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All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

WE-AB-201-04: The Recommendations of MPPG #5 and Practical Implementation Strategies

Treatment planning systems (TPS) are a cornerstone of modern radiation therapy. Errors in their commissioning or use can have a devastating impact on many patients. To support safe and high quality care, medical physicists must conduct efficient and proper commissioning, good clinical integration, and ongoing quality assurance (QA) of the TPS. AAPM Task Group 53 and related publications have served as seminal benchmarks for TPS commissioning and QA over the past two decades. Over the same time, continuing innovations have made the TPS even more complex and more central to the clinical process. Medical goals are now expressed in terms of the dose and margins around organs and tissues that are delineated from multiple imaging modalities (CT, MR and PET); and even temporally resolved (i.e., 4D) imaging. This information is passed on to optimization algorithms to establish accelerator movements that are programmed directly for IMRT, VMAT and stereotactic treatments. These advances have made commissioning and QA of the TPS much more challenging. This education session reviews up-to-date experience and guidance on this subject; including the recently published AAPM Medical Physics Practice Guideline (MPPG) #5 “Commissioning and QA of Treatment Planning Dose Calculations: Megavoltage Photon and Electron Beams”. Treatment Planning System Commissioning and QA: Challenges and Opportunities (Greg Salomons) This session will provide some key background and review publications describing prominent incidents relating to TPS commissioning and QA. Traditional approaches have been hardware and feature oriented. They aim to establish a functional configuration and establish specifications for regular testing of features (like dose calculation) to assure stable operation and detect failures. With the advent of more complex systems, more patient-specific testing has also been adopted. A number of actual TPS defects will be presented along with heuristics for identifying similar defects in the future. Finally, the Gamma test has become a popular metric for reporting TPS Commissioning and QA results. It simplifies complex testing into a numerical index, but noisy data and casual application can make it misleading. A brief review of the issues around the use of the Gamma test will be presented. TPS commissioning and QA: A process orientation and application of control charts (Michael Sharpe) A framework for commissioning a treatment planning system will be presented, focusing on preparations, practical aspects of configuration, priorities, specifications, and establishing performance. The complexity of the modern TPS make modular testing of features inadequate, and modern QA tools can provide “too much information” about the performance of techniques like IMRT and VMAT. We have adopted a process orientation and quality tools, like control charts, for ongoing TPS QA and assessment of patient-specific tests. The trending nature of these tools reveals the overall performance of the TPS system, and quantifies the variations that arise from individual plans, discrete calculations, and experimentation based on discrete measurements. Examples demonstrating application of these tools to TPS QA will be presented. TPS commissioning and QA: Incorporating the entire planning process (Sasa Mutic) The TPS and its features do not perform in isolation. Instead, the features and modules are key components in a complex process that begins with CT Simulation and extends to treatment delivery, along with image guidance and verification. Most importantly, the TPS is used by people working in a multi-disciplinary environment. It is very difficult to predict the outcomes of human interactions with software. Therefore, an interdisciplinary approach to training, commissioning and QA will be presented, along with an approach to the physics chart check and end-to-end testing as a tool for TPS QA. The role of standardization and automation in QA will also be discussed. The recommendations of MPPG #5 and practical implementation strategies (Jennifer Smilowitz) The recently published recommendations from Task Group No. 244, Medical Physics Practice Guideline on Commissioning and QA of Treatment Planning Dose Calculations: Megavoltage Photon and Electron Beams will be presented. The recommendations focus on the validation of commissioning data and dose calculations. Tolerance values for non-IMRT beam configurations are summarized based on established criteria and data collected by the IROC. More stringent evaluation criteria for IMRT dose calculations are suggested to test the limitations of the TPS dose algorithms for advanced delivery conditions. The MPPG encourages users to create a suite of validation tests for dose calculation for various conditions for static photon beams, heterogeneities, IMRT/VMAT and electron beams. This test suite is intended to be used for subsequent testing, including TPS software upgrades. In the past, the recommendations of some reports have not been widely implemented due to practical limitations. Implementation strategies, tools and processes developed by multiple centers for efficient and “do-able” MPPG #5 testing will be presented, as well as a discussion on the overall validation experience. Learning Objectives: Identify some of the key documents relevant for TPS commissioning and QA Understand strategies for testing TPS software Gain a practical knowledge of the Gamma test criteria Increase familiarity with the process of commissioning a TPS Learn about the use of Control Charts for TPS QA Review the role of the TPS in the overall planning process Increase awareness of the link between TPS QA and chart checking Gain an increased appreciation for the importance of interdisciplinary communication Understand the new recommendations from MPPG #5 on TPS Dose Algorithm Commissioning and QC/QA Learn practical implementation processes and tools for MPPG #5 validation recommendations.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

