Set Of Geometrical Parameters Research Articles

Performance and prediction of large deformation contractile shape memory alloy knitted actuators

Compliant, large deformation actuating functional fabrics are essential to next-generation wearables, aerospace structures, and medical devices as they excel at traditional mechanical performance metrics while being soft and pliable. Actuating functional fabrics have been implemented from a variety of multifunctional material systems and fabric manufacturing techniques. A specifically intriguing combination of material system and fabric manufacturing technique are contractile shape memory alloy (SMA) knitted actuators, which generate recoverable actuation deformations of up to 50%, provide actuation forces on the magnitude of 1 N–10 N, are biocompatible, and actuate in response to thermal stimuli. However, the prediction of the knitted functional fabric actuator performance is inherently difficult due to the complex geometry of knitted architectures and the nonlinear material behavior of most multifunctional fibers. This paper presents an empirical model of the contractile SMA knitted actuator performance based on the definition of a dimensionless geometric parameter, the knit index (ik). An experimental study of the contractile SMA knitted actuator quasi-static uniaxial thermo-mechanical performance validates the knit index and the wire diameter as the smallest set of performance-predicting geometric parameters. An empirical model is formulated for the prediction of the contractile SMA knitted actuator performance based on geometric inputs (forward design) and the recommendation of geometric parameters that accomplish specific performance metrics (inverse design). The process of describing and predicting the performance with dimensionless geometric parameters is a step to understanding the mechanics of contractile SMA knitted actuators, has merit for the design of other actuating functional fabrics, and propels the creation of novel wearables, medical devices, and aerospace structures with large actuation deformations.

Automated construction of a fan blade model according to data of CAD profile measurements

The principle of automated construction of a fan blade model according to the profile measurements performed in a CAD-system is presented. Automatic construction of the model is based on the results of measurements obtained in the course of the control measurement procedure. The process of the blade airfoil control with the use of a portal-type Coord3 Hera NT coordinate-measuring machine and a measuring head with a Renishaw PH10T probe is described. The main points of the check method and instrumentation measures are presented. For example, the principle of the fan blade fixing is considered, the process of measuring the position of the base surfaces and points is presented, the process of measuring the profile points coordinates is described, the geometric parameters obtained in the course of calculation of profile deviations are presented. A measured 3D model of the fan blade is created according to the data of the control measurement procedure, taking into account complementary construction tools. The order of work for the automation of constructing a three-dimensional blade model is described. The direction of further work is specified, related to carrying out strength calculations to create a hot model of the measured blade, and subsequent aerodynamic calculations of the resulting blade to determine the most efficient set of geometric parameters for robust optimization.

Calculation of transformation coefficient of piezoceramic transformer with sector electrodes

The multiplicity and variety of practical application of disks with sector electrodes naturally stimulates theoretical studies, the purpose of which is to predict the characteristics and technical parameters of piezoelectronic devices that are based on them. Prediction is based on mathematical model, which is the main result of theoretical description of a real device. As a result of research of mathematical model of a real device, a set of geometrical, physical, mechanical and electrical parameters of a real object that provides implementation of technical indicators of functional element of piezoelectronics specified in the technical task can be determined. This significantly reduces time and cost of new functional elements of piezoelectronics developing. The cost of the saved resources is the commercial price of the mathematical model. The rational methodology for mathematical model constructing of piezoceramic transformer with sector electrodes is proposed.

