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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Diverse data supports the transition of filamentous fungal model organisms into the post-genomics era

As model organisms filamentous fungi have been important since the beginning of modern biological inquiry and have benefitted from open data since the earliest genetic maps were shared. From early origins in simple Mendelian genetics of mating types, parasexual genetics of colony colour, and the foundational demonstration of the segregation of a nutritional requirement, the contribution of research systems utilising filamentous fungi has spanned the biochemical genetics era, through the molecular genetics era, and now are at the very foundation of diverse omics approaches to research and development. Fungal model organisms have come from most major taxonomic groups although Ascomycete filamentous fungi have seen the most major sustained effort. In addition to the published material about filamentous fungi, shared molecular tools have found application in every area of fungal biology. Likewise, shared data has contributed to the success of model systems. Furthermore, the scale of data supporting research with filamentous fungi has grown by 10 to 12 orders of magnitude. From genetic to molecular maps, expression databases, and finally genome resources, the open and collaborative nature of the research communities has assured that the rising tide of data has lifted all of the research systems together.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2015

LABORATORY MEASUREMENTS OF WHITE DWARF PHOTOSPHERIC SPECTRAL LINES: Hβ

We spectroscopically measure multiple hydrogen Balmer line profiles from laboratory plasmas to investigate the theoretical line profiles used in white dwarf (WD) atmosphere models. X-ray radiation produced at the Z Pulsed Power Facility at Sandia National Laboratories initiates plasma formation in a hydrogen-filled gas cell, replicating WD photospheric conditions. Here we present time-resolved measurements of Hβ and fit this line using different theoretical line profiles to diagnose electron density, n{sub e}, and n = 2 level population, n{sub 2}. Aided by synthetic tests, we characterize the validity of our diagnostic method for this experimental platform. During a single experiment, we infer a continuous range of electron densities increasing from n{sub e} ∼ 4 to ∼30 × 10{sup 16} cm{sup −3} throughout a 120-ns evolution of our plasma. Also, we observe n{sub 2} to be initially elevated with respect to local thermodynamic equilibrium (LTE); it then equilibrates within ∼55 ns to become consistent with LTE. This supports our electron-temperature determination of T{sub e} ∼ 1.3 eV (∼15,000 K) after this time. At n{sub e} ≳ 10{sup 17} cm{sup −3}, we find that computer-simulation-based line-profile calculations provide better fits (lower reduced χ{sup 2}) than the line profiles currently used in the WD astronomy community. The inferred conditions, however, are in good quantitative agreement. This work establishes an experimental foundation for the future investigation of relative shapes and strengths between different hydrogen Balmer lines.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

Quantum probabilities from quantum entanglement: experimentally unpacking the Born rule

The Born rule, a foundational axiom used to deduce probabilities of events from wavefunctions, is indispensable in the everyday practice of quantum physics. It is also key in the quest to reconcile the ostensibly inconsistent laws of the quantum and classical realms, as it confers physical significance to reduced density matrices, the essential tools of decoherence theory. Following Bohr's Copenhagen interpretation, textbooks postulate the Born rule outright. But, recent attempts to derive it from other quantum principles have been successful, holding promise for simplifying and clarifying the quantum foundational bedrock. Moreover, a major family of derivations is based on envariance, a recently discovered symmetry of entangled quantum states. Here, we identify and experimentally test three premises central to these envariance-based derivations, thus demonstrating, in the microworld, the symmetries from which the Born rule is derived. Furthermore, we demonstrate envariance in a purely local quantum system, showing its independence from relativistic causality.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

Form factors for dark matter capture by the Sun in effective theories

In the effective theory of isoscalar and isovector dark matter-nucleon interactions mediated by a heavy spin-1 or spin-0 particle, 8 isotope-dependent nuclear response functions can be generated in the dark matter scattering by nuclei. We compute the 8 nuclear response functions for the 16 most abundant elements in the Sun, i.e. H, {sup 3}He, {sup 4}He, {sup 12}C, {sup 14}N, {sup 16}O, {sup 20}Ne, {sup 23}Na, {sup 24}Mg, {sup 27}Al, {sup 28}Si, {sup 32}S, {sup 40}Ar, {sup 40}Ca, {sup 56}Fe, and {sup 59}Ni, through numerical shell model calculations. We use our response functions to compute the rate of dark matter capture by the Sun for all isoscalar and isovector dark matter-nucleon effective interactions, including several operators previously considered for dark matter direct detection only. We study in detail the dependence of the capture rate on specific dark matter-nucleon interaction operators, and on the different elements in the Sun. We find that a so far neglected momentum dependent dark matter coupling to the nuclear vector charge gives a larger contribution to the capture rate than the constant spin-dependent interaction commonly included in dark matter searches at neutrino telescopes. Our investigation lays the foundations for model independent analyses of dark matter induced neutrino signals from the Sun. The nuclear response functions obtained in this study are listed in analytic form in an appendix, ready to be used in other projects.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2015

