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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 1,189 records · Page 66

3-D Radiological Data Acquisition, Visualization and Modeling - 20211

The U.S. Army Corps of Engineers (USACE) was tasked to investigate and remediate low activity radiological contamination from research and production of the nation's first nuclear weapons at the former DuPont Chambers Works Formerly Utilized Sites Remedial Action Program (FUSRAP) site (DuPont). The DuPont site had several buildings used for the Manhattan project that were demolished in the 1940's and 1950's apparently using heavy earthmoving equipment. Some of the contaminated rubble from the demolition appears to have been spread out by this equipment resulting in somewhat random scattering of radiologically contaminated soil and debris along with aqueous spills. Traditional investigative methods such as soil borings, test pits and 2-dimensional gamma walkovers were only partially successful in delineating the radiological contamination at the site. It was feared that even 'chasing' the contamination during remediation would miss contamination if the demolition resulted in discontinuous trails of radiologically contaminated soils. In evaluating the data generated over the interceding decades, the USACE determined that a better method to collect and process the remedial action radiological data was needed to enable the project team to optimize predictive planning and meet documentation expectations. The purpose of this paper is to provide an overview of the effort and progress to combine and organize radiological survey methods into a highly flexible sampling, modeling, and decision analysis approach that emphasizes the quality of decision-making during remediation. This innovative system blends multiple tools to develop a methodology that can extend MARRSIM [1] into the subsurface and provide tools that can be applied to other sites. (authors)

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Development of a rate-based ENRTL-RK process model for a water-lean solvent

Advanced water-lean solvents (WLS) for post-combustion CO2 capture offer several advantages over the aqueous amine solvents . WLS have lower parasitic energy penalty, lower corrosion, lower temperature and high-pressure CO2 regeneration leading to lower cost of CO2 capture. RTI International, with funding from the US Department of Energy, has been developing its novel water-lean solvent, that has shown specific reboiler duty of 2.3 GJ/t-CO2 at the 60-kWe pilot testing unit (Tiller Plant, SINTEF, Norway) and 2.6 GJ/t-CO2 at the engineering scale testing system (12 MWe) at the Technology Centre Mongstad (TCM) in Norway. All heat duties, including the one from TCM testing, were consistent with Aspen Plus modeling of the specific configuration of each test plant. This work focuses on the development of a detailed process model using in-house laboratory measurements and process data at pilot scale. The eNTRL-RK model used in this work is based on an unsymmetric activity coefficient model with the reference states chosen to be pure liquids for solvents and ideal dilute solution at unit solute molality (resulting in activity coefficient of unity at infinite dilution) for electrolytes. It uses the Redlich-Kwong equation of state for vapor phase properties and Henry’s law for solubility of supercritical gases. The model was validated using process data from the pilot-scale campaign at the Tiller plant, and the engineering scale test campaign at TCM. Data on CO2 capture rate, absorber, and regenerator temperature profiles and specific reboiler duties from two different test campaigns at Tiller and TCM, were used to further refine and validate the model and the model compares favorably to experimental data. The validation results against TCM campaign will be presented in this work.

CO2 capture↗

Methods for safely sharing dual-use genetic data

Background: Some genetic data has dual-use potential. Sharing pathogen data has shown tremendous value. For example therapeutic development and lineage tracking during the COVID pandemic. This data sharing is complicated by the fact that these data have the potential to be used for harm. The genome sequence of a pathogen can be used to enable malicious genetic engineering approaches or to recreate the pathogen from synthetic DNA. Standard data security methods can be applied to genetic data, but when data is shared between institutions, ensuring appropriate security can be difficult. Sensitive data that is shared internationally among a wide array of institutions can be especially difficult to control. Methods for securely storing and sharing genetic data with potential for dual-use are needed to mitigate this potential harm.Results: Here we propose new methods that allow genetic data to be shared in a data format that prevents a nefarious actor from accessing sensitive aspects of the data. Our methods obfuscate raw sequence data by pooling reads from different samples. This approach can ensure that data is secure while stored and during electronic transfer. We demonstrate that by pooling raw sequence data from multiple samples of the same organism, the ability to fully reconstruct any individual sample is prevented. In the pooled data, most genomic information remains, but reads or mutations cannot be directly attributed to any individual sample. To further restrict access to information, regions of a genome can be removed from the reads.Conclusion: Our methods obscure genomic information within raw sequence reads. This method can allow genetic data to be stored and shared while preventing a nefarious actor from being able to perfectly reconstruct an organism. Broad-scale sequence information remains, while fine scale details about specific samples are difficult or impossible to reconstruct. Our software is available at https://github.com/Geneinfosec-Inc/ReadMixer.

