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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 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Master State Distributed Estimator (masde)

The MSE technology provides a distributed state estimation scheme for power utilities by making it a real time dynamic system, versus the static snapshot method used today. This will allow utilities to verify power grid readings and identify false data on the communication network. The prevailing method of estimation takes all the data from the system into a single load flow equation at the utilities command center. This becomes a large algorithm that is very time consuming to solve, providing the engineers only snap shots of the system. The MFD distributes an algorithm to devises that are already installed at various locations on the power grid. This allows for much faster computer times because the algorithms contain magnitudes less data. When each distributed estimator completes its calculation, it sends the results back to the master device to check against all other distributed estimators.

Reen, DylanW.↗
DOE OSTI2026

New Report Highlights LAMP's Role as a Robust and Reliable System for Wave Energy Converter Testing

Harnessing the power of waves requires more than just putting devices in the ocean - it takes tools that can refine and accelerate innovation before the first deployment. That's where NLR's largeamplitude motion platform, or LAMP, comes in. LAMP is a six-degree-of-freedom motion system designed to replicate the response of a wave energy converter (WEC) device in realistic ocean conditions. By letting researchers evaluate WEC performance in a safe, controlled lab environment before moving offshore, LAMP helps accelerate innovation while reducing risk. An NLR report, titled Initial Characterization of the NLR LargeAmplitude Motion Platform (https://www.nrel.gov/docs/fy26osti/93733.pdf), provides a deeper understanding of LAMP's capabilities and also lays the groundwork for future advancements in WEC testing methodologies. Researchers studied LAMP's amplitude and frequency limits across different payloads and collected data from 16 test profiles. Testing demonstrated that platform accuracy remained consistent across all payloads evaluated; researchers expect similar accuracy up to LAMP's 10,000-kilogram capacity limit. The measured position limits for single degrees of freedom experienced by WECs, including surge, sway, heave, roll, pitch, and yaw, also exceeded the original manufacturer specifications, providing new insight into the true boundaries of the system.

16 TIDAL AND WAVE POWER↗
DOE OSTI2023

The Regenerative Current Mirror: A Very Low Power Front-End Amplifier for Silicon Pixel Detectors

In pixelized detectors, reducing power consumption in the front end ASIC chips becomes a crucial demand. Optimization based on mature pre-amplifier schemes today is unlikely to bring sufficient improvements. A new CMOS front-end gain stage topology with very low power consumption called regenerative current mirror is developed to fulfill the demand. The circuit takes advantage of high speed performance of current amplification while operating with relatively low bias current. The regenerative current mirror uses a NMOS current mirror and a PMOS current mirror, both with nominal gain of 1, to form a loop-back topology that provides a positive feedback. An NMOS FET with an external adjustable voltage applied to it gate terminal is used to limit open loop gain of the current mirrors to be slightly lower than 1. This yields a net gain of the positive feedback loop to be much larger than 1 while operating the current mirrors under relatively low bias currents. Simulation shows that in 65 nm fabrication process, the power consumption of the gain stages suitable for silicon pixel detectors can be controlled < 10 micro-Watts per channel.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

The Regenerative Current Mirror: A Very Low Power Front-End Amplifier for Silicon Pixel Detectors

In pixelized detectors, reducing power consumption in the front- end ASIC chips becomes a crucial demand. Optimization based on mature pre-amplifier schemes today is unlikely to bring sufficient improvements. A new CMOS front-end gain stage topology with very low power consumption called regenerative current mirror is developed to fulfill the demand. The circuit takes advantage of high-speed performance of current amplification while operating with relatively low bias current. The regenerative current mirror uses a NMOS current mirror and a PMOS current mirror, both with nominal gain of 1, to form a loop-back topology that provides a positive feedback. An NMOS FET with an external adjustable voltage applied to it gate terminal is used to limit open loop gain of the current mirrors to be slightly lower than 1. This yields a net gain of the positive feedback loop to be much larger than 1 while operating the current mirrors under relatively low bias currents. Simulation shows that in 65 nm fabrication process, the power consumption of the gain stages suitable for silicon pixel detectors can be controlled < 10 micro-Watts per channel. Another novel low-power circuit called Pseudo-Thyristor presented in another document will replace traditional discriminator and the Regenerative Current Mirror plus Pseudo- Thyristor will provide a full solution for the silicon pixel low-power frontend ASIC.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

