SEARCH · Engineering Papers

Results for “conditional shift”

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.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 37 records · Page 2

All sources NASA NTRS DOE OSTI

DOE OSTI2025

Dependence of ion-cyclotron range of frequencies instabilities on species mix and fast-ion distribution: I. Stability

Ion cyclotron emission (ICE) driven by fast ions has the potential to be a reactor relevant diagnostic of confined and escaping fast ions; moreover, controlled experiments in magnetic fusion devices can shed light on similar magnetospheric instabilities below and above the ion cyclotron frequency f ci . Dedicated DIII-D experiments studied instabilities below f ci and at cyclotron harmonics l f ci by injecting thirteen different neutral beam populations into plasmas with different thermal compositions of H, D, and 3He at five different values of toroidal field. High-frequency magnetic loops diagnose mode properties. Each beam type is individually injected for an approximate slowing-down time (~100 ms), resulting in a database of 2529 conditions that are analyzed in frequency bands corresponding to ICE harmonics and < f ci global Alfvén eigenmodes. The sub-cyclotron modes are more unstable at low field and in plasmas with large H concentration. For D injection, first harmonic ICE at f cD is more unstable in hydrogen plasmas but, for H injection, the converse is true (ICE at f cH is more unstable in D), suggesting that thermal same-species ions damp fundamental ICE. ICE stability also depends upon the pitch-angle anisotropy gradient and upon the ‘bump-on-tail’ gradient ∂f/∂v. Although the frequency of unstable ICE in these plasmas always occurs near the central cyclotron frequency, the precise value also depends on the Alfvén speed and beam direction, consistent with the idea that instability occurs for modes that simultaneously satisfy ω ≃ 2πlf ci , the magnetosonic dispersion relation, and the Doppler-shifted resonance condition.

electromagnetic ion cyclotron instabilities↗

DOE OSTI2025

Intermediate-Temperature Reverse Water–Gas Shift under Process-Relevant Conditions Catalyzed by Dispersed Alkali Carbonates

Not Available

Tamakuwala, Kesha N.↗

DOE OSTI2025

Climate-driven succession in marine microbiome biodiversity and biogeochemical function

Abstract Seasonal and El Niño-Southern Oscillation (ENSO) warming result in similar ocean changes as predicted with climate change. Climate-driven environmental cycles have strong impacts on microbiome diversity, but impacts on microbiome function are poorly understood. Here we quantify changes in microbial genomic diversity and functioning over 11 years covering seasonal and ENSO cycles at a coastal site in the southern California Current. We observe seasonal oscillations between large-genome lineages during cold, nutrient rich conditions in winter and spring versus small-genome lineages, including Prochlorococcus and Pelagibacter , in summer and fall. Parallel interannual changes separate communities depending on ENSO condition. Biodiversity shifts translate into clear oscillations in microbiome functional potential. Ocean warming induced an ecosystem with less iron but more macronutrient stress genes, depressed organic carbon degradation potential and biomass, and elevated carbon-to-nutrient biomass ratios. The consistent microbial response observed across time-scales points towards large climate-driven changes in marine ecosystems and biogeochemical cycles.

Larkin, Alyse A. (ORCID:0000000344660791)↗

DOE OSTI2024

Microbial polyphenol metabolism is part of the thawing permafrost carbon cycle

Abstract With rising global temperatures, permafrost carbon stores are vulnerable to microbial degradation. The enzyme latch theory states that polyphenols should accumulate in saturated peatlands due to diminished phenol oxidase activity, inhibiting resident microbes and promoting carbon stabilization. Pairing microbiome and geochemical measurements along a permafrost thaw-induced saturation gradient in Stordalen Mire, a model Arctic peatland, we confirmed a negative relationship between phenol oxidase expression and saturation but failed to support other trends predicted by the enzyme latch. To inventory alternative polyphenol removal strategies, we built CAMPER, a gene annotation tool leveraging polyphenol enzyme knowledge gleaned across microbial ecosystems. Applying CAMPER to genome-resolved metatranscriptomes, we identified genes for diverse polyphenol-active enzymes expressed by various microbial lineages under a range of redox conditions. This shifts the paradigm that polyphenols stabilize carbon in saturated soils and highlights the need to consider both oxic and anoxic polyphenol metabolisms to understand carbon cycling in changing ecosystems.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Unravelling the origin of reaction-driven aggregation and fragmentation of atomically dispersed Pt catalyst on ceria support

