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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Region and cloud regime dependence of parametric sensitivity in E3SM atmosphere model

Abstract The Department of Energy (DOE)’s Energy Exascale Earth System Model (E3SM), including its atmosphere model (EAM), has many relatively new features. In a previous study we conducted a systematic parametric sensitivity analysis for EAM based on short, perturbed parameter ensemble (PPE) simulations, mainly focusing on global mean climate features and metrics. While parameter values in global climate models are generally invariant in space and time, model response to parameters perturbation may vary by regions and climate regimes, which motivates the need to better understand the EAM model behaviors and physics at regional scale and process level. In this study, using the same set of PPE simulations and a similar sensitivity analysis framework, we identify parameters that cause largest sensitivities over different regions and compare model responses in fast atmospheric processes to the parameters across different cloud regimes for several important cloud-related fidelity metrics. We find that cloud forcing has opposite response to some parameters over mid-latitude vs. tropical land. We also analyze how the parametric sensitivity varies as stratocumulus transitions to shallow convection and to deep convection over ocean. Low cloud forcing and shortwave cloud forcing in the subtropical eastern Pacific are most sensitive to the parameters controlling the width of the probability density function (PDF) of the subgrid vertical velocity ( w’ ) ( gamma ) and the damping of the w’ skewness ( c8 ) near the coast but become more sensitive to the parameter affecting the damping of the w’ variance ( c1 ) further offshore. Detailed interpretation of the spatial dependence of parametric sensitivity is provided. We also investigate how the parametric sensitivity evolves with prediction duration. This study improves our process-level understanding of cloud physics and parameterization and provides insights for developing more advanced regime-aware parameterization schemes in global climate model.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Influence of Tibetan Plateau sensible heat on pre-monsoon dust burdens over South Asia: Observational and modeling evidence

Tibetan Plateau sensible heating (TPSH) effect is recognized as a key driver of the South Asian climate; however its role in regulating the regional dust burdens over South Asia during the pre-monsoon season remains unclear. Using long-term reanalysis and/or observational dust and TPSH data, we show that the dust optical depth at 550 nm (DOD 550 ) over South Asia is significantly positively correlated with TPSH at the interannual scale. DOD 550 over South Asia increases (decreases) by 20 % (12 %) in the strongest (weakest) TPSH years. The phenomenon of TPSH-dust relationships is reinforced by sensitivity experiments by altering TPSH from global climate models. Further mechanism analysis reveals that TPSH perturbation induces regional circulation anomalies over South Asia, which features a low-tropospheric cyclonic response around the Tibetan Plateau. This cyclonic anomaly strengthens the prevailing northwesterly winds, increasing regional dust emissions and transportation over South Asia. This novel mechanism helps understand the South Asian dust change.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Reaction Mechanism Generator v3.0: Advances in Automatic Mechanism Generation

In chemical kinetics research, kinetic models containing hundreds of species and tens of thousands of elementary reactions are commonly used to understand and predict the behavior of reactive chemical systems. Reaction Mechanism Generator (RMG) is a software suite developed to automatically generate such models by incorporating and extrapolating from a database of known thermochemical and kinetic parameters. Here, we present the recent version 3 release of RMG and highlight improvements since the previously published description of RMG v1.0. Most notably, RMG can now generate heterogeneous catalysis models in addition to the previously available gas- and liquid-phase capabilities. For model analysis, new methods for local and global uncertainty analysis have been implemented to supplement first-order sensitivity analysis. The RMG database of thermochemical and kinetic parameters has been significantly expanded to cover more types of chemistry. The present release includes parallelization for faster model generation and a new molecule isomorphism approach to improve computational performance. RMG has also been updated to use Python 3, ensuring compatibility with the latest cheminformatics and machine learning packages. Overall, RMG v3.0 includes many changes which improve the accuracy of the generated chemical mechanisms and allow for exploration of a wider range of chemical systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Response of Ecosystem Productivity to High Vapor Pressure Deficit and Low Soil Moisture: Lessons Learned From the Global Eddy-Covariance Observations

