CFD-based Simulation Research Articles

Design and performance evaluation of toroidal TLCDs in bidirectional seismic control of structures using a modified dynamic model

In this study, a modified dynamic model which distinguishes between liquid oscillation and sloshing in vertical columns is derived for toroidal tuned liquid column dampers (TLCDs). In the modified model of toroidal TLCDs, the primary sloshing mode within vertical columns is modeled as mass–spring-dashpot systems, whereas the oscillatory behavior of the liquid is analyzed employing the conventional theory of TLCDs. The accuracy of the modified dynamic model in capturing bidirectional liquid responses is verified by computational fluid dynamics (CFD)-based simulations. A large number of CFD-based simulations are performed to establish a ready-to-use suggested formula for a newly introduced parameter (which is related to the geometric configuration of liquid containers and the initial liquid depth) in the modified model. Subsequently, considering the maximum allowable liquid displacement in vertical columns, an optimized design approach for toroidal TLCDs installed in symmetric and asymmetric structures is illustrated. On the basis of the proposed optimization design method, the bidirectional vibration control effects of toroidal TLCDs are comprehensively analyzed under El Centro, Loma Prieta, Northridge, and Chi–Chi seismic excitations in both the time and frequency domains. The results demonstrate the effectiveness of toroidal TLCDs for bidirectional seismic control of structures.

A combined CFD-based simulation and experimental study of particle dispersion in a high-concentration airtight space under unorganized airflow

It is significant to obtain the particle distribution data for workpiece processing and industrial protection strategies. To simulate the particle dispersion in a high-concentration airtight space under unorganized airflow, a CFD-based simulation and experimental were utilized in this study. The proposed method works in three steps. The first step is to use Stokes-MRF-Fan-CFD model to simplify the distribution of high-concentration particles calculation to the dispersion state of the gas components. The second step is to compute the airflow patterns and dispersion of particles. The third step is to prove the feasibility of Stokes-MRF-Fan-CFD model. The results of this model in particle dispersion show ±200 mg·m−3 of absolute error, ±20% of relative error, and 88.5747 grade of simulation accuracy. And the results of particle concentration distribution can be mutually confirmed with the streamline and velocity vector distribution in the airtight space, providing a promising and innovative model for the particle dispersion in a high-concentration airtight space under unorganized airflow.

Toward Data Center Digital Twins via Knowledge-based Model Calibration and Reduction

Computational fluid dynamics (CFD) models have been widely used for prototyping data centers. Evolving them into high-fidelity and real-time digital twins is desirable for the online operations of data centers. However, CFD models often have unsatisfactory accuracy and high computation overhead. Manually calibrating the CFD model parameters is tedious and labor-intensive. Existing automatic calibration approaches apply heuristics to search the model configurations. However, each search step requires a long-lasting process of repeatedly solving the CFD model, rendering them impractical, especially for complex CFD models. This article presents Kalibre , a knowledge-based neural surrogate approach that calibrates a CFD model by iterating four steps of (i) training a neural surrogate model, (ii) finding the optimal parameters through neural surrogate retraining, (iii) configuring the found parameters back to the CFD model, and (iv) validating the CFD model using sensor-measured data. Thus, the parameter search is offloaded to the lightweight neural surrogate. To speed up Kalibre’s convergence, we incorporate prior knowledge in training data initialization and surrogate architecture design. With about ten hours of computation on a 64-core processor, Kalibre achieves mean absolute errors (MAEs) of 0.57°C and 0.88°C in calibrating the CFD models of two production data halls hosting thousands of servers. To accelerate CFD-based simulation, we further propose Kalibreduce that incorporates the energy balance principle to reduce the order of the calibrated CFD model. Evaluation shows the model reduction only introduces 0.1°C to 0.27°C extra errors while accelerating the CFD-based simulations by thousand times.

CFD-Based Simulation Analysis for Motions through Multiphase Environments.

The motion process and force of the jumper crossing a multiphase environment are of great significance to the research of small amphibious robots. Here, CFD (Computational Fluid Dynamics)-based simulation analysis for motions through multiphase environments (water-air multiphase) is successfully realized by UDF (user-defined function). The analytical model is first established to investigate the jumping response of the jumpers with respect to the jump angle, force, and water depth. The numerical model of the jumper and its surrounding fluid domain is conducted to obtain various dynamic parameters in the jumping process, such as jumping height and speed. Satisfactory agreements are obtained by comparing the error of repeated simulation results (5%). Meanwhile, the influence of the jumper's own attributes, including mass and structural size, on the jumping performance is analyzed. The flow field information, such as wall shear and velocity when the jumper approaches and breaks through the water surface, is finally extracted, which lays a foundation for the structural design and dynamic underwater analysis of the amphibious robot.

