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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 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

SNL-NJOY-2016

This is a wrapper around the LANL NJOY-2016 code that interfaces with extended code capabilities and minor modification of the LANL NJOY-2016 code that supports modeling radiation damage to materials. The NJOY Nuclear Data Processing System is a modular computer code designed to read evaluated data in ENDF format, transform the data in various ways, and output the results as libraries designed to be used in various applications. The wrapper provided here permits Sandia-specific control parameters to be used in the input data file. The modifications incorporated here enhance the ability of NJOY to address material damage response functions for many materials, e.g. to include the NRT and arc-dpa forms of the damage energy in addition to the default NJOY-2016 implementation of the sharp-threshold Kinchin-Pease threshold energy treatment. All of the modifications provided here are being made available to the GitHub-based NJOY-2016 code. As useful enhancements found here are incorporated into the baseline NJOY-2016 code, they will be eliminated from this version so as to maintain our compatibility with the baseline NJOY-2016 code. SAND2020-13060 M 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-NA00035

Griffin, Patrick↗
DOE OSTI2022

RLC4CLR (Reinforcement Learning Controller for Critical Load Restoration Problems)

RLC4CLR demonstrates using a reinforcement learning controller (RLC) to solve a critical load restoration (CLR) problem, which improves the grid resilience after a substation outage event. RLC4CLR consists of two parts. (1) RL environment: This environment encapsulates the CLR problem to be solved and provides interfacing functions to follow the standard OpenAI Gym format. A power system simulator, i.e., OpenDSS, is included to provide the power flow solution. Controller inputs and outputs (RL state and action) as well as the reward are defined in this environment as well. In summary, the RL environment is the problem formulation from which the RL agent can learn. (2) RL training script: The training script enables the RL agent to learn its control policy by interacting with the RL environment. For RL training, an open-sourced RL library, i.e., RLlib, is leveraged which is based on a distributed computing framework (Ray). The training script is designed to be able to be run on both local machine or the NREL HPC system. Other components of RLC4CLR include input data, e.g., grid model (standard IEEE test feeders), and other files used for results analysis.

Zhang, Xiangyu↗
DOE OSTI2022

Impact of nuclear data covariance libraries on uncertainty quantification of sodium cooled fast reactor simulation

Uncertainty quantification in core modelling to assess reactor performance is a regular practice to identify design safety limits. Best-estimate plus uncertainty (BEPU) methods are commonly used to propagate uncertainties to core responses from input parameters, characterized by variance-covariance libraries. This study evaluates the impact of different covariance libraries on the uncertainty associated with core safety parameters and their propagation through reactor transient modelling for a metallic core (ABR-1000). The COMAC-1.0, COMMARA-2.0, and COMMARA-2.1 covariance libraries are used to propagate nuclear data uncertainties to neutron feedback coefficients using the Generalized Perturbation Theory, then through transient safety analyses to establish the confidence interval for safety performance of the reactor using stochastic sampling. The considered transients include Unprotected Transient Over Power and Unprotected Loss Of Flow. Most influential nuclide and reaction pairs in different variance-covariance libraries are identified and their impact on the uncertainty of safety parameters are evaluated. Significant differences were observed between uncertainties from COMAC compared to COMMARA libraries. Uncertainties from COMMARA libraries were consistently larger than COMAC for all cases. For structure, coolant density feedback coefficients and control rod worth, total nuclear data uncertainties were approximately 50% larger for COMMARA than COMAC. Differences were also observed in identification of top contributors of uncertainty in terms of reaction-cross sections. For instance, largest contribution to total uncertainty of radial expansion coefficient from COMMARA-2.0 and 2.1 originates from Na{sup 23} P1 Elastic cross section (0.81%) but from Pu{sup 239} Fission (0.53%) with COM C-1.0. Such differences are evaluated in this research for all quantities of interest. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2021

Pycheron: A Python-Based Seismic Waveform Data Quality Control Software Package

Supplementing an existing high-quality seismic monitoring network with openly available station data could improve coverage and decrease magnitudes of completeness; however, this can present challenges when varying levels of data quality exist. Without discerning the quality of openly available data, using it poses significant data management, analysis, and interpretation issues. Incorporating additional stations without properly identifying and mitigating data quality problems can degrade overall monitoring capability. If openly available stations are to be used routinely, a robust, automated data quality assessment for a wide range of quality control (QC) issues is essential. To meet this need, we developed Pycheron, a Python-based library for QC of seismic waveform data. Pycheron was initially based on the Incorporated Research Institutions for Seismology’s Modular Utility for STAtistical kNowledge Gathering but has been expanded to include more functionality. Pycheron can be implemented at the beginning of a data processing pipeline or can process stand-alone data sets. Its objectives are to (1) identify specific QC issues; (2) automatically assess data quality and instrumentation health; (3) serve as a basic service that all data processing builds on by alerting downstream processing algorithms to any quality degradation; and (4) improve our ability to process orders of magnitudes more data through performance optimizations. This article provides an overview of Pycheron, its features, basic workflow, and an example application using a synthetic QC data set.

