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DOE OSTI2015

Data handling with SAM and art at the NO v A experiment

During operations, NOvA produces between 5,000 and 7,000 raw files per day with peaks in excess of 12,000. These files must be processed in several stages to produce fully calibrated and reconstructed analysis files. In addition, many simulated neutrino interactions must be produced and processed through the same stages as data. To accommodate the large volume of data and Monte Carlo, production must be possible both on the Fermilab grid and on off-site farms, such as the ones accessible through the Open Science Grid. To handle the challenge of cataloging these files and to facilitate their off-line processing, we have adopted the SAM system developed at Fermilab. SAM indexes files according to metadata, keeps track of each file's physical locations, provides dataset management facilities, and facilitates data transfer to off-site grids. To integrate SAM with Fermilab's art software framework and the NOvA production workflow, we have developed methods to embed metadata into our configuration files, art files, and standalone ROOT files. A module in the art framework propagates the embedded information from configuration files into art files, and from input art files to output art files, allowing us to maintain a complete processing history within our files. Embedding metadata in configuration files also allows configuration files indexed in SAM to be used as inputs to Monte Carlo production jobs. Further, SAM keeps track of the input files used to create each output file. Parentage information enables the construction of self-draining datasets which have become the primary production paradigm used at NOvA. In this study we will present an overview of SAM at NOvA and how it has transformed the file production framework used by the experiment.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2021

Improving reproducibility in synchrotron tomography using implementation-adapted filters

For reconstructing large tomographic datasets fast, filtered backprojection-type or Fourier-based algorithms are still the method of choice, as they have been for decades. These robust and computationally efficient algorithms have been integrated in a broad range of software packages. The continuous mathematical formulas used for image reconstruction in such algorithms are unambiguous. However, variations in discretization and interpolation result in quantitative differences between reconstructed images, and corresponding segmentations, obtained from different software. This hinders reproducibility of experimental results, making it difficult to ensure that results and conclusions from experiments can be reproduced at different facilities or using different software. In this paper, a way to reduce such differences by optimizing the filter used in analytical algorithms is proposed. These filters can be computed using a wrapper routine around a black-box implementation of a reconstruction algorithm, and lead to quantitatively similar reconstructions. Use cases for this approach are demonstrated by computing implementation-adapted filters for several open-source implementations and applying them to simulated phantoms and real-world data acquired at the synchrotron. Our contribution to a reproducible reconstruction step forms a building block towards a fully reproducible synchrotron tomography data processing pipeline.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2015

Measurements of SNAC2 area dosimeters placed in different configurations around the PROSPERO reactor and comparison with TRIPOLI-4 calculations

In the context of criticality accident alarm system tests, several experiments were carried out in 2013 on the PROSPERO reactor to study the response to neutron and gamma of different devices and dosimeters, particularly on the SNAC2 dosimeter. This article presents the results of this criticality dosimeter in different configurations, and compares the experimental measurements with the results of calculation performed with the TRIPOLI-4 Monte-Carlo Neutral Particles transport code. PROSPERO is a metallic critical assembly managed by the Criticality, Neutron Science and Measurement Department located at the French CEA Research Center of Valduc. The core, surrounded by a reflector of depleted uranium, is composed of 2 horizontal cylindrical blocks made of a highly enriched uranium alloy which can be placed in contact, and of 4 depleted uranium control rods which allow the reactor to be driven. This reactor, placed in a cell 10 m x 8 m x 6 m high, with 1.4-meter-thick concrete walls, is used as a fast neutron spectrum source and is operated at stable power level in delayed critical state, which can vary from 3 mW to 3 kW. PROSPERO is extensively used for electronic hardening or to study the effect of the neutrons on various materials. The SNAC2 criticality dosimeter is a zone dosimeter allowing the off line measurement of criticality accident neutron doses. This dosimeter consists of the pile up of seven activation foils embedded into a 23 mm diameter x 21 mm height cadmium container. The activation measurement of each foil, using a gamma spectroscopy technique, gives information about the neutron reaction rates. The SNAC2 software allows the spectrum unfolding from these values, taking into account the hypothesis of a particular spectrum shape, in three components: a Maxwell spectrum component for the thermal range, a 1/E component for the epithermal range, and a Watt spectrum component for the high energy range. Moreover, from the neutron spectrum, the SNAC software can calculate the neutron fluence integrated by the dosimeter and the neutron dose. During the 3 weeks measurement campaign many radioprotection devices were used. To modify the spectrum seen by these devices, several shields of various thicknesses made of concrete or polyethylene, with or without cadmium covers, were placed in the PROSPERO cell. These devices allow the study of criticality accident spectra in several environments: from metal to pseudo liquid. The fluxes measured by the SNAC2 devices were compared with TRIPOLI-4 calculations. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2016

