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Mapping the genome of meta-generalized gradient approximation density functionals: The search for B97M-V

A meta-generalized gradient approximation density functional paired with the VV10 nonlocal correlation functional is presented. The functional form is selected from more than 10{sup 10} choices carved out of a functional space of almost 10{sup 40} possibilities. Raw data come from training a vast number of candidate functional forms on a comprehensive training set of 1095 data points and testing the resulting fits on a comprehensive primary test set of 1153 data points. Functional forms are ranked based on their ability to reproduce the data in both the training and primary test sets with minimum empiricism, and filtered based on a set of physical constraints and an often-overlooked condition of satisfactory numerical precision with medium-sized integration grids. The resulting optimal functional form has 4 linear exchange parameters, 4 linear same-spin correlation parameters, and 4 linear opposite-spin correlation parameters, for a total of 12 fitted parameters. The final density functional, B97M-V, is further assessed on a secondary test set of 212 data points, applied to several large systems including the coronene dimer and water clusters, tested for the accurate prediction of intramolecular and intermolecular geometries, verified to have a readily attainable basis set limit, and checked for grid sensitivity. Compared to existing density functionals, B97M-V is remarkably accurate for non-bonded interactions and very satisfactory for thermochemical quantities such as atomization energies, but inherits the demonstrable limitations of existing local density functionals for barrier heights.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

SU-F-R-11: Designing Quality and Safety Informatics Through Implementation of a CT Radiation Dose Monitoring Program

Purpose: Recent legislative and accreditation requirements have driven rapid development and implementation of CT radiation dose monitoring solutions. Institutions must determine how to improve quality, safety, and consistency of their clinical performance. The purpose of this work was to design a strategy and meaningful characterization of results from an in-house, clinically-deployed dose monitoring solution. Methods: A dose monitoring platform was designed by our imaging physics group that focused on extracting protocol parameters, dose metrics, and patient demographics and size. Compared to most commercial solutions, which focus on individual exam alerts and global thresholds, the program sought to characterize overall consistency and targeted thresholds based on eight analytic interrogations. Those were based on explicit questions related to protocol application, national benchmarks, protocol and size-specific dose targets, operational consistency, outliers, temporal trends, intra-system variability, and consistent use of electronic protocols. Using historical data since the start of 2013, 95% and 99% intervals were used to establish yellow and amber parameterized dose alert thresholds, respectively, as a function of protocol, scanner, and size. Results: Quarterly reports have been generated for three hospitals for 3 quarters of 2015 totaling 27880, 28502, 30631 exams, respectively. Four adult and two pediatric protocols were higher than external institutional benchmarks. Four protocol dose levels were being inconsistently applied as a function of patient size. For the three hospitals, the minimum and maximum amber outlier percentages were [1.53%,2.28%], [0.76%,1.8%], [0.94%,1.17%], respectively. Compared with the electronic protocols, 10 protocols were found to be used with some inconsistency. Conclusion: Dose monitoring can satisfy requirements with global alert thresholds and patient dose records, but the real value is in optimizing patient-specific protocols, balancing image quality trade-offs that dose-reduction strategies promise, and improving the performance and consistency of a clinical operation. Data plots that capture patient demographics and scanner performance demonstrate that value.

60 APPLIED LIFE SCIENCES↗

SU-E-I-29: Care KV: Dose It Influence Radiation Dose in Non-Contrast Examination of CT Abdomen/pelvis?

Purpose: CARE kV is a tool that automatically recommends optimal kV setting for individual patient for specific CT examination. The use of CARE kV depends on topogram and the user-selected contrast behavior. CARE kV is expected to reduce radiation dose while improving image quality. However, this may work only for certain groups of patients and/or certain CT examinations. This study is to investigate the effects of CARE kV on radiation dose of non-contrast examination of CT abdomen/pelvis. Methods: Radiation dose (CTDIvol and DLP) from patients who underwent abdomen/pelvis non-contrast examination with and without CARE kV were retrospectively reviewed. All patients were scanned in the same scanner (Siemens Somatom AS64). To mitigate any possible influences due to technologists’ unfamiliarity with the CARE kV, the data with CARE kV were retrieved 1.5 years after the start of CARE kV usage. T-test was used for significant difference in radiation dose. Results: Volume CTDIs and DLPs from 18 patients before and 24 patients after the use of CARE kV were obtained in a duration of one month. There is a slight increase in both average CTDIvol and average DLP with CARE kV compared to those without CARE kV (25.52 mGy vs. 22.65 mGy for CTDIvol; 1265.81 mGy-cm vs. 1199.19 mGy-cm). Statistically there was no significant difference. Without CARE kV, 140 kV was used in 9 of 18 patients, while with CARE KV, 140 kV was used in 15 of 24 patients. 80kV was not used in either group. Conclusion: The use of CARE kV may save time for protocol optimization and minimize variability among technologists. Radiation dose reduction was not observed in non-contrast examinations of CT abdomen/pelvis. This was partially because our CT protocols were tailored according to patient size before CARE kV and partially because of large size patients.

