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Highlight • New on/off controller for residential applications validated using minute-level field data. • On/off controller improves the HVAC accuracy around 19% in terms of NMBE. • On/off cycling makes the operation and associated energy use more realistic. Abstract Heating, ventilation, and air-conditioning (HVAC) systems are sized using design conditions, conditions that occur only a small percentage of time each year. As a result, HVAC systems frequently operate at part-load conditions since their capacity is larger than necessary except in the most extreme weather conditions. Most HVAC systems for residential and small commercial buildings in the U.S. use on/off controls, however, most energy modeling software tools do not simulate the on/off nature of this type of HVAC controls. This paper presents the development and validation of an on/off controller for residential applications in EnergyPlus using a custom EMS (energy management system). This controller is validated using minute-level field data collected for a house located in Sacramento, California with simulated occupancy and internal loads. The results obtained from EnergyPlus with and without the use of the developed on/off controller are also compared. The application of the developed on/off controller improves the HVAC energy use results accuracy around 19% in terms of the Normalized Mean Bias Error (NMBE) at the one-minute level compared to the results without the application of the on/off controller. It also makes the nature of operation and associated energy use signal of the HVAC system more realistic in terms of the on/off nature of the residential direct expansion coils. Furthermore, in this paper, the accuracy improvement of the results dominated by the internal loads is investigated by applying the one-minute schedule compared to the usual hourly schedules for the internal thermal loads. [ABSTRACT FROM AUTHOR]

Highlights • A new experimental procedure to test PCM-enhanced components is presented. • A modified Dynamic Heat Flow Meter Apparatus is used to perform the tests. • The thermal conductivity of PCMs is measured in different phases (solid-liquid). • Indications to solve the issues related to building PCM-specimens are provided. Abstract The implementation, in Building Performance Simulations (BPS) tools, of robust models capable of simulating the thermophysical behaviour of a Phase Change Material (PCM) represents a fundamental step for an appropriate thermal evaluation of buildings that adopt PCM-enhanced envelope components. Reliable and robust measuring procedures are essential, at a material and component level, to provide experimental data for the empirical validation of software tools. The traditional laboratory tests that are generally used for the validation of models present some limitations, because PCMs are usually subjected to conditions that may be very different from the real boundary conditions of the building components in which PCMs are applied. Furthermore, in many experimental full-scale mockups, the relatively small quantity of installed PCM and the combination of several thermal phenomena do not allow software tools to be tested in a reliable way. In this paper, an experimental procedure, based on a modified Heat Flow Meter Apparatus, has been developed to test the behaviour of PCM-enhanced components; the procedure, which is based on the measurement of the sinusoidal response, has been set up to provide data for the comparison and testing of numerical models and of BPS tools. Moreover, general indications and guidelines are provided to solve some issues related to building specimens that contain bulk PCM in order to obtain a more accurate measurement of their performance. The experimental results presented in this paper were obtained from two different bulk PCMs (organic and inorganic). It was found that it is important to evaluate different PCM typologies and different thermophysical boundary conditions, including partial and full phase transitions, to test simulation codes that implement PCM modelling functions. In fact, some phenomena, such as hysteresis and subcooling effects are more evident when partial phase transition takes place. The results related to the characterization of the thermal conductivity of a paraffin-based PCM have shown a significant increase (up to 42%) of the equivalent thermal conductivity from a solid to a liquid state, with an upward heat flux, thus highlighting that further investigations and improvements are needed to measure the equivalent thermal conductivity in the different PCM phases. [ABSTRACT FROM AUTHOR]

Highlights • Photovoltaic powered ventilation system for parked electric car. • Solar photovoltaic car roof charging system for parked car's ventilation. • Photovoltaic powered electro-mechanical system for climate control of parked electric car. Abstract This paper explores the use of electric car roof mounted photovoltaic (PV) powered ventilation for cabin heat management/ventilation. A fully-functional Renault Zoe electric car has been used for performance evaluation of parked electric car ventilation directly powered by PV. This work has been part of a research project of testing electric cars in the urban environment and it has been conducted at the Edinburgh Napier University's Transport Research Institute. In this work, parked electric car ventilation has been reported, when roof-mounted PV modules were used to operate DC powered fans for ventilation. It has been found that the DC motor-fan selection for removing the hot air from cabin space is of important (i.e. operating characteristics of motor-fan have been very close to the maximum power points locus of the PV modules at different solar insolation). The electric car cabin temperature models with reference to solar radiation have been presented and it will be useful for knowing the parked car cabin temperature variations and designing the car roof mounted PV powered ventilation system. In this paper, performance evaluation of parked electric car's cabin heat management is presented and analysed. Results from this work will be helpful for designing electric car ventilation system (operating at parking time), when powered by vehicle roof integrated PV modules. [ABSTRACT FROM AUTHOR]

Highlights • The ITER TBM Program plans to test DEMO-relevant tritium breeding blanket systems. • Each TBS is formed by various sub-systems with different functions and technologies. • For each TBS sub-system, description of its functions and its main components. • Identification of the ITER services required for operating each TBS sub-system. • Helium and water coolant systems, tritium extraction systems, Pb-16Li systems, I&C. Abstract Six Test Blanket Systems (TBS) will be installed and operated in ITER in the framework of the ITER Test Blanket Module (TBM) Program. After a short description of each TBS and of the main operating parameters, this paper gives the main features of the various TBSs sub-systems, in particular, the cooling systems (helium, water and/or lithium-lead), the tritium system for extracting the tritium from the breeder, the coolant purification system, the tritium accountancy system, and several instrumentation & control systems. This paper addresses also the main services that are needed to operate a TBS such as the secondary water cooling system, the chilled water system to cool the helium circulators, the liquid and gaseous nitrogen used in the tritium extraction process, the compressed air needed to operate the various valves present on the circuits, and the electrical power supply for all the active electrical components such as pumps, circulators and heaters. Other important aspects are the required interfaces with other ITER plant systems such as those involving air and process gas detritiation, power supply, radiological and environmental monitoring, remote handling, measurements, and services. [ABSTRACT FROM AUTHOR]

Solar-based radiant heating systems represent a sustainable, and relatively low-cost, technology to raise the temperature of the interior thermal mass of our buildings. Through the use of direct absorption solar thermal collectors, the same working fluid which absorbs the solar energy can be used to transfer the energy for storage in the thermal mass of the structure using a network of pipes embedded in concrete floors. This study investigates a promising working fluid which can be used in such systems – one which is based on multi-walled carbon-nanotubes suspended in normal base fluids. A major stumbling block affecting the wide spread use of carbon-nanotube nanofluids is their low dispersion stability at elevated temperatures, which significantly reduces the absorption capabilities of the nanofluids and could lead to clogging of the pumps used to circulate the fluids. In this paper, we report on a scalable UV-ozone (UVO) treatment technique to produce highly stable dispersions for the elevated temperatures experienced by working fluids in radiant heating systems. To probe suitability of UVO treated multi-walled carbon-nanotube (MWCNTs) for solar-assisted radiant heating systems, this paper investigates the effects of exposure time and temperature on stability, optical absorbance properties, the extent of functionalisation, and the photothermal conversion performance of UVO-treated MWCNT nanofluids. No agglomeration or degradation of the MWCNTs was observed at elevated temperatures (up to 150   °C), highlighting the stability of proposed nanofluids. [ABSTRACT FROM AUTHOR]

In this paper, the problem of dispatching the operation of a distribution feeder comprising a set of heterogeneous resources is investigated. The main objective is to track a power trajectory, called the dispatch plan , which is computed the day before the beginning of operation. In this paper, we propose a method to optimally compute the dispatch plan so as to optimize the operation of the feeder while making sure to allocate enough local reserves to absorb deviations of the realizations. Indeed, during real-time operation, due to the stochasticity of part of the resources in the feeder portfolio, tracking errors need to be absorbed in order to track the committed dispatch plan. This is achieved by modulating the power consumption of a utility-scale battery energy storage system and of the heating, ventilation and air conditioning system of a commercial controllable building. To this end, a hierarchical controller is designed to coordinate these two controllable entities while requiring a minimal communication infrastructure. Due to the inherent different response times of these systems, the power injection of the electrical battery is controlled at a sub-minute time-scale so as to absorb high-frequency tracking errors and, therefore, deliver the dispatch service. At a slower time-scale, the controllable building is controlled to maintain the state of charge for the electrical battery at a scheduled level by means of a model predictive controller. The model predictive controller is designed in order to account for both comfort and operational constraints of the controllable building, as well as power limits for the electrical storage. The effectiveness of the proposed control framework is demonstrated by means of both an extensive simulation analysis, as well as a set of 12 full day experimental results on the 20 kV distribution feeder in the campus of the Swiss institute of technology in Lausanne, that is comprised of: 1) A set of uncontrollable resources represented by five office buildings (350 kWp) and a roof-top photovoltaic installation (90 kWp), 2) a set of controllable resources, namely, a grid-connected electrical storage (720 kVA–500 kWh), and a fully-occupied multi-zone office building (45 kWp). [ABSTRACT FROM AUTHOR]

