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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 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

BROOD: Bilevel and Robust Optimization and Outlier Detection for Efficient Tuning of High-Energy Physics Event Generators

The parameters in Monte Carlo (MC) event generators are tuned on experimental measurements by evaluating the goodness of fit between the data and the MC predictions. The relative importance of each measurement is adjusted manually in an often time-consuming, iterative process to meet different experimental needs. In this work, we introduce several optimization formulations and algorithms with new decision criteria for streamlining and automating this process. These algorithms are designed for two formulations: bilevel optimization and robust optimization. Both formulations are applied to the datasets used in the ATLAS A14 tune and to the dedicated hadronization datasets generated by the SHERPA generator, respectively. The corresponding tuned generator parameters are compared using three metrics. We compare the quality of our automatic tunes to the published ATLAS A14 tune. Moreover, we analyze the impact of a pre-processing step that excludes data that cannot be described by the physics models used in the MC event generators.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2017

Validation of CTF Droplet Entrainment and Annular/Mist Closure Models using Riso Steam/Water Experiments

This report summarizes the work done to validate the droplet entrainment and de-entrainment models as well as two-phase closure models in the CTF code by comparison with experimental data obtained at Riso National Laboratory. The Riso data included a series of over 250 steam/water experiments that were performed in both tube and annulus geometries over a range of various pressures and outlet qualities. Experimental conditions were set so that the majority of cases were in the annular/mist ow regime. Measurements included liquid lm ow rate, droplet ow rate, lm thickness, and two-phase pressure drop. CTF was used to model 180 of the tubular geometry cases, matching experimental geometry, outlet pressure, and outlet ow quality to experimental values. CTF results were compared to the experimental data at the outlet of the test section in terms of vapor and entrained liquid ow fractions, pressure drop per unit length, and liquid lm thickness. The entire process of generating CTF input decks, running cases, extracting data, and generating comparison plots was scripted using Python and Matplotlib for a completely automated validation process. All test cases and scripting tools have been committed to the COBRA-TF master repository and selected cases have been added to the continuous testing system to serve as regression tests. The dierences between the CTF- and experimentally-calculated ow fraction values were con- sistent with previous calculations by Wurtz, who applied the same entrainment correlation to the same data. It has been found that CTF's entrainment/de-entrainment predictive capability in the annular/mist ow regime for this particular facility is comparable to the licensed industry code, COBRAG. While lm and droplet predictions are generally good, it has been found that accuracy is diminished at lower ow qualities. This nding is consistent with the noted deciencies in the Wurtz entrainment model employed by CTF. The CTF predicted two-phase pressure drop in the annular/mist ow regime has been found to be highly inaccurate, exhibiting a clear bias with respect to the experimental data. This inaccuracy led to an investigation that revealed deciencies in the implementation of the annular/mist interfacial friction model, which should be investigated further in the future. Looking to published COBRAG results for this same facility reveal it exhibits no bias with regard to experimental pressure drop results. In addition to the problems with pressure drop prediction, the lm thickness was also signicantly under-predicted by CTF compared to both experimental data and Wurtz's analytical calculations. Film thickness is calculated using a simple geometric relationship and lm void fraction in CTF, which is dependent on slip ratio and interfacial friction. It is possible that the issues aecting the pressure drop and lm void prediction are related.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Panel-Segmentation: A Python Package for Automated Solar Array Metadata Extraction Using Satellite Imagery

The NREL Python Panel-Segmentation package is a toolkit that automates the process of extracting accurate and valuable metadata related to solar array installations, using publicly available Google Maps satellite imagery. Previously published work includes automated azimuth estimation for individual solar installations in satellite images. Our continued research focuses on automated detection and classification of solar installation mounting configuration (tracking or fixed-tilt; rooftop, ground, or carport). Specifically, a Faster-RCNN Resnet-50 feature pyramid network (FPN) model was trained and validated on 862 manually labeled satellite images. This model was used to perform object detection on satellite imagery, locating and classifying individual solar installations' mounting configuration and type. Model results showed a mean average precision score (mAP) of 77.79%, with the model strongest at detecting fixed-tilt ground mount and fixed-tilt carport installations. The object detection model and its outputs have been incorporated into the Panel-Segmentation package's automated metadata extraction pipeline, which returns the mounting configuration and azimuth for individual solar arrays in satellite imagery. The complete image data set with labels has been released on the U.S. Department of Energy (DOE) DuraMAT DataHub, to encourage further research in this area.

deep learning↗
DOE OSTI2023

The GammaSpec Package for Automated Gamma-ray Analysis (V.1.0)

