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All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Accelerating Hanford Site Cleanup through Operations Research Modeling - 20238

The Hanford Site cleanup effort will require the integration of dozens of unique facilities and processes, many of which will be first-of-a-kind in implementation and design. Each facility will be governed by its own set of operating logic, configured with a unique array of unit operations, and subject to a set of constraints that will affect its behavior. The collection of facilities have multiple points of interface, making the operations of any one facility potentially significant to the operations of other up- or downstream processes. It is therefore highly desirable to accurately predict these operations, as it allows for Site officials to identify and preempt bottlenecks and vulnerabilities before they unexpectedly inhibit the cleanup mission. With the quantity and complexity of the processes that will be on Site, building a pen-and-paper or even a spreadsheet-assisted model of the cleanup mission quickly becomes overwhelming in scope and inaccurate in execution. The Engineering organization for the Site's Tank Operations Contract (TOC) has therefore implemented the use of operations research (OR) modeling to simulate and predict future operations of Site facilities. These models are created using a discrete event simulation tool that allows for the development of detailed, versatile, and robust models. Not only can these models account for complex logical behaviors, but they can also simulate process details down to the level of vessel sizing, labor utilization, equipment reliability, and resource availability. To date, the TOC has developed OR models for several facilities on Site, including for single-shell tank (SST) farms, double-shell tank (DST) farms, the Effluent Treatment Facility (ETF), and the waste transfer system. These models have focused on identifying bottlenecks and operational constraints, and have been used to quantify the effects of implementing process changes. This latter point is particularly valuable, as it allows for several alternatives to be studied in a virtual setting before committing resources to making a change in the field. The decision to develop OR models has gained tremendous support from the Site's stakeholders and the U.S. Department of Energy (DOE) management, and has prompted the use of the tool to support additional internal and external initiatives. Recently, an initiative was proposed to use the models to help identify and provide quantitative backing for risks and opportunities for the TOC. This application of OR could not only help inform how the TOC manages its risks (e.g. quantities and types of spare parts), but could also help drive process improvements whose benefits might otherwise be hard to quantify. The models have also been used to drive the TOC's cloud computing, artificial intelligence (AI), and machine learning (ML) initiatives. These initiatives will not only improve the ability of the TOC to more rapidly respond to the needs of its customers, but it will also aid in the ability of the TOC to analyze and improve the processes it studies. Partnership with two external software development and consulting companies (Lanner and Ynformed) has furthered not only the application of AI and ML within the TOC, but has also spurred the development of new/improved software tools and platforms used by the companies. These partnerships have proven to be mutually beneficial and productive, and have set a precedent for the types of gains that can be made by exploring such options. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
NASA NTRS2000

Effects of Gravity on Insect Circadian Rhythmicity

Circadian rhythms - endogenous daily rhythmic fluctuations in virtually all characteristics of life - are generated and coordinated by the circadian timing system (CTS). The CTS is synchronized to the external 24-hour day by time cues such as the light/dark cycle. In an environment without time cues, the length of an animal's day is determined by the period of its internal pacemaker (tau) and the animal is said to be free-running. All life on earth evolved under the solar day; the CTS exists as an adaptation that allows organisms to anticipate and to prepare for rhythmic environmental fluctuations. All life on earth also evolved under the force of earth's gravitational environment. While it is therefore not surprising that changes in the lighting environment affect the CTS, it is surprising that changes in the gravitational environment would do so. However, recent data from one of our laboratories using the brn-3.1 knockout mouse revealed that this model, which lacks the sensory receptor hair cells within the neurovestibular system, does not respond to exposure to a hyperdynamic environment in the same fashion as normal mice. The brn-3.1 mice did not show the expected suppression of circadian rhythmicity shown by control mice exposed to 2G. Exposure to altered ambient force environments affects the amplitude, mean and timing of circadian rhythms in species from unicellular organisms to man. In addition, there is a circadian influence on the homeostatic response to acute 2G acceleration and pulses of 2G can act as a time cue, synchronizing the CTS. This is of significance because maintenance of internal and external temporal coordination is critical for normal physiological and psychological function. Typically, during adaptation to an increased gravitational environment (+G), an initial acute reaction is followed by adaptation and, eventually, a new steady state (14-16), which can take weeks to months to establish. Until the development of space stations, exposure to microgravity was, of necessity, relatively short in duration. In early spaceflight experiments an organism's internal rhythms often expressed periods that were different from each other, even in the presence of a 24.0 hour light-dark cycle, suggesting that the organism was experiencing internal desynchronization (17, 18). In (micro)G, the body temperature rhythm was delayed with respect to other body rhythms and to the light-dark cycle in rhesus macaques (19) and man (20, 21). In the absence of a light-dark cycle, the circadian rhythm of spore formation persisted in Neurospora crassa, however, both the variability and average period of the rhythm increased (22). The beetle Trigonoscelis gigas, exhibited changes in period during and following 11-13 days in (micro)G (23, 24). Resynchronization of the urinary calcium rhythm following a 1800 phase shift of the LID cycle was retarded in rats exposed to (micro)G compared to 1G controls (25). With the development of the Russian Mir Space Station, long-term controlled microgravity exposure became possible. We recorded activity rhythms from black-bodied Tenebrionid beetles, Trigonoscelis gigas, in (micro)G (spaceflight). Each insect was housed individually within an activity monitor (26) and data (activity counts) were collected and stored in five-minute bins. Thirty-two individual activity monitors were housed within each of 2 experimental kits. The beetles within each kit were divided into two groups and the lighting was controlled separately for each group.

