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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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All sources NASA NTRS DOE OSTI

DOE OSTI2025

Scalable Unit Commitment with Security Constrained AC Power Flow via ADMM and Hybrid Modeling Strategies

This research introduces a more efficient way to optimize power grid operations, breaking the problem into manageable steps and using advanced mathematical techniques to speed up calculations. By incorporating smart heuristics, improved preprocessing, and contingency analysis, the approach allows operators to make better decisions faster. These innovations enhance our understanding of how to optimize energy generation, making it possible to anticipate failures before they happen, reduce system costs, and improve overall grid performance. Ultimately, this research helps bridge the gap between theoretical models and real-world applications, paving the way for a smarter, more resilient power grid. This research directly benefits the public by making electricity more affordable, reliable, and sustainable. By improving how power grids schedule and distribute electricity, the project helps energy providers reduce operational costs, which can lead to lower electricity prices for consumers. Additionally, the ability to predict and prevent power system failures enhances grid reliability, reducing the likelihood of blackouts that can disrupt homes, businesses, and critical infrastructure such as hospitals. From an environmental perspective, optimizing power generation reduces energy waste and lowers carbon emissions, contributing to cleaner air and a more sustainable energy system. Furthermore, with extreme weather events becoming more frequent, these advancements make the power grid more resilient, ensuring communities are better prepared for emergencies and natural disasters. By strengthening the nation's energy infrastructure, this research plays a crucial role in improving economic stability, public safety, and environmental sustainability.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2021

Stress-Induced Changes in Alternative Splicing Landscape in Rice: Functional Significance of Splice Isoforms in Stress Tolerance

Improvements in yield and quality of rice are crucial for global food security. However, global rice production is substantially hindered by various biotic and abiotic stresses. Making further improvements in rice yield is a major challenge to the rice research community, which can be accomplished through developing abiotic stress-resilient rice varieties and engineering durable agrochemical-independent pathogen resistance in high-yielding elite rice varieties. This, in turn, needs increased understanding of the mechanisms by which stresses affect rice growth and development. Alternative splicing (AS), a post-transcriptional gene regulatory mechanism, allows rapid changes in the transcriptome and can generate novel regulatory mechanisms to confer plasticity to plant growth and development. Mounting evidence indicates that AS has a prominent role in regulating rice growth and development under stress conditions. Several regulatory and structural genes and splicing factors of rice undergo different types of stress-induced AS events, and the functional significance of some of them in stress tolerance has been defined. Both rice and its pathogens use this complex regulatory mechanism to devise strategies against each other. This review covers the current understanding and evidence for the involvement of AS in biotic and abiotic stress-responsive genes, and its relevance to rice growth and development. Furthermore, we discuss implications of AS for the virulence of different rice pathogens and highlight the areas of further research and potential future avenues to develop climate-smart and disease-resistant rice varieties.

59 BASIC BIOLOGICAL SCIENCES↗

NASA NTRSDate not supplied

A 3D Simulation Platform for Decentralized Decision-Making in Advanced Air Mobility

This paper presents a general purpose, plug-and-play simulation platform for the use of future aviation stakeholders, such as urban airspace planners, air vehicle operators, ground operation managers, air traffic controllers and aviation researchers. The presented simulator platform is envisioned to serve as a toolkit to visualize, evaluate, and configure future advanced air mobility (AAM) operations. Highlighting features of this toolkit include a modular architecture that allows multiple smart unmanned aerial systems (UASs) to remotely connect to the simulation server and participate in decentralized decision-making scenario simulations. As an example of the decentralized decision-making scenario, an inter-agent negotiation-based conflict resolution use case is considered in this paper, where the UASs leverage the on-board/on-the-edge artificial intelligence (AI) capability to continually build situational awareness, and use this information to predict future conflicts and resolve them through machine-to-machine negotiation. As such operations are non-existent at scale currently, the presented simulation platform offers a viable and cost-effective alternative for assessing the efficacy of AAM research outcomes and challenges in future shared airspace usage. The simulation platform allows plug-n-play connectivity with AI and non-AI compute modules representing individual UAS’s flight control. Each module can interact with the simulation platform independently to communicate current and desired future states, situational awareness, and conflict resolution utilization costs for inter-agent negotiation. The simulation environment orchestrates realistic operational scenarios with spatiotemporal details, dynamic events, tactical conflict-resolution methods, interfaces for customizing air traffic control parameters, and information exchange uncertainties. In the future, this can serve as a community focused cloud simulation platform, incorporating multi-stakeholder airspace constraints from regulatory, government, city, and local agencies.

