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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 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Non-singlet quark helicity $\mathrm{PDF}$s of the nucleon from pseudo-distributions

The non-singlet helicity quark parton distribution functions (PDFs) of the nucleon are determined from lattice QCD, by jointly leveraging pseudo-distributions and the distillation spatial smearing paradigm. A Lorentz decomposition of appropriately isolated space-like matrix elements reveals pseudo-distributions that contain information on the leading-twist helicity PDFs, as well as an invariant amplitude that induces an additional z 2 contamination of the leading-twist signal. An analysis of the short-distance behavior of the space-like matrix elements using matching coefficients computed to next-to-leading order (NLO) exposes the desired PDF up to this additional z 2 contamination. Due to the non-conservation of the axial current, we elect to isolate the helicity PDFs normalized by the nucleon axial charge at the same scale μ 2 . The leading-twist helicity PDFs as well as several sources of systematic error, including higher-twist effects, discretization errors, and the aforementioned z 2 contaminating amplitude are jointly determined by characterizing the computed pseudo-distribution in a basis of Jacobi polynomials. The Akaike Information Criterion is exploited to effectively average over distinct model parameterizations and cuts on the pseudo-distribution. Encouraging agreement is observed with recent global analyses of each non-singlet quark helicity PDF, notably a rather small non-singlet anti-quark helicity PDF for all quark momentum fractions.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Holographic open quantum systems: toy models and analytic properties of thermal correlators

We present a unified picture of open quantum systems, the theory of a system probing a noisy thermal environment, distilling lessons learnt from previous holographic analyses. Our treatment is applicable both when the system is coupled to short-lived (Markovian), and long-lived (non-Markovian) environmental degrees of freedom. The thermal environment is modeled using an asymptotically AdS black hole, and the systems of interest are simple probe field theories. The effective stochastic dynamics of the system is governed by real-time thermal correlators, which we compute using the gravitational Schwinger-Keldysh (grSK) geometry. We describe the structure of arbitrary tree-level contact and exchange Witten diagrams in the grSK geometry. In particular, we argue, that all such diagrams reduce to integrals supported on a single copy of the exterior of the black hole. The integrand is obtained as a multiple discontinuity of a function comprising ingoing boundary-bulk propagators, monodromy functions which appear as radial Boltzmann weights, and vertex factors. These results allow us to deduce the analytic structure of real-time thermal n-point functions in holographic CFTs. We illustrate the general statements by a two-dimensional toy model, dual to fields in the BTZ background, which we argue captures many of the essential features of generic open holographic QFTs.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Towards unpolarized GPDs from pseudo-distributions

We present an exploration of the unpolarized isovector proton generalized parton distributions (GPDs) H u−d (x, ξ, t) and E u−d (x, ξ, t) in the pseudo-distribution formalism using distillation. Taking advantage of the large kinematic coverage made possible by this approach, we present results on the moments of GPDs up to the order x 3 — including their skewness dependence — at a pion mass m π = 358 MeV and a lattice spacing a = 0.094 fm.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

The holographic entropy cone from marginal independence

The holographic entropy cone characterizes the relations between entanglement entropies for a spatial partitioning of the boundary spacetime of a holographic CFT in any state describing a classical bulk geometry. We argue that the holographic entropy cone, for an arbitrary number of parties, can be reconstructed from more fundamental data determined solely by subadditivity of quantum entropy. We formulate certain conjectures about graph models of holographic entanglement, for which we provide strong evidence, and rigorously prove that they all imply that such a reconstruction is possible. Our conjectures (except only for the weakest) further imply that the necessary data is remarkably simple. In essence, all one needs to know to reconstruct the holographic entropy cone, is a certain subset of the extreme rays of this simpler “subadditivity cone”, namely those which can be realized in holography. This recasting of the bewildering entanglement structure of geometric states into primal building blocks paves the way to distilling the essence of holography for the emergence of a classical bulk spacetime.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Ecological stoichiometry as a foundation for omics-enabled biogeochemical models of soil organic matter decomposition

