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Different heating processes were applied to pretreat the pulp and paper mill sludge to enhance the hydrolysis stage. Hot air oven, autoclave, microwave and water bath were used for comparison. Chemical analyses exposed that all the pretreatment methods have shown improvement in solubilisation of organic matter. Among the pretreatments studied, heat transfer through hot air (80 °C for 90 min) mode had the highest impact on sludge solubilisation. There was an increase in cellulose (P = 0.0096), acid soluble (P = 0.0053) and insoluble lignin (P = 0.0012), but decrease in hemicellulose (P = 0.0009) content after pretreatment. The XRD and FT-IR spectroscopic characterisation shows the development of aliphatic, unsaturated and carbonyl carbon functionalities in the pretreated samples at higher severities. FESEM picture also confirms the change in structure after pretreatment. Thus, pretreatments contribute to disruption of the lignocellulosic structure making the cellulose easily accessible to acidogenic microorganisms. [ABSTRACT FROM AUTHOR]

A solution-processed conductive paper heater (CPH) with metallic features is used as a new class of low voltage ignitor of nanoenergetic materials (nEMs). In contrast to conventional electrothermal ignition techniques that typically require high operating voltages, the combustion of a paper substrate with a relatively low ignition point generates high thermal energy instantaneously, which makes it possible to ignite nEMs even at low voltages as low as ∼1 V. In addition, the ignition and explosion properties of CPH-based low voltage ignitors are highly controllable and reproducible, mainly due to their simple fabrication and reliable electrical properties. Based on the low voltage ignition property, a compact remote ignition system is demonstrated by integrating wireless a switching circuit, portable batteries, and heater mounter in a small plastic package and operated remotely to ignite the nEMs. [ABSTRACT FROM AUTHOR]

In this paper, we generalize a fast Fourier transforms (FFTs) based preconditioner and propose a novel α -absolute value preconditioner for all-at-once systems from heat equations. Our preconditioner is symmetric positive definite and can also be computed efficiently using fast Fourier transforms or discrete sine transforms (DSTs). Furthermore, we prove that the corresponding preconditioned matrix has a unitary-plus-low-rank decomposition, and the eigenvalues of the preconditioned matrix are clustered at ±1, which leads to fast convergence rate of the preconditioned MINRES method. Finally, numerical examples on all-at-once systems from heat equations with different discretization scheme demonstrate the effectiveness of our new preconditioner. [ABSTRACT FROM AUTHOR]

Abstract: Carbon paper is commonly used as the gas diffusion layer (GDL) in polymer electrolyte membrane (PEM) fuel cells as it exhibits high chemical and mechanical durability. This diffusion medium is also anisotropic, which directly affects its transport properties and specifically the thermal conductivity. In this study, the in-plane thermal conductivity of the carbon paper GDL was determined using thermal diffusivity measurements for a temperature range from −20 to +120°C and four Teflon loadings (0, 5, 20 and 50wt.%). It is important to understand the effect of temperature on the thermal conductivity since PEM fuel cells are designed to operate under various temperatures depending on the application of use. Further, Teflon is used to change the hydrophobic properties of the carbon paper GDL with 20wt.% as the most widely used percentage. In this study, the Teflon loadings were chosen to gain a comprehensive understanding of the thermal resistance due to Teflon. In this study, a quasi-steady method was used to measure the thermal properties of the carbon paper; hence, the phase transformation in the presence of PTFE was investigated. The thermal conductivity decreases with an increase in temperature for all samples. The addition of as little as 5wt.% Teflon resulted in high thermal resistance decreasing the overall thermal conductivity of the sample. Further addition of Teflon did not have major effects on the thermal conductivity. For all treated samples, the thermal conductivity lies in the range of 10.1–14.7W/mK. Finally, empirical relations for the thermal diffusivity and conductivity with temperature were deduced. [Copyright &y& Elsevier]

• Saturated-wave theory for snubber modeling is modified to fix three conceptual errors. • The equivalent resistance and inductance of the snubber are recalculated. • Calculating the thickness of eddy-current region no longer relies on external circuit. • The current rise of the model is nearly the same as the experiment with about 10 % over-estimated peak shorting current. Core snubber is a common device used for breakdown protection in auxiliary heating systems. It absorbs energy from the high-voltage power supply to protect the load. The existing snubber models are based on saturation-wave theory, but the theory still has several conceptual problems. In this paper, an improved saturated-wave theory is presented. We consider that the eddy current region of the tape needs to be layered and that there is an unsaturated region in the tape which enables the snubber to be equated to an inductor. Then we divided the working process of snubber into 4 stages and rederived the circuit model of the snubber. The comparison with the existing simulation model shows that the new model in this paper is closer to the experimental data, especially in the rising phase of short-circuit current. It can more accurately analyze the conditions within a few microseconds after breakdown, and give a useful reference for the design of breakdown protection and power supply systems. [ABSTRACT FROM AUTHOR]

• Comprehensive CHP unit scheduling formulation. • Quality assurance through optimal gap evaluation. • Two-stage stochastic approach with MINLP. • Uncertainty management in unit commitment. • Modeling of electrical and thermal ramp constraints. Renowned for their remarkable overall efficiencies ranging from 70% to 90%, combined heat and power systems stand as a pivotal strategy for optimizing energy consumption by capitalizing on the synergistic relationship between electricity and thermal energy production. However, achieving optimal performance in combined heat and power systems remains a formidable challenge due to the intricate interplay of numerous variables. This paper presents a novel approach to daily scheduling optimization for combined heat and power units, focusing on the integration of electrical and thermal storage systems and meticulous consideration of security constraints. The optimization of combined heat and power unit scheduling introduces a mixed-integer nonlinear programming challenge, replete with deterministic and random variables. Addressing this complexity requires resilient solutions. In this study, we employ a multilevel optimization technique, transforming the problem into a bilevel structure. The initial step involves mapping operating parameters and minimizing costs through a water cycle optimization algorithm, laying a robust foundation for combined heat and power unit operation. Subsequently, we immerse ourselves in the realm of stochastic contingency scenarios, acknowledging the myriad uncertainties inherent in real-world systems. To empirically validate the efficacy of our proposed algorithm, extensive simulations are conducted on IEEE 18-bus and 24-bus test systems that emulate practical power networks. The results unequivocally showcase the power of our approach in navigating the complexities of optimal CHP unit planning. This paper's contributions lie in its innovative multilevel optimization technique, adeptly addressing both deterministic and stochastic aspects, ultimately paving the way for increased energy efficiency and enhanced system reliability in practical applications. [ABSTRACT FROM AUTHOR]

Integrated Energy Systems (IES) serve as an effective solution to address grid fluctuations. However, mainstream IES still adhere to established supply strategies such as thermal and electrical non-conversion (TENC), heat determined by power (HDP), and power determined by heat (PDH). These strategies overlook the additional flexibility generated by the synergy between electricity and heat, preventing the full realization of their advantages in supporting the grid. This paper proposes a Flexible Scheduling (FS) operational strategy for IES that maximizes the utilization of flexibility resources to meet the demands of heating, cooling, and electricity while maintaining grid stability. The superiority of this strategy is analyzed through an IES multi-objective optimization scheduling model and a comprehensive flexibility margin model. The results of a case study indicate that the FS strategy reduces total costs by 19.9% compared to TENC, 16.6% compared to HDP, and 5.2% compared to PDH. It exhibits the strongest support for the grid, increasing the overall flexibility margin of IES by 40.5% compared to TENC, 12.7% compared to HDP, and 8.2% compared to PDH. The FS-based IES operational strategy proposed in this paper contributes significantly to the flexible and economical operation of IES. • Established a multi-objective optimization scheduling model for integrated energy systems that considers both economic and environmental factors. • Established a model for the flexibility margin of system electricity and heat. • Proposed the system's "flexible scheduling" operating strategy and validated it. [ABSTRACT FROM AUTHOR]

Although fully automated, operation of the District Heating Systems (DHS) is considered reactive and simplistic since control decisions are most often made based on the real-time ambient temperature. The research presented in this paper is aiming at facilitating proactive DHS control, by using predictive modeling techniques based on modern Artificial Intelligence (AI) architectures, namely the Deep Learning (DL)-based multivariate time-series forecasting. Proactive approach involves controlling fluid temperature in the DHS supply line, based on relevant meteorological features, heat demand in the past and weather forecast. In this paper, we evaluate state-of-the-art DL architectures for multivariate one-step and multi-step prediction based on Long-Short Term Memory (LSTM) approach, namely, stacked LSTM, bi-directional LSTM, encoder-decoder and attention models. The initial results of forecasting heat demand and local explanations are provided for the case of small 8MW DHS. For local explanations, Local Interpretable Model-agnostic Explanations (LIME) was successfully validated. [ABSTRACT FROM AUTHOR]

