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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 487 records · Page 27

Effects of foveal information processing

The scanning behavior of pilots must be understood so that cockpit displays can be assembled which will provide the most information accurately and quickly to the pilot. The results of seven years of collecting and analyzing pilot scanning data are summarized. The data indicate that pilot scanning behavior is: (1) subsconscious; (2) situation dependent; and (3) can be disrupted if pilots are forced to make conscious decisions. Testing techniques and scanning analysis techniques have been developed that are sensitive to pilot workload.

Harris, R. L., Sr.↗

3DBFSVBF (3D BatFinder Smart Video BioFilter and Multi-class BatFinder Smart Video BioFilter) [SWR-22-88]

Bats are notoriously difficult to study, therefore, identifying specific behavioral trends and the precise environmental conditions at the time of collision requires a monitoring solution that can reliably collect relevant data. To date, thermal infrared video surveillance has been extensively applied to study bats and has proven to be a powerful yet cumbersome tool. Current analytical approaches are time consuming because data processing data has not been fully automated. In the past, steps have been taken to record avian and bat activity in conjunction with complicated image processing techniques that separate species from other moving objects within the field of view (i.e. clouds and portions of the wind turbine). Once the videos are collected, the post-processing does not allow real time monitoring and identification, leading to a delay in both studying the behavior of these species and determining the effectiveness of any impact reduction strategy being studied. Moreover, object identification capability is lacking, thus limiting the usefulness of video data. To resolve these issues, we are using open source 3D computer vision and machine learning techniques allowing for automatic detection of objects in real-time with the ability to correlate these objects with environmental variables and recording the flight paths of each object. The machine learning has been trained on 3D data and allows for automated real-time data collection, identification and tracking, thereby eliminating the need for long and tedious post-analysis processing of the videos. This machine learning model is an added feature to the previous BatFinder Smart Video BioFilter and increases the accuracy of that systems classification by increasing the accuracy of identifying bats (90% accuracy) and insects (69% accuracy) to a 97% accuracy. There are two object classifier machine learning models, Binary and multi-classification. Binary object classifier labeled BatFinder_Smart_Video_BioFilter.h5 distinguishes between biological objects and non-biological objects. The main goal of this object classifier is to ignore the turbine blades while detecting biological object flying withing the rotor swept area of the turbine. Non-biological objects have a probability of 0 and biological objects have a probability of 1. Multi-classifier labeled Multiclass_BatFinder_Smart_Video_BioFilter.h5 distinguishes between bats, birds, insects and non-biological.

Yarbrough, John↗

Sink or source? Insights into the behavior of copper and zinc in the sediment porewater of a constructed wetland by peepers

The H-02 free water surface constructed wetland has been applied to remove heavy metals, mainly copper (Cu) and zinc (Zn), from wastewater on the Savannah River Site (Aiken, SC, USA). More and more studies focus on the metal behavior between the sediment and the overlying water, which directly reflects the stability of metals after sedimentation in constructed wetlands. This study focused on the biogeochemical pathways in metal bioavailability and remobilization in the sediment after metals were removed from the overlying water. The dialysis sampling devices (peepers) were used to collect porewater samples from eight depths in the sediment for the measurement of Cu, Zn, dissolved organic carbon (DOC), and major anions (sulfate and chloride). Surface water samples were also collected for the measurement of Cu, Zn, DOC, and anions. Different temporal trends were observed for dissolved Cu between the surface and bottom waters, but not for dissolved Zn. There were no obvious changes in porewater metal concentrations with increasing depths in the sediment. Sediment served as a sink for Cu as only 3% of porewater samples showed higher labile Cu concentrations than the surface water during the entire year. Furthermore, sediment served as a source for Zn in summer and winter as 32% of porewater samples showed higher labile Zn concentrations than the surface water, and these samples were collected at all sediment depths. We think the seasonal changes in the behaviors of Cu and Zn were primarily controlled by the sulfur dynamics and the metal removal processes in the constructed wetland, as well as the different complexing chemistry between Cu and Zn. Also, our study supports that peeper is a powerful tool for studying the biogeochemistry of metals in the sediment.

