TerraMosaic Daily Digest: April 29, 2026
Daily Summary
April 29 shifts the landslide signal from event cataloguing toward forecasting and scale. The strongest contribution replaces conventional intensity-duration warning thresholds with area-based probability-intensity curves for rainfall-triggered debris flows, while the U.S. seasonality analysis turns a national landslide archive into regional preparedness calendars. Together with the Kulon Progo weathering study, debris-avalanche erosion experiments, compound-climate hotspot analysis in Myanmar and Vietnam, and MPM-SDEM simulation of transported objects, the day advances a more spatially explicit and process-aware view of landslide initiation, mobility, and consequence.
The broader geohazard set shows the same movement toward coupled decision systems. Alpine precipitation products are evaluated against landslide and flood triggers; coastal groundwater is framed as an economic risk pathway; rockfall rebound, rockburst brittleness, tunnel blast resilience, seismic site effects, and mine-induced earthquakes connect material state to infrastructure performance. The remote-sensing and AI papers are strongest where prediction is tied to physical alignment, uncertainty, or observation geometry, as in flood-map explanation tests, cloud removal, tunnel reconstruction, thermal anisotropy, and groundwater causal inference.
Key Trends
The selected papers converge on hazard assessment that is probabilistic, spatially explicit, and checked against physical controls rather than only against aggregate accuracy.
- Warning thresholds are becoming probabilistic and spatially explicit: debris-flow probability-intensity curves, U.S. landslide seasonality, Mount Elgon susceptibility mapping, Alpine precipitation-extreme comparison, and the ML susceptibility review all move warning from fixed thresholds toward geographically defined decision support.
- Material state and terrain history control failure more than static class labels: weathering grade, basal erosion, mineral fabric, wet-dry fatigue, MICP-vegetation treatment, rock brittleness, and 3D flow-object interaction all show that hazard behavior depends on evolving mechanical state.
- Compound hydroclimate risks connect atmosphere, groundwater, and exposure: landslide hotspots in Myanmar and Vietnam, drought downscaling, coastal groundwater risk, Arctic wetland dynamics, lake optical change, floodplain-lake contamination, and groundwater causal pathways make water a coupled driver rather than a single trigger.
- Operational AI is being judged by physical alignment: GeoAI explanation alignment, GEE susceptibility mapping, GL-MambaLite building extraction, LiDAR-guided 3D Gaussian Splatting, ECRformer, thermal anisotropy modelling, and unsupervised aeromagnetic inversion all emphasize whether learned outputs preserve interpretable structure.
- Underground and infrastructure hazards are moving toward monitored performance: shield tunnel blast resilience, excavated block indices, tunnel partial freezing, mine blasting assessment, seismic site modelling, pile cyclic response, masonry retrofit, and induced-earthquake mechanisms translate geohazard loading into measurable structural response.
Selected Papers
This digest features 70 selected papers from 1,616 papers analyzed. The sequence opens with area-based probability-intensity curves for rainfall-triggered debris flows and U.S. landslide seasonality, then moves through weathering-controlled volcanic landslides, debris-avalanche seismic signatures, compound climate extremes, MPM-SDEM flow-type landslide simulation, Mount Elgon susceptibility mapping, Alpine precipitation hazards, coastal groundwater risk, rockfall rebound, seismic site effects, rockburst brittleness, and explainable GeoAI for flood mapping.
1. Improving predictions of rainfall-triggered debris flows using area-based probability intensity curves
Core Problem: Operational debris-flow warnings still depend heavily on intensity-duration thresholds that create many false alarms and rarely define the spatial footprint over which a warning is valid.
Key Innovation: The paper replaces point-style rainfall thresholds with area-based probability-intensity curves derived from gridded rainfall and time-constrained inventories, improving warning precision and critical success across British Columbia watersheds.
2. Asynchronous Landslide Seasonality Across the United States
Core Problem: Mid-range landslide outlooks need continental-scale timing information, but landslide seasonality in the United States has remained weakly quantified and regionally inconsistent.