60 APPLIED LIFE SCIENCES↗

NEET Enhanced Micro-Pocket Fission Detector for High Temperature Reactors - FY16 Status Report

A collaboration between the Idaho National Laboratory (INL), the Kansas State University (KSU), and the French Atomic Energy Agency, Commissariat à l'Énergie Atomique et aux Energies Alternatives, (CEA), has been initiated by the Nuclear Energy Enabling Technologies (NEET) Advanced Sensors and Instrumentation (ASI) program for developing and testing High Temperature Micro-Pocket Fission Detectors (HT MPFD), which are compact fission chambers capable of simultaneously measuring thermal neutron flux, fast neutron flux and temperature within a single package for temperatures up to 800 °C. The MPFD technology utilizes a small, multi-purpose, robust, in-core fission chambers and thermocouple. As discussed within this report, the small size, variable sensitivity, and increased accuracy of the MPFD technology represent a revolutionary improvement over current methods used to support irradiations in US Material Test Reactors (MTRs). Previous research conducted through NEET ASI1-3 has shown that the MPFD technology could be made robust and was successfully tested in a reactor core. This new project will further the MPFD technology for higher temperature regimes and other reactor applications by developing a HT MPFD suitable for temperatures up to 800 °C. This report summarizes the research progress for year two of this three year project. Highlights from research accomplishments include: • Continuation of a joint collaboration between INL, KSU, and CEA. Note that CEA is participating at their own expense because of interest in this unique new sensor. • An updated parallel wire HT MPFD design was developed. • Program support for HT MPFD deployments was given to Accident Tolerant Fuels (ATF) and Advanced Gas-cooled Reactor (AGR) irradiation test programs. • Quality approved materials for HT MPFD construction were procured by irradiation test programs for upcoming deployments. • KSU improved and performed electrical contact and fissile material plating. • KSU delivered fissile HT MPFD parts to INL for final construction of HT MPFD prototype. • A prototype HT MPFD was constructed and analyzed at INL. • The HT MPFD has been modeled in MCNP to optimize the amount of fissile material deposition. • The HT MPFD has been modeled in MCNP to optimize the sensor location in the irradiation test. • The fissile material deposition is undergoing independent verifications. • Detector amplifier electronics have been revised and tested by KSU. • Several project meetings were held at INL and KSU to discuss the roles and responsibilities between INL, KSU, and CEA for development and deployment of the HT MPFDs. As documented in this report, FY16 funding has allowed the project to meet year two planned accomplishments to develop a HT MPFD. In addition, the accomplishments of this project have attracted independent funding from other Department of Energy Office of Nuclear Energy (DOE-NE) programs for MTR irradiations of the MPFD technology. These are significant opportunities for this NEET Enhanced Micro-Pocket Fission Detector for High Temperature Reactors project because the irradiation expense of these experiments could not be included in the original project scope.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Installing Deep Groundwater Monitoring Wells in a Volcanic Dominated Rift Basin: Los Alamos National Laboratory, New Mexico - 17594