Accurate heating load prediction is essential to supply-demand collaboration in district heating systems and energy sustainability. With the development of the Internet of Things technology, massive monitoring data is collected that provides abundant data sources for the prediction models. However, the missing data from equipment anomalies, network transmissions and the complexity of heat load changing cause difficulty in realizing accurate heat load prediction. Therefore, the hybrid model based on bidirectional long short-term memory network and temporal convolutional network proposed in this paper to improve the accuracy of the heat load prediction from the aspects of reconstruction of missing values and extraction of complex features. The bidirectional long short-term memory algorithm imputes missing values based on bi-directional features of existing data and provides solid data foundation for subsequent training of predictive models. The temporal convolutional network achieves high-level feature extraction and parallel computation, which contributes to the effective modeling of complex changes in heat load and the realization of accurate heat load prediction. Comparative study was conducted with four heat exchange stations of actual environment to evaluate the performance of the prediction model. The results showed the mean absolute percentage error of the hybrid model decreased to 2.47% which is lower than the State-of-the-Art models, such as long short-term memory, temporal convolutional network, and support vector regression etc. The superior results further validated the feasibility of this hybrid model in heat load prediction. • The missing values in heating system were reconstructed by deep learning model. • A hybrid heating load prediction model was proposed considering missing values. • Detailed experiments were conducted to validate the model's superiority. [ABSTRACT FROM AUTHOR]

Hydrogen propulsion is generally treated as the ultimate net zero-emission option for aviation, therein liquid hydrogen storage appears to provide the only feasible solution for aircraft with the constraints imposed by aircraft weight and volume. Hydrogen liquefaction consumes a great amount of energy, which significantly boosts the cost of hydrogen as an aviation fuel. Besides the H 2 chemical exergy for combustion to provide thrust, the H 2 physical exergy in the form of cold energy is also a kind of high-quality clean energy to produce power output, which offers great opportunities to achieve cost-effective use of hydrogen fuel. Thus, this paper presents a Rankine cycle and H 2 direct expansion cycle (RC-DEC) combined power generation thermal management system for the simultaneous utilization of exhaust gas heat exergy and hydrogen fuel cold exergy from the liquid hydrogen-fueled turbojet engine. In the Rankine cycle, the transcritical mode is applied on the hot side while the liquid separation condensation concept is adopted on the cold side to achieve better thermal matchings with heat and cold sources. The hydrocarbon/inert gas binary mixture is proposed as the working fluid of the Rankine cycle. The effects of key thermodynamic parameters and the influence of Para-Ortho hydrogen conversion on system performance are discussed, then a comparison of the mixture working fluid is conducted. Results show that there exists an optimal separation temperature ratio and condensation pressure of RC to obtain maximum total net power output. As the DEC expander inlet pressure increases, the total net power output first increases and then levels off. The introduction of the Para-Ortho hydrogen conversion has a negligible impact on net power output but leads to a significant reduction in the exergy efficiency, which is attributed to the cold energy release nature of Para-Ortho hydrogen conversion. The results of the working fluid comparison indicate that the optimal inert gas retardant for CH 4 is Kr, while those for C 2 H 6 and C 3 H 8 are Xe to achieve the maximum net power output and exergy efficiency of the proposed power generation system. Among them, C 2 H 6 /Xe(0.6/0.4) obtains the maximum net power output of 2717.9 kW and maximum exergy efficiency of 33.1%, which suggests an opportunity to provide megawatts of electrical power for the aircraft in place of the APU. • RC-DEC combined thermal management system is proposed for LH 2 turbojet engine. • The hydrocarbon/inert gas binary mixture is proposed for LH 2 cold exergy recovery. • The influence of the Para-Ortho hydrogen conversion on the system is revealed. • The optimal inert gas retardant for the selected hydrocarbons is determined. [ABSTRACT FROM AUTHOR]

As the coupling between power distribution systems (PDSs) and district heating systems (DHSs) becomes tighter, it is critical to develop a coordinated strategy for load restoration in integrated electric and heating systems (IEHSs) after natural catastrophes. Similar to PDS reconfiguration, DHSs can modify network topology by remotely operating the ties and sectionalizing valves. A coordinated reconfiguration with soft open points (SOPs) is proposed in this paper for resilience-oriented restoration in IEHSs, which mitigates the fault propagation during fault isolation and explores the flexibility of network topology variation with SOPs for load restoration. To guarantee the privacy of electric and heating systems, we propose an adaptive alternating direction method of multipliers (ADMM), which divides the original problem into PDS and DHS subproblems. The proposed algorithm can intelligently dispatch SOPs and switches in the PDS sub-problem and valves in the DHS subproblem. Comprehensive case studies are carried out to illustrate the effectiveness of coordinated reconfiguration with SOPs for load restoration and verify the proposed algorithm. When considering coordinated reconfiguration with SOPs under the PDS fault scenario, the resilience metrics value increases by 9.6% compared to only PDS reconfiguration. • A Distributed coordinated load restoration strategy in integrated electric and heating systems is proposed. • Soft Open Point flexibility is fully exploited to improve load restoration levels. • Coordinated reconfiguration of the PDS and DHS is provided to improve service restoration level. • The adaptive ADMM is utilized to guarantee the privacy security of electric and heating systems. [ABSTRACT FROM AUTHOR]

Solar thermal energy is one of the important sources of renewable energy. The solar thermal energy gives clean energy which can be utilized for industrial applications. Industrial heaters which require heat energy for many industrial uses can be attained using these solar thermal absorbers. The solar thermal absorber is designed using a layer design that consists of material compositions of Titanium (Ti) and Stannic selenide (SnSe 2) for ground and substrate sections respectively. A graphene layer which has the good properties to be used in solar absorbers is added between the Aluminum and SnSe 2 material. A thin graphene section is inserted above the SnSe 2 substrate and below the Ti resonator. To catch the good absorption in the current design, the best four wavelengths (micrometer) have been attached such as 0.22, 0.8, 2.46, and 2.85. This design's contribution can be studied in 4-atm regimes (from UV, V to NIR, and MIR). According to the wavelength and bandwidth ranges, the current absorption explores more than 97% (97.4%) in between 2.4 and 3 μm (600 nm) bandwidth and exceeds 95% (95.2%) from 0.2 to 1 μm (800 nm) respectively. To the overall range of design, it extracts 90.3% for the 2800 nm band between 0.2 and 3 wavelength regime. The flow of the presentation of the proposed paper is (i) Introduction (ii) Design and Parameters, and (iii) Results and Discussions. The explored absorber can be effective in water heating and swimming pool heating for homes. Moreover, it can also be applied in large industries as a solar thermal absorber for heating applications. [ABSTRACT FROM AUTHOR]

Clarifying the aging characteristics of aluminum alloys during continuous heating is crucial for formulating isothermal and non-isothermal aging (continuous heating aging) processes. This paper investigates the stress relaxation characteristics of an Al-Cu-Mg-Ag alloy under three-point bending during continuous heating. Taking into account the mechanical properties and precipitate analysis, it demonstrates the feasibility of using the stress relaxation method to determine the peak aging temperature during continuous heating. This approach is efficient, requires minimal sample, and yields continuous data. The peak aging temperature of the sample increases from 260 °C to 305 °C when the heating rate increases from 1 to 3 °C/min with the same initial load (3 N). The peak aging temperature is around 280 ℃, when the initial load increases from 1 N to 9 N with the same heating rate (2 °C/min). Under low temperatures (25 ℃∼ 200 ℃), the sample displays the presence of GP zones, and a few Ω precipitates during the continuous heating process of 2 ℃/min. As the temperature increases, the GP zones dissolve and transform into the Ω precipitates. A large number of Ω precipitates appear in the matrix in a continuous precipitation manner when the temperature reaches 235 °C. The precipitation strengthening effect is strongest at 280 °C, and the Ω precipitates begin to coarsen as the temperature exceeds 280 °C. [Display omitted] • A method to determine the continuous heating peak aging temperature of aluminum alloys was proposed. • The peak aging temperature of Al-Cu-Mg-Ag alloy was related to the heating rate. • The evolution of the precipitates during continuous heating aging of Al-Cu-Mg-Ag alloy was obtained. [ABSTRACT FROM AUTHOR]

