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Data-driven modeling of hydrodynamic loading using NARX and harmonic probing
(Peer reviewed; Journal article, 2023)Optimizing floating wind turbines and their mooring systems requires validated computational models that predict wave-frequency and low-frequency hydrodynamic loads. Low-frequency loads are crucial for determining extreme ... -
Data-driven Modeling of Ship Motion Prediction Based on Support Vector Regression
(Journal article; Peer reviewed, 2017)This paper presents a flexible system structure to analyze and model for the potential use of huge ship sensor data to generate efficient ship motion prediction model. The noisy raw data is cleaned using noise reduction, ... -
Data-driven modelling of a R744 refrigeration system with parallel compression configuration
(Chapter, 2019)The type and characteristics of the employed components, subsystems and refrigerant in a commercial refrigeration system varies significantly depending on required functionalities (e.g. MT (medium temperature), LT (low ... -
Data-driven models of pelvic floor muscles dynamics subject to psychological and physiological stimuli
(Journal article; Peer reviewed, 2019)This paper proposes individualized, dynamical and data-driven models to describe pelvic floor muscle responses in women undergoing vaginal dilation. Specifically, the models describe how the aggregated pressure exerted by ... -
Data-Driven Personalized Cervical Cancer Risk Prediction: A Graph-Perspective
(Chapter, 2021)Routine cervical cancer screening at regular periodic intervals leads to either over-screening or too infrequent screening of patients. For this purpose, personalized screening intervals are desirable that account for ... -
Data-driven prediction of mean wind turbulence from topographic data
(Peer reviewed; Journal article, 2021)This study presents a data-driven model to predict mean turbulence intensities at desired generic locations, for all wind directions. The model, a multilayer perceptron, requires only information about the local topography ... -
Data-Driven Prediction of Ship Propulsion Power Using Spark Parallel Random Forest on Comprehensive Ship Operation Data
(Chapter, 2022)This paper aims to propose an efficient machine learning framework for maritime big data and use it to train a random forest model to estimate ships’ propulsion power based on ship operation data. The comprehensive data ... -
Data-Driven Prediction of Vortex-Induced Vibration Response of Marine Risers Subjected to Three-Dimensional Current
(Chapter, 2019)Slender marine structures such as deep-water marine risers are subjected to currents and will normally experience Vortex Induced Vibrations (VIV), which can cause fast accumulation of fatigue damage. The ocean current is ... -
Data-Driven Real-Time Price-Based Demand Response for Industrial Facilities Energy Management
(Journal article; Peer reviewed, 2021)Recent advances in smart grid technologies have highlighted demand response (DR) as an important tool to alleviate electricity demand–supply mismatches. In this paper, a real-time price (RTP)-based DR algorithm is proposed ... -
Data-driven recovery of hidden hysics in reduced order modeling of fluid flows
(Peer reviewed; Journal article, 2020)In this article, we introduce a modular hybrid analysis and modeling (HAM) approach to account for hidden physics in reduced order modeling (ROM) of parameterized systems relevant to fluid dynamics. The hybrid ROM framework ... -
Data-driven recovery of hidden physics in reduced order modeling of fluid flows
(Peer reviewed; Journal article, 2020)In this article, we introduce a modular hybrid analysis and modeling (HAM) approach to account for hidden physics in reduced order modeling (ROM) of parameterized systems relevant to fluid dynamics. The hybrid ROM framework ... -
Data-driven reduced order modelling using clusters of thermal dynamics
(Peer reviewed; Journal article, 2023) -
Data-Driven Robust Optimal Operation of Thermal Energy Storage in Industrial Clusters
(Peer reviewed; Journal article, 2020)Industrial waste heat recovery is an attractive option having the simultaneous benefits of reducing energy costs as well as carbon emissions. In this context, thermal energy storage can be used along with an optimal operation ... -
Data-driven Scenario Selection for Multistage Robust Model Predictive Control
(Journal article; Peer reviewed, 2018)A main assumption in many works considering multistage model predictive control (MPC) is that discrete realizations of the uncertainty are chosen a-priori and that the scenario tree is given. In this work, we focus on ... -
Data-driven sea state estimation for vessels using multi-domain features from motion responses
(Chapter, 2021)Situation awareness is of great importance for autonomous ships. One key aspect is to estimate the sea state in a real-time manner. Considering the ship as a large wave buoy, the sea state can be estimated from motion ... -
Data-Driven Ship Design
(Chapter, 2018)This paper proposes data-driven methods thinkingto the ship design practices, enabling effective data collection, quality, access, analysis and monitoring during the vessel lifecycle.Data is here understood as the key ... -
Data-driven simultaneous identification of the 6DOF dynamic model and wave load for a ship in waves
(Peer reviewed; Journal article, 2023)In marine operations, the performance of model-based automatic control design and decision support systems highly relies on the accuracy of the representative mathematical models. Model fidelity can be crucial for safe ... -
Data-driven smart eco-cities and sustainable integrated districts: A best-evidence synthesis approach to an extensive literature review
(Journal article; Peer reviewed, 2021) -
Data-Driven Smart Sustainable Cities of the Future: A Novel Model of Urbanism and Its Core Dimensions, Strategies, and Solutions
(Journal article; Peer reviewed, 2021)The big data revolution is heralding an era where instrumentation, datafication, and computation are increasingly pervading the very fabric of cities. Big data technologies are seen as a powerful force that has great ... -
Data-Driven Smart Sustainable Cities of the Future: An Evidence Synthesis Approach to a Comprehensive State-of-the-Art Literature Review
(Peer reviewed; Journal article, 2021)Sustainable cities are currently undergoing unprecedented transformative changes in light of the recent paradigm shift in science and technology brought on by big data science and analytics. These marked changes are motivated ...