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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 523 records · Page 29
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

In-vivo Raman microspectroscopy reveals differential nitrate concentration in different developmental zones in Arabidopsis roots

Abstract Background Nitrate (NO 3 − ) is one of the two major forms of inorganic nitrogen absorbed by plant roots, and the tissue nitrate concentration in roots is considered important for optimizing developmental programs. Technologies to quantify the expression levels of nitrate transporters and assimilating enzymes at the cellular level have improved drastically in the past decade. However, a technological gap remains for detecting nitrate at a high spatial resolution. Using extraction-based methods, it is challenging to reliably estimate nitrate concentration from a small volume of cells (i.e., with high spatial resolution), since targeting a small or specific group of cells is physically difficult. Alternatively, nitrate detection with microelectrodes offers subcellular resolution with high cell specificity, but this method has some limitations on cell accessibility and detection speed. Finally, optical nitrate biosensors have very good ( in-vivo ) sensitivity (below 1 mM) and cellular-level spatial resolution, but require plant transformation, limiting their applicability. In this work, we apply Raman microspectroscopy for high-dynamic range in-vivo mapping of nitrate in different developmental zones of Arabidopsis thaliana roots in-situ . Results As a proof of concept, we have used Raman microspectroscopy for in-vivo mapping of nitrate content in roots of Arabidopsis seedlings grown on agar media with different nitrate concentrations. Our results revealed that the root nitrate concentration increases gradually from the meristematic zone (~ 250 µm from the root cap) to the maturation zone (~ 3 mm from the root cap) in roots grown under typical growth conditions used for Arabidopsis, a trend that has not been previously reported. This trend was observed for plants grown in agar media with different nitrate concentrations (0.5–10 mM). These results were validated through destructive measurement of nitrate concentration. Conclusions We present a methodology based on Raman microspectroscopy for in-vivo label-free mapping of nitrate within small root tissue volumes in Arabidopsis. Measurements are done in-situ without additional sample preparation. Our measurements revealed nitrate concentration changes from lower to higher concentration from tip to mature root tissue. Accumulation of nitrate in the maturation zone tissue shows a saturation behavior. The presented Raman-based approach allows for in-situ non-destructive measurements of Raman-active compounds.

Fernández González, Alma↗
DOE OSTI2024

Data for Spatially Varying Costs of GHG Abatement with Alternative Cellulosic Feedstocks for Sustainable Aviation Fuels

Cellulosic biomass-based sustainable aviation fuels (SAFs) can be produced from various feedstocks. The breakeven price and carbon intensity of these feedstock-to-SAF pathways are likely to differ across feedstocks and across spatial locations due to differences in feedstock attributes, productivity, opportunity costs of land for feedstock production, soil carbon effects, and feedstock composition. We integrate feedstock to fuel supply chain economics and life-cycle carbon accounting using the same system boundary to quantify and compare the spatially varying greenhouse gas (GHG) intensities and costs of GHG abatement with SAFs derived from four feedstocks (switchgrass, miscanthus, energy sorghum, and corn stover) at 4 km resolution across the U.S. rainfed region. We show that the optimal feedstock for each location differs depending on whether the incentive is to lower breakeven price, carbon intensity, or cost of carbon abatement with biomass or to have high biomass production per unit land. The cost of abating GHG emissions with SAF ranges from $181 Mg−1 CO2e to more than $444 Mg−1 CO2e and is lowest with miscanthus in the Midwest, switchgrass in the south, and energy sorghum in a relatively small region in the Great Plains. While corn stover-based SAF has the lowest breakeven price per gallon, it has the highest cost of abatement due to its relatively high GHG intensity. Our findings imply that different types of policies, such as volumetric targets, tax credits, and low carbon fuel standards, will differ in the mix of feedstocks they incentivize and locations where they are produced in the U.S. rainfed region. Note: Column V in TableS7_DayCentSimulatedYield.csv should be labelled Corn Stover CoSo-NT-50% Max.

