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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 919 records · Page 51
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Extent of interlocking and metallurgical bonding in friction riveting of aluminum alloy to steel

In this study, the joining of 6061-T6 aluminum alloy and DP590 steel using a M42 steel rivet via friction riveting technique is investigated. The surface morphology and microstructure characterization reveal the formation of an anchor zone that imparts mechanical interlock as well as the formation of metallurgical bonds at the interface of aluminum and steel. A combination of interlocking and bonding results in the achievement of a high load-carrying capacity of 5.7 kN during lap shear testing at room temperature. A finite element-based computational model was developed which accurately predicted the lap shear response of the joint. The model revealed that the metallurgical bond formed during fric-riveting adds 39% peak load strength to the joint. An extensive microstructural investigation, post-lap-shear fractography, and the modeling results, together provided insights on the joint failure mechanism. In conclusion, this study highlights that friction riveting is a promising method for aluminum-to-steel dissimilar joining, which is important for lighweighing automotive vehicles for energy efficiency.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Possibilities for Optimizing the Self-Starting Process of Auxiliary Electric Motors at a Nuclear Power Plant

The existing technique of switching on the auxiliary reserve network of an NPP formulates the switch-on commands directly after a shutdown. Due to delay in activating the automatic switch, the command is completed with a certain time delay. The nature of the subsequent processes is not very predictable. It is proposed to determine, based on developed computer models of the actual equipment, the moments of formation of the reserve activation commands, thus ensuring smaller perturbations at the subsequent switch-on.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2018

Structural basis of the cystein protease inhibitor Clonorchis sinensis Stefin-1

Highlights: • Clonorchis sinensis Stefin-1 has known as a host immune modulator. • The first crystal structure of CsStefin-1 was determined by the MAD method. • CsStefin-1 inhibited CsCF-8 cysteine protease activity. • A molecular docking model of CsStefin-1 and CsCF-8 was developed. • The CsStefin-1 was physically bound to CsCF-8 with an apparent K{sub D} value. Cystein protease plays a critical role as a virulence factor in the development and progression of various diseases. Cystatin is a superfamily of cysteine protease inhibitors that participates in various physiological and pathological processes. The cysteine protease inhibitor CsStein-1 isolated from Clonorchis sinensis belongs to the type 1 stefin of cystatins. This inhibitor regulates the activity and processing of CsCF (Cathepsin F of Clonorchis sienesis), which plays an important role in parasite nutrition and host-parasite interaction. CsStefin-1 has also been proposed as a host immune modulator and a participant in the mechanism associated with anti-inflammatory ability. Here, we report the first crystal structure of CsStefin-1 determined by the multi-wavelength anomalous diffraction (MAD) method to 2.3 Å. There are six molecules of CsStefin-1 per asymmetric unit, with a solvent content of 36.5%. The structure of CsStefin-1 is composed of twisted four-stranded antiparallel β-sheets, a central α-helix, and a short α-helix. We also demonstrate that CsStefin-1 binds to CsCF-8 cysteine protease and inhibits its activity. In addition, a molecular docking model of CsStefin-1 and CsCF-8 was developed using homology modeling based on their structures. The structural information regarding CsStefin-1 and molecular insight into its interaction with CsCF-8 are important to understanding their biological function and to design of inhibitors that modulate cysteine protease activity.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

Theoretical investigation of the decarboxylation and decarbonylation mechanism of propanoic acid over a Ru(0 0 0 1) model surface

The hydrodeoxygenation of organic acids is often found to be a rate-controlling process during upgrading of biomass feedstocks into fuels. We developed a microkinetic model based on data obtained from density functional theory calculations for the decarboxylation and decarbonylation mechanisms of propanoic acid (CH 3 CH 2 COOH) over a Ru(0 0 0 1) model surface. The model predicts that the decarbonylation mechanism is two orders of magnitude faster than the decarboxylation mechanism. The most favorable decarbonylation pathway proceeds via removal of the acid –OH group to produce propanoyl (CH 3 CH 2 CO) followed by C–CO bond scission of propanoyl to produce CH 3 CH 2 and CO. Finally, CH 3 CH 2 is hydrogenated to CH 3 CH 3 . Dehydrogenation reactions that have been observed to be important over Pd catalysts play no role over Ru(0 0 0 1), and a sensitivity analysis indicates that removal of the acid –OH group is the rate-controlling step in the deoxygenation. Altogether, our results suggest that to improve the Ru catalyst performance for the decarbonylation of organic acids, the free site coverage needs to be increased by, for example, adding a catalyst promoter that decreases the hydrogen and CO adsorption strength (without significantly affecting the C–OH bond scission rate), or by raising the reaction temperature and operating at relatively low CO and H 2 partial pressures.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

