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DOE OSTI2019

A mathematical programming approach for the optimal placement of flame detectors in petrochemical facilities

Flame detectors provide an important layer of protection for personnel in petrochemical plants, but effective placement can be challenging. A mixed-integer nonlinear programming formulation is proposed for optimal placement of flame detectors while considering non-uniform probabilities of detection failure. We show that this approach allows for the placement of fire detectors using a fixed sensor budget and outperforms models that do not account for imperfect detection. In this study, we develop a linear relaxation to the formulation and an efficient solution algorithm that achieves global optimality with reasonable computational effort. We integrate this problem formulation into the Python package, Chama, and demonstrate the effectiveness of this formulation on a small test case and on two real-world case studies using the fire and gas mapping software, Kenexis Effigy.

47 OTHER INSTRUMENTATION↗

DOE OSTI2013

Singular linear-quadratic control problem for systems with linear delay

A singular linear-quadratic optimization problem on the trajectories of non-autonomous linear differential equations with linear delay is considered. The peculiarity of this problem is the fact that this problem has no solution in the class of integrable controls. To ensure the existence of solutions is required to expand the class of controls including controls with impulse components. Dynamical systems with linear delay are used to describe the motion of pantograph from the current collector with electric traction, biology, etc. It should be noted that for practical problems fact singularity criterion of quality is quite commonly occurring, and therefore the study of these problems is surely important. For the problem under discussion optimal programming control contained impulse components at the initial and final moments of time is constructed under certain assumptions on the functional and the right side of the control system.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2014

Characterization of unconventional electron fields for the treatment of mycosis fungoides using the total skin irradiation technique

Mycosis fungoides is a cutaneous lymphoma that accounts for 2–3% of all lymphomas. Several clinical studies have demonstrated the effectiveness of TSEBT (Total Skin Electron Beam Therapy) in patients with mycosis fungoides. It is important to develop this technique and make it available to a larger number of patients in Mexico. Because large fields for electron TSEBT are required in order to cover the entire body of the patient, beam characterization at conventional treatment distances is not sufficient and a calibration distance of 500cm or higher is required. Materials and methods: Calibration of radiochromic Gafchromic® EBT2 film (RCF) for electrons was performed in a solid water phantom (Scanditronix Wellhöfer) at a depth of 1.4cm and a Source Axis Distance (SAD) of 100cm. A polynomial fit was applied to the calibration curve, in order to obtain the equation relating dose response with optical density. The spatial distribution is obtained in terms of percentage of the dose, placing 3×3cm samples of RCF on the acrylic screen, which is placed in front of the patient in order to obtain maximum absorbed dose on the skin, covering an area of 200×100cm{sup 2}. The Percentage Depth Dose (PDD) curve was obtained placing RCF samples at depths of 0, 1, 1.2, 1.4, 1.5, 2, 3, 4, 5, 6, 7, 8 and 9cm in the solid water phantom, irradiated with an ELEKTA SINERGY Linear Accelerator electron beam, with an energy of 6 MeV, at a Source Skin Distance (SSD) of 500cm, with 1000MU = 100Gy, with a cone of 40×40cm and gantry angle of 90°. The RCFs were scanned on a flatbed scanner (EPSON EXPRESSION 10000 XL) and the images were processed with the ImageJ program using a region of interest (ROI) of 1×1cm{sup 2}. Results: The relative spatial dose distribution and the percentage depth dose for a SSD of 500±0.5cm, over an area of 200×100cm{sup 2} was obtained, resulting to an effective maximum dose depth (Z{sub ref}) for electrons of 1.4±0.05cm. Using the same experimental data, horizontal and vertical beam profiles were also graphed, showing a horizontal symmetry of ±035%, horizontal flatness of ±3.62%, vertical symmetry of ±2.1% and vertical flatness of ±14.2%. Conclusions: The electron beam was characterized and the data obtained were useful to determine the spatial dose distribution to a SSD of 500±0.5cm, in an area of 200×100cm{sup 2}. Dose profiles were obtained both horizontally and vertically, thus allowing to assess electron beam symmetry and flatness. PDD analysis up to a depth of 9±0.05cm, has made possible to establish the depth of electron penetration, assuring an only skin irradiation treatment.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

