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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 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Robust Adaptive Decentralized Dynamic State Estimation with Unknown Control Inputs using Field PMU Measurements

This paper proposes a robust adaptive decentralized dynamic state estimation method for power system with unknown inputs of the highly detailed synchronous machine model. The temporal and spatial correlations among the unknown inputs are used to derive a vector auto-regressive model. The latter is further integrated together with state transition and measurement models for joint state and unknown inputs estimation. Thanks to the consideration of implicit cross-correlations between the states and the unknown inputs, only generator terminal voltage and current phasors are needed. Test results on the US WECC system using the field PMU measurements show that the proposed method is able to track both the system dynamic states and unknown controller inputs. These information could significantly benefit the validation and calibration of generator controller parameters.

Zhao, Junbo↗
DOE OSTI2024

Nonlinear model predictive control for mode‐switching operation of reversible solid oxide cell systems

Abstract Solid oxide cells (SOCs) are a promising dual‐mode technology for the production of hydrogen through high‐temperature water electrolysis, and the generation of power through a fuel cell reaction that consumes hydrogen. Switching between these two modes as the price of electricity fluctuates requires reversible SOC operation and accurate tracking of hydrogen and power production set points. Moreover, a well‐functioning control system is important to avoid cell degradation during mode‐switching operation. In this article, we apply nonlinear model predictive control (NMPC) to an SOC module and supporting equipment and compare NMPC performance to classical proportional‐integral (PI) control strategies, while switching between the modes of hydrogen and power production. While both control methods provide similar performance across various metrics during mode switching, NMPC demonstrates a significant advantage in reducing cell thermal gradients and curvatures (mixed spatial‐temporal partial derivatives), thereby helping to mitigate long‐term degradation.

08 HYDROGEN↗
DOE OSTI2024

Characterization of Biomass-Based Fuels and Fuel Blends for Low-Emissions, Advanced Compression Ignition Engines (Final Report)

The goal of the Co-Optima program was to accelerate deployment of co-optimized fuels and engines that will reduce fuel consumption, and criterion pollutants and greenhouse gas (GHG) emissions for both spark and compression-ignited engines. In this project, combustion measurements from a constant pressure flow rig (CPFR) with optical access were used to assess fundamental combustion behavior of number of different candidate fuels and fuel blends. This chamber and its peripheral systems allowed stable control of ambient air pressure and temperature and fuel injection pressure and timing for hundreds of repeat injections allowing statistical interpretation of the results. The optical diagnostics enabled capturing of liquid length, vapor length, ignition timing, lift-off length as well as localized (temporal and spatially resolved) mixture refractive index, flame structure, and soot mass. The operating conditions allowed the study of combustion conditions promoting lean lifted flame combustion (LLFC), a mixing-controlled low-temperature combustion (LTC) strategy to reduce soot production in Advanced Compression Ignition (ACI) engines.

09 BIOMASS FUELS↗
DOE OSTI2022

Soil oxidoreductase zymography: Visualizing spatial distributions of peroxidase and phenol oxidase activities at the root-soil interface

Decomposition of organic material in the rhizosphere – the most dynamic microbial habitat in soil – involves arrays of oxidoreductase and hydrolytic enzymes. Spatial distributions of various hydrolytic activities in soil have already been explored by zymographic techniques. However, the distribution of oxidative activity in the rhizosphere remains to be studied. Thus, we extended a Time-Lapse Zymography technique, using Amplex Red® reagent, to visualize and quantify distributions of phenol oxidase and peroxidase activities in the rhizosphere of Zea mays L. growing in a Haplic Phaeozem and the non-rhizospheric soil. The gross oxidative activity was greatest at the root surfaces, and fell to background soil levels 1.26 and 0.73 mm from seminal (>1 mm diameter) and lateral (<0.5 mm diameter) roots, respectively. The rhizosphere extent relative to the root radius was 59% broader around lateral than around seminal roots. The greatest activities, up to 30 nmol cm –2 min –1 , were peroxidase-dominated and closely associated with roots. Here, the results confirm the utility of the approach for studying spatio-temporal distributions of oxidative activities in soil. However, actual activity of oxidoreductases in the field will be strongly controlled by fluctuating environmental conditions such as soil aeration and the gradient of reactive oxygen species, which need to be considered especially in anoxic soils.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Design of facilitated dissociation enables timing of cytokine signalling