Metal–support interaction plays a crucial role in governing the stability and activity of atomically dispersed platinum catalysts on ceria support. The migration and aggregation of platinum atoms during the catalytic reaction leads to the redistribution of active sites. In this study, by utilizing a multimodal characterization scheme, we observed the aggregation of platinum atoms at high temperatures under reverse water gas shift reaction conditions and the subsequent fragmentation of platinum clusters, forming “single atoms” upon cooling. Theoretical simulations of both effects uncovered the roles of carbon monoxide binding on perimeter Pt sites in the clusters and hydrogen coverage in the aggregation and fragmentation mechanisms. Finally, this study highlights the complex effects of adsorbate and supports interactions with metal sites in Pt/ceria catalysts that govern their structural transformations under in situ conditions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

Switchable client specificity in a dual functional chaperone coordinates light-harvesting complex biogenesis

The proper assembly of light-harvesting complexes (LHCs) is critical for photosynthesis and requires the biogenesis of light-harvesting chlorophylla,b-binding proteins (LHCPs) to be coordinated with chlorophyll (Chl) biosynthesis. The mechanism underlying this coordination is not well understood. Here, we show that a conserved molecular chaperone, chloroplast signal recognition particle 43-kDa protein (cpSRP43), provides a molecular thermostat that helps maintain this coordination. cpSRP43 undergoes a conformational rearrangement between a well-folded closed state and a partially disordered open state. Closed cpSRP43 is dedicated to the biogenesis of LHCPs, whereas open cpSRP43 protects multiple Chl biosynthesis enzymes from heat-induced destabilization. Rising temperature shifts cpSRP43 to the open state, enabling it to protect heat-destabilized Chl biosynthesis enzymes. Our results reveal the molecular basis of a posttranslational mechanism for the thermoadaptation of LHC biogenesis. They also demonstrate how an adenosine triphosphate–independent chaperone uses conformational dynamics to switch its activity and client selectivity, thereby adapting to different proteostatic demands under shifting environmental conditions.

Science & Technology - Other Topics↗

DOE OSTI2024

Generalized boost transformations in finite volumes and application to Hamiltonian methods

The investigation of hadron interactions within lattice QCD has been facilitated by the well-known quantisation condition, linking scattering phase shifts to finite-volume energies. Additionally, the ability to utilise systems at finite total boosts has been pivotal in smoothly charting the energy-dependent behaviour of these phase shifts. The existing implementations of the quantization condition at finite boosts rely on momentum transformations between rest and moving frames, defined directly in terms of the energy eigenvalues. This energy dependence is unsuitable in the formulation of a Hamiltonian. In this work, we introduce a novel approach to generalise the three-momentum boost prescription, enabling the incorporation of energy-independent finite-volume Hamiltonians within moving frames. We demonstrate the application of our method through numerical comparisons, employing a phenomenological ππ scattering example.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2025

Unraveling metabolism underpinning biomass composition shift in Scenedesmus obliquus under simulated outdoor conditions using 13 C-fluxomics