MO-G-201-01: A Multi-Institutional Study Investigating the Performance of a Knowledge-Based Planning System Against Pinnacle Auto-Planning Engine in SIB-IMRT for the Head-And-Neck Cancer

Purpose: Knowledge-based Planning (KBP) founded on prior planning experience and Auto-Planning Engine (APE; commercialized in Pinnacle v9.10 TPS) based on progressive optimization algorithm both aim to eliminate the trial-and-error process in radiotherapy inverse planning. This study investigates the performance of the approaches in a multi-institutional setting to evaluate their functionalities in oropharyngeal cancer and offers suggestions how they can be implemented in the clinic. Methods: Radboud University Medical Center (RUMC) provided 35 oropharyngeal cancer patients (SIB-IMRT with two-dose-level prescription: 68 Gy to PTV68 and 50.3 Gy to PTV50.3) with corresponding comparative APE plans. Johns Hopkins University (JHU) contributed to a three-dose-level (70 Gy 63 Gy and 58.1 Gy) plan library for RUMC’s patient KBP generation. MedStar Georgetown University Hospital (MGUH) contributed to a KBP approach employing overlap-volume histogram (OVH-KBP) for generating RUMC’s patient KBP plans using JHU’s plan library. Since both approaches need their own user-defined parameters as initial inputs the first 10 patients were set aside as training set to finalize them. Meanwhile cross-institutional comparisons and adjustments were implemented for investigating institutions’ protocol discrepancies and the approaches’ user-defined parameters were updated accordingly. The finalized parameters were then applied to the remaining 25 patients for OVH-KBP and APE generation. A Wilcoxon rank-sum test was used for statistical comparison with significance level of p<0.05. Results: On average PTV68’s V95 was 96.5% in APE plans vs. 97% in OVH-KBP plans (p=0.36); PTV50.3’s V95 in APE plans was 97.8% vs.97.6% in OVH-KBP plans (p=0.6); cord’s D0.1 cc was 38.6 Gy in OVH-KBP plans vs. 43.7 Gy in APE plans (p=0.0001); mean doses to larynxes oral cavities parotids and submandibular glands were similar with p>0.2. Conclusions: The study demonstrates that KBP and APE can generate plans of comparable quality in a multi-institutional setting. Variations in clinical protocols can be effectively addressed for cross-institutional adaptations. Binbin Wu and Todd McNutt are the co-inventors of a patent associated with the proposed knowledge-based planning system which was licensed to Varian Medical Systems in 2015; This research was in part supported by Philips Radiation Oncology Systems.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2019

Designing Metabolic Division of Labor in Microbial Communities

ABSTRACT Microbes face a trade-off between being metabolically independent and relying on neighboring organisms for the supply of some essential metabolites. This balance of conflicting strategies affects microbial community structure and dynamics, with important implications for microbiome research and synthetic ecology. A “gedanken” (thought) experiment to investigate this trade-off would involve monitoring the rise of mutual dependence as the number of metabolic reactions allowed in an organism is increasingly constrained. The expectation is that below a certain number of reactions, no individual organism would be able to grow in isolation and cross-feeding partnerships and division of labor would emerge. We implemented this idealized experiment using in silico genome-scale models. In particular, we used mixed-integer linear programming to identify trade-off solutions in communities of Escherichia coli strains. The strategies that we found revealed a large space of opportunities in nuanced and nonintuitive metabolic division of labor, including, for example, splitting the tricarboxylic acid (TCA) cycle into two separate halves. The systematic computation of possible solutions in division of labor for 1-, 2-, and 3-strain consortia resulted in a rich and complex landscape. This landscape displayed a nonlinear boundary, indicating that the loss of an intracellular reaction was not necessarily compensated for by a single imported metabolite. Different regions in this landscape were associated with specific solutions and patterns of exchanged metabolites. Our approach also predicts the existence of regions in this landscape where independent bacteria are viable but are outcompeted by cross-feeding pairs, providing a possible incentive for the rise of division of labor. IMPORTANCE Understanding how microbes assemble into communities is a fundamental open issue in biology, relevant to human health, metabolic engineering, and environmental sustainability. A possible mechanism for interactions of microbes is through cross-feeding, i.e., the exchange of small molecules. These metabolic exchanges may allow different microbes to specialize in distinct tasks and evolve division of labor. To systematically explore the space of possible strategies for division of labor, we applied advanced optimization algorithms to computational models of cellular metabolism. Specifically, we searched for communities able to survive under constraints (such as a limited number of reactions) that would not be sustainable by individual species. We found that predicted consortia partition metabolic pathways in ways that would be difficult to identify manually, possibly providing a competitive advantage over individual organisms. In addition to helping understand diversity in natural microbial communities, our approach could assist in the design of synthetic consortia.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

