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DOE OSTI2019

Stochastic self-tuning hybrid algorithm for reaction-diffusion systems

Many biochemical phenomena involve reactants with vastly different concentrations, some of which are amenable to continuum-level descriptions, while the others are not. We present a hybrid self-tuning algorithm to model such systems. The method combines microscopic (Brownian) dynamics for diffusion with mesoscopic (Gillespie-type) methods for reactions and remains efficient in a wide range of regimes and scenarios with large variations of concentrations. Furthermore, its accuracy, robustness, and versatility are balanced by redefining propensities and optimizing the mesh size and time step. We use a bimolecular reaction to demonstrate the potential of our method in a broad spectrum of scenarios: from almost completely reaction-dominated systems to cases where reactions rarely occur or take place very slowly. The simulation results show that the number of particles present in the system does not degrade the performance of our method. This makes it an accurate and computationally efficient tool to model complex multireaction systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2014

WE-G-BRD-03: Development of a Real-Time Optical Tracking Goggle System (OTGS) for Intracranial Stereotactic Radiotherapy

Purpose: Optical tracking systems (OTS) are an acceptable alternative to frame-based stereotactic radiotherapy (SRT). However, current surface-based OTS lack the ability to target exclusively rigid/bony anatomical features. We propose a novel marker-based optical tracking goggle system (OTGS) that provides real-time guidance based on the nose/facial bony anatomy. This ongoing study involves the development and characterization of the OTGS for clinical implementation in intracranial stereotactic radiotherapy. Methods: The OTGS consists of eye goggles, a custom thermoplastic nosepiece, and 6 infrared markers pre-attached to the goggles. A phantom and four healthy volunteers were used to evaluate the calibration/registration accuracy, intrafraction accuracy, interfraction reproducibility, and end-to-end accuracy of the OTGS. The performance of the OTGS was compared with that of the frameless SonArray system and cone-beam computed tomography (CBCT) for volunteer and phantom cases, respectively. The performance of the OTGS with commercial immobilization devices and under treatment conditions (i.e., couch rotation and translation range) was also evaluated. Results: The difference in the calibration/registration accuracy of 24 translations or rotation combinations between CBCT and in-house OTS software was within 0.5 mm/0.4°. The mean intrafraction and interfraction accuracy among the volunteers was 0.004+/−0.4mm with −0.09+/−0.5° (n=6,170) and −0.26+/−0.8mm with 0.15+/0.8° (n=11), respectively. The difference in end-to-end accuracy between the OTGS and CBCT was within 1.3 mm/1.1°. The predetermined marker pattern (1) minimized marker occlusions, (2) allowed for continuous tracking for couch angles +/− 90°, (3) and eliminated individual marker misplacement. The device was feasible with open and half masks for immobilization. Conclusion: Bony anatomical localization eliminated potential errors due to facial hair changes and/or soft tissue deformation. The OTGS offers a workflow-friendly, patient-friendly solution for intracranial SRT, while being comparable to other real-time options. The minimum rotation uncertainty of the OTGS can be combined with CBCT to ensure maximum accuracy for high-precision SRT.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2014

Cross-Layer Self-Adaptive/Self-Aware System Software for Exascale Systems

The extreme level of parallelism coupled with the limited available power budget expected in the exascale era brings unprecedented challenges that demand optimization of performance, power and resiliency in unison. Scalability on such systems is of paramount importance, while power and reliability issues may change the execution environment in which a parallel application runs. To solve these challenges exascale systems will require an introspective system software that combines system and application observations across all system stack layers with online feedback and adaptation mechanisms. In this paper we propose the design of a novel self-aware, self-adaptive system software in which a kernel-level Monitor, which continuously inspects the evolution of the target system through observation of Sensors, is combined with a user-level Controller, which reacts to changes in the execution environment, explores opportunities to increase performance, save power and adapts applications to new execution scenarios. We show that the monitoring system accurately monitors the evolution of parallel applications with a runtime overhead below 1-2%. As a test case, we design and implement a user-runtime system that aims at optimizing application’s performance and system power consumption on complex hierarchical architectures. Our results show that our adaptive system reaches 98% of performance efficiency of manually-tuned applications.