Los Alamos National Laboratory (LANL, or the Laboratory) is located in northern New Mexico near the west margin of the Espanola Basin. LANL is underlain by a complex basin-fill sequence of alluvial fan deposits, volcanic tuff, basaltic and dacitic lavas, and riverine deposits. On-going environmental remediation and characterization activities have evolved to improve the performance of groundwater monitoring wells, ensuring they yield representative groundwater and core samples. Groundwater occurs as canyon-fill alluvial water, perched intermediate-depth water associated with the basalts and other local-scale perching horizons, and as a regional-scale aquifer that is the main water supply for the area. Anthropogenic contaminants are found in all three groundwater zones. The regional aquifer below LANL is nominally 1000-1400 feet below ground surface (bgs). Monitoring wells at the Laboratory, are therefore, among the deepest routinely installed in the US. Logistical challenges at LANL include steep terrain, widespread cultural sites, and threatened and endangered species habitat restrictions. Additionally, the cost of installing monitoring wells is high because of groundwater depths and the variable drilling techniques that are required to characterize and install wells in a complex geologic environment. A major challenge to the characterization approach at LANL has been to meet sample quality requirements while minimizing drilling costs. In the late 1990's threaded drill-casing was advanced by rotary drilling methods using compressed air as the only circulation fluid. This resulted in relatively low impacts to the geochemical integrity of rock and groundwater samples, but led to frequent episodes of stuck casing. Additional fluids were introduced to the air-rotary program, improving penetration rates, but also resulting in non-representative groundwater samples due to long-term impacts to the aquifer in the vicinity of the well screen. Mud-rotary drilling was incorporated into the program, but it also had significant long-term impacts on groundwater quality, and often inhibited identification of perched groundwater zones and accurate identification of the water table in the regional aquifer. Current drilling practice makes limited use of fluid additives (e.g. foam) to supplement air circulation methods in order to advance drill casing through the vadose zone. Starting about 100 feet above the water table, drill casing is advanced to the target horizon in the regional aquifer using only air and municipal water (when needed) for circulation. Additionally, the threaded drill casing couplings have been replaced with welded connections, significantly reducing the occurrence of stuck casing. Careful observations of water production and water levels during drilling, coupled with the ability to retract casing for video and geophysical logs, now allows for robust characterization of perched groundwater systems and accurate definition of the top of regional saturation. Recent advances in the drilling program include combined dual-rotary/sonic drilling to depths up to 1150 feet and dual-rotary casing advance at angles up to 25 deg. from vertical. The former allows for core collection with minimal fluid addition, thereby preserving pore water chemistry. The latter method allows for well installation into portions of the aquifer otherwise inaccessible due to constraints at the surface (e.g., cultural sites or topography). Similar to the development of drilling techniques, both well design and groundwater sampling system design have evolved throughout the program. Current well design emphasizes a minimal annulus of filter pack, maximum screen slot size based on formation sieve analyses, and thorough well development to mitigate formation damage due to drilling. To sample groundwater at multiple levels in the same well, earlier sampling systems included Westbay{sup R} multi-zone systems and dual-screen single-pump and dual-screen dual-pump systems designed in collaboration with Baski, Inc. These multi-zone sampling systems proved difficult to develop and maintain given the depth to groundwater, and most current well installations are configured with a single screen and a submersible pump. The ability to purge from a well-developed single-screen well has substantially improved the collection of representative groundwater samples. A carefully crafted groundwater characterization program in target aquifers at depths ranging from 1,000 to 1,400 feet bgs within a complex geologic setting, while also retaining the ability to collect representative core and groundwater samples, may have application at a number of sites throughout the environmental industry. Optimizing each well to meet program objectives while reducing total project costs benefits all environmental investigations. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Scale translation yields insights into gas adsorption under nanoconfinement

This work describes a scale-translating simulation framework to investigate gas adsorption behavior in nanoconfined pores. The framework combines molecular simulations (MSs), equation of state (EoS), and lattice Boltzmann (LB) simulations. MSs reveal the physics of methane adsorption in nano-sized pores, where input values of fugacity coefficients are optimized based on EoS predictions. Then, an LB free-energy model, which incorporates a viral EoS, upscales intermolecular forces and estimates adsorption behavior via a proposed fluid–wall interaction model. Armed with the values of the LB interaction parameter as a function of pressure, the LB model is used to predict fluid behavior in irregular nanopores, and the results are validated against reference MS data. The LB model is then used to study adsorption behavior at a continuum scale in representative organic shale nanopores based on finely characterized Vaca Muerta shale samples. Furthermore, the results show that methane adsorption could significantly increase contained fluids by 10%–25% in pores smaller than 20 nm. However, in larger pores (40 nm to 90 nm), adsorption's impact diminishes to 2%–3%, suggesting sorption's negligible role beyond a 40 nm pore size.

