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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 307 records · Page 17
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Frontier Job-Centric Telemetry Dataset

Comprehensive analysis of high-performance computing (HPC) systems requires linking workload execution to system behavior. This kind of analysis is vital for diagnosing performance issues, managing capacity, detecting anomalous workloads, and understanding how applications interact with system hardware. This job-centric telemetry dataset unifies scheduler job records with node-level measurements, enabling direct association between workloads and their corresponding power, thermal, and performance characteristics. It contains sanitized, scheduler related metadata for 152,400 individual jobs that ran on the Frontier supercomputer and ended on selected days throughout 2024 and 2025, a subpopulation of ~6.8% of the total number of allocated jobs with non-zero run time on the system over that same period. Each is linked with files that contain telemetry time series records of the power utilization and temperature behavior of its allocated nodes and their processors during the run time of the job. Where available, a portion of the job files also contain network performance time series. Jobs are sampled from select days that reflect normal levels of user activity and possess job size distributions with large numbers of leadership class jobs (>20% of Frontier nodes). Jobs in this dataset attempt to best represent successful user workflows.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Data and scripts associated with “When do Riverine Systems 'Feel the Burn'? Simulating How Burn Extent and Severity Modulate Hydrologic Controls on Biogeochemical Export” (v2)

This data package is associated with the publication “When do Riverine Systems 'Feel the Burn'? Simulating How Burn Extent and Severity Modulate Hydrologic Controls on Biogeochemical Export” published in Water Resources Research (Wampler et al. 2025; preprint: https://doi.org/10.22541/essoar.174438106.63564767/v1). This study used the Soil and Water Assessment Tool (SWAT), a processed based model to explore the impacts of area burned and burn severity on streamflow, nitrate, and dissolved organic carbon (DOC) in two test basins: a semi-arid, mixed land use basin and a humid, primarily forested basin. We developed 1800 wildfire scenarios that we ran in each basin: 20 different burn extents (5 to 100% by 5%), 3 different burn severities (low, moderate, and high), and 30 different post-fire precipitation scenarios. We also ran an additional 30 scenarios associated with no wildfire for the 30 post-fire precipitation scenarios. For each scenario we were interested in the change in runoff ratio (streamflow) and average concentration and annual loads (nitrate and DOC) across the wildfire scenarios. This data package contains the data and scripts required to build SWAT models for the two test basins, create and run the wildfire scenarios, and generate the data summaries and figures used in the associated manuscript. This data package was originally published in March 2025. It was updated in January 2026 (v2; new and modified files) to include the final files after the manuscript went through reviews. See the change history section below for more details. For details on how to navigate data packages generated by this project, see https://data.ess-dive.lbl.gov/portals/PNNLRiverCorridorSFA/About.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Field Sensitivity Analysis of Turbulence Model Parameters for Flow Over a Wing

Reynolds-averaged-Navier-Stokes (RANS) turbulence models are a critical tool in computational-fluid-dynamics simulations of aerodynamic systems, but simulation results can be highly sensitive to RANS-model parameter choices. Sensitivity analysis can be used to quantify these impacts, and the objective of this study is to demonstrate field sensitivity analysis with respect to ten parameters in the 2003 Menter shear-stress-transport (SST) turbulence model. Here, the analysis is demonstrated for an application relevant to wind energy, namely, flow over a NACA 0015 wing at 12 degree angle of attack and a Reynolds number of 1.5 x 10 6 . We quantify sensitivity using Sobol indices and the mean-squared gradient, which are estimated using polynomial chaos and active subspace models, respectively. Our results indicate that there are substantial spatial variations in parameter sensitivities, with different sets of most-sensitive parameters near the wing, as well as in the downstream wake, consistent with the physical interpretations of the turbulence model inputs. We show that, for this particular turbulence model and flow, simultaneous dimension reduction is possible across all quantities of interest, enabling efficient exploration of model outcomes. Ultimately, this analysis provides new insights into turbulence model parameter sensitivities in incompressible flows, and also demonstrates the implementation of field sensitivity analysis for applications relevant to aerodynamics simulations.