CFD-based simulation study of dust transport law and air age in tunnel under different ventilation methods.

To solve the problem of high-concentration dust pollution in a bored tunnel, we conducted a simulation study on the dust transport law and air age of the wind flow in a bored tunnel under different ventilation methods. Air age was innovatively introduced as an index for evaluating tunnel air quality. The results show that dust pollution is serious under conditions of press-in ventilation, which is unfavorable to personnel operations. Following the installation of an on-board dust-removal fan, an effective dust-control air curtain forms in the tunnel, and the high-concentration dust is essentially controlled within the range of Z = 13m from the working face. The dust concentration in the working area on the left side of the tunnel is CD < 200mg/m3, and the dust-control effect is obvious. At the same time, the air age on both sides of the tunnel is reduced by 35.5% following the use of the on-board dust-removal fan. Taking into account dust control by ventilation and dust removal by fan, spraying dust reduction measures are added, and we developed automated wind-mist synergistic wet high-frequency oscillation dust-capturing technology for tunnel boring. This could effectively improve the problem of high levels of coal dust pollution in tunnels.

Parametric Reduced-Order Modeling of Battery Thermal Management Systems for Varying Rates of Cooling Liquid Flow

The thermal management system in battery packs for electrical/hybrid electric vehicles plays an important role in maintaining good performance and health of battery cells. In order to optimize the thermal management system design, computational fluid dynamics (CFD) simulations are often used. The CFD is a powerful tool that can accurately simulate the thermal behavior of the system using numerical computation techniques such as finite volume method. However, the days-long computational expense means that the CFD-based simulations are still unsuitable for situations when rapid results are required, for example for online predictive control or fast-pace optimization design.A new method of reduced-order modeling of battery thermal management systems (BTMS) was presented in [1]. Given a CFD model, the algorithm based on projection on Krylov-subspace yields a reduced-order model (ROM). The ROM accurately predicts the system’s transient response to arbitrary internal heating of individual batteries and temperature of cooling liquid at inlet. Unlike conventional Krylov-subspace approaches, the algorithm does not require the system matrix of the CFD model. Therefore, the method is more suitable for use with commercial CFD software which does not allow access to such internal information. The ROM uses a drastically reduced number of degrees of freedom requiring drastically reduced simulation time.This paper extends our ROM by including the mass flow rate of cooling liquid as a model parameter. The task is accomplished by interpolating the system matrices after several local reduced-order models are constructed at discrete mass flow rates (MFR). In order to interpolate the local ROMs, we first need to transform the local ROMs onto a common subspace. The transformation matrix is obtained by applying the singular value decomposition (SVD) to the local projection matrices. In this paper, three local ROMs are built at 3 different MFRs. After these local ROMs are transformed according to the above procedure, a parametric reduced-order model (pROM) is constructed via quadratic interpolation.The constructed pROM is tested against the new MFRs different from those used for building the local ROMs. For each new MFR, the pROM produced a transient response that is almost indistinguishable from that of the CFD model (e.g., see Figure 1). The several thousand core-hour computational time needed for CFD simulations is replaced by a few tens of seconds using the pROM on a personal computer. The low computing load of the pROM is deemed adequate for on-board applications. Reference [1] Xiang L, Lee CW, Zikanov O, Hsu C-C. Efficient reduced order model for heat transfer in a battery pack of an electric vehicle. Applied Thermal Engineering. 2022; 201:117641.Figure 1 Figure 1

A Lattice-Boltzmann-based modelling chain for traffic-related atmospheric pollutant dispersion at the local urban scale

Urban traffic-related air pollution is a major source of environmental and health damage and is difficult to quantify due to its inherent physical complexity. We construct a CFD-based simulation framework coupling an efficient numerical method for turbulent fluid flows with a microscopic traffic model and an emissions model to simulate road transport pollutant dispersion at the urban microscale. We improve the open-source Lattice-Boltzmann based CFD software OpenLB to overcome its original stability deficiencies for high Reynolds number flows. A stable recursive regularization procedure with a double distribution function approach is proposed to solve an advection diffusion equation for passive scalar transport at high Reynolds number. The code is successfully validated on three reference cases of increasing complexity and the traffic model SUMO along with a physical engine emissions model are coupled with OpenLB to simulate traffic-induced pollution from a road network in a realistic complex geometry. Transient flow features are analysed and the time-averaged concentration levels in different neighbourhoods of the considered geometry are evaluated: high concentration levels are observed close to the streets but also inside specific building infrastructures due to complex wind dynamics. Analyses of altitudinal concentration variations show that flow recirculations located close to traffic lights can drive pollutant over the buildings and increase concentration levels inside inner courtyards. Time-averaged concentration maps are constructed using both spatially uniform and non-uniform line sources and it is shown that using uniform sources leads to up to 20% local concentration overestimations inside the urban canopy.