Geospatial↗
DOE OSTI2023

Influence of ambient gas on self-reversal in Li transitions relevant to isotopic analysis

Laser induced breakdown spectroscopy is a promising, rapid analysis method for the detection and quantification of Li and its isotopes needed in geochemical, nuclear, and energy storage applications. However, spectral broadening in laser produced plasmas, presence of fine and hyperfine structures, and self-reversal effects make Li isotopic analysis via laser induced breakdown spectroscopy challenging. The present study explores the influence of Ar, N 2 , and He ambient gases over the pressure range of 0.05 - 100 Torr on line broadening and self-reversal of the Li I transition with the greatest isotopic shift in the VIS spectral region (i.e., ≈670.8 nm, ≈15.8 pm isotopic shift). We perform spatially and temporally resolved optical emission spectroscopy of plasmas produced via laser ablation of LiAlO 2 substrates. Our results show that the self-reversal and linewidth is reduced at lower pressures for all gases, and using optimized plasma conditions with chemometric methods, the 6 Li/ 7 Li isotopic ratios can be predicted.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Integrating Radio-Over-Fiber Communication System and BOTDR Sensor System

In this paper, we propose and experimentally demonstrate for the first time, the integration of a radio-over-fiber (RoF) communication system and a Brillouin optical time-domain reflectometry (BOTDR) distributed sensor system using a single optical fiber link. In this proof-of-concept integrated system, the communication system is composed of three modulation formats of quadrature phase-shift keying (QPSK), 16-quadrature amplitude modulation (16-QAM) and 64-QAM, which are modulated onto an orthogonal frequency division multiplexing (OFDM) signal. Whereas, the BOTDR sensor system is used for strain and/or temperature monitoring over the fiber distance with a spatial resolution of 5 m using a 25 km single-mode silica fiber. The error vector magnitude (EVM) is analyzed in three modulation formats in the presence of various BOTDR input pump powers. Using QPSK modulation, optimized 18 dBm sensing and 10 dBm data power, the measured EVM values with and without bandpass filter are 3.5% and 14.5%, respectively. The proposed system demonstrates a low temperature measurement error (±0.49 °C at the end of 25 km) and acceptable EVM values, which were within the 3GPP requirements. The proposed integrated system can be effectively applied for practical applications, which significantly reduces the fiber infrastructure cost by effective usage of a single optical fiber link.

42 ENGINEERING↗
DOE OSTI2022

Wave resource spatial and temporal variability dependence on WEC size

As the wave energy sector grows and looks to the Blue Economy for commercialization opportunities, there is a distinct and pressing need to clearly understand and quantify the coupled impacts of wave energy converter (WEC) size and wave resource characteristics on the annual energy production, spatial variability and temporal variability. Utilizing generic frequency domain representations of the Oscilla Power Triton WEC and spectral wave conditions at PacWave (Oregon), Los Angeles (California) and WETS (Hawaii), a series of interesting results emerge. Firstly, the ‘optimal’ WEC size, from an energy standpoint, is fundamentally dependent on the frequency distribution of the incoming wave variance density spectrum. Secondly, and from a seasonality perspective, the seasonal WEC energy generation doesn’t necessarily follow the seasonal distribution of gross wave power. Finally, from an hourly power variability perspective, a reduction in WEC size generally decreases variability. However, for each of the locations investigated, there appears to be a WEC size threshold; a threshold where further reducing WEC size results in increased power variability.

