Search NASA⌕ Search

SEARCH · Search NASA

Results for “dynamic events”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 433 records · Page 24
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Learning-Based Demand Response in Grid Interactive Buildings via Gaussian Processes

This paper presents a predictive controller for a grid-interactive multi-zone building where the temperature dynamics are learned via Gaussian Process (GP) regression. We investigate the development of a learning-based predictive control with two main objectives: (i) continuously learn the temperature dynamics of the building based on data; and, (ii) use the learned dynamics to solve a multi-objective predictive control problem to guarantee occupants' comfort and energy efficiency during normal conditions and demand response events. We leverage the probabilistic non-parametric properties of GPs to estimate the (unknown) non-linear temperature dynamics of the building and to incorporate the uncertainty of those predictions in a multi-objective optimization problem. The GP-based predictive control is solved via a zero-order primal-dual projected-gradient algorithm. We evaluate numerically the performance of the proposed controller using a five-zone commercial building.

demand response↗
DOE OSTI2024

Water loss through evapotranspiration after precipitation events in bioenergy crops grown in similar climatic conditions

The relationship between precipitation and evapotranspiration (ET) is critical to understanding water cycle related dynamics in ecosystems, including crops. Existing studies of bioenergy crops have primarily focused on annual or seasonal ET rates, with less attention given to the immediate ET response following precipitation events. This study examines the variation in ET rates in the days subsequent to precipitation events across various bioenergy crops—corn, switchgrass, and prairies—utilizing 13 years (2010–2022) of growing season data. Meteorological and eddy covariance flux data were collected from seven eddy covariance flux towers as part of the GLBRC scale-up experiment at the Kellogg Biological Station Long Term Ecological Research sites. The analysis revealed that average ET peaked the day after precipitation and declined linearly over the following days, with a statistically significant relationship (p-value = 0.00027, R2 = 0.96). Neither the type of biofuel vegetation nor the historical land use significantly influenced ET post-precipitation events (p-values = 0.53 and 0.153, respectively). Key predictors of ET following precipitation events include shortwave radiation, season, day of the year, ambient temperature, vapor pressure deficit (VPD), long-wave radiation, precipitation amount, soil moisture, and annual variability. These findings enhance our comprehension of ET responses in bioenergy crop systems, with implications for water management in sustainable agriculture.

09 BIOMASS FUELS↗
DOE OSTI2022

Influence of Thermal Treatment on Preceramic Polymer Grafted Nanoparticle Network Formation: Implications for Thermal Protection Systems and Aerospace Propulsion Components

Preceramic polymer grafted nanoparticles (PCP GNPs) offer potential advantages in the production of polymer-derived ceramic composites compared to neat preceramic polymers (PCPs), such as reduced thermal shrinkage and increased char yield. In comparison to traditional composites (particles + free polymer), PCPs avoid issues of compatibility, agglomeration, and phase separation during processing and provide routes to control nanoparticle arrangement. Prior literature has established that the conversion efficiency of PCPs and PCP GNPs to ceramics and ceramic composites is linked to the thermal pretreatment of these precursor polymers (e.g., curing). In this paper, we investigate the material transformations that occur when exposing PCP GNPs to a low-temperature thermal treatment (≤250 °C) prior to pyrolysis. The PCP GNPs explored in this study possessed silica nanoparticle cores but were distinct in their PCP coronas, having poly(1,1-dimethylpropylsilane) (allyl-GNP)- or poly(1,1-dimethylbenzylethylsilane) (styryl-GNP)-grafted polymers. After undergoing low-temperature thermal treatment, these PCP GNPs exhibited increased char yield at 800 °C; however, unlike commercial PCPs (e.g., allylhydridopolycarbosilane (SMP-10)), obvious cross-linkable sites are not present in the PCP corona structure. Differential scanning calorimetry, oscillatory rheology, and X-ray photon correlation spectroscopy were utilized to elucidate the thermally induced material changes in the allyl- and styryl-GNPs. Thermally induced changes to the structure and behavior of the PCP GNPs were determined to be linked to the chemical structure of the grafted polycarbosilane chains. Styryl-GNPs experienced a curing event between 180 and 250 °C, effecting the formation of a network, which contributed to char yield improvement (at 800 °C). The nanoscale dynamics of this material also shows a transition from diffuse behavior to ballistic behavior because of the cross-linking event. Conversely, the allyl-GNPs did not exhibit a curing event under heat treatment but did show an increase in thermally induced physical cross-linking. The allyl-GNP physical network is stronger after the first cycle of thermal treatment, and it is considered that this contributed to the improvement in char yield post thermal treatment. The advancements in the understanding of the cross-linking behavior of these hybrid materials are expected to advance the application of these materials to turbine engine, advanced friction, and heat-shielding components.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Roles for epigenetics in wood formation and stress response intrees–from basic biology to forest management