High Performance computing, Self-aware/self-adapti↗

DOE OSTI2016

SU-F-J-47: Inherent Uncertainty in the Positional Shifts Determined by a Volumetric Cone Beam Imaging System

Purpose: To quantify inherent uncertainty associated with a volumetric imaging system in its determination of positional shifts. Methods: The study was performed on an Elekta Axesse™ linac’s XVI cone beam computed tomography (CBCT) system. A CT image data set of a Penta- Guide phantom was used as reference image by placing isocenter at the center of the phantom.The phantom was placed arbitrarily on the couch close to isocenter and CBCT images were obtained. The CBCT dataset was matched with the reference image using XVI software and the shifts were determined in 6-dimensions. Without moving the phantom, this process was repeated 20 times consecutively within 30 minutes on a single day. Mean shifts and their standard deviations in all 6-dimensions were determined for all the 20 instances of imaging. For any given day, the first set of shifts obtained was kept as reference and the deviations of the subsequent 19 sets from the reference set were scored. Mean differences and their standard deviations were determined. In this way, data were obtained for 30 consecutive working days. Results: Tabulating the mean deviations and their standard deviations observed on each day for the 30 measurement days, systematic and random errors in the determination of shifts by XVI software were calculated. The systematic errors were found to be 0.03, 0.04 and 0.03 mm while random errors were 0.05, 0.06 and 0.06 mm in lateral, craniocaudal and anterio-posterior directions respectively. For rotational shifts, the systematic errors were 0.02°, 0.03° and 0.03° and random errors were 0.06°, 0.05° and 0.05° in pitch, roll and yaw directions respectively. Conclusion: The inherent uncertainties in every image guidance system should be assessed and baseline values established at the time of its commissioning. These shall be periodically tested as part of the QA protocol.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2024

Quantum computing for nuclear physics

Future quantum computers are anticipated to be able to perform simulations of quantum many-body systems and quantum field theories that lie beyond the capabilities of classical computation. This will lead to new insights and predictions for systems ranging from dense non-equilibrium matter, to low-energy nuclear structure and reactions, to high-energy collisions. I present an overview of digital quantum simulations in nuclear physics, with select examples relevant for studies of quark matter.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2019

High-Fidelity Calibration and Characterization of Hyperspectral Computed Tomography System

This document archives the results developed by the Lab Directed Research and Development (LDRD) project sponsored by Sandia National Laboratories (SNL). In this work, a numerical study was performed to show the feasibility of approximating the non-linear operator of SNL's unique high-energy hyperspectral computed tomography system as a sequence of linear operators. The four main results gained from this work include the development of a simulation test-bed using a particle-transport Monte Carlo approach; the demonstration to assemble a linear operator of almost-arbitrary resolution for a given narrow energy window, developing a compression approach to dramatically reduce the size of the linear operator via a spline approach, and the demonstration of using the linear operator to perform processing of x-ray data; in this case, the development of an iterative reconstruction method. This numerical study has indicated that if these results can be replicated on the SNL system, the improved performance could be revolutionary as the method to approximate the nonlinear operator for a hyperspectral CT system is not feasible to perform on a traditional CT system.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2019

SimCCS: An open-source tool for optimizing CO 2 capture, transport, and storage infrastructure

Commercial-scale carbon capture and storage (CCS) technology will involve deploying infrastructure on a massive and costly scale. This effort will require careful and comprehensive planning to ensure that capture locations, storage sites, and the dedicated CO 2 distribution pipelines are selected in a robust and cost-effective manner. Presented in 2009, SimCCS is an optimization model for integrated system design that enables researchers, stakeholders, and policy makers to design CCS infrastructure networks. SimCCS 2.0 is a complete, ground-up redesign that is now a portable software package, useable and shareable by the CCS research, industrial, policy, and public communities. SimCCS 2.0 integrates multiple new capabilities including a refined optimization model, novel candidate network generation techniques, and optional integration with high-performance computing platforms. Accessing user-provided CO 2 source, sink, and transportation data, SimCCS 2.0 creates candidate transportation routes and formalizes an optimization problem that determines the most cost-effective CCS system design. This optimization problem is further solved either through a high-performance computing interface, or through third-party software on a local desktop computing platform. Finally, SimCCS 2.0 employs an open-access geographic information system framework to enable analysis and visualization capabilities. SimCCS 2.0 is written in Java and is publicly available via GitHub to encourage collaboration, modification, and community development.