Key Innovation: More than 55,000 reported landslides are analyzed with circular statistics across 67 National Weather Service County Warning Areas, revealing asynchronous seasonal domains and movement-type differences relevant to preparedness windows.
3. Influence of weathering grades on landslide occurrences in the tropical volcanic region of Kulon Progo, Indonesia
Core Problem: Regional landslide assessments in tropical volcanic terrain often ignore how progressive rock weathering changes strength, mineralogy, and slope-material density.
Key Innovation: Field surveys, Schmidt hammer tests, XRD, laboratory geotechnics, and spatial analysis show that intermediate weathering grades concentrate landslide occurrence in Kulon Progo by weakening rock while retaining slope-forming mass.
4. Erosion-induced stress fluctuations and seismic signals in debris avalanches: insights from laboratory experiments
Core Problem: Debris avalanches entrain basal material and generate seismic signals, but the link between erosion geometry, basal stress fluctuations, and seismic observability is difficult to isolate in natural events.
Key Innovation: Controlled flume experiments vary erodible bed length, inclination, and entry angle to show how entrainment modifies stress duration, energy dissipation, mobility, and seismic signatures.
5. Compound climate extremes shape landslide hotspot heterogeneity in Myanmar and Vietnam
Core Problem: Landslide hotspots in monsoon Asia are shaped by compound climatic extremes, yet many hotspot maps treat climate forcing as static background context.
Key Innovation: The study links hotspot heterogeneity in Myanmar and Vietnam to compound climate extremes, reframing regional landslide clustering as a hydroclimatic interaction rather than only a terrain-conditioning problem.
6. A novel coupled MPM-SDEM framework for simulating non-spherical objects in flow-type landslide
Core Problem: Flow-type landslides can transport vehicles, shelters, and other non-spherical objects, but existing runout simulations poorly predict object travel distance and burial location.
Key Innovation: A coupled MPM-SDEM framework represents landslide flow with material points and entrained objects with sphero-polyhedron DEM, improving impact-force and travel-distance prediction with large efficiency gains.
7. Landslide Susceptibility Mapping in the Mount Elgon Districts of Eastern Uganda Using Google Earth Engine
Core Problem: Mountain districts around Mount Elgon require scalable landslide susceptibility mapping, but local assessments often lack high-resolution cloud-based workflows.
Key Innovation: Google Earth Engine integrates slope, elevation, vegetation, rainfall, land cover, soil, drainage, and geology to produce a regional susceptibility map for eastern Uganda.
8. Detection and characterization of precipitation extremes and geohydrological hazards over a transboundary Alpine area based on different methods and climate datasets
Core Problem: Geohazard detection in the Alps depends on how precipitation extremes are defined and which climate product is used, creating uncertainty for cross-border risk management.
Key Innovation: Multiple meteorological datasets and statistical definitions are compared over an Austria-Italy Alpine area, showing which high-resolution products and percentile metrics best align with hazardous events.
9. From Hydraulic Heads to Dollars and Decision: It's Time to Integrate Groundwater in Coastal Risk Assessment
Core Problem: Coastal risk assessments often price surface flooding while omitting rising groundwater, salinization, basement flooding, corrosion, and contaminant mobilization.
Key Innovation: The commentary argues for subsurface risk tools that translate hydraulic heads into exposure, vulnerability, costs, and adaptation decisions for coastal communities.
10. Impact and rebound dynamics of mineral-heterogeneous rocks: From micromechanical mechanisms to energy-based modeling
Core Problem: Rockfall models usually assign empirical restitution coefficients even though mineral fabric and impact velocity control rebound behavior in polycrystalline rocks.
Key Innovation: Discrete-element simulations with explicit mineral heterogeneity connect oblique impact, stage-dependent rebound, and energy partitioning to an energy-based restitution model.