On the nonlinear relationship between wall shear stress topology and multi-directionality in coronary atherosclerosis

Background and ObjectiveIn this paper we investigate twelve multi-directional/topological wall shear stress (WSS) derived metrics and their relationships with the formation of coronary plaques in both computational fluid dynamics (CFD) and dynamic fluid-structure interaction (FSI) frameworks. While low WSS is one of the most established biomechanical markers associated with coronary atherosclerosis progression, alone it is limited. Multi-directional and topological WSS derived metrics have been shown to be important in atherosclerosis related mechanotransduction and near-wall transport processes. However, the relationships between these twelve WSS metrics and the influence of both FSI simulations and coronary dynamics is understudied. MethodsWe first investigate the relationships between these twelve WSS derived metrics, stenosis percentage and lesion length through a parametric, transient CFD study. Secondly, we extend the parametric study to FSI, both with and without the addition of coronary dynamics, and assess their correlations. Finally, we present the case of a patient who underwent invasive coronary angiography and optical coherence tomography imaging at two time points 18 months apart. Associations between each of the twelve WSS derived metrics in CFD, static FSI and dynamic FSI simulations were assessed against areas of positive/negative vessel remodelling, and changes in plaque morphology. Results22–32% stenosis was the threshold beyond which adverse multi-directional/topological WSS results. Each metric produced a different relationship with changing stenoses and lesion length. Transient haemodynamics was impacted by coronary dynamics, with the topological shear variation index suppressed by up to 94%. These changes appear more critical at smaller stenosis levels, suggesting coronary dynamics could play a role in the earlier stages of atherosclerosis development. In the patient case, both dynamics and FSI vs CFD changes altered associations with measured changes in plaque morphology. An appendix of the linear fits between the various FSI- and CFD-based simulations is provided to assist in scaling CFD-based results to resemble the compliant walled characteristics of FSI more accurately. ConclusionsThese results highlight the potential for coronary dynamics to alter multi-directional/topological WSS metrics which could impact associations with changes in coronary atherosclerosis over time. These results warrant further investigation in a wider range of morphological settings and longitudinal cohort studies in the future.

Computational fluid dynamics comparison of prevalent liquid absorbents for the separation of SO2 acidic pollutant inside a membrane contactor

In recent years, the emission of detrimental acidic pollutants to the atmosphere has raised the concerns of scientists. Sulphur dioxide (SO2) is a harmful greenhouse gas, which its abnormal release to the atmosphere may cause far-ranging environmental and health effects like acid rain and respiratory problems. Therefore, finding promising techniques to alleviate the emission of this greenhouse gas may be of great urgency towards environmental protection. This paper aims to evaluate the potential of three novel absorbents (seawater (H2O), dimethyl aniline (DMA) and sodium hydroxide (NaOH) to separate SO2 acidic pollutant from SO2/air gaseous stream inside the hollow fiber membrane contactor (HFMC). To reach this goal, a CFD-based simulation was developed to predict the results. Also, a mathematical model was applied to theoretically evaluate the transport equations in different compartments of contactor. Comparison of the results has implied seawater is the most efficient liquid absorbent for separating SO2. After seawater, NaOH and DMA are placed at the second and third rank (99.36% separation using seawater > 62% separation using NaOH > 55% separation using DMA). Additionally, the influence of operational parameters (i.e., gas and liquid flow rates) and also membrane/module parameters (i.e., length of membrane module, hollow fibers’ number and porosity) on the SO2 separation percentage is investigated as another highlight of this paper.