DOE OSTI2024

PETSc/TAO Users Manual V.3.21

This manual describes the use of the Portable, Extensible Toolkit for Scientific Computation (PETSc) and the Toolkit for Advanced Optimization (TAO) for the numerical solution of partial differential equations (PDEs) and related problems on high-performance computers. PETSc/TAO is a suite of data structures and routines that provide the building blocks for implementing large-scale application codes on parallel (and serial) computers. PETSc uses the MPI standard for all distributed memory communication. PETSc/TAO includes a large suite of parallel linear solvers, nonlinear solvers, time integrators, and optimizers that may be used in application codes written in Fortran, C, C++, and Python (via petsc4py; see Getting Started ). The library is organized hierarchically, enabling users to employ the abstraction level most appropriate for a particular problem. By using techniques of object-oriented programming, PETSc provides enormous flexibility for users.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2015

Trajectory Modulated Arc Therapy: A Fully Dynamic Delivery With Synchronized Couch and Gantry Motion Significantly Improves Dosimetric Indices Correlated With Poor Cosmesis in Accelerated Partial Breast Irradiation

Purpose: To develop planning and delivery capabilities for linear accelerator–based nonisocentric trajectory modulated arc therapy (TMAT) and to evaluate the benefit of TMAT for accelerated partial breast irradiation (APBI) with the patient in prone position. Methods and Materials: An optimization algorithm for volumetrically modulated arc therapy (VMAT) was generalized to allow for user-defined nonisocentric TMAT trajectories combining couch rotations and translations. After optimization, XML scripts were automatically generated to program and subsequently deliver the TMAT plans. For 10 breast patients in the prone position, TMAT and 6-field noncoplanar intensity modulated radiation therapy (IMRT) plans were generated under equivalent objectives and constraints. These plans were compared with regard to whole breast tissue volume receiving more than 100%, 80%, 50%, and 20% of the prescription dose. Results: For TMAT APBI, nonisocentric collision-free horizontal arcs with large angular span (251.5 ± 7.9°) were optimized and delivered with delivery time of ∼4.5 minutes. Percentage changes of whole breast tissue volume receiving more than 100%, 80%, 50%, and 20% of the prescription dose for TMAT relative to IMRT were −10.81% ± 6.91%, −27.81% ± 7.39%, −14.82% ± 9.67%, and 39.40% ± 10.53% (P≤.01). Conclusions: This is a first demonstration of end-to-end planning and delivery implementation of a fully dynamic APBI TMAT. Compared with IMRT, TMAT resulted in marked reduction of the breast tissue volume irradiated at high doses.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

DOE OSTI2016

Frame average optimization of cine-mode EPID images used for routine clinical in vivo patient dose verification of VMAT deliveries

Purpose: The in vivo 3D dose delivered to a patient during volumetric modulated arc therapy (VMAT) delivery can be calculated using electronic portal imaging device (EPID) images. These images must be acquired in cine-mode (i.e., “movie” mode) in order to capture the time-dependent delivery information. The angle subtended by each cine-mode EPID image during an arc can be changed via the frame averaging number selected within the image acquisition software. A large frame average number will decrease the EPID’s angular resolution and will result in a decrease in the accuracy of the dose information contained within each image. Alternatively, less EPID images acquired per delivery will decrease the overall 3D patient dose calculation time, which is appealing for large-scale clinical implementation. Therefore, the purpose of this study was to determine the optimal frame average value per EPID image, defined as the highest frame averaging that can be used without an appreciable loss in 3D dose reconstruction accuracy for VMAT treatments. Methods: Six different VMAT plans and six different SBRT-VMAT plans were delivered to an anthropomorphic phantom. Delivery was carried out on a Varian 2300ix model linear accelerator (Linac) equipped with an aS1000 EPID running at a frame acquisition rate of 7.5 Hz. An additional PC was set up at the Linac console area, equipped with specialized frame-grabber hardware and software packages allowing continuous acquisition of all EPID frames during delivery. Frames were averaged into “frame-averaged” EPID images using MATLAB. Each frame-averaged data set was used to calculate the in vivo dose to the patient and then compared to the single EPID frame in vivo dose calculation (the single frame calculation represents the highest possible angular resolution per EPID image). A mean percentage dose difference of low dose (<20% prescription dose) and high dose regions (>80% prescription dose) was calculated for each frame averaged scenario for each plan. The authors defined their unacceptable loss of accuracy as no more than a ±1% mean dose difference in the high dose region. Optimal frame average numbers were then determined as a function of the Linac’s average gantry speed and the dose per fraction. Results: The authors found that 9 and 11 frame averages were suitable for all VMAT and SBRT-VMAT treatments, respectively. This resulted in no more than a 1% loss to any of the dose region’s mean percentage difference when compared to the single frame reconstruction. The optimized number was dependent on the treatment’s dose per fraction and was determined to be as high as 14 for 12 Gy/fraction (fx), 15 for 8 Gy/fx, 11 for 6 Gy/fx, and 9 for 2 Gy/fx. Conclusions: The authors have determined an optimal EPID frame averaging number for multiple VMAT-type treatments. These are given as a function of the dose per fraction and average gantry speed. These optimized values are now used in the authors’ clinical, 3D, in vivo patient dosimetry program. This provides a reduction in calculation time while maintaining the authors’ required level of accuracy in the dose reconstruction.

