Institute of Fundamental Technological Research

This paper introduces MorphoGen — an integrated reliability-based topology optimization and nonlinear finite element analysis system for 2D and 3D domains. The system’s key innovation is its seamless prototyping of scientific formulations for computational problems in topology optimization. Its layered and object-oriented architecture, based on the template method design pattern, facilitates effortless modifications of algorithms and the introduction of new types of finite elements, materials, and analyses. MorphoGen also offers flexible handling of objective functions and constraints during topological optimization, enhancing its adaptability. It empowers researchers and practitioners to explore a wide range of engineering challenges, fostering a deeper understanding of complex structural behaviors and efficient design solutions. There are many topology optimization software and open source codes, especially based on the classical SIMP method. Unlike these codes our package is freely distributed among users and since it is distributed on the MIT licence, which allows for its easy modification depending on the particular needs of the users. For this purpose, we use the topology optimization algorithm proposed for the first time in our previous paper (Blachowski et al., 2020). The algorithm is based on a fully stress design-based optimality criteria and can be applied for topology optimization of either linearly elastic and elastoplastic structures. Additionally, the novelty of the proposed system is related to its ability of solving optimal topology under various constraints such as displacement, stresses and fatigue in both deterministic and probabilistic cases. Another application are modular structures, which reduce design complexity and manufacturing costs as well as rapid reconfiguration. However, in the realm of structural optimization, modular systems are more challenging due to various: modes of operation of the modules and the stresses configurations. Moreover, this area of research is dramatically less explored. Thus the effectiveness of MorphoGen for structural engineering is demonstrated with examples of topological shape optimization of two Extremely Modular Systems: a planar robotic manipulator Arm-Z and spatial free-form ramp Truss-Z.

Stress Constrained Topology Optimizatio,Extremely Modular System,Object-oriented software architecture,MATLAB-based array programming,First Order Reliability Analysis

This paper addresses a challenging engineering problem that combines stress-limited topology optimization, reliability analysis, and plasticity-based low-cycle fatigue. Each of these issues represents a complex problem on its own, necessitating significant computational effort. In this study, we propose a novel approach that integrates safety assessment into the topology optimization process while considering the number of cycles for low-cycle fatigue. Our method employs a linear approximation of the performance function for safety control, incorporating the number of failure cycles within a complex, multi-level load program. The methodology is validated through real experiments, using a finite element model with cubic shape functions that yield nearly identical results between numerical and experimental outcomes in the case of fatigue-resistant design for a bi-axially tensioned structural joint.

Topology optimization, stress constraints, Reliability analysis, low-cycle fatigue, fatigueplasticity

This study presents a general computational framework for topology optimization under constraints related to various engineering design problems, including: reliability analysis, low-cycle fatigue assessment, and stress limited analysis. Such a framework aims to facilitate comprehensive engineering design considerations by incorporating traditional constraints such as displacement and stress alongside probabilistic assessments of fatigue failure and the complex behaviors exhibited by structures made of elastoplastic material. The framework's amalgamation of diverse analytical components offers engineers a versatile toolkit to address intricate design challenges. Notably, the inclusion of reliability analysis introduces a probabilistic perspective, transforming conventional design constraints into random parameters, thereby enhancing the robustness of the design process.

Key to the framework's efficacy is its implementation using MATLAB mathematical computing software, leveraging the platform's efficient code execution and object-oriented programming paradigm. This choice ensures an intuitive and potent environment for designers and researchers, facilitating seamless adaptation across various engineering applications. Additionally, the proposed previously by the Authors algorithm for the topology optimization is extended by adaptive strategy allowing for efficient adjustment of an amount of material removed at individual optimization step.

The presented framework is offering a comprehensive and integrated approach to address multifaceted design challenges while enhancing design robustness and efficiency.

Topology optimization, Stress constraints, First order reliability analysis, Low-cycle fatigue, Plasticity

In contemporary design practices, building structures are expected to not only meet safety requirements but also be optimized. However, optimal designs can be highly sensitive to random variations in model parameters and external actions. Solutions that appear effective under nominal conditions may prove inadequate when parameter randomness is considered. To address this challenge, the concept of robust optimization has been introduced, which extends deterministic optimization formulations to incorporate the random variability of parameter values. In this study, we demonstrate the applicability of robust optimization in the design of building structures using a simple orthogonal frame as an example. The static-strength analysis is conducted based on the displacement method, utilizing second-order theory. To assess the safety level of the steel frame, a preliminary evaluation is performed by determining the reliability index and failure probability using the Monte Carlo Method. Robust optimization is then employed, leveraging the second-order response surface. Experimental designs are generated following an optimal Latin hypercube plan. The proposal of a mathematical-numerical algorithm for solving the optimization problem while considering the random nature of design parameters constitutes the innovative aspect of this research.

reliability, robust optimization, second order theory, displacement method

In line with the principles of modern design a building structure should not only be safe but also optimized. In deterministic optimization, the uncertainties of the structures are not explicitly taken into account. Traditionally, uncertainties of the structural system (i.e. material parameters, loads, dimensions of the cross-sections) are considered by means of partial safety factors specified in design codes. Worth noticing, that optimal structures are sensitive to randomness design parameters and deterministic optimal solutions may lead to reduced reliability levels. It therefore seems natural to extend the formulation of deterministic optimization with the random scatter of parameter values. Such a formulation is offered by robust optimization and reliability-based design optimization. The applicability of RBDO is strongly dependent on the availability of the joint probability density function. A formulation of non-deterministic optimization that better adapts to the design realities is robust optimization. Unlike RBDO optimization, this formulation does not require estimation of failure probabilities. In the paper using the examples of steel beams, the authors compare the strengths and weaknesses of both formulations.

first order reliability method, reliability index, reliability-based design optimization, robust optimization

Cross-sectional transmission electron microscopy studies often reveal a-type dislocations located either below or above the interfaces in
InGaN/GaN structures deposited along the [0001] direction. We show that these dislocations do not emerge during growth but rather are a
consequence of the stress state on lateral surfaces and mechanical processing, making them a post-growth effect. In cathodoluminescence mapping, these defects are visible in the vicinity of the edges of InGaN/GaN structures exposed by cleaving or polishing. Finite element cal-culations show the residual stress distribution in the vicinity of the InGaN/GaN interface at the free edge. The stress distribution is discussed in terms of dislocation formation and propagation. The presence of such defects at free edges of processed devices based on InGaN layers may have a significant negative impact on the device performance.

