About

Smart structures adaptability to the changing environment during extreme events, transforming structural design inspired by imitating nature's wonders, and adaptable building envelope design's ability to mitigate windstorm related damage.

Research topics

• Computer Science
• Engineering
• Computer Security
• Electrical engineering
• Systems engineering
• Artificial Intelligence
• Risk analysis (engineering)
• Mathematics
• Environmental science
• Composite material
• Business
• Waste management
• Physics
• Materials science
• Telecommunications
• Architectural engineering

Selected publications

• Historic Buildings Affected by the 3 March 2020 Nashville Tornadoes

  International Journal of Architectural Heritage · 2026-03-09

  article
  PublisherDOI

• Microscale Investigation of Urban Heat Island in Tanzania: Evaluating the performance of extreme heat mitigation strategies for multifamily housing buildings

  2026-04-02

  articleOpen accessSenior author

  Urbanization and climate change are causing cities to become hotter, which has significant negative impacts on urban life. Extreme heat is exacerbated by climate change, anthropogenic activities, land use change, high-rise building density, and heat from vehicles and air conditioning systems. Unfortunately, many people cannot afford mechanical ventilation systems, which causes extreme heat events to disproportionately impact the elderly and low-income groups in marginalized communities. Protecting populations from extreme heat is crucial for sustainability and health, with short-term urban cooling solutions reducing risks.This paper investigated the impact of different mitigation strategies installed on multi-family housing blocks to reduce the UHI effect in Dar es Salaam, Tanzania. Through 17 microclimate simulation scenarios, this paper evaluates how changing the materials used for surfaces like walls and pavements could improve outdoor comfort compared to the current design in the area. It further compared the effect of a change in albedo for selected materials on pavements, walls, and roofs. The results revealed the thermal cooling effect of adding urban vegetation, such as trees and green walls, to reduce mean radiant temperature (TMRT) and hence improve outdoor thermal comfort in areas of warm humid climate.

  PublisherOA PDFDOI

• Historic Buildings Affected by the 2021 Quad State Tornadoes

  International Journal of Architectural Heritage · 2025-07-09 · 2 citations

  article
  PublisherDOI

• Camera-Based Real-Time Damage Identification of Building Structures through Deep Learning

  Journal of structural design and construction practice. · 2025-01-09 · 3 citations

  articleSenior author

  Real-time damage identification (DI) augments smart structures with instant damage information. Capturing the severity and location of the damage via real-time DI will allow for effective scheduling of preventive measures and action plans to isolate the damage and replace affected elements. It also improves structural safety, especially against extreme events unknown at the design stage. There is a need to overcome the difficulties and limitations of model-based approaches and train supervised machine-learning classifiers in the absence of measured damaged data. This paper proposes an image-based DI methodology using deep neural networks to provide real-time data-driven damage information for structural systems. The proposed methodology is evaluated experimentally using a three-dimensional (3D) moment-resisting frame structure subjected to dynamic loading. Two data acquisition configurations are studied simultaneously to measure the dynamic response and compare the accuracy between sensors and video recording. Video processing techniques track the floor levels to capture structural response. The deep learner outputs provide real-time DI describing the damage’s severity and location. Results show the effectiveness of the proposed nondestructive and model-free methodology for real-time DI.

  PublisherDOI

• Deep Reinforcement Learning‐Based Control for Real‐Time Hybrid Simulation of Civil Structures

  International Journal of Robust and Nonlinear Control · 2025-01-25 · 2 citations

  articleOpen accessCorresponding

  ABSTRACT Real‐time Hybrid Simulation (RTHS) is a cyber‐physical technique that studies the dynamic behavior of a system by combining physical and numerical components that are coupled through a boundary condition enforcer. In structural engineering, the numerical components are subjected to environmental loads that become dynamic displacements of the physical substructure applied through an actuator. However, the dynamics of the coupling between components and the complexities of the system lead to synchronization challenges that affect the accuracy of the simulation. Thus, requiring tracking controllers to ensure the fidelity of the simulation. This paper studies deep reinforcement learning (DRL) as a novel alternative to designing the tracking controller. Three controllers are designed: a DRL agent combined with a conventional time delay compensation, a conventional feedback controller combined with a DRL agent, and a DRL agent with a complex neural network architecture. The proposed approaches are tested using a virtual RTHS benchmark problem, and the results are compared with an optimized controller that has a proportional‐integral‐derivative controller and phase‐lead compensation. The results show that DRL can address the synchronization challenges of RTHS with a model‐free approach and simple neural network architectures. The work shown in this study is a critical step toward model‐free control methodologies that can transform and further develop the RTHS method. The proposed methodology can be used to address important challenges related to RTHS, including nonlinearities and uncertainties of the physical substructure, complex boundary conditions, and the computational efficiency when physical structures with complex dynamics are present.