This report describes the GammaSpec package, a tool developed to automate the analysis and comparison of gamma-ray spectra. The goal of this tool is to drastically reduce, or even eliminate, currently time consuming processes for comparing large sets of gamma-ray measurements. There are a number of potential applications for this work throughout the laboratory, but particularly within Global Security. Current work flows where large numbers of measured spectra must be compared for anomolies and outliers often consist of loading and visually inspecting individual spectra, or utilizing small-batch tools. One such example is the PeakEasy tool also developed at LANL. PeakEasy has a robust and tested feature set for calibrating, identifying, and fitting gamma-ray spectra. However it’s intention was not for batch processing and automated comparison of large numbers of spectra. This tool is not intended to replace PeakEasy in an analyzers arsenal, but to instead augment it. The intention here is to automate the isolation of spectra of particular interest, which can then be studied in further detail. This report is arranged as follows. Section 2 lays out the design goals and desired functionality of the package. Section 3 describes the algorithms developed and chosen to accomplish those goals. Section 4 describes the primary interaction with the tool, as well as it’s resulting output. Following these sections, results are presented from a set of example datasets from High Purity Germanium (HPGe) detectors in Sec. 5. Finally, the current status is summarized in Sec. 6.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2016

Policy-based secure communication with automatic key management for industrial control and automation systems

A method includes generating at least one access vector associated with a specified device in an industrial process control and automation system. The specified device has one of multiple device roles. The at least one access vector is generated based on one or more communication policies defining communications between one or more pairs of devices roles in the industrial process control and automation system, where each pair of device roles includes the device role of the specified device. The method also includes providing the at least one access vector to at least one of the specified device and one or more other devices in the industrial process control and automation system in order to control communications to or from the specified device.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

Toolpath generation for automated wind turbine blade finishing operations

Incorporating automation into wind turbine blade manufacturing is important for reducing costs to meet current offshore wind energy production goals in the United States. This work proposes a process for automating three operations in wind blade manufacturing: trimming to remove flashing left over after bonding two blade skins together, grinding to produce a desired leading-edge shape, and sanding to prepare the blade for bonding overlamination or adding paint to the surface. The majority of this work focuses on the toolpath generation. The algorithms were tested on a 5-m blade section, and the results were analyzed in terms of operation speed and accuracy. Finally, future work is discussed to improve the performance of the system.

17 WIND ENERGY↗
DOE OSTI2019

Degradation Mechanism Detection in Photovoltaic Backsheets by Fully Convolutional Neural Network

Materials and devices age with time. Material aging and degradation has important implications for lifetime performance of materials and systems. While consensus exists that materials should be studied and designed for degradation, materials inspection during operation is typically performed manually by technicians. The manual inspection makes studies prone to errors and uncertainties due to human subjectivity. In this work, we focus on automating the process of degradation mechanism detection through the use of a fully convolutional deep neural network architecture (F-CNN). We demonstrate that F-CNN architecture allows for automated inspection of cracks in polymer backsheets from photovoltaic (PV) modules. The developed F-CNN architecture enabled an end-to-end semantic inspection of the PV module backsheets by applying a contracting path of convolutional blocks (encoders) followed by an expansive path of decoding blocks (decoders). First, the hierarchy of contextual features is learned from the input images by encoders. Next, these features are reconstructed to the pixel-level prediction of the input by decoders. The structure of the encoder and the decoder networks are thoroughly investigated for the multi-class pixel-level degradation type prediction for PV module backsheets. The developed F-CNN framework is validated by reporting degradation type prediction accuracy for the pixel level prediction at the level of 92.8%.

14 SOLAR ENERGY↗
DOE OSTI2023

MLIR loop optimizations for High-Level Synthesis: a case study

High-Level Synthesis (HLS) tools simplify the design of hardware accelerators by automatically generating Verilog/VHDL code starting from a general purpose software programming language. They include a wide range of optimization techniques in the process, most of them performed on a low-level intermediate representation (IR) of the code. Introducing optimizations on a higher level of abstraction could significantly contribute to the automated design process results; for example, polyhedral techniques for the manipulation of loops could have a significant impact on the generated accelerators when applied on a specialized IR. We use loop pipelining as a case study to explore the introduction of compiler-based transformations on top of an existing HLS process. We leverage the Multi-Level Intermediate Representation (MLIR) framework and an external scheduler to implement the required transformations, and couple them with existing HLS tools to evaluate the improvements that loop pipelining brings to the performance of generated accelerators. The proposed approach can be integrated with other high-level transformations on the MLIR representation, combining different techniques to obtain pre-optimized inputs for HLS that do not have to rely on a specific backend tool.

