Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Distributed Software Development”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,117 records · Page 62
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

MAPPRAISER: A massively parallel map-making framework for multi-kilo pixel CMB experiments

Forthcoming cosmic microwave background (CMB) polarized anisotropy experiments have the potential to revolutionize our understanding of the Universe and fundamental physics. The sought-after, tale-telling signatures will be however distributed over voluminous data sets which these experiments will collect. These data sets will need to be efficiently processed and unwanted contributions due to astrophysical, environmental, and instrumental effects characterized and efficiently mitigated in order to uncover the signatures. This poses a significant challenge to data analysis methods, techniques, and software tools which will not only have to be able to cope with huge volumes of data but to do so with unprecedented precision driven by the demanding science goals posed for the new experiments. A keystone of efficient CMB data analysis is solvers of very large linear systems of equations. Such systems appear in very diverse contexts throughout CMB data analysis pipelines, however they typically display similar algebraic structures and can therefore be solved using similar numerical techniques. Linear systems arising in the so-called map-making problem are one of the most prominent and common ones. In this work we present a massively parallel, flexible and extensible framework, comprised of a numerical library, MIDAPACK, and a high level code, MAPPRAISER, which provide tools for solving efficiently such systems. Here, the framework implements iterative solvers based on conjugate gradient techniques: enlarged and preconditioned using different preconditioners. We demonstrate the framework on simulated examples reflecting basic characteristics of the forthcoming data sets issued by ground-based and satellite-borne instruments, executing it on as many as 16,384 compute cores. The software is developed as an open source project freely available to the community at: https://github.com/B3Dcmb/midapack.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2013

Fan-beam intensity modulated proton therapy

Purpose: This paper presents a concept for a proton therapy system capable of delivering intensity modulated proton therapy using a fan beam of protons. This system would allow present and future gantry-based facilities to deliver state-of-the-art proton therapy with the greater normal tissue sparing made possible by intensity modulation techniques.Methods: A method for producing a divergent fan beam of protons using a pair of electromagnetic quadrupoles is described and particle transport through the quadrupole doublet is simulated using a commercially available software package. To manipulate the fan beam of protons, a modulation device is developed. This modulator inserts or retracts acrylic leaves of varying thickness from subsections of the fan beam. Each subsection, or beam channel, creates what effectively becomes a beam spot within the fan area. Each channel is able to provide 0–255 mm of range shift for its associated beam spot, or stop the beam and act as an intensity modulator. Results of particle transport simulations through the quadrupole system are incorporated into the MCNPX Monte Carlo transport code along with a model of the range and intensity modulation device. Several design parameters were investigated and optimized, culminating in the ability to create topotherapy treatment plans using distal-edge tracking on both phantom and patient datasets.Results: Beam transport calculations show that a pair of electromagnetic quadrupoles can be used to create a divergent fan beam of 200 MeV protons over a distance of 2.1 m. The quadrupole lengths were 30 and 48 cm, respectively, with transverse field gradients less than 20 T/m, which is within the range of water-cooled magnets for the quadrupole radii used. MCNPX simulations of topotherapy treatment plans suggest that, when using the distal edge tracking delivery method, many delivery angles are more important than insisting on narrow beam channel widths in order to obtain conformal target coverage. Overall, the sharp distal falloff of a proton depth-dose distribution was found to provide sufficient control over the dose distribution to meet objectives, even with coarse lateral resolution and channel widths as large as 2 cm. Treatment plans on both phantom and patient data show that dose conformity suffers when treatments are delivered from less than approximately ten angles. Treatment time for a sample prostate delivery is estimated to be on the order of 10 min, and neutron production is estimated to be comparable to that found for existing collimated systems.Conclusions: Fan beam proton therapy is a method of delivering intensity modulated proton therapy which may be employed as an alternative to magnetic scanning systems. A fan beam of protons can be created by a set of quadrupole magnets and modified by a dual-purpose range and intensity modulator. This can be used to deliver inversely planned treatments, with spot intensities optimized to meet user defined dose objectives. Additionally, the ability of a fan beam delivery system to effectively treat multiple beam spots simultaneously may provide advantages as compared to spot scanning deliveries.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2016

TH-AB-201-10: Portal Dosimetry with Elekta IViewDose:Performance of the Simplified Commissioning Approach Versus Full Commissioning

