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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 577 records · Page 32
All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

Reliability and Geographic Trends of 50,000 Photovoltaic Systems in the USA: Preprint

This paper presents performance and reliability data from nearly 50,000 photovoltaic (PV) systems totaling 1.7 gigawatts installed capacity in the USA from 2009 to 2012 and their geographic trends. About 90% of the normal systems and about 85% of all systems, including systems with known issues, performed to within 10% or better of expected performance. Although considerable uncertainty may exist due to the nature of the data, hotter climates appear to exhibit some degradation not seen in the more moderate climates. Special causes of underperformance and their impacts are delineated by reliability category. Hardware-related issues are dominated by inverter problems (totaling less than 0.5%) and underperforming modules (totaling less than 0.1%). Furthermore, many reliability categories show a significant decrease in occurrence from year 1 to subsequent years, emphasizing the need for higher-quality installations but also the need for improved standards development. The probability of PV system damage because of hail is below 0.05%. Singular weather events can have a significant impact such as a single lightning strike to a transformer or the impact of a hurricane. However, grid outages are more likely to have a significant impact than PV system damage when extreme weather events occur.

14 SOLAR ENERGY↗
DOE OSTI2023

The importance of capturing power system operational details in resource adequacy assessments

Traditional methods for assessing the resource adequacy (RA) of a power system are becoming obsolete due to emerging trends such as the increasing deployment of variable renewable energy and storage. Consequently, analysts are recommending that RA be assessed using a Monte Carlo simulation approach that models chronological power system operations over many instances of possible operating conditions. However, this approach is necessarily more complex and computationally demanding, which is an obstacle to real-world implementation. Here, in this study, we investigate which operational details of power systems are important to capture in order to accurately evaluate a system's RA, versus details that add complexity but do not meaningfully affect RA results. To do so, we develop a probabilistic RA assessment framework by adapting an existing production cost model and apply it to a case study based on the IEEE Reliability Test System. Our results indicate that multi-year data, storage dispatch, and transmission limits are key details to incorporate. Accurate RA results can be obtained using non-economic dispatch strategies as long as they are coordinated with detailed operational strategies. We also demonstrate how popular expectation-based RA metrics can mask important differences in the characteristics of loss of load events.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2014

Interactive lung segmentation in abnormal human and animal chest CT scans

Purpose: Many medical image analysis systems require segmentation of the structures of interest as a first step. For scans with gross pathology, automatic segmentation methods may fail. The authors’ aim is to develop a versatile, fast, and reliable interactive system to segment anatomical structures. In this study, this system was used for segmenting lungs in challenging thoracic computed tomography (CT) scans. Methods: In volumetric thoracic CT scans, the chest is segmented and divided into 3D volumes of interest (VOIs), containing voxels with similar densities. These VOIs are automatically labeled as either lung tissue or nonlung tissue. The automatic labeling results can be corrected using an interactive or a supervised interactive approach. When using the supervised interactive system, the user is shown the classification results per slice, whereupon he/she can adjust incorrect labels. The system is retrained continuously, taking the corrections and approvals of the user into account. In this way, the system learns to make a better distinction between lung tissue and nonlung tissue. When using the interactive framework without supervised learning, the user corrects all incorrectly labeled VOIs manually. Both interactive segmentation tools were tested on 32 volumetric CT scans of pigs, mice and humans, containing pulmonary abnormalities. Results: On average, supervised interactive lung segmentation took under 9 min of user interaction. Algorithm computing time was 2 min on average, but can easily be reduced. On average, 2.0% of all VOIs in a scan had to be relabeled. Lung segmentation using the interactive segmentation method took on average 13 min and involved relabeling 3.0% of all VOIs on average. The resulting segmentations correspond well to manual delineations of eight axial slices per scan, with an average Dice similarity coefficient of 0.933. Conclusions: The authors have developed two fast and reliable methods for interactive lung segmentation in challenging chest CT images. Both systems do not require prior knowledge of the scans under consideration and work on a variety of scans.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

Closeout Report ARRA supplement to DE-FG02-08ER41546, 03/15/2010 to 03/14/2011 - Advanced Transfer Map Methods for the Description of Particle Beam Dynamics