54 ENVIRONMENTAL SCIENCES↗

BFSVBF (BatFinder Smart Video BioFilter) [SWR-22-87] and Multi-class BatFinder Smart Video BioFilter Keras

Bats are notoriously difficult to study, therefore, identifying specific behavioral trends and the precise environmental conditions at the time of collision requires a monitoring solution that can reliably collect relevant data. To date, thermal infrared video surveillance has been extensively applied to study bats and has proven to be a powerful yet cumbersome tool. Current analytical approaches are time consuming because data processing data has not been fully automated. In the past, steps have been taken to record avian and bat activity in conjunction with complicated image processing techniques that separate species from other moving objects within the field of view (i.e. clouds and portions of the wind turbine). Once the videos are collected, the post-processing does not allow real time monitoring and identification, leading to a delay in both studying the behavior of these species and determining the effectiveness of any impact reduction strategy being studied. Moreover, object identification capability is lacking, thus limiting the usefulness of video data. To resolve these issues, we are using open source computer vision and machine learning techniques allowing for automatic detection of objects in real-time with the ability to correlate these objects with environmental variables and recording the flight paths of each object. The code has gone through five rounds of development with images used to train the models. This advancement allows for automated real-time data collection, identification, and tracking, thereby eliminating the need for long and tedious post-analysis processing of the videos. We will discuss the two open source and publicly available machine learning models developed within this scope of this work: 1) a binary model with a 97.5% accuracy in identifying the difference between an object and an empty scene, including wind turbine and clouds; and 2) a multiple classification model with the capability of identifying the type of object detected: bats (90% accuracy), birds (83% accuracy), insects (69% accuracy) and non-biological (99% accuracy).

Yarbrough, John↗

Shared Use Travel Behavior for Improving Rural Mobility: Insights from Greene County, Pennsylvania

Rural communities are considered disadvantaged communities as they suffer from a lack of transport options. Thus, rural regionsprovide less accessibility for commuters to reach their destination as opposed to urban regions. However, the issues of transport disadvantageand shared use mobility in rural areas within the United States (US) have not been well investigated. Furthermore, transport disadvantagediffers between communities and regions across the globe; thus, there is a need to study the behavioral choices of rural commuters within theUS context. This study contributes by analyzing the behavioral choices of rural communities within the US through a case study site ofWaynesburg, Pennsylvania, for adopting a shared use shuttle service. K-means clusters showed that trips from the survey data were a goodrepresentation of real trips from Ecolane. Furthermore, random parameter-based binary logit models were calibrated using data collected fromstudents, faculty, and residents in Waynesburg, Greene County, to study the behavioral choices of commuters. The findings for the faculty andstudents group revealed that prior experience with shared services increases the likelihood of using a shared shuttle. An important personalcharacteristic of inconvenience showed a higher propensity toward using existing modes as opposed to a shared shuttle. Such commutersvalue personal vehicles as more convenient as they have childcare responsibilities and varying schedules for work that require them to moveback and forth across locations, thus making a shared shuttle less attractive for them. The socioeconomic factors of age and gender show ahigher propensity for using shared shuttles. Furthermore, the findings from this study could be helpful for agencies in improving rural mobility andconsidering such shared mobility services for rural communities

42 ENGINEERING↗

Behavior of Triple Langmuir Probes in Non-Equilibrium Plasmas

A model of current collection in Langmuir probes is used to investigate the effect representative non- equilibrium plasmas under various conditions have on the electron temperature and number density that would be calculated through analysis of the probe collection characteristics. The model uses the distribution function to calculate the charged particle flux to a probe and then, for fixed applied voltages, the current values that satisfy continuity in the probes are determined. The triple probe is not scanned in voltage, so there is no practical way using experimental triple probe data to determine if the plasma is in equilibrium. As a consequence, a triple probe analysis typically relies on the assumption that the plasma is in equilibrium. Proceeding from this point, the numerically-generated non-equilibrium triple probe data are analyzed assuming that the plasma is in equilibrium, with the data compared to the initial distribution function inputs of plasma temperature and number density to determine the effect the non-equilibrium distribution has on plasma measurements. The temperature and number density are both significantly affected when a fraction of the particles in the distribution are shifted from the equilibrium configuration into the non-equilibrium part of the distribution function. For all instances studied, the computed electron temperature and number density are extremely sensitive to small deviations from equilibrium ( ≤ 5% of the plasma shifted into the non-equilibrium function). Shifting more of the plasma into the non-equilibrium distribution beyond this initial level does not produce a significant additional shift in the computed plasma properties.

