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DOE OSTI2019

Availability and Reliability analysis of Proton Improvement Plan-II Superconducting Radio Frequency Linear Accelerator

Proton Improvement Plan -II is high intensity and high energy proton accelerator which will be used to support neutrino program at Fermilab. Due to the requirement from experiments, this accelerator is designed to be a highly reliable and available system. In this paper, a reliability model has been created which depicts a complete accelerator system and supporting utilities. Reliability and Availability of the complete system are estimated. It has been shown that Availability and Reliability of the system can be increased significantly by introducing failure tolerance of the beamline elements in each accelerating section of superconducting linac.

43 PARTICLE ACCELERATORS↗

DOE OSTI2019

Availability and Reliability Analysis of Proton Improvement Plan-II Superconducting Radio Frequency Linear Accelerator

43 PARTICLE ACCELERATORS↗

DOE OSTI2026

Regional surrogates for predictive control of digital twins

Digital twins of complex systems must involve a model that is fast, generalizable, and usable for real-time control. For example, high-fidelity nonlinear multiphysics simulations can capture laser-material interactions, but are too slow for optimization or model predictive control (MPC). Reduced-order models, used to accelerate such computation, frequently fail to generalize to unseen inputs or control states. We show theoretically that this failure is intrinsic, i.e., that a learned model is non-unique outside the sampled subspace when its low-rank structure arises from limited excitation and clustered eigenvalues, rather than from a user-imposed truncation alone. Motivated by this result, we propose a control-ready regional surrogate-construction framework for both autonomous and nonautonomous dynamics; it employs Koopman lifting to represent nonlinearities, while preserving spatial locality. We illustrate our approach by constructing a control-ready surrogate for the digital twin of a thermal component of additive-manufacturing process. Our surrogate, localized in space through a von Neumann stencil, is learned from noisy high-fidelity simulations that emulate thermal-camera images collected during the manufacturing. It is linear in thermo-physically augmented states so that MPC reduces to a convex quadratic program. The surrogate requires no online correction, generalizes to unseen scan paths and power profiles of the laser, and is more than three orders of magnitude faster than a finite-difference solver. Furthermore, when the MPC sequence computed on the digital twin is applied to this solver, closed-loop temperature regulation is recovered, showing that the surrogate preserves control-relevant input-output behavior.

Data-driven model↗

DOE OSTI2025

Data-Conforming Data-Driven Control: Avoiding Premature Generalizations Beyond Data

Data-driven and adaptive control approaches face the problem of introducing sudden distributional shifts beyond the distribution of data encountered during learning. Therefore, they are prone to invalidating the very assumptions used in their own construction. This is due to the linearity of the underlying system, inherently assumed and formulated in most data-driven control approaches, which may falsely generalize the behavior of the system beyond the behavior experienced in the data. This article seeks to mitigate these problems by enforcing consistency of the newly designed closed-loop systems with data and slowing down any distributional shifts in the joint state-input space. This is achieved through incorporating affine regularization terms and linear matrix inequality constraints to data-driven approaches, resulting in convex semi-definite programs that can be efficiently solved by standard software packages. We discuss the optimality conditions of these programs and then conclude this article with a numerical example that further highlights the problem of premature generalization beyond data and shows the effectiveness of our proposed approaches in enhancing the safety of data-driven control methods.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2016

Baryon spectroscopy with polarization observables from CLAS

Meson photoproduction is an important tool in the study of baryon resonances. The spectrum of broad and overlapping nucleon excitations can be greatly clarified by use of polarization observables. The N* program at Jefferson Lab with the CEBAF Large Acceptance Spectrometer (CLAS) includes experimental studies with linearly and circularly polarized tagged photon beams, longitudinally and transversely polarized nucleon targets, and recoil polarizations. An overview of these experimental studies and recent results will be given.