Effect of porous substrates on thermohydraulic performance enhancement of double layer microchannel heat sinks

Effect of utilizing porous substrates on thermal and hydraulic performance of double-layered microchannel heat sinks (MCHSs) is comprehensively analyzed in this work. Thermal resistance and pumping power of the porous double layer MCHSs are evaluated to find optimized designs which improve heat transfer while requiring lower pumping power compared to conventional MCHSs. Conjugate heat transfer is numerically simulated by developing three dimensional models of porous MCHSs with different solid and porous fin thicknesses at the top and bottom channels. For design optimization, various performance parameters are evaluated and compared to conventional microchannels by changing the porous substrate and solid fin thickness. The results show that for every combination set of geometrical parameters in double-layered MCHS, an optimized porous double-layered MCHS can be found which can enhance thermal and hydraulic performance. Studying the heat transfer effectiveness and pumping power effectiveness of the new porous double-layered MCHSs simultaneously indicate this. The enhancement is shown in all scenarios where the top and bottom channel can have different solid-porous thickness. The superior performance of porous double-layered microchannels is verified for different range of Reynolds number, porosity of substrates, and heat sink material.

Generalized Synthesis Technique for High-Order Low-Profile Dual-Band Frequency Selective Surfaces

A systematic design method for high-order dual-band bandpass frequency selective surfaces (FSSs) with a low profile is derived from classical filter theory and presented here. To complement the design procedure, a multilayer double-slot resonator unit cell topology is proposed for realizing dual-band operations. For simplicity, the resonators are made to work for only a single polarization. To design the FSS, first, a classical dual-band bandpass filter circuit is designed by performing successive frequency transformations on a lowpass prototype. The filter is then transformed into a form resembling the equivalent circuit of the proposed multilayer FSS structure. Finally, the transformed filter is mapped to a set of FSS geometrical parameters. The method presents very few inherent limitations to realizing a diverse range of filter responses. The resulting designs lend themselves to fabrication since very few layers of metallization are required. Two FSSs with third-order passbands at 4 and 7 GHz but different passband characteristics are designed and verified numerically. One of the designs is fabricated and experimentally verified. The overall thickness of the designs is $0.08\lambda _{l}$ where $\lambda _{l}$ is the free-space wavelength at 4 GHz. The unit cell size is approximately $\lambda _{l}/8$ .

A SEA BASS on the Exoplanet HD 209458b

Abstract We present here the first application of Stellar and Exoplanetary Atmospheres Bayesian Analysis Simultaneous Spectroscopy (SEA BASS) on real data sets. SEA BASS is a scheme that enables the simultaneous derivation of four-coefficient stellar limb-darkening profiles, transit depths, and orbital parameters from exoplanetary transits at multiple wavelengths. It relies on the wavelength independence of the system geometry and on the reduced limb-darkening effect in the infrared. This approach has been introduced by Morello et al. (without the SEA BASS acronym), who discuss several tests on synthetic data sets. Here, we (1) improve on the original algorithm using multiple Spitzer/InfraRed Array Camera passbands and a more effective set of geometric parameters, (2) demonstrate its ability with Hubble Space Telescope/Space Telescope Imaging Spectrograph data sets by (3) measuring the HD 209458 stellar limb-darkening profile over multiple passbands in the 290–570 nm range with sufficient precision to rule out some theoretical models that have been adopted previously in the literature, and (4) simultaneously extracting the transmission spectrum of the exoplanet atmosphere. The higher photometric precision of the next-generation instruments, such as those on board the James Webb Space Telescope, will enable modeling the star–planet systems with unprecedented detail, and increase the importance of SEA BASS for avoiding the potential biases introduced by inaccurate stellar limb-darkening models.

On the molecular mechanics of single layer graphene sheets

The molecular structural mechanics (MSM) method is developed by applying beam elements to model bonded interactions between carbon atoms in the atomic lattices of single-layer graphene sheets (SLGSs). The novelty of the approach developed in this paper lies in the accurate adjustment of the geometric and material parameters of Bernoulli–Euler beam elements to simulate reference mechanical moduli (2D Young’s modulus, Poisson’s ratio, and bending rigidity modulus) of graphene. The MSM method with an advanced geometric and material parameter set of Bernoulli–Euler beam elements is implemented by means of the commercial MSC.Marc finite element (FE) code. We also employ the standard molecular mechanics (MM) method using the DREIDING force field (see Mayo et al. The Journal of Physical Chemistry, 1990, 94: 8897–8909). We implemented this force field in the homemade PIONER FE code using a modified parameter set which reproduces the mechanical moduli of graphene reasonably well. Computer simulations show that the free vibration frequencies and modes of SLGSs obtained using the standard MM and MSM methods converge. However, the buckling forces of compressed SLGSs obtained by the two methods provide acceptable convergence only for the lowest values of the critical forces.