Hoban-Higgins, Tana M.↗
DOE OSTI2020

The Mu2e Experiment (Final Technical Report)

This is the final technical report for the initial two year funding period to start a new collaboration group at the University of California Davis for the Mu2e Experiment at Fermilab. The goal if the Mu2e Experiment is to search for the conversion to an electron of a muon that has been captured by an aluminum nucleus. While this process is effectively forbidden in the Standard Model, it is a virtually universal feature of models beyond the Standard Model. Mu2e will probe the reaction with a sensitivity that is roughly four orders of magnitude better than the best previous measurement. This range of sensitivity probes most of the parameters space of supersymmetry, and any signal will be unambigious proof of physics beyond the Standard Model. Professor Prebys was one of the founding members and first spokespersons of the Mu2e Experiment during his time af Fermilab. He came to UC Davis in 2017 with the goal of starting a Mu2e collaborating group here, and this grant has funded that effort. Specifically, in addition to summer salary, it has supported a graduate student and a postdoc, both of whom are now permanently stationed at Fermilab. During this time, their work has focused primarily on the understanding to the formation of the proton bunches in Fermilab Recycler, as this is critical to the experiment. This has included both measurements and simulations.

43 PARTICLE ACCELERATORS↗
DOE OSTI2025

ML-driven Strong Lens Discoveries: Down to θ E ~ $0^{_{''}}_{^.}03$ and M halo < 10 11 M ⊙

We present results on extending the strong lens discovery space down to much smaller Einstein radii ( θ E ≲ $0^{_{''}}_{^.}03$) and much lower halo mass (M halo < 10 11 M ⊙ ) through the combination of JWST observations and machine learning (ML) techniques. First, we forecast detectable strong lenses with JWST using CosmoDC2 as the lens catalog, and a source catalog down to 29th magnitude. By further incorporating the VELA hydrodynamical simulations of high-redshift galaxies, we simulate strong lenses. We train a ResNet on these images, achieving near-100% completeness and purity for “conventional” strong lenses ( θ E ≳ $0^{_{''}}_{^.}05$), applicable to JWST, the Hubble Space Telescope (HST), the Roman Space Telescope, and Euclid VIS. For the first time, we also search for very low halo mass strong lenses (M halo < 10 11 M ⊙ ) in simulations, with θ E << $0^{_{''}}_{^.}05$, down to the best resolution ($0^{_{''}}_{^.}03$) and depth (10,000 s) limits of JWST using ResNet. A U-Net model is employed to pinpoint these small lenses in images, which are otherwise virtually impossible for human detection. Our results indicate that JWST can find ∼17/deg 2 such low-halo-mass lenses, with the locations of ∼1.1/deg 2 of these detectable by the U-Net at ∼100% precision (and ∼7.0/deg 2 at a 99.0% precision). To validate our model for finding “conventional” strong lenses, we apply it to HST images, discovering two new strong lens candidates previously missed by human classifiers in a crowdsourcing project (E. O. Garvin et al. 2022). This study demonstrates the (potentially “superhuman”) advantages of ML combined with current and future space telescopes for detecting conventional, and especially, low-halo-mass strong lenses, which are critical for testing cold dark matter models.

