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DOE OSTI2025

The Viskores User's Guide (V.1.0)

High-performance computing relies on ever finer threading. Advances in processor technology include ever greater numbers of cores, hyperthreading, accelerators with integrated blocks of cores, and special vectorized instructions, all of which require more software parallelism to achieve peak performance. Traditional visualization solutions cannot support this extreme level of concurrency. Extreme scale systems require a new programming model and a fundamental change in how we design algorithms. To address these issues we created Viskores: the visualization toolkit for multi-/many-core architectures. Viskores supports a number of algorithms and the ability to design further algorithms through a top-down design with an emphasis on extreme parallelism. Viskores also provides support for finding and building links across topologies, making it possible to perform operations that determine manifold surfaces, interpolate generated values, and find adjacencies. Although Viskores provides a simplified high-level interface for programming, its template-based code removes the overhead of abstraction.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

The Viskores User's Guide, Release 1.1

High-performance computing relies on ever finer threading. Advances in processor technology include ever greater numbers of cores, hyperthreading, accelerators with integrated blocks of cores, and special vectorized instructions, all of which require more software parallelism to achieve peak performance. Traditional visualization solutions cannot support this extreme level of concurrency. Extreme scale systems require a new programming model and a fundamental change in how we design algorithms. To address these issues we created Viskores: the visualization toolkit for multi/many-core architectures. Viskores supports a number of algorithms and the ability to design further algorithms through a top-down design with an emphasis on extreme parallelism. Viskores also provides support for finding and building links across topologies, making it possible to perform operations that determine manifold surfaces, interpolate generated values, and find adjacencies. Although Viskores provides a simplified high-level interface for programming, its template-based code removes the overhead of abstraction.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

On the Road to Achieving Safety Excellence at the Idaho Cleanup Project: The Initial Challenges, Solutions, and Positive Results of Striving to be the Best and Safest in the DOE Complex - 20518

When Fluor Idaho, LLC (Fluor Idaho) assumed the Idaho Cleanup Project Core contract (ICP Core) in mid-2016, it inherited the successful multi-faceted, employee-owned safety programs of two prior contractors supporting cleanup operations at the Idaho National Laboratory Site. Fluor Idaho incorporated the best of both safety programs along with Fluor Corporate's 106-year legacy of safety initiatives and successes. Fluor Idaho integrated the separate programs and cultures under a One Fluor approach - one project, one mission, One Fluor. Job changes, management changes, and procedures, processes, and system changes presented multiple challenges. Those challenges combined with the severe Winter of 2016/2017 resulted in numerous slips, trips, and falls first aids and reportable injuries. The road to safety excellence started off bumpy and stayed that way for some time. Since then, Fluor Idaho has successfully implemented several key initiatives including employee engagement; management engagement and time in the field; communications improvements; safety culture sustainment; injury/illness prevention; organizational learning; and DOE Voluntary Protection Program (VPP) readiness and preparation. Management became more engaged by making more workplace visits and increasing their supervision of 'life critical work' or complex activities. Additional training became mandatory for first-line supervisors and front-line workers. Most recently, Fluor Idaho increased its injury and illness prevention initiatives extensively. In the last year, things have turned around in a dramatic way. This shift is directly attributable to the significant number of initiatives launched in late 2017 and 2018. These initiatives addressed safety performance in the five key areas of the DOE VPP and promoted sustainability of the company's safety culture. The five key areas are: management leadership, employee involvement, work-site analysis, hazard prevention and control, and safety and health training. Employees and managers alike recommitted to making safety the highest value. The result of this laser-like focus on safety and accident and injury prevention is that injuries and first aids are a fraction of what they were. During FY 2019, employees worked more than 4.2 million hours without a serious injury or lost work-day and 1 million hours without a recordable injury. Fluor Idaho is proud of its safety trend. The company invested significant resources in improving its safety record, and that investment is paying off. Other contractors in the DOE Complex can learn and benefit from this discussion of the challenges Fluor Idaho faced, as well as its innovative safety initiatives that are producing results that are being recognized by our U.S. Department of Energy (DOE) customer. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2025

