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At least 451 records · Page 25

Fluoride-Cooled High-Temperature Pebble-Bed Reactor Reference Plant Model Updates

This work presents the latest improvements to, and investigations performed with, the Fluoride-Cooled High-Temperature Pebble-Bed Reactor reference plant models for the United States Nuclear Regulatory Commission. These models, developed with the Comprehensive Reactor Analysis Bundle, or BlueCRAB, serve as the foundation for the future development of detailed design evaluation models based on license applications. BlueCRAB is the code suite proposed for non-light-water reactor systems safety analyses, and it incorporates various simulation tools developed by the Nuclear Energy Advance Modeling and Simulation program, including the Griffin code for reactor physics, the Pronghorn and SAM codes for core thermal fluids, the BISON code for solid conduction and fuel performance, and the SAM code for system analysis. The primary objective of this work is to assess the level of readiness of BlueCRAB for modeling fluoride-cooled high-temperature pebble-bed reactors. We first developed numerical models in BlueCRAB that include the key physics for this technology, ensuring an adequate level of fidelity for modeling the core performance during accident scenarios. This was followed by simulation of transient scenarios, two loss-of-forced-cooling events (one protected and one unprotected), and two control rod withdrawal events (one delayed and one prompt supercritical reactivity insertion). The analysis includes comparisons between the 2-D thermal fluid porous media models in Pronghorn and SAM, comparisons between coupled Pronghorn-Griffin and coupled SAM-Griffin models for two loss-of-forced cooling events and one control rod withdrawal event, and comparisons between SAM single-solve and domain-overlapping approaches for multi-scale thermal fluid coupling. In addition, we performed comparisons between 3-D, 2-D, and 0-D neutronic models for the two control rod withdrawal scenarios with Pronghorn-Griffin. The results show that the BlueCRAB models led to physically intuitive solutions for the scenarios examined. The changes in the various scalar and vector fields such as the neutron flux, power, temperatures, densities, pressures, and velocities are all within the expected ranges, and their distributions can be explained from the system response of the transients and the geometric and material variations. Several comparisons suggest that the porous media models in Pronghorn and SAM can lead to similar solutions, even though they are based on different methodologies. The simulations demonstrate that there are differences between the various levels of fidelity, and it is advisable to have flexible tools that can cover the breadth and depth of needs that may arise in future technical evaluations. We believe that BlueCRAB’s capabilities represent a significant asset for confirmatory analyses aimed at resolving important safety questions.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Hidden symmetries, spin and charge of artificial magnetic monopoles

Here, we discuss the non-Abelian artificial magnetic monopoles associated with n-level energy crossing in quantum systems. We found that hidden symmetries reveal themselves as observables such as spin, hypercharge, and other physical degrees of freedom. We illustrated our results on concrete examples of two and three energy-level crossings. Our findings can be helpful for modeling various phenomena in physical systems such as SU(N) topological insulators and spintronic devices based on topological insulators.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Green synthesis and characterization of nontoxic L-methionine capped silver and gold nanoparticles

The simple green method for synthesis of stable L-Methionine (L-Met) capped silver (Ag@LM NPs) and gold (Au@LM NPs) nanoparticles (NPs) without adding any additional reduction agent or stabilizer was developed. Colloidal dispersions were characterized by UV–Vis spectrophotometry. The size and spherical shape of NPs were evaluated by transmission electron microscopy. Their surface covering was confirmed by atomic force microscopy, Fourier transform infrared spectroscopy, dynamic light scattering, and zeta potential measurements. Density functional theory calculations pointed that the preferential adsorption mode of L-Met on both Ag and Au surfaces was a vertical binding geometry via –NH2 group, while horizontal binding mode via [sbnd]S[sbnd] and –NH2 groups is also possible. The genotoxicity (evaluated by the micronucleus assay) of NPs, as well as their effects on some oxidative stress parameters (catalase activity, malondialdehyde level), were assessed in vitro using human peripheral blood cells as a model system. The influence of NPs on the morphology of lymphocyte cells studied using atomic force microscopy revealed that the membrane of cells remained unaffected after the treatment with NPs. When considering the effects of NPs on catalase activity and malondialdehyde level, neither particle type promoted oxidative stress. However, the treatment of lymphocytes with Ag@LM NPs induced a concentration-dependent enhancement of the micronuclei incidence and suppression of the cell proliferation while Au@LM NPs promoted cell proliferation, with no significant effects on micronuclei formation. The Ag@LM NPs were more prone to induce DNA damage than Au@LM NPs, which makes the latter type more suitable for further studies in nano-medicine. © 2019.

