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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 217 records · Page 12

Unveiling the Potential of MeshGraphNets for Predicting Subsurface Evolution in Carbon Storage Projects

This is the conference paper accompanying an oral presentation “Unveiling the Potential of MeshGraphNets for Predicting Subsurface Evolution in Carbon Storage Projects” at the 17th International Conference on Greenhouse Gas Control Technologies GHGT-17 held in Calgary, Canada, October 20-24 , 2024. Carbon capture and storage (CCS) technology is critical for mitigating climate change but requires effective subsurface reservoir management to ensure safe containment of injected CO2. Accurate predictions of reservoir pressure and saturation are essential for assessing long-term CCS performance. Traditional numerical simulations, while effective, are computationally intensive, time-consuming, and constrained by data discretization. Previous work has shown the effectiveness of MeshGraphNets (MGN), a graph-based machine learning framework, as an innovative alternative for predicting reservoir behavior. MGN leverages graph neural networks (GNNs) and mesh representations to model complex geological formations, offering superior adaptability across different discretizations and reservoir configurations. Classic MGN implementations utilize an autoregressive technique to predict future behavior based on current predictions, but this technique is hampered by error accumulation over time. To enhance the model accuracy in time-series predictions, this study implemented a multi-step rollout strategy that integrates autoregressive predictions during training to stabilize prediction of saturation over time. Using the Illinois Basin – Decatur Project (IBDP) dataset, comprising 100 simulations of CO2 injection, pressure, and saturation changes, the framework demonstrated its ability to learn spatial dependencies and temporal dynamics. With inputs including permeabilities, porosities, and injection rates, MGN accurately predicted CO2 plume evolution over time, even with limited training data. Moreover, the addition of a multi-step rollout procedure during training improved the ability of MGN to predict stably over time by ~15%. This research positions MGN, enhanced with multi-step rollout capabilities, as a robust and efficient tool for CCS applications. It advances the field by enabling precise, computationally efficient predictions of reservoir behavior, providing a foundation for the broader adoption of machine learning frameworks in CCS and other geoscience domains.

Holcomb, Paul↗

Labor Contractions Enhance Oxygenation and Behavioral Activity of Newborn Rat Pups

Labor contractions help instigate behavioral responses at birth (viz., breathing and suckling) that are vital for the newborn's adaptation to the extrauterine world (Ronca et al., 1996). In the present study, we analyzed the role of labor contractions in postpartum oxygenation and behavioral activity of newborn rat pups. Newborns were observed following either vaginal (V) or cesarean delivery. For cesarean delivery, day 21 pregnant dams' were administered a spinal transaction to eliminate lower body sensation, a laparotomy was performed and the uterus was maintained in a heated (37.5 C) bath. Four rat fetuses in one of the dams' paired uterine horn were compressed (C) to Simulate labor contractions (20 sec/min for 10 min) while four fetuses in the opposite horn were not compressed (NC). Fetuses were surgically removed from the uterus, stroked with a soft brush to mimic postnatal licking by the dam, the umbilical cord occluded. Pups were exposed to room temperature (22 C) for one hr, then nest temperature (33 C) for one hr. PO2, CO2, and O2, saturation were determined at 0, 30, 60, or 120 min post delivery using a blood gas analyzer. V and C delivered neonates showed comparable rates of PO2, CO2 and O2 saturation whereas NC neonates showed depressed levels at all time points (p<0.05). Respiratory rates of V, C and NC neonates increased significantly (p<0.05) over the first two postpartum hrs and did not differ across groups. Postpartum behavioral activity was significantly greater in V and C conditions and positively correlated with postnatal oxygenation. These findings provide further evidence for importance of labor contractions in early postpartum adaptation.