Aditya N Das↗

NASA NTRS2022

A 3D Simulation Platform for Decentralized Decision-Making in Advanced Air Mobility

Aditya Das↗

NASA NTRS2009

Integrated System Health Management: Foundational Concepts, Approach, and Implementation

A sound basis to guide the community in the conception and implementation of ISHM (Integrated System Health Management) capability in operational systems was provided. The concept of "ISHM Model of a System" and a related architecture defined as a unique Data, Information, and Knowledge (DIaK) architecture were described. The ISHM architecture is independent of the typical system architecture, which is based on grouping physical elements that are assembled to make up a subsystem, and subsystems combine to form systems, etc. It was emphasized that ISHM capability needs to be implemented first at a low functional capability level (FCL), or limited ability to detect anomalies, diagnose, determine consequences, etc. As algorithms and tools to augment or improve the FCL are identified, they should be incorporated into the system. This means that the architecture, DIaK management, and software, must be modular and standards-based, in order to enable systematic augmentation of FCL (no ad-hoc modifications). A set of technologies (and tools) needed to implement ISHM were described. One essential tool is a software environment to create the ISHM Model. The software environment encapsulates DIaK, and an infrastructure to focus DIaK on determining health (detect anomalies, determine causes, determine effects, and provide integrated awareness of the system to the operator). The environment includes gateways to communicate in accordance to standards, specially the IEEE 1451.1 Standard for Smart Sensors and Actuators.

Figueroa, Fernando↗

DOE OSTI2022

Valuing Resilience Benefits of Microgrids for an Interconnected Island Distribution System

Extreme climate-driven events such as hurricanes, floods, and wildfires are becoming more intense in areas exposed to these threats, requiring approaches to improve the resilience of the electrical infrastructure serving these communities. Long-duration outages caused by such high impact events propagate to economic, health, and social consequences for communities. As essential service providers, electric utilities are mandated to provide safe, economical and reliable electricity to their customers. The public is becoming less tolerant to these more frequent disruptions, especially in view of technological advances that are intended to improve power quality, reliability and resilience. One promising solution is state-of-the-art microgrids and the advanced controls employed therein. This paper presents and demonstrates an approach to technoeconomic analysis that can be used to value the avoided economic consequences of grid resilience investments, as applied to the islands of Vieques and Culebra in Puerto Rico. This valuation methodology can support policies to incorporate resilience value into any investment decision-making process, especially those which serve the public interest.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2020

Measuring Cities with Software-Defined Sensors

The Chicago Array of Things (AoT) project, funded by the US National Science Foundation, created an experimental, urban-scale measurement capability to support diverse scientific studies. Initially conceived as a traditional sensor network, collaborations with many science communities guided the project to design a system that is remotely programmable to implement Artificial Intelligence (AI) within the devices-at the “edge” of the network-as a means for measuring urban factors that heretofore had only been possible with human observers, such as human behavior including social interaction. The concept of “software-defined sensors” emerged from these design discussions, opening new possibilities, such as stronger privacy protections and autonomous, adaptive measurements triggered by events or conditions. We provide examples of current and planned social and behavioral science investigations uniquely enabled by software-defined sensors as part of the SAGE project, an expanded follow-on effort that includes AoT.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2021

Active microbial biomass decreases, but microbial growth potential remains similar across soil depth profiles under deeply-vs. shallow-rooted plants

Climate-smart land management practices that replace shallow-rooted annual crop systems with deeply-rooted perennial plants can contribute to soil carbon sequestration. However, deep soil carbon accrual may be influenced by active microbial biomass and their capacity to assimilate fresh carbon at depth. Incorporating active microbial biomass, dormancy, and growth in microbially-explicit models can improve our ability to predict soil's capacity to store carbon. But, so far, the microbial parameters that are needed for such modeling are poorly constrained, especially in deep soil layers. Here, we used a lab incubation experiment and growth kinetics model to estimate how microbial parameters vary along 240 cm of soil depth in profiles under shallow- (soy) and deeply-rooted (switchgrass) plants 11 years after plant cover conversion. We also assessed resource origin and availability (total organic carbon, 14 C, extractable organic carbon, specific UV absorbance of K 2 SO 4 extractable organic C, total nitrogen, total dissolved nitrogen) along the soil profiles to examine associations between soil chemical and biological parameters. Even though root biomass was greater and rooting depth was deeper under switchgrass than soy, resource availability and microbial growth parameters were generally similar between vegetation types. Instead, depth significantly influenced soil chemical and biological parameters. For example, resource availability and total and relative active microbial biomass decreased with soil depth. Decreases in the relative active microbial biomass coincided with increased lag time (response time to external carbon inputs) along the soil profiles. Even at a depth of 210–240 cm, microbial communities were activated to grow by added resources within a day. Maximum specific growth rate decreased to a depth of 90 cm and then remained consistent in deeper layers. Our findings show that >10 years of vegetation and rooting depth changes may not be long enough to alter microbial growth parameters, and suggest that at least a portion of the microbial community in deep soils can grow rapidly in response to added resources. Our study determined microbial growth parameters that can be used in microbially-explicit models to simulate carbon dynamics in deep soil layers.

