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Physics Informed Neural Nets for Systems Health Management

To facilitate and solve the prediction problem, awareness of the current health state of the system is key, since it is necessary to perform condition-based predictions. To accurately predict the future state of any system, it is required to possess knowledge of its current health state and future operational conditions. Development in data-driven algorithms in regression of complex nonlinear functions and classification tasks have generated a growing interest in artificial intelligence for industrial applications. Complex multi-physics models as well as digital twins, once purely built on physics and corresponding simplified lumped parameter iterations, can now benefit from machine learning algorithms to mitigate the lack of understanding of some complex behavior. The research work presents application of physics-informed neural nets application to a representative electric powertrain for unmanned aerial vehicles. The model is composed of physics-derived and empirical equations, integrated with connected networks that are strategically placed within the model to substitute equations that are subject to large uncertainty. Polynomial fit driven by heuristics or empirical observations can be substituted by more flexible networks that can minimize the error between model predictions and observations without being restricted to a predefined functional form. This modeling strategy allows training of networks deep inside the model and unknown parameters in a single learning stage.

Physics Informed↗
DOE OSTI2012

The Influence of Accelerator Science on Physics Research

We evaluate accelerator science in the context of its contributions to the physics community. We address the problem of quantifying these contributions and present a scheme for a numerical evaluation of them. We show by using a statistical sample of important developments in modern physics that accelerator science has influenced 28% of post-1938 physicists and also 28% of post-1938 physics research. We also examine how the influence of accelerator science has evolved over time, and show that on average it has contributed to a physics Nobel Prize-winning research every 2.9 years.

43 PARTICLE ACCELERATORS↗
DOE OSTI2012

Geologic Assessment of the Damage Zone from the Second Test at Source Physics Experiment-Nevada (SPE-N)

The National Center for Nuclear Security, established by the U.S. Department of Energy, National Nuclear Security Administration (NNSA), is conducting a series of explosive tests at the Nevada National Security Site that are designed to increase the understanding of certain basic physical phenomena associated with underground explosions. These tests will aid in developing technologies that might be used to detect underground nuclear explosions in support of verification activities for the Comprehensive Nuclear-Test-Ban Treaty. The initial project is a series of explosive tests, known collectively as the Source Physics Experiment-Nevada (SPE-N), being conducted in granitic rocks. The SPE-N test series is designed to study the generation and propagation of seismic waves. The results will help advance the seismic monitoring capability of the United States by improving the predictive capability of physics-based modeling of explosive phenomena. The first SPE N (SPE-N-1) test was conducted in May 2011, using 100 kg of explosives at the depth of 54.9 m in the U 15n source hole. SPE-N-2 was conducted in October 2011, using 1,000 kg of explosives at the depth of 45.7 m in the same source hole. The SPE-N-3 test was conducted in the same source hole in July 2012, using the same amount and type of explosive as for SPE-N-2, and at the same depth as SPE-N-2, within the damage zone created by the SPE-N-2 explosion to investigate damage effects on seismic wave propagation. Following the SPE-N-2 shot and prior to the SPE-N-3 shot, the core hole U-15n#10 was drilled at an angle from the surface to intercept the SPE-N-2 shot point location to obtain information necessary to characterize the damage zone. The objective was to determine the position of the damage zone near the shot point, at least on the northeast, where the core hole penetrated it, and obtain information on the properties of the damaged medium. Geologic characterization of the post-SPE-N-2 core hole included geophysical logging, a directional survey, and geologic description of the core to document visual evidence of damage. Selected core samples were provided to Sandia National Laboratories (SNL) for measurement of physical and mechanical properties. A video was also run in the source hole after it was cleaned out. A significant natural fault zone was encountered in the angle core hole between 5.7 and 7.5 m from the shot point. However, several of the fractures observed in the core hole are interpreted as having been caused by the explosion. The fractures are characterized by a “fresh,” mechanically broken look, with uncoated and very irregular surfaces. They tend to terminate against natural fractures and have orientations that differ from the previously defined natural fracture sets; they are common starting at about 5.4 m from the shot point. Within about 3.3 m of the shot point to the end of the recovered core at 1.6 m from the shot point, some of the core samples are softer and lighter in color, but do not appear to be weathered. It is thought this could be indicative of the presence of distributed microfracturing.

