Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “optimization of nuclear systems”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 775 records · Page 43
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Single-shot in-line x-ray phase-contrast imaging of void-shockwave interactions in fusion energy materials

Recent breakthroughs in nuclear fusion, specifically the report of reactions exceeding scientific breakeven at the National Ignition Facility (NIF), highlight the potential of inertial fusion energy (IFE) as a sustainable and virtually limitless energy source. However, further progress in IFE requires characterization of defects in ablator materials and how they affect fuel capsule compression. Voids within the ablator can degrade energy yield, but their impact on the density distribution has primarily been studied through simulations, with limited high-resolution experimental validation. To address this, we used the x-ray free-electron laser (XFEL) at the matter in extreme conditions (MECs) instrument at the Linac coherent light source (LCLS) to capture 2D x-ray phase-contrast (XPC) images of a void-bearing sample with a composition similar to inertial confinement fusion (ICF) ablators. By driving a compressive shockwave through the sample using MEC's long-pulse laser system, we analyzed how voids influence shockwave propagation and density distribution during compression. To quantify this impact, we extracted phase information using two phase retrieval algorithms. First, we applied the contrast transfer function (CTF) method, paired with Tikhonov regularization and a fast optimization approach to generate an initial phase estimate. We then refined the result using a projected gradient descent (PGD) method that works directly with the sample's refractive index. Comparing these results with radiation adaptive grid Eulerian (xRAGE) radiation hydrodynamic simulations enables identification of model validation needs or improvements. By calculating phase maps in situ, it becomes possible to reconstruct areal density maps, improving understanding of laser-capsule interactions and advancing IFE research.

Hodge, D. S. [Colorado State Univ., Fort Collins, ↗
DOE OSTI2020

Evolution of the ROOT Tree I/O

The ROOT TTree data format encodes hundreds of petabytes of High Energy and Nuclear Physics events. Its columnar layout drives rapid analyses, as only those parts (“branches”) that are really used in a given analysis need to be read from storage. Its unique feature is the seamless C++ integration, which allows users to directly store their event classes without explicitly defining data schemas. In this contribution, we present the status and plans of the future ROOT 7 event I/O. Along with the ROOT 7 interface modernization, we aim for robust, where possible compile-time safe C++ interfaces to read and write event data. On the performance side, we show first benchmarks using ROOT’s new experimental I/O subsystem that combines the best of TTrees with recent advances in columnar data formats. A core ingredient is a strong separation of the high-level logical data layout (C++ classes) from the low-level physical data layout (storage backed nested vectors of simple types). We show how the new, optimized physical data layout speeds up serialization and deserialization and facilitates parallel, vectorized and bulk operations. This lets ROOT I/O run optimally on the upcoming ultra-fast NVRAM storage devices, as well as file-less storage systems such as object stores.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Empirically Optimized One-Electron Pseudopotential for the Hydrated Electron: A Proof-of-Concept Study

Mixed quantum-classical molecular dynamics simulations have been important tools for studying the hydrated electron. They generally use a one-electron pseudopotential to describe the interactions of an electron with the water molecules. Furthermore, this approximation shows both the strength and weakness of the approach. On the one hand, it enables extensive statistical sampling and large system sizes that are not possible with more accurate ab initio molecular dynamics methods. On the other hand, there has (justifiably) been much debate about the ability of pseudopotentials to accurately and quantitatively describe the hydrated electron properties. These pseudopotentials have largely been derived by fitting them to ab initio calculations of an electron interacting with a single water molecule. In this paper, we present a proof-of-concept demonstration of an alternative approach in which the pseudopotential parameters are determined by optimizing them to reproduce key experimental properties. Specifically, we develop a new pseudopotential, using the existing TBOpt model as a starting point, which correctly describes the hydrated electron vertical detachment energy and radius of gyration. In addition to these properties, this empirically optimized model displays a significantly modified solvation structure, which improves, for example, the prediction of the partial molar volume.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2024

