Article
Chemistry, Physical
Matthieu Dubarry, David Howey, Billy Wu
Summary: Digital twins are cyber-physical systems that integrate real-time sensor data and models for accurate predictions and optimal decisions in specific assets. In the case of batteries, this concept has been applied at different scales. However, a comprehensive approach is needed for battery digital twins to achieve their full potential in industrial settings. Standardized and transparent data sharing, as well as principled methods to quantify and propagate uncertainty, are essential. Physical modeling and sensing approaches for battery manufacturing and thermal runaway also need improvement.
Article
Mathematics
Nathalie Verdiere, Oscar Navarro, Aude Naud, Alexandre Berred, Damienne Provitolo
Summary: This study investigates the calibration of a mathematical model describing behaviors during catastrophes, developed in collaboration with geographers and psychologists. Through virtual reality experiments and measuring electrocardiograms, stress levels were collected to calibrate the behavioral model. The estimation procedure and theoretical analysis revealed the system's capability to understand non-observable human processes.
Review
Agriculture, Dairy & Animal Science
Rafael Munoz-Tamayo, Luis O. Tedeschi
Summary: Constructing dynamic mathematical models of biological systems involves parameter estimation using statistical fitting procedures and structural identifiability analysis. Structural identifiability analysis helps determine actions needed to improve the identifiability of model parameters. Dedicated software tools make this analysis accessible to non-expert users. This paper encourages the integration of identifiability analysis into animal science modeling practices.
JOURNAL OF ANIMAL SCIENCE
(2023)
Article
Multidisciplinary Sciences
Dominique Joubert, J. D. Stigter, Jaap Molenaar
Summary: Structural identifiability is crucial in model development, and problematic initial values may lead to unidentifiability, which can be resolved by changing these values.
SCIENTIFIC REPORTS
(2021)
Article
Environmental Sciences
Befekadu Taddesse Woldegiorgis, Helen Baulch, Howard Wheater, Jill Crossman, Martyn Clark, Tricia Stadnyk, Ajay Bajracharya
Summary: Proper numerical representation is crucial in mechanistic hydrological models for robust predictions. The commonly used sequential calculation method for multiple fluxes in hydrological models can lead to errors. This study compares two versions of the HYPE model and finds that the original model and the sequential calculation method have limitations in simulating interflow, while a modified version with implicit Euler method provides more accurate results.
WATER RESOURCES RESEARCH
(2023)
Article
Multidisciplinary Sciences
Yunliang Zang, Eve Marder
Summary: Biological neurons exhibit cell-to-cell variability, but still maintain key firing properties in the presence of unpredictable perturbations and stochastic noise. Through a study on the lateral pyloric neuron in the crab stomatogastric ganglion, which involves varied conductances in multi-compartment models, it is found that coupling between the axon and other compartments is crucial for the preservation of rebound bursting. Deviations from biologically realistic coupling range decrease the neuronal tolerance to conductance variations. Therefore, the morphological features of these neurons contribute to their robustness and expand the variability of maintaining desired output patterns.
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
(2023)
Article
Multidisciplinary Sciences
Sahil Bhola, Karthik Duraisamy
Summary: This paper proposes a novel information-theoretic approach to assess the practical identifiability of Bayesian statistical models globally. The method does not rely on any assumptions about the model structure or prior distribution, and can take into account different forms of uncertainties. By analyzing the dependencies between parameters, a subset of parameters that can be estimated with high certainty is found.
SCIENTIFIC REPORTS
(2023)
Article
Biochemical Research Methods
Xabier Rey Barreiro, Alejandro F. Villaverde
Summary: In this study, we conducted a comprehensive investigation on the available computational resources for analyzing structural identifiability. We evaluated the performance of 13 different software tools developed in 7 programming languages. Our results provide insights into the strengths and weaknesses of these tools, and offer guidance for selecting the most appropriate tool for specific problems. We also identify opportunities for future developments in this field.
Article
Automation & Control Systems
Krishnan Srinivasarengan, Jose Ragot, Christophe Aubrun, Didier Maquin
Summary: LPV models serve as a bridge between linear and nonlinear models, allowing for analysis of nonlinear models and introduction of varying model parameters. The identifiability of model parameters is a key issue, and this paper proposes an approach to verify the identifiability of unknown parameters.
INTERNATIONAL JOURNAL OF APPLIED MATHEMATICS AND COMPUTER SCIENCE
(2022)
Article
Construction & Building Technology
Dong Hyuk Yi, Cheol Soo Park
Summary: The study proposes using model evidence as an objective index for selecting the optimal hypothesis of unidentifiable parameters in Bayesian inference of building energy models. It shows that higher model evidence leads to posterior values closer to true values; however, there is no significant relationship between model prediction error and the accuracy of posterior inference.
