Search NASA⌕ Search

SEARCH · Search NASA

Results for “scale reduction”

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.

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

At least 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Quantifying the reduction in cavitation-induced erosion damage in the Spallation Neutron Source mercury target by means of small-bubble gas injection

Here, a model developed to represent the progress of erosion damage in liquid-metal spallation target vessels was modified to incorporate the effect of gas injection on the erosion rate. The liquid mercury target system for the Spallation Neutron Source (SNS) at Oak Ridge National Laboratory now operates with helium gas injection to reduce target vessel fatigue stress and cavitation-induced erosion damage. Erosion damage is a primary degradation phenomenon affecting the service life of SNS target vessels, and cavitation mitigation techniques, such as small-bubble gas injection, have been implemented to reduce damage and extend target lifetimes. Erosion depths in samples removed from SNS targets after operation were measured using laser line scanning. These measurements confirmed that gas injection reduced erosion damage. However, quantifying the damage reduction due to gas injection was complicated by variations in lifetime, power, and gas injection rates between different targets. In this study, the operating power and gas injection rate of targets were incorporated into an erosion damage prediction model to quantify their effects on erosion damage reduction. Values of a power scaling factor, β, were calculated by comparing modeled with measured erosion damage. These values indicate that the use of gas injection at the SNS reduced damage to a level equivalent to operating targets without gas injection at 35–47% of the actual beam power. To account for the gas injection effect on the cavitation damage, a simple exponential form based on analysis of the scaling factor β was developed to incorporate the gas rate history with a scaling factor γ in the erosion damage modeling.

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

Characterizing Hydrated Polymers via Dielectric Relaxation Spectroscopy: Connecting Relative Permittivity, State of Water, and Salt Transport Properties of Sulfonated Polysulfones

Sulfonated polysulfone is a promising membrane material for separation and energy generation processes that rely on membranes to control the rates of small-molecule (e.g., water and ions) transport. The interactions among water molecules, ions, and the sulfonate groups in these polymers play a key role in controlling these rates of transport, but much remains unknown about these fundamental interactions in sulfonated polymers. In this study, we used dielectric relaxation spectroscopy to characterize water molecule dynamics in sulfonated polysulfone and Nafion. We found that the charged sulfonate groups contribute to a restriction of water molecule dynamics (i.e., a reduction in the characteristic time scale of dipolar motions) in a manner that is governed by the concentration and nature (i.e., conjugate base strength) of the sulfonate group. Additionally, we develop strategies to use these data to aid in modeling ion transport in sulfonated polysulfone. These results may be useful to guide engineering strategies for polymeric membranes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Skyshine Calculations for a Large Spent Nuclear Fuel Storage Facility with SCALE 6.2.3

The SCALE code system developed at Oak Ridge National Laboratory includes state-of-the-art capabilities for radiation source term and radiation transport simulations that can be used in numerous applications, including dose rate analyses of complex consolidated interim storage facilities (CISFs). A licensed CISF could be used to store tens of thousands of tonnes of spent nuclear fuel discharged from commercial power reactors using various cask and storage pad designs. A CISF design must comply with the regulatory requirements provided in 10 CFR Part 72, including requirements related to annual dose limits applicable to real individuals located beyond the area controlled by the licensee. Therefore, calculating a dose to the public is a necessary part of the licensing process for the construction of a CISF. These calculations are very challenging because of the complexity of the CISF design and the low magnitude of dose rate at large distances from the facility. This paper describes detailed far-field dose rate calculations performed for a proposed CISF using MAVRIC, the Monte Carlo radiation shielding sequence in SCALE 6.2.3, with automated variance reduction based on discrete ordinates calculations. The method presented in this paper uses a detailed Monte Carlo radiation transport simulation in one step from source to dose rate. A series of independent simulations was made using the complete site geometry (all casks present), but with only one cask containing radiation sources to obtain the dose rate maps produced by each storage cask. The CISF dose rate map was obtained by adding the dose rate maps produced by the independent individual cask simulations. Ample volumes of air and soil extending beyond the location of interest for dose rate calculation were included in the calculation model to properly simulate important radiation attenuation and scattering events that affect far-field dose rates. Furthermore, a comprehensive sensitivity study is included in this paper to illustrate the importance of selecting appropriate air volume, mass density, and composition for CISF skyshine dose rate calculations. Dry soil and soil containing water were analyzed to determine their effects on groundshine radiation.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2024

