Calculation of Arc Power Losses in the Simplified Model of Intensively Blasted Electric Arc

In previous versions of the simplified model of intensively blasted electric arc burning in argon in the arc heater's anode channel, the authors used the constant total power loss coefficient for estimation of arc power losses in all anode channel individual parts. Using this approach, the model with relatively low computational complexity has led to very good agreement between the total computed and experimentally obtained values, but when the computed and measured power losses of individual anode channel segments have been compared, considerable differences have been revealed. In the modified model, theoretically computed net emission coefficient of argon is used in the energy equation to express the arc power losses. This way, satisfactory accordance is achieved between not only the total, but also partial measured and computed values. Exemplary results are given in figures and tables and discussed

Modelling of Intensively Blasted Electric Arc

The paper deals with a simplified model of an intensively blasted electric arc burning in the anode chan-nel of an arc heater. The model is based on the energy conservation law, continuity equation and Ohm’s law. For computation, transport and thermodynamic properties of working medium and real experimental results describing the external manifestation of the arc are necessary. Many experimental data have been collected during numerous experiments made out with a modular arc heater operated under various ex-perimental conditions, each experiment being characterized by the arc current, voltage, the sort and flow rate of working gas, and the flow rates and temperatures of cooling water in individual segments of the device. In the presented model a rectangular temperature profile of the arc is used. A dependency of the arc column radius rA on the distance from the cathode is prescribed and parameters of the function rA(z) are estimated using the total power balance at the output cross-section of the anode channel. Special at-tention is paid to the region near the beginning. The dependencies of the arc temperature and electric field intensity on the distance from the cathode are calculated and iterations are stopped if the sums of computed increments agree with the measured values. Computed dependencies are given in diagrams and discussed

Estimation of the Intensively Blasted Electric Arc Model Sensitivity to Selected Variables

Results of measurements carried out on the fabricated experimental modular-type arc heater serve as input data for the designed simplified model of the intensively blasted electric arc burning in argon inside the cylindrical arc heater's anode channel. The axial dependence of the arc temperature and radius is expressed using the exponent, the current density on the cathode tip and the arc temperature at the end of the near-cathode boundary layer. These quantities form the vector of state variables that is sought to minimize the value of the objective function expressing the deviations between measured and computed values. On a typical example, the paper demonstrates the sensitivity of the modelling to individual state variables

Reconciliation of weak pairwise spike-train correlations and highly coherent local field potentials across space

Chronic and acute implants of multi-electrode arrays that cover several mm$^2$ of neural tissue provide simultaneous access to population signals like extracellular potentials and the spiking activity of 100 or more individual neurons. While the recorded data may uncover principles of brain function, its interpretation calls for multiscale computational models with corresponding spatial dimensions and signal predictions. Such models can facilitate the search of mechanisms underlying observed spatiotemporal activity patterns in cortex. Multi-layer spiking neuron network models of local cortical circuits covering ~1 mm$^2$ have been developed, integrating experimentally obtained neuron-type specific connectivity data and reproducing features of in-vivo spiking statistics. With forward models, local field potentials (LFPs) can be computed from the simulated spiking activity. To account for the spatial scale of common neural recordings, we extend a local network and LFP model to 4x4 mm$^2$. The upscaling preserves the neuron densities, and introduces distance-dependent connection probabilities and delays. As detailed experimental connectivity data is partially lacking, we address this uncertainty in model parameters by testing parameter combinations within biologically plausible bounds. Based on model predictions of spiking activity and LFPs, we find that the upscaling procedure preserves the overall spiking statistics of the original model and reproduces asynchronous irregular spiking across populations and weak pairwise spike-train correlations observed in sensory cortex. In contrast with the weak spike-train correlations, the correlation of LFP signals is strong and distance-dependent, compatible with experimental observations. Enhanced spatial coherence in the low-gamma band may explain the recent experimental report of an apparent band-pass filter effect in the spatial reach of the LFP.Comment: 44 pages, 9 figures, 5 table

Runtime Construction of Large-Scale Spiking Neuronal Network Models on GPU Devices

