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All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

Towards a centralized Grid Speedometer

Given the distributed nature of the Worldwide LHC Computing Grid and the way CPU resources are pledged and shared around the globe, Virtual Organizations (VOs) face the challenge of monitoring the use of these resources. For CMS and the operation of centralized workflows, the monitoring of how many production jobs are running and pending in the Glidein WMS production pools is very important. The Dashboard Site Status Board (SSB) provides a very flexible framework to collect, aggregate and visualize data. The CMS production monitoring team uses the SSB to define the metrics that have to be monitored and the alarms that have to be raised. During the integration of CMS production monitoring into the SSB, several enhancements to the core functionality of the SSB were required, They were implemented in a generic way, so that other VOs using the SSB can exploit them. Alongside these enhancements, there were a number of changes to the core of the SSB framework. This paper presents the details of the implementation and the advantages for current and future usage of the new features in SSB.

Dzhunov, I.↗
DOE OSTI2018

Hydrogen Fuel-Cell Electric Hybrid Truck Demonstration (Final Technical Report)

The purpose of the project was to demonstrate three (3) fully developed, operational, advanced vehicle technology prototypes for ON-ROAD goods movement applications. The major vehicle OEM for this demonstration was Navistar International Trucks, with the fuel cell and power control hybrid technology provided and integrated by US Hybrid. CEM was to provide independent data collection and analysis, while EDF would provide education, outreach, and communication for the project. GTI managed the partnership and arranged for hydrogen fuel for the demonstration. The drayage truck is used to transfer the cargo container from/to ports in a warehouse or logistic yard. For port facilities in the Port of Houston Area, as well as virtually all other ports, drayage trucks often queue for long periods, inching along at slow speeds to await loading and unloading. During this process, the trucks are essentially idle, with conventional diesel engines continuously running and producing accompanying emissions. The ZECT would essentially power off during idle periods, or at least utilize minimal electric energy. As such, range limitation by using a gaseous fuel would be mitigated by the fact that the vehicle is not using fuel during much of its duty cycle. The project team expected the vehicle range to be about 200 miles which is well within the duty cycle requirements of the original fleet partner, Richardson Trucking. The project was intended to demonstrate commercialization and production potential, and to clearly illustrate the selected vehicle technology’s potential to reduce GHG emissions and petroleum use if implemented widely. To achieve this, the project team proposed a two-year demonstration project in the Port of Houston area to assess and track vehicle performance, and evaluate fuel savings, petroleum reduction, and emissions reduction benefits of the prototype technology. Additional time at the front end of the project was required for vehicle and support infrastructure preparation. In June 2017 the remaining project partners, which now included Air Liquide, agreed that the project would be unlikely to move forward with the vehicle demonstration, primarily due to the lack of a viable cargo truck fleet partner in the Port of Houston area willing to make a sufficient commitment of resources to operate the vehicles for the demonstration.

08 HYDROGEN↗
DOE OSTI2022

Understanding the EMC effect with tagged DIS measurements

Understanding the modification of quarks in nucleons within nuclei (EMC effect) is a longstanding open question in nuclear physics. Recent experimental results from electron scattering at Jefferson Lab strengthen the correlation between the EMC effect and short- range correlated pairs (SRC) of nucleons in nuclei. That means that the EMC effect is probably driven by the high-momentum highly-virtual nucleons of the SRC pairs. This connection can be tested experimentally by measuring electron deep inelastic scattering from a nucleon and detecting its correlated SRC partner nucleon (tagging). This allows us to measure the quark modification of high-momentum nucleons. Two tagged experiments on deuterium are underway at Jefferson Lab of which one already took data and the other will take data in the upcoming years. In my talk, I will present the current knowledge of the EMC effect and its correlation to SRC pair and the status of the tagged measurements at Jefferson Lab.

Hauenstein, Florian↗
DOE OSTI2023

Understanding the EMC effect with tagged DIS measurements

Understanding the modification of quarks in nucleons within nuclei (EMC effect) is a longstanding open question in nuclear physics. Recent experimental results from electron scattering at Jefferson Lab strengthen the correlation between the EMC effect and short- range correlated pairs (SRC) of nucleons in nuclei. That means that the EMC effect is probably driven by the high-momentum highly-virtual nucleons of the SRC pairs. This connection can be tested experimentally by measuring electron deep inelastic scattering from a nucleon and detecting its correlated SRC partner nucleon (tagging). This allows us to measure the quark modification of high-momentum nucleons. Two tagged experiments on deuterium are underway at Jefferson Lab of which one already took data and the other will take data in the upcoming years. In my talk, I will present the current knowledge of the EMC effect and its correlation to SRC pairs, the status of the tagged measurements at Jefferson Lab, and simulation results for tagged measurements at the EIC.