Curzel, Serena↗
DOE OSTI2023

Automated reactor physics analysis framework of High Flux Isotope Reactor low-enriched uranium silicide dispersion fuel designs

The High Flux Isotope Reactor (HFIR) is a versatile research reactor that provides one of the highest steady-state neutron fluxes of any reactor in the world. The HFIR reactor physics team investigated the conversion of the current 93 wt% highly enriched uranium U 3 O 8 -Al dispersion fuel to a 19.75% low-enriched uranium (LEU) U 3 Si 2 -Al dispersion fuel. The team continuously develops a Python module to streamline the analysis steps required for an LEU core design to ensure reproducible and agile design iteration. The Python module automates the data processing between analysis steps and automates the input perturbation for branch calculations and design changes. The automated framework has proven to significantly increase the efficiency and reproducibility of the reactor physics team to design High Flux Isotope Reactor (HFIR) LEU cores and thoroughly analyze performance metrics, safety metrics, and thermal safety margins. Consequently, the team can now respond rapidly to fuel fabrication engineer and thermal-hydraulic-structural analyst requests. Numerous combinations of LEU fuel designs are explored, of which two LEU fuel designs are presented here in this paper: a low density silicide design, and a high-density silicide design. Results show that both designs meet or exceed safety and performance metrics with exception for minor differences caused by the hardened spectrum from LEU.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2017

10th International Topical Meeting on Nuclear Plant Instrumentation, Control and Human Machine Interface Technologies, San Francisco, CA, USA, June 11–15, 2017

As part of the ongoing efforts at the U.S. Department of Energy’s Light Water Reactor Sustainability Program, Idaho National Laboratory is conducting several pilot projects in collaboration with the nuclear industry to improve the reliability, safety, and economics of the nuclear power industry, especially as the nuclear power plants extend their operating licenses to 80 years. One of these pilot projects is the automated work package (AWP) pilot project. An AWP is an electronic intelligent and interactive work package. It uses plant condition, resources status, and user progress to adaptively drive the work process in a manner that increases efficiency while reducing human error. To achieve this mission, the AWP acquires information from various systems of a nuclear power plant’s and incorporates several advanced instrumentation and control technologies along with modern human factors techniques. With the current rapid technological advancement, it is possible to envision several available or soon-to-be-available capabilities that can play a significant role in improving the work package process. As a pilot project, the AWP project develops a prototype of an expanding set of capabilities and evaluates them in an industrial environment. While some of the proposed capabilities are based on using technological advances in other applications, others are conceptual; thus, require significant research and development to be applicable in an AWP. The scope of this paper is to introduce a set of envisioned capabilities, their need for the industry, and the industry difficulties they resolve.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

OpenABLext: An automatic code generation framework for agent-based simulations on CPU-GPU-FPGA heterogeneous platforms

The execution of agent-based simulations (ABSs) on hardware accelerator devices such as graphics processing units (GPUs) has been shown to offer great performance potentials. However, in heterogeneous hardware environments, it can become increasingly difficult to find viable partitions of the simulation and provide implementations for different hardware devices. To automate this process, we present OpenABLext, an extension to OpenABL, a model specification language for ABSs. By providing a device-aware OpenCL backend, OpenABLext enables the co-execution of ABS on heterogeneous hardware platforms consisting of central processing units, GPUs, and field programmable gate arrays (FPGAs).We present a novel online dispatching method that efficiently profiles partitions of the simulation during run-time to optimize the hardware assignment while using the profiling results to advance the simulation itself. In addition, OpenABLext features automated conflict resolution based on user-specified rules, supports graph-based simulation spaces, and utilizes an efficient neighbor search algorithm. We show the improved performance of OpenABLext and demonstrate the potential of FPGAs in the context of ABS. We illustrate how co-execution can be used to further lower execution times. OpenABLext can be seen as an enabler to tap the computing power of heterogeneous hardware platforms for ABS.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Assessing Opportunities and Challenges for Streamlining Interconnection Processes

As part of the Minnesota Solar Pathways project, funded in part by the Department of Energy’s Solar Energy Technologies Office, Electric Power Research Institute conducted a survey of existing utility interconnection practices and evaluated opportunities for streamlining them. The report highlights opportunities for electric utilities to improve transparency and automate administrative processes with options to fit the level of interconnections that utilities are experiencing.

14 SOLAR ENERGY↗
DOE OSTI2017

MN Solar Pathways: Assessing Opportunities and Challenges for Streamlining Interconnection Processes

As part of the Minnesota Solar Pathways project, funded in part by the Department of Energy’s Solar Energy Technologies Office, Electric Power Research Institute conducted a survey of existing utility interconnection practices and evaluated opportunities for streamlining them. The report highlights opportunities for electric utilities to improve transparency and automate administrative processes with options to fit the level of interconnections that utilities are experiencing.

