Article
Neuroimaging
Mingzi Zhang, Xiaoxi Hou, Yi Qian, Winston Chong, Xin Zhang, Chuan-Zhi Duan, Chubin Ou
Summary: This study investigates the use of flowrate-independent parameters in predicting the stability of aneurysms and compares their performance against conventional parameters. The results show that the flowrate-independent hemodynamic parameters outperform the conventional parameters in predicting aneurysm stability, and can be potentially used when real vascular boundary conditions are unavailable for assessing the risk of aneurysm rupture.
JOURNAL OF NEUROINTERVENTIONAL SURGERY
(2023)
Article
Computer Science, Artificial Intelligence
Wenjie Jia, Wei Wang, Zhenzu Zhang
Summary: In this paper, a digital twin shop floor is constructed based on the modeling method of complex digital twin. The shop floor covers multi-dimensional information and multi-scale application scenarios, and is divided into simple digital twins focusing on different scales. The implementation of the complex digital twin shop floor demonstrates the feasibility of the proposed modeling method.
ADVANCED ENGINEERING INFORMATICS
(2023)
Article
Mechanics
Aadil Kureshee, S. Narayanan, Deepak Kumar Mandal
Summary: This study investigates the impact of an acoustic field on evaporation and internal circulation of twin drops with varying horizontal spacing. The results show that the maximum evaporation rate and circulation occur at the lowest frequency and highest spacing. The evaporation rate increases with spacing up to a critical distance, beyond which it becomes nearly identical. The spacing, evaporation rate, and outer flow velocity are found to be correlated. The perception that any acoustic wave enhances evaporation is proven incorrect, as the evaporation and circulation decline with increasing frequency.
Article
Chemistry, Analytical
Nikolaj T. Mucke, Prerna Pandey, Shashi Jain, Sander M. Bohte, Cornelis W. Oosterlee
Summary: In this study, a methodology based on generative deep learning and Bayesian inference was proposed for localizing leaks in large water distribution systems and quantifying the uncertainty. By embedding a surrogate model into a Bayesian inference scheme, leaks were located by combining sensor observations with a model output approximating the true posterior distribution. The results showed that this methodology produced fast, accurate, and trustworthy results, with accuracies upwards of 83% achieved for different test cases.
Article
Radiology, Nuclear Medicine & Medical Imaging
Dejan Jakimovski, Niels Bergsland, Michael G. Dwyer, Kunsang Choedun, Karen Marr, Bianca Weinstock-Guttman, Robert Zivadinov
Summary: This study aimed to investigate the relationship between systemic arterial blood flow (SABF) and cerebral perfusion in patients with multiple sclerosis (MS). The results showed that higher SABF was associated with shorter mean transit time (MTT) and time-to-peak (TTP) in the whole brain and gray matter, primarily in progressive MS patients. SABF remained a significant predictor of normal-appearing whole brain (NAWB) and gray matter (GM) TTP in progressive MS patients. Patients with lower SABF had significantly lower MTT and TTP.
EUROPEAN RADIOLOGY
(2022)
Article
Neuroimaging
Ryan Phillip Sabotin, Alberto Varon, Jorge A. Roa, Ashrita Raghuram, Daizo Ishii, Marco Nino, Adam E. Galloy, Devanshee Patel, Madhavan L. Raghavan, David Hasan, Edgar A. Samaniego
Summary: This study utilized advanced imaging techniques and computational analysis to investigate the unique characteristics and potential mechanisms of instability in cerebral fusiform aneurysms. The results showed that enhancing fusiform aneurysms had larger volume and diameter, more enhancement of reference vessels, and were more likely to exhibit microhemorrhages compared to non-enhancing aneurysms. Computational fluid dynamics and finite element analysis provided insights into the various pathophysiological processes underlying the formation and growth of different types of fusiform aneurysms.
JOURNAL OF NEUROINTERVENTIONAL SURGERY
(2021)
Article
Energy & Fuels
Bai Hao, Wang Yuli
Summary: This paper introduces the concept and characteristics of a digital power grid based on digital twin, and presents the architecture and key technologies of the digital power grid.
Article
Rheumatology
Antonietta Gigante, Annalisa Villa, Edoardo Rosato
Summary: This study evaluated peripheral blood perfusion in the hands of SSc patients using laser speckle contrast analysis and found that PDG can predict major vascular complications and 5-year mortality in SSc patients.
