Search NASA⌕ Search

SEARCH · Search NASA

Results for “emergency management”

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.

At least 235 records · Page 13

Active Temporal Control of Radiative Heat Transfer with Graphene Nanodisks

The ability to dynamically control the radiative transfer of heat at the nanoscale holds the key to the development of a diverse number of technologies, ranging from nanoscale thermal-management systems to improved thermophotovoltaic devices. Recently, graphene has emerged as an ideal material to achieve this goal, since it can be electrically doped to support surface plasmons, collective oscillations of the conduction electrons. These resonances produce large and spectrally narrow optical cross sections, which dictate the emission and absorption properties of the graphene nanostructure and, thus, the heat that it radiatively exchanges with other objects and the environment. For attainable levels of doping, the plasmons supported by graphene nanostructures naturally lie in the midinfrared part of the spectrum, which is the most relevant wavelength range for radiative heat transfer under realistic temperatures. Furthermore, these resonances are actively tunable, thus providing full dynamic control over the heat transfer. Motivated by this great potential, we present a comprehensive analysis of the temporal evolution of the radiative heat transfer between arrangements of graphene nanodisks, showing that it is possible to exploit the tunability of these structures to obtain actively controlled heat transfer scenarios not possible with conventional passive nanostructures. We report the results of this work provide a framework for achieving fully dynamical control over nanoscale radiative heat transfer and thus provide fundamental insights into this process.

36 MATERIALS SCIENCE↗

Quantifying the quantum heat contribution from a driven superconducting circuit

Heat flow management at the nanoscale is of great importance for emergent quantum technologies. For instance, a thermal sink that can be activated on-demand is a highly desirable tool that may accommodate the need to evacuate excess heat at chosen times, e.g., to maintain cryogenic temperatures or reset a quantum system to ground, and the possibility of controlled unitary evolution otherwise. Here we propose a design of such heat switch based on a single coherently driven qubit. We show that the heat flow provided by a hot source to the qubit can be switched on and off by varying external parameters, the frequency and the intensity of the driving. The complete suppression of the heat flow is a quantum effect occurring for specific driving parameters that we express and we analyze the role of the coherences in the free-qubit energy eigenbasis. We finally study the feasibility of this quantum heat switch in a circuit QED setup involving a charge qubit coupled to thermal resistances. In this work, we demonstrate robustness to experimental imperfections such as additional decoherence, paving the road towards experimental verification of this effect.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Towards Automatic Mapping of Vulnerabilities to Attack Patterns using Large Language Models

With the advent of new devices and applications, cyber attack surface is continuously evolving due to the emergence of new attack techniques and vulnerabilities. Hence, security management tool must assess the cyber risk of an enterprise at regular interval basis through comprehensively identifying associations among attack techniques, weakness, and vulnerabilities. However, existing repositories providing such associations are incomplete (i.e., missing associations), inducing the likelihood of undermining the risk of particular set of attack techniques. Moreover, such associations still rely on manual interpretation, which is slow compared to attack speed and ineffective for the increasing list of vulnerabilities and attack actions. Therefore, there is an urge to develop methodologies for automatically associating vulnerabilities to all relevant attack techniques. In this paper, we present a framework, named VWC-MAP, that can automatically identify all relevant attack techniques of a vulnerability via weakness based on their text descriptions, applying natural language process (NLP) techniques. To achieve that, we present a novel two-tiered classification approach, where the first tier classifies vulnerabilities to weakness, and the second tier classifies weakness to attack techniques. This research has improved the scalability of the current state-of-the-art tool to make vulnerability to weakness mapping significantly faster. Moreover, this paper presents two novel approaches for weakness to attack technique mapping applying Text-to-Text and link prediction techniques. Our experiment results cross-validated through cyber-security experts show that VWC-MAP can associate vulnerabilities to weakness types with 87% accuracy and to new attack patterns with 80% accuracy.

Das, Siddhartha Shankar↗

Point Source Likelihood Framework (psl) v1.0

PSL is a software framework for localizing radiation point sources in a 3D environment using a freely moving radiation detector system. The framework assumes a single point source of radiation is in the environment and uses known detector positions and orientations along with their radiation measurements to find the most likely location of the point source. This approach to the problem enables analyses that improve upon the capability of a standard Maximum Likelihood Expectation Maximization (MLEM) approach, such as setting a source detection threshold, finding a likelihood interval for the position of the source, finding a likelihood interval for the activity (intensity) of the source, determining whether more than one point source may be present, and generating a map of Minimum Detectable Activity (MDA) for a given source type. Applications include radiological and nuclear security, consequence management, decontamination and decommissioning of nuclear facilities, and radiological emergency response.

