Set Of Geometrical Parameters Research Articles

An empirical method for geometric calibration of a photon counting detector-based cone beam CT system.

Geometric calibration is essential in developing a reliable computed tomography (CT) system. It involves estimating the geometry under which the angular projections are acquired. Geometric calibration of cone beam CTs employing small area detectors, such as currently available photon counting detectors (PCDs), is challenging when using traditional-based methods due to detectors' limited areas. This study presented an empirical method for the geometric calibration of small area PCD-based cone beam CT systems. Unlike the traditional methods, we developed an iterative optimization procedure to determine geometric parameters using the reconstructed images of small metal ball bearings (BBs) embedded in a custom-built phantom. An objective function incorporating the sphericities and symmetries of the embedded BBs was defined to assess performance of the reconstruction algorithm with the given initial estimated set of geometric parameters. The optimal parameter values were those which minimized the objective function. The TIGRE toolbox was employed for fast tomographic reconstruction. To evaluate the proposed method, computer simulations were carried out using various numbers of spheres placed in various locations. Furthermore, efficacy of the method was experimentally assessed using a custom-made benchtop PCD-based cone beam CT. Computer simulations validated the accuracy and reproducibility of the proposed method. The precise estimation of the geometric parameters of the benchtop revealed high-quality imaging in CT reconstruction of a breast phantom. Within the phantom, the cylindrical holes, fibers, and speck groups were imaged in high fidelity. The CNR analysis further revealed the quantitative improvements of the reconstruction performed with the estimated parameters using the proposed method. Apart from the computational cost, we concluded that the method was easy to implement and robust.

Parametric beam-based crashworthiness optimisation for the crush zone of a subway vehicle

This study proposed a method to optimise the crashworthiness for the crush zone structure of a subway vehicle based on the beam element model. In the preliminary conceptual design, a simplified beam element model of the crush zone was established to verify the feasibility of the model. Then, a parameterised modelling method for the mechanical characteristic curves of the energy-absorbing structures and the front-end beam was proposed, and a hybrid-weight prediction model of the mechanical curves was built. Based on the mapping relationship, a database of mechanical and geometric parameters of the crush zone was established. Finally, beam element models of the crush zone with different arrangement schemes were obtained through optimisation based on genetic algorithm. Multiple sets of feasible geometric structure parameters were obtained and the best scheme was determined. The research results showed that the calculation speed for the simplified beam element model of the crush zone structure was 461 times faster than that of the finite element model. The prediction model of the mechanical characteristic curve of the crush zone structure built in this study exhibited sufficient accuracy. The mapping relationship between the geometric structure and the mechanical properties enabled the optimised structure by the discrete beam model to be quickly obtained. The mechanical parameters of the optimised crush zone were obtained with energy absorption of 597.51 kJ, mean crushing force of 2398.38 kN, and crushing displacement of 249.72 mm. The proposed method is expected to provide a convenient guideline for fast optimisation and upgrade of energy-absorbing structures.

Surrogate optimization of a lattice foot orthotic

Background:Additive manufacturing enables to print patient-specific Foot Orthotics (FOs). In FOs featuring lattice structures, the variation of the cell’s dimensions provides a locally variable stiffness to meet the therapeutic needs of each patient. In an optimization problem, however, using explicit Finite Element (FE) simulation of lattice FOs with converged 3D elements is computationally prohibitive. This paper presents a framework to efficiently optimize the cell’s dimensions of a honeycomb lattice FO for flat foot condition. Methods:We built a surrogate based on shell elements whose mechanical properties were computed by the numerical homogenization technique. The model was submitted to a static pressure distribution of a flat foot and it predicted the displacement field for a given set of geometrical parameters of the honeycomb FO. This FE simulation was considered as a black-box and a derivative-free optimization solver was employed. The cost function was defined based on the difference between the predicted displacement by the model against a therapeutic target displacement. Results:Using the homogenized model as a surrogate significantly accelerated the stiffness optimization of the lattice FO. The homogenized model could predict the displacement field 78 times faster than the explicit model. When 2000 evaluations were required in an optimization problem, the computational time was reduced from 34 days to 10 hours using the homogenized model rather than explicit model. Moreover, in the homogenized model, there was no need to re-create and re-mesh the insole’s geometry in each iteration of the optimization. It was only required to update the effective properties. Conclusion:The presented homogenized model can be used as a surrogate within an optimization framework to customize cell’s dimensions of honeycomb lattice FO in a computationally efficient manner.

