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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 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

The Impact of Crop Rotation and Spatially Varying Crop Parameters in the E3SM Land Model (ELMv2)

Abstract Earth System Models (ESMs) are increasingly representing agriculture due to its impact on biogeochemical cycles, local and regional climate, and fundamental importance for human society. Realistic large scale simulations may require spatially varying crop parameters that capture crop growth at various scales and among different cultivars, as well as common crop management practices, but their importance is uncertain, and they are often not represented in ESMs. In this study, we examine the impact of using constant versus spatially varying crop parameters using a novel, realistic crop rotation scenario in the Energy Exascale Earth System Model (E3SM) Land Model version 2 (ELMv2). We implemented crop rotation by using ELMv2's dynamic land unit capability, and then calibrated and validated the model against observations collected at three AmeriFlux sites in the US Midwest with corn soybean rotation. The calibrated model closely captured the magnitude and observed seasonality of carbon and energy fluxes across crops and sites. We performed regional simulations for the US Midwest using the calibrated model and found that spatially varying only a few crop parameters across the region, as opposed to using constant parameters, had a large impact, with the carbon fluxes and energy fluxes both varying by up to 40%. These results imply that large scale ESM simulations using spatially invariant crop parameters may result in biased energy and carbon fluxes estimation from agricultural land, and underline the importance of improving human‐earth systems interactions in ESMs.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Strategies for thorium fuel cycle transition in the SD-TMSR

Liquid-fueled Molten Salt Reactor (MSR) systems represent advances in safety, economics, and sustainability. The MSR has been designed to operate with a Th/ 233 U fuel cycle with 233 U used as startup fissile material. Since 233 U does not exist in nature, we must examine other available fissile materials to start up these reactor concepts. This work investigates the fuel cycle and neutronics performance of the Single-fluid Double-zone Thorium-based Molten Salt Reactor (SD-TMSR) with different fissile material loadings at startup: High Assay Low Enriched Uranium (HALEU) (19.79%), Pu mixed with HALEU (19.79%), reactor-grade Pu (a mixture of Pu isotopes chemically extracted from Pressurized Water Reactor (PWR) spent nuclear fuel (SNF) with 33 GW d/tHM burnup), transuranic elements (TRU) from Light Water Reactor (LWR) SNF, and 233 U. The MSR burnup routine provided by SERPENT-2 is used to simulate the online reprocessing and refueling in the SD-TMSR. The effective multiplication factor, fuel salt composition evolution, and net production of 233 U are studied in the present work. Additionally, the neutron spectrum shift during the reactor operation is calculated. The results show that the continuous flow of reactorgrade Pu helps transition to the thorium fuel cycle within a relatively short time (≈ 4.5 years) compared to 26 years for 233 U startup fuel. Finally, using TRU as the initial fuel materials offers the possibility of operating the SD-TMSR for an extended period of time (≈ 40 years) without any external feed of 233 U.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

Combined selection of the dynamic model and modeling error in nonlinear aeroelastic systems using Bayesian Inference

Here, we report a Bayesian framework for concurrent selection of physics-based models and (modeling) error models. We investigate the use of colored noise to capture the mismatch between the predictions of calibrated models and observational data that cannot be explained by measurement error alone within the context of Bayesian estimation for stochastic ordinary differential equations. Proposed models are characterized by the average data-fit, a measure of how well a model fits the measurements, and the model complexity measured using the Kullback–Leibler divergence. The use of a more complex error models increases the average data-fit but also increases the complexity of the combined model, possibly over-fitting the data. Bayesian model selection is used to find the optimal physical model as well as the optimal error model. The optimal model is defined using the evidence, where the average data-fit is balanced by the complexity of the model. The effect of colored noise process is illustrated using a nonlinear aeroelastic oscillator representing a rigid NACA0012 airfoil undergoing limit cycle oscillations due to complex fluid–structure interactions. Several quasi-steady and unsteady aerodynamic models are proposed with colored noise or white noise for the model error. The use of colored noise improves the predictive capabilities of simpler models.

