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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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
NASA NTRS1993

Edison and radiatively-cooled IR space observatories

Radiative cooling of IR space telescopes is an alternative to embedding within massive cryostats and should offer advantages for future missions, including longer life, larger aperture for a fixed spacecraft size, lower cost due to less complex engineering, and easier ground handling. Relatively simple analyses of conventional designs show that it is possible to achieve telescope temperatures in the range of 25 to 40 K at distances from the sun of about 1 AU. Lower temperatures may be possible with 'open' designs or distant orbits. At approximately 25 K, an observatory will be limited by the celestial thermal background in the near- and mid-IR and by the confusion limit in the far-IR. We outline here our concept for a moderate aperture (approximately 1.75 m; Ariane 4 or Atlas launch) international space observatory for the next decade.

Thronson, H. A.↗
NASA NTRS1982

Utility experience with two demonstration wind turbine generators

Edison has committed 360 MW of nameplate generating capacity to wind energy by year 1990 in its long-range generation plan. To reach this goal the Company's wind energy program focuses on three areas: the continuous evaluation of the wind resource, the hands-on demonstration of wind turbine generators (WTG) and an association with wind park developers. Two demonstration WTGs have been installed and operated at Edison's Wind Energy Center near Palm Springs, California: a 3 MW horizontal axis Bendix/Schachle WTG and a 500 kW vertical axis Alcoa WTG. They are part of a one to two year test program during which the performance of the WTGs will be evaluated, their system operation and environmental impact will be assessed and the design criteria of future WTGs will be identified. Edison's experience with these two WTGs is summarized and the problems encountered with the operation of the two machines are discussed.

Wehrey, M. C.↗
NASA NTRSDate not supplied

Alternating Direct Current (ADC) - A New Form of Efficient Energy Transmission for Renewable Sources

The prevailing means of electricity transmission through Direct Current (DC) and Alternating Current (AC) have limitations with the ongoing transition to renewable energy sources. In this paper, we discuss a new form of energy transmission, known as alternating direct current (ADC) that would provide significant savings in energy consumption and simultaneously allow efficient utilization of generated energy from renewable sources. This has become possible due to substantial advances in electronics and optoelectronics technologies since the days of Nicholas Tesla and Thomas Edison. Recent efforts of implementing the proposed ADC technology in relevant environments have demonstrated significant energy savings and opened a new paradigm that has the potential to provide an efficient and cost-effective pathway for transition to renewable energy sources even with the existing grid infrastructure. The DC power utilization initiated by Thomas Edison can be stored in battery arrangement but suffers from line loss and hence is not efficient for long-distance transmission. However, AC power developed by Nicholas Tesla cannot be stored efficiently but can be transmitted over long distances due to significantly lower line losses. Currently, AC power is the global foundational energy transmission methodology used because of events that took place over 135 years ago involving Edison, Tesla, and Westinghouse, and since AC power can transmit long distances from power plants to end users efficiently and economically. Approximately 50 years ago, the introduction of semiconductors in commercialized electronic devices and products changed the way people consume electricity. Also, over the years, the expanding adaptation of nonlinear loads has adversely affected the grid stability and hence the utility infrastructures worldwide.

AC↗
DOE OSTI2018

Towards understanding HPC users and systems: A NERSC case study

High performance computing (HPC) scheduling landscape currently faces new challenges due to thechanges in the workload. Previously, HPC centers were dominated by tightly coupled MPI jobs. HPCworkloads increasingly include high-throughput, data-intensive, and stream-processing applications. Asa consequence, workloads are becoming more diverse at both application and job levels, posing newchallenges to classical HPC schedulers. There is a need to understand the current HPC workloads andtheir evolution to facilitate informed future scheduling research and enable efficient scheduling in futureHPC systems.In this paper, we present a methodology to characterize workloads and assess their heterogeneity,at a particular time period and its evolution over time. We apply this methodology to the workloads ofthree systems (Hopper, Edison, and Carver) at the National Energy Research Scientific Computing Center(NERSC). We present the resulting characterization of jobs, queues, heterogeneity, and performance thatincludes detailed information of a year of workload (2014) and evolution through the systems’ lifetime(2010–2014).

