Prof. Joannes J. Westerink (University of Notre Dame)
Prof. Manolis Papadrakakis (National Technical University of Athens)
Seismic Assessment of Reinforced Concrete Structures based on State-of-the-art 3D Detailed Nonlinear Finite Element Simulations
The nonlinear dynamic numerical simulation of reinforced concrete structures is characterized by instabilities, which are mainly caused by the cracking of concrete and the rapture of steel reinforcement. When dealing with this numerically unstable and computationally demanding problem, the numerical solution procedure becomes extremely cumbersome, thus leading to convergence issues and the inability to capture the ultimate bearing capacity of the structure. Additionally, the lack of objectivity, when using 1D and 2D models, does not allow the study of the nonlinear dynamic response of R/C structures without introducing significant simplified assumptions in-terms of material behavior and the exact discretization of the structural geometry. In light of these well-known modeling limitations, the main objective of this research work is to alleviate the above-mentioned numerical constraints, by developing a state-of-the-art 3D detailed modeling approach that will provide the computational tools to perform dynamic nonlinear analysis and design on large-scale reinforced concrete structures, by accounting for soil-foundation-structure interaction phenomena as well. In order to achieve this objective, the numerical handling of the solution instabilities is addressed herein, while the use of the HYMOD surrogate modeling approach is discussed as a potential more practical solution to the overall modeling problem. Furthermore, the results from a developed parallel solver for both the generation of embedded rebar elements within the concrete mesh and the handling of the resulting discretized numerical model in parallel and distributed computing environments will also be presented.
Prof. Seiichi Koshizuka (The University of Tokyo)
Numerical Simulation for Nuclear Plant Safety in Tsunami using Particle Method
Severe accident occurred in a nuclear power plant by tsunami flooding after the 2011 off the Pacific coast of Tohoku Earthquake. The direct cause of the accident has been revealed as the inadequate countermeasures against tsunami. The predicted tsunami height was much smaller than the actual one. The underlying root cause is, to the author's opinion, unmatured behavior against uncertainties. Prediction about the natural disasters involves a lot of uncertainties which were not properly managed for the nuclear power plants. Particle methods have been developed for analyzing multiphase flows with phase change as well as violent free surface flows. Meshless discretization is a significant advantage for such complex phenomena. Spreading of the molten nuclear reactor core is analyzed by the particle method in the case of severe accidents. Solidification is modeled by fixing the relative motion of the moving particles. Large-scale tsunami run-up simulation is carried out on the nuclear plant site using the tsunami wave in 2011. Inundation in a turbine building is also analyzed because the blackout of emergency power is caused by the internal flooding. Floating objects are considered as fluid-rigid body coupling problems. The trajectory of the floating object is extremely sensitive to the initial position, the coefficient of restitution, etc. The effect of the floating objects should be assessed by statistical approach, which is expected to study more in future. Advancement of the simulation technologies considering uncertainties will make our society safer.
Prof. Olivier Allix (ENS Cachan)
Prof. Yuri Bazilevs (Brown University)
Recent Developments in Immersed IGA-Meshfree Methods for Extreme-Event SimulationThis presentation is focused on Isogeometric Analysis (IGA) and RKPM Meshfree method with applications to extreme-events simulation. A novel framework for air-blast-structure interaction (ABSI) based on an immersed approach coupling IGA and RKPM is presented and verified on a set of challenging examples. Several numerical challenges exist for carrying out the aforementioned simulations, and these are addressed in the present work. The challenges include shock capturing in both the fluid and solid parts of the problem, and addressing near incompressibility, which is important in the presence of plastic deformations. Extension of the proposed ABSI framework to handle energetic materials is also presented.
Prof. Kwok Fai Cheung(University of Hawaii)
Non-hydrostatic Modeling of Tsunami Waves
Tsunami waves are weakly dispersive and are often modeled using the nonlinear shallow-water equations. Inclusion of non-hydrostatic terms in the governing equations and a shock-capturing scheme in the numerical formulation greatly enhances the modeling capability for academic research and real-world application. The resulting non-hydrostatic model can describe tsunami generation from time-varying seafloor deformation making the calculation compatible with finite-fault modeling of earthquake rupture. Dispersion is a non-hydrostatic property responsible for the spatiotemporal resolution of trans-oceanic propagation that influences the subsequent coastal inundation processes. Shock-capturing is instrumental for modeling tsunami bores near the coast and conserving flow volume in flood hazard mapping. My talk will give an overview of the non-hydrostatic model NEOWAVE developed at the University of Hawaii and highlight its implementation in a series of cross-disciplinary studies from megathrust rupture mechanisms to tsunami loads on buildings.
