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At least 1,153 records · Page 64

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DOE OSTI2025

Self-Heating Conductive Ceramic Composites for High Temperature Thermal Energy Storage

The absence of affordable and deployable large-scale energy storage poses a major barrier to providing zero-emission energy on demand for societal decarbonization. High temperature thermal energy storage is one promising option with low cost and high scalability, but it is hindered by the inherent complexity of simultaneously satisfying all of the material requirements. Here we design a class of ceramic–carbon composites based on co-optimizing mechanical, electrical, and thermal properties. Further, these composites demonstrate stability in soak-and-hold tests and direct self-heating up to 1,936 °C and 750 thermal cycles from 500 to 1,630 °C without degradation. This thermal performance derives from their composition and microstructural design as verified by in situ high-temperature transmission electron microscopy and X-ray diffraction. They offer both higher energy density and lower cost than conventional storage technologies with a projected system Levelized Cost of Storage below the U.S. Department of Energy’s 2030 target 5 ¢/kWh (electric).

25 ENERGY STORAGE↗

DOE OSTI2025

Multi-faceted framework for extrapolating early age flexural strength to facilitate rapid lifting/handling of high-volume fly ash precast members

Maintaining adequate early-age structural performance for precast concrete components has grown in importance as more sustainable mix designs become more widespread. Achieving high-early flexural strength is particularly crucial to facilitate rapid removal of hardened concrete components from formwork, often within 24 h after fresh concrete placement. Limited research has assessed the effectiveness of traditional design methods in correlating flexural strength with compressive strength for next-generation mix designs, or demonstrated extrapolation of such material performance to larger-scale structural tests. This paper presents a multi-faceted framework to reassess early-age flexural strength for concretes made with relatively high proportions of fly ash from both fresh and harvested sources. Here, the framework provides several pathways, from which the user can select based upon available resources and the specific application, to improve accuracy of early-age cracking moment calculations. Furthermore, the scope includes evaluation of strength performance under curing conditions emulative of those in a precast facility, recommending modulus of rupture equations which are more performance-driven than current design provisions, and experimental tests on prefabricated concrete beams to validate the proposed methodologies. Correlations of early-age strength with both concrete age and maturity measurements compare the effectiveness of utilizing in-situ data to further enhance the prediction methods. Ultimately, the proposed framework helped reduce errors when calculating cracking moment capacity at early ages by tailoring calculations to reflect mix-dependent behavior. Furthermore, most estimates of cracking moment were within 25 % of their corresponding experimental test results, thus promoting confidence for using these strategies with high-volume fly ash precast structures.

42 ENGINEERING↗

DOE OSTI2021

Fast GPU-Based Generation of Large Graph Networks From Degree Distributions

Synthetically generated, large graph networks serve as useful proxies to real-world networks for many graph-based applications. The ability to generate such networks helps overcome several limitations of real-world networks regarding their number, availability, and access. Here, we present the design, implementation, and performance study of a novel network generator that can produce very large graph networks conforming to any desired degree distribution. The generator is designed and implemented for efficient execution on modern graphics processing units (GPUs). Given an array of desired vertex degrees and number of vertices for each desired degree, our algorithm generates the edges of a random graph that satisfies the input degree distribution. Multiple runtime variants are implemented and tested: 1) a uniform static work assignment using a fixed thread launch scheme, 2) a load-balanced static work assignment also with fixed thread launch but with cost-aware task-to-thread mapping, and 3) a dynamic scheme with multiple GPU kernels asynchronously launched from the CPU. The generation is tested on a range of popular networks such as Twitter and Facebook, representing different scales and skews in degree distributions. Results show that, using our algorithm on a single modern GPU (NVIDIA Volta V100), it is possible to generate large-scale graph networks at rates exceeding 50 billion edges per second for a 69 billion-edge network. GPU profiling confirms high utilization and low branching divergence of our implementation from small to large network sizes. For networks with scattered distributions, we provide a coarsening method that further increases the GPU-based generation speed by up to a factor of 4 on tested input networks with over 45 billion edges.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2022