11. 3D geological modelling and geotechnical characteristics of quaternary sediments for seismic site effect analysis: case study of Banda Aceh City, Indonesia
Core Problem: Urban seismic hazard in deltaic sediments requires a three-dimensional picture of shallow geology and geotechnical properties, not only regional earthquake source information.
Key Innovation: Banda Aceh is modeled with borehole lithology, laboratory properties, and 3D sediment geometry to support site-effect analysis for high-rise and long-span infrastructure.
12. A brittleness index for rock based on the full-process elastic energy conversion ratio under coupled temperature–loading-rate effects
Core Problem: Deep-rock brittleness under coupled temperature and loading-rate effects is hard to evaluate, limiting rockburst hazard interpretation in high-stress mining.
Key Innovation: Uniaxial and cyclic loading tests on heat-treated granite define a brittleness index based on full-process elastic energy conversion during failure.
13. Evaluating the Alignment Between GeoAI Explanations and Domain Knowledge in Satellite-Based Flood Mapping
Core Problem: Deep-learning flood maps are increasingly accurate, but their explanations must be checked against domain knowledge before they can support critical operational use.
Key Innovation: The ADAGE framework evaluates whether GeoAI explanations from satellite flood mapping align with hydrologic and remote-sensing expectations using channel-group attribution.
14. Research progress in landslide susceptibility assessment driven by machine learning: A bibliometric analysis
Core Problem: Machine-learning landslide susceptibility research has expanded rapidly, but its thematic evolution and dominant technical choices need synthesis.
Key Innovation: A CiteSpace and VOSviewer bibliometric review of 817 Web of Science papers maps publication growth, research fronts, and emerging themes in ML-driven susceptibility assessment.
15. A stacked generalization-based multi-model ensemble framework for precipitation downscaling and drought characterization in a semi-arid region
Core Problem: Semi-arid drought assessment requires precipitation fields fine enough for local characterization, but coarse data products blur spatial variability.
Key Innovation: A stacked-generalization ensemble downscales precipitation and feeds drought characterization, using base model outputs as secondary-model predictors.
16. Hydraulic behavior of unsaturated soils under microbially induced calcium carbonate precipitation–vegetation combined treatment
Core Problem: Vegetation and MICP can improve slope stability under extreme rainfall, but their combined effect on water retention and infiltration is not well resolved.
Key Innovation: Soil-column evaporation and rainfall experiments quantify how vetiver density and MICP treatment alter volumetric water content, suction, and infiltration behavior.
17. A hybrid geometric optical-radiative transfer model for characterizing thermal infrared anisotropy over sloping terrain
Core Problem: Satellite land-surface temperature over mountains is biased by directional anisotropy from topography and canopy structure.
Key Innovation: The GOSAILTIR model couples geometric optics and radiative transfer to represent thermal infrared anisotropy over sloping terrain and discontinuous vegetation.
18. Satellite-Based Chlorophyll-a Prediction Reveals Salinity-Dominated Regime Shifts in the East China Sea: A 22-Year Multi-Sensor Analysis with Explainable AI
Core Problem: Chlorophyll-a retrieval in complex coastal seas must distinguish environmental controls from location-dependent correlations.
Key Innovation: A 22-year multi-sensor XGBoost and SHAP framework identifies salinity thresholds that reorganize chlorophyll dynamics in the East China Sea.
19. The Gassy Sediments of the Cilento Offshore (Southern Tyrrhenian Sea, Italy) and Their Impact on the Marine Hazard Offshore the Cilento Promontory
Core Problem: Shallow gas and gas-charged sediments can influence offshore hazard, but their acoustic expression and stratigraphic context must be mapped in detail.
Key Innovation: A dense sub-bottom Chirp profile grid identifies acoustic blanking, shallow gas pockets, and gas-impregnated units offshore the Cilento Promontory.
20. Probabilistic resilience assessment of large-diameter shield tunnels under surface explosive hazards
Core Problem: Large-diameter shield tunnels exposed to surface explosions need resilience metrics that combine structural damage, spatial threat probability, and recovery.
