1,176 research outputs found

    Precision mass measurements for the astrophysical rp-process and electron cooling of trapped ions

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    Precision mass measurements of rare isotopes with decay half-lives far below one second are of importance to a variety of applications including studies of nuclear structure and nuclear astrophysics as well as tests of fundamental symmetries. The first part of this thesis discusses mass measurements of neutron-deficient gallium isotopes in direct vicinity of the proton drip line. The reported measurements of 60-63Ga were performed with the MR-TOF-MS of TRIUMF's Ion Trap for Atomic and Nuclear Science (TITAN) in Vancouver, Canada. The measurements mark the first direct mass determination of 60Ga and yield a 61Ga mass value three times more precise than the literature value from AME2020. Our 60Ga mass value constrains the location of the proton dripline in the gallium isotope chain and extends the experimentally evaluated IMME for isospin triplets up to A=60. The improved precision of the 61Ga mass has important implications for the astrophysical rapid proton capture process (rp-process). Calculations in a single-zone model demonstrate that the improved mass data substantially reduces uncertainties in the predicted light curves of Type I X-ray bursts. TITAN has demonstrated that charge breeding provides a powerful means to increase the precision and resolving power of Penning trap mass measurements of radioactive ions. However, the charge breeding process deteriorates the ion beam quality, thus mitigating the benefits associated with Penning trap mass spectrometry of highly charged ions (HCI). As a potential remedy for the beam quality loss, a cooler Penning trap has been developed in order to investigate the prospects of electron cooling the HCI prior to the mass measurement. The second part of this thesis reports exploratory studies of electron cooling of singly charged ions in this cooler Penning trap. Comparison of measured ion energy evolutions to a cooling model provides a detailed understanding of the underlying cooling dynamics. Extrapolation of the model enables the deduction of tentative estimates of the expected cooling times for radioactive HCI

    Computational development of models and tools for the kinetic study of astrochemical gas-phase reactions

