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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 955 records · Page 53
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Nonlinear Multiple Models Adaptive Secondary Voltage Control of Microgrids

This article proposes a model-free secondary voltage control (SVC) for microgrids (MG) using nonlinear multiple models adaptive control. Firstly, a linear robust adaptive controller is designed to guarantee the voltage stability in the bounded-input- bounded-output (BIBO) manner so as to meet the operation requirements of MGs. Secondly, a nonlinear adaptive controller is developed to improve the voltage tracking performance with the help of artificial neural networks (ANNs). A switching mechanism for coordinating such two controllers is designed to guarantee the closed-loop stability while achieving accurate voltage tracking. Here, by an online identification based on the input and output data of MGs, the proposed method does not resort to any apriori information of system model and primary control, thus exhibiting good robustness, ease of deployment and disturbance rejection.

17 WIND ENERGY↗
DOE OSTI2021

Invasion and rapid adaptation of guppies ( Poecilia reticulata ) across the Hawaiian Archipelago

How much does natural selection, as opposed to genetic drift, admixture, and gene flow, contribute to the evolution of invasive species following introduction to a new environment? Here we assess how evolution can shape biological invasions by examining population genomic variation in non-native guppies (Poecilia reticulata) introduced to the Hawaiian Islands approximately a century ago. By examining 18 invasive populations from four Hawaiian islands and four populations from the native range in northern South America, we reconstructed the history of introductions and evaluated population structure as well as the extent of ongoing gene flow across watersheds and among islands. Patterns of differentiation indicate that guppies have developed significant population structure, with little natural or human-mediated gene flow having occurred among populations following introduction. Demographic modeling and admixture graph analyses together suggest that guppies were initially introduced to O‘ahu and Maui and then translocated to Hawai‘i and Kaua‘i. We detected evidence for only one introduction event from the native range, implying that any adaptive evolution in introduced populations likely utilized the genetic variation present in the founding population. Environmental association tests accounting for population structure identified loci exhibiting signatures of adaptive variation related to predators and landscape characteristics but not nutrient regimes. When paired with high estimates of effective population sizes and detectable population structure, the presence of environment-associated loci supports the role of natural selection in shaping contemporary evolution of Hawaiian guppy populations. Our findings indicate that local adaptation may engender invasion success, particularly in species with life histories that facilitate rapid evolution. Finally, evidence of low gene flow between populations suggests that removal could be an effective approach to control invasive guppies across the Hawaiian archipelago.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

Climatic impact, future biomass production, and local adaptation of four switchgrass cultivars

Abstract Previous studies have shown that switchgrass has a wide range of genetic variation and that productivity is linked to local adaptation to the location of origin for many cultivars. In this meta‐analysis, we compiled and analyzed 900 observations associated with 41 field trials for four switchgrass cultivars (two lowlands, Alamo and Kanlow, and two uplands, Cave‐In‐Rock and Shelter). This extensive dataset and machine learning were used to identify the most influential variables impacting switchgrass productivity, to search for evidence of local adaptation to each cultivar's location of origin, and to predict change in productivity under future climate for each cultivar. In general, variables associated with climate and management are more important predictors of productivity relative to soil variables. Three climatic variables, annual mean temperature, annual precipitation, and precipitation in the wettest month, are identified as key environmental variables for productivity of all cultivars. Productivity under future climate (2041–2060) is predicted to stay stable for all cultivars relative to the prediction under current climate (1986–2005) across all trial locations and over a 20‐year simulation period. However, the productivity of each cultivar varies from location to location and from year to year, although productivity varies more between locations than between years. Additionally, we observe shifts in the most productive cultivar at the local field scale depending on the combination of management practice and climates. The shape of the relationship between productivity and the annual mean temperature relative to the cultivar's location of origin is a bell‐shaped curve for Kanlow, Cave‐in‐Rock, and Shelter, indicative of local adaptation. Identifying influential environmental variables and their relationships to productivity with respect to cultivar's location of origin help predicting productivity on the local field scale, and will help with the biofuel production planning through the selection of suitable cultivars for different locations under climate changes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Successional adaptive strategies revealed by correlating arbuscular mycorrhizal fungal abundance with host plant gene expression

