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Transition in interfacial failure mechanism of resistance spot welds during tensile–shear loading: role of fusion zone hardness
, Article Metals ; Volume 13, Issue 6 , 2023 ; 20754701 (ISSN) ; Pouranvari, M ; Sharif University of Technology
MDPI
2023
Abstract
The failure of resistance spot welds through the fusion zone along the sheet/sheet interface (i.e., interfacial failure) is critical for automotive crashworthiness. This paper investigates the effect of fusion zone hardness on the interfacial failure behavior of resistance spot welds during the tensile–shear test. AISI 1040 medium carbon steel, producing a high level of hardness mismatch during resistance spot welding, was selected as the base metal. By ex situ tempering heat treatment, various levels of fusion zone hardness are achieved in the welds with constant fusion zone size. It is shown that the interfacial failure of the spot welds is a competition between ductile shear failure and...
Failure of Automotive Steels Resistance Spot Welds under Mode I
, M.Sc. Thesis Sharif University of Technology ; Pouranvari, Majid (Supervisor)
Abstract
Automotive steels are dominant material for the manufacturing of automotive structures and components. Since an automotive body is mostly assembled by spot welding, spot weld failure in different loading conditions has a great influence on the crashworthiness of vehicle. Therefore, investigation of microstructure and failure behavior of resistance spot welded automotive steels is an important issue. The first part of the research is dedicated to microstructural evolution and fusion zone hardness of spot welded automotive steels based on optical and SEM micrographs and hardness measurements. In the FZ of automotive steels, except for austenitic steels, a mainly martensitic microstructure was...
Resistance spot welding of quenching and partitioning (Q&P) third-generation advanced high-strength steel: process–microstructure–performance
, Article Metallurgical and Materials Transactions A: Physical Metallurgy and Materials Science ; Volume 54, Issue 2 , 2023 , Pages 577-589 ; 10735623 (ISSN) ; Yadegari, R ; Pouranvari, M ; Sharif University of Technology
Springer
2023
Abstract
This paper investigates process–microstructure–performance relationships in Q&P980 third-generation advanced high-strength steel (AHSS) resistance spot welds. The hardening and softening phenomena during welding are discussed in terms of weldment microstructure. The fusion zone (FZ) microstructure was mainly lath martensite with an average hardness of 500 HV due to the high cooling rate resulting from resistance spot welding. No significant softening was observed in the sub-critical heat-affected zone which was related mainly to the presence of the low volume fraction of fresh martensite in the initial microstructure of the base metal. The factors controlling the tensile–shear peak load,...
Optimizing a Flowshop Model with the Objective of Minimizing Total Weighted Tardiness while Considering due Dates on All Machines
, M.Sc. Thesis Sharif University of Technology ; Ghassemi Tari, Farhad (Supervisor)
Abstract
Minimizing completion time of tasks in a flowshops has always attracted attention of researchers since it was introduced by Johnson, 1954. If all jobs are processed in the same order, the sequence is called a permutation sequence. Tardiness factor is one of important factors in permutation flowshop sequencing problem. Minimizing this factor brings about increase in service level of the shop and is helpful in meeting customer’s needs. Since, minimizing tardiness in PFSP in among NP-hard problems, computational efforts in this area has focused on heuristic approaches. However, the researches has always considered due dates only on the last machine. It means, always it has been assumed that due...
Understanding fusion zone hardness in resistance spot welds for advanced high strength steels: strengthening mechanisms and data-driven modeling
, Article Journal of Materials Research and Technology ; Volume 26 , 2023 , Pages 5549-5565 ; 22387854 (ISSN) ; Pouranvari, M ; Ansari, R ; Pouranvari, M ; Sharif University of Technology
Elsevier Editora Ltda
2023
Abstract
The fusion zone (FZ) hardness of resistance spot welds is a crucial factor affecting the performance and durability of the welds. Failure mode transition, tendency to fail in interfacial mode, interfacial failure load, and the impact of liquid metal embrittlement cracks on the weld strength are influenced by the FZ hardness. Therefore, accurately predicting the FZ hardness in resistance spot welds made on automotive steels is essential. A simple thermal model is used to calculate the time required for the temperature to drop from 800 °C to 500 °C (Δt[Formula presented]). With the aid of continuous cooling transformation (CCT) diagrams and experimental confirmation, it is shown that in most...
Interpretation of Hyperspectral Images Using Integrated Gradients to Detect Bruising in Lemons
, Article Horticulturae ; Volume 9, Issue 7 , 2023 ; 23117524 (ISSN) ; Sabzi, S ; Nadimi, M ; Paliwal, J ; Sharif University of Technology
Multidisciplinary Digital Publishing Institute (MDPI)
2023
Abstract
Lemons are a popular citrus fruit known for their medicinal and nutritional properties. However, fresh lemons are vulnerable to mechanical damage during transportation, with bruising being a common issue. Bruising reduces the fruit’s shelf life and increases the risk of bacterial and fungal contamination, leading to economic losses. Furthermore, discoloration typically occurs after 24 h, so it is crucial to detect bruised fruits promptly. This paper proposes a novel method for detecting bruising in lemons using hyperspectral imaging and integrated gradients. A dataset of hyperspectral images was captured in the wavelength range of 400–1100 nm for lemons that were sound and artificially...
Deep learning for caries detection: A systematic review
, Article Journal of Dentistry ; Volume 122 , 2022 ; 03005712 (ISSN) ; Motamedian, S. R ; Rohban, M. H ; Krois, J ; Uribe, S. E ; Mahmoudinia, E ; Rokhshad, R ; Nadimi, M ; Schwendicke, F ; Sharif University of Technology
Elsevier Ltd
2022
Abstract
Objectives: Detecting caries lesions is challenging for dentists, and deep learning models may help practitioners to increase accuracy and reliability. We aimed to systematically review deep learning studies on caries detection. Data: We selected diagnostic accuracy studies that used deep learning models on dental imagery (including radiographs, photographs, optical coherence tomography images, near-infrared light transillumination images). The latest version of the quality assessment tool for diagnostic accuracy studies (QUADAS-2) tool was used for risk of bias assessment. Meta-analysis was not performed due to heterogeneity in the studies methods and their performance measurements....
Deep learning for the classification of cervical maturation degree and pubertal growth spurts: A pilot study
, Article Korean Journal of Orthodontics ; Volume 52, Issue 2 , 2022 , Pages 112-122 ; 22347518 (ISSN) ; Motamadian, S. R ; Nadimi, M ; Hassanzadeh Samani, S ; Minabi, M. A. S ; Mahmoudinia, E ; Lee, V. Y ; Rohban, M. H ; Sharif University of Technology
Korean Association of Orthodontists
2022
Abstract
Objective: This study aimed to present and evaluate a new deep learning model for determining cervical vertebral maturation (CVM) degree and growth spurts by analyzing lateral cephalometric radiographs. Methods: The study sample included 890 cephalograms. The images were classified into six cervical stages independently by two orthodontists. The images were also categorized into three degrees on the basis of the growth spurt: pre-pubertal, growth spurt, and post-pubertal. Subsequently, the samples were fed to a transfer learning model implemented using the Python programming language and PyTorch library. In the last step, the test set of cephalograms was randomly coded and provided to two...