Heat Energy Research Articles

Design, Optimization and Analysis of Electric Heat Drier

The utilization of solar energy for food drying has long been a method of food preservation. Regrettably, certain methods that are implemented in rural areas have resulted in numerous drawbacks, including the inferior quality of the food that is produced and the extended drying time that is a result of numerous external factors. The Electric Powered Air Dryer is a novel technology that is derived from the combination of electric and thermal energy. The electric heater is employed in our endeavor to convert electric energy into heat energy through the use of a blower. We introduce the electric air dryer machine in our project for the primary purpose of dehydrating seeds, fruits, and other items with high moisture content. In our endeavor, the electric air dryer comprises four primary components: a blower, heat sensing element, 12v adapter, and electric heater. The blower is designed to transport heated air to the designated location, thereby eliminating the moisture content of the area. Additionally, our product is portable in size. Therefore, it is effortless to relocate the ground dehydrator to any location. This report includes a background on the project, with the first chapter introducing the topic of drying and our endeavor. The literature review is the subject of the second chapter. Chapter three comprises drier descriptions. The fourth chapter delves into the design of the dryer, while the fifth chapter provides an analysis of the dryer. The final chapter comprises references, while the sixth chapter compares conventional drying.

Mixed and forced convection heat transfer and pressure drop in inclined tube with twisted tape in transition flow

Understanding the influence of angular orientation on mixed convection heat transfer and pressure drop in circular tubes with swirl generators is crucial for optimizing thermal performance in various engineering applications, including heat exchangers and energy systems. This study aims to investigate the impact of angular orientation on heat transfer enhancement and pressure drop characteristics in a uniformly heated circular tube equipped with a twisted-tape longitudinal swirl generator. An experimental approach was employed, varying key parameters such as Reynolds number (435–10,130), heat flux (2, 3, and 4 kW/m²), twist ratio (P/D = 3, 4, and 5), and angular orientation (15° and 30°). The setup was validated against established correlations for Nusselt number and friction factor, demonstrating strong agreement. The results reveal that angular orientation significantly affects heat transfer and pressure drop at Reynolds numbers up to ~ 1000, where mixed convection plays a dominant role. Beyond this, forced convection prevails. In a plain channel, the transition from laminar to transitional flow occurs at Reynolds numbers of 2924–4088 for a 15° angle of inclination (AoI) and 3001–4274 for a 30° AoI, with the transition occurring slightly earlier at the lower angle. The Richardson number varied from 2.5 in the low laminar regime to 0.0087 in the turbulent regime, with additional variations observed when turbulators were introduced.

Bifurcated merging operations of two spherical tokamak plasmas for reconnection heating and magnetic helicity injection

Abstract In tokamak plasma merging experiments, high-power ion heating is achieved only when the current sheet thickness is compressed to ion gyroradius. The magnetic reconnection converts 40-50% of the reconnecting magnetic field energy into the ion heating energy with the scaling law of the ion heating energy proportional to the square of reconnecting magnetic field. If the compressed current sheet thickness is larger than the ion gyrodadius, the magnetic reconnection converts only 5-10% of the reconnecting magnetic energy into the ion heating energy. The high-power ion heating can be understood from the experimental finding that the poloidal electric field due to electrostatic quadrupolar potential in the downstream region increases linearly with both the reconnecting magnetic field and the guide field.

