Daily Heat Research Articles

Thermal Characteristics and Parametric Analysis of an Improved Solar Wall

Solar air collectors installed on buildings can significantly reduce conventional energy consumption in winter and summer. However, some problems arise in the utilization process, such as overheating, inconvenient operation control and low energy efficiency, etc. This work is a parametric analysis focusing on the automatic control and thermal efficiency improvement of the solar wall. An improved color-changing solar wall integrated with automatic control components, such as a photoelectric fan and temperature-controlled damper, was proposed in this paper. Based on the experimental data, the average daily heat output of the color-changing solar wall is 1.08 MJ per unit floor area on clear days in winter and the average thermal efficiency is 56.8%. Meanwhile, a quantitative analysis was carried out based on monitoring experiments for evaluating the thermal characteristic of automatic control components. Furthermore, in order to improve the thermal performance of the solar wall, parametric analysis was performed by numerical simulation. Results from this paper can provide a theoretical basis for the application of solar air collectors in modern buildings.

Optimal Operation of Low-Capacity Heat Pump Systems for Residential Buildings through Thermal Energy Storage

The paper provides results from a hardware-in-the-loop experimental campaign on the operation of an air-source heat pump (HP) for heating a reference dwelling in Pisa, Italy. The system performances suffer from typical oversizing of heat emission devices and high water-supply temperature, resulting in HP inefficiencies, frequent on-off cycles, and relevant thermal losses on the hydronic loop. An experimentally validated HP model under different supply temperatures and part-load conditions is used to simulate the installation of a thermal storage between heat generator and emitters, in both series and parallel arrangements. Results relative to a typical residential apartment show that the presence of the thermal storage in series configuration ensures smoother heat pump operation and energy performance improvement. The number of daily on-off cycles can be reduced from 40 to 10, also saving one-third of electric energy with the same building loads. Preliminary guidelines are proposed for correctly sizing the tank in relation to the HP capacity and the average daily heating load of the building. A storage volume of about 70 L for each kilowatt of nominal heating capacity is suggested.

Design of cascade analysis for renewable and waste heat recovery in a solar thermal regeneration unit of a liquid desiccant dehumidification system

Liquid desiccant dehumidification (LDD) system is an emerging technology with energy-saving benefit in HVAC applications. It removes moisture from the inlet air stream and handles the latent load without overcooling and reheating. The most energy-intensive process of the LDD system, the desiccant regeneration process, can be driven by renewable solar thermal energy with a temperature lower than 100 °C. However, the integration of solar heat needs to consider the inconsistent availability of solar radiation and regeneration heat demand.In this study, a pinch-based Cascade Analysis (CA) approach is used to optimally size the solar thermal collectors and thermal energy storage (TES) water tanks, which are the main components of the solar thermal system. From the analysis, the overall system efficiency, minimum area of solar thermal collectors and total TES volume are 78.8%, 59.83 m2 and 7.10 m3, respectively, with an average daily regeneration heat demand of 213.48 kWh. The overall system installation and operating cost is approximately 14219.98 USD or 948.00 USD annually over 15 years. This work serves as a preliminary study to provide an overview of the implementation of solar thermal systems for decision-makers who intend to implement solar-based LDD systems in HVAC or drying applications.

A novel approach for high-performance heat index forecasting for the hottest region in Thailand

In Thailand, the hottest area is the northern inland plains located in the Northern Thailand. In summer, from the middle of February to the middle of May, the temperature may rises up to 40◦ or above due to the changing of northeast monsoon to southwest monsoon and the impact of relative humidity. Relative humidity is the major factor that makes people feel hotter than the actual temperature. If only the air temperature was noticed, it is possible to take risk of overheating and heat illness, especially heat stroke that can be deadly. The heat index has used as an effective warning measurement, this calculated by Steadman’s equation and yields the real feel of body. In order to prevent the heat illness, the predictive analytics such as time series forecasting should be applied. The regular series was constructed by several time points in consecutive daily heat index, the seasonal and cycle effects will be analyzed simultaneously. This scenario leads to the complicated time series model and may cause inaccuracy of forecasting. The proposed study modify the data structure as the series of specific date and time for thirty years, i.e., 1-April to 30-April at time 4.00 p.m., this reveals distinguished increasing trend from year by year. Three trend-focused forecasting model be applied, the two benchmarking models are Holt’s linear trend model and time series regression model, being compared with the proposed model called autocorelated-based decomposition. The forecasting results of Uttaradit and Chiang Mai provinces heat index in recent thirty years show that the proposed approach yields more accuracy than the benchmarks. For Uttaradit, the MAPE of the proposed model less than the others from 26.8% to 36.9%, and less than the others from 48.9% to 55.9% in RMSE. For Chiang Mai, the MAPE of the proposed model less than the others from 16.9% to 36.9%, and less than the others from 27.5% to 61.6% in RMSE.

