Development of a quantitative health index and diagnostic method for efficient asset management of power transformers

Power transformers play a very important role in electrical power networks and are frequently operated longer than their expected design life. Therefore, to ensure their best operating performance in a transmission network, the fault condition of each transformer must be assessed regularly. For an accurate fault diagnosis, it is important to have maximum information about an individual transformer based on unbiased measurements. This can best be achieved using artificial intelligence (AI) that can systematically analyse the complex features of diagnostic measurements. Clustering techniques are a form of AI that is particularly well suited to fault diagnosis. To provide an assessment of transformers, a hybrid k-means algorithm, and probabilistic Parzen window estimation are used in this research. The clusters they form are representative of a single or multiple fault categories. The proposed technique computes the maximum probability of transformers in each cluster to determine their fault categories. The main focus of this research is to determine a quantitative health index (HI) to characterize the operating condition of transformers. Condition assessment tries to detect incipient faults before they become too serious, which requires a sensitive and quantified approach. Therefore, the HI needs to come from a proportionate system that can estimate health condition of transformers over time. To quantify this condition, the General Regression Neural Network (GRNN), a type of AI, has been chosen in this research. The GRNN works well with small sets of training data and avoids the needs to estimate large sets of model parameters, following a largely non-parametric approach. The methodology used here regards transformers as a collection of subsystems and summarizes their individual condition into a quantified HI based on the existing agreed benchmarks drawn from IEEE and CIGRE standards. To better calibrate the HI, it may be mapped to a failure probability estimate for each transformer over the coming year. Experimental results of the research show that the proposed methods are more effective than previously published approaches when diagnosing critical faults. Moreover, this novel HI approach can provide a comprehensive assessment of transformers based on the actual condition of their individual subsystems

Development of a quantitative health index and diagnostic method for efficient asset management of power transformers

Power transformers play a very important role in electrical power networks and are frequently operated longer than their expected design life. Therefore, to ensure their best operating performance in a transmission network, the fault condition of each transformer must be assessed regularly. For an accurate fault diagnosis, it is important to have maximum information about an individual transformer based on unbiased measurements. This can best be achieved using artificial intelligence (AI) that can systematically analyse the complex features of diagnostic measurements. Clustering techniques are a form of AI that is particularly well suited to fault diagnosis. To provide an assessment of transformers, a hybrid k-means algorithm, and probabilistic Parzen window estimation are used in this research. The clusters they form are representative of a single or multiple fault categories. The proposed technique computes the maximum probability of transformers in each cluster to determine their fault categories. The main focus of this research is to determine a quantitative health index (HI) to characterize the operating condition of transformers. Condition assessment tries to detect incipient faults before they become too serious, which requires a sensitive and quantified approach. Therefore, the HI needs to come from a proportionate system that can estimate health condition of transformers over time. To quantify this condition, the General Regression Neural Network (GRNN), a type of AI, has been chosen in this research. The GRNN works well with small sets of training data and avoids the needs to estimate large sets of model parameters, following a largely non-parametric approach. The methodology used here regards transformers as a collection of subsystems and summarizes their individual condition into a quantified HI based on the existing agreed benchmarks drawn from IEEE and CIGRE standards. To better calibrate the HI, it may be mapped to a failure probability estimate for each transformer over the coming year. Experimental results of the research show that the proposed methods are more effective than previously published approaches when diagnosing critical faults. Moreover, this novel HI approach can provide a comprehensive assessment of transformers based on the actual condition of their individual subsystems

