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Epsilon-Near-Zero materials exhibit a transition in the real part of the dielectric permittivity from positive to negative value as a function of wavelength. Here we study metal-dielectric layered metamaterials in the homogenised regime (each layer has strongly subwavelength thickness) with zero real part of the permittivity in the near-infrared region. By optically pumping the metamaterial we experimentally show that close to the Epsilon-Near-Zero (ENZ) wavelength the permittivity exhibits a marked transition from metallic (negative permittivity) to dielectric (positive permittivity) as a function of the optical power. Remarkably, this transition is linear as a function of pump power and occurs on time scales of the order of the 100 fs pump pulse that need not be tuned to a specific wavelength. The linearity of the permittivity increase allows us to express the response of the metamaterial in terms of a standard third order optical nonlinearity: this shows a clear inversion of the roles of the real and imaginary parts in crossing the ENZ wavelength, further supporting an optically induced change in the physical behaviour of the metamaterial.

Advanced numerical models, which predict heterogeneity of microstructural features, are needed to design modern steels with heterogeneous microstructures. Models based on stochastic internal variables meet this requirement. Our stochastic model accounts for the random character of the recrystallization and transfers this randomness into equations describing the evolution of the dislocation populations and the grain size during the hot deformation of steels. The idea of the internal variable model, with the dislocation density and the grain size being stochastic variables, is described in the paper. The material parameters, which influence accuracy and reliability of the model, were identified. They compose shear modulus, lattice friction stress and the mean free pass for dislocations. Numerical test showing influence of these parameters on the identification of the model coefficients were performed and a hint how these parameters should be selected is given. Compression loads and histograms of the grain size measured in the experimental compression tests were used to identify the coefficients in the model. The model was applied to simulations of the industrial process of the hot strip rolling. It was shown that the model can be used to both predictions of the microstructural heterogeneity caused by the stochastic character of microstructure evolution and to the evaluation of the uncertainty of phase composition in the final product. The latter is due to the uncertainty of the boundary conditions.

Knowledge of gross anatomy, as a basic core subject, is fundamental for medical students and essential to medical practitioners, particularly for those intending a surgical career. However, both medical students and clinical teachers have found a significant gap in teaching basic sciences and the transition into clinical skills. The authors present a Surgical Anatomy Course developed to teach the anatomical basis of surgical procedures with particular emphasis on laparo-scopic skills while incorporating medical simulation. An evaluation of the students' satisfaction of the Surgical Anatomy Course was completed using a mix of multiple choice and open-ended questions, and a six-point Likert Scale. Questions were asked about the students' perceived improvement in surgical and laparoscopic skills. Manual skills were assessed using a laparoscopic simulator. Both evaluation of the course structure and the general impression of the course were positive. Most students believed the course should be an integral part of a modern curriculum. The course supported the traditional surgical classes and improved anatomical knowledge and strengthened students' confidentiality and facilitated understanding and taking surgical rotations. A medical course combining the practical learning of anatomy and surgical-based approaches will bring out the best from the students. Medical students positively evaluated the Surgical Anatomy Course as useful and benefi-cial regarding understanding anatomical structure and relationship necessary for further surgical education. (Folia Morphol 2018; 77, 2: 279-285).

In hot forging process, tool life is an important factor which influences the economy of production. Wear mechanisms in these processes are dependent on each other, so modeling of them is a difficult problem. The present research is focused on development of a hybrid tool wear model for hot forging processes and evaluation of adding adhesive mechanism component to this model. Although adhesive wear is dominant in cases, in which sliding distances are large, there is a group of hot forging processes, in which adhesion is an important factor in specific tool parts. In the paper, a proposed hybrid tool wear model has been described and various adhesive wear models have been reviewed. The feasible model has been chosen, adapted and implemented. It has been shown that adding adhesive wear model increases predictive capabilities of the global hybrid tool wear model as far as characteristic hot forging processes is considered.

Residual stresses in hot-rolled strips are of practical importance when the laser cutting of these strip is applied. The factors influencing the residual stresses include the non uniform distribution of elastic-plastic deformations, phase transformation occurring during cooling and stress relaxation during rolling and cooling. The latter factor, despite its significant effect on the residual stress, is scarcely considered in the scientific literature. The goal of the present study was development of a model of residual stresses in hot-rolled strips based on the elastic-plastic material model, taking into account the stress relaxation. Residual stresses in hot-rolled strips were evaluated using the FEM model for cooling in the laminar cooling line and in the coil. Relaxation of thermal stresses was considered based on the creep theory. Coefficients of elastic-plastic material model and of the creep model for steels S235 and S355 were obtained from the experiments performed on the Gleeble 3800 simulator for the temperatures 35-1100°C. Experiments composed small tensile deformations of the sample (0.01-0.02) and subsequent shutter speed without removing the load. Model of the thermal deformation during cooling was obtained on the basis of the dilatometric tests at cooling rates of 0.057°C/s to 60°C/s. Physical simulations of the cooling process were performed to validate the model. Samples were fixed in the simulator Gleeble 3800, then heated to the temperature of 1200°C and cooled to the room temperature at a rate of 1-50°C/s. Changes of stresses were recorded. Good agreement between calculated and experimental values of stresses was observed. However, due to neglecting the effect of stress relaxation the stress at high temperatures was overestimated. Due to the change of their stress sign during the unloading process the resulting residual stresses were underestimated. Simulation of residual stresses in rolling and cooling were performed on the basis of the developed model. It was shown that the effect of stress relaxation and phase transformations on the distribution of residual stresses in strips is essential and neglecting these factors could lead to an underestimation of residual stresses.

