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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

VISILIENCE: An Interactive Visualization Framework for Resilience Analysis using Control-Flow Graph

Soft errors have become one of the major concerns for the error resilience of HPC applications, as those errors can cause HPC applications to generate serious outcomes such as Silent Data Corruptions (SDCs). A large body of approaches has been proposed to analyze the resilience of HPC applications. However, existing studies rarely address the challenges of the analysis result perception. Specifically, resilience analysis techniques often produce a massive volume of unstructured data, making it difficult for programmers to conduct the resilience analysis due to non-intuitive raw data. Furthermore, different analysis models produce diverse results with multiple levels of details, which may create hurdles to compare and explore the resilience of HPC program execution. To this end, we present VISILIENCE, an interactive VISual resILIENCE analysis framework to allow programmers to facilitate the resilience analysis of HPC applications. In particular, VISILIENCE leverages an effective visualization approach Control Flow Graph (CFG) to present a function execution. In addition, three widely-used models for resilience analysis (i.e., Y-Branch, IPAS, and TRIDENT) are seamlessly embedded into the framework for resilience analysis and result comparison. Multiple case studies have been conducted to demonstrate the effectiveness of our proposed framework VISILIENCE.

Jiang, Hailong↗
DOE OSTI2019

Efficient Modeling of HIL Multi-Grid System for Scalability & Concurrency in CPS Security Testbed

Cyber-event-triggered power grid blackout compels utility operators to intensify cyber-aware and physics-constrained recovery and restoration process. Recently, coordinated cyber attacks on the Ukrainian grid witnessed such a cyber-event-triggered power system blackout. Various cyber-physical system (CPS) testbeds have attempted with multitude designs to analyze such interdependent events and evaluate remedy measures. However, resource constraints and modular integration designs have been significant barriers while modeling large-scale grid models (scalability) and multi-grid isolated models (concurrency) under a single real-time execution environment for the hardware-in-the-loop (HIL) CPS security testbeds. This paper proposes a meticulous design and effective modeling for simulating large-scale grid models and multi-grid isolated models in a HIL realtime digital simulator environment integrated with industry-grade hardware and software systems. We have used our existing HIL CPS security testbed to demonstrate scalability by the realtime performance of a Texas-2000 bus US synthetic grid model and concurrency by the real-time performance of simultaneous ten IEEE-39 bus grid models and an IEEE-118 bus grid model. The experiments demonstrated significant results by 100% realtime performance with zero overruns, low latency while receiving and executing control signals from SEL Relays via IEC-61850 protocol and low latency while computing and transmitting grid data streams including stability measures via IEEE C37.118 synchrophasor data protocol to SEL Phasor Data Concentrators.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS1970

An experiment with interactive planning models

Experiments on decision making in planning problems are described. Executives were tested in dealing with capital investments and competitive pricing decisions under conditions of uncertainty. A software package, the interactive risk analysis model system, was developed, and two controlled experiments were conducted. It is concluded that planning models can aid management, and predicted uses of the models are as a central tool, as an educational tool, to improve consistency in decision making, to improve communications, and as a tool for consensus decision making.

Beville, J.↗
NASA NTRS1993

ESSOPE: Towards S/C operations with reactive schedule planning

The ESSOPE is a prototype front-end tool running on a Sun workstation and interfacing to ESOC's MSSS spacecraft control system for the exchange of telecommand requests (to MSSS) and telemetry reports (from MSSS). ESSOPE combines an operations Planner-Scheduler, with a Schedule Execution Control function. Using an internal 'model' of the spacecraft, the Planner generates a schedule based on utilization requests for a variety of payload services by a community of Olympus users, and incorporating certain housekeeping operations. Conflicts based on operational constraints are automatically resolved, by employing one of several available strategies. The schedule is passed to the execution function which drives MSSS to perform it. When the schedule can no longer be met, either because the operator interferes (by delays or changes of requirements), or because ESSOPE has recognized some spacecraft anomalies, the Planner produces a modified schedule maintaining the on-going procedures as far as consistent with the new constraints or requirements.

Wheadon, J.↗
NASA NTRS2014

Development and Implementation of Dynamic Scripts to Execute Cycled WRF/GSI Forecasts

Automating the coupling of data assimilation (DA) and modeling systems is a unique challenge in the numerical weather prediction (NWP) research community. In recent years, the Development Testbed Center (DTC) has released well-documented tools such as the Weather Research and Forecasting (WRF) model and the Gridpoint Statistical Interpolation (GSI) DA system that can be easily downloaded, installed, and run by researchers on their local systems. However, developing a coupled system in which the various preprocessing, DA, model, and postprocessing capabilities are all integrated can be labor-intensive if one has little experience with any of these individual systems. Additionally, operational modeling entities generally have specific coupling methodologies that can take time to understand and develop code to implement properly. To better enable collaborating researchers to perform modeling and DA experiments with GSI, the Short-term Prediction Research and Transition (SPoRT) Center has developed a set of Perl scripts that couple GSI and WRF in a cycling methodology consistent with the use of real-time, regional observation data from the National Centers for Environmental Prediction (NCEP)/Environmental Modeling Center (EMC). Because Perl is open source, the code can be easily downloaded and executed regardless of the user's native shell environment. This paper will provide a description of this open-source code and descriptions of a number of the use cases that have been performed by SPoRT collaborators using the scripts on different computing systems.