Dark matter directional detection in non-relativistic effective theories

We extend the formalism of dark matter directional detection to arbitrary one-body dark matter-nucleon interactions. The new theoretical framework generalizes the one currently used, which is based on 2 types of dark matter-nucleon interaction only. It includes 14 dark matter-nucleon interaction operators, 8 isotope-dependent nuclear response functions, and the Radon transform of the first 2 moments of the dark matter velocity distribution. We calculate the recoil energy spectra at dark matter directional detectors made of CF{sub 4}, CS{sub 2} and {sup 3}He for the 14 dark matter-nucleon interactions, using nuclear response functions recently obtained through numerical nuclear structure calculations. We highlight the new features of the proposed theoretical framework, and present our results for a spherical dark matter halo and for a stream of dark matter particles. This study lays the foundations for model independent analyses of dark matter directional detection experiments.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2017

Ideal MHD stability and characteristics of edge localized modes on CFETR

Investigation on the equilibrium operation regime, its ideal magnetohydrodynamics (MHD) stability and edge localized modes (ELM) characteristics is performed for the China Fusion Engineering Test Reactor (CFETR). The CFETR operation regime study starts with a baseline scenario (R = 5.7 m, B T = 5 T) derived from multi-code integrated modeling, with key parameters ${{\beta }_{{\rm N}}},{{\beta }_{{\rm T}}},{{\beta }_{{\rm p}}}$ varied to build a systematic database. These parameters, under profile and pedestal constraints, provide the foundation for the engineering design. The long wavelength low-n global ideal MHD stability of the CFETR baseline scenario, including the wall stabilization effect, is evaluated by GATO. It is found that the low-n core modes are stable with a wall at r/a = 1.2. An investigation of intermediate wavelength ideal MHD modes (peeling ballooning modes) is also carried out by multi-code benchmarking, including GATO, ELITE, BOUT++ and NIMROD. A good agreement is achieved in predicting edge-localized instabilities. Nonlinear behavior of ELMs for the baseline scenario is simulated using BOUT++. A mix of grassy and type I ELMs is identified. When the size and magnetic field of CFETR are increased (R = 6.6 m, B T = 6 T), collisionality correspondingly increases and the instability is expected to shift to grassy ELMs.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Advances in prediction of tokamak experiments with theory-based models

The successful validation of theory-based models of transport, MHD stability, heating and current drive, with tokamak measurements over the last 20 years, has laid the foundation for a new era where these models can be routinely used in a "predict first" approach to design and predict the outcomes of experiments on tokamaks today. The capability to predict the plasma confinement and core profiles with a quantified uncertainty, based on a multi-machine, international, database of experience, will provide confidence that a proposed discharge will remain within the operational limits of the tokamak. Developing this predictive capability for the first generation of burning plasma devices, beginning with ITER, and progressing to tokamak demonstration reactors, is a critical mission of fusion energy research. Major advances have been made implementing this predict first methodology on today's tokamaks. In this work, an overview of several of these recent advances will be presented, providing the integrated modeling foundations of the experimental successes. The first steps to include boundary plasmas, and tokamak control systems, have been made. A commitment to predicting experiments as part of the planning process is needed in order to collect predictive accuracy data and evolve the models and software into a robust whole discharge pulse design simulator.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Is tokenization needed for masked particle modeling?