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    This PhD thesis focuses on the application and development of computational tools and methodologies for the modeling of the kinetics of gas-phase reactions of astrophysical interest in the interstellar medium (ISM). The complexity related to the investigation of chemical reactivity in space is mostly due to the extreme physical conditions of temperature, pressure and exposure to high-energy radiation, which in turn also lead to the formation of exotic species, like radicals and ions. Nevertheless, there is still much to be understood about the formation of molecules, the major issue being the lack of sufficient laboratory (experimental and computational) studies. A more detailed and accurate study of all the chemical processes occurring in the ISM will allow us to obtain the data necessary to simulate the chemical evolution of an interstellar cloud over time using kinetic models including thousands of reactions that involve hundreds of species. The collection of the kinetic parameters required for the relevant reactions has led to the growth of different astrochemical databases, such as KIDA and UMIST. However, the data gathered in these catalogues are incomplete, and rely extensively on crude estimations and extrapolations. These rates are of paramount importance to get a better comprehension of the relative abundances of the chemical compounds extrapolated by the astronomers from the spectral data recorded through the radio telescopes and the in-orbit devices, like the satellites. Accurate state-of-the-art computational approaches play a fundamental role in analyzing feasible reaction mechanisms and in accurately predicting the associated kinetics. Such approaches usually rely on chemical intuition where a by-hand search of the most likely pathways is performed. Unfortunately, thisprocedure can lead to overlook significant mechanisms, especially when large molecular systems are investigated. Increasing the size of a molecule can also increase the number of its possible conformers which can show a different chemical reactivity with respect to the same chemical partner. This brings to get very complex chemical reaction networks in which hundreds of chemical species are involved and thousands of chemical reactions can occur.During the last decades, a lot of effort has been done to develop computational techniques able to perform extensive and thorough investigations of complex reaction mechanisms. Such approaches rely on automated computational protocols which drastically decrease the risk of making blunders during the search for significant reaction pathways.Furthermore, the accurate characterization of the potential energy surfaces (PESs) critical points, like reactants, intermediates, transition states and products involved in the reaction mechanism, is crucial in order to carry out a reliable kinetic investigation. The kinetic analysis of an erroneous potential energy surface, would lead to gross errors in the estimation of the rate constants of the chemical species involved in the reaction.In order to avoid such errors, the combination of high-level electronic structure calculations via composite scheme can be helpful to get a more precise estimation of the energy barriers involved in the reaction mechanism. It has been proven that "cheap"[1] composite schemes can achieve subchemical accuracy without any empirical parameters and with convenient computation times, making them perfect for the purpose of this thesis.In recent decades, many efforts have been made to develop theoretical and computational methodologies to perform accurate numerical simulations of the kinetics of such complex reaction mechanisms in a wide range of thermodynamic conditions that mimic extreme reaction environmentsas for combustion systems, the atmosphere and the ISM. Such methodologies are based on the ab initio-transition-state-theory-based master equation approach, which allows the determination of rate coefficients and branching ratios of chemical species involved in complex chemical reactions. This methodology allows to make accurate predictions of the relative abundances of the reaction products for complex reactions even under conditions of temperature and pressure not experimentally accessible, such as those that characterize the ISM. Based on these premises, this dissertation has been focused on the application of a computational protocol for the ab initio-based computational modeling and kinetic investigation of gas-phase reactions which can occur in the ISM.This protocol is based on the application of validated methodologies for the automated discovery of complex reaction mechanisms by means of the AutoMeKin[2] program, the accurate calculation of the energetic of the potential energy surfaces (PESs) through the junChS and junChS-F12a "cheap" composite schemes and the kinetic investigation using the StarRate computer program specifically designed to study gas-phase reactions of astrochemical interest in conjunction with the MESS program. Furthermore, this dissertation has been also focused on the development and implementation of StarRate, a computer program for the accurate calculation of kinetics through a chemical master equation approach of multi-step chemical reactions. StarRate is an object-based program written in the so-called F language. It is structured in three main modules, namely molecules, steps and reactions, which extract the properties needed to calculate the kinetics for the single-step reactions partecipating in the overall reaction. Another module, in_out, handles program’s input and output operations. The main program,starrate, controls the sequences of the calling of the procedures contained in each of the three main modules.Through these modular structure, StarRate[3] can compute canonical and microcanonical rate coefficients taking into account for the tunneling effect and the energy-dependent and time-dependent evolution of the species concentrations involved in the reaction mechanism. Such protocol has been applied to investigate the formation reaction mechanisms of some complex interstellar polyatomic molecules, named interstellar complex organic molecules (iCOMs). More specifically, the formation of prebiotic iCOMs in space has raised considerable interest in the scientific community, because they are considered as precursors of more complex biological systems involved in the origin of life in the Universe. Debate on the origins of these biomolecular building blocks has been further stimulated by the discovery of nucleobases and amino acids in meteorites and other extraterrestrial sources. However, few insights on the chemistry which brings to the formation of such compounds is known.  References: [1] Jacopo Lupi,Silvia Alessandrini,Cristina Puzzarini,and Vincenzo Barone.junchs and junchs-F12 models:Parameter-free efficient yet accurate compositeschemes for energies and structures of noncovalent complexes. Journal of Chem-ical Theory and Computation, 17(11):6974–6992, 2021. PMID: 34677974.[2] Emilio Martínez-Núñez, George L. Barnes, David R. Glowacki, Sabine Kopec,Daniel Peláez, Aurelio Rodríguez, Roberto Rodríguez-Fernández, Robin J. Shan-non, James J. P. Stewart, Pablo G. Tahoces, and Saulo A. Vazquez.Au-tomekin2021: An open-source program for automated reaction discovery. Journalof Computational Chemistry, 42(28):2036–2048, 2021.[3] Surajit Nandi, Bernardo Ballotta, Sergio Rampino, and Vincenzo Barone.Ageneral user-friendly tool for kinetic calculations of multi-step reactions withinthe virtual multifrequency spectrometer project. Applied Sciences, 10(5), 2020