Polzin, Kurt A.↗

Effects of elevated temperature on the viscoplastic modeling of graphite/polymeric composites

To support the development of new materials for the design of next generation supersonic transports, a research program is underway at NASA to assess the long term durability of advanced polymer matrix composites (PMC's). One of main objectives of the program was to explore the effects of elevated temperature (23 to 200 C) on the constitutive model's material parameters. To achieve this goal, test data on the observed nonlinear, stress-strain behavior of IM7/5260 and IM7/8320 composites under tension and compression loading were collected and correlated against temperature. These tests, conducted under isothermal conditions using variable strain rates, included such phenomena as stress relaxation and short term creep. The second major goal was the verification of the model by comparison of analytical predictions and test results for off axis and angle ply laminates. Correlation between test and predicted behavior was performed for specimens of both material systems over a range of temperatures. Results indicated that the model provided reasonable predictions of material behavior in load or strain controlled tests. Periods of loading, unloading, stress relaxation, and creep were accounted for.

Gates, Thomas S.↗

Development of Buffet Forcing Functions for a Transonic Condition Exhibiting Bimodal Flow Behavior

A wind-tunnel test campaign was used to derive Buffet Forcing Functions (BFFs) of the Space Launch System Block 1B vehicle configuration by measuring and integrating unsteady surface pressures on a 3-percent scale rigid buffet model (RBM) tested at the NASA Langley Transonic Dynamics Tunnel. The model was tested at predetermined and repeatable pitch and side-slip angles and flow Mach numbers encompassing a full range of possible flight conditions. Although each data point was collected at a steady wind-tunnel condition, a transient, bimodal flow behavior was observed in some Mach 1.10 measurements. The pressure time series was alternating between two states, which differed either in mean or fluctuation amplitude values, or both. As a consequence of this behavior, segments of the resultant BFFs can differ based on the duration that each measurement spends in a particular state. In this paper, a methodology is proposed, which envelopes the range of BFFs magnitudes resulting from this random bimodal phenomenon in pressure time histories of certain sensors.

wind-tunnel testing↗

Development of Buffet Forcing Functions for a Transonic Condition Exhibiting Bimodal Flow Behavior

A wind-tunnel test campaign was used to derive Buffet Forcing Functions (BFFs) of the Space Launch System Block 1B vehicle configuration by measuring and integrating unsteady surface pressures on a 3-percent scale rigid buffet model (RBM) tested at the NASA Langley Transonic Dynamics Tunnel. The model was tested at predetermined and repeatable pitch and side-slip angles and flow Mach numbers encompassing a full range of possible flight conditions. Although each data point was collected at a steady wind-tunnel condition, a transient, bimodal flow behavior was observed in some Mach 1.10 measurements. The pressure time series was alternating between two states, which differed either in mean or fluctuation amplitude values, or both. As a consequence of this behavior, segments of the resultant BFFs can differ based on the duration that each measurement spends in a particular state. In this paper, a methodology is proposed, which envelopes the range of BFFs magnitudes resulting from this random bimodal phenomenon in pressure time histories of certain sensors.

wind-tunnel testing↗

Advancing Tritium Self-Sufficiency in Fusion Power Plants: Insights from the BABY Experiment

