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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 OSTI2025

A User-Facing Metric to Quantify the Quality of Mobility (CRADA Final Report)

The leading urban mobility data analytics firm StreetLight Data, Inc. partnered with the National Renewable Energy Laboratory to explore a commercial version of the Mobility Energy Productivity (MEP) metric. The commercialization effort was aimed to expand the adoption of the metric to key stakeholders in the urban planning space. Research comprised industry analysis, stakeholder feedback and conducting transportation practitioner focus groups. StreetLight concluded that commercialization of MEP is not feasible in the current market because users need a dynamic MEP tool that enables scenario planning. It should be able to calculate a MEP score dynamically (near instantaneous) when different inputs are changed.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2020

Data Qualification Framework

Proposed Data Qualification System Background Originally developed as a data qualification system for the Bioenergy Feedstock Library Provide data users a means of assessing data quality based on user driven quality metrics. Give users information regarding common data quality metrics to determine and assess the data quality. Potential Use Same type of quality assessment framework could be potentially applied to other databases and/or datasets for common assessment. Provide metric for assessment of appropriateness of data for various uses.

09 BIOMASS FUELS↗
DOE OSTI2012

Analyses Of Two End-User Software Vulnerability Exposure Metrics

The risk due to software vulnerabilities will not be completely resolved in the near future. Instead, putting reliable vulnerability measures into the hands of end-users so that informed decisions can be made regarding the relative security exposure incurred by choosing one software package over another is of importance. To that end, we propose two new security metrics, average active vulnerabilities (AAV) and vulnerability free days (VFD). These metrics capture both the speed with which new vulnerabilities are reported to vendors and the rate at which software vendors fix them. We then examine how the metrics are computed using currently available datasets and demonstrate their estimation in a simulation experiment using four different browsers as a case study. Finally, we discuss how the metrics may be used by the various stakeholders of software and to software usage decisions.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2012

Dairy Analytics and Nutrient Analysis (DANA) Prototype System User Manual

This document is a user manual for the Dairy Analytics and Nutrient Analysis (DANA) model. DANA provides an analysis of dairy anaerobic digestion technology and allows users to calculate biogas production, co-product valuation, capital costs, expenses, revenue and financial metrics, for user customizable scenarios, dairy and digester types. The model provides results for three anaerobic digester types; Covered Lagoons, Modified Plug Flow, and Complete Mix, and three main energy production technologies; electricity generation, renewable natural gas generation, and compressed natural gas generation. Additional options include different dairy types, bedding types, backend treatment type as well as numerous production, and economic parameters. DANA’s goal is to extend the National Market Value of Anaerobic Digester Products analysis (informa economics, 2012; Innovation Center, 2011) to include a greater and more flexible set of regional digester scenarios and to provide a modular framework for creation of a tool to support farmer and investor needs. Users can set up scenarios from combinations of existing parameters or add new parameters, run the model and view a variety of reports, charts and tables that are automatically produced and delivered over the web interface. DANA is based in the INL’s analysis architecture entitled Generalized Environment for Modeling Systems (GEMS) , which offers extensive collaboration, analysis, and integration opportunities and greatly speeds the ability construct highly scalable web delivered user-oriented decision tools. DANA’s approach uses server-based data processing and web-based user interfaces, rather a client-based spreadsheet approach. This offers a number of benefits over the client-based approach. Server processing and storage can scale up to handle a very large number of scenarios, so that analysis of county, even field level, across the whole U.S., can be performed. Server based databases allow dairy and digester parameters be held and managed in a single managed data repository, while allows users to customize standard values and perform individual analysis. Server-based calculations can be easily extended, versions and upgrades managed, and any changes are immediately available to all users. This user manual describes how to use and/or modify input database tables, run DANA, view and modify reports.

09 BIOMASS FUELS↗
DOE OSTI2024

Metric DBSCAN

SAND2025-11725O Metric DBSCAN is an implementation of the popular DBSCAN clustering algorithm that works in general metric spaces. DBSCAN is a clustering algorithm, a fundamental building block in machine learning. It takes a set of objects and, given some notion of distance, identifies coherent groups of objects. With Metric DBSCAN, users can provide an arbitrary function to compute distance. Nearly all existing implementations of DBSCAN restrict distance to one of a few formulations. Metric DBScan accomplishes this cleanly and efficiently. The Python source code is on Github. 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.

