Search NASA⌕ Search

SEARCH · Search NASA

Results for “Profiling optimization”

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 1,657 records · Page 92
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Rapid quantification of whole seed fatty acid amount, composition, and shape phenotypes from diverse oilseed species with large differences in seed size

Seed oils are widely used in the food, biofuel, and industrial feedstock industries, with their utility and value determined by total oil content and fatty acid composition. Current high throughput seed oil analysis methods either lack accuracy in total fatty acid profiling or require extensive labor for lipid extraction prior to derivatization to fatty acid methyl esters (FAME) and quantification by gas chromatography (GC). Alternatively, direct whole seed FAME production methods have been developed for the very small seeds in the model species Arabidopsis thaliana but these have generally not been adapted to larger seeds of most oilseed crops. High-throughput direct whole seed FAME production methods were optimized for seeds up to 5 mg each utilizing acid-catalyzed esterification. For the oilseed species Camelina sativa, Thlaspi avernse (pennycress), Cuphea viscosissima, and Brassica napus (var. Canola), the total seed fatty acid content and composition from direct seed esterification to FAME matched that of lipid extract derivatization demonstrating the accuracy of the methods. In combination with seed phenotyping using GridFree, this approach enabled the development of a rapid pipeline for simultaneous seed weight, count, size/shape phenotyping, and oil analysis. For the larger and tougher seeds produced by Limnanthes alba (Meadowfoam) and Cannabis sativa L. (hemp) the whole seed acid-based method proved insufficient, and prior laborious homogenization of seeds was required. Therefore, a rapid one-tube bead homogenization and base catalyzed-esterification method was developed. Base-derived fatty acid esterification cannot derivatize free fatty acids leading to slightly lower total seed fatty acid than acid-catalyzed methods, however the seed oil content and fatty acid composition that is valuable for screening large numbers of samples in research populations was accurately measured. New rapid whole seed fatty acid esterification and phenotyping protocols were developed to accurately assess oilseed lipid content. These methods are particularly valuable in oilseed research, breeding, and engineering applications where efficient analysis of large numbers of samples and accurate oil fatty acid profiling is essential. While having been developed for current and emerging oilseed crops, these methods also provide a foundation from which protocols might be established for new and emerging crop species.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

Kelvin Probe Force Microscopy for High-Resolution Imaging of Hydrogen in Steel and Aluminum Alloys (Q3 Progress Report)

SRNL is working with Sandia NL, Pacific Northwest NL and Oak Ridge NL in the H-Mat consortium with the objective of developing materials with a higher resistance to hydrogen attack. Understanding the mechanism of hydrogen interactions in metal alloys is continually a topic of interest for applications which involve the long-term storage of hydrogen. Atomic hydrogen segregates to regions of extended defects, such as grain and phase boundaries, and can cause stress and premature cracking through a process known as hydrogen embrittlement. Advanced microstructural imaging techniques, with minimal sample preparation needs, that are capable of resolving hydrogen segregation at the nanometer scale is needed. Current imaging technologies to aid in understanding the effects of hydrogen in metals involve primarily fractography after mechanical testing. Hydrogen segregated at the surface and particularly at surface defect sites changes the local work function of the material. This can be measured by Kelvin Probe Force Microscopy, KPFM, a variant of atomic force microscopy (AFM). KPFM produces surface potential images and is capable of measuring the local change in work function of surfaces with very high spatial resolution. The spatial resolution of KPFM is optimally ~5 nm, yielding very high hydrogen concentration/microstructure coloration capabilities. By locating the presence of hydrogen and its relationship with extended defects, it may be possible to develop microstructures less susceptible to hydrogen embrittlement. The objective of this effort is to assess the utility of KPFM to determine the H 2 concentration profiles surrounding complex microstructural features in high strength steel and aluminum alloys subjected to high pressure hydrogen exposure.

