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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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All sourcesNASA NTRSDOE OSTI
NASA NTRS1991

Effect of 29 days of simulated microgravity on maximal oxygen consumption and fat-free mass of rats

Effects of a 29-days exposure to simulated microgravity on the values of maximal oxygen consumption and fat-free mass (FFM) and on the mechanical efficiency of running were investigated in rats randomly assigned to one of three regimens: head-down suspension (HDS) at 45 deg, horizontal suspension (HS), or cage control (CC). Before suspension and on days 7, 14, 21, and 28, five exercise performance tests were carried out, with measurements related to maximal oxygen consumption, treadmill run time, and mechanical efficiency. It was found that maximal oxygen consumption of both HDS and HS groups decreased significantly at day 7, after which the HDS rats remained decreased while the HS rats returned to presuspension values. Apparent mechanical efficiency in the HDS and HS groups decreased by 22-35 percent during the experimental period, and FFM decreased significantly.

Woodman, Christopher R.↗
NASA NTRS2004

Formation Control of the MAXIM L2 Libration Orbit Mission

The Micro-Arcsecond Imaging Mission (MAXIM), a proposed concept for the Structure and Evolution of the Universe (SEU) Black Hole Imaging mission, is designed to make a ten million-fold improvement in X-ray image clarity of celestial objects by providing better than 0.1 microarcsecond imaging. To achieve mission requirements, MAXIM will have to improve on pointing by orders of magnitude. This pointing requirement impacts the control and design of the formation. Currently the architecture is comprised of 25 spacecraft, which will form the sparse apertures of a grazing incidence X-ray interferometer covering the 0.3-10 keV bandpass. This configuration will deploy 24 spacecraft as optics modules and one as the detector. The formation must allow for long duration continuous science observations and also for reconfiguration that permits re-pointing of the formation. In this paper, we provide analysis and trades of several control efforts that are dependent upon the pointing requirements and the configuration and dimensions of the MAXIM formation. We emphasize the utilization of natural motions in the Lagrangian regions that minimize the control efforts and we address both continuous and discrete control via LQR and feedback linearization. Results provide control cost, configuration options, and capabilities as guidelines for the development of this complex mission.

Folta, David↗
NASA NTRS2003

Baroreflex-mediated heart rate and vascular resistance responses 24 h after maximal exercise

INTRODUCTION: Plasma volume, heart rate (HR) variability, and stimulus-response relationships for baroreflex control of forearm vascular resistance (FVR) and HR were studied in eight healthy men after and without performing a bout of maximal exercise to test the hypotheses that acute expansion of plasma volume is associated with 1) reduction in baroreflex-mediated HR response, and 2) altered operational range for central venous pressure (CVP). METHODS: The relationship between stimulus (DeltaCVP) and vasoconstrictive reflex response (DeltaFVR) during unloading of cardiopulmonary baroreceptors was assessed with lower-body negative pressure (LBNP, 0, -5, -10, -15, -20 mm Hg). The relationship between stimulus (Deltamean arterial pressure (MAP)) and cardiac reflex response (DeltaHR) during loading of arterial baroreceptors was assessed with steady-state infusion of phenylephrine (PE) designed to increase MAP by 15 mm Hg alone and during application of LBNP (PE+LBNP) and neck pressure (PE+LBNP+NP). Measurements of vascular volume and autonomic baroreflex responses were conducted on two different test days, each separated by at least 1 wk. On one day, baroreflex response was tested 24 h after graded cycle exercise to volitional exhaustion. On another day, measurement of baroreflex response was repeated with no exercise (control). The order of exercise and control treatments was counterbalanced. RESULTS: Baseline CVP was elevated (P = 0.04) from a control value of 10.5 +/- 0.4 to 12.3 +/- 0.4 mm Hg 24 h after exercise. Average DeltaFVR/DeltaCVP during LBNP was not different (P = 0.942) between the exercise (-1.35 +/- 0.32 pru x mm Hg-1) and control (-1.32 +/- 0.36 pru x mm Hg-1) conditions. However, maximal exercise caused a shift along the reflex response relationship to a higher CVP and lower FVR. HR baroreflex response (DeltaHR/DeltaMAP) to PE+LBNP+NP was lower (P = 0.015) after maximal exercise (-0.43 +/- 0.15 beats x min-1 x mm Hg-1) compared with the control condition (-0.83 +/- 0.14 beats x min-1 x mm Hg-1). CONCLUSION: Expansion of vascular volume after acute exercise is associated with altered operational range for CVP and reduced HR response to arterial baroreceptor stimulation.

