Noise shielding surrogate models using dynamic artificial neural networks

The optimal design methodologies in aeronautics are known to be constrained by the computational burden required by direct simulations. Due to this reason, the development of efficient metamodelling techniques represents nowadays an imperative need for the designers. In fact, surrogate models has been demonstrated to significantly reduce the number of high-fidelity evaluations, thus alleviating the computing effort. Over the last years, the aeronautical designers community has switched from a design approach predominantly based on direct simulations to an extensive use of metamodels. Recently, to further improve the efficiency, several dynamic approaches based on parameters self-tuning have been developed to support the metamodel construction. This work deals with the use of surrogate models based on Artificial Neural Network for the noise shielding of unconventional aircraft configurations. Here, the insertion loss field of the a Blended Wing Body is reproduced by means of advanced machine learning techniques. The relevant framework is the calculation of the noise emitted by innovative aircraft configurations by means of suitable corrections of existing well-assessed noise prediction tools. The self-tuning algorithm has demonstrated to be accurate and efficient, and the observed performance discloses the possibility to implement numerical strategies for the reliable and robust unconventional aircraft optimal design

SLM Simulation and MonteCarlo Path Tracing for Computer-Generated Holograms

Computer holography is a growing research field that must pay attention to two main issues concerning computing effort: the visualization of a 3D virtual scene with photo-realistic quality and the bottleneck related to hologram digitizalition and visualization limits. This work shows a computational approach based on a Monte Carlo path-tracing algorithm, which accounts for both geometrical and physical phenomena involved in hologram generation, and, therefore, makes a feasible estimation of computing time costs. As these holograms also require yet unavailable visualization devices, their behavior needs to be simulated by computer techniques.

Falco: high-speed FastQC emulation for quality control of sequencing data

Quality control is an essential first step in sequencing data analysis, and software tools for quality control are deeply entrenched in standard pipelines at most sequencing centers. Although the associated computations are straightforward, in many settings the total computing effort required for quality control is appreciable and warrants optimization. We present Falco, an emulation of the popular FastQC tool that runs on average three times faster while generating equivalent results. Compared to FastQC, Falco also requires less memory to run and provides more flexible visualization of HTML reports.

Performance Evaluation of Offline Motion Preparation Approaches on the Example of a Non-Linear Kinematics

In motion control, the generation of motion profiles for non-linear kinematics is usually computationally complex. In order to minimize the workload on the machine’s control system, the approach pursued is outsourcing complex calculation tasks to the offline area. In this offline motion preparation, predefined criteria have to be taken into account to guarantee process stability on the real machine. During the motion preparation, a high performance is desired, characterized by less data generated and at the same time little computing effort. The evaluation will use the example of a motion specification, which is characterized by a large amount of data compared to conventional motion specifications. Thus, the demands on performance become even higher. This paper examines the performance of different motion preparation approaches known from literature. On the one hand, selected spline-based algorithms are discussed and compared. A recursive algorithm based on monomial splines is recommended for use in the example. On the other hand, a very simple approach based on the linearization of the non-linear workspace of the mechanism is presented and applied on the algorithms. With this, the performance increased significantly again.

Falco: high-speed FastQC emulation for quality control of sequencing data

Quality control is an essential first step in sequencing data analysis, and software tools for quality control are deeply entrenched in standard pipelines at most sequencing centers. Although the associated computations are straightforward, in many settings the total computing effort required for quality control is appreciable and warrants optimization. We present falco, an emulation of the popular FastQC tool that runs on average three times faster while generating equivalent results. Compared to FastQC, falco also provides greater scalability for datasets with longer reads and more flexible visualization of HTML reports.

The European perspective for LSST

LSST is a next generation telescope that will produce an unprecedented data flow. The project goal is to deliver data products such as images and catalogs thus enabling scientific analysis for a wide community of users. As a large scale survey, LSST data will be complementary with other facilities in a wide range of scientific domains, including data from ESA or ESO. European countries have invested in LSST since 2007, in the construction of the camera as well as in the computing effort. This latter will be instrumental in designing the next step: how to distribute LSST data to Europe. Astroinformatics challenges for LSST indeed includes not only the analysis of LSST big data, but also the practical efficiency of the data access.

Constraint Solutions for Cracked Plates and Cylinders

There is little advice in fitness for service procedures for assessing constraint parameters T (elastic) and Q (elastic plastic) for biaxially loaded plates and cylinders. This paper presents the analytical determination of T stresses for biaxially loaded plates and the determination of Q for plates and cylinders using finite element analyses. It demonstrates the extent to which T can be used to conservatively predict Q and how, near collapse, Q can be estimated from the stress field corresponding to plastic collapse, enabling a significant reduction in computing effort. The effect of biaxial loading of plates and cylinders on these parameters is discussed as well as the differences found when comparing the values for plates and cylinders.

Navier-Stokes Equation and Computational Scheme for Non-Newtonian Debris Flow

This paper proposes a computational approach to debris flow model. In recent years, the theoretical activity on the classical Herschel-Bulkley model (1926) has been very intense, but it was in the early 80s that the opportunity to explore the computational model has enabled considerable progress in identifying the subclasses of applicability of different sets of boundary conditions and their approximations. Here we investigate analytically the problem of the simulation of uniform motion for heterogeneous debris flow laterally confined taking into account mainly the geological data and methodological suggestions derived from simulation with cellular automata and grid systems, in order to propose a computational scheme able to operate a compromise between “global” predictive capacities and computing effort.