Comparative analysis for various redox flow batteries chemistries using a cost performance model

A robust performance-based cost model is developed for all-vanadium, iron-vanadium and iron chromium redox flow batteries. Systems aspects such as shunt current losses, pumping losses and thermal management are accounted for. The objective function, set to minimize system cost, allows determination of stack design and operating parameters such as current density, flow rate and depth of discharge (DOD). Component costs obtained from vendors are used to calculate system costs for various time frames. A 2 kW stack data was used to estimate unit energy costs and compared with model estimates for the same size electrodes. The tool has been shared with the redox flow battery community to both validate their stack data and guide future direction.

electrolyte↗
DOE OSTI2022

Machine-learning-assisted high-temperature reservoir thermal energy storage optimization

High-temperature reservoir thermal energy storage (HT-RTES) has the potential to become an indispensable component in achieving the goal of the net-zero carbon economy, given its capability to balance the intermittent nature of renewable energy generation. In this study, a machine-learning-assisted computational framework is presented to co-optimize the performance metrics of HT-RTES by combining physics-based simulation with stochastic hydrogeologic formation and thermal energy storage operation parameters, artificial neural network regression of the simulation data, and genetic algorithm-enabled multi-objective optimization. A doublet well configuration with a layered (aquitard-aquifer-aquitard) generic reservoir is simulated for cases of continuous operation and seasonal-cycle operation scenarios. Further, neural network-based surrogate models are developed for the two scenarios and applied to generate the Pareto fronts of the HT-RTES performance for four potential HT-RTES sites. The developed Pareto optimal solutions indicate the performance of HT-RTES is operation-scenario (i.e., fluid cycle) and reservoir-site dependent, and the performance metrics have competing effects for a given site and a given fluid cycle. The developed neural network models can be applied to identify suitable sites for HT-RTES, and the proposed framework sheds light on the design of resilient HT-RTES systems.

15 GEOTHERMAL ENERGY↗
DOE OSTI2018

Plant roots alter microbial functional genes supporting root litter decomposition

Decomposition of soil organic carbon is central to the global carbon cycle and profoundly affected by plant roots. While root “priming” of decomposition has been extensively investigated, it is not known how plants alter the molecular ecology of soil microbial decomposers. We disentangled the effects of Avena fatua, a common annual grass, on 13 C-labeled root litter decomposition and quantified multiple genetic characteristics of soil bacterial and fungal communities. In our study, plants consistently suppressed rates of root litter decomposition. Microbes from planted soils had relatively more genes coding for low molecular weight compound degradation enzymes, while those from unplanted had more macromolecule degradation genes. Higher abundances of “water stress” genes in planted soils suggested that microbes experienced plant-induced water stress. We developed a conceptual model based on Mantel analyses of our extensive data set. This model indicates that plant root effects on the multiple soil environmental and microbial mechanisms involved in root litter decomposition act through changing the functional gene profiles of microbial decomposers living near plant roots.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Feedbacks Between Surface Deformation and Permafrost Degradation in Ice Wedge Polygons, Arctic Coastal Plain, Alaska

In the past three decades, an abrupt, pan-Arctic acceleration of ice wedge melting has transformed tundra landscapes, spurring the formation of hummock-like features known as high-centered polygons (HCPs). This rapid geomorphic transition profoundly alters regional hydrology and influences surface emissions of CO 2 and CH 4 . In Arctic Alaska, most recent instances of ice wedge degradation have arrested within 15–20 years of inception, stabilizing HCP microtopography. However, feedbacks between ground surface deformation and permafrost stability are incompletely understood, limiting our capacity to predict trajectories of landscape evolution in a still warmer future. In this work, we use field data from a site near Prudhoe Bay, Alaska, to develop a modeling-based framework for assessing the strength of positive (i.e., exacerbating) feedbacks on ice wedge degradation, focusing on the importance of heterogeneity in surface drainage and microtopographic conditions. Our simulations suggest that, when troughs are narrow, positive feedbacks on ice wedge melting (associated with thermokarst pool formation) are relatively weak. Positive feedbacks are markedly stronger beneath wide troughs, such as those that form above older, larger ice wedges. Seasonal thaw abruptly accelerates once a talik begins to form beneath wide and deep thermokarst pools. Once a talik initiates, winter severity and snowpack thickness increase in importance as predictors of thaw intensity in summer. Our results indicate that meter-scale heterogeneity in polygonal microtopography potentially exerts strong, nonlinear controls on thermokarst trajectories. These findings are useful for predicting future thermokarst dynamics and for interpreting the results from coarser-resolution land surface models operating at greater spatial and temporal scales.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Adaptation Strategies Strongly Reduce the Future Impacts of Climate Change on Simulated Crop Yields