Non-NASA Center↗
NASA NTRS2002

Differential half-maximal effects of human insulin and its analogs for in situ glucose transport and protein synthesis in rat soleus muscle

Analogs of human insulin have been used to discriminate between responses of metabolic and mitogenic (growth-related) pathways. This study compared the stimulatory effects of human insulin (HI) and 2 analogs (X2, B-Asp(9), B-Glu(27) and H2, A-His(8),B-His(4),B-Glu(10), B-His(27)) on glucose uptake and protein synthesis in rat soleus muscle in situ. Glucose uptake, estimated by intramuscular (IM) injection of 2-deoxy[1,2-3H]glucose with or without insulin, was maximally increased at 10(-6) mol/L for HI and X2 and 10(-7) mol/L for H2. HI had a larger effect (318%) than either X2 (156%) or H2 (124%). The half-maximal effect (ED(50)) values for HI, X2, and H2 were 3.3 x10(-8) mol/L, 1.7 x 10(-7) mol/L, and 1.6 x 10(-9) mol/L, respectively. Protein synthesis, estimated by protein incorporation of [(3)H]phenylalanine injected into muscles with or without insulin, was maximally increased at 10(-5) mol/L for HI and 10(-6) for X2 and H2. HI had a larger effect in stimulating protein synthesis (34%) than either X2 (25%) or H2 (19.8%). The ED(50) values for HI, X2, and H2 were 3.0 x 10(-7) mol/L, 3.2 x 10(-7) mol/L, and 1.0 x 10(-9) mol/L, respectively. The biological potency of each analog (ED(50)insulin/ED(50)analog) showed X2 to be less potent than HI for both glucose uptake (0.2) and protein synthesis (0.9), whereas H2 is more potent than HI with ratios of 20 and 300, respectively. These data suggest that this approach for studying insulin responsiveness in a single muscle in situ may be a useful tool for investigating insulin signaling in muscle in vivo. Copyright 2002, Elsevier Science (USA). All rights reserved.

NASA Discipline Developmental Biology↗
NASA NTRS1998

Restoration of peak vascular conductance after simulated microgravity by maximal exercise

We sought to determine if (i) peak vascular conductance of the calf was reduced following prolonged exposure to simulated microgravity, and (ii) if maximal cycle ergometry performed at the end of microgravity exposure stimulated a restoration of peak calf vascular conductance. To do this, peak vascular conductance of the calf was recorded following ischaemic plantar flexion exercise to fatigue in seven men after 16 days of head-down tilt (HDT) under two conditions: (i) after one bout of maximal supine cycle ergometry completed 24 h prior to performance of ischaemic plantar flexion exercise, and (ii) in a control (no cycle ergometry) condition. Following HDT, peak vascular conductance was reduced in the control condition (0.38 +/- 0.02 to 0.24 +/- 0.02 ml 100 ml-1 min-1 mmHg-1; P = 0.04), but was restored when subjects performed cycle ergometry (0.33 +/- 0.05 to 0.28 +/- 0.04 ml 100 ml-1 min-1 mmHg-1; P = 0.46). After HDT, time to fatigue during ischaemic plantar flexion exercise was not different from pre-HDT 24 h after performance of exhaustive cycle ergometry (120 +/- 24 vs. 122 +/- 19 s), but was decreased in the control condition (116 +/- 11 vs. 95 +/- 8 s; P = 0.07). These data suggest that a single bout of maximal exercise can provide a stimulus to restore peak vascular conductance and maintain time to fatigue during performance of ischaemic plantar flexion exercise.