A domain-specific compiler for a parallel multiresolution adaptive numerical simulation environment

This paper describes the design and implementation of a layered domain-specific compiler to support MADNESS---Multiresolution ADaptive Numerical Environment for Scientific Simulation. MADNESS is a high-level software environment for the solution of integral and differential equations in many dimensions, using adaptive and fast harmonic analysis methods with guaranteed precision. MADNESS uses k-d trees to represent spatial functions and implements operators like addition, multiplication, differentiation, and integration on the numerical representation of functions. The MADNESS runtime system provides global namespace support and a task-based execution model including futures. MADNESS is currently deployed on massively parallel supercomputers and has enabled many science advances. Due to the highly irregular and statically unpredictable structure of the k-d trees representing the spatial functions encountered in MADNESS applications, only purely runtime approaches to optimization have previously been implemented in the MADNESS framework. This paper describes a layered domain-specific compiler developed to address some performance bottlenecks in MADNESS. The newly developed static compile-time optimizations, in conjunction with the MADNESS runtime support, enable significant performance improvement for the MADNESS framework.

Rajbhandari, Samyam↗

DOE OSTI2015

An Investigation of Catastrophic Failure in Solid-State Lamps Exposed to Harsh Environment Operational Conditions

Today’s lighting technology is steadily becoming more energy efficient and less toxic to the environment since the passing of the Energy Independence and Security Act of 2007 (EISA) [1]. EISA has mandated a higher energy efficiency standard for lighting products and the phase out of the common incandescent lamp. This has led lighting manufacturers to pursue solid-state lighting (SSL) technologies for consumer lighting applications. However, two major roadblocks are hindering the transition process to SSL lamps: cost and quality. In order to cut cost, manufactures are moving towards cheaper packaging materials and a variety of package architecture construction techniques which may potentially erode the quality of the lamp and reduce its survivability in everyday applications. Typically, SSL lamps are given product lifetimes of over twenty years based off of the IES TM-21-11 lighting standard which does not include moisture effects or large operational temperatures [2]. A group of recently released off-the-shelf lamps have undergone a steady-state temperature humidity bias life test of 85°C/85%RH (85/85) to investigate the reliability in harsh environment applications. The lack of accelerated test methods for lamps to assess reliability prior to introduction into the marketplace does not exist in literature. There is a need for SSL physics based models for the assessment and prediction of a lamp’s lifetime which is being spearheaded by the DOE [3]. In order to be fully accepted in the marketplace, SSL lamps must be able to perform similarly to incandescent lamps in these environments, as well as live up to the lifetime claims of manufacturers. A lamp’s package architecture must be designed with performance factors in mind, as well as address some of the known and published package related failure mechanisms, such as carbonization of the encapsulant material, delamination, encapsulant yellowing, lens cracking, and phosphor thermal quenching [4]. Each failure mechanism produces the similar failure mode of lumen degradation predominately due to two contributing factors: high junction temperature and moisture ingress. The current state-of-the-art has focused on individual areas of the lamp, such as the LED chip, substrate material, electrical driver design and thermal management techniques. [5] – [16] Looking at the lamp as a whole is a novel approach and has not been seen before in literature. This work followed the JEDEC standard JESD22-A101C of 85/85 with a one hour interval of applied voltage followed by a one hour interval of no applied voltage [17]. This test was performed continuously for each SSL lamp until it became nonoperational, i.e. did not turn on. Periodically, photometric measurements were taken following the IES LM-79-08 standard at room temperature using an integrating sphere, a spectrometer, and lighting software. The overall health of the SSL lamps was assed using the relative luminous flux (RLF), correlated color temperature (CCT) and the color difference (Δu'v') using the Euclidean distance of the CIE 1976 color space coordinates. Finally, a Weibull analysis was completed to compare the characteristic lifetime of the SSL lamp to the actual rated lifetime. An important result from this work shows that the rated lifetime does not come close to the actual lifetime when the SSL lamps are used in a harsh humid environment which is fairly common in outdoor applications across the U.S. Also, the photometric results are presented for the entire lifetime of each SSL lamp under test.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2015

