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Results for “differentiable programming”

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 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Adsorption of CO on gold: effect of coverage and surface deformations

Recent insights into the nature of catalysts under reactive conditions have motivated investigating heterogeneously catalyzed reactions with non-rigid surfaces. As an example system to revisit, CO interactions with gold have been a longstanding system of interest due to its structure sensitivity. In this work, we investigate coverage-dependent CO adsorption trends on terraces, steps, and kinks. Calculating differential binding energy and mean absolute displacement of the atomic structures as a function of CO coverage, we propose a deformation quenching mechanism that partially determines CO saturation coverage. Extending this analysis to consider CO partial pressure, we show a phase change in CO step occupation, which we highlight as a possible explanation for previously reported temperature-programmed desorption and Fourier-transform infrared reflection-absorption spectroscopy measurements. Furthermore, this work shows how adopting a non-rigid surface model can lead to additional insights which may be applied to other heterogeneously catalyzed systems.

Kavalsky, Lance [University of Wisconsin-Madison, ↗
DOE OSTI2025

Disruption of histone acetylation homeostasis reveals multilayered chromatin regulation for transcriptional resiliency

Background Epigenetic modifications, nucleosome occupancy, and three-dimensional chromatin architecture collectively create a multi-layered, highly interactive regulatory system for controlling genomic functionality. Dysregulation of epigenetic processes leads to a plethora of abnormalities including disease states. Therapies focused on epigenetic modulation can alter gene expression to correct dysfunction, though the perpetuation of these states and the relationships among chromatin regulatory layers is not well understood. Results Here, we investigated global and local chromatin structural and functional responses after acute histone deacetylase inhibitor treatment (suberoylanilide hydroxamic acid) in lung cancer cells across time. Treatment substantially increased global histone acetylation resulting in a pervasive but not distinctive signature. The spread of acetylation did not significantly impact global chromatin accessibility, and nucleosome remodeling largely occurred at finer scales in functionally relevant genomic regions. Indeed, both H 3 K 4 trimethylation, a mark of active transcription, and gene expression changes were altered in a controlled locus-specific manner, suggesting aberrant acetylation indirectly leads to balanced and bidirectional gene expression profiles from tighter regulation of other chromatin features. HDACi treatment induced (13%) genomic rearrangement in chromatin compartmentalization and moderate weakening of topologically associating domains. Conclusions Continuous wavelet analysis of these features demonstrates that scale-dependent, locus-specific factors influence the relationship between chromatin architecture and functional output, suggesting that regulation of transcription and nucleosome remodeling is not entirely (nor linearly) dependent upon large scale compartment exchange. Structural and functional responses are most pronounced early after treatment with partial persistence of differential local chromatin features and expression later in time; this highlights the plasticity of chromatin regulation, which may have implications for the efficacy of epigenetic treatments. These results demonstrate the effectiveness of multi-layered regulation of transcription: in resilient systems, disruption of one chromatin feature does not distort the regulation of other features in supporting a transcriptional program that allows for survival.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Spin Diagnostics Using Mott Polarimeter for the EIC Pre-Injector

Polarization measurement and front-end commissioning are critical steps in the EIC preinjector program. We designed a spin-diagnostics beamline at around 4 MeV for front-end commissioning. This paper describes a high-energy Mott polarimeter, including Mott scattering, the Sherman function, and extrapolation toward single elastic scattering in finite-thickness foils. We summarize the key equations used to calculate essential design parameters, including detection time, effective Sherman function, differential cross section, and Mott polarimeter figure of merit. We also present the diagnostics beamline lattice design and kicker design for continuous spin-polarization monitoring. These notes provide concepts, formulas, and methods for diagnostic-beamline design and commissioning measurements.

43 PARTICLE ACCELERATORS↗
DOE OSTI2025

Separate, separated, and together: the transcriptional program of the Clostridium acetobutylicum-Clostridium ljungdahlii syntrophy leading to interspecies cell fusion

