SEARCH · Search NASA

Results for “Multi- Component”

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

SourceResearch connectionFrom yearThrough year

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

At least 541 records · Page 30

All sources NASA NTRS DOE OSTI

DOE OSTI2022

Snowmass2021 Topical Group Report from AF07: Targets and Sources

For the next multi-megawatt accelerator generation, targets and other beam-intercepting components will face even more severe challenges due to the higher power densities, higher energy, and higher radiation. A comprehensive research and development program must be implemented to address the challenges. International collaborations such as RaDIATE or High Power Targetry Workshop should be leveraged and expanded to accelerate knowledge gain and avoid duplicated efforts. The next generation of high power targets will need novel designs allowing better high heat flux cooling methods, novel materials, advanced simulations, and better instrumentation. Four main R&D tracks were identified and discussed for targets. For electron sources, current state of art and challenges we are facing for key components such as cathodes, guns and injector design for sources R&D are presented for highly polarized electrons and unpolarized high current high brightness beams. For ion sources such as electron cyclotron resonance ion source (ECRIS), laser ion source (LIS), charge breeders, status of development are reviewed, and areas require investment for future R&D are discussed separately. Facilities critical for various source development are recommended.

43 PARTICLE ACCELERATORS↗

DOE OSTI2018

Adaptable, modular, multi-purpose space vehicle backplane

An adaptable, modular, multi-purpose (AMM) space vehicle backplane may accommodate boards and components for various missions. The AMM backplane may provide a common hardware interface and common board-to-board communications. Components, connectors, test points, and sensors may be embedded directly into the backplane to provide additional functionality, diagnostics, and system access. Other space vehicle sections may plug directly into the backplane.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2022

Development of a high-fidelity multi-cycle model of the NuScale small modular reactor using VERA

With growing renewables penetration, there is increased interest in flexible power operation for nuclear reactors. For multi-unit SMRs, in particular the NuScale SMR, which is an integral pressurized water reactor, there are opportunities to optimize flexible power operation across multiple units to limit the degradation of structural and control components. Here, we focus on degradation of in-core components, specifically the control rods and reactor pressure vessel. To perform these studies a high-fidelity, multi-cycle representation of the NuScale SMR is required, with a detailed representation of the structural and control components. To this end, the NuScale SMR has been modelled using the Virtual Environment for Reactor Applications (VERA) software. The entire transition to equilibrium is simulated, from Cycle 1 through to the equilibrium cycle. The equilibrium cycle model shows a good agreement with the NuScale design certification application (DCA) results, with differences attributable to a combination of using public domain data for the present study, and methodological differences. K-effective, power distributions, reactivity coefficients, and boron letdown curves are compared and all found to closely match. This shows that the VERA model is suitable for further studies. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2025

A multi model ensemble reveals net climate benefits from regenerative practices in US Midwest croplands

Process-based cropping systems models (CSMs) are key components of measurement, monitoring, reporting, and verification frameworks of carbon markets, but model-specific differences limit their applicability across diverse pedo-climatic conditions and agronomic practices. Multi-model ensemble (MME) provides an opportunity to better estimate changes in soil organic carbon (SOC) and nitrous oxide (N 2 O) emissions from agronomic practices at scale. We used an MME across 46 million hectares of US Midwest cropland at a resolution of 4-km 2 to assess the aggregate ability of different regenerative practices to sequester SOC and N 2 O emissions compared to their counterfactual dynamic baselines. MME was validated against long-term trials and compared to its constituent CSMs, showing greater accuracy and lower uncertainty. The results show that adopting no-till combined with cover crops increased SOC stocks by 0.36 ± 0.12 Mg ha -1 yr -1 , corresponding to a net regional SOC gain of 16.4 Tg C yr -1 compared to business-as-usual baselines. These benefits are halved when each management is practiced individually, and the SOC gains are only fully realized with low initial carbon stock. By including N 2 O emissions, we can assess the overall climate mitigation potential, specifically, the extent to which carbon sequestration can offset direct N 2 O emissions. The magnitude of this potential varies depending on management practices and geographic location with net climate benefits on average ranging from 0 to 3 Mg CO 2 -eq ha -1 yr -1 . High-resolution MME results allow for robust estimates of climate mitigation, reducing barriers to carbon market participation and supporting regenerative agriculture initiatives at scale.

