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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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DOE OSTI2023

Auto-HPCnet: An Automatic Framework to Build Neural Network-based Surrogate for High-Performance Computing Applications

High-performance computing communities are increasingly adopt- ing Neural Networks (NN) as surrogate models in their applications to generate scientific insights. Replacing an execution phase in the application with NN models can bring significant performance im- provement. However, there is a lack of tools that can help domain scientists automatically apply NN-based surrogate models to HPC applications. We introduce a framework, named Auto-HPCnet, to democratize the usage of NN-based surrogates. Auto-HPCnet is the first end-to-end framework that makes past proposals for the NN-based surrogate model practical and disciplined. Auto-HPCnet introduces a workflow to address unique challenges when apply- ing the approximation, such as feature acquisition and meeting the application-specific constraint on the quality of final computation outcome. We show that Auto-HPCnet can leverage NN for a set of HPC applications and achieve 5.50× speedup on average (up to 16.8× speedup and with data preparation cost included) while meeting the application-specific constraint on the final computation quality.

Dong, Wenqian↗

NASA NTRS1987

File Usage Analysis and Resource Usage Prediction: a Measurement-Based Study

A probabilistic scheme was developed to predict process resource usage in UNIX. Given the identity of the program being run, the scheme predicts CPU time, file I/O, and memory requirements of a process at the beginning of its life. The scheme uses a state-transition model of the program's resource usage in its past executions for prediction. The states of the model are the resource regions obtained from an off-line cluster analysis of processes run on the system. The proposed method is shown to work on data collected from a VAX 11/780 running 4.3 BSD UNIX. The results show that the predicted values correlate well with the actual. The coefficient of correlation between the predicted and actual values of CPU time is 0.84. Errors in prediction are mostly small. Some 82% of errors in CPU time prediction are less than 0.5 standard deviations of process CPU time.

Devarakonda, Murthy V.-S.↗

NASA NTRS1987

Predictability of process resource usage: A measurement-based study of UNIX

A probabilistic scheme is developed to predict process resource usage in UNIX. Given the identity of the program being run, the scheme predicts CPU time, file I/O, and memory requirements of a process at the beginning of its life. The scheme uses a state-transition model of the program's resource usage in its past executions for prediction. The states of the model are the resource regions obtained from an off-line cluster analysis of processes run on the system. The proposed method is shown to work on data collected from a VAX 11/780 running 4.3 BSD UNIX. The results show that the predicted values correlate well with the actual. The correlation coefficient between the predicted and actual values of CPU time is 0.84. Errors in prediction are mostly small. Some 82% of errors in CPU time prediction are less than 0.5 standard deviations of process CPU time.

Devarakonda, Murthy V.↗

NASA NTRS1989

Predictability of process resource usage - A measurement-based study on UNIX

A probabilistic scheme is developed to predict process resource usage in UNIX. Given the identity of the program being run, the scheme predicts CPU time, file I/O, and memory requirements of a process at the beginning of its life. The scheme uses a state-transition model of the program's resource usage in its past executions for prediction. The states of the model are the resource regions obtained from an off-line cluster analysis of processes run on the system. The proposed method is shown to work on data collected from a VAX 11/780 running 4.3 BSD UNIX. The results show that the predicted values correlate well with the actual. The correlation coefficient betweeen the predicted and actual values of CPU time is 0.84. Errors in prediction are mostly small. Some 82 percent of errors in CPU time prediction are less than 0.5 standard deviations of process CPU time.

Devarakonda, Murthy V.↗

NASA NTRS2008

Next Generation Flight Controller Trainer System

The Next Generation Flight Controller Trainer (NGFCT) is a relatively inexpensive system of hardware and software that provides high-fidelity training for spaceshuttle flight controllers. NGFCT provides simulations into which are integrated the behaviors of emulated space-shuttle vehicle onboard general-purpose computers (GPCs), mission-control center (MCC) displays, and space-shuttle systems as represented by high-fidelity shuttle mission simulator (SMS) mathematical models. The emulated GPC computers enable the execution of onboard binary flight-specific software. The SMS models include representations of system malfunctions that can be easily invoked. The NGFCT software has a flexible design that enables independent updating of its GPC, SMS, and MCC components.

