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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 1,351 records · Page 75
All sourcesNASA NTRSDOE OSTI
NASA NTRS2007

Preliminary Investigation of Curved Liner Sample in the NASA LaRC Curved Duct Test Rig

This viewgraph presentation reviews the preliminary investigation of the curved liner sample in the NASA LaRC Curved Duct Test Rig (CDTR). It reviews the purpose of the Curved Duct Test Rig. Its purpose is to develop capability to investigate acoustic and aerodynamic properties in ducts. It has several features to accomplish that purpose: (1) Large scale (2) Flow rate to M = 0.275 (3) Higher order mode control (4) Curved flow path (5) Adaptable test section (6) Flexible test configurations. The liner has minimal effect on turbulence or boundary layer growth in duct. The curved duct sample attenuation is affected by mode scattering. In conclusion, the CDTR is valid tool for aerodynamic and acoustic evaluation of duct treatment

Gerhold, Carl H.↗
NASA NTRS2011

Browsing Space Weather Data and Models with the Integrated Space Weather Analysis (iSWA) System

The Integrated Space Weather Analysis (iSWA) System is a comprehensive web-based platform for space weather information that combines data from solar, heliospheric and geospace observatories with forecasts based on the most advanced space weather models. The iSWA system collects, generates, and presents a wide array of space weather resources in an intuitive, user-configurable, and adaptable format - thus enabling users to respond to current and future space weather impacts as well as enabling post-impact analysis. iSWA currently provides over 200 data and modeling products, and features a variety of tools that allow the user to browse, combine, and examine data and models from various sources. This presentation will consist of a summary of the iSWA products and an overview of the customizable user interfaces, and will feature several tutorial demonstrations highlighting the interactive tools and advanced capabilities.

Maddox, Marlo M.↗
NASA NTRS2011

Consequences of the Breakout Model for Particle Acceleration in CMEs and Flares

The largest and most efficient particle accelerators in the solar system are the giant events consisting of a fast coronal mass ejection (CME) and an intense X-class solar flare. Both flares and CMEs can produce l0(exp 32) ergs or more in nonthermal particles. Two general processes are believed to be responsible: particle acceleration at the strong shock ahead of the CME, and reconnection-driven acceleration in the flare current sheet. Although shock acceleration is relatively well understood, the mechanism by which flare reconnection produces nonthermal particles is still an issue of great debate. We address the question of CME/flare particle acceleration in the context of the breakout model using 2.5D MHD simulations with adaptive mesh refinement (AMR). The AMR capability allows us to achieve ultra-high numerical resolution and, thereby, determine the detailed structure and dynamics of the flare reconnection region. Furthermore, we employ newly developed numerical analysis tools for identifying and characterizing magnetic nulls, so that we can quantify accurately the number and location of magnetic islands during reconnection. Our calculations show that flare reconnection is dominated by the formation of magnetic islands. In agreement with many other studies, we find that the number of islands scales with the effective Lundquist number. This result supports the recent work by Drake and co-workers that postulates particle acceleration by magnetic islands. On the other hand, our calculations also show that the flare reconnection region is populated by numerous shocks and other indicators of strong turbulence, which can also accelerate particles. We discuss the implications of our calculations for the flare particle acceleration mechanism and for observational tests of the models.

Antiochos, S. K.↗
NASA NTRS2012

Cloud Computing for Mission Design and Operations

The space mission design and operations community already recognizes the value of cloud computing and virtualization. However, natural and valid concerns, like security, privacy, up-time, and vendor lock-in, have prevented a more widespread and expedited adoption into official workflows. In the interest of alleviating these concerns, we propose a series of guidelines for internally deploying a resource-oriented hub of data and algorithms. These guidelines provide a roadmap for implementing an architecture inspired in the cloud computing model: associative, elastic, semantical, interconnected, and adaptive. The architecture can be summarized as exposing data and algorithms as resource-oriented Web services, coordinated via messaging, and running on virtual machines; it is simple, and based on widely adopted standards, protocols, and tools. The architecture may help reduce common sources of complexity intrinsic to data-driven, collaborative interactions and, most importantly, it may provide the means for teams and agencies to evaluate the cloud computing model in their specific context, with minimal infrastructure changes, and before committing to a specific cloud services provider.

