Second-order Design Research Articles

Performance of insulators under variation of pollution, inclined angle, and temperature based on the design of experiment

The environmental conditions significantly impact the performance of the transmission line insulators. The current work investigated some variables that influence the flashover and breakdown voltages, such as insulator pollution (P), insulator inclined angles with the cross-arm (A), and insulator temperature (T). A prediction equation can be developed using Box-Behnken Design (BBD) to relate the input variables (P, A, and T) and the flashover voltage (VFO). BBD is a rotatable second-order design requiring three levels of each variable, influencing a specific experiment response. A statistical analysis was carried out to identify the significant variables affecting voltage VFO. So, the main objective of the work is to investigate the effect of P, A, and T on the VFO and use Box Behnken Design (BBD) to predict the value of VFO when the information about P, A, and T is available without requiring any experimental works. The results illustrated a prediction equation that facilitates the prediction of the voltage VFO if new values of the input parameters are known. The prediction error of the constructed equation was less than 5 % for a total number of 21 new data samples used to test and verify the robustness of the prediction equation.

A New Automated Algorithm for Optimization of Measurements for Achieving the Required Accuracy of a Geodetic Network

The optimization of measurements in a geodetic network (second-order design) has been investigated in the past; however, the practical usability of the outcomes of most of such studies is doubtful. Hence, we have proposed a new automated optimization algorithm, taking into account the practical aspects of total station measurements. The algorithm consists of four parallel partial algorithms, of which one is subsequently automatically selected—the one meeting the geodetic network accuracy requirements with the lowest number of necessary measurements. We tested the algorithm (and individual partial algorithms) on four geodetic networks designed to resemble real-world networks with 50–500 modifications to each of those networks in individual tests. The results indicate that (i) the results achieved by the combined algorithm are close to the optimal results and (ii) none of the four partial algorithms universally performs the best, implying that the combination of the four partial algorithms is necessary for achieving the best possible results of geodetic network optimization.

Further considerations in A-optimal second-order response surface designs

Second-order design of experiments over hypercubic regions is under consideration for the set -up in which the experimenters’ main interest is in estimation of parameters corresponding to higher-order terms of the model. The designs optimal under A-optimality criterion for the situation are obtained. Performances of the derived designs and the designs A-optimal for full model relative to each other are investigated. The derived A-optimal designs are found to have very high efficiency and, for all practical purposes, may be equally good for the full model. Under the set-up the best designs are also derived within the class of symmetric product designs and the class of central composite designs. AMS Subject Classification62K99, 62K05.

Improving Energy Efficiency of Grain Cleaning Technology

The relevance of the research topic was substantiated, and the purpose and objectives of the study were formulated. It was determined that the energy efficiency of the grain cleaning process can be evaluated only when all the machines operate in a single production line and are coordinated in productivity. Research on energy savings and energy efficiency in the technological process of post-harvest grain treatment using grain cleaning units by implementing the method of mathematical experiment planning (MEP) was conducted. The method is based on transforming the initial mathematical models of various research objects into a model in the form of regression equations convenient for solving the problems of research, analysis and optimization of the object. For the first time, the mathematical description of the target function was performed by conducting a multifactorial experiment based on second-order design. The research produced adequate second-order regression equations, making it possible to determine the minimum specific consumption of electricity for the technological process of post-harvest grain treatment at grain cleaning facilities, while complying with the agrotechnical requirements for the quality of the cleaned grain. The problem of optimization of the research object was solved by mathematical transformations, which enabled obtaining graphical and analytical interpretations of the optimum area. For this purpose, the canonical transformation of the mathematical model and the method of two-dimensional cross-sections of the response surface were used. Research has led to the development of scientifically based standards of specific electricity consumption for grain cleaning processing schemes, which serve as criteria for evaluating energy savings in the technological processes.