Coupled biogeochemical cycles drive ecosystem ecology by influencing individual-to-community scale behaviors; yet the development of process-based models that accurately capture these dynamics remains elusive. Soil organic matter (SOM) decomposition in particular is influenced by resource stoichiometry that dictates microbial nutrient acquisition (‘ecological stoichiometry’). Despite its basis in biogeochemical modeling, ecological stoichiometry is only implicitly considered in high-resolution microbial investigations and the metabolic models they inform. State-of-science SOM decomposition models in both fields have advanced largely separately, but they agree on a need to move beyond seminal pool-based models. This presents an opportunity and a challenge to maximize the strengths of various models across different scales and environmental contexts. To address this challenge, we contend that ecological stoichiometry provides a framework for merging biogeochemical and microbiological models, as both explicitly consider substrate chemistries that are the basis of ecological stoichiometry as applied to SOM decomposition. We highlight two gaps that limit our understanding of SOM decomposition: (1) understanding how individual microorganisms alter metabolic strategies in response to substrate stoichiometry and (2) translating this knowledge to the scale of biogeochemical models. We suggest iterative information exchange to refine the objectives of high-resolution investigations and to specify limited dynamics for representation in large-scale models, resulting in a new class of omics-enabled biogeochemical models. Assimilating theoretical and modelling frameworks from different scientific domains is the next frontier in SOM decomposition modelling; advancing technologies in the context of stoichiometric theory provides a consistent framework for interpreting molecular data, and further distilling this information into tractable SOM decomposition models.

Carbon cycling↗
DOE OSTI2023

Automated Extraction of Energy Systems Information from Remotely Sensed Data: A Review and Analysis

We report high quality energy systems information is a crucial input to energy systems research, modeling, and decision-making. Unfortunately, actionable information about energy systems is often of limited availability, incomplete, or only accessible for a substantial fee or through a non-disclosure agreement. Recently, remotely sensed data (e.g., satellite imagery, aerial photography) have emerged as a potentially rich source of energy systems information. However, the use of these data is frequently challenged by its sheer volume and complexity, precluding manual analysis. Recent breakthroughs in machine learning have enabled automated and rapid extraction of useful information from remotely sensed data, facilitating large-scale acquisition of critical energy system variables. Here we present a systematic review of the literature on this emerging topic, providing an in-depth survey and review of papers published within the past two decades. We first taxonomize the existing literature into ten major areas, spanning the energy value chain. Within each research area, we distill and critically discuss major features that are relevant to energy researchers, including, for example, key challenges regarding the accessibility and reliability of the methods. We then synthesize our findings to identify limitations and trends in the literature as a whole, and discuss opportunities for innovation. These include the opportunity to extend the methods beyond electricity to broader energy systems and wider geographic areas; and the ability to expand the use of these methods in research and decision making as satellite data become cheaper and easier to access. We also find that there are persistent challenges: limited standardization and rigor of performance assessments; limited sharing of code, which would improve replicability; and a limited consideration of the ethics and privacy of data.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

System efficiency and power assessment of the all-aqueous copper thermally regenerative ammonia battery

Thermally regenerative ammonia batteries (TRABs) use low-temperature (T < 100 °C) heat to provide stationary energy and power with higher power densities and efficiency relative to other waste heat devices. TRABs are an active area of research in waste heat devices, but currently there is little consensus on what aspect of the system is limiting TRAB performance and what maximum efficiencies are possible. Experiments and numerical models were used here to examine the sensitivity of the battery and distillation column in a TRAB system to key operating variables, thereby establishing practical limits and identifying focus areas for improving performance. Battery power was eight times more sensitive to ohmic losses than kinetic and mass transfer losses, regardless of the operating temperature, and the peak power density was simulated to be 18.8 mW cm –2 at 75 °C. Theoretical energy efficiency limits were defined for a series of ammonia concentrations and operating pressures, ranging from 5 – 12%, which is 2–3 times higher than previous experimental estimations. Atmospheric pressure column operation used a larger amount of waste heat compared to sub-atmospheric pressure. It is estimated that the volume of the battery would take up 9.2m 3 for every 1% of the power output of a natural gas turbine, but with realistic improvements to cell conductivity, the size would reduce to 2.5 m 3 . Finally, the results presented in this work will help streamline future development by focusing on minimizing ohmic losses and provide specific data for full system evaluation of future TRABs.

