Article
Engineering, Mechanical
P. L. Green, L. J. Devlin, R. E. Moore, R. J. Jackson, J. Li, S. Maskell
Summary: This paper discusses the optimization of the 'L-kernel' in Sequential Monte Carlo samplers to improve performance, resulting in reduced variance of estimates and fewer resampling requirements.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2022)
Article
Engineering, Manufacturing
P. Honarmandi, R. Seede, L. Xue, D. Shoukr, P. Morcos, B. Zhang, C. Zhang, A. Elwany, I. Karaman, R. Arroyave
Summary: The Eagar-Tsai (E-T) model in the context of 3D printing was studied systematically from an uncertainty quantification/propagation (UQ/UP) perspective. Model parameters were calibrated against experimental data using Markov Chain Monte Carlo (MCMC) sampling, and posterior distributions of parameter values were propagated. It was found that discrepancies between predicted and measured melt pool depths existed under keyholing conditions, but a physics-based correction improved agreement with experiments without increasing model complexity significantly.
ADDITIVE MANUFACTURING
(2021)
Article
Computer Science, Theory & Methods
Alix Marie d'Avigneau, Sumeetpal S. Singh, Lawrence M. Murray
Summary: Efficient MCMC algorithms are crucial in Bayesian inference, especially in the context of parallel tempering. This study addresses the issue of randomly varying local move completion times in multi-processor parallel tempering by imposing real-time deadlines on the parallel local moves and performing exchanges at these deadlines without any processor idling. The methodology of exchanges at real-time deadlines is shown to lead to significant performance enhancements without introducing bias, with potential applications in ABC algorithms for parameter estimation.
STATISTICS AND COMPUTING
(2021)
Article
Computer Science, Theory & Methods
Jiangqi Wu, Linjie Wen, Peter L. Green, Jinglai Li, Simon Maskell
Summary: Many real-world problems require estimation of parameters of interest in a Bayesian framework from sequentially collected data. Conventional methods for sampling from posterior distributions do not efficiently address these problems as they do not consider the sequential structure of the data. Therefore, sequential methods like EnKF and SMCS are often used to update the posterior distribution and solve such problems.
STATISTICS AND COMPUTING
(2022)
Article
Computer Science, Theory & Methods
Minas Karamanis, Florian Beutler
Summary: Slice sampling is a powerful Markov Chain Monte Carlo algorithm, but sensitive to user-specified parameters and struggles with strongly correlated distributions. Ensemble Slice Sampling introduces a new class of algorithms that adaptively tune parameters and utilize parallel walkers to efficiently handle strong correlations, significantly improving sampling efficiency.
STATISTICS AND COMPUTING
(2021)
Article
Genetics & Heredity
Kaixian Yu, Zihan Cui, Xin Sui, Xing Qiu, Jinfeng Zhang
Summary: Bayesian networks provide a probabilistic, graphical framework for modeling high-dimensional joint distributions with complex correlation structures and have wide applications in various disciplines. Researchers introduced a three-stage approach named GRASP based on sequential Monte Carlo, with a double filtering strategy and adaptive SMC algorithm to learn network structures of BNs. GRASP showed promising results when tested on benchmark networks, demonstrating its potential in discovering novel biological relationships in integrative genomic studies.
FRONTIERS IN GENETICS
(2021)
Article
Engineering, Chemical
Yota Yamamoto, Tomoyuki Yajima, Yoshiaki Kawajiri
Summary: A sequential Monte Carlo (SMC) parameter estimation method was developed for chromatographic processes to rigorously estimate parameter uncertainty, showing higher efficiency compared to existing methods and reducing time and effort for experimental data analysis.
CHEMICAL ENGINEERING RESEARCH & DESIGN
(2021)
Article
Computer Science, Theory & Methods
Xinzhu Liang, Shangda Yang, Simon L. L. Cotter, Kody J. H. Law
Summary: This paper addresses the problem of estimating expectations when the normalizing constant of the target distribution is unknown and the unnormalized target needs to be approximated at finite resolution. Building upon a recently introduced multi-index sequential Monte Carlo (SMC) ratio estimator, this work combines the complexity improvements of multi-index Monte Carlo (MIMC) with the efficiency of SMC for inference. The proposed method uses a randomization strategy to remove bias entirely, simplifying the estimation process, particularly in the context of MIMC.