42 ENGINEERING↗
DOE OSTI2026

A Vertical GaN-Based Neutral-Pointless Three-Level Inverter for High-Performance Automotive Traction Applications

Silicon Carbide (SiC) MOSFETs have emerged as a dominant solution for electric vehicle traction inverters because of their superior power density and efficiency compared to Silicon (Si) counterparts. However, SiC devices possess inherent switching speed limitations that constrain the maximum switching frequency and hinder further power density and efficiency improvements. To address these limitations, this paper proposes a vertical Gallium Nitride (vGaN) based X-type Neutral-Pointless (NPL.X) three-level (3L) inverter for an 800V, 200 kW traction system. Integrating 700V vGaN technology within the NPL.X 3L topology enables improved drive efficiency and higher switching frequencies, resulting in enhanced power density and output power quality. To evaluate the performance benefits, this work conducts a comprehensive loss characterization of the vGaN￾based NPL.X topology, providing a direct comparison with a SiC￾based two level (2L) inverter. The results show that the proposed vGaN-based inverter achieves superior efficiency, particularly within the low-torque regions that dominate standard automotive drive cycles. The proposed vGaN-based inverter represents a critical advancement toward high-power-density and high efficiency traction drives

Halawa, Ali [Purdue Univ., West Lafayette, IN (Uni↗
DOE OSTI2022

Evaluating Class 6 Delivery Truck Fuel Economy and Emissions Using Vehicle System Simulations for Conventional and Hybrid Powertrains and Co-Optima Fuel Blends

The US Department of Energy’s Co-Optimization of Engine and Fuels Initiative (Co-Optima) investigated how unique properties of bio-blendstocks considered within Co-Optima help address emissions challenges with mixing controlled compression ignition (i.e., conventional diesel combustion) and enable advanced compression ignition modes suitable for implementation in a diesel engine. Additionally, the potential synergies of these Co-Optima technologies in hybrid vehicle applications in the medium- and heavy-duty sector was also investigated. In this work, vehicles system were simulated using the Autonomie software tool for quantifying the benefits of Co-Optima engine technologies for medium-duty trucks. A Class 6 delivery truck with a 6.7 L diesel engine was used for simulations over representative real-world and certification drive cycles with four different powertrains to investigate fuel economy, criteria emissions, and performance. Comparisons were made between ultralow-sulfur diesel and a blend of 25% hexyl hexanoate with diesel. Model validation data were informed by 2019 model year Cummins ISB 6.7 L diesel engine maps and transient validation data in a pre-production hybrid configuration and a direct dyno coupled configuration with diesel fuel and a blend of 25% hexyl hexanoate with diesel.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2021

Contrasting characteristics of open- and closed-cellular stratocumulus cloud in the eastern North Atlantic

Abstract. Extensive regions of marine boundary layer cloud impact the radiative balance through their significant shortwave albedo while having little impact on outgoing longwave radiation. Despite this importance, these cloud systems remain poorly represented in large-scale models due to difficulty in representing the processes that drive their life cycle and coverage. In particular, the mesoscale organization and cellular structure of marine boundary clouds have important implications for the subsequent cloud feedbacks. In this study, we use long-term (2013–2018) observations from the Atmospheric Radiation Measurement (ARM) Facility's Eastern North Atlantic (ENA) site on Graciosa Island, Azores, Portugal, to identify cloud cases with open- or closed-cellular organization. More than 500 h of each organization type are identified. The ARM observations are combined with reanalysis and satellite products to quantify the cloud, precipitation, aerosol, thermodynamic, and large-scale synoptic characteristics associated with these cloud types. Our analysis shows that both cloud organization populations occur during similar sea surface temperature conditions, but the open-cell cases are distinguished by stronger cold-air advection and large-scale subsidence compared to the closed-cell cases, consistent with their formation during cold-air outbreaks. We also find that the open-cell cases were associated with deeper boundary layers, stronger low-level winds, and higher rain rates compared to their closed-cell counterparts. Finally, raindrops with diameters larger than 1 mm were routinely recorded at the surface during both populations, with a higher number of large drops during the open-cellular cases. The similarities and differences noted herein provide important insights into the environmental and cloud characteristics during varying marine boundary layer cloud mesoscale organization and will be useful for the evaluation of model simulations for ENA marine clouds.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Adiabatic and radiative cooling are both important causes of aerosol activation in simulated fog events in Europe

