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DOE OSTI2015

Collaborative project. Ocean-atmosphere interaction from meso-to planetary-scale. Mechanisms, parameterization, and variability

This project aims to improve long term global climate simulations by resolving ocean mesoscale activity and the corresponding response in the atmosphere. The main computational objectives are; i) to perform and assess Community Earth System Model (CESM) simulations with the new Community Atmospheric Model (CAM) spectral element dynamical core; ii) use static mesh refinement to focus on oceanic fronts; iii) develop a new Earth System Modeling tool to investigate the atmospheric response to fronts by selectively filtering surface flux fields in the CESM coupler. The climate research objectives are 1) to improve the coupling of ocean fronts and the atmospheric boundary layer via investigations of dependency on model resolution and stability functions: 2) to understand and simulate the ensuing tropospheric response that has recently been documented in observations: and 3) to investigate the relationship of ocean frontal variability to low frequency climate variability and the accompanying storm tracks and extremes in high resolution simulations. This is a collaborative multi-institution project consisting of computational scientists, climate scientists and climate model developers. It specifically aims at DOE objectives of advancing simulation and predictive capability of climate models through improvements in resolution and physical process representation.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2017

Intraseasonal to interannual variability of Kelvin wave momentum fluxes as derived from high-resolution radiosonde data

Abstract. Observational estimates of Kelvin wave momentum fluxes in the tropical lower stratosphere remain challenging. Here we extend a method based on linear wave theory to estimate daily time series of these momentum fluxes from high-resolution radiosonde data. Daily time series are produced for sounding sites operated by the US Department of Energy (DOE) and from the recent Dynamics of the Madden–Julian Oscillation (DYNAMO) field campaign. Our momentum flux estimates are found to be robust to different data sources and processing and in quantitative agreement with estimates from prior studies. Testing the sensitivity to vertical resolution, our estimated momentum fluxes are found to be most sensitive to vertical resolution greater than 1 km, largely due to overestimation of the vertical wavelength. Climatological analysis is performed over a selected 11-year span of data from DOE Atmospheric Radiation Measurement (ARM) radiosonde sites. Analyses of this 11-year span of data reveal the expected seasonal cycle of momentum flux maxima in boreal winter and minima in boreal summer, and variability associated with the quasi-biennial oscillation of maxima during easterly phase and minima during westerly phase. Comparison between periods with active convection that is either strongly or weakly associated with the Madden–Julian Oscillation (MJO) suggests that the MJO provides a nontrivial increase in the lowermost stratospheric momentum fluxes.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2016

Modelling individual variability in growth of bull trout in the Walla Walla River Basin using a hierarchical von Bertalanffy growth model

Abstract We examined growth in length of fluvial bull trout ( Salvelinus confluentus ) in the Walla Walla River Basin, Washington and Oregon. Our objectives were to quantify individual variability in growth; examine growth within and among years, life history forms, life stages and sexes; and estimate von Bertalanffy growth parameters. Individual variability was evaluated by modelling asymptotic length ( L ∞ ) and the growth coefficient ( k ) as random variables. All models were fit with Bayesian methods and were evaluated for fit by the deviance information criterion. By incorporating individual variability, population‐level estimates of L ∞ and k appeared appropriate and estimated growth trajectories for specific bull trout fit individual observed patterns in growth. Growth trajectories and positive correlation between individual estimates of L ∞ and k suggest that some individuals grow at a faster rate and reach a larger maximum size than other individuals and those differences are maintained throughout life. Selected models suggest that fluvial migrants have higher estimates of L ∞ and k than residents, but there were only slight differences in parameter estimates among migrants from two adjacent spawning populations in the Walla Walla River Basin, as well as between males and females. Growth rates increased for fluvial migrants after subadult emigration. Individual variability in growth is consistent with the life history diversity assumed essential for bull trout population persistence. Quantifying this variability is important for modelling population dynamics and viability to conserve this threatened species.

Harris, Julianne E.↗

DOE OSTI2024

gcm_eval (Global Climate Model Evaluation) [SWR-24-37]

The interplay between energy, climate, and weather is becoming more complex as our changing climate continues to affect the weather we experience which in turn drives changes in the ever increasing share of renewable energy generation and energy demand. Energy system analyses commonly rely on meteorological inputs to estimate renewable energy generation and energy demand; however, these inputs rarely represent the estimated impacts of future climate change. Climate models and publicly available climate change datasets can be used for this purpose, but the selection of inputs from the myriad of available models and datasets is a nuanced and often subjective process. There is no single perfect climate model or dataset for all applications. In this repository, we include software and the corresponding assessments of various global climate models (GCMs) from the Coupled Model Intercomparison Project (CMIP6), evaluating their skills with respect to the historical climate and comparing of their future projections of climate change. We focus on variables that directly affect the energy system including the representation of extreme values that can drive grid resilience events. The objective of this repository is not to recommend the best climate model and dataset for a given analysis, but instead to provide a reference to facilitate the selection of climate models and datasets in subsequent work.

