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Abstract The accurate information of the thermal stresses and temperature in isotropic elastic solids is the key for many engineering applications. At present the classical linear coupled theory of thermoelasticity deduced with the assumptions of small temperature changes is widely used to solve the thermoelastic problems in engineering. In this paper, to describe the thermoelastic behavior in isotropic solids undergoing large temperature changes more accurately, the novel coupled models of thermoelasticity and the corresponding finite element models have been presented explicitly and validated by experimental measurement. The effect of large temperature changes on the solutions of thermoelastic problems is discussed. For the heat transfer process, if the isotropic elastic solids will expand when heated and contract when cooled and the condition d E E d T · σ i j E − δ i j 1 − 2 ν α 0 can be met in the context of small deformations, the effect of large temperature changes can be regarded as increasing the specific heat. The proposed models are applied to solve two thermoelastic problems. From the obtained numerical results, the effect of large temperature changes will increase with the amplitude of temperature change and may be considerably even when the temperature changes slowly.

Interconnectivity and interoperability are very important features in the development of integrated energy management systems for industrial facilities. A simple and common strategy for exchanging energy-related information among the entities in a facility is currently lacking. To this end, the purpose of this study is to present an IoT-based communication framework with a common information model to facilitate the development of a demand response (DR) energy management system for industrial customers. Additionally, we developed and implemented an IoT-based energy-management platform based on a common information model and open communication protocols, which takes advantage of integrated energy supply networks to deploy DR energy management in an industrial facility. The experimental results of this study demonstrate that the proposed platform can not only improve the interconnectivity of the entities in industrial energy management systems but also reduce the energy costs of industrial facilities.

Abstract Date biomass is a carbon-rich renewable resource that can be considered a potential carbon-rich substrate for energy generation over anaerobic digestion (AD). However, due to its complex nature, appropriate pretreatment is necessary to achieve a higher methane yield. Hence, the current study was envisioned to evaluate the influence of three different pretreatment strategies, namely acid, alkali, and hydrothermal pretreatment on biochemical methane potential (BMP) of seven diverse sorts of Algerian date biomass, namely Pedicels, Fibrilium, Petiole, Fruit bunch, Spath, Palm, and its mixture. Among all the pretreatment conditions, alkaline pretreatment highly influenced the lignin composition of date biomass and showed higher BMP. Among all sorts of biomass, higher BMP was detected through Palm as 295.9 mL CH4/g-TS, whereas the lowest BMP values were recorded with Petiole as 226.74 mL CH4/g-TS. Among all the experimental variations, ammonium pretreated Palm biomass documented the highest substrate conversion efficiency (63.80%), which correlates well with the observed higher BMP values. Nevertheless, there was a very marginal improvement in BMP detected in the case of other pretreatment strategies compared to alkaline pretreatment. This might be due to the efficacy of the applied pretreatment method on delignification of date biomass.

This paper presents a CFD analysis of three types of axial-flow magnesium-based automotive cooling fans. The numerical modeling was conducted for geometrically modified fan designs: one with no-beads, the second one with beads at the suction-side of the fan namely reverse-beads fan, and the third one with beads installed at the pressure-side of the fan namely forward-beads fan. The effect of geometric modifications of the fan blades on the volumetric flow rate, fan efficiency, and energy efficiency was investigated using Reynolds-averaged Navier-Stokes (RANS) equations following the multiple reference frame methodology. The fan with no-beads was fabricated using 3D printing technology and tested to measure the flow velocity. Subsequently, the fans with beads along with the no-beads fan designs were numerically analyzed. The volumetric flow rate, fan efficiency, and energy efficiency were quantified as a function of fan rotating speed. The results show that the reverse-beads fan produced a relatively more volumetric flow rate and energy-efficient compared to the forward-beads fan. Moreover, to further improve the performance of the reverse-beads fan, the location and size of the bead structure were varied along the radial direction of the fan blade. The optimized reverse-beads fan significantly improves the fan performance.

