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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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Impact of Thermal Bridging, Imperfections, and Aging on Effective R-value of Walk-In Cooler and Freezer Panels
Coproduction of biochemicals from the thermochemical conversion of biomass is a strategy to reduce biofuel costs and improve bio-oil quality in an integrated biorefinery. (Challenge) Cost effective separations of coproducts from thermochemical conversion streams remains a challenge largely due to the heterogenous nature and stability of thermochemical conversion streams. (Solution) Bio-based insecticides isolated from catalytic fast pyrolysis (CFP) oils are a viable coproduct that can overcome the oil is more stable, they are a high value product, and they can remain a mixture of components. (Approach) This work focuses on the development of a bio-based insecticide coproduct that is distilled from a catalytic fast pyrolysis bio-oil produced using a platinum on titanium dioxide (Pt/TiO2) catalyst to upgrade pyrolysis vapors.
The Cybersecurity Value-at-Risk Framework tool will guide users through an assessment and detailed analysis of a hydropower plant's operations. The tool will then provide results and data to inform effective cybersecurity investment decision-making and planning. The results will help managers understand the risk probability of cyberattacks on their facilities and how best to use resources to mitigate those risks.
Various common crystalline silicon cell technologies were exposed to UVA radiation (1.24 Wm-2 nm-1 at 340 nm peak) on the front and back faces at 45 degrees Celsius for periods up to 3000 h, representing about 3 y of solar exposure in Phoenix, Arizona, USA. The resulting degradation of the open-circuit voltage and short-circuit current is presented. Of the various cell types examined, significant levels of degradation were seen in all cases. Less degradation was generally found after UV irradiation of cell fronts and older cell types, whereas a bifacial PERC type exposed on the rear showed about 25% degradation in short circuit current, attributable to lack of a diffused surface field. Selected cells were exposed to UV irradiation with the addition of long pass UV filters to replicate UV-absorbers in encapsulants. Modern cell designs are sensitive to UV-ID because of reduced or eliminated front and back surface field and increased dependence on high quality surface passivation. Single transformation of the independent variable (t, kW h/m^2) could be used to achieve a linear model of the data to extrapolate to 50 y. Solar Advisor Model (SAM) shows appropriate filtering of UV-irradiation can improve LCOE and net present value of plant. Some advanced cell types are seen to be UV-resistant (cell level solutions also exist). Solutions therefore exist on the cell, glass, and encapsulant level. Changes over time in each of these would also need to be considered (solarization, encapsulant browning...).
Embodiments of the invention utilize an optimized key-value storage engine to strike the optimal balance between cloud-cost and performance and supports queries, including updates, lookups, range queries, inserts, and read-modify-writes. Cloud cost is manifested in purchasing both storage and processing resources. The improved approach has the ability to self-design and instantiate holistic configurations given a workload, a cloud budget, and optionally performance goals and a set of Service Level Agreement (SLA) specifications. A configuration reflects an optimized storage engine design in terms of, for example, the individual data structures design (in-memory and on-disk) in the engine as well as their algorithms and interactions, a cloud provider, and the exact virtual machines to be used.
We present analysis results from the Electrification Futures Study, focused on the value of flexible loads.
This paper will outline a waste to value project currently underway. The project will profitably process 100,000 metric tons per year of secondary aluminum salt slag, which is currently landfilled, into recycled salt and refractory aggregate.
High-performance computing (HPC) facilities have employed flash-based storage tier near to compute nodes to absorb high I/O demand by HPC applications during periodic system-level checkpoints. To accelerate these checkpoints, proxy-based distributed key-value stores (PD-KVS) gained particular attention for their flexibility to support multiple backends and different network configurations. PD-KVS rely internally on monolithic KVS, such as LevelDB or RocksDB, to exploit the KV interface and query support. However, PD-KVS are unaware of the high redundancy factor in checkpoint data, which can be up to GBs to TBs, and therefore, tend to generate high write and space amplification on these storage layers. In this paper, we propose DenKv which is deduplication-extended node-local LSM-tree-based KVS. DenKv employs asynchronous partially inline dedup (APID) and aims to maintain the performance characteristics of LSM-tree-based KVS while reducing the write and space amplification problems. We implemented DenKv atop BlobDB and showed that our proposed solution maintains performance while reducing write amplification up to 2× and space amplification by 4× on average.
Overview of NETL CO2U LCA Guidance Toolkit and LCA results of Microwave-Assisted Catalytic Conversion of CO2 to Value-Added Chemicals.