SPE, Source Physics Experiment, geology↗
DOE OSTI2017

Method for Determining the Sensitivity of a Physical Security System.

Modern systems, such as physical security systems, are often designed to involve complex interactions of technological and human elements. Evaluation of the performance of these systems often overlooks the human element. A method is proposed here to expand the concept of sensitivity—as denoted by d’—from signal detection theory (Green & Swets 1966; Macmillan & Creelman 2005), which came out of the field of psychophysics, to cover not only human threat detection but also other human functions plus the performance of technical systems in a physical security system, thereby including humans in the overall evaluation of system performance. New in this method is the idea that probabilities of hits (accurate identification of threats) and false alarms (saying “threat” when there is not one), which are used to calculate d’ of the system, can be applied to technologies and, furthermore, to different functions in the system beyond simple yes-no threat detection. At the most succinct level, the method returns a single number that represents the effectiveness of a physical security system; specifically, the balance between the handling of actual threats and the distraction of false alarms. The method can be automated, and the constituent parts revealed, such that given an interaction graph that indicates the functional associations of system elements and the individual probabilities of hits and false alarms for those elements, it will return the d’ of the entire system as well as d’ values for individual parts. The method can also return a measure of the response bias* of the system. One finding of this work is that the d’ for a physical security system can be relatively poor in spite of having excellent d’s for each of its individual functional elements.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2023

IRIS-HEP Strategic Plan for the Next Phase of Software Upgrades for HL-LHC Physics

The quest to understand the fundamental building blocks of nature and their interactions is one of the oldest and most ambitious of human scientific endeavors. CERN's Large Hadron Collider (LHC) represents a huge step forward in this quest. The discovery of the Higgs boson, the observation of exceedingly rare decays of $B$ mesons, and stringent constraints on many viable theories of physics beyond the Standard Model (SM) demonstrate the great scientific value of the LHC physics program. The next phase of this global scientific project will be the High-Luminosity LHC (HL-LHC) which will collect data starting circa 2029 and continue through the 2030s. The primary science goal is to search for physics beyond the SM and, should it be discovered, to study its implications. In the HL-LHC era, the ATLAS and CMS experiments will record around 100 times as many collisions as were used to discover the Higgs boson (and at twice the energy). Both NSF and DOE are making large detector upgrade investments so the HL-LHC can operate in this high-rate environment. Similar investment in software R&D for acquiring, managing, processing and analyzing HL-LHC data is critical to maximize the return-on-investment in the upgraded accelerator and detectors. This report presents a strategic plan for a possible second 5-year funded phase (2023 through 2028) for the Institute for Research and Innovation in Software for High Energy Physics (IRIS-HEP) which will close remaining software and computing gaps to deliver HL-LHC science.

43 PARTICLE ACCELERATORS↗
DOE OSTI2020

DEMONSTRATION OF A DATA-DRIVEN PHYSICS-BASED APPROACH FOR COMPUTATIONALLY EFFICIENT CFD PREDICTION OF TWO-PHASE BUBBLY FLOW

To realize efficient computational fluid dynamics (CFD) prediction of two-phase flow, a multi-scale physics-guided data-driven approach, Feature Similarity Measurement (FSM) technique was developed for error estimation in two-phase flow simulation using coarse-mesh CFD, to achieve a comparable accuracy as fine-mesh simulations with fast-running feature. By defining physics-guided parameters and variable gradients as physical features, FSM has the capability to capture the underlying local patterns in the coarse-mesh CFD simulation. Massive low-fidelity data and respective high-fidelity data are used to explore the underlying information relevant to the main simulation errors and the effects of phenomenological scaling. By learning from previous simulation data, a surrogate model using deep feedforward neural network (DFNN) can be developed and trained to estimate the simulation error of coarse-mesh CFD. In a demonstration case of two-phase bubbly flow, the DFNN model well captured and corrected the unphysical “peaks” in the velocity and void fraction profiles near the wall in the coarse-mesh configuration, even for extrapolative predictions. The research documented supports the feasibility of the physics-guided deep learning methods for coarse mesh CFD simulations which has a potential for the efficient industrial design.

