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DOE OSTI2024

A New High-Impedance-Fault Detection Method to Prevent Power-Line-Induced Wildfires

High Impedance Faults (HIFs) occur when energized power lines come into contact with high impedance ground surfaces, such as tree branches and grassland. HIFs have the potential to cause arcing, leading to vegetation ignition and the initiation of wildfires. The challenge in detecting HIFs comes from the high impedance of the partially conductive materials in contact with the power lines. They create a fault current of low magnitude and traditional protective devices struggle to detect such faults. This paper proposes a novel HIF detection algorithm based upon the analyzed arcing signatures associated with HIFs. The algorithm is evaluated using the Australian Public Bushfire Safety Program (PBSP) dataset. For comparative analysis, a state-of-the-art commercial HIF detection product is also evaluated using the same dataset. The proposed algorithm demonstrates higher detection accuracy over the commercial products with fewer false flags and undetected faults.

grasslands↗

DOE OSTI2014

FutureGen 2.0 Monitoring Systems Design Basis and Technology Selection: Geohydrologic, Geochemical and Geophysical Considerations

Advances in carbon capture and storage (CCS) technology show promise for addressing carbon dioxide (CO 2 ) emissions and global climate change concerns related to coal-fueled energy. The FutureGen 2.0 Project is intended to demonstrate 1) the technical feasibility of oxy-combustion technology as an approach for implementing carbon capture at new and existing coal-fueled energy facilities, and 2) utility-scale integration of transport and permanent storage of captured CO 2 in a deep geologic formation. Development of the FutureGen 2.0 CO 2 storage site is part of a larger project to design, build, and operate a commercial-scale CCS system capable of capturing, treating, and storing the CO 2 off-gas from a 168-MW(e) gross capacity oxy-combustion coal-fueled power plant located in Meredosia, Illinois—a first-of-its-kind, near-zero emissions coal-fueled power plant with CCS. In cooperation with the U.S. Department of Energy, the FutureGen 2.0 project partners will repower a previously retired oil-fired power plant with oxy-combustion technology to capture approximately 1.1 million metric tons of CO 2 each year—more than 90 percent of the plant’s carbon emissions. Emissions such as sulfur oxides, nitrogen oxides, and mercury will be reduced to near-zero levels. Safe and proven pipeline technology will be used to transport the CO 2 to the storage site and inject it deep into the subsurface through a network of deep-injection wells for long-term storage through geologic sequestration. An evaluation that considered pertinent hydrologic, geochemical, and geophysical processes was performed during development of the testing and monitoring program for the FutureGen 2.0 project. This evaluation informed the technology screening process and, in conjunction with project- and regulation-driven monitoring objectives, was the basis for monitoring technology selection. A summary of the overall monitoring approach adopted by the FutureGen 2.0 project, and a detailed description of the testing and monitoring activities that the FutureGen Industrial Alliance, Inc. will undertake at the FutureGen 2.0 storage site near Jacksonville, Illinois, are documented in a project-maintained testing and monitoring plan. All testing and monitoring activities will be performed in accordance with Title 40 of the Code of Federal Regulations (CFR) Sections 146.89, 146.90, and 146.91 (40 CFR §146.89, 146.90, and 146.91) to verify that the storage site is operating as permitted and is not endangering any underground sources of drinking water (USDWs).

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2015

Fuel Cell Electric Vehicle Evaluation; NREL (National Renewable Energy Laboratory)

This presentation provides a summary of NREL's FY15 fuel cell electric vehicle evaluation project activities and accomplishments. It was presented at the U.S. Department of Energy Hydrogen and Fuel Cells Program 2015 Annual Merit Review and Peer Evaluation Meeting on June 10, 2015, in Arlington, Virginia.

