Article
Computer Science, Interdisciplinary Applications
Mhd Ammar Hafez, Jason P. Halloran
Summary: Computational knee models are sensitive to the mechanical parameters of ligaments. This study compared quasi-MC and polynomial chaos expansion sensitivity analyses of predicted condylar reactions, taking into account uncertainty in the ligament mechanical parameters.
COMPUTER METHODS IN BIOMECHANICS AND BIOMEDICAL ENGINEERING
(2023)
Article
Engineering, Civil
Jinyan Zhao, Andrea Franza, Matthew J. DeJong
Summary: The study introduces a method for assessing uncertainty in surface structure damage caused by tunneling-induced ground movements, utilizing Monte Carlo simulation and a numerical model to predict structural damage and identify dominant factors. Two case studies reveal that volume loss is the primary source of uncertainty in building damage prediction, while uncertainties in building properties and ground movements are nearly equally responsible for structural damage uncertainty.
ASCE-ASME JOURNAL OF RISK AND UNCERTAINTY IN ENGINEERING SYSTEMS PART A-CIVIL ENGINEERING
(2021)
Review
Engineering, Industrial
Giray Okten, Yaning Liu
Summary: Randomized quasi-Monte Carlo methods are becoming more popular in applications due to their faster convergence rate and the availability of simple statistical tools for analyzing estimation errors.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2021)
Article
Engineering, Geological
Chao Zhao, Wenping Gong, Tianzheng Li, C. Hsein Juang, Huiming Tang, Hui Wang
Summary: Accurate characterization of subsurface stratigraphic configuration is crucial to geotechnical engineering work, but uncertainty can be significant due to complexity and limited data availability. This paper presents a method for characterizing subsurface stratigraphy with limited borehole data, demonstrating its effectiveness and advantages through comparative analyses and a case study in Western Australia.
ENGINEERING GEOLOGY
(2021)
Article
Mathematics, Interdisciplinary Applications
John Barr, Herschel Rabitz
Summary: This paper describes a method for global sensitivity analysis based on embedding the joint probability distribution of multiple outputs into RKHS and measuring the distance between embeddings using maximum mean discrepancy. This method has the advantage of easy computability for high-dimensional outputs and determining the influence of input parameters on different features.
SIAM-ASA JOURNAL ON UNCERTAINTY QUANTIFICATION
(2022)
Article
Engineering, Industrial
Subal C. Kumbhakar, Mike G. Tsionas
Summary: This paper introduces a model that considers both output and input-specific inefficiency components using a translog function to represent production technology and Bayesian inference techniques for estimation. Empirical findings from the UK manufacturing firms panel data show average slacks for labor and capital at 2.35% and 10.74%, respectively, with revenue loss from technical inefficiency and input slacks at 2.43% and 9.2%, on average.
INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS
(2021)
Article
Computer Science, Interdisciplinary Applications
Matieyendou Lamboni
Summary: Weighted Poincare-type inequalities provide upper bounds for function variance, aiding in sensitivity analysis for identifying active inputs. However, these upper bounds may be impractically high. New results generalize for any function and propose a new proxy measure for sensitivity analysis.
MATHEMATICS AND COMPUTERS IN SIMULATION
(2021)
Article
Engineering, Biomedical
J. J. Scheins, M. Lenz, U. Pietrzyk, N. J. Shah, C. Lerche
Summary: Monte Carlo simulations are fundamental for modeling photon interactions in PET, with GATE being a popular software due to its accuracy and flexibility, but simulations are time-consuming. GPUs have been proposed as a solution for acceleration, while multi-threading on powerful CPUs can also improve speed significantly.
PHYSICS IN MEDICINE AND BIOLOGY
(2021)
Article
Engineering, Geological
Weizhang Liang, Huanxin Liu, Guoyan Zhao, Ying Chen, Ju Ma, Ming Lan
Summary: This study proposes a methodology that integrates Monte Carlo simulation (MCS) and machine learning (ML) algorithms to evaluate the probability of strainburst potential. By establishing a numerical model and proposing a novel indicator, the strainburst potential of rock mass can be quantitatively assessed. The combination of seven different ML algorithms and MCS improves computational efficiency and provides reliable probability evaluation of strainburst potential.
