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At least 1,531 records · Page 85

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NASA NTRS1991

Advanced electromagnetic methods for aerospace vehicles

During this period the research program addressed the following three topics: (1) composite materials; (2) precipitation static (P-Static); and (3) antenna technology. On the topic of Composite Materials our main efforts were directed toward making measurements on several new samples of composite materials made available to ASU by Stanford Research Institute (SRI) through the efforts of Mr. Frank Casler of AVRADA. These samples can be classified into three distinct materials with each material having its own distinct electrical properties. In addition, attempts were made to make predictions of the effects on antenna patterns by composite materials. This will take a greater emphasis in the next reporting period. In Precipitation Static (P-Static), the main effort was devoted toward developing a Voltage Finite-Difference Time-Domain computer code to account for the voltage variation on a conducting body as the primary source of corona discharge, instead of the electric field. Due to complexities stemming from the interactions between the potentials, the fields, and current sources, the decision was made to begin with a simple two-dimensional problem without the corona discharge and check our programs in a series of simple models, culminating in the full corona discharge problem. This report deals with the first stage of such development. During this reporting period, the main effort in Antenna Technology was toward the design, fabrication, and testing of a cavity-backed slot antenna using ferrite material. Using the ferrite material available to us during this period, the resonances of this antenna were around 5 and 8 GHz. Attempts will be made to model such an antenna and to lower its resonance down into the VHF and UHF bands.

Balanis, Constantine A.↗

NASA NTRS1993

Wind erosion in semiarid landscapes: Predictive models and remote sensing methods for the influence of vegetation

The objectives of this research are: to develop and test predictive relations for the quantitative influence of vegetation canopy structure on wind erosion of semiarid rangeland soils, and to develop remote sensing methods for measuring the canopy structural parameters that determine sheltering against wind erosion. The influence of canopy structure on wind erosion will be investigated by means of wind-tunnel and field experiments using structural variables identified by the wind-tunnel and field experiments using model roughness elements to simulate plant canopies. The canopy structural variables identified by the wind-tunnel and field experiments as important in determining vegetative sheltering against wind erosion will then be measured at a number of naturally vegetated field sites and compared with estimates of these variables derived from analysis of remotely sensed data.

Musick, H. Brad↗

NASA NTRS1998

Visual Methods for Model and Grid Validation

This joint research interchange proposal allowed us to contribute in two directions that are of interest to NASA. These are: (a) data level comparative visualization of experimental and computational fluid flow, and (b) visualization tools for analysis of adaptively refined Cartesian grids.

Pang, Alex↗

NASA NTRS1961

Considerations of Methods of Improving Helicopter Efficiency

Recent NASA helicopter research indicates that significant improvements in hovering efficiency, up to 7 percent, are available from the use of a special airfoil section formed by combining an NACA 632A015 thickness distribution with an NACA 230 mean line. This airfoil should be considered for flying-crane-type helicopters. Application of standard leading-edge roughness causes a large drop in efficiency; however, the cambered rotor is shown to retain its superiority over a rotor having a symmetrical airfoil when both rotors have leading-edge roughness. A simple analysis of available rotor static-thrust data indicates a greatly reduced effect of compressibility effects on the rotor profile-drag power than predicted from calculations. Preliminary results of an experimental study of helicopter parasite drag indicate the practicability of achieving an equivalent flat-plate parasite-drag area of less than 4 square feet for a rotor-head-pylon-fuselage configuration (landing gear retracted) in the 2,000-pound minimum-flying-weight class. The large drag penalty of a conventional skid-type landing (3.6 square feet) can be reduced by two-thirds by careful design. Clean, fair, and smooth fuselages that tend to have narrow, deep cross sections are shown to have advantages from the standpoint of drag and download. A ferry range of the order of 1,500 miles is indicated to be practicable for the small helicopter considered.