Superhalogen-Based Li-Rich Anti-Perovskite Superionic Conductors

Solid-state batteries are being widely explored to meet next-generation energy storage demand with a great potentiality of achieving high energy and power densities at All-solidstate Lithium-ion batteries (LIBs). In recent years, electronically inverted lithium-rich antiperovskite (LiRAP) solid electrolytes with the formula Li3OX, where X is a halogen or mixture of halogens have appeared as a prospective alternative of the commercially available flammable and corrosive organic liquid electrolytes because of their high ionic conductivity, structural variety, and wide electrochemical window. Here, For the first time, we have successfully formulated and synthesized a completely new class of super halogen based double anti-perovskite named Li6OS(BH4)2 using thin film methodology. As the earliest step, using density functional theory (DFT), the formation energy approach has been employed to determine the thermodynamically stability of Li6OS(BH4)2. The objective of this research is to find stable solid electrolyte that would be compatible for new lithium-ion battery. Experimental characterization supported the theoretical prediction that super halogen substitution of X (X= Cl, Br etc.) leads to stabilization of the double anti-perovskite structure with a low activation barrier for Li+ diffusion

Sustainable business development and its challenges : a study on Scandic hotels

This study analyses the housekeeping service performance of two Scandic hotels and perceptions of the hotel guests about the towel re-use and food waste issues, which make both environmental and business sense. The cleaning service in the hotel rooms is analyzed by the direct observation of 50 hotel rooms contributing to guests’ satisfaction. The present study has followed qualitative research approach to perceive the service gaps of the housekeeping employees and perceived gaps of the guests as to sustainability concerned with the towel re-use and food waste issues. Notably, the study presents that hotels face the challenges of offering standard and constant housekeeping service. Furthermore, factors contributing to guests’ satisfaction on the cleaning service were tested using the Wilcoxon test. In addition, guests’ perceptions regarding the cleaning service and food waste were tested. The relevant data were collected through the questionnaire survey, observation and interview methods. The complete sample data in the questionnaire consist of 132 observations, 130 were used in the analysis. The results of the study view that satisfaction of the guests on the cleaning service differed due to the service gaps of the housekeeping personnel. Additionally, perceived gaps of the guests and their demographics made a variation on their satisfaction. Besides, the study identified guests’ satisfaction as an important factor for the hotel sustainability. Moreover, towel re-use is an important issue since the guests perceive the economic aspect along with its environmental effect. Although hotels use small plates and communication message to reduce food waste, the guests wasted food due to the poor food taste. Habitual facts of the guests were also the causes of the food waste. Food waste and towel re-use are the concerns for the hotels. However, the hotel guests perceived these two issues differently. They perceived the impact of towel re-use on the environment more important than food waste. Increasing guests’ attention as to the towel re-use and food waste issues seems to be a challenge

Industry-Level Disparities in Antitrust Enforcement

Purpose- The purpose of this study is to analyze whether an increase in the concentration of industry causes an increase in the level of the Department of Justice Antitrust Division (DoJ)’s antitrust enforcement within that industry. Design/Methodology- The study employed secondary data and quantitative research method was also utilized to achieve the objectives of the study. Multiple regression analysis techniques were used to analyze the data. Findings- The results support the hypothesis that an increase in the concentration of industry causes an increase in the level of Department of Justice Antitrust Division (DoJ)’s antitrust enforcement within that industry. It appears that industry-level revenue from exports is highly correlated with the size of that industry and its lobbying activity. Practical Implications- These results have practical relevance which helps to predict the intensity of antitrust activity in future years. Its practical implication is that there are disparities in antitrust enforcement that are influenced by factors other than concentration. By creating a benchmark that takes into account components such as this, the Department of Justice Antitrust Division (DoJ) can identify those companies who are likely to be engaging in anticompetitive behavior

Weed competitiveness of winter rice (Oryza sativa L.) under modified aerobic system