16 TIDAL AND WAVE POWER↗
DOE OSTI2021

Wave Resource Spatial and Temporal Variability Dependence on WEC Size

As the wave energy sector grows and looks to the Blue Economy for commercialization opportunities, there is a distinct and pressing need to clearly understand and quantify the coupled impacts of wave energy converter (WEC) size and wave resource characteristics on the annual energy production, spatial variability and temporal variability. Utilizing generic frequency domain representations of the Oscilla Power Triton WEC and spectral wave conditions at PacWave (Oregon), Los Angeles (California) and WETS (Hawaii), a series of interesting results emerge. Firstly, the 'optimal' WEC size, from an energy standpoint, is fundamentally dependent on the frequency distribution of the incoming wave variance density spectrum. Secondly, and from a seasonality perspective, the seasonal WEC energy generation doesn't necessarily follow the seasonal distribution of gross wave power. Finally, from an hourly power variability perspective, a reduction in WEC size generally decreases variability. However, for each of the locations investigated, there appears to be a WEC size threshold; a threshold where further reducing WEC size results in increased power variability.

blue economy↗
DOE OSTI2020

Spatial Atomic Layer Deposition to Scale Manufacturing of Robust Catalysts for Biomass Conversion Applications: Cooperative Research and Development Final Report, CRADA Number CRD-17-715

This CRADA will facilitate technology maturation for NREL-developed ALD-coated catalyst materials that are tailored for durability during harsh biomass conversion chemistries. This project will address optimizing process parameters for scale-up of Al2O3 ALD-coated catalysts, demonstrating ALD-coated catalyst performance for muconic acid hydrogenation, and validating economic models that project significant cost benefits for ALD-enhanced catalytic processes. This work will strengthen private-public partnerships in the area of advanced catalyst manufacturing for energy-related technology. Critical information will be collected to elevate the Technology Readiness Level and increase our competitiveness for cooperative R&D agreements and licensing. Success of this work will be crosscutting as it can facilitate advanced catalyst development for both renewable and conventional processes.

09 BIOMASS FUELS↗
DOE OSTI2022

Investigating Particle Size‐Dependent Redox Kinetics and Charge Distribution in Disordered Rocksalt Cathodes

Abstract Understanding how various redox activities evolve and distribute in disordered rocksalt oxides (DRX) can advance insights into manipulating materials properties for achieving stable, high‐energy batteries. Herein, the authors present how the reaction kinetics and spatial distribution of redox activities are governed by the particle size of DRX materials. The size‐dependent electrochemical performance is attributed to the distinct cationic and anionic reaction kinetics at different sizes, which can be tailored to achieve optimal capacity and stability. Overall, the local charged domains in DRX particles display random heterogeneity caused by the isotropic delithiation pathways. Owing to the kinetic limitation, the micron‐sized particles exhibit a holistic “core‐shell” charge distribution, whereas sub‐micron particles show more uniform redox reactions throughout the particles and ensembles. Sub‐micron DRX particles exhibit increasing anionic redox activities yet inferior cycling stability. In summary, engineering particle size can effectively modulate how cationic and anionic redox activities evolve and distribute in DRX materials.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Can classical DEM simultaneously capture compressibility and flowability of milled biomass?

Accurate prediction of the rheological behavior of biomass is essential for the design and operation of hoppers, feeders, and storage systems in biorefineries. This study examines whether the classical, coarse-grained discrete element method (DEM) formulation can simultaneously reproduce the compressibility and flowability of milled herbaceous biomass, using Miscanthus × giganteus as a representative material. The model represents particles as rigid spheres interacting through Hertz-Mindlin elastic-frictional contacts augmented with an area-dependent cohesion term. Laboratory cyclic compression and wedge-shaped hopper discharge experiments were used as calibration benchmarks. Although the model can independently reproduce each behavior by appropriately tuning particle Young's modulus E and cohesion energy density k, an extensive parametric investigation comprising more than 600 simulations reveals that the optimal parameter regions for compression and hopper flow are distinct and non-overlapping in (E, k) space. Surrogate surface analysis further shows that the corresponding objective-function valleys exhibit similar trends but are approximately parallel and spatially offset, precluding a unified calibration within the explored domain. Sensitivity analysis indicates that compressibility is governed predominantly by stiffness and cohesion, whereas the slope of the mass flow rate-opening relation in hopper discharge is primarily controlled by tangential friction. Extensions incorporating particle size distribution and clumped-sphere representations do not eliminate the incompatibility. These results systematically reveal, for the first time, the structural limitation of simplified DEM formulations in representing biomass rheological behavior, underscoring the necessity for models incorporating additional physical mechanisms, such as particle deformability or enhanced interlocking, to achieve unified predictive capability for biomass handling behavior.

