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All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Source-to-Source Automatic Differentiation of OpenMP Parallel Loops

This article presents our work toward correct and efficient automatic differentiation of OpenMP parallel worksharing loops in forward and reverse mode. Automatic differentiation is a method to obtain gradients of numerical programs, which are crucial in optimization, uncertainty quantification, and machine learning. The computational cost to compute gradients is a common bottleneck in practice. For applications that are parallelized for multicore CPUs or GPUs using OpenMP, one also wishes to compute the gradients in parallel. Here, we propose a framework to reason about the correctness of the generated derivative code, from which we justify our OpenMP extension to the differentiation model. We implement this model in the automatic differentiation tool Tapenade and present test cases that are differentiated following our extended differentiation procedure. Performance of the generated derivative programs in forward and reverse mode is better than sequential, although our reverse mode often scales worse than the input programs.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2012

An Overview of Public Domain Tools for Measuring the Sustainability of Environmental Remediation - 12060

The application of sustainability principles to the investigation and remediation of contaminated sites is an area of rapid development within the environmental profession, with new business practices, tools, and performance standards for identifying, evaluating, and managing the 'collateral' impacts of cleanup projects to the environment, economy and society coming from many organizations. Guidelines, frameworks, and standards of practice for 'green and sustainable remediation' (GSR) have been released and are under development by the Sustainable Remediation Forum (SURF), the American Society for Testing Materials (ASTM), the Interstate Technology Roundtable Commission (ITRC) and other organizations in the U.S. and internationally. In response to Executive Orders from the President, Federal government agencies have developed policies, procedures and guidelines for evaluating and reporting the sustainability of their environmental restoration projects. Private sector companies in the petroleum, utility, manufacturing, defense, and other sectors are developing their own corporate GSR programs to improve day-to-day management of contaminated sites and to support external reporting as part of their corporate social responsibility (CSR) efforts. The explosion of mandates, policy, procedures and guidance raises the question of how to determine whether a remediation technology or cleanup approach is green and/or sustainable. The environmental profession has responded to this question by designing, developing and deploying a wide array of tools, calculators, and databases that enable regulatory agencies, site managers and environmental professionals to calculate the collateral impacts of their remediation projects in the environmental, social, and economic domains. Many of these tools are proprietary ones developed by environmental engineering/consulting firms for use in their consulting engagements and/or tailored specifically to meet the needs of their clients. When it comes to the public domain, Federal government agencies are spearheading the development of software tools to measure and report emissions of air pollutants (e.g., carbon dioxide, other greenhouse gases, criteria air pollutants); consumption of energy, water and natural resources; accident and safety risks; project costs and other economic metrics. Most of the tools developed for the Government are available to environmental practitioners without charge, so they are growing in usage and popularity. The key features and metrics calculated by the available public-domain tools for measuring the sustainability of environmental remediation projects share some commonalities but there are differences amongst the tools. The SiteWise{sup TM} sustainability tool developed for the Navy and US Army will be compared with the Sustainable Remediation Tool (SRT{sup TM}) developed for the US Air Force (USAF). In addition, the USAF's Clean Solar and Wind Energy in Environmental Programs (CleanSWEEP), a soon-to-be-released tool for evaluating the economic feasibility of utilizing renewal energy for powering remediation systems will be described in the paper. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2018

Multifamily Tool for Energy Audits (MulTEA) Engineering Manual (Version 1)

