Purpose This paper aims to use a fractional constitutive model with a nonlocal velocity gradient for replacing the nonlinear constitutive model to characterize its complex rheological behavior, where non-linear characteristics exist, for example, the inherent viscous behavior of the crude oil. The feasibility and flexibility of the fractional model are tested via a case study of non-Newtonian fluid. The finite element method is non-Newtonian used to numerically solve both momentum equation and energy equation to describe the fluid flow and convection heat transfer process. Design/methodology/approach This paper provides a comprehensive theoretical and numerical study of flow and heat transfer of non-Newtonian fluids in a pipe based on the fractional constitutive model. Contrary to fractional order a, the rheological property of non-Newtonian fluid changes from shear-thinning to shear-thickening with the increase of power-law index n, therefore the flow and heat transfer are hindered to some extent. Findings This paper discusses two dimensionless parameters on flow regime and thermal patterns, including Reynolds number ( Re ) and Nusselt number ( Nu ) in evaluating the flow rate and heat transfer rate. Analysis results show that the viscosity of the non-Newtonian fluid decreases with the rheological index (order α) increasing. While large fractional (order α) corresponds to the enhancement of heat transfer capacity. Research limitations/implications First, it is observed that the increase of the Re results in an increase of the local Nusselt number ( Nul ). It means the heat transfer enhancement ratio increases with Re. Meanwhile, the increasement of the Nul indicating the enhancement in the heat transfer coefficient, produces a higher speed flow of crude oil. Originality/value This study presents a new numerical investigation on characteristics of steady-state pipe flow and forced convection heat transfer by using a fractional constitutive model. The influences of various non-dimensional characteristic parameters of fluid on the velocity and temperature fields are analyzed in detail.

The number of patients with neurodegenerative disorders is growing rapidly, and it poses a major concern to discover effective therapies. The well-known deep brain stimulation as a treatment for Parkinson's disease has irredeemable impact on the brain tissue. Magnetothermal stimulation is a good alternative though, it is still invasive due to stereotactic injection for nanoparticle delivery. A good solution to this issue is to take advantage of microvasculature and excite the nanoparticles inside the brain capillaries. Hence, transport and dynamic analysis of blood flow through a brain capillary is crucial. This article presents a two-dimensional theoretical study of a blood flow with magnetic nanoparticles through a capillary when exposed to an alternating magnetic field. The magnetic nanoparticles are localized within the domain over time. The particle transport impacts and the dynamic interactions with the blood flow are elaborately investigated.

The biological systems are tied to the molecular transport across the living tissues which in turn highly depend on kinetic and thermal energy exchanges. For various applications ranging from artery modeling to very sensitive tissue modeling such as the brain, porous media modeling accurately predicts biological behavior. This article elaborately addresses the fundamentals of porous media and provides a comprehensive synthesis of the theory development from the primary methods available in the literature to the modern mathematical formulations. Specifically, this paper concentrates on two remarkable biological applications including (1) blood flow interactions with the porous tissue and (2) hydrodynamic impacts of particle-particle interactions in the microscale modeling that requires a Lagrangian frame.

The study of temperature profiles within the central nervous system (CNS) when exposed to an alternating magnetic field (AMF) as a plausible therapy for neuropsychiatric disorders is crucial. This new procedure can be a better alternative for conventional permanent implanted electrodes treatment for CNS diseases such as Parkinson's disease (PD). Hyperthermic treatments are highly dependent on biomaterial thermophysical properties, magnetic nanoparticle (MNP) solution and magnetic field characteristics. This manuscript aims to ascertain the optimum conditions for magnetothermal neuromodulation. Hence, we employ a comprehensive modeling and utilize finite element method (FEM) for simulations to obtain the temperature distribution across the exposed tissue by which the lesion size is evaluated. The results are compared against experimental data in the literature. Local temperature distribution demonstrates an elevated temperature of 57 °C particularly, at the center of the injected solution after exposure. It is shown that a high fraction of the tissue around the injected magnetic nanoparticle solution is damaged mainly due to crossing the safe temperature domain (43 °C < Ttissue < 50 °C). In this investigation, we advance an optimized approach to a theoretical model of neuromodulation, based on Pennes’ equation, that includes a novel stimulation constraint. We establish several new results with this technique; in particular, we demonstrate: the method can be utilized to compute optimized parameter values. Consequently, the minimum necessary activation temperature for magnetothermal stimulation is achieved. Meanwhile, the underlying biomaterial is maintained at low levels of thermal-induced damage.