61 RADIATION PROTECTION AND DOSIMETRY↗

DOE OSTI2019

The effect of linear regression modeling approaches on determining facility wide energy savings

Holistic energy management system business practices, such as the framework detailed in ISO 50001 – Energy management system, requirements and guidance for use , are centrally based upon the concept of energy performance improvement. For the purposes of ISO 50001, energy performance improvement can be determined for boundaries and following a process that is best suited for the implementing organization. Many organization and government ISO 50001 based programs, including the United States Department of Energy Superior Energy Performance (SEP) program, find value in demonstrating organizational energy performance improvement as the difference in energy consumption between two time periods within physically defined facility-boundaries. To make the difference in energy consumption for the two time periods meaningful, the amount of energy consumed must be adjusted to account for relevant variables. Relevant variables, such as metrics of production and weather conditions, affect directly the amount of energy consumed but are independent of the facility’s energy performance. Therefore, it is crucial to adjust the observed energy consumption by the relevant variables identified by the facility, so that the energy savings resulted from the energy performance improvement actions can be isolated and determined, which is the purpose of this program.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2017

Memory-optimized shift operator alternating direction implicit finite difference time domain method for plasma

Through introducing the alternating direction implicit (ADI) technique and the memory-optimized algorithm to the shift operator (SO) finite difference time domain (FDTD) method, the memory-optimized SO-ADI FDTD for nonmagnetized collisional plasma is proposed and the corresponding formulae of the proposed method for programming are deduced. In order to further the computational efficiency, the iteration method rather than Gauss elimination method is employed to solve the equation set in the derivation of the formulae. Complicated transformations and convolutions are avoided in the proposed method compared with the Z transforms (ZT) ADI FDTD method and the piecewise linear JE recursive convolution (PLJERC) ADI FDTD method. The numerical dispersion of the SO-ADI FDTD method with different plasma frequencies and electron collision frequencies is analyzed and the appropriate ratio of grid size to the minimum wavelength is given. The accuracy of the proposed method is validated by the reflection coefficient test on a nonmagnetized collisional plasma sheet. The testing results show that the proposed method is advantageous for improving computational efficiency and saving computer memory. The reflection coefficient of a perfect electric conductor (PEC) sheet covered by multilayer plasma and the RCS of the objects coated by plasma are calculated by the proposed method and the simulation results are analyzed.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2021

Behavioral state resource selection in invasive wild pigs in the Southeastern United States

