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Results for “Power Efficiency”

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 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Integration of a high oxygen permeability ionomer into polymer electrolyte membrane fuel cell cathodes for high efficiency and power density

In this work, we present a study on the integration of a high oxygen permeability ionomer (HOPI) with high durability carbon supported platinum (Pt/C) catalysts to prepare cathode catalyst layers (CCLs) for polymer electrolyte membrane fuel cells (PEMFCs). A key motivation is the production of PEMFCs with high efficiency and durability for heavy-duty fuel cell vehicles. Our results from integrating a pre-commercial HOPI with robust, state-of-the-art catalysts with medium and low surface area carbon supports show significant increases in specific activities (67% increase over the standard commercial ionomer) at low current densities and reduced oxygen (O 2 ) transport resistances (R O2 ’s) at high current densities, enabling both higher efficiency and peak power density. The reduction in the R O2 with the HOPI is most significant at low relative humidity (RH), due to its more rigid backbone structure resisting compaction at lower water contents. In our ink optimization analysis, we show that the HOPI in this study achieves its peak performance with an ionomer to carbon ratio (I/C) of 0.6 and a moderately alcohol-rich ink solvent when fabricating catalyst layers by the decal method with an automatic wet film coater.

08 HYDROGEN↗
DOE OSTI2022

Development and testing of a solar flux heating freeze recovery system for molten salt parabolic troughs

A major obstacle preventing commercialization of molten salt parabolic trough plants is freeze protection and recovery of the solar field. One of the most common nitrate salt compositions under consideration allows for solar field outlet temperatures up to 565°C and begins solidifying above 240°C. Using molten salt directly in the solar field can significantly reduce thermal energy storage costs and the higher temperature compared to oil heat transfer fluids can power a more efficient power cycle, but the very high freezing point is cause for concern. This work builds on a previous modeling effort investigating different methods for melting Solar Salt frozen in the solar field, which suggested the viability of a novel solar heating method to lower costs of the freeze protection system. In this work higher fidelity models are developed to better investigate the melting process with a more detailed 3D geometry which includes the insulated bellows. The thermal-fluid model of the melting process is updated to include temperature dependent density and data for solid phase properties. In addition, a finite element model is developed to resolve thermal stresses at the point with highest thermal gradients. Results with the new model confirm the viability of using controllable solar flux heating to thaw salt frozen in the solar field without damaging the receiver; however, the presence of non-illuminated sections significantly slows down the melting process. Solar heating simulations with pauses off-sun of 120 and 60 s require 18.5 and 11.9 h to melt salt from a night-time temperature of 10°C with 1000 W m2 DNI, which results in maximum thermal stresses of 48.2 and 53.5 MPa, respectively. Adding 150 W m−1 to the solar heating simulation with a 60 s pause off-sun decreases both the melt time and thermal stresses due to the more uniform heating, suggesting a combined heating method may be the best option.

14 SOLAR ENERGY↗
DOE OSTI2020

Spaceborne Accelerators Portfolio

MeV-range, satellite-mounted electron accelerators are needed for various space-related applications, such measuring the coupling between the magnetotail and ionosphere. The technologies and design approaches being developed for spaceborne accelerators emphasize high reliability, high average power, flexible operation, efficient power use, and operation from low-voltage DC power supplies. These same attributes are also relevant to industrial processing and inspection as well as medical applications.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Experimental Validation of a Modular All-Electric Power Take-Off Topology for Wave Energy Converter Enabling Marine Renewable Energy Interconnection

Power electronic converters are an enabling technology for the emerging marine energy applications, such as using ocean waves to produce electricity. This paper outlines the power take-off system and its key components used in a wave energy converter offering modularity and scalability to generate power efficiently. The proposed power take-off system was implemented based on a modular multilevel converter and could be deployed to convert any alternating current electrical energy to a different alternating current for interconnection to grid or non-grid applications. Examples of widespread deployment are supplying electricity to coastal communities or producing clean drinking water. The analysis using both the simulation tests and laboratory experiments verified the design objectives and basic functionality of the developed power take-off system. An acceptable response using a field programmable gate array-based controlled laboratory testbench was achieved, complying with guidelines specified in the prevalent industry standards. Seamless operation during steady-state and transients for the studied wave energy converter was achieved as supported by the obtained results. The key findings of this work were experimentally examined under different load conditions, direct current bus voltage fluctuations, and generator speed–torque regulation. The ability of the power take-off system to generate high-power quality of the waveforms, e.g., against adhering to the IEEE 519-2022 standard for total harmonic distortion limits, is also confirmed.

