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All sources NASA NTRS DOE OSTI

DOE OSTI2017

Development of a utility computer-based training program on setpoint methodology for nuclear power plants - 129

The purpose of this paper is to provide an overview of the development of the Computer- Based Training (CBT) Program for utility engineers on Setpoint Methodology for nuclear power plants. This computer based training module was prepared by the Advanced Engineering Training initiative. The Advanced Engineering Training initiative is a nuclear industry effort to develop technical computer-based training modules for targeted areas of engineering expertise. The target audience is engineers at commercial nuclear power facilities in the U. S. These modules are being developed using the systematic approach to training and are being designed to maintain industry engineering expertise and to facilitate engineering knowledge transfer. The objective of this training effort is to support the development of the next generation of site technical experts for specific topic areas. The training is one part of three key components that would facilitate knowledge transfer to the future site Subject Matter Expert (SME). The following are the major focus areas covered in the Setpoint Methodology CBT: Chapter 1 provides an overview of the role instrument setpoints perform in the defense-in-depth safety analysis for the plant as well introducing key definitions related to setpoints. Chapter 2 provides the history and current regulatory requirements related to setpoint control including the laws and guidance provided by the U.S. NRC. Chapter 3 provides describes the setpoint methodology including terms, formulae, methods of combination, graded approach and methods for drift analysis. This is a major part of the training module in covering the incremental uncertainty terms that need to be considered and how they are combined. Chapter 4 provides and overview of the role of setpoints in Technical Specifications and associated documents. Chapter 5 describes how the regulatory process, related to setpoint control, has been implemented in NRC inspections and how the major elements of the 10 CFR 50.59 reviews apply to the performance of a new or revised setpoint calculation. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2017

Additive Manufacturing of Fuel Injectors

Additive manufacturing (AM), also known as 3D-printing, has been shifting from a novelty prototyping paradigm to a legitimate manufacturing tool capable of creating components for highly complex engineered products. An emerging AM technology for producing metal parts is the laser powder bed fusion (L-PBF) process; however, industry manufacturing specifications and component design practices for L-PBF have not yet been established. Solar Turbines Incorporated (Solar), an industrial gas turbine manufacturer, has been evaluating AM technology for development and production applications with the desire to enable accelerated product development cycle times, overall turbine efficiency improvements, and supply chain flexibility relative to conventional manufacturing processes (casting, brazing, welding). Accordingly, Solar teamed with EWI on a joint two-and-a-half-year project with the goal of developing a production L-PBF AM process capable of consistently producing high-nickel alloy material suitable for high temperature gas turbine engine fuel injector components. The project plan tasks were designed to understand the interaction of the process variables and their combined impact on the resultant AM material quality. The composition of the high-nickel alloy powders selected for this program met the conventional cast Hastelloy X compositional limits and were commercially available in different particle size distributions (PSD) from two suppliers. Solar produced all the test articles and both EWI and Solar shared responsibility for analyzing them. The effects of powder metal input stock, laser parameters, heat treatments, and post-finishing methods were evaluated. This process knowledge was then used to generate tensile, fatigue, and creep material properties data curves suitable for component design activities. The key process controls for ensuring consistent material properties were documented in AM powder and process specifications. The basic components of the project were: • Powder metal input stock: Powder characterization, dimensional accuracy, metallurgical characterization, and mechanical properties evaluation. • Process parameters: Laser parameter effects, post-printing heat-treatment development, mechanical properties evaluation, and post-finishing technique. • Material design curves: Room and elevated temperature tensiles, low cycle fatigue, and creep rupture properties curves generated. • AM specifications: Key metal powder characteristics, laser parameters, and heat-treatment controls identified.

