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At least 1,153 records · Page 64

Risk Informed Timelines (RIT) v.1.0

Risk Informed Timelines (RIT) is a more modern and holistic method for understanding how access delay timelines are developed and utilized in physical security system evaluations. The software utilizes Bayesian methods to combine subject matter expert judgement and small performance test datasets in a consistent and defensible way. It allows a more holistic view of delay performance that provides distributions of task times and task success probabilities to account for tasks that, if failed, would result in failure of the attack. The RIT methodology is meant to enable security risk managers to begin the transition into more comprehensive delay timeline analysis. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525. SAND2021-8294 O

Noel, ToddG.↗

Nanoscopic Imaging of Self-Propelled Ultrasmall Catalytic Nanomotors

Ultrasmall nanomotors (<100 nm) are highly desirable nanomachines for their size-specific advantages over their larger counterparts in applications spanning nanomedicine, directed assembly, active sensing, and environmental remediation. While there are extensive studies on motors larger than 100 nm, the design and understanding of ultrasmall nanomotors have been scant due to the lack of high-resolution imaging of their propelled motions with orientation and shape details resolved. Here, we report the imaging of the propelled motions of catalytically powered ultrasmall nanomotors─hundreds of them─at the nanometer resolution using liquid-phase transmission electron microscopy. These nanomotors are Pt nanoparticles of asymmetric shapes (“tadpoles” and “boomerangs”), which are colloidally synthesized and observed to be fueled by the catalyzed decomposition of NaBH4 in solution. Statistical analysis of the orientation and position trajectories of fueled and unfueled motors, coupled with finite element simulation, reveals that the shape asymmetry alone is sufficient to induce local chemical concentration gradient and self-diffusiophoresis to act against random Brownian motion. Our work elucidates the colloidal design and fundamental forces involved in the motions of ultrasmall nanomotors, which hold promise as active nanomachines to perform tasks in confined environments such as drug delivery and chemical sensing.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Analysis of Noise Exposure Measurements Made Onboard the International Space Station

The International Space Station (ISS) is a unique workplace environment for U.S. astronauts and Russian cosmonauts to conduct research and live for a period of six months or more. Noise has been an enduring environmental physical hazard that has been a challenge for the U.S. space program since before the Apollo era. Noise exposure in ISS poses significant risks to the crewmembers, such as; hearing loss (temporary or permanent), possible disruptions of crew sleep, interference with speech intelligibility and communication, possible interference with crew task performance, and possible reduction in alarm audibility. Acoustic measurements are made aboard ISS and compared to requirements in order to assess the acoustic environment to which the crewmembers are exposed. The purpose of this paper is to describe in detail the noise exposure monitoring program as well as an assessment of the acoustic dosimeter data collected to date. The hardware currently being used for monitoring the noise exposure onboard ISS will be discussed. Acoustic data onboard ISS has been collected since the beginning of ISS (Increment 1, November 2000). Noise exposure data analysis will include acoustic dosimetry logged data from crew-worn during work and sleep periods and also fixed-location measurements from Increment 1 to present day. Noise exposure levels (8-, 16- and 24-hr), LEQ, will also be provided and discussed in this paper. Discussions related to hearing protection will also be included. Future directions and recommendations for the noise exposure monitoring program will be highlighted. This acoustic data is used to ensure a safe and healthy working and living environment for the crewmembers aboard the ISS.

Limardo, Jose G.↗

Analysis of Noise Exposure Measurements Acquired Onboard the International Space Station

The International Space Station (ISS) is a unique workplace environment for U.S. astronauts and Russian cosmonauts to conduct research and live for a period of six months or more. Noise has been an enduring environmental physical hazard that has been a challenge for the U.S. space program since before the Apollo era. Noise exposure in ISS poses significant risks to the crewmembers, such as; hearing loss (temporary or permanent), possible disruptions of crew sleep, interference with speech intelligibility and communication, possible interference with crew task performance, and possible reduction in alarm audibility. Acoustic measurements were made onboard ISS and compared to requirements in order to assess the acoustic environment to which the crewmembers are exposed. The purpose of this paper is to describe in detail the noise exposure monitoring program as well as an assessment of the acoustic dosimeter data collected to date. The hardware currently being used for monitoring the noise exposure onboard ISS will be discussed. Acoustic data onboard ISS has been collected since the beginning of ISS (Increment 1, November 2001). Noise exposure data analysis will include acoustic dosimetry logged data from crew-worn dosimeters during work and sleep periods and also fixed-location measurements from Increment 1 to present day. Noise exposure levels (8-, 16- and 24-hr), LEQ, will also be provided and discussed in this paper. Future directions and recommendations for the noise exposure monitoring program will be highlighted. This acoustic data is used to ensure a safe and healthy working and living environment for the crewmembers onboard the ISS.