Prediction of Hypoxia in Eutrophic Polymictic Lakes

AbstractQuantifying and predicting the drawdown of dissolved oxygen (DO) in lakes is important to ensuring healthy ecosystems and safe water sources. The characterization of DO depletion using available definitions and models requires extensive monitoring to obtain reliable results. These approaches have been mostly developed for seasonally stratified monomictic and dimictic lakes, limiting their applicability for polymictic systems which stratify and mix repeatedly. We compared the predicted duration of hypoxic events in the three basins of a large eutrophic polymictic lake (Clear Lake, CA, USA) by using three different one‐dimensional (1‐D) analytical approaches; two being original and requiring minimal input variables. Data on meteorology, lake temperature, and DO were all measured at multiple locations for one year and used to develop a novel method, named the Birge‐Winkler method. The daily net surface heat fluxes provided an energy term from which estimates of the onset and length of hypoxic periods could be made with minimal calibration. We used the Lake Number method to evaluate the level of accuracy of the Birge‐Winkler method. Finally, we estimated DO values next to the sediments using a Buoyancy Frequency method. Our results from the two original methods provided simple and effective tools for early warning of onset and duration of hypoxia, with a maximum of ±3–5 days uncertainty in the predictions. These indices can become powerful decision support tools for addressing aquatic ecological challenges triggered by hypoxia, including fish kills, internal nutrient loading, heavy metals release, and harmful algal blooms.

Important aspects for the planning of biogas energy plants: Malatya case study

Conventional energy use causes various environmental impacts of global warming. Also, as a result, renewable energy sources are more beneficial because they generate virtually no emissions. Biogas is historically recognized as a by-product of the anaerobic (oxygen-free) decomposition of agricultural waste. One of the most critical issues for biogas plants in electricity production is the economically and environmentally safe disposal of vast volumes of digestate. In this study, an extensive pathway for the establishment of a large-scale biogas energy plant was presented. Under these lightings, a case plant built in Akçadağ-Malatya was investigated from the techno-economic point of view. The case plant was built to generate heat and power as well as solid and liquid fertilizer. The produced biogas and methane were respectively recorded as 229,49 m3/h and 139,08 m3/h. It was determined that electricity generation in an amount of 5,256,000 kWh per year from the digested feedstock was available with the maximum power capacity of 625 kWh. The annual and daily heat energy outputs were calculated as 6,482,400 kWh and 640 kWh, respectively. The solid and liquid fertilizers were respectively determined as 40,891.03 t/a and 5,152.74 t/a. According to the results, total investment costs per the produced electricity for the biogas energy plant were calculated as 1451.53 €/kWh. The payback period was calculated as 2.22 with a net present value of 944,714.44 €. CO2 emissions have been reduced by 14,105 tons per year thanks to the co-generation system.

A novel approach for solar greenhouse air temperature and heating load prediction based on Laplace transform

