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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 397 records · Page 22
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Effect of Yagi–Uda nano-antenna element shape on the directivity and radiation efficiency

In this paper, different optimal designs of Yagi–Uda nano-antennas (NAs) are introduced and analyzed based on different element shapes to maximize the directivity and radiation efficiency. The studied element shapes include triangular, hexagonal, cube, square, rotated square, rectangular, ellipsoid, and elliptical cylinder shapes. The NAs parameters for each design are optimized using particle swarm optimization algorithm to achieve high directivity at a wavelength of 500 nm for wireless point-to-point applications. The designs are numerically analysed using 3-D finite difference time domain method (3-D FDTD) via Lumerical software package. To illustrate the performance of the proposed antennas, different radiation parameters such as radiation pattern, directivity, and radiation efficiency have been studied. Moreover, a tolerance of ± 5% is calculated to consider the imperfections that may appear in the fabrication process at a nanoscale. The optimized rectangular prism NA achieves the highest directivity of 24.21 with an efficiency of 50.74%. However, the optimized triangular prism NA has the highest efficiency of 73% with a directivity of 20.89. This enhancement is mainly attributed to the efficient coupling between array elements along with low side lobe level. However, a trade-off between directivity and radiation efficiency is obtained by the hexagonal prism NA with directivity of 21.9 and radiation efficiency of 69.1%.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2025

Optimizing fused silica debris shield use in the National Ignition Facility

The National Ignition Facility (NIF) deliberately and routinely operates with its final optics exposed to fluences likely to induce and grow damage. This choice has enabled the NIF to operate at energies previously unachievable at the expense of limitations to delivered power and energy contingent on the ability to repair damage on the final optics. Prior to the introduction of the fused silica debris shield (FSDS), the grating debris shield (GDS) was the optic type on the NIF most prone to damage and hence a primary limiter to the delivered energy. The introduction of the FSDS has reduced the damage initiation rate on the GDS by about two orders of magnitude to date. Despite the FSDS being a disposable optic, it is important to understand how the FSDS damages and when its damage requires it to be exchanged to maximize the FSDS lifetime while still protecting the GDS from damage. We will define the FSDS exchange criteria and evaluate the damage initiation mechanisms of the FSDS. The surface damage morphologies provide insight into the impact of the various damage mechanisms that limit the FSDS lifetime. These results are utilized in our analysis to optimize the FSDS exchange criteria to further extend the GDS lifetime.

42 ENGINEERING↗
DOE OSTI2017

Topology-Aware Performance Optimization and Modeling of Adaptive Mesh Refinement Codes for Exascale

Here, we introduce a topology-aware performance optimization and modeling workflow for AMR simulation that includes two new modeling tools, ProgrAMR and Mota Mapper, which interface with the BoxLib AMR framework and the SSTmacro network simulator. ProgrAMR allows us to generate and model the execution of task dependency graphs from high-level specifications of AMR-based applications, which we demonstrate by analyzing two example AMR-based multigrid solvers with varying degrees of asynchrony. Mota Mapper generates multiobjective, network topology-aware box mappings, which we apply to optimize the data layout for the example multigrid solvers. While the sensitivity of these solvers to layout and execution strategy appears to be modest for balanced scenarios, the impact of better mapping algorithms can be significant when performance is highly constrained by network hop latency. Furthermore, we show that network latency in the multigrid bottom solve is the main contributing factor preventing good scaling on exascale-class machines.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Low-order preconditioning of the Stokes equations

A well-known strategy for building effective preconditioners for higher-order discretizations of some PDEs, such as Poisson's equation, is to leverage effective preconditioners for their low-order analogs. In this work, we show that high-quality preconditioners can also be derived for the Taylor–Hood discretization of the Stokes equations in much the same manner. In particular, we investigate the use of geometric multigrid based on the Q 1 iso Q 2 /Q 1 discretization of the Stokes operator as a preconditioner for the Q 2 /Q 1 discretization of the Stokes system. We utilize local Fourier analysis to optimize the damping parameters for Vanka and Braess–Sarazin relaxation schemes and to achieve robust convergence. Furthermore, these results are then verified and compared against the measured multigrid performance. While geometric multigrid can be applied directly to the Q 2 /Q 1 system, our ultimate motivation is to apply algebraic multigrid within solvers for Q 2 /Q 1 systems via the Q 1 iso Q 2 /Q 1 discretization, which will be considered in a companion paper.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Design Optimization Study on the Single Tank Packed-bed Thermal Energy Storage System

