• Wildfires threaten road networks, complicating emergency responses.

• Proposed framework integrates wildfire simulation, risk assessment, and retrofitting.

• GAN-based model evaluates risks using synthetic and historical data.

• Network Performance Tensor combines key metrics for optimal retrofitting decisions.

• Tested in Los Angeles, the framework enhances resilience and scalability.

• Recent Californian route closures underscore earthquake landslide risks.

• Proposes a framework for managing landslide risk to road networks.

• Introduces Siamese Graph Convolutional Network (GCN) infused Genetic Algorithm (GA) for efficient optimization of retrofits.

• Retrofit policy aims for equitable outcomes across income groups.

• Framework applied to Los Angeles, enhances road network resilience.

Paper - link 

• Rapid urbanization strains roads, and increases disaster vulnerability.

• A capital investment algorithm is proposed for optimal road width expansion.

• Novel framework combines mobile mapping, cameras, and lidar.

• Utilizes deep learning, and point cloud processing for precision.

• Outperforms traditional methods in budget-limited situations.

• Enhances hillside road planning and automated feature detection.

Paper - link 

• Proposed method identifies critical road segments for resilience.

• Utilizes Graph Neural Network to assess road importance.

• Overcomes existing methods' limitations in compromised networks.

• Reduces computational load, suitable for large networks.

• Proven effectiveness with synthetic and real-world examples.

Paper - link 

• Sensors are vulnerable to faults from aging, defects, and environment.

• Novel framework introduced for sensor fault detection & data reconstruction.

• Utilizes Convolutional Neural Network (CNN) for fault detection and Convolutional Autoencoder (CAE) networks for data reconstruction.

•  Handles single, and multiple sensor faults with high accuracy.

• Improves data quality, and reduces downtime in health monitoring.

Paper - Link 

• Cable-stayed bridges need continuous monitoring for safety.

• Introduced non-contact, video-based cable tension measurement.

• Moving camera captures vibrations using Phase-based motion estimation and Complexity Pursuit (CP) but also captures camera motion.

• Proposed algorithm cancels camera motion by image processing.

• Study validates camera-based sensing for structural health monitoring.

• Results comparable to designed cable tension values of real bridges.

Paper 1 - Link ;  Paper 2 - Link

• Cost-effective real-time vibration response estimation framework introduced.

• Dense sensor setups are expensive; compressive sensing is employed instead.

• Uses a few sensors' time histories for data gathering.

• Data-driven, employs Dictionary learning for spatial basis functions.

• Promising for aerospace, mechanical, and civil systems' health monitoring.

Paper -  Link 

• An economical, practical method for precise damage estimation is proposed.

• Utilizes Compressive Sensing, and a few sensors for real-time estimates.

• Framework based on the system's partial differential equation.

• Reduces the need for extensive model knowledge.

• Promising for health monitoring in various engineering fields.

Paper - Link 

• Mobile sensors enhance structural vibration sensing capabilities.

• Traditional methods require manual or expensive autonomous vehicles.

• This work introduces formation control for automatic multi-agent sensing.

•  The Proposed algorithm enables full-field vibration response estimation using compressive sensing.

• Demonstrated accuracy with two formations, promising for health monitoring.

Paper - Link 

• Real-time monitoring is crucial for preventing cable damage.

• Wireless sensors present cost-effective, but face packet loss.

• Proposed framework reconstructs lost data for continuous monitoring.

• Combines compressive sensing, Blind Source Separation (BSS), and Sparse Component Analysis (SCA) for data recovery.

• Uses taut-string theory for real-time cable tension estimation.

Paper - Link 

• Research in dynamic property identification of nonlinear jointed systems.

• Modal testing with high-speed videography and Digital Image Correlation.

• Validated experimentally on half Brake–Reuß beam.

• This video-based system parameter estimation is comparable with accelerometer data.

•  Explores modal coupling and mode shape evolution for nonlinear systems.

Paper 1 - Link , Paper 2 - Link 

• Where to place the input for experimental modal analysis?

• A Fisher Information Matrix (FIM) trace optimization technique is proposed.

• Optimally located input reduces the estimation uncertainty.

• Validated numerically on shear building and experimentally on trusses.

• Extremely useful for damage localization.

Paper - Link 

• Research on wind effect on tall unconventional (pentagonal) buildings.

• Existing codes lack guidance for asymmetrical design and interference.

• Numerical analysis with varying wind angle of attack.

• Optimal interfering building placement for reduced wind impact

Paper - Link