Although there is mounting concern about how high vapor pressure deficit (VPD) and low soil moisture (SM) affect ecosystem productivity, their relative importance is still under debate. Here, we comprehensively quantified the relative impacts of these two factors on ecosystem gross primary production (GPP) using observations from a global network of eddy-covariance towers and two approaches (sensitivity analysis and linear regression model). Both approaches agree that a higher percentage of sites experience GPP reduction from high VPD than from low SM over the growing season. However, the constraint of high VPD and low SM on GPP reduction is tightly linked with climates and plant functional types. Humid and mesic ecosystems including forests and grasslands are dominated by VPD, while the semi-arid and arid ecosystems including shrublands and savannas are dominated by SM. The varying dominant role of these two factors on GPP is closely related to plant stomatal behavior, as predicted by a stomatal conductance model. Additionally, we highlight the non-linear impact of SM on GPP during droughts and the possible underestimation of the SM effects for deep-rooted plants when only using surface-layer SM. Our results shed light on a better understanding of the impacts of VPD and SM on vegetation productivity, with important implications for modeling the response and feedback of ecosystem dynamics to current and future climates.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

A Flexible Quasi-Static Mooring Design Optimization Method for Floating Structures

This paper presents a flexible and efficient design method for optimizing the mooring systems of floating structures. Mooring system optimization is challenging because of the strong nonlinearity of mooring system behavior and the many technical constraints that must be satisfied. Furthermore, different mooring configurations can have very different design spaces. While some successful examples of mooring design optimization exist in the literature, developing an optimization approach that can work across various mooring design problems is a larger challenge. We present such a method based on a flexible parameterization that allows a wide variety of mooring designs to be described by a list of variables, a quasi-static mooring model that provides efficient evaluation of a mooring design without directly considering mooring system dynamics, and an optimization framework that generates, evaluates, and adjusts the mooring design while considering user-specified constraints such as offset limits, strength safety factors, and seabed contact limits. We demonstrate the design optimization framework on four mooring design problems, each for a different type of mooring system. We compare the use of different design modes to simplify the optimization problem, showing that they can reduce the computation time by up to 75%. We also compare different optimization algorithms and find that the resulting computational speed can vary by up to 51 times. We perform a sensitivity study on one design and find that the local sensitivity of anchoring radius to water depth has a positive correlation of 0.29, but the global sensitivity shows large nonlinearities. Lastly, we perform a coupled dynamic analysis on one of the optimized designs and find that the predicted mean platform motions and mooring line tensions are within 1% of dynamic results and the extreme motions and tensions are within 14%. Lastly, we show that a DEA-Chain-Polyester mooring configuration is cost-optimal for the given design problem of the demonstrations, which aligns with general industry practice.

16 TIDAL AND WAVE POWER↗
DOE OSTI2023

Assessing sensitivities of climate model weighting to multiple methods, variables, and domains in the south-central United States

Given the increasing use of climate projections and multi-model ensemble weighting for a diverse array of applications, this project assesses the sensitivities of climate model weighting strategies and their resulting ensemble means to multiple components, such as the weighting schemes, climate variables, or spatial domains of interest. The purpose of this study is to assess the sensitivities associated with multi-model weighting strategies. The analysis makes use of global climate models from the Coupled Model Intercomparison Project Phase 5 (CMIP5) and their statistically downscaled counterparts created with the localized constructed analogs (LOCA) method. This work focuses on historical and projected future mean precipitation and daily high temperatures of the south-central United States. Results suggest that the model weights and the corresponding weighted model means can be sensitive to the weighting strategy that is applied. For instance, when estimating model weights based on Louisiana precipitation, the weighted projections show a wetter and cooler south-central domain in the future compared to other weighting strategies. Alternatively, for example, when estimating model weights based on New Mexico temperature, the weighted projections show a drier and warmer south-central domain in the future. However, when considering the entire south-central domain in estimating the model weights, the weighted future projections show a compromise in the precipitation and temperature estimates. As for uncertainty, our matrix of results provided a more certain picture of future climate compared to the spread in the original model ensemble. If future impact assessments utilize weighting strategies, then our findings suggest that how the specific weighting strategy is used with climate projections may depend on the needs of an impact assessment or adaptation plan.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