The Multifamily Tool for Energy Audits (MulTEA) is an energy audit tool designed to provide auditors with an improved energy simulation tool for multifamily buildings and an improved tool for identifying cost-effective energy-efficiency retrofit measures for multifamily buildings. MulTEA is designed specifically to help states and local weatherization agencies implement the Department of Energy (DOE) Weatherization Assistance Program. MulTEA was developed jointly by the Oak Ridge National Laboratory (ORNL) and the Lawrence Berkeley National Laboratory (LBNL). MulTEA is part of ORNL’s web-based Weatherization Assistant suite of audit tools (https://weatherization.ornl.gov/softwaredescription/). The energy calculation engine including the DOE- 2 simulation model and supplementary calculation modules is shared by MulTEA and LBNL’s Home Energy Saver pro (HESpro) (http://hespro.lbl.gov/pro/). On the ORNL side, the energy calculation engine is coupled with a user interface and output reporting capabilities based on Weatherization Assistance Program regulations and guidelines pertinent to MulTEA. On the LBNL side, the same engine will be used in HESpro to expand it to handle multifamily buildings. MulTEA is designed to address small and large multifamily buildings with decentralized and centralized heating, ventilation, and air-conditioning (HVAC) and domestic hot water (DHW) systems. Version 1 of MulTEA addresses small multifamily buildings with decentralized HVAC systems, and decentralized or centralized DHW systems. The capability to model large buildings and centralized HVAC systems will be incorporated in Version 2.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2017

Final Technical Report for Automated Manufacturing of Innovative CPV/PV Modules

Cogenra’s Dense Cell Interconnect system was designed to use traditional front-contact cells and string them together into high efficiency and high reliability “supercells”. This novel stringer allows one to take advantage of the ~100 GW/year of existing cell production capacity and create a solar product for the customer that will produce more power and last longer than traditional PV products. The goal for this program was for Cogenra Solar to design and develop a first-of-kind automated solar manufacturing line that produces strings of overlapping cells or “supercells” based on Cogenra’s Dense Cell Interconnect (DCI) technology for their Low Concentration Photovoltaic (LCPV) systems. This will enable the commercialization of DCI technology to improve the efficiency, reliability and economics for their Low Concentration Photovoltaic systems. In this program, Cogenra Solar very successfully designed, developed, built, installed, and started up the ground-breaking manufacturing tools required to assemble supercells. Cogenra then successfully demonstrated operation of the integrated line at high yield and throughput far exceeding expectations. The development of a supercell production line represents a critical step toward a high volume and low cost Low Concentration Photovoltaic Module with Dense Cell Interconnect technology and has enabled the evaluation of the technology for reliability and yield. Unfortunately, performance and cost headwinds on Low Concentration Photovoltaics systems including lack of diffuse capture (10-15% hit) and more expensive tracker requirements resulted in a move away from LCPV technology. Fortunately, the versatility of Dense Cell Interconnect technology allows for application to flat plate module technology as well and Cogenra has worked with the DOE to utilize the learning from this grant to commercialize DCI technology for the solar market through the on-going grant: Catalyzing PV Manufacturing in the US With Cogenra Solar’s Next-Generation Dense Cell Interconnect PV Module Manufacturing Technology. This program is now very successfully building off of this work and commercializing the technology to enable increased solar adoption.

14 SOLAR ENERGY↗
DOE OSTI2018

Alcator C-Mod (Final Technical Report)

Alcator C-Mod is the third in a series of compact high-field tokamaks built and operated on the MIT campus, the first to incorporate advanced shaping and poloidal divertors. For most of its 23 year operational history, C-Mod was the only diverted tokamak in the world program exclusively using all metal high-Z plasma facing components, and the only diverted tokamak able to operate at and above the magnetic field strength of ITER, and for many other burning plasma tokamak designs. The C-Mod facility also exclusively used RF waves for non-inductive heating and current drive, highly relevant to burning plasma applications and likely to be the main such tools in any commercial tokamak power reactor. A comprehensive summary of the key technical accomplishments from the C-Mod program is published in the review paper, M. Greenwald, et al., Phys. Plasmas 21(2014)110501. This final report contains a brief overview of those results, along with updates covering the final 3 years of operation, through September 2016. Ongoing analysis and modeling based on the archive of Alcator C-Mod data continues to provide new results, and this can be expected to continue for many years to come.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