ROCK MECHANICS AND ROCK ENGINEERING
(2023)
Article
Nuclear Science & Technology
Tung Dong Cao Nguyen, Hyunsuk Lee, Deokjung Lee
Summary: The study reports the generation of Multigroup cross section (MG XS) using the UNIST in-house Monte Carlo (MC) code MCS for fast reactor analysis, with validation and evaluation on two specified sodium fast reactor models; the results indicate the feasibility of this approach for high-fidelity analysis of fast reactors.
NUCLEAR ENGINEERING AND TECHNOLOGY
(2021)
Article
Mathematics
Hilmar Gudmundsson, David Vyncke
Summary: The proposed new calibration method of weighted Monte Carlo approach significantly improves the out-of-sample fit compared to the original method by incorporating a probability distortion scheme and assigning multiple weights per path to fit with different maturities.
Article
Computer Science, Interdisciplinary Applications
Ungki Lee, Ikjin Lee
Summary: Reliability-based design optimization (RBDO) aims to find an optimum design that meets reliability requirements and minimizes objective functions. This study introduces a weighted RBDO (WRBDO) framework that assigns different weights to failures based on their magnitude and derives an optimum design that quantitatively reflects the magnitude of failures.
STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION
(2022)
Article
Computer Science, Interdisciplinary Applications
Farshid Nasrfard, Mohammad Mohammadi, Mohammad Rastegar
Summary: This study proposes a probabilistic approach that considers correlations and uncertainties to find the optimal inspection rates for power systems. The results show that considering these factors can change the optimal inspection rates and reduce costs and unavailability in comparison to conventional approaches. The method is simple and accurate and can be integrated into asset management tools for maintenance decision-making.
COMPUTERS & INDUSTRIAL ENGINEERING
(2022)
Article
Chemistry, Physical
Kengo Takemoto, Yoshiki Ishii, Hitoshi Washizu, Kang Kim, Nobuyuki Matubayasi
Summary: The nematic-isotropic phase transition of 4-cyano-4'-pentylbiphenyl was simulated using the generalized replica-exchange method, and compared with the temperature replica-exchange method. The results showed that the generalized replica-exchange method was effective in sampling configurations around the transition temperature and exhibited a bimodal distribution of the order parameter, while the temperature replica-exchange method was ineffective due to the energy gap between the nematic and isotropic phases.
JOURNAL OF CHEMICAL PHYSICS
(2022)
Article
Thermodynamics
Mi Dong, Ya Li, Dongran Song, Jian Yang, Mei Su, Xiaofei Deng, Lingxiang Huang, M. H. Elkholy, Young Hoon Joo
Summary: This paper presents an analytical framework for uncertainty in the cost of wind power generation, improving cost prediction accuracy by considering inflation and the learning curve. The study finds that the scale parameter has the most significant impact on the levelized cost of energy, and a 38% margin is needed to ensure a 95% reliability for changes caused by uncertainty factors.
ENERGY CONVERSION AND MANAGEMENT
(2021)
Article
Engineering, Chemical
Jianlin Zhao, Feifei Qin, Qinjun Kang, Dominique Derome, Jan Carmeliet
Summary: In this work, a hybrid method coupling a pseudo-potential lattice Boltzmann model (LBM) and a pore network model (PNM) is proposed to simulate drying in porous media. By subdividing the porous medium into pore regions and using different models for different types of pores, the hybrid method combines the accuracy of LBM and the efficiency of PNM, leading to significant reduction of computation time in larger porous systems.
Article
Engineering, Aerospace
Tihao Yang, Yifu Chen, Yayun Shi, Jun Hua, Feifei Qin, Junqiang Bai
Summary: This study is of great importance for developing robust laminar-flow wings and understanding the generation mechanism of statistical response differences between natural laminar-flow wings and hybrid laminar-flow control wings. The study found that operational condition uncertainties have a significant impact on the statistical responses. In addition, disturbances in angle of attack and Mach number significantly affect pressure gradients and suction coefficients, thereby affecting the performance of laminar-flow wings.
