesion and coupling component to analyze the relationship between the component module. In this paper, proposed the component selection framework of Hexa-oval optimization algorithm for selecting the suitable components from the repository. It measures the interface density modules of coupling and cohesion in a modular software system. This cohesion measurement has been taken into two parameters for analyzing the result of complexity, with the help of low cohesion and high cohesion. In coupling measures between the component of inside parameters and outside parameters. The final process of coupling and cohesion, the measured values were used for the average calculation of components parameter. This paper measures the complexity of direct and indirect interaction among the component as well as the proposed algorithm selecting the optimal component for the repository. The better result is observed for high cohesion and low coupling in component-based software engineering.     

Knowledge-based systems using neural networks for electron beam welding process of reactive material (Zircaloy-4)

Bead-on-plate welding of zircaloy-4 (a reactive material) plates was conducted using electron beam according to central composite design of experiments. Its predictive models were developed in the form of knowledge-based systems in both forward and reverse directions using neural networks. Input parameters considered for this welding of reactive metals were accelerating voltage, beam current and weld speed. The responses of the welding process were measured in terms of bead width, depth of penetration and micro-hardness. Forward mapping of the welding process was conducted using regression analysis, back-propagation neural network (BPNN), genetic algorithm-tuned neural network (GANN) and particle swarm optimization algorithm-tuned neural network (PSONN). Reverse mapping of this process was also carried out using the BPNN, GANN and PSONN-based approaches. Neural network-based approaches could model this welding process of reactive material in both forward and reverse directions efficiently, which is required for the automation of the same. The performance of the neural network models was found to be data-dependent. The BPNN could outperform the other two approaches for most of the cases but not all in both the forward and reverse mappings.     

Cross‐polarization reduction of microstrip antenna using microwave absorbers

In this article, a metamaterial inspired microwave absorber is used to reduce the cross‐polarization (XP) level of the radiated wave in microstrip antenna (MSA). A microwave absorber unit‐cell has been analyzed and implemented to reduce the cross polarization (XP) level in a single element and a 2 × 2 microstrip patch array antennas. The antennas have been designed on a FR‐4 substrate of thickness 0.8 mm at 10.1 GHz center frequency. The 2 × 2 patch array antenna with and without the absorbers have been experimentally verified for the S11 parameter, the radiation pattern, and the XP suppression in H‐plane and a good comparison has been found.     

Development of Refined BOD and DO Models for Highly Polluted Kali River in India

Most commonly used river water quality models for biochemical oxygen demand (BOD) and dissolved oxygen (DO) simulations are mainly based on advection, decay, settling, and loading functions. Using these concepts, refined river water quality models for BOD and DO simulations are developed in the present work considering a large number of physically based parameters and input variables. The refined models developed can be transformed to some of the commonly used river water quality models, if physically based parameters and input variables are omitted or removed. To test the applicability of the refined models developed and commonly used models, a total of 732 water quality and flow data sets are collected during March 1999–February 2000 from 22 sampling stations of the River Kali in India. River Kali is a highly polluted river in India and receives continuous inflow of untreated point source pollution from municipal and industrial wastes and nonpoint source pollution from agricultural areas. Newton–Raphson technique is used to optimize the model parameters during calibration and the performance of different models are evaluated using error estimation, viz. standard error and mean multiplicative error, and correlation statistics (r2). The results indicate that the BOD–DO models proposed by Camp in 1963 provide better results in comparison to other commonly used models. Moreover, the refined models developed for BOD and DO simulations minimize error estimates and improve correlation between observed and computed BOD and DO values of River Kali.