Search NASA⌕ Search

SEARCH · Search NASA

Results for “Understanding”

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 1,369 records · Page 76
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Design and Production for Maximum Structural Efficiency With Respect to Fiber Orientation With Increased Understanding of Hybrid Fiber Flow Behavior

Discontinuous fiber-reinforced thermoplastic composites have gained considerable attention in automotive, aerospace, and other industries, due to their high-rate of production combined with their ability to attain complex and intricate shapes. Among other high-rate thermoplastic manufacturing processes, injection-molding is one of the most common manufacturing methods due to fast production and high surface finishing of complex geometries. Fiber orientation in discontinuous fiber composites plays a pivotal role in determining the mechanical, electrical, and thermomechanical properties, underscoring the necessity to comprehend fiber orientation in injection molded parts. Among different fiber types, glass and carbon fibers are most common in the composite industries. The recent trend of hybrid composites comprising both glass fiber (GF) and carbon fiber (CF) is also gaining importance in the automotive industry. Hybrid fiber options allow designers to optimize the balance between glass and carbon fibers by leveraging the high durability and low cost of GF while the strength and lightweight properties of CF. Consequently, comparing the fiber oriented distribution (FOD) of injection molded composites containing GF, CF, and a hybrid of GF/CF is critical to investigating the local mechanical properties of intricate structures for high-end applications. In Phase I of this project, FOD in injection-molded panels with respect to distance from the gate was analyzed using X-ray computed tomography (X-CT) for GF, CF, and hybrid CF/GF (CGF) reinforced nylon 66. To understand the reason behind the FOD with different fiber types, computational fluid dynamics (CFD) and rheology were performed. Samples were extracted at three locations: near the gate, center, and opposite end. Thickness of the layers of typical skin-shell-core type FOD varies with fiber type and location. GF achieved flow direction alignment (in shell) earlier than viscous CF and CGF near the gate, whereas CF showed the highest flow-direction alignment at the center due to shear induced orientation. At the opposite end, GF experienced more backflow than others indicating faster mold filling owing to its lower viscosity. Hybrid CGF exhibited GF-dominated center and CF-dominated end region. The numerical model used to obtain FOD and rheological predictions for the CF and GF composites served to corroborate the trends observed in the experimental trials. The FOD responses across fiber types and location were reflected in their longitudinal and transverse properties. Only GF showed higher longitudinal modulus over transverse modulus near the gate attributed to rapid alignment, whereas CF and CGF exhibited opposite trend. However, fountain flow enhanced the longitudinal modulus over transverse modulus with the distance for all, particularly for CF. This study offers insights into mold filling behavior of different fibers which are critical in optimizing injection molding conditions for tailored final properties.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Optimize the Autonomous Sensor Fish Device for Understanding Interactions of Aquatic Animals with Marine and Hydrokinetic and Hydro Systems (CRADA 476) Final Report

This project at the Pacific Northwest National Laboratory (PNNL) enhances our understanding of how aquatic life interacts with marine renewable energy (MRE) and hydropower systems through the development and testing of advanced sensor technology. The Marine Sensor Fish (MSF) and its smaller variants, the Sensor Fish Mini (SF Mini) and Flexible Sensor Fish (FSF), measure critical environmental stressors, such as shear forces, pressure changes, and strike impacts, that are essential for assessing the risks posed by energy devices, including tidal turbines, hydropower installations, and other MRE infrastructure. Rigorous field testing has shown that these tools are effective in capturing detailed data on turbulence, pressure variations, strike impacts, and other stressors near these devices, providing valuable insights into the conditions faced by aquatic species. Economically, these tools offer renewable energy developers a practical solution for streamlining environmental assessments and ensuring regulatory compliance, ultimately reducing costs associated with evaluating and mitigating ecological impacts. This research also benefits the public by promoting the growth of renewable energy sources that protect aquatic ecosystems, advancing both sustainable energy production and environmental stewardship.