To render the resulting biomass more attractive and amenable for utilization as the basis for low-carbon intensity bioproducts, single-celled algae need to be biochemically and metabolically poised to assimilate and store the delivered carbon in the fastest and most efficient manner. Accelerating biochemical carbon storage, as primarily carbohydrates or lipids, is critical to achieve the high carbon capture potential that is assigned to algae. To guide strain optimization and engineering for maximizing carbon capture and storage, it is essential to elucidate the link between carbon metabolism and biomass composition. Most published metabolomics work in algae remains largely restricted to ideal and simplified environmental conditions in model organisms, thereby limiting their translation to outdoor implementation. In this work, we utilize 13 C isotopic labeling to characterize distinct intracellular metabolic fluxes before, during, and after nitrogen depletion-induced compositional shifts in Scenedesmus obliquus UTEX 393. The results indicate that a transition to carbohydrates is characterized by diverting flux to starch instead of replenishing the Calvin cycle for CO 2 fixation whereas the subsequent transition to lipids is fueled by NADPH produced by upregulating the phosphoenolpyruvate carboxylase (PEPC)–malic enzyme (ME) cycle flux. Our work highlights bottlenecks to carbohydrate- and lipid-rich biomass and can guide implementable strategies to control the fate of fixed carbon in S. obliquus.

09 BIOMASS FUELS↗

DOE OSTI2025

Risk-informed Graded Approach for Reliability and Performance Assessment of Machine Learning and Artificial Intelligence for Advanced Condition Monitoring Techniques

With the shift away from time-based maintenance and toward condition-based maintenance, and to reduce overall maintenance costs, there has been an upsurge in the usage and development of advanced condition monitoring (ACM) techniques for real-time monitoring of nuclear power plant (NPP) components. ACM is particularly useful in the development of digital twins, which are designed to predict the failure or degradation of plant components. Successful implementation of ACM requires an assessment to inform the development of a risk-informed approach to evaluate the use of ACM to meet Nuclear Regulatory Committee (NRC) regulations for in-service testing (IST) programs. This includes the monitoring and diagnostics of reactor components and systems in current, new, and advanced reactors. A key component in ACM is the usage of machine learning (ML) and artificial intelligence (AI) algorithms that can employ real-time data from instrumentation and sensors to detect and predict reactor component degradations. Such predictive capabilities enable early detection of component degradation so as to help plant personnel plan and execute necessary maintenance. For successful implementation of ML/AI in ACM such that regulatory requirements are met, a risk-informed graded approach is needed to assess the reliability and performance of ML/AI for ACM. The American Society for Mechanical Engineers (ASME) developed their Operations and Maintenance (O&M) Code to provide guidance on safe, reliable O&M of NPPs. The IST section of the O&M Code specifically establishes requirements for IST and examination to gauge operational readiness of components in water-cooled NPPs. This paper presents a state-of-the-art review of how reliability and risk assessment can be integrated with ACM to assess component performance by non-nuclear industries. This is followed by different methodologies and approaches for conducting performance and reliability assessments so as to meet IST requirements for NPP components.

97 - MATHEMATICS AND COMPUTING↗

DOE OSTI2025

Risk-informed Graded Approach for Reliability and Performance Assessment for Advanced Condition Monitoring Techniques

99 - GENERAL AND MISCELLANEOUS↗

DOE OSTI2025

Analysis of the weighted shifted boundary method for the Poisson and Stokes problems

The Shifted Boundary Method (SBM) belongs to the class of unfitted (or immersed, or embedded) finite element methods, and relies on reformulating the original boundary value problem over a surrogate (approximate) computational domain. Accuracy is maintained by properly shifting the location and values of the boundary conditions. This avoids integration over cut cells and the associated implementation issues. Recently, the Weighted SBM (WSBM) was proposed for the Navier-Stokes equations with free surfaces and the Stokes flow with moving boundaries. The attribute “weighted” in the name WSBM stems from the fact that its variational form is weighted with the elemental volume fraction of active fluid. The motivation for the development of the WSBM was the preservation of the volume of active fluid to a higher degree of accuracy, which in turn resulted in improved stability and robustness characteristics in moving-boundary, time-dependent simulations. In this article, we present the numerical analysis of the WSBM formulations for the Poisson and Stokes problems. We give mathematical conditions under which the bilinear forms defining the discrete variational formulations are uniformly coercive (Poisson problem) or inf-sup stable (Stokes problem). By these results, stability and optimal convergence is proven in the natural norm; L2-error estimates can also be derived.

