Enhancement of the Mixing Efficiency for a Steam Boiler Premix Channel with a Surrogate Based Optimization

Global warming and the ever-increasing pollutants in the atmosphere force many governments to limit emissions. The use of methane as a fuel is widespread in the boiler industry, due to the low pollutant levels in its exhaust gas products. Nevertheless, in the combustion process, nitrogen and oxygen bind giving rise to a series of molecular compounds called NO x, which are considered pollutants because they react in the atmosphere causing the production of acid rain and reducing the level of ozone [1]. The aim of this work is to improve the mixture quality between fresh air, methane and recirculated exhaust gases introduced within Ecovapor Boiler's Mixing-Channel and, as consequence, to increase the combustion quality and limit the pollution production. The geometry is parameterized within Ansys Space Claim CAD software [2], and gas mixture flow is computed with Ansys Fluent solver [3]. To achieve these goals an automated shape optimization is adopted, which couples the Ansys Workbench environment to Dakota software [4]. In particular, a multi-objective genetic algorithm (MOGA) [5] combined with the Kriging response surface method is used, while the geometries are evaluated by solving for a compressible mixture of non-reacting gases the steady-state Reynolds Average NavierStokes (RANS) equations coupled with the kRealizable turbulence model [6]

The Wolf: The Last Remnants of the age of Sail in Southern Oman

This article looks at a specific southern Arabian sailing vessel named the Wolf (al-Dhi’b), in order to better understand the life of a coastal trader on the southern Arabian coast that lived in the last days of commercial sail. Vessels such as the Wolf carried local products such as sardines, abalone and frankincense to northern Oman and Yemen, returning with dates and necessary foodstuffs shipped to Aden from India and East Africa. The article examines the remains of the Wolf, based on data from multiple documentation surveys, in conjunction with information gained from oral history interviews in order to highlight the central role that vessels such as the Wolf played in the maritime economic and social networks of the region

On the algebraic modifications of traditional turbulence models to predict by-pass and separation induced transition

Many reliable and robust turbulence models are nowadays available for the ReynoldsAveraged Navier-Stokes (RANS) equations to accurately simulate a wide range of engineering flows. However, turbulence models are not able to correctly predict flow phenomena with low to moderate Reynolds numbers, which are characterized by strong transitions. Laminar to turbulent transition is common in aerospace, turbomachinery, maritime, and automotive. Therefore, numerical models able to accurately predict transitional flows are mandatory to overcome the limits of turbulence models for the efficient design of many industrial applications. A modified version of the k-~ and Spalart-Allmaras turbulence models is proposed in order to predict transition due to the bypass and separation-induced modes. The modifications here proposed are based on the kand the SA-BCM transition models. Both the models are correlation-based algebraic transition models that relies on local flow information and include an intermittency function instead of an intermittency equation. The basic idea behind the models is that, instead of writing a transport equation for intermittency, an intermittency function multiplies the production terms of the turbulent working variables of the formulation of the turbulence models. In particular, the turbulence production is damped until it satisfies some transition onset requirements. The proposed models are implemented in a high-order discontinuous Galerkin (dG) solver and validated on different transitional benchmark cases from the ERCOFTAC T3 suite, with bypass (T3A, T3Aand T3B) and separation-induced (T3L1 and T3L3) transition

Development of a discontinuous Galerkin solver for the simulation of turbine stages

A high-order Discontinuous Galerkin (DG) solver is assessed in the computation of the flow through an Organic Rankine Cycle turbine nozzle and stage. The flow features are predicted with a RANS (Reynolds averaged Navier­Stoke) approach and the k-log() turbulence model in a multi reference frame, where interfaces between fixed and rotating zones are treated with a mixing plane approach, and non reflecting boundary conditions are used. Primitive variables based on pressure and temperature logarithms are adopted to ensure non-negative thermodynamic variables at a discrete level. The fluid can be modeled with the polytropic ideal gas law and the Peng-Robinson equation of state

Increased Serum Beta-Secretase 1 Activity is an Early Marker of Alzheimer's Disease

Background: Beta-site APP cleaving enzyme 1 (BACE1) is the rate-limiting enzyme in amyloid-beta (A beta) plaques formation. BACE1 activity is increased in brains of patients with Alzheimer's disease (AD) and mild cognitive impairment (MCI) and plasma levels of BACE1 appears to reflect those in the brains.Objective: In this work, we investigated the role of serum BACE1 activity as biomarker for AD, estimating the diagnostic accuracy of the assay and assessing the correlation of BACE1 activity with levels of A beta(1-40), A beta(1-42), and A beta(40/42) ratio in serum, known biomarkers of brain amyloidosis.Methods: Serum BACE1 activity and levels of A beta(1-40), A beta(1-42), were assessed in 31 AD, 28 MCI, diagnosed as AD at follow-up (MCI-AD), and 30 controls. The BACE1 analysis was performed with a luciferase assay, where interpolation of relative fluorescence units with a standard curve of concentration reveals BACE1 activity. Serum levels of A beta(1-40), A beta(1-42) were measured with the ultrasensitive Single Molecule Array technology.Results: BACE1 was increased (higher than 60%) in AD and MCI-AD: a cut-off of 11.04 kU/L discriminated patients with high sensitivity (98.31%) and specificity (100%). Diagnostic accuracy was higher for BACE1 than A beta(40/42) ratio. High BACE1 levels were associated with worse cognitive performance and earlier disease onset, which was anticipated by 8 years in patients with BACE1 values above the median value (> 16.67 kU/L).Conclusion: Our results provide new evidence supporting serum/plasma BACE1 activity as an early biomarker of AD

Rare mutations in SQSTM1 modify susceptibility to frontotemporal lobar degeneration

Mutations in the gene coding for Sequestosome 1 (SQSTM1) have been genetically associated with amyotrophic lateral sclerosis (ALS) and Paget disease of bone. In the present study, we analyzed the SQSTM1 coding sequence for mutations in an extended cohort of 1,808 patients with frontotemporal lobar degeneration (FTLD), ascertained within the European Early-Onset Dementia consortium. As control dataset, we sequenced 1,625 European control individuals and analyzed whole-exome sequence data of 2,274 German individuals (total n = 3,899). Association of rare SQSTM1 mutations was calculated in a meta-analysis of 4,332 FTLD and 10,240 control alleles. We identified 25 coding variants in FTLD patients of which 10 have not been described. Fifteen mutations were absent in the control individuals (carrier frequency < 0.00026) whilst the others were rare in both patients and control individuals. When pooling all variants with a minor allele frequency < 0.01, an overall frequency of 3.2 % was calculated in patients. Rare variant association analysis between patients and controls showed no difference over the whole protein, but suggested that rare mutations clustering in the UBA domain of SQSTM1 may influence disease susceptibility by doubling the risk for FTLD (RR = 2.18 [95 % CI 1.24-3.85]; corrected p value = 0.042). Detailed histopathology demonstrated that mutations in SQSTM1 associate with widespread neuronal and glial phospho-TDP-43 pathology. With this study, we provide further evidence for a putative role of rare mutations in SQSTM1 in the genetic etiology of FTLD and showed that, comparable to other FTLD/ALS genes, SQSTM1 mutations are associated with TDP-43 pathology