Rotating-Beam Reversed-Bending Fatigue Curves

2004 ◽  
pp. 253-291
Keyword(s):  
Fatigue Tests ◽  
Rotating Beam ◽  
Aluminum Casting ◽  
Data Set ◽  
Bending Fatigue ◽  
Casting Alloys ◽  
Wide Range

Abstract This data set contains the results of rotating-beam reversed-bending fatigue tests for a wide range of aluminum casting alloys. These fatigue curves are the results of tests on individual lots of material considered representative of the respective alloys and tempers.

Creep Rupture Properties

2004 ◽  
pp. 243-252
Keyword(s):  
Room Temperature ◽  
Creep Rupture ◽  
Aluminum Casting ◽  
Data Set ◽  
Raw Data ◽  
Casting Alloys ◽  
Uniaxial Creep ◽  
Wide Range ◽  
Rupture Properties

Abstract This data set contains the results of uniaxial creep rupture tests for a wide range of aluminum casting alloys conducted at temperatures from 100 to 315 deg C. In most cases, tests were made of several lots of material of each alloy and temper, the results were analyzed, and the averages were normalized to the room-temperature typical values. For some alloys, "representative" values (raw data) rather than typical values are provided.

Growth Curves

2004 ◽  
pp. 175-192
Keyword(s):  
Growth Curves ◽  
Aluminum Casting ◽  
Data Set ◽  
Dimensional Changes ◽  
Casting Alloys ◽  
Aging Response ◽  
Wide Range ◽  
Hardness Values

Abstract This data set contains approximately 50 growth curves for a wide range of aluminum casting alloys at various temperatures. Growth curves are used to determine the dimensional changes that must be anticipated during service in applications where close dimensional tolerances are required. Hardness curves are provided for many of the alloys. The hardness values are from corresponding aging response studies in which measurements were made on individual lots considered representative of the respective alloys and tempers.

Aging Response Curves

2004 ◽  
pp. 133-173
Keyword(s):  
Tensile Strength ◽  
High Temperature ◽  
Ultimate Tensile Strength ◽  
Yield Strength ◽  
Casting Alloy ◽  
Response Curves ◽  
Data Set ◽  
Casting Alloys ◽  
Aging Response ◽  
Wide Range

Abstract This data set presents aging response curves for a wide range of aluminum casting alloys. The aging response curves are of two types: room-temperature, or "natural," curves and artificial, or "high-temperature," curves. The curves in each group are presented in the numeric sequence of the casting alloy designation. The curves included are the results of measurements on individual lots considered representative of the respective alloys and tempers. The properties considered are yield strength, ultimate tensile strength, elongation, and Brinell hardness.

Tensile Properties at High and Low Temperatures and at Room Temperature after High-Temperature Exposure

2004 ◽  
pp. 211-242
Keyword(s):  
High Temperatures ◽  
Room Temperature ◽  
Tensile Tests ◽  
Uniaxial Tensile ◽  
Data Set ◽  
Casting Alloys ◽  
Subzero Temperatures ◽  
Wide Range ◽  
Temperature Exposure ◽  
High And Low Temperatures

Abstract This data set contains the results of uniaxial tensile tests of a wide range of aluminum casting alloys conducted at high temperatures from 100 to 370 deg C, subzero temperatures from -269 to -28 deg C, and room temperature after holding at high temperatures from 100 to 370 deg C. In most cases, tests were made of several lots of material of each alloy and temper. The results for the several lots were then analyzed together graphically and statistically, and the averages were normalized to the room-temperature typical values. For some alloys, "representative" values (raw data) rather than typical values are provided.

Enhancement of Fatigue Life in St37 Steels by Carburizing Process

2021 ◽  
Vol 105 ◽  
pp. 59-67
Author(s):  
Jalal Joudaki ◽  
Mehdi Safari
Keyword(s):  
Fatigue Life ◽  
Fatigue Tests ◽  
Diffusivity Coefficient ◽  
Bending Fatigue ◽  
Steel Material ◽  
Wide Range ◽  
Different Temperatures ◽  
St37 Steel ◽  
Fatigue Life Test ◽  
Carburizing Process