Aerosol–fog interactions affect the visibility in, and life cycle of, fog and are difficult to represent in weather and climate models. Here we explore processes that impact the simulation of fog droplet number concentrations (N d ) at sub-kilometer scale horizontal grid resolutions in the UK Met Office Unified Model. We modify the parameterization of aerosol activation to include droplet activation by radiative cooling in addition to adiabatic cooling and determine the relative importance of the two cooling mechanisms. We further test the sensitivity of simulated N d to: (a) interception of droplets by trees and buildings, (b) overestimation of updrafts in temperature inversions (which leads to artificially high N d values), and (c) potential mechanisms for droplet deactivation due to downward fluctuations in supersaturation. We evaluate our model against observations from the ParisFog and LANFEX field campaigns, building on evaluation described in the companion paper. Including radiative cooling in the activation mechanism improves how accurately we represent the liquid water path and the vertical structure of the fog in our LANFEX case study. However, with radiative cooling, the N d are overestimated for most of the ParisFog cases and for the LANFEX case. The time-averaged overestimate exceeds a factor of three (the normalized mean bias factor exceeds 2.0) in 4 out of 11 ParisFog cases. Our sensitivity studies demonstrate how these overestimates can be mitigated. Assuming the overestimate affects both radiative and adiabatic cooling, we find that although radiative cooling is more often the dominant source, both cooling sources can sometimes dominate activation.

Ghosh, Pratapaditya [Carnegie Mellon University, P↗
DOE OSTI2023

Reversible solid oxide cells: Early performance and microstructural evolution during electrolysis and switched mode operation

Incorporating more renewables into our energy mix will require a diversity of technological solutions. Reversible solid oxide cell systems (RSOCs) operating reversibly between fuel cell and electrolysis modes with high round-trip efficiencies offer one such solution. However, questions remain about the stability of the oxygen and fuel electrodes under reversible operation. Here, in this study, single cells with the configuration Ni-YSZ|YSZ|GDC10|NNO-NDC50|NNO are operated by reversible cycling under potentiostatic conditions. Test conditions are chosen to be representative of average stack conditions that are likely to be encountered during operation of a stack constructed of such cells. The results of reversible cycling over 500 h (21 cycles) are compared with operating the cells under potentiostatic conditions in the electrolysis-only mode (i.e., without cycling). Voltage-current density (DC), AC complex impedance spectroscopy, distribution of relaxation times (DRT) analysis, and scanning electron microscopy (SEM) indicate excellent reversibility and stability of the neodymium nickelate-based oxygen electrodes in both electrolysis and reversible cycling modes. Degradation behavior is attributed to the loss and coarsening of connected Ni particles in the fuel electrode, particularly in the active layer. However, reversible operation mitigates this degradation compared to operation in the electrolysis-only (SOEC-only) mode.

25 ENERGY STORAGE↗
DOE OSTI2023

Electrochemical Evolution of Fuel Cell Platinum Nanocatalysts on Carbon Nanotubes at the Atomic Scale

The evolution of Pt nanoparticles supported on carbon nanotubes is analyzed before and after electrochemical potential cycling, using identical location aberration-corrected transmission electron microscopy, for applications in proton exchange membrane fuel cells. The work is focused on the half-cell accelerated stress test protocol of potential cycles ranging between 1.0 and 1.5 V RHE to represent the start-up/shutdown settings of a fuel cell vehicle. The research work reveals that particle migration and coalescence are key mechanisms for a reduction in the Pt nanoparticle surface area at the early stages of potential cycling. Further, the mechanism for particle movement and coalescence is attributed to carbon corrosion, catalyzed either by Pt or by bulk corrosion of the carbon nanotubes. Carbon corrosion results in the appearance of carbon vacancies at the carbon nanotube/Pt nanoparticle interface during cycling, as well as the formation of edge and surface defects. During cycling, the concentration of the dissoluble Pt increases. As soon as a significant amount is reached, subnanometer/atomic clusters emerge on the carbon nanotube support, which can move and coalesce, or redeposit on the surface of larger particles through Ostwald ripening.