Current Source Inverter Based Large Constant Power Speed Ratio SPM Machine Drive for Traction Applications

A high-performance surface permanent magnet (SPM) machine drive with an extended constant power speed ratio is proposed using a current source inverter (CSI) for a traction application. The constant-power operation regions of an SPM machine can be extended in an appealing fashion by taking advantage of the output voltage boost capability of the CSI. The CSI is naturally a boost-type converter, in contrast to the voltage source inverter (VSI) which has buck-type characteristics. To investigate the value of the CSI voltage boost feature, a new traction motor with higher rated voltage and lower rated current has been designed and compared to the motor that would be used with a VSI. The lower CSI current makes it possible to reduce the mass of the inverter and output power cable, benefiting power density and cost reduction. The SPM machine is modeled in the synchronous reference frame including the effect of the ac filter capacitors at the CSI output terminals. The capability of extending the speed range of the proposed motor is verified via closed-form analysis and FEA simulation, and its performance characteristics are compared with those of a VSI-based SPM motor of the same type.

42 ENGINEERING↗
DOE OSTI2022

Substructure at High Speed. I. Inferring the Escape Velocity in the Presence of Kinematic Substructure

Abstract The local escape velocity provides valuable inputs to the mass profile of the galaxy, and requires understanding the tail of the stellar speed distribution. Following Leonard & Tremaine, various works have since modeled the tail of the stellar speed distribution as ∝ ( v esc − v ) k , where v esc is the escape velocity, and k is the slope of the distribution. In such studies, however, these two parameters were found to be largely degenerate and often a narrow prior is imposed on k in order to constrain v esc . Furthermore, the validity of the power-law form can breakdown in the presence of multiple kinematic substructures or other mis-modeled features in the data. In this paper, we introduce a strategy that for the first time takes into account the presence of kinematic substructure. We model the tail of the velocity distribution as a sum of multiple power laws as a way of introducing a more flexible fitting framework. Using mock data and data from FIRE simulations of Milky Way-like galaxies, we show the robustness of this method in the presence of kinematic structure that is similar to the recently discovered Gaia Sausage. In a companion paper, we present the new measurement of the escape velocity and subsequently the mass of the Milky Way using Gaia eDR3 data.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Methods and system for siting advanced nuclear reactors and evaluating energy policy concerns

There is a growing sociopolitical desire to develop cleaner energy sources in the United States and maintain energy security. Regardless of politics, many coal-fired electric plants have already been shut down and many utilities are vowing to retire their current coal-fired assets within the next two decades. Replacement power assets require consideration of appropriate siting. A geographic information system (GIS)-based multicriteria decision analysis approach is useful to assist utility and energy companies, as well as policymakers, to evaluate potential areas for siting new plants in the contiguous United States. A GIS-based framework is simply a database of location information that allows for mapping, querying, modeling, and analyzing data based on location. The spatial output can be structured to be visual, allowing for easier analysis of location data. The need to site additional power assets, including renewable resources and clean power sources, such as nuclear, led to the development of the Oak Ridge Siting Analysis for power Generation Expansion (OR-SAGE) tool discussed in this paper. The tool takes inputs such as population growth, water availability, environmental indicators, and tectonic and geological hazards to provide an in-depth visual analysis for siting options. Energy companies and other stakeholders can use OR-SAGE to procure feedback quickly and effectively on land suitability based on technology specific inputs. Policymakers can use OR-SAGE to analyze the impacts of future energy technology decisions, while balancing competing resource use. Overall, this paper discusses the recent use of OR-SAGE for these purposes and plans for future development.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2021

Planned Relocation: A Pluralistic and Integrated Approach to Science and Governance

