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At least 1,621 records · Page 90
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

SCALE 6.2.4 Validation: Reactor Physics

This report is the third volume in a report series documenting the validation of SCALE 6.2.4, which is used herein with ENDF/B-VII.1 libraries, for nuclear criticality safety, reactor physics, and radiation shielding applications. This report focuses on validating SCALE capabilities that affect reactor physics applications. The experimental data used as basis for validation consists of measurement data for nuclide inventory, decay heat, and full-core experiments and include the following: 1. radiochemical assay measurements of 40 nuclides of importance to burnup credit, decay heat, and radiation shielding in 169 light-water reactor (LWR) spent nuclear fuel samples that cover burnups up to 70 GWd/MTU and initial enrichments up to 4.9% 235 U; 2. full-assembly decay heat measurements for 236 LWR assemblies with: a. initial fuel enrichments up to 4% 235 U, b. assembly burnups of 5–51 GWd/MTU, and c. cooling times after discharge in the 2- to 27-year range (of importance to spent nuclear fuel storage, transportation, and disposal); and 3. pulse fission irradiations for fissionable materials at cooling times of interest to severe accident analyses (<10 5 s). Validation examples for full-core analysis are based on startup experiments for the Watts Bar Nuclear Unit 1 (WBN1) pressurized water reactor (PWR) and two high-temperature gas-cooled reactor (HTGR) benchmarks for the HTR-10 pebble bed and the prismatic HTTR reactor.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Physics-informed Estimation of the Covariance Matrix for Various Neutron Spectra

A method for estimating covariance matrices which capture the uncertainties in calculated reactor spectra has been developed. This method is based on perturbing the parameters of a physics-based analytic model fitted to a calculated spectrum. The covariance of the perturbed analytic spectra imposes energy-dependent correlations due to the physics of the neutron processes in the reactor, i.e., a fission component, a 1/E down-scatting component, and a thermal Maxwellian component. An analytic model is developed which is shown to produce good fits to several reactor environments. The covariance matrices produced via this method are then used as the prior spectrum in STAYSL least squares spectrum adjustment where it is combined with integral metrics, such as activation measurements, to produce a high-fidelity neutron spectrum characterization. It was concluded that the methodology showed agreeable results for the ACRR free-field spectrum adjustment in STAYSL resulting in a 𝜒 2 value of 2.21 (per degree of freedom), but further work is needed to describe scattering and interface regions.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2026

High Energy Neutrino Physics

Of the twelve subatomic particles that are the building blocks of all the known matter in the universe, three are neutrinos, small neutral particles that interact through the weak interaction with other particles in the Universe. These three neutrinos, paired with the three charged leptons, the familiar electron, the heavier muon, and the still heavier tau, are some of the least well understood particles of these building blocks. Experiments using accelerator beams, like those that are the subject of this grant, can address some of the key questions scientists are posing with respect to the neutrino. Specifically, are there differences between neutrinos and their anti-particles, anti-neutrinos, that could give us some clue to the matter dominated universe, do we understand the spectrum of masses of the three neutrinos, and are there other kinds of neutirnos than the three neutrinos? Coupled with advances in precision neutrino detection, the US is addressing these questions from small scale experiments to the massive DUNE experiment. PI Fleming and her team play critical roles in accelerator based neutrino physics at short and long baseline with participation on MicroBooNE, SBND, and with the group's participation in DUNE. These experiments are at the heart of the US-based high energy physics program.

43 PARTICLE ACCELERATORS↗
DOE OSTI2022

Improving Variational Autoencoders for New Physics Detection at the LHC With Normalizing Flows

We investigate how to improve new physics detection strategies exploiting variational autoencoders and normalizing flows for anomaly detection at the Large Hadron Collider. As a working example, we consider the DarkMachines challenge dataset. We show how different design choices (e.g., event representations, anomaly score definitions, network architectures) affect the result on specific benchmark new physics models. Once a baseline is established, we discuss how to improve the anomaly detection accuracy by exploiting normalizing flow layers in the latent space of the variational autoencoder.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2019

The Orson Anderson Era of Mineral Physics at Lamont in the 1960s

From 1964 to the early 1970s, Orson Anderson led a research program at the Lamont Geological Observatory in the newly-emerging field of “mineral physics”. In collaboration with colleagues Edward Schreiber and Naohiro Soga, Orson exploited the techniques of physical acoustics to study the behavior of the sound velocities of minerals at elevated pressures and temperatures. This research program also included semi-empirical studies of the relationships between the bulk modulus and the molar volume of solids, the use of lattice dynamics to calculate the elastic moduli of cubic structures as a function of pressure to predict instabilities, and theoretical investigations of the Lagrangian and Eulerian formulations of finite strain equations of state.