A Nonlocal Feature-Driven Exemplar-Based Approach for Image Inpainting

Here, we present a nonlocal variational image completion technique which admits simultaneous inpainting of multiple structures and textures in a unified framework. The recovery of geometric structures is achieved by using general convolution operators as a measure of behavior within an image. These are combined with a nonlocal exemplar-based approach to exploit the self-similarity of an image in the selected feature domains and to ensure the inpainting of textures. We also introduce an anisotropic patch distance metric to allow for better control of the feature selection within an image and present a nonlocal energy functional based on this metric. Finally, we derive an optimization algorithm for the proposed variational model and examine its validity experimentally with various test images.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

A.I. for nuclear physics

Nuclear science is concerned with the understanding of the nature of matter, its basic constituents and their interaction to form the elements and the properties we observe. This includes the forms of matter we see around us and also exotic forms such as those that existed in the first moments after the Big Bang and that exist today inside neutron stars. The techniques, tools, and expertise needed for nuclear physics (NP) research are therefore diverse in nature. State-of-the art accelerators are being developed to illuminate the dynamical basis of the core of the atom in terms of the fundamental constituents called quarks and gluons and to increase the number of isotopes with known properties. This scientific infrastructure is reaching scales and complexities that require computational methods for tasks such as anomaly detection in operational data. New methodologies are needed to detect anomalies and to optimize operating parameters, predict failures as well as to discover new optimization algorithms.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2026

Reconstruction of cosmic-ray muon events with CUORE

We report the in-situ 3D reconstruction of through-going muons in the CUORE experiment, a cryogenic calorimeter array searching for neutrinoless double beta (0vββ) decay, leveraging the segmentation of the detector. Due to the slow time response of the detector, time-of-flight estimation is not feasible. Therefore, the track reconstruction is performed using a multi-objective optimization algorithm that relies on geometrical information from the detector as a whole. We measure the integral flux of cosmic-ray muons underground at the Laboratori Nazionali del Gran Sasso, and find our value to be in good agreement with other experiments that have performed a similar measurement. To our knowledge, this work represents the first demonstration of 3D particle tracking and reconstruction of through-going muons with per-event angular determination in a millikelvin cryogenic detector array. The analysis performed for this work will be critical for validating the muon-related background in CUPID, a next-generation 0vββ experiment, and for follow-up studies on detector response and on delayed products induced by cosmic-ray muons.

Adams, D. Q. [University of South Carolina]↗
DOE OSTI2018

Modeling Alzheimer’s Disease Progression with Fused Laplacian Sparse Group Lasso

Alzheimer’s disease (AD), the most common type of dementia, not only imposes a huge financial burden on the health care system, but also a psychological and emotional burden on patients and their families. There is furthermore an urgent need to infer trajectories of cognitive performance over time and identify biomarkers predictive of the progression. Here, we introduce the multi-task learning with fused Laplacian sparse group lasso model, which can identify biomarkers closely related to cognitive measures due to its sparsity-inducing property, and model the disease progression with a general weighted (undirected) dependency graphs among the tasks. An efficient alternative directions method of multipliers based optimization algorithm is derived to solve the proposed non-smooth objective formulation. The effectiveness of the presented model is demonstrated by its superior prediction performance over multiple state-of-the-art methods and accurate identification of compact sets of cognition-relevant imaging biomarkers that are consistent with prior medical studies.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Graph Contractions for Calculating Correlation Functions in Lattice QCD