Annual model and crop species have been the subject of most epigenetic studies for plants. In contrast to annuals, forest trees persist on natural landscapes and experience environmental variation within and across seasons, years, and decades or even centuries. Most forest trees species are undomesticated and typically grown on variable landscapes with no irrigation or application of agricultural chemicals. Forest trees must thus rely on their inherent ability to alter growth and physiology to mitigate the effects of changing abiotic and biotic stressors. Like other plants, trees have mechanisms encoded in their genomic DNA sequence that can respond directly to stress events such as drought or heat. Hypothetically, it would be highly advantageous to join these mechanisms with a dynamic “memory” of past exposure to stress. It is now well established that annual model and crop plants can establish epigenetic-based memory of stress events that support more rapid and robust response to stress in the future. Here, evidence is discussed for epigenetic regulation and “memory” in two fundamental biological processes in trees, wood formation and abiotic stress response. Wood formation is an ideal trait for epigenetic research in trees, as wood formation is highly responsive to environmental conditions and includes multiple rapid developmental changes as cells adopt distinct fates within complex tissues. This is followed by a discussion of research needs that would provide the foundation for new epigenetic applications for forestry.

Groover, Andrew↗
DOE OSTI2024

Coupled model intercomparison project phase 6 (CMIP6) high resolution model intercomparison project (HighResMIP) bias in extreme rainfall drives underestimation of amazonian precipitation

Abstract Extreme rainfall events drive the amount and spatial distribution of rainfall in the Amazon and are a key driver of forest dynamics across the basin. This study investigates how the 3-hourly predictions in the High Resolution Model Intercomparison Project (HighResMIP, a component of the recent Coupled Model Intercomparison Project, CMIP6) represent extreme rainfall events at annual, seasonal, and sub-daily time scales. TRMM 3B42 (Tropical Rainfall Measuring Mission) 3 h data were used as observations. Our results showed that eleven out of seventeen HighResMIP models showed the observed association between rainfall and number of extreme events at the annual and seasonal scales. Two models captured the spatial pattern of number of extreme events at the seasonal and annual scales better (higher correlation) than the other models. None of the models captured the sub-daily timing of extreme rainfall, though some reproduced daily totals. Our results suggest that higher model resolution is a crucial factor for capturing extreme rainfall events in the Amazon, but it might not be the sole factor. Improving the representation of Amazon extreme rainfall events in HighResMIP models can help reduce model rainfall biases and uncertainties and enable more reliable assessments of the water cycle and forest dynamics in the Amazon.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Allosterically coupled conformational dynamics in solution prepare the sterol transfer protein StarD4 to release its cargo upon interaction with target membranes

Complex mechanisms regulate the cellular distribution of cholesterol, a critical component of eukaryote membranes involved in regulation of membrane protein functions directly and through the physiochemical properties of membranes. StarD4, a member of the steroidogenic acute regulator-related lipid-transfer (StART) domain (StARD)-containing protein family, is a highly efficient sterol-specific transfer protein involved in cholesterol homeostasis. Its mechanism of cargo loading and release remains unknown despite recent insights into the key role of phosphatidylinositol phosphates in modulating its interactions with target membranes. We have used large-scale atomistic Molecular dynamics (MD) simulations to study how the dynamics of cholesterol bound to the StarD4 protein can affect interaction with target membranes, and cargo delivery. We identify the two major cholesterol (CHL) binding modes in the hydrophobic pocket of StarD4, one near S136&S147 (the Ser-mode), and another closer to the putative release gate located near W171, R92&Y117 (the Trp-mode). We show that conformational changes of StarD4 associated directly with the transition between these binding modes facilitate the opening of the gate. To understand the dynamics of this connection we apply a machine-learning algorithm for the detection of rare events in MD trajectories (RED), which reveals the structural motifs involved in the opening of a front gate and a back corridor in the StarD4 structure occurring together with the spontaneous transition of CHL from the Ser-mode of binding to the Trp-mode. Further analysis of MD trajectory data with the information-theory based NbIT method reveals the allosteric network connecting the CHL binding site to the functionally important structural components of the gate and corridor. Mutations of residues in the allosteric network are shown to affect the performance of the allosteric connection. These findings outline an allosteric mechanism which prepares the CHL-bound StarD4 to release and deliver the cargo when it is bound to the target membrane.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Demonstrating the Transient System Impact of Cyber-Physical Events Through Scalable Transmission and Distribution (T&D) Co-Simulation