Planned relocation is an ambitious objective that occurs in complex governance settings rife with inequalities of power, discrimination, distrust, deep uncertainty, misalignment of incentives and authorities, and other challenges. Taking planned relocation from ambition to an equitable and effective portfolio of measures will require changes in science, governance and how they work together. Research will need to understand perverse incentives, conflicts, limits to risk perception, and other factors across individuals, communities, governance levels, and sectors. Knowledge to enable planned relocation will emerge not just from technical studies but from entwined processes of action, learning and capacity building. Science and governance must advance their collaboration to better support and learn from these tangled processes to identify adaptive pathways, build agency and implement strategies under deep uncertainty.

global environmental change, adapatation, decision↗
DOE OSTI2022

ERL-Based Compact X-Ray FEL

We propose to develop an energy-recovery-linac (ERL)-based X-ray free-electron laser (XFEL). Taking advantage of the demonstrated high-efficiency energy recovery of the beam power in the ERL, the proposed concept offers the following benefits: i) recirculating the electron beam through high-gradient superconducting RF (SRF) cavities shortens the linac, ii) energy recovery in the SRF linac saves the klystron power and reduces the beam dump power, iii) the high average beam power produces a high average photon brightness. In addition, such a concept has the capability of delivering optimized high-brightness CW X-ray FEL performance at different energies with simultaneous multipole sources. In this paper, we will present the preliminary results on the study of feasibility, optics design and parameter optimization of such a device.

Lin, Fanglei↗
DOE OSTI2020

PETSc Users Manual (Rev. 3.13)

This manual describes the use of PETSc for the numerical solution of partial differential equations and related problems on high-performance computers. The Portable, Extensible Toolkit for Scientific Computation (PETSc) is a suite of data structures and routines that provide the building blocks for the implementation of large-scale application codes on parallel (and serial) computers. PETSc uses the MPI standard for all message-passing communication. PETSc includes an expanding suite of parallel linear solvers, nonlinear solvers, and time integrators that may be used in application codes written in Fortran, C, C++, and Python. PETSc provides many of the mechanisms needed within parallel application codes, such as parallel matrix and vector assembly routines. The library is organized hierarchically, enabling users to employ the level of abstraction that is most appropriate for a particular problem. By using techniques of object-oriented programming, PETSc provides enormous flexibility for users. PETSc is a sophisticated set of software tools; as such, for some users it initially has a much steeper learning curve than a simple subroutine library. In particular, for individuals without some computer science background, experience programming in C, C++, python, or Fortran and experience using a debugger such as gdb or dbx, it may require a significant amount of time to take full advantage of the features that enable efficient software use. However, the power of the PETSc design and the algorithms it incorporates may make the efficient implementation of many application codes simpler than \rolling them" yourself.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

PETSc/TAO Users Manual (Rev. 3.19)

This manual describes the use of the Portable, Extensible Toolkit for Scientific Computation (PETSc) and the Toolkit for Advanced Optimization (TAO) for the numerical solution of partial differential equations and related problems on high-performance computers. PETSc/TAO is a suite of data structures and routines that provide the building blocks for the implementation of large-scale application codes on parallel (and serial) computers. PETSc uses the MPI standard for all distributed memory communication. PETSc/TAO includes a large suite of parallel linear solvers, nonlinear solvers, time integrators, and opti mization that may be used in application codes written in Fortran, C, C++, and Python (via petsc4py; see Getting Started). PETSc provides many of the mechanisms needed within parallel application codes, such as parallel matrix and vector assembly routines. The library is organized hierarchically, enabling users to employ the level of abstraction that is most appropriate for a particular problem. By using techniques of object-oriented programming, PETSc provides enormous flexibility for users. PETSc is a sophisticated set of software tools; as such, for some users it initially has a much steeper learning curve than packages such as MATLAB or a simple subroutine library. In particular, for individuals without some computer science background, experience programming in C, C++, python, or Fortran and experience using a debugger such as gdb or lldb, it may require a significant amount of time to take full advantage of the features that enable efficient software use. However, the power of the PETSc design and the algorithms it incorporates may make the efficient implementation of many application codes simpler than “rolling them” yourself. For many tasks a package such as MATLAB is often the best tool; PETSc is not intended for the classes of problems for which effective MATLAB code can be written. There are several packages, built on PETSc, that may satisfy your needs without requiring directly using PETSc. We recommend reviewing these packages functionality before starting to code directly with PETSc. PETSc can be used to provide a “MPI parallel linear solver” in an otherwise sequential, or OpenMP parallel code. This approach cannot provide extremely large improvements in the application time by utilizing large numbers of MPI processes but can still improve the performance. Certainly all parts of a previously sequential code need not be parallelized but the matrix generation portion must be parallelized to expect true scalability to large numbers of MPI processes. See PCMPI for details on how to utilize the PETSc MPI linear solver server. Since PETSc is under continued development, small changes in usage and calling sequences of routines will occur. PETSc has been supported for twenty-five years; see mailing list information on our website for information on contacting support.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Machine Learning and Economic Models to Enable Risk-Informed Condition Based Maintenance of a Nuclear Plant Asset

