Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Compiler Validation”

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 343 records · Page 19
All sourcesNASA NTRSDOE OSTI
NASA NTRS2021

TESS Hunt for Young and Maturing Exoplanets (THYME). V. A Sub-Neptune Transiting a Young Star in a Newly Discovered 250 Myr Association

The detection and characterization of young planetary systems offer a direct path to study the processes that shape planet evolution. We report on the discovery of a sub-Neptune-sized planet orbiting the young star HD 110082(TOI-1098). Transit events we initially detected during TESS Cycle 1 are validated with time-series photometry from Spitzer. High-contrast imaging and high-resolution, optical spectra are also obtained to characterize the stellar host and confirm the planetary nature of the transits. The host star is a late-F dwarf(Må=1.2Me)with a low-mass,M dwarf binary companion(Må=0.26Me)separated by nearly one arc minute(∼6200 au). Based on its rapid rotation and Lithium absorption, HD 110082 is young, but is not a member of any known group of young stars(despite proximity to the Octans association). To measure the age of the system, we search for coeval, phase-space neighbors and compile a sample of candidate siblings to compare with the empirical sequences of young clusters and to apply quantitative age-dating techniques. In doing so, we find that HD 110082 resides in a new young stellar association we designate MELANGE-1, with an age of -+ 2507050 Myr. Jointly modeling the TESS and Spitzer light curves, we measure a planetary orbital period of 10.1827 days and radius of Rp=3.2±0.1R⊕. HD 110082 b’s radius falls in the largest 12% of field age systems with similar host-star mass and orbital period. This finding supports previous studies indicating that young planets have larger radii than their field-age counterparts

Benjamin M. Tofflemire↗
DOE OSTI2023

Verification of a Modeling Toolkit for the Design of Building Electrical Distribution Systems

DC electrical distribution systems offer many potential advantages over their AC counterparts. They can facilitate easier integration with distributed energy resources, improve system energy efficiency by eliminating AC/DC converters at end-use devices (e.g., laptop chargers), and reduce installation material, time, and cost. However, DC electrical distribution systems present additional design considerations, largely resulting from potentially greater magnitude and variation in cable losses. Modeling and simulation are rarely used to design such systems. However, the greater dependency of DC system energy efficiency on design choices such as distribution voltages, architecture, and integration of PV and BESS suggests that modeling and simulation may be required. Such system performance analysis is currently not a standard practice, in part due to limited availability and validation of capable software tools. This paper characterizes the accuracy of a Modelica-based Building Electrical Efficiency Analysis Model (BEEAM) toolkit, as a precursor for validating its use to perform system performance analysis and inform design decisions. The study builds upon previous verification research by characterizing complete systems comprised of commercially available equipment, and providing a more detailed analysis of simulation results. Five lighting systems with varying electrical distribution architectures were designed using market-available equipment, installed in a laboratory environment, modeled using BEEAM, and simulated using three Modelica integrated development environments (IDEs). Simulated and measured results were compared to characterize toolkit accuracy. Initial results revealed that simulated performance was mostly within ±5% of measured system-level and device-level performance. While simulation results were not found to be dependent on the IDE, some Modelica compiler interoperability issues were identified. Although the BEEAM toolkit showed promise for the targeted use case, further work is needed to determine whether the demonstrated 5% accuracy is sufficient for making real-world design decisions, and for BEEAM to advance from an interesting research tool to one that can impact real-world building projects.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

TESS Hunt for Young and Maturing Exoplanets (THYME). V. A Sub-Neptune Transiting a Young Star in a Newly Discovered 250 Myr Association

