Article
Environmental Sciences
Vinh Ngoc Tran, Jongho Kim
Summary: This study demonstrates that the SPCE approach outperforms the FPCE approach in terms of accuracy and efficiency in building surrogate models for hydrological systems. The SPCE method can efficiently capture streamflow uncertainty and parameter sensitivity, providing faster computational speeds compared to SFM and FPCE. Ultimately, the SPCE approach can benefit ensemble streamflow forecasting studies by quickly providing accurate information in real time.
Article
Engineering, Marine
Ming Chen, Xinhu Zhang, Kechun Shen, Guang Pan
Summary: This study investigates the high-dimensional uncertainty quantification of critical buckling pressure for a composite cylindrical shell with geometric and material uncertainties using sparse polynomial chaos expansion (PCE). The results show that the uncertainty of the longitudinal modulus has a massive influence on the critical buckling pressure, while the uncertainties of other parameters have a weak influence.
JOURNAL OF MARINE SCIENCE AND ENGINEERING
(2022)
Article
Metallurgy & Metallurgical Engineering
Marks Legkovskis, Peter J. Thomas, Michael Auinger
Summary: Uncertainty quantification is crucial in steel reheating simulations due to input uncertainties in defining surface properties and furnace conditions. The study uses polynomial chaos expansion to reduce computational effort and presents a comprehensive uncertainty quantification analysis of a walking-beam reheat furnace. The analysis reveals the significant influence of parameters related to emissivity and oxide scale growth on slab temperature and identifies the transition in importance of oxide scale growth inputs.
STEEL RESEARCH INTERNATIONAL
(2023)
Article
Engineering, Electrical & Electronic
Aristeides D. Papadopoulos, Theodoros Zygiridis, Yannis Kopsinis, Elias N. Glytsis
Summary: The stochastic response of resonant grating structures with a large number of geometric random design variables is studied using the new Anisotropic Sparse Adaptive Polynomial Chaos expansions (ASA-PC) method. Computationally inexpensive stochastic solutions are found to quantify the quantities of interest, including the probability density and statistical measures of the resonant grating response.
JOURNAL OF LIGHTWAVE TECHNOLOGY
(2022)
Article
Engineering, Civil
Rui Zhang, Chengyu Yang, Hetao Hou, Karlel Cornejo, Cheng Chen
Summary: Hybrid simulation is an efficient experimental technique for structural performance evaluation, but traditional methods cannot account for uncertainties. Stochastic hybrid simulation (SHS) explicitly considers substructure uncertainties, and this study explores the experimental design of SHS using the pseudo-random Sobol sequence. Computational simulation and laboratory experiments validate the effectiveness of using SHS for uncertainty quantification.
SMART STRUCTURES AND SYSTEMS
(2023)
Article
Engineering, Multidisciplinary
Steven Dixler, Ramin Jahanbin, Sharif Rahman
Summary: The optimal spline dimensional decomposition (SDD) method proposed in this study provides a more accurate way to calculate the second-moment statistics and the cumulative distribution function of output random variables in high-dimensional uncertainty quantification analysis of complex systems. This method reduces computational complexity compared to traditional methods such as polynomial chaos expansion and sparse-grid quadrature.
INTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN ENGINEERING
(2021)
Article
Computer Science, Interdisciplinary Applications
S. Rezaeiravesh, R. Vinuesa, P. Schlatter
Summary: This study combines various existing uncertainty quantification techniques to develop a framework for assessing metrics in computational physics problems, such as accuracy, sensitivity, and robustness. The framework analyzes the relationship between the simulator's outputs and uncertain inputs and parameters to enhance our understanding of different factors in physics simulations.
JOURNAL OF COMPUTATIONAL SCIENCE
(2022)
Article
Computer Science, Interdisciplinary Applications
Jacqueline Wentz, Alireza Doostan
Summary: In this study, a method for quantifying uncertainty in high-dimensional PDE systems with random parameters is proposed. The method utilizes a generative model to approximate the coefficients of the solutions. The approach outperforms sparsity promoting methods at small sample sizes in the examined high-dimensional problems.
JOURNAL OF COMPUTATIONAL PHYSICS
(2023)
Article
Engineering, Civil
Z. P. Xu, Y. P. Li, G. H. Huang, Z. Y. Shen
Summary: In this study, a PCE-ANOVA-RF method is developed to analyze the effects of multiple uncertain parameters in the SWAT model and generate probabilistic forecasts of daily streamflow. The proposed method not only reveals the impact of parameter uncertainty and saves computation time, but also expands PCE's ability to predict future streamflow processes. The feasibility and applicability of the method are verified in the Amu Darya River Basin in Central Asia.
