Prediction of diesel fuel cold properties using artificial neural networks

In this paper, two neural networks, multilayer perceptron and networks with radial-basis function, were used to predict important cold properties of commercial diesel fuels, namely cloud point and cold filter plugging point. The developed models predict the named properties using cetane number, density, viscosity, contents of total aromatics, and distillation temperatures at 10, 50, and 90 vol. % recovery as input data. The training algorithms, number of hidden layer neurons, and number of training data points were optimized in order to obtain a model with optimal predictive ability. The results indicated better prediction of cloud and cold filter plugging points in the case of multilayer perceptron networks. The obtained absolute error mean for the optimal neural network models (0.58°C for the cloud point and 1.46°C for the cold filter plugging point) are within the range of repeatability of standard cold properties determination methods.     

BPC – A binary priority countdown protocol

In modern wireless ad hoc networks, with a high speed PHY, every collision means a significant loss of useful bandwidth. In the last few years different binary contention protocols have been introduced to address this problem. In this work we propose a novel binary contention protocol called binary priority countdown (BPC) protocol, whose goal is to reduce collisions as well as contention time. BPC uses a new priority countdown mechanism which exploits the efficiency of binary countdown, but the priority countdown process is not constrained to a single binary countdown round. This way, the priority space is not defined by the length of binary countdown round, like in other binary countdown protocols proposed in the literature, and arbitrary medium access priorities can be decremented through multiple binary countdown rounds if necessary. The ability of a new priority countdown mechanism to count down any priority number without changing the length of a binary countdown round, allows independent management of priority space. This “independence” of priority space introduces new optimization and adaptation possibilities. Collision memory effect is recognized and described. BPC protocol reveals connection between unary, binary and digit contention protocols. All three groups of protocols can now be seen as members of the same class of contention algorithms. Preliminary simulation results are shown.     

A comparative study of reaction models applied for chemical looping combustion

Kinetic models applicable for chemical looping combustion in conjunction with relevant experimental studies investigating carrier material kinetics are reviewed. Based on a selection of experimental investigations from literature, where both data at different temperature levels and different gaseous reactant compositions are provided, a broad range of commonly used kinetic models is reviewed. The reaction rate as function of the degree of conversion is addressed which is important if kinetic models are applied within simulations on chemical looping combustion like particle based methods, multiphase CFD-approaches or macroscopic models. Results obtained indicate that most of the models tend to fail towards higher degrees of conversion where reaction rate is rapidly declining. As an alternative to commonly used models, several empirical models are proposed for the conversion rate. The new models perform well and might lead to improved large scale simulations.     

Frictional contact analysis of functionally graded materials with Lagrange finite block method

Based on the one‐dimensional differential matrix derived from the Lagrange series expansion, the finite block method was recently developed to solve both the elasticity and transient heat conduction problems of anisotropic and functionally graded materials. In this paper, the formulation of the Lagrange finite block method with boundary type in the strong form is presented and applied to non‐conforming contact problems for the functionally graded materials subjected to either static or dynamic loads. The first order partial differential matrices are only needed both in the governing equations and in the Neumann boundary condition. By introducing the mapping technique, a block of quadratic type is transformed from the Cartesian coordinate of global system to the normalized coordinate with eight seeds. Time dependent partial differential equations are analyzed in the Laplace transformed domain and the Durbin's inversion method is applied to determine all the physical values in the time domain. Conforming and non‐conforming contacts are investigated by using the iterative algorithm with full load technique. Illustrative numerical examples are given and comparisons have been made with analytical solutions. Copyright © 2015 John Wiley & Sons, Ltd.     