• A defect model modification method with surface heat flux identification is proposed for thermal protection system. • Levenberg–Marquardt method is adopted to identify surface heat flux, and whether the defect has occurred is determined. • A defect model modification method is proposed from the knowledge of the identified heat flux. • An experiment is designed to prove good accuracy of the proposed method. Thermal protection systems (TPS) have become a key issue in ensuring the reliability of hypersonic flights. Aimed at monitoring the thermal loads and possible defects for TPS, a defect model modification method with surface heat flux identification is proposed in this paper. Firstly, by the measured temperature from a distributed sensor network and the initial TPS model, the surface heat flux was identified with the Levenberg–Marquardt Method (LMM). If there existed outliers in the identified heat flux distribution, it can be visually indicated that the defect occurred. Then, defects were represented by shape parameters and can be determined by the model modification from the knowledge of the identified heat flux and the measured temperature. The effectiveness of the proposed method was verified numerically using TPS containing a surface defect. Meanwhile, the effects of various factors on the identified results were investigated in detail, such as defect sizes, defect shapes, sensor locations, and real aerodynamic heating. Finally, the proposed method was successfully applied to an experiment, and results demonstrated that the proposed method can achieve good identification results by experimentally measured temperature. [ABSTRACT FROM AUTHOR]

Cleaner end-uses of energy, including electrified heating, represent a cornerstone of a decarbonised energy transition. On the other hand, many governments have adopted measures to mitigate energy poverty and facilitate access to modern energy services, including heating. Both objectives may be interrelated, since energy poor people are less likely to use cleaner (and costlier) heating fuels. This paper analyses the impact of energy poverty on the decision to use different heating sources and identifies whether the events of COVID and the Ukraine war have affected this decision. Thus, a multinomial probit model is estimated using information from a large database of Spanish households in 2019, 2021 and 2022. The results show that being energy poor increases the probability to use carbon-intensive energy sources for heating compared to electricity, and that COVID and the war in Ukraine have affected this relationship. The increase in energy poverty over those years has negatively affected the decarbonisation goal with respect to heating choices. The influence of those events on the probability to use electric heating depends on some household and dwelling features. Therefore, mitigating energy poverty increases the welfare of energy poor people while supporting the choice of cleaner heating. [ABSTRACT FROM AUTHOR]

• The main thermal-hydraulic parameters of the ITER IBED PHTS have been assessed under selected operational scenarios. • The Fathom model of the ITER IBED PHTS has been revised and updated. • Three scenarios are presented, i.e. one that simulates hot standby conditions and the other two that simulate the normal operation. • The study confirms the correct operation of the system while highlighting some potential criticalities. One of the key elements for the success of ITER is the efficient removal of the thermal power generated by the deuterium-tritium fusion reaction within the confined plasma. The Integrated Blanket ELM/VS Coils and Divertor (IBED) Primary Heat Transport System (PHTS) is a pressurized, closed-loop cooling system designed to supply cooling water to the in-Vessel components. To support process design of the IBED PHTS, a thermal-hydraulic research campaign has been conducted to analyse the proper operation of the system during selected operational scenarios. The work has been carried out using the commercially available thermal-hydraulic software AFT Fathom, performing steady-state hydraulic and heat transfer analyses of complex hydraulic systems. The present paper summarizes the research activity, describing the computational model used and the scenarios investigated, as well as the results obtained and their critical discussion. [ABSTRACT FROM AUTHOR]

For the current molten salt storage heat to medium and high frequency electromagnetic coupling heating mainly, there are problems such as high failure rates and difficulties in achieving high-voltages and high-power. This paper proposes a power-frequency electromagnetic coupling direct heating technology that can realize high-voltage and high-power heating of molten salt. According to the theory of electromagnetic induction heating and the working principle of transformer, a power frequency electromagnetic coupling heating molten salt heat storage system that can achieve uniform heating effect is designed. By studying the influence of different heating power and different heat storage materials on parameters such as heat storage time, heat storage performance, and heat storage uniformity, a theoretical basis is provided for the system to determine a reasonable heating power and scope of application. A heat exchange tube layout scheme was proposed for the two operating modes of heat release, and simulation analysis was conducted. And the results show that the heat energy can be transferred outward quickly and uniformly. Through theoretical calculation and simulation experiments, the system can realize uniform heating and heat release of molten salt, and proposes a new solution to the current technical problems in the field of high-voltage and high-power direct heating of molten salt heat storage systems. [ABSTRACT FROM AUTHOR]

This paper experimentally investigates the effect of increasing ice thickness at a heater's edge on the thermal energy required to de-ice ice at the leading's edge. A correlation between ice thickness at the stagnation line and ice thickness at the heater edge is developed for the leading edge of a cylinder surface. An experimental approach is used to investigate whether the increase in ice thickness at the heater's edge is linked to the increase in ice thickness at the stagnation line. The de-icing investigation shows that as ice thickness at the heater's edge grows, the de-icing duration significantly increases. The results of this paper suggest that employing a correlation between the ice thickness at both the stagnation line and the heater's edge can help reduce the thermal energy required to remove ice from the leading edge of an airfoil or cylindrical surface. • Defining the ice thickness relationship at the stagnation line and heater edge for cylindrical ice accumulation. • Examining the impact of ice thickness at the heater edge on the thermal energy required for de-icing. • Using imaging techniques to measure accumulated ice on a cylindrical surface. • Using thermal imaging to analyze the behavior of ice during the de-icing process. [ABSTRACT FROM AUTHOR]

In this paper the aerothermal heating of a reusable launch vehicle is reconstructed on the basis of temperature measurements taken in the thermal protection system of this vehicle. The discussed integrated thermal protection system is composed of three layers. Mathematical model, describing the problem, takes into account the dependence on temperature of the material parameters as well as the thermal resistances occurring in the contact zones of the layers, which is a novelty in the proposed approach. For solving the direct problem, the implicit scheme of the finite difference method is applied. Next, by using the solution of the direct problem, the Tikhonov functional is created, which describes the error of the current approximate solution. Whereas for determining the solution of the inverse problem the Levenberg-Marquardt method, modified and adapted to the Tikhonov functional, is used. The paper presents the mathematical model of the problem and the method of solution together with the selected examples illustrating its exactness and stability. In order to better examination of the solution method some various values of parameters are taken in the demonstrated examples. • Reconstructing an aerothermal heating in space vehicle protection system with temperature dependent material properties. • Reconstructing an aerothermal heating taking into account the thermal resistance between layers. • Solving the problem for three layers model of the thermal protection system. • Inverse problem solved for input data taken from NASA measurements. • Heat flux measured by NASA reconstructed with good precision and stability. [ABSTRACT FROM AUTHOR]

Subgrade frost heave is the main reason that affects the safe operation and comfort of trains during the cold season. Solar heating system based on heat pipe technology is a promising method to mitigate the frost heave by raising the subgrade temperature. In this paper, a field experiment was conducted to evaluate the heating performance of the solar heating system based on heat pipe technology in the cold season. In addition, the heat collection performance and stability of the system are compared with other solar heating systems. Finally, its applicability is discussed. Experimental results revealed that the solar heating system based on heat pipe technology can effectively raising the soil temperature and mitigate the frost heave of subgrade. During the experiment period, the soil temperature at the depth of −0.5 m in the experiment site was 5 °C higher than that of the comparison site, and the maximum freezing depth was 0.4 m, which was 56 % lower than that of the comparison site. The mean daily temperature of heat collection units (HCUs)fluctuated around 30 °C, and the mean daily temperature of the two-phase closed thermosyphons (TPCTs) fluctuated between 15 °C and 30 °C. The heat transfer efficiency of System 1 and System 2 is greater than 0.5, and the total effective heat transfer during the experiment period is 512 MJ and 283 MJ, respectively, and the heat transfer difference is about 2 times. Compared with other solar heating systems, the system proposed in this paper has good heat collection performance and more superior system stability. The mean daily heat transfer of System 1 and System 2 is 6.4 MJ and 3.71 MJ, respectively, which is 62.9 % higher and 5.6 % lower than the mean daily heat loss of subgrade of 3.93 MJ, respectively. The system has the application prospect of low maintenance cost and good long-term anti-frost heave effect. • A solar heating system based on heat pipe technology was proposed for mitigating subgrade frost heave. • The soil temperature can be effectively increased under the heating effect of the system. • The system can provide effective heat transfer higher than 62.9 % of the mean daily heat loss of subgrade. • To provide a reference of using solar energy and heat pipe technology for mitigating subgrade frost heave. [ABSTRACT FROM AUTHOR]

