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At least 685 records · Page 38

Large-Scale Compute-Intensive Analysis via a Combined In-situ and Co-scheduling Workflow Approach

Large-scale simulations can produce tens of terabytes of data per analysis cycle, complicating and limiting the efficiency of workflows. Traditionally, outputs are stored on the file system and analyzed in post-processing. With the rapidly increasing size and complexity of simulations, this approach faces an uncertain future. Trending techniques consist of performing the analysis in situ, utilizing the same resources as the simulation, and/or off-loading subsets of the data to a compute-intensive analysis system. We introduce an analysis framework developed for HACC, a cosmological N-body code, that uses both in situ and co-scheduling approaches for handling Petabyte-size outputs. An initial in situ step is used to reduce the amount of data to be analyzed, and to separate out the data-intensive tasks handled off-line. The analysis routines are implemented using the PISTON/VTK-m framework, allowing a single implementation of an algorithm that simultaneously targets a variety of GPU, multi-core, and many-core architectures.

Big data↗

FTIR and Raman Spectroscopy of Reduced Graphene Oxide Carbon Nanoribbons and Graphene Oxide on Copper (Cu)

In the past couple of decades, carbon nanomaterials produced from graphene and graphite have emerged as one of the more important recently discovered substances. These carbon nanomaterials have been found to exhibit high levels of mechanical strength, thermal resistance, and electrical conductivity, thus having a multitude of applications. Therefore, it is important to identify and analyze their traits in order to maximize their effectiveness. Two spectroscopic techniques employed for such analyses of these materials are Fourier-Transform Infrared (FTIR) and Raman Spectroscopy. The advantages of FTIR and Raman include nondestructive analysis, relatively quick measurements under normal atmospheric conditions, and enhanced sensitivity with high resolution capacity. FTIR Spectroscopy was used in this research project to determine the effects of thermal exfoliation and photoreduction on the functionality groups of a carbon nanomaterial. Raman Spectroscopy was used in this research project to determine the effects of thermal exfoliation and photoreduction on the intensity of the disorder peak, which is greater in intensity if the carbon nanomaterial exhibits greater amounts of functionalities or defects in the graphitic material. There were two sample types which were analyzed with both FTIR and Raman Spectroscopy for the research project: graphene nanoribbons and graphene oxide. The m-grade graphene nanoribbons (GNRs) were produced from m-grade carbon nanotubes (CNTs) via Tour's method. The graphene oxide (GO) was produced from graphene via Tour's method, sonicated and centrifuged, dip-coated onto Copper (Cu) foil, and then photoreduced under a UV light source. FTIR measurements and analyses were conducted using a Jasco FTIR Spectrometer. Raman measurements and analyses were conducted using a Jasco Laser Raman Spectrometer. Tasks and techniques for this project included photoreduction, dip-coating, corrosion testing, FTIR and Raman data collection and analysis, and improvement of data collection for the Raman Spectrometer. GNRs exfoliated and reduced (deoxygenation) at 270 deg. C in air showed a significant decrease in O functionalities according to FTIR. However, Raman revealed that a large increase in graphene planar and edge defects are present as indicated by the disorder band at 1340 cm-1. Further optimization could be performed by thermal exfoliation at lower temperatures assuming a need for fewer structural defects. Graphene oxide coatings showed clear reduction with an increase with photoreduction time. Raman revealed that the reduced graphene oxide films had less disruption in the planar phonon lattice vibrations which indicates that the structure is returning to sp2 hybridization of pristine graphene without adding structural defects.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Weatherization Updates From the National Renewable Energy Laboratory

The National Renewable Energy Laboratory (NREL) provides technical assistance and research to support high-quality work and highly qualified workers in the weatherization and home performance industry. NREL staff will provide updates on their work on the Standard Work Specifications, Home Energy Professional Certifications, Continuous Improvement Workshops, workforce training and research, and other topics.

continuous improvement↗

Analyzing the impact of design factors on solar module thermomechanical durability using interpretable machine learning techniques