09 BIOMASS FUELS↗
DOE OSTI2023

Rolling Horizon Based Temporal Decomposition for the Offline Pickup and Delivery Problem with Time Windows

The offline pickup and delivery problem with time windows (PDPTW) is a classical combinatorial optimization problem in the transportation community, which has proven to be very challenging computationally. Due to the complexity of the problem, practical problem instances can be solved only via heuristics, which trade-off solution quality for computational tractability. Among the various heuristics, a common strategy is problem decomposition, that is, the reduction of a large-scale problem into a collection of smaller sub-problems, with spatial and temporal decompositions being two natural approaches. While spatial decomposition has been successful in certain settings, effective temporal decomposition has been challenging due to the difficulty of stitching together the sub-problem solutions across the decomposition boundaries. In this work, we introduce a novel temporal decomposition scheme for solving a class of PDPTWs that have narrow time windows, for which it is able to provide both fast and high-quality solutions. We utilize techniques that have been popularized recently in the context of online dial-a-ride problems along with the general idea of rolling horizon optimization. To the best of our knowledge, this is the first attempt to solve offline PDPTWs using such an approach. To show the performance and scalability of our framework, we use the optimization of paratransit services as a motivating example. Due to the lack of benchmark solvers similar to ours (i.e., temporal decomposition with an online solver), we compare our results with an offline heuristic algorithm using Google OR-Tools. In smaller problem instances (with an average of 129 requests per instance), the baseline approach is as competitive as our framework. However, in larger problem instances (approximately 2,500 requests per instance), our framework is more scalable and can provide good solutions to problem instances of varying degrees of difficulty, while the baseline algorithm often fails to find a feasible solution within comparable compute times.

Kim, Youngseo↗
DOE OSTI2025

A tri-level distribution locational marginal price-based demand response framework

Here, in this paper, we propose a tri-level, nested, two-stage price-based demand response (PBDR) framework that considers distribution locational marginal price (DLMP) as DR enabler between load-serving entities (LSE), demand response providers (DRPs), and customers in the day-ahead distribution market. It enables LSE and customer interactions by using multiple DRPs, positioned in-between, and independently optimizes their objectives. The problem is formulated using linear power flow with approximated power losses and its application in DLMP as DR pricing. The tri-level problem is solved using a nested reformulation & decomposition (R&D) method and tested on the real Indian-108 bus distribution system under various dynamic pricings. Further, the temporal–spatial variations in DLMPs are assessed using fairness criteria. Numerical analyses demonstrate that DLMP applications can effectively improve economic efficiency, and transparency in DR programs valuation with a favorable fairness margin. The results show that DLMP as DR pricing signal induces (0-2) % variation in DLMP for DR participation up to 10 %. Further, it gives over 90 % fairness over temporal–spatial variation for all the customers.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Accelerating error correction in tomographic reconstruction

Abstract Spurred by recent advances in detector technology and X-ray optics, upgrades to scanning-probe-based tomographic imaging have led to an exponential growth in the amount and complexity of experimental data and have created a clear opportunity for tomographic imaging to approach single-atom sensitivity. The improved spatial resolution, however, is highly susceptible to systematic and random experimental errors, such as center of rotation drifts, which may lead to imaging artifacts and prevent reliable data extraction. Here, we present a model-based approach that simultaneously optimizes the reconstructed specimen and sinogram alignment as a single optimization problem for tomographic reconstruction with center of rotation error correction. Our algorithm utilizes an adaptive regularizer that is dynamically adjusted at each alternating iteration step. Furthermore, we describe its implementation in a software package targeting high-throughput workflows for execution on distributed-memory clusters. We demonstrate the performance of our solver on large-scale synthetic problems and show that it is robust to a wide range of noise and experimental drifts with near-ideal throughput.

