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At least 253 records · Page 14

NEAMS-Multiphysics MOOSE End Year Framework Activities FY20

The Multiphysics Object Oriented Simulation Environment (MOOSE) is a general finite element package meant for high performance solution of multiphysics problems in science and engineering. In this report, we present additions and enhancements to MOOSE funded by the Nuclear Engineering Advanced Modeling and Simulation (NEAMS) program. NEAMS-funded MOOSE framework library improvements include: expansion of support for multi-level multi-application restart; enhancement of coupling between native MOOSE applications and external libraries; addition of a sparse automatic differentiation (AD) container enabling non-local degree of freedom coupling; block-specific quadrature rules; further development of an eigenvalue executioner; faster setup of periodic boundary conditions; and creation of a mesh meta-data system streamlining simulation startup. Besides developing the framework library, NEAMS funds were used to overhaul a swath of important MOOSE infrastructure in order to substantially improve user experience. These critical infrastructure changes included adapting MOOSE to python 3, improving the test harness to catch race conditions, and most importantly transitioning MOOSE to use Conda, a globally known packaging system, that greatly eases software adoption.

97 MATHEMATICS AND COMPUTING↗

EMT and Phasor-Domain Co-simulation of a Low Frequency AC Transmission System for Offshore Wind Integration

This work investigates system level interactions of multi-terminal low frequency high-voltage alternating current (LF-HVac) system using back-to back converters and grid-level 60 Hz system. A co-simulation framework by integrating high- fidelity dynamic model of multi-terminal LF-HVac system in electromagnetic transient (EMT) simulation platform and phasor model of IEEE 39 bus system in transient-stability (phasor) program. The co-simulation framework for multi-terminal LF- HVac system with offshore wind integrated in a bulk power system is developed successfully and its steady state and dynamic operation is demonstrated and compared with EMT simulation. The co-simulation results show accurate representation of the dynamic responses with reduced computation burden and time compared to EMT platform.

low-frequency transmission, co-simulation, electro↗

NASA spacecraft propulsion activities

The NASA's activities in the development of spacecraft propulsion systems are reviewed, with emphasis on program directions and recent progress made in this domain. The recent trends towards the use of smaller spacecraft and launch vehicles call for new onboard propulsion systems. The NASA's efforts are conducted within the framework of the onboard propulsion program. The research and development work carried out in relation to the different propulsion system technologies are considered: electromagnetic systems; electrostatic systems; electrothermal systems; bipropellant systems; and monopropellant systems.

Curran, Francis M.↗

Gas-Granular Simulation Framework for Spacecraft Landing Plume-Surface Interaction and Debris Transport Analysis

The Gas-Granular Flow Solver (GGFS) multi-phase flow computational framework has been developed to enable simulations of particle flows complex extra-terrestrial regolith materials. Particle flows of interest include the damage of unprepared landing sites from rocket plume impingement on Moon, Mars, and asteroids. The flow solver implements an Eulerian-Eulerian two-fluid model with fluid representation of the gas phase and granular phase to avoid the need to model billions of particle interactions. The granular phase is modeled as an Eulerian fluid with constituent physics closure models derived from first-principle Discrete Element Model (DEM) particle interaction simulations that capture the complex, non-linear granular particle interaction effects. Granular phase constituent models have been developed and integrated that address the complex, non-linear granular material mechanics complexities resulting from both: the irregular, jagged particle shapes and poly-disperse mixture effects encountered in extra-terrestrial regolith, with lunar regolith as the extreme. The GGFS capabilities are being integrated into a proven NASA plume-surface interaction and debris transport simulation framework featuring the Loci/CHEM CFD program and Debris Transport Analysis (DTA) post-processing tools for applications in robotic and human Moon and Mars lander development. Integration of the three simulation tool components. Loci/CHEM, GGFS, and DTA, into a coordinated simulation framework will enable time-accurate spacecraft landing simulations that account for the alteration of the landing surface through plume-induced cratering and the resulting redirection of plume impingement flow and debris transport. Initial implementation of this simulation framework and application examples will be presented.

