Towards an Output-based Re-meshing for Turbomachinery Applications

The truncation error estimation methodology using topologically inconsistent fine and coarse meshes was presented. Estimated truncation error was weighted with an adjoint solution to obtain a robust output-based adaptation sensor. Re-meshing using Boxer and output-based sensor field was successfully applied to the simple cube test case showing almost an order of magnitude cost function error reduction as compared to the uniformly refined grid. More application examples are required including a more realistic turbulent cases e.g. turbine stator in order to investigate how useful is the methodology in practice. The key challenge for viscous flows is related to the treatment of boundary layer when performing re-meshing with Boxe

Output-based R-refinement and the Use of Geometric Multi-Grid for Truncation Error Estimation in CFD

Output-based R-refinement and the Use of Geometric Multigrid for Truncation Error Estimation in CF

Output-based mesh adaptation using geometric multi-grid for error estimation

PhDThe adjoint method in computational fluid dynamics (CFD) made shape optimisation affordable. However, the typical cost of the process is still at least an order of magnitude higher than obtaining a ow solution only. In this work, the author presents methods that help to further reduce the computational effort in optimisation. The fi rst method involves reducing the run-time of the flow solver; the second involves developing a low-cost error estimate that could be used to create a computationally less expensive grid without affecting the accuracy of an objective function. Implicit solvers are well-established in CFD, but their performance is often limited by the instabilities that arise in the initial convergence stage of the code. To address this issue, a methodology to stabilise an implicit solver using adaptive CFL number adjustment technique is implemented in the in-house code STAMPS. The CFL number is altered at each solver iteration based on the outcome of a line-search algorithm - the Armijo rule. It is shown that the building blocks of a line-search algorithm can be accurately and easily evaluated using automatic differentiation of the Tapenade source code transformation tool without a need to approximate derivatives of discrete system of ow equations. The line-search algorithm is also used to control re-evaluation of Jacobian/preconditioner between solver iterations, by detecting when the linear convergence regime was reached, and the spectra of system matrix eigenvalues are contractive. This work shows that the proposed combination of automatic CFL adjustment and system matrix re-evaluation control result in improvements in solver stability and reductions of the overall run-time of the code. A method of manufactured solution is used by the author for veri fication of the discretisation accuracy of the STAMPS solver, as well as for the development of local error estimation. The truncation error, which is defi ned as a difference between the continuous PDEs and its discrete approximation, can be evaluated exactly using a known manufactured solution and used for verifi cation of error estimation methodology. In this work, a novel low-cost method is presented that estimates the truncation error using building blocks of the geometric multi-grid solver. The methodology requires little implementation effort and uses the same set of multi-grid meshes as the solver. It is shown that a reasonable indication of high-error regions can be achieved, even though the coarse and fine meshes are topologically inconsistent. Although the truncation error can be directly used to obtain an adaptation sensor it is benefi cial to apply adjoint-weighting beforehand. The adjoint-weighting of the local truncation error gives an outputbased sensor that determines the effect of the local error on the objective function of interest. The output-based sensor can be effectively used for the goal-driven mesh adaptation/coarsening process. This work presents example applications of mesh refi nement driven by output-based sensor and mesh regeneration technique.EPSRC grant EP/K000128/1

A cartilage tissue engineering approach combining starch-polycaprolactone fibre mesh scaffolds with bovine articular chondrocytes

In the present work we originally tested the suitability of corn starch-polycaprolactone (SPCL) scaffolds for pursuing a cartilage tissue engineering approach. Bovine articular chondrocytes were seeded on SPCL scaffolds under dynamic conditions using spinner flasks (total of 4 scaffolds per spinner flask using cell suspensions of 0.5×106 cells/ml) and cultured under orbital agitation for a total of 6 weeks. Poly(glycolic acid) (PGA) non-woven scaffolds and bovine native articular cartilage were used as standard controls for the conducted experiments. PGA is a kind of standard in tissue engineering approaches and it was used as a control in that sense. The tissue engineered constructs were characterized at different time periods by scanning electron microscopy (SEM), hematoxylin-eosin (H&E) and toluidine blue stainings, immunolocalisation of collagen types I and II, and dimethylmethylene blue (DMB) assay for glycosaminoglycans (GAG) quantification assay. SEM results for SPCL constructs showed that the chondrocytes presented normal morphological features, with extensive cells presence at the surface of the support structures, and penetrating the scaffolds pores. These observations were further corroborated by H&E staining. Toluidine blue and immunohistochemistry exhibited extracellular matrix deposition throughout the 3D structure. Glycosaminoglycans, and collagen types I and II were detected. However, stronger staining for collagen type II was observed when compared to collagen type I. The PGA constructs presented similar features toSPCLat the end of the 6 weeks. PGA constructs exhibited higher amounts of matrix glycosaminoglycans when compared to the SPCL scaffolds. However, we also observed a lack of tissue in the central area of the PGA scaffolds. Reasons for these occurrences may include inefficient cells penetration, necrosis due to high cell densities, or necrosis related with acidic by-products degradation. Such situation was not detected in the SPCL scaffolds, indicating the much better biocompatibility of the starch based scaffolds

Gene-enhanced tissue engineering for dental hard tissue regeneration: (1) overview and practical considerations

Gene-based therapies for tissue regeneration involve delivering a specific gene to a target tissue with the goal of changing the phenotype or protein expression profile of the recipient cell; the ultimate goal being to form specific tissues required for regeneration. One of the principal advantages of this approach is that it provides for a sustained delivery of physiologic levels of the growth factor of interest. This manuscript will review the principals of gene-enhanced tissue engineering and the techniques of introducing DNA into cells. Part 2 will review recent advances in gene-based therapies for dental hard tissue regeneration, specifically as it pertains to dentin regeneration/pulp capping and periodontal regeneration

Immunophenotypic predictive profiling of BRCA1-associated breast cancer

The immunophenotypic predictive profile of BRCA1-associated cancers including major predictive markers, i.e., PARP-1, EGFR, c-kit, HER-2, and steroid hormones (ER/PR) that may have therapeutic relevance has not yet been reported in a comprehensive study. Using immunohistochemistry, we examined the expression of these proteins in a large cohort of BRCA1-associated breast cancers. PARP-1 immunoreactivity was found in 81.9%, EGFR in 43.6%, ER/PR in 17.9%, c-kit in 14.7%, and overexpression of HER-2 in 3.6% of cancers. For all markers studied, 8.2% of tumors were negative. Expression of only one predictive marker was found in 29.7% of cancers, and most frequently, it was PARP-1 (20.8%). In 62.1% of tumors, more than one predictive marker was expressed: PARP-1 and EGFR in 30.4%, PARP-1, and hormone receptors in 13.3% and PARP-1 with c-kit in 7.5% of all tumors. Coexpression of two or more other predictive markers was rare. There were significant differences in the median age at diagnosis of BRCA1-associated cancer between patients with ER+ vs. ER− and grades 1–2 vs. grade 3 tumors. These results demonstrate that BRCA1-associated cancers differ with respect to expression of proteins that are regarded as targets for specific therapies and that 92% of patients with BRCA1-associated cancers may benefit from one or several options for specific therapy (in addition to DNA damaging agents, e.g., cisplatin). About 8% of cancers which do not express therapeutic target proteins may not respond to such therapies. Knowledge of the immunophenotypic predictive profile may help with the recruitment of patients for trials of targeted therapies