ENERGY AND BUILDINGS
(2021)
Article
Mathematics
Seth Gerberding, Nida Obatake, Anne Shiu
Summary: In this study, we investigate whether local and generic identifiability is preserved in linear compartmental models when parts of the model, such as inputs, outputs, leaks, and edges, are moved, added, or deleted. Our findings show that for certain catenary, cycle, and mammillary models, moving or deleting the leak preserves identifiability. Additionally, for cycle models with up to one leak, moving inputs or outputs also preserves identifiability.
LINEAR & MULTILINEAR ALGEBRA
(2022)
Article
Biochemical Research Methods
Kate E. Dray, Joseph J. Muldoon, Niall M. Mangan, Neda Bagheri, Joshua N. Leonard
Summary: Mathematical modeling is crucial for understanding and designing synthetic biological systems. However, the model development process is complex and nonintuitive, requiring iteration and comparison with experimental data. To address these challenges, we introduce the GAMES workflow, which combines automated and human-in-the-loop processes. This workflow enables biologists to more easily build and analyze models for various applications.
ACS SYNTHETIC BIOLOGY
(2022)
Article
Multidisciplinary Sciences
Marilisa Cortesi, Dongli Liu, Christine Yee, Deborah J. Marsh, Caroline E. Ford
Summary: Computational models are increasingly important in biomedical research, but their accuracy and effectiveness rely on suitable parameter identification and validation. This study calibrated an in-silico model of ovarian cancer using datasets from different experimental models, and compared the parameters and simulated behaviors. It provides a framework for studying the effect of experimental models on computational systems and offers guidelines for comparative testing and selection of experimental models and protocols for parameter optimization.
SCIENTIFIC REPORTS
(2023)
Review
Chemistry, Physical
Malin Andersson, Moritz Streb, Jing Ying Ko, Verena Lofqvist Klass, Matilda Klett, Henrik Ekstrom, Mikael Johansson, Goran Lindbergh
Summary: Physics-based battery models play a crucial role in battery research, development, and control. Accurate parametrization is essential for obtaining useful information from the models. Parametrization of physics-based battery models from input-output data is a growing research area. Successful parametrization requires knowledge of the underlying physical system and understanding of parameter estimation theory. This paper reviews the key aspects of parametrization in this field.
JOURNAL OF POWER SOURCES
(2022)
Article
Management
Michael Lingzhi Li, Hamza Tazi Bouardi, Omar Skali Lami, Thomas A. Trikalinos, Nikolaos Trichakis, Dimitris Bertsimas
Summary: This article introduces DELPHI, a novel epidemiological model for predicting COVID-19 cases and deaths. The model has been applied to over 200 geographical areas and has shown high accuracy in predictions. The article also demonstrates two applications of DELPHI, including assessing the impact of government interventions and predicting future incidence under different policies.
OPERATIONS RESEARCH
(2023)
Article
Mathematics, Applied
Puntani Pongsumpun, I-Ming Tang, Napasool Wongvanich
ADVANCES IN DIFFERENCE EQUATIONS
(2019)
Article
Mathematics, Applied
Napasool Wongvanich, Sungwan Boksuwan, Abdulhafiz Chesof
ADVANCES IN DIFFERENCE EQUATIONS
(2020)
Article
Mathematics
Anusit Chamnan, Puntani Pongsumpun, I-Ming Tang, Napasool Wongvanich
Summary: Dengue disease, caused by four serotypes of the dengue virus, is targeted by the CYD-TDV vaccine currently used in Thailand. This research focuses on determining optimal control measures when only individuals with a history of past dengue infection are vaccinated.
Article
Multidisciplinary Sciences
Anusit Chamnan, Puntani Pongsumpun, I-Ming Tang, Napasool Wongvanich
Summary: This research explores optimal control strategies for dengue fever vaccination only in individuals with prior dengue infections (seropositive), resulting in a significant reduction in the number of infected humans and vectors. The analysis of dengue transmission model establishes local asymptotic stabilities and highlights the importance of symmetry in achieving global asymptotic stabilities through Lyapunov function.
Article
Mathematics
Napasool Wongvanich, I-Ming Tang, Marc-Antoine Dubois, Puntani Pongsumpun
Summary: This study formulated a dynamic model of hand, foot and mouth disease (HFMD) using the SEIQR model, identifying higher and lower outbreak periods associated with regional residency. Two optimal control programs were developed, with one focusing on treatment and the other on vaccination in addition to treatment. Numerical solutions and sensitivity analyses revealed a logarithmic relationship between optimal control effort and control parameters.
