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

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

Methodology for the Incorporation of Passive Component Aging Modeling into the RAVEN/ RELAP-7 Environment

Passive system, structure and components (SSCs) will degrade over their operation life and this degradation may cause to reduction in the safety margins of a nuclear power plant. In traditional probabilistic risk assessment (PRA) using the event-tree/fault-tree methodology, passive SSC failure rates are generally based on generic plant failure data and the true state of a specific plant is not reflected realistically. To address aging effects of passive SSCs in the traditional PRA methodology [1] does consider physics based models that account for the operating conditions in the plant, however, [1] does not include effects of surveillance/inspection. This paper represents an overall methodology for the incorporation of aging modeling of passive components into the RAVEN/RELAP-7 environment which provides a framework for performing dynamic PRA. Dynamic PRA allows consideration of both epistemic and aleatory uncertainties (including those associated with maintenance activities) in a consistent phenomenological and probabilistic framework and is often needed when there is complex process/hardware/software/firmware/ human interaction [2]. Dynamic PRA has gained attention recently due to difficulties in the traditional PRA modeling of aging effects of passive components using physics based models and also in the modeling of digital instrumentation and control systems. RAVEN (Reactor Analysis and Virtual control Environment) [3] is a software package under development at the Idaho National Laboratory (INL) as an online control logic driver and post-processing tool. It is coupled to the plant transient code RELAP-7 (Reactor Excursion and Leak Analysis Program) also currently under development at INL [3], as well as RELAP 5 [4]. The overall methodology aims to: • Address multiple aging mechanisms involving large number of components in a computational feasible manner where sequencing of events is conditioned on the physical conditions predicted in a simulation environment such as RELAP-7. • Identify the risk-significant passive components, their failure modes and anticipated rates of degradation • Incorporate surveillance and maintenance activities and their effects into the plant state and into component aging progress. • Asses aging affects in a dynamic simulation environment 1. C. L. SMITH, V. N. SHAH, T. KAO, G. APOSTOLAKIS, “Incorporating Ageing Effects into Probabilistic Risk Assessment –A Feasibility Study Utilizing Reliability Physics Models,” NUREG/CR-5632, USNRC, (2001). 2. T. ALDEMIR, “A Survey of Dynamic Methodologies for Probabilistic Safety Assessment of Nuclear Power Plants, Annals of Nuclear Energy, 52, 113-124, (2013). 3. C. RABITI, A. ALFONSI, J. COGLIATI, D. MANDELLI and R. KINOSHITA “Reactor Analysis and Virtual Control Environment (RAVEN) FY12 Report,” INL/EXT-12-27351, (2012). 4. D. ANDERS et.al, "RELAP-7 Level 2 Milestone Report: Demonstration of a Steady State Single Phase PWR Simulation with RELAP-7," INL/EXT-12-25924, (2012).

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Asynchronous and Distributed Tracking of Time-Varying Fixed Points

NREL researcher Andrey Bernstein discusses asynchronous and distributed tracking of time-varying fixed points as part of the Innovative Optimization and Control Methods for Highly Distributed Autonomous Systems workshop. NREL hosted the workshop to exchange ideas on state-of-the-art control and optimization strategies as well as get feedback on work being done at NREL.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

A New Vision for Fusion Energy Research: Fusion Rocket Engines for Planetary Defense

Abstract We argue that it is essential for the fusion energy program to identify an imagination-capturing critical mission by developing a unique product which could command the marketplace. We lay out the logic that this product is a fusion rocket engine, to enable a rapid response capable of deflecting an incoming comet, to prevent its impact on the planet Earth, in defense of our population, infrastructure, and civilization. As a side benefit, deep space solar system exploration, with greater speed and orders-of-magnitude greater payload mass would also be possible.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

MPACT Programmer's Manual (V.4.3)

Figure 1 shows a high-level call chart for MPACT. The call chart uses the actual procedure names, starting with the main program name, MPACT. The only exception is the italicized names where the upstream procedure contains a number of subroutines calls. These calls are logically separated into blocks, such as setup basic info/inputs. Brief descriptions of what the procedure accomplishes are provided where needed. More detailed procedure information, including procedure arguments and definitions, can be found directly in the procedure header in the MPACT source code or Doxygen documentation (http://www.doxygen.nl/).