Zavodsky, Bradley↗
NASA NTRS1990

Strategies for concurrent processing of complex algorithms in data driven architectures

Performance modeling and performance enhancement for periodic execution of large-grain, decision-free algorithms in data flow architectures are discussed. Applications include real-time implementation of control and signal processing algorithms where performance is required to be highly predictable. The mapping of algorithms onto the specified class of data flow architectures is realized by a marked graph model called algorithm to architecture mapping model (ATAMM). Performance measures and bounds are established. Algorithm transformation techniques are identified for performance enhancement and reduction of resource (computing element) requirements. A systematic design procedure is described for generating operating conditions for predictable performance both with and without resource constraints. An ATAMM simulator is used to test and validate the performance prediction by the design procedure. Experiments on a three resource testbed provide verification of the ATAMM model and the design procedure.

Som, Sukhamoy↗
NASA NTRS2013

ION Configuration Editor

The configuration of ION (Inter - planetary Overlay Network) network nodes is a manual task that is complex, time-consuming, and error-prone. This program seeks to accelerate this job and produce reliable configurations. The ION Configuration Editor is a model-based smart editor based on Eclipse Modeling Framework technology. An ION network designer uses this Eclipse-based GUI to construct a data model of the complete target network and then generate configurations. The data model is captured in an XML file. Intrinsic editor features aid in achieving model correctness, such as field fill-in, type-checking, lists of valid values, and suitable default values. Additionally, an explicit "validation" feature executes custom rules to catch more subtle model errors. A "survey" feature provides a set of reports providing an overview of the entire network, enabling a quick assessment of the model s completeness and correctness. The "configuration" feature produces the main final result, a complete set of ION configuration files (eight distinct file types) for each ION node in the network.

Borgen, Richard L.↗
NASA NTRS1989

Performance impacts of look-ahead execution in the conversation scheme

The look-ahead execution approach, which allows participant processes that exist early to exit from a conversation before other participants finish their conversation activities, is presented here as a fundamental approach to reducing the synchronization overhead. Queuing network models are developed for systems operating under the basic conversation execution scheme and systems operating under the look-ahead execution scheme. Based on the models, various performance indicators such as the system throughput, the average number of processors idling inside a conversation due to the synchronization required, and the average time spent in conversation are evaluated numerically for different application environments. The results provide insights into the extent of benefits provided by the look-ahead execution approach.

Kim, K. H.↗
NASA NTRS2005

The SMART Theory and Modeling Team: An Integrated Element of Mission Development and Science Analysis

When targeting physical understanding of space plasmas, our focus is gradually shifting away from discovery-type investigations to missions and studies that address our basic understanding of processes we know to be important. For these studies, theory and models provide physical predictions that need to be verified or falsified by empirical evidence. Within this paradigm, a tight integration between theory, modeling, and space flight mission design and execution is essential. NASA's Magnetospheric MultiScale (MMS) mission is a pathfinder in this new era of space research. The prime objective of MMS is to understand magnetic reconnection, arguably the most fundamental of plasma processes. In particular, MMS targets the microphysical processes, which permit magnetic reconnection to operate in the collisionless plasmas that permeate space and astrophysical systems. More specifically, MMS will provide closure to such elemental questions as how particles become demagnetized in the reconnection diffusion region, which effects determine the reconnection rate, and how reconnection is coupled to environmental conditions such as magnetic shear angles. Solutions to these problems have remained elusive in past and present spacecraft missions primarily due to instrumental limitations - yet they are fundamental to the large-scale dynamics of collisionless plasmas. Owing to the lack of measurements, most of our present knowledge of these processes is based on results from modern theory and modeling studies of the reconnection process. Proper design and execution of a mission targeting magnetic reconnection should include this knowledge and have to ensure that all relevant scales and effects can be resolved by mission measurements. The SMART mission has responded to this need through a tight integration between instrument and theory and modeling teams. Input from theory and modeling is fed into all aspects of science mission design, and theory and modeling activities are tailored to SMART needs during mission development and science analysis. In this presentation, we will present an overview of SMART theory and modeling team activities. In particular, we will provide examples of science objectives derived from state-of-the art models, and of recent research results that continue to be utilized in SMART mission development.

