In order to evaluate the greenhouse gas (GHG) emissions from a reservoir or from several reservoirs in a country or a climatic zone, simpler or more complex models based on measurements and analyses of emissions presented in the literature were developed, which take into account one or more reservoir-specific parameters. The application of the models in the assessment of GHG emissions from a multipurpose reservoir gave values that are more or less close to the average values reported in the literature for the temperate zone reservoirs. This is explained by the fact that some models only consider emissions caused by impoundment and not degassing, spillway emissions, and downstream emissions, or those that use different calculation periods. The only model that calculates GHG emissions over the life cycle that occur pre-impoundment, post-impoundment, from unrelated anthropogenic sources and due to the reservoir construction is the model used by the G-res tool. In addition, this tool is best suited for multipurpose reservoirs because it allocates GHG emissions for each use, thus facilitating the correct reporting of emissions. The G-res tool used to calculate GHG emissions from the Stânca-Costești Multipurpose Reservoir shows that this is a sink of GHG with a net emission of −5 g CO_2eq/m²/yr (without taking into account the emissions due to dam construction).

The numerical simulation of biomass combustion requires a model that must contain, on one hand, sub-models for biomass conversion to primary products, which involves calculations for heat transfer, biomass decomposition rate, product fractions, chemical composition, and material properties, and on the other hand, sub-models for volatile products transport inside and outside of the biomass particle, their combustion, and the char reduction/oxidation. Creating such a complete mathematical model is particularly challenging; therefore, the present study proposes a versatile alternative—an originally formulated generalized 3D biomass decomposition model designed to be efficiently integrated with existing CFD technology. The biomass decomposition model provides the chemical composition and mixture fractions of volatile products and char at the cell level, while the heat transfer, species transport, and chemical reaction calculations are to be handled by the CFD software. The combustion model has two separate units: the static modeling that produces a macro function returning source/sink terms and local material properties, and the dynamic modeling that tightly couples the first unit output with the CFD environment independently of the initial biomass composition, using main component fractions as initial data. This article introduces the generalized 3D biomass decomposition model formulation and some aspects related to the CFD framework implementation, while the numerical modeling and testing shall be presented in a second article.

In spite of the tremendous advances in computing power and continuous improvements in simulation software made in recent decades, the accurate estimation of wind turbine performance using numerical methods remains challenging. Wind turbine aerodynamics, especially when operating outside of the design envelope, is highly complex: blade stall, laminar-to-turbulent boundary layer transition, rotational effects (lift augmentation near blade root), and tip losses are present. The scope of this research is to show that the classic Reynolds-Averaged Navier–Stokes (RANS) modeling approach, although extensively tried and tested, is not yet exhausted. The NREL Phase VI rotor was used as a basis for numerical methodology development, verification and validation. The numerical model results are compared in detail with the available measured data, both globally (turbine torque and thrust, and blade bending moment) and locally (pressure coefficient distributions and aerodynamic force coefficients at several locations on the blade) over the entire experimental wind speed range. Stall initiation and spread over the blade span are well captured by the model, and rotor performance is predicted with good accuracy. RANS still presents significant value for wind turbine engineering, with a great balance between accuracy and computational cost. The present work brings potential impact on all applications of wind turbines, especially targeting offshore wind energy extraction for which great development is expected in the near future.