Strauch, Steffen↗

DOE OSTI2020

Nevada Higher Education Benefits from US Department of Energy (DOE) Environmental Management (EM) Nevada Program's Transfer of Geologic Samples - 20442

The Nevada National Security Site (NNSS), formerly the Nevada Test Site, was the location of 100 historic atmospheric and 828 historic underground nuclear tests from 1951 to 1992. Related to this historic nuclear testing, geologic and hydrologic studies of the site were conducted utilizing the skills and the expertise of the U.S. Geological Survey (USGS) and national laboratories (Los Alamos National Laboratory, Lawrence Livermore National Laboratory), who were principal in leading the development of weapons and were responsible for specific underground testing programs. The subsurface samples and technical/scientific data associated with NNSS geologic studies (past and present) are preserved and stored at the USGS Mercury Core Library and Data Center located at the NNSS. Currently, the facility stores over 2,000,000 linear feet of cores and cuttings from more than 2,600 drill holes that can be accessed for study. Most of the samples and historic geologic work was focused directly on subsurface geologic settings that relate directly to historic underground nuclear testing. Since 1992, the United States has observed a unilateral moratorium on full-scale nuclear testing, and the U.S. Department of Energy (DOE) Environmental Management (EM) Nevada Program is now responsible for hydrogeologic characterization of the potential impacts to the natural groundwater systems that may have resulted from historic underground nuclear tests. As part of this effort, the EM Nevada Program Underground Test Area (UGTA) Activity has drilled and completed over 58 deep (2,000 - 7,000 ft.) characterization wells, totaling in excess of 170,000 linear feet of cuttings and core samples. Cutting samples were collected as triplicate samples for each respective depth interval, to account for potential later nondestructive/destructive analysis and to preserve samples for regulatory purposes. Recently, it was recognized by the EM Nevada Program that opportunities may exist to reduce the cost and floor space required for the storage of geologic samples at the Mercury Core Library without impacting the integrity and representative nature of the samples necessary for project execution. An initiative was sponsored by EM Nevada Program to evaluate several options: 1) disposal of a portion of cuttings and cores in a land fill setting; 2) reduction in sample volume through skeletonizing core and cuttings from wells to a representative but much smaller number of samples; and 3) solicit potential interest in the academic community where other geoscientists could freely access the samples for studies. The Nevada state university system through the Nevada Bureau of Mines and Geology responded positively to the opportunity to receive these NNSS samples from the EM Nevada Program. In June 2019, approximately 17,000 geologic samples, representing greater than 170,000 linear feet of drilling and weighing over 20,000 pounds, were shipped from the NNSS to the Great Basin Science Sample and Records Library located in Reno, Nevada. The benefits resulting from this transfer were realized by the EM Nevada Program in terms of cost and space savings for geologic sample storage at the NNSS. The transfer did not impact the EM Nevada Program mission as access to representative geologic samples for regulatory and scientific purposes was preserved. Moreover, the Nevada Bureau of Mines and Geology acquired a significant resource of subsurface geologic samples and supporting technical data to support academic and scientific studies in a complex volcanic setting in southwest Nevada. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2017

Introducing Human Mandible Identification [(hu)MANid]: A Free, Web‐Based GUI to Classify Human Mandibles

Abstract Statistical programs have revolutionized the way in which forensic anthropologists conduct casework by allowing practitioners to use computationally complex analytics at the click of a button. Importantly, the products of these statistical programs are reproducible and contain measures of error or uncertainty, thereby strengthening conclusions. This paper is an introduction to (hu) MAN id, a free, web‐based application that uses linear and mixture discriminant function analyses to classify human mandibles into one of many worldwide and/or periodic reference groups. The mechanics, development, and use of the application will be discussed. Further, the program was tested against other software to compare model performances and classifications. Total correct classifications among the test cases and programs were identical. Ten mandibles were tested using both statistical procedures. Mixture discriminant analysis improved classification by an average of 9.3% and correctly identified three more mandibles than LDA . Therefore, we believe (hu) MAN id will be an asset to the anthropological community.