42 ENGINEERING↗

DOE OSTI2025

Verification of the PERSENT Software

Ongoing commercial design activities require a thorough verification of the Argonne Reactor Computation codes be performed. DIF3D is central to this system and substantial work has been done to verify its accuracy on several identified commercial needs. This manuscript details the verification work done on PERSENT which relies upon the DIF3D code for its forward and adjoint flux solution. Previous work identified the PERSENT features required to be verified to support commercial design activities, features of which are generally applicable to hexagonal-Z fast reactor designs. The scope of this verification effort includes verifying PERSENT’s ability to correctly calculate four key quantities: perturbation worth distributions, kinetics parameters, sensitivity coefficients, and cross section uncertainty quantification. This manuscript provides the verification tasks and their results with respect to these quantities needed for commercial design activities. For the perturbation worth distributions, hand calculations are deployed to verify the PERSENT calculated results. Similarly, hand calculation of the PERSENT computed kinetics parameters is also used to verify the PERSENT results. In both of these, the input to PERSENT is manipulated to ensure the hand calculation exactly matches the equations PERSENT is calculating. The sensitivity coefficients involve calculating the derivatives of a parameter (such as reactivity worth), with respect to the cross section data. Direct finite difference calculations with DIF3D are used to verify the PERSENT calculated results. For the uncertainty quantification, manufactured input to PERSENT is used to allow an exact hand calculation to reproduce the PERSENT calculated results. The work detailed in this report verified that significant issues were identified for earlier versions of PERSENT for sensitivity coefficients which were corrected in this work and thus version 12.1.0 of PERSENT must be used to reproduce all of the verified work in this report.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2014

Onboard functional and molecular imaging: A design investigation for robotic multipinhole SPECT

Purpose: Onboard imaging—currently performed primarily by x-ray transmission modalities—is essential in modern radiation therapy. As radiation therapy moves toward personalized medicine, molecular imaging, which views individual gene expression, may also be important onboard. Nuclear medicine methods, such as single photon emission computed tomography (SPECT), are premier modalities for molecular imaging. The purpose of this study is to investigate a robotic multipinhole approach to onboard SPECT. Methods: Computer-aided design (CAD) studies were performed to assess the feasibility of maneuvering a robotic SPECT system about a patient in position for radiation therapy. In order to obtain fast, high-quality SPECT images, a 49-pinhole SPECT camera was designed which provides high sensitivity to photons emitted from an imaging region of interest. This multipinhole system was investigated by computer-simulation studies. Seventeen hot spots 10 and 7 mm in diameter were placed in the breast region of a supine female phantom. Hot spot activity concentration was six times that of background. For the 49-pinhole camera and a reference, more conventional, broad field-of-view (FOV) SPECT system, projection data were computer simulated for 4-min scans and SPECT images were reconstructed. Hot-spot localization was evaluated using a nonprewhitening forced-choice numerical observer. Results: The CAD simulation studies found that robots could maneuver SPECT cameras about patients in position for radiation therapy. In the imaging studies, most hot spots were apparent in the 49-pinhole images. Average localization errors for 10-mm- and 7-mm-diameter hot spots were 0.4 and 1.7 mm, respectively, for the 49-pinhole system, and 3.1 and 5.7 mm, respectively, for the reference broad-FOV system. Conclusions: A robot could maneuver a multipinhole SPECT system about a patient in position for radiation therapy. The system could provide onboard functional and molecular imaging with 4-min scan times.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

DOE OSTI2013

Network support for system initiated checkpoints

A system, method and computer program product for supporting system initiated checkpoints in parallel computing systems. The system and method generates selective control signals to perform checkpointing of system related data in presence of messaging activity associated with a user application running at the node. The checkpointing is initiated by the system such that checkpoint data of a plurality of network nodes may be obtained even in the presence of user applications running on highly parallel computers that include ongoing user messaging activity.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2014

Network support for system initiated checkpoints

Chen, Dong↗

DOE OSTI2020

An empirical study of I/O separation for burst buffers in HPC systems

To meet the exascale I/O requirements for the High-Performance Computing (HPC), a new I/O subsystem, Burst Buffer, based on solid state drives (SSD), has been developed. However, the diverse HPC workloads and the bursty I/O pattern cause severe data fragmentation that requires costly garbage collection (GC) and increases the number of bytes written to the SSD. To address this data fragmentation challenge, a new multi-stream feature has been developed for SSDs. In this work, we develop an I/O Separation scheme called BIOS to leverage this multi-stream feature to group the I/O streams based on the user IDs. We propose a stream-aware scheduling policy based on burst buffer pools in the workload manager, and integrate the BIOS with the workload manager to optimize the I/O separation scheme in burst buffer. We evaluate the proposed framework with a burst buffer I/O traces from Cori Supercomputer including a diverse set of applications. Experimental results show that the BIOS could improve the performance by 1.44x on average and reduce the Write Amplification Factor (WAF) by up to 1.20x. Finally, these demonstrate the potential benefits of the I/O separation scheme for solid state storage systems.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2022

