Oxide Nanofluids Research Articles

Dynamics of magneto-electric hybrid nanoparticles with chemically reacting and radiated moving plate: Entropy analysis

In this new era of fluid field, researchers are interested in hybrid nanofluid because of its thermal properties and potential, which are better than those of nanofluid when it comes to increasing the rate at which heat is transferred. In comparison to the dynamics of chemically reactive Ethylene Glycol - Zinc Oxide (nanofluid) and Ethylene Glycol - Zinc Oxide - Titanium dioxide (hybrid nanofluid) over a moving surface, nothing is known in terms of thermal radiation, entropy formation, viscous dissipation, and the Lorentz force. The thermo-physical characteristics of Ethylene Glycol, Zinc Oxide nanoparticles, and Titanium dioxide nanoparticles are used in this study to derive the governing equations for the transport of both dynamics. Flow-driven equations are transformed into nonlinear ODEs and solved using MATLAB bvp4c solver. It is noticed that, when magnetic field parameter (M) takes input in the range 0 ≤ M ≤ 3, skin friction coefficient decreases at a rate of 0.22052 (in case of hybrid nanofluid) and 0.19203 (in case of nanofluid) per unit value of magnetic field parameter. It is detected that the rise in Brinkmann number causes a rise in entropy generation and Bejan number decreases as Brinkmann number increases. Furthermore, when Eckert number rises, the heat transmission rate decreases. The heat transmission rate drops at a rate of 0.0869 (in case of hybrid Nanofluid) and 0.07429 (in case of nanofluid) when Eckert number (Eck) takes input in the range 0 ≤ Eck ≤ 0.7. The mass transmission rate increases at a rate of 1.013383 (in case of hybrid nanofluid) and 1.013125 (in case of nanofluid) when Schmidt number (Sc) takes input in the range 0 ≤ Sc ≤ 1. A comparison of the current results to previous results indicated a satisfactory agreement under certain conditions.

The translational, rotational, and phonon dynamics of water in ZrO2 /water nanofluid

The translational, rotational, and phonon dynamics of water in zirconium oxide (ZrO2) nanofluid were investigated by quasi-elastic neutron scattering, 17O NMR relaxation, and inelastic X-ray scattering, respectively. The particle size of ZrO2 is 3～100 nm, and the concentration of ZrO2 nanoparticles is 5, 10, 20, and 30 wt%. The translational and rotational motions of water molecules become retarded with increasing the concentration of ZrO2. This indicates that there is an attractive interaction between water molecules and the surface of the nanoparticles. The high-frequency sound velocity of the nanofluid obtained from phonon dynamics measurements is slightly larger than that of pure water although it is not much difference compared to the case of the translation and rotation. These findings indicate that water dynamics in the nanofluid is different from that of the bulk. It might be reasons for the enhancement of the thermal conductivity of the nanofluid.

Thermal convection in a rotating porous medium layer saturated by a nanofluid under a helical magnetic field

In recent years, experiments with flows of liquid metals in a helical magnetic field have been actively carried out. The study of the processes of mixing and crystallization of a liquid metal is of practical importance for metallurgy. With the development of nanotechnology, more and more new types of nanofluids (hybrid, ternary nanofluids) are being synthesized, and the thermophysical characteristics of which can compete with liquid metals. This circumstance served as a motivation for conducting this theoretical study. In this study, the criterion for the onset of convection in a Darcy–Brinkman porous medium layer saturated by an electrically conductive nanofluid under a helical magnetic field is investigated. The Brownian motion and thermophoresis effects are combined in the model for nanofluids, whereas the Darcy–Brinkman model is used for porous media. Instead of prescribing the nanoparticle volume fraction on the borders, we adopted a boundary condition in which the nanoparticle flow is considered to be zero. In the absence of a temperature gradient, a new type of instability in a helical magnetic field in a thin layer of a nanofluid is considered. The growth rate and the region of the development of this instability are numerically obtained depending on the profile of the azimuthal magnetic field (the magnetic Rossby number Rb) and the radial wave number k. In the presence of temperature, the stationary regime of nonuniformly rotating magnetoconvection is studied. The accurate analytical equation for the critical Rayleigh–Darcy number in terms of various non-dimensional parameters is determined using the linear stability theory. The results show that rotation and the axial (vertical) part of the helical magnetic field retard the onset of convection. While the azimuthal part of the helical magnetic field has a destabilizing effect at positive Rossby numbers Rb. The conditions for stabilization and destabilization of stationary convection in a helical magnetic field are determined for metal oxide, metallic, and semiconductor nanofluids.

