Structure Optimization of Semi-Solid Die Cast Steering Knuckle and its Experiment Verification

Steering knuckles are vital functional and structural components in automotive suspension systems, requiring high strength, high ductility, and complex shapes. In this study, an aluminum alloy knuckle with the semi-solid die casting process was developed to replace the conventional steel components. This research aims to optimize product design based on both structural simulation and casting process simulation to avoid defects and to meet mechanical requirements. Furthermore, the optimal design solutions need to be verified through the filling experiments and defect analysis. The results show that the removal of support rib located in the thick area of the shock absorber mounting arm is helpful to avoid the rewelding defects in the filling frontier of the SSM melt. Besides, the position of the steering rod is of medium thickness, and two ribs from different directions come together to support that area. Rewelding defects were detected when two ribs come together. To avoid rewelding defects in local areas of steering rod position, the ribs were reduced to uniform wall thickness. Thus, the local flow state was modified and the SSM melt was reinforced shear action. Ultimately, by controlling all the processes of the SSM die casting process, the high performance of aluminum knuckle was successfully developed.

Effect of Bottom Blowing Mode on Fluid Flow and Mixing Behavior in Converter

Bottom blowing agitation plays a crucial role in improving the reaction kinetics condition of molten bath during the steelmaking process. Herein, the influence of bottom blowing mode on the flow and mixing characteristics of molten bath and the abrasion characteristics of refractory lining in a 6:1 scaled-down model of a 100 t converter were investigated using physical and numerical simulations together. Eight bottom blowing modes were designed (uniform, three-point linear co-direction, three-point linear unco-direction, two-point linear, circumferential linear, A-type, V-type, and triangle alternating). The results indicated that bottom blowing mode has a significant effect on the local flow field at the inner ring of bottom tuyeres, the velocity interval distribution, and the turbulent kinetic energy, which in turn determines the tracer diffusion path and rate as well the mixing time of molten bath. Reasonable non-uniform bottom blowing modes promote the interaction between the various stirring sub-zones of the molten bath. Among them, the three-point linear co-direction mode and A-type mode have the highest mixing efficiency under the conditions of bottom blowing and combined blowing, respectively, which is superior to the uniform mode. In addition, the bottom blowing mode changed the location and degree of abrasion of the refractory lining, and the total abrasion of the non-uniform mode was reduced. The average value and fluctuation degree of integral wall shear stress for the A-type mode were minimal.

Influences of hydraulic boundary conditions on the deep fluid flow in a 3D regional model (central Upper Rhine Graben)

Knowledge of groundwater flow is of high relevance for groundwater management or the planning of different subsurface utilizations such as deep geothermal facilities. While numerical models can help to understand the hydrodynamics of the targeted reservoir, their predictive capabilities are limited by the assumptions made in their setup. Among others, the choice of appropriate hydraulic boundary conditions, adopted to represent the regional to local flow dynamics in the simulation run, is of crucial importance for the final modelling result. In this work, we systematically address this problematic in the area of the central part of the Upper Rhine Graben. We quantify how and to which degree different upper boundary conditions and vertical cross-boundary fluid movement influence the calculated deep fluid flow conditions in the area under study. Robust results, which are insensitive to the choice of boundary condition, are: (i) a regional groundwater flow component descending from the graben shoulders to rise at its centre and (ii) the presence of heterogeneous hydraulic potentials at the rift shoulders. Contrarily, results affected by the chosen boundary conditions are: (i) calculated flow velocities, (ii) the absolute position of the upflow axis, and (iii) the evolving local flow dynamics. If, in general, the investigated area is part of a supra-regional flow system—like the central Upper Rhine Graben is part of the entire Upper Rhine Graben—the inflow and outflow across vertical model boundaries need to be considered.

Flow instability in a volute-free centrifugal fan subjected to non-axisymmetric pre-swirl flow from upstream bended inflow tube

The characteristics of internal flow and performance of a centrifugal fan is greatly dependent on the inflow pattern. As the fan is subjected to incoming flow from an upstream tube, the size and geometry of the tube affect the three-dimensional motion of local flow and possibly degrades the aerodynamic performance of the fan. In this work, we performed a numerical investigation on the internal flow in a centrifugal fan subjected to incoming flow from an upstream bended inflow tube of various radii using the steady and unsteady Reynolds-averaged Navier-Stokes (RANS and URANS) simulation approaches. The effects of the non-axisymmetric pre-swirl flow generated due to the curvature of the bended inflow tube are demonstrated by analyzing the internal flow characteristics of the fan, including the spatial distributions and temporal variations of pressure field and streamlines, pressure fluctuations in the upstream tube, the inflow and outflow sections of the impeller, and the circumferential distributions of velocity and pressure in the impeller. The numerical results reveal that as the inflow tube is curved with larger curvature (smaller radius of the bended section), the pre-swirl inflow is strong and deteriorates the static pressure rise and static pressure efficiency of the centrifugal fan more remarkably, and the circumferential non-uniformity of pressure and velocity distributions appears inside of the channels of the fan. As the radius of the bended section increases, the instability of the internal flow gets more pronounced, as represented by the stronger pressure fluctuations at the inflow and outflow sections. The prediction capabilities of RANS and URANS approaches are also analyzed based on the numerical data and we found that the latter is more reliable in predicting the performance of the fan.