Purpose: Elekta recently developed a solution for in-vivo EPID dosimetry (iViewDose, Elekta AB, Stockholm, Sweden) in conjunction with the Netherlands Cancer Institute (NKI). This uses a simplified commissioning approach via Template Commissioning Models (TCMs), consisting of a subset of linac-independent pre-defined parameters. This work compares the performance of iViewDose using a TCM commissioning approach with that corresponding to full commissioning. Additionally, the dose reconstruction based on the simplified commissioning approach is validated via independent dose measurements. Methods: Measurements were performed at the NKI on a VersaHD™ (Elekta AB, Stockholm, Sweden). Treatment plans were generated with Pinnacle 9.8 (Philips Medical Systems, Eindhoven, The Netherlands). A farmer chamber dose measurement and two EPID images were used to create a linac-specific commissioning model based on a TCM. A complete set of commissioning measurements was collected and a full commissioning model was created.The performance of iViewDose based on the two commissioning approaches was compared via a series of set-to-work tests in a slab phantom. In these tests, iViewDose reconstructs and compares EPID to TPS dose for square fields, IMRT and VMAT plans via global gamma analysis and isocentre dose difference. A clinical VMAT plan was delivered to a homogeneous Octavius 4D phantom (PTW, Freiburg, Germany). Dose was measured with the Octavius 1500 array and VeriSoft software was used for 3D dose reconstruction. EPID images were acquired. TCM-based iViewDose and 3D Octavius dose distributions were compared against the TPS. Results: For both the TCM-based and the full commissioning approaches, the pass rate, mean γ and dose difference were >97%, <0.5 and <2.5%, respectively. Equivalent gamma analysis results were obtained for iViewDose (TCM approach) and Octavius for a VMAT plan. Conclusion: iViewDose produces similar results with the simplified and full commissioning approaches. Good agreement is obtained between iViewDose (simplified approach) and the independent measurement tool. This research is funded by Elekta Limited.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

WISP: Watching grid Infrastructure Stealthily through Proxies (Final Technical Report)

The complex interdependencies of cyber systems (sensors and communications), physical grids and associated electricity market operations make protecting electric power grids a significant challenge. The energy sector is constantly under new, targeted, advanced and dangerous cyber-attacks that have the potential to result in the loss of human life. These threats are further exacerbated by our need to modernize the grid. One focus of cyber security research in smart grids is the securing of the SCADA system through advanced intrusion detection systems (IDS) and bad data detection algorithms in state estimation. These methods either require full knowledge of the system topology and parameters or fail to understand the physical behaviors under attack. WISP (Watching grid Infrastructure Stealthily through Proxies) is designed to provide additional protection to the power grid using only publicly available data. In particular, WISP exploits the spatio-temporal nature of the real time locational marginal prices (LMPs), in conjunction with other information such as bids, weather, outages and load data to analyze anomalous power pricing behaviors and then correlate those observations to localize regions of interest and identify potential cyber events. WISP is non-intrusive as the tool is deployed as a service in the Cloud or on premise and provides reliable information to system operators for enhanced situational awareness, without impeding energy delivery functions. The WISP technology comprises three modules: the data-driven anomaly detection core, the vulnerability and risk analysis and the root cause analysis. The data-driven anomaly detection core performs the tasks of feature selection, anomaly detection and attack region localization. The vulnerability and risk analysis module provides system level information of the vulnerable variables and times, assisting the operators in selecting monitoring and protection nodes. The root cause analysis module takes the detection results and identifies potential operational conditions that contribute to the detected anomalies. In Phase I, we have demonstrated the feasibility and effectiveness of WISP. We developed a realistic electricity market simulator capable of generating normal and attack market data under various operational conditions. We developed a series of cyber-attack detection and analysis algorithms and evaluated them under multiple data sources. Finally, we integrated all modules into an end-to-end software, providing functions for data management, data analytics and visualization. Specifically, we have achieved: (i) real-time data acceptance from external utility interfaces with >99% acceptance rate; (ii) high performance anomaly detection algorithms with >98% detection accuracy and <0.1% false alarm rate; and (iii) ultra-low computing delay <50 milliseconds. Additionally, our team developed algorithms to identify the vulnerable variables in electricity market operations and root cause analysis functions to identify major contributors to the price spikes. These ancillary modules are necessary when deploying WISP in real world industry environment. In Phase II, we have demonstrated the effectiveness of WISP software on realistic largescale power systems. We performed red team testing for the Phase I WISP software and identified software vulnerabilities and implemented corresponding mitigation solutions. We adapted the electricity market simulator for the Texas synthetic 2000-bus system and generated datasets for the false data injection attacks. We created database and visualization interfaces for the Texas system and the ISO New England system. We performed software optimization in terms of operation efficiency, computing speed and detection accuracy. Finally, we tested the software on the Texas system and the ISO New England system and evaluated the detection performance. Overall, we achieved above 89% detection rate, below 3% false alarm rate and below 37 seconds of end-to-end detection delay.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2016