17 WIND ENERGY↗
DOE OSTI2020

Initial full core SMR simulations with NekRS

This document describes the completion of a recent milestone of the ExaSMR program concerning "Full core simulations". The ExaSMR project is developing tools for coupling Monte Carlo (MC) radiation transport solvers to a computational fluid dynamics (CFD) solver. Work is based on the Shift MC, OpenMC MC, and Nek5000/NekRS CFD codes. As part of this milestone, a novel set of pin-resolved CFD full-core simulations have been performed for the first time. These simulations represent a significant increase in capability in what is now possible with CFD on pre-Exascale systems. The simulations have been performed with the spectral element solvers NekRS on the supercomputer Summit. Multiple simulations campaigns have been conducted: (1) LES simulations in bare bundle, (2) RANS simulations in bare bundles, (3) RANS simulations with momentum sources and (4) Conjugate heat transfer calculations.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

A physics-informed data-driven low order model for the wind velocity deficit at the wake of isolated buildings

Detailed simulations of the Atmospheric boundary layer (ABL) provides information on wind velocity, direction and turbulence for optimizing the design of wind turbines and wind farms and their operations. Distributed wind turbines have been considered for use in urban or suburban areas for covering energy needs using a sustainable energy solution. Simulations of high Reynolds number turbulent ABL flows past obstacles can be used for the prediction of the velocity deficit and turbulence characteristics in the leeward side of building-like obstacles, allowing for the estimation of power losses and fatigue loads in wind turbines. However, fully three-dimensional simulations of high Reynolds number ABL flows using Large Eddy Simulation (LES) or Reynolds Average Navier-Stokes Simulations (RANS) continue to require large computational/ execution times. As a result, these 3D simulations may not be ideal tools for the rapid assessment of wind energy potential. In the present study, 3D numerical results from wall resolved RANS simulations were used for the development of a low order model that allows the rapid assessment of wind velocity and turbulence in the leeward side of an isolated building.

17 WIND ENERGY↗
DOE OSTI2021

Machine Learning Assisted Safety Modeling and Analysis of Advanced Reactors

With the advances in computational power and numerical methods, analysts can now rely on first-principle simulations to predict ultra-fine details in a variety of applications. Advances in machine learning (ML) have produced algorithms that can now learn high-level abstractions via hierarchical models. This project aims to leverage advances in ML techniques and the available high-resolution simulation data to develop a novel modeling and simulation (M\&S) methodology for reactor safety analysis. While application-agnostic ML techniques are available, complex physics constraints need to be incorporated into ML techniques to build ML-based closures for computationally efficient predictive simulations. This project intends to develop a physics-guided data-driven multi-scale methodology for M\&S of advanced reactors. The project focuses on thermal fluid (T/F) phenomena, which play major roles in advanced reactor safety. Specifically, we propose a data-driven coarse-mesh turbulence model based on local flow features for the transient analysis of thermal mixing and stratification in a sodium-cooled fast reactor (SFR). The model has a coarse-mesh setup to ensure computational efficiency, while it is trained by fine-mesh computational fluid dynamics (CFD) data with Reynolds-averaged Navier-Stokes (RANS) turbulence model to ensure accuracy. Three different neural networks are developed and tested for loss-of-flow transients in the hot pool of SFR, i.e. the densely connected convolutional neural network (DCNN), long-short-term-memory network based on proper orthogonal decomposition (POD-LSTM), and the DCNN informed by LSTM (DCNN-LSTM). The performances of these three neural networks are evaluated based on baseline models. The DCNN-LSTM model has been chosen for further hyperparameter optimization. Furthermore, based on a simplified two-dimensional case, uncertainty quantification (UQ) of the developed ML-based closure are investigated with three methods, i.e. Monte Carlo dropout, deep ensemble, and Bayesian neural network. The developed ML-based turbulent viscosity closure relation based on deep ensemble is then integrated into the system analysis module SAM and serves as a term in the conservation equations. Such a SAM-ML based procedure guarantees that the obtained results are consistent with the physical constraints of the thermal-fluid system. The SAM-ML simulation on the same loss-of-flow transient showed comparable accuracy with the CFD simulation but with a much coarser mesh setup. Last but not least, the ML-based closure improvement with the support of higher-fidelity data from large eddy simulation (LES) is discussed. As a first step towards this direction, a baseline LES simulation is performed to obtain comparable data with RANS results. Based on the early results, future investigation on further improving the ML-based closure is discussed. We believe the developed approach that combines scientific machine learning with nuclear system analysis code can benefit the advanced reactor community as more accurate safety analyses will better characterize reactor safety margins and reduce licensing efforts.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