    BDS GNSS for Earth Observation

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    For millennia, human communities have wondered about the possibility of observing phenomena in their surroundings, and in particular those affecting the Earth on which they live. More generally, it can be conceptually defined as Earth observation (EO) and is the collection of information about the biological, chemical and physical systems of planet Earth. It can be undertaken through sensors in direct contact with the ground or airborne platforms (such as weather balloons and stations) or remote-sensing technologies. However, the definition of EO has only become significant in the last 50 years, since it has been possible to send artificial satellites out of Earth’s orbit. Referring strictly to civil applications, satellites of this type were initially designed to provide satellite images; later, their purpose expanded to include the study of information on land characteristics, growing vegetation, crops, and environmental pollution. The data collected are used for several purposes, including the identification of natural resources and the production of accurate cartography. Satellite observations can cover the land, the atmosphere, and the oceans. Remote-sensing satellites may be equipped with passive instrumentation such as infrared or cameras for imaging the visible or active instrumentation such as radar. Generally, such satellites are non-geostationary satellites, i.e., they move at a certain speed along orbits inclined with respect to the Earth’s equatorial plane, often in polar orbit, at low or medium altitude, Low Earth Orbit (LEO) and Medium Earth Orbit (MEO), thus covering the entire Earth’s surface in a certain scan time (properly called ’temporal resolution’), i.e., in a certain number of orbits around the Earth. The first remote-sensing satellites were the American NASA/USGS Landsat Program; subsequently, the European: ENVISAT (ENVironmental SATellite), ERS (European Remote-Sensing satellite), RapidEye, the French SPOT (Satellite Pour l’Observation de laTerre), and the Canadian RADARSAT satellites were launched. The IKONOS, QuickBird, and GeoEye-1 satellites were dedicated to cartography. The WorldView-1 and WorldView-2 satellites and the COSMO-SkyMed system are more recent. The latest generation are the low payloads called Small Satellites, e.g., the Chinese BuFeng-1 and Fengyun-3 series. Also, Global Navigation Satellite Systems (GNSSs) have captured the attention of researchers worldwide for a multitude of Earth monitoring and exploration applications. On the other hand, over the past 40 years, GNSSs have become an essential part of many human activities. As is widely noted, there are currently four fully operational GNSSs; two of these were developed for military purposes (American NAVstar GPS and Russian GLONASS), whilst two others were developed for civil purposes such as the Chinese BeiDou satellite navigation system (BDS) and the European Galileo. In addition, many other regional GNSSs, such as the South Korean Regional Positioning System (KPS), the Japanese quasi-zenital satellite system (QZSS), and the Indian Regional Navigation Satellite System (IRNSS/NavIC), will become available in the next few years, which will have enormous potential for scientific applications and geomatics professionals. In addition to their traditional role of providing global positioning, navigation, and timing (PNT) information, GNSS navigation signals are now being used in new and innovative ways. Across the globe, new fields of scientific study are opening up to examine how signals can provide information about the characteristics of the atmosphere and even the surfaces from which they are reflected before being collected by a receiver. EO researchers monitor global environmental systems using in situ and remote monitoring tools. Their findings provide tools to support decision makers in various areas of interest, from security to the natural environment. GNSS signals are considered an important new source of information because they are a free, real-time, and globally available resource for the EO community

    Electron Thermal Runaway in Atmospheric Electrified Gases: a microscopic approach

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    Thesis elaborated from 2018 to 2023 at the Instituto de AstrofĂ­sica de AndalucĂ­a under the supervision of Alejandro Luque (Granada, Spain) and Nikolai Lehtinen (Bergen, Norway). This thesis presents a new database of atmospheric electron-molecule collision cross sections which was published separately under the DOI : With this new database and a new super-electron management algorithm which significantly enhances high-energy electron statistics at previously unresolved ratios, the thesis explores general facets of the electron thermal runaway process relevant to atmospheric discharges under various conditions of the temperature and gas composition as can be encountered in the wake and formation of discharge channels

    Modelling spread risk via time-change approach

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    The thesis considers two stochastic models for managing spread risk: i) the Duffie-Singleton model; ii) a model developed in the context of electricity spot price modelling, properly adapted to model spread risk, obtained by changing the Duffie-Singleton model with compound Poisson’s jumps with exponentially distributed jump size and a subordinated process as a random clock. The latter has a mean reverting jump component that leads to mean reversion in the level of credit spread in addition to the smooth mean reversion force. In order to calibrate the models the particle filtering technique is used, which allows for the estimate of real-world and risk-neutral probability distributions from time series of credit spread observations

    LIPIcs, Volume 261, ICALP 2023, Complete Volume

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    LIPIcs, Volume 261, ICALP 2023, Complete Volum

