Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “METRICS”

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 667 records · Page 37

Data Center Facility Monitoring with Physics Aware Approach

U.S. Department of Energy's National Renewable Energy Laboratory (NREL) hosts one of the world's most energy-efficient HPC data centers; this system uses component-level warm-water liquid cooling to efficiently remove heat from the data center and capture it for reuse in the building or rejection to the atmosphere. Given the complexity of this system, building data-driven tools for holistically monitoring and operating the entire data center is a priority for ensuring maximal efficiency and resiliency. In this advanced smart facility, over one million metrics are recorded per minute using state-of-the-art streaming data architecture and software to capture and process the state of the system in real time. Here we detail two efforts to effectively analyze, visualize, and interpret this large volume streaming data. We have developed a novel, flexible system for identifying and visualizing individual metric anomalies and component performance across the data center through automatic metadata extraction and physically-motivated visualization for quick interpretation. Additionally, to directly connect system maintenance to data stream processing we explore a physics informed multi-metric drift and anomaly detection application to detect scale-build up in heat exchangers.

anomaly detection↗

Separability in consistent truncations

The separability of the Hamilton-Jacobi equation has a well-known connection to the existence of Killing vectors and rank-two Killing tensors. This paper combines this connection with the detailed knowledge of the compactification metrics of consistent truncations on spheres. The fact that both the inverse metric of such compactifications, as well as the rank-two Killing tensors can be written in terms of bilinears of Killing vectors on the underlying “round metric,” enables us to perform a detailed analyses of the separability of the Hamilton-Jacobi equation for consistent truncations. We introduce the idea of a separating isometry and show that when a consistent truncation, without reduction gauge vectors, has such an isometry, then the Hamilton-Jacobi equation is always separable. When gauge vectors are present, the gauge group is required to be an abelian subgroup of the separating isometry to not impede separability. We classify the separating isometries for consistent truncations on spheres, S n , for n = 2, …, 7, and exhibit all the corresponding Killing tensors. These results may be of practical use in both identifying when supergravity solutions belong to consistent truncations and generating separable solutions amenable to scalar probe calculations. Finally, while our primary focus is the Hamilton-Jacobi equation, we also make some remarks about separability of the wave equation.

79 ASTRONOMY AND ASTROPHYSICS↗

Geometries with mismatched branes

We study Randall-Sundrum two brane setups with mismatched brane tensions. For the vacuum solutions, boundary conditions demand that the induced metric on each of the branes is either de Sitter, Anti-de Sitter, or Minkowski. For incompatible boundary conditions, the bulk metric is necessarily time-dependent. This introduces a new class of time-dependent solutions with the potential to address cosmological issues and provide alternatives to conventional inflationary (or contracting) scenarios. We take a first step in this paper toward such solutions. One important finding is that the resulting solutions can be very succinctly described in terms of an effective action involving only the induced metric on either one of the branes and the radion field. But the full geometry cannot necessarily be simply described with a single coordinate patch. We concentrate here on the time- dependent solutions but argue that supplemented with a brane stabilization mechanism one can potentially construct interesting cosmological models this way. This is true both with and without a brane stabilization mechanism.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

The phase space distance between collider events

How can one fully harness the power of physics encoded in relativistic N-body phase space? Topologically, phase space is isomorphic to the product space of a simplex and a hypersphere and can be equipped with explicit coordinates and a Riemannian metric. This natural structure that scaffolds the space on which all collider physics events live opens up new directions for machine learning applications and implementation. Here we present a detailed construction of the phase space manifold and its differential line element, identifying particle ordering prescriptions that ensure that the metric satisfies necessary properties. We apply the phase space metric to several binary classification tasks, including discrimination of high-multiplicity resonance decays or boosted hadronic decays of electroweak bosons from QCD processes, and demonstrate powerful performance on simulated data. Our work demonstrates the many benefits of promoting phase space from merely a background on which calculations take place to being geometrically entwined with a theory’s dynamics.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

A Goldstone boson equivalence for inflation

The effective field theory of single-field inflation characterizes the inflationary epoch in terms of a pattern of symmetry breaking. An operator acquires a time-dependent vacuum expectation value, defining a preferred spatial slicing. In the absence of dynamical gravity, the fluctuations around the time-dependent background are described by the Goldstone boson associated with this symmetry breaking process. With gravity, the Goldstone is eaten by the metric, becoming the scalar metric fluctuation. In this paper, we will show that in general single-field inflation, the statistics of scalar metric fluctuations are given by the statistics of this Goldstone boson decoupled from gravity up to corrections that are controlled as an expansion in slow-roll parameters. This even holds in the presence of additional parameters, like the speed of sound, that naively enhance the impact of the gravitational terms. In the process, we derive expressions for leading and sub-leading gravitational corrections to all-orders in the Goldstone boson.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