Plasma Photocatalysis: A Novel Approach for Enhanced Air Disinfection in Centralised Ventilation Systems

The COVID-19 pandemic highlighted the urgent need for sustainable and scalable air disinfection technologies in HVAC systems, addressing the limitations of energy-intensive and chemically intensive conventional methods. This study developed and evaluated a pilot experimental installation integrating plasma chemistry and photocatalysis for airborne pathogen and pollutant mitigation. The installation, designed with a modular architecture to simulate real-world HVAC dynamics, employed a bipolar plasma ioniser, a TiO2 photocatalytic module, and an adsorption-catalytic module for ozone abatement. Characterization techniques, including SEM and BET analysis, were used to evaluate the morphology and surface properties of the catalytic materials. Field tests in a production room demonstrated a 60% reduction in airborne microflora in three days, along with effective decomposition of ozone. The research also determined the optimal electrode geometry and interelectrode distance for stable corona discharge, which is essential for efficient plasma generation. Energy-efficient design considerations, which incorporate heat recovery and heat pump integration, achieved a 7–8-fold reduction in air heating energy consumption. These results demonstrate the potential of integrated plasma photocatalysis as a sustainable and scalable approach to enhance indoor air quality in centralised HVAC systems, contributing to both public health and energy efficiency.

Urban Heat Mitigation through Intelligent Green Design: A Case Study of Terminalia mantaly using AI and Environmental Sensing

The increasing rate of global warming due to urbanization, greenhouse gas emissions, and deforestation has amplified the urban heat island (UHI) effect, particularly in tropical and semi-arid areas. Strategic tree planting has become an essential nature-based solution for climate mitigation. In this study, the cooling capacity of Terminalia mantaly, a quick-growing, evergreen tree with broad canopy, is assessed using advanced AI tools, remote sensing methodologies, and in-field sensor observations. A multi-modal research methodology was used to investigate the influence of the tree on its microenvironment. Thermography and deep learning-based algorithms (YOLOv8, Mask R-CNN) indicated that Terminalia mantaly lowered surface temperatures under its canopy by a maximum of 4.8°C, the largest effects occurring around midday. Satellite-based NDVI and LST analysis showed that tree-covered zones had NDVI values of 0.74 and LST reductions of 3.5°C compared to adjacent unvegetated areas. AI models, particularly Random Forest and LSTM networks, achieved over 88% accuracy in predicting thermal changes and temporal cooling patterns. Ground-based environmental sensors confirmed a 3.0°C drop in ambient temperature, 7% increase in relative humidity, and 100% increase in soil moisture beneath the canopy. Simulations with Unity 3D and finite element modeling demonstrated a radial cooling effect up to 5 meters, and a 45% reduction in radiative heat absorption because of leaf structural scattering. Significantly, Terminalia mantaly had foliage year-round, providing consistent shade and cooling without the loss of seasonal canopy. The research concludes that Terminalia mantaly is a viable species for urban climatic resilience. Its high growth rate, dense canopy, minimal leaf shedding, and constant coverage make it the best for heat stress mitigation, energy savings, and ecological sustainability in urban areas. This research recommends the use of AI-supported afforestation as well as precision ecological planning in fighting global warming

Fabrication of photothermal carbon nanodot materials coated with luffa evaporation structure for solar energy water evaporation

Solar water evaporation is considered one of the most sustainable and environmentally friendly technologies. To achieve good evaporation performance, a combination of materials with good photothermal conversion efficiency and good evaporation structure is required. In this study, we used carbon nanodots as a photothermal material made that synthesis by hydrothermal of urea and citric acid. At the same time, luffa possessing advantages such as good water transport and easy attachment of carbon nanodots was chosen as the evaporation structure. The results showed that carbon nanodots material had an average size of less than 5 nm and a good absorption range in the wavelength of 200-800 nm. The absorption range of the material has expanded to the near-infrared region (NIR region), increasing the ability to absorb sunlight and convert it into heat energy, subsequently, improving the evaporation efficiency. The carbon nanodots/ luffa composite structure showed a high evaporation rate of 1.25 kg.m-2h -1 under 1 sun irradiation (1 kW.m-2).

