Results for “Power Train” — Page 11

DOE OSTI2024

Session de formation de l'USAID en Haiti n2: Introduction a l'outil Engage [Slides]

Welcome to Engage! Engage is a capacity expansion modeling tool supported by the National Renewable Energy Laboratory and based on the Calliope open-source capacity expansion model developed by the ETH Zurich University, maintained at the TU Delft University. Engage is an accessible (free, open-access, web-hosted) and flexible web-based energy system planning application for rapid multiple-energy-form energy system scenario exploration. Its cloud-based, collaborator-sharable data model, intuitive interface and visualization capabilities facilitate collaboration and communication among teams, with experts, and among diverse stakeholder groups exploring energy system implications from district to national-scale models. This training series was developed under USAID to empower Haitian stakeholders to explore modeling scenarios in Engage to develop a Haiti Energy Master Plan. This training series includes a general overview of how Engage works along with tailored exercises that target Haiti's specific energy needs, such as modeling the capacity expansion of the bulk power system, fuel scarcity challenges, the development of microgrids, and the economic viability of transmission strategies. See NREL/PR-7A40-88836 for the English translation of this document.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2024

Seance de formation de l'USAID en Haiti n3: Expansion des capacites [Slides]

Welcome to Engage! Engage is a capacity expansion modeling tool supported by the National Renewable Energy Laboratory and based on the Calliope open-source capacity expansion model developed by the ETH Zurich University, maintained at the TU Delft University. Engage is an accessible (free, open-access, web-hosted) and flexible web-based energy system planning application for rapid multiple-energy-form energy system scenario exploration. Its cloud-based, collaborator-sharable data model, intuitive interface and visualization capabilities facilitate collaboration and communication among teams, with experts, and among diverse stakeholder groups exploring energy system implications from district to national-scale models. This training series was developed under USAID to empower Haitian stakeholders to explore modeling scenarios in Engage to develop a Haiti Energy Master Plan. This training series includes a general overview of how Engage works along with tailored exercises that target Haiti's specific energy needs, such as modeling the capacity expansion of the bulk power system, fuel scarcity challenges, the development of microgrids, and the economic viability of transmission strategies. See NREL/PR-7A40-88837 for the English translation of this document.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2024

Seance de formation n4: Modelisation de la resilience et du secteur de l'electricite - Partie I [Slides]

Welcome to Engage! Engage is a capacity expansion modeling tool supported by the National Renewable Energy Laboratory and based on the Calliope open-source capacity expansion model developed by the ETH Zurich University, maintained at the TU Delft University. Engage is an accessible (free, open-access, web-hosted) and flexible web-based energy system planning application for rapid multiple-energy-form energy system scenario exploration. Its cloud-based, collaborator-sharable data model, intuitive interface and visualization capabilities facilitate collaboration and communication among teams, with experts, and among diverse stakeholder groups exploring energy system implications from district to national-scale models. This training series was developed under USAID to empower Haitian stakeholders to explore modeling scenarios in Engage to develop a Haiti Energy Master Plan. This training series includes a general overview of how Engage works along with tailored exercises that target Haiti's specific energy needs, such as modeling the capacity expansion of the bulk power system, fuel scarcity challenges, the development of microgrids, and the economic viability of transmission strategies. See NREL/PR-7A40-88838 for the English translation of this document.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2024

Seance de formation n4: Modelisation de la resilience et du secteur de l'electricite - Partie II [Slides]

Welcome to Engage! Engage is a capacity expansion modeling tool supported by the National Renewable Energy Laboratory and based on the Calliope open-source capacity expansion model developed by the ETH Zurich University, maintained at the TU Delft University. Engage is an accessible (free, open-access, web-hosted) and flexible web-based energy system planning application for rapid multiple-energy-form energy system scenario exploration. Its cloud-based, collaborator-sharable data model, intuitive interface and visualization capabilities facilitate collaboration and communication among teams, with experts, and among diverse stakeholder groups exploring energy system implications from district to national-scale models. This training series was developed under USAID to empower Haitian stakeholders to explore modeling scenarios in Engage to develop a Haiti Energy Master Plan. This training series includes a general overview of how Engage works along with tailored exercises that target Haiti's specific energy needs, such as modeling the capacity expansion of the bulk power system, fuel scarcity challenges, the development of microgrids, and the economic viability of transmission strategies. See NREL/PR-7A40-89389 for the English translation of this document.

