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

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At least 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

The Portals 4.3 Network Programming Interface

This report presents a specification for the Portals 4 network programming interface. Portals 4 is intended to allow scalable, high-performance network communication between nodes of a parallel computing system. Portals 4 is well suited to massively parallel processing and embedded systems. Portals 4 represents an adaption of the data movement layer developed for massively parallel processing platforms, such as the 4500-node Intel TeraFLOPS machine. Sandia's Cplant cluster project motivated the development of Version 3.0, which was later extended to Version 3.3 as part of the Cray Red Storm machine and XT line. Version 4 is targeted to the next generation of machines employing advanced network interface architectures that support enhanced offload capabilities.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

The Portals 4.1 Network Programming Interface

This report presents a specification for the Portals 4 networ k programming interface. Portals 4 is intended to allow scalable, high-performance network communication betwee n nodes of a parallel computing system. Portals 4 is well suited to massively parallel processing and embedded syste ms. Portals 4 represents an adaption of the data movement layer developed for massively parallel processing platfor ms, such as the 4500-node Intel TeraFLOPS machine. Sandia's Cplant cluster project motivated the development of Version 3.0, which was later extended to Version 3.3 as part of the Cray Red Storm machine and XT line. Version 4 is tar geted to the next generation of machines employing advanced network interface architectures that support enh anced offload capabilities.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Detecting Outliers in Network Transfers with Feature Extraction

Reliable file transfers are essential for successful science computations and experiments that need large complex data files to be moved across long distances. Networks use protocols such as TCP and UDP to support file transfers, and their performance degrades under packet losses and duplications, thereby adversely affecting science applications. Hence, scientists and engineers often monitor network statistics to find and repair network problems that cause such degradations.Outliers or anomalies can be detected using statistical and machine learning methods that highlight abnormal behaviors. However, without knowing what is normal, it is very difficult and subjective to determine the anomalies. In this paper, we investigate statistical and machine learning approaches to extract unknown or unsupervised features from TCP and perfSONAR data sets, with the aim to identify anomalies such as packet loss, duplication and retransmission sequencing that affect file transfer performance. Simple statistical and feature extraction methods (e.g. PCA) have shown that detecting anomalies is simpler if labeled data sets of normal behavior are available. While perfSONAR logs record losses,they do not detect duplications and reordering. We show that PCA applied to TCP statistics is able to determine abnormal behavior in the above cases. In particular, our results show that simple feature extraction techniques provide building blocks for more advanced network monitoring tools that can quickly flag anomalies using simple measurements, thereby helping to build confidence in file transfer reliability.

Rao, Nageswara S.↗
DOE OSTI2025

Abstraction hierarchy to define biofoundry workflows and operations for interoperable synthetic biology research and applications

Lack of standardization in biofoundries limits the scalability and efficiency of synthetic biology research. Here, we propose an abstraction hierarchy that organizes biofoundry activities into four interoperable levels: Project, Service/Capability, Workflow, and Unit Operation, effectively streamlining the Design‑Build‑Test‑Learn (DBTL) cycle. This framework enables more modular, flexible, and automated experimental workflows. It improves communication between researchers and systems, supports reproducibility, and facilitates better integration of software tools and artificial intelligence. Our approach lays the foundation for a globally interoperable biofoundry network, advancing collaborative synthetic biology and accelerating innovation in response to scientific and societal challenges.

Kim, Haseong↗
DOE OSTI2012

WHAT IS THE MOST PROMISING ELECTROMAGNETIC COUNTERPART OF A NEUTRON STAR BINARY MERGER?

The final inspiral of double neutron star and neutron-star-black-hole binaries are likely to be detected by advanced networks of ground-based gravitational wave (GW) interferometers. Maximizing the science returns from such a discovery will require the identification of an electromagnetic counterpart. Here we critically evaluate and compare several possible counterparts, including short-duration gamma-ray bursts (SGRBs), 'orphan' optical and radio afterglows, and day-long optical transients powered by the radioactive decay of heavy nuclei synthesized in the merger ejecta ('kilonovae'). We assess the promise of each counterpart in terms of four 'Cardinal Virtues': detectability, high fraction, identifiability, and positional accuracy. Taking into account the search strategy for typical error regions of tens of square degrees, we conclude that SGRBs are the most useful to confirm the cosmic origin of a few GW events, and to test the association with neutron star mergers. However, for the more ambitious goal of localizing and obtaining redshifts for a large sample of GW events, kilonovae are instead preferred. Off-axis optical afterglows are detectable for at most tens of percent of events, while radio afterglows are promising only for energetic relativistic ejecta in a high-density medium. Our main recommendations are: (1) an all-sky gamma-ray satellite is essential for temporal coincidence detections, and for GW searches of gamma-ray-triggered events; (2) the Large Synoptic Survey Telescope should adopt a one-day cadence follow-up strategy, ideally with 0.5 hr per pointing to cover GW error regions; and (3) radio searches should focus on the relativistic case, which requires observations for a few months.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2010

Why Does Flow Director Cause Packet Reordering?