NASA Discipline Cardiopulmonary↗
NASA NTRS2004

Formation Control of the MAXIM L2 Libration Orbit Mission

The Micro-Arcsecond X-ray Imaging Mission (MAXIM), a proposed concept for the Structure and Evolution of the Universe (SEU) Black Hole Imager mission, is designed to make a ten million-fold improvement in X-ray image clarity of celestial objects by providing better than 0.1 micro-arcsecond imaging. Currently the mission architecture comprises 25 spacecraft, 24 as optics modules and one as the detector, which will form sparse sub-apertures of a grazing incidence X-ray interferometer covering the 0.3-10 keV bandpass. This formation must allow for long duration continuous science observations and also for reconfiguration that permits re-pointing of the formation. To achieve these mission goals, the formation is required to cooperatively point at desired targets. Once pointed, the individual elements of the MAXIM formation must remain stable, maintaining their relative positions and attitudes below a critical threshold. These pointing and formation stability requirements impact the control and design of the formation. In this paper, we provide analysis of control efforts that are dependent upon the stability and the configuration and dimensions of the MAXIM formation. We emphasize the utilization of natural motions in the Lagrangian regions to minimize the control efforts and we address continuous control via input feedback linearization (IFL). Results provide control cost, configuration options, and capabilities as guidelines for the development of this complex mission.

Folta, David↗
NASA NTRS1996

Restoration of plasma volume after 16 days of head-down tilt induced by a single bout of maximal exercise

Seven healthy men performed maximal exercise 24 h before the end of 16 days exposure to 6 degrees head-down tilt (HDT) to test the hypothesis that such an exercise technique could restore plasma volume (PV) at the end of a simulated space mission. Exercise consisted of supine cycling with graded work rates increasing by 16 W/min to volitional fatigue and required an average of 16 min. The experimental protocol was a standard cross-over design in which the order of treatment (exercise or control) was counterbalanced across all seven subjects. PV, fluid intake (ad libitum), urine output, renal function, and hormones associated with fluid homeostasis were measured before HDT, 24 h before the end of HDT just prior to exercise, and at the end of HDT 24 h after exercise. HDT reduced PV by 16% in both control and exercise conditions. Maximal exercise completely restored plasma volume within 24 h to 3.9 +/- 3.2% of pre-HDT levels despite continued HDT. Compared with control, exercise induced a 660-ml larger positive fluid balance because of greater fluid intake and reduced urine volume during the 24 h after exercise. These results suggest that one bout of maximal leg exercise before return from 16 days of spaceflight may be completely effective in stimulating thirst and restoring plasma volume to preflight levels.

Non-NASA Center↗
NASA NTRS2005

An information maximization model of eye movements

We propose a sequential information maximization model as a general strategy for programming eye movements. The model reconstructs high-resolution visual information from a sequence of fixations, taking into account the fall-off in resolution from the fovea to the periphery. From this framework we get a simple rule for predicting fixation sequences: after each fixation, fixate next at the location that minimizes uncertainty (maximizes information) about the stimulus. By comparing our model performance to human eye movement data and to predictions from a saliency and random model, we demonstrate that our model is best at predicting fixation locations. Modeling additional biological constraints will improve the prediction of fixation sequences. Our results suggest that information maximization is a useful principle for programming eye movements.

NASA Discipline Neuroscience↗
NASA NTRS2004

Formation Control for the MAXIM Mission

Over the next twenty years, a wave of change is occurring in the space-based scientific remote sensing community. While the fundamental limits in the spatial and angular resolution achievable in spacecraft have been reached, based on today s technology, an expansive new technology base has appeared over the past decade in the area of Distributed Space Systems (DSS). A key subset of the DSS technology area is that which covers precision formation flying of space vehicles. Through precision formation flying, the baselines, previously defined by the largest monolithic structure which could fit in the largest launch vehicle fairing, are now virtually unlimited. Several missions including the Micro-Arcsecond X-ray Imaging Mission (MAXIM), and the Stellar Imager will drive the formation flying challenges to achieve unprecedented baselines for high resolution, extended-scene, interferometry in the ultraviolet and X-ray regimes. This paper focuses on establishing the feasibility for the formation control of the MAXIM mission. MAXIM formation flying requirements are on the order of microns, while Stellar Imager mission requirements are on the order of nanometers. This paper specifically addresses: (1) high-level science requirements for these missions and how they evolve into engineering requirements; and (2) the development of linearized equations of relative motion for a formation operating in an n-body gravitational field. Linearized equations of motion provide the ground work for linear formation control designs.