Engineering↗
DOE OSTI2024

Modeling the Impacts of Material Properties on Oscillatory Neuron Behavior

In this study, neuromorphic computing, which mimics the functions of biological brains, offers improvements in both latency and energy efficiency over typical von Neumann computing architectures. Spiking neural networks can be especially power-efficient because they encode information temporally and can use more sparse electrical inputs. Here, we study the design of volatile memristors (variable resistors with memory) for neuronal devices, with particular consideration toward the feasibility of all-on-chip oscillation using built-in capacitance. We use circuit simulations to model the behavior of oscillator neurons with a range of realistic material properties. We find that energy inputs increase with insulating-phase resistivity, thermal conductivity, and device aspect ratio. However, we also find that the minimum capacitance needed for oscillation decreases with increasing insulating-phase resistivity, which opposes the constraints for power efficiency. Based on published data on NbO 2 , VO 2 , and EuNiO 3 , we find that existing materials can be engineered for all-on-chip spiking using their parasitic capacitance.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Phase stability and magnetic and electronic properties of a spark plasma sintered CoFe – P soft magnetic alloy

More efficient power conversion devices are able to transmit greater electrical power across larger distances to satisfy growing global electrical needs. A critical requirement to achieve more efficient power conversion are the soft magnetic materials used as core materials in transformers, inductors, and motors. To that effect it is well known that the use of non-equilibrium microstructures, which are, for example, nanocrystalline or consist of single phase solid solutions, can yield high saturation magnetic polarization and high electrical resistivity necessary for more efficient soft magnetic materials. In this work, we synthesized CoFe – P soft magnetic alloys containing nanocrystalline, single phase solid solution microstructures and studied the effect of a secondary intermetallic phase on the saturation magnetic polarization and electrical resistivity of the consolidated alloy. Single phase solid solution CoFe – P alloys were prepared through mechanically alloying metal powders and phase decomposition was observed after subsequent consolidation via spark plasma sintering (SPS) at various temperatures. The secondary intermetallic phase was identified as the orthorhombic (Co x Fe 1-x ) 2 P phase and the magnetic properties of the (Co x Fe 1-x ) 2 P intermetallic phase were found to be detrimental to the soft magnetic properties of the targeted CoFe – P alloy.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Computational design of microarchitected porous electrodes for redox flow batteries

Porous electrodes are used as the core reactive component across electrochemical technologies. In flowing systems, controlling the fluid distribution, species transport, and reactive environment is critical to attaining high performance. However, conventional electrode materials like felts and papers provide few opportunities for precise engineering of the electrode and its microstructure. To address these limitations, architected electrodes composed of unit cells with spatially varying geometry determined via computational optimization are proposed. Resolved simulation is employed to develop a homogenized description of the constituent unit cells. These effective properties serve as inputs to a continuum model for the electrode when used in the negative half-cell of a vanadium redox flow battery. Porosity distributions minimizing power loss are then determined via computational design optimization to generate architected porosity electrodes. The architected electrodes are compared to bulk, uniform porosity electrodes and found to lead to increased power efficiency across operating flow rates and currents. The design methodology is further used to generate a scaled-up electrode with comparable power efficiency to the bench-scale systems. Finally, the variable porosity architecture and computational design methodology presented here thus offers a novel pathway for automatically generating spatially engineered electrode structures with improved power performance.

25 ENERGY STORAGE↗
DOE OSTI2020

The Minos Computing Library: Efficient Parallel Programming for Extremely Heterogeneous Systems

Hardware specialization has become the silver bullet to achieve efficient high performance, from Systems-on-Chip systems, where hardware specialization can be ``extreme'', to large-scale HPC systems. As the complexity of the systems increases, so does the complexity of programming such architectures in a portable way. This work introduces the Minos Computing Library (MCL), as system software, programming model, and programming model runtime that facilitate programming extremely heterogeneous systems. MCL supports the execution of several multi-threaded applications within the same compute node, performs asynchronous execution of application tasks, efficiently balances computation across hardware resources, and provides performance portability. We show that code developed on a personal desktop automatically scales up to fully utilize powerful workstations with 8 GPUs and down to power-efficient embedded systems. MCL provides up to 17.5x speedup over OpenCL on NVIDIA DGX-1 systems and up to 1.88x speedup on single-GPU systems. In multi-application workloads, MCL dynamically resource allocation provides up to 2.43x performance improvement over manual, static allocation of computing resources.