Limardo, Jose G.↗

Novel Module Architecture for Lower CapEx and Improved Recyclability for c-Si PV Modules

Photovoltaic (PV) energy production is currently increasing at a rate at which recycling is becoming necessary. A novel module architecture has been demonstrated that has potential for high value recycling for c-Si PV. This architecture eliminates the vacuum lamination process and cross-linked en capsulants. Functioning prototypes of c-Si have been fabricated for stress testing in collaboration with NREL. These modules are being tested against traditionally manufactured modules. Based on preliminary results, this module architecture is a potentially viable solution for improving the manufacturing cost and recyclability of PV modules while retaining module performance.

computer architecture↗

Combined Heat and Power Systems Technology Development and Demonstration 370 kW High Efficiency Microturbine

The C370 Program was awarded in October 2010 with the ambitious goal of designing and testing the most electrically efficient recuperated microturbine engine at a rated power of less than 500 kW. The aggressive targets for electrical efficiency, emission regulatory compliance, and the estimated price point make the system state-of-the-art for microturbine engine systems. These goals will be met by designing a two stage microturbine engine identified as the low pressure spool and high pressure spool that are based on derivative hardware of Capstone’s current commercially available engines. The development and testing of the engine occurred in two phases. Phase I focused on developing a higher power and more efficient engine, that would become the low pressure spool which is based on Capstone’s C200 (200kW) engine architecture. Phase II integrated the low pressure spool created in Phase I with the high pressure spool, which is based on Capstone’s C65 (65 kW) commercially available engine. Integration of the engines, based on preliminary research, would allow the dual spool engine to provide electrical power in excess of 370 kW, with electrical efficiency approaching 42%. If both of these targets were met coupled with the overall CHP target of 85% total combined heating and electrical efficiency California Air Resources Board (CARB) level emissions, and a price target of $600 per kW, the system would represent a step change in the currently available commercial generation technology. Phase I of the C370 program required the development of the C370 low pressure spool. The goal was to increase the C200 engine power by a minimum of 25% — 250 kW — and efficiency from 32% to 37%. These increases in the C200 engine output were imperative to meet the power requirements of the engine when both spools were integrated. An additional benefit of designing and testing the C370 low pressure spool was the possibility of developing a stand-alone product for possible commercialization. The low pressure spool design activity focused on an aeropath derivative of the current C200 engine. The aeropath derivative included changes to the compressor section —compressor and inducer — and to the turbine nozzle. The increased power also necessitated a larger, more powerful generator and generator controller to support the increased power requirements. These two major design changes were completed by utilizing both advanced 3D modeling and computational fluid dynamics modelling. After design, modeling, and analysis, the decision was made to acquire and integrate the components for testing. The second task of Phase I was to integrate and test the components of the low pressure spool to validate power and efficiency. Acquisition of the components for the low pressure spool was completed utilizing Capstone’s current supplier base. Utilization of Capstone’s supply base for integration of the test article would allow — if the decision was made —expedited commercialization of the product. After integration of the engine components, the engine was tested and evaluated for performance and emissions. Test data analysis confirmed that the engine met all power and efficiency requirements and did so while maintaining CARB level emissions. The emissions were met without the use of any post processing or catalyst. After testing was completed, the DOE authorized — via a milestone review — proceeding to Phase II: the development of the integrated C370 engine. The C370 high pressure spool design activity required significant changes to the C65 engine architecture. The engine required a high power density generator, completely redesigned compressor stage, turbine section, recuperator, controls architecture, and intercooler stage asThe two most critical design challenges were the turbine section (the nozzle and turbine) and the controls architecture. The design and analysis of all of the components was completed and integrated into a system model. The system model — after numerous iterations — indicated that, once integrated, the engine will meet or exceed all system requirements. Unfortunately, the turbine section’s life requirements remain a technical challenge and will require continued refinement of the bi-metallic turbine wheel design and manufacturing approach to meet the life requirement at theses high temperatures. The current controls architecture requires substantial effort to develop a system capable of handling the high-speed, near real-time controls requirement, but it was determined not to be a technical roadblock for the project. The C370 Program has been a significant effort with state-of-the-art technical targets. The targets have pushed Capstone’s designers to the limits of current technology. The program has been fortunate to see many successes: the successful testing of the low pressure spool (C250), the development of new material processes, and the implementation of new design practices. The technology and practices learned during the program will be utilized in Capstone’s current product lines and future products. The C370 Program has been a resounding success on many fronts for the DOE and for Capstone.

