Results for “LINEAR PROGRAMMING” — Page 59

DOE OSTI2019

Modeling the Performance and Cost of Lithium-Ion Batteries for Electric-Drive Vehicles, Third Edition

This Manual details the Battery Performance and Cost model (BatPaC) developed at Argonne National Laboratory for lithium-ion battery packs used in automotive transportation. The model designs the battery for a specified power, energy, and type of vehicle battery. The cost of the designed battery is then calculated by accounting for every step in the lithium-ion battery manufacturing process. The assumed annual production level directly affects each process step. The total price to vehicle manufacturers calculated by the model represent both our estimates for the present-day costs and projected costs for up to ten years in the future, depending upon the designated scale of production. BatPaC assumes that future plants with production volumes of up to 500,000 EV batteries per year would be highly automated resulting in lower capital equipment and labor costs per unit produced than present day plants that have lower production volumes. All costs are calculated in US$ for the year of the estimate with all input costs for that same year. BatPaC is the only publicly available model of which we are aware that performs a bottom-up lithium-ion battery design and cost calculation. The original model and Manual were publicly peer-reviewed by battery experts assembled by the U.S. Environmental Protection Agency. This revised model and Manual include changes made in response to the comments received from the users; most of the changes were made over a number of years and are summarized here. The purpose of the report is to document the equations and assumptions from which the model has been created. A user of the model will be able to recreate the calculations and perhaps more importantly, understand the driving forces for the results. Instructions for use and illustrations of the model results are also presented. Almost every variable in the calculation may be changed by the user to represent a system different from the default values pre-entered into the program. The distinct advantage of using a bottom-up cost and design model is that the entire power-to-energy space may be traversed to examine the correlation between performance and cost. The BatPaC model accounts for the physical limitations of the electrochemical processes within the battery. Thus, unrealistic designs are penalized in energy density and cost, unlike cost models based on linear extrapolations. Additionally, the consequences on cost and energy density from changes in cell capacity, parallel cell groups, and manufacturing capabilities are easily assessed with the model. New proposed materials may also be examined to translate bench-scale values to the design of full-scale battery packs providing realistic energy densities and prices to the original equipment manufacturer.

25 ENERGY STORAGE↗

DOE OSTI2016

TH-C-BRC-01: An Overview of Emerging Technologies in SRS/SBRT Delivery

The delivery techniques for SRS/SBRT have been under rapid developments in recent years, which pose new challenges to medical physicists ranging from planning and quality assurance to imaging and motion management. This educational course will provide a general overview of the latest delivery techniques in SRS/SBRT, and discuss the clinical processes to address the challenges of each technique with special emphasis on dedicated gamma-ray based device, robotic x-band linac-based system and conventional C-arm s-band linac-based SRS systems. (1). Gamma-ray based SRS/SRT: This is the gold standard of intracranial SRS. With the advent of precision imaging guidance and frameless patient positioning capabilities, novel stereoscopic CBCT and automatic dose adaption solution are introduced to the Gamma-ray based SRS for the first time. The first North American system has been approved by the US regulatory for patient treatments in the spring of 2016. (2). Robotic SRS/SBRT system: A number of technological milestones have been developed in the past few years, including variable aperture collimator, sequential optimization technique, and the time reduction technique. Recently, a new robotic model allows the option of a multi-leaf collimator. These technological advances have reduced the treatment time and improved dose conformity significantly and could potentially expand the application of radiosurgery for the treatment of targets not previously suitable for robotic SRS/SBRT or fractionated stereotactic radiotherapy. These technological advances have created new demanding mandates on hardware and patient quality assurance (QA) tasks, as well as the need for updating/educating the physicists in the community on these requirements. (3). Conventional Linac based treatments: Modulated arc therapy (MAT) has gained wide popularities in Linac-based treatments in recent years due to its high delivery efficiency and excellent dose conformities. Recently, MAT has been introduced to deliver highly conformal radiosurgery treatments to multiple targets simultaneously via a single isocenter to replace the conventional multi-iso multi-plan treatments. It becomes important to understand the advantages and limitations of this technique, and the pitfalls for implementing this technique in clinical practice. The planning process of single-iso multi-target MAT will be described, and its plan quality and delivery efficiency will be compared with multi-iso plans. The QA process for verifying such complex plans will be illustrated, and pitfalls in imaging and patient set up will be discussed. Overall, this session will focus on the following areas: 1) Update on the emerging technology in current SRS/SBRT delivery. 2) New developments in treatment planning and Quality Assurance program. 3) Imaging guidance and motion management. Learning Objectives: To understand the SRS/SBRT principles and its clinical applications, and gain knowledge on the emerging technologies in SRS/SBRT. To review planning concepts and useful tips in treatment planning. To learn about the imaging guidance procedures and the quality assurance program in SRS/SBRT. National Institutes of Health, Varian Medical System; L. Ren, The presenter is funded by National Institutes of Health and Varian Medical System.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

