Chemometric Approach to Assess Response Correlation and its Classification in simplex centroid design for Pre-Optimization stage of Catechin-SNEDDS

Catechins are isolated from tea leaves and shown to have pharmacological activities. However, the permeability and absorption capacity of the digestive tract is low, thus affecting the value of bioavailability. Self-nano emulsifying drug delivery system (SNEDDS) is formulated as a breakthrough in nano delivery to increase the value of bioavailability and stability in a model of natural compounds, namely catechins. This study applies chemometrics to the simplex centroid design (SCD) to analyze the catechin-SNEDDS pre-optimization design. The factors defined include oleic acid, croduret 50-SS, and propylene glycol. Evaluation parameters include emulsification time, percent transmittance (%T), freeze-thaw, and endurance test. The results showed a formula that met the requirements at the time of emulsification, stability, and %T. There were four clusters of results from the principal component analysis - cluster analysis (PCA-CA) in the SCD formula. The evaluation between responses in the SCD optimization design is indicated to have a positive correlation. Analysis using multivariate chemometric can describe the characteristics of each formula and the response based on the parameters used, which refers to the similarity, grouping, and correlation of each formula and response. The PCA-CA technique can group formulas from SCD in similar clusters and provide important information regarding response patterns or correlations.

Development of a Framework for Activation of Aggregator Led Flexibility

This paper presents a novel framework architecture for an online, real-time flexibility assessment and activation platform targeted at unlocking the flexibility potential of commercial buildings and smaller industrial sites, thereby enabling greater levels of renewable grid integration. Renewable integration targets in Europe of up to 40% of power generation from renewable sources by 2030 and over 90% by 2050 aim to decarbonize the electrical grid and increase electrification of transport, industry, and buildings. As renewable integration targets increase, participation in flexibility programs will be required from a much greater range of buildings and sites to balance grids hosting high levels of renewable generation. In this paper, an online implementation of a standardized flexibility assessment methodology, previously developed for offline contract negotiations between stakeholders, is modified to automate the assessment. The automated assessment is then linked to an aggregator-based multi-building or site optimization stage, enabling increased participation of multiple buildings and sites. To implement the assessment, models for individual flexible systems were reviewed, selected, and adapted, including physics-based, data-driven, and grey-box models. A review of optimization for flexibility found mixed-integer linear programming to be the optimal approach for the selection of flexible systems for demand response events.

PETAL AUXETICS WITH TARGETED POISSON’S RATIO USING ISOGEOMETRIC SHAPE OPTIMIZATION

Auxetic materials with negative Poisson’s ratio have potential applications across a broad range of engineering fields. Several design techniques have been developed to obtain auxetics with targeted mechanical properties. However, many of these finite element based techniques are difficult to use directly for auxetics, particularly during the design optimization stage which involves evolving boundary parts with large curvatures. This paper focusses on a series of smoothed petal auxetics, with lower stress concentrations at connecting parts, compared to the reference star shaped structures. An isogeometric shape optimization framework to achieve target Poisson’s ratios at large deformation is presented. Several smoothed petal auxetic designs with target constant Poisson’s ratios up to an effective tensile strain of 30% are shown to demonstrate the capability of the optimization framework.

The Application of Genetic Algorithm in Land Use Optimization Research: A Review

Land use optimization (LUO) first considers which types of land use should exist in a certain area, and secondly, how to allocate these land use types to specific land grid units. As an intelligent global optimization search algorithm, the Genetic Algorithm (GA) has been widely used in this field. However, there are no comprehensive reviews concerning the development process for the application of the Genetic Algorithm in land use optimization (GA-LUO). This article used a bibliometric analysis method to explore current state and development trends for GA-LUO from 1154 relevant documents published over the past 25 years from Web of Science. We also displayed a visualization network from the aspects of core authors, research institutions, and highly cited literature. The results show the following: (1) The countries that published the most articles are the United States and China, and the Chinese Academy of Sciences is the research institution that publishes the most articles. (2) The top 10 cited articles focused on describing how to build GA models for multi-objective LUO. (3) According to the number of keywords that appear for the first time in each time period, we divided the process of GA-LUO into four stages: the presentation and improvement of methods stage (1995–2004), the optimization stage (2005–2008), the hybrid application of multiple models stage (2009–2016), and the introduction of the latest method stage (after 2017). Furthermore, future research trends are mainly manifested in integrating together algorithms with GA and deepening existing research results. This review could help researchers know this research domain well and provide effective solutions for land use problems to ensure the sustainable use of land resources.

TeraVision: A LabVIEW Software for THz Hyper-Raman Spectroscopy

Terahertz Time-Domain Spectroscopy (TDS) has emerged during the last two decades as a very popular technique for characterizing the low-energy excitations of several materials, gaseous, liquids and solids, as well as artificial materials as for instance epitaxial heterostructures and more. In recent years, the advances in THz technology allowed obtaining nonlinear optical effects with THz photons, showing remarkable results. In particular, THz Hyper-Raman Spectroscopy greatly expands the spectroscopic capability of the standard THz-TDS by combining intense and broadband THz pulses with a detailed analysis of the spectral content of the generated signal. It is evident that this improvement needs an adequate software support. The main parameter for coding the software which differs with respect to a standard THz-TDS software is the control of a motorized grating (monochromator), but several routines employed in the setup optimization stage rather than the actual measurement are needed as well. In this paper we present the TeraVision software, based on LabVIEW code, in order to highlight the solutions we adopted to tackle the main experimental challenges as well as to give a pleasant and user-friendly experience to expert users.