SPECTER: efficient evaluation of the spectral EMD

The Energy Mover’s Distance (EMD) has seen use in collider physics as a metric between events and as a geometric method of defining infrared and collinear safe observables. Recently, the Spectral Energy Mover’s Distance (SEMD) has been proposed as a more analytically tractable alternative to the EMD. In this work, we obtain a closed-form expression for the Riemannian-like p = 2 SEMD metric between events, eliminating the need to numerically solve an optimal transport problem. Additionally, we show how the SEMD can be used to define event and jet shape observables by minimizing the distance between events and parameterized energy flows (similar to the EMD), and we obtain closed-form expressions for several of these observables. We also present the Specter framework, an efficient and highly parallelized implementation of the SEMD metric and SEMD-derived shape observables as an analogue of the previously-introduced Shaper for EMD-based computations. We demonstrate that computing the SEMD with Specter can be up to a thousand times faster than computing the EMD with standard optimal transport libraries.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Detecting impacts of surface development near weather stations since 1895 in the San Joaquin Valley of California

Abstract Temperature readings observed at surface weather stations have been used for detecting changes in climate due to their long period of observations. The most common temperature metrics recorded are the daily maximum (TMax) and minimum (TMin) extremes. Unfortunately, influences besides background climate variations impact these measurements such as changes in (1) instruments, (2) location, (3) time of observation, and (4) the surrounding artifacts of human civilization (buildings, farms, streets, etc.) Quantifying (4) is difficult because the surrounding infrastructure, unique to each site, often changes slowly and variably and is thus resistant to general algorithms for adjustment. We explore a direct method of detecting this impact by comparing a single station that experienced significant development from 1895 to 2019, and especially since 1970, relative to several other stations with lesser degrees of such development (after adjustments for the (1) to (3) are applied). The target station is Fresno, California (metro population ~ 15,000 in 1900 and ~ 1 million in 2019) situated on the eastern side of the broad, flat San Joaquin Valley in which several other stations reside. A unique component of this study is the use of pentad (5-day averages) as the test metric. Results indicate that Fresno experienced + 0.4 °C decade −1 more nighttime warming (TMin) since 1970 than its neighbors—a time when population grew almost 300%. There was little difference seen in TMax trends between Fresno and non-Fresno stations since 1895 with TMax trends being near zero. A case is made for the use of TMax as the preferred climate metric relative to TMin for a variety of physical reasons. Additionally, temperatures measured at systematic times of the day (i.e., hourly) show promise as climate indicators as compared with TMax and especially TMin (and thus TAvg) due to several complicating factors involved with daily high and low measurements.

54 ENVIRONMENTAL SCIENCES↗

Stacking Fault Energy Based Alloy Screening for Hydrogen Compatibility

The selection of austenitic stainless steels for hydrogen service is challenging since there are few intrinsic metrics that relate alloy composition to hydrogen degradation. One such metric, explored here, is intrinsic stacking fault energy. Stacking fault energy has an influence on the character and structure of dislocations and on the formation of secondary crystalline phases created during mechanical deformation in austenitic alloys. In this work, a data-driven model for the intrinsic stacking fault energy of common austenitic stainless steel alloys is applied to compare the relative degradation of tensile performance in the presence of hydrogen. A transition in the tensile reduction of area of both 300-series and manganese stabilized stainless steels is observed at a calculated stacking fault energy of approximately 43 mJ m -2 , below which pronounced hydrogen degradation on tensile ductility is observed. The model is also applied to suggest alloying strategies for low nickel austenitic stainless steels for hydrogen service. Lastly, through this investigation, we find that calculated intrinsic stacking fault energy is a high-throughput screening metric that enables the ranking of the performance of a diverse range of austenitic stainless steel compositions, as well as the identification of new alloys, with regard to hydrogen compatibility.

