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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 73 records · Page 4

Effect of laser melt schedule on the microstructure of additively manufactured IN718 Superalloy

Laser powder bed fusion (L-PBF) has enabled the fabrication of geometrically complex metallic structures and components that are challenging to producing using conventional manufacturing approaches. The site-specific and far from equilibrium thermal conditions of L-PBF offer the potential to facilitate multi-length scale design of structure and properties across the atomic-through macro-levels. However, L-PBF systems face scalability challenges due to throughput constraints. Laser rotary powder bed fusion (L-RPBF) systems are being investigated as a solution to enhance the deposition rates compared to conventional L-PBF. Rotary systems also offer additional flexibility for controlling the time structure of melting through laser interleaving on alternating layers. Here, in this study, IN718 test samples were printed using single-laser or interleaved dual-laser configuration in a L-RPBF system to investigates the effect of process settings and melt-interleaving on as-fabricated microstructure. The microstructural evolution, such as grain size and crystallographic texture, was assessed by determining variations in the melt-pool shapes. Laser interleaving leads to a reduction in average grain size compared to single laser by ∼ 40 % at high power (400 W) and by ∼36 % at medium power (370 W). Results presented here identify key challenge for obtaining uniform microstructures and barriers for the broader adoption of high-deposition rate L-RPBF.

Dual-laser↗

Operando carbon corrosion measurements in fuel cells using boron-doped carbon supports

Carbonaceous materials are the most common catalyst supports in proton exchange membrane fuel cell (PEMFCs), yet their corrosion is one of the limiting factors in achieving high durability. Herein, we doped carbon supports with boron (B) to increase the corrosion-resistance of the support. Two types of B-doped carbons were synthesized and studied as platinum support materials. Further, they varied in their morphologies, surface areas, and the types of boron species. The durability of Pt/B-doped carbon catalysts was investigated using the US-DOE catalysts’ supports accelerated stress test (AST) and a mass-spectrometer connected to the fuel cell effluent stream to quantify the mass of corroded carbon support in operando. The addition of boron to the carbon increased the stability of Pt catalysts in long-term usage of PEMFC. After 4000 AST cycles, more than 50% of initial current density was preserved for the boron-containing systems, while less than 30% of it remained with Vulcan carbon (Pt/V). Also, the Pt/B-doped carbon samples demonstrated better electrochemical active surface area (ECSA) stability when compared to Pt/V. Carbon loss measurements showed that B-doped carbons have higher resistance to electrochemical corrosion than unmodified carbon. Specifically, the substitutional boron-doped carbon demonstrated an extremely high stability and low corrosion rate.

25 ENERGY STORAGE↗

Computational and numerical analysis of AC optimal power flow formulations on large-scale power grids

We report that alternating current optimal power flow (AC-OPF) is a fundamental tool in electric utilities to determine optimal operation of the various resources. Typically, the AC-OPF problem uses power balance formulation containing voltages and power equations. Yet, there is no comprehensive comparison of the different AC-OPF formulations, especially for large-scale networks. This paper presents a detailed comparative evaluation of different formulations of the AC-OPF problem on networks ranging from 9-bus to 25,000 buses. Three different formulations: 1) power balance with polar voltages, 2) power balance with Cartesian voltages, and 3) current balance with Cartesian voltages are discussed in detail by comparing their characteristics, and numerical and computational performance.

24 POWER TRANSMISSION AND DISTRIBUTION↗

A high-throughput approach for statistical process optimization in Laser Powder Bed Fusion

Process variability is inherent in metal additive manufacturing (AM). However, it is often overlooked in process optimization frameworks, constraining the understanding of process uncertainties and their influence on parameter selection. To address this, we present an integrated framework that combines high-throughput single-track experiments, GAN-based melt pool geometry extraction, robust statistical and machine learning modeling, and uncertainty-quantified process mapping. Process variability is characterized through single-track melt pool behaviors, and its influence on defect formation is systematically quantified to enable statistically guided process parameter optimization. This approach is demonstrated on Laser Powder Bed Fusion (L-PBF) of stainless steel 316L, effectively capturing the interplay between process parameters, melt pool variability, and defect probability. By integrating uncertainty quantification into process optimization, this study provides a structured methodology for addressing variability challenges in AM quality control, ultimately contributing to enhanced manufacturing reliability.