Idaho National Laboratory (INL) is establishing the Dynamic Energy Transport and Integration Lab (DETAIL) as part of its commitment to research on nuclear-renewable hybrid energy systems and associated advanced reactor technologies. DETAIL is designed to allow several different energy systems to work in unison. Current plans include a PWR simulator, high-temperature steam electrolysis (HSTE) unit, and a renewable energy system (e.g., photovoltaics). DETAIL will provide the real world basis for studies on the systems integration and system configurations to be completed. Encompassed in the DETAIL program is the Thermal Energy Storage (TES) system. The TES system is one of the key components in DETAIL because it allows for the delayed release of energy and can be used to simulate storage capabilities currently being considered by utility providers. Of the various TES concepts, this paper deals with the single-tank packed bed TES system. Particular attention is given to the transient thermal behavior of fluid and solid particles within the packed bed thermocline tank and heat storage efficiency influenced by various design parameters. The effects of tank geometry (height-to-diameter ratio), filler size, filler packing ratio and operating temperature differentials are investigated. Based on the parametric study and cost analysis, the optimal TES tank design for DETAIL is discussed.

25 ENERGY STORAGE↗
DOE OSTI2015

Low cost back contact heterojunction solar cells on thin c-Si wafers. Integrating laser and thin film processing for improved manufacturability

An interdigitated back contact (IBC) Si wafer solar cell with deposited a-Si heterojunction (HJ) emitter and contacts is considered the ultimate single junction Si solar cell design. This was confirmed in 2014 by both Panasonic and Sharp Solar producing IBC-HJ cells breaking the previous record Si solar cell efficiency of 25%. But manufacturability at low cost is a concern for the complex IBC-HJ device structure. In this research program, our goals were to addressed the broad industry need for a high-efficiency c-Si cell that overcomes the dominant module cost barriers by 1) developing thin Si wafers synthesized by innovative, kerfless techniques; 2) integrating laser-based processing into most aspects of solar cell fabrication, ensuring high speed and low thermal budgets ; 3) developing an all back contact cell structure compatible with thin wafers using a simplified, low-temperature fabrication process; and 4) designing the contact patterning to enable simplified module assembly. There were a number of significant achievements from this 3 year program. Regarding the front surface, we developed and applied new method to characterize critical interface recombination parameters including interface defect density Dit and hole and electron capture cross-section for use as input for 2D simulation of the IBC cell to guide design and loss analysis. We optimized the antireflection and passivation properties of the front surface texture and a-Si/a-SiN/a-SiC stack depositions to obtain a very low (< 6 mA/cm2) front surface optical losses (reflection and absorption) while maintaining excellent surface passivation (SRV<5 cm/s). We worked with kerfless wafer manufacturers to apply defect-engineering techniques to improve bulk minority-carrier lifetime of thin kerfless wafers by both reducing initial impurities during growth and developing post-growth gettering techniques. This led insights about the kinetics of nickel, chromium, and dislocations in PV-grade silicon and to achieving millisecond lifetimes in kerfless silicon materials. Laser fired contacts to n-Si were developed for the first time using a Al/Sb/Ti metal stack giving contact resistances < 5 mOhm-cm2 when fired through several different dielectric layers. A new 2 step laser+chemical etch isolation technique was developed using a sacrificial top coating which avoids laser damage to Si passivation. Regarding the heterojunction emitter, analysis of front FHJ (1D) and IBC (2D) cells with range of p-layer conditions found that a 2-stage high/low doped p-layer was optimum: the low doped region has lower defects giving higher Voc and the high doped region gave a better contact to the metal. A significant effort was spent studying the patterning process and its contribution to degradation of passivation and reproducibility. Several promising new cleaning, contact and deposition patterning and processing approaches were implemented leading to fabrication of several runs with cells having 19-20% efficiency which were stable over several months. This program resulted in the training and support of 12 graduate students, publication of 21 journal papers and 14 conference papers.

