Search NASA⌕ Search

SEARCH · Search NASA

Results for “Human Systems Integration”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

204 records · Page 12

Modernizing the Nuclear Industry and New Ways of Working

Nuclear energy is recognized as the most feasible energy source towards achieving nation-wide net-zero goals (COP 208, MIT). Additionally, the demand for reliable, consistent energy supply is soaring with the construction of energy hungry data centers and AI tools. This means the construction of new nuclear and the continuation of current nuclear are a high national priority. However, this leaves the nuclear industry with a workforce challenge. The rising demand for nuclear power is threatened by an underpopulated workforce. There exist a few contributors to the decreased workforce such as skewed workforce demographics resulting in large-scale workforce retirement. Also, some plants have observed difficulty hiring and retaining skill sets that typically comprise the nuclear power workforce – specifically skilled craftsman. Those who are graduating with desirable skills are seeking employment in sectors that are more modern and culturally more aligned with younger generational values. Lastly, within the nuclear sector, skilled employees will be a competitive commodity as advanced plants come online offering work environments that incorporate modern technologies, skill sets, and opportunities for career advancement. These factors emphasize the need for legacy plants to modernize with a focus on the workplace environment and culture that meets younger generations’ skills, cultural expectations, and desire for advancement opportunities. Nuclear plants are actively engaged in deploying advancements that improve the management of systems, structures, and components as well as process improvements and technologies that can reduce the costs of operation and maintenance. However, the advancements must also be analyzed, reviewed and deployed in a manner that considers the impact on how people within the organization collaborate, communicate, make decisions, and solve problems. Neglecting to consider the cultural impact of modernization risks poor adoption, unrealized opportunities, or insignificant change toward helping attract new employees. The traditional way of working is not necessarily the way new generations want to engage with their employer. For instance, in a survey performed by North American Young Generation in Nuclear the top three reasons for younger nuclear employees to seek other job opportunities was seeking better work-life balance, a lack of advancement opportunities, and work culture and leadership style differences (Smyth et al. 2022). Integrated Operations for Nuclear (ION) is an approach for the nuclear industry to create long-term strategic modernization plans and analyze each advancement for the impact on people and processes and measure how those impacts flow up to support high-level, long-term plant goals and requirements. One principle of ION is to replace the current labor-centric operation style in legacy nuclear plants with data-centric collaborative operation styles. This paper will explain how transitioning operations to leverage centralized skills and responsibility, multi-skilled teams, and collaborative decision making can flatten the hierarchical structure in plants, enable greater individual efficacy while also offering more experiences and advancement opportunities to staff. Adopting the ION way of working shifts the industry mind-set towards more networked, collaborative, and modern way of working that will attract skilled, next-generation workers to operate the legacy nuclear fleet.

99 - GENERAL AND MISCELLANEOUS↗

Impact of Cyber Threat Awareness on Driver Response to an Unexpected Vehicle Cyberattack

Here, the integration of advanced cyber-physical systems in heavy vehicles introduces new vulnerabilities by expanding the possibility of cyberattacks. The objective of this study is to evaluate (1) how threat awareness influences driver response to an unexpected cyberattack, (2) how the provision of a basic cyberattack response protocol influences driver performance, and (3) how professionally trained versus standard drivers compare in their responses to a cyberattack. An on-road driving study (N = 50) was conducted using a medium heavy-duty vehicle. Participants were divided into three groups: Control, which remained unaware of any potential cyberattack; Aware, which was informed about the potential cyberattack; and Aware + Protocol, which received the same warning as the Aware group with the addition of a basic cyberattack response protocol. An instrument cluster cyberattack was executed at the same location for all participants. The findings highlight the essential role of awareness and response protocol in enhancing driver response to an unexpected vehicle cyberattack. The Aware + Protocol group had the highest stop rate (100%) and the shortest stopping distances (224 m for standard drivers and 254 m for professionals), compared to the Control group (828 and 520 m, respectively). Aware + Protocol also had the fastest reaction time, averaging 7.53 s, versus 16.12 s (Aware) and 30.29 s (Control). These results emphasize that awareness alone is insufficient. Providing drivers with clear, actionable protocols significantly improves their ability to react quickly and safely to cyberattacks, enhancing overall road safety.

