Effect of process parameters on friction stir welded joints between dissimilar aluminum alloys: A review

G Di Bella, F Favaloro, C Borsellino - Metals, 2023 - mdpi.com
Friction Stir Welding is a suitable solid-state joining technology to connect dissimilar
materials. To produce an effective joint, a phase of optimization is required which leads to …

Role of expert systems to optimize the friction stir welding process parameters using numerical modelling: a review

H Singh, A Mehta, Y Sharma, H Vasudev - International Journal on …, 2023 - Springer
The friction stir welding (FSW) process allow manufacturers the flexibility to use the process
in a wide variety of materials in different application areas. It has been discovered that the …

[PDF][PDF] A novel TOPSIS linear programming model based on response surface methodology for determining optimal mixture proportions of lightweight concrete blocks …

P To-On, N Wichapa, W Khanthirat - Heliyon, 2023 - cell.com
The idea of utilizing waste from the agro-industrial sector to produce lightweight concrete is
one of the good ideas for recycling and reusing waste materials. In a lightweight concrete …

[PDF][PDF] An investigation on optimizing the carbonation resistance of coal bottom ash concrete with its carbon footprints and eco-costs

N Ankur, N Singh - Research on Engineering Structures and Materials, 2023 - jresm.org
The durability and sustainability assessment of concrete are key aspects in the production of
concrete as it is the most consumed building material around the world. The majority of the …

A Multiple Response Prediction Model for Dissimilar AA-5083 and AA-6061 Friction Stir Welding Using a Combination of AMIS and Machine Learning

R Kraiklang, C Chueadee, G Jirasirilerd, W Sirirak… - Computation, 2023 - mdpi.com
This study presents a methodology that combines artificial multiple intelligence systems
(AMISs) and machine learning to forecast the ultimate tensile strength (UTS), maximum …

[HTML][HTML] A Predictive Model for Weld Properties in AA-7075-FSW: A Heterogeneous AMIS-Ensemble Machine Learning Approach

S Matitopanum, P Luesak, S Chiaranai… - Intelligent Systems with …, 2023 - Elsevier
This study addresses the research gap in materials science by developing an integrated
predictive model for Ultimate Tensile Strength (UTS), Maximum Hardness (MH), and Heat …

Feature Selection by Binary Differential Evolution for Predicting the Energy Production of a Wind Plant

S Al-Dahidi, P Baraldi, M Fresc, E Zio, L Montelatici - Energies, 2024 - mdpi.com
We propose a method for selecting the optimal set of weather features for wind energy
prediction. This problem is tackled by developing a wrapper approach that employs binary …

Plant production yield optimization and cost-effectiveness using an innovative artificial multiple intelligence system

K Sriprateep, S Sala-Ngam, Y Srithep… - Annals of Operations …, 2024 - Springer
The endeavor to augment the productivity of agricultural commodities is fundamentally
contingent upon the establishment of optimal cultivation conditions, particularly in the realm …

Optimization of process parameters for improved surface characteristics in friction stir processed AA6061-ZrO2-GNP surface composite

M Avadi Ammal, J Sudha - Advances in Materials and Processing …, 2024 - Taylor & Francis
Zirconium dioxide, also referred to as zirconia, is a metal oxide that has become popular in
the ceramic sector. It can be used to successfully reinforce aluminium alloys so that their …

Microstructure and Hardness Analysis of Aluminum Alloy Gradient Plate Prepared by Friction Stirring After Heat Treatment

WW Song, JF Pu, D Jiang, XL Ge, Q Dong… - Strength of Materials, 2023 - Springer
A friction stir joining technology was used in preparing a performance gradient aluminum
alloy sheet through friction stirring. The sheet was treated by solution aging, and the …