Minisymposia

MS 1

Organizers

Prof. Anatoly G. Yagola, Lomonosov Moscow State University, Russia, yagola@physics.msu.ru

Prof. Yanfei Wang, Chinese Academy of Sciences, China, yfwang@mail.iggcas.ac.cn

Topic: Computational methods for inverse problems and applications

In this minisymposium, inverse problems arising from applied sciences, e.g., geophysics, optics, medical science and engineering will be discussed. Related topics include geophysical data processing and imaging, signal/image processing, parameter identification and solution methods. In solving methodology, with different mathematical models, advanced numerical methods for solving these models such as iterative regularization methods, memory saving optimization methods, MPI programming, machine learning and distributed algorithms are discussed.

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MS 2

Organizer

Prof. Qing Li , The University of Sydney, Australia, qing.li@sydney.edu.au

Topic:

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MS 3

Organizer

Prof. Igor Nikolayevich Egorov, General Director, IOSOLabs, Russia, egorov300657@yandex.ru

Topic: Optimization problems for real-life objects

Our minisympozium will present different real-life examples of usage IOSO optimization technology in another areas: air engine, aircraft, material properties, oil production, car development, metallurgy area, structure of the building, nuclear station etc.

It will be Multi-Objective, Multi-Level, Parallel, Extra Large real-life optimization problem including Robust Design Optimization (RDO). Some of these examples are well-known on the world and anybody can look realization it’s in production.

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MS 4

Organizer

Prof. Daniel Lesnic, University of Leeds, United Kinddom, amt5ld@maths.leeds.ac.uk

Topic: Inverse coefficient identification problems

Inverse coefficient identification problems (ICIP) occur whenever the specimen under testing has unknown physical properties. For non-uniform materials, properties such as conductivity, capacity or storativity can be transient, inhomogeneous, anisotropic or nonlinear. The proposed workshop aims to gather experts on solving such problems to present, discuss and review the current state-of-the art on coefficient identification methodologies.

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MS 5

Organizer

Prof. Gyung-Jin Park, Hanyang University, South Korea, gjpark@hanyang.ac.kr

A/prof. Yingchun Bai, Beijing Institute of Technology, China, baiyc@bit.edu.cn

A/prof. Huiming Ning, Chongqing University, China, ninghuiming@cqu.edu.cn

Topic: Design methodologies for automotive structures and systems

The topics of interest for this mini-symposium include, but not limited to,

(1) Crashworthiness-based topolgoy optimization methods and applications;

(2) Additive manufacturing driven innovative design;

(3) Composite structural analysis and optimization;

(4) Lightweight joining methods and applications;

(5) Multi-mateiral body structural techniques;

(6) EVs and HEVs integration and optimization.

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MS 6

Organizer

Prof. Roland Potthast, Deutscher Wetterdienst (DWD), Germany; Applied Mathematics, University of Reading, UK, Roland.Potthast@dwd.de

Topic: Data Assimilation and Inverse Problems for Dynamical Systems

Data Assimilation is concerned with using measurement data for the reconstruction of the current state of a dynamical system. Further, parameters and structural functions which are basic ingredients of the dynamics need to be reconstructed. Data assimilation is a basic area needed for many important applications ranging from numerical weather prediction or climate science to neuroscience and medicine. The goal of our special session is to invite the inverse problems and data assimilation community to realize the close connection of the two fields, exchange ideas and inspiration.

(1) Methods and Algorithms for Data Assimilation and Dynamical Systems Parameter Estimation;

(2) Uncertainty Estimation in Data Assimilation and Inverse Problems;

(3) Non-linear Conditional Bias Correction;

(4) Estimation of Model Error and Model Uncertainty.