Carburizing is a heat treatment process, which used widely for surface hardening. In this process, the parts are placed in a concentrated atmosphere of Carbon atoms. The carbon atoms diffuse in the samples from the surface. In the present article, the effects of carburizing temperature on fatigue life will be studied. The St37 steel material is selected for study due to its wide range of usage in industry and little attention on the carburizing of this material. The samples are prepared by implementing the carburizing process at different temperatures (300, 400, 500, and 600 °C). The holding time is 1 hour for all samples. The two-point bending fatigue tests had been carried out on constant loading stresses. The results of the fatigue life test show that the fatigue life enhances the carburizing process. The fatigue life improved from about 45000 cycles to about 65000 cycles (about 44% increase) by increasing the temperature from 300°C to 600°C. Holding at higher temperatures leads to an increase in fatigue life smoothly due to the increase in the diffusivity coefficient. Also, the fracture surface demonstrates that the crack initiation starts from outer surfaces very slowly and failure happens as a brittle fracture in the samples.

Four Point Bending Fatigue Tests of Forged Ti 6Al 4V

2009 ◽  
Vol 51 (9) ◽  
pp. 580-586 ◽  
Author(s):  
Bernd Oberwinkler ◽  
Martin Riedler ◽  
Heinz Leitner ◽  
Ataollah Javidi
Keyword(s):  
Fatigue Tests ◽  
Bending Fatigue ◽  
Four Point Bending

Structure Guided Molecular Docking Assisted Alignment Dependent 3DQSAR Study on Steroidal Aromatase Inhibitors (SAIs) as Anti-breast Cancer Agents

2019 ◽  
Vol 16 (7) ◽  
pp. 808-817 ◽  
Author(s):  
Laxmi Banjare ◽  
Sant Kumar Verma ◽  
Akhlesh Kumar Jain ◽  
Suresh Thareja
Keyword(s):  
Breast Cancer ◽  
Molecular Docking ◽  
Aromatase Inhibitors ◽  
Direct Synthesis ◽  
3D Qsar ◽  
Chemotherapeutic Agents ◽  
Modeling Tools ◽  
Data Set ◽  
Wide Range ◽  
Steroidal Aromatase Inhibitors

Background: In spite of the availability of various treatment approaches including surgery, radiotherapy, and hormonal therapy, the steroidal aromatase inhibitors (SAIs) play a significant role as chemotherapeutic agents for the treatment of estrogen-dependent breast cancer with the benefit of reduced risk of recurrence. However, due to greater toxicity and side effects associated with currently available anti-breast cancer agents, there is emergent requirement to develop target-specific AIs with safer anti-breast cancer profile. Methods: It is challenging task to design target-specific and less toxic SAIs, though the molecular modeling tools viz. molecular docking simulations and QSAR have been continuing for more than two decades for the fast and efficient designing of novel, selective, potent and safe molecules against various biological targets to fight the number of dreaded diseases/disorders. In order to design novel and selective SAIs, structure guided molecular docking assisted alignment dependent 3D-QSAR studies was performed on a data set comprises of 22 molecules bearing steroidal scaffold with wide range of aromatase inhibitory activity. Results: 3D-QSAR model developed using molecular weighted (MW) extent alignment approach showed good statistical quality and predictive ability when compared to model developed using moments of inertia (MI) alignment approach. Conclusion: The explored binding interactions and generated pharmacophoric features (steric and electrostatic) of steroidal molecules could be exploited for further design, direct synthesis and development of new potential safer SAIs, that can be effective to reduce the mortality and morbidity associated with breast cancer.

Integrative Data Analysis from a Unifying Research Synthesis Perspective

2018 ◽  
Author(s):  
Eun-Young Mun ◽  
Anne E. Ray
Keyword(s):  
Data Analysis ◽  
Large Scale ◽  
Research Synthesis ◽  
Alcohol Intervention ◽  
Data Set ◽  
Integrative Data Analysis ◽  
Level Data ◽  
Model Complex ◽  
Wide Range ◽  
Individual Participant

Integrative data analysis (IDA) is a promising new approach in psychological research and has been well received in the field of alcohol research. This chapter provides a larger unifying research synthesis framework for IDA. Major advantages of IDA of individual participant-level data include better and more flexible ways to examine subgroups, model complex relationships, deal with methodological and clinical heterogeneity, and examine infrequently occurring behaviors. However, between-study heterogeneity in measures, designs, and samples and systematic study-level missing data are significant barriers to IDA and, more broadly, to large-scale research synthesis. Based on the authors’ experience working on the Project INTEGRATE data set, which combined individual participant-level data from 24 independent college brief alcohol intervention studies, it is also recognized that IDA investigations require a wide range of expertise and considerable resources and that some minimum standards for reporting IDA studies may be needed to improve transparency and quality of evidence.