Metadata Standards for the NSE: Core Fields

This standard presents a core set of metadata fields required for each managed digital object within the Nuclear Security Enterprise (NSE). Metadata standardization is a critical enabler for two primary objectives: 1) effectively sharing data, documents, and other digital objects between NSE sites; and 2) supporting digital engineering through the digital thread at the object level. Standardization is necessary for both schemas and vocabularies, meaning that both field standards and value standards must be specified. This document serves as a foundational field standard, recommending a core set of fields that should be uniformly required for all managed digital objects within the NSE.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2020

Mixed-precision iterative refinement using tensor cores on GPUs to accelerate solution of linear systems

Double-precision floating-point arithmetic (FP64) has been the de facto standard for engineering and scientific simulations for several decades. Problem complexity and the sheer volume of data coming from various instruments and sensors motivate researchers to mix and match various approaches to optimize compute resources, including different levels of floating-point precision. In recent years, machine learning has motivated hardware support for half-precision floating-point arithmetic. A primary challenge in high-performance computing is to leverage reduced-precision and mixed-precision hardware. We show how the FP16/FP32 Tensor Cores on NVIDIA GPUs can be exploited to accelerate the solution of linear systems of equations Ax = b without sacrificing numerical stability. The techniques we employ include multiprecision LU factorization, the preconditioned generalized minimal residual algorithm (GMRES), and scaling and auto-adaptive rounding to avoid overflow. We also show how to efficiently handle systems with multiple right-hand sides. On the NVIDIA Quadro GV100 (Volta) GPU, we achieve a 4×-5× performance increase and 5× better energy efficiency versus the standard FP64 implementation while maintaining an FP64 level of numerical stability.

GMRES↗
DOE OSTI2026

iDDS: intelligent distributed dispatch and scheduling for workflow orchestration

The intelligent distributed dispatch and scheduling (iDDS) service is a versatile workflow orchestration system designed for large-scale, distributed scientific computing. iDDS extends traditional workload and data management by integrating data-aware execution, conditional logic, and programmable workflows, enabling automation of complex and dynamic processing pipelines. Originally developed for the ATLAS experiment at the large hadron collider, iDDS has evolved into an experiment-agnostic platform that supports both template-driven workflows and a Function-as-a-Task model for Python-based orchestration. This paper presents the architecture and core components of iDDS, highlighting its scalability, modular message-driven design, and integration with systems such as PanDA and Rucio. We demonstrate its versatility through real-world use cases: fine-grained tape resource optimization for ATLAS, orchestration of large Directed Acyclic Graph (DAG) workflows for the Rubin Observatory, distributed hyperparameter optimization for machine learning applications, active learning for physics analyses, and AI-assisted detector design at the electron–ion collider. By unifying workload scheduling, data movement, and adaptive decision-making, iDDS reduces operational overhead and enables reproducible, high-throughput workflows across heterogeneous infrastructures. We conclude with current challenges and future directions, including interactive, cloud-native, and serverless workflow support.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

The Dependence of Iron-rich Metal-poor Star Occurrence on Galactic Environment Supports an Origin in Thermonuclear Supernova Nucleosynthesis

It has been suggested that a class of chemically peculiar metal-poor stars called iron-rich metal-poor (IRMP) stars formed from molecular cores with metal contents dominated by thermonuclear supernova nucleosynthesis. If this interpretation is accurate, then IRMP stars should be more common in environments where thermonuclear supernovae were important contributors to chemical evolution. Conversely, IRMP stars should be less common in environments where thermonuclear supernovae were not important contributors to chemical evolution. At constant [Fe/H] ≲ -1, the Milky Way's satellite classical dwarf spheroidal (dSph) galaxies and the Magellanic Clouds have lower [α/Fe] than the Milky Way field and globular cluster populations. This difference is thought to demonstrate the importance of thermonuclear supernova nucleosynthesis for the chemical evolution of the Milky Way's satellite classical dSph galaxies and the Magellanic Clouds. We use data from the Sloan Digital Sky Survey Apache Point Observatory Galactic Evolution Experiment and Gaia to infer the occurrence of IRMP stars in the Milky Way's satellite classical dSph galaxies η dSph and the Magellanic Clouds η Mag , as well as in the Milky Way field η MWF and globular cluster populations η MWGC . In order of decreasing occurrence, we find η dSph = $0.07$$^{+0.02}_{-0.02}$, η Mag = $0.037$$^{+0.007}_{-0.006}$, η MWF = $0.0013$$^{+0.0006}_{-0.0005}$, and a 1σ upper limit η MWGC < 0.00057. These occurrences support the inference that IRMP stars formed in environments dominated by thermonuclear supernova nucleosynthesis and that the time lag between the formation of the first and second stellar generations in globular clusters was longer than the thermonuclear supernova delay time.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Startup Test Plan and Predictions for Highly Enriched Uranium to Low-Enriched Uranium Fuel Conversion at the University of Missouri Research Reactor