Buster, Grant↗

DOE OSTI2022

Effective properties of semitransparent radiative cooling materials with spectrally variable properties

Radiative cooling is a promising solid-state, non-vapor-compression technology for passive refrigeration and air conditioning. Although this phenomenon occurs naturally, achieving a significant amount of cooling to make it a technically and economically viable technology requires highly engineered, spectrally selective radiative surfaces. These characteristics make radiative cooling difficult to estimate, particularly when it is integrated with other systems such as photovoltaic panels or building envelopes. The complexity further increases when the substrate also participates in the radiative cooling (along with the radiative coating). Energy estimation is becoming increasingly critical because of the recent focus on the semitransparent radiative coatings that transmit a variety of colors to enhance the aesthetic appeal of the system. In this work, we propose an iterative method to calculate the effective radiative properties, which provides the same net radiative cooling that would be observed using the spectral properties at both the coating and substrate surfaces. Compared to traditional methods that rely on either computationally expensive full spectral analysis or methods for averaging each radiative surface parameter locally, our proposed method focuses on calculating effective properties that provide the same the net cooling effect as a full spectral analysis by accounting the emissivity, absorptivity, and transmissivity collectively, thereby providing an overall estimation error of less than 0.2%. We believe that this study will be beneficial to the engineering communities that employ complex simulation codes and require lumped solar and thermal radiation related parameters.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2021

Effects of different vegetation drag parameterizations on the tidal propagation in coastal marshlands

Vegetation drag is a fundamental quantity directly affecting results for both long- and short-term coastal marsh and geomorphological studies. The vegetation drag in coastal marshland has been modeled by various two-dimensional (2D) and threedimensional (3D) numerical parameterizations. 2D parameterizations treat coastal marshes as bottom roughness elements, while 3D parameterizations resolve the vertically-variable vegetation drag through the water column. However, differences in tidal propagation arising from different drag parameterizations within a single model are largely unknown, and clear guidance on parameterization selection is still missing. In this study, we implemented four vegetation drag parameterizations into the Model for Prediction Across Scales-Ocean (MPAS-O), which include 1) a 2D parameterization using land-cover type-determined Manning’s n (2DLM); 2) a 2D parameterization using vegetation-determined Manning’s n (2DVM); 3) a 3D parameterization for stiff vegetation (3DSV); and 4) a 3D parameterization for flexible vegetation (3DFV). Estimates of the flow resistance effects from these parameterizations were compared using a series of idealized tidal propagation simulations. Given the same tidal condition, flooding depth and flooding distance are the largest in the 2DLM simulations and the smallest in the 3DSV simulations. 2DVM results are the closest to the 2DLM results. 3DFV results are the closest to the average of 2DVM, 3DSV, and 3DFV results. 2DVM and 3DSV results are the least and most sensitive to the vegetation aboveground biomass, respectively. Based on the input data requirement and computational efficiency of each parameterization, a comparison summary is provided to help inform parameterization selection for specific applications. Here, the effects of these parameterizations on coastal geomorphology are further discussed, and the results demonstrate that estimates of the long-term evolution of coastal marshes and coastal morphology depend upon the selection of the vegetation drag parameterization

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

Metal–Ligand Cooperativity via Exchange Coupling Promotes Iron- Catalyzed Electrochemical CO 2 Reduction at Low Overpotentials

