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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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At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

Baseline Optimization for the Measurement of CP Violation, Mass Hierarchy, and $\theta_{23}$ Octant in a Long-Baseline Neutrino Oscillation Experiment

Next-generation long-baseline electron neutrino appearance experiments will seek to discover C P violation, determine the mass hierarchy and resolve the θ 23 octant. In light of the recent precision measurements of θ 13 , we consider the sensitivity of these measurements in a study to determine the optimal baseline, including practical considerations regarding beam and detector performance. We conclude that a detector at a baseline of at least 1000 km in a wide-band muon neutrino beam is the optimal configuration.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2015

Baseline and Target Values for PV Forecasts: Toward Improved Solar Power Forecasting

Accurate solar power forecasting allows utilities to get the most out of the solar resources on their systems. To truly measure the improvements that any new solar forecasting methods can provide, it is important to first develop (or determine) baseline and target solar forecasting at different spatial and temporal scales. This paper aims to develop baseline and target values for solar forecasting metrics. These were informed by close collaboration with utility and independent system operator partners. The baseline values are established based on state-of-the-art numerical weather prediction models and persistence models. The target values are determined based on the reduction in the amount of reserves that must be held to accommodate the uncertainty of solar power output.

14 SOLAR ENERGY↗
DOE OSTI2022

A cosine-based correlation information entropy approach for building automatic fault detection baseline construction

Building automatic fault detection and diagnosis (AFDD) technologies have shown great potential for energy savings. To enable AFDD, a baseline depicting the normal operation mode is needed to detect whether the building operation deviates from normality. Existing research using physics-based knowledge and models for AFDD has mainly taken a trial-and-error approach to determine if a given baseline is sufficient via empirical experiments. A mechanism to support decisions such as how many samples and what samples should be included in the baseline is currently lacking. In this study, a data-driven method for AFDD baseline construction based on information entropy is developed. The entropy is derived based on cosine similarity among typical building automation system measurements in conjunction with outdoor weather information. The performance of the proposed method is evaluated using real building data. Evaluation results indicate that the fault detection strategy adopting the proposed method has similar or better accuracy in detecting faults compared to the same fault detection strategy using the baseline construction method from the literature. Additionally, the use of entropy enables the proposed method to automatically construct and assess the baseline consisting of information-rich samples.

42 ENGINEERING↗
DOE OSTI2018

New light Higgs boson and short-baseline neutrino anomalies

Here, the low-energy excesses observed by the MiniBooNE experiment have, to date, defied a convincing explanation under the standard model even with accommodation for nonzero neutrino mass. In this paper we explore a new oscillation mechanism to explain these anomalies, invoking a light neutrinophilic Higgs boson, conceived to induce a low Dirac neutrino mass in accord with experimental limits. Beam neutrinos forward scattering off of a locally overdense relic neutrino background give rise to a novel matter effect with an energy-specific resonance. An enhanced oscillation around this resonance peak produces flavor transitions which are highly consistent with the MiniBooNE neutrino- and antineutrino-mode data sets. The model provides substantially improved χ2 values beyond either the no-oscillation hypothesis or the more commonly explored 3+1 sterile neutrino hypothesis. This mechanism would introduce distinctive signatures at each baseline in the upcoming short-baseline neutrino program at Fermilab, presenting opportunities for further exploration.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2015

Future long-baseline neutrino oscillations: View from North America

In late 2012 the US Department of Energy gave approval for the first phase of the Long-Baseline Neutrino Experiment (LBNE) that will conduct a broad scientific program including neutrino oscillations, neutrino scattering physics, search for baryon violation, supernova burst neutrinos and other related astrophysical phenomena. The project is now being reformulated as an international facility hosted by the United States. The facility will consist of an intense neutrino beam produced at Fermi National Accelerator Laboratory (Fermilab), a highly capable set of neutrino detectors on the Fermilab campus, and a large underground liquid argon time projection chamber at Sanford Underground Research Facility (SURF) in South Dakota 1300 km from Fermilab. With an intense beam and massive far detector, the experimental program at the facility will make detailed studies of neutrino oscillations, including measurements of the neutrino mass hierarchy and Charge-Parity symmetry violation, by measuring neutrino and anti-neutrino mixing separately. At the near site, the high-statistics neutrino scattering data will allow for many cross section measurements and precision tests of the Standard Model. This presentation will describe the configuration developed by the LBNE collaboration, the broad physics program, and the status of the formation of the international facility.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Performance and Durability of Pure-Water-Fed Anion Exchange Membrane Electrolyzers Using Baseline Materials and Operation

