Search NASA⌕ Search

SEARCH · Search NASA

Results for “metric”

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 307 records · Page 17
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Battery Energy Storage Systems: A Review of Energy Management Systems and Health Metrics

With increasing concerns about climate change, there is a transition from high-carbon-emitting fuels to green energy resources in various applications including household, commercial, transportation, and electric grid applications. Even though renewable energy resources are receiving traction for being carbon-neutral, their availability is intermittent. To address this issue to achieve extensive application, the integration of energy storage systems in conjunction with these resources is becoming a recommended practice. Additionally, in the transportation sector, the increased demand for EVs requires the development of energy storage systems that can deliver energy for rigorous driving cycles, with lithium-ion-based batteries emerging as the superior choice for energy storage due to their high power and energy densities, length of their life cycle, low self-discharge rates, and reasonable cost. As a result, battery energy storage systems (BESSs) are becoming a primary energy storage system. The high-performance demand on these BESS can have severe negative effects on their internal operations such as heating and catching on fire when operating in overcharge or undercharge states. Reduced efficiency and poor charge storage result in the battery operating at higher temperatures. To mitigate early battery degradation, battery management systems (BMSs) have been devised to enhance battery life and ensure normal operation under safe operating conditions. Some BMSs are capable of determining precise state estimations to ensure safe battery operation and reduce hazards. Precise estimation of battery health is computed by evaluating several metrics and is a central factor in effective battery management systems. In this scenario, the accurate estimation of the health indicators (HIs) of the battery becomes even more important within the framework of a BMS. This paper provides a comprehensive review and discussion of battery management systems and different health indicators for BESSs, with suitable classification based on key characteristics.

Nazaralizadeh, Solmaz (ORCID:0009000737004039)↗
DOE OSTI2024

A Physical Metric for Inertial Confinement Fusion Capsules

The performance of fusion capsules on the National Ignition Facility (NIF) is strongly affected by the physical properties of the hot deuterium–tritium (DT) fuel, such as the mass, areal density, and pressure of the hot spot at the stagnation time. All of these critical quantities depend on one measured quantity, which is the ratio of the specific peak implosion energy to the specific internal energy of the hot spot. This unique physical quantity not only can measure the incremental progress of the inertial confinement fusion capsules towards ignition but also measures the conversion of the peak implosion kinetic energy of the pusher shell into the internal energy of the hot fuel in a capsule. Analysis of existing NIF shots to date are performed. The ratio metric is compared quantitatively with the ignition criterion. Results provide new perspectives on the NIF experiments by which the performance of the burning plasma can be determined and controlled through the fine tune of the implosion parameters, which improves future designs and predictions of the ignition capsules.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Atmospheric condition identification in multivariate data through a metric for total variation

Identification of atmospheric conditions within a multivariable atmospheric data set is a necessary step in the validation of emerging and existing high-fidelity models used to simulate wind plant flows and operation.Atmospheric conditions relevant for wind energy research include stationary conditions, given the need for well-converged statistics for model validation, as well as conditions observed less frequently, such as extreme atmospheric events, which are used in wind turbine and wind plant design.Aggregation of observations without regard to covariance between time series discounts the dynamical nature of the atmosphere and is not sufficiently representative of atmospheric conditions.Identification and characterization of continuous time periods with atmospheric conditions that have a high value for analysis or simulation set the stage for more advanced model validation and the development of real-time control and operational strategies.The current work explores a single metric for variation in a multivariate data sample that quantifies variability within each channel as well as covariance between channels.The total variation is used to identify conditions of interest that conform to desired objective functions, such as stationary conditions, ramps or waves of wind speed, and changes in wind direction.Total variation is somewhat sensitive to the presence of outliers in the input data, and the method is best complemented by quality-control procedures to ensure reliable results.The direct detection and classification of events or conditions of interest within atmospheric data sets is vital to developing our understanding of wind plant response and to the formulation of forecasting and control models.