Local atomic and magnetic structure of multiferroic (Sr,Ba)⁢(Mn,Ti)⁢O 3

Here, we present a detailed study of the local atomic and magnetic structure of the type-I multiferroic perovskite system (Sr,Ba)(Mn,Ti)O 3 using x-ray and neutron pair distribution function (PDF) analysis, polarized neutron scattering, and muon spin relaxation (μSR) techniques. The atomic PDF analysis reveals widespread nanoscale tetragonal distortions of the crystal structure even in the paraelectric phase with average cubic symmetry, corresponding to incipient ferroelectricity in the local structure. Magnetic PDF analysis, polarized neutron scattering, and μSR likewise confirm the presence of short-range antiferromagnetic correlations in the paramagnetic state, which grow in magnitude as the temperature approaches the magnetic transition. We show that these short-range magnetic correlations coincide with a reduction of the tetragonal (i.e., ferroelectric) distortion in the average structure, suggesting that short-range magnetism can play an important role in magnetoelectric and/or magnetostructural phenomena even without genuine long-range magnetic order. The reduction of the tetragonal distortion scales linearly with the local magnetic order parameter, pointing to spontaneous linear magnetoelectric coupling in this system. These findings provide greater insight into the multiferroic properties of (Sr,Ba)(Mn,Ti)O 3 and demonstrate the importance of investigating the local atomic and magnetic structure to gain a deeper understanding of the intertwined degrees of freedom in multiferroics.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

Rolling Horizon Based Temporal Decomposition for the Offline Pickup and Delivery Problem with Time Windows

The offline pickup and delivery problem with time windows (PDPTW) is a classical combinatorial optimization problem in the transportation community, which has proven to be very challenging computationally. Due to the complexity of the problem, practical problem instances can be solved only via heuristics, which trade-off solution quality for computational tractability. Among the various heuristics, a common strategy is problem decomposition, that is, the reduction of a large-scale problem into a collection of smaller sub-problems, with spatial and temporal decompositions being two natural approaches. While spatial decomposition has been successful in certain settings, effective temporal decomposition has been challenging due to the difficulty of stitching together the sub-problem solutions across the decomposition boundaries. In this work, we introduce a novel temporal decomposition scheme for solving a class of PDPTWs that have narrow time windows, for which it is able to provide both fast and high-quality solutions. We utilize techniques that have been popularized recently in the context of online dial-a-ride problems along with the general idea of rolling horizon optimization. To the best of our knowledge, this is the first attempt to solve offline PDPTWs using such an approach. To show the performance and scalability of our framework, we use the optimization of paratransit services as a motivating example. Due to the lack of benchmark solvers similar to ours (i.e., temporal decomposition with an online solver), we compare our results with an offline heuristic algorithm using Google OR-Tools. In smaller problem instances (with an average of 129 requests per instance), the baseline approach is as competitive as our framework. However, in larger problem instances (approximately 2,500 requests per instance), our framework is more scalable and can provide good solutions to problem instances of varying degrees of difficulty, while the baseline algorithm often fails to find a feasible solution within comparable compute times.

Kim, Youngseo↗
DOE OSTI2023

Mission Analysis for Marine Renewable Energy to Provide Power for Marine Carbon Dioxide Removal

The mission of this project was to provide a preliminary feasibility assessment of powering different marine carbon dioxide removal (mCDR), marine carbon capture, and marine carbon sequestration strategies with marine energy. In this report, carbon capture refers to methods that can separate or capture carbon dioxide (CO 2 ) from the air or ocean; carbon sequestration refers to methods that store CO 2 obtained by capture methods out of the atmosphere for long periods of time; and carbon dioxide removal (CDR) refers to methods that do both. The project found that mCDR powered by marine energy and offshore wind energy available in the United States could meet global CDR scales needed by 2040 and 2050 to limit warming to 1.5 degrees C by 2100. Note that this preliminary estimate assumes that it is possible to harvest all the marine and offshore wind resources available in the United States with existing technology options, and it does not account for the power needed for monitoring these methods, as these power needs are not yet well defined and require further research. Additionally, these CDR scales will still require emissions reductions.