Metal‐Organic Framework (MOF) Morphology Control by Design

Abstract Exerting morphological control over metal‐organic frameworks (MOFs) is critical for determining their catalytic performance and to optimize their packing behavior in areas from separations to fuel gas storage. A mechanism‐based approach to tailor the morphology of MOFs is introduced and experimentally demonstrated for five cubic Zn 4 O‐based MOFs. This methodology provides three key features: 1) computational screening for selection of appropriate additives to change crystal morphology based on knowledge of the crystal structure alone; 2) use of additive to metal cluster geometric relationships to achieve morphologies expressing desired crystallographic facets; 3) potential for suppression of interpenetration for certain phases.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2023

Reinforcement Learning for Load-balanced Parallel Particle Tracing

We explore an online reinforcement learning (RL) paradigm to dynamically optimize parallel particle tracing performance in distributed-memory systems. Our method combines three novel components: (1) a work donation algorithm, (2) a high-order workload estimation model, and (3) a communication cost model. First, we design an RL-based work donation algorithm. Our algorithm monitors workloads of processes and creates RL agents to donate data blocks and particles from high-workload processes to low-workload processes to minimize program execution time. The agents learn the donation strategy on the fly based on reward and cost functions designed to consider processes' workload changes and data transfer costs of donation actions. Second, we propose a workload estimation model, helping RL agents estimate the workload distribution of processes in future computations. Third, we design a communication cost model that considers both block and particle data exchange costs, helping RL agents make effective decisions with minimized communication costs. We demonstrate that our algorithm adapts to different flow behaviors in large-scale fluid dynamics, ocean, and weather simulation data. Our algorithm improves parallel particle tracing performance in terms of parallel efficiency, load balance, and costs of I/O and communication for evaluations with up to 16,384 processors.

Distributed and parallel particle tracing↗

DOE OSTI2024

Intermediate Scale Test Platform Conceptual Design and Hybrid Resin Performance Evaluation Recommendations

Recent laboratory evaluations demonstrated that further testing of alternative hybrid resins is warranted for their potential use as part of the 200 West Area (200W) pump-and-treat (P&T) remedy. 200W P&T has been treating technetium (Tc) since 2012 and uranium (U) since 2015 via two separate ion exchange (IX) treatment units: a single treatment train (i.e., a three-vessel system) for the removal of uranium utilizing a gel strong base anion (SBA) exchange resin, Dowex 21K; and two parallel treatment trains for the removal technetium using a gel SBA resin, Purolite® A532E. While these resins have been removing these contaminants effectively, new hybrid resins can provide additional benefits of further optimizing the IX treatment unit capacities and addressing additional treatment needs (e.g., Cr(VI)) by removing multiple contaminants simultaneously and/or through specific design configurations. Some of these resins also demonstrated some level of removal for I-129 which would be significant for expansion of the P&T into the 200 East Area. This document provides design recommendations for an intermediate scale test platform (ISTP) to evaluate alternative hybrid IX resin performance under conditions approaching field scale and using 200W P&T process groundwater. Results from the ISTP will provide the technical basis required to inform alternative IX resin selection in future 200W P&T facility operations where the treatment of multiple contaminants of concern may be required.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2020

