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[EN] The objective of this article is to compare the behaviour of the most representative domestic hot water systems (DHW) in single-family buildings. The study evaluates the energy consumption, equivalent CO2 emissions and cost for each system over a 15-year life period. This analysis is carried out in four cli- matic zones across Europe to observe the influence of climatic conditions on the results. The four climatic zones are located in the cities of Athens, Madrid, London and Berlin. The analysed systems are: a) natural gas-fired instantaneous water heaters, b) electric storage water heater, c) solar thermal system with gas- fired instantaneous, d) solar thermal system with electric storage water heater, e) air-source heat pump, f) photovoltaic system with electric storage water heater, and g) photovoltaic system with air-source heat pump. This range of technologies covers the most likely solutions to be implemented across domestic buildings in Europe.The heat pump system (HPWH) with PV considering self-consumption shows the lowest environmen- tal impact in all zones, but is not an attractive investment in the coldest zones due to lower natural gas prices. Thermal solar systems have a high purchase and maintenance costs which do not compensate their energy savings. The PV HPWH system has a greater reduction of emissions and a lower cost than HPWH across a 15-year life. The gas boiler system has the lowest cost in a 15-year period in the coldest areas, despite having a greater environmental impact than the heat pump.(c) 2023 Elsevier B.V. All rights reserved.

Filament seals, such as brush seals and leaf seals, are investigated as a potential improved seal for gas turbine applications. As these seals operate in contact with the rotor, a good understanding of their stiffness is required in order to minimize seal wear and degradation. This paper demonstrates that the filament and complete seal stiffness is affected in comparable magnitudes by mechanical and aerodynamic forces. In certain cases, the aerodynamic forces can also lead to an overall negative seal stiffness which may affect stable seal operation. In negative stiffness, the displacement of the seal or rotor into an eccentric position causes a resultant force, which, rather than restoring the rotor to a central position, acts to amplify its displacement. Insight into the forces acting on the seal filaments is gained by investigating a leaf seal, which consists of a pack of thin planar leaves arranged around the rotor, with coverplates on either side of the leaf pack, offset from the pack surfaces. The leaf seal is chosen due to its geometry being more suitable for analysis compared to alternative filament seals such as the brush seal. Data from two experimental campaigns are presented which show a seal exhibiting negative stiffness and a seal exhibiting a stiffness reduction due to aerodynamic effects. An empirical model for the forces acting on leaf filaments is developed based on the experimental data, which allows separation of mechanical and aerodynamic forces. In addition a numerical model is developed to analyze the flow approaching the leaf pack and the interleaf flow, which gives an insight into the causes of the aerodynamic forces. Using the empirical and numerical models together, a full picture of the forces affecting leaf stiffness is created. Validation of the models is achieved by successfully predicting seal stiffness for a further data set across the full range of operating conditions. The understanding of aerodynamic forces and their impact on filament and seal stiffness allows for their consideration in leaf seal design. A qualitative assessment of how they may be used to improve seal operation in filament seals is given.

The lifetime and reliability of power transformers are primarily dependent on the hot-spot temperature in the windings, as temperature is the most important factor determining the insulation degradation rate. Key to removing the heat from the transformer is the radiator which must be carefully designed to keep the temperatures within limits under all operating conditions whilst minimizing the transformer size, weight and cost. This paper compares the analytical method used to predict the radiator performance with computational fluid dynamics (CFD) models in terms of heat dissipation. It is found that the analytical method and CFD models give similar results in the air natural (AN) cooling modes, whereas the analytical method overestimates the heat dissipation in the air forced (AF) cooling modes. Moreover, the thermal conduction effect in the radiator wall is investigated under different operating conditions and for different radiator sizes using the CFD models. The simulation results indicate that the radiator wall contributes to 6%-10% of the total heat dissipation under some circumstances and therefore should not be simply ignored in radiator models.