The Determinants of Offshore Wind's Role in a Future U.S. Energy System: A Preliminary Modeling Sensitivity Analysis [Slides]

Offshore wind is an emerging industry in the with rapidly changing technology advancements and an accelerating global deployment. Policy demands and interest in the United States has grown, but the long-term future for offshore wind remains uncertain. This study is designed to evaluate offshore wind's potential role in the future U.S. energy system. The analysis uses long-term power system models to assess a wide-range of power system possibilities. Specific objectives of the analysis are to: (1) identify the determinants of offshore wind deployment under different scenarios and (2) understand the impacts of substantial levels of offshore wind deployment on the power system. We also highlight future research needs for more robust understanding the opportunities and challenges to U.S. offshore wind development.

17 WIND ENERGY↗
DOE OSTI2022

Global dipole symmetry, compact Lifshitz theory, tensor gauge theory, and fractons

We study field theories with global dipole symmetries and gauge dipole symmetries. The famous Lifshitz theory is an example of a theory with a global dipole symmetry. We study in detail its 1+1d version with a compact field. When this global symmetry is promoted to a $U(1)$ dipole gauge symmetry, the corresponding gauge field is a tensor gauge field. This theory is known to lead to fractons. In order to resolve various subtleties in the precise meaning of these global or gauge symmetries, we place these 1+1d theories on a lattice and then take the continuum limit. Interestingly, the continuum limit is not unique. Different limits lead to different continuum theories, whose operators, defects, global symmetries, etc. are different. We also consider a lattice gauge theory with a $\mathbb Z_N$ dipole gauge group. Surprisingly, several physical observables, such as the ground state degeneracy and the mobility of defects depend sensitively on the number of sites in the lattice. Our analysis forces us to think carefully about global symmetries that do not act on the standard Hilbert space of the theory, but only on the Hilbert space in the presence of defects. We refer to them as time-like global symmetries and discuss them in detail. Furthermore, these time-like global symmetries allow us to phrase the mobility restrictions of defects (including those of fractons) as a consequence of a global symmetry.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

Understanding PDF uncertainty in W boson mass measurements*

Abstract We study the dependence of the transverse mass distribution of charged leptons and the missing energy on parton distributions (PDFs) adapted to W boson mass measurements at the CDF and ATLAS experiments. We compare the shape variations of the distribution induced by different PDFs and find that the spread of predictions from different PDF sets can be significantly larger than the PDF uncertainty predicted by a specific PDF set. We suggest analyzing the experimental data using up-to-date PDFs to gain a better understanding of the PDF uncertainties in W boson mass measurements. We also perform a series of Lagrange multiplier scans to identify the constraints on the transverse mass distribution imposed by individual data sets in the CT18 global analysis. In the case of the CDF measurement, the distribution is mostly sensitive to d -quark PDFs in the intermediate x region, which are largely constrained by DIS and Drell-Yan data on deuteron targets and Tevatron lepton charge asymmetry data.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Gluon helicity from global analysis of experimental data and lattice QCD Ioffe time distributions

We perform a new global analysis of spin-dependent parton distribution functions with the inclusion of Ioffe time pseudodistributions computed in lattice QCD (LQCD), which are directly sensitive to the gluon helicity distribution, Δ g . These lattice data have an analogous relationship to parton distributions as do experimental cross sections, and can be readily included in global analyses. We focus in particular on the constraining capability of current LQCD data on the sign of Δ g at intermediate parton momentum fractions x , which was recently brought into question by analysis of data in the absence of parton positivity constraints. We find that present LQCD data cannot discriminate between positive and negative Δ g solutions, although significant changes in the solutions for both the gluon and quark sectors are observed. Published by the American Physical Society 2024

