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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 OSTI2024

Ground Source Heat Pump Screening Tool and Related Resources

This archive contains both a link to Oak Ridge National Laboratory's Ground Source Heat Pump (GSHP) Screening Tool and related resources documenting its development, technical features, and applications. The web-based screening tool is a techno-economic analysis resource designed to evaluate the feasibility, costs, and benefits of implementing GSHP systems in buildings across various U.S. climate zones. It is intended for use by building owners, HVAC system designers, and installers to support decision-making in residential and commercial applications, incorporating advanced modeling capabilities such as ground heat exchanger design. The included resources detail the tool's creation and use, covering topics such as innovative ground heat exchanger design methodologies, the development of an open library of g-functions for borehole configurations, and studies on GSHP performance and economic viability in retrofitting single-family homes.

15 GEOTHERMAL ENERGY↗

NASA NTRS2016

Uncertainty Reduction using Bayesian Inference and Sensitivity Analysis: A Sequential Approach to the NASA Langley Uncertainty Quantification Challenge

This paper presents a computational framework for uncertainty characterization and propagation, and sensitivity analysis under the presence of aleatory and epistemic un- certainty, and develops a rigorous methodology for efficient refinement of epistemic un- certainty by identifying important epistemic variables that significantly affect the overall performance of an engineering system. The proposed methodology is illustrated using the NASA Langley Uncertainty Quantification Challenge (NASA-LUQC) problem that deals with uncertainty analysis of a generic transport model (GTM). First, Bayesian inference is used to infer subsystem-level epistemic quantities using the subsystem-level model and corresponding data. Second, tools of variance-based global sensitivity analysis are used to identify four important epistemic variables (this limitation specified in the NASA-LUQC is reflective of practical engineering situations where not all epistemic variables can be refined due to time/budget constraints) that significantly affect system-level performance. The most significant contribution of this paper is the development of the sequential refine- ment methodology, where epistemic variables for refinement are not identified all-at-once. Instead, only one variable is first identified, and then, Bayesian inference and global sensi- tivity calculations are repeated to identify the next important variable. This procedure is continued until all 4 variables are identified and the refinement in the system-level perfor- mance is computed. The advantages of the proposed sequential refinement methodology over the all-at-once uncertainty refinement approach are explained, and then applied to the NASA Langley Uncertainty Quantification Challenge problem.

Uncertainty↗

DOE OSTI2016

A high-performance parallel algorithm for nonnegative matrix factorization

Non-negative matrix factorization (NMF) is the problem of determining two non-negative low rank factors W and H, for the given input matrix A, such that A ≈ WH. NMF is a useful tool for many applications in different domains such as topic modeling in text mining, background separation in video analysis, and community detection in social networks. Despite its popularity in the data mining community, there is a lack of efficient distributed algorithms to solve the problem for big data sets. We propose a high-performance distributed-memory parallel algorithm that computes the factorization by iteratively solving alternating non-negative least squares (NLS) subproblems for W and H. It maintains the data and factor matrices in memory (distributed across processors), uses MPI for interprocessor communication, and, in the dense case, provably minimizes communication costs (under mild assumptions). As opposed to previous implementations, our algorithm is also flexible: (1) it performs well for both dense and sparse matrices, and (2) it allows the user to choose any one of the multiple algorithms for solving the updates to low rank factors W and H within the alternating iterations. We demonstrate the scalability of our algorithm and compare it with baseline implementations, showing significant performance improvements.

Kannan, Ramakrishnan↗

NASA NTRS2002

Development and Flight Testing of an Adaptive Vehicle Health-Monitoring Architecture

On going development and testing of an adaptable vehicle health-monitoring architecture is presented. The architecture is being developed for a fleet of vehicles. It has three operational levels: one or more remote data acquisition units located throughout the vehicle; a command and control unit located within the vehicle, and, a terminal collection unit to collect analysis results from all vehicles. Each level is capable of performing autonomous analysis with a trained expert system. The expert system is parameterized, which makes it adaptable to be trained to both a user's subject reasoning and existing quantitative analytic tools. Communication between all levels is done with wireless radio frequency interfaces. The remote data acquisition unit has an eight channel programmable digital interface that allows the user discretion for choosing type of sensors; number of sensors, sensor sampling rate and sampling duration for each sensor. The architecture provides framework for a tributary analysis. All measurements at the lowest operational level are reduced to provide analysis results necessary to gauge changes from established baselines. These are then collected at the next level to identify any global trends or common features from the prior level. This process is repeated until the results are reduced at the highest operational level. In the framework, only analysis results are forwarded to the next level to reduce telemetry congestion. The system's remote data acquisition hardware and non-analysis software have been flight tested on the NASA Langley B757's main landing gear. The flight tests were performed to validate the following: the wireless radio frequency communication capabilities of the system, the hardware design, command and control; software operation and, data acquisition, storage and retrieval.

