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SAM Plug-in Development (Phase I Final Report)

The DOE Office of Nuclear Energy (NE) has created an extensive set of advanced modeling and simulation tools for nuclear engineering analysis. The advanced capabilities of these newer analysis codes require more in-depth training, skills, and knowledge in order to effectively utilize them for the design, analysis, and licensing of advanced nuclear systems and experiments. A high learning curve for inexperienced users may deter organizations from incorporating these tools into their internal processes. This project involved development of a plug-in to the Symbolic Nuclear Analysis Package (SNAP) for the System Analysis Module (SAM) tool. SAM is an advanced system analysis tool for reactor transient analyses being developed at Argonne National Laboratory under the U.S. DOE Office of Nuclear Energy’s Nuclear Energy Advanced Modeling and Simulation (NEAMS) program. SAM utilizes an object-oriented application framework (MOOSE), and its underlying meshing and finite-element library (libMesh) and linear and non-linear solvers (PETSc), to leverage modern advanced software environments and numerical methods. SNAP provides a highly flexible framework for creating, modifying and documenting input for engineering analysis codes such as SAM as well as extensive functionality for submitting, monitoring, and interacting with the codes through an intuitive graphical user interface (GUI). The common user interface provided by SNAP minimizes the learning curve for engineers starting with a new analysis code and provides an intuitive framework for transitioning between different analysis codes. SNAP provides a powerful but intuitive interface to facilitate access to advanced modeling and simulation tools for inexperienced users. Unlike many “form based” GUI’s, SNAP maps each engineering code’s component input to an internal database which manages all component input parameters along with component interconnections. This level of abstraction permits SNAP to support several advanced capabilities such as renodalization, model validation and consistency checks, embedded documentation, model notebook generation, data ownership and reviewer tracking, and variable assignment for inputs to name a few. SNAP includes a built-in Python interpreter and is interfaced to several commercial and open source packages including CPython, MATLAB/OCTAVE, Microsoft Office, Open Office, and SANDIA’s DAKOTA package which provides Uncertainty Quantification analysis through the SNAP plug-ins. Phase I of this project involved development a fully functional basic SAM plug-in to SNAP. This plug-in provides the ability to import existing models, graphically construct, edit and submit models using SNAP’s extensive functionality.

99 GENERAL AND MISCELLANEOUS↗

Overlapping Domain Coupling of Multidimensional and System Codes in NEAMS - Pronghorn and SAM

This report describes the implementation and testing of domain-overlapping coupling of the Pronghorn and SAM codes. Both Pronghorn and SAM are codes developed by the DOE Nuclear Energy Advanced Modeling and Simulation (NEAMS) program for analysis of advanced nuclear reactors. Pronghorn focuses on analyzing multi-dimensional core flow conditions, while SAM focuses on analysis of the entire system including, among other components, piping, pumps, and heat exchangers. It is desirable for many advanced reactor thermal-hydraulics simulations to couple Pronghorn and SAM to obtain self-consistent solutions in the core and the system. The domain-overlapping coupling approach provides a robust and numerically efficient candidate for this coupling. We describe the algorithm for obtaining self-consistent solutions between a SAM network of flow channels and an overlapped multi-dimensional Pronghorn domain. The algorithm is tested for a variety of simple canonical test problems and a model of the Molten Salt Reactor Experiment (MSRE). Results demonstrate that the domain overlapping coupling approach provides consistent pressure, mass flow rate, enthalpy, and passive scalar distributions between Pronghorn and SAM and converges reliably and efficiently (at most 15 iterations, usually much less than 10) for the considered test problems.