carbon credits↗

DOE OSTI2026

Design, Processing, and Properties of WTaCrV-Hf Multi-principal Element Alloys

Refractory multi-principal element alloys are candidates for high-temperature structural components due, in part, to their high strength and high melting points. Single-phase materials are initially preferred for isotropic material properties as a function of time and temperature in service conditions. This work outlines a computational rank-ordering and experimental validation methodology for single-phase body-centered-cubic phase stability in WTaCrV-Hf alloys using order–disorder transition temperature. Eight compositions were fabricated by arc-melting and heat-treated at 1400 °C for 24 hrs. X-ray diffraction, energy-dispersive x-ray spectroscopy, and Vickers hardness testing showed alloys with order–disorder transition temperatures below 600 °C formed a single-phase body-centered-cubic structure during solidification and remained single-phase after heat-treatment. The sample possessing the lowest order–disorder transition temperature exhibited slip traces suggestive of room-temperature plastic deformation under Vickers indentation, with both heat-treated single-phase samples exhibiting hardnesses over 800 HV with little cracking compared to tungsten. These results establish order–disorder transition temperature as a viable predictive parameter for multi-principal element alloy phase stability. The methodology outlined in this work provides a framework for future design, fabrication, and characterization of high-temperature structural multi-principal element alloys.

CALPHAD↗

DOE OSTI2024

Modeling of Induction Motors and Variable Speed Drives for Multi-Domain System Simulations Using Modelica and the OpenIPSL Library

This paper introduces an innovative method for characterizing, implementing, and validating both three-phase and single-phase induction motor models, accompanied by a variable speed drive model. The primary goal is to investigate interactions between the electrical power grid and other dynamic domains (e.g., thermofluidic) that impact motor/load drive behavior. Our approach involves establishing a mechanical interface based on a physically meaningful equation linking motor torque/speed to the electrical model in the phasor domain. This allows seamless integration of diverse domain subsystems into a unified multi-domain model using Modelica v4.0.0 and the OpenIPSL library v3.0.1, overcoming co-simulation limitations. The proposed model, which requires only one Modelica-compliant tool for simulation, introduces additional dynamics through the mechanical interface, enabling explicit simulation of load disturbances based on constitutive physics. This deepens our understanding of dynamic interactions between the electrical power domain and other subsystems connected through the motor. We detail the modeled components using mathematical equations and textual descriptions, emphasizing the Modelica modeling approach. Simulation examples validate the implementation, demonstrating the multi-domain modeling capabilities of the newly developed components.

Computer Science↗

DOE OSTI2020

Taming the fixed-node error in diffusion Monte Carlo via range separation

By combining density-functional theory (DFT) and wave function theory via the range separation (RS) of the interelectronic Coulomb operator, we obtain accurate fixed-node diffusion Monte Carlo (FN-DMC) energies with compact multi-determinant trial wave functions. In particular, we combine here short-range exchange-correlation functionals with a flavor of selected configuration interaction known as configuration interaction using a perturbative selection made iteratively (CIPSI), a scheme that we label RS-DFT-CIPSI. One of the take-home messages of the present study is that RS-DFT-CIPSI trial wave functions yield lower fixed-node energies with more compact multi-determinant expansions than CIPSI, especially for small basis sets. Indeed, as the CIPSI component of RS-DFT-CIPSI is relieved from describing the short-range part of the correlation hole around the electron-electron coalescence points, the number of determinants in the trial wave function required to reach a given accuracy is significantly reduced as compared to a conventional CIPSI calculation. Importantly, by performing various numerical experiments, we evidence that the RS-DFT scheme essentially plays the role of a simple Jastrow factor by mimicking short-range correlation effects, hence avoiding the burden of performing a stochastic optimization. Considering the 55 atomization energies of the Gaussian-1 benchmark set of molecules, we show that using a fixed value of mu = 0.5 bohr(-1) provides effective error cancellations as well as compact trial wave functions, making the present method a good candidate for the accurate description of large chemical systems.