cloud computing↗
NASA NTRS2024

Development of a Single Level Assessment Module for Simulating the Human Factors Concept Trade Space

This paper is a synopsis of the design and development of the Single Level Assessment Module (SLAM), a habitation mockup aimed at simulating volumetric conditions for astronauts in transit to Mars. Utilizing repurposed materials to enable low cost and constrained by various other design requirements from its parent vehicle, the SLAM embodies a critical step towards understanding human/habitat dynamics and interactions within the framework of the Mars Transit Habitat (TH) concept trade space. The synopsis begins by outlining the design constraints and goals, focusing on material availability and functional area volume requirements. Through various 3D design solutions, the SLAM emerges as a versatile habitat prototype, capable of accommodating various functional areas within its reconfigurable framework. The construction phase is then explored, highlighting the practical challenges and solutions encountered in assembling the SLAM's components. From panel assembly to outfitting functional areas, the construction process demonstrates a methodical approach to realizing the habitat's design intent. Looking ahead, the paper outlines future work, emphasizing the SLAM's adaptability for analysis and its potential to inform the design trade space future habitation concepts across the Moon to Mars architecture. By incorporating hinges for reconfigurability and facilitating volume assessments, the SLAM emerges as a crucial tool in advancing NASA’s ability to assess focused habitation configurations in conjunction with the development of the Moon to Mars architecture. In conclusion, this paper showcases the iterative process of habitat design, from conceptualization to construction.

Keith Lindsey↗
NASA NTRSDate not supplied

Sonic Boom Ground Noise Minimization Via the Adjoint Method

A multidisciplinary design optimization methodology to directly minimize the ground-level noise generated by the sonic boom of a high altitude supersonic body is presented. A Cartesian Euler flow solver is coupled with an atmospheric propagation tool to create a ground-noise analysis capability for supersonic bodies. Adjoint formulations for both the flow solver and propagation tool are also coupled to compute sensitivities of shape variations in the body in a highly efficient manner. A gradient-based optimizer is then introduced to forge a valuable design capability. Output-based mesh adaptation that is driven directly by ground-level noise is employed to increase accuracy and provide error estimation. The design method is demonstrated first on a simple axisymmetric body with few design variables to evaluate the efficacy of the optimization scheme. Guided by the results of this initial case, the problem is then repeated with somewhat different design variables to further demonstrate the capabilities of the design method. Finally, the method is applied to a real-world problem by optimizing control surface deflection settings of a low-boom aircraft to minimize ground noise while maintaining trimmed, level flight.

ARMD↗
DOE OSTI2023

A New Reflected Target Optical Assessment System - Stage 1 Development Results: Preprint

NREL has completed stage 1 development of an indoor optical measurement tool for fully assembled heliostats and single facets. This tool began as an indoor version of NREL's NIO technique. It uses similar techniques to other available tools (deflectometry, photogrammetry, etc.), but is designed require very little infrastructure, labor, and time to set up and collect surface slope and canting measurements on fully assembled heliostats and parabolic trough facets, making it a valuable tool for quality assurance and laboratory measurement of helio-stat optics. It accomplishes this by using computer vision, photogrammetry, and multiple images stitched together to minimize the printed target size and required setup precision. This adaptable setup is useful for taking measurements at a variety of heliostat pointing angles, and for measuring fully assembled heliostats on the assembly line. The measurement system's methodology and an analysis of its uncertainty, sensitivity and comparison with established optical measurement systems is described below.

canting↗
DOE OSTI2023

Are long-term climate projections useful for on-farm adaptation decisions?

