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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 721 records · Page 40
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Comparative Study of Nonlinear Black-Box Modeling for Power Electronics Converters

With the increasing penetration level of renewable sources and power electronics loads in modern power systems, accurate and computationally efficient models are needed. Black-box model (BBM) could be a useful method in such systems. However, not very extensive research efforts have been made for power electronics BBM so far, and existing works mostly focus on steady-state operation, neglecting the important transient behaviors such as load transients, voltage transients, and faults. This paper presents a comparative study of three commonly used nonlinear BBM approaches for transient behaviors of power electronics converters. Comparison methods are proposed, and the evaluations are conducted under different transients using a grid-connected single-phase photovoltaic inverter. The findings of this study provide valuable references for further feasibility investigations on implementing BBMs in large-scale power electronics-rich power systems.

Qiao, Liang↗
DOE OSTI2022

Sim-Situ: A Framework for the Faithful Simulation of in situ Processing

The amount of data generated by numerical simulations in various scientific domains led to a fundamental redesign of how the analysis and visualization of simulation outputs are performed. The throughput and capacity of storage subsystems have not evolved as fast as the computing power in extreme-scale supercomputers, making the classical post-hoc approach highly inefficient. In situ processing has then emerged as a solution in which simulation and data analysis/visualization are intertwined for better performance and greater interactivity.Determining the best allocation, i.e., how many resources to allocate to simulation and analysis respectively, mapping, i.e., where and at which frequency to run the analysis/visualization, and data transfer mode is a complex task whose performance assessment is crucial to the efficient execution of in situ processing. However, such a performance evaluation of different strategies usually relies either on directly running them on the targeted execution environments, which can rapidly become extremely time- and resource-consuming, or on resorting to simplified models of the components of an in situ application, which can lack of realism. In both cases, the validity of the performance evaluation is limited.In this paper, we present Sim-Situ, a simulation-based framework for the faithful performance evaluation of in situ processing strategies. We designed Sim-Situ to reflect the typical features of in situ processing systems. Thanks to its modular design, Sim-situ has the necessary flexibility to easily and faithfully evaluate the behavior and performance of various allocation, mapping, and data transfer strategies. We illustrate the simulation capabilities of Sim-Situ on a Molecular Dynamics use case. We study the impact of different strategies on performance and show how users can leverage Sim-Situ to determine interesting tradeoffs when adding analysis/visualization components to their application.

Honoré, Valentin↗
DOE OSTI2022

Running Ensemble Workflows at Extreme Scale: Lessons Learned and Path Forward

The ever-increasing volumes of scientific data combined with sophisticated techniques for extracting information from them have led to the increasing popularity of ensemble workflows which are a collection of runs of individual workflows. A traditional approach followed by scientists to run ensembles is to rely on simple scripts to execute different runs and manage resources. This approach is not scalable and is error-prone, thereby motivating the development of workflow management systems that specialize in executing ensembles on HPC clusters. However, when the size of both the ensemble and the target system reach extreme scales, existing workflow management systems face new challenges that hamper their efficient execution. In this paper, we describe our experience scaling an ensemble workflow from the computational biology domain from the early design stages to the execution at extreme scale on Summit, a leadership class supercomputer at the Oak Ridge National Laboratory. We discuss challenges that arise when scaling ensembles to several million runs on thousands of HPC nodes. We identify challenges with composition of the ensemble itself, its execution at large scale, post-processing of the generated data, and scalability of the file system. Based on the experience acquired, we develop a generic vision of the capabilities and abstractions to add to existing workflow management systems to enable the execution of ensemble workflows at extreme scales. We believe that the understanding of these fundamental challenges will help application teams along with workflow system developers with designing the next generation of infrastructure for composing and executing extreme-scale ensemble workflows.

Mehta, Kshitij↗
DOE OSTI2024

Automated Calibration of Parallel and Distributed Computing Simulators: A Case Study

Many parallel and distributed computing research results are obtained in simulation, using simulators that mimic real-world executions on some target system. Each such simulator is configured by picking values for parameters that define the behavior of the underlying simulation models it implements. The main concern for a simulator is accuracy: simulated behaviors should be as close as possible to those observed in the real-world target system. This requires that values for each of the simulator's parameters be carefully picked, or “calibrated,” based on ground-truth real-world executions. Examining the current state of the art shows that simulator calibration, at least in the field of parallel and distributed computing, is often undocumented (and thus perhaps often not performed) and, when documented, is described as a labor-intensive, manual process. In this work we evaluate the benefit of automating simulation calibration using simple algorithms. Specifically, we use a real-world case study from the field of High Energy Physics and compare automated calibration to calibration performed by a domain scientist. Our main finding is that automated calibration is on par with or significantly outperforms the calibration performed by the domain scientist. Furthermore, automated calibration makes it straightforward to operate desirable tradeoffs between simulation accuracy and simulation speed.

