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At least 937 records · Page 52

Algal Biomass Conversion to Fuels via Combined Algae Processing (CAP) (2021 State of Technology and Future Research)

The annual State of Technology (SOT) assessment is an essential activity for platform research conducted under the Bioenergy Technologies Office. It allows for the impact of research progress to be quantified in terms of economic improvements in the overall biofuel production process for a particular biomass processing pathway, whether based on terrestrial or algal biomass feedstocks. As such, initial benchmarks can be established for currently demonstrated performance, and progress can be tracked towards out-year goals to ultimately demonstrate economically viable biofuel technologies. NREL's algae state of technology benchmarking efforts focus both on front-end algal biomass production and separately on back-end conversion to fuels through NREL's "combined algae processing" (CAP) pathway. The production model is based on outdoor long-term cultivation data, enabled by comprehensive algal biomass production trials conducted under the Development of Integrated Screening, Cultivar Optimization, and Verification Research consortium (DISCOVR) efforts, driven by data furnished by Arizona State University (ASU) at the Arizona Center for Algae Technology and Innovation (AzCATI) testbed site. The CAP model is based on experimental efforts conducted under NREL research and development projects. This report focuses on back-end conversion of algal biomass through the CAP pathway, highlighting the 2021 updates to minimum fuel selling price (MFSP). This update maintains an important recent inclusion of polyurethane (PU) previously incorporated in the 2020 SOT as a value-added coproduct. Relative to the 2020 SOT case, this indicates a minimal increase of $0.10-$0.14/GGE (roughly 2%) for both the acids and BDO pathways, attributed to minimal increases in upstream algal biomass costs from slightly lower demonstrated cultivation productivities in the 2021 SOT.

09 BIOMASS FUELS↗

Global nitrogen deposition inputs to cropland at national scale from 1961 to 2020

Nitrogen (N) deposition is a significant nutrient input to cropland and consequently important for the evaluation of N budgets and N use efficiency (NUE) at different scales and over time. However, the spatiotemporal coverage of N deposition measurements is limited globally, whereas modeled N deposition values carry uncertainties. Here, we reviewed existing methods and related data sources for quantifying N deposition inputs to crop production on a national scale. We utilized different data sources to estimate N deposition input to crop production at national scale and compared our estimates with 14 N budget datasets, as well as measured N deposition data from observation networks in 9 countries. We created four datasets of N deposition inputs on cropland during 1961–2020 for 236 countries. These products showed good agreement for the majority of countries and can be used in the modeling and assessment of NUE at national and global scales. One of the datasets is recommended for general use in regional to global N budget and NUE estimates.

54 ENVIRONMENTAL SCIENCES↗

Search for the nonresonant and resonant production of a Higgs boson in association with an additional scalar boson in the $γγττ$ final state in proton-proton collisions at $\sqrt{s}=13$ TeV

The results of a search for the production of two scalar bosons in final states with two photons and two tau leptons are presented. The search considers both nonresonant production of a Higgs boson pair, HH, and resonant production via a new boson X which decays either to HH or to H and a new scalar Y. The analysis uses up to 138 fb −1 of proton-proton collision data, recorded between 2016 and 2018 by the CMS experiment at the LHC at a center-of-mass energy of 13 TeV. No evidence for signal is found in the data. For the nonresonant production, the observed (expected) upper limit at 95% confidence level (CL) on the HH production cross section is set at 930 (740) fb, corresponding to 33 (26) times the standard model prediction. At 95% CL, HH production is observed (expected) to be excluded for values of κ λ outside the range between −12 (−9.4) and 17 (15). Observed (expected) upper limits at 95% CL for the X → HH cross section are found to be within 160 to 2200 (200 to 1800) fb, depending on the mass of X. In the X → Y(ττ)H(γγ) search, the observed (expected) upper limits on the product of the production cross section and decay branching fractions vary between 0.059–1.2 fb (0.087–0.68 fb). For the X → Y(γγ)H(ττ) search the observed (expected) upper limits on the product of the production cross section and Y → γγ branching fraction vary between 0.69–15 fb (0.73–8.3 fb) in the low Y mass search, tightening constraints on the next-to-minimal supersymmetric standard model, and between 0.64–10 fb (0.70–7.6 fb) in the high Y mass search.