24 POWER TRANSMISSION AND DISTRIBUTION↗

NASA NTRS2010

Development of an Integrated Countermeasure Device for Use in Long-Duration Space Flight

Prolonged weightlessness is associated with declines in musculoskeletal, cardiovascular, and sensorimotor health. Consequently, in-flight countermeasures are required to preserve astronaut health. We developed and tested a novel exercise countermeasure device (CCD) for use in spaceflight with the aim of preserving musculoskeletal and cardiovascular health along with an incorporated balance-training component. Additionally, the CCD features a compact footprint, and a low power requirement. Methods: After design and development of the CCD, we carried out a training study to test its ability to improve cardiovascular and muscular fitness in healthy volunteers. Fourteen male and female subjects (41.4+/-9.0 years, 69.5+/-15.4Kg) completed 12 weeks (3 sessions per week) of concurrent strength and endurance training on the CCD. Subjects were tested at baseline and after 12 weeks for 1-repetition max leg press strength (1RM), peak oxygen consumption (VO2peak), and isokinetic joint torque (ISO) at the hip, knee, and ankle. Additionally, we evaluated subjects after 6 weeks of training for changes in VO2peak and 1RM. Results: VO2peak and 1RM improved after 6-weeks, with additional improvements after 12 weeks (1.95+/-0.5, 2.28+/-0.5, 2.47+/-0.6 LY/min and 131.2+/-63.9,182.8+/-75.0, 207.0+/-75.0 Kg) for baseline, 6 weeks, and 12 weeks respectively. ISO for hip adduction, adduction, and ankle plantar flexion improved after 12 weeks of training (70.3+/-39.5, 76.8+/-39.2 and 55.7+/-21.7 N-m vs. 86.1+/-37.3, 85.1+/-34.3 and 62.1+/-26.4 N-m respectively). No changes were observed for ISO during hip flexion, knee extension, or knee flexion. Conclusions: The CCD is effective at improving cardiovascular fitness and isotonic leg strength in healthy adults. Further, the improvement in hip adductor and abductor torque provides support that the CCD may provide additional protection for the preservation of bone health at the hip.

Streeper, Tim↗

NASA NTRS1992

Introduction to Space Station Freedom

NASA field centers and contractors are organized to develop 'work packages' for Space Station Freedom. Marshall Space Flight Center and Boeing are building the U.S. laboratory and habitation modules, nodes, and environmental control and life support system; Johnson Space Center and McDonnell Douglas are responsible for truss structure, data management, propulsion systems, thermal control, and communications and guidance; Lewis Research Center and Rocketdyne are developing the power system. The Canadian Space Agency (CSA) is contributing a Mobile Servicing Center, Special Dextrous Manipulator, and Mobile Servicing Center Maintenance Depot. The National Space Development Agency of Japan (NASDA) is contributing a Japanese Experiment Module (JEM), which includes a pressurized module, logistics module, and exposed experiment facility. The European Space Agency (ESA) is contributing the Columbus laboratory module. NASA ground facilities, now in various stages of development to support Space Station Freedom, include: Marshall Space Flight Center's Payload Operations Integration Center and Payload Training Complex (Alabama), Johnson Space Center's Space Station Control Center and Space Station Training Facility (Texas), Lewis Research Center's Power System Facility (Ohio), and Kennedy Space Center's Space Station Processing Facility (Florida). Budget appropriations impact the development of the Space Station. In Fiscal Year 1988, Congress appropriated only half of the funds that NASA requested for the space station program ($393 million vs. $767 million). In FY 89, NASA sought $967 million for the program, and Congress appropriated $900 million. NASA's FY 90 request was $2.05 billion compared to an appropriation of $1.75 billion; the FY 91 request was $2.45 billion, and the appropriation was $1.9 billion. After NASA restructured the Space Station Freedom program in response to directions from Congress, the agency's full budget request of $2.029 billion for Space Station Freedom in FY 92 was appropriated. For FY 93, NASA is seeking $2.25 billion for the program; the planned budget for FY 94 is $2.5 billion. Further alterations to the hardware configuration for Freedom would be a serious setback; NASA intends 'to stick with the current baseline' and continue planning for utilization.