Abstract Simulations of crop yield due to climate change vary widely between models, locations, species, management strategies, and Representative Concentration Pathways (RCPs). To understand how climate and adaptation affects yield change, we developed a meta‐model based on 8703 site‐level process‐model simulations of yield with different future adaptation strategies and climate scenarios for maize, rice, wheat and soybean. We tested 10 statistical models, including some machine learning models, to predict the percentage change in projected future yield relative to the baseline period (2000–2010) as a function of explanatory variables related to adaptation strategy and climate change. We used the best model to produce global maps of yield change for the RCP4.5 scenario and identify the most influential variables affecting yield change using Shapley additive explanations. For most locations, adaptation was the most influential factor determining the projected yield change for maize, rice and wheat. Without adaptation under RCP4.5, all crops are expected to experience average global yield losses of 6%–21%. Adaptation alleviates this average projected loss by 1–13 percentage points. Maize was most responsive to adaptive practices with a projected mean yield loss of −21% [range across locations: −63%, +3.7%] without adaptation and −7.5% [range: −46%, +13%] with adaptation. For maize and rice, irrigation method and cultivar choice were the adaptation types predicted to most prevent large yield losses, respectively. When adaptation practices are applied, some areas are predicted to experience yield gains, especially at northern high latitudes. These results reveal the critical importance of implementing adequate adaptation strategies to mitigate the impact of climate change on crop yields.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Advances in geophysical forensic event monitoring

Forensic analysis of man-made, non-nuclear events (such as industrial accidents, explosion experiments and mine collapses) has become more frequent and detailed owing to advancements in geophysical monitoring. Here, in this Technical Review, we demonstrate how geophysical forensic monitoring using seismic, infrasound and hydroacoustic recordings provides insights on events in the solid earth, atmosphere and underwater. Advanced techniques, including machine-learning-based models, have been developed to detect, identify and investigate these events, providing information on location, subevents, sources and explosive yield. The increase in data availability, application of advanced methods and computation and the growth of multitechnology approaches have increased the accuracy of forensic event analysis and enabled more realistic characterization of uncertainties. For example, the 2020 Beirut explosion in Lebanon demonstrated that various seismic, acoustic and other methods could be used to estimate explosive yield (and yield uncertainties) of about 1 ktonne, providing confidence in the application of these methods to smaller events where data are available. However, forensic investigations remain largely limited to known events with identified sources. Increased access to data, sophisticated analysis methods and high-resolution earth models will improve forensic event analysis further, enabling civil and scientific applications, such as localization in the search for the lost ARA San Juan submarine.

geophysics↗
DOE OSTI2011

Strange particle production at low and intermediate energies

The weak kaon production off the nucleon induced by neutrinos and antineutrinos is studied at low and intermediate energies of interest for some ongoing and future neutrino oscillation experiments. We develop a microscopical model based on the SU(3) chiral Lagrangians. The studied mechanisms are the main source of kaon production for neutrino energies up to 2 GeV for the various channels and the cross sections are large enough to be amenable to be measured by experiments such as Minerva, T2K and NOvA.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2014

Weakly relativistic quantum kinetic theory for electrostatic wave modes in magnetized plasmas

We have derived the electrostatic dispersion relation in a magnetized plasma using a recently developed quantum kinetic model based on the Dirac equation. The model contains weakly relativistic spin effects such as Thomas precession, the polarization currents associated with the spin and the spin-orbit coupling. It turns out that for strictly electrostatic perturbations the non-relativistic spin effects vanish, and the modification of the classical dispersion relation is solely associated with the relativistic terms. Several new wave modes appear due the electron spin effects, and an example for astrophysical plasmas are given.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2015

Recent modelling advances for ultrasonic TOFD inspections

The ultrasonic TOFD (Time of Flight Diffraction) Technique is commonly used to detect and characterize disoriented cracks using their edge diffraction echoes. An overview of the models integrated in the CIVA software platform and devoted to TOFD simulation is presented. CIVA allows to predict diffraction echoes from complex 3D flaws using a PTD (Physical Theory of Diffraction) based model. Other dedicated developments have been added to simulate lateral waves in 3D on planar entry surfaces and in 2D on irregular surfaces by a ray approach. Calibration echoes from Side Drilled Holes (SDHs), specimen echoes and shadowing effects from flaws can also been modelled. Some examples of theoretical validation of the models are presented. In addition, experimental validations have been performed both on planar blocks containing calibration holes and various notches and also on a specimen with an irregular entry surface and allow to draw conclusions on the validity of all the developed models.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2016

