Tuning Amorphous Selenium Composition with Tellurium to Improve Quantum Efficiency at Long Wavelengths and High Applied Fields
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37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
SEARCH · Engineering Papers
Results for “efficiency improvement”
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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Separating Physics and Dynamics Grids for Improved Computational Efficiency in Spectral Element Earth System Models
Previous studies have shown that atmospheric models with a spectral element grid can benefit from putting physics calculations on a relatively coarse finite volume grid. Here we demonstrate an alternative high-order, element-based mapping approach used to implement a quasi-equal-area, finite volume physics grid in E3SM. Unlike similar methods, the new method in E3SM requires topology data purely local to each spectral element, which trivially allows for regional mesh refinement. Simulations with physics grids defined by 2 × 2, 3 × 3, and 4 × 4 divisions of each element are shown to verify that the alternative physics grid does not qualitatively alter the model solution. The model performance is substantially affected by the reduction of physics columns when using the 2 × 2 grid, which can increase the throughput of physics calculations by roughly 60%–120% depending on whether the computational resources are configured to maximize throughput or efficiency. A pair of regionally refined cases are also shown to highlight the refinement capability.
71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
Cabin and Battery Thermal Management of Connected and Automated HEVs for Improved Energy Efficiency Using Hierarchical Model Predictive Control
Not provided.
Automation & Control Systems↗
Dynamic Undervolting to Improve Energy Efficiency on Multicore X86 CPUs
Chip manufacturers introduce redundancy at various levels of CPU design to guarantee correct operation, even for worst-case combinations of non-idealities in process variation and system operating conditions. This redundancy is implemented partly in the form of voltage margins. However, for a wide range of real-world execution scenarios these margins are excessive and merely translate to increased power consumption, hindering the effort towards higher-energy efficiency in both HPC and general purpose computing. Our study on the x86-64 Haswell and Skylake multicore microarchitectures reveals-wide voltage margins, which vary across different microarchitectures, different chip parts of the same microarchitecture, and across different workloads. We find that it is necessary to quantify-voltage margins using multi-threaded and multi-instance workloads, as characterization with single-threaded and single-instance workloads that do not stress the CPU to its full capacity typically identifies overly optimistic margins that lead to errors when applied in realistic program execution scenarios. In addition, we introduce, deploy and evaluate a run-time governor that dynamically reduces the supply voltage of modern multicore x86-64 CPUs. Our governor employs a model that takes as input a set of performance metrics which are directly measurable via performance monitoring counters and have high predictive value for the minimum tolerable supply voltage (V min ), to predict and apply the appropriate reduction for the workload at hand. Compared with the conventional DVFS governor, our approach in this study achieves up to 42 percent energy savings for the Skylake family and 34 percent for the Haswell family for complex, real-world applications.
97 MATHEMATICS AND COMPUTING↗
Ecological Adaptive Cruise Control of Plug-In Hybrid Electric Vehicle With Connected Infrastructure and On-Road Experiments
Abstract This paper examines both mathematical formulation and practical implementation of an ecological adaptive cruise controller (ECO-ACC) with connected infrastructure. Human errors are typical sources of accidents in urban driving, which can be remedied by rigorous control theories. Designing an ECO-ACC is, therefore, a classical research problem to improve safety and energy efficiency. We add two main contributions to the literature. First, we propose a mathematical framework of an online ECO-ACC for plug-in hybrid electric vehicle (PHEV). Second, we demonstrate ECO-ACC in a real world, which includes other human drivers and uncertain traffic signals on a 2.6 (km) length of the corridor with eight signalized intersections in Southern California. The demonstration results show, on average, 30.98% of energy efficiency improvement and 8.51% additional travel time.
Automation & Control Systems↗
Improving the efficiency of Rubisco by resurrecting its ancestors in the family Solanaceae
Plants and photosynthetic organisms have a remarkably inefficient enzyme named Rubisco that fixes atmospheric CO 2 into organic compounds. Understanding how Rubisco has evolved in response to past climate change is important for attempts to adjust plants to future conditions. In this study, we developed a computational workflow to assemble de novo both large and small subunits of Rubisco enzymes from transcriptomics data. Next, we predicted sequences for ancestral Rubiscos of the (nightshade) family Solanaceae and characterized their kinetics after coexpressing them inEscherichia coli. Predicted ancestors of C 3 Rubiscos were identified that have superior kinetics and excellent potential to help plants adapt to anthropogenic climate change. Our findings also advance understanding of the evolution of Rubisco’s catalytic traits.