scholarly journals A Self-Spatial Adaptive Weighting Based U-Net for Image Segmentation

Electronics ◽  
2021 ◽  
Vol 10 (3) ◽  
pp. 348
Author(s):  
Choongsang Cho ◽  
Young Han Lee ◽  
Jongyoul Park ◽  
Sangkeun Lee
Keyword(s):  
Image Segmentation ◽  
Medical Image ◽  
Medical Image Segmentation ◽  
Feature Maps ◽  
Data Set ◽  
Feature Map ◽  
Adaptive Weighting ◽  
Spatially Adaptive ◽  
Wide Range ◽  
Decoder Architecture

Semantic image segmentation has a wide range of applications. When it comes to medical image segmentation, its accuracy is even more important than those of other areas because the performance gives useful information directly applicable to disease diagnosis, surgical planning, and history monitoring. The state-of-the-art models in medical image segmentation are variants of encoder-decoder architecture, which is called U-Net. To effectively reflect the spatial features in feature maps in encoder-decoder architecture, we propose a spatially adaptive weighting scheme for medical image segmentation. Specifically, the spatial feature is estimated from the feature maps, and the learned weighting parameters are obtained from the computed map, since segmentation results are predicted from the feature map through a convolutional layer. Especially in the proposed networks, the convolutional block for extracting the feature map is replaced with the widely used convolutional frameworks: VGG, ResNet, and Bottleneck Resent structures. In addition, a bilinear up-sampling method replaces the up-convolutional layer to increase the resolution of the feature map. For the performance evaluation of the proposed architecture, we used three data sets covering different medical imaging modalities. Experimental results show that the network with the proposed self-spatial adaptive weighting block based on the ResNet framework gave the highest IoU and DICE scores in the three tasks compared to other methods. In particular, the segmentation network combining the proposed self-spatially adaptive block and ResNet framework recorded the highest 3.01% and 2.89% improvements in IoU and DICE scores, respectively, in the Nerve data set. Therefore, we believe that the proposed scheme can be a useful tool for image segmentation tasks based on the encoder-decoder architecture.

scholarly journals Prediction of Wide Range Two-Dimensional Refractivity Using an IDW Interpolation Method from High-Altitude Refractivity Data of Multiple Meteorological Observatories

2021 ◽  
Vol 11 (4) ◽  
pp. 1431
Author(s):  
Sungsik Wang ◽  
Tae Heung Lim ◽  
Kyoungsoo Oh ◽  
Chulhun Seo ◽  
Hosung Choo
Keyword(s):  
High Altitude ◽  
Korean Peninsula ◽  
Interpolation Method ◽  
Atmospheric Condition ◽  
Propagation Path ◽  
Two Dimensional ◽  
Data Set ◽  
Wide Range ◽  
Atmospheric Data ◽  
Terrain Surface

This article proposes a method for the prediction of wide range two-dimensional refractivity for synthetic aperture radar (SAR) applications, using an inverse distance weighted (IDW) interpolation of high-altitude radio refractivity data from multiple meteorological observatories. The radio refractivity is extracted from an atmospheric data set of twenty meteorological observatories around the Korean Peninsula along a given altitude. Then, from the sparse refractive data, the two-dimensional regional radio refractivity of the entire Korean Peninsula is derived using the IDW interpolation, in consideration of the curvature of the Earth. The refractivities of the four seasons in 2019 are derived at the locations of seven meteorological observatories within the Korean Peninsula, using the refractivity data from the other nineteen observatories. The atmospheric refractivities on 15 February 2019 are then evaluated across the entire Korean Peninsula, using the atmospheric data collected from the twenty meteorological observatories. We found that the proposed IDW interpolation has the lowest average, the lowest average root-mean-square error (RMSE) of ∇M (gradient of M), and more continuous results than other methods. To compare the resulting IDW refractivity interpolation for airborne SAR applications, all the propagation path losses across Pohang and Heuksando are obtained using the standard atmospheric condition of ∇M = 118 and the observation-based interpolated atmospheric conditions on 15 February 2019. On the terrain surface ranging from 90 km to 190 km, the average path losses in the standard and derived conditions are 179.7 dB and 182.1 dB, respectively. Finally, based on the air-to-ground scenario in the SAR application, two-dimensional illuminated field intensities on the terrain surface are illustrated.

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