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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 973 records · Page 54

Carbon Isotope Composition and the NDVI as Phenotyping Approaches for Drought Adaptation in Durum Wheat: Beyond Trait Selection

High-throughput phenotyping platforms provide valuable opportunities to investigate biomass and drought-adaptive traits. We explored the capacity of traits associated with drought adaptation such as aerial measurements of the Normalized Difference Vegetation Index (NDVI) and carbon isotope composition (δ13C) determined at the leaf level to predict genetic variation in biomass. A panel of 248 elite durum wheat accessions was grown at the Maricopa Phenotyping platform (US) under well-watered conditions until anthesis, and then irrigation was stopped and plot biomass was harvested about three weeks later. Globally, the δ13C values increased from the first to the second sampling date, in keeping with the imposition of progressive water stress. Additionally, δ13C was negatively correlated with final biomass, and the correlation increased at the second sampling, suggesting that accessions with lower water-use efficiency maintained better water status and, thus, performed better. Flowering time affected NDVI predictions of biomass, revealing the importance of developmental stage when measuring the NDVI and the effect that phenology has on its accuracy when monitoring genotypic adaptation to specific environments. The results indicate that in addition to choosing the optimal phenotypic traits, the time at which they are assessed, and avoiding a wide genotypic range in phenology is crucial.

54 ENVIRONMENTAL SCIENCES↗

ARM-IRL: Adaptive Resilience Metric Quantification Using Inverse Reinforcement Learning

The resilience of safety-critical systems is gaining importance due to the rise in cyber and physical threats, especially within critical infrastructure. Traditional static resilience metrics may not capture dynamic system states, leading to inaccurate assessments and ineffective responses to cyber threats. This work aims to develop a data-driven, adaptive method for resilience metric learning. We propose a data-driven approach using inverse reinforcement learning (IRL) to learn a single, adaptive resilience metric. The method infers a reward function from expert control actions. Unlike previous approaches using static weights or fuzzy logic, this work applies adversarial inverse reinforcement learning (AIRL), training a generator and discriminator in parallel to learn the reward structure and derive an optimal policy. The proposed approach is evaluated on multiple scenarios: optimal communication network rerouting, power distribution network reconfiguration, and cyber–physical restoration of critical loads using the IEEE 123-bus system. The adaptive, learned resilience metric enables faster critical load restoration in comparison to conventional RL approaches.

97 MATHEMATICS AND COMPUTING↗

Synergistic Integration of Multiple Wave Energy Converters with Adaptive Resonance and Offshore Floating Wind Turbines through Bayesian Optimization

We developed a synergistic ocean renewable system where an array of Wave Energy Converters (WEC) with adaptive resonance was collocated with a Floating Offshore Wind Turbine (FOWT) such that the WECs, capturing wave energy through the resonance adapting to varying irregular waves, consequently reduced FOWFT loads and turbine motions. Combining Surface-Riding WECs (SR-WEC) individually designed to feasibly relocate their natural frequency at the peak of the wave excitation spectrum for each sea state, and to obtain the highest capture width ratio at one of the frequent sea states for annual average power in a tens of kilowatts scale with a 15 MW FOWT based on a semi-submersible, Bayesian Optimization is implemented to determine the arrangement of WECs that minimize the annual representation of FOWT’s wave excitation spectra. The time-domain simulation of the system in the optimized arrangement is performed, including two sets of interactions: one set is the wind turbine dynamics, mooring lines, and floating body dynamics for FOWT, and the other set is the nonlinear power-take-off dynamics, linear mooring, and individual WECs’ floating body dynamics. Those two sets of interactions are further coupled through the hydrodynamics of diffraction and radiation. For sea states comprising Annual Energy Production, we investigate the capture width ratio of WECs, wave excitation on FOWT, and nacelle acceleration of the turbine compared to their single unit operations. We find that the optimally arranged SR-WECs reduce the wave excitation spectral area of FOWT by up to 60% and lower the turbine’s peak nacelle acceleration by nearly 44% in highly occurring sea states, while multiple WECs often produce more than the single operation, achieving adaptive resonance with a larger wave excitation spectra for those sea states. The synergistic system improves the total Annual Energy Production (AEP) by 1440 MWh, and we address which costs of Levelized Cost Of Energy (LCOE) can be reduced by the collocation.

