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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 811 records · Page 45
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Multi-frequency electrical impedance tomography

Apparatus includes a plurality of geological subsurface electrical line sensors spaced apart from each other proximate a predetermined geological subsurface region of interest, with at least one of the electrical line sensors situated as a line source to produce a multi-frequency electrical impedance tomography source signal, and with at least one of the electrical line sensors situated as a line detector to receive the multi-frequency electrical impedance tomography response signal associated with the source signal that propagates through the predetermined geological subsurface region of interest, and a controller including a processor and a memory configured with instructions that, when executed by the processor, cause the processor to determine an electrical mapping over the predetermined geological subsurface region of interest based on the multi-frequency electrical impedance tomography source signal, response signal, and the spatial positions of the geological subsurface electrical line sensors.

Karra, Satish↗
DOE OSTI2022

Multi-axis Accelerometry and Rotation Sensing using a Point Source Atom Interferometer

A point source atom interferometer (PSI) is a device where atoms are split and recombined by applying a temporal sequence of Raman pulses during the expansion of a cloud of cold atoms behaving approximately as a point source. Unlike a conventional light pulse atom interferometer, the PSI can produce a signal that corresponds to multi-axis rotation only, independent of acceleration. In addition, it can be used to measure acceleration along one direction, independent of rotation. Here, we describe a modified PSI that can be used to measure multi-axis rotation and multi-axis acceleration. Specifically, this type of PSI can be used to measure two-axes rotation around the directions perpendicular to the light pulses, as well as the acceleration in all three directions, with only one pair of Raman beams. Using two pairs of Raman beams in orthogonal directions sequentially, such a scheme would enable the realization of a complete atom interferometric inertial measurement unit.

Li, Jinyang↗
DOE OSTI2023

Multi-core high-temperature, irradiation-resistant thermocouple, and related methods

A multi-core thermocouple includes a plurality of wires, an insulation core surrounding the plurality of wires, a sheath surrounding the insulation core, and a plurality of electrical junctions. The plurality of electrical junctions may include a first electrical junction formed between a first wire of the plurality of wires and the sheath at a first axial mid-section of the multi-core thermocouple, the first electrical junction including a first swaged axial mid-section of the sheath and a second electrical junction formed between a second wire of the plurality of wires and the sheath at a second, different axial mid-section of the multi-core thermocouple, the second electrical junction including a second swaged axial mid-section of the sheath.

Skifton, Richard S.↗
DOE OSTI2023

Multi-chip photonics transceiver

A photonics transceiver is described herein, wherein the photonics transceiver exhibits improved areal bandwidth density and improved energy per bit consumption relative to conventional photonics transceivers. The photonics transceiver achieves an areal bandwidth density of at least 5 Tbps/mm2 with an energy consumption of less than 500 fJ/bit (sum of energy consumed for both a transmitted bit and a received bit). The photonics transceiver is a multi-chip module, where chips in the multi-chip module are tightly integrated with one another. The multi-chip module includes light source, photodetector, photonics, and control/logic chips. The photonics chip includes transparent conducting oxide integrated optical modulators and multiplexers and demultiplexers based on MEMS-tunable optical ring resonators.

Wood, Michael↗
DOE OSTI2024

Multi-physics Modeling of Radiative Heat Transfer and Fluid Flow for the Reactor Cavity Cooling System

High-temperature gas-cooled reactors (HTGRs) are notable for their high thermal efficiency and potential for combined heat and power applications. These reactors are particularly appealing due to their advanced passive safety features. HTGRs utilize passive safety systems that function without requiring active components like pumps or compressors during emergencies. These reactor designs depend on a Reactor Cavity Cooling System (RCCS) to manage decay heat removal from the reactor pressure vessel (RPV) during accident conditions. The RCCS consists of vertical rectangular channels known as "risers" or riser ducts positioned around the RPV. These risers receive heat from the RPV through both convective and radiative heat transfer mechanisms. Understanding the interplay of multiple physical phenomena, such as fluid dynamics, heat transfer, and neutron interactions, is essential for the effective design and operation of nuclear reactors, particularly for systems like the RCCS. Multi-physics simulations provide a comprehensive approach to studying these interactions, offering detailed insights and enhancing accuracy. They are especially important in RCCS designs, where the interaction between radiative and convective heat transfer can significantly impact system performance. By leveraging multi-physics simulations, complex reactor behaviors can be modeled without compromising the fidelity of the underlying physical processes. This work aims to establish a robust methodology for coupling multiple physical processes in an air-cooled RCCS. By focusing on validating this multi-physics approach, the study involves designing test cases that simulate various conditions to verify the numerical models employed. The outcomes of this research will provide critical insights for accurately modeling and optimizing complex nuclear systems like the RCCS.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2026