Production of Astatine-211 for Translational Science in Radiotherapy (Research Performance Progress Report)

In this proposal we outline the methods to improve the isotope production of astatine-211 at the University of Pennsylvania Cyclotron Facility. Astatine-211 is an isotope that emits alpha- radiation and has high potential for treating otherwise untreatable cancers. The goal of this proposal is two fold, 1) Optimize current production of astatine-211 and maintain routine production and 2) develop new isotope production target systems and chemical isolation systems. By completing this proposal we will ensure that the University of Pennsylvania Cyclotron Facility continues to build it’s isotope program in an effort that unites under DOE isotope network supply initiatives with the overall goal of increasing the national supply of isotopes. The University of Pennsylvania is uniquely located in the northeast corridor of the United States of America and has access to dozens of institutions that could use astatine-211 in their research. With the support of the DOE we have the opportunity to provide additional momentum to this growing field of research and will be able to provide the foundation for economical development of astatine-211 research and application in medicine.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2023

Prehydrodynamic evolution in large and small systems

We extend our previous investigation of the effects of prehydrodynamic evolution on final-state observables in heavy-ion collisions [38] to smaller systems. We use a state-of-the-art hybrid model for the numerical simulations with optimal parameters obtained from a previous Bayesian study. By studying p–Pb collisions, we find that the effects due to the assumption of a conformal evolution in the prehydrodynamical stage are even more important in small systems. We also show that this effect depends on the time duration of the pre-equilibrium stage, which is further enhanced in small systems. Finally, we show that the recent proposal of a free-streaming with subluminal velocity for the pre-equilibrium stage, thus effectively breaking conformal invariance, can alleviate the contamination of final-state observables. Furthermore, our study further reinforces the need for moving beyond conformal approaches in pre-equilibrium dynamics modeling, especially when extracting transport coefficients from hybrid models in the high-precision era of heavy-ion collisions.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Anion exchange and extraction chromatography tandem column isolation of zirconium-89 ( 89 Zr) from cyclotron bombarded targets using an automated fluidic platform

The long-lived positron emitter 89 Zr is a highly promising nuclide employed in diagnostic Positron Emission Tomography (PET) imaging. Methods of radiochemical processing to obtain 89 Zr for clinical use are traditionally performed with a single hydroxamate resin column. In this work, we present a tandem column purification method for the preparation of high-purity 89 Zr from cyclotron bombarded Y metal foils. The primary column is a macroporous, strongly basic anion exchange resin on styrene divinylbenzene co-polymer. The secondary microcolumn, with an internal volume of 33 µL, is packed with an extraction chromatography resin (ExCR) loaded with HDEHP. A condition of “inverted selectivity” is presented, wherein the 89 Zr elution from the primary column is synonymous with the load condition on the secondary column. The ability to transfer 89 Zr from one column to the next allows two sequential column clean-up methods to be performed prior to the final elution of the 89 Zr product. This approach assures delivery of very high purity 89 Zr . The tandem column purification process has been implemented into a prototype automated fluidic system. Optimization of the method is presented, followed by evaluation of the process using seven cyclotron bombarded Y metal foil targets. Once optimized, we found that 93.7±2.3% of the 89 Zr present in the foils was recovered in the secondary column elution fraction (0.8 M oxalic acid). Radiochromatograms of the product elution peaks enabled determination of full width at half-maximum (FWHM) and 89 Zr collection yields as a function of volume. Because of the small size of the secondary microcolumn, a 89 Zr product volume of ~0.28 mL is reported, which provides a substantially increased nuclide concentration over traditional methods. Finally, we evaluated the transchelation of the resulting 89 Zr oxalate product to deferoxamine mesylate (DFOM) salt. We observed effective specific activities (ESA) and bindable metals concentrations ([M B ]) that exceed those reported by the traditional single hydroxamate column method.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2020