The current literature on climate services for farmers predominantly focuses on seasonal forecasts, with an assumption that longer-term climate projections may not be suitable for informing farming decisions. In this paper, we explore whether certain types of long-term climate projections may be useful for some specific types of farming decisions. Through interviews with almond tree crop farmers and farm advisors in California, we examine how farmers perceive the utility and accuracy levels of long-term climate projections and identify the types of projections that they may find useful. The interviews revealed that farmers often perceive long-term climate projections as an extension of weather forecasts, which can lead to their initial skepticism of the utility of such information. However, we also found that when farmers were presented with long-term trends or shifts in crop-specific agroclimatic metrics (such as chill hours or summer heat), they immediately perceived these as valuable for their decision-making. Hence, the manner in which long-term projections are framed, presented, and discussed with farmers can heavily influence their perception of the potential utility of such projections. The iterative conversations as part of the exploratory interview questions, served as a tool for “ joint construction of meaning” of complex and ambiguous terms such as “long-term climate projections,” “long-term decisions” and “uncertainty.” This in-turn supported a joint identification (and understanding) of the types of information that can potentially be useful for on-farm adaptive decisions, where the farmer and the interviewer both improvise and iterate to find the best types of projections that fit specific decision-contexts. Overall, this research identifies both the types of long-term climate information that farmers may consider useful, and the engagement processes that are able to effectively elicit farmers' long-term information needs.

Jagannathan, Kripa↗
DOE OSTI2016

MO-E-BRC-00: Online Adaptive Radiotherapy - Considerations for Practical Clinical Implementation

Online adaptive radiation therapy has the potential to ensure delivery of optimal treatment to the patient by accounting for anatomical and potentially functional changes that occur from one fraction to the next and over the course of treatment. While on-line adaptive RT (ART) has been a topic of many publications, discussions, and research, it has until very recently remained largely a concept and not a practical implementation. However, recent advances in on-table imaging, use of deformable image registration for contour generation and dose tracking, faster and more efficient plan optimization, as well as fast quality assurance method has enabled the implementation of ART in the clinic in the past couple of years. The introduction of these tools into routine clinical use requires many considerations and progressive knowledge to understand how processes that have historically taken hours/days to complete can now be done in less than 30 minutes. This session will discuss considerations to perform real time contouring, planning and patient specific QA, as well as a practical workflow and the required resources. Learning Objectives: To understand the difficulties, challenges and available technologies for online adaptive RT. To understand how to implement online adaptive therapy in a clinical environment and to understand the workflow and resources required. To understand the limitations and sources of uncertainty in the online adaptive process I have research funding from ViewRay Inc. and Philips Medical Systems.; R. Kashani, I have research funding from ViewRay Inc. and Philips Medical Systems.; X. Li, Research supported by Elekta Inc.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

MO-E-BRC-01: Online Adaptive MR-Guided RT: Workflow and Clinical Implementation

Online adaptive radiation therapy has the potential to ensure delivery of optimal treatment to the patient by accounting for anatomical and potentially functional changes that occur from one fraction to the next and over the course of treatment. While on-line adaptive RT (ART) has been a topic of many publications, discussions, and research, it has until very recently remained largely a concept and not a practical implementation. However, recent advances in on-table imaging, use of deformable image registration for contour generation and dose tracking, faster and more efficient plan optimization, as well as fast quality assurance method has enabled the implementation of ART in the clinic in the past couple of years. The introduction of these tools into routine clinical use requires many considerations and progressive knowledge to understand how processes that have historically taken hours/days to complete can now be done in less than 30 minutes. This session will discuss considerations to perform real time contouring, planning and patient specific QA, as well as a practical workflow and the required resources. Learning Objectives: To understand the difficulties, challenges and available technologies for online adaptive RT. To understand how to implement online adaptive therapy in a clinical environment and to understand the workflow and resources required. To understand the limitations and sources of uncertainty in the online adaptive process I have research funding from ViewRay Inc. and Philips Medical Systems.; R. Kashani, I have research funding from ViewRay Inc. and Philips Medical Systems.; X. Li, Research supported by Elekta Inc.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

