scholarly journals Shielding parameters for cobalt free steel alloys

2021 ◽  
Vol 1171 (1) ◽  
pp. 012010
Author(s):  
M M Mourad ◽  
H A saudi ◽  
M M Eissa ◽  
M Y Hassaan ◽  
M A Abdel-Latif
Keyword(s):  
Steel Alloys

FX-XTRA and FS

Alloy Digest ◽  
1998 ◽  
Vol 47 (2) ◽  
Keyword(s):  
Tensile Properties ◽  
Heat Treating ◽  
Steel Alloys ◽  
Die Steels ◽  
Machine Parts

Abstract Finkl FX-XTRA and FS die steels are clean, tough, and machinable steel alloys used for replacement machine parts. FS is the annealed temper. This datasheet provides information on composition, hardness, and tensile properties. It also includes information on heat treating, machining, and joining. Filing Code: SA-493. Producer or source: A. Finkl & Sons Company.

CARPENTER CHROME CORE 12 and 12-FM ALLOYS

Alloy Digest ◽  
1994 ◽  
Vol 43 (5) ◽  
Keyword(s):  
Corrosion Resistance ◽  
Physical Properties ◽  
Tensile Properties ◽  
Heat Treating ◽  
Steel Alloys ◽  
Iron And Steel ◽  
Magnetic Components

Abstract CARPENTER CHROME CORE 12 AND 12-FM alloys are controlled alloys for use in magnetic components where better corrosion resistance than iron and steel alloys is needed. This datasheet provides information on composition, physical properties, hardness, elasticity, and tensile properties. It also includes information on corrosion resistance as well as heat treating, machining, and joining. Filing Code: SA-474. Producer or source: Carpenter.

scholarly journals FEM and Analytical Modeling of the Incipient Chip Formation for the Generation of Micro-Features

Materials ◽  
2021 ◽  
Vol 14 (14) ◽  
pp. 3789
Author(s):  
Michele Lanzetta ◽  
Marco Picchi Picchi Scardaoni ◽  
Armin Gharibi ◽  
Claudia Vivaldi
Keyword(s):  
Material Properties ◽  
Analytical Modeling ◽  
Cutting Tool ◽  
Sustainable Manufacturing ◽  
Cutting Parameters ◽  
Micro Machining ◽  
Machining Processes ◽  
Steel Alloys ◽  
Diamond Blade ◽  
Micro Features

This paper explores the modeling of incipient cutting by Abaqus, LS-Dyna, and Ansys Finite Element Methods (FEMs), by comparing also experimentally the results on different material classes, including common aluminum and steel alloys and an acetal polymer. The target application is the sustainable manufacturing of gecko adhesives by micromachining a durable mold for injection molding. The challenges posed by the mold shape include undercuts and sharp tips, which can be machined by a special diamond blade, which enters the material, forms a chip, and exits. An analytical model to predict the shape of the incipient chip and of the formed grove as a function of the material properties and of the cutting parameters is provided. The main scientific merit of the current work is to approach theoretically, numerically, and experimentally the very early phase of the cutting tool penetration for new sustainable machining and micro-machining processes.

scholarly journals Study on Molten Salt Corrosion Behavior of Several Stainless Steel Alloys

2021 ◽  
Vol 1885 (3) ◽  
pp. 032005
Author(s):  
Dandan Men ◽  
Jian Xiong ◽  
Wenyi Peng ◽  
Lingyun Bai
Keyword(s):  
Stainless Steel ◽  
Molten Salt ◽  
Corrosion Behavior ◽  
Steel Alloys ◽  
Salt Corrosion

scholarly journals A machine-learning-based alloy design platform that enables both forward and inverse predictions for thermo-mechanically controlled processed (TMCP) steel alloys

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Jin-Woong Lee ◽  
Chaewon Park ◽  
Byung Do Lee ◽  
Joonseo Park ◽  
Nam Hoon Goo ◽  
...  
Keyword(s):  
Machine Learning ◽  
Feature Space ◽  
Research Strategy ◽  
Nsga Ii ◽  
Steel Alloys ◽  
Non Linear ◽  
Data Driven Approach ◽  
Processing Information ◽  
Set Up ◽  
World Industry

AbstractPredicting mechanical properties such as yield strength (YS) and ultimate tensile strength (UTS) is an intricate undertaking in practice, notwithstanding a plethora of well-established theoretical and empirical models. A data-driven approach should be a fundamental exercise when making YS/UTS predictions. For this study, we collected 16 descriptors (attributes) that implicate the compositional and processing information and the corresponding YS/UTS values for 5473 thermo-mechanically controlled processed (TMCP) steel alloys. We set up an integrated machine-learning (ML) platform consisting of 16 ML algorithms to predict the YS/UTS based on the descriptors. The integrated ML platform involved regularization-based linear regression algorithms, ensemble ML algorithms, and some non-linear ML algorithms. Despite the dirty nature of most real-world industry data, we obtained acceptable holdout dataset test results such as R2 > 0.6 and MSE < 0.01 for seven non-linear ML algorithms. The seven fully trained non-linear ML models were used for the ensuing ‘inverse design (prediction)’ based on an elitist-reinforced, non-dominated sorting genetic algorithm (NSGA-II). The NSGA-II enabled us to predict solutions that exhibit desirable YS/UTS values for each ML algorithm. In addition, the NSGA-II-driven solutions in the 16-dimensional input feature space were visualized using holographic research strategy (HRS) in order to systematically compare and analyze the inverse-predicted solutions for each ML algorithm.