District heat load forecasting is a challenging task that involves predicting future heat demand based on historical data and various influencing factors. Accurate forecasting is essential for optimizing energy production and distribution in district heating systems. However, most existing forecasting models lack transparency and interpretability and fail to capture the spatial–temporal dependencies in the data. Moreover, they often require a large amount of annotated data for training, which can be costly and time-consuming to obtain. In this paper, we present a novel approach to district heat load forecasting, which involves predicting future heat demand based on historical data and various influencing factors. The proposed approach is based on an Active Graph Recurrent Network (Ac-GRN), which leverages the strengths of active deep learning and graph neural networks to capture the complex spatial–temporal dependencies in the data. The approach also provides explainability for its predictions by using correlation-based attribution methods. The active deep learning component can effectively select the most informative and representative samples from a large pool of data, reducing the frequency and cost of data collection and human effort. The graph neural network component can model both linear and nonlinear relationships among heat meters using bidirectional recurrent connections, enhancing the accuracy and robustness of the predictions. We conduct extensive experiments and compare our approach with eleven state-of-the-art models on a real-world dataset of district heating consumption data from Danish residential buildings. Our results show that our approach outperforms other models in terms of accuracy, robustness, reliability, and computational efficiency for multi-horizon multi-step district heat load forecasting. Our approach also provides meaningful explanations for its predictions by highlighting the most influential factors and heat meters for each prediction. This paper makes a novel contribution to district heat load forecasting with explainability. • Novel approach for district heat load forecasting with active deep learning and graph neural networks. • Explainable predictions using gradient-based attribution methods. • Outperforms state-of-the-art models in accuracy and robustness. • Evaluates on real-world district heating data and conducts ablation studies. [ABSTRACT FROM AUTHOR]

The district heating system (DHS) is one of the essential carriers for coordinating renewable energy with fossil energy and achieving flexible energy consumption. Considering the uncertainty of both the renewable energy units' power and the consumers' aggregate loads impact the transport process of the DHS, the thermal characteristics of the DHS transportation and the node temperature response under the source-load uncertainty need to be quantified and analyzed. This paper proposed a method to calculate the nodes' temperature dynamic response of the DHS under multiple source-load uncertainty scenarios. The prediction and combination methods of supply and demand probability intervals of source and load nodes under varying credibility levels were investigated. Additionally, the effects of source-load uncertainty boundary conditions on the DHS transport process were analyzed. The temperature response of the nodes was calculated based on the established dynamic DHS model under multiple source-load uncertainty scenarios. A DHS in Beijing was selected for case validation and analysis, and it has 90 nodes and 109 pipes. The simulation results showed that the relative average error of node flow rate in the dynamic DHS model was 3.02%, and the average difference in node temperature was 1 °C. The probability distribution semi-analytical method and the Bayesian credible interval calculation method can accurately describe the uncertainty on both source and load sides. The models and algorithms proposed in this paper could effectively quantify the nodes' dynamic temperature response under the source-load uncertainty. • Proposed uncertainty quantification models for the source and load nodes of DHS. • Developed a novel credible interval calculation method for nodes' thermal power. • Quantified nodes' temperature dynamic response considering source-load uncertainty. [ABSTRACT FROM AUTHOR]

Drones and UAVs are gaining worldwide popularity and are now considered a popular choice for both military and commercial applications. Icing poses tremendous safety and performance concerns for the operation of all types of drones. This paper is part of a project that studies icing effects on the hovering 0.66 m diameter Bell APT70 drone rotor and the development of potential ice protection systems. The objective of this paper is to investigate the use of electrothermal heaters with severe icing conditions and to characterize the energy efficiency of anti-icing or de-icing regimes. Rotor speeds of 3880, 4440 and 4950 RPM were used while two air temperatures, −5 and −12 °C, were also tested. The heat transfer profile on the blade was studied using dry run tests where the rotor operated with heating but without water spray. Anti-icing tests with variable heating power were tested to determine the location of the initial ice accumulation as well as the minimum heating power requirement to protect the leading edge. Moreover, anti-icing tests with constant heating rates were done and compared to previous tests of unprotected blades, under similar condition. On the other hand, de-icing tests with various heating cycles were also carried out. Results indicate that although de-icing requires significantly less heating energy compared to anti-icing, there is clear trade-off on rotor stable aerodynamic output, electrical power consumption and vibration levels, depending on the adopted de-icing mode. Future work is about investigating the rise of secondary effects, such as shed ice impact due to de-icing. Work is also planned for a hybrid ice protection system that combines electro-thermal heaters with icophobic or superhydrophobic coatings. [ABSTRACT FROM AUTHOR]

To decarbonize the heating sector, the 4th and 5th generations of district heating networks have been identified as promising solutions. They offer superior energy efficiency, economic viability, and environmental advantages compared to decentralized, individual heating systems. However, they raise several challenges concerning their design and control optimization due to their size and the operational constraints of the production systems involved such as inertial heat generators, intermittent renewable energy sources and thermal energy storage. As a result, numerical simulations of these networks are computationally heavy which makes fast optimal control a complex and challenging task. A common strategy to address this limitation is to formulate reduced order models or to establish fast and yet accurate surrogate models. In this work, we present a novel surrogate modeling framework to rapidly predict district heating networks transients. Our model is based on a physics-guided spatio-temporal convolutional graph neural network. While similar work focused mainly on the prediction of thermal loads, this paper tackles the challenge of simulating complex and non-linear behaviors of the distribution network of district heating systems. The results show that the simulation time using our model is 99% less than a physical simulator while maintaining a high accuracy. In addition, we have conducted an ablation study and a residual analysis to test the robustness of the proposed model. Furthermore, the generalization ability of our approach is assessed by evaluating it against different district heating network topologies. • A spatio-temporal graph neural network is used to predict district heating network dynamics. • A framework enables interaction between physical simulator and surrogate model. • The model achieves high accuracy and captures diverse network dynamics. • Computation time reduction unlocks global optimization with full dynamics of the system. [ABSTRACT FROM AUTHOR]

A comprehensive understanding of the thermal runaway (TR) and combustion characteristics of lithium-ion batteries (LIBs) is vital for safety protection of LIBs. LIBs are often subjected to abuse through the coupling of various thermal trigger modes in large energy storage application scenarios. In this paper, we systematically investigated the TR and combustion characteristics of heating + overcharge and heating + short circuit at different temperatures and compared them with individual heating, overcharge, and short circuit. Additionally, we analyzed the TR and combustion hazards of different thermal triggering modes using Analytic Hierarchy Process (AHP). The results show that heating + overcharge has a shorter time of safety valve opening and TR , a lower thermal runaway temperature, a higher peak heat release rate (HRR), and is more hazardous than heating and overcharge. Compared with heating, heating + short circuit shortens safety valve opening time and increases peak HRR ; versus short circuit, heating + short circuit lowers TR temperature and TR time, enhances peak HRR , and causes a higher hazard. The AHP analysis indicates that the TR temperature and fire growth index are the most critical parameters and that heating + overcharge has the biggest TR and combustion hazards; besides, heating + short circuit exists higher TR risk and hazards than short circuit and greater combustion risks and hazards than heating. The research findings can provide valuable guidance for protecting and preventing energy storage LIBs TR. • Investigate the behavior of thermal runaway and combustion properties of LIBs with varying coupled trigger modes. • The external short circuit shortens the valve opening time and increases the peak heat release rate. • The greatest risk and hazard of thermal runaway and combustion occurs when heating and overcharging are combined. [ABSTRACT FROM AUTHOR]

Efficient electric heat pumps that replace fossil-fueled heating systems could significantly reduce greenhouse gas emissions. However, electric heat pumps can sharply increase electricity demand, causing high utility bills and stressing the power grid. Residential neighborhoods could see particularly high electricity demand during cold weather, when heat demand rises and heat pump efficiencies fall. This paper presents the development and field demonstration of a predictive control system for an air-to-air heat pump with backup electric resistance heat. The control system adjusts indoor temperature set-points based on weather forecasts, occupancy conditions, and data-driven models of the building and heating equipment. Field tests from January to March of 2023 in an occupied, all-electric, 208 m 2 detached single-family house in Indiana, USA, included outdoor temperatures as low as − 15 ° C. On average over these tests, the control system reduced daily heating energy use by 19% (95% confidence interval: 13%–24%), energy used for backup heat by 38%, and the frequency of using the highest stage (19 kW) of backup heat by 83%. Concurrent surveys of residents showed that the control system maintained satisfactory thermal comfort. The control system could reduce the house's total annual heating costs by about $300 (95% confidence interval: 23%–34%). These real-world results could strengthen the case for deploying predictive home heating control, bringing the technology one step closer to reducing emissions, utility bills, and power grid impacts at scale. • First field deployment of predictive control for an air-to-air heat pump in a cold climate. • Review of all known field studies of supervisory control for residential HVAC. • Reduced heating energy use by 13%–24% and use of highest-stage backup heat by 83%. • Occupants reported similar thermal comfort to benchmark control system. • Discussion of deployment labor, costs, challenges, and scalability. [ABSTRACT FROM AUTHOR]

