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DOE OSTI2023

Architectural development of an ST fusion device

A recent U.S. National Academy study recommended the development of a next step Sustained High Power Density (SHPD) facility within the U.S. as an intermediate step in designing and building a Pilot Plant device. Several papers have been written describing the physics, design and engineering scoping analysis performed in developing this machine design. This paper places emphasis on the continued evolution of the architectural development of past activities to meet the requirements of an ST fusion pilot plant and power plant. The current effort centers on meeting basic physics and component requirements in a machine design that improves the chance of achieving fission level availability (95%) within an arrangement that promotes design simplicity, offsite construction with on-site modular assembly. As a prelude to both the SHPD and Pilot Plant, a scoping design of a 500MWe Spherical Tokamak Advanced Reactor (STAR) has been defined to investigate design options and physics scenarios that can successfully meet physics performance, engineering requirements and economic conditions of an ST power plant. Following a successful physics/engineering assessment, the STAR Power Plant design will be downsized to meet the specifications established in the design of a near term ST Pilot Plant

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

NASA NTRS2016

A Cognitive Systems Engineering Approach to Developing HMI Requirements for New Technologies

This document examines the challenges inherent in designing and regulating to support human-automation interaction for new technologies that will deployed into complex systems. A key question for new technologies, is how work will be accomplished by the human and machine agents. This question has traditionally been framed as how functions should be allocated between humans and machines. Such framing misses the coordination and synchronization that is needed for the different human and machine roles in the system to accomplish their goals. Coordination and synchronization demands are driven by the underlying human-automation architecture of the new technology, which are typically not specified explicitly by the designers. The human machine interface (HMI) which is intended to facilitate human-machine interaction and cooperation, however, typically is defined explicitly and therefore serves as a proxy for human-automation cooperation requirements with respect to technical standards for technologies. Unfortunately, mismatches between the HMI and the coordination and synchronization demands of the underlying human-automation architecture, can lead to system breakdowns. A methodology is needed that both designers and regulators can utilize to evaluate the expected performance of a new technology given potential human-automation architectures. Three experiments were conducted to inform the minimum HMI requirements a detect and avoid system for unmanned aircraft systems (UAS). The results of the experiments provided empirical input to specific minimum operational performance standards that UAS manufacturers will have to meet in order to operate UAS in the National Airspace System (NAS). These studies represent a success story for how to objectively and systematically evaluate prototype technologies as part of the process for developing regulatory requirements. They also provide an opportunity to reflect on the lessons learned from a recent research effort in order to improve the methodology for defining technology requirements for regulators in the future. The biggest shortcoming of the presented research program was the absence of the explicit definition, generation and analysis of potential human-automation architectures. Failure to execute this step in the research process resulted in less efficient evaluation of the candidate prototypes technologies in addition to the complete absence of different approaches to human-automation cooperation. For example, all of the prototype technologies that were evaluated in the research program assumed a human-automation architecture that relied on serial processing from the automation to the human. While this type of human-automation architecture is typical across many different technologies and in many different domains, it ignores different architectures where humans and automation work in parallel. Defining potential human-automation architectures a priori also allows regulators to develop scenarios that will stress the performance boundaries of the technology during the evaluation phase. The importance of adding this step of generating and evaluating candidate human-automation architectures prior to formal empirical evaluation is discussed.

human systems integration↗

NASA NTRS2005

Parallelization of Lower-Upper Symmetric Gauss-Seidel Method for Chemically Reacting Flow

Development of technologies for exploration of the solar system has revived an interest in computational simulation of chemically reacting flows since planetary probe vehicles exhibit non-equilibrium phenomena during the atmospheric entry of a planet or a moon as well as the reentry to the Earth. Stability in combustion is essential for new propulsion systems. Numerical solution of real-gas flows often increases computational work by an order-of-magnitude compared to perfect gas flow partly because of the increased complexity of equations to solve. Recently, as part of Project Columbia, NASA has integrated a cluster of interconnected SGI Altix systems to provide a ten-fold increase in current supercomputing capacity that includes an SGI Origin system. Both the new and existing machines are based on cache coherent non-uniform memory access architecture. Lower-Upper Symmetric Gauss-Seidel (LU-SGS) relaxation method has been implemented into both perfect and real gas flow codes including Real-Gas Aerodynamic Simulator (RGAS). However, the vectorized RGAS code runs inefficiently on cache-based shared-memory machines such as SGI system. Parallelization of a Gauss-Seidel method is nontrivial due to its sequential nature. The LU-SGS method has been vectorized on an oblique plane in INS3D-LU code that has been one of the base codes for NAS Parallel benchmarks. The oblique plane has been called a hyperplane by computer scientists. It is straightforward to parallelize a Gauss-Seidel method by partitioning the hyperplanes once they are formed. Another way of parallelization is to schedule processors like a pipeline using software. Both hyperplane and pipeline methods have been implemented using openMP directives. The present paper reports the performance of the parallelized RGAS code on SGI Origin and Altix systems.