Approximate domain boundaries↗

DOE OSTI2024

Data for: Time to anoxia: Observations and predictions of oxygen drawdown following coastal flood events

This dataset contains data and code associated with the paper Patel et al. "Time to anoxia: Observations and predictions of oxygen drawdown following coastal flood events".The coastal terrestrial-aquatic interface (TAI) is a highly dynamic system characterized by strong physical, chemical, and biological gradients. In particular, shifting soil redox conditions and consumption of terminal electron acceptors, due in part to dynamic hydrologic conditions, is a strong driver of carbon availability and transformations across TAIs. However, while redox dynamics are well described, our ability to quantitatively forecast rates of oxic to anoxic shifts in soils with different characteristics and inundation regimes is limited. We integrated field measurements, laboratory incubations, and model simulations to improve mechanistic understanding of oxygen consumption dynamics in coastal soils. Continuous in situ monitoring unexpectedly revealed that flooding caused temporary spikes in subsurface dissolved oxygen followed by rapid consumption in the wetlands. To further investigate these mechanisms in a controlled setting, we performed laboratory incubations using surface and subsurface soils from a TAI gradient (defined here as upland forest to transitional forest to wetland) in Western Lake Erie to measure oxygen consumption rates in TAI soils during flood events. In our experiments, wetland soils reached anoxia the fastest, in ∼ 9 h on average, whereas upland soils turned anoxic in ∼ 18 h. Subsurface upland soils did not turn anoxic even after two weeks of saturation in the lab, and their oxygen consumption patterns suggested carbon and/or nutrient limitation. These results are consistent with in-situ groundwater redox and oxygen measurements in the field, where wetland soils exhibited the highest rates of oxygen consumption along the TAI. Model simulations of oxygen consumption suggested that oxygen consumption had stronger abiotic controls in wetland soils but stronger biotic controls in upland soils, providing a useful framework for future incubation experiments. Microbial activity is a strong driver of oxygen consumption in TAI soils, although it is constrained by the availability of dissolved carbon in subsurface soils.This dataset contains a compressed (.zip) archive of the data and R scripts used for this manuscript. The dataset includes files in .csv format, which can be accessed and processed using MS Excel or R. This archive can also be accessed on GitHub at https://github.com/COMPASS-DOE/cmps-time_to_anoxia (DOI: 10.5281/zenodo.10815374).

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Prediction of Silicon Content in a Blast Furnace via Machine Learning: A Comprehensive Processing and Modeling Pipeline

Silicon content plays an important role in determining the operational efficiency of blast furnaces (BFs) and their downstream processes in integrated steelmaking; however, existing sampling methods and first-principles models are somewhat limited in their capability and flexibility. Current data-based prediction models primarily rely on a limited set of manually selected furnace parameters. Additionally, different BFs present a diverse set of operating parameters and state variables that are known to directly influence the hot metal’s silicon content, such as fuel injection, blast temperature, and raw material charge composition, among other process variables that have their own impacts. The expansiveness of the parameter set adds complexity to parameter selection and processing. This highlights the need for a comprehensive methodology to integrate and select from all relevant parameters for accurate silicon content prediction. Providing accurate silicon content predictions would enable operators to adjust furnace conditions dynamically, improving safety and reducing economic risk. To address these issues, a two-stage approach is proposed. First, a generalized data processing scheme is proposed to accommodate diverse furnace parameters. Second, a robust modeling pipeline is used to establish a machine learning (ML) model capable of predicting hot metal silicon content with reasonable accuracy. The method employed herein predicted the average Si content of the upcoming furnace cast with an accuracy of 91% among 200 target predictions for a specific furnace provisioned by the XGBoost model. This prediction is achieved using only the past shift’s operating conditions, which should be available in real time. This performance provides a strong baseline for the modeling approach with potential for further improvement through provision of real-time features.

