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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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

A new process sensitivity index to identify important system processes under process model and parametric uncertainty

Hydrological models are always composed of multiple components that represent processes key to intended model applications. When a process can be simulated by multiple conceptual-mathematical models (process models), model uncertainty in representing the process arises. While global sensitivity analysis methods have been widely used for identifying important processes in hydrologic modeling, the existing methods consider only parametric uncertainty but ignore the model uncertainty for process representation. To address this problem, this study develops a new method to probe multimodel process sensitivity by integrating the model averaging methods into the framework of variance-based global sensitivity analysis, given that the model averaging methods quantify both parametric and model uncertainty. A new process sensitivity index is derived as a metric of relative process importance, and the index includes variance in model outputs caused by uncertainty in both process models and model parameters. For demonstration, the new index is used to evaluate the processes of recharge and geology in a synthetic study of groundwater reactive transport modeling. The recharge process is simulated by two models that converting precipitation to recharge, and the geology process is also simulated by two models of different parameterizations of hydraulic conductivity; each process model has its own random parameters. The new process sensitivity index is mathematically general, and can be applied to a wide range of problems in hydrology and beyond.

Dai, Heng↗
DOE OSTI2019

The Iterative Processing Framework: A New Paradigm for Automatic Event Building

Abstract In a traditional data-processing pipeline, waveforms are acquired, a detector makes the signal detections (i.e., arrival times, slownesses, and azimuths) and passes them to an associator. The associator then links the detections to the fitting-event hypotheses to generate an event bulletin. Most of the time, this traditional pipeline requires substantial human-analyst involvement to improve the quality of the resulting event bulletin. For the year 2017, for instance, International Data Center (IDC) analysts rejected about 40% of the events in the automatic bulletin and manually built 30% of the legitimate events. Here, we introduce an iterative processing framework (IPF) that includes a new data-processing module that incorporates automatic analyst behaviors (auto analyst [AA]) into the event-building pipeline. In the proposed framework, through an iterative process, the AA takes over many of the tasks traditionally performed by human analysts. These tasks can be grouped into two major processes: (1) evaluating small events with a low number of location-defining arrival phases to improve their formation; and (2) scanning for and exploiting unassociated arrivals to form potential events missed by previous association runs. To test the proposed framework, we processed a two-week period (15–28 May 2010) of the signal-detections dataset from the IDC. Comparison with an expert analyst-reviewed bulletin for the same time period suggests that IPF performs better than the traditional pipelines (IDC and baseline pipelines). The majority of the additional events built by the AA are low-magnitude events that were missed by these traditional pipelines. The AA also adds additional signal detections to existing events, which saves analyst time, even if the event locations are not significantly affected.

58 GEOSCIENCES↗
DOE OSTI2017

Carbon Inputs From Riparian Vegetation Limit Oxidation of Physically Bound Organic Carbon Via Biochemical and Thermodynamic Processes: OC Oxidation Processes Across Vegetation

In light of increasing terrestrial carbon (C) transport across aquatic boundaries, the mechanisms governing organic carbon (OC) oxidation along terrestrial-aquatic interfaces are crucial to future climate predictions. Here, we investigate biochemistry, metabolic pathways, and thermodynamics corresponding to OC oxidation in the Columbia River corridor. We leverage natural vegetative differences to encompass variation in terrestrial C inputs. Our results suggest that decreases in terrestrial C deposition associated with diminished riparian vegetation induce oxidation of physically-bound (i.e., mineral and microbial) OC at terrestrial-aquatic interfaces. We also find that contrasting metabolic pathways oxidize OC in the presence and absence of vegetation and—in direct conflict with the concept of ‘priming’—that inputs of water-soluble and thermodynamically-favorable terrestrial OC protects bound-OC from oxidation. Based on our results, we propose a mechanistic conceptualization of OC oxidation along terrestrial-aquatic interfaces that can be used to model heterogeneous patterns of OC loss under changing land cover distributions.

Graham, Emily B.↗
DOE OSTI2018

Shear Assisted Processing and Extrusion (ShAPE™) of AZ91E Flake: A Study of Tooling Features and Processing Effects

Charges of melt-spun AZ91E flake were indirectly extruded into tubes using Shear Assisted Processing and Extrusion (ShAPE™). The effect of instrument parameters and tool features on densification and microstructural evolution was studied. At a constant extrusion ratio, the tool rotational velocity varied from 75 to 300 rpm and was demonstrated to reduce the forge force by a factor of four. Modification of the extrusion die face with successively more aggressive scrolled features was found to enhance material flow into the extrusion orifice which led to a 30% reduction in spindle torque. Microstructure, texture and hardness are reported for the range of rpm and scroll geometries investigated. It was observed that the ShAPE™ process is able to retain the average grain size of the as-spun flake (2.5-4 μm) while simultaneously imparting strong textural alignment in the resultant tube.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Process Interactions Can Change Process Ranking in a Coupled Complex System Under Process Model and Parametric Uncertainty