Key Innovation: A probabilistic resilience framework validated by 3D finite elements grades tunnel performance and couples blast risk assessment with recovery modeling.
21. Mechanism of Earthquakes Induced by Composite Key Stratum Fracturing During Deep Mining
Core Problem: Strong seismic events in deep mining are tied to thick hard overburden, but composite key-stratum fracture mechanisms remain difficult to diagnose.
Key Innovation: Theoretical analysis, numerical simulation, and microseismic monitoring define criteria for composite key strata and explain mining-induced earthquake generation.
22. Groundwater Level Response Processes in Arid Northwest China Based on Remote Sensing and Causal Inference: From Influential Variables to Transmission Pathways
Core Problem: Groundwater-level decline in arid basins is driven by interacting natural and human factors whose causal pathways are rarely separated.
Key Innovation: Remote sensing, trend decomposition, and PCMCI causal inference trace influential variables and transmission pathways across seven Tarim Basin sub-basins.
23. Failure behavior and energy-evolution processes of dolomite after wetting-drying under cyclic loading-unloading with variable confining pressure
Core Problem: Open-pit slope rocks experience both wetting-drying cycles and cyclic disturbances, but their combined energy evolution is poorly constrained.
Key Innovation: Multistage triaxial cyclic loading-unloading tests under variable confining pressure quantify dolomite strength, deformation, and energy partition after repeated wetting-drying.
24. Seepage control analysis of Baihetan hydropower station underground powerhouse during storage and operation periods
Core Problem: Deep underground powerhouses behind high dams require seepage control designs that remain effective during storage and operation.
Key Innovation: A finite-element drainage-hole simulation strategy evaluates water head and drainage response for the Baihetan Hydropower Station anti-seepage curtain and drainage system.
25. Upper Bound Analysis of 3D Uplift Failure Mechanisms for CAES Rock Caverns Considering Fatigue Damage
Core Problem: Lined rock caverns for compressed-air energy storage face uplift failure under size effects and long-term fatigue damage.
Key Innovation: Upper-bound limit analysis with nonlinear Hoek-Brown strength derives 3D uplift failure surfaces and limit pressures for tunnel-type and silo-type caverns.
26. Excavated block index: Towards a continuous classification of rock mass structure in shielded tunnelling
Core Problem: Shield tunnelling needs continuous recognition of jointed rock intervals, but machine data can be ambiguous in weakened ground.
Key Innovation: The Excavated Block Index counts joint-augmented blocks on conveyor-belt images with CNN detection to classify rock mass structure during tunnelling.
27. A novel spatio-temporal hybrid convolutional neural network-cellular automata for projecting discrete drought variables
Core Problem: Discrete drought-class projections need spatio-temporal models that learn changing transition probabilities instead of relying on static Markov matrices.
Key Innovation: A hybrid CNN-cellular automata framework replaces fixed CA-Markov transitions with data-driven transition functions and optional climatic drivers.
28. Responses to earthquakes and volcanic eruptions under authoritarian rule: a comparison between fascist Italy and Portugal during the Estado Novo
Core Problem: Disaster response histories under authoritarian regimes reveal how vulnerability, communication control, and recovery choices persist beyond individual events.
Key Innovation: A comparative analysis of fascist Italy and Portugal under the Estado Novo examines earthquake and eruption management, media control, and institutional continuity.
29. Dynamic Arctic wetland mapping: A multi-mission satellite time series approach
Core Problem: Static Arctic wetland maps miss short-term inundation driven by snowmelt, rainfall, flooding, and permafrost degradation.
Key Innovation: A multi-mission time-series framework combines Sentinel-1 backscatter and Sentinel-2 vegetation indices to map dynamic wetland extent across large Arctic-boreal regions.
30. LiDAR-Guided 3D Gaussian Splatting with Differentiable UDF-Based Regularization for Mine Tunnel Reconstruction
Core Problem: Underground mine tunnels are difficult to reconstruct from images because weak texture, uneven illumination, and moving objects break photometric consistency.