Nonpower reactors licensed by the U.S. Nuclear Regulatory Commission require a startup test plan as part of any facility modification to verify operability prior to resumption of operations. In order to support conversion of the University of Missouri Research Reactor from the use of highly enriched uranium to low-enriched uranium (LEU) fuel, a startup test plan has been devised to measure certain reactor physics parameters for the initial all-fresh LEU core licensing documentation that will be submitted. These parameters include the approach to critical, primary coolant void coefficient of reactivity, flux trap void coefficient of reactivity, determination of flux trap sample reactivity worth, radial and axial thermal neutron flux mapping, control blade worth calibration, primary and pool coolant temperature coefficient of reactivity, and flux mapping of experimental positions. Here, predictions for these parameters made using the Monte Carlo N-Particle Version 5 (MCNP5) radiation transport code are reported. These predictions will support the startup tests by providing a baseline set of expectations and additional insight into the performance of the LEU core.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

Estimating mass-absorption cross-section of ambient black carbon aerosols: theoretical, empirical, and machine learning models

The mass-absorption cross-section of black carbon (MAC BC ) is an essential parameter to link the atmospheric concentration of black carbon (BC) with its radiative forcing. When a direct calculation of MAC BC based on observations of aerosol light absorption and BC mass concentration is impossible, we rely on modeling and simulations to estimate MAC BC , but currently, there is no consensus model that can be relied on for accurate predictions across all atmospheric environments when BC particles have different coating thicknesses. Here, we applied five MAC BC prediction models (including three light scattering theories, an empirical model based on observations of particle mass concentrations, and a machine learning model developed in our previous work) to aerosols from three Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) field campaigns. While many studies have found that increasing the complexity of the models helps to constrain biases of the estimated MAC BC , our effort is to evaluate the models based on the criteria of simplicity and accuracy. We find that our machine learning model (support vector machine for regression, SVM) generally performs well across all DOE ARM field campaign data, while the accuracy of core-shell Mie theory depends on the bias correction algorithm applied to filter-based light absorption data. Generally, the empirical model for internally-mixed particles that we considered tends to over-predict MAC BC , while Mie theory for externally-mixed particles tends to under-predict MAC BC . An examination of the influence of coating material on BC cores suggests that the performance of our current SVM model is degraded when the BC is thickly-coated (e.g., it has undergone aging and mixing with other materials in the atmosphere).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

ConnectIt: a framework for static and incremental parallel graph connectivity algorithms

Connected components is a fundamental kernel in graph applications. The fastest existing multicore algorithms for solving graph connectivity are based on some form of edge sampling and/or linking and compressing trees. However, many combinations of these design choices have been left unexplored. In this paper, we design the ConnectIt framework, which provides different sampling strategies as well as various tree linking and compression schemes. ConnectIt enables us to obtain several hundred new variants of connectivity algorithms, most of which extend to computing spanning forest. In addition to static graphs, we also extend ConnectIt to support mixes of insertions and connectivity queries in the concurrent setting. We present an experimental evaluation of ConnectIt on a 72-core machine, which we believe is the most comprehensive evaluation of parallel connectivity algorithms to date. Compared to a collection of state-of-the-art static multicore algorithms, we obtain an average speedup of 12.4x (2.36x average speedup over the fastest existing implementation for each graph). Using ConnectIt, we are able to compute connectivity on the largest publicly-available graph (with over 3.5 billion vertices and 128 billion edges) in under 10 seconds using a 72-core machine, providing a 3.1x speedup over the fastest existing connectivity result for this graph, in any computational setting. For our incremental algorithms, we show that our algorithms can ingest graph updates at up to several billion edges per second. To guide the user in selecting the best variants in ConnectIt for different situations, we provide a detailed analysis of the different strategies. Finally, we show how the techniques in ConnectIt can be used to speed up two important graph applications: approximate minimum spanning forest and SCAN clustering.