14 SOLAR ENERGY↗
DOE OSTI2015

Low cost back contact heterojunction solar cells on thin c-Si wafers. integrating laser and thin film processing for improved manufacturability

An interdigitated back contact (IBC) Si wafer solar cell with deposited a-Si heterojunction (HJ) emitter and contacts is considered the ultimate single junction Si solar cell design. This was confirmed in 2014 by both Panasonic and Sharp Solar producing IBC-HJ cells breaking the previous record Si solar cell efficiency of 25%. But manufacturability at low cost is a concern for the complex IBC-HJ device structure. In this research program, our goals were to addressed the broad industry need for a high-efficiency c-Si cell that overcomes the dominant module cost barriers by 1) developing thin Si wafers synthesized by innovative, kerfless techniques; 2) integrating laser-based processing into most aspects of solar cell fabrication, ensuring high speed and low thermal budgets ; 3) developing an all back contact cell structure compatible with thin wafers using a simplified, low-temperature fabrication process; and 4) designing the contact patterning to enable simplified module assembly. There were a number of significant achievements from this 3 year program. Regarding the front surface, we developed and applied new method to characterize critical interface recombination parameters including interface defect density Dit and hole and electron capture cross-section for use as input for 2D simulation of the IBC cell to guide design and loss analysis. We optimized the antireflection and passivation properties of the front surface texture and a-Si/a-SiN/a-SiC stack depositions to obtain a very low (< 6 mA/cm2) front surface optical losses (reflection and absorption) while maintaining excellent surface passivation (SRV<5 cm/s). We worked with kerfless wafer manufacturers to apply defect-engineering techniques to improve bulk minority-carrier lifetime of thin kerfless wafers by both reducing initial impurities during growth and developing post-growth gettering techniques. This led insights about the kinetics of nickel, chromium, and dislocations in PV-grade silicon and to achieving millisecond lifetimes in kerfless silicon materials. Laser fired contacts to n-Si were developed for the first time using a Al/Sb/Ti metal stack giving contact resistances < 5 mOhm-cm2 when fired through several different dielectric layers. A new 2 step laser+chemical etch isolation technique was developed using a sacrificial top coating which avoids laser damage to Si passivation. Regarding the heterojunction emitter, analysis of front FHJ (1D) and IBC (2D) cells with range of p-layer conditions found that a 2-stage high/low doped p-layer was optimum: the low doped region has lower defects giving higher Voc and the high doped region gave a better contact to the metal. A significant effort was spent studying the patterning process and its contribution to degradation of passivation and reproducibility. Several promising new cleaning, contact and deposition patterning and processing approaches were implemented leading to fabrication of several runs with cells having 19-20% efficiency which were stable over several months. This program resulted in the training and support of 12 graduate students, publication of 21 journal papers and 14 conference papers.

14 SOLAR ENERGY↗
DOE OSTI2014

Geometry optimization for micro-pressure sensor considering dynamic interference

Presented is the geometry optimization for piezoresistive absolute micro-pressure sensor. A figure of merit called the performance factor (PF) is defined as a quantitative index to describe the comprehensive performances of a sensor including sensitivity, resonant frequency, and acceleration interference. Three geometries are proposed through introducing islands and sensitive beams into typical flat diaphragm. The stress distributions of sensitive elements are analyzed by finite element method. Multivariate fittings based on ANSYS simulation results are performed to establish the equations about surface stress, deflection, and resonant frequency. Optimization by MATLAB is carried out to determine the dimensions of the geometries. Convex corner undercutting is evaluated. Each PF of the three geometries with the determined dimensions is calculated and compared. Silicon bulk micromachining is utilized to fabricate the prototypes of the sensors. The outputs of the sensors under both static and dynamic conditions are tested. Experimental results demonstrate the rationality of the defined performance factor and reveal that the geometry with quad islands presents the highest PF of 210.947 Hz{sup 1/4}. The favorable overall performances enable the sensor more suitable for altimetry.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2017

FY17 Status Report on the Initial Development of a Constitutive Model for Grade 91 Steel

Grade 91 is a candidate structural material for high temperature advanced reactor applications. Existing ASME Section III, Subsection HB, Subpart B simplified design rules based on elastic analysis are setup as conservative screening tools with the intent to supplement these screening rules with full inelastic analysis when required. The Code provides general guidelines for suitable inelastic models but does not provide constitutive model implementations. This report describes the development of an inelastic constitutive model for Gr. 91 steel aimed at fulfilling the ASME Code requirements and being included into a new Section III Code appendix, HBB-Z. A large database of over 300 experiments on Gr. 91 was collected and converted to a standard XML form. Five families of Gr. 91 material models were identified in the literature. Of these five, two are potentially suitable for use in the ASME code. These two models were implemented and evaluated against the experimental database. Both models have deficiencies so the report develops a framework for developing and calibrating an improved model. This required creating a new modeling method for representing changes in material rate sensitivity across the full ASME allowable temperature range for Gr. 91 structural components: room temperature to 650° C. On top of this framework for rate sensitivity the report describes calibrating a model for work hardening and softening in the material using genetic algorithm optimization. Future work will focus on improving this trial model by including tension/compression asymmetry observed in experiments and necessary to capture material ratcheting under zero mean stress and by improving the optimization and analysis framework.

