Elastic-Plastic Finite Element Analysis of Fatigue Crack Growth in Mode 1 and Mode 2 Conditions

Presented is an alternate cost-efficient and accurate elastic-plastic finite element procedure to analyze fatigue crack closure and its effects under general spectrum loading. Both Modes 1 and 2 type cycling loadings are considered. Also presented are the results of an investigation, using the newly developed procedure, of various factors that cause crack growth acceleration or retardation and delay effects under high-to-low, low-to-high, single overload, and constant amplitude type cyclic loading in a Mode 1 situation. Further, the results of an investigation of a centercracked panel under external pure shear (Mode 2) cyclic loading, of constant amplitude, are reported

Programmable reconfiguration of Physarum machines

Plasmodium of Physarum polycephalum is a large cell capable of solving graph-theoretic, optimization and computational geometry problems due to its unique foraging behavior. Also the plasmodium is unique biological substrate that mimics universal storage modification machines, namely the Kolmogorov-Uspensky machine. In the plasmodium implementation of the storage modification machine data are represented by sources of nutrients and memory structure by protoplasmic tubes connecting the sources. In laboratory experiments and simulation we demonstrate how the plasmodium-based storage modification machine can be programmed. We show execution of the following operations with active zone (where computation occurs): merge two active zones, multiple active zone, translate active zone from one data site to another, direct active zone. Results of the paper bear two-fold value: they provide a basis for programming unconventional devices based on biological substrates and also shed light on behavioral patterns of the plasmodium

Natural Computing and Beyond

This book contains the joint proceedings of the Winter School of Hakodate (WSH) 2011 held in Hakodate, Japan, March 15–16, 2011, and the 6th International Workshop on Natural Computing (6th IWNC) held in Tokyo, Japan, March 28–30, 2012, organized by the Special Interest Group of Natural Computing (SIG-NAC), the Japanese Society for Artificial Intelligence (JSAI). This volume compiles refereed contributions to various aspects of natural computing, ranging from computing with slime mold, artificial chemistry, eco-physics, and synthetic biology, to computational aesthetics

Revisiting the Rist diagram for predicting operating conditions in blast furnaces with multiple injections

Background: The Rist diagram is useful for predicting changes in blast furnaces when the operating conditions are modified. In this paper, we revisit this methodology to provide a general model with additions and corrections. The reason for this is to study a new concept proposal that combines oxygen blast furnaces with Power to Gas technology. The latter produces synthetic methane by using renewable electricity and CO2 to partly replace the fossil input in the blast furnace. Carbon is thus continuously recycled in a closed loop and geological storage is avoided. Methods: The new model is validated with three data sets corresponding to (1) an air-blown blast furnace without auxiliary injections, (2) an air-blown blast furnace with pulverized coal injection and (3) an oxygen blast furnace with top gas recycling and pulverized coal injection. The error is below 8% in all cases. Results: Assuming a 280 tHM/h oxygen blast furnace that produces 1154 kgCO2/tHM, we can reduce the CO2 emissions between 6.1% and 7.4% by coupling a 150 MW Power to Gas plant. This produces 21.8 kg/tHM of synthetic methane that replaces 22.8 kg/tHM of coke or 30.2 kg/tHM of coal. The gross energy penalization of the CO2 avoidance is 27.1 MJ/kgCO2 when coke is replaced and 22.4 MJ/kgCO2 when coal is replaced. Considering the energy content of the saved fossil fuel, and the electricity no longer consumed in the air separation unit thanks to the O2 coming from the electrolyzer, the net energy penalizations are 23.1 MJ/kgCO2 and 17.9 MJ/kgCO2, respectively. Discussion: The proposed integration has energy penalizations greater than conventional amine carbon capture (typically 3.7 – 4.8 MJ/kgCO2), but in return it could reduce the economic costs thanks to diminishing the coke/coal consumption, reducing the electricity consumption in the air separation unit, and eliminating the requirement of geological storage

Limits on the integration of power to gas with blast furnace ironmaking

This article compares 16 Power to Gas integrations for blast furnace ironmaking by using 17 key performance indicators. The study includes 4 types of PtG (PtH2, PtSNG using pure CO2, PtSNG using treated BFG, and PtSNG using BFG), two types of blast furnaces (air-blown and oxygen) and two types of fossil replacement (coal or coke). The blast furnaces are modelled using the Rist diagram, validated with literature data (<2% deviation). For most cases, the decrease in total CO2 emissions is around 150–215 kgCO2/tHM per MW/(tHM/h) of electrolysis. The energy penalty (in terms of electricity consumption) was found to be mostly independent on the size of the PtG plant, but greatly dependent on the type of integration (10.1–20.6 MJ/kgCO2). If significant CO2 reductions are aimed, self-sufficiency in electricity consumption will not be achieved. In practice, the maximum PtG capacity to install is limited by the decrease in the flame temperature. In this context, the PtSNG integration consuming treated BFG, applied to OBF for coal replacement, provides the best results. Assuming a 500 tHM/h blast furnace, the PtG capacity of this concept could be as large as 490 MW and avoid up to 21% of the CO2 emissions

Flow-Induced Channel Formation in the Cytoplasm of Motile Cells

A model is presented to explain the development of flow channels within the cytoplasm of the plasmodium of the giant amoeba Physarum polycephalum. The formation of channels is related to the development of a self-organizing tubular network in large cells. Experiments indicate that the flow of cytoplasm is involved in the development and organization of these networks, and the mathematical model proposed here is motivated by recent experiments involving the observation of development of flow channel in small cells. A model of pressure-driven flow through a polymer network is presented in which the rate of flow increases the rate of depolymerization. Numerical solutions and asymptotic analysis of the model in one spatial dimension show that under very general assumptions this model predicts the formation of channels in response to flow