The study was conducted during winter season (February-June) of 2016 at the Agronomy Field Laboratory, Bangladesh Agricultural University, Mymensingh. Fourteen rice varieties namely, BRRI dhan28,  BRRI dhan29, BRRI dhan47, BRRI dhan50, BRRI dhan55, BRRI dhan58, BRRI dhan59, BRRI dhan67, Binadhan-5, Binadhan-6, Binadhan-8, Binadhan-10, BRRI hybriddhan3 and Agrodhan14 were grown under weedy and weed- free conditions. Plots with no rice were also maintained to study the natural growth of weed in absence of rice. Primed rice seeds were dry seeded following 25 cm ×15 cm spacing with 5 seeds hill-1 on non-puddled soil. Plots were surface irrigated as and when necessary to maintain aerobic condition (at around field capacity) up to heading stage followed by wet condition from heading to grain filling stage. The results revealed that rice varieties varied widely in yield performance and weed suppressive ability. Among varieties, BRRI dhan59 allowed the minimum weed growth (20.8 g m-2) while Binadhan-5 allowed the maximum weed growth (65.8 g m-2). Grain yield ranged from 2.2 t ha-1 (BRRI dhan55) to 4.67 t ha-1 (Binadhan-5) under weed-free condition and from 0.62 t ha-1 (BRRI dhan55) to 2.48 t ha-1 (BRRI dhan59) under weedy condition. Weed infected relative yield loss ranged from 40.1% to 78.2% among varieties. BRRI dhan59 incurred the least yield penalty (40.1%) while Binadhan-5 performed the best in terms of grain yield (4.67 t ha-1) but its weed inflicted relative yield loss was higher (76.4%) than any other variety with low yield potential. BRRI dhan59, on the other hand, appeared as the most weed competitive variety (only 40.1% relative yield loss) with yield of 4.19 t ha-1. Present study confirms that the varieties tested under study varied widely in terms of weed suppressive ability and yield performance. Considering both yield and weed competitiveness, BRRI dhan59 can be recommended for cultivation following modified aerobic system

Weed suppressive ability of BRRI released popular monsoon rice varieties

Develoment of weed competitive crop cultivars is an attractive low-cost strategy of integrated weed management program that can reduce the heavy dependence of crop cultivation to chemical herbicides. Hence, to evaluate the weed competitiveness Bangladesh Rice Research Institute (BRRI) released selected monsoon rice varieties, a field experiment was conducted during July to December 2018 at the Agronomy Field Laboratory of Bangladesh Agricultural University. Thirty-three rice varieties were grown under season long weedy and weed-free conditions. Plots without rice plants were also maintained to investigate the natural growth of weed in absence of rice. The experiment was conducted following randomized complete block design with three replicates. The results showed that rice varieties varied widely in yielding ability and weed competitiveness. Among rice varieties, BRRI dhan31 allowed the minimum weed growth (32.5 g m-2) while BRRI dhan51 allowed the maximum weed growth (155.3 g m-2). Grain yield ranged between 3.6 t ha-1 (BRRI dhan49) and 7.5 t ha-1 (BR10) under weed-free condition and between 2.2 t ha-1 (BRRI dhan70) and 3.9 t ha-1 (BRRI dhan34) under weedy condition. Weed imposed relative yield loss ranged from 10.2 to 66.9% among the rice varieties. BRRI dhan34 allowed the least yield penalty (10.2%) while BRRI dhan70 had the maximum yield penalty (66.9%) due to competition with weeds. Although BR10 appear as the most productive variety (7.5 t ha-1) its weed imposed relative yield loss was higher (51.3%) than many other varieties with low yield potential. On the other hand, BRRI dhan34 appeared as the most weed competitive variety (only 10.2% relative yield loss) with productivity of 3.9 t ha-1. Considering the yield, BR10 was the best but for weed suppressive ability BRRI dhan34 performed well

Effectiveness of integrated weed management in five varieties of aromatic rice in Bangladesh

