Computation, Volume 5, Issue 3 (September 2017) – 10 articles

Among the various blast load equations, the Kingery-Bulmash equation is applicable to both a free-air burst and a surface burst that enables calculations of the parameters of a pressure-time history curve. On the other hand, this equation is quite complicated. This paper proposes a modified equation that may replace the conventional Kingery-Bulmash equation. The proposed modified equation, which was constructed by performing curve-fitting of this equation, requires a brief calculation process with a simpler equation compared to the original equation. The modified equation is also applicable to both types of bursts and has the same calculable scaled distance range as the conventional equation. The calculation results obtained using the modified equation were similar to the results obtained from the original equation with a less than 1% difference. Full article

Accuracy improvement is among the primary key research focuses in the area of recommender systems. Traditionally, recommender systems work on two sets of entities, Users and Items, to estimate a single rating that represents a user’s acceptance of an item. This technique was later extended to multi-criteria recommender systems that use an overall rating from multi-criteria ratings to estimate the degree of acceptance by users for items. The primary concern that is still open to the recommender systems community is to find suitable optimization algorithms that can explore the relationships between multiple ratings to compute an overall rating. One of the approaches for doing this is to assume that the overall rating as an aggregation of multiple criteria ratings. Given this assumption, this paper proposed using feed-forward neural networks to predict the overall rating. Five powerful training algorithms have been tested, and the results of their performance are analyzed and presented in this paper. Full article

In this work, we summarize the recent progress made in constructing time-dependent density-functional theory (TDDFT) exchange-correlation (XC) kernels capable to describe excitonic effects in semiconductors and apply these kernels in two important cases: a “classic” bulk semiconductor, GaAs, with weakly-bound excitons and a novel two-dimensional material, MoS₂, with very strongly-bound excitonic states. Namely, after a brief review of the standard many-body semiconductor Bloch and Bethe-Salpether equation (SBE and BSE) and a combined TDDFT+BSE approaches, we proceed with details of the proposed pure TDDFT XC kernels for excitons. We analyze the reasons for successes and failures of these kernels in describing the excitons in bulk GaAs and monolayer MoS₂, and conclude with a discussion of possible alternative kernels capable of accurately describing the bound electron-hole states in both bulk and two-dimensional materials. Full article

A novel computational fluid dynamics-population balance model (CFD-PBM) for the simulation of gas mixing in activated sludge (i.e., an opaque non-Newtonian liquid) in a bubble column is developed and described to solve the problem of measuring the hydrodynamic behavior of opaque non-Newtonian liquid-gas two-phase flow. We study the effects of the inlet position and liquid-phase properties (water/activated sludge) on various characteristics, such as liquid flow field, gas hold-up, liquid dynamic viscosity, and volume-averaged bubble diameter. As the inlet position changed, two symmetric vortices gradually became a single main vortex in the flow field in the bubble column. In the simulations, when water was in the liquid phase, the global gas hold-up was higher than when activated sludge was in the liquid phase in the bubble column, and a flow field that was dynamic with time was observed in the bubble column. Additionally, when activated sludge was used as the liquid phase, no periodic velocity changes were found. When the inlet position was varied, the non-Newtonian liquid phase had different peak values and distributions of (dynamic) liquid viscosity in the bubble column, which were related to the gas hold-up. The high gas hold-up zone corresponded to the low dynamic viscosity zone. Finally, when activated sludge was in the liquid phase, the volume-averaged bubble diameter was much larger than when water was in the liquid phase. Full article

The lattice Boltzmann method is an efficient computational fluid dynamics technique that can accurately model a broad range of complex systems. As well as single-phase fluids, it can simulate thermohydrodynamic systems and passive scalar advection. In recent years, it also gained attention as a means of simulating chemical phenomena, as interest in self-organization processes increased. This paper will present a widely-used and versatile lattice Boltzmann model that can simultaneously incorporate fluid dynamics, heat transfer, buoyancy-driven convection, passive scalar advection, chemical reactions and enthalpy changes. All of these effects interact in a physically accurate framework that is simple to code and readily parallelizable. As well as a complete description of the model equations, several example systems will be presented in order to demonstrate the accuracy and versatility of the method. New simulations, which analyzed the effect of a reversible reaction on the transport properties of a convecting fluid, will also be described in detail. This extra chemical degree of freedom was utilized by the system to augment its net heat flux. The numerical method outlined in this paper can be readily deployed for a vast range of complex flow problems, spanning a variety of scientific disciplines. Full article