TH-C-BRC-02: A Review of Emerging Technologies in Robotic SRS/SBRT Delivery

The delivery techniques for SRS/SBRT have been under rapid developments in recent years, which pose new challenges to medical physicists ranging from planning and quality assurance to imaging and motion management. This educational course will provide a general overview of the latest delivery techniques in SRS/SBRT, and discuss the clinical processes to address the challenges of each technique with special emphasis on dedicated gamma-ray based device, robotic x-band linac-based system and conventional C-arm s-band linac-based SRS systems. (1). Gamma-ray based SRS/SRT: This is the gold standard of intracranial SRS. With the advent of precision imaging guidance and frameless patient positioning capabilities, novel stereoscopic CBCT and automatic dose adaption solution are introduced to the Gamma-ray based SRS for the first time. The first North American system has been approved by the US regulatory for patient treatments in the spring of 2016. (2). Robotic SRS/SBRT system: A number of technological milestones have been developed in the past few years, including variable aperture collimator, sequential optimization technique, and the time reduction technique. Recently, a new robotic model allows the option of a multi-leaf collimator. These technological advances have reduced the treatment time and improved dose conformity significantly and could potentially expand the application of radiosurgery for the treatment of targets not previously suitable for robotic SRS/SBRT or fractionated stereotactic radiotherapy. These technological advances have created new demanding mandates on hardware and patient quality assurance (QA) tasks, as well as the need for updating/educating the physicists in the community on these requirements. (3). Conventional Linac based treatments: Modulated arc therapy (MAT) has gained wide popularities in Linac-based treatments in recent years due to its high delivery efficiency and excellent dose conformities. Recently, MAT has been introduced to deliver highly conformal radiosurgery treatments to multiple targets simultaneously via a single isocenter to replace the conventional multi-iso multi-plan treatments. It becomes important to understand the advantages and limitations of this technique, and the pitfalls for implementing this technique in clinical practice. The planning process of single-iso multi-target MAT will be described, and its plan quality and delivery efficiency will be compared with multi-iso plans. The QA process for verifying such complex plans will be illustrated, and pitfalls in imaging and patient set up will be discussed. Overall, this session will focus on the following areas: 1) Update on the emerging technology in current SRS/SBRT delivery. 2) New developments in treatment planning and Quality Assurance program. 3) Imaging guidance and motion management. Learning Objectives: To understand the SRS/SBRT principles and its clinical applications, and gain knowledge on the emerging technologies in SRS/SBRT. To review planning concepts and useful tips in treatment planning. To learn about the imaging guidance procedures and the quality assurance program in SRS/SBRT. National Institutes of Health, Varian Medical System; L. Ren, The presenter is funded by National Institutes of Health and Varian Medical System.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

TH-C-BRC-03: Emerging Linac Based SRS/SBRT Technologies with Modulated Arc Delivery

