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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 577 records · Page 32
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Influence of regional nighttime atmospheric regimes on canopy turbulence and gradients at a closed and open forest in mountain-valley terrain

Stable stratification of the nocturnal lower boundary layer inhibits convective turbulence, such that turbulent vertical transfer of ecosystem carbon dioxide (CO 2 ), water vapor (H 2 O) and energy is driven by mechanically forced turbulence, either from frictional forces near the ground or top of a plant canopy, or from shear generated aloft. The significance of this last source of turbulence on canopy flow characteristics in a closed and open forest canopy is addressed in this paper. We present micrometeorological observations of the lower boundary layer and canopy air space collected on nearly 200 nights using a combination of atmospheric laser detection and ranging (lidar), eddy covariance (EC), and tower profiling instrumentation. Two AmeriFlux/Fluxnet sites in mountain-valley terrain in the Western U.S. are investigated: Wind River, a tall, dense conifer canopy, and Tonzi Ranch, a short, open oak canopy. On roughly 40% of nights lidar detected down-valley or downslope flows above the canopy at both sites. Nights with intermittent strong bursts of “top-down” forced turbulence were also observed above both canopies. The strongest of these bursts increased sub-canopy turbulence and reduced canopy virtual potential temperature (θv) gradient at Tonzi, but did not appear to change the flow characteristics within the dense Wind River canopy. At Tonzi we observed other times when high turbulence (via friction velocity, u*) was found just above the trees, yet CO2 and θv gradients remained large and suggested flow decoupling. These events were triggered by regional downslope flow. Lastly, a set of turbulence parameters is evaluated for estimating canopy turbulence mixing strength. The relationship between turbulence parameters and canopy θv gradients was found to be complex, although better agreement between the canopy θv gradient and turbulence was found for parameters based on the standard deviation of vertical velocity, or ratios of 3-D turbulence to mean flow, than for u*. These findings add evidence that the relationship between canopy turbulence, static stability, and canopy mixing is far from straightforward even within an open canopy.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Merging flux-variance with surface renewal methods in the roughness sublayer and the atmospheric surface layer

In this article, Two micrometeorological methods utilizing high-frequency sampled air temperature were tested against eddy covariance (EC) sensible heat flux (𝐻) measurements at three sites representing agricultural, agro-forestry, and forestry systems. The two methods cover conventional and newly proposed forms of the flux-variance (FV) and surface renewal (SR) schemes of differing complexities. The sites represent measurements in surface, roughness, and roughness to surface transitional layers. Regression analyzes against EC show that the most reliable FV and SR forms estimate 𝐻 with slopes within ±10% from unity and coefficient of determination 𝑅2 > 0.9 across all the three sites. The best performance of both FV and SR was found at the agricultural site with measurements well within the surface layer, while the worst was found for the tall forest with measurements within the roughness sublayer where its thickness needed to be additionally estimated. The main variable driving 𝐻 in FV is the temperature variance, whereas in SR, it is the geometry of ramp-like structures. Since these structures are also responsible for most of the temperature variance, a novel FV-SR approach emerging from combining the methods is proposed and evaluated against EC measurements and conventional FV and SR schemes. The proposed FV-SR approach requiring only a single fast response thermocouple is potentially independent of calibration and ameliorates some of the theoretical objections that arise when combining ramp statistics with similarity arguments. The combination of methods also provides new insights into the contribution of coherent structures to the temperature variance and its dependence on atmospheric stratification. Other potential utility of the new method is to include it in multi-tool assessments of surface energy fluxes, since a convergence or divergence of the results has a high diagnostic value.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Computational study of full-scale VHTR lower plenum for turbulent mixing assessment