58 GEOSCIENCES↗
NASA NTRS1986

Procedures and tools for building large Ada systems

Some of the problems unique to building a very large Ada system are addressed. This is done through examples from experience. In the winter of 1985 and 1986, Intermetrics bootstrapped the Ada compiler, which was being built over the last few years. This system consists of about one million lines of full Ada. Over the last few years a number of procedures and tools were adopted for managing the life cycle of each of the many parts of an Ada system. Many of these procedures are well known to most system builders: release management, quality assurance testing; and source file revision control. Others are unique to working in an Ada language environment; i.e., recompilation management, Ada program library management, and managing multiple implementations. First a look is taken at how a large Ada system is broken down into pieces. The Ada definition leaves unspecified a number of issues that the system builder must address: versions, subsystems, multiple implementations, and synchronization of branched development paths. Having introduced how the Ada systems are decomposed, a look is taken, via a series of examples, at how the life cylces of those parts is managed. The procedures and tools used to manage the evolution of the system are examined. It is hoped that other Ada system builders can build upon the experience of the last few years.

Hyde, Ben↗
NASA NTRS1991

A demonstration of CMOS VLSI circuit prototyping in support of the site facility using the 1.2 micron standard cell library developed by National Security Agency

Two silicon CMOS application specific integrated circuits (ASICs), a data generation chip, and a data checker chip were designed. The conversion of the data generator circuitry into a pair of CMOS ASIC chips using the 1.2 micron standard cell library is documented. The logic design of the data checker is discussed. The functions of the control circuitry is described. An accurate estimate of timing relationships is essential to make sure that the logic design performs correctly under practical conditions. Timing and delay information are examined.

Smith, Edwyn D.↗
NASA NTRS2012

Logic Model Checking of Time-Periodic Real-Time Systems

In this paper we report on the work we performed to extend the logic model checker SPIN with built-in support for the verification of periodic, real-time embedded software systems, as commonly used in aircraft, automobiles, and spacecraft. We first extended the SPIN verification algorithms to model priority based scheduling policies. Next, we added a library to support the modeling of periodic tasks. This library was used in a recent application of the SPIN model checker to verify the engine control software of an automobile, to study the feasibility of software triggers for unintended acceleration events.

software analysis↗
DOE OSTI2019

ADVERT: An Asynchronous Runtime for Fine-Grained Network Systems

The Data Vortex Network, a novel fine-grained high-radix interconnect, provides the performance and injection rates required by the fine-grained, unpredictable communication patterns of irregular applications. This paper presents ADVERT, an asynchronous runtime system that provides performance and productivity for the fine-grained Data Vortex Network. ADVERT integrates a lightweight memory manager (DVMem) for the user accessible SRAM integrated in the network interface, and a communication library (DVComm) that implements active messaging primitives (remote execution, and, based on this, get and put routines). ADVERT hides the complexity of controlling all the network hardware features through the low-level Data Vortex programming interface, while providing comparable performance. We discuss ADVERT's design and present an analysis of three exemplar irregular kernels (Triangle Count, Page Rank, and GUPS). ADVERT can provide the communication substrate required to build emerging higher level asynchronous many tasking runtimes and partitioned global address space libraries on top of the Data Vortex Network.

