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RESEARCH PAPER · ACM Computing Surveys · 2022

Integrating Scientific Knowledge with Machine Learning for Engineering and Environmental Systems

Jared Willard, Xiaowei Jia, Shaoming Xu, Michael S. Steinbach, Vipin Kumar

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42 direct citing works

Integrating Scientific Knowledge with Machine Learning for Engineering and Environmental SystemsOriginalSpace-Decomposition-Based Spectral Modeling for Distributed Battery Thermal Dynamics28Making Invisible Visible: Data-Driven Seismic Inversion With Spatio-Temporally Constrained Data Augmentation19Pyramid LSTM Network for Tool Condition Monitoring39On Strictly Enforced Mass Conservation Constraints for Modeling the Rainfall-Runoff Process43Physics-Constrained Deep Learning for Robust Inverse ECG Modeling28Applications of Physics-Informed Neural Networks in Power Systems - A Review619Can machine learning accelerate process understanding and decision‐relevant predictions of river water quality?79Combustion machine learning: Principles, progress and prospects265Predicting waves in fluids with deep neural network36Review of Machine Learning for Hydrodynamics, Transport, and Reactions in Multiphase Flows and Reactors294Applications of deep learning in water quality management: A state-of-the-art review142Assessing the Physical Realism of Deep Learning Hydrologic Model Projections Under Climate Change136Predicting growth and interaction of multiple cracks in structural systems using Dynamic Bayesian Networks18Predicting Rate of Penetration of Horizontal Drilling by Combining Physical Model with Machine Learning Method in the China Jimusar Oil Field38Review of Pedestrian Trajectory Prediction Methods: Comparing Deep Learning and Knowledge-Based Approaches180A framework for machine learning of model error in dynamical systems61Enhancing predictive skills in physically-consistent way: Physics Informed Machine Learning for hydrological processes166In‐season crop phenology using remote sensing and model‐guided machine learning20Information geometry for multiparameter models: new perspectives on the origin of simplicity43Boosting Personalized Musculoskeletal Modeling With Physics-Informed Knowledge Transfer25A Fault Detection Method for a Practical Electro-Hydraulic Variable-Displacement Pump With Unknown Swashplate Moment23A scientific machine learning framework to understand flash graphene synthesis24Digital Twins in Wind Energy: Emerging Technologies and Industry-Informed Future Directions102Physics-Guided Data-Driven Seismic Inversion: Recent progress and future opportunities in full-waveform inversion81Stacking ensemble learning model for predict anxiety level in university students using balancing methods34Modelling of Deep Learning-Based Downscaling for Wave Forecasting in Coastal Area25Mechanism-learning coupling paradigms for parameter inversion and simulation in earth surface systems41Long-term fatigue estimation on offshore wind turbines interface loads through loss function physics-guided learning of neural networks87A review of the application of artificial intelligence to nuclear reactors: Where we are and what's next111A Review of Physics-Informed Machine Learning in Fluid Mechanics248On strictly enforced mass conservation constraints for modelling the Rainfall‐Runoff process60Physics-informed machine learning method for modelling transport of a conservative pollutant in surface water systems53Stream Temperature Prediction in a Shifting Environment: Explaining the Influence of Deep Learning Architecture34Data reconstruction for complex flows using AI: Recent progress, obstacles, and perspectives20Future Research and Developments on Reuse and Recycling of Steelmaking By-Products30Identification of flow regimes in boiling flow with clustering algorithms: An interpretable machine-learning perspective19Physics-Informed Deep Learning for Tool Wear Monitoring89Effects of mass balance, energy balance, and storage-discharge constraints on LSTM for streamflow prediction44Physics-Guided Deep Learning for Improved Production Forecasting in Unconventional Reservoirs17Integrating Multi-Criteria Decision-Making Methods with Sustainable Engineering: A Comprehensive Review of Current Practices60Artificial Intelligence Applications in Electric Distribution Systems: Post-Pandemic Progress and Prospect23A comprehensive review on tungsten oxide nanostructures‐based electrochromic supercapacitors and machine learning models for design and process parameter optimization26A review of machine learning methods applied to structural dynamics and vibroacoustic149A review of the application of hybrid machine learning models to improve rainfall prediction71Generation and evaluation of a synthetic dataset to improve fault detection in district heating and cooling systems34Physics-Guided Neural Network Model for Aeroengine Control System Sensor Fault Diagnosis under Dynamic Conditions33Knowledge-informed deep learning for hydrological model calibration: an application to Coal Creek Watershed in Colorado36Toward impact-based monitoring of