1D Sediment Transport Modeling for a Sustainable Sediment Management: Two Case Studies of Reservoir Flushing

Sediment Transpor

About the use of Phase Field and FE to predict micostructures, Application on AlSi10Mg samples produced by Additive Manufacturing

Background & motivations Finite Element (FE) model in Additive Manufacturing (AM) AlSi10Mg Microstructure evolution FE Model of L-PBF (SLM) AlSi10Mg Phase-field model of microstructure evolution: Model description Model parameters Simulated calorimetric curve Conclusion

Python Data Driven framework for acceleration of Phase-Field simulations[Formula presented]

peer reviewedThe passage describes the development of a numerical framework in Python to create and process a large dataset for time-series prediction using Deep Learning algorithms. The dataset is generated by solving the Cahn–Hilliard equation for spinodal decomposition of a binary alloy and is labeled to train the algorithms. Prior to training, dimensionality reduction is performed using Auto-encoders and Principal Component Analysis. The framework identifies three distinct latent dimensions/spaces for the datasets. The primary dataset was generated by running up to 10,000 High-Fidelity Phase-Field simulations in parallel using High-Performance Computing (HPC). The framework is compatible with all major operating systems and has been thoroughly tested on Python 3.7 and later versions

Adaptive time stepping approach for Phase-Field modeling of phase separation and precipitates coarsening in additive manufacturing alloys

In the present work, the capacity of phase field method to highlight microstructural changes during the spinodal decomposition of a given binary alloy basing on the Cahn-Hilliard equation is presented. Then, growth and coarsening of precipitates are studied using the KKS (Kim-Kim-Suzuki) model, which includes Cahn-Hilliard and Allen-Cahn equations. The implementation of time stepping algorithms to resolve Phase-Field equations is illustrated. Within Fourier space, using semi-implicit spectral method, it has been demonstrated that it allows faster computing than schemes based on finite difference method. First, spinodal decomposition of a given binary alloy under isothermal loading is implemented and three time stepping approaches are applied: constant time stepping, non- iterative and an iterative method. While the non-iterative method is faster than the constant time stepping scheme, the iterative one, although relatively more CPU consuming, can guarantee the convergence of the computing. These methods are combined in an innovative approach tested on 1D, 2D and 3D grids. The effectiveness of the adopted adaptive time-stepping algorithm allows resolving equations in reasonable CPU time. It predicts different physical phenomena, such as phase separation and growth and coarsening of precipitates induced by important interfacial energies

Microstructure and properties of SLM AlSi10Mg: Understanding the influence of the local thermal history

peer reviewedSelective Laser Melting (SLM) is an Additive Manufacturing technique that is widely used to produce AlSi10Mg parts with a good strength-to-weight ratio. Indeed, strongly refined microstructures are obtained due to the ultra-fast cooling rates reached in this process, conferring high strength to the parts, even in the as-built state. However, microstructural heterogeneities at the scale of the melt pool may exert a detrimental influence on the mechanical properties e.g. by causing a loss in ductility. This study thus aims at a better understanding of the influence of the local thermal history on local variations of microstructure and mechanical properties. Microscopy (i.e. SEM+EDS) and nanoindentation have been combined to reach a detailed knowledge of the local microstructure and properties. In particular, the solute Si content in the -Al matrix, the volume fraction and the size of Si precipitates have been quantified by microscopy analysis. These local microstructural parameters are correlated with the matrix hardness as revealed by nanoindentation. Finally, the results of this detailed characterization are linked with the local thermal history that is approached in two different ways i.e. (i) an analytical description of thermal gradients inside the melt pool based on Rosenthal’s and Matyja’s equations and (ii) a simple Finite Element model for the deposition of a few layers in the SLM process