Liever, Peter A.↗

NASA's Advanced Information Systems Technology (AIST): Combining New Observing Strategies and Analytics Frameworks to Build Earth System Digital Twins

NASA's Advanced Information Systems Technology (AIST) Program is one of several Technology programs managed by the Earth Science Technology Office (ESTO) in the Earth Science Division (ESD). The AIST Program focuses on advanced information systems and novel computer science technologies that will be needed by NASA Earth Science in the next 5 to 10 years. The three main thrusts of the AIST Program deal with New Observing Strategies, Analytic Collaborative Frameworks and Earth System Digital Twins. This paper describes these three thrusts and how they work together to create future Earth Science information systems.

Jacqueline Le Moigne↗

Real-Time Optimization Workflow Status Update

Economically optimal and safe operation of integrated energy systems (IES) requires optimization at many different time scales. A real-time optimization (RTO) workflow will attempt to maximize revenue and minimize operational costs on a time scale of minutes to hours. Such a workflow requires the use of a digital twin (DT), which is a virtual representation of a physical system. The DT is updated using real-time data from the physical system, and serves as a model in an optimization framework. The optimization results are then sent back to the physical system to complete the loop. This report details the progress made in developing building blocks for a DT/RTO framework. The Risk Analysis Virtual Environment (RAVEN) platform within the Framework for Optimization of Resources and Economics (FORCE) tool suite can perform many of the tasks required for building a DT and performing RTO. The first item of this report details RAVEN enhancements that enable RAVEN workflows to be run in various environments. Data communication between the physical system and its DT is essential for successful RTO. This includes preprocessing real-time data, loading data into a data warehouse, and querying the stored data. The second section of this report describes the progress made in implementing an adapter in Python in order for Deep Lynx to handle the data communication. Typical dispatch optimization frameworks are built on linear programming (LP). The prototype RTO workflow developed in this report uses an LP problem as a part of a receding-horizon- or economic model predictive control (EMPC) based optimization. The third section of this report details the framework of an RTO workflow in which the system consists of a simple electrical storage device. A DT can be built from a reduced-order model (ROM). Integrating a ROM into a typical LP optimization framework has been challenging because most optimization packages require the user to write algebraic expressions for the system model. The final section of this report shows how an externally built RAVEN ROM can be integrated in an RTO framework by using the Python package Pyomo. This demonstrates the RTO workflow capability from a software-only perspective and is an important step in demonstrating the capability to implement an RTO workflow for a physical system.

97 MATHEMATICS AND COMPUTING↗

INSTRUMENTATION FOR IN-CORE REAL-TIME MECHANICAL TESTING OF STRUCTURAL MATERIALS (INCREASE) PROJECT

Idaho National Laboratory (INL), in collaboration with the Electric Power Research Institute (EPRI), Nuclear Regulatory Commission, French Atomic and Alternative Energies Commission (CEA), Joint Research Centre, Nuclear Research and Consultancy Group, and Research Center Rez, is the operating agent of the In-Core Real-Time Mechanical Testing of Structural Materials (INCREASE) joint experimental program (JEEP) project that operates within the Nuclear Energy Agency (NEA)’s Framework for Irradiation Experiments (FIDES-II) program. The first objective of the INCREASE project is to design a shared capsule that can house a variety of in-core mechanical testing instrumentation for enabling smart irradiation experiments. The second objective is to collect in core stress relaxation data pertaining to high priority stainless steel (SS) materials under light water reactor conditions with target temperature of 340°C +/-20°C and a minimum neutron damage of 2 displacement per atom (dpa). The INCREASE project will be demonstrated in the Massachusetts Institute of Technology Nuclear Research Reactor (MITR).

