Search NASA⌕ Search

SEARCH · Search NASA

Results for “Capacity estimation”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Wind turbine blade material in the United States: Quantities, costs, and end-of-life options

Wind energy has experienced enormous growth in the past few decades; as a result, there are thousands of wind turbines around the world that will reach the end of their design lifetimes in the coming years. Much of the material in those turbines can be recycled using conventional processes, but the composite material that is the main component of the blades is more challenging to recycle. In the United States, turbine blades may be disposed of in landfills, adding a new solid waste stream to the material already being landfilled. This paper presents a spatially resolved estimate of the mass and volume of wind turbine blade waste in each state by 2050 and compares these amounts to estimates of the remaining landfill capacity by state. In this work, we estimate costs for each stage of the disposal process to indicate cost levels for alternatives. Assuming a 20-year turbine lifetime, the cumulative blade waste in 2050 is approximately 2.2 million tons. This value represents approximately 1% of remaining landfill capacity by volume, or 0.2% by mass. We also find that the current cost of disposing of blades in large segments or through grinding is relatively low in comparison to the overall life-cycle cost of energy. Based on these findings, landfill space constraints and disposal costs appear unlikely to motivate a change in waste handling strategies under current policy conditions. Instead, more profound shifts in recycling technologies, blade materials, or policy may be needed to move towards a circular economy for wind turbine blades.

17 WIND ENERGY↗
DOE OSTI2018

Basic properties of eutectic chloride salts NaCl-KCl-ZnCl 2 and NaCl-KCl-MgCl 2 as HTFs and thermal storage media measured using simultaneous DSC-TGA

Concentrated solar power (CSP) technologies tend to work at high temperatures for better energy efficiency, which need high temperature heat transfer fluids (HTF) and thermal storage. A good HTF should have low melting point and be thermally stable at high temperatures. A thermal storage medium needs a high heat capacity in order to store more energy in per unit of mass or volume. The objective of this work is to study the basic thermophysical properties of several eutectic molten salts for HTF and thermal storage media, which can work at upper limit temperatures of 850 °C. The eutectic salts are mixtures by NaCl-KCl-ZnCl 2 , and by NaCl-KCl-MgCl 2 , respectively. The heat capacity, melting point, and heat of fusion of the eutectic salts at different temperatures were measured using Differential Scanning Calorimetry (DSC) and Thermal Gravimetric Analysis (TGA) simultaneously. Details of the measurements and obtained experience of operating the equipment are provided in the work. For each of the eutectic salts multiple samples were tested to check repeatability and to minimize random errors. Finally, in theoretical analysis, mixing rules from literature was used to estimate the heat capacity of the new HTFs, which showed good agreement with experimental data.

14 SOLAR ENERGY↗
DOE OSTI2019

Chemistry of Electrolyte Reduction on Lithium Silicide

Silicon anodes are promising for next-generation lithium-ion batteries due to high theoretical capacity. However, their performance and lifetime are currently limited by continuous electrolyte reduction and solid-electrolyte interphase (SEI) formation. Thus, SEI studies are important but often complicated due to the rough morphology of samples, buried interfaces, and the presence of binders. Here, we demonstrate the chemical origin of SEI formation by electrolyte reduction on lithium silicide thin films, synthesized by diffusion of pure evaporated lithium into smooth sputtered silicon. These model samples allowed for accurate estimation of irreversible capacity loss due to electrolyte reduction and for precise characterization of the resulting SEI by vibrational and photoelectron spectroscopies. Spectroscopic characterizations showed clear evidence that lithium silicide reduced electrolyte directly upon contact. Negligible first-cycle irreversible capacity loss was observed for the lithium silicide compared to silicon, indicating that the decomposition product of electrolyte on lithium silicide is able to stop further electrolyte reduction to a large extent. Fluoro-ethylene carbonate was shown to significantly affect the chemistry of electrolyte reduction on lithium silicide and subsequent cycling performance. The results of this basic study reveal the chemistry occurring at the interface of the lithium silicide and electrolyte and help in understanding the limited calendar lifetime of Li-ion batteries with Si anodes.