Berg, Gregory E.↗

DOE OSTI2020

Toward a scalable robust security-constrained optimal power flow using a proximal projection bundle method

Robust security-constrained optimal power flow (rSCOPF) aims to find the worst-case contingencies of alternating current optimal power flow (ACOPF) in power systems. With the rise of GPU architectures on the upcoming supercomputer architectures, optimization algorithms that rely on sparse linear algebra and indefinite linear systems are becoming increasingly hard to solve efficiently (e.g. interior-point method). To address this we revisit a maximin optimization formulation of the rSCOPF and the single-level mixed-integer semidefinite programming (MISDP) reformulation, which is obtained by taking the Lagrangian relaxation of the inner minimization ACOPF problem. In this paper, we focus on the development of a proximal projection bundle method (PPBM) for solving continuous relaxation node subproblems of the MISDP problem, based primarily on the well-known alternating direction method of multipliers. Cutting planes reminiscent of bundle method ideas are also applied in coordination with updates of the proximal parameter. The cutting-plane method can generate a large number of linear inequalities, leading to a large scale but decomposable quadratic programming (QP) subproblem that is amenable to GPUs. We present the numerical results on the IEEE 30, 57, 118, and 300-bus systems by using our PBMM method. We discuss the main computational bottleneck of our method, which is the time taken to solve each iteration of a QP subproblem instance of the PPBM, and how GPU architectures can accelerate this solution process.

bundle method↗

DOE OSTI2017

Structured Light-Matter Interactions Enabled By Novel Photonic Materials

The synergy of complex materials and complex light is expected to add a new dimension to the science of light and its applications [1]. The goal of this program is to investigate novel phenomena emerging at the interface of these two branches of modern optics. While metamaterials research was largely focused on relatively “simple” linearly or circularly polarized light propagation in “complex” nanostructured, carefully designed materials with properties not found in nature, many singular optics studies addressed “complex” structured light transmission in “simple” homogeneous, isotropic, nondispersive transparent media, where both spin and orbital angular momentum are independently conserved. However, if both light and medium are complex so that structured light interacts with a metamaterial whose optical materials properties can be designed at will, the spin or angular momentum can change, which leads to spin-orbit interaction and many novel optical phenomena that will be studied in the proposed project. Indeed, metamaterials enable unprecedented control over light propagation, opening new avenues for using spin and quantum optical phenomena, and design flexibility facilitating new linear and nonlinear optical properties and functionalities, including negative index of refraction, magnetism at optical frequencies, giant optical activity, subwavelength imaging, cloaking, dispersion engineering, and unique phase-matching conditions for nonlinear optical interactions. In this research program we focused on structured light-matter interactions in complex media with three particularly remarkable properties that were enabled only with the emergence of metamaterials: extreme anisotropy, extreme material parameters, and magneto-electric coupling–bi-anisotropy and chirality.

74 ATOMIC AND MOLECULAR PHYSICS↗

DOE OSTI2021

High-Speed Ionic Synaptic Memory Based on 2D Titanium Carbide MXene

Synaptic devices with linear high-speed switching can accelerate learning in artificial neural networks (ANNs) embodied in hardware. Conventional resistive memories however suffer from high write noise and asymmetric conductance tuning, preventing parallel programming of ANN arrays. Electrochemical random-access memories (ECRAMs), where resistive switching occurs by ion insertion into a redox-active channel, aim to address these challenges due to their linear switching and low noise. ECRAMs using 2D materials and metal oxides however suffer from slow ion kinetics, whereas organic ECRAMs enable high-speed operation but face challenges toward on-chip integration due to poor temperature stability of polymers. Here, ECRAMs using 2D titanium carbide (Ti 3 C 2 T x ) MXene that combine the high speed of organics and the integration compatibility of inorganic materials in a single high-performance device are demonstrated. These ECRAMs combine the speed, linearity, write noise, switching energy, and endurance metrics essential for parallel acceleration of ANNs, and importantly, they are stable after heat treatment needed for back-end-of-line integration with Si electronics. The high speed and performance of these ECRAMs introduces MXenes, a large family of 2D carbides and nitrides with more than 30 stoichiometric compositions synthesized to date, as promising candidates for devices operating at the nexus of electrochemistry and electronics.