Next-generation nuclear reactors are poised to efficiently provide reliable power at enhanced safety levels for many years to come. Among the fundamental designs for these reactors is the very-hightemperature reactor (VHTR), which employs helium as the primary coolant and has the potential of reaching elevated temperatures such that chemical processing (e.g., electrolysis for hydrogen production) is viable alongside traditional electricity generation. This and other next-generation reactors also represent a strategic bridge for ultimately transitioning from fossil fuel-dominated energy portfolios to one where renewable options abound. For the VHTR, the ultimate goal of constructing a new plant will be preceded by additional fundamental research aimed at generating trusted models for behavior prediction under normal and accident scenarios. This paper presents a detailed computational fluid dynamics simulation of the lower plenum, where hot coolant from the core mixes together in a turbulent fashion before traveling to power conversion equipment. Because the flow is expected to enter the lower plenum across a wide range of temperatures and velocities, concerns exist when the mixing is incomplete. The potential hot spots on cylindrical support pedestals and the uniformity of the main outlet are the primary metrics of interest in this study, along with flow velocities and temperatures at different locations within the lower plenum. Three locations are probed in detail and suggest a large range exists for approach velocities and temperatures. A large degree of stratification is also seen on the surfaces of the support pedestals, suggesting a facility should accommodate testing for such behavior. The characterizations presented provide the valuable data needed in order to design appropriate experimental testbeds, where scaled modeling can be carried out in a manner meaningful in predicting the full-scale behavior.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2018

Low pressure direct injection strategies effect on a small SI natural gas two-stroke engine’s energy distribution and emissions

This paper examines methods to simultaneously improve efficiency and reduce emissions from a 34 cc air-cooled two-stroke engine configured to operate on natural gas, using tuned intake plus exhaust resonators designed from Helmholtz resonance theory to promote effective scavenging. The engine was developed for novel application in a small, free piston engine for decentralized power generation. Operation occurred at wide-open-throttle at a speed of 5400 RPM for both port injection (PI) and low-pressure direct injection (LPDI). In both cases, the electronic ignition timing was adjusted for maximum brake torque, while the fuel was adjusted such that both rich and lean combustion were examined. The LPDI engine was then operated over a variety of engine speeds. An energy balance was completed for both PI and LPDI operation, which quantified all energy pathways, as engine operating regimes changed. Results showed that exhaust chemical energy (ECE) for LPDI was reduced significantly when compared to PI, mostly due to less fuel slip. The fuel slip rate ranged from 35 to 40% for PI operation while it was in the range of 6–20% for LPDI operation. However, mixture stratification with LPDI operation increased carbon monoxide emissions. The start-of-injection (SOI) was also examined, targeting a SOI to provide the highest trapping efficiency and most stable combustion. For LPDI operation, trapping efficiency, which is function of engine speed, showed significant effects on overall efficiency and fuel slip. Air volumetric efficiency increased due to the absence of gaseous fuel within the intake manifold. It was shown that, relative to PI, the overall engine indicated efficiency increased by 90% to a maximum indicated efficiency of 30% for LPDI operation with a SOI of 180 CAD BTDC.

42 ENGINEERING↗
DOE OSTI2019

Load response of a floating wind turbine to turbulent atmospheric flow

The two turbulence-generation models [Kaimal Spectrum Exponential Coherence (KSEC) and Mann] specified in the international standard for wind turbine design assume neutral atmospheric conditions and are based on statistical and spectral methods. Mainly due to the lack of physics, the flow fields simulated with these models ultimately differ in their underlying structure, especially in terms of the spatial coherence of longitudinal velocity perturbations. While this may not be critical for smaller wind turbine rotors, it becomes important when rotor sizes increase. Furthermore, it might be especially important in the context of floating technologies as they are more sensitive to large turbulent coherent structures. Previous work found that these differences between KSEC and Mann can propagate to loads predictions and thereby affect the design space of the entire wind turbine system. It is therefore crucial to determine in which ways these two models are underperforming. Up until now, validation of these models had only been done in the vertical direction because it is extremely difficult to obtain atmospheric turbulence measurements separated laterally, and sampled at heights relevant to wind energy. In this work, we address the lack of measurements by using high-fidelity, high-resolution simulation data as a reference. We perform hour-long, large-eddy simulations of turbulent velocity fields that are stability-dependent and contain three-dimensional coherent structures. These flow fields are then used to investigate which stochastic model is a better predictor of loads on a realistic spar-system floating offshore wind turbine, and to quantify how the assumption of neutral stratification propagates to short-term load estimates. Both stochastic turbulence models are found to overpredict fatigue loading in high-wind scenarios (in some cases, by more than 25%) and underpredict it when the wind speed is low (by as much as 20%). The KSEC model matches the high-fidelity flow fields more closely than Mann at high wind speeds, and the opposite is true at low wind speeds. Finally, turbine loading is found to be sensitive to atmospheric stability even when the turbulence intensity remains fairly constant. This sensitivity is most pronounced at low wind speeds, when fatigue load estimates on the spar system can differ by 40%.