Engineering↗

The Proper Motion of Pyxis: The First Use of Adaptive Optics in Tandem with HST on a Faint Halo Object

We present a proper motion measurement for the halo globular cluster Pyxis, using Hubble Space Telescope/ACS data as the first epoch and GeMS/GSAOI Adaptive Optics data as the second, separated by a baseline of ∼5 years. This is both the first measurement of the proper motion of Pyxis and the first calibration and use of Multi-Conjugate Adaptive Optics data to measure an absolute proper motion for a faint, distant halo object. Consequently, we present our analysis of the Adaptive Optics data in detail. We obtain a proper motion of μ{sub α} cos (δ) = 1.09 ± 0.31 mas yr{sup −1} and μ {sub δ} = 0.68 ± 0.29 mas yr{sup −1}. From the proper motion and line-of-sight velocity, we find that the orbit of Pyxis is rather eccentric, with its apocenter at more than 100 kpc and its pericenter at about 30 kpc. We also investigate two literature-proposed associations for Pyxis with the recently discovered ATLAS stream and the Magellanic system. Combining our measurements with dynamical modeling and cosmological numerical simulations, we find it unlikely Pyxis is associated with either system. We examine other Milky Way satellites for possible association using the orbit, eccentricity, metallicity, and age as constraints and find no likely matches in satellites down to the mass of Leo II. We propose that Pyxis probably originated in an unknown galaxy, which today is fully disrupted. Assuming that Pyxis is bound and not on a first approach, we derive a 68% lower limit on the mass of the Milky Way of 0.95 × 10{sup 12} M {sub ⊙}.

79 ASTRONOMY AND ASTROPHYSICS↗

CosmosDG: An hp -adaptive Discontinuous Galerkin Code for Hyper-resolved Relativistic MHD

We have extended Cosmos++, a multidimensional unstructured adaptive mesh code for solving the covariant Newtonian and general relativistic radiation magnetohydrodynamic (MHD) equations, to accommodate both discrete finite volume and arbitrarily high-order finite element structures. The new finite element implementation, called CosmosDG, is based on a discontinuous Galerkin (DG) formulation, using both entropy-based artificial viscosity and slope limiting procedures for the regularization of shocks. High-order multistage forward Euler and strong-stability preserving Runge–Kutta time integration options complement high-order spatial discretization. We have also added flexibility in the code infrastructure allowing for both adaptive mesh and adaptive basis order refinement to be performed separately or simultaneously in a local (cell-by-cell) manner. We discuss in this report the DG formulation and present tests demonstrating the robustness, accuracy, and convergence of our numerical methods applied to special and general relativistic MHD, although we note that an equivalent capability currently also exists in CosmosDG for Newtonian systems.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

An Hp-Adaptive Minimum Action Method Based on a Posteriori Error Estimate

In this work, we develop an hp-adaptive minimum action method (MAM). MAM plays an important role to minimize the Freidlin-Wentzell action functional, which is the central object of the Freidlin-Wentzell theory of large deviations for transitions induced by small random perturbations. Because of the demanding computation cost, especially in spatially extended systems, numerical efficiency is a critical issue for MAM. Difficulties come from discretizations of both time and space. One hurdle for the application of MAM to large scale systems is the global reparametrization in time direction, which is required by most versions of MAM. We recently introduced a new version of MAM in [25], called tMAM, where we used some simple heuristic criteria to demonstrate that tMAM can be effectively coupled with h-adaptivity. The target of this paper is to integrate hp-adaptivity into tMAM using a posterior error estimation techniques. More specifically, we use the arc length constraint given by geometric minimum action method (gMAM) to define an indicator of the effect of linear time scaling in tMAM, and the derivative recovery technique to construct an error indicator and a regularity indicator for hp-refinement. Numerical results are presented.

