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<pubDate xmlns="http://apache.org/cocoon/i18n/2.1">Sun, 08 Mar 2026 11:32:51 GMT</pubDate>
<dc:date>2026-03-08T11:32:51Z</dc:date>
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<title>A new system formulation for the tolerance analysis of overconstrained mechanisms</title>
<link>http://hdl.handle.net/10985/17421</link>
<description>A new system formulation for the tolerance analysis of overconstrained mechanisms
DUMAS, Antoine; GAYTON, Nicolas; SUDRET, Bruno; DANTAN, Jean-Yves
The goal of tolerance analysis is to verify whether design tolerances enable a mechanism to be functional. The current method consists in computing a probability of failure using Monte Carlo simulation combined with an optimization scheme called at each iteration. This time consuming technique is not appropriate for complex overconstrained systems. This paper proposes a transformation of the current tolerance analysis problem formulation into a parallel system probability assessment problem using the Lagrange dual form of the optimization problem. The number of events being very large, a preliminary selective search algorithm is used to identify the most contributing events to the probability of failure value. The First Order Reliability Method (FORM) for systems is eventually applied to compute the probability of failure at low cost. The proposed method is tested on an overconstrained mechanism modeled in three dimensions. Results are consistent with those obtained with the Monte Carlo simulation and the computing time is significantly reduced.
</description>
<pubDate>Thu, 01 Jan 2015 00:00:00 GMT</pubDate>
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<dc:date>2015-01-01T00:00:00Z</dc:date>
<dc:creator>DUMAS, Antoine</dc:creator>
<dc:creator>GAYTON, Nicolas</dc:creator>
<dc:creator>SUDRET, Bruno</dc:creator>
<dc:creator>DANTAN, Jean-Yves</dc:creator>
<dc:description>The goal of tolerance analysis is to verify whether design tolerances enable a mechanism to be functional. The current method consists in computing a probability of failure using Monte Carlo simulation combined with an optimization scheme called at each iteration. This time consuming technique is not appropriate for complex overconstrained systems. This paper proposes a transformation of the current tolerance analysis problem formulation into a parallel system probability assessment problem using the Lagrange dual form of the optimization problem. The number of events being very large, a preliminary selective search algorithm is used to identify the most contributing events to the probability of failure value. The First Order Reliability Method (FORM) for systems is eventually applied to compute the probability of failure at low cost. The proposed method is tested on an overconstrained mechanism modeled in three dimensions. Results are consistent with those obtained with the Monte Carlo simulation and the computing time is significantly reduced.</dc:description>
</item>
<item>
<title>Statistical study of the size and spatial distribution of defects in a cast aluminium alloy for the low fatigue life assessment</title>
<link>http://hdl.handle.net/10985/22778</link>
<description>Statistical study of the size and spatial distribution of defects in a cast aluminium alloy for the low fatigue life assessment
WILSON, Pablo; SAINTIER, Nicolas; PALIN-LUC, Thierry; SUDRET, Bruno; BERGAMO, Sebastien
Cast aluminium alloys, and more widely cast materials, are frequently used in industry. The casting process allows for complex geometries of parts, but, on the downside, often causes materials voids. It is well known these material defects are harmful for material fatigue performances, but the nature of these defects, in a statistical manner, are more seldom studied. This paper aims at proposing a methodology for finding the underlying characteristics of the defect population (size and spatial distribution) and determine their implication on fatigue behaviour in the presence of stress/strain gradients (notched specimens). To do so, various statistical tools are brought from different fields, such as point processes, and applied to experimentally observed defect distributions (by μCT tomography on virgin test specimens). The population of defects is&#13;
clearly identified, and it is shown these defects are not randomly distributed, but rather in cluster. It is also shown there is no strong link between the defect size an it’s location. Knowing the statistics of the defect population, it is then possible to confront the result of fatigue tests (and the observed initiating defects) with the simulated defect population: the fatigue crack initiation mechanisms, which favour (sub-) surface rather than core initiating defects, reduce the size of the active zone and therefore artificially shift the defect size distribution (by reducing their number).
</description>
<pubDate>Sun, 01 Jan 2023 00:00:00 GMT</pubDate>
<guid isPermaLink="false">http://hdl.handle.net/10985/22778</guid>
<dc:date>2023-01-01T00:00:00Z</dc:date>
<dc:creator>WILSON, Pablo</dc:creator>
<dc:creator>SAINTIER, Nicolas</dc:creator>
<dc:creator>PALIN-LUC, Thierry</dc:creator>
<dc:creator>SUDRET, Bruno</dc:creator>
<dc:creator>BERGAMO, Sebastien</dc:creator>
<dc:description>Cast aluminium alloys, and more widely cast materials, are frequently used in industry. The casting process allows for complex geometries of parts, but, on the downside, often causes materials voids. It is well known these material defects are harmful for material fatigue performances, but the nature of these defects, in a statistical manner, are more seldom studied. This paper aims at proposing a methodology for finding the underlying characteristics of the defect population (size and spatial distribution) and determine their implication on fatigue behaviour in the presence of stress/strain gradients (notched specimens). To do so, various statistical tools are brought from different fields, such as point processes, and applied to experimentally observed defect distributions (by μCT tomography on virgin test specimens). The population of defects is&#13;
clearly identified, and it is shown these defects are not randomly distributed, but rather in cluster. It is also shown there is no strong link between the defect size an it’s location. Knowing the statistics of the defect population, it is then possible to confront the result of fatigue tests (and the observed initiating defects) with the simulated defect population: the fatigue crack initiation mechanisms, which favour (sub-) surface rather than core initiating defects, reduce the size of the active zone and therefore artificially shift the defect size distribution (by reducing their number).</dc:description>
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