Global fluence estimators may be calculated on accelerators and processors for neutron and photon Monte Carlo transport. Monte Carlo random walk simulation may be performed on the processors and the calculation of a Volumetric-Ray-Casting (VRC) estimator may be offloaded to the accelerators. The VRC estimator may modify an expected-value estimator to extend a pseudo-particle ray along the direction of the emitted particle from source and collision event through not only the event volume, but also through all volumes that describe the problem geometry. Additionally, many pseudo-particle rays may be sampled per event, rather than just a single pseudo-particle ray per event, in order to provide more complete angular coverage.
Ocean current technology has been proposed as a potential contributor to Florida's energy portfolio. There has been limited investigation of how this energy would be valued when integrated into the Florida electrical grid. This study assesses three future grid scenarios to evaluate the impact of adding ocean current to each. NREL's capacity expansion model, Resource Planning Model, is used to identify the least-cost generation mix through 2050, with and without ocean current. The first scenario, Business as Usual, Base case assuming current policies, ocean current does not replace fossil-based technologies. In the second scenario, we allow solar and storage to have lower costs than the first scenario which allows ocean current to retire gas earlier and more variable generation technologies to be deployed. In the third scenario, the Florida carbon constraint 95 by 2050 from 2020 levels case, ocean current can play a bigger role in decarbonization than the two other cases when coupled with other technologies.
As the adoption of distributed energy resources and electric vehicles at residential customer premises increases exponentially, behind-the-meter assets can be utilized to achieve energy cost reduction and demand response through coordination and control strategies. A hierarchical control architecture from the utility headend to residential premises is implemented to attain these objectives. This paper extracts the values from the development, implementation, and deployment of that control hierarchy. The development of the control philosophy is built upon the existing advanced metering infrastructure, communication protocols, and industry-compatible application programming interfaces. Results are presented visually with analytical insights by utilizing the data from hardware-in-the-loop testing and simulation analysis out of the collected data from the field.
In our final report for DE-C0022186, we describe the work we did on this grant towards the goals we proposed. Our first goal was characterizing fundamental limits for sketching of discrete high-dimensional matrices with low-dimensional structures. Our second main goal was designing algorithms for data reconstruction from sketches. We focus on approaches that are either specifically designed for non-real-valued data (binary, finite field) or that will translate more readily to that setting.
The goal is to develop a technological process for converting U.S. coals into high-value solid carbon products such as graphene and high-quality graphite.
Recovering properties of correlation functions is typically challenging. On one hand, experimentally, it requires measurements with a temporal resolution finer than the system's dynamics. On the other hand, analytical or numerical analysis requires solving the system evolution. Here, we use recent results of quantum metrology with continuous measurements to derive general lower bounds on the relaxation and second-order correlation times that are both easy to calculate and measure. These bounds are based solely on steady-state expectation values and their derivatives with respect to a control parameter, and can be readily extended to the autocorrelation of arbitrary observables. We validate our method on two examples of critical quantum systems: a critical driven-dissipative resonator, where the bound matches analytical results for the dynamics, and the infinite-range Ising model, where only the steady state is solvable and thus the bound provides information beyond the reach of existing analytical approaches. Our results can be applied to experimentally characterize ultrafast systems, and to theoretically analyze many-body models with dynamics that are analytically or numerically hard.
Recovering properties of correlation functions is typically challenging. On one hand, experimentally, it requires measurements with a temporal resolution finer than the system's dynamics. On the other hand, analytical or numerical analysis requires solving the system evolution. Here, we use recent results of quantum metrology with continuous measurements to derive general lower bounds on the relaxation and second-order correlation times that are both easy to calculate and measure. These bounds are based solely on steady-state expectation values and their derivatives with respect to a control parameter, and can be readily extended to the autocorrelation of arbitrary observables. We validate our method on two examples of critical quantum systems: a critical driven-dissipative resonator, where the bound matches analytical results for the dynamics, and the infinite-range Ising model, where only the steady state is solvable and thus the bound provides information beyond the reach of existing analytical approaches. Our results can be applied to experimentally characterize ultrafast systems, and to theoretically analyze many-body models with dynamics that are analytically or numerically hard.
The Wind Asset Value Estimation System (WAVES) model is a coupling framework for core NREL techno economic analysis software models to estimate capital expenditures (ORBIT), operational expenditures (WOMBAT), and energy production (FLORIS) for offshore wind power plants. Existing workflows to couple the three models for lifecycle performance and cost estimation require a large amount of manual and error-prone setup to combine both shared inputs and dependent outputs, as such WAVES's primary functionality is to wrap the core logic for running standard modeling workflows to ensure shared settings and entangled results are correctly and efficiently combined every time. SEE ALSO: https://pypi.org/project/WAVES/