Hauenstein, Florian↗
DOE OSTI2016

Do circumnuclear dense gas disks drive mass accretion onto supermassive black holes?

We present a positive correlation between the mass of dense molecular gas (M{sub dense}) of ∼100 pc scale circumnuclear disks (CNDs) and the black hole mass accretion rate ( M-dot {sub BH}) in a total of 10 Seyfert galaxies, based on data compiled from the literature and an archive (median aperture θ {sub med} = 220 pc). A typical M{sub dense} of CNDs is 10{sup 7–8} M{sub ⊙}, estimated from the luminosity of the dense gas tracer, the HCN(1–0) emission line. Because dense molecular gas is the site of star formation, this correlation is virtually equivalent to the one between the nuclear star-formation rate and M-dot {sub BH} revealed previously. Moreover, the M{sub dense}-- M-dot {sub BH} correlation was tighter for CND-scale gas than for the gas on kiloparsec or larger scales. This indicates that CNDs likely play an important role in fueling black holes, whereas greater than kiloparesec scale gas does not. To demonstrate a possible approach for studying the CND-scale accretion process with the Atacama Large Millimeter/submillimeter Array, we used a mass accretion model where angular momentum loss due to supernova explosions is vital. Based on the model prediction, we suggest that only the partial fraction of the mass accreted from the CND ( M-dot {sub acc}) is consumed as M-dot {sub BH}. However, M-dot {sub acc} agrees well with the total nuclear mass flow rate (i.e., M-dot {sub BH} + outflow rate). Although these results are still tentative with large uncertainties, they support the view that star formation in CNDs can drive mass accretion onto supermassive black holes in Seyfert galaxies.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

High-precision measurement of the W boson mass with the CMS experiment at the LHC

In the standard model of particle physics, the masses of the carriers of the weak interaction, the W and Z bosons, are uniquely related. Physics beyond the standard model could change this relationship through the effects of quantum loops of virtual particles, thus making it of great importance to measure these masses with the highest possible precision. Although the mass of the Z boson is known to the remarkable precision of 22 parts per million (2.0 MeV), the W boson mass is known much less precisely, given the difficulty of the measurement. A global fit to electroweak data, used to predict the W boson mass in the standard model, yields an uncertainty of 6 MeV. Reaching a comparable experimental precision would be a sensitive and fundamental test of the standard model. Furthermore, a precision measurement of the W boson mass performed by the CDF Collaboration at the Fermilab Tevatron has challenged the standard model by significantly disagreeing with the prediction of the global electroweak fit and the average of other $m_\mathrm{W}$ measurements. We report the first W boson mass measurement by the CMS Collaboration at the CERN LHC, based on a data sample collected in 2016 at the proton-proton collision energy of 13 TeV. The W boson mass is measured using a large sample of W$\toμν$ events via a highly granular binned maximum likelihood fit to the kinematic properties of the muons produced in the W$^{+}$ and W$^{-}$ boson decays. The significant in situ constraints of theoretical inputs and their corresponding uncertainties, together with an accurate determination of the experimental effects, lead to a precise W boson mass measurement, $m_\mathrm{W} =$ 80$\,$360.2 $\pm$ 9.9 MeV, in agreement with the standard model prediction.

FOS: Physical sciences↗
DOE OSTI2014

Exclusive single pion electroproduction off the proton in the high-lying resonances at Q2 < 5 GeV2 from CLAS

The differential cross sections and structure functions for the exclusive electroproduction process ep --> e'n pi+ were measured in the range of the invariantmass for the np+ system 1.6 GeV lte W lte 2.0 GeV, and the photon virtuality 1.8 GeV2 lte Q2 lte 4.0 GeV2 using CLAS at Jefferson Lab. For the first time, these kinematics are probed in the exclusive p+ production from the protons with nearly full coverage in the azimuthal and polar angles of the np+ center-of-mass system. In this analysis, approximately 39,000 differential cross-section data points in terms of W, Q2, cosq theta* _ pi, and phi*_p-, were obtained. The preliminary differential cross section and structure function analyses are carried out, which allow us to extract the helicity amplitudes in high-lying resonances.

