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Results for “Flow Improvers”

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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Results from an improved flowing liquid lithium limiter with increased flow uniformity in high power plasmas in EAST

Significant engineering and physic progress was made by the upgrade of a flowing liquid lithium limiter (FLiLi) inserted into EAST H-mode discharges in 2016. The progress includes an improvement of liquid Li coverage uniformity, no macroscopic surface erosion by plasma materials interaction, effective removal of 55% of the discharge heat flux using high pressure He cooling during ohmic discharges, and the demonstrated ability to restart Li flow for a second experiment performed a week after the first. With increasing Li flow rate, fuel particle recycling and Fe impurity radiation gradually decreased, and plasma performance slightly improved, but there was no impact on the edge tungsten influx. No obvious Li bursts appeared during operation with up to about 4.5 MW auxiliary heating power with peak heat flux reaching ~4 MW m –2 on FLiLi. In addition, a gradual mitigation of edge localized mode (ELM) activity was observed with FLiLi operation. Lastly, short-lived ELM-free phases were observed for the first time in EAST during FLiLi insertion, with increasing τ E and transient H 98(y, 2) < 2.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2019

Joint Chance Constraints in AC Optimal Power Flow: Improving Bounds through Learning

This paper considers distribution systems with a high penetration of distributed, renewable generation and addresses the problem of incorporating the associated uncertainty into the optimal operation of these networks. Joint chance constraints, which satisfy multiple constraints simultaneously with a prescribed probability, are one way to incorporate uncertainty across sets of constraints, leading to a chance-constrained optimal power flow problem. Departing from the computationally-heavy scenario-based approaches or approximations that transform the joint constraint into conservative deterministic constraints, this paper develops a scalable, data-driven approach which learns operational trends in a power network, eliminates zero-probability events (e.g., inactive constraints), and accurately and efficiently approximates bounds on the joint chance constraint iteratively. In particular, the proposed framework improves upon the classic methods based on the union bound (or Boole's inequality) by generating a much less conservative set of single chance constraints that also guarantees the satisfaction of the original joint constraint. The proposed framework is evaluated numerically using the IEEE 37-node test feeder, focusing on the problem of voltage regulation in distribution grids.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2016

CRADA: Improved H2/Br2 Flow Batteries

This CRADA is established to jointly develop H2/Br2 flow batteries with improved materials sets and understanding between TVN Systems and LBNL. The focus of the activities is the testing and optimization of flow battery components to meet efficiency and power requirements. The proposed work is essentially all experimental where TVN Systems will use their knowledge and expertise in membrane-electrode-assembly (MEA) design and fabrication using novel catalyst and membrane materials and LBNL will use their existing knowledge and expertise in flow-battery cell assembly and testing for performance and durability.

25 ENERGY STORAGE↗
DOE OSTI2023

Uniform-in-phase-space data selection with iterative normalizing flows

Improvements in computational and experimental capabilities are rapidly increasing the amount of scientific data that are routinely generated. In applications that are constrained by memory and computational intensity, excessively large datasets may hinder scientific discovery, making data reduction a critical component of data-driven methods. Datasets are growing in two directions: the number of data points and their dimensionality. Whereas dimension reduction typically aims at describing each data sample on lower-dimensional space, the focus here is on reducing the number of data points. A strategy is proposed to select data points such that they uniformly span the phase-space of the data. The algorithm proposed relies on estimating the probability map of the data and using it to construct an acceptance probability. An iterative method is used to accurately estimate the probability of the rare data points when only a small subset of the dataset is used to construct the probability map. Instead of binning the phase-space to estimate the probability map, its functional form is approximated with a normalizing flow. Therefore, the method naturally extends to high-dimensional datasets. The proposed framework is demonstrated as a viable pathway to enable data-efficient machine learning when abundant data are available.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Hierarchical Optimal Power Flow with Improved Gradient Evaluation

Existing algorithms to solve alternating-current optimal power flow (AC-OPF) often exploit linear approximations to simplify system models and accelerate computations. In this paper, we improve a recent hierarchical OPF algorithm, which rested on primal-dual gradients evaluated in a linearized distribution power flow model. Specifically, we identify a risk of voltage violation arising from the model linearization, and propose a more accurate gradient evaluation method to eliminate that risk. We further develop a hierarchical primal-dual algorithm to solve OPF based on the proposed gradient evaluation method. Numerical results on IEEE networks show that our algorithm can enhance voltage safety with satisfactory computational efficiency.

distributed algorithm↗
DOE OSTI2019

Modeling Continuous-Flow Reactor Improvements over Batch Reactions for Enzyme Catalyzed Microsphere Surface Reactions

Our research objective was to study enzymatic reactions occurring on microsphere surfaces. Specifically, our work involved enzymatic polymerization reactions (chain lengthening) taking place both in batch and in a continuous flow reactor. My research involved creating simulations using COMSOL Multiphysics 5.4a to further study variable interactions within the continuous flow reactor. Our goal was to use suitable software to create a simulation platform suite that could be used for advanced research studies of continuous flow enzymatic surfaces reactions. In addition, we studied various characteristics of our present enzymatic polymerization reactor assembly, modeled inlet species flow (Species M) and estimated outlet species production (Species P). Our simulations spanned three levels of detail: Single-Bead, Packed-Bead Cell and Full Reactor Column. Furthermore, the Packed-Bead Cells were studied using three possible regular arrangement of solid spheres: Face-Centered Cubic (FCC), Hexagonal Close Packed (HCP) and Cubic Close Packed (CCP).