Computer Science↗
DOE OSTI2020

ECP ST Capability Assessment Report (CAR) for VTK-m (FY20)

The ECP/VTK-m project is providing the core capabilities to perform scientific visualization on Exascale architectures. The ECP/VTK-m project fills the critical feature gap of performing visualization and analysis on processors like graphics-based processors. The results of this project will be delivered in tools like ParaView, Vislt, and Ascent as well as in stand-alone form. Moreover, these projects are depending on this ECP effort to be able to make effective use of ECP architectures. One of the biggest recent changes in high-performance computing is the increasing use of accelerators. Accelerators contain processing cores that independently are inferior to a core in a typical CPU, but these cores are replicated and grouped such that their aggregate execution provides a very high computation rate at a much lower power. Current and future CPU processors also require much more explicit parallelism. Each successive version of the hardware packs more cores into each processor, and technologies like hyper threading and vector operations require even more parallel processing to leverage each core's full potential. VTK-m is a toolkit of scientific visualization algorithms for emerging processor architectures. VTK-m supports the fine-grained concurrency for data analysis and visualization algorithms required to drive extreme scale computing by providing abstract models for data and execution that can be applied to a variety of algorithms across many different processor architectures. The ECP/VTK-m project is building up the VTK-m codebase with the necessary visualization algorithm implementations that run across the varied hardware platforms to be leveraged at the Exascale. We will be working with other ECP projects, such as ALPINE, to integrate the new VTK-m code into production software to enable visualization on our HPC systems.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Update on Activities Related to the Library of Graphite Microstructures

This report provides an overview and update of the ongoing efforts to create a comprehensive library of microstructures for nuclear graphite and carbon-based materials under consideration for nuclear applications. The library includes data on microstructural characterization of unirradiated graphite materials, a guide to the techniques used to analyze graphite (which complements the ASME guidelines and ASTM standards), a summary of characterization data for neutron-irradiated or oxidized material, and a compendium of microstructural information for carbon-based materials. These efforts are being conducted at various length scales for the filler and binder phases in graphite to better understand graphite’s local structure and property relationships. This report is a follow-up to the previous milestone report titled Report on initial development of a database of nuclear graphite characteristics based on microstructural characterization, ORNL/TM/-2023/2992, published in July 2023.The effort to develop the library of microstructures supports the US Department of Energy Office of Advanced Reactor Technologies program objectives of aiding the material selection, licensing, management, and core assessments of a graphite core by documenting the unirradiated microstructure of relevant grades or characterizing the microstructure’s evolution under the reactor environment. Additionally, this project aims to provide (1) information and guidelines for the characterizing of graphite and (2) a protocol to assess a nuclear graphite grade.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Cryo-EM structure of the diapause chaperone artemin

The protein artemin acts as both an RNA and protein chaperone and constitutes over 10% of all protein in Artemia cysts during diapause. However, its mechanistic details remain elusive since no high-resolution structure of artemin exists. Here we report the full-length structure of artemin at 2.04 Å resolution. The cryo-EM map contains density for an intramolecular disulfide bond between Cys22-Cys61 and resolves the entire C-terminus extending into the core of the assembled protein cage but in a different configuration than previously hypothesized with molecular modeling. We also provide data supporting the role of C-terminal helix F towards stabilizing the dimer form that is believed to be important for its chaperoning activity. We were able to destabilize this effect by placing a tag at the C-terminus to fully pack the internal cavity and cause limited steric hindrance.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

