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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 127 records · Page 7

Experimental investigation of the physical properties of medium and heavy oils, their vaporization and use in explosion engines. Part I

While little has been accomplished in obtaining an abundant supply of light oils from coal and heavy oils, progress has been made on engine design to make use of the heavier oils. Progress has been made in two different directions which are outlined in this paper: the group of engines with medium and high-pressure carburetion in the cylinder; and the group of engines with low-pressure carburetion of the heavy oils before reaching the cylinder.

OILS↗

Experimental investigation of the physical properties of medium and heavy oils, their vaporization and use in explosion engines. Part IV

This report presents a theoretical treatment of the vaporization process of medium and heavy oils. The results of this investigation, which were mostly obtained from the lighter components of the heavy fuels, require a 10- or 16-fold vaporization in comparison with gasoline. We must attain a still finer degree of atomization, in order to include the heavier components.

OILS↗

Measurement of the inclusive isolated-photon production cross section in pp collisions at $\mathbf {\sqrt{\textit{s}}=13}$ TeV

The production cross section of inclusive isolated photons has been measured by the ALICE experiment at the CERN LHC in pp collisions at centre-of-momentum energy of $\mathbf {\sqrt{\textit{s}}=13}$ TeV collected during the LHC Run 2 data-taking period. The measurement is performed by combining the measurements of the electromagnetic calorimeter EMCal and the central tracking detectors ITS and TPC, covering a pseudorapidity range of and a transverse momentum range of |η γ | < 0.67 and a transverse momentum range 7 < p$^{γ}_{T}$ < 200 GeV/c. The result extends to lower p$^{γ}_{T}$ and x$^{γ}_{T}$ = 2p$^{γ}_{T}$/$\sqrt{s}$ ranges, the lowest x$^{γ}_{T}$ of any isolated photon measurements to date, extending significantly those measured by the ATLAS and CMS experiments towards lower p$^{γ}_{T}$ at the same collision energy with a small overlap between the measurements. The measurement is compared with next-to-leading order perturbative QCD calculations and the results from the ATLAS and CMS experiments as well as with measurements at other collision energies. The measurement and theory prediction are in agreement with each other within the experimental and theoretical uncertainties.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Transforming jet flavour tagging at ATLAS

Jet flavour tagging enables the identification of jets originating from heavy-flavour quarks in proton–proton collisions at the Large Hadron Collider, playing a critical role in its physics programmes. This paper presents GN2, a transformer-based flavour tagging algorithm deployed by the ATLAS Collaboration that represents a different methodology compared to previous approaches. Designed to classify jets based on the flavour of their constituent particles, GN2 processes low-level tracking information in an end-to-end architecture and incorporates physics-informed auxiliary training objectives to enhance both interpretability and performance. Its performance is validated in both simulation and collision data. The measured c-jet (light-jet) rejection in data is improved by a factor of 3.5 (1.8) for a 70% b-jet tagging efficiency, compared to the previous algorithm. GN2 provides substantial benefits for physics analyses involving heavy-flavour jets, such as measurements of Higgs boson pair production and the couplings of bottom and charm quarks to the Higgs boson, and demonstrates the impact of advanced machine learning methods in experimental particle physics.

Characterization and analytical techniques↗

Celeritas: Accelerating Geant4 with GPUs

Celeritas [1] is a new Monte Carlo (MC) detector simulation code designed for computationally intensive applications (specifically, High Lumi- nosity Large Hadron Collider (HL-LHC) simulation) on high-performance heterogeneous architectures. In the past two years Celeritas has advanced from prototyping a GPU-based single physics model in infinite medium to implementing a full set of electromagnetic (EM) physics processes in complex geometries. The current release of Celeritas, version 0.3, has incorporated full device-based navigation, an event loop in the presence of magnetic fields, and detector hit scoring. New functionality incorporates a scheduler to offload electromagnetic physics to the GPU within a Geant4-driven simulation, enabling integration of Celeritas into high energy physics (HEP) experimental frameworks such as CMSSW. On the Summit supercomputer, Celeritas performs EM physics between 6 and 32 faster using the machine’s Nvidia GPUs compared to using only CPUs. When running a multithreaded Geant4 ATLAS test beam application with full hadronic physics, using Celeritas to accelerate the EM physics results in an overall simulation speedup of 1.8–2.3× on GPU and 1.2× on CPU.

