Visual Analytics for Scientific Data in NSLS-II
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36 MATERIALS SCIENCE↗
SEARCH · Engineering Papers
Results for “data analytic”
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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Comprehensive Data Analysis and Analytic Method Development for PBX9501 Material (FY2019 Annual Report of Aging and Lifetimes Program)
In the polymer bonded explosive (PBX) 9501, a binder consisting of 2.5 wt% nitroplasticizer (NP) and 2.5 wt% Estane R 5703 (Estane) is combined with 94.9 wt% of the high-explosive HMX and 0.1 wt% stabilizer. Because of its flexibility and tensile strength, this binder lowers the sensitivity and improves the manufacturability of PBX 9501. However, like many plasticizers comprised of low molecular weight components, NP has a tendency to diffuse out of the PBX 9501 matrix and can decompose at moderate temperatures into reactive byproducts, such as NO, NO 2 , H 2 O, and HNO x . Through oxidation and hydrolysis, these molecules can further degrade NP and Estane, ultimately degrading the properties of PBX 9501. While gaseous molecules can readily diffuse out of the PBX 9501 charges, the intermediates with lower volatility are more likely trapped in the condensed phase inside the charges and, in a closed system, will co-exist with Estane for an extended period of time creating an ongoing reactive environment. Understanding the rates of formation for these volatiles and intermediates during the NP degradation is therefore a critical prerequisite for understanding the long-term stability of polymeric binders used in munition systems. To work toward this ultimate goal, in the past year, we have conducted comprehensive studies on the physical properties of NP and finished three-year long aging experiment to understand the aging behavior of NP under thermal treatment. Important results are summarized in this annual report. Although NP is widely used in the DOE complex, their physical properties are rather scattered and inconsistent in the open literature. For example, there are at least two widely different values, 14.5°C and -15°C, for the melting point of NP. Although it is known that NP is a eutectic 50:50 mixture of BDNPA and BDNPF, their eutectic phase diagram is not well documented. Furthermore, the effect of temperature on the miscibility between water and eutectic BDNPA/F mixture is rarely reported. To fill these knowledge gaps, a large set of BDNPA/F mixtures with BDNPA concentration ranging from 0 to 100 wt% was analyzed using DSC techniques. In addition to determining the eutectic melt point as -25°C, a phase diagram of the BDNPA/F system was constructed from -30°C to 45°C. With this phase diagram, the phase transition temperatures and composition can be readily found for the BDNPA/F mixtures with various mass ratios.
36 MATERIALS SCIENCE↗
Carbon Storage Technical Viability Approach (CS TVA): An Integrated Approach for Feasibility and Data Resource Assessment
There is currently a poor understanding and lack of workflow to understand the technical viability of carbon storage spatially. To address this gap, the multi-faceted Carbon Storage Technical Viability Approach (CS TVA) is being developed to incorporate CO2 storage resources, environmental and socio-economic justice (EJ/SJ) factors to enable more comprehensive assessments. The CS TVA includes a (1) matrix framework, (2) an integrated and labeled database, (3) a data availability assessment workflow, and (4) spatial data availability assessment results. This approach leverages spatial and data science analytics to communicate data density, uncertainty, and gaps. The workflow can be applied in whole or in part, based on user needs.
Rodriguez, Neyda Cordero↗
Data Visualization and Analytics for Optimal Process Parameter Selection in Turning
The objective of this project is to research physics-guided machine learning methods to recommend optimal tools and machining process parameters for turning applications using the MSC test database. For a given turning application, the MSC metalworking specialist needs to make decisions on tools and the associated process parameters for the MSC customer. For a given material, there are many alternatives for tools and a wide range of process parameters to consider. MSC has built a database of tools and parameters for different applications from the historical turning tests completed at various customer sites. The research project aims to use machine learning methods to predict optimal tools and process parameters for the MSC metalworking specialists using the MSC test database. This enables continuous learning of optimal tool and process parameters for different applications as new information is collected from testing. Through MSC, this information can be shared with machining shops across the US leading to improved productivity and efficiency.