Mills, N. A.↗

DriveSense: A Noise-Resilient Framework for Driving Mode Identification

Accurate drive mode classification is essential for enhancing the reliability and predictive maintenance of heavy-duty electric trucks. This study proposes a novel fuzzy logic-based framework, DriveSense, for real-time drive mode classification, addressing key challenges such as sensor noise, transitional behaviors, and computational efficiency. The proposed approach integrates a two-stage filtering pipeline, combining adaptive outlier removal and a dynamic Kalman filter to enhance data quality. A fuzzy inference system with smoothened trapezoidal membership functions is then applied to classify driving modes into standstill, constant speed, acceleration, and deceleration while mitigating the effects of noise and edge cases. Performance evaluation using real-world and simulated drive cycles demonstrates significant improvements in classification accuracy (up to 97.8%), F1-score (up to 0.97), and robustness against noise, while reducing false positives. Comparative analysis against baseline models, demonstrates DriveSense’s superior accuracy and generalizability across diverse driving patterns. The framework’s lightweight and interpretable fuzzy inference engine operates with low computational latency, ensuring compatibility with real-time embedded systems typical of heavy-duty electric trucks. Moreover, DriveSense models transitional behaviors through overlapping fuzzy sets and adaptive borderline classification logic, enabling smooth identification of subtle shifts such as rolling stops or gradual deceleration. These results highlight DriveSense’s potential to enhance predictive maintenance strategies, reduce downtime, and support scalable, fleet-wide diagnostics.

Kumar, Praveen [Oak Ridge National Laboratory (ORN↗

Flight Test Results from the NF-15B Intelligent Flight Control System (IFCS) Project with Adaptation to a Simulated Stabilator Failure

Adaptive flight control systems have the potential to be more resilient to extreme changes in airplane behavior. Extreme changes could be a result of a system failure or of damage to the airplane. A direct adaptive neural-network-based flight control system was developed for the National Aeronautics and Space Administration NF-15B Intelligent Flight Control System airplane and subjected to an inflight simulation of a failed (frozen) (unmovable) stabilator. Formation flight handling qualities evaluations were performed with and without neural network adaptation. The results of these flight tests are presented. Comparison with simulation predictions and analysis of the performance of the adaptation system are discussed. The performance of the adaptation system is assessed in terms of its ability to decouple the roll and pitch response and reestablish good onboard model tracking. Flight evaluation with the simulated stabilator failure and adaptation engaged showed that there was generally improvement in the pitch response; however, a tendency for roll pilot-induced oscillation was experienced. A detailed discussion of the cause of the mixed results is presented.

Bosworth, John T.↗

Flight Test Results from the NF-15B Intelligent Flight Control System (IFCS) Project with Adaptation to a Simulated Stabilator Failure

Adaptive flight control systems have the potential to be more resilient to extreme changes in airplane behavior. Extreme changes could be a result of a system failure or of damage to the airplane. A direct adaptive neural-network-based flight control system was developed for the National Aeronautics and Space Administration NF-15B Intelligent Flight Control System airplane and subjected to an inflight simulation of a failed (frozen) (unmovable) stabilator. Formation flight handling qualities evaluations were performed with and without neural network adaptation. The results of these flight tests are presented. Comparison with simulation predictions and analysis of the performance of the adaptation system are discussed. The performance of the adaptation system is assessed in terms of its ability to decouple the roll and pitch response and reestablish good onboard model tracking. Flight evaluation with the simulated stabilator failure and adaptation engaged showed that there was generally improvement in the pitch response; however, a tendency for roll pilot-induced oscillation was experienced. A detailed discussion of the cause of the mixed results is presented.

Bosworth, John T.↗

Flight Test Results from the NF-15B Intelligent Flight Control System (IFCS) Project with Adaptation to a Simulated Stabilator Failure

Adaptive flight control systems have the potential to be more resilient to extreme changes in airplane behavior. Extreme changes could be a result of a system failure or of damage to the airplane. A direct adaptive neural-network-based flight control system was developed for the National Aeronautics and Space Administration NF-15B Intelligent Flight Control System airplane and subjected to an inflight simulation of a failed (frozen) (unmovable) stabilator. Formation flight handling qualities evaluations were performed with and without neural network adaptation. The results of these flight tests are presented. Comparison with simulation predictions and analysis of the performance of the adaptation system are discussed. The performance of the adaptation system is assessed in terms of its ability to decouple the roll and pitch response and reestablish good onboard model tracking. Flight evaluation with the simulated stabilator failure and adaptation engaged showed that there was generally improvement in the pitch response; however, a tendency for roll pilot-induced oscillation was experienced. A detailed discussion of the cause of the mixed results is presented.