DUNE DAQ R&D integration in ProtoDUNE Single-Phase at CERN

The DAQ system of ProtoDUNE-SP successfully proved its design principles and met the requirements of the beam run of 2018. The technical design of the DAQ system for the DUNE experiment has major differences compared to the prototype due to different requirements placed on the detector, as well as a radically different location of operation. The single-phase prototype at CERN is a major integration facility for R&D aspects of the DUNE DAQ system. The facility allows for the exploration of additional data processing capabilities and optimization of the FELIX system, which is the chosen TPC readout solution for the DUNE single-phase detectors. One of the fundamental differences from the prototype is that the DUNE DAQ relies on self-triggering. Therefore, real-time processing of the data stream for hit and trigger primitive finding is essential for the requirement of continuous readout. The supernova burst trigger requires a large and fast buffering technique, where 3D XPoint persistent memory solutions are evaluated and integrated. In order to maximize resource utilization of the FELIX hosting servers, the elimination of the 100 Gb network communication stack is desired. This implies the design and development of a single-host application layer, which is a fundamental element of the self-triggering chain. This paper discusses the evaluation and integration of these developments for the DUNE DAQ, in the ProtoDUNE environment.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

Wireless Sensor Modalities at a Nuclear Plant Site to Collect Vibration Data

One of the major contributors to the total operating costs of domestic nuclear fleet of reactors today is the operation and maintenance (O&M) costs. These include labor-intense preventive maintenance programs involving manually-performed inspection, calibration, testing, and maintenance of plant assets at periodic frequency and time-based replacement of assets at periodic frequency, irrespective of their conditions. This has resulted in a labor-centric business model to achieve high capacity factors. To build an optimal maintenance program, it’s time to transition from this labor-centric business model to a technology-centric business model. Fortunately, there are technologies (advanced sensor, data analytics, and risk assessment methodologies) that will support this transition. The technology-centric business model will result in significant plant life extension and reduction of time-based maintenance activities. This will drive down O&M costs as labor is a rising cost and technology is a declining cost. This approach will lay the foundation for real-time condition assessment of plant assets, allowing condition-based maintenance to enhance plant safety, reliability, and economics of operation. The goal of this project is to address challenges in the area of digital monitoring, i.e., the application of advanced sensor technologies (particularly wireless sensor technologies) and science-based data analytic capabilities to advance online monitoring and predictive maintenance in nuclear plants to improve plant performance (efficiency gain and economic competitiveness). To achieve the project goal, in partnership with Exelon Generating Company (Exelon), researchers from Idaho National Laboratory (INL) and Oak Ridge National Laboratory (ORNL) are performing research and development (R&D) to demonstrate application of wireless sensors using the distributed antenna system and advanced data analytics to achieve predictive maintenance. In the report, wireless vibration sensors, vibration data and its indicator are described. The wireless vibration sensors presented in this report support three types of wireless communication, namely, Wi-Fi, cellular, and 900 MHz. These wireless vibration sensors are considered by partner plant site for installation on plant asset to enable online vibration monitoring to replace periodic measurements. These vibration data along with other plant process data will be utilized to develop diagnostic and prognostic models.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Thermodynamic Modeling of Complex Solid Solutions in the Lu-H-N System via Graph Neural Network Accelerated Monte Carlo Simulations