Performance investigation of graphene oxide-based water/oil nanofluids for high pressure and high temperature solar thermal technologies for sustainable energy systems

The first and second Working Group (WG I and II) contributions to the sixth assessment report of the Intergovernmental Panel on Climate Change (IPCC) have confirmed anthropogenic contribution to global climate change and issued severe lethal warnings against the ramifications of climate change. To achieve the objectives of sustainable development and combatting climate change, both economic progress and emissions control must go together. A clean, renewable, and reliable energy source is the need of the hour to decarbonize the energy sector. Concentrated Solar Power (CSP) technology can efficiently achieve this objective by offering a reliable, continuous power supply without emitting Greenhouse Gases (GHGs). However, an effective and stable Heat Transfer Fluid (HTF) is mandatory to ameliorate the CSP technology. The experimental analysis of Graphene Oxide (GO) nanofluids yielded maximum enhancement in thermal conductivity up to 39.5 %, whereas enhancement in heat capacity was 7.75 %. The zeta potential experiments exhibited values as high as 65 mV for the GO nanofluids. The simulation yielded a reduced Levelized Cost of Energy (LCOE) of up to 12 %, and an energy enhancement of up to 3.1 % was observed. The research lays the foundation for commercial-scale solar thermal technology-based integrated systems to meet the world's energy needs reliably, sustainably, and competitively.

A forced convection of water-aluminum oxide nanofluids in a square cavity containing a circular rotating disk of unit speed with high Reynolds number: A Comsol Multiphysics study

This research article concentrates on forced convection with a high Reynolds number of the water-alumina-based nanofluid in the square cavity containing a rotating disk with a unit speed. A very dense mesh is used to obtain the numerical results with the finite element package of COMSOL Multiphysics 5.6. For the research study, we select the parameters, the Reynolds number (106 to 1.005 × 106), a radius of the rotating disk (0.1m–0.2 m), and volume fraction (0.001–0.009 and 0.01–0.05). About 54 simulations are obtained using the Rayleigh numbers 7 × 106 to 1.54 × 106 and keeping the Prandtl number less than 0.7. The outcomes will be validated with correlations from the local Nusselt number literature and the independent mesh study. The results will be displayed with the surface plots and graphs for temperature, average temperature, local and average Nusselt number, mass flow rate, skin friction coefficient, and average values on the surface of the circular rotating disk. A correlation originated between the temperature as an average on the surface of a rotating cylinder and mass flow rate, which describe a negative association between the mass flow rate and the average temperature on the surface of a circular disk. It was concluded that the coefficient of skin friction improves with an upsurge in volume fraction of the nanofluid, whereas it shows a non-functionality with an average Nusselt number when an increment is made in the radius of a circular disk.

Irreversibility Analysis in the Ethylene Glycol Based Hybrid Nanofluid Flow amongst Expanding/Contracting Walls When Quadratic Thermal Radiation and Arrhenius Activation Energy Are Significant

In this new era of the fluid field, researchers are interested in hybrid nanofluids because of their thermal properties and potential, which are better than those of nanofluids when it comes to increasing the rate at which heat is transferred. Compared to the dynamics of radiative Ethylene Glycol-Zinc Oxide (nanofluid) and Ethylene Glycol-Zinc Oxide-Titanium Dioxide (hybrid nanofluid) flows between two permeable expanding/contracting walls, nothing is known in terms of Lorentz force, heat source, and the activation energy. The thermo-physical characteristics of Ethylene Glycol, Zinc Oxide nanoparticles, and Titanium Dioxide nanoparticles are used in this study to derive the governing equations for the transport of both dynamics. Governing equations are converted as a set of nonlinear ordinary differential equations (with the aid of suitable similarity mutations), and then the MATLAB bvp4c solver is used to solve the equations. This study’s significant findings are that rise in the reaction rate constant increases mass transfer rate, whereas an increase in the activation energy parameter decreases it. The mass transfer rate decreases at a rate of 0.04669 (in the case of hybrid nanofluid) and 0.04721 (in the case of nanofluid) when activation energy (E) takes input in the range 0≤E≤5. It has been noticed that the velocity profiles are greater when the walls are expanding as opposed to when they are contracting. It is detected that the heat transfer rate reduces as the heat source parameter increases. The heat transfer rate drops at a rate of 0.9734 (in the case of hybrid Nanofluid) and 0.97925 (in the case of nanofluid) when the heat source parameter (Q) takes input in the range 0≤Q≤0.3. In addition, it has been observed that the entropy generation increases as the Brinkmann number rises.