Elucidating correlations between wild pig ( Sus scrofa ) behavior and landscape attributes can aid in the advancement of management strategies for controlling populations. Using GPS data from 49 wild pigs in the southeastern U.S., we used hidden Markov models to define movement path characteristics and assign behaviors (e.g., resting, foraging, travelling). We then explored the connection between these behaviors and resource selection for both sexes between two distinct seasons based on forage availability (i.e., low forage, high forage). Females demonstrated a crepuscular activity pattern in the high-forage season and a variable pattern in the low-forage season, while males exhibited nocturnal activity patterns across both seasons. Wild pigs selected for bottomland hardwoods and dense canopy cover in all behavioral states in both seasons. Males selected for diversity in vegetation types while foraging in the low-forage season compared to the high-forage season and demonstrated an increased use of linear anthropogenic features across seasons while traveling. Wild pigs can establish populations and home ranges in an array of landscapes, but our results demonstrate male and female pigs exhibit clear differences in movement behavior and there are key resources associated with common behaviors that can be targeted to improve the efficiency of management programs.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

Sampling-based Sublinear Low-rank Matrix Arithmetic Framework for Dequantizing Quantum Machine Learning

We present an algorithmic framework for quantum-inspired classical algorithms on close-to-low-rank matrices, generalizing the series of results started by Tang’s breakthrough quantum-inspired algorithm for recommendation systems [STOC’19]. Motivated by quantum linear algebra algorithms and the quantum singular value transformation (SVT) framework of Gilyén et al. [STOC’19], we develop classical algorithms for SVT that run in time independent of input dimension, under suitable quantum-inspired sampling assumptions. Our results give compelling evidence that in the corresponding QRAM data structure input model, quantum SVT does not yield exponential quantum speedups. Since the quantum SVT framework generalizes essentially all known techniques for quantum linear algebra, our results, combined with sampling lemmas from previous work, suffice to generalize all prior results about dequantizing quantum machine learning algorithms. In particular, our classical SVT framework recovers and often improves the dequantization results on recommendation systems, principal component analysis, supervised clustering, support vector machines, low-rank regression, and semidefinite program solving. We also give additional dequantization results on low-rank Hamiltonian simulation and discriminant analysis. Our improvements come from identifying the key feature of the quantum-inspired input model that is at the core of all prior quantum-inspired results: ℓ 2 -norm sampling can approximate matrix products in time independent of their dimension. We reduce all our main results to this fact, making our exposition concise, self-contained, and intuitive.

Computer Science↗

DOE OSTI2025

Robustness of Deep Learning Classification to Adversarial Input on GPUs: Asynchronous Parallel Accumulation Is a Source of Vulnerability

The ability of machine learning (ML) classification models to resist small, targeted input perturbations—known as adversarial attacks—is a key measure of their safety and reliability. We show that floating-point non associativity (FPNA) coupled with asynchronous parallel programming on GPUs is sufficient to result in misclassification, without any perturbation to the input. Additionally, we show that this misclassification is particularly significant for inputs close to the decision boundary and that standard adversarial robustness results may be overestimated up to 4.6 when not considering machine-level details. We first study a linear classifier, before focusing on standard Graph Neural Network (GNN) architectures and datasets used in robustness assessments. We develop a novel black-box attack using Bayesian optimization to discover external workloads that can change the instruction scheduling which bias the output of reductions on GPUs and reliably lead to misclassification. Motivated by these results, we present a new learnable permutation (LP) gradient-based approach to learning floating-point operation orderings that lead to misclassifications. The LP approach provides a worst-case estimate in a computationally efficient manner, avoiding the need to run identical experiments tens of thousands of times over a potentially large set of possible GPU states or architectures. Finally, using instrumentation-based testing, we investigate parallel reduction ordering across different GPU architectures under external background workloads, when utilizing multi-GPU virtualization, and when applying power capping. Our results demonstrate that parallel reduction ordering varies significantly across architectures under the first two conditions, substantially increasing the search space required to fully test the effects of this parallel scheduler-based vulnerability. These results and the methods developed here can help to include machine-level considerations into adversarial robustness assessments, which can make a difference in safety and mission critical applications.