Scemama, Anthony↗

DOE OSTI2026

Agentic traffic intelligence: Augmented human-in-the-loop scenario generation for microscopic traffic simulation

Traditional microscopic traffic simulation generation often relies on static datasets and manual design, limiting its ability to simulate complex conditions easily. This paper presents a novel framework, Agentic Traffic Intelligence, which combines human approval large language models (LLMs), the Real-Twin tool, and multi-agent systems to perform realistic microscopic traffic simulation scenario generation. The proposed framework incorporates human-in-the-loop (HIL) control, retrieval-augmented generation (RAG), and multi-agent control mechanisms. HIL mechanisms are used to guide multiple LLMs focused on attributes for microscopic simulation generation and to improve the interpretability and transparency of LLM execution for users. RAG enhances context extraction by dynamically integrating external knowledge sources for traffic scenario generation foundations. A multi-agent architecture with supervisory control coordinates the interaction of simulation components, including traffic simulators, control logic, and calibration tools. This enables the synthesis of simulation-ready scenarios that reflect dynamic demand profiles and behavior controls. Furthermore, the framework fuses multisource traffic data with unstructured context and supports iterative refinement through interactive user feedback. Validated through microscopic simulation using Simulation of Urban Mobility, the generated scenarios demonstrate high-fidelity network generation with inflow and turn movement and behavioral calibration, offering a robust and efficient tool for stress-testing and optimizing urban mobility systems.

Hierarchical multi-agent control↗

DOE OSTI2023

Multi-scale modeling of the evolution of structure and properties in materials for nuclear energy applications

Nuclear energy is an important component of an overall strategy to address climate change. Idaho National Laboratory (INL) is the U.S. Department of Energy’s primary facility for research and development in nuclear science and technology for energy generation, supporting the improvement and life extension of the existing reactor fleet and the development and licensing of new reactor designs. Computational modeling is an important component of these activities, particularly in the area of materials for nuclear applications, where experimental data can be very challenging and expensive to acquire, and where data is especially scarce for new reactor designs. INL has used multi-scale modeling – linking atomistic, mesoscale, and engineering scales – to improve the ability to predict the performance of materials for nuclear energy applications. These modeling efforts make extensive of MOOSE (Multiphysics Object-Oriented Simulation Environment), a general-purpose open source finite element framework developed at INL. In this talk, I will give an overview of the approach and tools used, and several examples of application, including performance of nuclear fuels, understanding radiation-driven formation of nanoscale void and gas bubble superlattices, and powder densification through electric field assisted sintering.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2023

Multi-scale modeling of the evolution of structure and properties in materials for nuclear energy applications

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2019

Exact solution of multi-bunch instabilities for ultra-relativistic constant energy bunches in particle accelerators

In particle accelerators the multi-bunch beams of charged particles excite electromagnetic wakefields in the accelerating cavities and other beam-line components. These wakefields may cause instability in the longitudinal and transverse motion of these bunches leading to the beam loss. Thus, the analysis of such multi-bunch effects is critical in any accelerator design. Here in this paper, we present a new analytical method to exactly describe the multi-bunch transverse instabilities for ultra-relativistic electron bunches coasting at a constant energy through a uniform beam-focusing system. We discuss two cases: same bunch energy for all bunches and different energy from bunch to bunch. For the first case the solution is based on a special class of polynomials, while for the second case the solution is a finite sum of sinusoidal functions. We demonstrate the use of this approach with examples and compare the results of a numerical differential equation solver against our rigorous results. Our method could also be applied to the analysis of beam breakup within a single bunch. This approach can be extended beyond accelerator physics to study other many-body systems where an $n\mathrm{th}$ body is affected by only the preceding $n-1$ bodies.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2022