The shifts in adaptive strategies revealed by ecological succession and the mechanisms that facilitate these shifts are fundamental to ecology. These adaptive strategies could be particularly important in communities of arbuscular mycorrhizal fungi (AMF) mutualistic with sorghum, where strong AMF succession replaces initially ruderal species with competitive ones and where the strongest plant response to drought is to manage these AMF. Although most studies of agriculturally important fungi focus on parasites, the mutualistic symbionts, AMF, constitute a research system of human-associated fungi whose relative simplicity and synchrony are conducive to experimental ecology. First, we hypothesize that, when irrigation is stopped to mimic drought, competitive AMF species should be replaced by AMF species tolerant to drought stress. We then, for the first time, correlate AMF abundance and host plant transcription to test two novel hypotheses about the mechanisms behind the shift from ruderal to competitive AMF. Surprisingly, despite imposing drought stress, we found no stress-tolerant AMF, probably due to our agricultural system having been irrigated for nearly six decades. Remarkably, we found strong and differential correlation between the successional shift from ruderal to competitive AMF and sorghum genes whose products (i) produce and release strigolactone signals, (ii) perceive mycorrhizal-lipochitinoligosaccharide (Myc-LCO) signals, (iii) provide plant lipid and sugar to AMF, and (iv) import minerals and water provided by AMF. These novel insights frame new hypotheses about AMF adaptive evolution and suggest a rationale for selecting AMF to reduce inputs and maximize yields in commercial agriculture.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Smart Adaptive Structures for an Ocean Wave Energy Converter

Ocean wave energy converters face significant challenges including cost-effectiveness, minimizing maintenance requirements, and withstanding extreme conditions. However, by utilizing smart materials, these converters could overcome these challenges. Such energy harvesters could use dielectric elastomer generators to convert ocean wave energy into electricity through their dynamic straining. Conversely, by applying electricity to these generators, they become actuators - dielectric elastomer actuators - thereby enabling them to alter their stiffness and adapt to the ever-changing ocean energy environments. Such active adaptation could enhance the converter's ability to: reach resonance with ocean waves and protect itself from dangerous waves. This study utilizes numerical analyses through the COMSOL software framework to evaluate the potential energy that could be harvested by a conceptual ocean wave energy converter based upon dielectric elastomer generators/actuators. The converter is composed of an external hull (that is a hollow cylinder), an inertial mass (that is a hollow cylinder and concentric with the hull), and 'spokes' - made of dielectric elastomer generators/actuators - that connect the hull to the inertial mass. Results of the numerical analyses include those outcomes arising from the conceptual converter being simulated via a sinusoidal motion analogous to ocean waves. That motion, therefore, causes relative motion between the converter's hull and inertial mass thereby dynamically stretching the corresponding connecting elastomers. The stretching of the elastomers enables them to 'gain elastic strain energy' and is, therefore, considered to be the theoretical limit of possible electrical energy conversion for the dielectric elastomer generator/actuator spokes. Additionally, the elastomer material properties of the spokes were altered to simulate the actuation of those same elastomers; with overall strain energy being subsequently investigated. Ultimately this is a preliminary study exploring the ability of such smart materials - electricity-generating and self-actuating elastomers - to actively adapt an ocean wave energy converter's structure to address and overcome the aforementioned challenges.

