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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 667 records · Page 37

Advanced Self-Calibrating, Self-Repairing Data Acquisition System

An improved self-calibrating and self-repairing Data Acquisition System (DAS) for use in inaccessible areas, such as onboard spacecraft, and capable of autonomously performing required system health checks, failure detection. When required, self-repair is implemented utilizing a "spare parts/tool box" system. The available number of spare components primarily depends upon each component's predicted reliability which may be determined using Mean Time Between Failures (MTBF) analysis. Failing or degrading components are electronically removed and disabled to reduce power consumption, before being electronically replaced with spare components.

Pedro J Medelius↗

Use of a Novel Rover-mounted Fluorescence Imager and Fluorescent Probes to Detect Biological Material in the Atacama Desert in Daylight

We have developed an imaging system, the Fluorescence Imager (FI), for detecting fluorescence signals from sparse microorganisms and biofilms during autonomous rover exploration. The fluorescence signals arise both from naturally occurring chromophores, such as chlorophyll of cyanobacteria and lichens, and from fluorescent probes applied to soil and rocks. Daylight imaging has been accomplished by a novel use of a high-powered flashlamp synchronized to a CCD camera. The fluorescent probes are cell permanent stains that have extremely low intrinsic fluorescence (quantum yields less than 0.01) and a large fluorescence enhancement (quantum yields greater than 0.4) when bound to the target. Each probe specifically targets either carbohydrates, proteins, nucleic acids or membrane lipids, the four classes of macromolecules found in terrestrial life. The intent of the probes is to interrogate the environment for surface and endolithic life forms.

Weinstein, S.↗

Self-Healing RF/Microwave Communications Circuits/Systems for NASA Missions - A Review

The success of current and future NASA missions relies in great part on the performance reliability and robustness of the communication circuits and systems of said missions. Some of the manifestations of reliability and robustness are comprised by properties such as graceful degradation, which provide redundancy and potentially longer life to the mission, and the ability to perform efficiently in harsh environments destinations such as Venus and the Jovian and Saturnian moons Europa and Enceladus, respectively. While several approaches have been considered or are currently underway to develop communications circuitry capable of performing in harsh environments, they lack the flexibility to enable reconfigurability to preserve functionality under adverse or contingency scenarios. This paper discusses some examples of self-healing RF/Microwave communications circuits and systems that could provide advantageous options in support of NASA missions.

Self-healing↗

MEPHESTO: Modeling Energy-Performance in Heterogeneous SoCs and Their Trade-Offs

Integrated shared memory heterogeneous architectures are pervasive because they satisfy the diverse needs of mobile, autonomous, and edge computing platforms. Although specialized processing units (PUs) that share a unified system memory improve performance and energy efficiency by reducing data movement, they also increase contention for this memory since the PUs interact with each other. Prior work has investigated performance degradation due to memory contention, but few have studied the relationship of power and energy to memory contention. Moreover, a comprehensive solution that models memory contention for kernel placement on contemporary heterogeneous systems on chip (SoCs) in response to energy and performance has been largely unaddressed.This paper presents MEPHESTO, a novel and holistic approach for managing this balance. The authors characterize applications and PUs in terms of two memory contention factors - time factors and power factors - to achieve the desired trade-off between energy and performance for collocated kernel execution on heterogeneous systems. The authors believe that this investigation is the first to combine all of these factors and present a simple knob-based approach that expresses the target trade-off. The approach is evaluated on a diverse integrated shared memory heterogeneous system with a CPU, GPU, and programmable vision accelerator. By using an empirical model for memory contention that provides up to 92% accuracy, the kernel collocation approach can provide a near-optimal ordering and placement based on the user-defined, energy-performance trade-off parameter. Moreover, the dynamic programming-based heuristics provide up to 30% better energy or 20% performance benefits when compared with the greedy approaches commonly employed by previous studies.

