An engineering method for complex structural optimization involving both size and topology design variables

This work presents an engineering method for optimizing structures made of bars, beams, plates, or a combination of those components. Corresponding problems involve both continuous (size) and discrete (topology) variables. Using a branched multipoint approximate function, which involves such mixed variables, a series of sequential approximate problems are constructed to make the primal problem explicit. To solve the approximate problems, genetic algorithm (GA) is utilized to optimize discrete variables, and when calculating individual fitness values in GA, a second-level approximate problem only involving retained continuous variables is built to optimize continuous variables. The solution to the second-level approximate problem can be easily obtained with dual methods. Structural analyses are only needed before improving the branched approximate functions in the iteration cycles. The method aims at optimal design of discrete structures consisting of bars, beams, plates, or other components. Numerical examples are given to illustrate its effectiveness, including frame topology optimization, layout optimization of stiffeners modeled with beams or shells, concurrent layout optimization of beam and shell components, and an application in a microsatellite structure. Optimization results show that the number of structural analyses is dramatically decreased when compared with pure GA while even comparable to pure sizing optimization.     

Reasons for breaking of chemical bonds of gas molecules during movement of explosion products in cracks formed in rock mass

The purpose of this study was to develop a physico-mathematical model and technique for estimation of chemical bond stability depending on electric field intensity of an external point charge. A hypothesis for a possible physico-chemical mechanism of the formation of additional harmful gases in the rock destruction by blasting was proposed. The theoretical basis of the hypothesis is the method of theretical evaluation of bond energy depending on the distance to a point charge, the third Coulomb centre. The quantum-mechanical model for calculating the electronic terms of molecules makes it possible to solve problems associated with the determination of parameters of molecules under the action of various physical fields on the system under consideration. The model was approved for some diatomic molecules. The discrepancy between the experimental data and calculated data did not exceed 14%, which proves accuracy of the obtained results. The model can be used in the field of research into the causes of gas-dynamic phenomena in underground coal mines, in studies of the degree of stability of nanostructured components of coal under physical influences, and in the theoretical design of new compounds and structures in the field of nanomaterial science and nanotechnology.     

Waves in generalized thermo-viscoelastic infinite continuum with cylindrical cavity due to three-phase-lag time-nonlocal heat transfer

Abstract

Generalized thermoelastic interactions due to three-phase-lag time-nonlocal heat transfer in a Kelvin-Voigt type infinitely extended visco-thermoelastic continuum with cylindrical cavity has been investigated. The two-temperature generalized thermoelasticity theory has also been taken into account. The problem has been solved in the domain of Laplace on the assumption that the surface of the cavity is free from traction and is subjected to a smooth and time-dependent-heating effect. Laplace inversion of the transformed solutions has been carried out numerically. The obtained numerical data for different considerations are plotted in graphs to study the effects of time-nonlocal parameter, two-temperature parameter and visco-thermoelastic relaxation parameter on different thermoelastic quantities of physical interest.     

How to accelerate green technology diffusion? Directed technological change in the presence of coevolving absorptive capacity

The time window for effective climate change mitigation is closing. Technological change needs to be accelerated to limit global warming to a manageable level. Path dependence of technological change is one explanation for sluggish diffusion of green technologies. Firms acquire capital that differs by technology type and build up type-specific technological know-how needed to use capital efficiently. Path dependence emerges from cumulative knowledge stocks manifested in the productivity of supplied capital and firms’ capabilities. Increasing returns arise from induced innovation feedbacks and learning by doing. Relatively lower endowments with technological knowledge are a barrier to diffusion for new technologies. This paper shows how the evolution of relative stocks of technological knowledge explains different shapes of diffusion curves. Using an eco-technology extension of the macroeconomic agent-based model Eurace@unibi, it is shown how the effectiveness of different climate policies depends on the type and strength of diffusion barriers. Environmental taxes can outweigh lower productivity and subsidies perform better if lacking capabilities hinder firms to adopt a sufficiently mature technology.     