SU-E-J-108: Solving the Chinese Postman Problem for Effective Contour Deformation

Purpose: To develop a practical approach for accurate contour deformation when deformable image registration (DIR) is used for atlas-based segmentation or contour propagation in image-guided radiotherapy. Methods: A contour deformation approach was developed on the basis of 3D mesh operations. The 2D contours represented by a series of points in each slice were first converted to a 3D triangular mesh, which was deformed by the deformation vectors resulting from DIR. A set of parallel 2D planes then cut through the deformed 3D mesh, generating unordered points and line segments, which should be reorganized into a set of 2D contour points. It was realized that the reorganization problem was equivalent to solving the Chinese Postman Problem (CPP) by traversing a graph built from the unordered points with the least cost. Alternatively, deformation could be applied to a binary mask converted from the original contours. The deformed binary mask was then converted back into contours at the CT slice locations. We performed a qualitative comparison to validate the mesh-based approach against the image-based approach. Results: The DIR could considerably change the 3D mesh, making complicated 2D contour representations after deformation. CPP was able to effectively reorganize the points in 2D planes no matter how complicated the 2D contours were. The mesh-based approach did not require a post-processing of the contour, thus accurately showing the actual deformation in DIR. The mesh-based approach could keep some fine details and resulted in smoother contours than the image-based approach did, especially for the lung structure. Image-based approach appeared to over-process contours and suffered from image resolution limits. The mesh-based approach was integrated into in-house DIR software for use in routine clinic and research. Conclusion: We developed a practical approach for accurate contour deformation. The efficiency of this approach was demonstrated in both clinic and research applications. This work was partially supported by Cancer Prevention & Research Institute of Texas (CPRIT) RP110562.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

Design and validation of an MR-conditional robot for transcranial focused ultrasound surgery in infants

Purpose: Current treatment of intraventricular hemorrhage (IVH) involves cerebral shunt placement or an invasive brain surgery. Magnetic resonance-guided focused ultrasound (MRgFUS) applied to the brains of pediatric patients presents an opportunity to treat IVH in a noninvasive manner, termed “incision-less surgery.” Current clinical and research focused ultrasound systems lack the capability to perform neonatal transcranial surgeries due to either range of motion or dexterity requirements. A novel robotic system is proposed to position a focused ultrasound transducer accurately above the head of a neonatal patient inside an MRI machine to deliver the therapy. Methods: A clinical Philips Sonalleve MRgFUS system was expanded to perform transcranial treatment. A five degree-of-freedom MR-conditional robot was designed and manufactured using MR compatible materials. The robot electronics and control were integrated into existing Philips electronics and software interfaces. The user commands the position of the robot with a graphical user interface, and is presented with real-time MR imaging of the patient throughout the surgery. The robot is validated through a series of experiments that characterize accuracy, signal-to-noise ratio degeneration of an MR image as a result of the robot, MR imaging artifacts generated by the robot, and the robot’s ability to operate in a representative surgical environment inside an MR machine. Results: Experimental results show the robot responds reliably within an MR environment, has achieved 0.59 ± 0.25 mm accuracy, does not produce severe MR-imaging artifacts, has a workspace providing sufficient coverage of a neonatal brain, and can manipulate a 5 kg payload. A full system demonstration shows these characteristics apply in an application environment. Conclusions: This paper presents a comprehensive look at the process of designing and validating a new robot from concept to implementation for use in an MR environment. An MR conditional robot has been designed and manufactured to design specifications. The system has demonstrated its feasibility as a platform for MRgFUS interventions for neonatal patients. The success of the system in experimental trials suggests that it is ready to be used for validation of the transcranial intervention in animal studies.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2022

Useful python scripts

SAND2023-11904O This collection of original scripts is made up of Python, Makefile, and Vim. Each script performs a single commonly used function in an encapsulated manner that can easily integrate into larger application-specific software. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Penney, Keith↗

DOE OSTI2025

DEMographic MicrOSimulation (DEMOS) v2.0

DEMOS is an agent-based simulation framework used to evolve population demographic characteristics or lifecycle events such as education, marital status etc. DEMOS modules are designed to capture the interdependencies of short-term and long-term lifecycle events often influential in downstream transportation and land use modeling. An important facet of DEMOS is that it is dynamic, meaning it captures the impact of an agent's demographic characteristics in year 't' on their demographic status in year 't+1'. This has important consequences on medium- and long-term downstream modeling in different domains, such as transportation where decisions such as household vehicle transactions (i.e., buying, selling, or replacing a vehicle) depend current or past household vehicle holdings as well as household transitions. Other downstream modeling that can be enabled by DEMOS include building technology adoption or retrofit decisions, and more. DEMOS modules include: individual age progression year by year, individual mortality events, household restructuring events including marriage match-making; household birth events; individual education participation; individual labor force participation; child leaving household; household in-migration and out-migration for the region; household residence location choice and household mandatory destination choice (work and school). This version of DEMOS is tailored to be integrated with the land use simulation software UrbanSim.