Convolutional Neural Network Predictions for Unsteady Reynolds-Averaged Navier–Stokes-Based Numerical Simulations

The application of computational fluid dynamics (CFD) to turbulent flow has been a considerable topic of research for many years. Nonetheless, using CFD tools results in a large computational cost, which implies that, for some applications, CFD may be unviable. To date, several authors have carried out research applying deep learning (DL) techniques to CFD-based simulations. One of the main applications of DL with CFD is in the use of convolutional neural networks (CNNs) to predict which samples will have the desired magnitude. In this study, a CNN which predicts the streamwise and vertical velocities and the pressure fields downstream of a circular cylinder for a series of time instants is presented. The CNN was trained using a signed distance function (SDF), a flow region channel (FRC) and the t-1 sample as inputs, and the ground-truth CFD data as the output. The results showed that the CNN was able to predict multiple time instants with low error rates for turbulent flows with variable input velocities to the domain.

Precise thermo-fluid dynamics analysis of corrugated wall distribution transformer cooled with mineral oil-based nanofluids: Experimental verification

Corrugated wall distribution transformers (CWDTs) are one of the momentous and expensive equipment for power systems, and their failure has a negative impact on the security of the grid. The continuous operation of the transformer strongly depends on its insulation status and then on the hotspot temperature (HST). In this paper, a comprehensive and precise 3D computational fluid dynamic (CFD) based modeling is proposed for HST prediction. In this modeling, the conservator, which has a remarkable impact on the HST, is thoroughly modeled. Optical fiber sensors (OFSs) in the studied 500 kVA CWDT are employed to validate the precision of the proposed HST prediction method via a 3D CFD-based modeling during the temperature rise test (TRT). The experimental results indicate that the proposed 3D CFD-based model for HST prediction is very precise and there is suitable proximity with the practical values. The error percentage of the proposed 3D CFD-based model is 0.76 % (0.7 °C) compared to the OFSs results, which indicates the accuracy and efficiency of the proposed modeling. Also, a thermal camera is employed to verify the results of 3D CFD-based modeling in top-oil temperature (TOT), bottom-oil temperature (BOT) and conservator oil temperature (COT) during the TRT. According to the obtained results, temperatures of 3D CFD-based simulation and thermal camera in the aforementioned three points are in good agreement with each other. In this case, the error percentage is less than 2.7 %, which indicates the precision and proficiency of the proposed 3D modeling. Finally, the utilization effect of multi-walled carbon nanotubes (MWCNTs) and diamond nanoparticles on CWDT' HST reduction and loading capacity increment (LCI) has been studied and verified via the proposed 3D CFD-based modeling. The results show that the lowest effect is for MWCNT with 0.005 % concentration, where HST reduction and LCI are 3.3 °C and 5.6 %, respectively, and the highest effect is for diamond nanoparticle with 0.01 % concentration, where HST reduction and LCI are 5.1 °C and 7.8 %, respectively.

CFD-based simulation of heat transfer in a rectangular channel

Heat transfer is an important phenomenon in the industrial sector. Thus, the simulation is made to compute the distribution of heat in a rectangular channel in this paper. A heated rod is inserted at the center of the rectangular channel. The fluid flowing in the rectangular channel is considered to be a viscous fluid. Navier–Stokes equations of motion for laminar flow are used. The medium for the fluid motion is considered to be a porous medium. Heat transfer is computed for nonlinear two-dimensional incompressible and unsteady flows. The Fourier’s law of heat conduction is used for the transmission of heat in the rectangular channel. The Finite Element Method (FEM) is applied to the solution of the problem. For different values of the permeability parameter, Prandtl number and Rayleigh number, the graphic solution for the velocity and temperature fields is shown.

Detailed numerical investigation of the CO[formula omitted] two-phase ejector 3-D CFD model based on the flow visualisation experiments

3-D CFD-based simulations of CO2 flow inside two-phase ejectors are commonly used with various turbulence models. However, none of the previously published studies examined the influence of a local turbulence phenomenon on the simulation results. Therefore, in this study, a detailed numerical analysis of CO2 local flow behaviour was compared to experimental flow visualisation data as well as to turbulence approach validation. Furthermore, the kinetic behaviour of mixed streams in the boundary layer was examined under transcritical operating conditions for motive nozzle pressures above 80.0 bar. The mixing process mapped by different turbulence models showed differences in recapturing the angle of suction flow in the mixing chamber. Furthermore, the different flow shapes of the simulated motive expanded flow were observed. The best prediction of the mixed two-phase flows was obtained using the Reynolds stress model with linear pressure-strain approach with the suction mass flow rate discrepancy of 2%. The higher pressure lift caused the suction flow to be more perpendicular towards the motive flow, elongating the suction flow course in the mixing chamber and intensifying the mixing process. A further increase in the pressure lift eventually leads to the possible occurrence of suction reverse flow.