Beyond Standard Model↗

Search for the nonresonant and resonant production of a Higgs boson in association with an additional scalar boson in the $γγττ$ final state in proton-proton collisions at $\sqrt{s}$ = 13 TeV

The results of a search for the production of two scalar bosons in final states with two photons and two tau leptons are presented. The search considers both nonresonant production of a Higgs boson pair, HH, and resonant production via a new boson X which decays either to HH or to H and a new scalar Y. The analysis uses up to 138 fb$^{-1}$ of proton-proton collision data, recorded between 2016 and 2018 by the CMS experiment at the LHC at a center-of-mass energy of 13 TeV. No evidence for signal is found in the data. For the nonresonant production, the observed (expected) upper limit at 95% confidence level (CL) on the HH production cross section is set at 930 (740) fb, corresponding to 33 (26) times the standard model prediction. At 95% CL, HH production is observed (expected) to be excluded for values of $κ_λ$ outside the range between $-$12 ($-$9.4) and 17 (15). Observed (expected) upper limits at 95% CL for the XHH cross section are found to be within 160 to 2200 (200 to 1800) fb, depending on the mass of X. In the X $\to$ Y($γγ$)H($ττ$) search, the observed (expected) upper limits on the product of the production cross section and decay branching fractions vary between 0.059$-$1.2 fb (0.087$-$0.68 fb). For the X $\to$ Y($γγ$)H($ττ$) search the observed (expected) upper limits on the product of the production cross section and Y $to$ $γγ$ branching fraction vary between 0.69$-$15 fb (0.73$-$8.3 fb) in the low Y mass search, tightening constraints on the next-to-minimal supersymmetric standard model, and between 0.64$-$10 fb (0.70$-$7.6 fb) in the high Y mass search.

FOS: Physical sciences↗

Algal Biomass Conversion to Fuels via Combined Algae Processing (CAP): 2019 State of Technology and Future Research

NREL’s algae state of technology benchmarking efforts focus both on front-end algal biomass production and separately on back-end conversion to fuels through NREL’s “combined algae processing” (CAP) pathway. The production model is based on outdoor long-term cultivation data, enabled by comprehensive algal biomass production trials conducted under the Development of Integrated Screening, Cultivar Optimization, and Verification Research consortium (DISCOVR) efforts, driven by data furnished by Arizona State University (ASU) at the Arizona Center for Algae Technology and Innovation (AzCATI) testbed site. The CAP model is based on experimental efforts conducted under NREL research and development projects. This report focuses on back-end conversion of algal biomass through the CAP pathway, highlighting the 2019 updates to minimum fuel selling price (MFSP). This milestone reports on key process sustainability indicators for the CAP conversion stage including mass and carbon yields to fuels and coproducts, freshwater consumption, and facility power balances/natural gas demands.

09 BIOMASS FUELS↗

Monitoring Methods for Early Detection of Inadvertent Fission Product Release at the Advanced Test Reactor

Isotope effluent data obtained during three instances of experiment failures at the Advanced Test Reactor (ATR) are analyzed to provide an overview of the methods used to detect initial signs of unintended fission product release. The data is contextualized with the operational experience, including means of identification and subsequent mitigation strategies, gained during these events. General trends as well as variations in isotopic behavior between the three failures are explored. Background on the Real Time Monitor, a High Purity Germanium detector, and other fission product monitoring systems utilized at the Advanced Test Reactor is also provided. The presented analysis was used to establish administrative action levels which are currently utilized by ATR for early detection of experiment fission product release. Early identification provides time to make programmatic decisions before approaching safety and environmental limits.