Dingeldein, Richard C.↗

NASA NTRS2017

Benefits of International Collaboration on the International Space Station

The International Space Station is a valuable platform for research in space, but the benefits are limited if research is only conducted by individual countries. Through the e orts of the ISS Program Science Forum, international science working groups, and interagency cooperation, international collaboration on the ISS has expanded as ISS utilization has matured. Members of science teams benefit from working with counterparts in other countries. Scientists and institutions bring years of experience and specialized expertise to collaborative investigations, leading to new perspectives and approaches to scientific challenges. Combining new ideas and historical results brings synergy and improved peer-reviewed scientific methods and results. World-class research facilities can be expensive and logistically complicated, jeopardizing their full utilization. Experiments that would be prohibitively expensive for a single country can be achieved through contributions of resources from two or more countries, such as crew time, up- and downmass, and experiment hardware. Cooperation also avoids duplication of experiments and hardware among agencies. Biomedical experiments can be completed earlier if astronauts or cosmonauts from multiple agencies participate. Countries responding to natural disasters benefit from ISS imagery assets, even if the country has no space agency of its own. Students around the world participate in ISS educational opportunities, and work with students in other countries, through open curriculum packages and through international competitions. Even experiments conducted by a single country can benefit scientists around the world, through specimen sharing programs and publicly accessible \open data" repositories. For ISS data, these repositories include GeneLab, the Physical Science Informatics System, and different Earth science data systems. Scientists can conduct new research using ISS data without having to launch and execute their own experiments. Multilateral collections of research results publications, maintained by the ISS international partnership and accessible via nasa.gov, make ISS results available worldwide, and encourage new users, ideas and research. The paper explores effectiveness of international collaboration in the course of the ISS Program execution. The collaboration history, its evolution and maturation, change of focus during its different phases, and growth of its effectiveness (in accordance with the especially established criteria) are also considered in the paper in the light of benefits for the entire ISS community. With the International Space Station extended through at least 2024, more crew time becoming available and new facilities arriving on board the ISS, these benefits of international scientific collaboration on the ISS can only increase.

Robinson, Julie A.↗

DOE OSTI2021

Considerations regarding the Use of Computer Vision Machine Learning in Safety-Related or Risk-Significant Applications in Nuclear Power Plants

With the advancements made to date in the field of artificial intelligence (AI), significant potential exists to utilize AI capabilities for nuclear power plant (NPP) applications. AI can replicate human decision making and it is usually faster and more accurate than humans. For implementations that impact critical NPP applications (e.g., safety-related or non-safety systems that potentially affect overall plant risk), a deeper safety analysis of the AI methods is necessary. AI applied to NPP operations could resemble the use of digital I&C (DI&C) because such applications involve digital computer hardware and custom-designed software that input plant data, execute complex software algorithms, and output the results to a system or licensed human operator to potentially provoke an action. For AI methods to be compliant with current safety requirements for DI&C, AI compatibility must be evaluated, and AI-related gaps may exist that prevent the prompt deployment of AI in NPPs. This effort aims to evaluate how example AI technologies align with the DI&C safety framework, and discusses how they could be analyzed, modeled, tested, and validated in a manner similar to typical DI&C technologies. Because AI is a broad field that encompasses areas such as machine learning (ML), natural language processing, and computer vision, this research focused on a subset of methods categorized as the computer vision ML (CVML) methods. This report explores two CVML use cases, gauge reading and fire watch, considered relevant to the DI&C standards, as they could play a safety-critical role. For the gauge reading use case, a CVML-enabled technology that can read gauges at oblique angles is utilized. For the fire watch use case, a CVML-enabled technology is utilized that migrates fire watch from a manual (human) approach to automated fire detection. These use cases are mainly intended to give context to the CVML system discussion. This effort assumes the worst-case scenario, with the CVML system being used to replace a safety-related or risk-significant system, thus requiring evaluation. Evaluating CVML against most of the relevant safety requirements for DI&C yielded several CVML-specific considerations due to the uniqueness of its characteristics in comparison with typical DI&C systems. For example, CVML models often employ commonly used (open-source) datasets, and it is not always possible to determine the level of overlap among open-source datasets. Therefore, the independence of the developed CVML models when demonstrating diversity is questionable, therefore creating vulnerability to common cause failure (CCF). The design verification process is also impacted since the data overlap could result in overestimation of the software validation and verification (V&V) performance results. Section 2 of this report evaluates a list of the identified CVML-specific characteristics and discusses the resulting considerations and potential solutions in the context of each referenced requirement. A summation is provided in Section 3. This report is not to be used as a guideline. It was developed to identify and consider issues in the implementation of ML technologies used to augment activities that may have a bearing on plant operation. The report draws parallels to the use of DI&C technologies, for which many standards are available to guide their use in nuclear plant operation. It considers the technologies and some of the potential implications of their use in safety-related applications but is not intended to address regulatory or licensing related issues.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2023