Multivalued Neural Network Inverse Modeling and Applications to Microwave Filters

This paper presents a new technique for artificial neural network (ANN) inverse modeling and applications to microwave filters. In inverse modeling of a microwave component, the inputs to the model are electrical parameters such as $S$ -parameters, and the outputs of the model are geometrical or physical parameters. Since the analytical formula of the inverse input–output relationship does not exist, the ANN becomes a logical choice, because it can be trained to learn from the data in inverse modeling. The main challenge of inverse modeling is the nonuniqueness problem. This problem in the ANN inverse modeling is that different training samples with the same or very similar input values have quite different (contradictory) output values (multivalued solutions). In this paper, we propose a multivalued neural network inverse modeling technique to associate a single set of electrical parameters with multiple sets of geometrical or physical parameters. One set of geometrical or physical parameters is called one value of our proposed inverse model. Our proposed multivalued neural network is structured to accommodate multiple values for the model output. We also propose a new training error function to focus on matching each training sample using only one value of our proposed inverse model, while other values are free and can be trained to match other contradictory samples. In this way, our proposed multivalued neural network can learn all the training data by automatically redirecting contradictory information into different values of the proposed inverse model. Therefore, our proposed technique can solve the nonuniqueness problem in a simpler and more automated way compared with the existing ANN inverse modeling techniques. This technique is illustrated by inverse modeling and parameter extraction of four microwave filter examples.

Optimization of multiple arcs protrusion obstacle parameters using AHP-TOPSIS approach in an impingement jet solar air passage

Present investigation studied the influence of flow and geometric factors on the behavior of solar air passage (SAP) offered among the circular impingement air jets. The experimentation is performed for the variant criterion which is relevant to establish the best design of SAP. The experimental examination shows that the air impingement jet improves the thermal efficiency of a collector but at concurrent period friction factor rate also increases which reduces the whole functioning of arrangement. To overcome this analytical hierarchy process and order of preference by similarity to ideal solution (AHP-TOPSIS) technique is adopted using different performance condition in order to find out the best set of geometric parameters which provides the highest thermal efficiency and lowest friction factor within the SAP. The superlative set of geometric parameters achieved as a response of considered process is relative width ratio of 3, the relative height ratio of 1.0, relative pitch ratio of 9.5, the angle of arc 550 and tream Reynolds number of 19,000 respectively.

Development and validation of a semi-empirical model for two-phase heat transfer from arrays of impinging jets

Two-phase jet impingement is a compact cooling technology that provides high-heat-flux dissipation at manageable pressure drop, with applications in cooling power electronics and server modules. The extensive set of geometrical parameters and operating conditions that determine the heat transfer behavior of jet impingement systems provide an attractive level of design flexibility. In the present study, a semi-empirical approach is developed to predict heat transfer from arrays of jets of liquid that undergoes phase change upon impingement. In the modeling approach developed, the jet array is divided into unit cells centered on each orifice that are assumed to behave identically. Based on prior experimental observations, the impingement surface in each unit cell is divided into two distinct regions: a single-phase heat transfer region directly under the jet, and a surrounding boiling heat transfer region along the periphery. Single-phase convection and boiling heat transfer correlations available in the literature are used to estimate the heat transfer coefficient distribution in each region, and the mean surface temperature of the unit cell is estimated via area-averaging. An analysis is performed to show that the model outputs are sensitive to the heat transfer coefficient correlations used as inputs, with the choice depending on the heat flux input and the expected operating regime. Experiments are performed to validate the area-averaged thermal performance predictions. The model results are also compared against experimental data in the literature. The semi-empirical modeling approach developed in this work successfully represents the different heat transfer modes and transitions that occur during two-phase jet impingement. The location of transition to boiling predicted by the model is consistent with prior experimental observations of an inward-creeping boiling front with increasing heat flux. The predicted temperature difference between the surface and the jet inlet across all experimental comparisons has a mean absolute percentage error of 3.88%. The proposed modeling approach is demonstrated to be a practical tool in the development of two-phase jet array impingement devices, allowing for parametric exploration across the expansive design space.