drought and its cascading hazards104Applying Knowledge-Guided Machine Learning to Slope Stability Prediction91From data to insight, enhancing structural health monitoring using physics-informed machine learning and advanced data collection methods49Data-Aided Underwater Acoustic Ray Propagation Modeling41New insight into the multivariate relationships among process, structure, and properties in laser powder bed fusion AlSi10Mg26A synergistic future for AI and ecology72Physics-informed Gaussian process for tool wear prediction58Bioinspired materials for underwater adhesion with pathways to switchability23Integrating a tailored recurrent neural network with Bayesian experimental design to optimize microbial community functions52Physics informed neural networks for fault severity identification of axial piston pumps70Recent applications of AI to environmental disciplines: A review172Machine learning for phase-resolved reconstruction of nonlinear ocean wave surface elevations from sparse remote sensing data17A flexible and efficient knowledge-guided machine learning data assimilation (KGML-DA) framework for agroecosystem prediction in the US Midwest53Toward Physics-Informed Machine-Learning-Based Predictive Maintenance for Power Converters—A Review140Can domain knowledge benefit machine learning for concrete property prediction?24Improving the interpretability and predictive power of hydrological models: Applications for daily streamflow in managed and unmanaged catchments29Machine learning with monotonic constraint for geotechnical engineering applications: an example of slope stability prediction56Physics-enhanced deep surrogates for partial differential equations49Perspectives of physics-based machine learning strategies for geoscientific applications governed by partial differential equations42Enforcing Water Balance in Multitask Deep Learning Models for Hydrological Forecasting19Physics-Informed Machine Learning for Data Anomaly Detection, Classification, Localization, and Mitigation: A Review, Challenges, and Path Forward103Physics-Informed Machine Learning for Dry Friction and Backlash Modeling in Structural Control Systems18Port-Hamiltonian Neural ODE Networks on Lie Groups for Robot Dynamics Learning and Control30Knowledge-guided machine learning can improve carbon cycle quantification in agroecosystems189Physics-informed neural networks modelling for systems with moving immersed boundaries: Application to an unsteady flow past a plunging foil23Loss-attentional physics-informed neural networks95Hybrid data-driven and physics-based modeling for viscosity prediction of ionic liquids18NN‐mCRE: A modified constitutive relation error framework for unsupervised learning of nonlinear state laws with physics‐augmented neural networks36A Two-Stage Attention-Based Hierarchical Transformer for Turbofan Engine Remaining Useful Life Prediction44Enhancing Deep Learning Soil Moisture Forecasting Models by Integrating Physics-based Models38Physics-informed identification of marine vehicle dynamics using hydrodynamic dictionary library-inspired adaptive regression28Enhancing data-driven soil moisture modeling with physically-guided LSTM networks23Melting points of ionic liquids: Review and evaluation33Lake Water Temperature Modeling in an Era of Climate Change: Data Sources, Models, and Future Prospects128Battery Temperature Prediction Using an Adaptive Neuro-Fuzzy Inference System19Deep learning for water quality364Hybrid physics-machine learning models for predicting rate of penetration in the Halahatang oil field, Tarim Basin56Hybrid modeling design patterns29A hybrid deep learning approach for streamflow prediction utilizing watershed memory and process-based modeling37Meta-pragmatic investigation of passive strategies from ‘UHI– climatology’ nexus perspective with digital twin as assessment mechanism18Efficient Bayesian Physics Informed Neural Networks for inverse problems via Ensemble Kalman Inversion39Physics-guided spatio–temporal neural network for predicting dissolved oxygen concentration in rivers21A physics-embedded deep-learning framework for efficient multi-fidelity modeling applied to guided wave based structural health monitoring22IB-UQ: Information bottleneck based uncertainty quantification for neural function regression and neural operator learning26Machine Learning-Integrated Sustainable Engineering and Energy Systems34Solving partial differential equations using large-data models: a literature review21A process-driven deep learning hydrological model for daily rainfall-runoff simulation45Demonstrating a Hybrid Machine Learning Approach for Snow Characteristic Estimation Throughout the Western United States19Recent Advances in the Application of Machine Learning to Crystal Behavior and Crystallization Process Control39Physics Informed Machine Learning for Reservoir Connectivity Identification and Robust Production Forecasting36Machine learning in proton exchange membrane water electrolysis — A knowledge-integrated framework57Multilevel domain decomposition-based architectures for physics-informed neural networks101Explainable artificial intelligence: A