JOURNAL OF HYDROLOGY
(2023)
Article
Engineering, Multidisciplinary
Arash Mohammadi, Koji Shimoyama, Mohamad Sadeq Karimi, Mehrdad Raisee
Summary: An efficient surrogate model based on POD and compressed sensing is developed for affordable representation of high-dimensional stochastic fields, showing potential in engineering applications.
APPLIED MATHEMATICAL MODELLING
(2021)
Article
Mathematics, Applied
Xiang Sun, Jung-Il Choi
Summary: The proposed method utilizes POD and PCE to model spacetime-dependent parameterized problems, effectively estimating low-order moments and accuracy loss under uncorrelated or correlated input parameters.
COMPUTERS & MATHEMATICS WITH APPLICATIONS
(2021)
Article
Mathematics, Applied
Jun Man, Guang Lin, Yijun Yao, Lingzao Zeng
Summary: A generalized multi-fidelity PCE (GMF-PCE) method is developed in this study, approximating a high-fidelity model with the sum of a low-fidelity model and a correction function using the control variate method. Experimental results demonstrate that GMF-PCE can achieve higher accuracy compared to traditional methods at the same computational cost.
JOURNAL OF COMPUTATIONAL AND APPLIED MATHEMATICS
(2021)
Article
Materials Science, Multidisciplinary
Ming Chen, Xinhu Zhang, Guang Pan
Summary: This paper uses inexpensive-to-evaluate sparse polynomial chaos expansion (PCE) based on small data to analyze the impact of uncertainties in mechanical properties on the design of underwater vehicles. Buckling processes are simulated through experiments and finite element analysis, and the relative contribution of mechanical properties to critical buckling pressure is quantified. Distribution function histogram and risk of structural failure are obtained through Monte Carlo simulation (MCS) based on inexpensive-to-evaluate sparse PCE. The mean of critical buckling pressure is 8.27 MPa, with a coefficient of variation of 8.59%. The 95% confidence interval is 6.86 MPa-9.65 MPa.
MECHANICS OF ADVANCED MATERIALS AND STRUCTURES
(2023)
Article
Mathematics, Applied
Y. Wei, F. Vazeille, Q. Serra, E. Florentin
Summary: PCE is a powerful metamodeling technique, but requires exponentially increasing training samples with problem dimensionality. PGD has emerged as a popular solution with linear complexity growth based on separate representations. This work introduces a hybrid technique called PGD-PCE, utilizing orthonormal polynomial functions, demonstrating good accuracy and computational efficiency in handling large problems.
FINITE ELEMENTS IN ANALYSIS AND DESIGN
(2022)
Article
Engineering, Industrial
Wen Yao, Xiaohu Zheng, Jun Zhang, Ning Wang, Guijian Tang
Summary: This paper proposes an adaptive arbitrary polynomial chaos (aPC) method and combines it with a deep neural network (DNN) to propose a semi-supervised deep adaptive arbitrary polynomial chaos expansion (Deep aPCE) method. The Deep aPCE method reduces the training data cost by using a small amount of labeled data and abundant unlabeled data, and improves the accuracy of uncertainty quantification by dynamically fine-tuning the adaptive expansion coefficients using DNN. Additionally, the Deep aPCE method can construct accurate surrogate models of high dimensional stochastic systems.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2023)
Article
Energy & Fuels
Kevin Verleysen, Diederik Coppitters, Alessandro Parente, Ward De Paepe, Francesco Contino
Article
Energy & Fuels
Charles Lhuillier, Pierre Brequigny, Francesco Contino, Christine Mounaim-Rousselle
Article
Engineering, Mechanical
Jarl Beckers, Diederik Coppitters, Ward De Paepe, Francesco Contino, Joeri Van Mierlo, Bjorn Verrelst
Article
Energy & Fuels
Severine Cassiers, Francois Boveroux, Christophe Martin, Rafael Maes, Kris Martens, Benjamin Bergmans, Francois Idczak, Herve Jeanmart, Francesco Contino
Article
Thermodynamics
Krishna Prasad Shrestha, Charles Lhuillier, Amanda Alves Barbosa, Pierre Brequigny, Francesco Contino, Christine Mounaim-Rousselle, Lars Seidel, Fabian Mauss
Summary: This study experimentally investigated the laminar flame speeds of ammonia and ammonia-hydrogen blends under different temperature, pressure, and oxygen content conditions, and developed a new kinetic model for predicting the oxidation mechanisms, considering the formation and reduction of nitrogen oxides. The results showed that the laminar flame speed increases with increasing initial temperature, fuel hydrogen content, or oxidizer oxygen content, but decreases with increasing initial pressure. The proposed kinetic model predicts the same trends as experiments and highlights the importance of N2H2 formation under rich conditions.
