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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

SU-G-201-14: Is Maximum Skin Dose a Reliable Metric for Accelerated Partial Breast Irradiation with Brachytherapy?

Purpose: To evaluate the reliability of the maximum point dose (Dmax) to the skin surface as a dosimetric constraint, we investigated the correlation between Dmax at the skin surface and dose metrics at various definitions of skin thickness. Methods: 42 patients treated with APBI using a Strut Adjusted Volume Implant (SAVI) applicator between 2010 and 2014 were retrospectively reviewed. Target (PTV-EVAL) and organs at risk (OARs: skin, lung, and ribs) were delineated on a CT following NSABP B-39 guidelines. Six skin structures were contoured: a rind 3cm external to the body surface and 1, 2, 3, 4, and 5mm thick rinds deep to the body surface. Inverse planning simulated annealing optimization was used to deliver 32–34Gy in 8-10 fractions to the target while minimizing OAR doses. Dmax, D0.1cc, D1.0cc, and D2.0cc to the various skin structures were calculated. Linear regressions between the metrics were evaluated using the coefficient of determination (R{sup 2}). Results: The average±SD PTV-EVAL volume and cavity-to-skin distances were 71.1±28.5cc and 6.9±5.0mm. The target V90 and V95 were 97.3±2.3% and 95.1±3.2%. The Dmax to the skin structures were 78.7±10.2% (skin surface), 82.2±10.7% (skin-1mm), 89.4±12.6% (skin-2mm), 97.9±15.4% (skin-3mm), 114.1±32.5% (skin-4mm), and 157.0±85.3% (skin-5mm). Linear regression analysis showed D1.0cc and D2.0cc to the skin 1mm and Dmax to the skin-4mm and 5mm were poorly correlated with other metrics (R{sup 2}=0.413±0.204). Dmax to the skin surface was well correlated (R{sup 2}=0.910±0.047) and D1.0cc to the skin-3mm was strongly correlated with all subsurface skin layers (R{sup 2}=0.935±0.050). Conclusion: Dmax to the skin surface is a relevant metric for breast skin dose. Contouring discontinuities in the skin with a 1mm subsurface rind and the active dwells in the skin 4 and 5mm introduced significant variations in skin DVH. D0.1cc, D1.0cc, and D2.0cc to a 3mm skin rind are more robust metrics in breast brachytherapy.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

SU-G-BRB-16: Vulnerabilities in the Gamma Metric

Purpose: To explore vulnerabilities in the gamma index metric that undermine its wide use as a radiation therapy quality assurance tool. Methods: 2D test field pairs (images) are created specifically to achieve high gamma passing rates, but to also include gross errors by exploiting the distance-to-agreement and percent-passing components of the metric. The first set has no requirement of clinical practicality, but is intended to expose vulnerabilities. The second set exposes clinically realistic vulnerabilities. To circumvent limitations inherent to user-specific tuning of prediction algorithms to match measurements, digital test cases are manually constructed, thereby mimicking high-quality image prediction. Results: With a 3 mm distance-to-agreement metric, changing field size by ±6 mm results in a gamma passing rate over 99%. For a uniform field, a lattice of passing points spaced 5 mm apart results in a passing rate of 100%. Exploiting the percent-passing component, a 10×10 cm{sup 2} field can have a 95% passing rate when an 8 cm{sup 2}=2.8×2.8 cm{sup 2} highly out-of-tolerance (e.g. zero dose) square is missing from the comparison image. For clinically realistic vulnerabilities, an arc plan for which a 2D image is created can have a >95% passing rate solely due to agreement in the lateral spillage, with the failing 5% in the critical target region. A field with an integrated boost (e.g whole brain plus small metastases) could neglect the metastases entirely, yet still pass with a 95% threshold. All the failure modes described would be visually apparent on a gamma-map image. Conclusion: The %gamma<1 metric has significant vulnerabilities. High passing rates can obscure critical faults in hypothetical and delivered radiation doses. Great caution should be used with gamma as a QA metric; users should inspect the gamma-map. Visual analysis of gamma-maps may be impractical for cine acquisition.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Metrics for Decision-Making in Energy Justice