21 - SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLAN↗

Generalizing to new geometries with Geometry-Aware Autoregressive Models (GAAMs) for fast calorimeter simulation

Generation of simulated detector response to collision products is crucial to data analysis in particle physics, but computationally very expensive. One subdetector, the calorimeter, dominates the computational time due to the high granularity of its cells and complexity of the interactions. Generative models can provide more rapid sample production, but currently require significant effort to optimize performance for specific detector geometries, often requiring many models to describe the varying cell sizes and arrangements, without the ability to generalize to other geometries. Here, we develop a geometry-aware autoregressive model, which learns how the calorimeter response varies with geometry, and is capable of generating simulated responses to unseen geometries without additional training. The geometry-aware model outperforms a baseline unaware model by over 50% in several metrics such as the Wasserstein distance between the generated and the true distributions of key quantities which summarize the simulated response. A single geometry-aware model could replace the hundreds of generative models currently designed for calorimeter simulation by physicists analyzing data collected at the Large Hadron Collider. This proof-of-concept study motivates the design of a foundational model that will be a crucial tool for the study of future detectors, dramatically reducing the large upfront investment usually needed to develop generative calorimeter models.

47 OTHER INSTRUMENTATION↗

Production of Biocrude in an Advanced Photobioreactor-Based Biorefinery

Algenol Biotech, the National Renewable Energy Laboratory (NREL), Georgia Institute of Technology, Arizona State University, and Reliance Industries formed a team to advance the state of the art in algal biomass production and downstream processing technologies, with the end goal of a sustainable, economically viable biofuel intermediate (BFI, biocrude) product. The project included examination of high value co-product production as a market entry strategy and for enhancing the economics of a biorefinery for BFI production. The project targeted innovations in biology, operations, and engineering. The goals of the project were: BFI productivity greater than 4,000 gal-BFI/acre-yr on an annualized basis; energy efficient innovations in downstream operations resulting in an energy expenditure less than 10% of the BFI energy content and a carbon footprint reduction of more than 60% compared to fossil alternatives; and a comprehensive Techno-Economic Analysis (TEA) that identifies limiting factors for commercial viability of a photobioreactor (PBR)-based biofuel product. The project achieved the overall objectives. Strain development efforts led to the identification of a strain (Cyanobacterium sp. AB1166) that, relative to the previous best strain (Cyanobacterium sp. AB1), exhibited a ~10% increase in productivity under commercially-relevant cultivation conditions and also resulted in cultures with a >50% reduction in viscosity such that harvesting efficiency was improved; these results represent achievement of key project milestones. Progress was also made at NREL in altering the biochemical composition of algal biomass to improve the yield of BFI produced via HTL. These strain enhancements coupled with improved outdoor cultivation practices, including semi-continuous operation, increased areal biomass productivity by nearly 80% over the established baseline productivity. The annualized productivity achieved (26.8 g/m2-d), paired with HTL conversion yields realized at NREL and RIL (38% ± 2% BFI), translates to 4,100 gal-BFI/acre-yr, exceeding the FY20 BETO goal of 3,700 gal-BFI/acre-yr. Significant progress was also demonstrated in large scale PBR-based production system design, operability, and cost reduction. A 24,000-L production module comprised of 240 interlinked PBRs was constructed and successfully operated outdoors for over one year in Fort Myers, Florida. Aided by a state-of-the-art productivity model, the productivities achieved convincingly demonstrated scalability of laboratory results determined at the mL to L scale to large-scale outdoor operations exceeding 20,000 L. The system was used to cultivate Arthrospira platensis (Spirulina), an industrially-relevant cyanobacterium and source for phycocyanin, an approved blue food colorant that Algenol is developing as a risk reduction strategy for future biofuel projects and as a potential business opportunity. A key project milestone to develop phycocyanin extraction and purification technologies was achieved ahead of schedule, and product samples received positive feedback from potential customers. The production and downstream operations data generated in this project were used to conduct and refine Techno-Economic and Life Cycle Assessments to provide research guidance for reducing the costs and environmental footprint of algal biofuel and co-product manufacturing plants. Several CO 2 supply scenarios for an algal biorefinery were identified as being capable of providing a large (>60%) reduction in carbon footprint in comparison to gasoline. The TEA assessments incorporated detailed comparisons of PBR versus open pond production systems, yielding a 3-fold higher areal productivity for PBRs and suggesting overall production cost parity for the two systems. The progress in this ABY2 project addressed many of the the barriers identified for the Advanced Algal Systems R&D Program and are directly relevant to achieving the established BETO goals associated with large scale biofuel production and cost reduction.