Luminescence ,Transmission electron microscopy ,Focused ion beam ,Semiconductor materials ,Epitaxy ,Crystal structure ,Crystal lattices ,Crystallographic defects,Mechanical stress,X-ray diffraction

Computer vision (CV) methods for measurement of structural vibration are less expensive, and their application is more straightforward than methods based on sensors that measure physical quantities at particular points of a structure. However, CV methods produce significantly more measurement errors. Thus, computer vision-based structural health monitoring (CVSHM) requires appropriate methods of damage assessment that are robust with respect to highly contaminated measurement data. In this paper a complete CVSHM framework is proposed, and three damage assessment methods are tested. The first is the augmented inverse estimate (AIE), proposed by Peng et al. in 2021. This method is designed to work with highly contaminated measurement data, but it fails with a large noise provided by CV measurement. The second method, as proposed in this paper, is based on the AIE, but it introduces a weighting matrix that enhances the conditioning of the problem. The third method, also proposed in this paper, introduces additional constraints in the optimization process; these constraints ensure that the stiff ness of structural elements can only decrease. Both proposed methods perform better than the original AIE. The latter of the two proposed methods gives the best results, and it is robust with respect to the selected coefficients, as required by the algorithm.

computer vision,structural health monitoring,physics-based graphical models,augmented inverse estimate,model updating,non-negative least square method

The contents of this special issue comprise four research papers devoted to engineering optimization, three of which were presented during the 2nd edition of the Workshop on Engineering Optimization (WEO-2021). The workshop was held in Warsaw, Poland, on October 7–8, 2021. Due to the COVID-19 pandemic, the 2021 edition of the workshop was organized in a hybrid form and was dedicated to the exchange of experiences in the field of engineering optimization including its theoretical and algorithmic aspects as well as practical applications. The workshop hosted six invited lectures and six thematic sessions. 21 presentations by authors from seven European and non-European countries (50% of them from outside Poland) were delivered.
Additionally, the organization of the second edition of WEO was supported by the project entitled Development of regional network on autonomous systems for structural health monitoring financed by the Visegrad Fund, under the grant agreement 22110360. More details on the workshop and the V4SHM project can be found on the following website: http://v4shm.ippt.pan.pl.

The objective of this study is to propose a relatively simple and efficient method for reliability based topology optimization for structures made of elasto-plastic material. The process of determining the optimal topology of elasto-perfectly plastic structures is associated with the removal of material from the structure. Such a process leads to weakening of structural strength and stiffness causing at the same time increase the likelihood of structural failure. An important aspect of engineering design is to track this probability during the optimization process and not allow the structure safety to exceed a certain level specified by the designer. The purpose of this work is to combine the previously developed yield-limited topology optimization method with reliability analysis using first order approach. Effectiveness of the proposed methodology is demonstrated on benchmark problems proposed by Rozvany and Maute, and the elasto-plastic topology design of L-shape structure which is frequently used in different approaches for stress constrained topology optimization.

topology optimization, reliability analysis, elasto-plastic analysis

This paper proposes a computationally effective framework for load‐dependent optimal sensor placement in large‐scale civil engineering structures subjected to moving loads. Two common problems are addressed: selection of modes to be monitored and computational effectiveness. Typical sensor placement methods assume that the set of modes to be monitored is known. In practice, determination of such modes of interest is not straightforward. A practical approach is proposed that facilitates the selection of modes in a quasi‐automatic way based on the structural response at the candidate sensor locations to typical operational loads. The criterion used to assess sensor placement is based on Kammer's Effective Independence (EFI). However, in contrast to typical implementations of EFI, which treat the problem as a computationally demanding discrete problem and use greedy optimization, an approach based on convex relaxation is proposed. A notion of sensor density is applied, which converts the original combinatorial problem into a computationally tractable continuous optimization problem. The proposed framework is tested in application to a real tied‐arch railway bridge located in central Poland.

optimal sensor placement, effective independence method, Fisher information matrix

This study is devoted to a novel method for topology optimization of elastoplastic structures subjected to stress constraints. It should be noted that in spite of the classical solutions of the different type of elastoplastic topology problems are more than 70 years old, the integration of the Prandtl-Reuss constitutive equations into the topology optimization process is not very often investigated in the last three decades. In the presented methodology where the classical variational principles of plasticity and the functor-oriented programming technique are applied in topology design, the aim is to find a minimum weight structure which is able to carry a given load, fulfills the allowable stress limit, and is made of a linearly elastic, perfectly plastic material. The optimal structure is found in an iterative way using only a stress intensity distribution and a return mapping algorithm. The method determines representative stresses at every Gaussian point, averages them inside every finite element using the von Mises yield criterion, and removes material proportionally to the stress intensities in individual finite elements. The procedure is repeated until the limit load capacity is exceeded under a given loading. The effectiveness of the methodology is illustrated with three numerical examples. Additionally, different topologies are presented for a purely elastic and an elastoplastic material, respectively. It is also demonstrated that the proposed method is able to find the optimal elastoplastic topology for a problem with a computational mesh of the order of tens of thousands of finite elements.

topology optimization,elastoplastic structures,minimum-weight design,stress constraints

The paper deals with a novel approach to development of optimality criteria based finite element code for topology optimization of elasto-plastic structures. The novelty of this work is related to the concept of function object called functor and its application to efficient FE code development. First, the general problem of topology optimization under stress constraints is briefly formulated. Then, the programming aspects of topology optimization using traditional object-oriented and functor based programming are discussed. The advantages of the functor based approach are related to simplicity of designing the FE code architecture and reusability of this code. In particular the metric known as 'Lack of cohesion of methods' is useful in comparing these two different paradigms. Finally, the paper is also illustrated with numerical examples of topology optimization using the proposed methodology.

topology optimization, function object, functor programming, optimal design, elasto-plastic structures, finite element programming

The purpose of this study is to present an optimal design procedure for elasto-plastic structures subjected to impact loading. The proposed method is based on mode approximation of the displacement field and assumption of constant acceleration of impacted structure during whole time of deformation process until the plastic displacement limit is reached. Derivation of the method begins with the application of the principle of conservation of linear momentum, followed by determination of inertial forces. The final stage of the method utilizes an optimization technique in order to find a minimum weight structure. Eventually, effectiveness and usefulness of the proposed method is demonstrated on the example of a planar truss structure subjected to dynamic loading caused by a mass impacting the structure with a given initial velocity.

structural dynamics, optimal design, elasto-plastic structures, short-time dynamic loading

The main purpose of the study is an assessment of computational efficiency of selected numerical methods for estimation of vibrational response statistics of a large multi-bearing turbo-generator rotor-shaft system. The effective estimation of the probability distribution of structural responses is essential for robust design optimization and reliability analysis of such systems. The analyzed scatter of responses is caused by random residual unbalances as well as random stiffness and damping parameters of the journal bearings. A proper representation of these uncertain parameters leads to multidimensional stochastic models. Three estimation techniques are compared: Monte Carlo sampling, Latin hypercube sampling and the sparse polynomial chaos expansion method. Based on the estimated values of the first four statistical moments the probability density function of the maximal vibration amplitude is evaluated by the maximal entropy principle method. The method is inherently suited for an accurate representation of the probability density functions with an exponential behavior, which appears to be characteristic for the investigated rotor-shaft responses. Performing multiple numerical tests for a range of sample sizes it was found that the sparse polynomial chaos method provides the best balance between the accuracy and computational effectiveness in estimating the unknown probability distribution of the maximal vibration amplitude.

stochastic moment estimation, sparse polynomial chaos expansion, maximum entropy principle, rotor, uncertainties, hybrid mechanical model, random unbalance distribution