Solar modules in utility-scale systems are expected to maintain decades of lifetime to rival conventional energy sources. However, cyclic thermomechanical loading often degrades their long-term performance, highlighting the importance of effective design to mitigate thermal expansion mismatches between module materials. Given the complex composition of solar modules, isolating the impact of individual components on overall durability remains a challenging task. In this work, we analyze a comprehensive data set that comprises bill-of-materials (BOM) and thermal cycling power loss from 251 distinct module designs to identify the predominant design factors and their impacts on the thermomechanical durability of modules. The methodology of our analysis combines machine learning modeling (random forest) and Shapley additive explanation (SHAP) to correlate design factors with power loss and interpret the model’s decision-making. The interpretation reveals that silicon type (monocrystalline or polycrystalline), encapsulant thickness, busbar numbers, and wafer thickness predominantly influence the degradation. With lower power loss of around 0.6% on average in the SHAP analysis, monocrystalline cells present better durability than polycrystalline cells. This finding is further substantiated by statistical testing on our raw data set. The SHAP analysis also demonstrates that while thicker encapsulants lead to reduced power loss, further increasing their thickness over around 0.6 to 0.7 mm does not yield additional benefits, particularly for the front side one. In addition, other important BOM features such as the number of busbars are analyzed. This study provides a blueprint for utilizing explainable machine learning techniques in a complex material system and can potentially guide future research on optimizing the design of solar modules.

14 SOLAR ENERGY↗

Calibration of Car-Following Models Using a Dual Genetic Algorithm with Central Composite Design

We report the calibration of microscopic traffic simulation models has received much attention in the simulation field. Although no standard has been established for it, a genetic algorithm (GA) has been widely employed in recent literature because of its high efficiency to find solutions in such optimization problems. However, the performance still falls short in simulation analyses to support fast decision making. This paper proposes a new calibration procedure using a dual GA and central composite design (CCD) in order to improve the efficiency. The calibration exercise goes through three major sequential steps: (1) experimental design using CCD for a quadratic response surface model (RSM) estimation, (2) 1st GA procedure using the RSM with CCD to find a near-optimal initial population for a next step, and (3) 2nd GA procedure to find a final solution. The proposed method was applied in calibrating the Gipps car-following model with respect to maximizing the likelihood of a spacing distribution between a lead and following vehicle. In order to evaluate the performance of the proposed method, a conventional calibration approach using a single GA was compared under both simulated and real vehicle trajectory data. It was found that the proposed approach enhances the optimization speed by starting to search from an initial population that is closer to the optimum than that of the other approach. This result implies the proposed approach has benefits for a large-scale traffic network simulation analysis. Finally, this method can be extended to other optimization tasks using GA in transportation studies.

42 ENGINEERING↗

Analysis of the Sludge Batch 8 (Macrobatch 10) DWPF Pour Stream Glass Sample

To meet the objectives of the Defense Waste Processing Facility (DWPF) Glass Product Control Program, DWPF and Saltstone Facility Engineering (D&S-FE) requested that Savannah River National Laboratory (SRNL) analyze a radioactive glass pour stream (PS) sample collected during the processing of Sludge Batch 8 (SB8), also known as Macrobatch 10 (MB10). The analyses requested by D&S-FE (listed as tasks one through five in the Technical Task Request (TTR) included determination of the chemical and radionuclide composition, performance of the Product Consistency Test (PCT), and measurement of glass density and REDOX state. The tasks associated with accomplishing these analyses were controlled under a Task Technical and Quality Assurance Plan (TTQAP) and Analytical Study Plan. This report provides results from the requested analyses and satisfies deliverable number five of the TTR.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Fission Meter Information Barrier Attribute Measurement System: Task 1 Report: Document existing Fission Meter neutron IB system

An SNM attribute Information Barrier (IB) system was developed for a 2011 US/UK Exercise. The system was modified and extensively tested in a 2013-2014 US-UK Measurement Campaign. This work demonstrated rapid deployment of an IB system for potential treaty use. The system utilizes an Ortec Fission Meter neutron multiplicity counter and custom computer code. The system demonstrates a proof-of-principle automated Pu-240 mass determination with an information barrier. After a software start command is issued, the system automatically acquires and downloads data, performs an analysis, and displays the results. This system conveys the results of a Pu mass threshold measurements in a way the does not reveal sensitive information. In full IB mode, only red/green ‘lights’ are displayed in the software. In test mode, more detailed information is displayed. The code can also read in, analyze, and display results from previously acquired or simulated data. Because the equipment is commercial-off-the-shelf (COTS), the system demonstrates a low-cost short-lead-time technology for treaty SNM attribute measurements. A deployed system will likely require integration of additional authentication and tamper-indicating technologies. This will be discussed for the project in this and future progress reports.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Model-Based Extracted Water Desalination System for Carbon Sequestration