CFD and X-ray Analysis of Gaseous Direct Injection from an Outward Opening Injector

Using natural gas in an internal combustion engine (ICE) is emerging as a promising way to improve thermal efficiency and reduce exhaust emissions. In the development of such engine platforms, computational fluid dynamics (CFD) plays a fundamental role in the optimization of geometries and operating parameters. One of the most relevant issues in the simulation of direct injection (DI) gaseous processes is the accurate prediction of the gas jet evolution. The simulation of the injection process for a gaseous fuel does not require complex modeling, nevertheless properly describing high-pressure gas jets remains a challenging task. At the exit of the nozzle, the injected gas is under-expanded, the flow becomes supersonic and shocks occur due to compressibility effects. These phenomena lead to challenging computational requirements resulting from high grid resolution and low computational time-steps. In this paper, the simulation of gaseous injection from an outward opening injector was carried out with the commercial CFD software CONVERGE. Argon was injected into a quiescent chamber filled with Nitrogen. Two free-jet cases with injection pressure of 15 and 10 bar, and ambient pressure of 1 and 2 bar respectively, were tested. For the 15 bar injection pressure and 1 bar ambient pressure, a jet impinging on a barrier case was performed as well. The numerical results were validated against experimental mass measurements using X-ray radiography. The results, presented in terms of 2D maps and transverse sections of equivalent path length of argon, showed good agreement between modeling and experiments in terms of jet penetration, shape and gas mass distribution. These emphasized the significant impact of mesh size on the results for the simulation of this type of injector. Due to the small geometrical dimensions a fine mesh is required in order to deliver an accurate description of the mixture formation. Numerical results were discussed with a particular emphasis on the application to engine simulations, where a trade-off between accuracy and computational time is a necessity.

Bartolucci, Lorenzo↗
DOE OSTI2017

Open V2X at ESIF: June 2015 - February 2017 (Final Report)

The University of Delaware (UD), and their industrial partners, have carried out testing, documentation, and standards development at ESIF. These activities are intended to help meet the objective of NREL's INTEGRATE program, to enable clean energy technologies to increase the hosting capacity of the grid, by providing grid services in a holistic manner using an open source, interoperable platform. In particular, the 'Open V2X at ESIF' project worked to facilitate standardization and interoperability for Electric Vehicle technologies, including battery electric vehicles and plug-in hybrid vehicles (hence EV) to provide grid services. This was done by interconnecting and testing EV and EVSE (charging station) hardware from different manufacturers, by developing standards and test protocols for standards, and by documenting new protocols to be proposed as standards. Contractor-supplied equipment used in the testing included Vehicle Smart Links (VSLs) installed in an EV and School Bus, single-phase and three-phase charging stations, and an optimizing aggregator (software running on a server, hence just 'Aggregator'). The Aggregator software was developed by U of Delaware and is now licensed to Nuvve Corp for commercial development, and licensed to NRG/EVgo for demonstrations. The Aggregator monitors capacity and operations of the EVs and EVSEs, dispatches them in response to requests, and reports their operations and metered power flow. In operation, as vehicles move, plug-in and unplug, the aggregator tracks the total capacity available within a defined jurisdiction or RTO (Regional Transmission Organization, synonym for ISO or TSO), and dispatches part or all of that capacity based on market or direct dispatch signals from a grid entity. The VSL is the data acquisition and control module in the resource itself (EVSE or EV), with rich communication between a single Optimizing Aggregator and many VSL (one in each resource). All requests and dispatch events are also logged by the aggregator to make the provision of grid power auditable. For these tests, the dispatch was typically a recorded signal, the VSL was in the EV or EVSE, and the recording of experimental performance was often carried out by the normal logging functions of the aggregator.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2014