Woodard, Stanley E.↗

NASA NTRS1988

Knowledge-Acquisition Tool For Expert System

Digital flight-control systems monitored by computer program that evaluates and recommends. Flight-systems engineers for advanced, high-performance aircraft use knowlege-acquisition tool for expert-system flight-status monitor suppling interpretative data. Interpretative function especially important in time-critical, high-stress situations because it facilitates problem identification and corrective strategy. Conditions evaluated and recommendations made by ground-based engineers having essential knowledge for analysis and monitoring of performances of advanced aircraft systems.

Disbrow, James D.↗

DOE OSTI2018

International Neuroscience Initiatives through the Lens of High-Performance Computing

Neuroscience initiatives aim to develop new technologies and tools to measure and manipulate neuronal circuits. In this paper, to deal with the massive amounts of data generated by these tools, the authors envision the co-location of open data repositories in standardized formats together with high-performance computing hardware utilizing open source optimized analysis codes.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2018

Calibrating Parameters of Power System Stability Models Using Advanced Ensemble Kalman Filter

With the ever increasing penetration of renewable energy, smart loads, energy storage, and new market behavior, today's power grid becomes more dynamic and stochastic, which may invalidate traditional study assumptions and pose great operational challenges. Thus, it is of critical importance to maintain good-quality models for secure and economic planning and real-time operation. Following the 1996 Western Systems Coordinating Council (WSCC) system blackout, North American Electric Reliability Corporation (NERC) and Western Electricity Coordinating Council (WECC) in North America enforced a number of policies and standards to guide the power industry to periodically validate power grid models and calibrate poor parameters with the goal of building sufficient confidence in model quality. The PMU-based approach using online measurements without interfering with the operation of generators provides a low-cost alternative to meet NERC standards. This paper presents an innovative procedure and tool suites to validate and calibrate models based on a trajectory sensitivity analysis method and an advanced ensemble Kalman filter algorithm. The developed prototype demonstrates excellent performance in identifying and calibrating bad parameters of a realistic hydro power plant against multiple system events.

Huang, Renke (ORCID:0000000230947073)↗

DOE OSTI2018

Design and Simulation of a Novel Mechanical Power Take-Off for a Two-Body Wave Energy Point Absorber

In this paper, a two-body self-react wave energy converter with a novel mechanical Power Take-off (PTO) is introduced. The PTO rectifies the mechanical motion and regulates the flow with a mechanism called Mechanical Motion Rectifier (MMR), which converts the reciprocating motion of the ocean wave into unidirectional rotation of the generator. The overall system is analyzed in both time and frequency domain. In time domain, the piecewise non-linear dynamic model of the MMR PTO is derived, and parameters that could significantly influence the MMR property is extracted. By building the model into WEC-Sim, a time domain wave energy converter (WEC) simulation tool, to simulate and evaluate the performance of the PTO. In addition, the system is modelled as a two-body vibration system for frequency domain analysis in order to further investigate and optimize the proposed wave energy converter. The tunable parameters within the system, including the equivalent mass, the equivalent damping coefficient, and the PTO stiffness, are discussed based on the criteria of maximization of the total output power. To verify the theoretical analysis, a bench test prototype is developed and tested on a hydraulic test machine. The experimental results in line with the derived model and can be used for reasonable estimation on the output power of the proposed system in real ocean conditions.

16 TIDAL AND WAVE POWER↗

DOE OSTI2023

A standardized quantitative analysis strategy for stable isotope probing metagenomics

ABSTRACT Stable isotope probing (SIP) facilitates culture-independent identification of active microbial populations within complex ecosystems through isotopic enrichment of nucleic acids. Many DNA-SIP studies rely on 16S rRNA gene sequences to identify active taxa, but connecting these sequences to specific bacterial genomes is often challenging. Here, we describe a standardized laboratory and analysis framework to quantify isotopic enrichment on a per-genome basis using shotgun metagenomics instead of 16S rRNA gene sequencing. To develop this framework, we explored various sample processing and analysis approaches using a designed microbiome where the identity of labeled genomes and their level of isotopic enrichment were experimentally controlled. With this ground truth dataset, we empirically assessed the accuracy of different analytical models for identifying active taxa and examined how sequencing depth impacts the detection of isotopically labeled genomes. We also demonstrate that using synthetic DNA internal standards to measure absolute genome abundances in SIP density fractions improves estimates of isotopic enrichment. In addition, our study illustrates the utility of internal standards to reveal anomalies in sample handling that could negatively impact SIP metagenomic analyses if left undetected. Finally, we present SIPmg , an R package to facilitate the estimation of absolute abundances and perform statistical analyses for identifying labeled genomes within SIP metagenomic data. This experimentally validated analysis framework strengthens the foundation of DNA-SIP metagenomics as a tool for accurately measuring the in situ activity of environmental microbial populations and assessing their genomic potential. IMPORTANCE Answering the questions, “who is eating what?” and “who is active?” within complex microbial communities is paramount for our ability to model, predict, and modulate microbiomes for improved human and planetary health. These questions can be pursued using stable isotope probing to track the incorporation of labeled compounds into cellular DNA during microbial growth. However, with traditional stable isotope methods, it is challenging to establish links between an active microorganism’s taxonomic identity and genome composition while providing quantitative estimates of the microorganism’s isotope incorporation rate. Here, we report an experimental and analytical workflow that lays the foundation for improved detection of metabolically active microorganisms and better quantitative estimates of genome-resolved isotope incorporation, which can be used to further refine ecosystem-scale models for carbon and nutrient fluxes within microbiomes.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