survey of needs, techniques, applications, and future direction237On the deep learning approach for improving the representation of urban climate: The Paris urban heat island and temperature extremes21Streamflow Prediction at the Intersection of Physics and Machine Learning: A Case Study of Two Mediterranean‐Climate Watersheds22Physics-Informed Generalizable Wireless Channel Modeling with Segmentation and Deep Learning: Fundamentals, Methodologies, and Challenges27New Technologies for Monitoring Coastal Ecosystem Dynamics34The rise of scientific machine learning: a perspective on combining mechanistic modelling with machine learning for systems biology61Landslide susceptibility mapping using physics-guided machine learning: a case study of a debris flow event in Colorado Front Range57Reinforcement Twinning: From digital twins to model-based reinforcement learning37Active learning concerning sampling cost for enhancing AI-enabled building energy system modeling21Towards a new paradigm in intelligence-driven computational fluid dynamics simulations30Smart control of bridge support forces using adaptive bearings based on physics-informed neural network (PINN)21Simulating the land carbon sink: Progresses and challenges of terrestrial ecosystem models28Physics informed neural network can retrieve rate and state friction parameters from acoustic monitoring of laboratory stick-slip experiments20Machine learning to assess and support safe drinking water supply: a systematic review22Quantifying Global Wetland Methane Emissions With In Situ Methane Flux Data and Machine Learning Approaches25Artificial intelligence and machine learning at various stages and scales of process systems engineering36Physical-anchored graph learning for process key indicator prediction25A Review of Physics-Based, Data-Driven, and Hybrid Models for Tool Wear Monitoring80Minimizing the carbon footprint of 3D printing concrete: Leveraging parametric LCA and neural networks through multiobjective optimization19A differentiable, physics-based hydrological model and its evaluation for data-limited basins23Computing with oscillators from theoretical underpinnings to applications and demonstrators38Underwater acoustic communications126Physics informed neural network based multi-zone electric water heater modeling for demand response18Knowledge-guided machine learning for improving crop yield projections of waterlogging effects under climate change25Physics-guided neural network for predicting international roughness index on flexible pavements considering accuracy, uncertainty and stability31Physics-Informed Machine Learning for Predicting Stress Wave Transmission Across Realistic Rock Joints42Surrogate Modeling: Review and Opportunities for Expert Knowledge Integration22Towards the next generation of Geospatial Artificial Intelligence91Uncovering the multiple socio-economic driving factors of carbon emissions in nine urban agglomerations of China based on machine learning30Integrating large language model and digital twins in the context of industry 5.0: Framework, challenges and opportunities107Text Classification: How Machine Learning Is Revolutionizing Text Categorization60From traditional damage detection methods to Physics-Informed Machine Learning in bridges: A review61Machine learning-based prediction of nitrous oxide emissions from arable farming: Exploring management practices as predictor variables20Physics‐Informed Neural Networks for Estimating a Continuous Form of the Soil Water Retention Curve From Basic Soil Properties33From failure to fusion: A survey on learning from bad machine learning models18Multi-layer grid-scale soil moisture estimation using spatiotemporal deep learning methods with physical constraints21Artificial intelligence: A key fulcrum for addressing complex environmental health issues40Physics-informed machine learning for grade prediction in froth flotation26Gaps in Water Quality Modeling of Hydrologic Systems26Enhancing friction stir-based techniques with machine learning: a comprehensive review20Artificial Intelligence (AI) in Surface Water Management: A Comprehensive Review of Methods, Applications, and Challenges59Physics-informed self-supervised learning for tool wear monitoring leveraging signal and degradation features under limited labels24Advancements in multiscale modeling of damage in composite materials: A comprehensive review56Physics-informed Kolmogorov–Arnold network with Chebyshev polynomials for fluid mechanics29Deep Learning-Driven Intelligent Fluorescent Probes: Advancements in Molecular Design for Accurate Food Safety Detection18Physics-Informed Machine Learning in Design and Manufacturing: Status and Challenges23Machine learning-based hydrological models for flash floods: a systematic literature review20Nonlinear Model Reduction by Probabilistic Manifold Decomposition22A review of machine learning with small and limited data46Knowledge‐Guided Machine Learning for Global Change Ecology Research19Machine learning–empowered smartphone platforms for sustainable point-of-care bacterial detection30

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