In this work, we significantly enhance masked particle modeling (MPM), a self-supervised learning scheme for constructing highly expressive representations of unordered sets relevant to developing foundation models for high-energy physics. In MPM, a model is trained to recover the missing elements of a set, a learning objective that requires no labels and can be applied directly to experimental data. We achieve significant performance improvements over previous work on MPM by addressing inefficiencies in the implementation and incorporating a more powerful decoder. We compare several pre-training tasks and introduce new reconstruction methods that utilize conditional generative models without data tokenization or discretization. We show that these new methods outperform the tokenized learning objective from the original MPM on a new test bed for foundation models for jets, which includes using a wide variety of downstream tasks relevant to jet physics, such as classification, secondary vertex finding, and track identification.

conditional generative models↗
DOE OSTI2025

Eight decades of research on the long-term health effects of radiation in atomic bomb survivors and their offspring

Abstract This year marks the 80th anniversary of the atomic bombings of Hiroshima and Nagasaki. Over the past eight decades, large-scale cohort studies of atomic bomb survivors and their offspring conducted by the Radiation Effects Research Foundation and its predecessor, the Atomic Bomb Casualty Commission, have provided critical insights into the long-term health effects of radiation exposure. Key findings include early identification of radiation-associated leukemia, as well as excess risks of all solid cancers combined, and most individual cancer sites. Observed radiation dose–response relationships have generally followed a linear-quadratic model for leukemia and a linear model for all solid cancers. Recent findings indicating possible upward curvature in the dose–response for all solid cancers may reflect underlying heterogeneity in factors related to individual cancer sites and should be explored further. Generally, younger age at exposure, lower attained age, and female sex appear to show greater radiation sensitivity for all solid cancers combined but results differ by individual cancer site. Recent studies have also identified potential radiation-related excesses for non-cancer diseases such as cataracts, various circulatory diseases, and others. Studies of heritable effects on the offspring of exposed atomic bomb survivors, in contrast, have shown no elevated risk to date in offspring from parental radiation exposure, either at the molecular or disease level. With the cooperation of the atomic bomb survivors and their families, Radiation Effects Research Foundation’s research will continue to play a crucial role in informing the health of survivors, their families, and global radiation protection in the decades to come.

Oncology↗
DOE OSTI2023

PYK-SubstitutionOME: an integrated database containing allosteric coupling, ligand affinity and mutational, structural, pathological, bioinformatic and computational information about pyruvate kinase isozymes

Interpreting changes in patient genomes, understanding how viruses evolve and engineering novel protein function all depend on accurately predicting the functional outcomes that arise from amino acid substitutions. To that end, the development of first-generation prediction algorithms was guided by historic experimental datasets. However, these datasets were heavily biased toward substitutions at positions that have not changed much throughout evolution (i.e. conserved). Although newer datasets include substitutions at positions that span a range of evolutionary conservation scores, these data are largely derived from assays that agglomerate multiple aspects of function. To facilitate predictions from the foundational chemical properties of proteins, large substitution databases with biochemical characterizations of function are needed. We report here a database derived from mutational, biochemical, bioinformatic, structural, pathological and computational studies of a highly studied protein family—pyruvate kinase (PYK). A centerpiece of this database is the biochemical characterization—including quantitative evaluation of allosteric regulation—of the changes that accompany substitutions at positions that sample the full conservation range observed in the PYK family. We have used these data to facilitate critical advances in the foundational studies of allosteric regulation and protein evolution and as rigorous benchmarks for testing protein predictions. We trust that the collected dataset will be useful for the broader scientific community in the further development of prediction algorithms.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

UV background fluctuations and three-point correlations in the large-scale clustering of the Lyman α forest

Using the Lyman α (Lyα) Mass Association Scheme, we make theoretical predictions for the three-dimensional three-point correlation function (3PCF) of the Lyα forest at redshift z = 2.3. We bootstrap results from the (100 h -1 Mpc) 3 Horizon hydrodynamic simulation to a (1 h -1 Gpc) 3 N -body simulation, considering both a uniform ultraviolet background (UVB) and a fluctuating UVB sourced by quasars with a comoving n q ≈ 10 -5 h 3 Mpc -3 placed either in massive haloes or randomly. On scales of 10–30 h -1 Mpc, the flux 3PCF displays hierarchical scaling with the square of the two-point correlation function (2PCF), but with an unusual value of Q ≡ ζ 123 /(ξ 12 ξ 13 + ξ 12 ξ 23 + ξ 13 ξ 23 ) ≈ -4.5 that reflects the low bias of the Lyα forest and the anticorrelation between mass density and transmitted flux. For halo-based quasars and an ionizing photon mean free path of λ = 300 h -1 Mpc comoving, UVB fluctuations moderately depress the 2PCF and 3PCF, with cancelling effects on Q . For λ = 100 or 50 h -1 Mpc, UVB fluctuations substantially boost the 2PCF and 3PCF on large scales, shifting the hierarchical ratio to Q ≈ -3. We scale our simulation results to derive rough estimate of the detectability of the 3PCF in current and future observational data sets for the redshift range z = 2.1–2.6. At r = 10 and 20 h -1 Mpc, we predict a signal-to-noise ratio (SNR) of ~9 and ~7, respectively, for both Baryon Oscillation Spectroscopic Survey (BOSS) and extended BOSS (eBOSS), and ~37 and ~25 for Dark Energy Spectroscopic Instrument (DESI). At r = 40 h -1 Mpc the predicted SNR is lower by a factor of ~3–5. Measuring the flux 3PCF would provide a novel test of the conventional paradigm of the Lyα forest and help separate the contributions of UVB fluctuations and density fluctuations to Lyα forest clustering, thereby solidifying its foundation as a tool of precision cosmology.