Cybersecurity↗

Traffic Control via Connected and Automated Vehicles (CAVs): An Open-Road Field Experiment with 100 CAVs

The CIRCLES project aims to reduce instabilities in traffic flow, which are naturally occurring phenomena due to human driving behavior. Also called “phantom jams” or “stop-and-go waves,” these instabilities are a significant source of wasted energy. Toward this goal, the CIRCLES project designed a control system, referred to as the MegaController by the CIRCLES team, that could be deployed in real traffic. Our field experiment, the MegaVanderTest (MVT), leveraged a heterogeneous fleet of 100 longitudinally controlled vehicles as Lagrangian traffic actuators, each of which ran a controller with the architecture described in this article. The MegaController is a hierarchical control architecture that consists of two main layers. The upper layer is called the Speed Planner and is a centralized optimal control algorithm. It assigns speed targets to the vehicles, conveyed through the LTE cellular network. The lower layer is a control layer, running on each vehicle. It performs local actuation by overriding the stock adaptive cruise controller, using the stock onboard sensors. The Speed Planner ingests live data feeds provided by third parties as well as data from our own control vehicles and uses both to perform the speed assignment. The architecture of the Speed Planner allows for the modular use of standard control techniques, such as optimal control, model predictive control (MPC), kernel methods, and others. The architecture of the local controller allows for the flexible implementation of local controllers. Corresponding techniques include deep reinforcement learning (RL), MPC, and explicit controllers. Depending on the vehicle architecture, all onboard sensing data can be accessed by the local controllers or only some. Likewise, control inputs vary across different automakers, with inputs ranging from torque or acceleration requests for some cars to electronic selection of adaptive cruise control (ACC) setpoints in others. The proposed architecture technically allows for the combination of all possible settings proposed previously, that is {Speed Planner algorithms} × {local Vehicle Controller algorithms} × {full or partial sensing} × {torque or speed control}. As a result, most configurations were tested throughout the ramp up to the MegaVandertest (MVT).

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Mondo: integrating disease terminology across communities

Precision medicine aims to enhance diagnosis, treatment, and prognosis by integrating multimodal data at the point of care. However, challenges arise due to the vast number of diseases, differing methods of classification, and conflicting terminological coding systems and practices used to represent molecular definitions of disease. This lack of interoperability artificially constrains the potential for diagnosis, clinical decision support, care outcome analysis, as well as data linkage across research domains to support the development or repurposing of therapeutics. There is a clear and pressing need for a unified system for managing disease entities⁠—including identifiers, synonyms, and definitions. To address these issues, we created the Mondo disease ontology—a community-driven, open-source, unified disease classification system that harmonizes diverse terminologies into a consistent, computable framework. Mondo integrates key medical and biomedical terminologies, including Online Mendelian Inheritance in Man (OMIM), Orphanet, Medical Subject Headings (MeSH), National Cancer Institute Thesaurus (NCIt), and more, to provide a comprehensive and accurate representation of disease concepts with fully provenanced and attributed links back to the sources. Mondo can be used as the handle for curation of gene–disease associations utilized in diagnostic applications, research applications such as computational phenotyping, and in clinical coding systems in clinical decision support by pointing the clinician to the numerous knowledge resources linked to the Mondo identifier. Mondo's community-centric approach, stewarded by the Monarch Initiative's expertise in ontologies, ensures that the ontology remains adaptable to the evolving needs of biomedical research and clinical communities, as well as the knowledge providers.