25 ENERGY STORAGE↗
DOE OSTI2026

Inertia estimation for power grids: A review of methods, challenges, and future prospects

The electric power grid is undergoing a significant transformation, shifting from traditional synchronous generators to inverter-based resources (IBRs) such as solar photovoltaics, wind turbines, and energy storage systems. This evolution leads to a reduction in system inertia, a critical attribute for maintaining frequency stability in response to disturbances. Consequently, the ability to monitor and estimate system inertia has become increasingly essential. This paper provides a comprehensive review of existing inertia estimation methodologies, analyzing them from multiple perspectives, including the types of data utilized, underlying estimation principles, operational modes, and system-wide applicability. A comparative summary table is included to distill commonalities and key characteristics across various studies. In addition, the paper examines practical implementations of inertia estimation across several major power systems worldwide, including the U.S. interconnections, the Nordic power system, and the U.K. grid. Key challenges are identified, particularly in estimating contributions from virtual inertia sources and load-induced inertia in increasingly converter-dominated networks. To address these emerging challenges, the paper proposes an integrated framework for real-time inertia estimation and monitoring. This framework encompasses critical components such as data acquisition, inertia estimation from both synchronous and non-synchronous sources, load-induced effects, optimization techniques, forecasting, and virtual inertia scheduling. Collectively, these elements enable dynamic, system-wide monitoring and adaptive control of grid inertia.

Inertia estimation↗
DOE OSTI2022

Co-processing catalytic fast pyrolysis oil in an FCC reactor

Here, studies of co-processing catalytic fast pyrolysis (CFP) oil with vacuum gas oil (VGO) are conducted in a Davison Circulating Riser (DCR). The CFP oil (CFPO) for this study was produced by upgrading fast-pyrolysis vapors from pine in an ex-situ fixed-bed reactor. CFPOs were co-processed at up to a volume fraction of 0.05 with VGO at 521 degrees C and 257 kPa. The yields of oil, aqueous phase, tail gas, and coke were measured. The amount of coke was determined from the carbon containing components in the regenerator flue gas. A compositional analysis was conducted with gas chromatography and elemental analyzers. The organic liquids were distilled into gasoline, jet-fuel, diesel, and resid fractions. A biocarbon analysis was conducted on the organic phase and its individual boiling-point fractions. The results show a small decrease in liquid yield and a generally increased gas yield when co-processing CFPO with VGO. The experiments showed that 75%-100% of biocarbon is incorporated into liquid fuels relative to fossil carbon, depending on catalyst and CFPO. The measurements indicate that cracked CFPO components are predominantly included in the jet-fuel and diesel fractions. A techno-economic analysis (TEA) estimated the minimum fuel selling price (MSFP) for fuel-range products derived from FCC co-processing of CFPO at 24 to 29 $\$$/GJ ($\$$2.90 to $\$$3.50 per gasoline-gallon equivalent; GGE) at a yield of 4.87-7.14 GJ/t(biomass) or 40-58 GGE/t.

09 BIOMASS FUELS↗
DOE OSTI2025

Highly crystalline, low-ash, graphite from coal using an Fe 2 O 3 -based catalytic process with recovery and reuse of catalyst and process acid

