Search Results (190)

This article proposes and validates a hybrid structural reinforcement strategy for onshore wind turbine foundations in repowering projects, enabling the installation of higher-capacity units without demolishing the existing foundation. In a context of increasing demand for renewable energy and infrastructure optimization, the original foundation is reused as the primary element for global stability and serviceability limit state (SLS) requirements, while ultimate limit state (ULS) demands, arising from the replacement of approximately 1.5 MW turbines with 4.1 MW and 6.25 MW units with power ratings representative of various manufacturers’ models in the current market are resisted by a new peripheral reinforced concrete strengthening system. The study considers both shallow (gravity) and piled foundation typologies, which are the most common globally for wind turbines. This solution, applied to a commercially operating wind farm in southern Brazil with actual load data, demonstrated a substantial reduction in concrete volume–up to 80% for shallow foundations and 40% for piled foundations compared to constructing an entirely new foundation. Structural assessment was performed through numerical modeling in SAP2000, employing a shell-beam hybrid model validated against a 3D solid reference, combined with analytical verifications of limit states. Results confirm that the proposed solution ensures global serviceability and adequate ultimate limit state capacity, achieving significant material optimization. This offers a sustainable and efficient alternative for repowering wind turbine foundations, with notable economic and environmental benefits, including the elimination of demolition, transportation, and material disposal costs. Full article

This paper provides a historical perspective on comparatively low levels of trade in the Middle East and North Africa (MENA) region, focusing on studies addressing the impact of the Israeli–Palestinian conflict. Our literature review identifies best practices and reviews trade potential estimates and finds that the last year for which a relevant trade potential estimate for the region accounting for the influence of the Israeli–Palestinian conflict is available is 1999. First, we replicate the seminal study that provided the earliest estimation of trade potential. Next, we extend and update this study, using a best practice panel PPML gravity model with ex(/im)porter-year fixed effects for 76 countries (1991–2019 inclusive). Finally, we use two alternative approaches to estimate the intra-MENA trade potential that could have been reaped as a consequence of a geopolitically more stable and open Middle East (ME). In the year 2019, this ‘pot of gold’ (POG) in per cent of intra-MENA trade amounted to 10% to 54% (import-based) and 21% to 48% (export-based), substantially lower than earlier literature reports. Full article

Extended-solvent steam-assisted gravity drainage (ES-SAGD) has emerged as a promising advancement over conventional SAGD for improving the efficiency and sustainability of in situ heavy oil and bitumen recovery. By co-injecting light hydrocarbon or alternative solvents with steam, ES-SAGD integrates thermal and compositional mechanisms to reduce viscosity, accelerate chamber development, and reduce steam–oil ratios. This review synthesizes the current state of knowledge on ES-SAGD, encompassing fundamental transport mechanisms, solvent selection and phase behavior, mass transfer dynamics, laboratory and physical modeling studies, numerical simulation approaches, and field-scale operational experiences. Experimental evidence consistently demonstrates substantial mobility enhancement through solvent-induced dilution, while compositional thermal simulations highlight an improved sweep efficiency and reduced energy intensity relative to steam-only processes. Field pilots further validate accelerated early-time production and significant steam savings, though challenges related to solvent retention, asphaltene stability, and reservoir heterogeneity persist. Key research gaps are identified in solvent transport prediction, formation damage risk, long-term solvent recovery, and integrated economic–environmental optimization. Overall, ES-SAGD offers a viable pathway toward lower-emission, higher-efficiency bitumen production, provided that solvent chemistry, reservoir complexity, and operational controls are carefully managed through continued research and targeted field deployment. Full article

Rocky shores are characterized by rough, multi-scale bathymetric variations that result in enhanced wave energy dissipation by bottom friction compared to sandy beaches. Realistic SWAN simulations of surface gravity waves across the rocky shores of Monterey (CA, USA) are conducted, and model results are compared to 20 inner-shelf observational sites spanning 34–5 m water depth. The wave field was highly variable during the study, including alternately low energy waves dominated by southern swell and higher energy local waves aligned with strong north-westerly winds. Including a modified bottom friction parameterization is required for the model to reproduce bulk wave statistics with high skill across the entire inner shelf. The SWAN simulation with the default bottom friction parameterization overestimates significant wave height relative to observations because the friction factor $f_e$ parameterization has a maximum value of 0.3. Additional simulations included two empirical formulations relating $f_e$ to the normalized wave excursion $A_b/k_N$ in the large roughness regime $A_b/k_N<1$. Both simulations incorporate a higher $f_e$ that is required to model strong bottom friction dissipation over rocky seabeds. The higher friction factors, with 80% falling within the range 0.43 to 5.38, are associated with variability in the normalized orbital excursion within $0.1<A_b/k_N<1$. This range corresponds to a large bottom roughness length scale, $k_N=0.5$ m, characteristic of rocky shore environments. Full article

