N.S. Reddy
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View article: Modeling the Higher Heating Value of Spanish Biomass via Neural Networks and Analytical Equations
Modeling the Higher Heating Value of Spanish Biomass via Neural Networks and Analytical Equations Open
Accurate estimation of biomass higher heating value (HHV) is crucial for designing efficient bioenergy systems. In this study, we developed a Backpropagation artificial neural network (ANN) that predicts HHV from routine proximate/ultimate…
View article: Machine Learning-Based Prediction of Atmospheric Corrosion Rates Using Environmental and Material Parameters
Machine Learning-Based Prediction of Atmospheric Corrosion Rates Using Environmental and Material Parameters Open
Atmospheric corrosion significantly impacts infrastructure worldwide, with traditional assessment methods being time-intensive and costly. This study developed a comprehensive machine learning framework for predicting atmospheric corrosion…
View article: Mechanistic Behavior of Basicity of Bimetallic Ni/ZrO2 Mixed Oxides for Stable Oxythermal Reforming of CH4 with CO2
Mechanistic Behavior of Basicity of Bimetallic Ni/ZrO2 Mixed Oxides for Stable Oxythermal Reforming of CH4 with CO2 Open
The mixed oxides of Ni/ZrO2, Ni-Ca/ZrO2, Ni-Ba/ZrO2, and Ni-Ba-Ca/ZrO2 were prepared using the co-precipitation method at a pH of precisely 8.3. The catalytic mixed oxides of Ni/ZrO2, Ni-Ca/ZrO2, Ni-Ba/ZrO2, and Ni-Ba-Ca/ZrO2 were characte…
View article: Modeling Mechanical Properties of Industrial C-Mn Cast Steels Using Artificial Neural Networks
Modeling Mechanical Properties of Industrial C-Mn Cast Steels Using Artificial Neural Networks Open
This study develops a comprehensive artificial neural network (ANN) model for predicting the mechanical properties of carbon–manganese cast steel, specifically, the yield strength (YS), tensile strength (TS), elongation (El), and reduction…
View article: Estimation of Several Wood Biomass Calorific Values from Their Proximate Analysis Based on Artificial Neural Networks
Estimation of Several Wood Biomass Calorific Values from Their Proximate Analysis Based on Artificial Neural Networks Open
The accurate estimation of the higher heating value (HHV) of wood biomass is essential to evaluating the latter’s energy potential as a renewable energy material. This study proposes an Artificial Neural Network (ANN) model to predict the …
View article: SLA-Aware Load Balancing In Cloud Computing Using Machine Learning Based Virtual Machine Scheduling
SLA-Aware Load Balancing In Cloud Computing Using Machine Learning Based Virtual Machine Scheduling Open
Cloud computing has become an essential platform for delivering scalable and on-demand services, but it faces significant challenges in managing resource allocation while ensuring adherence to Service Level Agreements (SLAs). This research…
View article: ANN-Based Prediction of Corrosion Behavior of Alloy 600: Implications for an Anti-Corrosion Coating Design in PWSCC Environments
ANN-Based Prediction of Corrosion Behavior of Alloy 600: Implications for an Anti-Corrosion Coating Design in PWSCC Environments Open
The modeling of the corrosion rate of Alloy 600 in primary water stress corrosion cracking conditions (PWSCC) is a challenging task for existing as well as new structures due to the wide deviation of its composition across the worldwide PW…
View article: Mechanical Property Prediction of Industrial Low-Carbon Hot-Rolled Steels Using Artificial Neural Networks
Mechanical Property Prediction of Industrial Low-Carbon Hot-Rolled Steels Using Artificial Neural Networks Open
This study investigated the application of neural network techniques to predict the mechanical properties of low-carbon hot-rolled steel strips using industrial data. A feedforward neural network (FFNN) model was developed to predict the y…
View article: Quantitative and Qualitative Analysis of Atmospheric Effects on Carbon Steel Corrosion Using an ANN Model
Quantitative and Qualitative Analysis of Atmospheric Effects on Carbon Steel Corrosion Using an ANN Model Open
This study develops an artificial neural network (ANN) model to predict the corrosion rate of carbon steel under a wide range of atmospheric conditions. The model incorporates input variables, including temperature (−3.1–28.2 °C), relative…
View article: Under Level Ground Water Predicator
Under Level Ground Water Predicator Open
This research says aboug the quantity of water which present in underground and predicts the future climatic changes and gives precautions.