Shanmugavelu, Sanjif [Maxeler Technologies, a Groq↗

DOE OSTI2018

Josephson Effect in the Micron and Submicron YBCO Constrictions Fabricated Using the Femtosecond Laser Technique

A femtosecond laser was used successfully to fabricate planar micron and submicron-sized constrictiontype Josephson junctions on YBa{sub 2}Cu{sub 3}O{sub 7−x} thin films. A simple program using G-code (control systems) programming language was written to control the movement of the sample stage during the etching process. The constriction’s geometry was investigated using both atomic force microscopy (AFM) and scanning electron microscopy (SEM). Electrical transport measurements were performed at different temperatures. Shapiro steps were observed and analyzed. The micron-sized constriction shows a linear relationship for the measured critical current against the temperature which is consistent with the behavior of an S–s’–Stype Josephson junction where “S” stands for a bulk superconductive material that is untouched by the laser and “s”’ is superconducting material whose critical temperature is lower than the value of “S” In the case of the narrower submicronsized constriction, the measured critical current dependence with temperature shows an exponential decay, which is consistent with the behavior of the long S–N–Stype Josephson junction where “N” stands for a normal material. A model is proposed to describe the observed behavior by considering the effect of sample heating during the constriction’s fabrication.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2018

Heterogeneity in Warm‐Season Land‐Atmosphere Coupling Over the U.S. Southern Great Plains

Abstract Heterogeneity in warm‐season (May–August) land‐atmosphere (LA) coupling is quantified with the long‐time, multiple‐station measurements from the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) program and the Moderate Resolution Imaging Spectroradiometer satellite remote sensing at the Southern Great Plains (SGP). We examine the coupling strength at seven additional locations with the same surface type (i.e., pasture/grassland) as the ARM SGP central facility (CF). To simultaneously consider multiple factors and consistently quantify their relative contributions, we apply a multiple linear regression method to correlate the surface evaporative fraction (EF) with near‐surface soil moisture (SM) and leaf area index (LAI). The observations show moderate to weak terrestrial segment LA coupling with large heterogeneity across the ARM SGP domain in warm season. Large spatial variabilities in the contributions from SM and LAI to the EF changes are also found. The coupling heterogeneities appear to be associated with differences in land use, anthropogenic activities, rooting depth, and soil type at different stations. Therefore, the complex LA interactions at the SGP cannot be well represented by those at the CF/E13 based on the metrics applied here. Overall, the LAI exerts more influence on the EF than does the SM due to its overwhelming impacts on the latent heat flux. This study complements previous studies based on measurements only from the CF and has important implications for modeling LA coupling in weather and climate models. The multiple linear regression provides a more comprehensive measure of the integrated impacts on LA coupling from several different factors.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Advanced Shuttle Strategies for Parallel QCCD Architectures

Trapped ions (TIs) are at the forefront of quantum computing implementation, offering unparalleled coherence, fidelity, and connectivity. However, the scalability of TI systems is hampered by the limited capacity of individual ion traps, necessitating intricate ion shuttling for advanced computational tasks. The quantum charge-coupled device (QCCD) framework has emerged as a promising solution, facilitating ion mobility for universal quantum computation. Current QCCD architectures predominantly feature a linear topology, which is increasingly recognized as inefficient for complex quantum operations. Anticipating the shift toward more efficacious designs, this article introduces an innovative quantum scheduling strategy optimized for parallel QCCD topologies. Our strategy proposes a probabilistic formula for ion movement, alongside ingenious methods for local layer generation and layer compression, yielding a significant reduction in ion shuttle times. Through simulations, we demonstrate that our strategy not only substantially outstrips the linear model but also exhibits better performance over other parallel strategies that employ greedy algorithms. This is achieved through our nuanced resolution of complexities, such as traffic blocks and trap capacity limitations. The consequent reduction in shuttle operations leads to lower energy consumption and an enhancement in the quantum computer's fidelity, ultimately accelerating program execution times.

43 PARTICLE ACCELERATORS↗

DOE OSTI2014

SU-E-CAMPUS-J-03: Commissioning of the On-Board Cone-Beam CT System Equipped On the Rotating Gantry of a Proton Therapy System