GEOPHIRES v2.0

GEOPHIRES v2.0 is a geothermal techno-economic simulation tool upgraded from GEOPHIRES v1.2. The name stands for "GEOthermal energy for Production of Heat and electricity (“IR”) Economically Simulated". GEOPHIRES combines reservoir, wellbore, and surface plant technical models with cost correlations and levelized cost models to estimate the capital and operation and maintenance costs, instantaneous and lifetime energy production, and overall levelized cost of energy of a geothermal plant. In addition to electricity generation, direct-use heat applications and combined heat and power or cogeneration can be modeled. Various upgrades have been implemented to develop GEOPHIRES v2.0, including: updating the built-in cost correlations, coupling to the external reservoir simulator TOUGH2, enhancing the built-in wellbore simulator, converting the programming language to Python, and making the code open-source. Users are encouraged to build upon the tool, e.g. by implementing their own correlations or coupling to other simulators.

Beckers, Koenraad↗
DOE OSTI2012

North American Carbon Project (NACP) Regional Interim Synthesis: Terrestrial Biospheric Model Intercomparison

Understanding of carbon exchange between terrestrial ecosystems and the atmosphere can be improved through direct observations and experiments, as well as through modeling activities. Terrestrial biosphere models (TBMs) have become an integral tool for extrapolating local observations and understanding to much larger terrestrial regions. Although models vary in their specific goals and approaches, their central role within carbon cycle science is to provide a better understanding of the mechanisms currently controlling carbon exchange. Recently, the North American Carbon Program (NACP) organized several interim-synthesis activities to evaluate and inter-compare models and observations at local to continental scales for the years 2000 to 2005. Here, we compare the results from the TBMs collected as part of the regional and continental interim-synthesis (RCIS) activities. The primary objective of this work is to synthesize and compare the 19 participating TBMs to assess current understanding of the terrestrial carbon cycle in North America.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

2014 SRNL LDRD Annual Report, Rev. 0

Laboratory Directed Research and Development is a congressionally authorized program that provides the ‘innovation inspiration’ from which many of the Laboratory’s multi-discipline advancements are made in both science and engineering technology. The program is the backbone for insuring that scientific, technical and engineering capabilities can meet current and future needs. It is an important tool in reducing the probability of technological surprise by allowing laboratory technical staff room to innovate and keep abreast of scientific breakthroughs. Drawing from the synergism among the EM and NNSA missions, and work from other federal agencies ensures that LDRD is the key element in maintaining the vitality of SRNL’s technical programs. The LDRD program aims to position the Laboratory for new business in clean energy, national security, nuclear materials management and environmental stewardship by leveraging the unique capabilities of the Laboratory to yield foundational scientific research in core business areas, while aligning with SRS strategic initiatives and maintaining a vision for ultimate DOE applications.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2014

Evaluation of Application Space Expansion for the Sensor Fish

The Pacific Northwest National Laboratory has developed an instrument known as the sensor fish that can be released into downstream passage routes at hydropower facilities to collect data on the physical conditions that a fish might be exposed to during passage through a turbine. The US Department of Energy Wind and Water Power Program sees value in expanding the sensor fish application space beyond large Kaplan turbines in the northwest United States to evaluate conditions to which a greater variety of fish species are exposed. Development of fish-friendly turbines requires an understanding of both physical passage conditions and biological responses to those conditions. Expanding the use of sensor fish into other application spaces will add to the knowledge base of physical passage conditions and could also enhance the use of sensor fish as a site-specific tool in mitigating potential impacts to fish populations from hydropower. The Oak Ridge National Laboratory (ORNL) National Hydropower Assessment Program (NHAAP) database contains hydropower facility characteristics that, along with national fish distribution data, were used to evaluate potential interactions between fish species and project characteristics related to downstream passage issues. ORNL developed rankings for the turbine types in the NHAAP database in terms of their potential to impact fish through injury or mortality during downstream turbine passage. National-scale fish distributions for 31 key migratory species were spatially intersected with hydropower plant locations to identify facilities where turbines with a high threat to fish injury or mortality overlap with the potential range of a sensitive fish species. A dataset was produced that identifies hydropower facilities where deployment of the sensor fish technology might be beneficial in addressing issues related to downstream fish passage. The dataset can be queried to target specific geographic regions, fish species, license expiration dates, generation capacity levels, ownership characteristics, turbine characteristics, or any combination of these metrics.

