Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “factor analysis”

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 1,225 records · Page 68

Irradiation Experiment Design Parameters for NBSR Fuel Conversion

It has been proposed to convert the National Institute of Standards and Technology research reactor, known as the NBSR, from highly-enriched uranium (HEU) fuel to low-enriched uranium (LEU) fuel. The motivation to convert the NBSR to LEU fuel is to reduce the risk of proliferation of special nuclear material. This report is a compilation of relevant information from recent studies related to the proposed conversion using a metal alloy of LEU with 10 w/o molybdenum. The objective is to inform the design of irradiation experiments that are being planned. This report provides relevant nominal dimensions of the proposed LEU fuel element, and average and maximum power densities and fission densities. The latter profiles are given for different plates to show the variation throughout the core. A summary of the methodology to obtain these results is presented. Fuel element tolerance assumptions and hot channel factors used in the safety analysis are also given.

42 ENGINEERING↗

Production of Biocrude in an Advanced Photobioreactor-Based Biorefinery

Algenol Biotech, the National Renewable Energy Laboratory (NREL), Georgia Institute of Technology, Arizona State University, and Reliance Industries formed a team to advance the state of the art in algal biomass production and downstream processing technologies, with the end goal of a sustainable, economically viable biofuel intermediate (BFI, biocrude) product. The project included examination of high value co-product production as a market entry strategy and for enhancing the economics of a biorefinery for BFI production. The project targeted innovations in biology, operations, and engineering. The goals of the project were: BFI productivity greater than 4,000 gal-BFI/acre-yr on an annualized basis; energy efficient innovations in downstream operations resulting in an energy expenditure less than 10% of the BFI energy content and a carbon footprint reduction of more than 60% compared to fossil alternatives; and a comprehensive Techno-Economic Analysis (TEA) that identifies limiting factors for commercial viability of a photobioreactor (PBR)-based biofuel product. The project achieved the overall objectives. Strain development efforts led to the identification of a strain (Cyanobacterium sp. AB1166) that, relative to the previous best strain (Cyanobacterium sp. AB1), exhibited a ~10% increase in productivity under commercially-relevant cultivation conditions and also resulted in cultures with a >50% reduction in viscosity such that harvesting efficiency was improved; these results represent achievement of key project milestones. Progress was also made at NREL in altering the biochemical composition of algal biomass to improve the yield of BFI produced via HTL. These strain enhancements coupled with improved outdoor cultivation practices, including semi-continuous operation, increased areal biomass productivity by nearly 80% over the established baseline productivity. The annualized productivity achieved (26.8 g/m2-d), paired with HTL conversion yields realized at NREL and RIL (38% ± 2% BFI), translates to 4,100 gal-BFI/acre-yr, exceeding the FY20 BETO goal of 3,700 gal-BFI/acre-yr. Significant progress was also demonstrated in large scale PBR-based production system design, operability, and cost reduction. A 24,000-L production module comprised of 240 interlinked PBRs was constructed and successfully operated outdoors for over one year in Fort Myers, Florida. Aided by a state-of-the-art productivity model, the productivities achieved convincingly demonstrated scalability of laboratory results determined at the mL to L scale to large-scale outdoor operations exceeding 20,000 L. The system was used to cultivate Arthrospira platensis (Spirulina), an industrially-relevant cyanobacterium and source for phycocyanin, an approved blue food colorant that Algenol is developing as a risk reduction strategy for future biofuel projects and as a potential business opportunity. A key project milestone to develop phycocyanin extraction and purification technologies was achieved ahead of schedule, and product samples received positive feedback from potential customers. The production and downstream operations data generated in this project were used to conduct and refine Techno-Economic and Life Cycle Assessments to provide research guidance for reducing the costs and environmental footprint of algal biofuel and co-product manufacturing plants. Several CO 2 supply scenarios for an algal biorefinery were identified as being capable of providing a large (>60%) reduction in carbon footprint in comparison to gasoline. The TEA assessments incorporated detailed comparisons of PBR versus open pond production systems, yielding a 3-fold higher areal productivity for PBRs and suggesting overall production cost parity for the two systems. The progress in this ABY2 project addressed many of the the barriers identified for the Advanced Algal Systems R&D Program and are directly relevant to achieving the established BETO goals associated with large scale biofuel production and cost reduction.