The classical Erlangen Program sought to classify metric spaces entirely in terms of their symmetries. In physical spacetimes, these symmetries define transformations between classical reference frames, yielding a one-to-one correspondence between frame transformations and the underlying geometry. More recently, the classical notion of an ideal frame has been extended to the quantum regime, by considering observers as embodied physical systems, subject to the laws of quantum mechanics. Here, we build on this approach, but outline an alternative definition of the term ‘quantum reference frame’, which differs somewhat from the mainstream view. We then show how the new definition can be used to construct a simple model of Planck-scale spacetime, which makes contact with existing quantum gravity phenomenology. Finally, we show how classical spacetime symmetries can be ‘mathematically preserved but operationally broken’ using the new model, suggesting that quantum spacetime may be classified, at least locally, in terms of transformations between quantised frames of reference. This work is based on a talk given at the 13th Bolyai–Gauss–Lobachevsky Conference on Non-Euclidean Geometry in Oujda, Morocco, in May 2025. Full article

This paper studies the dynamic adjustment of bilateral trade following Economic Integration Agreements (EIAs) and examines how financial development and labor market rigidity moderate the timing of trade responses. We approximate the event time adjustment path using a Piecewise Linear Trend (PLT) specification that relaxes global linearity restrictions common in dynamic gravity models. Event study evidence reveals heterogeneous pre-entry and post-entry slopes, particularly at the product-margin level. Split joint pre-trend tests show that aggregate trade satisfies long-run parallel trends, while product-level margins exhibit significant secular restructuring prior to implementation, motivating explicit slope parameterization. Within the PLT framework, financial development is associated with short-run anticipation effects, whereas labor rigidity corresponds to delayed post-entry adjustments. Industry-level interactions indicate that these dynamics vary systematically with sectoral characteristics. The results remain robust to zero-inclusive estimators, alternative institutional proxies, and alternative event time discretizations. Overall, the findings demonstrate that institutional conditions shape the temporal profile of trade adjustment and that flexible slope modeling is essential for identifying dynamic responses to trade liberalization. Full article

We investigate the modifications to inflationary observables that arise when adopting an $\alpha$-vacuum instead of the standard Bunch–Davies vacuum for quantum fluctuations during inflation. Within the Starobinsky inflationary model, we compute and compare the scalar spectral index, its running, and the running of the running arising from different choices of the initial vacuum state. We further examine the energy scales associated with $\alpha$-vacua and argue that, for any number of extra spatial dimensions, the relevant scale can be truncated at the Hubble scale, ∼$\mathcal{O}\left({10}^{13}\right)\mathrm{GeV}$, without conflict with current Cavendish-type experimental bounds on sub-millimeter gravity (∼$250\mathsf{\mu }\mathrm{m}$). Our analysis demonstrates that the $\alpha$-vacuum is subject to stringent constraints as a viable de Sitter-invariant alternative to the Euclidean (Bunch–Davies) vacuum, with the corrections that it induces in the inflationary observables being strongly limited by the latest Planck data. Full article

Carbon dioxide injection is one of the most advanced and commercially proven methods of enhanced hydrocarbon recovery, and CO₂ injection has been shown to be very effective in conventional oil reservoirs and is gaining attention in gas, unconventional, and coalbed methane reservoirs. The advantages of CO₂ injection lie in the favorable phase properties and interactions with reservoir fluids, such as swelling, reduction in oil viscosity, reduction in interfacial tension, and miscible displacement in favorable cases. But the low viscosity and density of CO₂ compared to the reservoir fluids result in unfavorable mobility ratios and gravity override, resulting in sweep efficiency limitations. This review offers a broad and EOR-centric evaluation of the various CO₂ injection methods for a broad array of reservoir types, such as depleted oil reservoirs, gas reservoirs for the purpose of gas recovery, tight gas/sands, as well as coalbed methane reservoirs. Particular attention will be given to the use of mobility control/sweep enhancement techniques such as water alternating gas (CO₂-WAG), foam-assisted CO₂ injection, polymer-assisted WAG processes, as well as hybrid processes that combine the use of CO₂ injection with low salinity or engineered waterflood. Further, recent developments in compositional simulation, fracture-resolving simulation, hysteresis modeling, and data-driven optimization techniques have been highlighted. Operational challenges such as injectivity reduction, asphaltene precipitation, corrosion, and conformance problems have been reviewed, along with the existing methods to mitigate such issues. Finally, key gaps in the current studies have been identified, with an emphasis on the development of EHR processes using CO₂ in complex and low-permeability reservoirs, enhancing the resistance of chemical and foam methods in realistic conditions, and the development of reliable methods for optimizing the process on the field scale. This review article will act as an aid in the technical development process for the implementation of CO₂ injection projects for the recovery of hydrocarbons. Full article

