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At least 1,207 records · Page 67

Thermal modeling of directed energy deposition additive manufacturing using graph theory

Purpose: The purpose of this paper is to develop, apply and validate a mesh-free graph theory–based approach for rapid thermal modeling of the directed energy deposition (DED) additive manufacturing (AM) process. Design/methodology/approach: Here, the authors develop a novel mesh-free graph theory–based approach to predict the thermal history of the DED process. Subsequently, the authors validated the graph theory predicted temperature trends using experimental temperature data for DED of titanium alloy parts (Ti-6Al-4V). Temperature trends were tracked by embedding thermocouples in the substrate. The DED process was simulated using the graph theory approach, and the thermal history predictions were validated based on the data from the thermocouples. Findings: The temperature trends predicted by the graph theory approach have mean absolute percentage error of approximately 11% and root mean square error of 23°C when compared to the experimental data. Moreover, the graph theory simulation was obtained within 4 min using desktop computing resources, which is less than the build time of 25 min. By comparison, a finite element–based model required 136 min to converge to similar level of error. Research limitations/implications: This study uses data from fixed thermocouples when printing thin-wall DED parts. In the future, the authors will incorporate infrared thermal camera data from large parts. Practical implications: The DED process is particularly valuable for near-net shape manufacturing, repair and remanufacturing applications. However, DED parts are often afflicted with flaws, such as cracking and distortion. In DED, flaw formation is largely governed by the intensity and spatial distribution of heat in the part during the process, often referred to as the thermal history. Accordingly, fast and accurate thermal models to predict the thermal history are necessary to understand and preclude flaw formation. Originality/value: This paper presents a new mesh-free computational thermal modeling approach based on graph theory (network science) and applies it to DED. The approach eschews the tedious and computationally demanding meshing aspect of finite element modeling and allows rapid simulation of the thermal history in additive manufacturing. Although the graph theory has been applied to thermal modeling of laser powder bed fusion (LPBF), there are distinct phenomenological differences between DED and LPBF that necessitate substantial modifications to the graph theory approach.

42 ENGINEERING↗

Singe Library Review: XCAP Review Report

Singe is a computational library for simulating thermonuclear reactions written in C++14. It was inspired by the earlier Singe library, developed by Joann Campbell. From the beginning of the Singe project, the goal has been to create a library that provides the necessary functionality, runs efficiently, and is flexible enough to connect to a variety of multi-physics host codes. Such a library allows subject-matter experts to focus on development within the library, while library staff can support host-code staff in integrating Singe into their multi-physics codes. A common library used across multiple multi-physics codes allows those subject-matter experts to roll out new features to all host codes simultaneously, and eases the process of code-to-code comparison between codes that are leveraging the same physics in different ways. The Singe effort was established by Joann Campbell, who provided significant guidance on the goals, requirements, and philosophy of the library. It has been developed by Brendan K. Krueger, CJ Solomon, Jesse Canfield, and Terry Adams, with computer science support from Tyler Reddy and Karen Tsai. Discussions with multiple potential stakeholders have been critical to the planning of such a cross-cutting project, including representatives from multiple host codes and Brian Haines who helped define usage and needs for the inertial confinement fusion (ICF) program. This document is based on the XCAP review process. It is an updated version of the initial document distributed to the reviewers, memo XCP-2:21-005. We want to acknowledge the time and effort of the reviewers who participated in this process: Philipp Edelmann, Alan Harrison, Christopher Malone, Edward Norris, Ryosuke Park, Galen Shipman, CJ Solomon, and any others who may have contributed to the feedback that was provided to us.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Technology Area Roadmap for In Space Propulsion Technologies

This slide presentation reviews the technology area (TA) roadmap to develop propulsion technologies that will be used to enable further exploration of the solar system, and beyond. It is hoped that development of the technologies within this TA will result in technical solutions that will improve thrust levels, specific impulse, power, specific mass, volume, system mass, system complexity, operational complexity, commonality with other spacecraft systems, manufacturability and durability. Some of the propulsion technologies that are reviewed include: chemical and non-chemical propulsion, and advanced propulsion (i.e., those with a Technology Readiness level of less than 3). Examples of these advanced technologies include: Beamed Energy, Electric Sail, Fusion, High Energy Density Materials, Antimatter, Advanced Fission and Breakthrough propulsion technologies. Timeframes for development of some of these propulsion technologies are reviewed, and top technical challenges are reviewed. This roadmap describes a portfolio of in-space propulsion technologies that can meet future space science and exploration needs.