With the wide adoption of building automation system, and the advancement of data, sensing, and machine learning techniques, data-driven fault detection and diagnostics (FDD) for building heating, ventilation, and air conditioning systems has gained increasing attention. In this paper, data-driven FDD is defined as those that are built or trained from data via machine learning or multivariate statistical analysis methods. Following this definition, this paper reviews and summarizes the literature on data-driven FDD from three aspects: process, systems studied (including the systems being investigated, the faults being identified, and the associated data sources), and evaluation metrics. A data-driven FDD process is further divided into the following steps: data collection, data cleansing, data preprocessing, baseline establishment, fault detection, fault diagnostics, and potential fault prognostics. Literature reported data-driven methods used in each step of an FDD process are firstly discussed. Applications of data-driven FDD in various HVAC systems/components and commonly used data source for FDD development are reviewed secondly, followed by a summary of typical metrics for evaluating FDD methods. Finally, this literature review concludes that despite the promising performance reported in the literature, data-driven FDD methods still face many challenges, such as real-building deployment, performance evaluation and benchmarking, scalability and transferability, interpretability, cyber security and data privacy, user experience, etc. Addressing these challenges is critical for a broad real-building adoption of data-driven FDD. • This paper reviews data-driven fault detection and diagnostics studies for HVAC systems. • Papers are collected by Sub-keyword Synonym Subtopics Searching method. • Papers are reviewed regarding FDD process, systems studied, and evaluation metrics. • Ongoing efforts, gaps, and challenges are identified. [ABSTRACT FROM AUTHOR]

This paper presents a laboratory study of Offline-trained Reinforcement Learning (RL) control of a Heating Ventilation and Air-Conditioning (HVAC) system. We conducted the experiments on a radiant floor heating system consisting of two temperature zones located in Denmark. The buildings are subjected to real-world weather. A previous paper describes the algorithm we tested, which we summarize in this paper. First, we present a benchmarking test which we conducted during spring 2021 and winter 2021/2022. This data is used in the Offline RL framework to train and deploy the RL policy, which we then tested during winter 2021/2022 and spring 2022. An analysis of the data shows that the RL policy showed predictive control-like behavior, and reduced the oscillations of the system by a minimum of 40%. Additionally, we show that the RL policy is minimum 14% more cost-effective than the traditional control policy used in the benchmarking test. • Real-world data from laboratory test with underfloor heating. • Offline Multi-Agent Reinforcement Learning can eliminate poor behavior during training while converging. • Long Short Term Memory layers are an effective method for obtaining training models for Reinforcement Learning. • Heating costs are reduced by approximately 15% and comfort is maintained. [ABSTRACT FROM AUTHOR]

In this paper Double Multi Relaxation Time Lattice Boltzmann method (DMRT-LBM) is utilized to investigate the particle motion in a modeled room for the first time. The effect of indoor heating system location has been considered on both particle deposition and convective heat transfer so six different positions have been selected for the heating system. Results are shown for two Rayleigh numbers (104 and 105) and different particle sizes (1 μ m and 10 μ m). To study the particle motion, after the flow reaches steady state, 50 000 particles are randomly injected to the room and the number of deposited particles on the walls has been reported for 100 s. Considering the present results, when the heating system is in the middle of the wall, the maximum heat transfer rate is seen for both Rayleigh numbers. Also, the number of deposited 1 μ m particles on the walls for all locations of the heating system is zero for R a = 104, so the number of suspended particles is the maximum. For both Rayleigh numbers and 10 μ m particles, the number of deposited particles is maximum when the heating system is fixed on the top of the wall. It is also concluded that when the heating system is located on the top of the wall, the number of suspended 1 μ m particles for R a = 105 reaches its maximum value. [ABSTRACT FROM AUTHOR]

Air-to-water heat pumps are one of the most common and energy efficient heating systems for buildings, particularly floor-heating plants. One way to further improve their effectiveness is to control the heat pump exploiting the dependence of its coefficient of performance (COP) on the external temperature and temperature of the return water from the load. In particular, it is possible to exploit the heat pump when its efficiency is higher, so optimizing its performance in a predictive manner, anticipating the impact of external conditions. For the case of an air-to-water heat pump, the optimization problem is nonlinear due to the load dependence of the heat pump COP and variable supply water flow rate. This may pose implementation problems. If we address a standard control hardware, simplified optimal control formulations are more effective. In this paper, we specifically address this issue, and a reduced-order, linear, but adaptive time-varying predictive model of the heat pump COP is designed. Our solution takes into account the variation of the heat pump efficiency based on the external temperature and the load profile, which are changing within the control horizon. The proposed COP model is then used within a linear time-varying model predictive controller formulation which provides a prediction of the heat pump dynamical behavior based on the load dependence of the heat pump COP, while tackling the nonlinearities of the system imposed by the variable water flow rate in the hot water tank and also by the load dependence of the heat pump COP. The proposed approach has been implemented and in detail tested on a reference model based on a real case study from the Denmark Technical University, Risø Campus, SYSLAB. An intensive simulation analysis and complements the testing, showing the accuracy and the potential of the method, also in the perspective of practical implementation. • Optimization of heat pump behavior considering variable COP. • On-line estimation of simplified COP models with EKF. • Experimental validation of the model used. • Feasibility of realtime optimization proved. [ABSTRACT FROM AUTHOR]

Heating in wind-chilled environments is a serious task. The catalytic combustion heater (CCH) provides more efficient and cleaner in combustion compared to conventional heaters with high pollutant emission and low energy utilization. In this paper, the heating ability of CCH on human body in a wind-chilled environment (apparent temperatures between −14.8 °C and 12.4 °C) was investigated by collecting skin temperature and subjective thermal evaluation data from 23 subjects. The impact of cold air on localized heating of body parts by CCH was clarified using decision trees and dimensionless correlation coefficients. A human-computer interaction regulation strategy was proposed to simultaneously satisfy the requirements of effective heating, low energy consumption, and low pollution. Finally, CCH and a commercial heater were compared in terms of heating effectiveness and energy consumption in a real outdoor environment. The results showed that CCH effectively solved the problem of excessive cold extremities, and the temperature difference between thoracoabdominal area and extremities was reduced by 57.5–87.9% to within 2 °C. In a strong convective environment, wind speed was the decisive factor (coefficient of 0.95), inducing 46% radiant heat loss. Inputting personnel subjective perception, dynamic environmental parameters, and pollutant thresholds to adjust the injected gas flow enabled intelligent control. In a real cold scenario, the CCH saved 65.9% of energy compared to a commercial heater when achieving the same heating effect. This study provides a reference for the application of catalytic combustion technology in cold outdoor heating and also provides an important theoretical basis for the construction of heating strategies for CCH. [Display omitted] • A new catalytic combustion heat source was proposed to offset the cold exposure. • Heating characteristics of the CCH were obtained in wind-chilled condition. • The impact of strong convection on CCH radiant heating was quantified. • A comfortable and sustainable optimal control strategy for CCH was proposed. [ABSTRACT FROM AUTHOR]

Design and safety assessments of geological disposals of heat-emitting radioactive waste require accurate evaluation of the thermal conductivity of the host medium. This paper presents a new approach to evaluate the anisotropic thermal conductivity of Boom Clay, a clayey layer that is studied as a potential host medium in Belgium by ONDRAF/NIRAS. The present approach is based on an inverse analysis of two in situ heater tests (the small-scale ATLAS IV Heater test and the large-scale PRACLAY Heater test) carried out in the HADES underground research facility (URF). The inverse analysis is performed by using the absolute error function and tolerant error-based method based on temperatures measured from 60 sensors across the two tests (i.e., from 29 sensors during the 900-day heating and cooling phase in the ATLAS IV Heater test and from 31 sensors during the nearly 7-year heating phase in the PRACLAY Heater test). In addition, thousands of numerical modeling cases are applied for both tests. The objective is to estimate a reasonable range of thermal conductivity variation that is characteristic of the entire host clay. Finally, a thermal conductivity range (λ h , λ v) = (1.55–1.95, 1.10–1.25) W/(m⋅K) is identified for the Boom Clay. [ABSTRACT FROM AUTHOR]