components for the MuMMI software release

The Department of Energy and the National Cancer Institute have developed new software for conducting multi-scale simulations of complex systems. This software, called the Multiscale Machine-Learned Modeling Infrastructure (MuMMI), couples simulations on three spatial scales to study slow, large-scale reorganizations of biomolecular systems with the speed of continuum and coarse-grained models while revealing selected interactions at full atomic precision. In these simulations, coarse-to-fine model conversions are used to spawn relevant fine-scale simulations along chosen order parameters, and fine-to-coarse feedback is used to iteratively improve the accuracy and multi-scale consistency of coarse-scale and continuum simulations. The complete MuMMI framework will be reviewed and released as open-source software by Lawrence Livermore National Laboratory. This review covers a subset of the MuMMI components that were developed exclusively at the Los Alamos National Laboratory.

Neale, Christopher↗

DOE OSTI2025

Multi-Scale Modeling of the Evolution of Structure and Properties in Materials for Nuclear Energy Applications [Slides]

Nuclear energy is an important component of an overall strategy to address climate change. Idaho National Laboratory (INL) is the U.S. Department of Energy’s primary facility for research and development in nuclear science and technology for energy generation, supporting the improvement and life extension of the existing reactor fleet and the development and licensing of new reactor designs. Computational modeling is an important component of these activities, particularly in the area of materials for nuclear applications, where experimental data can be very challenging and expensive to acquire, and where data is especially scarce for new reactor designs. INL has used multi-scale modeling – linking atomistic, mesoscale, and engineering scales – to improve the ability to predict the performance of materials for nuclear energy applications. In this talk, I will give an overview of the approach and tools used, and several examples of application, including performance of nuclear fuels, understanding radiation-driven formation of nanoscale void and gas bubble superlattices, and powder densification through electric field assisted sintering.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2026

Toward Intelligent Multimodal Holography for Real-Time Chemical Imaging of Dynamic Ion Separation

Molecular-level visualization of ion transport and separation dynamics in complex environments is crucial for advancing energy systems, water purification, and critical materials recovery. Achieving this requires imaging platforms that combine structural sensitivity, chemical specificity, and real-time operation. Digital off-axis holography (DOAH) provides high-throughput, label-free quantitative phase imaging but inherently lacks chemical selectivity. Integrating DOAH with complementary spectroscopic channels such as fluorescence or hyperspectral imaging introduces the needed molecular specificity, while also creating challenges in multimodal data fusion, synchronization, and computational throughput. Artificial intelligence offers a powerful route to address these limitations by uniting physics-based reconstruction with data-driven interpretation. In this Perspective, we outline a framework for intelligent multimodal holography and demonstrate its potential using a preliminary AI-driven test case. Raw DOAH holograms of lanthanide solutions subjected to magnetic field gradients were analyzed using multi-agent AI workflows that autonomously selected reconstruction tools, extracted NMF components, and generated scientific claims consistent with true paramagnetic and diamagnetic behavior. This demonstration shows how AI-enabled reasoning can deliver real-time chemical–structural interpretation directly from raw holograms. Together, these advances define a path toward adaptive, intelligent holography platforms capable of supporting in situ chemical separations, dynamic ion transport analysis, and next-generation interfacial science.