Astronomy & Astrophysics↗
DOE OSTI2023

Speciation Underpinned by Unexpected Molecular Diversity in the Mycorrhizal Fungal Genus Pisolithus

The mutualistic ectomycorrhizal (ECM) fungal genus Pisolithus comprises 19 species defined to date which colonize the roots of >50 hosts worldwide suggesting that substantial genomic and functional evolution occurred during speciation. To better understand this intra-genus variation, we undertook a comparative multi-omic study of nine Pisolithus species sampled from North America, South America, Asia, and Australasia. We found that there was a small core set of genes common to all species (13%), and that these genes were more likely to be significantly regulated during symbiosis with a host than accessory or species-specific genes. Thus, the genetic “toolbox” foundational to the symbiotic lifestyle in this genus is small. Transposable elements were located significantly closer to gene classes including effector-like small secreted proteins (SSPs). Poorly conserved SSPs were more likely to be induced by symbiosis, suggesting that they may be a class of protein that tune host specificity. The Pisolithus gene repertoire is characterized by divergent CAZyme profiles when compared with other fungi, both symbiotic and saprotrophic. This was driven by differences in enzymes associated with symbiotic sugar processing, although metabolomic analysis suggest that neither copy number nor expression of these genes is sufficient to predict sugar capture from a host plant or its metabolism in fungal hyphae. Our results demonstrate that intra-genus genomic and functional diversity within ECM fungi is greater than previously thought, underlining the importance of continued comparative studies within the fungal tree of life to refine our focus on pathways and evolutionary processes foundational to this symbiotic lifestyle.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2017

Fluctuation localization imaging-based fluorescence in situ hybridization (fliFISH) for accurate detection and counting of RNA copies in single cells

Here, quantitative gene expression analysis in intact single cells can be achieved using single molecule-based fluorescence in situ hybridization (smFISH). This approach relies on fluorescence intensity to distinguish between true signals, emitted from an RNA copy hybridized with multiple oligonucleotide probes, and background noise. Thus, the precision in smFISH is often compromised by partial or nonspecific probe binding and tissue autofluorescence, especially when only a small number of probes can be fitted to the target transcript. Here we provide an accurate approach for setting quantitative thresholds between true and false signals, which relies on on-off duty cycles of photoswitchable dyes. This fluctuation localization imaging-based FISH (fliFISH) uses on-time fractions (measured over a series of exposures) collected from transcripts bound to as low as 8 probes, which are distinct from on-time fractions collected from nonspecifically bound probes or autofluorescence. Using multicolor fliFISH, we identified radial gene expression patterns in mouse pancreatic islets for insulin, the transcription factor, NKX2-2 and their ratio ( Nkx2 - 2/Ins2 ). These radial patterns, showing higher values in β cells at the islet core and lower values in peripheral cells, were lost in diabetic mouse islets. In summary, fliFISH provides an accurate, quantitative approach for detecting and counting true RNA copies and rejecting false signals by their distinct on-time fractions, laying the foundation for reliable single-cell transcriptomics.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

DeepLearnMOR: a deep-learning framework for fluorescence image-based classification of organelle morphology