Solar greenhouses have provided favorable microclimates for improving and increasing crop production. As a significant factor of microclimates, greenhouse indoor air temperature has received extensive research attention in recent years. Although dynamic models were studied in diverse greenhouses, previous researches failed to consider the existing models' applicability, simplicity, and accurate boundary conditions for solar greenhouses. Hence, a dynamic thermal model based on Laplace transform was proposed for predicting solar greenhouse air temperature and heating load. The heat flux boundary conditions on interior surfaces of the greenhouse north wall and soil were revised by amending the solar fraction expressions with solar azimuth angle considered. The results indicated that the predicted air temperature was in good agreement with experimental values, and three evaluation indices of MAE, RMSE, and NRMSE were -1.250, 1.608, and 15.441%, respectively. Moreover, under three different indoor air conditions, the north wall and soil's heat transfer flux were analyzed, indicating that the north wall is the main loss part of the experimental greenhouse's opaque envelope. Besides, the results also demonstrated that the daily total heating load in Case 1 was larger than that in Case 3, which means different greenhouse air design temperature between day and night is more energy-saving in winter. Furthermore, the physical meaning of the air temperature solution expression and the limitations of this approach were also elaborated. The contribution of this study is to offer accurate temperature forecasting for solar greenhouses' heating, ventilation, and air conditioning applications in the future.

Thermal evolution ameliorates the long‐term plastic effects of warming, temperature fluctuations and heat waves on predator–prey interaction strength

Abstract How thermal evolution may affect trophic interactions and its implications for trophic system stability remains unstudied. To advance insights in how global warming shapes trophic interactions, we need to consider besides increases in mean temperatures, also daily thermal fluctuations (DTF) and heat waves (HW), and how their effects are modulated by thermal evolution. Using a common‐garden approach, we tested how each thermal factor affected predator metabolic rate and functional response parameters, and used these responses to predict long‐term predator–prey interaction strength between larvae of the damselfly Ischnura elegans and the water flea Daphnia magna. Using high‐ and low‐latitude predator populations with the latter being exposed to higher mean temperatures, higher DTF and more frequent HW, we assessed the potential impact of thermal evolution at the high latitude using a space‐for‐time substitution. In line with thermal adaptation, growth rates were faster and handling times shorter in low‐latitude compared to high‐latitude larvae at 24°C while the opposite was true at 20°C. Warming weakened the long‐term interaction strength, except for the high‐latitude trophic system at DTF and HW where plastic responses therefore may not stabilize the high‐latitude system. This extends the emerging insight that temperature variation may make ectotherms more vulnerable to warming. The contributions of metabolic rate, search rate and handling time in shaping thermal effects on interaction strength differed between latitudes. A key finding was that thermal evolution may further weaken the long‐term interaction strength of the high‐latitude trophic system under increases in mean temperatures, even at DTF and potentially also at HW. Our results underscore the importance of daily thermal fluctuations and heat waves in shaping predator–prey interactions, and may suggest an overall stabilizing contribution of predator thermal evolution ameliorating thermal plastic effects on food web stability. A free Plain Language Summary can be found within the Supporting Information of this article.

Continuous insulation strategy of organic waste composting in cold region: Based on cold-adapted consortium

Compost is a self-heating process for organic waste. Microbes are the main executors in composting process. However, due to low temperature in winter and low efficiency of composting, a lot of heat is lost in composting. In this study, taking-out and feed-batch composting method (TFC) can supplement nutrition and improve composting microenvironment. Compared with NC, the amount of carbohydrates, protein and fat decomposed by TFC increase by 56.8%, 237% and 122%, respectively, in the composting start-up period (0–100 h). Structure and function of microbial community have changed due to stimulation of cold-adapted consortium. In addition, this study shows that core bacteria stimulate cooperation among different bacteria in the organic components metabolism networks. Finally, based on the important role of cold-adapted consortium, the sustainable heating strategy of composting system is put forward, which converts organic wastes into released heat for daily heating and hot water preparation, leading role of cold-adapted consortium.

Energy performance of phase change materials integrated into brick masonry walls for cooling load management in residential buildings