42 ENGINEERING↗
DOE OSTI2012

Nuclear data uncertainty propagation in a lattice physics code using stochastic sampling

A methodology is presented for 'black box' nuclear data uncertainty propagation in a lattice physics code using stochastic sampling. The methodology has 4 components: i) processing nuclear data variance/covariance matrices including converting the native group structure to a group structure 'compatible' with the lattice physics code, ii) generating (relative) random samples of nuclear data, iii) perturbing the lattice physics code nuclear data according to the random samples, and iv) analyzing the distribution of outputs to estimate the uncertainty. The scheme is described as implemented at PSI, in a modified version of the lattice physics code CASMO-5M, including all relevant practical details. Uncertainty results are presented for a BWR pin-cell at hot zero power conditions and a PWR assembly at hot full power conditions with depletion. Results are presented for uncertainties in eigenvalue, 1-group microscopic cross sections, 2-group macroscopic cross sections, and isotopics. Interesting behavior is observed with burnup, including a minimum uncertainty due to the presence of fertile U-238 and a global effect described as 'synergy', observed when comparing the uncertainty resulting from simultaneous and one-at-a-time variations of nuclear data. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2013

Research on acceleration method of reactor physics based on FPGA platforms

The physical designs of the new concept reactors which have complex structure, various materials and neutronic energy spectrum, have greatly improved the requirements to the calculation methods and the corresponding computing hardware. Along with the widely used parallel algorithm, heterogeneous platforms architecture has been introduced into numerical computations in reactor physics. Because of the natural parallel characteristics, the CPU-FPGA architecture is often used to accelerate numerical computation. This paper studies the application and features of this kind of heterogeneous platforms used in numerical calculation of reactor physics through practical examples. After the designed neutron diffusion module based on CPU-FPGA architecture achieves a 11.2 speed up factor, it is proved to be feasible to apply this kind of heterogeneous platform into reactor physics. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2016

Benchmark Comparisons of Lattice Physics Calculations for Thorium-Based Fuels in Pressure-Tube Heavy Water Reactors

Thorium is a fertile nuclear fuel resource that is nearly three times as abundant as uranium in the earth's crust and that can be exploited and used to extend uranium resources. The pressure tube heavy water reactor (PTHWR) is an excellent existing technology for utilizing thorium-based fuels, due to its high neutron economy achieved by using heavy water as a moderator and coolant, the ability to perform online refueling, and its flexibility in fuel management. Reactor physics studies are underway at the Canadian Nuclear Laboratories (CNL) to evaluate several types of thorium-based fuels that could be implemented in PT-HWRs in the near-term and intermediate future, building upon past experience. For preliminary, conceptual studies, deterministic lattice physics and core physics codes such as WIMS-AECL and RFSP are used to provide quick and more approximate estimates of performance and safety characteristics. The objective of this study was to perform 2D lattice physics benchmark comparisons between WIMS-AECL and MCNP5 for several types of thorium-based fuel bundle lattices for potential use in PT-HWRs. Benchmark comparisons will help confirm the validity of deterministic calculation results, and provide estimates of the potential magnitude of calculation errors and uncertainties. Areas for potential improvements in the WIMS-AECL calculations may also be identified. (authors)

