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Literature Synthesis -- Batch 02 Agent 5 (Files 361-400)

Generated: 2026-04-17 | 40 papers | Period: 2020-2021

Paper Extractions

# Author(s) Year Title Core Finding Method Tags
1 Yang et al. 2020 Aero-hydro-servo-elastic coupling framework for FOWTs F2A framework integrating FAST+AQWA shows excellent agreement with OpenFAST for FOWT dynamics Coupled numerical simulation (F2A), verification against OpenFAST FOWT, aero-hydro-servo-elastic, numerical-coupling
2 Zhang S. et al. 2020 Deep Learning for Bearing Fault Diagnostics -- Review DL outperforms conventional ML in bearing fault feature extraction; bearing faults cause 30-40% of machine failures Comprehensive survey; CWRU benchmark comparison of DL architectures deep-learning, bearing-fault, SHM, condition-monitoring
3 Zhang P. et al. 2020 Random forest model for caisson foundation failure envelopes in sand RF accurately learns failure mechanisms from FEM data and generalizes to new soils with minimal additional calibration Random forest + coupled Lagrangian FEM-SPH (CLSPH-SIMSAND) machine-learning, caisson-foundation, failure-envelope, sand
4 Zhang X. et al. 2020 Small-scale modelling of root-soil interaction under lateral loads Shallow-wide root architecture gives higher anchorage; effective stress governs regardless of water condition 1:20 scaled 3D-printed root models; centrifuge (20g) + 1g push-over tests centrifuge, root-soil, scaling-laws, lateral-loading
5 Zhou et al. 2020 High-speed railway subgrade settlement in soft soil -- review Post-construction settlement control in soft soil is critical; existing prediction methods have significant defects Literature review of treatment methods and settlement prediction algorithms soft-soil, settlement, railway, review
6 Zhu et al. 2020 Centrifuge modelling of tetrapod jacket foundation in soft soil Jacket foundations accumulate deformation under cyclic lateral loading in soft soil; safe design must consider cumulative effects Centrifuge modelling, lateral cyclic and monotonic loading centrifuge, jacket-foundation, cyclic-loading, soft-soil
7 Zorzi et al. 2020 Reliability analysis of OWT foundations under lateral cyclic loading Probabilistic framework quantifies SLS reliability for monopile rotation under extreme cyclic events using 3D FE 3D FE with cyclic strain accumulation + reliability analysis monopile, reliability, SLS, cyclic-loading, probabilistic
8 Ostlund et al. 2020 Model assumptions' influence on dynamic impedance of shallow foundations Model assumptions (embedment, modulus variation, permanent load) can change static stiffness by >100% FE parametric study with small-strain modulus reduction dynamic-impedance, shallow-foundation, SSI, soil-dynamics
9 Kariyawasam 2020 Vibration-based bridge scour monitoring (PhD thesis, Cambridge) Vibration-based monitoring can detect scour indirectly, avoiding fragile underwater equipment Vibration-based indirect monitoring technique SHM, scour, bridge, vibration-monitoring
10 Whyte 2020 Practical constitutive models in FEA of offshore foundations (DEng thesis, Oxford) 3D FEA calibrates simplified 1D models for rapid foundation sizing; constitutive model choice is critical 3D FEA with hypoplastic/critical-state models, macro-element calibration FEA, constitutive-model, offshore-foundation, monopile
11 Samui et al. (eds.) 2020 Modeling in Geotechnical Engineering (book) Comprehensive coverage of ML and numerical methods in geotechnical modelling Edited volume: AI, FEM, and hybrid approaches geotechnical-modelling, ML, book
12 Adedipe & Shafiee 2021 Economic assessment framework for OWF decommissioning Turbine/foundation removal is the costliest stage; CBS approach identifies critical cost drivers Cost breakdown structure (CBS), case study 500MW OWF decommissioning, life-cycle-cost, offshore-wind
13 Ali et al. 2021 Offshore wind farm-grid integration review PQ issues from PECs remain challenging; FACTS, DFIG control, ESS, and LVRT are key mitigation strategies Comprehensive review of grid codes, PQ solutions offshore-wind, grid-integration, power-quality, review
14 Almuqhim & Saeed 2021 ASD-SAENet: sparse autoencoder for autism detection via fMRI Sparse autoencoder + DNN achieves improved ASD detection from fMRI data Sparse autoencoder, deep neural network, fMRI autoencoder, medical-imaging, deep-learning
15 Alves et al. 2021 PSD variability effect on SWCC predictions of coarse-grained materials Cu influences residual suction prediction; D10 governs transition and residual stages of SWCC Five SWCC prediction models; sieve, laser diffraction, image analysis unsaturated-soil, SWCC, particle-size, variability
16 Anandan et al. 2021 CNN for soil texture property prediction from hyperspectral data CNN with spatial interpolation of hyperspectral data predicts six soil properties (OC, CEC, N, pH, clay, sand) 1D-CNN on hyperspectral arrays CNN, soil-classification, hyperspectral, remote-sensing
17 Atar et al. 2021 First-order finite similitude in structural mechanics and earthquake engineering Finite similitude theory provides countably infinite scaling alternatives beyond classical dimensional analysis Zeroth- and first-order finite similitude; case studies on steel buildings with viscous dampers scaling-laws, similitude, earthquake-engineering, physical-modelling
18 Basack et al. 2021 OWT power generation -- overview of research and developments OWT technology still under development with significant unsolved problems in dynamics, foundations, and power efficiency Literature review offshore-wind, OWT, review
19 Bellan 2021 Statistical effects of frequency instability on power monitoring Frequency instability introduces bias and standard deviation in harmonic power measurements via DFT Analytical statistical characterization, DFT-based measurement model power-measurement, frequency, signal-processing