08 HYDROGEN↗
DOE OSTI2019

Kelvin Probe Force Microscopy for High-Resolution Imaging of Hydrogen in Steel and Aluminum Alloys

SRNL is working with Sandia NL, Pacific Northwest NL and Oak Ridge NL in the H-Mat consortium with the objective of developing materials with a higher resistance to hydrogen attack. Understanding the mechanism of hydrogen interactions in metal alloys is continually a topic of interest for applications which involve the long-term storage of hydrogen. Atomic hydrogen segregates to regions of extended defects, such as grain and phase boundaries, and can cause stress and premature cracking through a process known as hydrogen embrittlement. Advanced microstructural imaging techniques, with minimal sample preparation needs, that are capable of resolving hydrogen segregation at the nanometer scale is needed. Current imaging technologies to aid in understanding the effects of hydrogen in metals involve primarily fractography after mechanical testing. Hydrogen segregated at the surface and particularly at surface defect sites changes the local work function of the material. This can be measured by Kelvin Probe Force Microscopy, KPFM, a variant of atomic force microscopy (AFM). KPFM produces surface potential images and is capable of measuring the local change in work function of surfaces with very high spatial resolution. The spatial resolution of KPFM is optimally ~5 nm, yielding very high hydrogen concentration/microstructure coloration capabilities. By locating the presence of hydrogen and its relationship with extended defects, it may be possible to develop microstructures less susceptible to hydrogen embrittlement. The objective of this effort is to assess the utility of KPFM to determine the H 2 concentration profiles surrounding complex microstructural features in high strength steel and aluminum alloys subjected to high pressure hydrogen exposure.

08 HYDROGEN↗
NASA NTRS1976

Advanced helium regulator for a fluorine propellant system

The space storable propulsion module is an advanced high performance (375 seconds Isp minimum) planetary spacecraft propulsion system with a mission life of 5-10 years. The propellants used are liquid fluorine and amine fuel. This application requires high pressure regulator accuracy to optimize propellant depletion characteristics. An advanced regulator concept was prepared which is compatible with both fuel and oxidizer and which features design concepts such as redundant bellows, all-metallic/ceramic construction, friction-free guidance of moving parts and gas damping. Computer simulation of the propulsion module performance over two mission profiles indicated satisfactory minimization of those propellant residual requirements imposed by regulator performance variables.

Wichmann, H.↗
NASA NTRS1984

Aging properties of Kodak type 101 emulsions

Aging tests for several batches of Kodak type 101 emulsion show that storage conditions significantly influence how well the film will maintain its sensitometric properties, with sensitivity and density increasing to a maximum during this period. Any further aging may result in higher fog levels and sensitivity loss. It is noted that storage in an environment free of photographically active compounds allows film property optimization, and that film batches with different sensitivities age differently. Emulsions with maximum 1700-A sensitivity are 2.5 times faster than those at the low end of the sensitivity scale. These sensitive emulsions exhibit significantly accelerated changes in aging properties. Their use in space applications requires careful consideration of time and temperature profiles, encouraging the use of less sensitive emulsions when the controllability of these factors is limited.

Dohne, B.↗
NASA NTRS2007

Center Director's Discretionary Fund 2005 Annual Report

The FY 2005 CDDF projects were selected from the following spaceport and range technology and science areas: fluid system technologies; spaceport structures and materials; command, control, and monitoring technologies; and biological sciences (including support for environmental stewardship). The FY 2005 CDDF research projects involved development of the following: a) Capacitance-based moisture sensors to optimize plant growth in reduced gravity; b) Commodity-free calibration methods; c) Application of atmospheric plasma glow discharge to alter the surface properties of polymers for improved electrostatic dissipation characteristics; d) A wipe-on, wipe-off chemical process to remove lead oxides found in paint; e) A robust metabolite profiling platform for better understanding the "law" of biological regulation; f) An explanation of the excavation processes that occur when a jet of gas impinges on a bed of sand; g) "Smart coatings" to detect and control corrosion at an early stage to prevent further corrosion h) A model that can produce a reliable diagnosis of the quality of a software product; i) The formulation of advanced materials to meet system safety needs to minimize electrostatic charges, flammability, and radiation exposure; j) A lab-based instrument that uses the electro-optic Pockels effect to make static electric fields visible; k) A passive volatile organic compound (VOC) cartridge to filter, identify, and quantify VOCs flowing into or emanating from plant flight experiments.