Towards optimal gas cooling with minimal aero-optical distortion for a laser amplifier head

Next-generation lasers combining high-peak-power, ultrashort pulses with high repetition rates have the potential to efficiently deliver the high-average-power outputs required by many emerging technologies and areas of research. This work introduces a three-stage workflow consisting of low- and high-fidelity fluid simulations, in addition to aero-optical analyses. The final goal is to optimize gas cooling within a laser amplifier head while maintaining minimal aero-optical distortions. Low-fidelity RANS simulations are used to obtain mean flow solutions and transition locations. High-fidelity LES simulations, informed by their RANS counterparts, provide solutions containing density fluctuations, which are then passed on to the aero-optical analysis. The aero-optical analysis provides insight into the optical quality of the laser beam passing through the flow found in the LES results.

42 ENGINEERING↗
DOE OSTI2023

Report on ISR-1 High-Altitude Balloon Flight

To test small technologies at lower cost for space science applications, LANL has developed a small high altitude balloon payload that could, in the future, be regularly and inexpensively launched from LANL. A neutron detector, NEMO, was integrated to evaluate its performance in a space-like mixed-radiation environment and collect neutron data in the atmosphere. In collaboration with EES-14, a high-altitude balloon payload was launched from LANL Technical Area 51 on February 27, 2023 and April 17, 2023. For real-time geolocation, a SAM-M8Q M8 GNSS module was used to get position and time, and an Iridium RockBLOCK 9603 was used to communicate with the ground using the Iridium satellite fleet. These modules were all controlled using an Iteaduino Mega microcontroller board. Finally, a High Altitude Science Eagle Flight Computer with a temperature pressure sensor ran independently, writing data to an SD card. All of these modules were powered by a 5 mAh lithium polymer battery. The battery was attached to the bottom of the payload while the remaining electronics were embedded in the underside of the top of the payload. These modules were wired as seen in Figure 1-2. The Iteaduino Mega microcontroller board was programmed to use the RockBLOCK to send a message once every 10 minutes containing neutron and GPS data read off the NEMO and SAM M8Q, respectively. Once the message send attempt finished, the RockBLOCK would be slept for the rest of the 10 minute interval. The Eagle Flight Computer ran continuously throughout the flight, taking data every 6 seconds. The RockBLOCK message data was set up to be delivered from the Iridium satellite fleet to a website, where it was stored and parsed to create live maps and plots for analysis and balloon retrieval. The RockBLOCK message data was additionally configured to be sent to an email as a fail-safe. The payload was ground-tested successfully for over 50 hours, with multiple revisions occurring to best prepare for conditions at altitude and improve the software and firmware to fix any issues that cropped up with the data pipeline. Additional to the balloon payload, the flight had an attached iMet-4 radiosonde and Garmin T5 GPS Dog Collar. The radiosonde provided GPS and meteorological data. The T5 dog collar is used along with a Garmin Astro 430 to track the balloon at a range of up to 9 miles for retrieval. The balloon itself was initially a 1600 g meteorological balloon with an attached High Altitude Science parachute, both of which can be seen in Figure 1-3. After the first flight, the EES team swapped to a Rocketman parachute.

42 ENGINEERING↗
DOE OSTI2025

INTEGRATE – Inverse Network Transformations for Efficient Generation of Robust Airfoil and Turbine Enhancements

The INTEGRATE (Inverse Network Transformations for Efficient Generation of Robust Airfoil and Turbine Enhancements) project developed a new inverse-design capability for the aerodynamic design of wind turbine rotors using invertible neural networks. Training data was obtained from improved turbulence and transition models for RANS and hybrid RANS/LES solvers with machine-learned physics-based data-augmented corrections and then using the resulting neural-network(s) augmented RANS model to run thousands of 2-D and 3-D CFD simulations.