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MS 7

Organizer

Prof. Daniel Watzenig, Graz University of Technology, Austria, daniel.watzenig@tugraz.at

Topic: Statistical inference and uncertainty quantification

Deterministic inversion consists of applying an approximation to the inverse of the forward map, referred to as regularization, in order to give a single point estimate of the unknown parameters. These regularized solutions can provide qualitatively appealing solutions in many situations but lead to quantitatively inaccurate estimates and predictions. This property is shared by estimators in general, since conditioning on point estimates gives poor predictive densities. In contrast, Bayesian inferential methods present averages over all solutions consistent with the data. This leads to a marked difference in robustness of properties calculated from solutions. These differences occur because the single most likely solution, found by a regularized minimization of misfit to the measured data, is typically unrepresentative of the bulk of feasible solutions particularly in high dimensional nonlinear problems. Bayesian inference applied to inverse problems provides a framework for quantified model fitting. Estimation of unknown quantities of interest is based on the posterior distribution over the unknowns and unobserved data, conditioned on measured data. Uncertainty in recovered parameters arises from measurement noise, measurement sensitivities, model inaccuracy, discretization error and a priori uncertainty; each of these sources may be accounted for and in some cases taken advantage of. Estimates or properties of the unknown parameters can be calculated as summary statistics over the posterior distribution using sampling techniques. Inferential solutions to inverse problems provide substantial advantages over deterministic methods, such as:

(1) a range of parameters that are consistent with measured data can be quantified;

(2) data-dependent error estimates can be given;

(3) calculation of confidence intervals;

(4) inclusion of arbitrary forward maps and treatment of arbitrary error distributions;

(5) the parameter space can be discrete, discontinuous, or of variable dimension;

(6) treatment of non-stationary measurement data using recursive Bayesian formalism.

The proposed minisymposium will address recent advances in computational statistical inference, Bayesian analysis, numerical approximations, and quantification of model and measurement uncertainties in the probabilistic design and robust optimization of today’s engineering problems.

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MS 8

Organizer

Prof. Benny Y.C. Hon, City University of Hong Kong, China, maychon@cityu.edu.hk

Topic: Inverse problems related to medical imaging

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MS 9

Organizer

Prof. Zuhair Nashed, University of Central Florida, USA, M.Nashed@ucf.edu

Topic: Inverse problems and optimization meet the geosciences

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MS 10

Organizers

Prof. Sergey Kabanikhin, Russian Academy of Sciences, Russia, ksi52@mail.ru

Prof. Shuhua Zhang, Tianjin University of Finance and Economics, China, szhang@tjufe.edu.cn

Topic: Inverse problems in finance and economics

We are going to discuss new and very important class of inverse problems arising in finance and economics, including Solow and Black-Scholes models, stochastic approach, theoretical and numerical analyses.

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MS 11

Organizer

Prof. Lydie Mpinganzima, University of Rwanda, Rwanda, lydiem421@gmail.com

Topic: Inverse problem for acoustic and electromagnetic waves

This minisymposium concerns recent development in wave modeling and related inverse problems based on acoustic and electromagnetic waves. In these problems, it is assumed that the acoustic or electromagnetic field can be measured on an open part of the domain. Applications range from the determination of acoustic cavities, the determination of the radiation field surrounding a source of radiation, …

The minisymposium aims to bring together experts and young researchers in the field, to give them the opportunity to present their recent work and exchange ideas, and to possibly start new collaborations. .

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MS 12

Organizers

Prof. Haitian Yang , Dalian University of Technology, China, haitian@dlut.edu.cn

Prof. Miao Cui, Dalian University of Technology, China, miaocui@dlut.edu.cn

Prof. Yiqian He, Dalian University of Technology, China, heyiqian@dlut.edu.cn

Topic: Recent findings in inverse heat transfer problems

This MS aims at to promote, exchange and disseminate recent findings on wide-ranging topics of inverse heat transfer problems, and their application in science and engineering, either in the theoretical aspect, or /experimental/numerical aspects. Under the framework of inverse heat transfer problem, subjects of interests include but are not limited to，

(1) Identifications of thermophysical properties, boundary/initial conditions, and geometrical parameters;

(2) Ill-posed problems;

(3) Uncertain forward/invers problems;

(4) Optimization.