Multi-Agent Control Planes for Quantum Networks: A Scalable Architecture for Autonomous Quantum Internet Management

Quantum networks are expected to enable distributed quantum computing, secure communication, and global entanglement distribution. However, operating such networks presents significant challenges, including stochastic quantum processes, fragile entanglement resources, dynamic topology, and cross-layer control requirements. Current quantum network control architectures largely rely on centralized or hierarchical controllers inspired by classical software-defined networking (SDN). While effective for small testbeds, these approaches face scalability, latency, and reliability limitations as quantum networks grow. This paper proposes a multi-agent control plane architecture for quantum networks. In this design, intelligent software agents operate at quantum nodes, repeaters, and orchestration layers, collectively managing entanglement generation, routing, purification, and scheduling. The distributed intelligence of the agent system allows the network to adapt dynamically to quantum hardware variability and environmental noise. We argue that multi-agent systems provide significant advantages over centralized control approaches, including scalability, resilience, local autonomy, and real-time adaptation. The paper discusses architectural design principles, agent coordination mechanisms, and research challenges in deploying multi-agent control planes for the emerging quantum Internet.

Alnajjar, Anees [ORNL] (ORCID:0000000237101601)↗
DOE OSTI2020

Gradient-Based Multi-Area Distribution System State Estimation

The increasing distributed and renewable energy resources and controllable devices in distribution systems make fast distribution system state estimation (DSSE) crucial in system monitoring and control. We consider a large multi-phase distribution system and formulate DSSE as a weighted least squares (WLS) problem. We divide the large distribution system into smaller areas of subtree structure, and by jointly exploring the linearized power flow model and the network topology, we propose a gradient-based multi-area algorithm to exactly and efficiently solve the WLS problem. The proposed algorithm enables distributed and parallel computation of the state estimation problem without compromising any performance. Numerical results on a 4,521-node test feeder show that the designed algorithm features fast convergence and accurate estimation results. Comparison with traditional Gauss-Newton method shows that the proposed method has much better performance in distribution systems with a limited amount of reliable measurement. The real-time implementation of the algorithm tracks time-varying system states with high accuracy.

41 EE - Solar Energy Technologies Office (EE-4S)↗
NASA NTRS2015

An Assessment of the SEA Multi-Element Sensor for Liquid Water Content Calibration of the NASA GRC Icing Research Tunnel

The NASA Glenn Icing Research tunnel has been using an Icing Blade technique to measure cloud liquid water content (LWC) since 1980. The IRT conducted tests with SEA Multi-Element sensors from 2009 to 2011 to assess their performance in measuring LWC. These tests revealed that the Multi-Element sensors showed some significant advantages over the Icing Blade, particularly at higher water contents, higher impingement rates, and large drop sizes. Results of these and other tests are presented here.

multi-wire↗
DOE OSTI2021

Frequency Domain Multi-user Processing for Single Carrier Modulation with Cyclic Prefix

Frequency domain (FD) detection and precoding have been shown to be effective means of approaching the theoretical per-user capacity for single carrier modulation SCM) schemes. When a cyclic prefix is added to the SCM waveform, the circulant structures of the resulting convolutional channel matrix allows for relatively simple expressions for the FD processing, and achieves performance near the theoretical capacity even for high signal to noise ratio values. This paper details the signal processing for uplink and downlink multi-user operation with a multi-antenna base station.

5G and Beyond Communication↗
DOE OSTI2020

Determining Multi-Component Phase Diagrams with Desired Characteristics Using Active Learning

Herein, we demonstrate how to predict and experimentally validate phase diagrams for multi-component systems from a high-dimensional virtual space of all possible phase diagrams involving several elements based on small existing experimental data. The experimental data for bulk phases for known systems represents a sampling from this space, and screening the space allows multi-component phase diagrams with given design criteria to be built. This approach uses machine learning methods to predict phase diagrams and Bayesian experimental design to minimize experiments for refinement and validation, all within an active learning loop. The approach is proven by predicting and synthesizing the ferroelectric ceramic system (1-ω)(Ba 0.61 Ca 0.28 Sr 0.11 TiO 3 )-ω(BaTi 0.888 Zr 0.0616 Sn 0.0028 Hf 0.0476 O 3 ) with a relatively high transition temperature and triple point, as well as the NiTi-based pseudo-binary phase diagram (1-ω)(Ti 0.309 Ni 0.485 Hf 0.20 Zr 0.006 )-ω(Ti 0.309 Ni 0.485 Hf 0.07 Zr 0.068 Nb 0.068 ) designed for high transition temperature (ω ≤ 1). Each phase diagram is validated and optimized through only three new experiments. The complexity of these compounds is beyond the reach of today’s computational methods.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Multi–Step Nucleation of a Crystalline Silicate Framework via a Structurally Precise Prenucleation Cluster