Modern power systems become more vulnerable to cyber threats due to their growing interconnectivity, interdependence, and complexity. Widespread deployment of distributed energy resources (DERs) further expands the threat landscape to the grid edge, where fewer cybersecurity protections exist. In this article, a systematic cyber-physical events demonstration, enabled by an integrated transmission, distribution, and communication co-simulation framework, is performed. It analyzes cyber risks to power grid under DER-enabled automatic generation control from different angles. Unlike existing works, the simulation captures millisecond-to-minutes frequency and voltage transient dynamics at a cross-region system scale.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

A Hybrid Dynamic/Steady-State Tool With Protection Simulation for Cascading-Outage Analysis of Extreme Events in Power Systems

The bulk electric power grid is subject to vulnerabilities from component outages, which in certain combinations (extreme events) might lead to cascading outages. Some of these outages can be severe enough to trigger brownouts and blackouts. Much is known about mitigating the first few failures near the beginning of a cascade, but there are few established methods and tools for directly analyzing the risks of cascading component outages over a longer time scale. Current power system tools have limited ability to perform detailed and accurate cascading-outage analysis, which could be computationally intensive. The Dynamic Contingency Analysis Tool (DCAT) enables power system planning engineers to more realistically assess the consequences of extreme contingencies and potential cascading events across their systems and interconnections. DCAT has several unique features: (i) detailed hybrid dynamic and steady-state analysis of power systems to mimic real-world cascading outages, (ii) detailed modeling of protection systems embedded in the dynamic simulation, (iii) simulation of corrective action after transients, (iv) simulation of islanding , and (v) high-performance computing capability to simulate a large number of contingencies in a reasonable time. DCAT outputs will help find technically sound solutions to reduce the risk of cascading outages. This paper provides details of DCAT methodology and shows its capabilities with extreme events on real-world cases.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Ballistic Ejection of Microdroplets from Overpacked Interfacial Assemblies

Spontaneous emulsification, resulting from the assembly and accumulation of surfactants at liquid–liquid interfaces, is an interfacial instability where microdroplets are generated and diffusively spread from the interface until complete emulsification. Here, it is shown that an external magnetic field can modulate the assembly of paramagnetic nanoparticle surfactants (NPSs) at liquid–liquid interfaces to trigger an oversaturation in the areal density of the NPSs at the interface, as evidenced by a marked reduction in the interfacial tension, γ, and corroborated with a magnetostatic continuum theory. Despite the significant reduction in γ, the presence of the magnetic field does not cause stable interfaces to become unstable. Upon rapid removal of the field, however, an explosive ejection of a plume of microdroplets from the surface occurs, a dynamical interfacial instability which is termed explosive emulsification. Further, this explosive event rapidly reduces the areal density of the NPSs to its pre-field level, stabilizing the interface. The ability to externally suppress or trigger the explosive emulsification and controlled generation of tens of thousands of microdroplets, uncovers an efficient energy storage and release process, that has potential applications for controlled and directed delivery of chemicals and remotely controlled soft microrobots, taking advantage of the ferromagnetic nature of the microdroplets.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Phenomenological opportunities at the EIC

This review presents a comprehensive overview of key phenomenological opportunities at the future Electron–Ion Collider (EIC), synthesizing discussions and collaborative research efforts developed within the Korean EIC community and the EICφ collaboration. We explore a diverse range of physics topics central to the EIC scientific program, including the multidimensional tomography of nucleon and nuclear structure, precision Quantum Chromodynamics studies through jet physics and event-shape observables, heavy quarkonium production as a probe of partonic dynamics, and the spectroscopy of exotic hadrons. Furthermore, we discuss the transformative potential of emerging technologies—specifically Machine Learning and Quantum Computing—as essential tools for addressing the computational challenges and maximizing the scientific discovery potential of the EIC era.

