Computational modeling and analysis of a fluid test rig

Nanofluids, which are suspensions of metallic or ceramic nanoparticle fillers in a variety of liquids, are a new category of heat-transfer fluids. Owing to the changes in thermal conductivity caused by nanofillers, they have thermal properties that are superior to those of conventional fluids; this leads to a more efficient heat transfer, making them attractive for various industrial applications. Using numerical models to support in situ experiments is necessary to analyze nanofluids’ thermal properties and flow; creating a test ring has been suggested to describe the characteristics and behavior of fluids under controlled conditions. Modeling and computational analysis support such advances, which are essential for understanding and optimizing phenomena occurring during experimental tests; the modeling and computational analysis of a test rig designed to characterize a diphenyl oxide/biphenyl blend base fluid are presented in this research work. The test rig design included an integrated stainless-steel piping system with a flow-controlled pump and heat exchanger; the computational model considers the conjugate effects of fluid dynamics to facilitate the construction of test rigs.


Introduction
In recent years, nanofluids have emerged as an innovative category of heat transfer fluids, possessing superior thermal properties compared to conventional fluids [1,2]; which are mainly suspensions of metallic or ceramic nanofillers diluted in water, ethylene glycol, and oil [3,4].Nanofillers cause changes in the thermal conductivity of the fluid, which leads to more efficient heat transfer because of the contact surface and aggregation of the nanofillers; some studies have shown that nanofluids provide a much higher thermal conductivity than conventional fluids; this characteristic makes them attractive for a variety of industrial applications.
The analysis of the thermal properties and flow of nanofluids, as well as their behavior in practical applications, requires the implementation of numerical models to support in situ experiments [5].One of the proposed developments involves the construction of a test ring that characterizes the properties and behavior of fluids under controlled conditions.Several test rigs have been developed to evaluate fluids and nanofluids [6,7].This type of development is supported by modeling and computational analysis, which are essential for understanding and optimizing phenomena involved in experimental tests [8].
Accordingly, this research presents a test rig's modeling and computational analysis to characterize a diphenyl oxide/biphenyl blend base fluid.The design of the test rig consists of an integrated stainlesssteel piping system with a flow-controlled pump and a heat exchanger, and the computational model considers the conjugate effects of fluid dynamics to facilitate the construction of the test rigs.

Methodology
The development of a numerical model and computational analysis of a system that will be used to characterize the thermal and dynamic behavior of a fluid is proposed; the process starts with precise calculations that determine the technical specifications required by the test rig, geometry, flow, velocity, volume, operating pressure, and physicochemical characteristics of the fluid [9].Subsequently, a computer-aided design (CAD) was created to visualize and analyze the fluid in detail and accurately in the test rig, and a finite element analysis was performed to verify, validate, optimize, and simulate the behavior of the fluid in the test ring under different operating conditions before proceeding with the physical implementation.

Fluid dynamics
In the design and modeling of the test rig, a specific base fluid, diphenyl oxide/biphenyl blend [10], which can operate at a temperature of 350 °C, was used; in this regard, a suitable pump was selected, which provides a fluid flow rate in the range of 100 l/h to 1000 l/h.Equation (1), Equation ( 2), and Equation (3) allow the calculation of the mass flow rate, pressure drop, and total energy of the system [11], as well as the test rig length that maximizes the system efficiency.
In Equation (1) Q ! is used to determine the mass flow rate as a function of the volume flow rate; in Equation ( 2), H "#"$ used to calculate the total head of the system considering pressures (p), velocities (V), elevations (Z), and head loss (H ' ), which were previously determined according to the pump specifications; and in Equation (3) H ' is used to model the head loss in the pipe, depending on the length (L), diameter (D), velocity (V), friction factor (f), and losses (K).The volumetric flow rate, pressure, cross-sectional area, velocity, displacement height, and physical properties of the fluid are used to estimate the length of the fluid circulation pipe.

Finite element design and modeling
Based on the fluid dynamics results, we proceeded to recreate the test rig system design, as shown in Figure 1(a); subsequently, each component of the test system assembly was designed based on the elements and operating conditions established by the suppliers.In Figure 1(b), the 3D model of the system is shown; this visualization approach allows us to analyze each system component with detail and precision, ensuring that the test rig conforms to our specifications and requirements.
Figure 1(b) designs and the diphenyl oxide/biphenyl blend fluid properties are loaded into the numerical simulation software to recreate the fluid behavior in the test rig; the convergence of the mesh is established from the tetrahedral method with an independent trajectory (see Table 1), which allows us to simulate the fluid behavior efficiently and accurately by varying the fluid velocity and temperature, which leads to the optimization of our test rig designs.

Results and discussions
The behavior of the diphenyl oxide/biphenyl blend fluid at a flow rate of 0.054 m/s was analyzed using CFD, with a maximum flow velocity of 9.62 m/s observed in the reduced zone [12] (see Figure 3); this behavior was compared to other models showing similarities in the reduced zone [13].The fluid is subjected to a shear stress of 4.25 MPa, a value that resembles that observed in [13], and describes the frictional behavior of a Newtonian fluid (see Figure 4(a)).Immediately after the nozzle exit, areas of turbulence are detected.However, as the fluid advances, a tendency to re-establish a laminar flow is observed; this change manifests itself with a Reynolds number of 596, suggesting a transition to a laminar regime (see Figure 4(b)).The path followed by a fluid particle moving through the three-rig is shown in the streamline, and the pressure changes due to the variation in cross-sectional area as the fluid moves through the test rig, providing the highest velocity value at the nozzle.

Conclusions
An exhaustive numerical analysis of the fluid behavior was performed using the computer-aided design of a test rig.Likewise, the validation and optimal understanding of the system were carried out through the analysis of the flow velocity and shear stress, which are crucial because they provide accurate information that guides the meticulous construction of the test rig.The design, computational modeling, and analysis of a fluid test rig not only contribute to the optimal and accurate construction of a test rig but also lay the foundation for the application of a solid experimental methodology; this methodology allows us to accurately reproduce the conditions and variations of the system, providing a reliable platform to perform tests and analyses that contribute significantly to technical, academic and scientific knowledge in the area of science and engineering.

Figure 2
Figure2shows the input parameters, indicating a fluid flow value of 0.054 m/s and an output value known as pressure-outlet, which allow us to control and monitor the behavior of the fluid during the simulation, ensuring that the results are accurate and representative of the real conditions.The computational model was constructed with the purpose of analyzing the behavior of the fluid at the pump outlet and at the tank inlet because, in this section, there is a cross-sectional area reduced to 2 mm in diameter.

Figure 2 .
Figure 2. The blue vectors represent the fluid input at 0.054 m/s, and the red vectors represent the pressure-outlet output of the system.

Figure 3 .
Figure 3. Flow behavior through the nozzle with a diameter of 2 mm.

Figure 4 .
Fluid behavior on the test stand, (a) shaft stress on the nozzle, (b) flow line with velocity result throughout the system.IMRMPT-2023 Journal of Physics: Conference Series 2726 (2024) 012007

Table 1 .
Convergence of the mesh in velocity.