Additive manufacturing has emerged as a key enabling technology for in-space manufacturing, offering the potential to reduce logistics mass, enhance mission autonomy, and support long-duration exploration. The suppression of gravity-driven phenomena fundamentally alters melt pool dynamics, heat transfer, surface-tension-dominated flow, and defect formation, limiting the direct transferability of terrestrial AM process knowledge to space applications. This paper reviews the current understanding of metallic additive manufacturing process physics under reduced gravity, with emphasis on melt pool behavior, dimensional stability, and in situ monitoring constraints. Approaches for qualification and certification are critically examined, including the applicability of existing AM standards, the role of digital twins and model-based verification, and emerging strategies for space-based validation. Enabling technologies such as autonomous and AI-assisted fabrication, compact hardware architectures, and alternative energy sources are discussed in the context of reliable in-space operation. By synthesizing current developments and identifying key limitations and open challenges, the review provides a roadmap for advancing additive manufacturing toward operational readiness, supporting sustainable exploration, in-space infrastructure development, and long-duration human presence beyond low Earth orbit. Full article

Fermentation is a complex biochemical process that transforms brewer’s wort into beer. Beer fermentation is driven by yeast and is influenced by process parameters such as the content of fermentable sugars in wort, temperature, and pH. Traditional methods of modelling this process rely heavily on empirically tuned kinetic models. However, these models tend to be recipe-specific and often require retuning when processes change. This paper proposes a data-driven approach using a Long Short-Term Memory (LSTM) network, a type of recurrent neural network, to model beer fermentation dynamics. By training the LSTM model on real-world fermentation data (1305 fermentations across ales, IPAs, lagers, and mixed-culture beers), including variables such as apparent extract (derived from specific gravity), temperature, and pH, we demonstrate that this technique can accurately predict key fermentation trajectories and support process monitoring and optimisation. When evaluated on representative medoid fermentations as one-step-ahead roll-outs over 0–300 h, the model produces accurate predictions with low errors and minimal residuals. These results show that the LSTM-based model provides accurate and robust predictions across beer styles and operating conditions, offering a practical alternative to traditional mechanistic kinetic models. This work highlights the potential of LSTM networks to enhance our understanding, monitoring, and control of fermentation processes, providing a scalable and efficient tool for both research and industrial applications. The findings suggest that LSTM models can be effectively adapted to model other fermentation processes in beverage production, opening new possibilities for advancing food science and engineering. Full article

The International Energy Agency (IEA) asserts that worldwide electricity demand is rising exponentially every year. Energy storage is the cornerstone of electricity demand. Gravity-based energy storage systems represent the optimum alternative for energy storage systems. They offer zero carbon emission, environmental sustainability, cost-effectiveness, geographical flexibility, long-duration storage, and scalability ranging from 0.5 to 10 GWh. This research introduces a novel design to confirm the workability of the gravity energy storage model. It validates the feasibility of the system through the drive train setup. The drive train model involves storing potential energy by elevating the stack weight using solar photovoltaic input and releasing the weight to generate electrical energy using the gravitational field. The gravity motion is theoretically proven by the mathematical analysis, drive train control system transfer function model, and golden ratio-based design. Solidworks simulation model enhances the working of the drive train setup. Through hardware iterative experimental results with different load profiles, validate the performance metrics. The gravity energy storage system’s feasibility is demonstrated by its scalability in comparison with battery energy systems. Gravity-based energy storage is the best option for utility-scale renewable energy grid integration, since it has a low energy density, medium and large capacity, long-lasting storage, and high scalability. Full article