For a complex hydrologic system with multiple processes and process interactions, global sensitivity analysis is often used to identify important or influential parameters for model development and improvement. The identification is complicated by process model uncertainty, when a system process can be represented by multiple process models. This study develops a new total-effect process sensitivity index to identify influential processes under model uncertainty. This is done by extending Sobol's total-effect parameter sensitivity index for one system model to total-effect process sensitivity index for multiple system models to account for uncertainty in process models and model parameters. The total-effect process sensitivity index includes not only the first-order process sensitivity index for measuring the importance of individual processes but also higher-order indices that account for process interactions. The total-effect process sensitivity index can identify an influential process that itself and its interactions with other processes influence a model output. Here, the total-effect process sensitivity index is applied to two numerical examples: (a) Sobol's G*-functions with analytical solutions of first-order and total-effect process sensitivity indices, and (b) groundwater flow models with interactions between recharge, geology, and snowmelt processes. The second evaluation shows that, due to second-order and higher-order process interactions, the first-order and total-effect process sensitivity indices give different process ranking. It is thus necessary to estimate both first-order and total-effect process sensitivity indices to appreciate the difference between the first-order impact of a process alone and the overall total-effect impact of the process itself and its interactions with other processes on a model output.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

The R -process Alliance: A Nearly Complete R -process Abundance Template Derived from Ultraviolet Spectroscopy of the R -process-enhanced Metal-poor Star HD 222925 *

We present a nearly complete rapid neutron-capture process (r-process) chemical inventory of the metal-poor ([Fe/H] = -1.46 ± 0.10) r-process-enhanced ([Eu/Fe] = +1.32 ± 0.08) halo star HD 222925. This abundance set is the most complete for any object beyond the solar system, with a total of 63 metals detected and seven with upper limits. It comprises 42 elements from 31 ≤ Z ≤ 90, including elements rarely detected in r-process-enhanced stars, such as Ga, Ge, As, Se, Cd, In, Sn, Sb, Te, W, Re, Os, Ir, Pt, and Au. We derive these abundances from an analysis of 404 absorption lines in ultraviolet spectra collected using the Space Telescope Imaging Spectrograph on the Hubble Space Telescope and previously analyzed optical spectra. A series of appendices discusses the atomic data and quality of fits for these lines. The r-process elements from Ba to Pb, including all elements at the third r-process peak, exhibit remarkable agreement with the solar r-process residuals, with a standard deviation of the differences of only 0.08 dex (17%). In contrast, deviations among the lighter elements from Ga to Te span nearly 1.4 dex, and they show distinct trends from Ga to Se, Nb through Cd, and In through Te. The r-process contribution to Ga, Ge, and As is small, and Se is the lightest element whose production is dominated by the r-process. The lanthanide fraction, log X La = -1.39 ± 0.09, is typical for r-process-enhanced stars and higher than that of the kilonova from the GW170817 neutron-star merger event. We advocate adopting this pattern as an alternative to the solar r-process-element residuals when confronting future theoretical models of heavy-element nucleosynthesis with observations.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2018

Linking process and structure in the friction stir scribe joining of dissimilar materials: A computational approach with experimental support

We present that friction stir welding (FSW) is a popular technique to join dissimilar materials in numerous applications. The solid state nature of the process enables joining materials with strikingly different physical properties. For welds in lap configuration, an enhancement to this technology is made by introducing a short, hard insert, referred to as a cutting-scribe, at the bottom of the tool pin. The cutting-scribe induces deformation in the bottom plate which leads to the formation of mechanical interlocks or hook like structures at the interface of two materials. A thermo-mechanical computational model employing a coupled Eulerian-Lagrangian approach is developed to quantitatively capture the morphology of these interlocks during the FSW process. Simulations using this model are validated by experimental observations. In conclusion, the identified interface morphology coupled with the predicted temperature field from this process–structure model can be used to estimate the post-weld microstructure and joint strength.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Techno-Economic Evaluation of Cellulosic Ethanol Production Based on Pilot Biorefinery Data: a Case Study of Sweet Sorghum Bagasse Processed via L+SScF

Replacing fossil fuels with renewable fuels derived from lignocellulosic biomass can contribute to the mitigation of global warming and the economic development of rural communities. This will require lignocellulosic biofuels to become price competitive with fossil fuels. Techno-economic analyses can provide insights into which parts of the biofuel production process need to be optimized to reduce cost or energy use. Here, we used data obtained from a pilot biorefinery to model a commercial-scale biorefinery that processes lignocellulosic biomass to ethanol, with a focus on the minimum ethanol selling price (MESP). The process utilizes a phosphoric acid-catalyzed pre-treatment of sweet sorghum bagasse followed by liquefaction and simultaneous saccharification and co-fermentation (L+SScF) of hexose and pentose sugars by an engineered Escherichia coli strain. After validating a techno-economic model developed with the SuperPro Designer software for the conversion of sugarcane bagasse to ethanol by comparing it to a published Aspen Plus model, six different scenarios were modeled for sweet sorghum bagasse Under the most optimistic scenario, the ethanol can be produced at a cost close to the energy-equivalent price of gasoline. Aside from an increase in the price of gasoline, the gap between ethanol and gasoline prices could also be bridged by either a decrease in the cost of cellulolytic enzymes or development of value-added products from lignin.