25 ENERGY STORAGE↗
NASA NTRS2017

Novel Estimation of Pilot Performance Characteristics

Two mechanisms internal to the pilot that affect performance during a tracking task are: 1) Pilot equalization (i.e. lead/lag); and 2) Pilot gain (i.e. sensitivity to the error signal). For some applications McRuer's Crossover Model can be used to anticipate what equalization will be employed to control a vehicle's dynamics. McRuer also established approximate time delays associated with different types of equalization - the more cognitive processing that is required due to equalization difficulty, the larger the time delay. However, the Crossover Model does not predict what the pilot gain will be. A nonlinear pilot control technique, observed and coined by the authors as 'amplitude clipping', is shown to improve stability, performance, and reduce workload when employed with vehicle dynamics that require high lead compensation by the pilot. Combining linear and nonlinear methods a novel approach is used to measure the pilot control parameters when amplitude clipping is present, allowing precise measurement in real time of key pilot control parameters. Based on the results of an experiment which was designed to probe workload primary drivers, a method is developed that estimates pilot spare capacity from readily observable measures and is tested for generality using multi-axis flight data. This paper documents the initial steps to developing a novel, simple objective metric for assessing pilot workload and its variation over time across a wide variety of tasks. Additionally, it offers a tangible, easily implementable methodology for anticipating a pilot's operating parameters and workload, and an effective design tool. The model shows promise in being able to precisely predict the actual pilot settings and workload, and observed tolerance of pilot parameter variation over the course of operation. Finally, an approach is proposed for generating Cooper-Harper ratings based on the workload and parameter estimation methodology.

Human pilot models↗
DOE OSTI2018

Investigation on offshore wind turbine with an innovative hybrid monopile foundation: An experimental based study

The support structure for offshore wind turbines (OWTs) plays significant roles in maintaining the structural stability and reducing the initial cost. An innovative hybrid monopile foundation for OWTs is proposed. The concept has a wider adaptability by using established knowledge to solve for new problems. A series of centrifuge tests is performed to investigate the behavior of this hybrid foundation system in extreme and service conditions. OWTs with the original monopile foundation as well as the wheel-only foundations are tested for comparisons, and two clay profiles are considered. The test results show that the hybrid monopile foundation provides larger ultimate bearing capacities compared to the traditional foundations. Two analytical methods are proposed to estimate the ultimate bearing capacity of this innovative design, and the results are calibrated by the centrifuge tests. In service conditions, the hybrid monopile foundation shows stronger cyclic resistances. Influence factors of the cyclic responses are summarized. An analytical solution is put forward to estimate the accumulated lateral displacement of the hybrid monopile foundation. A degradation factor is suggested based on the results of the centrifuge tests. The study aims to enrich the understanding of the innovative foundation concept and to provide design references for practical applications.

17 WIND ENERGY↗
NASA NTRS2017

Analysis of Convective Weather Impact on Pre-Departure Routing of Flights from Fort Worth Center to New York Center

In response to severe weather conditions, Traffic Managers specify flow constraints and reroutes to route air traffic around affected regions of airspace. Providing analysis and recommendations of available reroute options and associated airspace capacities would assist Traffic Managers in making more efficient decisions in response to convective weather. These recommendations can be developed by examining historical data to determine which previous reroute options were used in similar weather and traffic conditions. This paper describes the initial steps and methodology used towards this goal. The focus of this work is flights departing from Fort Worth Center destined for New York Center. Dominant routing structures used in the absence of convective weather are identified. A method to extract relevant features from the large volume of weather data available to quantify the impact of convective weather on this routing structure over a given time range is presented. Finally, a method of estimating flow rate capacity along commonly used routes during convective weather events is described. Results show that the flow rates drop exponentially as a function of the values of the proposed feature and that convective weather on the final third of the route was found to have a greater impact on the flow rate restriction than other portions of the route.

traffic flow management↗
DOE OSTI2016

On the Path to SunShot. Emerging Issues and Challenges in Integrating Solar with the Distribution System