Alaul haque monil, Mohammad↗

Mechanisms underlying very-low-frequency RR-interval oscillations in humans

BACKGROUND: Survival of post-myocardial infarction patients is related inversely to their levels of very-low-frequency (0.003 to 0.03 Hz) RR-interval variability. The physiological basis for such oscillations is unclear. In our study, we used blocking drugs to evaluate potential contributions of sympathetic and vagal mechanisms and the renin-angiotensin-aldosterone system to very-low-frequency RR-interval variability in 10 young healthy subjects. METHODS AND RESULTS: We recorded RR intervals and arterial pressures during three separate sessions, with the patient in supine and 40 degree upright tilt positions, during 20-minute frequency (0.25 Hz) and tidal volume-controlled breathing after intravenous injections: saline (control), atenolol (0.2 mg/kg, beta-adrenergic blockade), atropine sulfate (0.04 mg/kg, parasympathetic blockade), atenolol and atropine (complete autonomic blockade), and enalaprilat (0.02 mg/kg, ACE blockade). We integrated fast Fourier transform RR-interval spectral power at very low (0.003 to 0.03 Hz), low (0.05 to 0. 15 Hz), and respiratory (0.2 to 0.3 Hz) frequencies. Beta-adrenergic blockade had no significant effect on very-low- or low-frequency RR-interval power but increased respiratory frequency power 2-fold. ACE blockade had no significant effect on low or respiratory frequency RR-interval power but modestly (approximately 21%) increased very-low-frequency power in the supine (but not upright tilt) position (P<0.05). The most profound effects were exerted by parasympathetic blockade: Atropine, given alone or with atenolol, abolished nearly all RR-interval variability and decreased very-low-frequency variability by 92%. CONCLUSIONS: Although very-low-frequency heart period rhythms are influenced by the renin-angiotensin-aldosterone system, as low and respiratory frequency RR-interval rhythms, they depend primarily on the presence of parasympathetic outflow. Therefore the prognostic value of very-low-frequency heart period oscillations may derive from the fundamental importance of parasympathetic mechanisms in cardiovascular health.

