Geometric Sensitivity Analysis Research Articles

Numerical Investigation and Performance Enhancement by Means of Geometric Sensitivity Analysis and Parametric Tuning of a Radial-Outflow High-Pressure Oil–Gas Turbine

The pressure at the natural gas wellhead typically ranges from tens to hundreds of atmospheres. Traditionally, the wellhead pressure must be throttled into a low level to satisfy the requirement of gathering pipelines, in which a large amount of pressure energy is wasted. The high-pressure oil–gas turbine is a promising approach to convert the wellhead pressure energy into shaft power or electricity. In this paper, a numerical investigation is conducted on a radial-outflow high-pressure oil–gas turbine utilized in a wellhead pressure power generation system. Using the self-defined real oil–gas physical properties and Computational Fluid Dynamics (CFD), the internal flow and performance of the high-pressure oil–gas turbine under complex operating conditions are investigated. To improve the turbine flow and performance, a Latin Hypercube Sampling-based parametric tuning is performed on the stator and rotor blade geometries. The application of such an approach effectively adjusts the flow matching and eliminates the flow separation, by which the turbine performance is significantly enhanced.

Identification of 11 position-independent geometric errors of a five-axis machine tool using 3D geometric sensitivity analysis

In this paper, a method is proposed for identification of 11 position-independent geometric errors (PIGEs) of five-axis machine tools with a tilting/rotary table via single-ball measurements and three-dimensional (3D) geometric sensitivity analysis. Eleven PIGEs were identified, including three squareness errors between three linear axes, two offset errors, and two squareness errors for the tilting/rotary axis. The approach uses a set-up of a ball and three circular measurements involving simultaneous control of two linear axes and a tilting/rotary axis. A 3D geometric sensitivity analysis is carried out to investigate the effects of the 11 PIGEs on each of the measurement’s paths and between the measurement paths. The particular measurement paths used allow the radius of the circular path at the first measurement, and the distance between the circular paths of the second and third measurements, to be increased for accurate identification of the 11 PIGEs. The proposed method was also used to derive root-sum-square values of sensitivity coefficients, and then applied to a commercial five-axis machine tool for experimental verification. It calculates the peak-to-valley values of the positional deviations in the x-, y-, and z-directions along the test paths as 152.1, 118.2, and 47.1 μm, respectively, without compensation for the identified PIGEs, and as 17.6, 15.0, and 11.4 μm, respectively, with compensation. The results confirm the validity of our proposed method.

Geometric sensitivity analysis of generalized response function with RMC code

GEneralized Adjoint Responses in Monte Carlo (GEAR-MC) method has been developed to perform sensitivity analysis of reaction rate ratios, which was to compute sensitivity coefficients of reaction rate ratios to nuclear data e.g. nuclear cross sections. In this work, the GEAR-MC method is extended to calculate sensitivity coefficients of reaction rate ratios to geometric parameters for the first time and is implemented in the Reactor Monte Carlo (RMC) code. This newly developed geometric sensitivity analysis capability is tested by four benchmark problems. The results are shown to agree within 4% and 3 σ with reference results obtained by the direct perturbation method for all cases. Moreover, the contributions from different terms to the sensitivity results are compared. It is shown that, for Godiva, Hemisphere Godiva and Jezebel benchmarks, the intergenerational term contributes much to sensitivity coefficients, and this term is necessarily considered correctly in the practical application.

Computer-Aided Geometric Sensitivity Analysis of Plane Trusses with a Square Grid Topology

A recent theory assigns a single scalar 0 ≤ r ≤ 1 to pin-jointed plane trusses, characterising their geometric sensitivity with respect to small displacements of individual joints. Here we investigate how r is varying in n × m minimally rigid quadrangulations and find that nontrivial patterns correspond both to maximal and minimal values of r.

Geometric sensitivity of patient-specific finite element models of the spine to variability in user-selected anatomical landmarks

Software to create individualised finite element (FE) models of the osseoligamentous spine using pre-operative computed tomography (CT) data-sets for spinal surgery patients has recently been developed. This study presents a geometric sensitivity analysis of this software to assess the effect of intra-observer variability in user-selected anatomical landmarks. User-selected landmarks on the osseous anatomy were defined from CT data-sets for three scoliosis patients and these landmarks were used to reconstruct patient-specific anatomy of the spine and ribcage using parametric descriptions. The intra-observer errors in landmark co-ordinates for these anatomical landmarks were calculated. FE models of the spine and ribcage were created using the reconstructed anatomy for each patient and these models were analysed for a loadcase simulating clinical flexibility assessment. The intra-observer error in the anatomical measurements was low in comparison to the initial dimensions, with the exception of the angular measurements for disc wedge and zygapophyseal joint (z-joint) orientation and disc height. This variability suggested that CT resolution may influence such angular measurements, particularly for small anatomical features, such as the z-joints, and may also affect disc height. The results of the FE analysis showed low variation in the model predictions for spinal curvature with the mean intra-observer variability substantially less than the accepted error in clinical measurement. These findings demonstrate that intra-observer variability in landmark point selection has minimal effect on the subsequent FE predictions for a clinical loadcase.

Flow structures at an idealized bifurcation: a numerical experiment

ABSTRACTRiver bifurcations are key nodes within braided river systems controlling the flow and sediment partitioning and therefore the dynamics of the river braiding process. Recent research has shown that certain geometrical configurations induce instabilities that lead to downstream mid‐channel bar formation and the formation of bifurcations. However, we currently have a poor understanding of the flow division process within bifurcations and the flow dynamics in the downstream bifurcates, both of which are needed to understand bifurcation stability. This paper presents results of a numerical sensitivity experiment undertaken using computational fluid dynamics (CFD) with the purpose of understanding the flow dynamics of a series of idealized bifurcations. A geometric sensitivity analysis is undertaken for a range of channel slopes (0.005 to 0.03), bifurcation angles (22° to 42°) and a restricted set of inflow conditions based upon simulating flow through meander bends with different curvature on the flow field dynamics through the bifurcation. The results demonstrate that the overall slope of the bifurcation affects the velocity of flow through the bifurcation and when slope asymmetry is introduced, the flow structures in the bifurcation are modified. In terms of bifurcation evolution the most important observation appears to be that once slope asymmetry is greater than 0.2 the flow within the steep bifurcate shows potential instability and the potential for alternate channel bar formation. Bifurcation angle also defines the flow structures within the bifurcation with an increase in bifurcation angle increasing the flow velocity down both bifurcates. However, redistributive effects of secondary circulation caused by upstream curvature can very easily counter the effects of local bifurcation characteristics. Copyright © 2011 John Wiley & Sons, Ltd.