Demand side management is perceived as a tool to support a secure and reliable energy system operation amid growing integration of renewable energy resources. However, the lack of scalable modeling and control procedures hinders the practical implementation. To address this challenge, this paper proposes a novel signal matrix model predictive control algorithm. Compared to existing data-driven methods, this approach explicitly provides stochastic predictions considering both disturbance and measurement errors with few tuning parameters, ensuring reliability by high-probability constraint satisfaction. The performance is extensively compared with three state-of-the-art algorithms in a space heating case study using a high-fidelity simulator. The results are further validated with physical experiments using the same system that the simulator is based on. To assess transferability, the algorithm is further implemented on diverse controlled systems, including a domestic hot water heating system and a stationary electric battery. The simulation results show that, compared to existing data-driven methods, the proposed approach improves constraint satisfaction and energy savings by up to 90 % and 8 %, respectively. The experimental results further confirm that the algorithm is applicable to multiple tasks of demand side management, with reasonable control performance observed in all case studies. • A novel signal matrix model predictive control algorithm. • Extensive comparison of multiple data-driven algorithms on a high-fidelity simulator. • Improvement of constraint satisfaction and energy savings by up to 90% and 8%. • Experimental validation of transferability on various controlled systems. • Data-driven predictive control can be reliable with a stochastic control framework. [ABSTRACT FROM AUTHOR]

Distributed solar heating systems have high energy-saving potential as clean and energy-efficient production units in residential building applications. Solar energy resources are weak in hot summer and cold winter zone in China, which makes it difficult to completely rely on solar energy to heat residential buildings. A critical challenge is the lack of a theoretical basis for how to choose the solar-assisted heating system form. In this paper, seven solar-assisted heating systems are modeled and their performances are evaluated in six cities by using TRNSYS software. In terms of performance indicators, the solar fraction, the season performance factor, and the heat efficiency are used to thoroughly discuss the viability of using solar heating technologies in this zone. Based on the results, the average indoor air temperature was maintained between 16 °C and 20 °C, and the lowest solar fraction obtained was 10.1%. The carbon emission reduction in each city ranged from 60 kg to 400 kg, yielding good environmental benefits. According to the comprehensive comparison of the six evaluation indexes considered, the parallel or dual-source solar-assisted air source heat pump system can be used in a zone with medium solar energy resources. It is more suitable to use a dual-source solar-assisted air-source heat pump system in a zone with poor solar energy resources. The findings of this work can guide and promote the widespread application of distributed solar heating in household residential buildings in the hot summer and cold winter zone in China. [Display omitted] • The application status of solar heating technology is investigated in HSCW zone. • TRNSYS simulation verifies the feasibility of 7 different solar-assisted systems. • Comprehensively evaluate the thermal performance of 7 systems in 6 cities. • Multi-dimensional investigations of which system is suitable in HSCW zone. [ABSTRACT FROM AUTHOR]

• MFEA was prepared for strong adhesion, self-healing property and recyclability. • MFEA/AgNWs films realized stretchable, self-healing and recyclable EMI shielding. • MFEA can adhere to other commercial EMI shielding films with conventional methods. Although the electromagnetic interference (EMI) shielding materials have attracted much attention in recent years, it is still a big challenge to develop EMI materials with stretchable, self-healing and recyclable property, realizing reliable usage and avoiding electronic waste. In this paper, we have developed a multifunctional elastomeric adhesive called MFEA, which comprises polydimethylsiloxane, dimethylacetohydrazide/4,4-methylene bis(phenyl isocyanate), and catechol. MFEA exhibits outstanding mechanical performance(3.75 MPa), strong adhesion(1 MPa), self-healing capabilities(91 %), and recyclability. By leveraging its adhesive properties, we can combine MFEA with silver nanowires. The composite MFEA/AgNWs film not only exhibits outstanding performance, including stretchability, self-healing, adhesion, and recyclability, but can also be used to manufacture EMI shielding films with an shielding strength of up to 53.6 dB. Additionally, the composite film exhibits Joule heating behavior, rapidly heating to over 50 ℃ under a 1.5 V and maintaining stability for an extended duration. Moreover, MFEA can be used to adhere to other commercial EMI shielding films to achieve desired functionalities using conventional methods. This approach provides a universal, convenient, and rapid strategy for preparing flexible electronic materials with various functionalities. [ABSTRACT FROM AUTHOR]

International Energy Agency predicts that the global number of installed heat pumps (HP) will increase from 180 million in 2020 to approximately 600 million by 2030, covering 20% of buildings heating needs. Electric power consumption is one of the main key performance indicators for the heat pump systems from techno-economic perspective. However a common issue prevalent in many existing heat pumps is the lack of electric power measurement. The modern installations might be equipped with electric power measurement sensors but this comes at a higher system cost for the manufacturers and end-users. The primary objective of this work is to propose a virtual measurement for estimating power consumption, thereby eliminating the need for field measurement of power for heat pumps. To achieve the objective, a data-driven approach is proposed. Firstly, the in-situ data is preprocessed through data merging, cleaning, and normalization. Then, input features are pre-selected using Spearman correlation coefficients, and further refined by addressing multicollinearity problem. Following this, Extreme Gradient Boosting (XGBoost) models and polynomial models are developed by considering different features as inputs. All models are finally validated against the in-situ data from multi-units of ground source heat pump (GSHP) and air source heat pump (ASHP) installations. The results showed that the electric power consumption of GSHP can be estimated with high accuracy (99% for R 2 , 10 W for MAE, and 1% for MAPE) through generic data-driven models using only four easy-to-measure input features. Taking three input features as inputs for ASHP generic model, the accuracy can be reached to 83% for R 2 , 125 W for MAE, and 9% for MAPE. The method presented in this paper can be applied to estimate power consumption of millions of heat pumps and consequently add a significant value as well as provide different types of services, such as cost-saving benefits for manufacturers and end-users, flexibility services for aggregators and electricity grids. • Collect and analyze in-situ data from multiple residential GSHP and ASHP units. • Propose a two-step feature selection method to indicate the most essential inputs. • Evaluate the most predominant features by data-driven models with different inputs. • Develop high accuracy generic data-driven models with limited inputs features. [ABSTRACT FROM AUTHOR]

To better make use of the waste heat in distributed data centers, a new design of integrated waste heat recovery system that can meet different needs including heating for users and data center cooling is introduced. The system can switch among different operation modes including waste heat recovery mode, natural cooling mode, composite cooling mode and refrigeration mode based on the ambient temperature. The integrated waste heat recovery system is experimented in the enthalpy-difference laboratory, and the experimental results show well consistency compared with the modeling results. The operation strategies to switch among different modes are determined based on the experimental and modeling results. The paper introduced PUE (Power Usage Effectiveness) and ERE (Energy Reuse effectiveness) to comprehensively evaluate the cooling and energy reutilization effectiveness of the system. According to the evaluation result, the integrated waste heat recovery system has well performed energy effectiveness, environmental and economic effect. The ERE values of using the integrated waste heat recovery system in Chinese typical climate cities including Harbin, Beijing, Xi'an, Shanghai and Guangzhou are 0.87, 1.02, 1.04, 1.17 and 1.29 respectively. Using this system at 96 kW distributed data center instead of CRAC (computer room air conditioning) system can save 152.7 MWh electricity, 56.4 tons of standard coal, and 244.7 tons of CO 2 emission in Beijing annually. The payback periods of this new system in different climate regions in China are all within 3 years. • An integrated data center cooling and waste heat recovery system is proposed. • Operation performance of the system is verified by experiment and modeling. • Energy Reuse Factor in Beijing is 1.02, and payback period is within 3 years. [ABSTRACT FROM AUTHOR]

• A fully visualized experimental facility combined with PIV system was designed to study the reverse flow phenomenon in the EHDPHRS. • Single-phase reverse flow velocity is proportional to heating power and inversely proportional to subcooled-water temperature. • Two-phase reverse flow velocity increases first and then decreases with heating power. • Buoyancy lift induced by density difference and pressure difference induced by direct contact condensation are the driving force for reverse flow. • Flow inertia force caused by forward flow is the restraining force for reverse flow. The equal-height-difference passive heat removal system (EHDPHRS) has a large potential in floating nuclear power plants (FNPPs) due to its ability to fully utilize the marine environment to achieve residual heat removal. However, the horizontal connection between the heat sink and the heat source could easily lead to the subcooled-water reverses flow and thus trigger serious flow instabilities. In the present paper, a fully visualized experimental set was built, combined with a particle image velocity (PIV) system to investigate the subcooled-water reverses flow in the EHDPHRS. First, PIV observations clearly highlighted five flow stages during a complete natural circulation, including the reverse flow occurred in the single-phase and two-phase flow. Then, it was shown that the single-phase reverse velocity is proportional to heating power and inversely proportional to subcooled-water temperature. While, the two-phase reverse velocity increases first and then decreases with the increase in heating power. Moreover, the two-phase reverse flow phenomenon shows obvious periodicity. Finally, the buoyancy force (F b) caused by the density contrast, and the pressure difference (F Δ P) caused by the direct contact condensation (DCC) are the triggering forces for the reverse flow, while the flow inertia force (F i) caused by the forward flow represents the restraining force. [ABSTRACT FROM AUTHOR]