active materials↗
DOE OSTI2016

Accelerated Dimension-Independent Adaptive Metropolis

This work describes improvements from algorithmic and architectural means to black-box Bayesian inference over high-dimensional parameter spaces. The well-known adaptive Metropolis (AM) algorithm [33] is extended herein to scale asymptotically uniformly with respect to the underlying parameter dimension for Gaussian targets, by respecting the variance of the target. The resulting algorithm, referred to as the dimension-independent adaptive Metropolis (DIAM) algorithm, also shows improved performance with respect to adaptive Metropolis on non-Gaussian targets. This algorithm is further improved, and the possibility of probing high-dimensional (with dimension d 1000) targets is enabled, via GPU-accelerated numerical libraries and periodically synchronized concurrent chains (justi ed a posteriori). Asymptotically in dimension, this GPU implementation exhibits a factor of four improvement versus a competitive CPU-based Intel MKL parallel version alone. Strong scaling to concurrent chains is exhibited, through a combination of longer time per sample batch (weak scaling) and yet fewer necessary samples to convergence. The algorithm performance is illustrated on several Gaussian and non-Gaussian target examples, in which the dimension may be in excess of one thousand.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Adaptive Time Step Control for Multirate Infinitesimal Methods

Multirate methods have been used for decades to temporally evolve initial-value problems in which different components evolve on distinct time scales, and thus use of different step sizes for these components can result in increased computational efficiency. Generally, such methods select these different step sizes based on experimentation or stability considerations. For problems that evolve on a single time scale, adaptivity approaches that strive to control local temporal error are widely used to achieve numerical results of a desired accuracy with minimal computational effort, while alleviating the need for manual experimentation with different time step sizes. However, there is a notable gap in the publication record on the development of adaptive time step controllers for multirate methods. In this paper, we extend the single-rate controller work of Gustafsson [ACM Trans. Math. Software, 20 (1994), pp. 496-517] to the multirate method setting. Specifically, we develop controllers based on polynomial approximations to the principal error functions for both the "fast" and "slow" time scales within multirate infinitesimal (MRI) methods. We additionally investigate a variety of approaches for estimating the errors arising from each time scale within MRI methods. We then numerically evaluate the proposed multirate controllers and error estimation strategies on a range of multirate test problems, comparing their performance against an estimated optimal performance. Through this work, we combine the most performant of these approaches to arrive at a set of multirate adaptive time step controllers that robustly achieve desired solution accuracy with minimal computational effort.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Learning Robust Marking Policies for Adaptive Mesh Refinement

Here in this work, we revisit the marking decisions made in the standard adaptive finite element method (AFEM). Experience shows that a naïve marking policy leads to inefficient use of computational resources for adaptive mesh refinement (AMR). Consequently, using AMR in practice often involves ad-hoc or time-consuming offline parameter tuning to set appropriate parameters for the marking subroutine. To address these practical concerns, we recast AMR as a Markov decision process in which refinement parameters can be selected on-the-fly at run time, without the need for pre-tuning by expert users. In this new paradigm, the refinement parameters are also chosen adaptively via a marking policy that can be optimized using methods from reinforcement learning. We use the Poisson equation to demonstrate our techniques on h- and hp-refinement benchmark problems, and our experiments suggest that superior marking policies remain undiscovered for many classical AFEM applications. Furthermore, an unexpected observation from this work is that marking policies trained on one family of PDEs are sometimes robust enough to perform well on problems far outside the training family. For illustration, we show that a simple hp-refinement policy trained on 2D domains with only a single re-entrant corner can be deployed on far more complicated 2D domains, and even 3D domains, without significant performance loss. For reproduction and broader adoption, we accompany this work with an open-source implementation of our methods.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Replicated Computational Results (RCR) Report for “Adaptive Precision Block-Jacobi for High Performance Preconditioning in the Ginkgo Linear Algebra Software”

The article by Flegar et al. titled “Adaptive Precision Block-Jacobi for High Performance Preconditioning in the Ginkgo Linear Algebra Software” presents a novel, practical implementation of an adaptive precision block-Jacobi preconditioner. Performance results using state-of-the-art GPU architectures for the block-Jacobi preconditioner generation and application demonstrate the practical usability of the method, compared to a traditional full-precision block-Jacobi preconditioner. A production-ready implementation is provided in the Ginkgo numerical linear algebra library. In this report, the Ginkgo library is reinstalled and performance results are generated to perform a comparison to the original results when using Ginkgo’s Conjugate Gradient solver with either the full or the adaptive precision block-Jacobi preconditioner for a suite of test problems on an NVIDIA GPU accelerator. After completing this process, the published results are deemed reproducible.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