Direct Current Photovoltaic Solar Energy for Water Heating

In this study, an experimental device is developed and implemented to evaluate the process of heating water using photovoltaic solar energy in direct current. The prototype consists of a 147 L stainless steel tank, a 5000 W heating element, and four solar panels (370 W each). Tests were carried out with a direct photovoltaic power supply and with the use of a maximum power point tracking (MPPT) device. Temperature and electrical sensors were installed and connected to a data acquisition system. The results show that the electrical energy produced by the PV solar panels can be used directly for water heating. For the direct PV power supply, the average total efficiency is 12%; with the MPPT, the average value is 18.2%. There is a clear improvement in efficiency when using a device with maximum power tracking, improving the heating process and reducing the time needed to reach the set temperature. This technology can be applied to water heating in residences, medical centers, and other buildings that require it.

Energy Cost Optimisation in a Wastewater Treatment Plant by Balancing On-Site Electricity Generation with Plant Demand

Wastewater treatment plants (WWTPs) consume a considerable amount of energy. They also generate energy in combined heat and power (CHP) units, which utilise biogas from the anaerobic digestion of sewage sludge to produce renewable electricity. Different prices apply to electricity generated on site in CHP units, to the purchase of electricity from the grid, to the sale of surplus electricity to the grid and energy tariffs, which motivates the optimisation of energy costs. This paper presents a strategy for optimising electricity costs by adapting on-site electricity generation in CHP units to the demand of the WWTP. The approach is designed for a CHP system that generates electricity in multiple internal combustion gas engines. It is implemented as a two-level control system, where the lower control level dynamically adjusts the power of the individual gas engines, and the upper control level optimises the desired total power, taking into account the current energy consumption of the WWTP, biogas reserves and electricity tariffs. The proposed concept was implemented at the Domžale-Kamnik WWTP. A six-month evaluation showed that electricity purchased from the grid could be reduced from 8.7% to 3.3% of the WWTP’s electricity consumption. This reduction affects the system economically, as electricity purchased from the grid at low and high tariffs is 35% and 76% more expensive than electricity generated on site (excluding the grid fee). This approach can be extended to balance dispatchable electricity generation at the WWTP to respond to short-term grid demand.

Development of n-type ZnAlInO Semiconductor Materials for Thermoelectric Generators in Aerospace Applications.

Thermoelectric conversion is a system that can convert heat energy originating from temperature difference into electrical energy. Although it has many advantages in terms of usage, research is required to acquire high-efficiency thermoelectric materials due to their low efficiency. Herein, Al- and In-doped ZnO semiconductor thermoelectric material is synthesized, produced, and examined for use in the production of thermoelectric generators that can be used in aviation applications. The synthesis of ZnAlIn powders is carried out by the sol-gel method. The xerogel is dried at 200 °C for 10 h, and the dried material is then calcined at 600 °C for 4 h in an atmospheric oven to obtain ZnAlIn material. The obtained powder is then compressed with a cold press to produce pellet samples. Pellet samples are sintered in an atmospheric furnace at 1350 °C for 36 h and are made ready for measurements. Comprehensive characterization and analysis of microstructural and structural properties are performed by Fourier transform infrared spectroscopy, differential thermal analysis-thermogravimetry, X-ray photoelectron spectroscopy, scanning electron microscopy, and X-ray diffraction methods. Seebeck coefficient and thermal capacity measurements are performed to determine thermoelectric properties. The results obtained from the study show that ceramic-based ZnAlIn semiconductor thermoelectric material has the required efficiency for thermoelectric generator production.

A predictive model for damp risk in english housing with explainable AI

Damp in residential buildings poses risks to indoor air quality, occupant health, and structural integrity, and affects up to 27% of homes in the England. This study develops a predictive model for damp risk, using 2,073 inspection records from a housing association across 125 local authorities. Homes were labelled as damp (1,630) or non-damp (443), with data supplemented by national Energy Performance Certificate (EPC) records, incorporating building characteristics and energy efficiency indicators. To evaluate model performance, both a balanced dataset (869 homes, 426 damp, 443 non-damp) and a larger imbalanced dataset (2,073 homes) were used. Seven machine learning algorithms were deployed, with the best-performing model achieving 0.636 accuracy on balanced data and 0.793 on imbalanced data. SHAP (SHapley Additive exPlanations) analysis identified heating cost, energy consumption, and wall energy efficiency as the strongest predictors of damp. Statistical tests and causal analysis were applied to interpret SHAP results, offering insights into potential damp risk and mitigations. The findings suggest that machine learning can support early identification of homes likely to develop damp, helping housing managers prioritise interventions before damp issues escalate.