Protein design has focused on the design of ground states, ensuring that they are sufficiently low energy to be highly populated. Designing the kinetics and dynamics of a system requires, in addition, the design of excited states that are traversed in transitions from one low-lying state to another. This is a challenging task because such states must be sufficiently strained to be poorly populated, but not so strained that they are not populated at all, and because protein design methods have focused on generating near-ideal structures. Here we describe a general approach for designing systems that use an induced-fit power stroke to generate a structurally frustrated and strained excited state, allosterically driving protein complex dissociation. X-ray crystallography, double electron–electron resonance spectroscopy and kinetic binding measurements show that incorporating excited states enables the design of effector-induced increases in dissociation rates as high as 5,700-fold. We highlight the power of this approach by designing rapid biosensors, kinetically controlled circuits and cytokine mimics that can be dissociated from their receptors within seconds, enabling dissection of the temporal dynamics of interleukin-2 signalling.

deformation dynamics↗
DOE OSTI2022

Controlled Injection of Electrons for Improved Performance of Laser-Wakefield Acceleration

Our lab performed a series of experiments on controlled injection of LWFA with two extreme laser pulses: one laser pulse was used to drive LWFA. In contrast, the other precisely controls the injection of electrons into the wakefield plasma wave. We have demonstrated an efficient reduction of electron beam emittance by optical injection and novel spatio-temporal manipulation of the electron beam by the extreme laser-plasma waves. Moreover, the optical injection process involves unprecedented new physics, which will benefit studies in astrophysics, inertial confinement fusion, laser-driven x-ray light sources, and ultrafast science. We further improved the performance of LWFA by a better understanding and control of the extreme laser-plasma wave dynamics for optical injection. Three novel mechanisms were identified in the optical injection process: (1) collision of two laser pulses, (2) collision of a laser pulse with a wakefield plasma wave, and (3) collision of two laser wakefields. All three methods improved electron-beam energy spread, emittance, stability, and reproducibility. First, we identified, compared, and independently controlled these different injection mechanisms by controlling the polarization of the injector laser pulse. Second, we manipulated the spatiotemporal splitting of LWFA electron beams to reduce their emittance. Third, we applied the same laser-plasma-wave dynamics and the same experimental setup for improved performance of ion acceleration, which has also been predicted by the recent simulations.

43 PARTICLE ACCELERATORS↗
DOE OSTI2020

Temporal Resource Continuity Increases Predator Abundance in a Metapopulation Model: Insights for Conservation and Biocontrol

The amount of habitat in a landscape is an important metric for evaluating the effects of land cover on biodiversity, yet it fails to capture complex temporal dimensions of resource availability that could be consequential for species population dynamics. Here, we use a spatially-explicit predator–prey metapopulation model to test the effect of different spatiotemporal resource patterns on insect predators and their prey. We examined population responses in model landscapes that varied in both the amount and temporal variability of basal vegetation. Further, we examined cases where prey comprised either a single generalist species or two specialist species that use different resources available either early or late in the growing season. We found that predators and generalist prey benefitted from lower temporal variance of basal resources, which increased landscape-scale abundances. However, increasing the amount of basal resources also increased the variability of generalist prey populations. Specialist prey, on the other hand, did not benefit from less temporally variable basal resources, as they were restricted by habitat type, while also suffering greater predation. Predators achieved greater prey suppression in landscapes with less temporally variable resources, but the overall effects on prey abundance depended on prey habitat specialization. Our simulations demonstrate the joint importance of both the amount and temporal variability of resources for understanding how landscape heterogeneity influences biodiversity and ecosystem services such as the biological control of agricultural pests.

Spiesman, Brian↗
DOE OSTI2025

Interference Control of Fano Resonances and Dynamical Imaging of an Electron Wave Packet

The Fano line shape, arising from the interference of pathways for the excitation of discrete and continuum states, plays a fundamental role in many branches of physics, chemistry, and materials science. Exciting the resonance with a high harmonic provides naturally a phase delay between the pathways leading to a complex asymmetry parameter. We demonstrate that its amplitude and phase can be controlled on the femtosecond and attosecond time scales, respectively. With our high-energy-resolution (10-meV) experiment, we dynamically image a resonance-enhanced electron wave packet during its temporal evolution, extracting both the amplitude and the phase. Calculations reproduce our experimental results. Our approach constitutes a method for measuring the photoionization delays of a resonance and enables the reconstruction of the electron wave packet in the time domain. This concept of an interference-controlled Fano line shape is a step toward attosecond quantum optics with potential ramifications into nanoscience and next-generation optical materials.