The detection and characterization of young planetary systems offer a direct path to study the processes that shape planet evolution. We report on the discovery of a sub-Neptune-sized planet orbiting the young star HD 110082 (TOI-1098). Transit events we initially detected during TESS Cycle 1 are validated with time-series photometry from Spitzer. High-contrast imaging and high-resolution, optical spectra are also obtained to characterize the stellar host and confirm the planetary nature of the transits. The host star is a late-F dwarf (M {sub ⋆} = 1.2M {sub ⊙}) with a low-mass, M dwarf binary companion (M {sub ⋆} = 0.26M {sub ⊙}) separated by nearly one arcminute (∼6200 au). Based on its rapid rotation and Lithium absorption, HD 110082 is young, but is not a member of any known group of young stars (despite proximity to the Octans association). To measure the age of the system, we search for coeval, phase-space neighbors and compile a sample of candidate siblings to compare with the empirical sequences of young clusters and to apply quantitative age-dating techniques. In doing so, we find that HD 110082 resides in a new young stellar association we designate MELANGE-1, with an age of 250{sub −70}{sup +50} Myr. Jointly modeling the TESS and Spitzer light curves, we measure a planetary orbital period of 10.1827 days and radius of R {sub p} = 3.2 ± 0.1R {sub ⊕}. HD 110082 b’s radius falls in the largest 12% of field-age systems with similar host-star mass and orbital period. This finding supports previous studies indicating that young planets have larger radii than their field-age counterparts.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

Unveiling the transferability of PLSR models for leaf trait estimation: lessons from a comprehensive analysis with a novel global dataset

Leaf traits are essential for understanding many physiological and ecological processes. Partial least squares regression (PLSR) models with leaf spectroscopy are widely applied for trait estimation, but their transferability across space, time, and plant functional types (PFTs) remains unclear. We compiled a novel dataset of paired leaf traits and spectra, with 47 393 records for >700 species and eight PFTs at 101 globally distributed locations across multiple seasons. Using this dataset, we conducted an unprecedented comprehensive analysis to assess the transferability of PLSR models in estimating leaf traits. While PLSR models demonstrate commendable performance in predicting chlorophyll content, carotenoid, leaf water, and leaf mass per area prediction within their training data space, their efficacy diminishes when extrapolating to new contexts. Specifically, extrapolating to locations, seasons, and PFTs beyond the training data leads to reduced R 2 (0.12–0.49, 0.15–0.42, and 0.25–0.56) and increased NRMSE (3.58–18.24%, 6.27–11.55%, and 7.0–33.12%) compared with nonspatial random cross-validation. The results underscore the importance of incorporating greater spectral diversity in model training to boost its transferability. These findings highlight potential errors in estimating leaf traits across large spatial domains, diverse PFTs, and time due to biased validation schemes, and provide guidance for future field sampling strategies and remote sensing applications.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2024

Unveiling the Transferability of PLSR Models for Leaf Trait Estimation: Lessons from a Comprehensive Analysis with a Novel Global Dataset

Leaf traits are essential for understanding many physiological and ecological processes. Partial least-squares regression (PLSR) models with leaf spectroscopy are widely applied for trait estimation, but their transferability across space, time and plant functional types (PFTs) remains unclear. We compiled a novel dataset of paired leaf traits and spectra, with 47,393 records for >700 species and eight PFTs at 101 globally-distributed locations across multiple seasons. Using this dataset, we conducted an unprecedented comprehensive analysis to assess the transferability of PLSR models in estimating leaf traits. While PLSR models demonstrate commendable performance in predicting chlorophyll content, carotenoid, leaf water and leaf mass per area prediction within their training data space, their efficacy diminishes when extrapolating to new contexts. Specifically, extrapolating to locations, seasons, and PFTs beyond the training data leads to reduced R 2 (0.12-0.49, 0.15-0.42, and 0.25-0.56) and increased NRMSE (3.58-18.24%, 6.27-11.55% and 7.0-33.12%) compared to nonspatial random cross-validation (NRCV). The results underscore the importance of incorporating greater spectral diversity in model training to boost its transferability. These findings highlight potential errors in estimating leaf traits across large spatial domains, diverse PFTs and time due to biased validation schemes and provide guidance for future field sampling strategies and remote sensing applications.