The ARRA funds were utilized to acquire a cluster of high performance computers, consisting of one Altus 2804 Server based on a Quad AMD Opteron 6174 12C with 4 2.2 GHz nodes of 12 cores each, resulting in 48 directly usable cores; as well as a Relion 1751 Server using an Intel Xeon X5677 consisting of 4 3.46 GHz cores supporting 8 threads. Both systems run the Unix flavor CentOS, which is designed for use without need of updates, which greatly enhances their reliability. The systems are used to operate our COSY INFINITY environment which supports MPI parallelization. The units arrived at MSU in September 2010, and were taken into operation shortly thereafter.

43 PARTICLE ACCELERATORS↗
DOE OSTI2021

Resilient Information Architecture Platform for Smart Grid (RIAPS)

A number of emerging trends will substantially alter the operation and control of the electric grid over the next several decades. These trends include ensuring resiliency under severe weather events, increasing integration of renewable electricity generation, supporting changing electricity demand patterns, and the improving cost effectiveness of distributed energy resources. To address these challenges, the future “Smart Grid” management will need to transition from centralized to coordinated distributed control paradigm. Reliable operation of the Smart Grid depends on distributed intelligence realized through software applications that run on distributed computing devices attached to the power system to collect data and collaboratively manage resources. However, much of the existing software for Smart Grid-enabled devices is either proprietary or developed with custom solutions, which limits interoperability among the heterogeneous devices and hinders the ability to manage system-level reliability, security, and resiliency requirements. Additionally, this approach makes Smart Grid applications hard to maintain, evolve, verify, and replace; resulting in high development and deployment costs. Further development of the Smart Grid requires a reusable software base-layer to move from hard-coded functionality to a plug-and-play architecture capable of managing system-level objectives and constraints in addition to providing consistent common services across heterogeneous devices and applications. Vanderbilt University, in collaboration with North Carolina State University and Washington State University has developed a foundation ‘software platform’ for developing and deploying robust, reliable, effective and secure software applications for the Smart Grid. The Resilient Information Architecture Platform for the Smart Grid (RIAPS) provides core services for building effective and powerful smart grid applications. It offers unique services for real-time data dissemination, fault tolerance, and coordination across apps distributed over the network.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Investigations into EGR dilution tolerance in a pre-chamber ignited GDI engine

EGR is a useful means to improve fuel economy in spark-ignited gasoline engines, especially under part-load conditions by means of reducing throttling losses. There is also a significant reduction in NOx emissions due to the reduced peak cylinder temperatures. However, the ability of conventional spark ignition systems to reliably ignite dilute mixtures limits the dilution tolerance due to the onset of combustion instability. In this study, an active pre-chamber system was evaluated at part load condition with various EGR rates using a regular grade full boiling range gasoline. A premixed air-fuel mixture was supplied to the pre-chamber, which assists in scavenging the residual mass fractions to enable reliable ignition of EGR dilute mixtures in the main combustion chamber. A range of pre-chamber injection, air-fuel mixture formulation, and ignition timing strategies were evaluated during the EGR sweeps. In addition, 0-D and 1-D simulations were conducted in GT-Power to assess the thermodynamic state and composition in the pre-chamber, as well as estimate the jet momentum at the various dilution rates. The active pre-chamber extended the EGR dilution limit from 20% for conventional SI to above 30%, with a higher pre-chamber flow rate (more scavenging) resulting in increased combustion stability. A tradeoff between the jet momentum and spark timing was observed when analyzing the GT-Power simulations and the pre-chamber jet momentum was found to decrease with increasing EGR rate. At unstable high EGR operation, no relation could be found between the pre-chamber indicated data and main chamber combustion stability.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2015