Dalbey, Keith↗
DOE OSTI2012

User's Guide to the Energy Charting and Metrics Tool (ECAM)

The intent of this user guide is to provide a brief description of the functionality of the Energy Charting and Metrics (ECAM) tool, including the expanded building re-tuning functionality developed for Pacific Northwest National laboratory (PNNL). This document describes the tool's general functions and features, and offers detailed instructions for PNNL building re-tuning charts, a feature in ECAM intended to help building owners and operators look at trend data (recommended 15-minute time intervals) in a series of charts (both time series and scatter) to analyze air-handler, zone, and central plant information gathered from a building automation system (BAS).

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2014

IOPro: a parallel I/O profiling and visualization framework for high-performance storage systems

Efficient execution of large-scale scientific applications requires high-performance computing systems designed to meet the I/O requirements. To achieve high-performance, such data-intensive parallel applications use a multi-layer layer I/O software stack, which consists of high-level I/O libraries such as PnetCDF and HDF5, the MPI library, and parallel file systems. To design efficient parallel scientific applications, understanding the complicated flow of I/O operations and the involved interactions among the libraries is quintessential. Such comprehension helps identify I/O bottlenecks and thus exploits the potential performance in different layers of the storage hierarchy. To profile the performance of individual components in the I/O stack and to understand complex interactions among them, we have implemented a GUI-based integrated profiling and analysis framework, IOPro. IOPro automatically generates an instrumented I/O stack, runs applications on it, and visualizes detailed statistics based on the user-specified metrics of interest. We present experimental results from two different real-life applications and show how our framework can be used in practice. By generating an end-to-end trace of the whole I/O stack and pinpointing I/O interference, IOPro aids in understanding I/O behavior and improving the I/O performance significantly.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

astroABC : An Approximate Bayesian Computation Sequential Monte Carlo sampler for cosmological parameter estimation

Given the complexity of modern cosmological parameter inference where we arefaced with non-Gaussian data and noise, correlated systematics and multi-probecorrelated data sets, the Approximate Bayesian Computation (ABC) method is apromising alternative to traditional Markov Chain Monte Carlo approaches in thecase where the Likelihood is intractable or unknown. The ABC method is called"Likelihood free" as it avoids explicit evaluation of the Likelihood by using aforward model simulation of the data which can include systematics. Weintroduce astroABC, an open source ABC Sequential Monte Carlo (SMC) sampler forparameter estimation. A key challenge in astrophysics is the efficient use oflarge multi-probe datasets to constrain high dimensional, possibly correlatedparameter spaces. With this in mind astroABC allows for massive parallelizationusing MPI, a framework that handles spawning of jobs across multiple nodes. Akey new feature of astroABC is the ability to create MPI groups with differentcommunicators, one for the sampler and several others for the forward modelsimulation, which speeds up sampling time considerably. For smaller jobs thePython multiprocessing option is also available. Other key features include: aSequential Monte Carlo sampler, a method for iteratively adapting tolerancelevels, local covariance estimate using scikit-learn's KDTree, modules forspecifying optimal covariance matrix for a component-wise or multivariatenormal perturbation kernel, output and restart files are backed up everyiteration, user defined metric and simulation methods, a module for specifyingheterogeneous parameter priors including non-standard prior PDFs, a module forspecifying a constant, linear, log or exponential tolerance level,well-documented examples and sample scripts. This code is hosted online athttps://github.com/EliseJ/astroABC

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2016

I/O-aware bandwidth allocation for petascale computing systems

In the Big Data era, the gap between the storage performance and an appli- cation's I/O requirement is increasing. I/O congestion caused by concurrent storage accesses from multiple applications is inevitable and severely harms the performance. Conventional approaches either focus on optimizing an ap- plication's access pattern individually or handle I/O requests on a low-level storage layer without any knowledge from the upper-level applications. In this paper, we present a novel I/O-aware bandwidth allocation framework to coordinate ongoing I/O requests on petascale computing systems. The motivation behind this innovation is that the resource management system has a holistic view of both the system state and jobs' activities and can dy- namically control the jobs' status or allocate resource on the y during their execution. We treat a job's I/O requests as periodical subjobs within its lifecycle and transform the I/O congestion issue into a classical scheduling problem. Based on this model, we propose a bandwidth management mech- anism as an extension to the existing scheduling system. We design several bandwidth allocation policies with different optimization objectives either on user-oriented metrics or system performance. We conduct extensive trace- based simulations using real job traces and I/O traces from a production IBM Blue Gene/Q system at Argonne National Laboratory. Experimental results demonstrate that our new design can improve job performance by more than 30%, as well as increasing system performance.