58 GEOSCIENCES↗
DOE OSTI2024

Investigating the Effects of Mixing Dynamics on Twin-Screw Granule Quality Attributes via the Development of a Physics-Based Process Map

Twin-screw granulation (TSG) is an emerging continuous wet granulation technique that has not been widely applied in the industry due to a poor mechanistic understanding of the process. This study focuses on improving this mechanistic understanding by analyzing the effects of the mixing dynamics on the granule quality attributes (PSD, content uniformity, and microstructure). Mixing is an important dynamic process that simultaneously occurs along with the granulation rate mechanisms during the wet granulation process. An improved mechanistic understanding was achieved by identifying and quantifying the physically relevant intermediate parameters that affect the mixing dynamics in TSG, and then their effects on the granule attributes were analyzed by investigating their effects on the granulation rate mechanisms. The fill level, granule liquid saturation, extent of nucleation, and powder wettability were found to be the key physically relevant intermediate parameters that affect the mixing inside the twin-screw granulator. An improved geometrical model for the fill level was developed and validated against existing experimental data. Finally, a process map was developed to depict the effects of mixing on the temporal and spatial evolution of the materials inside the twin-screw granulator. This process map illustrates the mechanism of nucleation and the growth of the granules based on the fundamental material properties of the primary powders (solubility and wettability), liquid binders (viscosity), and mixing dynamics present in the system. Furthermore, it was shown that the process map can be used to predict the granule product quality based on the granule growth mechanism.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Use of Thermistor Temperature Sensors for Cyber-Physical System Security

The last few decades have seen a large proliferation in the prevalence of cyber-physical systems. This has been especially highlighted by the explosive growth in the number of Internet of Things (IoT) devices. Unfortunately, the increasing prevalence of these devices has begun to draw the attention of malicious entities which exploit them for their own gain. What makes these devices especially attractive is the various resource constraints present in these devices that make it difficult to add standard security features. Therefore, one intriguing research direction is creating security solutions out of already present components such as sensors. Physically Unclonable Functions (PUFs) are one potential solution that use intrinsic variations of the device manufacturing process for provisioning security. In this work, we propose a novel weak PUF design using thermistor temperature sensors. Our design uses the differences in resistance variation between thermistors in response to temperature change. To generate a PUF that is reliable across a range of temperatures, we use a response-generation algorithm that helps mitigate the effects of temperature variation on the thermistors. We tested the performance of our proposed design across a range of environmental operating conditions. From this we were able to evaluate the reliability of the proposed PUF with respect to variations in temperature and humidity. We also evaluated the PUF’s uniqueness using Monte Carlo simulations.

Internet of Things (IoT)↗
DOE OSTI2025

Rapid Inference of Logic Gate Neural Networks for Anomaly Detection in High Energy Physics

The increasing data rates and complexity of detectors at the Large Hadron Collider (LHC) necessitate fast and efficient machine learning models, particularly for rapid selection of what data to store, known as triggering. Building on recent work in differentiable logic gates, we present a public implementation of a Convolutional Differentiable Logic Gate Neural Network (CLGN). We apply this to detecting anomalies at the Level-1 Trigger at CMS using public data from the CICADA project. We demonstrate that the CLGN achieves physics performance on par with or superior to conventional quantized neural networks. We also synthesize an LGN for a Field-Programmable Gate Array (FPGA) and show highly promising FPGA characteristics, notably zero Digital Signal Processor (DSP) resource usage. This work highlights the potential of logic gate networks for high-speed, on-detector inference in High Energy Physics and beyond.

