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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 1,477 records · Page 82
All sourcesNASA NTRSDOE OSTI
NASA NTRS1986

Evaluation of the infrared test method for the olympus thermal balance tests

The performance of the infrared (IR) rig used for the thermal balance testing of the Olympus S/C thermal model is discussed. Included in this evaluation are the rig effects themselves, the IRFLUX computer code used to predict the radiation inputs, the Monitored Background Radiometers (MBR's) developed to measure the absorbed radiation flux intensity, the Uniform Temperature Reference (UTR) based temperature measurement system and the data acquisition system. A preliminary set of verification tests were performed on a 1 m x 1 m zone to assess the performance of the IR lamps, calrods, MBR's and aluminized baffles. The results were used, in part, to obtain some empirical data required for the IRFLUX code. This data included lamp and calrod characteristics, the absorptance function for various surface types, and the baffle reflectivities.

Donato, M.↗
NASA NTRS1993

Effects of prolonged head-down bed rest on physiological responses to moderate hypoxia

To determine the effects of hypoxia on physiological responses to simulated zero-gravity cardiopulmonary and fluid balance measurements were made in 6 subjects before and during 5-degree head-down bed rest (HDBR) over 8 d at 10,678 ft and a second time at this altitude as controls (CON). The V-dot(O2)(max) increased by 9 percent after CON, but fell 3 percent after HDBR. This reduction in work capacity during HDBR could be accounted for by inactivity. The heart rate response to a head-up tilt was greatly enhanced following HDBR, while mean blood pressure was lower. No significant negative impact of HDBR was noted on the ability to acclimatize to hypoxia in terms of pulmonary mechanics, gas exchange, circulatory or mental function measurements. No evidence of pulmonary interstitial edema or congestion was noted during HDBR at the lower PIO2 and blood rheology properties were not negatively altered. Symptoms of altitude illness were more prevalent, but not marked, during HDBR and arterial blood gases and oxygenation were not seriously effected by simulated microgravity. Declines in base excess with altitude were similar in both conditions. The study demonstrated a minimal effect of HDBR on the ability to adjust to this level of hypoxia.

Loeppky, J. A.↗
NASA NTRS2002

Interactions between muscle and the immune system during modified musculoskeletal loading

Interactions between the immune system and skeletal muscle may play a significant role in modulating the course of muscle injury and repair after modified musculoskeletal loading. Current evidence indicates that activation of the complement system is an early event during modified loading, which then leads to inflammatory cell invasion. However, the functions of those inflammatory cells are complex and they seem to be capable of promoting additional injury and repair. Recent findings implicate an early invading neutrophil population in increasing muscle damage that is detected by the presence of muscle membrane lesions. Macrophages that invade subsequently serve to remove cellular debris, and seem to promote repair. However, macrophages also have the ability to increase damage in muscle in which there is an impaired capacity to generate nitric oxide. In vivo and in vitro evidence indicates that muscle-derived nitric oxide can serve an important role in protecting muscle from membrane damage by invading inflammatory cells. Collectively, these findings indicate that the dynamic balance between inflammatory cells, the complement system, and muscle-derived free radicals can play important roles in the secondary damage of muscle during modified musculoskeletal loading.

