scholarly journals Langer–Schwartz–Kampmann–Wagner precipitation simulations: assessment of models and materials design application for Cu precipitation in PH stainless steels

2020 ◽  
Vol 56 (3) ◽  
pp. 2650-2671
Author(s):  
Ze Sheng ◽  
Manon Bonvalet Rolland ◽  
Tao Zhou ◽  
Joakim Odqvist ◽  
Peter Hedström
Keyword(s):  
Stainless Steels ◽  
Precipitation Hardening ◽  
Alloy Composition ◽  
State Of The Art ◽  
Material Design ◽  
Materials Design ◽  
Quantitative Agreement ◽  
Experimental Results ◽  
Nucleation Model ◽  
Precipitate Composition

Abstract Quantitative modelling of precipitation kinetics can play an important role in a computational material design framework where, for example, optimization of alloying can become more efficient if it is computationally driven. Precipitation hardening (PH) stainless steels is one example where precipitation strengthening is vital to achieve optimum properties. The Langer–Schwartz–Kampmann–Wagner (LSKW) approach for modelling of precipitation has shown good results for different alloy systems, but the specific models and assumptions applied are critical. In the present work, we thus apply two state-of-the-art LSKW tools to evaluate the different treatments of nucleation and growth. The precipitation modelling is assessed with respect to experimental results for Cu precipitation in PH stainless steels. The LSKW modelling is able to predict the precipitation during ageing in good quantitative agreement with experimental results if the nucleation model allows for nucleation of precipitates with a composition far from the equilibrium and if a composition-dependent interfacial energy is considered. The modelling can also accurately predict trends with respect to alloy composition and ageing temperature found in the experimental data. For materials design purposes, it is though proposed that the modelling is calibrated by measurements of precipitate composition and fraction in key experiments prior to application. Graphic abstract

State of the Art Stainless Steel Provides Improved Properties for Widely Varying Applications

2011 ◽  
Vol 413 ◽  
pp. 341-346 ◽  
Author(s):  
Quan Ming Song ◽  
David Wert
Keyword(s):  
Stainless Steel ◽  
Corrosion Resistance ◽  
Stainless Steels ◽  
High Performance ◽  
Precipitation Hardening ◽  
State Of The Art ◽  
High Strength ◽  
Design Engineers ◽  
Aerospace Alloys ◽  
Industrial Energy

Carpenter Technology Corporation’s Custom 465® stainless steel is a state-of-the-art alloy which has seen its applications expanding at a rapid rate. This alloy is a premium double vacuum melted (VIM/VAR) martensitic precipitation hardening stainless steel that offers an excellent combination of strength, toughness, and corrosion resistance. With its exceptional properties, design engineers have specified the alloy for high-performance components in various industries, such as aerospace, industrial, energy, consumer and medical. The high strength, greater than 250 ksi (1722 MPa) typical, and toughness of the alloy have allowed Custom 465 stainless to be used as a high-strength upgrade to conventional PH stainless steels such as 13-8 and 17-4. The addition of corrosion resistance to the high strength and toughness properties has allowed the alloy to be used as a stainless alternative to non-stainless steels such as AISI 4340 and 300M. This paper will compare mechanical and corrosion resistance properties of Custom 465 stainless steel to those of other PH stainless steels such as 17-4, 15-5, and 13-8, as well as to those of other aerospace alloys such as 300M and AerMet® 100 alloy. In addition, examples of the varied uses of the alloy will be provided, these examples will highlight the benefits obtained by the use of Custom 465 stainless steel over the previous alloys of choice for the applications.

NiAl precipitation in Fe-12w/o Cr-5w/o Ni-4w/o Al

1983 ◽  
Vol 41 ◽  
pp. 202-203
Author(s):  
L.E. Murr ◽  
J.S. Dunning ◽  
S. Shankar
Keyword(s):  
Solid Solution ◽  
Stainless Steel ◽  
Stainless Steels ◽  
Alloy Composition ◽  
Chromium Content ◽  
Scale Up ◽  
Optical Metallography ◽  
Property Evaluation ◽  
310 Stainless Steel ◽  
Microstructural Studies

Aluminum additions to conventional 18Cr-8Ni austenitic stainless steel compositions impart excellent resistance to high sulfur environments. However, problems are typically encountered with aluminum additions above about 1% due to embrittlement caused by aluminum in solid solution and the precipitation of NiAl. Consequently, little use has been made of aluminum alloy additions to stainless steels for use in sulfur or H2S environments in the chemical industry, energy conversion or generation, and mineral processing, for example.A research program at the Albany Research Center has concentrated on the development of a wrought alloy composition with as low a chromium content as possible, with the idea of developing a low-chromium substitute for 310 stainless steel (25Cr-20Ni) which is often used in high-sulfur environments. On the basis of workability and microstructural studies involving optical metallography on 100g button ingots soaked at 700°C and air-cooled, a low-alloy composition Fe-12Cr-5Ni-4Al (in wt %) was selected for scale up and property evaluation.