17 WIND ENERGY↗
DOE OSTI2026

Neutral beams for the burning plasma era: Simulations and modeling of deuterium ion beams for plasma heating (CRADA Final Report)

Together with Realta Fusion, we set up several simulation scenarios and ran simulations using the WarpX code which is developed by LBNL and especially by members of the LBNL team. We investigated beam transport and beam neutralization and ran optimization and benchmark simulations. To achieve this, several new features were added to the warpX code. These code additions will also be beneficial to other users of warpX including several fusion companies and researchers at National Laboratories. Furthermore, we supported Realta Fusion in setting up their own instances of WarpX. We presented our results at the American Physical Society Division of Plasma Physics meeting and are in the process of writing a publication that will be submitted to a peer-reviewed journal to share our results with the broader community.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

A numerical investigation of coal particle modeling for the inlet section of a pressurized oxy-combustion burner

Concerns over climate change have led to numerous efforts to develop low-carbon technologies, and pressurized oxy-combustion (POC) is a promising candidate to reduce carbon emissions in the power industry. Designing an effective burner for such technologies is vital for the development of these and other coal combustion technologies. Because of the high pressure, the volume fraction of coal particles at the fuel inlet of the pressurized oxy-combustor burner is close to or even higher than the maximum limit for commercial CFD codes (e.g., ANSYS FLUENT). At these high particle volume fractions, the interactions among particles, fluid flow and wall need to be re-evaluated. The present computational work is a first step in a systematic analysis of the influence of various parameters, like method of particle release, release location, and particle size, in a pilot-scale POC combustor, developed at Washington University in St. Louis (WUSTL). In the POC process, pulverized coal is burned under elevated pressure in an O2-CO2 environment. Specifically, a 15-bar, 100 kWth, POC combustor is modeled employing Ansys FLUENT commercial sodtware using the Reynolds-Averaged Navier-Stokes (RANS) approach. It is revealed that for this pilot-scale, pressurized burner, velocity profiles in the near-wall region exhibit some anomalies. In order to investigate the influence of particle loading in the near-wall region, particle release location was investigated. The numerical simulations incorporate the coupling between the turbulent flow and the particles. A sensitivity investigation of particle release location found that by tuning the release location, the velocity profile can be consistent with the pure gas flow velocity profile. More importantly, the particle releasing location also affects flame stability. Particle size was also found to have a significant impact on particle trajectory, flame stability and temperature. Finally, Large Eddy Simulations (LES) were performed and compared with the results from two-dimensional RANS.

Li, Lei↗
DOE OSTI2022

Validation of Calibrated k–ε Model Parameters for Jet-in-Crossflow

Previous efforts determined a set of calibrated, optimal model parameter values for Reynolds-averaged Navier–Stokes (RANS) simulations of a compressible jet in crossflow (JIC) using a $k–ε$ turbulence model. These parameters were derived by comparing simulation results to particle image velocimetry (PIV) data of a complementary JIC experiment under a limited set of flow conditions. Here, a $k–ε$ model using both nominal and calibrated parameters is validated against PIV data acquired from a much wider variety of JIC cases, including a realistic flight vehicle. The results from the simulations using the calibrated model parameters showed considerable improvements over those using the nominal values, even for cases that were not used in the calibration procedure that defined the optimal parameters. This improvement is demonstrated using a number of quality metrics that test the spatial alignment of the jet core, the magnitudes of multiple flow variables, and the location and strengths of vortices in the counter-rotating vortex cores on the PIV planes. These results suggest that the calibrated parameters have applicability well outside the specific flow case used in defining them and that with the right model parameters, RANS solutions for the JIC can be improved significantly over those obtained from the nominal model.

42 ENGINEERING↗
DOE OSTI2023

Multifidelity Approach to Sensitivity Estimation in Large-Eddy Simulation

A novel approach to compute affordable approximate sensitivities in a large-eddy simulation (LES) is proposed and assessed. The approach is based on solving a Reynolds-averaged Navier–Stokes (RANS) problem that has been linearized around the mean LES solution, with closure modeling required for the linearized changes in turbulent Reynolds stresses. In the present study, the closure modeling is based on a linearized algebraic turbulence model. The method is assessed for the flow over a NACA0012 airfoil at a fixed angle of attack, with the Reynolds number as the variable parameter. The results show that, provided an accurate linearized closure model, the method predicts the correct sensitivity of the skin friction coefficient and the mean velocity field at the cost of a linearized RANS, which provides an important proof-of-concept for this approach. Here, the linearized algebraic turbulence model with standard model coefficients produces a reasonably accurate sensitivity, but the results also suggest that accuracy could be gained from recalibrating the model coefficients for this new use of the model.