• For heat conduction system, a response spatiotemporal correlation (RSTC) model of temperatures between measurement space and estimation space is proposed. • A RSTC based direct reconstruction (RSTC-DR) method is developed for transient temperature field of heat conduction system. • The proposed method does not rely on specific system heat source and can achieve non-destructive reconstruction of temperature field in real-time. In this paper, according to a spatiotemporal correlation characteristic of the temperature response of a transient heat conduction system, a response spatiotemporal correlation (RSTC) model of the temperatures between measurement space and estimation space of the system is proposed. Furthermore, a RSTC based direct reconstruction (RSTC-DR) method is developed for a transient temperature field reconstruction problem of a heat conduction system with unknown heat sources. In the offline stage, firstly, mapping eigenvectors of a heat conduction system are determined by the transfer equations without specific heat source information. Then, according to the correlation degree between the mapping eigenvectors, a finite number of representative spatial points (RPs) are extracted. Meanwhile, a fuzzy membership relationship between the mapping characteristics of the RPs and that of the temperature field is determined. Namely, effective mapping characteristic coverage of the RPs to the whole temperature field is realized. Moreover, a RSTC model between the measurement spatial points (MPs) and the RPs is obtained by the step response model of the temperature field. In the online stage, based on the RSTC model, the temperature responses of the RPs are estimated by employing the time series vector of the temperature measurements of the MPs. Next, according to the fuzzy membership relationship, the temperature field can be reconstructed in real time by synthesizing the temperature estimations of the RPs. The RSTC-DR method is employed to achieve the non-destructive reconstruction of the transient temperature field of a two-dimensional heat conduction system. The temperature field is reconstructed by the numerical experiment to verify the effectiveness of the proposed method and to discuss its adaptability. Furthermore, the practical effectiveness of the method is demonstrated by applying the existing experimental data. [ABSTRACT FROM AUTHOR]

• A thermoelastic theory for fast and ultrafast heating of materials is proposed. • Sign of temperature gradient rate indicate the precedence scenario in heat equation. • The calculated displacements are in very good agreement with the experiments. • Ablation surface temperature is significantly higher for ultrashort laser pulses. • As the laser pulse duration decreases, sensitivity to relaxation times increases. This paper introduces an improved thermoelastic theory designed specifically to address the challenges posed by fast and ultrafast heating of materials. The proposed theory incorporates a time delay in the temperature gradient and introduces the rate of temperature gradient as an additional term in the heat equation. This term accounts for the phase lag and the precedence of the temperature gradient and heat flux vector. By leveraging the sign of the temperature gradient rate, the theory automatically determines the precedence of either the temperature gradient or the heat flux vector. To verify the effectiveness of the proposed theory, experiments reported in the literature were simulated using several theories, namely the classical, Lord-Schulman (LS), Green-Lindsay (GL), dual-phase-lag (DPL), and the presented theory. The simulations considered the effects of relaxation times and pulse duration on the results. The findings reveal that for pulse durations shorter than 50 ps, the second-order time derivative of the temperature gradient becomes a crucial term in the energy equation for accurately predicting temperature profiles. Additionally, as the pulse duration decreases, the sensitivity to relaxation times increases. Regarding the surface temperature corresponding to the material ablation threshold, it is observed that for an 80 fs laser pulse, the ablation temperature falls between the boiling and critical temperatures, significantly higher than the boiling temperature associated with the ablation by a 270 ps pulse duration. Lastly, the simulation results exhibit a high level of agreement with the experimental data, particularly in terms of displacements, further validating the accuracy of the presented simulations. [ABSTRACT FROM AUTHOR]

This paper aims to evaluate the potential of heat recovery from the integrated heat exchanger within the exhaust stack silencer baffles in a simple cycle gas turbine. Heat transfer channels were incorporated into the upstream (nose) and downstream (tail) sections of the parallel silencer baffles in the exhaust stack. The gas turbine exhaust gas represents the hot side flow across the baffles' sections. The integrated heat exchanger system offered an advantage of extracting waste heat from the exhaust stream, while reducing pressure drop on the flow and improving acoustic attenuation. In this work, a series of parametric studies were carried out across a range of internal and external heat transfer area configurations within the silencers to maximize the heat transfer. Further enhancement opportunities were introduced and discussed based on the conducted parametric studies and practical aspects borne out of common industry practice. The proposed heat recovery system was implemented to power the gas fuel performance heater which is used to enhance the gas turbine cycle performance through utilization of the extracted waste heat while keeping lower exhaust pressure drop in the stack. The obtained results showed that the proposed integrated heat exchanger within the silencers has a potential of generating a 5.48 MW net gain from the gas turbine exhaust stacks which are normally lost to the atmosphere from the simple cycle exhaust stack. The proposed heat recovery system proved significant fuel savings that lead to economic benefits and reduction in CO 2 emissions. [ABSTRACT FROM AUTHOR]

Anormal temperature data caused by various reasons such as sensor faults and operation faults, which has a negative influence on heat metering and operation regulation in district heating system (DHS). However, it is difficult to detect and diagnose anormal temperature among massive unlabeled operation data. Therefore, this paper proposes a novel hierarchical classifying and two-step training strategy to facilitate the anormal temperature detection and diagnosis task. Firstly, self-defined feature change rate of operation data like water temperature, flow rate, and valve opening are constructed as additional training features to capture the characteristics of anormal temperature conditions. Then, a hierarchical classifying method is proposed to detect anormal temperature data. Finally, a two-step training strategy which combines expert knowledge with support vector machine (SVM) to fulfill anormal temperature type diagnosis. The proposed strategy is applied to a typical DHS in cold region of China. A total of 10,920 anormal data are detected. Four anormal temperature conditions are diagnosed including offline sensor, inversely connected sensor, anormal operation of heat source, and shutdown of heat station. The diagnosis accuracy for the 4 kinds of anormal temperature conditions all reached over 98%. • Detecting anormal temperature based on hierarchical classifying strategy. • Self-defined feature change rate added to train the diagnosis model. • A novel two-step training strategy is proposed to train the diagnosis model. • 4 anormal types diagnosed and over 98% diagnosis accuracy achieved. [ABSTRACT FROM AUTHOR]

• A model for calculating the thermal carrying capacity of water bodies was established. • The impact of meteorological parameters on water bodies was analysed. • Water source heat pumps failing to meet building heat demand in winter is analysed. • Solar radiation is the main source of thermal regeneration of water bodies. • Increasing the water depth or area can raise the thermal heat load-carrying capacity. Meteorological parameter changes not only affect the heat load-carrying capacity of the surface water, but also affect the heat load demand of the building, thus changing the heat load matching between the water source heat pump system and the users. In order to study the climatic adaptation of the heat load-carrying capacity, this paper establishes an analytical model of the water body's heat load-carrying capacity and the building's heat load with the solar radiation intensity, the change of the water body and the heat extraction time as variables. Experimental and simulation studies on the heat load-carrying capacity of lake water were carried out under the winter climate conditions in hot summer and cold winter areas. The results show that increasing the depth or area of the lake can improve the heat load-carrying capacity. Solar radiation is an important factor affecting the temperature of surface water body, the stronger the solar radiation the greater the temperature rise of the water body. Changes in outdoor air temperature have a significant impact on water temperature, and a sudden drop in outdoor air temperature will result in a sharp drop in water temperature. When the water body area was 3000 m2 and 50000 m2, the maximum integrated temperature drop of the water body was 15.0℃ and 9.7℃, which was 2.02 and 4.85 times of the temperature drop of heat extraction, respectively. Reduced heat load-carrying capacity of the surface water body or decreased COP of the heat pump is an important reason why the surface water source heat pump heat supply fails to meet the user's heat demand in winter. [ABSTRACT FROM AUTHOR]

• A trilevel risk-averse operation strategy for the integrated electricity and heat system for resilience enhancement is proposed. • Comprehensive multi-energy network operations that integrates network reconfiguration in the PDN and the mass flow rate control in the DHN to enhance system resilience. • A tractable formulation of variable-flow variable-temperature thermal flow model is proposed. • An efficient solution method based on the nested constraint-and-column algorithm is proposed to solve this tri-level mixed integer program. The increasing penetration of renewable energy and the growing frequency and severity of extreme weather events pose a significant challenge to the secure and economic operation of local energy systems. This paper presents a risk-averse scheduling model of the integrated electricity and heat system (IEHS) for resilience enhancement against contingencies. A tri-level formulation is proposed to formulate the worst line outage events and identify the optimal resilience enhancement strategies. The main idea is to find the least-cost scheduling solution that meets the predefined resilience requirements. The model incorporates multi-energy network operations that integrate network reconfiguration in the PDN and mass flow rate control in the DHN. This approach provides more flexibility for load restoration in the face of uncertainties. A nonlinear thermal flow model is adopted to realistically capture thermal dynamics, and a tractable linear approximation is then proposed to balance accuracy and tractability. To solve this tri-level mixed integer program, an efficient solution method based on the nested column-and-constraint-generation algorithm is developed for the proposed IEHS scheduling model. Numerical studies indicate that the proposed model provides optimal solutions that are cost-effective to enhance the resilience of IEHS at minimum expense. [ABSTRACT FROM AUTHOR]

