In situ repair welding of steam turbine shroud for replacing a cracked blade

A root-cracked blade in a high-pressure steam turbine of a nuclear power plant had to be replaced with a new blade by cutting the shroud to remove the cracked blade. This necessitated in situ welding of a new shroud piece with the existing shroud after the blade replacement. The in situ welding of the shroud, a 12% Cr martensitic stainless steel with tempered martensite microstructure, was carried out using gastungsten arc welding and 316L austenitic stainless steel filler metal followed by localized postweld heat treatment at 873 K for 1 h using a specially designed electrical resistance-heating furnace. Mock-up trials were carried out to ensure that sound welds could be made under the constraints present during the in situ repair welding operation. In situ metallography of the repair weld after postweld heat treatment confirmed the adequate tempering of the martensitic structure in the heat-affected zone. Metallurgical investigations carried out in the laboratory on a shroud test-piece that had been welded using the same procedure as employed in the field confirmed the success of the in situ repair operation. The alternate option available was replacing the cracked blade and the shroud piece to which it is riveted with a new one, reducing the height of all the blades attached to the shroud by machining, riveting the blades with reduced height to the new shroud, and, finally, dynamic balancing of the entire turbine after completion of the repair. This option is both time-consuming and expensive. Hence, the successful completion of this repair welding resulted in enormous savings both in terms of reducing the downtime of the plant and the cost of the repair. The turbine has been put back into service and has been operating satisfactorily since December 2000.     

On the applicability of diploid genetic algorithms in dynamic environments

Diploid genetic algorithms (DGAs) promise robustness as against simple genetic algorithms which only work towards optimization. Moreover, these algorithms outperform others in dynamic environments. The work examines the theoretical aspect of the concept by examining the existing literature. The present work takes the example of dynamic TSP to compare greedy approach, genetic algorithms and DGAs. The work also implements a greedy genetic approach for the problem. In the experiments carried out, the three variants of dominance were implemented and 115 runs proved the point that none of them outperforms the other.     

A compact asymmetric slot dual band antenna fed by CPW for PCS and UWB applications

A compact slot antenna with an overall dimension of 30 × 30 × 1.6 mm³ is proposed for dual band applications. The radiating element is a hexagonal shape patch which protrudes from a Co‐Planar Waveguide (CPW) feed into a step shape slot. The slot is basically rectangular in shape and is extended by inserting rectangular cuts of different sizes on the ground plane around it. The ultrawide impedance bandwidth is achieved using asymmetric feed line along with extended rectangular cuts around the slot. For realizing the second band for personal communication system applications (near 1.9 GHz), a metallic stub of quarter wave length is attached at the top of the slot. The measured impedance bandwidth (for S₁₁ < ?10 dB) is 110 MHz (1.86–1.97 GHz) for the first band and 9 GHz (3.0–12.0 GHz) for the second band. The antenna is further characterized by omnidirectional radiation patterns in the H‐plane, dumb‐bell shape radiation patterns in the E‐plane and a peak gain of 3–5 dBi over the ultrawideband. All the measured results are found to be in good agreement with the simulated results. © 2014 Wiley Periodicals, Inc. Int J RF and Microwave CAE 25:243–254, 2015.     

Design of Barrages with Genetic Algorithm Based Embedded Simulation Optimization Approach

Barrages are hydraulic structures constructed across rivers to divert flow into irrigation canals or power generation channels. The most of these structures are founded on permeable foundation. The optimum cost of these structures is nonlinear function of factors that cause the seepage forces under the structure. There is, however, no procedure to ascertain the basic barrage parameters such as depth of sheet piles or cutoffs and the length and thickness of floor in a cost–effective manner. In this paper, a nonlinear optimization formulation (NLOF), which consists of an objective function of minimizing total cost, is solved using genetic algorithm (GA). The mathematical model that represents the subsurface flow is embedded in the NLOF. The applicability of the approach has been illustrated with a typical example of barrage profile. The results obtained in this study shows drastic cost savings when the proposed NLOF is solved using GA than that of using classical optimization technique and conventional method. A parametric analysis has also been performed to study the effect of varying soil and hydrological conditions on design parameters and on over all cost.     