36 MATERIALS SCIENCE↗
DOE OSTI2014

Stochastic approximation methods-Powerful tools for simulation and optimization: A survey of some recent work on multi-agent systems and cyber-physical systems

Stochastic approximation methods have found extensive and diversified applications. Recent emergence of networked systems and cyber-physical systems has generated renewed interest in advancing stochastic approximation into a general framework to support algorithm development for information processing and decisions in such systems. This paper presents a survey on some recent developments in stochastic approximation methods and their applications. Using connected vehicles in platoon formation and coordination as a platform, we highlight some traditional and new methodologies of stochastic approximation algorithms and explain how they can be used to capture essential features in networked systems. Distinct features of networked systems with randomly switching topologies, dynamically evolving parameters, and unknown delays are presented, and control strategies are provided.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

Dynamic Event Tree advancements and control logic improvements

The RAVEN code has been under development at the Idaho National Laboratory since 2012. Its main goal is to create a multi-purpose platform for the deploying of all the capabilities needed for Probabilistic Risk Assessment, uncertainty quantification, data mining analysis and optimization studies. RAVEN is currently equipped with three different sampling categories: Forward samplers (Monte Carlo, Latin Hyper Cube, Stratified, Grid Sampler, Factorials, etc.), Adaptive Samplers (Limit Surface search, Adaptive Polynomial Chaos, etc.) and Dynamic Event Tree (DET) samplers (Deterministic and Adaptive Dynamic Event Trees). The main subject of this document is to report the activities that have been done in order to: start the migration of the RAVEN/RELAP-7 control logic system into MOOSE, and develop advanced dynamic sampling capabilities based on the Dynamic Event Tree approach. In order to provide to all MOOSE-based applications a control logic capability, in this Fiscal Year an initial migration activity has been initiated, moving the control logic system, designed for RELAP-7 by the RAVEN team, into the MOOSE framework. In this document, a brief explanation of what has been done is going to be reported. The second and most important subject of this report is about the development of a Dynamic Event Tree (DET) sampler named “Hybrid Dynamic Event Tree” (HDET) and its Adaptive variant “Adaptive Hybrid Dynamic Event Tree” (AHDET). As other authors have already reported, among the different types of uncertainties, it is possible to discern two principle types: aleatory and epistemic uncertainties. The classical Dynamic Event Tree is in charge of treating the first class (aleatory) uncertainties; the dependence of the probabilistic risk assessment and analysis on the epistemic uncertainties are treated by an initial Monte Carlo sampling (MCDET). From each Monte Carlo sample, a DET analysis is run (in total, N trees). The Monte Carlo employs a pre-sampling of the input space characterized by epistemic uncertainties. The consequent Dynamic Event Tree performs the exploration of the aleatory space. In the RAVEN code, a more general approach has been developed, not limiting the exploration of the epistemic space through a Monte Carlo method but using all the forward sampling strategies RAVEN currently employs. The user can combine a Latin Hyper Cube, Grid, Stratified and Monte Carlo sampling in order to explore the epistemic space, without any limitation. From this pre-sampling, the Dynamic Event Tree sampler starts its aleatory space exploration. As reported by the authors, the Dynamic Event Tree is a good fit to develop a goal-oriented sampling strategy. The DET is used to drive a Limit Surface search. The methodology that has been developed by the authors last year, performs a Limit Surface search in the aleatory space only. This report documents how this approach has been extended in order to consider the epistemic space interacting with the Hybrid Dynamic Event Tree methodology.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

Hydrogen adsorption and desorption with 3D silicon nanotube-network and film-network structures: Monte Carlo simulations