Key Innovation: LiDAR-guided 3D Gaussian Splatting uses dynamic-object removal and differentiable UDF regularization to stabilize tunnel geometry in weak-texture regions.
31. Dynamic run-up and run-down characteristics in successive solitary waves on a slope
Core Problem: Successive solitary-wave run-up on slopes involves vortex dynamics and quasi-steady behavior that are hard to observe experimentally.
Key Innovation: A high-precision numerical wave tank simulates six solitary waves over a 1:10 slope and resolves the transition from primary breaking vortices to periodic run-up and run-down.
32. Deep Learning-Based Waterline Detection Applied to Wave Period Measurement in the Nearshore Swash Zone
Core Problem: Swash-zone wave-period measurements from UAV video are sensitive to thin waterline detection errors and false temporal tracks.
Key Innovation: DeepUNet waterline extraction, timestack analysis, and spatial-temporal quality control convert high-resolution UAV videos into robust nearshore wave-period estimates.
33. Effect of rubber-soil mixture as geotechnical seismic isolator on structure dynamic performance by centrifuge modeling
Core Problem: Low-rise structures need practical seismic isolation methods that reduce transmitted motion without expensive structural systems.
Key Innovation: Centrifuge tests and OpenSees validation evaluate waste-tire rubber-soil mixtures beneath building bases as geotechnical seismic isolators.
34. GL-MambaLite: A Lightweight Global–Local Feature Enhanced Network for Building Extraction
Core Problem: Large-scale building extraction must capture fine structural detail and long-range context without the computational burden of heavy hybrid models.
Key Innovation: GL-MambaLite combines lightweight global-local feature enhancement for scalable building mapping from remote-sensing imagery.
35. 3D Aeromagnetic Inversion Using Unsupervised Deep Learning: Imaging Deep Magnetic Structures in the Panxi Region, SW China
Core Problem: Deep magnetic structures and fault-controlled intrusions are difficult to image with conventional 3D inversion in complex mineral regions.
Key Innovation: Unsupervised deep-learning aeromagnetic inversion reconstructs 3D susceptibility in the Panxi region and links magnetic anomalies to rift and fault systems.
36. Towards a framework for mapping forest cover fractions: A cross-biome evaluation
Core Problem: Categorical forest maps obscure fractional cover changes in heterogeneous landscapes where disturbance and recovery are spatially mixed.
Key Innovation: Cross-biome experiments compare classical ML and deep-learning regressors with spectral-temporal composites for sub-pixel forest-cover fraction mapping.
37. Field monitoring and numerical analysis of a novel micro-disturbance partial freezing technology: A case study of the first Bangkok power tunnel rehabilitation project in Thailand
Core Problem: Post-disaster urban tunnel rehabilitation must stabilize collapse zones while limiting frost-heave disturbance to adjacent structures.
Key Innovation: A monitored partial-freezing technology with optimized long-inlet and short-outlet pipe layout is validated through numerical simulation and field data in Bangkok.
38. Geothermal Resource Exploration Using Multi-Temporal Infrared Remote Sensing Data Based on Annual Temperature Variation Model
Core Problem: Weak geothermal surface signals are easily masked by seasonal temperature cycles, topography, land cover, and clouds in thermal infrared imagery.
Key Innovation: A nonlinear annual temperature-variation model fitted to Landsat thermal time series separates persistent geothermal anomalies from seasonal noise.
39. FA-CTNet: A Geometry-Aware Deep Learning Approach for Tree Species Classification from LiDAR Point Clouds
Core Problem: Tree-species classification from LiDAR point clouds is limited by complex geometry and long-tailed species distributions.
Key Innovation: FA-CTNet combines biologically meaningful geometric features, global attention, and class-balanced focal loss for improved near-range LiDAR species recognition.
