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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 775 records · Page 43

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NASA NTRS1992

Habituation and adaptation of the vestibuloocular reflex: a model of differential control by the vestibulocerebellum

We habituated the dominant time constant of the horizontal vestibuloocular reflex (VOR) of rhesus and cynomolgus monkeys by repeated testing with steps of velocity about a vertical axis and adapted the gain of the VOR by altering visual input with magnifying and reducing lenses. After baseline values were established, the nodulus and ventral uvula of the vestibulocerebellum were ablated in two monkeys, and the effects of nodulouvulectomy and flocculectomy on VOR gain adaptation and habituation were compared. The VOR time constant decreased with repeated testing, rapidly at first and more slowly thereafter. The gain of the VOR was unaffected. Massed trials were more effective than distributed trials in producing habituation. Regardless of the schedule of testing, the VOR time constant never fell below the time constant of the semicircular canals (approximately 5 s). This finding indicates that only the slow component of the vestibular response, the component produced by velocity storage, was habituated. In agreement with this, the time constant of optokinetic after-nystagmus (OKAN) was habituated concurrently with the VOR. Average values for VOR habituation were obtained on a per session basis for six animals. The VOR gain was adapted by natural head movements in partially habituated monkeys while they wore x 2.2 magnifying or x 0.5 reducing lenses. Adaptation occurred rapidly and reached about +/- 30%, similar to values obtained using forced rotation. VOR gain adaptation did not cause additional habituation of the time constant. When the VOR gain was reduced in animals with a long VOR time constant, there were overshoots in eye velocity that peaked at about 6-8 s after the onset or end of constant-velocity rotation. These overshoots occurred at times when the velocity storage integrator would have been maximally activated by semicircular canal input. Since the activity generated in the canals is not altered by visual adaptation, this finding indicates that the gain element that controls rapid changes in eye velocity in the VOR is separate from that which couples afferent input to velocity storage. Nodulouvulectomy caused a prompt and permanent loss of habituation, returning VOR time constants to initial values. VOR gain adaptation, which is lost after flocculectomy, was unaffected by nodulouvulectomy. Flocculectomy did not alter habituation of the VOR or of OKAN. Using a simplified model of the VOR, the decrease in the duration of vestibular nystagmus due to habituation was related to a decrement in the dominant time constant of the velocity storage integrator (1/h0).(ABSTRACT TRUNCATED AT 400 WORDS).

NASA Discipline Neuroscience↗

NASA NTRS1997

Adaptive Performance Seeking Control Using Fuzzy Model Reference Learning Control and Positive Gradient Control

Performance Seeking Control attempts to find the operating condition that will generate optimal performance and control the plant at that operating condition. In this paper a nonlinear multivariable Adaptive Performance Seeking Control (APSC) methodology will be developed and it will be demonstrated on a nonlinear system. The APSC is comprised of the Positive Gradient Control (PGC) and the Fuzzy Model Reference Learning Control (FMRLC). The PGC computes the positive gradients of the desired performance function with respect to the control inputs in order to drive the plant set points to the operating point that will produce optimal performance. The PGC approach will be derived in this paper. The feedback control of the plant is performed by the FMRLC. For the FMRLC, the conventional fuzzy model reference learning control methodology is utilized, with guidelines generated here for the effective tuning of the FMRLC controller.

Kopasakis, George↗

NASA NTRS1993

A generic efficient adaptive grid scheme for rocket propulsion modeling

The objective of this research is to develop an efficient, time-accurate numerical algorithm to discretize the Navier-Stokes equations for the predictions of internal one-, two-dimensional and axisymmetric flows. A generic, efficient, elliptic adaptive grid generator is implicitly coupled with the Lower-Upper factorization scheme in the development of ALUNS computer code. The calculations of one-dimensional shock tube wave propagation and two-dimensional shock wave capture, wave-wave interactions, shock wave-boundary interactions show that the developed scheme is stable, accurate and extremely robust. The adaptive grid generator produced a very favorable grid network by a grid speed technique. This generic adaptive grid generator is also applied in the PARC and FDNS codes and the computational results for solid rocket nozzle flowfield and crystal growth modeling by those codes will be presented in the conference, too. This research work is being supported by NASA/MSFC.