Neurodegenerative disorders, e.g., Alzheimer's and Parkinson's are signal irregularities in neuron cells. Deep brain stimulation (DBS) is a conventional method for Parkinson's treatment. This method manages Parkinson's symptoms, e.g., tremor, by surgically implanting an electrode to deliver constant stimulation in deep brain levels. The fatal impacts of DBS motivated scientists to propose a minimally invasive treatment, termed as “Magnetothermal Neuromodulation.” This technique employs an alternating magnetic field (AMF) to excite injected transducers, i.e., magnetic nanoparticles (MNP). The nanoparticles exposed to the magnetic field dissipate heat via thermal hysteresis. The local elevated temperature activates a type of heat-sensitive ion-channel, which leads to calcium cation (Ca2 +) influx. The Ca2 + influx eventually ameliorates the symptoms. In the magnetothermal modulation, the primary aim is to reach the minimum temperature required for stimulation (43°C) and maintain the tissue temperature below 50°C to avoid the thermal cytotoxic impacts. Hence, neurosurgical operations seek the Thermo engineering theories to alleviate the risk levels and effectively administer the remote therapy. The success and safety of the treatment strongly relies on thermal interactions of the brain capillary wall with blood flow carrying heat dissipative nano-transducers. Our emphasis is on microscale modeling of nanoparticles undergone magnetothermal stimulation and the consequences on the targeted neural circuits. As such, for medical advancements, the present contribution provides a mathematical model that extensively elaborates the physical attributes such as the blood flow dynamics, nanoparticle interactions with capillary flow, heat transfer, and the subsequent regulated neural signaling.

A successful cogeneration system design project needs an estimation of the economical parameters of the project, including capital investment, costs of fuel, expenses in maintenance and operating, and the proper cost for the products. This study describes the economic consideration of the benchmark cogeneration systems, called CGAM system located in the United States. To evaluate the profitability of alternative investments, cost estimation of the capital investment, calculation of the main product cost under the realistic assumption of fuel inflation, electricity inflation, and discount rate are required. Probabilistic analysis of lifetime discounted costs, including fuel and electricity cost changes, are defined by using the Monte-Carlo method for the next 20 years. Also, the total Revenue Requirement (TRR) method is selected as the main evaluation method for the economic model. As the result of calculations, the range of optimized value for inlet and outlet temperature of the combustion chamber, the efficiency of the gas turbine, efficiency and pressure ratio of air compressor in which the plant is economically and functionally in the best operation for the minimum cost of products of the cycle are achieved.

This work aims to provide a state-of-the-art review of the performance of combined cycle power plant (CCPP) based on several proposed inlet air cooling systems. Investigators strive to meet the significant need to promote and develop inlet air cooling technologies to recover heat from the wasted energy in the exhaust gasses of the CCPP and diminish the environmental impacts. Various types of cooling systems mainly offer a boost for electric power generation during the peak load hours. The output power of the CCPP directly depends on the mass flow rate of air that flows through the air compressor. Therefore, during extremely hot weather conditions, subsequently, the air density drops, and this leads to a drastic decrease in the power output. This paper reviews available studies investigated the impacts of inlet air cooling systems on the performance of the CCPP. The fogging cooling system contributed by up to 17% in improving the total performance of the CCPP; however, with the use of the evaporative cooling, the performance was enhanced by only 4%. The energy consumption of mechanical chiller compared to that of evaporative cooling is high due to the effectiveness of the evaporative cooler which depends on the humidity of inlet airflow. Further, the mechanical cooling system can provide the CCPP with a cooling effect for around 7-hour on-peak periods. This method increases the gain of the CCPP performance by 13.6%. Ultimately, the CCPP equipped with an absorption chiller demonstrates the best solution to increase the performance by up to 23%.