Friese, Ryan D.↗
DOE OSTI2022

Modelica-based modeling and simulation of district cooling systems: A case study

While equation-based object-oriented modeling language Modelica can evaluate practical energy improvements for district cooling systems, few have adopted Modelica for this type of large-scale thermo-fluid system. Further, to our best knowledge, district cooling modeling studies have yet to include hydraulics in piping networks alongside plant models featuring realistic mechanical systems and controls. These are critical details to include when looking to make energy and control improvements in many physical system installations. To fill these gaps, this study released new open-source district cooling models at the Modelica Buildings Library and leveraged these models for a real-world case study at the University of Colorado Boulder. Here, the site includes six buildings connected to a central chiller plant featuring a waterside economizer. Several energy saving strategies are pursued based on the validated model, including control setpoint optimization, equipment modification, and pump setpoint adjustments. Results indicate that a combination of the studied measures can save the campus annually 84.6 MWh of energy, 8.9% of electricity costs, 58.0 metric tons of carbon dioxide emissions, while the waterside economizer cuts down chillers’ run times by 201 days/year, reducing maintenance costs and extending chiller life.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

A High-Throughput Computing Infrastructure to Generate Custom, Open Community Geothermal Datasets

The most significant challenge facing geothermal research, development, and deployment is a lack of comprehensive datasets describing the geological and economical properties of North America. Automated knowledge base construction, the process of designing algorithms to analyze text and images to programmatically build new datasets, is one possible solution to this problem. The xDD library of full-text scientific articles (https://xdd.wisc.edu) is one of the largest collections of open and controlled-access scientific documents available for knowledge base construction in the world, but it has been underutilized by experts in geothermal research. The xDD development team attributed the lack of engagement by software developers and geothermal researchers to two perceived shortcomings of the system. First, the workflow for obtaining data from xDD for local development and testing of data mining applications was unnecessarily abstruse and required significant manual intervention by xDD systems administrators. Second, although xDD already held articles from a broad cross-section of scientific literature with an emphasis on the geosciences, it did not have an explicit set of geothermal research documents that could serve as the nucleus of a geothermal data mining application. To address these issues, the Automated Data Extraction PlaTform (ADEPT) was proposed to extend the data distribution capabilities of the xDD system. The ADEPT extension added the following four key features to xDD: 1) integration of National Geothermal Data System (NGDS) documents into the xDD library to provide an explicitly geothermally-themed collection; 2) improved RESTful (i.e., https-protocol driven) web services for external partners to access xDD data for machine learning application development; 3) a web platform for end-users and xDD administrators to coordinate the development of data mining applications from the initial step of browsing available documents to the final stage of deploying a production-quality machine learning application on high-throughput computing infrastructure; and 4) the development of demonstration data mining applications to illustrate the new workflow to potential collaborators. A total of 21,674 geothermal documents from NGDS were fully ingested into the xDD library and the associated metadata is publicly available through the xDD web services; furthermore, the ADEPT web platform is now publicly accessible and fully live at https://xdd.wisc.edu/adept/.

15 GEOTHERMAL ENERGY↗
DOE OSTI2022

Memory forensic analysis of a programmable logic controller in industrial control systems

In industrial control systems (ICS), programmable logic controllers (PLCs) are used to automate physical processes such as nuclear plants and power grid stations, and are often subject to cyber attacks. As in conventional IT domain, the memory analysis of the PLCs can help answer important forensic questions about the attack, such as the presence of malicious firmware, injection of modified control logic (the program running on the PLC), and manipulation of I/O devices (e.g., sensors and actuators). Unlike conventional IT domain, PLCs have heterogeneous hardware architecture, proprietary firmware and control software, making it challenging to employ a unified framework for their memory forensics. For merely extracting artifacts of forensic importance, reverse-engineering the firmware is a tedious task, and the effort needs to be repeated for every PLC model. As a community, a step-wise approach to tackle this challenge is to analyze the memory of specific PLCs, and subsequently find a generic framework applicable to all PLCs. Our work is a step forward in this direction. By following a methodology that focuses on the functional layer of PLCs instead of reverse engineering the firmware, we analyze the digital forensic artifacts available in a common PLC, Allen-Bradley ControlLogix 1756-L61. Before diving into the memory dump, we analyze the PLC control software to create a list of important artifacts that are sure to exist in the PLC memory dump. The approach employs a setup where PLC control software RSLogix-5000 is connected to the PLC, and the memory dump can be obtained as and when needed. We create test cases that sequentially highlight each category of artifacts, followed by an examination of the resultant impact on memory. After attaining the listed artifacts, we employ conventional string and known data searches to extract interesting information present in this PLC's memory. The memory analysis profile, presented as a Python library and shared with the community, can help a forensic investigator to readily extract forensic artifacts from the same model's controller. The adopted approach may help researchers in creating memory profile of other PLCs, and ultimately formulating a generic PLC memory analysis framework.