The use of machine learning in building technology has become increasingly important in recent years. One of the applications is heating load prediction, which enables demand-side flexibility. Most studies consider the heating load prediction without sufficient context with the existing building characteristics. For an accurate load prediction, suitable features have to be selected according to their importance, the feature importance (FI). The scope of this paper is to investigate whether there is a relationship between the building characteristics and the FI and if so, how strong this relationship is. Additionally, an analysis has been conducted to determine which building characteristic have the most significant impact on FI. For this purpose, a full factorial design of a room with six different building characteristics is carried out. In total, the heating load is calculated for 15 552 room variants. The thermal balance, correlation, random forest FI, permutation FI and SHapley Additive exPlanations (SHAP) values are calculated for these different rooms. The local SHAP values were used to explain the model. These values also provide insight into the interaction of individual features with the heating load. For most variants, the outdoor temperature had the highest FI. It is investigated which building characteristics have the greatest influence on the thermal balance, correlation, FI and SHAP values. A relationship was found between the proportion of thermal balance, the correlation between the features and the label as well as the FI. The greatest association with the thermal balance characteristics was found for the SHAP values. The study shows the systematic relationship between building characteristics and FI. Therefore, FI should always be considered in the context of building characteristics. [Display omitted] • SHAP values provide an excellent way of showing how features affect heating load. • Comparison of various feature selection methods for 15 552 different rooms. • Characteristics of the building are reflected in the feature importance. • Air exchange rate has the greatest influence on the feature importance. [ABSTRACT FROM AUTHOR]

Heat storage is a critical measure to realize the utilization of waste heat and to enhance the heating capacity of the medium-deep U-type borehole heat exchanger (MDUBHE) system. However, the effects of heat storage on the operation of the MDUBHE system remain unclear. The effects of heat storage measures on the building and the environment have not been assessed. In this paper, the effects of heat storage measures on system performance are revealed and assessed using the numerical heat transfer model. The results show that heat storage measures are particularly necessary in severe cold regions of China. The minimum value of the storage inlet temperature in this study should be more than 42.25 °C, and the flow rate is recommended at no more than 15 kg/s. Although increasing the inlet temperature of heat storage enhances the MDUBHE system's heating performance, the storage system's energy and exergy efficiencies are attenuated. Heat is mainly stored in the underground region within 6 m from the MDUBHE and at a depth of up to 2000 m, and the shape of the thermal plume is an inverted funnel. After adopting heat storage measures, the heating area supplied to buildings by the MDUBHE system increases, and reduces environmental pollution. Compared with the no heat storage measure, the heating area of the MDUBHE system is increased by 6770 m2 when the storage inlet temperature is 80 °C, and the corresponding solar collector area needs to be 756.1 m2. When T i n s increases from 45 °C to 80 °C, the reduction of CO 2 emissions increases by 12.43 tons, 21.05 tons, 38.26 tons, 55.41 tons, and 72.50 tons, respectively. This study could promote the application of the MDUBHE system and the heat storage system in severe cold regions. [Display omitted] • A heat storage system based on the medium and deep U-type borehole heat exchanger is proposed. • The energy efficiency and the exergy efficiency of the heat storage system are clarified. • The effects of heat storage on the temperature field of rock and soil are revealed. • The effects of heat storage on system performance and the environment were assessed. [ABSTRACT FROM AUTHOR]

This study assesses alternative energy technologies (i.e., PV and battery systems, electric heat pumps, hybrid gas heating with solar thermal energy) in terms of profitability and CO 2 emissions, for the case of two simulated typical households living in detached houses in Germany. Under the status-quo regulatory framework, the energy transition in the heating sector is fostered through grants for replacing old heating systems, whereas PV generation is fostered by feed-in tariffs and indirect subsidies for self-consumption. This study considers an alternative regulatory scenario with a more market-oriented approach, finding that a CO 2 -oriented reform of energy surcharges and taxes, as well as a reform of network charges, can support a more cost-efficient energy transition in the residential sector. The paper concludes with a discussion of the consistency, cost efficiency and effectiveness of past and current policies underpinning the energy transition in the residential sector. • Assessment of home energy systems across 2 households and 2 regulatory scenarios. • Consideration of PV, batteries, heat pumps and hybrid gas-solar heating systems. • Comparison of subsidies and flat energy tariffs vs. cost-reflective, dynamic tariffs. • Market-oriented approach incentivizes far more cost-efficient CO 2 emission reduction. • The German residential energy sector needs a consistent regulatory framework. [ABSTRACT FROM AUTHOR]

Given the continuous expansion of heating areas in recent years, the design of a precise and dependable district heating system (DHS) has become increasingly crucial. Traditional control decisions are made based on real-time environmental temperature feedback, often leading to uneven heating on the user side and affecting residents' comfort. This paper proposes an intelligent control strategy based on the deep reinforcement learning recurrent deterministic policy gradient (RDPG) algorithm for DHSs. To explore the control performance of the RDPG algorithm on DHS, we have meticulously modeled the pivotal components of the DHSs, namely plate heat exchangers, secondary heating pipe networks, and heat users. Moreover, taking into account the periodic factors in heating regulation, the traditional recurrent neural network (RNN) in the recurrent deterministic policy gradient (RDPG) algorithm has been replaced with the long short-term memory (LSTM) network. The proposed algorithm was trained using actual data from a heat exchange station in Tianjin and compared with reinforcement learning algorithms such as TD3, DPPO, DDPG, and A3C in terms of training rewards, effectiveness, and training stability. The results of the models are evaluated and visualized. Experimental results show that the proposed control method based on the RDPG algorithm, compared to other control schemes, can achieve the highest training reward and the most stable control performance, with an indoor temperature fluctuation range of only 0.1 °C. [ABSTRACT FROM AUTHOR]

The reversible solid oxide cell (rSOC) is a promising technology for advancing energy decarbonization by enabling bidirectional conversion between electricity and hydrogen in a single device. However, previous studies have not fully explored the operational flexibility of rSOCs due to inadequate consideration of heat recovery potentials and dynamics of operating mode transitions. To address this research gap, this paper presents a model-based optimal operation method for managing multi-energy transactions in rSOC-based microgrids, aiming to minimize operation costs. The method incorporates detailed operational models of the rSOC, including a lumped thermal model to account for heat recovery capability and modeling of various operating modes and their transitions. Additionally, a linearization process is introduced to address nonlinear and implicit operational constraints, resulting in a computationally efficient mixed-integer linear programming (MILP) formulation for the operation model. Comparative case studies are conducted using modified energy portfolios of a Danish energy island. The results demonstrate that the proposed method effectively captures operating mode transitions within the rSOC and enhances its profitability via waste heat recovery. Notably, the rSOC model contributes to enhanced operational flexibility through heat recovery behaviors and a wider temperature range, resulting in substantial economic savings for the microgrid. • Dynamic transition modeling of operating modes in rSOCs. • Waste heat recovery analysis from rSOCs for district heating systems. • Computationally efficient economic operation model for rSOC-integrated microgrids. • Unleashing rSOC flexibility through heat recovery and extended temperature range. • Enhanced cost-effectiveness of microgrids through heat recovery benefits of rSOCs. [ABSTRACT FROM AUTHOR]