Abstract The proper biogenesis, morphogenesis, and dynamics of subcellular organelles are essential to their metabolic functions. Conventional techniques for identifying, classifying, and quantifying abnormalities in organelle morphology are largely manual and time-consuming, and require specific expertise. Deep learning has the potential to revolutionize image-based screens by greatly improving their scope, speed, and efficiency. Here, we used transfer learning and a convolutional neural network (CNN) to analyze over 47,000 confocal microscopy images from Arabidopsis wild-type and mutant plants with abnormal division of one of three essential energy organelles: chloroplasts, mitochondria, or peroxisomes. We have built a deep-learning framework, DeepLearnMOR (Deep Learning of the Morphology of Organelles), which can rapidly classify image categories and identify abnormalities in organelle morphology with over 97% accuracy. Feature visualization analysis identified important features used by the CNN to predict morphological abnormalities, and visual clues helped to better understand the decision-making process, thereby validating the reliability and interpretability of the neural network. This framework establishes a foundation for future larger-scale research with broader scopes and greater data set diversity and heterogeneity.

Plant Sciences↗
DOE OSTI2016

Structural Biology of Aromatic Amino Acid Biosynthesis in Plants: The Prephenate Branch Point

Plants are chemists that have spent the last 425 million years evolving unique secondary metabolites to communicate with their surroundings, defend themselves against pathogens, insects, and herbivores, and grow and develop. Many secondary metabolites are biosynthesized from the aromatic amino acids tryptophan, tyrosine, and phenylalanine, and the shikimate and aromatic amino acid biosynthetic pathways link primary and specialized metabolism. Prephenate aminotransferase (PAT) is a key enzyme in aromatic amino acid biosynthesis because its product, arogenate, is the immediate precursor for both tyrosine and phenylalanine. Interestingly, the enzyme has a dual role in metabolism and can also function as a classical aspartate aminotransferase. AtPAT is pyridoxal 5′‐phosphate‐dependent (PLP) enzyme belonging to the AAT‐like aspartate aminotransferase domain and follows a ping‐pong bi‐bi reaction mechanism through Schiff‐base formation to a catalytic K306 in the active site. Each subunit of the AtPAT dimer consists of a large domain and a small domain that belong to the α‐β class of protein fold. Despite the structural similarities to aspartate aminotransferases, the molecular basis of prephenate binding specificity remains elusive. To gain an understanding of the enzyme's chemistry and substrate selectivity, a 2.5 Å x‐ray structure of PAT from the model plant Arabidopsis thaliana (thale cress) was solved in complex with the PLP. To our knowledge, this is the first structure of a bona fide prephenate aminotransferase. Amino acid sequence comparisons of all known functional PATs shows that T84 and K169 are highly conserved; however, some enzymes annotated as PAT display sequence variations at these positions. Biochemical analysis of T84V, K169V, and T84V/K169V PAT reveals that the double mutant gained tyrosine aminotransferase activity and was able to convert 4‐hydroxyphenylpyruvate to tyrosine. T84 is on the opposite side of the active site pocket, while the amine backbone of K169 hydrogen bonds to PLP. We hypothesize that Thr84 and Lys169 are important for substrate recognition in the active site and will use these mutants in future crystallographic experiments. Overall, our structural studies will assist in understanding the role of this bi‐functional enzyme in the context of aromatic amino acid biosynthesis in plants. Support or Funding Information This material is based upon work supported by the National Science Foundation Graduate Research Fellowship under Grant No. DGE‐1143954. Any opinion, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation. Results shown in this report are derived from work performed at Argonne National Laboratory, Structural Biology Center at the Advanced Photon Source. Argonne is operated by UChicago Argonne, LLC, for the U.S. Department of Energy, Office of Biological and Environmental Research under contract DE‐AC02‐06CH11357.

Holland, Cynthia K.↗
DOE OSTI2025

Time-domain theory of transient heat conduction in the local limit

Ultrafast and nanoscale heat conduction demands a unified theoretical framework that rigorously bridges macroscopic transport equations with microscopic material properties derived from statistical physics. Existing empirical generalizations of Fourier's law often lack a solid microscopic foundation, failing to connect observed non-Fourier behavior with underlying atomic-scale mechanisms. In this work, we present a time-domain theory of transient heat conduction rooted in Zwanzig's statistical theory of irreversible processes. Central to this framework is the time-domain transport function $\overleftrightarrow{𝑍}$⁡(𝑡) defined through equilibrium time-correlation functions of heat fluxes. This function generalizes the conventional concept of steady-state thermal conductivity, governing the transition of conduction dynamics from onset second sound type wave propagation at finite speeds to diffusion-dominated behavior across broad temporal and spatial scales. Unlike phonon hydrodynamic models that rely on mesoscopic constructs such as phonon drift velocity, our approach provides a quantitative and microscopic description of intrinsic memory effects in transient heat fluxes and applies universally to bulk materials at any temperature or length scale. By integrating atomistic-scale first-principles calculations with continuum-level macroscopic equations, this framework offers a robust foundation for numerical simulations of transient temperature fields. Furthermore, it facilitates the interpretation and design of transient thermal grating experiments using nanometer-scale heat sources and ultrafast laser systems in the extreme ultraviolet and x-ray wavelength ranges, advancing our understanding of heat dissipation dynamics.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