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

A Comparative Study of Compressive Effects on the Morphology and Performance of Carbon Paper and Cloth Electrodes in Redox Flow Batteries

Compressing porous carbon electrodes is a common approach to improve flow battery performance, but the resulting impact on electrode structure, fluid dynamics, and cell performance is not well understood. Herein, microtomographic imaging, load cell testing, and flow cell diagnostics are employed to characterize how compression‐induced changes impact pressure drop, polarization, and mass‐transfer scaling. Five different compressions are tested, spanning ranges typically used in literature, for AvCarb 1071 cloth (0%, 9%, 20%, 25%, 32%) and Freudenberg H23 paper (0%, 8%, 12%, 17%, 22%). It is found that the two electrode structures have distinct responses to compression, resulting in differing optimal conditions identified for each material; specifically, the Freudenberg H23 exhibits lower combined ohmic, charge‐transfer, and mass‐transport values at 8% compression, resulting in improved electrochemical performance across all compressive values, as compared to the optimal AvCarb 1071 compression (20%). Overall, Freudenberg H23 exhibits a greater sensitivity to compression with peak electrochemical activity correlating with increased permeability, whereas AvCarb 1071 is insensitive to compressive loads but produces lower electrochemical performance. Herein, the trade‐offs of mechanical robustness on fluid‐dynamic and electrochemical performance between the two electrodes are demonstrated by the aforementioned findings, suggesting each could be used for specific operating environments.

25 ENERGY STORAGE↗
DOE OSTI2026

Design of a SiC-Si moving packed-bed particle-to-sCO 2 heat exchanger for high temperature concentrating solar power applications

Particle-based concentrating solar power systems integrated with sCO 2 power cycles offer high thermal efficiencies but require durable heat exchangers to transfer heat from high-temperature particles to the sCO 2 working fluid. Here, this study presents the design and optimization of a silicon carbide-silicon moving packed-bed heat exchanger for fabrication via binder jetting additive manufacturing. The heat exchanger was designed to withstand a 20 MPa sCO 2 pressure and operate at particle inlet temperatures up to 750 °C. The final design features 152 sCO 2 channels distributed across 19 plates, with elliptical corners and a minimum wall thickness of 3 mm. Flow restrictors at the sCO 2 channel inlets significantly improved flow uniformity, reducing thermal stresses and achieving a structural reliability of 99 % under representative operating conditions. The heat exchanger delivers a thermal duty of 9 kW and a volumetric power density of approximately 1 MW/m 3 in the channel region. Sensitivity studies confirmed the heat exchanger’s robustness under varying operating conditions, demonstrating its viability as a high-performance alternative to metallic heat exchangers for particle-based high-temperature concentrating solar power applications.

Barua, Bipul [Argonne National Laboratory (ANL), A↗
DOE OSTI2017

Evaluation of single and multiple Doppler lidar techniques to measure complex flow during the XPIA field campaign

Abstract. Accurate three-dimensional information of wind flow fields can be an important tool in not only visualizing complex flow but also understanding the underlying physical processes and improving flow modeling. However, a thorough analysis of the measurement uncertainties is required to properly interpret results. The XPIA (eXperimental Planetary boundary layer Instrumentation Assessment) field campaign conducted at the Boulder Atmospheric Observatory (BAO) in Erie, CO, from 2 March to 31 May 2015 brought together a large suite of in situ and remote sensing measurement platforms to evaluate complex flow measurement strategies. In this paper, measurement uncertainties for different single and multi-Doppler strategies using simple scan geometries (conical, vertical plane and staring) are investigated. The tradeoffs (such as time–space resolution vs. spatial coverage) among the different measurement techniques are evaluated using co-located measurements made near the BAO tower. Sensitivity of the single-/multi-Doppler measurement uncertainties to averaging period are investigated using the sonic anemometers installed on the BAO tower as the standard reference. Finally, the radiometer measurements are used to partition the measurement periods as a function of atmospheric stability to determine their effect on measurement uncertainty. It was found that with an increase in spatial coverage and measurement complexity, the uncertainty in the wind measurement also increased. For multi-Doppler techniques, the increase in uncertainty for temporally uncoordinated measurements is possibly due to requiring additional assumptions of stationarity along with horizontal homogeneity and less representative line-of-sight velocity statistics. It was also found that wind speed measurement uncertainty was lower during stable conditions compared to unstable conditions.

17 WIND ENERGY↗
DOE OSTI2019

Tatsuno Coriolis Flow Meter Development Testing in High Pressure Hydrogen: Cooperative Research and Development Final Report

This project will provide test data on the new Tatsuno coriolis flow meter. This flow meter has been developed by Tatsuno for the purpose of achieving improved flow meter performance for 70 mega pascal (MPA) hydrogen dispensing. Testing will be conducted at the National Renewable Laboratory (NREL) Hydrogen Infrastructure Testing and Research Facility (HITRF) facility utilizing the hydrogen flow meter benchmark testing apparatus. The benchmarking apparatus utilizes a gravimetric method for measuring flow for direct comparison with flow meter output. Using the NREL meter benchmarking apparatus will allow direct comparison with data taken on previous versions of the Tatsuno coriolis flow meter product. Flow meter accuracy at 70 MPA hydrogen dispensers is an issue that has generated a lot of effort by both standards organizations and the station providers.

33 ADVANCED PROPULSION SYSTEMS↗