This study presents a sustainable process for producing highly crystalline, low-ash graphite from sub-bituminous coal using an Fe 2 O 3 -based catalytic method. The process integrates coal mineral removal, catalyst regeneration, and reagent recycling into a closed-loop system. Acid-soluble Fe-residue and mineral impurities are eliminated from the solid graphite through HCl treatment, followed by hydrolytic distillation to regenerate Fe 2 O 3 and recover HCl for reuse. Coal-derived silica is removed with a KOH rinse, yielding low-ash graphite suitable for high-performance applications. The closed-loop catalytic graphitization, where the recovered Fe 2 O 3 and HCl are used in subsequent graphitization runs, produces graphite with a degree of graphitization exceeding 95%. The L a and L c crystallite sizes reach 65–78 nm and 44–48 nm, respectively, with BET surface areas of 4–10 m 2 /g and an ash content below 0.1 wt.%. Lithium-ion battery testing reveals that anodes fabricated with this graphite deliver an initial discharge capacity between 384.5 and 421.2 mAh/g, averaging 395.0 ± 19.1 mAh/g, along with initial coulombic efficiencies of 85.0–89.1%. After 100 discharge–charge cycles at 0.25C, reversible capacities remain between 358.8 and 369.7 mAh/g, while coulombic efficiency stays above 99.9%. The findings highlight that coal can serve as a viable precursor for high-quality graphite production under relatively mild conditions, avoiding the need for extreme temperatures or aggressive reagents such as hydrofluoric acid, commonly employed in conventional processes. This work demonstrates both technical feasibility and environmental benefits, emphasizing its potential to support large-scale, sustainable graphite production for applications such as lithium-ion batteries.

Catalytic graphitization↗
DOE OSTI2022

Plastic waste upgrade to olefins via mild slurry microwave pyrolysis over solid acids

Chemical upcycling technologies are emerging as the most viable to combat plastic waste accumulation. Among them, catalytic pyrolysis is very promising as it is feedstock agnostic. However, the high energy demand associated with pyrolysis can lead to significant carbon dioxide production. In this work, we demonstrate that coupling microwave heating with suitable solid acid promoters in a slurry reactor coupled with a distillation unit can overcome the energy-related challenge of conventional pyrolysis, by operating at modest temperatures (350–375 °C), enhancing transport, and furnishing high yields of olefins (~88 %) in seconds, with medium-sized olefins (>75 %) composing a significant fraction. Reduced thermal gradients minimize coke formation, further improving the performance. Techno-economic analysis and life cycle assessment indicate the potential of the technology.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

The effect of pore structure in ethane-selective metal-organic frameworks for ethylene purification

Separation of ethylene from ethane is of great importance in petrochemical industry. Adsorptive separation making use of porous materials such as metal-organic frameworks (MOFs) is an energy efficient technology compared to the conventional cryogenic distillation. However, preferential adsorption of ethylene over ethane represents the major current challenge. Here we demonstrate how pore structure can significantly alter the adsorption selectivity in two isoreticular Zr-MOFs. A simple ligand functionalization in UiO-66 yields smaller/better matching pore for ethane, and weaker interaction with ethylene, greatly enhancing ethane/ethylene selectivity in MOF-801. Ab initio calculations combined with in situ infrared spectroscopic analysis unveil the nature of host-guest interactions and differences in the overall binding energies. Polymer-grade ethylene (99.9%) can be produced directly from ethane/ethylene mixture in a single step. Having well-balanced adsorption capacity and selectivity, low-cost synthesis and easy scalability MOF-801 stands out as a promising ethane-selective adsorbent for one-step ethylene purification under ambient conditions.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Catalytic conversion of post-consumer recycled high-density polyethylene oil over Zn-impregnated ZSM-5 catalysts

The catalytic conversion of post-consumer recycled high-density polyethylene (PCR-HDPE) pyrolysis oil was investigated using modified ZSM-5 zeolites, prepared under different conditions. The PCR-HDPE oil, obtained through pyrolysis at 500 °C followed by distillation at 165 °C, contained a naphtha fraction hydrocarbons suitable for catalytic upgrading. H/ZSM-5 converts PCR-HDPE naphtha fraction oil primarily into BTX, along with light paraffins and olefins. Introducing mesoporosity led to increased propylene yield at the expense of BTX. Zn impregnation onto H/ZSM-5 and H-meso/ZSM-5 enhanced BTX yield by up to 13 %. However, Zn-meso/ZSM-5 exhibited a lower BTX yield than Zn/ZSM-5 with the same Zn loadings, especially after additional steam treatment at 700 °C. Spent catalysts revealed no noticeable increase in metal contaminants such as calcium and aluminum that were present in the PCR-HDPE. Here, the Zn/ZSM-5 catalyst was stable for more than 50 h time on stream and showed promising potential for upgrading PCR-HDPE naphtha fraction oils.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Harnessing dimethyl ether with ultra-low-grade heat for scaling-resistant brine concentration and fractional crystallization

