Using conservation laws to infer deep learning model accuracy of Richtmyer-Meshkov instabilities

Richtmyer-Meshkov Instability (RMI) is a complicated phenomenon that occurs when a shockwave passes through a perturbed interface. Over a thousand hydrodynamic simulations were performed to study the formation of RMI for a parameterized high velocity impact. Deep learning was used to learn the temporal mapping of initial geometric perturbations to the full-field hydrodynamic solutions of density and velocity. The continuity equation was used to include physical information into the loss function, however only resulted in very minor improvements at the cost of additional training complexity. Predictions from the deep learning model appear to accurately capture temporal RMI formations for a variety of geometric conditions within the domain. First principle physical laws were investigated to infer the accuracy of the model's predictive capability. While the continuity equation appeared to show no correlation with the accuracy of the model, conservation of mass and momentum were weakly correlated with accuracy. Since conservation laws can be quickly calculated from the deep learning model, they may be useful in applications where a relative accuracy measure is needed

Obtaining non-linear orthotropic material models for PVC-coated polyester via inverse bubble inflation

Thesis (MEng)--Stellenbosch University, 2016.ENGLISH ABSTRACT: Uniaxial tests in the warp, fill, and 45° bias direction were performed on PVCcoated polyester to determine a non-linear orthotropic material model. Optimization was used to minimize the load displacement error of the uniaxial test results and uniaxial finite element models. A method for determining non-linear orthotropic material models from an inverse bubble inflation test is described. The inverse bubble inflation method is demonstrated with a known non-linear orthotropic material model. Inverse bubble inflation analyses were performed on four PVC-coated polyester samples, and a unique non-linear orthotropic material model was determined from each sample. Three point bending tests of inflatable PVC-coated polyester cylinders were used to compare and validate the material models. Finite element models were created replicating the three point bending tests. It was shown that the bubble material models overestimate the stiffness of the inflatable beams, while the uniaxial material model underestimates the stiffness.AFRIKAANSE OPSOMMING: Eenassige (of uniaksiale) toetse in die skering-, inslag- en 45° skuins-rigtings is uitgevoer op PVC -bedekte poliëster om 'n nie-liniêre ortotropiese materiaal model vas te stel. Optimering is gebruik om die ladingsverplasingsfout van die uniaksiaaltoets se resultate en uniaksiaal eindige element-modelle te minimeer. 'n Metode vir die vasstelling van nie-liniêre ortotropiese materiaalmodelle vanaf 'n omgekeerde borrel-opblaastoets word beskryf. Die omgekeerde borrel-opblaasmetode word gedemonstreer met 'n bekende nie-liniêre ortotropiese materiaalmodel. Omgekeerde borrel-opblaas-analise is uitgevoer op vier PVC-bedekte poliëster voorbeelde, en 'n unieke nie-liniêre ortotropiese materiaalmodel is vasgestel uit elke voorbeeld. Drie-punt buigtoetse op die opblaasbare PVC-bedekte poliëster-silinders is gebruik om die materiaalmodelle te vergelyk en te verifieer. Eindige element-modelle is geskep deur die drie-punt toetse te dupliseer. Die resultate het gewys dat die borrel-materiaalmodelle die styfheid van die opblaasbare balke oorskat, en die uniaksiale materiaalmodel die styfheid onderskat

X-ray analysis of two antibiotic-synthesizing bacterial ester hydrolases: preliminary results

α-Amino-acid ester hydrolases are multimeric enzymes of potential use in antibiotic production. Knowledge of their structure could help to engineer these enzymes into economically viable biocatalysts. The α-amino-acid ester hydrolases from Xanthomonas citri and Acetobacter turbidans have been crystallized. The X. citri enzyme crystallizes in a primitive monoclinic space group (unit-cell parameters a = 90.1, b = 125.8, c = 132.1 Å, β = 90.9°). The A. turbidans enzyme crystallizes in both a primitive orthorhombic (a = 99.1, b = 104.9, c = 284.9 Å) and a body-centred cubic space group with a = b = c = 342.2 Å. From both enzymes, diffraction-quality crystals (resolution 3.0 Å or better) were obtained. Data-collection statistics are reported for data sets from both enzymes.

CCDC 198867: Experimental Crystal Structure Determination

Related Article: O.K.B.Staal, D.J.Beetstra, A.P.Jekel, B.Hessen, J.H.Teuben, P.Stepnicka, R.Gyepes, M.Horacek, J.Pinkas, K.Mach|2003|Collect.Czech.Chem.Commun.|68|1119|doi:10.1135/cccc20031119,An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.

Sequence context-specific profiles for homology searching

Sequence alignment and database searching are essential tools in biology because a protein's function can often be inferred from homologous proteins. Standard sequence comparison methods use substitution matrices to find the alignment with the best sum of similarity scores between aligned residues. These similarity scores do not take the local sequence context into account. Here, we present an approach that derives context-specific amino acid similarities from short windows centered on each query sequence residue. Our results demonstrate that the sequence context contains much more information about the expected mutations than just the residue itself. By employing our context-specific similarities (CS-BLAST) in combination with NCBI BLAST, we increase the sensitivity more than 2-fold on a difficult benchmark set, without loss of speed. Alignment quality is likewise improved significantly. Furthermore, we demonstrate considerable improvements when applying this paradigm to sequence profiles: Two iterations of CSI-BLAST, our context-specific version of PSI-BLAST, are more sensitive than 5 iterations of PSI-BLAST. The paradigm for biological sequence comparison presented here is very general. It can replace substitution matrices in sequence- and profile-based alignment and search methods for both protein and nucleotide sequences