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

NISQ+: Boosting quantum computing power by approximating quantum error correction

Quantum computers are growing in size, and design decisions are being made now that attempt to squeeze more computation out of these machines. In this spirit, we design a method to boost the computational power of near-term quantum computers by adapting protocols used in quantum error correction to implement "Approximate Quantum Error Correction (AQEC)." By approximating fully-fledged error correction mechanisms, we can increase the compute volume (qubits × gates, or "Simple Quantum Volume (SQV)") of near-term machines. The crux of our design is a fast hardware decoder that can approximately decode detected error syndromes rapidly. Specifically, we demonstrate a proof-of-concept that approximate error decoding can be accomplished online in near-term quantum systems by designing and implementing a novel algorithm in Single-Flux Quantum (SFQ) superconducting logic technology. This avoids a critical decoding backlog, hidden in all offline decoding schemes, that leads to idle time exponential in the number of T gates in a program. Our design utilizes one SFQ processing module per physical qubit. Employing state-of-the-art SFQ synthesis tools, we show that the circuit area, power, and latency are within the constraints of contemporary quantum system designs. Under pure dephasing error models, the proposed accelerator and AQEC solution is able to expand SQV by factors between 3,402 and 11,163 on expected near-term machines. The decoder achieves a 5% accuracy-threshold and pseudo-thresholds of ~ 5%,4.75%,4.5%, and 3.5% physical error-rates for code distances 3,5,7, and 9. Decoding solutions are achieved in a maximum of ~20 nanoseconds on the largest code distances studied. By avoiding the exponential idle time in offline decoders, we achieve a 10x reduction in required code distances to achieve the same logical performance as alternative designs.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2012

Compiled MPI: Cost-Effective Exascale Applications Development

The complexity of petascale and exascale machines makes it increasingly difficult to develop applications that can take advantage of them. Future systems are expected to feature billion-way parallelism, complex heterogeneous compute nodes and poor availability of memory (Peter Kogge, 2008). This new challenge for application development is motivating a significant amount of research and development on new programming models and runtime systems designed to simplify large-scale application development. Unfortunately, DoE has significant multi-decadal investment in a large family of mission-critical scientific applications. Scaling these applications to exascale machines will require a significant investment that will dwarf the costs of hardware procurement. A key reason for the difficulty in transitioning today's applications to exascale hardware is their reliance on explicit programming techniques, such as the Message Passing Interface (MPI) programming model to enable parallelism. MPI provides a portable and high performance message-passing system that enables scalable performance on a wide variety of platforms. However, it also forces developers to lock the details of parallelization together with application logic, making it very difficult to adapt the application to significant changes in the underlying system. Further, MPI's explicit interface makes it difficult to separate the application's synchronization and communication structure, reducing the amount of support that can be provided by compiler and run-time tools. This is in contrast to the recent research on more implicit parallel programming models such as Chapel, OpenMP and OpenCL, which promise to provide significantly more flexibility at the cost of reimplementing significant portions of the application. We are developing CoMPI, a novel compiler-driven approach to enable existing MPI applications to scale to exascale systems with minimal modifications that can be made incrementally over the application's lifetime. It includes: (1) New set of source code annotations, inserted either manually or automatically, that will clarify the application's use of MPI to the compiler infrastructure, enabling greater accuracy where needed; (2) A compiler transformation framework that leverages these annotations to transform the original MPI source code to improve its performance and scalability; (3) Novel MPI runtime implementation techniques that will provide a rich set of functionality extensions to be used by applications that have been transformed by our compiler; and (4) A novel compiler analysis that leverages simple user annotations to automatically extract the application's communication structure and synthesize most complex code annotations.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

