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DOE OSTI2025

In-service corrosion and grain boundary oxidation in neutron-irradiated 316 stainless steel baffle-former bolts

Reactor core internal components such as baffle-former bolts (BFBs) are subjected to significant mechanical stress, corrosive environment, and neutron irradiation from the reactor core during the plant operation. Over the long operation period, these conditions lead to potential degradation and of the bolts. In this work, characterization was performed on the oxidized surface of stainless steel BFBs harvested from a commercial pressurized water reactor (PWR) after 40 years of operation. The analysis shows that a complex multilayered surface oxide with six identified layers formed that is different from 2-layer structure commonly observed in model experiments. The oxide varies by composition – predominantly Fe, Cr, and Ni, grain size, and phase, and has features resembling both unirradiated and radiation/ corrosion experiments likely due to the low radiation flux compared to ion-irradiation or the test reactor radiation. In addition, grain boundary oxidative attack featured a pathway for Fe and other elements to move from the metal matrix to the outermost oxide. In conclusion, the results help assess PWR lifetime extension, put into context previous experimental studies, and provide input for designing experiments combining radiation and corrosion effects.

Baffle-former bolt↗

DOE OSTI2019

LandMOD ET mapper: A new matlab-based graphical user interface (GUI) for automated implementation of SEBAL and METRIC models in thermal imagery

Remote sensing based surface energy balance (SEB) models, such as SEB Algorithm for Land (SEBAL) and Mapping evapotranspiration (ET) at high Resolution with Internalized Calibration (METRIC) are widely used to monitor ET. However, their operational use is challenged by model complexity and the tedious process of selecting hot and cold pixels. We developed a new Matlab-based ET mapping toolbox named “LandMOD ET Mapper” for automated implementation of these models to facilitate their widespread applications among new users. The toolbox is demonstrated using one Landsat and one Moderate Resolution Imaging Spectroradiometer (MODIS) Terra image covering three AmeriFlux sites in Nebraska, U.S. Daily ET estimates were comparable with the observed ET for five days when near cloud-free Landsat and MODIS Terra images were available in the 2006 maize growing season. The toolbox provides a viable ET mapping option to new and inexperienced users with reduced time and labor demands.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

A machine learning approach for particle accelerator errant beam prediction using spatial phase deviation

Particle accelerators are extremely complex systems that are expected to operate on high availability. Predicting impending failures only by utilizing data collected from diagnostic equipment already on board can help operators to avoid installing expensive sensors, unscheduled downtime and associated costs. For this purpose we explore the predictive power of Machine Learning algorithms to detect faulty beams prior to the failure. In this study, we propose a Machine Learning approach to model mapping from a pair of sensors located across the accelerator. While the model is trained to represent normal operation, we evaluate the predictive performance on known faulty beam pulses. We also investigate the model performance on unseen data through k-fold cross-validation. Then we recap the analysis with a neural architecture search and hyperparameter optimization study to fine tune our initial model. In conclusion, this paper will also introduce a sustainable framework that can standardize Machine Learning workflow applied to particle accelerators.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2023

Magnetohydrodynamics with physics informed neural operators

Abstract The modeling of multi-scale and multi-physics complex systems typically involves the use of scientific software that can optimally leverage extreme scale computing. Despite major developments in recent years, these simulations continue to be computationally intensive and time consuming. Here we explore the use of AI to accelerate the modeling of complex systems at a fraction of the computational cost of classical methods, and present the first application of physics informed neural operators (NOs) (PINOs) to model 2D incompressible magnetohydrodynamics (MHD) simulations. Our AI models incorporate tensor Fourier NOs as their backbone, which we implemented with the TensorLY package. Our results indicate that PINOs can accurately capture the physics of MHD simulations that describe laminar flows with Reynolds numbers Re ⩽ 250 . We also explore the applicability of our AI surrogates for turbulent flows, and discuss a variety of methodologies that may be incorporated in future work to create AI models that provide a computationally efficient and high fidelity description of MHD simulations for a broad range of Reynolds numbers. The scientific software developed in this project is released with this manuscript.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2025