Johnson, Les↗

Final report- UFL - RAPIDS2: A SciDAC Institute for Computer Science, Data, and Artificial Intelligence

The research initiatives supported by the U.S. Department of Energy (DOE) Grant DE-SC0022265 are fundamentally aimed at pioneering advanced machine learning (ML) techniques for scientific data compression within high-performance computing (HPC) environments. This comprehensive body of work addresses the critical challenge posed by the exponential growth of data generated by scientific simulations in domains such as fusion energy, climate modeling, and computational fluid dynamics (CFD). A core objective is to develop compression algorithms that achieve substantial data reduction—often by orders of magnitude—while rigorously ensuring the fidelity of both the primary data (PD) and scientifically crucial derived quantities of interest (QoI). The methodologies deployed under this grant integrate sophisticated deep learning architectures, prominently featuring autoencoders, advanced generative models like conditional diffusion, and hybrid learning techniques. Key innovations include the development of Guaranteed Autoencoders (GAE) and the Guaranteed Conditional Diffusion with Tensor Correction (GCDTC) framework, which provide explicit, instance-level error bounds on reconstructed data. Furthermore, specialized strategies such as nonlinear constraint satisfaction are employed to preserve the integrity of QoI, a vital requirement for the trustworthiness of downstream scientific analyses. This research also focuses on the design and implementation of scalable, GPU-accelerated software pipelines that seamlessly integrate into existing HPC workflows, ensuring both computational efficiency and practical applicability. The CAESAR framework, for example, unifies foundation and generative models to create an adaptive and efficient compression solution for spatio-temporal scientific data. Collectively, these efforts represent a significant advancement in mitigating the scientific data deluge, enabling more effective data management, accelerated scientific discovery, and optimized utilization of HPC resources.

97 MATHEMATICS AND COMPUTING↗

Suppressing simulation bias in multi-modal data using transfer learning

Abstract Many problems in science and engineering require making predictions based on few observations. To build a robust predictive model, these sparse data may need to be augmented with simulated data, especially when the design space is multi-dimensional. Simulations, however, often suffer from an inherent bias. Estimation of this bias may be poorly constrained not only because of data sparsity, but also because traditional predictive models fit only one type of observed outputs, such as scalars or images, instead of all available output data modalities, which might have been acquired and simulated at great cost. To break this limitation and open up the path for multi-modal calibration, we propose to combine a novel, transfer learning technique for suppressing the bias with recent developments in deep learning, which allow building predictive models with multi-modal outputs. First, we train an initial neural network model on simulated data to learn important correlations between different output modalities and between simulation inputs and outputs. Then, the model is partially retrained, or transfer learned, to fit the experiments; a method that has never been implemented in this type of architecture. Using fewer than 10 inertial confinement fusion experiments for training, transfer learning systematically improves the simulation predictions while a simple output calibration, which we design as a baseline, makes the predictions worse. We also offer extensive cross-validation with real and carefully designed synthetic data. The method described in this paper can be applied to a wide range of problems that require transferring knowledge from simulations to the domain of experiments.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Physics principles of inertial confinement fusion and U.S. program overview

Inertial confinement fusion (ICF) has existed as a field of study since the 1970s, but the field was born out of the Cold War. In the decades since the 1960s, pioneering research developing the principles and technologies of ICF culminated in the creation of three major Department of Energy facilities that still exist today, the National Ignition Facility (NIF) at Lawrence Livermore National Lab, the OMEGA laser at the Laboratory for Laser Energetics, and the Z pulsed power facility at Sandia National Laboratories. While the technology of ICF facilities themselves is fascinating, this review concentrates upon the physics principles of the targets fielded on U.S. ICF facilities and upon results from the last decade of research. Furthermore, while there have been periods of frustration on the road to ICF ignition, recent research has demonstrated great leaps in understanding what aspects of the implosions need more control. Tangible progress in ICF is evident as burning plasmas and ignited plasmas have recently been generated, repeatedly, on the NIF stemming from decades of science and engineering understanding generated from work on the above three facilities and international community.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

A provably stable numerical method for the anisotropic diffusion equation in confined magnetic fields

We present a novel numerical method for solving the anisotropic diffusion equation in magnetic fields confined to a periodic box which is accurate and provably stable. We derive energy estimates of the solution of the continuous initial boundary value problem. A discrete formulation is presented using operator splitting in time with the summation by parts finite difference approximation of spatial derivatives for the perpendicular diffusion operator. Weak penalty procedures are derived for implementing both boundary conditions and parallel diffusion operator obtained by field line tracing. We prove that the fully-discrete approximation is unconditionally stable. Discrete energy estimates are shown to match the continuous energy estimate given the correct choice of penalty parameters. A nonlinear penalty parameter is shown to provide an effective method for tuning the parallel diffusion penalty and significantly minimises rounding errors. Several numerical experiments, using manufactured solutions, the “NIMROD benchmark” problem and a single island problem, are presented to verify numerical accuracy, convergence, and asymptotic preserving properties of the method. Finally, we present a magnetic field with chaotic regions and islands and show the contours of the anisotropic diffusion equation reproduce key features in the field.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Stability of the fcc phase in shocked nickel up to 332 GPa