Electron–Ion collider↗
DOE OSTI2022

Disclination-dislocation based model for grain boundary stress field evolution due to slip transmission history and influence on subsequent dislocation transmission

This work demonstrates how the structure of a grain boundary (GB) and its evolution due to slip transmission history influences subsequent dislocation transmission. First, a model for the evolution of stress fields within grain boundaries that accounts for the effects of coherent dislocation transmission is introduced. Starting with a disclination-based construct of GBs at minimum energy (equilibrium), the model describes the evolution of the GB stress field to a state characteristic of excess energy (non-equilibrium) due to the incorporation of residual Burgers vector content following sequential slip transmission events. Several essential features of this model are verified via molecular dynamics simulations of lattice dislocation absorption. Second, this model is implemented into a discrete dislocation dynamics (DDD) code and simulations are performed to understand the influence of Non-equilibrium GB stress fields, conditioned by the slip transmission history, on subsequent dislocation transmission. DDD simulations reveal that the critical resolved stress necessary for slip propagation can be reduced by with continued absorption of residual dislocation content. Moreover, DDD simulations prove that a comprehensive consideration of both the binding and driving stresses, and the evolution of the transmission configuration is necessary to quantify the influence of the mechanical state of the GB on slip propagation. In general, this work provides important insights into the role of GB structure evolution, conditioned by prior deformation history, on intergranular plasticity.

42 ENGINEERING↗
DOE OSTI2023

Amazon windthrow disturbances are likely to increase with storm frequency under global warming

Abstract Forest mortality caused by convective storms (windthrow) is a major disturbance in the Amazon. However, the linkage between windthrows at the surface and convective storms in the atmosphere remains unclear. In addition, the current Earth system models (ESMs) lack mechanistic links between convective wind events and tree mortality. Here we find an empirical relationship that maps convective available potential energy, which is well simulated by ESMs, to the spatial pattern of large windthrow events. This relationship builds connections between strong convective storms and forest dynamics in the Amazon. Based on the relationship, our model projects a 51 ± 20% increase in the area favorable to extreme storms, and a 43 ± 17% increase in windthrow density within the Amazon by the end of this century under the high-emission scenario (SSP 585). These results indicate significant changes in tropical forest composition and carbon cycle dynamics under climate change.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Advanced co-simulation framework for assessing the interplay between occupant behaviors and demand flexibility in commercial buildings

With buildings contributing significantly to electricity usage, enabling demand flexibility becomes a challenge, especially when accounting for occupant comfort. This study introduces an innovative co-simulation framework integrating multiple models: heating, ventilation, and air conditioning (HVAC) system, building zone load, indoor airflow, supervisory control, and occupant comfort and behavior. Uniquely, this framework allows for a comprehensive and dynamic analysis of building systems and occupant interactions in demand response events. Using this framework, we conducted a case study using a typical small office building model. Specifically, we focused on three areas: (1) the impact of indoor airflow modeling on energy use, occupant comfort, and behaviors forecasting, (2) the impact of occupant behaviors on demand flexibility, and (3) occupant comfort and behaviors under demand response events. Key performance indicators such as energy use, flexibility factor, durations of occupant discomfort and occupant behaviors were analyzed. Our findings indicated variations in energy usage and occupant comfort within demand flexibility events, marked by uncertainty boundaries, with variability in demand shedding up to 57.9%. Here, we concluded that this framework is suitable for analyzing typical commercial buildings and their HVAC systems in terms of demand flexibility potential under the impact of occupant behaviors.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Bulk Power System Dynamics with Varying Levels of Synchronous Generators and Grid-Forming Power Inverters