Intel Ethernet Flow Director is an advanced network interface card (NIC) technology. It provides the benefits of parallel receive processing in multiprocessing environments and can automatically steer incoming network data to the same core on which its application process resides. However, our analysis and experiments show that Flow Director cannot guarantee in-order packet delivery in multiprocessing environments. Packet reordering causes various negative impacts. E.g., TCP performs poorly with severe packet reordering. In this paper, we use a simplified model to analyze why Flow Director can cause packet reordering. Our experiments verify our analysis.

Wu, Wenji↗
DOE OSTI2025

DISTRI: Distributed Multi-Facility HPC Simulator (DISTRI) v2.1

DISTRI is an advanced network simulator designed for multi-facility computational infrastructures with agentic behavior. It simulates HPC facilities where computational resources act as autonomous agents, making intelligent decisions about job scheduling, load balancing, and resource allocation. The simulator focuses on developing and testing decentralized algorithms that promote resilience and efficiency in multi-facility environments. Key Features: - Agentic Resource Behavior: Processors and DTNs act as autonomous agents with decision-making capabilities - Pheromone-Based Load Balancing: Decentralized load balancing inspired by ant colony optimization - Dual Topology Support: Mesh (normal operations) and Dumbell (network testing) topologies - Comprehensive TCP Simulation: Realistic TCP implementations with multiple congestion control algorithms - Failure Resilience Testing: Processor failure simulation with automatic job reassignment - Extensive Visualization: Detailed performance analysis and metrics collection - Research-Ready: Designed for algorithm development and benchmarking

Bez, Jean Luca [Lawrence Berkeley National Laborat↗
DOE OSTI2026

Resilience Measurement Framework For Post-deployment Artificial Intelligence (ai) Integrated Systems

Resilience is largely defined as the ability to adapt or recover from adverse conditions, stresses, attacks, or compromises on systems that use or are enabled by digital resources. In Artificial Intelligence Management and Research for Advanced Networked Testbed Hub (AMARANTH), resilience is measured in the amount of time it took from the beginning of a testing period for the model to reach predictions outside of the original 95% confidence interval or using the Kullback-Leibler (KL) divergence theorem, the Population Stability Index (PSI), and traditional methods such as root mean squared error (RMSE) threshold. Artificial Intelligence (AI) model drift is of significant concern when deploying AI-integrated systems into critical and/or secure environments. Drift can impact resilience of the AI-integrated system post-deployment and requires consistent maintenance and upkeep to ensure the model is accurate and precise. To quantify model drift and predict the point when a model's drift becomes unacceptable, we describe using Kullback-Leibler (KL) divergence, Population Stability Index (PSI) and/or confidence interval width estimations to determine the point of failure and time to failure of a model post-deployment. Through simple code functions, the KL-divergence, PSI, confidence interval, and root mean squared (RMSE) point of failures can be used to derive when a model needs to be maintained as well as the impact of adversarial action through statistical means.

Yockey, Patience [Idaho National Laboratory (INL),↗
DOE OSTI2014

DOE Advanced Scientific Advisory Committee (ASCAC): Workforce Subcommittee Letter

Simulation and computing are essential to much of the research conducted at the DOE national laboratories. Experts in the ASCR ¬relevant Computing Sciences, which encompass a range of disciplines including Computer Science, Applied Mathematics, Statistics and domain Computational Sciences, are an essential element of the workforce in nearly all of the DOE national laboratories. This report seeks to identify the gaps and challenges facing DOE with respect to this workforce. This letter is ASCAC’s response to the charge of February 19, 2014 to identify disciplines in which significantly greater emphasis in workforce training at the graduate or postdoctoral levels is necessary to address workforce gaps in current and future Office of Science mission needs.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2016