Silver, Ethan [Harvard University, Cambridge, MA (↗
DOE OSTI2025

Physics-constrained superresolution diffusion for six-dimensional phase space diagnostics

Adaptive physics-constrained superresolution diffusion is developed for noninvasive virtual diagnostics of the six-dimensional (6D) phase space density of charged particle beams. An adaptive variational autoencoder embeds initial beam condition images and scalar measurements to a low-dimensional latent space from which a 32 6 pixel 6D tensor representation of the beam's 6D phase space density is generated. Projecting from a 6D tensor generates physically consistent two-dimensional projections. Physics-guided superresolution diffusion transforms low-resolution images of the 6D density to high resolution 256 × 256 pixel images. Unsupervised adaptive latent space tuning enables tracking of time-varying beams without knowledge of time-varying initial conditions. The method is demonstrated with experimental data and multiparticle simulations at the HiRES UED. The general approach is applicable to a wide range of complex dynamic systems evolving in high-dimensional phase space. The method is shown to be robust to distribution shift without retraining. Published by the American Physical Society 2025

43 PARTICLE ACCELERATORS↗
DOE OSTI2026

Backward-Angle Electroproduction of η′ Mesons off Protons at W = 2.13 GeV and Q 2 = 0.46 (GeV/ c ) 2

The electroproduction of $\eta ^{\prime }$ mesons from a $\mathrm{^{1}H}$ target at $W=\mathrm{2.13~GeV}$, $Q^{2} = 0.46~\left( \mathrm{GeV/}c\right)^{2}$, and $\cos \theta ^{\mathrm{CM}}_{\gamma ^{*}\eta ^{\prime }} \approx -1$ has been experimentally measured. The differential cross section of virtual photoproduction has been obtained as $4.4 \pm 0.8 ~\left( \mathrm{stat.} \right) \pm 0.4 ~\left( \mathrm{sys.} \right)~ \mathrm{nb/sr}$ in the One-Photon-Exchange Approximation. This value is one-sixth of that of real photoproduction at backward angles. A comparison with newly developed isobar model calculations not only shows the validity of the theoretical framewark employed, but also imposes new constraints on coupling strength between the $\eta ^{\prime }p$ final state and nucleon resonances.

Nuclear Physics↗
DOE OSTI2025

Surrogate modeling of Cellular-Potts agent-based models as a segmentation task using the U-Net neural network architecture

The Cellular-Potts model is a powerful and ubiquitous framework for developing computational models for simulating complex multicellular biological systems. Cellular-Potts models (CPMs) are often computationally expensive due to the explicit modeling of interactions among large numbers of individual model agents and diffusive fields described by partial differential equations (PDEs). In this work, we develop a convolutional neural network (CNN) surrogate model using a U-Net architecture that accounts for periodic boundary conditions. We use this model to accelerate the evaluation of a mechanistic CPM previously used to investigate in vitro vasculogenesis. The surrogate model was trained to predict 100 computational steps ahead (Monte-Carlo steps, MCS), accelerating simulation evaluations by a factor of 562 times compared to single-core CPM code execution on CPU. Over short timescales of up to 3 recursive evaluations, or 300 MCS, our model captures the emergent behaviors demonstrated by the original Cellular-Potts model such as vessel sprouting, extension and anastomosis, and contraction of vascular lacunae. This approach demonstrates the potential for deep learning to serve as a step toward efficient surrogate models for CPM simulations, enabling faster evaluation of computationally expensive CPM simulations of biological processes.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Proton stopping measurements at low velocity in warm dense carbon

Abstract Ion stopping in warm dense matter is a process of fundamental importance for the understanding of the properties of dense plasmas, the realization and the interpretation of experiments involving ion-beam-heated warm dense matter samples, and for inertial confinement fusion research. The theoretical description of the ion stopping power in warm dense matter is difficult notably due to electron coupling and degeneracy, and measurements are still largely missing. In particular, the low-velocity stopping range, that features the largest modelling uncertainties, remains virtually unexplored. Here, we report proton energy-loss measurements in warm dense plasma at unprecedented low projectile velocities. Our energy-loss data, combined with a precise target characterization based on plasma-emission measurements using two independent spectroscopy diagnostics, demonstrate a significant deviation of the stopping power from classical models in this regime. In particular, we show that our results are in closest agreement with recent first-principles simulations based on time-dependent density functional theory.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