Improved honeycomb and hyperhoneycomb lattice Hamiltonians for quantum simulations of non-Abelian gauge theories

Improved Kogut-Susskind Hamiltonians for quantum simulations of non-Abelian Yang-Mills gauge theories are developed for honeycomb (2+1⁢D) and hyperhoneycomb (3+1⁢D) spatial tessellations. This is motivated by the desire to identify lattices for quantum simulations that involve only 3-link vertices among the gauge field group spaces in order to reduce the complexity in applications of the plaquette operator. For the honeycomb lattice, we derive a classically 𝒪⁡(𝑏 2 )-improved Hamiltonian, with 𝑏 being the lattice spacing. Tadpole improvement via the mean-field value of the plaquette operator is used to provide the corresponding quantum improvements. We have identified the (nonchiral) hyperhoneycomb as a candidate spatial tessellation for 3+1⁢D quantum simulations of gauge theories, and determined the associated 𝒪⁡(𝑏)-improved Hamiltonian.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2024

Direct pulse-level compilation of arbitrary quantum logic gates on superconducting qutrits

Advanced simulations and calculations on quantum computers require high-fidelity implementations of quantum operations. The universal gateset approach builds complex unitaries from a small set of primitive gates, often resulting in a long gate sequence, which is typically a leading factor in the total accumulated error. Compiling a complex unitary for processors with higher-dimensional logical elements, such as qutrits, exacerbates the accumulated error per unitary, since an even longer gate sequence is required. Optimal control methods promise time- and resource-efficient compact gate sequences and, therefore, higher fidelity. These methods generate pulses that can directly implement any complex unitary on a quantum device. In this work, we demonstrate that any arbitrary qubit and qutrit gate can be realized with high fidelity, which can significantly reduce the length of a gate sequence. We generate and test pulses for a large set of randomly selected arbitrary unitaries on several quantum processing units (QPUs): the Lawrence Livermore National Laboratory Quantum Device and Integration Testbed’s (QuDIT’s) standard QPU and three of Rigetti’s QPUs: Ankaa-2, Ankaa-9Q-1, and Aspen-M-3. On the QuDIT platform’s standard QPU, the average fidelity of random qutrit gates is 97.9 ± 0.5% measured with conventional QPT and 98.8 ± 0.6% from QPT with gate folding. Rigetti’s Ankaa-2 achieves random qubit gates with an average fidelity of 98.4 ± 0.5% (conventional QPT) and 99.7 ± 0.1% (QPT with gate folding). On Ankaa-9Q-1 and Aspen-M-3, the average fidelities with conventional qubit QPT measurements were higher than 99% (see Appendix). Here we show that optimal control gates are robust to drift for at least 3 h and that the same calibration parameters can be used for all implemented gates. Our work promises that the calibration overheads for optimal control gates can be made small enough to enable efficient quantum circuits based on this technique.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2018

Launching and controlling Gaussian beams from point sources via planar transformation media

Based on operations prescribed under the paradigm of Complex Transformation Optics (CTO) [1- 4], it was recently shown in [5] that a complex source point (CSP) can be mimicked by a paritytime transformation media. Such coordinate transformation has a mirror symmetry and results a balanced loss/gain metamaterial slab. A point source placed at the center of such slab produces a Gaussian beam propagating away from the slab surface. Here, we extend the CTO analysis to non-symmetric complex coordinate transformations and show that by using simply a (homogeneous) doubly anisotropic gain-media metamaterial slab, one can still mimic a CSP and produce Gaussian beam. Notably, a Gaussian beam can be produced in this case by point sources placed outside the slab as well. By making use of the extra degrees of freedom provided by CTO, the near-zero requirement on the real part of the resulting constitutive parameters can be relaxed to facilitate potential realization. In addition, exploitation of both real and imaginary parts of the CTO design yield direct control of the Gaussian beam properties such as peak amplitude and waist (focus) location.