Computing correlation functions for many-particle systems in Lattice QCD is vital to extract nuclear physics observables like the energy spectrum of hadrons such as protons. However, this type of calculation has long been considered to be very challenging and computing-resource intensive because of the complex nature of a hadron composed of quarks with many degrees of freedom. In particular, a correlation function can be calculated through a sum of all possible pairs of quark contractions, each of which is a batched tensor contraction, dictated by Wick's theorem. Because the number of terms of this sum can be very large for any hadronic system of interest, fast evaluation of the sum faces several challenges: an extremely large number of contractions, a huge memory footprint at runtime, and the speed of tensor contractions. In this paper, we present a Lattice QCD analysis software suite, Redstar, which addresses these challenges by utilizing novel algorithmic and software engineering methods targeting modern computing platforms such as many-core CPUs and GPUs. In particular, Redstar represents every term in the sum of a correlation function by a graph, applies efficient graph algorithms to reduce the number of contractions to lower the cost of computations, and minimizes the total memory footprint. Moreover, Redstar carries out the contractions on either CPUs or GPUs utilizing an internal and highly efficient Hadron contraction library. Specifically, we illustrate some important algorithmic optimizations of Redstar, show various key design features of Hadron library, and present the speedup values due to the optimizations along with performance figures for calculating six correlations functions on four computing platforms.

Chen, Jie↗
DOE OSTI2025

Adversarial Binaries: AI-guided Instrumentation Methods for Malware Detection Evasion

Adversarial binaries are executable files that have been altered without loss of function by an AI agent in order to deceive malware detection systems. Progress in this emergent vein of research has been constrained by the complex and rigid structure of executable files. Although prior work has demonstrated that these binaries deceive a variety of malware classification models which rely on disparate feature sets, a consensus as to the best approach has not been reached, either in terms of the optimization algorithms or the instrumentation methods. Furthermore, although inconsistencies in the data sets, target classifiers, and functionality verification methods make head-to-head comparisons difficult, here we extract lessons learned and make recommendations for future research.

malware obfuscation↗
DOE OSTI2022

Topology Optimization of 3D Flow Fields for Flow Batteries

We report as power generated from renewables becomes more readily available, the need for power-efficient energy storage devices, such as redox flow batteries, becomes critical for successful integration of renewables into the electrical grid. An important aspect of a redox flow battery is the planar flow field, which is usually composed of two-dimensional channels etched into a backing plate. As reactant-laden electrolyte flows into the flow battery, the channels in the flow field distribute the fluid throughout the reactive porous electrode. We utilize topology optimization to design flow fields with full three-dimensional geometry variation, i.e., 3D flow fields. Specifically, we focus on vanadium redox flow batteries and use the optimization algorithm to generate 3D flow fields evolved from standard interdigitated flow fields by minimizing the electrical and flow pressure power losses. To understand how these 3D designs improve performance, we analyze the polarization of the reactant concentration and exchange current within the electrode to highlight how the designed flow fields mitigate the presence of electrode dead zones. While interdigitated flow fields can be heuristically engineered to yield high performance by tuning channel and land dimensions, such a process can be laborious; this work provides a framework for automating that design process.

25 ENERGY STORAGE↗
DOE OSTI2021

Devastator Parallel Discrete Event Simulation Runtime (Devastator) v1.0

The Devastator runtime is a modern C++ implementation of optimistic parallel discrete event simulation methods. Devastator allows simulation application code to productively specify their component and event functionality with C++14 constructs. It utilizes GASNet-EX for distributed memory communication and includes parallel performance optimizations such as light-weight thread message queues and asynchronous GVT. Furthermore, it supports efficient event broadcasts and pause-rewind-resume functionality to support periodic load balancing and outer loop optimization algorithms.

Chan, Cy↗
DOE OSTI2025

O4855---Geometry_Optimizer_with_NSGA-II

It is a geometry optimizer, written for MCNP geometries but also applicable to other simulation programs. It uses NSGA-II optimization algorithm to change the specified input parameters to iteratively improve the requested tally values over generations.

Erdem, Omer↗
DOE OSTI2025

NuFast-LBL

NuFast is designed to calculate all nine neutrino oscillation probabilities in matter for long-baseline accelerator (e.g. NOvA, T2K, DUNE, HK) and reactor experiments (e.g. JUNO) very quickly, using the algorithms optimized for realistic oscillation scenarios. NuFast is provided in Fortran, C++, and Python, although no particular guarantees are made that the Python code is "fast".