STATISTICS AND COMPUTING
(2023)
Article
Statistics & Probability
Lewis J. Rendell, Adam M. Johansen, Anthony Lee, Nick Whiteley
Summary: In order to conduct Bayesian inference with large datasets, it is beneficial to distribute the data across multiple machines. By introducing an instrumental hierarchical model and using an SMC sampler with a sequence of association strengths, approximations of posterior expectations can be improved and the association strength can be adjusted accordingly.
JOURNAL OF COMPUTATIONAL AND GRAPHICAL STATISTICS
(2021)
Article
Statistics & Probability
Joe Marion, Joseph Mathews, Scott C. Schmidler
Summary: We present bounds for the finite-sample error of sequential Monte Carlo samplers on static spaces. Our approach explicitly relates the performance of the algorithm to properties of the chosen sequence of distributions and mixing properties of the associated Markov kernels. This allows us to give the first finite-sample comparison to other Monte Carlo schemes. We obtain bounds for the complexity of sequential Monte Carlo approximations for a variety of target distributions such as finite spaces, product measures, and log-concave distributions including Bayesian logistic regression. The bounds obtained are within a logarithmic factor of similar bounds obtainable for Markov chain Monte Carlo.
ANNALS OF STATISTICS
(2023)
Article
Water Resources
Macarena Amaya, Niklas Linde, Eric Laloy
Summary: ASMC is a method that is well-suited for solving challenging inverse problems in the field of water resources, outperforming parallel tempering (PT) with similar computational budgets. ASMC can partly retrieve both posterior modes in the distribution。
ADVANCES IN WATER RESOURCES
(2022)
Article
Evolutionary Biology
Jakub Truszkowski, Allison Perrigo, David Broman, Fredrik Ronquist, Alexandre Antonelli
Summary: Bayesian phylogenetics faces challenges due to its computational expense and the increasing amount of genomic data. However, new approaches such as online phylogenetics and alternatives to Markov chain Monte Carlo (MCMC) offer potential solutions to scale up Bayesian analyses. Collaborative efforts are needed to develop methods for real-time tree expansion through online phylogenetics.
SYSTEMATIC BIOLOGY
(2023)
Article
Computer Science, Theory & Methods
Ajay Jasra, Kody J. H. Law, Neil Walton, Shangda Yang
Summary: This paper discusses the problem of estimating expectations with respect to a target distribution with an unknown normalizing constant. A multi-index sequential Monte Carlo method is proposed to improve the efficiency of inference, and it is illustrated on various examples to verify its effectiveness.
FOUNDATIONS OF COMPUTATIONAL MATHEMATICS
(2023)
Review
Ecology
Matthias Speich, Carsten F. Dormann, Florian Hartig
Summary: This paper introduces the use of SMC algorithms for Bayesian model calibration and explores the trade-off between efficiency and parallelizability for MCMC and SMC algorithms. By comparing different ecological models, it was found that SMC algorithms can be faster and more efficient than state-of-the-art MCMC algorithms under certain conditions, such as a sufficiently long model runtime and availability of a large number of parallel cores.
ECOLOGICAL MODELLING
(2021)
Review
Statistics & Probability
Christopher Nemeth, Paul Fearnhead
Summary: MCMC algorithms are considered the gold standard technique for Bayesian inference, but the computational cost can be prohibitive for large datasets, leading to the development of scalable Monte Carlo algorithms. One type of these algorithms is SGMCMC, which reduces per-iteration cost by utilizing data subsampling techniques.
JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION
(2021)
Article
Mechanics
William S. LePage, John A. Shaw, Samantha H. Daly
Summary: The study revealed that crystallographic texture significantly affects the fatigue performance of NiTi sheet, with strong orientation-dependent mechanisms of plasticity, transformation, and twinning on both functional and structural fatigue. Under stress-controlled cycling, tension along textures similar to that of the TD demonstrated better fatigue performance.
