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DOE OSTI2024

PRIMO - The P&A Project Optimizer

In support of the Methane Emissions Reduction Program (MERP) and under the National Methane Emissions Reduction Initiative (NEMRI), the National Energy Technology Laboratory (NETL) and NETL site support contractors are developing and releasing an open-source decision-support tool (“PRIMO”) to help organizations determine which marginal conventional wells (MCWs) or other low-producing wells make the best candidates for plugging utilizing MERP funds, while also optimizing subsequent plugging and abandonment (P&A) campaigns for both program impact and efficiency. The framework—which is fully customizable—provides three main capabilities: 1. Ranking candidate wells (based on user preferences) 2. Identifying high-impact, high-efficiency P&A project candidates (with transparently computed scores for relevant metrics) 3. Comparing competing P&A projects quantitatively (through transparently computed project impact and efficiency scores) As such, PRIMO is a versatile, fully customizable tool that is meant to support organizations in making data-based, transparent, and defensible well selection and P&A project design decisions. For questions, comments or feedback, please contact primo@netl.doe.gov.

MERP↗

NASA NTRS2009

Metrics for the NASA Airspace Systems Program

This document defines an initial set of metrics for use by the NASA Airspace Systems Program (ASP). ASP consists of the NextGen-Airspace Project and the NextGen-Airportal Project. The work in each project is organized along multiple, discipline-level Research Focus Areas (RFAs). Each RFA is developing future concept elements in support of the Next Generation Air Transportation System (NextGen), as defined by the Joint Planning and Development Office (JPDO). In addition, a single, system-level RFA is responsible for integrating concept elements across RFAs in both projects and for assessing system-wide benefits. The primary purpose of this document is to define a common set of metrics for measuring National Airspace System (NAS) performance before and after the introduction of ASP-developed concepts for NextGen as the system handles increasing traffic. The metrics are directly traceable to NextGen goals and objectives as defined by the JPDO and hence will be used to measure the progress of ASP research toward reaching those goals. The scope of this document is focused on defining a common set of metrics for measuring NAS capacity, efficiency, robustness, and safety at the system-level and at the RFA-level. Use of common metrics will focus ASP research toward achieving system-level performance goals and objectives and enable the discipline-level RFAs to evaluate the impact of their concepts at the system level.

Smith, Jeremy C.↗

DOE OSTI2021

BSSD Performance Metric report: LLNL Soil Microbiome SFA (Q1 2021)

The LLNL “Microbes Persist” Soil Microbiome Scientific Focus Area (SFA) seeks to determine how microbial soil ecophysiology, population dynamics, and microbe-mineral-organic matter interactions regulate the persistence of microbial residues and the formation of soil carbon. Our SFA research program is now four years old; it evolved and benefited from previously-funded BSSD projects in the Firestone (UCB), Banfield (UCB), Sullivan (OSU) and Hungate (NAU) labs. We use stable isotope probing in combination with ‘omics to measure how changing water regimes shape activity of individual microbial populations and ecophysiological traits that affect the fate of microbial and plant C. Using measures of population dynamics and microbiome-mineral interactions, we are working to synthesize both genomescale and ecosystem-scale models of soil organic matter (SOM) turnover, to predict the long-aspired connection between soil microbiomes and fate of soil C.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

EXCHANGE Campaign 1: A Community-Driven Baseline Characterization of Soils, Sediments, and Water Across Coastal Gradients