Bosworth, John T.↗

Behavior and Performance Project

Behavior is an overt manifestation of underlying biology. As such, alterations in biological systems that result from spaceflight would be expected to evidence themselves in subtle or even pronounced changes in the behavior of that organism. These alterations in visible behavior may then indicate or even be diagnostic of alterations in the physical well-being of humans and other animals as they adapt to space environments or readapt to Earth--alterations that might not otherwise be detected without relatively invasive and frequently expensive procedures. Moreover, behavior and performance constitute the central standard for evaluating the mission success of spaceflight ventures. The success or failure of any excursion into space is primarily indexed by the ability of astronauts and cosmonauts to perform the tasks and experiments of any particular mission, to land a re-entry vehicle after extended exposure to microgravity (as with the space shuttle), or to make time-critical and life-saving repairs or other decisions while in orbit (as with the recent Mir events). Thus, understanding the effects spaceflight on behavior and performance is inherently important, in addition to those insights that behavior can provide about the physiological consequences of space adaptation.

Washburn, David A.↗

Neural Predictors of Visuomotor Adaptation Rate and Multi-Day Savings

Recent studies of sensorimotor adaptation have found that individual differences in task-based functional brain activation are associated with the rate of adaptation and savings at subsequent sessions. However, few studies to date have investigated offline neural predictors of adaptation and multi-day savings. In the present study, we explore whether individual differences in the rate of visuomotor adaptation and multi-day savings are associated with differences in resting state functional connectivity and gray matter volume. Thirty-four participants performed a manual adaptation task during two separate test sessions, on average 9 days apart. We found that resting state functional connectivity strength between sensorimotor, anterior cingulate, and temporoparietal areas of the brain was a significant predictor of adaptation rate during the early, cognitive phase of practice. In contrast, default mode network functional connectivity strength was found to predict late adaptation rate and savings on day two, which suggests that these behaviors may rely on overlapping processes. We also found that gray matter volume in temporoparietal and occipital regions was a significant predictor of early learning, whereas gray matter volume in superior posterior regions of the cerebellum was a significant predictor of late adaptation. The results from this study suggest that offline neural predictors of early adaptation facilitate the cognitive mechanisms of sensorimotor adaptation, with support from by the involvement of temporoparietal and cingulate networks. In contrast, the neural predictors of late adaptation and savings, including the default mode network and the cerebellum, likely support the storage and modification of newly acquired sensorimotor representations. These findings provide novel insights into the neural processes associated with individual differences in sensorimotor adaptation.

Cassady, Kaitlin↗

Toward applied behavior analysis of life aloft

This article deals with systems at multiple levels, at least from cell to organization. It also deals with learning, decision making, and other behavior at multiple levels. Technological development of a human behavioral ecosystem appropriate to space environments requires an analytic and synthetic orientation, explicitly experimental in nature, dictated by scientific and pragmatic considerations, and closely approximating procedures of established effectiveness in other areas of natural science. The conceptual basis of such an approach has its roots in environmentalism which has two main features: (1) knowledge comes from experience rather than from innate ideas, divine revelation, or other obscure sources; and (2) action is governed by consequences rather than by instinct, reason, will, beliefs, attitudes or even the currently fashionable cognitions. Without an experimentally derived data base founded upon such a functional analysis of human behavior, the overgenerality of "ecological systems" approaches render them incapable of ensuring the successful establishment of enduring space habitats. Without an experimentally derived function account of individual behavioral variability, a natural science of behavior cannot exist. And without a natural science of behavior, the social sciences will necessarily remain in their current status as disciplines of less than optimal precision or utility. Such a functional analysis of human performance should provide an operational account of behavior change in a manner similar to the way in which Darwin's approach to natural selection accounted for the evolution of phylogenetic lines (i.e., in descriptive, nonteleological terms). Similarly, as Darwin's account has subsequently been shown to be consonant with information obtained at the cellular level, so too should behavior principles ultimately prove to be in accord with an account of ontogenetic adaptation at a biochemical level. It would thus seem obvious that the most productive conceptual and methodological approaches to long-term research investments focused upon human behavior in space environments will require multidisciplinary inputs from such wide-ranging fields as molecular biology, environmental physiology, behavioral biology, architecture, sociology, and political science, among others.

