Physics Informed Machine Learning of SPH: Machine Learning Lagrangian Turbulence

Smoothed particle hydrodynamics (SPH) is a mesh-free Lagrangian method for obtaining approximate numerical solutions of the equations of fluid dynamics; which has been widely applied to weakly- and strongly compressible turbulence in astrophysics and engineering applications. We present a learn-able hierarchy of parameterized and "physics-explainable" Lagrangian based fluid simulators using both physics based parameters and Neural Networks (NNs) as universal function approximators. This hierarchy of parameterized Lagrangian models gradually introduces more SPH based structure, which we show improves interpretability, generalizability (over larger ranges of time scales and Mach numbers), preservation of physical symmetries (corresponding to conservation of linear and angular momentum), and requires less training data. Our learning algorithm develops a mixed mode approach, mixing forward and reverse mode automatic differentiation with local sensitivity analyses to efficiently perform gradient based optimization. We train this hierarchy on both weakly compressible SPH and DNS data, and show that our physics informed learning method is capable of: (a) solving inverse problems over the physically interpretable parameter space, as well as over the space of NN parameters; (b) learning Lagrangian statistics of turbulence (interpolation); (c) combining Lagrangian trajectory based, probabilistic, and Eulerian field based loss functions; (d) extrapolating beyond training sets into more complex regimes of interest; (e) learning new parameterized smoothing kernels better suited to weakly compressible DNS turbulence data

Numerical investigation of Differential Biological-Models via GA-Kansa Method Inclusive Genetic Strategy

In this paper, we use Kansa method for solving the system of differential equations in the area of biology. One of the challenges in Kansa method is picking out an optimum value for Shape parameter in Radial Basis Function to achieve the best result of the method because there are not any available analytical approaches for obtaining optimum Shape parameter. For this reason, we design a genetic algorithm to detect a close optimum Shape parameter. The experimental results show that this strategy is efficient in the systems of differential models in biology such as HIV and Influenza. Furthermore, we prove that using Pseudo-Combination formula for crossover in genetic strategy leads to convergence in the nearly best selection of Shape parameter.Comment: 42 figures, 23 page

A framework for quantification and physical modeling of cell mixing applied to oscillator synchronization in vertebrate somitogenesis

In development and disease, cells move as they exchange signals. One example is found in vertebrate development, during which the timing of segment formation is set by a ‘segmentation clock’, in which oscillating gene expression is synchronized across a population of cells by Delta-Notch signaling. Delta-Notch signaling requires local cell-cell contact, but in the zebrafish embryonic tailbud, oscillating cells move rapidly, exchanging neighbors. Previous theoretical studies proposed that this relative movement or cell mixing might alter signaling and thereby enhance synchronization. However, it remains unclear whether the mixing timescale in the tissue is in the right range for this effect, because a framework to reliably measure the mixing timescale and compare it with signaling timescale is lacking. Here, we develop such a framework using a quantitative description of cell mixing without the need for an external reference frame and constructing a physical model of cell movement based on the data. Numerical simulations show that mixing with experimentally observed statistics enhances synchronization of coupled phase oscillators, suggesting that mixing in the tailbud is fast enough to affect the coherence of rhythmic gene expression. Our approach will find general application in analyzing the relative movements of communicating cells during development and disease.Fil: Uriu, Koichiro. Kanazawa University; JapónFil: Bhavna, Rajasekaran. Max Planck Institute of Molecular Cell Biology and Genetics; Alemania. Max Planck Institute for the Physics of Complex Systems; AlemaniaFil: Oates, Andrew C.. Francis Crick Institute; Reino Unido. University College London; Reino UnidoFil: Morelli, Luis Guillermo. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigación en Biomedicina de Buenos Aires - Instituto Partner de la Sociedad Max Planck; Argentina. Max Planck Institute for Molecular Physiology; Alemania. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Física; Argentin

Structural response and optimization of airtight blast door under gas explosion load

Airtight blast door, as one of the key components of a rescue device or a ventilating device in underground coal mine, which can not only guarantee the normal operation ventilation system, but also can prevent the propagation of shock wave and invasion of toxic gases. Therefore, high structural stability and safety is fundamental when designing a door. An airtight blast door was developed and optimized based on static analysis and topological optimization, and dynamic response analysis of the optimized airtight blast door subjected to gas explosion load was conducted using a novel approach proposed in this paper-the FEM-SPH contact algorithm. Results showed that the main component weight of this kind of door is 27.4 % smaller than the original one without reducing the blast and impact behavior, the maximum displacement and stress of the optimization door obtained by FEM-SPH contact algorithm (dynamic response) are much larger than those using static mechanical analysis. The FEM-SPH contact algorithm and typical optimization method as well as the example presented in this paper are helpful for the original design and optimization of other products. Some conducive suggestions were recommended based on the simulation results