Over the last 1.5 years, GE Global Research and Pennsylvania State University defined a model-based, scalable, and multi-stage extracted water desalination system that yields clean water, concentrated brine, and, optionally, salt. The team explored saline brines that ranged across the expected range for extracted water for carbon sequestration reservoirs (40,000 up to 220,000 ppm total dissolved solids, TDS). In addition, the validated the system performance at pilot scale with field-sourced water using GE’s pre-pilot and lab facilities. This project encompassed four principal tasks, in addition to Project Management and Planning: 1) identify a deep saline formation carbon sequestration site and a partner that are suitable for supplying extracted water; 2) conduct a techno-economic assessment and down-selection of pre-treatment and desalination technologies to identify a cost-effective system for extracted water recovery; 3) validate the downselected processes at the lab/pre-pilot scale; and 4) define the scope of the pilot desalination project. Highlights from each task are described below: Deep saline formation characterization The deep saline formations associated with the five DOE NETL 1260 Phase 1 projects were characterized with respect to their mineralogy and formation water composition. Sources of high TDS feed water other than extracted water were explored for high TDS desalination applications, including unconventional oil and gas and seawater reverse osmosis concentrate. Technoeconomic analysis of desalination technologies Techno-economic evaluations of alternate brine concentration technologies, including humidification-dehumidification (HDH), membrane distillation (MD), forward osmosis (FO), turboexpander-freeze, solvent extraction and high pressure reverse osmosis (HPRO), were conducted. These technologies were evaluated against conventional falling film-mechanical vapor recompression (FF-MVR) as a baseline desalination process. Furthermore, a quality function deployment (QFD) method was used to compare alternate high TDS desalination technologies to FF-MVR. High pressure reverse osmosis was found to a be a promising alternative desalination technology. A deep-dive technoeconomic analysis of HPRO was performed, including Capex and Opex estimates, for seawater RO (SWRO). Additionally, two additional cases were explored: 1) a comparison of a SWRO plus HPRO system to the option of doubling the size of a standard seawater RO system to achieve the same total pure water recovery rate; and 2) a flue gas desulfurization wastewater treatment zero-liquid discharge (ZLD) application, where preconcentration with RO (SWRO or SWRO + HPRO) before evaporation and crystallization was compared to FF-MVR and crystallization technologies without RO preconcentration. Pre-pilot process validation Pre-pilot-scale tests were conducted using field production water to validate key process steps for extracted water pretreatment. Approximately 5,000 gallons of field produced water was processed through, microfiltration, ultrafiltration, and steam regenerable sorbent operations. Smaller quantities were processed through microclarification. In addition, analytical methods (purge-and-trap gas chromatography and Hach TOC analytical methods) were validated. Lab-scale HPRO elements were constructed and tested at high pressures, to identify and mitigate technical risks of the technology. Lastly, improvements in RO membrane materials were identified as the necessary next step to achieve further improvement in element performance at high pressure. Scope of Field Pilot A field pilot for extracted water pretreatment was designed.

