Numerical Parameter Optimization Research Articles

The Optimization of Numerical Algorithm Parameters with a Genetic Algorithm to Animate Letters of the Sign Alphabet

At present, the development of animation-based works for human–computer interaction applications has increased. To generate animations, actions are pre-recorded and animation flows are configured. In this research, from two images of letters of the sign language alphabet, intermediate frames were generated using a numerical traced algorithm based on homotopy. The parameters of a homotopy curve were optimized with a genetic algorithm to generate intermediate frames. In the experiments performed, sequences where a person executes pairs of letters in sign language were recorded and animations of the same pairs of letters were generated with the proposed method. Subsequently, the similarity of the real sequences to the animations was measured using Dynamic Time Wrapping. The results obtained show that the images obtained are consistent with their execution by a person. Animation files between sign pairs were created from sign images, with each file weighing an average of 18.3 KB. By having sequences between pairs of letters it is possible to animate words and sentences. The animations generated by this homotopy-based animation method optimized with a genetic algorithm can be used in various deaf interaction applications to provide assistance. From several pairs of letters a file base was generated using the animations between pairs of letters; with these files you can create animations of words and sentences.

The Optimization of Numerical Algorithm Parameters with a Genetic Algorithm to Animate Letters of the Sign Alphabet

The Optimization of Numerical Algorithm Parameters with a Genetic Algorithm to Animate Letters of the Sign Alphabet

Experimental and numerical optimization of deep drawing process parameters for square medical container design with the Taguchi method

Medical containers that sterilize surgical instruments are constantly needed in the healthcare industry. In line with this need, improvements in the fabrication of medical containers are important. Determining the design factors of medical containers fabricated by deep drawing saves time and cost. This study determined, the design factors of square medical containers and experimentally verified the deep drawing process modeled in Abaqus/Explicit finite element (FE) software. Taguchi statistical method was used to reduce the number of experiments. Blank holder force (BHF), punch radius (RP), die radius (RD), coefficient of friction between die and blank (µDB), coefficient of friction between punch and blank (µPB), coefficient of friction between holder and blank (µHB) as variable factors while selecting thickness reduction (TR) and maximum punch force (PF) were selected as output parameters. The effect of variable factors on the output parameters was determined by ANOVA analysis. As a result of the examinations, it was deter-mined that TR and PF increased as BHF, µDB and µHB values increased, whereas they decreased as RP and RD increased. On the other hand, it was determined that TR decreased and PF increased as µPB increased. In addition, the corners of the sheets were chamfered in different sizes to prevent the formation of ears in the containers. Finally, the appropriate chamfer size was determined by examining the sheet thicknesses.

Integrated approach to Wire Arc Additive Manufacturing (WAAM) optimization: Harnessing the synergy of process parameters and deposition strategies

The flexibility of Additive Manufacturing (AM) technologies in the metal 3D printing process has gained significant attention in research and industry, which allows for fabricating complicated and intricate Near-Net-Shape (NNS) geometry designs. The achievement of desired characteristics in Wire-Arc Additive Manufactured (WAAM) components is primarily contingent upon the careful selection and precise control of significant processing variables, including bead deposition strategy, wire materials, type of heat source, wire feed speed, and the application of shielding gas. As a result, optimizing these most significant process parameters has improved, producing higher-quality WAAM-manufactured components. Consequently, this has contributed to the overall rise in the method's popularity and many applications. This article aims to provide an overview of the wire deposition strategy and the optimization of process parameters in WAAM. The optimization of numerous wire deposition techniques and process parameters in the WAAM method, which is required to manufacture high-quality additively manufactured metal parts, is summarised. The WAAM optimization algorithm, in addition to anticipate technological developments, has been proposed. Subsequently, a discussion ensues regarding the potential for WAAM optimization within the swiftly growing domain of WAAM. In the end, conclusions have been derived from the reviewed research work.

Numerical Simulation and Parameter Optimization for Water-to-CO2 Flooding in a Strongly Water-Sensitive Reservoir.