Rodrigo, Gonzalo P.↗
DOE OSTI2016

Adaptive Transmission Planning: Implementing a New Paradigm for Managing Economic Risks in Grid Expansion

The problem of whether, where, when, and what type of transmission facilities to build in terms of minimizing costs and maximizing net economic benefits has been a challenge for the power industry from the beginning-ever since Thomas Edison debated whether to create longer dc distribution lines (with their high losses) or build new power stations in expanding his urban markets. Today's planning decisions are far more complex, as grids cover the continent and new transmission, generation, and demand-side technologies are emerging.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2016

Towards Real-Time Detection and Tracking of Spatio-Temporal Features: Blob-Filaments in Fusion Plasma [Spatio-Temporal Features in Large Irregular Data: Blob-Filaments in Fusion Plasma]

This work was originally motivated the need to identify and track blob filaments, a feature often associated with instability in magnetically confined fusion plasma. Understanding and mitigating such instability would improve fusion reactors and make fusion a truly inexhaustible source of clean energy. Similar spatio-temporal features are important in many other applications, for example, ignition kernels in combustion and tumor cells in a medical image. This work presents an approach for extracting these features by dividing the overall task into three steps: local identification of feature cells, grouping feature cells into extended feature, and tracking movement of feature through overlapping in space. Through our extensive work in parallelization, we demonstrate that this approach can effectively make use of a large number of compute nodes to detect and track blobs in fusion plasma. On a set of 4.3TB data, we observed linear speedup on 1024 processes and completed blob detection in less than three milliseconds using Edison, a Cray XC30 system at NERSC.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Low-cost embedded optical sensing systems for distribution transformer monitoring

There is a mounting need for low-cost monitoring with online sensing technologies to maintain grid reliability and uptime. Here we introduce an innovative low-cost, embedded optical sensing technology initially focused on transformers that was developed and demonstrated at a major electric utility, Con Edison. A version of it that can be retrofitted onto existing transformers in the field was also developed. Two new 500 kVA distribution network transformers were built with embedded fiber-optic (FO) sensors and qualified per industry standards. Vibration, temperature, and corrosion were key parameters monitored. The first transformer with embedded FO sensors was installed at a Con Edison facility and monitored at our team’s office. The second one was installed in an urban street-side underground location with online data processing/feature extraction algorithms and monitored through a wireless router. Additionally, an older transformer was also retrofitted. Data analysis was done on these transformers showing promising correlations with their corresponding loading cycles. Furthermore, key events such as the transformer primary-side energizing, and other events were detected. In general, the technology was demonstrated over 6 months across the 3 transformers instrumented with promising results. Thus, it has the potential to enable predictive maintenance for transformers and other grid assets.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2016

High-performance epistasis detection in quantitative trait GWAS

epiSNP is a program for identifying pairwise single nucleotide polymorphism (SNP) interactions (epistasis) in quantitative-trait genome-wide association studies (GWAS). A parallel MPI version (EPISNPmpi) was created in 2008 to address this computationally expensive analysis on large data sets with many quantitative traits and SNP markers. However, the falling cost of genotyping has led to an explosion of large-scale GWAS data sets that challenge EPISNPmpi’s ability to compute results in a reasonable amount of time. Therefore, we optimized epiSNP for modern multi-core and highly parallel many-core processors to efficiently handle these large data sets. This paper describes the serial optimizations, dynamic load balancing using MPI-3 RMA operations, and shared-memory parallelization with OpenMP to further enhance load balancing and allow execution on the Intel Xeon Phi coprocessor (MIC). For a large GWAS data set, our optimizations provided a 38.43× speedup over EPISNPmpi on 126 nodes using 2 MICs on TACC’s Stampede Supercomputer. We also describe a Coarray Fortran (CAF) version that demonstrates the suitability of PGAS languages for problems with this computational pattern. We show that the Coarray version performs competitively with the MPI version on the NERSC Edison Cray XC30 supercomputer. Finally, the performance benefits of hyper-threading for this application on Edison (average 1.35× speedup) are demonstrated.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

MPAS-Ocean NESAP Status Report

NESAP performance improvements on MPAS-Ocean have resulted in a 5% to 7% speed-up on each of the examined systems including Cori-KNL, Cori-Haswell, and Edison. These tests were configured to emulate a production workload by using 128 nodes and a high-resolution ocean domain. Overall, the gap between standard and many-core architecture performance has been narrowed, but Cori-KNL remains considerably under-performing relative to Edison. NESAP code alterations affected 600 lines of code, and most of these improvements will benefit other MPAS codes (sea ice, land ice) that are also components within ACME. Modifications are fully tested within MPAS. Testing in ACME across many platforms is underway, and must be completed before the code is merged. In addition, a ten-year production ACME global simulation was conducted on Cori-KNL in late 2016 with the pre-NESAP code in order to test readiness and configurations for scientific studies. Next steps include assessing performance across a range of nodes, threads per node, and ocean resolutions on Cori-KNL.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Grid Ready: Strategies for Interconnecting Large-Scale PV in New York City