Non-NASA Center↗

CLINICAL DECISION SUPPORT: PATH TO FUNCTIONAL REQUIREMENTS

Long-duration, deep-space exploration missions present significant challenges to crew health and performance. These challenges include the individual and combined effects of microgravity, radiation exposure, isolation, limited resources (mass, volume, power, data and crew time), limited options for evacuation and those associated with delayed or constrained communications, all of which demand greater crew autonomy. Specifically, as the communication delays intensify the further we explore space, the unqualified need for Earth-independent medical operations focused on autonomous diagnosis, treatment and prevention will be key to mission continuation and success. To augment the requisite knowledge, skills and abilities (KSAs) of a time-constrained crew operating under stressful conditions, combatting fatigue, and facing a potential medical crisis, a robust clinical decision support system (CDSS) is a probable solution that would facilitate, guide and inform Earth-independent medical operations, while assisting crewmembers through various clinical presentations. The Exploration Medical Capability (ExMC) Element of the Human Research Program (HRP) is expanding the boundaries of space medical systems to advance the care of astronauts on future exploration missions beyond low Earth orbit. ExMC is actively identifying and testing next-generation medical care and crew health maintenance technologies. The Clinical Decision Support (CDS) project addresses gap Medical-701 within the Inflight Medical Conditions risk: “Enhance medical capabilities within an exploration medical system.” Though mass, volume, and power will face increasing constraints, the projected computational capabilities of spacecraft systems will increase exponentially as information technology continues to advance this decade and beyond. Hence, data, software and computational resources will play an essential and synergistic role in maintaining crew health, wellness and performance in deep space missions. The focus of the CDS project is to develop recommended requirements for an in-vehicle CDSS that acts as a ‘virtual assistant’ for delivering optimal health, performance and medical care during exploration missions. The CDSS is envisioned as an integrated, software-based tool deployed on a laptop computer or handheld device. The CDSS will assist the crew and ground support when interacting with knowledge/databases (e.g. records, pharmacy, schedule), instrumentation (e.g. imaging, physiological monitoring devices), and habitat (e.g. wellness system, task performance system) and vehicle systems (e.g. environmental system, communication system). In addition, the human interface will employ a context-based approach that accounts for the crew’s situation. Thus, extraneous and clinically/operationally non-relevant information are reduced to avoid an increase in cognitive load. The framework of an ideal spaceflight CDSS is to include core and advanced analytical features that incorporate work from collaborators yet maintain a flexible platform for integrating new technology in the future. In fiscal year 2021 (FY21), the CDS project identified requirements through two primary mechanisms: (i) the development of software implementation prototypes and (ii) the application of systems engineering processes. The CDS project developed and tested a series of increasingly complex system prototypes that were based on use cases derived from the CDSS concept of operations (ConOps). These software implementations yielded insights on CDSS functionality as well as lessons learned that provided the initial requirements for CDSS capability. By applying a systems engineering (SE) approach, medical scenarios provided in the ConOps and the use cases for software implementation underwent functional decomposition to identify CDSS functionality. Also, systems-based modeling language (SysML) tools such as activity diagrams were developed from the same ConOps and use cases to identify CDSS functionality. The lessons learned from software implementation defined both specific requirements and broad areas of requirements. Within these defined broad requirement areas, further analysis of the SE products identified specific capability that resulted in the final functional requirements. In summary, the software prototypes, functional decomposition of the ConOps and use cases, and SysML diagrams provided the basis for the CDSS requirements developed in FY21. In the upcoming year, these requirements will be refined for their final ExMC baseline review in latter FY22.

clinical decision support↗

Clinical Decision Support: Path to Functional Requirements

Long-duration, deep-space exploration missions present significant challenges to crew health and performance. These challenges include the individual and combined effects of microgravity, radiation exposure, isolation, limited resources (mass, volume, power, data and crew time), limited options for evacuation and those associated with delayed or constrained communications, all of which demand greater crew autonomy. Specifically, as the communication delays intensify the further we explore space, the unqualified need for Earth-independent medical operations focused on autonomous diagnosis, treatment and prevention will be key to mission continuation and success. To augment the requisite knowledge, skills and abilities (KSAs) of a time-constrained crew operating under stressful conditions, combatting fatigue, and facing a potential medical crisis, a robust clinical decision support system (CDSS) is a probable solution that would facilitate, guide and inform Earth-independent medical operations, while assisting crewmembers through various clinical presentations. The Exploration Medical Capability (ExMC) Element of the Human Research Program (HRP) is expanding the boundaries of space medical systems to advance the care of astronauts on future exploration missions beyond low Earth orbit. ExMC is actively identifying and testing next-generation medical care and crew health maintenance technologies. The Clinical Decision Support (CDS) project addresses gap Medical-701 within the Inflight Medical Conditions risk: “Enhance medical capabilities within an exploration medical system.” Though mass, volume, and power will face increasing constraints, the projected computational capabilities of spacecraft systems will increase exponentially as information technology continues to advance this decade and beyond. Hence, data, software and computational resources will play an essential and synergistic role in maintaining crew health, wellness and performance in deep space missions. The focus of the CDS project is to develop recommended requirements for an in-vehicle CDSS that acts as a ‘virtual assistant’ for delivering optimal health, performance and medical care during exploration missions. The CDSS is envisioned as an integrated, software-based tool deployed on a laptop computer or handheld device. The CDSS will assist the crew and ground support when interacting with knowledge/databases (e.g. records, pharmacy, schedule), instrumentation (e.g. imaging, physiological monitoring devices), and habitat (e.g. wellness system, task performance system) and vehicle systems (e.g. environmental system, communication system). In addition, the human interface will employ a context-based approach that accounts for the crew’s situation. Thus, extraneous and clinically/operationally non-relevant information are reduced to avoid an increase in cognitive load. The framework of an ideal spaceflight CDSS is to include core and advanced analytical features that incorporate work from collaborators yet maintain a flexible platform for integrating new technology in the future. In fiscal year 2021 (FY21), the CDS project identified requirements through two primary mechanisms: (i) the development of software implementation prototypes and (ii) the application of systems engineering processes. The CDS project developed and tested a series of increasingly complex system prototypes that were based on use cases derived from the CDSS concept of operations (ConOps). These software implementations yielded insights on CDSS functionality as well as lessons learned that provided the initial requirements for CDSS capability. By applying a systems engineering (SE) approach, medical scenarios provided in the ConOps and the use cases for software implementation underwent functional decomposition to identify CDSS functionality. Also, systems-based modeling language (SysML) tools such as activity diagrams were developed from the same ConOps and use cases to identify CDSS functionality. The lessons learned from software implementation defined both specific requirements and broad areas of requirements. Within these defined broad requirement areas, further analysis of the SE products identified specific capability that resulted in the final functional requirements. In summary, the software prototypes, functional decomposition of the ConOps and use cases, and SysML diagrams provided the basis for the CDSS requirements developed in FY21. In the upcoming year, these requirements will be refined for their final ExMC baseline review in latter FY22.