Biological and heterogeneous catalysts for the electrochemical CO 2 reduction reaction (CO 2 RR) often exhibit a high degree of electronic delocalization that serves to minimize overpotential and maximize selectivity over the hydrogen evolution reaction (HER). Here, we report a molecular iron(II) system that captures this design concept in a homogeneous setting through the use of a redox non-innocent terpyridine-based pentapyridine ligand (tpyPY2Me). As a result of strong metal-ligand exchange coupling between the Fe(II) center and ligand, [Fe(tpyPY2Me)] 2+ exhibits redox behavior at potentials 640 mV more positive than the isostructural [Zn(tpyPY2Me)] 2+ analog containing the redox-inactive Zn(II) ion. This shift in redox potential is attributed to the requirement for both an open-shell metal ion and a redox non-innocent ligand. The metal-ligand cooperativity in [Fe(tpyPY2Me)] 2+ drives the electrochemical reduction of CO 2 to CO at low overpotentials with high selectivity for CO 2 RR (>90%) and turnover frequencies of 100,000 s -1 with no degradation over 20 h. The decrease in the thermodynamic barrier engendered by this coupling also enables homogeneous CO 2 reduction catalysis in water without compromising selectivity or rates. Synthesis of the two-electron reduction product, [Fe(tpyPY2Me)] o , and characterization by X-ray crystallography, Mössbauer spectroscopy, X-ray absorption spectroscopy (XAS), variable temperature NMR, and density functional theory (DFT) calculations, support assignment of an open-shell singlet electronic structure that maintains a formal Fe(II) oxidation state with a doubly reduced ligand system. Furthermore, this work provides a starting point for the design of systems that exploit metal-ligand cooperativity for electrocatalysis where the electrochemical potential of redox non-innocent ligands can be tuned through secondary metal-dependent interactions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

Assessing methods in fusion and fitting for time series construction in remote sensing-based earth observations

This study evaluates the comparative performance of spatiotemporal fusion and time-series fitting methods for constructing high-spatiotemporal-resolution remote sensing time-series data. Due to in-class similarity of fusion methods and fitting methods, we employ the Fit-FC (Fitting, spatial Filtering, and residual Compensation) model as a representative fusion method and the linear harmonic fitting model as a representative fitting method. Both Fit-FC and the linear harmonic fitting are widely used for high-spatiotemporal-resolution time-series data construction, and we modify the original Fit-FC model to enable automatic time-series fusion. To ensure data representativeness, we use 3 years (2019–2021) of Harmonized Landsat and Sentinel-2 surface reflectance datasets and Terra MCD43A4 products. Eight experimental regions are selected worldwide to guarantee generalization of the comparative performance between fusion and fitting methods, covering diverse land-use types (cropland, developed land, forest, and grassland) and varying climatological conditions. Time-series of NDVI and surface reflectance are analyzed under both actual observations and simulated data-missing scenarios. The constructed time-series data reveals that (1) the modified Fit-FC and linear harmonic fitting model achieve excellent performance in constructing high-resolution time-series images; (2) the fusion method outperforms the fitting method in constructing time-series of NDVI and surface reflectance images in cropland-, forest-, and grassland-dominated regions; (3) both methods achieve comparable performance in developed-dominated regions; (4) the fusion method is more robust to missing data, and better captures abrupt phenological transitions under conditions of continuous missing data; (5) the fitting method is computationally more efficient, making it suitable for large-scale time-series image reconstruction. This study provides valuable insights for selecting optimal strategies to generate high-resolution time-series images across diverse application scenarios and lays a foundation for extensions to other vegetation indices or land surface variables.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2015

SU-F-BRD-12: When Does Pencil Beam Scanning Become Superior to Passive Scattered Proton Therapy for Pediatric Head and Neck Cancers?

Purpose: To investigate the dosimetric benefits of pencil beam scanning (PBS) compared with passive scattered (PS) proton therapy for treatment of pediatric head&neck patients as a function of the PBS spot size and explore the advantages of using apertures in PBS. Methods: Ten pediatric patients with head&neck cancers treated by PS proton therapy at our institution were retrospectively selected. The histologies included rhabdomyosarcoma, ependymoma, astrocytoma, craniopharyngioma and germinoma. The prescribed dose ranged from 36 to 54 Gy(RBE). Five PBS plans were created for each patient using variable spot size (average sigma at isocenter) and choice of beam specific apertures: (1) 10mm spots, (2) 10mm spots with apertures, (3) 6mm spots, (4) 6mm spots with apertures, and (5) 3mm spots. The plans were optimized for intensity modulated proton therapy (IMPT) with no single beam uniformity constraints. Dose volume indices as well as equivalent uniform dose (EUD) were compared between PS and PBS plans. Results: Although target coverage was clinically adequate for all cases, the plans with largest (10mm) spots provide inferior quality compared with PS in terms of dose to organs-at-risk (OAR). However, adding apertures to these plans ensured lower OAR dose than PS. The average EUD difference between PBS and PS plans over all patients and organs at risk were (1) 2.5%, (2) −5.1%, (3) -5%, (4) −7.8%, and (5) −9.5%. As the spot size decreased, more conformal plans were achieved that offered similar target coverage but lower dose to the neighboring healthy organs, while alleviating the need for using apertures. Conclusion: The application of PBS does not always translate to better plan qualities compared to PS depending on the available beam spot size. We recommend that institutions with spot size larger than ∼6mm at isocenter consider using apertures to guarantee clinically comparable or superior dosimetric efficacy to PS treatments.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2015