Mo, J. D.↗

NASA NTRS2006

Adaptive Failure Compensation for Aircraft Tracking Control Using Engine Differential Based Model

An aircraft model that incorporates independently adjustable engine throttles and ailerons is employed to develop an adaptive control scheme in the presence of actuator failures. This model captures the key features of aircraft flight dynamics when in the engine differential mode. Based on this model an adaptive feedback control scheme for asymptotic state tracking is developed and applied to a transport aircraft model in the presence of two types of failures during operation, rudder failure and aileron failure. Simulation results are presented to demonstrate the adaptive failure compensation scheme.

Liu, Yu↗

NASA NTRS1999

Adaptive-Grid Methods for Phase Field Models of Microstructure Development

In this work the authors show how the phase field model can be solved in a computationally efficient manner that opens a new large-scale simulational window on solidification physics. Our method uses a finite element, adaptive-grid formulation, and exploits the fact that the phase and temperature fields vary significantly only near the interface. We illustrate how our method allows efficient simulation of phase-field models in very large systems, and verify the predictions of solvability theory at intermediate undercooling. We then present new results at low undercoolings that suggest that solvability theory may not give the correct tip speed in that regime. We model solidification using the phase-field model used by Karma and Rappel.

Provatas, Nikolas↗

NASA NTRS1986

Space Station dynamic modeling, control and simulation

Dynamic disturbances of many orders of magnitude greater than those of conventional spacecraft will be routine for the Space Station. Accurate knowledge of inflight structural dynamics and disturbances will be lacking. System identification will reduce uncertainties. To deal with the remaining model errors and time-varying elements, adaptive control may be required. Dynamic models for two Space Station configurations are derived. A direct model reference adaptive control algorithm is synthesized and evaluated with respect to the station model parameter errors and plant dynamics truncations. Both the rigid body and the flexible modes are treated. Simulation results show that convergence of the adaptive algorithm can be achieved in 100 to about 300 seconds with reasonable performance even during Shuttle hard docking operations in which station mass and inertia are instantaneously changed by more than 100 percent.

Ih, C.-H. C.↗

NASA NTRS2020

Adaptation in U.S. Corn Belt Increases Resistance to Soil Carbon Loss With Climate Change

Increasing the amount of soil organic carbon (SOC) has agronomic benefits and the potential to mitigate climate change. Previous regional predictions of SOC trends under climate change often ignore or do not explicitly consider the effect of crop adaptation (i.e., changing planting dates and varieties). We used the DayCent biogeochemical model to examine the effect of adaptation on SOC for corn and soybean production in the U.S. Corn Belt using climate data from three models. Without adaptation, yields of both corn and soybean tended to decrease and the decomposition of SOC tended to increase leading to a loss of SOC with climate change compared to a baseline scenario with no climate change. With adaptation, the model predicted a substantially higher crop yield. The increase in yields and associated carbon input to the SOC pool counteracted the increased decomposition in the adaptation scenarios, leading to similar SOC stocks under different climate change scenarios. Consequently, we found that crop management adaptation to changing climatic conditions strengthen agroecosystem resistance to SOC loss. However, there are differences spatially in SOC trends. The northern part of the region is likely to gain SOC while the southern part of the region is predicted to lose SOC.

