121 research outputs found
Proceedings of SIRM 2023 - The 15th European Conference on Rotordynamics
It was our great honor and pleasure to host the SIRM Conference after 2003 and 2011 for the third time in Darmstadt. Rotordynamics covers a huge variety of different applications and challenges which are all in the scope of this conference. The conference was opened with a keynote lecture given by Rainer Nordmann, one of the three founders of SIRM “Schwingungen in rotierenden Maschinen”. In total 53 papers passed our strict review process and were presented. This impressively shows that rotordynamics is relevant as ever. These contributions cover a very wide spectrum of session topics: fluid bearings and seals; air foil bearings; magnetic bearings; rotor blade interaction; rotor fluid interactions; unbalance and balancing; vibrations in turbomachines; vibration control; instability; electrical machines; monitoring, identification and diagnosis; advanced numerical tools and nonlinearities as well as general rotordynamics. The international character of the conference has been significantly enhanced by the Scientific Board since the 14th SIRM resulting on one hand in an expanded Scientific Committee which meanwhile consists of 31 members from 13 different European countries and on the other hand in the new name “European Conference on Rotordynamics”. This new international profile has also been
emphasized by participants of the 15th SIRM coming from 17 different countries out of three continents. We experienced a vital discussion and dialogue between industry and academia at the conference where roughly one third of the papers were presented by industry and two thirds by academia being an excellent basis to follow a bidirectional transfer what we call xchange at Technical University of Darmstadt. At this point we also want to give our special thanks to the eleven industry sponsors for their great support of the conference. On behalf of the Darmstadt Local Committee I welcome you to read the papers of the 15th SIRM giving you further insight into the topics and presentations
Nanoscale Field Emission Devices for High-Temperature and High-Frequency Operation
Field emission—the quantum-mechanical tunneling of electrons from the surface of a material into vacuum by means of a strong electric field—has been studied for over a century. However, the usage of devices based on this mechanism has been limited to a handful of niche applications such as high-power RF systems and field emission displays. The preference for solid-state devices relies on their low cost, long lifetimes, reduced power consumption, ease of integrability, and simple and scalable fabrication. Nonetheless, with the advent of modern fabrication techniques, it has been possible to build field emission devices with nanoscale dimensions that offer several advantages over traditional semiconductor devices. The use of vacuum allows ballistic transport with no lattice scattering. As device capacitance can be engineered by tuning the geometry, these devices are appealing for high-frequency operation. Vacuum is also inherently immune to harsh operating conditions such as high temperature and radiation, which is desirable for aerospace, nuclear, and military applications. In addition, even though field emission requires substantial electric fields, by exploiting the nanoscale gaps that can be easily fabricated with state-of-the-art lithographic capabilities, we can expect operating voltages comparable to CMOS. Thus, vacuum emission devices have the potential to greatly improve upon the limitations of current technologies.
In this work, we experimentally demonstrate various design paradigms to develop nanoscale field emission devices for high-temperature environments and high-frequency operation. First, we propose suspended lateral two- and four-terminal devices. By removing the underlying solid substrate, we aim to increase the resistance of the leakage current pathways that emerge at elevated temperatures. Tungsten is the chosen electrode material due to its low work function and ability to withstand high temperatures. Our next architecture consists of a multi-tip two-terminal array, which exclusively relies on the inherent fast response of field emission. Due to the strong non-linearity in the emission characteristic, frequency mixing is measured. Lastly, we combine field emission with plasmonics to conceive devices that can be modulated both electrically and optically at telecommunication wavelength. By taking advantage of the strong confinement and significant optical field enhancement of surface plasmon polaritons, we seek to minimize the applied voltages required for field emission as well as the necessary laser powers for photoemission towards the development of high-speed, low-power, nanoscale optoelectronic systems.</p
Modelling, Monitoring, Control and Optimization for Complex Industrial Processes
This reprint includes 22 research papers and an editorial, collected from the Special Issue "Modelling, Monitoring, Control and Optimization for Complex Industrial Processes", highlighting recent research advances and emerging research directions in complex industrial processes. This reprint aims to promote the research field and benefit the readers from both academic communities and industrial sectors
Thermal-Hydraulics in Nuclear Fusion Technology: R&D and Applications