The coupled finite element multiscale simulations (FE ) require costly numerical procedures in both macro and micro scales. Attempts to improve numerical efficiency are focused mainly on two areas of development, i.e. parallelization/distribution of numerical procedures and simplification of virtual material representation. One of the representatives of both mentioned areas is the idea of Statistically Similar Representative Volume Element (SSRVE). It aims at the reduction of the number of finite elements in micro scale as well as at parallelization of the calculations in micro scale which can be performed without barriers. The simplification of computational domain is realized by transformation of sophisticated images of material microstructure into artificially created simple objects being characterized by similar features as their original equivalents. In existing solutions for two-phase steels SSRVE is created on the basis of the analysis of shape coefficients of hard phase in real microstructure and searching for a representative simple structure with similar shape coefficients. Optimization techniques were used to solve this task. In the present paper local strains and stresses are added to the cost function in optimization. Various forms of the objective function composed of different elements were investigated and used in the optimization procedure for the creation of the final SSRVE. The results are compared as far as the efficiency of the procedure and uniqueness of the solution are considered. The best objective function composed of shape coefficients, as well as of strains and stresses, was proposed. Examples of SSRVEs determined for the investigated two-phase steel using that objective function are demonstrated in the paper. Each step of SSRVE creation is investigated from computational efficiency point of view. The proposition of implementation of the whole computational procedure on modern High Performance Computing (HPC) infrastructures is described. It includes software architecture of the solution as well as presentation of the middleware applied for data farming purposes.

The paper deals with the problem of identification of microstructure evolution model on the basis of two-step compression test. Classical interpretation of this test assumes uniform fields of strains, stresses and temperatures in the deformation zone and calculates the coefficients in the model on the basis of force measurements in the second step. In the present paper the inverse approach was applied. Finite element (FE) simulations of the compression test were performed and local values of microstructural parameters were determined accounting for the inhomogeneity of deformation. Objective function was formulated as the Euclid norm for the error between measured and calculated forces for various interpass times. Coefficients in the microstructure evolution model were determined by searching for the minimum of the objective function. Optimized model was validated in simulations of plane strain compression tests.

The development of the best manufacturing technology for fasteners was the subject of this work. Physical and numerical simulations were used to evaluate various technological variants. Possibility of application of new generation bainitic steels was considered, as well. Improvement of exploitation properties was the objective of the optimization having in mind tool wear and manufacturing costs as constraints. Several fasteners were investigated but results for three parts, including Allen screw, screw anchors used to carry concrete plates are presented as a case study. Industrial trials were performed and confirmed correctness of the designed manufacturing technology.

The paper describes the hybrid computer system dedicated to identification of models of materials subjected to thermomechanical processing. The functionalities of the system consist of plastometric tests data processing and application of the inverse analysis. The latter functionality is realized unconventionally, instead of the finite element method the metamodel is implemented using artificial neural network. The metamodels, used for simulations of the plastometric tests, are imported to the proposed computer system as external plugins, what guarantees flexibility and possibility of further development. On the other hand, application of rich optimization libraries assures the best possible solution of the problem. Basic principles of the inverse analysis with metamodels and mentioned optimization procedures are described in the paper. Selected examples of identification of models for various metallic materials recapitulate the paper.

The paper presents the results of physical and numerical modeling of the kinetics of phase transformation, taking into account the precipitation of niobium carbonitride. Strain induced precipitation is a phenomenon, which controls the evolution of the microstructure in these steels during thermo-mechanical treatment. For the numerical simulation of precipitation Dutta-Sellars model was used, which describes the precipitation kinetics of Nb (C, N) at dislocations in the deformed and non-deformed austenite. The size of precipitates after continuous cooling of steel was calculated using the additivity rule. Numerical model combines a solution of the finite element method with model of phase transitions. Physical modeling included dilatometric study and rolling of rods made of niobium microalloyed steel. Microstructure studies were also carried out. Developed model allowed the assessment of the influence of precipitation on the progress of phase transition. Verification of model prediction by comparison with the experiments carried out in conditions close to semi-industrial is described in the paper, as well. W pracy przedstawiono wyniki modelowania fizycznego oraz model numeryczny opisujący kinetykę przemiany fazowej z uwzględnieniem procesu wydzieleniowego węglikoazotku niobu. Proces ten silnie wpływa na zmiany zachodzące w mikrostrukturze tych stali w trakcie obróbki cieplno - plastycznej. Do symulacji numerycznej procesu wydzieleniowego wykorzystano model Dutty-Sellarsa opisujący kinetykę procesu wydzieleniowego Nb(C, N) na dyslokacjach w austenicie odkształconym i nieodkształconym. Wielkość wydzieleń w warunkach ciągłego chłodzenia stali obliczona została z wykorzystaniem reguły addytywności. Model numeryczny łączy rozwiązanie metodą elementów skończonych z modelem przemian fazowych. Modelowanie fizyczne obejmowało badania dylatometryczne oraz walcowanie prętów ze stali z mikrododatkiem niobu uzupełnione badaniami mikrostruktury. Opracowany model pozwolił na ocenę wpływu procesu wydzieleniowego na postęp przemiany fazowej. Wyniki modelowania zweryfikowano doświadczalnie w warunkach zbliżonych do półprzemysłowych.