A Review of Geophysical Modeling Based on Particle Swarm Optimization

This paper reviews the application of the algorithm particle swarm optimization (PSO) to perform stochastic inverse modeling of geophysical data. The main features of PSO are summarized, and the most important contributions in several geophysical felds are analyzed. The aim is to indicate the fundamental steps of the evolution of PSO methodologies that have been adopted to model the Earth’s subsurface and then to undertake a critical evaluation of their benefts and limitations. Original works have been selected from the existing geophysical literature to illustrate successful PSO applied to the interpretation of electromagnetic (magnetotelluric and time-domain) data, gravimetric and magnetic data, self-potential, direct current and seismic data. These case studies are critically described and compared. In addition, joint optimization of multiple geophysical data sets by means of multi-objective PSO is presented to highlight the advantage of using a single solver that deploys Pareto optimality to handle diferent data sets without conficting solutions. Finally, we propose best practices for the implementation of a customized algorithm from scratch to perform stochastic inverse modeling of any kind of geophysical data sets for the beneft of PSO practitioners or inexperienced researchers

Russia–Ukraine Conflict, Commodities and Stock Market: A Quantile VAR Analysis

The Russia–Ukrainian war, which began in 2014 and exploded with the invasion of the Russian army on 24 February 2022, has profoundly destabilized the political, economic and financial balance of Europe and beyond. To the humanitarian emergency associated with every war has been added the deep crisis generated by the strong energy and food dependence that many European countries, and not only European, have developed over decades on Ukraine (especially for wheat) and Russia (especially for natural gas). The aim of this article is to verify the existence of a link between the performance of the Eurostoxx index and the price of wheat futures and TTF natural gas, from 25 February 2019 to 28 September 2023. Through a quantile VAR analysis, a link is sought between the Eurostoxx 50 index, and wheat and TTF gas futures prices. Furthermore, the analysis intends to understand whether the presence of such relationship only manifested itself following the war events, or whether it was already present in the market. The analysis carried out also shows that the relationship between the stock market and raw material prices was present even before the conflict

Joint optimization of geophysical data using multi-objective swarm intelligence

The joint inversion of multiple data sets encompasses the advantages of different geophysical methods but may yield to conflicting solutions. Global search methods have been recently developed to address the issue of local minima found by derivative-based methods, to analyse the data compatibility and to find the set of trade-off solutions, since they are not unique. In this paper, we examine two evolutionary algorithms to solve the joint inversion of electrical and electromagnetic data. These nature-inspired metaheuristics also adopt the principle of Pareto optimality in order to identify the result among the feasible solutions and then infer the data compatibility. Since the joint inversion is characterized by more than one objective, we implemented the algorithm multi-objective particle swarm optimization (MOPSO) to jointly interpret time-domain electromagnetic data and vertical electrical sounding. We first tested MOPSO on a synthetic model. The performance of MOPSO was directly compared with that of a multi-objective genetic algorithm, the non-dominated sorting genetic algorithm (NSGAIII), which has often been adopted in geophysics. The adoption of MOPSO and NSGA-III enabled avoiding both simplification into a single-objective problem and the use of a weighting factor between the objectives. We tested the two methods on real data sets collected in the northwest of Italy. The results obtained from MOPSO and NSGA-III were highly comparable to each other and largely consistent with literature findings. The MOPSO performed a rigorous selection of the best trade-off solutions and its convergence was faster than NSGA-III. The analysis of the Pareto Front reported data incompatibility, which is very common for real data due to different resolutions, sensitivities and depth of investigations. Notwithstanding this, the multi-objective optimizers provided a complementary interpretation of the data, ensuring significant advantages with respect to the separate optimizations we carried out using the single-objective particle swarm optimization algorithm

Thermal Impact Assessment of Groundwater Heat Pumps (GWHPs): Rigorous vs. Simplified Models

Groundwater Heat Pumps (GWHPs) are increasingly adopted for air conditioning in urban areas, thus reducing CO2 emissions, and this growth needs to be managed to ensure the sustainability of the thermal alteration of aquifers. However, few studies have addressed the propagation of thermal plumes from open-loop geothermal systems from a long-term perspective. We provide a comprehensive sensitivity analysis, performed with numerical finite-element simulations, to assess how the size of the thermally affected zone is driven by hydrodynamic and thermal subsurface properties, the vadose zone and aquifer thickness, and plant setup. In particular, we focus the analysis on the length and width of thermal plumes, and on their time evolution. Numerical simulations are compared with two simplified methods, namely (i) replacing the time-varying thermal load with its yearly average and (ii) analytical formulae for advective heat transport in the aquifer. The former proves acceptable for the assessment of plume length, while the latter can be used to estimate the width of the thermally affected zone. The results highlight the strong influence of groundwater velocity on the plume size and, especially for its long-term evolution, of ground thermal properties and of subsurface geometrical parameter