Arnold, Scott↗

NASA NTRS2020

Progressive Failure Analysis Correlation with Notched Composite Laminate Test Data

Testing of small and intermediate laminate panels with notches was performed and Progressive Failure Analyses (PFA) models were developed for aid in test planning and for correlation with the test data. Two progressive damage failure models were included in the study: the commercially available Abaqus built-in damage model and COmplete STress Reduction (COSTR) damage model developed at NASA Langley Research Center (LaRC). The finite elements models used for the analysis were developed using shell elements. The pre-test PFA results obtained from the two damage models were compared to test data. Then a post-test PFA with updated material properties based on additional available material property data was executed with the COSTR damage model and compared to the test data. The panels tested in compression all exhibited less scatter in the failure load with self-similar failure behavior. The panels tested in tension exhibited more scatter in the failure load with a failure mode that included delamination of plies. However, a self-similar crack path was also observed as the overall failure mode for all panels tested. When comparing test data to the pre-test analysis results, both damage models with shell element models were considered adequate for predicting the behavior and failure load of both the small and intermediate panels when tested in compression. However, for the tension load cases, larger differences were observed between the test and analysis results. When comparing test data to the post-test analysis performed using the COSTR damage model, better correlation was observed. However, large discrepancies were still observed for the tension load cases. Consequently, a higher fidelity finite element model including solid elements for sub-laminates and the modeling of cohesive layers between sub-laminate layers is recommended for tension loading of notched composite laminates.

Damage Model,Progressive Failure Analysis,Open Hol↗

DOE OSTI2021

Platform Agnostic Streaming Data Application Performance Models

The mapping of computational needs onto execution resources is, by and large, a manual task, and users are frequently guided simply by intuition and past experiences. We present a queueing theory based performance model for streaming data applications that takes steps towards a better understanding of resource mapping decisions, thereby assisting application developers to make good mapping choices. The performance model (and associated cost model) are agnostic to the specific properties of the compute resource and application, simply characterizing them by their achievable data throughput. We illustrate the model with a pair of applications, one chosen from the field of computational biology and the second is a classic machine learning problem.

Faber, Clayton↗

NASA NTRS2004

Testing of Environmental Satellite Bus-Instrument Interfaces Using Engineering Models

This paper discusses the formulation and execution of a laboratory test of the electrical interfaces between multiple atmospheric science instruments and the spacecraft bus that carries them. The testing, performed in 2002, used engineering models of the instruments that will be flown on the Aura s p a c m and of the Aura spacecraft bus electronics. Aura is one of NASA's Earth Observing System @OS) Program missions managed by the Goddard Space Flight Center. The test was designed to evaluate the complex interfaces in the spacecraft and instrument command and data handling (C&DH) subsystems prior to integration of the complete flight instruments on the spacecraft. A problem discovered during (and not before) the flight hardware integration phase can cause significant cost and schedule impacts. The testing successfully surfaced problems and led to their resolution before the full-up integration phase, saving significant cost and schedule time. This approach could be used on future environmental satellite programs involving multiple, complex scientific instruments being integrated onto a bus.

Gagnier, Don↗

NASA NTRS2004

Testing of Environmental Satellite Bus-Instrument Interfaces Using Engineering Models

This paper discusses the formulation and execution of a laboratory test of the electrical interfaces between multiple atmospheric scientific instruments and the spacecraft bus that carries them. The testing, performed in 2002, used engineering models of the instruments and the Aura spacecraft bus electronics. Aura is one of NASA s Earth Observatory System missions. The test was designed to evaluate the complex interfaces in the command and data handling subsystems prior to integration of the complete flight instruments on the spacecraft. A problem discovered during the flight integration phase of the observatory can cause significant cost and schedule impacts. The tests successfully revealed problems and led to their resolution before the full-up integration phase, saving significant cost and schedule. This approach could be beneficial for future environmental satellite programs involving the integration of multiple, complex scientific instruments onto a spacecraft bus.