08 HYDROGEN↗

Quantifying precursors to void nucleation and coalescence in aluminum

Ductile rupture is a common failure mode for engineering alloys. It is generally comprised of three mechanisms: void nucleation at secondary particles, void growth, and coalescence of voids. Conventional models for ductile rupture have limited precision for predicting macroscopic failure. This is partially because they have been corroborated using ex-situ observations of these three mechanisms and calibrated by macroscopic strain or stress metrics. In this study, in-situ high-energy X-ray characterization was conducted to correlate sites of void nucleation via particle cracking and sites of void growth with grain-scale metrics. Here it is shown that particle cracking is not predicated by elevated stress metrics, which disagrees with classical models. Instead, particle cracking tended to occur for the largest, least spherical particles. This trend persisted on the aggregate-scale and within individual neighborhoods around particles. Furthermore, an Eshelby analysis illuminated a statistically significant increase in maximum principal stress within a cracked particle, compared to an uncracked particle. In-situ observations also revealed two separate examples of intragranular void growth comprised of flat, crack-like features that grew showing alignment with slip systems of the highest resolved shear stress. Post-mortem fractography revealed a secondary population of dimples on these crack-like features, implying that void sheeting may be occurring during this crack-like void growth. Furthermore, these in-situ observations imply that classical models for void growth, that assume a homogenous medium, should be extended to account for the anisotropic grain-level behavior to correctly capture distinct features of void nucleation and growth.

Al-2219↗

Micromechanical and fatigue in situ synchrotron characterization of an additively manufactured superalloy with porosity

Additive manufacturing (AM) has the potential to transform component production, but its widespread adoption is constrained by defects, such as pores, that compromise structural integrity. Here, this study investigates the influence of porosity on the micromechanical and fatigue response of AM Inconel 718 (IN718), a widely used aerospace superalloy. One baseline specimen with minimal stochastic porosity and another intentionally seeded with lack of fusion (LOF) pores were examined using high-energy X-ray diffraction microscopy (HEDM) and micro-computed tomography during cyclic loading. Fatigue cracks in the LOF specimen initiated more frequently and at lower cycle counts than in the baseline specimen. The number fraction of fatigue cracks that grew was comparatively higher in the LOF specimen. Grain-level metrics, including stress and diffraction spot widths, were quantified using far-field HEDM. Across the thousands of grains detected in both specimens, the pores in the LOF specimen increased the variability of stress and spot width evolution in the azimuthal direction, the latter serving as a surrogate measure of plastic deformation. However, no correlations emerged between these metrics and grain proximity to fatigue crack initiation sites or pores, underscoring the limitations of grain-averaged metrics for predicting fatigue. Nonetheless, the rich dataset reported here provides a foundation for future modeling efforts.

High-energy X-ray diffraction microscopy↗

Techno-economic analysis of bioplastic and biofuel production from a high-ash microalgae biofilm cultivated in effluent from a municipal anaerobic digester

Rotating Algae Biofilm Reactors (RABRs) are a promising technology for efficient treatment of wastewater and production of algae-based bioproducts. However, RABR-grown algae can contain a high content of ash (30–60 wt%, dry basis), which influences the technical and economic feasibility of bioproduct conversion processes. In this report, experimental studies and economic analysis were conducted to compare different processes for bioproduct conversion of a high-ash microalgae biofilm grown using a RABR treating 0.6 million gallons per day of anaerobic digestion centrate at the Central Valley Water Reclamation Facility in Salt Lake City, UT. Process and economic models were developed and compared for three conversion processes: 1) the production of bioplastics, 2) the production of bioplastics with a lipid-extraction pretreatment, and 3) the production of biocrude via hydrothermal liquefaction. Techno-economic analysis was performed for each conversion process, including three cases for algae productivity: 231, 391, and 577 metric tons per year (dry basis). The calculated value for the minimum plastic selling price (MPSP) of bioplastics produced from algae ranges from $\$4050$ to $\$3520$ per metric ton based on the baseline and final productivity cases of the RABR, respectively. The extraction of lipids in addition to bioplastic production results in an MPSP of $\$4570$ to $\$4000$ per metric ton for the same productivity cases. The relatively small production scale and complex processing for hydrothermal liquefaction results in a minimum fuel selling price of the biocrude of $\$5.32$ per gallon of gasoline equivalent. In conclusion, the conversion process for bioplastic production from whole algae has the highest income:expense ratio and the most cost-competitive pricing of the three modeled processes.

