Detecting Equilibrium Cells in DSMC to Improve the Computational Efficiency

DSMC in the large collision rate limit has previously been used as an approximate Euler solver [Pullin, J. Comput. Phys., v34, 1980, pp. 231--244, Lengrand et al. Rarefied Gas Dynamics 12, Progress in Astronautics and Aeronautics, v74, AIAA, 1981, p994, Merkle et al. Rarefied Gas Dynamics 12, Progress in Astronautics and Aeronautics, v74, AIAA, 1981, p256]. Macrossan [Rarefied Gas Dynamics 22, AIP Conference Proceedings 585, American Institute of Physics, New York, 2001, pp. 388--395] suggested that therefore a particle-only approach could be taken to flows which contain a mixture of rarefied and continuum or near-continuum conditions; in those parts of the flow that would more conventionally be solved by a continuum Navier-Stokes or Euler solver, DSMC could be invoked in its `Euler solver mode'. The regions where the Euler solver can be invoked were determined (as is usual in such hybrid codes) by evaluating the breakdown parameter which compares the local collision time to the flow transit time through a local characteristic flow length. The flow length is derived from the gradient of some flow property. Here we investigate a different, but related, approach to this problem. In regions where the Euler equations apply, the velocity distribution function has the Maxwell form. If the velocity distribution in a cell is examined after the particles have been moved, but before the collisions are calculated, it could be established that the cell is already in, or very close to, its equilibrium state. Such "equilibrium cells" may be found anywhere in the flow where the flow gradients are small; it is only when the movement of the particles brings to one `recipient cell' particles which started in different "donor cells" with different flow conditions that a non-equilibrium velocity distribution is established in the recipient cell. Here two different measures derived from the velocity distribution were used to identify the equilibrium cells: the ratio of shear stress to pressure and a measure of the departure of all temperature components from the overall kinetic temperature. These were evaluated from the time-averaged flow state found from flow samples taken before the collision calculations were performed. In the equilibrium cells there would appear to be no need to calculate any collisions; the effect of the collisions would merely be to bring about a new statistical representation of the same equilibrium distribution. To maintain stability it was found that new velocities must be established in these equilibrium cells. Two different methods were used to set new velocities in equilibrium cells. These were (1) Pullin's EPSM method by which new particle velocities are selected from an equilibrium distribution and (2) a form of `collision limiting' in which a reduced number of collisions are calculated in equilibrium cells. These methods were tested for a Mach 5, blunt body flow with freestream Knudsen numbers of 0.1 and 0.064. Savings of CPU times of 10% (over standard DSMC) were achieved. We believe the general method could lead to greater savings in the CPU times for flows at lower Knudsen numbers, where the collision calculations could become more time consuming

Hybrid expansions for local structural relaxations

A model is constructed in which pair potentials are combined with the cluster expansion method in order to better describe the energetics of structurally relaxed substitutional alloys. The effect of structural relaxations away from the ideal crystal positions, and the effect of ordering is described by interatomic-distance dependent pair potentials, while more subtle configurational aspects associated with correlations of three- and more sites are described purely within the cluster expansion formalism. Implementation of such a hybrid expansion in the context of the cluster variation method or Monte Carlo method gives improved ability to model phase stability in alloys from first-principles.Comment: 8 pages, 1 figur

Search for Low Mass Exotic mesonic structures. Part I: experimental results

Recently, several papers discussed on the existence of a low mass new structure at a mass close to M=214.3 MeV. It was suggested that the $\Sigma^{+}$ disintegration: $\Sigma^{+}\to$pP$^{0}$, P$^{0}\to\mu^{-}\mu^{+}$ proceeds through an intermediate particle P$^{0}$ having such mass. The present work intends to look at other new or available data, in order to observe the eventual existence of small narrow peaks or shoulders in very low mesonic masses. Indeed narrow structures were already extracted from various data in dibaryons, baryons and mesons (at larger masses that those studied here).Comment: 7 pages 11 figure

