Simplex Optimization Research Articles

Analysis of the Response of Urban Water Consumption to Climatic Variables: Case Study of Khorramabad City in Iran

Iran is located in a dry climate belt. Such conditions have made the supply of urban water resources one of the most fundamental management challenges. The amount of water consumed in a city is affected by the weather conditions greatly such that as the weather changes, the amount of water consumed changes as well. In this study, several models including zero-order Pearson’s correlation coefficient, first-order Pearson’s correlation, generalized additive model (GAM), generalized linear model (GLM), support vector machine (SVM-Nu), and simplex optimization algorithm were used in order to identify linear/nonlinear reactions of monthly water consumption to the individual and combined associations of meteorological variables (temperature, air pressure, and relative humidity) in Khorramabad city. Zero-order and first-order correlations showed that, by controlling the air temperature, the effect of pressure and relative humidity on changes in water consumption increase. On the other hand, both individual and combined GAM models showed the same result in the nonlinear response of water consumption to the changes in relative humidity and air pressure. The spline method also revealed that, by eliminating the effect of air temperature, the nonlinear reaction of water consumption to changes in pressure and relative humidity was increasing, and by eliminating the effects of the relative humidity and air pressure, the nonlinear reaction of water consumption to the air temperature was intensified. In general, by decreasing the air pressure and temperature, the amount of urban household water consumption decreases drastically. These conditions are generally provided by entering low-pressure systems.

Mass Spectrometric Profiling of Neuropeptides in Response to Copper Toxicity via Isobaric Tagging.

Copper is a necessary nutrient but quickly becomes toxic at elevated levels. To properly handle environmental copper influxes and maintain metal homeostasis, organisms utilize various methods to chelate, excrete, and metabolize heavy metals. These mechanisms are believed to involve complex signaling pathways mediated by neuropeptides. This study incorporates custom N,N-dimethyl leucine isobaric tags to characterize the neuropeptidomic changes after different time points (1, 2, and 4 h) of copper exposure in a model organism, blue crab, Callinectes sapidus. Using a modified simplex optimization strategy, the number of identifiable and quantifiable neuropeptides was increased 3-fold to facilitate a deeper understanding of the signaling pathways involved in responding to heavy metal exposure. The time course exposure showed many interesting findings, including upregulation of inhibitory allatostatin peptides in the pericardial organs. Additionally, there was evidence of transport of a pigment dispersing hormone from the sinus glands to the brain. Overall, this study improves the multiplexing capabilities of neuropeptidomic studies to understand the temporal changes associated with copper toxicity.

Clustering Using Student t Mixture Copulas

Tewari et al. (Parametric characterization of multimodal distributions with non-Gaussian modes, pp 286–292, 2011) introduced Gaussian mixture copula models (GMCM) for clustering problems which do not assume normality of the mixture components as Gaussian mixture models (GMM) do. In this paper, we propose Student t mixture copula models (SMCM) as an extension of GMCMs. GMCMs require weak assumptions, yielding a flexible fit and a powerful cluster tool. Our SMCM extension offers, in a natural way, even more flexibility than the GMCM approach. We discuss estimation issues and compare Expectation-Maximization (EM)-based with numerical simplex optimization methods. We illustrate the SMCM as a tool for image segmentation.

Random Walk와 Simplex 방법을 이용한 V-shape 매입형 영구자석 동기전동기의 코깅토크 저감 최적 설계

This paper presents random walk and simplex optimization algorithm on an optimal design of V-shape interior permanent synchronous motor (V-shape IPMSM). The IPMSM can easily generates a cogging torque because of change in magnetic circuit by interaction between permanent magnets and stator slots. Therefore minimization of the cogging torque, which generates vibration and noise, is an important factor in design of IPMSM. This paper proposes the optimal shape design of V-shape IPMSM using random walk and simplex method for minimizing cogging torque.

Identifying bedrest using waist-worn triaxial accelerometers in preschool children.