Nurge, Mark↗
NASA NTRSDate not supplied

NASA’s Evolving Ka-Band Network Capabilities to Meet Mission Demand

Space missions are increasingly demanding higher data rates to support the growth in information-intensive mission operations. This growth is reflected in planned and operational missions from low Earth orbit, such as the upcoming NASA-Indian Space Research Organization (ISRO) Synthetic Aperture Radar (NISAR) and Plankton, Aerosol, Cloud and Ocean Ecosystem (PACE) missions, to the future Artemis lunar campaign, and the recently launched James Webb Space Telescope (JWST) orbiting at the Sun-Earth L2 Lagrange point. JWST was the first L2 mission to be defined as a high data rate mission transmitting at 28 Megabits per second (Mbps), or 270 Gigabits of science data per day. ISRO and PACE anticipate achieving data throughputs of 5-40 Terabits per day. These data rates exceed the capabilities of S-band and X-band frequency allocations and are a key driver for migrating to the 26 GHz Ka-band frequency allocation. The NASA Space Communications and Navigation (SCaN) program has been preparing the networks to support this demand by pursuing critical Ka-band infrastructure. The status of current and evolving network capability, including the Near Space Network’s Initiative for Ka-band Advancement (NIKA), and the Deep Space Network’s Lunar Exploration Upgrades (DLEU), as well as profiling mission usage of Ka-band services, are discussed in detail. The push toward Kaband, is not only an opportunity for increased performance, but alleviates current challenges with contentious and cluttered spectrum access in S- and X-band. The paper provides an overview of these advantages and advanced techniques that optimize its use before the transition to optical communications becomes an imperative. The challenges and potential mitigations for missions considering selection of Ka-band network services are also discussed.

Ka-band↗
DOE OSTI2020

Role of Alkali-Metal Cations in Electronic Structure and Halide Segregation of Hybrid Perovskites

The ability to control or prevent phase segregation in perovskites is crucial to realizing stable and tunable mixed-halide optoelectronic devices. Here, we systematically examine the impact of alkali-metal-cation (Cs + and K + ) concentration on the band structure, chemical composition, phase segregation, and polycrystalline microstructure on formamidinium-dominated mixed-halide mixed-cation perovskite films. It was found that the incorporation of Cs + and K + cations decreases the work function and the core levels of all components shift toward higher binding energy consistent with n-doping the perovskite film, which facilitates electron transfer to the electron transport layer TiO 2 . A concentration-dependent film structure was observed by X-ray photoemission spectroscopy and grazing incidence wide-angle X-ray scattering where the halides and cations are distributed evenly across perovskite films at low metallic cation concentration (5%). A high metal-cation ratio (20%) leads to halide segregation within the perovskite film and the surface becomes bromide-poor, whereas the bromide and metal cations diffuse more deeply within the film. These differences in electronic properties, element distribution, and film morphology were reflected in the device performance where the power conversion efficiency of low-metallic-cation concentration (5% of Cs + and K + ) perovskite solar cells is ≈5% higher than the high-concentration ones (20%). This study provides valuable chemical and physical insight into the underlying trade-offs in the careful tuning of electrical properties and film structure to optimize multication and mixed-halide hybrid perovskites.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Visible spectroscopy diagnostics for tungsten source assessment in the WEST tokamak: First measurements

The present work concerns the measurements obtained with the Tungsten (W) Environment in Steady-state Tokamak (WEST) visible spectroscopy system during the first experimental campaign. This system has been developed in the framework of the WEST project that equipped the existing Tore Supra device with a tungsten divertor in order to test actively cooled tungsten Plasma Facing Components (PFC) in view of preparing for ITER operation. The goal of this diagnostic is to measure the PFC sources and the deuterium recycling with spectral, spatial, and temporal resolution adapted to the predicted power deposition profiles on the objects observed. Three kinds of PFCs are monitored: the Ion Cyclotron Resonance Heating (ICRH) antenna and Low Hybrid Current Drive (LHCD) launcher W limiters; one of the 6 W inner bumpers; and the upper and lower W divertors. Large-aperture in-vessel actively cooled optical systems (f-number ~ 3) were installed for each view and connected to optical fibres. A total of 240 optical fibers can be distributed on various detection systems including a fast response-time, multi-channel, filtered photodetector-based “Filterscope” system, developed by Oak Ridge National Laboratory (USA) as well as grating spectrometers optimized for multi-sightline analysis. The first WEST experimental campaign conducted in 2017 has been dedicated to plasma start-up development during which the visible spectroscopy system has provided crucial information related to the impurity content first and then impurity sources. The diagnostic setup for that first experimental campaign was limited to the inner bumper and outer limiters but was sufficient to demonstrate that the optical setup was in accordance with the specifications. The radiance calibration procedure allowed us to estimate fluxes from the main limiter of about 8 × 10 18 atoms/(s m 2 ) and to show a first W source radial profile along the outboard limiter.

