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- Amouzgar, Kaveh
(author)
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Metamodel based multi-objective optimization
- 2015
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Licentiate thesis (other academic/artistic)abstract
- As a result of the increase in accessibility of computational resources and the increase in the power of the computers during the last two decades, designers are able to create computer models to simulate the behavior of a complex products. To address global competitiveness, companies are forced to optimize their designs and products. Optimizing the design needs several runs of computationally expensive simulation models. Therefore, using metamodels as an efficient and sufficiently accurate approximate of the simulation model is necessary. Radial basis functions (RBF) is one of the several metamodeling methods that can be found in the literature.The established approach is to add a bias to RBF in order to obtain a robust performance. The a posteriori bias is considered to be unknown at the beginning and it is defined by imposing extra orthogonality constraints. In this thesis, a new approach in constructing RBF with the bias to be set a priori by using the normal equation is proposed. The performance of the suggested approach is compared to the classic RBF with a posteriori bias. Another comprehensive comparison study by including several modeling criteria, such as problem dimension, sampling technique and size of samples is conducted. The studies demonstrate that the suggested approach with a priori bias is in general as good as the performance of RBF with a posteriori bias. Using the a priori RBF, it is clear that the global response is modeled with the bias and that the details are captured with radial basis functions.Multi-objective optimization and the approaches used in solving such problems are briefly described in this thesis. One of the methods that proved to be efficient in solving multi-objective optimization problems (MOOP) is the strength Pareto evolutionary algorithm (SPEA2). Multi-objective optimization of a disc brake system of a heavy truck by using SPEA2 and RBF with a priori bias is performed. As a result, the possibility to reduce the weight of the system without extensive compromise in other objectives is found.Multi-objective optimization of material model parameters of an adhesive layer with the aim of improving the results of a previous study is implemented. The result of the original study is improved and a clear insight into the nature of the problem is revealed.
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2. |
- Amouzgar, Kaveh, 1980-
(author)
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Metamodel Based Multi-Objective Optimization with Finite-Element Applications
- 2018
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Doctoral thesis (other academic/artistic)abstract
- As a result of the increase in accessibility of computational resources and the increase of computer power during the last two decades, designers are able to create computer models to simulate the behavior of complex products. To address global competitiveness, companies are forced to optimize the design of their products and production processes. Optimizing the design and production very often need several runs of computationally expensive simulation models. Therefore, integrating metamodels, as an efficient and sufficiently accurate approximate of the simulation model, with optimization algorithms is necessary. Furthermore, in most of engineering problems, more than one objective function has to be optimized, leading to multi-objective optimization(MOO). However, the urge to employ metamodels in MOO, i.e., metamodel based MOO (MB-MOO), is more substantial.Radial basis functions (RBF) is one of the most popular metamodeling methods. In this thesis, a new approach to constructing RBF with the bias to beset a priori by using the normal equation is proposed. The performance of the suggested approach is compared to the classic RBF and four other well-known metamodeling methods, in terms of accuracy, efficiency and, most importantly, suitability for integration with MOO evolutionary algorithms. It has been found that the proposed approach is accurate in most of the test functions, and it was the fastest compared to other methods. Additionally, the new approach is the most suitable method for MB-MOO, when integrated with evolutionary algorithms. The proposed approach is integrated with the strength Pareto evolutionary algorithm (SPEA2) and applied to two real-world engineering problems: MB-MOO of the disk brake system of a heavy truck, and the metal cutting process in a turning operation. Thereafter, the Pareto-optimal fronts are obtained and the results are presented. The MB-MOO in both case studies has been found to be an efficient and effective method. To validate the results of the latter MB-MOO case study, a framework for automated finite element (FE) simulation based MOO (SB-MOO) of machining processes is developed and presented by applying it to the same metal cutting process in a turning operation. It has been proved that the framework is effective in achieving the MOO of machining processes based on actual FE simulations.
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3. |
- Amouzgar, Kaveh, 1980-, et al.
(author)
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Multi-objective optimization of material model parameters of an adhesive layer by using SPEA2
- 2015
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In: Advances in structural and multidisciplinary optimization. - : The International Society for Structural and Multidisciplinary Optimization (ISSMO). - 9780646943947 ; , s. 249-254
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Conference paper (peer-reviewed)abstract
- The usage of multi material structures in industry, especially in the automotive industry are increasing. To overcome the difficulties in joining these structures, adhesives have several benefits over traditional joining methods. Therefore, accurate simulations of the entire process of fracture including the adhesive layer is crucial. In this paper, material parameters of a previously developed meso mechanical finite element (FE) model of a thin adhesive layer are optimized using the Strength Pareto Evolutionary Algorithm (SPEA2). Objective functions are defined as the error between experimental data and simulation data. The experimental data is provided by previously performed experiments where an adhesive layer was loaded in monotonically increasing peel and shear. Two objective functions are dependent on 9 model parameters (decision variables) in total and are evaluated by running two FEsimulations, one is loading the adhesive layer in peel and the other in shear. The original study converted the two objective functions into one function that resulted in one optimal solution. In this study, however, a Pareto frontis obtained by employing the SPEA2 algorithm. Thus, more insight into the material model, objective functions, optimal solutions and decision space is acquired using the Pareto front. We compare the results and show good agreement with the experimental data.
