• Energy Research

Drying is a fundamental process for preserving agricultural products, involving heat and mass exchanges. As a sustainable selection, researchers are focusing on solar dryers to improve drying efficiency, shorten drying times, and maintain product quality. Indirect type solar dryers (ITSD) have shown promise in post-harvest preservation. However, there is a lack of detailed investigation in their unique features, types, and performance-enhancement techniques. Thermal energy storage methods, which store excess energy for times when there is no solar irradiance, can improve the dependability of solar drying. Expensive experimental setups have led to the use of computer simulation techniques like computational fluid dynamics (CFD) to optimize drying conditions and dryer design while maintaining product quality. The review aims to provide an overview of different ITSD designs, techniques of thermal energy storage, and explore the use of CFD in analyzing heat and mass transfer phenomena in indirect solar drying systems. Additionally, this review study inspires researchers to explore the development of indirect solar dryers suitable for various drying environments, diverse product drying capacities, and different drying durations. Further research and development in these areas will continue to enhance the performance, energy efficiency, and scalability of indirect solar dryers, contributing to sustainable agriculture and energy conservation.

Gas-path diagnostics is an essential part of gas turbine (GT) condition-based maintenance (CBM). There exists extensive literature on GT gas-path diagnostics and a variety of methods have been introduced. The fundamental limitations of the conventional methods such as the inability to deal with the nonlinear engine behavior, measurement uncertainty, simultaneous faults, and the limited number of sensors available remain the driving force for exploring more advanced techniques. This review aims to provide a critical survey of the existing literature produced in the area over the past few decades. In the first section, the issue of GT degradation is addressed, aiming to identify the type of physical faults that degrade a gas turbine performance, which gas-path faults contribute more significantly to the overall performance loss, and which specific components often encounter these faults. A brief overview is then given about the inconsistencies in the literature on gas-path diagnostics followed by a discussion of the various challenges against successful gas-path diagnostics and the major desirable characteristics that an advanced fault diagnostic technique should ideally possess. At this point, the available fault diagnostic methods are thoroughly reviewed, and their strengths and weaknesses summarized. Artificial intelligence (AI) based and hybrid diagnostic methods have received a great deal of attention due to their promising potentials to address the above-mentioned limitations along with providing accurate diagnostic results. Moreover, the available validation techniques that system developers used in the past to evaluate the performance of their proposed diagnostic algorithms are discussed. Finally, concluding remarks and recommendations for further investigations are provided.

Abstract This paper aims to address the issues related to renewable energy (RE) resources optimization in the areas where providing power from main grid is challenging. A region having ten different sub-regions has been considered for the optimization based on transportation algorithm. The partitions are made based on customer segmentation to ensure that various scattered demand for the RE is represented at the best location to enhance energy optimization by minimizing the energy loss during transmission. Three cases, i.e., when the demand and supply are equal, when there is more demand than supply, and when the supply is greater than demand are considered for the analysis. For the first case, the total energy requirement and the energy potential available from the regions is 1.26 GW h/year. For this scenario, most of the regions (seven regions) received the energy requirements from single RE source; three regions received the required energy from two different RE sources. The annual optimized total cost of energy supply for this scenario is determined to be $187,961.68. Results obtained from the transportation model have been validated based on other RE studies in the area. For the similar case study considered, it is noted that the minimized total cost obtained using transportation algorithm depicts an improvement in cost over integrated renewable energy system (IRES) models. The developed optimization model could be used as a decision making support tool to evaluate and select various alternative renewable energy resources and to determine the optimal locations for developing these resources.