13 HYDRO 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 OSTI2025

Selection Algorithm Improvement for MicroBooNE

Data selection is an extremely important part of data analysis for any experiment. Finding a physics result is often the result of sifting through a massive amount of data, keeping data that we believe to be signal and throwing out data we do not. This process is called data selection. Creating a selection algorithm is an intensive process that must balance keeping enough data to have statistics and maximizing the signal purity of that data. In this study, we used three different reconstruction tools, Pandora, WireCell, and LANTERN, for the MicroBooNE experiment in conjunction to improve the selection algorithm for analysis. For the case of this study, we look into the charged current N proton 0 pions (CCNp0$\pi$) interaction channel. This is the dominant channel for the Short Baseline Neutrino (SBN) program and is expected to be a large contributor to the Deep Underground Neutrino Experiment (DUNE). We first investigated each of the three tools to find out more about their strengths and weaknesses as reconstructions. We then put together a direct comparison of the three methods to find which method or combination of methods would return the best result for us. While the study is ongoing, we have learned a lot about data selection for the experiment and the differences between the reconstruction tools.

Dillon, Brayden [Michigan State U.]↗
DOE OSTI2025

Data Selection Improvement For MicroBooNE

Data selection is an extremely important part of data analysis for any experiment. Finding a physics result is often the result of sifting through a massive amount of data, keeping data that we believe to be signal, and throwing out data we do not. This process is called data selection. Creating a selection algorithm is an intensive process that must balance keeping enough data to have statistics and maximizing the signal purity of that data. We also need to choose the right reconstruction method, a tool to take raw data from the detector and convert it into physics results. In this study, we used three different reconstruction tools, Pandora, WireCell, and LANTERN, for the MicroBooNE experiment in conjunction to improve the selection algorithm for analysis. For the case of this study, we look into the charged current N proton 0 pions (CCNp0$\pi$) interaction channel. This is the dominant channel for the Short Baseline Neutrino (SBN) program and is expected to be a large contributor to the Deep Underground Neutrino Experiment (DUNE). We first investigated each of the three tools to find out more about their strengths and weaknesses as reconstructions, and compared them to the truth information directly from the MicroBooNE simulation pipeline. We then put together a direct comparison of the three methods to find which method or combination of methods would return the best result for us. While the study is ongoing, we have learned a lot about data selection for the experiment and the differences between the reconstruction tools.

Dillon, Brayden [Fermilab]↗
DOE OSTI2023

Federal Automotive Statistical Tool: Federal Vehicle Fleet Reporting Update (Combined FedFleet/FEVAR/INTERFUEL Meeting, November 2023) [Slides]

This presentation presents an overview of coming changes to how federal agencies with motor vehicles will submit required information about the electric vehicle supply equipment (EVSE) inventory and planned deployments through the Federal Automotive Statistical Tool (FAST), as well as updates on fleet reporting in general. This presentation is intended for delivery via WebEx/GoToMeeting at the November 2023 meeting of the DOE/GSA jointly-organized combined meeting of the Federal Electric Vehicle Agency Round-table (FEVAR), FedFleet, and INTERFUEL working groups. FAST is a web-based information management tool developed and maintained by Idaho National Laboratory and funded by GSA's Office of Government-wide Policy and DOE's Federal Energy Management Program.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2023

Federal Automotive Statistical Tool: Updates to EVSE Reporting (Federal Electric Vehicle Agency Round-table, October 2023) [Slides]