The NUMPRESS System has been developed in IPPT PAN as a result of a project financially supported by European Regional Development Fund (within the Innovative Economy Programme) and is dedicated to small and middle enterprises dealing with sheet metal forming. The program consists of (i) an analytical module for analysis of forming processes with the finite element method, (ii) an optimization module controlling execution of the analytical module and performing optimization with respect to selected process parameters, in both deterministic and robust formulation, (iii) a reliability analysis module controlling execution of the analytical module to assess how random distribution of design parameters affects forming results, and (iv) a graphical user interface enabling communication between modules and easy definition of design parameters and optimization criteria. The analytical module consists of two independent programs up to the user's choice: NUMPRESS-Flow, a faster and less accurate program for implicit quasi-static analysis of rigid-viscoplastic shells (based on the flow approach) and NUMPRESS-Explicit, a program for explicit dynamical analysis of elastic-plastic and elastic-viscoplastic shells. Both programs are interfaced to a well-known commercial graphical pre- and postprocessor GiD. Fundamentals of formulations employed in the system and numerical examples are presented in the paper.

sheet metal forming, finite element method, deterministic and robust design optimization, reliability analysis

The commonly observed nowadays tendency to weight minimization of rotor-shafts of the rotating machinery leads to a decrease of shaft bending rigidity making a risk of dangerous stress concentrations and rubbing effects more probable. Thus, a determination of the optimal balance between reducing the rotor-shaft weight and assuring its admissible bending flexibility is a major goal of this study. The random nature of residual unbalances of the rotor-shaft as well as randomness of journal-bearing stiffness have been taken into account in the framework of robust design optimization. Such a formulation of the optimization problem leads to the optimal design that combines an acceptable structural weight with the robustness with respect to uncertainties of residual unbalances – the main source of bending vibrations causing the rubbing effects. The applied robust optimization technique is based on using Latin hypercubes in scatter analysis of the vibration response. The so-called optimal Latin hypercubes are used as experimental plans for building kriging approximations of the objective and constraint functions. The proposed method has been applied for the optimization of the typical single-span rotor-shaft of the 8-stage centrifugal compressor.

Rotor-shaft system, Robust design optimization, Lateral vibrations, Rubbing effects, Random unbalance distribution

The main objective of the presented study is an evaluation of the effectiveness of various methods for estimating statistics of rotor-shaft vibration responses. The computational effectiveness as well as the accuracy of statistical moment estimation are essential for efficient robust design optimization of the rotor-shaft systems. The compared methods include sampling techniques, the perturbation approach, the dimension reduction method and the polynomial chaos expansion method. For comparison, two problems of the rotor-shaft vibration analysis are considered: a typical single-span rotor-shaft of the 8-stage centrifugal compressor driven by the electric motor and a large multi-bearing rotor-shaft system of the steam turbo-generator. The most important reason for the observed scatter of the rotor-shaft vibration responses is the inherently random nature of residual unbalances as well as stiffness and damping properties of the journal bearings. A proper representation of these uncertain parameters leads to multidimensional stochastic models. It was found that methods that provide a satisfactory balance between the estimation accuracy and computational effectiveness are sampling techniques. On the other hand, methods based on Taylor series expansion in most of the analysed cases fail to approximate the rotor-shaft response statistics.

Scatter analysis, rotor-shaft vibrations

The aim of this paper is to create new type of plastic limit design procedures where the influence of the limited load carrying capacity of the beam-to-column connections of elasto-plastic steel (or composite) frames under multi-parameter static loading and probabilistically given conditions are taken into consideration. In addition to the plastic limit design to control the plastic behaviour of the structure, bound on the complementary strain energy of the residual forces is also applied. If the design uncertainties (manufacturing, strength, geometrical) are taken into consideration at the computation of the complementary strain energy of the residual forces the reliability based extended plastic limit design problems can be formed. Two numerical procedures are elaborated. The formulations of the problems yield to nonlinear mathematical programming which are solved by the use of sequential quadratic algorithm.

reliability analysis, limit analysis, residual strain energy, Monte Carlo simulation, optimal design

In the paper a stochastic method for fault detection and identification in the shafts of rotating machines is proposed. This approach is based on the Monte Carlo simulations of rotor-shaft lateral–torsional–longitudinal vibrations mutually coupled by transverse cracks of various possible and randomly selected depths and locations on the shaft. For this purpose the structural hybrid model of a real faulty object is applied. This model is characterized by a high practical reliability and great computational efficiency, so important for many hundred thousand single numerical simulations necessary for a creation of the databases applied for inverse problem solution finally leading to crack identification. These databases are created with an arbitrary assumed probability densities of crack parameters which ensures appropriate spread of the dynamic responses of the considered faulty mechanical system. A sufficiently large database determined for the investigated object enable us to estimate almost immediately, i.e. within less than 1 s, the crack depth and axial position with identification errors not exceeding 9% and 5%, respectively. Thus, the proposed method seems to be a very convenient diagnostic tool for engineering applications in the industry.

Rotor-shaft system, Dynamic diagnostics, Crack identification, Monte Carlo simulation, Coupled vibration analysis

In the paper several stochastic methods for detection and identification of cracks in the shafts of rotating machines are proposed. All these methods are based on the Monte Carlo simulations of the rotor-shaft lateral-torsional-longitudinal vibrations mutually coupled by transverse cracks of randomly selected depths and locations on the shaft. For this purpose there is applied a structural hybrid model of a real cracked rotor-shaft. This model is characterized by a high practical reliability and great computational effi-ciency, so important for hundreds of thousands numerical simulations necessary to build databases used in solving the inverse problem, i.e. crack parameter identifications. In order to ensure a good identification accuracy, for creating the Monte Carlo samples of data points there are proposed special probability density functions for locations and depths of the crack. Such an approach helps in enhancing databases corresponding to the most probable faults of the rotor-shaft system of the considered rotor machine. In the presentedstudy six different database sizes are considered to compare identification efficiency and accuracy of considered methods. A sufficiently large database enables us to estimate almost immediately (usually in less than one second) the crack parameters with precision that is in most of the cases acceptable in practice. Then, as a next stage, one of the proposed fast improvement algorithms can be applied to refine identification results in a reasonable time. The proposed methods seem to provide very convenient diagnostic tools for industrial applications.

Crack rotor dynamics, Nonlinear and parametric vibrations, Hybrid modeling, Monte Carlo simulation, Crack identification methods

An assessment of structural reliability requires multiple evaluations of the limit state function for various realizations of random parameters of the structural system. In the majority of industrial applications the limit state functions cannot be expressed explicitly in terms of the random parameters but they are specified using selected outcomes of the FE analysis. In consequence, in order to be useful in practice, a structural reliability analysis program should be closely integrated with a FE module or it should be interfaced with an advanced external FE program. When the FE source code is not available, which is usually the case, the only option is to establish a communication between the reliability analysis program and an external FE software through the batch mechanism of data modification, job submission and results extraction. The main subject of this article is to present the reliability analysis capabilities of STAND software, which is being developed in the Institute of Fundamental Tech no logical Research of Polish Academy of Sciences. A special emphasis is put on the issues related to it s interfacing with external general purpose FE codes. It is shown that when shape type random variables are used, leading to modifications of the FE mesh, or when the limit state function contains numerical noise, standard algorithms for localizing the design point often fail to converge and a special method based on some response surface approximation is needed. A proposition of such a strategy that employs an adaptive response surface approximation of the limit state function is presented in this article. Development of a reliability analysis program is a challenging project and calls for such a code organization, which would facilitate a simultaneous work of many programmers and allow for easy maintenance and modifications. The so-called object-oriented programming seems to provide a convenient framework to realize these objectives. The object-oriented approach is used in STAND development. The advantages of this programming paradigm and a short description of the STAND’s class hierarchy are presented in the text. The study is concluded with two numerical examples of interfacing STAND with state of the art commercial FE programs.