Hierarchical nucleation pathways are ubiquitous in the synthesis of minerals and materials. In the case of zeolites and metal–organic frameworks, pre-organized multi-ion “secondary building units” (SBUs) have been proposed as fundamental building blocks. However, detailing the progress of multi-step reaction mechanisms from monomeric species to stable crystals and defining the structures of the SBUs remains an unmet challenge. Furthermore, combining in situ nuclear magnetic resonance, small-angle X-ray scattering, and atomic force microscopy, we show that crystallization of the framework silicate, cyclosilicate hydrate, occurs through an assembly of cubic octameric Q 3 8 polyanions formed through cross-linking and polymerization of smaller silicate monomers and other oligomers. These Q 3 8 are stabilized by hydrogen bonds with surrounding H 2 O and tetramethylammonium ions (TMA + ). When Q 3 8 levels reach a threshold of ≈32 % of the total silicate species, nucleation occurs. Further growth proceeds through the incorporation of [(TMA) x (Q 3 8 )•n H 2 O] (x–8) clathrate complexes into step edges on the crystals.

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

A practical extension of the recursive multi-fidelity model for the emulation of hole closure experiments

We report in regimes of high strain rate, the strength of materials often cannot be measured directly in experiments. Instead, the strength is inferred based on an experimental observable, such as a change in shape, that is matched by simulations supported by a known strength model. In hole closure experiments, the rate and degree to which a central hole in a plate of material closes during a dynamic loading event are used to infer material strength parameters. Due to the complexity of the experiment, many computationally expensive, three-dimensional simulations are necessary to train an emulator for calibration or other analyses. These simulations can be run at multiple grid resolutions, where dense grids are slower but more accurate. In an effort to reduce the computational cost, a combination of simulations with different resolutions can be combined to develop an accurate emulator within a limited training time. We explore the novel design and construction of an appropriate functional recursive multi-fidelity emulator of a strength model for tantalum in hole closure experiments that can be applied to arbitrarily large training data. Hence, by formulating a multi-fidelity model to employ low-fidelity simulations, we were able to reduce the error of our emulator by approximately 81% with only an approximately 1.6% increase in computing resource utilization.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Autonomous direct freeform fabrication strategy for multi-axis additive manufacturing

Multi-axis additive manufacturing (M-AM) enables precise material deposition along both planar and curved layers, eliminating the need for support structures through a continuous material deposition approach. In contrast to conventional 2-dimensional planar layers constrained to a fixed building orientation, the deposition on freeform layers demands the specification of guided curves to determine material deposition directions which are no longer to be fixed to a build direction. There are challenges that arise when fabricating components with multiple “build” directions, necessitating the decomposition of geometries and the specification of guided curves for the resulting volumes. Furthermore, multi-axis systems introduce heightened challenges due to an increased degree of freedom in motion. Consequently, the potential risks of collision between the deposited geometry and the motion platform become a notable concern. This research proposes a freeform layering algorithm to address the challenge of seamless transitions between planar and curved layers in the process planning of M-AM. The algorithm computes 3D “printable” layers by leveraging topological information derived from the geometry to be built and integrates collision-free manufacturability considerations into the computational process. These accumulated volumes serve as a “substrate” and support volumes for subsequent deposition, allowing later layers to be built without the need for additional support material. In conclusion, the proposed method successfully devises a freeform layering approach suitable for intricate models that demand substantial support, thus enabling the fabrication of diverse geometries in a manner previously unachievable.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Quantum multi-programming for Grover’s search

Quantum multi-programming is a method utilizing contemporary noisy intermediate-scale quantum computers by executing multiple quantum circuits concurrently. Despite early research on it, the research remains on quantum gates or small-size quantum algorithms without correlation. In this paper, we propose a quantum multi-programming (QMP algorithm for Grover's search. Our algorithm decomposes Grover's algorithm by the partial diffusion operator and executes the decomposed circuits in parallel by QMP. We proved that this new algorithm increases the rotation angle of the Grover operator which, as a result, increases the success probability. The new algorithm is implemented on IBM quantum computers and compared with the canonical Grover's algorithm and other variations of Grover's algorithms. So, the empirical tests validate that our new algorithm outperforms other variations of Grover's algorithms as well as the canonical Grover's algorithm.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Multi-fidelity Uncertainty Quantification for Homogenization Problems in Structure-Property Relationships from Crystal Plasticity Finite Elements