High Performance Heat Pipe Power Transient Testing at SPHERE Facility

Microreactors are being researched, designed, and built at Idaho National Laboratory (INL). Microreactors are small reactors defined at less than 20MW of power. These reactor concepts are also being looked at throughout industry for various applications. An important aspect of these reactor designs is economic feasibility i.e. lower overnight capital cost. The driving factors for implementing microreactors are quick setup and takedown, minimal operators, and the ability to manufacture them readily and to fit in mid-sized containers for transport. A specific area of research to aid in successful integration of these factors within the designs is passive heat removal of the core’s thermal power. Interest in heat pipes to achieve this passive heat removal has been shown across multiple industry partners. Because of this interest, INL has developed a test facility to facilitate experimental tests for sodium filled heat pipes. INL has developed the Single Primary Heat Extraction and Removal Emulator (SPHERE) facility to run experiments on high performance, sodium filled heat pipes. As mentioned above, heat pipes are passive heat transfer devices. Radially, heat pipes are broken up into an outer wall, a small annular gap, a wick structure, and a centerline gap. They function by utilizing latent heat transfer. Heat pipes are traditionally separated into three regions, an evaporator (heat input), an adiabatic region, and finally a condenser region (heat removal). As heat is being applied to the evaporator, the working fluid undergoes a phase change to a vapor. This phase change causes a differential pressure across the axial length of the pipe driving flow down the center gap of the heat pipe. The vapor flows down past the adiabatic region to the condenser where the heat is removed. This heat removal forces the working fluid to phase change back to a liquid. The wick structure is then utilized to drive the flow back towards the evaporator by capillary forces. This backflow is aided by the annular gap. Because this heat transfer mechanism functions with latent heat transfer, the heat pipe is close to isothermal down the axial length. Heat pipes can operate under a wide range of working fluids. Considerations for these working fluids are primarily driven by operating temperatures amongst other important factors based around overall performance. Sodium filled heat pipes operate from 450°C up to 900°C. This temperature range works well for the current microreactor designs. In conjunction with this experimental capability, INL has developed a modeling software to simulate heat pipe physics within reactor cores. This modeling software is called Sockeye and functions under the established INL Multiphysics Object Oriented Simulation Environment (MOOSE). SPHERE also supports Sockeye development by providing the modeling team with experimental data on an array of setups and operating parameters to support validation efforts. A power transient experiment was performed utilizing the SPHERE facility to continue to aid with Sockeye development. The testing followed a proposed test plan to ramp up and down the temperature of the heat pipe. Sockeye models steady state heat pipe operation with high accuracy, the data provided by the power transient testing aims to assist with the validation efforts and further enhance transient modeling capability of the tool [2].

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

Knowledge Transfer Program for International Nuclear Safeguards

Nuclear safeguards were first announced in 1945 by the U.S., Canadian and British governments as a means to exchange scientific information about peaceful uses of atomic energy and prevent the use of nuclear material for weapons. International nuclear safeguards, now under the provision of the International Atomic Energy Agency (IAEA), serves to hold accountable the 140 member countries (States) that have entered into treaties and agreements against the spread of nuclear weapons. Most notably, the IAEA acts as a nuclear materials inspectorate under the global Nuclear Non-Proliferation Treaty, brought about in 1968, that specifies commitments member States make to the world?s non-proliferation regime. The Office of International Nuclear Safeguards (OINS) is part of the National Nuclear Security Administration, a semi-autonomous agency within the U.S. Department of Energy. Within OINS, the Human Capital Development program recognizes the need to build workforce capacity and safeguards expertise. This includes supporting the education and training of younger generations working in international nuclear safeguards. One of the program?s main concerns is core competencies being lost to retirement or attrition and building knowledge retention pipelines from senior to new professionals. One identified core competency is knowledge gained by individuals who have completed IAEA assignments such as missions to member States to conduct safeguards inspections. Such individuals possess unique knowledge, and efforts are being put forth to effectively capture this knowledge within the national laboratories complex. To this end, we report findings from a one-year mentor-mentee knowledge retention program in which an international safeguards subject matter expert imparted knowledge and skills to a willing professional mentee. The knowledge and skills stem from the mentor?s multi-year assignment at the IAEA in Vienna, Austria.