This Grid Ready Solar project is intended to help create transparency for building owners and developers, so they can better understand and more quickly navigate the interconnection process for large-scale photovoltaic (PV) projects on Con Edison's electrical grid in New York City. Phase 1 of the project provided high-level technical screens of grid interconnection requirements in an attempt to streamline the interconnection of large-scale solar PV systems to the New York City grid. In Phase 2 of the Grid Ready project, the focus of this report, Sustainable CUNY worked with NREL to evaluate a range of solutions for improving the economics of large-scale (over 200 kW) PV within the five boroughs of New York City that are in Con Edison's service territory, as identified on the NY Solar Map.

14 SOLAR ENERGY↗
DOE OSTI2026

ICE Calculator 2: Final Report for Phase 1 and 2 of the National Initiative to Update the Interruption Cost Estimate (ICE) Calculator

ICE 2.0 Phase 2 Final Report In 2021, Berkeley Lab and Resource Innovations, Inc. launched the “ICE Calculator 2 Initiative” – a national study to refresh the underlying data and enhance the functionality of the ICE Calculator. The Initiative involves Berkeley Lab contracting with sponsoring utilities to administer identical, updated and comprehensive interruption cost surveys to statistically representative samples of each utility’s customers. Berkeley Lab and Resource Innovations then pool the survey results across the utilities and use them to update the analytical engines that drive the ICE Calculator. The ICE Calculator 2 Initiative is being conducted in phases. Each phase involves the administration of interruption cost surveys to the customers of sponsoring utilities, followed by an update to the ICE Calculator based on analysis of the pooled survey results. This report describes the activities and findings from Phase 1 and 2 of the ICE Calculator 2 Initiative. Phase 1 was sponsored by eight utilities: American Electric Power, Commonwealth Edison, Dominion Energy, Duke Energy, DTE Electric, Exelon, National Grid, and Puget Sound Energy. Phase 2 was sponsored by six utilities: Empire District Electric Company, Evergy Missouri, Pacific Gas & Electric, San Diego Gas & Electric, Southern California Edison, and Union Electric. Phase 1 and 2 involved 15 customer interruption cost survey activities representing a total of 30 electricity distribution service territories. ICE Calculator Version 2.0 and 2.2 Comparison This memorandum describes–at a high-level–the improvements in interruption cost estimates for the version 2.2 of the ICE Calculator (released February 2026) compared to version 2.0 (released in April 2025). Version 2.2 of the ICE Calculator corresponds to Phase 2 of the initiative, while version 2.0 corresponds to Phase 1. The improvements in version 2.2 result from both a significant increase in the number of customer responses that have been collected and the identification of seven additional factors that help estimate customer interruption costs.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS1983

Advanced cogeneration research study: Executive summary

This study provides a broad based overview of selected areas relevant to the development of a comprehensive Southern California Edison (SCE) advanced cogeneration project. The areas studied are: (1) Cogeneration potential in the SCE service territory; (2) Advanced cogeneration technologies; and (3) Existing cogeneration computer models. An estimated 3700 MW sub E could potentially be generated from existing industries in the Southern California Edison service territory using cogeneration technology. Of this total, current technology could provide 2600 MW sub E and advanced technology could provide 1100 MW sub E. The manufacturing sector (SIC Codes 20-39) was found to have the highest average potential for current cogeneration technology. The mining sector (SIC Codes 10-14) was found to have the highest potential for advanced technology.

Bluhm, S. A.↗
DOE OSTI2026

Residential Vehicle-to-Home Backup Power Capabilities: Key Findings from a ComEd Beneficial Electrification R&D Pilot

This report summarizes key findings from a collaborative technical study of residential, non-grid-tied vehicle-to-home (V2H) backup power systems in Commonwealth Edison’s (ComEd’s) service territory. The work integrates (1) a feeder-level technoeconomic analysis (TEA) using historical outage-event data and simulated electric-vehicle (EV) driving/charging profiles to estimate potential reliability and customer interruption-cost impacts under V2H and vehicle-to-grid (V2G) adoption scenarios; (2) controlled laboratory performance testing of a representative V2H backup ecosystem to characterize transfer-to-backup behavior, sustained power delivery, efficiency trends, and repeatable reliability limitations; and (3) a cybersecurity assessment aligned with NIST Cybersecurity Framework (CSF) 2.0 and ISO/SAE 21434 to evaluate interface-level risk drivers and identify program-relevant mitigations. Results indicate that V2H can provide measurable resilience value, but outcomes are strongly context dependent on outage patterns and the share of events that are “V2H-applicable.” Typical transfer-to-backup behavior clustered on the order of minutes, but rare long-delay edge cases were observed (including an event approaching 30 minutes) and should be treated as a reliability risk. High-power testing showed that peak-rated output is not necessarily continuously deliverable; stable operation may require operation below nameplate ratings and attention to thermal and installation constraints. The cybersecurity assessment highlights a broad attack surface spanning commissioning, home networks, embedded services, and cloud/OTA pathways, motivating minimum controls for secure onboarding, signed updates, patch cadence, and coordinated vulnerability response for any scaled deployment.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2018