09 BIOMASS FUELS↗

Search for non-resonant production of semi-visible jets using Run 2 data in ATLAS

Semi-visible jets, with a significant contribution to the event's missing transverse momentum, can arise in strongly interacting dark sectors. This results in an event topology where one of the jets can be aligned with the direction of the missing transverse momentum. The first search for semi-visible jets produced via a t-channel mediator exchange is presented. The analysis uses proton-proton collisions with an integrated luminosity of 139 fb —1 and a centre-of-mass energy of 13 TeV, collected with the ATLAS detector during the Run 2 of the LHC. No excess over Standard Model predictions is observed. Assuming a coupling strength of unity between the mediator, a Standard Model quark and a dark quark, mediator masses up to 2.7 TeV are excluded at the 95% confidence level. Upper limits on the coupling strength are also derived.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Data for Soil Fertility Management for Sustainable Miscanthus × giganteus Production: Increased Tiller Weight from Nitrogen Management Explains Yield Gains in Aged Miscanthus

Aging-related yield decline in Miscanthus × giganteus (miscanthus) remains a major constraint to sustainable biomass production. This study evaluated how nitrogen (N) management and soil fertility influence yield-component traits and productivity in aging miscanthus. Trials were conducted at two sites established in 2008 at the University of Illinois Energy Farm, Urbana, IL. (i) The Sun Grant trial received 0, 60, and 120 kg N ha−1 annually until 2015. Starting 2021, half of each plot received 60 or 120 kg N ha−1, resulting in six legacy-contemporary treatments: 0N–0N, 0N–120N, 60N–0N, 60N–60N, 120N–0N, 120N–120N. (ii) The Energy Farm trial remained unfertilized until 2014, when one half of each plot received 56 kg N ha−1, forming two treatments: 0N–0N, 0N–56N. Sun Grant trial results showed N fertilization increased tiller density (tillers m−2) and tiller weight (g tiller−1) in juvenile to early-mature miscanthus (2011–2015). After N withdrawal, both traits declined (20 % and 40 %), though legacy effects persisted in tiller weight in the aging stands (2020–2023). Contemporary N had little effect on tiller density but increased tiller weight by 34 %–77 %, resulting in 23 %–106 % higher machine-harvested biomass yield in 0–120N, 60-60N, and 120-120N plots. At the Energy Farm trial, 0N–56N plots yielded 59 %–108 % more biomass than 0N–0N. Soil total N increased (Sun Grant: 47 % by 2020; Energy Farm: 58 % by 2023), while Mehlich-3 P (42 %–44 %) and K (21 %–46 %) declined. These findings identify tiller weight as a key determinant of biomass yield in aging miscanthus and highlight the need for P and K management for long-term productivity.

miscanthus↗

Narrow-linewidth laser cooling for rapid production of low-temperature atoms for high data-rate quantum sensing

We present a proof-of-concept demonstration of a narrow linewidth $^{87}$Rb magneto-optical trap (MOT) operating on the narrow linewidth $5S_{1/2}$ → $6P_{3/2}$ transition at 420 nm. We stabilized the absolute frequency of the 420 nm laser to an atomic transition in $^{87}$Rb and demonstrate a MOT using 420 nm light driving the $5S_{1/2}$, $F = 2$ → $6P_{3/2}, F' = 3$ transition. We then use tome-of-flight measurements to characterize the 420 nm MOT temperature, observing a minimum temperature of about $T^{(420)}_{horizontal}$ = 150μK and $T^{(420)}_{vertical}$ = 250μK before the opportunity to perform significant characterization and optimization. Although this temperature is significantly higher then the expected 420 nm Doppler cooling limit ($T_D^{(420)}$ ≈ 34 μK), these are already approaching the Doppler limit of a standard 780 nm MOT ($T_D^{(780)}$ ≈ 146 μK). We believe that with further optimization the Doppler cooling limit of ≈ 34 μK can be achieved. This initial result answers our key research question and demonstrates the viability of applying narrow linewidth laser cooling as a robust technique for future fieldable quantum sensors.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