97 MATHEMATICS AND COMPUTING↗

Validation of NEAMS Tools Using MSRE Data

This report documents the benchmarks developed and performed for the tools and codes developed under the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program utilizing the MSRE experiment data. There are three focus areas explored in this work: fuel evolution, CFD, and system transient analyses. Fuel depletion is important for MSR reactor physics and fuel cycle analysis. Fuel depletion capability is currently being developed in the Griffin reactor physics code. To support this, a benchmark problem is developed using the MSRE data and an existing depletion code with flowing fuel analysis functionality (ADDER) to validate this new capability in Griffin. The ADDER calculation is compared with the TRITON-MSR results as well as the MSRE experimental data. This benchmark can be directly used to verify and validate the Griffin fuel depletion capability in future years. For CFD simulation, the MSRE CAD model is obtained from the Copenhagen Atomics and a mesh is generated for the MSRE inlet plenum. The Nek5000 code will be employed to find the flow distribution in the MSRE inlet plenum based on the mesh generated. For system analysis, a simple benchmark problem for three types of MSR system transients is developed. The SAM and SPECTRA codes are used to solve the simple problem, and the results from the two codes agree well. The SAM code is also employed to obtain the frequency response of the MSRE system at the 5 and 8 MWt power levels. The results agree well with the experiment measurements. These verification and validation efforts gives SAM users more confidence in MSR system transient simulations using SAM. Lastly, the SAM-Griffin Multiphysics coupling work is initiated. A simple one-way coupling of evaluating the precursor drift effect on the MSRE k-eff is demonstrated. This preliminary coupling work serves as the basis for future more complex Multiphysics simulation and modelling.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Modelling Accident Tolerant Fuel Concepts

The catastrophic events that occurred at the Fukushima-Daiichi nuclear power plant in 2011 have led to widespread interest in research of alternative fuels and claddings that are proposed to be accident tolerant. The United States Department of Energy (DOE) through its Nuclear Energy Advanced Modeling and Simulation (NEAMS) program has funded an Accident Tolerant Fuel (ATF) High Impact Problem (HIP). The ATF HIP is a three-year project to perform research on two accident tolerant concepts. The final outcome of the ATF HIP will be an in-depth report to the DOE Advanced Fuels Campaign (AFC) giving a recommendation on whether either of the two concepts should be included in their lead test assembly scheduled for placement into a commercial reactor in 2022. The two ATF concepts under investigation in the HIP are uranium silicide fuel and iron-chromium-aluminum (FeCrAl) alloy cladding. Utilizing the expertise of three national laboratory participants (Idaho National Laboratory, Los Alamos National Laboratory, and Argonne National Laboratory), a comprehensive multiscale approach to modeling is being used that includes atomistic modeling, molecular dynamics, rate theory, phase-field, and fuel performance simulations. Model development and fuel performance analysis are critical since a full suite of experimental studies will not be complete before AFC must prioritize concepts for focused development. In this paper, we present simulations of the two proposed accident tolerance fuel systems: U3Si2 fuel with Zircaloy-4 cladding, and UO2 fuel with FeCrAl cladding. Sensitivity analyses are completed using Sandia National Laboratories’ Dakota software to determine which input parameters (e.g., fuel specific heat) have the greatest influence on the output metrics of interest (e.g., fuel centerline temperature). We also outline the multiscale modelling approach being employed. Considerable additional work is required prior to preparing the recommendation report for the Advanced Fuels Campaign.

Accident Tolerant Fuel↗

A Search for Kilonovae in the Dark Energy Survey

The coalescence of a binary neutron star pair is expected to produce gravitational waves (GW) and electromagnetic radiation, both of which may be detectable with currently available instruments. We describe a search for a predicted r-process optical transient from these mergers, dubbed the “kilonova” (KN), using griz broadband data from the Dark Energy Survey Supernova Program (DES-SN). Some models predict KNe to be redder, shorter-lived, and dimmer than supernovae (SNe), but the event rate of KNe is poorly constrained. We simulate KN and SN light curves with the Monte-Carlo simulation code SNANA to optimize selection requirements, determine search efficiency, and predict SN backgrounds. Our analysis of the first two seasons of DES-SN data results in 0 events, and is consistent with our prediction of 1.1 ± 0.2 background events based on simulations of SNe. From our prediction, there is a 33% chance of finding 0 events in the data. Assuming no underlying galaxy flux, our search sets 90% upper limits on the KN volumetric rate of 1.0 ×10{sup 7} Gpc{sup −3} yr{sup −1} for the dimmest KN model we consider (peak i-band absolute magnitude M{sub i}=−11.4 mag) and 2.4 ×10{sup 4} Gpc{sup −3} yr{sup −1} for the brightest (M{sub i}=−16.2 mag). Accounting for anomalous subtraction artifacts on bright galaxies, these limits are ∼3 times higher. This analysis is the first untriggered optical KN search and informs selection requirements and strategies for future KN searches. Our upper limits on the KN rate are consistent with those measured by GW and gamma-ray burst searches.