42 ENGINEERING↗
Grid-Ready Energy Analytics Training with Data (“GREAT with Data”)
GridEd is a collaborative educational initiative consisting of the Electric Power Research Institute (EPRI), 5 Partner Universities (Stony Brook University, The University of Texas at Austin, University of California – Riverside, Virginia Tech, Washington State University), and participating industry sponsors. This educational initiative focuses on developing and training the next generation of power engineers so they can help shape the electric grid of the future by anticipating and fulfilling the needs of changing electric industry requirements. GridEd is leveraging electric industry research to educate a future electric grid workforce by empowering new and continuing education students, not only to become competent and well-informed engineers, but also to participate and influence major technological, social, and policy decisions that address critical global challenges. GridEd’s activities are centered around four core pillars: Enhancement of university power systems engineering curricula; Professional development and training for a diverse electric industry workforce; Stimulating students to join the movement for the next generation of power engineers, and; Improve workforce development efforts in the electric utility industry. Major accomplishments over the course of the project were: Over 50 unique professional short courses were delivered by more than 30 instructors across the GridEd network; Over 3,600 unique learners, many who took multiple courses, received more than 27,000 professional development hours (PDH) and over 1,000 certificates of completion; Approximately 2,900 unique learners undertook a course that was offered LIVE online or in-person; Approximately 700 unique learners undertook a course that was offered as computer-based training (CBT); Over 35 unique university courses were delivered by more than 30 instructors to 1,500 university students across the GridEd network; One-hundred-and-fifty-seven (157) students were funded to completed 43 student projects in topics of power systems and data science, and; Six (6) Historically Black Colleges and Universities (HBCUs) recruited as Affiliate Universities via Utility Partners. The professional training initiative and workforce development activities launched by this project will be sustained through EPRI’s collaborative business model with industry. Stimulating students to join the power engineering workforce of the future and the enhancement of tertiary training may continue to need government support.
14 SOLAR ENERGY↗
RADIANCE: Rapid AI for Data Integration and Analytics in Childhood and Young Adult Cancer Ecosystems: FY26 AIM-3 MVP Report
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Chandra Shekar, Mayanka [ORNL] (ORCID:000000023697↗
Space Transportation System solid rocket booster thrust vector control system
The Solid Rocket Booster, Thrust Vector Control (TVC) system was designed in accordance with the following requirements: self-contained power supply, failsafe operation, 20 flight uses after exposure to seawater landings, optimized cost, and component interchangeability. Trade studies were performed which led to the selection of a recirculating hydraulic system powered by Auxiliary Power Units (APU) which drive the hydraulic actuators and gimbal the solid rocket motor nozzle. Other approaches for the system design were studied in arriving at the recirculating hydraulic system powered by an APU. These systems must withstand the imposed environment and be usable for a minimum of 20 Space Transportation System flights with a minimum of refurbishment. The TVC system completed the required qualification and verification tests and is certified for the intended application. Substantiation data include analytical and test data.
Verble, A. J., Jr.↗
Acoustic Treatment Design Scaling Methods: Analytical and Experimental Data Correlation - Volume 5
The primary purpose of the study presented in this volume is to present the results and data analysis of in-duct transmission loss measurements. Transmission loss testing was performed on full-scale, 1/2-scale, and 115-scale treatment panel samples. The objective of the study was to compare predicted and measured transmission loss for full-scale and subscale panels in an attempt to evaluate the variations in suppression between full- and subscale panels which were ostensibly of equivalent design. Generally, the results indicated an unsatisfactory agreement between measurement and prediction, even for full-scale. This was attributable to difficulties encountered in obtaining sufficiently accurate test results, even with extraordinary care in calibrating the instrumentation and performing the test. Test difficulties precluded the ability to make measurements at frequencies high enough to be representative of subscale liners. It is concluded that transmission loss measurements without ducts and data acquisition facilities specifically designed to operate with the precision and complexity required for high subscale frequency ranges are inadequate for evaluation of subscale treatment effects.
