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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 19 records

A materials data framework and dataset for elastomeric foam impact mitigating materials

The availability of materials data for impact-mitigating materials has lagged behind applications-based data. For example, data describing on-field helmeted impacts are available, whereas material behaviors for the constituent impact-mitigating materials used in helmet designs lack open datasets. Here, we describe a new FAIR (findable, accessible, interoperable, reusable) data framework with structural and mechanical response data for one example elastic impact protection foam. The continuum-scale behavior of foams emerges from the interplay of polymer properties, internal gas, and geometric structure. This behavior is rate and temperature sensitive, therefore, describing structure-property characteristics requires data collected across several types of instruments. Data included are from structure imaging via micro-computed tomography, finite deformation mechanical measurements from universal test systems with full-field displacement and strain, and visco-thermo-elastic properties from dynamic mechanical analysis. These data facilitate modeling and design efforts in foam mechanics, e.g., homogenization, direct numerical simulation, or phenomenological fitting. The data framework is implemented using data services and software from the Materials Data Facility of the Center for Hierarchical Materials Design.

36 MATERIALS SCIENCE↗

Tunable Metamaterials for Impact Mitigation

Traditional methods of shielding fragile goods and human tissues from impact energy rely on isotropic foam materials. The mechanical properties of these foams are inferior to an emerging class of metamaterials called plate lattices, which have predominantly been fabricated in simple 2.5-dimensional geometries using conventional methods that constrain the feasible design space. Here in this work, additive manufacturing is used to relax these constraints and realize plate lattice metamaterials with nontrivial, locally varying geometry. The limitations of traditional computer-aided design tools are circumvented and allow the simulation of complex buckling and collapse behaviors without a manual meshing step. By validating these simulations against experimental data from tests on fabricated samples, sweeping exploration of the plate lattice design space is enabled. Numerical and experimental tests demonstrate plate lattices absorb up to six times more impact energy at equivalent densities relative to foams and shield objects from impacts ten times more energetic while transmitting equivalent peak stresses. In contrast to previous investigations of plate lattice metamaterials, designs with nonuniform geometric prebuckling in the out-of-plane direction is explored and showed that these designs exhibit 10% higher energy absorption efficiency on average and 25% higher in the highest-performing design.

36 MATERIALS SCIENCE↗

Dust Mitigation: Impacts & Opportunities for Science on the Lunar South Pole

Lunar dust will be a feature of all lunar surface science investigations, whether welcome or not. While lunar dust may pose problems for some investigations, it is also the subject of many critical scientific discoveries made since the Apollo days. Dust mitigation, or learning how to work with and around the inevitable dust we will encounter on the surface, is not a new concept. However, new initiatives throughout NASA are underway in an effort to tackle dust mitigation strategically for the Artemis program. Dust mitigation efforts and technologies will enable successful lunar surface science investigations.

lunar dust↗

Community-Informed Urban Flood Modeling for Impact Mitigation

Climate change is intensifying the hydrologic cycle, leading to more frequent and severe rainfall-driven (pluvial) flooding in urban areas. In the mid-Atlantic US cities, aging and under-designed stormwater infrastructure is increasingly strained by these events, resulting in recurring damage to property and disruptions to transportation networks. In this study, we combine community engagement with hydrologic modeling to develop and evaluate potential urban flood adaptation strategies. Over a three-year period, local technical experts and community representatives met regularly to discuss flooding concerns, identify priorities, and co-develop adaptation strategies. These discussions informed the development of an urban flooding model (EPA Storm Water Management Model) for the Baltimore Harbor watershed, the focus location of this study. The flooding model integrates complex surface and subsurface stormwater infrastructure data, local expert knowledge, and community insights. We simulate stakeholder-prioritized adaptations, such as green and gray infrastructure strategies. Model results demonstrate that enhanced infrastructure maintenance is the most effective adaptation for reducing flood depths, but has varied effects across the watershed, and can increase flooding in some locations. Spatially concentrated greening provides limited benefit to the watershed as a whole, but moderate benefit in community priority areas. Together, these adaptations have the potential to reduce flood depths by as much as 58% in some locations, greatly reducing property damage and mobility impacts, primary concerns of stakeholders. Future work will implement robust optimization tools to search for adaptations which meet stakeholder objectives and perform highly under varied future climate conditions. This work contributes to the expanding literature on collaborative modeling and demonstrates that community-engaged approaches can enhance model credibility and generate more actionable insights for communities seeking to strengthen climate resilience.

