Abstract

Edge data centres and small server rooms are widely embedded in non-domestic buildings, yet their cooling systems remain energy intensive and under-optimised. This study reports the operational evidence of dew-point cooling (DPC) in a live edge data centre in Hull, the UK. The units feature a heat-and-mass exchanger, high-performance wetting medium, and intermittent water supply. Results from representative operating periods showed that the DPC system delivered stable cooling with low electrical input, achieving a Coefficient of Performance (COP) of up to 40. The monitored hourly profiles also showed important maintenance periods, with a legionella monitoring scheme as a routine risk management. These findings provide evidence to demonstrate that the DPC system is an efficient and practical cooling solution for small edge data centres and support its wider application in similar built environments.

Abstract

This paper addresses the challenges of high injection pressures, difficulty in establishing displacement systems, and low recovery rates in ultra-low permeability reservoirs by proposing an integrated development strategy that combines large-scale complex fracture network fracturing with a COâ‚‚ cooperative injection-production process based on the “injection–shut-in–production” cycle. The approach aims to enhance both oil recovery and COâ‚‚ sequestration potential through reservoir modification and crude oil property regulation. A non-intrusive embedded discrete fracture model (EDFM) is used to accurately represent the complex fracture network in three-dimensional space, overcoming the limitations of traditional methods in multi-scale fracture handling. The paper compares the effects of three development methods: conventional water injection, COâ‚‚ huff-and-puff, and COâ‚‚-water alternating injection (COâ‚‚-WAG). Key parameters such as injection timing, total COâ‚‚ volume, injection rate, and shut-in time are optimized, with carbon sequestration efficiency introduced as a core evaluation index. Simulation results show that cyclic COâ‚‚-WAG can increase recovery by 8.9% compared to conventional water injection. Key mechanisms include: COâ‚‚ reducing oil viscosity and expanding its volume during the shut-in phase, water injection controlling COâ‚‚ flow and expanding sweep volume, and periodic injection–shutdown operations restoring fracture conductivity and maintaining reservoir pressure. This method improves fluid exchange between fractured and unfractured zones, reducing recovery discrepancies. Optimized injection gas rates and timing can delay production decline and reduce fracture closure risks. From a carbon sequestration perspective, the optimized COâ‚‚-WAG scheme improves both oil recovery and COâ‚‚ sequestration efficiency, achieving synergistic optimization. This study offers an integrated method for ultra-low permeability tight oil reservoirs, providing a reliable pathway for green and efficient development.

Abstract

Dynamic analysis and reserve estimation for deep fractured-vuggy carbonate reservoirs pose significant challenges due to severe reservoir heterogeneity, complex production dynamics, and the extreme scarcity of key static formation pressure data. While conventional physics-based models struggle with such data sparsity, standard Artificial Intelligence methods often lack the physical consistency and interpretability required for high-stakes engineering applications. To bridge this gap, this paper introduces PG-TCRN, an innovative physics-guided AI architecture that integrates a Temporal Convolutional Network with a Long Short-Term Memory network to synergize deep learning with domain knowledge. Guided by a composite physics-based loss function, this model leverages continuous production data to intelligently reconstruct a reliable formation pressure profile from only a few static measurements. Subsequently, with the material balance equation serving as a strong physical constraint, our framework transforms the history matching task into a low-dimensional optimization problem, enabling the accurate inversion of key parameters like dynamic reserves and water influx coefficient. Application to a real-world case from the Z Reservoir validates our approach, achieving a precise match of the production history and confirming the physical reliability of the inverted parameters. Furthermore, the framework’s interpretable results quantify the contribution of different energy sources, revealing the dominant reservoir drive mechanism. This study presents an efficient and interpretable new paradigm for AI-driven dynamic analysis in fractured-vuggy reservoirs, offering a powerful tool for data-scarce scenarios.

Abstract

Employing inverse emulsion polymerization with acrylamide (AM) as the principal monomer and acrylic acid (AA) as the functional comonomer, an AM-AA emulsion polymer was successfully synthesized under optimized reaction conditions, including polymerization temperature. The structure of the resulting copolymer was characterized using Fourier transform infrared spectroscopy (FTIR) and thermogravimetric analysis (TGA), confirming the incorporation of both AM and AA repeating units. The emulsion displayed an average particle size of 222.4 nm with a polydispersity index (PDI) of 0.075, indicating a uniform and narrow size distribution. The AM-AA copolymer exhibited favorable water solubility and thermal stability. It also demonstrated moderate resistance to temperature and shear: after exposure to 90℃ the viscosity retention rate of a 3000 mg/L AM-AA polymer solution reached 47.52%. Furthermore, The drag reduction rate of AM-AA polymer is relatively high when the shear rate is 12000s-1, reaching 64.8%.