25 ENERGY STORAGE↗
DOE OSTI2026

Tracing U.S. fuel life-cycle greenhouse gas emissions in a multi-sector dynamics model using LC-GCAM

Model-based analysis of fuel pathways is essential for informing energy and environmental policy. Two major model types are typically used: multi-sector dynamics models, which capture the broader energy-economy, such as GCAM (Global Change Analysis Model), and life cycle assessment models, such as GREET (Greenhouse Gases, Regulated Emissions, and Energy Use in Transportation). Each has distinct strengths and limitations, and recent studies increasingly adopt hybrid approaches to harness the advantages of both. However, such integration is often time-consuming and complicated by inconsistencies in system boundaries and technology definitions. We present LC-GCAM, a new tool that enables estimation of life-cycle greenhouse gas emissions and primary energy use for any fuel pathway represented in GCAM. We apply LC-GCAM to 300 scenarios designed to explore key uncertainties affecting the life-cycle performance of future fuel options in the U.S. freight sector. To evaluate LC-GCAM, we compare its results with those from GREET for nine fuel types in a 2030 reference scenario. When input assumptions are modestly aligned, LC-GCAM and GREET estimates typically agree within 10% (absolute sum-based mean absolute percentage error). LC-GCAM offers a flexible and efficient approach to generating life-cycle metrics within an integrated modeling framework, supporting robust policy analysis across a wide range of interacting energy system uncertainties.

Wolfram, Paul↗
DOE OSTI2021

Deuterium transport and retention properties of representative fusion blanket structural materials

Reduced activation ferritic-martensitic (RAFM) steels have been developed for decades for use as fusion blanket structural materials, and have advantages in both mechanical properties and irradiation resistance following careful engineering of the microstructure. However, the hydrogen isotope behavior in these proposed fusion structural materials is not well understood, but is important to assess since it impacts the fusion reactor safety and self-sufficient tritium fuel cycle. Here, we investigated deuterium transport and retention in representative advanced RAFM steels, including castable nanostructured alloys (CNAs), and oxide-dispersion-strengthened (ODS) steels. A gas-driven permeation (GDP) system was used to measure the permeability, diffusivity and solubility of the studied materials, covering the temperature range from 623 K to 873 K, and the loading pressures from 1.8 x 10 4 to 1.0 x 10 5 Pa. The results indicated that the deuterium permeability has little material dependence. In contrast, the deuterium diffusivity of the studied materials showed significant variation. The deuterium diffusivity in ODS steels is one order of magnitude lower than that in RAFM steels and CNAs, and correspondingly, have an effective solubility that is 2–10 times larger than RAFM steels and CNAs. In addition, thermal desorption spectroscopy (TDS) measurements were performed to assess the deuterium retention and desorption of these materials following a static thermal deuterium charging at 723 Kfor 1 hour under the deuterium pressure of 1.0 x 10 5 Pa. It was found that ODS steels exhibit the highest deuterium retention and have broader desorption peaks. Microstructural features contributing to deuterium retention and impacting deuterium transport are discussed to rationalize the observed deuterium behavior in the studied RAFM steels.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Design, Modeling, and Control of a Hardware-in-the-Loop Testbed for Off-Road Vehicles

This paper presents the design, modeling, and control of a hardware-in-the-loop (HIL) testbed for off-road vehicles. The proposed HIL testbed employs a transient hydrostatic dynamometer to load a diesel engine to emulate any loading cycles of a wheel loader, which is a representative off-road vehicle. A fully validated wheel loader model is used to calculate the engine load, including both the drive and work functions. Besides, iterative learning control (ILC) has been designed for the loading torque tracking of the hydrostatic dynamometer to ensure accurate emulation of real-world operation scenarios. The developed HIL testbed is used to demonstrate more than 26% energy benefits of automated wheel loaders through systematic optimization compared with human-operated wheel loaders. As a result, this HIL testbed serves as a robust platform for advancing research and development across various off-road vehicles, including excavators, tractors, and harvesters.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2022

Active anaerobic methane oxidation and sulfur disproportionation in the deep terrestrial subsurface