We resume our analysis of Newtonian Fractional-Dimension Gravity (NFDG), an alternative gravitational model that does not require the dark matter (DM) paradigm. We add three more galaxies (NGC 6946, NGC 3198, NGC 2841) to the catalog of those studied with NFDG methods. Once again, NFDG can successfully reproduce the observed rotation curves by using a variable fractional dimension $D\left(R\right)$, as with the nine other galaxies previously studied with these methods. In addition, we introduce a mass-dimension field equation for our model, which is capable of deriving the fractional mass dimension $D_m\left(R\right)$ from a single equation, as opposed to the previous $D\left(R\right)$, which was obtained simply by matching the experimental rotational velocity data for each galaxy. While the NFDG predictions computed with this new $D_m\left(R\right)$ dimension are not as accurate as those based on the original $D\left(R\right)$, they nevertheless confirm the validity of our fractional-dimension approach. Three previously studied galaxies (NGC 7814, NGC 6503, NGC 3741) were analyzed again with these new methods, and their structure was confirmed to be free from any dark matter components. Full article

In the São Brás de Alportel municipality, water scarcity poses a significant constraint on agricultural activities. This study utilises Remote Sensing (RS) and Geographical Information Systems (GISs) to identify existing irrigated areas, delineate catchment basins, and select the most suitable sites for the installation of new surface water reservoirs. First, the principal territorial components were characterised, including physical elements (climate, geology, soils, and hydrography) and anthropogenic infrastructure (road network and high-voltage power lines). Summer Sentinel-2 satellite imagery was then analysed to calculate the Normalised Difference Vegetation Index (NDVI), enabling the identification and classification of irrigated agricultural parcels. Flow directions and accumulations derived from Digital Elevation Models (DEMs) facilitated the characterisation of 38 micro-catchments and the extraction of 758 km of the drainage network. The siting criteria required a minimum setback of 100 m from roads and high-voltage lines, excluded farmland currently in use, and favoured mountainous areas with low permeability. Only 18.65% (2854 ha) of the municipality is agricultural land, of which just 4% (112 ha) currently benefits from irrigation. The NDVI-based classification achieved a Kappa coefficient of 0.88, indicating high reliability. Three sites demonstrated adequate storage capacity, with embankments measuring 8 m, 10 m, and 12 m in height. At one of these sites, two reservoirs arranged in a cascade were selected as an alternative to a single structure exceeding 12 m in height, thereby reducing environmental and landscape impact. The reservoirs fill between October and November in an average rainfall year and between October and January in a dry year, maintaining a positive annual water balance and allowing downstream plots to be irrigated by gravity. The methodology proved to be objective, replicable, and essential for the sustainable expansion of irrigation within the municipality. Full article

The Two-Measure Theory (TMT) has been developing since 1998 and has yielded a number of highly interesting results, including those not realized in traditional field theory models. The most important advantage of TMT as an alternative theory is that, under the conditions under which all classical tests of general relativity are performed, TMT models are able to accurately reproduce Einstein’s general relativity. Despite this, TMT is still often perceived as something too exotic to be relevant to reality. In fact, the fundamental idea underlying TMT seems undeniable: if we truly believe in the effectiveness of mathematics in studying nature, we must agree that there must be a correspondence between the fundamental laws of nature and the structure of the mathematical apparatus necessary to adequately describe them. It then turns out that there is no reason to ignore the volume measure existing on the differentiable manifold on which the theory of gravity and matter fields is built. This idea has far-reaching implications. The goals of this paper are (1) to provide a clear mathematical and conceptual justification for TMT and (2) to collect in a single article some of the main results of TMT obtained over the past 25 years. Full article

Traditional gravity models, while widely used in transport planning, often struggle to capture nonlinear spatial patterns and the heterogeneity of real-world mobility. In contrast, DNNs offer a flexible framework capable of integrating diverse explanatory variables and learning complex relationships from data. The study evaluates multiple DNN architectures trained on more than 90,000 observed OD pairs between 2477 municipalities, comparing their performance against a calibrated national gravity model. Key methodological considerations include the treatment of zero-trip observations, intra-zonal flows, and spatial aggregation levels. Results show that DNNs significantly outperform the gravity model in terms of prediction accuracy (MAE, R², GEH), with the best-performing model achieving an R² of 94%. The findings highlight the importance of data preprocessing, model architecture, and post-processing in improving predictive performance. Overall, the study demonstrates the potential of DNNs as a robust alternative to classical models in transport demand modeling, particularly when working with large, sparse, and heterogeneous datasets. Full article