Review↗
NASA NTRS2016

Estimating the Rate of Occurrence of Renal Stones in Astronauts

Changes in urine chemistry, during and post flight, potentially increases the risk of renal stones in astronauts. Although much is known about the effects of space flight on urine chemistry, no inflight incidence of renal stones in US astronauts exists and the question "How much does this risk change with space flight?" remains difficult to accurately quantify. In this discussion, we tackle this question utilizing a combination of deterministic and probabilistic modeling that implements the physics behind free stone growth and agglomeration, speciation of urine chemistry and published observations of population renal stone incidences to estimate changes in the rate of renal stone presentation. The modeling process utilizes a Population Balance Equation based model developed in the companion IWS abstract by Kassemi et al. (2016) to evaluate the maximum growth and agglomeration potential from a specified set of urine chemistry values. Changes in renal stone occurrence rates are obtained from this model in a probabilistic simulation that interrogates the range of possible urine chemistries using Monte Carlo techniques. Subsequently, each randomly sampled urine chemistry undergoes speciation analysis using the well-established Joint Expert Speciation System (JESS) code to calculate critical values, such as ionic strength and relative supersaturation. The Kassemi model utilizes this information to predict the mean and maximum stone size. We close the assessment loop by using a transfer function that estimates the rate of stone formation from combining the relative supersaturation and both the mean and maximum free stone growth sizes. The transfer function is established by a simulation analysis which combines population stone formation rates and Poisson regression. Training this transfer function requires using the output of the aforementioned assessment steps with inputs from known non-stone-former and known stone-former urine chemistries. Established in a Monte Carlo system, the entire renal stone analysis model produces a probability distribution of the stone formation rate and an expected uncertainty in the estimate. The utility of this analysis will be demonstrated by showing the change in renal stone occurrence predicted by this method using urine chemistry distributions published in Whitson et al. 2009. A comparison to the model predictions to previous assessments of renal stone risk will be used to illustrate initial validation of the model.

gravitational physiology↗
NASA NTRS2017

Effects of Ionizing Radiation on Murine Gene Expression in Skin and Bone

Long duration spaceflight causes a negative calcium balance and reduces bone density in astronauts. The potential for exposure to space radiation to contribute to lasting decrements in bone mass is not yet understood. Sustained changes to bone mass have a relatively long latency for development, however skin is a radiation sensitive organ and changes in skin gene expression may serve as an early radiation biomarker of exposures and may correlate with adverse effects on skeletal tissue. Previous studies have shown that FGF18 gene expression levels of hair follicles collected from astronauts on the ISS rose over time. In the hair follicle, FGF18 signaling mediates radioresistance in the telogen by arresting the cell cycle, and FGF18 has the potential to function as a radioprotector. In bone, FGF18 appears to regulate cell proliferation and differentiation positively during osteogenesis and negatively during chondrogenesis. Cellular defense responses to radiation are shared by a variety of organs, hence in this study, we examined whether radiation induced gene expression changes in skin may be predictive of the responses of skeletal tissue to radiation exposure. We have examined oxidative stress and growth arrest pathways in mouse skin and long bones by measuring gene expression levels via quantitative polymerase chain reaction (qPCR) after exposure to total body irradiation (TBI). To investigate the effects of irradiation on gene expression, we used skin and femora (cortical shaft) from the following treatment groups: control (normally loaded, sham-irradiated), and TBI (0.5 Gy Fe-56 600 MeV/n and 0.5 Gy H-1 150 MeV/n). Animals were euthanized one and 11 days post-IR. Statistical analysis was performed via a Student's ttest. In skin samples one day after IR, skin expression of FGF18 was significantly greater (3.8X) than sham-irradiated controls (3.8X), but did not differ 11 days post TBI. Expression levels of other radiation related genes (Nfe2l2, Trp53, Cdkn1a, FoxO3, Gadd45g, SOD1), was not different due to TBI at either time point. In bone (femora) TBI significantly increased (3.8X) expression of the pro-bone resorption cytokine, MCP-1, one day after TBI. FGF18 expression in skin and MCP- 1 expression in bone were found to be positively correlated (P less than 0.002, r=0.8779). Further, microcomputed tomography analysis of tibae from these animals showed reduced fractional cancellous bone volume (-21.7%) at 11 days post exposure. These results suggest that early radiation induced changes in FGF18 gene expression in skin may have value for predicting subsequent loss of cancellous bone mass.

space radiation↗
DOE OSTI2022

All‐Polymer Bulk‐Heterojunction Organic Electrochemical Transistors with Balanced Ionic and Electronic Transport