Carbon dioxide flooding can accelerate the development of low-permeability reservoirs of the Kexia group in the K region of the T oil field, thus resolving the issue of inadequate water drive effects. This study was focused on the well group 80513 in the K region, and based on the reservoir and fluid parameters, a simulation model of water-sensitive post-CO2 flooding was constructed to refine the gas injection strategy gradually. The injection rate of the continuous gas injection stage was preferred based on the degree of recovery. Multiindicator and multifactor injection and extraction schemes were established to optimize and analyze the key controlling factors, including the gas injection rate, gas injection period, gas-to-water ratio, and bottom-hole flow pressure, in the carbon dioxide gas-to-water alternation process. Recovery efficiency, oil exchange rate, formation pressure, and carbon dioxide storage rate were used as indicators. After 5 years of continuous CO2 flooding, the results indicated that switching to CO2 gas-water alternating flooding was more appropriate for the target block's environment. The best development plan was achieved when the gas injection rates were 1.0 and 1.25 × 104 m3·d-1 for continuous gas injection and CO2 gas-water alternating flooding, respectively, with a gas-water ratio of 1:1, a gas injection cycle of 90 days, and a bottom-hole flow pressure of 25 MPa in the production wells. A comparison between the results revealed that the formation pressure and oil recovery efficiency of this well group significantly increased upon CO2 flooding, and the parameter optimization results were well suited for controlling the gas flurry, offering a versatile model for future development of the block.

Numerical Simulation and Process Parameter Optimization of Warm Forging Near-Net Forming for Spiral Bevel Gear

Numerical Simulation and Process Parameter Optimization of Warm Forging Near-Net Forming for Spiral Bevel Gear

Optimizing impedance matching parameters for single-frequency capacitively coupled plasma via machine learning

Impedance matching plays a critical role in achieving stable and controllable plasma conditions in capacitive coupled plasma (CCP) systems. However, due to the complex circuit system, the nonlinear relationships between components, and the extensive parameter space of the matching network, finding optimal component values pose significant challenges. To address this, we employ an artificial neural network as a surrogate model for the matching system, leveraging its powerful pattern learning capability for a reliable and efficient search for matching parameters. In this paper, we designed four different parameters as optimization objectives and took the modulus of the reflection coefficient as an example to demonstrate the impedance matching optimization process of a CCP in detail using a particle-in-cell/Monte Carlo collision model. Our approach not only provides an effective optimization direction but also furnishes an entire parameter space that aligns with expectations, rather than just a single point. Moreover, the method presented in this paper is applicable to both numerical simulations and experimental matching parameter optimization.

Numerical simulation and parameter optimization of Coriolis force scale measurement process based on DEM

The Coriolis force method is a recently developed and highly regarded direct measurement technique that enables high-precision measurement of bulk materials. The operational parameters and variations thereof directly influence the measurement accuracy of the equipment. In this study, a measurement correction coefficient is introduced to improve the calculation method for mass flow rate of the materials. The DEM is employed to simulate the motion of particle groups within the Coriolis force scale under different parameters, and the effects of various structural and operational parameters on the measurement results are compared. The research findings indicate that a lower rotational speed leads to more stable instantaneous measurement results, although the measurement error is relatively large. When the rotational speed exceeds 300 rpm, the measurement error remains within 15%. For materials with a radius of 1–2 mm, the variation range of precision error is approximately 0.4%. Among the structural parameters, the radius of the measurement wheel has the most significant impact on the measurement results, wherein a larger measurement wheel radius corresponds to a smaller measurement error. The horizontal angle of the blades follows as the next influential parameter, with a clockwise rotation and a horizontal angle of 30° resulting in a measurement error below 2%.