Gagnier, Donald↗

DOE OSTI2021

A model-independent data assimilation (MIDA) module and its applications in ecology

Abstract. Models are an important tool to predict Earth system dynamics. An accurate prediction of future states of ecosystems depends on not only model structures but also parameterizations. Model parameters can be constrained by data assimilation. However, applications of data assimilation to ecology are restricted by highly technical requirements such as model-dependent coding. To alleviate this technical burden, we developed a model-independent data assimilation (MIDA) module. MIDA works in three steps including data preparation, execution of data assimilation, and visualization. The first step prepares prior ranges of parameter values, a defined number of iterations, and directory paths to access files of observations and models. The execution step calibrates parameter values to best fit the observations and estimates the parameter posterior distributions. The final step automatically visualizes the calibration performance and posterior distributions. MIDA is model independent, and modelers can use MIDA for an accurate and efficient data assimilation in a simple and interactive way without modification of their original models. We applied MIDA to four types of ecological models: the data assimilation linked ecosystem carbon (DALEC) model, a surrogate-based energy exascale earth system model: the land component (ELM), nine phenological models and a stand-alone biome ecological strategy simulator (BiomeE). The applications indicate that MIDA can effectively solve data assimilation problems for different ecological models. Additionally, the easy implementation and model-independent feature of MIDA breaks the technical barrier of applications of data–model fusion in ecology. MIDA facilitates the assimilation of various observations into models for uncertainty reduction in ecological modeling and forecasting.

58 GEOSCIENCES↗

NASA NTRS2021

A model-independent data assimilation (MIDA) module and its applications in ecology

Models are an important tool to predict Earth system dynamics. An accurate prediction of future states of ecosystems depends on not only model structures but also parameterizations. Model parameters can be constrained by data assimilation. However, applications of data assimilation to ecology are restricted by highly technical requirements such as model-dependent coding. To alleviate this technical burden, we developed a model-independent data assimilation (MIDA) module. MIDA works in three steps including data preparation, execution of data assimilation, and visualization. The first step prepares prior ranges of parameter values, a defined number of iterations, and directory paths to access files of observations and models. The execution step calibrates parameter values to best fit the observations and estimates the parameter posterior distributions. The final step automatically visualizes the calibration performance and posterior distributions. MIDA is model independent, and modelers can use MIDA for an accurate and efficient data assimilation in a simple and interactive way without modification of their original models. We applied MIDA to four types of ecological models: the data assimilation linked ecosystem carbon (DALEC) model, a surrogate-based energy exascale earth system model: the land component (ELM), nine phenological models and a stand-alone biome ecological strategy simulator (BiomeE). The applications indicate that MIDA can effectively solve data assimilation problems for different ecological models. Additionally, the easy implementation and model-independent feature of MIDA breaks the technical barrier of applications of data–model fusion in ecology. MIDA facilitates the assimilation of various observations into models for uncertainty reduction in ecological modeling and forecasting.

Earth system dynamics↗

DOE OSTI2021

Enabling Pulse-level Programming, Compilation, and Execution in XACC

Noisy gate-model quantum processing units (QPUs) are currently available from vendors over the cloud, and digital quantum programming approaches exist to run low-depth circuits on physical hardware. These digital representations are ultimately lowered to pulse-level instructions by vendor quantum control systems to affect unitary evolution representative of the submitted digital circuit. Vendors are beginning to open this pulse-level control system to the public via specified interfaces. Robust programming methodologies, software frameworks, and backend simulation technologies for this analog model of quantum computation will prove critical to advancing pulse-level control research and development. Prototypical use cases for this include error mitigation, optimal pulse control, and physics-inspired pulse construction. Here we present an extension to the XACC quantum-classical software framework that enables pulse-level programming for superconducting, gate-model quantum computers, and a novel, general, and extensible pulse-level simulation backend for XACC that scales on classical compute clusters via MPI. Our work enables custom backend Hamiltonian definitions and gate-level compilation to available pulses with a focus on performance and scalability. We end with a demonstration of this capability, and show how to use XACC for pertinent pulse-level programming tasks.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2016

Staghorn: An Automated Large-Scale Distributed System Analysis Platform

Conducting experiments on large-scale distributed computing systems is becoming significantly easier with the assistance of emulation. Researchers can now create a model of a distributed computing environment and then generate a virtual, laboratory copy of the entire system composed of potentially thousands of virtual machines, switches, and software. The use of real software, running at clock rate in full virtual machines, allows experiments to produce meaningful results without necessitating a full understanding of all model components. However, the ability to inspect and modify elements within these models is bound by the limitation that such modifications must compete with the model, either running in or alongside it. This inhibits entire classes of analyses from being conducted upon these models. We developed a mechanism to snapshot an entire emulation-based model as it is running. This allows us to \freeze time" and subsequently fork execution, replay execution, modify arbitrary parts of the model, or deeply explore the model. This snapshot includes capturing packets in transit and other input/output state along with the running virtual machines. We were able to build this system in Linux using Open vSwitch and Kernel Virtual Machines on top of Sandia's emulation platform Firewheel. This primitive opens the door to numerous subsequent analyses on models, including state space exploration, debugging distributed systems, performance optimizations, improved training environments, and improved experiment repeatability.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS1985