Han, Meng [ETH Zürich (Switzerland); Kansas State ↗
DOE OSTI2021

Temporal nitrogen dynamics in intensively managed loblolly pine early stand development

Forest production is strongly dependent on nutrient uptake; however, sustainable management of intensively managed plantations requires an improved understanding of this relationship when fertilization occurs frequently across short rotations. Here, we studied temporal nitrogen (N) concentration ([N]) and content (Nc) dynamics under different silvicultural practices (herbicide, fertilization, and planting density) throughout early loblolly pine (Pinus taeda) stand development (5 years). We describe relationships of [N] and Nc of different stand components (foliage, branches, stem, roots, and competing vegetation) with carbon and biomass. Our results demonstrate that [N] of perennial loblolly tissues do not respond to silvicultural practices and progressively decrease through development. While foliar [N] was most responsive to resource availability, it was not consistent across time. Controlling competing vegetation was crucial to promote the use of site resources by the crop tree and increased loblolly Nc by >500%. However, increased N uptake and expedited growth is dependent upon fertilization early in stand development. At age 5, herbicide plus reduced and full fertilization rates exhibited similar aboveground Nc, which was 32% higher than with herbicide only. Increasing planting density resulted in increased above- and belowground loblolly Nc; however, increases in Nc were not proportional with increases in planting density. Net primary productivity and N uptake were linearly related, but age/development strongly controlled N use efficiency. Our study helps to understand complex relationships between N, biomass, and silvicultural practices during early stand development and demonstrates that temporal evaluation of nutrient dynamics is crucial to better understand loblolly pine growth, carbon sequestration potential, and to inform sustainable silvicultural practices across short rotations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Properties and Controlling Processes of Aerosol and Cloud Condensation Nuclei in Marine Boundary Layer Over Eastern North Atlantic (Final Report)

Remote marine low cloud systems have large spatial and temporal coverages. Because of their relatively low optical thickness and background aerosol concentrations, marine low clouds are particularly susceptible to perturbations in aerosols associated with anthropogenic emissions. Recent studies show that a large fraction of the global aerosol indirect forcing can be attributed to changes in marine low clouds, despite their relatively long distance from most anthropogenic sources. Currently, there remain large uncertainties in the magnitude of the global aerosol indirect radiative forcing. One major contribution to this large uncertainty derives from poor understanding of the aerosols under natural conditions, the perturbation by anthropogenic emissions, and the processes that drive them. In this project, we took advantage of the comprehensive, multi-dimensional characterization of meteorological parameters, trace gases, aerosol, cloud, and drizzle fields during the Aerosol and Cloud Experiments in Eastern North Atlantic (ACE-ENA) and the long-term measurements at the Atmospheric Radiation Measurement (ARM) Eastern North Atlantic (ENA) site on Graciosa Island. By synergistically combining in situ measurements, remote sensing retrievals, and model simulations, we quantified aerosol properties in the ENA, their vertical profiles, and variations with season, synoptic state, and airmass. We investigated key aerosol processes, including entrainment of free troposphere aerosol into marine boundary layer, new particle formation, growth of Aitken mode particles, and the influences of these processes on the cloud condensation nuclei (CCN) population in marine boundary layer. The representation of key aerosol processes in the Energy Exascale Earth System Model (E3SM) was evaluated using the observations. This project has led to 26 publications, which are listed at the end of this report.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Fracture Characterization Via AI‐Assisted Analysis of Temperature Logs

Abstract Fractures control fluid flow, mass transport, and heat transfer in a geothermal reservoir. This makes accurate characterization of fracture networks a prerequisite for optimal design and control of a reservoir's exploitation. We develop a deep‐learning procedure to identify fracture locations via interpretation of temporally and spatially continuous downhole temperature measurements. A long short‐term memory fully convolutional network (LSTM‐FCN) is used both to capture long‐term dependencies in sequential temperature data and to distill local features around fractures. A wellbore and fractured‐reservoir thermal model is established to generate temperature data for network training. The trained LSTM‐FCN exhibits a unique ability to detect multiple fractures intersecting a borehole. We use the LSTM‐FCN algorithm to evaluate the effectiveness of different‐stage wellbore temperature measurements on fracture detection in a complex fractured system. Our experiments reveal that the use of various‐stage temperature information as an input feature set improves the robustness of fracture detection to noise interference. This study indicates the practical feasibility of obtaining accurate fracture‐network reconstructions from temperature signals, at reasonable computational cost.