Numerical optimization of process parameters and quality stability of active edible coated jaggery cubes during storage

The present investigation was focused on the optimization of process parameters for edible coating and the evaluation of quality characteristics of coated jaggery cubes stored for a period of 150 days. Quality parameters were evaluated at intervals of 0, 45, 90, 120, 135, and 150 days under ambient storage conditions. A total of 17 experiments as per BBD were carried out with three independent variables, including the HDPE bag thickness (100, 150, and 200 μm), the moisture absorber (1.5, 2.5, and 3.5 g/L), and the concentration ratio of CMC and HPMC (0.8, 1.2, and 1.6 g/100 mL). The responses, i.e., moisture content, pH, hardness, overall acceptability, and yeast/mould count for coated jaggery cubes, were evaluated. The optimization was performed using design expert software (ver. 13), and optimised values for process parameters were observed as 100 μm (HDPE bag thickness), 1.5 g/L (moisture absorber), and 0.8 g/100 mL (concentration of CMC and HPMC). From the storage study results, it was observed that after 150 days of storage, the yeast/mould count (98 cfu/g) in the control sample was highest compared to the control sample (15 cfu/g). The highest overall acceptability score was observed in the case of packed coated jaggery cubes (8.5), while the least (5.5) was observed for control after 150 days of storage. It was concluded that edible coatings consisting of moisture absorbers (dimethyl fumarate and silica gel) and concentration ratios of CMC and HPMC, along with HDPE bags, could maintain the quality characteristics of jaggery cubes and enhance the shelf life up to 150 days.

Numerical Simulation and Parameter Optimization of a New Reed–Nylon Net Combined Sand Fence

This paper introduces a kind of double-row reed–nylon net combined sand barrier. Using the computational fluid dynamics (CFD) method and the Euler–Euler double-fluid model, the new sand fences’ windproof effect and airflow features are simulated under different porosities and spacings, and the optimal configuration parameters are selected. The new sand fence has better windproof performance and practical significance than double-row reed and double-row nylon net fences. The new sand fences with a porosity of 0.3–0.4 and spacing of 28 H provide a longer protection range and a better wind protection effect. Considering the serious sand damage in China’s Taklamakan Desert, the new fences’ impact on sand buildup is examined. The combined sand fences have powerful sand blocking and accumulation effects, even though there is only a small quantity of sand accumulation on the leeward side of the second row. The sand particles primarily settle between sand fences in the center and rear areas. The combination of sand fences made of different materials combines the advantages of both, improves the construction efficiency and service life, and provides a more economical and efficient sand barrier arrangement for the arrangement of wind and sand-blocking facilities around railroads and highways in desert areas.

Сверхширополосный металлодиэлектрический облучатель на основе пирамидального рупора

An ultra-wideband single-polarization pyramidal metal-dielectric horn feed with a dielectric pyramidal insert and a coaxial input is proposed and investigated. As a result of numerical modeling and optimization of parameters by the finite element and finite difference methods in the time domain, it is shown that the optimized feed provides matching and stable radiation patterns in two planes, as well as the position of the phase center in a frequency band of more than an octave.

Self-Referenced Method for Geometrical Distortion Removal in THz Time-Domain Reflection Imaging

In this article, we develop a method for removing the phase drift induced by physically distorted object in terahertz time-domain reflection imaging (THz-TDRI). The proposed approach is defined as self-referenced, as it does not rely on any numerical parameter optimization nor extra instrumental components, and it is based on the unique manipulation of time-domain imaging data. In fact, we demonstrate that the problem can be solved assuming a linear contribution of the temporal shift induced by surface curvature. We illustrate how the self-referenced method is modeled and implemented, and we report the results obtained on two objects with different characteristics: a tilted and highly reflective surface, and a warped and heterogeneous surface. The proposed method demonstrates how to successfully remove the phase alterations induced on the reflected electric field, and how to repair the heavily corrupted images in the frequency-domain.