16 TIDAL AND WAVE POWER↗
DOE OSTI2026

Topology-Dependent Performance of Free-Space Photonic Quantum Networks Under Noise

Photonic quantum communication enables secure and high-fidelity information transfer beyond classical limits, with direct relevance to emerging quantum networks operating in free-space environments. While physical-layer models of depolarizing noise, Gamma–Gamma turbulence statistics, entanglement swapping, and decoy-state QKD security bounds are individually well established, prior work typically treats these components in isolation or under fixed network assumptions. In this work, we develop a unified topology-aware analytical framework that simultaneously integrates free-space optical link budgets, turbulence-induced visibility degradation, depolarizing qubit noise, multi-hop entanglement cascade dynamics, teleportation fidelity thresholds, CHSH nonlocality certification, and asymptotic decoy-state secret key rate bounds across star, mesh, and ring graph structures. Rather than introducing new physical channel models, we demonstrate that identical physical links exhibit fundamentally different end-to-end performance once embedded within different network topologies. Mesh architectures minimize visibility cascade through hop-count reduction but incur quadratic hardware scaling. Star topologies minimize link count but concentrate noise and synchronization overhead at the hub. Ring configurations offer linear hardware scaling with multiplicative fidelity degradation. The results establish topology as a first-order design parameter in near-term free-space quantum networks operating without full quantum repeater infrastructures. While motivated by distributed multi-agent architectures, the framework applies broadly to terrestrial, airborne, and satellite-assisted photonic quantum communication systems.

QKD↗
DOE OSTI2025

Techno-Economic Analysis of Sorbent-Based Direct Air Capture Informed by EPC Input and Recent Technological Advancements

Direct air capture (DAC) technology has been developing at an accelerated rate. Independent, comprehensive, and transparent techno-economic analyses (TEAs) of DAC technologies are required to inform future development. NETL is publishing an update to the 2022 sorbent-based DAC case study report. This manuscript highlights select TEA results that will be presented in the upcoming NETL report. The analysis considers three sorbent-based DAC system configurations (direct steam temperature swing, indirect steam temperature swing, and direct steam temperature/vacuum swing) and two scenarios for providing the required electricity and steam (stand-alone system with a combined heat and power plant generating the required steam and electricity, and a purchased power case utilizing an electric boiler). Detailed sensitivity analyses are included and highlight the impact of external market factors, sorbent performance, and economies of scale. The potential for cost reductions by opting for temperature vacuum swing adsorption is highlighted. More detailed background and TEA results will be presented in the upcoming NETL report titled “Direct Air Capture Case Studies: Sorbent System (Revision 1)”.

carbon dioxide removal↗
DOE OSTI2020

Improving PGM-free ORR Electrocatalyst Activity: Suggestions from DFT Studies

In this opinion, the limitations of platinum group metal–free oxygen reduction reaction electrocatalyst activity based on scaling laws and resulting Balandin-Sabatier volcano plots are presented. Previous theoretical work aimed at overcoming this limitation is discussed. In this work, a theoretical study of a novel approach toward catalyst activity improvement, dynamic strain engineering, is proposed and tested for a possible platinum group metal–free oxygen reduction reaction active site. It is shown that not only can this approach produce thermodynamic limiting potentials well beyond scaling law relationship limits but also be capable of doing so in an energy-efficient manner.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Low-synch Gram–Schmidt with delayed reorthogonalization for Krylov solvers