Reliability, optimization software

The aim of this paper is to take into consideration the influence of the limited load carrying capacity of the connections on the plastic limit state of elasto-plastic steel (or composite) framed structures under multi-parameter stochastic loading and probabilistically given conditions. In addition to the plastic limit design to control the plastic behaviour of the structure, bound on the complementary strain energy of the residual forces is also applied. This bound has significant effect for the load parameter. If the design uncertainties (manufacturing, strength, geometrical) are expressed by the calculation of the complementary strain energy of the residual forces a reliability based extended limit design problem is formed. The formulations of the problems yield to nonlinear mathematical programming which are solved by the use of sequential quadratic algorithm. The bi-level optimization procedure governed by the reliability index calculation.

limit analysis of frames, reliability analysis, optimization

Possibly the most common application of spot welding is in the automobile manufacturing industry, where it is almost universally used to weld the sheet-metal car components. However, due to manufacturing inaccuracies and fatigue failures an important number of spot welds may be missing in an operational vehicle. It seems that to properly analyse the reliability of such structures, in particular crashworthiness reliability, the spot weld failures must be considered. Representing properties of each spot weld in a stochastic model by corresponding random variables is extremely inefficient. Therefore, in this article an approach is proposed for handling spot-weld defects in the reliability analysis by accounting for their averaged influence on a failure criterion. The approach consists of the appropriate treatment of a random noise component of the limit state function. The noise results from the strategy of deleting a certain number of randomly selected spot-weld elements from the finite element model each time the limit state function value is computed. Dealing with noisy limit state functions in structural reliability analysis is a challenging task. The only method that seems to be insensitive to this phenomenon is Monte Carlo sampling, which for most of the applications of practical interest is prohibitively expensive. Having this in mind, a method based on the algorithm proposed by Zou et al. and published in the journal of Reliability Engineering and System Safety in 2002 is investigated in this article. The method combines the best features of the first-order reliability method, the response surface technique and the importance sampling method to achieve both accuracy and efficiency. A detailed study on the reliability of thin-walled s-rail subjected to crash is performed. Some suggestions concerning the modification of the original algorithm are proposed.

crashworthiness reliability, response surface approximation, adaptive importance sampling, spot weld failures

Gradient-based optimization methods are still most efficient methods for solving structural optimization problems. The sensitivity formulation has been one of the central issues in the gradient-based optimization algorithm. Thermo-viscoelastic constitutive and parameter sensitivity formulation are presented in this paper. The model considered is composed of two coupled subproblems: the transient heat transfer problem and a rheological, viscoelastic material model known in literature as the standard model. Design variables considered are with material and shape-defining parameters. The investigation includes a finite element formulation and implementation in an object-oriented finite element environment. Results of numerical analysis are presented.

Finite element method, Sensitivity analysis, Viscoelasticity

This contribution considers the problem of topology optimization of modular structures. A bionic trunk-like robotic “Arm-Z” manipulator is considered. The manipulator is modular, that is, it is composed of a sequence of identical modules. In geometric terms, each module is essentially an obliquely cut section of an elliptical pipe, so in the cutting plane it forms a circle. With respect to the previous module, it has a single degree of freedom: the relative twist. Therefore, the total number of the degrees of freedom of the entire manipulator equals the number of its modules. Such a manipulator belongs to the family of Extremely Modular Systems. The advantages of such systems are the economization (due to the possible mass production of modules) and robustness (replacement of a failed module instead of a complex repair).

Topology optimization, Modular manipulator, Multiple loadings, Geometric transformations, Kinematics, Stress constraints.

In the present study a comparison of frequently used computer vision (CV)-based methods for structural health monitoring of truss structures is shown. The attention is paid to template matching methods that can be classified into one of two groups: area-based and feature-based methods. Synthetic but realistic video is used in this study. Results of the comparison are reliable due to the fact that the exact displacements are known from the finite element model of the investigated structure. From the variety of tested CV methods, the Kanade–Lucas–Tomasi algorithm with FREAK-based repetitive correction outperforms the remaining tested methods in terms of the computation time with a negligibly greater estimation error.

computer vision, structural health monitoring, physics-based graphics models (PBGM), IC-SHM 2021, benchmark test

Performance of any Structural Health Monitoring (SHM) system strongly depends on a set of sensors which are distributed over the structure under investigation. Optimal deployment of sensors on large scale structures such as tied-arch bridges is quite a challenging problem. Moreover, deployment of a sensor network consisting of different types of sensors (accelerometers, inclinometers or strain gauges) over a large scale bridge renders the task of optimization even more demanding. In the present study, a conventional sensor placement method for distribution of a homogenous sensor network is expanded to the heterogeneous case. First, the basic equations governing the estimation error will be recalled. Then, the Fisher information matrix is assembled using normalized translational and rotational mode shapes. Finally, a computational procedure is proposed which allows optimal sensor positions to be selected among thousands candidate locations. The effectiveness of the proposed strategy is demonstrated using a realistic example of a tied-arch bridge located in Poland.

optimal sensor placement, structural health monitoring, tied-arch bridges, multi-type sensor network

The success of virtually all structural health monitoring (SHM) methods depends on the information content of the measurements, and thus on the placement of the available sensors. This paper presents an efficient method for finding optimal sensor distribution over structural system with many degrees of freedom (DOFs). The objective function is based on the classical Fisher information matrix. Originally, this yields a computationally hard discrete optimization problem. However, the proposed numerical solution method is based on a concept taken from structural topology optimization, where a discrete optimization problem is replaced with a continuous one. Two numerical examples demonstrate the effectiveness of the proposed methodology. These are a 5-bay truss with 24 DOFs and a two-story frame structure whose finite element model has been condensed to 14 DOFs.

Damage identification attracted a lot of attention during the last three decades. The reason for that is the fact that large number of existing civil infrastructures reached their service life and growing number of structures is equipped with Structural Health Monitoring (SHM) systems. A successful structural damage identification is determined by three inseparably coupled factors: sensor placement, damage location and its extend, and finally location and time-frequency characteristics of the applied excitation. The purpose of this study is to address the first of the mentioned aspects, namely optimal sensor placement. A vast literature has been devoted to optimal sensor placement methods among which Effective Independence (EI) method proposed by Kammer and Tinker is one of the most successfully applied in practice. However, EI method is dedicated rather to test-analysis correlation and therefore more specific methods for damage identification are still needed. Additionally, in the case of large civil structures, which are intended to be equipped with large amount of sensors of different type, other sensor placement methods can be more efficient. Recently, a promising idea of utilizing a topology optimization approach for the purpose of sensor placement has been proposed by Bruggi and Mariani. The goal of this study is to extend their method, which has been verified on a plate structure, to the case of a FE model of a real arch bridge structure consisting a few thousands degrees of freedom. The main purpose of this work is to find the optimal arrangement of sensors on the structure to detect defects most accurately. The objective function for the problem formulated in this way is the total, weighted difference between the deformation of a damaged and undamaged state. This problem is very similar to the topological optimization, where we search for the optimal material distribution minimizing the mass of the structure while meeting the conditions related to some mechanical properties such as the maximum displacement of the structure, stress intensity or load capacity. This similarity led us to apply topological optimization to the problem of optimal placement of damage sensors. Several numerical examples prove the applicability of topological optimization for optimal sensor placement problem.