Development of L12-ordered Ni3(Al,Ti)-strengthened alumina-forming austenitic stainless steel alloys

2013 ◽  
Vol 69 (11-12) ◽  
pp. 816-819 ◽  
Author(s):  
Yukinori Yamamoto ◽  
Govindarajan Muralidharan ◽  
Michael P. Brady
Keyword(s):  
Stainless Steel ◽  
Austenitic Stainless Steel ◽  
Steel Alloys

scholarly journals Development of Creep-Resistant, Alumina-Forming Ferrous Alloys for High-Temperature Structural Use

2018 ◽  
Author(s):  
Y. Yamamoto ◽  
M. P. Brady ◽  
G. Muralidharan ◽  
B. A. Pint ◽  
P. J. Maziasz ◽  
...  
Keyword(s):  
High Temperature ◽  
Elevated Temperatures ◽  
Extreme Environments ◽  
Alloy Design ◽  
Austenitic Steels ◽  
Strength Development ◽  
Second Phase ◽  
Ferrous Alloys ◽  
Steel Alloys ◽  
Structural Applications

This paper overviews recent advances in developing novel alloy design concepts of creep-resistant, alumina-forming Fe-base alloys, including both ferritic and austenitic steels, for high-temperature structural applications in fossil-fired power generation systems. Protective, external alumina-scales offer improved oxidation resistance compared to chromia-scales in steam-containing environments at elevated temperatures. Alloy design utilizes computational thermodynamic tools with compositional guidelines based on experimental results accumulated in the last decade, along with design and control of the second-phase precipitates to maximize high-temperature strengths. The alloys developed to date, including ferritic (Fe-Cr-Al-Nb-W base) and austenitic (Fe-Cr-Ni-Al-Nb base) alloys, successfully incorporated the balanced properties of steam/water vapor-oxidation and/or ash-corrosion resistance and improved creep strength. Development of cast alumina-forming austenitic (AFA) stainless steel alloys is also in progress with successful improvement of higher temperature capability targeting up to ∼1100°C. Current alloy design approach and developmental efforts with guidance of computational tools were found to be beneficial for further development of the new heat resistant steel alloys for various extreme environments.

Development of a Model for Experimental Data Treatment of Diffusion and Activation Limited Polarization Curves for Magnesium and Steel Alloys

2017 ◽  
Vol 164 (11) ◽  
pp. E3576-E3582 ◽  
Author(s):  
L. I. Stephens ◽  
S. C. Perry ◽  
S. M. Gateman ◽  
R. Lacasse ◽  
R. Schulz ◽  
...  
Keyword(s):  
Experimental Data ◽  
Polarization Curves ◽  
Steel Alloys ◽  
Data Treatment

scholarly journals Imaging Hydrogen in Stainless Steel Alloys by Kelvin Probe Force Microscopy

2018 ◽  
Author(s):  
J. D. McNamara ◽  
A. J. Duncan ◽  
M. J. Morgan ◽  
P. S. Korinko
Keyword(s):  
Stainless Steel ◽  
Grain Boundaries ◽  
Contact Potential Difference ◽  
Kelvin Probe Force Microscopy ◽  
Grain Structure ◽  
Kelvin Probe ◽  
Contact Potential ◽  
Steel Alloys ◽  
Force Microscopy ◽  
Net Shaping

Kelvin probe force microscopy (KPFM) was used to image austenitic stainless steel (SS) samples (Type 304L) fabricated by the laser engineered net shaping (LENS®) process. The samples were hydrogen charged (H-charged) and subsequently cut and polished. The surface contact potential difference (CPD) of the samples was measured using the KPFM technique, a form of atomic force microscopy. A set of uncharged samples was also studied for reference and changes in the CPD were on the noise level. For H-charged samples fabricated by the LENS® process, the resulting surface potential images show a change in CPD of about 10 – 20mV around cell-like boundaries (5–10 μm in size) and grain boundaries (50–100 μm in size). The significant change in the CPD is affected by variation of the local work function, which indicates the presence of hydrogen. The elemental composition of the LENS® samples was studied using energy dispersive spectroscopy (EDS) which showed an increase in the atomic percentage of Cr and a decrease in Ni around the cell-like boundaries. The existence of intercellular ferrite on the sub-grain boundaries may explain the propensity of hydrogen to segregate around these regions. The finer grain structure of LENS® samples compared to that of forged or welded samples suggests that the hydrogen can be dispersed differently throughout this material than in traditionally forged austenitic SS. This study is conducted to elucidate the behavior of hydrogen with respect to the microstructure of additively manufactured stainless steel alloys.

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