Caicedo, Juan [UrbanSim, Inc.]↗

DOE OSTI2025

otsdaq

otsdaq is a Ready-to-Use data-acquisition (DAQ) solution aimed at scaling down to test-beam, detector development, and other rapid-deployment scenarios; and scaling up through the development cycle to fullscale production and operation. otsdaq uses the artdaq DAQ framework under-the-hood, providing flexibility and scalability to meet evolving DAQ needs. otsdaq provides a library of supported front-end boards and firmware modules which implement a custom UDP protocol. Additionally, an integrated Run Control GUI and readout software are provided, preconfigured to communicate with otsdaq firmware.

Rivera, Ryan [Fermi National Accelerator Laborator↗

DOE OSTI2018

“MS-Ready” structures for non-targeted high-resolution mass spectrometry screening studies

Chemical database searching has become a fxture in many non-targeted identifcation workfows based on highresolution mass spectrometry (HRMS). However, the form of a chemical structure observed in HRMS does not always match the form stored in a database (e.g., the neutral form versus a salt; one component of a mixture rather than the mixture form used in a consumer product). Linking the form of a structure observed via HRMS to its related form(s) within a database will enable the return of all relevant variants of a structure, as well as the related metadata, in a single query. A Konstanz Information Miner (KNIME) workfow has been developed to produce structural representations observed using HRMS (“MS-Ready structures”) and links them to those stored in a database. These MS-Ready structures, and associated mappings to the full chemical representations, are surfaced via the US EPA’s Chemistry Dashboard (https://comptox.epa.gov/dashboard/). This article describes the workfow for the generation and linking of ~700,000 MS-Ready structures (derived from ~760,000 original structures) as well as download, search and export capabilities to serve structure identifcation using HRMS. The importance of this form of structural representation for HRMS is demonstrated with several examples, including integration with the in silico fragmentation software application MetFrag. The structures, search, download and export functionality are all available through the CompTox Chemistry Dashboard, while the MetFrag implementation can be viewed at https://msbi.ipb-halle.de/MetFragBeta/.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2019

PTT System Performance Evaluation in 3-D Imaging of AM Components

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2019

First Annual Report on Pulsed Thermal Tomography Nondestructive Evaluation of Additively Manufactured Reactor Materials and Components: Pulsed Thermal Tomography Nondestructive Examination of Additively Manufactured Reactor Materials and Components