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Techno-Economic and life cycle assessment of standalone Single-Stream material recovery facilities in the United states

Material Recovery Facilities (MRFs) are crucial players in achieving a circular economy. MRFs receive complex waste streams and separate valuable recyclables from these mixtures. This study conducts techno-economic analysis (TEA) to estimate the net present value (NPV) and life cycle assessment (LCA) to estimate different environmental impacts of a commercial scale standalone, single-stream MRF to assess the economic feasibility and environmental impacts of recovering valuable recyclables from an MRF processing 120,000 tonnes per year (t/y). The TEA employs a discounted cash flow rate of return (DCFROR) analysis over a 20-year facility lifetime, along with a sensitivity analysis on the impact of different operating and economic parameters. Results show that the total fixed cost of building the MRF facility is $\$ $23 MM, and the operating cost is $\$ $45.48/tonne. Further the NPV of the MRF can vary from $\$ $3.57 MM to $\$ $60 MM, while 100-year global warming potential can range from 5.98 to 8.53 kg carbon dioxide equivalents (CO2-eq) per tonne of MSW. We have also found that MSW composition (arising from regional effects) significantly impacts costs, 100-year global warming potential, and other impact categories such as acidification potential, eutrophication potential, ecotoxicity, ozone depletion, photochemical oxidation, carcinogenic effects, and non-carcinogenic effects. Sensitivity and uncertainty analysis indicate that waste composition and market prices significantly impact the profitability of the MRF, and the waste composition mostly impacts global warming potential. Our analysis also indicates that facility capacity, fixed capital cost, and waste tipping fees are vital parameters that affect the economic viability of MRF operations.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Vegetation-induced asymmetric diurnal land surface temperatures changes across global climate zones

Unprecedented global vegetation greening during past decades is well known to affect annual and seasonal land surface temperatures (LST). However, the impact of observed vegetation cover change on diurnal LST across global climatic zones is not well understood. In this study, using global climatic time-series datasets, we investigated the long-term growing season daytime and nighttime LST changes globally and explored associated dominant contributors including vegetation and climate factors including air temperature, precipitation, and solar radiation. Results revealed asymmetric growing season mean daytime and nighttime LST warming (0.16 °C/10a and 0.30 °C/10a, respectively) globally from 2003 to 2020, as a result, the diurnal LST range (DLSTR) declined at 0.14 °C/10a. The sensitivity analysis indicated the LST response to changes in LAI, precipitation, and SSRD mainly concentrated during daytime instead of nighttime, however, which showed comparable sensitivities for air temperature. Combining the sensitivities results and the observed LAI and climate trends, we found rising air temperature contributes to 0.24 ± 0.11 °C/10a global daytime LST warming and 0.16 ± 0.07 °C/10a nighttime LST warming, turns to be the dominant contributor to the LST changes. Increased LAI cooled global daytime LST (–0.068 ± 0.096 °C/10a) while warmed nighttime LST (0.064 ± 0.046 °C/10a); hence LAI dominates declines in DLSTR trends (–0.12 ± 0.08 °C/10a), despite some daynight process variations across climate zones. In Boreal regions, reduced DLSTR was due to nighttime warming from LAI increases. In other climatic zones, daytime cooling, and DLSTR decline, was induced by increased LAI. Biophysically, the pathway from air temperature heats the surface through sensible heat and increased downward longwave radiation during day and night, while the pathway from LAI cools the surface by enhancing energy redistribution into latent heat rather than sensible heat during the daytime. These empirical findings of diverse asymmetric responses could help calibrate and improve biophysical models of diurnal surface temperature feedback in response to vegetation cover changes in different climate zones.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Simulation of hardened cement degradation and estimation of uncertainty in predicted failure times with peridynamics