Energy equity and justice have become priority considerations for policymakers, practitioners, and scholars alike. To ensure that energy equity is incorporated into actual decisions and analysis, it is necessary to design, use, and continually improve energy equity metrics. In this article, we review the literature and practices surrounding such metrics. We present a working definition for energy justice and equity, and connect them to both criteria for and frameworks of metrics. We then present a large sampling of energy equity metrics, including those focused on vulnerability, wealth creation, energy poverty, life cycle, and comparative country-level dynamics. We conclude with a discussion of the limitations, gaps, and trade-offs associated with these various metrics and their interactions thereof.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

Applying energy justice metrics to photovoltaic materials research

Abstract Achieving the energy transition sustainably requires addressing how new technologies may impact justice in the energy system. The Justice Underpinning Science and Technology Research (JUST-R) metrics framework was recently proposed to aid researchers in considering justice in early-stage research on energy technologies; however, case study evaluations of the framework revealed a desire from researchers to see metrics specialized to particular fields of study. Here, we refine metrics from the JUST-R framework to enhance its applicability to photovoltaic (PV) materials research. Metrics are reorganized to align with aspects of the research process (e.g., research team or source materials). For most metrics, baseline values are suggested to enable researchers to compare their project to competing technologies or standards at their institutions. These refinements are integrated into a tool to facilitate easier understanding and evaluation of justice considerations in early-stage PV research, which can serve as a template for evaluating other energy technologies. Graphical abstract

14 SOLAR ENERGY↗
DOE OSTI2011

Impact of Different Economic Performance Metrics on the Perceived Value of Solar Photovoltaics

Photovoltaic (PV) systems are installed by several types of market participants, ranging from residential customers to large-scale project developers and utilities. Each type of market participant frequently uses a different economic performance metric to characterize PV value because they are looking for different types of returns from a PV investment. This report finds that different economicperformance metrics frequently show different price thresholds for when a PV investment becomes profitable or attractive. Several project parameters, such as financing terms, can have a significant impact on some metrics [e.g., internal rate of return (IRR), net present value (NPV), and benefit-to-cost (B/C) ratio] while having a minimal impact on other metrics (e.g., simple payback time). Assuch, the choice of economic performance metric by different customer types can significantly shape each customer's perception of PV investment value and ultimately their adoption decision.

14 SOLAR ENERGY↗
DOE OSTI2014

Smart Grid Status and Metrics Report Appendices

A smart grid uses digital power control and communication technology to improve the reliability, security, flexibility, and efficiency of the electric system, from large generation through the delivery systems to electricity consumers and a growing number of distributed generation and storage resources. To convey progress made in achieving the vision of a smart grid, this report uses a set of six characteristics derived from the National Energy Technology Laboratory Modern Grid Strategy. The Smart Grid Status and Metrics Report defines and examines 21 metrics that collectively provide insight into the grid’s capacity to embody these characteristics. This appendix presents papers covering each of the 21 metrics identified in Section 2.1 of the Smart Grid Status and Metrics Report. These metric papers were prepared in advance of the main body of the report and collectively form its informational backbone.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS2016

Performance Metrics, Error Modeling, and Uncertainty Quantification

A common set of statistical metrics has been used to summarize the performance of models or measurements-­ the most widely used ones being bias, mean square error, and linear correlation coefficient. They assume linear, additive, Gaussian errors, and they are interdependent, incomplete, and incapable of directly quantifying un­certainty. The authors demonstrate that these metrics can be directly derived from the parameters of the simple linear error model. Since a correct error model captures the full error information, it is argued that the specification of a parametric error model should be an alternative to the metrics-based approach. The error-modeling meth­odology is applicable to both linear and nonlinear errors, while the metrics are only meaningful for linear errors. In addition, the error model expresses the error structure more naturally, and directly quantifies uncertainty. This argument is further explained by highlighting the intrinsic connections between the performance metrics, the error model, and the joint distribution between the data and the reference.