17 WIND ENERGY↗
DOE OSTI2022

Metrics for Intercomparison of Remapping Algorithms (MIRA) protocol applied to Earth system models

Abstract. Strongly coupled nonlinear phenomena such as those described by Earth system models (ESMs) are composed of multiple component models with independent mesh topologies and scalable numerical solvers. A common operation in ESMs is to remap or interpolate component solution fields defined on their computational mesh to another mesh with a different combinatorial structure and decomposition, e.g., from the atmosphere to the ocean, during the temporal integration of the coupled system. Several remapping schemes are currently in use or available for ESMs. However, a unified approach to compare the properties of these different schemes has not been attempted previously. We present a rigorous methodology for the evaluation and intercomparison of remapping methods through an independently implemented suite of metrics that measure the ability of a method to adhere to constraints such as grid independence, monotonicity, global conservation, and local extrema or feature preservation. A comprehensive set of numerical evaluations is conducted based on a progression of scalar fields from idealized and smooth to more general climate data with strong discontinuities and strict bounds. We examine four remapping algorithms with distinct design approaches, namely ESMF Regrid (Hill et al., 2004), TempestRemap (Ullrich and Taylor, 2015), generalized moving least squares (GMLS) (Trask and Kuberry, 2020) with post-processing filters, and WLS-ENOR (Li et al., 2020). By repeated iterative application of the high-order remapping methods to the test fields, we verify the accuracy of each scheme in terms of their observed convergence order for smooth data and determine the bounded error propagation using challenging, realistic field data on both uniform and regionally refined mesh cases. In addition to retaining high-order accuracy under idealized conditions, the methods also demonstrate robust remapping performance when dealing with non-smooth data. There is a failure to maintain monotonicity in the traditional L2-minimization approaches used in ESMF and TempestRemap, in contrast to stable recovery through nonlinear filters used in both meshless GMLS and hybrid mesh-based WLS-ENOR schemes. Local feature preservation analysis indicates that high-order methods perform better than low-order dissipative schemes for all test cases. The behavior of these remappers remains consistent when applied on regionally refined meshes, indicating mesh-invariant implementations. The MIRA intercomparison protocol proposed in this paper and the detailed comparison of the four algorithms demonstrate that the new schemes, namely GMLS and WLS-ENOR, are competitive compared to standard conservative minimization methods requiring computation of mesh intersections. The work presented in this paper provides a foundation that can be extended to include complex field definitions, realistic mesh topologies, and spectral element discretizations, thereby allowing for a more complete analysis of production-ready remapping packages.

58 GEOSCIENCES↗
DOE OSTI2020

A Community Energy Operations and Planning System: Concept, Use cases, Metrics, and Benefits

Community and city leaders are interested in achieving sustainability goals, providing resilient energy infrastructure, and improving economic competitiveness. Community-level data acquisition and analysis can provide energy and associated benefits that are not possible at the single building level. However, there is a lack of organizational structure, common semantic data models, interoperable systems, and methods to support data-driven decision-making for community-scale energy supply and demand systems. We explored the need and opportunity for a Community Energy Operations and Planning System (Community EOPS), a potential data exchange platform. We conducted “customer discovery” interviews, and reviewed literature, public tools, and technology platforms to identify key energy data “users” and use cases in communities. The key users of the Community EOPS could be developers of mixed-use districts, corporate, defense and university campus energy managers, and city managers of cities that own their energy utility. The value could be for community planning and reporting (for energy data-integrated land use planning and community infrastructure investments in microgrids, storage, district heating and cooling), energy efficiency (leveraging optimizations for community scale energy supply and demand), flexible load management (grid-edge load management to offset, shift, and flatten loads for multiple buildings and EV fleets), cost savings and revenue generation (participating in grid services), and social benefits such as energy resilience, equity, and awareness. We developed a conceptual Community EOPS architecture with recommendations for streamlined and prioritized data acquisition, sharing, and integration driven by prioritized use cases, common metrics, and actionable visualizations that can provide value to a community’s users.