𝜂 and 𝜂′ Production in 𝐽/𝜓 Radiative Decays from Quantum Chromodynamics

We present a first principles calculation within quantum chromodynamics (QCD) of the radiative decays of the 𝐽/𝜓 into the light pseudoscalar mesons 𝜂 and 𝜂′. Within a lattice computation we obtain the transition form factors as a function of photon virtuality from the timelike region, accessible experimentally via the “Dalitz” decay 𝐽/𝜓 →𝑒 + ⁢𝑒 − ⁢𝜂 (′) , through to the real photon point corresponding to 𝐽/𝜓 →𝛾⁢𝜂 (′) . This is the first calculation in lattice QCD with two (heavier than physical) degenerate flavors of light quark and a heavier strange quark, in which the 𝜂′ appears as the first excited state with pseudoscalar isoscalar quantum numbers. We access it reliably by using variationally optimized operators , the use of which also improves the purity of the 𝐽/𝜓 and 𝜂 signals, reducing systematic uncertainties. High quality results at a large number of kinematic points are obtained in a typically noisy disconnected process by using a novel correlator averaging procedure. Our results show the expected enhanced production of the 𝜂′ over the 𝜂 in this process, and suggest that the demonstrated lattice technology is suitable for future calculations considering processes in which light meson resonances are produced.

form factors↗
DOE OSTI2024

Measurement of the Pion Exclusive Electro-Production Cross-Section in the E12-19-006 Experiment in Hall-C at Jefferson Lab

One of the most effective methods for exploring the transition from hadronic degrees of freedom to quark-gluon degrees of freedom in Quantum Chromodynamics (QCD) is through the investigation of \exclusive" pion and kaon electro-production reactions at various Q2 and ?t values. The E12-19-006 experiment is conducted within the confi?nes of experimental Hall C at the Thomas Jefferson National Accelerator Facility, USA, for such studies. The primary aim of the experiment is to ?first enhance our comprehension of the pion electro-production cross-section and its form factor at Q2 = 0.38 and 0.42 GeV2. This is the fi?rst run period of the E12-19-006 experiment which ran in summer 2019. A more profound understanding of the pion electro-production reaction, 1H(e,e'?+)n, at low Q2 is deemed essential to employ this electro-production reaction (an indirect technique) for the high Q2 studies, thereby delving deeper into the realm of QCD. Consequently, this dissertation presents a thorough analysis of the experimental data acquired in the ?first run period of the E12-19-006 experiment. In pursuit of precision, a series of systematic studies (target boiling correction study, the elastic reaction cross-section measurements, study for determining vari- ous kinematics o?sets, etc.) are conducted to discern the accuracy of the analyzed data, a prerequisite for the use of Rosenbluth separation technique to separate the pion electro-production cross-section terms in t bins. The separated pion electro-production cross-section through the Rosenbluth separation technique is then used to extract the pion electromagnetic form factor. In this dissertation, the pion electro-production cross-section is carefully dissected into its four constituent components: longitudinal (?L), transverse (?T ), longitudinal-transverse (?LT ), and transverse-transverse (?TT ), using the full version of Rosenbluth separation technique for the Q2 = 0.38 GeV2. The technique is simultaneously fi?tted to the unseparated pion electro-production cross-sections at the three values of polarization of the virtual photon (?), i.e., ? = 0.286, 0.629 and 0.781. An iterative process is applied to re?ne the parameters of the model cross-sections until the yield ratio of experimental and Monte Carlo simulation converges. In this study, 21 iterations are conducted to re?ne the model cross-section parameters. The fi?nal pion electro-production cross-section terms are then determined for 7 t bins using the optimized parameters of the model cross-sections.

