Using surrogate models and response surfaces in structural optimization ? with application to crashworthiness design and sheet metal forming

Jansson, Tomas; Nilsson, Larsgunnar; Redhe, Marcus

doi:10.1007/s00158-002-0279-y

Cited by 98 publications

(24 citation statements)

References 11 publications

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“…Surrogate models such as polynomial response surfaces are frequently used in structural optimization research to approximate the inputoutput relationships of a computationally expensive model (Jansson et al 2003). For the calibration process, the relationship between errors in predicted adduction torque peaks (i.e.…”

Section: Discussionmentioning

confidence: 99%

Evaluation of a patient-specific cost function to predict the influence of foot path on the knee adduction torque during gait

Fregly

Reinbolt

Chmielewski

2008

Computer Methods in Biomechanics and Biomedical Engineering

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A large external knee adduction torque during gait has been correlated with the progression of knee osteoarthritis (OA). Though foot path changes (e.g. toeing out) can reduce the adduction torque, no method currently exists to predict whether an optimal foot path exists for a specific patient. This study evaluates a patient-specific optimization cost function to predict how foot path changes influence both adduction torque peaks. Video motion and ground reaction data were collected from a patient with knee OA performing normal, toe out, and wide stance gait. Joint and inertial parameters in a dynamic, 27 degree-of-freedom, full-body gait model were calibrated to the patient's normal gait data. The model was then used in gait optimizations that predicted how the patient's adduction torque peaks would change due to changes in foot path. The cost function tracked the patient's normal gait data using weight factors calibrated to toe out gait and tested using wide stance gait. For both gait motions, the same cost function weights predicted the change in both adduction torque peaks to within 7% error. With further development, this approach may eventually permit the design of patient-specific rehabilitation procedures such as an optimal foot path for patients with knee OA.

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Section: Discussionmentioning

confidence: 99%

Evaluation of a patient-specific cost function to predict the influence of foot path on the knee adduction torque during gait

Fregly

Reinbolt

Chmielewski

2008

Computer Methods in Biomechanics and Biomedical Engineering

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“…end-effector designs and the force on the part. Depending on the application range for these parameters, the samples are obtained by for example random (done in this work) or uniform sampling, or by using advanced space mapping methods (Wang et al 2017;Jansson et al 2003;Shan and Wang 2010). A physics-driven model (with a FEA-based kernel) is solved for each sample to calculate the corresponding output value for the maximum induced stress (Franciosa et al 2014).…”

Section: Yield Stress Constraintmentioning

confidence: 99%

End-effector design optimisation and multi-robot motion planning for handling compliant parts

Glorieux

Franciosa

Ceglarek

2017

Struct Multidisc Optim

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The deformation of compliant parts during material handling is a critical issue that can significantly affect the productivity and the parts' dimensional quality. There are multiple relevant aspects to consider when designing end-effectors to handle compliant parts, e.g. motion planning, holding force, part deformations, collisions, etc. This paper focuses on multi-robot material handling systems where the end-effector designs influence the coordination of the robots to prevent that these collide in the shared workspace. A multi-disciplinary methodology for end-effector design optimisation and multi-robot motion planning for material handling of compliant parts is proposed. The novelty is the co-adaptive optimisation of the end-effectors' structure with the robot motion planning to obtain the highest productivity and to avoid excessive part deformations. Based on FEA, the dynamic deformations of the parts are modelled in order to consider these during the collision avoidance between the handled parts and obstacles. The proposed methodology is evaluated for a case study that considers the multi-robot material handling of sheet metal parts in a multi-stage tandem press line. The results show that a substantial improvement in productivity can be achieved (up to 1.9%). These also demonstrate the need and contribution of the proposed methodology.

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“…However, the accuracy of the obtained optimum completely depends on the accuracy of the metamodel. Examples where approximate optimization algorithms are applied to optimize metal forming processes include Jansson et al (2003Jansson et al ( , 2005, Naceur et al (2004), . This paper describes Sequential Approximate Optimization algorithms to optimize forging processes using timeconsuming Finite Element simulations.…”

Section: Introductionmentioning

confidence: 99%

Optimization of forging processes using Finite Element simulations

Bonte

Fourment

et al. 2010

Struct Multidisc Optim

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During the last decades, simulation software based on the Finite Element Method (FEM) has significantly contributed to the design of feasible forming processes. Coupling FEM to mathematical optimization algorithms offers a promising opportunity to design optimal metal forming processes rather than just feasible ones. In this paper Sequential Approximate Optimization (SAO) for optimizing forging processes is discussed. The algorithm incorporates time-consuming nonlinear FEM simulations. Three variants of the SAO algorithm-which differ by their sequential improvement strategies-have been investigated and compared to other optimization algorithms by application to two forging processes. The other algorithms taken into account are two iterative algorithms (BFGS and SCPIP) and a Metamodel Assisted Evolutionary Strategy (MAES). It is essential for sequential approximate optimization algorithms to implement an improvement strategy that uses as much information obtained during previous iterations as possible. If such a sequential improvement strategy is used, SAO provides a very efficient algorithm to optimize forging processes using time-consuming FEM simulations.

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Using surrogate models and response surfaces in structural optimization ? with application to crashworthiness design and sheet metal forming

Cited by 98 publications

References 11 publications

Evaluation of a patient-specific cost function to predict the influence of foot path on the knee adduction torque during gait

Evaluation of a patient-specific cost function to predict the influence of foot path on the knee adduction torque during gait

End-effector design optimisation and multi-robot motion planning for handling compliant parts

Optimization of forging processes using Finite Element simulations

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