40. Landsat observations reveal increasing trend in lake clarity on the Qinghai-Tibetan Plateau: Insights into the lake optical response to climate change
Core Problem: Qinghai-Tibetan Plateau lakes are changing rapidly, but long-term optical responses to climate forcing remain under-characterized.
Key Innovation: Landsat time series from 1986 to 2024, cross-calibrated with MODIS, retrieve Secchi disk depth and reveal increasing lake clarity trends.
41. Biotic mediation of mineral-associated organic carbon vulnerability in dryland subsoils
Core Problem: Deep dryland soil carbon is often treated as stable, but its sensitivity to aridity and microbial controls is uncertain.
Key Innovation: A Mongolian Plateau aridity-gradient study links subsoil mineral-associated organic carbon vulnerability to microbial biomass and fungal diversity.
42. Seasonal water level fluctuations regulate the distribution and risk of antibiotic resistance genes in the sediments of the largest floodplain-lake in China
Core Problem: Seasonal water-level fluctuations in floodplain lakes may regulate antibiotic resistance genes, but this hazard pathway is rarely assessed.
Key Innovation: An integrative study of China's largest floodplain lake shows dry-season water-level zones reshape ARG abundance, drivers, and ecological risk.
43. Intelligent blasting fragmentation assessment in open-pit mines: An automated system based on YOLOv8-seg and binocular vision
Core Problem: Blast-fragmentation assessment in mines is labor intensive and reference-object dependent, limiting rapid feedback on blasting performance.
Key Innovation: YOLOv8-seg and binocular vision produce automated reference-free rock-fragment size distributions from open-pit mine imagery.
44. Geospatial Analysis of Soil Quality Parameters and Soil Health in the Lower Mahanadi Basin, India
Core Problem: Land-cover transformation changes soil quality and ecosystem resilience, but basin-scale spatial-temporal soil health evidence is often fragmented.
Key Innovation: A geospatial soil quality index tracks land cover, organic carbon, nitrogen, and bulk density changes in the lower Mahanadi Basin from 2011 to 2020.
45. Multiscale Analysis of TanDEM-X InSAR Phase Measurements for Forest Structure Characterization
Core Problem: Three-dimensional forest structure must be observed at multiple spatial scales because disturbance effects are scale dependent.
Key Innovation: Wavelet analysis of TanDEM-X InSAR phase-center height characterizes forest structural heterogeneity across spatial resolutions.
46. Arctic Sea Ice Type Classification Using a Multi-Dimensional Feature Set Derived from FY-3E GNSS-R and SMOS
Core Problem: Sea-ice type classification needs features that capture both scattering dynamics and surface conditions across polar regions.
Key Innovation: FY-3E GNSS-R and SMOS observations are fused into a multi-dimensional feature set for Arctic sea-ice classification.
47. Snow-Covered Filter-Enhanced Canopy Surface Points: A Lightweight and Efficient Framework for Individual Tree Segmentation from LiDAR Data
Core Problem: Individual tree segmentation must balance 3D information preservation with computational efficiency across multi-platform LiDAR datasets.
Key Innovation: A snow-covered-filter framework extracts canopy surface points, reducing point-cloud volume while retaining tree-crown structure for segmentation.
48. Test-Time Candidate-Aware Dual Refinement for Remote Sensing Image–Text Retrieval
Core Problem: Remote-sensing image-text retrieval suffers from asymmetry between sparse captions and dense overhead imagery during inference.
Key Innovation: CADRE uses test-time candidate-aware dual refinement to improve bidirectional visual-text alignment without changing the retrieval backbone.
49. Benchmarking individual tree segmentation using multispectral airborne laser scanning data: The FGI-EMIT dataset
Core Problem: Individual tree segmentation lacks large multispectral airborne LiDAR benchmarks for supervised and unsupervised algorithm comparison.
Key Innovation: FGI-EMIT provides 1,561 manually annotated boreal trees captured at 532, 905, and 1550 nm for benchmarking multispectral ALS segmentation.