Parametric optimization of heat exchanger tube having twisted tape turbulent promoters and silicon oxide nanofluid

Parametric optimization of heat exchanger tube having twisted tape turbulent promoters and silicon oxide nanofluid

Experimental studies of different operating parameters on the photovoltaic thermal system using a flattened geometrical structure.

The efficiency of the photovoltaic (PV) cell reduces with an increase in solar irradiation. The reduction in the efficiency of the photovoltaic (PV) cell can be attributed to the increase in cell temperature. A novel design of a thermal absorber fabricated by a flat spiral tube is used to remove heat and decrease the cell temperature, thus forming the photovoltaic thermal system (PVTS). Water and titanium oxide (TiO2) nanofluid (NF) with a concentration ratio of 0.1% are used as the working fluid in the PVTS. The study has been carried out for the mass flow rates (mf) of 0.05, 0.066, and 0.083kg/s. The reduction in the cell temperature is obtained to be 5.7 and 11.2°C due to the cooling effect of water and TiO2 NF, respectively. The percentage increase in electrical efficiency is 2.93 and 5.28% by cooling using water and TiO2 NF, respectively. The hourly variation of the performance of the PVTS shows that TiO2 NF at 0.083kg/s shows the highest photovoltaic thermal efficiency of 69.2% and thermal and electrical efficiency of 56.45 and 12.75%, respectively. The best coefficient of energy for TiO2 NF is 1.27 for a mf of 0.083kg/s.

Effects of modified graphene oxide (GO) nanofluid on wettability and IFT changes: Experimental study for EOR applications

The application of nanoparticles (NPs) in enhanced oil recovery (EOR) offers a practical approach to resolving some surface-related problems encountered in contemporary technological processes. In this study, graphene oxide nanosheets (GONs) were synthesized by Hummer's method and, then, were subjected to surface modification by hexamethyldisilazane (HMDS) and diazonium sulfonic (DS) compounds. The new combination was known as GO-Su-HMDS. The potential stability of GO-Su-HMDS nanofluids (NFs) was investigated using the zeta ( ζ ) potential test. A comparative study of the effect of the synthesized NFs on wettability alteration of the reservoir rock was performed using interfacial tension (IFT) and contact angle experiments. According to the results of this study, the contact angle decreased from the initial value of 161° (oil wet) to 35° (water wet). In addition, IFT decreased from 18.45 mN/m for deionized (DI) water to 8.8 mN/m for 500 ppm GO-Su-HMDS NF. Moreover, the results of flooding experiments showed that the NPs of a GO-Su-HMDS concentration of 400 and 500 ppm could increase the oil recovery by 20% and 19%, respectively. The experimental results showed that GO-Su-HMDS NFs with a concentration of 500 ppm have the best efficiency in terms of altering the wettability of the rock from oil wet to water wet. Thus, it can be said that this nanofluid can reduce the contact angle and IFT and also increase the sweeping efficiency of oil.

Augmenting the performance of photovoltaic panel by decreasing its temperature using various cooling techniques

The photovoltaic (PV) systems suffer efficiency drop and performance retrogression as their operating temperature increases. This research investigates the routine of polycrystalline silicon PV modules using dissimilar cooling techniques and compares the routine of the PV modules with and without cooling. The available studied PV module output maximum power decreases by up to 0.42% for every one-degree increase in temperature. To investigate the cooling techniques, the experiments were done in July 2021 at the Faculty of Engineering, Ismailia, Egypt (30°35′N 32°16′E). The used cooling methods were; forced air cooling onto the PV module front surface by a direct current fan (case 1); back surface cooling by circulating a coolant in a heat exchanger copper serpentine fixed at the PV module back surface, water (case 2), and copper oxide nanofluid (0.2% mass fraction) (case 3) was used as different coolants in the serpentine; front surface cooling using water as a coolant that flows from small nozzles equally distributed along with the pipe fixes at the PV module frame (case 4). After comparing the recorded results of the four cooling techniques with a conventional system, cooling efficiency, the front PV module surface water cooling technique produced the best results. This technique is easy to be designed, manufactured, and installed. Also, it saves the cost of cleanliness of the surface of the PV module from dirt and dust. These cooling techniques increase the conventional PV system voltage output by 2.7%, 2.43%, 0.9%, and 7.43% and decrease in average temperature by 13.46%, 8.64%, 7.27%, and 29.37%, with an increase in PV energy conversion efficiency by 2.94%, 2.46%, 2.2% and 6.84% via using air cooling, water back cooling, nanofluid back cooling and waterfront cooling respectively.