Metal hydrides are important across diverse applications, such as hydrogen storage, batteries, gas sensors, nuclear reactions, and high-temperature superconductivity. Previous computational studies of metal hydrides under extreme pressures, e.g., 𝑂⁡(10 2 ) ⁢GPa, usually treat them as stoichiometric compounds without considering interstitial lattice disorder. As pressures become more moderate in the 𝑂⁡(10 0 ) ⁢GPa and below range, hydrogen disorder at interstitial lattice sites becomes prominent, e.g., in the N-doped Lu hydride that was recently claimed superconducting near 1 GPa. Further adding compositional complexity from alloying and/or multielement interstitial occupation makes elucidating pressure- and temperature-dependent observables intractable by first-principles calculations alone. We therefore propose a lattice graph neural-network surrogate modeling approach to predict configuration- and pressure-dependent equation-of-state properties. Their efficiency permits Monte Carlo simulations to calculate Gibbs energies and pressure-dependent phase diagrams, thereby revealing insights into the synthesis conditions required for achieving desired phase equilibria. We demonstrate this concept for the compositionally complex cubic Lu(H,N,Va) 3 system where three constituents (hydrogen, nitrogen and vacancy) have disordered multielement interstitial occupancies and insights into pressure-dependent phase equilibria are critically needed, e.g., N-doping levels can significantly lower dehydrogenation temperatures and provide a new strategy to optimize hydrogen-storage alloys. This work can improve the thermodynamic understanding of the Lu-H-N system and help rational synthesis of N-doped Lu hydrides, but more generally demonstrates an efficient approach to model pressure-dependent thermodynamics of multicomponent solid solutions.

Monte Carlo methods↗
DOE OSTI2022

Enabling machine learning-ready HPC ensembles with Merlin

With the growing complexity of computational and experimental facilities, many scientific researchers are turning to machine learning (ML) techniques to analyze large scale ensemble data. With complexities such as multi-component workflows, heterogeneous machine architectures, parallel file systems, and batch scheduling, care must be taken to facilitate this analysis in a high performance computing (HPC) environment. Here, we present Merlin, a workflow framework to enable large ML-friendly ensembles of scientific HPC simulations. By augmenting traditional HPC with distributed compute technologies, Merlin aims to lower the barrier for scientific subject matter experts to incorporate ML into their analysis. As a producer–consumer workflow model, Merlin enables multi-machine, cross-batch job, dynamically allocated yet persistent workflows capable of utilizing surge-compute resources. Key features of Merlin are a flexible HPC-centric interface, low per-task overhead, multi-tiered fault recovery, and a hierarchical sampling algorithm that allows for $\mathscr{O}$(N) task execution and $\mathscr{O}$(N ln N) task queuing to ensembles of millions of tasks. In addition to Merlin’s design, we test the algorithm’s performance in an HPC center and demonstrate the ability to enqueue 40 million simulations in 100 s, with a 30 millisecond per-task overhead that is independent of ensemble size. Finally, we describe some example applications that Merlin has enabled on leadership-class HPC resources, such as the ML-augmented optimization of nuclear fusion experiments and the calibration of infectious disease models to study the progression of and possible mitigation strategies for COVID-19.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

LensingETC: A Tool to Optimize Multifilter Imaging Campaigns of Galaxy-scale Strong Lensing Systems

Imaging data is the principal observable required to use galaxy-scale strong lensing in a multitude of applications in extragalactic astrophysics and cosmology. In this paper, we develop Lensing Exposure Time Calculator (LensingETC; to optimize the efficiency of telescope-time usage when planning multifilter imaging campaigns for galaxy-scale strong lenses. This tool simulates realistic data tailored to specified instrument characteristics and then automatically models them to assess the power of the data in constraining lens model parameters. We demonstrate a use case of this tool by optimizing a two-filter observing strategy (in the IR and ultraviolet-visual (UVIS)) within the limited exposure time per system allowed by a Hubble Space Telescope (HST) Snapshot program. We find that higher resolution is more advantageous to gain constraining power on the lensing observables, when there is a trade-off between signal-to-noise ratio and resolution; for example, between the UVIS and IR filters of the HST. We also find that, whereas a point-spread function (PSF) with sub-Nyquist sampling allows the sample mean for a model parameter to be robustly recovered for both galaxy–galaxy and point-source lensing systems, a sub-Nyquist-sampled PSF introduces a larger scatter than a Nyquist-sampled one in the deviation from the ground truth for point-source lens systems.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Inference of response functions with the help of machine-learning algorithms