09 BIOMASS FUELS↗

Validating automated resonance evaluation with synthetic data

The integrity and precision of nuclear data are crucial for a broad spectrum of applications, from national security and nuclear reactor design to medical diagnostics, where the associated uncertainties can significantly impact outcomes. A substantial portion of uncertainty in nuclear data originates from the subjective biases in the evaluation process, a crucial phase in the nuclear data production pipeline. Recent advancements indicate that automation of certain routines can mitigate these biases, thereby standardizing the evaluation process and enhancing reproducibility. This research aims to provide a methodology, framework, and metrics for the validation of automated nuclear data evaluation software leveraging high-quality synthetic data that closely mimic real experimental observables. An introduced error metric provides a scale and intuitive measure of the evaluation quality by quantifying the estimate’s accuracy and performance across the specified energy range. Synthetic data provides access to experimental observables and underlying resonance parameters, enabling comparison of different evaluations. The methodology is demonstrated using Ta-181 isotope data in the resolved resonance region. The Automated Resonance Identification Subroutine (ARIS), which operates without prior resonance information, was used to test and showcase the framework’s capabilities utilizing the proposed error metrics. The results demonstrate the effectiveness of the proposed approach and framework for optimizing software parameters and testing hypotheses through “what-if” controlled experiments, such as modifying assumptions about experimental conditions or average resonance parameters.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Microalgae to biofuels through hydrothermal liquefaction: Open-source techno-economic analysis and life cycle assessment

Hydrothermal liquefaction is a promising conversion technology in algae biofuel research due to its ability to agnostically convert proteins, carbohydrates, and lipids to biocrude. The high-temperature conditions that define this conversion process require the material to maintain a subcritical liquid state, which complicates the assessment of accurate thermochemical properties due to the required pressure. To clarify this issue, this work compares the estimated performance of algal hydrothermal liquefaction between different thermodynamic models. A process model was developed in Aspen Plus from a robust assessment of current literature. Techno-economic assessment and life-cycle assessment metrics are derived from this model and used as key performance indicators. The baseline fuel price contribution of hydrothermal liquefaction is $0.45 per liter gasoline equivalent. Independently decreasing the temperature from 350 °C to 260 °C while maintaining yield reduces the conversion cost by 19%, illustrating the importance of understanding the high-temperature thermodynamics of the system. Different thermodynamic property models can vary fuel conversion cost results by $0.07 per liter gasoline equivalent. The baseline global warming potential is +23 g CO 2 eq MJ -1 and the net energy ratio is 0.30. Environmental metrics beyond global warming potential and net energy ratio are also discussed for the first time. Uncertainties in conversion performance are bounded through a scenario analysis that manipulates parameters such as product yield and nutrient recycle to produce a range of economic and environmental metrics. The report is supplemented with an open source model to support future hydrothermal liquefaction assessments and accelerate the development of commercial-scale systems.

09 BIOMASS FUELS↗

CIEL ∗ Ch color map for visualization and analysis of sea ice motion

The International Commission on Illumination (CIE) designed its color space to be perceptually uniform so that a given numerical change in the color code corresponds to perceived change in color. This color encoding is demon- strated to be advantageous in scientific visualization and analysis of vector fields. The specific application is analysis of ice motion in the Arctic where patterns in smooth monthly-averaged ice motion are seen. Furthermore, fractures occurring in the ice cover result in discontinuities in the ice motion. This vector jump in displacement can also be visualized. We then analyze modeled and observed fractures through the use of a metric on the color space, and image amplitude and phase metrics. Amplitude and phase met- rics arise from image registration that is accomplished by sampling images using space filling curves, thus reducing the image registration problem to the more reliable functional alignment problem. We demonstrate this through an exploration of the metrics to compare model runs to an observed ice crack.

97 MATHEMATICS AND COMPUTING↗

Effect of substrate orientation and anisotropic strength on corrosion pits

The complexities of pitting corrosion and its associated pit morphologies are critical for predicting and preventing pit-related failure in materials. With the advances in computational tools, modeling of pitting corrosion has lately gained momentum. We recently developed a phase field model for 3-D pit morphology, and in the current work, the model is utilized to gain insight into the role of substrate orientation and anisotropic strength on crystallographic pits. The influence of these parameters on pit morphology and corrosion metrics such as pit volume, current, pit area, current density, and pit depth are studied. The crystallographic pit morphology changes with substrate orientation but not significantly with anisotropic strength. Finally, the anisotropic strength strongly influences the corrosion metrics whereas most corrosion metrics remain unaffected by substrate orientation.