Mc donald, Jesse↗
DOE OSTI2024

Scaling Ensembles of Data-Intensive Quantum Chemical Calculations for Millions of Molecules

Deep learning models are efficient computational tools that can accelerate the inverse design of molecules with desired functional properties by generating predictions at a fraction of the time required by traditional quantum chemical approaches. To ensure that a model maintains accuracy and transferability across broad regions of the chemical space explored during the inverse design, it must be trained on massively large volumes of simulation data. This requires running large-scale ensemble quantum chemical calculations on high-performance computing (HPC) systems for data collection. However, the efficient execution of such large ensemble calculations and the management of large volumes of output data require tools that can judiciously utilize computational resources and manage metadata overhead on the file system. Therefore, we present a high-performance, scalable, ensemble management framework for performing data-intensive quantum chemical electronic structure calculations for organic molecules. This framework provides abstractions to plug different ab initio, first principles, and first principles-based semi-empirical methods and executes them efficiently at large scale on HPC systems. It dynamically distributes tasks to resources and uses tiered storage for managing large collections of files. We employed this framework to process over ten million organic molecules and generate open-source datasets that provide UV-vis absorption spectra by running time-dependent density-functional tight-binding calculations. It is the largest database containing molecular optical spectra that were simulated with quantum chemical methods in a consistent manner.

Mehta, Kshitij↗
DOE OSTI2016

Circulating Current Suppressing Control’s Impact on Arm Inductance Selection for Modular Multilevel Converter

Arm inductor in a modular multilevel converter (MMC) is used to limit the circulating current and dc short circuit fault current. The circulating current in MMC is dominated by second-order harmonic, which can be largely reduced with circulating current suppressing control. By analyzing the mechanism of the circulating current suppressing control, it is found that the circulating current at switching frequency becomes the main harmonic when suppression control is implemented. Unlike the second-order harmonic that circulates only within the three phases, switching frequency harmonic also flows through the dc side and may further cause high-frequency dc voltage harmonic. This article develops the theoretical relationship between the arm inductance and switching frequency circulating current, which can be used to guide the arm inductance selection. The experimental results with a downscaled MMC prototype verify the existence of the switching frequency circulating current and its relationship with arm inductance.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2019

Optimal Design of Megahertz $LLC$ Converter for 48-V Bus Converter Application

Intermediate bus architecture employing 48-V bus converters is widely used in power supply applications. With the rapid increase of demanded power by these loads, higher efficiency and power density are driving better performance power management solutions. In this article, a Gallium Nitride (GaN) based design of a two-stage solution is proposed. The first stage is a multi-phase Buck for regulation. The second stage is an LLC converter with a fixed switching frequency for isolation. The detailed design and optimization of the LLC converter are studied. To achieve high power density and high efficiency, the transformer design becomes critical at megahertz frequency. The matrix transformer concept is applied and a merged winding structure is used for flux cancellation, which effectively reduces the ac winding losses. A novel primary termination and via structure is proposed, resulting in a great loss reduction. In addition, to study the current sharing of parallel winding layers, a 1-D analytic model is proposed, and a symmetrical winding layer scheme is used to balance the current distribution. Finally, the prototype for the two-stage bus converter is developed, with a peak efficiency of 96% and a power density of 615 W/in 3 .

42 ENGINEERING↗
DOE OSTI2020

Design Optimization of Medium-Frequency Transformer for DAB Converters With DC Bias Capacity

Medium-frequency transformer (MFT) dc bias is critical for the safe operation of dual-active-bridge (DAB) converters. To analyze the dc bias, expressions of dc bias are derived for SiC MOSFET DAB converters. It shows that the dc bias is a current source in steady state; thus, a dc bias current capacity is defined and used as a design constraint in the optimization of MFT. The dc bias current capacity is related to core materials, geometric parameters, and flux density, which is analyzed with analytical expression. Optimization equations with geometric variables are derived, which can be solved theoretically or numerically for both interleaved winding (IW) and separated winding (SW) MFT without and/or with leakage inductance design. Based on the optimization equations, different MFT designs for a 150-kW SiC MOSFET DAB converter are compared on the aspects of core materials, winding structures, and without/with leakage inductance design. The combination of IW structure MFT with auxiliary phase shift inductors is chosen, and the assembled prototype is tested with the 150-kW DAB converter. Here, the designed dc bias capacity, temperature rise, and efficiency are verified.