Development and Commercialization of an IDAES-Based Power Plant Performance Monitoring and Optimization System

DOE and NETL have created an advanced, open-source computational platform through the Institute for the Design of Advanced Energy Systems (IDAES). The IDAES platform is a very extensive modeling environment that can be used for a broad range of power plant and process applications. MapEx Software is developing and commercializing a software application that makes it easier to set-up and run IDAES-based analyses. The MapEx-developed software application will replace the need for custom Python language coding with a user-friendly graphical user interface where the user can construct a flowsheet diagram of the IDAES model by inserting icons representing the plant equipment onto the screen. This application will make the implementation of modeling and optimization of existing fossil-fired power plants more straight-forward and less time-consuming. The effort focuses on performance monitoring and optimization of plant operations for the existing coal-fired power plant fleet but is built on a structure that allows expansion into the broad range of applications where IDAES methods may be applied.

20 FOSSIL-FUELED POWER PLANTS↗

DOE OSTI2017

Clinical benefits of new immobilization system for hypofractionated radiotherapy of intrahepatic hepatocellular carcinoma by helical tomotherapy

Objective: A comprehensive clinical evaluation was conducted, assessing the Body Pro-Lok immobilization and positioning system to facilitate hypofractionated radiotherapy of intrahepatic hepatocellular carcinoma (HCC), using helical tomotherapy to improve treatment precision. Methods: Clinical applications of the Body Pro-Lok system were investigated (as above) in terms of interfractional and intrafractional setup errors and compressive abdominal breath control. To assess interfractional setup errors, a total of 42 patients who were given 5 to 20 fractions of helical tomotherapy for intrahepatic HCC were analyzed. Overall, 15 patients were immobilized using simple vacuum cushion (group A), and the Body Pro-Lok system was used in 27 patients (group B), performing megavoltage computed tomography (MVCT) scans 196 times and 435 times, respectively. Pretreatment MVCT scans were registered to the planning kilovoltage computed tomography (KVCT) for error determination, and group comparisons were made. To establish intrafractional setup errors, 17 patients with intrahepatic HCC were selected at random for immobilization by Body Pro-Lok system, undergoing MVCT scans after helical tomotherapy every week. A total of 46 MVCT re-scans were analyzed for this purpose. In researching breath control, 12 patients, randomly selected, were immobilized by Body Pro-Lok system and subjected to 2-phase 4-dimensional CT (4DCT) scans, with compressive abdominal control or in freely breathing states, respectively. Respiratory-induced liver motion was then compared. Results: Mean interfractional setup errors were as follows: (1) group A: X, 2.97 ± 2.47 mm; Y, 4.85 ± 4.04 mm; and Z, 3.77 ± 3.21 mm; pitch, 0.66 ± 0.62°; roll, 1.09 ± 1.06°; and yaw, 0.85 ± 0.82°; and (2) group B: X, 2.23 ± 1.79 mm; Y, 4.10 ± 3.36 mm; and Z, 1.67 ± 1.91 mm; pitch, 0.45 ± 0.38°; roll, 0.77 ± 0.63°; and yaw, 0.52 ± 0.49°. Between-group differences were statistically significant in 6 directions (p < 0.05). Mean intrafractional setup errors with use of the Body Pro-Lok system were as follows: X, 0.41 ± 0.46 mm; Y, 0.86 ± 0.80 mm; Z, 0.33 ± 0.44 mm; and roll, 0.12 ± 0.19°. Mean liver-induced respiratory motion determinations were as follows: (1) abdominal compression: X, 2.33 ± 1.22 mm; Y, 5.11 ± 2.05 mm; Z, 2.13 ± 1.05 mm; and 3D vector, 6.22 ± 1.94 mm; and (2) free breathing: X, 3.48 ± 1.14 mm; Y, 9.83 ± 3.00 mm; Z, 3.38 ± 1.59 mm; and 3D vector, 11.07 ± 3.16 mm. Between-group differences were statistically different in 4 directions (p < 0.05). Conclusions: The Body Pro-Lok system is capable of improving interfractional and intrafractional setup accuracy and minimizing tumor movement owing to respirations in patients with intrahepatic HCC during hypofractionated helical tomotherapy.