Chien, W. E.↗
FITNESS FOR PURPOSE: OVERVIEW OF ASTM GUIDES FOR QUALITY ASSURANCE OF DATA FROM NUCLEAR ANALYTICAL LABORATORIES
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Brisson, Mike↗
Data Management, Organization & Analytics
Presented by LRST at the eXtremeMAT Stakeholder Advisory Board Review Meeting, 10/15
Wenzlick, Madison Z.↗
An analytical technique for predicting the characteristics of a flexible wing equipped with an active flutter-suppression system and comparison with wind-tunnel data
An analytical technique for predicting the performance of an active flutter-suppression system is presented. This technique is based on the use of an interpolating function to approximate the unsteady aerodynamics. The resulting equations are formulated in terms of linear, ordinary differential equations with constant coefficients. This technique is then applied to an aeroelastic model wing equipped with an active flutter-suppression system. Comparisons between wind-tunnel data and analysis are presented for the wing both with and without active flutter suppression. Results indicate that the wing flutter characteristics without flutter suppression can be predicted very well but that a more adequate model of wind-tunnel turbulence is required when the active flutter-suppression system is used.
Abel, I.↗
Big Data Synchrophasor Monitoring and Analytics for Resiliency Tracking (BDSMART)
This report contains key findings from a project titled Big Data Synchrophasor Monitoring and Analytics for Resiliency Tracking (BDSMART), which was carried out through a collaborative effort of a team of researchers from Texas A&M Engineering Experiment Station, Temple University, and Quanta Technology, LLC. The in-kind support came from OSIsoft (acquired by AVEVA), which provided their PI Historian software to demonstrate the use case of streaming PMU data. The first section of the report describes the project goals and objectives related to the development of Machine Learning (ML) models capable of detecting and classifying events by processing phasor measurements captured in the field by Phasor Measurement Units (PMUs). The data for this study was contributed by the utilities/ISOs from the Western and Eastern interconnects and ERCOT, further referred to as Interconnect B (IC B), Interconnect A (IC A), and Interconnect C (IC C), respectively. The approach that the BDSMART Research Team proposed and the key research tasks defined by the team are outlined in this section. The next section describes the technical approach. We first discuss the data constraints related to the PMU measurements and data interpretation constraints imposed by the data contributors. They provided neither the topological information of the grid nor PMU placement locations and captured recorded data at very few locations in the system with the reporting rate of either 30 or 60 fps. The recordings are mostly positive sequence voltage, frequency, and ROCOF, and in some limited cases, three-phase voltages and currents. We then reflect on the bad data issues that stem from poor recording practices and vague definitions of the PMU status bits to supposedly be used for bad data identification. Finally, the data discovery points to imprecise time stamps with incomplete event start/end time, as well as inconsistent and incomplete event labeling, which combined make the implementation of the data models using supervising learning quite challenging. Following the data discovery study, we hypothesize that because the IC B data has the most complete labels, we should focus our model development on that data and then test it on data from other interconnects. We also define the common metrics used to evaluate the results from the ML algorithm tests. We concluded this section by summarizing the common ML models we used and explaining how we implemented and tested them. The issues from this section are expanded in the Training Dataset Report from this project. The final section of this report deals with the accomplishments and conclusions. As the accomplishments, we formulate the problem we are solving and what is achieved by solving the problem. We then reflect on each of the analytics tools we developed and point out the performance of each tool when applied to solving the mentioned problems. We reference this work for further details to the papers we published on each tool. In the conclusions, we give recommendations on how to improve future PMU recording practices to facilitate the ML algorithm implementation and guidance for the future standardization work aimed at clarifying the ambiguities associated with the PMU status bits. We finally list future tasks that can bring about further improvements in the proposed algorithms. The issues from this section are expanded in the Training, and Test Dataset Report filed at the project completion date.
97 MATHEMATICS AND COMPUTING↗
Data-driven occupant-behavior analytics for residential buildings
Many advances have been made in building technology to help save energy, but influencing the behavior of the occupants is still necessary to achieve low-energy use targets. One of the most practical ways to influence and change occupant behaviors is through incentives. Developing incentives for energy-saving and quantifying the impact of occupant behaviors are both active areas of research. Here, we propose a data analytics framework for detecting changes in occupant behaviors, which will help build an analytics feedback loop from behavior impact to incentive design. The framework has two major parts. The first forecasts energy consumption for each occupant, while the second determines a probability distribution for changes in energy consumption. The parts are interchangeable with other existing machine learning and statistical methods. A specific instantiation of the framework, using kernel ridge-regression for forecasting and k-means to find an empirical behavior distribution, is described in detail. An HVAC use-case with 5 different incentivized behaviors is used as an example to show that the framework can detect behavior changes induced by incentives. Furthermore, we show that some simpler behavior-change detection methods do not work, further justifying the use of advanced analytics.