Quantum Graph Analysis

In recent years, advanced network analytics have become increasingly important to na- tional security with applications ranging from cyber security to detection and disruption of ter- rorist networks. While classical computing solutions have received considerable investment, the development of quantum algorithms to address problems, such as data mining of attributed relational graphs, is a largely unexplored space. Recent theoretical work has shown that quan- tum algorithms for graph analysis can be more efficient than their classical counterparts. Here, we have implemented a trapped-ion-based two-qubit quantum information proces- sor to address these goals. Building on Sandia's microfabricated silicon surface ion traps, we have designed, realized and characterized a quantum information processor using the hyperfine qubits encoded in two 171 Yb + ions. We have implemented single qubit gates using resonant microwave radiation and have employed Gate set tomography (GST) to characterize the quan- tum process. For the first time, we were able to prove that the quantum process surpasses the fault tolerance thresholds of some quantum codes by demonstrating a diamond norm distance of less than 1 . 9 x 10 [?] 4 . We used Raman transitions in order to manipulate the trapped ions' motion and realize two-qubit gates. We characterized the implemented motion sensitive and insensitive single qubit processes and achieved a maximal process infidelity of 6 . 5 x 10 [?] 5 . We implemented the two-qubit gate proposed by Molmer and Sorensen and achieved a fidelity of more than 97 . 7%.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2017

Development of a Repeatable Protocol to Uniformly Coat Internal Complex Geometries of Fine Featured 3D Printed Objects with Ceramic Material, including Determination of Viscosity Limits to Properly Coat Certain Pore Sizes

HEPA filters are commonly used in air filtration systems ranging in application from simple home systems to the more advanced networks used in research and development. Currently, these filters are most often composed of glass fibers with diameter on the order of one micron with polymer binders. These fibers, as well as the polymers used, are known to be fragile and can degrade or become extremely brittle with heat, severely limiting their use in high temperature applications. Ceramics are one promising alternative and can enhance the filtration capabilities compared to the current technology. Because ceramic materials are more thermally resistant and chemically stable, there is great interest in developing a repeatable protocol to uniformly coat fine featured polymer objects with ceramic material for use as a filter. The purpose of this experiment is to determine viscosity limits that are able to properly coat certain pore sizes in 3D printed objects, and additionally to characterize the coatings themselves. Latex paint was used as a surrogate because it is specifically designed to produce uniform coatings.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Route Views Project (CRADA Final Report)

The Route Views Project (“Project”) was founded by the Advanced Network Technology Center at the University of Oregon to allow internet users to view global Border Gateway Protocol routing information from the perspective of the other locations around the Internet. It is a significant tool used in global research and education networks. It is an open source tool, maintained by the core Route Views team and serves as an aid for ESnet and other scientific and education network peers to operate these networks in an effective and efficient manner.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

Security-Oriented and Load-Balancing Wireless Data Routing Game in the Integration of Advanced Metering Infrastructure Network in Smart Grid

Ensuring flexible and reliable data routing is indispensable for the integration of Advanced Metering Infrastructure (AMI) networks, we propose a secure-oriented and load-balancing wireless data routing scheme. A novel utility function is designed based on security routing scheme. Then, we model the interactive security-oriented routing strategy among meter data concentrators or smart grid meters as a mixed-strategy network formation game. Finally, such problem results in a stable probabilistic routing scheme with proposed distributed learning algorithm. One contributions is that we studied that different types of applications affect the routing selection strategy and the strategy tendency. Another contributions is that the chosen strategy of our mixed routing can adaptively to converge to a new mixed strategy Nash equilibrium (MSNE) during the learning process in the smart grid.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2016

Advance Reservation Access Control Using Software-Defined Networking and Tokens

Advance reservation systems allow users to reserve dedicated bandwidth connection resources from an advanced high-speed network. A common use case for such systems is data transfers in distributed science environments in which a user wants exclusive access to the reservation. However, current advance network reservation methods cannot ensure exclusive access of a network reservation to the specific flow for which the user made the reservation. We present here a novel network architecture that addresses this limitation and ensures that a reservation is used only by the intended flow. We achieve this by leveraging software-defined networking (SDN) and token-based authorization. We use SDN to orchestrate and automate the reservation of networking resources, end-to-end and across multiple administrativedomains, and tokens to create a strong binding between the user or application that requested the reservation and the flows provisioned by SDN.