59 BASIC BIOLOGICAL SCIENCES↗

DOE Project 18546, AOP Task 1.1, Fuel Effects on Advanced Combustion Engines

Research in 2011 was focused on diesel range fuels and diesel combustion and fuels evaluated in 2011 included a series of oxygenated biofuels fuels from University of Maine, oxygenated fuel compounds representing materials which could be made from sewage, oxygenated marine diesel fuels for low emissions, and a new series of FACE fuel surrogates and FACE fuels with detailed exhaust chemistry and particulate size measurements. Fuels obtained in late 2011, which will be evaluated in 2012, include a series of oil shale derived fuels from PNNL, green diesel fuel (hydrotreated vegetable oil) from UOP, University of Maine cellulosic biofuel (levulene), and pyrolysis derived fuels from UOP pyrolysis oil, upgraded at University of Georgia. We were able to demonstrate, through a project with University of Wisconsin, that a hybrid strategy for fuel surrogates provided both accurate and rapid CFD combustion modeling for diesel HCCI. In this strategy, high molecular weight compounds are used to more accurately represent physical processes and smaller molecular weight compounds are used for chemistry to speed chemical calculations. We conducted a small collaboration with sp3H, a French company developing an on-board fuel quality sensor based on near infrared analysis to determine how to use fuel property and chemistry information for engine control. We were able to show that selected outputs from the sensor correlated to both fuel properties and to engine performance. This collaboration leveraged our past statistical analysis work and further work will be done as opportunity permits. We conducted blending experiments to determine characteristics of ethanol blends based on the gasoline characteristics used for blending. Results indicate that much of the octane benefits gained by high level ethanol blending can be negated by use of low octane gasoline blend stocks, as allowed by ASTM D5798. This may limit ability to optimize engines for improved efficiency with ethanol fuels. Extensive data from current and previous years was leveraged into participation with several large proposal teams, as our fuels database covers a very wide range of conventional and emerging fuels and biofuels.

02 PETROLEUM↗

Opportunities and data requirements for data-driven prognostics and health management in liquid hydrogen storage systems

During the past decade, Prognostics and Health Management (PHM) has become an important set of tools in various areas of industry and academic reliability engineering. PHM consists of a variety of mathematical and computational methods used to support data-driven decision-making to increase the safety, availability, and reliability of complex engineering systems. In particular, PHM can provide crucial insight into reliability and safety design improvements for developing technologies where historical performance and failure data are limited. This is the case of hydrogen fueling and storage technologies. This work presents a high-level approach for designing data-driven PHM applications for bulk liquid hydrogen (LH 2 ) storage systems for hydrogen fueling stations. This paper addresses core aspects of the design, development, and implementation of data-driven PHM applications that can improve the reliability assessment of hydrogen components. The analysis focuses on the relationship between data availability and diagnostic/prognostic capabilities; potential challenges; and integration schemes for current risk mitigation measures. We identify potential condition-monitoring data sources for key components in an LH 2 storage system, including storage tanks, piping, and pumps. Further, we determine that the short-term goals for the implementation of data-driven models in PHM frameworks in hydrogen systems should focus on developing adequate data collection and analysis strategies, as well as exploring the effect on reliability, safety, and regulations for hydrogen systems.