59 BASIC BIOLOGICAL SCIENCES↗
CRAVE: Analyzing Cross-Resource Interaction to Improve Energy Efficiency in Systems-on-Chip
Explore the source record for details and available documents.
Ma, Tian J. [Sandia National Laboratories (SNL-NM)↗
Modeling the Environment-Dependent Kinetics of Oxygen Reduction Reaction – a Continuum Model for Electric Double Layer
Here, for proton-exchange-membrane fuel cells (PEMFCs) to achieve broad commercialization, improved energy-conversion efficiency with minimal Pt-based electrocatalyst is required. Because the sluggish rate of oxygen reduction reaction (ORR) limits the efficiency of PEMFCs, the efficiency improvement requires a better understanding of ORR kinetics and mechanism to design better catalyst. To understand the ORR mechanism, theoretical and experimental analyses have been conducted. While previous studies reasonably explained the catalyst-dependent activity on single crystal catalysts in 0.1 M perchloric acid solution, the explicit effect of electrolyte and related microenvironments is not thoroughly understood. The change in the electrolyte alters the electric-double-layer (EDL) structure and thus the local microenvironment at the electrode/electrolyte interface. Thus, the structure of the EDL should be carefully analyzed to uncover the electrolyte-dependent reaction kinetics. In this talk, we propose a multiscale continuum model to predict the EDL structure and examine the effect of perchloric acid concentration on ORR activity on Pt (111). The model includes Density Potential Functional Theory (DPFT) for electron density and Modified Poisson Boltzmann equation for species’ density and electric potential. Also, the interaction between adsorbents and electric field is taken into account by minimizing the grand potential. After model validation with experimentally measured double-layer capacity data as a function of applied potential and concentration, the effect of the perchloric acid concentration (0.02 M – 0.2 M) on ORR activity is analyzed and discussed. It is shown that the model reproduces the specific activity obtained in the experiments when assuming the oxygen adsorption is limiting the rate, which can be attributed to the large energetic barrier for solvent reorganization. Then, extension of the model to PEMFC ionomer electrolytes will be introduced. Overall, the model framework and findings provide insights into the ORR mechanism and guidance on how to tailor catalyst materials for increased PEMFC performance.
30 DIRECT ENERGY CONVERSION↗
Long-Term Vehicle Speed Prediction via Historical Traffic Data Analysis for Improved Energy Efficiency of Connected Electric Vehicles
Connected and automated vehicles (CAVs) are expected to provide enhanced safety, mobility, and energy efficiency. While abundant evidence has been accumulated showing substantial energy saving potentials of CAVs through eco-driving, traffic condition prediction has remained to be the main challenge in capitalizing the gains. The coupled power and thermal subsystems of CAVs necessitate the use of different speed preview windows for effective and integrated power and thermal management. Real-time vehicle-to-infrastructure (V2I) communications can provide an accurate speed prediction over a short prediction horizon (e.g., 30 s to 60 s), but not for a long range (e.g., over 180 s). Therefore, advanced approaches are required to develop detailed speed prediction for robust optimization-based energy management of CAVs. This paper presents an integrated speed prediction framework based on historical traffic data classification and real-time V2I communications for efficient energy management of electrified CAVs. The proposed framework provides multi-range speed predictions with different fidelity over short and long horizons. The proposed multi-range speed prediction is integrated with an economic model predictive control (MPC) strategy for the battery thermal management (BTM) of connected and automated electric vehicles (EVs). The simulation results over real-world urban driving cycles confirm the enhanced prediction performance of the proposed data classification strategy over a long prediction horizon. Despite the uncertainty in long-range CAVs’ speed predictions, the vehicle-level simulation results show that 14% and 19% energy savings can be accumulated sequentially through eco-driving and BTM optimization (eco-cooling), respectively, when compared with normal driving (i.e., human driver) and conventional BTM strategy.