Optimization of baseline configuration in a GNSS network (Nile Delta network, Egypt) – A case study

Abstract When starting any GNSS measurements, there is a need to establish a survey plan with the required optimal baselines. The optimal GNSS baselines can be chosen by solving the geodetic second-order design (SOD). The particle swarm optimization PSO is used widely to solve geodetic design issues. This work employed the particle swarm optimization (PSO) algorithm, a stochastic global optimization method, to select the optimal GNSS baselines. The optimal baselines satisfy the set criterion matrix at a reasonable cost. The fundamentals of the algorithm are presented. The effectiveness and usefulness of the technique are then demonstrated using a Nile Delta GNSS network as an example. In some cases, we have to observe many GNSS benchmarks with limited instrumentations. PSO represents a powerful tool for optimizing baseline to get the required accuracy with limited capabilities (like limited receivers). The PSO algorithm, a stochastic global optimization approach, was used in this paper to find the best observation weights to measure in the field that will match the predetermined criterion matrix with a fair degree of precision. The method’s fundamentals are presented with an actual geodetic network over the Nile delta in Egypt. In the current work, two survey strategies were applied. One represents a case with 9 GNSS receivers (high capability), and another one represents the tested survey plan with limited GNSS receivers (3 receivers, low capability) after applying PSO. By comparing two survey strategies, applying the PSO algorithm to a real Nile delta geodetic network shows its effectiveness on the obtained coordinate accuracy. This obtained accuracy ranged from 2 mm to 3 mm in X, Y, Z, and 3 mm in height. Also, the linear closure error between known and estimated coordinates improved to be 1.4 cm after applying PSO.

DIRECTED REGULATION OF THE STRUCTURAL AND RHEOLOGICAL PROPERTIES OF HEAT-INSULATING ACRYLIC AQUEOUS DISPERSIONS USING THE COMBINED USE OF HYDROPHILIC AND HYDROPHOBIC SILICATE FILLERS

The formation technology and performance characteristics of coatings based on aqueous dispersions are largely determined by the properties of the initial film-forming materials, which should ensure uniform thin-layer distribution on the substrate surface and the formation of coatings with the required technological complex of properties. Among them, due to their functional properties and relatively low cost, the most widespread are water-dispersion polymer coatings based on acrylic film-formers. In this paper, mathematical models of the structural and rheological dependences of heat-insulating acrylic aqueous dispersions are considered depending on the combined content of hydrophilic-hydrophobic fillers. To describe these dependencies, it is advisable to use equations of the second degree. According to the mathematical theory of experiment, the second-order orthogonal central compositional design makes it possible to predict the behavior of the response function. Carrying out an experiment in accordance with this plan makes it possible to establish the analytical dependence of the response function on the corresponding factors in the form of a polynomial equation of the second degree. The main response functions were: conditionally static yield stress, viscosity at the minimum rate of onset of fracture (initial effective viscosity), viscosity of the “destroyed” structure according to the Newtonian nature of the flow, activation energy of viscous flow at minimum, average and maximum shear rates. On the basis of the established dependences, the optimal ratios of hydrophobized aerosil and aluminosilicate microspheres were selected, the combined use of which makes it possible to reduce shear stresses to create a homogeneous aqueous acrylic dispersion, to predict the activation energy at various technological stages of preparation and application of heat-insulating coatings. The established results made it possible to create a hydrophilic-hydrophobic aqueous acrylic dispersion, which, without the use of surfactants, makes it possible to simplify the production technology of heat-insulating water-dispersion coatings, namely, to exclude the stage of pretreatment of fillers, to reduce the rotation speed of the frame mixer, and also to increase the kinetic stability of the finished dispersion.