14C↗

DOE OSTI2023

High-dimensional data analytics in civil engineering: A review on matrix and tensor decomposition

Recent developments in sensing and monitoring techniques have led to the generation of high-dimensional data in the field of civil engineering. High-dimensional data analytics methods have thus been developed to interpret such complex data. Among the different high-dimensional data analytics techniques, matrix and tensor decomposition methods have acquired a notable interest in the civil engineering community over the past decade. Due to their unique ability to deal with highly redundant and correlated data, these methods are establishing themselves as promising and efficient tools to analyze high-dimensional data in the civil engineering arena. In this paper, high-dimensional data is referred to as a data set in which the number of features is comparable or larger than the number of observations. This review paper aims to summarize the applications of matrix and tensor decomposition methods in civil engineering over the last decade. The survey begins with a general overview of matrix and tensor decomposition followed by highlighting their significance in the field. Afterward, various applications of these high-dimensional data analytics methods in civil engineering are presented, while the advantages offered by these methods are discussed. Lastly, challenges and potential research avenues for employing matrix and tensor decomposition and future emerging trends for their novel use are highlighted.

42 ENGINEERING↗

DOE OSTI2024

Deep Generative Models in Energy System Applications: Review, Challenges, and Future Directions

In recent years, with the advent of mature machine learning products like ChatGPT, Stable Diffusion, and Sora, the world has witnessed tremendous changes driven by the rapid development of generative artificial intelligence (GAI). Beyond applications in text, speech, image, and video creation, deep generative models (DGMs) underpinning these cutting-edge technologies have also been employed by domain researchers to address scientific and engineering challenges. This paper aims to fill a gap in the research community by providing a systematic review of how DGMs have been utilized in energy system applications. After introducing four most popular DGMs, we review and categorize 196 research articles into five focus areas: data generation, forecasting, situational awareness, modeling, and optimal decision-making. Through this classification, we uncover trends in how DGMs are employed for each type of problem, highlighting GAI techniques that contribute to breakthroughs over traditional methods. We discuss limitations in existing literature, engineering challenges, and propose future directions, all tailored to the unique nature of problems in energy system engineering. Our goal is to offer insights for energy system domain researchers, providing a comprehensive view of existing studies and potential future opportunities.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2021

Integrated Models for Electrical Distribution Network Planning and District-Scale Building Energy Use

The increase of greenhouse emissions caused by a rise in global energy consumption is pushing the scientific community to develop tools that address key environmental, techno-economic and social issues. One specific area of focus is to create tools that enable the design of high-performance energy districts, including grid-interactive efficient buildings and electrical distribution infrastructure. This paper outlines the approach of integrating a synthetic distribution network tool (RNM-US) with URBANopt™, a modular and customizable software development kit for thermal and electrical modelling of buildings and energy systems at a district scale. First, we describe the algorithms implemented to integrate RNM-US with URBANopt to automatically generate the distribution network for the district considered. Following, we present a case study for the potential uses of the RNM-US integrations with URBANopt, highlighting the capabilities for economic and technical analysis of the distribution network built in relation to the electricity needs of the modelled buildings.