• STEAM will host the mock-up of the EU-DEMO Steam Generators. • STEAM primary loop has been investigated with RELAP5/Mod3.3 system code. • DEMO normal operations have been studied including pulse-dwell transitions. • Different primary loop management strategies have been numerically simulated. • Setting the primary average temperature minimizes the loop operative fluctuations. The Water Cooled Lithium Lead Breeding Blanket (WCLL BB) is a key candidate for the driver blanket of the European DEMO reactor, progressing toward its Conceptual phase by the end of 2027. To assess different water and lithium-lead technologies for the WCLL BB and Balance of Plant (BoP) systems, the Water-thermal-HYDRAulic (W-HYDRA) experimental platform is under development at the ENEA Brasimone Research Centre. Among the facilities constituting the new W-HYDRA multipurpose infrastructure, STEAM is going to experimentally investigate the DEMO WCLL BoP thermal-hydraulics, focusing on the Steam Generator (SG) of the Primary Heat Transfer Systems (PHTS), to qualify its performances and suitability under its unconventional operation. The paper aims at supporting the thermal-hydraulic characterization of the Steam Generator mock-up during the sudden power variations typical of a pulsed fusion reactor. The analyzed selected scenario is the operational transient dwell-pulse-dwell, which determines high thermal cycling and correspondent high thermo-mechanical stresses on the primary side components. Two control logics with their relative drawbacks have been analyzed with a RELAP5/Mod3.3 1-D model, the first regulating the primary side average temperature, the second monitoring the minimum one. The comparison of the two systems highlighted that neither approach leads to hazardous conditions for the facility. However, while the average temperature controller is characterized by reduced thermal stresses on the components, the minimum temperature controller is characterized by higher thermal gradients for the primary loop. Both methodologies will be tested in the dedicated experimental campaign, aiming at yielding insights and evaluations concerning control strategies applicable to the DEMO reactor. [ABSTRACT FROM AUTHOR]

• A unique experimental apparatus was built to study rapid phase transition. • • HFE-7100 ON data for at high heating rates, 106 K/s, are measured for the 1st time. • • Results are obtained in the intermediate heating rates regime (105 to 106. • K/s). • • Maximum superheating degree of 14 K was obtained for a heating rate of 2.2・106 K/s. • • For slower heating rates, superheating spans 12 K for water and 4 K for HFE-7100. Effective thermal management of electronics is crucial for maintaining their reliability, longevity, and optimal performance. As electronic devices become increasingly compact and powerful, the need to explore new and innovative methods for thermal management becomes ever more critical. Rapid transitions of power lead to temperature spikes (hotspots) of up to 100 K, and thus can dramatically increase the failure occurrence of chips. Power spikes imply that heterogeneous nucleation occurs due to rapid heating, which can vary between 104 – 106 K/s, and hence the coolant is in its metastable region under various degrees of superheating. Gaining ONB data with respect to the heating rate holds significance for diverse applications including nuclear installations, engines, inkjet printers, and laser-based systems. In the present paper, we have refined the definition to a heterogeneous nucleation event due to a rapid heating process, that occurs when the timescale for the wall heating is shorter than the critical bubble's significant growth time. Data pertaining to the dependence of the onset of nucleate boiling (ONB) on the heating rate is presented for the first time. Experiments are performed with HFE-7100 fluid that is rapidly heated using a uniquely designed micro-heater, 122 × 234 μm2 in size. The newly designed and constructed system facilitates precise measurements of fast heating processes. In this study, we conducted a series of experiments spanning heating rates from 104 to ∼106 K/s. This range of heating rates was identified in our previous studies as an intermediate regime for water. The region of intermediate heating rates was previously proved in our research to be challenging to attain, due to the varying stability of the metastable zone; it is primarily attributed to pre-existing nucleation sites. Consequently, this led to a notable gap in the experimental results for water, within this particular region, in the literature. Notably, in the current study, we were able to achieve a maximum superheating degree of 14 K at a heating rate of 2.2·106 K/s. Preheated liquids reach the same superheating degree with different heating rates, depending on the coexistence and spinodal curves. It was found that water and HFE-7100 differ significantly in their metastable zone, and that the first zone, for slower heating rates, spans approximately 12 K for water, but only 4 K for HFE-7100. [ABSTRACT FROM AUTHOR]

The ever-increasing functional density and complexity of the heat source system, the harsh chip cooling environment, as well as the cost reduction measures that require less sensor involvement are increasingly driving the need to develop new approaches for temperature monitoring and predicting. Most current researches investigate the temperature field reconstruction of the whole system. However, the reconstruction is not necessary or practical in some cases for computing consumption and unprocurable structure. The temperature prediction of the points of interest (PoIs) like the heat-sensitive area in the electronics is essentially important for function maintenance. Thus, a complete solution is proposed based on the graph convolutional networks (GCN) in this paper including the dimensional alignment, graph modeling and corresponding GCN construction. Moreover, various methods have been explored for edge modeling and node embedding obtained by Node2Vec has been integrated for better graph representation. After model training, the real-time temperature prediction of PoIs can be realized according to the corresponding temperature of monitoring points (MoPs) by the GCN. The results of experiments show that this method approach well prediction that the mean absolute error is less than 0.01K under the condition possessing diverse MoPs and PoIs. Moreover, the comparison experiments with the baseline methods further verify the validity of this GCN-based solution. [ABSTRACT FROM AUTHOR]

Efficient cooling of the trans-critical CO 2 vapor compression cycle to improve system performance is a crucial research topic. This paper proposes an innovative approach called distribution compression (DC) to achieve the same effect as subcooling in a trans-critical CO 2 thermodynamic cycle. In the DC system, the trans-critical CO 2 at the gas cooler outlet is no longer further cooled but subjected to a secondary pressure boost and releases heat in ordinary heat sink conditions as in the gas cooler. Thermodynamics calculated the change in performance of the DC system under different working conditions with different secondary boost ratios. The optimal secondary boost ratio related to evaporation and gas cooler outlet temperatures under optimal discharge pressure based on the baseline system was obtained. The results show that compared with the baseline system, the DC system can effectively improve the system performance, and the maximum refrigeration COP increase is between 8.2 % ∼ 10.76 %, and the maximum heating COP increase is between 5.37 % ∼ 6.34 %. The cooling or heating capacity increase can reach up to about 26 %. The ideal secondary boost ratio in a DC system is not highly demanding, and the increased input power for the second input power for the secondary boost will not exceed 20 % relative to the baseline system. Comparing the COP of the DC system over current systems that only use a single subcooling technology still shows advantages. The DC system provides a new idea to improve the performance of the trans-critical CO 2 vapor compression cycle. [ABSTRACT FROM AUTHOR]

Demand-side flexibility is an important tool for enhancing the interaction of renewable energy resources and reducing the need for grid upgrades. To employ this flexibility as a market product, it is necessary to aggregate and coordinate by coordinating responsive loads. In this regard, designing effective load coordination mechanisms that consider the preferences of aggregators, end-users, and network operators is critical for the successful implementation of demand response (DR) programs. This paper proposes an incentive-based method for coordinating a group of controllable devices that is practical, does not require complex, high-order models of the entire system, respects end-users privacy and quality of service (QoS), and can readily incorporate network conditions to ensure grid reliability. The proposed method includes algorithms at both the end-user level for controllable device operation and the aggregator level for managing the grid access requests. These algorithms are fast and with low computational burden which makes them suitable for the designed framework, reduces the implementation cost and increases the chance of scalability. The method is illustrated with a realistic test system consisting of a set of controllable heat pumps used in pool heating systems and uncontrollable loads placed in a distribution feeder and supplied by a distribution substation transformer. Simulation results highlight the effectiveness of the proposed method in satisfying the controllable device, end-users, and grid constraints. Comparing the results with similar existing methods shows that the method is 11% more cost-effective than traditional ON/OFF methods while reducing the number of rejected grid access requests from the devices, significantly. • Proposing a bottom-up methodology for coordinating grid access requests of devices. • Introducing a computationally lightweight incentive-based device controller algorithm. • Designing the method in such a way as to guarantee the quality of service for end-user. • Simulation-based implementation of the method on a set of swimming pool heat systems. • Decrease in electricity costs by 11% compared to conventional methods. [ABSTRACT FROM AUTHOR]

• Localized heating upon the droplet was proposed to suppress the coffee-ring effect. • Deposition morphology of the particles can be adjusted by controlling temperature gradient. • Inward flows were induced by the temperature gradient inside the droplet. • This method can be applicable to uniform deposition of colloidal solution independent of solutes and substrates. Coffee-ring effect is a very common phenomenon in our daily life, especially in the evaporation process of colloidal solutions on solid surfaces. However, in processes such as inkjet printing, this effect can change the uniformity of the deposited film, thus affecting the quality of the printed products. In this paper, a facile and convenient method of localized heating of liquid droplets by using a tiny steel wire is proposed. The results indicated that this method can effectively suppress the generation of coffee-ring effect, and the deposition morphology of the suspended particles can be adjusted by controlling the applied temperature, wire diameter and the distance from the wire to the droplet. And it was found that the heated wire-induced inward flows caused by the temperature gradient of the droplet are the main reason for adjusting the deposition morphology. The coffee-ring effect is mainly controlled by the free convection from the edge to the center caused by the evaporation loss of the solution, so as to adjust the distribution of suspended particles in the evaporating droplet and thus achieve the goal of suppressing the coffee-ring effect. This method has no special requirements for the substrate and droplet solution, and it is expected to be universally applicable to uniform deposition of colloidal solutions. [Display omitted] [ABSTRACT FROM AUTHOR]