20 FOSSIL-FUELED POWER PLANTS↗

Accelerating k-NN Algorithm with Hybrid MPI and OpenSHMEM

Machine Learning algorithms are benefiting from the continuous improvement of programming models, including MPI, MapReduce and PGAS. k-Nearest Neighbors (k-NN) algorithm is a widely used machine learning algorithm, applied to supervised learning tasks such as classification. Several parallel implementations of k-NN have been proposed in the literature and practice. However, on high-performance computing systems with high-speed interconnects, it is important to further accelerate existing designs of the k-NN algorithm through taking advantage of scalable programming models. To improve the performance of k-NN on large-scale environment with InfiniBand network, this paper proposes several alternative hybrid MPI+OpenSHMEM designs and performs a systemic evaluation and analysis on typical workloads. The hybrid designs leverage the one-sided memory access to better overlap communication with computation than the existing pure MPI design, and propose better schemes for efficient buffer management. The implementation based on k-NN program from MaTEx with MVAPICH2-X (Unified MPI+PGAS Communication Runtime over InfiniBand) shows up to 9.0% time reduction for training KDD Cup 2010 workload over 512 cores, and 27.6% time reduction for small workload with balanced communication and computation. Experiments of running with varied number of cores show that our design can maintain good scalability.

Lin, Jian↗

ARCH: Large-scale knowledge graph via aggregated narrative codified health records analysis

Objective: Electronic health record (EHR) systems contain a wealth of clinical data stored as both codified data and free-text narrative notes (NLP). The complexity of EHR presents challenges in feature representation, information extraction, and uncertainty quantification. Here, to address these challenges, we proposed an efficient Aggregated naRrative Codified Health (ARCH) records analysis to generate a large-scale knowledge graph (KG) for a comprehensive set of EHR codified and narrative features. Methods: Using data from 12.5 million Veterans Affairs patients, ARCH first derives embedding vectors and generates similarities along with associated p-values to measure the strength of relatedness between clinical features with statistical certainty quantification. Next, ARCH performs a sparse embedding regression to remove indirect linkage between features to build a sparse KG. Finally, ARCH was validated on various clinical tasks, including detecting known relationships between entity pairs, predicting drug side effects, disease phenotyping, as well as sub-typing Alzheimer’s disease patients. Results: ARCH produces high-quality clinical embeddings and KG for over 60,000 codified and narrative EHR concepts. The KG and embeddings are visualized in the R-shiny powered web-API.3 ARCH achieved high accuracy in detecting EHR concept relationships, with AUCs of 0.926 (codified) and 0.861 (NLP) for similar EHR concepts, and 0.810 (codified) and 0.843 (NLP) for related pairs. It detected drug side effects with a 0.723 AUC, which improved to 0.826 after fine-tuning. Using both codified and NLP features, the detection power increased significantly. Compared to other methods, ARCH has superior accuracy and enhances weakly supervised phenotyping algorithms’ performance. Notably, it successfully categorized Alzheimer’s patients into two subgroups with varying mortality rates. Conclusion: The proposed ARCH algorithm generates large-scale high-quality semantic representations and knowledge graph for both codified and NLP EHR features, useful for a wide range of predictive modeling tasks.

Electronic health records↗

Estimating the density of states of frustrated spin systems

Abstract Estimating the density of states (DOS) of systems with rugged free energy landscapes is a notoriously difficult task of the utmost importance in many areas of physics ranging from spin glasses to biopolymers. DOS estimation has also recently become an indispensable tool for the benchmarking of quantum annealers when these function as samplers. Some of the standard approaches suffer from a spurious convergence of the estimates to metastable minima, and these cases are particularly hard to detect. Here, we introduce a sampling technique based on population annealing enhanced with a multi-histogram analysis and report on its performance for spin glasses. We demonstrate its ability to overcome the pitfalls of other entropic samplers, resulting in some cases in large scaling advantages that can lead to the uncovering of new physics. The new technique avoids some inherent difficulties in established approaches and can be applied to a wide range of systems without relevant tailoring requirements. Benchmarking of the studied techniques is facilitated by the introduction of several schemes that allow us to achieve exact counts of the degeneracies of the tested instances.

Barash, Lev (ORCID:000000022298785X)↗

PaRSEC: Scalability, flexibility, and hybrid architecture support for task-based applications in ECP

This paper highlights the most significant enhancements made to PaRSEC, a scalable task-based runtime system designed for hybrid machines, during the Exascale Computing Project (ECP). The enhancements focus on expanding the capabilities of PaRSEC to address the evolving landscape of parallel computing. Notable achievements include the integration of support for three major types of accelerators (NVIDIA, AMD, and Intel GPUs), the refinement and increased flexibility of the communication subsystem, and the introduction of new programming interfaces tailored for irregular applications. Additionally, the project resulted in the development of powerful debugging and performance analysis tools aimed at assisting users in understanding and optimizing their applications. We present a comprehensive demonstration of these advancements through a series of benchmarks and applications within ECP and beyond, thereby showcasing the enhanced capabilities of PaRSEC across the diverse architectures within the ECP, providing valuable insights into the runtime system’s adaptability and performance across varied computing environments.