30 DIRECT ENERGY CONVERSION↗

DOE OSTI2023

Coexistence between similar invaders: The case of two cosmopolitan exotic insects

Biological invasions are usually examined in the context of their impacts on native species. However, few studies have examined the dynamics between invaders when multiple exotic species successfully coexist in a novel environment. Yet, long-term coexistence of now established exotic species has been observed in North American lady beetle communities. Exotic lady beetles Harmonia axyridis and Coccinella septempunctata were introduced for biological control in agricultural systems and have since become dominant species within these communities. In this study, we investigated coexistence via spatial and temporal niche partitioning among H. axyridis and C. septempunctata using a 31-year data set from southwestern Michigan, USA. We found evidence of long-term coexistence through a combination of small-scale environmental, habitat, and seasonal mechanisms. Across years, H. axyridis and C. septempunctata experienced patterns of cyclical dominance likely related to yearly variation in temperature and precipitation. Within years, populations of C. septempunctata peaked early in the growing season at 550 degree days, while H. axyridis populations grew in the season until 1250 degree days and continued to have high activity after this point. C. septempunctata was generally most abundant in herbaceous crops, whereas H. axyridis did not display strong habitat preferences. These findings suggest that within this region H. axyridis has broader habitat and abiotic environmental preferences, whereas C. septempunctata thrives under more specific ecological conditions. These ecological differences have contributed to the continued coexistence of these two invaders. Understanding the mechanisms that allow for the coexistence of dominant exotic species contributes to native biodiversity conservation management of invaded ecosystems.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2025

The Implications of Advanced Manufacturing in a Connected Economy Moving Towards a Smart, Sustainable, and Productive Economy

This report intends to provide a comprehensive overview of information and communications technologies (ICT), which play increasingly vital roles in the United States (U.S.) and global economies and continue to evolve rapidly as both technological capabilities and needs grow in tandem. To underscore the importance of the sector, the U.S. Congress recently passed a $\$$20–$\$$50 billion federal program Creating Helpful Incentives to Produce Semiconductors Act (CHIPS Act) to spur the competitiveness of the U.S. semiconductor industry and encourage U.S. investment, often complemented by state-level incentives (Kessler 2022).

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2021

Pricing and Energy Trading in Peer-to-Peer Zero Marginal-Cost Microgrids

Efforts to utilize 100% renewable energy in community microgrids require new approaches to energy markets and transactions to efficiently address periods of scarce energy supply. In this paper we contribute to the promising approach of peer-to-peer (P2P) energy trading in two main ways: analysis of a centralized, welfare-maximizing economic dispatch that characterizes optimal price and allocations, and a novel P2P system for negotiating energy trades that yields physically feasible and at least weakly Pareto-optimal outcomes. Our main results are 1) that optimal pricing is insufficient to induce agents with batteries to take optimal actions, 2) a novel P2P algorithm to addresses this while keeping private information, 3) a formal proof that this algorithm converges to the centralized solution in the case of two agents negotiating for a single period, and 4) numerical simulations of the P2P algorithm performance with up to 10 agents and 24 periods that show it converges on average to total welfare within 0.1% of the social optimum in on the order of 10s to 100s of iterations, increasing with the number of agents, time periods, and total storage capacity.

batteries↗

NASA NTRS2006

Providing Housing, Food and Medical Support for 25,000 Katrina Evacuees with 12 Hours Notice: The Harris County Medical Support of the Superdome Evacuees

Hurricane Katrina was responsible for trapping 25,000 people in the New Orleans Superdome and isolating many others throughout Louisiana and Mississippi. The transport of these evacuees to the Reliant Park (Houston, Texas) used 500 buses each containing about 55 people. Processing the arriving evacuees included addressing their health status and medical needs as follows: an initial triage at disembarkation, a secondary triage in the Reliant Astrodome and Center, and definitive clinical care in the Reliant Arena "Katrina" Clinic. Baylor College of Medicine (BCM) physicians boarded buses and identified the sickest for emergency transport to Harris County Hospital District (HCHD) hospitals. BCM departments represented included pediatrics, family and community medicine, internal medicine, radiology, obstetrics and gynecology, orthopedics, surgery, and psychiatry. Astrodome and Center triage was managed by BCM physicians and staffed by HCHD Nurses and volunteers from Texas and beyond. The Reliant Astrodome, Center and Arena reached peak headcounts of 15,000,4500, and 2500, respectively Most evacuees visiting the triage sites in the Astrodome and Center were treated using "over-the-counter" medications with the remaining being transported to the "Katrina" clinic. The clinic was equipped with a lab, pharmacy, digital X-ray, and ultrasound machines in addition to electronic patient records created using 80 computer terminals. The Katrina clinic saw more than 15,000 patients during 15 days of operations (2,000 on the first full day), administered 10,000 tetanus shots, and filled thousands of prescriptions. At the peak of operations, the clinic saw 150 patients/hour with 25 physicians scheduled for each 12-hour shift. Approximately 900 people were transported to hospital emergency rooms. Within 3 weeks of arriving at the Reliant Park facilities, more than 90% of the families found permanent housing, enrolled children in schools, and found work. Using data obtained from manual and electronic medical records, this presentation will document the major milestones and lessons learned from this extraordinary project to help the Katrina evacuees.

