Modeling of casting microstructures and defects

Abstract

3. 4. 1.Art Shapiro (MWNTED) -project leader, theoretical developments and experiment design Leonard Summers (C&MS) -Appendix 2 Physical Properties of Solid and Liquid Uranium Del Eckels (MWNTED) -experiment fabrication and execution Vivek Sahai (ME/NTED) -GLO code optimization calculations IntroductionOur interest in casting is linked to DOE efforts to reduce hazardous waste and scrap produced by metal component fabrication processes. Improved processes for manufacturing plutonium and uranium components, for example, can minimim scrap metal, contaminated waste, and possible radiation exposure, and reduce the cost of equipment and facilities.Casting is an ancient art that has been a trial-and-em' process for more than 4000 years. To predict the size, shape, and quality of a cast pmduc~casting manufacturers typically cast fidl-sim prototypes. If one pat of the process is done incorrectly, the entire process is repted until SIIacceptable product is achieved.One way to reduce the time, COSL and waste associated with casting is to use computer modeling to predict not only the quality of a product on the macro-scale, such as distortion and part shape, but also on the micro-scale such as grain defects. Modeling of solidification is becoming increasingly feasible with the advent of parallel computers. Them am essentially two approaches to solidification modeling. The first is that of macro-modeling where heat transfer codes model latent heat release during solidification as a constant and based solely on the local temperature. This approach is useftd in pdicting large scale distortion and final part shape. The second approach, micro-modeling, is more fimdamental. The micro-models estimate the latent heat release during solidification using nucleation and grain growth kinetics. Micro-models give insight into cast grain morphology and show promise in the future to pndict engineering properties such as tensile strength.The micro-model solidification kinetics can be evaluated using first principles or they can be evaluated using experiments. This work describes an implementation of a micro-model for uranium which uses experimental results to estimate nucleation and growth kinetics. Mathematical FormulationThe primary and most obvious phenomenon controlling casting is the transfer of heat fmm the cooling metal to the mold and surroundings. The present needs of many foundries are being satisfied by relatively simple heat conduction modeling that reedy indicate regions of risk for shrinkage porosity. Coupled with empirical experience, foundry engineers 1 successfi.dly cast parts used in life critical applications (e.g., jet engine turbine components[1]). However, DOE's vision is to move from empiricism to science based design. V @ groti law constant 3.Oe-06 m /s C* Heat conduction analvsis codes model latent heat release during solidification as a constant and based solely on&e local temperature. The next step in soli-tication modeling is to make the latent heat a function of the solidification fraction which depends on the n...

High-Temperature Thermodynamics of Uranium from Ab Initio Modeling

“…Our theory (solid circles and dashed line) in Figure 1 agrees very well with the experimental data [97,98]; only a very small shift is evident relative to one experimental set [97]. The small errors (<1%) are consistent with the findings for the low-temperature volume in Table 1.…”

“…In Figure 1, we show our calculated volume expansion for γ-U together with results from AIMD [46,66], MEAM [30], and experiments [97,98].…”

“…Solid symbols represent our DFT + OP + SCAILD model, AIMD[46,66], and MEAM results[30]. Open symbols indicate experimental data[97,98]. The dashed line is provided only as a guide.…”