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This paper aims to study the fluid flow and heat transfer through a spiral double-pipe heat exchanger. Nowadays using spiral double-pipe heat exchangers has become popular in different industrial segments due to its complex and spiral structure, which causes an enhancement in heat transfer.

In these heat exchangers, by converting the fluid motion to the secondary motion, the heat transfer coefficient is greater than that of the straight double-pipe heat exchangers and cause increased heat transfer between fluids.

The present study, by using the Fluent software and nanofluid heat transfer simulation in a spiral double-tube heat exchanger, investigates the effects of operating parameters including fluid inlet velocity, volume fraction of nanoparticles, type of nanoparticles and fluid inlet temperature on heat transfer efficiency.

After presenting the results derived from the fluid numerical simulation and finding the optimal performance conditions using a genetic algorithm, it was found that water–Al₂O₃ and water–SiO₂ nanofluids are the best choices for the Reynolds numbers ranging from 10,551 to 17,220 and 17,220 to 31,910, respectively.

This paper aims to propose a new nonlinear function estimation fuzzy system as a novel statistical approach to estimate nanofluids’ thermal conductivity.

A fuzzy system having a product inference engine, a singleton fuzzifier, a center average defuzzifier and Gaussian membership functions is proposed for this purpose.

Results indicate that the proposed fuzzy system can predict the thermal conductivity of Al₂O₃/paraffin nanofluid with appropriate precision and generalization and it also outperforms the classic interpolation methods.

A new nonlinear function estimation fuzzy system was introduced as a novel statistical approach to estimate nanofluids’ thermal conductivity for the first time.

A boiling surface with different initial roughness and under various nanoparticles volume fractions was studied in present work.

Develop a correlation and sensitivity analysis.

The results showed that for small (7.3 nm) and much larger (about 2,000 nm) surface roughness, compared to nanoparticle size of around 25 nm, the heat transfer rate of nanofluid diminishes relative to that of base fluid. The results also demonstrated that the boiling heat transfer rate is reduced by increasing the concentration of nanoparticles. For larger boiling surface roughness (480 nm) and nanoparticles volume fractions of less than 0.1 Vol.%, the value of heat transfer increases with the increase of nanoparticles concentration; and for those of more than 0.1 Vol.%, heat transfer rate decreases by adding more nanoparticles, significantly.

Finally, an equation was presented for estimating the wall superheat and the C_sf coefficient in terms of mentioned parameters.

The purpose of this paper is to improve the lattice Boltzmann method’s ability to simulate a microflow under constant heat flux.

Develop the thermal lattice Boltzmann method based on double population of hydrodynamic and thermal distribution functions.

The buoyancy forces, caused by gravity, can change the hydrodynamic properties of the flow. As a result, the gravity term was included in the Boltzmann equation as an external force, and the equations were rewritten under new conditions.

To the best of the authors’ knowledge, the current study is the first attempt to investigate mixed-convection heat transfer in an inclined microchannel in a slip flow regime.

This paper aims to present a black-box fuzzy system identification method coupled with genetic algorithm optimization approach to predict the mixture thermal conductivity at dissimilar temperatures and nanoparticle concentrations, in the examined domains.

WO3 nanoparticles are dispersed in the deionized water to produce a homogeneous mixture at various nanoparticles mass fractions of 0.1, 0.5, 1.0 and 5.0 Wt.%.

The results depicted that the models not only have satisfactory precision, but also have acceptable accuracy in dealing with non-trained input values.

The transmission electron microscopy is applied to measure the mean diameters, shape and morphology of the dry nanoparticles. Moreover, the stability of nanoparticles inside the water is evaluated by using zeta potential and dynamic light scattering (DLS) tests. Then, the prepared nanofluid thermal conductivity is presented at different values of temperatures and concentrations.

The purpose of this paper is to review studies on mathematical optimization of the sustainable gasoline supply chain to help decision-makers understand the current situation, the exact dimensions of the problem and the models provided in the literature. So, a more realistic mathematical optimization model can be achieved by fully covering all dimensions of the supply chain of this product.

To evaluate and comprehend the mathematical optimization of the sustainable gasoline supply chain research area, a systematic literature review is undertaken that covers material collection, descriptive analysis, content analysis and material evaluation steps. Finally, based on this process, 69 related articles were carefully investigated.

The results of the systematic literature review show the main areas of the published papers on mathematical optimization of sustainable gasoline supply chain problems and the gaps for future research in this field presented based on them.

This approach is subject to limitations because the protocol of the systematic review of the research literature only included searching for the considered combination of keywords in the Scopus and ProQuest databases. Furthermore, the protocol used in this paper restricts documents to English.