17 WIND ENERGY↗
DOE OSTI2022

Performance evaluation of a wrapped around condenser for heat pump water heater applications

In this report, accurate performance evaluation of a wrapped-around condenser for heat pump water heaters (WHPWH) is critical since the COP of the system depends heavily on thermal stratification and condenser design. An analytical, quasi-steady state heat balance method has been developed to determine the optimal spacing between adjacent channels, tube diameter, tube shape, and total refrigerant charge amount for the condenser. The heat transfer rate is compared among three approaches: the refrigerant thermodynamic model, the condenser-wrap fin model, and the analytical natural convection model on the inside of the tank for the three regions based on the refrigerant phase (e.g., super-heated, saturated, or subcooled). The heat transfer rate was predicted by a combination of slug-plug and annular flow for a D-shaped helical tube. Experimental data were used as boundary conditions for validating the model. The rate of heat transfer based on tube shape and tank wall temperatures was compared by CFD analysis. Parametric analysis indicates a tradeoff between refrigerant mass, pressure drop, tube diameter, and tube length to maximize the heat transfer rate. The model suggests the saturated region length can be extended by 400%, and the condenser pressure drop can be reduced by 23% with an optimal spacing pattern.

42 ENGINEERING↗
DOE OSTI2022

Aerosols consistently suppress the convective boundary layer development

Aerosols with different vertical distribution and various optical properties induce diverse heating rates and thereby affecting convective boundary layer (CBL) development. Our results showed consistent CBL-suppression of aerosols during daytime with numerical experiments, in which aerosols were specified at different heights with synthesized single scattering albedo from 64 studies and asymmetry factor from 20 studies globally. Absorbing aerosols concentrated below but close to the CBL top had the strongest suppression effect on CBL development relative to that concentrated near surface or above CBL. Aerosol cooling effect by attenuating incident solar radiation and surface heat flux exceeded its warming effect by reheating the atmosphere layer with absorbed shortwave radiation, and eventually declined net heating rate, which inhibited CBL development, lowered mixed-layer potential temperature and stabilized atmospheric stratification. Stove effect of absorbing aerosols (CBL enhancement) under a zero background aerosol extinction coefficient is negligible for dominant dome effect (CBL suppression) which consistently suppresses CBL development regardless of aerosol vertical height and background aerosol extinction coefficient. Our study also highlighted the importance of specifying background aerosol extinction coefficient in numerical experiments for accurate assessment of aerosol radiative forcing and CBL-aerosol interactions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Dust-planetary boundary layer interactions amplified by entrainment and advections

Mineral dust contributes to more than half of the global aerosol loading. However, the radiative impacts of dust aerosols on planetary boundary layer (PBL) structure have not been explored sufficiently. During a typical dust storm event over Tarim Basin, dust aerosols exhibit a well-mixed distribution during the daytime in spite of a shallow layer of dust particles accumulated at higher altitudes. By contrast, nocturnal dust plumes are located near the surface due to stable stratification. We demonstrate that these differentiated vertical distributions determine the spatial heterogeneity of dust loading, radiative fluxes and PBL height variations. Dust aerosols cause daytime PBL suppression and nighttime PBL promotion through modulating surface and atmospheric radiative budgets. Specifically, dust-induced cooling effect within PBL directly inhibits the daytime PBL development. PBL suppression effect is then amplified by entrainment processes resulting in excessively low PBL height, especially for dust particles below but near the PBL top. Dust plumes weaken updrafts from PBL and downdrafts of the free atmosphere, which further reduce the entrainment mixing through attenuating horizontal and vertical advection, and eventually amplify PBL suppression. At night, near-surface dust aerosols stimulate a warm and unstable lower atmosphere, generate warm advection heating and promote the PBL development. Our study highlights the importance of specifying entrainment parameters and nighttime advection activities in quantifying the dust-PBL interactions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Exploring the impact of surface topography on Rayleigh-Bénard dry convection in the Pi cloud chamber using OpenFOAM: In cylindrical and rectangular geometries