Quantum and quasi-classical collisional dynamics of O{sub 2}–Ar at high temperatures

A hypersonic vehicle traveling at a high speed disrupts the distribution of internal states in the ambient flow and introduces a nonequilibrium distribution in the post-shock conditions. We investigate the vibrational relaxation in diatom-atom collisions in the range of temperatures between 1000 and 10 000 K by comparing results of extensive fully quantum-mechanical and quasi-classical simulations with available experimental data. The present paper simulates the interaction of molecular oxygen with argon as the first step in developing the aerothermodynamics models based on first principles. We devise a routine to standardize such calculations also for other scattering systems. Our results demonstrate very good agreement of vibrational relaxation time, derived from quantum-mechanical calculations with the experimental measurements conducted in shock tube facilities. At the same time, the quasi-classical simulations fail to accurately predict rates of vibrationally inelastic transitions at temperatures lower than 3000 K. This observation and the computational cost of adopted methods suggest that the next generation of high fidelity thermochemical models should be a combination of quantum and quasi-classical approaches.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2013

Propagation of broadband optical radiation in a spun high-birefringent fibre

The evolution of the polarisation state of the broadband optical radiation, propagating through a spun high-birefringent fibre is studied. A theoretical model describing the polarisation state of the radiation in the spun fibre depending on the input polarisation parameters is developed. The model is based on the geometric analysis of the polarisation states of the spectral components of the radiation on the Poincare sphere. It is shown that when the propagation path length of the radiation in the optical fibre exceeds some value (the coherence length), the spectrum-averaged polarisation state of the output light is determined only by the parameters of the spun fibre, while the degree of polarisation of the output radiation depends on the input polarisation state. (optical fibres)

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Polyubiquitin ligand-induced phase transitions are optimized by spacing between ubiquitin units

Biomolecular condensates form via multivalent interactions among key macromolecules and are regulated through ligand binding and/or posttranslational modifications. One such modification is ubiquitination, the covalent addition of ubiquitin (Ub) or polyubiquitin chains to target macromolecules. Specific interactions between polyubiquitin chains and partner proteins, including hHR23B, NEMO, and UBQLN2, regulate condensate assembly or disassembly. Here, we used a library of designed polyubiquitin hubs and UBQLN2 as model systems for determining the driving forces of ligand-mediated phase transitions. Perturbations to either the UBQLN2-binding surface of Ub or the spacing between Ub units reduce the ability of hubs to modulate UBQLN2 phase behavior. By developing an analytical model based on polyphasic linkage principles that accurately described the effects of different hubs on UBQLN2 phase separation, we determined that introduction of Ub to UBQLN2 condensates incurs a significant inclusion energetic penalty. This penalty antagonizes the ability of polyUb hubs to scaffold multiple UBQLN2 molecules and cooperatively amplify phase separation. The extent to which polyubiquitin hubs promote UBQLN2 phase separation is encoded in the spacings between Ub units. This spacing is modulated by chains of different linkages and designed chains of different architectures, thus illustrating how the ubiquitin code regulates functionality via the emergent properties of the condensate. The spacing in naturally occurring linear polyubiquitin chains is already optimized to promote phase separation with UBQLN2. We expect our findings to extend to other condensates, emphasizing the importance of ligand properties, including concentration, valency, affinity, and spacing between binding sites in studies and designs of condensates.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Demonstration of the Advanced Dynamic System Modeling Tool TRANSFORM in a Molten Salt Reactor Application via a Model of the Molten Salt Demonstration Reactor

Liquid-fueled nuclear reactors, particularly molten salt reactors (MSRs), have recently gained significant interest in the advanced reactor community. As with all reactors, modeling and simulation are critical to advanced reactor design and licensing and will be required for MSR deployment. However, there are significant gaps in existing simulation capabilities for MSRs, particularly with the unique challenges of liquid-fueled systems (e.g., fission product transport). Furthermore, advanced reactor designers require near-term tools that are readily modifiable to perform design and analysis, including the ability to extend their analysis beyond the primary system to auxiliary systems. Transient Simulation Framework of Reconfigurable Models (TRANSFORM), a Modelica-based, system modeling library developed at Oak Ridge National Laboratory, is an advanced tool that can help meet some of the near-term needs of the advanced reactor community. Here, this paper describes advanced system modeling criteria and presents TRANSFORM to the advanced reactor community by demonstration of system modeling capabilities and support of advanced analysis workflows, i.e., the Risk Analysis Virtual Environment (RAVEN) framework from Idaho National Laboratory, using the liquid-fueled Molten Salt Demonstration Reactor (MSDR) as a reference design.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