79 ASTRONOMY AND ASTROPHYSICS↗

Nuclear Science User Facilities: Instrument Scientist Program

The traditional single institution User Facility model prevalent in the DOE complex funds Instrument Scientists (IS) full-time to collaborate with and guide users, disseminate results through publication, build a broad and competent user base, continuously improve instrumentation, enhance data collection methods, and improve data analysis methods. This model focuses the Instrument Scientist on ensuring that visiting researchers obtain the best and most comprehensive data. Instrument Scientists are also expected to establish personal research programs based on the use of the instrument(s) under their charge, which allows for further advances in instrumentation and science. This model ensures that the User Facility offers unique, world-leading instruments and data analysis to the user community, creates high demand among top researchers for the use of these capabilities, and as a result, positively impacts science and technology in the United States.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Coupling coarse-mesh CFD with fine-mesh CFD for modeling molten-salt reactors in the Virtual Test Bed (VTB)

The Nuclear Energy Advanced Modeling and Simulation (NEAMS) program aims at developing a simulation tool kit to accelerate the development and deployment of nuclear power technologies. NEAMS multiphysics tools have been designed to provide numerical simulation support for the design and licensing of GEN IV reactors. Pronghorn is NEAMS's coarse-mesh computational fluid dynamics (CFD) tool, which is designed to run 3D core transients in GEN IV reactors at a reduced computational cost. To increase their accuracy, coarse-mesh CFD simulations require calibrated closure coefficients. One way of computing these coefficients is via the Nek5000, NEAMS's high-fidelity CFD tool. This article discusses our current research lines in informing Pronghorn closure coefficients via Nek5000 to enable multiphysics simulations of the core cavity of the molten-salt fast reactor. We present an application in which Pronghorn mixing length turbulent viscosity has been calibrated from Nek5000 simulations. The resulting Pronghorn thermal-hydraulics model is then coupled to Griffin, the NEAMS neutron transport solver, to solve for the steady-state configuration of the molten-salt fast reactor. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Coupling coarse mesh CFD with fine mesh CFD for modeling for Molten Salt Reactors in the Virtual Test Bed VTB

The Nuclear Energy Advanced Modeling and Simulation (NEAMS) program aims at developing a simulation tool kit to accelerate the development and deployment of nuclear power technologies. NEAMS multiphysics tools have been designed to provide numerical simulation support for the design and licensing of GEN IV reactors. Pronghorn is NEAMS’s coarse-mesh computational fluid dynamics (CFD) tool, which is designed to run 3D core transients in GEN IV reactors at a reduced computational cost. To increase their accuracy, coarse-mesh CFD simulations require calibrated closure coefficients. One way of computing these coefficients is via the Nek5000, NEAMS’s high-fidelity CFD tool. This article discusses our current research lines in informing Pronghorn closure coefficients via Nek5000 to enable multiphysics simulations of the core cavity of the molten-salt fast reactor. We present an application in which Pronghorn mixing length turbulent viscosity has been calibrated from Nek5000 simulations. The resulting Pronghorn thermal-hydraulics model is then coupled to Griffin, the NEAMS neutron transport solver, to solve for the steady-state configuration of the molten-salt fast reactor.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Developing an Interactive OpenMP Book with Large Language Models