To adapt and validate a previously developed decision tree for youth to identify bedrest for use in preschool children. Parents of healthy preschool (3-6-year-old) children (n = 610; 294 males) were asked to help them to wear an accelerometer for 7 to 10 days and 24 hours/day on their waist. Children with ≥3 nights of valid recordings were randomly allocated to the development (n = 200) and validation (n = 200) groups. Wear periods from accelerometer recordings were identified minute-by-minute as bedrest or wake using visual identification by two independent raters. To automate visual identification, chosen decision tree (DT) parameters (block length, threshold, bedrest-start trigger, and bedrest-end trigger) were optimized in the development group using a Nelder-Mead simplex optimization method, which maximized the accuracy of DT-identified bedrest in 1-min epochs against synchronized visually identified bedrest (n = 4,730,734). DT's performance with optimized parameters was compared with the visual identification, commonly used Sadeh's sleep detection algorithm, DT for youth (10-18-years-old), and parental survey of sleep duration in the validation group. On average, children wore an accelerometer for 8.3 days and 20.8 hours/day. Comparing the DT-identified bedrest with visual identification in the validation group yielded sensitivity = 0.941, specificity = 0.974, and accuracy = 0.956. The optimal block length was 36 min, the threshold 230 counts/min, the bedrest-start trigger 305 counts/min, and the bedrest-end trigger 1,129 counts/min. In the validation group, DT identified bedrest with greater accuracy than Sadeh's algorithm (0.956 and 0.902) and DT for youth (0.956 and 0.861) (both P<0.001). Both DT (564±77 min/day) and Sadeh's algorithm (604±80 min/day) identified significantly less bedrest/sleep than parental survey (650±81 min/day) (both P<0.001). The DT-based algorithm initially developed for youth was adapted for preschool children to identify time spent in bedrest with high accuracy. The DT is available as a package for the R open-source software environment ("PhysActBedRest").

Simplex optimisation in practice.

While the underlying principles of simplex optimisation are easy to understand and the small number of trial experiments involved make the approach very attractive, there are several important issues to be considered in the practical application of the method to the analytical sciences and other areas. These include the selection of suitable factor levels to set the size and position of the initial simplex, and the variation of the step sizes used to find the positions of subsequent simplexes. The possibility of accidentally finding a local maximum rather than a global maximum must also be considered.

Innovation Management in the Supply Chains of Russian Natural Gas, Taking into Account the Regional Structure of its Production

The article describes the role of Russia in the global gas industry, on the basis of the analysis of the factual data cited, conclusions are drawn about the provision of the economy with the considered minerals, the main problems in managing the supply chains of natural gas and liquefied natural gas are formulated, and innovative ways to solve them are proposed. Based on the fuzzy modeling method, it was shown that the maximum amount of budget revenues from the export duty of Russian natural gas from the main gas-bearing regions can almost double. At the same time, the minimum volume in the same case remains virtually unchanged, remaining within 10%. The use of fuzzy modeling in innovation management in the supply chains of Russian natural gas is caused by high volatility in the global commodity markets, both for the underlying asset (in this case, natural gas) and for derivative financial instruments (derivatives). Based on the simplex optimization method, innovation management schemes have been developed in the supply chains of Russian natural gas, taking into account the regional structure of its production. The differences in the economic efficiency of the export duty for the Russian budget between the supply of pipeline natural gas and liquefied natural gas are shown. The author’s methods presented in the article can be used as additional innovative tools for making strategic and operational management decisions by industry leaders and public authorities.

Effect of renewable energy sources integration on the optimal coordination of directional over-current relays in distribution system

&lt;div data-canvas-width="397.21009877040933"&gt;The demand for power electricity is growing fast and one of the main tasks for power engineers is to generate electricity from renewable energy sources (RES).&lt;/div&gt;&lt;div data-canvas-width="277.2073926627698"&gt;Nevertheless, problems arise when the new generation is integrated in the power distribution network. Under this condition, the main purpose in this paper, an investigation of the effect of RES integration on the optimal coordination of directional over-current relays in distribution system, a dual simplex optimization algorithm has been presented to determine the coordination of directional over-current relays (DOCRs). The system used to check the efficiency of the optimization algorithm which is IEEE 33-bus models. The analysis is performed in MATLAB software environment.&lt;/div&gt;

Reverse-loading coefficients identification for updated homogeneous anisotropic hardening model

The homogeneous anisotropic hardening (HAH) model formulation, which is solely based on distortional plasticity, was improved recently. In this study, a robust coefficient identification scheme was developed for this updated model. Tension-compression tests were conducted on a mild steel sheet sample to assess the hardening behavior in the forward-reverse loading mode. An inverse identification procedure was employed to calibrate the coefficients of the model. The Nelder-Mead simplex and genetic optimization methods were investigated and the results regarding the accuracy of the calibration were compared. As a result, both optimization methods led to reasonable coefficients for the new model.