Abstract The energy-saving propensity of liquid desiccant air dehumidification technique compared with its counterparts, mitigating the limitations of conventional desiccant solutions and the need for energy optimization in indoor space cooling, has invigorated the exploration of alternative desiccant solutions. This study investigates different binary deep eutectic solvents as a potential alternative working fluids in liquid desiccant air conditioning systems. Hydrogen bond acceptors (Choline chloride, N, N-Diethylethanolammonium chloride, 1-Butyl-3-methylimidazolium chloride, ZnCl 2) and hydrogen bond donor (Ethylene glycol) were synthesized in different ratios to form binary deep eutectic solvents. The physiochemical, thermophysical and rheological properties of the investigated solutions were characterized and evaluated. DES A1 (mixture of choline chloride and ethylene glycol in ratio 1:2) and DES D1 (1-Butyl-3-methylimidazolium chloride and ethylene glycol in ratio 1:1) were found best among investigated binary DES solutions. The dehumidification and thermal regeneration potential of these promising solutions were further investigated in a humidity chamber and a drying oven, respectively. At 65 % relative humidity, 30 °C air temperature, and 3.77 × 10−4 m2 moisture-desiccant contact area, the estimated dehumidification mass flux of DES A1 and DES D1 are 4.61 × 10−2 and 3 × 10−2 g/m2 ∙s, respectively. Empirical correlations obtained for deep eutectic solvents moisture absorption in this study provide an error limit between ±2.6 % to ±3.5 %. These solutions are found promising as alternative solutions for dehumidification and thermal regeneration.

AbstractCO2 has low critical pressure and temperature. This gives an opportunity CO2 cycles to work in a transcritical nature where heat rejection and absorption are done at supercritical and subcritical conditions, respectively. However, this characteristic posed some performance issues for CO2 refrigeration cycle such as the pressure and temperature of CO2 becomes independent of one another above the critical point thus specifying the operating conditions would be tough. It is also important to identify the optimum cooler pressure and control it; in order to get high cycle coefficient of performance (COP). Thus, the objective of this paper is to investigate the performance of a transcritical CO2 compression refrigeration cycle for different parameters and evaluate its COP. To achieve that, a refrigeration cycle was modeled using thermodynamic concepts. Then, the model was simulated for various parameters that were manipulated to investigate the cycle performance. Maintaining other operating parameters constant the highest COP was 3.24 at 10MPa gas cooler pressure. It was also observed that the cycle is suitable for air-condition application than refrigeration cycle, as COP increases when the evaporator temperature increases. Simulations were conducted using EXCEL developed program. The results can be used in the design of CO2 refrigeration cycle.

Abstract Hybrid nanofluids are a novel class of colloidal fluids which have drawn significant attention due to potential tailoring of their thermo-physical properties for heat transfer enhancement by a combination of more than one nano-additive to meet specific requirements of an application. In the present work, ceramic copper oxide/carbon (SiO2-CuO/C) nanoparticles in 80:20 (wt%) composition were prepared by ultrasonic-assisted wet mixing technique. The hybrid nanofluid was formulated by dispersing the nanoparticles into a base fluid mixture of 60:40 (% by mass) glycerol and ethylene glycol (G/EG) using the two-steps method. The influence of nanoparticles on the augmentation of specific heat, thermal conductivity and viscosity was examined in the volume concentration range of 0.5–2.0% in the temperature range of 303.15–353.15 K. The results demonstrate that the synthesized SiO2-CuO/C hybrid nanoparticles enhanced the thermo-physical properties of the base fluid mixture which is higher than using SiO2 alone. In the case of SiO2–G/EG nanofluid, the specific heat capacity decremented by a maximum value of 5.7% whereas the thermal conductivity and viscosity incremented by 6.9% and 1.33-times as compared with G/EG at maximum volume concentration of 2.0% at a temperature of 353.15 K. Comparatively, a reinforcement of 80% SiO2 with 20% CuO/C in G/EG mixture led to thermal conductivity and viscosity enhancement by 26.9% and 1.15-times, respectively with a significant reduction of specific heat by 21.1%. New empirical correlations were proposed based on the experimental data for evaluation of thermophysical properties.