Sustainable Rural Housing in Cold Climates: A Model for Rumicruz-Ecuador

Background The loss of cultural identity in the rural architecture of Rumicruz, Chimborazo, is a consequence of the adoption of generic models and unsustainable modern materials, which has affected thermal comfort and the connection with local traditions. This research proposes sustainable housing that combines vernacular and modern techniques, respecting both the environment and the community's needs. Method Based on a mixed approach (qualitative and quantitative), the architectural, social, and environmental context was analyzed through a field diagnosis, literature review and critical observation. During this process, problems related to thermal comfort, housing deterioration, and the use of inadequate materials were identified. The proposal includes the use of mudbrick, stone, and concrete blocks, complemented with solar heating systems and energy efficiency, significantly improving thermal comfort compared to traditional housing. Conclusions It is concluded that the proposal integrates cultural identity and sustainability, adapting traditional techniques to current demands. The bioclimatic analysis and design support the thermal comfort values, highlighting the relevance of designs adapted to the local context.

EXPERIMENTAL INVESTIGATION ON DOUBLE-PASS SOLAR AIR HEATER WITH INTERNAL HEAT STORAGE

Solar energy is one of the crucial energy sources for agricultural drying, industrial process heat and space heating requirements, that is renewable as well as pollution-free. In drying applications and heating of the building spaces, solar energy has an important role to play, as it provides an enormous amount of heat energy where the air is the final receiver of the heat energy. Flat plate collectors are good enough for heating air, but the technology and applications of solar air collectors have not been so developed as a liquid solar collector. As solar energy is inconsistent and nature dependent, more often there is a mismatch between the solar thermal energy availability and requirement. This drawback could be addressed to an extent with the help of thermal energy storage systems combined with solar air heaters. The solar air heaters typically have single-pass type airflow, having flow over or under or both over and under the absorber plate. Double- pass type solar collectors will have flow over the absorber plate for the first pass and returns under the absorber plate for the second pass or vice-versa. Key Words: Wireless Sensor Networks (WSNs), Energy-efficient techniques, Clustering algorithm, Routing protocol, Load balancing.

Integrating Big Data and AI in Nutrition

Food nutrition is the source of heat energy in human body. The human body obtains nutrients from food, such as proteins, fats, carbohydrates and so on. Nutrition is very important for human health. The technology is used in every sectors. Indeed, AI is emerging as an important tool in clinical nutrition using telematic means to self-monitor various health metrics, including blood glucose levels, body weight, heart rate, fat percentage, blood pressure, activity tracking and calorie intake trackers. In particular, the most common application of digital technology is in the area of nutrition. Data Analytics and similar technologies play a leading role, and here in this paper different aspect related to the Big-data and Artificial Intelligence with references to the Food and Nutritional Systems have been described with current and future scenario. The existing works related to the fields are well described and reported with major highlights.

Optimization of aerodynamic heater blade shape based on NSGA-II and fuzzy C-means clustering