Sensitivity and Uncertainty Quantification of Transition Scenario Simulations

This report documents the first collective attempt at developing and applying capabilities to quantify uncertainties, assess parametric sensitivities, and optimize multiple parameters and metrics in fuel cycle simulations generated by the SA&I Campaign. To do this, external codes that were designed to perform sensitivity analysis and uncertainty quantification (SA&UQ) needed to be coupled to the SA&I Campaign’s nuclear fuel cycle simulators (NFCS). In FY20, two approaches were pursued: 1) coupling Cyclus to an ORNL-internal code called MOT (Metaheuristic Optimization Tool) and 2) coupling DYMOND to the opensource SA&UQ tool kit Dakota. The primary objective of having these NFCS/SA&UQ coupled capabilities is to better inform DOE-NE and other stakeholders on the results generated from the NFCS. For a given set of fuel cycle strategies, policies, and technology assumptions that make up a fuel cycle scenario, these NFCS have traditionally been used by the SA&I Campaign to provide quantitative answers in terms of year-by-year mass flows, infrastructure requirements, costs, etc. With these newly developed coupled capabilities, the SA&I Campaign can now efficiently simulate hundreds or thousands of these scenarios, sample large ranges of parameters and assumptions, and use the unique features of the SA&UQ tools to process the data. This enables providing answers with known and propagated uncertainties, determining the sensitivity of important metrics to different parameters and assumptions, quantifying how much fuel cycle and technology parameters impact each other, and producing optimized fuel cycle strategies for single and multiple variables. To demonstrate these new capabilities, the Cyclus/MOT was used to model several scenarios ranging from simple fleet retirements to transitions to advanced reactors. Specifically, for a transition scenario from LWRs to SFRs and advanced LWRs, uncertainty quantification, sensitivity analysis, and optimization studies were applied to cases involving single and multiple parameter (input) and single and multiple metric (output) variations. In addition, a similar transition scenario was modeled to demonstrate how to optimize the reprocessing capacity parameter to minimize two performance metrics while taking into account uncertainties from two other parameters. Lastly, a depletion module based on SCALE/ORIGEN was added in Cyclus to simulate the third scenario that was designed to quantify the impact of the modeling assumption that all LWR used nuclear fuel have the same burnup. The newly developed DYMOND/Dakota capability was also applied to a transition scenario from the existing fleet to small modular reactors and fast reactors. This particular scenario involves not only explicit isotopic depletion via ORIGEN-2, but also includes multirecycling and utilizing the criticality search feature to determine the fresh fuel composition of recycled fuel, a feature unique to the DYMOND NFCS. A large database of simulations were run with 4 main parameters that were sampled: start date of reprocessing, reprocessing capacity, energy demand growth rate, and advanced reactor share of the fleet. The 4 main metrics were uranium consumption, enrichment requirements, waste generation, and levelized cost of electricity using data from the Cost Basis Report. The demonstrated SA&UQ results include those that inform on how to choose parameters to avoid “failed” scenarios, Sobol’ indices that inform on the importance of various parameters individually and synergistically, and Analysis of Variance (ANOVA) studies that decompose parameter ranges into groups and informs on whether variations are statistically significant.

Feng, B.↗

DOE OSTI2020

Performance simulation of the soft gamma-ray concentrator

The soft gamma-ray concentrator is a telescope mission concept utilizing a suitable arrangement of bent multilayer structures of alternating low- and high-density materials. This lens is able to channel gamma-ray photons via total external reflection and concentrate the incident radiation to a point. The channeling technique offers the potential for concentrating gamma rays with focal lengths <10 m and energies >100 keV, beyond the reach of current grazing-incidence hard x-ray mirrors. For the performance estimation of such an instrument, we have developed a flexible set of computer modeling tools to compute the optical properties of multilayer structures, predict the channeling efficiency for a given multilayer configuration, and aid in the optimization of potential gamma-ray concentrator-based telescope designs. This modeling includes the multilayer optical properties calculated by the IMD software, the ray tracing using an IDL code, and the focal plane detector simulation by MEGAlib. We illustrate the potential of this approach by presenting simulated astronomical observations from a balloon-borne platform. The final result, including simulated effective area, instrument sensitivity, and polarization performance, shows that the gamma-ray concentrator will provide greatly increased sensitivity for next-generation soft gamma-ray missions with modest cost and complexity.