The inclusion of uncertainty in circularity transition modeling: A case study on wind turbine blade end-of-life management

The transition to a more circular economy (CE) is complex and hard to predict, including in sustainable energy technologies. Many sources of uncertainty make it challenging to model CE scenarios and their potential benefits. As an example, the high variability in costs and revenues of different recycling options makes future wind turbine blade recycling highly uncertain. To better understand this challenge, the circular economy, life cycle assessment and visualization (CELAVI) framework - a discrete event simulation and life cycle assessment framework - is modified to incorporate uncertainty analysis capabilities. Moreover, a 3-step procedure that covers different aspects of uncertainty in CE studies and includes a Monte-Carlo analysis is proposed. The procedure is tested in a case study on wind turbine blade recycling using CELAVI. Results highlight that grinding and landfilling costs are the most influential parameters for wind power circularity. The model's output coefficients of variation (when input parameter uncertainties are propagated) are between 92% and 384% depending on the indicator. The approach developed in this study may help researchers and decision-makers who study circularity prioritize their data collection effort. Finally, our method contributes to a mounting yet critical body of research: the measurement of uncertainty in circularity transitions.

17 WIND ENERGY↗

NASA NTRS1986

ECUT (Energy Conversion and Utilization Technologies Program). Biocatalysis Project

Presented are the FY 1985 accomplishments, activities, and planned research efforts of the Biocatalysis Project of the U.S. Department of Energy, Energy Conversion and Utilization Technologies (ECUT) Program. The Project's technical activities were organized as follows: In the Molecular Modeling and Applied Genetics work element, research focused on (1) modeling and simulation studies to establish the physiological basis of high temperature tolerance in a selected enzyme and the catalytic mechanisms of three species of another enzyme, and (2) determining the degree of plasmid amplification and stability of several DNA bacterial strains. In the Bioprocess Engineering work element, research focused on (1) studies of plasmid propagation and the generation of models, (2) developing methods for preparing immobilized biocatalyst beads, and (3) developing an enzyme encapsulation method. In the Process Design and Analysis work element, research focused on (1) further refinement of a test case simulation of the economics and energy efficiency of alternative biocatalyzed production processes, (2) developing a candidate bioprocess to determine the potential for reduced energy consumption and facility/operating costs, and (3) a techno-economic assessment of potential advancements in microbial ammonia production.

Source record↗

DOE OSTI2023

Exploring Classification of Topological Priors With Machine Learning for Feature Extraction

In many scientific endeavors, increasingly abstract representations of data allow for new interpretive methodologies and conceptualization of phenomena. For example, moving from raw imaged pixels to segmented and reconstructed objects allows researchers new insights and means to direct their studies toward relevant areas. Thus, the development of new and improved methods for segmentation remains an active area of research. With advances in machine learning and neural networks, scientists have been focused on employing deep neural networks such as U-Net to obtain pixel-level segmentations, namely, defining associations between pixels and corresponding/referent objects and gathering those objects afterward. Topological analysis, such as the use of the Morse-Smale complex to encode regions of uniform gradient flow behavior, offers an alternative approach: first, create geometric priors, and then apply machine learning to classify. This approach is empirically motivated since phenomena of interest often appear as subsets of topological priors in many applications. Using topological elements not only reduces the learning space but also introduces the ability to use learnable geometries and connectivity to aid the classification of the segmentation target. Here, in this article, we describe an approach to creating learnable topological elements, explore the application of ML techniques to classification tasks in a number of areas, and demonstrate this approach as a viable alternative to pixel-level classification, with similar accuracy, improved execution time, and requiring marginal training data.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2023