Engineering↗
Improving Energy Efficiency of Wireless Communication Circuitry in Miscellaneous Electric Loads (Final Report)
The overarching objective of this project is to reduce phantom power in miscellaneous electric loads (MELs). We achieve this power reduction with a wireless Connectivity Module that uses ultra-low power (ULP) custom wakeup receivers (WRXs) paired with an ULP node controller (NC) chip. These components can remain always-on at power levels much lower than the inherent standby power of MELs, allowing them to cut off the phantom power to the MELs device while still preserving responsiveness of the MELs devices with low latency when they are needed, either via a wireless wakeup signal received by the WRX or a prediction that the device is needed based on a model.
32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
Improving Energy Efficiency and Self-Sufficiency on the Pechanga Indian Reservation
This project will study the feasibility and identify the preferred options necessary to allow the Pechanga Tribal Utility, now renamed Pechanga Western Electric (“PWE”) to carefully and thoughtfully expand from providing electrical service to the Tribe’s commercial enterprises and government center loads to also providing electrical service to the Tribe’s over 300 residential loads and potential future non-tribal commercial loads on the reservation. As well as, explore an option under which PWE will acquire solar and battery storage systems for the residential community.
14 SOLAR ENERGY↗
Fabrication of Advanced Nanocarbon-Metal Composites for Improved Energy Efficiency
We fabricated nanocarbon metal composites (NCMC) of Al alloys with a process called “electrocharging assisted process” (EAP). This method consists of the application of a high current to a mixture of liquid metal and carbon particles. We investigated aluminum alloys (6061 and 1350) and used activated carbon and graphite powder as the source of carbon. The high current induces the formation of carbon chains and ribbons in the liquid metal. Upon solidification of the metal an epitaxial relation between the carbon nanostructures and the metal lattice is produced. The purpose of the project was to find the parameters during the reaction that would give rise to a high density of nanoribbons extending throughout the metal such that the electrical conductivity and the mechanical strength of the composite increased and that the method could be extended to large scale manufacturing. For this purpose, we designed two reactors for the incorporation of nanocarbon ribbons in aluminum metal. The first reactor was designed to have more control of the region with the high current density. However, there were problems with getting good mixing of the carbon in small volumes. A second reactor was designed with a stirrer that allowed for better mixing of the carbon by the introduction of argon gas through the shaft of the stirrer. NCMC were fabricated with a series of parameters to understand the role of current, time of applied current, type and shape of the cathode electrode and stirring speed of the mixture. We analyzed the composites by Raman scattering to gain information on the crystallite size of the nanocarbon, XRD to obtain the crystal structure of the composite, SEM and TEM to characterize the grain size of the aluminum grains and the quality of the crystal structure. We also measured the electrical conductivity and mechanical properties of selected samples. The nanocomposites showed increase in crystallite size of the nanocarbon with a linear dependence of the crystallite size on the duration of the applied current. There is a minimum current density necessary for the crystallite size to increase compared to the ~ 10 nm size of the activated carbon source used in the fabrication. The electrical conductivity of the nanocomposites increased with crystallite size of the nanocarbon and with the concentration of converted carbon. The maximum increase in electrical conductivity was 5.7% above the baseline for samples with ~ 4 wt % nanocarbon with crystallite size larger than 30 nm. These samples presented a hardness ~ 8% higher than the baseline samples with no carbon.
24 POWER TRANSMISSION AND DISTRIBUTION↗
A Guide for Creating a Building-Level Action Plan to Improve Energy Efficiency and Reduce Carbon Emissions
Action plans are tools for commercial building owners to create pathways for reducing energy use and decarbonize, hence reducing carbon emissions. This template and associated direction manual provides a method for creating an action plan. Originally created for the Better Buildings Low Carbon Pilot, it can also be applied to the Better Buildings Climate Challenge and for any building owner striving towards lower carbon footprints.