30 DIRECT ENERGY CONVERSION↗

DOE OSTI2014

Event Tree Success Branch Modeling Approaches in SAPHIRE/SPAR

Standardized Plant Analysis Risk (SPAR) models are a set of linked fault tree/event tree PRA models that have been used by the Nuclear Regulatory Commission (NRC) to evaluate the risk of operations at U.S. nuclear power plants since 1990s. The models use the Systems Analysis Programs for Hands-on Integrated Reliability Evaluations (SAPHIRE) code developed by the NRC and Idaho National Laboratory (INL). Currently Version 8, SAPHIRE is a powerful software with advanced features to perform separated or integrated Level 1, Level 2, internal events, external events, at-power, and low power shutdown PRA [1]. One of its features is the availability of three different approaches to model the success branch of a top event in event tree: delete term, complement of system logic, and developed event. However, improper choosing and modeling success branch might yield unexpected and incorrect results. This paper will discuss the two most often used success branch modeling approaches, delete term and developed event, and provide recommendations for using proper approaches in different models. A potential SAPHIRE code enhancement is also proposed to address the adverse impact brought by the developed event approach.

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2012

Automated Comparison of Building Energy Simulation Engines [Slides]

This presentation describes the BEopt comparative test suite, which is a tool that facilitates the automated comparison of building energy simulation engines. It also demonstrates how the test suite is improving the accuracy of building energy simulation programs.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2019

Comparing High Performance Computing Accelerator Programming Models

Accelerator devices are becoming a norm in High Performance Computing (HPC). With more systems opting for heterogeneous architectures, portable programming models like OpenMP and OpenACC are becoming increasingly important. The SPEC ACCEL 1.2 benchmark suite consists of comparable benchmarks in OpenCL, OpenMP 4.5, and OpenACC 2.5 that can be used to evaluate the performance and support for programming models and frameworks on heterogeneous platforms. In this paper we go beneath the normative metric of performance times and look at the individual kernels to study the usage, strengths, and weaknesses of the two prevalent portable heterogeneous programming models, OpenMP and OpenACC. From our analysis we identify that benchmarks like MRI-Q, SP and BT have better performance using OpenACC, while benchmarks like MiniGhost, LBM and LBDC do consistently better with the OpenMP programming model across supercomputers like Titan, and Summit.We deep dive into the kernels of select four benchmarks to answer questions like: Where does the benchmark spend most of its cycles? What is the parallelization strategy used? Why is one programming model more performant than the other? By identifying the similarities and dierences we want to contrast between the benchmark implementation strategies in the SPEC ACCEL 1.2 benchmarks and provide more insights into the OpenMP and OpenACC programming models.

Pophale, Swaroop S.↗

DOE OSTI2016

Prospect evaluation of shallow I-35 reservoir of NE Malay Basin offshore, Terengganu, Malaysia

A potential accumulation of hydrocarbon that describes significant and conceivable drilling target is related to prospect. Possibility of success estimation, assuming discovery of hydrocarbons and the potential recoverable quantities range under a commercial development program are the basis of Prospect evaluation activities. The objective was to find the new shallow prospects in reservoir sandstone of I –Formation in Malay basin. The prospects in the study area are mostly consisting of faulted structures and stratigraphic channels. The methodology follows seismic interpretation and mapping, attribute analysis, evaluation of nearby well data i.e., based on well – log correlation. The petrophysical parameters analogue to nearby wells was used as an input parameter for volumetric assessment. Based on analysis of presence and effectiveness, the prospect has a complete petroleum system. Two wells have been proposed to be drilled near the major fault and stratigraphic channel in I-35 reservoir that is O-1 and O-2 prospects respectively. The probability of geological success of prospect O-1 is at 35% while for O-2 is 24%. Finally, for hydrocarbon in place volumes were calculated which concluded the best estimate volume for oil in O-1 prospect is 4.99 MMSTB and O-2 prospect is 28.70 MMSTB while for gas is 29.27 BSCF and 25.59 BSCF respectively.