The Pi convection-cloud chamber can generate steady-state turbulence in both rectangular and cylindrical shapes via Rayleigh-Bénard convection (RBC) by maintaining warm bottom and cold top surfaces. Although most experiments in the Pi chamber were conducted in cylindrical shapes, all previous Pi chamber simulations were conducted in a rectangular shape due to the limitations of those models to discretize a cylindrical domain when using the finite difference method therein. Here, we use OpenFOAM, an open-source finite-volume-based Computational Fluid Dynamics (CFD) software package, to conduct Large-Eddy Simulation (LES) of dry RBC in the Pi chamber at high Rayleigh numbers (10 8 to 10 9 ). Results show that large-scale circulation (LSC) direction varies in the chamber with a constant side wall temperature. Imposing a slight temperature imbalance at the side wall ranging from 0.1 to 0.7 degrees can lock the LSC, aligning better with Pi chamber observations, particularly at higher Rayleigh numbers. In addition, we examine the impact of surface topography on LSC and heat transfer in RBC systems within cylindrical and rectangular shapes under varying conditions. Results show that roughing top/bottom surfaces by adding bars of a few tens millimeters height can strengthen thermal plumes and enhance temperature fluctuations in the chamber. Furthermore, we observe that different bar height configurations lead to notable changes in LSC orientation and thermal stratification, highlighting the complex interactions between surface features and convection patterns. This finding highlights how surface topography and chamber geometry affect Rayleigh-Bénard convection, improving understanding of turbulent heat transfer and atmospheric boundary-layer processes. Direct Numerical Simulations (DNS) are also conducted to validate LES results. In conclusion, while LES effectively captures qualitative behaviors seen in DNS, it tends to underestimate velocity variances near walls, illustrating a trade-off between computational efficiency and accuracy.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Proteogenomic insights suggest druggable pathways in endometrial carcinoma

We characterized a prospective endometrial carcinoma (EC) cohort containing 138 tumors and 20 enriched normal tissues using 10 different omics platforms. Targeted quantitation of two peptides can predict antigen processing and presentation machinery activity, and may inform patient selection for immunotherapy. Association analysis between MYC activity and metformin treatment in both patients and cell lines suggests a potential role for metformin treatment in non-diabetic patients with elevated MYC activity. PIK3R1 in-frame indels are associated with elevated AKT phosphorylation and increased sensitivity to AKT inhibitors. CTNNB1 hotspot mutations are concentrated near phosphorylation sites mediating pS45-induced degradation of β-catenin, which may render Wnt-FZD antagonists ineffective. Deep learning accurately predicts EC subtypes and mutations from histopathology images, which may be useful for rapid diagnosis. Overall, this study identified molecular and imaging markers that can be further investigated to guide patient stratification for more precise treatment of EC.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Personalized and uncertainty-aware coronary hemodynamics simulations: From Bayesian estimation to improved multi-fidelity uncertainty quantification

Non-invasive simulations of coronary hemodynamics have improved clinical risk stratification and treatment outcomes for coronary artery disease, compared to relying on anatomical imaging alone. However, simulations typically use empirical approaches to distribute total coronary flow amongst the arteries in the coronary tree, which ignores patient variability, the presence of disease, and other clinical factors. Further, uncertainty in the clinical data often remains unaccounted for in the modeling pipeline. We present an end-to-end uncertainty-aware pipeline to (1) personalize coronary flow simulations by incorporating vessel-specific coronary flows as well as cardiac function; and (2) predict clinical and biomechanical quantities of interest with improved precision, while accounting for uncertainty in the clinical data. We assimilate patient-specific measurements of myocardial blood flow from clinical CT myocardial perfusion imaging to estimate branch-specific coronary artery flows. Simulated noise in the clinical data is used to estimate the joint posterior distributions of the model parameters using adaptive Markov Chain Monte Carlo sampling. Additionally, the posterior predictive distribution for the relevant quantities of interest is determined using a new approach combining multi-fidelity Monte Carlo estimation with non-linear, data-driven dimensionality reduction. This leads to improved correlations between high- and low-fidelity model outputs. Our framework accurately recapitulates clinically measured cardiac function as well as branch-specific coronary flows under measurement noise uncertainty. We observe substantial reductions in confidence intervals for estimated quantities of interest compared to single-fidelity Monte Carlo estimation and state-of-the-art multi-fidelity Monte Carlo methods. This holds especially true for quantities of interest that showed limited correlation between the low- and high-fidelity model predictions. In addition, the proposed multi-fidelity Monte Carlo estimators are significantly cheaper to compute than traditional estimators, under a specified confidence level or variance. The proposed pipeline for personalized and uncertainty-aware predictions of coronary hemodynamics is based on routine clinical measurements and recently developed techniques for CT myocardial perfusion imaging. The proposed pipeline offers significant improvements in precision and reduction in computational cost.