The parallel strong-scaling of iterative methods is often determined by the number of global reductions at each iteration. Low-synch Gram-Schmidt algorithms are applied here to the Arnoldi algorithm to reduce the number of global reductions and therefore to improve the parallel strong-scaling of iterative solvers for nonsymmetric matrices such as the GMRES and the Krylov-Schur iterative methods. In the Arnoldi context, the factorization is "left-looking" and processes one column at a time. Among the methods for generating an orthogonal basis for the Arnoldi algorithm, the classical Gram-Schmidt algorithm, with reorthogonalization (CGS2) requires three global reductions per iteration. A new variant of CGS2 that requires only one reduction per iteration is presented and applied to the Arnoldi algorithm. Delayed CGS2 (DCGS2) employs the minimum number of global reductions per iteration (one) for a one-column at-a-time algorithm. The main idea behind the new algorithm is to group global reductions by rearranging the order of operations. DCGS2 must be carefully integrated into an Arnoldi expansion or a GMRES solver. Numerical stability experiments assess robustness for Krylov-Schur eigenvalue computations. Performance experiments on the ORNL Summit supercomputer then establish the superiority of DCGS2 over CGS2.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Low‐dimensional manifold learning for uncertainty quantification in complex multi‐scale stochastic systems

Broadly speaking, the goals of the project are to develop techniques to use manifold learning to develop reduced‐order and surrogate models for "hyper‐reduction" of very high‐dimensional complex multi‐scale systems. This is being achieved by employing a newly proposed form of manifold projection and learning that leverages recent advancements in computational geometry and data‐driven modeling. In particular, we are applying a manifold projection technique to project the solutions of very high‐dimensional systems onto the so‐called Grassmannmanifold, a Reimannian manifold comprised of orthonormal matrices. We then apply data‐driven machine learning techniques to classify the solutions on the manifold (e.g. clustering techniques) according to their proximity on the manifold and leverage a further nonlinear dimension reduction to organize the structured data on the manifold. Finally, we are developing novel techniques that enable us to directly interpolate the hyper‐reduced data such that we can predict the solution of the complex, high‐ dimensional system without need to call the full expensive computational model. Given their adherence to the underlying structure of the solution of the physical system, it is expected that these approximate solutions will be sufficiently constrained so as to (approximately) adhere to physical principles.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Atomic-scale 3D structural dynamics and functional degradation of Pt alloy nanocatalysts during the oxygen reduction reaction

Pt-based electrocatalysts are the primary choice for fuel cells due to their superior oxygen reduction reaction (ORR) activity. To enhance ORR performance and durability, extensive studies have investigated transition metal alloying, doping, and shape control to optimize the three key governing factors for ORR: geometry, local chemistry, and strain of their surface and subsurface. However, systematic optimization remains incomplete, as it requires an atomic-scale understanding of these factors and their dynamics over potential cycling, as well as their relationship to ORR activity. Here, we implement neural network-assisted atomic electron tomography to measure the 3D atomic structural dynamics and their effects on the functional degradation of PtNi alloy catalysts. Our results reveal that PtNi catalysts undergo shape changes, surface alloying, and strain relaxation during cycling, which can be effectively mitigated by Ga doping. By combining geometry, local chemistry, and strain analysis, we calculated the changes in ORR activity over thousands of cycles and observed that Ga doping leads to higher initial activity and greater stability. These findings offer a pathway to understanding 3D atomic structural dynamics and their relation to ORR activity during cycling, paving the way for the systematic design of durable, high-efficiency nanocatalysts.

Jeong, Chaehwa↗
DOE OSTI2022

Establishing the Role of Operating Potential and Mass Transfer in Multicarbon Product Generation for Photoelectrochemical CO 2 Reduction Cells Using a Cu Catalyst

There is increasing interest in the possibility of photoelectrochemical (PEC) reduction of CO 2 to C 2+ products; however, the criteria for maximizing PEC solar-to-C 2+ (STC 2+ ) rates are not well understood. We report here a continuum-scale model of PEC CO 2 reduction (CO 2 R) on Cu in 0.1 M CsHCO 3 and use it to optimize the design and operating conditions for generating C 2+ products. Furthermore, we demonstrate that the potential-dependent product distribution of CO 2 R on Cu requires operating near the potential that maximizes C 2+ generation rates ($V$ id ), unlike PEC water splitting, which desires operation at the maximum photocurrent density. Because of this requirement, the criterion for a high STC 2+ rate includes high-photocurrent semiconductors with photovoltages near $V$ id and low series resistance. The STC 2+ rate in these systems is enhanced by optimal CO 2 transport and exhibits low sensitivity to dirunal solar irradiance variations.