Solvent-driven separations may enable scalable concentration of hypersaline brines, supporting a circular resource economy from the extraction of lithium and rare earth elements from spent battery and magnet leachates. This work analyses a novel solvent-driven water extraction (SDWE) system employing dimethyl ether (DME) and ultra-low-grade heat for brine concentration and fractional crystallization. SDWE exploits DME’s unique properties: (1) a low dielectric constant that promotes water solubility over charged solutes by a factor of 10 3 , and (2) a high volatility that facilitate efficient DME reconcentration with ultra-low-grade heat. The techno-economic viability of SDWE is assessed with a computational framework that encompasses a liquid–liquid separator and a solvent concentrator. We integrate the extended universal quasichemical model with the virial equation of state to predict the compositions of the complex three-phase DME-water mixture at vapor–liquid and liquid–liquid equilibrium. Subsequently, we optimize the thermodynamic and economic performance of SDWE, by controlling the interstage flash pressure, heat source temperature, and the number of concentrating stages. DME-based SDWE concentrates an input saline feed to 5.5 M and regenerates over 99 % of the DME using ultra-low-grade heat below 50 °C, with a DME/water selectivity ratio of 125. Here our calculations reveal that optimal performance is achieved at interstage flash pressures of 0.4 – 0.5 bar for heat source temperatures between 323–373 K, with improved exergetic efficiencies at lower temperatures. At a heat source temperature of 323 K and an interstage pressure of 0.489 bar, DME-driven SDWE achieves an optimal thermodynamic efficiency of 20.5 % and a projected specific cost of US$ 1.93 m -3 . These specific costs suggest that SDWE is competitive with commercialized thermal distillation technologies, while mitigating the traditional risks associated with scaling in heat and mass exchangers with hypersaline brines.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Cooperative Effects Associated with High Electrolyte Concentrations in Driving the Conversion of CO2 to C2H4 on Copper

Compared to a conventional electrolyte concentration of 1 M HCOOK, the use of a highly concentrated 7.1 M HCOOK electrolyte increases the Faradaic efficiency (FE) ratio of C2H4/CO from 2.2 +- 0.3 to 18.3 +- 4.8 at -1.08 V vs. reversible hydrogen electrode (RHE) on a Cu gas-diffusion electrode. Based on electrochemical analysis and ab initio molecular dynamics (AIMD) simulation, the identity and concentration of the cation and anion play more important roles in controlling the CO2R reaction pathway than the bulk CO2 solubility and the bulk pH of electrolytes. In situ attenuated reflectance surface enhanced infrared absorption spectroscopy (ATR-SEIRAS) suggests that, unlike 1 M HCOOK, the *CO-bridge-binding mode on Cu is dominant in 7.1 M HCOOK electrolyte, which potentially results in less CO release and higher yield of C2H4. This study demonstrates that although we can tailor the electrolyte composition to shift product selectivity, the factors that control the product selectivity are numerous and cannot be distilled down into one correlated property-reactivity relationship.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Shifting modes of iron sulfidization at the onset of OAE-2 drive regional shifts in pyrite δ 34 S records

