Journal of Energy Engineering

By coupling fluid dynamics and solid mechanics, a numerical framework has been developed to investigate the temperature distribution and stress field on the boiler walls and to propose useful advice on reducing the thermal stress and improving the mechanical reliability. Simulation of a laboratory scale, gas fuel opposed firing boiler has been conducted, including the combustion and heat transfer process, as well as the thermal stress distribution by finite-element analysis. The results have been verified by a previous parallel experiment. The results show that heat load and the symmetry of flame can obviously affect the mean temperature of the boiler. In the upper furnace, the amount of fuel is the major factor affecting temperature profile, while the temperature in the burner zone is mainly determined by the distribution of the flame. The temperature is extremely high (about 520 K) at the wall connections. Stress distribution is of great relevance to temperature and asymmetric combustion, which causes extremely strong stress (more than 630 kPa). The study is of great significance for providing guidance for the design, manufacture, installation, and operation of boilers.

A comparison of the thermal performance and energy efficiency of walls constructed using autoclaved aerated concrete (AAC) block with thermal insulating plaster and reflective coating and the standard hollow-core concrete block (HCB) wall is presented. The study was performed through the field monitoring of two test rooms with AAC and HCB walls located in Eastern Saudi Arabia, with weather characterized by a hot and humid climate during the summer. Weather stations, infrared cameras, thermocouples, heat flux meters, temperature/relative humidity sensors, U-value equipment, and power meters were used to assess the thermal performance and energy consumption of the two test rooms. The results indicated that the thermal resistance of AAC walls was about five times that of the HCB walls, whereas the thermal transmittance of AAC walls was reduced by 82%. The AAC blocks with insulating plaster and reflective coating tendered a 58% reduction in the energy consumption in the AAC wall test room. Simulation of the test rooms using DesignBuilder software version 5.4 captured the field results with reasonable accuracy.

A new type self-circulating structure for flue gas was designed, with a corresponding low-nitrogen oxides (NOx) burner developed. A three-dimensional finite element model was established, and independent grid study and model verification were carried out to guarantee the accuracy. The temperature distribution and gas composition of different cross-sections along the axial direction were measured at different air–gas speed ratios. The influences of nozzle diameter and composition of the mixed gas on combustion and NOx emissions were compared and studied in depth. The results show that as the gas jet speed decreased, the gas permeability decreased, and the degree of mixing of the air and gas was aggravated, which caused the maximum temperature to rise and a large amount of NOx was generated. However, the higher air jet aggravated the airflow disturbance, which improved the low oxygen and low combustible atmosphere, and temperature uniformity was better. Increasing the proportion of blast furnace gas improved the low-oxygen atmosphere. The maximum temperature and temperature difference decreased accordingly, and the NOx emissions were greatly reduced. When the fuel was changed from coke oven gas to blast furnace gas, the NOx concentration at the outlet was reduced from 188.08 to 1.09 ppm.

A battery energy storage system (BESS) can provide flexible energy management solutions for power systems. A BESS with the ability to maintain functionality can greatly affect power system reliability. In this paper, two fault-tolerant (FT) strategies (i.e., a lower-rated power mode and times-rated power mode) and four reliability evaluation indexes are proposed for vanadium redox-flow batteries (VRFBs) in power systems. Each strategy is evaluated in terms of both power and energy response capabilities of VRFBs and verified via experiments. The testing results show that the lower-rated power mode is suitable for energy applications, such as load shifting, and the times-rated power mode is suitable for power applications, such as power smoothing. The reliability evaluation index, considering power and energy, is an extension of the traditional index and can be used to quantitatively evaluate the FT method in the energy storage field.

The paper focuses on the performance of thermoelectric generators (TEGs) in different positions and under different running conditions. Three-dimensional numerical models of two designs of exhaust heat recovery systems were studied in which two kinds of heat exchangers were designed, and their flow and temperature field characteristics were analyzed. Thermoelectric generators were arranged on the upper and lower surfaces of the heat exchanger, and their thermoelectric output performance was investigated under different engine running conditions (i.e., medium load, high load, and full load). The results showed that the surface temperature of the heat exchanger with vortex rods is higher and more uniform than that of the heat exchanger without vortex rods. Although the backpressure increases for the heat exchanger design with the vortex rods, this is in the order of 1,392 Pa in the condition of full load and therefore negligible. One can see that the position of TEGs and diesel engine running conditions greatly impact the performance of TEGs. Compared with the heat exchanger without vortex rods, the heat exchanger with vortex rods could supply a higher open-circuit voltage at the corresponding position. The output characteristics of TEGs are better, as the temperature is higher in a full load condition.

In this paper, an accumulative factor was defined to quantify the accumulative effect caused by heat storage by building envelopes in heating, ventilating, and air-conditioning (HVAC) systems. This factor was calculated using a novel model that was developed using the harmonic reaction method, the heat balance method, and a heat storage coefficient. Furthermore, simulations by EnergyPlus and experiments for three case walls (Wall E1, Wall E2, and Wall E3) were conducted under different outdoor conditions to determine the accumulative effect and verify the new model. The results show that the model can effectively evaluate the accumulative effect: when the outdoor temperature is below and above 10°C in the winter, the inner surface temperature and the indoor air temperature of the case walls vary greatly. A small slip region in the inner surface temperature curve appeared for one cycle. The accumulative factor ranged from 0.67 to 0.99 for the case of Wall E1, and the variation in the indoor air temperature was $\pm 1°\mathrm{C}$. The novel model that is developed in this paper simplifies the calculation of the accumulative effect and improves the accuracy of the calculated cooling and heating load in HVAC systems.

In the current work, the artificial intelligence techniques multilayer perceptron neural network (MLP), radial basis function neural network (RBF), and group method of data handling (GMDH) were used to estimate the indoor temperature ($T_{\mathrm{int}}$) in buildings under tropical climate conditions. The data used for modeling correspond to experimental samples measured during one year, considering as a case study the installation of a university laboratory. The models were developed utilizing as independent variables the climatological measurements of solar radiation, wind speed, outdoor relative humidity, and environmental temperature, and the working hours and occupancy of the building. The training, statistical comparison, and modeling performance were conducted through a computational methodology to obtain the best estimation architectures for each technique. The statistical parameter applied in the study were the root mean square error (RMSE) and the coefficient of correlation (R). Results reported the MLP as the technique with the best estimation accuracy ($\mathrm{R}=93.08\%$ and $\mathrm{RMSE}=1.0166$ for training, and $\mathrm{R}=92.90\%$ and $\mathrm{RMSE}=1.1494$ for testing), with an architecture composed by 6-30-1 (input variables, hidden neurons, and output value). Additionally, a sensitivity analysis identified the MLP and RBF as the techniques that best represent the physical behavior of the phenomenon studied. According to the sensitivity analysis, the most influential variables were the environmental temperature and outdoor relative humidity, followed by solar irradiation, working hours, wind speed, and the number of occupants. The proposed methodology represents an alternative method to simplify the analysis of thermal modeling in buildings exposed to tropical climates based on an experimental measurement approach. It can be applied for the development of smart sensors aimed at the efficient management of energy and thermal comfort in buildings.