Abstract The rapid development of organic electrochemical transistor (OECTs)‐based circuits brings new opportunities for next‐generation integrated bioelectronics. The all‐polymer bulk‐heterojunction (BHJ) offers an attractive, inexpensive alternative to achieve efficient ambipolar OECTs, and building blocks of logic circuits constructed from them, but have not been investigated to date. Here, the first all‐polymer BHJ‐based OECTs are reported, consisting of a blend of new p‐type ladder conjugated polymer and a state‐of‐the‐art n‐type ladder polymer. The whole ladder‐type polymer BHJ also proves that side chains are not necessary for good ion transport. Instead, the polymer nanostructures play a critical role in the ion penetration and transportation and thus in the device performance. It also provides a facile strategy and simplifies the fabrication process, forgoing the need to pattern multiple active layers. In addition, the development of complementary metal–oxide–semiconductor (CMOS)‐like OECTs allows the pursuit of advanced functional logic circuitry, including inverters and NAND gates, as well as for amplifying electrophysiology signals. This work opens a new approach to the design of new materials for OECTs and will contribute to the development of organic heterojunctions for ambipolar OECTs toward high‐performing logic circuits.

Chemistry↗
DOE OSTI2021

MPC-based double-layer real-time conditional cSelf-restoration for interconnected microgrids

In this report, we propose a novel model predictive control(MPC)-based real-time conditional self-restoration energy management system (CSR-EMS) for interconnected microgrids (IMGs) integrated with renewable energy sources (RESs) and energy storage systems (ESSs). Superior to the existing IMG self-restoration methods, the “conditionality” of the proposed CSR-EMS can economically realize self-restoration and grid-assisted restoration during energy deficiency or faults, in both islanded and grid-connected modes. Cost minimization is implemented as the objective function to judge in real-time which restoration mode is economically preferred. The proposed CSR-EMS comprises two layers–the lower layer operates locally to eliminate electricity fluctuations created by RESs and ensure economic effectiveness within an MG, whereas the upper layer oversees the real-time operational status of the IMG system and determines power exchange among microgrids (MGs) during abnormalities. In detail, when a microgrid inside the IMG system experiences an energy deficiency, the CSR-EMS, on an MPC basis, intelligently optimizes power production from each dispatchable distributed generator (DG), ESS, power imported from the main grid, and power exchange among the IMGs to maintain the demand–supply balance, while considering system recovery cost, state of charge (SoC) of ESSs and operation modes of the IMGs (i.e., grid-connected or islanded mode). Simulation results and comparisons with existing IMG self-healing EMSs demonstrate the economic efficacy of the proposed CSR-EMS strategy during normal and abnormal operations, which can be used as an energy control framework for modern power systems with multiple interconnected microgrids.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

Highly Emissive Semi-Ladder-Type Copolymers, Aggregation State, and Solution-Processed Organic Light-Emitting Transistor

An organic light-emitting transistor (OLET) integrates the logic function of a field-effect transistor (FET) with electroluminescence of a light-emitting diode (LED) into a single device. This has the potential to play an important role in smart displays, electrically pumped organic laser, and other flexible electronic devices. For achieving high-performance solution-processed OLET, three semiladder copolymers—TPTI-CC, TPTI-C, and TPTI-F—were developed in this study. It was found that variation in the chemical structure lead to significant differences in energy level, emission color, and intermolecular aggregation. High photoluminescence quantum yields (PLQY) was obtained in these three polymers. Solution-processed trilayered OLET devices were fabricated, which exhibited strong electroluminescence, balanced charge mobility, and external quantum efficiency (EQE) of 2.8%.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Understanding the Reactivity, Selectivity, and Deactivation of Frustrated Lewis Pairs for Semihydrogenation of Acetylene

A good catalyst for semihydrogenation of alkynes must preclude both over-hydrogenation of alkene to alkane and isomerization to the other alkene isomer. In addition, it should balance the trade-off between selectivity and activity. In 2013, the Repo and Pápai groups reported a frustrated Lewis pair (FLP) (1-NMe 2 -2-B(C 6 F 5 ) 2 -C 6 H 4 ), 1, which is a metal-free catalyst and for the first time shows excellent reactivity for the hydrogenation of internal alkynes. However, it is unreactive for terminal alkynes. In this work, we have designed 13 FLPs, a–m, based on 1 by varying the Lewis base site with N and P and the Lewis acid site with B, Al, Ga, and In and replacing pentafluorophenyl with 1,3,5-trifluorophenyl, phenyl, or trifluoromethyl. We apply density functional theory to study the activity, selectivity, and deactivation of FLP 1-m for acetylene semihydrogenation. The catalytic cycle consists of three steps: (1) alkyne insertion, (2) H 2 heterolysis, and (3) intramolecular protonation. We found the activity does not change much by the modification of bulky ligands, while it decreases with the direct replacement of LA and LB sites. The overall activity depends on steps 1 and 3, which are, respectively, positively and negatively linear correlated with the charge of the Lewis acid site. Most of the FLPs in this work show comparable or better selectivity for semihydrogenation of acetylene than 1. FLP deactivation is due to the strong binding of acetylene and the elimination of electron-withdrawing bulky ligands at the preactivated catalyst rather than at activated catalysts. Furthermore, taking the selectivity and stability of FLPs into account, we predict d and k are potentially active for terminal alkynes.