09 BIOMASS FUELS↗

Business Models for Coal Plant Decommissioning

Aging coal-fired power plants are retiring across the United States. Researchers at Pacific Northwest National Laboratory studied coal-fired power plant decommissioning business models to support program development for the Department of Energy’s Office of Energy Efficiency & Renewable Energy (EERE) to engage with communities affected by power plant retirement processes. Evaluating and reducing the impact on coal-dependent communities from phasing out coal production is a crucial piece of nationwide economic development and community-directed engagement in the clean energy future. This report describes the steps in the typical coal-fired power plant decommissioning process, including analysis of the following key factors: Drivers including policy and regulations, competition with other fuels, and corporate responsibility goals; Types of coal plant decommissioning including plant retirement without full decommissioning, repurposing with fuel switch, redeveloping to utilize existing transmission, and decommissioning and repurposing with other commercial activities; and, Costs of coal plant decommissioning, including variations across regulated and deregulated markets and the funding resources to support decommissioning activities. The details described in this report relied heavily on the availability of local news reports and communications regarding plant retirements, as the researchers identified a lack of formal literature surrounding business models for coal plant decommissioning and a need for a more robust source material collection. In addition, a lack of oversight entities responsible for decommissioning processes may have led to this shortfall of information. Future research regarding coal plant decommissioning can include quantitative studies on power plant retirement drivers, procedures, and costs, qualitative assessments on affects decommissioning has on surrounding communities, investors, and other stakeholders, and identifying best practices to engage community stakeholders in the decommissioning process.

01 COAL, LIGNITE, AND PEAT↗

Tracking the Sun: Pricing and Design Trends for Distributed Photovoltaic Systems in the United States, 2024 Edition [Slides]

Berkeley Lab’s annual Tracking the Sun report describes trends among grid-connected, distributed solar photovoltaic (PV) and paired PV+storage systems in the United States. For the purpose of this report, distributed solar includes residential systems, roof-mounted non-residential systems, and ground-mounted systems up to 5 MW-AC. Ground-mounted systems larger than 5 MW-AC are covered in Berkeley Lab’s companion annual report, Utility-Scale Solar. The latest edition of the report is based on 3.7 million systems installed through year-end 2023, representing close to 80% of systems installed to date. The report describes and discusses key trends related to: -Project characteristics, including system size, module efficiencies, roof-coverage ratios, prevalence of paired PV with storage, use of module-level power electronics, third-party ownership, mounting configurations, panel orientation, and customer segmentation -Median installed-price trends, both nationally and by state -Variability in pricing according to system size, state, installer, equipment type, and other factors, relying on both descriptive analysis and a multi-variate regression to estimate the effects of key pricing drivers for residential systems installed in 2023.

14 SOLAR ENERGY↗

Retention of LDR Inorganics in Solidified/Immobilized Waste

This report provides a summary of the laboratory data and statistical analysis used to calculate retention factors in solidified/stabilized Hanford tank waste for the 13 LDR inorganic species associated with Hanford tank waste (SRNL-STI-2020-00228). The data presented is a summary of the results of research performed to build a correlation between the untreated waste concentration and the TCLP response of a solidified/stabilized waste form. This report establishes the efficacy of two treatment technologies found in 40 CFR 268.42, CHRED (chemical reduction) and STABL (stabilization), that are key to the Sample-and-Send strategy.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Resilience Lessons From the Southeast United States Woody Pellet Supply Chain Response to the COVID-19 Pandemic†

The Coronavirus Disease 2019 (COVID-19) instigated a pandemic that impacted economies, employment, and shipping worldwide. This paper reviews how one international supply chain performed and identifies lessons that may be helpful to improve future resilience. Economic and employment data through November 2020 are used to review the effects of COVID-19 on operations of the bioenergy supply chain in the southeastern United States (SE United States) that utilizes wood fiber to fabricate pellets. Conditions associated with the production of pellets in the SE United States changed with the outbreak of COVID-19. Federal and state government programs and classification of workers in this sector as “essential” during the pandemic helped maintain the woody pellet supply chain and other industries during a period of general shut down in 2020. The availability of personal protective equipment, long-term supply contracts, and established safety cultures are among the factors that enhance supply chain resilience while limited availability of skilled workers, inadequate stakeholder engagement, and dependence on external policies are among factors that reduce resilience. The analysis concludes with recommendations for the SE pellet supply chain, and other biomass supply chains, to improve their resilience to future disturbances. When best practices are implemented, SE United States biomass offers opportunities to contribute to post-pandemic economic recovery while incentivizing better forest resource management.