60 APPLIED LIFE SCIENCES↗

Engineering tertiary chirality in helical biopolymers

Tertiary chirality describes the handedness of supramolecular assemblies and relies not only on the primary and secondary structures of the building blocks but also on topological driving forces that have been sparsely characterized. Helical biopolymers, especially DNA, have been extensively investigated as they possess intrinsic chirality that determines the optical, mechanical, and physical properties of the ensuing material. Here, we employ the DNA tensegrity triangle as a model system to locate the tipping points in chirality inversion at the tertiary level by X-ray diffraction. We engineer tensegrity triangle crystals with incremental rotational steps between immobile junctions from 3 to 28 base pairs (bp). We construct a mathematical model that accurately predicts and explains the molecular configurations in both this work and previous studies. Our design framework is extendable to other supramolecular assemblies of helical biopolymers and can be used in the design of chiral nanomaterials, optically active molecules, and mesoporous frameworks, all of which are of interest to physical, biological, and chemical nanoscience.

Science & Technology - Other Topics↗

Historical Hydropower Operations and Economic Value

This report on historical hydropower operations and economic value focuses primarily on addressing HydroWIRES Objective 1.3: Advance valuation of conventional and pumped-storage hydropower assets. It is informed by previous work performed by Argonne and other national laboratories on the modeling and analysis of value of pumped storage and conventional hydropower. The results from this report will feed into the new projects that are planned under the HydroWIRES initiative and that will examine hydropower’s value in providing grid reliability and resilience, as well as in improving the modeling and representation of hydropower in power system models. Other relevant DOE efforts include various WPTO-funded projects, such as the Beyond Levelized Cost of Energy Project and Integrated Hydropower and Storage Systems, that are currently addressing similar challenges associated with defining grid service values that arise from hydropower machine capabilities.

13 HYDRO ENERGY↗

Plant Nutrition Influences Resistant Maize Defense Responses to the Fall Armyworm ( Spodoptera frugiperda )

Plants are often confronted by different groups of herbivores, which threaten their growth and reproduction. However, they are capable of mounting defenses against would-be attackers which may be heightened upon attack. Resistance to insects often varies among plant species, with different genotypes exhibiting unique patterns of chemical and physical defenses. Within this framework, plant access to nutrients may be critical for maximal functioning of resistance mechanisms and are likely to differ among plant genotypes. In this study, we aimed to test the hypothesis that access to nutrition would alter the expression of plant resistance to insects and alter insect performance in a manner consistent with fertilization regime. We used two maize (Zea mays) genotypes possessing different levels of resistance and the fall armyworm (Spodoptera frugiperda) as model systems. Plants were subjected to three fertilization regimes prior to assessing insect-mediated responses. Upon reaching V4 stage, maize plants were separated into two groups, one of which was infested with fall armyworm larvae to induce plant defenses. Plant tissue was collected and used in insect bioassays and to measure the expression of defense-related genes and proteins. Insect performance differed between the two plant genotypes substantially. For each genotype, fertilization altered larval performance, where lower fertilization rates hindered larval growth. Induction of plant defenses by prior herbivory substantially reduced naïve fall armyworm growth in both genotypes. The effects between fertilization and induced defenses were complex, with low fertilization reducing induced defenses in the resistant maize. Gene and protein expression patterns differed between the genotypes, with herbivory often increasing expression, but differing between fertilization levels. The soluble protein concentrations did not change across fertilization levels but was higher in the susceptible maize genotype. These results demonstrate the malleability of plant defenses and the cascading effects of plant nutrition on insect herbivory.