74 ATOMIC AND MOLECULAR PHYSICS↗

IDAES-PSE 2.4.0 Release

The Institute for the Design of Advanced Energy Systems (IDAES) Integrated Platform is a versatile computational environment offering extensive process systems engineering (PSE) capabilities for optimizing the design and operation of complex, interacting technologies and systems. IDAES enables users to efficiently search vast, complex design spaces to discover the lowest cost, most environmentally sustainable solutions while supporting the full process modeling lifecycle, from conceptual design to dynamic optimization and control. The extensible, open platform empowers users to create models of novel processes and rapidly develop custom analyses, workflows, and end-user applications.. Deprecations • Convergence Analysis tool (idaes/core/util/convergence): deprecated in favor of new Parameter Sweep tools. To be removed in v3.0.0. New Beta Capabilities • Parameter Sweep Tool (idaes.core.util.parameter_sweep) o A new API for defining and performing parameter sweep studies on IDAES models has been developed • Diagnostics Tools (idaes.core.util.model_diagnostics) o New methods for identifying duplicate variables and constraints have been added to the diagnostics toolbox o New tools for detecting ill conditioning in Jacobians have been developed and are available in the model_diagnostics module. These provide alternatives to the existing DegeneracyHunter toolbox, and will eventually be merged with this capability, but initial working versions have been provided as beta capabilities for interested users o IpoptConvergenceAnalysis (replaces deprecated Convergence Analysis tool):  A new tool for performing convergence analysis studies that leverages the new Parameter Sweep tools has been developed. This tool allows users to define the input parameters to their model and sampling methods for these (leveraging Pysmo's sampling tools) and to then solve their model across the sampled domains and return a summary of the solver performance (IPOPT only) Improved Models • Thickener model (idaes.models.unit_models.solid_liquid.thickener) o Improved model to include predictive correlations for unit sizing based on settling velocity measurements (steady-state only) • Modular Property Packages o Added general support for calculating critical properties of mixtures using defined Equation of State modules. New API defined for Equation of State modules in order to define the necessary constraints for calculating critical properties (most EoS modules DO NOT support calculation of critical properties (yet)) o Added new methods to Cubic Equation of State module to support calculation of critical properties

DiagnosticsToolbox↗

Increasing the hardness of posiform planting using random QUBOs for programmable quantum annealer benchmarking

Posiform planting is a method for constructing QUBO instances with a unique planted solution that can be tailored to arbitrary connectivity graphs. In this study we investigate making posiform planted QUBOs computationally harder by fusing many smaller random Ising models, whose global minimum is computed classically, with posiform planted QUBOs. The unique ground state of the resulting QUBO is the concatenation of (exactly one of) the ground states of each smaller problem. Our method generates QUBO instances that have a unique solution, are native to the hardware graph, and have tunable computational hardness. We use our QUBOs to benchmark three D-Wave quantum annealing processors (with 563–5627 qubits), and compare them against simulated annealing and Gurobi. Surprisingly, we find that the D-Wave ground state sampling success rate is not dependent on the glued random QUBO size, and that some QUBO classes are solved at high success rates at short annealing times on the Zephyr processors.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

A Grid Intensity Map-Based Source Model for Monte Carlo Modeling of IMRT Field Irradiation - Paper 5

An accurate source model is important for TPS (Treatment Planning System) dose calculation and verification, especially for IMRT (Intensity Modulated Radiotherapy) irregular and inhomogeneous fields. Monte Carlo simulation is the most accurate way to calculate dose distributions in the heterogeneous media like human bodies. A full radiotherapy modeling generally includes Linac modeling and phantom dose calculation. Full Linac modeling is very time-consuming and requires highly detailed knowledge of the accelerator composition and structure, however, which is very difficult to obtain for commercial interests. Often all relevant parameters are not known with sufficient accuracy, and thus a time-consuming tuning of e.g. the electron beam spot size and energy must be performed. A multiple source model (MSM) regards particles coming from different parts of an accelerator as if they are coming from different virtual sources. MSM uses a set of virtual sources representing the treatment beam (e.g. primary photons, head scatter, electron contamination) by a set of analytic functions or histograms with parameters derived from dosimetric measurements or a full MC simulation. Tillikainen et al built a three sub-source model by matching with measurement data using an automatic process to optimize the free model parameters for a Varian 2100 C/D accelerator. Lin et al have built a convenient five-photon-sub-source model for Varian 2300C 6 MV-X beam based on Monte Carlo simulated Linac for ARTS (Accurate Radiotherapy System). The particle generation of MSM is very fast compared to full Linac simulation, and its sampling efficiency is not limited by the size of the phase space file (PSF). However, generally MSM is generated based on regular field PSF and needs an irregular component to form the beam shape meanwhile apt to bringing error Linac modeling and MSM producing from PSF analysis actually both are multi-freedom optimization process by adjusting several parameters (e.g. electron energy and angular divergence). Linac modeling adjusts its parameters from the beginning of electron hitting target through all components to fit the simulation to the measurement. MSM tunes its PSF-derived parameters by optimizing to minimize the deviations between the simulation and the measurement. Since the full Linac modeling and the MSM model both need to fine tune their parameters to match the simulation to the measurement, and sometimes maybe offsets the real accelerator for its multi-parameter optimization process. So, why not fine tune directly all source model parameters just behind all Linac components to fit the simulation to the measurement? A grid intensity-based surface source model was suggested here, which assumed the particle emitting from the bottom surface of Linac last beam trimmer MLC (Multi Leaf Collimator). The particle emitting position is sampled on the grid intensity map optimized by TPS, and the particle weight is adjusted by its original grid intensity. This source model not only takes advantage of the Monte Carlo method in the heterogeneous media, but also avoids effectively the transportation speed shortcoming of Monte Carlo simulation through Linac components. (authors)