36 MATERIALS SCIENCE↗

Alternative Analysis and Prioritization of Department of Energy “TBD” Materials with No Identified Disposition Pathway

The Department of Energy (DOE) complex manages a significant inventory of excess nuclear materials for which disposition pathways have not been identified, commonly referred to as "To Be Determined" (TBD) items. The Disposition Pathways Program, initiated in FY2018, provides a standardized framework for identifying viable disposition pathways for these materials. In 2023, the program undertook a comprehensive review and systematic analysis of the remaining TBD material groups, updating the assessment from the 2020 TBD Study using the 2022 fiscal year-end Nuclear Material Inventory Assessment (NMIA) as the primary data source. This effort aimed to utilize quantitative analysis to down-select from a wide range of potential disposition options and prioritize the remaining pathways to facilitate informed, risk-based decision-making for future programmatic funding and execution. This paper details the alternative analysis methodology used for screening and prioritization, highlighting the key criteria, ranking process, and resultant recommendations. The study successfully narrowed fifty-two potential disposition options down to nineteen, providing a focused path forward for addressing a longstanding challenge within the DOE complex.

Ramsey, Catherine [Savannah River National Laborat↗

Expandable Log Analyzing Framework

Prior to my internship, I was informed that a previous intern had built a tool to analyse MongoDB logs and look for invalid access attempts, which served as a great reference point for my project. I was initially tasked with expanding on her prototype and filling in the gaps such as integrating it with the main monitoring tool the lab uses. Eventually, the scope grew, expanding to support other databases and a growing collection of tools. I organized the framework around an observer pattern, meaning one point in the program sending updates to the rest of the framework. Every time a log was read and parsed, it was sent to be processed by the tools, using the type of event as a means to determine which tools should get a chance to act on the log. This decouples the tools from the log reader, making future updates and additions much easier. The framework processes MongoDB logs at ~135,000 entries per second and PostgreSQL logs at ~170,500 entries per second, accurately detecting anomalies such as slow queries and connections from unknown addresses. This framework serves to fill gaps in database monitoring tools currently implemented at the lab, such as tracking failed authentication for PostgreSQL and MongoDB which had very minimal or none before this framework. National labs such as Fermilab hold sensitive data and valuable computing resources, making them attractive targets. Monitoring intrusion attempts on databases is made much easier by this comprehensive monitoring suite.

Clark, Dylan [Unlisted, IL]↗

Expandable Log Analyzing Framework

Prior to my internship, I was informed that a previous intern had built a tool to analyse MongoDB logs and look for invalid access attempts, which served as a great reference point for my project. I was initially tasked with expanding on her prototype and filling in the gaps such as integrating it with the main monitoring tool the lab uses. Eventually, the scope grew, expanding to support other databases and a growing collection of tools. I organized the framework around an observer pattern, meaning one point in the program sending updates to the rest of the framework. Every time a log was read and parsed, it was sent to be processed by the tools, using the type of event as a means to determine which tools should get a chance to act on the log. This decouples the tools from the log reader, making future updates and additions much easier. The framework processes MongoDB logs at ~135,000 entries per second and PostgreSQL logs at ~170,500 entries per second, accurately detecting anomalies such as slow queries and connections from unknown addresses. This framework serves to fill gaps in database monitoring tools currently implemented at the lab, such as tracking failed authentication for PostgreSQL and MongoDB which had very minimal or none before this framework. National labs such as Fermilab hold sensitive data and valuable computing resources, making them attractive targets. Monitoring intrusion attempts on databases is made much easier by this comprehensive monitoring suite.

Clark, Dylan [Unlisted, IL]↗

Database-Agnostic Log Analysis and Monitoring Framework

Prior to my internship, I was informed that a previous intern had built a tool to analyse MongoDB logs and look for invalid access attempts, which served as a great reference point for my project. I was initially tasked with expanding on her prototype and filling in the gaps such as integrating it with the main monitoring tool the lab uses. Eventually, the scope grew, expanding to support other databases and a growing collection of tools. I organized the framework around an observer pattern, meaning one point in the program sending updates to the rest of the framework. Every time a log was read and parsed, it was sent to be processed by the tools, using the type of event as a means to determine which tools should get a chance to act on the log. This decouples the tools from the log reader, making future updates and additions much easier. The framework processes MongoDB logs at ~135,000 entries per second and PostgreSQL logs at ~170,500 entries per second, accurately detecting anomalies such as slow queries and connections from unknown addresses. This framework serves to fill gaps in database monitoring tools currently implemented at the lab, such as tracking failed authentication for PostgreSQL and MongoDB which had very minimal or none before this framework. National labs such as Fermilab hold sensitive data and valuable computing resources, making them attractive targets. Monitoring intrusion attempts on databases is made much easier by this comprehensive monitoring suite.