32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
Testing of Densified Liquid Hydrogen Stratification in a Scale Model Propellant Tank
This paper describes a test program that was conducted at NASA to demonstrate the ability to load densified LH2 into a subscale propellant tank. This work was done through a collaborative effort between NASA Glenn Research Center and the Lockheed Martin Michoud Space Systems (LMMSS). The Multilobe tank, which was made from composite materials similar to that to be used on X-33, was formed from two lobes with a center septum. Test results are shown for data that was collected on filling the subscale tank with densified liquid hydrogen (DLH2) propellant that was produced at the NASA Plum Brook Station. Data is compared to analytical predictions. Data collected for this test series agrees well with analytical predictions of the environmental heat leak into the tank and the thermal stratification characteristics of the hydrogen propellant in the tank as it was filled with DLH2.
Jurns, John M.↗
Boundary-layer stability analysis of Langley Research Center 8-foot LFC experimental data
An analytical study of linear-amplifying instabilities of a laminar boundary layer as found in the experimental data of the LaRC/8-foot laminar-flow control (LFC) experiment was completed and the results are presented. The LFC airfoil used for this experiment was a swept, supercritical design which removed suction air through spanwise slots. The amplification of small disturbances by linear processes on a swept surface such as this can be due to either Tollmien-Schlichting (TS) and/or crossflow (CF) mechanisms. This study consists of the examination of these two instabilities by both the commonly used incompressible (SALLY and MARIA) analysis and the more involved compressible (COSAL) analysis. A wide range of experimental test conditions with variations in Mach number, Reynolds number, and suction distributions were available for this study. Experimentally determined transition locations were found from thin-film techniques and were used to correlate the n-factors at transition for the range of test cases.
Berry, Scott↗
CO 2 Storage Site Screening Platform Development and CO 2 Storage Resource Analysis in SECARB Offshore Reservoirs Using SAS Viya
A major goal of the SECARB Offshore Partnership (DE-FE0031557) is to screen deep saline aquifers and hydrocarbon reservoirs in the central Gulf of Mexico for CO 2 sequestration and CO 2 -enhanced oil and gas recovery (EOR/EGR) and estimate the corresponding CO 2 storage resources for select reservoirs. CO 2 storage potential associated with offshore CO 2 -EOR is considerable and likely represents “low hanging fruit” for near-term CO 2 storage given the in-place infrastructure in the region. It is for these reasons that this assessment focuses on oil and gas fields. To this end, three major objectives have been completed and include (1) managing geological data derived from different sources, (2) building a reservoir screening platform for CO 2 storage, and (3) ranking the reservoirs based on the estimated CO 2 storage resources. The SAS ® Viya platform was used for data management and analytics. The Viya platform is a cloud service platform that provides data integration, data management, quick analytics, data visualization, machine learning functions, and application programming interfaces (APIs) for multi-programming languages. Different sources of data containing geologic information, reservoir properties, and EOR/EGR information were collected, cleaned, formatted, and loaded into the SAS ® Viya platform for evaluation. The major geological characteristics of both shelf and deep-water areas of the central Gulf were examined and compared to define the appropriate reservoir screening criteria. Next, a CO 2 storage site screening system was built in the SAS ® Viya platform with the pre-defined criteria. Finally, the CO 2 storage resources of the screened reservoirs were calculated and reported at the BOEM field level to identify fields with the highest estimated CO 2 storage resource. The fields with the largest total estimated CO 2 storage resource are located in the Mississippi Canyon protraction area. Due to proximity to the Mississippi Delta (indicative of less infrastructure) and large estimated CO 2 storage resources, future development activities may wish to focus efforts in the Mississippi Canyon protraction area.
02 PETROLEUM↗
Space shuttle wing leading edge heating environment prediction derived from development flight data
An analytical program is in progress at Rockwell International to revise wing leading edge heating predictions in order to improve correlation with STS-1 to -5 flight radiometer data. This paper discusses the methods that have been used to improve agreement between prediction and flight and summarizes the aerodynamic correlations which, when updated, will be used to analyze future orbiter missions.
Cunningham, J. A.↗