CRUCIBLE 174 SXR

Alloy Digest ◽  
2009 ◽  
Vol 58 (5) ◽  
Keyword(s):  
Fracture Toughness ◽  
Stainless Steel ◽  
Corrosion Resistance ◽  
Austenitic Stainless Steel ◽  
Stainless Steels ◽  
Precipitation Hardening ◽  
High Strength ◽  
Heat Treating ◽  
Martensitic Stainless Steels ◽  
Excellent Corrosion Resistance

Abstract Crucible 174 SXR is a premium-quality precipitation-hardening stainless steel designed for use as rifle barrels. It is a modification of Crucible’s 17Cr-4Ni that offers substantially improved machinability without sacrificing toughness. Its excellent corrosion resistance approaches that of a 300 series austenitic stainless steel, while its high strength is characteristic of 400 series martensitic stainless steels. At similar hardness levels, Crucible 174 SXR offers greater toughness than either the 410 or 416 stainless steels which are commonly used for rifle barrels. This datasheet provides information on composition, physical properties, hardness, and elasticity as well as fracture toughness. It also includes information on forming and heat treating. Filing Code: SS-1034. Producer or source: Crucible Service Centers.

Browser Security Attacks and Detection Techniques: A Case of Tabnabbing

2020 ◽  
Vol 8 (1) ◽  
pp. 33-41
Author(s):  
Dr. S. Sarika ◽  
Keyword(s):  
Credit Card ◽  
State Of The Art ◽  
Experimental Results ◽  
Detection Technique ◽  
Security Attacks ◽  
Agent Based ◽  
Detection Techniques ◽  
Browser Security ◽  
Cyber Threats ◽  
Multi Agent

Phishing is a malicious and deliberate act of sending counterfeit messages or mimicking a webpage. The goal is either to steal sensitive credentials like login information and credit card details or to install malware on a victim’s machine. Browser-based cyber threats have become one of the biggest concerns in networked architectures. The most prolific form of browser attack is tabnabbing which happens in inactive browser tabs. In a tabnabbing attack, a fake page disguises itself as a genuine page to steal data. This paper presents a multi agent based tabnabbing detection technique. The method detects heuristic changes in a webpage when a tabnabbing attack happens and give a warning to the user. Experimental results show that the method performs better when compared with state of the art tabnabbing detection techniques.

scholarly journals Automatic Detection of Discrimination Actions from Social Images

Electronics ◽  
2021 ◽  
Vol 10 (3) ◽  
pp. 325
Author(s):  
Zhihao Wu ◽  
Baopeng Zhang ◽  
Tianchen Zhou ◽  
Yan Li ◽  
Jianping Fan
Keyword(s):  
Action Recognition ◽  
State Of The Art ◽  
Automatic Detection ◽  
Experimental Results ◽  
Practical Approach ◽  
Detection And Identification ◽  
Art Methods ◽  
Image Set ◽  
Social Images ◽  
Relationship Identification

In this paper, we developed a practical approach for automatic detection of discrimination actions from social images. Firstly, an image set is established, in which various discrimination actions and relations are manually labeled. To the best of our knowledge, this is the first work to create a dataset for discrimination action recognition and relationship identification. Secondly, a practical approach is developed to achieve automatic detection and identification of discrimination actions and relationships from social images. Thirdly, the task of relationship identification is seamlessly integrated with the task of discrimination action recognition into one single network called the Co-operative Visual Translation Embedding++ network (CVTransE++). We also compared our proposed method with numerous state-of-the-art methods, and our experimental results demonstrated that our proposed methods can significantly outperform state-of-the-art approaches.

scholarly journals PyConvU-Net: a lightweight and multiscale network for biomedical image segmentation

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Changyong Li ◽  
Yongxian Fan ◽  
Xiaodong Cai
Keyword(s):  
Image Segmentation ◽  
Deep Learning ◽  
State Of The Art ◽  
Experimental Results ◽  
Actual Situation ◽  
Controlled Experiments ◽  
Biomedical Image ◽  
Segmentation Methods ◽  
Art Performance