Quantification↗
DOE OSTI2011

Metrics Evolution in an Energy Research & Development Program

All technology programs progress through three phases: Discovery, Definition, and Deployment. The form and application of program metrics needs to evolve with each phase. During the discovery phase, the program determines what is achievable. A set of tools is needed to define program goals, to analyze credible technical options, and to ensure that the options are compatible and meet the program objectives. A metrics system that scores the potential performance of technical options is part of this system of tools, supporting screening of concepts and aiding in the overall definition of objectives. During the definition phase, the program defines what specifically is wanted. What is achievable is translated into specific systems and specific technical options are selected and optimized. A metrics system can help with the identification of options for optimization and the selection of the option for deployment. During the deployment phase, the program shows that the selected system works. Demonstration projects are established and classical systems engineering is employed. During this phase, the metrics communicate system performance. This paper discusses an approach to metrics evolution within the Department of Energy's Nuclear Fuel Cycle R&D Program, which is working to improve the sustainability of nuclear energy.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

Machine Learning Calabi–Yau Metrics

We apply machine learning to the problem of finding numerical Calabi–Yau metrics. Building on Donaldson's algorithm for calculating balanced metrics on Kähler manifolds, we combine conventional curve fitting and machine-learning techniques to numerically approximate Ricci-flat metrics. We show that machine learning is able to predict the Calabi–Yau metric and quantities associated with it, such as its determinant, having seen only a small sample of training data. Using this in conjunction with a straightforward curve fitting routine, we demonstrate that it is possible to find highly accurate numerical metrics much more quickly than by using Donaldson's algorithm alone, with our new machine-learning algorithm decreasing the time required by between one and two orders of magnitude.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2016

Quantitative metrics for assessment of chemical image quality and spatial resolution

Rationale: Currently objective/quantitative descriptions of the quality and spatial resolution of mass spectrometry derived chemical images are not standardized. Development of these standardized metrics is required to objectively describe chemical imaging capabilities of existing and/or new mass spectrometry imaging technologies. Such metrics would allow unbiased judgment of intra-laboratory advancement and/or inter-laboratory comparison for these technologies if used together with standardized surfaces. Methods: We developed two image metrics, viz., chemical image contrast (ChemIC) based on signal-to-noise related statistical measures on chemical image pixels and corrected resolving power factor (cRPF) constructed from statistical analysis of mass-to-charge chronograms across features of interest in an image. These metrics, quantifying chemical image quality and spatial resolution, respectively, were used to evaluate chemical images of a model photoresist patterned surface collected using a laser ablation/liquid vortex capture mass spectrometry imaging system under different instrument operational parameters. Results: The calculated ChemIC and cRPF metrics determined in an unbiased fashion the relative ranking of chemical image quality obtained with the laser ablation/liquid vortex capture mass spectrometry imaging system. These rankings were used to show that both chemical image contrast and spatial resolution deteriorated with increasing surface scan speed, increased lane spacing and decreasing size of surface features. Conclusions: ChemIC and cRPF, respectively, were developed and successfully applied for the objective description of chemical image quality and spatial resolution of chemical images collected from model surfaces using a laser ablation/liquid vortex capture mass spectrometry imaging system.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

A ductility metric for refractory-based multi-principal-element alloys

We propose a quantum-mechanical dimensionless metric, the local-lattice distortion (LLD), as a reliable predictor of ductility in refractory multi-principal-element alloys (RMPEAs). The LLD metric is based on electronegativity differences in localized chemical environments and combines atomic-scale displacements due to local lattice distortions with a weighted average of valence-electron count. To evaluate the effectiveness of this metric, we examined body-centered cubic (bcc) refractory alloys that exhibit ductile-to-brittle behavior. Our findings demonstrate that local-charge behavior can be tuned via composition to enhance ductility in RMPEAs. With finite-sized cell effects eliminated, the LLD metric accurately predicted the ductility of arbitrary alloys, which compares well with existing tensile-elongation experiments. To validate further, we qualitatively evaluated the ductility of two refractory RMPEAs, i.e., NbTaMoW and Mo 72 W 13 Ta 10 Ti 2.5 Zr 2.5 , through the observation of crack formation under indentation, again showing excellent agreement with LLD predictions. Additionally, a comparative study of three refractory alloys provides further insights into the electronic-structure origin of ductility in refractory RMPEAs. This proposed metric enables rapid and accurate assessment of ductility behavior in the vast RMPEA composition space.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Are grid cells used for navigation? On local metrics, subjective spaces, and black holes