Kohrs, Richard↗

DOE OSTI2025

Predictive Assessment of the Chemical Composition of Coal Ash in Reserve at U.S. Disposal Sites

In the United States, more than 2 Gt of coal combustion residuals (i.e., coal ash) are stored in hundreds of disposal units. Recent federal regulations mandate the closure or retrofitting of most coal ash impoundments, presenting significant challenges for waste management. These regulatory pressures also present opportunities to reuse coal ash. However, the quality and quantity of discarded coal ash across the U.S. are not well known, even though this information is crucial for spurring its reuse for conventional and new material applications. This study describes a predictive model for the major element composition of coal ash in reserve at disposal sites of major U.S. coal-fired power plants. This model was constructed from coal purchase records of 705 power stations from 1973 to 2022 and was trained on coal ash composition data, showing that coal ash elemental composition is strongly associated with the source of feedstock coal. The model showed regional shifts in the major element contents of ash produced by power plants in the last 50 years, particularly for calcium and iron (expressed as %CaO and %Fe2O3), as power stations changed their source of coal over this time frame. Our approach enables an estimation of chemical composition for ash stored in waste impoundments at individual power stations. Such information can help to delineate the regional market resource potential of supplementary cements for concrete and other material innovations that would utilize coal ash harvested from disposal sites across the U.S.

01 COAL, LIGNITE, AND PEAT↗

NASA NTRS1987

Flight research with the MIT Daedalus prototype

The MIT Light Eagle human-powered aircraft underwent long-duration testing over Rogers Dry Lake in California during January, 1987. Designed as a prototype for the MIT Daedalus Project, the Light Eagle's forty-eight flights provided pilot training, established new distance records for human-powered flight, and provided quantitative data through a series of instrumented flight experiments. The experiments focused on: (1) evaluating physiological loads on the pilot, (2) determining airframe power requirements, and (3) developing an electronic flight control system. This paper discusses the flight test program, its results and their implications for the follow-on Daedalus aircraft, and the potential uses of the Light Eagle as a low Reynolds number testbed.

Bussolari, Steven R.↗

NASA NTRS2015

Improvements to the Tendon-Actuated Lightweight In-Space MANipulator (TALISMAN)

Devices for manipulating and precisely placing payloads are critical for efficient space operations including berthing of spacecraft, in-space assembly, construction and repair. Key to the success of many NASA space activities has been the availability of long-reach crane-like devices such as the Shuttle Remote Manipulation System (SRMS) and the Space Station Remote Manipulation System (SSRMS). These devices have been used for many operations including berthing visiting spacecraft to the International Space Station, deployment of spacecraft, space station assembly, astronaut positioning, payload transfer, and spacecraft inspection prior to atmospheric re-entry. Retiring the Space Transportation System has led to the removal of the SRMS from consideration for in-space missions, thus creating a capability gap. Recognizing this gap, work was initiated at NASA on a new architecture for long-reach space manipulators. Most current devices are constructed by joining revolute joints with carbon composite tubes, with the joints accounting for the majority of the device mass. For example in the case of the SRMS, the entire device mass is 410 kg (904 lbm); the joint structure, motors, gear train, cabling, etc., accounts for the majority of the system mass because the carbon composite tubes mass is 46 kg (101 lbm). An alternate space manipulator concept, the Tendon-Actuated Lightweight In-Space MANipulator (TALISMAN) was created to address deficiencies in the current state-of-the-art in long-reach manipulators. The antagonistic tendon actuated joint architecture allows the motors actuating the joint to be removed from the joint axis, which simplifies the joint design while simultaneously providing mechanical advantage for the motors. The improved mechanical advantage, in turn, reduces the size and power requirements for the motor and gear train. This paper will describe recent architectural improvements to the TALISMAN design that: 1) improve the operational robustness of the system by enabling maneuvers not originally possible by varying the TALISMAN geometry; 2) enable efficient active antagonistic control of a joint while sharing cable between antagonistic tension networks; and 3) uses a unique arrangement of differential capstans to reduce motor torque requirements by an order of magnitude. The paper will also summarize recent efforts to enable autonomous deployment of a TALISMAN including the deployment concept of operations and associated hardware system design. The deployment forces are provided by the same motor systems that are used for articulation, thus reducing the mass associated with the deployment system. The deployment approach is being tested on a TALISMAN prototype which is designed to provide the same operational performance as a shuttle-class manipulator. The prototype has been fabricated and is operational in a new facility at NASA Langley Research Center that has a large area (15.2 m by 21.3 m [50 ft by 70 ft]) air-bearing floor.