Order-disorder Effects on Equation of State in FCC Ni-Al Alloys

Order-disorder effects on equation of state (EOS) properties of substitutional binary alloys are investigated with the cluster variation method (CVM) based on ab initio effective cluster interactions (ECI). Calculations are applied to the fcc based Ni-Al system. Various related quantities are shown to vary with concentration around stoichiometry with a surprising "W shape", such as the thermal expansion coefficient, the heat capacity and the Gruneisen parameter, due to configurational ordering effects. Analysis shows that this feature originates from the dominated behavior of some elements of the inverse of Hessian matrix. For the first time we point out that the strong compositional variation of these properties might be partially responsible for local fractures in alloys and mineral crystals under heating, highlighting the importance of subtle thermodynamic behavior of order-disorder systems.Comment: 17 pages, 10 figure

Magnetic moments of the low-lying JP= 1/2−J^P=\,1/2^-, 3/2−3/2^- Λ\Lambda resonances within the framework of the chiral quark model

The magnetic moments of the low-lying spin-parity $J^P=$ $1/2^-$, $3/2^-$ $\Lambda$ resonances, like, for example, $\Lambda(1405)$ $1/2^-$, $\Lambda(1520)$ $3/2^-$, as well as their transition magnetic moments, are calculated using the chiral quark model. The results found are compared with those obtained from the nonrelativistic quark model and those of unitary chiral theories, where some of these states are generated through the dynamics of two hadron coupled channels and their unitarization

Shock Induced Order-disorder Transformation in Ni3Al

The Hugoniot of Ni3Al with L12 structure is calculated with an equation of state (EOS) based on a cluster expansion and variation method from first principles. It is found that an order-disorder transition occurs at a shock pressure of 205GPa, corresponding to 3750K in temperature. On the other hand, an unexpected high melting temperature about 6955K is obtained at the same pressure, which is completely different from the case at ambient pressure where the melting point is slightly lower than the order-disorder transition temperature, implying the high pressure phase diagram has its own characteristics. The present work also demonstrates the configurational contribution is more important than electronic excitations in alloys and mineral crystals within a large range of temperature, and an EOS model based on CVM is necessary for high pressure metallurgy and theoretical Earth model.Comment: 14 pages, 5 figure

Understanding entangled spins in QED

The stability of two entangled spins dressed by electrons is studied by calculating the scattering phase shifts. The interaction between electrons is interpreted by fully relativistic QED and the screening effect is described phenomenologically in the Debye exponential form $e^{-\alpha r}$. Our results show that if the (Einstein-Podolsky-Rosen-) EPR-type states are kept stable under the interaction of QED, the spatial wave function must be parity-dependent. The spin-singlet state $s=0$ and the polarized state $\frac 1{\sqrt{2}}(\mid +-> -\mid -+>)$ along the z-axis\QTR{bf}{\}give rise to two different kinds of phase shifts\QTR{bf}{.} Interestingly, the interaction between electrons in the spin-singlet pair is found to be attractive. Such an attraction could be very useful when we extract the entangled spins from superconductors. A mechanism to filter the entangled spins is also discussed.Comment: 6 pages, 3 figures. changes adde

Reliable Cost Prediction and Control for Intelligent Manufacture: A Key Performance Indicator Perspective

Data Availability Statement: Not applicable. Acknowledgments: We would like to thank Primal Electro for providing the industrial data.Intelligent manufacturing is facing significant challenges in adapting to the ever-changing equipment, instrumentation, process and economics. Such a trend together with the pressure to reliably control and contain production costs means that frequent adjusting decisions are required to adapt to incessant volatility imposed on manufacturing systems. Under this circumstance, cost-effective and quality-guaranteed manufacturing strategies would be the most logical route to reducing production costs. In this paper, a novel dynamical cost prediction and control (CPC) model is proposed to support collective decision-making in intelligent manufacturing, where the model output is the real-time prediction of possible manufacturing costs, while the inputs are generic manufacturing key performance indicators covering inventory, product quality, production efficiency, resource utilisation and environmental impact. This proposed CPC model distinguishes itself from existing ones for its capability to translate manufacturing data (at both the physical level and operation management level) into financial metrics that contribute to forming a common language between engineering, financial and administrative departments of an enterprise. The case study about the assembly line of optoelectronic devices demonstrates that, although different enterprise departments have different priorities, our CPC model helps them to achieve certain consensus on intended production that finally creates satisfactory profitability for the company at controlled manufacturing costs.Natural Science Foundation of Sichuan Province of China under Grant 23NSFSC1427; National Natural Science Foundation of China under Grants U2330206, U2230206, 62173068l European Union’s Horizon 2020 Research and Innovation Programme under Grant 820677 (IQONIC)