PROCEEDINGS OF THE COMBUSTION INSTITUTE
(2021)
Article
Thermodynamics
Charles Lhuillier, Pierre Brequigny, Francesco Contino, Christine Mounaim-Rousselle
Summary: The study aims to elucidate the combustion characteristics of ammonia blends under engine-relevant turbulent conditions, finding that the effects of hydrogen or methane enrichment observed in SI engines cannot be fully explained by the measured laminar burning velocities. The combustion regimes studied are at the boundary between thin and broken reaction zones, influenced by flame-turbulence interactions.
PROCEEDINGS OF THE COMBUSTION INSTITUTE
(2021)
Article
Engineering, Mechanical
Ward De Paepe, Alessio Pappa, Diederik Coppitters, Marina Montero Carrero, Panagiotis Tsirikoglou, Francesco Contino
Summary: The study provides a detailed analysis of the recuperator performance under humidified conditions using averaged experimental data and applying support vector regression (SVR) to improve accuracy. Despite increased total exchanged heat flux, the recuperator is found to be too small to fully exploit the potential of humidification.
JOURNAL OF ENGINEERING FOR GAS TURBINES AND POWER-TRANSACTIONS OF THE ASME
(2021)
Article
Engineering, Mechanical
Jarl Beckers, Tom Verstraten, Bjorn Verrelst, Francesco Contino, Joeri Van Mierlo
Summary: This paper proposes a new design of a slider-crank mechanism, which achieves continuous movement and minimizes the loads transmitted through the mechanical structure through local linear actuation. The study indicates that operating at the resonance frequency of the system yields optimal results.
MECHANISM AND MACHINE THEORY
(2021)
Article
Energy & Fuels
Xavier Rixhon, Gauthier Limpens, Diederik Coppitters, Herve Jeanmart, Francesco Contino
Summary: Wind and solar energies face a challenge of time and space disparity leading to a mismatch between supply and demand, which can be addressed by electrofuels like hydrogen, methane, and methanol. However, the uncertainties and costs associated with electrofuels may influence the total costs of future energy systems.
Article
Thermodynamics
Diederik Coppitters, Ward De Paepe, Francesco Contino
Summary: This study considers the effects of limited information on the natural variability through probability-boxes, finding the least-sensitive designs to natural variability and effective actions to reduce the effects of limited information. The photovoltaic-battery-heat pump configuration achieves higher robustness towards aleatory uncertainty, while clarifying the grid electricity contract and adopting specific energy demand profiles are key actions to determine the true-but-unknown performance and robustness of the optimized designs.
Article
Thermodynamics
Kevin Verleysen, Alessandro Parente, Francesco Contino
Summary: The development of a sustainable energy sector relies on the safe management of energy transportation and storage. Producing an energy carrier like ammonia for large-scale storage of renewable energy is crucial, but attention must be paid to the stability of the ammonia reactor and the impact of uncertainties on performance. Inlet temperature has the most significant impact on ammonia production standard deviation, and more precise control over it can reduce this impact.
Article
Computer Science, Interdisciplinary Applications
S. Tipler, G. D'Alessio, Q. Van Haute, A. Parente, F. Contino, A. Coussement
Summary: This research highlights the importance of using predictive methods when measuring RON and MON at a low price. Through the investigation of 41 parameters and the application of PCA and ANN, the study identified the inherent links between fuel properties and RON/MON.
COMPUTERS & CHEMICAL ENGINEERING
(2022)
Article
Thermodynamics
Kevin Verleysen, Alessandro Parente, Francesco Contino
Summary: Ammonia serves as a crucial energy vector for storing and releasing excess renewable energy. However, the current synthesis process lacks flexibility, requiring large hydrogen storage tanks. To reduce tank capacity, optimizing the dynamic power-to-ammonia process under renewable uncertainty is necessary.
PROCEEDINGS OF THE COMBUSTION INSTITUTE
(2023)
Article
Thermodynamics
Kun Wu, Francesco Contino, Xuejun Fan
Summary: To overcome the challenges of simulating reactive flow in supersonic combustion, on-the-fly mechanism reduction using dynamic adaptive chemistry (DAC) is necessary. This study investigates the influential factors of mechanism reduction methods, error threshold values, and search initiating species for high fidelity simulation of supersonic combustion. The results show that all four mechanism reduction methods are adequate for global performance prediction, while the DRGEP method achieves the best balance between accuracy and efficiency. The error threshold value should not exceed 10(-4) for high fidelity simulations. The combination of stable species incurs larger errors in radical mass fraction prediction but is more computationally efficient than including intermediate species. The computational overheads for mechanism reduction are mainly determined by the CPU time for solving the simplified ODE system.