Johnson, Seth R.↗

Scaling the SciDAC QuantOm Workflow

As part of the Scientific Discovery through Advanced Computing (SciDAC) program, the Quantum Chromodynamics Nuclear Tomography (QuantOM) project aims to analyze data from Deep Inelastic Scattering (DIS) experiments conducted at Jefferson Lab and the upcoming Electron Ion Collider. The DIS data analysis is performed on an event-level by combining the input from theoretical and experimental nuclear physics into a single, composable workflow. The optimization itself (I.e. fitting the experimental data with theoretical predictions) is carried out by a machine / deep learning algorithm. The size of the acquired DIS data as well as the complexity of the workflow itself require that the analysis is performed across multiple GPUs on high performance computing systems, such as Polaris at Argonne National Laboratory. This presentation discusses the novelties and challenges that came along with parallelizing this workflow. Recent results are compared to common distributed training techniques.

Lersch, Daniel↗

Electron heating in superhigh Mach number shocks

Fluid and MHD models, as well as direct extrapolation of the earth's bow shock measurements in the high Mach number (HMN) range to the superhigh Mach number (SHMN) range predict that the downstream electron pressure is only a negligible fraction of the Rankine-Hugoniot downstream pressure. Following Alfven, plasma physics experimental-theoretical data combined with magnetospheric observations were used to probe the physics of the SHMN shocks. It is shown that inclusion of proper plasma physics considerations in the interaction of the reflected and transmitted ions and the electrons at the 'foot' of the shock leads to the surprising result that electron heating can dominate in the SHNM range. A stationary model of the shock structure is derived and shown to be the result of extrapolation of the high Mach number shock physics wiht incorporation of collective interactions at the foot.

Papadopoulos, K.↗

Future Circular Collider Feasibility Study Report

Volume 1 of the FCC Feasibility Report presents an overview of the physics case, experimental programme, and detector concepts for the Future Circular Collider (FCC). This volume outlines how FCC would address some of the most profound open questions in particle physics, from precision studies of the Higgs and EW bosons and of the top quark, to the exploration of physics beyond the Standard Model. The report reviews the experimental opportunities offered by the staged implementation of FCC, beginning with an electron-positron collider (FCC-ee), operating at several centre-of-mass energies, followed by a hadron collider (FCC-hh). Benchmark examples are given of the expected physics performance, in terms of precision and sensitivity to new phenomena, of each collider stage. Detector requirements and conceptual designs for FCC-ee experiments are discussed, as are the specific demands that the physics programme imposes on the accelerator in the domains of the calibration of the collision energy, and the interface region between the accelerator and the detector. The report also highlights advances in detector, software and computing technologies, as well as the theoretical tools/reconstruction techniques that will enable the precision measurements and discovery potential of the FCC experimental programme. The content and structure of this report are guided by the scope and priorities defined in the mandate of the FCC Feasibility Study. It is therefore not intended to serve as an exhaustive review of the full physics potential of FCC. Several topics, already covered in earlier reports such as the FCC CDR, are not reiterated here or are addressed only briefly, in alignment with the study’s focus. This volume reflects the outcome of a global collaborative effort involving hundreds of scientists and institutions, aided by a dedicated community-building coordination, and provides a targeted assessment of the scientific opportunities and experimental foundations of the FCC programme.

Benedikt, M. [European Organization for Nuclear Re↗

A low-latency graph computer to identify metastable particles at the Large Hadron Collider for real-time analysis of potential dark matter signatures

Abstract Image recognition is a pervasive task in many information-processing environments. We present a solution to a difficult pattern recognition problem that lies at the heart of experimental particle physics. Future experiments with very high-intensity beams will produce a spray of thousands of particles in each beam-target or beam-beam collision. Recognizing the trajectories of these particles as they traverse layers of electronic sensors is a massive image recognition task that has never been accomplished in real time. We present a real-time processing solution that is implemented in a commercial field-programmable gate array using high-level synthesis. It is an unsupervised learning algorithm that uses techniques of graph computing. A prime application is the low-latency analysis of dark-matter signatures involving metastable charged particles that manifest as disappearing tracks.

47 OTHER INSTRUMENTATION↗

Smooth trends in fermium charge radii and the impact of shell effects

The quantum-mechanical nuclear-shell structure determines the stability and limits of the existence of the heaviest nuclides with large proton numbers Z ≳ 100. Shell effects also affect the sizes and shapes of atomic nuclei, as shown by laser spectroscopy studies in lighter nuclides. However, experimental information on the charge radii and the nuclear moments of the heavy actinide elements, which link the heaviest naturally abundant nuclides with artificially produced superheavy elements, is sparse. Here we present laser spectroscopy measurements along the fermium (Z = 100) isotopic chain and an extension of data in the nobelium isotopic chain (Z = 102) across a key region. Multiple production schemes and different advanced techniques were applied to determine the isotope shifts in atomic transitions, from which changes in the nuclear mean-square charge radii were extracted. A range of nuclear models based on energy density functionals reproduce well the observed smooth evolution of the nuclear size. Both the remarkable consistency of model prediction and the similarity of predictions for different isotopes suggest a transition to a regime in which shell effects have a diminished effect on the size compared with lighter nuclei.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Experimental evidence for modifying the current physical model for ice accretion on aircraft surfaces