Abstract. This paper presents an approach to authoring a textbook titled Interactive OpenMP Programming with the assistance of Large Language Models (LLMs). The writing process utilized state-of-the-art LLMs, including Gemini Pro 1.5, Claude 3, and ChatGPT-4, to generate the initial structure and outline of the book, as well as the initial content for specific chapters. This content included detailed descriptions of individual OpenMP constructs and practical programming examples. The outline and content have then undergone extensive manual revisions to meet our book goals. In this paper, we report our findings about the capabilities and limitations of these LLMs. We address critical questions concerning the necessity of textbook resources and the effectiveness of LLMs in creating fundamental and practical programming content. Our findings suggest that while LLMs offer significant advantages in generating textbook content, they require careful integration with traditional educational methodologies to ensure depth, accuracy, and pedagogical effectiveness. The Interactive OpenMP Programming book is developed with the framework of Jupyter Book, enabling the execution of code within the book from the web browser, providing instant feedback and a dynamic learning experience that stands in contrast to traditional educational resources. The book represents a significant step towards modernizing programming education, offering insights into practical strategies for generating the textbook through advanced AI tools.

Large Language Model · OpenMP · Interactive Book ·↗

Prenatal ethanol exposure-induced adrenal developmental abnormality of male offspring rats and its possible intrauterine programming mechanisms

Fetal adrenal developmental status is the major determinant of fetal tissue maturation and offspring growth. We have previously proposed that prenatal ethanol exposure (PEE) suppresses fetal adrenal corticosterone (CORT) synthesis. Here, we focused on PEE-induced adrenal developmental abnormalities of male offspring rats before and after birth, and aimed to explore its intrauterine programming mechanisms. A rat model of intrauterine growth retardation (IUGR) was established by PEE (4 g/kg·d). In PEE fetus, increased serum CORT concentration and decreased insulin-like growth factor 1 (IGF1) concentration, with lower bodyweight and structural abnormalities as well as a decreased Ki67 expression (proliferative marker), were observed in the male fetal adrenal cortex. Adrenal glucocorticoid (GC)-metabolic activation system was enhanced while gene expression of IGF1 signaling pathway with steroidogenic acute regulatory protein (StAR), 3β-hydroxysteroid dehydrogenase (3β-HSD) was decreased. Furthermore, in the male adult offspring of PEE, serum CORT level was decreased but IGF1 was increased with partial catch-up growth, and Ki67 expression demonstrated no obvious change. Adrenal GC-metabolic activation system was inhibited, while IGF1 signaling pathway and 3β-HSD was enhanced with the steroidogenic factor 1 (SF1), and StAR was down-regulated in the adult adrenal. Based on these findings, we propose a “two-programming” mechanism for PEE-induced adrenal developmental toxicity: “the first programming” is a lower functional programming of adrenal steroidogenesis, and “the second programming” is GC-metabolic activation system-related GC-IGF1 axis programming. - Highlights: • Prenatal ethanol exposure induces adrenal developmental abnormality in offspring rats. • Prenatal ethanol exposure induces intrauterine programming of adrenal steroidogenesis. • Intrauterine GC-IGF1 axis programming might mediate adrenal developmental abnormality.