Kumar, Vijay↗
DOE OSTI2025

Modeling Co2 Flow Through Faulted/Fractured Reservoirs Using Tedfm in Corner-Point Grids

Interest in underground CO2 storage has increased significantly over the last decade, driven by growing concern about global warming and rising levels of greenhouse gases in the atmosphere. Given that CO2 accounts for 80% of these greenhouse gases, carbon capture, utilization, and storage (CCUS) is considered one of the most direct approaches to achieving the net-zero carbon target. Although CO2 storage in deep saline aquifers and depleted gas reservoirs has been studied extensively, most studies use commercial simulators that model faults/fractures by simply modifying the transmissibility in the direction perpendicular to the fault surfaces. This work shows that this simplistic approach ignores the accelerated flow in the directions parallel to the fault plane, leading to significantly higher leakage along the fault surface. To accurately model CO2 flow in faulted reservoirs, we present the first transient embedded discrete-fracture model for corner-point grids (tEDFM-CPG). By comparing the tEDFM-CPG results with high-resolution reference solutions, we show that this approach is accurate and efficient at predicting CO2 flow in faulted/fractured reservoirs. In conclusion, this work presents the use of mixed reality (MR) to efficiently observe CO2 gas migration in the interior of these corner-point grid systems.

02 PETROLEUM↗
DOE OSTI2021

Randomized Algorithms for Scientific Computing (RASC)

Randomized algorithms have propelled advances in artificial intelligence (AI) and represent a foundational research area in advancing AI for Science. Future advancements in DOE Office of Science priority areas such as climate science, astrophysics, fusion, advanced materials, combustion, and quantum computing all require randomized algorithms for surmounting challenges of complexity, robustness, and scalability. Advances in data collection and numerical simulation have changed the dynamics of scientific research and motivate the need for randomized algorithms. For instance, advances in imaging technologies such as X-ray ptychography, electron microscopy, electron energy loss spectroscopy, or adaptive optics lattice light-sheet microscopy collect hyperspectral imaging and scattering data in terabytes, at breakneck speed enabled by state-of-the-art detectors. The data collection is exceptionally fast compared with its analysis. Likewise, advances in high-performance architectures have made exascale computing a reality and changed the economies of scientific computing in the process. Floating-point operations that create data are essentially free in comparison with data movement. Thus far, most approaches have focused on creating faster hardware. Ironically, this faster hardware has exacerbated the problem by making data still easier to create. Under such an onslaught, scientists often resort to heuristic deterministic sampling schemes (e.g., low-precision arithmetic, sampling every nth element) and sacrifice potentially valuable accuracy. Dramatically better results can be achieved via randomized algorithms, reducing the data size as much as or more than naive deterministic subsampling can achieve, while retaining the high accuracy of computing on the full data set. By randomized algorithms we mean those algorithms that employ some form of randomness in internal algorithmic decisions to accelerate time to solution, increase scalability, or improve reliability. Examples include matrix sketching for solving large-scale least-squares problems (see Figure 1) and stochastic gradient descent for training machine learning models. We are not recommending heuristic methods but rather randomized algorithms that have certificates of correctness and probabilistic guarantees of optimality and near-optimality. Such approaches can be useful beyond acceleration, for example, in understanding how to avoid measure zero worst-case scenarios that plague methods such as QR matrix factorization.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1996

Spinoff 1996

By their challenging nature, NASA programs are particularly demanding of technological input. Meeting the aeronautical and space goals of the past four decades has necessitated leading edge advancements across a diverse spectrum that embraces virtually every scientific and technological discipline. Technology is simply knowledge and, like other forms of knowledge, it is often broadly applied and transferable. For that reason, the vast storehouse of technology NASA has built is a national resource, a bank of knowledge available for commercial applications and enhancements to the quality of life-"spinoff"-to new products and processes of benefit to the national economy, industrial efficiency and human welfare. Multiple use of technology has never been more important. Budgetary stringency is reducing the amount of government funding available for new research and development, but at the same time intensifying international competition demands increasing technological innovation to strengthen the U.S. posture in the global marketplace. Reuse of technology offers a relatively inexpensive supplementary means of partnering with industry focused on bringing new products and processes to the market. More than a thousand of spinoff products and processes have emerged from reapplication of technology developed for NASA mission programs. Each has Contributed some measure of benefit to the national economy, productivity or lifestyle; some bring only moderate increments of gain, but many generate benefits of significant order with economic values in the millions of dollars. Other technologies with moderate economic return have added measurably to the quality of life of U.S. citizens. Collectively, they represent a substantial dividend on the national investment in aerospace research. By Congressional mandate, it is NASA's responsibility to promote expansion of spinoff in the public interest. Through its Technology Transfer Program, NASA seeks to encourage greater use of its technological resources by providing a link between the technology and those who might be able to put it to advantageous use. The program's aim is to broaden and accelerate the transfer accomplishments and thereby to gain national benefit in terms of new products, services, and new jobs. This publication is an instrument of-and documents the outcome of-that purpose. It is intended to heighten awareness of the technology available for transfer and its potential for public benefit. Spinoff 1996 is organized in three sections: Section 1, summarizes NASA's current mainline programs, whose objectives require development of new technology and therefore replenish and expand the bank of knowledge available for reapplication. Section 2, the focal point of this volume, contains a representative sampling of spinoff products and processes that resulted from secondary application of NASA technology. Section 3, describes the various mechanisms NASA employs to stimulate technology transfer and lists, in an appendix, contact sources for Further information about the Technology Transfer Program.