74 ATOMIC AND MOLECULAR PHYSICS↗

DOE OSTI2020

Wireless Interrogation of High Temperature Surface Acoustic Wave Dynamic Strain Sensor

Dynamic strain sensing is necessary for high-temperature harsh-environment applications, including powerplants, oil wells, aerospace, and metal manufacturing. Monitoring dynamic strain is important for structural health monitoring and condition-based maintenance in order to guarantee safety, increase process efficiency, and reduce operation and maintenance costs. Sensing in high-temperature (HT), harsh-environments (HE) comes with challenges including mounting and packaging, sensor stability, and data acquisition and processing. Wireless sensor operation at HT is desirable because it reduces the complexity of the sensor connection, increases reliability, and reduces costs. Surface acoustic wave resonators (SAWRs) are compact, can operate wirelessly and battery-free, and have been shown to operate above 1000°C, making them a potential option for HT HE dynamic strain sensing. This paper presents wirelessly interrogated SAWR dynamic strain sensors operating around 288.8MHz at room temperature and tested up to 400°C. The SAWRs were calibrated with a high-temperature wired commercial strain gauge. The sensors were mounted onto a tapered-type Inconel constant stress beam and the assembly was tested inside a box furnace. The SAWR sensitivity to dynamic strain excitation at 25°C, 100°C, and 400°C was .439 μV/με, 0.363μV/με, and .136 μV/με, respectively. Furthermore, the experimental outcomes verified that inductive coupled wirelessly interrogated SAWRs can be successfully used for dynamic strain sensing up to 400°C.

47 OTHER INSTRUMENTATION↗

DOE OSTI2018

Dynamic Adaptable Asynchronous Progress Model for MPI RMA Multiphase Applications

Casper is a process-based asynchronous progress model for MPI one-sided communication on multi-and many-core architectures. The one-sided communication is not truly one-sided in most MPI implementations: the target process still relies on software progress to complete incoming operations. Casper allows the user to specify an arbitrary number of cores dedicated to background ghost processes and transparently redirects the RMA operations to ghost processes by utilizing the PMPI redirection and MPI-3 shared-memory technologies. Although Casper benefits applications that suffer from lack of asynchronous progress, the operation redirection design might not support complex multiphase applications effectively, which often involve dynamically changing communication density and computing workloads. In this paper, we present an adaptive mechanism in Casper to address the limitation of static asynchronous progress in multiphase applications. For this we exploit two adaptive strategies, a user-guided strategy and a fully transparent and automatic strategy based on self-profiling and prediction, to dynamically reconfigure the asynchronous progress in Casper according to real-time performance characteristics during multiphase execution. We evaluate the adaptive approaches in both microbenchmarks and a real quantum chemistry application suite, NWChem, on the Cray XC30 supercomputer and an Intel Omni-Path cluster.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2023

Neural Networks-Based Inverter Control: Modeling and Adaptive Optimization for Smart Distribution Networks

The optimal voltage control of inverter-based resources, especially under the high penetration of solar photovoltaics, is critical to the stability of the distribution power system. However, the computational complexity as well as the coordinated operation performance of the voltage control optimization in the distribution power system limits the real-time applications. To mitigate this issue, a model-free based adaptive optimal control scheme for the smart inverter is proposed to maximize the active power generation, minimize the power loss, and maintain the bus voltages in smart distribution networks. An inverter-based optimization model for coordinated operation is first established, considering the uncertainties of renewable power generation. Subsequently, by collecting the data and control strategies, the neural networks (NNs) based algorithm is proposed to efficiently predict the best possible control strategy. The main objective of this scheme is to accurately predict candidate optimal solutions with near-negligible feasibility and optimization gaps, with the advantage of avoiding complicated iteration-based numerical algorithms. Thereafter, the co-simulation among OpenDSS, MATLAB, and Python is set up to fully take advantage of the three individual software. Experiments are conducted based on different control parameter characteristics and structures of NNs. Finally, the results reveal that an average mean squared error of 0.013 and 1 ms response time are achieved, which is lower than some state-of-the-art methods.