I/O congestion↗
DOE OSTI2022

OptZConfig: Efficient Parallel Optimization of Lossy Compression Configuration

Lossless compressors have very low compression ratios that do not meet the needs of today's large-scale scientific applications that produce vast volumes of data. Error-bounded lossy compression (EBLC) is considered a critical technique for the success of scientific research. Although EBLC allows users to set an error bound for the compression, users have been unable to specify the requirements on the compression quality, limiting practical use. Our contributions are: (1) We formulate the problem of configuring EBLC to preserve a user-defined metric as an optimization problem. This allows many classes of new metrics to be preserved, which improves over current practices. (2) We present a framework, OptZConfig, that can adapt to improvements in the search algorithm, compressor, and metrics with minimal changes, enabling future advancements in this area. (3) We demonstrate the advantages of our approach against the leading methods to configure compressors to preserve specific metrics. Here, our approach improves compression ratios against a specialized compressor by up to 3 x, has a 56x speedup over FRaZ, 1000x speedup over MGARD-QOI post tuning, and 110x speedup over systematic approaches which had not been bounded by compressors before.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Distinguishability of quantum states and shannon complexity in quantum cryptography

The proof of the security of quantum key distribution is a rather complex problem. Security is defined in terms different from the requirements imposed on keys in classical cryptography. In quantum cryptography, the security of keys is expressed in terms of the closeness of the quantum state of an eavesdropper after key distribution to an ideal quantum state that is uncorrelated to the key of legitimate users. A metric of closeness between two quantum states is given by the trace metric. In classical cryptography, the security of keys is understood in terms of, say, the complexity of key search in the presence of side information. In quantum cryptography, side information for the eavesdropper is given by the whole volume of information on keys obtained from both quantum and classical channels. The fact that the mathematical apparatuses used in the proof of key security in classical and quantum cryptography are essentially different leads to misunderstanding and emotional discussions [1]. Therefore, one should be able to answer the question of how different cryptographic robustness criteria are related to each other. In the present study, it is shown that there is a direct relationship between the security criterion in quantum cryptography, which is based on the trace distance determining the distinguishability of quantum states, and the criterion in classical cryptography, which uses guesswork on the determination of a key in the presence of side information.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2019

Evaluating Knowledge to Support Climate Action: A Framework for Sustained Assessment. Report of an Independent Advisory Committee on Applied Climate Assessment

As states, cities, tribes, and private interests cope with climate damages and seek to increase preparedness and resilience, they will need to navigate myriad choices and options available to them. Making these choices in ways that identify pathways for climate action that support their development objectives will require constructive public dialogue, community participation, and flexible and ongoing access to science- and experience-based knowledge. In 2016, a Federal Advisory Committee (FAC) was convened to recommend how to conduct a sustained National Climate Assessment (NCA) to increase the relevance and usability of assessments for informing action. The FAC was disbanded in 2017, but members and additional experts reconvened to complete the report that is presented here. A key recommendation is establishing a new nonfederal ‘‘climate assessment consortium’’ to increase the role of state/local/tribal government and civil society in assessments. The expanded process would 1) focus on applied problems faced by practitioners, 2) organize sustained partnerships for collaborative learning across similar projects and case studies to identify effective tested practices, and 3) assess and improve knowledge-based methods for project implementation. Specific recommendations include evaluating climate models and data using user-defined metrics; improving benefit–cost assessment and supporting decision-making under uncertainty; and accelerating application of tools and methods such as citizen science, artificial intelligence, indicators, and geospatial analysis. The recommendations are the result of broad consultation and present an ambitious agenda for federal agencies, state/local/tribal jurisdictions, universities and the research sector, professional associations, nongovernmental and community-based organizations, and private-sector firms.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Integrating ytopt and libEnsemble to autotune OpenMC

Ytopt is a Python machine-learning-based autotuning software package developed within the ECP PROTEAS-TUNE project. The ytopt software adopts an asynchronous search framework that consists of sampling a small number of input parameter configurations and progressively fitting a surrogate model over the input-output space until exhausting the user-defined maximum number of evaluations or the wall-clock time. libEnsemble is a Python toolkit for coordinating workflows of asynchronous and dynamic ensembles of calculations across massively parallel resources developed within the ECP PETSc/TAO project. libEnsemble helps users take advantage of massively parallel resources to solve design, decision, and inference problems and expands the class of problems that can benefit from increased parallelism. In this paper we present our methodology and framework to integrate ytopt and libEnsemble to take advantage of massively parallel resources to accelerate the autotuning process. Specifically, we focus on using the proposed framework to autotune the ECP ExaSMR application OpenMC, an open source Monte Carlo particle transport code. OpenMC has seven tunable parameters some of which have large ranges such as the number of particles in-flight, which is in the range of 100,000 to 8 million, with its default setting of 1 million. Setting the proper combination of these parameter values to achieve the best performance is extremely time-consuming. Therefore, we apply the proposed framework to autotune the MPI/OpenMP offload version of OpenMC based on a user-defined metric such as the figure of merit (FoM) (particles/s) or energy efficiency energy-delay product (EDP) on Crusher at Oak Ridge Leadership Computing Facility. In conclusion, the experimental results show that we achieve the improvement up to 29.49% in FoM and up to 30.44% in EDP.