58 GEOSCIENCES↗

DOE OSTI2013

Interlaboratory Evaluation of in Vitro Cytotoxicity and Inflammatory Responses to Engineered Nanomaterials: The NIEHS Nano GO Consortium

Background: Differences in interlaboratory research protocols contribute to the conflicting data in the literature regarding engineered nanomaterial (ENM) bioactivity. Objectives: Grantees of a National Institute of Health Sciences (NIEHS)-funded consortium program performed two phases of in vitro testing with selected ENMs in an effort to identify and minimize sources of variability. Methods: Consortium program participants (CPPs) conducted ENM bioactivity evaluations on zinc oxide (ZnO), three forms of titanium dioxide (TiO2), and three forms of multiwalled carbon nanotubes (MWCNTs). In addition, CPPs performed bioassays using three mammalian cell lines (BEAS-2B, RLE-6TN, and THP-1) selected in order to cover two different species (rat and human), two different lung epithelial cells (alveolar type II and bronchial epithelial cells), and two different cell types (epithelial cells and macrophages). CPPs also measured cytotoxicity in all cell types while measuring inflammasome activation [interleukin-1β (IL-1β) release] using only THP-1 cells. Results: The overall in vitro toxicity profiles of ENM were as follows: ZnO was cytotoxic to all cell types at ≥ 50 μ g/mL, but did not induce IL-1β. TiO2 was not cytotoxic except for the nanobelt form, which was cytotoxic and induced significant IL-1β production in THP-1 cells. MWCNTs did not produce cytotoxicity, but stimulated lower levels of IL-1β production in THP-1 cells, with the original MWCNT producing the most IL-1β. Conclusions: The results provide justification for the inclusion of mechanism-linked bioactivity assays along with traditional cytotoxicity assays for in vitro screening. In addition, the results suggest that conducting studies with multiple relevant cell types to avoid false-negative outcomes is critical for accurate evaluation of ENM bioactivity.

cell viability↗

DOE OSTI2023

The Uniform Methods Project: Smart Thermostat Evaluation Protocol

A smart thermostat is an internet-connected device that controls home heating, ventilation, and air-conditioning (HVAC) equipment and can automatically adjust temperature set points to optimize performance and achieve energy savings. Smart thermostat features often include two way communication, occupancy detection (such as geofencing and occupancy sensors), schedule learning, and seasonal optimization algorithms. Smart thermostats can control most conventional HVAC systems, including central air conditioners, heat pumps, and forced air furnaces. Several types of residential utility programs offer smart thermostats as replacements measures. Working with smart thermostat vendors, utilities can offer separate optimization programs to produce energy savings beyond those achieved by installing a smart thermostat. From an evaluation perspective, smart thermostat programs have several noteworthy features. First, the energy savings from a smart thermostat may change over the life of the device. As a smart thermostat is connected to the internet, original equipment manufacturers can update the thermostat software to improve the thermostat's energy efficiency. Likewise, users can adjust the thermostat settings and schedules over time in response to changes in weather, thermal comfort, energy prices, or preferences for energy efficiency. Additionally, many thermostat manufacturers offer seasonal optimization programs that recommend changes or make minor, automated adjustments to the thermostat settings to improve energy efficiency. These opt-in programs are now standard offerings for many smart thermostat manufacturers and provided at no additional cost to users. The potential for software updates and continuous optimization and the evolving nature of user interactions mean future energy savings may differ from first-year savings and the energy savings of smart thermostats may need to be evaluated more than once. Second, smart thermostats often have small unit energy savings relative to a home's total energy consumption, especially in comparison to whole- home retrofit programs. This can make it difficult to detect the smart thermostat savings in billing or advanced metering infrastructure (AMI) meter consumption data. For example, as cooling loads in many regions average about 20% of annual electricity consumption, smart thermostat savings of 10% of cooling energy use would equate to a 2% reduction in home electricity consumption. Evaluators should use regression analysis of whole-home billing consumption or advanced metering infrastructure (AMI) meter consumption data to evaluate smart thermostat savings because, as explained at greater length below , these data are usually available to evaluators and regression can control for the impacts of weather and other potentially confounding factors on a home's energy consumption. Finally, as with other energy efficiency programs, participation in smart thermostat programs is self-selective. As discussed at greater length below , smart thermostat participants tend to be, among other things, younger, higher-income, and more likely to adopt electric vehicles (EVs) and internet connected devices than nonparticipants. These differences are often unobservable to the evaluator and correlated with a home's energy consumption, creating the potential for bias in estimating savings. Due to the small unit savings of thermostats, errors and biases from self-selection that may not be very consequential when evaluating a whole- home retrofits (e.g., ±2% of home electricity consumption) can have a major impact when evaluating the savings and cost-effectiveness of smart thermostat programs. A percentage point change in the estimated savings could affect the cost-effectiveness of a program. This means it is important for evaluators to assess and to minimize the potential for error from selection bias in estimating smart thermostat program savings. The Uniform Methods Project provides model protocols for determining energy savings and demand reductions that result from specific energy efficiency measures implemented through state and utility programs. In most cases, the measure protocols are based on a particular option identified by the International Performance Verification and Measurement Protocol ; however, this work provides a more detailed approach to implementing that option. Each chapter is written by technical experts in collaboration with their peers, reviewed by industry experts, and subject to public review and comment. The UMP protocols can be used by utilities, program administrators, public utility commissions, evaluators, and other stakeholders for both program planning and evaluation.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2019