INTERNATIONAL JOURNAL OF SOLIDS AND STRUCTURES
(2021)
Article
Nanoscience & Nanotechnology
Brent R. Goodlet, Sean P. Murray, Ben Bales, Jeff Rossin, Chris J. Torbet, Tresa M. Pollock
Summary: A novel experimental setup was developed to collect resonant ultrasound spectroscopy (RUS) data from heated metallic specimens, specifically focusing on the CoNi-based superalloy SB-CoNi-10+. Bayesian inference was used to estimate elastic constants and crystal orientation parameters at elevated temperatures, revealing changes in material properties with increasing temperature.
MATERIALS SCIENCE AND ENGINEERING A-STRUCTURAL MATERIALS PROPERTIES MICROSTRUCTURE AND PROCESSING
(2021)
Article
Engineering, Mechanical
Sriram Ganesan, Mohammadreza Yaghoobi, Alan Githens, Zhe Chen, Samantha Daly, John E. Allison, Veera Sundararaghavan
Summary: This study investigates the effects of heat treatment on the mechanical response of a WE43 Mg alloy using an integrated framework of SEM-DIC experiment and CPFE simulation, focusing on local displacement and strain. By evaluating the CPFE framework with results from SEM-DIC experiment, the effects of heat treatment were analyzed using CRSS and relative slip activity. The study also addresses the contributions of different strengthening mechanisms on CRSS in WE43 Mg alloy.
INTERNATIONAL JOURNAL OF PLASTICITY
(2021)
Article
Materials Science, Multidisciplinary
Ryan Sperry, Songyang Han, Zhe Chen, Samantha H. Daly, Martin A. Crimp, David T. Fullwood
Summary: This study assessed the use of various methods including SEM-DIC, AFM, ECCI, and HR-EBSD to characterize slip-system activity on Ti-7Al material. The comparison presented the advantages, disadvantages, and effective complementary use of these methods. The study showed that by using these methods in tandem, multi-modal information on slip band identification, strain and orientation gradients, and the presence of GNDs and SSDs can be obtained to inform and validate dislocation-based crystal plasticity models.
MATERIALS CHARACTERIZATION
(2021)
Article
Engineering, Mechanical
M. E. Harr, S. Daly, A. L. Pilchak
Summary: Research found that slip activity in Ti-6Al-2Sn-4Zr-2Mo was more rapid and accumulated more at lower temperatures exhibiting dwell sensitivity, compared to higher temperatures. Plasticity primarily occurred through long-range basal slip in colocated grains with a high basal Schmid factor at all temperatures.
INTERNATIONAL JOURNAL OF FATIGUE
(2021)
Article
Chemistry, Physical
C. Muir, B. Swaminathan, K. Fields, A. S. Almansour, K. Sevener, C. Smith, M. Presby, J. D. Kiser, T. M. Pollock, S. Daly
Summary: In this study, it was demonstrated that identifying damage mechanisms from acoustic emission signals in minicomposites with elastically similar constituents is possible. By partitioning signals through spectral clustering, matrix cracking and fiber failure were successfully identified based on the frequency information they contained, following the damage chronology.
NPJ COMPUTATIONAL MATERIALS
(2021)
Article
Engineering, Mechanical
J. Geathers, C. J. Torbet, J. W. Jones, S. Daly
Summary: Water vapor has a significant impact on the small fatigue crack growth rates in Ti-6242S alloy, with a linear dependence observed between crack growth rate and water vapor pressure. This work highlights the importance of humidity in determining fatigue life even at high cyclic frequencies.
INTERNATIONAL JOURNAL OF FATIGUE
(2022)
Article
Materials Science, Multidisciplinary
Jeff Rossin, Patrick Leser, Kira Pusch, Carolina Frey, Sven C. Vogel, Alec I. Saville, Chris Torbet, Amy J. Clarke, Samantha Daly, Tresa M. Pollock
Summary: This study used Bayesian inference with Sequential Monte Carlo to determine the single crystal elastic constants of additively manufactured cobalt-nickel-based superalloy specimens from resonant frequencies and texture data. The results were validated with measurements on bulk single crystal specimens and neutron diffraction data. This approach offers an economical and efficient way to determine elastic constants, avoiding the need for expensive single crystal fabrication or synchrotron experiments.