Chemistry↗

DOE OSTI2022

Detailed Laboratory Evaluation of Electric Demand Load Shifting Potential of Controlled Heat Pump Water Heaters

The demand profile management of electric end uses is vital research for utilities and policymakers planning greenhouse gas emission reductions. In this study, detailed laboratory research was conducted on the load shifting potential of 4 grid-connected HPWHs and one electric resistance water heaters (ERWH). The testing applied different CTA-2045 shed and critical peak command designs under three water draw profiles. Highly-controlled laboratory experiments were conducted in Florida. One of the four HPWHs was a prototype incorporating the new CTA-2045-B protocol feature allowing ‘advanced’ load-up above tank setpoint. A three-hour morning (6 – 9 AM) and four-hour evening curtailment (4 – 8 PM) were defined as the shed or critical peak periods reflecting high-value control periods for utility coincident load for system-wide electric demand reductions. Tests were performed under baseline conditions (no load shift) and under varied load-shifting schemes, including load up and advanced load up, ahead of shed and critical peak commands. Data were collected from December 2020 – February 2022 in the laboratory and compared with field experiments in Florida and the Pacific Northwest. Grid-connected HPWHs were found to reduce peak demand by up to 0.47 kW compared to uncontrolled HPWH units, depending on time of day, control scheme, draw profile, and temperature cluster. The load up strategy demonstrated the ability of all units to utilize heat pump mode for extended periods ahead of peak events. Demand reductions for the HPWHs were much larger when compared with the ERWH— up to 1.64 kW with large hot water draws in winter.

Fenaughty, Karen↗

DOE OSTI2022

Comment on Comment on “Anomalous structural recovery in the near glass transition range in a polymer glass: Data revisited in light of temperature variability in vacuum oven‐based experiments”*

Abstract Cangialosi, Alegría, and Colmenero have made a comment on a paper of ours [Polym. Eng. Sci. 2022:1–13], in which we discussed the concern that the enthalpy recovery data reported by Cangialosi and co‐workers [Phys. Rev. Lett. 2013;111(9):095701] for polystyrene aged up to 15 K below glass transition temperature was anomalous and contradicted existing experimental results from the literature over a similar range of aging conditions. Their response shifts the focus away from the raised questions about their experimental results and attempts to invalidate the data that we cited in support of our argument. Here we respond to the comment and add additional analysis that suggests the structural recovery response of glassy materials exhibits smooth behavior over the full range of measurements, up to 7 or 8 logarithmic decades. We do this by referring to the work on the intrinsic isotherm down‐jump and memory responses of poly(vinyl acetate) between 40°C and 15°C over six logarithmic decades by Kovacs [Fortsch. Hochpolym. Fo. 1963;3(1/2):394–508], the small‐strain tensile creep of poly(vinyl chloride) quenched from 90°C to 40°C (approximately 40°C below T g ) over seven logarithmic decades from Struik [Polym Eng. Sci., 1977;17:165–173], and the volume recovery behavior for aging times up to 3 months in a temperature range between 95°C and −50°C by Greiner and Schwarzl [Rheol. Acta. 1984;23(4):378–395]. We also add discussion that an isothermal aging procedure using a vacuum oven is highly vulnerable to temperature errors due to the problem of good temperature control when the heat transfer mechanism is primarily radiative.

Jin, Shuang↗

DOE OSTI2022

Metabolic responses to increased temperatures in three semi-aquatic turtle species from the southeastern United States

Physiological maintenance of ectotherms is largely dependent on temperature. Abrupt changes in environmental conditions can cause shifts in energy budgets, with higher temperatures requiring more energy be devoted to maintenance functions, making less energy available for other activities. As a group, freshwater turtles are of conservation concern; thus, it is important to understand their physiological responses to temperature shifts, particularly given current climate change predictions. Here, we quantified metabolic rates (MR) for three species of semi-aquatic turtles that vary in their degree of terrestriality and propensity to aestivate: chicken turtles (Deirochelys reticularia), eastern mud turtles (Kinosternon subrubrum), and eastern musk turtles (Sternotherus odoratus). Metabolic trials were performed using a flow-through respirometer at three environmentally-relevant temperatures: 25°C, 30°C, and 35°C. As expected, MRs of turtles were significantly and positively associated with increases in mass and temperature. Pairwise comparisons revealed that D. reticularia exhibited significantly higher oxygen consumption rates (VO 2 ) relative to K. subrubrum, which had significantly higher VO 2 than S. odoratus. The combination of higher metabolic rates, the tendency to terrestrially aestivate, and declining quantity of high quality thermal habitats may place some semi-aquatic turtles at a disadvantage when considering future climate scenarios. Our findings, when combined with knowledge of other ecological traits, may be a useful tool for predicting relative sensitivities of turtle species to predicted climate change, particularly those species inhabiting seasonal wetlands.