Joshi, Tenzing↗

An Investigation of Innovative Energy Technologies Entering the Market between 2009-2015, Enabled by EERE-Funded R&D

This report documents technologies that have been commercialized by the private sector and other partners—such as technology developers in startups, companies, and universities—in part because of R&D funding from EERE. It also documents emerging technologies that have the potential to reach the market within the next three years with the support of EERE R&D investments. Commercial and emerging technology tracking in this manner assists EERE technology managers, analysts, communications staff, and senior management in describing and explaining the benefits of EERE-funded research. Policy- and decision-makers would then have the latest information to guide future program development and direction.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Workflows Community Summit 2024: Future Trends and Challenges in Scientific Workflows

The 2024 Workflows Community Summit report presents the outcomes of a three-day international gathering that brought together 109 experts from 18 countries to discuss future trends and challenges in scientific workflows. The summit focused on six key areas: time-sensitive workflows, convergence of AI and HPC workflows, multi-facility workflows, heterogeneous HPC environments, user experience and interfaces, and FAIR computational workflows. Discussions highlighted emerging challenges such as integrating AI with traditional HPC, managing workflows across diverse facilities, addressing heterogeneity in computing environments, and ensuring workflows are findable, accessible, interoperable, and reusable (FAIR). The report outlines recent advances, ongoing challenges, and provides recommendations for each topic area, emphasizing the need for standardization, improved interoperability, and the development of more sophisticated tools and frameworks to support the evolving landscape of scientific workflows in the era of exascale computing and AI integration.

97 MATHEMATICS AND COMPUTING↗

A terminology for scientific workflow systems

The term “scientific workflow” has evolved over the last two decades to encompass a broad range of compositions of interdependent compute tasks and data movements. It has also become an umbrella term for processing in modern scientific applications. Today, many scientific applications can be considered as workflows made of multiple dependent steps, and hundreds of workflow systems have been developed to manage and run these scientific workflows. However, no turnkey solution has emerged from the field to address the diversity of scientific processes and the infrastructure on which they are supposed to be implemented. Instead, new research problems requiring the execution of scientific workflows with some novel feature often lead to the development of an entirely new workflow system. A direct consequence of this situation is that many existing workflow management systems (WMSs) share some salient features, offer similar functionalities, and can manage the same categories of workflows but at the same time also have some distinct capabilities that can be important for specific applications. This situation makes researchers who develop workflows face the complex question of selecting a WMS. This selection can be driven by technical considerations, to find the system that is the most appropriate for their application and for the computing and storage resources available to them, or other factors such as reputation, adoption, strong community support, or long-term sustainability. To address this problem, a group of WMS developers and practitioners joined their efforts to produce a community-based terminology of WMSs. This paper summarizes their findings and introduces this new terminology to characterize WMSs. Furthermore, this terminology is composed of fives axes: workflow structure and characteristics, composition, orchestration, data management, and metadata capture. Each axis comprises several concepts that capture the prominent features of WMSs. Based on this terminology, this paper also presents a classification of 23 existing WMSs according to the proposed axes and terms.

Community-based terminology↗

Minimum GHG emissions and energy consumption of U.S. PET and polyolefin packaging supply chains in a circular economy

There is a wide agreement on the urgency of transforming linear management of plastics towards a circular economy model. However, no clear pathways exist as to required recycling technologies involved and system-wide environmental impacts. This study explores such pathways in the U.S. for the most commonly used packaging plastics through a combination of mechanical and emerging advanced recycling technologies. A system optimization model aimed at minimizing environmental impacts was developed to determine optimal end-of-life (EOL) management and locations of existing and emerging U.S. recycling infrastructures. Our study includes material flows from virgin resin production through semi-manufacturing processes to existing EOL disposal and recycling processes. An optimized circular plastics packaging system achieved greenhouse gas (GHG) emission savings of up to 28% and cumulative energy demand (CED) savings of up to 46%, compared to the linear economy. Moreover, these savings of GHG emissions and CED impacts represent a reduction of 0.16% and 0.49% compared to annual U.S. GHG emissions and energy consumption in 2022, respectively. The optimal recycling rates and systems-level circularity ranged from 78–99% and 57–75%, respectively. Increased energy savings led to increased GHG emissions showing a potential trade-off between GHG emissions and energy. Analysis of 40 scenarios showed the importance of material collection distances, blend limit of mechanically recycled resins, process yields, and mandated recycling rates for achieving a sustainable circular economy of plastics.