02 PETROLEUM↗
NASA NTRS1993

The implementation and validation of improved land-surface hydrology in an atmospheric general circulation model

New land-surface hydrologic parameterizations are implemented into the NASA Goddard Institute for Space Studies (GISS) General Circulation Model (GCM). These parameterizations are: 1) runoff and evapotranspiration functions that include the effects of subgrid-scale spatial variability and use physically based equations of hydrologic flux at the soil surface and 2) a realistic soil moisture diffusion scheme for the movement of water and root sink in the soil column. A one-dimensional climate model with a complete hydrologic cycle is used to screen the basic sensitivities of the hydrological parameterizations before implementation into the full three-dimensional GCM. Results of the final simulation with the GISS GCM and the new land-surface hydrology indicate that the runoff rate, especially in the tropics, is significantly improved. As a result, the remaining components of the heat and moisture balance show similar improvements when compared to observations. The validation of model results is carried from the large global (ocean and land-surface) scale to the zonal, continental, and finally the regional river basin scales.

Johnson, Kevin D.↗
NASA NTRS1993

GGOT total pressure loss control concept evaluation

Total pressure loss is one of the most important parameters in the design of a turbine. This parameter effects not only the turbine performance, but consequently the engine power balance and engine performance. Computational Fluid Dynamics (CFD) can be an effective tool in predicting turbine total pressure loss, and also for performing sensitivity studies to achieve an optimal design with respect to pressure loss. In the present study, the AEROVISC code was used to predict the total pressure loss in the Turbine Technology Team Gas Generator Oxidizer Turbine (GGOT). The objectives in this study are two-fold. It is first necessary to determine an optimal methodology in predicting total pressure loss. The type of grid, grid density and distribution are parameters which may affect the loss prediction. Also, the effect of using a standard K-epsilon turbulence model with wall functions versus a two-layer turbulence model needs to be investigated. The use of grid embedding to resolve areas with high flow gradients needs to be explored. The second objective of the study is to apply the optimal methodology toward evaluating different tip leakage control concepts.

Blumenthal, R. F.↗
NASA NTRS1998

Validation of POLDER/ADEOS data using a ground-based lidar network: Preliminary results for semi-transparent and cirrus clouds

At mid and tropical latitudes, cirrus clouds are present more than 50% of the time in satellites observations. Due to their large spatial and temporal coverage, and associated low temperatures, cirrus clouds have a major influence on the Earth-Ocean-Atmosphere energy balance through their effects on the incoming solar radiation and outgoing infrared radiation. At present the impact of cirrus clouds on climate is well recognized but remains to be asserted more precisely, for their optical and radiative properties are not very well known. In order to understand the effects of cirrus clouds on climate, their optical and radiative characteristics of these clouds need to be determined accurately at different scales in different locations i.e. latitude. Lidars are well suited to observe cirrus clouds, they can detect very thin and semi-transparent layers, and retrieve the clouds geometrical properties i.e. altitude and multilayers, as well as radiative properties i.e. optical depth, backscattering phase functions of ice crystals. Moreover the linear depolarization ratio can give information on the ice crystal shape. In addition, the data collected with an airborne version of POLDER (POLarization and Directionality of Earth Reflectances) instrument have shown that bidirectional polarized measurements can provide information on cirrus cloud microphysical properties (crystal shapes, preferred orientation in space). The spaceborne version of POLDER-1 has been flown on ADEOS-1 platform during 8 months (October 96 - June 97), and the next POLDER-2 instrument will be launched in 2000 on ADEOS-2. The POLDER-1 cloud inversion algorithms are currently under validation. For cirrus clouds, a validation based on comparisons between cloud properties retrieved from POLDER-1 data and cloud properties inferred from a ground-based lidar network is currently under consideration. We present the first results of the validation.