13 HYDRO ENERGY↗
DOE OSTI2024

Enhancing Biopreparedness through a Model System to Understand the Molecular Mechanisms that Lead to Pathogenesis and Disease Transmission: NW-BRaVE

The science of biopreparedness to counter biological threats hinges on understanding the fundamental principles and molecular mechanisms that lead to pathogenesis and disease transmission. Our vision to address this challenge is to create a powerful and user-friendly platform to elucidate the fundamental principles of how molecular interactions drive pathogen-host relationships and host shifts. We will enable groundbreaking discoveries by integrating a wide range of structural, genomics, proteomics, and other advanced omics measurements, along with evolutionary and artificial intelligence predictions. To make sure the system is applicable to real-world problems, we will develop it in the context of a tractable model system, the small, abundant, and accessible photosynthetic cyanobacteria and their constantly co-adapting viral pathogens, cyanophages. This model will maintain the system’s applicability to real-world problems and techniques, but the overall focus will be on elucidating general principles of detecting, assessing, and surveilling molecular interaction, adaptation, and coevolution that are system agnostic and therefore extensible to other viral-host interactions. Our overall objectives are to (1) identify the molecular complexes that comprise the cyanobacteria redox macromolecular subsystem and how they dynamically change with bacteriophage infection in situ, using cryo-electron tomography; (2) profile regulatory changes during infection using proteomics, multiomics, and experimental validation, and integrate the data with in situ structures; (3) use genomics and metagenomics to determine environmental and population factors across time scales that impact the interactions between marine cyanobacteria and their cyanophage parasites, predicting the evolutionary origins of in situ structural and functional interactions, convergence and coevolution; and (4) develop a data integration and transformation platform that facilitates the integration of in situ, proteomic, and evolutionary measurements of molecular interactions to surveil diverse hosts and parasites in various environmental contexts. These objectives address Focus Area 2 Reveal Molecular Interactions Across Biological Scales for Design of Targeted Interventions. Our powerful and user-friendly platform will enhance connections between the often-siloed fields of structure, molecular phenotype, and evolutionary genomics that are key to biopreparedness, but in need of integration (Figure 1). We will build an integrated navigation tool to facilitate the effective use of globally distributed experimental data for integrated analysis and predictive modeling. The project will develop, implement, and test a platform to assess host-pathogen molecular interactions, adaptation to hosts and host shifts, and coevolution between hosts and pathogens, successfully impacting the research community by revolutionizing abilities to study any host-pathogen interaction, encourage diverse community contributions, and gain fundamental insights into how proteins adapt to new contexts. This ability will be critical for designing early interventions to address future threats. We will build surveillance training capability, aiming for a fair and equitable response to future pandemics and biothreats.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Leveraging ARM Data to Improve Models for Predictive Understanding of Energy and Security Challenges