20 Bendixen et al. 2021 Sand, gravel, and UN SDGs: conflicts, synergies, pathways Sand/gravel extraction conflicts with multiple SDGs; governance frameworks needed for sustainable aggregate sourcing Policy analysis mapping extraction impacts to 17 SDGs sustainability, aggregate, SDG, environmental-policy
21 Bienen et al. 2021 Installation process effect on monopile lateral response Impact-driven installation changes soil state, producing stiffer lateral response than wished-in-place piles CEL large-deformation FEA with hypoplastic model + centrifuge validation monopile, installation-effect, CEL, lateral-response, sand
22 Bortolotti et al. 2021 Land-based wind turbines with flexible rail-transportable blades (File not found -- no extraction possible) -- --
23 Bossuyt et al. 2021 Wake shape modulation for tilt and yaw misaligned wind turbines Negative tilt (downward deflection) gives best wake recovery through increased curling and high-momentum downdraft Stereo-PIV cross-plane measurements wind-farm, wake-steering, tilt, yaw, PIV
24 Canet et al. 2021 On the scaling of wind turbine rotors Scaling laws formulated for aeroservoelastic matching; even very large scaling factors can match key performance indicators Constrained optimal aerodynamic/structural matching; 10MW reference scaled to 54m, 27m, 2.8m scaling-laws, wind-turbine, aeroservoelastic, subscaling
25 Cerfontaine et al. 2021 Control of screw pile installation for offshore energy Screw pile installation parameters (advance ratio) control performance; optimised installation improves capacity Centrifuge testing, installation parameter control screw-pile, installation, offshore, centrifuge
26 Chadebec et al. 2021 Data augmentation in HDLSS setting using geometry-based VAE Riemannian-manifold VAE with normalizing flows significantly boosts classification in small-sample medical imaging Geometry-based VAE, Riemannian metric learning, ADNI brain MRI VAE, data-augmentation, small-sample, medical-imaging
27 Che et al. 2021 Transient wave-based anomaly detection in fluid pipes -- review Five transient-wave methods reviewed (reflection, damping, FRF, time/frequency inversion); each has distinct applicability Comprehensive review of wave-based pipe inspection methods SHM, pipe-inspection, transient-wave, anomaly-detection
28 Chen C. et al. 2021 Efficient fatigue life prediction of OWTs using aerodynamic decoupling Aerodynamic decoupling dramatically reduces computational cost for fatigue life prediction with acceptable accuracy Decoupled aero-structural simulation fatigue, OWT, aerodynamic-decoupling, computational-efficiency
29 Chen P. et al. 2021 Software-in-the-Loop + RL for FOWT dynamic response Reinforcement learning combined with SIL simulation improves FOWT dynamic response prediction Software-in-the-loop, reinforcement learning, OpenFAST FOWT, reinforcement-learning, dynamic-response
30 Cooperman et al. 2021 Wind turbine blade material in the US: quantities, costs, EOL 2.2M tons cumulative blade waste by 2050 (~1% landfill capacity by volume); current disposal costs are low Spatially-resolved waste and cost estimation, 20-year lifetime assumption blade-waste, circular-economy, end-of-life, composite
31 Cornel et al. 2021 Condition monitoring of roller bearings using acoustic emission AE detects bearing damage ~4% earlier than vibration-based CMS; sub-surface damage signals detected ~50% before failure AE sensors on downscaled bearing test rigs, comparison with vibration CMS condition-monitoring, acoustic-emission, bearing, wind-turbine
32 Cross et al. 2021 Physics-informed ML for SHM Grey-box models (physics + data) improve generalization beyond training regimes for SHM applications Gaussian process regression with physics-informed kernels/mean functions PIML, SHM, Gaussian-process, grey-box
33 Dhandapani & Varadarajan 2021 Multi-channel CNN for leaf disease and soil property prediction MCNN with separate channels for leaf/soil images achieves 87.8% leaf disease and 90.4% soil property accuracy Multi-channel CNN, Pearson correlation CNN, soil-property, agriculture, multi-channel
34 Dirwai et al. 2021 Soil wetting geometry model under Moistube Irrigation Buckingham pi-based empirical model estimates wetted dimensions with nRMSE 0.5-10% Buckingham pi theorem, experimental calibration/validation Buckingham-pi, irrigation, soil-wetting, empirical-model
35 Erinmwingbovo & La Mantia 2021 Instrument artefact correction in dynamic impedance spectra Proposed method enables proper dynamic impedance above potentiostat bandwidth by correcting I/E converter artefacts Transimpedance and stray capacitance estimation, correction algorithm impedance-spectroscopy, artefact-correction, electrochemistry
36 Fan et al. 2021 Monopile installation effects on lateral response in sand (Part II) Installation method (driven vs jacked vs wished-in-place) significantly affects subsequent lateral stiffness and capacity CEL numerical analysis + centrifuge validation monopile, installation, lateral-loading, sand, centrifuge
37 Galvin et al. 2021 Fast simulation of railway bridge dynamics with SSI Sub-structuring with PML-based impedance functions + complex modal superposition matches FE-BE results at minimal cost FE sub-structuring, PML, complex modal superposition SSI, railway-bridge, dynamics, computational-efficiency
38 Ghimire et al. 2021 CNN-LSTM for streamflow prediction CNN-LSTM outperforms standalone CNN, LSTM, DNN, and conventional AI; 84% predictions within 0.05 m3/s error CNN feature extraction + LSTM sequential prediction CNN-LSTM, hydrology, time-series, deep-learning
39 Gravett & Markou 2021 Wind turbine structures on soft clay: SFSI with battered RC piles Optimum battered pile inclination is 10 degrees; failure localizes at tower base via local buckling 3D hexahedral FE (superstructure + piles + soil), modal + pushover analysis wind-turbine, SFSI, battered-piles, soft-clay, FEA
40 Grigoriu 2021 Linear Dynamical Systems (book, Cornell) Textbook on SDOF/MDOF dynamics, frequency domain, numerical methods, shear beam models Analytical + numerical methods for structural dynamics structural-dynamics, textbook, shear-beam