60 APPLIED LIFE SCIENCES↗

Multi-scale fission product release model with comparison to AGR data

TRistructural ISOtropic (TRISO) particle fuel is central to several advanced, high-temperature reactor designs. Each particle consists of a fuel kernel encapsulated by three layers of carbon and ceramics that prevent the release of fission products and ensure physical integrity. Despite outstanding retention properties, fission product release has been observed from intact particles. To better understand and quantify fission product release from TRISO particles, a multiscale, mechanistic model of fission product transport is being developed by the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program. Previous work focused on silver (Ag) transport and improved Ag release predictions. The work described in this report builds on this experience to better understand cesium (Cs) transport in silicon carbide (SiC), the main barrier to the release of fission products. Atomistic simulations provide bulk and grain boundary (GB) Cs diffusivities in SiC, which are used by phase field simulations in the mesoscale code Marmot to determine the temperature, microstructure, and irradiation-dependent Cs diffusivity at the mesoscale in SiC. This approach attributes the different temperature regimes experimentally observed for Cs diffusivities in SiC to a transition from bulk-dominated diffusivity at high temperatures to a GB-dominated regime at low temperatures, providing new insight. The multiscale, mechanistic effective diffusivity is then implemented in the fuel performance code BISON and further validated by comparing Cs release predictions from Advanced Gas Reactor (AGR)-1 and AGR-2 post-irradiation measurements. The new model improves BISON’s predictability. This document also reports improvements made on Ag transport modeling by accounting for different GB types having different diffusivities. Moreover, this report details preliminary efforts to model palladium (Pd) attack of the SiC at the mesoscale using a phase field approach. Pd attack and its impact on accelerated Ag transport remains a misunderstood phenomenon, and we use the model to demonstrate that the formation of lamellae that has been observed in experiments can be explained by the reaction of Pd with SiC to form alternating layers of graphite and Pd 2 Si. This effort aims to improve our understanding of the reaction and eventually provide a model for BISON to account for Pd penetration and its effects on fission product release.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Energy & Environmental Research Center (EERC)–U.S. Department of Energy (DOE) Joint Program on Research and Development for Fossil Energy-Related Resources

The EERC teamed with the DOE National Energy Technology Laboratory to conduct complementary research and development under the Joint Program on Research and Development for Fossil Energy-Related Resources (Cooperative Agreement No. DE-FC26-08NT43291). This 10-year program merged two previous 10-year agreements—DE-FC26-98FT40320 and DE-FC26-98FT40321—into a single follow-on agreement. The Fossil Energy cooperative agreement between DOE and the EERC was initiated in 1983 when the EERC was defederalized. This dynamic 35-year partnership has evolved to further research in areas that address DOE Office of Fossil Energy program goals while serving the missions and exploiting the strengths of both organizations through this agreement and a new 5-year Fossil Energy-Related Resources cooperative agreement established in 2015. As the 10-year program has ended, the purpose of this report is to summarize the activity and significant outcomes that were accomplished by the EERC. This program is an excellent model for research, development, demonstration, and commercialization partnerships between government, industry, and the applied science and engineering communities to bring cutting-edge science closer to commercial application. The overarching goal was to support DOE Fossil Energy goals by advancing the scientific knowledge and technical development essential to ensuring future sustainable supplies of affordable energy and clean water, protecting and restoring the environment, and reducing dependence on foreign energy sources, thereby increasing U.S. energy security. The strategic objective was to advance continued use of domestic fossil fuels as a mainstay of U.S. energy production by making fossil energy systems nonpolluting and more efficient, capturing and sequestering greenhouse gases, and integrating the use of fossil and renewable energy sources into the energy mix. The research achievements from this partnership have exceeded the goals and objectives by contributing substantially to the development of science-based energy and environmental policy, educational foundations for science and technology, and commercialization and international marketing of energy technologies. The program comprised 75 individual projects, which included basic/applied fossil energy research projects involving no cost share and development, demonstration, and commercialization projects (many derived from applied research projects) that included nonfederal cost share of approximately 40% (the contractually required minimum level of cumulative nonfederal cost share was 29%). In all, 32,798,698 of federal funding was leveraged with industry cash and in-kind cost share of 21,697,129 from 80 nonfederal partners for a total of 54,495,827 of funded research that 1) advanced the development of unconventional tight oil resources in the Bakken Formation; 2) demonstrated the application of CO 2 Storage and EOR in tight oil formations; 3) developed advanced carbon capture technology; 4) addressed key application and infrastructure concerns for commercial deployment of CO 2 ; 5) demonstrated innovative, integrated water management strategies for energy development projects; 6) developed novel pollution control technologies for mercury and hazardous air pollutants; and 7) performed world-class outreach and dissemination of research results to industry partners and other stakeholders. These outcomes speak to the valuable return on the substantial investment in this program.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Online Model-Free DER Dispatch Via Adaptive Voltage Sensitivity Estimation and Chance Constrained Programming