Abstract In the pursuit of fusion power, achieving tritium self-sufficiency stands as a pivotal challenge.
Tritium breeding within molten salts is a critical aspect of next-generation fusion reactors, yet experimental measurements of \gls{tbr} have remained elusive.
Here we present the results of the \gls{baby} experiment, which represents a pioneering effort in tritium research by utilizing high-energy (\SI{14}{\mega\electronvolt}) neutron irradiation of molten salts, a departure from conventional low-energy neutron approaches. 
Using a small-scale (\SI{100}{\milli\litre}) molten salt tritium breeding setup, we not only simulated, but also directly measured a \gls{tbr} \textcolor{red}{(\num{3.57e-4})}. 
This innovative approach provides crucial experimental validation, offering insights unattainable through simulation alone.
Moreover, our findings reveal a surprising outcome: tritium was predominantly collected as HT, contrary to the expected TF. 
This underscores the complexity of tritium behavior in molten salts, highlighting the need for further investigation.
This work lays the foundation for a more sophisticated experimental setup, including increasing the volume of the breeder, enhancing neutron detection, and refining tritium collection systems.
Such improvements are crucial for advancing our understanding of fusion reactor feasibility and paving the way for future experiments.

Delaporte-Mathurin, Rémi (ORCID:0000000310648882)↗

Coupled Thermo-Hydro-Mechanical Processes in Fractured Rocks: Some Past Scientific Highlights and Future Research Directions

Abstract Coupled thermo-hydro-mechanical (THM) processes in fractured rocks have been a topic of intense scientific research for more than 30 years. The present paper takes a look into the past and highlights some scientific advances which are of an unusual “out-of-the-box” nature, and then looks forward and discusses possible directions of future research in this interesting field of study. Concerning future research directions, we see a trend from a focus on coupled THM processes in single fractures or a few interacting fractures, to the study of coupled THM behavior in complex fracture network systems where the fractures act collectively giving rise to local stress concentration points and points of large pressure gradients. Three examples of future research directions are presented. First is an effort towards identifying characterizing parameters of a fracture network that play a direct controlling role in major coupled THM phenomena (such as induced seismicity and flow channeling), rather than parameters of stochastic distributions of fractures in the network. The second example of research direction is accounting for the heterogeneity and hierarchy of fractures in a fault or fracture zone which has been associated with major THM events in a number of geo-energy projects. The third example is at the opposite end of the first; here it is recognized that in some cases, the coupled THM processes in fractured rocks may be controlled dominantly by only a few key bridges. Identification, characterization, and evaluation of these key bridges should be one of the important research directions in the coming days.

58 GEOSCIENCES↗

BrainXcan identifies brain features associated with behavioral and psychiatric traits using large-scale genetic and imaging data

Advances in brain MRI have enabled many discoveries in neuroscience. Case-control comparisons of brain MRI features have highlighted potential causes of psychiatric and behavioral disorders. However, due to the cost and difficulty of collecting MRI data, most studies have small sample sizes, limiting their reliability. Furthermore, reverse causality complicates interpretation because many observed brain differences are the result rather than the cause of the disease. Here we propose a method (BrainXcan) that leverages the power of large-scale genomewide association studies (GWAS) and reference brain MRI data to discover new mechanisms of disease etiology and validate existing ones. BrainXcan tests the association with genetic predictors of brain MRI-derived features and complex traits to pinpoint relevant brain-wide and region-specific features. Requiring only genetic data, BrainXcan allows us to test a host of hypotheses on mental illness, across many MRI modalities, using public data resources. For example, our method shows that reduced axonal density across the brain is associated with schizophrenia risk, consistent with the disconnectivity hypothesis. We also find that the hippocampus volume is associated with schizophrenia risk, highlighting the potential of our approach. Taken together, our results show the promise of BrainXcan to provide insights into the biology of GWAS traits.

Association study↗

Recent results from satellite beacon measurements

The techniques are reviewed for measuring ionospheric electron content, the most important parameter in the study of transionospheric propagation. Data collected since 1964 have yielded a synoptic description of the behavior of the electron content in midlatitudes. Empirical relationships between the level of solar activity and the electron content were developed permitting the prognostication of the electron content values. Construction of such prognostication schemes was stimulated by current efforts to create accurate satellite borne navigation systems. Gravity waves propagating in the thermosphere leave a signature in the electron content records. Studies of such records have allowed the identification of the position of the gravity wave source, and its radiation pattern. A one-to-one relationship between these waves and polar substorms was revealed. Electron content measurements were used to monitor the protonosphere with good time resolution. Protonospheric storms were observed with this technique. Slab thickness data obtained from content measurements were used to determine the neutral air temperature in the thermosphere.