Bouteiller, Aurelien↗

NRC Multiphysics Analysis Capability Deployment (FY2021 - Part 2)

This report details the progress and activities of Idaho National Laboratory (INL) on the Nuclear Regulatory Commission (NRC) project “Development and Modeling Support for Advanced Non-Light Water Reactors.” Task 4b was completed for this report. INL developed a sample problem showing how to use Serpent 2 to calculate macroscopic cross sections for use in Griffin for a typical sodium fast reactor Unprotected Loss of Flow (ULOF) transient. The complicating factor is the relatively large axial gradient of the coolant (and hence fuel) temperature and its evolution during the transient. A 3D Griffin model of the Advanced Burner Test Reactor (ABTR) is coupled to the System Analysis Module (SAM) to perform the ULOF transient. The model includes various explicit feedback mechanisms for fast reactors, including Doppler, radial expansion from the displacement of the support plate, and axial expansion from the displacement of the fuel pins. The results for the ULOF transient are consistent with published values. We observed small effects in the transient results that arise from the superhomogenization equivalence correction of uniform and nonuniform temperature data sets, but they diminish as more dominant reactivity mechanisms are added to the model. Potential improvements to the neutronics model include: adding the differential control rod and sodium feedback mechanisms, implementing cross section re-homogenization based on the partial volume of the various materials, and enhancing the kinetics parameters. Furthermore, the fluids model only includes four subchannels to represent the entire active core due to performance limitations in SAM when attempting to model one subchannel per assembly.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Models to Incorporate Reaction Mechanisms into DG-OSPREY: Fixed-Bed Simulations for Organic Iodides Capture Using Ag 0 Z

As one of the most potent radioisotopes released during spent nuclear fuel reprocessing, 129 I is strictly regulated and must be removed before discharge. Organic iodides (primarily alkyl iodides with different chain lengths, i.e., CH 3 I, C 4 H 9 I, and C 12 H 25 I) comprise ~2% of the total iodine in the reprocessing off-gases and are primarily present in vessel off-gas (VOG). Reduced silver mordenite (Ag 0 Z) is predominantly considered for the removal of radioiodine; however, its capture performance and underlying interaction processes with long-chain organic iodides are not fully understood. Two major tasks were accomplished in this study. First, to improve upon the previous experimental studies where Ag 0 Z was used to capture CH 3 I, C 4 H 9 I, and C 12 H 25 I at different concentrations, we comprehensively investigated the corresponding capture mechanisms by characterizing fully loaded Ag 0 Z samples. Second, computational codes were implemented to perform fixed-bed simulations that account for transport and reaction mechanisms. Scanning electron microscopy with energy dispersive X-ray analysis (SEM-EDX), powder X-ray diffraction (PXRD), UV-visible diffuse reflectance spectroscopy (UV-vis DRS), and thermogravimetric analysis (TGA) were conducted on Ag 0 Z samples that are saturated with I 2 , CH 3 I, C 4 H 9 I, and C 12 H 25 I), respectively. Results indicate that AgI is the predominant adsorption product regardless of the adsorbed iodine species, yet alkyl iodides with different carbon chain lengths may have different compositions of α- and γ-AgI. Synchrotron pair distribution function (PDF) measurements and TGA coupled with a Fourier transformed infrared detector (TGA FTIR) have been performed, and experimental data are currently analyzed. Results are expected to provide further insights into the adsorption mechanisms. The fixed-bed capture performance for CH 3 I was successfully simulated by solving mathematical equations that describe the underlying transport processes and adsorption reactions. The computational framework, Catalytic After Treatment System (CATS), that was originated in our research group, was used to solve the governing equations. Kinetic parameters, including the pore diffusivity and reaction rate constant were obtained by optimization techniques using data from thin-bed experiments performed at Oak Ridge National Laboratory. The performance of a deep bed predicted using the optimized parameters showed promising agreement with the experimental data.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Saint Joseph's University Institute for Environmental Stewardship