Despite making up 5-20 wt.% of Earth’s predominantly iron core, the melting properties of elemental nickel at core conditions remain poorly understood, due largely to a dearth of experimental data. We present here an in situ X-ray diffraction study performed on laser shock-compressed samples of bulk nickel, reaching pressures up to ~ 500 GPa. Hugoniot states of nickel were targeted using a flat-top laser drive, with in situ X-ray diffraction data collected using the Linac Coherent Light Source. Rietveld methods were used to determine the densities of the shocked states from the measured diffraction data, while peak pressures were determined using a combination of measured particle velocities, shock transit times, hydrodynamic simulations, and laser intensity calibrations. We observed solid compressed face-centered cubic (fcc) Ni up to at least 332 ± 30 GPa along the Hugoniot—significantly higher than expected from the majority of melt lines that have been proposed for nickel. We also bracket the partial melting onset to between 377 ± 38 GPa and 486 ± 35 GPa.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

3D modeling of the Staged Z-pinch with the FLASH code

The Staged Z-pinch (SZP) fusion concept is a magneto-inertial compression scheme developed by Magneto-Inertial Fusion Technologies, Inc. (MIFTI), in which small amounts of fusion fuel are brought to fusion-relevant conditions by passing multi-million amperes strong current through a cylindrical shell of high atomic number material. One- and two-dimensional modeling performed by MIFTI with the MACH2 code, suggests that net fusion energy gain can be achieved when currents in the 10 million amperes range compress a 50%-50% mixture of deuterium and tritium gas. In this project we enhance and use the FLASH code to execute high-fidelity, simulations of various SZP configurations, a collaboration between the Flash Center for Computational Science at the University of Rochester and the Laboratory for Laser Energetics, and MIFTI. FLASH is a high-performance computing, multi-physics, radiation magnetohydrodynamic (MHD) code with extended physics capabilities, which is developed at the Flash Center. The goal of this project is to assess the shell/fuel stability of the pinch to two- and three-dimensional MHD instabilities and to utilize FLASH’s extended physics capabilities to understand how extended-MHD effects impact implosion dynamics and plasma conditions at stagnation. The project is a natural extension of an ongoing collaborative effort between MIFTI and the Flash Center through the U.S. DOE Advanced Research Projects Agency-Energy (ARPA-E) BETHE program and can provide MIFTI with simulation capabilities that are currently beyond their reach with MACH2. Ultimately, MIFTI wants FLASH to become one of their simulation workhorses for reliable, high-fidelity SZP platform design. During the project, the Flash Center team developed a suite of in one- and two-dimensional FLASH simulations to model different variants of the SZP platform, performed code-to-code comparisons with MACH2, and used the FLASH code to design and model SZP experiments like the Double Eagle experiments that MIFTI recently performed. Also, the Flash Center team developed the capabilities of FLASH to be able to do three-dimensional simulations of pulsed-power experiments with the code for the first time. Two publications from this effort are currently under review and two more are in preparation. MIFTI has also committed to the use of FLASH for future SZP simulation efforts.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Roadmap for warm dense matter physics

This roadmap presents the state-of-the-art, current challenges and near future developments anticipated in the thriving field of warm dense matter (WDM) physics. Originating from strongly coupled plasma physics, high pressure physics and high energy density science, the WDM physics community has recently taken a giant leap forward. This is due to spectacular developments in laser technology, diagnostic capabilities, and computer simulation techniques. Only in the last decade has it become possible to perform accurate enough simulations & experiments to truly verify theoretical results as well as to reliably design experiments based on predictions. Consequently, this roadmap discusses recent developments of and contemporary challenges for theoretical methods and experimental techniques needed to describe, create and diagnose WDM. A large part of this roadmap is dedicated to specific WDM systems and applications in astrophysics, inertial confinement fusion and novel material synthesis.

dense astrophysical objects↗

Effects of size, geometry, and testing temperature on additively manufactured Ti-6Al-4V titanium alloy

This article presents a comprehensive study concerning size and geometry effect on the ambient and high-temperature mechanical behavior of additively manufactured laser powder bed fusion Ti-6Al-4V alloy. Key mechanical property metrics are presented, including strain hardening rate, yield strength, and Young’s modulus as a function of thickness and testing temperature (ambient, 250 °C, and 450 °C). Here, the effect of specimen size on manufacturing-induced microstructural feature formation is demonstrated and discussed. A detailed analysis regarding Young’s modulus, yield strength, and strain hardening rate variation at elevated temperatures is also presented. Size effect and temperature-sensitive deformation mechanisms are linked to the underlying microstructural deformation mechanisms activated at respective temperatures. Counter-intuitively, this study determined that irrespective of the geometry, strain hardening rates increased as temperature increased. An in-depth microstructural examination is presented to explain the stated observation. The texture of Interrupted tensile test samples examined for ambient, 250 °C, and 450 °C post-yield was observed to be unchanged, indicating the strain hardening behavior was not texture dependent. Schmid factor analysis, coupled with experimental findings from previous work, was implemented to generate a hypothesis. This hypothesis suggests that the drop in critical resolved shear stress for basal and pyramidal slip systems, as temperature increases, paired with the high dislocation density of laser powder bed fusion Ti-6Al-4V, leads to dislocation entanglement and results in increased strain hardening at elevated temperatures.