08 HYDROGEN↗

Communicating the Impacts of Projected Climate Change on Heavy Rainfall Using a Weighted Ensemble Approach

Urban flood risks are often determined by the frequency analysis of observed rainfall data, communicated using isohyetal maps showing rainfall totals for a range of durations and recurrence intervals. However, to assess future changes in heavy rainfall, it is necessary to study the future projected rainfall time series. Impacts of climate change are typically assessed using climate projections based on global climate model (GCM) outputs and downscaled to finer temporal and spatial scales. The projected data, however, are not generated in a format that urban planners and engineers can easily use to design for future conditions. This paper presents a method to analyze and express climate data in a format that can be readily used in hydrologic models to assess the effects of future extreme rainfall events. Future conditions’ climate data were analyzed using a weighted ensemble approach, which resulted in projected rainfall frequency estimates and their confidence limits. Two multimodel data sets were selected to illustrate this approach in Cook County, Illinois, which belongs to the Chicago metropolitan area. The first data set included statistical downscaling data based on the Intergovernmental Panel for Climate Change’s (IPCC) Coupled Model Intercomparison Project Phase 3 (CMIP3) data. The weighted ensemble analysis applied to this data set produced results that indicated significant increases in projected heavy rainfall. For example, for CMIP3 Scenario A2, for the late 21st century, the 100-year, 24-h rainfall in the northern parts of the county was 29% larger than the model-generated rainfall for the present time. Finally, for the same time horizon and scenario, the confidence interval based on projected data was 87% wider compared with that of the published source (NOAA Atlas 14), calculated using the past observed data. Also, equal-weight delta-corrected IPCC CMIP5-based dynamical downscaling data were applied to the same region for the mid-21st century, producing increases in heavy rainfall fairly similar to those of CMIP3.

54 ENVIRONMENTAL SCIENCES↗

OpenOA: An Open-Source Codebase For Operational Analysis of Wind Farms

OpenOA is an open source framework for operational data analysis of wind energy plants, implemented in the Python programming language. OpenOA provides a common data model, high level analysis workflows, and low-level convenience functions that engineers, analysts, and researchers in the wind energy industry can use to facilitate analytics workflows on operational data sets. OpenOA contains documentation, worked out examples in Jupyter notebooks, and a corresponding example dataset from the Engie Renewable’s La Haute Borne Dataset.

17 WIND ENERGY↗

In-Water Data Acquisition Tool Supports Four Marine Energy Projects

The NREL-developed Modular Ocean Data Acquisition (MODAQ) system is built from open-source hardware and software. The tool can both collect and store data and even share curated information through the cloud. Marine energy developers can work with NREL's engineers to design their own customized MODAQ and capture high-quality field data to help monitor and improve their technology designs. For example, users could assess how much power their device produces at sea, analyze the durability of a specific device component, or even control their device from a desk halfway around the world.