This report analyzes distribution-integration challenges, solutions, and research needs in the context of distributed generation from PV (DGPV) deployment to date and the much higher levels of deployment expected with achievement of the U.S. Department of Energy's SunShot targets. Recent analyses have improved estimates of the DGPV hosting capacities of distribution systems. This report uses these results to statistically estimate the minimum DGPV hosting capacity for the contiguous United States using traditional inverters of approximately 170 GW without distribution system modifications. This hosting capacity roughly doubles if advanced inverters are used to manage local voltage and additional minor, low-cost changes could further increase these levels substantially. Key to achieving these deployment levels at minimum cost is siting DGPV based on local hosting capacities, suggesting opportunities for regulatory, incentive, and interconnection innovation. Already, pre-computed hosting capacity is beginning to expedite DGPV interconnection requests and installations in select regions; however, realizing SunShot-scale deployment will require further improvements to DGPV interconnection processes, standards and codes, and compensation mechanisms so they embrace the contributions of DGPV to system-wide operations. SunShot-scale DGPV deployment will also require unprecedented coordination of the distribution and transmission systems. This includes harnessing DGPV's ability to relieve congestion and reduce system losses by generating closer to loads; minimizing system operating costs and reserve deployments through improved DGPV visibility; developing communication and control architectures that incorporate DGPV into system operations; providing frequency response, transient stability, and synthesized inertia with DGPV in the event of large-scale system disturbances; and potentially managing reactive power requirements due to large-scale deployment of advanced inverter functions. Finally, additional local and system-level value could be provided by integrating DGPV with energy storage and 'virtual storage,' which exploits improved management of electric vehicle charging, building energy systems, and other large loads. Together, continued innovation across this rich distribution landscape can enable the very-high deployment levels envisioned by SunShot.

14 SOLAR ENERGY↗
DOE OSTI2024

Data-driven search for promising intercalating ions and layered materials for metal-ion batteries

The rise in demand for lithium-ion batteries has led to a large-scale search for electrode materials and intercalating ion species to meet the demands of next-generation energy technologies. Recent efforts largely focus on searching for cathodes that can accommodate large amounts of intercalating ions, but similar work on anodes is relatively limited. This study utilizes machine learning methods to find alternative two-dimensional (2D) materials and intercalating ions beyond Li for metal-ion batteries with high-power efficiencies. The approach first uses density functional theory (DFT) calculations to estimate the theoretical capacities and voltages of various metal ions on 2D materials. The DFT-generated data also provide insights into the local structural accommodation upon ion intercalation on various 2D materials. Significant changes to the lattice can result in irreversible changes to the bonding environments in the anode material, resulting in poor cycling stability. Next, this study develops a binding energy and structural accommodation-based classification model to screen anode materials for next-generation batteries. The classification model selects intercalating ions and 2D material pairs suitable for batteries based on the calculated voltage and volumetric changes in the 2D material upon intercalation. Finally, this study builds a regression model to accurately predict the binding energies of the various intercalating ions on 2D materials. The approach highlights the importance of different elemental and structural features for classification and regression tasks. In conclusion, the insights gained from this study on the role of involved features, such as electronegativities of the constituent ions and the presence of unfilled electronic levels, will help to streamline further studies towards the search for future layered battery materials.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Toward efficient elastocaloric systems: Predicting material thermal properties with high fidelity

A critical need to accurately model thermal behaviors of materials that exhibit strong elastocaloric effects, including predicting the effects themselves at varying stresses and temperatures, has been addressed using a simple and versatile physics-based approach. The key factor leading to the high precision is approximating the underlying elastic phase transition as a smooth modification of lattice entropy between coexisting phases. Once the phase transformation entropy is modeled to match experimentally measured strain as a function of temperature and applied stress, estimating the heat capacity, entropy, and isothermal entropy and adiabatic temperature changes in temperature-stress coordinates becomes straightforward. This approach provides insight into how thermal properties of elastocaloric materials vary through the transition based on strain measurements that are simple to perform and interpret. In addition to aiding in the rapid evaluation of new and existing elastocaloric materials, this advance is expected to prove invaluable for accurate heat transfer modeling aimed at designing efficient regenerative elastocaloric cooling devices.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Estimate long-term impact on battery degradation by considering electric vehicle real-world end-use factors

Many estimates of battery capacity degradation are based on accelerated lab tests that involve charge-discharge cycles or rely on data or electrochemical modeling. These methods are reasonable for technology benchmarking but rarely consider real-world end-use factors. To address this issue, this study develops the Battery Run-down under Electric Vehicle Operation (BREVO) model. It links the driver's travel pattern to physics-based battery degradation and powertrain energy consumption models. The model simulates the impacts of charging behavior, charging rate, driving patterns, and multiple energy management modules on battery capacity degradation. It finds that, over a 10-year timespan, firstly, for a random driver situated in the New England area, daily direct-current fast charging (60 kW) could lead to up to 22% less battery capacity when compared to daily Level-1 charging (1.8 kW). Second, the battery thermal management system can delay battery degradation by approximately 0.5% in the New England area. Third, warmer ambient temperatures enhance BEV battery usage. The model indicates that the battery capacity in the Los Angeles area is 6% higher than that in the New England area. The BREVO model provides crucial information for consumers and BEV manufacturers on range anxiety, BEV battery design, and decision support of battery warranty.