Luquette, Richard J.↗
NASA NTRS2008

Quantum-Inspired Maximizer

A report discusses an algorithm for a new kind of dynamics based on a quantum- classical hybrid-quantum-inspired maximizer. The model is represented by a modified Madelung equation in which the quantum potential is replaced by different, specially chosen 'computational' potential. As a result, the dynamics attains both quantum and classical properties: it preserves superposition and entanglement of random solutions, while allowing one to measure its state variables, using classical methods. Such optimal combination of characteristics is a perfect match for quantum-inspired computing. As an application, an algorithm for global maximum of an arbitrary integrable function is proposed. The idea of the proposed algorithm is very simple: based upon the Quantum-inspired Maximizer (QIM), introduce a positive function to be maximized as the probability density to which the solution is attracted. Then the larger value of this function will have the higher probability to appear. Special attention is paid to simulation of integer programming and NP-complete problems. It is demonstrated that the problem of global maximum of an integrable function can be found in polynomial time by using the proposed quantum- classical hybrid. The result is extended to a constrained maximum with applications to integer programming and TSP (Traveling Salesman Problem).

Zak, Michail↗
NASA NTRS2018

Optimization of Second Fault Detection Thresholds to Maximize Mission POS

In order to support manned spaceflight safety requirements, the Space Launch System (SLS) has defined program-level requirements for key systems to ensure successful operation under single fault conditions. To accommodate this with regards to Navigation, the SLS utilizes an internally redundant Inertial Navigation System (INS) with built-in capability to detect, isolate, and recover from first failure conditions and still maintain adherence to performance requirements. The unit utilizes multiple hardware- and software-level techniques to enable detection, isolation, and recovery from these events in terms of its built-in Fault Detection, Isolation, and Recovery (FDIR) algorithms. Successful operation is defined in terms of sufficient navigation accuracy at insertion while operating under worst case single sensor outages (gyroscope and accelerometer faults at launch). In addition to first fault detection and recovery, the SLS program has also levied requirements relating to the capability of the INS to detect a second fault, tracking any unacceptable uncertainty in knowledge of the vehicle's state. This detection functionality is required in order to feed abort analysis and ensure crew safety. Increases in navigation state error and sensor faults can drive the vehicle outside of its operational as-designed environments and outside of its performance envelope causing loss of mission, or worse, loss of crew. The criteria for operation under second faults allows for a larger set of achievable missions in terms of potential fault conditions, due to the INS operating at the edge of its capability. As this performance is defined and controlled at the vehicle level, it allows for the use of system level margins to increase probability of mission success on the operational edges of the design space. Due to the implications of the vehicle response to abort conditions (such as a potentially failed INS), it is important to consider a wide range of failure scenarios in terms of both magnitude and time. As such, the Navigation team is taking advantage of the INS's capability to schedule and change fault detection thresholds in flight. These values are optimized along a nominal trajectory in order to maximize probability of mission success, and reducing the probability of false positives (defined as when the INS would report a second fault condition resulting in loss of mission, but the vehicle would still meet insertion requirements within system-level margins). This paper will describe an optimization approach using Genetic Algorithms to tune the threshold parameters to maximize vehicle resilience to second fault events as a function of potential fault magnitude and time of fault over an ascent mission profile. The analysis approach, and performance assessment of the results will be presented to demonstrate the applicability of this process to second fault detection to maximize mission probability of success.