Laser Powder Bed Fusion↗

Electrocatalysis of Oxygen Reduction Reaction in a Polymer Electrolyte Fuel Cell with a Covalent Framework of Iron Phthalocyanine Aerogel

Carbon aerogels have been studied in the context of fuel cell electrodes mainly as catalyst support materials due to their high surface area, porosity, and electrical conductivity. Recently, aerogels composed solely of inorganic molecular complexes have shown to be promising materials for the electrocatalysis of oxygen reduction reaction (ORR). These aerogels consist of atomically dispersed catalytic sites. Herein, we report on the synthesis and characterization of an aerogel-based catalyst: iron phthalocyanine aerogel. It was synthesized by coupling of ethynyl-terminated phthalocyanine monomers and then heat-treated at 800 °C to increase its electrical conductivity and catalytic activity. Further, the aerogels reported here were tested as catalysts for ORR in acidic conditions for the first time and found to have a ultra-high number of atomically dispersed catalytic sites (7.11 × 10 20 sites g –1 ) and very good catalytic activity (E onset = 0.9 V vs RHE and TOF = 9.2 × 10 –3 e – s –1 site –1 at 0.8 V vs RHE). The iron phthalocyanine aerogel was also studied in a proton exchange membrane fuel cell, reaching a peak power density of 292 mW cm –2 and an open circuit voltage of 0.83 V.

25 ENERGY STORAGE↗

Modular Iron–Bipyridine-Based Conjugated Aerogels as Catalysts for Oxygen Reduction Reaction

Aerogels have a large surface area and a porous structure, which make them an attractive catalyst support materials for fuel cells. Modifying the aerogels’ building blocks and introducing catalytic sites into their backbones allow them to function as both catalysts and supports, thereby increasing the density and distribution of catalyst active sites. In this work, we studied conjugated aerogels containing iron–bipyridine catalytic sites for the oxygen reduction reaction. To demonstrate the variation in physical and electrochemical properties of these aerogels, a series of aerogels were synthesized by a Glaser coupling reaction. Iron salt was added to the three-dimensional gel to produce iron–bipyridine complexes and obtain atomically dispersed catalytic sites. The electrocatalytic activity and electrical conductivity of the aerogels were increased after their heat treatment to yield Fe-doped carbon aerogels. The control of metal loadings was accomplished by changing the bipyridine content during the aerogel synthesis, resulting in 0.9–4.1 wt % Fe. In conclusion, the results show a correlation between Fe loading, aerogel structure, and catalytic activity, achieving high performance for the oxygen reduction reaction in both acidic and alkaline media.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

IMITATION SWITCH is required for normal chromatin structure and gene repression in PRC2 target domains

Significance Polycomb Repressive Complex 2 (PRC2) methylates histones to regulate multicellular development, maintenance of stem cell identity, X-chromosome inactivation, and other important processes. Given these essential roles, there is significant interest in identifying components that function with PRC2 to establish and maintain transcriptionally repressive heterochromatin. Here we document an unexpected new role for a well-studied and conserved chromatin remodeling factor, ISWI. We found that the Neurospora ISWI homolog is required for normal facultative heterochromatin structure and gene repression at PRC2 target regions, and we defined requirements for ATP-dependent catalytic activity and accessory regulatory proteins. These findings provide mechanistic insights into the formation and function of facultative heterochromatin in a model eukaryote.

Kamei, Masayuki↗

Evaluation of AC optimal power flow on graphical processing units

This paper investigates the performance of alternating current optimal power flow (ACOPF) on hardware accelerators such as graphical processing units (GPUs). We describe the strategies employed and the software used to port the ACOPF application to GPU. Through reorganizing the flow of fundamental calculations, restructuring data organization for the GPUs, and using portability libraries, maximum utilization of GPU is attempted. We present details of our efforts with representative results on 200, 500, and 2000-bus networks.