The delivery techniques for SRS/SBRT have been under rapid developments in recent years, which pose new challenges to medical physicists ranging from planning and quality assurance to imaging and motion management. This educational course will provide a general overview of the latest delivery techniques in SRS/SBRT, and discuss the clinical processes to address the challenges of each technique with special emphasis on dedicated gamma-ray based device, robotic x-band linac-based system and conventional C-arm s-band linac-based SRS systems. (1). Gamma-ray based SRS/SRT: This is the gold standard of intracranial SRS. With the advent of precision imaging guidance and frameless patient positioning capabilities, novel stereoscopic CBCT and automatic dose adaption solution are introduced to the Gamma-ray based SRS for the first time. The first North American system has been approved by the US regulatory for patient treatments in the spring of 2016. (2). Robotic SRS/SBRT system: A number of technological milestones have been developed in the past few years, including variable aperture collimator, sequential optimization technique, and the time reduction technique. Recently, a new robotic model allows the option of a multi-leaf collimator. These technological advances have reduced the treatment time and improved dose conformity significantly and could potentially expand the application of radiosurgery for the treatment of targets not previously suitable for robotic SRS/SBRT or fractionated stereotactic radiotherapy. These technological advances have created new demanding mandates on hardware and patient quality assurance (QA) tasks, as well as the need for updating/educating the physicists in the community on these requirements. (3). Conventional Linac based treatments: Modulated arc therapy (MAT) has gained wide popularities in Linac-based treatments in recent years due to its high delivery efficiency and excellent dose conformities. Recently, MAT has been introduced to deliver highly conformal radiosurgery treatments to multiple targets simultaneously via a single isocenter to replace the conventional multi-iso multi-plan treatments. It becomes important to understand the advantages and limitations of this technique, and the pitfalls for implementing this technique in clinical practice. The planning process of single-iso multi-target MAT will be described, and its plan quality and delivery efficiency will be compared with multi-iso plans. The QA process for verifying such complex plans will be illustrated, and pitfalls in imaging and patient set up will be discussed. Overall, this session will focus on the following areas: 1) Update on the emerging technology in current SRS/SBRT delivery. 2) New developments in treatment planning and Quality Assurance program. 3) Imaging guidance and motion management. Learning Objectives: To understand the SRS/SBRT principles and its clinical applications, and gain knowledge on the emerging technologies in SRS/SBRT. To review planning concepts and useful tips in treatment planning. To learn about the imaging guidance procedures and the quality assurance program in SRS/SBRT. National Institutes of Health, Varian Medical System; L. Ren, The presenter is funded by National Institutes of Health and Varian Medical System.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2021

The high-power helicon program at DIII-D: gearing up for first experiments

Helicon current drive, also called fast wave current drive in the lower hybrid range of frequencies, has long been regarded as a promising current drive tool for reactor grade plasmas. A newly installed MW-level system at DIII-D will be the first test of this technology in reactor-relevant plasmas, in the sense that full single-pass absorption is expected. A 30-module traveling wave antenna has been installed and optimized in-vessel in early 2020. The linear electromagnetic characteristics of the unloaded module array have been extensively tested both on the bench and in the vessel at instrumentation power levels. Excellent performance has been achieved, ~2% reflected power and ~1.5% dissipated power per module in air, in a 10 MHz band around 476 MHz. Stripline feeds on both ends of the antenna allow either co or counter current drive. The installation of a 1.2 MW klystron and associated high-power electronics was completed in Fall 2020. Commissioning of the antenna is ongoing. An important goal of this experiment is to validate the helicon current drive physics basis using an extensive set of new and upgraded diagnostics.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2025

Dual-ion ECRAM as a stable and accurate analog synapse

Electrochemical random-access memory (ECRAM) works by tuning the bulk electronic conductance of functional materials via reversible, electrochemical insertion of ions, resulting in stable analog resistive switching, attractive for analog in-memory and neuromorphic computing. However, achieving fast programming for training and long retention for inference has been elusive. Protonic ECRAM demonstrates fast programming but insufficient retention, while oxygen-based ECRAM with excellent retention requires elevated programming temperatures. Cu-based ECRAM offers a compromise, with an activation energy (E A ) of ≈0.76 eV between protons (E A ≈ 0.4 eV) and oxygen (E A > 1 eV), enabling extensive retention and room temperature programming. Combining Cu 2+ ions with protons to form a dual-ion ECRAM, we demonstrate two distinct switching behaviors: fast switching at ≤5 V, (E A ≈ 0.45 eV) via protons, and nonvolatile, room temperature switching at ≥8 V, with E A ≈ 0.76 eV via Cu 2+ ions. In conclusion, the Cu-based state exhibits a wide conductance range, with excellent retention, low noise, and linear current-voltage behavior, achieving digital-equivalent ImageNet inference accuracy.

