Tip: use quotes for an exact phrase, e.g. "teacher education"
Soft computing techniques, with their self-learning capabilities, fuzzy principles, and evolutionary computational philosophy, are being increasingly utilized in modeling complex machining processes. This study develops artificial neural…
The aim of this study is to analyze the effect of different geometries and sections on the mechanical properties of epoxy specimens. Five tensile tests were carried out on three types of series. The experimental results obtained were…
The dynamic experimental and numerical analysis of cracked beams has been studied with the aim of quantifying the influence of depth crack on the dynamic response of steel beams. Artificial Neural Method ANN has been used where a numerical…
Machining with a cutting edge with extensive damage or a fractured cutting edge significantly influences the machining performance. Therefore, investigations on tool wear behavior, their forms, and wear mechanisms will be very helpful in…
The hot behaviour of micro-alloy steel CMn (Nb-Ti-V) was studied using hot compression tests in a wide range of temperatures (700 to 1050 °C, step 50 °C), deformation rates (0.000794, 0.0029 and 0.01436 s-1) and true deformation rates of 0…
The importance of delamination detection can be understood from aircraft components like Vertical Stabilizer, which is subjected to heavy vibration during the flight movement and it may lead to delamination and finally even flight crash…
This paper discusses the application of machine learning techniques, notably artificial neural networks (ANN), in the fracture analysis of semi-infinite elastic plates with edge cracks. The Stress Intensity Factor (SIF) model for a…
This study focuses on ductile fracture behavior prediction for Ti6Al4V alloys fabricated via Selective Laser Melting (SLM). A modified Gurson-Tvergaard-Needleman (GTN) model characterizes void growth and shear mechanisms under uniaxial…
A new method for computing fracture mechanics parameters using computational Eddy Current Modelling by Multi-layer Perceptron Neural Networks for detecting surface cracks. The method is based upon an inverse problem using an Artificial…
Cracks in clayey soil cause a reduction in the seismic loading capacity which can lead to structural failures. Seismic acceleration is the primary cause of crack propagation and damage to the earth's structure. This study investigated the…
In this paper, the initial and maximum load was studied using the Finite Element Modeling (FEM) analysis during impact testing (CVN) of pipeline X70 steel. The Gurson-Tvergaard-Needleman (GTN) constitutive model has been used to simulate…
The ground external columns of buildings are vulnerable to the extreme actions such as a vehicle collision. This event is a common scenario of buildings' damages. In this study, a nonlinear model of 2-story steel moment-resisting frame (…
Enhancing the machinability of difficult-to-cut materials is imperative, and a non-conventional rotary tool has shown high potential when machining these materials. This work comparatively evaluates the tool wear of conventional round…
Damage assessment in the actual operating process of the structure is a modern and exciting problem of construction engineering due to several practical knowledge about the current condition of the inspected structures. However, the…
Bearings, considered crucial components in rotating machinery, are widely used in the industry. Bearing status monitoring has become an essential step in the deployment of preventive maintenance policy. This work is part of the diagnosis…
Dynamic loading on composite components may induce damages such as cracks, delaminations, etc. and development of an early damage detection technique for delaminations is one of the most important aspects in ensuring the integrity and…
The use of miniaturized specimen testing methods is a promising way to solve the problem of limited materials in RPV monitoring programs. The use of miniature specimens allows the evaluation of fracture toughness from other specimen…