COMBUSTION SCIENCE AND TECHNOLOGY
(2022)
Article
Energy & Fuels
Paolo Thiran, Herve Jeanmart, Francesco Contino
Summary: Studying a large number of scenarios and using complex energy system models are necessary for considering uncertainty and integrating renewable energy sources. Typical days clustering technique can accurately approximate the full-year time series while maintaining computational tractability. However, its impact on energy system models, especially for multi-regional whole-energy systems, has rarely been studied. In this study, the EnergyScope Multi-Cells model is used to optimize multiple interconnected regions, and a design error metric is developed to find trade-offs between accuracy and computational cost. Results show that using 10 typical days reduces computational time by 8.6 to 23.8 times with a design error below 17%. Time series error is a good predictor of design error in all cases studied, suggesting that it can be used as an a priori metric for selecting the number of typical days without running the optimization model.
Article
Computer Science, Interdisciplinary Applications
Tian Liang, Lin Fu
Summary: In this work, a new shock-capturing framework is proposed based on a new candidate stencil arrangement and the combination of infinitely differentiable non-polynomial RBF-based reconstruction in smooth regions with jump-like non-polynomial interpolation for genuine discontinuities. The resulting scheme achieves high order accuracy and resolves genuine discontinuities with sub-cell resolution.
JOURNAL OF COMPUTATIONAL PHYSICS
(2024)
Article
Computer Science, Interdisciplinary Applications
Lukas Lundgren, Murtazo Nazarov
Summary: In this paper, a high-order accurate finite element method for incompressible variable density flow is introduced. The method addresses the issues of saddle point system and stability problem through Schur complement preconditioning and artificial compressibility approaches, and it is validated to have high-order accuracy for smooth problems and accurately resolve discontinuities.
JOURNAL OF COMPUTATIONAL PHYSICS
(2024)
Article
Computer Science, Interdisciplinary Applications
Gabriele Ciaramella, Laurence Halpern, Luca Mechelli
Summary: This paper presents a novel convergence analysis of the optimized Schwarz waveform relaxation method for solving optimal control problems governed by periodic parabolic PDEs. The analysis is based on a Fourier-type technique applied to a semidiscrete-in-time form of the optimality condition, which enables a precise characterization of the convergence factor at the semidiscrete level. The behavior of the optimal transmission condition parameter is also analyzed in detail as the time discretization approaches zero.
JOURNAL OF COMPUTATIONAL PHYSICS
(2024)
Article
Computer Science, Interdisciplinary Applications
Jonas A. Actor, Xiaozhe Hu, Andy Huang, Scott A. Roberts, Nathaniel Trask
Summary: This article introduces a scientific machine learning framework that uses a partition of unity architecture to model physics through control volume analysis. The framework can extract reduced models from full field data while preserving the physics. It is applicable to manifolds in arbitrary dimension and has been demonstrated effective in specific problems.
JOURNAL OF COMPUTATIONAL PHYSICS
(2024)
Article
Computer Science, Interdisciplinary Applications
Nozomi Magome, Naoki Morita, Shigeki Kaneko, Naoto Mitsume
Summary: This paper proposes a novel strategy called B-spline based SFEM to fundamentally solve the problems of the conventional SFEM. It uses different basis functions and cubic B-spline basis functions with C-2-continuity to improve the accuracy of numerical integration and avoid matrix singularity. Numerical results show that the proposed method is superior to conventional methods in terms of accuracy and convergence.
JOURNAL OF COMPUTATIONAL PHYSICS
(2024)
Article
Computer Science, Interdisciplinary Applications
Timothy R. Law, Philip T. Barton
Summary: This paper presents a practical cell-centred volume-of-fluid method for simulating compressible solid-fluid problems within a pure Eulerian setting. The method incorporates a mixed-cell update to maintain sharp interfaces, and can be easily extended to include other coupled physics. Various challenging test problems are used to validate the method, and its robustness and application in a multi-physics context are demonstrated.
JOURNAL OF COMPUTATIONAL PHYSICS
(2024)
Article
Computer Science, Interdisciplinary Applications
Xing Ji, Fengxiang Zhao, Wei Shyy, Kun Xu
Summary: This paper presents the development of a third-order compact gas-kinetic scheme for compressible Euler and Navier-Stokes solutions, constructed particularly for an unstructured tetrahedral mesh. The scheme demonstrates robustness in high-speed flow computation and exhibits excellent adaptability to meshes with complex geometrical configurations.