09 BIOMASS FUELS↗

From Mouse to Human: Cellular Morphometric Subtype Learned From Mouse Mammary Tumors Provides Prognostic Value in Human Breast Cancer

Mouse models of cancer provide a powerful tool for investigating all aspects of cancer biology. In this study, we used our recently developed machine learning approach to identify the cellular morphometric biomarkers (CMB) from digital images of hematoxylin and eosin (H&E) micrographs of orthotopic Trp53-null mammary tumors (n = 154) and to discover the corresponding cellular morphometric subtypes (CMS). Of the two CMS identified, CMS-2 was significantly associated with shorter survival (p = 0.0084). We then evaluated the learned CMB and corresponding CMS model in MMTV-Erbb2 transgenic mouse mammary tumors (n = 53) in which CMS-2 was significantly correlated with the presence of metastasis (p = 0.004). We next evaluated the mouse CMB and CMS model on The Cancer Genome Atlas breast cancer (TCGA-BRCA) cohort (n = 1017). Kaplan–Meier analysis showed significantly shorter overall survival (OS) of CMS-2 patients compared to CMS-1 patients (p = 0.024) and added significant prognostic value in multi-variable analysis of clinical and molecular factors, namely, age, pathological stage, and PAM50 molecular subtype. Thus, application of CMS to digital images of routine workflow H&E preparations can provide unbiased biological stratification to inform patient care.

60 APPLIED LIFE SCIENCES↗

Neural Network Approaches for Mobile Spectroscopic Gamma-Ray Source Detection

Artificial neural networks (ANNs) for performing spectroscopic gamma-ray source identification have been previously introduced, primarily for applications in controlled laboratory settings. To understand the utility of these methods in scenarios and environments more relevant to nuclear safety and security, this work examines the use of ANNs for mobile detection, which involves highly variable gamma-ray background, low signal-to-noise ratio measurements, and low false alarm rates. Simulated data from a 2” × 4” × 16” NaI(Tl) detector are used in this work for demonstrating these concepts, and the minimum detectable activity (MDA) is used as a performance metric in assessing model performance.In addition to examining simultaneous detection and identification, binary spectral anomaly detection using autoencoders is introduced in this work, and benchmarked using detection methods based on Non-negative Matrix Factorization (NMF) and Principal Component Analysis (PCA). On average, the autoencoder provides a 12% and 23% improvement over NMF- and PCA-based detection methods, respectively. Additionally, source identification using ANNs is extended to leverage temporal dynamics by means of recurrent neural networks, and these time-dependent models outperform their time-independent counterparts by 17% for the analysis examined here. The paper concludes with a discussion on tradeoffs between the ANN-based approaches and the benchmark methods examined here.

Bilton, Kyle J. (ORCID:0000000184553689)↗

metabCombiner 2.0: Disparate Multi-Dataset Feature Alignment for LC-MS Metabolomics

Liquid chromatography–high-resolution mass spectrometry (LC-HRMS), as applied to untargeted metabolomics, enables the simultaneous detection of thousands of small molecules, generating complex datasets. Alignment is a crucial step in data processing pipelines, whereby LC-MS features derived from common ions are assembled into a unified matrix amenable to further analysis. Variability in the analytical factors that influence liquid chromatography separations complicates data alignment. This is prominent when aligning data acquired in different laboratories, generated using non-identical instruments, or between batches from large-scale studies. Previously, we developed metabCombiner for aligning disparately acquired LC-MS metabolomics datasets. Here, we report significant upgrades to metabCombiner that enable the stepwise alignment of multiple untargeted LC-MS metabolomics datasets, facilitating inter-laboratory reproducibility studies. To accomplish this, a “primary” feature list is used as a template for matching compounds in “target” feature lists. We demonstrate this workflow by aligning four lipidomics datasets from core laboratories generated using each institution’s in-house LC-MS instrumentation and methods. We also introduce batchCombine, an application of the metabCombiner framework for aligning experiments composed of multiple batches. metabCombiner is available as an R package on Github and Bioconductor, along with a new online version implemented as an R Shiny App.

97 MATHEMATICS AND COMPUTING↗

Chemical identification of new particle formation and growth precursors through positive matrix factorization of ambient ion measurements

Abstract. In the lower troposphere, rapid collisions between ions and trace gases result in the transfer of positive charge to the highest proton affinity species and negative charge to the lowest proton affinity species. Measurements of the chemical composition of ambient ions thus provide direct insight into the most acidic and basic trace gases and their ion–molecule clusters – compounds thought to be important for new particle formation and growth. We deployed an atmospheric pressure interface time-of-flight mass spectrometer (APi-ToF) to measure ambient ion chemical composition during the 2016 Holistic Interactions of Shallow Clouds, Aerosols, and Land Ecosystems (HI-SCALE) campaign at the United States Department of Energy Atmospheric Radiation Measurement facility in the Southern Great Plains (SGP), an agricultural region. Cations and anions were measured for alternating periods of ∼ 24 h over 1 month. We use binned positive matrix factorization (binPMF) and generalized Kendrick analysis (GKA) to obtain information about the chemical formulas and temporal variation in ionic composition without the need for averaging over a long timescale or a priori high-resolution peak fitting. Negative ions consist of strong acids including sulfuric and nitric acid, organosulfates, and clusters of NO3- with highly oxygenated organic molecules (HOMs) derived from monoterpene (MT) and sesquiterpene (SQT) oxidation. Organonitrates derived from SQTs account for most of the HOM signal. Combined with the diel profiles and back trajectory analysis, these results suggest that NO3 radical chemistry is active at this site. SQT oxidation products likely contribute to particle growth at the SGP site. The positive ions consist of bases including alkyl pyridines and amines and a series of high-mass species. Nearly all the positive ions contained only one nitrogen atom and in general support ammonia and amines as being the dominant bases that could participate in new particle formation. Overall, this work demonstrates how APi-ToF measurements combined with binPMF analysis can provide insight into the temporal evolution of compounds important for new particle formation and growth.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Extracting the \(\Lambda \) Polarizing Fragmentation Function from Belle e + e − Data within the TMD Formalism