Wan, Xiaoliang↗

Adaptive Mixed GMsFEM for Flows in Heterogeneous Media

Abstract In this paper, we present two adaptive methods for the basis enrichment of the mixed Generalized Multiscale Finite Element Method (GMsFEM) for solving the flow problem in heterogeneous media. We develop an a-posteriori error indicator which depends on the norm of a local residual operator. Based on this indicator, we construct an offline adaptive method to increase the number of basis functions locally in coarse regions with large local residuals. We also develop an online adaptive method which iteratively enriches the function space by adding new functions computed based on the residual of the previous solution and special minimum energy snapshots. We show theoretically and numerically the convergence of the two methods. The online method is, in general, better than the offline method as the online method is able to capture distant effects (at a cost of online computations), and both methods have faster convergence than a uniform enrichment. Analysis shows that the online method should start with a certain number of initial basis functions in order to have the best performance. The numerical results confirm this and show further that with correct selection of initial basis functions, the convergence of the online method can be independent of the contrast of the medium. We consider cases with both very high and very low conducting inclusions and channels in our numerical experiments.

Mathematics↗

Supporting Information - How Can Crop Production Adapt to growing groundwater restrictions in the West?

Abstract This data plan outlines the structure and content of datasets generated and utilized in the research presented in the manuscript abstract. Groundwater overdraft has led to serious water supply issues in the US West. Most western states manage groundwater use through a permitting system, but California has only recently begun to restrict groundwater use statewide with the 2014 passage of groundwater restrictions which target the elimination of groundwater overdraft practices by 2042. With groundwater extraction curtailed, crop production in the US West (a $95 billion industry annually) will be affected, and appropriate response strategies will be needed to ensure minimal disruption to food production and the regional economy. In this paper, we explore the adoption of alternative adaptive responses: (a) deficit irrigation; (b) switching to less water-intensive crops; (c) changing the extent of irrigated land (including fallowing); and (d) geographically shifting crop production. Employing an integrated modeling approach, we explicitly capture the interactions and feedbacks between local hydrology, changes in crop yields, crop and land use decision-making, changes in crop prices, and regional shifts in crop production. We find that the optimal adaptive response is spatially heterogeneous and comprises a portfolio of strategies. Southwestern states and California will be the most impacted by groundwater restrictions. The optimal responses in these states are to both adopt deficit irrigation strategies and reduce a portion of their irrigated croplands, resulting in a shift in crop production to northwestern states with a larger supply of water. The datasets detailed in this repository represent the output from these integrated models, specifically designed to support the analysis and visualization presented in the manuscript and supplemental information. These datasets, used in conjunction with the scripts available at our associated GitHub repository (https://github.com/pches/Femeena_etal_How_can_crop_production_adapt), enable the reproduction of figures and facilitate a comprehensive understanding of the optimal adaptive strategies in agriculture for mitigating water stress under varying groundwater extraction scenarios, as outlined in the abstract.

DNDCe↗

Supporting Information - How Can Crop Production Adapt to growing groundwater restrictions in the West?

Abstract This data plan outlines the structure and content of datasets generated and utilized in the research presented in the manuscript abstract. Groundwater overdraft has led to serious water supply issues in the US West. Most western states manage groundwater use through a permitting system, but California has only recently begun to restrict groundwater use statewide with the 2014 passage of groundwater restrictions which target the elimination of groundwater overdraft practices by 2042. With groundwater extraction curtailed, crop production in the US West (a $95 billion industry annually) will be affected, and appropriate response strategies will be needed to ensure minimal disruption to food production and the regional economy. In this paper, we explore the adoption of alternative adaptive responses: (a) deficit irrigation; (b) switching to less water-intensive crops; (c) changing the extent of irrigated land (including fallowing); and (d) geographically shifting crop production. Employing an integrated modeling approach, we explicitly capture the interactions and feedbacks between local hydrology, changes in crop yields, crop and land use decision-making, changes in crop prices, and regional shifts in crop production. We find that the optimal adaptive response is spatially heterogeneous and comprises a portfolio of strategies. Southwestern states and California will be the most impacted by groundwater restrictions. The optimal responses in these states are to both adopt deficit irrigation strategies and reduce a portion of their irrigated croplands, resulting in a shift in crop production to northwestern states with a larger supply of water. The datasets detailed in this repository represent the output from these integrated models, specifically designed to support the analysis and visualization presented in the manuscript and supplemental information. These datasets, used in conjunction with the scripts available at our associated GitHub repository (https://github.com/pches/Femeena_etal_How_can_crop_production_adapt), enable the reproduction of figures and facilitate a comprehensive understanding of the optimal adaptive strategies in agriculture for mitigating water stress under varying groundwater extraction scenarios, as outlined in the abstract.