Emerging strategy recognition in agile portfolios

Agile practices become increasingly popular for projects and project portfolios offering firms a higher flexibility to adapt to dynamic environments. This study investigates the antecedents and consequences of agile practices' relevance for strategy formulation in project portfolio management processes. Building on complex adaptive systems theory, we hypothesize a positive relationship between agile capabilities and emerging strategy initiatives and eventually portfolio success. Agile capabilities refer to both the project portfolio organization's intensity of and competence in applying agile practices. Using a sample of 135 portfolios and multiple informants for each portfolio, the results support entrepreneurial orientation and voice behavior as antecedents for agile capabilities. Furthermore, the findings support an agile portfolio's positive relationship with emergence recognition and overall portfolio success. The findings contribute to the literature by identifying two significant antecedents of agile capabilities as well as empirically demonstrating the positive relationship between agile portfolios and emerging strategy recognition. For practitioners, the study encourages the application of agile practices by stressing the general positive influence of agile capabilities and underlines entrepreneurial orientation and voice behavior as important methods of empowerment for agile portfolio processes.     

Effects of ethylene-octene copolymer (POE) on the brittle to ductile transition of high-density polyethylene/POE blends

Three kinds of ethylene-octene copolymers (POE) were melt-blended with high-density polyethylene (PE-HD) in different proportions. Detailed characterizations were conducted to analyze their structural differences of POE and its effects in toughening PE-HD. The higher molecular weight POE can improve the toughness of PE-HD. 60:40 PE-HD/POE is elongated to break up to 700% while impact strength is 84.7 kJ/m² at −30°C, which is 21-fold of PE-HD. In the brittle to ductile transition (BDT) during impact, the fracture mechanism changes from the crazing mode to the shear yield-plastic deformation mode. The BDT temperature decreases as the POE molecular weight and its content increase. The interface strength in tension is estimated to access their effects. The Boltzmann-type models were successfully extended to describe the typical S-shaped curves in BDT of notched impact strength vs POE content or temperature. The supplementary decay model is suggested for the attenuation in toughening. Transition map in impact is proposed to select the use range of composition (c ) and temperature (T ) for high toughness. The curves are converted into 3D graph of T -c -impact strength for illustrating their coupling-separate effects, and further into the contour map of impact strength in T -c space for finding their partial equivalence.     

A multi-start central force optimization for global optimization

Central force optimization (CFO) is an efficient and powerful population-based intelligence algorithm for optimization problems. CFO is deterministic in nature, unlike the most widely used metaheuristics. CFO, however, is not completely free from the problems of premature convergence. One way to overcome local optimality is to utilize the multi-start strategy. By combining the respective advantages of CFO and the multi-start strategy, a multi-start central force optimization (MCFO) algorithm is proposed in this paper. The performance of the MCFO approach is evaluated on a comprehensive set of benchmark functions. The experimental results demonstrate that MCFO not only saves the computational cost, but also performs better than some state-of-the-art CFO algorithms. MCFO is also compared with representative evolutionary algorithms. The results show that MCFO is highly competitive, achieving promising performance.     

Convergence analysis of the alternating RGLS algorithm for the identification of the reduced complexity Volterra model

In this paper we provide a convergence analysis of the alternating RGLS (Recursive Generalized Least Square) algorithm used for the identification of the reduced complexity Volterra model describing stochastic non-linear systems. The reduced Volterra model used is the 3rd order SVD-PARAFC-Volterra model provided using the Singular Value Decomposition (SVD) and the Parallel Factor (PARAFAC) tensor decomposition of the quadratic and the cubic kernels respectively of the classical Volterra model. The Alternating RGLS (ARGLS) algorithm consists on the execution of the classical RGLS algorithm in alternating way. The ARGLS convergence was proved using the Ordinary Differential Equation (ODE) method. It is noted that the algorithm convergence canno׳t be ensured when the disturbance acting on the system to be identified has specific features. The ARGLS algorithm is tested in simulations on a numerical example by satisfying the determined convergence conditions. To raise the elegies of the proposed algorithm, we proceed to its comparison with the classical Alternating Recursive Least Squares (ARLS) presented in the literature. The comparison has been built on a non-linear satellite channel and a benchmark system CSTR (Continuous Stirred Tank Reactor). Moreover the efficiency of the proposed identification approach is proved on an experimental Communicating Two Tank system (CTTS).     

Optimal scheduling of single stage batch plants with direct heat integration

This paper addresses the multi-objective optimization problem arising in the operation of heat integrated batch plants, where makespan and utility consumption are the two conflicting objectives. A new continuous-time MILP formulation with general precedence variables is proposed to simultaneously handle decisions related to timing, product sequencing, heat exchanger matches (selected from a two-stage superstructure) and their heat loads. It features a complex set of timing constraints to synchronize heating and cooling tasks, derived from Generalized Disjunctive Programming. Through the solution of an industrial case study from a vegetable oil refinery, we show that major savings in utilities can be achieved while generating the set of Pareto optimal solutions through the ɛ-constraint method.