Solitary Wave Interaction with a Floating Pontoon Based on Boussinesq Model and CFD-Based Simulations

A mathematical model of solitary wave interaction with a pontoon-type rigid floating structure over a flat bottom is formulated based on Boussinesq-type equations under weakly nonlinear dispersive waves. Based on the higher-order Boussinesq equations, the solitary wave equation is derived, and a semi-analytical solution is obtained using the perturbation technique. On the other hand, brief descriptions of the application of wave2Foam and OceanWave3D on the aforementioned problem are presented. The analytical solitary wave profiles in the outer region are compared with Computational Fluid Dynamics (CFD) and OceanWave 3D model simulations in different cases. The comparison shows a good level of agreement between analytical, wave2Foam, and OceanWave3D. In addition, based on the wave2Foam and coupled OceanWave3D model, the horizontal, vertical wave forces, and the pressure distributions around the pontoon are analysed. Further, the effect of the Ursell number, pontoon length, and water depth on the solitary wave profiles are analysed based on the analytical solution. The paper validates each of the three models and performs intercomparison among them to assess their fidelity and computational burden.

Erosion under turbulent flow: a CFD-based simulation of near-wall turbulent impacts with experimental validation

Engineering systems operating under particle-laden turbulent flow regimes, such as slurry pumps, are prone to erosive wear, where the specific conditions of particle impingement are crucial for determining the wear rate of the eroding surface and thus its relevance for the mechanical or hydraulic system. However, the near-wall interactions under turbulent flows impose a challenge for the formulation and validation of experimental and numerical models that describe the particle’s trajectories close to the surface. This work analyzes the statistics of particle impacts obtained from a Large-Eddy Simulation (LES) with the Wall-Adapting Local Eddy-Viscosity (WALE) model of the flow and its consistency with experimental data on the statistical distributions of particle impact angle and impact direction determined in a slurry pot configuration. The resulting distributions of impact angle, impact direction, and particle velocity derived from the implemented CFD formulation produced characteristic values similar to those derived from experimental data. The LES-WALE approach used in this work offers shorter computational times and is shown valid by comparative analysis with direct simulation. The model’s applicability and prospective dynamic simulation of practical engineering cases are discussed.

Numerical prediction of cavitation phenomena on marine vessel: Effect of the water environment profile on the propulsion performance

Abstract Energy-saving and emission reduction are crucial since shipping activity due to the global maritime trade has increased exponentially. Several agreements have been engaged to optimize ship energy efficiency composed of ship design and shipping operation planning. However, most up-to-date studies focused on speed and route optimization. The interaction analysis between speed and route efficiency below varied environmental conditions is limited. To attain energy and cost efficiency, a study of cavitation on the propeller that considers the ocean environmental condition will be discussed in this work. Although researchers have previously observed cavitation phenomena, the predictability of simulations is not yet such that problems can be eliminated. Since the multiphase flow of water and vapor is sensitive to environmental conditions, it leads to varying observation accuracy. Thus, the current paper proposes a new performance indicator of the ship propeller under cavitation predicted by computational fluid dynamics (CFD). CFD-based simulation to observe the propeller cavitation was used to model the Zwart cavitation and Kunz cavitation models under two turbulence models of K−ε at different flow conditions and operating environments. Initial validation tests between experimental and numerical simulation show good agreement with a mean error of 4.7% in the Zwart model and 3.7% in the Kunz model, where the k−ε turbulence model provides an almost higher relative error. It is revealed from the result that the increase in temperature causes the rise in the cavitation problem. It is revealed from the result that the increase of temperature causes the increase in cavitation problem.

Comparative Study of Lifting Surface and CFD Methods in the Simulation of Morphing Process of Folding Wing

A folding wing aircraft can autonomously change its configuration in flight to respond to different flying environments. Hinge moment during morphing process is an important basis for driving mechanism design and structural strength check, and its calculation depends on the simulation of the morphing process. Existing studies mostly use the simplified lifting surface method for aerodynamic modeling. In this paper, the CFD-based simulation method is studied, and the results are compared with those by the lifting surface method. First, the unsteady aerodynamic modeling method of the folding wing based on the CFD method is studied, an effective description method is given to define the wall mesh motion caused by wing folding and aileron deflection, and an unfolding–refolding strategy is proposed to improve the quality of the internal mesh in the case of large folding angles. Then, the CFD aerodynamic model is coupled through a developed coupling calculation program with the flexible multibody structure model for the simulation of a flight-morphing process. The comparison with the results of the lifting surface method shows that hinge moments obtained according to the two aerodynamic models are markedly different. Analysis of the difference shows that airfoil thickness considerably affects aerodynamic loading distributions and hinge moments of folding wing aircraft. The lifting surface method ignores airfoil thickness, which will cause large simulation errors in hinge moments.