none↗

Illuminating the Material World: Autonomous Microscopy to Understand Order, Disorder, and Everything In Between

Artificial intelligence (AI) holds immense promise for revolutionizing microscopy, yet its widespread adoption has been hindered by challenges ranging from user inexperience to limited model transferability and difficulties in operationalizing machine learning. This presentation showcases our approach to developing practical autonomy for materials discovery, aiming to accelerate the integration of AI into everyday microscopy workflows. As shown in Fig. 1, I will focus on three key areas: understanding order-disorder transitions, quantifying point defects, and achieving truly device-scale microscopy. First, I will demonstrate the power of multi-modal knowledge graphs for integrating diverse microscopy data. By combining imaging, spectroscopy, and diffraction data, these graphs provide a holistic view of material behavior, capturing the intricate relationships between different modalities [1,2]. I will present a case study on how these models illuminate the structural and chemical changes associated with irradiation in oxide thin films, revealing critical insights for designing materials for extreme environments like spaceflight and nuclear energy. Specifically, I will show how multi-modal analysis clarifies the evolution of order-disorder transitions under irradiation, a key factor influencing material performance in these applications. Next, I will address the challenge of quantifying point defects in 2D materials. We demonstrate the application of computer vision and transfer learning to accurately identify and classify various defect types, such as vacancies and substitutional atoms, and to quantify their concentrations. This information is crucial for understanding and tailoring the properties of 2D materials for applications in electronics, optoelectronics, and catalysis. For example, I will show how our models can characterize the topological distribution of point defects in MXene transition metal carbides, providing valuable insights for optimizing their performance in energy storage and separation science. Finally, I will discuss our progress toward autonomous device-scale microscopy [3,4]. We are fundamentally redesigning electron microscopes around the principles of machine reasoning, enabling automation beyond basic tasks like sample navigation and data acquisition to include sophisticated experimental design. This approach paves the way for truly reproducible and massively scaled analysis campaigns. I will emphasize the importance of autonomous microscopy platforms for high-throughput materials discovery and characterization, facilitating the rapid screening of materials for a broad range of applications and accelerating the development of next-generation technologies.

36 MATERIALS SCIENCE↗

Managed Development Environment Successes for MSFC's VIPA Team

This paper outlines the best practices of the Vehicle Design Team for VIPA. VIPA is the Vehicle Integrated Performance Analysis Team at MSFC. This team was created to reconnect the individual engineering disciplines to be able to perform system level technical assessments in support of program decisions. The functions of the VIPA Vehicle Design (VVD) discipline team are to maintain the controlled reference geometry and provide linked, simplified geometry for each of the other discipline analyses. The core of the VVD work, and the approach for VVD s first task of controlling the reference geometry, involves systems engineering, top-down, layout-based CAD modeling within a Product Data Manager (PDM) development environment. The topdown approach allcws for simple contrnl of very large, integrated assemblies and greatly enhances the ability to generate trade configurations and reuse data. The second W D task, model simplification for analysis, is handled within the managed environment through application of the master model concept. In this approach, there is a single controlling, or master, product definition dataset. Connected to this master model are reference datasets with live geometric and expression links. The referenced models can be for drawings, manufacturing, visualization, embedded analysis, or analysis simplification. A discussion of web based interaction, including visualization, between the design and other disciplines is included. Demonstrated examples are cited, including the Space Launch Initiative development cycle, the Saturn V systems integration and verification cycle, an Orbital Space Plane study, and NASA Exploration Office studies of Shuttle derived and clean sheet launch vehicles. The VIPA Team has brought an immense amount of detailed data to bear on program issues. A central piece of that success has been the Managed Development Environment and the VVD Team approach to modeling.