Haggerty, James J.↗
NASA NTRS2023

Unusually Long Path Length for a Nearly Scatter-Free Solar Particle Event Observed By Solar Orbiter at 0.43 au

Context. After their acceleration and release at the Sun, solar energetic particles (SEPs) are injected into the interplanetary medium and are bound to the interplanetary magnetic field (IMF) by the Lorentz force. The expansion of the IMF close to the Sun focuses the particle pitch-angle distribution, and scattering counteracts this focusing. Solar Orbiter observed an unusual solar particle event on 9 April 2022 when it was at 0.43 astronomical units (au) from the Sun. Aims. We show that the inferred IMF along which the SEPs traveled was about three times longer than the nominal length of the Parker spiral and provide an explanation for this apparently long path. Methods. We used velocity dispersion analysis (VDA) information to infer the spiral length along which the electrons and ions traveled and infer their solar release times and arrival direction. Results. The path length inferred from VDA is approximately three times longer than the nominal Parker spiral. Nevertheless, the pitch-angle distribution of the particles of this event is highly anisotropic, and the electrons and ions appear to be streaming along the same IMF structures. The angular width of the streaming population is estimated to be approximately 30 degrees. The highly anisotropic ion beam was observed for more than 12 h. This may be due to the low level of fluctuations in the IMF, which in turn is very probably due to this event being inside an interplanetary coronal mass ejection The slow and small rotation in the IMF suggests a flux-rope structure. Small flux dropouts are associated with very small changes in pitch angle, which may be explained by different flux tubes connecting to different locations in the flare region. Conclusions. The unusually long path length along which the electrons and ions have propagated virtually scatter-free together with the short-term flux dropouts offer excellent opportunities to study the transport of SEPs within interplanetary structures. The 9 April 2022 solar particle event offers an especially rich number of unique observations that can be used to limit SEP transport models.

Robert F. Wimmer-Schweingruber↗
DOE OSTI2022

Thermal Process Intensification: Transforming the Way Industry Uses Thermal Process Energy (Workshop Report)