Machine Learning Based Parallel I/O Predictive Modeling: A Case Study on Lustre File Systems

Parallel I/O hardware and software infrastructure is a key contributor to performance variability for applications running on large-scale HPC systems. This variability confounds efforts to predict application performance for characterization, modeling, optimization, and job scheduling. We propose a modeling approach that improves predictive ability by explicitly treating the variability and by leveraging the sensitivity of application parameters on performance to group applications with similar characteristics. We develop a Gaussian process-based machine learning algorithm to model I/O performance and its variability as a function of application and file system characteristics. We demonstrate the effectiveness of the proposed approach using data collected from the Edison system at the National Energy Research Scientific Computing Center. The results show that the proposed sensitivity-based models are better at prediction when compared with application-partitioned or unpartitioned models. We highlight modeling techniques that are robust to the outliers that can occur in production parallel file systems. Using the developed metrics and modeling approach, we provide insights into the file system metrics that have a significant impact on I/O performance.

I/O performance variability↗
DOE OSTI2018

Modeling I/O Performance Variability Using Conditional Variational Auto Encoders

Storage system performance modeling is crucial for efficient use of heterogeneous shared resources on leadership class computers. Variability in application performance, particularly variability arising from concurrent applications sharing I/O resources, is a major hurdle in the development of accurate performance models. We adopt a deep learning approach based on conditional variational auto encoders (CVAE) for I/O performance modeling, and use it to quantify performance variability. We illustrate our approach using the data collected on Edison, a production supercomputing system at the National Energy Research Scientific Computing Center (NERSC). The CVAE approach is investigated by comparing it to a previously proposed sensitivity-based Gaussian process (GP) model. We find that the CVAE model performs slightly better than the GP model in cases where training and testing data come from different applications, since CVAE can inherently leverage the whole data from multiple applications whereas GP partitions the data and builds separate models for each partition. Hence, the CVAE offers an alternative modeling approach that does not need preprocessing; it has enough flexibility to handle data from a wide variety of applications without changing the inference approach.

I/O perfornance variability↗
DOE OSTI2017

Spark and HPC for High Energy Physics Data Analyses

A full High Energy Physics (HEP) data analysis is divided into multiple data reduction phases. Processing within these phases is extremely time consuming, therefore intermediate results are stored in files held in mass storage systems and referenced as part of large datasets. This processing model limits what can be done with interactive data analytics. Growth in size and complexity of experimental datasets, along with emerging big data tools are beginning to cause changes to the traditional ways of doing data analyses. Use of big data tools for HEP analysis looks promising, mainly because extremely large HEP datasets can be represented and held in memory across a system, and accessed interactively by encoding an analysis using highlevel programming abstractions. The mainstream tools, however, are not designed for scientific computing or for exploiting the available HPC platform features. We use an example from the Compact Muon Solenoid (CMS) experiment at the Large Hadron Collider (LHC) in Geneva, Switzerland. The LHC is the highest energy particle collider in the world. Our use case focuses on searching for new types of elementary particles explaining Dark Matter in the universe. We use HDF5 as our input data format, and Spark to implement the use case. We show the benefits and limitations of using Spark with HDF5 on Edison at NERSC.

Sehrish, Saba↗
DOE OSTI2018

Protection Coordination Considerations for a Highly Meshed Urban Microgrid

In microgrid distribution systems, irregular system fault characteristics (with respect to grid-connected mode) and the variability of power flow direction, present challenges to developing a robust and reliable protection scheme that will effective response in both grid-connected and grid-isolation mode. The following investigation captures a meshed network from a larger urban low-voltage (LV) network system in the service area of Consolidated Edison Company of New York (ConEdison), a United States (US) utility that has sufficient customer supplied generation to act as a standalone microgrid. The investigation assesses the viability of differential protection schemes. Protection response has been reviewed with respect to real world application; including, benefits and limitations of selectivity, sensitivity and reliability.

Bello, Mobolaji↗