61 RADIATION PROTECTION AND DOSIMETRY↗

DOE OSTI2020

Predictive Modeling and Diagnostic Monitoring of Extreme Science Workflows (Final Report)

This proposal addresses a critical issue of performance prediction identified in the report from the ASCR \Computational Modeling of Big Networks (COMBINE)" workshop: "end-to-end performance is not predictable due to a variety of factors. Even when some performance forecasts or predictions can be made, they often cannot explain the reasons why some predictions fail." We will develop new analytical models to predict the end-to-end performance of scientific workflows on DOE computing infrastructures, and use simulations and experimentation to validate and refine these models, as well as to pinpoint the sources of model inaccuracy. We will also use these models to help diagnose application and infrastructure problems, and to adapt the system based on this diagnosis. This section provides background in the areas relevant to the proposed work. RPI’s specific tasks within the Panorama project are as follows: (1) Develop Aspen-Simulation interface for Workflow Model Driven Simulation. (2) Validate manual performance models of two target workflow scenarios with empirical measurement and simulation. (3) Extend ROSS-Aspen API to simulate workflow descriptions when required. (4) Validate Aspen performance models of two target workflow scenarios with automatic performance model empirical measurement and simulation. (5) Design and implement final system to automatically generate Aspen performance models from workflow descriptions (including methods to compensate for limitations of Aspen analytical models). (6) Validate improved Aspen performance models with target workflow on production infrastructure. To date, all the project milestones assigned to us where reached within the best of our abilities over the course of the project performance period. Below describes the key outcome from our collaborative research in a system named, Durango .

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2023

Incorporation of aerosol into the COSPv2 satellite lidar simulator for climate model evaluation

Abstract. Atmospheric aerosol has substantial impacts on climate, air quality and biogeochemical cycles, and its concentrations are highly variable in space and time. A key variability to evaluate within models that simulate aerosol is the vertical distribution, which influences atmospheric heating profiles and aerosol–cloud interactions, to help constrain aerosol residence time and to better represent the magnitude of simulated impacts. To ensure a consistent comparison between modeled and observed vertical distribution of aerosol, we implemented an aerosol lidar simulator within the Cloud Feedback Model Intercomparison Project (CFMIP) Observation Simulator Package version 2 (COSPv2). We assessed the attenuated total backscattered (ATB) signal and the backscatter ratios (SRs) at 532 nm in the U.S. Department of Energy's Energy Exascale Earth System Model version 1 (E3SMv1). The simulator performs the computations at the same vertical resolution as the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP), making use of aerosol optics from the E3SMv1 model as inputs and assuming that aerosol is uniformly distributed horizontally within each model grid box. The simulator applies a cloud masking and an aerosol detection threshold to obtain the ATB and SR profiles that would be observed above clouds by CALIOP with its aerosol detection capability. Our analysis shows that the aerosol distribution simulated at a seasonal timescale is generally in good agreement with observations. Over the Southern Ocean, however, the model does not produce the SR maximum as observed in the real world. Comparison between clear-sky and all-sky SRs shows little differences, indicating that the cloud screening by potentially incorrect model clouds does not affect the mean aerosol signal averaged over a season. This indicates that the differences between observed and simulated SR values are due not to sampling errors, but to deficiencies in the representation of aerosol in models. Finally, we highlight the need for future applications of lidar observations at multiple wavelengths to provide insights into aerosol properties and distribution and their representation in Earth system models.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

HPC at NREL: FY 2019

Brochure featuring Fiscal Year 2019 accomplishments at the NREL High-Performance Computing User Facility and Data Center at the Energy Systems Integration Facility, including information on the facility's HPC systems as well as highlights from several modeling and simulation projects across the spectrum of energy efficiency and renewable energy technologies.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2023

Comparison of machine learning systems trained to detect Alfvén eigenmodes using the CO 2 interferometer on DIII-D

Abstract A Machine-Learning (ML) based detection scheme that automatically detects Alfvén Eigenmodes (AE) in a labelled DIII-D database is presented here. Controlling AEs is important for the success of planned burning plasma devices such as ITER, since resonant fast ions can drive AEs unstable and degrade the performance of the plasma or damage the first walls of the machine vessel. Artificial Intelligence could be useful for real-time detection and control of AEs in steady-state plasma scenarios by implementing ML-based models into control algorithms that drive actuators for mitigation of AE impacts. Thus, the objective is to compare differences in performance between using two different recurrent neural network systems (Reservoir Computing Network and Long Short Term Memory Network) and two different representations of the C O 2 phase data (simple and crosspower spectrograms). All C O 2 interferometer chords are used to train both models, but only one is processed during each training step. The results from the model and data comparison show higher performance for the RCN model (True Positive Rate = 90% and False Positive Rate = 14%), and that using simple magnitude spectrograms is sufficient to detect AEs. Also, the vertical C O 2 interferometer chord passing near the center is better for ML-based detection of AEs.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