Fuel Fabrication Capability Research and Development Plan

The purpose of this document is to provide a comprehensive review of the mission of the Fuel Fabrication Capability (FFC) within the Global Threat Reduction Initiative Convert Program, along with research and development (R&D) needs that have been identified as necessary to ensuring mission success. The design and fabrication of successful nuclear fuels must be closely linked endeavors. Therefore, the overriding motivation behind the FFC R&D program described in this plan is to foster closer integration between fuel design and fabrication to reduce programmatic risk. These motivating factors are all interrelated, and progress addressing one will aid understanding of the others. The FFC R&D needs fall into two principal categories, 1) baseline process optimization, to refine the existing fabrication technologies, and 2) manufacturing process alternatives, to evaluate new fabrication technologies that could provide improvements in quality, repeatability, material utilization, or cost. The FFC R&D Plan examines efforts currently under way in regard to coupon, foil, plate, and fuel element manufacturing, and provides recommendations for a number of R&D topics that are of high priority but not currently funded (i.e., knowledge gaps). The plan ties all FFC R&D efforts into a unified vision that supports the overall Convert Program schedule in general, and the fabrication schedule leading up to the MP-1 and FSP-1 irradiation experiments specifically. The fabrication technology decision gates and down-selection logic and schedules are tied to the schedule for fabricating the MP-1 fuel plates, which will provide the necessary data to make a final fuel fabrication process down-selection. Because of the short turnaround between MP-1 and the follow-on FSP-1 and MP-2 experiments, the suite of specimen types that will be available for MP-1 will be the same as those available for FSP-1 and MP-2. Therefore, the only opportunity to explore parameter space and alternative processing is between now and 2016 when the candidate processes are down-selected in preparation for the MP-1, FSP-1, and MP-2 plate manufacturing campaigns. A number of key risks identified by the FFC are discussed in this plan, with recommended mitigating actions for those activities within FFC, and identification of risks that are impacted by activities in other areas of the Convert Program. The R&D Plan does not include discussion of FFC initiatives related to production-scale manufacturing of fuel (e.g., establishment of the Pilot Line Production Facility), rather, the goal of this plan is to document the R&D activities needed ultimately to enable high-quality and cost-effective production of the fuel by the commercial fuel fabricator. The intent is for this R&D Plan to be a living document that will be reviewed and updated on a regular basis (e.g., annually) to ensure that FFC R&D activities remain properly aligned to the needs of the Convert Program. This version of the R&D Plan represents the first annual review and revision.

Convert Program↗
DOE OSTI2024

Surf-Deformer: Mitigating Dynamic Defects on Surface Code via Adaptive Deformation

In this paper, we introduce Surf-Deformer, a code deformation framework that seamlessly integrates adaptive defect mitigation functionality into the current surface code workflow. It crafts several basic deformation instructions based on fundamental gauge transformations, which can be combined to explore a larger design space than previous methods. This enables more optimized deformation processes tailored to specific defect situations, restoring the QEC capability of deformed codes more efficiently with minimal qubit resources. Additionally, we design an adaptive code layout that accommodates our defect mitigation strategy while ensuring efficient execution of logical operations. Our evaluation shows that Surf-Deformer outperforms previous methods by significantly reducing the end-to-end failure rate of various quantum programs by 35× to 70×, while requiring only about 50% of the qubit resources compared to the previous method to achieve the same level of failure rate. Ablation studies show that Surf-Deformer surpasses previous defect removal methods in preserving QEC capability and facilitates surface code communication by achieving nearly optimal throughput.

Yin, Keyi↗
DOE OSTI2014

Industry Research and Recommendations for New Commercial Buildings

Researchers evaluated industry needs and developed logic models to support possible future commercial new construction research and deployment efforts that could be led or supported by DOE's Commercial Building Integration program or other national initiatives. The authors believe that these recommendations support a proposed course of action from the current state of commercial building energy efficiency to a possible long-term goal of achieving significant market penetration of cost-effective NZE buildings in all building sectors and climates by 2030.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2012

Executing a gather operation on a parallel computer

Methods, apparatus, and computer program products are disclosed for executing a gather operation on a parallel computer according to embodiments of the present invention. Embodiments include configuring, by the logical root, a result buffer or the logical root, the result buffer having positions, each position corresponding to a ranked node in the operational group and for storing contribution data gathered from that ranked node. Embodiments also include repeatedly for each position in the result buffer: determining, by each compute node of an operational group, whether the current position in the result buffer corresponds with the rank of the compute node, if the current position in the result buffer corresponds with the rank of the compute node, contributing, by that compute node, the compute node's contribution data, if the current position in the result buffer does not correspond with the rank of the compute node, contributing, by that compute node, a value of zero for the contribution data, and storing, by the logical root in the current position in the result buffer, results of a bitwise OR operation of all the contribution data by all compute nodes of the operational group for the current position, the results received through the global combining network.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2013

Generating and executing programs for a floating point single instruction multiple data instruction set architecture

Mechanisms for generating and executing programs for a floating point (FP) only single instruction multiple data (SIMD) instruction set architecture (ISA) are provided. A computer program product comprising a computer recordable medium having a computer readable program recorded thereon is provided. The computer readable program, when executed on a computing device, causes the computing device to receive one or more instructions and execute the one or more instructions using logic in an execution unit of the computing device. The logic implements a floating point (FP) only single instruction multiple data (SIMD) instruction set architecture (ISA), based on data stored in a vector register file of the computing device. The vector register file is configured to store both scalar and floating point values as vectors having a plurality of vector elements.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Flowsheet Definition for the Tank Side Cesium Removal Unit and the Importance of Early Communication - 19142

