•A cryogenic flow electrification test rig has been set up.•The influence of velocity, pipe diameter, material and roughness has been analysed.•A modified semi-empirical correlation for streaming ...current based on our test data has been proposed.
Flow electrification occurs in all fluid flow scenarios involving solid–liquid interfaces. Due to electrostatic safety considerations, extensive research, both experimental and theoretical, has been conducted in the petroleum transportation field. However, research on flow electrification related to cryogenic fluids is relatively scarce, with even fewer experimental studies conducted. With the increasing use of cryogenic fluids such as liquid hydrogen and liquefied natural gas in aerospace and energy fields, there is an urgent need to expand the experimental database on cryogenic fluid flow electrification. In this context, a study focusing on cryogenic flow electrification using liquid nitrogen (LN2) as the working fluid was initiated, accompanied by the establishment of a flow electrification experimental platform capable of capturing ultra-low electrical signals at cryogenic conditions. Three measurement methods were designed and implemented, including charge, potential, and current measurements. By comparing their performance, the streaming charge method was identified as the optimal choice due to the stability and linearity of the raw signal. Subsequently, extensive testing was conducted to analyze the effects of various parameters, including flow velocity, pipe diameter, pipe material, and pipe roughness, on flow electrification intensity. The conclusions drawn include: within the experimental measurement range, the current induced by flow turbulence is on the order of 10−12 A for LN2. Moreover, increasing pipe diameter and roughness exacerbate the charge transported. Among the four materials tested, PTFE exhibits the highest intensity of flow electrification, followed by aluminum and stainless steel, with copper showing the weakest effect. Finally, based on the experimental data obtained, a modified semi-empirical correlation formula for the streaming current was proposed, which can reflect the specific effects of flow velocity, pipe diameter, material, and pipe roughness. Our measurement research has significant implications for the study of flow electrification in LN2 and its applications in aerospace and energy security fields.
•Local thermal equilibrium state is experimentally proved with and without fin inserted.•Inserting fins into metal foam makes a promotional improvement on solidification rate.•Solidification rate is ...significantly improved by increasing fin width and number.•Changing fin pitch has negligible effect on the global solidification process.
Cold storage can effectively turn electricity to cold energy during off peak hours and reduce electricity peak load by supplying cold energy for air conditioning. Solid-liquid phase change rate is seriously encumbered by the relatively-low thermal conductivity of phase change materials (PCMs). A novel fin-foam structure was established to enhance solidification heat transfer and the solidification characteristics were experimentally explored. An experimental system visualizing solid-liquid interface and temperature monitoring was built. The parameters of fin-foam structure, including fin sizes, fin pitch and number were investigated experimentally. Particular attention was paid to justifying the local thermal equilibrium state via measuring temperature on metallic ligament surface and the saturating fluid in pore space. Results showed that inserting fins into metal foam can make a promotional improvement on solidification rate of water by 28.35%. The solid-liquid interface became locally curved after inserting fins. Thermal adhesive and insulation adhesive did not affect the accuracy at pore-scale temperature measurement. Solidification process can be further enhanced through increasing fin width and number rather than fin pitch.
•Composites made of cement paste containing Posidonia-Oceanica natural fibers were studied.•Thermal and mechanical properties of composites were experimentally and analytically studied.•Composites ...thermal conductivity decreases with fibers incorporating.•There is a slight increase of composites mechanical strengths. Optimum values are obtained for fiber volume fractions of 5 - 10%.•Material ductility is greatly improved by fiber adding, fracture toughness is 65% higher than control cement.
This paper focuses on thermal and mechanical properties of a hardened cement paste reinforced with Posidonia-Oceanica fibers. Fibers volume fractions are varied from 0% to 20%. Thermophysical and mechanical properties are measured. Simplified models are developed to predict thermal conductivity, tensile and compressive stresses and fracture toughness variation as a function of fibers volume fraction and geometrical characteristics of samples. Results showed that the addition of Posidonia-Oceanica fibers improved the material insulating properties. In fact, a decrease of about 22% (from 0.0718 W.m-1.K-1 to 0.559 W.m-1.K-1) of thermal conductivity was found with adding 20% of fibers compared to control cement paste.
Concerning mechanical properties, flexural and compressive strengths increased for fiber volume fractions in the range of 5 to 10% and then decreased for higher fiber volume fractions. It was shown through a simplified model and MEB observations that agglomeration of fibers for high volume fraction is behind this phenomenon. Moreover, a noticeable increase of toughness was observed with increasing fibers amount: for instance, an increase of about 65% (from 0.245 MPa.m1/2 to 0.404 MPa.m1/2) was observed with the introduction of 20% of fibers in the composite. Simplified analytical models are also developed to predict thermal conductivity, tensile and compressive strengths and fracture toughness. These models are validated with experimental data.
