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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 937 records · Page 52
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

High resolution viscous fingering simulation in miscible displacement using a p-adaptive discontinuous Galerkin method with algebraic multigrid preconditioner

High resolution simulation of viscous fingering can offer an accurate and detailed prediction for subsurface engineering processes involving fingering phenomena. The fully implicit discontinuous Galerkin (DG) method has been shown to be an accurate and stable method to model viscous fingering with high Peclet number and mobility ratio. In this study, we present two techniques to speedup large scale simulations of this kind. The first technique relies on a simple p-adaptive scheme in which high order basis functions are employed only in elements near the finger fronts where the concentration has a sharp change. As a result, the number of degrees of freedom is significantly reduced and the simulation yields almost identical results to the more expensive simulation with uniform high order elements throughout the mesh. The second technique for speedup involves improving the solver efficiency. We present an algebraic multigrid (AMG) preconditioner which allows the DG matrix to leverage the robust AMG preconditioner designed for the continuous Galerkin (CG) finite element method. The resulting preconditioner works effectively for fixed order DG as well as p-adaptive DG problems. Finally, with the improvements provided by the p-adaptivity and AMG preconditioning, we can perform high resolution three-dimensional viscous fingering simulations required for miscible displacement with high Peclet number and mobility ratio in greater detail than before for well injection problems.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Dominant balance-based adaptive mesh refinement for incompressible fluid flows

This work introduces a novel adaptive mesh refinement (AMR) method that utilizes dominant balance analysis (DBA) for efficient and accurate grid adaptation in computational fluid dynamics (CFD) simulations. The proposed method leverages a Gaussian mixture model (GMM) to classify grid cells into active and passive regions based on the dominant physical interactions within the equation space. By modeling truncation error probabilistically from discretized terms, the method identifies regions of high interaction where numerical accuracy is most sensitive to resolution. Unlike traditional AMR strategies, this approach does not rely on heuristic-based sensors or user-defined thresholds, providing a fully automated and problem-independent framework for AMR. Applied to the incompressible Navier-Stokes equations for steady and unsteady flow past a cylinder, the DBA-based AMR method achieves comparable accuracy to high-resolution grids while reducing computational costs by up to 70 %. The validation highlights the method’s effectiveness in capturing complex flow features while minimizing grid cells, directing computational resources toward regions with the most critical dynamics. This modular and scalable strategy is adaptable to a wide range of applications, presenting a promising tool for efficient high-fidelity simulations in CFD and other multiphysics domains.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

Impact of climate change on adaptive management decisions in the face of water scarcity

Reoccurring drought through the early 2000s has caused a serious water scarcity issue in the Colorado River Basin. Previous modeling studies have focused on the impact of climate change without considering the adaptive behaviors of farmers and under-utilized Indian water rights. Here, we use a coupled agent-based water resource model (ABM) to investigate how the adaptive decisions of farmers can affect water resource management under both climate change impacts and fully utilized Indian water right conditions. We used five General Circulation Model projections with RCP8.5 scenarios for the study. The results of farm-level decision-making showed different responses in irrigated areas that were changing due to climate change impact. While winter precipitation changes might partially explain the behavior changes, no specific pattern could be concluded based on their location. Also, farmers’ responses about annual water diversion showed more significant inter-year variation compared to irrigated areas. Basin-level metrics showed that climate change impacts will generally worsen water scarcity issues as measured in Navajo Reservoir storage, flow to Lake Powell, and instream flow requirement. But these basin-level water scarcity metrics cannot reflect individual farm-level impacts under climate change, which is why modeling the bottom-up management actions is necessary. When the under-utilized Indian water rights are fully used, it is more likely to trigger the shortage sharing agreement due to the higher tribal water depletion. Evaluation of model uncertainty and a more realistic setup for adaptive actions under drought contingency plans are suggested for future research.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Printable, emissivity-adaptive and albedo-optimized covering for year-round energy saving

Radiative cooling uses high-emissivity materials to passively cool the surface of outdoor objects, such as building roofs on hot days. The issue of overcooling with this technology on cold days can be addressed by structures with thermal emissivity that is adaptive to temperature. Despite recent advances in temperature-adaptive structures, great challenges remain in their fabrication feasibility and unoptimized solar heating that may override the radiative cooling benefit. Here, in this work, we develop a printable, emissivity-adaptive and albedo-optimized covering (PEAC) based on recyclable materials with roll-to-roll fabrication. A PEAC automatically switches its sky-window emissivity from 0.25 to 0.85 when the surface temperature exceeds a pre-set transition temperature, delivering an albedo optimized for maximal year-round energy saving or thermal comfort in a given climate.

