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Image
Induction welding data fusion models of process data and nondestructive eva...
Available to Purchase
in Nondestructive Testing of Composites (Polymer- and Metal-Matrix Composites)[1]
> Nondestructive Evaluation of Materials
Published: 01 August 2018
Fig. 43 Induction welding data fusion models of process data and nondestructive evaluation measurements
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Published: 01 January 2001
Image
Typical process data traces-time graph of ultrasonic-welding process when u...
Available to PurchasePublished: 01 January 1993
Fig. 13 Typical process data traces-time graph of ultrasonic-welding process when using tie layers at the interface. Source: Ref 40
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Image
Common framework to use process data for online process monitoring in polym...
Available to Purchase
in Online Monitoring and Control of Polymer Additive Manufacturing Processes
> Additive Manufacturing Design and Applications
Published: 30 June 2023
Fig. 10 Common framework to use process data for online process monitoring in polymer additive manufacturing
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Image
Schematic representation of the specimen, data, and modeling process for ge...
Available to PurchasePublished: 01 January 1996
Fig. 16 Schematic representation of the specimen, data, and modeling process for generating fatigue crack growth rate ( da / dN − Δ K ) data. (a) Specimen and loading. (b) Measured data. (c) Rate data. Source: Ref 44
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Typical laboratory-based x-ray computed tomography process flow, from data ...
Available to Purchase
in Surface and Geometrical Characterization and Measurements in Additive Manufacturing
> Additive Manufacturing Design and Applications
Published: 30 June 2023
Fig. 7 Typical laboratory-based x-ray computed tomography process flow, from data acquisition to measurement evaluation
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Data flows for a variety of use cases for in situ process monitoring and co...
Available to Purchase
in In Situ Process Control and Monitoring in Additive Manufacturing—An Overview
> Additive Manufacturing Design and Applications
Published: 30 June 2023
Fig. 2 Data flows for a variety of use cases for in situ process monitoring and control. ML, machine learning; AI, artificial intelligence
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Image
in Failures of Rolling-Element Bearings and Their Prevention
> Analysis and Prevention of Component and Equipment Failures
Published: 30 August 2021
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Real-time process control data from a predominantly hydrocarbon stream with...
Available to Purchase
in Corrosion in Petroleum Refining and Petrochemical Operations
> Corrosion: Environments and Industries
Published: 01 January 2006
Fig. 50 Real-time process control data from a predominantly hydrocarbon stream with 1 to 2 vol% corrosive water. Simultaneous measurement of chemical feed and corrosion monitoring of carbon steel and type 304L and 316L stainless steels. Source: Ref 202
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Book Chapter
Measurement and Interpretation of Flow Stress Data for the Simulation of Metal-Forming Processes
Available to PurchaseSeries: ASM Handbook
Volume: 22B
Publisher: ASM International
Published: 01 November 2010
DOI: 10.31399/asm.hb.v22b.a0005508
EISBN: 978-1-62708-197-9
... in the calculated strain Errors in the load readings, which result in errors in the calculated stress Errors in the processing of the data due to barreling of the test specimens The first and second type of errors may be reduced or eliminated by careful calibration of the transducers and data...
Abstract
This article describes the most commonly used test methods for determining flow stress in metal-forming processes. The methods include tension, ring, uniform compression, plane-strain compression, torsion, split-Hopkinson bar, and indentation tests. The article discusses the effect of deformation heating on flow stress. It provides metallurgical considerations at hot working temperatures and presents flow curves at conventional metalworking strain rates. The article describes the effect of microstructural scale, crystallographic texture, and equiaxed phases on flow stress at hot working temperatures. It tabulates a summary of certain values describing the flow stress-strain rate relation for steels, aluminum alloys, copper alloys, titanium alloys, and other metals at various temperatures.
Book Chapter
Modeling and Simulation of Steel Heat Treatment—Prediction of Microstructure, Distortion, Residual Stresses, and Cracking
Available to PurchaseSeries: ASM Handbook
Volume: 4B
Publisher: ASM International
Published: 30 September 2014
DOI: 10.31399/asm.hb.v04b.a0005950
EISBN: 978-1-62708-166-5
... and discusses reliable data sources as well as experimental and computational methods for material data acquisition. The article provides information on the process data needed for accurate heat treatment simulation and the methods for their determination. Methods for validating heat treatment simulations...
Abstract
This article describes the fundamental concepts of heat treatment simulation, including the physical events and their interactions, the heat treatment simulation software, and the commonly used simulation strategies. It summarizes material data needed for heat treatment simulations and discusses reliable data sources as well as experimental and computational methods for material data acquisition. The article provides information on the process data needed for accurate heat treatment simulation and the methods for their determination. Methods for validating heat treatment simulations are also discussed with an emphasis on the underlying philosophy for the selection and design of validation tests. The article also discusses the applications, capabilities, and limitations of heat treatment simulations via selected industrial case studies for a better understanding of the effect of microstructure, distortion, residual stress, and cracking in gears, shafts, and bearing rings.
Image
Outputs from Minitech Predictor data processing for best fit to measured Jo...
Available to Purchase
in Hardenability Calculation of Carbon and Low-Alloy Steels with Low or Medium Carbon
> Steel Heat Treating Fundamentals and Processes
Published: 01 August 2013
Fig. 10 Outputs from Minitech Predictor data processing for best fit to measured Jominy data. (a) Initial trial. (b) Final trial. Source: Ref 7
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Nonferrous casting processes by tons poured. Source: From data of AFS 2002 ...
Available to PurchasePublished: 01 December 2008
Image
Crack growth data for compact tension specimens from commercially processed...
Available to PurchasePublished: 01 January 1996
Fig. 57 Crack growth data for compact tension specimens from commercially processed (CP) plate and experimental intermediate thermomechanical treatment (ITMT) material in the as-recrystallized (AR) condition and the as-recrystallized plus hot-rolled (AR + HR) condition. The CP 7050 material
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Image
Examples of full matrix capture (FMC) data-processing capabilities. (a) Sta...
Available to PurchasePublished: 01 August 2018
Fig. 32 Examples of full matrix capture (FMC) data-processing capabilities. (a) Standard summation, 40 to 70 SW. (b) FMC, elementary A-scans. (c) Software summation, 40 to 70 SW. (d) Software summation, −10 to 10 LW. Source: Ref 49
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Image
Published: 01 June 2012
Fig. 17 Rotary-bend fatigue data of thermomechanically processed Ni 50.8 Ti 49.2 wires (A f = 10 °C, or 50 °F) tested at −25 °C (−13 °F), room temperature, and 60 °C (140 °F). Fatigue life strongly depends on test temperature, where the 60 °C test data have shorter lives and the −25 °C test
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Nonferrous casting processes by tons poured. Source: From data of American ...
Available to PurchasePublished: 15 June 2019
Fig. 1 Nonferrous casting processes by tons poured. Source: From data of American Foundry Society’s 2002 survey
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Effect of processing parameters on dilution with experimental data plotted ...
Available to PurchasePublished: 01 January 1997
Fig. 3 Effect of processing parameters on dilution with experimental data plotted for SAW process. Source: Ref 18
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Published: 01 January 2006
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Programming system block diagram for an automated tape layer. (1) Manufactu...
Available to PurchasePublished: 01 January 2001
Fig. 10 Programming system block diagram for an automated tape layer. (1) Manufacturing process data include specifications such as tape width, tape thickness, fiber orientation, and gap tolerances. (2) Part geometry consists of numerical descriptions of the contoured surface and boundaries
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