The Moroccan TRIGA Mark II serves as a pivotal cornerstone in the advancement of nuclear science and technology within the region. Precise modeling is crucial for ensuring safe and efficient reactor ...operation. OpenMC, known for its versatility as a stochastic code with a powerful Python API, offers unique capabilities for reactor analysis, optimization, and automation. This makes OpenMC the ideal choice for neutronic analysis in the development of multi-physics models aimed at enhancing the accuracy and reliability of reactor analysis. Leveraging its Python interface, we have developed a high-fidelity model for the Moroccan TRIGA Mark II, enhancing modeling precision. A central element of this study involved making crucial modifications to OpenMC’s source code, enabling the prompt method and calculating the βeff. These modifications are essential, representing a significant advancement in the capacity to conduct a comprehensive analysis of a wide range of critical neutronic parameters. These parameters include the neutron flux spectrum, keff, control rods worth and core excess reactivity, and power peaking factors. The results exhibit strong agreement with the performed experimental measurements and MCNP6.2 calculations.
The findings underscore the model’s precision and reliability, making it a valuable asset for neutronic analysis and, particularly, for developing a comprehensive multi-physics model of the Moroccan TRIGA Mark II.
•High-fidelity TRIGA Mark II model with OpenMC, distinguished by its Python API.•OpenMC’s source code modifications enabling the prompt method and calculate βeff.•Model validated via extensive experimental measurements and MCNP6.2 calculations.•The model is developed as part of the IAEA-CRP initiative.
The linear attenuation coefficients (LAC) of four soils (Black cotton (S1), Sandy (S2), Clay (S3), and Sandy (S4)) samples were measured at photon energies released from radioisotopes Co57 (122 keV), ...Ba133 (356 keV), 22Na (511 and 1275 keV), Cs137 (662 keV), Mn54 (840 keV), and Co60 (1330 keV) using a gamma spectrometer includes a NaI (Tl) scintillation detector. The experimental measurements were confirmed utilizing the Monte Carlo N-particle transport code. The linear attenuation coefficient values enhanced from 0.256 cm−1 to 0.296 cm−1 (at Eγ of 122 keV), from 0.126 cm−1 to 0.142 cm−1 (at Eγ of 662 keV), and from 0.0938 cm−1 to 0.105 cm−1 (at Eγ of 1275 keV), raising the (Fe + Mn) concentration from 0.912 wt% to 11.214 wt%, as well as raising the soil samples density from 1.62 g/cm3 to 1.79 g/cm3. The study also shows an enhancement in the half value thickness, transmission factor, radiation protection efficiency and lead's equivalent thickness due to the enrichment of Fe + Mn concentrations within the studied soils. The results show that the Black cotton soil exhibits better shielding properties for γ-ray than the other soils.
This research suggests new experimental outcomes regarding the viscosity and thermal conductivity of silver, copper and titanium oxide nanoparticles dispersed in mineral insulating oil by ...high-pressure homogenization process without using any additives or surfactants. Later, via employing non-linear regression, an adaptive neuro-fuzzy inference system (ANFIS) and achieved experimental data, new models were evolved to predict the viscosity besides thermal conductivity of nanofluids. For modelling, viscosity as well as thermal conductivity of nanofluids was picked as the target factor, and the volume concentration in addition to types of nanoparticles was regarded as the design (input) factors and all experimental data was classified into a train and a test data set. The model was conducted through the train set and the outcomes were contrasted with the experimental data set. Predicted thermal conductivities as well as viscosities were compared with experimental data for three different nanofluids, having nanoparticles volume concentrations of 0.00125% and 0.050%. A comparison was made between the ANFIS and regression outcomes. To evaluate the results, the coefficient of determination (R2) and root-mean-square error (RMSE) are reported. The achieved results of this research indicate that thermal conductivity of nanofluids enhance by nanoparticles concentration increment. Thermal conductivity of silver is higher compared to thermal conductivity of titanium oxide and copper nanoparticles. According to the ANFIS and non-linear regression outputs, two sets of correlations for calculating the dynamic viscosity as well as thermal conductivity were suggested. Comparing the experimental data with suggested correlations demonstrate very good agreement between the suggested correlations and experimental data. However, equations of previous researches would not be perfectly able to predict the experimental data of present study.
ANFIS structure for present study with five layers. Display omitted
•Cu, Ag and TiO2 nanoparticles dispersed in mineral oil without any usage of additives.•Thermal conductivity and viscosity of the nanofluids were measured experimentally.•ANFIS model were used to predict the thermophysical properties of nanofluids.•A comprehensive correlation was derived for thermophysical properties prediction.•ANFIS suggested correlation is in excellent agreement with the experimental data.