47 OTHER INSTRUMENTATION↗

DOE OSTI2021

Technoeconomic Analysis of Novel PV Plant Designs for Extreme Cost Reductions

This project sought to gain a deeper understanding of the cost and performance of future solar photovoltaic (PV) plant components, including bifacial PV modules, tandem PV modules, increased plant voltage architectures, and module-level power electronics, and how they may be integrated into new PV plant designs to significantly reduce the levelized cost of electricity (LCOE) of PV. This was done through extensive modeling of current PV plants and future technologies in three different locations, informed by a comprehensive literature review and informational interviews to develop performance and cost assumptions for these technologies. Sensitivities were conducted to understand tradeoffs between different design options, such as the added energy from increasing row spacing versus additional land costs. An optimization tool was then created utilizing an evolutionary algorithm to determine an optimal PV plant configuration for a given set of technologies that resulted in minimized plant LCOE based upon typical performance and cost inputs.

14 SOLAR ENERGY↗

DOE OSTI2025

Openpronghorn

OpenPronghorn is a simulation tool specifically tailored for modeling thermal-hydraulic phenomena in advanced nuclear reactors. It is built on the Multiphysics Object-Oriented Simulation Environment (MOOSE), an open-source platform that facilitates the development of high-performance scientific computing applications. OpenPronghorn solves the Navier-Stokes equations, which describe the conservation of mass, momentum, and energy in fluid flows, using the finite volume numerical method. The code supports a wide range of fluid flow conditions that are applicable to nuclear reactors, including incompressible and weakly compressible flows, as well as single-phase and multiphase flows. It is capable of modeling diverse flow regimes, including laminar and turbulent flows, using various turbulence models such as the standard k-epsilon models, the v2f model, and the mixing length model. For multiphase flows, OpenPronghorn employs a mixture a Eulerian modeling approach with mixture, drift-flux, and full Eulerian models, and includes open-sourced interfacial transfer correlations for drag, exchange, and heat transfer coming from the scientific literature. OpenPronghorn's modular design allows it to handle multiscale simulations, ranging from detailed Reynolds-Averaged Navier Stokes (RANS) simulations to coarse-mesh and lumped parameter models. This flexibility enables users to perform high-fidelity simulations of specific reactor components as well as system-level analyses of entire reactor circuits. The code can be coupled with other MOOSE-based tools using the MultiApp system, allowing for the transfer of coupling quantities such as mass flow rates, heat fluxes, and boundary conditions between different simulation scales. One of the main features of OpenPronghorn is the it includes built-in validation cases from the open-source scientific literature and supports the implementation of user-defined models and correlations through MOOSE's FunctorMaterial system. OpenPronghorn is designed to be computationally efficient, leveraging the SIMPLE projection method for large-scale problems, and can be run on high-performance computing systems to handle the extensive computational demands of detailed reactor simulations. Overall, OpenPronghorn is a versatile and robust tool that provides critical insights into the thermal-hydraulic behavior of advanced nuclear reactors, supporting the design, safety, and optimization of next-generation nuclear energy systems.

Retamales, Mauricio Eduardo Tano [Idaho National L↗

DOE OSTI2024

ECAR-6440 Rev 2 MARVEL Hazard Evaluation

This hazard evaluation supports the Microreactor Applications Research, Validation, and Evaluation (MARVEL) Project’s design effort and the development of the preliminary documented safety analysis (PDSA) (addendum to safety analysis report [SAR]-420, “Transient Reactor Test [TREAT] Facility FSAR”) (SAR-420-ADD-1). The hazard evaluation process for the MARVEL project for compliance with the requirements in 10 CFR 830, “Nuclear Safety Management,” follows a process similar to the Licensing Modernization Project (LMP) as outlined in Nuclear Energy Institute (NEI)-18-04, “Risk-Informed Performance-Based Guidance for Non-Light Water Reactor Licensing Basis Development,” and supporting documents. The LMP process is adapted to fit Department of Energy (DOE) reactor regulatory requirements as applicable and appropriate using a graded approach based on the MARVEL microreactor design. This approach provides reasonable assurance of meeting the requirements of 10 CFR 830 for protection of the public, workers, and environment.