Magneto-optical studies of kerosene based ferrofluid

Magnetic fluids are technologically important due to their tunable magnetic, electrical and optical properties. The magneto optical properties of ferrofluid have a major role for the development of optoelectronic devices. This paper represents the detailed analysis of kerosene based ferrofluid, their structure and magneto optical properties will be investigated. Iron oxide nanofluids are synthesised by a Co-precipitation method. The X-ray diffraction technique is used for structural characterization. The magneto optical property of the iron oxide nanofluid have been investigated by linear dichroism measurements. Individual magnetic particle’s intrinsic optical anisotropy or shape anisotropy create linear dichroism. The magnetic susceptibility of ferrofluid with different volume fractions is measured using Quincke’s method.

Improving the cooling performance of photovoltaic panels by using two passes circulation of titanium dioxide nanofluid

The major goal of this study is to achieve the cooling effect of a photovoltaic panel by employing titanium dioxide nanofluid as a cooling fluid in two passes circulation to lower the panel surface temperature, improve the performance of the photovoltaic/thermal system, and increase efficiency. Photovoltaic technology is constantly losing efficiency due to the high temperature of the PV panel's upper surface, which results in lower output power and lower overall efficiency. Five photovoltaics panels were utilized in this investigation to compare the three concentrations of Titanium Oxide nanofluid (1 wt%,2 wt%,3 wt%), as well as cooling by water and an uncooled penal. The output powers were (44.5, 44, 43.2, 42.6, and 39.5 W) when the three concentrations of Titanium Oxide nanofluid (3 wt%, 2 wt%, and 1 wt%) were used, then water cooled and uncooled, respectively. Cooling by nanofluid at concentration (3 wt%) had the highest efficiency (19.23%). Depending on the concentrations, there is a variation in temperature between the cooling fluids' output and inlet. For the three concentrations of Titanium Oxide nanofluid (3 wt%, 2 wt%, and 1 wt%), and water, the results were (7.3, 7.8, 8.3, 8.6 °C). When the surface temperatures of the solar panels were compared to the uncooled photovoltaic panels, it was discovered that the cooling system reduced the surface temperatures by 19.0%. All of the results were obtained at 30° tilt angles with fluid rotating in two passes. The high concentration of nanofluids produced the best results, resulting in a benefit of greater heat extraction.

CFD Simulation of Tapered Coil by Using Silicon Dioxide and Zinc Oxide Nanofluid with Water and Ethylene Glycol as Its Base Fluid

Abstract: Helical coils are very essential for various heat exchangers, nuclear reactors and in chemical engineering because of large quantity of heat transfer in a small space with high heat transfer rates and slight residence time dispersals even it suffers through a disadvantage of larger pressure drop. The curvature creates secondary flow arrangement which is perpendicular to main axial stream path. The secondary flow has insignificant capability to improve heat transfer owed to mingling of the fluid. The objective of this work is to compare and increase the pressure drop inside tapered helical coil heat exchanger in copper tube to succeed a better and more quantitative insight into heat transfer process by increasing secondary flow inside the coil and this can allow proper intermixing of the fluid and to maintain desired flow rate inside the helical coil. I work on CFD to analyze the helical coil by using ANSYS 15. Generation of 3D CAD model of aluminium and copper tapered helical tube of diameter (d) 10 mm keeping PCD 50 mm, pitch 20 mm , tapered angle 20 and length of 500 mm by using SOLIDWORKS and exporting to the IGES format and then import in ANSYS fluent 15

Deep neural network prediction of modified stepped double-slope solar still with a cotton wick and cobalt oxide nanofluid