Sensor Placement, Damage Identification, Topology Optimization

Recent progress in sensing technology and measurement techniques allows a growing number of critical infrastructures to be equipped with Structural Health Monitoring (SHM) systems. Sensors in such SHM systems should be placed in a proper way to facilitate extracting valuable information from the structure under investigation. In the case of relatively simple spatial truss structures, sensors can be located with the aid of classical methods such as Effective Independence (EI) method proposed by Kammer. However, in the case of large structures, which are intended to be equipped with hundreds if not thousands of sensors, other sensor placement methods may be needed.
The goal of this study is to extend a topology optimization based approach for sensor placement (proposed originally by Mariani and co-workers) to the case of real bridge structures represented by finite element models with a few thousand degrees of freedom. Structural topology optimization aims to find the optimum material distribution in order to minimize the mass of the structure while maintaining mechanical properties (load capacity, displacements, etc.). A similar concept can be used to determine the optimal placement of sensors in a structure to identify its dynamic characteristics. The sensor positions are determined in such a way that estimation error of modal coordinates is minimized. The effectiveness of the proposed methodology is demonstrated on an example of a detailed FE model of a tied-arch bridge.

Optimal sensor placement, Structural parameter identification, Topology optimization

This paper present elasto-plastic topology optimization with reliability constraint. It recalls fundamental concepts from first order reliability analysis and introduces an algorithm for topology optimization of elasto-plastic structures. The presented numerical example shows dependence of the volume fraction on probability of failure.

Structural topology optimization, Elastoplastic analysis, Reliability based optimization

Optimal topologies obtained for structures subjected to deterministic loading can be sensitive to loading variations in terms of both magnitude and direction. Therefore, in this study we consider problem of topology optimization for structures subjected to probabilistic loading. The proposed method applies basic findings from probability theory, which allow to transform the original problem of topology optimization under single probabilistic loading into analogous problem of topology optimization under multiple deterministic loading cases. After recalling the theoretical background of the method,' its effectiveness is demonstrated on an examples of cantilever structure subjected to horizontally oriented load with randomly varying angle of action.

Topology optimization, Stochastic load, Elastoplastic FE analysis

The purpose of this study is a practical engineering formulation of the topology optimization problem for three dimensional elastoplastic structures. The present study constitutes a comprehensive approach to topology optimization of elastoplastic structures, including both the mechanical problem statement and its efficient computer implementation. Instead of the traditional approach based on compliance minimization the aim of this work is to find a minimum weight structure, which is able to carry a given load while satisfying the condition that the corresponding stresses do not exceed an allowable limit. The general form of the problem is based on the classical limit design formulations of plasticity. The proposed method finds the optimal structure in an iterative way using only stress intensity distribution and does not require from the User explicit knowledge of any gradients or sensitivities. The effectiveness of the proposed methodology has been illustrated on two representative examples including simply supported and cantilever beams.

topology optimization, computational morphogenesis, elastoplastic FE analysis

The commonly observed nowadays tendency to weight minimization of rotor-shafts of the rotating machinery leads to a decrease of shaft bending rigidity making a risk of dangerous stress concentrations and rubbing effects more probable. Thus, a determination of the optimal balance between reducing the rotor-shaft weight and assuring its admissible bending flexibility is a major goal of this study. The random nature of residual unbalances of the rotor-shaft as well as randomness of journal bearing stiffness have been taken into account in the framework of robust design optimization. Such a formulation of the optimization problem leads to the optimal design that combines an acceptable structural weight with the robustness with respect to uncertainties of residual unbalances, the main source of bending vibrations causing the rubbing effects. The applied robust optimization technique is based on using Latin hypercubes in scatter analysis of the vibration response. The so-called optimal Latin hypercubes are used as experimental plans for building kriging approximations of the objective and constraint functions. The proposed method has been applied for the optimization of the typical single-span rotor-shaft of the 8-stage centrifugal compressor.

Rotor-shaft system, robust design optimization, lateral vibrations, rubbing effects, random unbalance distribution

The topic of smart civil infrastructure has attracted significant attention. An important component of such structural systems is the network of sensors used to monitor the structure and deliver information about its current health status. The task of optimal sensor placement is not trivial due to the discrete, combinatorial nature of the problem. The brute force search is unfeasible for large structures, which calls for approximate and heuristic approaches. This problem has been investigated for several decades, beginning probably with the landmark 1978 paper of Shah [1]. A recent review can be found in [2].

The criteria typically used for assessing candidate placements are based either on Kammer’s Effective Independence (EFI) and the Fisher Information Matrix (FIM) [3], and quantify the amount of information provided by sensors, or on covariance matrices obtained within the Kalman filtering procedure used to quantify the uncertainty of the unknown response of interest being estimated [4]. However ingenious, most of the proposed procedures are computationally costly in large-scale problems.

This talk will discuss two optimal placement methods that have been recently developed with the objective of computational efficiency [5, 6]. One of them is based on Kalman filter covariance matrices and has—instead of typically quadratic—a linear complexity in the number of potential sensor locations. The other method uses the technique of convex relaxation to represent the problem in a computationally tractable continuous form and speed up the solution procedure even further. The presented application examples will use models of bridge structures.

[1] P.C. Shah, F.E. Udwadia, A methodology for optimal sensor locations for identification of dynamic systems, J. Appl. Mech. 45(1), 188–196 (1978)
[2] Y. Tan, L. Zhang, Computational methodologies for optimal sensor placement in structural health monitoring: A review, Struct. Health Monit. 19(4), 1287–1308 (2020)
[3] D.C. Kammer, Sensor placement for on-orbit modal identification and correlation of large space structures, J. Guid. Control Dyn. 14(2), 251–259 (1991)
[4] C. Zhang, Y.-L. Xu, Optimal multi-type sensor placement for response and excitation reconstruction, J. Sound Vib. 360, 112–128 (2016)
[5] B. Błachowski, A. Świercz A., M. Ostrowski, P. Tauzowski, P. Olaszek, L. Jankowski, Convex relaxation for efficient sensor layout optimization in large-scale structures subjected to moving loads, Comput.-Aided Civ. Inf. 35(10), 1085–1100 (2020)
[6] B. Błachowski, A. Świercz, P. Olaszek, Ł. Jankowski, Implementation of multi-type sensor placement strategy for large-scale engineering structures, 10th ECCOMAS Thematic Conference on Smart Structures and Materials (SMART 2023), July 3–5, 2023, Patras, Greece, pp. 498–506 (2023)

This study deals with topology optimization of spatial robotic manipulator, the geometry of which was
proposed initially in [1]. The manipulator consists of serially connected modules in a form of a
cylinder cut at a certain angle at its ends. The manipulator constructed in this way allows for relative
rotation of adjacent modules, which gives one degree of freedom per module. The operation of overall
robotic system resembles the elephant trunk manipulator. Previous research involved the possible
kinematic transformations of the manipulator [2], but not its structural optimization [3]. However,
structural design of the involved modules is a challenging task, as the process has to take into account
the current configuration of the module along the manipulator, which results in variable internal force.
It leads to optimization problem under multiple loading conditions with a significantly large number of
loads. This study considers optimal topology of such a modular manipulator structure. Due to the large
variety of possible load conditions, the initial analysis involves a 3D model of the structure with a
continuous set of possible arrangements of individual modules. An additional constraint imposed on
the solution will take into account the symmetry of the optimal topology of a single module, which is
dictated by manufacturing considerations.