    Lattice Boltzmann Methods for Partial Differential Equations

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    Lattice Boltzmann methods provide a robust and highly scalable numerical technique in modern computational fluid dynamics. Besides the discretization procedure, the relaxation principles form the basis of any lattice Boltzmann scheme and render the method a bottom-up approach, which obstructs its development for approximating broad classes of partial differential equations. This work introduces a novel coherent mathematical path to jointly approach the topics of constructability, stability, and limit consistency for lattice Boltzmann methods. A new constructive ansatz for lattice Boltzmann equations is introduced, which highlights the concept of relaxation in a top-down procedure starting at the targeted partial differential equation. Modular convergence proofs are used at each step to identify the key ingredients of relaxation frequencies, equilibria, and moment bases in the ansatz, which determine linear and nonlinear stability as well as consistency orders of relaxation and space-time discretization. For the latter, conventional techniques are employed and extended to determine the impact of the kinetic limit at the very foundation of lattice Boltzmann methods. To computationally analyze nonlinear stability, extensive numerical tests are enabled by combining the intrinsic parallelizability of lattice Boltzmann methods with the platform-agnostic and scalable open-source framework OpenLB. Through upscaling the number and quality of computations, large variations in the parameter spaces of classical benchmark problems are considered for the exploratory indication of methodological insights. Finally, the introduced mathematical and computational techniques are applied for the proposal and analysis of new lattice Boltzmann methods. Based on stabilized relaxation, limit consistent discretizations, and consistent temporal filters, novel numerical schemes are developed for approximating initial value problems and initial boundary value problems as well as coupled systems thereof. In particular, lattice Boltzmann methods are proposed and analyzed for temporal large eddy simulation, for simulating homogenized nonstationary fluid flow through porous media, for binary fluid flow simulations with higher order free energy models, and for the combination with Monte Carlo sampling to approximate statistical solutions of the incompressible Euler equations in three dimensions

    Management of Distributed Energy Storage Systems for Provisioning of Power Network Services

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    Because of environmentally friendly reasons and advanced technological development, a significant number of renewable energy sources (RESs) have been integrated into existing power networks. The increase in penetration and the uneven allocation of the RESs and load demands can lead to power quality issues and system instability in the power networks. Moreover, high penetration of the RESs can also cause low inertia due to a lack of rotational machines, leading to frequency instability. Consequently, the resilience, stability, and power quality of the power networks become exacerbated. This thesis proposes and develops new strategies for energy storage (ES) systems distributed in power networks for compensating for unbalanced active powers and supply-demand mismatches and improving power quality while taking the constraints of the ES into consideration. The thesis is mainly divided into two parts. In the first part, unbalanced active powers and supply-demand mismatch, caused by uneven allocation and distribution of rooftop PV units and load demands, are compensated by employing the distributed ES systems using novel frameworks based on distributed control systems and deep reinforcement learning approaches. There have been limited studies using distributed battery ES systems to mitigate the unbalanced active powers in three-phase four-wire and grounded power networks. Distributed control strategies are proposed to compensate for the unbalanced conditions. To group households in the same phase into the same cluster, algorithms based on feature states and labelled phase data are applied. Within each cluster, distributed dynamic active power balancing strategies are developed to control phase active powers to be close to the reference average phase power. Thus, phase active powers become balanced. To alleviate the supply-demand mismatch caused by high PV generation, a distributed active power control system is developed. The strategy consists of supply-demand mismatch and battery SoC balancing. Control parameters are designed by considering Hurwitz matrices and Lyapunov theory. The distributed ES systems can minimise the total mismatch of power generation and consumption so that reverse power flowing back to the main is decreased. Thus, voltage rise and voltage fluctuation are reduced. Furthermore, as a model-free approach, new frameworks based on Markov decision processes and Markov games are developed to compensate for unbalanced active powers. The frameworks require only proper design of states, action and reward functions, training, and testing with real data of PV generations and load demands. Dynamic models and control parameter designs are no longer required. The developed frameworks are then solved using the DDPG and MADDPG algorithms. In the second part, the distributed ES systems are employed to improve frequency, inertia, voltage, and active power allocation in both islanded AC and DC microgrids by novel decentralized control strategies. In an islanded DC datacentre microgrid, a novel decentralized control of heterogeneous ES systems is proposed. High- and low frequency components of datacentre loads are shared by ultracapacitors and batteries using virtual capacitive and virtual resistance droop controllers, respectively. A decentralized SoC balancing control is proposed to balance battery SoCs to a common value. The stability model ensures the ES devices operate within predefined limits. In an isolated AC microgrid, decentralized frequency control of distributed battery ES systems is proposed. The strategy includes adaptive frequency droop control based on current battery SoCs, virtual inertia control to improve frequency nadir and frequency restoration control to restore system frequency to its nominal value without being dependent on communication infrastructure. A small-signal model of the proposed strategy is developed for calculating control parameters. The proposed strategies in this thesis are verified using MATLAB/Simulink with Reinforcement Learning and Deep Learning Toolboxes and RTDS Technologies' real-time digital simulator with accurate power networks, switching levels of power electronic converters, and a nonlinear battery model
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