Design of global positioning system (GPS) networks using different artificial intelligence techniques

The selection of optimal GPS baselines can be realized by solving the geodetic second-order design (SOD) problem. Basically, there are two techniques to be used for selecting optimal baselines in GPS network, namely traditional techniques and artificial techniques. Traditional techniques include the method of trial and error and the analytical method, while artificial methods include both local and global optimization techniques. The global optimization techniques, such as Genetic Algorithms (GAs), Simulated Annealing (SA) method, Particle Swarm Optimization (PSO) Algorithm, and Butterfly Optimization Algorithm (BOA) have been used recently in geodesy. In the current study, (BOA) has been used for the selection of the optimal GPS baselines to be measured in the field that will meet the postulated criterion matrix, at a reasonable cost. Ithas been tasted on a GPS network. The BOA is already designed and it determined the number of baselines that would be observed due to obtaining high accuracy. The results showed that the BOA method was more efficient than the traditional ones by 19.2%. It was better than the artificial methods in terms of length. Asit enhanced (SA) method by 21.7% and (PSO) method by 4.6% . Consequently, the use of the BOA is proven to be more effective and applicable.

Statistical Multiobjective Optimization of Thiospinel CoNi2S4 Nanocrystal Synthesis via Design of Experiments.

Thiospinels, such as CoNi2S4, are showing promise for numerous applications, including as catalysts for the hydrogen evolution reaction, hydrodesulfurization, and oxygen evolution and reduction reactions; however, CoNi2S4 has not been synthesized as small, colloidal nanocrystals with high surface-area-to-volume ratios. Traditional optimization methods to control nanocrystal attributes such as size typically rely upon one variable at a time (OVAT) methods that are not only time and labor intensive but also lack the ability to identify higher-order interactions between experimental variables that affect target outcomes. Herein, we demonstrate that a statistical design of experiments (DoE) approach can optimize the synthesis of CoNi2S4 nanocrystals, allowing for control over the responses of nanocrystal size, size distribution, and isolated yield. After implementing a 25-2 fractional factorial design, the statistical screening of five different experimental variables identified temperature, Co:Ni precursor ratio, Co:thiol ratio, and their higher-order interactions as the most critical factors in influencing the aforementioned responses. Second-order design with a Doehlert matrix yielded polynomial functions used to predict the reaction parameters needed to individually optimize all three responses. A multiobjective optimization, allowing for the simultaneous optimization of size, size distribution, and isolated yield, predicted the synthetic conditions needed to achieve a minimum nanocrystal size of 6.1 nm, a minimum polydispersity (σ/d̅) of 10%, and a maximum isolated yield of 99%, with a desirability of 96%. The resulting model was experimentally verified by performing reactions under the specified conditions. Our work illustrates the advantage of multivariate experimental design as a powerful tool for accelerating control and optimization in nanocrystal syntheses.

An innovative second-order design method for the structural optimization of the SpiderFLOAT offshore wind Platform

The SpiderFLOAT (SF) is an offshore wind turbine substructure that promises to drastically reduce project capital expenditure via its modularized slender structure, efficient load path, and effective use of materials. The structural design of the SF must both guarantee component reliability as well as floater stability. This article discusses the theory and the analytically developed method to determine the internal loads and the required dimensions of the SF's main components during preliminary design. The classical elastic beam theory is extended to a higher order to account for buckling risk and shortening due to bending, and applied to the SF's typical leg member. Two key load cases are considered in this preliminary sizing, analyzed against both service and ultimate limit states (SLS and ULS). The first loading scenario occurs on a dry-dock during SF's assembly and is associated with the pretensioning of the cables, which realizes both the overall structure stiffness as well as the concrete leg and stem prestress. The second load case is an operational condition at sea and near turbine rated-power. After assessing the loads, the leg dimensions and the reinforcement geometry are determined by satisfying both SLS and ULS requirements based on design standards. The newly developed structural model is implemented in the software tool SOFT4S which was verified against ANSYS. The excellent agreement between the two codes proved that the computationally light SOFT4S can be reliably used in the optimization of the SF components in the context of control co-design, where both controls and structures are simultaneously designed to reduce overall costs.