Abstract Microbial life is widespread in the terrestrial subsurface and present down to several kilometers depth, but the energy sources that fuel metabolism in deep oligotrophic and anoxic environments remain unclear. In the deep crystalline bedrock of the Fennoscandian Shield at Olkiluoto, Finland, opposing gradients of abiotic methane and ancient seawater-derived sulfate create a terrestrial sulfate-methane transition zone (SMTZ). We used chemical and isotopic data coupled to genome-resolved metaproteogenomics to demonstrate active life and, for the first time, provide direct evidence of active anaerobic oxidation of methane (AOM) in a deep terrestrial bedrock. Proteins from Methanoperedens (formerly ANME-2d) are readily identifiable despite the low abundance (≤1%) of this genus and confirm the occurrence of AOM. This finding is supported by 13C-depleted dissolved inorganic carbon. Proteins from Desulfocapsaceae and Desulfurivibrionaceae, in addition to 34S-enriched sulfate, suggest that these organisms use inorganic sulfur compounds as both electron donor and acceptor. Zerovalent sulfur in the groundwater may derive from abiotic rock interactions, or from a non-obligate syntrophy with Methanoperedens, potentially linking methane and sulfur cycles in Olkiluoto groundwater. Finally, putative episymbionts from the candidate phyla radiation (CPR) and DPANN archaea represented a significant diversity in the groundwater (26/84 genomes) with roles in sulfur and carbon cycling. Our results highlight AOM and sulfur disproportionation as active metabolisms and show that methane and sulfur fuel microbial activity in the deep terrestrial subsurface.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Defining the Sphagnum Core Microbiome across the North American Continent Reveals a Central Role for Diazotrophic Methanotrophs in the Nitrogen and Carbon Cycles of Boreal Peatland Ecosystems

Peat mosses of the genus Sphagnum are ecosystem engineers that frequently predominate over photosynthetic production in boreal peatlands. Sphagnum spp. host diverse microbial communities capable of nitrogen fixation (diazotrophy) and methane oxidation (methanotrophy), thereby potentially supporting plant growth under severely nutrient-limited conditions. Moreover, diazotrophic methanotrophs represent a possible “missing link” between the carbon and nitrogen cycles, but the functional contributions of the Sphagnum-associated microbiome remain in question. A combination of metagenomics, metatranscriptomics, and dual-isotope incorporation assays was applied to investigate Sphagnum microbiome community composition across the North American continent and provide empirical evidence for diazotrophic methanotrophy in Sphagnum-dominated ecosystems. Remarkably consistent prokaryotic communities were detected in over 250 Sphagnum SSU rRNA libraries from peatlands across the United States (5 states, 17 bog/fen sites, 18 Sphagnum species), with 12 genera of the core microbiome comprising 60% of the relative microbial abundance. Additionally, nitrogenase (nifH) and SSU rRNA gene amplicon analysis revealed that nitrogen-fixing populations made up nearly 15% of the prokaryotic communities, predominated by Nostocales cyanobacteria and Rhizobiales methanotrophs. While cyanobacteria comprised the vast majority (>95%) of diazotrophs detected in amplicon and metagenome analyses, obligate methanotrophs of the genus Methyloferula (order Rhizobiales) accounted for one-quarter of transcribed nifH genes. Furthermore, in dual-isotope tracer experiments, members of the Rhizobiales showed substantial incorporation of 13 CH 4 and 15 N 2 isotopes into their rRNA. Our study characterizes the core Sphagnum microbiome across large spatial scales and indicates that diazotrophic methanotrophs, here defined as obligate methanotrophs of the rare biosphere (Methyloferula spp. of the Rhizobiales) that also carry out diazotrophy, play a keystone role in coupling of the carbon and nitrogen cycles in nutrient-poor peatlands.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Comprehensive framework for assessing and optimizing existing research networks

Conservation, monitoring, and research networks, or collections of ecological research sites unified under a common mission of data collection or a research mission, are essential infrastructure for understanding large landscapes. However, most networks developed opportunistically over decades rather than through systematic design, creating potential limitations in the ability to address conservation challenges across entire regions. We developed a framework to evaluate how well an existing research network represents the environmental conditions its members study and devised an approach to rank sites of priority for strategic expansion. Our approach measures performance through environmental representativeness, geographic coverage, and adequacy for scientific inference and thus optimizes limited monitoring resources to maximize scientific impact. We demonstrated this approach with the U.S. Department of Agriculture (USDA) Forest Service Experimental Forests and Ranges Network (EFRN), a 79‐site network across the United States that grew opportunistically over a century. At the national scale, the network effectively captured high‐biomass forests important for carbon cycle research; 82% of forest biomass was in well‐represented areas. Some areas in Texas, Florida, the Rocky Mountains, and the West Coast had no relevant EFRN sites, which limits the ability to make regional inferences. A fundamental challenge for the EFRN was that sites improving regional extent coverage sometimes provided minimal national benefits, which can create conflicts between local and global priorities. Adding the highest‐ranked candidate site provided a relevant site for 17% of currently poorly represented 1‐km pixel cells nationally, but regional and national site rankings varied considerably due to nested spatial inference. This framework provides quantitative tools for strategic infrastructure decision‐making, ensures that limited monitoring resources maximize conservation impact, and can be applied broadly to address the widespread challenge of optimizing conservation and monitoring networks worldwide.