Leaf traits↗
DOE OSTI2017

Proteomic analysis of hair shafts from monozygotic twins: Expression profiles and genetically variant peptides

Forensic association of hair shaft evidence with individuals is currently assessed by comparing mitochondrial DNA haplotypes of reference and casework samples, primarily for exclusionary purposes. Present work tests and validates more recent proteomic approaches to extract quantitative transcriptional and genetic information from hair samples of monozygotic twin pairs, which would be predicted to partition away from unrelated individuals if the datasets contain identifying information. Protein expression profiles and polymorphic, genetically variant hair peptides were generated from ten pairs of monozygotic twins. Profiling using the protein tryptic digests revealed that samples from identical twins had typically an order of magnitude fewer protein expression differences than unrelated individuals. The data did not indicate that the degree of difference within twin pairs increased with age. In parallel, data from the digests were used to detect genetically variant peptides that result from common nonsynonymous single nucleotide polymorphisms in genes expressed in the hair follicle. Compilation of the variants permitted sorting of the samples by hierarchical clustering, permitting accurate matching of twin pairs. The results demonstrate that genetic differences are detectable by proteomic methods and provide a framework for developing quantitative statistical estimates of personal identification that increase the value of hair shaft evidence.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2014

Stochastic Particle Real Time Analyzer (SPARTA) Validation and Verification Suite

This report presents the test cases used to verify, validate and demonstrate the features and capabilities of the first release of the 3D Direct Simulation Monte Carlo (DSMC) code SPARTA (Stochastic Real Time Particle Analyzer). The test cases included in this report exercise the most critical capabilities of the code like the accurate representation of physical phenomena (molecular advection and collisions, energy conservation, etc.) and implementation of numerical methods (grid adaptation, load balancing, etc.). Several test cases of simple flow examples are shown to demonstrate that the code can reproduce phenomena predicted by analytical solutions and theory. A number of additional test cases are presented to illustrate the ability of SPARTA to model flow around complicated shapes. In these cases, the results are compared to other well-established codes or theoretical predictions. This compilation of test cases is not exhaustive, and it is anticipated that more cases will be added in the future.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

Stochastic Particle Real Time Analyzer (SPARTA) Validation and Verification Suite

This report presents the test cases used to verify, validate and demonstrate the features and capabilities of the first release of the 3D Direct Simulation Monte Carlo (DSMC) code SPARTA (Stochastic Real Time Particle Analyzer). The test cases included in this report exercise the most critical capabilities of the code like the accurate representation of physical phenomena (molecular advection and collisions, energy conservation, etc.) and implementation of numerical methods (grid adaptation, load balancing, etc.). Several test cases of simple flow examples are shown to demonstrate that the code can reproduce phenomena predicted by analytical solutions and theory. A number of additional test cases are presented to illustrate the ability of SPARTA to model flow around complicated shapes. In these cases, the results are compared to other well-established codes or theoretical predictions. This compilation of test cases is not exhaustive, and it is anticipated that more cases will be added in the future.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2006

Logistics Lessons Learned in NASA Space Flight

The Vision for Space Exploration sets out a number of goals, involving both strategic and tactical objectives. These include returning the Space Shuttle to flight, completing the International Space Station, and conducting human expeditions to the Moon by 2020. Each of these goals has profound logistics implications. In the consideration of these objectives,a need for a study on NASA logistics lessons learned was recognized. The study endeavors to identify both needs for space exploration and challenges in the development of past logistics architectures, as well as in the design of space systems. This study may also be appropriately applied as guidance in the development of an integrated logistics architecture for future human missions to the Moon and Mars. This report first summarizes current logistics practices for the Space Shuttle Program (SSP) and the International Space Station (ISS) and examines the practices of manifesting, stowage, inventory tracking, waste disposal, and return logistics. The key findings of this examination are that while the current practices do have many positive aspects, there are also several shortcomings. These shortcomings include a high-level of excess complexity, redundancy of information/lack of a common database, and a large human-in-the-loop component. Later sections of this report describe the methodology and results of our work to systematically gather logistics lessons learned from past and current human spaceflight programs as well as validating these lessons through a survey of the opinions of current space logisticians. To consider the perspectives on logistics lessons, we searched several sources within NASA, including organizations with direct and indirect connections with the system flow in mission planning. We utilized crew debriefs, the John Commonsense lessons repository for the JSC Mission Operations Directorate, and the Skylab Lessons Learned. Additionally, we searched the public version of the Lessons Learned Information System (LLIS) and verified that we received the same result using the internal version of LLIS for our logistics lesson searches. In conducting the research, information from multiple databases was consolidated into a single spreadsheet of 300 lessons learned. Keywords were applied for the purpose of sorting and evaluation. Once the lessons had been compiled, an analysis of the resulting data was performed, first sorting it by keyword, then finding duplication and root cause, and finally sorting by root cause. The data was then distilled into the top 7 lessons learned across programs, centers, and activities.