Task A: Examination of the physiological, morphological, and reproductive responses of Panicum virgatum (switchgrass) cultivars identified as potential biofuel producing cultivars as well as naturally-occurring varieties of switchgrass to projected changes in climate for the central portion of the United States. This project was a multi-year project set in a field site located at the Konza Prairie Biological Station near Manhattan, KS USA. The major objective of the study was to understand the physiological and growth responses of the important biofuel grass species, Panicum virgatum (switch grass) to simulated changes in precipitation expected for the Central Plains region of the United States. Population level adaptation to broad-scale regional climates or within-population variation in genome size of this genetically and phenotypically diverse C4 grass species may influence the responses to future precipitation variability associated with climate change. Therefore, we investigated switchgrass responses to water variability between natural populations collected across latitudinal gradient and populations. P. virgatum plants from natural populations originating from Kansas, Oklahoma, and Texas received frequent, small precipitation events (“ambient’) or infrequent, large precipitation events (‘altered”) to simulate contrasting rainfall variability expected from this region. We measured leaf-level physiology, aboveground biomass varied significantly by population origin but did not differ by genome size. Our results suggest that trait variation in P. virgatum is primarily attributed to population-level adaptation across latitudinal gradient, not genome size, and that neither population-level adaptation nor genome size may be important predictors of P. virgatum responses to future climatic conditions. Based solely on the data presented here, the most important consideration when deciding what varieties of switchgrass to cultivate for biofuel feedstocks under future climate scenarios is local adaptation and not necessarily genome size as has been hypothesized in the literature. Task B: Installation of an extensive green roof system on the Science Center at Saint Joseph's University for research, research-training and educational outreach activities. An experimental green roof system was designed and installed by an outside contractor (Roofmeadows) on the roof of the Science Center at Saint Joseph's University. The roof system includes four test plots, each with a different drainage system, instrumentation to monitor storm water retention, roof deck temperature, heat flux into and out of the building, rain fall, wind speed and direction, relative humidity and heat emission from the roof system. The vegetative roof was planted with 26 species of plants, distributed throughout the roof area, to assess species/variety growth and coverage characteristics, both in terms of the different drain layer systems, and in terms of the different exposures along the north to south axis of the building. Analysis of the drain layer performance, in terms of storm water retention, shows that the aggregate (stone) drainage layer system performed the best, with the moisture management mat system second, and the geotextile drain layer and reservoir sheet layer systems coming in last. This information is of value in the planning and design of vegetative roof systems since the different types of drainage layer systems have different installation costs and different weights. The different drainage layer systems also seem to be having an impact on plant growth and spread with the test plot with the reservoir sheet layer actually having the poorest plant coverage and plant spread of all areas of the roof studied. Plant growth performance analysis is ongoing, but significant differences have been observed in the third growing season ('13) along the north to south axis, with most species doing better towards the northern end of the roof (in terms of percent ground coverage and plant spread and reproduction). Interestingly, plant growth in all four of the test plots was reduced relative to the lower areas of the roof (the lower area was ca. 2 inches lower than the test plots, due to the space needed for sensors under the plots. The lower roof area uses an aggregate drain layer comparable to that in the third test plot), even when accounting for the north to south differences. The reasons for these differences are not clear and studies are underway to examine the impact of wind scour, drainage rates, temperature, and other factors. This information will be of value to planners of extensive vegetative roof systems in the Philadelphia (and broader) region, since plant growth and roof system overall performance is influenced by local climate, making broad generalizations of performance difficult. Task C: Education and community outreach efforts by the IES involving conferences at SJU, presentations by faculty and students off campus, and educational signage. The Institute for Environmental Stewardship hosted three storm water management workshops on the SJU campus in Philadelphia, in collaboration with the Lower Merion Conservancy, a not-for-profit organization located in Montgomery County, PA. These workshops were free and open to the public. The three workshops (held each year in March) drew more than 200 participants total. The presenters included local and state government agencies, not for profit organizations involved in storm water and open space preservation, designers, engineers, planners and others. Feedback was uniformly positive and we plan to continue the workshops for the foreseeable future. Educational signage has been installed at four locations on campus to explain campus infrastructure related to storm water (rain gardens, vegetative roof and green facades), as well as detailed signage installed on the Science Center roof for the vegetative roof system. More than 100 people (from in and outside of SJU) have thus far participated in tours of the roof system. A digital signage system has been installed in the adjacent library and this system provides information about the vegetative roof project and other efforts. A web camera system for the roof has also been installed and the video will be simulcast to the digital signage and with web site (www.sju.edu/ies) in the near future.