THE NEW ONLINE METADATA EDITOR FOR GENERATING STRUCTURED METADATA

Nobody is better suited to “describe” data than the scientist who created it. This “description” about a data is called Metadata. In general terms, Metadata represents the who, what, when, where, why and how of the dataset [1]. eXtensible Markup Language (XML) is the preferred output format for metadata, as it makes it portable and, more importantly, suitable for system discoverability. The newly developed ORNL Metadata Editor (OME) is a Web-based tool that allows users to create and maintain XML files containing key information, or metadata, about the research. Metadata include information about the specific projects, parameters, time periods, and locations associated with the data. Such information helps put the research findings in context. In addition, the metadata produced using OME will allow other researchers to find these data via Metadata clearinghouses like Mercury [2][4]. OME is part of ORNL’s Mercury software fleet [2][3]. It was jointly developed to support projects funded by the United States Geological Survey (USGS), U.S. Department of Energy (DOE), National Aeronautics and Space Administration (NASA) and National Oceanic and Atmospheric Administration (NOAA). OME’s architecture provides a customizable interface to support project-specific requirements. Using this new architecture, the ORNL team developed OME instances for USGS’s Core Science Analytics, Synthesis, and Libraries (CSAS&L), DOE’s Next Generation Ecosystem Experiments (NGEE) and Atmospheric Radiation Measurement (ARM) Program, and the international Surface Ocean Carbon Dioxide ATlas (SOCAT).Researchers simply use the ORNL Metadata Editor to enter relevant metadata into a Web-based form. From the information on the form, the Metadata Editor can create an XML file on the server that the editor is installed or to the user’s personal computer. Researchers can also use the ORNL Metadata Editor to modify existing XML metadata files.As an example, an NGEE Arctic scientist use OME to register their datasets to the NGEE data archive and allows the NGEE archive to publish these datasets via a data search portal (http://ngee.ornl.gov/data). These highly descriptive metadata created using OME allows the Archive to enable advanced data search options using keyword, geo-spatial, temporal and ontology filters. Similarly, ARM OME allows scientists or principal investigators (PIs) to submit their data products to the ARM data archive.How would OME help Big Data Centers like the Oak Ridge National Laboratory Distributed Active Archive Center (ORNL DAAC)?The ORNL DAAC is one of NASA’s Earth Observing System Data and Information System (EOSDIS) data centers managed by the Earth Science Data and Information System (ESDIS) Project. The ORNL DAAC archives data produced by NASA's Terrestrial Ecology Program. The DAAC provides data and information relevant to biogeochemical dynamics, ecological data, and environmental processes, critical for understanding the dynamics relating to the biological, geological, and chemical components of the Earth's environment. Typically data produced, archived and analyzed is at a scale of multiple petabytes, which makes the discoverability of the data very challenging. Without proper metadata associated with the data, it is difficult to find the data you are looking for and equally difficult to use and understand the data.OME will allow data centers like the NGEE and ORNL DAAC to produce meaningful, high quality, standards-based, descriptive information about their data products in-turn helping with the data discoverability and interoperability. Useful Links:USGS OME: http://mercury.ornl.gov/OME/NGEE OME: http://ngee-arctic.ornl.gov/ngeemetadata/ARM OME: http://archive2.ornl.gov/armome/Contact: Ranjeet Devarakonda (devarakondar@ornl.gov)References:[1] Federal Geographic Data Committee. Content standard for digital geospatial metadata. Federal Geographic Data Committee, 1998.[2] Devarakonda, Ranjeet, et al. "Mercury: reusable metadata management, data discovery and access system." Earth Science Informatics 3.1-2 (2010): 87-94.[3] Wilson, B. E., Palanisamy, G., Devarakonda, R., Rhyne, B. T., Lindsley, C., & Green, J. (2010). Mercury Toolset for Spatiotemporal Metadata.[4] Pouchard, L. C., Branstetter, M. L., Cook, R. B., Devarakonda, R., Green, J., Palanisamy, G., ... & Noy, N. F. (2013). A Linked Science investigation: enhancing climate change data discovery with semantic technologies. Earth science informatics, 6(3), 175-185.