Numerical Simulation and Parameter Optimization for Semi-solid Powder Rolling of Al–Cu–Mg Alloy

Numerical Simulation and Parameter Optimization for Semi-solid Powder Rolling of Al–Cu–Mg Alloy

Numerical Analysis and Parametric Optimization of T-Shaped Symmetrical Metasurface with Broad Bandwidth for Solar Absorber Application Based on Graphene Material

Solar energy is an essential renewable energy source among all the other renewable energy sources. It is possible to improve the efficiency of the solar energy absorber by increasing the solar energy absorber’s capacity for absorption, which can help in building better solar-based renewable energy devices. The need of covering the whole solar spectrum led us to design this T-shaped metasurface solar absorber which is based on graphene material. The T-shaped absorber gives 90, 88 and 57% absorption in the visible, infrared and UV regions, respectively. This symmetrical structure is also periodic with respect to x-axis and y-axis. This solar absorber demonstrates better efficiency compared to many other existing solar absorbers. The solar absorber is also compared with two other square-1 and square-2 designs to show the improvement in solar energy absorption. The parametric optimization method is applied to optimize the design. The parameters, such as the length and width of the substrate and the thicknesses of the T-shaped metasurface and substrate, are varied to find out the optimized design for maximum solar energy absorption. The optimized parameters obtained from the optimization are 1000, 2500, 3000 and 3000 nm, for resonator thickness, substrate thickness, substrate length and substrate width, respectively. The design results for graphene material and its potential variation are also observed. The design also shows good absorption for a wide-angle of incidence of about 0 to 50°. The increased efficiency of this design can be applied in future solar absorber devices.

Parametric study of the transient period characteristics of distributed feedback laser diodes

Subject of study. The operating response characteristics for a distributed feedback laser model has presented. Aim of study. A numerical optimization of model parameters is used to reduce the laser transient period by analyzing the effects of the laser injection current, the temperature variation, the dc-bias level, and the gain compression factor on transient period characteristics. Method. The transient period value decreases when the current ratio (i.e., injection current/threshold current) is increased. Main results. Significant reduction is observed in the relaxation oscillation period and the laser turn-on time delay as the effect of increasing the injection current and/or the biasing current. Practical significance. However, varying temperatures resulted in distributed feedback operating in the off-mode region due to increasing the transient period value. Meanwhile, the relaxation oscillation period value is reduced significantly with a faster stabilization period due to the damped sinusoidal oscillations as a result of increasing the ε value.

KNN Based Denoising Algorithm for Photon-Counting LiDAR: Numerical Simulation and Parameter Optimization Design

Photon-counting LiDAR can obtain long-distance, high-precision target3D geographic information, but extracting high-precision signal photons from background noise photons is the key premise of photon-counting LiDAR data processing and application. This study proposes an adaptive noise filtering algorithm that adjusts parameters according to the background photon count rate and removes noise photons based on the local mean Euclidean distance. A simulated photon library that provides different background photon count rates and detection probabilities was constructed. It was then used to fit the distribution relationship between the background photon count rate and the average KNN (K-Nearest Neighbor) distance (k = 2–6) and to obtain the optimal denoising threshold under different background photon count rates. Finally, the proposed method was evaluated by comparing it with the modified density-based spatial clustering (mDBSCAN) and local distance-based statistical methods. The experimental results show that various methods are similar when the background noise rate is high. However, at most non-extreme background photon count rate levels, the F of this algorithm was maintained between 0.97–0.99, which is an improvement over other classical algorithms. The new strategy eliminated the artificial introduction of errors. Due to its low error rates, the proposed method can be widely applied in photon-counting LiDAR signal extraction under various conditions.

Numerical Analysis and Parametric Optimization of a Static Wavy Flag for Heat Transfer Enhancement

This work investigates the effect of different parameters of a static wavy flag vortex generator on the heat transfer in a rectangular channel using Computational Fluid Dynamics (CFD) analysis. This work encompasses optimizing several parameters of a flag such as flag height from the surface, position in the channel, number of triangular shapes in a flag, and rectangular surface area of the flag. Post analysis results exhibit encouraging results with average Nusselt number in flag height (FH) optimization exceeding that in no flag condition by 41.84%, 47.79%, 54.68% for Re 8236, 12354, and 18344, respectively whereas further position optimization of FH optimized flag exceeds average Nusselt number in no flag condition by 46.86%, 70.68% and 87.26% for the corresponding Re. With significantly less practical application of flags for heat transfer enhancement in industry, this work aims to establish flags as an effective heat transfer enhancement device and demonstrate that with the right optimized parameters, a significant increase of heat transfer in the channel can be achieved.