Design Optimization, Thermohydraulic, and Enviro-Economic Analysis of Twisted Perforated Tape Insert-Based Heat Exchanger With Nanofluid Using Computational Fluid Dynamics and Taguchi Grey Method

Abstract In this paper, the effect of perforated twisted tape insert (PTTI)-based heat exchanger (HX) utilizing nanofluid as working fluid undercooling, turbulent flow model has been investigated numerically. Parameters, i.e., nanofluid mass flow rates (0.018–0.038 kg/s), perforated pitches (20 mm–40 mm), and perforated diameters (2 mm–4 mm) variation effects on fluid outlet temperature, Nusselt ratio, Friction ratio, pressure drop, overall thermal performance, CO2 discharge, and heat exchanger operating cost (HXOC) have been investigated. This work also focuses on design optimization with three different factors and three levels for higher heat transfer coefficient (HTC) and minimum pressure drop based on the Taguchi–Grey method. Computational fluid dynamics (CFD) output is used as an input value for statistical analysis. Results revealed that the PTTI in HX successfully achieved overall heat transfer enhancement in the range of 19.2% to 28.5%, but at the cost of pressure penalty of 126% to 163% higher than the plain tube. Critical Reynolds number 7927, above which PTTI in HX is least suitable for heat transfer enhancement as fluid velocity dominates over heat transfer and 1.7–2.5 times higher carbon discharge to the environment and HXOC. Preference sets of geometrical and fluid parameters are obtained using Grey analysis. Based on statistical analysis, in the considered levels, a group of parameters to attain higher HTC and minimum pressure drop are mass flow rate of 0.018 kg/s, a perforated pitch of 20 mm, and a perforated diameter of 4 mm.

Optimization of the utilization of phase change materials in planar structures to control and optimize energy flux

The optimal use of phase change materials (PCMs) in multilayer constructions in hot climates is taken into account in this study. PCMs could reduce energy use and improve indoor thermal comfort by being added to the building envelope. To achieve this, an optimization-based numerical model is created to predict the thermal behavior of a multilayer wall of the building in a hot environment. The finite element model is coupled with design exploration tools based on design of experiments methodology and the response surface technique to analyze the relationships between the influencing PCM parameters and the response variable, which is represented by the heat flow into the internal space. Optimization analysis is carried out to identify a set of PCM thermophysical and geometrical parameters which minimize the output variable. The set of input parameters that includes the PCM thickness and location as well as melting temperature and melting zone is implemented in the computational model for a simulation period of 10 days. The achieved results show a decrease in the maximum temperature at the internal wall compared to the original wall without PCM, with <20% of the heat entering the occupant area. The analysis demonstrates the potential utilization of PCMs as an approach to enhance the thermal characteristics of the building and decrease energy use in regions with high temperatures.

A low-thrust finite state machine based controller for N-satellites formations in distributed synthetic aperture radar applications

Spacecraft formation flying has attracted notable interest in recent years, thanks to the properties of flexibility to different mission needs and enhanced robustness and capabilities compared to monolithic space systems. A key element for the full exploitation of this technology consists in the automation of formation management and control, allowing higher independence from ground stations as well as prompter reactions and higher autonomy in task-assignment and decision making. In this context, this work proposes a distributed architecture to autonomously coordinate and control formations containing any number of members applying low-thrust propulsion and employing finite state machines to make decisions and assign tasks to the elements of the formation based on their current state. The nominal relative trajectories (called slots) are represented within the architecture through a set of geometric parameters characterizing their stability, size, and shape. The architecture can autonomously maintain the spacecraft on a set of nominal slots, as well as reconfigure the formation to a newly assigned geometry and deal with contingency situations, performing collision avoidance manoeuvres and keeping track of the slots of the formation that remain empty to autonomously define a course of action allowing the evading spacecraft to re-join the formation safely. At the same time, a strategy for the identification of the geometrical conditions to be violated to efficiently perform formation maintenance is proposed. The architecture is tested by means of numerical simulations within a GMAT-MATLAB integrated environment considering a quasi-linear safe ellipse formation aimed at distributed synthetic aperture radar applications as reference test case. Simulation results demonstrate that the proposed architecture allows effective autonomous coordination within tight formations, with cm-level ΔV expenses, while being fully scalable with the number of satellites.