Yang, Xiaoyu↗
DOE OSTI2024

NMPC for Mode-Switching Operation of Reversible Solid Oxide Cell Systems

Solid oxide cells (SOCs) are a promising dual-mode technology that generates hydrogen through high-temperature water electrolysis and generates power through a fuel cell reaction that consumes hydrogen. Reversible operation of SOCs requires a transition between these two modes for hydrogen production setpoints as the demand and price of electricity fluctuate. Moreover, a well-functioning control system is important to avoid cell degradation during mode-switching operation. In this work, we apply nonlinear model predictive control (NMPC) to an SOC module and supporting equipment and compare NMPC performance to classical proportional integral (PI) control strategies, while ramping between the modes of hydrogen and power production. While both control methods provide similar performance in many metrics, NMPC significantly reduces cell thermal gradients and curvatures (mixed spatial-temporal partial derivatives) during mode switching. A dynamic process flowsheet of the reversible SOC system was developed in the open-source, equation-based IDAES modeling framework. Our IDAES dynamic simulation results show that NMPC can ramp the SOC system between hydrogen and power production targets within short mode-switching times. Moreover, NMPC can comply with operating limits in the SOC system more effectively than PI, and only NMPC can directly enforce user-specified limits for mixed spatial-temporal partial derivatives of temperature. This allows for management of the trade-off be-tween operating efficiency and cell degradation, which is dependent on these temperature curvatures.

Li, Mingrui↗
DOE OSTI2023

System and method for temporal dispersion compensator

The present disclosure relates to a system for modifying temporal dispersion in an optical signal. The system makes use of a segmented array including a plurality of independently controllable, reflective optical elements. The optical elements are configured to segment a received input optical signal into a plurality of beamlets, and to reflect and steer selected ones of the plurality of beamlets in predetermined angular orientations therefrom. A variable optical dispersion subsystem is used which has a plurality of optical components configured to receive and impart different predetermined time delays to different ones of the received beamlets, and to output the plurality of beamlets therefrom.

Panas, Robert Matthew↗
DOE OSTI2023

Longitudinal Changes in Immune Activation Serum Biomarkers Prior to Diagnosis and Risk of B-cell NHL Subtypes

To examine the contribution of B-cell activation molecules to B-cell follicular lymphoma (FL) and diffuse large B-cell lymphoma (DLBCL), a prospective study was conducted using pre-diagnosis serial serum samples from the US Department of Defense Serum Repository. Each case (n = 142 FL, n = 211 DLBCL) was matched to two controls on age, gender, race, military branch, and blood collection dates. Immune activation molecules (IL1β, IL2, IL4, IL5, IL6, IL10, IL12, CXCL13, IL8, TNFα, IFNγ, GM-CSF, VEGF, sCD30, IgE) were quantified using ELISA or multiplex immunometric (Luminex) assay. Longitudinal data were analyzed using linear mixed modeling. As serial specimens were collected over several years before diagnosis, we evaluated the temporal dynamics of these markers. Increased serum levels of sCD30, CXCL13, and to a lesser extent IL10, were associated with both FL and DLBCL in cases compared with controls, with a median follow-up of 5.5 years from the earliest specimen collection to diagnosis date. Significant increasing sCD30 and CXCL13 trajectories for FL and DLBCL subtypes were noted starting at the earliest time points and with IL10 levels increasing significantly at time points closer to diagnosis. In conclusion, these results suggest that sCD30, CXCL13, and IL10 may contribute to the etiology of FL and DLBCL and are potential biomarkers for these non–Hodgkin lymphoma subtypes. The increasing trajectories of the B-cell activation molecules, sCD30, CXCL13, and to a lesser extent IL10, may indicate early disease-induced effects or reflect the chronic stimulation of B-cells that promotes the development of FL and DLBCL subtypes.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2026