Review↗

Actuator design for rotor control

Active control of dynamical behavior of rotor systems involves the following modeling of the rotor system including active elements as a control process, positioning of actuators and sensors, implementation of problem-adapted control concepts. The key to attaining the desired influence on the dynamic behavior of rotor systems lies in the presence of suitable actuators. Some types of actuators (magnetic, electrohydraulic and piezoelectric) will be discussed and their respective drawbacks indicated. Their design will be outlined and functional correlations will be presented. Theoretical and experimental results demonstrate that an improvement of the system dynamics by the use of control forces is always possible.

Ulbrich, H.↗

Altered astronaut lower limb and mass center kinematics in downward jumping following space flight

Astronauts exposed to the microgravity conditions encountered during space flight exhibit postural and gait instabilities upon return to earth that could impair critical postflight performance. The aim of the present study was to determine the effects of microgravity exposure on astronauts' performance of two-footed jump landings. Nine astronauts from several Space Shuttle missions were tested both preflight and postflight with a series of voluntary, two-footed downward hops from a 30-cm-high step. A video-based, three-dimensional motion-analysis system permitted calculation of body segment positions and joint angular displacements. Phase-plane plots of knee, hip, and ankle angular velocities compared with the corresponding joint angles were used to describe the lower limb kinematics during jump landings. The position of the whole-body center of mass (COM) was also estimated in the sagittal plane using an eight-segment body model. Four of nine subjects exhibited expanded phase-plane portraits postflight, with significant increases in peak joint flexion angles and flexion rates following space flight. In contrast, two subjects showed significant contractions of their phase-plane portraits postflight and three subjects showed insignificant overall changes after space flight. Analysis of the vertical COM motion generally supported the joint angle results. Subjects with expanded joint angle phase-plane portraits postflight exhibited larger downward deviations of the COM and longer times from impact to peak deflection, as well as lower upward recovery velocities. Subjects with postflight joint angle phase-plane contraction demonstrated opposite effects in the COM motion. The joint kinematics results indicated the existence of two contrasting response modes due to microgravity exposure. Most subjects exhibited "compliant" impact absorption postflight, consistent with decreased limb stiffness and damping, and a reduction in the bandwidth of the postural control system. Fewer subjects showed "stiff" behavior after space flight, where contractions in the phase-plane portraits pointed to an increase in control bandwidth. The changes appeared to result from adaptive modifications in the control of lower limb impedance. A simple 2nd-order model of the vertical COM motion indicated that changes in the effective vertical stiffness of the legs can predict key features of the postflight performance. Compliant responses may reflect inflight adaptation due to altered demands on the postural control system in microgravity, while stiff behavior may result from overcompensation postflight for the presumed reduction in limb stiffness inflight.

Clinical Trial↗

A Behavior Tree Approach for Battery-Aware Inspection of Large Structures Using Drones

Electric multi-rotor drones have been used to inspect several structures, including large buildings and dams. In these inspections, energy consumption is a concern. To prevent the drone from running out of battery, commercial drones usually come back to their home position when the battery level reaches a minimum threshold. The pilots then need to replace the battery and use their own experience to restart the inspection mission approximately from where it ended before the drone returned home. Instead of relying on the human operator, in this paper, we automate this process using behavior trees, which is an effective way to perform autonomous mission control and supervision. By integrating battery management strategies into a behavior tree framework, this paper demonstrates the drone’s adaptive and resilient decision-making when confronted with limited power constraints. We implemented our methodology using a commercial drone and tested the proposed ideas in a photogrammetry-based inspection task.