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2026

pop-cosmos : redshifts and physical properties of KiDS-1000 galaxies

ABSTRACT Principled Bayesian inference of galaxy properties has not previously been performed for wide-area weak-lensing surveys with millions of sources. We address this gap by applying the pop-cosmos generative model to perform spectral energy distribution (SED) fitting for 4 million KiDS (Kilo-Degree Survey)-1000 galaxies. Calibrated on deep COSMOS2020 photometric data, pop-cosmos specifies a physically motivated prior over the galaxy population up to $z \simeq 6$ in stellar population synthesis (SPS) parameter space. Using the Speculator SPS emulator with GPU (graphics processing unit)-accelerated Markov Chain Monte Carlo sampling, we perform full posterior inference at 8.2 GPU seconds per galaxy, obtaining joint constraints on galaxy redshifts and physical properties. We validate photometric redshifts against $\sim \!185\,\!000$ KiDS galaxies cross-matched to Dark Energy Spectroscopic Instrument Data Release 1 spectroscopic samples, achieving low bias ($2\times 10^{-3}$), scatter ($\sigma _{\mathrm{MAD}}=0.03$), and outlier fraction (3.2 per cent) for the Bright Galaxy Survey, with comparable performance (bias $3\times 10^{-2}$, $\sigma _{\mathrm{MAD}}=0.05$, 1.0 per cent outliers) for luminous red galaxies (LRGs). Within the LRG sample, we identify massive, dusty, star-forming contaminants at $z \simeq 0.4$ satisfying standard colour selections for quenched populations. We infer trends in stellar mass, star formation, metallicity, and dust across five tomographic redshift bins consistent with established scaling relations. Using specific star formation rate constraints, we identify $\sim$7 per cent of KiDS-1000 galaxies as quenched, versus 37 per cent implied by conservative colour cuts. This enables the construction of weak-lensing samples defined by physical properties while mitigating intrinsic alignment systematics and preserving statistical power. Our analysis validates pop-cosmos out of sample, establishing it as a scalable approach for galaxy evolution and cosmological analyses with photometric surveys.

Halder, Anik [Institute of Astronomy and Kavli Ins↗
DOE OSTI2022

Review of Particle Physics

Abstract The Review summarizes much of particle physics and cosmology. Using data from previous editions, plus 2,143 new measurements from 709 papers, we list, evaluate, and average measured properties of gauge bosons and the recently discovered Higgs boson, leptons, quarks, mesons, and baryons. We summarize searches for hypothetical particles such as supersymmetric particles, heavy bosons, axions, dark photons, etc. Particle properties and search limits are listed in Summary Tables. We give numerous tables, figures, formulae, and reviews of topics such as Higgs Boson Physics, Supersymmetry, Grand Unified Theories, Neutrino Mixing, Dark Energy, Dark Matter, Cosmology, Particle Detectors, Colliders, Probability and Statistics. Among the 120 reviews are many that are new or heavily revised, including a new review on Machine Learning, and one on Spectroscopy of Light Meson Resonances. The Review is divided into two volumes. Volume 1 includes the Summary Tables and 97 review articles. Volume 2 consists of the Particle Listings and contains also 23 reviews that address specific aspects of the data presented in the Listings. The complete Review (both volumes) is published online on the website of the Particle Data Group (pdg.lbl.gov) and in a journal. Volume 1 is available in print as the PDG Book. A Particle Physics Booklet with the Summary Tables and essential tables, figures, and equations from selected review articles is available in print, as a web version optimized for use on phones, and as an Android app.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Experimental neutrino physics in a nuclear landscape

There are profound connections between neutrino physics and nuclear experiments. Exceptionally precise measurements of single and double beta-decay spectra illuminate the scale and nature of neutrino mass and may finally answer the question of whether neutrinos are their own anti-matter counterparts. Neutrino–nucleus scattering underpins oscillation experiments and probes nuclear structure, neutrinos offer a rare vantage point into collapsing stars and nuclear fission reactors and techniques pioneered in neutrino nuclear physics experiments are advancing quantum sensing technologies. In this article, we review current and planned efforts at the intersection of neutrino and nuclear experiments. This article is part of the theme issue ‘The liminal position of Nuclear Physics: from hadrons to neutron stars’.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2016