FGDC CSDGM↗
DOE OSTI2016

SU-F-T-580: New Tumor Modeling Using 3D Gel Dosimeter for Brain Stereoctactic Radiotherpy (SRT)

Purpose: The purpose of this study is to develop new tumor model using 3D printing with 3D dosimeter for brain stereoctactic radiotherpy (SRT). Methods: BANG{sup 3} polymer gel was prepared and the gel-filled glass vials were irradiated with a 6 MV photon beam to acquire the calibration curve that present the change of R2 (1/T{sub 2}) value with dose. Graded doses from 0 to 12 Gy with an interval of 2 Gy were delivered. A kit for calibration of gel dosimeter and an 2 tumor model phantoms with a spherical shape were produced using a 3D printer with a polylactic acid after its 3D images were created using Autodesk software. 3D printed tumor phantoms and EBT3 films were irradiated to compare with treatment plan. After irradiation, vials for calibration and tumor model phantoms were scanned at 9.4T MRI. The spin-spin relaxation times (T{sub 2}) according to the each dose were calculated to evaluate the dose response. Acquired images were analyzed using an ImageJ. Scanned MRI images of tumor models were transferred treatment planning system and these were registered to the CT images. In all treatment plans, two arc plans (CW and CCW) were designed to deliver 50 Gy for 10 fractions. For first PTV, treatment plan was accurately designed that 95% of dose to cover 100% of PTV. But 2nd PTV was not intentionally cover 100% of PTV to evaluate the intensity of delivered tumor phantom with polymer gel. We compared the 3D dose distributions obtained from measurements with the 3D printed phantom and calculated with the TPS. Results: 3D printed phantom with a polymer gel was successfully produced. The dose distributions showed qualitatively good agreement among gel, film, and RTP data. Conclusion: A hybrid phantom represents a useful to validate the 3D dose distributions for patient-specific QA.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

SU-D-BRC-03: Development and Validation of an Online 2D Dose Verification System for Daily Patient Plan Delivery Accuracy Check

Purpose: All plan verification systems for particle therapy are designed to do plan verification before treatment. However, the actual dose distributions during patient treatment are not known. This study develops an online 2D dose verification tool to check the daily dose delivery accuracy. Methods: A Siemens particle treatment system with a modulated scanning spot beam is used in our center. In order to do online dose verification, we made a program to reconstruct the delivered 2D dose distributions based on the daily treatment log files and depth dose distributions. In the log files we can get the focus size, position and particle number for each spot. A gamma analysis is used to compare the reconstructed dose distributions with the dose distributions from the TPS to assess the daily dose delivery accuracy. To verify the dose reconstruction algorithm, we compared the reconstructed dose distributions to dose distributions measured using PTW 729XDR ion chamber matrix for 13 real patient plans. Then we analyzed 100 treatment beams (58 carbon and 42 proton) for prostate, lung, ACC, NPC and chordoma patients. Results: For algorithm verification, the gamma passing rate was 97.95% for the 3%/3mm and 92.36% for the 2%/2mm criteria. For patient treatment analysis,the results were 97.7%±1.1% and 91.7%±2.5% for carbon and 89.9%±4.8% and 79.7%±7.7% for proton using 3%/3mm and 2%/2mm criteria, respectively. The reason for the lower passing rate for the proton beam is that the focus size deviations were larger than for the carbon beam. The average focus size deviations were −14.27% and −6.73% for proton and −5.26% and −0.93% for carbon in the x and y direction respectively. Conclusion: The verification software meets our requirements to check for daily dose delivery discrepancies. Such tools can enhance the current treatment plan and delivery verification processes and improve safety of clinical treatments.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2011

RECOVERY ACT: DYNAMIC ENERGY CONSUMPTION MANAGEMENT OF ROUTING TELECOM AND DATA CENTERS THROUGH REAL-TIME OPTIMAL CONTROL (RTOC): Final Scientific/Technical Report