Bayesian parameter estimation↗
DOE OSTI2022

Influence of gasoline fuel formulation on lean autoignition in a mixed-mode-combustion (deflagration/autoignition) engine

We report stoichiometric spark-ignition engines suffer efficiency penalties due to throttling losses at low loads, a low specific-heat ratio of the stoichiometric working fluid, and limits on compression ratio due to end-gas autoignition leading to undesirable knocking. Mixed-Mode Combustion (MMC) mitigates these shortcomings by using a lean working fluid where a spark-initiated pilot-stabilized deflagrative flame front is followed by controlled end-gas autoignition. This MMC study investigates the effects of initial conditions (intake air temperature, intake pressure, equivalence ratio, and intake oxygen fraction) on autoignition tendency of four gasoline-range fuels with varying properties and composition. The use of fuels with varying octane sensitivity (S) allowed exploring the importance of low-temperature heat release in triggering autoignition. Fuels with high S were less reactive for conditions that promote low-temperature chemistry (operation at high intake air pressure or without N2 dilution). Conversely, an Alkylate fuel with low S showed a greater autoignition resistance at operating conditions that were unfavorable for low-temperature chemistry. Next, the effect of residual gas composition on autoignition tendency of fuels was examined with a chemical-kinetics model. Among the various molecules in the residual gas, nitric oxide (NO) enhanced the low-temperature chemistry and increased the autoignition tendency most significantly. The fuels’ autoignition response to increasing NO amount corroborates the experimental observations. Next, the sequential autoignition of the end-gas was assessed to be less impacted by thermal stratification because of lean mixtures showing relatively less low-temperature chemistry, when compared to stoichiometric mixtures. Next, the effect of changing equivalence ratio on the autoignition was found to be similar for all fuels, regardless of their S. With changing intake air temperature, the response of fuels’ autoignition tendency depended on the dilution level used. At high dilution (i.e. low intake [O2]), fuels’ reactivity increased with increasing intake air temperature. In contrast, for operation without dilution, the autoignition tendency of the low-S Alkylate fuel decreased with increasing intake air temperature, while that of high-S High Cycloalkane fuel still increased with increasing intake air temperature. In conclusion, conventional octane metrics (RON and MON) have utility in assessing the autoignition tendency under lean MMC operation. Moreover, the fuel requirements for MMC align with that of stoichiometric operation: i.e., high RON and high S fuels are desirable for stable non-knocking operation.

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

Impact of gasoline composition on the effects of nitric oxide on autoignition and knock in a DISI engine

Modern spark-ignition engines use exhaust gas recirculation (EGR) to dilute the charge and suppress knock, enabling the use of higher compression ratios and/or more optimum combustion phasing for higher efficiency. The effectiveness of EGR is affected by the composition of the fuel and its chemical-kinetic interactions with combustion products. Among those, nitric oxide (NO) has been shown to strongly affect autoignition reactivity. However, the impact of fuel composition of the effect of NO on reactivity is not well-understood. Here, in this study, engine experiments were conducted to assess the impact of NO seeded to the intake on knock-limited operation of two gasoline fuels (high cycloalkane content, or HCA, and high olefin content, or HO). Results showed that compositionally-different fuels responded differently to NO. HCA, which was less knock-limited than HO for NO < 200 ppm, became more knock-limited for NO > 200 ppm. Moreover, it was found that differences in knock between fuels were caused by differences in autoignition chemistry and not in the sequential autoignition process of the end gas that occurs due to thermal stratification. Chemical kinetic simulations were performed to better understand the experimental results. For HCA, intermediate-temperature heat release had a greater impact on autoignition reactivity than low-temperature heat release, while the opposite was observed for HO. For both fuels, NO enhances the magnitude of low-temperature heat release via NO + HO 2 → NO 2 + OH. The effect of NO on reactivity was stronger for HCA because OH produced from NO helped to overcome the OH quenching effect of cyclopentane, a main species in HCA. In contrast, HO had relatively strong inherent low-temperature chemistry arising from iso-octane, which reduced the impact of NO on reactivity. For the range of NO mole fractions tested in this study, in-cylinder NO increased fuel’s knock propensity, especially for fuels with mild low-temperature chemistry.