21 - SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLAN↗

DOE OSTI2021

An Overview of Non-LWR Vessel Cooling Systems for Passive Decay Heat Removal (Technical Letter Final Report)

The following report provides a technical review of various reactor vessel cooling system (VCS) concepts under consideration for decay heat removal (DHR) in non-light water advanced reactor designs. This review focuses on ex-vessel designs, including the Reactor Cavity Cooling System (RCCS), the Reactor Vessel Auxiliary Cooling System (RVACS), and hybrid iterations, using both air and water cooling to achieve their heat removal function. Based on a literature review of publicly available sources published between 1979 and 2021, a technical summary is presented detailing existing and planned VCS design options, their applicability to specific reactor type, and review of authored research and development studies. Following an assessment of the availability of data and modeling tools, an evaluation was performed analyzing their likely performance during normal, degraded, and accident conditions, including reliability, stability, and longevity. With renewed consideration of air-based DHR systems by some US vendors, there is a need to fully understand the complexities inherent to natural circulation systems, and more importantly, how they may influence safety-related heat removal functions and system performance. For DHR systems that rely on air-based mode of cooling, this entails quantification of the impacts of low flow conditions during start-up, relative elevations of inlet and outlet ducts for below-grade installations, effects of the use of multiple parallel chimneys for redundancy, and impact of weather conditions at the plant site. For systems relying on water-based mode cooling, reliance on limited coolant inventory in an event of pipe break or extended duration accident scenarios, sensitivities related to stability of boiling flow and heat transfer conditions, and quantification of full-scale structural vibrations on balance of plant structures are among the complicating factors.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2020

Broadband Characterization and Circuit Model Development of Transmission-Scale Transformers

This report describes broadband measurements of transmission-scale transformers typical in the electric power grid. This work was performed as part of the EMP Resilient Grid LDRD project at Sandia National Laboratories to generate circuit models that can be used for high-altitude electromagnetic pulse (HEMP) coupling simulations and response predictions. The objective of the work was to obtain characterization data of substation yard equipment across a frequency range relevant to HEMP. Vector network analyzer measurements up to 100 MHz were performed on two power transformers at ABB-Hitachi and a single ITEC potential transformer. Custom cable breakouts were designed to interface with the transformer terminals and provide ground connections to the chassis at the base of the transformer bushings. The three-phase terminals of the power transformers were measured as a common mode impedance using a parallel resistive splitter, and the single-phase terminals of the potential transformer were measured directly. A vector fitting algorithm was used to empirically fit circuit models to the resulting two-port networks and input impedances of the measured objects. Simplified circuit representations of the input impedances were also generated to assess the degree of precision needed for high-altitude electromagnetic pulse response predictions, which were performed in Sandia's XYCE circuit simulator platform. HEMP coupling simulations using the transformer models showed significant reduction in the voltage peak and broadening in the pulse width seen at the power transformer compared to the traveling wave voltage. This indicated the importance of the load condition when defining the coupled insult in an electric power substation. Simplified circuit models showed a similar voltage at the transformer with a smoothed waveform. The presence of potential transformers in the simulation did not significantly change the simulated voltage at the power transformer. Single-port input impedance models were also developed to define load conditions when transfer characteristics were not necessary.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2021

Deployable Wind-Hybrid Power Systems for Defense and Disaster Response Applications

This report presents an analysis of the performance of deployable energy systems comprised of wind energy systems integrated with diesel generators, photovoltaic systems, and battery storage to meet the load requirements of a representative U.S. Army forward operating base. The analysis is conducted using HOMER, a microgrid analysis software that can search through a wide range of parameters to design and optimize microgrid power systems. The search parameters include the system architecture, the wind and solar resources, and the availability of diesel fuel. The results of the analysis measure the relative performance of the different systems and environments in terms of the overall transportation cost to deploy the system and the ability to provide resilience in terms of meeting mission critical loads.