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

Lignin Derived Ionic Liquids: Synthesis and Application for Biopolymer Processing (CRADA Final Report)

We have established a scalable and economically viable process to convert lignin into ionic liquids for use in biopolymer processing. We have studied the four main topics: 1) lignin depolymerization to produce vanillin through oxidation, 2) lignin reduction to produce guaiacols, 3) oxidation process scale up, and 4) ionic liquid synthesis and application for biopolymer processing. The main accomplishment is summarized below: A maximal vanillin yield of 4.9% (8.8% total product yield) was achieved under optimal oxidation conditions using design of experiments (DOE); Aminophenol with 94.5% purity was synthesized via reductive amination using vanillin isolated from ion-exchange chromatography; At a higher lignin loading (10%), the vanillin yield in the scale up reaction was lower than the bench scale reaction; The filtration-based downstream separation of the scale-up process was able to recover 76% of vanillin; A maximal lignin reduction product (guaiacols) yield of 6.5% was achieved in the presence of Ru/C, formic acid, and methanol; The lignin reduction product yield and composition were affected by the use of different solvent and catalytic reagents (methanol in combination of Ru/C and formic acid gives the highest product yield); Lignin oxidation and reduction products: vanillin, acetovanillone, guaiacols, and eugenol are successfully used for IL synthesis; XX based ILs showed cellulose solubility with up to xx%; Technoeconomic analysis results indicate the potential of producing affordable ILs from kraft lignin (MSP: $14/kg); Life-cycle assessment results show the potential to reduce GHG emissions by up to 85% relative to existing ILs ([Ch][Lys]) with GHG emission: 1.2 kg CO 2e /kg of IL produced.

09 BIOMASS FUELS↗
DOE OSTI2025

Manufacturing Cost Analysis for PEM Electrolyzers and Perspectives for Future Cost Reduction

Electrolyzer capital costs strongly influence the total levelized cost of hydrogen production and have implications for hydrogen deployment. Current electrolyzer costs are high, and large cost reductions may be needed to achieve competitive hydrogen costs and targets. Understanding pathways for cost reduction via R&D and deployment is a critical research area for informed energy planning and enabling hydrogen use. This work presents bottom-up cost estimates of polymer electrolyte membrane (PEM) electrolyzer systems tied to design specifications and discusses perspectives for cost reduction opportunities based on ongoing research. We use a detailed manufacturing and process model for a 1 MW PEM electrolyzer stack and balance of plant (BOP) for rigorous cost estimation. This allows for robust estimates of component and manufacturing costs and examination of key cost contributors. Stack costs are dominated by material costs such as iridium and platinum catalysts, especially at high manufacturing rates; power electronics and hydrogen purification equipment are the largest contributors to BOP cost. At higher manufacturing rates, better equipment utilization could reduce stack costs significantly, and we estimate that experience and bulk purchasing will allow for cost reductions to some BOP components. Still, many well-established BOP technologies and stack material costs are less likely to see significant cost reductions at high manufacturing rates. As such, manufacturing scale is limited in how much it can reduce electrolyzer costs, and additional advances for cost reduction may be needed to achieve cost targets. It will likely take many combined strategies to achieve significant cost reductions for electrolyzers and enable low-cost hydrogen production. We can use our manufacturing cost model to quantify potential cost reductions from the considerations described above and demonstrate pathways to lower cost electrolyzers. This allows for better understanding of cost reduction strategies and enables more informed research, development, and deployment for electrolyzers.