36 MATERIALS SCIENCE↗
DOE OSTI2014

In-hardware demonstration of model-independent adaptive tuning of noisy systems with arbitrary phase drift

In this work, an implementation of a recently developed model-independent adaptive control scheme, for tuning uncertain and time varying systems, is demonstrated on the Los Alamos linear particle accelerator. The main benefits of the algorithm are its simplicity, ability to handle an arbitrary number of components without increased complexity, and the approach is extremely robust to measurement noise, a property which is both analytically proven and demonstrated in the experiments performed. We report on the application of this algorithm for simultaneous tuning of two buncher radio frequency (RF) cavities, in order to maximize beam acceptance into the accelerating electromagnetic field cavities of the machine, with the tuning based only on a noisy measurement of the surviving beam current downstream from the two bunching cavities. The algorithm automatically responds to arbitrary phase shift of the cavity phases, automatically re-tuning the cavity settings and maximizing beam acceptance. Because it is model independent it can be utilized for continuous adaptation to time-variation of a large system, such as due to thermal drift, or damage to components, in which the remaining, functional components would be automatically re-tuned to compensate for the failing ones. We start by discussing the general model-independent adaptive scheme and how it may be digitally applied to a large class of multi-parameter uncertain systems, and then present our experimental results.

42 ENGINEERING↗
DOE OSTI2016

Filter accuracy for the Lorenz 96 model: Fixed versus adaptive observation operators

In the context of filtering chaotic dynamical systems it is well-known that partial observations, if sufficiently informative, can be used to control the inherent uncertainty due to chaos. The purpose of this paper is to investigate, both theoretically and numerically, conditions on the observations of chaotic systems under which they can be accurately filtered. In particular, we highlight the advantage of adaptive observation operators over fixed ones. The Lorenz ’96 model is used to exemplify our findings. Here, we consider discrete-time and continuous-time observations in our theoretical developments. We prove that, for fixed observation operator, the 3DVAR filter can recover the system state within a neighbourhood determined by the size of the observational noise. It is required that a sufficiently large proportion of the state vector is observed, and an explicit form for such sufficient fixed observation operator is given. Numerical experiments, where the data is incorporated by use of the 3DVAR and extended Kalman filters, suggest that less informative fixed operators than given by our theory can still lead to accurate signal reconstruction. Adaptive observation operators are then studied numerically; we show that, for carefully chosen adaptive observation operators, the proportion of the state vector that needs to be observed is drastically smaller than with a fixed observation operator. Indeed, we show that the number of state coordinates that need to be observed may even be significantly smaller than the total number of positive Lyapunov exponents of the underlying system.

3DVAR↗
DOE OSTI2019

Adaptive harnessing damping in hydrokinetic energy conversion by two rough tandem-cylinders using flow-induced vibrations

Alternating lift technology (ALT) harnesses hydrokinetic energy from currents and tides and is different from conventional steady lift technologies (turbines). ALT is still under development with an important research issue being the mitigation of wake effect on downstream cylinders in Flow Induced Oscillations (FIO) of multi-cylinder Current Energy Converters (CEC). Rather than adjust the configuration/parameters of the converter, a more direct and effective way is to actively adjust the harnessed power. In this paper, a hydrokinetic energy converter using FIO of two cylinders in tandem in one-degree-of-freedom oscillators, with nonlinear adaptive damping and linear spring stiffness, is tested experimentally. FIO include Vortex Induced Vibrations (VIV), galloping, and their coexistence. Introducing adaptive damping into the tandem cylinders overcomes the shielding effect, which previous research on two tandem cylinders has shown to reduce power output by the downstream cylinder. Shielding along with fixed damping result either in ceasing motion due to excessive damping, or in low harnessed energy due to insufficient damping. In this experimental study, damping-to-velocity rate, linear spring-stiffness, cylinder spacing, and flow-velocity are the parameters with Reynolds number 30,000 ≤ Re ≤ 120,000. Comparison to linear-oscillators in FIO shows that this nonlinear converter, with velocity-proportional damping coefficient, is more effective over the entire FIO range but especially in galloping, where both flow and cylinder speeds are higher. Experimental results for energy harvesting, efficiency and instantaneous energy of the converter are presented and discussed supported by amplitude and frequency response data. Here the results show that the nonlinear, adaptive, velocity-proportional damping coefficient is an effective way to increase the overall harnessed power and the power of downstream cylinder. The harnessed power in the VIV to galloping transition increases by up to 94%. The most significant improvement is in the galloping region, where the increase in harnessed power and efficiency is around 33%.

