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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 1,783 records · Page 99

Battery Key Performance Projections based on Historical Trends and Chemistries

Recent improvements in state-of-the-art (SOA) batteries driven by the automotive sector have led to many electrified aircraft concepts choosing batteries as the preferred energy-storage method. Current SOA batteries are at the point of enabling certain hybrid and all-electric aircraft, particularly small, short range, lower speed aircraft. Higher performance batteries improve aircraft range and can enable larger, higher speed aircraft. In this work, we develop specific energy projections for future electrified aircraft. The projections are developed based on examining historical commercial SOA trends as well as practical limitations of future chemistries. Accurate projections of future specific energy values are important for estimating the timeline for commercial introduction of electrified aircraft. This work estimates nominal cell level specific energies for rechargeable batteries of 489 Wh/kg by 2030, 638 Wh/kg by 2040, and 764 Wh/kg by 2050. More conservative as well as more aggressive estimates are also provided.

Blake Tiede↗

Indian Ocean warming as key driver of long-term positive trend of Arctic Oscillation

Arctic oscillation (AO), which is the most dominant atmospheric variability in the Northern Hemisphere (NH) during the boreal winter, significantly affects the weather and climate at mid-to-high latitudes in the NH. Although a climate community has focused on a negative trend of AO in recent decades, the significant positive trend of AO over the last 60 years has not yet been thoroughly discussed. By analyzing reanalysis and Atmospheric Model Inter-comparison Project (AMIP) datasets with novel pacemaker experiments, we found that sea surface temperature warming in the Indian Ocean is conducive to the positive trend of AO from the late 1950s. The momentum flux convergence by stationary waves due to the Indian Ocean warming plays an important role in the positive trend of AO, which is characterized by a poleward shift of zonal-mean zonal winds. In addition, the reduced upward propagating wave activity flux over the North Pacific due to Indian Ocean warming also plays a role to strengthen the polar vortex, subsequently, it contributes to the positive trend of AO. Our results imply that the respective warming trend of tropical ocean basins including Indian Ocean, which is either anthropogenic forcing or natural variability or their combined effect, should be considered to correctly project the future AO’s trend.

Indian Ocean↗

Clean Air Policies Are Key for Successfully Mitigating Arctic Warming

A tighter integration of modeling frameworks for climate and air quality is urgently needed to assess the impacts of clean air policies on future Arctic and global climate. We combined a new model emulator and comprehensive emissions scenarios for air pollutants and greenhouse gases to assess climate and human health co-benefits of emissions reductions. Fossil fuel use is projected to rapidly decline in an increasingly sustainable world, resulting in far-reaching air quality benefits. Despite human health benefits, reductions in sulfur emissions in a more sustainable world could enhance Arctic warming by 0.8 °C in 2050 relative to the 1995–2014, thereby offsetting climate benefits of greenhouse gas reductions. Targeted and technically feasible emissions reduction opportunities exist for achieving simultaneous climate and human health co-benefits. It would be particularly beneficial to unlock a newly identified mitigation potential for carbon particulate matter, yielding Arctic climate benefits equivalent to those from carbon dioxide reductions by 2050.

Atmospheric chemistry↗

Development and Validation of Two-Phase CFD Models for Key Elements of Propellant Tank CFM Operations in 1G and Microgravity – An Overview

This paper presents an overview of the state-of-the-art two-phase CFD models that have been developed for various propellant tank storage and transfer operations in 1g, partial gravity and microgravity. The models are developed in the framework of the industry standard ANSYS/Fluent CFD code, the capabilities of which have been significantly enhanced and customized through incorporation of unique submodels via User Defined Functions (UDF)s to satisfy the requirements of its intended variable gravity Cryogenic Fluid Management (CFM) applications. These models/submodels have been validated against experimental data that cross spatial scales, fluid types, and gravity levels in order to properly anchor the models’ physical and numerical fidelity. The CFM application/processes that have been modeled include tank self-pressurization, tank autogenous pressurization, tank pressure control using both subcooled jet mixing and droplet spray injection mechanisms, tank chilldown/filling, tank drainage, tank slosh for both volatile and non-volatile fluids. The strength and shortcomings of the two-phase models for each application is highlighted and discussed briefly.