Guest Editors' Introduction: Hot Chips 19

This special issue showcases articles written from five of the best presentations at the Hot Chips 19 conference, held in August 2007. The guest editors give highlights of the conference and introduce the articles, which cover the mobile-optimized northbridge of AMD's Griffin microprocessor family; the IBM z10 next-generation mainframe microprocessor; fault tolerance in IBM's Power6 microprocessor; NVIDIA's Tesla unified graphics and computing architecture; and SiBEAM's 4-Gbps 1080p-capable uncompressed HD A/V wireless 60-GHz transceiver chipset.     

BS-SC Model: A Novel Method for Predicting Child Abuse Using Borderline-SMOTE Enabled Stacking Classifier

For a long time, legal entities have developed and used crime prediction methodologies. The techniques are frequently updated based on crime evaluations and responses from scientific communities. There is a need to develop type-based crime prediction methodologies that can be used to address issues at the subgroup level. Child maltreatment is not adequately addressed because children are voiceless. As a result, the possibility of developing a model for predicting child abuse was investigated in this study. Various exploratory analysis methods were used to examine the city of Chicago’s child abuse events. The data set was balanced using the Borderline-SMOTE technique, and then a stacking classifier was employed to ensemble multiple algorithms to predict various types of child abuse. The proposed approach successfully predicted crime types with 93% of accuracy, precision, recall, and F1-Score. The AUC value of the same was 0.989. However, when compared to the Extra Trees model (17.55), which is the second best, the proposed model’s execution time was significantly longer (476.63). We discovered that Machine Learning methods effectively evaluate the demographic and spatial-temporal characteristics of the crimes and predict the occurrences of various subtypes of child abuse. The results indicated that the proposed Borderline-SMOTE enabled Stacking Classifier model (BS-SC Model) would be effective in the real-time child abuse prediction and prevention process.     

Design and Development of Flexible PDMS Antenna for UWB-WBAN Applications

Wireless Personal Communications - This paper presents the design and development of a flexible Ultra Wide Band (UWB) antenna using polydimethylsiloxane as a substrate. Copper foil having a...     

Detection of Malicious Profiles and Protecting Users in Online Social Networks

Wireless Personal Communications - Everyone today actively uses online social networks to get in touch with their friends, for career opportunities, and business also. Some of the most popular...     

An extended hesitant fuzzy set using SWARA-MULTIMOORA approach to adapt online education for the control of the pandemic spread of COVID-19 in higher education institutions

The world has been challenged since late 2019 by COVID-19. Higher education institutions have faced various challenges in adapting online education to control the pandemic spread of COVID-19. The present study aims to conduct a survey study through the interview and scrutinizing the literature to find the key challenges. Subsequently, an integrated MCDM framework, including Stepwise Weight Assessment Ratio Analysis (SWARA) and Multiple Objective Optimization based on Ratio Analysis plus Full Multiplicative Form (MULTIMOORA), is developed. The SWARA procedure is applied to the analysis and assesses the challenges to adapt the online education during the COVID-19 outbreak, and the MULTIMOORA approach is utilized to rank the higher education institutions on hesitant fuzzy sets. Further, an illustrative case study is considered to express the proposed idea's feasibility and efficacy in real-world decision-making. Finally, the obtained result is compared with other existing approaches, confirming the proposed framework's strength and steadiness. The identified challenges were systemic, pedagogical, and psychological challenges, while the analysis results found that the pedagogical challenges, including the lack of experience and student engagement, were the main essential challenges to adapting online education in higher education institutions during the COVID-19 outbreak.

     

Fusion of ANNs as decoder of retinal spike trains for scene reconstruction

Applied Intelligence - The retina is one of the most developed sensing organs in the human body. However, the knowledge on the coding and decoding of the retinal neurons are still rather limited....