Hesse, Michael↗
NASA NTRS1988

Modeling and optimum time performance for concurrent processing

The development of a new graph theoretic model for describing the relation between a decomposed algorithm and its execution in a data flow environment is presented. Called ATAMM, the model consists of a set of Petri net marked graphs useful for representing decision-free algorithms having large-grained, computationally complex primitive operations. Performance time measures which determine computing speed and throughput capacity are defined, and the ATAMM model is used to develop lower bounds for these times. A concurrent processing operating strategy for achieving optimum time performance is presented and illustrated by example.

Mielke, Roland R.↗
DOE OSTI2023

High-Level Synthesis of Irregular Applications: A Case Study on Influence Maximization

The Influence Maximization problem is the problem of identifying a small cohort of actors from a broader population that, when initially activated in a diffusion process, are expected to result in a large number of activations in the population. While the problem is known to be NP-hard, several approximation algorithms have been devised by leveraging its submodular structure. While these algorithms are theoretically efficient, they are computationally very expensive in practice. This work advances the current state-of-the-art parallelization scheme for the IMM algorithm by devising the adoption of custom hardware accelerators implemented on FPGAs by leveraging High Level Synthesis from OpenCL. We study the performance of our proposed approach by exploring optimizations tailored at improving the parallel efficiency of the accelerators and highlight their effects and limitations in accelerating complex graph analytic applications. Our experimental evaluation shows that FPGA acceleration can improve the performance of the LT diffusion model up to 1.72x for the entire application and up to 2.90x for its most important kernel with respect to a CPU only parallel execution. The FPGA acceleration of the LT model shows also a 1.54x reduction in energy consumption when compared to a parallel CPU only run.

Neff, Reece W.↗
NASA NTRSDate not supplied

Model Predictive Control Strategies for Turbine Electrified Energy Management

The increasing electrification of aircraft propulsion systems is leading to new control architectures being developed to address integration between electric machines and gas-based turbine engines. For hybrid-electric propulsion systems, current conceptual architectures often couple electric machines with the shafts of gas turbine engines and introduce energy storage. Leveraging the electrical power system of hybridized engines, Turbine Electrified Energy Management (TEEM) is a recent control approach that improves transient operability in an effort to enable more efficient and lighter weight turbomachinery. This study seeks to expand TEEM’s application beyond traditional proportional-integral (PI) control by presenting linear model predictive control (MPC) schemes to execute the TEEM concept. Through constraint selection and cost function design, transient operability goals for TEEM are considered with no external logic or saturation. Unique to the designs are the use of a washout filter, which simplifies transient detection and motor activation logic. The proposed architectures are implemented with both centralized MPC and distributed MPC approaches, and comparisons are drawn to a benchmark PI controller simulated on a nonlinear turbofan engine model at one ground condition and one cruise condition. Performance is evaluated using compressor maps, stall margin performance, and two novel metrics: transient stack usage and transient excursion integral. Results reveal the linear MPC scheme performs comparably to the baseline controller and can be implemented in at least two distinct configurations with potential for further modifications, thus establishing the groundwork for future investigations.

Model Predictive Control↗
NASA NTRSDate not supplied

Model Predictive Control Strategies for Turbine Electrified Energy Management

The increasing electrification of aircraft propulsion systems is leading to new control architectures being developed to address integration between electric machines and gas-based turbine engines. For hybrid-electric propulsion systems, current conceptual architectures often couple electric machines with the shafts of gas turbine engines and introduce energy storage. Leveraging the electrical power system of hybridized engines, Turbine Electrified Energy Management (TEEM) is a recent control approach that improves transient operability in an effort to enable more efficient and lighter weight turbomachinery. This study seeks to expand TEEM’s application beyond traditional proportional integral (PI) control by presenting linear model predictive control (MPC) schemes to execute the TEEM concept. Through constraint selection and cost function design, transient operability goals for TEEM are considered with no external logic or saturation. Unique to the designs are the use of a washout filter, which simplifies transient detection and motor activation logic. The proposed architectures are implemented with both centralized MPC and distributed MPC approaches, and comparisons are drawn to a benchmark PI controller simulated on a nonlinear turbofan engine model at one ground condition and one cruise condition. Performance is evaluated using compressor maps, stall margin performance, and two novel metrics: transient stack usage and transient excursion integral. Results reveal the linear MPC scheme performs comparably to the baseline controller and can be implemented in at least two distinct configurations with potential for further modifications, thus establishing the groundwork for future investigations.