Ali, Sajid (ORCID:0000000321864636)↗
DOE OSTI2025

Serpentine Magnet Designs for the Interaction Region of the Electron-Ion Collider (EIC)

The Electron-Ion Collider (EIC), hosted by Brookhaven National Laboratory, is designed to deliver a peak luminosity of 1 × 10 34 cm −2 sec −1 . The interaction region (IR) of the EIC imposes several constraints in terms of field quality, aperture, and spatial layout, which necessitates the development of several unique superconducting serpentine direct wind magnets. These magnets are constructed using either a single strand or a small-diameter 6-around-1 NbTi cable, presenting unique challenges for design and optimization. This paper introduces a new computational code specifically developed to streamline and integrate the design process for these magnets, enabling faster design iterations while addressing their complex requirements. Here, in this paper, we first introduce the code, which builds on established electromagnetic fundamentals. The code incorporates tools for optimizing winding patterns and for correcting magnetic multipoles; additionally, it interfaces with established magnet design software. We also present the design of several serpentine magnets for the EIC IR, demonstrating the code’s capability to deliver precise and efficient solutions. These designs highlight the code’s ability to accelerate the development cycle, ensuring the serpentine magnets meet the demanding specifications of the EIC project.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

Smart-DS: Synthetic Models for Advanced, Realistic Testing: Distribution Systems and Scenarios

The explosion of new ideas for distributed energy resources and advanced distribution grid algorithms faces a critical challenge: how can one effectively develop and evaluate these breakthrough technologies without an adequate set of power systems network, load, and resource data to test against? Today's open test systems, particularly for distribution systems, are tiny and incomplete; and though with enough effort, obtaining utility data under NDA can overcome scale challenges, the results can't be openly shared, preventing fair comparison. The Smart-DS project-led by NREL in partnership with MIT, Universidad Pontificia Comillas, CYME, and EDD-is working to overcome this gap by generating multiple large-scale, open, synthetic, distribution systems that are realistic but not real. These datasets go beyond a single medium voltage feeder (~1000 customers) to cover entire metropolitan areas and their surrounds with up to hundreds of feeders and millions of customers, complete with low voltage customer connections and high voltage sub-transmission. This scale allows adequate testing and analysis of not just local controls and advanced DERs, but also multiple substation interactions, optimized switching, full-scale distribution-OPF, and more. To accompany these datasets, the project is also building a rich set of scenario generation tools that can be used for distribution and transmission systems alike. This includes automated, spatially aware access to world-class, high-resolution solar, wind, and weather data: forward looking generation mixes: and highly configurable DER, load, climate, outage, control-scheme, and other scenarios. We will also highlight DiTTo, an exciting open-source, multi-way distribution dataset transformation tool for many-to-many format translation with scenario, merge/split, and many other manipulation capabilities.

DERs↗
DOE OSTI2023

MOOSE Optimization Module Overview: Application to Residual Stress Inversion in Nuclear Fuel Plates

Manufacturing methods, material selections and unique plate geometries used in low enriched uranium plate fuels for the High Performance Research Reactor (HPRR) have led to concerns about the residual stresses effect on bond strength of the fuel/cladding interfaces and overall fuel performance under irradiation. The current HPRR plate fuel test program performed residual stress calculations using the contour method with experimental displacement data obtained by incrementally cutting the plate fuel. In this work, we use a gradient based inverse optimization module developed within the MOOSE framework to estimate normal and shear residual stresses within the plate fuels using displacement data taken from a cut placed in the HPRR fuel plate. These results are verified against residual stress calculations obtained from the contour method. The inversion protocol used in this work utilizes two meshes to separately discretize the physics and parameter space. This allows a fine mesh to be used to fully resolve the physics and geometry of the forward problem. A coarser mesh is used to resolve the parameter space with spatially varying mesh density determined from a sensitivity analysis. The adaptive resolution of the parameter space essentially has the effect of regularization as it is designed to achieve the bias-variance tradeoff.