Inverters using phase-locked loops for control depend on voltages generated by synchronous machines to operate. This might be problematic if much of the conventional generation fleet is displaced by inverters. To solve this problem, grid-forming control for inverters has been proposed as being capable of autonomously regulating grid voltages and frequency. Presently, the performance of bulk power systems with massive penetration of grid-forming inverters has not been thoroughly studied as to elucidate benefits. Hence, this paper presents inverter models with two grid-forming strategies: virtual oscillator control and droop control. The two models are specifically developed to be used in positive-sequence simulation packages and have been implemented in PSLF. The implementations are used to study the performance of bulk power grids incorporating inverters with gridforming capability. Specifically, simulations are conducted on a modified IEEE 39-bus test system and the microWECC test system with varying levels of synchronous and inverter-based generation. The dynamic performance of the tested systems with gridforming inverters during contingency events is better than cases with only synchronous generation.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Urbanization-induced land and aerosol impacts on storm propagation and hail characteristics

Changes in land surface and aerosol characteristics from urbanization can affect dynamic and microphysical properties of severe storms, thus affecting hazardous weather events resulting from such storms such as hail and tornado. We examine the joint and individual effects of urban land and anthropogenic aerosols of Kansas City on a severe convective storm observed during the 2015 Plains Elevated Convection At Night (PECAN) field campaign, focusing on storm evolution, convective intensity, and hail characteristics. The simulations are carried out at the cloud-resolving scale (1 km) using a version of WRF-Chem in which the spectral-bin microphysics (SBM) is coupled with the Model for Simulating Aerosol Interactions and Chemistry (MOSAIC). It is found that the urban land effect of Kansas City initiated a much stronger convective cell and the storm got further intensified when interacting with stronger turbulence induced by the urban land. The urban land effect also changed the storm path by diverting the storm toward the city mainly resulting from enhanced urban land-induced convergence in the urban area and around the urban-rural boundaries. The joint effect of urban land and anthropogenic aerosols enhances occurrences of both severe hail and significant severe hail by ~ 20% by enhancing hail formation and growth from riming. Overall the urban land effect on convective intensity and hail is relatively larger than the anthropogenic aerosol effect, but the joint effect is much notable than either of the individual effects, emphasizing the importance to consider both effects in evaluating urbanization effects.

Lin, Yun↗
DOE OSTI2025

Regional Source-Type Discrimination Using Nonlinear Alignment Algorithms

The discrimination problem in seismology aims to accurately classify different underground source types based on local, regional, and/or teleseismic observations of ground motion. Typical discriminant approaches are rooted in fundamental, physics-based differences in radiation pattern or wave excitation, which can be frequency-dependent and may not make use of the full waveform. In this article, we explore whether phase and amplitude distances derived from dynamic time warping (DTW) and elastic shape analysis (ESA) can inform event discrimination. We demonstrate the ability to distinguish underground point sources using synthetic waveforms calculated for a 1D Earth model and various source mechanisms. We then apply the method to recorded data from events in the Korean Peninsula, which includes declared nuclear explosions, a collapse event, and naturally occurring earthquakes. Phase and amplitude distances derived from DTW and ESA are then used to classify the event types via dendrogram and k-nearest-neighbor clustering analyses. Using information from the full waveform, we show how different underground sources can be distinguished at regional distances. We highlight the potential of these nonlinear alignment algorithms for discrimination and comment on ways we can extend the framework presented here.

58 GEOSCIENCES↗
DOE OSTI2022

Di-$\pi^0$ correlations in p+p, p+Al and p+Au collisions at $\sqrt{s_{NN}}$ = 200 GeV at STAR

The STAR Collaboration reports measurements of back-to-back azimuthal correlations of di- \pi^0 π 0 produced at forward pseudorapidity ( 2.6<\eta<4.0 2.6 < η < 4.0 ) in p+ p + p p , p+ p + \mathrm{Al} A l and p+ p + \mathrm{Au} A u collisions at a center-of-mass energy per nucleon-nucleon pair of 200 GeV. A clear suppression of the correlated away-side yields is observed in p+ p + \mathrm{Au} A u and for the first time in p+ p + \mathrm{Al} A l collisions, compared with the p p + + p p data. The enhanced suppression found in p+ p + \mathrm{Au} A u with respect to p+ p + \mathrm{Al} A l collisions exhibits the saturation scale ( Q_s^2 Q s 2 ) dependence on the mass number A A . The observed suppression of back-to-back pairs as a function of event activity and transverse momentum points to non-linear gluon dynamics arising at high parton densities.

Chu, Xiaoxuan↗