This presentation presents an overview of coming changes to how federal agencies with motor vehicles will submit required information about the electric vehicle supply equipment (EVSE) inventory and planned deployments through the Federal Automotive Statistical Tool (FAST). This presentation is intended for delivery via WebEx/GoToMeeting at the October 2023 meeting of the DOE-organized Federal Electric Vehicle Agency Round-table (FEVAR). FAST is a web-based information management tool developed and maintained by Idaho National Laboratory and funded by GSA's Office of Government-wide Policy and DOE's Federal Energy Management Program.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2022

The E3SM Diagnostics Package (E3SM Diags v2.7): a Python-based diagnostics package for Earth system model evaluation

Abstract. The E3SM Diagnostics Package (E3SM Diags) is a modern, Python-based Earth system model (ESM) evaluation tool (with Python module name e3sm_diags), developed to support the Department of Energy (DOE) Energy Exascale Earth System Model (E3SM). E3SM Diags provides a wide suite of tools for evaluating native E3SM output, as well as ESM data on regular latitude–longitude grids, including output from Coupled Model Intercomparison Project (CMIP) class models. E3SM Diags is modeled after the National Center for Atmospheric Research (NCAR) Atmosphere Model Working Group (AMWG, 2022) diagnostics package. In its version 1 release, E3SM Diags included a set of core essential diagnostics to evaluate the mean physical climate from model simulations. As of version 2.7, more process-oriented and phenomenon-based evaluation diagnostics have been implemented, such as analysis of the quasi-biennial oscillation (QBO), the El Niño–Southern Oscillation (ENSO), streamflow, the diurnal cycle of precipitation, tropical cyclones, ozone and aerosol properties. An in situ dataset from DOE's Atmospheric Radiation Measurement (ARM) program has been integrated into the package for evaluating the representation of simulated cloud and precipitation processes. This tool is designed with enough flexibility to allow for the addition of new observational datasets and new diagnostic algorithms. Additional features include customizable figures; streamlined installation, configuration and execution; and multiprocessing for fast computation. The package uses an up-to-date observational data repository maintained by its developers, where recent datasets are added to the repository as they become available. Finally, several applications for the E3SM Diags module were introduced to fit a diverse set of use cases from the scientific community.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Hydropower flexibility valuation tool for flow requirement evaluation

Timing of generation is becoming more and more valuable. This creates greater potential tension between environmental and power system objectives since both systems require their own flow patterns. Identifying win–win outcomes in this context requires being able to discuss the value of flexibility across stakeholder groups. This research proposes a two-stage optimization method to understand hydropower flexibility to meet both environmental and power system requirements. The tool simulates the two-settlement market process in the U.S. by maximizing revenues from both the day-ahead and real-time markets, subject to plant operational limits, regulatory flow and ramping requirements, and uncertainties associated with water availability and market prices. The model is formulated as linear programming problems and solved using IBM ILOG CPLEX optimizer. By examining a range of flow requirements, ramping constraints, and storage capacities, the proposed tool shows how to make more informed decisions to weigh the cost of specific flow requirements in the context of the overall license requirements. Results from the case study show that revenue is more sensitive to the ramping constraints than the minimum flow constraints. We also demonstrate that removing flow constraints in a dry month increases monthly revenue by up to 118%, as opposed to only 1% in a wet month. In addition, our results suggest that using a learning-based water flow forecast results in an increase of monthly revenue up to 6.4% compared with persistence forecast.