Abstract Aerodynamic heaters are widely used in industrial applications, such as gas preheating, mine ventilation, and circulation drying, serving as critical gas heating equipment. Improving their efficiency is of great significance for energy conservation and emission reduction. However, despite their industrial importance, studies on the impact of blade geometry on the thermal and flow performance of aerodynamic heaters have not yet been reported. To address this gap, this study proposes a novel multi-objective optimization framework to enhance the heating performance and energy efficiency of aerodynamic heater blades. Parametric modeling of the heater was conducted using inlet angle, outlet angle, and blade height as design variables, with temperature and velocity as optimization objectives. A surrogate model was constructed using fuzzy C-means clustering, combined with the Non-Dominated Sorting Genetic Algorithm II (NSGA-II) for multi-objective optimization. The optimization results demonstrate that the redesigned blades significantly improve temperature and velocity distributions, enhance heat diffusion and fluid mixing, improve outlet flow stability, and reduce energy losses. Compared to the original model, the thermal efficiency of the optimized aerodynamic heater increased by 3%, while the heat flux density improved by 4%. This study provides a robust theoretical foundation for the optimal design of aerodynamic heater blades, offering valuable support for energy efficiency improvements in industrial applications.

Building heating energy demand estimated by random forest model in individual and hybrid approaches

Building heating energy demand estimated by random forest model in individual and hybrid approaches

Energy and Exergy Analysis of a Hybrid Photovoltaic–Thermoelectric System with Passive Thermal Management

Hybrid photovoltaic (PV) and thermoelectric generator (TEG) systems combine heat and light energy harvesting in a single module by utilizing the entire solar spectrum. This work analyzed the feasibility and performance of a hybrid photovoltaic–thermoelectric generator system with efficient thermal management by integrating heat pipe (HP), radiative cooling (RC), and heat sink (HS) systems. The proposed system effectively reduces the PV operation temperature by evacuating the residual heat used in the TEG system to generate an additional amount of electricity. The remaining heat is evacuated from the TEG’s cold side to the atmosphere using RC and HS systems. This study also analyzed the inclusion of two TEG arrays on both sides of the HP condenser section. This numerical analysis was performed using COMSOL Multiphysics 5.5 software and was validated by previous analysis. The performance was evaluated through an energy and exergy analysis of the TEG and PV systems. Enhancing the thermal management of the hybrid PV-TEG system can increase energy production by 2.4% compared to a PV system operating under the same ambient and solar radiation conditions. Furthermore, if the proposed system includes a second array of TEG modules, the energy production increases by 5.8% compared to the PV system. The exergy analysis shows that the enhancement in the thermal management of the PV operating temperature decreases the thermal exergy efficiency of the proposed system but increases the electricity exergy efficiency. Including TEG modules on both sides of the condenser section of the HP shows the system’s best thermal and electrical performance. These results may be helpful for the optimal design of realistic solar-driven hybrid systems for globally deserted locations.

Climate Adaptation of Folk House Envelopes in Xinjiang Arid Region: Evaluation and Multi-Objective Optimization from Historical to Future Climates

Under intensifying global warming and extreme climate events, the climate adaptability of folk houses in Xinjiang’s arid regions faces critical challenges. However, existing studies predominantly focus on traditional folk houses under current climate conditions, neglecting modern material hybrids and long-term performance under future warming scenarios. This study develops a data-driven framework to assess and enhance building envelope performance across historical-to-future climate conditions (2007–2021 TMY data, 2024 observations, and 2050/2080 SSP3–7.0 projections) using the entropy-weighted TOPSIS method and NSGA-II algorithm. Analyzing rammed earth, brick–wood, and brick–concrete folk houses in Kashgar, Hotan, Kuqa, and Turpan, the optimization targets thermal discomfort hours (TDHs), heating energy consumption (HEC), and net present value (NPV). The results demonstrate optimized solutions achieve 30–60 year climate resilience, reducing HEC by 51.54–84.76% (43.02–125.78 kW·h/m2·a) compared to baseline buildings, TDH by 15–52.93% (301–1236 h) in arid Zone A and by 5.54–10.8% (208–352 h) in the extreme hot-arid Zone B (Turpan), and NPV values by CNY 31,000–85,000. Rammed earth constructions demonstrate superior performance in Zone A, while brick–concrete exhibits optimal extreme hot-arid adaptability, and brick–wood requires prioritized retrofitting. The findings advocate revising China’s design standards to address concurrent winter overcooling and summer overheating risks under future warming. This work establishes a climate-resilient optimization paradigm for arid-region folk houses, advancing energy efficiency and thermal comfort.