25 ENERGY STORAGE↗
DOE OSTI2024

Improved constraints on hematite refractive index for estimating climatic effects of dust aerosols

Abstract Uncertainty in desert dust composition poses a big challenge to understanding Earth’s climate across different epochs. Of particular concern is hematite, an iron-oxide mineral dominating the solar absorption by dust particles, for which current estimates of absorption capacity vary by over two orders of magnitude. Here, we show that laboratory measurements of dust composition, absorption, and scattering provide valuable constraints on the absorption potential of hematite, substantially narrowing its range of plausible values. The success of this constraint is supported by results from an atmospheric transport model compared with station-based measurements. Additionally, we identify substantial bias in simulating hematite abundance in dust aerosols with current soil mineralogy descriptions, underscoring the necessity for improved data sources. Encouragingly, the next-generation imaging spectroscopy remote sensing data hold promise for capturing the spatial variability of hematite. These insights have implications for enhancing dust modeling, thus contributing to efforts in climate change mitigation and adaptation.

Environmental Sciences & Ecology↗
DOE OSTI2019

Magnetocaloric effect near room temperature in quintenary and sextenary Heusler alloys

An inverse magnetocaloric effect is studied in Ni 2 Mn 1+x X 1-x -type Heusler alloys. Principally known for their shape-memory properties, these alloys also exhibit significant entropy and temperature changes (ΔS and ΔT Ad , respectively) under adiabatic conditions when a modest magnetic field is applied. We investigated the impact on magnetocaloric properties of introducing substantial chemical disorder on the X-site (X=Si,Ga,In), of replacing Ni with nonmagnetic Ag, and of replacing a small amount of Mn with Gd. While a reduction in ΔS is observed in the first two cases, we observe a significant enhancement of ΔS when a small amount of Gd is substituted for Mn. A thermodynamic analysis was conducted using magnetization and heat capacity data to estimate adiabatic temperature changes in the range of ΔT Ad ≃ -1 to -3 K for a 5 T magnetic field. Several alloys characterized in this study exhibit these respectable ΔT Ad values near room temperature, making them potentially viable candidates for magnetic refrigeration applications.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Detection of correlated fragments in a sequence of images by superimposed Fourier holograms

The problem of detecting correlated fragments in a sequence of images recorded by the superimposing holograms within the Fourier holography scheme with angular multiplication of a spatially modulated reference beam is considered. The approach to the solution of this problem is based on the properties of the variance of the image sum. It is shown that this problem can be solved by providing a constant distance between the signal and reference images when recording superimposed holograms and a partial mutual correlatedness of reference images. The detection efficiency is analysed from the point of view of estimated image data capacity, the degree of mutual correlation of reference images, and the hologram recording conditions. The results of a numerical experiment under the most complicated conditions (representation of images by realisations of homogeneous random fields) confirm the theoretical conclusions. (holographic memory)

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2017

Giant reversible magnetocaloric effect in the pyrochlore Er 2 Mn 2 O 7 due to a cooperative two-sublattice ferromagnetic order

Most magnetic refrigeration materials showing a large and reversible magnetocaloric effect (MCE) undergo a second-order ferromagnetic (FM) transition involving large-moment magnetic species on one sublattice. Furthermore, a stronger MCE is expected near a cooperative FM order of two or more magnetic species with large magnetic moments residing on different sublattices, but experimental realizations are rare. Here we report on the discovery of large MCE in the cubic pyrochlore Er 2 Mn 2 O 7 near its second-order FM transition at T c ≈ 34K; under the magnetic field change of 1 and 5 T, the maximum magnetic entropy change –ΔS M is 5.27 and 16.1Jkg –1 K –1 , and the estimated magnetic refrigerant capacity reaches 68 and 522Jkg –1 , respectively. These latter values are among the largest for the known MCE materials. The observed giant and reversible MCE in Er 2 Mn 2 O 7 is mainly attributed to the large saturation moment of 18.9μ B per formula unit owing to a simultaneous FM ordering of the rear-earth Er 3+ and transition-metal Mn 4+ localized moments. Our results suggest that Er 2 Mn 2 O 7 pyrochlore is a promising candidate for magnetic refrigeration applications in the temperature range 20–80 K. More importantly, this work provides a new material system for developing high-performance MCE materials that can exhibit a strongly coupled FM transition involving two magnetic sublattices of large local moments in a single-phase material.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2019