Ricchiuti, Giovanna↗

DOE OSTI2022

Concurrent Enhancement of Acetylene Uptake Capacity and Selectivity by Progressive Core Expansion and Extra–Framework Anions in Pore–Space–Partitioned Metal–Organic Frameworks

A multi-stage core-expansion method is proposed here as one component of the integrative binding-site/extender/core-expansion (BEC) strategy. The conceptual deconstruction of the partitioning ligand into three editable parts draws our focus onto progressive core expansion and allows the optimization of both acetylene uptake and selectivity. Herein the effectiveness of this strategy is shown through a family of eight cationic pore-partitioned materials containing three different partitioning ligands and various counter anions. The optimized structure, Co 3 -cpt-tph-Cl (Hcpt=4-(p-carboxyphenyl)-1,2,4-triazole, H-tph=(2,5,8-tri-(4-pyridyl)-1,3,4,6,7,9-hexaazaphenalene) with the largest surface area and highest C 2 H 2 uptake capacity (200 cm 3 /g at 298 K), also exhibits (desirably) the lowest CO 2 uptake and hence the highest C 2 H 2 /CO 2 selectivity. The successful boost in both C 2 H 2 capacity and IAST selectivity allows Co 3 -cpt-tph-Cl to rank among the best crystalline porous materials, ionic MOFs in particular, for C 2 H 2 uptake and C 2 H 2 /CO 2 experimental breakthrough separation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2026

Recoil-safe subtraction, matching and merging in e$^{+}$e$^{−}$ → hadrons

We present the first next-to-leading order matched and multi-jet merged predictions based on the Alaric parton shower. The components needed for infrared subtraction in the S-Mc@Nlo algorithm are computed analytically for the case of color singlet decays to hadronic final states and validated against existing approaches for up to e$^{−}$e$^{+}$ → 5 jets. Phenomenological results for e$^{−}$e$^{+}$ → hadrons at the Z pole are obtained with up to five jets at next-to-leading order precision, for the first time using an evolution algorithm with NLL-preserving kinematics mapping.

Höche, Stefan [Fermilab] (ORCID:0000000213706059)↗

DOE OSTI2023

Characterization of microstructure and residual stress following the friction stir welding of dissimilar aluminum alloys

Friction-stir-welding (FSW) has gained importance as an effective way to join dissimilar materials due to its solid-state nature. However, FSW produces substantial residual stresses in aluminum welding, often deteriorating the component's structural performance and reliability. In the current study, the d-spacing (inter-atomic distance) of several locations on a battery tray and stress-free reference samples are measured with neutron diffraction to calculate the residual stresses in a lap 6061 to A365 dissimilar friction-stir-weld. Furthermore, the present study connects the measured residual stress to microstructure properties through electron backscatter diffraction (EBSD) and optical microscopy analyses. The EBSD results indicate that the FSW operation affects the grains’ orientation, thereby producing location-specific directionally varying elasticity across the weldment. Further, this varied elasticity creates unique d-spacing profiles even in the stress-free material. Additionally, the resulting stressed and stress-free d-spacing profiles show dependencies on the FSW tool geometry, traverse direction, and rotational direction. Lastly, this study suggests that the final component residual stress can be influenced by the sequence of multi-pass welds contributing to a rise in temperature in the presence of a completed weld relaxing its residual stress.

36 MATERIALS SCIENCE↗

DOE OSTI2024

A techno-economic survey of energy storage media for long-duration energy storage applications

Energy storage technologies that can economically store and provide electricity over multi-day and seasonal timescales are likely to be a critical component of a sustainable and resilient energy system. In this analysis, we perform a broad survey of energy storage technologies to find storage media (SM) that are promising for these long-duration energy storage (LDES) applications. The energy capital cost of the SM is identified as a key figure of merit for LDES. We develop a data collection framework to collect material price and physical property data, which are used to calculate the energy capital cost floor for 376 SM. These costs are then compared with cost targets for the LDES applications. The results show a multitude of thermal and chemical SM are economically promising, including some synthetic fuels, sensible thermal, latent thermal, thermochemical, and batteries based on low-cost materials. In contrast, currently deployed energy storage systems such as lithium-ion batteries and pumped hydro storage do not appear to be promising systems for LDES applications.

25 ENERGY STORAGE↗