The symmetric, lattice-like spatial pattern of grid-cell activity is thought to provide a neuronal global metric for space. This view is compatible with grid cells recorded in empty boxes but inconsistent with data from more naturalistic settings. Here, we review evidence arguing against the global-metric notion, including the distortion and disintegration of the grid pattern in complex and three-dimensional environments. We argue that deviations from lattice symmetry are key for understanding grid-cell function. We propose three possible functions for grid cells, which treat real-world grid distortions as a feature rather than a bug. First, grid cells may constitute a local metric for proximal space rather than a global metric for all space. Second, grid cells could form a metric for subjective action-relevant space rather than physical space. Third, distortions may represent salient locations. Finally, we discuss mechanisms that can underlie these functions. These ideas may transform our thinking about grid cells.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

Optimizing multi-modal, non-axisymmetric plasma response metrics with additional coil rows on DIII-D

The expansion of the DIII-D tokamak operational space via the addition of new non-axisymmetric coil rows is investigated using the linear MHD plasma response code MARS-F. The plasma response to magnetic perturbations imposed by five distinct low- and high-field side coil geometries is modeled for toroidal mode numbers up to n = 6. A set of linear (~δB^2: resonant, kink mode amplitude) and quadratic (~δB: core and edge integrated NTV torque) plasma metrics are defined and compared directly for the various coil geometries. Coil size is also scanned as a secondary optimization variable. An in-vessel coil located at the low-field side midplane is identified as the most efficient plasma response actuator across all metrics and toroidal mode numbers. The multi-row combination of this new midplane (M) coil with the existing DIII-D non-axisymmetric coil set is considered in numerical optimization studies to quantify the impact of this new coil on modeled plasma response metrics. The addition of the M coil is shown to significantly increase the actuator efficiency in maximizing individual plasma response metrics as well as maximizing multi-modal ratios of response metrics, e.g. maximizing resonant modes or edge NTV torque while minimizing kink modes or core NTV torque. The ex-vessel midplane (C) coil is also observed to have an outsize effect on multi-modal optimization due to its uniquely narrow poloidal spectra, and the expansion of optimization space due to the combined use of the two existing in-vessel coil rows with both the M and C coils is notably larger than either coil's individual contribution even though both share similar poloidal locations. This four-row system is expected to greatly extend abilities to understand and optimize the control of transients and rotation on the DIII-D tokamak.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Assessing tension metrics with dark energy survey and Planck data

ABSTRACT Quantifying tensions – inconsistencies amongst measurements of cosmological parameters by different experiments – has emerged as a crucial part of modern cosmological data analysis. Statistically significant tensions between two experiments or cosmological probes may indicate new physics extending beyond the standard cosmological model and need to be promptly identified. We apply several tension estimators proposed in the literature to the dark energy survey (DES) large-scale structure measurement and Planck cosmic microwave background data. We first evaluate the responsiveness of these metrics to an input tension artificially introduced between the two, using synthetic DES data. We then apply the metrics to the comparison of Planck and actual DES Year 1 data. We find that the parameter differences, Eigentension, and Suspiciousness metrics all yield similar results on both simulated and real data, while the Bayes ratio is inconsistent with the rest due to its dependence on the prior volume. Using these metrics, we calculate the tension between DES Year 1 3 × 2pt and Planck, finding the surveys to be in ∼2.3σ tension under the ΛCDM paradigm. This suite of metrics provides a toolset for robustly testing tensions in the DES Year 3 data and beyond.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

Superposed metric for spinning black hole binaries approaching merger

Here, we construct an approximate metric that represents the spacetime of spinning binary black holes (BBH) approaching merger. We build the metric as an analytical superposition of two Kerr metrics in harmonic coordinates, where we transform each black hole term with time-dependent boosts describing an inspiral trajectory. The velocities and trajectories of the boost are obtained by solving the post-Newtonian (PN) equations of motion at 3.5 PN order. We analyze the spacetime scalars of the new metric and we show that it is an accurate approximation of Einstein’s field equations in vacuum for a BBH system in the inspiral regime. Furthermore, to prove the effectiveness of our approach, we test the metric in the context of a 3D general relativistic magnetohydrodynamical (GRMHD) simulation of accreting minidisks around the black holes. We compare our results with a previous well-tested spacetime construction based on the asymptotic matching method. We conclude that our new spacetime is well-suited for long-term GRMHD simulations of spinning binary black holes on their way to the merger.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Metric Learning to Accelerate Convergence of Operator Splitting Methods