The program TFF calculates stripping single-particle form factors for one-neutron transfer in prior representation with appropriate perturbative treatment of recoil. Coupled equations are then integrated along a semiclassical trajectory to obtain one- and two-neutron transfer amplitudes and probabilities within first- and second-order perturbation theory. Total and differential cross-sections are then calculated by folding with a transmission function (obtained from a phenomenological imaginary absorption potential). The program description, user instructions and examples are discussed. Full article

This article gives an overview of the diverse range of teaching applications that can be realized using an interactive lattice Boltzmann simulation tool in fluid mechanics instruction and outreach. In an inquiry-based learning framework, examples are given of learning scenarios that address instruction on scientific results, scientific methods or the scientific process at varying levels of student activity, from consuming to applying to researching. Interactive live demonstrations on portable hardware enable new and innovative teaching concepts for fluid mechanics, also for large audiences and in the early stages of the university education. Moreover, selected examples successfully demonstrate that the integration of high-fidelity CFD methods into fluid mechanics teaching facilitates high-quality student research work within reach of the current state of the art in the respective field of research. Full article

Biomedicine is a pillar of the collective, scientific effort of human self-discovery, as well as a major source of humanistic data codified primarily in biomedical documents. Despite their rigid structure, maintaining and updating a considerably-sized collection of such documents is a task of overwhelming complexity mandating efficient information retrieval for the purpose of the integration of clustering schemes. The latter should work natively with inherently multidimensional data and higher order interdependencies. Additionally, past experience indicates that clustering should be semantically enhanced. Tensor algebra is the key to extending the current term-document model to more dimensions. In this article, an alternative keyword-term-document strategy, based on scientometric observations that keywords typically possess more expressive power than ordinary text terms, whose algorithmic cornerstones are third order tensors and MeSH ontological functions, is proposed. This strategy has been compared against a baseline using two different biomedical datasets, the TREC (Text REtrieval Conference) genomics benchmark and a large custom set of cognitive science articles from PubMed. Full article

The author demonstrates a stable Lagrangian solid modeling method, tracking the interactions of solid mass particles rather than using a meshed grid. This numerical method avoids the problem of tensile instability often seen with smooth particle applied mechanics by having the solid particles apply stresses expected with Hooke’s law, as opposed to using a smoothing function for neighboring solid particles. This method has been tested successfully with a bar in tension, compression, and shear, as well as a disk compressed into a flat plate, and the numerical model consistently matched the analytical Hooke’s law as well as Hertz contact theory for all examples. The solid modeling numerical method was then built into a 2-D model of a pressure vessel, which was tested with liquid water particles under pressure and simulated with smoothed particle hydrodynamics. This simulation was stable, and demonstrated the feasibility of Lagrangian specification modeling for fluid–solid interactions. Full article

Much of biology-inspired computer science is based on the Central Dogma, as implemented with genetic algorithms or evolutionary computation. That 60-year-old biological principle based on the genome, transcriptome and proteasome is becoming overshadowed by a new paradigm of complex ordered associations and connections between layers of biological entities, such as interactomes, metabolomics, etc. We define a new hierarchical concept as the “Connectosome”, and propose new venues of computational data structures based on a conceptual framework called “Grand Ensemble” which contains the Central Dogma as a subset. Connectedness and communication within and between living or biology-inspired systems comprise ensembles from which a physical computing system can be conceived. In this framework the delivery of messages is filtered by size and a simple and rapid semantic analysis of their content. This work aims to initiate discussion on the Grand Ensemble in network biology as a representation of a Persistent Turing Machine. This framework adding interaction and persistency to the classic Turing-machine model uses metrics based on resilience that has application to dynamic optimization problem solving in Genetic Programming. Full article