Abstract

To achieve the 1.5 °C climate goal, global aviation must reach net-zero COâ‚‚ emissions around 2050. Yet, aviation is widely regarded as a “hard-to-abate” sector due to its strong reliance on high-energy-density liquid fuels. This paper briefly reviews and compares decarbonization models and pathways published by major organizations such as ICAO, IATA, ATAG and ICCT. Key findings include: (1) Sustainable aviation fuel is viewed across all major scenarios as the primary emissions reduction lever during 2030–2050. (2) Revolutionary technologies such as hydrogen/electric propulsion exhibit the highest level of uncertainty. (3) Operational improvements are unable to fully offset demand growth. (4) Sector-internal measures alone cannot achieve absolute zero emissions by 2050; external market-based measures or carbon dioxide removal will be necessary. The study further notes that current models are evolving toward integrated techno-economic-policy-climate assessments, AI-enhanced interpretable projections, and improved accounting of non-COâ‚‚ effects and socio-economic impacts.

Abstract

Peer-to-peer (P2P) electricity trading has the potential to enhance the integration of renewable energy, increase flexibility, and bolster community resilience; however, the design of settlements still poses a significant challenge. Traditional fiat systems incur ongoing banking and payment service charges, while generic cryptocurrencies carry risks of volatility and systemic issues. This paper introduces EnergiRING Coin, an energy-linked settlement token that is incorporated into the realSES platform, along with a hybrid co-settlement strategy that switches between fiat and token depending on marginal cost differences, employing a brief cooldown period to avoid oscillations. We carry out a year-long agent-based simulation (8,760 hourly intervals; 2,000 diverse agents) under deterministic disturbances, including two significant cryptocurrency crashes, a market rally, and repeated spikes in fiat fees. The physical clearing (hence total welfare) remains unchanged across different regimes, but net results vary: the fiat-only model is inefficient due to fees, the token-only model fails during shocks, and the hybrid model consistently achieves positive net welfare, reduced inequality, and enhanced resilience; not only avoiding losses during downturns but also capturing additional gains during token price rallies. These findings elevate the concept of settlement from a mere back-office function to an essential market-design tool for maintaining stable, efficient, and low-carbon P2P trading, positioning EnergiRING Coin as a viable method to synchronize financial flows with renewable generation and demand-side adaptability.

Abstract

The limited availability of fossil fuel resources and the environmental issues caused by greenhouse gas emissions have underscored the need to adopt renewable energy sources, particularly solar energy. Improving the efficiency of solar energy systems increases productivity, reduces fuel and electricity consumption, and improves air quality. In this study, the governing equations were numerically solved in ANSYS Fluent using the finite volume method (FVM) with the k-ω-SST turbulence model. The thermal–hydraulic performance of a parabolic trough solar collector was investigated using a water-based CuO-SWCNT hybrid nanofluid at nanoparticle volume fractions of 1%, 2%, and 4%, and Reynolds numbers ranging from 4000 to 10000. Two modified twisted tape turbulators with different V-cut numbers and angles were examined. The results showed that the twisted tape with three V-cuts achieved the highest performance evaluation coefficient (PEC) and improved collector efficiency compared to the two-cut design, particularly at higher Reynolds numbers.

Abstract

Dual-stator axial flux permanent magnet motors (DSSR-AFPM) have been widely applied in electric vehicle drive systems due to their high torque density and compact structure. However, most existing DSSR-AFPM motors employ a surface-mounted permanent magnet (SPM) rotor topology, which suffers from the inability to utilize reluctance torque, high harmonic content in the air-gap flux density, and significant torque ripple. To overcome these drawbacks, this paper proposes a novel interior permanent magnet (NIPM) rotor with magnetic isolation slots. Under identical design constraints, the electromagnetic performances of three rotor topologies—SPM, surface-embedded permanent magnet (SEPM), and NIPM—are compared using three-dimensional finite element analysis. The results show that the NIPM rotor achieves a more sinusoidal air-gap flux distribution, reduced torque ripple, and enhanced flux-weakening capability, while maintaining high efficiency over a wide speed range.

Abstract

In deepwater drilling, low-temperature and high-pressure seabed conditions readily promote natural gas hydrate formation, leading to wellbore blockage and operational risks. To mitigate hydrate formation, chemical inhibitors are commonly added to drilling fluids. This study employed an automated visual hydrate reactor under controlled cooling, with real-time monitoring of temperature, pressure, and torque, while methane consumption was quantified using the Peng-Robinson equation. The effects of calcium chloride (CaCl₂, thermodynamic inhibitor) and modified cellulose (CHNF, kinetic inhibitor) were systematically evaluated. Increasing CaCl₂ concentration prolonged nucleation time and reduced nucleation temperature. At 8wt%, the total pressure drop decreased from 5.25MPa (pure water) to 2.46MPa without significant hydrate accumulation; higher concentrations yielded limited additional benefit, and 8wt% was identified as the optimal dosage considering both efficiency and corrosion risk. CHNF displayed a dose-dependent kinetic inhibition effect: at 0.2wt%, the induction time extended to 213 min and nucleation temperature dropped to 8.1°C, whereas 0.1wt% showed negligible effect. Mechanistic analysis suggests that CaCl₂ suppresses hydrate formation by reducing water activity and shifting the gas-liquid equilibrium toward lower temperature and higher pressure, while CHNF delays nucleation and destabilizes hydrate clusters via interfacial adsorption and hydrogen-bond competition. These findings provide practical guidance for optimizing drilling fluid formulations in deepwater operations.