ZFS on RBODs - Leveraging RAID Controllers for Metrics and Enclosure Management

Traditionally, the Lustre file system has relied on the ldiskfs file system with reliable RAID (Redundant Array of Independent Disks) storage underneath. As of Lustre 2.4, ZFS was added as a backend file system, with built-in software RAID, thereby removing the need of expensive RAID controllers. ZFS was designed to work with JBOD (Just a Bunch Of Disks) storage enclosures under the Solaris Operating System, which provided a rich device management system. Long time users of the Lustre file system have relied on the RAID controllers to provide metrics and enclosure monitoring and management services, with rich APIs and command line interfaces. This paper will study a hybrid approach using an advanced full featured RAID enclosure which is presented to the host as a JBOD, This RBOD (RAIDed Bunch Of Disks) allows ZFS to do the RAID protection and error correction, while the RAID controller handles management of the disks and monitors the enclosure. It was hoped that the value of the RAID controller features would offset the additional cost, and that performance would not suffer in this mode. The test results revealed that the hybrid RBOD approach did suffer reduced performance.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Competitiveness Metrics for Electricity System Technologies

The relative economic competitiveness of power generation technologies is a topic of much interest to diverse electric industry participants. However, assessing competitiveness can be challenging as it requires considering both total costs and total system value of each technology, which are complicated by the (1) numerous and diverse grid services needed to operate a reliable power system; (2) variations in the economic value of the grid services with system state and location, and over multiple timescales, due to the challenges of transporting and storing electricity; and (3) the unique characteristics of different electric system assets. Ideally, metrics designed or used to convey technology competitiveness must consider these complexities, but existing metrics often fall short. For example, the levelized cost of energy does not consider the system economic value of the various technologies nor does it consider services beyond electricity production. Various other metrics have been designed with the purpose of more-accurately communicating the economic viability of electric system technologies. In this report, we summarize the primary sources and components of costs and value and review the known competitiveness metrics by presenting their definitions, applications, advantages, and disadvantages. We also introduce a new set of competitiveness metrics, which we refer to as System Profitability metrics, that more-directly applies the economic principles of return-on-investment to electric system technologies. We use conceptual examples to show how the System Profitability metrics better reflect economic viability and relative technology competitiveness compared with existing metrics. We also describe how competitiveness metrics can be quantified using optimization-based models and demonstrate this capability using a U.S. electric sector capacity expansion model.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2023

Analyzing Hardware and Software Common Cause Failures in Digital Instrumentation and Control Systems using Dual Error Propagation Method

This paper develops a methodology for quantifying software common cause failures (CCFs) in digital instrumentation and control (I&C) systems of nuclear power plants. To support the transition of analog I&C systems to digital in nuclear power plants, probabilistic risk assessment (PRA) techniques are used. The hardware components of the I&C systems have reliability databases that can be used in the PRA studies. However, the failure data for redundant software components of the systems is sparse. Failure of components constitutes a CCF, wherein two or more components or systems fail due to a single shared cause and coupling mechanism. This paper proposes a quantification approach that can simultaneously model hardware and software components, incorporate the CCFs of software systems in the models, and bridge the gap between the failure quantification of models and the development of CCF parametric databases. We demonstrate the dual error propagation method (DEPM) by developing I&C systems failure models for a representative digital reactor trip system. The DEPM models are built to simulate the control and data flows within the systems and can accommodate failure states. By expanding DEPM to software CCFs, we generated alpha factor parameter estimates for each of the modeled error propagation mechanisms.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2018

DIRECT SIMULTANEOUS MEASUREMENT OF PARTICULATE MATTER AND AMMONIA STORAGE ON COMBINED SELECTIVE CATALYTIC REDUCTION FILTER SYSTEMS USING RADIO FREQUENCY SENSORS

Tightening global emissions regulations are motivating interest in the development and implementation of Selective Catalytic Reduction + Filtration (SCRF) systems, which are designed to reduce the concentration of tailpipe particulate matter (PM) and NO x emissions. These systems allow designers to combine the NO x reduction capability of an SCR with the filtration capability of a particulate filter on a single unit. Practical implementation of these systems requires reliable measurement and diagnosis of their state – both with respect to trapped particulate matter as well as adsorbed ammonia. Currently, these systems rely on a variety of gas sensors, mounted upstream or downstream of the system, that only provide an indirect inference of the operation state. In this study, a single radio frequency (RF) sensor was used to perform simultaneous measurements of soot loading and ammonia inventory on an SCRF. Several SCRF core samples were tested at varying soot and ash loads in a catalyst reactor bench. Soot levels were measured by monitoring changes in the bulk dielectric properties within the catalyst using the sensor, while ammonia levels were determined by feeding selected regions of the RF spectrum into a pretrained generalized regression neural network model. Results show the RF sensor is able to directly measure the instantaneous ammonia inventory, while simultaneously providing soot loading measurements within 0.5 g/L. These results confirm that simultaneous measurements of both the PM and ammonia loading state of an SCRF are possible using a single RF sensor via analysis of specific features in the full RF spectrum. The results indicate significant potential to remove the control barriers typically associated with the implementation of advanced SCRF systems.

