Testing Techniques for Mechanical Characterization of Nanostructured Materials

2003 ◽  
Vol 791 ◽  
Author(s):  
Carl C. Koch ◽  
Ronald O. Scattergood ◽  
K. Linga Murty ◽  
Ramesh K. Guduru ◽  
Gopinath Trichy ◽  
...  
Keyword(s):  
Indentation Test ◽  
Small Sample ◽  
Small Samples ◽  
Punch Test ◽  
Ball Indentation ◽  
Shear Punch Test ◽  
Testing Techniques ◽  
Ball Indentation Test ◽  
Small Sample Sizes

ABSTRACTTesting methods are reviewed that can be applied to the small sample sizes which result from many of the processing routes for preparation of nanocrystalline materials. These include the measurement of elastic properties on small samples; hardness, with emphasis on nanoindentation methods; the miniaturized disk bend test (MDBT); the automated ball indentation test (ABI); the shear punch test; and the use of subsize compression and tensile samples.

scholarly journals G-computation and machine learning for estimating the causal effects of binary exposure statuses on binary outcomes

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Florent Le Borgne ◽  
Arthur Chatton ◽  
Maxime Léger ◽  
Rémi Lenain ◽  
Yohann Foucher
Keyword(s):  
Machine Learning ◽  
Support Vector Machine ◽  
Statistical Power ◽  
Small Sample ◽  
Causal Effects ◽  
Small Samples ◽  
Support Vector ◽  
Sample Sizes ◽  
Super Learner ◽  
Small Sample Sizes

AbstractIn clinical research, there is a growing interest in the use of propensity score-based methods to estimate causal effects. G-computation is an alternative because of its high statistical power. Machine learning is also increasingly used because of its possible robustness to model misspecification. In this paper, we aimed to propose an approach that combines machine learning and G-computation when both the outcome and the exposure status are binary and is able to deal with small samples. We evaluated the performances of several methods, including penalized logistic regressions, a neural network, a support vector machine, boosted classification and regression trees, and a super learner through simulations. We proposed six different scenarios characterised by various sample sizes, numbers of covariates and relationships between covariates, exposure statuses, and outcomes. We have also illustrated the application of these methods, in which they were used to estimate the efficacy of barbiturates prescribed during the first 24 h of an episode of intracranial hypertension. In the context of GC, for estimating the individual outcome probabilities in two counterfactual worlds, we reported that the super learner tended to outperform the other approaches in terms of both bias and variance, especially for small sample sizes. The support vector machine performed well, but its mean bias was slightly higher than that of the super learner. In the investigated scenarios, G-computation associated with the super learner was a performant method for drawing causal inferences, even from small sample sizes.

Implications of Small Samples for Generalization: Adjustments and Rules of Thumb

2016 ◽  
Vol 41 (5) ◽  
pp. 472-505 ◽  
Author(s):  
Elizabeth Tipton ◽  
Kelly Hallberg ◽  
Larry V. Hedges ◽  
Wendy Chan
Keyword(s):  
Observational Studies ◽  
Small Sample ◽  
Average Treatment Effect ◽  
Small Samples ◽  
Sample Sizes ◽  
Random Samples ◽  
Rules Of Thumb ◽  
Large Populations ◽  
Small Sample Sizes ◽  
Combine Information

Background: Policy makers and researchers are frequently interested in understanding how effective a particular intervention may be for a specific population. One approach is to assess the degree of similarity between the sample in an experiment and the population. Another approach is to combine information from the experiment and the population to estimate the population average treatment effect (PATE). Method: Several methods for assessing the similarity between a sample and population currently exist as well as methods estimating the PATE. In this article, we investigate properties of six of these methods and statistics in the small sample sizes common in education research (i.e., 10–70 sites), evaluating the utility of rules of thumb developed from observational studies in the generalization case. Result: In small random samples, large differences between the sample and population can arise simply by chance and many of the statistics commonly used in generalization are a function of both sample size and the number of covariates being compared. The rules of thumb developed in observational studies (which are commonly applied in generalization) are much too conservative given the small sample sizes found in generalization. Conclusion: This article implies that sharp inferences to large populations from small experiments are difficult even with probability sampling. Features of random samples should be kept in mind when evaluating the extent to which results from experiments conducted on nonrandom samples might generalize.