36 MATERIALS SCIENCE↗

DOE OSTI2014

Review of Graph Databases for Big Data Dynamic Entity Scoring

Modeling data as a graph enables users to quickly analyze networked phenomenon, such as social network-based marketing data (e.g., linking entities in social media based on their friends and their "likes", their friend-of-a-friend's "likes", etc.) and scientific data, such as in biology to assess a gene's proximity in a graph to particular disease phenotype. Numerous purpose-built graph databases (DBs) called “NoSQL” or “Not Only SQL” DBs are emerging to support this type of graph analysis. These DBs differ from traditional relational DBs in that they are optimized to improve storage and query performance across large, complex graphs. This document reviews the state of the art in graph DBs and identifies potential DBs that show promise for dynamic entity-scoring algorithms. Dynamic entity scoring is a new area of research that allows analysis of data within graphs using undirected methods to weigh the edges of the graph based on the proximity or ambient influence of near-by nodes. The EntityScore (eScore) methodology developed at Lawrence Livermore National Laboratory (LLNL) is one application of these emerging graph-analysis algorithms to help analysts identify and prioritize entities, based on complex, analyst-defined weighting criteria. Our review examines a wide range of different, well-known graph DBs in use since at least 2010 and identifies unique advantages and disadvantages that may impact eScore-specific requirements. Specifically, we review data structures employed, query features employed, load times, query calculation times, memory usage and several other important attributes reported in the literature. We limited our considerations for eScore to Blueprints-compliant graph DBs (https://github.com/tinkerpop/blueprints/) because they provide a standard, java application programming interface (API) based on the property graph model.

42 ENGINEERING↗

NASA NTRS2018

Modeling Principles Using the Relation Between Lagrange Multipliers and Bond Graphs

Final document is attached. Modeling dynamic systems by bond graphs has become state of the art technology since hundreds of researchers around the world have incorporated the technology in many fields of engineering and science. The legacy of its invertor Prof. Henry Paynter at MIT in 1959 is now a fundamental and practical technique to understand reality by building computer models. This paper addresses a particular aspect of this technology when modeling of mechanical systems require relaxation of constraints by means of Lagrange principles. Lagrange's equations are a useful means of describing and solving systems with kinematic constraints. Lagrange multipliers are variables used in equations to find the extremes of multivariate functions. Here we explore the relation of Lagrange multipliers to solve modeling difficulties of a space vehicle with equations with dependent derivatives. Lagrange multipliers were used in conjunction with bond graphs to simulate a system where joints of kinematic linkages produce dependent derivatives. NASA's Morpheus Project lunar lander was used as a case study. The Morpheus Project is a terrestrial test vehicle designed to fly the terminal descent trajectory of a lunar lander to advance the Autonomous Landing Hazard Avoidance Technology (ALHAT). An objective of this study is to apply the modeling approach herein to capture the dynamic movement of the lander as the propellant is sloshed and consumed. This paper expands further the analysis presented by (Granda, J J. Nguyen, L, Carlson, T, Sahragard-Monfared, G., Fornalski, E., Brocker 2016). Using an automated approach bond graph models of state space equations were generated using the Computer Aided Modeling Program (CAMPG). Integral causality models and derivative causality models were considered in order to find the simpler solution for the mathematical dependencies produced in modeling this vehicle.