Simulation speed matters for neuroscientific research: this includes not only how quickly the simulated model time of a large-scale spiking neuronal network progresses but also how long it takes to instantiate the network model in computer memory. On the hardware side, acceleration via highly parallel GPUs is being increasingly utilized. On the software side, code generation approaches ensure highly optimized code at the expense of repeated code regeneration and recompilation after modifications to the network model. Aiming for a greater flexibility with respect to iterative model changes, here we propose a new method for creating network connections interactively, dynamically, and directly in GPU memory through a set of commonly used high-level connection rules. We validate the simulation performance with both consumer and data center GPUs on two neuroscientifically relevant models: a cortical microcircuit of about 77,000 leaky-integrate-and-fire neuron models and 300 million static synapses, and a two-population network recurrently connected using a variety of connection rules. With our proposed ad hoc network instantiation, both network construction and simulation times are comparable or shorter than those obtained with other state-of-the-art simulation technologies while still meeting the flexibility demands of explorative network modeling

Retention of arsenic and selenium compounds present in coal combustion and gasification flue gases using activated carbons

7 pages, 7 figures, 6 tables.-- Printed version published Aug 2007.The emission of potentially toxic compounds of arsenic and selenium present in flue gases from coal combustion and gasification processes has led to the need for gas cleaning systems capable of reducing their content. This work is focused on the capture of these elements in activated carbons which have proven to have good retention capacities for mercury compounds in gas phase. Two commercial activated carbons (Norit RBHG3 and Norit RB3) and a carbon prepared via activation of a pyrolysed coal (CA) were tested in simulated coal combustion and gasification atmospheres in a laboratory scale reactor. Arsenic and selenium compounds were retained to different extents on these carbons, retention efficiency depending mainly on the speciation of the element, which in turn depends on the gas atmosphere. Arsenic retention was similar in both combustion and gasification atmospheres unlike selenium retention. Moreover the retention of arsenic was lower than that of selenium.This work was carried out with the financial support of ECSC (7220-ED/095). We are also grateful to our colleagues in ICB (CSIC) R. Juan and C. Ruiz who prepared the CA activated carbon and Amelia Martínez Alonso of INCAR who assisted us in the textural characterization.Peer reviewe

Phenomenological modeling of diverse and heterogeneous synaptic dynamics at natural density

This chapter sheds light on the synaptic organization of the brain from the perspective of computational neuroscience. It provides an introductory overview on how to account for empirical data in mathematical models, implement them in software, and perform simulations reflecting experiments. This path is demonstrated with respect to four key aspects of synaptic signaling: the connectivity of brain networks, synaptic transmission, synaptic plasticity, and the heterogeneity across synapses. Each step and aspect of the modeling and simulation workflow comes with its own challenges and pitfalls, which are highlighted and addressed in detail.Comment: 35 pages, 3 figure

Relationship between solidification microstructure and hot cracking susceptibility for continuous casting of low-carbon and high-strength low-alloyed steels: A phase-field study

© The Minerals, Metals & Materials Society and ASM International 2013Hot cracking is one of the major defects in continuous casting of steels, frequently limiting the productivity. To understand the factors leading to this defect, microstructure formation is simulated for a low-carbon and two high-strength low-alloyed steels. 2D simulation of the initial stage of solidification is performed in a moving slice of the slab using proprietary multiphase-field software and taking into account all elements which are expected to have a relevant effect on the mechanical properties and structure formation during solidification. To account for the correct thermodynamic and kinetic properties of the multicomponent alloy grades, the simulation software is online coupled to commercial thermodynamic and mobility databases. A moving-frame boundary condition allows traveling through the entire solidification history starting from the slab surface, and tracking the morphology changes during growth of the shell. From the simulation results, significant microstructure differences between the steel grades are quantitatively evaluated and correlated with their hot cracking behavior according to the Rappaz-Drezet-Gremaud (RDG) hot cracking criterion. The possible role of the microalloying elements in hot cracking, in particular of traces of Ti, is analyzed. With the assumption that TiN precipitates trigger coalescence of the primary dendrites, quantitative evaluation of the critical strain rates leads to a full agreement with the observed hot cracking behavior. © 2013 The Minerals, Metals & Materials Society and ASM International