Meyer, O.↗
DOE OSTI2024

FORCE Update 2024

The Framework for Optimization of Resources and Economics (FORCE) tool suite is the U.S. Department of Energy’s Nuclear Integrated Energy Systems (IES) Program flagship tool suite for technoeconomic IES analysis of IES. This tool suite is useful for analysis designed to evaluate and improve the technoeconomics of energy production systems, particularly for systems including nuclear technology. In this report, we document the development activity for the FORCE tool suite to extend its capabilities as performed during fiscal year 2024. In addition to reliability and accessibility, capability is one of the three standards guiding the development of the FORCE tool suite and the software codes that are its constituent parts. Extending the capabilities of the FORCE tool suite allows analysis both within the IES program as well as industry, university, and laboratory partners to perform analysis with more accuracy, insight, and impactful narrative. Four areas of capability development were the focus of activity this year: economic parameter uncertainty quantification, multiresolution analysis, components-to-optimization workflow automation, and statespace construction workflows for real-time optimal control. In economic parameter uncertainty quantification, the ability of HERON to capture risk due to scenarios (weather and energy demand uncertainty) was expanded to also include uncertainties in financial parameters such as capital cost or operation and maintenance costs. By including these sources of uncertainty, which are sometimes very large compared with scenario uncertainty, HERON is better able to capture the risk posed by investment in various IES technology. Because of this, analysts can also consider the reduction in risks that can be realized by choice of some technologies. In multiresolution analysis, development activity extended on work completed previously. In fiscal year 2023, methods for decomposing time series signals, such as demand, solar and wind availability, and price profiles, were analyzed and down-selected to those most effective at splitting signals into different resolutions. These resolutions allow considering the influence of different energy demand and supply behaviors across different time scales. For example, energy demand might be divided into seasonal, weekly, and hourly profiles. In fiscal year 2024, this preliminary work was extended and implemented within the Risk Analysis Virtual Environment (RAVEN) risk and uncertainty analysis platform, which is used throughout the FORCE framework. This development of the “multi-resolution time series analysis” (MR-TSA) module in RAVEN allows training synthetic history generators on complex time series. These synthetic history generators can then be used in HERON for generating scenarios that represent possible market and weather scenarios that can be analyzed on different time scales. We envision completing this work in the future, implementing multiresolution dispatch optimization strategies that can make the most beneficial use of these stratified time histories. In components-to-optimization workflow development, workflows for translating user inputs of components into algorithms for algebraic optimization were selected and implemented. Similar algorithms within the Holistic Energy Resource Optimization Network (HERON) were separated from the main code base of HERON and gathered with the components-to-optimization workflows in the new Dispatch Optimization Variable Engine (DOVE) software library. This modularization allows FORCE users to analyze dispatch optimization and energy system duty cycles independently of HERON, which previously was a burdensome task. Additionally, these dispatch optimization algorithms, set up in an independent library, can now be used across all software applications within FORCE, especially including the real-time optimal control software Optimization of Real-time Capacity Allocation (ORCA). Allowing FORCE software to share dispatch optimization algorithms within a single library allows for improved software maintenance and reliability. In statespace characterization workflow development, alternative workflows for optimizing dispatch with additional technical accuracy was the focus, particularly to improve the real-time optimization decision making in ORCA. Using algorithms and workflows initially developed for the Feasible Actuator Range Modifier (FARM), workflows for determining the statespace representation of IES were identified and demonstrated. The resulting dispatch optimization required a more robust optimization algorithm than that originally used in HERON (and moved to DOVE), which required adding an alternate workflow to DOVE that can more accurately match the behavior of physical systems using a partial differential equation representation. In conclusion, capability developments in the FORCE tool suite in fiscal year 2024 have improved the ability of the FORCE tool suite to perform

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2019

Lead optimization and efficacy evaluation of quinazoline-based BET family inhibitors for potential treatment of cancer and inflammatory diseases