biomedical informatics↗

Global Methane Budget 2000–2020

Abstract. Understanding and quantifying the global methane (CH4) budget is important for assessing realistic pathways to mitigate climate change. CH4 is the second most important human-influenced greenhouse gas in terms of climate forcing after carbon dioxide (CO2), and both emissions and atmospheric concentrations of CH4 have continued to increase since 2007 after a temporary pause. The relative importance of CH4 emissions compared to those of CO2 for temperature change is related to its shorter atmospheric lifetime, stronger radiative effect, and acceleration in atmospheric growth rate over the past decade, the causes of which are still debated. Two major challenges in quantifying the factors responsible for the observed atmospheric growth rate arise from diverse, geographically overlapping CH4 sources and from the uncertain magnitude and temporal change in the destruction of CH4 by short-lived and highly variable hydroxyl radicals (OH). To address these challenges, we have established a consortium of multidisciplinary scientists under the umbrella of the Global Carbon Project to improve, synthesise, and update the global CH4 budget regularly and to stimulate new research on the methane cycle. Following Saunois et al. (2016, 2020), we present here the third version of the living review paper dedicated to the decadal CH4 budget, integrating results of top-down CH4 emission estimates (based on in situ and Greenhouse Gases Observing SATellite (GOSAT) atmospheric observations and an ensemble of atmospheric inverse-model results) and bottom-up estimates (based on process-based models for estimating land surface emissions and atmospheric chemistry, inventories of anthropogenic emissions, and data-driven extrapolations). We present a budget for the most recent 2010–2019 calendar decade (the latest period for which full data sets are available), for the previous decade of 2000–2009 and for the year 2020. The revision of the bottom-up budget in this 2025 edition benefits from important progress in estimating inland freshwater emissions, with better counting of emissions from lakes and ponds, reservoirs, and streams and rivers. This budget also reduces double counting across freshwater and wetland emissions and, for the first time, includes an estimate of the potential double counting that may exist (average of 23 Tg CH4 yr−1). Bottom-up approaches show that the combined wetland and inland freshwater emissions average 248 [159–369] Tg CH4 yr−1 for the 2010–2019 decade. Natural fluxes are perturbed by human activities through climate, eutrophication, and land use. In this budget, we also estimate, for the first time, this anthropogenic component contributing to wetland and inland freshwater emissions. Newly available gridded products also allowed us to derive an almost complete latitudinal and regional budget based on bottom-up approaches. For the 2010–2019 decade, global CH4 emissions are estimated by atmospheric inversions (top-down) to be 575 Tg CH4 yr−1 (range 553–586, corresponding to the minimum and maximum estimates of the model ensemble). Of this amount, 369 Tg CH4 yr−1 or ∼ 65 % is attributed to direct anthropogenic sources in the fossil, agriculture, and waste and anthropogenic biomass burning (range 350–391 Tg CH4 yr−1 or 63 %–68 %). For the 2000–2009 period, the atmospheric inversions give a slightly lower total emission than for 2010–2019, by 32 Tg CH4 yr−1 (range 9–40). The 2020 emission rate is the highest of the period and reaches 608 Tg CH4 yr−1 (range 581–627), which is 12 % higher than the average emissions in the 2000s. Since 2012, global direct anthropogenic CH4 emission trends have been tracking scenarios that assume no or minimal climate mitigation policies proposed by the Intergovernmental Panel on Climate Change (shared socio-economic pathways SSP5 and SSP3). Bottom-up methods suggest 16 % (94 Tg CH4 yr−1) larger global emissions (669 Tg CH4 yr−1, range 512–849) than top-down inversion methods for the 2010–2019 period. The discrepancy between the bottom-up and the top-down budgets has been greatly reduced compared to the previous differences (167 and 156 Tg CH4 yr−1 in Saunois et al. (2016, 2020) respectively), and for the first time uncertainties in bottom-up and top-down budgets overlap. Although differences have been reduced between inversions and bottom-up, the most important source of uncertainty in the global CH4 budget is still attributable to natural emissions, especially those from wetlands and inland freshwaters. The tropospheric loss of methane, as the main contributor to methane lifetime, has been estimated at 563 [510–663] Tg CH4 yr−1 based on chemistry–climate models. These values are slightly larger than for 2000–2009 due to the impact of the rise in atmospheric methane and remaining large uncertainty (∼ 25 %). The total sink of CH4 is estimated at 633 [507–796] Tg CH4 yr−1 by the bottom-up approaches and at 554 [550–567] Tg CH4 yr−1 by top-down approaches. However, most of the top-down models use the same OH distribution, which introduces less uncertainty to the global budget than is likely justified. For 2010–2019, agriculture and waste contributed an estimated 228 [213–242] Tg CH4 yr−1 in the top-down budget and 211 [195–231] Tg CH4 yr−1 in the bottom-up budget. Fossil fuel emissions contributed 115 [100–124] Tg CH4 yr−1 in the top-down budget and 120 [117–125] Tg CH4 yr−1 in the bottom-up budget. Biomass and biofuel burning contributed 27 [26–27] Tg CH4 yr−1 in the top-down budget and 28 [21–39] Tg CH4 yr−1 in the bottom-up budget. We identify five major priorities for improving the CH4 budget: (i) producing a global, high-resolution map of water-saturated soils and inundated areas emitting CH4 based on a robust classification of different types of emitting ecosystems; (ii) further development of process-based models for inland-water emissions; (iii) intensification of CH4 observations at local (e.g. FLUXNET-CH4 measurements, urban-scale monitoring, satellite imagery with pointing capabilities) to regional scales (surface networks and global remote sensing measurements from satellites) to constrain both bottom-up models and atmospheric inversions; (iv) improvements of transport models and the representation of photochemical sinks in top-down inversions; and (v) integration of 3D variational inversion systems using isotopic and/or co-emitted species such as ethane as well as information in the bottom-up inventories on anthropogenic super-emitters detected by remote sensing (mainly oil and gas sector but also coal, agriculture, and landfills) to improve source partitioning. The data presented here can be downloaded from https://doi.org/10.18160/GKQ9-2RHT (Martinez et al., 2024).