Article
Multidisciplinary Sciences
Napasool Wongvanich
Summary: This paper presents mathematical modeling and stability analyses based on the SEIR model with a nonlinear incidence rate to describe the COVID-19 pandemic, considering media interactions and control strategies. The sliding mode control methodology is used to design a robust closed loop control system for the epidemiological model, and numerical simulations are conducted to evaluate the control algorithms.
Article
Mathematics
Anusit Chamnan, Puntani Pongsumpun, I-Ming Tang, Napasool Wongvanich
Summary: This paper investigates the effect of vaccination on the dengue fever epidemic using a mathematical model. The results show that vaccination can significantly reduce the severity of the disease, and the optimal age for vaccination is determined.
Article
Mathematics
Jiraporn Lamwong, Puntani Pongsumpun, I-Ming Tang, Napasool Wongvanich
Summary: This study proposes a standard dynamic model for COVID-19, comparing a simple model and an optimal control model to reduce the number of infected people and serve as a guideline for outbreak control. Equilibrium point, basic reproduction number, and stability conditions are analyzed using Lyapunov functions, and optimal control conditions are determined using Pontryagin's maximum principle. Sensitivity analysis of parameters reveals the impact of vaccine efficacy and infection rate on outbreak incidence. Numerical analysis of the Omicron variant outbreak data demonstrates the potential of optimal control strategies for managing and controlling the COVID-19 outbreak.
Article
Energy & Fuels
Varin Cholahan, Napasool Wongvanich, Worapong Tangsrirat
Summary: This paper presents a Robust Constant Exponent Coefficient Fixed-Time Control (CECFSMC) technique for precisely regulating the speed of a permanent magnet synchronous motor (PMSM) using fixed-time stability and constant exponent coefficients. It reduces chattering and offers faster convergence within a specific time period. A finite-time extended sliding-mode observer (ESMO) is designed to estimate the velocity of the PMSM and lumped load disturbances, ensuring desired performance under bounded disturbances. Numerical simulation results demonstrate good robustness against load disturbances, better convergence, and reaching time of less than 2 seconds, highlighting the superior performance and simplicity of the proposed fixed-time constant exponent coefficient compared to conventional finite-time methods.
Article
Computer Science, Information Systems
Napasool Wongvanich, Natchanai Roongmuanpha, Worapong Tangsrirat
Summary: This paper investigates the use of the sigr function in the implementation of finite-time terminal sliding mode control in closed-loop circuit realizations of chaotic synchronization and control. A CFOA-based implementation of the sigr function is proposed, and an Extended Exploration Grey Wolf Optimization method is used to approximate the non-integer powered transfer function inside the sigr function. Two closed-loop circuit realizations of second- and third-order systems demonstrate the effectiveness of the developed sigr function in achieving finite-time terminal sliding mode control.
Article
Computer Science, Information Systems
Napasool Wongvanich, Natchanai Roongmuanpha, Worapong Tangsrirat
Summary: This work presents a method for finite-time synchronization of a new six-term chaotic system with only stable equilibria and its circuitry implementation. The chaotic system allows adjustment of its complex dynamical behavior and transformation to chaotic flows through a single parameter. A finite-time chaotic synchronizer is designed using a nonsingular terminal integral backstepping sliding mode controller, with reduced theoretical finite-time convergence and a modified sliding surface for analog circuitry implementations. Comparison with conventional integral backstepping sliding mode controller showed successful active synchronization in finite time. Analog circuitry implementation for both open-loop and closed-loop configurations is achieved using commercially available active components. The master and slave systems were found to be in synchronization with less than 0.95% maximum errors.
Proceedings Paper
Automation & Control Systems
Sungwan Boksuwan, Abdulhafiz Chesof, Napasool Wongvanich, Sumit Panaudomsap
CONFERENCE PROCEEDINGS OF 2019 5TH INTERNATIONAL CONFERENCE ON CONTROL, AUTOMATION AND ROBOTICS (ICCAR)
(2019)
Proceedings Paper
Automation & Control Systems
Panuwat Ahpichitpongchai, Kamonchanok Kamonwattana, Wiriya Intarit, Napasool Wongvanich, Viriya Kongratana
2019 19TH INTERNATIONAL CONFERENCE ON CONTROL, AUTOMATION AND SYSTEMS (ICCAS 2019)
(2019)
Proceedings Paper
Automation & Control Systems
Napasool Wongvanich, Puntani Pongsumpun
2018 15TH INTERNATIONAL CONFERENCE ON CONTROL, AUTOMATION, ROBOTICS AND VISION (ICARCV)
(2018)
Proceedings Paper
Automation & Control Systems
Napasool Wongvanich, Pongsakorn Somkane, Viriya Kongratana
2018 18TH INTERNATIONAL CONFERENCE ON CONTROL, AUTOMATION AND SYSTEMS (ICCAS)
(2018)