Yoon, Seokkwan↗

NASA NTRS1988

Kanerva's sparse distributed memory: An associative memory algorithm well-suited to the Connection Machine

The advent of the Connection Machine profoundly changes the world of supercomputers. The highly nontraditional architecture makes possible the exploration of algorithms that were impractical for standard Von Neumann architectures. Sparse distributed memory (SDM) is an example of such an algorithm. Sparse distributed memory is a particularly simple and elegant formulation for an associative memory. The foundations for sparse distributed memory are described, and some simple examples of using the memory are presented. The relationship of sparse distributed memory to three important computational systems is shown: random-access memory, neural networks, and the cerebellum of the brain. Finally, the implementation of the algorithm for sparse distributed memory on the Connection Machine is discussed.

Rogers, David↗

NASA NTRS2000

Using XML and Java for Astronomical Instrumentation Control

Ames, Troy↗

NASA NTRS2001

Using XML and Java Technologies for Astronomical Instrument Control

Traditionally, instrument command and control systems have been highly specialized, consisting mostly of custom code that is difficult to develop, maintain, and extend. Such solutions are initially very costly and are inflexible to subsequent engineering change requests, increasing software maintenance costs. Instrument description is too tightly coupled with details of implementation. NASA Goddard Space Flight Center, under the Instrument Remote Control (IRC) project, is developing a general and highly extensible framework that applies to any kind of instrument that can be controlled by a computer. The software architecture combines the platform independent processing capabilities of Java with the power of the Extensible Markup Language (XML), a human readable and machine understandable way to describe structured data. A key aspect of the object-oriented architecture is that the software is driven by an instrument description, written using the Instrument Markup Language (IML), a dialect of XML. IML is used to describe the command sets and command formats of the instrument, communication mechanisms, format of the data coming from the instrument, and characteristics of the graphical user interface to control and monitor the instrument. The IRC framework allows the users to define a data analysis pipeline which converts data coming out of the instrument. The data can be used in visualizations in order for the user to assess the data in real-time, if necessary. The data analysis pipeline algorithms can be supplied by the user in a variety of forms or programming languages. Although the current integration effort is targeted for the High-resolution Airborne Wideband Camera (HAWC) and the Submillimeter and Far Infrared Experiment (SAFIRE), first-light instruments of the Stratospheric Observatory for Infrared Astronomy (SOFIA), the framework is designed to be generic and extensible so that it can be applied to any instrument. Plans are underway to test the framework with other types of instruments, such as remote sensing earth science instruments.

Ames, Troy↗

DOE OSTI2025

Computational Power of Random Quantum Circuits in Arbitrary Geometries

Empirical evidence for a gap between the computational powers of classical and quantum computers has been provided by experiments that sample the output distributions of two-dimensional quantum circuits. Many attempts to close this gap have utilized classical simulations based on tensor network techniques, and their limitations shed light on the improvements to quantum hardware required to frustrate classical simulability. In particular, quantum computers having in excess of approximately 50 qubits are primarily vulnerable to classical simulation due to restrictions on their gate fidelity and their connectivity, the latter determining how many gates are required (and, therefore, how much infidelity is suffered) in generating highly entangled states. Here, we describe recent hardware upgrades to Quantinuum’s H2 quantum computer, enabling it to operate on up to 56 qubits with arbitrary connectivity and 99.843(5)% two-qubit gate fidelity. We define a class of circuits with random geometries that become hard to classically simulate in very low depth and implement them utilizing the flexible connectivity of H2. A careful analysis demonstrating the fast saturation of classical simulation complexity with depth indicates that H2 can yield data well beyond the reach of state-of-the art classical simulation methods at unprecedented fidelities. We find that the considerable difficulty of classically simulating H2 is likely limited only by qubit number, demonstrating the promise and scalability of the quantum charge-coupled device architecture as continued progress is made toward building larger machines. Published by the American Physical Society 2025

DeCross, M.↗

DOE OSTI2021

Data-driven physics-informed constitutive metamodeling of complex fluids: A multifidelity neural network (MFNN) framework

Not provided.