• A fast battery preheating method based on inductive heating is proposed. • Heating performance of inductive heating and conventional methods are compared. • Numerical model for battery inductive heating is established. • Inductive heating provides better temperature uniformity and heating efficiency. • Inductive heating is improved with lower current frequency and battery thickness. The fast preheating of lithium ion batteries (LIBs) is a challenge hindering its wide application in cold climate. This study proposes a new preheating method that employs an inductive heating operation. The performance of inductive heating on LIB is evaluated and compared with conventional heating methods using metal resistance film (MRF) and positive temperature coefficient (PTC) elements. Subsequently, an inductive heating numerical model is established to investigate the influence of critical factors, including current frequency and battery thickness, on the inductive heating performance. Results show that conventional MRF and PTC heating cannot provide safe fast preheating of LIBs owing to significant temperature difference inside battery. In comparison, inductive heating offers a better battery preheating performance with fast temperature increment, uniform temperature distribution and high efficiency. The battery utilizing sandwich inductive heating achieves a temperature increase rate up to 71.4 °C/min, an insignificant temperature deviation less than 6 °C, and a heating efficiency of 79.2% in the experimental test. The higher temperature uniformity of inductive heating is attributed to the fact that heat is generated within the battery electrode layers and that the contact thermal resistance induced by battery case can be eliminated. Moreover, the inductive heating performance is highly related with current frequency and battery thickness. The inductive heating of LIB is more suitable for operations at low frequencies, such as 10 kHz, as the skin effect of inductive heating can be decreased, and the temperature uniformity is increased. The battery thickness less than 4 mm is recommended as the maximum temperature deviation is less than 2 °C. This paper provides a preliminary investigation into the feasibility of LIB inductive preheating technology and offers new insights into the thermal management design of LIB application in cold climates. [ABSTRACT FROM AUTHOR]

It is difficult to alter the thermal performance of a minichannel heat sink with a fixed structure under constant operating conditions. In particular, if the local heat transfer of the substrate cannot be regulated in real time, the dynamic heat dissipation needs of high-power electronic components cannot be met in the electrical servo systems of flight vehicles. In this paper, a new minichannel heat sink structure based on the classical rectangular channel is proposed and a piezoelectric oscillating fin (POF) is introduced to replace the fixed fin. The thermal performance of the heat sink can then be regulated using the swing of the POF, with supercritical carbon dioxide (S–CO 2) as the coolant. Transient numerical simulations are applied to investigate the influence of various POF operating parameters on the heat transfer of the channel, such as the oscillation amplitude and frequency. The results demonstrate that a channel with a POF can allow for dynamic and rapid adjustment of the thermal performance through control of the oscillation frequency and amplitude of the POF, with a constant channel configuration, coolant, and operating conditions. The heat transfer can be enhanced significantly by the swing of the POF, with the local Nusselt number growing up to 8.3 times and the overall one up to 1.14 times. Both the oscillation frequency and amplitude have a positive correlation with the intensity of heat transfer. The POF also contributes to a greater pressure drop and fluctuation in pumping power. A comprehensive evaluation coefficient shows that the POF is effective at improving the overall thermal performance with a low-frequency swing, while high-frequency operation enhances the local heat transfer and decreases the local temperature near the tail end of the POF. Finally, considering the effects of the frequency and amplitude of the POF, as well as the variable thermophysical properties of the supercritical coolant, a heat transfer correlation based on the Dittus–Boelter equation is established to predict the thermal performance of the channel with a POF. This prediction has a maximum error of ±0.56%. • A minichannel introducing piezoelectric oscillating fin (POF) to replace the fixed fin is proposed. • The thermal performance of the minichannel heat sink is regulated using the POF and S–CO 2. • The influence of oscillation frequency and amplitude of the POF on heat transfer is investigated. • A heat transfer correlation for POF channel based on the Dittus–Boelter equation is established. [ABSTRACT FROM AUTHOR]

The present paper reports experimental and numerical investigations into the post-fire cross-sectional behaviour and residual resistances of hot-rolled austenitic stainless steel channel section stub columns under combined compression and minor-axis bending. An experimental programme included heating, soaking and cooling of specimens as well as post-fire initial local geometric imperfection measurements and minor-axis eccentric compression tests on fourteen specimens. The minor-axis eccentric compression test results were used in a parallel numerical modelling programme for validation of finite element models, which were then adopted to perform a series of parametric studies to generate further numerical data. Since there are no existing design rules for stainless steel structures after exposure to elevated temperatures, the relevant codified ambient temperature design interaction curves in combination with post-fire material properties were evaluated for their applicability to eccentrically loaded hot-rolled austenitic stainless steel channel section stub columns after exposure to elevated temperatures. The evaluation results revealed that the design interaction curves given in the European code and American specification led to rather conservative and scattered resistance predictions, which were attributed to the conservative end points and inefficient shapes. To address the shortcomings, new design interaction curves anchored to more accurate end points and having more efficient shapes were developed and resulted in more accurate and consistent resistance predictions than their codified counterparts. The reliability of the new design interaction curves was also confirmed by means of statistical analyses. • The post-fire behaviour of stainless steel channel sections under minor-axis combined loading was studied. • Fourteen post-fire minor-axis eccentric compression tests were performed. • FE models were firstly developed to simulate the test results and then used to conduct parametric studies. • The applicability of the relevant ambient temperature design interaction curves was evaluated. • New improved design interaction curves were proposed. [ABSTRACT FROM AUTHOR]

In an effort to minimise electricity consumption and greenhouse gases emissions, the heating, ventilation and air-conditioning sector has focused its attention on developing alternative solutions to electrically-driven vapour-compression cooling. Liquid desiccant air-conditioning systems represent an energy-efficient and more environmentally friendly alternative technology for dehumidification and cooling, particularly in those cases with high latent loads to maintain indoor air quality and comfort conditions. This technology is considered particularly efficient in hot and humid climates. As a matter of fact, the choice of the desiccant solution influences the overall performance of the system. The current paper reviews the working principle of liquid desiccant systems, focusing on the thermodynamic properties of the desiccant solutions and describes an evaluation of the reference thermodynamic properties of different desiccant solutions to identify which thermodynamic, physical, transport property influences the liquid desiccant process and to what extent. The comparison of these thermodynamic properties for the commonly used desiccants is conducted to estimate which fluid could perform most favourably in the system. The economic factors and the effect of different applications and climatic conditions on the system performance are also described. The paper is intended to be the first step in the evaluation of alternative desiccant fluids able to overcome the problems related to the use of the common desiccant solutions, such as crystallization and corrosion to metals. Ionic liquids seem a promising alternative working fluid in liquid desiccant air-conditioning systems and their characteristics and cost are discussed. [ABSTRACT FROM AUTHOR]

Many applications in additive manufacturing involve the dynamic deposition of powders and the in-flight heating of such material by a laser. In order to characterize such systems, the Discrete Element Method (DEM) is employed. Specifically, this paper focuses on the initial stages of this process by developing a modular discrete-element type multiphysics simulation method for the particle dynamics and heating by a laser and detailed thermal behavior. The objective is to provide researchers with a framework to construct computational tools for this growing industry. In order to achieve this, from a simulation standpoint, the overall particle-mixture system is constructed by coupling submodels for each primary physical process (dynamics and heating) together. An iterative staggering scheme is developed whereby, within every time step, each individual particle is solved “freezing” the state of the remaining multiparticle system. The state of the particle is then updated and the algorithm moves to the next particle in the system and the process is repeated. The overall process sweeps through the entire system repeatedly until convergence is achieved in an appropriate norm. As the system evolves, an error estimate dictates the time-step size that is needed to induce convergence to below an appropriate error level. Thus, the process can be considered as an implicit time-stepping scheme, which is combined with an (internal) iterative staggering process. In order to control rates of convergence within a time-step, the algorithm adjusts the time-step size. If the iterative process does not converge within a desired number of iterations, below an error tolerance, the time-step is reduced. The degree of time-step reduction is determined by utilizing an estimate of the spectral radius of the coupled system. Since the construction of model and solution process is modular, one can easily replace physical submodels with other choices, making it easy to numerically experiment with a variety of models. Qualitative and quantitative analyses are provided, as well as three-dimensional numerical examples. This paper addresses the first of two overall “macrostages” of a complex manufacturing process with DEM. The first stage, addressed in this paper, concentrates on dry-powder materials, which are of a discrete particulate character, using DEM to characterize the deposition and in-flight particle heating. Other papers of the author (Zohdi, 2010, 2013, 2014, 2015 [81,82], 2008) have addressed stage two, namely phase transformations, curing (cooling) and stress analysis, using more appropriate continuum and hybrid DEM-continuum approaches. [ABSTRACT FROM AUTHOR]