A New Robust and Secure 3-Level Digital Image Watermarking Method Based on G-BAT Hybrid Optimization

This contribution applies tools from the information theory and soft computing (SC) paradigms to the embedding and extraction of watermarks in aerial remote sensing (RS) images to protect copyright. By the time 5G came along, Internet usage had already grown exponentially. Regarding copyright protection, the most important responsibility of the digital image watermarking (DIW) approach is to provide authentication and security for digital content. In this paper, our main goal is to provide authentication and security to aerial RS images transmitted over the Internet by the proposal of a hybrid approach using both the redundant discrete wavelet transform (RDWT) and the singular value decomposition (SVD) schemes for DIW. Specifically, SC is adopted in this work for the numerical optimization of critical parameters. Moreover, 1-level RDWT and SVD are applied on digital cover image and singular matrices of LH and HL sub-bands are selected for watermark embedding. Further selected singular matrices SLH and SHL are split into 3×3 non-overlapping blocks, and diagonal positions are used for watermark embedding. Three-level symmetric encryption with low computational cost is used to ensure higher watermark security. A hybrid grasshopper–BAT (G-BAT) SC-based optimization algorithm is also proposed in order to achieve high quality DIW outcomes, and a broad comparison against other methods in the state-of-the-art is provided. The experimental results have demonstrated that our proposal provides high levels of imperceptibility, robustness, embedding capacity and security when dealing with DIW of aerial RS images, even higher than the state-of-the-art methods.

Receptance-based natural frequency assignment of a real fluid-conveying pipeline system with interval uncertainty

The resonance problem of an industrial fluid-conveying pipeline system can be mitigated by shifting or assigning its natural frequencies. However, the desired natural frequencies are difficult to realize using typical numerical model-based parameter optimization technologies because of the modelling errors. Herein, the first theoretical and experimental study is reported on achieving desired natural frequencies of an industrial pipeline system by using measured receptances. This research involves the one-way fluid–structure interaction of the steady flow. On this basis, this paper considers the changeability of working conditions of the pipeline system and characterizes the uncertain flow speed as an interval uncertainty. The primary framework of the classic receptance method is employed, and a novel interval-based frequency assignment method is proposed. This method inherits the advantage of the receptance methodology, in which the determination of the optimal structural modifications entirely relies on the measured frequency response functions. More especially, the obtained stiffness modifications by using the proposed method can improve the robustness of the assignment results to uncertain flow speeds, and then actually achieved values of the assigned natural frequencies have a smaller perturbation. Several numerical examples demonstrate that the proposed method provides effective results. The application of the method to the modification of a real U-shaped fluid-conveying pipeline system gives experimental evidence of its effectiveness. The effective experimental results give the confidence to use the receptance-based structural modification method to improve the dynamical behaviour of real structures.

A Biomimetic Design Method for 3D-Printed Lightweight Structures Using L-Systems and Parametric Optimization

Biological structures and organisms are determined and optimized to adapt to changes and constraints imposed by the environment. The multiple functionalities and properties exhibited by such structures are currently a source of inspiration for designers and engineers. Thus, biomimetic design has been increasingly used in recent years with the intensive development of additive manufacturing to deliver innovative solutions. Due to their multifunctional properties combining softness, high stiffness, and light weight, many potential applications can be seen in the medical, aerospace, and automotive sectors. This paper introduces a biomimetic design and geometric modeling method of 3D-printed lightweight structures based on L-systems generated and distributed along their principal stress lines. Numerical simulations and parametric optimization were conducted with three case studies to demonstrate the relevance and applicability of this method in adapting mechanical structures to various load cases as well as ensuring a proper stiffness-to-weight ratio.