Numerical considerations in spectral multidomain methods for BiGlobal instability analysis of open cavity configurations

A novel approach for the solution of the viscous incompresible and/or compressible BiGlobal eigenvalue problems (EVP) in complex open cavity domains is discussed. The algorithm is based on spectral multidomain spatial discretization, decomposing space into rectangular subdomains which are resolved by spectral collocation based on Chebyshev polynomials. The eigenvalue problem is solved by Krylov subspace iteration. Here particular emphasis is placed on aspects of the parallel developments that have been necessary, on account of the high computing demands placed on the solver, as ever more complex “T-store” configurations are addressed

Modeling, Simulation and Application of Bacterial Transduction in Genetic Algorithms

At present, all methods in Evolutionary Computation are bioinspired in the fundamental principles of neo-Darwinism as well as on a vertical gene transfer. Thus, on a mechanism in which an organism receives genetic material from its ancestor. Horizontal, lateral or cross-population gene transfer is any process in which an organism transfers a genetic segment to another one that is not its offspring. Virus transduction is one of the key mechanisms of horizontal gene propagation in microorganism (e.g. bacteria). In the present paper, we model and simulate a transduction operator, exploring a possible role and usefulness of transduction in a genetic algorithm. The genetic algorithm including transduction has been named PETRI (abbreviation of Promoting Evolution Through Reiterated Infection). The efficiency and performance of this algorithm was evaluated using a benchmark function and the 0/1 knapsack problem. The utility was illustrated designing an AM radio receiver, optimizing the main features of the electronic components of the AM radio circuit as well as those of the radio enclosure. Our results shown how PETRI approaches to higher fitness values as transduction probability comes near to 100%. The conclusion is that transduction improves the performance of a genetic algorithm, assuming a population divided among several sub-populations or ‘bacterial colonies’

Pressure Bifurcation Phenomenon on Supersonic Blowing Trailing Edges

Turbine blades operating in transonic-supersonic regime develop a complex shock wave system at the trailing edge, a phenomenon that leads to unfavorable pressure perturbations downstream and can interact with other turbine stages. Understanding the fluid behavior of the area adjacent to the trailing edge is essential in order to determine the parameters that have influence on these pressure fluctuations. Colder flow, bled from the high-pressure compressor, is often purged at the trailing edge to cool the thin blade edges, affecting the flow behavior and modulating the intensity and angle of the shock waves system. However, this purge flow can sometimes generate non-symmetrical configurations due to a pressure difference that is provoked by the injected flow. In this work, a combination of RANS simulations and global stability analysis is employed to explain the physical reasons of this flow bifurcation. Analyzing the features that naturally appear in the flow and become dominant for some value of the parameters involved in the problem, an anti-symmetrical global mode, related to the sudden geometrical expansion of the trailing edge slot, is identified as the main mechanism that forces the changes in the flow topology.Comment: Submitted to AIAA Journa

The Beauty of Living

The CE “The Beauty of Living” encapsulates three main projects: the production of a three songs EP, the development of artist branding and look, and the accompaniment of the music with visuals. With the songs the aim is to finish three songs at a professional level, leaving them ready to be released at a record label. With the visuals, complete visuals for the whole duration of the three songs, so there’s always a background and a story for the music. And the purpose of the artist branding is to have the presentation material ready when releasing the tracks in the future.https://remix.berklee.edu/graduate-studies-production-technology/1160/thumbnail.jp

The use of hipertext in dissemination of science among children: national geographic kids as a case study

New technologies have generated a new way of communicating science in the digital environment: hypertext. The aim of this research is to analyse the quality, quantity, typology, provenance and function of hypertexts in the informative items published in National Geographic Kid. The methodology is based on a literature review in international databases and content analysis. The results indicate that this resource is part of the digital discursive practices of this magazine, and that they are of high quality, although there is no specific quantity per informational item. These links are mainly internal as opposed to external links. Likewise, they comprise mostly archival and bibliographic hypertexts, followed by terminological hypertexts. A very specific pattern of use is revealed for content exploring geography, zoology and history. It is concluded that the specific hypertextual discursive practices used in a children’s magazine such as National Geographic Kids serve to educate their audiences in scientific content through curiosity and imagination, fostering interest in the world around them and critical thinking. These practices also identify the rules that govern the construction of messaging in the digital narrative of a children’s magazine.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