Gioiosa, Roberto↗
DOE OSTI2026

Holistic energy analysis method for thermal management architectures of data centers

Modern high-performance computing (HPC) data centers (DCs), particularly those supporting energy-intensive artificial intelligence (AI) workloads, face escalating thermal management challenges that degrade performance through thermal throttling and drive up cooling power consumption and operational costs. To address this challenge, many have developed a wide variety of thermal management solutions (single-phase, two-phase, direct, indirect, hybrid, and more) which attempt to cool HPC DCs effectively while attempting to minimize overall system power consumption. However, the analysis of these solutions and methods to effectively compare one with another is lacking. Overall power usage effectiveness (PUE) and total-power usage effectiveness (TUE) provide a metric to quantify power consumption but fail to identify components in the system which require further optimization. To address this, we propose a holistic analytical framework – the waterfall diagram (WFD) – which leverages a waterfall chart methodology, offering a comprehensive visualization of both the thermal management system loop and heat flow pathways from individual server components to the outdoor ambient. Use of the WFD enables graphical estimations of power efficiency and cooling performance across each component of a DC cooling system and complements Sankey-style energy flow visualizations by additionally resolving stage-wise temperature changes and incremental TUE contributions. The framework is used in conjunction with simulation-based approaches, to conduct a detailed pressure drop and flow distribution analysis aimed at identifying the optimal coolant distribution architecture for a single-phase direct-to-chip water-cooled DC, which serves as the baseline for subsequent WFD analysis. Among the evaluated architectures, the 3 U modular coolant distribution architecture is found to demonstrate the best performance, considering minimal pressure drop and uniform flow distribution. In addition, TUE is calculated for each cooling loop component based on its associated pressure drop and corresponding pumping power, which are integrated into the WFD. This correlation between TUE and local temperature offers immediate insight into the power efficiency and thermal performance contributions of individual components, facilitating further development and optimization. Examples of WFD applications are presented under varying thermal loads and ambient conditions, demonstrating reasonable cooling strategies. Notably, the 3 U modular architecture maintains a consistent chip case temperature of 85°C, achieving a TUE of 1.016 at ambient temperature of 47°C, and a TUE of 1.026 at ambient temperature of 52°C. The WFD methodology provides an efficient, holistic, and streamlined framework for DC thermal management architecture assessment and enables design optimization which is important for addressing the thermal-fluidic energy challenges of current and next-generation DCs.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Solid-State Lighting Using Side-by-Side White Phosphorescent Organic Light-Emitting Diodes

White organic light-emitting diodes (WOLEDs) have become increasingly popular for use in solid-state illumination, where diffuse, large area light sources that achieve a high color rendering index and luminous power efficiency are desirable. Color-tunable emission, where the light source combines emission from multiple, separately addressed color elements, is conveniently provided by WOLEDs for the purpose of adapting the lighting source to a particular illumination requirement. In this work, we demonstrate a method for side-by-side positioning of monochromatic blue and yellow phosphorescent OLED stripes that are combined to create tunable white light, using a high resolution mechanical peel-off patterning method. We achieve a peak luminous power efficiency of 17.1 ± 0.3 lm W –1 and an external quantum efficiency of 11.8 ± 0.2% and demonstrate color tunability of the 1960 Commission Internationale d’Eclairage chromaticity coordinates from (u,v) = (0.33,0.36) to (0.12,0.32). This corresponds to a tuning rnge of the color rendering index from 74 ± 1 to 86 ± 1 and the correlated color temperature from 2000 to 8000 ± 500 K. Here, due to the nondestructive nature of the peel-off technique, patterned devices exhibit a lifetime comparable to conventional, shadow mask-patterned devices.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Frequency Domain Detection and Precoding for Massive MIMO With Single Carrier Modulation

Single carrier modulation (SCM) schemes are attractive for uplink (UL) transmissions due to improved power efficiency at the user equipment (UE) transmitter compared with multi-carrier modulation schemes. In a massive MIMO scenario with SCM, the UL detection must mitigate the effects of inter-symbol interference and multiuser interference. This processing is effectively performed in the frequency domain (FD) using a minimum mean squared error (MMSE) detector when the transmission is framed with a cyclic prefix. This paper presents a MMSEbased detector that is compatible with distributed processing in a time-division duplex (TDD) system. The matrix inverses computed for the UL detection are then reused to perform multi-user precoding for the downlink (DL). We find that this scheme yields a tremendous savings in computational complexity compared to commonly used zero-forcing (ZF) precoding without sacrificing any performance. Since MMSE processing introduces a bias to the estimates, we then derive the scalar coefficients necessary to cancel the MMSE bias. The impact of channel estimation errors are analyzed for both the UL and DL cases in conjunction with a power-efficient approach to SCM channel estimation. Moreover, extensive simulations are performed to confirm our theoretical findings.

