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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 37 records · Page 2

Serial Propellant Tank Pressure Behavior in Artemis 1 Orion-ESM Propulsion System

An oscillatory pressure behavior was observed throughout the Orion-ESM propulsion system during the Artemis I mission. This behavior was attributed to propellant oscillations within the serial line connecting the two propellant tanks for each commodity. A linearized dynamic model of the serial propellant tank system was derived to explain this behavior. The model showed excellent agreement with the flight data, with the predicted system natural frequencies matching the flight data within 1%.

Liquid propulsion systems

Serial Propellant Tank Pressure Behavior in Artemis I Orion-ESM Propulsion System

An oscillatory pressure behavior was observed throughout the Orion-ESM propulsion system during the Artemis I mission. This behavior was attributed to propellant oscillations within the serial line connecting the two propellant tanks for each commodity. A linearized dynamic model of the serial propellant tank system was derived to explain this behavior. The model showed excellent agreement with the flight data, with the predicted system natural frequencies matching the flight data within 1 percent.

Propellant Tank

ESM Roughness Datasets (ARC)

This work focused on the effects on turbulent heat transfer due to surface roughness of types relevant to NASA entry missions, and was supported by NASA’s Entry Systems Modeling (ESM) Project. The emphasis was on new classes of woven materials, which are enabling for many missions.

heat transfer

esm_watermasses

A water mass analysis package for gridded ocean and atmospheric data and Earth system model output

Moore-Maley, Ben [@SciDAC-ImPACTS @E3SM-Project @M

Using Technology Readiness Level (TRL), Life Cycle Cost (LCC), and Other Metrics to Supplement Equivalent System Mass (ESM) in Advanced Life Support (ALS)

The ALS project plan goals are reducing cost, improving performance, and achieving flight readiness. ALS selects projects to advance the mission readiness of low cost, high performance technologies. The role of metrics is to help select good projects and report progress. The Equivalent Mass (EM) of a system is the sum of the estimated mass of the hardware, of its required materials and spares, and of the pressurized volume, power supply, and cooling system needed to support the hardware in space. EM is the total payload launch mass needed to provide and support a system. EM is directly proportional to the launch cost.

Jones, Harry

Overview and Assessment of the ESM Pressure Control Performance on Artemis I

The European Service Module propulsion system is a bipropellant hypergolic serial system used to provide translational thrust and attitude control for Orion. To control propellant tank pressure, a bang-bang pressure control system is employed. Each propellant commodity is regulated by a pressure control assembly consisting of two pressurization branches (a primary and redundant pressurization path) where each branch includes 3 valves in series. Regulation is accomplished via flight software control of two downstream solenoid valves triggered off propellant tank ullage pressure. This paper presents an overview of system level challenges which have been overcome to enable a successful Artemis I flight. Principle among the challenges was valve-to-valve pneumatic interactions which drove changes to the control scheme. During the Artemis I mission, the pressure control assembly was able to control tank pressure within allowable tolerances. Comparison between flight data and mathematical models are presented showing excellent agreement. Finally, during flight, a pressure surge was observed during the first regulation cycle when there was propellant in the upstream propellant tank. This was attributed to a gas hammer effect within the pressurization system and was not observable in a 1g environment. This paper also discusses the conclusion that this gas hammer effect is a nominal feature of the system during operations. Assessment of the in-flight performance of the electronic pressure regulation scheme on the European Service Module propulsion system shows the system behaved nominally during the Artemis I mission.

propulsion system

Overview and Assessment of the ESM Pressure Control Performance on Artemis I

The European Service Module propulsion system is a bipropellant hypergolic serial system used to provide translational thrust and attitude control for Orion. To control propellant tank pressure, a bang-bang pressure control system is employed. Each propellant commodity is regulated by a pressure control assembly consisting of two pressurization branches (a primary and redundant pressurization path) where each branch includes 3 valves in series. Regulation is accomplished via flight software control of two downstream solenoid valves triggered off propellant tank ullage pressure. This paper presents an overview of system level challenges which have been overcome to enable a successful Artemis I flight. Principle among the challenges was valve-to-valve pneumatic interactions which drove changes to the control scheme. During the Artemis I mission, the pressure control assembly was able to control tank pressure within allowable tolerances. Comparison between flight data and mathematical models are presented showing excellent agreement. Finally, during flight, a pressure surge was observed during the first regulation cycle when there was propellant in the upstream propellant tank. This was attributed to a gas hammer effect within the pressurization system and was not observable in a 1g environment. This paper also discusses the conclusion that this gas hammer effect is a nominal feature of the system during operations. Assessment of the in-flight performance of the electronic pressure regulation scheme on the European Service Module propulsion system shows the system behaved nominally during the Artemis I mission.