Finckenor, Jeff↗

Extending the Roofline Model for Asynchronous Many-Task Runtimes

New architectural trends and extreme scale parallelism challenge the efficient mapping of applications to large scale and emerging systems. Fine-grained Asynchronous Manytask Runtimes (AMR) offer a unique flexibility to hide the varying latencies of contentious operations, and facilitate the effective exploitation of abundant resources. By decomposing work into smaller asynchronous chunks, the impact of unpredictable operations can be mitigated through a tighter overlapping of tasks. Unfortunately, the cost of this decomposition comes at a potentially steep price in the form of runtime overhead which can at times rival the cost of the computation itself. This leads to the question, how large should a task be? A common practice for application developers is to experimentally determine the granularity of a task after a code has been parallelized. Instead, we propose a new methodology based on an extended Roofline model to provide practical upper bounds on the throughput performance of an application. First, we extend the Roofline model to support not only latency hiding analysis, but also a multidimensional amortized analysis. By combining this new methodology with a serial application and an AMR implementation, we can predict the worst case runtime overhead attribution of individual runtime features prior to the development of parallel code. Thus, this runtimecentric methodology can provide a vehicle for application/runtime codesign by providing a comprehensive bottleneck analysis based on existing runtime features.

Suetterlein, Joshua D.↗

Driving Next-Generation Workflows from the Data Plane

We observe the emergence of a new generation of scientific workflows that process data produced at a sustained rate by scientific instruments and large scale numerical simulations. This data is consumed by multiple analysis, visualization, or Machine Learning components not only to enable inference and justify the scientific program, but also to monitor and steer the evolution of these experiments. In such workflows, moving intermediate data efficiently is key to performance, more than efficiently scheduling computational tasks. However, most traditional workflow management systems focus on optimizing task scheduling and then deal with data management, assuming a “move little, compute for long” model, which makes them unfit to the efficient management of this new generation of workflows. Therefore, we advocate for a new way to manage scientific workflows. We propose to consider an efficiently and independently managed data plane that can store and stream data. Workflows compute components, in the application plane can then interact with the data plane, abstracted from complexities of data management. Then, the role of a workflow management system would become that of a control plane that allows users to connect services together to execute the workflow and manages connections between the application and data planes. In this position paper, we characterize several next-generation workflow motifs and describe how their interaction with the data plane is a challenge to traditional workflow management systems. Then, we express a set of requirements that a workflow management system should meet to efficiently manage next-generation workflows at different scales. Based on these requirements, we expose our vision of driving next-generation workflows from the data plane and list remaining open challenges.

Suter, Fred↗

ASCENDS: Advanced data SCiENce toolkit for Non-Data Scientists

Recently, advances in machine learning and artificial intelligence have been playing more and more critical roles in a wide range of areas. For the last several years, industries have shown that how learning from data, identifying patterns and making decisions with minimal human intervention can be extremely useful to their business (e.g., image classification, recommending a product to a customer, finding friends in a social network, predicting customers actions, etc.). These success stories have been motivating scientists who study physics, chemistry, materials, medicine, and many other subjects, to explore a new pathway of utilizing machine learning techniques like regression and classification for their scientific activities. However, most existing machine learning tools, systems, and methodologies have been developed for programming experts but not for scientists (or any users) who have no or little knowledge of programming. ASCENDS is a toolkit that is developed to assist scientists (or any persons) who want to use their data for machine learning tasks, more specifically, correlation analysis, regression, and classification. ASCENDS does not require programming skills. Instead, it provides a set of simple but powerful CLI (Command Line Interface) and GUI (Graphic User Interface) tools for non-data scientists to be able to intuitively perform advanced data analysis and machine learning techniques. ASCENDS has been implemented by wrapping around opensource software including Keras, TensorFlow, and scikit-learn.

97 MATHEMATICS AND COMPUTING↗

Low-pressure

This final technical progress report describes work conducted by Membrane Technology and Research, Inc. (MTR) for the Department of Energy (DOE NETL) on development of low-pressure membrane contactors for carbon dioxide (CO 2 ) capture from power plant flue gas (award number DE-FE0007553). The work was conducted from October 1, 2011 through September 30, 2014. The overall goal of this three-year project was to build and operate a prototype 500 m 2 low-pressure sweep membrane module specifically designed to separate CO 2 from coal-fired power plant flue gas. MTR was assisted in this project by a research group at the University of Toledo, which contributed to the computational fluid dynamics (CFD) analysis of module design and process simulation. This report details the work conducted to develop a new type of membrane contactor specifically designed for the high-gas-flow, low-pressure, countercurrent sweep operation required for affordable membrane-based CO 2 capture at coal power plants. Work for this project included module development and testing, design and assembly of a large membrane module test unit at MTR, CFD comparative analysis of cross-flow, countercurrent, and novel partial-countercurrent sweep membrane module designs, CFD analysis of membrane spacers, design and fabrication of a 500 m 2 membrane module skid for field tests, a detailed performance and cost analysis of the MTR CO 2 capture process with low-pressure sweep modules, and a process design analysis of a membrane-hybrid separation process for CO 2 removal from coal-fired flue gas. Key results for each major task are discussed in the report.