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MS 13

Organizers

Prof. Shutian Liu, Dalian University of Technology, China, stliu@dlut.edu.cn

Prof. Qi Wang, Dalian University of Technology, China, qiwang@dlut.edu.cn

Topic: New trends in structural optimization for additive manufacturing

Additive manufacturing (AM) is an emerging technique that provides a great flexibility for the fabrication of complex structures, and gives engineers great freedoms to design novel structures with complex geometries. This has led to a growing interest in AM-oriented structural optimization, especially topology optimization, among the researchers from all over the world. The objective of this symposium is to provide a forum for researchers from academia, industry and national labs to present, discuss and exchange the latest development in theoretical, computational, and experimental studies on structure optimization for additive manufacturing. Both fundamental research and practical applications are welcome. Topics invited for this symposium include but are not limited to,

(1) Topology optimization for AM;

(2) AM-oriented lattice material or meta-material design;

(3) Optimization design subjected to manufacturing constraints;

(4) Material property prediction considering size effect;

(5) Robust/Reliability design considering material and manufacturing uncertainties;

(6) Post-treatment of topology optimization results for AM;

(7) Practical applications of AM-oriented structural design.

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MS 14

Organizers

Prof. Bo Han , Harbin Institute of Technology, China, bohan@hit.edu.cn

A/prof. Yong Chen , Harbin Institute of Technology, China, yongchen@hit.edu.cn

Topic: Accelerated iterative regularization methods and applications

This minisymposium will discuss some fast iterative regularization methods obtained with acceleration techniques, such as Nesterov acceleration, proximal algorithm, sequential subspace optimization method, Kaczmarz method, et al., in Hilbert or Banach spaces. We seek to bring together researchers to present and discuss their latest results in analysis and numerical simulations of regularization methods for ill-posed problems and their applications in full waveform inversion in seismic, diffuse optical tomography, electrical impedance tomography, and so on.

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MS 15

Organizers

Prof. Gongsheng Li, Shandong University of Technology, China, ligs@sdut.edu.cn

A/prof. Dr. Zhiyuan Li, Shandong University of Technology, China, zyli@sdut.edu.cn

Topic: Inverse problems in nonlocal models and related topics

In recent years, partial differential equations with fractional derivatives have gathered increasing popularity among multidisciplinary researchers, owing to their novel features in mathematics and potential feasibility in applied sciences. Especially, many related inverse problems possess practical significance in some environmental issues of common concern. This minisymposium will bring together researchers on inverse problems for fractional-order partial differential equations to share new ideas and present the latest progresses on this topic and related areas, including inverse source problems, coefficient inverse problems, etc.. Also, this minisymposium aims at further strengthening the collaboration in the mathematical and numerical analyses of relevant problems.

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MS 16

Organizers

Prof. Zhihai Xiang, Tsinghua University, China, xiangzhihai@tsinghua.edu.cn

Prof. Xiaoming Zhou, Beijing Institute of Technology, China, zhxming@bit.edu.cn

Prof. Yiqian He, Dalian University of Technology, China, heyiqian@dlut.edu.cn

Topic: Novel methods in the design of functional materials and structures

Design of functional materials and structures is a typical inverse problem. In recent years, many novel ideas emerge in this field, such as meta-materials, super lubrication, smart structures with optimized sensor placement, etc. We welcome relevant researchers, either in the theoretical, experimental or numerical aspects, to participate this mini-symposium that will be richly rewarding. The topics of interest for this mini-symposium include, but not limited to,

(1) Inverse design of meta-materials and meta-structures for wave controlling；

(2) Identification of effective parameters for heterogeneous materials；

(3) Novel damping or low friction materials；

(4) Smart structures with embedded actuators and sensors.

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MS 17

Organizers

Prof. Chao Jiang , Hunan University, China, jiangc@hnu.edu.cn

Dr. Bingyu Ni, Hunan University, China, nby@hnu.edu.cn

Topic: Structural uncertainty analysis and reliability design

Uncertainties have been acknowledged as being extremely important in a wide variety of areas relating to risk assessment and reliability design of structures. To handle with the aleatory and epistemic uncertainties that frequently encountered in practical engineering, a series of effective uncertainty quantification models and reliability analysis approaches have been proposed and developed. Among the various research topics in structural uncertainty analysis and reliability design, this mini-symposium aims to provide a forum for in-depth discussion of key issues including uncertainty quantification models, uncertainty propagation analysis methods, structural reliability analysis methods, reliability-based design optimization, etc. Topics of interests include but are not limited to the following aspects:

(1) Interval analysis;

(2) Imprecise probability methods;

(3) Time-variant/dynamic reliability analysis;

(4) Interval finite element methods;

(5) Reliability-based design optimization;

(6) Interval uncertain optimization;

(7) Advanced Monte Carlo simulation methods;

(8) Reliability analysis of engineering structures.