Building a Business Case for Compressed Natural Gas in Fleet Applications

VICE 2.0 is the second generation of the VICE financial model developed by the National Renewable Energy Laboratory for fleet managers to assess the financial soundness of converting their fleets to run on CNG. VICE 2.0 uses a number of variables for infrastructure and vehicles to estimate the business case for decision-makers when considering CNG as a vehicle fuel. Enhancements in version 2.0 include the ability to select the project type (vehicles and infrastructure or vehicle acquisitions only), and to decouple vehicle acquisition from the infrastructure investment, so the two investments may be made independently. Outputs now include graphical presentations of investment cash flow, payback period (simple and discounted), petroleum displacement (annual and cumulative), and annual greenhouse gas reductions. Also, the Vehicle Data are now built around several common conventionally fueled (gasoline and diesel) fleet vehicles. Descriptions of the various model sections and available inputs follow. Each description includes default values for the base-case business model, which was created so economic sensitivities can be investigated by altering various project parameters one at a time.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2014

System and method for selective catalytic reduction of nitrogen oxides in combustion exhaust gases

A multi-stage selective catalytic reduction (SCR) unit (32) provides efficient reduction of NOx and other pollutants from about 50-550.degree. C. in a power plant (19). Hydrogen (24) and ammonia (29) are variably supplied to the SCR unit depending on temperature. An upstream portion (34) of the SCR unit catalyzes NOx+NH.sub.3 reactions above about 200.degree. C. A downstream portion (36) catalyzes NOx+H.sub.2 reactions below about 260.degree. C., and catalyzes oxidation of NH.sub.3, CO, and VOCs with oxygen in the exhaust above about 200.degree. C., efficiently removing NOx and other pollutants over a range of conditions with low slippage of NH.sub.3. An ammonia synthesis unit (28) may be connected to the SCR unit to provide NH.sub.3 as needed, avoiding transport and storage of ammonia or urea at the site. A carbonaceous gasification plant (18) on site may supply hydrogen and nitrogen to the ammonia synthesis unit, and hydrogen to the SCR unit.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2016

Model Predictive Control of A Matrix-Converter Based Solid State Transformer for Utility Grid Interaction

The matrix converter solid state transformer (MC-SST), formed from the back-to-back connection of two three-to-single-phase matrix converters, is studied for use in the interconnection of two ac grids. The matrix converter topology provides a light weight and low volume single-stage bidirectional ac-ac power conversion without the need for a dc link. Thus, the lifetime limitations of dc-bus storage capacitors are avoided. However, space vector modulation of this type of MC-SST requires to compute vectors for each of the two MCs, which must be carefully coordinated to avoid commutation failure. An additional controller is also required to control power exchange between the two ac grids. In this paper, model predictive control (MPC) is proposed for an MC-SST connecting two different ac power grids. The proposed MPC predicts the circuit variables based on the discrete model of MC-SST system and the cost function is formulated so that the optimal switch vector for the next sample period is selected, thereby generating the required grid currents for the SST. Simulation and experimental studies are carried out to demonstrate the effectiveness and simplicity of the proposed MPC for such MC-SST-based grid interfacing systems.

Xue, Yaosuo↗

DOE OSTI2024

Integrated solution techniques for security constrained unit commitment problem

Apparatus and methods are disclosed for solving Mixed Integer Programming (MIP) problems, such as Security Constrained Unit Commitment (SCUC) problems used by power grid authorities to perform day-ahead market clearing. In certain examples, a plurality of threads of a software tool implementing a concurrent optimizer can be executed concurrently and sequentially to generate new solutions to a SCUC problem for an upcoming planning horizon. Data can be shared among the concurrently executing threads, such as intermediate/incumbent solutions and hints regarding the fixing of variables and constraints to reduce the size of the SCUC problem. In some examples, the threads are seeded with historical solutions from prior planning horizons. The software tool can select a best solution from the solutions generated by the threads, and determine dispatch instructions for a device coupled to the power grid for the upcoming planning horizon based at least in part on the selected solution.