Mechanics↗

DOE OSTI2022

Smart Spectral Matching (SSM)

Smart Spectral Matching (SSM) catalogs spectroscopic data and, within the platform, investigates subtle attributes of spectral signatures from Raman and infrared spectroscopic data and enables statistical identification of connections between underlying structural units and spectroscopic information, particularly in fuel cycle materials that are amorphous or a mixture of several phases. Catalogs spectroscopic data, provides UIs for machine learning training either via JupyterHub for notebooks or domain scientist-specific views, machine learning and catalog REST API Python client libraries, and ability to identify features in files uploaded using pre-trained machine learning models. This is a "service-based" architecture with multiple applications represented by each repository in the group https://github.com/smart-spectral-matching

McDonnell, Marshall [Oak Ridge National Lab. (ORNL↗

DOE OSTI2024

CRADA Final Report: CRADA Number NFE-22-09330 with General Fusion

General Fusion is developing a magnetized target fusion (MTF) approach that involves compressing an initial magnetically confined plasma inside a cavity formed in liquid metal. This approach builds from concepts initially developed under the Linus program at the U.S. Naval Research Laboratory and combines it with advances from compact toroid experiment (CTX) and sustained spheromak plasma experiment (SSPX) in compact toroid plasmas and coaxial Marshall gun systems. Modeling the tokamak during compression is central to designing a successful MTF device. The plasma is formed by coaxial helicity injection in the General Fusion device. Immediately after formation, the plasma has a diverted tokamak configuration with a single null. As the wall moves inwards, the plasma is repelled from the conducting surface and driven inwards by currents induced by its magnetic field in the liquid metal wall. As the liquid metal closes (or bridges) the opening of the coaxial plasma injector, the magnetic field topology alters to remove the null. Due to this, the plasma moves from a diverted to a wall-limited configuration. The liquid metal liner continues to close in and change shape, reducing in radius by a factor of ten at the peak of plasma compression. A model of the MTF plasma must be able to handle this continually varying geometry, and to be predictive, it must faithfully include the real imperfections arising in the process. In this project, we pursued a Monte Carlo approach to closures for MHD by computing kinetic electron trajectories in an MHD plasma background from simulations of GF devices. This requires enhancing the capabilities of the KORC-T code for running large ensembles of kinetic trajectories by porting it to GPU architectures and enabling workflows for large ensembles on OLCF machines. With these capabilities, it is possible to produce a large library of kinetic calculations of electron orbits evolving in plasma configurations spanning the magnetic configurations and plasma density profiles, including non-axisymmetry, arising in the General Fusion’s existing PI3 spherical tokamak device. Using ensembles will capture particles passing a single point in space in a given magnetic configuration, and the entire dataset will cover a range of global magnetic field geometries. By sampling around many starting points, this dataset will capture the spatial dependence of the plasma parameters. From this large dataset, it is possible to produce a reduced model for the kinetic effects not captured in MHD.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

NASA NTRS1986

The Navier-Stokes computer

The Navier-Stokes computer (NSC) has been developed for solving problems in fluid mechanics involving complex flow simulations that require more speed and capacity than provided by current and proposed Class VI supercomputers. The machine is a parallel processing supercomputer with several new architectural elements which can be programmed to address a wide range of problems meeting the following criteria: (1) the problem is numerically intensive, and (2) the code makes use of long vectors. A simulation of two-dimensional nonsteady viscous flows is presented to illustrate the architecture, programming, and some of the capabilities of the NSC.

Nosenchuck, D. M.↗

NASA NTRS1987

First Annual Workshop on Space Operations Automation and Robotics (SOAR 87)

Several topics relative to automation and robotics technology are discussed. Automation of checkout, ground support, and logistics; automated software development; man-machine interfaces; neural networks; systems engineering and distributed/parallel processing architectures; and artificial intelligence/expert systems are among the topics covered.

Griffin, Sandy↗

NASA NTRS1992

Unsteady turbomachinery flow simulations on massively parallel architectures

The accurate numerical simulation of unsteady, three-dimensional viscous flow in turbomachines is computationally very intensive, requiring prohibitively large amounts of computer time on current vector supercomputers. In recent years, computer systems based on massively parallel architectures have been developed that offer the promise of meeting the computational power requirements of such large-scale simulations. However, a rethinking of existing algorithms and methodology is required in order to fully harness the computational power of such architectures. In this paper the capabilities of the Connection Machine (CM-2) in predicting unsteady flows in turbomachines are evaluated. The implementation on the CM-2 of an implicit, time-accurate, zonal algorithm for the Navier-Stokes equations in two dimensions is described. Programming issues and modifications made to the original algorithm (developed for vector, pipelined supercomputers) in order to improve performance on the CM-2 are outlined. Algorithm performance is evaluated and compared with a functionally equivalent code for the CRAY-YMP.