ABSTRACT Syntrophic cocultures (hitherto assumed to be commensalistic) of Clostridium acetobutylicum and Clostridium ljungdahlii , whereby CO 2 and H 2 produced by the former feed the latter, result in interspecies cell fusion involving large-scale exchange of protein, RNA, and DNA between the two organisms. Although mammalian cell fusion is mechanistically dissected, the mechanism for such microbial-cell fusions is unknown. To start exploring this mechanism, we used RNA sequencing to identify genes differentially expressed in this coculture using two types of comparisons. One type compared coculture to the two monocultures, capturing the combined impact of interactions through soluble signals in the medium and through direct cell-to-cell interactions. The second type compared membrane-separated versus -unseparated cocultures, isolating the impact of interspecies physical contact. While we could not firmly identify specific genes that might drive cell fusion, consistent with our hypothesized model for this interspecies microbial cell fusion, we observed differential regulation of genes involved in C. ljungdahlii’s autotrophic Wood-Ljungdahl pathway metabolism and genes of the motility machinery. Unexpectedly, we also identified differential regulation of biosynthetic genes of several amino acids, and notably of arginine and histidine. We verified that they are produced by C. acetobutylicum and are metabolized by C. ljungdahlii to its growth advantage. These and other findings, and notably upregulation of C. acetobutylicum ribosomal-protein genes, paint a more complex syntrophic picture and suggest a mutualistic relationship, whereby beyond CO 2 and H 2 , C. acetobutylicum feeds C. ljungdahlii with growth-boosting amino acids, while benefiting from the H 2 utilization by C. ljungdahlii . IMPORTANCE The construction and study of synthetic microbial cocultures is a growing research area due to the untapped potential of defined multi-species industrial bioprocesses and the utility of defined cocultures for generating insight into complex, undefined, natural microbial consortia. Our previous work showed that coculturing C. acetobutylicum and C. ljungdahlii leads to a unique metabolic phenotype (production of isopropanol) and heterologous cell fusion events. Here, we used RNAseq to explore genes involved in and impacted by these fusions. First, we compared gene expression in coculture to each monoculture. Second, we utilized a transwell system to compare gene expression in mixed cocultures to cocultures with both species physically separated by a permeable membrane, isolating the impact of interspecies “touching” on the transcriptome. This study deepens our mechanistic understanding of the C. acetobutylicum-C. ljungdahlii coculture phenotype, laying the groundwork for reverse genetic studies of heterologous cell fusion in Clostridium cocultures.

Willis, Noah B. (ORCID:0009000689365955)↗
DOE OSTI2025

Postirradiation Examination of HFIR-Irradiated Yttrium Hydrides

The US Department of Energy Microreactor Program is developing compact, high-temperature microreactors that require robust neutron moderators. Known for its high hydrogen retention and structural stability, YH x is a leading candidate for this purpose. As part of an ongoing evaluation, Oak Ridge National Laboratory conducted post-irradiation examinations on YH x specimens irradiated in the High Flux Isotope Reactor under the legacy Transformational Challenge Reactor program, focusing on their structural integrity, hydrogen retention, and thermal properties. The post-irradiation examination campaign primarily examined specimens from two irradiation campaigns, covering a range of hydrogen-to-yttrium atomic ratios (H/Y), neutron damage levels (0.1–2 displacements per atom), and targeted irradiation temperature of 600°C. The investigations included electron microscopy, high-energy x-ray diffraction, laser flash analysis, differential scanning calorimetry, and SiC thermometry analysis.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Systems Level Fuel Cycle Modeling in TMAP8 - A Demonstration

The tritium migration analysis program (TMAP) has been used for tritium inventory tracking and analysis for several years, and the Multiphysics Object Oriented Simulation Environment (MOOSE)-based TMAP8 has several improvements over TMAP4 and TMAP7, such as support for multiple dimensions and non-cartesian coordinate systems, as well as interoperability with sub-apps at higher and lower length scales. We demonstrate that TMAP8 has the additional capacity to solve systems-level problems using zero-dimensional ordinary differential equations by reproducing a literature model which describes a systems-level fuel-cycle of tritium inventory in a hypothetical fusion power plant. The capacity to run several coupled multi-scale physics calculations as part of a single package will be necessary for accurate blanket and fuel-cycle design.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Symplectic machine learning model for fast simulation of space-charge effects

Symplectic simulation of space-charge effects is crucial for the design and operation of high-intensity particle accelerators. Traditional methods for simulating these effects are often computationally expensive, resulting in significant overhead. In this work, we introduce a generative model based on a U-Net architecture within a generative adversarial network framework to efficiently simulate space-charge effects. The model is trained to predict the transverse multiparticle space-charge Hamiltonian, which can be physically computed using a gridless spectral method. The one-step symplectic transverse transfer map for the particles is then obtained by differentiating the predicted Hamiltonian. Benchmarking results demonstrate that this generative model achieves an order of magnitude higher computational efficiency compared to the spectral method, providing a highly efficient alternative for simulating space-charge effects with a large number of particles. By maintaining symplecticity, the model effectively preserves the phase-space structure and mitigates nonphysical errors in long-term simulations. This model has been integrated into jutrack, a novel autodifferentiable accelerator modeling code developed in the julia programming language.

