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At least 325 records · Page 18

Bayesian Cloud Property Retrievals from ARM Active and Passive Measurements

The optimum use of the continuous measurements of thermodynamics, radiation, aerosols, clouds and precipitation from the DOE Atmospheric Radiation Measurement (ARM) program is key to achieve the DOE Atmospheric System Research (ASR)’s objectives. One of the key mission requirements is to retrieve cloud and precipitation properties, as well as vertical motion parameters, along the vertical cross- section defined by the profiling active sensors. Such retrievals are challenging to perform continuously in the entire spectrum of cloud and precipitation conditions due to the large natural microphysical and dynamical variability, the often-limited information content in the measurements, and the lack of proper characterization of measurement quality and uncertainty. Today, the acquisition of new remote and in-situ sensors by the ARM program creates opportunities to address the microphysical retrieval problem by exploiting new, more robust retrieval techniques and integrating various scattered advancements in both sensor techniques and retrieval algorithms. During this project, we constructed a robust Bayesian Markov chain Monte Carlo (MCMC) cloud property retrieval algorithm that includes a state of the art radar forward model. Our MCMC-based retrieval produces both the best estimate of height-resolved cloud and precipitation properties in the radar profile, as well as an estimate of the in-cloud vertical motion and turbulence. In addition, the MCMC algorithm automatically produces robust and flexible estimates of retrieval uncertainty. We tested the algorithm on several synthetic cloud profiles obtained from large eddy simulation (LES) models with bin-resolved microphysics.

54 ENVIRONMENTAL SCIENCES↗

Optimal economic operation of liquid petroleum products pipeline systems

The majority of overland transport needs for crude petroleum and refined petroleum products are met using pipelines. Numerous studies have developed optimization methods for design of these systems in order to minimize construction costs while meeting capacity requirements. Here, we formulate problems to optimize the operations of existing single liquid commodity pipeline systems subject to physical flow and pump engineering constraints. The objectives are to maximize the economic value created for users of the system and to minimize operating costs. We present a general computational method for this class of continuous, non-convex nonlinear programs, and examine the use of pump operating settings and flow allocations as decision variables. Furthermore, the approach is applied to compute optimal operating regimes and perform engineering economic sensitivity analyses for a case study of a crude oil pipeline developed using publicly available data.

02 PETROLEUM↗

Effect of operating parameters on H 2 /CO 2 conversion to methanol over Cu-Zn oxide supported on ZrO 2 polymorph catalysts: Characterization and kinetics

Kinetic aspects of the operating parameters for the catalytic conversion of H 2 /CO 2 to methanol over two novel catalysts were evaluated to understand the effect of the polymorphic ZrO 2 phase composed of Cu 0/+ -ZnO sites at the atomic level and its impact on the reaction mechanism. The catalysts were characterized by in situ and ex-situ XRD, N 2 adsorption/desorption isotherms, FRX, TPR, TPD-N 2 O, in situ XANES, TPD-CO 2 , and in situ DRIFTS techniques. The influence of different reaction variables such as the GHSV, temperature, pressure, and H 2 /CO 2 ratio were studied using a fixed bed continuous plug flow reactor. The Cu-ZnO catalyst supported on the tetragonal zirconia polymorph exhibited the highest methanol yield due to the lower activation energy when compared to the catalyst with a greater amount of the monoclinic phase. In addition, the catalysts were reused for 8 cycles of 6 hours to evaluate their stability, which can translate into lower costs for large-scale methanol production. As a result, the estimation of the kinetic parameters over Cu-Zn oxide supported on ZrO 2 polymorphs was significant for understanding the reaction mechanism, as well as to provide a pathway for scaling-up of the process.