An experimental study has been carried out to characterize bubble formation, growth, and detachment mechanisms in a stagnant liquid column. Both bubble frequency and bubble detachment size were measured in different gas flow rates, injector diameters and orientations, submergence height, and liquid properties. Experiments were performed for air injection flow rate ranges between 200 mlph and 1200 mlph using needle diameters of 1.6, 1.19, 1.07, and 0.84 mm submerged in liquids with viscosities of 0.001, 0.1, 0.35, and 1 Pa.s. The data for bubble formation was obtained using a high-speed imaging technique. The results show that the bubble diameter at the departure increases as the needle diameter, liquid viscosity, and gas flow rate increase. In addition, the decrease in the submergence height results in a larger bubble at the departure. In order to analyze the changes in bubble detachment characteristics, a force modelling on a growing bubble was proposed. The experimental data were utilized for training a feed-forward back propagation neural network system to estimate the bubble detachment diameter. They were also used to propose a correlation to predict bubble diameter at the departure. The proposed correlation is found to be in the range of ± 8% of the obtained experimental data.

In some case of laboratory and industrial applications, various kind of measurement instruments must be placed in a conduit, in which multiphase fluid flows. Vortex shedding for any immersed body in flow field is created with a frequency, which according to flow conditions such as flow rates, geometry of body, etc. may be constant or variable. Failure may happen, if this frequency is close to one of the natural frequencies of the instruments. These flows can play a significant role in long-term reliability and safety of industrial and laboratory systems. In this study, an Eulerian–Eulerian approach is employed to simulate Air-Water two-phase flow around a rectangular probe with different volume fractions (0.01-0.5) and Reynolds numbers (1000-3000). Two-phase flow characteristics around the probe have been analyzed numerically. The results show vortex shedding in all cases with distinct Strouhal number. In addition, results illustrate that shedding is intensified by increasing Reynolds number. In order to validate the results, fraction of inlet volume was set to zero, and drag coefficient and its relation with low Reynolds number (1000-3000) in single phase flow were compared to experimental and numerical results in published article. The results show a complete agreement between the simulation and available data.

Bubble formation and growth play an important role in various processes and industries, where the dispersion of gas bubbles in a liquid medium occurs frequently. In this paper, the formation, growth, and detachment of gas bubbles produced from a submerged needle in water are numerically and experimentally investigated. The effect of injected gas properties on bubble characteristics, including bubble diameter, contact angle, and the frequency of bubble formation, is evaluated. In particular, the changes in bubble characteristics during the injection process are investigated for three different gases to evaluate the effect of density and surface tension on the bubble detachment criteria. The present numerical results show an acceptable agreement with experiments under different operating conditions. The results show that the increase in surface tension, and the decrease in gas density result in larger bubble sizes before detachment occurs. Moreover, the bubble generation frequency is found to strongly depend on the contact angle and the surface tension.

This paper analyses adiabatic gas bubble formation, growth, and detachment which are produced from a submerged needle in water with the aim of elucidating the impact of surface tension on bubble properties.A simulation model is utilized to enable examination of the problem for the mentioned parameter.The numerical results are compared with experimental observations on the bubble for validation purposes.The simulation results, including changes in bubble properties during the process, are recorded and a comprehensive research for different surface tensions is applied to understand the effect of this parameter on the bubble.It is found that higher surface tension between gas and water results in larger bubbles right before the departure occurs.