Hamilton, Douglas↗

DOE OSTI2020

Safe and Private Forward-trading Platform for Transactive Microgrids

Power grids are evolving at an unprecedented pace due to the rapid growth of distributed energy resources (DER) in communities. These resources are very different from traditional power sources, as they are located closer to loads and thus can significantly reduce transmission losses and carbon emissions. However, their intermittent and variable nature often results in spikes in the overall demand on distribution system operators (DSO). To manage these challenges, there has been a surge of interest in building decentralized control schemes, where a pool of DERs combined with energy storage devices can exchange energy locally to smooth fluctuations in net demand. Building a decentralized market for transactive microgrids is challenging, because even though a decentralized system provides resilience, it also must satisfy requirements such as privacy, efficiency, safety, and security, which are often in conflict with each other. As such, existing implementations of decentralized markets often focus on resilience and safety but compromise on privacy. In this article, we describe our platform, called TRANSAX, which enables participants to trade in an energy futures market, which improves efficiency by finding feasible matches for energy trades, enabling DSOs to plan their energy needs better. TRANSAX provides privacy to participants by anonymizing their trading activity using a distributed mixing service, while also enforcing constraints that limit trading activity based on safety requirements, such as keeping planned energy flow below line capacity. We show that TRANSAX can satisfy the seemingly conflicting requirements of efficiency, safety, and privacy. We also provide an analysis of how much trading efficiency is lost. Trading efficiency is improved through the problem formulation, which accounts for temporal flexibility, and system efficiency is improved using a hybrid-solver architecture. Lastly, we describe a testbed to run experiments and demonstrate its performance using simulation results.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

NASA NTRSDate not supplied

Monitoring Human Performance on Future Deep Space Missions Abstract

NASA and the commercial spacecraft community are working diligently to put the first woman on the moon in the 2024 timeframe. At the same time, NASA researchers are thinking about how to solve the even larger challenges that future deep space missions will bring. Space travel itself is difficult, but astronauts on deep space missions will face obstacles and unknowns never before experienced. In addition to the altered gravity and hostile/closed environment of a spacecraft, deep space crews will face increased radiation, isolation, and distance from Earth. During Extravehicular Activity (EVA, or “spacewalk”) operations, crew will experience increased physical and cognitive workload due to extended types, frequencies and durations of tasks performed on exploration missions in partial gravity environments. All of these stressors will impact crew physical and mental health and performance in difficult-to-anticipate ways. Crew autonomy may be one of the biggest challenges faced. Communication delays and blackouts will occur, and in those situations, the crew may not have access to the Mission Control Center (MCC). They may be forced to be solely dependent on each other and the available information onboard to stay alive, healthy, and achieve the mission. The only conceivable way to meet the challenges of Earth independence is to enable the crew to monitor their own health and performance -- preferably unobtrusively as they perform their duties. Technologies and techniques must be developed to aid the crew in these assessments. A deep space mission is expected to have relatively short periods of high cognitive demand, stress, and fatigue, alongside potentially long periods of cognitive underload during the transit, where boredom, loneliness, and depression can set in. Both ends of this spectrum are dangerous. Crew must be made aware when their task performance drops significantly, when their cognitive workload is too high, when they have lost situation awareness, or when they are too stressed or too fatigued to perform well. They must be able to identify these risks, and then mitigate them with countermeasures available onboard. A number of self-monitoring technologies are presently being explored by NASA to advance crew state determination capabilities. These range from real-time, physiological workload and situation awareness assessments, to crew health measurements determining physical and mental fitness for duty, to task performance metrics such as suit resource expenditures. For EVA tasks during surface exploration missions, biomedical information such as metabolic rate may be provided to crewmembers for situational awareness related to task performance efficiency. In addition, translation distances, hydration, nutrition, inspired CO2 exposure and other consumables usage rates may be useful input metrics for modeling individualized performance during tasks to inform crew or provide estimates of work efficiency. Oculomotor metrics such as gaze dwell time, pupilometry, and eye tracking collected in advanced helmet mounted displays could potentially be used to characterize crew situation awareness. This paper highlights some of these projects, and provides broader discussion about the need for advanced monitoring and smart technologies, as NASA takes the leap into the next generation of space exploration.

Kritina Holden↗