Evans, William A.↗
DOE OSTI2023

Wind Energy Accomplishments and Year-End Performance Report: Fiscal Year 2023

As the United States' largest source of renewable energy, wind is already playing a vital role in the nation's shift to electricity generated from sustainable resources. Scientists, engineers, and analysts at the U.S. Department of Energy's (DOE's) National Renewable Energy Laboratory (NREL) are propelling our country closer to this clean energy future with new efficient, reliable, and cost-competitive wind technologies and deployment strategies. In Fiscal Year 2023 (FY 2023), NREL received national acclaim for recent wind technology breakthroughs, applauded sustained decades of progress in wind energy research, and heralded new initiatives to support the next generation of wind development. This report and NREL's achievements of the last year set the stage for innovative research to come. Two NREL software innovations used to assess wind technology options were recognized with R&D 100 Awards. The Renewable Energy Potential (reV) model helps planners, developers, and researchers calculate wind energy capacity, generation, and cost for specific facilities, fleets and scenarios. NREL's Simulation and Emulation for Advanced Systems validates transmission and distribution solutions to minimize implementation risks. Both of these tools can be applied to a range of renewable solutions to cut costs and improve the reliability of systems in even the most remote locations. The laboratory commemorated landmark anniversaries for wind energy research facilities and programs managed by NREL. The National Wind Technology Center (NWTC) celebrated 30 years as a world-class hub for renewable energy research. An important component of the NWTC on NREL's Flatirons Campus, the one-of-a-kind 7-megawatt (MW) Controllable Grid Interface wind energy research apparatus, turned 10 this year. The Collegiate Wind Competition completed its tenth annual competition in May 2023. Six years after the grand challenges in wind energy science were first compiled, NREL brought together more than 100 wind energy experts from 15 countries to revisit the field's most pressing research needs. Other key new research initiatives examined ways to simultaneously address the needs for skilled wind energy workers and equitable job opportunities. NREL released the first national-level report evaluating offshore wind industry workforce gaps and ways to build a large, diverse pool of job candidates. The lab also co-hosted the International Partnering Forum's Offshore Wind Workforce Summit as part of its ongoing efforts to address the special challenges of that industry sector. NREL research and development (R&D) for the DOE Wind Energy Technologies Office (WETO) continues to build momentum in its efforts to combat climate change, create clean energy jobs, and promote energy justice. This report provides more detail on these top achievements and other accomplishments made by NREL and its partners during FY 2023 (between Oct. 1, 2022, and Sept. 30, 2023).

accomplishments↗
DOE OSTI2025

Optimizing Deep Learning Models for Climate-Related Natural Disaster Detection from UAV Images and Remote Sensing Data

This research study utilized artificial intelligence (AI) to detect natural disasters from aerial images. Flooding and desertification were two natural disasters taken into consideration. The Climate Change Dataset was created by compiling various open-access data sources. This dataset contains 6334 aerial images from UAV (unmanned aerial vehicles) images and satellite images. The Climate Change Dataset was then used to train Deep Learning (DL) models to identify natural disasters. Four different Machine Learning (ML) models were used: convolutional neural network (CNN), DenseNet201, VGG16, and ResNet50. These ML models were trained on our Climate Change Dataset so that their performance could be compared. DenseNet201 was chosen for optimization. All four ML models performed well. DenseNet201 and ResNet50 achieved the highest testing accuracies of 99.37% and 99.21%, respectively. This research project demonstrates the potential of AI to address environmental challenges, such as climate change-related natural disasters. This study’s approach is novel by creating a new dataset, optimizing an ML model, cross-validating, and presenting desertification as one of our natural disasters for DL detection. Three categories were used (Flooded, Desert, Neither). Our study relates to AI for Climate Change and Environmental Sustainability. Drone emergency response would be a practical application for our research project.