Abstract Background With the development of deep learning (DL), more and more methods based on deep learning are proposed and achieve state-of-the-art performance in biomedical image segmentation. However, these methods are usually complex and require the support of powerful computing resources. According to the actual situation, it is impractical that we use huge computing resources in clinical situations. Thus, it is significant to develop accurate DL based biomedical image segmentation methods which depend on resources-constraint computing. Results A lightweight and multiscale network called PyConvU-Net is proposed to potentially work with low-resources computing. Through strictly controlled experiments, PyConvU-Net predictions have a good performance on three biomedical image segmentation tasks with the fewest parameters. Conclusions Our experimental results preliminarily demonstrate the potential of proposed PyConvU-Net in biomedical image segmentation with resources-constraint computing.

scholarly journals Evaluation of recent advances in recommender systems on Arabic content

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Mehdi Srifi ◽  
Ahmed Oussous ◽  
Ayoub Ait Lahcen ◽  
Salma Mouline
Keyword(s):  
Recommender Systems ◽  
High Performance ◽  
Large Scale ◽  
State Of The Art ◽  
Experimental Results ◽  
Recent Advances ◽  
Research Gap ◽  
Text Preprocessing

AbstractVarious recommender systems (RSs) have been developed over recent years, and many of them have concentrated on English content. Thus, the majority of RSs from the literature were compared on English content. However, the research investigations about RSs when using contents in other languages such as Arabic are minimal. The researchers still neglect the field of Arabic RSs. Therefore, we aim through this study to fill this research gap by leveraging the benefit of recent advances in the English RSs field. Our main goal is to investigate recent RSs in an Arabic context. For that, we firstly selected five state-of-the-art RSs devoted originally to English content, and then we empirically evaluated their performance on Arabic content. As a result of this work, we first build four publicly available large-scale Arabic datasets for recommendation purposes. Second, various text preprocessing techniques have been provided for preparing the constructed datasets. Third, our investigation derived well-argued conclusions about the usage of modern RSs in the Arabic context. The experimental results proved that these systems ensure high performance when applied to Arabic content.

scholarly journals Contour Detection for Fibre of Preserved Szechuan Pickle Based on Dilated Convolution

2019 ◽  
Vol 9 (13) ◽  
pp. 2684 ◽  
Author(s):  
Hongyang Li ◽  
Lizhuang Liu ◽  
Zhenqi Han ◽  
Dan Zhao
Keyword(s):  
Edge Detection ◽  
State Of The Art ◽  
Contour Detection ◽  
Experimental Results ◽  
Contour Method ◽  
Class Differences ◽  
Dilated Convolution ◽  
The Mean ◽  
Art Performance

Peeling fibre is an indispensable process in the production of preserved Szechuan pickle, the accuracy of which can significantly influence the quality of the products, and thus the contour method of fibre detection, as a core algorithm of the automatic peeling device, is studied. The fibre contour is a kind of non-salient contour, characterized by big intra-class differences and small inter-class differences, meaning that the feature of the contour is not discriminative. The method called dilated-holistically-nested edge detection (Dilated-HED) is proposed to detect the fibre contour, which is built based on the HED network and dilated convolution. The experimental results for our dataset show that the Pixel Accuracy (PA) is 99.52% and the Mean Intersection over Union (MIoU) is 49.99%, achieving state-of-the-art performance.

scholarly journals Random Forest with Adaptive Local Template for Pedestrian Detection

2015 ◽  
Vol 2015 ◽  
pp. 1-11 ◽  
Author(s):  
Tao Xiang ◽  
Tao Li ◽  
Mao Ye ◽  
Zijian Liu
Keyword(s):  
Computer Vision ◽  
Random Forest ◽  
Classification Accuracy ◽  
Template Matching ◽  
Detection Method ◽  
State Of The Art ◽  
Pedestrian Detection ◽  
Sliding Window ◽  
Experimental Results ◽  
Training Samples

Pedestrian detection with large intraclass variations is still a challenging task in computer vision. In this paper, we propose a novel pedestrian detection method based on Random Forest. Firstly, we generate a few local templates with different sizes and different locations in positive exemplars. Then, the Random Forest is built whose splitting functions are optimized by maximizing class purity of matching the local templates to the training samples, respectively. To improve the classification accuracy, we adopt a boosting-like algorithm to update the weights of the training samples in a layer-wise fashion. During detection, the trained Random Forest will vote the category when a sliding window is input. Our contributions are the splitting functions based on local template matching with adaptive size and location and iteratively weight updating method. We evaluate the proposed method on 2 well-known challenging datasets: TUD pedestrians and INRIA pedestrians. The experimental results demonstrate that our method achieves state-of-the-art or competitive performance.

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