Autotuning↗
DOE OSTI2025

Intelligent Manufacturing Support: Specialized LLMs for Composite Material Processing and Equipment Operation

Engineering educational curriculum and standards cover many material and manufacturing options. However, engineers and designers are often unfamiliar with certain composite materials or manufacturing techniques. Large language models (LLMs) could potentially bridge the gap. Their capacity to store and retrieve data from large databases provides them with a breadth of knowledge across disciplines. However, their generalized knowledge base can lack targeted, industry-specific knowledge. To this end, we present two LLM-based applications based on the GPT-4 architecture: (1) The Composites Guide: a system that provides expert knowledge on composites material and connects users with research and industry professionals who can provide additional support and (2) The Equipment Assistant: a system that provides guidance for manufacturing tool operation and material characterization. By combining the knowledge of general AI models with industry-specific knowledge, both applications are intended to provide more meaningful information for engineers. In this paper, we discuss the development of the applications and evaluate it through a benchmark and two informal user studies. The benchmark analysis uses the Rouge and Bertscore metrics to evaluate our models’ performance against GPT-4o. The results show that GPT-4o and the proposed models perform similarly or better on the ROUGE and BERTScore metrics. The two user studies supplement this quantitative evaluation by asking experts to provide qualitative and open-ended feedback about our model’s performance on a set of domain-specific questions. The results of both studies highlight a potential for more detailed and specific responses with the Composites Guide and the Equipment Assistant.

Kapoor, Gunnika [Oak Ridge National Laboratory (OR↗
DOE OSTI2015

Benefits of utilizing CellProfiler as a characterization tool for U–10Mo nuclear fuel

Automated image processing techniques have the potential to aid in the performance evaluation of nuclear fuels by eliminating judgment calls that may vary from person-to-person or sample-to-sample. Analysis of in-core fuel performance is required for design and safety evaluations related to almost every aspect of the nuclear fuel cycle. This study presents a methodology for assessing the quality of uranium–molybdenum fuel images and describes image analysis routines designed for the characterization of several important microstructural properties. The analyses are performed in CellProfiler, an open-source program designed to enable biologists without training in computer vision or programming to automatically extract cellular measurements from large image sets. The quality metric scores an image based on three parameters: the illumination gradient across the image, the overall focus of the image, and the fraction of the image that contains scratches. The metric presents the user with the ability to ‘pass’ or ‘fail’ an image based on a reproducible quality score. Passable images may then be characterized through a separate CellProfiler pipeline, which enlists a variety of common image analysis techniques. The results demonstrate the ability to reliably pass or fail images based on the illumination, focus, and scratch fraction of the image, followed by automatic extraction of morphological data with respect to fission gas voids, interaction layers, and grain boundaries. - Graphical abstract: Display Omitted - Highlights: • A technique is developed to score U–10Mo FIB-SEM image quality using CellProfiler. • The pass/fail metric is based on image illumination, focus, and area scratched. • Automated image analysis is performed in pipeline fashion to characterize images. • Fission gas void, interaction layer, and grain boundary coverage data is extracted. • Preliminary characterization results demonstrate consistency of the algorithm.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2011

User's Guide to Pre-Processing Data in Universal Translator 2 for the Energy Charting and Metrics Tool (ECAM)

This document is a user's guide for the Energy Charting and Metrics Tool to facilitate the examination of energy information from buildings, reducing the time spent analyzing trend and utility meter data. This user guide was generated to help pre-process data with the intention of utilizing the Energy Charting and Metrics (ECAM) tool to improve building operational efficiency. There are numerous occasions when the metered data that is received from the building automation system (BAS) isn't in the right format acceptable for ECAM. This includes, but isn't limited to, cases such as inconsistent time-stamps for the trends (e.g., each trend has its own time-stamp), data with holes (e.g., some time-stamps have data and others are missing data), each point in the BAS is trended and exported into an individual .csv or .txt file, the time-stamp is unrecognizable by ECAM, etc. After reading through this user guide, the user should be able to pre-process all data files and be ready to use this data in ECAM to improve their building operational efficiency.

99 GENERAL AND MISCELLANEOUS↗