54 ENVIRONMENTAL SCIENCES↗

Solar and Storage Integration in the U.S. Southeast: Implications for Resource Adequacy

Resource adequacy concerns may be very different in electricity systems that have higher levels of solar and storage, requiring changes to existing planning models. This study explores a novel approach to evaluating resource adequacy under future scenarios with higher solar and storage in the Southeast U.S. It uses NREL’s Probabilistic Resource Adequacy Suite (PRAS), a collection of probabilistic resource adequacy modeling tools, and compares results when interacting PRAS and a portfolio planning tool with a more traditional modeling approach. The results suggest that traditional models perform reasonably well with lower levels of solar PV, but at higher levels of solar probabilistic tools better capture the changes in resource adequacy concerns—such as winter energy availability—associated with higher solar systems. This is the final study in the Preparing Southeast Markets for Reliable and Affordable Integration of Solar into Operations and Planning project. Two prior reports can be found at: Solar and Storage Integration in the Southeastern United States: Economics, Reliability, and Operations. https://emp.lbl.gov/publications/solar-and-storage-integration Solar and Wind Forecast Error Reserve Sharing in a Multi-Utility Region. https://eta-publications.lbl.gov/sites/default/files/2024-11/multiutility_fe_reserve_sharing_final.pdf

14 SOLAR ENERGY↗

2022 Peer Review Project Summary: Advanced Protection for Microgrids and DER in Secondary Networks and Meshed Distribution Systems

Although there are increasing numbers of distributed energy resources (DERs) and microgrids being deployed, current IEEE and utility standards generally strictly limit their interconnection inside secondary networks. Secondary networks are low-voltage meshed (non-radial) distribution systems that create redundancy in the path from the main grid source to each load. This redundancy provides a high level of immunity to disruptions in the distribution system, and thus extremely high reliability of electric power service. There are two main types of secondary networks, called grid and spot secondary networks, both of which are used worldwide. In the future, primary networks in distribution systems that might include looped or meshed distribution systems at the primary-voltage (mediumvoltage) level may also become common as a means for improving distribution reliability and resilience. The objective of this multiyear project is to increase the adoption of microgrids in secondary networks and meshed distribution systems by developing novel protection schemes that allow for safe reliable operation of DERs in secondary networks. We will address these challenges by working with the appropriate stakeholders of secondary network operators, protection vendors, and standards committee. The outcomes of this project include: a) development and/or demonstration of candidate methods for enabling protection of secondary networks containing high levels of DER; b) development of modeling and testing tools for protection systems designed for use with secondary networks including DERs; and c) development of new industrial partnerships to facilitate widespread results dissemination and eventual commercialization of results as appropriate.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Continuous-time look-ahead flexible ramp scheduling in real-time operation

This paper develops a novel continuous-time look-ahead optimization model for co-optimizing balancing energy and flexible ramp products in real-time power systems operation. In addition, a continuous-time day-ahead operation model is developed to commit and schedule an adequate subset of generating units for providing balancing energy and ramping requirements in real-time operation. The up and down flexible ramp products are defined as continuous-time decision trajectories that continuously supply the real-time up and down ramping requirements of the system. The deliverability of flexible ramp products is secured through reserving the respective power requirements in generation capacity constraints of generating units. A function space solution method is proposed to reduce the dimensionality of day-ahead and real-time models through projecting them into finite-dimensional function spaces spanned by Bernstein polynomials, where the real-time operation decisions are modeled with a higher accuracy level than day-ahead decisions. Simulations are conducted on the IEEE-RTS system using CAISO load data, and the numerical results showcase the effectiveness of the proposed model in supplying the energy and flexible ramp requirements and avoiding ramping scarcity in the system, while reducing the operation costs.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Gas-Cooled High-Temperature Pebble-Bed Reactor Reference Plant Model Updates