Toward the Development of a Universal Choke Correlation – Global Optimization and Rigorous Computational Techniques

Wellhead choke is an integral part of production systems. Wellhead chokes act as regulators to protect surface facilities from high rate slugs, formation damage, and water coning. These chokes also control the decline rate of reservoir pressure. Accordingly, a diverse data bank of critical flow across wellhead chokes has been compiled to develop a universal choke performance model. Three models developed to predict liquid flow rate in two-phase flow through chokes. The first two models are measured by computational intelligence paradigms such as the Artificial Neural Network and the Least Square Support Vector Machine. The third model was developed using a global optimization simplex algorithm. The three models outperformed all existing models, and the results clearly highlight the accuracy and superiority of the intelligence models over the existing empirical correlations.

Development of prepubertal goat oocytes after their in vitro maturation and chemical activation.

Experiments were conducted to study in vitro maturation of prepubertal goat oocytes and their developmental potential after chemical activation. In Experiment 1, cumulus-oocytes complexes collected from the ovaries of prepubertal goats slaughtered at a local abattoir were matured in vitro in TCM-199-based medium supplemented with 10 µg/ml luteinizing hormone (LH) (treatment 1) or 10 µg/ml LH + 0.1 mM l-cysteine (treatment 2). In Experiment 2, mature oocytes were activated with either 5 µM ionomycin or 7% ethanol. After 18 h, some oocytes were randomly fixed and stained to evaluate their chromatin status, while others were cultured in embryo culture medium to study their further development. In Experiment 3, oocytes activated with 5 µM ionomycin were cultured for 7 days in one of the four different culture media [Charles Rosenkrans medium (CR-1), TCM-199, potassium simplex optimization medium (KSOM) and synthetic oviductal fluid (SOF)] to study their developmental potential. The maturation rate in control, treatment 1, and treatment 2 media did not differ from each other (P > 0.05). However, the lowest degeneration of oocytes was observed in treatment 3 (P < 0.05) when compared with the other two groups. The proportion of activated oocytes was higher, while non-activated oocytes were lower in ionomycin group when compared with the group activated with ethanol (P < 0.05). The proportions of oocytes cleaved were 65.7, 56.8, 61.0 and 54.4% in CR-1, TCM-199, KSOM and SOF medium, respectively, with no significant difference. However, further development of cleaved oocytes was better in KSOM followed by SOF.

Non-probabilistic polygonal convex set model for structural uncertainty quantification

In this paper, a general polygonal convex set model and clustering polygonal convex set model are proposed for more reasonably quantifying non-probabilistic uncertainties. Firstly, through the principal component analysis of uncertain samples, a new interval model based on principal component analysis is constructed to characterize the correlation of uncertain parameters. Then, the polygonal convex set model is further constructed by combining the traditional interval model and the interval model based on principal component analysis. Because the polygonal convex set model more compactly and adaptively envelopes all the uncertain samples using the irregular boundaries, it is very suitable for quantification analysis of high-dimensional uncertain problems. In addition, as the polygonal convex set model has the linear boundaries, the classical simplex optimization method is properly adopted to effectively solve the corresponding uncertainty propagation problems. In order to handle the complex problems with large uncertainties, the clustering polygonal convex set model is further established by combing a several sub polygonal convex set models based on cluster analysis. Because the linear approximation of performance function is suitable in the local range of each sub polygonal convex set model, the simplex optimization method can still provide an effective propagation results by solving each sub model. Finally, three numerical examples are investigated to illustrate the feasibility and effectiveness of the proposed two non-probabilistic models on structural uncertainty quantification.