  PublisherOA PDFDOI

• Comparison and Evaluation of Model-Based Optimal Sensor Placement Implementation: A Case Study of a Hybrid Cross-Laminated Timber and Steel Building

  Journal of structural design and construction practice. · 2025-03-24

  articleSenior author

  The construction industry has reshaped timber building practice into the integration of timber structures with other materials such as steel, termed hybrid timber-based structures, as an attractive, sustainable, and aesthetic solution. However, novel hybrid timber-based structures may require critical validation of design assumptions and structural dynamic performance. This paper conducts a study of model-based optimal sensor placement (OSP) implementation in which two OSP methods and six evaluation criteria are compared and evaluated to ensure the most significant dynamic information content by analyzing two comparison metrics for a resulting sensor configuration in the dynamic identification of a hybrid cross-laminated timber (CLT)-steel building with structural irregularities. The Engineering Design and Innovation building at The Pennsylvania State University is a rectangular 4-story hybrid building with moment-resisting steel frames and composite floors of reinforced concrete layer and CLT panels. For this case study, the OSP problem is a sensitive factor, motivated by the potential torsional effects of structural irregularities from the lateral force-resisting system during serviceability, in the capture of the most significant information content and identification of dynamic properties by a cost-effective structural health monitoring (SHM) strategy. The proposed investigation compares and examines the backward sequential sensor placement (BSSP) and genetic algorithm (GA) methods using different evaluation criteria to capture and maximize the most relevant dynamic information, evaluated by a Pareto analysis constructed based on the modal assurance criterion (MAC) trace and Fisher information matrix (FIM) determinant metrics simultaneously, for the numerical mode shape identification. The model-based OSP implementation plays a critical role in SHM applications, simplifying data collection and improving dynamic information quality for dynamic identification and damage detection in order to better comprehend the structural health condition and performance of existing civil infrastructure such as the hybrid mass timber-steel building presented.

  PublisherDOI

• Wave attenuation and tunability of a diatomic metamaterial

  2025-05-05

  articleSenior author

  The exposition level of the built environment to seismic wave propagation underscores the critical need for advanced strategies to mitigate structural damage and life-threatening conditions during earthquake events. To reduce seismic wave impact, metamaterials have unveiled promising wave attenuation performance due to their design, adaptability, and effectiveness. While numerical studies have demonstrated the effectiveness of metamaterials in attenuating different frequency excitations (including earthquake excitations), experimental evidence to corroborate wave attenuation predictions and tunable mechanisms for low-frequency waves remains limited. This research presents the evaluation of wave attenuation in a mass-and-mass metamaterial under low-frequency excitations, incorporating a tunable mechanism based on the engagement of electromagnets. The mass-and-mass metamaterial consists of a one-dimensional diatomic chain, where varying engagements of electromagnets can modify the wave attenuation effect for different tunability purposes. The dispersive behavior and frequency bandgap of the metamaterial are derived for theoretical wave attenuation. In an analytical study, the predicted wave attenuation is examined through the time-history responses and frequency response functions of analytical metamaterial models according to different engagements of electromagnets. Then, an experimental study testing a small-scale metamaterial specimen is conducted to corroborate the wave attenuation effect and its tunability in the analytical results. The results demonstrate that intentional structural modifications via the engagement of electromagnets enable adaptive solutions over wave propagation characteristics. This investigation also contributes to the development of reconfigurable metamaterials for vibration mitigation in different wave propagation problems. Consequently, new pathways for tunable and efficient wave attenuation can be envisioned in large-scale applications, including earthquake engineering.

  PublisherDOI

• Flood Resilience Quantification Framework of Rural Communities: Case Study of Harlan County, Kentucky

  Natural Hazards Review · 2024-06-19 · 3 citations

  articleSenior author

  Communities need to prepare for anticipated hazards, adapt to varying conditions, and resist and recover rapidly from disturbances. Protecting the built environment from natural and human-made hazards and understanding the impact of these hazards helps allocate resources efficiently. Recently, an indicator-based and time-dependent approach was developed for continuously defining and measuring the functionality and disaster resilience at the community level. The PEOPLES framework consists of seven dimensions (population and demographics, environmental and ecosystem, organized governmental services, physical infrastructure, lifestyle and community competence, economic development, and social-cultural capital), and the indicator-based approach finds qualitative characteristics and transforms them into quantitative measures. The proposed framework is used to study the resilience of rural communities subject to flood hazards. Harlan County, Kentucky, in the US Appalachian region is chosen as a case study to evaluate the proposed resilience quantification framework subject to severe flooding. The results show the validity of the proposed approach as a decision-support mechanism to assess and enhance the resilience of rural communities. The novelty of this case study paper is threefold: (1) a holistic indicator-based resilience quantification framework is used, (2) the aim of this study is focused on rural communities, and (3) it offers a unified way of addressing the effects of flood hazards.