Empirical Validation of Building Energy Modeling using Flexible Research Platform

Recently, efforts have been made to provide reliable empirical data for ANSI/ASHRAE Standard 140, Standard Method of Test for the Evaluation of Building Energy Analysis Computer Programs, to enable improved accuracy of building energy model (BEM) engines and improved characterization of their accuracy. The motivation for this effort is that the use of reliable empirical validation data sets in the evaluation of building energy modeling tools will lead to more consistent and validated simulation engines across all software vendors. This would expedite the use of building energy modeling in designing new buildings and retrofitting existing buildings, which delivers more energy efficient buildings.As part of a three-year multi-lab empirical validation project sponsored by U.S. DOE, this research project generated cooling season test plans by reviewing ASHRAE Standard 140, and the tests were performed based on the test plan. Finally, the experimental data sets were compared with the EnergyPlus model to demonstrate the validation procedure.

Im, Piljae↗

DOE OSTI2022

Effects of Supplementation in Upper Yakima River Chinook Salmon

Abstract To promote recovery of natural salmonid populations, managers are utilizing hatchery supplementation programs to increase abundance of spawners on the spawning grounds. However, studies have provided evidence that captive breeding can result in domestication, demonstrated by lower fitness of hatchery‐origin compared with natural‐origin fish. Supplementation programs, therefore, typically use natural‐origin broodstock in an effort to minimize long‐term negative fitness impacts. Here we evaluated the upper Yakima River spring supplementation program for Chinook Salmon Oncorhynchus tshawytscha , which has broodstock comprised exclusively of unmarked fish presumed to be of natural‐origin. Using 5 years of spawner data, we tested for effects of hatchery breeding and rearing on total adult returns and their individual reproductive success when spawning naturally. Our study revealed that supplementation increased overall abundance of fish spawning naturally on the spawning grounds. However, on average, compared with natural‐origin spawners, hatchery‐origin fish had reduced reproductive success, which also translated to reduced reproductive success in three out of five return years for natural‐origin fish that spawned with hatchery‐origin fish. As expected, body length and return timing were also significant predictors of reproductive success. However, more generations of data are needed to establish the extent to which reduced reproductive success is passed on to naturally produced progeny.