This work presents the latest improvements to, and investigations performed with, the pebble-bed high-temperature gas-cooled reactor (PB-HTGR) reference plant models for the United States Nuclear Regulatory Commission. These models serve as the foundation for the future development of detailed design evaluation models based on license applications. The reference plant models have been developed with the Comprehensive Reactor Analysis Bundle, or BlueCRAB, which is the code suite proposed for non-light-water reactor systems safety analysis. It incorporates various simulation tools developed by the Nuclear Energy Advanced Modeling and Simulation program, including the Griffin code for reactor physics, the Pronghorn and SAM codes for core thermal fluids, the BISON code for solid conduction and fuel performance, and the SAM code for system analysis. The primary objective of the work that was performed was to assess BlueCRAB’s level of readiness for modeling a PB-HTGR. To do so, we first developed numerical models in BlueCRAB that include the key physics for this technology to ensure an adequate level of fidelity for modeling PB-HTGR core performance and for performing multiphysics simulations for equilibrium core conditions and different accident scenarios. Then we simulated transient scenarios, including depressurized and pressurized loss of forced cooling accidents, over-cooling, and control rod withdrawal events with delayed and prompt supercritical reactivity insertions. The analysis in this report includes comparisons of the 2D thermal fluid porous media models in Pronghorn and SAM, and comparisons of coupled SAM/Griffin/SAM and coupled Pronghorn/Griffin for depressurized and pressurized loss of forced cooling, over-cooling, and control rod withdrawal events. In addition, we compare 3D, 2D, and 0D/PKE neutronic models for the two control rod withdrawal scenarios with coupled Pronghorn/Griffin. The comparisons show that the BlueCRAB models lead to physically intuitive solutions for the scenarios examined. The changes in the various scalar and vector fields, such as neutron flux, power, temperature, density, pressure, and velocity, are within the expected ranges, and their distributions can be explained by the system response of the transients and the geometric and material variations. Several comparisons suggest that the porous media models in Pronghorn and SAM can lead to similar solutions, even though they are based on different methodologies. This work further highlights the need for flexible tools with various levels of fidelity to cover the breadth and depth of needs that may arise in future technical evaluations of the PB-HTGR. We believe that the BlueCRAB capabilities will be a significant asset for confirmatory analyses in order to resolve important safety questions.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Nitrogen and phosphorus cycling in an ombrotrophic peatland: a benchmark for assessing change

Aims Slow decomposition and isolation from groundwater mean that ombrotrophic peatlands store a large amount of soil carbon (C) but have low availability of nitrogen (N) and phosphorus (P). To better understand the role these limiting nutrients play in determining the C balance of peatland ecosystems, we compile comprehensive N and P budgets for a forested bog in northern Minnesota, USA. Methods N and P within plants, soils, and water are quantified based on field measurements. The resulting empirical dataset are then compared to modern-day, site-level simulations from the peatland land surface version of the Energy Exascale Earth System Model (ELM-SPRUCE).

Salmon, Verity G.↗

FY2020 Energy Efficient Mobility Systems Annual Progress Report

EEMS Program activities during FY 2020 focused on analytical research and large-scale modeling and simulation to understand the impacts that new mobility technologies and services will have at the vehicle-, traveler-, and overall transportation system-level. This research included the development of a multi-fidelity, end-to-end transportation system models and tools to evaluate the complex interactions among the various actors within the mobility landscape, analysis of empirical data to characterize which solutions may provide the largest benefits, and development of new control systems and algorithms that use vehicle connectivity and automation to improve the performance and efficiency of individual vehicles as well as the overall traffic system. This document presents a brief overview of the EEMS Program and documents progress and results from projects within each of the EEMS activity areas. The Computational Modeling and Simulation key activity area summarizes work within the sub-areas of (1) the SMART (Systems and Modeling for Accelerated Research in Transportation) Mobility Lab Consortium, (2) Artificial Intelligence, High-Performance Computing, and Data Analytics, and (3) Core Simulation and Evaluation Tools. Additionally, the program’s advanced R&D projects are summarized within (4) the Connectivity and Automation Technology key activity area. Each of the individual progress reports provide a project overview and highlights of the technical results.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