54 ENVIRONMENTAL SCIENCES↗

Nitrogen Deposition Weakens Soil Carbon Control of Nitrogen Dynamics Across the Contiguous United States

ABSTRACT Anthropogenic nitrogen (N) deposition is unequally distributed across space and time, with inputs to terrestrial ecosystems impacted by industry regulations and variations in human activity. Soil carbon (C) content normally controls the fraction of mineralized N that is nitrified ( ƒ nitrified ), affecting N bioavailability for plants and microbes. However, it is unknown whether N deposition has modified the relationships among soil C, net N mineralization, and net nitrification. To test whether N deposition alters the relationship between soil C and net N transformations, we collected soils from coniferous and deciduous forests, grasslands, and residential yards in 14 regions across the contiguous United States that vary in N deposition rates. We quantified rates of net nitrification and N mineralization, soil chemistry (soil C, N, and pH), and microbial biomass and function (as beta‐glucosidase (BG) and N ‐acetylglucosaminidase (NAG) activity) across these regions. Following expectations, soil C was a driver of ƒ nitrified across regions, whereby increasing soil C resulted in a decline in net nitrification and ƒ nitrified . The ƒ nitrified value increased with lower microbial enzymatic investment in N acquisition (increasing BG:NAG ratio) and lower active microbial biomass, providing some evidence that heterotrophic microbial N demand controls the ammonium pool for nitrifiers. However, higher total N deposition increased ƒ nitrified , including for high soil C sites predicted to have low ƒ nitrified , which decreased the role of soil C as a predictor of ƒ nitrified . Notably, the drop in contemporary atmospheric N deposition rates during the 2020 COVID‐19 pandemic did not weaken the effect of N deposition on relationships between soil C and ƒ nitrified . Our results suggest that N deposition can disrupt the relationship between soil C and net N transformations, with this change potentially explained by weaker microbial competition for N. Therefore, past N inputs and soil C should be used together to predict N dynamics across terrestrial ecosystems.

Nieland, Matthew A. [Stockbridge School of Agricul↗