Clark, Dylan [Unlisted, US, IL; Fermilab]↗

Constellation Program: Lessons Learned: Executive Summary - Volume 1

This document (Volume I) provides an executive summary of the lessons learned from the Constellation Program. A companion Volume II provides more detailed analyses for those seeking further insight and information. In this volume, Section 1.0 introduces the approach in preparing and organizing the content to enable rapid assimilation of the lessons. Section 2.0 describes the contextual framework in which the Constellation Program was formulated and functioned that is necessary to understand most of the lessons. Context of a former program may seem irrelevant in the heady days of new program formulation. However, readers should take some time to understand the context. Many of the lessons would be different in a different context, so the reader should reflect on the similarities and differences in his or her current circumstances. Section 3.0 summarizes key findings developed from the significant lessons learned at the program level that appear in Section 4.0. Readers can use the key findings in Section 3.0 to peruse for particular topics, and will find more supporting detail and analyses in Section 4.0 in a topical format. Appendix A contains a white paper describing the Constellation Program formulation that may be of use to readers wanting more context or background information. The reader will no doubt recognize some very similar themes from previous lessons learned, blue-ribbon committee reviews, National Academy reviews, and advisory panel reviews for this and other large-scale human spaceflight programs; including Apollo, Space Shuttle, Shuttle/Mir, and the ISS. This could represent an inability to learn lessons from previous generations; however, it is more likely that similar challenges persist in the Agency structure and approach to program formulation, budget advocacy, and management. Perhaps the greatest value of these Constellation lessons learned can be found in viewing them in context with these previous efforts to guide and advise the Agency and its stakeholders.

Constellation Program↗

Ciel

Compiler optimizations can alter the numerical results of scientific computing applications. When numerical results differ significantly between compilers, optimization levels, and floating-point hardware, these numerical inconsistencies can impact programming productivity. Ciel is a framework that helps programmers identify locations in the source code that are affected by compiler optimizations in CPU and GPU code. Ciel uses a floating-point precision enhancement strategy, guided by a recursive bisection search algorithm with increasing search granularity, to identify the program expressions that induce numerical inconsistencies due to compiler optimizations.

Miao, Wenjun↗

Optimization Framework to Assess the Demand Response Capacity of a Water Distribution System

As large electricity consumers, water distribution system (WDS) pumping stations have the potential to become meaningful participants in demand response (DR) programs. The authors propose an optimization framework for assessing the DR capacity of a WDS and identifying the optimal bidding strategy for maximizing WDS revenue in the DR spot market. The proposed mixed integer linear programming (MILP) model overcomes computational constraints of previous DR optimization models by adopting a preprocessing procedure to minimize the number of binary variables and implementing a convex relaxation technique to linearize the hydraulic equations. The proposed MILP model also explicitly accounts for varying levels of risk tolerance of WDS operators by varying the recovery period over which pumping returns to business-as-usual operation. The optimization framework is implemented on a skeletonized 48-node WDS model that includes 7 pumps, 6 tanks, and 39 pipes. Using a simulated DR event and water consumption profile, the authors derive the optimal DR supply curves (i.e., compensation price versus load curtailment quantity) and revenue potential of the WDS under six scenarios for DR participation.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Introduction

Progress reported on principle NASA programs for the reduction of aircraft engine noise emphasizes the Quiet Engine Program. Considered are fan noise and performance, fan noise suppression, and jet noise reduction for a broad spectrum of airplanes including new subsonic airplanes, the older subsonic airplanes in service today, STOL airplanes of the future, and future supersonic transports. Noise reductions achieved in the framework of the Quiet Engine Program are demonstrated and future possible applications of low noise technology to airplanes are discussed.