36 MATERIALS SCIENCE↗

Long-term dynamics of soil, tree stem and ecosystem methane fluxes in a riparian forest

The carbon (C) budgets of riparian forests are sensitive to climatic variability. Therefore, riparian forests are hot spots of C cycling in landscapes. Only a limited number of studies on continuous measurements of methane (CH 4 ) fluxes from riparian forests is available. Here, in this work, we report continuous high-frequency soil and ecosystem (eddy-covariance; EC) measurements of CH 4 fluxes with a quantum cascade laser absorption spectrometer for a 2.5-year period and measurements of CH 4 fluxes from tree stems using manual chambers for a 1.5 year period from a temperate riparian Alnus incana forest. The results demonstrate that the riparian forest is a minor net annual sink of CH 4 consuming 0.24 kg CH 4 -C ha –1 y –1 . Soil water content is the most important determinant of soil, stem, and EC fluxes, followed by soil temperature. There were significant differences in CH 4 fluxes between the wet and dry periods. During the wet period, 83% of CH 4 was emitted from the tree stems while the ecosystem-level emission was equal to the sum of soil and stem emissions. During the dry period, CH 4 was substantially consumed in the soil whereas stem emissions were very low. A significant difference between the EC fluxes and the sum of soil and stem fluxes during the dry period is most likely caused by emission from the canopy whereas at the ecosystem level the forest was a clear CH 4 sink. Our results together with past measurements of CH 4 fluxes in other riparian forests suggest that temperate riparian forests can be long-term CH 4 sinks.

54 ENVIRONMENTAL SCIENCES↗

Save or spend? Diverging water‐use strategies of grasses and encroaching clonal shrubs

Abstract Shrub encroachment is one of the primary threats to mesic grasslands around the world. This dramatic shift in plant cover has the potential to alter ecosystem‐scale water budgets and responses to novel rainfall regimes. Understanding divergent water‐use strategies among encroaching shrubs and the grasses they replace is critical for predicting shifts in ecosystem‐scale water dynamics as a result of shrub encroachment, particularly if drought events become more frequent and/or severe in the future. In this study, we assessed how water‐use traits of a rapidly encroaching clonal shrub (Cornus drummondii) and a dominant C 4 grass (Andropogon gerardii) impact responses to changes in water availability in tallgrass prairie. We assessed intra‐annual change in depth of water uptake, turgor loss point and stomatal regulation in each species. Sampling took place at Konza Prairie Biological Station (northeastern KS, USA) during the 2021 and 2022 growing seasons. Cornus drummondiishifted from shallow to deep soil water sources across the 2021 and 2022 growing seasons. This plasticity in depth of water uptake facilitated a ‘wasteful’ water‐use strategy inC. drummondii, where stomatal conductance and transpiration rates continued to increase even when no further gain in photosynthetic rate occurred.A. gerardiiphotosynthetic rates and stomatal conductance were more variable through time and were more responsive to changes in leaf water potential thanC. drummondii. However, intra‐annual adjustment of turgor loss point was more pronounced inC. drummondii(Δπ TLP = −0.48 MPa ± 0.15 SD) than inA. gerardii(Δπ TLP = −0.29 MPa ± 0.19 SD). Synthesis. These results suggest thatC. drummondiiis highly resilient to changes in water availability in surface soils and will likely remain unaffected by future droughts unless they are severe enough to reduce the availability of deep soil water. Given that clonal shrubs are key invaders of grasslands world‐wide, increased leaf‐level water loss is expected to accelerate ecosystem‐level drying as clonal shrub encroachment proceeds in mesic grasslands.

Environmental Sciences & Ecology↗

WINDPROF: Merged Best-Estimate Wind Profile Data – Rhode Island (WFIP3 Campaign)

WINDPROF provides 10-minute wind and turbulence profiles that integrate a scanning Doppler lidar, a continuous-wave profiling lidar, and a sonic anemometer across Northeast U.S. coastal and offshore sites during the WFIP3 campaign. Variables include wind speed, wind direction, vertical velocity, turbulence intensity, and turbulent kinetic energy, each with per-instrument quality control and inter-instrument agreement validation. Profiles are mapped to a standardized height grid – a dedicated near-surface level at the sonic measurement height (4 m AGL), 20 m spacing to 100 m, and 30 m spacing above – and carry component and derived uncertainty estimates. Heights are reported above ground level; the site's ground elevation is stored separately. The Rhode Island dataset covers 7 February 2024 – 4 September 2025.