61 RADIATION PROTECTION AND DOSIMETRY↗

Ambient aging of rhenium filaments used in thermal ionization mass spectrometry: Growth of oxo-rhenium crystallites and anti-aging strategies

Degassing is a common preparation technique for rhenium filaments used for thermal ionization mass spectrometric analysis of actinides, including plutonium. Although optimization studies regarding degassing conditions have been reported, little work has been done to characterize filament aging after degassing. In this study, the effects of filament aging after degassing were explored to determine a “shelf-life” for degassed rhenium filaments, and methods to limit filament aging were investigated. Zone-refined rhenium filaments were degassed by resistance heating under high vacuum before exposure to ambient atmosphere for up to 2 months. After degassing the nucleation and preferential growth of oxo-rhenium crystallites on the surface of polycrystalline rhenium filaments was observed by atomic force microscopy and scanning electron microscopy (SEM). Compositional analysis of the crystallites was conducted using SEM-Raman spectroscopy and SEM energy dispersive X-ray spectroscopy, and grain orientation at the metal surface was investigated by electron back-scatter diffraction mapping. Spectra collected by SEM-Raman suggest crystallites are composed primarily of perrhenic acid. The relative extent of growth and crystallite morphology were found to be grain dependent and affected by the dissolution of carbon into filaments during annealing (often referred to as carbonization or carburization). Crystallites were observed to nucleate in region specific modes and grow over time through transfer of material from the surface. Factors most likely to affect the rates of crystallite growth include rhenium substrate properties such as grain size, orientation, levels of dissolved carbon, and relative abundance of defect sites; as well as environmental factors such as length of exposure to oxygen and relative humidity. Thin (~180 nm) hydrophobic films of poly(vinylbenzyl chloride) were found to slow the growth of oxo-rhenium crystallites on the filament surfaces and may serve as an alternative carbon source for filament carburization.

36 MATERIALS SCIENCE↗

Probing the Role of Zr Addition versus Textural Properties in Enhancement of CO 2 Adsorption Performance in Silica/PEI Composite Sorbents

Polymeric amines such as poly(ethylenimine) (PEI) supported on mesoporous oxides are promising candidate adsorbents for CO 2 capture processes. One important aspect to the design and optimization of these materials is a fundamental understanding of how the properties of the oxide support such as pore structure, particle morphology, and surface properties affect the efficiency of the guest polymer in its interactions with CO 2 . Previously, the efficiency of impregnated PEI to adsorb CO 2 was shown to increase upon the addition of Zr as a surface modifier in SBA-15. But, the efficacy of this method to tune the adsorption performance has not been explored in materials of differing textural and morphological nature. These issues are directly addressed via the preparation of an array of SBA-15 support materials with varying textural and morphological properties, as well as varying content of zirconium doped into the material. Zirconium is incorporated into the SBA-15 either during the synthesis of the SBA-15, or postsynthetically via deposition of Zr species onto pure-silica SBA-15. The method of Zr incorporation alters the textural and morphological properties of the parent SBA-15 in different ways. Importantly, the CO 2 capacity of SBA-15 impregnated with PEI increases by a maximum of ~60% with the quantity of doped Zr for a “standard” SBA-15 containing significant microporosity, while no increase in the CO 2 capacity is observed upon Zr incorporation for an SBA-15 with reduced microporosity and a larger pore size, pore volume, and particle size. Finally, adsorbents supported on SBA-15 with controlled particle morphology show only modest increases in CO 2 capacity upon inclusion of Zr to the silica framework. The data demonstrate that the textural and morphological properties of the support have a more significant impact on the ability of PEI to capture CO 2 than the support surface composition.