Ball-indentation test technique for evaluating thermal and creep damage of modified 9Cr-1Mo steel

2010 ◽  
Vol 63 (2-3) ◽  
pp. 431-436 ◽  
Author(s):  
V. Karthik ◽  
K. Laha ◽  
K. S. Chandravathi ◽  
P. Parameswaran ◽  
K. V. Kasiviswanathan ◽  
...  
Keyword(s):  
Indentation Test ◽  
Creep Damage ◽  
Test Technique ◽  
Ball Indentation ◽  
Ball Indentation Test

Taphonomy and ecology of modern avifaunal remains from Amboseli Park, Kenya

Paleobiology ◽  
2003 ◽  
Vol 29 (1) ◽  
pp. 52-70 ◽  
Author(s):  
Anna K. Behrensmeyer ◽  
C. Tristan Stayton ◽  
Ralph E. Chapman
Keyword(s):  
Habitat Preferences ◽  
Large Body ◽  
Bird Community ◽  
Skeletal Remains ◽  
Small Sample ◽  
Small Samples ◽  
Scaling Analysis ◽  
Ecological Data ◽  
Small Sample Sizes ◽  
Grassland Habitats

Avian skeletal remains occur in many fossil assemblages, and in spite of small sample sizes and incomplete preservation, they may be a source of valuable paleoecological information. In this paper, we examine the taphonomy of a modern avian bone assemblage and test the relationship between ecological data based on avifaunal skeletal remains and known ecological attributes of a living bird community. A total of 54 modern skeletal occurrences and a sample of 126 identifiable bones from Amboseli Park, Kenya, were analyzed for weathering features and skeletal part preservation in order to characterize preservation features and taphonomic biases. Avian remains, with the exception of ostrich, decay more rapidly than adult mammal bones and rarely reach advanced stages of weathering. Breakage and the percentage of anterior limb elements serve as indicators of taphonomic overprinting that may affect paleoecological signals. Using ecomorphic categories including body weight, diet, and habitat, we compared species in the bone assemblage with the living Amboseli avifauna. The documented bone sample is biased toward large body size, representation of open grassland habitats, and grazing or scavenging diets. In spite of this, multidimensional scaling analysis shows that the small faunal sample (16 out of 364 species) in the pre-fossil bone assemblage accurately represents general features of avian ecospace in Amboseli. This provides a measure of the potential fidelity of paleoecological reconstructions based on small samples of avian remains. In the Cenozoic, the utility of avian fossils is enhanced because bird ecomorphology is relatively well known and conservative through time, allowing back-extrapolations of habitat preferences, diet, etc. based on modern taxa.

Evaluation of Local Tensile Properties of Bi-Metallic Weld Joints by Small Tensile and Ball Indentation Tests

2007 ◽  
Vol 353-358 ◽  
pp. 2073-2076
Author(s):  
Jin Won Kim ◽  
Jong Sun Park ◽  
Jong Sung Kim ◽  
Tae Eun Jin
Keyword(s):  
Weld Metal ◽  
Tensile Properties ◽  
Ferritic Steel ◽  
Indentation Test ◽  
Ultimate Tensile Stress ◽  
Base Metals ◽  
Weld Joints ◽  
Ball Indentation ◽  
Indentation Tests ◽  
Ball Indentation Test

This study performed tensile test using small-size flat specimen and ball indentation test at room temperature to characterize the local tensile properties of bi-metallic weld joints. The weld specimens used were fabricated by joining between SA508 Gr.3 ferritic steel and Type 316 stainless steel with Alloy 82 buttering on the ferritic steel side and Alloy 82/182 weld metal. The test results showed that yield stress (YS) of weld metal was slightly higher than that of Type 316 and smaller than that of SA508 Gr.3, and ultimate tensile stress (UTS) of weld metal was similar as those of Type 316 and SA508 Gr.3 base metals. Also, the values of YS and UTS of buttering layer (Alloy 82) were nearly same as those of weld metal. Heat-affected-zones (HAZs) showed higher YS and UTS values compared to their base metals. Especially, the strengths of SA508 Gr.3 were significantly higher than those of surrounding materials. Also, it was known that the ball indentation test reasonably measured the local YS and UTS of bi-metallic weld joints.

In-Situ Damage Evaluation Using Ball Indentation Test Method

2010 ◽  
Author(s):  
Raghu V. Prakash
Keyword(s):  
True Strain ◽  
Base Material ◽  
Indentation Test ◽  
Test Method ◽  
Fatigue Properties ◽  
Invasive Test ◽  
Ball Indentation ◽  
Loading And Unloading ◽  
Ball Indentation Test

Automated ball indentation is a semi-invasive test method that is gaining importance as a field test method in the recent times. Based on the few cycles of loading and unloading, and corresponding load, deflection characteristics, it is possible to estimate the true stress-true strain information of a material. In the present work, ball indentation has been used to evaluate the static and fatigue properties of base material as well as material subjected to different types of damage, such as fatigue, weldment etc. The tensile properties and fatigue properties were found to be affected by the prior damage history.

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