Beam code development & simulation techniques↗
DOE OSTI2025

Emerging Per- and Polyfluoroalkyl Substances in Tap Water from the American Healthy Homes Survey II

Humans experience widespread exposure to anthropogenic per- and polyfluoroalkyl substances (PFAS) through various media, which can lead to a wide range of negative health impacts. Tap water is an important source of exposure in communities with any degree of contamination but routine or large-scale PFAS monitoring often depends on targeted analytical methods limited to measuring specific PFAS. We analyzed 680 tap water samples from the American Healthy Homes Survey II for PFAS using non-targeted analysis (NTA) to expand the range of detectable PFAS. Based on detection frequency and relative abundance, about half of the identified PFAS were found only by NTA. We identified (with varying degrees of confidence) 75 distinct PFAS, including 57 exclusively detected by NTA. The identified PFAS are members of seven structural subclasses differentiated by their head groups and degree of fluorination. Clustering analysis categorized the PFAS into four coabundance groups dominated by specific PFAS subclasses. One group uniquely identified by NTA contains zwitterionic PFAS and other PFAS transformation products which are likely associated with aqueous firefighting foam contaminants in a small number of spatially correlated samples. These results help further characterize the scope of exposure to emerging PFAS experienced by the U.S. population via tap water and augment nationwide targeted-PFAS monitoring programs.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗
DOE OSTI2025

IER 516 - Zirconium Test Assembly (ZTA) Preliminary Experimental Design [Slides]

Zirconium present in large quantities in criticality safety applications such as fuel manufacturing and processing facilities, and in commercial thermal nuclear reactors. ICSBEP lacks benchmarks optimized for zirconium sensitivity to validate zirconium evaluations. Evaluators lack isotopic differential nuclear data in regions of high importance to fission systems.

K-PSO 2.0↗
DOE OSTI2026

Reconstruction of Six-Dimensional Phase Space

A phase space is a mathematical representation of all possible physical states of a system. Particle beams at Fermilab exist within a six-dimensional (6D) phase space defined by three positional components, (x, y, z) and three momentum components, (px, py, pz). To reconstruct this space implies taking measurement data from detectors and mapping out particle behavior using computational methods. The beam detectors, however, are only able to detect spatial distribution among the events of the beam, therefore being limited to positional data. Also, due to the vast number of events in a particle beam, it is extremely difficult to analyze and differentiate every single one’s behavior. However, with Machine Learning (ML), which can distinguish between patterns and map out particle behavior more efficiently. We first used the particle beam software, G4beamline, to simulate a 10,000-event muon beam, adjusting parameters such as initial momentum magnitude (p¬0) and virtual detector position. Using ten virtual detectors, we analyzed p0 values such that minimum 9,990 events were analyzed by every detector. We then input the data from these beam simulations to a C++ program, that randomly selects 100 events, and creates a 2D histogram based on spatial distribution, detector position, and event intensity. This process is repeated 100 times to create 100 histograms per p0 value. These images were then input to a modified ResNet18 Convolutional Neural Network (CNN) for training, and to predict p0 from some unseen set of histograms. The model was accurate when trained on momentum increments of 5 MeV/c and provided with denser training samples around highly variable test values. These results displayed machine learning being able to accurately predict p0 from being trained on different particle behaviors.