Energy demand for space cooling in residential buildings is projected to witness rapid growth, primarily fueled by increasing household incomes in developing countries. To manage this ever-increasing cooling demand, integration of phase change materials (PCMs) in building walls is a potential solution that can reduce the buildings’ cooling energy consumption and peak cooling loads. However, to attain the proposed benefits from PCM integration, it is crucial to appropriately select PCM parameters such as its phase-change temperature and positioning in the wall. Thus, this investigation studied the energy performance of PCM integrated brick masonry walls for cooling load management in residential buildings under periodic steady-state conditions to identify the parameters that govern its performance and develop simple design guidelines.The research found that regardless of the amount of latent heat stored by the PCM, the daily heat gains and cooling loads were equal for wall configurations having equal thermal resistances under identical boundary conditions. Furthermore, even with the application of night ventilation, adding a PCM layer to a well-insulated wall did not reduce its cooling load; thus, PCM integration was ineffective in reducing the cooling load. However, the latent heat stored by the PCM reduced the fluctuations in the hourly heat gains and cooling loads; thus, PCM integration was found suitable for peak load management. For the PCM's proper utilization, its recommended position is on the inner side of the wall with sufficient insulation shielding it from outdoor conditions, and its melting temperature should be close to the indoor set-point temperature.

Preview the Products on Display at Display Week 2021

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Multi‐Year Estimates of Daily Heat Transport by the Atlantic Meridional Overturning Circulation at 34.5°S

AbstractVariations in the mass and heat transported by the meridional overturning circulation (MOC) have important, well‐documented, influences on global and regional climate, weather, ecosystems, and coastal sea levels. However, continuous, high‐frequency, observations of these quantities have been limited to date. Multiple years of full‐depth daily observations from moored instruments in the South Atlantic at 34.5°S are combined with satellite observations to resolve the volume transports in both the upper and abyssal MOC cells, and the associated full‐depth meridional heat transport (MHT), on daily to interannual timescales. A newly developed method for combining satellite sea level observations with historical hydrographic measurements was used to estimate daily full‐depth ocean profiles of temperature in the ocean interior where mooring coverage is sparse. The average MHT during 2013–2017 is 0.5 PW, with a daily standard deviation of 0.8 PW. The MHT variability is most strongly driven by the geostrophic relative velocity contributions (horizontal density‐gradient changes). This variability is highly correlated with the volume transport variability of the MOC upper cell (r = 0.96) and modestly anti‐correlated (r = −0.52) with the abyssal cell variations. An empirical relationship between the MHT and MOC values was developed allowing the reconstruction of a longer MHT time series including the pilot array period (2009–2010). Seasonal variation of the MHT is significant, and results from strong variations of all terms (Ekman, barotropic, and baroclinic). Although the 2013–2017 shows an increasing MHT trend (0.14 PW/year), the longer time period record suggests that the apparent trend may simply be interannual modulation of MHT at 34.5°S.

Hybrid artificial intelligence model for prediction of heating energy use

Currently, in the building sector there is an increase in energy use due to the increased demand for indoor thermal comfort. Proper energy planning based on a real measurement data is a necessity. In this study, we developed and evaluated hybrid artificial intelligence models for the prediction of the daily heating energy use. Building energy use is defined by significant number of influencing factors, while many of them are difficult to adequately quantify. For heating energy use modelling, the complex relationship between the input and output variables is hard to define. The main idea of this paper was to divide the heat demand prediction problem into the linear and the non-linear part (residuals) by using different statistical methods for the prediction. The expectations were that the joint hybrid model, could outperform the individual predictors. Multiple linear regression was selected for the linear modelling, while the non-linear part was predicted using feedforward and radial basis neural networks. The hybrid model prediction consisted of the sum of the outputs of the linear and the non-linear model. The results showed that both hybrid models achieved better results than each of the individual feedforward and radial basis neural networks and multiple linear regression on the same dataset. It was shown that this hybrid approach improved the accuracy of artificial intelligence models.

Influence of Traditional and Solar Reflective Coatings on the Heat Transfer of Building Roofs in Mexico

Building roofs are sources of unwanted heat for buildings situated in zones with a warm climate. Thus, reflective coatings have emerged as an alternative to reject a fraction of the solar energy received by roofs. In this research, the thermal behavior of concrete slab roofs with traditional and solar reflective coatings was simulated using a computational tool. The studied slab configurations belong to two groups, non-insulated and insulated roofs. In the second group, the thermal insulation thickness complies with the value recommended by a national building energy standard. Weather data from four cities in Mexico with a warm climate were used as boundary conditions for the exterior surface of the roofs. The computational tool consisted of a numerical model based on the finite volume method, which was validated with experimental data. A series of comparative simulations was developed, taking a gray roof as the control case. The results demonstrated that white roofs without insulation had an exterior surface temperature between 11 and 16 °C lower than the gray roof without insulation. Thus, the daily heat gain of these white roofs was reduced by a factor ranging between 41 and 54%. On the other hand, white roofs with insulation reduced the exterior surface temperature between 17 and 21 °C compared to the gray roof with insulation. This temperature reduction caused insulated white roofs to have a daily heat gain between 37 and 56% smaller than the control case. Another contribution of this research is the assessment of two retrofitting techniques when they are applied at once. In other words, a comparison between a non-insulated gray roof and an insulated white roof revealed that the latter roof had a daily heat gain up to 6.4-times smaller than the first.