This research work intends to enhance the stepped double-slope solar still performance through an experimental assessment of combining linen wicks and cobalt oxide nanoparticles to the stepped double-slope solar still to improve the water evaporation and water production. The results illustrated that the cotton wicks and cobalt oxide (Co3O4) nanofluid with 1wt% increased the hourly freshwater output (HP) and instantaneous thermal efficiency (ITE). On the other hand, this study compares four machine learning methods to create a prediction model of tubular solar still performance. The methods developed and compared are support vector regressor (SVR), decision tree regressor, neural network, and deep neural network based on experimental data. This problem is a multi-output prediction problem which is HP and ITE. The prediction performance for the SVR was the lowest, with 70 (ml/m2 h) mean absolute error (MAE) for HP and 4.5% for ITE. Decision tree regressor has a better prediction for HP with 33 (ml/m2 h) MAE and almost the same MAE for ITE. Neural network has a better prediction for HP with 28 (ml/m2 h) MAE and a bit worse prediction for ITE with 5.7%. The best model used the deep neural network with 1.94 (ml/m2 h) MAE for HP and 0.67% MAE for ITE.

Novel usage of the curved rectangular fin on the heat transfer of a double-pipe heat exchanger with a nanofluid

The convection heat transfer in a countercurrent double-tube heat exchanger with various fins in a turbulent flow is investigated. The suitable heating or cooling process of fluids is the effective use of the double-pipe heat exchanger. We use water-aluminum oxide nanofluid and water-titanium dioxide at four concentrations (0.4%, 2%, 4%, 6%) as the cold fluid in the inner tube and water as the hot fluid in the annular space. The single-phase model for nanofluid modeling and the standard k-ε model with scalable wall function for simulating the turbulent flow is utilized. To better examine this novel geometry, its performance is compared with simple and rectangular-finned geometries. The results show that the water aluminum oxide nanofluid has a better convection heat transfer coefficient than water titanium dioxide and pure water. Raising the nanofluid concentration from 0.4% to 6% increases the convection heat transfer coefficient by 12%. Heat exchangers with a rectangular and curved fin have 81% and 85% better efficiency than the heat exchanger without a fin. The novel geometry causes a smaller pressure drop despite its higher convection heat transfer coefficient. Also, it is shown that with raising the Reynolds number and nanofluid concentration, the pressure drop increases.

Hydromagnetic CuO-H2O nanofluid transportation through irreversibility analysis

The current investigation aimed for the exploration of steady-state, incompressible flow and energy transportation of water-based copper oxide nanofluid past a linear stretching sheet through suction/injection possessions. Furthermore, the impact of magnetohydrodynamic, radiation, and entropy generation are taken in the problem development. The nonlinear equations are reframed into single independent variable equations by the implication of appropriate similarity transformations. The Fehlberg scheme is developed for the numerical computations of re-structured non-linear expressions. The variations of influential constraints on the dimensionless physical quantities are investigated and reported in detail. The prominent features of the investigation include the higher velocity and weaker temperature is achieved against the incrementing stretching constraint values. The irreversibility ratio is reduced against the emerging stretching strength constraint. The Bejan number is decaying against the higher magnetic constraint. The blowing and suction have opposite impacts on the skin-friction factors.

Numerical investigation of heat transfer in helical tubes modified with aluminum oxide nanofluid and modeling of data obtained by artificial neural network

The purpose of this study is to investigate the computational fluid dynamics to find the effects of Reynolds number, different volume fractions of aluminum oxide nanofluid and different heat fluxes in heat transfer performance (Nusselt number) in a helical tube. This simulation was investigated at Reynolds number range 2000 and 10,000 and volumetric fraction range 1% and 4% of aluminum oxide nanofluid and constant heat fluxes of 4000–6000 W/m2. The single-phase model was used to model the nanofluid and the feasible k-ε model was used to simulate the turbulent flow. Then, perceptron artificial neural networks with the Levenberg–Marquardt algorithm were used to predict the Nusselt number such that input parameters include Reynolds number, nanoparticle volume fraction and output or target was considered Nusselt number for the network. The results show that with increasing the volume fraction of aluminum oxide nanofluid and Reynolds number, the Nusselt number increases by about 20.35%. Also, by increasing the constant heat flux from 4000–6000 W/m2, the Nusselt number increases by 18.75%. The results of the artificial neural network show that the topology 2-10-1 is very successful in predicting the Nusselt number so that the minimum mean squared error for the data allocated to the training and validation sections were 0.024449627 and 0.117025052, respectively, which are obtained under optimal epochs 19 and 9. The value of the correlation coefficient obtained in predicting the Nusselt number is 0.944416302.