Denton, PeterB. [Brookhaven National Laboratory (B↗
DOE OSTI2020

Inversion of downhole electrical measurements for proppant mapping using very fast simulated annealing

Proppant mapping is critical for optimizing fracture treatment design and improving wells’ productivity. An electrode-based resistivity tool concept was developed earlier for proppant mapping in cased-hole wells. An array of insulating gaps is installed and cemented in place as a permanent part of the casing string. The electrical measurements are performed by imposing a voltage across each insulating gap, one at a time, before and after hydraulic fracture operations. The voltages across other insulating gaps near the transmitter gap are recorded. The method relies on direct excitation of the casing, which is expected to overcome the severe limitations of induction tools in cased-hole wells. A forward model based on a finite volume method has been developed to simulate the tool’s response to one or multiple fractures. To enable the implementation of such a practical system in multistage fractured horizontal wells, a fast and robust inversion approach is required. To that end, we have developed a divide-and-conquer approach based on a global optimization algorithm very fast simulated annealing (VFSA). Specifically, the original inverse problem is divided into subproblems and each subproblem can be solved separately using VFSA. The results indicate that our approach can invert the data and output widths and radii of multiple fractures without requiring a large number of forward simulations. The robustness of the inverse solver is also tested by adding Gaussian noise to the synthetic data. We tested example cases that demonstrate that when up to 5% noise is introduced, VFSA still provides very accurate inversion results with moderate uncertainties. Inversion results with some more realistic conditions, e.g., tilted fractures, complex fractures, and so on, are also presented.

Geochemistry & Geophysics↗
DOE OSTI2019

MASK3 for Advanced WEC Dynamics and Controls

This report outlines the "MASK3" wave tank test within the Advanced WEC Dynamics and Controls (AWDC) project. This test represents the final test in the AWDC project. The focus of the MASK3 test was to consider coordinated 3-degree-of-freedom (3DOF) control of a WEC in a realistic ocean environment. A key aspect of this test was the inclusion of a "self-tuning" mechanism which uses an optimization algorithm to update controller gains based on a changing sea state. The successful implementation of the self-tuning mechanism is the last crucial step required for such a controller to be implemented in real ocean environments.

16 TIDAL AND WAVE POWER↗
DOE OSTI2016

Quantitative microstructural imaging by scanning Laue x-ray micro- and nanodiffraction

We present that local crystal structure, crystal orientation, and crystal deformation can all be probed by Laue diffraction using a submicron x-ray beam. This technique, employed at a synchrotron facility, is particularly suitable for fast mapping the mechanical and microstructural properties of inhomogeneous multiphase polycrystalline samples, as well as imperfect epitaxial films or crystals. As synchrotron Laue x-ray microdiffraction enters its 20th year of existence and new synchrotron nanoprobe facilities are being built and commissioned around the world, we take the opportunity to overview current capabilities as well as the latest technical developments. Fast data collection provided by state-of-the-art area detectors and fully automated pattern indexing algorithms optimized for speed make it possible to map large portions of a sample with fine step size and obtain quantitative images of its microstructure in near real time. Lastly, we extrapolate how the technique is anticipated to evolve in the near future and its potential emerging applications at a free-electron laser facility.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Beam-Based Diagnostics of Electric Guide Fields and Lattice Parameters for Run-1 of the Muon g-2 Storage Ring at Fermilab

A portion of the Muon g-2 Storage Ring electric system, which provides vertical beam focusing, exhibited an unexpected time dependence that produced a characteristic evolution of the stored beam during Run-1 of the Muon g-2 Experiment at Fermilab (E989). A method to reconstruct the Run-1 electric guide fields has been developed, which is based on a numerical model of the muon storage ring and optimization algorithms supported by COSY INFINITY. This method takes beam profile measurements from the Muon g-2 straw tracking detectors as input, and it produces a full reconstruction of the time-dependent fields. The fields can then be used for the reproduction of detailed beam tracking simulations and the calculation of ring lattice parameters for acceptance studies and systematic error evaluations.

43 PARTICLE ACCELERATORS↗
DOE OSTI2017

Ising Processing Units: Potential and Challenges for Discrete Optimization

The recent emergence of novel computational devices, such as adiabatic quantum computers, CMOS annealers, and optical parametric oscillators, presents new opportunities for hybrid-optimization algorithms that leverage these kinds of specialized hardware. In this work, we propose the idea of an Ising processing unit as a computational abstraction for these emerging tools. Challenges involved in using and bench- marking these devices are presented, and open-source software tools are proposed to address some of these challenges. The proposed benchmarking tools and methodology are demonstrated by conducting a baseline study of established solution methods to a D-Wave 2X adiabatic quantum computer, one example of a commercially available Ising processing unit.

97 MATHEMATICS AND COMPUTING↗