Madavan, N. K.↗

NASA NTRS2001

Web-Based Distributed Simulation of Aeronautical Propulsion System

An application was developed to allow users to run and view the Numerical Propulsion System Simulation (NPSS) engine simulations from web browsers. Simulations were performed on multiple INFORMATION POWER GRID (IPG) test beds. The Common Object Request Broker Architecture (CORBA) was used for brokering data exchange among machines and IPG/Globus for job scheduling and remote process invocation. Web server scripting was performed by JavaServer Pages (JSP). This application has proven to be an effective and efficient way to couple heterogeneous distributed components.

Zheng, Desheng↗

NASA NTRS2005

Introduction to System Health Engineering and Management in Aerospace

This paper provides a technical overview of Integrated System Health Engineering and Management (ISHEM). We define ISHEM as "the paper provides a techniques, and technologies used to design, analyze, build, verify, and operate a system to prevent faults and/or minimize their effects." This includes design and manufacturing techniques as well operational and managerial methods. ISHEM is not a "purely technical issue" as it also involves and must account for organizational, communicative, and cognitive f&ms of humans as social beings and as individuals. Thus the paper will discuss in more detail why all of these elements, h m the technical to the cognitive and social, are necessary to build dependable human-machine systems. The paper outlines a functional homework and architecture for ISHEM operations, describes the processes needed to implement ISHEM in the system life-cycle, and provides a theoretical framework to understand the relationship between the different aspects of the discipline. It then derives from these and the social and cognitive bases a set of design and operational principles for ISHEM.

Johnson, Stephen B.↗

NASA NTRS2004

Toward a Systematic Approach for Selection of NASA Technology Portfolios

There is an important need for a consistent analytical foundation supporting the selection and monitoring of R&D tasks that support new system concepts that enable future NASA missions. This capability should be applicable at various degrees of abstraction, depending upon whether one is interested in formulation, development, or operations. It should also be applicable to a single project, a program comprised of a group of projects, an enterprise typically including multiple programs, and the overall agency itself. Emphasis here is on technology selection and new initiatives, but the same approach can be generalized to other applications, dealing, for example, with new system architectures, risk reduction, and task allocation among humans and machines. The purpose of this paper is to describe one such approach, which is in its early stages of implementation within NASA programs, and to discuss several illustrative examples.

return on investment↗

DOE OSTI2026

CONTROL AND DATA ACQUISITION IN A CYBER-PHYSICAL MIDSTREAM TESTBED

This thesis presents the development of a laboratory-scale cyber–physical midstream pipeline testbed designed to address this gap and support research in industrial control systems security. The platform integrates pumps, valves, sensors, programmable logic controllers (PLCs), and a human–machine interface (HMI) to emulate the monitoring and control architecture of real pipeline operations. The physical process is implemented as a closed-loop liquid circulation system designed to replicate flow behavior characteristic of midstream pipeline infrastructure. The testbed enables real-time data acquisition of key process variables, including flow rate and pressure facilitating the generation of datasets representative of normal pipeline operation. A threat model encompassing common ICS attack vectors was developed, including sensor spoofing, command injection, false data injection, denial-of-service attacks, and relay manipulation. Multiple attack scenarios were implemented and evaluated to demonstrate how cyber intrusions targeting sensors, actuators, networks, and software propagate into measurable physical consequences in pipeline flow and pressure. The developed platform serves as a practical, cost-effective environment for experimentation, education, and future cybersecurity research in midstream pipeline systems.

42 ENGINEERING↗

DOE OSTI2025

Performance Evaluation of Vertical Federated Machine Learning Against Adversarial Threats on Wide-Area Control System: Preprint

Federated machine learning (FL) is gaining significant popularity to develop cybersecurity solutions in power grids because of its advanced capability to support decentralized data handing at local devices, its privacy preservation, and its low-bandwidth requirement. However, the evolving adversarial machine learning (AML) threats raise significant concerns for the cybersecurity of FL architectures. The FL-based split neural network (SplitNN) achieves high performance through the decentralized training of local neural network models while preserving data privacy across multiple entities. In this paper, we propose a methodology for evaluating the performance of a vertical FLbased anomaly detector against different types of AML attacks, including denial-of-service attacks, adversarial data injection attacks, and replay attacks on the trained local models deployed in the grid network. For a case study, we consider the modified IEEE 13-bus system, and we develop SplitNN-based binary and multiclass classification models to detect, locate, and identify different types of data integrity attacks on the volt-watt control with two pooling layers: maximum pooling and AvgPool. Our experimental results, computed through performance metrics, reveal that the severity of these AML attacks varies with the integrated pooling mechanism, the type of classification model, and the nature of the cyberattack. Further, the AML attacks negatively impacted the prediction time per sample for the pretrained SplitNN during the online testing.

adversarial threats↗