Ragaller, Paul↗
DOE OSTI2018

Self-Navigating Robotic Assistant for Long-term Wide Area Floor Contamination Monitoring - 18213

For Routine Contamination Testing (RCT) of an operational nuclear facility or one undergoing Decontamination and Decommissioning (D and D), workers utilize specified travel corridors (enclosed hallways or areas designated with tape or rope in open spaces) to minimize the risk of spreading contamination. Radiation health technicians must continually monitor these areas for contamination to minimize worker dose and prevent its spread to uncontrolled areas. For many sites, it is impractical for the technician to adequately survey such areas. The Nuclear Robotics Group (NRG) at UT Austin has developed a self-navigating robotic platform equipped with radiation detectors to augment the technician to improve both survey coverage and frequency. While maintaining a controlled velocity and floor-to-sensor distance, the system takes radiation measurements to identify and/or localize contamination sources. Readings above background levels are reported to a remote workstation to allow technicians to then respond accordingly. The completion of these mundane tasks by a robot allows the trained technicians to focus instead on operational tasks, D and D, or responding to alarms. The robot generates a map using a Lidar range sensor with established Simultaneous Localization and Mapping (SLAM) techniques. Range data is then compared to previously generated maps for robot localization and autonomous navigation. To maximize coverage, the robot executes a Complete Coverage Path Planning (CCPP) algorithm using a static map that is discretized into cells to assure comprehensive yet efficient coverage. As the system executes the generated plan, it builds a radiation map of the area for the technician to validate and verify the results. If contamination is detected, the robot will minimize the spread of contamination by stopping, sounding an alarm, and alerting the remote technician. The proposed system allows for long-term deployment with minimal human intervention. It is robust to both highly dynamic obstacles (i.e. personnel) and low dynamic changes (i.e. temporally stored cart) in the environment. This is accomplished through continuous spatiotemporal updating of the static map, and the utilization of a supervisory controller that allows the system to reliably respond to unexpected events or states (i.e. low battery, closed door, etc.). While the supervisory controller can respond to temporary complications, the system also recognizes the environment can change slowly over time necessitating that the CCPP automatically be updated to account for observed 'permanent' changes to the environment. To do this, the robot uses intermediate probabilistic data to make intelligent planning decisions offline while still maintaining local reactive obstacle avoidance and safety features. The self-updating of the map allows the robot to run longer without the need to remake the map, leading to more consistent monitoring data and less maintenance from the human technician. This paper will review the current system hardware, the CCPP algorithm, the supervisory controller, the probabilistic algorithm for identifying permanent changes, and recent experiments at UT Austin to experimentally validate the reported sensor coverage. (authors)

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

Simulation Modeling for Reliable Biomass Supply Chain Design Under Operational Disruptions