Response functions are a key quantity to describe the near-equilibrium dynamics of strongly interacting many-body systems. Recent techniques that attempt to overcome the challenges of calculating these ab initio have employed expansions in terms of orthogonal polynomials. We employ a neural network prediction algorithm to reconstruct a response function 𝑆⁡(𝜔) defined over a range in frequencies 𝜔. Here, we represent the calculated response function as a truncated Chebyshev series whose coefficients can be optimized to reduce the representation error. We compare the quality of response functions obtained using coefficients calculated using a neural network (NN) algorithm with those computed using the Gaussian integral transform (GIT) method. In the regime where only a small number of terms in the Chebyshev series are retained, we find that the NN scheme outperforms the GIT method.

Kurkcuoglu, Doga Murat [Fermi National Accelerator↗
DOE OSTI2024

Economically Viable Intermediate to Long Duration Hydrogen Energy Storage Solutions for Fossil Fueled Assets

This report was prepared as an account of work sponsored by the Office of Fossil Energy and Carbon Management of U.S. Department of Energy under Funding Opportunity Announcement Number DE-FOA-0002332 “Energy Storage for Fossil Power Generation”. The work aimed to explore and advance an innovative hydrogen energy storage system – the synergistically integrated hydrogen energy storage system (SIHES) – that has the following characteristics: • Compatible with existing or new coal and gas fuel electricity generation units, • best suited for intermediate to long duration energy storage, from 12 hours to weeks even months, and • capable of storing energy at the utility scale – hundreds of MWh to GWh energy storage with power output level in tens to hundreds of MW. Preliminary front-end engineering design (Pre-FEED) studies was carried out to develop and refine a site-specific SIHES as peaking power generation units (so named as HyPeaker) as the first market entry point, to demonstrate both the technical feasibility and the economic viability to integrate the HyPeaker “within the fence” of a fossil power plant. This specific site was TVA’s Johnsonville Combustion Turbine Plant. The HyPeaker was designed and engineered to integrate with a 60MW aeroderivative gas turbine unit already available at TVA’s Johnsonville site. This site-specific HyPeaker consists of an alkaline electrolyzer to produce hydrogen from CO 2 free electricity sources, an innovative low-cost high-pressure hydrogen storage system (Big-Ton) and the aero gas turbine to generate electricity using blend of hydrogen and natural gas. A holistic system level technoeconomic analysis tool specific to HyPeaker was developed to optimize the engineering design of the Johnsonville site-specific HyPeaker for cost and performance. The optimal design and specification of the Johnsonville site-specific HyPeaker are the following: • Alkaline electrolyzer: 3MW • Big-Ton storage vessel: 11,000kg H 2 at 3000psi. • 4-stage diaphragm hydrogen compressor: 55kg-H 2 /hr from 150psi to 3000psi. The HyPeaker is designed to provide sufficient hydrogen for 90% continuous operation of the HyPeaker. All major components have design life of 30 years. The capex of HyPeaker is estimated at $\$$7.1M. This included $\$$1.5M for the electrolyzer, $\$$5.6M for the storage vessel and compressor. The cost of aero gas turbine was included as it is already available at the site. Key findings are: • HyPeaker can be designed, manufactured, installed and integrated with the fossil power plants, with sub-systems and components commercially available on the market today, even when it is scaled up to an order of magnitude larger than the one at the Johnsonville site. HyPeaker is a technologically viable solution to cover a wide range of energy storage duration needs, from daily peaking operation to seasonal shifting for fossil fueled assets. • The cost advantage of SCCV based Big-Ton H 2 storage vessel made it possible to “oversize” the H 2 storage subsystem to achieve overall system level cost optimization. The benefits are two-fold. First, it allows to significantly reduce the capacity and cost of electrolyzer by spreading H 2 production over a much longer period of time when the fuel cost for electricity production is low. Second, it allows to balance the hydrogen production and usage shift over weeks to months to meet the peak demands. As such, the capital cost of HyPeaker system using the Big-Ton was less than half of the cost of a system with today’s steel tube based H 2 storage system. The HyPeaker has even better cost advantage Li-ion battery based energy storage system. The estimated capital cost of Li-Ion battery system would be at $\$$38M, under the same projected 20-year electricity generation profile of the Johnsonville site. This is over 5 times more expensive than the HyPeaker system. • Since industry scale energy storage systems do not have 100% energy conversion and storage efficiency, energy storage systems using fossil fuel generated electricity would increase the CO 2 emission. This is particularly the case for HyPeaker due to its low round trip efficiency. Therefore, a more sensible solution would be to the excessive or curtailed electricity from CO 2 emission free sources such as solar farms, wind farms or nuclear power plants, to produce hydrogen, and integrate them with the HyPeaker. Electricity from TVA’s nuclear power plants was used for the Johnsonville HyPeaker. • The economic viability of HyPeaker is expected to be further improved when global supply chains are taken into consideration. For the same Johnsonville site specific HyPeaker, the capex would be reduced to ~$\$$3.6M from ~$\$$7.1M, and the added LCOE is reduced to ~$\$$85/MWh. With the bipartisan Infrastructure Investment and Jobs Act, the cost of domestically produced HyPeaker sub-systems would be at the level of today’s global suppliers. Since the peaking units generally operate at peak usage period, thereby demanding higher price, the projected $\$$85/MWh LCOE would be within the realm of financial viability for utility operators.