Shirlee, Jermain [Fermilab]↗
DOE OSTI2024

Report on technical development in ANL for innovative creep testing and measurement

This report summarizes a research effort undertaken by Argonne National Laboratory to accelerate the development of creep data package for ASME code qualification. Progress on the fabrication of a 3-sample load train and the application of a direct current potential drop (DCPD) technique to measure large creep strains are reported. Specifically: (1) The 3-sample load train, with three sets of Linear Variable Differential Transformers (LVDT), has been fabricated and assembled. (2) A DCPD method for creep-strain measurement up to 50% has been demonstrated. The DCPD data matches very well to LVDT results, suggesting its potential application in future creep testing. The technical developments contribute towards shortening the time needed to generate a creep data package for an ASME code case of the laser powder bed fusion 316H stainless steel, an effort under the US Department of Energy’s Advanced Materials and Manufacturing Technologies (AMMT) program.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

GPU-enabled extreme-scale turbulence simulations: Fourier pseudo-spectral algorithms at the exascale using OpenMP offloading

Fourier pseudo-spectral methods for nonlinear partial differential equations are of wide interest in many areas of advanced computational science, including direct numerical simulation of three-dimensional (3-D) turbulence governed by the Navier-Stokes equations in fluid dynamics. This paper presents a new capability for simulating turbulence at a new record resolution up to 35 trillion grid points, on the world's first exascale computer, Frontier, comprising AMD MI250x GPUs with HPE's Slingshot interconnect and operated by the US Department of Energy's Oak Ridge Leadership Computing Facility (OLCF). Key programming strategies designed to take maximum advantage of the machine architecture involve performing almost all computations on the GPU which has the same memory capacity as the CPU, performing all-to-all communication among sets of parallel processes directly on the GPU, and targeting GPUs efficiently using OpenMP offloading for intensive number-crunching including 1-D Fast Fourier Transforms (FFT) performed using AMD ROCm library calls. With 99% of computing power on Frontier being on the GPU, leaving the CPU idle leads to a net performance gain via avoiding the overhead of data movement between host and device except when needed for some I/O purposes. Memory footprint including the size of communication buffers for MPI_ALLTOALL is managed carefully to maximize the largest problem size possible for a given node count. Detailed performance data including separate contributions from different categories of operations to the elapsed wall time per step are reported for five grid resolutions, from 2048 3 on a single node to 32768 3 on 4096 or 8192 nodes out of 9408 on the system. Both 1D and 2D domain decompositions which divide a 3D periodic domain into slabs and pencils respectively are implemented. The present code suite (labeled by the acronym GESTS, GPUs for Extreme Scale Turbulence Simulations) achieves a figure of merit (in grid points per second) exceeding goals set in the Center for Accelerated Application Readiness (CAAR) program for Frontier. The performance attained is highly favorable in both weak scaling and strong scaling, with notable departures only for 2048 3 where communication is entirely intra-node, and for 32768 3 , where a challenge due to small message sizes does arise. Communication performance is addressed further using a lightweight test code that performs all-to-all communication in a manner matching the full turbulence simulation code. Performance at large problem sizes is affected by both small message size due to high node counts as well as dragonfly network topology features on the machine, but is consistent with official expectations of sustained performance on Frontier. Overall, although not perfect, the scalability achieved at the extreme problem size of 32768 3 (and up to 8192 nodes — which corresponds to hardware rated at just under 1 exaflop/sec of theoretical peak computational performance) is arguably better than the scalability observed using prior state-of-the-art algorithms on Frontier's predecessor machine (Summit) at OLCF. New science results for the study of intermittency in turbulence enabled by this code and its extensions are to be reported separately in the near future.

3D fast Fourier transform↗
DOE OSTI2025

A critical analysis of U-Pu-Zr phase transitions using calorimetric, microstructural, and phase equilibria data

Metallic fuels consisting primarily of uranium, plutonium, and zirconium (U-Pu-Zr) are a leading material candidate for fast-spectrum nuclear reactors. Early demonstration programs proved the principle of safe and efficient fast reactor operation, however there is still considerable uncertainty regarding the phase equilibria and microstructural evolution across the ternary composition space. Quantitative phase formation and identification measurements are scarce and often incomplete, with studies reporting either phase transition temperatures or phase identification data, but not both from the same specimens. In this study, we critically compared experimental and calculated phase transition data and correlated with the microstructure and phase characterization data of as-cast and annealed U-Pu-Zr alloys. Differential scanning calorimetry (DSC) was used to measure phase transitions in the subsolidus regions (723−948 K) of three ternary U-Pu-Zr alloys with similar plutonium concentrations but various U/Zr ratios. Due to sluggish kinetics and narrow ranges of phase stability, complex peaks required the use of a Frazier-Suzuki peak fitting algorithm to deconvolute and calculate transition peak temperatures and enthalpies. We also identified trends of phase transition behavior by critically comparing our DSC data with previous phase transition measurements as well as historical and calculated phase equilibrium diagrams. In conclusion, this provides a critical approach for benchmarking and assessing the quality of new U-Pu-Zr phase equilibria data prior to its incorporation into nuclear material databases.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Recognizing Unrecognized Sources of Uncertainty (USU) in Nuclear Data