Rais, Muhammad Haris↗
DOE OSTI2022

The influence of molecular design on structure–property relationships of a supramolecular polymer prodrug

Supramolecular self-assemblies of hydrophilic macromolecules functionalized with hydrophobic, structure-directing components have long been used for drug delivery. In these systems, loading of poorly soluble compounds is typically achieved through physical encapsulation during or after formation of the supramolecular assembly, resulting in low encapsulation efficiencies and limited control over release kinetics, which are predominately governed by diffusion and carrier degradation. To overcome these limitations, amphiphilic prodrugs that leverage a hydrophobic drug as both the therapeutic and structure-directing component can be used to create supramolecular materials with higher loading and controlled-release kinetics using biodegradable or enzymatically cleavable linkers. Here, we report the design, synthesis, and characterization of a library of supramolecular polymer prodrugs based on poly(ethylene glycol) (PEG) and the proregenerative drug 1,4-dihydrophenonthrolin-4-one-3-carboxylic acid (DPCA). Structure–property relationships were elucidated through experimental characterization of prodrug behavior in both the wet and dry states using scattering techniques and electron microscopy and corroborated by coarse-grained modeling. Molecular architecture and the hydrophobic-to-hydrophilic ratio of PEG–DPCA conjugates strongly influenced their physical state in water, ranging from fully soluble to supramolecular spherical assemblies and nanofibers. Molecular design and supramolecular structure, in turn, were shown to dramatically alter hydrolytic and enzymatic release and cellular transport of DPCA. In addition to potentially expanding therapeutic options for DPCA through control of supramolecular assemblies, the design principles elaborated here may inform the development of other supramolecular prodrugs based on hydrophobic small-molecule compounds.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
NASA NTRS2016

MONTE Python for Deep Space Navigation

The Mission Analysis, Operations, and Navigation Toolkit Environment (MONTE) is the Jet Propulsion Laboratory’s (JPL) signature astrodynamic computing platform. It was built to support JPL’s deep space exploration program, and has been used to fly robotic spacecraft to Mars, Jupiter, Saturn, Ceres, and many solar system small bodies. At its core, MONTE consists of low-level astrodynamic libraries that are written in C++ and presented to the end user as an importable Python language module. These libraries form the basis on which Python-language applications are built for specific astrodynamic applications, such as trajectory design and optimization, orbit determination, flight path control, and more. The first half of this paper gives context to the MONTE project by outlining its history, the field of deep space navigation and where MONTE fits into the current Python landscape. The second half gives an overview of the main MONTE libraries and provides a narrative example of how it can be used for astrodynamic analysis.

aerospace↗
DOE OSTI2024

Autonomous closed-loop mechanistic investigation of molecular electrochemistry via automation

Abstract Electrochemical research often requires stringent combinations of experimental parameters that are demanding to manually locate. Recent advances in automated instrumentation and machine-learning algorithms unlock the possibility for accelerated studies of electrochemical fundamentals via high-throughput, online decision-making. Here we report an autonomous electrochemical platform that implements an adaptive, closed-loop workflow for mechanistic investigation of molecular electrochemistry. As a proof-of-concept, this platform autonomously identifies and investigates an EC mechanism, an interfacial electron transfer ( E step) followed by a solution reaction ( C step), for cobalt tetraphenylporphyrin exposed to a library of organohalide electrophiles. The generally applicable workflow accurately discerns the EC mechanism’s presence amid negative controls and outliers, adaptively designs desired experimental conditions, and quantitatively extracts kinetic information of the C step spanning over 7 orders of magnitude, from which mechanistic insights into oxidative addition pathways are gained. This work opens opportunities for autonomous mechanistic discoveries in self-driving electrochemistry laboratories without manual intervention.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

*-DCC: A platform to collect, annotate, and explore a large variety of sequencing experiments

Background: Over the past few years the variety of experimental designs and protocols for sequencing experiments increased greatly. To ensure the wide usability of the produced data beyond an individual project, rich and systematic annotation of the underlying experiments is crucial. Findings: We first developed an annotation structure that captures the overall experimental design as well as the relevant details of the steps from the biological sample to the library preparation, the sequencing procedure, and the sequencing and processed files. Through various design features, such as controlled vocabularies and different field requirements, we ensured a high annotation quality, comparability, and ease of annotation. The structure can be easily adapted to a large variety of species. We then implemented the annotation strategy in a user-hosted web platform with data import, query, and export functionality. Conclusions: We present here an annotation structure and user-hosted platform for sequencing experiment data, suitable for lab-internal documentation, collaborations, and large-scale annotation efforts.

59 BASIC BIOLOGICAL SCIENCES↗