13 HYDRO ENERGY↗
DOE OSTI2026

Dynamic Interfacial Design in Adaptive Hybrid Materials Enables Reversible and Tunable Mechano-Optic Smart Responses

Next-generation polymeric materials are shifting toward adaptive and interactive behaviors of living systems; however, designing materials that can reversibly modulate optical properties under mechanical deformation while maintaining mechanical robustness remains a key challenge. Here, we report a mechanically robust vitrimer-based adaptive hybrid material (AHM) that exhibits a stretch-induced reversible transparency-to-opacity transition, enabled by the integration of dynamic interactions at the polymer–silica nanoparticle interface and controlled nanoparticle self-assembly. The AHM combines boronic ester–functionalized polystyrene-b-poly(ethylene-co-butylene)-b-polystyrene (S-Bpin) with diol-functionalized silica nanoparticles (diol-SiNPs) to form a hybrid network hosting both dynamic boronic ester and hydrogen-bonding interactions. These reversible linkages facilitate controlled nanoparticle self-assembly and enable strain-induced nanoparticle alignment/aggregation. Upon stretching, SiNP-rich domains align and aggregate within the polymer matrix, while local modulus mismatch between stiff aggregated SiNP/borylated-styrene-rich regions and the softer elastomeric midblock induces surface microwrinkle formation. These internal aggregates and surface wrinkles cooperatively enhance light scattering, producing the opaque state under strain. Furthermore, the tailored AHM exhibits high toughness, thermomechanical stability, reprocessability, and programmable shape-memory behavior. This work presents a dynamic interfacial design strategy for mechanically robust, optically reconfigurable, and reusable soft materials for adaptive optics, smart windows, sensing, soft robotics, and circular smart-material platforms.

adaptive hybrid materials↗
DOE OSTI2024

Adaptive Narrowband Damping for Improving Harmonic Stability of Modular Multilevel Converter

Harmonic instability events between modular multilevel converter (MMC) and ac systems have been widely reported in recent years. To damp harmonic resonance, this paper proposes an adaptive narrowband damping control that automatically programs, adds, and adjusts the damping around the oscillation frequency when an oscillation is detected. First, the paper presents a low-pass filter design for MMC control loops that pushes all negative damping of the MMC impedance down to the medium-frequency range (< ~ 1000 Hz). Then, an adaptive damping control that uses online oscillation detection is proposed, which can automatically configure the narrowband damper to provide positive damping to the MMC around the detected oscillation frequency. In contrast to existing narrowband damping methods, the proposed adaptive narrowband damper dynamically adjusts the damping gain and the width of the damping range based on continuous monitoring of system resonance conditions (e.g., adjust damping gain to zero when the system resonance disappears). Electromagnetic transient simulation results validate the efficacy of the proposed method in two typical MMC-based power systems.

active damping↗
DOE OSTI2025

Closed-form expressions for unitaries of spin-adapted fermionic operators

One of the open challenges in quantum computing simulations of problems of chemical interest is the proper enforcement of spin symmetry. Efficient quantum circuits implementing unitaries generated by spin-adapted operators remain elusive, while naïve Trotterization schemes break spin symmetry. Here, in this work, we analyze the mathematical structure of spin-adapted operators and derive closed-form expressions for unitaries generated by singlet spin-adapted generalised single and double excitations. These results represent significant progress toward the economical enforcement of spin symmetry in quantum simulations.

fermionic algebra↗
DOE OSTI2021

Genomic patterns of structural variation among diverse genotypes of Sorghum bicolor and a potential role for deletions in local adaptation

Genomic structural mutations, especially deletions, are an important source of variation in many species and can play key roles in phenotypic diversification and evolution. Previous work in many plant species has identified multiple instances of structural variations (SVs) occurring in or near genes related to stress response and disease resistance, suggesting a possible role for SVs in local adaptation. Sorghum [Sorghum bicolor (L.) Moench] is one of the most widely grown cereal crops in the world. It has been adapted to an array of different climates as well as bred for multiple purposes, resulting in a striking phenotypic diversity. In this study, we identified genome-wide SVs in the Biomass Association Panel, a collection of 347 diverse sorghum genotypes collected from multiple countries and continents. Using Illumina-based, short-read whole-genome resequencing data from every genotype, we found a total of 24,648 SVs, including 22,359 deletions. The global site frequency spectrum of deletions and other types of SVs fit a model of neutral evolution, suggesting that the majority of these mutations were not under any types of selection. Clustering results based on single nucleotide polymorphisms separated the genotypes into eight clusters which largely corresponded with geographic origins, with many of the large deletions we uncovered being unique to a single cluster. Even though most deletions appeared to be neutral, a handful of cluster-specific deletions were found in genes related to biotic and abiotic stress responses, supporting the possibility that at least some of these deletions contribute to local adaptation in sorghum.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2017