analog in-memory computing↗

DOE OSTI2018

Adsorption and Structure of Chiral Epoxides on Pd(111): Propylene Oxide and Glycidol

Here, the adsorption of enantiopure versus racemic propylene oxide (PO) on Pd(111) is studied by temperature-programmed desorption (TPD) to explore possible differences in their saturation coverage. It is found that that the saturation coverage of enantiopure PO on Pd(111) is identical to that of racemic PO, in contrast to results on Pt(111) where significant coverage differences were found. The surface structures of enantiopure PO on Pd(111) were characterized by scanning tunneling microscopy (STM), which shows the formation of linear chains and hexagonal structures proposed to be due to freely rotating PO, in contrast to the relatively disordered PO overlayers found on Pt(111). STM experiments were carried out for enantiopure glycidol, which contains the same epoxy ring as PO, but where the methyl group of propylene oxide is replaced by a -CH 2 OH group to provide a hydrogen-bonding sites. Glycidol STM images show the formation of completely different surface structures; at low coverages, glycidol forms pseudohexagonal structures which assemble from glycidol dimers, while at high coverages the surface shows extensive hydrogen-bonded networks. Density functional theory (DFT) calculations were carried out to model the enantiopure PO linear chain and the glycidol dimers that are observed by STM. Similar calculations were carried out for racemic PO and glycidol structures. The calculated interaction energies for the enantiopure and the racemic pairs reveal that there is no difference for homochiral versus heterochiral structures for both PO and glycidol on Pd(111).

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2017

Laser-driven magnetized liner inertial fusion on OMEGA

Magneto-inertial fusion (MIF) combines the compression of fusion fuel, a hallmark of inertial confinement fusion (ICF), with strongly magnetized plasmas that suppress electron heat losses, a hallmark of magnetic fusion. It can reduce the traditional velocity, pressure, and convergence ratio requirements of ICF. The magnetized liner inertial fusion (MagLIF) concept being studied at the Z Pulsed-Power Facility is a key target concept in the U.S. ICF Program. Laser-driven MagLIF is being developed on OMEGA to test the scaling of MagLIF over a range of absorbed energy of the order of 1 kJ on OMEGA to 500 kJ on Z. It is also valuable as a platform for studying the key physics of MIF. An energy-scaled point design has been developed for OMEGA that is roughly 10 × smaller in linear dimensions than Z MagLIF targets. A 0.6-mm-outer-diameter plastic cylinder filled with 2.4 mg/cm3 of D2 is placed in a ∼10-T axial magnetic field, generated by a Magneto-inertial fusion electrical discharge system, the cylinder is compressed by 40 OMEGA beams, and the gas fill is preheated by a single OMEGA beam propagating along the axis. Preheating to >100 eV and axially uniform compression over 0.7 mm have been demonstrated, separately, in a series of preparatory experiments that meet our initial expectations. The preliminary results from the first integrated experiments combining magnetization, compression, and preheat demonstrating a roughly 2 x increase in the neutron yield will be reported here for the first time.