  PublisherDOI

• Robust control of friction-driven reconfigurable adaptive structures

  2024-05-09

  articleSenior author

  Traditional design methods for engineering applications aim to achieve optimal performance for specific conditions or moderate performance for a broader range of conditions. However, the optimal performance for a wide spectrum of situations can be facilitated if such systems possess reconfiguration capability. It can be illustrated in the example of structures with steerable joints, which is a popular approach in robotics. By rotating the joints to a different degree, a plethora of resulting configurations can be achieved – configurations that might be specifically suited for the required conditions. Systems based on these principles can be implemented on the macroscopic level in adaptive facades, on the mesoscopic level in mechanical metamechanisms, and at the microscopic level in microelectromechanical devices. In general, adaptive structures often require numerous actuators to facilitate a wide range of reachable configurations, leading to increasing energy demands as the system size increases. This can be seen in the case of robotics when each joint can be independently actively rotated to drive the motion corresponding to the specific degree of freedom. This paper analyzes an alternative situation, when the joins are semi-active and can exist only in either a locked or unlocked state, with only one (last joint) being actively steered. In the ideal case, the energy should be consumed only for switching between states, while maintaining the state should be free with locking achieved via switchable friction. While theoretically improving energy efficiency, such a system makes it much more challenging to control the resulting shape of the structure as compared with its counterpart with actively rotating joints. In this paper, we develop a motion planning algorithm to facilitate the achievement of the desired shape via control over the state of the joints and the position of the last link. In particular, the change of shape is performed by a sequence of single-degree- of-freedom motions determined by a motion planning algorithm based on Rapidly exploring Random Trees and sub-slider-crank systems (RRT-SC). One application of the proposed method is evaluated for reconfigurable building facades and paves the way for the next generation of structures in smart cities.

  PublisherDOI

• Reinforcement Learning for Integrated Structural Control and Health Monitoring

  Practice Periodical on Structural Design and Construction · 2024-04-17 · 6 citations

  articleSenior author

  Structural systems are vulnerable to dynamic loading and need special protection while facing extreme conditions. This study proposes an integrated structural control and health monitoring (ISCHM) system to enhance the safety and performance of building structures subjected to seismic loading. The system encompasses a semiactive controller based on reinforcement learning (RL) as well as a real-time damage identification (RTDI) system for structural health monitoring. The controller uses Deep Q-Networks (DQNs) to operate a semiactive control device and suppress the dynamic vibrations. The DQN controller was integrated with the RTDI system proposed in the preliminary phase of the project. The damage information provided by the RTDI was used to train the DQN controller and optimize the control policy in different damage conditions. The performance of the ISCHM system was evaluated through the numerical example of a building structure with variable viscous dampers installed between adjacent floors. OpenAI Gym and Keras were used to create a custom environment, define the DQN agent, simulate the interaction between the agent and environment, and train the agent while exploring the environment. The smart structure equipped with the ISCHM system was subjected to earthquake loading and the performance was compared with conventional semiactive control alternatives including skyhook and Lyapunov controllers. The results show the effectiveness of the proposed ISCHM system especially in the presence of damage. The ISCHM system can enhance the episode score by up to 58%.

  PublisherDOI

Frequent coauthors

• Alejandro Palacio-Betancur

  16 shared

• Sajad Javadinasab Hormozabad

  University of Kentucky

  9 shared

• Hojjat Adeli

  The Ohio State University

  9 shared

• Saanchi S. Kaushal

  Pennsylvania State University

  7 shared

• Rebecca Napolitano

  Pennsylvania State University

  6 shared

• Amanda Melendez

  ORCID

  5 shared

• G. R. Demarée

  University of Kentucky

  4 shared

• David B. Roueche

  Auburn University

  3 shared

Labs

• DREAM structures research groupPI

Awards & honors

• Outstanding Engineering Alumni Award
• ASAE Early Career Impact Award
• Penn State Engineering Alumni Society Awards
• Penn State Alumni Association Awards