Extreme weather and natural hazards can disrupt the energy sector, affecting demand, generation, transmission, distribution, consumption and operational planning at regional and national scales. These disruptions stem from a broad range of atmospheric phenomena, including winter storms, freezing rain, wet snow loading, severe convection, flooding and landslides, wildfires, prolonged heat, and drought. Many of these same phenomena can also affect national security through impacts to transportation and infrastructure. To support the U.S. Department of Energy (DOE) focus on energy resilience and national security, the Atmospheric Radiation Measurement (ARM) User Facility is uniquely positioned to contribute measurement data, analyses, and modeling frameworks that can significantly improve predictive understanding of these hazards to mitigate their effects. To explore this opportunity, ARM convened a two-part virtual workshop in November 2025. The workshop engaged interdisciplinary experts in atmospheric science, energy systems, modeling, and operations. The goal of the meeting was to engage with these interdisciplinary experts to address three questions: • What are examples of atmospheric processes that represent significant risks to energy security or national security and where are those risks greatest? • What measurements or measurement strategies would improve ARM’s capacity to address these issues? • How can ARM and users of the ARM facility better work with the Energy Exascale Earth System Model (E3SM) and multi-sector modeling communities to apply ARM data to improving E3SM simulations of these phenomena? Participants were asked to submit white papers ahead of the meeting to initiate thinking on these themes and to help organize discussions. Workshop sessions were then organized around themes identified in the white papers. First from the white papers and then through subsequent discussions, workshop participants identified many examples that address the three questions listed above. Participants called out energy system vulnerabilities to weather phenomena such as the impact of freezing rain, strong winds, and excessive heat on power grids. They also noted the effects that weather phenomena could have on energy demand or supply (e.g., through effects of extreme temperatures). They called out security vulnerabilities such as impacts to crops from aerosol-borne pathogens and risks to industry due to melting permafrost in the Arctic. In all, over a dozen meteorological phenomena were linked to energy or security vulnerabilities. For many of the identified phenomena, participants pointed out where ARM was well poised to address issues (e.g., through measurements of cloud microphysics to inform studies of freezing rain) but also noted needs for additional measurements or modified measurement strategies. For example, adaptive scanning of severe weather would be valuable for probing winter storms or severe convection. Participants pointed out the value in integrating external observations with ARM measurements and with applying artificial intelligence (AI) to ARM observation analysis and they advocated for using model simulations to help optimize measurement strategies through Observing System Simulation Experiments (OSSEs). It was clear from the workshop that there are many ways that ARM observations can be used to mitigate energy and security concerns, but meeting participants were also asked to identify what they considered to be the greatest opportunities by ranking issues pertaining to the three workshop questions. This was accomplished through a survey administered to participants between the two virtual sessions. The highest-priority phenomena identified were winter storms, severe convection, and arctic processes. Discussion in the second session, therefore, focused primarily on these three areas, which were most fully developed in exploring ARM opportunities. Nevertheless, it was also clear that ARM has opportunities to contribute to all the identified topics. This report describes the workshop, including input from discussion and white papers (Sections 2 and 3) and a list of priority recommendations (section 4). Many other ideas for ARM contributions are discussed in individual white papers (Appendix D).

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2026

Understanding neutrinos with accelerator beams and liquid argon time-projection chambers: ICARUS and DUNE

A global program of experiments has worked towards characterizing neutrino oscillation over the past few decades. However, important parameters remain to be measured, and mysteries remain to be elucidated. Current and upcoming experiments are targeting the open questions and probing the consistency of the neutrino oscillation paradigm. Likewise, the liquid argon (LAr) time-projection chamber (TPC) has emerged as a sensitive particle detection technology for neutrino experiments. A current generation of LAr TPC detectors are being used to study neutrinos while also gaining important experience in operating and analyzing with this technology. SBND, MicroBooNE, and ICARUS have collected or are collecting data from beams at Fermilab (near Chicago) to explore the possibility of a sterile neutrino and/or other beyond Standard Model (BSM) physics. SBND and ICARUS will be used to conduct a two-detector analysis as part of the Short Baseline Neutrino (SBN) Program. Additionally, these detectors are enabling important neutrino interaction studies necessary to prepare for the next generation of oscillation experiments. One such oscillation experiment that will come online over the next years is the Deep Underground Neutrino Experiment (DUNE), which will install multiple 10 kiloton LAr TPCs underground in South Dakota (south of Saskatchewan) to conduct oscillation measurements with neutrinos originating in a beamline at Fermilab. A detector complex will be installed at Fermilab as well, to study the beam before the expected flavour oscillations. This “near detector” will also employ a LAr TPC, with a segmented and pixel-based design, as well as other technologies to constrain uncertainties in the oscillation measurement by characterizing the beam and neutrino interactions. This talk will discuss the ICARUS and DUNE experiments, the LAr TPC detector technology, and the efforts to realize and leverage these experiments to better understand the properties of neutrinos.