propulsion system

Overestimated natural biological nitrogen fixation translates to an exaggerated CO 2 fertilization effect in Earth system models

CO 2 fertilization of the terrestrial biosphere is limited by nitrogen. Biological nitrogen fixation (BNF) is the dominant natural nitrogen source to the terrestrial biosphere and can alleviate nitrogen limitation but is poorly constrained in Earth system models (ESMs). Here, in this study, we compare terrestrial BNF from an ensemble of ESMs of the 6th Coupled Model Intercomparison Project to a new global synthesis of observations across natural and agricultural biomes. We find that compared to observations, ESMs underestimate agricultural BNF but overestimate natural BNF in the present day by over 50%. Natural BNF is overestimated in the most productive ecosystems that contribute most to the terrestrial carbon sink (forests and grasslands). ESMs with different BNF representations yield a range of BNF responses to CO 2 enrichment. Some ESMs with phenomenological representations of BNF predict a natural BNF increase in response to a doubling of CO 2 that aligns with a meta-analysis of CO 2 enrichment experiments (31% increase) but fail to account for the substantial carbon cost of BNF. In contrast, ESMs with mechanistic representations of BNF account for its carbon cost as well as its regulation by nitrogen limitation but overestimate the BNF response to a doubling of CO 2 (135% increase). Overall, all current BNF representations in ESMs fall short of fully capturing its response to rising atmospheric CO 2 . Finally, we find a positive correlation between modeled present-day natural BNF and the CO 2 fertilization effect across ESMs, suggesting that overestimated natural BNF translates to an exaggerated CO 2 fertilization effect of approximately 11% in ESMs.

Biological nitrogen fixation

flat10MIP: an emissions-driven experiment to diagnose the climate response to positive, zero and negative CO2 emissions

Abstract. The proportionality between global mean temperature and cumulative emissions of CO2 predicted in Earth system models (ESMs) is the foundation of carbon budgeting frameworks. Deviations from this behavior could impact estimates of required net-zero timings and negative emissions requirements to meet the Paris Agreement climate targets. However, existing ESM diagnostic experiments do not allow for direct estimation of these deviations as a function of defined emissions pathways. Here, we perform a set of climate model diagnostic experiments for the assessment of transient climate response to cumulative CO2 emissions (TCRE), the Zero Emissions Commitment (ZEC), and climate reversibility metrics in an emissions-driven framework. The emissions-driven experiments provide consistent independent variables simplifying simulation, analysis and interpretation, with emissions rates more comparable to recent levels than existing protocols using model-specific compatible emissions from the CMIP DECK 1pctCO2 experiment, where emissions rates tend to increase during the experiment, such that at the time of CO2 doubling in year 70, emissions are much greater than present-day values. A base experiment, “esm-flat10”, has constant emissions of CO2 of 10 GtC per year (near-present-day values), and initial results show that the TCRE estimated in this experiment is about 0.1 K less than that obtained using 1pctCO2. A subset of ESMs exhibit land carbon sinks that saturate during this experiment. A branch experiment, esm-flat10-zec, illustrates that both positive and negative ZEC effects are less pronounced under esm-flat10 than under 1pctCO2 – the magnitude of ZEC50 in ESMs is, on average, reduced by 30 % compared with 1pctCO2 branch experiments. A final experiment, esm-flat10-cdr, assesses climate reversibility under negative emissions, where we find that peak warming may occur before or after net zero and that the asymmetry in temperature at a given level of cumulative emissions between the positive and negative emissions phases is well described by ZEC in most models. Further, we find that existing probabilistic simple climate model (SCM) ensembles tend to overestimate temperature reversibility compared with ESMs, highlighting the need for additional constraints. We propose a set of climate diagnostic indicators to quantify various aspects of climate reversibility. These experiments were suggested as potential candidates in CMIP7 and have since been adopted as “fast track” simulations.