42 ENGINEERING↗

SDN-Based Smart Cyber Switching (SCS) for Cyber Restoration of a Digital Substation

In recent years, critical infrastructure and power grids have increasingly been targets of cyber-attacks, causing widespread and extended blackouts. Digital substations are particularly vulnerable to such cyber incursions, jeopardizing grid stability. This paper addresses these risks by proposing a cybersecurity framework that leverages software-defined networking (SDN) to bolster the resilience of substations based on the IEC- 61850 standard. The research introduces a strategy involving smart cyber switching (SCS) for mitigation and concurrent intelligent electronic device (CIED) for restoration, ensuring ongoing operational integrity and cybersecurity within a substation. The SCS framework improves the physical network’s behavior (i.e., leveraging commercial SDN capabilities) by incorporating an adaptive port controller (APC) module for dynamic port management and an intrusion detection system (IDS) to detect and counteract malicious IEC-61850-based sampled value (SV) and generic object-oriented system event (GOOSE) messages within the substation’s communication network. The framework’s effectiveness is validated through comprehensive simulations and a hardware-in-the-loop (HIL) testbed, demonstrating its ability to sustain substation operations during cyber-attacks and significantly improve the overall resilience of the power grid.

Liu, Chen-Ching (ORCID:0000000289417958)↗

Multilevel Parareal Algorithm with Averaging for Oscillatory Problems

The present study is an extension of the work done by Peddle, Haut, and Wingate and Haut and Wingate, where a two-level Parareal method with mapping and averaging is examined. The method proposed in this paper is a multilevel Parareal method with arbitrarily many levels, which is not restricted to the two-level case. We give an asymptotic error estimate which reduces to the two-level estimate for the case when only two levels are considered. Introducing more than two levels has important consequences for the averaging procedure, as we choose separate averaging windows for each of the different levels, which is an additional new feature of the present study. The different averaging windows make the proposed method especially appropriate for nonlinear multiscale problems, because we can introduce a level for each intrinsic scale of the problem and adapt the averaging procedure such that we reproduce the behavior of the model on the particular scale resolved by the level. The method is applied to nonlinear differential equations. The nonlinearities can generate a range of frequencies in the problem. The computational cost of the new method is investigated and studied on several examples.

97 MATHEMATICS AND COMPUTING↗

Psychobiology and Food Perception

Psychobiology is a scientific discipline which encompasses the phenomena known to be important as regards nutrition and food consumption in space. Specifically, it includes those areas of biology which are clearly related to behavior, human subjective experience and problems of coping and adapting to stress. Taste and odor perception; perception (knowledge gaps); perception (needs); food preference and menu selection; and choosing of acceptable diets are discussed.

Neilson, A.↗

ACTS and OLYMPUS propagation experiments

The OLYMPUS and ACTS satellites both provide opportunities for 10 to 30 GHz propagation measurements. The spacecraft are sufficiently alike that OLYMPUS can be used to test some prototype ACTS equipment and experiments. Data are particularly needed on short term signal behavior and in support of uplink power control and adaptive forward error correction (FEC) techniques. The Virginia Tech Satellite Communications Group has proposed a set of OLYMPUS experiments including attenuation and fade rate measurements, data communications, uplink power control, rain scatter interference, and small-scale site diversity operation. A digital signal processing receiver for the OLYMPUS and ACTS beacon signals is being developed.

Bostian, Charles W.↗

Human operator response to error-likely situations in complex engineering systems

The causes of human error in complex systems are examined. First, a conceptual framework is provided in which two broad categories of error are discussed: errors of action, or slips, and errors of intention, or mistakes. Conditions in which slips and mistakes might be expected to occur are identified, based on existing theories of human error. Regarding the role of workload, it is hypothesized that workload may act as a catalyst for error. Two experiments are presented in which humans' response to error-likely situations were examined. Subjects controlled PLANT under a variety of conditions and periodically provided subjective ratings of mental effort. A complex pattern of results was obtained, which was not consistent with predictions. Generally, the results of this research indicate that: (1) humans respond to conditions in which errors might be expected by attempting to reduce the possibility of error, and (2) adaptation to conditions is a potent influence on human behavior in discretionary situations. Subjects' explanations for changes in effort ratings are also explored.

Morris, Nancy M.↗