17 WIND ENERGY↗

Deep Sequencing of MHC-Adapted Viral Lines Reveals Complex Recombinational Exchanges With Endogenous Retroviruses Leading to High-Frequency Variants

Experimental evolution (serial passage) of Friend virus complex (FVC) in mice demonstrates phenotypic adaptation to specific host major histocompatibility complex (MHC) genotypes. These evolved viral lines show increased fitness and virulence in their host-genotype-of-passage, but display fitness and virulence tradeoffs when infecting unfamiliar host MHC genotypes. Here, we deep sequence these viral lines in an attempt to discover the genetic basis of FVC adaptation. The principal prediction for genotype-specific adaptation is that unique mutations would rise to high frequency in viral lines adapted to each host MHC genotype. This prediction was not supported by our sequencing data as most observed high-frequency variants were present in each of our independently evolved viral lines. However, using a multi-variate approach to measure divergence between viral populations, we show that populations of replicate evolved viral lines from the same MHC congenic mouse strain were more similar to one another than to lines derived from different MHC congenic mouse strains, suggesting that MHC genotype does predictably act on viral evolution in our model. Sequence analysis also revealed rampant recombination with endogenous murine leukemia virus sequences (EnMuLVs) that are encoded within the BALB/c mouse genome. The highest frequency variants in all six lines contained a 12 bp insertion from a recombinant EnMuLV source, suggesting such recombinants were either being favored by selection or were contained in a recombinational hotspot. Interestingly, they did not reach fixation, as if they are low fitness. The amount of background mutations linked to FVC/EnMuLV variable sites indicated that FVC/EnMuLV recombinants had not reached mutation selection equilibrium and thus, that EnMuLV sequences are likely continuously introgressing into the replicating viral population. These discoveries raise the question: is the expression of EnMuLV sequences in mouse splenocytes that permit recombination with exogenous FVC a pathogen or host adaptation?

59 BASIC BIOLOGICAL SCIENCES↗

Joint Modeling of Quasar Variability and Accretion Disk Reprocessing Using Latent Stochastic Differential Equations

Quasars are bright active galactic nuclei powered by the accretion of matter around supermassive black holes at the center of galaxies. Their stochastic brightness variability depends on the physical properties of the accretion disk and black hole. The upcoming Rubin Observatory Legacy Survey of Space and Time (LSST) is expected to observe tens of millions of quasars, so there is a need for efficient techniques like machine learning that can handle the large volume of data. Quasar variability is believed to be driven by an X-ray corona, which is reprocessed by the accretion disk and emitted as UV/optical variability. We are the first to introduce an auto-differentiable simulation of the accretion disk and reprocessing. We use the simulation as a direct component of our neural network to jointly model the driving variability and reprocessing, trained with supervised learning on simulated LSST-like 10 yr quasar light curves. We encode the light curves using a transformer encoder, and the driving variability is reconstructed using latent stochastic differential equations, a physically motivated generative deep learning method that can model continuous-time stochastic dynamics. By embedding the physical processes of the driving signal and reprocessing into our network, we achieve a model that is more robust and interpretable. We demonstrate that our model outperforms a Gaussian process regression baseline and can infer accretion disk parameters and time delays between wave bands, even for out-of-distribution driving signals. Our approach provides a powerful framework that can be adapted to solve other inverse problems in multivariate time series.

Fagin, Joshua [City Univ. of New York (CUNY), NY (↗

Biomass Feedstock National User Facility--Improving Bale Deconstruction and Material Flow

The project aims to reduce feedstock variability using a quality-by-design approach beginning when the biomass is introduced to the process and will continue through the size reduction process, which will yield the results of fine generation reduction, contaminant removal, control of the physical and chemical critical material attributes in the process, and management of the flowability.