Prof. Maenghyo Cho(Seoul National University)
Data-Driven Multiscale Simulations of the Polymer Plasticity
A data-driven multiscale framework is proposed to model the three-dimensional constitutive model from the data-driven yield function formulated only by multi-axial yield data using a machine learning technique. The main focus of this talk is to predict the yield function that correctly represents the unique yielding characteristics of materials and specific post-yielding trend using machine learning technique. To identify the intrinsic yielding behaviors, the quasi-static yielding responses of multi-axial deformations were derived from Molecular Dynamics (MD) simulations with the suggested strain rate calibration method. Then, a new yield function is formulated from the calibrated yield data set by constrained symbolic regressions and is implemented in finite element framework. It is discussed to confirm the automatically mined functional structure of yield function can properly represents the yielding feature of the epoxy polymer compared to the existing yield functions.
Prof. Kazuo Kashiyama (Chuo University)
Experience-Based Noise Evaluation System Using VR Technology
The evaluation of noise is very important for planning and designing of various construction works in an urban area. There have been presented a number of evaluation methods for noise simulation. Based on the frame of reference used, those methods can be classified into two categories: 1) Methods based on the geometrical acoustic theory and 2) Methods based on acoustic wave theory. Both methods have advantages and disadvantages. For the methods based on the geometrical acoustic theory, the CPU time is very short but the numerical accuracy is low comparing with the methods based on the acoustic wave theory. On the other hand, the method based on the acoustic wave theory gives accurate solution but the simulation becomes a large scale simulation. In the conventional studies, the computed noise level is described by the visualization using computer graphic such as iso-surface. Although the visualization is a powerful tool to understand the distribution of noise, it is difficult to recognize the noise level intuitively.
In this presentation, an experience based noise evaluation system using virtual reality technology is presented. Both geometrical acoustic and acoustic wave theories are employed. The system exposes to the users the computed noise level with both the auditory information using sound source signal and the visual information using CG image. The CIP method using AMR, BEM based on a fast multipole method are employed for the system based on the wave acoustic theory. In order to investigate the validity and efficiency of the method, we performed the observation of traffic noise for various types of vehicle, trains, airplane and construction noise. The present systems are useful for planning and designing tools for various constructions works in an urban area, and also for consensus building for designers and the local residents.
Prof. P. Benson Shing (University of California, San Diego)
Prof. Kenichi Soga (University of California, Berkeley)
Large Deformation Modeling and Simulations of LandslidesTraditional geotechnical analyses for landslides involve failure prediction (i.e. onset of failure) and the design of structures that can safely withstand the applied loads. But the analyses provide limited information on the post-failure behavior such as failure geometry and the rate of movement. Modern numerical methods for large deformation simulations are now emerging and some of them are started to be adopted by geotechnical engineers to simulate large mass movements. There is also a broader impact because of their potential ability to evaluate the risks of catastrophic damage if a landslide occurs. In this talk, various large-deformation analysis methods are introduced and their applicability for solving landslide problems is discussed. In particular, a technique called the material point method (MPM) is attractive because it allows numerical implementation of history-dependent soil constitutive models and boundary conditions commonly used in geotechnical analysis in a relatively straightforward manner. The recent theoretical development on the multi-phase soil-fluid coupled MPM framework is also providing an opportunity to simulate catastrophic landslides involve seepage forces. On the other hand, further development is required to build confidence in the engineering community to use large deformation simulation methods in engineering practice. This includes better appreciation of failure development processes such as softening induced shear band formation and tensile cracking, identification of energy dissipation mechanisms that are responsible for runout distance and rate, and the role of thermo-hydro-mechanical interaction on these processes and mechanisms.
Prof. Tetsuro Tamura (Tokyo Institute of Technology)
Prof. Zhuo Zhuang (Tsinghua University)
Data-driving-based theoretical and numerical fracking models to optimize recovery efficiency in shale
Hydraulic fracture (fracking) technology in gas shale field engineering is highly developed last decades in North America and also recent years in China, but the knowledge of actual fracturing process is mostly empirical and makes the mechanician wonder. In this work, the data-driving-based theoretical and numerical fracking model is proposed to predict and optimize recovery efficiency in shale. Shale is a typical layered and anisotropic material whose properties are characterized primarily by locally oriented anisotropic clay minerals and naturally formed bedding planes. The debonding of bedding planes will greatly influence the shale fracking to form a large-scale highly permeable fracture network, which is the stimulate reform volume (SRV). Both theoretical and numerical models are developed to quantitatively predict the growth of debonding zone in layered shale under fracking. Some parameters are proposed to characterize the corresponding conditions of tensile and shear debonding of bedding planes. It is found that debonding is mainly caused by the shear failure of bedding planes in the actual reservoir. Then the theoretical model is applied to design the perforation cluster spacing to optimize SRV. The SRV and optimal perforation cluster spacing range can be quantitatively calculated to guide the fracking design. These results are comparable with the data from real-time signal evolution by micro earthquake monitor in field engineering.