Hybrid Particle Method for Computational Shock Physics

A long-standing area of research for Eulerian shock wave physics codes has been the treatment of strength and damage for materials. Here we present a method that will aid in the analysis of strength and failure in shock physics applications where excessive diffusion of critical variables can occur and control the solution outcome. Eulerian methods excel for large deformation simulations in general but are inaccurate in capturing structural behavior. Lagrangian methods provide better structural response, but finite element meshes can become tangled. Therefore, a technique for merging Lagrangian and Eulerian treatments of material response, within a single numerical framework, was implemented in the Multiple Component computational shock physics hydrocode. The capability is a Lagrangian/Eulerian Particle Method (LEPM) that uses particles to interface a Lagrangian treatment of material strength with a more traditional Eulerian treatment of the Equation of State (EOS). Lagrangian numerical methods avoid the advection diffusion found in Eulerian methods, which typically strongly affects strength constitutive law internal variables, such as equivalent plastic strain, porosity and/or damage. The Lagrangian capability enhances existing capabilities and permits accurate predictions of high rate, large deformation and/or shock of mechanical structures.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS2015

Multilateral Research Opportunities in Ground Analogs

The global economy forces many nations to consider their national investments and make difficult decisions regarding their investment in future exploration. International collaboration provides an opportunity to leverage other nations' investments to meet common goals. The Humans In Space Community shares a common goal to enable safe, reliable, and productive human space exploration within and beyond Low Earth Orbit. Meeting this goal requires efficient use of limited resources and International capabilities. The International Space Station (ISS) is our primary platform to conduct microgravity research targeted at reducing human health and performance risks for exploration missions. Access to ISS resources, however, is becoming more and more constrained and will only be available through 2020 or 2024. NASA's Human Research Program (HRP) is actively pursuing methods to effectively utilize the ISS and appropriate ground analogs to understand and mitigate human health and performance risks prior to embarking on human exploration of deep space destinations. HRP developed a plan to use ground analogs of increasing fidelity to address questions related to exploration missions and is inviting International participation in these planned campaigns. Using established working groups and multilateral panels, the HRP is working with multiple Space Agencies to invite International participation in a series of 30- day missions that HRP will conduct in the US owned and operated Human Exploration Research Analog (HERA) during 2016. In addition, the HRP is negotiating access to Antarctic stations (both US and non-US), the German :envihab and Russian NEK facilities. These facilities provide unique capabilities to address critical research questions requiring longer duration simulation or isolation. We are negotiating release of international research opportunities to ensure a multilateral approach to future analog research campaigns, hoping to begin multilateral campaigns in the latter facilities by 2017. Collaborative use of analog facilities and shared investment in the development of spaceflight countermeasures through multilateral campaigns or missions that leverage the global scientific community will focus high quality research and provide sufficient power to accelerate the development of countermeasures and drive sound recommendations for exploration missions. This panel will provide an overview of efforts to encourage and facilitate multilateral collaboration in analog missions or campaigns and describe the facilities currently under consideration to reach the common goal of enabling safe, reliable, and productive human space exploration.