AI↗
NASA NTRS1992

The role of global cloud climatologies in validating numerical models

Global maps of the monthly mean net upward longwave radiation flux at the ocean surface were obtained for April, July, October 1985 and January 1986. These maps were produced by blending information obtained from a combination of general circulation model cloud radiative forcing fields, the top of the atmosphere cloud radiative forcing from ERBE and TOVS profiles and sea surface temperature on ISCCP C1 tapes. The fields are compatible with known meteorological regimes of atmospheric water vapor content and cloudiness. There is a vast area of high net upward longwave radiation flux (greater than 80/sq Wm) in the eastern Pacific Ocean throughout most of the year. Areas of low net upward longwave radiation flux ((less than 40/sq Wm) are the tropical convective regions and extra tropical regions that tend to have persistent low cloud cover.The technique used relies on General Circulation Model simulations and so is subject to some of the uncertainties associated with the model. However, all input information regarding temperature, moisture, and cloud cover is from satellite data having near global coverage. This feature of the procedure alone warrants its consideration for further use in compiling global maps of longwave radiation.

HARSHVARDHAN↗
DOE OSTI2014

Research and Development of High-Power and High-Energy Electrochemical Storage Devices

The accomplishments and technology progressmade during the U.S. Department of Energy (DOE) Cooperative Agreement No. DE-FC26- 05NT42403 (duration: July 11, 2005 through April 30, 2014, funded for $\$$125 million in cost- shared research) are summarized in this Final Technical Report for a total of thirty-seven (37) collaborative programs organized by the United States Advanced Battery Consortium, LLC (USABC). The USABC is a partnership, formed in 1991, between the three U.S. domestic automakers Chrysler, Ford, and General Motors, to sponsor development of advanced high-performance batteries for electric and hybrid electric vehicle applications. The USABC provides a unique opportunity for developers to leverage their resources in combination with those of the automotive industry and the Federal government. This type of pre-competitive cooperation minimizes duplication of effort and risk of failure, and maximizes the benefits to the public of the government funds. A major goal of this program is to promote advanced battery development that can lead to commercialization within the domestic, and as appropriate, the foreign battery industry. A further goal of this program is to maintain a consortium that engages the battery manufacturers with the automobile manufacturers and other key stakeholders, universities, the National Laboratories, and manufacturers and developers that supply critical materials and components to the battery industry. Typically, the USABC defines and establishes consensus goals, conducts pre-competitive, vehicle-related research and development (R&D) in advanced battery technology. The R&D carried out by the USABC is an integral part of the DOE’s effort to develop advanced transportation technologies that will significantly improve fuel economy, comply with projected emissions and safety regulations, and use domestically produced fuels. The USABC advanced battery development plan has the following three focus areas: 1. Existing technology validation, implementation, and cost reduction. 2. Identification of the next viable technology with emphasis on the potential to meet USABC cost and operating temperature range goals. 3. Support high-risk, high-reward battery technology R&D. Specific to the Cooperative Agreement DE- FC26-05NT42403, addressing High-Energy and High Power Energy Storage Technologies, the USABC focus was on understanding and addressing the following factors (listed in priority of effort): • Cost: Reducing the current cost of lithium- ion batteries (currently about 2-3 times the FreedomCAR target ($\$$20/kW). • Low Temperature Performance: Improving the discharge power and removing lithium plating during regenerative braking. • Calendar Life: Achieving 15-year life and getting accurate life prediction. • Abuse Tolerance: Developing a system level tolerance to overcharge, crush, and high temperature exposure. This Final Technical Report compilation is submitted in fulfillment of the subject Cooperative Agreement, and is intended to serve as a ready-reference for the outcomes of following eight categories of projects conducted by the USABC under award from the DOE’s Energy Efficiency and Renewable Energy ) Vehicle Technologies Program: USABC DoE Final Report – DoE Cooperative Agreement DE-FC26-95EE50425 8 Protected Information 1. Electric Vehicle (EV) (Section A of this report) 2. Hybrid Electric Vehicle (HEV) (Section B 3. Plug-In Hybrid Electric Vehicle (PHEV) (Section C) 4. Low-Energy Energy Storage Systems (LEESS) (Section D) 5. Technology Assessment Program (TAP) (Section E) 6. Ultracapacitors (Section F) 7. 12 Volt Start-Stop (Section G) 8. Separators (Section H) The report summarizes the main areas of activity undertaken in collaboration with the supplier community and the National Laboratories. Copies of the individual supplier final reports are available upon request. Using project gap analysis versus defined USABC goals in each area, the report documents known technology limits and provides direction on future areas of technology and performance needs for vehicle applications. The report was developed using information such as program plans, gap analysis charts, quarterly reports and final project reports submitted by the developers. The public benefit served by this USABC program is that it continues the development of critical advanced battery technology that is needed to make electric, hybrid electric, and fuel cell vehicles attractive to a wide segment of the vehicle market. This will allow for a substantial savings in petroleum fuel use as these vehicles are introduced into the nation’s transportation system. It will also allow a sharp reduction in automotive air pollution emissions in critical areas that are currently classified as non-attainment by the Environmental Protection Agency. This program will also help ensure the long term health and viability of the U.S. Battery and Ultracapacitor Manufacturing Industry. The goals of eight categories of projects follow and summarization of each of the project’s accomplishments are in sequence of the list above.