This paper proposes an online data-driven distributed energy resource management system (DERMS) for distribution system optimal DER dispatch as well as voltage regulation. Here, the key innovation is to leverage the Local Sensitivity Factor (LSF) for transforming the DER control into a computationally efficient linear programming (LP) problem. By taking real-time measurements, the estimation of LSF eliminates the need for an accurate distribution system model as well as full nodal load information, which is difficult to achieve in practice. A robust recursive least squares method is also developed to ensure the robust estimation of LSF, which is initialized using reasonable values from model-derived LSFs. This allows the system to adapt to changing operational conditions effectively. A scenario-based, chance-constrained framework is further employed to ensure voltage remains within acceptable limits in the presence of measurement and estimation uncertainties. Test results on a real-world, 759-node distribution network located in western Colorado, U.S., validate the effectiveness and robustness of the proposed control approach and demonstrate its superior performance as compared to alternative methods.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Development of Integrated Thermal Fluids Modeling Capability for MSRs

The DOE Nuclear Energy Advanced Modeling and Simulation (NEAMS) program supports a full range of computational thermal fluids analysis capabilities and code developments for a broad class of light-water and advanced reactor concepts. The research and development approach under thermal fluids technical area synergistically combines three length and time scales in a hierarchal multi-scale approach. To demonstrate the feasibility and capabilities of a multi-scale thermal fluids capability using these codes, a key joint effort has been pursued to develop an integrated system-and engineering-scale thermal fluids analysis capability with the MOOSE-based codes, through integration of SAM and Pronghorn, both based on the MOOSE framework. This report summarizes the progress in developing an integrated system- and engineering-scale thermal fluids analysis capability based on SAM and Pronghorn for molten salt reactors (MSRs), which gained significant interest in recently years. Two coupling approaches were studied, i.e. separate domain or domain-segregated coupling approach and the domain-overlapping approach. A series of coupled multi-physics models have been developed for a common reference molten salt fast reactor (MSFR) concept, ranging from standalone SAM system model to integrated SAM-Pronghorn-Griffin models. Both the steady state and the transient simulations are performed to the state-of-the-art simulation capabilities of NEAMS software suite in MSFR system applications. This report also covers further development and testing of the gas transport model in SAM for MSR modeling support. The presence of noncondensable gas in MSR systems would have strong impacts on fission gas removal and transport of noble metals throughout the system. Fission products removed through the off-gas system can also impact reactivity and can act as an additional point of heat removal. To ensure that the gas transport model is adequately tested, the supported modeling capabilities and features of SAM were identified, and a suite of tests were developed to test the model for each identified feature. Validation and UQ testing were also performed for the model and demonstrated that the buoyancy term, which was originally developed using non-salt/helium gas experimental data, can capture the experimental gas bubble velocity and diameter to within experimental and code uncertainty. An existing MSRE model was also modified in this work to include the gas transport model and to demonstrate the gas model behavior for realistic conditions of interest.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

FENIX: An Open-Source Multiphysics Integrated Framework Enabling Collaborative Development of Plasma Facing Component Modeling Capabilities

Advanced modeling and simulation tools have a crucial role to play in accelerating fusion energy deployment as a sustainable power source. Multiphysics, high-fidelity computational tools can help understand, model, and quantify the complex interactions between materials performance, plasma and neutron exposure, and engineering processes. As a result, they accelerate the design, safety analysis, and performance evaluation of fusion systems. This webinar introduces the Fusion ENergy Integrated multiphys-X (FENIX) framework, an open-source multiphysics tool for plasma facing component modeling. FENIX leverages the Multiphysics Object-Oriented Simulation Environment (MOOSE) framework, which has been developed by the United States Department of Energy Nuclear Energy Advanced Modeling and Simulation (NEAMS) program. FENIX couples various MOOSE capabilities such as heat transfer, thermomechanics, thermal hydraulics, electromagnetics, and plasma kinetics with the MOOSE-based applications Cardinal (neutronics) and TMAP8 (tritium transport). During the webinar, we will present FENIX and discuss how its modularity, openness, software quality assurance processes, and licensing approach supports effective collaborations, including public-private partnerships.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