Analyzing the Adaptive Mesh Refinement (AMR) Characteristics of a High-Order 2D Cubed-Sphere Shallow-Water Model

Adaptive mesh refinement (AMR) is a technique that has been featured only sporadically in atmospheric science literature. This study aims to demonstrate the utility of AMR for simulating atmospheric flows. Several test cases are implemented in a 2D shallow-water model on the sphere using the Chombo-AMR dynamical core. This high-order finite-volume model implements adaptive refinement in both space and time on a cubed-sphere grid using a mapped-multiblock mesh technique. The tests consist of the passive advection of a tracer around moving vortices, a steady-state geostrophic flow, an unsteady solid-body rotation, a gravity wave impinging on a mountain, and the interaction of binary vortices. Both static and dynamic refinements are analyzed to determine the strengths and weaknesses of AMR in both complex flows with small-scale features and large-scale smooth flows. The different test cases required different AMR criteria, such as vorticity or height-gradient based thresholds, in order to achieve the best accuracy for cost. The simulations show that the model can accurately resolve key local features without requiring global high-resolution grids. The adaptive grids are able to track features of interest reliably without inducing noise or visible distortions at the coarse–fine interfaces. Finally and furthermore, the AMR grids keep any degradations of the large-scale smooth flows to a minimum.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Adaptive Stiffness Power Take-Off System for a Hydraulic Hose-Pump Point Absorber Wave Energy Converter

Two crucial challenges faced in the design of ocean wave energy converters (WECs) are maintaining high capacity factors and remaining robust in everchanging, harsh ocean environments. This study introduces a novel mechanism for achieving reactive WEC control with a soft hydraulic power take-off, thereby addressing both challenges. The device of interest involves a hydraulic pump, constructed from a fluidic flexible matrix composite (F2MC), which is cyclically stretched by driving waves and pressurizes working fluid through a turbine-generator. This class of fiber-reinforced stretch hoses is established for ocean use as robust moorings and shock absorbers. The dynamic properties of the F2MC pump depend on internal pressure, which can be controlled by a continuously variable transmission between the turbine and generator, allowing the system to be adapted for better performance over a wide range of wave conditions. This work presents a dynamic model for operation and adaptive behavior of this power take-off system, experimentally validates components of the model, and performs dynamic simulations of the system that show increases in power production and capacity factor compared to non-adaptive operation for a variety of driving wave conditions. This work develops the basis for future large-scale experimental testing and controller design of this system.

Wave energy conversion, fluidic flexible matrix co↗
DOE OSTI2019

Seed culture pre-adaptation of Bacillus coagulans MA-13 improves lactic acid production in simultaneous saccharification and fermentation

Background: Lignocellulosic biomass is an abundant and sustainable feedstock, which represents a promising raw material for the production of lactic acid via microbial fermentation. However, toxic compounds that affect microbial growth and metabolism are released from the biomass upon thermochemical pre-treatment. So far, susceptibility of bacterial strains to biomass-derived inhibitors still represents a major barrier to lactic acid production from lignocellulose. Detoxification of the pre-treated lignocellulosic material by water washing is commonly performed to alleviate growth inhibition of the production microorganism and achieve higher production rates. Results: In this study, we assessed the feasibility of replacing the washing step with integrated cellular adaptation during pre-culture of Bacillus coagulans MA-13 prior to simultaneous saccharification and lactic acid fermentation of steam exploded wheat straw. Using a seed culture pre-exposed to 30% hydrolysate led to 50% shorter process time, 50% higher average volumetric and 115% higher average specific productivity than when using cells from a hydrolysate-free seed culture. Conclusions: Pre-exposure of B. coagulans MA-13 to hydrolysate supports adaptation to the actual production medium. This strategy leads to lower process water requirements and combines cost-effective seed cultivation with physiological pre-adaptation of the production strain, resulting in reduced lactic acid production costs.