Historically, time-of-flight (TOF) nuclear cross section measurements on different nuclides are assumed to be uncorrelated if they were recorded in different facilities with identical methods, identical facilities with different methods, and even identical facilities with identical methods. Ideally, measurements of different nuclides would truly be uncorrelated thus providing independent assessments of some cross section. In reality, correlations exist between measurements but are simply assumed to be unimportant. To eliminate these qualitative assumptions, in this paper we make a counter-intuitive suggestion to perform an intentionally correlated measurement of energy-differential fission and capture reactions for nuclides in a single criticality safety benchmark during a single experimental campaign. While this would introduce undesirable correlations, it would fully quantify correlations between datasets, rather than assume that the correlations do not exist.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

The Functor system: a new on-the-fly take on Material Properties based on C++ functions

In the context of solving multiphysics problems, the discretization of the partial differential equations (PDE) at hand often takes the spotlight. However, for most engineering users and even application developers, the discretization of the equations has already been performed. Instead, they are tasked with implementing specific closure relations and material properties. MOOSE has long enabled this using the Materials system. This system relied on the pre-computation of all properties before they are used in the PDE or in postprocessing. In this talk we will introduce the Functor system, which was deployed in MOOSE in 2021, then present a few applications of functors in flow modeling simulations by the NEAMS program. Functors first offer great flexibility in their evaluation. Rather than storing various arrays for material properties, they are evaluated on the fly at the location and state, e.g. current or old value, requested. Unlike regular material properties, several operations such as the time derivative, the divergence and the curl can be requested from a functor. Similar to material properties, functors can be made to depend on arbitrary combinations of variables, functions, postprocessors and other properties. However, unlike material properties, any of these can be substituted for a functor material property. Thanks to this, objects no longer need to be duplicated based on the types of their parameters.

97 - MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Bayesian analysis of (3 +1)⁢D relativistic nuclear dynamics with the RHIC beam energy scan data

This work presents a Bayesian inference study for relativistic heavy-ion collisions in the beam energy scan program at the BNL Relativistic Heavy-Ion Collider. The theoretical model simulates event-by-event (3+1)-dimensional [(3+1)⁢D] collision dynamics using hydrodynamics and hadronic transport theory. We analyze the model's 20-dimensional posterior distributions obtained using three model emulators with different accuracy and demonstrate the essential role of training an accurate model emulator in the Bayesian analysis. Our analysis provides robust constraints on the quark-gluon plasma's transport properties and various aspects of (3+1)⁢D relativistic nuclear dynamics. By running full model simulations with 100 parameter sets sampled from the posterior distribution, we make predictions for p T -differential observables and estimate their systematic theory uncertainty. Here, a sensitivity analysis is performed to elucidate how individual experimental observables respond to different model parameters, providing useful physics insights into the phenomenological model for heavy-ion collisions.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Predictive Modeling and Uncertainty Quantification in Condition Monitoring of Active Components: A Reactor Coolant Pump Use Case

This work develops data-driven models for onset of thermal barrier leakage in reactor coolant pumps. It incorporates uncertainty quantification to enhance the reliability and robustness of pre- dictions. Using synthetic data generated by the Generic Pressurized Water Reactor simulator, realistic degradation scenarios were simulated across lifecycle stages—beginning, middle, and end of life. Key variables, including differential pressure, flow rate, vibration, and temperatures, were analyzed using machine learning framework. The fully connected neural network models demonstrated exceptional performance, achieving R2 scores exceeding 0.99 and root mean square errors as low as around 8.23 × 10-2 gallon per minute (gpm) for the three stages of the lifecy- cle. UQ analysis further validated the model’s robustness, with narrow uncertainty bounds during steady-state operations and appropriately wider bounds during transitional phases, reflecting the physical behavior of the system. This work addresses important gaps in real-time condition moni- toring and regulatory compliance by integrating advanced condition monitoring technologies with UQ into IST programs. The ability to detect thermal barrier leakage early and quantify prediction reliability supports optimizing maintenance strategies while ensuring nuclear power plants’ safe and reliable operation.

99 - GENERAL AND MISCELLANEOUS↗