Howard, Bruce L. [Fermilab]↗
DOE OSTI2026

Understanding NBI heating and fueling in LTX-β tokamak

My work on the contract DE-SC=0023274 (July, 2022 - July, 2025) was focused on understanding the plasma fueling by NBI. On Dec. 1998 with Sergei Krasheninnikov (UCSD, San Diego, CA) we initiated the Li Wall Fusion (LiWFusion) as a new concept of magnetic fusion [1]. The new 1 2 plasma 3 4 5 6 2.1 Overview of rate coefficients, mean-free paths λH0 , and diffusions coefficients 6 2. GSV code for ⟨σv⟩ analysis of NBI fueling concept was a reaction of the lack of luck of tokamak fusion with QDT = 1 on TFTR and JET. We recognized the edge plasma cooling by recycling to be the route reason of the tokamak problems on the way to burning plasma. LiWFusion relies on plasma pumping by a lithium layer on the inner walls of the plasma chamber, combined with the plasma heating and fueling by the Neutral Beam Injection (NBI). These two innovations eliminate the route problem of the tokmak fusion. The concept became theoretically mature in 2006. In 2012, the technology of continuously Flowing Liquid Lithium (24/7-FLiLi) was invented by me for the future implementations of the LWFusion concept. At the same time, my every presentation on LiWFusion to International Symposium on Lithium Applications since 2010 was objected by some person with words “Everybody since the 1970s knows that plasma fueling by NBI is impossible”. I dropped the name of the author of this objection and ignored his views. My work on the current grant on NBI fueling of LTX-β not only clarified the issue but resolved it in an astonishing way. The NBI fueling was fully understood (thus humiliating the current dogmatic fusion community). The new future of LTX-β dedicated for decades to Li in tokamaks, as well as of the entire magnetic fusion program was envisioned, in sharp contrast with the fallure of OFES in the post-TFTR era of 21st century.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Plasma Flow Reactor Investigation into Nucleation of Uranium Oxide on Silica Substrates to Better Understand Fallout Formation

Understanding particulate formation in nuclear debris is critical for predicting fallout transport after a nuclear event. Improved characterization of fallout formation and transport could lead to better guidance for emergency response in a post-detonation scenario. By analyzing how U-oxides nucleate onto different forms of SiO 2 (crystalline and amorphous), we can gain insight into how entrained environmental materials may incorporate into fallout. In this experiment a Plasma Flow Reactor (PFR), was used to replicate the high temperature and extreme flow conditions in a nuclear fireball. Uranyl nitrate was injected into the plasma, and PFR-generated Uranium oxides were allowed to condense onto amorphous (nanoparticles of varying sizes) or crystalline (quartz) SiO 2 substrates. SiO 2 substrates were characterized before and after U-oxide deposition using Scanning Electron Microscopy (SEM) based techniques (i.e. EDS) in order to characterize how U-oxides may nucleate onto these substrates. After a collection time of 4 minutes at an RF coil distance of 25cm, both the amorphous SiO 2 nanoparticles and the crystalline structures demonstrated dendritic nucleation of U-oxide species as identified by SEM/EDS.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

UNLOQ: UNderstanding coherence in Light-matter interfaces for Quantum Science (Final Technical Report)

The general goal of this project is to prepare next-generation quantum systems for novel quantum information science applications. Decades of research on quantum optics have provided revolutionary systems for manipulating atomic and photonic quantum coherence in transformative ways. Our hypothesis is that the next-generation quantum systems will come from nano-molecular quantum optics. Specifically, we are interested in coupling the electronic states of molecules or nanoparticles to the quantized radiation field inside an optical cavity to create a set of new photon-matter hybrid excitations, called polaritons. As opposed to atoms, the vibrational modes of molecules and nanoparticles provide new degrees of freedom to mediate the quantum transduction between electronic and photonic states, offering new ways to tune and ultimately control the quantum coherence of the integrated system. In this project we are interested in designing, fabricating, and characterizing the polaritons that arise from coupling CdSe nanoplatelets (NPLs) to a Fabry-Pérot optical cavity. Specific attention was paid to parameters of the system (cavity mode volume, quality factor, etc.) that would maximize the collective coupling strength. Through a combined theoretical and experimental approach, we were able to make important contributions to understanding NPL exciton-polariton photophysics including how to use cavity loss as a tunable parameter in order to manipulate the populations of the upper and lower polariton states. Finally, using state-of-the-art theoretical methods, we were able to show how the collective coupling of many molecular excitons in a cavity can protect polariton coherence from vibrationally-induced decoherence. In particular, for NPL-cavity polaritonic systems, the quantum coherence can be extended by over an order of magnitude at room temperature.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Grid Architecture Mapping to Understand Transformation (GAMUT): Methods and Framework Architecture