42 ENGINEERING↗

DOE OSTI2019

Lu-Hf and Sm-Nd geochronological constraints on the influence of subduction metamorphism in controlling the Hf-Nd terrestrial array: Evidence from the world’s orogenic belts

To create a better understanding of the influence of subduction metamorphism on the Hf-Nd terrestrial array, this study examines all of the available Lu-Hf and Sm-Nd garnet isochron ages from the world’s orogenic eclogites and amphi bolites. The garnet isochron y-intercept values provide a record of each sample’s epsilon Hf ( ε Hf) and Nd ( ε Nd) at the age recorded by the isochron, which in the case of most orogenic eclogites and amphibolites is the time of prograde metamorphism during subduction. It is further possible to assess the extent to which each sample’s Lu-Hf and Sm-Nd isotope systematics have remained undisturbed since the date recorded by the isochron by comparison of the bulk-rock isotope systematics with the isochron initial value. This approach provides a means of understanding the Lu-Hf and Sm-Nd systematics of post-subduction metamorphic oceanic crust. On a global scale, the coupled Lu-Hf and Sm-Nd isotope systematics of this crust closely align with the Hf-Nd terrestrial array and have average 176 Lu/ 177 Hf and 147 Sm/ 144 Nd ratios within error of the chondritic uniform reservoir values. This is an important finding because it suggests that a reservoir of deeply subducted oceanic crust, possibly residing at the core-mantle boundary, is unlikely to be significantly fractionated from the Hf-Nd terrestrial array. In contrast to the samples of subduction-metamorphosed oceanic crust, metamorphic rocks with a continental crustal protolith demonstrate garnet isochron initial values and bulk-rock Lu-Hf and Sm-Nd isotope systematics indicating significant decoupling from the Hf-Nd terrestrial array. However, because this material is not readily subducted, this strongly decoupled signature is unlikely to be transferred into deep Earth. Mixing calculations aimed at developing a clearer understanding of what factors control decoupling of a sample’s Lu-Hf and Sm-Nd systematics from the Hf-Nd terrestrial array highlight the complexity of mass-transfer regimes operating in the subduction environment.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2018

Risk-Informed Systems Analysis (RISA) Dynamic Fire PRA Roadmap

Modeling and implementing fire safety for nuclear power plants is a costly activity. Because of the complexity of fire phenomenon and multiple operational procedures, it is difficult to computationally provide assurance that the mitigation methods are adequate for critical areas using current analysis methods. An economical method to provide more accurate modeling and optimize mitigation methods is needed to improve nuclear power viability. This report describes the initial investigation into modeling and simulation tools for application of fire as part of the Risk-Informed Systems Analysis (RISA), formerly Risk-Informed Safety Margin Characterization (RISMC). The report provides a framework of how 3D modeling and simulation techniques could be combined with a dynamic Probabilistic Risk Analysis (PRA) to reduce compounding conservatism present in current Fire PRA methods. Electrical Power Research Institute has analyzed current Fire PRA practices and identified the most significant contributors to risk and areas for improving analysis. This framework describes how to apply dynamic PRA and simulation methods for key contributors/scenarios, credit missing factors of manual fire suppression, and applying conditional probabilities.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2018

Literature Review of Potential Thermally Activated Heat Pump Cycles

Thermally driven heat pumps are gaining more strategic value as the electric grid moves toward decentralization. There exists a significant opportunity for them to raise the national primary energy efficiency. Historically, thermally driven heat pumps have been dominated by absorption. It is a mature technology, but it is limited by operational conditions and or cost and complexity. Other thermally driven heat pump cycles and technologies do exist that can provide practical solutions to maximizing the utilization of available heat. This report provides insights into the needed research to leverage the potential of those technologies. An extensive literature review on thermally driven heat pumps was conducted and four promising technologies were reported. The report highlights the research gaps that need to be addressed to mature those technologies.

