Contactless ultrasound generation in a crucible

Ultrasound treatment is used in light alloys during solidification to refine microstructure, remove gas, or disperse immersed particles. A mechanical sonotrode immersed in the melt is most effective when probe tip vibrations lead to cavitation. Liquid contact with the probe can be problematic for high temperature or reactive melts leading to contamination. An alternative contactless method of generating ultrasonic waves is proposed, using electromagnetic (EM) induction. As a bonus, the EM force induces vigorous stirring distributing the effect to treat larger volumes of material. In a typical application, the induction coil surrounding the crucible— also used to melt the alloy—may be adopted for this purpose with suitable tuning. Alternatively, a top coil, immersed in the melt (but still contactless due to EM force repulsion) may be used. Numerical simulations of sound, flow, and EM fields suggest that large pressure amplitudes leading to cavitation may be achievable with this method

Modelling the deagglomeration of nanoparticle inclusions by ultrasonic melt processing

The aerospace and automotive industries are seeking advanced materials with low weight-to-strength ratio, such as light alloy-based metal matrix composites (MMC) with nanoparticle rein-forcements. However, van der Waals and adhesive forces between nanoparticles result in large agglomerates that compromise the final properties of MMCs. Ultrasonic melt processing is a potential technology for de-agglomerating these clusters and producing samples with improved properties via grain refinement. This paper considers two hypotheses of cluster de-agglomeration: the breakup of a cluster due to the growth of gas contained in the cluster and the stripping of nanoparticles by pulsating neighbouring bubbles

Zonal method for simultaneous definition of block-structured geometry and mesh

A new method is proposed for specifying the geometrical shape and for meshing of the computational domain for CFD or general numerical PDE solvers which allow block-structured or unstructured meshes. The new method is based on highlighting pre-meshed spatial zones for boundary and material definitions with subsequent shape-matching deformations. The new method combines functionality with ease of implementation and ease of use which make it suitable for in-house computational codes. Although intended predominantly for research, the proposed method has been used successfully in a number of computational engineering projects

Choosing the appropriate level of coupling in multi-physics modeling of metallurgical processes

A computational model for the interrelated phenomena in the process of vacuum arc remelting is analyzed and adjusted of optimal accuracy and computation time. The decision steps in this case study are offered as an example how the coupling in models of similar processes can be addressed. Results show dominance of the electromagnetic forces over buoyancy and inertia for the investigated process conditions

A multi-scale 3D model of the vacuum arc remelting process

A multi-scale model of the VAR process was developed to simulate unsteady phenomena within the ingot melt pool due to arc motion and the resulting effects on dendritic microstructure. External magnetic field and surface current measurements were used as boundary conditions, to determine the trajectory of the arcs between electrode and ingot and between ingot and sidewalls. The interactions between magnetic field, turbulent metal flow and heat transfer were modeled using CFD techniques and this "macro" model was linked to a micro model, to resolve the evolving dendritic microstructure, and to establish a relationship between operational parameters and microstructure defects. Arc-driven solute convection in the mushy zone leading to local remelting and changes in local Rayleigh number provided an indicator of when fluid flow channels (freckles) will initiate within the mushy zone. Particle tracking was further used, to characterize the trajectory and dissolution of inclusions entering the melt, causing "white spot" defects

Observation of a new boson at a mass of 125 GeV with the CMS experiment at the LHC

The article is the pre-print version of the final publishing paper that is available from the link below.Results are presented from searches for the standard model Higgs boson in proton–proton collisions At √s = 7 and 8 TeV in the Compact Muon Solenoid experiment at the LHC, using data samples corresponding to integrated luminosities of up to 5.1 fb−1 at 7TeV and 5.3 fb−1 at 8 TeV. The search is performed in five decay modes: γγ, ZZ, W+W−, τ+τ−, and bb. An excess of events is observed above the expected background, with a local significance of 5.0 standard deviations, at a mass near 125 GeV, signalling the production of a new particle. The expected significance for a standard model Higgs boson of that mass is 5.8 standard deviations. The excess is most significant in the two decay modes with the best mass resolution, γγ and ZZ; a fit to these signals gives a mass of 125.3±0.4(stat.)±0.5(syst.) GeV. The decay to two photons indicates that the new particle is a boson with spin different from one

The CMS Barrel Calorimeter Response to Particle Beams from 2 to 350 GeV/c

The response of the CMS barrel calorimeter (electromagnetic plus hadronic) to hadrons, electrons and muons over a wide momentum range from 2 to 350 GeV/c has been measured. To our knowledge, this is the widest range of momenta in which any calorimeter system has been studied. These tests, carried out at the H2 beam-line at CERN, provide a wealth of information, especially at low energies. The analysis of the differences in calorimeter response to charged pions, kaons, protons and antiprotons and a detailed discussion of the underlying phenomena are presented. We also show techniques that apply corrections to the signals from the considerably different electromagnetic (EB) and hadronic (HB) barrel calorimeters in reconstructing the energies of hadrons. Above 5 GeV/c, these corrections improve the energy resolution of the combined system where the stochastic term equals 84.7$\pm$1.6$\%$ and the constant term is 7.4$\pm$0.8$\%$. The corrected mean response remains constant within 1.3$\%$ rms