Clinical decision support↗

Cislunar Autonomous Positioning System Technology Operations and Navigation Experiment (CAPSTONE)

NASA has partnered with Advanced Space to develop and build the Cislunar Autonomous Positioning System Technology Operations and Navigation Experiment (CAPSTONE) mission which will serve as a pathfinder for Near Rectilinear Halo Orbit (NHRO) operations around the Moon. The NHRO, (Perilune = 3,200 km; Apolune = 70,000 km) will be the intended orbit for the NASA’s Artemis Gateway lunar orbital platform. The CAPSTONE mission will validate simulations and confirm operational planning for Gateway while also validating performance of navigation and station-keeping requirements for the Power and Propulsion Element. Thus, this mission will provide operational experience to NASA, commercial, and international missions for operations in a demanding orbital regime. The baseline for CAPSTONE is to fly a 12U cubesat developed, integrated, and tested by Tyvak Nanosatellite Systems carrying a payload communications system capable of cross-link ranging with the Lunar Reconnaissance Orbiter (LRO), a dedicated payload flight computer for software demonstration, and a camera. The launch, coordinated by NASA Launch Services Program, will be provided by a Rocket Lab launch vehicle utilizing their new Proton upper stage to deploy the CAPSTONE spacecraft into the lunar orbit. The CAPSTONE mission is targeting a launch no earlier than September 23, 2021. Upon launch, the spacecraft will traverse a highly efficient transfer taking approximately three months to enter a primary demonstration phase in an NRHO for six months followed by a twelve month technology enhancement operations phase. The CAPSTONE Project is lead by Advanced Space, LLC of Boulder Colorado. Spacecraft development and mission operations will be conducted by Tyvak Nanosatellite Systems of Irvine, California. Noted objectives for the CAPSTONE mission will be to demonstrate the accessibility of NHROs, validate key operational concepts in the NHRO environment, lay a foundation for commercial support of future lunar operations and accelerate the availability of peer-to-peer navigation capabilities provided by the Cislunar Autonomous Positioning System (CAPS). The CAPSTONE mission is funded through NASA's Small Spacecraft Technology Program (SSTP), which is one of several programs in NASA’s Space Technology Mission Directorate. SSTP is chartered to develop and demonstrate technologies to enhance and expand the capabilities of small spacecraft with a particular focus on enabling new mission architectures through the use of small spacecraft, expanding the reach of small spacecraft to new destinations, and augmenting future missions with supporting small spacecraft. The launch for the CAPSTONE Mission is provided by Human Exploration & Operations Missions Directorate Advanced Exploration Systems Division. Coordination and Acquisition of the Launch is managed by NASA’s Launch Services Program. The CAPSTONE Mission and project status will be presented.