15 GEOTHERMAL ENERGY↗

DOE OSTI2019

Broad Scope Analysis of the MOX Fuel Fabrication Facility and Disposition of Plutonium

The Plutonium Management and Disposition Agreement (PMDA), signed into effect in 2000, between the United States and Russia, was made in a post-Cold War effort to dispose of military-useable material, a combined 68 metric tons of weapon-grade plutonium. The United States has been pursuing a disposition path through conversion to MOX fuel for use in current commercial nuclear reactors. The Savannah River Site’s (SRS) MOX Fuel Fabrication Facility (MFFF, the MOX facility) began construction in 2007 with intent to uphold the United States’ half of the agreement. In the FY2017 budget, the Obama administration proposed a termination of the MFFF after lack of sufficient funding to the project, which caused paralyzing delays and drastically inflated costs for completion. Prolonged construction, piled costs, and divergent policies between shifting administrations have resulted in turmoil between the United States and Russia, culminating with the proposed abandonment of the MOX disposition path and being used as a justification by Russia to withdraw from the agreement until the United States is able to identify a clear plan, fulfilling the requirements set forth by the PMDA. The leading expedient to replace MOX fuel is the dilute and dispose method, which leaves uncertainty for the SRS MFFF and places reliance on New Mexico’s Waste Isolation Pilot Plant (WIPP) to legally accommodate the additional and unaccounted waste. If the current capacity of WIPP proves insufficient, construction of a new repository for transuranic waste would only incur additional costs and regulatory burdens, along with extreme schedule delays. Future proposed adaptations of the SRS MFFF include pit production, which would require complex and costly alterations to be operational at the current site. Restrictions from Congress, such as mandating the proposed solution to abandoning MFFF must equal half of the costs required for completing the facility, have fueled severely underestimated quotations of these alternatives. The increasing pressure from both Russia and South Carolina government officials to make a decision could result in the pursuit of another doomed project, leaving the United States with even further sunk costs and strained international relations. This paper will summarize the involved history of the MFFF, explicate the recourses to salvage the facility for pit production, and provide postulation on the dilute and dispose method.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2019

Industry Fire Modeling Enhancement Tools and Methods. Light Water Reactor Sustainability Program report

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2019

Mixed Integer Nonlinear Programming Approaches to Enhance Resiliency and Response Strategies in Critical Infrastructure

Motivation. Critical infrastructures are large, complex engineered systems that must be operated robustly under abnormal conditions resulting from natural hazards or intentional acts. For example, electric power systems must be robust to line faults, water utilities must rapidly mitigate contamination incidents, and computing networks must adapt to adversarial intrusions to protect critical information. Problem. It is difficult for decision-makers within resiliency analysis in critical infrastructure to optimize designs and develop effective response strategies that can account for uncertainties. Facing incomplete information and the sheer scope that a natural hazard or attack vector may incorporate, response can be ineffective without reliable, scalable decision support tools. These problems are intrinsically nonlinear and involve discrete decisions, and unfortunately, existing off-the-shelf mathematical programming methods cannot support optimization-based decision-making of these nonlinear at scale. Method/Approach and Results. This project emphasized development of fundamental optimization strategies that supported real- time mitigation and response for critical infrastructures. In particular, the project developed multi- tree approaches based on piecewise outer-approximations for solution of mixed-integer nonlinear programming (MINLP) problems. These techniques alternate between an MILP or MISOCP relaxation to obtain a lower bound and candidate discrete solutions and an NLP subproblem to obtain upper bounds. Using tailored relaxations based on problem structure, these methods were used to solve several key applications in resilience and response of critical infrastructure. This work resulted in two open-source, copyrighted software packages: CORAMIN (https://github.com/Coramin/Coramin) -- an object-oriented mathematical programming framework that supports tailored multi-tree algorithms for solution of large- scale mixed-integer nonlinear programming; and EGRET (Electrical Grid Research and Engineering Toolkit) (https://github.com/grid- parity-exchange/Egret) -- a declarative mathematical programming framework built upon CORAMIN and Pyomo for formulation and solution of resilience and operations problems in power grid systems. Furthermore, these tools resulted in several important published results, including the following: The first known global optimization approach that could solve the unit-commitment problem with nonlinear power flow constraints on medium-sized test problems; Improved parallel optimization-based bounds tightening and strengthening of relaxations of AC power flow constraints; and, Optimization-based approaches for improved grid resilience and use of demand response to improve grid resilience with reduction in capital requirements. Result Implications. This project developed first-of-a-kind algorithms for decision-making in critical infrastructure resilience operations and planning, as well as a next-generation toolkit for MINLP researchers. These approaches leveraged high-performance computing architectures to solve some of the largest, most challenging nonlinear discrete optimization problems to global optimality, and these successes were captured in open-source software to enable optimization-based decision-making, and efficient solution of MINLP formulations for electric power transmission grids.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2021