DNDCe↗

Supporting Information - How Can Crop Production Adapt to growing groundwater restrictions in the West?

Abstract This data plan outlines the structure and content of datasets generated and utilized in the research presented in the manuscript abstract. Groundwater overdraft has led to serious water supply issues in the US West. Most western states manage groundwater use through a permitting system, but California has only recently begun to restrict groundwater use statewide with the 2014 passage of groundwater restrictions which target the elimination of groundwater overdraft practices by 2042. With groundwater extraction curtailed, crop production in the US West (a $95 billion industry annually) will be affected, and appropriate response strategies will be needed to ensure minimal disruption to food production and the regional economy. In this paper, we explore the adoption of alternative adaptive responses: (a) deficit irrigation; (b) switching to less water-intensive crops; (c) changing the extent of irrigated land (including fallowing); and (d) geographically shifting crop production. Employing an integrated modeling approach, we explicitly capture the interactions and feedbacks between local hydrology, changes in crop yields, crop and land use decision-making, changes in crop prices, and regional shifts in crop production. We find that the optimal adaptive response is spatially heterogeneous and comprises a portfolio of strategies. Southwestern states and California will be the most impacted by groundwater restrictions. The optimal responses in these states are to both adopt deficit irrigation strategies and reduce a portion of their irrigated croplands, resulting in a shift in crop production to northwestern states with a larger supply of water. The datasets detailed in this repository represent the output from these integrated models, specifically designed to support the analysis and visualization presented in the manuscript and supplemental information. These datasets, used in conjunction with the scripts available at our associated GitHub repository (https://github.com/pches/Femeena_etal_How_can_crop_production_adapt), enable the reproduction of figures and facilitate a comprehensive understanding of the optimal adaptive strategies in agriculture for mitigating water stress under varying groundwater extraction scenarios, as outlined in the abstract.

DNDCe↗

Drought adaptation in Arabidopsis thaliana by extensive genetic loss-of-function

Interdisciplinary syntheses are needed to scale up discovery of the environmental drivers and molecular basis of adaptation in nature. Here we integrated novel approaches using whole genome sequences, satellite remote sensing, and transgenic experiments to study natural loss-of-function alleles associated with drought histories in wild Arabidopsis thaliana. The genes we identified exhibit population genetic signatures of parallel molecular evolution, selection for loss-of-function, and shared associations with flowering time phenotypes in directions consistent with longstanding adaptive hypotheses seven times more often than expected by chance. We then confirmed predicted phenotypes experimentally in transgenic knockout lines. These findings reveal the importance of drought timing to explain the evolution of alternative drought tolerance strategies and further challenge popular assumptions about the adaptive value of genetic loss-of-function in nature. These results also motivate improved species-wide sequencing efforts to better identify loss-of-function variants and inspire new opportunities for engineering climate resilience in crops.

Life Sciences & Biomedicine - Other Topics↗

Time domain and frequency domain design techniques for model reference adaptive control systems

Some problems associated with the design of model-reference adaptive control systems are considered and solutions to these problems are advanced. The stability of the adapted system is a primary consideration in the development of both the time-domain and the frequency-domain design techniques. Consequentially, the use of Liapunov's direct method forms an integral part of the derivation of the design procedures. The application of sensitivity coefficients to the design of model-reference adaptive control systems is considered. An application of the design techniques is also presented.

Boland, J. S., III↗

Nonlinear and adaptive estimation techniques in reentry

The development and testing of nonlinear and adaptive estimators for reentry (e.g. space shuttle) navigation and model parameter estimation or identification are reported. Of particular interest is the identifcation of vehicle lift and drag characteristics in real time. Several nonlinear filters were developed and simulated. Adaptive filters for the real time identification of vehicle lift and drag characteristics, and unmodelable acceleration, were also developed and tested by simulation. The simulations feature an uncertain system environment with rather arbitrary model errors, thus providing a definitive test of estimator performance. It was found that nonlinear effects are indeed significant in reentry trajectory estimation and a nonlinear filter is demonstrated which successfully tracks through nonlinearities without degrading the information content of the data. Under the same conditions the usual extended Kalman filter diverges and is useless. The J-adaptive filter is shown to successfully track errors in the modeled vehicle lift and drag characteristics. The same filter concept is also shown to track successfully through rather arbitrary model errors, including lift and drag errors, vehicle mass errors, atmospheric density errors, and wind gust errors.