Koch, Ilana J.↗

DOE OSTI2017

Frequency Domain Reflectometry NDE for Aging Cables in Nuclear Power Plants

Cable insulation polymers are among the more susceptible materials to age-related degradation within a nuclear power plant. This is recognized by both regulators and utilities, so all plants have developed cable aging management programs to detect damage before critical component failure in compliance with regulatory guidelines. Although a wide range of tools are available to evaluate cables and cable systems, cable aging management programs vary in how condition monitoring and nondestructive examinations are conducted as utilities search for the most reliable and cost-effective ways to assess cable system condition. Frequency domain reflectometry (FDR) is emerging as one valuable tool to locate and assess damaged portions of a cable system with minimal cost and only requires access in most cases to one of the cable terminal ends. Since laboratory studies to evaluate the use of FDR for inspection of aged cables can be expensive and data interpretation may be confounded by multiple factors which influence results, a model-based approach is desired to parametrically investigate the effect of insulation material damage in a controlled manner. This work describes development of a physics-based FDR model which uses finite element simulations of cable segments in conjunction with cascaded circuit element simulations to efficiently study a cable system. One or more segments of the cable system model have altered physical or electrical properties which represent the degree of damage and the location of the damage in the system. This circuit model is then subjected to a simulated FDR examination. The modeling approach is verified using several experimental cases and by comparing it to a commercial simulator suitable for simulation of some cable configurations. The model is used to examine a broad range of parameters including defect length, defect profile, degree of degradation, number and location of defects, FDR bandwidth, and addition of impedance-matched extensions to minimize the end-shadow effect.

Cable Inspection, Frequency Domain Reflectometry↗

DOE OSTI2011

Ultra-scale Visualization Climate Data Analysis Tools (UV-CDAT)

This report summarizes work carried out by the Ultra-scale Visualization Climate Data Analysis Tools (UV-CDAT) Team for the period of January 1, 2011 through June 30, 2011. It discusses highlights, overall progress, period goals, and collaborations and lists papers and presentations. To learn more about our project, please visit our UV-CDAT website (URL: http://uv-cdat.org). This report will be forwarded to the program manager for the Department of Energy (DOE) Office of Biological and Environmental Research (BER), national and international collaborators and stakeholders, and to researchers working on a wide range of other climate model, reanalysis, and observation evaluation activities. The UV-CDAT executive committee consists of Dean N. Williams of Lawrence Livermore National Laboratory (LLNL); Dave Bader and Galen Shipman of Oak Ridge National Laboratory (ORNL); Phil Jones and James Ahrens of Los Alamos National Laboratory (LANL), Claudio Silva of Polytechnic Institute of New York University (NYU-Poly); and Berk Geveci of Kitware, Inc. The UV-CDAT team consists of researchers and scientists with diverse domain knowledge whose home institutions also include the National Aeronautics and Space Administration (NASA) and the University of Utah. All work is accomplished under DOE open-source guidelines and in close collaboration with the project's stakeholders, domain researchers, and scientists. Working directly with BER climate science analysis projects, this consortium will develop and deploy data and computational resources useful to a wide variety of stakeholders, including scientists, policymakers, and the general public. Members of this consortium already collaborate with other institutions and universities in researching data discovery, management, visualization, workflow analysis, and provenance. The UV-CDAT team will address the following high-level visualization requirements: (1) Alternative parallel streaming statistics and analysis pipelines - Data parallelism, Task parallelism, Visualization parallelism; (2) Optimized parallel input/output (I/O); (3) Remote interactive execution; (4) Advanced intercomparison visualization; (5) Data provenance processing and capture; and (6) Interfaces for scientists - Workflow data analysis and visualization construction tools, and Visualization interfaces.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2019

Annual Status Report (FY 2018): Composite Analysis for Low Level Waste Disposal in the Central Plateau of the Hanford Site

In accordance with U.S. Department of Energy (DOE) requirements in DOE M 435.1-1 Chg 11, and as implemented by DOE/RL-2000-292, the DOE Richland Operations Office has prepared this annual summary of the Hanford Site Composite Analysis for fiscal year (FY) 2018. The Hanford Site Composite Analysis was originally reported in PNNL-118003 and PNNL-11800, Addendum 14 (hereinafter referred to collectively as the Hanford Site Composite Analysis). The Hanford Site Composite Analysis was approved by a 2002 memorandum. As required by DOE/RL-2000-29, an annual evaluation of new information and data developed by a number of onsite programs was completed. The reporting period for this annual evaluation is FY 2018 (October 1, 2017, through September 30, 2018).