Soil Organic Carbon (SOC)↗

NASA NTRS2015

Adaptive State Predictor Based Human Operator Modeling on Longitudinal and Lateral Control

Control-theoretic modeling of the human operator dynamic behavior in manual control tasks has a long and rich history. In the last two decades, there has been a renewed interest in modeling the human operator. There has also been significant work on techniques used to identify the pilot model of a given structure. The purpose of this research is to attempt to go beyond pilot identification based on collected experimental data and to develop a predictor of pilot behavior. An experiment was conducted to categorize these interactions of the pilot with an adaptive controller compensating during control surface failures. A general linear in-parameter model structure is used to represent a pilot. Three different estimation methods are explored. A gradient descent estimator (GDE), a least squares estimator with exponential forgetting (LSEEF), and a least squares estimator with bounded gain forgetting (LSEBGF) used the experiment data to predict pilot stick input. Previous results have found that the GDE and LSEEF methods are fairly accurate in predicting longitudinal stick input from commanded pitch. This paper discusses the accuracy of each of the three methods - GDE, LSEEF, and LSEBGF - to predict both pilot longitudinal and lateral stick input from the flight director's commanded pitch and bank attitudes.

Trujillo, Anna C.↗

DOE OSTI2021

Optimality versus reality: Closing the gap between renewable energy decision models and government deployment in the United States

Energy decision models are widely used to evaluate the technical and economic feasibility of renewable energy, as well as to help inform the deployment of these technologies. However, a gap exists between the optimal model solutions and what is deployed. This paper explores why these gaps exist in the public sector using the results of interviews with 20 federal, state, and city government agencies that have used the Renewable Energy Integration and Optimization (REopt™) model to inform energy decisions. We then propose adaptations to technical modeling capabilities, and communication of results, which may help increase clean energy deployment. This research may be useful to both analytical modelers and the organizations using such decision tools to inform policy, regulation, planning, and deployment of clean energy systems.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2021

A novel in vivo mouse intervertebral disc degeneration model induced by compressive suture

Intervertebral disc degeneration (IDD) is the root cause of many musculoskeletal disorders of the spine. However, the etiology of IDD is complex and still not well understood. Animal models of IDD would be useful in deciphering the underlying mechanisms. But the existing animal models have their limitations. Therefore, to establish a novel mouse model that can simulate the human IDD process in vivo, we proposed to carefully circumcise the 2 mm-wide tail skin and then compressively sutured the defect with a simple end-to-end suture to exert excessive pressure on the disc. After 1-week, 2-week, and 4-week compression, the mice were sacrificed and the intervertebral discs were harvested for tissue analysis. The radiological, morphological, and molecular modifications of intervertebral discs were measured to characterize this model. Radiologically, the water content of the intervertebral disc decreased significantly after 2-week compression. Morphologically, the nucleus pulposus showed a decrease in volume and the number of notochordal cells. The compressive suture also broke the balance between anabolic and catabolic enzymes in nucleus pulposus, which led to the remodeling of the extracellular matrix in nucleus pulposus as the content of aggrecan and collagen II decreased. The compressive suture could induce intervertebral discs degeneration in a more reasonable way, which was solely influenced by mechanical loading, as the mice caudal vertebrae still moved freely after the operation. This kind of animal model could be adapted as a reliable in vivo mouse IDD model for the research regarding the etiology and treatments of IDD.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2022

Development of Land‐River Two‐Way Hydrologic Coupling for Floodplain Inundation in the Energy Exascale Earth System Model

Abstract Floodplain inundation links river and land systems through significant water, sediment, and nutrient exchanges. However, these two‐way interactions between land and river are currently missing in most Earth System Models. In this study, we introduced the two‐way hydrological coupling between the land component, E3SM Land Model, and the river component, Model for Scale Adaptive River Transport, in Energy Exascale Earth System Model (E3SM) to study the impacts of floodplain inundation on land and river processes. We calibrated the river channel geometry and developed a new data‐driven inundation scheme to improve the simulation of inundation dynamics in E3SM. The new inundation scheme captures 96% of the spatial variation of inundation area in a satellite inundation product at global scale, in contrast with 7% when the default inundation scheme of E3SM was used. Global simulations including the new inundation scheme performed at resolution with and without land‐river two‐way coupling was used to quantify the impact of coupling. Comparisons show that two‐way coupling modifies the water and energy cycle in 20% of the global land cells. Specifically, riverine inundation is reduced by two‐way coupling, but inland inundation is intensified. Wetter periods are more impacted by the two‐way coupling at the global scale, while regions with different climates exhibit different sensitivities. The two‐way exchange of water between the land and river components of E3SM provides the foundation for enabling two‐way coupling of land‐river sediment and biogeochemical fluxes. These capabilities will be used to improve understanding of the interactions between water and biogeochemical cycles and their response to human perturbations.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1995