Singh, Reshma↗
DOE OSTI2021

Side-channel Leakage Assessment Metrics: A Case Study of GIFT Block Ciphers

Determination of an adequate level of security and providing subsequent mechanisms to achieve it, is one of the most pressing problems regarding embedded computing devices. While there are some solutions available for resource-rich computer systems, direct application of these solutions to resource-constrained environments are often unfeasible. The fundamental problem for such resource-constrained systems is the fact that current cryptographic algorithms utilize significant energy consumption and storage overhead. Both the cryptographic algorithm and its physical implementation affect the resilience of a cryptosystem against side-channel attacks. A side-channel attack represents a process that exploits leakages in order to extract sensitive information such as the key. This paper focuses on Correlation Power Analysis (CPA) which is side-channel attack based on the power consumption leakage. In 2016 the U.S. Commerce Department’s National Institute of Standards and Technology (NIST) initiated the call for proposals of new cryptographic algorithms to strengthen the cryptographic defense of networked devices against cyberattacks and to protect the data created by those innumerable device. This work evaluates S-boxes used by NIST candidates PICCOLO, GIFT, and PRESENT, as well as several S-box variants that demonstrated sufficient weaknesses against classical cryptanalysis, for a quantitative comparison in terms of resiliency to CPA attack. Three well-known theoretical metrics are evaluated: transparency order (TO and RTO), nonlinearity, and signal-to-noise (SNR) ratio, aiming to characterize the resistance of these S-boxes against adversaries exploiting physical leakages. Experimental results from attacks on an 8- bit XMEGA were obtained via the ChipWhisperer platform and of all the S-boxes evaluated, GIFT64 with a PICCOLO S-box was found to be the most susceptible to CPA. Results showed that variations in TO and RTO were not sufficient to ensure practical CPA resistance and that among S-boxes with equal non-linearity there were no significant differences in the TO and SNR variants.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Side-channel Leakage Assessment Metrics: A Case Study of GIFT Block Ciphers

Determination of an adequate level of security and providing subsequent mechanisms to achieve it, is one of the most pressing problems regarding embedded computing devices. While there are some solutions available for resource-rich computer systems, direct application of these solutions to resource-constrained environments are often unfeasible. The fundamental problem for such resource-constrained systems is the fact that current cryptographic algorithms utilize significant energy consumption and storage overhead. Both the cryptographic algorithm and its physical implementation affect the resilience of a cryptosystem against side-channel attacks. A side-channel attack represents a process that exploits leakages in order to extract sensitive information such as the key. This paper focuses on Correlation Power Analysis (CPA) which is side-channel attack based on the power consumption leakage. In 2016 the U.S. Commerce Department’s National Institute of Standards and Technology (NIST) initiated the call for proposals of new cryptographic algorithms to strengthen the cryptographic defense of networked devices against cyberattacks and to protect the data created by those innumerable device. This work evaluates S-boxes used by NIST candidates PICCOLO, GIFT, and PRESENT, as well as several S-box variants that demonstrated sufficient weaknesses against classical cryptanalysis, for a quantitative comparison in terms of resiliency to CPA attack. Three well-known theoretical metrics are evaluated: transparency order (TO and RTO), nonlinearity, and signal-to-noise (SNR) ratio, aiming to characterize the resistance of these S-boxes against adversaries exploiting physical leakages. Experimental results from attacks on an 8- bit XMEGA were obtained via the ChipWhisperer platform and of all the S-boxes evaluated, GIFT64 with a PICCOLO S-box was found to be the most susceptible to CPA. Results showed that variations in TO and RTO were not sufficient to ensure practical CPA resistance and that among S-boxes with equal non-linearity there were no significant differences in the TO and SNR variants.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Retrofit-ability: A supplementary metric to inform energy efficiency policies and programs

Building Energy Use Intensity (EUI) has been commonly used to facilitate policy makers and utilities to design energy efficacy programs and help building managers prioritize investment in building upgrades. Buildings with higher EUIs are usually chosen as better candidates for retrofit. Our study of nearly one hundred buildings in Seattle’s Building Tune Up Accelerator program and thousands of buildings in the Asset Score database reveals that EUI (after weather/location/use type normalization) alone is not the best indicator of a building’s potential to save energy, especially for those buildings in the mid-range (30-70 percentile EUI). In this paper, we introduce the concept of “retrofit-ability” — a building’s real potential to reduce its energy use cost-effectively — as a supplementary metric to inform energy efficiency policy and investment. Currently, such potential analyses are predicted for a building stock using prototypical building models or statistical data. However, typical buildings or general historical data may not sufficiently represent building configurations in a portfolio and predict their saving potentials. We utilized machine learning to investigate how key building characteristics (such as envelope attributes, HVAC type, location, use type, etc.) affect a building’s improvement potentials and developed a low-cost method to quantify such potentials for a portfolio of buildings. The supplementary perspective provided by “retrofit-ability” highlights which building assets correlate most with a building’s energy savings potential across region, building use type and more.