36 MATERIALS SCIENCE↗

Synergistic effects of chlorine substitution in sulfide electrolyte solid state batteries

All-solid-state battery is considered as one of the most promising competitors to Li ion batteries. Two widely known performance metrics for solid electrolytes, among others, are ionic conductivity and stability. In this study, it is found that both can be improved by the synergistic effects of chlorine substitution in sulfide-based solid electrolytes. Particularly, instabilities arising from both bulk decompositions and interfacial reactions to electrodes can be better inhibited in the chlorine substituted sulfide solid electrolytes through the increased susceptibility to the mechanical constriction induced enhancement of voltage stability. As a result, the stability window of some chlorine-rich Li-argyrodites can be systematically higher than some other chlorine-deficient or chlorine-free electrolytes, especially under the implementation of the mechanical constriction battery assembly and test conditions. Thus, a solid-state battery system of 4 V to 5 V-class cathodes paired with lithium metal anode is demonstrated using these chlorine-rich Li-argyrodites without additional coatings. Furthermore, since Cl composition modulates the stability and instability of Li-argyrodite at low voltages, it allows us to design a multilayer configuration with a hierarchy of Li metal stabilities to demonstrate the stable cycling at relatively high current densities for solid-state batteries. It is found that a moderate Cl composition in the electrolyte is the best to inhibit Li dendrite penetration as the central electrolyte layer, emphasizing a slightly increased “instability” as the hidden performance metric of relevance here, in addition to the two well-known metrics of stability and ionic conductivity. The understanding of the chlorine substitution effect in sulfide electrolytes provides an important design principle for all-solid-state batteries.

25 ENERGY STORAGE↗

A conceptual framework for residential energy security in the context of clean energy transitions

Energy security is a crucial aspect of human well-being. As climate change impacts become more evident, countries are constructing equitable, resilient, and sustainable clean energy transition policies to reduce emissions while ensuring energy security. Climate policies globally highlight the importance of national energy security. Furthermore, adequate and affordable access to household energy is also critical to the continued prioritization of climate mitigation. However, past energy security discussions within the broader climate research and policymaking community primarily focused on national-level energy supply as a critical metric of energy security. Less research has explored the potential implications of energy transitions for residential energy security, often focusing on a single dimension of residential energy security. Thus, we conduct a review of journal articles and governmental plans to develop a conceptual framework of residential energy security and facilitate communication among researchers and policymakers. The framework is designed around four foundational pillars, five metrics measuring residential energy security, and seven drivers influencing the metrics. Additionally, we provide policy examples to show how this framework can be applied to inform decision-making. Thus, this paper makes important contributions to the literature by (a) creating a framework to better understand the concept of energy security at the household level for future research and policy-relevant communications, (b) identifying gaps in the current literature, and (c) highlighting instances where aspects of residential energy security are discussed in policies and governmental plans, which help serve as guiding examples for future applications of our framework in the policymaking processes.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

An automated and portable method for selecting an optimal GPU frequency

Power consumption poses a significant challenge in current and emerging graphics processing unit (GPU) enabled high-performance computing systems. In modern GPUs, dynamic voltage frequency scaling (DVFS) appears to be a reliable control to regulate power consumption and performance. However, the DVFS design space is large - hence, brute-force approaches are infeasible to select the optimal frequency. Furthermore, no single frequency can be universally optimal for applications with varying computational intensities. Thus, the application's complexity and the availability of a wide range of frequency settings are a challenge in selecting the optimal frequency configuration for a given GPU workload. To that end, this paper proposes a systematic approach that consists of three steps. The feature characterization study identifies the fine-grain GPU utilization metrics that influence the power consumption and execution time of a given workload. To understand the performance, power, and energy consumption behaviors of a workload across GPU's DVFS design space, we derived analytical power and performance models using the identified fine-grain features. Here, it is shown that the same set of GPU utilization metrics can estimate both the power consumption and execution time while being agnostic of changes to frequency and input sizes. Applying a power control with the single objective of reducing power may cause performance degradation, leading to more energy consumption. A multi-objective approach is proposed to select the optimal GPU DVFS configuration for a workload that reduces power consumption with negligible degradation in performance. The evaluation was conducted using SPEC ACCEL benchmarks and three real applications - NAMD LAMMPS, and LSTM on NVIDIA GV100, GA100, and AMD MI210 GPUs. On average, real applications showed 29.6% energy savings with a performance loss of 5.2% on GA100 and 22.6% energy savings with a performance loss of 4.7% on GV100. Moreover, the proposed models are portable to real applications, GPU architectures, and vendors, and require metric collection at only the default frequency rather than all supported DVFS configurations. Additionally, we conducted a comparison between our models and the GPU assembly instructions (PTX)-based static models. The results revealed a significant reduction in the average error rates, with a decrease from 19.7% to 3.1% for power models and from 29.4% to 5.2% for performance models.

97 MATHEMATICS AND COMPUTING↗