An Integrated High Pressure SOFC and Premixed Compression Ignition (PCI) Engine System

Components for a transformative, high pressure, intermediate temperature solid oxide fuel cell (SOFC) and premixed compression ignition (PCI) engine system were developed. The resulting system is a 1 MWe natural gas fueled hybrid SOFC and reciprocating internal combustion engine system capable of achieving over 70% electrical efficiency at a cost of $0.87/W. To achieve 70% electric efficiency, the SOFC system operates at 80% fuel utilization; however, when operating at this high level of fuel utilization, fuel to the engine (anode tailgas) is extremely dilute. Accordingly, a substantial portion of the effort focused on development and assessment of the combustion strategy capable of consuming this dilute fuel mixture. The engine testing effort showed that pre-chamber assisted compression ignition provides the best combination of controllability, efficiency and emissions. The engine experiments showed that high efficiency combustion can be achieved with near zero criteria pollutants. It is likely that the engine system could operate with minimal aftertreatment requirements, reducing complexity, cost, and precious metal usage. System level modeling was used to assess the overall efficiency, determine cost and efficiency tradeoffs, and demonstrate the potential to perform load following with the hybrid system. Finally, advanced manufacturing was used to demonstrate the potential to fabricate heat exchangers needed for the hybrid system from low chromium materials, which addresses the issue of chromium poisoning of the SOFC stack material.

03 NATURAL GAS↗

DOE OSTI2021

Microchannel Reactor for Ethanol to Butene: CRADA 503 [Abstract only]

A key challenge facing most bioprocessing operations is that multiple unit operations are required, thereby resulting in complex, energy-intensive, and expensive processes. Further, biomass transportation costs drive the need for smaller, distributed processing plants. To incorporate the smaller scales desirable for biomass, novel processes must be developed with reduced capital costs. With over 20 years of experience in the development and commercialization of microchannel reactor technology, Oregon State University will partner with Pacific Northwest National Laboratory to demonstrate a microchannel reactor with lower capital costs for an alcohol-to-jet (ATJ) process technology that is currently being commercialized by LanzaTech. Ethanol can be produced from biomass feedstocks such as LanzaTech’s proprietary biochemical process using carbon from a number of possible feedstocks; syngas generated from biomass resources (e.g., MSW, organic industrial waste, agriculture waste) or reformed biogas, or from other biomass feedstocks such as corn kernel fiber. Ethanol then undergoes catalytic dehydration to form ethylene followed by a two-step oligomerization, hydrogenation, and fractionation to control the hydrocarbon product slate to the jet-range. Successful process development aided by a market pull for low carbon aviation fuel has spurred scale-up and commercial demonstration. However, Sustainable Aviation Fuel is a very price sensitive market and improved economics through process intensification will make the current ATJ process even more attractive. Recent efforts at PNNL have culminated in the development of a new catalyst technology for the conversion of ethanol to n-butene-rich olefins. A greater than 90% conversion, total olefin selectivity of 80-90% (n-butene selectivity ~60%), and good stability over a 100 hour test duration has been demonstrated at the bench scale. Producing butene-rich olefins directly from ethanol with high yield is new and impactful because the higher olefins can be selectively oligomerized to distillate-range hydrocarbons, thus eliminating one process step from the current ATJ process. Further, coupling the severely endothermic ethanol dehydration with exothermic C-C bond formation results in more energy efficient processing. Additional intensification and energy savings will stem from incorporating this new ethanol to n-butene catalyst technology within the ATJ process implemented using a microchannel reactor platform. Due to recent advances in microchannel manufacturing methods and associated cost reductions we believe the time is right to adapt this technology toward new commercial bioconversion applications.

02 PETROLEUM↗