Adaptive Optimization of Aircraft Engine Performance Using Neural Networks

Preliminary results are presented on the development of an adaptive neural network based control algorithm to enhance aircraft engine performance. This work builds upon a previous National Aeronautics and Space Administration (NASA) effort known as Performance Seeking Control (PSC). PSC is an adaptive control algorithm which contains a model of the aircraft's propulsion system which is updated on-line to match the operation of the aircraft's actual propulsion system. Information from the on-line model is used to adapt the control system during flight to allow optimal operation of the aircraft's propulsion system (inlet, engine, and nozzle) to improve aircraft engine performance without compromising reliability or operability. Performance Seeking Control has been shown to yield reductions in fuel flow, increases in thrust, and reductions in engine fan turbine inlet temperature. The neural network based adaptive control, like PSC, will contain a model of the propulsion system which will be used to calculate optimal control commands on-line. Hopes are that it will be able to provide some additional benefits above and beyond those of PSC. The PSC algorithm is computationally intensive, it is valid only at near steady-state flight conditions, and it has no way to adapt or learn on-line. These issues are being addressed in the development of the optimal neural controller. Specialized neural network processing hardware is being developed to run the software, the algorithm will be valid at steady-state and transient conditions, and will take advantage of the on-line learning capability of neural networks. Future plans include testing the neural network software and hardware prototype against an aircraft engine simulation. In this paper, the proposed neural network software and hardware is described and preliminary neural network training results are presented.

Simon, Donald L.↗

NASA NTRS1998

Vestibulospinal adaptation to microgravity

Human balance control is known to be transiently disrupted after spaceflight; however, the mechanisms responsible for postflight postural ataxia are still under investigation. In this report, we propose a conceptual model of vestibulospinal adaptation based on theoretical adaptive control concepts and supported by the results from a comprehensive study of balance control recovery after spaceflight. The conceptual model predicts that immediately after spaceflight the balance control system of a returning astronaut does not expect to receive gravity-induced afferent inputs and that descending vestibulospinal control of balance is disrupted until the central nervous system is able to cope with the newly available vestibular otolith information. Predictions of the model are tested using data from a study of the neurosensory control of balance in astronauts immediately after landing. In that study, the mechanisms of sensorimotor balance control were assessed under normal, reduced, and/or altered (sway-referenced) visual and somatosensory input conditions. We conclude that the adaptive control model accurately describes the neurobehavioral responses to spaceflight and that similar models of altered sensory, motor, or environmental constraints are needed clinically to predict responses that patients with sensorimotor pathologies may have to various visual-vestibular or changing stimulus environments.

manned↗

DOE OSTI2023

Iterative Stability Enforcement in Adaptive Antoulas–Anderson Algorithms for \({\boldsymbol{\mathcal{H}_2}}\) Model Reduction

This paper presents an extension of the Adaptive-Antoulas-Anderson (AAA) algorithm for rational modelling. Specifically, our new stable multi-input multi-output AAA (smiAAA) algorithm builds rational approximations of multi-input signals with a common set of stable poles. A new methodology is presented for iteratively enforcing stability constraints on the poles. We demonstrate the strengths of this approach compared to the stability enforcement in the FastAAA algorithm. Results using the smiAAA algorithm are compared with the commonly used Vector Fitting algorithm and the more recently published RKFIT algorithm. Vector Fitting and RKFIT both require the user to input the number of poles to use in the approximations. If the final approximation is not accurate enough, the user must re-start Vector Fitting or RKFIT with a larger number of poles and/or a new starting location for the poles. In contrast, the smiAAA algorithm is designed to allow the user to simply input the desired accuracy of the approximations, and the necessary number of poles is detected automatically. This permits users to produce approximations of a desired accuracy with no knowledge about the underlying order of the system being approximated, preventing the algorithm from ever needing to be rerun. An additional feature for preventing extraneous poles from being returned by AAA is also discussed. The cause of these extraneous poles is efficiently detected and removed by our presented methodology. In conclusion, the examples presented demonstrate that smiAAA can efficiently produce approximations of similar or better accuracy than Vector Fitting and RKFIT while requiring less input from the user.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2024