14 SOLAR ENERGY↗
DOE OSTI2024

Benefits of the SolarAPP+ Online Permitting Software

The Solar Automated Permit Processing Plus (SolarAPP+) software is an online platform that provides plan review and instantly issues permits for code-compliant residential photovoltaic (PV) systems.

automated permitting↗
DOE OSTI2018

Automated Aerial Triangulation for UAV-Based Mapping

Accurate 3D reconstruction/modelling from unmanned aerial vehicle (UAV)-based imagery has become the key prerequisite in various applications. Although current commercial software has automated the process of image-based reconstruction, a transparent system, which can be incorporated with different user-defined constraints, is still preferred by the photogrammetric research community. In this regard, this paper presents a transparent framework for the automated aerial triangulation of UAV images. The proposed framework is conducted in three steps. In the first step, two approaches, which take advantage of prior information regarding the flight trajectory, are implemented for reliable relative orientation recovery. Then, initial recovery of image exterior orientation parameters (EOPs) is achieved through either an incremental or global approach. Finally, a global bundle adjustment involving Ground Control Points (GCPs) and check points is carried out to refine all estimated parameters in the defined mapping coordinate system. Four real image datasets, which are acquired by two different UAV platforms, have been utilized to evaluate the feasibility of the proposed framework. In addition, a comparative analysis between the proposed framework and the existing commercial software is performed. The derived experimental results demonstrate the superior performance of the proposed framework in providing an accurate 3D model, especially when dealing with acquired UAV images containing repetitive pattern and significant image distortions.

3D reconstruction↗
DOE OSTI2017

TRACC: An open source software for processing sap flux data from thermal dissipation probes

Here, thermal dissipation probes (TDPs) have become a widely used method of monitoring plant water use in recent years. The use of TDPs requires calibration to a theoretical zero-flow value (ΔT0); usually based upon the assumption that at least some nighttime measurements represent zero-flow conditions. Fully automating the processing of data from TDPs is made exceedingly difficult due to errors arising from many sources. However, it is desirable to minimize variation arising from different researchers’ processing data, and thus, a common platform for processing data, including editing raw data and determination of ΔT0, is useful and increases the transparency and replicability of TDP-based research. Here, we present the TDP data processing software TRACC (Thermal dissipation Review Assessment Cleaning and Conversion) to serve this purpose. TRACC is an open-source software written in the language R, using graphical presentation of data and on screen prompts with yes/no or simple numerical responses. It allows the user to select several important options, such as calibration coefficients and the exclusion of nights when vapor pressure deficit does not approach zero. Although it is designed for users with no coding experience, the outputs of TRACC could be easily incorporated into more complex models or software.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Imagery Applications for Advanced Event Analytics (WBS 24.3.1.3.3-IDC FY202 Final Project Report)

Accurate event locations and replicability of location analyses are essential for assessing the nature of an event, its context, ambient site conditions, and proximity to relevant facilities and infrastructure. Additionally, accurate event locations provide valuable information that reduce uncertainties, improve confidence in event analyses, and inform in-field verification activities. However, event location/relocation and replicability are difficult due to a number of factors, including spatially-sparse network coverage in some areas of the globe and variability in seismic data processing. This team proposed that the incorporation of high-fidelity imagery as a data backbone to the analytical assessment of a suspected underground explosion and/or an advanced seismic event bulletin produced by the International Data Centre (IDC) of the Preparatory Commission for the Comprehensive Nuclear-Test-Ban Treaty Organization (CTBTO PrepCom) could reduce uncertainties and improve confidence in analyses. Specifically, temporally-separated images can reduce uncertainty by identifying areas where change has occurred (e.g., building construction or demolition, road or facilities improvements). The primary goal of this project was to develop an automated geospatial processing script for imagery change detection to better reflect needs of the technical community (including the IDC) and to make the use of such a tool accessible in a variety of settings across platforms. Technical experts at Los Alamos National Laboratory successfully built GAIA: the Geospatial Automated Imagery Analysis tool, to fill this need. GAIA combines five tool components to produce orthorectified time separated imagery and imagery change detection maps. Our toolkit (1) reduces error by providing a standardized workflow for image analyses and (2) significantly reduces processing time from between 7 and 24+ hours to approximately 5 minutes. Technical experts at Sandia National Laboratories supported GAIA via beta-testing and by introducing a web-based system approach for increased applicability. To test the function, performance, broad application, and ease-of-use of GAIA, we applied it to four separate test cases. The results of this preliminary investigation show promise in reducing uncertainty in seismic event locations: if satellite imagery can show regions where operations that produce seismic activity likely occurred, then pursuing imagery to locate epicenters of seismic nuclear events could reduce the time needed to find the true epicenter location.

58 GEOSCIENCES↗