Prediction of static properties of LPBFAlSi10Mg samples post-treated by Friction Stir Processing or thermal treatments

peer reviewedLongLifeA

The Case for a Muon Collider Higgs Factory

We propose the construction of a compact Muon Collider Higgs Factory. Such a machine can produce up to \sim 14,000 at 8\times 10^{31} cm^-2 sec^-1 clean Higgs events per year, enabling the most precise possible measurement of the mass, width and Higgs-Yukawa coupling constants.Comment: Supporting letter for the document: "Muon Collider Higgs Factory for Smowmass 2013", A White Paper submitted to the 2013 U.S. Community Summer Study of the Division of Particles and Fields of the American Physical Society, Y. Alexahin, et. al, FERMILAB-CONF-13-245-T (July, 2013

Microstructure prediction in additive manufacturing(TA6V, AlSi10Mg, AISI M4 materials)

Bilan des travaux depuis 3 ans sur 3 matériaux en additive manufacturin

Controlled precipitation in a new Al-Mg-Sc alloy for enhanced corrosion behavior while maintaining the mechanical performance

peer reviewedThe hot working of 5xxx series alloys with Mg ≥3.5 wt% is a concern due to the precipitation of β (Al3Mg2) phase at grain boundaries favoring Inter Granular Corrosion (IGC). The mechanical and corrosion properties of a new 5028-H116 Al-Mg-Sc alloy under various β precipitates distribution is analyzed by imposing different cooling rates from the hot forming temperature (i.e. 325 °C). The mechanical properties are maintained regardless of the heat treatment. However, the different nucleation sites and volume fractions of β precipitates for different cooling rates critically affect IGC. Controlled furnace cooling after the 325 °C heat treatment is ideal in 5028-H116 alloy to reduce susceptibility to IGC after sensitization

Complex nature of apparently balanced chromosomal rearrangements in patients with autism spectrum disorder

Background: Apparently balanced chromosomal rearrangements can be associated with an abnormal phenotype, including intellectual disability and autism spectrum disorder (ASD). Genome-wide microarrays reveal cryptic genomic imbalances, related or not to the breakpoints, in 25% to 50% of patients with an abnormal phenotype carrying a microscopically balanced chromosomal rearrangement. Here we performed microarray analysis of 18 patients with ASD carrying balanced chromosomal abnormalities to identify submicroscopic imbalances implicated in abnormal neurodevelopment. Methods: Eighteen patients with ASD carrying apparently balanced chromosomal abnormalities were screened using single nucleotide polymorphism (SNP) arrays. Nine rearrangements were de novo, seven inherited, and two of unknown inheritance. Genomic imbalances were confirmed by fluorescence in situ hybridization and quantitative PCR. Results: We detected clinically significant de novo copy number variants in four patients (22%), including three with de novo rearrangements and one with an inherited abnormality. The sizes ranged from 3.3 to 4.9 Mb; three were related to the breakpoint regions and one occurred elsewhere. We report a patient with a duplication of the Wolf-Hirschhorn syndrome critical region, contributing to the delineation of this rare genomic disorder. The patient has a chromosome 4p inverted duplication deletion, with a 0.5 Mb deletion of terminal 4p and a 4.2 Mb duplication of 4p16.2p16.3. The other cases included an apparently balanced de novo translocation t(5;18)(q12;p11.2) with a 4.2 Mb deletion at the 18p breakpoint, a subject with de novo pericentric inversion inv(11)(p14q23.2) in whom the array revealed a de novo 4.9 Mb deletion in 7q21.3q22.1, and a patient with a maternal inv(2)(q14.2q37.3) with a de novo 3.3 Mb terminal 2q deletion and a 4.2 Mb duplication at the proximal breakpoint. In addition, we identified a rare de novo deletion of unknown significance on a chromosome unrelated to the initial rearrangement, disrupting a single gene, RFX3. Conclusions: These findings underscore the utility of SNP arrays for investigating apparently balanced chromosomal abnormalities in subjects with ASD or related neurodevelopmental disorders in both clinical and research settings