FOS: Physical sciences↗
NASA NTRS2009

Comparison of GOES Cloud Classification Algorithms Employing Explicit and Implicit Physics

Cloud-type classification based on multispectral satellite imagery data has been widely researched and demonstrated to be useful for distinguishing a variety of classes using a wide range of methods. The research described here is a comparison of the classifier output from two very different algorithms applied to Geostationary Operational Environmental Satellite (GOES) data over the course of one year. The first algorithm employs spectral channel thresholding and additional physically based tests. The second algorithm was developed through a supervised learning method with characteristic features of expertly labeled image samples used as training data for a 1-nearest-neighbor classification. The latter's ability to identify classes is also based in physics, but those relationships are embedded implicitly within the algorithm. A pixel-to-pixel comparison analysis was done for hourly daytime scenes within a region in the northeastern Pacific Ocean. Considerable agreement was found in this analysis, with many of the mismatches or disagreements providing insight to the strengths and limitations of each classifier. Depending upon user needs, a rule-based or other postprocessing system that combines the output from the two algorithms could provide the most reliable cloud-type classification.

EXPLICIT PHYSICS ALGORITHMS↗
NASA NTRSDate not supplied

Physical Oceanography in the Solar System and Beyond

A key controller of a planet’s rotational evolution, and hence habitability, is tidal dissipation, which on Earth occurs primarily in the oceans. As the discovery of habitable exoplanets is a primary objective of exoplanet research, it is imperative that we understand how “exo-oceans” behave. Despite this importance, little research has investigated the physical oceanography of worlds other than Earth. This oversight has occurred even though the Earth science community has studied tidal flows in Earth’s oceans for over a century and developed sophisticated models that exquisitely match satellite altimetry data, e.g. Here, we present a) models of tidal effects on exoplanets to motivate the problem, b) the application of a physical oceanography model to a putative ancient Venus ocean, and c) the application of that model to an ensemble of “alternative Earths” with a range of continental configurations and seafloor properties. We find that oceanic tidal dissipation can span 5 orders of magnitude, revealing that simulating exo-oceans with Earth science tools will provide fundamental insight into exoplanet evolution and habitability

Physical Oceanography↗
DOE OSTI2016

Strangeness Physics at CLAS in the 6 GeV Era

A very brief overview is presented of varied strangeness-physics studies that have been conducted with the CLAS system in the era of 6 GeV beam at Jefferson Lab. A full bibliography of articles related to open strangeness production is given, together with some physics context for each work. One natural place where these studies could be continued, using a K L beam and the GlueX detector, is in the further investigation of the Λ(1405) baryon. The line shapes and cross sections of this state were found, using photoproduction at CLAS, to differ markedly in the three possible Σπ final states. The analogous strong-interaction reactions using a K L beam could further bring this phenomenon into focus. 1. The CLAS program ran from 1998 to 2012, during the time when the maximum Jefferson Lab beam energy was 6 GeV. An important thrust of this program was to investigate the spectrum of N * and Δ * (non-strange) baryon resonances using photo-and electro-production reactions. To this end, final states containing strange particles (K mesons and low-mass hyperons) played a significant role. The reason for this is partly due to favorable kinemat-ics. When the total invariant energy W (= √ s) of a baryonic system exceeds 1.6 GeV it becomes possible to create the lightest strangeness-containing final state, K + Λ. This is a two-body final state that is straightforward to reconstruct in the CLAS detector system [1], and theoretically it is easier to deal with two-body reaction amplitudes than with three-and higher-body reaction amplitudes. In the mass range W > 1.6 GeV the decay modes of excited nucleons tend to not to favor two-body π-nucleon final states but rather multi-pion states. As input to partial-wave decompositions and resonance-extraction models, therefore, the strangeness-containing final states of high-mass nucleon excitations have had importance. Excited baryons decay through all possible channels simultaneously, constrained by unitarity of course, and channel-coupling is crucial to determining the spectrum of excita-tions. Within this mix of amplitudes, however, the KY decay modes have proven useful. The end result has been, as summarized in the recent edition of the Review of Particle Properties [2], clearer definition of the spectrum of baryonic excitations, with definite contributions from the strangeness sector channels. To this end, strangeness photoproduction cross sections measurements at CLAS for the K + Λ, K + Σ 0 and K 0 Σ + channels on a proton target were published [3–6]. Cross sections are not enough, in general, to define the reaction mechanism, including the underlying N * excitation spectrum. Photoproduction of pseudo-scalar mesons is described by four complex amplitudes, leading to fifteen spin observables in addition to the cross section. Full knowledge of these spin observables would exhaust the information that can be gleaned experimentally about any given reaction channel. Here the hyperonic channels offer another advantage when compared with the non-strange reaction channels: the polarization of most hyperons can be measured directly through their parity-violating weak decay asymmetries. Unlike 163