Measuring Study on Energy Saving Performance of the Trombe Wall in School Building

The thermal engineering and energy saving performance of the Trombe wall of a laboratory building in a middle school of Lanzhou region in northwest China were measured and investigated. The results show that during the normal using period in winter 10 years after the building was built, the daily convection heat supply of single group vents is 6.89 kW, the daily average thermal efficiency of the Trombe wall is 18.4 %. In addition, in the process of using the building, it needs to notice that the ventilated channel must be maintained clean and unhindered status, the vents devices must be repaired periodically in order to ensure good opening and closing function, and the vents should be avoided blocking and the ventilation heating mechanism of the Trombe wall should be avoided destroying in later renovation or decoration of the building.

Si and SiGe Nanowire for Micro-Thermoelectric Generator: A Review of the Current State of the Art

In our environment, the large availability of wasted heat has motivated the search for methods to harvest heat. As a reliable way to supply energy, SiGe has been used for thermoelectric generators (TEGs) in space missions for decades. Recently, micro-thermoelectric generators (μTEG) have been shown to be a promising way to supply energy for the Internet of Things (IoT) by using daily waste heat. Combining the predominant CMOS compatibility with high electric conductivity and low thermal conductivity performance, Si nanowire and SiGe nanowire have been a candidate for μTEG. This review gives a comprehensive introduction of the Si, SiGe nanowires, and their possibility for μTEG. The basic thermoelectric principles, materials, structures, fabrication, measurements, and applications are discussed in depth.

The Impact of Microclimate on the Reproductive Phenology of Female Populus tomentosa in a Micro-Scale Urban Green Space in Beijing

The spatial variation of poplars’ reproductive phenology in Beijing’s urban area has aggravated the threat of poplar fluff (cotton-like flying seeds) to public health. This research explored the impact of microclimate conditions on the reproductive phenology of female Populus tomentosa in Taoranting Park, a micro-scale green space in Beijing (range <1 km). The observed phenophases covered flowering, fruiting, and seed dispersal, and ENVI-MET was applied to simulate the effect of the microclimate on SGS (start day of the growing season). The results showed that a significant spatial variation in poplar reproductive phenology existed at the research site. The variation was significantly affected by the microclimate factors DMT (daily mean temperature) and DMH (daily mean heat transfer coefficient), with air temperature playing a primary role. Specifically, the phenology of flowering and fruiting phenophases (BBB, BF, FF, FS) was negatively correlated with DMT (−0.983 ≤ r ≤ −0.908, p <0.01) and positively correlated with DMH (0.769 ≤ r ≤ 0.864, p < 0.05). In contrast, DSD (duration of seed dispersal) showed a positive correlation with DMT (r = 0.946, p < 0.01) and a negative correlation with DMH (r = −0.922, p < 0.01). Based on the findings, the increase in air convection with lower air temperature and decrease in microclimate variation in green space can be an effective way to shorten the seed-flying duration to tackle poplar fluff pollution in Beijing’s early spring.