MO-E-BRC-02: MRI-Guided Online Adaptive Radiotherapy: The UCLA Approach to Quality Management

Online adaptive radiation therapy has the potential to ensure delivery of optimal treatment to the patient by accounting for anatomical and potentially functional changes that occur from one fraction to the next and over the course of treatment. While on-line adaptive RT (ART) has been a topic of many publications, discussions, and research, it has until very recently remained largely a concept and not a practical implementation. However, recent advances in on-table imaging, use of deformable image registration for contour generation and dose tracking, faster and more efficient plan optimization, as well as fast quality assurance method has enabled the implementation of ART in the clinic in the past couple of years. The introduction of these tools into routine clinical use requires many considerations and progressive knowledge to understand how processes that have historically taken hours/days to complete can now be done in less than 30 minutes. This session will discuss considerations to perform real time contouring, planning and patient specific QA, as well as a practical workflow and the required resources. Learning Objectives: To understand the difficulties, challenges and available technologies for online adaptive RT. To understand how to implement online adaptive therapy in a clinical environment and to understand the workflow and resources required. To understand the limitations and sources of uncertainty in the online adaptive process I have research funding from ViewRay Inc. and Philips Medical Systems.; R. Kashani, I have research funding from ViewRay Inc. and Philips Medical Systems.; X. Li, Research supported by Elekta Inc.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

MO-E-BRC-03: Fast Online Replanning Techniques

Online adaptive radiation therapy has the potential to ensure delivery of optimal treatment to the patient by accounting for anatomical and potentially functional changes that occur from one fraction to the next and over the course of treatment. While on-line adaptive RT (ART) has been a topic of many publications, discussions, and research, it has until very recently remained largely a concept and not a practical implementation. However, recent advances in on-table imaging, use of deformable image registration for contour generation and dose tracking, faster and more efficient plan optimization, as well as fast quality assurance method has enabled the implementation of ART in the clinic in the past couple of years. The introduction of these tools into routine clinical use requires many considerations and progressive knowledge to understand how processes that have historically taken hours/days to complete can now be done in less than 30 minutes. This session will discuss considerations to perform real time contouring, planning and patient specific QA, as well as a practical workflow and the required resources. Learning Objectives: To understand the difficulties, challenges and available technologies for online adaptive RT. To understand how to implement online adaptive therapy in a clinical environment and to understand the workflow and resources required. To understand the limitations and sources of uncertainty in the online adaptive process I have research funding from ViewRay Inc. and Philips Medical Systems.; R. Kashani, I have research funding from ViewRay Inc. and Philips Medical Systems.; X. Li, Research supported by Elekta Inc.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

pystorms: A simulation sandbox for the development and evaluation of stormwater control algorithms

Advances in cyber–physical technologies have enabled real-time sensing and adaptive control of stormwater infrastructure. These smart stormwater systems allow for inexpensive, minimally-invasive stormwater control interventions in lieu of new construction. Importantly, however promising the area of smart stormwater control, there still remain barriers – for experts and novices alike – to access shared tools and methods for investigating, developing, and contributing to it. In an effort to make smart stormwater control research more methodical and accessible, we present pystorms, an open-source Python-based simulation sandbox that facilitates the quantitative evaluation and comparison of control strategies. pystorms consists of a collection of real world-inspired smart stormwater control scenarios on which any number of control strategies can be applied and tested via an accompanying Python programming interface and coupled stormwater simulator. pystorms provides a framework for the rigorous and efficient evaluation of smart stormwater control methodologies across diverse watersheds with only a few lines of code.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

SU-E-E-07: An Adaptable Approach for Education On Medical Physics at Undergraduate and Postgraduate Levels