Park, Kijun↗
DOE OSTI2026

Integrating Immersive Visualization in Molten-Salt Reactor Waste Management for Experimental Design and Planning

The Molten Salt Reactor (MSR) represents a significant innovation in nuclear technology, offering several operational and safety benefits over traditional solid-fuel reactors. However, MSRs face uncertainties in waste management due to their flexible designs and variable waste compositions. To address these challenges, we propose a visualization platform that illustrates solutions and performance predictions for various waste management strategies, enhancing user experience and improving strategy and communication. Immersive visualizations are widely used in the nuclear industry for training, simulation, and safety enhancement. Our project aims to develop a visualization platform incorporating virtual reality (VR) technologies to illustrate MSR characteristics immediately following reactor shutdown. This immersive simulation will allow users to interact, explore, and understand different waste management strategies. The platform will display MSR reactor characterizations, including nuclide decay, salt solidification, and corrosion, which are crucial for assessing and selecting backend management strategies. Using the Meta Quest 3 VR headset with Unity software, our platform will provide real-scale visualizations, enabling users to experience and evaluate designs and plans as if they were physically present. This user-friendly interface will make complex data accessible and understandable for non-domain experts, aiding in decision-making for MSR waste management. Our proposed visualization workflow can be applied to other nuclear reactors, assisting in the design and planning of waste management strategies.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

Validation and Verification for INL Modelica-based TEDS models Via Experimental Results

This report provides an overview on the verification and validation (V&V) of the Thermal Energy Distribution System (TEDS) model developed in the Modelica process modeling ecosystem using experimental data. Model development has led to the creation of a dynamic process model of the experimental TEDS facility housed within the Energy Systems Laboratory (ESL) at Idaho National Laboratory (INL). The model was then used during the preconstruction phase of the experimental effort to inform experimental design (e.g., insulation requirements, bypass line placement, expected performance of components) and to test innovative control schemes prior to the initial operation. The TEDS model developed in Modelica includes the primary components of the TEDS experimental unit: a 200kW Chromalox heater; a single-tank packed-bed thermal energy storage system filled with 0.125-inch alumina (Al2O3) beads; an ethylene-glycol-to-Therminol-66 heat exchanger; system piping; five control valves; and all associated temperature, pressure, and volumetric flow sensors. Using the Institute of Electrical and Electronics Engineers (IEEE) V&V methodologies, considered the gold standard in the engineering field, the model was verified using a combination of static analysis, spatial convergence, and regression tests. Then using dynamic time warping (DTW) initial runs to validate and tune the TEDS model versus the experiment were conducted. This tuning method was accomplished using the INL Risk Analysis Virtual ENvironment (RAVEN) software package. Tuning is required to account for physical phenomena that are less understood within the empirical heat transfer correlations. Through the commencement of this work, a systems-level model of TEDS with associated control systems, sensors, piping diameters, and component capabilities has been created. This model was utilized in the pre-experimental phase to inform system design, insulation thicknesses, and potential control schemes to operate the system effectively and safely. Then, initial experimental startup and operational data were used to demonstrate the validation and tuning methodology. This process demonstrates the classical two-step approach of a model informing experimental design followed by the experiment validation and tuning the model.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

Determination of asymptotic normalization coefficients for the channel 16 O→ α+ 12 C: excited state 16 O(0 + ; 6.05 MeV)

Asymptotic normalization coefficients (ANC) determine the overall normalization of cross sections of peripheral radiative capture reactions. In the present paper, we treat the ANC C for the virtual decay 16 O(0 + ; 6.05 MeV)→ α+ 12 C(g.s.), the known values of which are characterized by a large spread (0.29 - 1.65) × 10 3 fm -1/2 . The ANC C is found by analytic continuation in energy of the α 12 C s-wave scattering amplitude, known from the phase-shift analysis of experimental data, to the pole corresponding to the 16O bound state and lying in the unphysical region of negative energies. To determine C, two different methods of analytic continuation are used. In the first method, the scattering data are approximated by the sum of polynomials in energy in the physical region and then extrapolated to the pole. The best way of extrapolation is chosen on the basis of the exactly solvable model. Within the second approach, the ANC C is found by solving the Schrödinger equation for the two-body α 12 C potential, the parameters of which are selected from the requirement of the best description of the phase-shift analysis data at a fixed experimental binding energy of 16 O(0 + ; 6.05 MeV) in the α+ 12 C channel. The values of the ANC C obtained within these two methods lie in the interval (886–1139) fm -1/2 .