The U.S. Department of Energy (DOE) tank operations contractor Washington River Protection Solutions, LLC (WRPS) is working toward the start of low-activity waste (LAW) treatment in direct feed mode as soon as 2022. WRPS is responsible for providing the pre-treated feed for this direct feed mode and had originally planned to use the Low Activity Waste Pretreatment System (LAWPS) to supply the initial feed in 2021. In September 2017, in response to a DOE-sponsored LAWPS program review, a new system was proposed to provide the initial feed during direct feed mode until a supplemental pretreatment capability is ready to begin processing feed. This system, known as the Tank Side Cesium Removal (TSCR) system, is based on the Savannah River Tank Closure Cesium Removal (TCCR) system and technology used to separate cesium out of reactor water at Fukushima. A preliminary flowsheet was needed to form the initial basis for future decisions and allow discussions between operations, project management, and the customer. The main goal of the TSCR flowsheet was to form a process flow diagram, process description, and much of the preliminary information to be used to help inform future decisions. When flowsheet development first began, little to no information was readily known and what was known needed to be compiled in one place and digestible by several audiences. The impacts of various parameters on the system also needed a vehicle for clear communication to varying audiences. While a more complicated model was being completed, a model of the process was created using Microsoft Excela which could have several parameters changed while maintaining basic logical requirements (such as treated waste volume cannot exceed the volume of the Interim LAW Storage Tank [ILST], must shutdown for so many days for column changeout, etc.). This program allowed the unit downtime, start dates, treatment rates, and several other variables to be modified and reflect the ILST storage volume as a function of mission progression. The model with several different parameters gathered from the various groups was combined into an early flowsheet of the TSCR process and created one of the first citable documents about TSCR implementation at Hanford. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2023

Machine Learning Models for Network Traffic Classification in Programmable Logic

Network traffic classification via machine learning on network packet payloads has emerged as an active area of research for network security due to the high accuracy machine learning models have achieved in classifying payloads. For effective deployment as part of network security, these machine learning models must not only classify malicious packet payloads accurately, they must also identify anomalous payloads and perform inference at speeds generally faster than 10,000 packets per second to be effective. This work explores the in- ference speeds and accuracy of several neural network models implemented in programmable logic on various field programmable gate arrays (FPGA) including the Xilinx VC1902 and Xilinx Zynq Ultrascale+. This work also presents the design and performance of both an autoencoder and variational autoencoder programmed on the FPGA for identifying anomalous packet payloads. The performance benefits of the FPGA implementation for this type of packet payload inspection driven by machine learning are compared against graphics processing unit (GPU) inference implementations run on two state-of-the-art datacenter GPU devices, the NVIDIA V100 and A100. The model accuracy difference between the FPGA and GPU implementations was found to be 4% or less while the Xilinx VC1902 outperformed both the NVIDIA V100 and A100 for inference speeds on all the models explored except the variational autoencoder.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Control System Upgrade for Battery State-of-Charge Indications

The Advanced Test Reactor (ATR) Complex at Idaho National Laboratory (INL) relies on Battery Backed Power (BBP) systems and Uninterruptible Power Supplies (UPS) to ensure continuous power supply to critical components. This project aims to enhance the reliability and functionality of the battery monitoring and control systems by updating the State-of-Charge (SOC) system, Programmable Logic Controller (PLC), and Human-Machine Interface (HMI) for the nuclear safety-related battery banks. The current system, while functional, has areas for improvement, particularly in recharging calculations and alarm functions. The project objectives include developing flow charts, programming the new PLC and HMI, conducting bench tests, and updating design documentation. Additionally, the project ensures compliance with safety standards, develops training materials, creates comprehensive documentation, and integrates seamlessly with existing ATR infrastructure. The new SOC system is designed to be scalable for future upgrades, improve efficiency, enhance data accuracy, implement redundancy features, and achieve project goals within budget constraints while considering environmental impact. The methodology involved familiarizing with BBP and UPS systems, collecting current readings, rescaling signals, learning ladder logic, and updating the HMI. The transition from SLC 5/03 PLC using RS Logix 500 to CompactLogix 5380 using Studio 5000 was a key step. Despite challenges in transferring outdated PLC ladder logic and HMI code, starting from scratch led to a more accurate and efficient monitoring system, contributing to improved safety and operational efficiency. The project is currently awaiting approval of the Engineering Calculation and Analysis Report (ECAR) before implementation.