Granda, Jose J.↗

DOE OSTI2024

Artificial Intelligence/Machine Learning Technology in Power System Applications

The primary purpose of this report is to provide an overview of the advancement in artificial intelligence and machine learning (AI/ML) technologies and their applications in power systems. It offers a foundation for understanding the transformative role of AI/ML in power systems and aims to stimulate further research and development in this area. This report begins with a historical perspective of AI/ML technologies, then explores their advancement to today’s prominence. The document highlights key contributors to the success of AI/ML technologies, including increased computational power, greater data availability, innovative algorithms, and advanced tools. It further introduces various AI/ML techniques, including supervised, unsupervised and reinforcement learning, graph neural networks, and generative AI. It also emphasizes the critical importance of ensuring the safety, security, and trustworthiness of these AI/ML techniques within this sector. The report reviews the recent representative advancements in various power system applications enhanced by AI/ML techniques, underscoring key developments and their transformative impact as evidenced by numerous studies. It also explores both the opportunities and challenges associated with the application of AI/ML technologies to improve power system applications. While the report extensively covers AI/ML applications in power systems, focusing primarily on the technical and operational aspects, it may not thoroughly explore the sociopolitical, economic, and broader regulatory implications of AI/ML integration in power systems. AI/ML techniques hold significant potential for enhancing power system applications; however, they are not omnipotent. It is crucial to acknowledge their limitations and understand that they may not be able to address all challenges in the power system domain. Various factors must be considered that influence the implementation, adoption, and effectiveness of AI/ML solutions, including but not limited to safety, security, transparency, and trustworthiness. Additionally, the incorporation of advanced human–machine interfaces is essential, as it enables humans to validate the effectiveness of AI/ML solutions while remaining actively engaged, fostering trust in AI/ML deployment. Finally, the report summarizes AI/ML research activities supported by the Department of Energy (DOE) Office of Electricity (OE) through the Advanced Grid Modeling (AGM) program. The work aligns with the interests and mission of DOE-OE AGM, with the report serving as a resource for identifying existing progress and for pinpointing future applications within AI/ML that need further exploration and support.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2015

RAVEN User Manual

RAVEN is a generic software framework to perform parametric and probabilistic analysis based on the response of complex system codes. The initial development was aimed to provide dynamic risk analysis capabilities to the Thermo-Hydraulic code RELAP-7, currently under development at the Idaho National Laboratory (INL). Although the initial goal has been fully accomplished, RAVEN is now a multi-purpose probabilistic and uncertainty quantification platform, capable to agnostically communicate with any system code. This agnosticism includes providing Application Programming Interfaces (APIs). These APIs are used to allow RAVEN to interact with any code as long as all the parameters that need to be perturbed are accessible by inputs files or via python interfaces. RAVEN is capable of investigating the system response, and investigating the input space using Monte Carlo, Grid, or Latin Hyper Cube sampling schemes, but its strength is focused toward system feature discovery, such as limit surfaces, separating regions of the input space leading to system failure, using dynamic supervised learning techniques. The development of RAVEN has started in 2012, when, within the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program, the need to provide a modern risk evaluation framework became stronger. RAVEN principal assignment is to provide the necessary software and algorithms in order to employ the concept developed by the Risk Informed Safety Margin Characterization (RISMC) program. RISMC is one of the pathways defined within the Light Water Reactor Sustainability (LWRS) program. In the RISMC approach, the goal is not just the individuation of the frequency of an event potentially leading to a system failure, but the closeness (or not) to key safety-related events. Hence, the approach is interested in identifying and increasing the safety margins related to those events. A safety margin is a numerical value quantifying the probability that a safety metric (e.g. for an important process such as peak pressure in a pipe) is exceeded under certain conditions. The initial development of RAVEN has been focused on providing dynamic risk assessment capability to RELAP-7, currently under development at the INL and, likely, future replacement of the RELAP5-3D code. Most the capabilities that have been implemented having RELAP-7 as principal focus are easily deployable for other system codes. For this reason, several side activaties are currently ongoing for coupling RAVEN with software such as RELAP5-3D, etc. The aim of this document is the explanation of the input requirements, focalizing on the input structure.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2017