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2017

Fifth International Conference on High Energy Density Physics

The Fifth International Conference on High Energy Density Physics (ICHED 2015) was held in the Catamaran Hotel in San Diego from August 23-27, 2015. This meeting was the fifth in a series which began in 2008 in conjunction with the April meeting of the American Physical Society (APS). The main goal of this conference has been to bring together researchers from all fields of High Energy Density Science (HEDS) into one, unified meeting.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2018

Multi-physics Object Oriented Simulation Environment (MOOSE)

This two-day workshop is a hands-on introduction to the Multi-Physics Object Oriented Simulation Environment (MOOSE). MOOSE is a simulation framework built from PETSc that enables efficient simulation of complex physical systems with minimal programming background. Attendees are encouraged to visit the MOOSE website at www.mooseframework.org and walk through the step by step process of installing the framework on their computer. Support through this process is provided through the MOOSE Google Group message board. The workshop itself will consist of interactive modules where instructors from the MOOSE development team will work with attendees to build a simple plasma model. Each module will build on previous modules to introduce fundamental MOOSE features that will combine to demonstrate simulation capabilities for low temperature plasma modeling. The intention is not to provide an exhaustive overview of simulation capabilities but to instead provide attendees with the necessary tools to build unique simulation capabilities for their specific research challenges. Users should attend the workshop with laptop computers with MOOSE installed to allow for interactive instruction. At the completion of the workshop attendees will be able to install and run MOOSE and associated applications as well as carry out plasma simulations studies.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

Overview of ST40 results and future: expanding the physics basis of high-field spherical tokamaks

The goal of the ST40 programme is to explore the physics of high-field spherical tokamaks (STs), to validate empirical and theoretical models and, hence, to build confidence in predictions required to support the design of future generations of STs. ST40 is a compact high-field ST that has achieved the following parameters: R 0 = 0.4–0.55 m, I p = 0.20–0.85 MA, B t (R= 0.4 m) = 0.7–2.1 T, κ ⩽ 1.9, and A = 1.6–1.9. Highlights of recent experimental results include (i) H-mode and confinement studies at B t ⩽ 2.1 T, (ii) observation of bifurcation of the scrape-off-layer power fall-off width, λ q , into a ‘wide’ branch that follows existing H-mode scalings and a ‘narrow’ branch that exhibits λ q values that are up to 10 times lower than the predictions of established scalings, (iii) development of high-performance scenarios with plasma current, I p , up to 0.85 MA, (iv) development of highly non-inductive scenarios with high β p , and (v) the first ST40 experiments utilising the newly commissioned impurity powder dropper. The work on all these topics has been supported by a number of advancements in ST40 hardware and software, from plasma control to data analysis and interpretation. At the end of 2025, ST40 embarked on a major upgrade to further expand its capabilities by introducing, among other improvements, all-metal plasma-facing components, 1 MW of electron cyclotron heating, a pellet injector, and a pair of lithium evaporators for wall conditioning.

confinement↗
DOE OSTI2017

Constraining the Magmatic System at Mount St. Helens (2004-2008) Using Bayesian Inversion With Physics-Based Models Including Gas Escape and Crystallization