optimal topology, modular systems, engineering software

The aim of the paper is a practical engineering formulation of the topology optimization for
structures made of elastoplastic material. This paper provides a comprehensive approach to
optimizing the topology of elastoplastic structures, including both the problem statement and its
efficient computer implementation. Instead of the traditional compliance minimization approach,
the aim of this work is to find a structure with the minimum mass that can carry on a given load,
provided that the corresponding stresses do not exceed an acceptable limit. The general formulation
of the problem is based on the classical approach allowing to determine the yield strength of the
designed structure [4]. The proposed method finds the optimal structure in an iterative way, using
only the stress intensity distribution and does not require the user to explicitly know sensitivity.

topology optimization, stress constraints, optimal design

In practice, the broadly used finite element (FE) models can have very large number of degrees of freedom (DOFs). A small subset of DOFs representing sensor locations that provides an extremum of a selected objective function corresponding to a metric of the expected measurement accuracy is sought. Thus, optimal sensor placement is characterized by its complex combinatorial nature and tremendous computational effort required. With the aid of convex relaxation, the proposed approach allows one to transform the original combinatorial problem into its continuous counterpart, which requires smaller computational effort – by a few orders of magnitude than famous Effective Independence method. The effectiveness of the method has been demonstrated using an example of a FE model of an existing railway bridge. First, the FE model has been calibrated with measured responses of the bridge under the moving load of a passing train. Then, sensor layout has been obtained in such a way that it optimises the estimate of modal coordinates of the mode shapes participating most significantly in the measured structural response. The authors acknowledge the support of the National Science Centre, Poland (grant agreement 2018/31/B/ST8/03152).

This contribution concerns a snake-like robotic manipulator arm proposed first in [1]. The manipulator is composed of linearly but nonaxially joined identical modules with a possibility of relative twist, which amounts to one degree of freedom per module. It is an example of an extremely modular system [2], and its advantages are: economization (due to modularity and possible mass production) and robustness (easy repair by replacement of a failed module). The hitherto research involved the possible geometric transformations of the manipulator arm [3], but not its structural optimization. However, structural design of the involved modules is a challenging task, as the process has to take into account the relative position of the module along the arm, as well as the variety of global configurations of the deployed manipulator. It leads to a multi-load structural optimization problem with a significantly large number of loads. This contribution considers topology optimization of such a modular manipulator structure. Due to the large variety of possible load conditions, the initial analysis involves a 2D model of the structure with a discrete set of two possible relative arrangements of adjacent modules. Such a formulation allows the proposed approach to be preliminarily explored, tested and optimized in a numerically manageable simplified environment. The support of the National Science Centre, Poland, granted under the grant agreement 2019/33/B/ST8/02791 is gratefully acknowledged.

To solve the problem of reliability-based topological optimization, a heuristic algorithm was used, consisting in removing redundant material in the areas with the lowest stress intensity. In this algorithm, the design variables represent the material densities in the individual finite elements. The material is removed by reducing the density of finite elements as a function of the stress intensity.

topology optimization, reliability analysis, first order approximation

Despite significant advances in structural health monitoring (SHM), the design of contact sensor networks and their power supply for large-scale structures is still expensive and difficult. Due to the recent progress in computer vision (CV) it is possible to monitor structural components or even whole structures with the aid of digital cameras that allow to avoid the use of the contact sensors. However, CV-based measurements have a significantly lower accuracy than the techniques based on the contact sensors. Moreover, the amount of benchmark data available for development, testing and comparison of CV-based methods is limited. This problem has been partially overcome in recent years by the use of the physics-based graphical models (PBGM) in generation of synthetic but realistic video data. In this work, a comparison of two popular methods of CV-based object tracking applicable in SHM is discussed. PBGM-based videos used in this study are a part of The 2nd International Competition for Structural Health Monitoring'. Exact structural displacements are available due to the fact that PBGM-based video are generated using the structural model. Hence, calculation of the error metrics is straightforward and reliable. The PBGM-based videos show a spatial truss subjected to an unknown excitation.

In the present study a benchmark test of selected methods of template matching-bated methods for computer vision-based object tracking is performed. The attention is paid to compare these methods in terms of estimation of nodal displacements in a flexible truss structure, aiming at assessment of their reliability in Structural Health Monitoring (SHM) applications. Thanks to the use of synthetic but realistic videos generated with the aid of physics-based graphics models (PBGM), exact displacement of tracked structural nodes are known. Therefore, reliable assessment of the accuracy of the examined methods is possible.

computer vision, structural health monitoring, physics-based graphics models (PBGM)

The uNET neural network architecture has shown very promising results when applied to semantic segmentation of biomedical images. The aim of this work is to check whether this architecture is equally applicable to semantic segmentation distinguishing the structural elements of railway viaducts. Artificial images generated by a computer graphics program rendering the 3D model of the viaduct in a photorealistic manner will be used as data sets. This approach produces a large number of
images that provide a solid training set for machine learning model.

Computer vision, deep learning, semantic segmentation

The goal of the project is the development of methodology for reliable identification of different structural defects, including concrete cracks, spalling and delamination. The basic idea of this project combines machine learning and image processing techniques to localize and quantify stiffness degradation with concrete structures. The overall system is intended to operate in fully autonomous way. it is allowed by recent advancement in image capturing utilizing the unmanned ground or aerial vehicles and artificial intelligence.

structural health monitoring, computer vision, crack detection

Plasticity in topology optimization is almost forgotten direction in this popular research area. This paper presents a recently
developed elasto-plastic topology optimization procedure extended with reliability constraint. It recalls fundamental concepts from
reliability analysis and introduces an algorithm for topology optimization of elasto-plastic structures. In addition to the elasto-plastic
constitutive law of the applied material the optimization algorithm includes stress constraints, as well. The presented numerical examples
show dependence of the volume fraction on probability of failure.