RAVEN User Manual

RAVEN is a generic software framework to perform parametric and probabilistic analy- sis based on the response of complex system codes. The initial development was aimed to provide dynamic risk analysis capabilities to the Thermo-Hydraulic code RELAP-7, currently under development at the Idaho National Laboratory (INL). Although the initial goal has been fully accomplished, RAVEN is now a multi-purpose probabilistic and uncer- tainty quantification platform, capable to agnostically communicate with any system code. This agnosticism includes providing Application Programming Interfaces (APIs). These APIs are used to allow RAVEN to interact with any code as long as all the parameters that need to be perturbed are accessible by inputs files or via python interfaces. RAVEN is capable of investigating the system response, and investigating the input space using Monte Carlo, Grid, or Latin Hyper Cube sampling schemes, but its strength is focused to- ward system feature discovery, such as limit surfaces, separating regions of the input space leading to system failure, using dynamic supervised learning techniques. The development of RAVEN has started in 2012, when, within the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program, the need to provide a modern risk evaluation framework became stronger. RAVEN principal assignment is to provide the necessary software and algorithms in order to employ the concept developed by the Risk Informed Safety Margin Characterization (RISMC) program. RISMC is one of the pathways defined within the Light Water Reactor Sustainability (LWRS) program. In the RISMC approach, the goal is not just the individuation of the frequency of an event potentially leading to a system failure, but the closeness (or not) to key safety-related events. Hence, the approach is in- terested in identifying and increasing the safety margins related to those events. A safety margin is a numerical value quantifying the probability that a safety metric (e.g. for an important process such as peak pressure in a pipe) is exceeded under certain conditions. The initial development of RAVEN has been focused on providing dynamic risk assess- ment capability to RELAP-7, currently under develop-ment at the INL and, likely, future replacement of the RELAP5-3D code. Most the capabilities that have been implemented having RELAP-7 as principal focus are easily deployable for other system codes. For this reason, several side activates are currently ongoing for coupling RAVEN with soft- ware such as RELAP5-3D, etc. The aim of this document is the explaination of the input requirements, focalizing on the input structure.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2022

Compare $\overline{ν}$ parameterizations for 235 U(n,f) with fitted fission barriers

In this document, we compare observables computed with CGMF to some available data for 235 U(n,f), to investigate the multi-chance fission probabilities (fission barriers from CoH were refit) and two TKE parametrization. The four parametrizations include i) default CGMF multi-chance fission probabilities with bends in TKE for all fission chances, ii) default CGMF multi-chance fission probabilities with a TKE bend in only first-chance fission iii) refitted multi-chance fission probabilities with bends in TKE for all fission chances, and iv) refitted multi-chance fission probabilities with a bend in TKE for only first-chance fission. In all figures where the four parametrizations are on the same plot, the ones with bends in TKE for all chance fission are in black, with only first-chance bend in red, the default multi-chance fission probabilities are dashed and the new multi-chance fission probabilities are the solid lines.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

NASA NTRS1990

Development of a knoweledge-based system for validating finite element models

The finite element modeling of an airframe structure requires knowledge of general purpose programs such as NASTRAN as well as a detailed understanding of the airframe structure. Due to the sophistication of general purpose programs such as NASTRAN, a substantial investment in time and effort is required to gain expertise in using them effectively. This paper describes the development of an expert system used in the validation of NASTRAN based finite element models. Experts in the NASTRAN based finite element modeling of airframe structures were interviewed to document, understand, and represent their knowledge and reasoning in the expert system. Finite element stress analysis and internal loads reports generated by the experts were reviewed to determine expert resolution of problem areas. As a result, areas requiring expert assistance in the modeling of the airframe structures were identified. The finite element input data is represented as a set of 'facts'. A rule based representation is used to code the expert knowledge. A hierarchical set of rules are applied. The expert system first acts as an intelligent front end to insure that all the prerequisites needed to perform the analysis are present. This includes material properties, boundary conditions, and connectivity information. The next step examines if incompatible sets of elements are connected. The succeeding step examines if the specific airframe component is modeled by the appropriate set of elements. The next and final step examines if the airframe members used are adequate to represent the anticipated state of stress. The expert system is designed to inform the user the severity of the error, the likely consequence and possible remedial action. The shell used in the development of the expert system is CLIPS. CLIPS contains a forward chaining inference engine based on the Rete algorithm. CLIPS may be implemented on most personal computers as well as mini computers and mainframes. The approach taken is general and can be implemented using commercially available expert system shells.