Purpose: To contribute to the professional profile of future medical physicists, technologists and physicians, and implement an adaptable educational strategy at both undergraduate and postgraduate levels. Methods: The Medical Physics Block of Electives (MPBE) designed was adapted to the Program of B.S. in Physics. The conferences and practical activities were developed with participatory methods, with interdisciplinary collaboration from research institutions and hospitals engaged on projects of Research, Development and Innovation (RDI). The scientific education was implemented by means of critical analysis of scientific papers and seminars where students debated on solutions for real research problems faced by medical physicists. This approach included courses for graduates not associated to educational programs of Medical Physics (MP). Results: The implementation of the MPBE began in September 2014, with the electives of Radiation MP and Introduction to Nuclear Magnetic Resonance. The students of second year received an Introduction to MP. This initiative was validated by the departmental Methodological Workshop, which promoted the full implementation of the MPBE. Both postgraduated and undergraduate trainees participated in practices with our DICOM viewer system, a local prototype for photoplethysmography and a home-made interface for ROC analysis, built with MATLAB. All these tools were designed and constructed in previous RDI projects. The collaborative supervision of University’s researchers with clinical medical physicists will allow to overcome the limitations of residency in hospitals, to reduce the workload for clinical supervisors and develop appropriate educational activities. Conclusion: We demonstrated the feasibility of adaptable educational strategies, considering available resources. This provides an innovative way for prospective medical physicists, technologists and radiation oncologists. This strategy can be implemented in several regions without formal programs of MP, like most of developing countries. Starting with undergraduate students would allow to reach appropriate certification faster than most of traditional or alternative approaches for education on MP. The authors acknowledge Radiation Consulting Group, LLC, an Arizona Corporation which promotes the use of ionizing radiation in the healing arts, for the “Oscar Luis Caballero” travel grant. The authors thanks to professors Meisbel Daudinot, David Adame and Alexander Pascau for the practices through imagis, imageROC and ANGIODIN PD3000 respectively.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Editorial: Genomic insights on fungal hybrids

Hybrids are chimeric organisms that result from the crossing of two genetically divergent lineages. Compared to their parents, hybrids sometimes show higher adaptive capacities towards specific niches, thereby contributing to diversification (Abbott et al., 2013). Fungal hybrids have been neglected by formal studies for a long time due to the inherent challenges of the microbial species concept and the difficulty of identifying hybrids based on morphological characters (Gabaldon, 2020a; Boekhout et al., 2021). Although the first fungal hybrids were identified in Saccharomyces, thanks to careful dissection of metabolic properties (Morales and Dujon, 2012) and emerging genome sequencing technologies (Hittinger, 2013), it was the spread of these sequencing technologies that revealed the true pervasiveness of hybrids across the fungal tree of life (Naranjo-Ortiz and Gabaldon, 2020; Gabaldon, 2020b). Sequencing techniques, particularly genomic approaches, have not only unearthed the hybrid nature of many fungal organisms, but also serve as ideal tools for the study of hybrids. Hybrids have chimeric genomes, which usually display high instability and are subject to evolutionary pressures that are different from that of non-hybrid genomes (Runemark et al., 2019). Understanding how hybrids are formed, how they cope with their chimeric genomes, and how they evolve and adapt to distinct environments is a matter of intensive research. This Research Topic gathers six outstanding contributions that use genomic approaches to tackle diverse questions that relate to fungal hybrids.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2013

Cross-validation based single response adaptive design of experiments for Kriging metamodeling of deterministic computer simulations