The primary objective of this research is to address challenges in the implementation of risk-informed, condition-based predictive maintenance (PdM), which reduces operating costs while still maintaining the safety and reliability of commercial nuclear power plants (NPPs). To achieve the objective, risk models are being developed by taking advantage of advancements in data analytics, deep learning, machine learning (ML), and artificial intelligence (AI). The notable outcomes presented in the report include ? Development of a ML models using heterogeneous plant process and vibration data collected at different spatial and temporal resolutions from the Salem?s CWS to diagnose a circulating water pump (CWP) failure based on salient fault signatures. The developed diagnostic models are extendable to other faults associated with CWPs and CWP motors given associated fault signatures. ? Development of a natural language processing (NLP) technique to automatically classify the WO data into different categories. The developed NLP technique was validated on independent WO data. This automates the tedious and time-consuming activity of mining and classifying WOs by subject matter experts. ? Estimation of mean time between downtime (i.e., time duration between time instances when 1 or more CWPs are not available) and developed an approach to establish reliability of CWS components using unstructured WO data along with CWS plant process data. ? Formulation of economic model based on Markov chain models. The parameters of associated with the transition rate between different states of Markov chain models were estimated using WO data. The economic model formulation and discussion captures both time-independent and time-dependent parameter variation, leading to risk-informed decision-making.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

ERL-BASED COMPACT X-RAY FEL

We propose to develop an energy-recovery-linac (ERL)- based X-ray free-electron laser (XFEL). Taking advantage of the demonstrated high-efficiency energy recovery of the beam power in the ERL, the proposed concept offers the following benefits: i) recirculating the electron beam through high-gradient superconducting RF (SRF) cavities shortens the linac, ii) energy recovery in the SRF linac saves the klystron power and reduces the beam dump power, iii) the high average beam power produces a high average photon brightness. In addition, such a concept has the capability of delivering optimized high-brightness CW X-ray FEL performance at different energies with simultaneous multipole sources. In this paper, we will present the preliminary results on the study of feasibility, optics design and parameter optimization of such a device.

Lin, Fanglei↗
DOE OSTI2023

Online Output-Based Inertia Estimation of Modern Power Systems

The overall inertia of modern power systems is drastically impacted by the penetration level of converter-based resources (CBRs). The intermittent output of CBRs and their dependence on the weather conditions affirm the need for a realtime inertia estimation approach. This can help the transmission system operators(TSOs) to be continuously aware of the changes in the system inertia and to take suitable control actions. This paper is a step forward to a totally data-driven framework for power system inertia estimation using the available measurements from the phasor measurement units (PMUs). This inertia estimation is done based on the spectral analysis of the so-called Koopman linear operator. Koopman operator considers the relationship between the system's inertia and its dynamical response to slight disturbances in the load. Simulation results show that Koopman operator can approximate the system behavior in a reconstructed linear space hence inertia constant is estimated accurately.

