Reverse osmosis (RO) is a desalination technique that is commonly preferred because of its low energy consumption. In this paper, an innovative, thermally powered RO desalination process is presented. This new thermo-hydraulic process uses solar thermal energy in order to realize the pressurization of the saltwater beyond its osmotic pressure to allow its desalination. This pressurization is enabled thanks to a piston or a membrane set in motion in a reservoir by a working fluid that follows a thermodynamic cycle similar to an Organic Rankine Cycle. In this cycle, the evaporator is heated by low-grade heat, such as the one delivered by flat-plate solar collectors, while the condenser is cooled by the saltwater to be treated. Such an installation, designed for small-scale (1 to 10 m³·day⁻¹) brackish water desalination, should enable an average daily production of 500 L of drinkable water per m² of solar collectors with a specific thermal energy consumption of about 6 kWh_th·m⁻³. A dynamic modeling of the whole process has been developed in order to study its dynamic cyclic operating behavior under variable solar thermal power, to optimize its design, and to maximize its performances. This paper presents the preliminary performance results of such a solar-driven desalination process.

In response to increasingly stringent emissions regulations and the depletion of conventional fuel sources, integrating carbon-free fuels into the transport sector has become imperative. While hydrogen (H₂) presents significant technical challenges, ammonia (NH₃) could present a better alternative offering ease of transport, storage, and distribution, with both ecological and economic advantages. However, ammonia substitution leads to high emissions of unburned NH₃, particularly at high loads. Combustion chamber retrofitting has proven to be an effective approach to remedy this problem. In order to overcome the problems associated with the difficult combustion of ammonia in engines, this study aims to investigate the effect of the piston bowl shape of an ammonia/diesel dual fuel engine on the combustion process. The primary objective is to determine the optimal configuration that offers superior engine performance under high load conditions and with high ammonia rates. In this study, a multi-objective optimization approach is used to control the creation of geometries and the swirl rate under the CONVERGE^TM 3.1 code. To maximize indicated thermal efficiency and demonstrate the influence of hydrogen enrichment on ammonia combustion in ammonia/diesel dual fuel engines, a synergistic approach incorporating hydrogen enrichment of the primary fuel was implemented. Notably, the optimum configuration, featuring an 85% energy contribution from ammonia, outperforms others in terms of combustion efficiency and pollutant reduction. It achieves over 43% reduction in unburned NH₃ emissions and a substantial 31% improvement in indicated thermal efficiency.

Faced with environmental issues and depleting oil reserves, engine research is venturing into novel paths, such as the dual-fuel engine. This has motivated the development of numerical models that provide highly accurate predictive tools. In this context, 0D/quasi-D modeling is necessary, with a compromise between control of computation time and acceptable prediction level, which will certainly enable the various studies on the dual fuel mode to be explored at reduced cost. The aim of the present study is to develop a combustion model adapted to the hydrogen-natural gas (HNG)/diesel dual fuel engine to ensure 0D/1D simulations over a wide load range and under different gas mixture compositions. This model is based on the separation of the different types of combustion in this mode, by first treating the combustion of the pilot fuel by jet modeling, then the combustion of the gas mixture (HNG) by a mathematical model based on the Gaussian function. This phase separation is carefully combined with a mathematical treatment of the heat release rate, in order to determine ignition delays for both phases and model each of them separately. The modeling approach unveiled in this work is based on a phenomenological aspect, where the distinction between pilot and primary fuel combustion is ensured with phase separation allowing precise monitoring of the combustion sequence with the detection of the start and end of each phase and the contribution of each to the overall heat release rate. The results confirm the predictive power of the model developed with a maximum error of around 2%. This accurate prediction is particularly evident at high loads with high hydrogen enrichment, where the combustion sequence becomes complicated.

In the context of increasing energy demand and the global transition toward sustainable solutions, the integration of renewable energy sources into power systems is becoming a necessity. Data centers, as major energy consumers, are particularly impacted by this shift. Photovoltaic (PV) panels represent a promising alternative to conventional electricity sources due to their low environmental impact. However, their intermittent nature leads to instability in power supply, requiring efficient energy storage solutions to ensure reliability and self-sufficiency. Among the various storage technologies available, hydrogen stands out as a viable energy carrier due to its high energy density, long-term storage capability, and minimal environmental footprint. To address these challenges, a hybrid energy storage system combining hydrogen production, battery storage, and grid connection is designed in this study to enhance energy autonomy while maintaining cost efficiency. The system relies on a combination of an electrolyzer, hydrogen storage tanks, a fuel cell, and a battery to ensure a continuous and stable energy supply. A simulation-based optimization approach is conducted using Python to determine the optimal configuration of these components. The results show that a self-sufficiency rate of 95% is achieved, with a levelized cost of electricity (LCOE) of 0.47 US$/kWh, demonstrating the feasibility of the proposed system. The environmental impact is also assessed, revealing a significant reduction in carbon emissions, with 8.97 tons of CO₂ saved over the system’s 15-year lifespan, compared to the 10 tons emitted by a conventional grid-powered system over the same period. Furthermore, a detailed analysis of energy flow within the system highlights the role of each storage component in balancing supply and demand. The hybrid design leverages the advantages of both hydrogen and battery storage, where the battery is primarily used to compensate for short-term fluctuations, while hydrogen ensures long-term energy storage. The impact of different electrolyzer and fuel cell sizes on system performance is also evaluated, leading to an optimal configuration with an electrolyzer of 5 kW, a hydrogen storage capacity of 200 L at 350 bars, a fuel cell of 2 kW, and a battery of 50 kWh.