The EXploration of Coastal Hydrobiogeochemistry Across a Network of Gradients and Experiments (EXCHANGE) program is a consortium of scientists working together to improve our understanding of how the two-way exchange of water between estuaries or large lake lacustuaries and the terrestrial landscape influence the state and function of ecosystems across the coastal interface. EXCHANGE Campaign 1 (EC1) focuses on the spatial variation in biogeochemical structure and function at the coastal terrestrial-aquatic interface (TAI). In the Fall of 2021, the EXCHANGE Consortium gathered samples from 52 TAIs. Samples collected from EC1 were analyzed for bulk geochemical parameters, bulk physicochemical parameters, organic matter characteristics, and redox-sensitive elements.Please download ec1_README.pdf for a complete list of available data in each .zip folder, package version history, and detailed information about the project. This README will serve as the central place for EC1 Data Package updates. Experimental setup and v1 methods are documented in Myers-Pigg and Pennington et al., 2023 (https://doi.org/10.1038/s41597-023-02548-7).EC1 Data Package Structure:ec1_README.pdfec1_methods.pdfec1_metadata_v3.zip...ec1_dd.csv...ec1_flmd.csv...ec1_sample_catalog.csv...ec1_metadata_kitlevel.csv...ec1_metadata_collectionlevel.csv...ec1_data_collectionlevel.csv...ec1_igsn_metadata.csvec1_soil_v3.zipec1_sediment_v3.zipec1_water_v3.zipec1_processingscripts_v3.zipThis data package is on v3 and was originally published May 2023 (v1). Subsequent updates will be published here with new version numbers. Please see the Change History section in ec1_README.pdf for detailed changes.---Acknowledging EXCHANGE: General Support and Data Product UseWe ask that users of EXCHANGE data add the following acknowledgement when publishing data in scholarly articles and data repositories:"This research is based on work supported by COMPASS-FME, a multi-institutional project supported by the U.S. Department of Energy, Office of Science, Biological and Environmental Research as part of the Environmental System Science Program."

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Wind Plant Performance Prediction Benchmark Phase 1 (Technical Report)

Financial risk resulting from the uncertainty associated with developing, owning, and operating wind power plants remains a barrier to reducing the levelized cost of energy (LCOE). On average, modern wind power plants in the U.S. underperform their expected annual energy output by 3.5-4.5% , with many underperforming by over 10%. To compensate for this uncertainty, investors require a larger return on investment (ROI) and apply "knock-down" factors that mask much of the underlying sources of uncertainty. Wind energy projects thus have reduced access to low-cost capital. Furthermore, operating wind plants often take a simple approach to estimating operations & maintenance (O&M) costs (e.g. straight-line estimates based on similar plants), which can eat into profits. To overcome these issues, the wind industry must improve the models they use for estimating wind plant performance and operations. An industry consortium (IC) requested that the National Renewable Energy Laboratory (NREL) lead a Department of Energy (DOE) working group to benchmark the accuracy of wind power plant energy predictions against real operational data. The IC was also motivated by DOE and NREL's potential to characterize systematic energy underperformance, identify sources of uncertainty, and explore root causes. The Wind Plant Performance Prediction (WP3) project was created out of this request, and this report represents the successful completion of Phase 1 of the WP3 project. During the project, wind plant owners provided both pre-construction and operational data to NREL. The pre-construction data was provided to wind resource assessment (WRA) consultants so they could conduct energy yield assessments (EYA). NREL took all of the completed EYAs, along with the operational data, and conducted an operational assessment to benchmark the EYA results against actual operational data. Given the large amounts of sensitive data required for this effort, as well as historical opposition to sharing data within industry, successful completion of Phase 1 represents an unprecedented milestone for industry data sharing. To improve the accuracy and confidence of pre-construction EYAs, wind plant owners and investors need better, more certain, energy yield predictions. The WP3 Benchmark Project is an industry-driven response to this reality. For the first time, industry has taken the important step of working together at scale, sharing valuable operational data with DOE and NREL in order to investigate the sources of bias and uncertainty in these energy estimates. This IC provides wind plant preconstruction and operational data to NREL in an organized and documented fashion and provides guidance and feedback as needed. The IC also provides introspection of the design of experiment, key metrics of success, data challenges, analysis best practices, and quality of results.