US energy system transitions under cumulative emissions budgets

Cumulative emissions budgets are increasingly being used by decision makers and analysts to understand emissions reductions and associated transitions in the context of long-term goals such as limiting global mean temperature increase over the century to 1.5 or 2°C (IPCC, 2014). While previous studies have explored the implications of cumulative emissions budgets for the global economy, few studies have conducted regional and national-level analyses (Iyer et al., 2015; Riahi et al., 2015). This paper explores cumulative emissions budgets through 2050 consistent with the 1.5 and 2°C long-term temperature goals in the context of the United States. We employ a state-level model of the United States embedded within a global human-Earth system model (GCAM-USA) to study the implications of such budgets for the U.S. energy system (Iyer et al., 2017a; Iyer et al., 2017b). Our results show that achieving the stringent cumulative emissions budgets entails accelerated deployment of energy conserving technology, almost complete decarbonization of the power sector and increased electrification of buildings and industrial end-use sectors and decarbonization of transport employing a combination of electrification and the substitution of bioenergy for fossil fuels by the mid-century. We also find substantial state-level differences in the relative roles of these decarbonization strategies. Furthermore, our results highlight that increased ambition in the near-term will be valuable in setting the stage for smoother transformations in the future to achieve stringent cumulative emissions budgets consistent with long-term temperature goals established by the international community.

Feijoo, Felipe↗

Simulating large one-dimensional neutral-atom quantum systems

While abstract models of quantum computation assume a closed system of two-level states, practical quantum devices inevitably couple to the environment in some way, creating sources of noise. Understanding the tolerance to noise of specific quantum algorithms run on specific devices is important for determining the feasibility of quantum computing in the current noisy intermediate-scale quantum era. Of particular interest is understanding the noise sensitivity of these devices as more qubits are added to the system. Classical simulations are a useful tool to understand the effects of this noise, but direct classical simulations of open quantum systems are burdened by an exponentially growing cost in the number of qubits and a large local Hilbert space dimension. For onedimensional, shallow circuits, using tensor networks can replace this exponential cost with a linear one and simulate far wider systems than what would normally be available. In this paper, we describe a tensor network simulation of a neutral atom quantum system under the presence of noise, while introducing a purity-preserving truncation technique that compromises between the simplicity of the matrix product state and the positivity of the matrix product density operator. We apply this simulation to a near-optimized iteration of the quantum approximate optimization algorithm on a transverse field Ising model in order to investigate the influence of large system sizes on the performance of the algorithm. We find that while circuits with a large number of qubits fail more often under noise that depletes the qubit population, their outputs on a successful measurement are just as robust under Rydberg atom dissipation or qubit dephasing as smaller systems. However, such circuits might not perform as well under coherent multiqubit errors such as Rydberg atom crosstalk. We also find that the optimized parameters are especially robust to noise, suggesting that a noisier quantum system can be used to find the optimal parameters before switching to a cleaner system for measurements of observables.

Allen, James↗

From Atoms to Wheels: The Role of Multi-Scale Modeling in the Future of Transportation Electrification

Traditionally, prototype hardware is built for validation testing to ensure battery systems design changes meet vehicle-level requirements, which is expensive both in cost and time. Virtual engineering (VE) of battery systems for electric vehicle (EV) propulsion offers a reduced-cost alternative to the traditional development process and uses multi-scale modeling to virtually probe the impact of design changes in a particular part on the overall performance of the system. This allows for rapid iteration over multiple design spaces, without committing to build hardware. This perspective article discusses current trends in VE for EV applications and proposes improvements to accelerate EV adoption.