Corbin, Barbara J.↗

DOE OSTI2021

Reliable Power Rating of Perovskite PV Modules

As the perovskite technology is ramping up into commercialization, reliable and accurate power rating of large-size perovskite modules becomes a prominent aspect for its future deployment in the PV market. It is known that the performance calibration of perovskite PV devices is very challenging due to its complex dynamic response during a conventional current-voltage (IV) measurement. PV researchers have previously proposed several steady-state performance calibration methods to reliably extract PV efficiencies, but mostly focus on small area research-type cells. In this paper, we emphasize the importance of reliable performance calibration on large-size perovskite modules. Extending the NREL Cell and Module Performance (CMP) group's steady-state performance calibration protocol (i.e., Asymptotic P MAX Scan) for perovskite cells to modules, we justify the necessity of reporting steady-state efficiencies for perovskite cells and discuss the challenges of applying this protocol to modules. We also present our protocol for Maximum Power Point Tracking (MPPT), which is a technique often used for performance calibration of perovskite cells and modules, and show a comparison between MPPT and Asymptotic P MAX . Using MPPT we demonstrate the interplay between metastability and degradation in perovskite modules, and emphasize the necessity to develop preconditioning protocols for stabilizing these devices. Our aim is to promote development of consensus protocols for performance calibration of perovskite modules, and to advance their credible power ratings, which will be beneficial to the growth of perovskite technology in the PV market.

perovskite↗

DOE OSTI2021

Reliable Power Rating of Perovskite PV Modules: Preprint

As the perovskite technology is ramping up into commercialization, reliable and accurate power rating of large-size perovskite modules becomes a prominent aspect for its future deployment in the PV market. It is known that the performance calibration of perovskite PV devices is very challenging due to its complex dynamic response during a conventional current-voltage (IV) measurement. PV researchers have previously proposed several steady-state performance calibration methods to reliably extract PV efficiencies, but mostly focus on small area research-type cells. In this paper, we emphasize the importance of reliable performance calibration on large-size perovskite modules. Extending the NREL Cell and Module Performance (CMP) group’s steady-state performance calibration protocol (i.e., Asymptotic PMAX Scan) for perovskite cells to modules, we justify the necessity of reporting steady-state efficiencies for perovskite cells and discuss the challenges of applying this protocol to modules. We also present our protocol for Maximum Power Point Tracking (MPPT), which is a technique often used for performance calibration of perovskite cells and modules, and show a comparison between MPPT and Asymptotic PMAX. Using MPPT we demonstrate the interplay between metastability and degradation in perovskite modules, and emphasize the necessity to develop preconditioning protocols for stabilizing these devices. Our aim is to promote development of consensus protocols for performance calibration of perovskite modules, and to advance their credible power ratings, which will be beneficial to the growth of perovskite technology in the PV market.

41 EE - Solar Energy Technologies Office (EE-4S)↗

NASA NTRS1983

Assessment of NASA and RAE viscous-inviscid interaction methods for predicting transonic flow over nozzle afterbodies

The Langley Research Center of the National Aeronautics and Space Administration and the Royal Aircraft Establishment have undertaken a cooperative program to conduct an assessment of their patched viscous-inviscid interaction methods for predicting the transonic flow over nozzle afterbodies. The assessment was made by comparing the predictions of the two methods with experimental pressure distributions and boattail pressure drag for several convergent circular-arc nozzle configurations. Comparisons of the predictions of the two methods with the experimental data showed that both methods provided good predictions of the flow characteristics of nozzles with attached boundary layer flow. The RAE method also provided reasonable predictions of the pressure distributions and drag for the nozzles investigated that had separated boundary layers. The NASA method provided good predictions of the pressure distribution on separated flow nozzles that had relatively thin boundary layers. However, the NASA method was in poor agreement with experiment for separated nozzles with thick boundary layers due primarily to deficiencies in the method used to predict the separation location.