1. CONSENSUS

  • Installation effects matter for monopile design. Bienen (2021) and Fan (2021) independently demonstrate that impact-driven installation changes soil state and produces stiffer lateral response than idealized wished-in-place conditions. The field is converging on the view that ignoring installation effects leads to conservative or inaccurate foundation stiffness predictions.

  • Deep learning surpasses conventional ML for time-series and fault diagnostics. Zhang S. (2020) on bearing faults, Ghimire (2021) on streamflow, and Cross (2021) on SHM all confirm that DL architectures (CNN, LSTM, autoencoders) outperform traditional methods in feature extraction and prediction accuracy, particularly for nonlinear, non-stationary signals.

  • Soil-structure interaction is essential for dynamic structural assessment. Ostlund (2020), Galvin (2021), Gravett (2021), and Zorzi (2020) all show that SSI significantly alters dynamic impedance, modal properties, and structural response. Neglecting SSI can produce errors exceeding 100% in stiffness coefficients.

  • Centrifuge testing remains the gold standard for validating geotechnical numerical models. Zhang X. (2020), Zhu (2020), Bienen (2021), Fan (2021), and Cerfontaine (2021) all rely on centrifuge experiments to validate or calibrate numerical/analytical predictions of foundation behavior.

  • Coupled multi-physics simulation is necessary for OWT/FOWT design. Yang (2020), Chen C. (2021), and Chen P. (2021) demonstrate that aerodynamic, hydrodynamic, structural, and control coupling cannot be decoupled without careful justification, though decoupling can achieve computational savings when validated.