50. Satellite based lithological Mapping: A review of Sensors, Methods, and emerging Machine-Learning approaches
Core Problem: Satellite lithological mapping is expanding across multispectral, hyperspectral, and machine-learning methods, but the sensor-method landscape is fragmented.
Key Innovation: The review synthesizes sensors, feature spaces, and emerging ML approaches for mapping geological formations across inaccessible regions.
51. ECRformer: An efficient cloud removal Transformer with semantic-decoupled learning for multimodal satellite imagery
Core Problem: Clouds severely limit optical satellite monitoring, while SAR-optical cloud removal remains computationally heavy and ill posed.
Key Innovation: ECRformer combines efficient Transformer design with semantic-decoupled learning for multimodal SAR-optical cloud removal.
52. Improving ocean color algorithms for Chlorophyll-a retrieval with Machine learning and ensemble modeling in optically complex coastal waters
Core Problem: Chlorophyll-a retrieval in turbid coastal waters is confounded by overlapping optical signals and poor model transferability.
Key Innovation: A hybrid strategy integrates optimized ocean-color algorithms with ML and ensemble modeling to improve cross-sensor and cross-region coastal Chl-a retrieval.
53. A Multi‐Scale Geophysical–Geochemical Footprint of Persistent Methane Leakage at a Legacy Petroleum Well
Core Problem: Surface methane flux measurements are strongly modulated by shallow conditions, making persistent leakage from legacy wells difficult to distinguish.
Key Innovation: Repeated flux surveys, electromagnetic conductivity, and geochemistry identify a coherent subsurface footprint around a decommissioned gas well.
54. Multi-scale study on the cracking performance of overlying soils in relation to the interaction between polymer intervention and rock interface roughness amplitude
Core Problem: Sprayed soils on rocky slopes can crack and lose moisture during early restoration, weakening ecological recovery and shallow stability.
Key Innovation: Evaporation and wetting-drying tests quantify how polymer treatment and soil-rock interface roughness control overlying-soil cracking.
55. Acoustic inversion of high-resolution seismic data applied to geotechnical characterization of marine sediments in the Campos Basin
Core Problem: Geotechnical characterization of shallow marine sediments is sparse, yet offshore engineering needs continuous estimates of cone resistance and pore pressure.
Key Innovation: Acoustic impedance inversion of sub-bottom profiler data is calibrated against MSCL-S and CPT measurements to predict vertical geotechnical trends.
56. Multiscale evaluation of bio-treated residual granitic soil strength for sustainable applications
Core Problem: Residual granitic soils need sustainable strengthening methods that also address waste and contaminant interactions.
Key Innovation: Polybutylene succinate and xanthan gum treatments are evaluated through mechanical, microstructural, thermal, spectroscopic, and curing tests.
57. An artificial neural network-based cyclic p-y curve model for predicting the lateral cyclic response of piles in sand
Core Problem: Cyclic lateral pile response in sand controls the serviceability of structures such as wind turbines but remains hard to model under complex stress paths.
Key Innovation: Recurrent neural networks trained on DEM cyclic triaxial simulations feed an ANN-based cyclic p-y curve model for laterally loaded piles.
58. Seismic strengthening of low-strength masonry walls using internal steel strips and polymer mortar: experimental and parametric numerical investigations
Core Problem: Low-strength masonry walls require retrofit methods that improve ductility and load capacity without full reconstruction.
Key Innovation: Full-scale cyclic tests and parametric models evaluate internal steel strips and polymer mortar as composite seismic strengthening systems.
59. Dynamic behavior of oxalic acid modified loess with experimental research and constitutive modeling
Core Problem: Loess in seismic regions has weak structure and complex dynamic behavior that require environmentally acceptable modification methods.
Key Innovation: Oxalic-acid treatment is tested with cyclic torsional shear experiments and constitutive modeling to improve dynamic shear resistance.
60. Impact Load Profile and Vibrations in Dynamic Compaction of Soil with Flat and Conical-Bottom Tampers
Core Problem: Dynamic compaction can transmit damaging vibrations to adjacent structures depending on tamper geometry and soil stiffness.