A unified ensemble soil moisture dataset across the continental United States

Abstract A unified ensemble soil moisture (SM) package has been developed over the Continental United States (CONUS). The data package includes 19 products from land surface models, remote sensing, reanalysis, and machine learning models. All datasets are unified to a 0.25-degree and monthly spatiotemporal resolution, providing a comprehensive view of surface SM dynamics. The statistical analysis of the datasets leverages the Koppen-Geiger Climate Classification to explore surface SM’s spatiotemporal variabilities. The extracted SM characteristics highlight distinct patterns, with the western CONUS showing larger coefficient of variation values and the eastern CONUS exhibiting higher SM values. Remote sensing datasets tend to be drier, while reanalysis products present wetter conditions. In-situ SM observations serve as the basis for wavelet power spectrum analyses to explain discrepancies in temporal scales across datasets facilitating daily SM records. This study provides a comprehensive soil moisture data package and an analysis framework that can be used for Earth system model evaluations and uncertainty quantification, quantifying drought impacts and land–atmosphere interactions and making recommendations for drought response planning.

54 ENVIRONMENTAL SCIENCES↗

The fortedata R package: open-science datasets from a manipulative experiment testing forest resilience

The fortedata R package is an open data notebook from the Forest Resilience Threshold Experiment (FoRTE) – a modeling and manipulative field experiment that tests the effects of disturbance severity and disturbance type on carbon cycling dynamics in a temperate forest. Package data consist of measurements of carbon pools and fluxes and ancillary measurements to help analyze and interpret carbon cycling over time. Currently the package includes data and metadata from the first three FoRTE field seasons, serves as a central, updatable resource for the FoRTE project team, and is intended as a resource for external users over the course of the experiment and in perpetuity. Further, it supports all associated FoRTE publications, analyses, and modeling efforts. This increases efficiency, consistency, compatibility, and productivity while minimizing duplicated effort and error propagation that can arise as a function of a large, distributed and collaborative effort. More broadly, fortedata represents an innovative, collaborative way of approaching science that unites and expedites the delivery of complementary datasets to the broader scientific community, increasing transparency and reproducibility of taxpayer-funded science. The fortedata package is available via GitHub: https://github.com/FoRTExperiment/fortedata (last access: 19 February 2021), and detailed documentation on the access, used, and applications of fortedata are available at https://fortexperiment.github.io/fortedata/ (last access: 19 February 2021). The first public release, version 1.0.1 is also archived at https://doi.org/10.5281/zenodo.4399601 (Atkins et al., 2020b). All data products are also available outside of the package as .csv files: https://doi.org/10.6084/m9.figshare.13499148.v1 (Atkins et al., 2020c).

97 MATHEMATICS AND COMPUTING↗

Big Data Analytics for Long-Term Meteorological Observations at Hanford Site

A growing number of physical objects with embedded sensors with typically high volume and frequently updated data sets has accentuated the need to develop methodologies to extract useful information from big data for supporting decision making. This study applies a suite of data analytics and core principles of data science to characterize near real-time meteorological data with a focus on extreme weather events. To highlight the applicability of this work and make it more accessible from a risk management perspective, a foundation for a software platform with an intuitive Graphical User Interface (GUI) was developed to access and analyze data from a decommissioned nuclear production complex operated by the U.S. Department of Energy (DOE, Richland, USA). Exploratory data analysis (EDA), involving classical non-parametric statistics, and machine learning (ML) techniques, were used to develop statistical summaries and learn characteristic features of key weather patterns and signatures. The new approach and GUI provide key insights into using big data and ML to assist site operation related to safety management strategies for extreme weather events. Specifically, this work offers a practical guide to analyzing long-term meteorological data and highlights the integration of ML and classical statistics to applied risk and decision science.