Windowed multipole representation of R -matrix cross sections

Nuclear cross sections are basic inputs to any nuclear computation. Campaigns of experiments are fitted with the parametric R-matrix model of quantum nuclear interactions, and the resulting cross sections are documented—both pointwise and as resonance parameters (with uncertainties)—in standard evaluated nuclear data libraries (ENDF, JEFF, BROND, JENDL, CENDL, TENDL): these constitute our common knowledge of fundamental low-energy nuclear cross sections. In the past decade, a collaborative effort has been deployed to establish a new nuclear cross-section library format—the Windowed Multipole Library—with the goal of considerably reducing the computational cost of cross-section calculations in nuclear transport simulations. This work lays the theoretical foundations underpinning these efforts. From general R-matrix scattering theory, we derive the windowed multipole representation of nuclear cross sections. Though physically and mathematically equivalent to R-matrix cross sections, the windowed multipole representation is particularly well suited for subsequent temperature treatment of angle-integrated cross sections, in particular Doppler broadening, which is the averaging of cross sections over the thermal motion of the target atoms. Doppler broadening is of critical importance in neutron transport applications, as it ensures the stability of many nuclear reactors (negative thermal reactivity). Yet, Doppler broadening of nuclear cross sections has been a considerable bottleneck for nuclear transport computations, often requiring memory-costly pretabulations. We show that the windowed multipole representation can perform accurate Doppler broadening analytically (up to the first reaction threshold), from which we derive cross-section temperature derivatives to any order—all computable on the fly (without precalculations stored in memory). Furthermore, we here establish a way of converting the R-matrix resonance parameters uncertainty (covariance matrices) into windowed multipole parameters uncertainty. We show that generating stochastic nuclear cross sections by sampling from the resulting windowed multipole covariance matrix can reproduce the cross-section uncertainty in the original nuclear data file. The windowed multipole representation is therefore a novel nuclear physics formalism able to generate Doppler broadened stochastic nuclear cross sections on the fly, unlocking breakthrough computational gains for nuclear computations. Through this foundational paper, we hope to make the windowed multipole representation accessible, reproducible, and usable for the nuclear physics community, as well as provide the theoretical basis for future research on expanding its capabilities.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

A functional modeling approach for quality assurance in metal additive manufacturing

Purpose: Due to the complexity of and variations in additive manufacturing (AM) processes, there is a level of uncertainty that creates critical issues in quality assurance (QA), which must be addressed by time-consuming and cost-intensive tasks. This deteriorates the process repeatability, reliability and part reproducibility. So far, many AM efforts have been performed in an isolated and scattered way over several decades. Here, a systematically integrated holistic view is proposed to achieve QA for AM. Design/methodology/approach: A systematically integrated view is presented to ensure the predefined part properties before/during/after the AM process. It consists of four stages, namely, QA plan, prospective validation, concurrent validation and retrospective validation. As a foundation for QA planning, a functional workflow and the required information flows are proposed by using functional design models: Icam DEFinition for Function Modeling. Findings: The functional design model of the QA plan provides the systematically integrated view that can be the basis for inspection of AM processes for the repeatability and qualification of AM parts for reproducibility. Research limitations/implications: A powder bed fusion process was used to validate the feasibility of this QA plan. Feasibility was demonstrated under many assumptions; real validation is not included in this study. Social implications: This study provides an innovative and transformative methodology that can lead to greater productivity and improved quality of AM parts across industries. Furthermore, the QA guidelines and functional design models provide the foundation for the development of a QA architecture and management system. Originality/value: This systematically integrated view and the corresponding QA plan can pose fundamental questions to the AM community and initiate new research efforts in the in-situ digital inspection of AM processes and parts.

36 MATERIALS SCIENCE↗