Water electrolysis powered by renewable electricity produces green hydrogen and oxygen gas, which can be used for energy, fertilizer, and industrial applications and thus displace fossil fuels. Pure-water anion-exchange-membrane (AEM) electrolyzers in principle offer the advantages of commercialized proton-exchange-membrane systems (high current density, low cross over, output gas compression, etc.) while enabling the use of less-expensive steel components and nonprecious metal catalysts. AEM electrolyzer research and development, however, has been limited by the lack of broadly accessible materials that provide consistent cell performance, making it difficult to compare results across studies. Further, even when the same materials are used, different pretreatments and electrochemical analysis techniques can produce different results. Here, we report an AEM electrolyzer comprising commercially available catalysts, membrane, ionomer, and gas-diffusion layers operating near 1.9 V at 1 A cm –2 in pure water. After the initial break in, the performance degraded by 0.67 mV h –1 at 0.5 A cm –2 at 55 °C. We detail the key preparation, assembly, and operation techniques employed and show further performance improvements using advanced materials as a proof-of-concept for future AEM-electrolyzer development. Here, the data thus provide an easily reproducible and comparatively high-performance baseline that can be used by other laboratories to calibrate the performance of improved cell components, nonprecious metal oxygen evolution, and hydrogen evolution catalysts and learn how to mitigate degradation pathways.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

Long-Baseline Neutrino Facility (LBNF) and Deep Underground Neutrino Experiment (DUNE): Conceptual Design Report. Volume 3: Long-Baseline Neutrino Facility for DUNE

This volume of the LBNF/DUNE Conceptual Design Report covers the Long-Baseline Neutrino Facility for DUNE and describes the LBNF Project, which includes design and construction of the beamline at Fermilab, the conventional facilities at both Fermilab and SURF, and the cryostat and cryogenics infrastructure required for the DUNE far detector.

43 PARTICLE ACCELERATORS↗
DOE OSTI2015

Fusion power production in International Thermonuclear Experimental Reactor baseline H-mode scenarios

Self-consistent simulations of 15 MA ITER H-mode DT scenarios, from ramp-up through flat-top, are carried out. Electron and ion temperatures, toroidal angular frequency, and currents are evolved, in simulations carried out using the predictive TRANSPort and integrated modeling code starting with initial profiles and equilibria obtained from tokamak simulation code studies. Studies are carried out examining the dependence and sensitivity of fusion power production on electron density, argon impurity concentration, choice of radio frequency heating, pedestal temperature without and with E × B flow shear effects included, and the degree of plasma rotation. The goal of these whole-device ITER simulations is to identify dependencies that might impact ITER fusion performance.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Development of new baseline models for U.S. medium office buildings based on commercial buildings energy consumption survey data

Building energy estimation for the building sector under various scenarios are needed for building energy regulation and policy making. This often starts with representative baselines (either empirical baseline or modeled baseline). Commercial Buildings Energy Consumption Survey (CBECS) data is a widely used empirical baseline for U.S. commercial buildings, but none of the existing baseline model are developed to represent the CBECS data. This paper aims to develop new baseline models for the U.S. medium office buildings, which can produce modeled baselines consistent with the CBECS data. Here, we introduced the methodology to create baseline models and the criteria to evaluate the performance of baseline models. The methodology consists of three phases: (1) identification of model inputs, (2) model calibration, and (3) model validation with uncertainty analysis. The evaluation index is the coefficient of variation of the root-mean-square deviation (CV(RMSD)) of site energy use intensities (EUIs) between the modeled baseline and empirical baseline. Then 30 new baseline models for two vintages (pre- and post-1980) and 15 climate zones were created. The evaluation shows that the CV(RMSD) is lower than 0.05 for the modeled baselines produced by the new baseline models. As a comparison, the CV(RMSD) is higher than 0.1 for the existing modeled baselines generated by DOE Commercial Reference Building Models. Further analysis shows that the new baseline models are able to capture the uncertainties of the representative features of existing buildings.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Life-Cycle Baseline Customization for the Formerly Utilized Sites Remedial Action Program - 20304