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2014

Multi-Tenant Isolation via Reconfigurable Networks

High performance computing environments are often used for a wide variety of workloads ranging from simulation, data transformation and analysis, and complex workflows to name just a few. These systems may process data at various security levels but in so doing are often enclaved at the highest security posture. This approach places significant restrictions on the users of the system even when processing data at a lower security level and exposes data at higher levels of confidentiality to a much broader population than otherwise necessary. The traditional approach of isolation, while effective in establishing security enclaves poses significant challenges for the use of shared infrastructure in HPC environments. This report details current state-of-the-art in reconfigurable network enclaving through Software Defined Networking (SDN) and Network Function Virtualization (NFV) and their applicability to secure enclaves in HPC environments. SDN and NFV methods are based on a solid foundation of system wide virtualization. The purpose of which is very straight forward, the system administrator can deploy networks that are more amenable to customer needs, and at the same time achieve increased scalability making it easier to increase overall capacity as needed without negatively affecting functionality. The network administration of both the server system and the virtual sub-systems is simplified allowing control of the infrastructure through well-defined APIs (Application Programming Interface). While SDN and NFV technologies offer significant promise in meeting these goals, they also provide the ability to address a significant component of the multi-tenant challenge in HPC environments, namely resource isolation. Traditional HPC systems are built upon scalable high-performance networking technologies designed to meet specific application requirements. Dynamic isolation of resources within these environments has remained difficult to achieve. SDN and NFV methodology provide us with relevant concepts and available open standards based APIs that isolate compute and storage resources within an otherwise common networking infrastructure. Additionally, the integration of the networking APIs within larger system frameworks such as OpenStack provide the tools necessary to establish isolated enclaves dynamically allowing the benefits of HPC while providing a controlled security structure surrounding these systems.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Expanding the Domain of Applicability of Machine Learning Models with Limited Data for Drug Property Prediction

Accurate machine learning models for predicting small molecule interactions with biological targets are essential for therapeutic discovery, biothreat response, and computational drug design, but their performance is often limited for understudied targets with sparse experimental data. To address this challenge, we developed and evaluated methods to improve molecular property prediction under low-data conditions, using the NimA-related kinase (NEK) family as a proof-of-concept. This work focused on two complementary goals within the ATOM Modeling PipeLine (AMPL) and the Generative Molecular Design (GMD) loop: expanding model applicability through transfer learning, representation learning, feature scaling, sampling strategies, and active-learning-inspired compound selection; and enabling efficient virtual screening to prioritize compounds that balance predicted activity, design objectives, and synthetic accessibility.

organic↗
DOE OSTI2024

Advanced manufacturing and digital twin technology for nuclear energy*

Advanced manufacturing techniques and digital twin technology are rapidly transforming the nuclear industry, offering the potential to enhance productivity, safety, and cost-effectiveness. Customized parts are being produced using additive manufacturing, automation, and robotics, while digital twin technology enables the virtual modeling and optimization of complex systems. These advanced technologies can significantly improve operational efficiency, predict system behavior, and optimize maintenance schedules in the nuclear energy sector, leading to heightened safety and reduced downtime. However, the nuclear industry demands the highest levels of safety and security, as well as intricate manufacturing processes and operations. Thus, challenges such as data management and cybersecurity must be addressed to fully realize the potential of advanced manufacturing techniques and digital twin technology in the nuclear industry. This comprehensive review highlights the critical role of digital twin technology with advanced manufacturing toward nuclear energy to improve performance, minimize downtime, and heighten safety, ultimately contributing to the global energy mix by providing dependable and low-carbon electricity.