An Electron Cyclotron (EC) Heating and Current Drive (HCD) system will be installed in the EU DEMO Tokamak to provide plasma heating and stabilization by coupling up to 130 MW of mm-wave power into specific regions of the plasma. The mm-waves will be generated by gyrotrons and propagated through a quasi-optical multi-beam mirror system (MBMS), and subsequently through corrugated waveguides, to launchers located at dedicated Equatorial Ports (EPs). The present design of the launcher features two mid steering antennas (MSAs) for plasma stabilization each consisting of three-beam layouts and steering mirrors positioned at the upper and lower locations of the EP. The proposed concept for the steering mirrors operates on the pantograph principle, a mechanical assembly of parallel linkages, which translates the movement produced by pneumatic actuators into an exact angular rotation of the mirror around an offset virtual axis. This design uses flexures with specific structural compliance as mechanical joints resulting in the desired movement of the linkage system while avoiding the tribological difficulties associated with mechanisms operating under vacuum. This paper describes the present status of the DEMO EC HCD steering mirror as well as the analyses performed to validate this design. [ABSTRACT FROM AUTHOR]

• The optimization problem of EPS and flexibility-enhanced DHSis formulated. • The DHS is retrofitted with BCT and uses a variable mass flow operation strategy. • A conditional-DRO is employed to hedge against the uncertainty of renewable energy. • Propose adouble-layer distributed algorithm to achieve the distributed solution. In an integrated electricity and heating system (IEHS), building flexibility-enhanced district heating systems (DHSs) that use advanced flexibility-enhanced technologies are effective for promoting renewable energy accommodation. However, it is challenging to comprehensively utilize these flexibility-enhanced technologies in IEHS dispatch. This paper proposes a distributed conditional-distributionally robust coordination method for an electrical power and flexibility-enhanced DHS. The DHS is retrofitted with bypass compensation technology and uses a variable mass flow operation strategy to enhance its flexibility and promote renewable energy accommodation. Moreover, conditional-distributionally robust optimization is used to consider the inherent dependency between the forecasting error of a wind farm and the forecast output information, which goes beyond the state-of-the-art models. Additionally, a novel reformulation method is adopted to transform the problem with random variables and bilinear constraints into a more tractable programming problem, yielding a conservative approximative model of the original model that guarantees feasibility. Finally, to protect the privacy of electrical power system and DHS operators, this paper proposes a double-layer distributed algorithm to solve the problem in a distributed fashion while guaranteeing feasibility. Case studies demonstrate that the proposed model with flexibility-enhanced DHSs significantly promotes renewable energy accommodation and reduces dispatch costs, and the proposed double-layer distributed algorithm effectively solves the dispatch problem in a distributed fashion and guarantees the feasibility of dispatch results. [ABSTRACT FROM AUTHOR]

[Display omitted] • Localized heating systems are a proper solution for providing thermal comfort. • Providing personalized heating by radiation or conduction is more convenient, so the inhaled air is kept cool and pleasant. • Local radiant heating systems directly heat the body without heating the environment, leading to lower energy consumption. • With local radiant heating systems, proper thermal comfort and sensation can be achieved even at low air temperatures. Localized heating systems are a proper solution for providing thermal comfort while lowering energy consumption in cold environments. Local radiant heating systems provide thermal comfort at lower air temperatures than convective systems which heats air, resulting in cool and pleasant inhalation air. This paper reviews experimental studies regarding local radiant heating systems considering thermal sensation and comfort. These systems can heat body directly, often with a big view factor toward the body. They do not necessarily heat the air and environment, leading to lower energy consumption. Other types of heating systems combined with local radiant heating systems are also reviewed in this paper. According to reviewed studies, localized methods improved thermal comfort, and the same thermal sensation could be achieved in lower air temperatures, especially when using local radiant heating systems. To design local radiant heating systems properly, improvement of existing local thermal comfort and sensation modeling based on radiant heat transfer is needed. [ABSTRACT FROM AUTHOR]

• Combining deep reinforcement learning DRL and Computational Fluid Dynamics CFD • Control and optimization of two and three dimension conjugate heat transfer applications • Loss function engineering as a key aspect for a good optimization • Policy-Based Optimization improved the temperature homogeneity during heating Gas furnaces are the most widely used means of heating in industry, and with the growing concern for environmental issues, and a global energy crisis at our doorstep, the optimization of the processes related to them becomes a key challenge. This paper aims at introducing a new way of practicing gas furnace control involving simulations, virtual sensors and deep reinforcement learning (DRL) techniques. In order to do so we designed a set of simulations of conjugate heat transfer systems governed by the coupled Navier–Stokes and heat equations for single-step control. The DRL algorithm used in this paper is the policy-based optimization (PBO) algorithm specialized in single-step (or open-loop) control. We explore its ability to find global maxima in different situations and under various constraints. Therefore, various 2D and 3D cases are tackled, in which the position of the work piece, the flow rate, and other parameters are controlled. The obtained results highlight the potential of the DRL framework combined with computational fluid dynamics (CFD) conjugate heat transfer systems for optimizing searches in large parameter spaces. For the 2D case, PPO achieved an increase of 89 % in temperature homogeneity, and for the 3D case an increase of 7 % in final temperature with the same total input. [ABSTRACT FROM AUTHOR]

This paper proposes a scalable and widely replicable framework for the energy management of district systems. The framework is built on a graph-based energy characterization of the system, whose supply and demand dynamics are numerically represented by hybrid mathematical models involving the available control inputs and measurable outputs. Following the graph topology connecting supply and demand nodes, a suitable optimization problem is formulated to take into consideration the actual availability of the involved control input and measurements, resulting in a computationally tractable mixed-integer linear control problem which can be implemented in a receding-horizon fashion. As an illustrative case, the framework is applied to a real-case district heating system, and the validity of the approach is showed through model-in-the-loop and system-in-the-loop numerical results. • Wide replicability and applicability of District Energy Management is a challenge. • Data-driven hybrid systems offer flexibility to capture complex system dynamics. • Replicable optimization framework based on district topological graph. • Topological graph and hybrid models captures the district energy characterization. • Performances and applicability proved in real and simulated district system. [ABSTRACT FROM AUTHOR]

Highlights • Redefine the heating load patterns with people behavior and temperature related sub-patterns. • GMM clustering algorithm is used for heating load patterns in-depth identification. • A case study with four typical operation patterns is analyzed. • The prediction accuracy improvement with clustering result is proved. Abstract The identification of heating load patterns, also known as load profiles, is of vital importance to effective management and operation of district heating system (DHS). Clustering algorithms have been successfully applied in identifying heating load patterns. In this paper, we propose that the heating load patterns should be analyzed more specifically, and Gaussian Mixture Model (GMM) clustering is selected to extract sub-patterns. The novelty of this paper is that a new GMM clustering is applied to identify temperature related sub-pattern and people behavior related sub-pattern, and the clustering result is further utilized to improve the accuracy of prediction models. An energy station in Tianjin is used as case studies and four typical operation patterns are found with their characteristic of occur time and energy signature, which are defined as working pattern, on-duty pattern, daytime–nighttime pattern and nighttime–daytime pattern. The results reveal that this proposed method can make an in-depth identification of heating load patterns and also proves that the prediction accuracies of regression and artificial intelligence model are significantly improved by utilizing the GMM clustering results. [ABSTRACT FROM AUTHOR]

Highlights • In-situ neutron tomography experiments on heated concrete are used for the first time in this paper to support the results (temperature and 3D moisture distribution) of a fully coupled thermo-hydro-mechanical model. • The influence of the experimental boundary condition on the moisture distribution is explored. • A 3D mesoscale extension of the model taking into account explicitly the concrete components (aggregates, cementitious matrix etc.) is proposed. Abstract The exposure of concrete to fire, which often leads to spalling, is a phenomenon that is not yet fully understood. Given the complexity of the thermo-hydro-mechanical phenomena and their strong interaction, a combined numerical-experimental approach is indispensable for understanding the behaviour of concrete at high temperature with respect to spalling. This paper deals with the numerical modeling of moisture distribution in heated concrete, a parameter often linked with spalling, by making use of original experimental data from in-situ neutron tomography. A homogenized continuum model has been employed for investigating various aspects, such as: speed of the drying front, moisture accumulation behind this front, experimental boundary effects etc. In addition, a fully coupled 3D thermo-hydo-mechanical (THM) model on the mesoscale is presented and used for simulating an experiment with a single aggregate for the purpose of investigating the influence of the aggregate on the drying front. [ABSTRACT FROM AUTHOR]