Numerical study of dumbbell-shaped gold nanoparticles using in plasmonic waveguides in near infra-red spectrums

In this paper, we investigated plasmonic waveguides in near infra-red spectrum using dumbbell-shaped gold nanoparticles. It is possible to shift localized surface plasmon resonance (LSPR) to the desired wavelength with proper geometrical properties. 3-D FDTD simulations are used to determine the set of geometrical parameters of nanoparticles to obtain LSPR at 1310 and 1550 nm. Employing different configuration of nanoparticles chains, we not only can design waveguides with better optical characteristics but also achieve the demultiplexing function in V-form arrays. The proposed nanoparticles show sharp resonance peak, 168 FWHM bandwidth for λ = 1310, and 204 nm for λ = 1550 nm. Linear chains of particles can transport the electromagnetic energy at λ = 1310 nm, with transmission losses γL = 3 dB/452 and γT = 3 dB/446 nm and group velocities vgL = 0.336C0 and vgT = 0.256C0 for longitudinal and transverse polarizations, respectively, where C0 is the speed of light in the vacuum. At λ = 1550 nm, γL = 3 dB/490, γT = 3 dB/604, vgL = 0.382C0 and vgT = 0.260C0. Moreover, we attained 8.13 as minimum ratio of averaged electric field intensity and 36.8 as minimum ratio of averaged Poynting vector as a function of position between two ports in demultiplexing function.

Polarization-independent and tunable flat lenses based on graded index two-dimensional photonic crystals

In this paper, we perform numerical analyses on polarization-independent and tunable graded index lenses based on two-dimensional graded photonic crystals and utilizing liquid crystals. A simple triangular lattice is used for the graded lens, in which the refractive index profile in the transverse direction varies in such a way that the modulus of the refractive index is biggest at the centre and decreases towards the edges. Three variation functions of linear, parabolic and hyperbolic are implemented for creating graded structures and investigating focusing characteristics of the designed lenses, using plane wave expansion and finite-difference time-domain methods. Finally, we study the variation of the lenses properties by changing the optical axis orientation of liquid crystals. Our numerical results show that, through an appropriate set of design geometrical parameters, polarization-independent and tunable lenses can be achieved.

Thermal and hydraulic performance enhancement of microchannel heat sinks utilizing porous substrates

A comprehensive study utilizing porous substrates in microchannel heat sinks (MCHS) is presented in this work to find an optimized design which improves thermal and hydraulic performance of conventional microchannels. Three dimensional models of MCHS with different solid and porous fin thicknesses have been analyzed in this work. A parametric optimization has been done on the thickness of the solid and porous fin, and various performance parameters are evaluated for different MCHSs. The results are compared with the conventional heat sinks and demonstrate that for every combination set of MCHS geometrical parameters, there is an optimized porous design which can improve the thermal and hydraulic performance at the same time, or at least improving one while keeping the other at the same level as a conventional heat sink. This improvement is examined for different ranges of Reynolds numbers and pumping powers. Optimization process has been applied for porous MCHSs with various heat sink material and porosities. The superior effect of optimized porous design has been observed in all cases.