Munir, N. I.↗

DOE OSTI2016

Experiments and Computational Theory for Electrical Breakdown in Critical Components: THz Imaging of Electronic Plasmas.

This report describes the development of ultra-short pulse laser (USPL) induced terahertz (THz) radiation to image electronic plasmas during electrical breakdown. The technique uses three pulses from two USPLs to (1) trigger the breakdown, (2) create a 2 picosecond (ps, 10 -12 s), THz pulse to illuminate the breakdown, and (3) record the THz image of the breakdown. During this three year internal research program, sub-picosecond jitter timing for the lasers, THz generation, high bandwidth (BW) diagnostics, and THz image acquisition was demonstrated. High intensity THz radiation was optically-induced in a pulse-charged gallium arsenide photoconductive switch. The radiation was collected, transported, concentrated, and co-propagated through an electro-optic crystal with an 800 nm USPL pulse whose polarization was rotated due to the spatially varying electric field of the THz image. The polarization modulated USPL pulse was then passed through a polarizer and the resulting spatially varying intensity was detected in a high resolution digital camera. Single shot images had a signal to noise of %7E3:1. Signal to noise was improved to %7E30:1 with several experimental techniques and by averaging the THz images from %7E4000 laser pulses internally and externally with the camera and the acquisition system (40 pulses per readout). THz shadows of metallic films and objects were also recorded with this system to demonstrate free-carrier absorption of the THz radiation and improve image contrast and resolution. These 2 ps THz pulses were created and resolved with 100 femtosecond (fs, 10 -15 s) long USPL pulses. Thus this technology has the capability to time-resolve extremely fast repetitive or single shot phenomena, such as those that occur during the initiation of electrical breakdown. The goal of imaging electrical breakdown was not reached during this three year project. However, plans to achieve this goal as part of a follow-on project are described in this document. Further modifications to improve the THz image contrast and resolution are proposed, and after they are made, images of photo-induced carriers in gallium arsenide and silicon will be acquired to evaluate image sensitivity versus carrier density. Finally electrical breakdown will be induced with the first USPL pulse, illuminated with THz radiation produced with the second USPL pulse and recorded with the third USPL pulse.

36 MATERIALS SCIENCE↗

DOE OSTI2017

The MARS Code System User’s Guide Version 15(2016)

This paper is a user’s guide to the current version of the MARS15 Monte Carlo code. MARS allows inclusive and, in many cases, exclusive simulations of three-dimensional hadronic and electromagnetic cascades and modeling of heavy ion, muon and low energy neutron-photon transport in accelerator, detector, spacecraft and shielding components. Particles can have energies from a fraction of an electronvolt up to about 100 TeV. The code has undergone substantial improvements since the last documented version MARS13(95) and since previous releases of MARS15; all these as well as other specific features of the MARS code system are explained in detail. Descriptions of general input and output with commentary and recommendations are given. Examples are given for running the program with distributed sources, complex compounds, arbitrary geometries, and magnetic fields. A built-in graphical-user interface allows the visualization and detailed analysis of the geometry description. Enhanced options are described for the MARS code being coupled with: the DPMJET hadron event generator, the MCNP code for low-energy neutron transport, the ANSYS system for thermal and stress analysis, physics analysis and graphics packages, the MAD accelerator lattice description via a universal MAD-MARS beam line builder, the STRUCT program for tracking particles in accelerator lattices with beam loss recording, the DETRA code for nuclide decay and transmutation calculations, the EGS5 code for precise modeling of low-energy electromagnetic showers, and the ROOT system for description and visualization of arbitrary geometries. Use of the code in a multistage mode, coupled with event generators (DPMJET), with the STRUCT program for tracking particles in accelerator lattices with beam loss recording, and with physics analysis and graphics packages is demonstrated with typical input and output examples.