54 ENVIRONMENTAL SCIENCES↗

Agricultural crop and residue production by county - mature-market medium scenario at $70

This dataset contains data on agricultural crop and residue production by county from 2022 to 2041. The agricultural crop in this dataset includes barley, biomass sorghum, corn, cotton, energy cane, eucalyptus, grain sorghum, hay, miscanthus, oats, pine, poplar, rice, soybean, switchgrass, wheat, and willow, and the agricultural residue includes barley straw, corn stover, oats straw, sorghum stubble, and wheat straw. The dataset was obtained from the database of the BT23 (Davis et al., 2024) for the mature-market medium scenario with biomass market prices of up to $70 per dry ton.

agricultural production↗

Uranium integral fission product yields for a spectrally-shaped 14.1 MeV neutron source at the National Ignition Facility

This paper describes the experimental results for an energy tuning assembly created to modify the National Ignition Facility deuterium–tritium fusion neutron source into a notional thermonuclear and prompt fission neutron spectrum, which has applications in integral measurements, nuclear data benchmarks, and radiation effects on microelectronics. The Monte Carlo neutron transport utilized MCNP5 to estimate the ETA-modified fluence using the ENDF-B/VIII.0 and IRDFF-II continuous energy nuclear data libraries, and SCALE Sampler was used to estimate the systematic nuclear data covariance using ENDF-B/VII.1 and IRDFF-II in a 252-group structure. The experiment fielded eight activation foils and a highly enriched uranium sample. This provided fifteen reaction channels that were used in a forward-fit comparison to the modeled results and to unfold the neutron spectrum using STAYSL. Gamma-ray spectrometry was performed on the activation and highly enriched uranium foils, and the reduced Χ 2 between the modeled and experimental values was 1.21. The results from the STAYSL unfold, reduced Χ 2 = 1.62, indicated that the modeled neutron spectrum was achieved and the systematic nuclear data uncertainty associated with the neutron transport and activation product cross sections was representative of the experiment. Integral cumulative fission product yield data were collected for 37 mass chains with a combination of gamma-ray spectrometry and radiochemical analysis. Fission product analysis was generally in agreement with two models using a semi-empirical fit and the General Observables of Fission code, with the exception of mass chains 88, 109, 111, 112, 113, 129, 139, 142, 144, 151, and 156.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

Interim Report on FY22 ORNL A709 Welding Research and Testing of Production Welds in Support of Developing ASME A709 Code Case Data Package

As part of the Alloy 709 ASME Code Case development effort under the Advanced Reactor Technologies (ART) Program, this work covers the development of the technical basis for weld fabrication and weld qualification of Alloy 709. This report summarizes the Alloy 709 welding research conducted at Oak Ridge National Laboratory (ORNL) in FY 2022. Two new production welds were fabricated on two commercial heats of Alloy 709 of different phosphorus (P) levels using Alloy 709 filler metal with P content less than 20 wppm with gas tungsten arc welding (GTAW). Both production welds successfully passed ASME Section IX weld qualification tests, and this concludes the Alloy 709 welding procedure development to scale up to 2-in thick plates. In FY 2022, we also demonstrated the success in welding of high P commercial Alloy 709 plates with weld wires having higher P content at 30 wppm. A test weld fabricated with the 30 wppm weld wire on the first commercial heat (140 wppm P) passed all weld qualification tests without issues. Additionally, experiment setup and testing procedure of the circular patch weldability test has been developed, for evaluating the P effect in weld wire on solidification cracking susceptibility of Alloy 709 weld, with the preliminary results summarized in this report. Research on further relaxing the P level restriction beyond 30 wppm are planned in FY 2023. The preliminary cross-weld creep tests results continue to show little or no creep strength reduction relative to the base metal.

36 MATERIALS SCIENCE↗