Pan, Feng↗

DOE OSTI2019

Variable genome evolution in fungi after transposon-mediated amplification of a housekeeping gene

Transposable elements (TEs) can be key drivers of evolution, but the mechanisms and scope of how they impact gene and genome function are largely unknown. Previous analyses revealed that TE-mediated gene amplifications can have variable effects on fungal genomes, from inactivation of function to production of multiple active copies. For example, a DNA methyltransferase gene in the wheat pathogen Zymoseptoria tritici (synonym Mycosphaerella graminicola) was amplified to tens of copies, all of which were inactivated by Repeat-Induced Point mutation (RIP) including the original, resulting in loss of cytosine methylation. In another wheat pathogen, Pyrenophora tritici-repentis, a histone H3 gene was amplified to tens of copies with little evidence of RIP, leading to many potentially active copies. To further test the effects of transposon-aided gene amplifications on genome evolution and architecture, the repetitive fraction of the significantly expanded genome of the banana pathogen, Pseudocercospora fijiensis, was analyzed in greater detail. These analyses identified a housekeeping gene, histone H3, which was captured and amplified to hundreds of copies by a hAT DNA transposon, all of which were inactivated by RIP, except for the original. In P. fijiensis the original H3 gene probably was not protected from RIP, but most likely was maintained intact due to strong purifying selection. Comparative analyses revealed that a similar event occurred in five additional genomes representing the fungal genera Cercospora, Pseudocercospora and Sphaerulina. These results indicate that the interplay of TEs and RIP can result in different and unpredictable fates of amplified genes, with variable effects on gene and genome evolution.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2018

Numerical similarity solution for a variable coefficient K(m, n) equation

A technique for finding numerical similarity solutions to an initial boundary value problem (IBVP) for generalized K(m, n) equations is described. The equation under consideration is nonlinear and has variable coefficients. The original problem is transformed with the aid of Lie symmetries to an initial value problem (IVP) for a nonlinear third-order ordinary differential equation. The existence and uniqueness of the solution are examined, and the problem is consequently solved with the aid of a finite-difference scheme for various values of the governing parameters. In lieu of an exact symbolic solution, the scheme is validated by comparing the numerical solutions with the approximate analytic solutions obtained with the aid of the method of successive approximations in their region of validity. The accuracy, efficiency, and consistency of the scheme are demonstrated. Numerical solutions to the original initial boundary value problem are constructed for selected parameter values with the aid of the transforms. The qualitative behavior of the solutions as a function of the governing parameters is analyzed, and it is found that the examined IBVPs for generalized K(m, n) equations with variable coefficients that are functions of time, do not admit solitary wave or compacton solutions.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2023

Penetrant shape effects on activated dynamics and selectivity in polymer melts and networks based on self-consistent cooperative hopping theory

We generalize and apply the microscopic self-consistent cooperative hopping theory for activated penetrant dynamics in polymer melts and crosslinked networks to address the role of highly variable non-spherical molecular shape.

Chemistry↗

DOE OSTI2024

Functional Data Analysis in Wearable Body Sensor Networks

Improving response time of indirect room-size calorimeters is still an outstanding problem in metabolic research. Accurate estimates of instantaneous rates of gaseous exchange require numerical differentiation of measured gaseousgas concentrations. We propose a new method to estimate the instantaneous gaseousgas exchange rates in indirect calorimetry. In contrast to the previously developed techniques, the method addresses the problem of differentiation of gaseous concentrations as an ill-posed problem. By applying the method of regularization, the problem of differentiation is converted into a well-posed problem resulting in smooth and consistent gaseous exchange rates. The validity of the method is tested on a large dataset of calorimeter experiments which included 313 human experiments along with 231 alcohol combustion experiments. It is demonstrated that the method is able to reliably differentiate between the “unphysiological” process of alcohol combustion and physiological variations produced by human metabolism. The method also allowed unraveling the previously unreported relative kinetics of O2 consumption and Respiratory Quotient (RQ) in humans. It was found that the kinetics of oxidative fuel selection lags behind the energy expenditure in humans exhibiting some sort of oxidative inertia. The time lag varies from 2-3 min up to 30 min, depending on particular individual. No such lag was found in alcohol combustion experiments. In addition to the relative kinetics of substrate oxidation, two statistical indexes reflecting variability of minute-by-minute RQ were estimated. The indexes were the RQ’s standard deviation and RQ’s first-order derivative. Both indexes showed statistically significant difference between human experiments and alcohol combustion experiments. We conclude that the proposed method can consistently extract physiologically-relevant information from noisy calorimetry data and the aforesaid information can provide additional insights into the mechanism of metabolic fuel selection in humans.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Functional Data Analysis in Wearable Body Sensor Networks

60 - APPLIED LIFE SCIENCES↗