Article
Computer Science, Interdisciplinary Applications
Yong Pang, Liangliang Yang, Yitang Wang, Xiaonan Lai, Wei Sun, Xueguan Song
Summary: This research addresses the limitations of Latin hypercube design in constrained design space by developing Latin hypervolume designs with good space-filling and noncollapsing properties. Monte Carlo sampling is introduced to approximate the hypervolume in high-dimensional and irregular design spaces. The experiments demonstrate that the proposed method is considerably better compared to other methods in benchmark numerical examples and engineering modeling scenarios.
ENGINEERING WITH COMPUTERS
(2023)
Article
Green & Sustainable Science & Technology
Jilin Cai, Lili Hao, Qingshan Xu, Keqi Zhang
Summary: A scalable Latin hypercube importance sampling (ELHIS) method is proposed in this paper, which combines importance sampling (IS) and Latin hypercube sampling (LHS) to reduce the computational costs of evaluating power system reliability, and shows good performance on test systems.
SUSTAINABLE ENERGY TECHNOLOGIES AND ASSESSMENTS
(2022)
Article
Multidisciplinary Sciences
Roland Sandt, Robert Spatschek
Summary: Quantum annealing is an efficient technique for determining ground state configurations of binary optimization problems described by Ising Hamiltonians. In this study, we demonstrate a low-cost computational method for calculating finite temperature properties. The method is particularly effective at low temperatures, where conventional approaches suffer from high rejection rates and significant statistical noise. We validate the approach by applying it to spin glasses and Ising chains.
SCIENTIFIC REPORTS
(2023)
Article
Engineering, Civil
Huy-Khanh Dang, Duc-Kien Thai, Seung-Eock Kim
Summary: This paper proposes a stochastic analysis model that combines the refined plastic-hinge analysis method with the Monte Carlo simulation to predict the realistic resistance of steel structures. The model treats the uncertainty quantifications of the material properties, geometry, and semi-rigid connections as independent random variables in the discretized stochastic fields using Latin hypercube sampling. The study finds that the uncertainties in material properties are the most sensitive, and the correlation of these parameters with the strength of structures is also significant. To improve the load and resistance factor design criterion, a resistance factor of 0.93 is suggested for the beam-columns in the frames under axial force, torsion, and biaxial bending moments. A stochastic response spectrum is proposed to define the boundary of strength, where a clearly defined plastic mechanism is attained. Furthermore, this study provides valuable insights into the stochastic resistance of steel frames, which are essential for practical engineering applications.
ENGINEERING STRUCTURES
(2023)
Article
Computer Science, Interdisciplinary Applications
Minh-Chien Trinh, Hyungmin Jun
Summary: This study thoroughly examines the deterministic and stochastic bending and buckling characteristics of antisymmetric cross-ply and angle-ply laminated composite plates, and presents two stochastic sampling methods. The probability distribution functions provide good assessments for the effects of uncertainty on the bending and buckling behaviors of the laminated composites.
ENGINEERING WITH COMPUTERS
(2023)
Article
Statistics & Probability
Michael Gnewuch, Nils Hebbinghaus
Summary: In this paper, a new class of gamma-negatively dependent random samples is introduced, and probabilistic upper bounds for star discrepancies are provided. These bounds are optimal for Monte Carlo and Latin hypercube samples.
ANNALS OF APPLIED PROBABILITY
(2021)
Article
Computer Science, Interdisciplinary Applications
Huy-Khanh Dang, Duc-Kien Thai, Seung-Eock Kim
Summary: This paper develops a Stochastic Practical Advanced Analysis Program for stochastic analysis of structural steel frames by combining the second-order refined plastic-hinge analysis method with the simulation of Latin Hypercube Sampling. The program predicts the ultimate load-carrying capacity of steel frames and investigates the sensitivity of uncertain input parameters. The results can be used in steel structure design and maintenance in practice.
ADVANCES IN ENGINEERING SOFTWARE
(2023)
Article
Chemistry, Multidisciplinary
Karol Durczak, Piotr Rybacki, Agnieszka Sujak
Summary: Knowledge of the use-to-failure periods of process equipment, including agricultural vehicles, is crucial for assessing their durability and reliability. However, obtaining empirical data on this issue is challenging. This study compares empirical data with data generated using statistical tools and finds that the Monte Carlo method is the most effective in the studied case. The findings validate the use of these methods in predicting the use-to-failure periods.
APPLIED SCIENCES-BASEL
(2022)
Article
Operations Research & Management Science
Roberto Casarin, Bertrand B. Maillet, Anthony Osuntuyi
Summary: This article introduces two new stochastic optimization-based simulated annealing algorithms for addressing problems associated with statistical methods. These methods are effective in handling integral constrained optimization problems and show potential in financial applications.