additional site↗
DOE OSTI2021

High foliar K and P resorption efficiencies in old-growth tropical forests growing on nutrient-poor soils

Resorption is the active withdrawal of nutrients before leaf abscission. This mechanism represents an important strategy to maintain efficient nutrient cycling; however, resorption is poorly characterized in old-growth tropical forests growing in nutrientpoor soils. We investigated nutrient resorption from leaves in 39 tree species in two tropical forests on the Guiana Shield, French Guiana, to investigate whether resorption efficiencies varied with soil nutrient, seasonality, and species traits. The stocks of P in leaves, litter, and soil were low at both sites, indicating potential P limitation of the forests. Accordingly, mean resorption efficiencies were higher for P (35.9%) and potassium (K; 44.6%) than for nitrogen (N; 10.3%). K resorption was higher in the wet (70.2%) than in the dry (41.7%) season. P resorption increased slightly with decreasing total soil P; and N and P resorptions were positively related to their foliar concentrations. We conclude that nutrient resorption is a key plant nutrition strategy in these old-growth tropical forests, that trees with high foliar nutrient concentration reabsorb more nutrient, and that nutrients resorption in leaves, except P, are quite decoupled from nutrients in the soil. Seasonality and biochemical limitation played a role in the resorption of nutrients in leaves, but species-specific requirements obscured general tendencies at stand and ecosystem level.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Characterizing Peatland Microtopography Using Gradient and Microform-Based Approaches

Abstract Peatlands represent an important component of the global carbon cycle, storing 180–621 Gt of carbon (C). Small-scale spatial variations in elevation, frequently referred to as microtopography, influence ecological processes associated with the peatland C cycle, including Sphagnum photosynthesis and methane flux. Microtopography can be characterized with measures of topographic variability and by using conceptual classes (microforms) linked to function: most commonly hummocks and hollows. However, the criteria used to define these conceptual classes are often poorly described, if at all, and vary between studies. Such inconsistencies compel development of explicit quantitative methods to classify microforms. Furthermore, gradient-based characterizations that describe spatial variability without the use of microforms are lacking in the literature. Therefore, the objectives of this study were to (1) calculate peatland microtopographical elevation gradients and measures of spatial variability, (2) develop three microform classification methods intended for specific purposes, and (3) evaluate and contrast classification methods. Our results suggest that at spatial scales much larger than microforms, elevation distributions are unimodal and are well approximated with parametric probability density functions. Results from classifications were variable between methods and years and exhibited significant differences in mean hollow areal coverages of a raised ombrotrophic bog. Our results suggest that the conceptualization and classification of microforms can significantly influence microtopographic structural metrics. The three explicit methods for microform classification described here may be used and built upon for future applications.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

A multi-dimensional dataset for two-phase instability in low pressure natural circulation based on direct transient local measurement

Thermal hydraulic instability can challenge the control and the safety of nuclear reactors. This experimental research captures and investigates the instability in a low-pressure (1–10 atmospheres) natural circulation loop with an adiabatic chimney installed above the heated section. Direct transient local measurement of two-phase flow is performed at multiple axial locations along the flow channel with thermocouples and conductivity probes traversed by customized high-precision mechanisms. Based on the periodicity of oscillations, a post-processing method is proposed to align the data captured non-simultaneously to reconstruct the instability behavior in one representative period. The averaging operation over multiple oscillation cycles is performed to reduce the random errors. Cyclic phenomena are clearly demonstrated by the post-processed data, and rapid void fraction change induced by the flashing is observed to be significant in the driving mechanism for low pressure oscillations. Parametric effects of inlet subcooling, heat flux, inlet flow restriction and system pressure are studied within the experiment range, and qualitative results are explained and compared with existing literature. The ratio between the oscillation period and the travelling time of the fluid particle through the test section is compared with the theoretical value for the density wave oscillation. The new dataset contains directly measured transient multi-dimensional two-phase data along the flow channel for natural circulation under density wave oscillations. The generated dataset is valuable for the validation of system analysis codes and CFD codes in the simulation of natural circulation phenomena and dynamic two-phase flow.

42 ENGINEERING↗