Heating, ventilation, and air-conditioning (HVAC) are among the major energy demand in the buildings sector globally. Improving the energy efficiency of such systems is a critical objective for mitigating greenhouse gas emissions and transitioning towards renewable sources of energy supply. The interest of this paper is to explore means to increase the efficiency of HVAC systems in accommodating occupants’ behavior in real time. For instance, rooms in office buildings are not always occupied by occupants during scheduled HVAC service periods. This offers an opportunity to reduce unnecessary energy demands of HVAC systems associated with occupants’ behavior. An in-depth analysis of occupants’ stochastic behavior within an office building is conducted in this paper. A demand-driven control strategy is proposed that automatically responds to occupants’ energy-related behavior for reducing energy consumption and maintains room temperature for occupants with similar performances as a static cooling. In this control strategy, two types of machine learning methods – unsupervised and supervised learning – are applied to learn occupants’ behavior in two learning processes. The occupancy-related information learned by the algorithms is used by a set of specified rules to infer real-time room setpoints for controlling the office's space cooling system. This learning-based approach intends to reduce the need for human intervention in the cooling system’s control. The proposed strategy was applied to control the cooling system of the office building under real-world conditions. Eleven case study office spaces were selected, representing three typical office uses: single person offices, multi-person offices, and meeting rooms. The experimental results report between 7% and 52% energy savings as compared to the conventionally-scheduled cooling systems. [ABSTRACT FROM AUTHOR]

In the past decades, increasing attention has been directed to understanding the structural response to various scenario fires, which is stimulated by the trend of considering localised burning in large open plan compartments. Beam-column elements as widely used in modelling steel frames have been extended to account for the thermal impact in OpenSees, the development of which is undertaken to formulate the displacement and force-based beam elements. After including the non-uniform thermal expansion along the element length caused by localised heating, the force-based beam-column element has shown greater efficiency compared to the displacement-based element. A detailed discussion regarding the computational performance of both beam-column elements has been presented in this paper, which concludes that force-based beam-column elements can better represent the localised plasticity of fibres caused by non-uniform heating. A generic simply supported steel beam can be modelled even with two force-based elements to reproduce accurate mid-span deflection under localised heating. A steel beam subjected to a localised fire is presented as a case study in this paper, experiencing run-away collapse after 15 min of exposure when the load ratio reaches 50%. Using a 12 element force-based beam-column model and shows equivalent accuracy against 48 element displacement-based beam-column model. [ABSTRACT FROM AUTHOR]

In times of great transition of the European construction sector to energy efficient and nearly zero energy buildings (nZEB), a market observation containing qualitative and quantitative indications should help to fill out some of the current gaps concerning the EU 2020 carbon targets. Next to the economic challenges, there are equally important factors that hinder renovating the existing residential building stock and adding newly constructed high performance buildings. Under these circumstances this paper summarises the findings of a cross-comparative study of the societal and technical barriers of nZEB implementation in 7 Southern European countries. The study analyses the present situation and provides an overview on future prospects for nZEB in Southern Europe. The result presents an overview of challenges and provides recommendations based on available empirical evidence to further lower those barriers in the European construction sector. The paper finds that the most Southern European countries are poorly prepared for nZEB implementation and especially to the challenge/opportunity of retrofitting existing buildings. Creating a common approach to further develop nZEB targets, concepts and definitions in synergy with the climatic, societal and technical state of progress in Southern Europe is essential. The paper provides recommendations for actions to shift the identified gaps into opportunities for future development of climate adaptive high performance buildings. [ABSTRACT FROM AUTHOR]

[Display omitted] • Mobilized thermal energy storage system can be powered by heat from geothermal sources. • One of the main factors justifying the application of M-TES is the use of phase change materials (PCM) with the greatest possible heat accumulation capacity. This presents a large area for new research. • M-TES should be designed in detail and adapted to the available heat source and the needs of the recipient. It is possible to create a set of basic assumptions for M-TES (like: requirements for PCM and TES-tank construction, transport requirements, legal, economic and environmental aspects) which can be more widely used and applied for future systems. The main focus of this paper is the mobilized thermal energy storage system designed to be applied in the heating system of a single-family residential building. It has been investigated if it is possible to use geothermal heat as a heat source for M-TES based on PCMs. To analyze this possibility, tests were carried out under real conditions. The M-TES with 700 kg of Rubitherm RT70HC PCM filled into the tank equipped with internal heat exchanger was designed and experimentally tested in Szaflary and Zakopane, Poland. Conceptual and research work were carried out in cooperation with innogy Polska S.A., PEC Geotermia Podhalańska S.A. and the startup company Enetech sp. z o. o. The field tests were preceded by the series of laboratory experiments. On their basis and on the basis of literature research, a hypothesis was put forward that: it is possible to supply single-family buildings with the M-TES based on PCM, powered by geothermal sources. This has been confirmed in practice by observing the process of loading the storage in the heat source, its transport and heat collection at the user's location. The process was observed through the acquisition of the temperature data inside the tank. The appropriate distribution of sensors allowed the analysis of temperatures at the entrance, exit and located both centrally and at the walls of the tank. Results show that there can be indicated some important aspects that have a significant influence on the operation and justification of the application of the M-TES. Among them: proper selection of PCM, proper design of the heat exchanger, supply temperature and constancy of the heat source operating conditions, distance between charging and discharging points. An additional goal of this article is to present guidelines for the design of such systems, which were formulated on the basis of measurements and observations. The paper was designed to highlight the weakest points of the tests and areas for improvement. [ABSTRACT FROM AUTHOR]

• Load shifting experiments were performed in a single-family inhabited house. • Room radiators were controlled with variable set-point schedules. • Heat consumption was successfully shifted from the controlled rooms. • The total load shifting on a building level was limited. • A list of challenges for developing E-MPC in real buildings was identified. Recent simulation-based studies have indicated that load shifting using Economic Model Predictive Control (E-MPC) of radiators for residential space heating can be utilized for demand response purposes in energy systems. However, there is a lack of studies on whether this load shift potential can be realized in real, inhabited buildings. This paper reports on a field experiment aiming at realizing load shifting of space heating in a single-family house with a hydronic radiator system connected to the local district heating. Radiators in a limited number of 'active' rooms were controlled using set-point schedules mimicking the typical behavior of E-MPC. The results indicate that it was possible to load shift heating consumption in the 'active' rooms but that the load shift for the building as a whole was limited due to the hydronics of the radiator system. The paper also reports on the several practical issues encountered during the experiments – issues that in different ways are barriers to the practical realization of demand response from E-MPC of hydronic space heating systems. [ABSTRACT FROM AUTHOR]

This paper presents a two-stage framework for monitoring the decline of pipeline insulation and diagnosing leakage fault. The task of the first stage is to estimate the parameters of the pipeline network, so as to monitor the abnormal heat conduction data of pipelines, and use the estimation results to update the parameters of the pipeline model. The task of the second stage is to obtain the location and the water loss of after a leakage fault. In the framework, the tasks of the two stages are formulated into the problem of minimizing the divergence between the real system and the simulation system. And the problem is solved by the group search optimizer (GSO) algorithm with improved boundary search strategy in this paper. In the simulation tests, the framework is verified to be able to diagnose the faults. And in comparison with other heuristic algorithms, the GSO algorithm has the best ability to accurately diagnose the fault. Finally, the framework is applied in the cooling system, which shows that the framework has good migration capability. [ABSTRACT FROM AUTHOR]

• The algorithm of recursive modified partial least square (RMPLS) is proposed and employed to enhance the precision of prediction with low computation complexity. • The problem of signal prediction is equivalently transformed into parameter prediction with the help of locally weighted projection regression (LWPR), which makes the nonlinear quadratic problem of predictive controller for nonlinear process solvable. • The proposed predictive control strategy is updated by learning from the online measurable data. It is therefore suitable for the tracking control of chemical industry with complex and changeable work conditions. In this paper, a data-driven predictive control strategy for nonlinear system is proposed and testified on a continuous stirred tank heater (CSTH) benchmark. A recursive modified partial least square (RMPLS) algorithm is employed to regress the local linear model. The algorithm of locally weighted projection regression (LWPR) is then leveraged to build the predictive model, based on which a novel data-driven predictive control strategy is put forward. The proposed predictive controller has the ability to deal with changing working conditions, benefiting from the incremental learning ability of RMPLS and LWPR. The performance of the proposed control strategy is demonstrated with the CSTH while the superiority is illustrated by comparison with an existing model-free adaptive control approach. [ABSTRACT FROM AUTHOR]