A novel machine learning‐based methodology for tool wear prediction using acoustic emission signals

There is an increasing trend in the industry of knowing in real-time the condition of their assets. In particular, tool wear is a critical aspect, which requires real-time monitoring to reduce costs and scrap in machining processes. Traditionally, for the purpose of predicting tool wear conditions in machining, mathematical models have been developed to extract the information from the signal of sensors attached to the machines. To reduce the complexity of developing physical models, where an in-depth knowledge of the system being modelled is required, the current trend is to use machine-learning (ML) models based on data from the tool wear. The acoustic emission (AE) technique has been widely used to capture data from and understand the real-time condition of industrial assets such as cutting tools. However, AE signal interpretation and processing is rather complex. One of the most common features extracted from AE signals to predict the tool wear is the counts parameter, defined as the number of times that the amplitude of the signal exceeds a predefined threshold. A recurrent problem of this feature is to define the adequate threshold to obtain consistent wear prediction. Additionally, AE signal bandwidth is rather wide, and the selection of the optimum frequencies band for feature extraction has been pointed out as critical and complex by many authors. To overcome these problems, this paper proposes a methodology that applies multi-threshold count feature extraction at multiresolution level using wavelet packet transform, which extracts a redundant and non-optimal feature map from the AE signal. Next, recursive feature elimination is performed to reduce and optimize the vast number of predicting features generated in the previous step, and random forests regression provides the estimated tool wear. The methodology presented was tested using data captured when turning 19NiMoCr6 steel under pre-established cutting conditions. The results obtained were compared with several ML algorithms such as k-nearest neighbors, support vector machines, artificial neural networks and decision trees. Experimental results show that the proposed method can reduce the predicted root mean squared error by 36.53%

Making Transport Safer: V2V-Based Automated Emergency Braking System

An important goal in the field of intelligent transportation systems (ITS) is to provide driving aids aimed at preventing accidents and reducing the number of traffic victims. The commonest traffic accidents in urban areas are due to sudden braking that demands a very fast response on the part of drivers. Attempts to solve this problem have motivated many ITS advances including the detection of the intention of surrounding cars using lasers, radars or cameras. However, this might not be enough to increase safety when there is a danger of collision. Vehicle to vehicle communications are needed to ensure that the other intentions of cars are also available. The article describes the development of a controller to perform an emergency stop via an electro-hydraulic braking system employed on dry asphalt. An original V2V communication scheme based on WiFi cards has been used for broadcasting positioning information to other vehicles. The reliability of the scheme has been theoretically analyzed to estimate its performance when the number of vehicles involved is much higher. This controller has been incorporated into the AUTOPIA program control for automatic cars. The system has been implemented in Citroën C3 Pluriel, and various tests were performed to evaluate its operation

The estimation of truncation error by tau-estimation revisited

The aim of this paper was to accurately estimate the local truncation error of partial differential equations, that are numerically solved using a finite difference or finite volume approach on structured and unstructured meshes. In this work, we approximated the local truncation error using the @t-estimation procedure, which aims to compare the residuals on a sequence of grids with different spacing. First, we focused the analysis on one-dimensional scalar linear and non-linear test cases to examine the accuracy of the estimation of the truncation error for both finite difference and finite volume approaches on different grid topologies. Then, we extended the analysis to two-dimensional problems: first on linear and non-linear scalar equations and finally on the Euler equations. We demonstrated that this approach yields a highly accurate estimation of the truncation error if some conditions are fulfilled. These conditions are related to the accuracy of the restriction operators, the choice of the boundary conditions, the distortion of the grids and the magnitude of the iteration error