Purpose: Proton therapy requires highly-precise image guidance in patient setup to ensure accurate dose delivery. Cone-beam CT (CBCT) is expected to play an important role to reduce uncertainties in patient setup. Hokkaido University has developed a new proton therapy system dedicated to spot-scanning under a collaborative work with Hitachi Ltd. In our system, an orthogonal X-ray imaging system is mounted on a full-rotating gantry. On-board CBCT imaging is therefore available. We have conducted commissioning of the CBCT system for clinical use in proton therapy. Methods: The orthogonal X-ray imaging system, which consists of two sets of X-ray tubes and flat panel detectors (FPDs), are equipped on the rotating gantry. The FPDs are mounted on the proton beam nozzle and can be retracted when not in use. The distance between the X-ray source and the FPD is about 2.1 m. The maximum rotation speed of the gantry is 1 rpm, so CBCT images can be acquired in approximately 1 minute. The maximum reconstruction volume is nearly 40 cm in diameter and 20 cm in axial length. For commissioning of the CBCT system, mechanical accuracy of the rotating gantry first was evaluated. Imaging performance was examined via quantitative evaluation of image quality. Results: Through the mechanical test, the isocentricity of the gantry was confirmed to be less than 1 mm. Moreover, it was improved to 0.5 mm with an appropriate correction. The accurate rotation of the gantry contributes to the CBCT image quality. In the image quality test, objects with 7 line-pairs per cm, which corresponds to a line spacing of 0.071 cm, could be discerned. Spatial linearity and uniformity were also sufficient. Conclusion: Clinical commissioning of the on-board CBCT system for proton therapy was conducted, and CBCT images with sufficient quality were successfully obtained. This research was supported by the Cabinet Office, Government of Japan and the Japan Society for the Promotion of Science (JSPS) through the Funding Program for World-Leading Innovative R and D on Science and Technology (FIRST Program), initiated by the Council for Science and Technology Policy (CSTP)

07 ISOTOPE AND RADIATION SOURCES↗

DOE OSTI2023

Protecting Customer Privacy Through Distributed Energy Resource Anonymization

Due to their stochastic nature, the increase of Renewable Energy Resources (RERs) as a primary source of energy for power grids creates challenges regarding the reliability and resilience of the system. In order to combat these obstacles, expansion of Distributed Energy Resources (DERs) and their participation in Demand Response (DR) programs is necessary. Widespread participation requires prioritizing customer privacy and addressing concerns that may arise regarding communication between DERs and the Grid Service Provider (GSP). This paper discusses the use of flow reservation resources to split the operating cycles of DER load profiles into unique phases. The splitting of phases increases anonymization of the DERs by making it more difficult to determine the individual characteristics of the device. We discuss an example of this using simulated DER load profile data and examine the resulting effectiveness by using a machine learning algorithm for classification, called Support Vector Machine (SVM).

Distributed Energy Resource, Anonymization, Renewa↗

DOE OSTI2018

ButterflyPACK

ButterflyPACK is a mathematical software for rapidly solving large-scale dense linear systems that exhibit off-diagonal rank-deficiency properties. These targeted systems are either matrices arising from discretized boundary integral equations, or frontal matrices in multi-frontal solvers for differential equations. ButterflyPACK relies on low-rank and butterfly formats under Hierarchical matrix, HODLR or HSS frameworks to compress, factor/precondition and solve the linear system in quasi-linear time. ButterflyPACK is particularly useful for large-scale ill-conditioned matrices arising from high-frequency wave equations involving multiple right-hand-sides. ButterflyPACK is based on Fortran 2003, it also has interface written in C++. In addition, ButterflyPACK can be readily invoked from the software STRUMPACK. ButterflyPACK supports hybrid MPI/OpenMP programming models.

Liu, Yang↗

DOE OSTI2024

Low-Alpha Operation of the IOTA Storage Ring

Operation with ultra-low momentum-compaction factor (alpha) is a desirable capability for many storage rings and synchrotron radiation sources. For example, low-alpha lattices are commonly used to produce picosecond bunches for the generation of coherent THz radiation and are the basis of a number of conceptual designs for EUV generation via steady-state microbunching (SSMB). Achieving ultra-low alpha requires not only a high-level of stability in the linear optics but also flexible control of higher-order compaction terms. Operation with lower momentum-compaction lattices has recently been investigated at the IOTA storage ring at Fermilab. Experimental results from some initial feasibility studies will be discussed in the context of ensuring an improved understanding of the IOTA optics for future research programs.

43 PARTICLE ACCELERATORS↗