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MS 18

Organizers

Prof. Hu Wang, Hunan University, China, wanghuenying@hotmail.com

Prof. Haobo Qiu, Huazhong University of Science and Technology, China, hobbyqiu@hust.edu.cn

Prof. Jian Zhang, Jiangsu University, China, jianzhang@ujs.edu.cn

Topic: Data-driven surrogate modeling techniques for inverse and other engineering problems

The surrogate modeling technique is an important tool for parameter inverse methodology. However, with the ever-increasing complexity of inverse problems, the surrogate modeling technique is difficult to handle some critical issues, such as curse of dimensionality, uncertainties, massive sampling data, etc. Therefore, in this mini-symposium, some recently proposed novel strategies might be employed for inverse problems. The themes involve but not limited to,

(1) Surrogate modeling theory and methodology;

(2) Surrogate-based optimization;

(3) Surrogate-assisted evolutionary optimization;

(4) Machine learning methods in surrogate modeling;

(5) Uncertainty Quantification and Uncertainty Propagation in Surrogate modeling;

(6) Data-driven (Numerical simulation-based) design and optimization;

(7) Design of Experiments for surrogate modeling;

(8) Surrogate model assessment;

(9) Surrogate modeling for large data set and high dimensional problems;

(10) Surrogate modeling and surrogate-based optimization in practical engineering applications.

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MS 19

Organizers

Prof. Tommy H.T. Chan, Queensland University of Technology, Australia, tommy.chan@qut.edu.au

Dr. Zhen Chen, North China University of Water Resources and Electric Power, China, yuchenfish@163.com

A/Prof. Jie Liu, Hunan University, China, liujie@hnu.edu.cn

A/Prof. Baijie Qiao, Xi’an Jiaotong University, China, qiao1224@xjtu.edu.cn

Topic: Recent regularization methods for dynamic load identification

Load identification as the second kind of inverse problem in structural dynamics, plays an important role in structural health monitoring, optimization design, transfer path analysis, etc. Recently, various regularization methods such as Tikhonov regularization, function approximation, sparse regularization, compressed sensing, Bayesian and Kalman filters are widely developed to overcome the ill-posedness of load identification in the time or frequency domain. The topics of interest for this mini-symposium include, but not limited to,

(1) Impact force identification for structural health monitoring;

(2) Moving force identification for beam/bridge structure;

(3) Distributed load identification in space-time domain;

(4) Dynamic load identification with uncertainty quantification.

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MS 20

Organizer

A/prof. Qian Zhang, Tianjin University, China, zhangqian@tju.edu.cn

Topic: Detection data intelligent analysis and parameter identification

Submissions related on methods or applications of detection data analysis are welcomed, such as but not limited to:

(1) Intelligent analysis of engineering detection data;

(2) Mechanical modeling of experimental data;

(3) Parameters identification of detection data.

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MS 21

Organizer

A/prof. Fei Lei, Hunan University, China, lei_fei@hnu.edu.cn

Topic: Optimization methods for Intelligent, Connected and Electric Vehicles

Intelligent, Connected and Electric Vehicles are considered to be the key solutions for the future energy-efficient and environment-friendly transportation system. The development of these emerging techniques requires more innovative thinking in design and optimization methods. Topics of interest include but are not limited to:

(1) Energy management for EVs;

(2) Path planning for self-driving cars;

(3) Intelligent Transportation System；

(4) Algorithms in V2X and V2G;

(5) Intelligent power management for EVs;

(6) Thermal management for electric motors and battery pack；.

(7) Inverse problems in battery cells；

(8) Efficiency optimization for motor and invertor system;

(9) Estimation of SoC and range；

(10) Energy conversion and management;

(11) Design of Electric Powertrain;

(12) Integration of active and passive safety for cars.