2. DEBATES

  • Wished-in-place vs. installation-modelled piles: The degree to which installation effects improve or degrade lateral capacity remains debated. Bienen (2021) shows stiffer response from driving, but pore-fluid effects during impact driving and vibro-driving remain unresolved.

  • Black-box vs. grey-box vs. white-box for SHM: Cross (2021) argues for physics-informed grey-box models that generalize beyond training data, while Zhang S. (2020) and Ghimire (2021) demonstrate strong purely data-driven results. The trade-off between interpretability/generalization and raw predictive power is unresolved.

  • Classical dimensional analysis vs. finite similitude: Atar (2021) challenges dimensional analysis as the sole scaling framework, proposing infinite alternative similitude orders. Whether this new theory is practical for routine scaled testing (versus classical Buckingham pi) remains under investigation (cf. Canet 2021, Zhang X. 2020).

  • Cyclic degradation models for SLS design: Zorzi (2020) highlights that soil response under cyclic loading involves nonlinearity, pore pressure, and stiffness changes, but the community lacks consensus on which constitutive framework best captures long-term cyclic accumulation for reliability-based design.

3. GAPS

  • Pore-fluid response during impact driving of monopiles is acknowledged as unresolved by both Bienen (2021) and Fan (2021). No validated coupled hydro-mechanical model of the driving process currently exists.

  • Long-term cyclic loading validation data for OWT foundations in soft clay are scarce. Gravett (2021) and Zhu (2020) rely on limited loading histories; multi-decadal field monitoring data do not exist.

  • Scaling laws for soil-foundation systems under dynamic/cyclic loading lack a unified framework. Atar (2021) offers theoretical advances but does not apply them to geotechnical problems. Canet (2021) addresses rotor scaling only; foundation scaling remains ad hoc.

  • Data augmentation for small geotechnical datasets. Chadebec (2021) demonstrates geometry-based VAE for medical imaging; equivalent techniques have not been applied to geotechnical data despite similar small-sample challenges (Zhang P. 2020 relies on numerical augmentation instead).

  • End-of-life strategies for composite blades beyond landfilling remain economically uncompetitive (Cooperman 2021). No cost-effective recycling technology has emerged at industrial scale.

  • Vibration-based scour monitoring (Kariyawasam 2020) needs field validation at scale and under varying flow conditions; lab-to-field transfer is incomplete.

4. METHODS

Method Category Papers Notes
Centrifuge physical modelling Zhang X., Zhu, Bienen, Fan, Cerfontaine Standard for offshore/geotechnical validation; scales 20g-100g
Large-deformation FEA (CEL) Bienen, Fan Coupled Eulerian-Lagrangian for installation modelling
3D FEA with constitutive models Whyte, Gravett, Zorzi, Ostlund Hypoplastic, critical-state, small-strain models
Machine learning (RF, CNN, LSTM) Zhang P., Zhang S., Anandan, Ghimire, Dhandapani Supervised learning on numerical/experimental databases
Physics-informed ML Cross Gaussian process regression with physics kernels
Autoencoders/VAE Almuqhim, Chadebec Sparse AE for classification; geometry-based VAE for augmentation
Reliability/probabilistic Zorzi Monte Carlo + FE for SLS reliability index
Sub-structuring / impedance functions Ostlund, Galvin Frequency-dependent stiffness/damping for SSI
Buckingham pi / dimensional analysis Dirwai, Atar, Canet Classical and extended scaling frameworks
Coupled aero-hydro-servo-elastic Yang, Chen C., Chen P. FAST+AQWA, decoupled approaches, RL-augmented
Acoustic emission monitoring Cornel AE for pre-damage detection in bearings
Stereo-PIV Bossuyt Wake flow measurement for tilt/yaw studies

5. BENCHMARKS

Benchmark Used By Domain
CWRU bearing dataset Zhang S. (2020) Bearing fault diagnostics DL comparison
NREL 5MW / OC3-Hywind spar Yang (2020) FOWT aero-hydro-servo-elastic validation
NREL 10MW reference turbine Zorzi (2020), Canet (2021) Monopile reliability; rotor scaling
Brisbane River / Teewah Creek flow data Ghimire (2021) Streamflow CNN-LSTM prediction
ADNI brain MRI database Chadebec (2021) VAE data augmentation for medical imaging
Karlsruhe/UWA sand databases Bienen (2021), Fan (2021) CEL installation modelling validation
WindAfrica geotechnical site data Gravett (2021) Soft clay SFSI pile optimization
500MW baseline OWF Adedipe (2021) Decommissioning cost estimation