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4. |
- Andersson, Tobias, et al.
(author)
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Meso-Mechanical Modelling Of Thin Adhesive Layers
- 2004
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In: ECF15, Stockolm 2004.
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Conference paper (other academic/artistic)abstract
- A meso-mechanical finite element model for a thin adhesive layer is developed. The model is calibrated to experimental results where the adhesive layer is loaded in monotonically increasing peel or shear, cf. Andersson and Stigh [1] and Alfredsson et al. [2], and to an in situ SEM study of the fracture process. The purpose of the meso-mechanical finite element model is to facilitate the development of constitutive laws for adhesive layers. Ideas developed by Needleman [3], where structural continuum elements are bonded by cohesive elements are used as a basis for the finite element mesh. This thus enables micro cracks to propagate along the finite element boundaries. The simulations are found to be in good agreement with the experiments. The model is also capable of reproducing realistically the deformation observed in both peel [1] and shear [2] experiments.
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6. |
- Arjomandi Rad, Mohammad, et al.
(author)
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Correlation-based feature extraction from computer-aided design, case study on curtain airbags design
- 2022
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In: Computers in industry (Print). - : Elsevier. - 0166-3615 .- 1872-6194. ; 138
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Journal article (peer-reviewed)abstract
- Many high-level technical products are associated with changing requirements, drastic design changes, lack of design information, and uncertainties in input variables which makes their design process iterative and simulation-driven. Regression models have been proven to be useful tools during design, altering the resource-intensive finite element simulation models. However, building regression models from computer-aided design (CAD) parameters is associated with challenges such as dealing with too many parameters and their low or coupled impact on studied outputs which ultimately requires a large training dataset. As a solution, extraction of hidden features from CAD is presented on the application of volume simulation of curtain airbags concerning geometric changes in design loops. After creating a prototype that covers all aspects of a real curtain airbag, its CAD parameters have been analyzed to find out the correlation between design parameters and volume as output. Next, using the design of the experiment latin hypercube sampling method, 100 design samples are generated and the corresponding volume for each design sample was assessed. It was shown that selected CAD parameters are not highly correlated with the volume which consequently lowers the accuracy of prediction models. Various geometric entities, such as the medial axis, are used to extract several hidden features (referred to as sleeping parameters). The correlation of the new features and their performance and precision through two regression analyses are studied. The result shows that choosing sleeping parameters as input reduces dimensionality and the need to use advanced regression algorithms, allowing designers to have more accurate predictions (in this case approximately 95%) with a reasonable number of samples. Furthermore, it was concluded that using sleeping parameters in regression-based tools creates real-time prediction ability in the early development stage of the design process which could contribute to lower development lead time by eliminating design iterations.
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7. |
- Arjomandi Rad, Mohammad, 1987, et al.
(author)
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Image regression-based digital qualification for simulation-driven design processes, case study on curtain airbag
- 2023
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In: Journal of engineering design (Print). - : Taylor & Francis. - 0954-4828 .- 1466-1837. ; 34:1, s. 1-22
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Journal article (peer-reviewed)abstract
- Today digital qualification tools are part of many design processes that make them dependent on long and expensive simulations, leading to limited ability in exploring design alternatives. Conventional surrogate modelling techniques depend on the parametric models and come short in addressing radical design changes. Existing data-driven models lack the ability in dealing with the geometrical complexities. Thus, to address the resulting long development lead time problem in the product development processes and to enable parameter-independent surrogate modelling, this paper proposes a method to use images as input for design evaluation. Using a case study on the curtain airbag design process, a database consisting of 60,000 configurations has been created and labelled using a method based on dynamic relaxation instead of finite element methods. The database is made available online for research benchmark purposes. A convolutional neural network with multiple layers is employed to map the input images to the simulation output. It was concluded that the showcased data-driven method could reduce digital testing and qualification time significantly and contribute to real-time analysis in product development. Designers can utilise images of geometrical information to build real-time prediction models with acceptable accuracy in the early conceptual phases for design space exploration purposes.
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8. |
- Belov, Ilja, et al.