MATERIALS CHARACTERIZATION
(2022)
Article
Materials Science, Multidisciplinary
N. R. Brodnik, C. Muir, N. Tulshibagwale, J. Rossin, M. P. Echlin, C. M. Hamel, S. L. B. Kramer, T. M. Pollock, J. D. Kiser, C. Smith, S. H. Daly
Summary: Experimental solid mechanics is experiencing a crucial moment where the integration of machine learning (ML) approaches into the discovery process is rapidly increasing. The adoption of ML methods in mechanics originated from non-science and engineering applications, raising concerns about the reliability of the obtained physical results. To address this, it is necessary to incorporate physical principles into ML architectures, evaluate and compare them using benchmark datasets, and test their broad applicability. These principles allow for meaningful categorization, comparison, evaluation, and extension of ML models across various experimental and computational frameworks. Two different use cases, acoustic emission and resonant ultrasound spectroscopy, are examined to demonstrate the application of these principles and discussions are provided regarding the future prospects of trustworthy ML in experimental mechanics.
JOURNAL OF THE MECHANICS AND PHYSICS OF SOLIDS
(2023)
Article
Chemistry, Physical
Devendra K. Jangid, Neal R. Brodnik, Michael G. Goebel, Amil Khan, SaiSidharth Majeti, McLean P. Echlin, Samantha H. Daly, Tresa M. Pollock, B. S. Manjunath
Summary: In computer vision, single-image super-resolution (SISR) has been extensively explored on optical images, but its application on images outside this domain, such as scientific experiment images, is not well investigated. This paper presents a broadly adaptable approach for applying state-of-art SISR networks to generate high-resolution EBSD images.
NPJ COMPUTATIONAL MATERIALS
(2022)
Article
Materials Science, Ceramics
C. Muir, B. Swaminathan, A. K. Musaffar, N. R. Mccarthy, A. S. Almansour, T. M. Pollock, J. D. Kiser, C. Smith, S. Daly, K. Sevener
Summary: Crack opening displacements (CODs) in ceramic matrix composites (CMCs) affect their environmental degradation rates. This study experimentally demonstrates that a significant proportion of CODs deviate from the commonly assumed s(2) dependence in models. In situ measurements of transverse matrix cracks in SiC/SiC minicomposites reveal that crack geometries and proximity to neighboring cracks contribute to this deviation.
JOURNAL OF THE EUROPEAN CERAMIC SOCIETY
(2023)
Article
Engineering, Manufacturing
Devendra K. Jangid, Neal R. Brodnik, Amil Khan, Michael G. Goebel, McLean P. Echlin, Tresa M. Pollock, Samantha H. Daly, B. S. Manjunath
Summary: This paper presents a GAN capable of producing realistic microstructure morphology features and demonstrates its capabilities on a dataset of crystalline titanium grain shapes. It also introduces an approach to train deep learning networks to understand material-specific descriptor features based on existing conceptual relationships.
INTEGRATING MATERIALS AND MANUFACTURING INNOVATION
(2022)
Article
Engineering, Manufacturing
Mohammadreza Yaghoobi, Zhe Chen, Veera Sundararaghavan, Samantha Daly, John E. Allison
Summary: Crystal plasticity simulation is an important tool for advanced Integrated Computational Materials Engineering for metals and alloys. In this study, a calibration and validation framework for CPFE simulation of extension twinning in Mg alloy WE43 using SEM-DIC technique was presented. The results show that CPFE can successfully model the macroscopic stress-strain response and the twin area fraction and can also capture microscale strain and twinning.
INTEGRATING MATERIALS AND MANUFACTURING INNOVATION
(2021)
Article
Materials Science, Multidisciplinary
Y. Liu, K. Zweiacker, C. Liu, J. T. McKeown, J. M. K. Wiezorek
Summary: The evolution of rapid solidification microstructure and solidification interface velocity of hypereutectic Al-20at.%Cu alloy after laser melting has been studied experimentally. It was found that the formation of microstructure was dominated by eutectic, alpha-cell, and banded morphology grains, and the growth modes changed with increasing interface velocity.