data-driven↗
DOE OSTI2021

Online PMU Missing Value Replacement Via Event-Participation Decomposition

We introduce a new method for online Phasor Measurement Unit (PMU) missing value replacement. Our approach allows us to decompose PMU event responses into a non-dynamic component (denoted the participation factor) that can be inferred directly from the past and a dynamic component that can be inferred directly from all other PMUs (denoted the event strength). When missing values occur, we can use these two components, which do not rely on the missing index, to estimate the correct value. The method is extremely fast and can easily be used for online applications. Furthermore, extensive testing on real power system event data reveals that our approach achieves state-of-the-art performance in terms of Mean Absolute Percent Errors (MAPEs) for PMU data dropped during event periods. Here, the method also yields an interpretable and simplified view of events for further analysis and applications. The method relies only on PMU data and does not take outside information such as network topology.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

High-Performance Computing Based EMT Simulation of Large PV or Hybrid PV Plants

Faults in the transmission grid have led to reduced power generation from power electronics resources that are typically not connected to the faulted transmission line. In many of the cases, partial loss of power is observed within the power electronics resources like large photovoltaic (PV) power plants. This phenomena is not captured in existing simulation models and/or simulators. High-fidelity switched system electromagnetic transient (EMT) dynamic models of PV power plants can improve the fidelity of models available for accurate analysis of the impact on PV plants during simulation of faults. However, these models are extremely computationally expensive and take a long time to simulate. Long simulation times limit the ability to use these models as larger regions are studied in EMT simulations with more power electronics resources. In this paper, numerical simulation algorithms are combined with high-performance computing techniques and applied to the high-fidelity switched system EMT model of PV plants. Using these techniques, a speed-up of up to 58x is obtained, while preserving the accuracy of the simulation at greater than 98%.

Debnath, Suman↗
DOE OSTI2024

Is infrared-collinear safe information all you need for jet classification?

Machine learning-based jet classifiers are able to achieve impressive tagging performance in a variety of applications in high-energy and nuclear physics. However, it remains unclear in many cases which aspects of jets give rise to this discriminating power, and whether jet observables that are tractable in perturbative QCD such as those obeying infrared-collinear (IRC) safety serve as sufficient inputs. In this article, we introduce a new classifier, Jet Flow Networks (JFNs), in an effort to address the question of whether IRC unsafe information provides additional discriminating power in jet classification. JFNs are permutation-invariant neural networks (deep sets) that take as input the kinematic information of reconstructed subjets. The subjet radius and a cut on the subjet’s transverse momenta serve as tunable hyperparameters enabling a controllable sensitivity to soft emissions and nonperturbative effects. We demonstrate the performance of JFNs for quark vs. gluon and Z vs. QCD jet tagging. For small subjet radii and transverse momentum cuts, the performance of JFNs is equivalent to the IRC-unsafe Particle Flow Networks (PFNs), demonstrating that infrared-collinear unsafe information is not necessary to achieve strong discrimination for both cases. As the subjet radius is increased, the performance of the JFNs remains essentially unchanged until physical thresholds that we identify are crossed. For relatively large subjet radii, we show that the JFNs may offer an increased model independence with a modest tradeoff in performance compared to classifiers that use the full particle information of the jet. These results shed new light on how machines learn patterns in high-energy physics data.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Robust and ultrafast state preparation by ramping artificial gauge potentials

Abstract The implementation of static artificial magnetic fields in ultracold atomic systems has become a powerful tool, e.g. for simulating quantum-Hall physics with charge-neutral atoms. Taking an interacting bosonic flux ladder as a minimal model, we investigate protocols for adiabatic state preparation via magnetic flux ramps. Considering the fact that it is actually the artificial vector potential (in the form of Peierls phases) that can be experimentally engineered in optical lattices, rather than the magnetic field, we find that the time required for adiabatic state preparation dramatically depends on which pattern of Peierls phases is used. This can be understood intuitively by noting that different patterns of time-dependent Peierls phases that all give rise to the same magnetic field ramp, generally lead to different artificial electric fields during the ramp. As an intriguing result, we find that an optimal choice allows for preparing the ground state almost instantaneously in the non-interacting system, which can be related to the concept of counterdiabatic driving. Remarkably, we find extremely short preparation times also in the strongly-interacting regime. Our findings open new possibilities for robust state preparation in atomic quantum simulators.

Wang, Botao (ORCID:0000000282202452)↗