Modeling the degradation of cement-based infrastructure due to aqueous environmental conditions continues to be a challenge. In order to develop a capability to predict concrete infrastructure failure due to chemical degradation, here we created a chemomechanical model of the effects of long-term water exposure on cement paste. The model couples the mechanical static equilibrium balance with reactive–diffusive transport and incorporates fracture and failure via peridynamics (a meshless simulation method). The model includes fundamental aspects of degradation of ordinary Portland cement (OPC) paste, including the observed softening, reduced toughness, and shrinkage of the cement paste, and increased reactivity and transport with water induced degradation. This version of the model focuses on the first stage of cement paste decalcification, the dissolution of portlandite. Given unknowns in the cement paste degradation process and the cost of uncertainty quantification (UQ), we adopt a minimally complex model in two dimensions (2D) in order to perform sensitivity analysis and UQ. We calibrate the model to existing experimental data using simulations of common tests such as flexure, compression and diffusion. Then we calculate the global sensitivity and uncertainty of predicted failure times based on variation of eleven unique and fundamental material properties. We observed particularly strong sensitivities to the diffusion coefficient, the reaction rate, and the shrinkage with degradation. Also, the predicted time of first fracture is highly correlated with the time to total failure in compression, which implies fracture can indicate impending degradation induced failure; however, the distributions of the two events overlap so the lead time may be minimal. Extension of the model to include the multiple reactions that describe complete degradation, viscous relaxation, post-peak load mechanisms, and to three dimensions to explore the interactions of complex fracture patterns evoked by more realistic geometry is straightforward and ongoing.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Nano-Engineered Catalyst Supported on Ceramic Hollow Fibers for the Utilization of CO 2 in Dry Reforming to Produce Syngas

The objective of this project was to develop a novel catalytic reactor containing nano-engineered catalysts for the utilization of CO 2 (captured from coal-fired power plants and other CO 2 emitting sources) in dry methane reforming (DMR) (CO 2 + CH 4 → 2 H 2 + 2 CO) to produce synthesis gas (syngas). The technology aims to reduce CO2 emissions by developing beneficial uses for CO 2 from coal-fired power plants. It also offers an alternative to mitigate CO 2 emissions in areas where geologic storage may not be an optimal solution and/or utilization could significantly offset the costs of carbon capture and sequestration. The nano-engineered Ni-based catalyst was prepared by atomic layer deposition (ALD). The Ni particles were as small as ~2-4 nm. The nano-engineered catalyst showed CH 4 conversion >95%, H 2 /CO ratio in the range of 0.7-1.0, and CH 4 reforming rate as high as 2,500 L/h/gNi at 850 ºC and pressure of 15-25 psia. The Ni-based ALD catalyst also showed good stability in DMR reaction during a 200-h continuous operation at 850 °C. This is due to strong bonding between the nanoparticles and substrates since the Ni nanoparticles were chemically bonded to the substrate during the ALD process. The high thermal stability maintains the high dispersion of Ni nanoparticles, which can inhibit coke formation because their step edges are small enough to limit carbon nucleation and growth. Technoeconomic analysis (TEA) indicates the levelized cost of syngas (LCOS) is $172/ton with our technology, which is lower than the equivalent (molar) cost of hydrogen produced by steam methane reforming (SMR) or autothermal reforming (ATR). The major operating cost is natural gas feed and fuel, and the levelized cost is highly sensitive to the price of natural gas and relatively insensitive to the CAPEX. Revenues from syngas could have a significant impact on the net cost of electricity (COE), depending on the cost of natural gas and the selling price of syngas, estimated at $36 per MWh if the syngas were sold at $195 per ton. Following DOE NETL’s guidance, a lifecycle analysis (LCA) was conducted to compare with SMR. The functional unit for the basis of comparison was defined as 1kg carbon monoxide in the product stream. The global warming potential (GWP) of our process was found to be 40% lower than the state-of-the-art SMR process. The sensitivity analysis confirms the emissions are most sensitive to the natural gas fuel requirements to deliver heat to the process.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2023