Development and Analysis of Easy-to-Implement Green Retrofit Technologies for Windows to Reduce Heating Energy Use in Older Residential Buildings

Green remodeling and retrofitting are effective strategies for enhancing the sustainability of existing buildings. While green remodeling involves significant structural modifications, green retrofitting typically focuses on improving energy efficiency and reducing environmental impact. However, easy-to-implement green retrofit technologies can be particularly valuable for low-income communities, offering a more affordable way to upgrade residences without extensive renovations. This paper analyzed the effectiveness of newly developed, easy-to-implement green retrofit technologies for windows in reducing heating energy use and greenhouse gas emissions. We conducted experiments using secondary glazing and windproof materials to enhance the thermal insulation and air-tightness performance of a residential building. Subsequently, we simulated the effectiveness of these green retrofit technologies under various conditions for residential buildings. In addition, we analyzed utility bills using data collected from residents. Our findings demonstrated an average reduction of 10–15% in heating energy consumption through the implementation of these green retrofit technologies for windows in older residential buildings.

The effectiveness test of film forming hydrogel (FFH) of Yellow Root Extract (Arcangelisia flava (L.) Merr) on healing burns of male white mice (Mus Musculus)

The Burns are conditions where skin tissue is lost due to direct contact with heat energy. Therefore, a preparation was developed as film forming hydrogel (FFH) from yellow root extract. Yellow roots contain alkaloids, flavonoids, and saponins, which can improve wound healing. This study aims to determine the effect of the concentration of yellow root extract on wound diameter percentage and increasing the number of fibroblast cells and epithelial thickness. This research uses a true experimental laboratory with a design pre-post test study method on mice aged 2-3 months weighing 20-35 g. Samples were taken using a random sampling technique and divided into five treatment groups, namely formula 1 (F1) with 0.5% yellow root extract, formula 2 (F2) with 1% yellow root extract (F2), formula 3 (F3) with 1.5% yellow root extract, bioplacentonÒ (positive control), normal saline 0.9% (negative control). Treatment of mice for 14 days. The observation parameters were measuring the diameter of the burn wound using the Morton method and the percentage of burn wound healing. The number of fibroblast cells and epithelial thickness were observed at 400x magnification by taking five fields of view in a zig-zag manner. This research shows that the film forming hydrogel (FFH) preparations from yellow root extract with a 1.5% yellow root extract (F3) are the most effective for healing burn wounds. This can be seen from the diameter of the wound, the percentage of wound healing, the increase in fibroblasts, and the thickness of the epithelium.

A Colorful Electrochromic Infrared Emissivity Regulator for All‐Season Intelligent Thermal Management in Buildings

AbstractRadiative cooling is a technology that utilizes the high emissivity of materials in the atmospheric window to achieve cooling, showing great application prospects in building energy‐saving. However, traditional static passive radiative cooling materials with broad‐spectrum high emissivity can lead to increased heating energy consumption in winter due to overcooling and a weakened cooling effect in summer due to the urban heat island effect. In this study, a colorful, intelligent infrared emissivity regulator is well designed based on a multi film ultrathin electrochromic device for all‐season thermal management in buildings. The infrared emissivity of the regulator can vary in real time in response to seasonal or temperature variations, allowing for the switching between radiative cooling and insulation. Guided by nano‐photonics theory for multilayer optical films, the regulator achieves multi‐modal dynamic infrared emissivity regulation in the atmospheric window , and the high reflectance in the non‐atmospheric window inhibits heat gains from the external environment. The regulator demonstrates excellent environmental adaptivity with an acceptable response time, a long cycle life, and good bending resistance. The regulator can achieve ≈2 °C/3 °C (nighttime/daytime) temperature adjustment. The simulation results indicate that the regulator can achieve an annual building energy saving of 3.46 MJ m−2.