A shape sampling technique via particle tracing for CAD models

In this paper, a shape sampling approach is proposed for CAD products that can be used to suggest innovative product shapes to designers and consumers. These shapes are intended to inspire designers and can be employed during the design process. For a given set of geometric parameters defining the product shapes, parameter relationships (i.e., geometric constraints), and parameter ranges, a particle tracing (PT) algorithm is proposed to find product shapes that satisfy the defined geometric constraints in the shape space. Particles are placed at points in the shape space by minimizing the Audze–Eglais potential energy of the particle positions using a permutation genetic algorithm. They then move until one of the predetermined stopping criteria is met. Particle movement is achieved using a cost function that favors movement towards feasible shapes. By iteratively running the PT algorithm, feasible shapes are obtained. Representatives of these shapes are identified using a k-medoids clustering approach, and such representatives can be used by designers or shown to consumers to customize the product according to their preferences. In this paper, eight CAD models (e.g., car hood, yacht hull, wheel rim) are utilized to validate the performance of the proposed sampling technique. We also compare our technique with related methods.

SLALOM: Open-source, portable, and easy-to-use solar cell optimizer. Application to the design of InGaN solar cells

The design and optimization of novel structures is an essential part of the next-generation solar cells development. Indeed, the technological steps involved in the development of high-performance solar cells involve a huge set of interdependent physical and geometrical parameters: layers thicknesses, dopings, compositions, and defect characteristics. In this work, we propose a new open-source and free solar cell optimizer: SLALOM − for SoLAr ceLl multivariate OptiMizer − that implements a rigorous multivariate approach, which improves from the one-parameter-at-a-time procedure that is traditionally used in the field to a state-of-the-art multivariate approach. Applied to indium gallium nitride (InGaN) solar cells, it shows its potential to become a useful tool for the development of novel solar cells. SLALOM is implemented to be extended to any semiconductor simulation engine. Several models for solar cells have been implemented in SLALOM, including, for instance, InGaN. One can adapt these models to any solar cell technology by changing the parameter set, the here proposed generic code structure remaining unchanged.

Electrostatic Spectrograph with a Wide Range of Simultaneously Recorded Energies Composed of Two Coaxial Electrodes with Closed End Faces and a Discrete Combined External Electrode

An optimal set of geometric and electrical parameters of a high-aperture electrostatic charged-particle spectrograph with a range of simultaneously recorded energies of E/Emin = 1–50 has been found by computer simulation, which is especially important for the energy analysis of charged particles during fast processes in various materials. The spectrograph consists of two coaxial electrodes with end faces closed by flat electrodes. The external electrode with a conical-cylindrical form is cut into parts with potentials that increase linearly, except for the last cylindrical part, which is electrically connected to the rear end electrode. The internal cylindrical electrode and the front end electrode are grounded. In the entire energy range, the system is sharply focused on the internal cylindrical electrode, which provides an energy resolution of no worse than 3 × 10-3.

An optimized routing algorithm for the automated assembly of standard multimode ribbon fibers in a full-mesh optical backplane

Abstract In this paper a parametric, modular and scalable algorithm allowing a fully automated assembly of a backplane fiber-optic interconnection circuit is presented. This approach guarantees the optimization of the optical fiber routing inside the backplane with respect to specific criteria (i.e. bending power losses), addressing both transmission performance and overall costs issues. Graph theory has been exploited to simplify the complexity of the NxN full-mesh backplane interconnection topology, firstly, into N independent sub-circuits and then, recursively, into a limited number of loops easier to be generated. Afterwards, the proposed algorithm selects a set of geometrical and architectural parameters whose optimization allows to identify the optimal fiber optic routing for each sub-circuit of the backplane. The topological and numerical information provided by the algorithm are then exploited to control a robot which performs the automated assembly of the backplane sub-circuits. The proposed routing algorithm can be extended to any array architecture and number of connections thanks to its modularity and scalability. Finally, the algorithm has been exploited for the automated assembly of an 8x8 optical backplane realized with standard multimode (MM) 12-fiber ribbons.