36 MATERIALS SCIENCE↗
DOE OSTI2019

The Next Generation System Analysis Model: Capabilities for Simulating a Waste Management System - 19131

The U.S. Department of Energy (DOE) Office of Nuclear Energy Office of Spent Fuel and Waste Disposition's Integrated Waste Management System (IWMS) program is applying integrated waste management system architecture analysis, system engineering, and decision analysis principles to inform potential future decisions regarding potential nuclear waste management system architectures. Architecture analyses of the IWMS are being conducted to support the future deployment of a comprehensive system for managing nuclear waste that considers all major aspects of the back end of the nuclear fuel cycle (i.e., transportation, storage, and disposal). The system architecture analyses consider alternative disposition pathways for commercial spent nuclear fuel (SNF) being stored dry in at-reactor Independent Spent Fuel Storage Installations (ISFSIs) or wet in spent-fuel pools. One method for evaluating these alternatives is simulating the movement of SNF throughout the system components. Successfully simulating a system on the scale of a national waste management system requires - accurate baseline information (e.g., historic fuel discharges from reactors and dry storage loadings at reactor sites), - modeling all logistic interactions between components of the proposed system, and - tracking and reporting all relevant details regarding the simulation's execution. The Next Generation System Analysis Model (NGSAM) is an agent-based simulation software tool designed for the express purpose of modeling the IWMS. It is based on the Performance Analysis Tool, a simulation platform that has been used to model logistics for the Department of Defense and the Federal Emergency Management Agency. Using existing, government-owned software allows NGSAM developers to modify the software at the level of source code and to develop flexible usability and modeling solutions for developing and running simulations of the IWMS. NGSAM imports data from the Oak Ridge National Laboratory (ORNL) Unified Database (e.g., historic assembly information, thermal profiles for assembly heat, at-reactor dry storage loadings) to ensure that the simulation initializes with a realistic representation of the state of commercial SNF in the United States. NGSAM is designed with the flexibility to model and track the behavior of virtually any IWMS architecture assumptions or design considerations. For example, NGSAM can model multiple interim storage facilities or repositories or none at all. Similarly, all assumptions regarding shipment schedules, operating schedules, and reactor operation assumptions can be modeled and adjusted in NGSAM with relative ease. The development of NGSAM was targeted to waste management system analysts as the primary users. With that in mind, analysts from ORNL, Sandia National Laboratories (SNL), and Argonne National Laboratory (ANL) were intimately involved in the development process. That involvement extended beyond merely defining requirements. System analysts have been involved with design decisions and software benchmarking and tests, and they have provided subject-matter expertise where necessary. The result is a high degree of interaction between professional software developers and system analysts, with a multitude of benefits to both groups. This paper explores some of the underlying methodology of the agile software development process used in the creation of NGSAM. It illustrates the capabilities of NGSAM. Some example use cases are discussed as well, with relevant results providing context for how NGSAM is used by system analysts to gain a greater understanding of alternative waste management system architectures. This is a technical paper that does not take into account the contractual limitations under the Standard Contract for Disposal of Spent Nuclear Fuel and/or High-Level Radioactive Waste (Standard Contract) (10 CFR Part 961). Under the provisions of the Standard Contract, DOE does not consider spent nuclear fuel in multi-assembly canisters to be an acceptable waste form, absent a mutually agreed-to contract amendment. To the extent discussions or recommendations in this paper conflict with the provisions of the Standard Contract, the Standard Contract provisions prevail. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2017

Robust online monitoring for calibration assessment of transmitters and instrumentation - 260

Robust online monitoring (OLM) technologies are expected to enable the extension or elimination of periodic sensor calibration intervals in operating and new reactors. Advances in OLM technologies will improve the safety and reliability of current and planned nuclear power systems through improved accuracy and increased reliability of sensors used to monitor key parameters. In this paper, we discuss an overview of research being performed within the Nuclear Energy Enabling Technologies (NEET)/Advanced Sensors and Instrumentation (ASI) program, for the development of OLM algorithms to use sensor outputs and, in combination with other available information, 1) determine whether one or more sensors are out of calibration or failing and 2) replace a failing sensor with reliable, accurate sensor outputs. A Gaussian Process (GP)-based uncertainty quantification (UQ) method previously developed for UQ in OLM, was adapted for this purpose. The resulting models are being evaluated for use in high-confidence signal validation for the purpose of detecting and diagnosing sensor faults, and for computing virtual sensor outputs that may be used as a temporary replacement for failing sensors. In addition to assessing sensor drift, approaches for extracting sensor response time in an automated fashion were developed, for monitoring changes in sensor response time in pressure transmitters. Such changes are also indicative of various fault modes. These algorithms were evaluated with existing measurement data from several laboratory-scale flow loops. Ongoing research in this project is focused on further evaluation of the algorithms, optimization for accuracy and computational efficiency, and integration into a suite of tools for robust OLM that are applicable to monitoring sensor calibration state in nuclear power plants. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2021