17 WIND ENERGY↗

NASA NTRS1992

Distance and organization in multifunction displays

One approach to organizing information in a multifunction display (MFD) is to place related screens of information closer to each other. This study identified three metrics that could be used to operationalize the concept of distance in an MFD. The proposed distance metrics - navigational (the number of choice points lying between two screens), organizational (the hierarchical structure of the data base), and cognitive (the user's perception of relationships among screens) - were empirically examined by using a simulated, hierarchically arranged, menu-driven MFD in an aviation context. Subjects engaged in two tasks that required them to access different target screens from various starting screens in a 290-screen MFD. The tasks differed in the navigational mechanisms subjects were allowed to use to navigate around the MFD and the relationships between the starting and target screens. The results suggest that the three distance metrics are meaningful within the context of a multifunction display.

Seidler, Karen S.↗

DOE OSTI2025

Livewire: Automatic Annotations

Diogenes processes datasets to provide data quality metrics for the Livewire platform and creates standardized data dictionaries from data annotations. Diogenes needs data annotations that clearly outline thenformat and organization of the data. It also relies on the type, class, and unit of each data piece for comprehensive analysis, which it cannot determine independently. The Annotation Tool significantly reduces the time needed to create annotations for Diogenes by generating data annotations with the correct formatting and content. It also employs machine learning and hard-coded models to automatically annotate data class, quality type, and data units.

33 - ADVANCED PROPULSION SYSTEMS↗

NASA NTRSDate not supplied

The System Complexity Metric (SCM) Explains Systems Design and is Correlated with Cost and Failure Rate

The human short term memory span and working capacity is limited to three to five items, especially if they are organized complex “chunks” of information. The impression of complexity occurs when a system is simply difficult to understand, where there is no apparent pattern to predict its behavior. Hierarchical systems design can reduce perceived complexity and increase the amount of information that can be managed. The SCM was developed to measure complexity and help compare proposed overall system architectures before detailed design information is available. The SCM is defined as the sum of the number of major nodes, N, in the system block diagram plus the number of one-way interactions, I, between the nodes. SCM = N + I. SCM’s are easily determined by direct inspection of high-level block diagrams of life support systems. Axiomatic design develops a hierarchy of subsystem requirements and designs together in a top-down, back-and-forth process. A coupling matrix is used to control the relationships between the subsystem functions and design concepts. Axiomatic design can improve system design by decoupling requirements and designs. Axiomatic design was applied to the planning of a closed life support system, similar to that used on the International Space Station. A materially open as opposed to a closed system design was created by removing the interconnections required to close the system. The open system had the same number of designed subsystems as the closed system, but it had many fewer interconnections and its SCM was lower by about half. The costs were estimated and the MTBF (Mean Time Before Failure) tabulated for open and closed space life support systems. The estimated costs were linearly proportional to SCM for the wide variations of SCM in life support, but small differences may not be significant. The flight and preflight MTBF’s both declined exponentially with increasing MTBF, faster than MTBF-2, even though the preflight estimated MTBF’s were about ten times higher than the flight MTBF’s.

System Complexity Metric (SCM)↗

DOE OSTI2020

Achieving high hydrogen productivities of 20 L/L-day via microbial electrolysis of corn stover fermentation products

Microbial electrolysis cells have the potential to generate renewable hydrogen from underused waste streams, however current devices have not reached very large productivity targets using real waste products at any scale. This study used a waste from fermented corn stover known as corn stover fermentation product to reach performance metrics that could be commercialized, if adequately scaled. Average current densities in MECs with mature biofilms reached 17.9 +/- 1.6 A/m 2 at an organic loading rate of 30 grams of chemical oxygen demand per liter of anode volume per day (g/L-day), reaching a maximum current density of 27.2 +/- 2.9 A/m 2 . Hydrogen productivities reached 20.2 +/- 2.0 L of H 2 per L anode volume per day (L/L-day). These represent the highest current densities and highest hydrogen productivities using a complex feedstock in a microbial electrolysis cell. Organic acids and sugars present in untreated substrate were converted at high percentages in MECs, with most above 90% conversion, at organic loading rates of 10, 20, and 30 g/L-day. The effect of periodic high liquid flow rates through the anode on performance was assessed. These tests, called pulsing, showed that hydrogen productivities and current densities increased most dramatically as flow was pulsed every hour at a baseline flow rate of 0.3 mL/min. These productivities show promise for high performance systems, if adequate scale up can be achieved.