Recent developments in machine learning have led to promising advances in accelerating the solution of constrained optimization problems. Increasing demand for real-time decision-making capabilities in applications such as artificial intelligence and optimal control has led to a variety of proposed strategies for learning to produce fast solutions to optimization problems. For example, recent works have shown that it is possible to accelerate the convergence of optimization algorithms by learning to select their parameters, such as gradient descent stepsizes. This work proposes a new approach, in which the underlying metric spaces of proximal operator splitting algorithms are learned to maximize convergence rate. While prior works in optimization theory have derived optimal metrics in simple cases, no such result exists for many practical problem forms including general Quadratic Programming (QP). This paper shows how differentiable optimization can enable the end-to-end learning of proximal metrics, enhancing the convergence of proximal algorithms for QP problems beyond what is possible based on known theory. Additionally, the results illustrate a strong connection between the learned proximal metrics and active constraints at the optima, leading to an interpretation in which the predicted proximal metrics can be viewed as a form of active set prediction.

King, Ethan [BATTELLE (PACIFIC NW LAB)]↗
DOE OSTI2021

Validation Metrics for Fixed Effects and Mixed-Effects Calibration

The modern scientific process often involves the development of a predictive computational model. To improve its accuracy, a computational model can be calibrated to a set of experimental data. A variety of validation metrics can be used to quantify this process. Some of these metrics have direct physical interpretations and a history of use, while others, especially those for probabilistic data, are more difficult to interpret. In this work, a variety of validation metrics are used to quantify the accuracy of different calibration methods. Frequentist and Bayesian perspectives are used with both fixed effects and mixed-effects statistical models. Through a quantitative comparison of the resulting distributions, the most accurate calibration method can be selected. Two examples are included which compare the results of various validation metrics for different calibration methods. It is quantitatively shown that, in the presence of significant laboratory biases, a fixed effects calibration is significantly less accurate than a mixed-effects calibration. This is because the mixed-effects statistical model better characterizes the underlying parameter distributions than the fixed effects model. The results suggest that validation metrics can be used to select the most accurate calibration model for a particular empirical model with corresponding experimental data.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

How accurately can the peak skin dose in fluoroscopy be determined using indirect dose metrics?

Purpose: Skin dosimetry is important for fluoroscopically-guided interventions, as peak skin doses (PSD) that result in skin reactions can be reached during these procedures. There is no consensus as to whether or not indirect skin dosimetry is sufficiently accurate for fluoroscopically-guided interventions. However, measuring PSD with film is difficult and the decision to do so must be madea priori. The purpose of this study was to assess the accuracy of different types of indirect dose estimates and to determine if PSD can be calculated within ±50% using indirect dose metrics for embolization procedures. Methods: PSD were measured directly using radiochromic film for 41 consecutive embolization procedures at two sites. Indirect dose metrics from the procedures were collected, including reference air kerma. Four different estimates of PSD were calculated from the indirect dose metrics and compared along with reference air kerma to the measured PSD for each case. The four indirect estimates included a standard calculation method, the use of detailed information from the radiation dose structured report, and two simplified calculation methods based on the standard method. Indirect dosimetry results were compared with direct measurements, including an analysis of uncertainty associated with film dosimetry. Factors affecting the accuracy of the different indirect estimates were examined. Results: When using the standard calculation method, calculated PSD were within ±35% for all 41 procedures studied. Calculated PSD were within ±50% for a simplified method using a single source-to-patient distance for all calculations. Reference air kerma was within ±50% for all but one procedure. Cases for which reference air kerma or calculated PSD exhibited large (±35%) differences from the measured PSD were analyzed, and two main causative factors were identified: unusually small or large source-to-patient distances and large contributions to reference air kerma from cone beam computed tomography or acquisition runs acquired at large primary gantry angles. When calculated uncertainty limits [−12.8%, 10%] were applied to directly measured PSD, most indirect PSD estimates remained within ±50% of the measured PSD. Conclusions: Using indirect dose metrics, PSD can be determined within ±35% for embolization procedures. Reference air kerma can be used without modification to set notification limits and substantial radiation dose levels, provided the displayed reference air kerma is accurate. These results can reasonably be extended to similar procedures, including vascular and interventional oncology. Considering these results, film dosimetry is likely an unnecessary effort for these types of procedures when indirect dose metrics are available.

60 APPLIED LIFE SCIENCES↗