Autoignition↗
DOE OSTI2021

Characterizing Long COVID: Deep Phenotype of a Complex Condition

Background: Numerous publications describe the clinical manifestations of post-acute sequelae of SARS-CoV-2 (PASC or "long COVID"), but they are difficult to integrate because of heterogeneous methods and the lack of a standard for denoting the many phenotypic manifestations. Patient-led studies are of particular importance for understanding the natural history of COVID-19, but integration is hampered because they often use different terms to describe the same symptom or condition. This significant disparity in patient versus clinical characterization motivated the proposed ontological approach to specifying manifestations, which will improve capture and integration of future long COVID studies. Methods: The Human Phenotype Ontology (HPO) is a widely used standard for exchange and analysis of phenotypic abnormalities in human disease but has not yet been applied to the analysis of COVID-19. Funding: We identified 303 articles published before April 29, 2021, curated 59 relevant manuscripts that described clinical manifestations in 81 cohorts three weeks or more following acute COVID-19, and mapped 287 unique clinical findings to HPO terms. We present layperson synonyms and definitions that can be used to link patient self-report questionnaires to standard medical terminology. Long COVID clinical manifestations are not assessed consistently across studies, and most manifestations have been reported with a wide range of synonyms by different authors. Across at least 10 cohorts, authors reported 31 unique clinical features corresponding to HPO terms; the most commonly reported feature was Fatigue (median 45.1%) and the least commonly reported was Nausea (median 3.9%), but the reported percentages varied widely between studies. Interpretation: Translating long COVID manifestations into computable HPO terms will improve analysis, data capture, and classification of long COVID patients. If researchers, clinicians, and patients share a common language, then studies can be compared/pooled more effectively. Furthermore, mapping lay terminology to HPO will help patients assist clinicians and researchers in creating phenotypic characterizations that are computationally accessible, thereby improving the stratification, diagnosis, and treatment of long COVID.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Predicting lake surface water phosphorus dynamics using process-guided machine learning

Phosphorus (P) loading to lakes is degrading the quality and usability of water globally. Accurate predictions of lake P dynamics are needed to understand whole-ecosystem P budgets, as well as the consequences of changing lake P concentrations for water quality. However, complex biophysical processes within lakes, along with limited observational data, challenge our capacity to reproduce short-term lake dynamics needed for water quality predictions, as well as long-term dynamics needed to understand broad scale controls over lake P. Here we use an emerging paradigm in modeling, process-guided machine learning (PGML), to produce a phosphorus budget for Lake Mendota (Wisconsin, USA) and to accurately predict epilimnetic phosphorus over a time range of days to decades. In our implementation of PGML, which we term a Process-Guided Recurrent Neural Network (PGRNN), we combine a process-based model for lake P with a recurrent neural network, and then constrain the predictions with ecological principles. We test independently the process-based model, the recurrent neural network, and the PGRNN to evaluate the overall approach. The process-based model accounted for most of the observed pattern in lake P; however it missed the long-term trend in lake P and had the worst performance in predicting winter and summer P in surface waters. The root mean square error (RMSE) for the process-based model, the recurrent neural network, and the PGRNN was 33.0 μg P L -1 , 22.7 μg P L -1 , and 20.7 μg P L -1 , respectively. All models performed better during summer, with RMSE values for the three models (same order) equal to 14.3 μg P L -1 , 10.9 μg P L -1 , and 10.7 μg P L -1 . Although the PGRNN had only marginally better RMSE during summer, it had lower bias and reproduced long-term decreases in lake P missed by the other two models. For all seasons and all years, the recurrent neural network had better predictions than process alone, with root mean square error (RMSE) of 23.8 μg P L -1 and 28.0 μg P L -1 , respectively. The output of PGRNN indicated that new processes related to water temperature, thermal stratification, and long term changes in external loads are needed to improve the process model. By using ecological knowledge, as well as the information content of complex data, PGML shows promise as a technique for accurate prediction in messy, real-world ecological dynamics, while providing valuable information that can improve our understanding of process.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Explicit quantification of residence and flushing times in the Salish Sea using a sub-basin scale shoreline resolving model