One of the responsibilities of the federal government is to estimate sound and defensible life-cycle baseline costs for use in federal budget estimates and to meet federal financial reporting requirements. To accomplish this, the US Department of Energy (DOE) Office of Legacy Management (LM) and the US Army Corps of Engineers (USACE) have partnered together to ensure that the liabilities documented in each Formerly Utilized Sites Remedial Action Program (FUSRAP) site's life-cycle baseline are specifically tailored. FUSRAP was created in the mid-1970's to clean up radiological contamination resulting from the early development of nuclear weapons. DOE was responsible for FUSRAP until October 1997, when Congress transferred the administration and execution of FUSRAP site cleanups to USACE. By 1997, DOE had completed the cleanup of 25 of the 46 sites that were active within the program and had begun cleanup at 13 additional sites. USACE was assigned responsibility for the cleanup of the 21 remaining FUSRAP sites, and at 8 additional sites that had since been referred for cleanup. The LM mission for the FUSRAP sites is to perform long-term surveillance and maintenance (LTS and M). Currently, LM provides long-term stewardship for 34 completed FUSRAP sites. Another 20 sites are under active remediation by USACE. Within the last 5 years, USACE has completed the cleanup at five FUSRAP sites and the LTS and M responsibility has been transferred to LM. By 2029, USACE will compete remediation at eight additional sites and LTS and M for those sites will transfer to LM. Because responsibilities for the FUSRAP sites transfer between USACE and LM upon completion of remedial actions, both agencies maintain life-cycle baselines for different stages of the project and both must have a strong understanding of the needs and requirements for each site. This understanding ensures that the life-cycle baselines form a complete and accurate picture of what is required for the site and for the FUSRAP program. LM focuses on several things when customizing the life-cycle baseline estimates for the FUSRAP sites, including (1) Understanding the unique requirements for each site. By reviewing site-specific documents prepared by USACE, such as Feasibility Studies and Records of Decision, and partnering with USACE to gain additional insight about site conditions and requirements for stewardship, as well as potential risks, LM can better develop the life-cycle baselines. (2) Developing site-specific labor breakdowns. This ensures the required labor mix is baselined for specific activities by comparing the labor mix required to perform activities at (a) other LM-managed FUSRAP sites and (b) non-FUSRAP LM sites and (c) by USACE at active FUSRAP sites. (3) Taking a tiered approach to life-cycle baseline planning. Estimates for sites transferring to LM in the near term (5 years) are more definitive than for sites transferring in the out-year period. Remedial actions at the near-term sites are at or near completion, providing LM a strong understanding of the LTS and M requirements and remaining liabilities. This in turn allows for site-specific customization of the baseline. (4) Using a robust risk management approach to ensure that liabilities specific to each site are identified, evaluated by probability and severity, and documented in relation to the impact to cost or schedule. To ensure the most accuracy within all the baselines, the FUSRAP life-cycle baselines are updated as needed to support program, project, and contract management needs. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2022

Individualized empirical baselines for evaluating the energy performance of existing buildings

The evaluation of building energy performance requires a baseline for comparison. Common empirical baselines are usually used for existing buildings since they are fast and convenient. However, the same type of building at the same location will receive the same baseline despite their difference in usage. Individualized baselines by creating building energy models are possible solutions, but it is labor intensive and time-consuming. To fill the gap, this study is to develop individualized empirical baselines for existing buildings in a fast way. First, common empirical baselines are created based on survey data. Then, to get training samples, building energy models for large-scale existing buildings are created and simulated. So finally, based on simulation results, mathematical models to get individualized empirical baselines in a fast way are created. U.S. medium office buildings were used as an example to demonstrate the method. We developed 30 mathematical models for medium office buildings in two vintages (constructed before 1980 and after 1980) and 15 climate zones. The mean absolute percentage errors (MAPE) between the individualized empirical baselines and the modeled baselines for those 30 mathematical models are all lower than 5.5%. An engineer can obtain the individualized empirical baseline for an existing building in a few seconds by using the open-source tool we developed.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Efficient population representation with more genetic markers increases performance of a steelhead (Oncorhynchus mykiss) genetic stock identification baseline