2D materials↗

DOE OSTI2015

HPC Programming on Intel Many-Integrated-Core Hardware with MAGMA Port to Xeon Phi

This paper presents the design and implementation of several fundamental dense linear algebra (DLA) algorithms for multicore with Intel Xeon Phi coprocessors. In particular, we consider algorithms for solving linear systems. Further, we give an overview of the MAGMA MIC library, an open source, high performance library, that incorporates the developments presented here and, more broadly, provides the DLA functionality equivalent to that of the popular LAPACK library while targeting heterogeneous architectures that feature a mix of multicore CPUs and coprocessors. The LAPACK-compliance simplifies the use of the MAGMA MIC library in applications, while providing them with portably performant DLA. High performance is obtained through the use of the high-performance BLAS, hardware-specific tuning, and a hybridization methodology whereby we split the algorithm into computational tasks of various granularities. Execution of those tasks is properly scheduled over the heterogeneous hardware by minimizing data movements and mapping algorithmic requirements to the architectural strengths of the various heterogeneous hardware components. Our methodology and programming techniques are incorporated into the MAGMA MIC API, which abstracts the application developer from the specifics of the Xeon Phi architecture and is therefore applicable to algorithms beyond the scope of DLA.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2019

Mimicking Geologic Depositional Fabrics for Multiphase Flow Experiments

A novel laboratory technique is presented for generating two-dimensional beadpacks with reproducible natural geologic sedimentary bedforms. The heterogeneous beadpacks are deposited in a 0.6 m × 0.6 m × 0.02 m glass slab chamber using a programmable two-axis linear actuator. The method takes advantage of natural mechanical sorting processes, along with the ability to program the motion of the arm, to efficiently build cross-beds and ripple laminae similar to those seen in natural water-lain clastic deposits. By using a mixture of grain sizes (200 to 800 μm diameter), depositional fabrics with multiscale heterogeneity (mm to dm) are generated. Reproducibility tests show very high correlation among multiple fabric realizations produced with similar inputs. After introducing this first-of-a-kind capability to produce depositionally realistic fabrics at scales larger than that of rock cores, a demonstrative study is presented that illustrates gravity unstable multiphase flow which is relevant in the context of CO 2 sequestration. Preliminary results highlight the dramatic impact small scale capillary heterogeneities have on multiphase immiscible displacement and can help bridge understanding between core scale experiments and reservoir scale observations.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2014

Intrinsic SiO{sub x}-based unipolar resistive switching memory. II. Thermal effects on charge transport and characterization of multilevel programing

Multilevel programing and charge transport characteristics of intrinsic SiO{sub x}-based resistive switching memory are investigated using TaN/SiO{sub x}/n{sup ++}Si (MIS) and TiW/SiO{sub x}/TiW (MIM) device structures. Current transport characteristics of high- and low-resistance states (HRS and LRS) are studied in both device structures during multilevel operation. Analysis of device thermal response demonstrates that the effective electron energy barrier is strongly dependent on the resistance of the programed state, with estimates of 0.1 eV in the LRS and 0.6 eV in the HRS. Linear data fitting and conductance analyses indicate Poole-Frenkel emission or hopping conductance in the low-voltage region, whereas Fowler-Nordheim (F-N) or trap-assisted tunneling (TAT) is indicated at moderate voltage. Characterizations using hopping transport lead to hopping distance estimates of ∼1 nm in the LRS for both device structures. Relative permittivity values (ε{sub r}) were extracted using the Poole-Frenkel formulism and estimates of local filament temperature, where ε{sub r} values were ∼80 in the LRS and ∼4 in the HRS, suggesting a strongly polarized medium in the LRS. The onset of F-N tunneling or TAT corresponds to an observed “overshoot” in the I-V response with an estimated threshold of 1.6 ± 0.2 V, in good agreement with reported electro-luminescence results for LRS devices. Resistive switching is discussed in terms of electrochemical reactions between common SiO{sub 2} defects, and specific defect energy levels are assigned to the dominant transitions in the I-V response. The overshoot response in the LRS is consistent with TAT through either the Eγ' oxygen vacancy or the hydrogen bridge defect, both of which are reported to have an effective bandgap of 1.7 eV. The SET threshold at ∼2.5 V is modeled as hydrogen release from the (Si-H){sub 2} defect to generate the hydrogen bridge, and the RESET transition is modeled as an electrochemical reaction that re-forms (SiH){sub 2}. The results provide further insights into charge transport and help identify potential switching mechanisms in SiO{sub x}-based unipolar resistive switching memory.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2022