View article: Artificial Neural Network-Based Modeling of Atmospheric Zinc Corrosion Rates Using Meteorological and Pollutant Data
Artificial Neural Network-Based Modeling of Atmospheric Zinc Corrosion Rates Using Meteorological and Pollutant Data Open
Understanding the depth and severity of corrosion is crucial for predicting the long-term durability and economic viability of Zn-based structures. This study investigates the relationship between meteorological and pollution parameters on…
View article: Evaluating Machine Learning Models for Predicting Hardness of AlCoCrCuFeNi High-Entropy Alloys
Evaluating Machine Learning Models for Predicting Hardness of AlCoCrCuFeNi High-Entropy Alloys Open
This study evaluates the predictive capabilities of various machine learning (ML) algorithms for estimating the hardness of AlCoCrCuFeNi high-entropy alloys (HEAs) based on their compositional variables. Among the ML methods explored, a ba…
View article: Evaluating Machine Learning Models for Predicting Hardness of AlCoCrCuFeNi High-Entropy Alloys
Evaluating Machine Learning Models for Predicting Hardness of AlCoCrCuFeNi High-Entropy Alloys Open
This study evaluates the predictive capabilities of various machine learning (ML) al-gorithms for estimating the hardness of AlCoCrCuFeNi high-entropy alloys (HEAs) based on their compositional variables. Among the ML methods explored, a b…
View article: Multi-layered yolk-shell design containing carbon bridge connection for alloying anodes in lithium-ion batteries
Multi-layered yolk-shell design containing carbon bridge connection for alloying anodes in lithium-ion batteries Open
Designing a material structure that supports high-capacity and long cycle life in silicon (Si) anodes has been a long-standing challenge for advancing lithium-ion batteries. Yolk-shell design has been considered a most promising design for…
View article: Prediction of Creep Rupture Life of 5Cr-0.5Mo Steel Using Machine Learning Models
Prediction of Creep Rupture Life of 5Cr-0.5Mo Steel Using Machine Learning Models Open
The creep rupture life of 5Cr-0.5Mo steels used in high-temperature applications is significantly influenced by factors such as minor alloying elements, hardness, austenite grain size, non-metallic inclusions, service temperature, and appl…
View article: Artificial Neural Network Modeling of Ti-6Al-4V Alloys to Correlate Their Microstructure and Mechanical Properties
Artificial Neural Network Modeling of Ti-6Al-4V Alloys to Correlate Their Microstructure and Mechanical Properties Open
The heat treatment process of Ti-6Al-4V alloy alters its microstructural features such as prior-β grain size, Widmanstatten α lath thickness, Widmanstatten α volume fraction, grain boundary α lath thickness, total α volume fraction, α colo…
View article: Data-Driven ANN-Based Predictive Modeling of Mechanical Properties of 5Cr-0.5Mo Steel: Impact of Composition and Service Temperature
Data-Driven ANN-Based Predictive Modeling of Mechanical Properties of 5Cr-0.5Mo Steel: Impact of Composition and Service Temperature Open
The mechanical properties of steel are intricately connected to their composition and service temperature. Predicting these properties across different work temperatures using traditional statistical methods, algorithms, and equations is h…
View article: Knowledge Discovery in Predicting Martensite Start Temperature of Medium-Carbon Steels by Artificial Neural Networks
Knowledge Discovery in Predicting Martensite Start Temperature of Medium-Carbon Steels by Artificial Neural Networks Open
Martensite start (Ms) temperature is a critical parameter in the production of parts and structural steels and plays a vital role in heat treatment processes to achieve desired properties. However, it is often challenging to estimate accur…
View article: Influence of Alkaline and Sulfate Electrolytes on the Electrochemical Performance of Wo3 Pyramid Anodes with Sno2 Particles Cap
Influence of Alkaline and Sulfate Electrolytes on the Electrochemical Performance of Wo3 Pyramid Anodes with Sno2 Particles Cap Open
View article: Classification of the Crystal Structures of Orthosilicate Cathode Materials for Li-Ion Batteries by Artificial Neural Networks
Classification of the Crystal Structures of Orthosilicate Cathode Materials for Li-Ion Batteries by Artificial Neural Networks Open
The crystal structures of orthosilicate cathode materials play a critical role in determining the physical and chemical properties of Li-ion batteries. Accurate predictions of these crystal structures are essential for estimating key prope…