Wang, Na↗
DOE OSTI2022

Review of Wave Energy Converter Power Take-Off Systems, Testing Practices, and Evaluation Metrics: Preprint

While the field of wave energy has been the subject of numerical simulation, scale model testing, and precommercial project testing for decades, wave energy technologies remain in the early stages of development and must continuing proving themselves as a promising modern renewable energy field. One of the difficulties that wave energy systems have been struggling to overcome is the design of highly efficient energy conversion systems that can convert the mechanical power, derived from the oscillation of wave activated bodies, into another useful product. Often the power take-off (PTO) is defined as the single unit responsible for converting mechanical power into another usable form such as electricity, pressurized fluid, compressed air, and others. The PTO, and the entire power conversion chain (PCC), is of great importance as it affects not only how efficient wave power is converted into electricity, but also contributes to the mass, size, structural dynamics, and levelized cost of energy (LCOE) of the wave energy converter (WEC). Unlike wind and solar, there is no industrial standard device, or devices, for wave energy conversion and this diversity is transferred to the PTO system. The majority of current WEC PTO systems incorporate a mechanical or hydraulic drive train, power generator, and an electrical control system. The challenge of WEC PTO designs is designing a mechanical-to-electrical component that can efficiently convert irregular, bi-directional, low frequency and low alternating velocity wave motions. While gross average power levels can be predicted in advance, the variable wave elevation input has to be converted into smooth electrical output and hence usually necessitates some type of energy storage system, such as battery storage, accumulator super capacitors, etc., or other means of compensation such as an array of devices. One of the primary challenges for wave energy converter systems is the fluctuating nature of wave resources, which require WEC components to be designed to handle loads (i.e. torques, forces, and powers) that are many times greater than the average load. This approach requires a much greater PTO capacity than the average power output and indicates a higher cost. In addition, supporting mechanical coupling and or gearing can be added to the PCC to help alleviate the difficulties with transmission and control of fluctuating large loads with low frequencies (indicative of wave forcing) into smaller loads at higher frequencies (optimum for conventional electrical machine design) can quickly increase the complexity of the PCC which could result in a greater number of failure modes and increased maintenance costs. All of the previous points demonstrate how the PTO influences WEC dynamics, reliability, performance and cost which are critical design factors. This paper further explores these topics by providing a review of the state-of-the-art PTO systems currently under development, how these novel PTO systems are tested and derisked prior to precommercial deployment, and the evaluation metrics historically used to differentiate between PTO designs and how they can be improved to support control co-design focused development of wave energy systems.

laboratory testing↗
DOE OSTI2024

Equitable Energy Metrics for Integration into Building Performance Standard Tracking Platforms: Preprint

Building Performance Standards (BPS) are being adopted globally and in the United States of America, where 14 different states and jurisdictions have a policy in place and many others are under development (Department of Energy (DOE) 2023). Accurate and equitable data sources are essential to make informed decisions about focusing investment on upgrading buildings to meet jurisdictional goals. There have been multiple new tools developed related to Energy Equity and Environmental Justice (EEEJ) and the resulting datasets need to be integrated into large building port-folios for quick access and better scalability. Integrating EEEJ data in a user-friendly format can help decision makers more quickly assess impacts and analyze the multitude of potentially significant metrics for which there is not yet consensus. In the U.S. and Canada, many BPS ordinances rely primarily on ENERGY STAR Portfolio Manager (ESPM) to capture building characteristics and energy and water consumption data. These datasets can then be imported into city-specific building tracking tools like the Standard Energy Efficiency Data Platform (SEED). Crucially, BPS decision makers require an efficient means of identifying buildings in priority communities to effectively allocate resources and funding. This process must integrate seamlessly with existing jurisdictional toolsets for optimal utility. This paper will demonstrate, for the case of Washington D.C.'s (the District) data, a workflow that provides actionable data for building upgrade investment prioritization in disadvantaged communities.

BPS↗
DOE OSTI2024

Sustainable Aviation Fuel Grand Challenge: Tracking Metrics and Mid-2024 Dashboard

The Sustainable Aviation Fuel Grand Challenge is the result of the U.S. Department of Energy, the U.S. Department of Transportation, the U.S. Department of Agriculture, and other federal government agencies working together to develop a comprehensive strategy for scaling up new technologies to produce sustainable aviation fuels (SAF) on a commercial scale. The SAF Grand Challenge Roadmap outlines a whole-of-government approach with coordinated policies and specific activities that should be undertaken to achieve the SAF Grand Challenge goals. Progress made supporting the SAF Grand Challenge occurs when federal agencies release new funding opportunities and initiatives aligned with the SAF Grand Challenge Roadmap; provide expertise and technical assistance to industry; increase interagency collaboration; and provide data, modeling, and analysis to decision makers. To track progress on achieving the SAF Grand Challenge goals, the following four metrics have been developed: Estimated total U.S. SAF production. Estimated life cycle CO2 equivalent reductions achieved with U.S. SAF production and use. Planned production potential of SAF in the United States. Applicable research, development, demonstration, and deployment projects. SAF Grand Challenge Goal Progress