Article
Chemistry, Analytical
Xue Han, Zihuai Lin, Cameron Clark, Branka Vucetic, Sabrina Lomax
Summary: This paper develops an innovative digital twin model powered by artificial intelligence that can remotely monitor and predict the status of cattle, enabling the forecasting of the cattle's future time budget.
Article
Computer Science, Interdisciplinary Applications
Zequn Zhang, Yuchen Ji, Dunbing Tang, Jie Chen, Changchun Liu
Summary: This paper proposes a digital twin system for human-robot collaboration (HRC) that overcomes the limitations of current methods and improves the overall performance. The system includes a human mesh recovery algorithm and uncertainty estimation to enhance the system's capabilities. Experimental results demonstrate the superiority of the proposed methods over baseline methods. The feasibility and effectiveness of the HRC system are validated through a case study involving component assembly.
ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING
(2024)
Review
Construction & Building Technology
De-Graft Joe Opoku, Srinath Perera, Robert Osei-Kyei, Maria Rashidi
Summary: Digital twin (DT) technology, with its potential to transform the construction industry and address its challenges, has attracted significant attention and is rapidly developing. This study comprehensively reviewed and analyzed the current state of DT applications in the construction industry, providing a theoretical basis for the widespread adoption of this technology in the industry.
JOURNAL OF BUILDING ENGINEERING
(2021)
Article
Clinical Neurology
Victoria Hellstern, Marta Aguilar-Perez, Elina Henkes, Carmen Serna-Candel, Christina Wendl, Hansjoerg Baezner, Oliver Ganslandt, Hans Henkes
Summary: The study evaluated the safety and effectiveness of p64 FD for treating saccular, unruptured aneurysms in the posterior circulation. The results showed that p64 FD implantation is a safe and effective device with a high success rate and low complication rate.
FRONTIERS IN NEUROLOGY
(2021)
Article
Computer Science, Information Systems
Deuk-Young Jeong, Myung-Sun Baek, Tae-Beom Lim, Yong-Woon Kim, Se-Han Kim, Yong-Tae Lee, Woo-Sug Jung, In-Bok Lee
Summary: Digital twin is a technology that replicates physical objects in the real world into digital objects in the digital world, utilizing simulations to solve problems or improve operations. Due to its complexity, creating a digital twin model requires step-by-step implementation involving various technology elements. This study introduces implementation layers and suggests technology elements to guide practical applications of digital twin. Additionally, the paper describes the evolution of digital twins and presents future directions of digital twin technology.
Article
Construction & Building Technology
Gozde Basak Ozturk
Summary: This study aims to explore the current patterns, gaps, and trends in Digital Twin research in the AECO-FM industry and propose future directions. The research covers a wide range of topics including model-based information management, building information management, and the interaction between buildings and smart cities. The study highlights the importance of addressing information-based predictive management and virtual-based information utilization for holistic Digital Twin adoption in the industry.
JOURNAL OF BUILDING ENGINEERING
(2021)
Article
Engineering, Electrical & Electronic
Yongchao Zhang, Jia Hu, Geyong Min
Summary: The paper proposes a digital twin-driven intelligent task offloading framework for collaborative mobile edge computing (MEC). By mapping the MEC system into a virtual space using digital twin and optimizing task offloading decisions with deep reinforcement learning, the proposed framework effectively adapts to dynamic environments and significantly improves the MEC system's income.
IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS
(2023)
Article
Thermodynamics
Tisha Dixit, Perumal Nithiarasu, S. Kumar
Summary: Utilizing additive manufacturing techniques, adjusting architectural characteristics of lattice materials has led to the development of various lattice heat sink fins to meet high heat dissipation requirements and structural needs. The study reveals that polymer-based architected heat sinks perform closely to metallic counterparts on a per unit mass basis, and some lattice structures exhibit better thermal performance than microchannel and open-cell foam heat sinks.
INTERNATIONAL JOURNAL OF THERMAL SCIENCES
(2021)
Article
Thermodynamics
HamidReza Tamaddon Jahromi, Samuel Rolland, Jason Jones, Alberto Coccarelli, Igor Sazonov, Chris Kershaw, Chedly Tizaoui, Peter Holliman, David Worsley, Hywel Thomas, Perumal Nithiarasu
Summary: A novel modelling approach is proposed to study ozone distribution and destruction in indoor spaces. The methodology was validated against experimental measurements and showed good agreement in predicting the time evolution of ozone concentration at different locations within the enclosed space. The study introduces a computational methodology for predicting ozone concentration levels during a disinfection process, with a parametric study evaluating the impact of system settings on ozone concentration variation over time.