Deep Learning-Based Dynamic Modeling of Three-Phase Voltage Source Inverters

Inverter-based resource (IBR) models are necessary to analyze modern power system stability and create effective control strategies. Modeling IBRs in converter-rich power systems is crucial, yet challenging due to the lack of commercial information on converter topologies and control parameters. This paper proposes novel convolutional neural network (CNN)–based data-driven techniques for modeling IBRs, addressing adaptability and proprietary concerns without requiring internal system physics knowledge. The proposed method is tested using real grid-tied commercial IBR transient data and demonstrates effectiveness and accuracy. Furthermore, the developed modeling approach is integrated and implemented in the open-source power distribution simulation and analysis tool, GridLAB-D, to illustrate the potentiality of dynamic analysis of large-scale power systems with high IBRs.

deep learning, artificial intelligence↗

DOE OSTI2022

Mouse models of Ebola virus tolerance and lethality: characterization of CD-1 mice infected with wild-type, guinea pig-adapted, or mouse-adapted virus

Development of lethal models of Ebola virus disease has been achieved by the serial passage of virus isolates from human cases in mice and guinea pigs. Use of mice infected with non-adapted virus has been limited due to the absence of overt clinical disease. In recent years, newly recognized sequelae identified in human cases has highlighted the importance of continued investigations of non-lethal infection both in humans and animal models. Here, we revisit the use of rodent-adapted and non-adapted Ebola virus (EBOV) in mice to investigate infection tolerance and future utility of these models in pathogenesis and therapeutic intervention studies. We found that like non-adapted wild-type EBOV, guinea pig-adapted EBOV resulted in widespread tissue infection, variably associated with tissue pathology, and alterations in clinical and immunological analytes in the absence of overt disease. Notably, infection with either non-lethal variant did not greatly differ from lethal mouse-adapted EBOV until near the time end-point criteria are reached in these mice. Furthermore, these data support future investigations of pathogenesis, convalescence, and sequelae in mouse models of virus tolerance.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2020

Microsecond Molecular Dynamics Simulations of Proteins Using a Quasi-Equilibrium Solvation Shell Model

In this work, we describe the development and implementation of a quasi-equilibrium hydration shell model of biomolecular solvation with adaptive boundaries. Applying the model to microsecond-long molecular dynamics simulations of several protein systems of varying complexity, we find that the model simulation results are of comparable quality to those obtained from simulations of fully solvated systems, but at a reduced computational cost. We discuss the dominant sources of error in the model and outline directions for future improvements.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

NASA NTRS1993

Nonlinear stability and control study of highly maneuverable high performance aircraft

This project is intended to research and develop new nonlinear methodologies for the control and stability analysis of high-performance, high angle-of-attack aircraft such as HARV (F18). Past research (reported in our Phase 1, 2, and 3 progress reports) is summarized and more details of final Phase 3 research is provided. While research emphasis is on nonlinear control, other tasks such as associated model development, system identification, stability analysis, and simulation are performed in some detail as well. An overview of various models that were investigated for different purposes such as an approximate model reference for control adaptation, as well as another model for accurate rigid-body longitudinal motion is provided. Only a very cursory analysis was made relative to type 8 (flexible body dynamics). Standard nonlinear longitudinal airframe dynamics (type 7) with the available modified F18 stability derivatives, thrust vectoring, actuator dynamics, and control constraints are utilized for simulated flight evaluation of derived controller performance in all cases studied.

Mohler, R. R.↗