Abstract This study newly introduces a complementary cooperative algorithm considering generative adversarial network (GAN)-Conditional Latent Space (CLS) combined with bidirectional long short-term memory (BLSTM) for improved and efficient lithium-ion rechargeable battery state prediction. The GAN-CLS algorithm, which is an advanced method of GAN, can generate corresponding images from an input label description. Long short-term memory (LSTM) is a specific recurrent neural network (RNN) architecture that can predict sequences more accurately than conventional RNNs. In terms of battery state prediction, the combination of two methods (GAN-CLS and LSTM) surely provides more improved and efficient rechargeable battery state prediction in contrast to conventional state predictors. The procedure of this study is as follows. First, we propose methods to enhance the data from battery charge/discharge by converting prepared data to images; then, the GAN-CLS method is used to generate corresponding battery data from previous images. Subsequently, the generated data is used to train the BLSTM model. Finally, the trained model is used to predict the battery state. By various experiments and verification, it is concluded that the proposed study can be a good solution for rechargeable battery state prediction (reduction of the time cost 50 times in modeling and 20 times in train/test, provision of a more accurate prediction mean square error (MSE) smaller than 0.0025 and the average MSE less than 0.0013).

Abstract This paper addresses three main subjects in supercritical heat transfer: (1) difference in thermal characteristics between upward and downward flows; (2) effect of simulating flow channel shape; (3) evaluation of the existing supercritical heat transfer correlations. To achieve the objectives, a series of experiments was carried out with CO2 flowing upward and downward in a circular tube with an inner diameter of 4.57 mm and an annular channel created between a tube with an inner diameter of 10 mm and a heater rod with an outer diameter of 8 mm. The working fluid, CO2, has been regarded as an appropriate modeling fluid for water, primarily because of their similarity in property variations against reduced temperatures. The mass flux ranged from 400 to 1200 kg/m2 s. The heat flux was varied between 30 and 140 kW/m2 so that the pseudo-critical point was located in the middle of the heated section at a given mass flux. The measurements were made at a pressure of 8.12 MPa, which corresponds to 110% of the critical pressure of CO2. The difference between the upward and downward flows was observed clearly. The heat transfer deterioration was observed in the downward flow through an annular subchannel over the region beyond the critical point. Several well-known correlations were evaluated against the experimental data, and new correlations were suggested for both a tube and an annular channel.

In this study, heat transfer and thermal performance of a periodically dimple-protrusion patterned surface have been investigated to enhance energy-efficiency in compact heat exchangers. The local heat transfer coefficients on the dimple/protrusion walls are derived using a transient TLC (Thermochromic Liquid Crystal) technique. The periodically patterned surface is applied to the bottom wall only or both the bottom and top walls in the test duct. The ratio of dimple (or protrusion) depth to duct height is 0.25, and the ratio of duct height to dimple (or protrusion) print diameter is 1.15. The Reynolds number is tested in low range values from 1000 to 10000. On the single-side patterned walls, various secondary flows generated from the dimple/protrusion coexist. The vortices induced from the upstream affect strongly on the downstream pattern. For the double-side patterned wall case, vortex interaction affected by the opposite wall enhances highly the heat transfer. The heat transfer augmentation is higher in the lower Reynolds number due to the effective vortex interactions. Therefore, the performance factor considering both heat transfer enhancement and pressure loss increases with decreasing the Reynolds number.

Abstract This paper presents numerical optimization results for the thermal and effective efficiencies of a solar air heater duct as a function of various roughness geometries on the heated plate. A methodology for the prediction of thermal and effective efficiency of the SAH has been developed on the basis of heat transfer and friction factor correlations. Among the roughness geometries considered, the discrete multiple V-shaped rib results in the best thermal and effective efficiencies over the entire range of design conditions. This work also addresses the scope for future research in the area of roughened SAH ducts and will be helpful for researchers investigating new artificial shapes for SAH ducts to enhance the heat transfer.