JOURNAL OF COMPUTATIONAL PHYSICS
(2024)
Article
Computer Science, Interdisciplinary Applications
Alsadig Ali, Abdullah Al-Mamun, Felipe Pereira, Arunasalam Rahunanthan
Summary: This paper presents a novel Bayesian statistical framework for the characterization of natural subsurface formations, and introduces the concept of multiscale sampling to localize the search in the stochastic space. The results show that the proposed framework performs well in solving inverse problems related to porous media flows.
JOURNAL OF COMPUTATIONAL PHYSICS
(2024)
Article
Computer Science, Interdisciplinary Applications
Jacob Rains, Yi Wang, Alec House, Andrew L. Kaminsky, Nathan A. Tison, Vamshi M. Korivi
Summary: This paper presents a novel method called constrained optimized DMD with Control (cOptDMDc), which extends the optimized DMD method to systems with exogenous inputs and can enforce the stability of the resulting reduced order model (ROM). The proposed method optimally places eigenvalues within the stable region, thus mitigating spurious eigenvalue issues. Comparative studies show that cOptDMDc achieves high accuracy and robustness.
JOURNAL OF COMPUTATIONAL PHYSICS
(2024)
Article
Computer Science, Interdisciplinary Applications
Andrea La Spina, Jacob Fish
Summary: This work introduces a hybridizable discontinuous Galerkin formulation for simulating ideal plasmas. The proposed method couples the fluid and electromagnetic subproblems monolithically based on source and employs a fully implicit time integration scheme. The approach also utilizes a projection-based divergence correction method to enforce the Gauss laws in challenging scenarios. Numerical examples demonstrate the high-order accuracy, efficiency, and robustness of the proposed formulation.
JOURNAL OF COMPUTATIONAL PHYSICS
(2024)
Article
Computer Science, Interdisciplinary Applications
Junhong Yue, Peijun Li
Summary: This paper proposes two numerical methods (IP-FEM and BP-FEM) to study the flexural wave scattering problem of an arbitrary-shaped cavity on an infinite thin plate. These methods successfully decompose the fourth-order plate wave equation into the Helmholtz and modified Helmholtz equations with coupled conditions on the cavity boundary, providing an effective solution to this challenging problem.
JOURNAL OF COMPUTATIONAL PHYSICS
(2024)
Article
Computer Science, Interdisciplinary Applications
William Anderson, Mohammad Farazmand
Summary: We develop fast and scalable methods, called RONS, for computing reduced-order nonlinear solutions. These methods have been proven to be highly effective in tackling challenging problems, but become computationally prohibitive as the number of parameters grows. To address this issue, three separate methods are proposed and their efficacy is demonstrated through examples. The application of RONS to neural networks is also discussed.
JOURNAL OF COMPUTATIONAL PHYSICS
(2024)
Article
Computer Science, Interdisciplinary Applications
Marco Caliari, Fabio Cassini
Summary: In this paper, a second order exponential scheme for stiff evolutionary advection-diffusion-reaction equations is proposed. The scheme is based on a directional splitting approach and uses computation of small sized exponential-like functions and tensor-matrix products for efficient implementation. Numerical examples demonstrate the advantage of the proposed approach over state-of-the-art techniques.
JOURNAL OF COMPUTATIONAL PHYSICS
(2024)
Article
Computer Science, Interdisciplinary Applications
Sebastiano Boscarino, Seung Yeon Cho, Giovanni Russo
Summary: This work proposes a high order conservative semi-Lagrangian method for the inhomogeneous Boltzmann equation of rarefied gas dynamics. The method combines a semi-Lagrangian scheme for the convection term, a fast spectral method for computation of the collision operator, and a high order conservative reconstruction and a weighted optimization technique to preserve conservative quantities. Numerical tests demonstrate the accuracy and efficiency of the proposed method.
JOURNAL OF COMPUTATIONAL PHYSICS
(2024)
Article
Computer Science, Interdisciplinary Applications
Jialei Li, Xiaodong Liu, Qingxiang Shi
Summary: This study shows that the number, centers, scattering strengths, inner and outer diameters of spherical shell-structured sources can be uniquely determined from the far field patterns. A numerical scheme is proposed for reconstructing the spherical shell-structured sources, which includes a migration series method for locating the centers and an iterative method for computing the inner and outer diameters without computing derivatives.
JOURNAL OF COMPUTATIONAL PHYSICS
(2024)