In nuclear fusion technology, thermal-hydraulics is a key discipline employed in the design phase of the systems and components to demonstrate performance, and to ensure the reliability and their efficient and economical operation. ITER is in charge of investigating the transients of the engineering systems; this included safety analysis. The thermal-hydraulics is required for the design and analysis of the cooling and ancillary systems such as the blanket, the divertor, the cryogenic, and the balance of plant systems, as well as the tritium carrier, extraction and recovery systems. This Special Issue collects and documents the recent scientific advancements which include, but are not limited to: thermal-hydraulic analyses of systems and components, including magneto-hydrodynamics; safety investigations of systems and components; numerical models and code development and application; codes coupling methodology; code assessment and validation, including benchmarks; experimental infrastructures design and operation; experimental campaigns and investigations; scaling issue in experiments
Green Energy Technology
This book, entitled “The Green Energy Technology”, covers technologies, products, equipment, and devices, as well as energy services, based on software and data protected by patents and/or trademarks. The recent trends underline the principles of a circular economy such as sustainable product design, extending the product’s lifecycle, reusability, and recycling. These are highly related to climate change and environmental impact, and limited natural resources require scientific research and novel technical solutions. This book will serve as a collection of the latest scientific and technological approaches to “green”—i.e., environmentally friendly and sustainable—technologies. While the focus is on energy and bioenergy, it also covers "green" solutions in all aspects of industrial engineering. Green Energy Technology addresses researchers, advanced students, technical consultants and decision-makers in industries and politics. This book is a comprehensive overview and in-depth technical research paper addressing recent progress in Green Energy Technology. We hope that readers will enjoy reading this book
Advanced Data Processing Techniques for Exoplanet Detection in High Contrast Images
High contrast imaging (HCI) is one of the most challenging techniques for exoplanet detection, but also one of the most promising. The main difficulties encountered with HCI arise from the small angular separation between the host star and the potential exoplanets, the flux ratio between them, and the image degradation caused by the Earth's atmosphere. Adaptive optics and coronagraphic techniques are now widely used to improve the quality and the dynamic range of the images with dedicated instruments. However, despite the use of these cutting-edge technologies, the resulting images are still affected by residual aberrations. Under good observing conditions, the performance of HCI instruments is limited by aberrations arising in the optical train of the telescope and instrument, generating quasi-statics speckles in the field of view. Different post-processing techniques along with observing strategies have been proposed in the last decade to deal with these quasi-static speckles, whose shape and intensity are similar to potential companions.This PhD thesis builds upon these recent advances, focusing mainly on the development of a new data processing technique to unveil fainter planetary signals from angular differential imaging (ADI) sequences, and to retrieve their observed properties.
Most post-processing techniques are based on the ADI observing strategy and perform a subtraction of a reference point spread function (PSF), which models the speckle field. Such techniques generally make use of signal-to-noise maps to infer the existence of planetary signals via thresholding. An alternative method to generate the final detection map based on a regime-switching model (RSM) is developed in the first part of this thesis. This approach considers a planetary regime and a speckle regime to describe, via a Markov chain, the evolution of the pixels intensity within cubes of residuals generated by one or multiple PSF-subtraction techniques. The short memory process used in the RSM algorithm allows quasi-static speckles to be treated more effectively. Using multiple PSF-subtraction techniques helps reducing further the residual speckle noise level, better discriminating planetary signals from residual speckles. The RSM map algorithm showed an overall better performance in the receiver operating characteristic space when compared with standard signal-to-noise ratio maps for several state-of-the-art ADI-based post-processing algorithms.
Building on the good results obtained with the RSM algorithm, several improvements of the vanilla RSM map algorithm are then implemented. We started by considering two forward-model versions of the RSM map algorithm based on the LOCI and KLIP PSF-subtraction techniques, allowing to account for the planetary signal self-subtraction observed at short separations. We then addressed the question of optimally selecting the PSF subtraction techniques to optimise the overall performance of the RSM map. A new forward-backward approach is also implemented to take into account both past and future observations to compute the RSM map probabilities, leading to improved precision in terms of astrometry and lowering the background speckle noise. Performance analysis demonstrate the benefits of these improvements.