42 ENGINEERING↗
DOE OSTI2024

Exploring the Frontiers of Energy Efficiency using Power Management at System Scale

In the face of surging power demands for exascale HPC systems, this work tackles the critical challenge of understanding the impact of software-driven power management techniques like Dynamic Voltage and Frequency Scaling (DVFS) and Power Capping. These techniques have been actively developed over the past few decades. By combining insights from GPU benchmarking to understand application power profiles, we present a telemetry data-driven approach for deriving energy savings projections. This approach has been demonstrably applied to the Frontier supercomputer at scale. Our findings based on three months of telemetry data indicate that, for certain resource-constrained jobs, significant energy savings (up to 8.5%) can be achieved without compromising performance. This translates to a substantial cost reduction, equivalent to 1438 MWh of energy saved. The key contribution of this work lies in the methodology for establishing an upper limit for these best-case scenarios and its successful application. This work enables HPC professionals to optimize the power-performance trade-off within constrained power budgets, not only for the exascale era but also beyond.

Karimi, Ahmad Maroof↗
DOE OSTI2024

Ion transport and ultra-efficient osmotic power generation in boron nitride nanotube porins

Nanotube porins form transmembrane nanomaterial-derived scaffolds that mimic the geometry and functionality of biological membrane channels. We report synthesis, transport properties, and osmotic energy harvesting performance of another member of the nanotube porin family: boron nitride nanotube porins (BNNTPs). Cryo–transmission electron microscopy imaging, liposome transport assays, and DNA translocation experiments show that BNNTPs reconstitute into lipid membranes to form functional channels of ~2-nm diameter. Ion transport studies reveal ion conductance characteristics of individual BNNTPs, which show an unusual C 1/4 scaling with ion concentration and pronounced pH sensitivity. Reversal potential measurements indicate that BNNTPs have strong cation selectivity at neutral pH, attributable to the high negative charge on the channel. BNNTPs also deliver very large power density up to 12 kW/m 2 in the osmotic gradient transport experiments at neutral pH, surpassing that of other BNNT-based devices by two orders of magnitude under similar conditions. Our results suggest that BNNTPs are a promising platform for mass transport and osmotic power generation.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Operational Probabilistic Tools for Solar Uncertainty (OPTSUN) (Final Project Report for DOE Solar Forecasting II Project)

Increasing levels of solar PV can challenge system operations and may require novel methods to operate the power system reliably and efficiently. Power system operating plans generally use deterministic forecasts, in which the variable energy resources are represented by the expected value for each interval of the decision horizon. Probabilistic forecasts are relatively new but have the potential to address the shortfalls of deterministic forecasts. However, understanding how best to use such forecasts is still a key gap in industry and was the focus of this project. The project had three workstreams. In a forecasting workstream, improvements were made to baseline probabilistic forecasts using a number of new approaches such as machine learning methods and improved input data. In a design workstream, advanced simulation tools used these forecasts to investigate newly proposed reserve determination methods. Lastly, in a demonstration workstream a scheduling management platform (SMP) was developed to leverage probabilistic forecasts in a modular and customizable manner. In order to study the benefits that could be accrued, the project team collaborated with three utility partners (Duke Energy, Southern Company and Hawaiian Electric) to deliver improved probabilistic forecasts for each region and to model each region in case studies using advanced production cost modeling tools. Different methods to determine operating reserve requirements from probabilistic forecasts were developed, simulated, and tested across each region. The benefits of using these newly proposed methods varied by utility, but, in general, using probabilistic forecasts as well as historical data to set the reserve requirements seems to improve reliability related results, with less risk of reserve or supply shortfalls. The cost implications were not always straightforward; in some cases the new methods could show a reduction in expected operating costs, but often the increase in reserves associated with better risk mitigation using probabilistic forecasts could result in an increase in operating costs in the simulations. The SMP tool was developed to process probabilistic forecasts from their initial receipt through to scheduling decisions. This open-source tool consists of several modules for scenario development, reserve requirements calculation, and visualization. The SMP tool was demonstrated to a wide range of operators and stakeholders at all three utilities and further improved based on their feedback. The tool will be available on www.epri.com/optsun. The proposed probabilistic information-based reserve determination approaches have the potential to be implemented by different regions to ensure an economic and reliable power system operation on power systems integrating increasing levels of variable renewable resources. The innovative yet practical methods developed in this project demonstrated tangible benefits from using probabilistic forecasts beyond just study-based assessments to include three unique balancing areas. The demonstrated benefits across the multiple utility environments, are expected to provide system operators in all regions the confidence required and a platform to adopt the new forecasting and operating methods.

14 SOLAR ENERGY↗