The US Department of Energy’s (DOE’s) Advanced Manufacturing Office held the virtual workshop entitled “Thermal Process Intensification: Transforming the Way Industry Uses Thermal Process Energy” in November and December 2020. The workshop brought together participants from universities/laboratories, industries, equipment manufacturers, technology vendors, nongovernmental organizations, and subject-matter experts to discuss transformative technologies and strategies to substantially improve the performance (e.g., energy productivity, thermal efficiency, reduced greenhouse gas [GHG] emissions, reduced number of process steps) of thermal processing systems in the industrial sector. The US industrial sector accounts for 32% of the nation’s primary energy use (including feedstocks), and refining, chemicals, pulp and paper, iron and steel, and food products represent the top energy-consuming sectors. Thermal processing or process heating represents the largest energy use category; it accounts for 63% of all energy use in manufacturing. Additionally, thermal processing is the largest contributor of carbon dioxide (CO2) generation, resulting from combustion of fuels and process related chemical reactions, such as in the case of cement and lime production. The challenge of achieving net-zero industrial GHG emissions is colossal considering the established industrial base that depends mainly on carbon-based processes and energy sources; the time frame and cost to replace carbon-based energy sources and feedstocks; and the long-term outlook for development with large-scale adaptation of alternative non carbon–based technologies. The goals of the DOE Advanced Manufacturing Office Thermal Process Intensification Workshop were as follows: (1) Identify R&D gaps and opportunities to facilitate transformative improvement in industrial thermal processes beyond current technologies and allow for entirely new methods for processing materials; (2) Gain insight into new and innovative approaches to thermally intensify processes, reduce heat demand, harness waste heat, and use fuels and hydrocarbon feedstocks more efficiently; (3) Identify the R&D pathways to thermal process intensification (TPI) with the highest potential for impact and adoption by the industrial sector; (4) Define areas of research, development, and demonstration (RD&D) activities to accelerate development and application of emerging and transformative technologies to intensify thermal processes in industry. The scope and focus of the workshop were defined to meet these goals. Based on the available data for energy use and GHG emissions, the industries that collectively use more than 80% of the total process heating energy consumption were selected as primary focus areas. The chosen industries were combined into the following four groups based on similarities in their thermal processes: high-temperature metal processing (iron and steel industry, alumina-aluminum industry); high-temperature nonmetal and mineral processing (cement and glass industry); medium- to low-temperature thermal processing (food processing and pulp and paper industry as part of forest products sector); and hydrocarbon processing (petroleum refining and chemical industry). Furthermore, all potential TPI technologies associated with the processes defined were considered as part of the workshop. Different types of TPI technologies possible in industrial in the document.

42 ENGINEERING↗
NASA NTRS2000

Gravitational Effects on Flow Instability and Transition in Low Density Jets

Recent experiments have shown that low-density gas jets injected into a high-density ambient gas undergo an instability mode, leading to highly-periodic oscillations in the flow-field for certain conditions. The transition from laminar to turbulent flow in these jets is abrupt, without the gradual change in scales. Even the fine scale turbulent structure repeats itself with extreme regularity from cycle to cycle. Similar observations were obtained in buoyancy-dominated and momentum-dominated jets characterized by the Richardson numbers, Ri = [gD(rho(sub a)-rho(sub j))/rho(sub j)U(sub j)(exp 2) ] where g is the gravitational acceleration, D is the jet diameter, rho(sub a) and rho(sub a) are, respectively, the free-stream and jet densities, and U(sub j) is the mean jet exit velocity. At high Richardson numbers, the instability is presumably caused by buoyancy since the flow-oscillation frequency (f) or the Strouhal number, St = [fD/U(sub j)] scales with Ri. In momentum-dominated jets, however, the Strouhal number of the oscillating flow is relatively independent of the Ri. In this case, a local absolute instability is predicted in the potential core of low-density jets with S [= rho(sub j)/rho(sub a)] < 0.7, which agrees qualitatively with experiments. Although the instability in gas jets of high Richardson numbers is attributed to buoyancy, direct physical evidence has not been acquired in experiments. If the instability is indeed caused by buoyancy, the near-field flow structure of the jet will change significantly when the buoyancy is removed, for example, in the microgravity environment. Thus, quantitative data on the spatial and temporal evolutions of the instability, length and time scale of the oscillating mode and its effects on the mean flow and breakdown of the potential core are needed in normal and microgravity to delineate gravitational effects in buoyant jets. In momentum dominated low-density jets, the instability is speculated to originate in the potential core. However, experiments have not succeeded in identifying the direct physical cause of the instability. For example, the theory predicts an oscillating mode for S<0.62 in the limit of zero momentum thickness, which contradicts with the experimental findings of Kyle and Sreenivasan. The analyses of momentum-dominated jets neglect buoyancy effects because of the small Richardson number. Although this assumption is appropriate in the potential core, the gravitational effects are important in the annular region surrounding the jet, where the density and velocity gradients are large. This reasoning provides basis for the hypothesis that the instability in low Richardosn number jets studied by Kyle and Sreenivasan and Monkewitz et al. is caused by buoyancy. The striking similarity in characteristics of the instability and virtually the identical conclusions reached by Subbarao and Cantwell in buoyant (Ri>0.5) helium jets on one hand and by Kyle and Sreenivasan in momentum-dominated (Ri<1x10(exp -3)) helium jets on the other support this hypothesis. However, quantitative experiments in normal and microgravity are necessary to obtain direct physical evidence of buoyancy effects on the flow instability and structure of momentum-dominated low-density jets. The primary objective of this new research project is to quantify how buoyancy affects the flow instability and structure in the near field of low-density jets. The flow will be described by the spatial and temporal evolutions of the instability, length and time scales of the oscillating mode, and the mean and fluctuating concentration fields. To meet this objective, concentration measurements will be obtained across the whole field using quantitative Rainbow Schlieren Deflectometry, providing spatial resolution of 0.1mm and temporal resolution of 0.017s to 1ms. The experimental effort will be supplemented with linear stability analysis of low-density jets by considering buoyancy. The first objective of this research is to investigate the effects of gravity on the flow instability and structure of low-density jets. The flow instability in these jets has been attributed to buoyancy. By removing buoyancy in our experiments, we seek to obtain the direct physical evidence of the instability mechanism. In the absence of the instability, the flow structure will undergo a significant change. We seek to quantify these changes by mapping the flow field (in terms of the concentration profiles) of these jets at non-buoyant conditions. Such information is presently lacking in the existing literature. The second objective of this research is to determine if the instability in momentum-driven, low-density jets is caused by buoyancy. At these conditions, the buoyancy effects are commonly ignored because of the small Richardson based on global parameters. By eliminating buoyancy in our experiments, globally as well as locally, we seek to examine the possibility that the instability mechanism in self-excited, buoyant or momentum-driven jets is the same. To meet this objective, we would quantify the jet flow in normal and microgravity, while systematically decreasing the Richardson number from buoyancy-driven to momentum driven flow regime. The third objective of this research is to perform a linear stability analysis of low-density gas jets by including the gravitational effects. The flow oscillations in these jets are attributed to an absolute instability, whereby the disturbance grows exponentially at the site to ultimately contaminate the entire flow field. We seek to study the characteristics of both convective and absolute instabilities and demarcate the boundary between them.