Hydrogen is clean, sustainable, and renewable, thus is viewed as promising energy carrier. However, its industrial utilization is greatly hampered by the lack of effective hydrogen storage and release method. Carbon nanotubes (CNTs) were viewed as one of the potential hydrogen containers, but it has been proved that pure CNTs cannot attain the desired target capacity of hydrogen storage. In this paper, we present a numerical study on the material-driven and structure-driven hydrogen adsorption of 3D silicon networks and propose a deformation-driven hydrogen desorption approach based on molecular simulations. Two types of 3D nanostructures, silicon nanotube-network (Si-NN) and silicon film-network (Si-FN), are first investigated in terms of hydrogen adsorption and desorption capacity with grand canonical Monte Carlo simulations. It is revealed that the hydrogen storage capacity is determined by the lithium doping ratio and geometrical parameters, and the maximum hydrogen uptake can be achieved by a 3D nanostructure with optimal configuration and doping ratio obtained through design optimization technique. For hydrogen desorption, a mechanical-deformation-driven-hydrogen-release approach is proposed. Compared with temperature/pressure change-induced hydrogen desorption method, the proposed approach is so effective that nearly complete hydrogen desorption can be achieved by Si-FN nanostructures under sufficient compression but without structural failure observed. The approach is also reversible since the mechanical deformation in Si-FN nanostructures can be elastically recovered, which suggests a good reusability. This study may shed light on the mechanism of hydrogen adsorption and desorption and thus provide useful guidance toward engineering design of microstructural hydrogen (or other gas) adsorption materials.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Hydrogen bond arrangements in (H 2 O) 20, 24, 28 clathrate hydrate cages: Optimization and many-body analysis

Here we provide a detailed study of hydrogen bonding arrangements, relative stability, residual entropy, and an analysis of the many-body effects in the (H 2 O) 20 (D-cage), (H 2 O) 24 (T-cage), and (H 2 O) 28 (H-cage) hollow cages making up structures I (sI) and II (sII) of clathrate hydrate lattices. Based on the enumeration of the possible hydrogen bonding networks for a fixed oxygen atom scaffold, the residual entropy (S 0 ) of these three gas phase cages was estimated at 0.754 82, 0.754 44, and 0.754 17 · Nk b , where N is the number of molecules and k b is Boltzmann’s constant. A previously identified descriptor of enhanced stability based on the relative arrangement and connectivity of nearest-neighbor fragments on the polyhedral water cluster [strong-weak-effective-bond model] also applies to the larger hollow cages. The three cages contain a maximum of 7, 9, and 11 such preferable arrangements of trans nearest dimer pairs with one “free” OH bond on the donor molecule (t1d dimers). The Many-Body Expansion (MBE) up to the 4-body suggests that the many-body terms vary nearly linearly with the cluster binding energy. Using a hierarchical approach of screening the relative stability of networks starting from optimizations with the TIP4P, TTM2.1-F, and MB-pol classical potentials, subsequently refining at more accurate levels of electronic structure theory (DFT and MP2), and finally correcting for zero-point energy, we were able to identify a group of four low-lying isomers of the (H 2 O) 24 T-cage, two of which are antisymmetric and the other two form a pair of antipode configurations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2014

Geospatial Optimization of Siting Large-Scale Solar Projects

Recent policy and economic conditions have encouraged a renewed interest in developing large-scale solar projects in the U.S. Southwest. However, siting large-scale solar projects is complex. In addition to the quality of the solar resource, solar developers must take into consideration many environmental, social, and economic factors when evaluating a potential site. This report describes a proof-of-concept, Web-based Geographical Information Systems (GIS) tool that evaluates multiple user-defined criteria in an optimization algorithm to inform discussions and decisions regarding the locations of utility-scale solar projects. Existing siting recommendations for large-scale solar projects from governmental and non-governmental organizations are not consistent with each other, are often not transparent in methods, and do not take into consideration the differing priorities of stakeholders. The siting assistance GIS tool we have developed improves upon the existing siting guidelines by being user-driven, transparent, interactive, capable of incorporating multiple criteria, and flexible. This work provides the foundation for a dynamic siting assistance tool that can greatly facilitate siting decisions among multiple stakeholders.

14 SOLAR ENERGY↗
DOE OSTI2023

A decision support tool for e-waste recycling operations using the hen-and-chicks bio-inspired optimization metaheuristic

E-waste from end-of-life electrical and electronic devices is one of the fastest growing waste streams from households and businesses. E-waste recycling yields environmental sustainability and economic benefits. Due to continuous changes in e-waste types and compositions, recycling businesses face challenges to optimize their operational configuration to achieve better economic and environmental performance. To help e-waste recyclers mitigate this problem, we have developed a modular decision support tool called the Comprehensive Manufacturing Assessment Tool (CMAT) that can simulate both e-waste recycling operations and economics. This tool can give valuable insights regarding the profitability of the entire operation and different e-waste types. In addition, a new bio-inspired metaheuristic optimization algorithm, hen-and-chicks optimization (HACO), was developed to assign manpower to different workstations to maximize operational efficiencies. According to the results of our case study, laptops, desktops, and computer peripherals are the three electronic waste products that produce the most profit. Our examination of the sensitivity of material prices shows that the price of steel has the most significant influence on total profit, because it is the most widely used material in the majority of electronic devices. We have released the decision support tool as open-source software under a general public license. It could be customized for other recycling industries beyond e-waste to achieve business sustainability by making their operations more efficient.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2015