42 - ENGINEERING↗
DOE OSTI2020

The GABLE Report: Garbled Autonomous Bots Leveraging Ethereum

Simple but mission-critical internet-based applications that require extremely high reliability and availability could potentially benefit from running on robust public programmable blockchain platforms such as Ethereum. Unfortunately, program code running on such blockchains is ordinarily publicly viewable, rendering these platforms unsuitable for applications requiring strict privacy of application code, data, and results. However, might it be possible to encode an application's business logic and data for these platforms in such a way that it becomes impossible for unauthorized parties to infer any meaningful information whatsoever about the semantics of the data, and the operations being performed on that data? In this report, we describe GABLE (Garbled Autonomous Bots Leveraging Ethereum), a system concept developed at Sandia that achieves this security goal in a limited, but still useful range of circumstances. GABLE, uses simple but effective algorithms to permit secure private execution of garbled state machines (and more efficient garbled circuits) on public computing resources. We give an example working implementation for garbled state machines, written using the Python and Solidity programming languages, and outline how our methods can be extended to support a more powerful garbled universal circuit model of computation. The capability embodied by the GABLE, system has significant potential applications, a few of which we discuss in this report.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2013

Hanford River Protection Project Life cycle Cost Modeling Tool to Enhance Mission Planning - 13396

The Life cycle Cost Model (LCM) Tool is an overall systems model that incorporates budget, and schedule impacts for the entire life cycle of the River Protection Project (RPP) mission, and is replacing the Hanford Tank Waste Operations Simulator (HTWOS) model as the foundation of the RPP system planning process. Currently, the DOE frequently requests HTWOS simulations of alternative technical and programmatic strategies for completing the RPP mission. Analysis of technical and programmatic changes can be performed with HTWOS; however, life cycle costs and schedules were previously generated by manual transfer of time-based data from HTWOS to Primavera P6. The LCM Tool automates the preparation of life cycle costs and schedules and is needed to provide timely turnaround capability for RPP mission alternative analyses. LCM is the simulation component of the LCM Tool. The simulation component is a replacement of the HTWOS model with new capability to support life cycle cost modeling. It is currently deployed in G22, but has been designed to work in any full object-oriented language with an extensive feature set focused on networking and cross-platform compatibility. The LCM retains existing HTWOS functionality needed to support system planning and alternatives studies going forward. In addition, it incorporates new functionality, coding improvements that streamline programming and model maintenance, and capability to input/export data to/from the LCM using the LCM Database (LCMDB). The LCM Cost/Schedule (LCMCS) contains cost and schedule data and logic. The LCMCS is used to generate life cycle costs and schedules for waste retrieval and processing scenarios. It uses time-based output data from the LCM to produce the logic ties in Primavera P6 necessary for shifting activities. The LCM Tool is evolving to address the needs of decision makers who want to understand the broad spectrum of risks facing complex organizations like DOE-RPP to understand how near-term programmatic decisions affect life cycle costs and commitments. (authors)

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2013

Dynamic Event Tree Analysis Through RAVEN

Conventional Event-Tree (ET) based methodologies are extensively used as tools to perform reliability and safety assessment of complex and critical engineering systems. One of the disadvantages of these methods is that timing/sequencing of events and system dynamics is not explicitly accounted for in the analysis. In order to overcome these limitations several techniques, also know as Dynamic Probabilistic Risk Assessment (D-PRA), have been developed. Monte-Carlo (MC) and Dynamic Event Tree (DET) are two of the most widely used D-PRA methodologies to perform safety assessment of Nuclear Power Plants (NPP). In the past two years, the Idaho National Laboratory (INL) has developed its own tool to perform Dynamic PRA: RAVEN (Reactor Analysis and Virtual control ENvironment). RAVEN has been designed in a high modular and pluggable way in order to enable easy integration of different programming languages (i.e., C++, Python) and coupling with other application including the ones based on the MOOSE framework, developed by INL as well. RAVEN performs two main tasks: 1) control logic driver for the new Thermo-Hydraulic code RELAP-7 and 2) post-processing tool. In the first task, RAVEN acts as a deterministic controller in which the set of control logic laws (user defined) monitors the RELAP-7 simulation and controls the activation of specific systems. Moreover, RAVEN also models stochastic events, such as components failures, and performs uncertainty quantification. Such stochastic modeling is employed by using both MC and DET algorithms. In the second task, RAVEN processes the large amount of data generated by RELAP-7 using data-mining based algorithms. This paper focuses on the first task and shows how it is possible to perform the analysis of dynamic stochastic systems using the newly developed RAVEN DET capability. As an example, the Dynamic PRA analysis, using Dynamic Event Tree, of a simplified pressurized water reactor for a Station Black-Out scenario is presented.

42 ENGINEERING↗