Additive manufacturing (AM, or 3D printing) for commercial nuclear energy applications is an emerging method for cost-efficient manufacturing aimed at replacing aging nuclear reactor parts and reducing costs for new construction. Because of the geometry of metallic structures of interest for nuclear applications, which consist of planar primitives with no symmetry of revolution, limited options are available for nondestructive evaluation (NDE), either during or post manufacturing. Known material flaws in AM include low-density regions consisting of non-sintered powder, which have to be detected to ensure the safety of long-term performance nuclear reactor components. As a solution to NDE of AM, we are developing pulsed thermal tomography (PTT) models and depth inversion algorithms for 3D imaging. PTT has many advantages because the method is non-contact and allows for in-service, NDE of AM nuclear reactor parts. By analyzing transients of surface temperature response due to internal thermal resistances, one can obtain 3D reconstructions of material effusivity using a unique inversion algorithm developed at Argonne. This report provides results of preliminary performance evaluation of PTT capability in detection of flaws in metallic structures, as well imaging complex geometry AM structures. Performance of PTT was investigated through modeling and experiments, Computer models of PTT were developed using COMSOL Heat Transfer module. Defects were modeled as cylindrical flat bottom holes (FBH), which is a common model of calibrated material flaws in thermal tomography experiments. Materials considered in this study include stainless steel 316 (SS316), stainless steel 304 (SS304), and Inconel 718. Theoretical analyses were conducted to validate inversion of simulated PTT data with COMSOL for a plate. Subsequently, 3D reconstructions were performed on COMSOL simulations for FBH, revealing a decrease in spatial resolution over depth due to thermal diffusion. The results of this study show that the performance of the inversion algorithm for detecting smaller defects depends strongly on the depth of the defect as well as the incident heat flux. The size of detectable defect was estimated by fitting a Gaussian function to surface temperature profile. The criteria for detectability was taken as 20mK noise equivalent temperature difference (NETD), which is currently the sensitivity limit of high-performance infrared cameras. It was determined through computer simulations that the smallest detectable FBH in SS316 has a 50µm diameter and is located 0.5mm below the plate surface. Preliminary experimental studies were performed to evaluate PTT performance in detecting calibrated flaws using metallic specimens with AM defects simulated as drilled-in FBH’s. High strength Stainless Steel 316 and Inconel 718 alloys were considered, as well as lower grade Stainless Steel 304, Nickel 200, and Hastelloy C276. Specimens investigated in this report consisted of approximately 1/4in-thick plates made out of these alloys using conventional manufacturing methods. The diameters of FBH’s varied from 1mm to 8mm, and their depths below the plate flat surface varied between 1mm and 6mm. The size of the smallest FBH was limited to 1mm because conventional mechanical drills were used for creating the holes. PTT imaging results have shown that 1mm-diameter FBH located 1mm and 2mm below the surface were detectable. Larger size FBH were detectable at greater depth. For example, 6mm-diameter FBH could be detected at 8mm depth. Image contrast varied slightly between the specimens, with the best reconstructions obtained in SS316 and C276 plates. Finally, PTT capability in imaging several AM structures fabricated from Inconel 718 (IN718) powder feedstock was investigated. The AM structures have complex geometry, but do not have calibrated internal defects. The objective is to determine PTT settings, such as the total integration time, for imaging of representative AM structures. A new FLIR X8500sc IR camera with higher spatial resolution (1280x1024 at 181Hz frame rate) was integrated into the PTT laboratory setup. Software tools were developed to ensure compatibility of new camera files with legacy effusivity reconstruction codes. The new camera was used to obtain 3-D reconstructions of AM IN718 nozzle plate and a particle filter plate. It was shown that PTT can scan through 2/3in-thick Inconel 718 plates in approximately 15s. Several modes of 3-D data visualization were explored, including using ImageJ and MATLAB software packages. The results demonstrate the capability of PTT in 3-D imaging of complex geometry AM structures. Intermediate results demonstrated in this report will be developed further to investigate detection of flaws in AM specimens.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2020

FAUST - Benchmark and Validation Framework [Slides]

This presentation discusses Python packages for nuclear data applications and for benchmarking. It also discusses the goals and objectives for FAUST which include providing input and output processing for different calculation codes, allowing for exchanging results between different applications and codes, running benchmarks and processing the results, automating and simplify plot and report generation, and providing a basis for developing applications useful for nuclear data evaluators. The presentation also discusses how the packages can be used both inside and outside LANL.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2020

Selection of Components for the Remote, Canister-Monitoring System

This report documents the selection of components as part of the efforts initiated to develop a remote, canister-monitoring system (RCMS) for determining and monitoring environmental conditions within dry fuel storage canisters containing aluminum clad spent nuclear fuel (ASNF) at the Idaho National Laboratory (INL). These efforts are in support of Department of Energy Office of Environmental Management (DOE-EM) investigations into technical issues associated with extended dry storage (50+ years) of ASNF. The capability to establish and monitor the performance of ASNF in situ provides the opportunity to (1) evaluate the appropriate technologies for monitoring, (2) collect canister environment conditions as soon as possible, (3) verify and validate current laboratory-based study results and analytic modeling approaches, and (4) potentially identify additional dry storage options for ASNF at the INL site. The improved understanding of ASNF behavior gained by performing this work would also contribute to the safety basis for extended dry storage in current and future configurations as well as to provide information for future transportation, conditioning, and disposal of ASNF. The parameters to be monitored by the RCMS include temperature, relative humidity, hydrogen gas concentration and radiation environment (dose). Components are selected based on the expected environmental conditions within the canister and fuel storage area, and the desired performance of the RCMS. Several of these components have been purchased and received. Future activities include component testing and calibration, software development for operation of the integrated sensor module and fabrication of a representative test volume. The results of these tests and changes to desired performance characteristics will inform subsequent activities.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2026