Converting tabular data into images for deep learning with convolutional neural networks

Abstract Convolutional neural networks (CNNs) have been successfully used in many applications where important information about data is embedded in the order of features, such as speech and imaging. However, most tabular data do not assume a spatial relationship between features, and thus are unsuitable for modeling using CNNs. To meet this challenge, we develop a novel algorithm, image generator for tabular data (IGTD), to transform tabular data into images by assigning features to pixel positions so that similar features are close to each other in the image. The algorithm searches for an optimized assignment by minimizing the difference between the ranking of distances between features and the ranking of distances between their assigned pixels in the image. We apply IGTD to transform gene expression profiles of cancer cell lines (CCLs) and molecular descriptors of drugs into their respective image representations. Compared with existing transformation methods, IGTD generates compact image representations with better preservation of feature neighborhood structure. Evaluated on benchmark drug screening datasets, CNNs trained on IGTD image representations of CCLs and drugs exhibit a better performance of predicting anti-cancer drug response than both CNNs trained on alternative image representations and prediction models trained on the original tabular data.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

Development of the multigroup cross section library for the CASL neutronics simulator MPACT: Method and procedure

The MPACT neutronics module of the Consortium for Advanced Simulation of Light Water Reactors (CASL) core simulator is a 3D whole core transport code being developed for the CASL toolset known as the Virtual Environment for Reactor Analysis (VERA). Key characteristics of the MPACT code include a subgroup method for resonance self-shielding and a whole-core transport solver with a 2D/1D synthesis method. The AMPX and SCALE code packages have been significantly improved to include intermediate resonance parameters, as well as new modules to enhance the accuracy of resonance data and scattering matrices for the Bondarenko approach and transport cross sections of hydrogen. In addition, CASL XSTools have been developed to generate the MPACT multigroup cross section library. A simple super-homogenization method for 238U has been developed to resolve reaction rate discrepancy issues caused by angle-dependent total cross sections, poor scattering matrices, and a poor resonance interference model at coarse group structure. Here, due to the limitation of computing capacity that can occur even in high performance computing, a new 51-group structure has been developed for efficient simulation that is applicable for both pressurized water reactor (PWR) and boiling water reactor (BWR) simulations. A new ENDF/B-VII.1 MPACT 51-group library has been developed using the AMPX/SCALE and XSTools code packages, and it has been verified and validated by performing various benchmark calculations.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2018

Plant Modernization Pathway: FY 2019 External Review Summary Report

This report describes an external review conducted by the Light Water Reactor Sustainability Program Plant Modernization Pathway (referred to as Pathway) to solicit feedback on the topics and results of the ongoing Instrumentation and Control (I&C) research program. This review was held in conjunction with the Nuclear Energy Institute (NEI) Digital I&C Working Group meeting that was held at Idaho National Laboratory on October 16–17, 2018. Members of the Nuclear Regulatory Commission (NRC) staff working on digital I&C issues through their Integrated Action Plan also attended. The NEI and NRC agreed that the meeting participants would serve as an external review panel for the purpose of obtaining expert input on the value and timing of the research projects. Five major research areas were presented, along with demonstrations of new technologies in the Human Systems Simulation Laboratory and the Computer-Assisted Virtual Environment. Following the presentations, the external review was conducted by referring to a set of summary slides of the five research areas, and allowing each participant to enter ratings and comments on a survey form as each area was addressed. Fourteen forms were returned. These feedback forms were analyzed by the Pathway who compiled and responded to the data and comments, which are documented in this report. The participants also had opportunity to provide comments on the LWRS Program as a whole and to suggest additional research topics of value. The feedback provided by the external review participants is taken to be a strong endorsement of the types of projects being conducted by the Pathway, the value they hold for the operating nuclear plants, and the general timing of need. The feedback aligns well with the priorities, levels of efforts allocated for the research projects, and project schedules of the current Pathway research program. The feedback also provides realistic observations on the practicality of some aspects of implementing these technologies. The Pathway will consider all of the feedback and address the recommended research topics that have been identified by the external review participants. Pathway research plans will be adjusted as warranted.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