•The novel chilled beam can operate as three modes to meet various thermal needs.•Simulation of airflow and heat transfer in the novel beam validated by experiment.•New beam’s high thermal capacities ...demonstrated in simulation and lab tests.•Novel chilled beam is able to merge the advantages of two beams in one unit.•Simulation-based optimization proved effective and efficient in design process.
Chilled beams have been widely used in many regions of the world due to the high energy efficiency and satisfactory thermal comfort they provide. This paper employed a Computational Fluid Dynamics (CFD) based optimization strategy to develop a novel multi-mode chilled beam (MCB) that could merge the advantages of both passive chilled beam and active chilled beam units. Depending on the specific thermal requirement of indoor space, the novel chilled beam could operate as three different modes which were fast cooling mode, fast heating mode and gentle cooling mode. With the optimal design parameters achieved through numerical optimization, a prototype was built for model validation and a comprehensive performance evaluation. Results showed that the cooling and heating capacities of the optimized MCB unit could reach 3600 W and 4000 W, respectively. Compared with conventional HVAC systems, MCB system improved the energy efficiency by 9.2% under gentle cooling mode and by 19.0% under fast cooling mode. The noise level for the new chilled beam could be as low as 19.8 dB, providing a good acoustic performance. The CFD based optimization strategy, followed by experimental validation, proved to be an effective and efficient approach for developing a novel chilled beam unit.
•The effect of concrete crack on chloride transmission was investigated by ABAQUS.•The macro/meso-scale simulation model were used to simulate the chloride migration.•The developed meso-scale model ...was used to simulate the transmission behavior.
The influence of cracks with different widths on chloride transmission has been investigated by experimental tests using the method of rapid chloride migration (RCM) and numerical simulation using finite element analysis with software ABAQUS. Meso-scale finite element simulation model has been developed to study the aggregate heterogeneity. It is found that numerical simulation results are in good agreement with the experimental measurements. When the crack width is less than 0.05mm, the influence of the crack can be ignored. While the crack with width is in the range from 0.08mm to 0.1mm, the dispersion accelerates with crack width increasing. When the crack width is larger than 0.1mm, the transmission of chloride is similar to the transmission in the liquid. The finite element method verified by the experimental results can be further applied to systemically explore the correlation of the behavior of chloride dispersion with specific crack width.
•Measuring system for normal spectral emissivity of low thermal conductivity materials.•Method for simultaneously measuring normal spectral emissivity and temperature.•Temperature homogeneity ...simulation of the materials heated by the synergistic heating method.•Measurement of normal spectral emissivity of alumina ceramic fiber at high temperatures.
This study develops a measurement system and a method for measuring the normal spectral emissivity and temperature of low thermal conductivity materials at high temperatures. A self-design heating device using a synergistic heating treatment including a high-power laser and a radiation heating cavity is introduced, and a Fourier transform infrared spectrometer is utilized to measure the radiation signal of sample. Based on the temperature hypothesis model, which considers normal spectral emissivity keeps constant within small temperature difference less than 10.0 K, a method is proposed for realizing the inversion of normal spectral emissivity and temperature with the multispectral radiation signal. A genetic algorithm-based technique with big mutations is used to estimate the normal spectral emissivity and temperature of sample at high temperatures. The variation of blackbody radiation signals with the blackbody radiance is analyzed to verify the linearity for the detector of FTIR spectrometer. The apparent normal spectral emissivity of an alumina ceramic fiber is determined in the spectral range of 2.5–25.0 μm at 673–1273 K. Furthermore, the uniformity of temperature distribution on the sample surface and inside the sample is numerically evaluated. The standard uncertainty in the experiment at 1273 K is less than 4.0 % in the investigated bands.
In the most case, the manufacturer measure electrical or thermal parameters under environment conditions that are artificial in the laboratory scale and rarely occur in reality outside. Therefore, ...the characterization of photovoltaic modules under dynamic environmental conditions will be an essential phase to go forward with renewable energy technology. In this study an experimental setup, uses sensors (current, voltage and temperature) interfaced with a MicroLab data acquisition card, was developed with low-cost to measure current-voltage and power-voltage curves of the PV modules under dynamic environmental conditions. In addition to on-site measurement of meteorological parameters like solar irradiance, temperature, humidity and wind speed, spatial modeling of the conditions was performed using the WRF weather model. A performance-based experimental method for PV module characterization under dynamic conditions was presented along with suitable modeling tools. The obtained results indicate that the evolutionary algorithms proved effective for parameter extraction of the three common electrical models single diode, double diode and triple diode, from experimental module test data and MLBSA algorithm successfully modeled the experimental I–V curves, showing good agreement with measured current, voltage and power values based on statistical metrics.
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