Observations from a parametric study of the seismic design of soil nailing

A parametric study of the seismic design of soil-nailed walls is performed. Values of a set of geometrical and mechanical parameters for the nail and soil of a slope have been varied to assess their effects on the global factor of safety FSG. Equations of limit equilibrium of forces based on the Coulomb criterion for a two-block-failure mechanism are adopted. Pseudo-static force analyses with a horizontal seismic coefficient of 0·15 are carried out, which is normally used in engineering practice for temporary soil-nailing projects. It was found that FSG clearly increases with soil cohesion and friction as well as nail length, diameter and inclination, although nail inclinations higher than 15° can become detrimental. It was found that there is a combination of nail spacing and wall inclination for which the trend of FSG changes from decreasing to increasing. This situation is caused by a software mathematical optimisation routine, which does not take into account whether it is possible for the failure surface shape to occur or not. Additionally, perforation diameters larger than 100 mm are necessary for FSG ≥ 1·1 and soil–nail shear stress rs values of more than 200 kPa are not significantly beneficial.

Neural network dose models for knowledge-based planning in pancreatic SBRT.

Stereotactic body radiation therapy (SBRT) for pancreatic cancer requires a skillful approach to deliver ablative doses to the tumor while limiting dose to the highly sensitive duodenum, stomach, and small bowel. Here, we develop knowledge-based artificial neural network dose models (ANN-DMs) to predict dose distributions that would be approved by experienced physicians. Arc-based SBRT treatment plans for 43 pancreatic cancer patients were planned, delivering 30-33 Gy in five fractions. Treatments were overseen by one of two physicians with individual treatment approaches, with variations in prescribed dose, target volume delineation, and primary organs at risk. Using dose distributions calculated by a commercial treatment planning system (TPS), physician-approved treatment plans were used to train ANN-DMs that could predict physician-approved dose distributions based on a set of geometric parameters (vary from voxel to voxel) and plan parameters (constant across all voxels for a given patient). Patient datasets were randomly allocated, with two-thirds used for training, and one-third used for validation. Differences between TPS and ANN-DM dose distributions were used to evaluate model performance. ANN-DM design, including neural network structure and parameter choices, was evaluated to optimize dose model performance. Remarkable improvements in ANN-DM accuracy (i.e., from > 30% to < 5% mean absolute dose error, relative to the prescribed dose) were achieved by training separate dose models for the treatment style of each physician. Increased neural network complexity (i.e., more layers, more neurons per layer) did not improve dose model accuracy. Mean dose errors were less than 5% at all distances from the PTV, and mean absolute dose errors were on the order of 5%, but no more than 10%. Dose-volume histogram errors (in cm3 ) demonstrated good model performance above 25 Gy, but much larger errors were seen at lower doses. ANN-DM dose distributions showed excellent overall agreement with TPS dose distributions, and accuracy was substantially improved when each physician's treatment approach was taken into account by training their own dedicated models. In this manner, one could feasibly train ANN-DMs that could predict the dose distribution desired by a given physician for a given treatment site.

What Do Kinematic Models Imply About the Constitutive Properties of Rocks Deformed in Flat‐Ramp‐Flat Folds?

AbstractKinematic theories of flat‐ramp‐flat folds relate fault angles to stratal dips in a way that allows prediction of structural geometries in areas of economic or scientific interest. However, these geometric descriptions imply constitutive properties of rocks that might be discordant with field and laboratory measurements. In this study, we compare deformation resulting from kinematic and mechanical models of flat‐ramp‐flat folds with identical geometries to determine the conditions over which kinematic models may be reasonably applied to folded rocks. Results show that most mechanical models do not conform to the geometries predicted by the kinematic models, and only low basal friction (μ ≤ 0.1) and shallow ramps (ramp angle ≤10°) produce geometries consistent with kinematic predictions. This implies that the kinematic models might be appropriate for a narrow set of geometric and basal fault friction parameters.