Jazwinski, A. H.↗

Adaptive stochastic control for a class of linear systems.

The problem considered in this paper deals with the control of linear discrete-time stochastic systems with unknown (possibly time-varying and random) gain parameters. The philosophy of control is based on the use of an open-loop feedback optimal (OLFO) control using a quadratic index of performance. It is shown that the OLFO system consists of (1) an identifier that estimates the system state variables and gain parameters and (2) a controller described by an 'adaptive' gain and correction term. Several qualitative properties and asymptotic properties of the OLFO adaptive system are discussed. Simulation results dealing with the control of stable and unstable third-order plants are presented. The key quantitative result is the precise variation of the control system adaptive gains as a function of the future expected uncertainty of the parameters; thus, in this problem the ordinary 'separation theorem' does not hold.

Tse, E.↗

Adaptive variable-length coding for efficient compression of spacecraft television data.

An adaptive variable length coding system is presented. Although developed primarily for the proposed Grand Tour missions, many features of this system clearly indicate a much wider applicability. Using sample to sample prediction, the coding system produces output rates within 0.25 bit/picture element (pixel) of the one-dimensional difference entropy for entropy values ranging from 0 to 8 bit/pixel. This is accomplished without the necessity of storing any code words. Performance improvements of 0.5 bit/pixel can be simply achieved by utilizing previous line correlation. A Basic Compressor, using concatenated codes, adapts to rapid changes in source statistics by automatically selecting one of three codes to use for each block of 21 pixels. The system adapts to less frequent, but more dramatic, changes in source statistics by adjusting the mode in which the Basic Compressor operates on a line-to-line basis. Furthermore, the compression system is independent of the quantization requirements of the pulse-code modulation system.

Rice, R. F.↗

Digital adaptive sampling.

Discussion of digital adaptive sampling, which is consistently better than fixed sampling in noise-free cases. Adaptive sampling is shown to be feasible and, it is considered, should be studied further. It should be noted that adaptive sampling is a class of variable rate sampling in which the variability depends on system signals. Digital rather than analog laws should be studied, because cases can arise in which the analog signals are not even available. An extremely important problem is implementation.

Breazeale, G. J.↗

Adaptive multibeam experiment for aeronautical and maritime services /AMEAMS/.

An experiment using NASA's ATS-G satellite was designed to provide essential data and field experience for the application of adaptive multiple satellite beam techniques to small mobile terminal communications system designs. Two approaches to the system were considered: an adaptive simultaneous multibeam mode and a hopped-beam mode. In the former case, both interbeam and intrabeam adaptive power management are used, while in the latter, beam energy is controlled through the use of time division techniques. The objectives of the experiment, design and implementation approaches, and potential applications are discussed.

Redisch, W. N.↗

An adaptive technique for a redundant-sensor navigation system.

An on-line adaptive technique is developed to provide a self-contained redundant-sensor navigation system with a capability to utilize its full potentiality in reliability and performance. This adaptive system is structured as a multistage stochastic process of detection, identification, and compensation. It is shown that the detection system can be effectively constructed on the basis of a design value, specified by mission requirements, of the unknown parameter in the actual system, and of a degradation mode in the form of a constant bias jump. A suboptimal detection system on the basis of Wald's sequential analysis is developed using the concept of information value and information feedback. The developed system is easily implemented, and demonstrates a performance remarkably close to that of the optimal nonlinear detection system. An invariant transformation is derived to eliminate the effect of nuisance parameters such that the ambiguous identification system can be reduced to a set of disjoint simple hypotheses tests. By application of a technique of decoupled bias estimation in the compensation system the adaptive system can be operated without any complicated reorganization.

Chien, T.-T.↗