43 PARTICLE ACCELERATORS↗

DOE OSTI2017

RAVEN User Manual

97 MATHEMATICS AND COMPUTING↗

NASA NTRS1995

Control of unsteady separated flow associated with the dynamic stall of airfoils

An effort to understand and control the unsteady separated flow associated with the dynamic stall of airfoils was funded for three years through the NASA cooperative agreement program. As part of this effort a substantial data base was compiled detailing the effects various parameters have on the development of the dynamic stall flow field. Parameters studied include Mach number, pitch rate, and pitch history, as well as Reynolds number (through two different model chord lengths) and the condition of the boundary layer at the leading edge of the airfoil (through application of surface roughness). It was found for free stream Mach numbers as low as 0.4 that a region of supersonic flow forms on the leading edge of the suction surface of the airfoil at moderate angles of attack. The shocks which form in this supersonic region induce boundary-layer separation and advance the dynamic stall process. Under such conditions a supercritical airfoil profile is called for to produce a flow field having a weaker leading-edge pressure gradient and no leading-edge shocks. An airfoil having an adaptive-geometry, or dynamically deformable leading edge (DDLE), is under development as a unique active flow-control device. The DDLE, formed of carbon-fiber composite and fiberglass, can be flexed between a NACA 0012 profile and a supercritical profile in a controllable fashion while the airfoil is executing an angle-of-attack pitch-up maneuver. The dynamic stall data were recorded using point diffraction interferometry (PDI), a noninvasive measurement technique. A new high-speed cinematography system was developed for recording interferometric images. The system is capable of phase-locking with the pitching airfoil motion for real-time documentation of the development of the dynamic stall flow field. Computer-aided image analysis algorithms were developed for fast and accurate reduction of the images, improving interpretation of the results.

Wilder, M. C.↗

DOE OSTI2021

Nanosecond Gated CMOS Camera (NSGCC) ICD (Rev. 2.1)

The Ultra-Fast X-ray Imager (UXI) program is an ongoing effort at Sandia National Laboratories to create high speed, multi-frame, time-gated Read Out Integrated Circuits (ROICs), and a corresponding suite of photodetectors to image a wide variety of High Energy Density (HED) physics experiments on both Sandia’s Z-Machine and LLNL’s National Ignition Facility (NIF). Several cameras have been designed over the length of the program; one of the most recent is the Icarus, which is an improvement on past imagers (Furi and Hippogriff). A second sensor that can be connected is the Daedalus sensor. The Icarus is a 1024 × 512-pixel array with either 25 μm or 8 µm spatial resolution containing four frames of storage per pixel and has improved timing generation and distribution components while achieved 2 ns time gating. The Daedalus sensor is also a 1024 x 512-pixel array with 25 µm special resolution containing three frames of storage per pixel and has an increased set of features for a wider variety of applications from interlacing of rows in each frame to configurability of all shutters. See Section 14 for details regarding the Icarus implementation of the firmware and Section 15 for details regarding the Daedalus implementation. Due to the unique test environments UXI sensors are targeted for, full custom hardware was required to physically mount an Icarus or Daedalus sensor, manage its various functions, and read out pixel data for transfer to a host computer. Beyond experimental functionality, the hardware also needed to accommodate sensor characterization requirements. Lawrence Livermore National Laboratory’s ‘Version 4.0 Board’ was the result of these efforts. It mounts all the components required to fully utilize the Icarus and Daedalus sensors including analog to digital converters to convert pixel data and various system voltages to digital form for readout and analysis, DAC channels for remote configuration of critical bias voltages, static random-access memories to buffer pixel data, RS422 and Gigabit Ethernet communications for remote access, and an FPGA to tie these components together. This document describes the FPGA electrical interfaces in detail to allow the reader a greater understanding of the device, and to facilitate implementation of custom software to control and manage it. The Version 4.0 Board is a continuation of the Nano-second Gated CMOS hardware design that retains much of the functionality of the Version 1.0 Board while adding features including a DAC instead of digital potentiometers, as well as sensors for pressure and radiation. The Version 4.0 board is intended for applications requiring tight form-factor enclosures. It is composed of two stacking boards; one holds the FPGA and regulators to power the various components of the board while the other contains the mating connector to the sensor, image-readoff ADCs, the DAC, and other components.