SIOUX project: a simultaneous multiband camera for exoplanet atmospheres studies

The exoplanet revolution is well underway. The last decade has seen order-of-magnitude increases in the number of known planets beyond the Solar system. Detailed characterization of exoplanetary atmospheres provide the best means for distinguishing the makeup of their outer layers, and the only hope for understanding the interplay between initial composition chemistry, temperature-pressure atmospheric profiles, dynamics and circulation. While pioneering work on the observational side has produced the first important detections of atmospheric molecules for the class of transiting exoplanets, important limitations are still present due to the lack of sys- tematic, repeated measurements with optimized instrumentation at both visible (VIS) and near-infrared (NIR) wavelengths. It is thus of fundamental importance to explore quantitatively possible avenues for improvements. In this paper we report initial results of a feasibility study for the prototype of a versatile multi-band imaging system for very high-precision differential photometry that exploits the choice of specifically selected narrow-band filters and novel ideas for the execution of simultaneous VIS and NIR measurements. Starting from the fundamental system requirements driven by the science case at hand, we describe a set of three opto-mechanical solutions for the instrument prototype: 1) a radial distribution of the optical flux using dichroic filters for the wavelength separation and narrow-band filters or liquid crystal filters for the observations; 2) a tree distribution of the optical flux (implying 2 separate foci), with the same technique used for the beam separation and filtering; 3) an exotic solution consisting of the study of a complete optical system (i.e. a brand new telescope) that exploits the chromatic errors of a reflecting surface for directing the different wavelengths at different foci

Personalized architectural documentation based on stakeholders' information needs

The stakeholders of a software system are, to a greater or lesser extent, concerned about its software architecture, as an essential artifact for capturing the key design decisions of the system. The architecture is normally documented in the Software Architecture Document (SAD), which tends to be a large and complex technical description, and does not always address the information needs of every stakeholder. Individual stakeholders are interested in dierent, sometimes overlapping, subsets of the SAD and they also require varying levels of detail. As a consequence, stakeholders are aected by an information overload problem, which in practice discourages the usage of the architectural knowledge and diminishes its value for the organization. Along this line, this work presents a semi-automated approach to recommend relevant contents of a given SAD to specific stakeholder profiles. Our approach assumes that SADs are hosted in Wikis, which not only favor communication and interactions among stakeholders, but also enable us to apply User Profiling techniques to infer stakeholders´ interests with respect to particular documents. We have built a recommendation tool implementing our approach, which was tested in two experiments with Wiki-based SADs. Although preliminary, the results have shown that the recommendations of the tool help to nd the architectural documents that best match the stakeholders´ interests.Fil: Tommasel, Antonela. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Tandil. Instituto Superior de Ingenieria del Software; ArgentinaFil: Nicoletti, Matías Alberto. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Tandil. Instituto Superior de Ingenieria del Software; ArgentinaFil: Diaz Pace, Jorge Andres. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Tandil. Instituto Superior de Ingenieria del Software; ArgentinaFil: Schiaffino, Silvia Noemi. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Tandil. Instituto Superior de Ingenieria del Software; ArgentinaFil: Godoy, Daniela Lis. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Tandil. Instituto Superior de Ingenieria del Software; Argentin

Three-Dimensional Magnetotelluric Characterization of the Travale Geothermal Field (Italy) Remote Sens. 2022, 14, 542.

The geoelectrical features of the Travale geothermal field (Italy), one of the most productive geothermal fields in the world, have been investigated by means of three-dimensional (3D) magnetotelluric (MT) data inversion. This study presents the first resistivity model of the Travale geothermal field derived from derivative-based 3D MT inversion. We analyzed MT data that have been acquired in Travale over the past decades in order to determine its geoelectrical dimensionality, directionality, and phase tensor properties. We selected data from 51 MT sites for 3D inversion. We carried out a number of 3D MT inversion tests by changing the type of data to be inverted, the inclusion of static-shift correction at some sites where new time-domain electromagnetic soundings (TDEM) were acquired, the grid rotation, as well as the starting model in order to assess the connection between the inversion model and the geology. The final 3D model herein presents deep elongated resistive bodies between the depths of 1.5 and 8 km. They are transverse to the Apennine structures and suggest a correlation with the strike-slip tectonics. Comparison with a seismic velocity model and well log data suggests a highly-fractured volume of rocks with vapor-dominated circulation. The outcome of this study provides new insights into the complex geothermal system of Travale