42 ENGINEERING↗
DOE OSTI2022

CFD simulations of electric motor end ring cooling for improved thermal management

Proper thermal management of an electric motor for vehicle applications extends its operating range. One cooling approach is to impinge Automatic Transmission Fluid (ATF) onto the rotor end ring. Increased ATF coverage correlates to enhanced heat transfer. Computational Fluid Dynamics (CFD) analytical tools provide a mechanism to assess motor thermal management prior to hardware fabrication. The complexity of the fluid flow (e.g., jet atomization, interface tracking, wall impingement) and heat transfer makes these simulations challenging. Computational costs are high when solving these flows on high-speed rotating meshes. Typically, a Volume-of Fluid (VOF) technique (i.e., two-fluid system) is used to resolve ATF dynamics within this rotating framework. Suitable numerical resolution of the relevant physics for thin films under strong inertial forces at high rotor speeds is computationally expensive, further increasing the run times. In this work, a numerical study of rotor-ring cooling by ATF is presented using a patent automated Cartesian cut-cell based method coupled with Automatic Mesh Refinement (AMR). This approach automatically creates the Cartesian mesh on-the-fly and can effectively handle complex rotating geometries by adaptively refining the mesh based on local gradients in the flow field which results in better resolution of the air-ATF interface. A Single non-inertial Reference Frame (SRF) approach is used to account for the rotating geometry and to further improve the overall computational efficiency. Quasi-steady state conditions are targeted in the analysis of the results. Important physics such as ATF jet structure, velocity detail near the air-jet interface, ATF coverage/accumulation on the ring surface, and cooling capacity are presented for a low-resolution Reynolds averaged Navier-Stokes (RANS), high-resolution RANS, and high-resolution Large-Eddy Simulation (LES) models. Computations are scaled over hundreds of cores on a supercomputer to maximize turnaround time. Each numerical approach is shown to capture the general trajectory of the oil jet prior to surface impingement. The high-resolution LES simulation, however, is superior in capturing small scale details and heat transfer between the free jet and surrounding air.

42 ENGINEERING↗
DOE OSTI2021

Large Eddy Simulations of Turbulent and Buoyant Flows in Urban and Complex Terrain Areas Using the Aeolus Model

Fast and accurate predictions of the flow and transport of materials in urban and complex terrain areas are challenging because of the heterogeneity of buildings and land features of different shapes and sizes connected by canyons and channels, which results in complex patterns of turbulence that can enhance material concentrations in certain regions. To address this challenge, we have developed an efficient three-dimensional computational fluid dynamics (CFD) code called Aeolus that is based on first principles for predicting transport and dispersion of materials in complex terrain and urban areas. The model can be run in a very efficient Reynolds average Navier–Stokes (RANS) mode or a detailed large eddy simulation (LES) mode. The RANS version of Aeolus was previously validated against field data for tracer gas and radiological dispersal releases. As a part of this work, we have validated the Aeolus model in LES mode against two different sets of data: (1) turbulence quantities measured in complex terrain at Askervein Hill; and (2) wind and tracer data from the Joint Urban 2003 field campaign for urban topography. As a third set-up, we have applied Aeolus to simulate cloud rise dynamics for buoyant plumes from high-temperature explosions. For all three cases, Aeolus LES predictions compare well to observations and other models. These results indicate that Aeolus LES can be used to accurately simulate turbulent flow and transport for a wide range of applications and scales.