Darosa, A. V.↗

Recent results from satellite beacon measurements

A review is made of the techniques for measuring ionospheric electron content, the most important parameter in the study of transionospheric propagation. Data collected since 1964 have yielded a synoptic description of the behavior of the electron content in mid-latitudes. Empirical relationships between the level of solar activity and the electron content have been developed permitting the prognostication of the electron content values. Marked discrepancies between prognostication and observation which occur during ionospheric storms are being studied to identify their causes. Electron content bite-outs during solar eclipses fall off with distance from totality more rapidly than simple theory predicts suggesting the action of eclipse induced neutral winds. Gravity waves propagating in the thermosphere leave a signature in the electron content records. Studies of such records have allowed the identification of the position of the gravity wave source, and its radiation pattern.

Da Rosa, A. V.↗

Accurate low-cost methods for performance evaluation of cache memory systems

Methods of simulation based on statistical techniques are proposed to decrease the need for large trace measurements and for predicting true program behavior. Sampling techniques are applied while the address trace is collected from a workload. This drastically reduces the space and time needed to collect the trace. Simulation techniques are developed to use the sampled data not only to predict the mean miss rate of the cache, but also to provide an empirical estimate of its actual distribution. Finally, a concept of primed cache is introduced to simulate large caches by the sampling-based method.

Laha, Subhasis↗

Small Expendable-tether Deployer System (SEDS) development status

Plans for proposed flight of the Small Expendable-tether Deployer System (SEDS) on a Delta II launch vehicle are discussed. The SEDS tether concept and mission requirements are outlined. Results are presented from calculations of the tether dynamics and computer modeling to determine tether behavior. The tether's thermal characteristics, electronics system, material, data collection procedure, payload, and orbital trace are described.

Harrison, James K.↗

Venus magmatic and tectonic evolution

Two years beyond the initial mapping by the Magellan spacecraft, hypotheses for the magmatic and tectonic evolution of Venus have become refined and focused. We present our view of these processes, attempting to synthesize aspects of a model for the tectonic and magmatic behavior of the planet. The ideas presented should be taken collectively as an hypothesis subject to further testing. The quintessence of our model is that shear and buoyancy forces in the upper boundary layer of mantle convection give rise to a spatially and temporally complex pattern of strain in a one-plate Venusian lithosphere and modulate the timing and occurrence of magmatism on a global basis.

Phillips, R. J.↗

Studies of Two-Phase Gas-Liquid Flow in Microgravity

Two-phase gas-liquid flows are expected to occur in many future space operations. Due to a lack of buoyancy in the microgravity environment, two-phase flows are known to behave differently than those in earth gravity. Despite these concerns, little research has been conducted on microgravity two-phase flow and the current understanding is poor. This dissertation describes an experimental and modeling study of the characteristics of two-phase flows in microgravity. An experiment was operated onboard NASA aircraft capable of producing short periods of microgravity. In addition to high speed photographs of the flows, electronic measurements of void fraction, liquid film thickness, bubble and wave velocity, pressure drop and wall shear stress were made for a wide range of liquid and gas flow rates. The effects of liquid viscosity, surface tension and tube diameter on the behavior of these flows were also assessed. From the data collected, maps showing the occurrence of various flow patterns as a function of gas and liquid flow rates were constructed. Earth gravity two-phase flow models were compared to the results of the microgravity experiments and in some cases modified. Models were developed to predict the transitions on the flow pattern maps. Three flow patterns, bubble, slug and annular flow, were observed in microgravity. These patterns were found to occur in distinct regions of the gas-liquid flow rate parameter space. The effect of liquid viscosity, surface tension and tube diameter on the location of the boundaries of these regions was small. Void fraction and Weber number transition criteria both produced reasonable transition models. Void fraction and bubble velocity for bubble and slug flows were found to be well described by the Drift-Flux model used to describe such flows in earth gravity. Pressure drop modeling by the homogeneous flow model was inconclusive for bubble and slug flows. Annular flows were found to be complex systems of ring-like waves and a substrate film. Pressure drop was best fitted with the Lockhart- Martinelli model. Force balances suggest that droplet entrainment may be a large component of the total pressure drop.

Bousman, William Scott↗