Recent tendencies in the use of optimization techniques in geotechnics:a review

The use of optimization methods in geotechnics dates back to the 1950s. They were used in slope stability analysis (Bishop) and evolved to a wide range of applications in ground engineering. We present here a non-exhaustive review of recent publications that relate to the use of different optimization techniques in geotechnical engineering. Metaheuristic methods are present in almost all the problems in geotechnics that deal with optimization. In a number of cases, they are used as single techniques, in others in combination with other approaches, and in a number of situations as hybrids. Different results are discussed showing the advantages and issues of the techniques used. Computational time is one of the issues, as well as the assumptions those methods are based on. The article can be read as an update regarding the recent tendencies in the use of optimization techniques in geotechnics

Multi-method-modeling of interacting galaxies. I. A unique scenario for NGC 4449?

(abridged) We combined several N-body methods in order to investigate the interaction scenario between NGC 4449 and DDO 125, a close companion in projected space. In a first step fast restricted N-body models are used to confine a region in parameter space reproducing the main observational features. In a second step a genetic algorithm is applied for a uniqueness test of our preferred parameter set. We show that our genetic algorithm reliably recovers orbital parameters, provided that the data are sufficiently accurate, i.e. all the key features are included. In the third step the results of the restricted N-body models are compared with self-consistent N-body simulations. In the case of NGC 4449, the applicability of the simple restricted N-body calculations is demonstrated. Additionally, it is shown that the HI gas can be modeled here by a purely stellar dynamical approach. In a series of simulations, we demonstrate that the observed features of the extended HI disc can be explained by a gravitational interaction between NGC 4449 and DDO 125. According to these calculations the closest approach between both galaxies happened $\sim 4-6 \cdot 10^8$ yr ago at a minimum distance of $\sim 25$ kpc on a parabolic or slightly elliptic orbit. In the case of an encounter scenario, the dynamical mass of DDO 125 should not be smaller than 10% of NGC 4449's mass. Before the encounter, the observed HI gas was arranged in a disc with a radius of 35-40 kpc around the center of NGC 4449. It had the same orientation as the central ellipsoidal HI structure. The origin of this disc is still unclear, but it might have been caused by a previous interaction.Comment: 19 pages with 19 figures, accepted for publication in Astron. & Astrophys., a full PostScript version is available at http://www.astrophysik.uni-kiel.de/pershome/theis/pub.htm

ASCR/HEP Exascale Requirements Review Report

This draft report summarizes and details the findings, results, and recommendations derived from the ASCR/HEP Exascale Requirements Review meeting held in June, 2015. The main conclusions are as follows. 1) Larger, more capable computing and data facilities are needed to support HEP science goals in all three frontiers: Energy, Intensity, and Cosmic. The expected scale of the demand at the 2025 timescale is at least two orders of magnitude -- and in some cases greater -- than that available currently. 2) The growth rate of data produced by simulations is overwhelming the current ability, of both facilities and researchers, to store and analyze it. Additional resources and new techniques for data analysis are urgently needed. 3) Data rates and volumes from HEP experimental facilities are also straining the ability to store and analyze large and complex data volumes. Appropriately configured leadership-class facilities can play a transformational role in enabling scientific discovery from these datasets. 4) A close integration of HPC simulation and data analysis will aid greatly in interpreting results from HEP experiments. Such an integration will minimize data movement and facilitate interdependent workflows. 5) Long-range planning between HEP and ASCR will be required to meet HEP's research needs. To best use ASCR HPC resources the experimental HEP program needs a) an established long-term plan for access to ASCR computational and data resources, b) an ability to map workflows onto HPC resources, c) the ability for ASCR facilities to accommodate workflows run by collaborations that can have thousands of individual members, d) to transition codes to the next-generation HPC platforms that will be available at ASCR facilities, e) to build up and train a workforce capable of developing and using simulations and analysis to support HEP scientific research on next-generation systems.Comment: 77 pages, 13 Figures; draft report, subject to further revisio