The results have significant implications for both academicians and practitioners in this field. It can be useful for academics to comprehend the gaps and future trends in this field. Also, for practitioners, it can be useful to identify and understand the parts of the mathematical optimization model, which can help them model this problem effectively and efficiently.

No systematic literature review has been done in this field by considering gasoline to the best of the authors’ knowledge and delivers new facts for the future development of this field.

This research work demonstrates the method of examining the influence of digitalization in social entrepreneurial perspectives. For this purpose, three major digital transformation domains, namely, blockchain, artificial intelligence (AI) and cloud services were considered. For all three domains, their adoption over time is studied and further analyzed. Consequently, it is observed that all three have a noteworthy positive influence to improve the business performance, trade, supply chain and similar disciplines. For the blockchain, their user activity like addition of new wallets, transactions made and the market price for bitcoins over time was used. For AI, data from tech fundings prior to the year 2020–2021 were obtained and AI adoption in several regions was analyzed. Finally, for cloud services, cloud computing adoption data (2009–2019) at both the individual and organizational level were studied. This research is useful for business entities to further support the fact that digitalization has modernized legacy processes, enabled rapid innovation, strengthened security and increased profitability.

One of the main issues which microelectronics industry encounter is reliability as feature sizes scale down to nano-design level. The purpose of this paper is to provide a probabilistic transfer matrix based to find the accurate and efficient method of finding circuit’s reliability.

The proposed method provides a probabilistic description of faulty behavior and is well-suited to reliability and error susceptibility calculations. The proposed method offers accurate circuit reliability calculations in the presence of reconvergent fanout. Furthermore, a binary probability matrix is used to not only resolve signals correlation problem but also improve the accuracy of the obtained reliability in the presence of reconverging signals.

The results provide the accuracy and computation time of reliability evaluation for ISCAS85 benchmark schemes. Also, simulations have been conducted on some digital circuits involving LGSynth’91 circuits. Simulation results show that proposed solution is a fast method with less complexity and gives an accurate reliability value in comparison with other methods.

The proposed method is the only scheme giving the low calculation time with high accuracy compared to other schemes. The library-based method also is able to evaluate the reliability of every scheme independent from its circuit topology. The comparison exhibits that a designer can save its evaluation time in terms of performance and complexity.

The purpose of this paper is achieving a leader–follower formation of unmanned aerial vehicles which is a cooperative scenario inspired by formation flying of living organisms such as geese. Designing a control strategy based on only vision measurement (without radio communication) and keeping connectivity in vision are important challenges in the formation flying problem which is the base of formation flying in living organisms.

To achieve the mentioned purposes, a feedback linearization technique is used. Moreover, a Takagi-Sugeno-based supervisory control strategy for visibility maintenance combined with an acceleration estimator to compensate the leader maneuvers is proposed.

The authors conclude that by using practical seeker sensors, all the mentioned objectives (under the proposed strategy) can be satisfied.

Keeping formation and visibility maintenance in the presence of the leader maneuver are the main contributions of the paper.

The purpose of this paper is to investigate the effects of the sintering temperature on the microstructural, morphological and electrical characteristics of Zinc oxide (ZnO)-based varistors.

This study used a conventional method to design and produce ZnO varistors by sintering ZnO powder with small amounts of various metal oxides. Furthermore, the effect of sintering temperature on varistor properties of (Bi, Co, Cr, Sb, Mn)-doped ZnO ceramics was investigated in the range of 1280–1350 °C.

The obtained results showed an E_B value of 2109.79 V/cm, a V_gb value of 0.831 V and a nonlinear coefficient (α) value of 19.91 for sample sintered at temperature of 1300 °C. In addition, the low value of tan δ at low frequency range confirmed that the grain boundaries created in 1300 °C sintering temperature were obviously good.

Based on the previous research on the ZnO-based varistors, a thorough study was carried out on these components to improve their electrical characteristics. Thus, it is necessary that those varistors have low leakage current and low value of dissipation factor to ensure their good quality. High breakdown fields and nonlinearity coefficients are also required in such kind of components. The effect of sintering temperature on the varistor properties of the new compositions (zinc, bismuth, manganese, chrome, cobalt, antimony and silicon oxides)-doped ZnO ceramics was studied in the range of 1280–1350 °C. Also, the microstructure and the phase evolution of the samples sintered at various temperatures (1280 °C, 1300 °C, 1320 °C and 1350 °C) were investigated according to X-ray diffraction and scanning electron microscope measurements.