Agrawal A. K.↗
DOE OSTI2025

Generative diffusion model surrogates for mechanistic agent-based biological models

Mechanistic, multicellular, agent-based models are commonly used to investigate tissue, organ, and organism-scale biology at single-cell resolution. The Cellular-Potts Model (CPM) is a powerful and popular framework for developing and interrogating these models. CPMs become computationally expensive at large space- and time- scales making application and investigation of developed models difficult. Surrogate models may allow for the accelerated evaluation of CPMs of complex biological systems. However, the stochastic nature of these models means each set of parameters may give rise to different model configurations, complicating surrogate model development. In this work, we leverage denoising diffusion probabilistic models (DDPMs) to train a generative AI surrogate of a CPM used to investigate in vitro vasculogenesis. We describe the use of an image classifier to learn the characteristics that define unique areas of a 2-dimensional parameter space. We then apply this classifier to aid in surrogate model selection and verification. Our CPM model surrogate generates model configurations 20,000 timesteps ahead of a reference configuration and demonstrates approximately a 22x reduction in computational time as compared to native code execution. Our work represents a step towards the implementation of DDPMs to develop digital twins of stochastic biological systems.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Measurement of the top-quark Yukawa coupling from $t\overline{t}$ production in the lepton+jets final state using pp collisions at $\sqrt{s}=13$ TeV with the ATLAS detector

The top-quark Yukawa coupling is extracted from the distribution of the top-quark pair ($t\overline{t}$) invariant mass in proton-proton collisions using 140 fb −1 of data at $\sqrt{s}=13$ TeV collected in 2015–2018 by the ATLAS experiment at the Large Hadron Collider. In the region near the production threshold, the $t\overline{t}$ invariant mass spectrum is sensitive to electroweak virtual corrections, including contributions from Higgs boson exchange, thereby providing sensitivity to the top-quark Yukawa coupling. This is the first measurement in ATLAS that aims to obtain this coupling exploiting this approach. The $t\overline{t}$ system is reconstructed in the single-lepton final state, requiring exactly one isolated electron or muon and at least four jets with at least two identified as originating from b-quarks. The measured Yukawa coupling is found to be in good agreement with the Standard Model prediction. An upper limit on the top-quark Yukawa coupling strength of Y t < 2.1 relative to the Standard Model prediction is observed at 95% confidence level, consistent with the expected sensitivity.

Hadron-Hadron Scattering↗