In-use emissions and usage trend of pellet heating stoves in rural Yangxin, Shandong Province

The use of coal in Chinese households for winter heating emits harmful pollutants that severely affect indoor air quality and climate. Therefore, China has made efforts to transition into clean heating using improved heating stoves and biomass pellets. Although the economic and policy implications of such demonstration projects have been extensively investigated, little has been done to understand the real-world performance and adoption trends of such stoves. This study measured in-use emissions from nine different pellet stoves used for heating among 52 rural households in Yangxin, Shandong Province. The temperature of the stove chimney of 21 households was monitored and 56 households were surveyed to explore the stove use trend. The particulate and gaseous emission concentrations for most of the stoves exceeded the limits specified in the Chinese national standard. The measured fuel energy-based emission factors (mean±standard deviation) for CO2, CO, NOx, and PM2.5 were 103±3, 1.41±1.19, 0.336±0.237, and 0.146±0.108g/MJ, respectively. Between January to February, the average daily heating duration was 8.71h, and the sustained use of heating stoves was seen among over 85% of the households. On average, the households used their heating stoves for 3.28 months and the estimated annual pellets consumption for a household was 2.7 tons. Besides inherent variabilities associated with user habits, the stove's design-related shortcomings and low-grade pellets hindered the performance and effectiveness of pellet stoves. This study provides insights into opportunities and challenges for the promotion of cleaner fuels and heating technologies. Furthermore, it will provide information on emissions from rural residential sources to build the emission inventory and inform policymaking for successful stove promotion programs.

Virtual metering of heat supplied by zone-level perimeter heaters: An investigation with three inverse modelling approaches

Virtual metering at the equipment level provides a non-intrusive tool to understand energy flows in commercial buildings and monitor building energy performance. The accuracy of virtual meters depends on the modelling approach and its ability to capture the underlying physical processes. This paper presents a novel comparison and provides guidance for the selection of inverse modelling approaches used to create virtual meters to estimate the heat supplied by zone-level hydronic perimeter heaters. The approaches investigated are: steady-state inverse greybox modelling, transient inverse greybox modelling, and water-side load disaggregation. Models that represent these three approaches are trained using data from a highly instrumented academic building in Ottawa, Canada. Model parameters are identified using the genetic algorithm and used in creating virtual meters that can estimate the heat added by perimeter heaters into building variable air volume zones. The accuracy of these virtual meters is assessed by comparing them to physical meters installed in these zones. The results indicate that the three modelling approaches can estimate the daily heating energy supplied by perimeter heaters at a normalized root-mean-square error between 16% and 18%. However, the accuracy of the virtual meters declines as the number of zones increases. The performance of the three modelling approaches is evaluated through illustrative examples that compare modelling assumptions, data requirements, data processing, and model prediction accuracy.

The effect of clean cooking interventions on mother and child personal exposure to air pollution: results from the Ghana Randomized Air Pollution and Health Study (GRAPHS).

Background:Clean cooking interventions to reduce air pollution exposure from burning biomass for daily cooking and heating needs have the potential to reduce a large burden of disease globally.Objective:To evaluate the air pollution exposure impacts of a fan-assisted efficient biomass-burning cookstove and a liquefied petroleum gas (LPG) stove intervention in rural Ghana.Methods:We randomized 1 414 households in rural Ghana with pregnant mothers into a control arm (N = 526) or one of two clean cooking intervention arms: a fan-assisted efficient biomass-burning cookstove (N = 527) or an LPG stove and cylinder refills as needed (N = 361). We monitored personal maternal carbon monoxide (CO) at baseline and six times after intervention and fine particulate matter (PM2.5) exposure twice after intervention. Children received three CO exposure monitoring sessions.Results:We obtained 5 655 48-hour maternal CO exposure estimates and 1 903 for children, as well as 1 379 maternal PM2.5 exposure estimates. Median baseline CO exposures in the Control, improved biomass, and LPG arms were 1.17, 1.17, and 1.30 ppm, respectively. Based on a differences-in-differences approach, the LPG arm showed a 47% reduction (95% CI: 34–57%) in mean 48-hr CO exposure compared to the control arm. Mean maternal PM2.5 exposure in the LPG arm was 32% lower than the control arm during the post-intervention period (52 ± 29 μg/m3 vs 77 ± 44 μg/m3). The biomass stove did not meaningfully reduce CO or PM2.5 exposure.Conclusions:We show that LPG interventions lowered air pollution exposure significantly compared to three-stone fires. However, post-intervention exposures still exceeded health-relevant targets.Significance:In a large controlled trial of cleaner cooking interventions, an LPG stove and fuel intervention reduced air pollution exposure in a vulnerable population in a low-resource setting.