Sensing and modeling of the hot isostatic pressing of copper pressing

Wadley, H.N.G.; Schaefer, Robert; Kahn, Arnold H.; Ashby, Michael F.; Clough, R. B.; Geffen, Y.; Wlassich, John J.

doi:10.1016/0956-7151(91)90298-f

Cited by 40 publications

(8 citation statements)

References 4 publications

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“…Models for the growth or collapse of voids via plastic deformation can be linked to models for the evolution of plasticity in bulk material (cf. [351]). The task is then determining which plasticity mechanisms to represent.…”

Section: Continuum Methodsmentioning

confidence: 99%

Survey of Modeling and Simulation Techniques for Advanced Manufacturing Technologies Volume I – Predicting Initial Microstructures

Nicolas

Chakraborty

Paulson

et al. 2020

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This report summarizes the current state of modeling and simulation methods for predicting the initial structure and properties of material in components assembled using advanced manufacturing technologies (AMTs). The report is the first volume in a two-volume series. This first volume focuses on predicting initial microstructures of AM material. The second volume discusses predicting material properties given the initial microstructure. The focus is on technologies of particular relevance to the design and manufacture of nuclear reactor components. The purpose of the report is to help develop the technical knowledge base to support regulatory decisions that will be needed to assess nuclear components manufactured with AMTs as these components are installed at nuclear power plants (NPPs). The report develops a list of AMTs of particular interest to the NRC and summarizes the key microstructural features and corresponding processing parameters relevant to each technology. Further sections describe available physically-based and data-driven prediction methods and survey widely available software tools. The report concludes with a summary of gaps that may be of particular interest to the NRC when evaluating modeling and simulation methods for AMTs. v

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Section: Continuum Methodsmentioning

confidence: 99%

Survey of Modeling and Simulation Techniques for Advanced Manufacturing Technologies Volume I – Predicting Initial Microstructures

Nicolas

Chakraborty

Paulson

et al. 2020

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“…Ashby's micromechanical model (Reardon 1998b, c) has 19 parameters that must be optimized so that the calculated densities match experimental densities for given processing conditions. The experimental data to be used here are hot pressed copper powder data (Wadley et al 1991) as well as warm isostatically pressed beryllium powder data (Roberts 1983). The micromechanical model as well as the data used for the optimization have been discussed extensively in previous papers and reports (Reardon 1998b, c).…”

Section: Inverse and Ill-posed Problems In Materials Science And Engi...mentioning

confidence: 99%

Inversion of micromechanical powder consolidation and sintering models using Bayesian inference and genetic algorithms

Reardon¹

1999

Modelling Simul. Mater. Sci. Eng.

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It is shown that a genetic algorithm (GA) is in fact a Bayesian inference engine and as such the tools of Bayesian analysis can be applied to the output of a GA to rectify a number of deficiencies in the overall GA technique. In this work, the Bayesian enhanced GA addresses the inverse and ill-posed problem of optimizing the parameters of the micromechanical powder densification models for beryllium and copper powder using limited and uncertain data sets that leave the optimization problem underdetermined. The advantages of using the Bayesian approach to analyse GA output are described in detail. Firstly, the stochasticity of the GA is suppressed and thus a realistic assessment of model parameter sensitivity and covariance becomes available. Secondly, a suitable stopping criterion for the GA is defined by when the sum of the eigenvalues obtained from the principal component analysis of the a posteriori covariance matrix reaches a limiting value. Lastly, the generation of the posterior probability density allows a distribution of optimal model parameter vectors to be applied to the physics of the forward problem. The distribution of the resulting outcomes is then used as a guide in experimental design.

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“…Swinkels and Ashby () developed a widely accepted model to study the sintering of metal powders, which calculates the increase in neck size (Figure , x ), decrease in interparticle distance or densification (Figure , a − y ), and change in grain and pore morphology (Figure ) driven by several diffusive mass fluxes (Figure ) in a 3‐D aggregate of spherical particles. This model was validated with laboratory measurements of eight different metal alloys and since then has been used extensively in the metallurgy literature (e.g., Parhami et al, ; Svoboda & Riedel, ; Wadley et al, ). Many modern sintering models are based, in some part, on this work.…”

Section: Introductionmentioning

confidence: 99%

“…has been used extensively in the metallurgy literature (e.g., Parhami et al, 1999;Svoboda and Riedel, 1995;Wadley et al, 1991). Many modern sintering models are based, in some part, on this work.…”

Section: Introductionmentioning

confidence: 99%

The Microstructural Evolution of Water Ice in the Solar System Through Sintering

et al. 2019

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Ice sintering is a form of metamorphism that drives the microstructural evolution of an aggregate of grains through surface and volume diffusion. This leads to an increase in the grain‐to‐grain contact area (neck) and density of the aggregate over time, resulting in the evolution of its strength, porosity, thermal conductivity, and other properties. This process plays an important role in the evolution of icy planetary surfaces, though its rate and nature are not well constrained. In this study, we explore the model of Swinkels and Ashby (1981, https://doi.org/10.1016/0001-6160%2881%2990154-1) and assess the extent to which it can be used to quantify sintering timescales for water ice. We compare predicted neck growth rates to new and historical observations of ice sintering and find agreement to some studies at the order of magnitude level. First‐order estimates of neck growth timescales on planetary surfaces show that ice may undergo significant modification over geologic timescales, even in the outer solar system. Densification occurs over much longer timescales, suggesting that some surfaces may develop cohesive, but porous, crusts. Sintering rates are extremely sensitive to temperature and grain size, occurring faster in warmer aggregates of smaller grains. This suggests that the microstructural evolution of ices may vary not only throughout the solar system but also spatially across the surface and in the near surface of a given body. Our experimental observations of complex grain growth and mass redistribution in ice aggregates point to components of the model that may benefit from improvement and areas where additional laboratory studies are needed.

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Sensing and modeling of the hot isostatic pressing of copper pressing

Cited by 40 publications

References 4 publications

Survey of Modeling and Simulation Techniques for Advanced Manufacturing Technologies Volume I – Predicting Initial Microstructures

Survey of Modeling and Simulation Techniques for Advanced Manufacturing Technologies Volume I – Predicting Initial Microstructures

Inversion of micromechanical powder consolidation and sintering models using Bayesian inference and genetic algorithms

The Microstructural Evolution of Water Ice in the Solar System Through Sintering

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