09 - BIOMASS FUELS↗

Panel Session 70: Nuclear Power Plant Waste Management, LLRW Processing Issues

This panel focused on senior utility managers discussing issues with commercial LLW processors. LLW processors had an opportunity to update utilities/NPPs on new or different services or technologies being offered to assist in their radioactive waste management goals, changes to their facility license, revisions to their acceptance guidelines, and emerging compliance issues. Panelists with presentations: UniTech - 'Expanding to Reduce Costs' LLW Processor Update (Gregg Johnstone); Veolia Nuclear Solutions Federal Services - Alaron Nuclear Services (Dave Garber); EnergySolutions Tennessee Processing Facilities (Fred Schulz); Complex Waste Management Issues Services and Treatment Facilities (George M. Taylor)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

A Safety and Management Framework to Enable Automated Mobility Districts in Urban Areas

Automated mobility technology is beginning to emerge as a viable means to create sustainable and effective public mobility systems within denser urban environments. Automated mobility districts (AMDs) describe major urban districts or activity centers in which deployments of multiple automated vehicle (AV) transit and ride-hailing fleets are supported to meet public mobility needs. The authors put forward a framework to enable AMDs and their governing and management jurisdictional authorities to manage safety of AV operations based on lessons learned from the last century of automated guideway transit and roadway intersection traffic control systems. The essential concept is that of operational management and safety-critical control of multiple AV fleets using a “system-of-systems” approach to system safety analysis. The safety analysis would focus on safe passage of the AV fleet vehicles through complex roadway intersections and junctions, especially in the presence of other non-automated modes such as pedestrians and manually operated vehicles.

47 OTHER INSTRUMENTATION↗

Trade-offs of forest management scenarios on forest carbon exchange and threatened and endangered species habitat

Management of forest lands under climate warming poses challenges to managers, some of which are difficult to predict. Examining the trade-offs associated with forest stewardship choices is essential to avoid consequences with loss of natural capital. We utilized LANDIS-II process model simulations for three forested sites located in disparate parts of the United States with the purpose of understanding the trade-offs imposed by management choices under climate warming and associated wildfire. There were only small trade-offs that emerged from the simulations, between habitat area for threatened and endangered species (TES), net ecosystem exchange for CO2 (NEE), and risk of wildfire. Stand management in the form of thinning and prescribed burning typically increased NEE while simultaneously increasing habitat for TES, while reducing the risk of wildfire. These benefits were also observed under a climate warming scenario; however, the benefits were greatly outweighed by the negative impacts f warming on both TES habitat and NEE. Balancing these ecosystem services via thinning and burning treatments is a strategic approach to mitigate risks of wildfire both currently and under a warming future climate.

54 ENVIRONMENTAL SCIENCES↗

Towards FAIR Workflows for Federated Experimental Sciences

A de-centralized, peer-to-peer AI metadata framework is demonstrated which can enable end-to-end metadata & lineage tracking for distributed Machine Learning pipelines spanning edge, High Performance Computing, and cloud environments. With a specific example of end-to-end microscopy algorithm and datasets, the proposed method shows how to enable reproducibility, audit trail, provenance of metadata artifacts. The emerging needs of automation in experimental sciences, ML-centric workflows, and FAIR metadata management across federated compute environments is addressed.

machine learning↗

Of impacts, agents, and functions: An interdisciplinary meta-review of smart home energy management systems research

Smart home energy management technologies (SHEMS) have long been viewed as a promising opportunity to manage the way households use energy. Research on this topic has emerged across a variety of disciplines, focusing on different pieces of the SHEMS puzzle without offering a holistic vision of how these technologies and their users will influence home energy use moving forward. This paper presents the results of a systematic, interdisciplinary meta-review of SHEMS literature, assessing the extent to which it discusses the role of various SHEMS components in driving energy benefits. Results reveal a bias towards technical perspectives and controls approaches that seek to drive energy impacts such as load management and energy savings through SHEMS without user or third-party participation. Not only are techno-centric approaches more common, there is also a lack of integration of these approaches with user-centric, information-based solutions for driving energy impacts. Finally, these results suggest future work should investigate more holistic solutions for optimal impacts on household energy use. We hope these results will provoke a broader discussion about how to advance research on SHEMS to capitalize on their potential contributions to demand-side management initiatives moving forward.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Enabling HPC Scientific Workflows for Serverless

The convergence of edge computing, big data analytics, and AI with traditional scientific calculations is increasingly being adopted in HPC workflows. Workflow management systems are crucial for managing and orchestrating these complex computational tasks. However, it is difficult to identify patterns within the growing population of HPC workflows. Serverless has emerged as a novel computing paradigm, offering dynamic resource allocation, quick response time, fine-grained resource management and auto-scaling. In this paper, we propose a framework to enable HPC scientific workflows on serverless. Our approach integrates a widely used traditional HPC workflow generator with an HPC serverless workflow management system to create benchmark suites of scientific workflows with diverse characteristics. These workflows can be executed on different serverless platforms. We comprehensively compare executing workflows on traditional local containers and serverless computing platforms. Our results show that serverless can reduce CPU and memory usage respectively by 78.11% and 73.92% without compromising performance.

