Elisaveta Kirilova

The aim of the study is to determine the optimal geometry and magnitude of the applied load to ensure safety and prevent delamination in a three-layered nanocomposite structure under axial mechanical loading. The structure consists of a layer of the nanomaterial tungsten disulfide (WS2) and a substrate layer of poly(methyl methacrylate) (PMMA), which are adhesively bonded using SU-8 glue. To achieve this aim, a multi-parameter optimization problem (MOP) is formulated. It includes a two-dimensional stress function model that describes stress transfer in the considered three-layer structure. Two types of analytical solutions for the interface shear stress (ISS) are derived, featuring real and complex roots. The decision variables in MOP include the external load, layer thicknesses, and structure length. The optimization criterion is defined as the minimization of the difference between the model ISS and ultimate shear stress (USS) in the adhesive layer to assure no delamination occurs in the nanocomposite structure. A genetic algorithm and alternative optimization approach developed within the framework of “Mathematica” are implemented for the optimization of both model solutions. As a result, optimal values for the given external load, layer thicknesses, and structure length are obtained for considered nanostructure. For the case of an ISS model solution with real roots, the optimization procedures ensure optimal geometries that physically correspond to thinner structural layers, but they are limited at lower possible loads. In contrast, for the case of a model solution for the ISS with complex roots, solutions for the optimal geometries of the nanostructures were obtained with thicker layers requiring higher loads, than thinner ones, but delamination does not occur.

In the present study, a two-dimensional stress-function method is applied to model the axial strain distribution in the tungsten disulfide (WS₂) flake embedded in an epoxy/polymethyl methacrylate nanocomposite structure subjected to an axial tension load. The analytical model strain distribution along the flake is calculated and compared with experimental and shear-lag model literature data for monolayer flake at an external strain of 0.35% and 0.55%, as well as with results for few-layer flakes at an external strain of 0.55%. The comparison shows good agreement and confirms the applicability of our model method for describing strains in nanocomposite layered structures in the elastic region of applied loads. The presented method is not appropriate for few layers flake at an external strain of 0.55% because of the appearance of relaxation zone and the formation of wrinkles in the flake.

This study proposes a multi-objective approach for the optimal design of a sustainable Integrated Biodiesel/Diesel Supply Chain (IBDSC) based on first- (sunflower and rapeseed) and second-generation (waste cooking oil and animal fat) feedstocks with solid waste use. It includes mixed-integer linear programming (MILP) models of the economic, environmental and social impact of IBDSC, and respective criteria defined in terms of costs. The purpose is to obtain the optimal number, sizes and locations of bio-refineries and solid waste plants; the areas and amounts of feedstocks needed for biodiesel production; and the transportation mode. The approach is applied on a real case study in which the territory of Bulgaria with its 27 districts is considered. Optimization problems are formulated for a 5-year period using either environmental or economic criteria and the remainder are defined as constraints. The obtained results show that in the case of the economic criterion, 14% of the agricultural land should be used for sunflower and 2% for rapeseed cultivation, while for the environmental case, 12% should be used for rapeseed and 3% for sunflower. In this case, the price of biodiesel is 14% higher, and the generated pollutants are 6.6% lower. The optimal transport for both cases is rail.

The production of dairy products is related to water and energy costs and generation of large amounts of greenhouse gas (GHG) emissions and wastewater. This has a direct bearing on the reduction of natural resources, the negative impact on the environment as well as the rise of social concerns due to increased product costs, pollution, etc. Full sustainability of this type of systems can be achieved by optimizing all activities across the chain of raw materials, through production to customers while considering all aspects of sustainability - environmental, economic and social. The study proposes a multi-objective modelling approach for optimal design of three-echelon supply chain (SC) for production of dairy products according to different recipes where all aspects of sustainability are taken into consideration. The approach was implemented on a real case study from Bulgaria. Four mix integer nonlinear programming (MINLP) optimization models were defined without and with social impact consideration. They are solved using General Algebriac Modeling System (GAMS) software. The obtained results have shown how the social impact assessment affects the obtained optimal products portfolios and profits. In these cases, varying the values of environmental constraints also affect the products portfolios and profits without affect the social costs. The stricter constraints on the environment impact leads to higher economic costs and lower profits, and conversely, high values of environmental constraints result in higher profits and lower economic costs. The obtained solutions can be used in the decision-making process to achieve social sustainability of the considered dairy supply chain.