Sanders, N. D.↗

Satellite observations of weather and climate

The SEASAT-A program is viewed as a new way to obtain atmospheric observations for weather and climatic studies in the framework of the Global Atmospheric Research Program (GARP). Total information derived from SEASAT-A sensor package provides a synoptic picture of the upper parts of the world's oceans as a prerequisite to the development of dynamic ocean models and combined ocean/atmospheric models for weather forecasting requirements.

Kellogg, W. W.↗

Developing CORBA-Based Distributed Scientific Applications from Legacy Fortran Programs

Recent progress in distributed object technology has enabled software applications to be developed and deployed easily such that objects or components can work together across the boundaries of the network, different operating systems, and different languages. A distributed object is not necessarily a complete application but rather a reusable, self-contained piece of software that co-operates with other objects in a plug-and-play fashion via a well-defined interface. The Common Object Request Broker Architecture (CORBA), a middleware standard defined by the Object Management Group (OMG), uses the Interface Definition Language (IDL) to specify such an interface for transparent communication between distributed objects. Since IDL can be mapped to any programming language, such as C++, Java, Smalltalk, etc., existing applications can be integrated into a new application and hence the tasks of code re-writing and software maintenance can be reduced. Many scientific applications in aerodynamics and solid mechanics are written in Fortran. Refitting these legacy Fortran codes with CORBA objects can increase the codes reusability. For example, scientists could link their scientific applications to vintage Fortran programs such as Partial Differential Equation(PDE) solvers in a plug-and-play fashion. Unfortunately, CORBA IDL to Fortran mapping has not been proposed and there seems to be no direct method of generating CORBA objects from Fortran without having to resort to manually writing C/C++ wrappers. In this paper, we present an efficient methodology to integrate Fortran legacy programs into a distributed object framework. Issues and strategies regarding the conversion and decomposition of Fortran codes into CORBA objects are discussed. The following diagram shows the conversion and decomposition mechanism we proposed. Our goal is to keep the Fortran codes unmodified. The conversion- aided tool takes the Fortran application program as input and helps programmers generate C/C++ header file and IDL file for wrapping the Fortran code. Programmers need to determine by themselves how to decompose the legacy application into several reusable components based on the cohesion and coupling factors among the functions and subroutines. However, programming effort still can be greatly reduced because function headings and types have been converted to C++ and IDL styles. Most Fortran applications use the COMMON block to facilitate the transfer of large amount of variables among several functions. The COMMON block plays the similar role of global variables used in C. In the CORBA-compliant programming environment, global variables can not be used to pass values between objects. One approach to dealing with this problem is to put the COMMON variables into the parameter list. We do not adopt this approach because it requires modification of the Fortran source code which violates our design consideration. Our approach is to extract the COMMON blocks and convert them into a structure-typed attribute in C++. Through attributes, each component can initialize the variables and return the computation result back to the client. We have tested successfully the proposed conversion methodology based on the f2c converter. Since f2c only translates Fortran to C, we still needed to edit the converted code to meet the C++ and IDL syntax. For example, C++/IDL requires a tag in the structure type, while C does not. In this paper, we identify the necessary changes to the f2c converter in order to directly generate the C++ header and the IDL file. Our future work is to add GUI interface to ease the decomposition task by simply dragging and dropping icons.

Sang, Janche↗

Automata-Based Verification of Temporal Properties on Running Programs

This paper presents an approach to checking a running program against its Linear Temporal Logic (LTL) specifications. LTL is a widely used logic for expressing properties of programs viewed as sets of executions. Our approach consists of translating LTL formulae to finite-state automata, which are used as observers of the program behavior. The translation algorithm we propose modifies standard LTL to Buchi automata conversion techniques to generate automata that check finite program traces. The algorithm has been implemented in a tool, which has been integrated with the generic JPaX framework for runtime analysis of Java programs.

Giannakopoulou, Dimitra↗