09 BIOMASS FUELS↗

Design of a Continuous Pellet Fueling System for Wendelstein 7-X

A continuous pellet fueling system (CPFS) is currently being designed at the Oak Ridge National Laboratory (ORNL) for the long pulse operation of the Wendelstein 7-X (W7-X) stellarator. The purpose of the CPFS is to provide deep continuous fueling for feedback-controlled high-density operation and mitigation of predicted hollow density profiles. As described here, the system will provide the capability to inject cylindrical pellets of solid hydrogen or deuterium into the plasma core, with flexibility to vary the pellet size, velocity, and injection frequency. Pellets are nominally of 3 mm in diameter and have a length between 1 and 4 mm. The heart of the CPFS is a vertically oriented, twin-screw extruder, cooled by three Gifford-McMahon cryocoolers in parallel, designed to form a continuous filament of hydrogen or deuterium. The filament width, which determines the pellet length, can be adjusted by means of a variable nozzle driven by a linear actuator at the base of the extruder. Coupled to the nozzle is a solenoid-operated gas gun and cutter assembly. A pneumatic propellant valve pulses a burst of ~60 bar helium to accelerate the cut pellet into W7-X. Three gaps in the guide tubes provide pumping locations to remove the helium propellant before it reaches the plasma. The maximum velocity of the pellet is limited by its ability to survive navigating the guide tube trajectory intact. A microwave cavity located within the guide tube provides the capability to measure the pellet size and velocity. The mechanical and thermal designs of the W7-X extruder, adjustable nozzle, and gun and cutter assembly design are described. A guide tube design and experimental pellet survivability test results are presented.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Testing- and Model- Based Optimization of Coal-fired Primary Heater Design for Indirect Supercritical CO 2 Power Cycles (Final Scientific and Technical Report)

The overall objective of this project was to perform the R&D necessary to mitigate the risk associated with the design of a primary heat exchanger for a solid-fired combustion system coupled with an indirect-fired closed-loop Brayton Cycle utilizing supercritical CO 2 . The key technological hurdle was the coupling of a solid-fuel firing system with the primary heater, which poses a singular challenge, which is the management of burner performance and operational conditions in a way to manage heat exchanger tube metal temperatures and temperature ramp rates in the absence of fluid phase change on the inside of the tubes. We designed and built the first ever pseudo power system employing a simple recuperated supercritical CO 2 closed-loop Brayton Cycle coupled to a solid-fuel fired system. Advanced coupled CFD and process modeling were used to design the primary heat exchanger (PHX), which consisted of both radiative and convective sections, to limit tube metal temperatures resulting from the heat release profile of the solid fuel flame near the radiative tubes. The heat exchanger was designed to produce finished CO 2 temperatures of 600 °C a pressure of 20.7 MPa and CO 2 flow of 5.5 kg/s. The constructed PHX was capable of 1.2 MWth heat uptake. During design of the PHX, the modeling showed that most variables influencing flame shape (burner stoichiometric ratio and register velocities and swirl) were not suitable to manage heat flux to the metal surfaces. This is because they substantially increased adiabatic flame temperature through the influence of localized stoichiometric ratio. Excess air and firing rate were the two most powerful variables that could be used to control tube surface temperatures. The coupled system was operated for a total of 407 hours, with the longest continuous run of 248 hours. For 62% of the operational time, the unit was unmanned and in automatic control. The fuels used for the testing included natural gas, two Utah Bituminous coals, woody biomass, and bagasse. During the testing we were able to verify the 1.2 MWth heat uptake and we operated at a finished CO 2 temperature of 607 °C and a pressure of 20.3 MPa simultaneously. The real-time corrosion rate of the Super 304H tube CO 2 surface in the region of the radiative section of the PHX were measured, at an approximate temperature of 550 °C. The two key variables related to corrosion rate are the pressure and flow rate of the CO 2 . A technoeconomic analysis was performed at a scale of 120 MWE. The updated analysis showed that the efficiency of an sCO 2 power producing plant will be related to the pressure drop of the PHX.