Closeup movies, still photographs, and other experimental data suggest that the current physical model for ice accretion needs significant modification. At aircraft airspeeds there was no flow of liquid over the surface of the ice after a short initial flow, even at barely subfreezing temperatures. Instead, there were very large stationary drops on the ice surface that lose water from their bottoms by freezing and replenish their liquid by catching the microscopic cloud droplets. This observation disagrees with the existing physical model, which assumes there is a thin liquid film continuously flowing over the ice surface. With no such flow, the freezing-fraction concept of the model fails when a mass balance is performed on the surface water. Rime ice does, as the model predicts, form when the air temperature is low enough to cause the cloud droplets to freeze almost immediately on impact. However, the characteristic shapes of horn-glaze ice or rime ice are primarily caused by the ice shape affecting the airflow locally and consequently the droplet catch and the resulting ice shape. Ice roughness greatly increases the heat transfer coefficient, stops the movement of drops along the surface, and may also affect the airflow initially and thereby the droplet catch. At high subreezing temperatures the initial flow and shedding of surface drops have a large effect on the ice shape. At the incipient freezing limit, no ice forms.

Olsen, W.↗

Electromagnetic properties of indium isotopes illuminate the doubly magic character of 100 Sn

Understanding the nuclear properties in the vicinity of 100 Sn, which has been suggested to be the heaviest doubly magic nucleus with proton number Z equal to neutron number N, has been a long-standing challenge for experimental and theoretical nuclear physics. In particular, contradictory experimental evidence exists regarding the role of nuclear collectivity in this region of the nuclear chart. Here, we provide further evidence for the doubly magic character of 100 Sn by measuring the ground-state electromagnetic moments and nuclear charge radii of indium (Z = 49) isotopes as N approaches 50 from above using precision laser spectroscopy. Our results span almost the complete range between the two major closed neutron shells at N = 50 and N = 82 and reveal parabolic trends as a function of the neutron number, with a clear reduction towards these two closed neutron shells. Furthermore, a detailed comparison between our experimental results and numerical results from two complementary nuclear many-body frameworks (density functional theory and ab initio methods) exposes deficiencies in nuclear models and establishes a benchmark for future theoretical developments.

100Sn↗

FM4NPP: A Scaling Foundation Model for Nuclear and Particle Physics

Large language models have revolutionized artificial intelligence by enabling large, generalizable models trained through self-supervision. This paradigm has inspired the development of scientific foundation models (FMs). However, applying this capability to experimental particle physics is challenging due to the sparse, spatially distributed nature of detector data, which differs dramatically from natural language. This work addresses if an FM for particle physics can scale and generalize across diverse tasks. We introduce a new dataset with more than 11 million particle collision events and a suite of downstream tasks and labeled data for evaluation. We propose a novel self-supervised training method for detector data and demonstrate its neural scalability with models that feature up to 188 million parameters. With frozen weights and task-specific adapters, this FM consistently outperforms baseline models across all downstream tasks. The performance also exhibits robust data-efficient adaptation. Further analysis reveals that the representations extracted by the FM are task-agnostic but can be specialized via a single linear mapping for different downstream tasks.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

The Profiled Feldman-Cousins Method for Confidence Interval Construction for the Nova 3-Flavor Oscillation Analysis

The small interaction cross-section of neutrinos makes experimental neutrino physics particularly responsive to technological advancements. A significant development leveraged by the NOvA experiment is large-scale parallel processing, enabling novel computational approaches to longstanding experimental challenges. Central to managing the resulting high-throughput data is NOvA’s implementation of the Freight Train model, designed for efficient data production and handling.This dissertation details the methodology and execution of the NOvA 2024 3-Flavor Oscillation Analysis, supported by a comprehensive dataset spanning ten years. It emphasizes frequentist results refined through the Feldman-Cousins (FC) technique, specifically addressing confidence interval corrections in parameter estimation. The computational intensity associated with Feldman-Cousins arises from extensive Monte Carlo simulations, which were substantially mitigated through parallel computing on the Perlmutter supercomputer at the National Energy Research Scientific Computing Center (NERSC), employing the MPI framework.To further enhance computational efficiency, an Importance Sampling method is introduced and evaluated, demonstrating significant potential to reduce complexity, particularly in exploring extreme parameter space regions. This thesis presents both the successful application of advanced computational resources and the development of sophisticated statistical techniques, aiming to enhance the precision and scope of neutrino oscillation analyses.