Anzalone, Evan↗
NASA NTRS2018

Optimization of Second Fault Detection Thresholds to Maximize Mission Probability of Success

In order to support manned spaceflight safety requirements, the Space Launch System (SLS) has defined program-level requirements for key systems to ensure successful operation under single fault conditions. The SLS program has also levied requirements relating to the capability of the Inertial Navigation System to detect a second fault. This detection functionality is required in order to feed abort analysis and ensure crew safety. Increases in navigation state error due to sensor faults in a purely inertial system can drive the vehicle outside of its operational as-designed environmental and performance envelope. As this performance outside of first fault detections is defined and controlled at the vehicle level, it allows for the use of system level margins to increase probability of mission success on the operational edges of the design. A top-down approach is utilized to assess vehicle sensitivity to second sensor faults. A wide range of failure scenarios in terms of both fault magnitude and time is used for assessment. The approach also utilizes a schedule to change fault detection thresholds autonomously. These individual values are optimized along a nominal trajectory in order to maximize probability of mission success in terms of system-level insertion requirements while minimizing the probability of false positives. This paper will describe an approach integrating Genetic Algorithms and Monte Carlo analysis to tune the threshold parameters to maximize vehicle resilience to second fault events over an ascent mission profile. The analysis approach and performance assessment and verification will be presented to demonstrate the applicability of this approach to second fault detection optimization to maximize mission probability of success through taking advantage of existing margin.

Anzalone, Evan J.↗
DOE OSTI2024

GraMeR: Gra ph Me ta R einforcement learning for multi-objective influence maximization

Influence maximization (IM) is a combinatorial problem of identifying a subset of seed nodes in a network (graph), which when activated, provide a maximal spread of influence in the network for a given diffusion model and a budget for seed set size. IM has numerous applications such as viral marketing, epidemic control, sensor placement and other network-related tasks. However, its practical uses are limited due to the computational complexity of current algorithms. Recently, deep reinforcement learning has been leveraged to solve IM in order to ease the computational burden. However, there are serious limitations in current approaches, including narrow IM formulation that only consider influence via spread and ignore self-activation, low scalability to large graphs, and lack of generalizability across graph families leading to a large running time for every test network. In this work, we address these limitations through a unique approach that involves: (1) Formulating a generic IM problem as a Markov decision process that handles both intrinsic and influence activations; (2)incorporating generalizability via meta-learning across graph families. There are previous works that combine deep reinforcement learning with graph neural network, but this work solves a more realistic IM problem and incorporates generalizability across graphs via meta reinforcement learning. Extensive experiments are carried out in various standard networks to validate performance of the proposed Graph Meta Reinforcement learning (GraMeR) framework. Finally, the results indicate that GraMeR is multiple orders faster and generic than conventional approaches when applied on small to medium scale graphs.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Maximizing machine learning interatomic potential transferability for the discovery of the novel stellated octadecagon Bi18-Pt24 cage structure

Achieving true transferability remains the central challenge for Machine Learning Interatomic Potentials (ML-IAPs) in modeling complex bimetallic nanoclusters across their vast potential energy surfaces. We systematically investigate data selection strategies to optimize the Chebyshev Interaction Model for Efficient Simulation (ChIMES) potential for the Bi-Pt nanoclusters by comparing three innovative sampling methods: Principal Component Analysis (PCA)/k-means (structural diversity), t-distributedStochasticNeighborEmbedding (t-SNE)/k-means (force-space diversity), and hierarchical clustering. Quantitatively, the PCA/k-means strategy proved most effective for global accuracy, yielding the lowest force errors and achieving energy root mean square errors (RMSE) values competitive with Density Functional Theory (DFT), demonstrating excellent accuracy (19.16meV/atom). Structural validation on 34 unique DFT-optimized isomers further confirmed the potential’s high fidelity, with the best model PCA/k-means reproducing structures with an average root mean square deviation (RMSD) of 0.10 Å. However, the t-SNE methods, by maximizing diversity in the force space, demonstrated superior extrapolative power, leading to the more precise prediction of a novel stellated octadecagon Bi18⁢Pt24 cage structure, demonstrating the potential for exploring previously unseen morphologies. Our results establish a clear methodology for strategic data sampling that successfully maximizes ML-IAP transferability, providing an accurate and computationally efficient tool that accelerates the theoretical discovery of complex bimetallic architectures.