CAPSTONE↗

Cislunar Autonomous Positioning System Technology Operations and Navigation Experiment (CAPSTONE) Mission

NASA has partnered with Advanced Space to develop and build the Cislunar Autonomous Positioning System Technology Operations and Navigation Experiment (CAPSTONE) mission which will serve as a pathfinder for Near Rectilinear Halo Orbit (NHRO) operations around the Moon. The NHRO, (Perilune = 3,200 km; Apolune = 70,000 km) will be the intended orbit for the NASA’s Artemis Gateway lunar orbital platform. The CAPSTONE mission will validate simulations and confirm operational planning for Gateway while also validating performance of navigation and station-keeping requirements for the Power and Propulsion Element. Thus, this mission will provide operational experience to NASA, commercial, and international missions for operations in a demanding orbital regime. The baseline for CAPSTONE is to fly a 12U cubesat developed, integrated, and tested by Tyvak Nanosatellite Systems carrying a payload communications system capable of cross-link ranging with the Lunar Reconnaissance Orbiter (LRO), a dedicated payload flight computer for software demonstration, and a camera. The launch, coordinated by NASA Launch Services Program, will be provided by a Rocket Lab launch vehicle utilizing their new Proton upper stage to deploy the CAPSTONE spacecraft into the lunar orbit. The CAPSTONE mission is targeting a launch no earlier than September 23, 2021. Upon launch, the spacecraft will traverse a highly efficient transfer taking approximately three months to enter a primary demonstration phase in an NRHO for six months followed by a twelve month technology enhancement operations phase. The CAPSTONE Project is lead by Advanced Space, LLC of Boulder Colorado. Spacecraft development and mission operations will be conducted by Tyvak Nanosatellite Systems of Irvine, California. Noted objectives for the CAPSTONE mission will be to demonstrate the accessibility of NHROs, validate key operational concepts in the NHRO environment, lay a foundation for commercial support of future lunar operations and accelerate the availability of peer-to-peer navigation capabilities provided by the Cislunar Autonomous Positioning System (CAPS). The CAPSTONE mission is funded through NASA's Small Spacecraft Technology Program (SSTP), which is one of several programs in NASA’s Space Technology Mission Directorate. SSTP is chartered to develop and demonstrate technologies to enhance and expand the capabilities of small spacecraft with a particular focus on enabling new mission architectures through the use of small spacecraft, expanding the reach of small spacecraft to new destinations, and augmenting future missions with supporting small spacecraft. The launch for the CAPSTONE Mission is provided by Human Exploration & Operations Missions Directorate Advanced Exploration Systems Division. Coordination and Acquisition of the Launch is managed by NASA’s Launch Services Program. The CAPSTONE Mission and project status will be presented.

CAPSTONE↗

Forecasting of in situ electron energy loss spectroscopy

Abstract Forecasting models are a central part of many control systems, where high-consequence decisions must be made on long latency control variables. These models are particularly relevant for emerging artificial intelligence (AI)-guided instrumentation, in which prescriptive knowledge is needed to guide autonomous decision-making. Here we describe the implementation of a long short-term memory model (LSTM) for forecasting in situ electron energy loss spectroscopy (EELS) data, one of the richest analytical probes of materials and chemical systems. We describe key considerations for data collection, preprocessing, training, validation, and benchmarking, showing how this approach can yield powerful predictive insight into order-disorder phase transitions. Finally, we comment on how such a model may integrate with emerging AI-guided instrumentation for powerful high-speed experimentation.