36 MATERIALS SCIENCE↗

Natural orbitals for the ab initio no-core configuration interaction approach

Ab initio no-core configuration interaction (NCCI) calculations for the nuclear many-body problem have traditionally relied upon an antisymmetrized product (Slater determinant) basis built from harmonic oscillator orbitals. The accuracy of such calculations is limited by the finite dimensions which are computationally feasible for the truncated many-body space. We therefore seek to improve the accuracy obtained for a given basis size by optimizing the choice of single-particle orbitals. Natural orbitals, which diagonalize the one-body density matrix, provide a basis which maximizes the occupation of low-lying orbitals, thus accelerating convergence in a configuration-interaction basis, while also possibly providing physical insight into the single-particle structure of the many-body wave function. We describe the implementation of natural orbitals in the NCCI framework and examine the nature of the natural orbitals thus obtained, the properties of the resulting many-body wave functions, and the convergence of observables. After taking 3 He as an illustrative testbed, we explore aspects of NCCI calculations with natural orbitals for the ground state of the p-shell neutron halo nucleus 6 He .

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Tumor Radiation Therapy Creates Therapeutic Vaccine Responses to the Colorectal Cancer Antigen GUCY2C

Purpose: Radiation therapy (RT) is thought to produce clinical responses in cancer patients, not only through direct toxicity to cancer cells and supporting tumor stroma cells, but also through activation of immunologic effectors. More recently, RT has potentiated the local and systemic effects of cancer immunotherapy (IT). However, combination regimens that maximize immunologic and clinical efficacy remain undefined. Methods and Materials: We evaluated the impact of local RT on adenoviral-mediated vaccination against the colorectal cancer antigen GUCY2C (Ad5-GUCY2C) in a murine subcutaneous tumor model using mouse CT26 colon cancer cells (CT26-GUCY2C). Immune responses were assessed by ELISpot, and clinical responses were assessed by tumor size and incidence. Results: The specific sequence of tumor-directed RT preceding Ad5-GUCY2C IT transformed inactive therapeutic Ad5-GUCY2C vaccination into a curative vaccine. GUCY2C-specific T cell responses were amplified (P<.05), tumor eradication was maximized (P<.01), and tumor volumes were minimized (P<.001) in mice whose tumors were irradiated before, compared with after, Ad5-GUCY2C vaccination. The immunologic and antitumor efficacy of Ad5-GUCY2C was amplified comparably by unfractionated (8 Gy × 1), or biologically equivalent doses of fractionated (3.5 Gy × 3), RT. The antitumor effects of sequential RT and IT (RT-IT) depended on expression of GUCY2C by tumor cells and the adenoviral vaccine vector, and tumor volumes were inversely related to the magnitude of GUCY2C-specific T cell responses. Moreover, mice cured of CT26-GUCY2C tumors by RT-IT showed long-lasting antigen-dependent protection, resisting tumors formed by GUCY2C-expressing 4T1 breast cancer cells inoculated 50 days after CT26 cells. Conclusions: Optimal sequencing of RT and IT amplifies antigen-specific local and systemic immune responses, revealing novel acute and long-term therapeutic antitumor protection. These observations underscore the importance of modality sequence optimization before the initiation of clinical trials of RT and IT to maximize immune and antitumor responses.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Technical Note: Dose effects of 1.5 T transverse magnetic field on tissue interfaces in MRI-guided radiotherapy