Grid architecture (GA) is a concept that was developed to address the need for a comprehensive view of power grid challenges. GA can be viewed as a relatively consistent and fixed high-level approach; however, for any instantiation of grid structures, a combinatorial explosion results from each lower-layer expansion. This constitutes the main challenge with GA—it is a grid architect’s view of the system, which might not be very informative at the implementation level. Grid Architecture Mapping to Understand Transformation (GAMUT project) seeks to bridge that gap by integrating subject matter expertise across GA structures, providing users who lack expertise in GA approaches with valuable insights and informational materials. GAMUT seeks to answer feasibility questions for the approach. System-level expectations are that a GA baseline needs to be established in order for GA to be the common framework to which any lower layer approach is tied. This report explores a potential information ingestion and documentation framework to support GAMUT. The main concepts that enable the solution domain of GAMUT are discussed, and examples are provided. The solution domain leverages already-existing technology and concepts related to GA, knowledge management, and other relevant areas. To assess GAMUT building blocks and the overall approach, a feasibility assessment is proposed, rooted in systems engineering and GA architecture evaluation concepts.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Formation of Zeolites Responsible for Waste Glass Rate Acceleration: An Experimental and Computational Study for Understanding Thermodynamic and Kinetic Processes

This report summarizes work on the NEUP Project 18-15496, DE-NE0008774 (Formation of Zeolites Responsible for Waste Glass Rate Acceleration: An Experimental and Computational Study for Understanding Thermodynamic and Kinetic Processes). The content of the report is from four journal articles that resulted from work on the project.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2018

Design Principles of Microbial Communities: From Understanding to Engineering

The goal of this thematic issue is to provide an overview of advances in fundamental and applied research on microbial communities - advances that promote our understanding of the design principles of microbial interactions. The three papers in this issue address this goal by providing focused reviews on the following key science topics: 1) the resistome, which is the collection of all genes and their precursors involved in antibiotic resistance; 2) community metabolic network modeling; and 3) synthesis of model consortia

Song, Hyun-Seob↗
DOE OSTI2024

UPGRADE-E: Understanding Patterns Guiding Residential Adoption and Decisions about Energy Efficiency

This work represents the largest and most comprehensive dataset to-date of responses surveyed from U.S. residents regarding home modifications and energy-related decision-making, including both objective measures describing the occupants and their homes and subjective measures describing the more unpredictable human factors behind residential decision-making. First, to develop the survey, we interviewed 121 individual decision-makers within their households regarding planned or completed projects. We used the insights of these interviews to design a survey that was distributed to 10,000 households across the U.S. The overarching topics approached in the survey include descriptive information about the respondent, their household, their home, home modifications they have made, and the human cognition-based contextual factors involved in home projects and decision-making, such as preferences, motivations, barriers, and information sources. The processed data from the survey was compiled into a dataset entitled UPGRADE-E: Understanding Patterns Guiding Residential Adoption and Decisions about Energy Efficiency and represents the basis for the analyses included in this paper. The dataset represents a rich repository of home energy technology and modification decision-making results, the largest of its kind to-date. The abundance of contextual considerations within this dataset provides a robust resource for continual analysis, with possibilities for considering cross-cuts of data from a variety of perspectives.

Fuentes, Tracy L↗
DOE OSTI2024

Understanding Generative AI Content with Embedding Models

The construction of high-quality numerical features is critical to any quantitative data analysis. Feature engineering has been historically addressed by carefully hand-crafting data representations based on domain expertise. This work views the internal representations of modern deep neural networks (DNNs), called embeddings, as an implicit form of traditional feature engineering. For trained DNNs, we show that these embeddings can reveal interpretable, high-level concepts in unstructured sample data. We use these embeddings in natural language and computer vision tasks to uncover both inherent heterogeneity in the underlying data and human-understandable explanations for it. In particular, we find empirical evidence that there is inherent separability between real data and those generated from AI models.

Vargas, Max↗