In the present study topology optimization with constraints on the probability of failure is presented. The proposed approach allows controlling the safety level during the optimization process. The number of cycles to structural failure in the case of low-cycle fatigue problem is chosen as a constraint. The low-cycle fatigue requires elastic-plastic formulation of the problem, because in the optimized structure the phenomenon related to accumulation of plastic deformation is observed. In order to estimate the probability of failure for this numerically complex problem, the First Order Reliability Method (FORM) is proposed. The above mentioned methodology is implemented in object-oriented code written in MATLAB programming language.

topology optimization, reliability analysis, low-cycle fatigue, object oriented programming

Structural safety is a critical aspect in modern engineering practice. One of the factors leading to the risk of failure is the variability of design parameters. To be able to estimate the risk of failure, this variability should be taken into account in design process. One way to tackle this issue is to assume a random nature of selected design parameters. These parameters can represent: loads acting on a structure, material properties or shape parameters. Minimizing the structural mass in the process of topology optimization is equivalent to removing the material from the initial, usually regular design space. This process can lead also to a reduction of the structural safety. Therefore, apart from deterministic constraints (such as stresses, displacements or load capacity), it is also worth to control the probabilistic ones. The purpose of this work is to introduce in topology optimization of elastoplastic structures an additional constraint on the probability of failure. Deterministic constraints, in the form of constraints on stresses, are imposed on elastoplastic analysis and utilized by the return mapping algorithm. One of the difficulties coming from the application of these random effects in the process topology optimization is its numerical complexity. Topological optimization itself is a complex issue. Adding a structural safety estimation can extend this process significantly. Fortunately, in the field of reliability analysis, which deals with determining reliability, there are methods that allow for relatively fast estimation of the probability of failure. These are First and Second Order Reliability Methods (FORM, SORM). Only several finite element iterations are sufficient to determine the probability of failure. These methods are based on the concept of the design point or the most probable point. This is the point on the limit state surface that lies closest to the mean point, and represents the most probable failure scenario. Moreover, approximation of limit state surface is linear (FORM) or quadratic (SORM). This allows to estimate quite accurately low probabilities of failure. Such a low probability of failure should characterized a safe structure. The search for a design point is based on the iterative formula developed by Rackwitz and Fiesler. The paper will present the formulation of the elasto-plastic problem of structural analysis as well as the detailed description of the algorithm for topology optimization under reliability constraint. The paper will be illustrated by examples, in which we will demonstrate, how probability of failure changes in the topological optimization process.

topology optimization, elasto-plastic structures, reliability analysis, probabilistic design

The present study provides a comprehensive framework for sensor layout optimization aiming at accurate estimation of the modal coordinates coming from the structural response. The proposed procedure consists of two steps briefly described below. The first step is a selection of vibrational modes taking part in the motion of structures during their normal operation – in this case subjected to traveling load. Among these structures there are various types of bridges especially railway bridges. In the case of present study structural responses are obtained from rigorous finite element (FE) model of the bridge. The FE model is calibrated with measured response of real bridge located in Huta Zawadzka. The calibration process is based on the displacement signals of the bridge under the traveling load. In the second step modes of interest are selected and a set of candidate sensor locations is proposed. It is a subset of all degrees of freedom (DOFs) of the FE model from which several locations are chosen as best possible locations for the displacement sensors. The above sensor placement problem is a combinatorial task. Many methods for solving such problems have been developed previously, but in the case of large scale structures they require tremendous computational effort. To reduce this effort the so-called convex relaxation is incorporated into optimization process. The technique consists in reformulation of combinatorial problem into continuous convex one. Then, the convex relaxation is achieved by introducing the so-called sensor density function, which assigns a certain metric for individual candidate sensor location. Next, the value of this function is optimized in such a way that it maximize determinant of the Fisher Information Matrix. It has been shown that above algorithm is very effective and is distributing a number of sensors in several iterations only. Finally, it is worth noting that presented method can be used to distribute sensors for structural health monitoring. Moreover, it can be also applied in modal control strategies in vibration suppression.

This study is devoted to a practical method for topology optimization of elastoplastic structures subjected to stress constraints. Instead of the classical compliance minimization problem the aim of this work is to find a minimum weight structure, which is able to carry given load and the corresponding stresses do not exceed an allowable limit. The general form of the problem is based on the classical limit design formulations of plasticity. The proposed method finds optimal structure in an iterative way using only stress intensity distribution and doesn't require computing of any gradients or sensitivities. Our method starts with determining representative stresses in every quadrilateral finite element. At first an elastoplastic analysis is performed to obtain stress values in four Gaussian points, then by the use of von Misses criterion and these stress values the resultant stress is calculated. Next, having obtained stress intensity distribution within the structure we apply penalization to avoid stress concentration issues. Finally, the material is removed proportionally to the stress intensities of individual finite elements. The above mentioned procedure is repeated until limit load capacity is achieved for a given loading vector. The checkerboard problem is solved by means of design filter. Two benchmark problems have been selected as illustrative examples. They are: cantilever and simply supported beam. For these examples parametric studies on different length to height ratios and support patterns are conducted. Additionally, the results of topology optimization for different values of filter radius and penalty parameter are presented.
Finally, efficient computer implementation based on functor-oriented programming is discussed. It is demonstrated how Functor and Template-based programming can be utilized to create versatile Finite Element environment. Within this environment computation of all element matrices and loading vectors can be called in the same way, this in turn allows for implementation of effective aggregation procedure.

topology optimization, minimum-weight design, functor-oriented programming, stress constraints

The subject of this study is an efficient approach to the development of a finite element framework, which is intended to be used for solving a variety of problems in computational solid mechanics. One of such problems, recently becoming an active field of research, is topology optimization of structures made of elastic-plastic materials. For finding the optimal topology of real, practical and complex structures the knowledge of a number of numerical algorithms is required, to mention a few: modification of finite element meshes, aggregation of tangent stiffness matrices, or direct and iterative solvers. The classical computer implementation of the original Classical Optimality Criteria method (COC) of the topology optimization problem given by Bendsoe and Sigmund is relatively simple and contains 99 lines of code in the MATLAB language. However, it assumes that there exists only a single loading case, single displacement (compliance) constraint, the material is linearly elastic and the optimal topology can be found using the so-called Solid Isotropic Material with Penalization (SIMP) algorithm, which is based on the original COC method. In reality, engineers face a slightly different problem. They need to find the topology of a minimum weight structure subjected to multiple loading cases, made of an elasto-plastic material, and with a limit on stresses. The above mentioned SIMP approach may not lead to an optimal solution.

functor-oriented programming, topology optimization, elastoplastic FE analysis

Classical programming of finite elements contains usual class, which duty is not only to approximate some physical field of interest (displacements, accelerations or temperature), but also definition of matrices necessary for particular analysis. It often leads to sophisticated class hierarchy of finite elements. In our approach matrices necessary for FE analysis are in separate classes. Hierarchy of these classes can be developed almost separately from declaration of the finite element class. Also finite elements hierarchy is much smaller, because each class represents one kind of matrix computed in FE analysis. In our opinion the functor is best suited object for this kind of approach. The functor represents one subroutine and it can also be invoked as function. The study presents application of functor oriented programming to finite element analysis.

stress constrained topology optimization, finite element programming, functor-oriented implemenetation

The interdiffusion of chemical components coupled with vacancy movement can cause void formation and/or spinodal decomposition in crystal growth. In the case of SiC growth on Si, the higher mobility of Si atoms compared to C results in the migration of SiC/Si interface and formation of voids in the substrate in some thermodynamic conditions. In the case of In -rich InGaN layers deposited on GaN a precipitation of metallic indium bordering with voids is observed. In the current approach we consider interdiffusion, lattice distortion and chemical maps extracted from HRTEM images of SiC/Si and InGaN/GaN. Dislocations and void surface are treated as local regions of nucleation and annihilation of the vacancies transporting the mass in FE mesh. In result, the interface and FE mesh are convected with the crystal lattice drift. In the constitutive modeling applied [1] the lattice strain and the atom fraction of chemical component are used as two independent thermodynamic variables. Due to climbing of misfit dislocations the plastic distortion tensor field is taken into account in the form of additional nodal variables. This tensor field is spanned on corner nodes of Lagrangian finite elements (FE) which gives the possibility for reconstruction of the atomistic model of dislocation network interpenetrating the considered FE mesh [2,3]. The chemo-mechanical coupling is based on the use of Vegard's law formulated in terms of Biot strain. Due to the logarithmic strain applied in hyperelastic modeling, some transformation rule is considered for Vegard's law. This rule allowed us to eliminate artificial residual stresses yielding from incompatibe fields of the atom fraction and plastic distortions spanned on nodes by means of shape functions [2]. In the case of single finite elements, the mentioned approach allowed us to reduce spurious stresses in integration points from the level 100 MPa to 10^ -5 MPa, while at the same time holding the stress components yielding from Vegard's law at the level of 1 GPa (relaxed by plastic distortions).