Current and Future Global Lake Methane Emissions: A Process‐Based Modeling Analysis

Abstract Freshwater ecosystem contributions to the global methane budget remains the most uncertain among natural sources. With warming and accompanying carbon release from thawed permafrost and thermokarst lake expansion, the increase of methane emissions could be large. However, the impact and relative importance of various factors related to warming remain uncertain. Based on diverse lake characteristics incorporated in modeling and observational data, we calibrate and verify a lake biogeochemistry model. The model is then applied to estimate global lake methane emissions and examine the impacts of temperature increase for the first and the last decades of the 21st century under different climate scenarios. We find that current emissions are 24.0 ± 8.4 Tg CH 4 yr −1 from lakes larger than 0.1 km 2 , accounting for 11% of the global total natural source as estimated based on atmospheric inversion. Future projections under the RCP8.5 scenario suggest a 58%–86% growth in emissions from lakes. Our model sensitivity analysis indicates that additional carbon substrates from thawing permafrost may enhance methane production under warming in the Arctic. Warming enhanced methane oxidation in lake water can be an effective sink to reduce the net release from global lakes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Ensemble modeling of global lake evaporation under climate change

Global projections of lake evaporation are typically based on simulations using single mechanistic models. However, because of its complex interactions with various lake physical properties, environmental and anthropogenic drivers, lake evaporation is highly variable and sensitive to the choice of model used. In this study, we present a multi-model analysis to investigate differences across global simulations of lake evaporation during the warm-season using three different lake models driven by outputs from four general circulation models (GCM) (i.e. 12 model combinations in total) for historic and future scenarios. Our results suggest substantial differences among lake-climate model simulations of lake evaporation. These differences varied throughout the 20th and 21st century, with model driver data explaining 74% of the variance in future projections of warm- season lake evaporation. Our projections indicate that, by the end of the 21st century (2070–2099), global annual lake evaporation rates will increase by 10–27% under Representative Concentration Pathways (RCPs) 2.6–8.5. Finally, we highlight the importance of using a multi-model approach for the prediction of future global lake evaporation responses to climate change.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Sensitivity Studies, Gap Analysis, and Benchmark Experiment Optimization for Reactor Physics and Criticality Safety Applications

Many new reactor designs, such as advanced reactors and micro reactors, have materials that lack nuclear data validation. This is also true for many other applications in criticality safety and global security. Both differential and integral experiments are needed to validate cross-section data. Without this, a user cannot have confidence in the predicted results of a radiation-transport code. This work describes an approach called ARCHIMEDES (Application Relevant Critical/Subcritical HEU/Pu-based Integral Measurements for Enhancing Data and Evaluating Sensitivities) to design new criticality experiments that have similar k eff cross-section sensitivities to an application of interest. This process involves simulations to generate cross-section sensitivities to a parameter of interest (such as k eff ), a gap analysis to determine which existing benchmarks are most similar to the application, and an experiment optimization. Recently, there has been a great deal of interest in the reactor physics community on advanced reactors, micro reactors, and accelerator driven systems (ADS). This work will apply the described method to specific examples in this area. The focus of this work will be on the sensitivity study and gap analysis, while future work will include experiment design.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

A Type II Hamiltonian Variational Principle and Adjoint Systems for Lie Groups

We present a novel Type II variational principle on the cotangent bundle of a Lie group which enforces Type II boundary conditions, i.e., fixed initial position and final momentum. In general, such Type II variational principles are only globally defined on vector spaces or locally defined on general manifolds; however, by left translation, we are able to define this variational principle globally on cotangent bundles of Lie groups. Type II boundary conditions are particularly important for adjoint sensitivity analysis, which is our motivating application. As such, we additionally discuss adjoint systems on Lie groups, their properties, and how they can be used to solve optimization problems subject to dynamics on Lie groups.

97 MATHEMATICS AND COMPUTING↗