Doggett, William R.↗

DOE OSTI2024

Resources, Training, and Education Under the Heliostat Consortium: Industry Gap Analysis and Building a Resource Database

Concentrating solar power is not a widely deployed or known technology area, and the heliostat workforce community in the United States is currently small, with knowledge and expertise not widely available. The resource, training, and education (RTE) topic within the Heliostat Consortium (HelioCon) was established to address this. RTE encompasses resources, practices, and programs to ensure that (1) newcomers to the heliostat development community have an adequate knowledge base and training to conduct R&D efforts, (2) outsiders to the field are provided with resources and opportunities to join the workforce, and (3) the workforce community is a productive, healthy, and fulfilling environment for all workers. In the first year of the project, a roadmap study was conducted, in which the major gaps in RTE were identified by consulting experts in the industry, with the top gap being the lack of public accessibility to concentrating solar-thermal power (CSP) knowledge. Here, to address this, the HelioCon team has been developing a centralized web-based resource database, containing a reference library, educational videos, lists of components suppliers and software/metrology tools, a power tower plant database, and information on existing standards/guidelines.

14 SOLAR ENERGY↗

NASA NTRSDate not supplied

Using Long-Short Term Memory Models to Predict Solar Active Regions Emergence

We train Long Short-Term Memory (LSTM) models that predict the formation of active regions (ARs), the main source of eruptive solar activity. Using the Doppler shift velocity, the continuum intensity and the magnetic field full-disk maps from SDO/HMI we have created time-series datasets of acoustic power and magnetic flux which are used to train Long Short-Term Memory (LSTM) models on predicting decreases in continuum intensity 12 hours in advance. Testing of the models' performance was done on data from 5 ARs, unseen from the model during training. The model predicted the emergence of AR11726, AR13165 and AR13179, 10, 29 and 5 hours in advance, and variations of this model achieved average RMSE values of 0.11 for both active and quiet parts of the solar disc, showing the ability of the model to capture acoustic power anomalies and predict continuum intensity variations. This work sets the foundations for the very first ML-aided prediction of solar ARs.