AEGIS (Air Emissions Grouped by Industrial Sectors) [SWR-24-49]

AEGIS is a robust framework designed to build and compile emissions inventories for various industrial sectors. It integrates multiple emissions databases provided by the USEPA – including GHGRP, NEI, and TRI – and leverages the STEWI and STEWICOMBO tools to retrieve, merge, and process data. The framework produces facility- and process-level inventories, identifies discrepancies (e.g., NAICS or FRS mismatches), and performs exploratory analysis including emission concentration calculations and visualization.

Atnoorkar, Swaroop↗

DOE OSTI2014

FINAL SCIENTIFIC REPORT Southwest United States of America – Distributed Technology Training Consortia (SWUSA-DTTC) Contract Number: DE-EE0006339

The Southwest United States of America – Distributed Technology Training Consortia (SWUSA-DTTC) leveraged the highest concentration of renewable resources in the U.S. as well as operation of the leading independent microgrid installations and other distributed technologies to collect and analyze real-time data streams, advance power system simulations and analysis, identify educational and training gaps and develop solutions-focused curricula. The SWUSA-DTTC consortium posed a unique collaboration between universities and utilities to ensure that classes were focused on subjects and topics of interest to the utilities and ones that had practical benefit related to the preparedness for accommodating high penetration of solar and other distributed energy technologies. This approach to have a close collaboration and shared effort to develop the course content and curriculum is unique and a significant departure from conventional course development. This coursework and training was intended to endure over a long time horizon (10-20 year time frame), and include professionals over the entire Southwest region and the rest of the US, and even outreach into foreign countries. Project Objectives In order to support the increase in power systems research, development, and analytical capacity, the SWUSA-DTTC brought together respected professors in Power Systems education, student/professor research and development, and valuable industry and utility experience. Through this program, the partnered universities created and/or modified existing curricula available to students and professionals in the form of university courses, short courses, videos, consortia-led training, and online materials. During this time, the supporting vendors and utilities provided the SWUSA-DTTC with technical advisory roles as well as providing input and feedback in terms of utility and related energy industry needs. The goals were to create power and energy systems training, curricula, and workforce preparedness through the inclusion of data collection and analysis, power systems expertise, and application-specific training activities which build on fundamental principles, modeling and simulation tools, field-immersed training and methods of performance validation. The outcome of the program was to result in better prepared and greater number of graduates ready to contribute to the field of power systems which depend upon the safe, reliable and efficient generation sources which make up an increasingly diverse mix of renewable power. Additionally, the program was to deliver critical training modules which are intended to support mid-career professionals and be woven into utility training programs used all over the country. Discontinuation Summary On September 29, 2014, Electricore received notice of discontinuation of federal funding under subject Award DE-EE0006339. DOE’s notice of discontinuation was the first indication provided to Electricore that the work completed against Task 1 - Program Planning and Evaluation during Budget Period 1 was inadequate. Significantly, the discontinuation was based in large part on the erroneous assertion that many of the tasks were incomplete as indicated in the Continuation Application. However, the Continuation Application was submitted July 29, 2014, while the period of performance for this last quarter in Budget Period 1 did not end until September 30, 2014. Accordingly, the performance for this last quarter in Budget Period 1 will be reported in the upcoming Quarterly Report which is not due until October 30, 2014. Nevertheless, in response to DOE’s letter and in further support of Electricore’s Continuation Application, we are providing a detailed status demonstrating adherence to all program requirements for each Task 1, Budget Period 1 SOPO activity and milestones in response to the DOE review.