Key Innovation: Axisymmetric and 3D finite-element models show that conical-bottom tampers reduce near-field PPV while expanding the strain influence zone.
61. Experimental and numerical study of prefabricated bridge columns with UHPC-core socket connection
Core Problem: Accelerated bridge construction needs prefabricated column connections that retain seismic performance under cyclic loading.
Key Innovation: Scaled quasi-static tests and numerical simulations evaluate UHPC-core socket connections against cast-in-place bridge columns.
62. Adaptive Harmony Search-Based Optimization of Tuned Mass Damper Inerters Under Near-Fault Earthquake Records
Core Problem: Tall buildings under near-fault earthquake records need tuned vibration-control systems with optimized displacement reduction.
Key Innovation: Adaptive Harmony Search optimizes tuned mass damper inerter parameters by updating memory and pitch adjustment during the search.
63. Global collapse mode-guided plastic design for K-shaped eccentrically braced frames with replaceable shear links (KEBF-RSLs)
Core Problem: Replaceable shear-link braced frames need plastic design rules that explicitly control global collapse mode and energy dissipation.
Key Innovation: A two-stage plastic design method integrates kinematic collapse theory for K-shaped eccentrically braced frames with replaceable shear links.
64. Multi-Objective Adaptive Harmony Search for Optimization of Seismic Base Isolator Systems
Core Problem: Base-isolator design must balance displacement demand and acceleration reduction, but objective weighting can change optimal parameter choices.
Key Innovation: Multi-objective Adaptive Harmony Search explores weighting effects for seismic base isolator optimization.
65. Experimental and non-linear FEA-based seismic evaluation of corroded flexural and shear R/C columns
Core Problem: Corrosion undermines reinforced-concrete column behavior in earthquakes, while many standards treat degradation with empirical judgment.
Key Innovation: Experiments and nonlinear finite-element analysis incorporate bond degradation to evaluate flexural and shear corroded RC columns.
66. Quantifying model error uncertainty in seismic assessment of unreinforced masonry buildings using the equivalent frame method
Core Problem: Equivalent-frame seismic assessment is efficient but model-error uncertainty remains poorly quantified for masonry buildings.
Key Innovation: A comprehensive uncertainty study estimates model errors in global response parameters predicted by equivalent-frame methods.
67. Numerical evaluation of hybrid reinforcement strategies for seismic enhancement of exterior RC beam–column joints
Core Problem: Exterior RC beam-column joints need reinforcement strategies that increase ductility and energy dissipation while limiting residual drift.
Key Innovation: LS-DYNA simulations compare SMA-steel and dual-grade-steel hybrid reinforcement strategies with localized hinge relocation.
68. Seismic evaluation and retrofit of an existing corner beam-column joint reinforced with plain bars using large-scale bidirectional cyclic reversal experimental tests
Core Problem: Existing corner beam-column joints with plain bars can fail in shear under bidirectional earthquake loading.
Key Innovation: Large-scale bidirectional cyclic tests evaluate as-built behavior and a retrofit using planted horizontal and diagonal reinforcement.
69. Experimental investigation of the shear performance of interlocking dry-joint masonry walls under varying ratios of the ultimate compressive load
Core Problem: Dry-stacked interlocking masonry needs shear-performance evidence across axial load levels for low-cost seismic construction.
Key Innovation: Prism and wall tests quantify in-plane shear response, stress-strain behavior, and damage patterns under varying compressive-load ratios.
70. Evaluation of seismic energy demand in height-dependent moment frames: Implementing comprehensive seismic scenarios, different nonlinear materials and drift correlations
Core Problem: Energy-based seismic design needs clearer links among frame height, nonlinear material assumptions, drift, and energy distribution.
Key Innovation: OpenSees simulations of NIST-designed steel moment frames under FEMA P695 records compute input, kinetic, damping, and hysteretic energy terms.