A new approach for single response adaptive design of deterministic computer experiments is presented. The approach is called SFCVT, for Space-Filling CrossValidation Tradeoff. SFCVT uses metamodeling to obtain an estimate of cross-validation errors, which are maximized subject to a constraint on space filling to determine sample points in the design space. The proposed method is compared, using a test suite of forty four numerical examples, with three DOE methods from the literature. The numerical test examples can be classified into symmetric and asymmetric functions. Symmetric examples refer to functions for which the extreme points are located symmetrically in the design space and asymmetric examples are those for which the extreme regions are not located in a symmetric fashion in the design space. Based upon the comparison results for the numerical examples, it is shown that SFCVT performs better than an existing adaptive and a non-adaptive DOE method for asymmetric multimodal functions with high nonlinearity near the boundary, and is comparable for symmetric multimodal functions and other test problems. The proposed approach is integrated with a multi-scale heat exchanger optimization tool to reduce the computational effort involved in the design of novel air-to-water heat exchangers. In conclusion, the resulting designs are shown to be significantly more compact than mainstream heat exchanger designs.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Utilizing plant synthetic biology to accelerate plant-microbe interactions research

Plant-microbe interactions are critical to ecosystem resilience and substantially influence crop production. From the perspective of plant science, two important focus areas concerning plant-microbe interactions include: 1) understanding plant molecular mechanisms involved in plant-microbe interfaces and 2) engineering plants for increasing plant disease resistance or enhancing beneficial interactions with microbes to increase their resilience to biotic and abiotic stress conditions. Molecular biology and genetics approaches have been used to investigate the molecular mechanisms underlying plant responses to various beneficial and pathogenic microbes. While these approaches are valuable for elucidating the functions of individual genes and pathways, they fall short of unraveling the complex cross-talk across pathways or systems that plants employ to respond and adapt to environmental stresses. Also, genetic engineering of plants to increase disease resistance or enhance symbiosis with microbes has mainly been attempted or conducted through targeted manipulation of single genes/pathways of plants. Recent advancements in synthetic biology tool development are paving the way for multi-gene characterization and engineering in plants in relation to plant-microbe interactions. Here, we briefly summarize the current understanding of plant molecular pathways involved in plant interactions with beneficial and pathogenic microorganisms. Then, we highlight the progress in applying plant synthetic biology to elucidate the molecular basis of plant responses to microbes, enhance plant disease resistance, engineer synthetic symbiosis, and conduct in situ microbiome engineering. Lastly, we discuss the challenges, opportunities, and future directions for advancing plant-microbe interactions research using the capabilities of plant synthetic biology.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Understanding the Physics Representation of Deep Learning Models in Environmental Applications

Deep learning (DL) models have been popular in earth and environmental modeling and analysis, which exhibit huge potential in capturing and reconstructing the non-linearity of relevant environmental processes. They are extensively used as analytical tools or emulators for multiple domains (atmosphere, land surface, ocean, and biogeochemistry). Despite their success, their internal working mechanism remains largely unknown. Such a lack of knowledge hinders the identification of physically consistent models that are fully adaptive to non-stationary climate, as well as the development of physics-informed machine learning such as physics-informed neural network (PINN). To establish preliminary knowledge and framework of such physics representation evaluation, this project focuses on an improved understanding of DL models in the environmental applications. DL models are increasingly applied to environmental modeling and prediction. However, they have been evaluated mostly from a performance perspective, and there is a gap in understanding how they represent the known physics internally. Such knowledge is especially critical when applying DL models under climate change conditions, where new inputs are likely outside the ranges of the training datasets. In this project, we reveal how the known physical processes are represented within DL models from both statistical and mechanistic perspectives. Leveraging the traditional model evaluations that focus more on the accuracies of predictions, we establish a framework that examines both the accuracy and physics representation of DL models. This analysis framework can identify DL models that make the correct predictions based on correct physics, thus enhancing the existing explainable artificial intelligence (explainable-AI) portfolio. It lays a foundation for developing novel metrics to evaluate the emerging DL models in environmental applications. This knowledge also informs the development of physics-informed DL models by revealing the direct connections between the known physical processes and specific model components or structures.

54 ENVIRONMENTAL SCIENCES↗