Development of a CFD-based simulation model and optimization of thermal diffusion column: application on noble gas separation

Abstract In this study, numerical simulations were carried out to investigate the separation of the helium-argon gas mixture by thermal diffusion column. This research determined the significant parameters and their effects on the process performance. Effects of feed flow rate, cut ratio, and hot wire temperature in a 950 mm height column with an inner tube of 9.5 mm radius were examined through the simulation of the thermal diffusion column. For minimizing the number of simulations and obtaining the optimum operating conditions, response surface methodology (RSM) was used. Analysis of separative work unit (SWU) values as a target function for helium-argon separation clearly showed that the maximum amount of SWU in thermal diffusion column was achieved, when hot wire temperature increased as large as technically possible, and the feed rate and cut ratio were equal to 55 Standard Cubic Centimeters per Minute (SCCM) and 0.44, respectively. Finally, the SWU value in optimum conditions was compared with the experimental data. Results illustrated that the experimental data were in good agreement with simulation data with an accuracy of about 90%.

Use of Organic and Copper-Based Nanoparticles on the Turbulator Installment in a Shell Tube Heat Exchanger: A CFD-Based Simulation Approach by Using Nanofluids

Heat exchangers with unique specifications are administered in the food industry, which has expanded its sphere of influence even to the automotive industry due to this feature. It has been used for convenient maintenance and much easier cleaning. In this study, two different nanomaterials, such as Cu-based nanoparticles and an organic nanoparticle of Chloro-difluoromethane (R22), were used as nanofluids to enhance the efficiency of heat transfer in a turbulator. It is simulated by computational fluid dynamics software (Ansys-Fluent) to evaluate the Nusselt number versus Reynolds number for different variables. These variables are diameter ratio, torsion pitch ratio, and two different nanofluids through the shell tube heat exchanger. It is evident that for higher diameter ratios, the Nusselt number has been increased significantly in higher Reynolds numbers as the heat transfer has been increased in turbulators. For organic fluids (R22), the Nusselt number has been increased significantly in higher Reynolds numbers as the heat transfer has been increased in turbulators due to the proximity of heat transfer charges. At higher torsion pitch ratios, the Nusselt number has been increased significantly in the higher Reynolds number as the heat transfer has been increased in turbulators, especially in higher velocities and pipe turbulence torsions.

Correlating the weld-bead's ‘macro-, micro-features’ with the weld-pool's ‘fluid flow’ for electron beam welded SS 201 plates

The phenomenological modeling, a CFD-based simulation tool, was implemented to study the nature and magnitude of fluid flow within the weld zone (WZ) at varying heat input conditions, and further, analyzed its effect on the macroscopic (bead geometry and spiking) and the microscopic (hardness and ferrite arm spacing) features of the WZ during electron beam welding of SS201 plates. Upon calculation of the fluid flow parameters, the mean flow velocity ‘Vm’, Reynolds number, Peclet number, and Grashof number of the molten fluid in the weld-pool were observed to increase by around 3 times with the increase in heat input. The fluid convection was found to be a dominant factor in determining the mode of heat transfer. The weld-bead geometrical features, namely depth and width, were determined by the fluid flow velocities ‘(Vf)depth or width’ along the respective axes. The micro-hardness (MH) and secondary ferrite arm spacing (SFAS) were observed to have an inverse relationship. The increment in SFAS by approximately 1.3 times, due to the (a) decrease in the weld zone cooling rate by around 2.5 times and (b) increase in the coarsening coefficient by approximately 2 times because of Cr diffusion at the higher mean flow velocity ‘Vm’, was observed. Upon microstructural investigation, it was found that the slower cooling rate through the transformation temperature zones favored the formation of vermicular δ-ferrite in the austenite ‘γ’ phase matrix in the WZ, and thus, MH of base metal was observed to be more than that of the weld zone. The spiking amplitude was observed to be influenced by the gap generated between the capillary tip and the weld-pool bottom, and the velocity of approach ‘Va’ of the molten fluid, and the same was found to increase by around 2.5 times with the increase in the melting efficiency by approximately 1.4 times.