Design of Multi-function Power Factor Instrument with STM32

Background: A multifunctional power factor device based on the FFT algorithm has been designed. The digital panel can display power factor, voltage, current, frequency, phase angle, active power and reactive power. Objective: To solve the influence of the harmonic interference and the aperiodic component on the accuracy of power factor measurement. Methods: In this paper, by combining a fixed-point 256-point FFT algorithm and taking STM32 as the core microcontroller, the hardware circuit and the software program are designed respectively. The hardware circuit is tested and analyzed in practice. Among them, the hardware circuit mainly includes the main circuit design, STM32 control circuit design, EMI and second-order RC filter circuit design, sampling circuit design, and signal conditioning circuit design. The software program mainly includes the main program, AD conversion subroutine, voltage and current acquisition subroutine, LCD display subroutine and twirl factor array. FFT algorithm is achieved by the table look-up method. Results: Finally, the hardware circuit is built and the software program is debugged to test the designed device. The experimental results show that the designed power factor instrument meets the task requirements under the different types of loads. Conclusion: After processing and analyzing the measurement results, it can be concluded that: under the pure resistive load, the maximal relative error of electrical parameters is 4.49%; and under the resistive inductive load, the maximal relative error of electrical parameters is 2.86%. Both results meet the design requirements.

Seismic vulnerability of above-ground storage tanks with unanchored support conditions for Na-tech risks based on Gaussian process regression

This paper aims to investigate the seismic vulnerability of an existing unanchored steel storage tank ideally installed in a refinery in Sicily (Italy), along the lines of performance-based earthquake engineering. Tank performance is estimated by means of component-level fragility curves for specific limit states. The assessment is based on a framework that relies on a three-dimensional finite element (3D FE) model and a low-fidelity demand model based on Gaussian process regression, which allows for cheaper simulations. Moreover, to approximate the system response corresponding to the random variation of both peak ground acceleration and liquid filling level, a second-order design of experiments method is adopted. Hence, a parametric investigation is conducted on a specific existing unanchored steel storage tank. The relevant 3D FE model is validated with an experimental campaign carried out on a shaking table test. Special attention is paid to the base uplift due to significant inelastic deformations that occur at the baseplate close to the welded baseplate-to-wall connection, offering extensive information on both capacity and demand. As a result, the tank performance is estimated by means of component-level fragility curves for the aforementioned limit state which are derived through Monte Carlo simulations. The flexibility of the proposed framework allows fragility curves to be derived considering both deterministic and random filling levels. The comparison of the seismic vulnerability of the tank obtained with probabilistic and deterministic mechanical models demonstrates the conservatism of the latter. The same trend is also exhibited in terms of risk assessment.

Enzymatic hydrolysis of high gravity extruded corn starch media

Increase of solubles concentration in processable liquid media is one of the trends of technological development of starchy materials bioconversion. It promotes the reduction in operating costs, in heat and energy consumption and increases the efficiency of using capacitive equipment. The use of thermoplastic extrusion in the bioconversion processes as a pretreatment stage is perspective. Extrusion provides intensive gelatinization of starch with a moisture content of 15-30 % that has become a prerequisite for the development of extrusion-hydrolytic technology for obtaining of concentrated hydrolysates from starch-containing raw materials. As a part of the technology development, the effect of the key factors of biocatalysis on the formation of hydrolysis products and the rheological properties of highly concentrated hydrolysates of corn starch has been studied. The dosage of thermostable α-amylase and the concentration of the medium were taken as independent variables. The ranges of variation of the factors were set in the range of 5-13 units of amylolytic activity per 1 g of starch and 40- 60 % soluble concentration in accordance with the central orthogonal second-order design of the experiment. The value of dextrose equivalent in the area of the studied factor space varied from 23 to 40. Dynamic viscosity values were in the range from 89 to 2219 mPa·s. The analysis of the results and the mathematical model showed that an increase in the dextrose equivalent in the hydrolysis products was facilitated by a decrease of the concentration of the medium and an increase in the dosage of α-amylase. The growth dynamics of the dextrose equivalent value decreased with an excess of the dosage of the enzyme preparation of 9 units of amylolytic activity per 1 g of starch. Rheological studies have shown that a dosage of α-amylase of 1- 13 units of amylolytic activity per gram of starch at 40 % concentration of the medium provided dynamic viscosity values in the range 89-780 mPa·s, which is sufficient for the subsequent stages of hydrolyzate processing. Increasing the concentration to 50-60 % requires the introduction of α-amylase at a dosage of more than 5 units of amylolytic activity to ensure a rheologically safe process.