View article: Machine Learning Modeling of the Mechanical Properties of Al2024-B4C Composites
Machine Learning Modeling of the Mechanical Properties of Al2024-B4C Composites Open
Aluminum-based composites are in high demand in industrial fields due to their light weight, high electrical conductivity, and corrosion resistance. Due to its unique advantages for composite fabrication, powder metallurgy is a crucial pla…
View article: Multi-objective parametric modelling during wire-cut electric discharge machining of Incoloy 800H
Multi-objective parametric modelling during wire-cut electric discharge machining of Incoloy 800H Open
Incoloy 800H exhibits exceptional resistance to corrosion in aqueous environments and demonstrates a strong resistance to chloride stress-corrosion cracking. In this study, a multi-objective parametric optimization technique is used to mod…
View article: Multi-objective parametric modelling during minimum quantity lubrication machining of Incoloy 800H
Multi-objective parametric modelling during minimum quantity lubrication machining of Incoloy 800H Open
This study utilizes multi-objective optimization to minimize surface roughness and maximize material removal rate (MRR) during minimum quantity lubrication (MQL) turning of Incoloy 800H under different cutting conditions. The correlations …
View article: Wire arc additive manufacturing method for Ti–6Al–4V alloy to improve the grain refinement efficiency and mechanical properties
Wire arc additive manufacturing method for Ti–6Al–4V alloy to improve the grain refinement efficiency and mechanical properties Open
Wire and arc additive manufacturing (WAAM) technique has introduced a novel approach for producing complex Ti–6Al–4V parts with metric dimensions. However, the produced part leads to the development of a strong texture and anisotropic mech…
View article: Modeling the Nonlinearities Between Coaching Leadership and Turnover Intention by Artificial Neural Networks
Modeling the Nonlinearities Between Coaching Leadership and Turnover Intention by Artificial Neural Networks Open
This present work uses artificial neural networks (ANNs) to examine the association between various dimensions of coaching leadership and turnover Intention. The coaching leadership data were collected from 194 employees across multiple sc…
View article: Progress of machinability on the machining of Inconel 718: A comprehensive review on the perception of cleaner machining
Progress of machinability on the machining of Inconel 718: A comprehensive review on the perception of cleaner machining Open
Inconel 718 nickel superalloys' superior properties at elevated temperatures necessitate several applications in the aviation, marine, and automotive industries. However, the poor thermal conductivity and rapid strain hardening properties …
View article: Effect of Interdendritic Precipitations on the Mechanical Properties of GBF or EMS Processed Al-Zn-Mg-Cu Alloys
Effect of Interdendritic Precipitations on the Mechanical Properties of GBF or EMS Processed Al-Zn-Mg-Cu Alloys Open
The effects of nanoprecipitations on the mechanical properties of Al-Zn-Mg-Cu alloys after GBF (gas bubbling filtration) and EMS (electromagnetic stirring) casting were investigated. Dendritic cell structures were formed after GBF processi…
View article: Machine learning and statistical approach in modeling and optimization of surface roughness in wire electrical discharge machining
Machine learning and statistical approach in modeling and optimization of surface roughness in wire electrical discharge machining Open
View article: Influence of Direct Energy Deposition Parameters on Ti–6Al–4V Component’s Structure-Property Homogeneity
Influence of Direct Energy Deposition Parameters on Ti–6Al–4V Component’s Structure-Property Homogeneity Open
Ti–6Al–4V alloy is a typical 3D printing metal, and its application has been expanded to various fields owing to its excellent characteristics such as high specific strength, high corrosion resistance, and biocompatibility. In particular, …
View article: Corrigendum to “Quantitative estimation of corrosion rate in 3C steels under seawater environment” [J Mater Res Technol vol. 11 (March–April 2021) 681–686]
Corrigendum to “Quantitative estimation of corrosion rate in 3C steels under seawater environment” [J Mater Res Technol vol. 11 (March–April 2021) 681–686] Open
The authors regret to inform you that there are two corresponding authors for this article (B.B. Panigrahi and N. S. Reddy). Corresponding authors: 1. B.B. Panigrahi, 040-23016555, [email protected] 2. N. S. Reddy, 055-7721669, nsreddy@gnu…