cost↗
DOE OSTI2022

liionpack: A Python package for simulating packs of batteries with PyBaMM

Electrification of transport and other energy intensive activities is of growing importance as it provides an underpinning method to reduce carbon emissions. With an increase in reliance on renewable sources of energy and a reduction in the use of more predictable fossil fuels in both stationary and mobile applications, energy storage will play a pivotal role and batteries are currently the most widely adopted and versatile form. Therefore, understanding how batteries work, how they degrade, and how to optimize and manage their operation at large scales is critical to achieving emission reduction targets. The electric vehicle (EV) industry requires a considerable number of batteries even for a single vehicle, sometimes numbering in the thousands if smaller cells are used, and the dynamics and degradation of these systems, as well as large stationary power systems, is not that well understood. As increases in the efficiency of a single battery become diminishing for standard commercially available chemistries, gains made at the system level become more important and can potentially be realised more quickly compared with developing new chemistries. Mathematical models and simulations provide a way to address these challenging questions and can aid the engineer and designers of batteries and battery management systems to provide longer lasting and more efficient energy storage systems.

25 ENERGY STORAGE↗
DOE OSTI2024

The Significance of the 'Insignificant': Non-covalent Interactions in CO 2 Reduction Reactions with 3C-TM (TM=Sc-Zn) Single-Atom Catalysts

With energy shortages and excessive CO 2 emissions driving climate change, converting CO 2 into high-value-added products offers a promising solution for carbon recycling. We investigate CO 2 reduction reactions (CO2RR) catalyzed by 10 single-atom catalysts (SACs), incorporating weak non-covalent interactions, specifically lone pair-π and H-π interactions. The SACs, consisting of transition metals coordinated by three carbon atoms in a defective graphene substrate (3C-TM, TM=Sc-Zn), leverage these interactions to influence the energy fluctuations of intermediates and the limiting potentials of CO 2 RR, without altering the overall reaction pathway. Further, our findings show that SACs based on early transition metals (Sc, Ti, V, Cr) can serve as catalysts for C 1 products, including HCOOH, HCHO, CH 3 OH, and CH 4 , while those based on Fe and Co are suitable for CO formation. Driving force analysis helps bridge theoretical results with experimental observations and propose a modified approach for assessing hydrogen evolution reactions (HER) competition. SACs based on Ni and Cu exhibit moderate HER tolerance, while early transition metals excel in selective CO 2 reduction. We also identify a linear scaling relationship between the free energies of *COOH and *CO. This study offers valuable insights for future experimental studies and large-scale computational screenings.

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

Trade and Climate Mitigation Interactions Create Agro–Economic Opportunities With Social and Environmental Trade–Offs in Latin America and the Caribbean

The Latin America and the Caribbean (LAC) region plays key roles in both meeting global agricultural demands and maintaining carbon sinks due to its abundant land and water resources. In this study we use the Global Change Analysis Model (GCAM) to evaluate the opportunities and challenges posed by two global-scale drivers: agricultural market integration (i.e., reduction of trade barriers) and land-based climate mitigation policy. We evaluate their potential individual and combined impacts on agricultural production and trade revenues across LAC’s economies through mid-century, as well as the resulting impacts on agricultural consumers and integrated land-water-climate systems across the region’s diverse sub-regions. Increased global market integration results in increased agricultural production and trade revenues for many LAC economies driven by their evolving comparative advantages. Climate mitigation measures on CO 2 and non-CO 2 greenhouse gases increase revenues due to increased agricultural prices from land competition and emissions abatement. The combined outcomes from both drivers are complex and sometimes non-linear, highlighting the importance of understanding the interactions between multiple drivers. Our results show that increased agricultural production and trade opportunities pose significant trade-offs that require careful multi-sectoral planning, such as emissions reduction challenges, potential loss of livestock production when pursuing land-based climate mitigation strategies, increased consumer expenditures, and changes in land-use or water withdrawals, resulting in deforestation or water scarcity pressures. There is considerable heterogeneity in economic and environmental outcomes across LAC sub-regions and agricultural commodities, illustrating the value of considering outcomes at finer scales.

54 ENVIRONMENTAL SCIENCES↗