Extensive optimization of quinazoline-based lead 8 is described. The structure-activity relationship studies indicate the S-configuration is preferred for the phenylmorpholine substitution. Together with incorporation of a (2-hydroxyl-2-methylpropyl)pyrazole moiety at the 2-position leads to analogs with comparable potency and marked improvement in the pharmacokinetic profile over our previously reported lead compounds. Further in vivo efficacy studies in Kasumi-1 xenograft mouse model demonstrates that the selected inhibitors are well tolerated and highly efficacious in the inhibition of tumor growth. Additionally, the representative analog 19 also demonstrated significant improvement of arthritis severity in a collagen-induced arthritis (CIA) mouse model. These results indicate potential use of these quinazoline-based BET inhibitors for treatment of cancer and inflammatory diseases. Finally, a brief discussion of the co-crystallized structure of 19 with BRD4 (BD1) is also highlighted.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

TRANSP integrated modeling code for interpretive and predictive analysis of tokamak plasmas

This paper provides a comprehensive review of the TRANSP code, a sophisticated tool for interpretive and predictive analysis of tokamak plasmas, detailing its major capabilities and features. It describes the equations for particle, power, and momentum balance analysis, as well as the poloidal field diffusion equations. The paper outlines the spatial and time grids used in TRANSP and details the equilibrium assumptions and solvers. Various models for heating and current drive and radiation, including updates to the NUBEAM model, are discussed. The handling of large-scale events such as sawtooth crashes and pellet injections is examined, along with the predictive capabilities for advancing plasma profiles. The integration of TRANSP with the ITER Integrated Modeling and Analysis Suite (IMAS) is highlighted, demonstrating enhanced data access and analysis capabilities. Additionally, the paper discusses best practices and continuous integration techniques to enhance TRANSP's robustness. The suite of TRANSP tools, designed for efficient data analysis and simulation, further supports the optimization of tokamak operations and coupling with other tokamak codes. Continuous development and support ensure that TRANSP remains a major code for the analysis of experimental data for controlled thermonuclear fusion, maintaining its critical role in supporting the optimization of tokamak operations and advancing fusion research.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

Time of Flight Secondary Ion Mass Spectrometry for Characterization of Pt-Coated Porous Transport Layers in PEM Water Electrolyzers

Titanium-based porous transport layers (PTLs) and iridium-based catalyst layers (CLs) are two main components of proton exchange membrane water electrolyzers (PEMWEs). PTLs are typically coated with platinum to minimize interfacial losses and to support long-term operation. Optimizing coatings and the PTL-CL interface requires comprehensive characterization. This study establishes time-of-flight secondary ion mass spectrometry (ToF-SIMS) as a valuable technique for PTL characterization, addressing capabilities and limitations related to PTL morphology. A methodology was developed that uses a Cs + sputter beam for dynamic depth profiling, with data collected in both positive-ion (MCs + ) and negative-ion modes to generate depth profiles, 2D ion maps, and 3D ion reconstructions. ToF-SIMS detected relative differences in platinum-layer thickness between samples; these trends were validated by cross-sectional scanning transmission electron microscope (STEM) measurements and flat-titanium substrate controls. Interfacial oxide layers are identified in both ion modes, with enhanced oxide sensitivity in negative mode. The technique’s high sensitivity enables detection of nanometer-scale coatings and trace impurities within the bulk PTL structure. These results provide a methodological framework for analyzing Pt-coated PTLs, with the potential to extend to other components in PEMWEs and other electrolyzer systems.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Wake forces in a background of quadratically coupled mediators

Two particles can exert forces on each other when embedded in a sea of weakly coupled particles. These “wake forces” occur whenever the source and target particles have quadratic interactions with the mediating particles; they are proportional to the ambient energy density and typically have a range of order the characteristic de Broglie wavelength of the background. The effect can be understood as source particles causing a disturbance in the background waves—a wake—which subsequently interacts with the target particles. Wake forces can be mediated by bosons or fermions, can have spin dependence, may be attractive or repulsive, and have a generally anisotropic spatial profile and range that depends on the phase-space distribution of the ambient particles. In this work, I investigate the application of wake forces to dark matter searches, recast existing limits on short-range forces into leading constraints on dark matter with quadratic couplings, and sketch out potential experimental modifications to optimize sensitivity. Wake forces occur in the Standard Model: the presence of the cosmic neutrino background induces a millimeter-range force about 22 orders of magnitude weaker than gravity. Wake forces may also be relevant in condensed-matter and atomic physics. Published by the American Physical Society 2024

Astronomy & Astrophysics↗
DOE OSTI2020

GET-Solar (Generation forecasting and parameter Estimation Tool for Solar) [SWR-20-115]