09 BIOMASS FUELS↗

GronOR: Massively Parallel and GPU-Accelerated Non-Orthogonal Configuration Interaction for Large Molecular Systems

GronOR is a program package for non-orthogonal configuration interaction calculations for an electronic wave function built in terms of anti-symmetrized products of multi-configuration molecular fragment wave functions. The two-electron integrals that have to be processed may be expressed in terms of atomic orbitals or in terms of an orbital basis determined from the molecular orbitals of the fragments. The code has been specifically designed for execution on distributed memory massively parallel and Graphics Processing Unit (GPU)-accelerated computer architectures, using an MPI+OpenACC/OpenMP programming approach. The task-based execution model used in the implementation allows for linear scaling with the number of nodes on the largest pre-exascale architectures available, provides hardware fault resiliency, and enables effective execution on systems with distinct central processing unit-only and GPU-accelerated partitions. The code interfaces with existing multi-configuration electronic structure codes that provide optimized molecular fragment orbitals, configuration interaction coefficients, and the required integrals. Algorithm and implementation details, parallel and accelerated performance benchmarks, and an analysis of the sensitivity of the accuracy of results and computational performance to thresholds used in the calculations are presented.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Pretreatment of Crystalline Silicotitanate (CST) and development of a digestion standard to support Tank Closure Cesium Removal (TCCR)

In support of Savannah River Remediation’s (SRR) deployment of an ion exchange process to remove radioactive cesium from waste supernate, referred to as the Tank Closure Cesium Removal (TCCR) process, SRNL was tasked with validating the field protocol for pretreating the crystalline silicotitanate (CST) material to be used in the columns, preparing CST for use in in-tank batch contact testing, as well as developing a digestion standard to verify complete dissolution of the CST prior to characterization after each in-tank batch contact test. A procedure (SRNL L29 Manual, ITS-0229) was developed to document the protocol for pretreating CST utilizing conditions similar to what will be performed in the field. Analysis of material pretreated following the procedure confirmed similar conversion to the Na+ form of the resin as had been obtained previously. Portions of the batch of material pretreated according to the developed protocol were also used for development of a digestion standard. Results from digestion and analysis of this standard were used to establish a set of control limits for the measured Ti, Zr, and Nb concentrations in digested CST material. An aliquot of this standard CST material will be digested and analyzed alongside each in-tank batch contact sample, and the measured concentrations of Ti, Zr, and Nb will be compared against the established control limits to confirm complete digestion has occurred.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Analyses to support waste disposition of SNS Inner Reflector Plug

The Spallation Neutron Source Inner Reflector Plug (IRP) is scheduled for replacement. It reached end of life-time because of moderator neutron poison and decoupler burn-out, which is used for shaping neutron pulses. The replacement of IRP is a complex task due to its location in the area receiving high irradiation, being under significant amount of shielding, and size, which requires removal in segments. In order to support the disposal of spent IRP, waste characterization analyses are performed. These analyses include an accurate estimate of the radionuclide inventory and the residual dose rate. Using this data, the package class is determined for the and appropriate containers for temporary storage and subsequent transport are assigned. Analyses are performed in four steps: a radiation transport analysis of the radiation environment for producing the flux and isotope production information using MCNPX, a multi-cell transmutation analysis based n CINDER90, the generation of decay gamma source terms, and the gamma transport analyses of the decay gammas arriving at residual dose rates again using MCNPX. . Due to the complexity of the geometry of the lower segment, transport analyses for the residual dose rate require elaborate work for the source terms definition.

Popova, Irina I.↗