Finite-Volume Filtering in Large-Eddy Simulations Using a Minimum-Dissipation Model

Large-eddy simulation (LES) seeks to predict the dynamics of the larger eddies in turbulent flow by applying a spatial filter to the Navier-Stokes equations and by modeling the unclosed terms resulting from the convective non-linearity. Thus the (explicit) calculation of all small-scale turbulence can be avoided. This paper is about LES-models that truncate the small scales of motion for which numerical resolution is not available by making sure that they do not get energy from the larger, resolved, eddies. To identify the resolved eddies, we apply Schumann’s filter to the (incompressible) Navier-Stokes equations, that is the turbulent velocity field is filtered as in a finite-volume method. The spatial discretization effectively act as a filter; hence we define the resolved eddies for a finite-volume discretization. The interpolation rule for approximating the convective flux through the faces of the finite volumes determines the smallest resolved length scale δ. The resolved length δ is twice as large as the grid spacing h for an usual interpolation rule. Thus, the resolved scales are defined with the help of box filter having diameter δ= 2 h. The closure model is to be chosen such that the solution of the resulting LES-equations is confined to length scales that have at least the size δ. This condition is worked out with the help of Poincarés inequality to determine the amount of dissipation that is to be generated by the closure model in order to counterbalance the nonlinear production of too small, unresolved scales. The procedure is applied to an eddy-viscosity model using a uniform mesh

Iterative signal processing for coded LSTF architectures

For high speed orthogonal frequency division multiplexing (OFDM) plus multiple-input multiple-output (MIMO) multiplexing, a new coded layered space-time-frequency (LSTF) architecture with iterative signal processing at the receiver is proposed, where each independent codeword is threaded in the three-dimensional (3-D) space-time-frequency transmission resource array. The iterative receiver structure is adopted consisting of a joint minimum-mean-square-error soft-interference-cancellation (MMSE-SIC) detector and the maximum a postetiori (MAP) convolutional decoders. Simulation results show that the proposed LSTF architecture can achieve almost the same performance as the LSTF (i.e., LSTF-a) where coding is applied across the whole information stream. However, due to its structure of multiple parallel lower speed encoders/decoders with shorter codeword length, the proposed LSTF architecture can be more easily implemented than the LSTF-a

Biosynthesis and mode of action of the β-lactone antibiotic obafluorin

DNA sequencing technologies have advanced rapidly in the 21st century and there are now an abundance of microbial genomes available to mine in search of novel biosynthetic gene clusters and the bioactive natural products they encode. Whilst an enormously exciting prospect, this abundance of genomic data presents a challenge in determining how to select clusters for further study. To address this issue, this project focusses on the biosynthesis of the β-lactone antibiotic obafluorin produced by the soil bacterium Pseudomonas fluorescens. β-Lactones occur infrequently in nature but possess a variety of potent and valuable biological activities. They are commonly derived from β-hydroxy-α-amino acids, which are themselves privileged chiral building blocks in a variety of pharmacologically and agriculturally important natural products and medicines. I report the delineation of the entire obafluorin biosynthetic pathway using complementary mutagenesis and biochemical assay-based approaches. As part of this work I have been able to characterise ObaG, a novel PLP-dependent L-threonine transaldolase responsible for the biosynthesis of an unusual nonproteinogenic β-hydroxy-α-amino acid precursor from which the β-lactone ring of obafluorin is derived. Phylogenetic analysis has shed light on the evolutionary origin of this rare enzyme family and has identified further gene clusters encoding putative L-threonine transaldolases. Furthermore, I have been able to biochemically assay an entire intact nonribosomal peptide synthetase that displays a noncanonical domain architecture and is responsible for obafluorin assembly and β-lactone ring formation. These studies allowed both mechanism- and redundancy-guided genome mining strategies to be developed that might allow the specific targeting of novel chemistry in the uncharted reaches of the natural product world