On the thickness distribution and the maximum thinning ratio in hydrostatic forming for sheet metal

In manufacturing, thickness distribution and maximum thinning greatly affect product quality in sheet metal forming. They depend on many input parameters, such as technological parameters, geometric shape of die, workpiece’s materials and forming methods. Hydrostatic forming technology is particularly suitable for forming thin-shell products with complex shapes. However, due to the forming characteristics, the thinning phenomenon in this technology is much more intense than in other forming methods. Therefore, this study aims to determine the thickness distribution and the relationship between the maximum thinning ratio and input parameters including blank holder pressure, relative depth of the die and relative thickness of the workpiece in this technology. The chosen product shape is cylinder and the chosen method is the orthogonal second-order design. The results are expressed in graphs and functions and they can be applied in product design, calculation and control of input parameters in industrial manufacturing.

Constructing response surface designs with orthogonal quadratic effects using cyclic generators

The central composite designs (CCDs [1]) and small composite designs (SCDs [2,3]) are designs for sequential experimentation for response surface optimization. The CCDs for fitting the second-order response surface require a 2-level factorial or a resolution V fraction at the first stage (screening stage). The SCDs developed for fitting the same model require many fewer runs at the first stage as they only require a resolution III* fraction. This paper introduces an algorithm which can augment a 2-level first-order design with additional 3-level runs to form a second-order design. This algorithm does not require the 2-level first-order design in stage I to be a resolution V or resolution III* fraction. These augmented runs are made up of circulant matrices. Since CCDs and SCDs are special cases of the designs constructed this way, we call the new designs generalized composite designs or GCDs. Like CCDs and SCDs, GCDs have orthogonal quadratic effects. GCDs can often be found with numbers of runs between those of SCDs and CCDs. This is useful because SCDs often have poorly estimated parameters and CCDs often require substantially more runs than required to fit a full quadratic model.

Photogrammetric Solution for Analysis of Out-Of-Plane Movements of a Masonry Structure in a Large-Scale Laboratory Experiment

This paper proposes a photogrammetric procedure able to determine out-of-plane movements experienced by a masonry structure subjected to a quasi-static cyclic test. The method tracks the movement of circular targets by means of a coarse-to-fine strategy. These targets were captured by means of a photogrammetric network, made up of four cameras optimized following the precepts of a zero-, first-, and second-order design. The centroid of each circular target was accurately detected for each image using the Hough transform, a sub-pixel edge detector based on the partial area effect, and a non-linear square optimization strategy. The three-dimensional (3D) coordinates of these targets were then computed through a photogrammetric bundle adjustment considering a self-calibration model of the camera. To validate the photogrammetric method, measurements were carried out in parallel to an ongoing test on a full-scale two-story unreinforced masonry structure (5.4 × 5.2 × 5.4-m) monitored with more than 200 contact sensors. The results provided by the contact sensors during one of the load phases were compared with those obtained by the proposed approach. According to this accuracy assessment, the method was able to determine the out-of-plane displacement during the quasi-static cyclic test with a sub-pixel accuracy of 0.58.