Lignocellulosic biomass derived fuels and chemicals are a promising and sustainable supplement for petroleum-based products. Currently, the lignocellulosic biofuel industry relies on a conventional system where feedstock is harvested, baled, stored locally, and then delivered in a low-density format to the biorefinery. However, the conventional supply chain system causes operational disruptions at the biorefinery mainly due to seasonal availability, handling problems, and quality variability in biomass feedstock. Operational disruptions decrease facility uptime, production efficiencies, and increase maintenance costs. For a low-value high-volume product where margins are very tight, system disruptions are especially problematic. In this work we evaluate an advanced system strategy in which a network of biomass processing centers (depots) are utilized for storing and preprocessing biomass into stable, dense, and uniform material to reduce feedstock supply disruptions, and facility downtime in order to boost economic returns to the bioenergy industry. A database centric discrete event supply chain simulation model was developed, and the impact of operational disruptions on supply chain cost, inventory and production levels, farm metrics and facility metrics were evaluated. Three scenarios were evaluated for a 7-year time-period: (1) bale-delivery scenario with biorefinery uptime varying from 20 to 85%; (2) pellet-delivery scenario with depot uptime varying from 20 to 85% and biorefinery uptime at 85%; and (3) pellet-delivery scenario with depot and biorefinery uptime at 85%. In scenarios 1 and 2, tonnage discarded at the field edge could be reduced by increasing uptime at facility, contracting fewer farms at the beginning and subsequently increasing contracts as facility uptime increases, or determining alternative corn stover markets. Harvest cost was the biggest contributor to the average delivered costs and inventory levels were dependent on facility uptimes. We found a cascading effect of failure propagating through the system from depot to biorefinery. Therefore, mitigating risk at a facility level is not enough and conducting a system-level reliability simulation incorporating failure dependencies among subsystems is critical.

09 BIOMASS FUELS↗
DOE OSTI2021

Cryogenic control system operational experience at SNS

Abstract The helium cryogenic system at Spallation Neutron Source (SNS) provides cooling to 81 superconducting radio frequency cavities. To support the operation of the cryogenic facility, a highly reliable control system consisting of software, hardware, and Human Machine Interface (HMI) has been developed and improved during the first fifteen years of operation. Integrating the cryogenic control system with other subsystems of the SNS complex is an important aspect to the success of the operation. The operating experience, lessons learned and recommendations to consider for future facilities will be detailed in this paper.

Howell, M. (ORCID:0000000310360707)↗
DOE OSTI2022

Stable Catalysts for Combined Dry and Steam Reforming of Methane and Carbon Dioxide

The specific aim of this project is to develop a comprehensive understanding of cheaper and more stable methane and carbon dioxide reforming catalysts with an optimal introduction of steam to reduce carbon deposits that typically prevent the catalytic systems from transferring to commercial implementation. The work was proposed as a two-year project with the end goal of to show a reliable catalyst system run for at least 400 hours at temperatures less than 800 °C with less than 5% loss of activity of the catalyst and a carbon monoxide to hydrogen product ratio of at least 1:1. The project went for one-year and met the end of year milestone by developing two strategies (use of a cerium co-catalyst and introducing 5% water) that reduced the carbon deposition rates by at least 20% relative to the baseline 10% NiMgAlO methane reforming of CO 2 at < 800 °C in order to shown technical feasibility of the concept.

36 MATERIALS SCIENCE↗
DOE OSTI2014

Reliable and Efficient Distributed Checkpointing System for Grid Environments

In Fine-Grained Cycle Sharing (FGCS) systems, machine owners voluntarily share their unused CPU cycles with guest jobs, as long as their performance degradation is tolerable. However, unpredictable evictions of guest jobs lead to fluctuating completion times. Checkpoint-recovery is an attractive mechanism for recovering from such “failures”. Today’s FGCS systems often use expensive, high-performance dedicated checkpoint servers. However, in geographically distributed clusters, this may incur high checkpoint transfer latencies. Here we present a distributed checkpointing system called FALCON that uses available disk resources of the FGCS machines as shared checkpoint repositories. However, an unavailable storage host may lead to loss of checkpoint data. Therefore, we model the failures of a storage host and develop a prediction algorithm for choosing reliable checkpoint repositories. We experiment with FALCON in the university-wide Condor testbed at Purdue and show improved and consistent performance for guest jobs in the presence of irregular resource availability.

checkpoint↗
DOE OSTI2020

Development of a Safe, Reliable, and Versatile Explosive Demolition Initiation System

Demolition contractors have a need to simultaneously detonate many demolition charges safely, cheaply, and reliably. An explosive distribution company has contracted the Initiation Systems Group at Lawrence Livermore Laboratory as consultants. The task is to develop a new, safer initiation system to detonate anywhere from 1 to 2000 demolition charges. The primary user of the system will be the explosive demolition contractors.

42 ENGINEERING↗