Aviation↗
DOE OSTI2023

Counter Unmanned Aircraft System Metrics Tool

SAND2023-05387O The Counter Unmanned Aircraft System (CUAS) Metrics Tool consists of three applications: • The Data Collection Tool is designed to be used during testing and captures details that can be imported into the Figure Creator application. • The Unmanned Aircraft System (UAS) Log Converter converts different UAS logs into a standardized hierarchical data format with a timeline of geospatial data. • The Figure Creator develops relevant images for the test event. The application includes logic to ingest and correlate data from the Data Collection Tool and the UAS Log Converter to produce the chosen figures. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Mayle, Ashley↗
DOE OSTI2021

The effect of WAAM process parameters on process conditions and production metrics in the fabrication of single-pass multi-layer wall artifacts

The present work seeks to understand the impact of varying dwell time and input deposition power on part quality and overall production time for wire arc additive manufacturing. In this work, multi-layer wall geometries were deposited under different input power conditions without affecting the material deposition rate by setting traverse speed and wire feed speed constant and varying the contact tip-to-workpiece distance and the deposition power settings. Current and voltage data and optical imaging of the deposition zone were captured in situ, and wall geometry was characterized using laser scanning, so to understand the applicability of these methods for determining part height in situ. Furthermore, the present results demonstrate that alternating dwell times with lower input deposition power can result in significantly reduced overall production time and minimal material underbuilding, despite increased deposition geometry width. Furthermore, it is shown that while elimination of process dwell results in severe underbuilding of the deposition, it also yields the highest production rate for a hybrid-finished (e.g., deposited, machined) wall in terms of mm in build direction per minute and the highest buy-to-fly ratio.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Temperature-dependent changes in gas chromatographic separation metrics for trihexyl(tetradecyl)phosphonium-based ionic liquid stationary phases and comparison to conventional polysiloxane stationary phases

Here, to assess whether the trihexyl(tetradecyl)phosphonium chloride ([P 66614 + ][Cl - ]) ionic liquid (IL), employed as a gas chromatographic stationary phase, exhibits temperature-dependent phase transitions or structural heterogeneity, retention thermodynamics for probe molecules of varied chemical structure were investigated by gas chromatography (GC) over the temperature range of 25 to 64 °C using van’t Hoff analysis. All van’t Hoff plots for n-alkanes (C8–C12) and other probe analytes were linear, indicating the absence of detectable phase-transition behavior. The [P 66614 + ][Cl - ] IL was further compared with the [P 66614 + ] bis[(trifluoromethyl)sulfonyl]imide ([P 66614 + ][NTf 2 - ]) IL and commercial polysiloxane stationary phases in terms of temperature-dependent resolution behavior and chromatographic selectivity over the temperature range of 28–52 °C. The resolution factors of analytes in mixtures obtained using gas chromatography–mass spectrometry (GC–MS) and the summation of resolution values decreased smoothly with temperature on both IL stationary phases and on the dimethylphenylcyano-substituted polymeric stationary phase (OV-1701), whereas the poly(50% diphenyl/50% dimethyl siloxane) stationary phase (SPB-50) exhibited irregularities in its temperature-dependent summation of resolution profile, showing a distinct maximum in the temperature range of 34–40 °C. Selectivity values for the IL stationary phases were largely determined by the anion, with the [P 66614 + ][Cl - ] IL providing enhanced separation between polar and aromatic analytes, while the [P 66614 + ][NTf 2 - ] IL favored dispersive and π-π interactions that resulted in a reversal of elution order for some aliphatic–aromatic and alkyne-containing analyte pairs. Capillary columns prepared using different surface activation methods and coated with identical [P 66614 + ][Cl - ] IL stationary phase showed indistinguishable temperature-dependent trends in summation of resolution value and selectivity. An evaluation of analyte-specific selectivity provides insight into the characteristic separation behavior of the stationary phases and enables identification of analyte classes that are more efficiently separated on the [P 66614 + ]-based IL stationary phases compared to conventional stationary phase materials.

Chromatographic selectivity↗