Kettimuthu, R.↗
DOE OSTI2026

Robustness of the Ensemble Score Filter to the Type of Assimilated Observation Networks

Recent advances in data assimilation (DA) have focused on developing more flexible approaches that can better accommodate nonlinearities in models and observations. However, it remains unclear how the performance of these advanced methods depends on the observation network characteristics. In this study, we present initial experiments with the surface quasi‐geostrophic model, in which we compare a recently developed ensemble filter using score‐based diffusion models with the standard Local Ensemble Transform Kalman Filter (LETKF). Our results show that the analysis solutions respond differently to the number, spatial distribution, and nonlinear fraction of assimilated observations. We also find notable changes in the multiscale characteristics of the analysis errors. Given that standard DA techniques will eventually be replaced by more advanced methods, we hope this study sets the ground for future efforts to reassess the value of Earth observing systems in the context of newly emerging algorithms.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

An optimization framework for the network design of advanced district thermal energy systems

In this work, a topology optimization framework for district thermal energy systems is presented. The framework seeks to address the questions, for a given district, "What is the best subset of buildings to connect to a district thermal energy system, and by what network should they be connected, to minimize life cycle cost?" A particle swarm optimization approach is validated to address the selection of the subset of buildings, and a graph theory-based heuristic is validated for selection of the network topology for any candidate subset of buildings. The framework is applied to a prototypical urban district for illustrative purposes. Additionally, modeling of prototypical districts revealed reductions in source energy use intensity for heating and cooling of 21-25% through the use of advanced district energy systems relative to code-compliant, building level systems. The framework identifies solutions with life cycle cost values 14% to 72% lower than that of base case scenarios based on conventional design approaches, depending on the base case scenario selected. Analysis of the search space indicates that topology optimization facilitates reductions in life cycle cost, source energy use intensity, and carbon emissions.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2026

Neural-Network-Enhanced COTSIM: Advancing Predictive Capabilities for Fast DIII-D Simulations

Sustaining fusion reactions in tokamaks requires heating plasma to thermonuclear temperatures while maintaining confinement and stability. Neutral beam injection (NBI) provides heating, current drive, torque, and fueling, while electron cyclotron (EC) waves are widely used for heating and current drive; together, these actuators shape the plasma current, temperature, and density profiles. The control-oriented tokamak simulator (COTSIM), a predictive, control-oriented code, has been enhanced with neural-network surrogates for transport and sources. Turbulent transport is predicted by MMMnet—a neural-network version of the updated multimode model (MMM 9.0.10)—with significantly reduced computation time relative to MMM; neoclassical transport follows the Chang–Hinton model. NUBEAMnet, a surrogate of the Monte Carlo NUBEAM module, predicts beam-driven heating, current, and torque. EC heating and current drive use a control-oriented, empirically scaled source model; plasma resistivity follows the Spitzer formulation; bootstrap current uses the Sauter model. Equilibrium is computed using both prescribed and fixed-boundary solvers (FBSs), and the pedestal structure is modeled with an empirical pedestal model. For a representative DIII-D discharge, COTSIM predicts electron and ion temperature and safety-factor profiles in close agreement with TRANSP predictive and interpretive simulations while extending predictions through the pedestal region to the plasma edge (versus 80% of the minor radius in TRANSP). Furthermore, the equivalent COTSIM simulation runs in under 3 min compared to about 2 h for TRANSP, enabling rapid scenario planning, optimization of tokamak operation, and between-pulse control design.

Control-oriented tokamak simulator (COTSIM)↗
DOE OSTI2011

A Survey of Recent Advances in Transmission Network Switching

Optimal Transmission Switching for electric power networks is a research topic of great interest for both researchers and electric power engineers. Transmission switching is commonly considered a corrective mechanism tool for overloaded networks; however in recent years it has been sought as a means to reduce power loss in the network. Ultimately the objective of this analysis is to provide smart tools for power and economic dispatch planning, allowing utilities and engineers to utilize existing infrastructure as a means of automatic control. The optimization problem is a complex multi-objective search including criteria such as system power loss, equality/non-equality constraints, islanding management, and radial topology configuration in the case of distribution networks. Many optimization methods have been adopted for the transmission switching problem in past years using various heuristic search algorithms. The scope of methodology extends from tried and true methods such as simulated annealing to more modern methods like neural network optimization. Solution benchmarks under consideration commonly include solution state accuracy, computational burden and solution time. The objective of this presentation is to provide a comprehensive account of development in transmission switching methodologies. Benchmarking and testing strategies will be discussed as well as application of the Transmission Expansion Planning Tool in finding transmission switching solutions. Limited Discrepancy Search (LOS) and Probe Discrepancy Search (PDS) Algorithms are compared with more classic optimization strategies, as seen in defining literature and publications in this research field.

24 POWER TRANSMISSION AND DISTRIBUTION↗