data acquisition↗

Nuclear Data and Cross Section Testing Using ENDF/B-VIII.0

With the release of the Evaluated Nuclear Data File (ENDF)/B-VIII.0 library, nuclear criticality safety practitioners and engineers have access to the latest cross section sets available for their analyses. However, these cross sections must be rigorously tested and validated to ensure that the nuclear data are responsive to the needs of the individuals responsible for developing, implementing, and maintaining computational tools for criticality safety applications. Thus, the ENDF/B-VIII.0 library is tested and validated with a large collection of experiments that were vetted by the International Criticality Safety Benchmark Evaluation Project and made available in the International Handbook of Evaluated Criticality Safety Benchmark Experiments. A selection of benchmark experiments for use within the criticality safety community were prepared and reviewed within the Verified, Archived Library of Inputs and Data (VALID), which is maintained by the Nuclear Energy and Fuel Cycle Division at Oak Ridge National Laboratory. The performance of the ENDF/B-VIII.0 library is assessed by using VALID models of benchmark experiments with the beta 12 version of SCALE 6.3 KENO V.a and KENO-VI Monte Carlo codes. The performance is compared with the results obtained from with the ENDF/B-VII.1 library. This report considers multigroup (MG) and continuous energy (CE) formats of the ENDF/B-VIII.0 and -VII.1 libraries. The benchmark experiments within VALID that validate the ENDF/B-VIII.0 library cover 15 broad system categories by using a range of fissile materials, uranium enrichments, plutonium isotopic vectors, and mixed uranium/plutonium systems. These forms are represented as metals, solutions, or various arrays of rods or plates that cover a variety of neutron energy spectra: thermal, fast, mixed, and intermediate. Over 600 cases were considered for use with the KENO V.a and KENO-VI codes with the ENDF/B-VIII.0 library. The results of the Monte Carlo comparison of ENDF/B-VIII.0 to ENDF/B-VII.1 with both KENO V.a and KENO-VI indicate that there is a less than 0.53% Δk difference between the bias of calculated k eff from the expected values. The CE ENDF/B-VIII.0 library results in smaller magnitude biases than the ENDF/B-VII.1 data for HEU-MET-FAST, HEU-SOL-THERM, IEU-MET-FAST, LEU-SOL-THERM, PU-SOL-THERM, and U233-MET-FAST systems, while the MG results yielded smaller magnitude biases for HEU-MET-FAST, HEU-SOL-THERM, IEU-MET-FAST, LEU-COMP-THERM, LEU-SOL THERM, MIX-COMP-FAST, and U233-MET-FAST systems. Most notable are the adjustments to the plutonium and 233 U cross section data, which has resulted in noticeably lower biases in the ENDF/B VIII.0 results for the mixed, plutonium, and 233 U systems. Results of the sensitivity data file comparison generated from TSUNAMI-3D for selected VALID cases for the ENDF/B-VIII.0 library indicate a very high level of agreement with correlation coefficients of the effect of nuclear data uncertainty on k eff (the c k integral parameter) all above 0.99. This indicates that cases with the ENDF/B-VIII.0 library would see very similar responses to any nuclear data errors or change as those with the ENDF/B-VII.1 library.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Modelling piloted ignition of wood and plastics

Highlights: Black-Right-Pointing-Pointer We model piloted ignition times of wood and plastics. Black-Right-Pointing-Pointer The model is applied on a packed bed. Black-Right-Pointing-Pointer When the air flow is above a critical level, no ignition can take place. - Abstract: To gain insight in the startup of an incinerator, this article deals with piloted ignition. A newly developed model is described to predict the piloted ignition times of wood, PMMA and PVC. The model is based on the lower flammability limit and the adiabatic flame temperature at this limit. The incoming radiative heat flux, sample thickness and moisture content are some of the used variables. Not only the ignition time can be calculated with the model, but also the mass flux and surface temperature at ignition. The ignition times for softwoods and PMMA are mainly under-predicted. For hardwoods and PVC the predicted ignition times agree well with experimental results. Due to a significant scatter in the experimental data the mass flux and surface temperature calculated with the model are hard to validate. The model is applied on the startup of a municipal waste incineration plant. For this process a maximum allowable primary air flow is derived. When the primary air flow is above this maximum air flow, no ignition can be obtained.

42 ENGINEERING↗

Municipal solid waste management: Identification and analysis of engineering indexes representing demand and costs generated in virtuous Italian communities