CFD analysis of the performance impact of geometrical shape on volumetric absorbers in a standard cup

The effect of three geometrical parameters of volumetric absorbers in a standard cup –height of the chamfer, the angle of the chamfer and the height of the straight protruding side– on the air temperature at the receiver outlet, the receiver's thermal efficiency and the temperature of the interface between the absorber and the cup are analysed. For the study, 126 different geometrical configurations have been checked in a two-dimensional CFD model. A silicon carbide (SiC) ceramic foam volumetric absorber was selected for the study, and the numerical model adopted includes the simulation of the performance of both the porous media and the cup body. The modelling strategy used was implemented in the commercial CFD code STAR-CCM+ v16.02.009® with a local thermal non-equilibrium model and the Rosseland approximation for the volumetric absorber. The results conclude that different sets of geometrical parameters can produce similar results in terms of air temperature at the cup outlet, thermal efficiency of the system and temperature at the interface between the volumetric absorber and the cup. Emphasizing that the larger the chamfer height the lower the air temperature at the outlet and that the effect of the protruding absorber parameter is influenced by two possible boundary conditions, inlet fluid velocity and wall, and the latter produces the higher air outlet temperature.

Determination of Cutting Transition Parameters in the APQP Pre-production Process of the Engine Camshaft Bearing Housing

An example of the application of the experimental planning method in the APQP pre-production process to find the values of the cutting process parameters that provide a given margin of accuracy is considered on the example of roughing and finishing boring of the inner hole of the camshaft bearing housing. From the total set of geometric parameters, special characteristics are highlighted - the size of the inner hole, which ensures the fit tolerance of the steel-fiber sleeve and the height parameter of roughness Ra, as well as radial runout. The objectives and results of the application of engineering methods (calculation of allowances, dimensional analysis, evaluation of technological accuracy of machine systems, planning experiments) as well as special methods of APQP process (quality management tools - FMEA analysis, SPS, MSA) are considered. Attention is drawn to the insufficient information content of the methods, which does not allow for the selection of process indicators to ensure the necessary margin of accuracy of special characteristics. In order to achieve a given margin of accuracy, technological components of the internal diametrical size are identified - the deviation of the tuning size, the deviation of the cross-section profile and the height roughness parameter Ra, the values of which are found as a result of production experiments. The planning of a full-factor experiment is carried out according to the parameters of the cutting process - cutting speed, feed and cutting depth. To implement the plan, special samples of products with a stepped allowance were designed and manufactured. The shape of the product samples makes it possible to reduce the number of samples for a full-factor experiment from eight to four, providing a check of the linearity of regression models. The calculation and regression models are given, which allow predicting the values of the components of the internal diametrical size at the design stage of the manufacturing operations of parts. The solution of the regression model system that satisfies the specified limitations for a given margin of accuracy allows you to find the optimal range of values of the parameters of the cutting process, to provide rare settings of special characteristics in the serial manufacturing process of camshaft bearing housings. Systematic application of the methodology, along with statistical methods of quality management, allows monitoring the technical condition of equipment and maintaining it in the condition required for the production of quality products. Systematic application of the methodology, along with statistical methods of quality management, allows monitoring the technical condition of equipment and maintaining it in the condition required for the production of quality products.

A snowman-like seismic metamaterial

A snowman-like seismic metamaterial is proposed in this study. The proposed model gives a lower and wider complete bandgap compared with the seismic metamaterials of the same volume in previous research. The vibration modes are investigated to clarify the mechanism of bandgap formation. Past studies used large amounts of steel to attenuate waves at low frequencies. On the contrary, to reduce the cost, this work only uses concrete. In addition, a set of geometric parameters is suggested through parametric studies. The shielding performance of the proposed seismic metamaterials against surface waves is also demonstrated using time domain finite element simulations. The results from the transient analysis are in good agreement with the dispersion curves, validating the accuracy of the numerical simulations.