32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
Policy Framework to Improve Mobility Efficiency and Electrify Transportation in Tonga
The Kingdom of Tonga, like many small island developing states, is heavily dependent on imported fossil fuels to meet its current energy needs, especially for transportation. The Kingdom has requested a policy framework that benefits its land transportation sector by saving cost and time, increasing resilience, and reducing petroleum and greenhouse gas (GHG) emissions. This framework was developed by building on past work, namely the Tonga Energy Efficiency Master Plan 2020-2030 (TEEMP), the Tonga Energy Road Map 2021-2035 (TERMPLUS), and the Regional Electric Mobility Policy for Pacific Island Countries and Territories developed by the Pacific Centre for Renewable Energy and Energy Efficiency (PCREEE). The strengths, weaknesses, opportunities, and threats to Tonga's land transportation system were identified at stakeholder working group meetings in Tonga in June 2023. A set of appropriate policies that have been effective in relevant jurisdictions were then discussed and refined by the working group. The resulting 27 policies are defined according to intended outcomes, relationship to other proposed policies, applications in other relevant jurisdictions, hurdles to implementation, resilience impact, equity impact, and government revenue impact. Some of the policies are also accompanied by implementation recommendations.
29 ENERGY PLANNING, POLICY, AND ECONOMY↗
Nuclear imaging to diagnose and correct target-driver registration at high-repetition-rate for improved reactor efficiency
Inertial Confinement Fusion produces energy from a burning plasma lasting a fraction of a nanosecond. Power plant designs based on Inertial Fusion Energy (IFE) will need to ignite targets 1-10 times a second, fired as projectiles into a chamber and delivering the driver to the target location. Driver asymmetry is known to impact ICF experiments at gain near unity and remains a candidate for primary yield degradation, and therefore fusion power plant energy output, for high-gain target designs. For a Fusion Power Plant (FPP), continuous and real-time monitoring of target performance provides an opportunity to stabilize or correct the target-driver registration. This requires x-ray and neutron imaging with a large field-of-view, sufficiently high resolution, fast analysis and to subtend a minimal solid angle. We introduce design criteria for such an imaging system that uses a coded aperture and time-gated, lens-coupled scintillators as a viable solution and outline the research steps required to field such a system. Integrating the imaging system into an IFE power plant as part of an active feedback loop could increase average power output by reducing the failure rate due to mis-aligned drivers with respect to the target.
46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
Louisville Communities LEAP Engagement: Improving Energy Efficiency in Affordable Housing [Slides]
This presentation outlines the initial results from a year-plus engagement between the National Renewable Energy Lab and Louisville, Kentucky through the U.S. Department of Energy's Communities LEAP (Local Energy Action Program) effort. Louisville, as represented by the Louisville Metro Government, Kentuckians for the Commonwealth, and the Metropolitan Housing Coalition, sought technical assistance from the labs to address energy usage in its residential housing stock as part of efforts to reduce community-wide emissions and high energy burdens throughout its community. The Communities LEAP scope of work included an energy efficiency analysis that leveraged ResStock data to identify key efficient technologies to explore for retrofitting Louisville's housing stock; technical support around developing a community benchmarking ordinance to help Louisville track its progress towards reducing energy usage; a workforce development overview to help Louisville ensure a sufficient and equitable distribution of clean-energy-related jobs supported by its energy efficiency efforts; a policy analysis component to track energy efficiency related policies Louisville may be interested in adapting from peer communities across the country; and a financing analysis component to identify opportunities to lower the barrier to clean energy adoption.
29 ENERGY PLANNING, POLICY, AND ECONOMY↗
Modularization of EDGE Workflows Using Nextflow: Improving the Efficiency and Maintainability of Bioinformatics Software
EDGE is a bioinformatics platform developed in 2016 by researchers at Los Alamos National Laboratory (LANL) to facilitate the analysis of next-generation sequencing data by researchers with varying levels of experience in bioinformatics (Li et al., 2017). Users with single-end, paired-end or long-read sequencing data can provide their reads as input to EDGE and select the combination of workflows to run that are most useful for their research (e.g., quality control of reads, genome assembly, or the taxonomic classification of input reads). Table 1 summarizes the modules available in EDGE. EDGE is available as a web platform at https://edgebioinformatics.org, as installable source code maintained on GitHub under a GPLv3 license, and as a publicly hosted Docker image.
59 BASIC BIOLOGICAL SCIENCES↗