Adaptive Prediction Emerges Over Short Evolutionary Time Scales

Adaptive prediction is a capability of diverse organisms, including microbes, to sense a cue and prepare in advance to deal with a future environmental challenge. Here, we investigated the timeframe over which adaptive prediction emerges when an organism encounters an environment with novel structure. We subjected yeast to laboratory evolution in a novel environment with repetitive, coupled exposures to a neutral chemical cue (caffeine), followed by a sublethal dose of a toxin (5-FOA), with an interspersed requirement for uracil prototrophy to counter-select mutants that gained constitutive 5-FOA resistance. We demonstrate the remarkable ability of yeast to internalize a novel environmental pattern within 50–150 generations by adaptively predicting 5-FOA stress upon sensing caffeine. We also demonstrate how novel environmental structure can be internalized by coupling two unrelated response networks, such as the response to caffeine and signaling-mediated conditional peroxisomal localization of proteins.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Adaptive evolution of Methylotuvimicrobium alcaliphilum to grow in the presence of rhamnolipids improves fatty acid and rhamnolipid production from CH4

Abstract Rhamnolipids (RLs) are well-studied biosurfactants naturally produced by pathogenic strains of Pseudomonas aeruginosa. Current methods to produce RLs in native and heterologous hosts have focused on carbohydrates as production substrate; however, methane (CH4) provides an intriguing alternative as a substrate for RL production because it is low cost and may mitigate greenhouse gas emissions. Here, we demonstrate RL production from CH4 by Methylotuvimicrobium alcaliphilum DSM19304. RLs are inhibitory to M. alcaliphilum growth (<0.05 g/l). Adaptive laboratory evolution was performed by growing M. alcaliphilum in increasing concentrations of RLs, producing a strain that grew in the presence of 5 g/l of RLs. Metabolomics and proteomics of the adapted strain grown on CH4 in the absence of RLs revealed metabolic changes, increase in fatty acid production and secretion, alterations in gluconeogenesis, and increased secretion of lactate and osmolyte products compared with the parent strain. Expression of plasmid-borne RL production genes in the parent M. alcaliphilum strain resulted in cessation of growth and cell death. In contrast, the adapted strain transformed with the RL production genes showed no growth inhibition and produced up to 1 μM of RLs, a 600-fold increase compared with the parent strain, solely from CH4. This work has promise for developing technologies to produce fatty acid-derived bioproducts, including biosurfactants, from CH4.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2017

Utilization of Supercapacitors in Adaptive Protection Applications for Resiliency against Communication Failures: A Size and Cost Optimization Case Study

Microgrids’ adaptive protection techniques rely on communication signals from the point of common coupling to ad- just the corresponding relays’ settings for either grid-connected or islanded modes of operation. However, during communication out- ages or in the event of a cyberattack, relays settings are not changed. Thus adaptive protection schemes are rendered unsuc- cessful. Due to their fast response, supercapacitors, which are pre- sent in the microgrid to feed pulse loads, could also be utilized to enhance the resiliency of adaptive protection schemes to communi- cation outages. Proper sizing of the supercapacitors is therefore im- portant in order to maintain a stable system operation and also reg- ulate the protection scheme’s cost. This paper presents a two-level optimization scheme for minimizing the supercapacitor size along with optimizing its controllers’ parameters. The latter will lead to a reduction of the supercapacitor fault current contribution and an increase in that of other AC resources in the microgrid in the ex- treme case of having a fault occurring simultaneously with a pulse load. It was also shown that the size of the supercapacitor can be reduced if the pulse load is temporary disconnected during the transient fault period. Simulations showed that the resulting super- capacitor size and the optimized controller parameters from the proposed two-level optimization scheme were feeding enough fault currents for different types of faults and minimizing the cost of the protection scheme.