Abstract Genetic stock identification (GSI) is an important fisheries management tool to identify the origin of fish harvested in mixed stock fisheries. Periodic updates of genetic baselines can improve performance via the addition of unsampled or under‐sampled populations and the inclusion of more informative markers. We used a combination of baselines to evaluate how population representation, marker number, and marker type affected the performance and accuracy of genetic stock assignments (self‐assignment, bias, and holdout group tests) for steelhead ( Oncorhynchus mykiss ) in the Snake River basin. First, we compared the performance of an existing genetic baseline with a newly developed one which had a reduced number of individuals from more populations using the same set of markers. Self‐assignment rates were significantly higher ( p < 0.001; +5.4%) for the older, larger baseline, bias did not differ significantly between the two, but there was a significant improvement in performance for the new baseline in holdout results ( p < 0.001; mean increase of 25.0%). Second, we compared the performance of the new baseline with increased numbers of genetic markers (~2x increase of single‐nucleotide polymorphisms; SNPs) for the same set of baseline individuals. In this comparison, results produced significantly higher rates of self‐assignment ( p < 0.001; +9.7%) but neither bias nor leave‐one‐out were significantly affected. Third, we compared 334 SNPs versus opportunistically discovered microhaplotypes from the same amplicons for the new baseline, and showed the latter produced significantly higher rates of self‐assignment ( p < 0.01; +2.6%), similar bias, but slightly lower holdout performance (−0.1%). Combined, we show the performance of genetic baselines can be improved via representative and efficient sampling, that increased marker number consistently improved performance over the original baseline, and that opportunistic discovery of microhaplotypes can lead to small improvements in GSI performance.

Hargrove, John S.↗
DOE OSTI2020

Energy Intensity Baselining and Tracking Guidance

Each company joining the U.S. Department of Energy’s (DOE’s) Better Buildings, Better Plants Program (Better Plants) commits to establishing an energy consumption and energy intensity (EI) baseline and to tracking its energy performance over a 10-year period against that baseline. The baseline must reflect a company’s energy consumption over a 12-month period, covering all its U.S.-based operations. Energy consumption is calculated by fuel type in terms of primary energy (also known as source energy). EI is broadly defined as the amount of energy consumed per unit of output produced. For this guidance document and for the program, the term energy performance represents an evaluation of a facility’s capacity to use energy efficiently. Metrics used to assess a facility’s energy performance can include EI, energy consumption, improvements in EI, etc. Establishing an energy baseline and tracking system is a critical first step in effectively managing energy use. Developing a baseline can help a company understand energy use within the corporation and give it a point of comparison to evaluate future efforts to improve energy performance. It can also support efforts to validate a company’s energy management activities, improve comparative analyses when using benchmarks, and help in predicting future energy needs. In addition, a company that normalizes its performance data can determine highly defensible measures of energy savings generated through implemented energy efficiency projects. Establishing a baseline and tracking energy performance is also a requirement for ISO 50001 certification. Although basic energy data can be collected through utility bills, most manufacturers will have to perform additional analyses to develop accurate and robust energy baselines and tracking systems. Energy is consumed in many ways within the manufacturing sector and can come from multiple sources. Energy is sometimes generated and sold to other parties or captured and reused on-site. External events can exert a significant impact on a facility or company’s energy use independent of any purposeful efforts to improve energy efficiency. Operational changes, such as production shifts—which may be inevitable for some companies over the 10-year period covered by the program—can also make a big difference in energy use. Since Better Plants asks companies to account for all their U.S.-based operations, mergers, acquisitions, and divestitures can also have significant implications for a company’s energy metrics. This document aims to demystify the sometimes complex baselining process. It devotes special attention to the task of normalizing and adjusting energy consumption to account for external factors, such as weather and production changes. A key recommendation is that companies use regression analysis to normalize their energy consumption data whenever possible. Regression analysis is a statistical technique that estimates the dependence of a variable (i.e., energy use in the context of Better Plants) on one or more independent variables such as ambient temperature, while controlling for the influence of other variables at the same time. A properly developed regression analysis can provide a reliable estimate of energy savings resulting from energy improvement strategies and projects by accounting for the effects of variables such as annual production levels and weather. DOE has developed a companion Energy Performance Indicator software tool (EnPI) to simplify the baselining process. This tool can run regression models, calculate changes in EI at the facility level, and automatically compile facility-level data into a corporate-wide metric. Note that although the relevant equations used to calculate EI are provided in this document, the EnPI tool will automatically perform most calculations for the user. Additionally, Better Plants Partners (Partners) can call on their Technical Account Manager (TAM) to help them establish a baseline and assist with the necessary calculations to track progress.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Are System Baselines within OT Environments Feasible?