98 - NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL↗
DOE OSTI2023

Supporting Risk-informed Decision-making During Reactor Accidents

Uncertainty in severe accident evolution and outcome is driven by event bifurcations that represent distinctive challenges to defensive layers and tend to promote the emergence of discrete classes of core damage and accident risk. This discrete set of "attractor" states arise from the complex networks of competing physical phenomena and conditional event cascades occurring as the overall system degrades – a process that yields increasing degrees of freedom and accident progression pathways. Characterization of these event spaces has proven elusive to more traditional data interrogation methods, but proves tractable by application of more advanced data collection and machine learning approaches. Through application of these approaches we demonstrate a conceptual framework that enables real-time/robust, risk-informed decision-making support to improve accident mitigation and encourage “graceful exits” during low probability, extreme events limiting accident consequences. In this analysis, we simulated over 8,000 short-term station blackout (STSBO) accidents with the state-of-the-art integral severe accident code, MELCOR, and demonstrate the potential for ML approaches to predict simulation outcomes. We chose to pair ML tools with interpretable and mechanistic event trees for the considered STSBO accident space to predict the likelihood of future event paths along the tree. In addition to the current state of the system, we use information from recent trajectories of temperature, pressure, and other physical features, combining both the current state and past trajectories to forecast future event paths. Finally, we simulate the random injection of variable amounts of water to quantify the efficacy of available actions at reducing risks along the many branches in the event tree. We identify scenarios and windows of opportunity to mitigate risk as well as scenarios in which such actions are unlikely to alter the accident end-state.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Evaluation of Second Target Station Target Streaming for the Preliminary Design of the Target Assembly

This report documents the analysis of dose rate fields from a combination of two sources stemming from the target system of the Oak Ridge National Laboratory (ORNL) Spallation Neutron Source (SNS) Second Target Station (STS). This analysis supports the target drive components’ lifetime estimates and conventional facilities’ preliminary design. The two sources detailed in this report are the radiation generated by the proton beam incident on the target and the activated cooling water in the pipes at the top of the target assembly. The analysis considers the STS target system in operational configuration, with all shielding in place. The dose rate fields are calculated in the target drive room and through the target drive room ceiling. This report calculates the thickness necessary for the target drive room’s high-density concrete ceiling to meet the 0.25 mrem/hr dose limit requirement in the high bay directly above the target drive room. In addition to sizing the target drive room ceiling, this report includes details of the dose field surrounding the target drive assembly to estimate the deposited dose in the target drive assembly components resulting from both streaming and decay of activated water. Prompt neutrons and gammas generated by the proton beam incident on the target primarily stream along the gaps between the target assembly and core vessel shielding. Because the models and analysis detailed in this report are based on the STS preliminary design, future analysis is needed to support the STS final design.

43 PARTICLE ACCELERATORS↗
DOE OSTI2022

Need for advanced research reactors for the next-generation reactor physics, analysis tools, and technology

Full text of publication follows. There is an urgent need for design and deployment of advanced research and test reactors in support of design, licensing and operation of advanced power reactors and education of next generation nuclear workforce. Existing research reactors mostly were designed and constructed decades ago with the main objectives of training operators, performing reactor physics experiments, and educating nuclear engineers and scientists. There are already gaps and significant concern about future capabilities for the existing research reactor facilities to address modern instrumentation and/or flexible environments for: performing reactor physics studies for advanced designs which have significantly different core materials forms and compositions, reactor shapes and size; validation of advanced high-fidelity software; development of machine learning algorithms for enhancement of human-machine collaboration in support of reactor monitoring, operation and safeguards; and, effective education of the next-generation workforce. The authors will focus on the need for advanced research reactors to improve and validate fast and accurate simulation tools for high-fidelity modeling and analysis of nuclear reactors in support of their design, optimization, licensing, operation, and monitoring. In the past, simulation tools were limited to relatively coarse models using approximate methodologies that benefited from two main factors: i) allowance for large margins and tolerances; ii) ability to construct prototype (e.g., zero power) reactors for adjustment of approximate methodologies. The next generation reactors have to be designed mainly by using novel high-fidelity computational tools that are accurate and fast, and therefore can be used for parametric studies and uncertainty quantification. To sufficiently demonstrate the accuracy of these tools, advanced research reactors are needed. The authors argue the need for new computational paradigms such as the MRT (Multistage, Response- function Transport) methodology which has resulted in the development of the novel high-fidelity RAPID (Real-time Analysis for Particle-transport and In-situ Detection) code system. Such code systems have to be robust in modeling any complex system, and should be fast and accurate, henceforth their uncertainties can be quantified at reasonable costs. Again, advanced research reactors are needed for the validation of the fidelity and accuracy of new computational tools. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