Highlights: • Collection and analysis of real life data in the field of Municipal Solid Waste (MSW) generation and costs for management. • Study of 92 virtuous Italian communities. • Elaboration of trends of engineering indexes useful during design and evaluation of MSWM systems. - Abstract: The definition and utilisation of engineering indexes in the field of Municipal Solid Waste Management (MSWM) is an issue of interest for technicians and scientists, which is widely discussed in literature. Specifically, the availability of consolidated engineering indexes is useful when new waste collection services are designed, along with when their performance is evaluated after a warm-up period. However, most published works in the field of MSWM complete their study with an analysis of isolated case studies. Conversely, decision makers require tools for information collection and exchange in order to trace the trends of these engineering indexes in large experiments. In this paper, common engineering indexes are presented and their values analysed in virtuous Italian communities, with the aim of contributing to the creation of a useful database whose data could be used during experiments, by indicating examples of MSWM demand profiles and the costs required to manage them.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Biological and Environmental Research Network Requirements

The Energy Sciences Network (ESnet) is the primary provider of network connectivity for the U.S. Department of Energy (DOE) Office of Science (SC), the single largest supporter of basic research in the physical sciences in the United States. In support of SC programs, ESnet regularly updates and refreshes its understanding of the networking requirements of the instruments, facilities, scientists, and science programs that it serves. This focus has helped ESnet be a highly successful enabler of scientific discovery for over 25 years. In November 2012, ESnet and the Office of Biological and Environmental Research (BER) of the DOE SC organized a review to characterize the networking requirements of the programs funded by the BER program office. Several key findings resulted from the review. Among them: 1) The scale of data sets available to science collaborations continues to increase exponentially. This has broad impact, both on the network and on the computational and storage systems connected to the network. 2) Many science collaborations require assistance to cope with the systems and network engineering challenges inherent in managing the rapid growth in data scale. 3) Several science domains operate distributed facilities that rely on high-performance networking for success. Key examples illustrated in this report include the Earth System Grid Federation (ESGF) and the Systems Biology Knowledgebase (KBase). This report expands on these points, and addresses others as well. The report contains a findings section as well as the text of the case studies discussed at the review.

09 BIOMASS FUELS↗

Front-End Engineering and Design: Project Tundra Carbon Capture System (Final Report)

As the next phase of Project Tundra, Minnkota Power Cooperative (MPC) completed a front-end engineering and design (FEED) study to install a post-combustion CO 2 capture system (CCS) at the MPC operated (Square Butte Electric Cooperative-owned) Milton R. Young Station (MRYS) Unit 2 (MRY2), a 477-MW power plant fueled by North Dakota lignite. The project team completed the FEED with Fluor’s Econamine FG Plus℠ (EFG+) technology and is taking the next steps leading up to start of construction. Team members included FEED technical lead Fluor Enterprises (Fluor); owner’s engineer and balance of plant (BOP) engineer Burns & McDonnell (BMcD); leading carbon capture consultants (David Greeson Consulting, Hunt International Energy Services); environmental consultants (AECOM, Agora Environmental), other BOP engineering consultants (Golder Associates, Nels); cost-share funding agency, the North Dakota Industrial Commission (NDIC); and the Energy & Environmental Research Center (EERC). Project Tundra’s goal is to implement carbon capture, utilization, and storage (CCUS) in North Dakota, while preserving the use of lignite. Future options could lead to revitalizing legacy oil fields and creating a new CO 2 enhanced oil recovery (EOR) industry. The topic of this report is the FEED study for the carbon dioxide capture portion of Project Tundra. Building on the findings of a pre-FEED study for MRY2, the key deliverables contained in this FEED study are: a) design, costing, and performance data needed to commence project financing activities; b) engineering and material balances required to file for all project permits; and c) a final project schedule. Based on the results of the previous pre-FEED study, MPC and its team evaluated two options to provide the large amount of steam needed to operate the CCS: 1) installation of new natural gas package boilers and a new pipeline to supply natural gas to the facility and 2) extraction of steam from the existing MRYS steam turbine generator. The FEED study was performed using the package boilers option, as it was deemed to have the lowest technical risk, overall cost, and cost uncertainty. A key feature of the design, however, was the mixing the natural gas boilers’ flue gas with the MRY2 flue gas. This increased the size of the CCS system. This design also enabled the tie-in of Unit 1 flue gas for times when Unit 2 is offline. The CCS was designed to capture a combined 12,978 short tons per day (STPD) of CO 2 from the flue gases produced by the existing MRY Unit 2 along with flue gas produced by the new boiler package within the CCS. The 12,978 STPD CO 2 capture is achieved by normally processing 100% of the total available MRY Unit 2 flue gas (considering full load operation) and 100% of the boiler package flue gas, then removing 90% of the CO 2 available from the processed flue gas streams.