Sternotherus odoratus↗

DOE OSTI2023

Quantifying the local adaptive landscape of a nascent bacterial community

Abstract The fitness effects of all possible mutations available to an organism largely shape the dynamics of evolutionary adaptation. Yet, whether and how this adaptive landscape changes over evolutionary times, especially upon ecological diversification and changes in community composition, remains poorly understood. We sought to fill this gap by analyzing a stable community of two closely related ecotypes (“L” and “S”) shortly after they emerged within the E. coli Long-Term Evolution Experiment (LTEE). We engineered genome-wide barcoded transposon libraries to measure the invasion fitness effects of all possible gene knockouts in the coexisting strains as well as their ancestor, for many different, ecologically relevant conditions. We find consistent statistical patterns of fitness effect variation across both genetic background and community composition, despite the idiosyncratic behavior of individual knockouts. Additionally, fitness effects are correlated with evolutionary outcomes for a number of conditions, possibly revealing shifting patterns of adaptation. Together, our results reveal how ecological and epistatic effects combine to shape the adaptive landscape in a nascent ecological community.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2025

The advanced evolution of massive stars

The nuclear rates for reactions involving 12 C and 16 O are key to computing the energy release and nucleosynthesis evolution of massive stars during their advanced burning phases. Ultimately, these burning rates shape the stellar structure and evolution and influence the nature of the compact objects produced at the end of the stellar life. We explore the implications of new nuclear reaction rates from both experimental and theoretical studies for 12 C(α, γ) 16 O, 12 C+ 12 C, 12 C+ 16 O, and 16 O+ 16 O reactions for massive stars. Our goal is to investigate how the chemical structure and nucleosynthesis evolve from the He-exhaustion stage to the O-burning phase and how these processes influence the ultimate stellar fate. We computed rotating and non-rotating models for stars of different masses at solar metallicity. We used the stellar evolution code GENEC, which includes a large network of nuclear reactions and isotopes involved in advanced phases, as well as updated rates for 12 C(α,γ) 16 O. For the three fusion reactions involving 12 C and 16 O, we considered new rates following a data-driven fusion suppression scenario (hereafter HIN(RES)) and new theoretical rates obtained with time-dependent Hartree-Fock (TDHF) calculations. The updated 12 C(α, γ) 16 O rates mainly impact the chemical structure evolution changing the 12 C/ 16 O ratio at He-exhaustion and have little effect on the CO core mass. This variation in the 12 C/ 16 O ratio is in some cases critical for predicting the final fate of the model, which is very sensitive to 12 C abundance, and in particular the 20 M ⊙ remnant may change from a black hole to a neutron star. The He-burning (C-burning) lifetime is also decreased (increased) by about −2% (+15%). The combined new rates for 12 C+ 12 C and 16 O+ 16 O fusion reactions according to the HIN(RES) model lead to shorter C- and O-burning lifetimes by ≈ − 10%, and −50%, respectively, and shift the ignition conditions to higher temperatures and densities. In contrast, the theoretical TDHF rates primarily affect C-burning, increasing its duration by about 30% and lowering the ignition temperature. These changes modify the chemical structure of the core, the size and duration of C-burning shells, and hence their compactness. They also impact the central and shell nucleosynthesis (by ±1 dex and by factors of ±2–10, respectively), while 12 C+ 16 O reaction rates variations remain the least important.

abundances↗