Biogas is an important driver in carbon-neutral energy sources. Many biogas digester setups, however, are not well optimized and waste energy or fail to maximize their gas output potential. To optimize these systems, a framework was developed to measure and predict digester systems’ efficiencies by closely monitoring fluid movements. This framework includes a numerical calculation of fluid behavior (Computational Fluid Dynamics (CFD)), and Deep Learning to estimate the fluid shear-rates introduced by the agitator’s action. Additionally, a novel measurement system is presented that can measure the same metrics, as simulated, in real-world environments. Lastly, an outlook is given that presents the options and extensions of the presented setup to reduce prediction error, minimize measuring efforts further, and recommend optimization approaches to the operator.

Industrial convective drying is energy-intensive, and its specific energy consumption (SEC) directly determines its greenhouse gas emissions. Recirculation of the exhaust drying agent and superheated steam drying (SSD) reduce the SEC with little investment, but their benefit in impingement dryers depends on fan power and on finite heat and mass transfer. This study presents a system-level model of an electrically heated dryer with impingement flow, comprising a mixer, heater, fan, dryer and recirculation. Coupled mass and energy balances and impingement transfer correlations are solved for drying agents from ambient air to superheated steam at up to $350 °\mathrm{C}$. Three evaluation quantities are introduced: the evaporation potential, the evaporation potential fraction and the normalized drying power. Drying agents are compared at constant volume flow, mass flow and Reynolds number and, as a new case, hydraulic power. With recirculation, superheated steam at about 105 °C to 200 °C yields the highest normalized drying power in all cases (up to $0.92$ for a pressure loss coefficient of 10). Only at high pressure losses and constant mass flow does the optimum shift to moist air. Higher vapor fractions reduce the drying rate, except at constant mass flow above an inversion temperature of about $240 °\mathrm{C}$.

Industrial drying is associated with significant energy consumption and greenhouse gas emissions. Given current climate and energy policy targets, improving drying processes through minimal modifi-cations and optimal operating points has become an important research topic. One such measure is air recirculation, which increases moisture. However, its effect on the efficiency and drying rate of an impingement flow dryer is not straightforward. In this study, we examine the optimal operating point of a dryer model while considering fan power and limited heat and mass transfer coefficients. We define the drying rate by solving a nonlinear system of coupled mass and energy balance equations for dry air, moist air, and superheated steam. To fairly compare these drying agents, we consider four normalization criteria: constant volumetric flow rate, constant mass flow rate, constant Reynolds number, and constant hydraulic power. The results show that increasing the moisture content of the drying agent reduces the drying rate but increases the efficiency for a given volumetric flow rate, hydraulic power, and Reynolds number. However, for a constant mass flow rate, the influence of humidity on the drying rate reverses beyond a specific inversion temperature.