01 COAL, LIGNITE, AND PEAT↗

Parameter-Varying Hydrodynamic Model of a Single Vane in a Variable-Geometry Oscillating Surge Wave Energy Converter

This paper presents a preliminary study on the parameter-varying hydrodynamic modeling of an individual vane of a variable-geometry oscillating surge wave energy converter (VGOSWEC). The WEC design incorporates controlled surfaces that can modify their orientation relative to the wave motion, reducing hydrodynamic pressure and related loads. This research focuses on characterizing the behavior of the oscillating WEC using a simplified model and three methods for achieving a continuous parameter-varying model: coarse hydrodynamic parameters, interpolation of hydrodynamic parameters, and a fitting function. The results of this study contribute to the understanding of parameter-varying hydrodynamic effects in variable geometry oscillating WECs. The findings provide insights into the potential for reducing structural loads and improving the overall performance of such devices. Further research and development in this area could lead to advancements in WEC technologies, enabling their integration into the competitive energy market.

analytical models↗

Parameter-Varying Hydrodynamic Model of a Single Vane in a Variable-Geometry Oscillating Surge Wave Energy Converter: Preprint

This paper presents a study on the time-varying hydrodynamic modeling of an individual flap of a variable geometry oscillating surge wave energy converter (VGOSWEC). The WEC design incorporates controlled surfaces that can modify their orientation relative to the wave motion, reducing hydrodynamic pressure and related loads. This research focuses on characterizing the behavior of the oscillating WEC using a simplified model and three methods for achieving a continuous time-variant model: discrete hydrodynamic parameters, interpolation of hydrodynamic parameters, and a fitting function. The results of this study contribute to the understanding of time-varying hydrodynamic effects in variable geometry oscillating WECs. The findings provide insights into the potential for reducing structural loads and improving the overall performance of such devices. Further research and development in this area could lead to advancements in WEC technologies, enabling their integration into the competitive energy market.

HYDRO ENERGY,TIDAL AND WAVE POWER↗

235-F GoldSim Fate and Transport Model: Uncertainty Quantification

Building 235-F was configured with two missions in mind: Actinide Billet Line (ABL) and the fabrication of Pu-238 oxide for space program applications. ABL produced Np-237 billets for use in SRS reactors, whereas the design process, fabrication, and examination of Pu-238 oxide powder occurred within the following areas, respectively: Plutonium Experimental Facility (PEF), Plutonium Fuel Form (PuFF), and Old Metallography Lab (OML). By 1990 production ceased and by 2006 de-inventory occurred; however, assays have shown significant holdup remains within ABL and PuFF. As a result, 235-F is a Category 2 nuclear facility, with plans to undergo deactivation and decommission (D and D) via In-Situ Disposal (ISD). The purpose of this project is to ensure United States Environmental Protection Agency (USEPA) groundwater radiation maximum contaminant level (MCL) and dosage standards are met during the D and D of 235-F by quantifying uncertainty through probabilistic modeling and evaluation of various ISD alternatives. GoldSim is a dynamic modeling software package with a graphical, object-oriented interface capable of capturing the influence of complex system input variability on probabilistic system outcomes. A GoldSim stochastic fate and transport model for 235-F was developed and matched with a PORFLOW deterministic model to simulate probabilistic release and flow of radionuclides from ABL and PuFF into the vadose zone, the Upper Three Runs (UTR) Aquifer, and UTR Creek. The GoldSim model was used to probabilistically evaluate four ISD scenarios against USEPA groundwater radiation MCLs and dosage standards. The deterministic 235-F GoldSim fate and transport model continues to be refined to match the results of the PORFLOW deterministic model to ensure the model accurately represents radionuclide movement through the groundwater system. The stochastic variables that are utilized within the GoldSim model are founded on the most current data; a conservative perspective is taken where needed. Alignment with the PORFLOW deterministic model, coupled with input stochastic variability, allows the probabilistic 235-F GoldSim model to capture the conservative breadth of possible outcomes for radionuclide fate within this particular system. This ensures that the USEPA MCLs and dosage limits hold even in the worst case scenarios.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Volume extrapolation via eigenvector continuation