Global vegetation biomass production efficiency constrained by models and observations

Typically, plants use only a fraction of their photosynthetically derived carbon for biomass production (BP). The biomass production efficiency (BPE), defined as the ratio of BP to photosynthesis, and its variation across and within vegetation types is poorly understood, which hinders our capacity to accurately estimate carbon turnover times and carbon sinks. In this work, we introduce a new global estimation of BPE obtained by combining field measurements from 113 sites with 14 carbon cycle models. Our best estimate of global BPE is 0.41 ± 0.05, excluding cropland. The largest BPE is found in boreal forests (0.48 ± 0.06) and the lowest in tropical forests (0.40 ± 0.04). Carbon cycle models overestimate BPE, although models with carbon–nitrogen interactions tend to be more realistic. Using observation-based estimates of global photosynthesis, we quantify the global BP of non-cropland ecosystems of 41 ± 6 Pg C/year. This flux is less than net primary production as it does not contain carbon allocated to symbionts, used for exudates or volatile carbon compound emissions to the atmosphere. Our study reveals a positive bias of 24 ± 11% in the model-estimated BP (10 of 14 models). When correcting models for this bias while leaving modeled carbon turnover times unchanged, we found that the global ecosystem carbon storage change during the last century is decreased by 67% (or 58 Pg C).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

From the Arctic to the tropics: multi-biome prediction of leaf mass per area using leaf reflectance

Leaf-mass-per-area (LMA) is a key plant trait, reflecting tradeoffs between leaf photosynthetic function, longevity, and structural investment. Capturing spatial and temporal variability in LMA has been a long-standing goal of ecological research and is an essential component for advancing Earth system models. Despite the substantial variation in LMA within and across Earth's biomes, an efficient, globally generalizable approach to predict LMA is still lacking. In this work, we explored the capacity to predict LMA from leaf spectra across much of the global LMA trait space, with values ranging from 17 g m -2 to 393 g m -2 . Our dataset contained leaves from a wide range of biomes from the high Arctic to the tropics, included broad- and needle-leaf species, and upper and lower canopy (i.e. sun and shade) growth environments. Here we demonstrate the capacity to rapidly estimate LMA using only spectral measurements across a wide range of species, leaf age, and canopy position, from diverse biomes. Our model captures LMA variability with high accuracy and low error (R 2 =0.89; RMSE=15.45 g m -2 ). Lastly, our finding highlights that the leaf economic spectrum is mirrored by the leaf optical spectrum paving the way for this technology to predict the diversity of LMA in ecosystems across global biomes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

FAD-Toolset (Floating Array Design Toolset) [SWR-26-056]

The Floating Array Design (FAD) Toolset is a collection of tools for modeling and designing arrays of floating offshore structures. It was originally designed for floating wind systems but has applicability for many offshore applications. A core part of the FAD Toolset is the floating array model, which serves as a high-level library for efficiently modeling a floating array, such as a floating wind array. It combines site condition information and a description of the floating array design, and contains functions for evaluating the array's behavior considering the site conditions. For example, it combines information about site soil conditions, mooring line loads, and an array's anchor characteristics to estimate the holding capacity of each anchor. The library works in conjunction with the tools RAFT, MoorPy, and FLORIS to model floating platforms, wind turbines, mooring systems, power cables, and array wakes respectively. Layered on top of the floating array model is a set of design tools that can be used for algorithmically adjusting or optimizing parts of the a floating array. Specific tools existing for mooring lines, shared mooring systems, dynamic power cables, static power cable routing, and overall array layout. These capabilities work with the design representation and evaluation functions in the floating array model, and they can be applied by users in various combinations to suit different purposes. In addition to standalone uses of the FAD Toolset, a coupling has been made with Ard, (https://github.com/NLRWindSystems/Ard) a sophisticated and flexible wind farm optimization tool. This coupling allows Ard to use certain mooring system capabilities from FAD to perform layout optimization of floating wind farms with Ard's more advanced layout optimization capabilities. The FAD Toolset works with the IEA Wind Task 49 Ontology (https://github.com/IEAWindTask49/Ontology), which provides a standardized format for describing floating wind farm sites and designs. See example use cases in our examples folder (https://github.com/NLRWindSystems/FAD-Toolset/blob/main/examples/README.md) For working with the library, it is important to understand the floating array model structure, which is described more here: https://github.com/NLRWindSystems/FAD-Toolset/blob/main/fad/README.md.

Sirkis, Leah [National Laboratory of the Rockies (↗