This paper presents a novel framework for the preliminary design of multi-energy Pumped Thermal Energy Storage (m-PTES) systems, also known as Carnot batteries. Built upon Finite Dimension Thermodynamics (FDT), the steady-state approach determines the operating conditions corresponding to near-maximum round-trip efficiency. The proposed method offers three key advantages. It is: 1) general, remaining independent of working fluids and cycle architecture; 2) analytical, relying on few physical parameters to describe system behavior; and 3) computationally very efficient, requiring minimal numerical resources. These attributes make FDT well suited for early-stage design of complex multi-energy PTES systems, where rapid evaluation of thermodynamic potential is essential. The proposed method is applied to a case study in northern Canada to illustrate the influence of main parameters on system performance. The results reveal that the storage temperature has a major impact on all key optimal operating conditions, including intermediate temperature, heat-exchanger conductances and heat rates. From an energetic standpoint, the optimal configuration corresponds to the highest achievable storage temperature. At a storage temperature of 800 degrees C, when transitioning from the endoreversible case to an irreversible case with 30% internal losses, the round-trip efficiency eta RT decreases almost linearly from 0.63 to 0.42, while the optimal storage capacity CTES increases from 199 MWh to 263 MWh. Overall, this work demonstrates that FDT is a powerful framework for preliminary conceptual m-PTES design, enabling efficient identification of suitable working fluids and boundary conditions for further detailed modeling and optimization.
Chemical doping in transition metal oxides drives a complex interplay among lattice, charge, and spin degrees of freedom. Herein, we investigate the structural and magnetic evolution of Nd2-xSrxNiO4+delta (0 <= x <= 0.7), a layered nickelate system with mixed-valence Ni2+/Ni3+ ions and tunable oxygen nonstoichiometry (delta), using high-resolution synchrotron X-ray and neutron diffraction, complemented by macroscopic measurements over a broad temperature range. High-temperature solid-state synthesis in air promotes oxygen interstitial incorporation, yielding hyper-stoichiometric compounds (delta > 0). For Nd2NiO4.23 (x = 0), excess oxygen atoms exhibit long-range ordering, giving rise to incommensurate structural modulations and a sequence of order-order transitions persisting up to 800 K. Sr substitution disrupts this ordering via Coulombic effects and suppresses both oxygen uptake and NiO6 octahedral tilting. Stripe-like spin ordering emerges at x = 0.25, 0.33, and 0.5. The x = 0.5 sample exhibits magnetic incommensurability (epsilon approximate to 0.44) below 95 K, indicative of charge discommensuration in NiO2 planes. Unlike the oxygen-doped (x = 0) phase, Sr-doped samples show quasi-two-dimensional magnetism, with in-plane and out-of-plane magnetic correlation lengths of 114(2) & Aring; and 16(3) & Aring;, respectively. These results reveal strong coupling among chemical doping, crystal structure, oxygen ordering, and magnetism in layered nickelates.
Today most of the coastal dunes in temperate latitudes, especially in the northern hemisphere, are relatively stable. However, over the last decade, the Gironde coast, southwest France, has experienced substantial natural dune remobilization following a major marine erosion event. Annual, large-scale and high-resolution, airborne LiDAR data and Satellite imagery (Sentinel-2) are combined to address the coastal dune morphological changes and establish relations with forcing and controlling factors (vegetation cover, geomorphological descriptors). Between 2014 and 2023, about 10 out of 85 km of the Gironde dunes have switched from fixed to transgressive state. The analysis showed that in the vast majority of the cases the dominant process involved was dune front cannibalism. However, there is considerable spatial and temporal variability along the coast, depending on the vegetation cover evolution, the amount of sediment remobilized and the morphological characteristics of the dunes (steepness of the front slope, width).
This paper deals with the optimal integration of power plants, including a storage device. For such systems, numerous structures are possible, involving different numbers of heat exchangers, and for each of them, optimal operating temperatures need to be found. Moreover, the heat-storage system can be located at different temperature levels, offering another degree of freedom when optimizing the whole system. If process simulators are presently very powerful tools for optimizing complex processes, they need to propose a primary design before any optimization steps. Finite-Dimension Thermodynamics (FDT) could help engineers to propose this primary design, close to the optimal one. To this aim, the FDT method is generalized for power-generation systems including a storage device and any number of heat exchangers. The optimization step consists of maximizing the power generation submitted to the thermodynamics constraints (first and second laws) related to each heat exchanger, power block, and thermal storage system. Two types of heat transfer law are studied and compared: Newton’s law K×∆T and phenomenological law issued from thermodynamics of irreversible processes L×∆1/T). Remarkable results have been found: (i) all the studied structures lead to the Curzon–Ahlborn efficiency when optimized with Newton’s law, (ii) for the same driving source (same high temperature and same power), and without any storage system, the output power production varies as N−2, N being the number of the heat exchangers, (iii) Charge and discharge times scenarios have a big impact on the optimal operating temperatures and on the resulting daily energy production. Efficiencies of operational plants, including nuclear or solar plants and ORC, are finally compared with the theoretical efficiency found at the maximum power point. This shows that FDT provides a good assessment of the actual efficiency of existing power plants.
Soil erosion is a significant environmental problem that can have devastating impacts on ecosystems and the sustainability of agricultural lands, including landscape degradation and biodiversity loss. Estimating erosion rates requires the installation of measurement devices such as sediment traps and runoff collectors or the use of erosion plots considering soil texture and vegetation cover. However, these procedures have significant spatial and temporal limitations, in addition to high implementation costs. The objective of this study was to analyze soil erosion in Ecuadorian basins using the Revised Universal Soil Loss Equation (RUSLE) based on Geographic Information System (GIS) and high-resolution satellite data from 2001 to 2020. The methodology involved delineating and evaluating the environmental characteristics of Ecuadorian basins, precipitation data, soil physical and chemical properties, identification of the Normalized Difference Vegetation Index (NDVI), land use, Digital Elevation Model (DEM) selection and assigning values based on slope raster. Basin delineation was obtained from regional literature; precipitation data from GPM-IMERG web servers; sand, clay, silt, and Soil Organic Carbon (SOC) content from SoilGrids web servers; DEM from SRTM database; spatial-temporal distribution of NDVI and land use from MODIS database; and P Factor value ranges based on slope from global literature. Recorded erosion rates ranged from 0.28 t/ha year to 2373.85 t/ha year, with the highest values identified in the Andes Mountains due to steep slopes. The main driver of soil erosion in Ecuadorian basins was the R-Factor, followed by LS and C. Land use variations indicated a loss of 9771 km2 of forests and 80 km2 of cultivated lands between 2001 and 2020, while semi-natural vegetation increased by 9851 km2. These results provide relevant information to assist land managers in making decisions to address this natural phenomenon.