08 HYDROGEN↗
DOE OSTI2025

Flow Enhanced Electrochemical Sensor Performance in Complex Salt Systems

To advance MSR MC&A practices, Argonne National Laboratory developed and optimized robust flow enhanced electrochemical sensors (FEES) and multielectrode array voltammetry sensors (MAVS) which provide accurate near-real time measurements of actinides in molten salts. Flow-enhanced electrochemical sensors are installed directly into MSR flow conduits for inline salt chemistry measurement, while MAVS are deployed in quiescent salt conditions enabling online species concentration determination in stationary salt vessels. This report summarizes efforts to improve electrochemical sensor technological readiness through (1) sensor testing in complex, high concentration molten salt systems to demonstrate low uncertainty actinide measurements in MSR-representative solutions and (2) demonstrations of sensor performance in challenging real-world conditions in collaboration with partner MSR institutions.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

A SiPM-based optical readout system for the EIC dual-radiator RICH

Silicon photomultipliers (SiPM) are candidates selected as the potential photodetector technology for the dual-radiator Ring-Imaging Cherenkov (dRICH) detector at the future Electron-Ion Collider (EIC). SiPM are cheap devices, highly efficient and insensitive to the high magnetic field at the expected location of the sensors in the experiment. Here, on the other hand, SiPM are not radiation tolerant. Despite the integrated radiation level is expected to be moderate it should be tested whether single photon-counting capabilities and the increase in dark count rate can be kept under control to maintain the optimal dRICH detector performance across the years. The current status of the research for the EIC dRICH application and the first results on studies performed on a sample of commercial and prototype SiPM sensors are presented.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

Stochastic Analysis for Long Term Capital Structures, Systems, and Components Refurbishment and Replacement