Andrei da silva, Anderson↗

Magnon spectroscopy in the electron microscope

Abstract The miniaturization of transistors is approaching its limits owing to challenges in heat management and information transfer speed 1 . To overcome these obstacles, emerging technologies such as spintronics 2 are being developed, which make use of the electron’s spin as well as its charge. Local phenomena at interfaces or structural defects will greatly influence the efficiency of spin-based devices, making the ability to study spin-wave propagation at the nanoscale and atomic scale a key challenge 3,4 . The development of high-spatial-resolution tools to investigate spin waves, also called magnons, at relevant length scales is thus essential to understand how their properties are affected by local features. Here we detect bulk THz magnons at the nanoscale using scanning transmission electron microscopy (STEM). By using high-resolution electron energy-loss spectroscopy with hybrid-pixel electron detectors, we overcome the challenges posed by weak signals to map THz magnon excitations in a thin NiO nanocrystal. Advanced inelastic electron scattering simulations corroborate our findings. These results open new avenues for detecting magnons and exploring their dispersions and their modifications arising from nanoscale structural or chemical defects. This marks a milestone in magnonics and presents exciting opportunities for the development of spintronic devices.

Science & Technology - Other Topics↗

Spatial Replication Is Important for Developing Landscape Genetic Inferences for a Wetland Salamander

Habitat fragmentation is a pressing threat to wildlife populations, and maintenance of gene flow between populations is an essential goal of conservation. Resistance surfaces have emerged as an important tool for modelling connectivity and developing management strategies to mitigate effects of habitat fragmentation. However, recent studies have noted inconsistencies in the factors most strongly associated with connectivity across different landscapes. Thus, replication of genetic-based resistance surface optimisation across landscapes may be necessary for making robust conclusions about the influence of environmental variables. Accordingly, replication represents a substantive challenge and opportunity in the field of landscape genetics. In this study, we conducted replicated landscape genetic analyses across five landscapes in Tennessee and Kentucky for a threatened wetland amphibian, the four-toed salamander (Hemidactylium scutatum). We tested multiple hypotheses of how different landscape features that could directly affect small, desiccation-intolerant amphibians (e.g., canopy cover) influenced gene flow and assessed the appropriate scale at which to model different features. We found some concordance in the landscape features that influenced gene flow (e.g., a common importance of forest cover and topography), but also some differences—potentially owing to the difference in variability of predictors across landscapes. We also found discordance in the scale of effect of different features across landscapes. In conclusion, our work emphasises that flat areas of moist forest not bisected by roads may be important for H. scutatum conservation, and our replicated design allows us to identify relationships that would have been missed if only using one study site.

59 BASIC BIOLOGICAL SCIENCES↗

SuiteGoo [Slides]

SuiteGoo is a liquid product used to detect "undetectable" material traces. It is used when you need to improve detection limits, anywhere where cotton swiping is used, and anywhere where cotton swiping fails. It is also used by law enforcement to find DNA from fingerprints, used by health care to detect the presence of viruses and bacteria, used by emergency response to detect explosive traces, and used by environmental management to detect pollutant traces.

54 ENVIRONMENTAL SCIENCES↗

Scalable, Dual-Mode Occupancy Sensing for Commercial Venues

The ability to establish accurate occupancy is a key enabler for improved energy efficiency in human-occupied indoor spaces. The accurate counts can be used to adjust, in real-time, air exchange, heating, and cooling, to closely match the environmental needs of the occupants rather than to use a single setting based on maximum room occupancy. This project focuses on the use of overhead fisheye cameras and artificial intelligence (AI) algorithms as the technology to realize accurate people counting in large commercial spaces. We developed Computational Occupancy Sensing SYstem ("COSSY''), which supports large-scale deployment (thousands of square feet) and straightforward installation (using conventional power over ethernet), while providing high accuracy and low cost. COSSY has been validated at Boston University and by a third party, demonstrating people-counting accuracy of at least 89.5% in large spaces (2,000 sqft). A cost/benefit analysis performed for Boston commercial market indicates that a full payback of COSSY deployment costs due to energy savings would occur within 3-6 months from installation. Applications of COSSY reach far beyond saving energy. The precise people counting in real time could also be useful for emergency response (e.g., fire), in spatial analytics (e.g., office space management) and in some health applications (e.g., social distance assessment during pandemics).

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