02 PETROLEUM↗

DOE OSTI2021

Occupant-Centric key performance indicators to inform building design and operations

Building performance indicators are widely used to guide building design and track and benchmark operational performance. Traditional building performance indicators mostly focus on the energy efficiency perspective. As occupants are the primary building service recipients in residential and most commercial buildings, their comfort and wellbeing are crucial. As such, this study first identified significant attributes of occupant-centric key performance indicators (KPIs) and analyzed the diverse factors that should be considered in formulating an occupant-centric KPI. Then a suite of occupant-centric KPIs were synthesized from the review and enhancement of existing occupant-related performance metrics. The proposed occupant KPIs represent the occupant lens on three integrative aspects of building performance: resource use (including energy and water), indoor environmental quality, and human–building interactions. A simulation-based case study was conducted to demonstrate how occupant-centric KPIs can be used to quantify the impacts of building operation changes from the occupants’ point of view. Highlights: Occupant-centric metrics are currently ad hoc and limited, yet crucial to inform building design and operations. Literature was reviewed to reveal the state-of-the-art and gaps of occupant-centric metrics. A suite of occupant-centric key performance indicators (KPIs) covering five groups of building services were synthesized. Proposed occupant KPIs represent three aspects of performance: resource use and demand, occupant comfort and health, and human–building interactions. A case study using whole building simulation was conducted to demonstrate the use of occupant-centric KPIs in evaluating building operations during a power outage.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2020

Rendezvous algorithms for large-scale modeling and simulation

Rendezvous algorithms encode a communication pattern that is useful when processors sending data do not know who the receiving processors should be, or vice versa. The idea is to define an intermediate decomposition where datums from different sending processors can ”rendezvous” to perform a computation, in a manner that both the senders and eventual receivers of the results can identify the appropriate rendezvous processor. Though they were originally designed for interpolating between overlaid grids with independent parallel decompositions (Plimpton et al., 2004), we have recently found rendezvous algorithms useful for a variety of operations in particle- or grid-based simulation codes when running large problems on large numbers of processors. In particular, we show they can perform well when a load-balanced intermediate decomposition is randomized and not spatial, requiring all-to-all communication to move data between processors. In this case rendezvous algorithms leverage the large bisection communication bandwidths which parallel machines provide. We describe how rendezvous algorithms work in a scientific computing context and give specific examples for molecular dynamics and Direct Simulation Monte Carlo codes which result in dramatic performance improvements versus simpler algorithms which do not scale as well. We explain how a generic rendezvous algorithm can be implemented, and also point out similarities with the MapReduce paradigm popularized by Google and Hadoop.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2020

Dakota A Multilevel Parallel Object-Oriented Framework for Design Optimization Parameter Estimation Uncertainty Quantification and Sensitivity Analysis: Version 6.12 Theory Manual

The Dakota toolkit provides a flexible and extensible interface between simulation codes and iterative analysis methods. Dakota contains algorithms for optimization with gradient and nongradient-based methods; uncertainty quantification with sampling, reliability, and stochastic expansion methods; parameter estimation with nonlinear least squares methods; and sensitivity/variance analysis with design of experiments and parameter study methods. These capabilities may be used on their own or as components within advanced strategies such as surrogate-based optimization, mixed integer nonlinear programming, or optimization under uncertainty. By employing object-oriented design to implement abstractions of the key components required for iterative systems analyses, the Dakota toolkit provides a flexible and extensible problem-solving environment for design and performance analysis of computational models on high performance computers. This report serves as a theoretical manual for selected algorithms implemented within the Dakota software. It is not intended as a comprehensive theoretical treatment, since a number of existing texts cover general optimization theory, statistical analysis, and other introductory topics. Rather, this manual is intended to summarize a set of Dakota-related research publications in the areas of surrogate-based optimization, uncertainty quantification, and optimization under uncertainty that provide the foundation for many of Dakota's iterative analysis capabilities.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2021

Dakota A Multilevel Parallel Object-Oriented Framework for Design Optimization Parameter Estimation Uncertainty Quantification and Sensitivity Analysis (V.6.14) (Theory Manual)

97 MATHEMATICS AND COMPUTING↗