Barnak, D. H. (ORCID:0000000246467517)↗

DOE OSTI2018

Efficient and Collision-Free Anticipative Cruise Control in Randomly Mixed Strings

Connected intelligent vehicle following can improve safety and efficiency compared to today's road transport, but real traffic in the near future will not provide an ideal setting for its deployment. Unconnected human-driven vehicles will follow variable behavior patterns that combine with differences in dynamic capability to create heterogeneous scenarios. In this paper, connected automated vehicles employ model predictive control for following in traffic that may include both heavy and passenger vehicles at quasi-random positions. Adding further realism, some quasi-randomly mixed vehicles are completely unconnected and equipped with the reactive intelligent driver model using pseudorandom parameters. A mixed-integer quadratic programming formulation adapts the predictive algorithm to diverse powertrain operating point constraints. The preceding vehicle's control input is estimated from velocity and brake light observations and used to probabilistically generate a preview for the ego vehicle. Here, a terminal constraint designed using particle kinematics prevents collisions due to shortsightedness. Results are simulated at various heavy and predictive vehicle concentrations in the presence of packet loss. Linear fuel economy improvements between 1.4% and 1.9% per 10% increase in predictive vehicle penetration rate are shown.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2015

Novel spirometry based on optical surface imaging

Purpose: To evaluate the feasibility of using optical surface imaging (OSI) to measure the dynamic tidal volume (TV) of the human torso during free breathing. Methods: We performed experiments to measure volume or volume change in geometric and deformable phantoms as well as human subjects using OSI. To assess the accuracy of OSI in volume determination, we performed experiments using five geometric phantoms and two deformable body phantoms and compared the values with those derived from geometric calculations and computed tomography (CT) measurements, respectively. To apply this technique to human subjects, an institutional review board protocol was established and three healthy volunteers were studied. In the human experiment, a high-speed image capture mode of OSI was applied to acquire torso images at 4–5 frames per second, which was synchronized with conventional spirometric measurements at 5 Hz. An in-house MATLAB program was developed to interactively define the volume of interest (VOI), separate the thorax and abdomen, and automatically calculate the thoracic and abdominal volumes within the VOIs. The torso volume change (TV C = ΔV{sub torso} = ΔV{sub thorax} + ΔV{sub abdomen}) was automatically calculated using full-exhalation phase as the reference. The volumetric breathing pattern (BP{sub v} = ΔV{sub thorax}/ΔV{sub torso}) quantifying thoracic and abdominal volume variations was also calculated. Under quiet breathing, TVC should equal the tidal volume measured concurrently by a spirometer with a conversion factor (1.08) accounting for internal and external differences of temperature and moisture. Another MATLAB program was implemented to control the conventional spirometer that was used as the standard. Results: The volumes measured from the OSI imaging of geometric phantoms agreed with the calculated volumes with a discrepancy of 0.0% ± 1.6% (range −1.9% to 2.5%). In measurements from the deformable torso/thorax phantoms, the volume differences measured using OSI imaging and CT imaging were 1.2% ± 2.1% (range −0.5% to 3.6%), with a linear regression fitting (slope = 1.02 and R{sup 2} = 0.999). In volunteers, the relative error in OSI tidal volume measurement was −2.2% ± 4.9% (range −9.2% to 4.8%) and a correlation of r = 0.98 was found with spirometric measurement. The breathing pattern values of the three volunteers were substantially different from each other (BP{sub v} = 0.15, 0.45, and 0.32). Conclusions: This study demonstrates the feasibility of using OSI to measure breathing tidal volumes and breathing patterns with adequate accuracy. This is the first time that dynamic breathing tidal volume as well as breathing patterns is measured using optical surface imaging. The OSI-observed movement of the entire torso could serve as a new respiratory surrogate in the treatment room during radiation therapy.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

Poster - 44: Development and implementation of a comprehensive end-to-end testing methodology for linac-based frameless SRS QA using a modified commercial stereotactic anthropomorphic phantom