Two-stage aerodynamic optimization method based on early termination of CFD convergence and variable-fidelity model

Efficient aerodynamic design optimization method is of great value for improving the aerodynamic performance of little UAV's airfoil. Using engineering or semi-engineering estimation method to analyze aerodynamic forces in solving aerodynamic optimization problems costs little computational time, but the accuracy cannot be guaranteed. However, CFD method ensuring high accuracy needs much more computational cost, which is unfordable for optimization. Surrogate-based optimization can reduce the number of high-fidelity analyses to increase the optimization efficiency. However, the cost of CFD analyses is still huge for aerodynamic optimization due to multiple design variables, multi-optimal and strong nonlinearities. To solve this problem, a two-stage aerodynamic optimization method based on early termination of CFD convergence and variable-fidelity model is proposed. In the first optimization stage, the solutions by early termination CFD convergence and the convergenced CFD solutions are regarded as low-and high-fidelity data respectively for building variable-fidelity model. Then, the multi-island genetic algorithm is used in the global optimization based on the built variable-fidelity model. The modeling efficiency can be greatly improved due to many cheap low-fidelity data. In the second stage optimization, the global optimum from the first optimization stage is treated as the start of the Hooke-Jeeves algorithm to search locally based on convergenced CFD computations in order to acquire better-optimum. The proposed method is utilized in optimizing the aerodynamic performance of the airfoil of little UAV, and is compared with the EGO method based on single-fidelity Kriging surrogate model. The results show that the present two-level aerodynamic optimization method consumes less time.

Adaptive Control for Energy Exchange with Probabilistic Interval Predictors in Isolated Microgrids

Stability and reliability are of the most important concern for isolated microgrid systems that have no support from the utility grid. Interval predictions are often applied to ensure the system stability of isolated microgrids as they cover more uncertainties and robust control can be achieved based on more sufficient information. In this paper, we propose a probabilistic microgrid energy exchange method based on the Model Predictive Control (MPC) approach to make better use of the prediction intervals so that the system stability and cost efficiency of isolated microgrids are improved simultaneously. Appropriate scenarios are selected from the predictions according to the evaluation of future trends and system capacity. In the meantime, a two-stage adaptive reserve strategy is adopted to further utilize the potential of interval predictions and maintain the system security adaptively. Reserves are determined at the optimization stage to prepare some extra capacity for the fluctuations in the renewable generation and load demand at the operation stage based on the aggressive and conservative level of the system, which is automatically updated at each step. The optimal dispatch problem is finally formulated using the mixed-integer linear programming model and the MPC is formulated as an optimization problem with a discount factor introduced to adjust the weights. Case studies show that the proposed method could effectively guarantee the stability of the system and improve economic performance.

FORMATION OF THE CAPITAL STRUCTURE OF THE ENTERPRISE

The article reveals the role of the process of attracting sources of funding for activities. Depending on the source of financing and the method of attracting them, three main financing mechanisms are identified: counterparty, credit and capital market. The peculiarities and advantages of some ways of attracting financing are identified and analyzed. Also, the mechanism of planning of attraction of financial resources considering a real financial position of the enterprise is formed. It is proved that in conditions of fierce competition the company's growth rate has a key impact on the factors of the company's continued existence in the market. The formation of a base for attracting investment in advance provides a stable and affordable source of funds for further expansion. An algorithm for forming the capital structure considering the current financial and economic condition of the enterprise has been developed. Opportunities for the company's growth are directly related to the availability of financial resources that can be obtained from various sources. The decision to use certain sources influences time and financial costs for obtaining and securing borrowed capital and for the diversification of government entities over the company, which to some extent pursue their own goals. Therefore, when building a financial strategy of the enterprise it is important to rationally and pragmatically approach the definition of ways to use financial resources and combine different sources of business financing. The effectiveness of the entire financial strategy of the enterprise largely depends on how correctly and in detail the choice of capital structure was worked out. Using the company's management of the proposed algorithm for the formation of capital structure optimization stage, as well as in the implementation phase of expansion with external sources funded, will allow the company to better attract and use the attracted financial resources without losing the investment attractiveness for future creditors and investors and not losing trust from other financially interested stakeholders.

Optimal design of watt six-bar transmission mechanism for morphing trailing edge

The morphing trailing edge could realize a continuous smooth deformation compared with conventional trailing edge, which effectively improves the aerodynamic performance. In this paper, a multi-step optimization design of watt six-bar transmission mechanism for morphing trailing edge is proposed. In the first optimization stage, the most effective aerodynamic shape and bar position in the middle of the morphing trailing edge is determined. In the second optimization stage, a watt six link transmission mechanism is proposed by using genetic algorithm to match the optimal shape from the first optimization stage. Result shows that the optimal design could achieve the determined aerodynamic shape in the first optimization stage perfectly.

Praxeological conditioning of the decision-making process in environmental protection

In the paper, the author attempts to identify the components and a course of the decision-making process in the area of environmental protection. Simultaneously, he pays attention to its conditions and context. The issues related to environmental protection are presented in a systemic approach with an emphasis on their practical nature. It is due to the necessity of decision making and a specific scheme of conduct. The author constructs such a scheme referring to a control system (in the context of a decision-making problems-solving) proposed by Marian Mazur and presented in the Deming cycle. At the same time, he points to the guidelines and characters of the efficient operation, whereby the broadly understood decision-making process becomes more efficient and more effective. He also pays special attention to the optimization stage including the selection of a precise (the most efficient and the most effective) action meaning a decision. The choice mentioned entails necessity of including certain criteria. Thus, it is disclosed that a decision-making process depends on the defined set of values.