36 MATERIALS SCIENCE↗

Security Evaluation of Two Intrusion Detection Systems in Smart Grid SCADA Environment

The increased complexity and interconnectivity of SCADA infrastructure in the power system have exposed it to the multitude of vulnerabilities. There is a growing emphasis towards developing an efficient intrusion detection system (IDS) to strengthen the security of the SCADA control system. This is a research-in-progress paper which presents the application of two anomaly-based intrusion detection systems (AIDS) in detecting the stealthy cyber-attack on the SCADA control system. We have applied the IDS tools Snort and Bro, in designing the IDS and later, compared their performances in terms of detection rate and latency in the alert packets with a motive of selecting better IDS for the SCADA security. Specifically, the timing-based rule is applied to identify the malicious packets based on the high temporal frequency in the network traffic. For the case study, we have implemented the SCADA based protection scheme which performs an autonomous protection to mitigate the system disturbances. We first implemented the stealthy cyber-attack which compromised the SCADA controller followed by data integrity attack on the system generator. Next, we perform the impact analysis during the attack followed by performance evaluation of IDS tools. Our experimental results show that the IDS tools are efficient in detecting cyber-attacks within an acceptable time frame for different sizes of network packets.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DINGO: Digital assistant to grid operators for resilience management of power distribution system

With increasing adverse weather events and disasters, enabling resiliency of the power distribution system (PDS) is becoming increasingly important. Here in this work, resiliency is defined as the systems ability to keep supplying critical loads even with multiple contingencies. Resiliency may depend on: (a) advanced tools to assist operators in situational awareness and decision making with the increasing volume of data generated by the PDS, (b) visualization and ease of interaction with system resources and information, especially during extreme events and resulting human operator stress, and (c) flexible resources and autonomous control. Operators and support engineers need to interact with the system for key information and take action under stress, given the requirement for decisions in a short time. Integrated technological solutions are prevailing steps to support the most appropriate decision during critical times to serve essential loads. In order to meet the required goals, a Real-time Resiliency Monitoring and Operational Decision Support (RT-RMOD) tool have been developed. It supports various functionalities, including real-time monitoring, resilience assessment, and proactive decision support. However, this work makes advanced feature additions to the tool by developing data-enabled resilience management algorithms for (i) outage detection and localization, (ii) Resiliency-metric driven restoration and reconfiguration, and (iii) NLP based digital assistant for operators called DINGO (DIgital assistaNt to Grid Operators) to interact with Advanced Distribution Management System (ADMS) and RT-RMOD. The developed algorithm was validated for multiple cases of weather events using a real-world, off-grid microgrid system modeled in a real-time simulator, sensor data, and software tools.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Autonomous sensor fish to support advanced hydropower development

An improved sensor fish with robust design and enhanced measurement capabilities. This sensor fish contains sensors for acceleration, rotation, magnetic field intensity, pressure, and temperature. A low-power microcontroller collects data from the sensors and stores up to 5 minutes of data on a non-volatile flash memory. A rechargeable battery supplies power to the sensor fish. A recovery system helps locating sensor fish. The package, when ready for use is nearly neutrally buoyant and thus mimics the behavior of an actual fish.

Deng, Daniel Z.↗

Autonomous sensor fish to support advanced hydropower development

An improved sensor fish with robust design and enhanced measurement capabilities. This sensor fish contains sensors for acceleration, rotation, magnetic field intensity, pressure, and temperature. A low-power microcontroller collects data from the sensors and stores up to 5 minutes of data on a non-volatile flash memory. A rechargeable battery supplies power to the sensor fish. A recovery system helps locating sensor fish. The package, when ready for use is nearly neutrally buoyant and thus mimics the behavior of an actual fish.