Purpose: An end-to-end testing methodology was designed to evaluate the overall SRS treatment fidelity, incorporating all steps in the linac-based frameless radiosurgery treatment delivery process. The study details our commissioning experience of the Steev (CIRS, Norfolk, VA) stereotactic anthropomorphic head phantom including modification, test design, and baseline measurements. Methods: Repeated MR and CT scans were performed with interchanging inserts. MR-CT fusion accuracy was evaluated and the insert spatial coincidence was verified on CT. Five non-coplanar arcs delivered a prescription dose to a 15 mm spherical CTV with 2 mm PTV margin. Following setup, CBCT-based shifts were applied as per protocol. Sequential measurements were performed by interchanging inserts without disturbing the setup. Spatial and dosimetric accuracy was assessed by a combination of CBCT hidden target, radiochromic film, and ion chamber measurements. To facilitate film registration, the film insert was modified in-house by etching marks. Results: MR fusion error and insert spatial coincidences were within 0.3 mm. Both CBCT and film measurements showed spatial displacements of 1.0 mm in similar directions. Both coronal and sagittal films reported 2.3 % higher target dose relative to the treatment plan. The corrected ion chamber measurement was similarly greater by 1.0 %. The 3 %/2 mm gamma pass rate was 99% for both films Conclusions: A comprehensive end-to-end testing methodology was implemented for our SRS QA program. The Steev phantom enabled realistic evaluation of the entire treatment process. Overall spatial and dosimetric accuracy of the delivery were 1 mm and 3 % respectively.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2019

Benchmarking Parametric and Machine Learning Models for Genomic Prediction of Complex Traits

The usefulness of genomic prediction in crop and livestock breeding programs has prompted efforts to develop new and improved genomic prediction algorithms, such as artificial neural networks and gradient tree boosting. However, the performance of these algorithms has not been compared in a systematic manner using a wide range of datasets and models. Using data of 18 traits across six plant species with different marker densities and training population sizes, we compared the performance of six linear and six non-linear algorithms. First, we found that hyperparameter selection was necessary for all non-linear algorithms and that feature selection prior to model training was critical for artificial neural networks when the markers greatly outnumbered the number of training lines. Across all species and trait combinations, no one algorithm performed best, however predictions based on a combination of results from multiple algorithms (i.e., ensemble predictions) performed consistently well. While linear and non-linear algorithms performed best for a similar number of traits, the performance of non-linear algorithms vary more between traits. Although artificial neural networks did not perform best for any trait, we identified strategies (i.e., feature selection, seeded starting weights) that boosted their performance to near the level of other algorithms. Our results highlight the importance of algorithm selection for the prediction of trait values.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2018

DEGAS: Dynamic Exascale Global Address Space Programming Environments

The Dynamic, Exascale Global Address Space programming environment (DEGAS) project will develop the next generation of programming models and runtime systems to meet the challenges of Exascale computing. The Berkeley part of the project concentrated on communication-optimal code generation to optimize speed and energy efficiency by reducing data movement. Our work developed communication lower bounds, and/or communication avoiding algorithms (that either meet the lower bound, or do much less communication than their conventional counterparts) for a variety of algorithms, including linear algebra, machine learning and genomics. The Berkeley part of the project concentrated on communication-optimal code generation to optimize speed and energy efficiency by reducing data movement. Our work developed communication lower bounds, and/or communication avoiding algorithms (that either meet the lower bound, or do much less communication than their conventional counterparts) for a variety of algorithms, including linear algebra, machine learning and genomics.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2022

Bayesian Monte-Carlo Framework: New Methods for Resonance Parameter Evaluation [Slides]

BMC evaluation is a tool to address imperfect data & models, non-linear models, and non-normal PDFs. ENDF-6 format does not allow non-normal parameter PDFs. Storing posterior sets allow for variance, covariance, skewness, etc. To better predict criticality, we could document non-normal parameter PDFs (i.e. asymmetric uncertainty), consider non-linear sensitivity of $\kappa$ eff to resonance parameters, and reduce uncertainty in key resonance parameters.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2026

A Simulator for Neyer Tests of Explosives

Explosives and explosive devices such as detonators are typically tested by applying a range of stimuli such as voltage or mechanical shock, and recording binary “detonated/did not detonate” responses. These are analyzed using maximum likelihood or generalized linear models to provide estimates of quantities such as the all-fire and no-fire points. Given that the true threshold for detonation is unknown a priori , sequential design methods are typically used to optimize the set of test points. One popular method, implemented in commercial software, is Neyer’s algorithm. To support simulation and experimental design, we have developed code in the R programming language to duplicate the functions of the Neyer software. We provide code for the simulator along with a description and examples of usage.