09 BIOMASS FUELS↗

DOE OSTI2026

Medium- and Heavy-Duty Truck Duty Cycles

This dataset provides second-by-second duty cycle data for Class 6 and Class 8 diesel trucks in Texas, including key vehicle metrics, engine-related data, and GPS data (excluding GPS latitude and longitude to ensure confidentiality). The data were collected via tablets installed on the trucks and organized into daily datasets, each associated with a unique vehicle ID and date. There are 12 daily datasets for Class 6 diesel trucks (three unique vehicle IDs) and 43 daily datasets for Class 8 diesel trucks (six unique vehicle IDs). The units associated with each column are included in the name. The engine performance data include columns such as engine speed, engine percent torque, and engine fuel rate. Road grade (%/100) was estimated using the GPS altitude and wheel-based vehicle speed, which is used as an input for FASTSim. Cumulative distance was also calculated using the wheel-based vehicle speed. Additional columns include: - Engine Speed (RPM): Removed inaccurate readings and used to calculate angular velocity (radians/second). - Torque (N·m): Calculated using engine percent torque, nominal friction percent torque, and engine reference torque values (those columns were removed from dataset), then normalized to express as torque (%). - Flywheel Power (%): Calculated using the angular velocity and torque (in kW), then normalized as a percentage of the maximum value. - Engine Fuel Rate (%) and Torque (%): Both metrics were normalized by dividing by their respective maximum values within each dataset to express them as percentages. The datasets were analyzed to assess the energy impact of various driving behaviors, simulate energy efficiency, and recommend optimal routes for diesel trucks using NLR’s tool called RouteE. For driver coaching, factors like speed and acceleration limits were considered, and idle periods were reduced (assuming the engine was off during idling) to adjust each drive cycle. These adjusted drive cycles were then simulated in FASTSim to evaluate their effect on fleet energy consumption and estimate potential energy savings. The original cycles are available for download on this page ![image](CoVaR_Image_for_Data_Page_Kenworth_Truck.jpg)

1Hz↗

DOE OSTI2023

Evaluating Retention Index Score Assumptions to Refine GC–MS Metabolite Identification

As metabolomics grows into a high-throughput and high demand research field, current metrics for the identification of small molecules in gas chromatography–mass spectrometry (GC–MS) still require manual verification. Though steps have been taken to improve scoring metrics by combining spectral similarity (SS) and retention index (RI), the problem persists. A large body of literature has analyzed and refined SS scores, but few studies have explicitly studied improvements to RI scores. Here, in this study, we examined whether uninvestigated assumptions of the RI score are valid and propose ways to improve them. Query RIs were matched to library RI with a generous window of ±35 to avoid unintentional removal of valid compound identifications. Each match was manually verified as a true positive (TP), true negative, or unknown. Metabolites with at least 30 TP identifications were included in downstream analyses, resulting in a total of 87 metabolites from samples of varying complexity and type (e.g., amino acid mixtures, human urine, fungal species, and so on.). Our results showed that the RI score assumptions of normality, consistent variance across metabolites, and a mean error centered at 0 are often violated. We demonstrated through a cross-validation analysis that modifying these underlying assumptions according to empirical metabolite-specific distributions improved the TP and negative rankings. Further, we statistically determined the minimum number of samples required to estimate distributional parameters for scoring metrics. Overall, this work proposes a robust statistical pipeline to reduce the time bottleneck of metabolite identification by improving RI scores and thus minimize the effort to complete manual verification.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

Discrete Element Method Analysis for Metal Powders Used in Additive Manufacturing, and DEM Simulation Tutorial Using LIGGGHTS-PUBLIC [PowerPoint and paper]