Article
Materials Science, Multidisciplinary
Ritian Ji, Hui Wang, Feifei Qin, Chen Ding, Qiangang Fu
Summary: An ablation model considering the reaction kinetics of carbon interphase in carbon/carbon composites is proposed in this paper. This model comprehensively considers various factors that affect the ablation morphology and validates the accuracy of the model through simulation results.
Article
Chemistry, Multidisciplinary
Linlin Fei, Feifei Qin, Jianlin Zhao, Dominique Derome, Jan Carmeliet
Summary: In this work, a numerical model for isothermal liquid-vapor phase change is proposed based on the pseudopotential lattice Boltzmann method. The model is verified and applied to study convective drying of a dual-porosity porous medium at the pore scale, providing new insights into the drying physics and direct modeling at the pore scale.
Article
Environmental Sciences
Jianlin Zhao, Feifei Qin, Qinjun Kang, Chaozhong Qin, Dominique Derome, Jan Carmeliet
Summary: This study successfully simulates the dynamics of corner film flow in strongly wetting porous media using a modified interacting capillary bundle model (ICB) incorporated into a single-pressure dynamic pore network model (DPNM). The interaction between corner film and main meniscus flow in porous media is analyzed from a pore-scale perspective.
WATER RESOURCES RESEARCH
(2022)
Article
Chemistry, Multidisciplinary
Hongfei Xie, Qi Pan, Dongdong Wu, Feifei Qin, Shuoran Chen, Wei Sun, Xu Yang, Sisi Chen, Tingqing Wu, Jimei Chi, Zengqi Huang, Huadong Wang, Zeying Zhang, Bingda Chen, Jan Carmeliet, Meng Su, Yanlin Song
Summary: This study investigates a template-assisted sequential printing strategy to construct visible and near-infrared (Vis-NIR) photodetectors for precise tumor diagnosis and surgical dissection. The lateral heterostructured detectors show better responsiveness to Vis-NIR light and can be used for rapid classification of glioma with high detection accuracy.
Article
Chemistry, Physical
Bingda Chen, Feifei Qin, Meng Su, Daixi Xie, Zeying Zhang, Qi Pan, Huadong Wang, Xu Yang, Sisi Chen, Jingwei Huang, Dominique Derome, Jan Carmeliet, Yanlin Song
Summary: By tuning the Peclet number, the reaction kinetics of nanoparticles can be controlled. A self-driven multi-dimension microchannels reactor (MMR) was proposed for the one droplet synthesis of multi-sized nanoparticles. The MMR enables precise control of nanoparticle diameter and offers a new approach for the production and engineering of nanostructured materials.
Article
Thermodynamics
Chuangde Zhang, Li Chen, Feifei Qin, Luguo Liu, Wen-Tao Ji, Wen-Quan Tao
Summary: Understanding flow boiling in a serpentine microchannel with U-bends is crucial for its practical design and application. In this study, a hybrid thermal multiphase model was used to investigate the heat transfer during flow boiling. The effects of curvature ratio, flow orientation, heat flux, and Reynolds number on bubble dynamics and heat transfer performance were comprehensively evaluated. The results showed that increasing curvature ratio led to elongated bubbles at the U-bend, and flow orientation had a significant impact on bubble dynamics and heat transfer characteristics.
APPLIED THERMAL ENGINEERING
(2023)
Article
Thermodynamics
Chuangde Zhang, Li Chen, Zi Wang, Feifei Qin, Yi Yuan, Luguo Liu, Wen-Quan Tao
Summary: In this study, the corrosion process and morphology under reactive transport conditions are investigated using the corrosion lattice Boltzmann (LB) model. The flow boiling heat transfer in corroded microchannels is then studied using the hybrid thermal multiphase LB model and compared with intact microchannels. The effects of corrosion morphology, pit height, and staggered distance between pits on heat transfer characteristics are explored.