GET-Solar (Generation forecasting and parameter Estimation Tool for Solar) can be used to estimate behind the meter (BTM) solar generation from limited datasets. Using distributed sets of diverse solar sites, but with close spatial proximity, and/or limited historical PV generation information can be used to generate of solar profiles. This is useful for applications where partial solar generation data is available, and on-site irradiance data is not available. GET-Solar calculates PV technical data parameters and calculates output by modeling shading and cloud cover impacts. Clear sky irradiance profiles are used to calculate base generation profiles on which the local shading and cloud cover layers are added. In order to arrive at clear sky generation data, PV mounting information like panel tilt and and angle is needed. For cases where PV mounting information is missing, panel tilt and azimuth angle can be estimated using a non-linear optimization algorithm. GET-Solar can also be used for forecasting applications where historical PV data is available to estimate local shading at various solar positions. This overall framework can be used for estimation of solar parameters, and assisting in analyzing and modeling diverse sets of DER where solar generation is also present in utility meter data. GET-Solar has been developed in Python and uses the Pyomo optimization language.

Abraham, Sherin Ann↗
NASA NTRS1974

The 1974 NASA-ASEE summer faculty fellowship aeronautics and space research program

Research activities by participants in the fellowship program are documented, and include such topics as: (1) multispectral imagery for detecting southern pine beetle infestations; (2) trajectory optimization techniques for low thrust vehicles; (3) concentration characteristics of a fresnel solar strip reflection concentrator; (4) calaboration and reduction of video camera data; (5) fracture mechanics of Cer-Vit glass-ceramic; (6) space shuttle external propellant tank prelaunch heat transfer; (7) holographic interferometric fringes; and (8) atmospheric wind and stress profiles in a two-dimensional internal boundary layer.

Obrien, J. F., Jr.↗
NASA NTRS2021

Probabilistic Machine Learning Estimation of Ocean Mixed Layer Depth from Dense Satellite and Sparse In-Situ Observations

The ocean mixed layer plays an important role in the coupling between the upper ocean and atmosphere across a wide range of time scales. Estimation of the variability of the ocean mixed layer is therefore important for atmosphere-ocean prediction and analysis. The increasing coverage of in situ Argo profile data allows for an increasingly accurate analysis of the mixed layer depth (MLD) variability associated with deviations from the seasonal climatology. However, sampling rates are not sufficient to fully resolve subseasonal (<90 day) MLD variability. Yet, many multivariate observations-based analyses include implicit modeled subseasonal MLD variability. One analysis method is optimal interpolation of in situ data, but the interior analysis can be improved by leveraging surface data with regression or variational approaches. Here, we demonstrate how machine learning methods and satellite sea surface temperature, salinity, and height facilitate MLD estimation in a pilot study of two regions: the mid-latitude southern Indian and the eastern equatorial Pacific Oceans. We construct multiple machine learning architectures to produce weekly 1/2° gridded MLD anomaly fields (relative to a monthly climatology) with uncertainty estimates. We test multiple traditional and probabilistic machine learning techniques to compare both accuracy and probabilistic calibration. We validate our methodology by applying it to ocean model simulations. We find that incorporating sea surface data through a machine learning model improves the performance of spatiotemporal MLD variability estimation compared to optimal interpolation of Argo observations alone. These preliminary results are a promising first step for the application of machine learning to MLD prediction.

Machine Learning↗
DOE OSTI2018

Optimization of Zero Emission Hydrogen Fuel Cell Ferry Design, With Comparisons to the SF-BREEZE

Zero emission hydrogen fuel cell technology has the potential to drastically reduce total “well-to-waves” maritime emissions. Through realistic design studies of five commercially-relevant passenger vessels, this study examines the most cost-effective entry points in the US fleet for deploying today’s available technology, and includes analysis of resulting well-to-waves emission profiles. The results show that per-passenger mile vessel energy use is directly correlated to increased emissions, capital costs, and operating costs. As a consequence, low speed, large capacity vessels offer a cost-effective starting place today. Increases in vessel efficiency through such measures as hull design and light-weighting can have large impacts in reducing cost and emissions of these systems. Overall this work showed all five vessel types to be feasible with today’s hydrogen fuel cell technology and presents more options to fleets that are committed to reducing maritime emissions in cost effective ways.

08 HYDROGEN↗