Discrete Element Method (DEM) is a method of analysis to evaluate the dynamic interactions between granular particles. This method has been used in the pharmaceutical industry to improve the powder compaction process for tablet manufacturing. There are also applications in agriculture, food industry, and manufacturing. Direct energy deposition is an additive manufacturing technique which uses metallic powders fed through a nozzle, melted using a directed laser, and transformed into a solid object layer by layer. One way of feeding metal particles into the system involves the use of a vibrating hopper. Given a specified amplitude and frequency input, the hopper will enable the powder to travel up a path, and inject through the system with assistance from a stream of gas. The mechanical properties of a printed object can vary, depending on the characteristics of the powder flow and the particles’ as-received properties. Improved understanding of dynamic interactions of flowing powders could enable additive manufacturing components with 2D or 3D variations in mechanical properties, e.g., density. This work uses DEM simulation software to investigate the effects of particle cohesion, friction, and density on the quality of the flow by performing an angle of repose simulation, which is often used as a metric to evaluate the flowability of powders.

36 MATERIALS SCIENCE↗

NASA NTRS1999

Controlling Rapid Change Through Systems Engineering the Organization

A new approach to change management has been developed and applied at the Jet Propulsion Laboratory (JPL). It's main focus is on aligning the organization with the strategic plan; and understanding the internal organizational relationships that impact change, which ultimately determine an organizations ability to be transformed and renewed.

change↗

DOE OSTI2022

Methods and algorithms of cyclic coulometry

Systems, devices, and methods of diagnosing an electrochemical cell using cyclic coulometry are discussed. An exemplary battery diagnostic system comprises a current generator to generate symmetric charge current and discharge current to excite an electrochemical cell, and a cyclic coulometer to evaluate performance of the electrochemical cell. The cyclic coulometer can adjust at least one of a charge time for applying the charge current, or a discharge time for applying the discharge current, to keep a monitored cell voltage toward a specific setpoint. The adjustment of charge or discharge time can be achieved by changing a current switch timing for reversing current from a first to a second current direction. The cyclic coulometer measures one or more electrical parameters during the charge or discharge cycle, and generates a performance metric using the measured electrical parameters.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2023

State Energy Justice Roundtable Series: Energy Justice Metrics

The National Association of Regulatory Utility Commissioners (NARUC), National Association of State Energy Officials (NASEO), and National Governors Association (NGA) hosted a State Energy Justice Roundtable (Roundtable) in April 2022. Participants included federal and state decision-makers, members of community-based organizations, and subject-matter experts. The Roundtable members explored current state efforts to articulate and incorporate energy justice concerns into energy-related decision-making. Participants established connections with one another to better understand the current landscape of existing resources, learn about emerging efforts, and identify ongoing support opportunities for advancing energy justice.This paper is one of five authored by the host organizations on topics that were the focus of the Roundtable. Each paper summarizes key themes, emerging efforts, and group takeaways that were discussed at the Roundtable and should assist state members in developing and meeting their own state goals around energy justice. The papers all include the same discussions of background, introduction, and reading list so they can be read separately. Each paper is written from the perspective of one association and includes options for its members to take actions that could support more equitable state energy policies and programs. The five papers cover: (1) Participation in decision making (NARUC), (2) Customer affordability and arrearages (NARUC), (3) Energy justice metrics (NARUC), (4) Equity in clean energy research and development (NASEO), and (5) Equitable distributed energy resource (DER) access (NGA). The resources and recommendations listed in these papers are not meant to be exhaustive, as this field of study continues to evolve. Although this brief is focused on electricity, energy justice considerations extend to all energy needs and services, including the impact of energy extraction, processing, and distribution functions.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2023

Vitamin interdependencies predicted by metagenomics-informed network analyses and validated in microbial community microcosms