SMD↗

DOE OSTI2026

Dataset of Generative AI Workload Power Profiles

This dataset provides a collection of high-resolution (5/10 Hz or every 0.2/0.1 seconds) power consumption profiles for generative artificial intelligence (GenAI) workloads executed on NLR's High Performance Computing (HPC) platform Kestrel. The dataset also includes examples of representative whole-facility power profiles generated using a bottom-up, event-driven, data center energy model . This dataset is designed to support research in energy modeling, infrastructure planning, energy system integration, and sustainability analysis for AI-driven computing systems. The dataset captures time-resolved electrical power measurements across a diverse set of configurations, including variations in job type (inference vs. training), workload (LLM vs. image generation), datasets, and number of compute nodes. Power traces are provided in a standardized format and include both raw/instantaneous and aggregated files. Each profile is accompanied by metadata describing workload parameters, enabling reproducibility and cross-study comparison. The dataset is intended for use in applications such as data center infrastructure planning, energy modeling, demand response and grid impact studies, and development and validation of system-level simulation tools. By making these workload-specific power profiles publicly available, this dataset aims to address the current lack of open, empirical energy data for generative AI systems and to facilitate transparent, reproducible research on the energy and environmental impacts of large-scale AI deployment. If you use this dataset, please cite the associated publication: Vercellino et al., “Measurement of Generative AI Workload Power Profiles for Whole-Facility Data Center Infrastructure Planning,” arXiv:2604.07345 (2026).

97 MATHEMATICS AND COMPUTING↗

NASA NTRS2007

Exploring and Visualizing A-Train Instrument Data

The succession of US and international satellites that follow each other in close succession, known as the A-Train, affords an opportunity to atmospheric researchers that no single platform could provide: Increasing the number of observations at any given geographic location.. . a more complete "virtual science platform". However, vertically and horizontally, co-registering and regridding datasets from independently developed missions, Aqua, Calipso, Cloudsat, Parasol, and Aura, so that they can be inter-compared can be daunting to some, and may be repeated by many. Scientists will individually spend much of their time and resources acquiring A-Train datasets of interest residing at various locations, developing algorithms to match up and graph datasets along the A-Train track, and search through large amounts of data for areas and/or phenomena of interest. The aggregate amount of effort that can be expended on repeating pre-science tasks could climb into the tens of millions of dollars. The goal of the A-Train Data Depot (ATDD) is to enable free movement of remotely located A-Train data so that they are combined to create a consolidated vertical view of the Earth's Atmosphere along the A-Train tracks. The innovative approach of analyzing and visualizing atmospheric profiles along the platforms track (i.e., time) is accomplished by through the ATDDs Giovanni data analysis and visualization tool. Giovanni brings together data from Aqua (MODIS, AIRS, AMSR-E), Cloudsat (cloud profiling radar) and Calipso (CALIOP, IIR), as well as the Aura (OMI, MLS, HIRDLS, TES) to create a consolidated vertical view of the Earth's Atmosphere along the A-Train tracks. This easy to learn and use exploration tool will allow users to create vertical profiles of any desired A-Train dataset, for any given time of choice. This presentation shows the power of Giovanni by describing and illustrating how this tool facilitates and aids A-Train science and research. A web based display system Giovanni provides users with the capability of creating co-located profile images of temperature and humidity data from the MODIS, MLS and AIRS instruments for a user specified time and spatial area. In addition, Cloud and Aerosol profiles may also be displayed for the Cloudsat and Caliop instruments. The ability to modify horizontal and vertical axis range, data range and dynamic color range is also provided. Two dimensional strip plots of MODIS, AIRS, OM1 and POLDER parameters, co-located along the Cloudsat reference track, can also be plotted along with the Cloudsat cloud profiling data. Center swath pixels for the same parameters can also be shown as line plots overlaying the Cloudsat or Calipso profile images. Images and subsetted data produced in each analysis run may be downloaded. Users truly can explore and discover data specific to their needs prior to ever transferring data to their analysis tools.