25 ENERGY STORAGE↗
DOE OSTI2023

Quality Assessment of Molten Salt Thermochemical Property Data

Recommendations are made to enhance user confidence in property values included in the Molten Salt Thermal Database-Thermochemical Properties (MSTDB-TC). Specifically, it is recommended that all available measured values be included with a transparent assessment of each to arrive at a preferred value for each salt composition in the database. The use of a quality assessment and ranking system is recommended for data and property values compiled in the MSTDB-TC that is analogous to the approach developed for data and property values included in the MSTDB-Thermophysical Properties (TP) database. The approach includes assessments of five features of data collection: the method used to measure the property value, calibration of devices used to make the measurements, the quantified uncertainty of the results, control of the environmental conditions, and determination of the salt composition. The quality of each facet is ranked as High, Moderate, or Incomplete based on objective metrics. The overall quality of the dataset is ranked based on rankings of the five data features and traceability of the reported property value, with rankings of A and B indicating the data and property value are deemed suitable for quantitative use, C indicating the value is computed and not validated and U indicating uncertainties restrict the recommended use to qualitative purposes. Sufficient information should be provided or cited within each data set included in the database to verify the reported property value. The recommended approach is suitable for assessing data already in the MSTDB-TC and screening new entries.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2020

Availability of Shielding Benchmark Experiment Data in the ICSBEP Handbook

The International Criticality Safety Benchmark Evaluation Projects (ICSBEP) has over two decades of experience under the auspices of the Organisation for Economic Co-operation and Development (OECD) Nuclear Energy Agency (NEA) to identify, evaluate, and compile a comprehensive data set of criticality safety benchmark data [1]. The activities of the ICSBEP have led to the continued success of the International Handbook of Evaluated Criticality Safety Benchmark Experiments (ICSBEP Handbook) [2]. The contents of the ICSBEP Handbook include benchmark specifications derived from nuclear facilities around the world, which have been utilized to support criticality safety efforts and also integral testing of nuclear data [3]. The 2020 edition of the ICSBEP Handbook will include data from 582 evaluations containing benchmark specifications for 5,053 critical, subcritical, or near-critical configurations. There are seven criticality-alarm-placement/shielding evaluations containing a total of 45 benchmark configurations, and ten fundamental physics evaluations containing a total of 237 measurements relevant to criticality safety applications. The purpose of this paper is to summarize those benchmarks relative to validation needs in shielding applications currently found within the ICSBEP Handbook. The current and future plans of shielding benchmarks with regards to the ICSBEP will also be discussed.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2015