42 ENGINEERING↗
DOE OSTI2015

Solitary Waves of a $\mathcal {P}$ $\mathcal {T}$ -Symmetric Nonlinear Dirac Equation

In our study we consider we consider a prototypical example of a mathcalP mathcalT-symmetric Dirac model. We discuss the underlying linear limit of the model and identify the threshold of the mathcalP mathcalT -phase transition in an analytical form. We then focus on the examination of the nonlinear model. We consider the continuation in the mathcalP mathcalT -symmetric model of the solutions of the corresponding Hamiltonian model and find that the solutions can be continued robustly as stable ones all the way up to the mathcalP mathcalT-transition threshold. In the latter, they degenerate into linear waves. We also examine the dynamics of the model. Given the stability of the waveforms in the mathcalP mathcalT-exact phase, we consider them as initial conditions for parameters outside of that phase. We also find that both oscillatory dynamics and exponential growth may arise, depending on the size of the corresponding “quench”. The former can be characterized by an interesting form of bifrequency solutions that have been predicted on the basis of the SU symmetry. Finally, we explore some special, analytically tractable, but not mathcalP mathcalT-symmetric solutions in the massless limit of t- e model.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Explaining Neural Spike Activity for Simulated Bio-plausible Network through Deep Sequence Learning

With significant improvements in large-scale simulations of brain models, there is a growing need to develop tools for rapid analysis and interpreting the simulation results. In this work, we explore the potential of sequential deep learning models to understand and explain the network dynamics among the neurons extracted from a large-scale neural simulation in STACS (Simulation Tool for Asynchronous Cortical Stream). Our method employs a representative neuroscience model that abstracts the cortical dynamics with a reservoir of randomly connected spiking neurons with a low stable spike firing rate throughout the simulation duration. We subsequently analyze the spike dynamics of the simulated spiking neural network through an autoencoder model and an attention-based mechanism.

Kulkarni, Shruti↗
DOE OSTI2020

Reconfigurable Real-Time Power Grid Emulator for Systems With High Penetration of Renewables

Novel power system control and new utility devices need to be tested before their actual deployment to the power grid. To assist with such a testing need, real-time digital emulators such as RTDS and Opal-RT can be used to connect to the physical world and form a hardware in the loop (HIL) emulation. However, due to the limitations of today's computational resources, the accuracy and fidelity suffer from different levels of model reductions in purely digital simulations. CURENT has developed a reconfigurable electric grid hardware testbed (HTB) to overcome the limitations of digital emulators. The HTB has been used to develop measurement, control, modeling, and actuation techniques for a national grid with a high penetration of renewables. The power electronic-based system includes emulators for synchronous generators; photovoltaics with grid-interfacing inverter; wind turbines; induction motor loads, ZIP loads, power electronic loads; batteries; ac and dc transmission lines; short circuit faults and grid relay protection; and a multiterminal HVDC overlay including power electronics interfaces. The system contains real elements of power flow, measurement, communication, protection, and control that mimic what would be seen in an actual electric grid. This paper presents an overview of the HTB and several scenarios that have been run to determine control and actions needed for the future power grid.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Spectral Clustering-Based Partitioning of Large-Scale Power Electronics-Based Power Systems for Small-Signal Stability Analysis

The nodal admittance matrix (NAM)-based approach is well-suited for small-signal stability analysis of large-scale power electronics-based power systems (PEPSs), as it preserves the system structure through its admittance matrix. Previous studies have explored partitioning such systems into subareas and interconnections to reduce computational burden; however, they lacked a formal algorithmic procedure for determining feasible partitions. While several grid partitioning methods, such as those based on graph theory or machine learning, exist in the literature, they cannot be directly applied to NAM-based analysis due to differing objectives and constraints. Here, this paper addresses this gap by presenting a systematic, step-by-step procedure for applying a spectral partitioning algorithm that yields a division of the system into subareas suitable for NAM-based analysis. The computational complexity of the proposed method is also derived to demonstrate its efficiency and justify the practicality of the resulting subarea decomposition. The performance of the partitioning method is evaluated by applying the spectral clustering-derived subareas and interconnections to the NAM-based partitioning approach on a 140-bus system. Computational times for the full-system and partitioned NAM analyses are compared using MATLAB. Additionally, PSCAD simulations of the complete system and partitioned subareas are carried out to verify the effectiveness of the proposed method.

Nupur [Univ. of Tennessee, Knoxville, TN (United S↗
DOE OSTI2021

Primary Frequency Control Using Motor Drives for Short Term Grid Disturbances

Industrial motor systems make up a quarter of all electric sales in the United States. Variable speed drives (VSDs) can provide energy efficiency savings to the customer by regulating motor speed based on specific and varying needs. In addition to the benefits provided to the customer, VSDs can provide support to the grid through ancillary services. The Center for Ultra-Wide-Area Resilient Electric Energy Transmission Networks (CURENT) developed a power electronics converter-based grid emulator to allow testing of various power system architectures and demonstration of key technologies in monitoring, control, actuation, and visualization. This paper proposes using an active front-end VSD's connected motor load to provide frequency regulation to a large scale power grid. Each part of the emulator is described including motor and power electronics model and control. The proposed frequency regulation is implemented in VSDs and modeled in both a transmission system in EMTDC/PSCAD and verified on CURENT's hardware testbed.

24 POWER TRANSMISSION AND DISTRIBUTION↗