42 ENGINEERING↗

NASA NTRS1997

An Approach to Building a Traceability Tool for Software Development

It is difficult in a large, complex computer program to ensure that it meets the specified requirements. As the program evolves over time, a11 program constraints originally elicited during the requirements phase must be maintained. In addition, during the life cycle of the program, requirements typically change and the program must consistently reflect those changes. Imagine the following scenario. Company X wants to develop a system to automate its assembly line. With such a large system, there are many different stakeholders, e.g., managers, experts such as industrial and mechanical engineers, and end-users. Requirements would be elicited from all of the stake holders involved in the system with each stakeholder contributing their point of view to the requirements. For example, some of the requirements provided by an industrial engineer may concern the movement of parts through the assembly line. A point of view provided by the electrical engineer may be reflected in constraints concerning maximum power usage. End-users may be concerned with comfort and safety issues, whereas managers are concerned with the efficiency of the operation. With so many points of view affecting the requirements, it is difficult to manage them, communicate information to relevant stakeholders. and it is likely that conflicts in the requirements will arise. In the coding process, the implementors will make additional assumptions and interpretations on the design and the requirements of the system. During any stage of development, stakeholders may request that a requirement be added or changed. In such a dynamic environment, it is difficult to guarantee that the system will preserve the current set of requirements. Tracing, the mapping between objects in the artifacts of the system being developed, addresses this issue. Artifacts encompass documents such as the system definition, interview transcripts, memoranda, the software requirements specification, user's manuals, the functional specifications, design reports, and system code. Tracing helps 1) validate system features against, the requirement specification, 2) identify error sources and, most importantly, 3) manage change. With so many people involved in the development of the system, it becomes necessary to identify the reasons behind the design requirements or the implementation decisions. This paper is concerned with an approach that maps documents to constraints that capture properties of and relationships between the objects being modeled by the program. Section 2 provides the reader with a background on traceability tools. Section 3 gives a brief description of the context monitoring system on which the approach suggested in this paper is based. Section 4 presents an overview of our approach to providing traceability. The last section presents our future direction of research.

Delgado, Nelly↗

NASA NTRS2017

Programmable Logic Device (PLD) Design Description for the Integrated Power, Avionics, and Software (iPAS) Space Telecommunications Radio System (STRS) Radio

The Space Telecommunications Radio System (STRS) provides a common, consistent framework for software defined radios (SDRs) to abstract the application software from the radio platform hardware. The STRS standard aims to reduce the cost and risk of using complex, configurable and reprogrammable radio systems across NASA missions. To promote the use of the STRS architecture for future NASA advanced exploration missions, NASA Glenn Research Center (GRC) developed an STRS compliant SDR on a radio platform used by the Advance Exploration System program at the Johnson Space Center (JSC) in their Integrated Power, Avionics, and Software (iPAS) laboratory. At the conclusion of the development, the software and hardware description language (HDL) code was delivered to JSC for their use in their iPAS test bed to get hands-on experience with the STRS standard, and for development of their own STRS Waveforms on the now STRS compliant platform.The iPAS STRS Radio was implemented on the Reconfigurable, Intelligently-Adaptive Communication System (RIACS) platform, currently being used for radio development at JSC. The platform consists of a Xilinx ML605 Virtex-6 FPGA board, an Analog Devices FMCOMMS1-EBZ RF transceiver board, and an Embedded PC (Axiomtek eBox 620-110-FL) running the Ubuntu 12.4 operating system. Figure 1 shows the RIACS platform hardware. The result of this development is a very low cost STRS compliant platform that can be used for waveform developments for multiple applications.The purpose of this document is to describe the design of the HDL code for the FPGA portion of the iPAS STRS Radio particularly the design of the FPGA wrapper and the test waveform.