Model Predictive Control↗
NASA NTRS2023

Model Predictive Control Strategies for Turbine Electrified Energy Management

The increasing electrification of aircraft propulsion systems is leading to new control architectures being developed to address integration between electric machines and gas-based turbine engines. For hybrid-electric propulsion systems, current conceptual architectures often couple electric machines with the shafts of gas turbine engines and introduce energy storage. Leveraging the electrical power system of hybridized engines, Turbine Electrified Energy Management (TEEM) is a recent control approach that improves transient operability in an effort to enable more efficient and lighter weight turbomachinery. This study seeks to expand TEEM’s application beyond traditional proportional-integral (PI) control by presenting linear model predictive control (MPC) schemes to execute the TEEM concept. Through constraint selection and cost function design, transient operability goals for TEEM are considered with no external logic or saturation. Unique to the designs are the use of a washout filter, which simplifies transient detection and motor activation logic. The proposed architectures are implemented with both centralized MPC and distributed MPC approaches, and comparisons are drawn to a benchmark PI controller simulated on a nonlinear turbofan engine model at one ground condition and one cruise condition. Performance is evaluated using compressor maps, stall margin performance, and two novel metrics: transient stack usage and transient excursion integral. Results reveal the linear MPC scheme performs comparably to the baseline controller and can be implemented in at least two distinct configurations with potential for further modifications, thus establishing the groundwork for future investigations.

Model Predictive Control↗
DOE OSTI2022

Summary Analysis Hanford Site Composite (Analysis Update)

This Summary Analysis has three primary purposes: (1) Define the overall technical scope and approach for conducting the Hanford Site CA update; (2) Define the approach for complying with modeling requirements in the Williams (2012) memorandum; and (3) Serve as the mechanism for the Groundwater Vadose Zone Executive Council to review and approve the overall modeling approach for the Hanford Site CA.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
NASA NTRS1994

Automated synthesis of image processing procedures using AI planning techniques

This paper describes the Multimission VICAR (Video Image Communication and Retrieval) Planner (MVP) (Chien 1994) system, which uses artificial intelligence planning techniques (Iwasaki & Friedland, 1985, Pemberthy & Weld, 1992, Stefik, 1981) to automatically construct executable complex image processing procedures (using models of the smaller constituent image processing subprograms) in response to image processing requests made to the JPL Multimission Image Processing Laboratory (MIPL). The MVP system allows the user to specify the image processing requirements in terms of the various types of correction required. Given this information, MVP derives unspecified required processing steps and determines appropriate image processing programs and parameters to achieve the specified image processing goals. This information is output as an executable image processing program which can then be executed to fill the processing request.

Chien, Steve↗
DOE OSTI2016

Optimization of tomographic reconstruction workflows on geographically distributed resources

New technological advancements in synchrotron light sources enable data acquisitions at unprecedented levels. This emergent trend affects not only the size of the generated data but also the need for larger computational resources. Although beamline scientists and users have access to local computational resources, these are typically limited and can result in extended execution times. Applications that are based on iterative processing as in tomographic reconstruction methods require high-performance compute clusters for timely analysis of data. Here, time-sensitive analysis and processing of Advanced Photon Source data on geographically distributed resources are focused on. Two main challenges are considered: (i) modeling of the performance of tomographic reconstruction workflows and (ii) transparent execution of these workflows on distributed resources. For the former, three main stages are considered: (i) data transfer between storage and computational resources, (i) wait/queue time of reconstruction jobs at compute resources, and (iii) computation of reconstruction tasks. These performance models allow evaluation and estimation of the execution time of any given iterative tomographic reconstruction workflow that runs on geographically distributed resources. For the latter challenge, a workflow management system is built, which can automate the execution of workflows and minimize the user interaction with the underlying infrastructure. The system utilizes Globus to perform secure and efficient data transfer operations. The proposed models and the workflow management system are evaluated by using three high-performance computing and two storage resources, all of which are geographically distributed. Workflows were created with different computational requirements using two compute-intensive tomographic reconstruction algorithms. Experimental evaluation shows that the proposed models and system can be used for selecting the optimum resources, which in turn can provide up to 3.13× speedup (on experimented resources). Furthermore, the error rates of the models range between 2.1 and 23.3% (considering workflow execution times), where the accuracy of the model estimations increases with higher computational demands in reconstruction tasks.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS1989

Average-passage flow model development

A 3-D model was developed for simulating multistage turbomachinery flows using supercomputers. This average passage flow model described the time averaged flow field within a typical passage of a bladed wheel within a multistage configuration. To date, a number of inviscid simulations were executed to assess the resolution capabilities of the model. Recently, the viscous terms associated with the average passage model were incorporated into the inviscid computer code along with an algebraic turbulence model. A simulation of a stage-and-one-half, low speed turbine was executed. The results of this simulation, including a comparison with experimental data, is discussed.

Adamczyk, John J.↗