Chepfer, H.↗
DOE OSTI2023

Data-driven analysis and prediction of stable phases for high-entropy alloy design

High-entropy alloys (HEAs) represent a promising class of materials with exceptional structural and functional properties. However, their design and optimization pose challenges due to the large composition-phase space coupled with the complex and diverse nature of the phase formation dynamics. In this study, a data-driven approach that utilizes machine learning (ML) techniques to predict HEA phases and their composition-dependent phases is proposed. By employing a comprehensive dataset comprising 5692 experimental records encompassing 50 elements and 11 phase categories, we compare the performance of various ML models. Our analysis identifies the most influential features for accurate phase prediction. Furthermore, the class imbalance is addressed by employing data augmentation methods, raising the number of records to 1500 in each category, and ensuring a balanced representation of phase categories. The results show that XGBoost and Random Forest consistently outperform the other models, achieving 86% accuracy in predicting all phases. Additionally, this work provides an extensive analysis of HEA phase formers, showing the contributions of elements and features to the presence of specific phases. We also examine the impact of including different phases on ML model accuracy and feature significance. Notably, the findings underscore the need for ML model selection based on specific applications and desired predictions, as feature importance varies across models and phases. This study significantly advances the understanding of HEA phase formation, enabling targeted alloy design and fostering progress in the field of materials science.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Towards automating structural discovery in scanning transmission electron microscopy *

Abstract Scanning transmission electron microscopy is now the primary tool for exploring functional materials on the atomic level. Often, features of interest are highly localized in specific regions in the material, such as ferroelectric domain walls, extended defects, or second phase inclusions. Selecting regions to image for structural and chemical discovery via atomically resolved imaging has traditionally proceeded via human operators making semi-informed judgements on sampling locations and parameters. Recent efforts at automation for structural and physical discovery have pointed towards the use of ‘active learning’ methods that utilize Bayesian optimization with surrogate models to quickly find relevant regions of interest. Yet despite the potential importance of this direction, there is a general lack of certainty in selecting relevant control algorithms and how to balance a priori knowledge of the material system with knowledge derived during experimentation. Here we address this gap by developing the automated experiment workflows with several combinations to both illustrate the effects of these choices and demonstrate the tradeoffs associated with each in terms of accuracy, robustness, and susceptibility to hyperparameters for structural discovery. We discuss possible methods to build descriptors using the raw image data and deep learning based semantic segmentation, as well as the implementation of variational autoencoder based representation. Furthermore, each workflow is applied to a range of feature sizes including NiO pillars within a La:SrMnO 3 matrix, ferroelectric domains in BiFeO 3 , and topological defects in graphene. The code developed in this manuscript is open sourced and will be released at github.com/nccreang/AE_Workflows .

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

Source:sink imbalance detected with leaf and canopy-level spectroscopy in a field-grown crop

The finely-tuned balance between sources and sinks determines plant resource partitioning and regulates growth and development. Understanding and measuring metabolic indicators of source or sink limitation forms a vital part of global efforts to increase crop yield for future food security. Here, we measured metabolic profiles of Cucurbita pepo (zucchini) grown in the field under carbon sink limitation and control conditions. We demonstrate that these profiles can be measured non-destructively using hyperspectral reflectance at both leaf and canopy scales. Total non-structural carbohydrates (TNC) increased 82% in sink-limited plants; leaf mass per unit area (LMA) increased 38%; free amino acids increased 22%. Partial least-squares regression models link these measured functional traits with reflectance data, enabling high-throughput estimation of traits comprising the sink limitation response. Leaf- and canopy-scale models for TNC had R 2 values of 0.93 and 0.64 and %RMSE of 13% and 38% respectively. For LMA, R 2 values were 0.91 and 0.60 and %RMSE 7% and 14%; for free amino acids, R 2 was 0.53 and 0.21 with %RMSE 20% and 26%. Remote sensing can enable accurate, rapid detection of sink limitation in the field at the leaf and canopy scale, greatly expanding our ability to understand and measure metabolic responses to stress.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2000