Interstellar Neutral He Parameters from Crossing Parameter Tubes with the Interstellar Mapping and Acceleration Probe Informed by 10 yr of Interstellar Boundary Explorer Observations

The Sun's motion through the interstellar medium leads to an interstellar neutral (ISN) wind through the heliosphere. Several ISN species, including He, moderately depleted by ionization are observed with pickup ions and directly imaged. Since 2009, analyzed Interstellar Boundary Explorer (IBEX) observations returned a precise 4D parameter tube associated with the bulk velocity vector and the temperature of ISN flow distribution. This 4D parameter tube is typically expressed in terms of the ISN speed, the inflow latitudinal direction, and the temperature as a function of the inflow longitudinal direction and the local flow Mach number. We have used IBEX observations and those from other spacecraft to reduce statistical parameter uncertainties: V ISN ∞ = 25.99 ± 0.18 km s−1, λ ISN ∞ = 75 .° 28 ± 0 .° 13 , β ISN ∞ = −5 .° 200 ± 0 .° 075 , and T ISN ∞ = 7496 ± 172 K. IBEX ISN viewing is restricted almost perpendicular to the Earth–Sun line, which limits observations in ecliptic longitude to ∼130° ± 30° and results in relatively small uncertainties across the IBEX parameter tube but large uncertainties along it. Operations over the last three years enabled the IBEX spin axis to drift to the maximum operational offset (7°) west of the Sun, helping to break the ISN parameter degeneracy by weakly crossing the IBEX parameter tubes: the range of possible inflow longitudes extends over the range λ ISN ∞ = 75 .° 28 − 2.21 + 2.27 and the corresponding range of other ISN parameters is V ISN ∞ = 25.99 − 1.76 + 1.86 km s−1, β ISN ∞ = −5 .° 200 − 0.085 + 0.093 , and T ISN ∞ = 7496 − 1528 + 1274 K. This enhances the full χ 2 analysis of ISN parameters through comparison with detailed models. The next-generation IBEX-Lo sensor on IMAP will be mounted on a pivot platform, enabling IMAP-Lo to follow the ISN flow over almost the entire spacecraft orbit around the Sun. A near-continuous set of 4D parameter tube orientations on IMAP will be observed for He and for O, Ne, and H that cross at varying angles to substantially reduce the ISN flow parameter uncertainties and mitigate systematic uncertainties (e.g., from ionization effects and the presence of secondary components) to derive the precise parameters of the primary and secondary local interstellar plasma flows.

Navigation of micro-swimmers in steady flow: the importance of symmetries

Marine micro-organisms must cope with complex flow patterns and even turbulence as they navigate the ocean. To survive they must avoid predation and find efficient energy sources. A major difficulty in analysing possible survival strategies is that the time series of environmental cues in nonlinear flow is complex and that it depends on the decisions taken by the organism. One way of determining and evaluating optimal strategies is reinforcement learning. In a proof-of-principle study, Colabrese et al. (Phys. Rev. Lett., vol. 118, 2017, 158004) used this method to find out how a micro-swimmer in a vortex flow can navigate towards the surface as quickly as possible, given a fixed swimming speed. The swimmer measured its instantaneous swimming direction and the local flow vorticity in the laboratory frame, and reacted to these cues by swimming either left, right, up or down. However, usually a motile micro-organism measures the local flow rather than global information, and it can only react in relation to the local flow because, in general, it cannot access global information (such as up or down in the laboratory frame). Here we analyse optimal strategies with local signals and actions that do not refer to the laboratory frame. We demonstrate that symmetry breaking is required to find such strategies. Using reinforcement learning, we analyse the emerging strategies for different sets of environmental cues that micro-organisms are known to measure.

Development of the method of laser Doppler anemometry for diagnostics of turbulent flows at high speed

The aim of the work was to develop a laser Doppler anemometry method for high-speed turbulent aerodynamic flow diagnostic. As a result, this allowed us to measure two projections of the velocity vector in the range of 0.1 - 400 m/s with a relative error not exceeding 0.5%. The measurement area was 0.1x0.1x0.5mm. The positioning device moved the measuring unit in the area of 250 x 250 x 250 mm with an accuracy of 0.1 mm. This method also provides the ability to measure local flow rate fluctuations.

Mode classification for vortex shedding from an oscillating wind turbine using machine learning

This study presents an effective strategy that applies machine learning methods to classify vortex shedding modes produced by the oscillating cylinder of a bladeless wind turbine. A 2-dimensional computational fluid dynamic (CFD) simulation using OpenFOAMv2006 was developed to simulate a bladeless wind turbines vortex shedding behavior. The simulations were conducted at two wake modes (2S, 2P) and a transition mode (2PO). The local flow measurements were recorded using four sensors: vorticity, flow speed, stream-wise and transverse stream-wise velocity components. The time-series data was transformed into the frequency domain to generate a reduced feature vector. A variety of supervised machine learning models were quantitatively compared based on classification accuracy. The best performing models were then reevaluated based on the effects of artificial noisy experimental data on the models’ performance. The velocity sensors orientated transverse to the pre-dominant flow (u y ) achieved improved testing accuracy of 15% compared to the next best sensor. The random forest and k-nearest neighbor models, using u y , achieved 99.3% and 99.8% classification accuracy, respectively. The feature noise analysis conducted reduced classification accuracy by 11.7% and 21.2% at the highest noise level for the respective models. The random forest algorithm trained using the transverse stream-wise component of the velocity vector provided the best balance of testing accuracy and robustness to data corruption. The results highlight the proposed methods’ ability to accurately identify vortex structures in the wake of an oscillating cylinder using feature extraction.