Critical infrastructure stakeholders need to baseline their systems to understand expected protocol communications.Baseline behaviors may vary based on operational context.Expected operations during a maintenance window, for example, may be different from normal operations.Furthermore, constructing system baselines for Industrial Control Systems (ICS) is difficult and time-consuming.ICS processes generate artifacts expressed across heterogeneous data sources such as network and device logs. There needs to be a corpus of data in order to develop and compare methods that evaluate the feasibility, performance, and generality of approaches to construct baselines for ICS events. Standalone repositories of network packet captures are insufficient to develop methods to classify or recognize operational events expressed across multiple data sources. Moreover, static data corpora do not enable researchers to compare the impact of changing the underlying system for which a baseline is being constructed and this limits the ability to evaluate the performance of system baselines given system changes (e.g. patches, configuration, maintenance events). In order to address these limitations within the community, this talk intends to promote discussion about the state of the practice of constructing baselines. In this manner, we can continue to understand requirements within industry that are not being met by current approaches to baseline construction. This talk builds on two previous talks on the topic of system baselines for OT environments. First, Weaver co-presented at the RSA Conference ICS Sandbox with Dan Gunter. The talk confirmed the need within industry to construct baselines across multiple types of data sources relative to the semantics of specific business processes. Second, Weaver presented at IEEE Security and Privacy Workshop on Language-Theoretic Security.

02 PETROLEUM↗
DOE OSTI2022

Micro Baselines for Operational Technology Environments

Critical infrastructure stakeholders need to baseline their networks to understand expected communications. Top-down approaches to baselining rely on observables that are generally available but lack properties upon which traditional statistical tools depend. We propose to construct micro-baselines: signatures within operational networks based on observables associated with specific events. Such observables are informed by precursor analysis reports of historical cyber attacks on operational environments developed by Cybersecurity for Operational Technology Environments (CyOTE). Baseline measurements depend upon context beyond the cyber domain. An energy plant's baseline running in the summer may statistically differ from a similar facility in a colder region. Domain knowledge must be integrated to apply general micro-baselining algorithms to a facility-specific context. Therefore, we propose to explore the feasibility of transferring micro baselining algorithms across different facilities. Facilities that implement the same processes in different geographic locations will be compared relative to observable measurements used in micro-baselining for comparable events. One evaluation approach would condition or augment dynamic observables measured within a facility network testbed with additional observables derived from geographic context or infrastructure dependencies such as those provided by the All-Hazards Analysis tool.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Engineering Analysis Baseline Model Requirements

The purpose of this document is to set requirements for the development, documentation, implementation, and maintenance of engineering analysis baseline models used by the Advanced Engineering and Analysis group to model and simulate systems. The intended audience of this document is the Engineering Technology and Design division Advanced Engineering and Analysis group—in particular the baseline model owners and users—and the Group Leaders and members of the Systems Engineering groups. Section 1 presents a discussion of general concepts related to engineering analysis models and baseline models, including definitions of common terms used in this requirements document. It also presents the purpose and intentions of creating and using baseline models and exposes some underlying assumptions about what baseline models are supposed to be. Section 2 presents requirements on the general categories of: the Advanced Engineering and Analysis Group Leader and the baseline model owner; parts, materials, and load cases; the process of generating and using the model; and how the baseline model will be stored, maintained, and documented. This document presents requirements on the baseline model as well as some aspects of the development process and the people responsible for the development; it does not address how the results of simulations utilizing these models will be used to make assessments

42 ENGINEERING↗