Hydrolysate↗
DOE OSTI2014

Adaptive Evolution of Synthetic Cooperating Communities Improves Growth Performance

Symbiotic interactions between organisms are important for human health and biotechnological applications. Microbial mutualism is a widespread phenomenon and is important in maintaining natural microbial communities. Although cooperative interactions are prevalent in nature, little is known about the processes that allow their initial establishment, govern population dynamics and affect evolutionary processes. To investigate cooperative interactions between bacteria, we constructed, characterized, and adaptively evolved a synthetic community comprised of leucine and lysine Escherichia coli auxotrophs. The co-culture can grow in glucose minimal medium only if the two auxotrophs exchange essential metabolites — lysine and leucine (or its precursors). Our experiments showed that a viable co-culture using these two auxotrophs could be established and adaptively evolved to increase growth rates (by ~3 fold) and optical densities. While independently evolved co-cultures achieved similar improvements in growth, they took different evolutionary trajectories leading to different community compositions. Experiments with individual isolates from these evolved co-cultures showed that changes in both the leucine and lysine auxotrophs improved growth of the co-culture. Interestingly, while evolved isolates increased growth of co-cultures, they exhibited decreased growth in mono-culture (in the presence of leucine or lysine). A genome-scale metabolic model of the co-culture was also constructed and used to investigate the effects of amino acid (leucine or lysine) release and uptake rates on growth and composition of the co-culture. When the metabolic model was constrained by the estimated leucine and lysine release rates, the model predictions agreed well with experimental growth rates and composition measurements. While this study and others have focused on cooperative interactions amongst community members, the adaptive evolution of communities with other types of interactions (e.g., commensalism, ammensalism or parasitism) would also be of interest.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2014

Scalable Adaptive Multilevel Solvers for Multiphysics Problems

In this project, we carried out many studies on adaptive and parallel multilevel methods for numerical modeling for various applications, including Magnetohydrodynamics (MHD) and complex fluids. We have made significant efforts and advances in adaptive multilevel methods of the multiphysics problems: multigrid methods, adaptive finite element methods, and applications.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

An Intelligent Adaptable Monitoring Package. Final Report

The “Intelligent Adaptable Monitoring Package” project was a four-year effort that demonstrated the feasibility of integrated sensing packages at tidal and wave energy sites. Such integration is generally required by the breadth of sensors required to understand environmental effects at marine energy sites and the operational difficulty of deploying, maintaining, and recovering such sensors. Over the course of the project, the Adaptable Monitoring Package (AMP) was deployed in multiple settings, each corresponding to a project budget period: - Budget Period 1: Demonstration of cabled deployment at Pacific Northwest National Laboratory’s Marine Science Laboratory. The deployment highlighted AMP hardware endurance over a 4-month deployment in a tidally-dominated environment and laid the groundwork for machine learning algorithms to detect and classify targets present in active sonar data. - Budget Period 2: Demonstration of an autonomous deployment at PacWave South off the coast of Newport, Oregon. The deployment highlighted the stability of AMP hardware and software, with the autonomous package collecting data on a duty cycle over a 1.5-month deployment. - Budget Period 3: Demonstration of an autonomous deployment powered by a wave energy converter at the U.S. Navy’s Wave Energy Test Site. The deployment highlighted the potential of wave energy to power ocean observatories and led to the development of machine learning algorithms to detect and classify targets in optical camera data. In aggregate, this project’s greatest success was demonstrating the AMP’s flexibility in a range of deployment scenarios. Each budget period represented a “first of a kind” demonstration of integrated instrumentation – cabled AMP, autonomous AMP, wave-energy powered AMP – and each deployment helped to identify and set goals for the next. Further, despite the exploratory nature of these deployments, each one achieved high system up-time and proved that flexible integration of multiple sensors in a single package represents a viable strategy for marine energy environmental monitoring. The key lessons learned from the project are: - Without continuous power, either from a shore cable or in situ source, many of the benefits of integration are lost (If continuous power is not available, the ability to detect rare events is lost, as is the ability to minimize the risk of behavioral changes through adaptive sensing. However, even on a duty cycle, there is still value in being able to acquire synchronous data from multiple sensors.); and - Observations from a moving platform present substantially greater data processing challenges than those from stationary platforms. Finally, these deployments also demonstrate an important truth: successful integration alone does not guarantee that relevant data are collected. To grow the knowledge base about environmental interactions with marine energy converters, integrated systems, like the AMP, need to include the right sensor mix and connect the data pipelines to effective processing algorithms. These deployments establish a strong foundation for future collaborations with the environmental research community: not only to understand the environmental effects of marine energy, but also to improve our general ability to study life in the sea.