ANNALS OF OPERATIONS RESEARCH
(2022)
Article
Optics
Yu Jiang, Manabu Machida, Norikazu Todoroki
Summary: Diffuse optical tomography uses near-infrared light and an iterative numerical scheme, with simulated annealing proposed as a method to find solutions even without good initial guesses. The proposed numerical method successfully reconstructs targets in the medium by finding the ground state of a spin Hamiltonian using simulated annealing.
JOURNAL OF THE OPTICAL SOCIETY OF AMERICA A-OPTICS IMAGE SCIENCE AND VISION
(2021)
Article
Engineering, Mechanical
Fernando Valentini, Olavo M. Silva, Andre Jacomel Torii, Eduardo Lenz Cardoso
Summary: This work proposes a new forward uncertainty method for evaluating the expected value, the variance and their sensitivities. The method is evaluated for different numbers of uncertain variables in a highly nonlinear problem, and compared against baseline methods. The results show that the proposed method provides accurate estimates.
JOURNAL OF THE BRAZILIAN SOCIETY OF MECHANICAL SCIENCES AND ENGINEERING
(2022)
Article
Engineering, Civil
John Thedy, Kuo-Wei Liao
Summary: A novel Importance Sampling method for calculating reliability in structural engineering problems using multiple spheres was proposed, which maximizes the number of safety samples by introducing spheres with different radii and centers, leading to reduced computational cost and improved efficiency. Compared to traditional methods, the proposed approach demonstrates higher robustness and efficiency.
Article
Materials Science, Multidisciplinary
Matthew Grasinger, Kaushik Dayal, Gal deBotton, Prashant K. Purohit
Summary: Constitutive modeling of dielectric elastomers has been developed over the last two decades to couple the electrical response of polymers with large deformations, but lacks consideration of the coupled electromechanical response of single polymer chains, which can be addressed using statistical mechanics. This paper computes the stretch and polarization of single polymer chains subjected to fixed force and electric field through statistical mechanics, obtaining analytical results and validating them through Monte Carlo simulations. The study also introduces a new sampling method that improves convergence and shows agreement between analytical expressions and simulation results across a range of forces and electric fields.
JOURNAL OF THE MECHANICS AND PHYSICS OF SOLIDS
(2022)
Article
Operations Research & Management Science
Jangho Park, Rebecca Stockbridge, Guzin Bayraksan
Summary: This paper investigates the variance reduction techniques Antithetic Variates (AV) and Latin Hypercube Sampling (LHS) when used for sequential sampling in stochastic programming and presents a comparative computational study. The results show that LHS typically dominates in the non-sequential setting while performing well sequentially and AV gains some advantages in the sequential setting. These findings suggest that AV and LHS sequential procedures can be attractive alternatives for a class of stochastic programs due to their ease of implementation and improved empirical performance compared to random sampling.
ANNALS OF OPERATIONS RESEARCH
(2021)
Article
Engineering, Mechanical
Aleksander Karolczuk, Marta Kurek
Summary: The estimation of uncertainty in fatigue life prediction is an important factor in structural design. In the case of multiaxial loading, numerical algorithms are often used to narrow down the choice of uncertainty estimation to stochastic sampling. This study tests and compares the effectiveness of Latin hypercubes and Monte Carlo technique in the uncertainty of life prediction under multiaxial loading, using the results of experimental tests on 16Mo3 steel.
INTERNATIONAL JOURNAL OF FATIGUE
(2022)
Article
Statistics & Probability
Miroslav Vorechovsky, Jan Elias
Article
Chemistry, Analytical
Ronghua Fu, Hao Xu, Zijian Wang, Lei Shen, Maosen Cao, Tongwei Liu, Drahomir Novak
Article
Mechanics
Miroslav Vorechovsky, Jan Elias
ENGINEERING FRACTURE MECHANICS
(2020)
Article
Mechanics
Jan Elias, Miroslav Vorechovsky
ENGINEERING FRACTURE MECHANICS
(2020)
Article
Engineering, Multidisciplinary
Rostislav Chudoba, Yingxiong Li, Rostislav Rypl, Homam Spartali, Miroslav Vorechovsky
Summary: The paper presents a probabilistic model to capture the multiple-cracking behavior of unidirectional brittle-matrix composites loaded in tension. This model introduces two key features that enhance efficiency and flexibility, including identifying emerging cracks within a minimum number of load increments and using a crack-tracing algorithm based on an abstract description of crack bridge behavior. By combining the crack-tracing algorithm with a variety of crack bridge models, specific phenomena of bond behavior in different types of composites can be accounted for.