Optical characterization of collagen scaffolds using multispectral images and a light-scaffold interaction model

The study of biomaterials and their interaction with biological tissue is one of the fastest growing areas in the generation of therapeutic alternatives in clinical practice. Biomaterials can be used in order to promote the healing of skin lesion, such as cutaneous ulcers caused by: venous insufficiency, pressure, diabetes, and tropical diseases. The use of biomaterials for tissue engineering leads to the challenge of creating non-invasive tools for tissue reparation follow-up. Those tools can be developed based on instruments and methods that allow measuring physical, chemical, and optical properties of materials. Among the biomaterials used for tissue regeneration, collagen is one of the most used for the creation of scaffolds. Collagen scaffolds offer the good conditions for cellular adhesion and growth on to their surface. This paper proposes the use of a light-material interaction model, for the processing of multispectral images of collagen scaffolds. The model together with an optimization approach, allows the optical characterization of collagen scaffolds by means of absorption and scattering coefficients in the visible-near infrared spectrum. Multispectral images of collagen scaffolds built from six different type of gelatin concentrations were processed with the proposed model and the Nelder-Mead simplex optimization approach. As a result, we obtain that the absorption coefficients considered in the mathematical model are highly related to the used gelatin concentrations of the evaluated scaffolds.

Modeling the powder compaction process by an integrated simulation and inverse optimization method

A method of integrated modeling using the inverse optimization was proposed to simulate the compaction process of metal powders in this work. By using the present work, one can alleviate the time consuming and expensive experiment, and the material parameters can be determined more accurately. The constitutive parameters of the modified Drucker-Prager Cap model were identified using finite element simulations in ABAQUS- iSIGHT integrated environment. The downhill simplex optimization method has been used to predict the material parameters in a way to minimize the differences between experimental and simulation result of uniaxial powder compaction. The accuracy of inverse parameters has been validated as the powder Distaloy AE, while the sensitivity of the plasticity parameters of the DPC model has been discussed. The results show that the ejection process cannot be fully simulated when the plastic parameters are assumed to be constants, while for the case that adopting plastic parameters changed with relative density can show a good agreement with the experimental data. Finally, the parametric module of Python was applied to simulate the compaction of industrial part. The integrated modeling using inverse optimization method was verified again in compaction of a typical multi-level gear component. And the numerical results show that the errors of the maximum and the minimum relative density are about 5% and 4% respectively.

The Use of Factorial Design and Simplex Optimization to Improve Analytical Performance of In Situ Film Electrodes.

This work presents a systematic approach to determining the significance of the individual factors affecting the analytical performance of in-situ film electrode (FE) for the determination of Zn(II), Cd(II), and Pb(II). Analytical parameters were considered simultaneously, where the lowest limit of quantification, the widest linear concentration range, and the highest sensitivity, accuracy, and precision of the method evidenced a better analytical method. Significance was evaluated by means of a fractional factorial (experimental) design using five factors, i.e., the mass concentrations of Bi(III), Sn(II), and Sb(III), to design the in situ FE, the accumulation potential, and the accumulation time. Next, a simplex optimization procedure was employed to determine the optimum conditions for these factors. Such optimization of the in situ FE showed significant improvement in analytical performance compared to the in situ FEs in the initial experiments and compared to pure in situ FEs (bismuth-film, tin-film, and antimony-film electrodes). Moreover, using the optimized in situ FE electrode, a possible interference effect was checked for different species and the applicability of the electrode was demonstrated for a real tap water sample.

Simplex optimization of shield coil geometry for increasing magnetic shielding performance of air-core superconducting generator

This study deals with the simplex optimization of a shield coil geometry for improving the magnetic shielding performance of fully air-cored superconducting generators. The superconducting generator in this study has a 10 MW-3000 rpm class, fully air-cored, rotating armature structure designed for electric propulsion aircraft applications. The magnetic flux radiated to the outside of the machine is shielded by the shield coil, and the shielding performance is determined by the shape of the shield coil. In this study, the design of the shield coil is developed using simplex optimization to improve the shield performance. The shape optimization is conducted using the simplex optimal design method, and the validity of the designed shield coil is verified by comparing the shielding performance of the initial and the optimized models.