Measurement of the neutral axis in avian eggshells reveals which species conform to the golden ratio.

Avian eggs represent a striking evolutionary adaptation for which shell thickness is crucial. An understudied eggshell property includes the neutral axis, a line that is drawn through any bent structure and whose precise location is characterized by the k-factor. Previous studies have established that, for chicken eggs, mean k corresponds to the golden ratio (Φ = 1.618, or 0.618 in its reciprocal form). We hypothesized whether such an arrangement of the neutral axis conforms to the eggshell of any bird or only to eggshells with a certain set of geometric parameters. Implementing a suite of innovative methodological approaches, we investigated variations in k of 435 avian species, exploring which correspond to Φ. We found that mean k is highly variable among birds and does not always conform to Φ, being much lower in spherical and ellipsoid eggs and higher in pyriform eggs. While 21 species had k values within 0.618 ± 0.02 (including four falcon species) and the Falconinae subfamily (six species) revealed a mean of 0.618, it is predominantly domesticated species (chicken, ducks, and geese) that lay eggs whose neutral axis corresponds to the golden ratio. Thus, the study of the mathematical secrets of the eggshell related to the golden ratio of its neutral axis suggests its species-specific signatures in birds.

Optimization Techniques and Mathematical Modeling Applied to Reluctance Motors

The present work aims at the application of different optimization strategies in the electromagnetic analysis of the Variable Reluctance Motor (VRM) through Finite Element (FE) simulation. Two case studies are investigated: the first one aims to optimize the geometry and electrical characteristics of windings of a single-phase VRM 6/6, minimizing copper losses; the second aims to optimize a restricted set of geometric parameters of a 4- phase VRM 8/6, maximizing the flux linkage in the phase coils per unit volume of magnetic core. In this way, by using the Finite Element Method (FEM), the results from the Differential Evolution (DE) and Particle Swarm Optimization (PSO) algorithms will be compared and highlighted. Then, the magnetic flux densities of the motors are analyzed before and after the optimization. The results obtained show good efficiency of the algorithms, since the objective functions were satisfied with respect to the reference models.

Application of a multi-objective optimization model for the design of Piano Key Weirs with a fixed dam height

Piano Key Weirs (PKWs) have recently been used as new or rehabilitation options in the world because of their advantages in hydraulic performance and construction costs. However, designing an efficient PKW is challenging due to a large and complex set of geometric and hydraulic parameters. Therefore, reaching an optimal PKW design depends on the examination of various geometric combinations and hydraulic parameters. In this study, we applied a multi-objective optimization model known as Non-dominated Sorting Genetic Algorithm-II to determine an optimal design by maximizing hydraulic discharge while minimizing the volume of the concrete. Here, we evaluated the capability of our approach in two separate case studies, one which represented as a rehabilitated weir and other as a new design. Both studies show that the developed approach could significantly reduce the concrete volume per unit of discharge. Moreover, the results show similar patterns in terms of the hydro-economic behavior of the model, which were discussed in three distinguished regions. The unique characteristics of these regions were elaborated, and their most cost-effective values of design parameters were identified. Finally, we discussed how the proposed model and findings of this study could be used for improving the preliminary design of PKWs in practice.

Multi-Scale Crystal Plasticity Model of Creep Responses in Nickel-Based Superalloys.