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MS 22

Organizer

Prof. Bo Wang, Dalian University of Technology, China, wangbo@dlut.edu.cn

Prof. Jihong Zhu, Northwestern Polytechnical University, China, Jh.zhu@nwpu.edu.cn

A/prof. Zhanli Liu, TsingHua University, China, liuzhanli@tsinghua.edu.cn

Prof. Shujuan Hou, Hunan University, China, shujuanhou@hnu.edu.cn

Topic: Integrated Design of Material and Structure

The macroscopic properties of structures are closely related to the microscopic and mechanical behavior of materials. The design of components includes not only the optimization of structures, but also the design of materials. Therefore, the integrated design of material and structure should be considered in the application.

(1) Integrated design techniques for material and structure;

(2) Effects of microstructure and microscopic behavior of materials on macroscopic properties;

(3) The application of experimental means in integrated design;

(4) Integrated design cases of sea, land and air carrier.

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MS 23

Organizer

A/Prof. Yong Ding, Harbin Institute of Technology, China, dingyong@hit.edu.cn

A/Prof. Dongyu Zhang, Harbin Institute of Technology, China, dongyu.zhang@hit.edu.cn

Topic: Novel system identification methods in Civil Engineering

Important civil infrastructures, like high-rise building, long-span bridge etc., gradually lose their carrying capacity, which makes them vulnerable when facing extrem loads(e.g., earthquakes, overweight vehicles, hurricane). Thus, it is crucial to detect structural damage at an early stage and identify the parameters and the unknown loads during the disaster. Structural system identification is a powerful tool to evaluate structural condition from easily obtainable structural vibration signals. The purpose of this minisymposium is to invite the researchers to share their latest research development in structural system identification, including but not limited to:

(1) Advances in structural identification and condition assessment;

(2) Inverse problems in Structural Health Diagnosis;

(3) Structural damage detection during extrem loads;

(4) Kalman-filter based Identificatin methods;

(5) Compressive sensing;

(6) Structural parameter identification with substructure methods;

(7) Inverse problem in advanced testing technology in civil engineering.

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MS 24

Organizer

Prof. Jianguo Zhu, University of Sydney, Australia, jianguo.zhu@sydeny.edu.au

Prof. Shiyou Yang, Zhejiang University, China, eesyyang@zju.edu.cn

Prof. Yongjian Li, Hebei University of Technology, China, liyongjian@hebut.edu.cn

Topic: Recent methods for multidisciplinary design and optimization

Design sensitivity analysis, Design under uncertainty, Multidisciplinary analysis and optimization, Multi-objective optimization, Multi-level optimization, Robust optimization, Meta-models for high-dimensional problems, Shape and topology optimization. The topics of interest for this mini-symposium include, but not limited to,

(1) Topology and robust design optimization techniques;

(2) Uncertainty quantization and numerical solution methodology;

(3) Multi-physics analysis and mechanical state evaluation of electrical equipment;

(4) Magnetic-thermal-fluid coupling method.

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MS 25

Organizer

Prof. Maosen Cao, Hohai University, China, cmszhy@hhu.edu.cn

Prof. Qiang Wang, Nanjing University of Posts and Telecommunications, China, wangqiang@njupt.edu.cn

Dr. Wei Xu，Hong Kong Polytechnic University, China, weixu@polyu.edu.hk

Topic: Inverse analysis of responses for interrogating structural damage

Structural damage identification is of great significance for ensuring the integrity and safety of structures, whose essence relies on inverse analysis of structural responses, like stress, strain, vibration signals, acoustics, ultrasonics, eddy current, X-ray, infrared ray, thermal imaging, et al. In structural health monitoring, the aim of inverse analysis of structural responses is to reveal and extract anomaly features caused by structural damage, whereby damage could be localized and quantified. The topics of interest for this mini-symposium include, but not limited to,

(1) Signal processing methods for structural damage detection;

(2) Modern sensing technologies in structural damage detection;

(3) Inverse analysis algorithms for revealing structural damage;

(4) Extraction of damage features under noisy conditions;

(5) Damage modelling and simulation;

(6) Methods for model updating using dynamic features;

(7) Damage interrogation relying on deep learning;

(8) Dig data interpretation for characterizing damage.

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