Load carrying ability and optimal characteristics of the roof slab made of profiled sheeting

The subject of the study is the roof slabs, made of profiled sheetings, supported by bottom truss systems. The profiled sheet, being the upper belt of these structures, experiences longitudinal-transverse bending under the distributed transverse load and a longitudinal eccentric compressive force. Analytical and numerical studies determined the stress-strain state of the profiled sheeting. The dependences of the limiting value of the distributed load on the compressive longitudinal force and the eccentricity of its application are revealed. A technique for optimizing the design parameters of roof slabs have been developed. The studied roof slabs made of profiled sheeting, supported by a truss system, have a rather complicated design with many parameters, on which the performance criteria depend. Studies of the ties between these parameters are quite laborious. Therefore, it is not possible to solve the problems of optimizing these structures by known analytical and numerical methods. To find the rational parameters of the studied slabs, we used the method of phased numerical experiments using simplex optimization. Using this technique, the optimal structural parameters of the slabs with spans of 6-12 m were determined for a given efficiency criterion.

Novel Time Method of Identification of Fractional Model Parameters of Supercapacitor

Accurate dynamic models of supercapacitors (SCs) are a basis for the design, control and exploitation of the hybrid energy storage systems for electric vehicles. This paper concerns a fractional model of SC impedance, based on the Cole–Cole equation describing relaxation in electric double layer. This article provides a new method of identifying the parameters of fractional order model of SC impedance, performed without disconnecting the SC module from the energy storage system. The test drive for this purpose needs only the respect a few simple recommendations. The article presents the conditions of the mentioned test drive that will ensure the frequency spectra of the recorded signals lying in the bandwidth necessary for the correct identification of the model parameters. These parameters are determined by means of the Nelder–Mead simplex optimization method. The results of the identification described by the time method coincide with those obtained in the frequency domain. It has been shown in the last part of the article that the real energy losses in these systems significantly exceed the losses determined only on the basis of the nominal capacity and series equivalent resistance (ESR), to which the SC catalogue data are usually limited. This paper also provides an auxiliary frequency criterion for the selection of SCs intended for energy storage systems of electric vehicles.

A computational bio-chemo-mechanical model of in vivo tissue-engineered vascular graft development.

Stenosis is the primary complication of current tissue-engineered vascular grafts used in pediatric congenital cardiac surgery. Murine models provide considerable insight into the possible mechanisms underlying this situation, but they are not efficient for identifying optimal changes in scaffold design or therapeutic strategies to prevent narrowing. In contrast, computational modeling promises to enable time- and cost-efficient examinations of factors leading to narrowing. Whereas past models have been limited by their phenomenological basis, we present a new mechanistic model that integrates molecular- and cellular-driven immuno- and mechano-mediated contributions to in vivo neotissue development within implanted polymeric scaffolds. Model parameters are inferred directly from in vivo measurements for an inferior vena cava interposition graft model in the mouse that are augmented by data from the literature. By complementing Bayesian estimation with identifiability analysis and simplex optimization, we found optimal parameter values that match model outputs with experimental targets and quantify variability due to measurement uncertainty. Utility is illustrated by parametrically exploring possible graft narrowing as a function of scaffold pore size, macrophage activity, and the immunomodulatory cytokine transforming growth factor beta 1 (TGF-β1). The model captures salient temporal profiles of infiltrating immune and synthetic cells and associated secretion of cytokines, proteases, and matrix constituents throughout neovessel evolution, and parametric studies suggest that modulating scaffold immunogenicity with early immunomodulatory therapies may reduce graft narrowing without compromising compliance.

Mathematical modeling of NaCl and KCl diffusion in mozzarella cheese using static and stirred brine

Sodium chloride salt is used in the cheese salting because it promotes sensorial changes besides preserving the food, but in excess can cause hypertension. Therefore, it has been partially replaced by potassium chloride to not affect the sensory characteristics. In this work the mozzarella cheese was subjected to the diffusion of Na+ and K+ in brine by static and stirred immersion. The diffusion was modeled using the second law of Fick and simulated by the finite element method through the software COMSOL Multiphysics® version 5.2. The main, cross coefficients and the relation between mass transfer coefficient and the mass conductivity were determined through simplex optimization, minimizing the percentage errors between the experimental and simulated concentrations, obtaining 3.79%(w/v) for NaCl and 5.66%(w/v) of KCl in static brine. In stirring brine, the errors obtained were 5.40%(w/v) for NaCl and 6.01%(w/v) for KCl. The resulting main diffusion coefficients were 1.12 × 10−9 (m2/s) for NaCl and 0.91 × 10−9 (m2/s) for KCl.