Determination of heterocyclic aromatic amines in ashes from biomass burning by UHPLC-MS/MS after ultrasound-assisted dispersive solid-liquid microextraction

A simple, rapid and efficient methodology was developed for the extraction and determination of heterocyclic aromatic amines (HAAs) in cigarette and forest fire ash samples based on a novel Ultrasound-Assisted Dispersive Solid-liquid Microextraction (UA-DSLME) coupled to polyurethane foam (PUF) mini-column as a clean-up strategy and on-line determination by liquid chromatography-tandem mass spectrometry (LC-MS/MS). The optimal working conditions were found by (i) application of two-level full factorial designs and (ii) implementation of a response surface methodology based on the second-order design as central composite designs. Under optimal experimental conditions, good linearity was obtained for concentrations ranging from 8.3 to 500 ng g−1, with correlation coefficients (r2) varying from 0.995 to 0.999 for all HAAs investigated. The limits of detection and quantification resulted to be between 2.1 and 10.7 ng g−1 and 8.3–16.9 ng g−1, respectively. The recoveries from 92.2 to 100.6% were reached and the relative standard deviations (RSDs) were lower than 9.2%. The developed method was successfully applied to the determination of HAAs in ashes generated by cigarette and forest fire combustion.

Design and implementation of second-order microwave integrator

ABSTRACTIn this paper, a new design methodology is developed for the implementation of a second-order microwave integrator on microstrip circuit. Firstly, an existing digital first-order integrator with best magnitude and phase performance is adopted as a prototype to give digital second-order integrator transfer function. Then, by using the autoregressive process and a least mean square based error function, coefficients of the formulated second-order digital integrator are transformed into the impedance values of transmission line elements. Different sets of impedance values are obtained through the optimization process, and design with a highly accurate frequency response having maximum relative error value not more than 7.2% over the angular frequency range 0.18pi to 0.94pi is selected for implementation purpose. RT/Duroid 5880 is used to fabricate the proposed second-order microwave integrator design. Measured results for transmission coefficient S21(f) are found to follow theoretical values over the frequency range of 1.8 GHz to 8.6 GHz.

Controlled Design of Phase- and Size-Tunable Monodisperse Ni2P Nanoparticles in a Phosphonium-Based Ionic Liquid through Response Surface Methodology

Nanoparticles of nickel phosphide are finding wide ranging utility as catalysts for hydrodesulfurization, hydrogen evolution reaction, and hydrodeoxygenation of bio-oils. Herein, we present a methodology to tailor monodisperse nickel phosphide nanoparticles in terms of size and phase through the use of a statistical response surface methodology. Colloidal nickel phosphide nanoparticles were synthesized by replacing octadecene (ODE), a commonly used organic solvent, by a more sustainable phosphonium-based ionic liquid (IL). The replacement of ODE with the phosphonium-based IL resulted in faster crystallization at lower temperatures to yield phase-pure, monodisperse Ni2P nanoparticles. Using a first-order design, the PPh3/Ni precursor ratio was identified as the most critical factor influencing the resulting size and phase of the nanoparticles. Optimization using a Doehlert matrix for second-order design yielded a second-degree polynomial equation used to predict the mean diameter of the nanoparticles (over...

Power Bounds and Energy Efficiency in Incremental <inline-formula> <tex-math notation="LaTeX">$\Delta\Sigma$ </tex-math> </inline-formula> Analog-to-Digital Converters

Incremental analog-to-digital-converters (IADCs) are variants of $\triangle \Sigma $ ADCs, which have been increasingly used for low-power sensory applications in recent years. Most IADC applications require high resolution and high energy efficiency. In this paper, we present a systematic analysis of IADCs. We derive analytical design equations for practical IADC designs. Process limitations are included in the model as well. The equations are verified with a 14-bit second-order IADC design in a 0.18- $\mu \text{m}$ process. With the design equations, the theoretical energy efficiency bound is derived for IADCs. The efficiency bound is compared with previously reported IADC designs. It is found that the derived bound matches existing designs well.

Measure of rotatability of modified five-level second-order rotatable design using supplementary difference sets

ABSTRACTRotatability is a desirable quality of fitting response surface experimental designs. The property states that the variance of the estimated response made from the Taylor’s series expansion are constant on circles, spheres and hyper-spheres about the centre of the design. In this article, a measure of rotatability of modified second-order rotatable design is presented. The variance function of a second-order response design and an infinite class of supplementary difference sets is used in coming up with the design.