Data from the Belle Collaboration for associated production (with a light unpolarized hadron) and single-inclusive production of transversely polarized Λ-hyperons in e + e − annihilation processes allowed to extract within a TMD approach, for the first time, the Λ polarizing fragmentation function. Recent theoretical developments on the computation of cross sections for single-inclusive hadron production in e + e − annihilation processes, within a Soft Collinear Effective Theory approach, combined with the CSS formalism for the double-hadron production case, can be used to perform a renewed analysis, adopting a full TMD factorization scheme. Preliminary results and a comparison between the two analyses are presented.

CSS evolution equations↗

Parametric analysis of ATT configurations.

This paper describes the results of a Lockheed parametric analysis of the performance, environmental factors, and economics of an advanced commercial transport envisioned for operation in the post-1985 time period. The design parameters investigated include cruise speeds from Mach 0.85 to Mach 1.0, passenger capacities from 200 to 500, ranges of 2800 to 5500 nautical miles, and noise level criteria. NASA high performance configurations and alternate configurations are operated over domestic and international route structures. Indirect and direct costs and return on investment are determined for approximately 40 candidate aircraft configurations. The candidate configurations are input to an aircraft sizing and performance program which includes a subroutine for noise criteria. Comparisons are made between preferred configurations on the basis of maximum return on investment as a function of payload, range, and design cruise speed.

Lange, R. H.↗

Analysis of transient heat flow to thick-walled plates and cylinders

A methodology is described for the analysis of a transient temperature measurement made in a flat or curved plate subjected to convective heat transfer, such that the surface heat flux, the hot-gas temperture, and the gas heat transfer coefficient can be determined. It is shown that if the transient temperature measurement is made at a particular point located nearly midway in the thickness of the plate there is an important simplification in the data analysis process, in that the factor relating the surface heat flux to the measured rate of rise of temperature becomes invariant for a Fourier Number above 0.60 and for all values of the Biot Number. Parameters are derived, tabulated, and plotted which enable straightforward determination of the surface heat flux, the hot-gas temperature, of the plate, the rate of rise of temperature, the plate thickness and curvature, and the mean thermal properties of the plate material at the test temperature.

Powell, W. B.↗

Agriculture, forestry, range resources

In the area of crop specie identification, it has been found that temporal data analysis, preliminary stratification, and unequal probability analysis were several of the factors that contributed to high identification accuracies. Single data set accuracies on fields of greater than 80,000 sq m (20 acres) are in the 70- to 90-percent range; however, with the use of temporal data, accuracies of 95 percent have been reported. Identification accuracy drops off significantly on areas of less than 80,000 sq m (20 acres) as does measurement accuracy. Forest stratification into coniferous and deciduous areas has been accomplished to a 90- to 95-percent accuracy level. Using multistage sampling techniques, the timber volume of a national forest district has been estimated to a confidence level and standard deviation acceptable to the Forest Service at a very favorable cost-benefit time ratio. Range specie/plant community vegetation mapping has been accomplished at various levels of success (69- to 90-percent accuracy). However, several investigators have obtained encouraging initial results in range biomass (forage production) estimation and range readiness predictions. Soil association map correction and soil association mapping in new area appear to have been proven feasible on large areas; however, testing in a complex soil area should be undertaken.

Crea, W. J.↗

Ballistic intercept missions to Comet Encke

The optimum ballistic intercept of a spacecraft with the comet Encke is determined. The following factors are considered in the analysis: energy requirements, encounter conditions, targeting error, comet activity, spacecraft engineering requirements and restraints, communications, and scientific return of the mission. A baseline model is formulated which includes the basic elements necessary to estimate the scientific return for the different missions considered. Tradeoffs which have major impact on the cost and/or scientific return of a ballistic mission to comet Encke are identified and discussed. Recommendations are included.

Mumma, M.↗