Baltimore MD↗

Mitigating Impact Through Community-Engaged Flood Modeling

Urban pluvial flooding poses a growing threat to the city of Baltimore, driven by heavy rainfall, increased impervious area, and aging infrastructure. Adapting to the risks posed by pluvial flooding is critical for building greater climate resiliency in Baltimore's Inner Harbor Watershed. This study addresses these challenges through community-informed decision analysis, which uses hydrologic modeling and optimization tools to identify robust flooding adaptation pathways. We will collaborate with community partners to identify key concerns and objectives regarding flooding. These concerns have been purposefully built in to a combined surface-subsurface dynamic flow simulation model. Model outputs are used to identify flooding locations within the Inner Harbor, and to test adaptation methods. Machine learning will be used search for solutions which meet diverse environmental, financial, and social goals, and solution performance will be examined under a wide range of potential future climatic conditions and integrated with an adaptive planning approach. This novel set of adaptation pathways will enhance the City's capacity to respond to evolving pluvial flood risk.

climate resilience↗

Community-Informed Urban Flood Modeling for Impact Mitigation

The intensification of the hydrologic cycle due to climate change poses a threat to aging and under-designed water infrastructure systems which cannot adequately manage intense storm events. Developing a comprehensive plan for managing rain-driven flooding events is challenging due to uncertainties in the magnitude and frequency of future storm events and conflicting stakeholder objectives. In the City of Baltimore, Maryland, stormwater infrastructure is struggling to keep up with rainfall-driven (pluvial) flooding events, which regularly damage housing and disrupt transportation for residents. In this study, a hybrid of community engagement, numerical modeling, and artificial intelligence techniques are employed to explore prospective urban flooding adaptations. Community engagement drives the development of an urban flooding model (EPA Storm Water Management Model) for the Baltimore Harbor watershed. The model integrates complex surface and subsurface stormwater infrastructure data from the City, high-resolution spatial data, insights from local public works experts, and the lived experiences of City residents. This co-developed model simulates adaptations of interest to stakeholders in the city, including green and grey infrastructure and operational management strategies. Stormwater management scenarios focused on inlet cleaning and spatially concentrated green infrastructure are found to be the most effective in reducing flood depths in community priority locations. Together, these adaptations can reduce the duration of intersection inundation by more than twenty minutes, allowing for quicker emergency response and restoration of typical transportation systems. Future work will combine this community engaged flooding model with the Deep Uncertainties Pathways framework to explore tradeoffs between adaptations and develop dynamic adaptations which align with community objectives, enhance climate resilience in Baltimore, and can be adjusted in response to changing future conditions.

Ava, Spangler [Pennsylvania State University]↗

Models Required to Mitigate Impacts of Space Weather on Space Systems

This viewgraph presentation attempts to develop a model of factors which need to be considered in the design and construction of spacecraft to lessen the effects of space weather on these vehicles. Topics considered include: space environments and effects, radiation environments and effects, space weather drivers, space weather models, climate models, solar proton activity and mission design for the GOES mission. The authors conclude that space environment models need to address issues from mission planning through operations and a program to develop and validate authoritative space environment models for application to spacecraft design does not exist at this time.

Barth, Janet L.↗

The Atacama Cosmology Telescope: Mitigating the Impact of Extragalactic Foregrounds for the DR6 Cosmic Microwave Background Lensing Analysis

We investigate the impact and mitigation of extragalactic foregrounds for the cosmic microwave background (CMB) lensing power spectrum analysis of Atacama Cosmology Telescope (ACT) data release 6 (DR6) data. Two independent microwave sky simulations are used to test a range of mitigation strategies. We demonstrate that finding and then subtracting point sources, finding and then subtracting models of clusters, and using a profile bias-hardened lensing estimator together reduce the fractional biases to well below statistical uncertainties, with the inferred lensing amplitude, A lens , biased by less than 0.2σ. We also show that another method where a model for the cosmic infrared background (CIB) contribution is deprojected and high-frequency data from Planck is included has similar performance. Other frequency-cleaned options do not perform as well, either incurring a large noise cost or resulting in biased recovery of the lensing spectrum. In addition to these simulation-based tests, we also present null tests on the ACT DR6 data for sensitivity of our lensing spectrum estimation to differences in foreground levels between the two ACT frequencies used, while nulling the CMB lensing signal. These tests pass whether the nulling is performed at the map or bandpower level. The CIB-deprojected measurement performed on the DR6 data is consistent with our baseline measurement, implying that contamination from the CIB is unlikely to significantly bias the DR6 lensing spectrum. This collection of tests gives confidence that the ACT DR6 lensing measurements and cosmological constraints presented in companion papers to this work are robust to extragalactic foregrounds.

79 ASTRONOMY AND ASTROPHYSICS↗

Incorporation of Functionalized Polyhedral Oligomeric Silsesquioxane Nanomaterials as Reinforcing Agents for Impact Ice Mitigating Coatings

In-flight, aircraft are exposed to a wide range of environments. One commonly exposed environment are clouds containing super-cooled water droplets. These water drop- lets exist in a metastable state below the freezing point of water, in the range of 0 to -20°C. As the vehicle impacts the droplets, latent heat is released and within milliseconds the droplets convert to ice. This process is referred to as impact icing or in-flight icing.1 Impact icing is a major concern for aircraft since it can lead to degraded aerodynamic performance and, if left un- treated, can lead to loss of the vehicle. Active approaches (i.e., pneumatic boots, heated air ducts) typically utilized in mitigating in-flight ice accretion significantly increases vehicle weight and cannot be applied to all aircraft.1-3 A passive approach based on coatings is desired, but durability issues are a concern, especially on the wing leading edge.3 Nanomaterials have been shown to afford significant improvement in coating and composite physical properties at low loading levels.4 In this study, Polyhedral Oligomeric Silsesquioxane (POSS) nanomaterials have been shown to increase coating durability. Also, with wide variety of functionalities present on the arm structure, POSS nanomaterials have been shown to readily alter coating surface chemistry to mitigate impact ice adhesion from -16 to -8°C in a simulated in-flight icing environment.