Selective removal of coatings by lasers can facilitate the reuse of coated tools in a circular economy. In order to optimise and control the process, it is essential to study the impact of process input variables on process performance. In this paper, coating removal from tooling was carried out using a picosecond a pulsed fibre laser, in order to investigate the effects of laser pulse energy, pulse frequency, galvo scanning speed and scanning track stepover. A fractional factorial design of experiments and analysis of variance was used to optimise the process; considering cleaning rate, specific energy consumption and surface integrity as assessed by changes in surface roughness and composition of the tooling after laser cleaning. The results shows synergy between cleaning rate and specific energy with the laser pulse frequency and galvo scanning speed as the two most significant factors, while the laser pulse energy had the greatest contribution to changes in surface composition. Based on extensive experiments, the relationship between processing rate and system specific energy consumption was mathematically modelled. The paper contributes a new specific energy model for laser cleaning and provides a benchmark of the process energy requirements compared to other manufacturing processes. Additionally, the generic scientific learning from this is that the rate of energy input is a key tool for maximising cleaning rate and minimising specific energy requirements, while the intensity of energy applied, is a key metric that influences surface integrity. More complex factors, influence the surface integrity.

This paper proposes a novel online and self-learning algorithm to the identification of fuzzy neural networks, which not only learns the structure and parameters online but also learns the threshold parameters by itself and automatically. For structure learning, a self-constructing approach including adding neurons and merging highly similar fuzzy rules is proposed based on the criteria of the system error between actual and model output and the maximum firing strength of neurons. In order to achieve the efficient merging computing, a new calculation method of similarity degree between fuzzy rules is developed. Further and more importantly, the varying width of Gaussian membership functions can be learned by itself according to the underfitting and overfitting criteria. Similarly, different from the existing constant threshold of similarity degree for merging, the varying threshold of similarity degree can be self-learned according to the real-time accuracy of model. The proposed self-learning mechanism significantly improves the model accuracy and greatly enhances the easy usability. Several benchmark examples are implemented to illustrate the effectiveness and feasible of the proposed approach.

Seaweed fibre is usually discarded as biomass waste after extraction of useful ingredients from seaweed. However this seaweed fibre, a natural abundant cellulose material with uniform dimensions 10 times smaller than other plant-based fibre can be utilized as electrode material for energy storage. In this work, we converted seaweed fibre into conductive carbon electrodes by a thermal carbonisation method. The morphology, chemical composition and conductivity are highly influenced by the carbonisation temperature. In comparison to other biomass sources such as cotton pulp, seaweed fibre is finer, smoother and more conductive at low carbonisation temperature. These carbonized seaweeds were then used as a supercapacitor, giving a high supercapacitance (226.3 Fg−1) at the carbonisation temperature of 900°C, and good stability within 2400 cycles. This specific capacitance is significantly higher than values obtained from filter paper or cotton pulp.

The focus of this study is to analyse and compare the predictive capabilities of univariate and multivariate methods of forecasting the global horizontal irradiance (GHI) for an hour ahead. The forecasting problem is addressed using supervised machine learning methods. In order to simplify the model, a feature selection algorithm is used to identify the highly correlated features. The forecasting is performed by utilizing popular machine learning algorithms viz., random forest (RF), K-nearest neighbors regression (KNN), support vector machine (SVM) and artificial neural networks (ANN). The paper evaluates and contrasts the effectiveness of these models for this application. Additionally, the study examines how the forecasting models' performance varies throughout the year and across seasons.

National net zero emission targets could, if fully implemented, reduce best estimates of projected global average temperature increase to 2.0–2.4 °C by 2100, bringing the Paris Agreement temperature goal within reach. A total of 131 countries are discussing, have announced or have adopted net zero targets, covering 72% of global emissions. These targets could substantially lower projected warming as compared to currently implemented policies (2.9–3.2 °C) or pledges submitted to the Paris Agreement (2.4–2.9 °C). Current pledges for emissions cuts are insufficient to meet the Paris Agreement temperature goal. The wave of net zero targets being discussed and adopted could make the Paris goal possible if further countries follow suit.