The Salish Sea, located in the Pacific Northwest region of North America has complex currents and circulation features distributed over numerous interconnected deep basins with islands. Increased risk of exposure to oil spills and untreated wastewater from maritime emergencies and treatment plant failures have led to a need for quantifying residence and flushing characteristics at a sub-basin scale using a shoreline resolving hydrodynamic model. An unstructured grid model of the Salish Sea was developed using FVCOM with a ≈75-100m shoreline resolution. In addition to 7 tides and 23 salinity and temperature monitoring stations, an extensive currents data set from 135 stations collected over a span of three years was used for skill assessment and validation. Explicit forward computations were then conducted to define and quantify residence and flushing times in various sub-basins of interest using (a) Lagrangian particles and (b) Numerical/virtual dye experiments. The results in most basins show expected seasonal variability with longer flushing time associated with summer lower tides and lower freshwater inflows. However, contrary to expectation, flushing time is significantly longer in wintertime in large fjord-like basins such as Hood Canal (≈138 days), likely due to increased stratification and reduced mixing. The flushing time for the Puget Sound region of the Salish Sea is ≈115 days, while Georgia Basin is 240 days when analyzed as stand-alone basins with zero background concentrations. When examined as part of the flushing of the entire Puget Sound filled with virtual dye, the compounded flushing times for embedded sub-basins can be significantly longer in order of magnitudes and largely dictated by the flushing time of Puget Sound. The computed residence and flushing time scales tabulated over 36 sub-basins provide an improved understanding of water renewal in the system, informing pollution management actions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Gaseous fuels variation effects on first and second law analyses of a small direct injection engine for micro-CHP systems

This report examines the detailed energy and exergy distribution of a 34 cc (cc) air-cooled, two-stroke engine configured to operate on different natural gas (NG) compositions, pure methane, and propane. The engine was developed for application in a small, decentralized combined heat and power (CHP) system. It included optimized intake and exhaust resonators designed from Helmholtz resonance theory to promote effective scavenging. Operation occurred at wide-open-throttle (WOT) at an engine speed of 5400 revolutions per minute (RPM) with low-pressure direct injection (LPDI). Electronic ignition timing was adjusted for maximum brake torque (MBT) while the air-fuel ratio (AFR) was adjusted by injection duration, such that both rich and lean combustion were examined. In addition, start of injection (SOI) was adjusted to balance maximum fuel trapping and combustion stability. Full energy and exergy distribution analyses were completed, as engine operating regimes changed. Exergy was divided into work (available), lost (recoverable), and destructed availabilities. It was found that fuel loss and heat transfer contributed the most to exergy losses, accounting for around 15% and 9% of fuel exergy, respectively. Propane with the highest density, showed the highest in-cylinder trapped energy, heat transfer and, peak utilization factor (UF) of 85.3%. Due to fuel presence in the exhaust, lower 1st law efficiency did not necessarily result into a lower 2nd law efficiency. Higher mixture stratification with propane operation increased carbon monoxide (CO) emissions and hydrogen (H 2 ) content due to rich operation. CO oxidation could recover up to around 5% and 4% of injected fuel energy as heat for CHP system with propane and NG, respectively. Peak 2nd law efficiencies were around 60.5% while peak 1st law indicated efficiency was around 29%. This discrepancy was due to both exhaust hydrocarbon (HC from fuel slip and incomplete combustion) content, exhaust CO content, and heat loss availabilities.

03 NATURAL GAS↗