Beck, Devon M.↗

An Innovative Solution to NASA's NEO Impact Threat Mitigation Grand Challenge and Flight Validation Mission Architecture Development

This paper presents the results of a NASA Innovative Advanced Concept (NIAC) Phase 2 study entitled "An Innovative Solution to NASA's Near-Earth Object (NEO) Impact Threat Mitigation Grand Challenge and Flight Validation Mission Architecture Development." This NIAC Phase 2 study was conducted at the Asteroid Deflection Research Center (ADRC) of Iowa State University in 2012-2014. The study objective was to develop an innovative yet practically implementable mitigation strategy for the most probable impact threat of an asteroid or comet with short warning time (< 5 years). The mitigation strategy described in this paper is intended to optimally reduce the severity and catastrophic damage of the NEO impact event, especially when we don't have sufficient warning times for non-disruptive deflection of a hazardous NEO. This paper provides an executive summary of the NIAC Phase 2 study results. Detailed technical descriptions of the study results are provided in a separate final technical report, which can be downloaded from the ADRC website (www.adrc.iastate.edu).

NEO Impact Threat Mitigation↗

Impact of breech geometry and propellant flow on the release of large pellets for the ITER disruption mitigation system

Studies have been performed on the release mechanism for large pellets using high pressure gas in a shattered pellet injector. Typically, pellets are dislodged from the cryogenic surface and accelerated down a barrel using high pressure gas delivered by a fast-acting propellant valve. The pellets impact an angled surface which shatters the pellet into many small fragments before entering the plasma. This technique was initially demonstrated on DIII-D (Commaux et al 2016 Nucl. Fusion 56 046007) and is now deployed on JET, KSTAR, ASDEX-Upgrade, and other tokamaks around the world in support of ITER's disruption mitigation system design and physics basis. The large hydrogen, 28.5 mm diameter, 2 length-to-diameter ratio, pellets foreseen for ITER SPI operation have low material strength and low heat of sublimation, which cause the pellets to be fragile and highly reactive to the impact of warm propellant gas. Due to the size of the pellets, significantly more propellant gas is required to dislodge and accelerate them. This creates a potentially significant propellant gas removal issue as 2–6 bar-L of gas is expected to be required for release and speed control. The research presented in this paper is an in-depth exploration of the parameters that are keys to reliable pellet release and speed control. Computational fluid dynamics (CFD) modeling of propellant flows through various breech designs was conducted to determine the force generated on the back surface of a pellet. These simulations assumed the use of the ORNL designed flyer plate valve. CFD modeling combined with experimental measurements provide adequate insight to determine a path to an optimal valve and breech design for ITER SPI pellet release and speed control while minimizing propellant gas usage.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

An Innovative Solution to NASA's NEO Impact Threat Mitigation Grand Challenge and Flight Validation Mission Architecture Development

This final technical report describes the results of a NASA Innovative Advanced Concept (NIAC) Phase 2 study entitled "An Innovative Solution to NASA's NEO Impact Threat Mitigation Grand Challenge and Flight Validation Mission Architecture Development." This NIAC Phase 2 study was conducted at the Asteroid Deflection Research Center (ADRC) of Iowa State University in 2012-2014. The study objective was to develop an innovative yet practically implementable solution to the most probable impact threat of an asteroid or comet with short warning time (less than 5 years). The technical materials contained in this final report are based on numerous technical papers, which have been previously published by the project team of the NIAC Phase 1 and 2 studies during the past three years. Those technical papers as well as a NIAC Phase 2 Executive Summary report can be downloaded from the ADRC website (www.adrc.iastate.edu).

NEO↗

The Feedstock-Conversion Interface Consortium - Understanding and Mitigating the Impacts of Feedstock Variability in Bioconversion Processes

The Feedstock-Conversion Interface Consortium is led by DOE as a collaborative effort among researchers from 9 National Laboratories. The FCIC was formed because biomass feedstock properties are variable and different from other commodities, and empirical approaches to address these issues have been unsuccessful. The FCIC uses first-principles-based science to de-risk biorefinery scale-up and deployment by understanding and mitigating the impacts of feedstock variability on bioenergy conversion processes. In this presentation, we present a brief overview of key FCIC prinicples and recent results.

biomass↗

Mitigating the Impact of Sensor Uncertainty on Unmanned Aircraft Operations

Without a pilot onboard an aircraft, a Detect-and-Avoid (DAA) system, in conjunction with surveillance sensors, must be used to provide the remotely-located Pilot-in-Command sufficient situational awareness in order to keep the Unmanned Aircraft (UA) safely separated from other aircraft. To facilitate safe operations of UA within the U.S.' National Airspace System, the uncertainty associated with surveillance sensors must be accounted for. An approach to mitigating the impact of sensor uncertainty on achievable separation has been developed to support technical requirements for DAA systems.

Jack, Devin P.↗