Space vehicles and habitats are complex systems with tightly coupled interdependencies. They operate under extreme, unforgiving conditions that challenge system performance and crew safety. Effective health management in such systems demands strong architectural and situational knowledge, leading to heavy reliance on ground control. As missions venture deeper into space, growing communication delays make such support impractical, prompting a paradigm shift toward greater on-board autonomy. However, computational constraints limit the migration of all health management components to the habitat. Running high-fidelity fault detection and diagnosis modules on the ground can conserve on-board resources but introduces delays in decision-making. This latency increases the need for effective decision-making policies, which may require interrupting agents to enable timely responses to higher-priority situations. In this paper, we study how communication delays and agent interruptibility impact decision-making in a habitat system, using the Human-centered Autonomous Resilient Space Habitat (HARSH), a reconfigurable cyber-physical testbed. A series of experiments is conducted to evaluate different design configurations under single and compound disruption scenarios. The ability of each configuration to respond and recover from faults is assessed using resilience metrics. Findings from the experiments inform recommendations to advance autonomous decision-making policies and enhance system resilience in future deep space habitats.

Real-time hybrid simulation (RTHS) is an important tool in the design and testing of civil and mechanical structures when engineers and scientists wish to understand the performance of an isolated component within the context of a larger structure. Performing full-scale physical experimentation with a large structure can be prohibitively expensive. Instead, a hybrid testing framework connects part of a physical structure within a closed loop (through sensors and actuators) to a numerical simulation of the rest of the structure. If we wish to understand the dynamic response of the combined structure, this testing must be done in real-time, which significantly restricts both the size of the simulation and the rate at which it can be conducted.

Our deteriorating civil infrastructure faces the critical challenge of long-term structural health monitoring for damage detection and localization. In contrast to existing research that often separates the designs of wireless sensor networks and structural engineering algorithms, this paper proposes a cyber-physical codesign approach to structural health monitoring based on wireless sensor networks. Our approach closely integrates 1) flexibility-based damage localization methods that allow a tradeoff between the number of sensors and the resolution of damage localization, and 2) an energy-efficient, multilevel computing architecture specifically designed to leverage the multiresolution feature of the flexibility-based approach. The proposed approach has been implemented on the Intel Imote2 platform. Experiments on a simulated truss structure and a real full-scale truss structure demonstrate the system's efficacy in damage localization and energy efficiency.

Real-time hybrid testing of civil structures represents agrand challenge in the emerging area of cyber-physical systems. Hybrid testing improves significantly on either purely numerical or purely empirical approaches by integrating physical structural components and computational models. Actuator dynamics, complex interactions among computers and physical components, and computation and communication delays all hamper the ability to conduct accurate tests. To address these challenges, this paper presents initial work towards a Cyber-physical Instrument for Real-time hybrid Structural Testing (CIRST). CIRST aims to provide two salient features: a highly configurable architecture for integrating computers and physical components; and system support for real-time operations in distributed hybrid testing. This paper presents the motivation of the CIRST architectureand preliminary test results from a proof-of-concept implementation that integrates a simple structural element and simulation model. CIRST will have broad impacts on thefields of both civil engineering and real-time computing.It will enable high-fidelity real-time hybrid testing of awide range of civil infrastructures, and will also providea high-impact cyber-physical application for the study andevaluation of real-time middleware.

Wireless sensor networks (WSNs) have become an increasingly compelling platform for Structural Health Monitoring (SHM) applications, since they can be installed relatively inexpensively onto existing infrastructure. Existing approaches to SHM in WSNs typically address computing system issues or structural engineering techniques, but not both in conjunction. In this paper, we propose a holistic approach to SHM that integrates a decentralized computing architecture with the Damage Localization Assurance Criterion algorithm. In contrast to centralized approaches that require transporting large amounts of sensor data to a base station, our system pushes the execution of portions of the damage localization algorithm onto the sensor nodes, reducing communication costs by an order of magnitude in exchange for moderate additional processing on each sensor. We present a prototype implementation of this system built using the TinyOS operating system running on the Intel Imote2 sensor network platform. Experiments conducted using two different physical structures demonstrate our system's ability to accurately localize structural damage. We also demonstrate that our decentralized approach reduces latency by 64.8% and energy consumption by 69.5% compared to a typical centralized solution, achieving a projected lifetime of 191 days using three standard AAA batteries. Our work demonstrates the advantages of a holistic approach to cyber-physical systems that closely integrates the design of computing systems and physical engineering techniques.