MO-FG-204-06: A New Algorithm for Gold Nano-Particle Concentration Identification in Dual Energy CT

Purpose: Gold nano-particle (GNP) has recently attracted a lot of attentions due to its potential as an imaging contrast agent and radiotherapy sensitiser. Imaging the GNP at its low contraction is a challenging problem. We propose a new algorithm to improve the identification of GNP based on dual energy CT (DECT). Methods: We consider three base materials: water, bone, and gold. Determining three density images from two images in DECT is an under-determined problem. We propose to solve this problem by exploring image domain sparsity via an optimization approach. The objective function contains four terms. A data-fidelity term ensures the fidelity between the identified material densities and the DECT images, while the other three terms enforces the sparsity in the gradient domain of the three images corresponding to the density of the base materials by using total variation (TV) regularization. A primal-dual algorithm is applied to solve the proposed optimization problem. We have performed simulation studies to test this model. Results: Our digital phantom in the tests contains water, bone regions and gold inserts of different sizes and densities. The gold inserts contain mixed material consisting of water with 1g/cm3 and gold at a certain density. At a low gold density of 0.0008 g/cm3, the insert is hardly visible in DECT images, especially for those with small sizes. Our algorithm is able to decompose the DECT into three density images. Those gold inserts at a low density can be clearly visualized in the density image. Conclusion: We have developed a new algorithm to decompose DECT images into three different material density images, in particular, to retrieve density of gold. Numerical studies showed promising results.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Towards a Robust Adaptive Digital Twin for Fusion Applications

The development of a digital twin system for fusion applications is essential for enhancing the prediction, analysis, and optimization of complex plasma processes. Machine learning (ML), particularly deep learning has demonstrated strong capabilities in modeling such highly nonlinear and intricate systems. However, two critical challenges limit the deployment of deep learning-based digital twins: Uncertainty Quantification (UQ) and data drift. UQ is vital for ensuring trustworthy predictions, especially in decision-support scenarios. Additionally, data-driven models are often sensitive to changes in the underlying data distribution, such as shot-to-shot variations in fusion experiments, which can lead to performance degradation over time. To address these challenges, we are developing an uncertainty-aware, adaptive digital twin framework. Our approach incorporates deep learning models enhanced with Gaussian Process approximations for predictive uncertainty estimation, coupled with an online learning mechanism that enables continuous model adaptation to new experimental data. This adaptive capability allows the data driven models to respond effectively to evolving plasma behaviors and equipment conditions. Specifically, to mitigate the effects of shot-to-shot drift, our system updates itself incrementally as new data becomes available, improving both robustness and fidelity. Our vision is to evolve this data driven model into a self-sustaining digital twin system that leverages UQ based feedback to continuously refine itself and potentially support real-time decision making. This presentation will cover a brief background on uncertainty quantification for ML, our ongoing effort on development of UQ capabilities for ML, our data science pipeline from data collection to model development and analysis and online learning framework for modeling coil deflection at DIII-D. I will also briefly touch upon opportunities and challenges in development of digital twin framework.

Sammuli, Brian [General Atomics]↗
DOE OSTI2015

Strategic coating of NdFeB magnets with Dy to improve the coercivity of permanent magnets

Here, we present a method, supported by theoretical analysis, for optimizing the usage of the critical rare earth element dysprosium in Nd 2 Fe 14 B (NdFeB)-based permanent magnets. In this method, we use Dy selectively in locations such as magnet edges and faces, where demagnetization factors are most significant, rather than uniformly throughout the bulk sample. A 200 nm thick Dy film was sputtered onto commercial N-38, NdFeB magnets with a thickness of 3 mm and post-annealed at temperatures from 600 - 700 C. Magnets displayed enhanced coercivities after post-annealing. Furthermore, our experimental results indicate as large as a 5 percent increase in the energy product of NdFeB magnets, achieved for a total Dy weight percentage of 0.06 percent, much less than that used in commercial grade Dy-NdFeB magnets. Finally, by assuming all Dy diffused into NdFeB magnets, the improvement in energy product corresponds to a saving of over 1% Dy (critical element). Magnets manufactured using this technique will therefore be higher performing and significantly less expensive than those made presently.

36 MATERIALS SCIENCE↗