• Propose a novel CCHP system integrated with solar thermal biomass gasification. • Model solar thermal biomass gasification using thermochemical equilibrium method. • Present energy and exergy analysis at the design and off-design work conditions. • Analyze the impacts of electric load ratio and solar irradiance on hybrid system. • Discuss the benefits of biomass gasification assisted by solar energy. The objectives of this paper are to propose a novel combined cooling heating and power (CCHP) system based on solar thermal biomass gasification, and to present thermodynamic analyses to effectively improve the utilization of distributed renewable energy sources. By adopting the Engineering Equation Solver software, the thermodynamic models of components were constructed, and the simulation procedures, mainly including the heat transfer of the solar cavity receiver and the biomass gasification, were presented. Based on a 100 kW electricity capacity, the design parameters of the CCHP system were obtained to simulate and discuss the thermodynamic performances and the energy and exergy flow diagrams in the cooling and heating operation modes. The influences of the key variable parameters, including the electric load ratio and the solar direct normal irradiance in the off-design work conditions on the thermodynamic performances, were analyzed and discussed. The simulation results indicate that the CCHP system achieves average energy and exergy efficiencies of 56% and 28%, respectively, and the energy ratio of solar to biomass is approximately 0.19 in the full load operating mode. Compared to the conventional biomass gasification CCHP system without solar energy, the increasing ratio of heating value of product gas based on the solar thermal biomass gasification reaches 55.09%, and the biomass saving ratios are approximately 9.22% and 2.02% in the cooling and heating modes respectively, which indicate that the proposed hybrid system is an effective and feasible method to improve the utilization efficiency of biomass energy. [ABSTRACT FROM AUTHOR]

[Display omitted] • A novel design of 1D serpentine stretchable conductor with a sheath-core structure. • A novel strategy to achieve thickness-controllable wrapping of the elastic sheath. • This serpentine stretchable conductor has distinctive strain-insensitive behavior. • Many advantages to adapt to various harsh circumstances. Stretchable conductors (SCs) have shown promising potential in the field of stretchable electronic devices for their lightweight, high flexibility, stable performance, and easy integration. However, the conductivity of most reported stretchable conductive composites is sensitive to deformation, and it is still unsatisfactory due to their poor recoverability and low reliability under large strain. In this paper, we have fabricated a serpentine stretchable conductor (SSC) with high conductivity, stretchability, and ultra-stability by spontaneously wrapping elastic waterborne polyurethane (WPU) sheath on the surface of the multi-walled carbon nanotube (MWCNT)/WPU nanocomposite conductive yarn, which was prepared by a simple wet-spinning method. The WPU elastic sheath endows SSC with long-term tensile durability and recoverability. Remarkably, benefiting from the sharing effect of the serpentine structure on the tensile strain energy, SSC shows distinctive strain-insensitive behavior (ΔR/R 0 less than 1.6%) up to 100% strain and ultra-high quality factor (Q = 105) at 80% strain. Furthermore, SSC also has temperature resistance, waterproof ability, and self-healing capability, making it capable of being used in harsh circumstances. The combination of high conductivity, stretchability, and super reliability renders many potential applications for SSC, such as stretchable interconnects and wearable heaters. Such serpentine stretchable device with distinctive strain-insensitive behavior provides a novel design idea for stretchy electronics. [ABSTRACT FROM AUTHOR]

A 5th generation district heating (5GDH) system consists of a low-temperature network used as a heat source for de-centralized heat pumps to serve heating demand. Until now, there is a lack of studies looking into the economic aspect of implementing the 5GDH concept. The performance characteristics, system dynamics, and economic feasibility of the 5GDH system are insufficiently investigated in cold climates. This paper aims to bridge the research gap by performing the techno-economic analysis of a 5GDH system using a case study based in Tallinn, Estonia. A detailed thermo-hydraulic simulation model is constructed in TRNSYS and Fluidit Heat. In addition, the uncertainty and sensitivities on the economic performance are analysed using Monte Carlo method implemented in Python. The study further analyses the effectiveness of using solar power technologies in reducing the cost of heating. For designed boundary conditions, the system can deliver heat at levelised cost of heating (LCOH) of 80 €/MWh. Integration of photovoltaic up to a limited capacity results in 1 % reduction when compared to the base case LCOH. The economic benefit of photovoltaic thermal is lower compared to photovoltaic. This study can provide a benchmark for the application of 5GDH systems in heating dominated regions. [ABSTRACT FROM AUTHOR]

Experimental Advanced Superconducting Tokamak (EAST) is one of the important steady-state divertor Tokamak physical experiment platforms in the world. The main functions of the high-temperature and high-pressure Divertor Primary Heat Transfer System (DIV PHTS) are to provide high-pressure cooling water for the divertor to remove the heat load deposited on the divertor under the plasma operation mode and to provide high-temperature nitrogen gas for the divertor system to achieve vacuum condition during the baking mode. The stability and reliable operation of the DIV PHTS play an important role in the EAST tokamak plasma physics experiment. The high-temperature and high-voltage electrical insulation break are one of the important components of the system. The main function of the Electrical Insulation Break (EIB) is to break the closed circuit of the heat transfer system to avoid eddy current during plasma discharge affecting the magnetic field distribution characteristics of the tokamak. On the other way, it also needs to meet the requirement, there is no leak of the cooling water and nitrogen gas during cooling and baking operation mode. This paper proposes the design of an electrical insulating break (EIB) to meet the design requirements of EAST tokamak at first. Then the electric field analysis is carried out by using a finite element model to evaluate its electrical insulation characteristics. And the sealing structural characteristics are verified by applying the finite element method under two design modes. Finally, the sealing test result under the high-temperature baking and high-pressure cooling modes are presented to validate the design. [ABSTRACT FROM AUTHOR]

Numerous cost-optimal studies have been undertaken by EU member states to define minimum energy performance requirements for buildings within that member state in accordance with the Energy Performance of Buildings Directive. As few of these studies have examined the effect of heating and ventilation system parameters on life cycle cost (LCC) and energy use in detail, this paper analysed 84 HVAC solution-sets, including parameters for the heating supply system, heating distribution system and ventilation system, for a case study in Norway. The choice of heating supply system was the dominant parameter, with ground source heat pump solutions offering the lowest purchased energy use and LCC. Electric water heating and district heating systems had low capital costs which make these options more attractive to property developers looking for a good return on investment. Using an exhaust ventilation system with an exhaust air heat pump lowered LCC and capital costs for ground source heat pump and district heating systems but does not meet current Norwegian energy regulations. Despite using more energy, a constant setpoint schedule resulted in a lower LCC than a variable setpoint system due to the variation in hourly energy pricing and the dominant role of monthly pricing based on peak load. The choice of yearly heating strategy and heat emitter had a relatively small impact on energy use, capital cost and LCC. With all the parameters combined, there was variation within each heating system of up to 21 kWh/(m2∙year) in energy use, 78 Euro/m2 in capital cost and 236 Euro/m2 in LCC. Therefore, it is important that such system parameters are considered in cost-optimal assessments to give a fair comparison of HVAC systems. [ABSTRACT FROM AUTHOR]

• Combined heat and power dispatch (CHPD) exploits the potential flexibility in the district heating system (DHS) and provides an economic-effective solution for wind accommodation. However, DHS operators bear extra operation cost, which have insufficient incentive to participate in CHPD in field practice. • A novel benefit allocation model based on the A-S method is proposed, which solves incentive issue among different agents. • An improve A-S method is proposed to enhance computation efficiency, which develops new solution scheme with the Gauss-Legendre quadrature formula. • Mutual trust is momentous in the process of benefit allocation. Once dishonest energy agents perform malicious behavior, the interests of honest energy agents are likely to be damaged, which triggers trust crisis among multiple energy agents. • A blockchain framework with the PoSo consensus is introduced to prevent potential malicious behavior during allocating benefit, which ensures mutual trust among multiple agents. Combined heat and power dispatch (CHPD) has attracted wide attention recently, which exploits the potential flexibility in the district heating system (DHS) and provides an economic-effective solution for better wind accommodation. However, DHS operators bear extra operation cost in CHPD, which is proved theoretically in this paper, so that they have insufficient incentive to coordinate with electrical power system. To cope with this issue, a cost allocation strategy based on the Aumann-Shapley value method is proposed, which can rationally allocate the benefit among multiple agents. And a new solution scheme with the Gauss-Legendre quadrature formula is developed to enhance computation efficiency. Also, considering the potential malicious behavior of dishonest agents in the process of allocation, the blockchain framework with Proof of Solution consensus mechanism is introduced to ensure mutual trust among multiple agents. Numerical simulations based on different cases demonstrate the effectiveness of the proposed method of benefit allocation among multiple agents. In addition, the validity of the proposed blockchain framework in preventing malicious behavior when CHPD is verified. [ABSTRACT FROM AUTHOR]

• A 5th-generation district heating and cooling system in business district is studied. • Design and operation strategies are based on load analysis and load forecasting. • Load predictions are based on machine learning algorithms and historical loads. • Larger flow rate in water loop than that on source-side makes system more efficient. • Source-network-load-storage collaboration in a district energy system is explored. The fifth-generation heating and cooling system (5GDHC) is a bidirectional low temperature network, which is a good solution for decarbonization and energy-saving in building cooling and heating. Because of its complex configurations, 5GDHC requires specific advanced control strategies for different scenarios. This paper aims to investigate 5GDHC with multiple sources in the business district in hot-summer and cold-winter zone through modelica simulation. The analysis and forecasting of district loads were used to study the design and operation strategies of 5GDHC. A suitable heat pump performance curve was presented for 5GDHC after comparing several heat pumps. And the larger the total flow in the network, the more beneficial it is for users. In this study, 5GDHC for the business district performed best when it adopted the strategy of continuous operation of the ground heat exchanger, nighttime operation of the surface-water coil, and supplemental cooling of the cooling tower upon it is needed, resulting in a 16.6% reduction in CO 2 emissions compared to the strategy that all sources operated continuously. Besides, carbon emission analysis showed the importance of balancing operational cost with carbon emission. This study will help optimize the design and operation of 5GDHC in business district scenarios. [ABSTRACT FROM AUTHOR]