New digital measurement methods for left ventricular volume using real-time three-dimensional echocardiography: comparison with electromagnetic flow method and magnetic resonance imaging

AIM: The aim of this study was to investigate the feasibility and accuracy of using symmetrically rotated apical long axis planes for the determination of left ventricular (LV) volumes with real-time three-dimensional echocardiography (3DE). METHODS AND RESULTS: Real-time 3DE was performed in six sheep during 24 haemodynamic conditions with electromagnetic flow measurements (EM), and in 29 patients with magnetic resonance imaging measurements (MRI). LV volumes were calculated by Simpson's rule with five 3DE methods (i.e. apical biplane, four-plane, six-plane, nine-plane (in which the angle between each long axis plane was 90 degrees, 45 degrees, 30 degrees or 20 degrees, respectively) and standard short axis views (SAX)). Real-time 3DE correlated well with EM for LV stroke volumes in animals (r=0.68-0.95) and with MRI for absolute volumes in patients (r-values=0.93-0.98). However, agreement between MRI and apical nine-plane, six-plane, and SAX methods in patients was better than those with apical four-plane and bi-plane methods (mean difference = -15, -18, -13, vs. -31 and -48 ml for end-diastolic volume, respectively, P<0.05). CONCLUSION: Apically rotated measurement methods of real-time 3DE correlated well with reference standards for calculating LV volumes. Balancing accuracy and required time for these LV volume measurements, the apical six-plane method is recommended for clinical use.

Evaluation Studies↗
NASA NTRS2006

Long-Term Validation and Variability of the Shortwave and Longwave Radiation Data of the GEWEX Surface Radiation Budget (SRB) Project

In this investigation, we make systematic Surface Radiation Budget-Baseline Surface Radiation Network (SRB-BSRN), Surface Radiation Data Centre (SRB-WRDC) and Surface Radiation Budget-Global Energy Balance Archive (SRB-GEBA) comparisons for both shortwave and longwave daily and monthly mean radiation fluxes at the Earth's surface. We first have an overview of all the comparable pairs of data in scatter or scatter density plots. Then we show the time series of the SRB data at grids in which there are ground sites where longterm records of data are available for comparison. An overall very good agreement between the SRB data and ground observations is found. To see the variability of the SRB data during the 21.5 years, we computed the global mean and its linear trend. No appreciable trend is detected at the 5% level. The empirical orthogonal functions (EOF) of the SRB deseasonalized shortwave downward flux are computed over the Pacific region, and the first EOF coefficient is found to be correlated with the ENSO Index at a high value of coefficient of 0.7083.

Zhang, Taiping↗
NASA NTRS2011

Dynamic Monitoring of Cleanroom Fallout Using an Air Particle Counter

The particle fallout limitations and periodic allocations for the James Webb Space Telescope are very stringent. Standard prediction methods are complicated by non-linearity and monitoring methods that are insufficiently responsive. A method for dynamically predicting the particle fallout in a cleanroom using air particle counter data was determined by numerical correlation. This method provides a simple linear correlation to both time and air quality, which can be monitored in real time. The summation of effects provides the program better understanding of the cleanliness and assists in the planning of future activities. Definition of fallout rates within a cleanroom during assembly and integration of contamination-sensitive hardware, such as the James Webb Space Telescope, is essential for budgeting purposes. Balancing the activity levels for assembly and test with the particle accumulation rate is paramount. The current approach to predicting particle fallout in a cleanroom assumes a constant air quality based on the rated class of a cleanroom, with adjustments for projected work or exposure times. Actual cleanroom class can also depend on the number of personnel present and the type of activities. A linear correlation of air quality and normalized particle fallout was determined numerically. An air particle counter (standard cleanroom equipment) can be used to monitor the air quality on a real-time basis and determine the "class" of the cleanroom (per FED-STD-209 or ISO-14644). The correlation function provides an area coverage coefficient per class-hour of exposure. The prediction of particle accumulations provides scheduling inputs for activity levels and cleanroom class requirements.

Perry, Radford↗