Dye ajdye11190@gmail.com, Andrew Joseph [Mississip↗

Measurement of the inclusive isolated-photon production cross section in pp and Pb–Pb collisions at $\mathbf {\sqrt{\textit{s}_{NN }} = 5.02}$ TeV

The ALICE Collaboration at the CERN LHC has measured the inclusive production cross section of isolated photons at midrapidity as a function of the photon transverse momentum (p$^{γ}_{T}$), in Pb–Pb collisions in different centrality intervals, and in pp collisions, at centre-of-momentum energy per nucleon pair of $\sqrt{s_{NN}}$ = 5.02 TeV. The photon transverse momentum range is between 10–14 and 40–140 GeV/c, depending on the collision system and on the Pb–Pb centrality class. The result extends to lower p$^{γ}_{T}$ than previously published results by the ATLAS and CMS experiments at the same collision energy. The covered pseudorapidity range is |η γ | < 0.67. The isolation selection is based on a charged particle isolation momentum threshold p$^{iso, ch}_{T}$ GeV/c within a cone of radii R = 0.2 and 0.4. The nuclear modification factor is calculated and found to be consistent with unity in all centrality classes, and also consistent with the HG-PYTHIA model, which describes the event selection and geometry biases that affect the centrality determination in peripheral Pb–Pb collisions. The measurement is compared to next-to-leading order perturbative QCD calculations and to the measurements of isolated photons and Z 0 bosons from the CMS experiment, which are all found to be in agreement.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

The spherical tokamak advanced reactor (STAR) fusion power plant design

Scientific and technical advancements have been made that improve fusion’s prospects to provide a new energy source, showing enhanced plasma confinement conditions with plasma temperatures reaching or exceeding 100 million degrees. Overshadowing this progress is the challenge involved in developing an economically viable fusion power plant design. Many proposed next-step DEMO and pilot plant designs are extensions of existing physics-focused experimental devices defined to understand and control plasma operations to achieve and sustain a fusion reaction. Transitioning scientific and technical advancements into a functional power plant requires a dedicated focus on architectural designs that integrate diverse technologies, while optimizing physics conditions, with a focus on economic viability. This holistic approach is essential in turning the promise of fusion energy into a reality. The Spherical Tokamak Advanced Reactor (STAR) is a fusion power plant conceptual design with the architectural focus that strives to balance physics, engineering, and cost considerations. In conclusion, it has been set up to introduce relevant physics, engineering and concept features that an intermediate pilot plant might follow, with the goal of meeting system performances and economic requirements that lead to a commercially competitive fusion power plant.

Blanket segmentation↗

First Time-Resolved Leader Spectra Associated With a Downward Terrestrial Gamma-Ray Flash Detected at the Telescope Array Surface Detector

Optical emissions associated with Terrestrial Gamma ray Flashes (TGFs) have recently become important subjects in space-based and ground-based observations as they can help us understand how TGFs are produced during thunderstorms. In this paper, we present the first time-resolved leader spectra of the optical component associated with a downward TGF. The TGF was observed by the Telescope Array Surface Detector (TASD) simultaneously with other lightning detectors, including a Lightning Mapping Array (LMA), an INTerFerometer (INTF), a Fast Antenna (FA), and a spectroscopic system. The spectroscopic system recorded leader spectra at 29,900 frames per second (33.44 μs time resolution), covering a spectral range from 400 to 900 nm, with 2.1 nm per pixel. The recordings of the leader spectra began 11.7 ms before the -18 kA return stroke and at a height of 2.37 km above the ground. These spectra reveal that optical emissions of singly ionized nitrogen and oxygen occur between 167 μs before and 267 μs after the TGF detection, while optical emissions of neutrals (H I, 656 nm; N I, 744 nm, and O I, 777 nm) occur right at the moment of the detection. The time-dependent spectra reveal differences in the optical emissions of lightning leaders with and without downward TGFs.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

AI-supported mini-labs: combining smartphone-based experiments and multimodal AI

Multimedia learning has always been a topic in physics education—whether through specialized digital data acquisition systems, simulations, or animations. Due to increasing digitalization, more and more media from our everyday lives have also found their way into education in recent decades. This contribution introduces a conceptual framework and illustrative examples for AI-supported experimentation in physics education. It does not yet present empirical data but outlines directions for forthcoming classroom studies evaluating learning outcomes and engagement.

generative AI↗