Vangheluwe, Raphaël [Université Paris-Saclay, CNRS↗
DOE OSTI2025

Simultaneous inference of equation of state parameters and unknown data errors with uncertainty quantification via hierarchical Bayesian posterior maximization

Equations of state (EOSs) are a key component in running hydrodynamic simulations as they relate the thermodynamic states for the material. The Davis reactants EOS is commonly used for modeling high explosives (HEs), and the EOS model parameters are calibrated using material specific data. The calibrations are often performed with uncertainty quantification via Bayesian inference to account for uncertainty in the data and generate ensembles of likely parameters. However, there are relatively few HE data sets to use for calibration and many are historical and lack error information. In this work, we simultaneously calibrate the Davis reactants EOS model parameters and unknown data error terms for the high explosive PBX 9501. To quantify the uncertainty in the models and the data, we use a Bayesian framework for the calibration and compute the hierarchical Bayesian posterior distribution with both a posteriori maximization approach and Markov Chain Monte Carlo. In general, we find that, given our assumptions, the two approaches result in similar calibrated parameters, posterior covariance matrices, and insights about the parameters but that the posterior maximization requires far less computational resources.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Analysis of Power-Maximizing Region 2 Controllers for Wind and Marine Turbines

Wind and marine energy are rapidly growing and complementary technologies that share some techniques for simplified modeling and control, particularly in below-rated flow speeds. A turbine operator has several choices of controller for maximizing power in Region 2. The simple and ubiquitous KΩ 2 control law is often effective but limited in its flexibility. Alternative controllers use reference tracking to split the control objectives into a low-bandwidth optimal tip-speed ratio tracking loop to maximize steady-state power and a higher-bandwidth proportional-integral control loop to reject inflow turbulence. Several options exist for identifying the slowly varying optimal set point during operation, based on estimating the inflow velocity or filtering the power or torque signals. This study compares the trade-offs between performance and other design priorities for a few choices of reference-tracking controller in the literature for reference wind and marine turbines. Analysis is performed in the frequency domain using the linearization of each controller, and the impact of turbulent disturbances on the closed-loop system is described. The controllers are simulated in OpenFAST to analyze their performance with higher-order nonlinear turbine dynamics.

17 WIND ENERGY↗
DOE OSTI2025

Maximally entangled gluons for any x

Individual quarks and gluons at small x inside an unpolarized hadron can be regarded as Bell states in which qubits in the spin and orbital angular momentum spaces are maximally entangled. Using the machinery of quantum information science, we generalize this observation to all values 0 < x <1 and describe gluons (but not quarks) as maximally entangled states between a qubit and a qudit. We introduce the conditional probability distribution P⁡(l z |s z ) of a gluon’s orbital angular momentum l z given its helicity s z . Restricting to the three states l z =0,±1, which constitute a qutrit, we explicitly compute P as a function of x.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Maximizing the Radar Generalized Image Quality Equation for Bistatic SAR Using Waveform Frequency Agility

The radar generalized image quality equation (RGIQE) is a metric used to measure both monostatic and bistatic synthetic aperture radar (BSAR) image quality, it is a function of signal-to-noise ratio (SNR) and 2-D bandwidth. The 2-D bandwidth is equal to the area of the transfer function’s (TF) passband region. With the exception of side-looking monostatic geometries, almost all monostatic and bistatic geometries have skewed passband shapes when waveform frequency parameters remain unchanged from pulse to pulse. Most synthetic aperture radar (SAR) applications require a rectangular-shaped passband region, this is achieved by inscribing a rectangular region within the skewed intrinsic passband region. Increasing skewness results in less inscription area reducing 2-D bandwidth, image SNR, and thus RGIQE capacity. In this article, a waveform with frequency agility is used to rectify the skewness that degrades RGIQE capacity. By changing the waveform’s center frequency and instantaneous bandwidth from pulse to pulse in a particular manner, the intrinsic passband region can be de-skewed. The de-skewed shape maximizes the inscription area thus maximizing 2-D bandwidth, image SNR, and RGIQE capacity. Here, three examples are given in this article, one monostatic geometry, and two bistatic geometries. RGIQE capacity is increased by 52.02%, 44.42%, and 79.09% for the three examples.

47 OTHER INSTRUMENTATION↗