Propellant Storage & Pressure Control↗

Development and Validation of Two-Phase CFD Models for Key Elements of Propellant Tank CFM Operations in 1G and Microgravity –An Overview

This paper presents an overview of the state-of-the-art two-phase CFD models that have been developed for various propellant tank storage and transfer operations in 1g, partial gravity, and microgravity. The models are developed in the framework of the industry standard ANSYS/Fluent CFD code, the capabilities of which have been significantly enhanced and customized through the incorporation of unique submodels via User Defined Functions (UDF)s to satisfy the requirements of its intended variable gravity Cryogenic Fluid Management (CFM) applications. These models/submodels have been validated against experimental data that cross spatial scales, fluid types, and gravity levels in order to properly anchor the models’ physical and numerical fidelity. The CFM application/processes that have been modeled include tank self-pressurization, tank autogenous pressurization, tank pressure control using both subcooled jet mixing and droplet spray injection mechanisms, tank chilldown/filling, tank drainage, tank slosh for both volatile and non-volatile fluids. The strength and shortcomings of the two-phase models for each application are highlighted and discussed briefly.

Computational Fluid Dynamics↗

Analysis of Input from Wildfire Incident Experts to Identify Key Risks and Hazards in Wildfire Emergency Response

The United States Department of Agriculture (USDA) describes wildland fires as, “a force of nature that can be nearly as impossible to prevent, and as difficult to control, as hurricanes, tornadoes and floods.” Existing challenges in managing wildland fires often put first responders’ lives at risk. The emergence of drones and their capabilities to supplement human efforts could alleviate some, if not all, of those risks that first responders face during wildfire management efforts. However, the process of adding drones to wildfire response has come with its own challenges as well. NASA’s System-Wide Safety Project is working towards overcoming these challenges to enable routine transfer of risk from responders to aviation assets. The concept of operations and model-based systems engineering (MBSE) effort for this shift is underway. To inform and to validate the MBSE effort, we delivered a questionnaire to wildland firefighting experts on the hazards they currently face. This questionnaire has given us insight and a better understanding of the challenges related to the use of drones from a first responder’s point of view. We are using this information to better address responders’ concerns, develop a safety management system, and eliminate the roadblocks that prevent the use of drones in wildfire management.

Wildfire↗

Meteoritic Carbonates - The Key to Sampling Extraterrestrial Fluids?

Fluid inclusions are naturally occurring mineral features that preserve trapped fluid phases inside a solid phase. These cavities exist as a closed system, recording the environmental conditions present during entrapment – both physical and chemical. As a result, fluid inclusions are great candidates for directly studying past fluid activity on extraterrestrial bodies within the Solar System. On Earth, fluid inclusions are abundant as they occur within numerous host minerals. They are a powerful tool for accurately and directly understanding the driving processes in various geological environments. In contrast, extraterrestrial fluid inclusions have only been positively identified on three separate occasions within host materials ranging from ordinary chondrites to C/B-type asteroid mission return samples. The possibility of directly studying the fluids involved in aqueous alteration and accurately constraining their heliocentric distances drives the hunt for these elusive capsules. Our goals are to locate new fluid inclusion candidates (hereon referred to as candidates) and assess whether fluid inclusions are a common feature within meteoritic carbonates and why they may have eluded detection for so long. We also aim to characterize the host grain’s mineralogical properties and assess the potentially preferential conditions for fluid entrapment on the asteroid parent body.

P A B Krizan↗

Microbial Optical Data Processing: A Key Step in the Metabolic Assessment of Lunar Explorer Instrument for Space Biology Applications (LEIA) and Biosentinel’s Payload Data

The BioSensor payload platform on BioSentinel and LEIA autonomously collects optical data from microbial model organisms in liquid culture. The BioSensor is designed to monitor metabolic activity using absorbance measurements of cell density and alamarBlue, a readily available colorimetric redox indicator dye. BioSentinel, a pioneering NASA CubeSat, uses yeast to study deep space radiation. LEIA investigates radiation and lunar gravity response. The experimental setup includes 16 wells equipped with three LEDs (570, 630, and 850 nm) and their corresponding photodetectors. One well is a calibration control without biology while the rest have desiccated cultures. Autonomous rehydration initiates the experiment. Data from the BioSensor are received from the flight and ground units, enabling comparison to uncover location-based metabolic rate variations. This study presents a Python Jupyter notebook developed for efficient data processing of multiple CSV files containing date and time columns, temperature, and well illumination data. It offers a user-friendly interface while maintaining computational power, automatically recognizing and iteratively processing data files in a user-input path. A Hampel filter with a short window eliminates outlier artifacts from sensor dropout. Because absorbance is a relative measurement, conversion from raw illumination requires defining a “blank” value, so the first data points are averaged to provide the necessary denominator. A cube-root function correction mitigates undesired drift caused by air pockets during the fluidic card filling phase, maintaining optical path length consistency. Beer-Lambert's law is applied to further convert absorbance values to cell and dye form concentrations, the desired science parameters. The processed data are saved and visualized as SVG plots. Future plans include extracting specific science parameters from the processed data like growth rate and metabolic rate, and identification of features corresponding to metabolic and phenotypic shifts such as starvation, shifts from aerobic to anaerobic growth, and osmotic stresses.

Space biology↗