13 HYDRO ENERGY↗
DOE OSTI2021

Ring Model Development and Validation for Prismatic HTGR Core Thermal-hydraulics and Safety Analysis

Because of the complex core geometry, prismatic high temperature gas-cooled reactors (prismatic HTGRs) often exhibit complex thermal fluid behaviors during both normal operating and transient conditions. Most HTGR designs rely on passive safety system for decay heat removal, such as the reactor cavity cooling system (RCCS). During postulated accidents like Pressurized Conduction Cooldown (PCC) event, the decay heat is first radially transferred from the core region to the reactor vessel outer surface, then to the RCCS cooling panels. The peak fuel temperature is controlled by heat transfer mechanisms with two distinctive characteristic length scales, i.e., the core-wise effective heat conduction and local heat conduction in the fuel pellet scale. As both length scales are essential to determine the fuel temperature, from the modeling perspective, computer codes must be able to capture heat transfer in both scales. This is challenging for both computational fluid dynamics (CFD) tools because of extremely large amount of computation resources required, and for system analysis codes because of the challenge to model the complex core geometry. Under the support of DOE-NE’s Nuclear Energy Advanced Modeling and Simulation (NEAMS) program, efforts have been pursued to support HTGR technology development and its modeling and simulation needs. There is a particular need for advanced modeling and simulation tools to predict thermal-fluid behavior during safety-related transients. In our previous studies, the ring model was adopted in SAM and further developed to simulate the normal operating condition and a PCC event using the MHTGR-350 design of General Atomics as the reference design. This current work represents a continuation of these previous efforts, and the focus is to critically review and examine simplifications and assumptions made to develop the ring model, and to perform code validation using experimental data from an integral-effect test facility, the High Temperature Test Facility (HTTF) at the Oregon State University. In this study, the test PG-27 from the HTTF test suite was selected for code validation purpose. The test PG-27 is a transient test designed to simulate the PCC event of the MHTGR design. Very good agreements between SAM prediction and experimental measurements were found in both coolant and solid structure temperatures during the transient.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2013

The National Center for Radioecology (NCoRE): A Network of Excellence for Environmental and Human Radiation Risk Reduction - 13365

Radioecology in the United States can be traced back to the early 1950's when small research programs were established to address the fate and effects of radionuclides released in the environment from activities at nuclear facilities. These programs focused primarily on local environmental effects, but global radioactive fallout from nuclear weapons testing and the potential for larger scale local releases of radioisotopes resulted in major concerns about the threat, not only to humans, but to other species and to ecosystems that support all life. These concerns were shared by other countries and it was quickly recognized that a multi-disciplinary approach would be required to address and understand the implications of anthropogenic radioactivity in the environment. The management, clean-up and long-term monitoring of legacy wastes at Department of Energy (DOE), Department of Defense (DOD), and Nuclear Regulatory Commission (NRC)-regulated facilities continues to be of concern as long as nuclear operations continue. Research conducted through radioecology programs provides the credible scientific data needed for decision-making purposes. The current status of radioecology programs in the United States are: fragmented with little coordination to identify national strategies and direct programs; suffering from a steadily decreasing funding base; soon to be hampered by closure of key infrastructure; hampered by aging and retiring workforce (loss of technical expertise); and in need of training of young scientists to ensure continuation of the science (no formal graduate education program in radioecology remaining in the U.S.). With these concerns in mind, the Savannah River National Laboratory (SRNL) took the lead to establish the National Center for Radioecology (NCoRE) as a network of excellence of the remaining radioecology expertise in the United States. As part of the NCoRE mission, scientists at SRNL are working with six key partner universities to re-establish a graduate education training program for radioecology. Recently, NCoRE hosted a workshop to identify the immediate needs for science-driven discoveries, tool development and the generation of scientific data to support the legislative decision-making process for remediation strategies, long-term monitoring of radiologically- contaminated sites and protection of human health and the environment. Some of the immediate strategic research needs were identified in the fields of functional genomics for determining low-dose effects, improved low-level dosimetry, and mixed (radiological and chemical) contaminant studies. Longer term strategic research and tool development areas included development of radioecology case study sites, comprehensive decision-making tools, consequence response actions, and optimized scenario based ecosystem modeling. A summary of the NCoRE workshop findings related to waste management needs and priority areas will be presented in this paper. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