The current study focuses on the modeling of two-phase - nickel-based superalloys, utilizing multi-scale approaches to simulate and predict the creep behaviors through crystal plasticity finite element (CPFE) platforms. The multi-scale framework links two distinct levels of the spatial spectrum, namely, sub-grain and homogenized scales, capturing the complexity of the system responses as a function of a tractable set of geometric and physical parameters. The model considers two dominant features of morphology and composition. The morphology is simulated using three parameters describing the average size, volume fraction, and shape. The sub-grain level is expressed by a size-dependent, dislocation density-based constitutive model in the CPFE framework with the explicit depiction of - morphology as the building block of the homogenized scale. The homogenized scale is developed as an activation energy-based crystal plasticity model reflecting intrinsic composition and morphology effects. The model incorporates the functional configuration of the constitutive parameters characterized over the sub-grain - microstructural morphology. The developed homogenized model significantly expedites the computational processes due to the nature of the parameterized representation of the dominant factors while retains reliable accuracy. Anti-Phase Boundary (APB) shearing and, glide-climb dislocation mechanisms are incorporated in the constitutive model which will become active based on the energies associated with the dislocations. The homogenized constitutive model addresses the thermo-mechanical behavior of nickel-based superalloys for an extensive temperature domain and encompasses orientation dependence as well as the loading condition of tension-compression asymmetry aspects. The model is validated for diverse compositions, temperatures, and orientations based on previously reported data of single crystalline nickel-based superalloy.

Optimal Parametric Design of Radial Magnetic Torque Couplers via Dimensional Analysis

In this article, we apply dimensional analysis to the optimization of radial magnetic torque couplers. Our goal is to find the design that maximizes the torque potential in a given package size. We consider two types of torque coupler: the permanent-magnet (a.k.a. synchronous) torque coupler, in which both the inner and outer rotors contain permanent magnets; and the variable-reluctance torque coupler, in which the inner rotor contains permanent magnets and the outer rotor contains soft-magnetic teeth. Both types of torque coupler are defined by the same set of independent geometric and material parameters. First, the Buckingham <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\Pi $ </tex-math></inline-formula> theorem is used to find the minimal set of dimensionless parameters required for design optimization. Then, using a combination of 2-D and 3-D finite-element analysis, we find and characterize the optimal designs. We explicitly consider torque couplers with eight stable magnetic equilibria (i.e., 45° of rotation between stable equilibria), but the methodology can be repeated for other configurations.

Analytical model of the dynamic behavior of a vibrating mesh nebulizer for optimal atomization efficiency

This work deals with the assessment of optimal working condition of a mesh nebulizer on-demand droplet generation. The purpose of this paper is to introduce a model of vibrating mesh nebulizer to identify optimal working regime from a mechanical point of view. The influence of geometrical parameters and mechanical properties of both the piezoelectric component, vibrating plate and geometry of perforations is investigated and discussed based on an analytical model of stepped plate. This model is validated by 2D-axisymmetric finite element computations. The main trends identified by the model are recovered by the simulation and enable to formulate design rules to maximize the atomization efficiency with respect to a given set of mechanical and geometrical parameters.

Experimental analysis and thermal management of solar air heater roughened with sine wave baffles

In the present study, a thermo-hydraulic performance (THP) of solar air heater (SAH) has been assessed by placing sine wave-shaped baffles on the heat-absorbing surface. The experiments have been performed by varying Reynolds number ([Formula: see text]) ranging from 3000-18,000, relative pitch ([Formula: see text]) ranging from 8 to 14, relative height ([Formula: see text]) ranging from 0.4 to 0.55, relative baffle length [Formula: see text] ranging from 0.054 to 0.081 and angle of attack(α) ranging from 10° to 45° while the duct aspect ratio has been kept fixed at 12. The best set of geometric parameters has been decided based on Nusselt number [Formula: see text] and friction factor [Formula: see text] characteristics of the roughened SAH and compared with the smooth surface SAH, under analogous experimentation conditions. The cost analysis has also been performed and results revels that roughened SAH is more cost-effective than smooth SAH. The correlation for Nusselt number [Formula: see text], friction factor [Formula: see text], and thermo-hydraulic performance parameters (η) have been developed using regression analysis and found an average deviation of ±9.15%, ±7%, and ±9.2% respectively, from experimental results.