Purpose: The integration of MRI with a linear accelerator (MR-linac) offers great potential for high-precision delivery of radiation therapy (RT). However, the electron deflection resulting from the presence of a transverse magnetic field (TMF) can affect the dose distribution, particularly the electron return effect (ERE) at tissue interfaces. The purpose of the study is to investigate the dose effects of ERE at air-tissue and lung-tissue interfaces during intensity-modulated radiation therapy (IMRT) planning. Methods: IMRT and volumetric modulated arc therapy (VMAT) plans for representative pancreas, lung, breast, and head and neck (HN) cases were generated following commonly used clinical dose volume (DV) criteria. In each case, three types of plans were generated: (1) the original plan generated without a TMF; (2) the reconstructed plan generated by recalculating the original plan with the presence of a TMF of 1.5 T (no optimization); and (3) the optimized plan generated by a full optimization with TMF = 1.5 T. These plans were compared using a variety of DV parameters, including V{sub 100%}, D{sub 95%}, DHI [dose heterogeneity index: (D{sub 20%}–D{sub 80%})/D{sub prescription}], D{sub max}, and D{sub 1cc} in OARs (organs at risk) and tissue interface. All the optimizations and calculations in this work were performed on static data. Results: The dose recalculation under TMF showed the presence of the 1.5 T TMF can slightly reduce V{sub 100%} and D{sub 95%} for PTV, with the differences being less than 4% for all but one lung case studied. The TMF results in considerable increases in D{sub max} and D{sub 1cc} on the skin in all cases, mostly between 10% and 35%. The changes in D{sub max} and D{sub 1cc} on air cavity walls are dependent upon site, geometry, and size, with changes ranging up to 15%. The VMAT plans lead to much smaller dose effects from ERE compared to fixed-beam IMRT in pancreas case. When the TMF is considered in the plan optimization, the dose effects of the TMF at tissue interfaces (e.g., air-cavity wall, lung-tissue interfaces, skin) are significantly reduced in most cases. Conclusions: The doses on tissue interfaces can be significantly changed by the presence of a TMF during MR-guided RT when the magnetic field is not included in plan optimization. These changes can be substantially reduced or even eliminated during VMAT/IMRT optimization that specifically considers the TMF, without deteriorating overall plan quality.

60 APPLIED LIFE SCIENCES↗

A Fast and Scalable Genetic Algorithm-Based Approach for Planning of Microgrids in Distribution Networks

As a result of climate change, extreme weather events are occurring more frequently and with increasing impact. This trend poses a significant challenge for distribution utilities and system operators to ensure that there is uninterrupted power supply to critical loads in their networks; thus, the level of proactive preparation of the distribution system to be able to handle severe impacts of extreme weather events represents the system's resilience. One method that distribution system planners can use to prepare for future extreme events is to plan multiple microgrids which can use local generation as much as possible to supply critical loads. But partitioning an existing distribution system such that multiple feasible islands are planned and which are capable of supporting critical loads is still challenging for distribution systems - first, because of the size of the network graph partitioning problem and, second, because of the difficulty in properly formulating the desired attributes of such islands or microgrids. Therefore, this paper presents a genetic algorithm based approach that facilitates incorporating multiple objectives for grid partitioning by formulating two types of problems - node allocation and edge elimination - and it considers multiple topological and resilience-enhancing objectives. The performance of the proposed genetic algorithm-based approach is numerically evaluated on multiple test systems as well as on a real distribution feeder in Colorado, United States.

genetic algorithm↗

SU-E-J-04: A Data-Driven, Response-Based, Multi-Criteria Decision Support System for Personalized Lung Radiation Treatment Planning

Purpose: To develop a decision support tool to predict a patient's potential overall survival (OS) and radiation induced toxicity (RIT) based on clinical factors and responses during the course of radiotherapy, and suggest appropriate radiation dose adjustments to improve therapeutic effect. Methods: Important relationships between a patient's basic information and their clinical features before and during the radiation treatment are identified from historical clinical data by using statistical learning and data mining approaches. During each treatment period, a data analysis (DA) module predicts radiotherapy features such as time to local progression (TTLP), time to distant metastases (TTDM), radiation toxicity to different organs, etc., under possible future treatment plans based on patient specifics or responses. An information fusion (IF) module estimates intervals for a patient's OS and the probabilities of RIT from a treatment plan by integrating the outcomes of module DA. A decision making (DM) module calculates “satisfaction” with the predicted radiation outcome based on trade-offs between OS and RIT, and finds the best treatment plan for the next time period via multi-criteria optimization. Results: Using physical and biological data from 130 lung cancer patients as our test bed, we were able to train and implement the 3 modules of our decision support tool. Examples demonstrate how it can help predict a new patient's potential OS and RIT with different radiation dose plans along with how these combinations change with dose, thus presenting a range of satisfaction/utility for use in individualized decision support. Conclusion: Although the decision support tool is currently developed from a small patient sample size, it shows the potential for the improvement of each patient's satisfaction in personalized radiation therapy. The radiation treatment outcome prediction and decision making model needs to be evaluated with more patients and demonstrated for use in radiation treatments for other cancers. P01-CA59827;R01CA142840.