Garrick, Taylor R. (ORCID:0000000322518129)↗

Validation of Power Distribution Models using Load Flow Analysis in an ADMS Environment

Electric utilities are facing the need for better monitoring, analysis, and control of their distribution systems. An accurate mathematical model is a key to both the development of cutting-edge, scalable model-based algorithms and the assessment of emerging technologies such as distributed energy resources (DER) for grid planning and operation. However, the constantly evolving nature of power distribution systems poses challenges to maintaining accurate models. In this paper, we propose a novel load flow based approach to validate power distribution models. Networked equipment models described according to the Common Information Model (CIM) standard and a measurement model are used to formulate the distribution load flow problem. First, a system admittance matrix (Ybus) is derived from device-level CIM parameters. Next, the operational parameters (dynamic Ybus and nodal injections) are extracted from the measurement model using sensor configuration and equipment state. An iterative power flow method is then used to compute nodal voltages and branch flows that are compared against the measurement data to find any inconsistencies in the networked equipment model. This approach is implemented within GridAPPS-D, an open-source standards-based platform for advanced distribution management system (ADMS) application development, and demonstrated on the IEEE 13-bus, 123-bus, and 8500-node test feeders.

Common information model, model validation, power ↗

SPIDARman: System-Level Physics-Informed Detection of Anomalies in Reactor Collected Data Considering Human Errors

In nuclear power plants (NPPs), anomalies arising from sensors or human errors (HEs) can undermine the performance and reliability of plant operations. Anomaly detection models can be employed to detect sensor errors and HEs. Additionally, physics-informed machine learning models can utilize the known physics of the system, as described by mathematical equations, to ensure that sensor values are consistent with physical laws. Hence, we propose SPIDARman: System-level Physics-Informed Detection of Anomalies in Reactor Collected Data Considering Human Errors, a holistic physics-informed anomaly detection approach based on generative adversarial networks (GANs) to detect anomalies in both automatically collected sensor data and manually collected surveillance data. Here we test our approach on data collected from a flow loop testbed, showcasing its potential to detect anomalies. Results demonstrate that the proposed model performs better than the baseline GAN-based models in detecting sensor and surveillance anomalies, suggesting the potential of physics-informed anomaly detection GAN models in NPPs.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

What Questions Would a Systems Engineer Ask to Assess Systems Engineering Models as Credible

Digital Systems Engineering strategies typically call for digital Systems Engineering models to be retained in repositories and certified as an authoritative source of truth (enabling model reuse, qualification, and collaboration). In order for digital Systems Engineering models to be certified as authoritative (credible), they need to be assessed - verified and validated - and with the amount of uncertainty in the model quantified (consider reusing someone else's model without knowing the author). Due to this increasing model complexity, the authors assert that traditional human-based methods for validating, verifying, and uncertainty quantification - such as human-based peer-review sessions - cannot sufficiently establish that a digital Systems Engineering model of a complex system is credible. Digital Systems Engineering models of complex systems can contain millions of nodes and edges. The authors assert that this level of detail is beyond the ability of any group of humans - even working for weeks at a time - to discern and catch every minor model infraction. In contrast, computers are highly effective at discerning infractions with massive amounts of information. The authors suggest that a better approach might be to focus the humans at what model patterns should be assessed and enable the computer to assess the massive details in accordance with those patterns - by running through perhaps 100,000 test loops. In anticipation of future projects to implement and automate the assessment of models at Sandia National Laboratories, a study was initiated to elicit input from a group of 25 Systems Engineering experts. The authors positioning query began with - 'What questions would a Systems Engineer ask to assess Systems Engineering models for credibility?" This report documents the results of that survey.

42 ENGINEERING↗