Article
Materials Science, Multidisciplinary
Bharat Gwalani, Julian Escobar, Miao Song, Jonova Thomas, Joshua Silverstein, Andrew Chihpin Chuang, Dileep Singh, Michael P. Brady, Yukinori Yamamoto, Thomas R. Watkins, Arun Devaraj
Summary: Castable alumina forming austenitic alloys exhibit superior creep life and oxidation resistance at high temperatures. This study reveals the mechanism behind the enhanced creep performance of these alloys by suppressing primary carbide formation and offers a promising alloy design strategy for high-temperature applications.
Article
Materials Science, Multidisciplinary
Jian Song, Qi Zhang, Songsong Yao, Kunming Yang, Houyu Ma, Jiamiao Ni, Boan Zhong, Yue Liu, Jian Wang, Tongxiang Fan
Summary: Recent studies have shown that achieving an atomically flat surface for metals can greatly improve their oxidation resistance and enhance their electronic-optical applications. Researchers have explored the use of graphene as a covering layer to achieve atomically flat surfaces. They found that high-temperature deposited graphene on copper surfaces formed mono-atomic steps, while annealed copper and transferred graphene on copper interfaces formed multi-atomic steps.
Article
Materials Science, Multidisciplinary
Jennifer A. Glerum, Jon-Erik Mogonye, David C. Dunand
Summary: Elemental powders of Al, Ti, Sc, and Zr are blended and processed via laser powder-bed fusion to create binary and ternary alloys. The microstructural analysis and mechanical testing show that the addition of Ti results in the formation of primary precipitates, while the addition of Sc and Zr leads to the formation of fine grain bands. The Al-0.25Ti-0.25Zr alloy exhibits comparable strain rates to Al-0.5Zr at low stresses, but significantly higher strain rates at higher stresses during compressive creep testing. Finite element modeling suggests that the connectivity of coarse and fine grain regions is a critical factor affecting the creep resistance of the alloys.
Article
Materials Science, Multidisciplinary
P. Jannotti, B. C. Hornbuckle, J. T. Lloyd, N. Lorenzo, M. Aniska, T. L. Luckenbaugh, A. J. Roberts, A. Giri, K. A. Darling
Summary: This work characterizes the thermo-mechanical behavior of bulk nanocrystalline Cu-Ta alloys under extreme conditions. The experiments reveal that the alloys exhibit unique mechanical properties, behaving differently from conventional nanocrystalline Cu. They do not undergo grain coarsening during extrusion and exhibit behavior similar to coarse-grained Cu.
Article
Materials Science, Multidisciplinary
Yiqing Wei, Jingwei Li, Daliang Zhang, Bin Zhang, Zizhen Zhou, Guang Han, Guoyu Wang, Carmelo Prestipino, Pierric Lemoine, Emmanuel Guilmeau, Xu Lu, Xiaoyuan Zhou
Summary: This study proposes a new strategy to modify microstructure by phase regulation, which can simultaneously enhance carrier mobility and reduce lattice thermal conductivity. The addition of Cu in layered SnSe2 induces a phase transition that leads to increased grain size and reduced stacking fault density, resulting in improved carrier mobility and lower lattice thermal conductivity.
Article
Materials Science, Multidisciplinary
Jia Chen, Zhengyu Zhang, Eitan Hershkovitz, Jonathan Poplawsky, Raja Shekar Bhupal Dandu, Chang-Yu Hung, Wenbo Wang, Yi Yao, Lin Li, Hongliang Xin, Honggyu Kim, Wenjun Cai
Summary: In this study, the structural origin of the pH-dependent repassivation mechanisms in multi-principal element alloys (MPEA) was investigated using surface characterization and computational simulations. It was found that selective oxidation in acidic to neutral solutions leads to enhanced nickel enrichment on the surface, resulting in reduced repassivation capability and corrosion resistance.
Article
Materials Science, Multidisciplinary
X. Y. Xu, C. P. Huang, H. Y. Wang, Y. Z. Li, M. X. Huang
Summary: The limited slip systems of magnesium (Mg) and its alloys hinder their wide applications. By conducting tensile straining experiments, researchers discovered a rate-dependent transition in the dislocation mechanisms of Mg alloys. At high strain rates, glissile dislocations dominate, while easy-glide dislocations dominate at low strain rates. Abundant glissile dislocations do not necessarily improve ductility.