High Frequency Transverse Instabilities in Low NOx Gas Turbines

This program addresses the topic of combustion instabilities under the goal of developing “Low-NOx Combustion Technology for ‘Air-Breathing’ Advanced Turbines”. With recent advances in high-temperature withstanding materials, the push towards higher efficiency has resulted in efforts to design high temperature, low NOx gas turbines. The development of such low NOx systems is often plagued with combustion instabilities. These instabilities manifest with acoustic modes that are longitudinal, transverse or both. A large body of literature and work exists addressing the underlying mechanisms and models for longitudinal instabilities and these have been successfully implemented in the design tools for low NOx gas turbines. The flame response aspect of the thermoacoustic feedback loop was often modeled in an acoustically compact framework since for low frequencies, the flame length scale was small compared to the acoustic wavelength. This enabled simplification where the modeling focused only on the overall flame response and not the local spatial distribution of the flame response. In addition, additional mechanisms such as the direct effect of pressure fluctuations on the flame response could be neglected. In contrast, high frequency instabilities which often are transverse in nature, have received relatively less attention in the literature. The flame is no longer acoustically compact and thus the local distribution of heat release must be accurately understood. The flame responds to velocity fluctuations, equivalence ratio fluctuations as before, but also to pressure fluctuations through kinetic effects. These aspects of high-frequency instabilities make it a challenging problem that requires a detailed elucidation of the underlying mechanisms and creating models for them. In this program we significantly improved the understanding of these instabilities through a combination of experiments (informed by interactions with OEMs), modeling of measured data and reduced order modeling of flame response. The results from the program can be used as basis for robust design tools that are essential for successfully developing gas turbines that operate in an environmentally acceptable manner with mitigation strategies for high-frequency instabilities.

08 HYDROGEN↗

The potential of quantum annealing for rapid solution structure identification

Abstract The recent emergence of novel computational devices, such as quantum computers, coherent Ising machines, and digital annealers presents new opportunities for hardware-accelerated hybrid optimization algorithms. Unfortunately, demonstrations of unquestionable performance gains leveraging novel hardware platforms have faced significant obstacles. One key challenge is understanding the algorithmic properties that distinguish such devices from established optimization approaches. Through the careful design of contrived optimization tasks, this work provides new insights into the computation properties of quantum annealing and suggests that this model has the potential to quickly identify the structure of high-quality solutions. A meticulous comparison to a variety of algorithms spanning both complete and local search suggests that quantum annealing’s performance on the proposed optimization tasks is distinct. This result provides new insights into the time scales and types of optimization problems where quantum annealing has the potential to provide notable performance gains over established optimization algorithms and suggests the development of hybrid algorithms that combine the best features of quantum annealing and state-of-the-art classical approaches.

97 MATHEMATICS AND COMPUTING↗

Water resource recovery modelling 2021 (WRRmod2021 conference)

Our society is transitioning fast into the digital age, spurred by development of cheap and new sensing technology, breakthroughs in computing, and development of efficient algorithms for optimization. This transition is also visible in the field of wastewater treatment and is driving new model developments, especially by exploiting the large data sets available with many utilities. Not surprisingly, WRRmod2021 had featured a strong session on ‘data-driven models and digitalization’ focused on this hot topic. At the same time, engineering practice calls for more robust models for performance evaluation and optimization of both conventional facilities and innovative processes. As a result, the WRRmod2021 program also exhibited sessions on modelling of new process units (e.g., aerobic granular sludge), modelling of the nitrogen cycle, and integrated/plant-wide modelling.

54 ENVIRONMENTAL SCIENCES↗