Physics-based models of volcanic eruptions track conduit processes as functions of depth and time. When used in inversions, these models permit integration of diverse geological and geophysical data sets to constrain important parameters of magmatic systems. We develop a 1-D steady state conduit model for effusive eruptions including equilibrium crystallization and gas transport through the conduit and compare with the quasi-steady dome growth phase of Mount St. Helens in 2005. Viscosity increase resulting from pressure-dependent crystallization leads to a natural transition from viscous flow to frictional sliding on the conduit margin. Erupted mass flux depends strongly on wall rock and magma permeabilities due to their impact on magma density. Including both lateral and vertical gas transport reveals competing effects that produce nonmonotonic behavior in the mass flux when increasing magma permeability. Using this physics-based model in a Bayesian inversion, we link data sets from Mount St. Helens such as extrusion flux and earthquake depths with petrological data to estimate unknown model parameters, including magma chamber pressure and water content, magma permeability constants, conduit radius, and friction along the conduit walls. Even with this relatively simple model and limited data, we obtain improved constraints on important model parameters. We find that the magma chamber had low (<5 wt %) total volatiles and that the magma permeability scale is well constrained at ~10 –11.4 m 2 to reproduce observed dome rock porosities. Here, compared with previous results, higher magma overpressure and lower wall friction are required to compensate for increased viscous resistance while keeping extrusion rate at the observed value.

58 GEOSCIENCES↗
DOE OSTI2017

The Deep Underground Neutrino Experiment: The precision era of neutrino physics

The last decade was remarkable for neutrino physics. In particular, the phenomenon of neutrino flavor oscillations has been firmly established by a series of independent measurements. All parameters of the neutrino mixing are now known, and we have the elements to plan a judicious exploration of new scenarios that are opened by these recent advances. With precise measurements, we can test the three-neutrino paradigm, neutrino mass hierarchy, and charge conjugation parity (CP) asymmetry in the lepton sector. The future long-baseline experiments are considered to be a fundamental tool to deepen our knowledge of electroweak interactions. The Deep Underground Neutrino Experiment (DUNE) will detect a broadband neutrino beam from Fermilab in an underground massive liquid argon time-projection chamber at an L/E of about 103 km GeV-1 to reach good sensitivity for CP-phase measurements and the determination of the mass hierarchy. The dimensions and the depth of the far detector also create an excellent opportunity to look for rare signals like proton decay to study violation of the baryonic number, as well as supernova neutrino bursts, broadening the scope of the experiment to astrophysics and associated impacts in cosmology. In this paper, we discuss the physics motivations and the main experimental features of the DUNE project required to reach its scientific goals.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Identifying Heterogeneous Micromechanical Properties of Biological Tissues via Physics–Informed Neural Networks

The heterogeneous micromechanical properties of biological tissues have profound implications across diverse medical and engineering domains. However, identifying full-field heterogeneous elastic properties of soft materials using traditional engineering approaches is fundamentally challenging due to difficulties in estimating local stress fields. Recently, there has been a growing interest in data-driven models for learning full-field mechanical responses, such as displacement and strain, from experimental or synthetic data. However, research studies on inferring full-field elastic properties of materials, a more challenging problem, are scarce, particularly for large deformation, hyperelastic materials. Here, a physics-informed machine learning approach is proposed to identify the elasticity map in nonlinear, large deformation hyperelastic materials. This study reports the prediction accuracies and computational efficiency of physics-informed neural networks (PINNs) in inferring the heterogeneous elasticity maps across materials with structural complexity that closely resemble real tissue microstructure, such as brain, tricuspid valve, and breast cancer tissues. Further, the improved architecture is applied to three hyperelastic constitutive models: Neo-Hookean, Mooney Rivlin, and Gent. Furthermore, the improved network architecture consistently produces accurate estimations of heterogeneous elasticity maps, even when there is up to 10% noise present in the training data.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

Search for new physics in final states with a single photon and missing transverse momentum in proton-proton collisions at $ \sqrt{s}=13 $ TeV

Here, a search is conducted for new physics in final states containing a photon and missing transverse momentum in proton--proton collisions at $\sqrt{s} =$ 13 TeV, using the data collected in 2016 by the CMS experiment at the LHC, corresponding to an integrated luminosity of 35.9 fb$^{-1}$. No deviations from the predictions of the standard model are observed. The results are interpreted in the context of dark matter production and models containing extra spatial dimensions, and limits on new physics parameters are calculated at 95% confidence level. For the two simplified dark matter production models considered, the observed (expected) lower limits on the mediator masses are both 950 (1150) GeV for 1 GeV dark matter mass. For an effective electroweak-dark matter contact interaction, the observed (expected) lower limit on the suppression parameter $\Lambda$ is 850 (950) GeV. Values of the effective Planck scale up to 2.85-2.90 TeV are excluded for between 3 and 6 extra spatial dimensions.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