Putnam, L. E.↗

NASA NTRS2000

Prediction of Hyper-X Stage Separation Aerodynamics Using CFD

The NASA X-43 "Hyper-X" hypersonic research vehicle will be boosted to a Mach 7 flight test condition mounted on the nose of an Orbital Sciences Pegasus launch vehicle. The separation of the research vehicle from the Pegasus presents some unique aerodynamic problems, for which computational fluid dynamics has played a role in the analysis. This paper describes the use of several CFD methods for investigating the aerodynamics of the research and launch vehicles in close proximity. Specifically addressed are unsteady effects, aerodynamic database extrapolation, and differences between wind tunnel and flight environments.

Buning, Pieter G.↗

DOE OSTI2025

Recent evolution of risk analyses in atomic bomb survivor studies: new methods and applications

Abstract Several decades ago a dramatic leap forward occurred in the development and application of statistical methods for modeling radiation risk at the Radiation Effects Research Foundation (RERF). Poisson regression analysis for grouped person-year cohort data and the linear excess relative risk model were introduced, and subsequently a devoted software system, Epicure® (https://www.hirosoft.com), was developed by researchers at RERF and at the U.S. National Cancer Institute. Numerous advancements in understanding radiation effects on humans were made possible with these methods, which are still the state-of-the-art for risk assessment at RERF and have remained part of the standard toolbox for radiation—and other environmental—epidemiological studies worldwide. Nevertheless, as our understanding of radiation risk has increased, so have the breadth and depth of questions that require answers based on emerging data that are not amenable to these conventional methods. This overview briefly recounts the conventional methods and then describes our recent diversification into the use or development of new statistical approaches to meet the challenges of burgeoning biological data and emerging mechanistic information. We briefly discuss the development and application of new methods, current and planned, that are part of the RERF Statistics Department’s role in supporting institution-wide research, especially in our collaborations involving the Life Span Study, Adult Health Study, and First-generation Offspring Clinical Study. Some approaches to modeling and assessing radiation risk with newer methods mentioned herein have already been published, while some are still in development or are only beginning at the proposal stage.

Oncology↗

DOE OSTI2022

A Review on Application of Poly(3,4-ethylenedioxythiophene) (PEDOT) in Rechargeable Batteries

Since the very first patent on poly(3,4-ethylenedioxythiophene) (PEDOT) that was filed in 1988, this polymer has been widely utilized and has achieved great success owing to its high electrical conductivity and excellent stability. The application of the conducting polymer, PEDOT, in renewable energy devices, especially rechargeable batteries, is attracting increasing attention due to its potential to solve the energy and climate crisis. In this review, we summarize the research over the past few decades directed toward the application of PEDOT in rechargeable batteries aimed at improving their electrochemical performance. We focus on PEDOT synthesized via oxidative chemical vapor deposition (oCVD), a relatively new process known for its ability to grow conducting polymer thin films with uniform, pinhole-free properties, and controllable thickness and conformality. For a comparison purpose, PEDOT synthesized via solution-based methods is also briefly summarized. Finally, future research directions for applying oCVD PEDOT in rechargeable batteries are discussed. Introduction PEDOT Synthesis Methods Application of oCVD PEDOT in Rechargeable Batteries Applications of Solution-Based PEDOT in Rechargeable Batteries Conclusions and Outlook

25 ENERGY STORAGE↗

NASA NTRS2002

Atomistic Modeling of Semiconductors: Si, C, and 3C-SiC

An ongoing task of the Computational Materials Group (CMG) at the NASA Glenn Research Center is to enhance the role of atomistic simulations based on quantum-approximate methods in the study of new materials and their properties. One of the main goals of the activity continues to be breaching limitations that arise from the natural balance between accuracy, range of application, and computational simplicity. Whether that balance can be maintained while breaking new ground depends on the methods available with a minimum of constraints and limitations for the study of the energetics of arbitrary systems. The main tool used in CMG research, the Bozzolo- Ferrante-Smith (BFS) method for alloys, has no inherent constraint in its formulation, a feature that has allowed for successful research on various topics. In this article, we report on the latest development of the CMG program, namely, the extension and application of the BFS method to compound semiconductors, a departure from our previous research based primarily on metallic alloys.

Bozzolo, Guillermo↗