Research in Theoretical High-Energy Physics at Southern Methodist University

The SMU Theory group has developed a strong expertise in QCD, PDFs, and incisive comparisons between collider data and theory. The group pursues realistic phenomenological calculations for high-energy processes, the highly demanded research area driven by the LHC physics. Our field has seen major discoveries in recent years from a variety of experiments, large and small, including a number recognized by Nobel Prizes. There is a wealth of novel QCD data to explore. The SMU theory group develops the most advanced and innovative tools for comprehensive analysis in applications ranging from Higgs physics and new physics searches to nuclear scattering.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Physics Flash (Summer 2021)

The Summer 2021 issue of Physics Flash includes a note from Physics Division Leader Tanja Pietraß, Physics Division staff in the news, LANSCE neutron beam transport, novel application of 'computer vision' techniques and using pRad to visualize electromagnetic fields.

43 PARTICLE ACCELERATORS↗
DOE OSTI2012

Searching for New Physics with Flavor Violating Observables

In this talk, I review the status and prospects of several low energy flavor observables that are highly sensitive to New Physics effects. In particular I discuss the implications for possible New Physics in b {yields} s transitions coming from the recent experimental results on the B{sub s} mixing phase, the branching ratio of the rare decay B{sub s} {yields} {mu}{sup +}{mu}{sup -}, and angular observables in the B {yields} K* {mu}{sup +}{mu}{sup -} decay. Also the recent evidence for direct CP violation in singly Cabibbo suppressed charm decays and its interpretation in the context of New Physics models is briefly discussed.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2018

2018 Fermilab Physics Slam: Explaining neutrino oscillations

For his 2018 Physics Slam presentation at Fermilab, Northwestern University scientist André de Gouvêa took on one of the most fascinating particles in physics: the neutrino. In 10 minutes, he explained—with the help of a few props—what neutrinos are and how physicists discovered that these particles can transform into one other, a phenomenon known as neutrino oscillation. At the end of the evening, the audience declared him to be the winner of the 2018 Physics Slam. Curious about neutrinos? Learn more about these particles at All Things Neutrino: http://neutrinos.fnal.gov

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Scintillating glass for precision calorimetry in nuclear physics

High-performance scintillator materials are needed for particle identification and measurements of energy and momentum of electromagnetic particles in modern nuclear physics experiments. As an example, the US Electron-Ion Collider, a unique collider with diverse physics topics, requires electromagnetic calorimetry enabling high-quality electron identification and detection in the momentum range of 0.3 to tens of GeV. The highest resolution in electromagnetic calorimeters can be provided by homogeneous materials, e.g., lead tungstate crystals. Inorganic glass scintillators have been investigated as an attractive and cost-effective alternative to crystals, that is also easier and faster to manufacture in mass production. In this paper, we discuss progress in the fabrication and characterization of recent scintillating glass samples on both test bench and beam tests. Further, the results are well-reproduced by simulation and are discussed in the context of the Electron-Ion Collider experimental requirements and bench-marked against lead tungstate crystals.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

A physics-based parametric regression approach for feedwater pump system diagnosis

Here in this paper, we assessed the performance of a model-based approach for fault diagnosis of a nuclear power plant feedwater pump system. Physics-based models were constructed to monitor the performance of the system components. Plant data were used for the calibration of the models and subsequently in the diagnosis of abnormal events. We considered two real-time events representing scenarios of a pump fault and component performance degradation. The two events were correctly diagnosed, and the results demonstrated the high detection sensitivity of the physics-based models. Various sensor fault scenarios were simulated to show the capability of the approach to detect and uniquely identify sensor faults. Results for a scenario in which the plant operated in flexible power mode also showed that the diagnostic approach is insensitive to changes of operating conditions, which is one of the advantages of the model-based approach using physics-based models over purely data-driven approach.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