Deng, Z. Daniel↗

NASA's Space Launch System: Moving Toward the Launch Pad

The National Aeronautics and Space Administration's (NASA's) Space Launch System (SLS) Program, managed at the Marshall Space Flight Center, is making progress toward delivering a new capability for human space flight and scientific missions beyond Earth orbit. Developed with the goals of safety, affordability, and sustainability in mind, the SLS rocket will launch the Orion Multi-Purpose Crew Vehicle (MPCV), equipment, supplies, and major science missions for exploration and discovery. Supporting Orion's first autonomous flight to lunar orbit and back in 2017 and its first crewed flight in 2021, the SLS will evolve into the most powerful launch vehicle ever flown, via an upgrade approach that will provide building blocks for future space exploration and development. NASA is working to develop this new capability in an austere economic climate, a fact which has inspired the SLS team to find innovative solutions to the challenges of designing, developing, fielding, and operating the largest rocket in history. This paper will summarize the planned capabilities of the vehicle, the progress the SLS program has made in the 2 years since the Agency formally announced its architecture in September 2011, and the path the program is following to reach the launch pad in 2017 and then to evolve the 70 metric ton (t) initial lift capability to 130-t lift capability. The paper will explain how, to meet the challenge of a flat funding curve, an architecture was chosen which combines the use and enhancement of legacy systems and technology with strategic new development projects that will evolve the capabilities of the launch vehicle. This approach reduces the time and cost of delivering the initial 70 t Block 1 vehicle, and reduces the number of parallel development investments required to deliver the evolved version of the vehicle. The paper will outline the milestones the program has already reached, from developmental milestones such as the manufacture of the first flight hardware and the record-breaking testing of the J-2X engine, to life-cycle milestones such as the vehicle's Preliminary Design Review. The paper will also discuss the remaining challenges in both delivering the 70 t vehicle and in evolving its capabilities to the 130 t vehicle, and how the program plans to accomplish these goals. As this paper will explain, SLS is making measurable progress toward becoming a global infrastructure asset for robotic and human scouts of all nations by harnessing business and technological innovations to deliver sustainable solutions for space exploration

Creech, Stephen D.↗

Designing, synthesizing, and modeling active fluids

We review recent advances in the design, synthesis, and modeling of active fluids. Active fluids have been at the center of many technological innovations and theoretical advances over the past two decades. Research on this new class of fluids has been inspired by the fascinating and remarkably efficient strategies that biological systems employ, leading to the development of biomimetic nano- and micro-machines and swimmers. The review encompasses active fluids on both the nano- and micro-scale. We start with examples of biological active systems before we discuss how experimentalists leverage novel propulsion mechanisms to power nano- and micro-machines. Furthermore, we then examine how the study of these far-from-equilibrium systems has prompted the development of new simulation methods and theoretical models in nonequilibrium physics to account for their mechanical, thermodynamic, and emergent properties. Recent advances in the field have paved the way for the design, synthesis, and modeling of autonomous systems at the nano- and micro-scale and opened the door to the development of soft matter robotics.

36 MATERIALS SCIENCE↗

Operational Resilience of Nuclear-Renewable Integrated-Energy Microgrids

The increasing prevalence and severity of wildfires, severe storms, and cyberattacks is driving the introduction of numerous microgrids to improve resilience locally. While distributed energy resources (DERs), such as small-scale wind and solar photovoltaics with storage, will be major components in future microgrids, today, the majority of microgrids are backed up with fossil-fuel-based generators. Small modular reactors (SMRs) can form synergistic mix with DERs due to their ability to provide baseload and flexible power. The heat produced by SMRs can also fulfill the heating needs of microgrid consumers. This paper discusses an operational scheme based on distributed control of flexible power assets to strengthen the operational resilience of SMR-DER integrated-energy microgrids. A framework is developed to assess the operational resilience of SMR-DER microgrids in terms of system adaptive real-power capacity quantified as a response area metric (RAM). Month-long simulation results are shown with a microgrid developed in a modified Institute of Electrical and Electronics Engineers (IEEE)-30 bus system. The RAM values calculated along the operational simulation reflect the system resilience in real time and can be used to supervise the microgrid operation and reactor’s autonomous control.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