As commercial Nuclear Power Plants (NPPs) pursue extended plant operation in the form of Second License Renewal (SLR), opportunities exist for these plants to provide capital investments to ensure long-term safe and economic performance. At the current time, several utilities have announced an intention to pursue extended operation for one or more of their NPPs via SLR . The goal of this research is to develop a risk-informed approach to evaluate and prioritize plant capital investments made in preparation for, and during the period of, extended plant operations to support decisions for NPP operations. Since the capital investments are influenced by various factors, such as markets, safety and regulatory, the decision-making process of NPP operations should take into account relevant factors for balancing risks, costs and profits. The traditional method of capital budgeting is based on the priority list of candidate projects using economic measures such as benefit-investment ratio, net present value (NPV) and internal rate of return. In the literatures, the problem of capital budgeting or the variant can be represented by an appropriate knapsack problem. The knapsack approach to capital budgeting takes as input as investment, along with the cost and profit of each project. The objective of capital budgeting is to find the combination of the binary decisions for every investment such that the overall profit is as large as possible. The output is a collection of projects to be carried out, and we refer this selected collection of projects as a project portfolio. One limitation of traditional optimization models for capital budgeting is that they do not account for risk/uncertainty in profit and cost streams associated with individual projects, they do not account for risk in resource availability in future years [1,2,3]. Projects can incur cost over-runs, especially when projects are large, performed infrequently, and when there is risk regarding technical viability, external contractors, and/or suppliers of requisite parts and materials. Occasionally, projects are performed ahead of schedule and with cost savings. Planned budgets for capital improvements can be cut and key personnel may be lost. Or, there may be surprise windfalls in budgets for maintenance activities due to decreased costs for “unplanned” maintenance. In these cases, how should we resolve capital budgeting when we have risk forecasts for costs, profits and budgets? One approach we proposed in this summary is to re-solve the optimization models based on assumed statistical distributions of given parameters. If these distributions were not available, a two-stage stochastic optimization approach can be used to provide priority lists to decision-makers to support better risk-informed decisions [4, 5]. In this summary, we will only focus on the first approach.

42 ENGINEERING↗
DOE OSTI2022

Three-dimensional Skyrme Hartree-Fock-Bogoliubov solver in coordinate-space representation

The coordinate-space representation of the Hartree-Fock-Bogoliubov theory is the method of choice to study weakly bound nuclei whose properties are affected by the quasiparticle continuum space. To describe such systems, we developed a three-dimensional Skyrme-Hartree-Fock-Bogoliubov solver HFBFFT based on the existing, highly optimized and parallelized Skyrme-Hartree-Fock code Sky3D. The code does not impose any self-consistent spatial symmetries such as mirror inversions or parity. The underlying equations are solved in HFBFFT directly in the canonical basis using the fast Fourier transform. To remedy the problems with pairing collapse, we implemented the soft energy cutoff and pairing annealing. The convergence of HFB solutions was improved by a sub-iteration method. The Hermiticity violation of differential operators brought by Fourier-transform-based differentiation has also been solved. Furthermore, the accuracy and performance of HFBFFT were tested by benchmarking it against other HFB codes, both spherical and deformed, for a set of nuclei, both well-bound and weakly-bound.

3D coordinate-space representation↗
DOE OSTI2023

Novel refractory high-entropy metal-ceramic composites with superior mechanical properties

A new concept of refractory high-entropy metal-ceramic composites (HEMCC) has been proposed that combines the outstanding physical properties of both high-entropy alloy (HEA) and high-entropy ceramic (HEC). As the first HEMCC system, to the best of our knowledge, TiTaNbZr-(TiTaNbZr)C, has been developed by a powder metallurgy process. The HEA and HEC phases exhibit body-centered cubic (BCC) and rock-salt B1 crystal structures, respectively, and both phases have non-equimolar chemical compositions. Further, with the increase of the HEC phase in HEMCC, the hardness is enhanced while the density and fracture toughness are decreased. HEA50C sintered from 50vol% HEA and 50vol% HEC precursor powders shows a favorable combination of flexural strength (541±48MPa) and fracture toughness (6.93±0.27 MPa·m 1/2 ) at room temperature and a high compressive strength at 1300ºC (275MPa). The optimized mechanical performance of HEMCC might be attributed to the combination of the ductile HEA and strong HEC phases, smaller grain size, and crack arrest at HEC/HEA interfaces.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