Compositional Reasoning for Hierarchical State Machines

Harel statecharts and its derivatives are popular graphical languages for specifying discrete control systems via hierarchical state machines. Separately, there has been a long line of work on specifying concurrent systems with process calculi which come equipped with an algebraic theory, the ability reason compositionally about various temporal properties, and strong type systems. While these two approaches to modeling systems are tantalizingly similar, the integrated reasoning principles that exist for process calculi have not been demonstrated in hierarchical state machines. A key issue is that operational theories for process calculi do not behave like control systems, and thus, there is virtually no tool support for modeling control systems with such languages. For a control system designer, bringing the integrated, more scalable reasoning from the process calculi to state-machine languages would enable the specification of more complex systems and a more modular systems development process. Our insight is that we can recover many important results from the process calculi in hierarchical state machines with local scope. We employ a structural operational semantics, which is ubiquitous in process and 𝜆-calculi but uncommon in hierarchical statemachine formalizations, to enable inductive reasoning about behavior. Taking inspiration from the structure of process calculi metatheories, we define a calculus of refinement and equivalence that we prove sound with respect to local notion of (bi)simulation. Furthermore, we prove that the calculus preserves the behavioral properties of reactivity, observational determinism, traces, and linear temporal properties. Our results are mechanized in the Rocq proof assistant.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Science Area 1: Standard Award: Model-Data Fusion to Examine Multiscale Dynamical Controls on Snow Cover and Critical Zone Moisture Inputs (Final Report)

In many mountain watersheds of the world, seasonal snowpacks play an important role as natural reservoirs of water. Seasonal snowpacks accumulate water during cold, wet winter months that subsequently melts. Downstream communities depend on water from melting seasonal snowpacks to support agricultural, industrial, and municipal water needs. Rapidly melting snowpacks can also present a flooding hazard, particularly if snowpacks melt at rates faster than anticipated and where adequate reservoir capacity is unavailable to buffer river flows associated with melt. The spatial and temporal dynamics of snow accumulation and melt also play an important role in supporting upland ecosystems in mountain landscapes. Snowmelt provides soil moisture that enable terrestrial ecosystem productivity and exert control on soil microorganisms that play important roles in global carbon cycles. Climate warming is gradually decreasing the amount of precipitation in mountain watersheds arriving as snow, presenting potentially profound disruptions to mountain ecosystems, as well as downstream delivery of water. The overarching goal of this project was to understand how interactions between the near-surface atmosphere and surface topography control the input, accumulation, retention, and release of water from mountain snowpacks. Over a 5-year period, this project pursued an approach combining high-resolution regional climate modeling, satellite and airborne remote sensing data, and ground-based observations to develop and analyze benchmark datasets to address overarching science questions and hypotheses. Key products include a continuous, long-term, high spatiotemporal resolution (1 km/1 hr) dataset characterizing key climate variables in the Upper Colorado River Basin. The dataset included historical estimates of precipitation, temperature, humidity, solar and longwave radiation, and wind speeds. Additionally, the project developed a 20+ year long, 30 m spatial, daily temporal multi-sensor dataset characterizing snow presence/absence in the East/Taylor River watersheds in the Central Rocky Mountains of Colorado. The project supported training of 1 postdoctoral scholar, 1 Ph.D. student, and 1 M.S. student.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Forty-year hydropower generation reanalysis for Conterminous United States

First published in 2022, the RectifHyd dataset provides hydrologically consistent estimates of monthly net generation for approximately 1,500 hydropower plants in the United States, addressing a gap in industrial surveys that have collected monthly generation data from only ~10% of plants post-2003. Here we present RectifHydPlus—an extended and enhanced dataset that improves on both the proxy information and temporal downscaling methodology adopted in RectifHyd. In addition to providing updated estimates of historical monthly generation for 590 plants with >10 MW nameplate capacity from 1980 through 2019, RectifHydPlus adds a hydrological control dataset that isolates the influence of historical water availability on generation. The new hydrological control dataset is suited to applications seeking to represent the capabilities of the contemporary fleet subject to historical interannual variability in climate. RectifHydPlus also includes a forty-year, daily-resolution, spill-adjusted water release time series for each dam, allowing users to aggregate generation estimates to the desired temporal resolution.

Hydroelectricity↗