Photo-thermal characteristics of water-based graphene oxide (GO) nanofluids at reverse-irradiation conditions with different irradiation angles for high-efficiency solar thermal energy harvesting

In this paper, the optical absorption properties and photo-thermal conversion characteristics of GO-water nanofluids were experimentally studied and compared. With the increase of GO mass fraction or the decrease of GO sheet size, the optical absorption capacity of nanofluids can be enhanced, and a thin layer of nanofluid can absorb most of the solar irradiation. As for a direct absorption solar collector (DASC), the temperature rise increased with the irradiation angle at the reverse-irradiation mode because of the natural convection induced temperature uniformity improvement. There existed optimal GO concentrations with respect to the maximum temperature rises of GO nanofluids, and the optimal value is GO sheet size dependent. For GO sheet sizes of 50–200 nm, 200–500 nm and >500 nm, the optimal mass fractions are 150, 180 and 220 ppm, respectively, and the corresponding temperature rises were increased by 9.2 °C (28.2%), 7.9 °C (24.1%), and 6.9 °C (21.0%) as compared with that of water at the reverse irradiation angle of 45°. A 3D numerical simulation was performed to understand the irradiation angle induced natural convection contribution to the photo-thermal conversion performance, and an agreement was achieved with the experiment.

Evaluation of energy efficiency, visualized energy, and production of environmental pollutants of a solar flat plate collector containing hybrid nanofluid

Energy efficiency, visualized energy, and production of environmental pollutants of a solar flat plate collector containing water/copper–aluminum hybrid nanofluid are evaluated. The results are compared with water/aluminum oxide nanofluid and water. The Reynolds number (Re) for the investigation is between 700 and 2300, and the nanoparticles volume fraction is 0.1%. A developed model in the engineering equations solver is used to solve the governing equations. The outputs show that the most suitable collector operating fluid is the hybrid nanofluid. Collector energy efficiency employing hybrid nanofluid is more than other operating fluids, and its maximum increment applying mono and hybrid nanofluids relative to water is 3.86 and 4.23 %, respectively. The criterion evaluation performance of the collector in the presence of hybrid nanofluid is larger than mono-nanofluid of aluminum oxide–water. Environmental analysis of the collector shows that the productions of sulfur oxides, carbon dioxide, and nitrogen oxides in a solar flat plate collector are maximum and minimum for water and hybrid nanofluid, respectively. In the case of hybrid nanofluid, the rate of production reduction of carbon dioxide, sulfur oxides and nitrogen oxides are respectively 29.15 kg, 0.0149 kg and 0.0255 kg compared to water. However, these amounts are 26.64 kg, 0.0136 kg and 0.0233 kg for mono nanofluids, respectively.

Numerical analysis and two-phase modeling of water Graphene Oxide nanofluid flow in the riser condensing tubes of the solar collector heat exchanger

Graphene Oxide is one of the carbon-based-materials that has wide application range such as Water purification, Flexible rechargeable battery electrode, Solar Collectors, and Energy conversion. In this research, initially, Graphene Oxide nanoparticles were dispersed in water to make a nanofluid. The nanofluid was prepared at 0.10, 0.15, 0.20, 0.25, 0.35, and 0.45% mass fractions. After that, heat transfer and viscosity (at 10 and 100 Revolutions per minute (RPM)) of the prepared samples were calculated at 25, 30, 35, 40, 45, and 50 °C temperatures. In the Flat Plate Solar Collector (FPSC) - Riser tube, from the start point to the end of tube, the temperature decreases and thus the heat transfer and viscosity change. As the calculated range does not contain all the temperatures and mass fractions, and to lower the experimental costs, thus, Fuzzy system and Artificial Neural Network models were used to predict the whole range of data. After that, the trained models were compared to detect the error and to choose the best model with the least error. Results confirmed that Fuzzy system has lower error. This means that Fuzzy system predicts the input-target dataset as definite as obtainable.