Here, we develop an extension of eigenvector continuation (EC) that makes it possible to extrapolate simulations of quantum systems in finite periodic boxes across large ranges of box sizes. The formal justification for this approach, which we call finite-volume eigenvector continuation (FVEC), is provided by matching periodic functions at different box sizes. As concrete FVEC implementation we use a discrete variable representation based on plane-wave states and present several applications calculated within this framework.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Light Water Reactor Sustainability Program: Materials Research Pathway: FY 23 Technical Program Plan

Components in operating commercial nuclear power plants must withstand very harsh environments that include extended time at neutron and gamma irradiation, stress, and temperature, as well as possible exposure to corrosive media. The many modes of materials degradation are complex and often include synergies between multiple environmental variables and conditions that vary depending on locations and materials. Understanding and managing materials degradation is a requirement for the continued safe and reliable operation of nuclear power plants.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Variable Effects of Dispersed Nanoparticles on Triboelectric Nanogenerators

Technology has recently seen a drastic physical downsizing. Wearable and small devices with lower power demands have become the norm and continue to be more prominent in daily life. With modern devices growing smaller and requiring less electricity, a power source will always be needed. Contemporary batteries are the most common means to power small electronics. However, reliance on conventional batteries may prove insufficient due to the non renewable resources (Li, Ni, Co) required to power the growing number of individual devices each person may own. Additionally, the infrastructure required to harvest and recycle the sheer number of batteries produced presents a further logistic issue to be addressed. A promising alternative to batteries is the usage of triboelectric nanogenerators (TENGs). TENGs are a class of energy harvesting devices that utilize triboelectric generation to convert mechanical/kinetic energy into electrical energy and have exhibited efficiencies up to 85 % at low frequencies. TENGs exhibit a high voltage but low current. Even with the high voltage, the low current output proves to be a significant factor preventing undoped TENGs from being commercially viable. This review will investigate factors that increase the total current produced by TENGs when nanoparticles are utilized in TENGs. Factors such as increasing porosity, surface area, surface charge density, charge storage, deep trap formation, and dielectric constant can be altered to affect the total current by impregnating nanoparticles into the polymer material will be explored.

36 MATERIALS SCIENCE↗

Variable Effects of Dispersed Nanoparticles on Triboelectric Nanogenerators

Technology has recently seen a drastic physical downsizing. Wearable and small devices with lower power demands have become the norm and continue to be more prominent in daily life. With modern devices growing smaller and requiring less electricity, a power source will always be needed. Contemporary batteries are the most common means to power small electronics. However, reliance on conventional batteries may prove insufficient due to the non renewable resources (Li, Ni, Co) required to power the growing number of individual devices each person may own. Additionally, the infrastructure required to harvest and recycle the sheer number of batteries produced presents a further logistic issue to be addressed. A promising alternative to batteries is the usage of triboelectric nanogenerators (TENGs). TENGs are a class of energy harvesting devices that utilize triboelectric generation to convert mechanical/kinetic energy into electrical energy and have exhibited efficiencies up to 85 % at low frequencies. TENGs exhibit a high voltage but low current. Even with the high voltage, the low current output proves to be a significant factor preventing undoped TENGs from being commercially viable. This review will investigate factors that increase the total current produced by TENGs when nanoparticles are utilized in TENGs. Factors such as increasing porosity, surface area, surface charge density, charge storage, deep trap formation, and dielectric constant can be altered to affect the total current by impregnating nanoparticles into the polymer material will be explored.

42 ENGINEERING↗