Abstract The mathematical model of heating substation, which is an important part of district heating system, is presented in this paper. The main components of district heating substation system, from the automatic control perspective, that are observed in this paper are heat exchanger and three-way valve. Presented mathematical model is developed so it could operate in real-time, since the crucial aspect of development, deployment and testing of new control techniques and optimization algorithms is their accurate validation on the real system. However, the accessibility to a real system is often not possible. Corresponding to this, an alternative is the existence of the correct mathematical model of a process, with the ability to operate in real-time. First, the presented mathematical model of district heating substation is decomposed to the simpler models of its main elements, in order to provide the analysis of the various parameters on the model performance through numerical simulation. Second, a real-time model is developed in LabVIEW software package and deployed on the embedded controller with a real-time processor as a three-layer application which enables data acquisition and communication with a programmable controller. [ABSTRACT FROM AUTHOR]

Abstract In this study, a thermal de-icing/anti-icing system for aircraft surfaces was designed using flexible graphene film/paper. It was placed between two Carbon Fiber Reinforced Plastic (CFRP) laminates. The flexible heater paper presents high mechanical and thermal properties and requires up to nine times less power than current known resistance heating pad thermal systems to achieve de-icing. The temperature of the surface was controlled by varying the power input. This allows the monitoring of de-icing time, which can be tuned in less than 10 min. The feasibility of the de-icing performance was demonstrated through a series of experiments and the results indicate that the developed method could be a very promising electrical heating strategy able to maintain lightness, efficiency in the de-icing performance and for reducing the environmental impact of de-icing realized through polluting fluids. Graphical abstract Image 1 [ABSTRACT FROM AUTHOR]

Highlights • Development of an innovative building integrated air based solar thermal collector. • Dynamic modelling and experimental validation of the whole building/device system. • Solar collectors are integrated in the façades of an office building. • Active/passive effects on the building are analysed for several boundary conditions. • Interesting energy and comfort results are achieved. Abstract In this paper the design and the energy performance investigation of a new flat-plate solar thermal air collector prototype is presented. The adoption of cost-effective materials and simple design solutions represent the main novelties of the proposed device when compared to existing commercial collectors. In addition, the prototype is suitably designed to be integrated into the building envelope (façade), which is a key feature for the market uptake of building integrated solar thermal systems. The paper includes the description of the dynamic simulation model, developed for the energy and economic performance analyses of the whole building-prototype system. The simulation model, implemented with a computer code written in MatLab, is able to predict both active (hot air production for building space heating) and passive (winter free heating and summer overheating) effects due to the building integration of the proposed solar collector. By such tool, indoor comfort investigations can also be carried out. The dynamic simulation models of both the building and the collector prototype were successfully validated. In order to show the features of the developed simulation code, a suitable case study was carried out. It refers to an office space, part of a high-rise multi-use building, simulated as located in three different weather zones (Freiburg, Naples and Almeria). The examined solar collector is modelled as vertically integrated into the building façade, and three different orientations (East, South-East and South) were taken into account. Interesting results for the energetic, economic and occupants comfort points of view are obtained. By taking into account an initial cost of the system of about 5 k€, the primary energy savings achieved by the proposed system against the traditional buildings range between 1.9 and 8.0 MWh/y (depending on the selected weather zone and backup system). The shortest payback for all the investigated weather zones is obtained for Naples, which is equal to 6.2 years. [ABSTRACT FROM AUTHOR]

Abstract Studies show that energy efficiency should play a significant role towards achieving cost-efficient 100% renewable energy systems. One way to attain cleaner heating solutions for the future is to utilise waste heat from power plants and industry through district heating. In the European Union, approximately 50% of thermal energy is lost in conversion processes. This research paper investigates the potential for the implementation of district heating in a future energy system originally intended not to include district heating. The paper approaches the problem by utilising TIMES modelling to frame the initial future energy system. However, MARKAL/TIMES is not ideal to investigate the operation of different heating scenarios, due to a lack of hourly modelling. Hence, the study utilises EnergyPLAN to investigate the implementation of district heating as an alternative heating scenario to individual heating. EnergyPLAN allows for simulating the hourly operation of not only electricity systems but also heating systems. The study investigates the implementation of district heating in the CO2-80 scenario created with the Irish TIMES model. As the Irish CO2-80 scenario does not include district heating, this study uses EnergyPLAN to simulate an 80% reduction scenario, with and without district heating, to compare the operation of the two systems. A sensitivity analysis is included to reflect on the uncertainties of the study. The results show that a district heating solution is more fuel-efficient while more investment heavy, however the fuel savings more than compensates for the increased investments. In total, the district heating scenario is close to 300 M € cheaper in annual costs than the individual heating scenario for Ireland, and achieves a fuel efficiency increase of 3.5% in the whole energy system due to an efficiency increase in the heating sector. The article shows both the relevance of using multiple models, and the need to consider district heating in a future Irish energy system. Highlights • EnergyPLAN is capable of simulating energy systems identified in MARKAL/TIMES. • EnergyPLAN and Markal/TIMES combined enables better analysis of heating scenarios. • District heating can compete with individual heating in an Irish energy system. [ABSTRACT FROM AUTHOR]

Abstract In recent years, with the gradual deterioration of atmospheric environment in China, the "coal to electricity" project is being implemented by the government vigorously. Even though "coal to electricity" project has a positive impact on eliminating serious pollution and promoting clean energy, in the rural areas, the power grid enterprises have less interest in implementing this project. Aimed at this background, the present paper explored the economic benefits generated by the implementation of "coal to electricity" project of grid enterprises. The results indicate that the project carried out by grid company has poor economic performance during its life cycle, which could attributable to its large investment, irrational electricity price mechanism and the big seasonal difference between peak and valley power demand. Finally, based on the conclusion, this paper gives some specific suggestions for grid corporation to increase the economic efficiency of "coal to electricity" project, including reforming the existing irrational price mechanism, taking full advantage of distributed renewable energy and so on. Graphical abstract Image 1 Highlights • "Coal to electricity" project implemented by grid company has a poor economic performance. • The deficiency in economic performance mainly caused by large investment and irrational price mechanism. • Measures need to be taken such as reforming the existing irrational price mechanism or use distributed renewable energy. [ABSTRACT FROM AUTHOR]

Abstract This paper presents analyses of complex flows and heat transfer induced by twin oblique turbulent slot-jets of different directions (divergent, convergent or parallel) impinging a heated wall. A comparison of the heat transfer characteristics between perpendicular and three cases of twin oblique jets (parallel, convergent and divergent). The twin slot jets are located on a confining adiabatic wall at a distance of 8 slot jet width. Convective heat is investigated numerically examining the effect of Reynolds number (Re) and jet inclination angle (α). This problem is relevant to a wide range of practical applications including nuclear engineering devices, manufacturing, material processing, electronic cooling, drying paper or textile, tempering of glass, etc. All computations are performed using two dimensional large eddy simulations (LES) approach with Smagorinsky sub-grid scale (SGS) models. For all directions and inclinations of the jets, the location of the stagnation points is changed and hence, the location and magnitude of the maximum Nusselt number on the heated wall vary. When Reynolds number increases, Nusselt number is improved for all types of inclination. The averaged Nusselt number shows that the perpendicular impingement gives better heat transfer than that of the oblique jets. The poor heat transfer is obtained for the parallel oblique jets. For the same angle, divergent jets give smallest heat transfer than the convergent jets. Graphical abstract Twin-jets flow configuration. (a) Perpendicular (b) Divergent (c) Parallel (d) Convergent. Image 1 Highlights • Four types of flow patterns of impinging twin jet are studied by Large Dissipation Simulation. • Nusselt number is enhanced for all types of inclination for increasing Reynolds number. • Averaged Nusselt number of the perpendicular impingement gives better heat transfer than that of the oblique jets. • The poor heat transfer is obtained for the parallel oblique jets. • For the same angle, divergent jets give smallest heat transfer than the convergent jets. [ABSTRACT FROM AUTHOR]