This study focused on investigating the bottoming power cycles operating with CO2-based binary mixture, taking into account exergetic, economic and exergo-environmental impact indices. The main intent is to assess the benefits of employing a CO2-based mixture working fluid in closed Brayton bottoming power cycles in comparison with pure CO2 working fluid. Firstly, selection criteria for the choice of suitable additive compound for CO2-based binary mixture is delineated and the composition of the binary mixture is decided based on required cycle minimum temperature. The decided CO2-C7H8 binary mixture with a 0.9 mole fraction of CO2 is analyzed in two cycle configurations: Simple regenerative cycle (SRC) and Partial heating cycle (PHC). Comparative analysis among two configurations with selected working fluid are carried out. Thermodynamic analyses at varying cycle pressure ratio shows that cycle with CO2-C7H8 mixture shows maximum power output and exergy efficiency at rather higher cycle pressure ratio compared to pure CO2 power cycles. PHC with CO2-C7H8 mixture shows 28.68% increment in exergy efficiency with the levelized cost of electricity (LCOE) 21.62% higher than pure CO2 PHC. Whereas, SRC with CO2-C7H8 mixture shows 25.17% increment in exergy efficiency with LCOE 57.14% higher than pure CO2 SRC. Besides showing lower economic value, cycles with a CO2-C7H8 mixture saves larger CO2 emissions and also shows greater exergo-environmental impact improvement and plant sustainability index.

Abstract Nanocomposites of a paraffin wax base containing various concentrations (0.5, 1.0, and 1.5 wt.%) of the aluminium, copper, zinc and iron nanoadditives were investigated experimentally and theoretically. The experimental results revealed that an increased weight percent of the additives, within the investigated range, enhanced the thermal properties for TES application. Adding 1.5 wt.% of Cu and Zn nanoparticles enhanced the thermal conductivity of the nanocomposite by 20.6% and 61.5%, respectively. The thermal diffusivity was observed to increase proportionally as the thermal conductivity increases, whereas the specific heat decreases. The experimental results were compared with existing models, and they disagreed with the prediction results of the thermal conductivity values for all of the models in the literature. The Maxwell and Hamilton-Crosser models predicted the closest values to the experimental results; however, they underpredicted the thermal conductivity of the nanocomposite, whereas the values from the other models significantly overpredicted the thermal conductivity values. The collector efficiency performance was enhanced by 15.5% when integrated with PCM-TES. A further enhancement was reported when the collector system was integrated with nanocomposite-TES. The enhanced PCM nanocomposites exhibited improved thermal energy storage capability, mainly in solar/TES integrated applications.

Our objective was to develop a Fuzzy logic (FL) based industrial two-shaft gas turbine gas path diagnostic method based on gas path measurement deviations. Unlike most of the available FL based diagnostic techniques, the proposed method focused on a quantitative analysis of both single and multiple component faults. The data required to demonstrate and verify the method was generated from a simulation program, tuned to represent a GE LM2500 engine running at an existing oil & gas plant, taking into account the two most common engine degradation causes, fouling and erosion. Gaussian noise is superimposed into the data to account measurement uncertainty. Finally, the fault isolation and quantification effectiveness of the proposed method was tested for single, double and triple component fault scenarios. The test results show that the implanted single, double and triple component fault case patterns are isolated with an average success rate of 96 %, 92 % and 89 % and quantified with an average accuracy of 83 %, 80 % and 78.5 %, respectively.

To maximize and improve utilization of solar collector system, there is need to integrate the system with thermal energy storage (TES), this will increase the over all efficiency of the system and provide continuous supply of energy day and night. The performance of the TES depends on its thermal conductivity and this can be enhanced by introducing nanoparticles. Thus, this paper focus on the thermal conductivity enhancement of Cu and Fe nanoparticles dispersed in paraffin based suspension was investigated experimentally for utilization in solar collector integrated with TES. The enhanced thermal conductivity measurement was performed by transient hot disk sensor technique. The increment in thermal conductivity showed approximately linear progression with increase in percentage of mass concentration of the dispersed metal-nanoparticles. It was observed that the nanoparticle with lower thermal conductivity value (Fe-80 W/mK) at bulk enhanced the polymer matrix higher than the nanoparticle with higher thermal conductivity value (Cu-401 W/mK) at the bulk. The Cu and Fe nanoparticles, at mixing ratio of 1.5% by mass, increased the thermal conductivity of the paraffin based nanocomposites by 20.63% and 51.95%, respectively when compared with the pure paraffin. The experimentally measured thermal conductivities of the Cu and Fe-paraffin nanocomposites were compared with some models and it was observed that they were under predicted. The thermal diffusivity and specific heat showed irregular increase and decrease with varying percentage mass concentration of the nanoparticles. The enhanced nanocomposite will be utilized as heat transfer medium in a solar collector system integrated with TES.