Kempler, S.↗

NASA NTRS2012

CloudSat Anomaly Recovery and Operational Lessons Learned

In April 2011, NASA's pioneering cloud profiling radar satellite, CloudSat, experienced a battery anomaly that placed it into emergency mode and rendered it operations incapable. All initial attempts to recover the spacecraft failed as the resultant power limitations could not support even the lowest power mode. Originally part of a six-satellite constellation known as the "A-Train", CloudSat was unable to stay within its assigned control box, posing a threat to other A-Train satellites. CloudSat needed to exit the constellation, but with the tenuous power profile, conducting maneuvers was very risky. The team was able to execute a complex sequence of operations which recovered control, conducted an orbit lower maneuver, and returned the satellite to safe mode, within one 65 minute sunlit period. During the course of the anomaly recovery, the team developed several bold, innovative operational strategies. Details of the investigation into the root-cause and the multiple approaches to revive CloudSat are examined. Satellite communication and commanding during the anomaly are presented. A radical new system of "Daylight Only Operations" (DO-OP) was developed, which cycles the payload and subsystem components off in tune with earth eclipse entry and exit in order to maintain positive power and thermal profiles. The scientific methodology and operational results behind the graduated testing and ramp-up to DO-OP are analyzed. In November 2011, the CloudSat team successfully restored the vehicle to consistent operational collection of cloud radar data during sunlit portions of the orbit. Lessons learned throughout the six-month return-to-operations recovery effort are discussed and offered for application to other R&D satellites, in the context of on-orbit anomaly resolution efforts.

cloud profiling radar satellite↗

NASA NTRS1991

Debris Collision Warning Sensor (DCWS) telescope design

The 60-cm diameter, f/2 DCWS telescope is a modified Ritchey Chretein configuration which collects radiation in three spectral bands, 0.4 to 0.9/micron (visible), 5.0 to 9.0/microns (MWIR), and 9.0 to 12.0 microns (LWIR). The visible and infrared radiation are separated by a dichroic beamsplitter and focused on to separate focal planes; the MWIR and LWIR radiation share a common focal plane with separate detector arrays residing side-by-side. The conic constants of the primary and secondary mirrors are that of a Ritchey Chretein telescope; to improve the image quality at the edges of the field of view, a set of zero power correcting optics have been introduced to each optical train. The Ritchey Chretein telescope is corrected to have zero third order spherical aberration and zero third order coma; the DCWS telescope is further configured such that the positive power in the primary mirror is approximately equal to the negative power in the secondary mirror, resulting in a telescope with very little field curvature.

Brown, Robert J.↗

NASA NTRS1983

SETI Pulse Detection Algorithm: Analysis of False-alarm Rates

Some earlier work by the Search for Extraterrestrial Intelligence (SETI) Science Working Group (SWG) on the derivation of spectrum analyzer thresholds for a pulse detection algorithm based on an analysis of false alarm rates is extended. The algorithm previously analyzed was intended to detect a finite sequence of i periodically spaced pulses that did not necessarily occupy the entire observation interval. This algorithm would recognize the presence of such a signal only if all i-received pulse powers exceeded a threshold T(i): these thresholds were selected to achieve a desired false alarm rate, independent of i. To simplify the analysis, it was assumed that the pulses were synchronous with the spectrum sample times. This analysis extends the earlier effort to include infinite and/or asynchronous pulse trains. Furthermore, to decrease the possibility of missing an extraterrestrial intelligence signal, the algorithm was modified to detect a pulse train even if some of the received pulse powers fall below the threshold. The analysis employs geometrical arguments that make it conceptually easy to incorporate boundary conditions imposed on the derivation of the false alarm rates. While the exact results can be somewhat complex, simple closed form approximations are derived that produce a negligible loss of accuracy.

Levitt, B. K.↗

DOE OSTI2025

Computing Nonlinear Power Spectra Across Dynamical Dark Energy Model Space with Neural ODEs

I show how to compute the nonlinear power spectrum across the entire $w(z)$ dynamical dark energy model space. Using synthetic ΛCDM data, I train a neural ordinary differential equation (ODE) to infer the evolution of the nonlinear matter power spectrum as a function of the background expansion and mean matter density across ∼9 Gyr of cosmic evolution. After training, the model generalises to any dynamical dark energy model parameterised by $w(z)$. With little optimisation, the neural ODE is accurate to within 4% up to $k = 5\, h\, {\mathrm Mpc}^{−1}$. Unlike simulation rescaling methods, neural ODEs naturally extend to summary statistics beyond the power spectrum that are sensitive to the growth history.

cosmology↗

DOE OSTI2024

Unsupervised learning for equitable DER control

Not Available

Yuan, Zhenyi (ORCID:0000000151133020)↗