An experiment was carried out at the Agronomy Field Laboratory, Bangladesh Agricultural University, Mymensingh, Bangladesh to evaluate the efficacy, rice selectivity and cost-effectiveness of some integrated weed control methods on the productivity of aromatic rice under randomized complete block design with three replications. The experiment consisted of five aromatic rice varieties; Kalijira, BRRI dhan34, BRRI dhan37, BRRI dhan38 and Binadhan-13, and six different weed management practices comprising no weeding, weed free, mechanical + manual weeding, pre–emergence herbicide + manual weeding, post–emergence herbicide + manual weeding, pre– + post–emergence herbicide. Ten weed species belonging to five families infested the experimental plots. Herbicide treatments provided excellent weed control efficiency and produced much higher net benefit and cost benefit ratio than weedy plot. Among the herbicidal and mechanical treatments, sequential application of Bensulfuran methyl + Acetachlor at early growth stage (pre-emergence herbicide) followed by Pyrazosulfuran ethyl at mid growth stage (post-emergence herbicide) provided the highest weed control efficiency, productivity and net benefit. Single application of Pyrazosulfuran ethyl at mid growth stage followed by one hand weeding performed very close to the pre– + post–emergence herbicide application in terms of productivity and net benefit but in terms of weed control efficiency at 45 days after transplanting application of Bensulfuran methyl + Acetachlor at early growth stage followed by one hand weeding performed very close to pre– + post–emergence herbicide application. Mechanical weeding followed by one hand weeding and application of Bensulfuran methyl + Acetachlor at early growth stage followed by one hand weeding also provided satisfactory results in terms of productivity and economic return. Since manual weeding was less economic, sequential application of pre- and post-emergence herbicides may be recommended for effective weed management in aromatic rice

Sustainable Generation of Ni(OH)2 Nanoparticles for the Green Synthesis of 5-Substituted 1 H-Tetrazoles:A Competent Turn on Fluorescence Sensing of H2O2

A mutually correlated green protocol has been devised that originates from a sustainable production of β-Ni(OH)2 nanoparticles which is used for an efficient catalytic synthesis of versatile substituted tetrazoles, under mild reaction conditions in water via a simple, one-pot, eco-friendly method. The synthesis is followed by derivatization into a highly fluorescence active compound 9-(4-(5-(quinolin-2-yl)-1H-tetrazol-1-yl)phenyl)-9H-carbazole that can be used at tracer concentrations (0.1 μM) to detect as well as quantify hydrogen peroxide down to 2 μM concentration. The nanocatalyst was synthesized by a simple, proficient, and cost-effective methodology and characterized thoroughly by UV-vis absorption and Fourier transform infrared spectra, N2 adsorption/desorption, high resolution transmission electron microscopy, powder X-ray diffraction pattern, field emission scanning electron microscopy, and thermogravimetric analysis. Broad substrate scope, easy handling, higher efficiency, low cost, and reusability of the catalyst are some of the important features of this heterogeneous catalytic system. The strong analytical performance of the resultant derivative in low-level quantification of potentially hazardous hydrogen peroxide is the key success of the overall green synthesis procedure reported here

Identifying the Amount of Heat Flux and Thermal Conduction through Fabrics with Appropriate Heat Equation

Heat equations such as heat flux and thermal conduction were applied in this paper so that these values were obtained during heat setting. Cotton spandex woven fabrics have the properties of stretch ability like stretch, growth, elasticity etc. Due to controlling such types of properties heat setting is mandatory. The values of heat flux and thermal conduction would be beneficial to heat application the fabrics more accurately. A heavy weight stretched woven fabric of twill weave was used in this research. The width of the fabric was 60 inch and had a thickness of 2.5 millimeter. Fabric was heated in a stenter machine with adjusted industrial settings. Heat flux values and thermal conduction values of the clothes were investigated using equations stated in this paper. Overheat can damage the fabrics drastically and all the comfort properties are also influenced seriously. Using heat flux equation and thermal conduction equation, fabrics are heated preciously and all these things are practically analyzed, examined and investigated in this research. This research is trial based and the findings are useful to the employees functioning in textile factories who are in duty of heat setting the cotton spandex woven fabrics and to controlling of their all comfort characteristics