Sanderson, Benjamin M

Earth-System-Model Evaluation of Cloud and Precipitation Occurrence for Supercooled and Warm Clouds Over the Southern Ocean's Macquarie Island

Over the remote Southern Ocean (SO), cloud feedbacks contribute substantially to Earth system model (ESM) radiative biases. The evolution of low Southern Ocean clouds (cloud-top heights < ∼ 3 km) is strongly modulated by precipitation and/or evaporation, which act as the primary sink of cloud condensate. Constraining precipitation processes in ESMs requires robust observations suitable for process-level evaluations. A year-long subset (April 2016–March 2017) of ground-based profiling instrumentation deployed during the Macquarie Island Cloud and Radiation Experiment (MICRE) field campaign (54.5∘ S, 158.9∘ E) combines a 95 GHz (W-band) Doppler cloud radar, two lidar ceilometers, and balloon-borne soundings to quantify the occurrence frequency of precipitation from the liquid-phase cloud base. Liquid-based clouds at Macquarie Island precipitate ∼ 70 % of the time, with deeper and colder clouds precipitating more frequently and at a higher intensity compared to thinner and warmer clouds. Supercooled cloud layers precipitate more readily than layers with cloud-top temperatures > 0 ∘C, regardless of the geometric thickness of the layer, and also evaporate more frequently. We further demonstrate an approach to employ these observational constraints for evaluation of a 9-year GISS-ModelE3 ESM simulation. Model output is processed through the Earth Model Column Collaboratory (EMC2) radar and lidar instrument simulator with the same instrument specifications as those deployed during MICRE, therefore accounting for instrument sensitivities and ensuring a coherent comparison. Relative to MICRE observations, the ESM produces a smaller cloud occurrence frequency, smaller precipitation occurrence frequency, and greater sub-cloud evaporation. The lower precipitation occurrence frequency by the ESM relative to MICRE contrasts with numerous studies that suggest a ubiquitous bias by ESMs to precipitate too frequently over the SO when compared with satellite-based observations, likely owing to sensitivity limitations of spaceborne instrumentation and different sampling methodologies for ground- versus space-based observations. Despite these deficiencies, the ESM reproduces the observed tendency for deeper and colder clouds to precipitate more frequently and at a higher intensity. The ESM also reproduces specific cloud regimes, including near-surface clouds that account for ∼ 25 % of liquid-based clouds during MICRE and optically thin, non-precipitating clouds that account for ∼ 27 % of clouds with bases higher than 250 m. We suggest that the demonstrated framework, which merges observations with appropriately constrained model output, is a valuable approach to evaluate processes responsible for cloud radiative feedbacks in ESMs.

cloud feedbacks

DiffESM: Conditional Emulation of Temperature and Precipitation in Earth System Models With 3D Diffusion Models

Earth system models (ESMs) are essential for understanding the interaction between human activities and the Earth's climate. However, the computational demands of ESMs often limit the number of simulations that can be run, hindering the robust analysis of risks associated with extreme weather events. While low-cost climate emulators have emerged as an alternative to emulate ESMs and enable rapid analysis of future climate, many of these emulators only provide output on at most a monthly frequency. This temporal resolution is insufficient for analyzing events that require daily characterization, such as heat waves or heavy precipitation. We propose using diffusion models, a class of generative deep learning models, to effectively downscale ESM output from a monthly to a daily frequency. Trained on a handful of ESM realizations, reflecting a wide range of radiative forcings, our DiffESM model takes monthly mean precipitation or temperature as input, and is capable of producing daily values with statistical characteristics close to ESM output. Combined with a low-cost emulator providing monthly means, this approach requires only a small fraction of the computational resources needed to run a large ensemble. We evaluate model behavior using a number of extreme metrics, showing that DiffESM closely matches the spatio-temporal behavior of the ESM output it emulates in terms of the frequency and spatial characteristics of phenomena such as heat waves, dry spells, or rainfall intensity.

54 ENVIRONMENTAL SCIENCES