Abhyankar, Shrirang G.↗

Experiences Readying Applications for Exascale

The advent of Exascale computing invites an assessment of existing best practices for developing application readiness on the world's largest supercomputers. This work details observations from the last four years in preparing scientific applications to run on the Oak Ridge Leadership Computing Facility's (OLCF) Frontier system. This paper addresses a range of topics in software including programmability, tuning, and portability considerations that are key to moving applications from existing systems to future installations. A set of representative workloads provides case studies for general system and software testing. We evaluate the use of early access systems for development across several generations of hardware. Finally, we discuss how best practices were identified and disseminated to the community through a wide range of activities including user-guides and trainings. We conclude with recommendations for ensuring application readiness on future leadership computing systems.

exascale↗

HyKKT

HyKKT (pronounced as "hiked") is a package for solving systems of linear equations of Karush-Kuhn-Tucker (KKT) form, which typically arise in optimization problems, such as optimal power flow analysis. HyKKT uses Cholesky instead of LDL^T factorization and solves the general KKT system to a desired numerical precision via block reduction and conjugate gradient on the Schur complement. Such implementation is more suitable for implementation on graphic processing units (GPUs).

Regev, Shaked↗

ReSolve

Library of GPU-resident linear solvers

Swirydowicz, Kasia↗

GridKit

Modeling framework for power systems simulations and analysis.

Peles, Slaven (0000000171103021)↗

Ipopt Interface to Re::Solve Linear Solver

The software provides Ipopt optimization package an interface to the Re::Solve linear solver library. Re::Solve features GPU-resident direct and iterative linear solvers that could be used to accelerate optimization computations.

Alam, Maksudul [Oak Ridge National Laboratory (ORN↗

ExaGO v2

ExaGO is a high-performance computing power systems modeling suite providing models for different power flow analyses. It supports forward AC power flow, multiperiod AC and DC optimal power flow analyses, contingency analysis, as well as stochastic optimal power flow analysis. ExaGO can use HiOp and Ipopt optimization engines. It supports Matpower and PSS/E input file formats. ExaGO v2 includes code from ExaGO 1.6.0.

Peles, Slaven [Oak Ridge National Laboratory (ORNL↗

A Co-Registered In-Situ and Ex-Situ Dataset from a Laser Powder Bed Fusion Additive Manufacturing Process (Peregrine v2023-10)

This release contains a co-registered in-situ and ex-situ Peregrine dataset from a single Concept Laser M2 Laser Powder Bed Fusion (L-PBF) stainless steel 316L build. These data were collected at the Manufacturing Demonstration Facility (MDF) located at Oak Ridge National Laboratory (ORNL). The dataset includes layer-wise visible-light in-situ imaging data, the laser scan paths and parameters, in-situ temporal sensor data, X-Ray Computed Tomography (X-CT) scans, pycnometry and tensile test results, etched micrographs from selected locations, and the target part geometries. Additionally, anomaly detections produced by a modified Dynamic Segmentation Convolutional Neural Network (DSCNN) are provided.

36 MATERIALS SCIENCE↗

Laser-induced fluorescence thermometry of supercritical CO 2 flows inside a micro-channel

This work demonstrates a thermometric technique using laser-induced fluorescence (LIF) in supercritical carbon dioxide flows in a micro-channel. Rhodamine 6G was used as a temperature-sensitive fluorescent dye. The flow conditions were at a pressure of 7.9 MPa and temperature in the range of 23°–90°C. 2D spatial distributions and time-resolved temperature profiles were obtained at this high pressure. Measured LIF signals showed close relations to the temperatures obtained from resistance temperature detectors.

Park, Suhyeon↗

ExaSGD: 2021 Kernel Thrust Activities

The Kernel Thrust milestone ADSE22-214 covers the development of device-capable optimization algorithms and solvers technologies required by the ExaSGD project’s software stack in order to solve security-constrained alternating current optimal power flow (SC-ACOPF) problems on emerging exascale architectures. To this extent, in FY21 the main objective of the Kernel Thrust was (i) provide robust optimization solver(s) that run efficiently on hardware accelerator devices (i.e., NVIDIA and AMD GPUs) to perform intra-node computations and (ii) provide coarse-grain parallel optimization capabilities that exploit the decomposition opportunities present in the SC-ACOPF challenge problems to provide exascale-capable solvers.

97 MATHEMATICS AND COMPUTING↗