Biofuel↗
DOE OSTI2018

Impacts of feedstock properties on the process economics of fast-pyrolysis biorefineries

Feedstock properties are an important factor affecting process yields and economics of fast pyrolysis biorefineries. Here, this study develops a fast pyrolysis process model sensitive to feedstock properties based on the experimental results. 64 simulations are run to evaluate the impacts of carbon, ash and moisture content in biomass feedstocks on process yields and energy consumptions. An economic analysis is conducted for each run to quantify process economics under different feedstock properties. With biomass feedstocks of 48% carbon and 15% moisture, Minimum Fuel Selling Price (MFSP) increases from 0.97/L to 1.06/L when ash content increases from 1% to 7%, due to reduced hydrocarbon yields. With biomass feedstocks of 48% carbon and 3% ash content, MFSP increases from 1.03/L to 1.08/L when feedstock moisture increases from 15% to 45% as a consequence of increased energy demand for feedstock drying. Finally, the impact of feedstock ash content decreases gradually as ash content increases. Feedstock carbon content has less significant impacts on process economics in this study.

09 BIOMASS FUELS↗
DOE OSTI2020

Dehalogenation of electrochemical processing salt simulants with ammonium phosphates and immobilization of salt cations in an iron phosphate glass waste form

This study demonstrates the conversion of simulated pyroprocessing salt wastes [i.e., ER(SF) and ERV2] into chemically durable iron phosphate glass waste forms through reactions with ammonium hydrogen phosphate precursors [i.e., NH4H2PO4 and (NH4)2HPO4] and added Fe2O3. The reaction of the salt simulants with the phosphate precursors resulted in dehalogenation of the salt through the production of NH4Cl and NH4I (along with water), of which the NH4Cl can be used to produce UCl3 oxidant for use in the electrorefiner during pyroprocessing. These iron phosphate glasses contain a notably higher waste loading than the baseline glass-bonded sodalite ceramic waste form, which requires about 70 vol% sodalite to accommodate Cl from the salt, because they are dehalogenated prior to vitrification. The high waste loadings coupled with higher bulk densities (~3×103 kg/m3) than glass-bonded sodalite (~2.3×103 kg/m3) mean that these glasses have a higher storage volume, i.e., the volume required to immobilize a given mass of waste. The iron phosphate glass waste forms were characterized using a variety of techniques including physical property measurements and chemical durability testing. Following initial testing, a proof-of-concept demonstration was conducted to show that the NH4Cl generated from this process could be used to produce UCl3 using depleted uranium dendrites as a feedstock.

phosphate glass, pyroprocessing, waste forms, salt↗
DOE OSTI2021

Processable High Electron Mobility {pi}-Copolymers via Mesoscale Backbone Conformational Ordering

The synthesis and experimental/theoretical characterization of a new series of electron-transporting copolymers based on the naphthalene bis(4,8-diamino-1,5-dicarboxyl)amide (NBA) building block are reported. Comonomers are designed to test the emergent effects of manipulating backbone torsional characteristics, and density functional theory (DFT) analysis reveals the key role of backbone conformation in optimizing electronic delocalization and transport. The NBA copolymer conformational and electronic properties are characterized using a broad array of molecular/macromolecular, thermal, optical, electrochemical, and charge transport techniques. All NBA copolymers exhibit strongly aggregated morphologies with significant nanoscale order. Copolymer charge transport properties are investigated in thin-film transistors and exhibit excellent electron mobilities ranging from 0.4 to 4.5 cm(2) V-1 s(-1). Importantly, the electron transport efficiency correlates with the film mesoscale order, which emerges from comonomer-dependent backbone planarity and extension. These results illuminate the key NBA building block structure-morphology-bulk property design relationships essential for processable, electronics-applicable high-performance polymeric semiconductors.

n‐↗
DOE OSTI2020

Description of the Fission Process: Nuclear Models for Fission Dynamics

Nuclear fission is the splitting of a heavy nucleus into two or more fragments, a process that releases a substantial amount of energy. It is ubiquitous in modern applications, critical for national security, energy generation and reactor safeguards. Fission also plays an important role in understanding the astrophysical formation of elements in the universe. Eighty years after the discovery of the fission process, its theoretical understanding from first principles remains a great challenge. In this paper, we present promising new approaches to make more accurate predictions of fission observables.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