APPLIED THERMAL ENGINEERING
(2023)
Article
Chemistry, Multidisciplinary
Bingda Chen, Zelong Zhang, Meng Su, Feifei Qin, Qi Pan, Daixi Xie, Xu Yang, Kun Zhang, Zeying Zhang, Hongfei Xie, Jan Carmeliet, Yanlin Song
Summary: The traditional synthesis strategy for nanomaterials is complicated and costly, restricting their applications. In this study, we propose a simple process for the simultaneous synthesis and patterning of silver nanoparticles (Ag NPs) using a self-driven microchannel reactor inspired by transpiration. The evaporation process creates capillary and accumulation effects in the microchannels. Through the capillary effect, silver reactant droplets can be spontaneously divided and distributed in multiple microchannels throughout the fabrication process. The newly formed Ag NPs assemble on both sides of the microchannels through the accumulation effect. By combining microchannels of different widths, various Ag NPs-assembled patterns with stable electrical properties can be achieved. This efficient strategy with a simple fabrication procedure contributes to the technological engineering of nanoscale architected materials.
CHEMICAL RESEARCH IN CHINESE UNIVERSITIES
(2023)
Article
Mechanics
Linlin Fei, Feifei Qin, Jianlin Zhao, Dominique Derome, Jan Carmeliet
Summary: A mesoscopic lattice Boltzmann model is used to simulate isothermal two-component evaporation in porous media. The model incorporates a pseudopotential multiphase model with two components, and employs a cascaded collision operator for improved numerical performance. The model is validated through theoretical analysis and microfluidic experiments. The effects of inflow vapour concentration and contact angle on the evaporation process are investigated, and a scaling formulation for the evaporation rate is proposed.
JOURNAL OF FLUID MECHANICS
(2023)
Article
Engineering, Civil
Jianlin Zhao, Feifei Qin, Linlin Fei, Chaozhong Qin, Qinjun Kang, Dominique Derome, Jan Carmeliet
Summary: In this study, an advanced modified interacting capillary bundle model (MICBM) is developed to simulate imbibition dynamics in a strongly wetting square tube. The wetting corner film development is found to be less significant compared to the main meniscus flow under different conditions. Parameters such as viscosity ratio between wetting and non-wetting fluids, driving force, gravity, and contact angle are shown to influence the development of the corner film.
JOURNAL OF HYDROLOGY
(2022)
Article
Mechanics
Feifei Qin, Linlin Fei, Jianlin Zhao, Qinjun Kang, Dominique Derome, Jan Carmeliet
Summary: A 2-D double-distribution lattice Boltzmann method (LBM) is implemented to study the isothermal drying process of a colloidal suspension considering the local effects of nanoparticles. The model is validated by comparing with experimental results for drying of suspended colloidal droplet and a colloidal suspension in a capillary tube. The influence of three local nanoparticle effects on drying dynamics, deposition process and final configurations is analyzed, and a unified relation is proposed and verified.
JOURNAL OF FLUID MECHANICS
(2023)
Article
Biochemical Research Methods
Jimei Chi, Yuanbin Wu, Feifei Qin, Meng Su, Nan Cheng, Jiabing Zhang, Chunbao Li, Zewei Lian, Xu Yang, Lijun Cheng, Hongfei Xie, Huadong Wang, Zeying Zhang, Jan Carmeliet, Yanlin Song
Summary: Designing and preparing a fast and easy-to-use immunosensing biochip are crucial for clinical diagnosis and biomedical research. In this study, an all-printed immunosensing biochip with hydrodynamic enrichment and photonic crystal-enhanced fluorescence is demonstrated. Quantitative detection of cardiac biomarkers is achieved in just 10 minutes using one drop of blood. This approach provides a general and user-friendly method for fast quantitative detection of biomarkers, which can be further improved for portable clinical diagnostics and home medical monitoring.
Article
Physics, Fluids & Plasmas
Linlin Fei, Feifei Qin, Geng Wang, Kai H. Luo, Dominique Derome, Jan Carmeliet
Summary: In this work, a revised theoretical analysis of single droplet evaporation is presented for finite-size open systems, taking into consideration 2D and 3D cases. The classical D2-Law is found to be applicable only for 3D large systems, while deviations occur for small and/or 2D systems. Theoretical solutions for the temperature field are derived, and numerical simulations using the lattice Boltzmann method are performed, achieving remarkable agreement with the theoretical solution.