APPLIED MATHEMATICAL MODELLING
(2021)
Article
Mechanics
Miroslav Vorechovsky, Yingxiong Li, Rostislav Rypl, Rostislav Chudoba
Summary: A combined experimental and numerical characterization method is presented for the composite tensile behavior of concrete reinforced with non-impregnated carbon textile fabrics. The modeling approach needs to account for the heterogeneous structure of the bond layer.
COMPOSITE STRUCTURES
(2021)
Article
Computer Science, Interdisciplinary Applications
Petr Henys, Miroslav Vorechovsky, Michal Kuchar, Axel Heinemann, Jiri Kopal, Benjamin Ondruschka, Niels Hammer
Summary: This study investigated the variability in bone density at different locations using a random field model and found that average bone density can be well simulated with a Gaussian random field. The proposed model enhances computational biomechanical models and represents a step forward in in-silico medicine.
COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE
(2021)
Article
Engineering, Multidisciplinary
Lukas Novak, Miroslav Vorechovsky, Vaclav Sadilek, Michael D. Shields
Summary: This paper introduces a novel adaptive sequential sampling method for constructing Polynomial Chaos Expansion surrogate models. The technique aims to obtain an optimal sample at each stage by extending the experimental design one by one. The strategy selects candidate points proportionally to their local variance contribution, balancing the exploitation of the surrogate model and exploration of the design domain.
COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING
(2021)
Article
Engineering, Biomedical
Petr Henys, Miroslav Vorechovsky, Jan Stebel, Michal Kuchar, Pavel Exner
Summary: The study compared the continuous and discontinuous finite element methods for mapping bone density data, with the discontinuous zero-order variant appearing to be the most advantageous in terms of accuracy and efficiency. The continuous finite element method is analogous to the nodal formulation, while the discontinuous finite element method is analogous to the element formulation.
CLINICAL BIOMECHANICS
(2022)
Article
Engineering, Multidisciplinary
Rostislav Chudoba, Miroslav Vorechovsky, Mario Aguilar, Abedulgader Baktheer
Summary: This study proposes a thermodynamically consistent model for computational components, which captures the 3D kinematics of interfaces under different loading histories. The model introduces novel forms of potentials for free energy, threshold function, and dissipation, and incorporates features such as damage development, general time integration, and coupling between normal and tangential damage evolution.
COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING
(2022)
Article
Engineering, Multidisciplinary
Miroslav Vorechovsky
Summary: The paper presents a new method for estimating the rare event probability for computational models that only return categorical information. The method uses a distance-based surrogate model and performs sequential adaptive selection of points for evaluation and improvement. The method allows for estimation of failure probability and selection of the best candidate for further model evaluation.
COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING
(2022)
Article
Engineering, Civil
Aleksei Gerasimov, Miroslav Vorechovsky
Summary: This article proposes an algorithm for point selection and failure probability estimation in small to moderate dimension design domains. The algorithm improves failure probability estimation by progressively refining the boundary between safe and failure domains. It is particularly useful for situations where evaluating the performance function is expensive and the function is highly nonlinear, noisy, or discrete.
Article
Multidisciplinary Sciences
Marcos Gonzalez Lopez, Barbora Huteckova, Josef Lavicky, Nikodem Zezula, Vladislav Rakultsev, Vendula Fridrichova, Haneen Tuaima, Cita Nottmeier, Julian Petersen, Michaela Kavkova, Tomas Zikmund, Jozef Kaiser, Rupali Lav, Haza Star, Vitezslav Bryja, Petr Henys, Miroslav Vorechovsky, Abigail S. S. Tucker, Jakub Harnos, Marcela Buchtova, Jan Krivanek
Summary: Mineralized tissues, such as bones or teeth, are vital structures that enable movement, protection, and food processing for vertebrates. However, accurately tracking the growth and healing dynamics of these tissues is currently challenging. The BEE-ST approach presented here allows precise quantification of development, regeneration, remodeling, and healing in any type of calcified tissue across different species, opening up possibilities in developmental biology, bone and tooth healing, tissue engineering, and disease modeling.
Article
Computer Science, Interdisciplinary Applications
Miroslav Vorechovsky, Jan Masek
ADVANCES IN ENGINEERING SOFTWARE
(2020)
Article
Computer Science, Interdisciplinary Applications
Jan Elias, Miroslav Vorechovsky, Vaclav Sadilek
ADVANCES IN ENGINEERING SOFTWARE
(2020)