(author)
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Fin‐Tube and Plate Heat Exchangers : Evaluation of Transient Performance
- 2017
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In: 18th International Conference on Thermal, Mechanical and Multi-Physics Simulation and Experiments in Microelectronics and Microsystems (EuroSimE). - : IEEE. - 9781509043446 - 9781509043439 - 9781509043453
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Conference paper (peer-reviewed)abstract
- A methodology for evaluation of transient performance of, and comparison between plate heat exchanger and plate-fin-and-tube heat exchanger was developed and realized, including experiment and 3-D simulation. Heat transfer from water to a gas medium was addressed. The heated gas volume was the same for both heat exchanger designs. This was achieved by placing the plate-fin-and-tube heat exchanger into enclosure. The volume average temperature of the gas as function of time was computed. Estimated material cost for the studied designs was at least seven times lower than for the stainless steel plate heat exchanger. The performance of the selected plate-fin-and-tube heat exchanger design was found comparable to the plate heat exchanger, when both fin and tube materials were set to Al, and the enclosure was a light-weight thermal insulator. Transient behavior of the studied heat exchangers should be of interest for micro-grid applications, but also for thermal management in electronic cabinets and data centers.
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9. |
- Bengnér, Johannes, et al.
(author)
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Serum amyloid A – A prime candidate for identification of neonatal sepsis
- 2021
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In: Clinical Immunology. - : Elsevier. - 1521-6616 .- 1521-7035. ; 229:108787
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Journal article (peer-reviewed)abstract
- Neonatal sepsis is common, lethal, and hard to diagnose. In combination with clinical findings and blood culture, biomarkers are crucial to make the correct diagnose. A Swedish national inquiry indicated that neonatologists were not quite satisfied with the available biomarkers. We assessed the kinetics of 15 biomarkers simultaneously: ferritin, fibrinogen, granulocyte colony-stimulating factor (G-CSF), interferon (IFN)-γ, interleukin (IL)-1β, −6, −8, −10, macrophage inflammatory protein (MIP)-1β, procalcitonin, resistin, serum amyloid A (SAA), tumor necrosis factor (TNF)-α, tissue plasminogen activator-3 and visfatin. The goal was to observe how quickly they rise in response to infection, and for how long they remain elevated. From a neonatal intensive care unit, newborns ≥28 weeks gestational age were recruited. Sixty-eight newborns were recruited to the study group (SG), and fifty-one to the control group (CG). The study group subjects were divided into three subgroups depending on clinical findings: confirmed sepsis (CSG), suspected sepsis (SSG) and no sepsis. CSG and SSG were also merged into an entire sepsis group (ESG) for sub-analysis. Blood samples were collected at three time-points; 0 h, 12–24 h and 48–72 h, in order to mimic a “clinical setting”. At 0 h, visfatin was elevated in SSG compared to CG; G-CSF, IFN-γ, IL-1β, −8 and − 10 were elevated in SSG and ESG compared to CG, whereas IL-6 and SAA were elevated in all groups compared to CG. At 12–24 h, IL-8 was elevated in ESG compared to CG, visfatin was elevated in ESG and SSG compared to CG, and SAA was elevated in all three groups compared to CG. At 48–72 h, fibrinogen was elevated in ESG compared to CG, IFN-γ and IL-1β were elevated in SSG and ESG compared to CG, whereas IL-8 and SAA were elevated in all three groups compared to CG. A function of time-formula is introduced as a tool for theoretical prediction of biomarker levels at any time-point. We conclude that SAA has the most favorable kinetics regarding diagnosing neonatal sepsis, of the biomarkers studied. It is also readily available methodologically, making it a prime candidate for clinical use.
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10. |
- Cenanovic, Mirza
(author)
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Finite element methods for surface problems
- 2017
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Doctoral thesis (other academic/artistic)abstract
- The purpose of this thesis is to further develop numerical methods for solving surface problems by utilizing tangential calculus and the trace finite element method. Direct computation on the surface is possible by the use of tangential calculus, in contrast to the classical approach of mapping 2D parametric surfaces to 3D surfaces by means of differential geometry operators. Using tangential calculus, the problem formulation is only dependent on the position and normal vectors of the 3D surface. Tangential calculus thus enables a clean, simple and inexpensive formulation and implementation of finite element methods for surface problems. Meshing techniques are greatly simplified from the end-user perspective by utilizing an unfitted finite element method called the Trace Finite Element Method, in which the basic idea is to embed the surface in a higher dimensional mesh and use the shape functions of this background mesh for the discretization of the partial differential equation. This method makes it possible to model surfaces implicitly and solve surface problems without the need for expensive meshing/re-meshing techniques especially for moving surfaces or surfaces embedded in 3D solids, so called embedded interface problems. Using these two approaches, numerical methods for solving three surface problems are proposed: 1) minimal surface problems, in which the form that minimizes the mean curvature was computed by iterative update of a level-set function discretized using TraceFEM and driven by advection, for which the velocity field was given by the mean curvature flow, 2) elastic membrane problems discretized using linear and higher order TraceFEM, which makes it straightforward to embed complex geometries of membrane models into an elastic bulk for reinforcement and 3) stabilized, accurate vertex normal and mean curvature estimation with local refinement on triangulated surfaces. In this thesis the basics of the two main approaches are presented, some aspects such as stabilization and surface reconstruction are further developed, evaluated and numerically analyzed, details on implementations are provided and the current state of work is presented.
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