USER DEFINED GEOMETRIC FEATURE FOR THE CREATION OF THE FEMORAL NECK ENVELOPING SURFACE

There is a growing demand for application of personalized bone implants (endoprostheses or macro-scaffolds, and fixators) which conform the anatomy of patient. Hence the need for a CAD procedure that enables fast and sufficiently accurate digital reconstruction of the traumatized bone geometry. Research presented in this paper addresses digital reconstruction of the femoral neck fracture. The results point out that User-Defined (geometric) Feature (UDF) concept is the most convenient to use in digital reconstruction of numerous variants of the same topology, such as in this kind of bone region. UDF, named FemoNeck, is developed to demonstrate capability of the chosen concept. Its geometry, controlled by a dozen of parameters, can be easily shaped according to anatomy of femoral neck region of the specific patient. That kind of CAD procedure should use minimally required set of geometric (anatomical) parameters, which can be easily captured from X-ray or Computed Tomography (CT) images. For the statistical analysis of geometry and UDF development we used CT scans of proximal femur of 24 Caucasian female and male adults. The validation of the proposed method was done by applying it for remodeling four femoral necks of four different proximal femurs and by comparing the geometrical congruency between the raw polygonal models gained directly from CT scan and reconstructed models.

Thermomechanical Modeling and Optimization of Zero-Power Micromechanical Photoswitch

This paper presents an in-depth thermomechanical analysis of zero-power micromechanical photoswitches (MPs) aiming at aggressive performance enhancement for applications that require ultralow infrared (IR) detection threshold. An accurate analytical model was first derived and used to maximize the thermal sensitivity of the MPs through a loop-based optimization program. With specific pre-defined boundary conditions, such a program can be used to generate a set of device geometrical parameters leading to highest possible thermal sensitivity without sacrificing the structural strength of the device (i.e., spring constant), which otherwise will have to be done with time-consuming numerical simulations. The optimized MPs show more than 4 times improvement in thermal sensitivity compared to previous demonstrations, thanks to the high thermal resistance and temperature sensitivity achieved using the thermomechanical model. The demonstrated theoretical analysis and thermomechanical optimization methods for the MPs are critical for the development of the next-generation zero-power IR sensors specifically designed for applications that require ultra-sensitive IR detection capability without compromising their sensor size, weight and power consumption. [2021-0231]

Graphene-based tunable plasmon-induced transparency utilizing circular and two rectangular gold rings in the near-infrared spectrum

A plasmonic induced transparency utilizing one circular and two rectangular gold rings in silicon substrate covered by a monolayer graphene sheet is investigated numerically and theoretically in the near infra-red spectrum. Three-dimensional finite difference time domain (3D-FDTD) simulations are employed to extract the set of geometrical parameters to achieve a 1200–2200 nm transparency window. By sweeping the Fermi level of the graphene, we study transmissions, phase shifts, and group delays of the proposed structure. The group delay was about 0.02 ps (ps) for 0.6 electron-volt(eV) Fermi level, and it showed the capability of slow light applications. Moreover, a linear modulation index of 11% was achieved at λ = 1550 nm for 4-layer graphene. The results offered that the plasmonic induced transparency (PIT) effect may be used in the slow-light devices and active plasmonic modulation in the communication wavelength.

Base drag estimation in suddenly expanded supersonic flows using backpropagation genetic and recurrent neural networks

In recent years, base pressure management has gained a lot of industrial importance due to its applications in missiles and projectiles. For certain aerodynamic vehicles, the base pressure becomes a critical factor in regulating the base drag. That prompted the current work to develop input–output relationships for a suddenly expanded flow process using experiments and neural network-based forward and reverse mapping. The objective of forward mapping (FM) is to predict the responses, namely base pressure (β), base pressure with cavity (βcav), and base pressure with rib (βrib), for a known combination of flow and geometric parameters, namely Mach number (M), nozzle pressure ratio (η), area ratio (α), and length to diameter ratio (ψ). On the other hand, an effort is made to decide the optimal set of flow and geometric parameters for achieving the desired base pressure by reverse mapping (RM). Neural network-controlled backpropagation and recurrent and genetic algorithms have been employed to carry out the forward and reverse mapping trials. A batch mode of training was employed to conduct a parametric study for adjusting and optimizing the neural network parameters. Due to the requirement of massive data for batch mode training, the data required for training was achieved using the response equations developed through response surface methodology. Further, the forecasting performances of the neural network algorithms are compared with the regression models (FM) and among themselves (RM) through random test cases. The findings indicate that all evolved neural network (NN) models could make accurate predictions in both forward and reverse mappings. The results obtained would help aerodynamic engineers control various parameters and their values that affect base drag.