42 ENGINEERING↗

DOE OSTI2019

Benchmarking parametric and machine learning models for genomic prediction of complex traits

The usefulness of genomic prediction in crop and livestock breeding programs has prompted efforts to develop new and improved genomic prediction algorithms, such as artificial neural networks and gradient tree boosting. However, the performance of these algorithms has not been compared in a systematic manner using a wide range of datasets and models. Using data of 18 traits across six plant species with different marker densities and training population sizes, we compared the performance of six linear and six non-linear algorithms. First, we found that hyperparameter selection was necessary for all non-linear algorithms and that feature selection prior to model training was critical for artificial neural networks when the markers greatly outnumbered the number of training lines. Across all species and trait combinations, no one algorithm performed best, however predictions based on a combination of results from multiple algorithms (i.e. ensemble predictions) performed consistently well. While linear and non-linear algorithms performed best for a similar number of traits, the performance of non-linear algorithms vary more between traits. Although artificial neural networks did not perform best for any trait, we identified strategies (i.e. feature selection, seeded starting weights) that boosted their performance to near the level of other algorithms. Our results highlight the importance of algorithm selection for the prediction of trait values.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2014

SU-E-T-473: A Patient-Specific QC Paradigm Based On Trajectory Log Files and DICOM Plan Files

Purpose: To evaluate a remote QC tool for monitoring treatment machine parameters and treatment workflow. Methods: The Varian TrueBeamTM linear accelerator is a digital machine that records machine axis parameters and MLC leaf positions as a function of delivered monitor unit or control point. This information is saved to a binary trajectory log file for every treatment or imaging field in the patient treatment session. A MATLAB analysis routine was developed to parse the trajectory log files for a given patient, compare the expected versus actual machine and MLC positions as well as perform a cross-comparison with the DICOM-RT plan file exported from the treatment planning system. The parsing routine sorts the trajectory log files based on the time and date stamp and generates a sequential report file listing treatment parameters and provides a match relative to the DICOM-RT plan file. Results: The trajectory log parsing-routine was compared against a standard record and verify listing for patients undergoing initial IMRT dosimetry verification and weekly and final chart QC. The complete treatment course was independently verified for 10 patients of varying treatment site and a total of 1267 treatment fields were evaluated including pre-treatment imaging fields where applicable. In the context of IMRT plan verification, eight prostate SBRT plans with 4-arcs per plan were evaluated based on expected versus actual machine axis parameters. The average value for the maximum RMS MLC error was 0.067±0.001mm and 0.066±0.002mm for leaf bank A and B respectively. Conclusion: A real-time QC analysis program was tested using trajectory log files and DICOM-RT plan files. The parsing routine is efficient and able to evaluate all relevant machine axis parameters during a patient treatment course including MLC leaf positions and table positions at time of image acquisition and during treatment.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2017

Thermochimica

Thermochimica is a software library that determines a unique combination of phases and their compositions at thermochemical equilibrium. Thermochimica can be used for stand-alone calculations or it can be directly coupled to other codes. This release of the software does not have a graphical user interface (GUI) and it can be executed from the command line or from an Application Programming Interface (API). Also, it is not intended for thermodynamic model development or for constructing phase diagrams. The main purpose of the software is to be directly coupled with a multi-physics code to provide material properties and boundary conditions for various physical phenomena. Significant research efforts have been dedicated to enhance computational performance through advanced algorithm development, such as improved estimation techniques and non-linear solvers. Various useful parameters can be provided as output from Thermochimica, such as: determination of which phases are stable at equilibrium, the mass of solution species and phases at equilibrium, mole fractions of solution phase constituents, thermochemical activities (which are related to partial pressures for gaseous species), chemical potentials of solution species and phases, and integral Gibbs energy (referenced relative to standard state). The overall goal is to provide an open source computational tool to enhance the predictive capability of multi-physics codes without significantly impeding computational performance.

Simunovic, Srdjan↗