16 TIDAL AND WAVE POWER↗
DOE OSTI2022

Adaptive Neurocontrol for Grid-Following Inverters

The new generation of power systems involve a large number of autonomous operating units with the flow of data being restricted by privacy concerns or infrastructure hurdles. The systems are also time-varying so the control should adjust in a timely manner to avoid failures that usually have very negative economical implications. Adaptive neurocontrol which takes elements from adaptive control (great for time-varying problems) and model identification (could be in the form of neural network) by using local available data is a compelling tool. In this work, we summarize analytical results for adaptive neurocontrol, followed with numerical verification of how the method could work for future grids.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Adaptive lighting for streets and residential areas

Adaptive lighting is an approach to lighting application in which the lighting levels are controlled based on the needs of the users of the lighted environment. Such systems are enabled by the instant-on and dimming capabilities of solid-state lighting and have been shown to have the potential to reduce energy consumption by over 50%, both through the use of maintained lighting levels without over-lighting and dimming. This investigation considered the impact of adaptive lighting within Cambridge NA. The impact of adaptive lighting on crashes and crime was considered using both the timing of the installation of the LED system in a before-and-after comparison, as well as a comparison to a neighboring non-dimming city. Industry practitioners and the public were also surveyed. As a follow-on to the first analysis, a human factors experiment was performed to investigate if the lighting levels could be further refined to improve energy performance. Overall, the energy savings from the dimming system range from 55% initially to 36% at the end of the life of the luminaire system

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2015

The molecular dimension of microbial species: 2. Synechococcus strains representative of putative ecotypes inhabiting different depths in the Mushroom Spring microbial mat exhibit different adaptive and acclimative responses to light

Closely related strains of thermophilic Synechococcus were cultivated from the microbial mats found in the effluent channels of Mushroom Spring, Yellowstone National Park (YNP). These strains have identical or nearly identical 16S rRNA sequences but are representative of separate, predicted putative ecotype (PE) populations, which were identified by using the more highly resolving psaA locus and which predominate at different vertical positions within the 1-mm-thick upper-green layer of the mat. Pyrosequencing confirmed that each strain contained a single, predominant psaA genotype. Strains differed in growth rate as a function of irradiance. A strain with a psaA genotype corresponding to a predicted PE that predominates near the mat surface grew fastest at high irradiances, whereas strains with psaA genotypes representative of predominant subsurface populations grew faster at low irradiance and exhibited greater sensitivity to abrupt shifts to high light. The high-light-adapted and low-light-adapted strains also exhibited differences in pigment content and the composition of the photosynthetic apparatus (photosystem ratio) when grown under different light intensities. Cells representative of the different strains had similar morphologies under low-light conditions, but under high-light conditions, cells of lowlight-adapted strains became elongated and formed short chains of cells. Collectively, the results presented here are consistent with the hypothesis that closely related, but distinct, ecological species of Synechococcus occupy different light niches in the Mushroom Spring microbial mat and acclimate differently to changing light environments.

59 BASIC BIOLOGICAL SCIENCES↗