36 MATERIALS SCIENCE↗

Plasmon-enhanced ultralow-threshold solid-state triplet fusion upconversion

Triplet fusion upconversion has potential applications in solar cells, photoredox catalysis, additive manufacturing and bioimaging. However, solid-state upconversion systems have struggled to measure up to their solution-phase counterparts, often requiring enormous optical power densities to operate at the maximum efficiency. Here we substantially improve the performance of upconversion films through excitation with surface plasmons that propagate along a planar silver-film interface, leading to an absorption enhancement that reduces the intensity threshold I th by a factor of 19 and enhances the external quantum efficiency by a factor of 17. From this, we achieve I th values as low as 3.4 mW cm −2 and an external quantum efficiency up to 0.094%. To demonstrate real-world viability, we couple the upconversion film to plasmons generated by the near-field of excitons in an organic light-emitting diode. As a result, this scheme is then used to fabricate a white-emitting organic light-emitting diode where blue emission sources from plasmon-excited upconversion, achieving a high colour rendering index of 86.2 and setting precedent for blue emission in the absence of high-energy polarons or triplets.

36 MATERIALS SCIENCE↗

Advanced Fabrication Techniques of Metal Hydrides for Science and Technology Applications (Abbreviated Final Report)

Lithium Hydride (LiH) atomic properties make it an excellent candidate for thermal energy storage, hydrogen storage, and nuclear reactor technology. High Energy Density (HED) experiments on LiH at the National Ignition Facility (NIF) can also provide critical Equation of State (EOS) and Hugoniot data. Density requirements for LiH vary per application and therefore physical and structural requirements for LiH are non-uniform. Historical production of LiH relies on casting processesthat are limited by density and grain-size control, which leads to unfavorable machinable characteristics. LiH manufacturing is further hindered due to its chemical reactivity and propensity to readily react with moisture. This work aimed at exploring advanced fabrication techniques for LiH such as 1) uniaxial powder pressing methods and 2) laser powder bed fusion (L-PBF) additive manufacturing. Uniaxial powder compaction offers advantageous tailorable mechanical and physical properties via density control, and L-PBF can produce net-shaped complex parts with unique microstructure. Uniaxial pressing proved successful in readily producing LiH with density control.

36 MATERIALS SCIENCE↗

Advanced Fabrication Techniques of Metal Hydrides for Science and Technology Applications (Full Technical Report)

Lithium Hydride (LiH) atomic properties make it an excellent candidate for thermal energy storage, hydrogen storage, and nuclear reactor technology. High Energy Density (HED) experiments on LiH at the National Ignition Facility (NIF) can also provide critical Equation of State (EOS) and Hugoniot data. Density requirements for LiH vary per application and therefore physical and structural requirements for LiH are non-uniform. Historical production of LiH relies on casting processes that are limited by density and grain-size control, which leads to unfavorable machinable characteristics. LiH manufacturing is further hindered due to its chemical reactivity and propensity to readily react with moisture. This work aimed at exploring advanced fabrication techniques for LiH such as 1) uniaxial powder pressing methods and 2) laser powder bed fusion (L-PBF) additive manufacturing. Uniaxial powder compaction offers advantageous tailorable mechanical and physical properties via density control, and L-PBF can produce net-shaped complex parts with unique microstructure. Uniaxial pressing proved successful in readily producing LiH with density control.

36 MATERIALS SCIENCE↗

In Situ Analysis of Laser Powder Bed Fusion Using Simultaneous High-Speed Infrared and X-ray Imaging

Laser powder bed fusion is a metal additive manufacturing technique that has received significant scientific and industrial attention over the past decades. However, the quality and reproducibility of parts manufactured by this technique is still a problem. Overcoming this issue requires an understanding of multiple complex physical phenomena which occur simultaneously during the process. Here, we illustrate a powerful new technique which synchronizes high-speed x-ray imaging with high-speed infrared imaging to study laser powder bed fusion processes in real time. Using this technique, we demonstrate the simultaneous observation of multiple phenomena including three-dimensional melt pool visualization, vapor plume dynamics, spatter formation, thermal history, and point cooling rates. The paired observation of these dynamic phenomena is critical to understanding the fundamentals of laser powder bed fusion, and the overall impact of process parameters on print quality.

36 MATERIALS SCIENCE↗