Deterministic and Monte Carlo Nuclear Data Adjustment Methods [Slides]

For the Bayesian Monte Carlo methodology, a need to understand convergence of the posterior moments as a function of the number of parameter realizations is required. In high-dimensional systems, it can be very costly to sample entire parameter space and perform functional evaluation for every realization. Bayesian Monte Carlo allows one to relax the GLLS approximations of model linearity and prior/posterior PDF shape. The Bayesian Stochastic Collocation Method is a deterministic approach to “sample” the parameter space. It allows one to relax the GLLS approximations of model linearity and posterior PDF shape. Higher-order posterior moments (i.e., skewness, kurtosis, etc.) can be studied through polynomial expansion. Tensor product quadrature scales poorly and can use sparse grid quadrature methods.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2017

Using Whisper-1.1 to Guide Improvements to Nuclear Data Evaluations [Slides]

This presentation covers the use of Whisper-1.1 to guide improvements to nuclear data evaluations. This presentation provides a brief overview on what Whisper-1.1 is. Additionally covered is the benchmark selection: using benchmark and application correlations (ck) computed using nuclear data sensitivity profiles and covariance data. Next the presentation touches on compute bias and bias uncertainty based on selected benchmarks using Extreme Value Theory Finally the presentation shows the additional margin for nuclear data uncertainty estimated by GLLS.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2014

A Flexible CUDA LU-based Solver for Small, Batched Linear Systems

This chapter presents the implementation of a batched CUDA solver based on LU factorization for small linear systems. This solver may be used in applications such as reactive flow transport models, which apply the Newton-Raphson technique to linearize and iteratively solve the sets of non linear equations that represent the reactions for ten of thousands to millions of physical locations. The implementation exploits somewhat counterintuitive GPGPU programming techniques: it assigns the solution of a matrix (representing a system) to a single CUDA thread, does not exploit shared memory and employs dynamic memory allocation on the GPUs. These techniques enable our implementation to simultaneously solve sets of systems with over 100 equations and to employ LU decomposition with complete pivoting, providing the higher numerical accuracy required by certain applications. Other currently available solutions for batched linear solvers are limited by size and only support partial pivoting, although they may result faster in certain conditions. We discuss the code of our implementation and present a comparison with the other implementations, discussing the various tradeoffs in terms of performance and flexibility. This work will enable developers that need batched linear solvers to choose whichever implementation is more appropriate to the features and the requirements of their applications, and even to implement dynamic switching approaches that can choose the best implementation depending on the input data.

bached linear solvers↗

DOE OSTI2015

Stochastic Control of Energy Efficient Buildings: A Semidefinite Programming Approach

The key goal in energy efficient buildings is to reduce energy consumption of Heating, Ventilation, and Air- Conditioning (HVAC) systems while maintaining a comfortable temperature and humidity in the building. This paper proposes a novel stochastic control approach for achieving joint performance and power control of HVAC. We employ a constrained Stochastic Linear Quadratic Control (cSLQC) by minimizing a quadratic cost function with a disturbance assumed to be Gaussian. The problem is formulated to minimize the expected cost subject to a linear constraint and a probabilistic constraint. By using cSLQC, the problem is reduced to a semidefinite optimization problem, where the optimal control can be computed efficiently by Semidefinite programming (SDP). Simulation results are provided to demonstrate the effectiveness and power efficiency by utilizing the proposed control approach.

Ma, Xiao↗

DOE OSTI2021

ILC: Beyond Higgs Factory

The first stage of the International Linear Collider is one of the contenders for a “Higgs factory”, as prioritised by the recent update of the European Strategy for Particle Physics. This article highlights the physics opportunities beyond its Higgs factory program, which is enabled by high luminosity, the polarised beams and the triggerless operation of the detectors, as well as the energy-extendability of the accelerator as key features of Linear Colliders.

List, Jenny↗