Genome-Wide Association Analysis and Genomic Prediction of Thyroglobulin Plasma Levels

Thyroglobulin (Tg) is an iodoglycoprotein produced by thyroid follicular cells which acts as an essential substrate for thyroid hormone synthesis. To date, only one genome-wide association study (GWAS) of plasma Tg levels has been performed by our research group. Utilizing recent advancements in computation and modeling, we apply a Bayesian approach to the probabilistic inference of the genetic architecture of Tg. We fitted a Bayesian sparse linear mixed model (BSLMM) and a frequentist linear mixed model (LMM) of 7,289,083 variants in 1096 healthy European-ancestry participants of the Croatian Biobank. Meta-analysis with two independent cohorts (total n = 2109) identified 83 genome-wide significant single nucleotide polymorphisms (SNPs) within the ST6GAL1 gene (p<5×10−8). BSLMM revealed additional association signals on chromosomes 1, 8, 10, and 14. For ST6GAL1 and the newly uncovered genes, we provide physiological and pathophysiological explanations of how their expression could be associated with variations in plasma Tg levels. We found that the SNP-heritability of Tg is 17% and that 52% of this variation is due to a small number of 16 variants that have a major effect on Tg levels. Our results suggest that the genetic architecture of plasma Tg is not polygenic, but influenced by a few genes with major effects.     

Modeling of dibenzothiophene oxidative desulfurization using response surface methodology

The effect of reaction temperature, mixing speed and oxidant to catalyst volume ratio, including their interactions on the oxidative desulfurization of dibenzothiophene by using response surface methodology was studied. Hydrogen peroxide was used as oxidant and acetic acid as catalyst. The obtained model accurately predicts conversion of dibenzothiophene and the best conversion of 98.7% was observed at temperature 70°C, mixing speed of 1250 rpm and oxidant to catalyst volume ratio of 1:1. At high temperatures, a major limitation of the desulfurization process is the mass transfer and the high mixing speed is needed to achieve an efficient process.     

Performance of integration schemes in discrete element simulations of particle systems involving consecutive contacts

In this investigation, which is a follow-up study extending earlier work (Kruggel-Emden, Sturm, Wirtz, & Scherer, 2008), a realistic assessment of the performance of integration schemes in systems of moving particles and consecutive contacts is conducted. Linear contact models are applied throughout this work as they allow for an analytical solution of consecutive oblique impacts. The many-particle systems considered are the discharge of particles from a hopper and particle movement in a shaken container. Results for many-particle systems are robust with respect to the applied integration method and step size once particle interactions are resolved with a sufficient number of steps. The integration schemes are also evaluated based on consecutive particle/wall contacts. Integration of consecutive contacts in a discrete element framework implies repeatedly solving non-continuous systems of differential equations. Various termination conditions for the normal force models and adaptive time stepping for one-step integration methods are investigated. The effect of softened contacts on particle trajectories is discussed. Based on these insights, recommendations for the most accurate integration schemes are made.     

Development and testing of an interconnected multiphase CFD-model for chemical looping combustion

An interconnected multi-phase CFD model is developed capable of describing the transient behavior of a coupled chemical looping combustion systems comprising of both air and fuel reactors. The air reactor is modeled as a high velocity riser, the fuel reactor as a bubbling fluidized bed. The models of both reactors are implemented as separate CFD simulations allowing for an exchange of solid mass through time-dependent inlet and outlet boundary conditions as well as mass, momentum, heat and species sinks. The developed framework is applied to a chemical looping combustion system based on Mn₃O₄ as carrier material in combination with CH₄ as fuel gas. Starting from a base case, different system configurations are investigated. The results indicate clearly that interconnected multi-phase CFD models are well suited for the design process of coupled chemical looping systems.     

MR linear contact detection algorithm

Large‐scale discrete element simulations, as well as a whole range of related problems, involve contact of a large number of separate bodies and an efficient and robust contact detection algorithm is necessary. There has been a number of contact detection algorithms with total detection time proportional to N ln(N) (where N is the total number of separate bodies) reported in the past. In more recent years algorithms with total CPU time proportional to N have been developed. In this work, a novel contact detection algorithm with total detection time proportional to N is proposed. The performance of the algorithm is not influenced by packing density, while memory requirements are insignificant. The algorithm is applicable to systems comprising bodies of a similar size. The algorithm is named MR (Munjiza–Rougier: Munjiza devised the algorithm, Rougier implemented it). In the second part of the paper the algorithm is extended to particles of different sizes. The new algorithm is called MMR (multi‐step MR) algorithm. Copyright © 2005 John Wiley & Sons, Ltd.