Following these developments, the RSM map algorithm can use up to seven PSF-subtraction techniques. The selection of the optimal parameters for these PSF-subtraction techniques as well as for the RSM map is therefore not straightforward, time consuming, and can be biased by assumptions made as to the underlying data set. We propose in the fourth chapter of this thesis a novel optimisation procedure that can be applied to each of the PSF-subtraction techniques alone, or to the entire RSM framework. This optimisation procedure, called auto-RSM, consists of three main steps: (i) definition of the optimal set of parameters for the PSF-subtraction techniques, (ii) optimisation of the RSM algorithm, and (iii) selection of the optimal set of PSF-subtraction techniques and ADI sequences used to generate the final RSM probability map. The optimisation procedure is applied to the data sets of the exoplanet imaging data challenge (EIDC). The results demonstrate the interest of the proposed optimisation procedure, with better performance metrics compared to the earlier version of RSM, as well as to other HCI data-processing techniques.
The auto-RSM framework is finally applied to the SHARDDS survey to bring an additional piece to the exoplanet puzzle, by contributing to the characterisation of planetary population via the estimation of occurrence rate maps. This survey gathers 55 main-sequence stars within 100\,pc, known to host a high-infrared-excess debris disk, allowing us to potentially better understand the complex interactions between substellar companions and disks. A clustering approach is used to divide the set of targets into multiple subsets, in order to reduce the computation time by estimating a single optimal parametrisation for each considered subset. A new planetary characterisation algorithm, based on the RSM framework, is developed and tested successfully. We uncover the companion around HD206893, but do not detect any new companion around other stars. Planet detection and planet occurrence frequencies are nevertheless derived from the generated contrast curves and show a high sensitivity between 10 and 100 au for substellar companions with masses over 10 Jupiter masses.
Throughout the different chapters of this thesis, we have built a complex but highly efficient post-processing framework for ADI sequences, adding in each chapter many new features and simplifying its use. All these developments have been compiled into a python package, called PyRSM, which offers a parameter-free detection map computation algorithm with a very low level of residual speckles. This package has largely increased in maturity thanks to the SHARDDS survey and has become a robust HCI post-processing pipeline, achieving good performance in terms of contrasts. PyRSM will hopefully be used for many more surveys and provide unprecedented detection limits, allowing the detection of many exoplanets with the next generation of telescopes and instruments
Computational Optimizations for Machine Learning
The present book contains the 10 articles finally accepted for publication in the Special Issue “Computational Optimizations for Machine Learning” of the MDPI journal Mathematics, which cover a wide range of topics connected to the theory and applications of machine learning, neural networks and artificial intelligence. These topics include, among others, various types of machine learning classes, such as supervised, unsupervised and reinforcement learning, deep neural networks, convolutional neural networks, GANs, decision trees, linear regression, SVM, K-means clustering, Q-learning, temporal difference, deep adversarial networks and more. It is hoped that the book will be interesting and useful to those developing mathematical algorithms and applications in the domain of artificial intelligence and machine learning as well as for those having the appropriate mathematical background and willing to become familiar with recent advances of machine learning computational optimization mathematics, which has nowadays permeated into almost all sectors of human life and activity
LIPIcs, Volume 248, ISAAC 2022, Complete Volume
LIPIcs, Volume 248, ISAAC 2022, Complete Volum
Heat Exchangers
The demand for energy to satisfy the basic needs and services of the population worldwide is increasing as are the economic costs associated with energy production. As such, it is essential to emphasize energy recovery systems to improve heat transfer in thermal processes. Currently, significant research efforts are being conducted to expose criteria and analysis techniques for the design of heat exchange equipment. This book discusses optimization of heat exchangers, heat transfer in novel working fluids, and the experimental and numerical analysis of heat transfer applications
Geothermal Energy Utilization and Technologies 2020
Rising pollution, climate change and the depletion of fossil fuels are leading many countries to focus on renewable-based energy conversion systems. In particular, recently introduced energy policies are giving high priority to increasing the use of renewable energy sources, the improvement of energy systems’ security, the minimization of greenhouse gas effect, and social and economic cohesion. Renewable energies’ availability varies during the day and the seasons and so their use must be accurately predicted in conjunction with the management strategies based on load shifting and energy storage. Thus, in order to reduce the criticalities of this uncertainty, the exploitation of more flexible and stable renewable energies, such as the geothermal one, is necessary. Geothermal energy is an abundant renewable source with significant potential in direct use applications, such as in district heating systems, in indirect use ones to produce electricity, and in cogeneration and polygeneration systems for the combined production of power, heating, and cooling energy. This Special Issue includes geothermal energy utilization and the technologies used for its exploitation considering both the direct and indirect use applications
- …