Article
Materials Science, Multidisciplinary
M. S. Szczerba, M. J. Szczerba
Summary: Inverse temperature dependences of the detwinning stress were observed in face-centered cubic deformation twins in Cu-8at.%Al alloy. The detwinning stress increased with temperature when the pi detwinning mode was involved, but decreased when the pi/3 mode was involved. The dual effect of temperature on the detwinning stress was due to the reduction of internal stresses pre-existing within the deformation twins. The complete reduction of internal stresses at about 530 degrees C led to the equivalence of the critical stresses of different detwinning modes and a decrease in the yield stress anisotropy of the twin/matrix structure.
Article
Materials Science, Multidisciplinary
Taowen Dong, Tingting Qin, Wei Zhang, Yaowen Zhang, Zhuoran Feng, Yuxiang Gao, Zhongyu Pan, Zixiang Xia, Yan Wang, Chunming Yang, Peng Wang, Weitao Zheng
Summary: The interaction between the electrode and the electric double layer (EDL) significantly influences the energy storage mechanism. By studying the popular alpha-Fe2O3 electrode and the EDL interaction, we find that the energy storage mechanism of the electrode can be controlled by modulating the EDL.
Article
Materials Science, Multidisciplinary
Matthew R. Barnett, Jun Wang, Sitarama R. Kada, Alban de Vaucorbeil, Andrew Stevenson, Marc Fivel, Peter A. Lynch
Summary: The elastic-plastic transition in magnesium alloy Mg-4.5Zn exhibits bursts of deformation, which are characterized by sudden changes in grain orientation. These bursts occur in a coordinated manner among nearby grains, with the highest burst rate observed at the onset of full plasticity. The most significant burst events are associated with twinning, supported by the observation of twinned structures using electron microscopy. The bursts are often preceded and followed by a stasis in peak movement, indicating a certain "birth size" for twins upon formation and subsequent growth at a later stage.
Article
Materials Science, Multidisciplinary
Vaidehi Menon, Sambit Das, Vikram Gavini, Liang Qi
Summary: Understanding solute segregation thermodynamics is crucial for investigating grain boundary properties. The spectral approach and thermodynamic integration methods can be used to predict solute segregation behavior at grain boundaries and compare with experimental observations, thus aiding in alloy design and performance control.
Article
Materials Science, Multidisciplinary
Feiyu Qin, Lei Hu, Yingcai Zhu, Yuki Sakai, Shogo Kawaguchi, Akihiko Machida, Tetsu Watanuki, Yue-Wen Fang, Jun Sun, Xiangdong Ding, Masaki Azuma
Summary: This study reports on the negative and zero thermal expansion properties of Cd2Re2O7 and Cd1.95Ni0.05Re2O7 materials, along with their ultra-low thermal conductivity. Through investigations of their structures and phonon calculations, the synergistic effect of local structure distortion and soft phonons is revealed as the key to achieving these distinctive properties.
Article
Materials Science, Multidisciplinary
Thomas Beerli, Christian C. Roth, Dirk Mohr
Summary: A novel testing system for miniature specimens is designed to characterize the plastic response of materials for which conventional full-size specimens cannot be extracted. The system has an automated operation process, which reduces the damage to specimens caused by manual handling and improves the stability of the test results. The experiments show that the miniature specimens extracted from stainless steel and aluminum have high reproducibility, and the results are consistent with those of conventional-sized specimens. A correction procedure is provided to consider the influence of surface roughness and heat-affected zone caused by wire EDM.
Article
Materials Science, Multidisciplinary
Rani Mary Joy, Paulius Pobedinskas, Nina Baule, Shengyuan Bai, Daen Jannis, Nicolas Gauquelin, Marie-Amandine Pinault-Thaury, Francois Jomard, Kamatchi Jothiramalingam Sankaran, Rozita Rouzbahani, Fernando Lloret, Derese Desta, Jan D'Haen, Johan Verbeeck, Michael Frank Becker, Ken Haenen
Summary: This study investigates the influence of film microstructure and composition on the Young's modulus and residual stress in nanocrystalline diamond thin films. The results provide insights into the mechanical properties and intrinsic stress sources of these films, and demonstrate the potential for producing high-quality nanocrystalline diamond films under certain conditions.