An Integrated Analysis of the Physiological Effects of Space Flight: Executive Summary

A large array of models were applied in a unified manner to solve problems in space flight physiology. Mathematical simulation was used as an alternative way of looking at physiological systems and maximizing the yield from previous space flight experiments. A medical data analysis system was created which consist of an automated data base, a computerized biostatistical and data analysis system, and a set of simulation models of physiological systems. Five basic models were employed: (1) a pulsatile cardiovascular model; (2) a respiratory model; (3) a thermoregulatory model; (4) a circulatory, fluid, and electrolyte balance model; and (5) an erythropoiesis regulatory model. Algorithms were provided to perform routine statistical tests, multivariate analysis, nonlinear regression analysis, and autocorrelation analysis. Special purpose programs were prepared for rank correlation, factor analysis, and the integration of the metabolic balance data.

Leonard, J. I.↗

NASA NTRS1988

Diagnosing faults in autonomous robot plan execution

A major requirement for an autonomous robot is the capability to diagnose faults during plan execution in an uncertain environment. Many diagnostic researches concentrate only on hardware failures within an autonomous robot. Taking a different approach, the implementation of a Telerobot Diagnostic System that addresses, in addition to the hardware failures, failures caused by unexpected event changes in the environment or failures due to plan errors, is described. One feature of the system is the utilization of task-plan knowledge and context information to deduce fault symptoms. This forward deduction provides valuable information on past activities and the current expectations of a robotic event, both of which can guide the plan-execution inference process. The inference process adopts a model-based technique to recreate the plan-execution process and to confirm fault-source hypotheses. This technique allows the system to diagnose multiple faults due to either unexpected plan failures or hardware errors. This research initiates a major effort to investigate relationships between hardware faults and plan errors, relationships which were not addressed in the past. The results of this research will provide a clear understanding of how to generate a better task planner for an autonomous robot and how to recover the robot from faults in a critical environment.

Lam, Raymond K.↗

NASA NTRS1989

Diagnosing faults in autonomous robot plan execution

Lam, Raymond K.↗

NASA NTRS2006

Multi-Platform Avionics Simulator

Multi-Platform Avionics Simulator (MPAvSim) is a software library for development of simulations of avionic hardware. MPAvSim facilitates simulation of interactions between flight software and such avionic peripheral equipment as telecommunication devices, thrusters, pyrotechnic devices, motor controllers, and scientific instruments. MPAvSim focuses on the behavior of avionics as seen by flight software, rather than on performing high-fidelity simulations of dynamics. However, MPAvSim is easily integrable with other programs that do perform such simulations. MPAvSim makes it possible to do real-time partial hardware- in-the-loop simulations. An MPAvSim simulation consists of execution chains (see figure) represented by flow graphs of models, defined here as stateless procedures that do some work. During a simulation, MPAvSim walks the execution chain, running each model in turn. Using MPAvSim, flight software can be run against a spacecraft that is all simulation, all hardware, or part hardware and part simulation. With respect to a specific piece of hardware, either the hardware itself or its simulation can be plugged in without affecting the rest of the system. Thus, flight software can be tested before hardware is available, and as items of hardware become available, they can be substituted for their simulations, with minimal disruption.

Clark, Micah↗

DOE OSTI2023

Application of machine learning for modeling brønsted-guggenheim-scatchard specific ion interaction theory (SIT) coefficients

Machine learning methodologies can provide insight into Brønsted-Guggenheim-Scatchard specific ion interaction theory (SIT) parameter values where experimental data availability may be limited. This study develops and executes machine learning frameworks to model the SIT interaction coefficient, ε. Key findings include successful estimations of ε via artificial neural networks using clustering and value prediction approaches. Additionally, applicability to other chemical parameters is also assessed briefly. Models developed here provide support for a use-case of machine learning in geologic nuclear waste disposal research applications, namely in predictions of chemical behaviors of high ionic strength solutions (i.e., subsurface brines).

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