01 COAL, LIGNITE, AND PEAT↗

Making Roads Safer: Optimizing De-icing Using Snowmelt Rates and Slope Data

More than $ 1.5 B is spent annually on snow-control programs in the United States. With an increase in severe winter storms, many municipalities are encountering difficulty in clearing their roads of ice and snow within their budgetary limits. Currently, roads are classified based on traffic counts, with busier (arterial) roads being treated before less busy (secondary) roads. This approach is problematic because most people live on secondary roads and must travel over these untreated roads before they can reach treated roads. In addition, inefficient distribution of de-icing material can have knock-on environmental impacts with increased material run-off into surrounding areas. To address these concerns, we developed a model for categorizing road vulnerability based on snowmelt rate and slope. We calculated the snowmelt rates in 1-m by 1-m squares of all roads in Knox County, Tennessee, using an empirical equation developed by the U.S. Army Corps of Engineers. This equation takes in freely available weather data and incident solar radiation, which we calculated based on LiDAR (Light Detection And Ranging) data. Using the model results, we propose a more efficient plan: apply de-icers to the steepest roads with the slowest snowmelt, rather than to the busiest roads. Under this approach, we argue that given existing budgetary constraints, more vulnerable roads can be treated with de-icing material and provide for easier mobility for motorists traveling on secondary roads. Our approach provides a more cost-effective, environmentally-conscious, and mobility enhancing application strategy.

Chapin, Fletcher↗

xdamp Version 6: An IDL®-based Data and Image Manipulation Program

The original DAMP (DAta Manipulation Program) was written by Mark Hedemann of Sandia National Laboratories and used the CA-DISSPLA™ (available from Computer Associates International, Inc., Garden City, NY) graphics package as its engine. It was used to plot, modify, and otherwise manipulate the one-dimensional data waveforms (data vs. time) from a wide variety of accelerators. With the waning of CA-DISSPLA and the increasing popularity of Unix®-based workstations, a replacement was needed. This package uses the IDL® software, available from Research Systems Incorporated, a Xerox company, in Boulder, Colorado, as the engine, and creates a set of widgets to manipulate the data in a manner similar to the original DAMP and earlier versions of xdamp. IDL is currently supported on a wide variety of Unix platforms such as IBM® workstations, Hewlett Packard workstations, SUN® workstations, Microsoft® Windows™ computers, Macintosh® computers and Digital Equipment Corporation VMS® and Alpha® systems. Thus, xdamp is portable across many platforms. We have verified operation, albeit with some minor IDL bugs, on personal computers using Windows 7 and Windows Vista; Unix platforms; and Macintosh computers. Version 6 is an update that uses the IDL Virtual Machine to resolve the need for licensing IDL.

43 PARTICLE ACCELERATORS↗

Building Initial Dynamic System Models for Digital Twins of the Cryogenic Moderator System at the ORNL Spallation Neutron Source