On the influence of the power plant operational history on the inventory and the uncertainties of radionuclides relevant for the final disposal of PWR spent fuel - 15149

A mandatory requisite for official granting safe final disposal approval of SNF is the comprehensive specification and declaration of the nuclear inventory in SNF by the NPP-operators. The whole radiochemical characterization of each spent fuel assembly hides many difficulties such as very high radiation burden, destruction method, the inhomogeneous burn-up of fuel assembly, very high cost. Thus, non-destructive characterization is usually applied on industrial scale. In this case only several nuclides can be measured, and the rest is calculated using simulations and typical irradiation history. Like any other German rad-waste acceptance requirements all these declarations will have to be checked and verified by an independent inspector. In this verification process not only values of radionuclide (RN) activities are important, but also their uncertainties. The simple simulation using burn-up calculations based on typical and generic reactor operational parameters do not answer the question about possible uncertainties observed in real reactor operations. At the same time, the details of irradiation history are often unknown, which complicates the assessment of declared RN inventories. Therefore, the development of dedicated generic proof tools, which can be applied to different types of waste, often of unknown origin and history is worth a serious consideration. Here, we have compiled a set of burn-up calculations considering the operational history of 339 published or anonymized real PWR fuel assemblies. This gives us the possibility to calculate the realistic variation or spectrum of RN inventories. These histories were used as a basis for 'SRP analysis', to provide information about the range of the values of the associated secondary reactor parameters (SRP's), i.e. initial enrichment (IE), specific power (SP), irradiation time (IT), downtime (DT), boric acid concentration (BA), moderator and fuel density (MD and FD) and temperatures (MT and MT) used as input parameters for the simulation models. Then, burn-up calculation codes provide the anticipated results for the entire nuclear inventory such as characteristic activity values and the corresponding minimum and maximum limits as a function of the fuel burn-up. These results are being validated with the experimental data from various publications and the online database - SFCOMPO and subsequently transferred and summarized into our own database. Ultimately, this database will provide the basis of proof tools for the operator independent verification of the declared nuclear inventories for the quality and safety assessment of a radioactive waste compound and bounding values for certain RN as a function of burn-up. The RN inventory can hence be verified without taking credit of the whole of the operational history of the SNF. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
NASA NTRS2006

Ozone Observations by the Gas and Aerosol Measurement Sensor during SOLVE II

The Gas and Aerosol Measurement Sensor (GAMS) was deployed aboard the NASA DC-8 aircraft during the second SAGE III Ozone Loss and Validation Experiment (SOLVE II). GAMS acquired line-of-sight (LOS) direct solar irradiance spectra during the sunlit portions of ten science flights of the DC-8 between 12 January and 4 February 2003. Differential line-of-sight (DLOS) optical depth spectra are produced from the GAMS raw solar irradiance spectra. Then, DLOS ozone number densities are retrieved from the GAMS spectra using a multiple linear regression spectral fitting technique. Both the DLOS optical depth spectra and retrieved ozone data are compared with coincident measurements from two other solar instruments aboard the DC-8 platform to demonstrate the robustness and stability of the GAMS data. The GAMS ozone measurements are then utilized to evaluate the quality of the Wulf band ozone cross sections, a critical component of the SAGE III aerosol, water vapor, and temperature/pressure retrievals. Results suggest the ozone cross section compilation of Shettle and Anderson currently used operationally in SAGE III data processing may be in error by as much as 10-20% in theWulf bands, and their lack of reported temperature dependence is a significant deficiency. A second, more recent, cross section database compiled for the SCIAMACHY satellite mission appears to be of much better quality in the Wulf bands, but still may have errors as large as 5% near the Wulf band absorption peaks, which is slightly larger than their stated uncertainty. Additional laboratory measurements of the Wulf band cross sections should be pursued to further reduce their uncertainty and better quantify their temperature dependence.

Pitts, M. C.↗