VHDL↗

DOE OSTI2013

The SCALE Verified, Archived Library of Inputs and Data - VALID

The Verified, Archived Library of Inputs and Data (VALID) at ORNL contains high quality, independently reviewed models and results that improve confidence in analysis. VALID is developed and maintained according to a procedure of the SCALE quality assurance (QA) plan. This paper reviews the origins of the procedure and its intended purpose, the philosophy of the procedure, some highlights of its implementation, and the future of the procedure and associated VALID library. The original focus of the procedure was the generation of high-quality models that could be archived at ORNL and applied to many studies. The review process associated with model generation minimized the chances of errors in these archived models. Subsequently, the scope of the library and procedure was expanded to provide high quality, reviewed sensitivity data files for deployment through the International Handbook of Evaluated Criticality Safety Benchmark Experiments (IHECSBE). Sensitivity data files for approximately 400 such models are currently available. The VALID procedure and library continue fulfilling these multiple roles. The VALID procedure is based on the quality assurance principles of ISO 9001 and nuclear safety analysis. Some of these key concepts include independent generation and review of information, generation and review by qualified individuals, use of appropriate references for design data and documentation, and retrievability of the models, results, and documentation associated with entries in the library. Some highlights of the detailed procedure are discussed to provide background on its implementation and to indicate limitations of data extracted from VALID for use by the broader community. Specifically, external users of data generated within VALID must take responsibility for ensuring that the files are used within the QA framework of their organization and that use is appropriate. The future plans for the VALID library include expansion to include additional experiments from the IHECSBE, to include experiments from areas beyond criticality safety, such as reactor physics and shielding, and to include application models. In the future, external SCALE users may also obtain qualification under the VALID procedure and be involved in expanding the library. The VALID library provides a pathway for the criticality safety community to leverage modeling and analysis expertise at ORNL.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2018

Managing Resin Wastes - Crossing the Digital Divide - 18326

The most important factor undercutting optimal waste management in the nuclear industry is developing a clear picture of the radioactivity content of the waste and its impact on waste disposal cost. For almost 35 years since the publishing of 10CFR61, waste characterization has relied on building its basis from samples collected from the final waste product as it is drawn from service or as it is packaged for disposal. This practice of sampling the product after it was collected continues to be followed to this day; 35 years after the publication of 10CFR61. This process, as it is followed, relies on minimum information and plant knowledge to formulate the characterization. While 10CFR61 and additional guidance documents promote the approach of using anticipated and statistically based scaling factors in addition to using data collected over time and a finite grouping of waste streams encompassing plant wastes, this guidance is often ignored in favor of using the earlier fallback options in the case of a limited sample base. The fallback allows the use of a final sample drawn from the waste when other data was not sufficiently available to be aligned to develop meaningful statistics. The determination of representativeness is obviated by the single sample resulting in a new waste stream being declared with every package. The sample used without statistical corroboration often is not representative. It would be unexpected if that sample were actually representative of anything more than itself. This paper discusses viable options for developing the basis for characterization through direct process monitoring to follow the accumulation of activity at the point of generation relying on hundreds of measurements being collected on a daily and weekly basis that can provide a much more reliable result along with significant cost savings. Direct monitoring of the accumulation of activity in process streams generating solid radwaste, including demineralizers and filter streams, is a more precise approach. Nearly all of these streams are monitored by plant chemistry on a regular schedule to maintain water quality and track fuel performance. The discussion in this paper will focus on resin bed tracking and how process knowledge drawn from routinely collected chemistry data can be brought together to form a consistent and precise solid waste radioactivity inventory. Some of the specific points covered in the paper include application and expansion of the fission product release computer program 3R-STAT, the importance of the spent fuel pool in radioactivity generation and its influence on the overall source term, and results from sample measurements collected over several years to corroborate using direct process measurements for the primary characterization basis. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