Large Language Model for Validation, Optical Calibration, and Learning (VOCAL) Distributed Temperature Sensing Interface

Distributed temperature sensing (DTS) using fiber optic sensors (FOS) offers a promising method for temperature measurements in advanced reactors, such as sodium fast reactors and molten salt cooled reactors. To support the calibration and validation of DTS measurements, Argonne National Laboratory developed the Validation, Optical Calibration, and Learning (VOCAL) software package. This report describes the integration of a local large language model (LLM) with a retrieval-augmented generation (RAG) system into the VOCAL interface to serve as an interactive user assistant. The LLM framework enhances the VOCAL platform’s accessibility to users by explaining interface components, clarifying inputs and outputs, and answering user queries dynamically in real-time. The accuracy of the LLM assistant performance was evaluated with 20 queries regarding the interface and its parameters using experimental data from the Thermal Hydraulic Experimental Test Article (THETA) facility. Results demonstrate that the LLM achieved a 95% accuracy rate, with a BERTScore of 0.8816 and SBERT value of 0.7417. Furthermore, validation of the RAG system within the LLM framework showed optimal accuracy with k-values between 1 and 2 using the k-refinement convergence test. The prompt perturbation analysis demonstrated good initial consistency for the RAG system, exhibiting the highest accuracy under punctuation variations and the greatest sensitivity under query reordering. Notably, the model’s errors were limited to data retrieval failures rather than factual hallucinations, reinforcing its baseline reliability. The integration of LLM provides a highly accurate, userfriendly enhancement to the VOCAL platform without disrupting its core computational capabilities for FOS calibration and validation.

Hong, Evan↗

DOE OSTI2021

SALT3: An Improved Type Ia Supernova Model for Measuring Cosmic Distances

Abstract A spectral-energy distribution (SED) model for Type Ia supernovae (SNe Ia) is a critical tool for measuring precise and accurate distances across a large redshift range and constraining cosmological parameters. We present an improved model framework, SALT3, which has several advantages over current models—including the leading SALT2 model (SALT2.4). While SALT3 has a similar philosophy, it differs from SALT2 by having improved estimation of uncertainties, better separation of color and light-curve stretch, and a publicly available training code. We present the application of our training method on a cross-calibrated compilation of 1083 SNe with 1207 spectra. Our compilation is 2.5× larger than the SALT2 training sample and has greatly reduced calibration uncertainties. The resulting trained SALT3.K21 model has an extended wavelength range 2000–11,000 Å (1800 Å redder) and reduced uncertainties compared to SALT2, enabling accurate use of low- z I and iz photometric bands. Including these previously discarded bands, SALT3.K21 reduces the Hubble scatter of the low- z Foundation and CfA3 samples by 15% and 10%, respectively. To check for potential systematic uncertainties, we compare distances of low (0.01 < z < 0.2) and high (0.4 < z < 0.6) redshift SNe in the training compilation, finding an insignificant 3 ± 14 mmag shift between SALT2.4 and SALT3.K21. While the SALT3.K21 model was trained on optical data, our method can be used to build a model for rest-frame NIR samples from the Roman Space Telescope. Our open-source training code, public training data, model, and documentation are available at https://saltshaker.readthedocs.io/en/latest/ , and the model is integrated into the sncosmo and SNANA software packages.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2024

Neural Networks for Prediction of Complex Chemistry in Water Treatment Process Optimization

Water chemistry plays a critical role in the design and operation of water treatment processes. Detailed chemistry modeling tools use a combination of advanced thermodynamic models and extensive databases to predict phase equilibria and reaction phenomena. The complexity and formulation of these models preclude their direct integration in equation-oriented modeling platforms, making it difficult to use their capabilities for rigorous water treatment process optimization. Neural networks (NN) can provide a pathway for integrating the predictive capability of chemistry software into equation-oriented models and enable optimization of complex water treatment processes across a broad range of conditions and process designs. Herein, we assess how NN architecture and training data impact their accuracy and use in equation-oriented water treatment models. We generate training data using PhreeqC software and determine how data generation and sample size impact the accuracy of trained NNs. The effect of NN architecture on optimization is evaluated by optimizing hypothetical black-box desalination processes using a range of feed compositions from USGS brackish water data set, tracking the number of successful optimizations, and testing the impact of initial guess on the final solution. Our results clearly demonstrate that data generation and architecture impact NN accuracy and viability for use in equation-oriented optimization problems.

Dudchenko, Alexander V↗