42 ENGINEERING↗
DOE OSTI2023

Fully Distributed Acoustic and Magnetic Field Monitoring Via a Single Fiber Line for Optimized Production of Unconventional Resource Plays

This is the final technical report for the Virginia Tech Center for Photonics Technology (VT-CPT) research project entitled “Fully Distributed Acoustic and Magnetic Field Monitoring Via a Single Fiber Line for Optimized Production of Unconventional Resource Plays”. In the the four-year effort, VT-CPT collaborated with the Departments of Mathmatics at VT and Sentek Instrument, LLC (Sentek) to develop a fiber-optic sensing system capable of real-time simultaneous distributed measurement of multiple subsurface, drilling, and production parameters. The ultra-sensitive fiber optic distributed acoustic sensing technology, picoDAS, developed by Sentek was integrated with a novel multi-material optical sensing fiber fabricated by CPT-VT to obtain distributed acoustic and magnetic field measurements with ultrahigh sensitivity and high spatial resolution. The sensing technology successfully developed and demonstrated under this research program is truly unique has application beyond subsurface imaging to include carbon storage and electrical grid monitoring, as well as healthcare and nuclear fusion. The project, sponsored by the Advanced Technology Program, began in 2019 and had the original goal of developing the next generation of harsh environment sensing systems. Exhaustive theoretical modeling was performed to optimize the multi-material optical fiber design. VT developed the processing techniques employed to successfully fabricate single mode fibers with metal cladding wires. Sensing fibers with nickel and Metglas cladding wires were fully characterized, inscribed with sensors, and fully integrated with the picoDAS system. Laboratory scale testing was performed to demonstrate performance upon exposure to lateral and transverse magnetic fields. Preliminary field trials were performed for prototype magnetic and acoustic sensing systems upon near surface deployment at VT. The distributed acoustic and magnetic field sensing system was advanced from a (Technology Readiness Level) TRL=2 to a TRL=5 via laboratory scale system validation in relevant environments. The truly one-of-its kind distributed magnetic and acoustic sensing system is expected to find immediate applications that require subsurface monitoring, to include carbon storage site monitoring, and has the potential to be a distributive technology in healthcare and electric grid markets. The technologies developed by Virginia Tech’s Center for Photonics Technology will support the mission of the National Energy Technology Laboratory (NETL) to drive innovation and deliver solutions for an environmentally sustainable and prosperous energy future by ensuring affordable, abundant, and reliable energy that drives a robust economy and national security. Technical accomplishments during the program are summarized briefly here and described in detail in the remainder of the report.

02 PETROLEUM↗
DOE OSTI2020

Fast Automatic Knot Placement Method for Accurate B-spline Curve Fitting

The choice of knot vector has immense influence on the resulting accuracy of a B-spline approximation of a curve. However, despite the significance of this problem and the various solutions that were proposed in the literature, optimizing the number and placement of knots remains a difficult task. This paper presents a novel method for the approximation of a curve by a B-spline of arbitrary order, which automatically determines a knot vector that achieves high approximation quality. Additionally, at the core of our approach is a feature function that characterizes the amount and spatial distribution of geometric details in the input curve by estimating its derivatives. Knots are then selected in such a way as to evenly distribute the feature contents across their intervals. A comparison to the state of the art for a wide variety of curves shows that our method is faster and achieves more accurate reconstruction results, while typically reducing the number of necessary knots.

97 MATHEMATICS AND COMPUTING↗