42 ENGINEERING↗
DOE OSTI2022

Development of Explainable Data-Driven Turbulence Models with Application to Liquid Fuel Nuclear Reactors

Liquid fuel nuclear reactors offer innovative possibilities in terms of nuclear reactor designs and passive safety systems. Molten Salts Reactors (MSRs) with a fast spectrum are a particular type of these reactors using liquid fuel. MSFRs often involve large open cavities in their core in which the liquid fuel circulates at a high speed to transport the heat generated by the nuclear reactions into the heat exchangers. This high-speed flow yields a turbulent field with large Reynolds numbers in the reactor core. Since the nuclear power, the neutron precursor’s transport and the thermal exchanges are strongly coupled in the MSFR’s core cavity, having accurate turbulent models for the liquid fuel flow is necessary to avoid introducing significant errors in the numerical simulations of these reactors. Nonetheless, high-accuracy simulations of the turbulent flow field in the reactor cavity of these reactors are usually prohibitively expensive in terms of computational resources, especially when performing multiphysics numerical calculations. Therefore, in this work, we propose a novel method using a modified genetic algorithm to optimize the calculation of the Reynolds Shear Stress Tensor (RST) used for turbulence modeling. The proposed optimization methodology is particularly suitable for advanced liquid fuel reactors such as the MSFRs since it allows the development of high-accuracy but still low-computational-cost turbulence models for the liquid fuel. We demonstrate the applicability of this approach by developing high accuracy Reynolds-Averaged Navier–Stokes (RANS) models (averaged flow error less than 5%) for a low and a large aspect ratio in a Backward-Facing Step (BFS) section particularly challenging for RANS models. The newly developed turbulence models better capture the flow field after the boundary layer tipping, over the extent of the recirculation bubble, and near the boundary layer reattachment region in both BFS configurations. The main reason for these improvements is that the developed models better capture the flow field turbulent anisotropy in the bulk region of the BFS. Then, we illustrate the interest in using this turbulence modeling approach for the case of an MSFR by quantifying the impact of the turbulence modeling on the reactor key parameters.

42 ENGINEERING↗
NASA NTRS1974

Synthesis and evaluation of C-ether formulations for use as high temperature lubricants and hydraulic fluids

The formulation and evaluation of C-ether fluids for use in the hydraulic and lubrication systems of the space shuttle and advanced air breathing engines were studied to lower the pour point of a reference C-ether from -29 C to -40 C without changing its evaporation loss. Use of disiloxanes mixed with C-ethers gave a -40 C pour point fluid with little change in the desired evaporation loss or in oxidative stability. A second -40 C pour point fluid containing only C-ethers was also developed. A screening program tested lubrication additives for C-ethers and the new fluids. Six additive packages were chosen for evaluation in 316 C bearing tests, two for evaluation in 260 C pump tests. The goal of the bearing test was a 100 hour run. The rig was a specially designed 80-mm axially loaded ball bearing. The C-ether base fluid ran only one hour at 316 C before cage wear failure occurred. The best additive blends ran 47, 94 and 100 hours. The 96 hour test gave excessive deposits. The 100 hour test had no wear failures; an unexplained loss of cage silver occurred from areas of direct fluid impingement on the cage.

Clark, F. S.↗
NASA NTRS1987

Hemolysis in runners as evidenced by low serum haptoglobin: Implications for preflight monitoring of astronauts

Hematological parameters and serum haptoglobin were examined in 21 male employees of the Kennedy Space Center who were at 3 levels of physical activity: 7 subjects regularly ran more than 40 km (25 miles) per week (Group I); 7 ran 13 to 24 km (8 to 15 miles) per week (II), and 7 were sedentary (III). Blood was drawn on a different day of the week for five weeks. Differences between day of the week, visit number, and activity level were examined. No differences were observed for day of week or visit number; thus mean values for each variable were calculated for each subject. Variables did not differ among groups. However, trends with level of training were observed in some critical variables. Hemoglobin (Hb) and hematocrit (Hct) conformed to a staircase effect with Group I (14.5 gm/dl and 41.3 percent) lower than Group III (15.1 gm/dl and 42.9 percent). Reticulocyte count was higher and haptoglobin levels lower in Group I (1.35% and 75.7 gm/dl) than Group III (.99 percent and 132.9 gm/dl), with haptoglobin for the high mileage Group I in the clinically abnormal range. Since haptoglobin binds free Hb following RBC destruction, these results suggest that intravascular hemolysis occurs in trained male runners. These results may have special meaning for astronauts training before long-duration spaceflights, since the further reduction in red blood cells which is reported to occur during spaceflight could become detrimental to their health and performance.

Owens, Joyce↗