A laboratory–scale mechanical draft cooling tower equipped with eight sections of perforated inclined plates was designed to determine the effect of operating conditions on the volumetric mass transfer coefficient (kya) between water and air. A three–factor, three–level design of experiments (DOE) was implemented, considering liquid mass flow rate L (120, 240, and 360 kg/h), gas mass flow rate G (36, 57, and 75 kg/h), and top water temperature TL2 (50, 60, and 70◦C). A total of 54 runs were performed, and the global volumetric mass transfer coefficient was calculated by combining energy and mass balances with the Mickley method. The experimental data were fitted to a power–law correlation using multivariable regression. The ANOVA showed that TL2 is the dominant factor, followed by L, whereas the influence of G is comparatively small in the studied range. The selected correlation, based on the nominal gas flow rate, achieved R2=0.869 and a RMSE of 5930 kg/(m3h). The kya values were found in the range from 4600 to 62000 kg/(m3h). Vertical temperature profiles of water and air along the column revealed that, for high liquid flow rates, most of the cooling occurs in the lower stages, suggesting that the upper sections are underutilized.
This work optimizes the conventional intuitive sizing method for standalone photovoltaic systems with energy storage, still widely used despite its limitations, particularly neglecting battery aging. It often leads to oversized storage and higher costs due to excessive autonomy days assumptions. This paper proposes an improved iterative approach based on hourly irradiance and consumption profiles while integrating a predictive battery aging model to enhance system reliability and economic feasibility. A global energy model, performance indicators, a battery aging model, and a MATLAB algorithm were developed. A simulation for a 4.5 kWh/day consumption in a peri-urban area of Ouagadougou, Burkina Faso, yielded an optimal configuration: a 1060 Wp Photovoltaic generator and a 100.60 Ah storage renewed every two years, covering 90% of demand at 0.20 EUR/kWh. This approach reduces the storage size by 35.92% and the Levelized Cost of Energy by 37.50% compared to the conventional method.
Understanding learning preferences and empathetic needs remains a key challenge in developing aligned learning strategies in higher education, particularly within science, technology, engineering, arts, and mathematics. The study explores how learning content can address diverse cognitive, metacognitive, and emotional student preferences. It assumes that integrating students' learning preferences can improve alignment between learning approaches and sustainability-and innovation-oriented education. An empathetic questionnaire was used to examine visual, auditory, hands-on, and emotionally driven learning preferences among students from five European higher education institutions. The results suggest a strong preference for visual and hands-on learning approaches. Subject-specific differences indicate that visual and practical methods are preferred for sustainability topics, whereas auditory and experiential methods are preferred for entrepreneurial learning. The findings highlight the potential importance of empathy-based learning design in developing inclusive, adaptable, and student-centred learning approaches that may better prepare students to address complex sustainability challenges.
This paper presents a practical framework for the design and evaluation of local, nature-based water retention measures for small and medium-sized municipalities. The framework consists of two components: first, a site-selection score operationalises social, economic, and environmental-geographical sustainability pillars using transparent binary criteria aggregated through a multiplicative rule; and second, a lean monitoring design defines key hydrological, ecological and socio-economic indicators including the use of control sites. The framework is demonstrated on municipal climate-adaptation pilot interventions in Hungary, illustrating how the multiplicative aggregation highlights weak sustainability dimensions that may be concealed by additive indices. A three-dimensional visual representation supports communication of trade-offs to non-expert stakeholders. Overall, the framework improves measurability, comparability, and replicability of local climate adaptation and is suitable for municipalities with limited technical capacity.
Moroccan buildings remain electricity-intensive despite ambitious renewable-electricity targets, and household energy economics are shaped by tariff design and export limitations. This study develops a two-stage optimisation framework that couples genetic-algorithm envelope optimisation (DesignBuilder/EnergyPlus) with a dispatch-constrained mixed-integer linear programme that co-optimises rooftop photovoltaic and battery capacities and hourly operation-of-use tariff, a no-grid-to-battery charging rule, and export constraints. For a representative dwelling in Oujda, envelope upgrades reduce annual space-conditioning electricity demand by 26.9%. Under self-consumption with unpaid exports, the cost-optimal design shifts from 8.0 kW photovoltaic without storage (self-supply ratio 46.4%) to 10.4 kW photovoltaic with 11.8 kWh storage (self-supply ratio 76.6%), reducing annual total cost by 18.6%. When paid exports are enabled under a 20% annual quota, the optimum becomes 10.9 kW photovoltaic with 13.5 kWh storage (self-supply ratio 81.3%) and annual total cost decreases by 9.8% through surplus value recovery. Capacity sweeps confirm diminishing marginal returns: beyond the optima, additional capacity increasingly converts into curtailment or low-value surplus, increasing annual total cost and the levelized cost of electricity. A policy grid over export remuneration and permitted export share identifies a regime transition at a 70% export allowance, beyond which photovoltaic capacity reaches a stable plateau and optimal storage requirements decrease as the economic driver shifts from time shifting toward direct surplus sales. The results support an efficiency-first, then optimal-sized photovoltaic-plus-storage strategy and highlight the importance of bankable export remuneration and broader time-of-use participation for improving household economics.