14 SOLAR ENERGY↗

DOE OSTI2016

High-Throughput Method for Strontium Isotope Analysis by Multi-Collector-Inductively Coupled Plasma-Mass Spectrometer

This technical report presents the details of the Sr column configuration and the high-throughput Sr separation protocol. Data showing the performance of the method as well as the best practices for optimizing Sr isotope analysis by MC-ICP-MS is presented. Lastly, this report offers tools for data handling and data reduction of Sr isotope results from the Thermo Scientific Neptune software to assist in data quality assurance, which help avoid issues of data glut associated with high sample throughput rapid analysis.

47 OTHER INSTRUMENTATION↗

DOE OSTI2016

High-Throughput Method for Strontium Isotope Analysis by Multi-Collector-Inductively Coupled Plasma-Mass Spectrometer

47 OTHER INSTRUMENTATION↗

DOE OSTI2018

SULI Final Report

This project looks at alternative water sources, specifically in the field of desalination and selective ion removal through capacitive deionization (CDI). It project aims to both scale up the desalination capabilities of CDI cells as well as determine the selectivity of CDI for particular ions. My task is to design and build cells that have reproducible performance and characterize the materials for building these cells. The scientific methods I’ve learned through my work in CDI and the data mining and analysis tools I’ve become familiar with through CAES will be important catalysts in my future success in a graduate program. The purpose of this presentation is to give a standard of practice for my current method of building of capacitive deionization cells. Parts 1 and 2 will be discussed in which the electrodes are prepared, and the cell is built.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2021

Fission Product Yield Data Adjustment in a Prototype Version of TSURFER

The TSURFER (Tool for Sensitivity/Uncertainty analysis of Response Functionals using Experimental Results) module of Oak Ridge National Laboratory’s (ORNL’s) SCALE code system has been updated to perform nuclear data adjustments for fixed-source irradiation/depletion problems. TSURFER uses a generalized linear least squares (GLLS) approach to consolidate a prior set of measured responses and corresponding calculated values to create the most self-consistent set of nuclear data. Traditionally, TSURFER adjustments have been performed for multigroup nuclear data such as reaction cross sections. In this work, TSURFER is expanded to perform adjustments to independent fission product yields and branching ratios that need equality constraints. To preserve equality constraints after the data adjustment procedure, an updated GLLS formulation includes a new Lagrange multiplier that forces data adjustment to sum to 0 for a given fission yield/branching ratio parent. A test problem illustrates that the newly updated TSURFER module satisfies the required constraint that adjustments for fission yield data sum to 0.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2021

COTS Data Analytics Software User Manual: Version 1.0

Large volumes of data are being collected by Sandia National Laboratories as part of an active commercial-off-the-shelf (COTS) part testing and surveillance program. This user manual documents Python-based COTS Data Analytics software that has been developed for standardizing, displaying, visualizing, and analyzing the resulting COTS part testing and surveillance data. It is the objective of these software tools to streamline the analysis of COTS testing and surveillance data and improve the efficiency with which test engineers and data analytics experts can pinpoint possible performance and reliability problems in COTS parts.

42 ENGINEERING↗

DOE OSTI2025

Landscaper v1

Understanding the inner workings of machine learning models through their loss landscapes offers crucial insights into model properties, optimization dynamics, and generalizability. However, accessing these insights has traditionally required specialized mathematical expertise, limiting broader adoption. Landscaper is an open-source Python package designed to bridge this gap. Landscaper seamlessly integrates a suite of multi-dimensional loss landscape analyses with cutting-edge topological data analysis (TDA) methods. This powerful combination makes both fundamental loss landscape analysis and advanced TDA techniques accessible to the broader scientific ML community, without requiring deep pre-existing mathematical knowledge. Landscaper offers three key functionalities: * Construction: Builds detailed loss landscape representations through versatile low and high-dimensional sampling techniques. * Quantification: Applies advanced metrics, including a novel topological data analysis (TDA) based smoothness metric, enabling new perspectives on model behavior. * Visualization: Offers intuitive tools to visualize and interpret loss landscapes, providing actionable insights beyond traditional performance metrics.

Weber, Gunther [Lawrence Berkeley National Laborat↗

NASA NTRS1982

Response studies of rotors and rotor blades with application to aeroelastic tailoring

Various tools for the aeroelastic stability and response analysis of rotor blades in hover and forward flight were developed and incorporated in a comprehensive package capable of performing aeroelastic tailoring of rotor blades in forward flight. The results indicate that substantial vibration reductions, of order 15-40%, in the vibratory hub shears can be achieved by relatively small modifications of the initial design. Furthermore the optimized blade can be up to 20% lighter than the original design. Accomplishments are reported for the following tasks: (1) finite element modeling of rotary-wing aeroelastic problems in hover and forward flight; (2) development of numerical methods for calculating the aeroelastic response and stability of rotor blades in forward fight; (3) formulation of the helicopter air resonance problem in hover with active controls; and (4) optimum design of rotor blades for vibration reduction in forward flight.

Friedmann, P. P.↗