60 APPLIED LIFE SCIENCES↗

Final technical report for: Insertional Mutagenesis of Brachypodium distachyon DE-AI02-07ER64452

Several bioenergy grasses are poised to become a major source of energy in the United States. Despite their increasing importance, we know little about the basic biology underlying the traits that control the utility of grasses as energy crops. Better knowledge of grass biology (e.g. identification of the genes that control cell wall composition, plant architecture, cell size, cell division, reproduction, nutrient uptake, carbon flux, etc.) could be used to design rational strategies for crop improvement and shorten the time required to domesticate these species. The use of an appropriate model system is an efficient way to gain this knowledge. Brachypodium distachyon is a small annual grass with all the attributes needed to be a modern model organism including simple growth requirements, fast generation time, small stature, small genome size and self-fertility. These attributes led to the recommendation in the DOE’s “Breaking the Biological Barriers to Cellulosic Ethanol: A Joint Research Agenda” report to propose developing and using B. distachyon as a model for energy crops to accelerate their domestication. Strategic investments (e.g. genome sequencing) in B. distachyon by the DOE are now bearing fruit and B. distachyon is being used as a model grass by hundreds of laboratories worldwide. Sequence indexed insertional mutants are an extremely powerful tool for both forward and reverse genetics. They allow researchers to order mutants in any gene tagged in the collection by simply emailing a request. The goal of this project was to create a collection of sequence indexed insertional mutants (T-DNA lines) for the model grass Brachypodium distachyon in order to facilitate research by the scientific community. During the course of this grant we created a collection of 23,649 B. distachyon T-DNA lines and identified 26,112 unique insertion sites. The collection can be queried through the project website (http://jgi.doe.gov/our-science/science-programs/plant-genomics/brachypodium/brachypodium-t-dna-collection/) and through the Phytozome genome browser (http://phytozome.jgi.doe.gov/pz/portal.html). The collection has been heavily utilized by the research community and, as of October 23, 2015, 223 orders for 12,069 seeds packets have been filled. In addition to creating this resource, we also optimized methods for transformation and sequencing DNA flanking insertion sites.

09 BIOMASS FUELS↗

Accelerate Nuclear Research and Development by Reducing Time and Cost Spend in the Pre-conceptual Design Phase of Advanced Reactor Experiments

The design process of every new concept, such as advanced nuclear reactors or associated experiments, starts with the pre-conceptual design phase. In this phase, the viability of a wide range of design options needs to be assessed quickly, to understand the operating envelope and its feasibility. A variety of physics models (thermal-hydraulics, neutronics, mechanical design, etc.) has to be considered at this very first design stage and optimum component sizes and materials (e.g. heat exchangers, piping, turbomachinery, coolant type, etc.) have to be chosen for a given set of boundary conditions (e.g. heat source, heat sink, flow rate, etc.). Detailed solutions such as provided by high fidelity methods like computational fluid dynamics (CFD), Monte Carlo methods, etc. and even lower fidelity tools such as system or subchannel codes, etc. are usually not used during the pre-conceptual design due to the relatively long time needed to create input models, the computational time to obtain a solution and the lack of flexibility to quickly investigate different combinations of components, individual component sizes and material properties. High fidelity tools are usually only employed in the conceptual design and later phases once a base concept has been identified during the pre-conceptual design stage. The current practice during the pre-conceptual design stage is that analysts collect the needed equations, material properties, closure laws, etc. and create ad-hoc solutions form scratch for every new problem. There clearly is a lack of a flexible scoping tool that can be used during pre-conceptional design before higher fidelity tools (as described above) come into play. To reduce user errors in ad-hoc solutions and increase fidelity and efficiency, this project aims to investigate and develop a user-friendly scoping tool to address the thermal-hydraulic designing needs during preconceptual experiment design, i.e. Thermal-hydraulic Research Universal Scoping Tool (TRUST). The success of TRUST will provide the nuclear engineers with an easy-to-use and affordable calculator for early reactor system design and optimization.

42 ENGINEERING↗