This final scientific report documents the Industrial Technology Program (ITP) Stage 2 Concept Development effort on Data Center Energy Reduction and Management Through Real-Time Optimal Control (RTOC). Society is becoming increasingly dependent on information technology systems, driving exponential growth in demand for data center processing and an insatiable appetite for energy. David Raths noted, 'A 50,000-square-foot data center uses approximately 4 megawatts of power, or the equivalent of 57 barrels of oil a day1.' The problem has become so severe that in some cases, users are giving up raw performance for a better balance between performance and energy efficiency. Historically, power systems for data centers were crudely sized to meet maximum demand. Since many servers operate at 60%-90% of maximum power while only utilizing an average of 5% to 15% of their capability, there are huge inefficiencies in the consumption and delivery of power in these data centers. The goal of the 'Recovery Act: Decreasing Data Center Energy Use through Network and Infrastructure Control' is to develop a state of the art approach for autonomously and intelligently reducing and managing data center power through real-time optimal control. Advances in microelectronics and software are enabling the opportunity to realize significant data center power savings through the implementation of autonomous power management control algorithms. The first step to realizing these savings was addressed in this study through the successful creation of a flexible and scalable mathematical model (equation) for data center behavior and the formulation of an acceptable low technical risk market introduction strategy leveraging commercial hardware and software familiar to the data center market. Follow-on Stage 3 Concept Development efforts include predictive modeling and simulation of algorithm performance, prototype demonstrations with representative data center equipment to verify requisite performance and continued commercial partnering agreement formation to ensure uninterrupted development, and deployment of the real-time optimal control algorithm. As a software implementable technique for reducing power consumption, the RTOC has two very desirable traits supporting rapid prototyping and ultimately widespread dissemination. First, very little capital is required for implementation. No major infrastructure modifications are required and there is no need to purchase expensive capital equipment. Second, the RTOC can be rolled out incrementally. Therefore, the effectiveness can be proven without a large scale initial roll out. Through the use of the Impact Projections Model provided by the DOE, monetary savings in excess of $100M in 2020 and billions by 2040 are predicted. In terms of energy savings, the model predicts a primary energy displacement of 260 trillion BTUs (33 trillion kWh), or a 50% reduction in server power consumption. The model also predicts a corresponding reduction of pollutants such as SO2 and NOx in excess of 100,000 metric tonnes assuming the RTOC is fully deployed. While additional development and prototyping is required to validate these predictions, the relative low cost and ease of implementation compared to large capital projects makes it an ideal candidate for further investigation.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2015

Mass Spectrometry Imaging of Biological Tissue: An Approach for Multicenter Studies

Mass spectrometry imaging has become a popular tool for probing the chemical complexity of biological surfaces. This led to the development of a wide range of instrumentation and preparation protocols. It is thus desirable to evaluate and compare the data output from different methodologies and mass spectrometers. Here, we present an approach for the comparison of mass spectrometry imaging data from different laboratories (often referred to as multicenter studies). This is exemplified by the analysis of mouse brain sections in five laboratories in Europe and the USA. The instrumentation includes matrix-assisted laser desorption/ionization (MALDI)-time-of-flight (TOF), MALDI-QTOF, MALDIFourier transform ion cyclotron resonance (FTICR), atmospheric-pressure (AP)-MALDI-Orbitrap, and cluster TOF-secondary ion mass spectrometry (SIMS). Experimental parameters such as measurement speed, imaging bin width, and mass spectrometric parameters are discussed. All datasets were converted to the standard data format imzML and displayed in a common open-source software with identical parameters for visualization, which facilitates direct comparison of MS images. The imzML conversion also allowed exchange of fully functional MS imaging datasets between the different laboratories. The experiments ranged from overview measurements of the full mouse brain to detailed analysis of smaller features (depending on spatial resolution settings), but common histological features such as the corpus callosum were visible in all measurements. High spatial resolution measurements of AP-MALDI-Orbitrap and TOF-SIMS showed comparable structures in the low-micrometer range. We discuss general considerations for planning and performing multicenter studies in mass spectrometry imaging. This includes details on the selection, distribution, and preparation of tissue samples as well as on data handling. Such multicenter studies in combination with ongoing activities for reporting guidelines, a common data format (imzML) and a public data repository can contribute to more reliability and transparency of MS imaging studies.