We report total reduced inorganic S isotope ratios (δ 34 S CRS ) shift toward more negative values across much of the southern North Atlantic just before the onset of the Cenomanian-Turonian Ocean Anoxic Event (OAE-2). At the same time, there is no parallel isotopic change in the significantly larger pool of kerogen (organic) S, which indicates that the distribution and S-isotope composition of sulfide in the environment likely did not drive the change in δ 34 S CRS . Here, we investigate possible explanations for the negative shift in δ 34 S CRS values and their divergence from organic S by isolating iron sulfides for morphological identification and grain-specific isotopic analysis using secondary ion mass spectrometry (SIMS). In pre- and syn-OAE-2 sedimentary rocks from Demerara Rise, we find four distinct morphologies of iron sulfides: pyrite framboids (1–20 μm diameter), irregular pyrite aggregates (1–38 μm diameter), large cemented pyrite aggregates (~60 μm diameter), and irregular and cemented aggregates of the pyrite polymorph marcasite (1–45 μm diameter). These different textural groups have distinct S-isotopic compositions that are largely consistent through the onset of OAE-2. As such, the secular change in bulk δ 34 S CRS values likely reflects the changing proportions of these phases stratigraphically across OAE-2. All textural groups feature resolvable intra-grain δ 34 S variability, suggesting that the environments in which they formed were characterized by dynamic sulfide δ 34 S values and/or by partial closed-system distillation. We use grain-specific δ 34 S distributions to rule out shoaling of the chemocline within the sediments as a mechanism for the observed decrease in δ 34 S CRS . Instead, we propose that changes in the reactivity of the iron species delivered to Demerara Rise over the ~200 kyr leading up to the onset of OAE-2 impacted the relative contributions of pyrite with S-isotope signatures reflecting the water column, shallow sediments, and deeper sediments to the bulk sedimentary δ 34 S CRS value. Specifically, the change in iron reactivity at the onset of OAE-2 favored the production of 34 S-depleted large, cemented aggregates and framboids at the expense of more 34 S-enriched irregular aggregates. Our results underscore that bulk δ 34 S CRS measurements integrate multiple reduced phases that form via distinct reaction mechanisms and potentially in different parts of the depositional environment. Grain-specific SIMS analyses dramatically enrich our ability to interpret pyrite isotopic patterns in the geologic record.

58 GEOSCIENCES↗
DOE OSTI2025

Crosslinked polymeric ionic liquid stationary phases incorporating a combination of silver(I) and copper(II) ions for olefin separations by gas chromatography

The development of efficient and selective olefin separation technologies is a critical challenge within the chemical industry given the high energy demands of conventional cryogenic distillation methods. To address this, the study explores the effectiveness of polymeric ionic liquid (PIL) stationary phases in gas chromatography (GC) that incorporate both silver(I) ([Ag + ]) and copper(II) ([Cu 2+ ]) ions for enhanced olefin separation via π-complexation interactions. Further, the effects of both non-crosslinked and crosslinked PIL stationary phases containing varying ratios of [Ag⁺] and [Cu²⁺] ions were systematically investigated to evaluate their impact on the separation of olefins from paraffins and structurally similar olefins. Retention measurements using a broad range of olefinic probes revealed that [Ag⁺] ions provided stronger and more consistent π-complexation in PIL-based stationary phases, while [Cu²⁺] ions preferentially enhance olefin retention in crosslinked systems. Furthermore, thermal stability studies showed that [Ag + ]-containing PIL stationary phases maintain stable olefin separation efficiency over prolonged exposure under elevated temperatures, while crosslinked PIL stationary phases containing [Cu 2+ ] ions exhibited stronger retention due to increased surface adsorption. These findings provide insight into the tunability of metal–olefin interactions using PIL-based stationary phases and suggest design strategies for achieving thermally stable and highly selective chromatographic separations of unsaturated hydrocarbons.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Self-supervised learning of spatiotemporal thermal signatures in additive manufacturing using reduced order physics models and transformers

Microstructure control via additive manufacturing has enormous potential as manufacturers, materials scientists, and designers alike seek to exploit novel fabrication technologies to improve component performance. Recent works have demonstrated the feasibility of producing materials with controlled microstructures across various length scales. However, the experimental approach towards exploring the process-structure space can be laborious and costly. This is particularly true if also considering scan pattern optimization which is well suited for processes such as powder bed fusion electron beam melting. In this work we propose an approach for encoding additive manufacturing layer-wise thermal response signatures using self-supervised representation learning. Thermal simulations from a reduced order model are utilized to estimate the spatiotemporal response during printing. A machine learning framework, using video-transformers, is utilized to efficiently distill spatiotemporal patterns into a compact latent space representation. This latent state representation encodes the relevant physics which is then utilized to establish a data-driven process-structure model for an additively manufactured Ni-based superalloy. In conclusion, the proposed methodology could potentially be used towards in-situ process monitoring, scan pattern experimental design, and component qualification.

97 MATHEMATICS AND COMPUTING↗