This work describes the initial development of dynamic system models of the cryogenic moderator system (CMS) of the Spallation Neutron Source (SNS) at ORNL as a part of the ORNL LDRD funded project Building TRANSFORM to Accelerate Digital Twin Applications for Nuclear Systems, LOIS 10563. The goal of the work is to start the dynamic system modeling effort with the end goal of using them for real-time applications as digital twins. The CMS is a cryogenic liquid hydrogen flow loop that provides moderation of the neutrons that are generated by the SNS. For optimal neutron production, the CMS needs to maintain a steady and controlled density of cryogenic hydrogen in the moderator section thus requiring precise temperature and pressure control. Due to the varied time scales and system characteristics, control of the system is complex, and diagnostics are also difficult. Difficulty in accessing the flow loop during operations, limited instrumentation and unknown design details of the equipment combine to make the case for having sophisticated digital twin models of the system. Operationally the CMS also provides a strong use case for digital twins due to the constant need of optimization and for troubleshooting/diagnostics. The large amount of data collected which are freely available for using in building the model and verifying and validating the model also makes it a great candidate for a proof-of-concept for digital twins. The project extends ORNL's capacity of development and implementation of the open-source dynamic system modeling tool TRANSFORM for engineering design and digital twin/real-time applications. Specific system configuration data for the CMS have been gathered and an initial dynamic model was created in the TRANSFORM library using Dymola as the solution platform. Models of increasing complexity are created to demonstrate the need for a multi-layered approach in digital twin modeling depending on the scale and phenomena being focused on. The dynamic modeling is shown to bring the dynamic operational aspects to the design process for systems as well as serve as a digital twin to the hardware and allow for models to be tuned and compared against real time operational data. These aims should help to push forward strategic goals of application of digital twins and increase the impact of ORNL systems modeling capabilities with TRANSFORM/Modelica for various advanced energy systems.

42 ENGINEERING↗

Applying Infrared Thermography as a Quality-Control Tool for the Rapid Detection of Proton-Electrolyte-Membrane-Fuel-Cell Catalyst-Layer-Thickness Variations

As fuel cells become more prominent, new manufacturing and production methods are needed to enable increased volumes with high quality. One necessary component of this industrial growth will be the accurate measurement of the variability of a wide range of material properties during the manufacturing process. In this study, a method to detect defects in fuel cell catalyst layers is investigated through experiment and mathematical simulation. The method uses infrared thermography and direct-current electronic-excitation methods to detect variations in platinum-containing catalyst-layer thickness with high spatial and temporal resolution. Data analysis, operating-condition impacts, and detection limits are explored, showing the measurement of defects on the millimeter length scale. Overall, the experimental and modeling results demonstrate great potential of this technique as a nondestructive method to measure defects that is amenable to use on roll-to-roll manufacturing lines.

08 HYDROGEN↗

Polarimetric Radar Variables in Snowfall at Ka- and W-Band Frequency Bands: A Comparative Analysis

Dual-frequency millimeter-wavelength radar observations in snowfall are analyzed in order to evaluate differences in conventional polarimetric radar variables such as differential reflectivity (ZDR) specific differential phase shift (K DP ) and linear depolarization ratio (LDR) at traditional cloud radar frequencies at Ka and W bands (~35 and ~94 GHz, correspondingly). Low radar beam elevation (~5°) measurements were performed at Oliktok Point, Alaska, with a scanning fully polarimetric radar operating in the horizontal–vertical polarization basis. This radar has the same gate spacing and very close beam widths at both frequencies, which largely alleviates uncertainties associated with spatial and temporal data matching. It is shown that observed Ka- and W-band Z DR differences are, on average, less than about 0.5 dB and do not have a pronounced trend as a function of snowfall reflectivity. The observed Z DR differences agree well with modeling results obtained using integration over nonspherical ice particle size distributions. For higher signal-to-noise ratios, KDP data derived from differential phase measurements are approximately scaled as reciprocals of corresponding radar frequencies indicating that the influence of non-Rayleigh scattering effects on this variable is rather limited. This result is also in satisfactory agreement with data obtained by modeling using realistic particle size distributions. Observed Ka- and W-band LDR differences are strongly affected by the radar hardware system polarization “leak” and are generally less than 4 dB. Smaller differences are observed for higher depolarizations, where the polarization “leak” is less pronounced. Realistic assumptions about particle canting and the system polarization isolation lead to modeling results that satisfactorily agree with observational dual-frequency LDR data.

42 ENGINEERING↗