Environmental Molecular Sciences Laboratory↗
DOE OSTI2024

Grid Optimization Competition Challenge 3 Problem Formulation

This report contains the problem formulation for the Grid Optimization (GO) Competition Challenge 3. The Grid Optimization Competition is run by a team of researchers from a number of organizations, including the sponsor Advanced Research Projects Agency - Energy (ARPA-E), lead organization Pacific Northwest National Laboratory (PNNL), and technical contributors from Los Alamos National Laboratory (LANL), National Renewable Energy Laboratory (NREL), Texas A&M University (TAMU), Georgia Institute of Technology (GT), University of Wisconsin (UW), and others. The GO Competition poses challenge problems in the field of power grid management, invites entrants to develop solvers for these problems, invokes the solvers on a set of problem instances using common hardware, ranks the solvers according to their performance, and awards prizes according to the rankings. The overall goal of the GO Competition is to spur innovative research on high impact and computationally challenging problems in power grid management from initial development through commercial deployment. Complete information about the GO Competition can be found online at [2]. The webpage covers previous Challenges, rules, timeline, registration information, data formats, scoring methods, computational platform information, information on supported solvers and languages, sponsor information, frequently asked questions, administrator contact information, publicly available problem instances, computer code for reading and evaluating problem and solution data, a sandbox for testing solvers, and a solver submission interface, results, and publications.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2018

A New Approach for Short-Term Solar Radiation Forecasting Using the Estimation of Cloud Fraction and Cloud Albedo

Solar generation is an increasing part of the energy portfolio in the United States. An accurate forecast of the available solar resource and power is essential to managing the electric grid, market operations, and reducing the cost of solar energy. High-frequency forecasts of solar radiation in intra-hour horizons is important for real-time electric power system energy management, especially at the distribution level. Conventional Numerical Weather Prediction models perform poorly in intra-hour, high-frequency forecasts because of the limits on real-time computing, spatial resolution, and infrequent availability of observations. Although a number of alternative technologies, e.g., time-series analysis and machine learning, have been used to fill this gap, the smart persistence model is among the top-performing models in short-term forecasting and therefore often serves as the baseline to evaluate other forecasting models. Although the smart persistence model often serves as the baseline model in these intra-hour forecasts, obvious uncertainties exist in the current smart persistence model: (1) clear-sky index does not respond to the variation of the solar incident angle when cloud conditions are persistent within the forecast horizon, and (2) cloud coverage is inherently persistent though it is constrained by cloud advection. In this study, we developed a Physics-Based Smart Persistence Model for Intra-Hour Solar Forecasting (PSPI) that integrates cloudy property estimation, a radiative transfer model, and cloud fraction forecasts to improve the performance of the smart persistence model. Compared to the smart persistence model, PSPI does not require additional observations of various atmospheric parameters past global horizontal irradiance, but it is customizable because additional observations, if available, can be ingested to further improve the forecast. Our results show that the PSPI outperforms the persistence and smart persistence model on 5-minute, 15-minute, and 30-minute forecast horizons. The software package of PSPI is flexible to users' needs and provides low computational time to run at site-specific locations across the continental United States.

14 SOLAR ENERGY↗
DOE OSTI2024

Final Technical Report - Rapid Surface Microanalysis using a Low Temperature Plasma

This project focused on improving our current understanding and scientific knowledge in the area of plasma-surface interactions and plasma assisted material synthesis related to advanced microelectronics and nanotechnology. Current challenges include: controlling the interaction of Low Temperature Plasma (LTP) with a single layer of atoms to manufacture integrated circuits, continued miniaturization of integrated circuits, LTP processing of material surfaces and thin films to enable industrial scale fabrication of advanced microelectronics, synthesis of new materials, nanomaterials, nanotubes, and complex materials, Technology developed in this subtopic is of value to either (i) enable scans of surfaces (~1 sq. cm area) using various microscopies (electron, optical, other) at high resolution (micron or sub-micron resolution) rapidly (hours or days rather than years to complete a high-resolution scan of such a large surface area), or (ii) enable scans of surfaces (~1 sq. cm area) using various microscopies (electron, optical, other) at relatively low resolution rapidly, then apply algorithms to select spots for micron-scale imaging. Sputtering occurs when particles of a solid material are ejected from its surface by energetic particles from a plasma. While the degradation of the solid material and the subsequent deposition of the ejected material onto vulnerable surfaces are the usual subjects of sputtering studies, plasma science has yet to be combined with sputtering to create new diagnostics devices and systems. Small changes in the design of the plasma discharge device make it possible to create broad plasma beams for rapid scanning or small plasma beams to obtain the distribution of ejected elements with micron resolution. In the high-resolution use, the ion flux is extracted from the gas-discharge plasma and focused by a spherical emission surface to micron sizes onto the target specimen, providing very local sputtering and local elemental analysis. We call this “self-focusing”. The radiation from the excited and ionized sputtered atoms is recorded by a spectrometer through a window and fiberglass cable and analyzed with standard software packages used for optical glow discharge spectroscopy. Computer simulations of beam formation were used to verify and optimize the designs to be tested. A prototype was designed, constructed, and used to start experiments of beam formation.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2015