INTERNATIONAL JOURNAL OF NUMERICAL METHODS FOR HEAT & FLUID FLOW
(2022)
Review
Engineering, Biomedical
Chengyuan Wang, Si Li, Adesola S. Ademiloye, Perumal Nithiarasu
Summary: Computational biomechanical models for cells have made significant progress but still face challenges. This review summarizes cellular components at different spatial levels and offers insights into future directions.
INTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN BIOMEDICAL ENGINEERING
(2021)
Article
Computer Science, Interdisciplinary Applications
Gareth Jones, Jim Parr, Perumal Nithiarasu, Sanjay Pant
Summary: The study assesses the ability of machine learning classifiers to predict arterial stenosis, achieving certain accuracy in distinguishing between healthy and unhealthy virtual patients, and making important observations about classification accuracy.
MEDICAL & BIOLOGICAL ENGINEERING & COMPUTING
(2021)
Article
Virology
Dmitry Grebennikov, Ekaterina Kholodareva, Igor Sazonov, Antonina Karsonova, Andreas Meyerhans, Gennady Bocharov
Summary: This study utilized mathematical and computational modelling to formulate a deterministic model of the SARS-CoV-2 life cycle, identifying the three most influential parameters affecting viral replication and providing data support for guiding the search for antiviral drug targets.
Article
Engineering, Biomedical
Neeraj Kavan Chakshu, Jason M. Carson, Igor Sazonov, Perumal Nithiarasu
Summary: FFR provides the functional relevance of coronary atheroma and has shown to reduce unnecessary stenting and improve health outcomes. Non-invasive cFFR is an emerging method that reduces invasive catheter measurements, but requires expertise and labor.
INTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN BIOMEDICAL ENGINEERING
(2022)
Article
Thermodynamics
Hamid Reza Tamaddon Jahromi, Igor Sazonov, Jason Jones, Alberto Coccarelli, Samuel Rolland, Neeraj Kavan Chakshu, Hywel Thomas, Perumal Nithiarasu
Summary: This paper presents a tool based on computational fluid dynamics (CFD) and machine learning (ML) to assess potential airborne microbial transmission in enclosed spaces. By using a gated recurrent units neural network (GRU-NN), the behavior of droplets expelled through breaths can be accurately predicted. The study demonstrates the accuracy of the developed ML model in predicting airborne particle movement in different ventilation conditions and source locations. This research contributes to the development of efficient tools for predicting virus airborne movement in indoor environments.
INTERNATIONAL JOURNAL OF NUMERICAL METHODS FOR HEAT & FLUID FLOW
(2022)
Article
Virology
Igor Sazonov, Dmitry Grebennikov, Andreas Meyerhans, Gennady Bocharov
Summary: Mathematical modelling is important for understanding the infection process of SARS-CoV-2 in cells. This study transforms a deterministic model into a stochastic one and uses it to compute statistical characteristics of the virus's life cycle. The results show the strong inhibitory effects of type I IFN response on viral progeny.
Article
Virology
Igor Sazonov, Dmitry Grebennikov, Rostislav Savinkov, Arina Soboleva, Kirill Pavlishin, Andreas Meyerhans, Gennady Bocharov
Summary: A mathematical model of HIV-1 life cycle in CD4 T cells was developed, which accounts for the activation of IFN-I response and its suppression of viral replication. The model includes inhibition of viral replication by IFN-induced antiviral factors and their inactivation by viral proteins Vpu and Vif. Both deterministic and stochastic models were constructed to predict the efficiency of IFN-I-induced suppression in different initial conditions, and the heterogeneity of HIV-1 and IFN-I production was characterized statistically.
Proceedings Paper
Engineering, Multidisciplinary
Sam Rolland, Hamid Tamaddon Jahromi, Jason Jones, Alberto Coccarelli, Igor Sazonov, Chris Kershaw, Chedly Tizaoui, Peter Holliman, David Worsley, Hywel Thomas, Perumal Nithiarasu
Summary: A modelling approach is proposed to study the distribution and destruction of ozone in indoor spaces. The study validates a computational fluid dynamics (CFD) model for ozone concentration and demonstrates the suitability of ozone circulation as a disinfection process. The research highlights the importance of a well-controlled ozone removal process.
PROGRESS IN INDUSTRIAL MATHEMATICS AT ECMI
(2022)