Abstract Metagenomic or metabarcoding data are often used to predict microbial interactions in complex communities, but these predictions are rarely explored experimentally. Here, we use an organism abundance correlation network to investigate factors that control community organization in mine tailings-derived laboratory microbial consortia grown under dozens of conditions. The network is overlaid with metagenomic information about functional capacities to generate testable hypotheses. We develop a metric to predict the importance of each node within its local network environments relative to correlated vitamin auxotrophs, and predict that a Variovorax species is a hub as an important source of thiamine. Quantification of thiamine during the growth of Variovorax in minimal media show high levels of thiamine production, up to 100 mg/L. A few of the correlated thiamine auxotrophs are predicted to produce pantothenate, which we show is required for growth of Variovorax , supporting that a subset of vitamin-dependent interactions are mutualistic. A Cryptococcus yeast produces the B-vitamin pantothenate, and co-culturing with Variovorax leads to a 90-130-fold fitness increase for both organisms. Our study demonstrates the predictive power of metagenome-informed, microbial consortia-based network analyses for identifying microbial interactions that underpin the structure and functioning of microbial communities.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2021

Ab-Initio Simulation Studies of Cr Solvation in Fluoride Molten Salts

Understanding molten salt chemistry is essential in ongoing research of the molten salt nuclear reactor (MSR). In this context, detailed understanding of the mechanisms underlying selective oxidation of metal species, such as Cr, is required to guide the design of effective corrosion mitigation strategies in molten salts. An important starting point for such mechanistic understanding is knowledge of the solvation structure and its role in controlling metal speciation. In this work, we use ab initio molecular dynamics simulations to study the short-range (on the scale of the nearest-neighbor bond lengths) and medium-range (over length scales of several neighbor spacings) structure in three different fluoride melts with and without Cr addition; namely, 2KF-NaF, 2LiF-BeF 2 , and 3LiF-AlF3. We find that Cr 0 ,Cr 2+ ,Cr 3+ can each be coordinated by different numbers of F-, with the variance in coordination number decreasing as oxidation state increases, and that these coordination geometries are largely independent of solvent. The manner by which Cr changes the medium-range structure, however, is found to be solvent-dependent. While 2KF-NaF melts show short and medium range order that is highly dynamic, 2LiF-BeF 2 and 3LiF-AlF 3 are characterized by molecular associates that are relatively long-lived that organize into oligomer structures on larger length scales. Rather than being solvated by F- ions alone, we find that Cr can incorporate into and be solvated within this oligomer structure. Fluoroacidity, alone, may therefore prove too simple a metric for assessing the corrosivity of molten fluorides. As our work suggests, the ability of Cr to solvate must be understood in the context of the short- and medium-range structure of the solvent.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

Probing the potential of type V Deep eutectic solvents as sustainable electrolytes

The increasing interest within the scientific community in environmentally friendly solvents has led to a focus on Deep Eutectic Solvents (DES), which have natural components. DES are viewed as alternatives to traditional organic solvents and have the potential to be used as electrolytes. For the first time, transport properties of four Type V Deep Eutectic Salt Solutions (DESS) were accessed to investigate the potential of this technology, selecting precursors ranked as excellent in Eco-Scale metrics. The DESS were composed of terpene and trioctylphosphine oxide (TOPO), and varying concentrations of lithium bis(trifluoromethane)sulfonimide (LiTFSI), and their properties were assessed through self-diffusion, viscosity, density, and conductivity measurements. While Type V DESS are capable of dissolving significant amounts of LiTFSI (up to 30 % molar), their ionic conductivity is low, with values ranging from 3.6·10 –3 to 9.3·10 –2 mS·cm –1 at 25 °C, thus limiting their suitability as electrolytes, for instance, for lithium-ions batteries applications. Similar diffusion coefficients for Li + and TFSI – ions suggest the formation of long-lived ion pairs moving as a neutral species. As a result, future research aims to introduce additives to disrupt contact ion pairs and enhance transport properties, leveraging the sustainable appeal of DES and their use in advanced energy storage technologies.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