Sequencing of 15 622 gene-bearing BACs clarifies the gene-dense regions of the barley genome

Barley ( Hordeum vulgare L.) possesses a large and highly repetitive genome of 5.1 Gb that has hindered the development of a complete sequence. In 2012, the International Barley Sequencing Consortium released a resource integrating whole-genome shotgun sequences with a physical and genetic framework. However, because only 6278 bacterial artificial chromosome (BACs) in the physical map were sequenced, fine structure was limited. To gain access to the gene-containing portion of the barley genome at high resolution, we identified and sequenced 15 622 BACs representing the minimal tiling path of 72 052 physical-mapped gene-bearing BACs. This generated ~1.7 Gb of genomic sequence containing an estimated 2/3 of all Morex barley genes. Exploration of these sequenced BACs revealed that although distal ends of chromosomes contain most of the gene-enriched BACs and are characterized by high recombination rates, there are also gene-dense regions with suppressed recombination. We made use of published map-anchored sequence data from Aegilops tauschii to develop a synteny viewer between barley and the ancestor of the wheat D-genome. Except for some notable inversions, there is a high level of collinearity between the two species. The software HarvEST:Barley provides facile access to BAC sequences and their annotations, along with the barley– Ae. tauschii synteny viewer. These BAC sequences constitute a resource to improve the efficiency of marker development, map-based cloning, and comparative genomics in barley and related crops. Additional knowledge about regions of the barley genome that are gene-dense but low recombination is particularly relevant.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

PowerModel-AI: A First On-the-Fly Machine-Learning Predictor for AC Power Flow Solutions

The real-time creation of machine-learning models via active or on-the-fly learning has attracted considerable interest across various scientific and engineering disciplines. These algorithms enable machines to build models autonomously while remaining operational. Through a series of query strategies, the machine can evaluate whether newly encountered data fall outside the scope of the existing training set. In this study, we introduce PowerModel-AI, an end-to-end machine learning software designed to accurately predict AC power flow solutions. We present detailed justifications for our model design choices and demonstrate that selecting the right input features effectively captures load flow decoupling inherent in power flow equations. Our approach incorporates on-the-fly learning, where power flow calculations are initiated only when the machine detects a need to improve the dataset in regions where the model’s suboptimal performance is based on specific criteria. Otherwise, the existing model is used for power flow predictions. This study includes analyses of five Texas A&M synthetic power grid cases, encompassing the 14-, 30-, 37-, 200-, and 500-bus systems. The training and test datasets were generated using PowerModels.jl, an open-source power flow solver/optimizer developed at Los Alamos National Laboratory, NM, USA.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

Application of Gaussian Bayes classifier to differentiate chlorine-based chemical agents

The Portable Isotopic Neutron Spectroscopy (PINS) is a commercialized system developed by Idaho National Laboratory (INL) to examine chemical warfare agents (CWA) non-destructively, utilizing Prompt Gamma Neutron Activation Analysis (PGNAA) techniques. The PINS system takes advantage of a high-resolution gamma-ray spectrum from a mechanically-cooled high-purity germanium (HPGe) detector. One of the difficult technical challenges is to discriminate the chlorine-based chemical agents. Especially, CN, CNB, CNS and CG have similar chemical compositions to make it hard to discriminate them with a higher confidence. Current identification algorithms for PINS systems with 252-Cf sources have been improved and updated continuously as more field data became available, and new algorithms was studied to complement the current algorithms by adopting the Gaussian Bayes classifier. These new algorithms were intended to be applied to a subset of chlorine-based chemical agents, and their main goal is discriminate CN, CNB, CNS and CG with their ratios of the chlorine neutron inelastic 1763keV peak to the chlorine thermal neutron capture 1959keV peak, which is referred to as the “Cl i/c” or “clic” ratio in this study. The Cl i/c ratios were assumed to follow Gaussian distributions with the means and the standard deviations unique to their corresponding chemical agents. The prior probabilities of these four chemical agents were optimized with a collection of field data to achieve the best performance in terms of precision or positive predictive value (PPV). Finally, their posterior probabilities as functions of the Cl i/c ratio were implemented in the current version of PINS analysis software in order to be tested with more field data.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