25 ENERGY STORAGE↗
DOE OSTI2021

FPV Video Adaptation for UAV Collision Avoidance

First person view (FPV) technology for unmanned aerial vehicles (UAVs) provides an immersive experience for pilots and enables various personal and commercial applications such as aerial photography, drone racing, search and rescue operations, agricultural surveillance, and structural inspection. While real time video streaming from a UAV and vision-based collision avoidance strategies have been studied in literature as separate topics, in this paper we tackle collision avoidance in FPV scenarios, taking into account network delays and real time video parameters. We present a theoretical model for obstacle collisions that considers the current communication channel conditions, the real time video parameters, and the UAV's position relative to the closest obstacle. A video adaptation algorithm is then designed, using this metric, to tune the FPV video resolution, number of re-transmission attempts, and the modulation scheme to maximize the probability of avoiding collisions. This algorithm also takes into account specific latency constraints of the application. This video algorithm was evaluated in various scenarios and its ability to respond to both distances to the obstacle as well as the communication channel conditions was demonstrated. It was found that, for the considered scenarios, the performance of the proposed adaptive algorithm was, on an average, 58.63% higher than the closest non-adaptive one in terms of maximizing the probability of avoiding collision. Such collision avoidance strategies could be used to make UAV FPV applications safer and more reliable.

47 OTHER INSTRUMENTATION↗
DOE OSTI2018

Dynamic Adaptable Asynchronous Progress Model for MPI RMA Multiphase Applications

Casper is a process-based asynchronous progress model for MPI one-sided communication on multi-and many-core architectures. The one-sided communication is not truly one-sided in most MPI implementations: the target process still relies on software progress to complete incoming operations. Casper allows the user to specify an arbitrary number of cores dedicated to background ghost processes and transparently redirects the RMA operations to ghost processes by utilizing the PMPI redirection and MPI-3 shared-memory technologies. Although Casper benefits applications that suffer from lack of asynchronous progress, the operation redirection design might not support complex multiphase applications effectively, which often involve dynamically changing communication density and computing workloads. In this paper, we present an adaptive mechanism in Casper to address the limitation of static asynchronous progress in multiphase applications. For this we exploit two adaptive strategies, a user-guided strategy and a fully transparent and automatic strategy based on self-profiling and prediction, to dynamically reconfigure the asynchronous progress in Casper according to real-time performance characteristics during multiphase execution. We evaluate the adaptive approaches in both microbenchmarks and a real quantum chemistry application suite, NWChem, on the Cray XC30 supercomputer and an Intel Omni-Path cluster.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Adaptive Control of Distributed Energy Resources for Distribution Grid Voltage Stability

Volt-VAR and Volt-Watt functionality in photovoltaic (PV) smart inverters provide mechanisms to ensure system voltage magnitudes and power factors remain within acceptable limits. However, these control functions can become unstable, introducing oscillations in system voltages when not appropriately configured or maliciously altered during a cyberattack. In the event that Volt-VAR and Volt-Watt control functions in a portion of PV smart inverters in a distribution grid are unstable, the proposed adaptation scheme utilizes the remaining and stably-behaving PV smart inverters and other Distributed Energy Resources to mitigate the effect of the instability. The adaptation mechanism is entirely decentralized, model-free, communication-free, and requires virtually no external configuration. Here we provide a derivation of the adaptive control approach and validate the algorithm in experiments on the IEEE 37 and 8500 node test feeders.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2016

Adaptive Hierarchical Voltage Control of a DFIG-Based Wind Power Plant for a Grid Fault

This paper proposes an adaptive hierarchical voltage control scheme of a doubly-fed induction generator (DFIG)-based wind power plant (WPP) that can secure more reserve of reactive power (Q) in the WPP against a grid fault. To achieve this, each DFIG controller employs an adaptive reactive power to voltage (Q-V) characteristic. The proposed adaptive Q-V characteristic is temporally modified depending on the available Q capability of a DFIG; it is dependent on the distance from a DFIG to the point of common coupling (PCC). The proposed characteristic secures more Q reserve in the WPP than the fixed one. Furthermore, it allows DFIGs to promptly inject up to the Q limit, thereby improving the PCC voltage support. To avert an overvoltage after the fault clearance, washout filters are implemented in the WPP and DFIG controllers; they can prevent a surplus Q injection after the fault clearance by eliminating the accumulated values in the proportional-integral controllers of both controllers during the fault. Test results demonstrate that the scheme can improve the voltage support capability during the fault and suppress transient overvoltage after the fault clearance under scenarios of various system and fault conditions; therefore, it helps ensure grid resilience by supporting the voltage stability.

24 POWER TRANSMISSION AND DISTRIBUTION↗