Constitutive modelling, Finite Element Method

In the current approach we consider interdiffusion, lattice distortions and chemical maps corresponding the growth of SiC/Si and In- GaN/GaN layers. Dislocations and free surfaces are treated as local regions for nucleation and annihilation of the vacancies transporting the mass between finite elements (FEs). In result, the interface and FE mesh are convected with the crystal lattice drift. In the constitutive modelling applied [1] the lattice distortion and the Si and vacancy molar fractions are used as independent nodal variables. Due to the climbing down of misfit dislocations the plastic distortion tensor field is taken into account in the form of additional nodal variables. This tensor field is spanned on corner nodes of the second order Lagrangian finite elements [2]. The chemo-mechanical coupling is based on the use of Vegard’s law formulated alternatively in terms of Biot or Hencky strains. Due to the logarithmic strain applied in hyperelastic modelling, some transformation rule is considered for Vegard’s law. This rule allowed us to eliminate artificial residual stresses yielding from incompatibility of the fields of atom fraction and plastic distortions spanned by means of the same shape functions on the corner nodes.

residual stresses, Kirkendall effect, diffusion, mass transport, semiconductor layers, crystal growth

This paper presents NUMPRESS System that has been developed in IPPT PAN as a result of a project financially supported by European Regional Development Fund (within the Innovative Economy Programme) and is dedicated to small and middle enterprises dealing with sheet metal forming. It seems undoubted that efficient design of an industrial sheet forming process requires reliable computer simulations and a tool for numerical optimization of the process parameters. It has to be also admitted that. among small and medium enterprises (SME) in this industrial branch, there are many who do not use any such numerical tools in their practice.
Computer simulation of sheet metal forming processes is a very specific branch of computational mechanics. Finite element systems dedicated strictly to this kind of processes are needed and actually present on the market. Commercial systems (like Autoform, PAM-Stamp, Stampack, etc.) are, due to their prices, usually beyond financial ability of SME.

Design of the drawing process and tools, i.e. choice of proper values of several design parameters, require efficient optimization strategy. In this process, random character of at least some of the parameters has to be taken into account. In view of this fact, the traditional, deterministic approach to optimization is insufficient and elements of robust design optimization techniques and reliability analysis have to be included in the formulation of the optimization problem. It has to be admitted that, even if some of the mentioned commercial simulation systems offer numerical optimization modules, not all of them reach beyond the deterministic concept of the optimization process.

sheet metal forming, finite element method, deterministic and robust design optimization, reliability analysis

This paper presents basic features of the NUMPRESS system and some examples ofuse. The system has been developed at IPPT PAN as a result of a project financially supported by European Regional Development Fund and is dedicated to small and middle enterprises (SME) dealing with sheet metal forming. The program consists of (i) an analytical finite element method module (ii) an optimization module, (iii) a reliability analysis module, and (iv) a graphical user interface enabling communication between modules. The analytical module consists of two independent programs up to the user’s choice: NUMPRESS-Flow, a faster and less accurate program for implicit quasi-static analysis of rigid-viscoplastic shells (based on the flow approach) and NUMPRESS-Explicit, a program for explicit dynamical analysis of elastic-plastic shells. Both programs are interfaced to a well-known commercial graphical pre-and postprocessor GiD.

sheet metal forming, finite element method, deterministic and robust design optimization, reliability analysis

Contrary to higher order elastic constants for momentum stresses the second (classical) and third-order elastic coefficients (TOEC) for symmetric elasticity are measured and tabulated successfully with good accuracy for tens of years. In the classical experimental measurements of TOEC, the correct recalculation of instantaneous stiffness changes onto TOEC has an important role. A similar problem arises in the constitutive and finite element (FE) modelling. Namely, because of a very strong dependency of TOEC on the strain measure choice, the constitutive and FE modelling of elastic materials is considered here in terms of different finite strain measures. To this aim, the known analytical formulae for calculation of two first derivatives of the isotropic tensor function of tensor variable are verified by means of the finite difference method. In result, the revised formulae are used for calculation of the tangent stiffness matrix. This paper closes with some remarks on the use of TOEC in finite element modelling.

nonlinear elasticity, third-order elastic coefficients, logarithmic strain

The failure probability estimation of FEM simulated sheet metal forming process is a computationally challenging task. The application of efficient gradient-based reliability techniques is very much limited due to the numerical noise introduced by the explicit dynamic algorithm used to perform the sheet stamping analysis and by the nonlinearity of the failure function. To cope with this difficulty, in the current study a two stage metamodel-based adaptive importance sampling method is employed. In order to assess the reliability of sheet metal forming operations the stochastic character of such parameters as friction, blankholding force, blank thickness, strain hardening parameters of the constitutive law as well as parameters defining the forming limit curve (FLC) are considered. Using the numerical example of a square cup deep drawing, the benchmark problem of the Numisheet’93 conference, it is investigated how the assumptions concerning the probabilistic distribution of the FLC location parameter affect the probability of sheet metal fracture.

Reliability, Metal forming

A method for reconstruction of atomistic models of dislocations and stacking faults in the interfacial region of heterostructures is presented. Its mathematical foundations come back to the algebra of the finite deformation fields related to introducing of discrete dislocations into an initially coherent interface. From the practical point of view the method concerns generation of interfacial regions with misfit/treading partial dislocations and stacking faults being formed in the interfacial region between crystal structures of different crystallographic type.

atomistic models, dislocations, stacking faults, lattice distortion

The main objective of the presented study is an evaluation of the effectiveness of various methods for estimating statistics of rotor-shaft vibration responses. The computational effectiveness as well as the accuracy of statistical moment estimation are essential for efficient robust design optimization of the rotor-shaft systems. The most important sources of the observed response scatter are inherently random rotor-shaft residual unbalances as well as stiffness and damping properties of the journal bearings. A relevant representation of these parameters leads to multidimensional stochastic models. The compared stochastic moment estimation methods include sampling techniques, the dimension reduction method and the polynomial chaos expansion method. Two problems of the rotor-shaft vibration analysis are considered: a typical single-span rotor-shaft of the 8-stage centrifugal compressor driven by the electric motor and a large multi-bearing rotor-shaft system of the steam turbogenerator. It is shown that methods that provide a satisfactory balance between the estimation accuracy and computational effectiveness are sampling techniques. Methods employing polynomial chaos expansion perform well in the case of reduced stochastic models. On the other hand, low accuracy of the methods based on Taylor series expansion very often renders these techniques unsuitable for the robust design optimization of vibrating rotor shafts.

ibrations, robustness, numerical analysis, stochastic phenomena