42 ENGINEERING↗

User data management

The primary objective is to identify, develop, and demonstrate key data management technologies to support user access to Space Station data. To accomplish this objective, there are several technical challenges which must be addressed. The first is how to provide routine customer access to high volume, dynamic and distributed data bases. This access will encompass the functions of mission and payload planning and operations, data processing and analysis, and data archive and distribution. Secondly, there must be some analysis of architectures for handling high volume data streams like those expected from the Space Station. This analysis will examine the use of packetized versus non-packetized data formats, modular expansion capabilities, real-time versus non-real-time data processing, and the interfaces and architecture required to support telescience operations. The task will also determine benchmarks of performance capabilities for technology operations, such as varied data base structures, data access procedures, distributed data base design, and data base machines. Information is provided here in outline form.

Source record↗

The implementation and use of Ada on distributed systems with high reliability requirements

The use and implementation of Ada were investigated in distributed environments in which reliability is the primary concern. In particular, the focus was on the possibility that a distributed system may be programmed entirely in Ada so that the individual tasks of the system are unconcerned with which processors are being executed, and that failures may occur in the software and underlying hardware. A secondary interest is in the performance of Ada systems and how that performance can be gauged reliably. Primary activities included: analysis of the original approach to recovery in distributed Ada programs using the Advanced Transport Operating System (ATOPS) example; review and assessment of the original approach which was found to be capable of improvement; development of a refined approach to recovery that was applied to the ATOPS example; and design and development of a performance assessment scheme for Ada programs based on a flexible user-driven benchmarking system.

Knight, J. C.↗

F-14 modeling study

This study explored application of a closed loop pilot/simulator model to the analysis of some simulator fidelity issues. The model was applied to two data bases: (1) a NASA ground based simulation of an air-to-air tracking task in which nonvisual cueing devices were explored, and (2) a ground based and inflight study performed by the Calspan Corporation to explore the effects of simulator delay on attitude tracking performance. The model predicted the major performance trends obtained in both studies. A combined analytical and experimental procedure for exploring simulator fidelity issues is outlined.

Levison, William H.↗

Compiling global name-space programs for distributed execution

Distributed memory machines do not provide hardware support for a global address space. Thus programmers are forced to partition the data across the memories of the architecture and use explicit message passing to communicate data between processors. The compiler support required to allow programmers to express their algorithms using a global name-space is examined. A general method is presented for analysis of a high level source program and along with its translation to a set of independently executing tasks communicating via messages. If the compiler has enough information, this translation can be carried out at compile-time. Otherwise run-time code is generated to implement the required data movement. The analysis required in both situations is described and the performance of the generated code on the Intel iPSC/2 is presented.

Koelbel, Charles↗

An analysis of the loads applied to a heavy Space Station rack during translation and rotation tasks

To prepare for Space Station Alpha's on-orbit assembly, maintenance, and resupply, NASA requires information about the crew members' ability to move heavy masses on orbit. Ease of movement in microgravity and orbiter stay time constraints may change the Space Station equipment and outfitting design requirements. Therefore, the time and effort required to perform a particular task and how and where the forces and torque should be applied become critical in evaluating the design effort. Thus, the three main objectives of this investigation were to: (1) quantify variables such as force and torque as they relate to heavy mass handling techniques; (2) predict the time required to perform heavy mass handling tasks; and (3) note any differences between males and females in their ability to manipulate a heavy mass.

Stoycos, Lara E.↗

Vector quantizer designs for joint compression and terrain categorization of multispectral imagery

Two vector quantizer designs for compression of multispectral imagery and their impact on terrain categorization performance are evaluated. The mean-squared error (MSE) and classification performance of the two quantizers are compared, and it is shown that a simple two-stage design minimizing MSE subject to a constraint on classification performance has a significantly better classification performance than a standard MSE-based tree-structured vector quantizer followed by maximum likelihood classification. This improvement in classification performance is obtained with minimal loss in MSE performance. The results show that it is advantageous to tailor compression algorithm designs to the required data exploitation tasks. Applications of joint compression/classification include compression for the archival or transmission of Landsat imagery that is later used for land utility surveys and/or radiometric analysis.

Gorman, John D.↗