5 research outputs found
Maintenance Optimization in Process Plant Using Failure mode effect analysis
No full textExperimental investigations are conducted to assess the influence of various equipment in terms of MTBF(Mean time between failures) and MTTR(Mean Time To Repair) in this study. Analysis of these data has helped to find out the critical components in coil and mill Plant at Anjar, Kutch, India. The goal of this work is to analyze the maintenance data and recommend optimized maintenance plan. The genetic algorithm is proposed as a heuristic search method for maintenance optimization in Plate and coil mill plant unit. Genetic algorithm searches for the best solution for the efficiency enhancement of the plant. This paper presents the influence of genetic algorithm in maintenance optimization in Plate and coil mill plant. Failure mode effect analysis is the used methodology in proposed work which is a fundamental piece of the specialized plan of support to enhance framework quality and hence lessens costs related with upkeep that is utilized as a part of a wide range industry
Optimization of solar and battery-based hybrid renewable energy system augmented with bioenergy and hydro energy-based dispatchable source
No full textSummary: The hybrid renewable energy system (HRES) can overcome the problem of the mismatch of supply of variable renewable energies and demand. The optimal sizing of the HRES methodology is implemented by employing the generalized reduced gradient (GRG) method. A case study of HRES with solar, bio, and hydro sources for tribal areas in a hilly region of India is demonstrated. Both the grid-connected scenario and the standalone scenario in island mode are simulated. The optimal LCOE of 0.106–0.053 /kWh for the prospective grid-connected mode cases. The sensitivity analysis and validation of the work are also performed
Disturbance Storm Time forecast using ML methods with observations from sensors on Advanced Composition Explorer
No full textThis study discusses simulations performed to predict the Disturbance Storm Time (DST) index of Solar-wind using the data obtained by sensors on the Advanced Composition Explorer (ACE) satellite of The National Aeronautics and Space Administration (NASA) from 2016. Because of various features present in the dataset, the paper involves the use of a variety of feature selection techniques like correlation matrix, use of ROC-AUC (Area Under the Receiver Operating Characteristic Curve) score, and Random Forest generation to find the effective parameters for the prediction of DST index. It was observed that all the feature selection techniques have different degrees of elimination of the features. The features having high impact were further considered for model preparation. With these features, several machine learning techniques like Multiple linear Regression, Decision Tree, Random Forest, Support Vector Machines (SVM), Artificial Neural Network (ANN), and Long Short-Term Memory (LSTM) were implemented. Results show that SVM outperformed the linear regression model. Although various advanced models have already been created showing different accuracy levels to predict the DST index, it is felt that the field needs more accurate models to predict the intensity of Solar wind using Real-Time Solar Winds
The disorder of things: rethinking social critique in postcolonial Pakistan
No full textOn 8 March 2022, Shebaz Sharif, leader of the Pakistani opposition party, the Pakistan Muslim League (N), tabled a no-confidence motion asking for the removal of Imran Khan as the Prime Minister of Pakistan for being unable to handle the country’s economic crises. This motion was allowed to be tabled by a majority vote that included members of Imran Khan’s own party. As time got closer to the no-confidence vote, Khan attempted to resist the growing opposition on all political fronts. This included rallies where Khan claimed fear of assassination and foreign intervention, and served legal notice to members of his own political party for ‘defection’ under Article 63A of the Constitution of Pakistan. On 3 April, by which time Khan had lost all his political allies, President Arif Alvi announced the dissolution of the National Assembly on Khan’s behest. On the same day, the opposition party challenged the dissolution in the Supreme Court, which ruled all orders for dissolution are subject to the Supreme Court’s consent. The court order enabled the opposition party and its coalition to conduct their own session of the National Assembly on the same day and vote Khan out and vote in the opposition leader, Sharif, as the interim Prime Minister on 3 April 2022. Amid an economic crash on 10 June 2022, the interim government released the financial budget for 2022-2023 while reaching agreement with the International Monetary Fund (IMF) for an extension of the bailout agreement, made previously with Khan’s Government, from USD 6 billion to 8 billion. Soon after, in another political surprise, the by-elections showed a clear win for Khan’s party in the province of Punjab, historically dominated by the Sharif family, raising calls for a general election. On 20 August 2022, a warrant for the arrest of Imran Khan was filed under the Anti-Terrorism Act 1997 for ‘threatening the Police and Judiciary’ at a public rally
Mathematical Modelling of Solar Still and its Comparison Analysis with Experimental Investigation through Parametric Analysis
No full textSolar distillation is very much effective for availing drinkable pot water, especially in desert areas and salt-producing areas. A Solar Still is a device that can be used to convert impure (saline) water into fresh drinking water using the process of Distillation. The energy source used in a Solar Still is sunlight thus it uses renewable energy. This paper describes a set of equations that can be used to find the distillate yield of a solar still by taking input parameters such as Solar Insolation and the basin area. A solar still is used for producing fresh drinking water from impure water and the equations help in estimating the yield. It also determines the efficiency of the solar still