The thermal process of heating buildings is characterized by the multivariable, nonlinear, and large time lag. Accurately predicting building heat loads is crucial for regulating building heating systems. However, the current black-box method of heat load prediction has challenges such as extensive data usage and weak integration with the building's heat transfer process. To address these challenges, a physics-guided long short-term memory (LSTM) model for dynamic heat load prediction in the next seven days based on data-driven and mechanism analysis was proposed. The data for the model were collected from in-situ measurement and numerical simulation. Specifically, the thermal mechanism was introduced to the training loss function of LSTM and the selection of input variables. The influence of the adaptive data time step on prediction accuracy was investigated. The main conclusions obtained from the current data in this paper are drawn as follows. 1) Refining solar radiation intensity calculation for each orientation reduced mean absolute percentage error (MAPE) of heat load prediction results by 0.02%–1.8% compared to horizontal solar radiation intensity. 2) Improving the training loss function decreased MAPE of heat load prediction results by 0.04%–0.43% compared with the original loss function. 3) Adaptive data time step lowered the MAPE of heat load prediction results by 0.08%–1.8% compared with fixed time step. 4) Mean absolute errors corresponding to those three aspects decreased by 25 kJ–558 kJ, 6 kJ–157 kJ, and 41 kJ–1881 kJ. In the future, wider promotion and application of the prediction model will lead to better performance and be more beneficial to energy saving and carbon reduction of the heating system. [ABSTRACT FROM AUTHOR]

• A comprehensive model is developed to simulate reheating furnaces. • It explicitly considers the dislocated skids and skid buttons. • The model improves temperature predictions by up to 20 K than a simplified one. • The great effect of skid buttons on slab temperature distributions is revealed. The slab heating process inside a walking-beam reheating furnace is critical for slab quality. This paper presents a comprehensive CFD model simulating the fuel combustion, flow field, temperature distribution, and heating process of walking slabs in an industrial-scale furnace. It explicitly considers the effects of dislocated skids and skid buttons. After the model validation through industrial measurements, the model is used to analyze the influences of skid buttons and dislocated skids on the flow and temperature field and the slab heating process. The results show that the dislocated skids and skid buttons significantly affect the flow field and furnace temperature distribution. The simplifications on the structures of skid buttons and dislocated skids cause the neglect of shielding radiation of skids in the modeling. Overcoming this problem by the present model reduces the difference between the measured and predicted slab temperature by more than 20 K. Overall, the skid buttons reduce the sheltered area for slab heating by 86%, and the dislocated skids change the sheltered region of the slabs. These together favor a more uniform temperature of slabs. The results suggest that the CFD model can offer convenience to understanding, designing, controlling, and optimizing the slab heating process in a walking-beam reheating furnace. [ABSTRACT FROM AUTHOR]

The paper describes commissioning of the inductive heater based on numerical simulation of inductive heating in the hypervapotron sample and test channel. The HEFEL loop is being developed to research a high heat flux cooling channels applicable in fusion devices. The Box Scraper hypervapotron channel geometry represents a primary focus of research. Conditions in the first wall of tokamak are simulated by induction heating of the tested hypervapotron channel. The exact heat flux of tested sample is difficult to measure, thus the numerical simulation of induction heating and thermohydraulic model of the cooling channel are an important part of HEFEL loop commissioning. ANSYS Maxwell 3D and ANSYS Fluent coupling is used for optimalization of the induction heating to achieve the highest heat fluxes using selected induction heating source. [ABSTRACT FROM AUTHOR]

The crude oil in the floating roof tank is troubled by the problem of gelling at low temperature which eventuate the storage of crude oil needs to be assisted by coil heating technology. However, the low heating performance of the technology restricts the benefits of crude oil storage due to the limited heat exchange area between coil and crude oil. A finned coil heating technology is proposed to address the above issues. The influence of the fin number and the inclination angle on the heating effect of crude oil is analyzed by FLUENT software. The results indicate that increasing the number of fins has a more significant effect on improving crude oil temperature than adjusting the inclination angle. The increase in the number of fins shows a nonlinear relationship with the increase in crude oil temperature, and there is an optimal combination for coils with different fin numbers and different inclination angles. From the perspective of thermos-economics, the optimal arrangement is the coil with 2 fins inclined at 60°, which can increase the crude oil zone average temperature by 2.83% (1.021 °C), and reduce the temperature inhomogeneity by 6.31%, as well as increase the cost saving by 91.65%, compared with the bare coil inclined at 0° (i.e. existing engineering formation). This paper is of great significance for ensuring the safe storage of crude oil. • Optimize the structure and arrangement of coil for the coil heating technology. • The best crude oil thermal performance is obtained by optimal coil arrangement. • Coil with 2 fins inclined at 60° is recommended to heating crude oil. • Appling coil with 2 fins inclined at 60° can achieve cost saving 91.65%. [ABSTRACT FROM AUTHOR]

Steady-state energy flow calculation (EFC) is the cornerstone of the long-term operation assessment of integrated energy systems (IES). The conventional EFC methods mainly focus on calculation speed and efficiency. However, the robustness is often ignored, which may result in a failure in finding the solutions under ill-conditioned and unsolvable situations. To address this issue, this paper proposes a robust EFC method for integrated electricity-gas-heat system. First, a novel robust EFC method based on Levenberg–Marquardt (L–M) method is proposed for a comprehensive formulation of the energy flow model combining the electricity, natural gas, district heating system and detailed interdependence. Further, a consecutive adaptive damping factor updating approach is proposed. It enables a secure search step to avoid the flutter in iteration process, thus enhancing computational efficiency and convergence for EFC. In addition, the influence of the direction and the size of search step are jointly considered. It is helpful to guarantee solutions for both ill-conditioned and unsolvable situations. Numerical simulation results demonstrate the strong robustness, convergence and universality of the proposed EFC method that works under diversified operation modes, e.g., well-conditioned mode, inappropriate initial values, heavy load mode, and ill-conditioned operation mode. • The integrated electrical, gas and heat system with detailed interdependence energy conversion is formulated. • A novel energy flow calculation method is proposed to enhance the calculation robustness and convergence efficiency. • Numerical simulations are carried out to validate the proposed method. • Satisfactory robustness and universality in multi-categories: well-conditioned, ill-conditioned and unsolvable situations. [ABSTRACT FROM AUTHOR]

• Long term field evaluation of forecast control of heating. • Easy integration with existing installations in buildings. • Widely applicable measure for energy savings around 10%. • Payback time below one heating season. The priority for reaching carbon neutral buildings by 2050 is to first increase energy efficiency in existing buildings by use of easily and widely applicable measures that are verified based on long-term field research. One such solution is a forecast control of heating systems, which can be quickly and easily integrated to existing weather based controls. However, there are still no long-term field evaluation and detailed analyses of the main features of such a system, which would provide a clear picture about the system's energetical and economical features and thus increase their wide application in existing buildings. This paper provides the data from a long term field evaluation of an innovative forecast control of heating systems (forHEAT), which can be easily installed (in less than 2 h) and integrated with existing installations in millions of existing buildings in Europe and throughout the world. The energy consumption for heating was evaluated in seven residential buildings and three public office buildings before and after the installation and use of the forecast control. The resulting energy savings averaged 13.4% in the residential and 10.7% in the public buildings located in continental European climate, with very cold winters. The payback time averaged a 0.6 heating season and in most case studies does not exceed a single heating season. [ABSTRACT FROM AUTHOR]

The Experimental Advanced Superconducting Tokamak (EAST) had been under major upgrading from 2020 to 2021 in China. In this campaign of major upgrading, the new lower tungsten divertor is successfully installed to achieve the targets of long pulse and high β H-mode plasma operation. High temperature and high pressure Divertor primary heat transfer system (DIV PHTS) is also developed to remove the plasma deposition heat load on the Divertor. This paper presents a description of the design and construction of DIV PHTS for EAST Tokamak. Starting from the requirements specified in the Technical Specifications of DIV PHTS, the process to meet the Divertor cooling and baking requirement is designed and validated by the supported thermal-hydraulic analysis. Then, the piping stress analysis under different types of load combinations is performed to verify the structural design requirements. General layout design is also performed based on the component requirement and the allocated space in the EAST Tokamak hall. Finally, the procurement and test of the system main equipment is also given. [ABSTRACT FROM AUTHOR]