Crystal plasticity finite element method (CPFEM) has been an integrated computational materials engineering (ICME) workhorse to study materials behaviors and structure-property relationships for the last few decades. These relations are mappings from the microstructure space to the materials properties space. Due to the stochastic and random nature of microstructures, there is always some uncertainty associated with materials properties, for example, in homogenized stress-strain curves. For critical applications with strong reliability needs, it is often desirable to quantify the microstructure-induced uncertainty in the context of structure-property relationships. However, this uncertainty quantification (UQ) problem often incurs a large computational cost because many statistically equivalent representative volume elements (SERVEs) are needed. In this article, we apply a multi-level Monte Carlo (MLMC) method to CPFEM to study the uncertainty in stress-strain curves, given an ensemble of SERVEs at multiple mesh resolutions. By using the information at coarse meshes, we show that it is possible to approximate the response at fine meshes with a much reduced computational cost. We focus on problems where the model output is multi-dimensional, which requires us to track multiple quantities of interest (QoIs) at the same time. In conclusion, our numerical results show that MLMC can accelerate UQ tasks around 2.23x, compared to the classical Monte Carlo (MC) method, which is widely known as ensemble average in the CPFEM literature.

36 MATERIALS SCIENCE↗
DOE OSTI2022

A multi-stage stochastic programming model for adaptive biomass processing operation under uncertainty

Variations of physical and chemical characteristics of biomass reduce equipment utilization and increase operational costs of biomass processing. Biomass processing facilities use sensors to monitor the changes in biomass characteristics. Integrating sensory data into the operational decisions in biomass processing will increase its flexibility to the changing biomass conditions. In this paper, we propose a multi-stage stochastic programming model that minimizes the expected operational costs by identifying the initial inventory level and creating an operational decision policy for equipment speed settings. These policies take the sensory information data and the current biomass inventory level as inputs to dynamically adjust inventory levels and equipment settings according to the changes in the biomass' characteristics. We ensure that a prescribed target reactor utilization is consistently achieved by penalizing the violation of the target reactor feeding rate. A case study is developed using real-world data collected at Idaho National Laboratory's biomass processing facility. We show the value of multi-stage stochastic programming from an extensive computational experiment. Our sensitivity analysis indicates that updating the infeed rate of the system, the processing speed of equipment, and bale sequencing based on the moisture level of biomass improves the processing rate of the reactor and reduces operating costs.

09 BIOMASS FUELS↗
DOE OSTI2021

Multi-physics Peridynamic Modeling of Damage Processes in Protective Coatings

Protective coatings can revolutionize the aerospace industry by providing a way to build a fuel-efficient and low-emission gas turbine engine operating at elevated temperature. Currently, significant challenges persist in the multi-physics modeling of damage processes in protective coatings exposed to the hot corrosive environment of gas turbine engine. Examples of such detrimental processes include an interface damage between different material layers forming protective coating, a formation of the through-the-thickness vertical cracks, a diffusion of oxygen and moisture through those cracks, an oxidation, and a delamination. In this paper, a feasibility of a multi-physics peridynamic model to provide insight to these detrimental processes has been demonstrated. 3-Dimensional peridynamic equations which are valid everywhere, including dynamically evolving discontinuities, have been presented. In conclusion, validation and demonstration have been shown for conduction heat transfer, reactive oxidation, and delamination of protective coating with a composition borrowed from the open literature.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

On dysprosium utilisation in multi-main-phase Nd–Dy–Fe–B magnets with core–shell microstructures

The development of high-performance Nd–Dy–Fe–B magnets that minimise the consumption of the scarce rare earth (RE) element Dy remains a major global scientific and technological quest. Here, we designed an alloy microstructure comprising of a uniform Dy-lean core–Dy-rich shell in a series of multi-main-phase (MMP) Nd–Dy–Fe–B magnets. The resulting MMP Dy1 and Dy3 magnets with an overall Dy level of 1 and 3 wt.% possessed values of 0.48 and 0.29 T/wt.% of coercivity increment per unit weight percentage of the Dy addition, respectively. Most importantly, the resulting MMP Dy3 magnet exhibited a high coercivity (2.38 T), an excellent thermal stability of the coercivity (|β| = 0.531%/°C), a high squareness factor (> 95%), all with little diminishment in the remanent magnetisation (1.35 T) and maximum energy product (43.6 MGOe). These properties are superior to the currently available sintered Nd–Dy–Fe–B magnets which utilise higher levels of Dy of 5 wt.%. Via magnetic and multi-scale microstructural characterisation experiments and micromagnetic simulations, the formation of the Dy-lean core–Dy-rich shell microstructure is rationalised via solid-state-diffusion and solution reprecipitation during liquid-phase sintering. The Dy-lean core–Dy-rich shell microstructure and the non-ferromagnetic low-Fe RE-rich grain boundary phase led to the synergistic magnetic performance. This is significant in the context of the MMP Nd–Dy–Fe–B magnets being applied to large-scale production. The present work establishes a pathway for the more sustainable utilisation of Dy in permanent magnets via formation of a uniform core–shell microstructure.

36 MATERIALS SCIENCE↗