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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 469 records · Page 26

Integrating Reanalysis and Satellite Cloud Information to Estimate Surface Downward Long-Wave Radiation

The estimation of downward long-wave radiation (DLR) at the surface is very important for the understanding of the Earth’s radiative budget with implications in surface–atmosphere exchanges, climate variability, and global warming. Theoretical radiative transfer and observationally based studies identify the crucial role of clouds in modulating the temporal and spatial variability of DLR. In this study, a new machine learning algorithm that uses multivariate adaptive regression splines (MARS) and the combination of near-surface meteorological data with satellite cloud information is proposed. The new algorithm is compared with the current operational formulation used by the European Organization for the Exploitation of Meteorological Satellites (EUMETSAT) Satellite Application Facility on Land Surface Analysis (LSA-SAF). Both algorithms use near-surface temperature and dewpoint temperature along with total column water vapor from the latest European Centre for Medium-range Weather Forecasts (ECMWF) reanalysis ERA5 and satellite cloud information from the Meteosat Second Generation. The algorithms are trained and validated using both ECMWF-ERA5 and DLR acquired from 23 ground stations as part of the Baseline Surface Radiation Network (BSRN) and the Atmospheric Radiation Measurement (ARM) user facility. Results show that the MARS algorithm generally improves DLR estimation in comparison with other model estimates, particularly when trained with observations. When considering all the validation data, root mean square errors (RMSEs) of 18.76, 23.55, and 22.08 W·m –2 are obtained for MARS, operational LSA-SAF, and ERA5, respectively. The added value of using the satellite cloud information is accessed by comparing with estimates driven by ERA5 total cloud cover, showing an increase of 17% of the RMSE. The consistency of MARS estimate is also tested against an independent dataset of 52 ground stations (from FLUXNET2015), further supporting the good performance of the proposed model.

54 ENVIRONMENTAL SCIENCES↗

Data compression for data archival, browse or quick-look

Soon after space and Earth science data is collected, it is stored in one or more archival facilities for later retrieval and analysis. Since the purpose of the archival process is to keep an accurate and complete record of data, any data compression used in an archival system must be lossless, and protect against propagation of error in the storage media. A browse capability for space and Earth science data is needed to enable scientists to check the appropriateness and quality of particular data sets before obtaining the full data set(s) for detailed analysis. Browse data produced for these purposes could be used to facilitate the retrieval of data from an archival facility. Quick-look data is data obtained directly from the sensor for either previewing the data or for an application that requires very timely analysis of the space or Earth science data. Two main differences between data compression techniques appropriate to browse and quick-look cases, are that quick-look can be more specifically tailored, and it must be limited in complexity by the relatively limited computational power available on space platforms.

Dozier, Jeff↗

Space Operations Center: A concept analysis

The Space Operations Center is a concept for a shuttle-service, permanent, manned facility in low Earth orbit. An analysis of this concept was conducted and the results are reported. It is noted that there are no NASA plans at present to implement such a concept. The results are intended for consideration in future planning.

Livingston, L. E.↗

Combined Techno-Economic Analysis and Life Cycle Assessment of an Integrated Direct Air Capture System with Advanced Algal Biofuel Production

The continuous increase in carbon dioxide (CO2) concentration in the atmosphere since the First Industrial Revolution correlates convincingly with the ongoing rise of the Earth's global average temperature contributing to climate change. As a response, carbon capture and sequestration (CCS) technologies are being implemented to mitigate anthropogenic CO2 emissions by capturing CO2 from high emitting point sources, such as power plants, refineries, and cement factories, and subsequently buried in geological formations underground for long term storage. Recently direct air capture (DAC) has emerged as a promising alternative technology that captures CO2 directly from the atmosphere for use or sequestration. This study investigates the potential synergistic benefits of integrating a solid amine-based DAC system with advanced algal biofuel production in photobioreactors (PBRs). DAC utilization allows the removal of atmospheric CO2 while also decoupling algae production facilities from anthropogenic point CO2 sources and avoiding the cost and logistics challenges of transporting CO2 long distances to remote facilities. Techno-economic analysis and life cycle assessment are performed to assess the economic and environmental benefits of heat and mass integration between the DAC and the PBR for biofuel production. The DAC-PBR system integration also considers on-site flue gas handling options, DAC capital utilization, the tradeoff between centralization or decentralization of key unit operations, and the PBR array. This presentation will discuss how optimizing DAC-PBR process integration can enhance the algal biofuel's economic and environmental sustainability and the prospect of DAC enabling the circular carbon economy.

algal biofuel production↗

Updated General Aviation Non-Airport Crash Density Values Using Data Obtained from the U.S. National Transportation Safety Board for 2000 through 2019

This report documents the calculation of the General Aviation (GA) non-airport crash density for Department of Energy (DOE) sites and power generating facilities licensed by the Nuclear Regulatory Commission (NRC) using the methodology outlined in DOE-STD-3014-2006, Accident Analysis for Aircraft Crash Into Hazardous Facilities. The results of this report will be used by the American Nuclear Society (ANS) for the development of ANS standard 2.36, Accident Analysis for Aircraft Crash into Reactor and Nonreactor Nuclear Facilities.

99 GENERAL AND MISCELLANEOUS↗

Isotherm Sensor Calibration Program for Mars Science Laboratory Heat Shield Flight Data Analysis

Seven instrumented sensor plugs were installed on the Mars Science Laboratory heat shield in December 2008 as part of the Mars Science Laboratory Entry, Descent, and Landing Instrumentation (MEDLI) project. These sensor plugs contain four in-depth thermocouples and one Hollow aErothermal Ablation and Temperature (HEAT) sensor. The HEAT sensor follows the time progression of a 700 C isotherm through the thickness of a thermal protection system (TPS) material. The data can be used to infer char depth and, when analyzed in conjunction with the thermocouple data, the thermal gradient through the TPS material can also be determined. However, the uncertainty on the isotherm value is not well defined. To address this uncertainty, a team at NASA Ames Research Center is carrying out a HEAT sensor calibration test program. The scope of this test program is described, and initial results from experiments conducted in the laboratory to study the isotherm temperature of the HEAT sensor are presented. Data from the laboratory tests indicate an isotherm temperature of 720 C 60 C. An overview of near term arc jet testing is also given, including preliminary data from 30.48cm 30.48cm PICA panels instrumented with two MEDLI sensor plugs and tested in the NASA Ames Panel Test Facility. Forward work includes analysis of the arc jet test data, including an evaluation of the isotherm value based on the instant in time when it reaches a thermocouple depth.

Santos, Jose A.↗

Atmospheric numerical modeling resource enhancement and model convective parameterization/scale interaction studies

Research will be undertaken in this contract in the area of Modeling Resource and Facilities Enhancement to include computer, technical and educational support to NASA investigators to facilitate model implementation, execution and analysis of output; to provide facilities linking USRA and the NASA/EADS Computer System as well as resident work stations in ESAD; and to provide a centralized location for documentation, archival and dissemination of modeling information pertaining to NASA's program. Additional research will be undertaken in the area of Numerical Model Scale Interaction/Convective Parameterization Studies to include implementation of the comparison of cloud and rain systems and convective-scale processes between the model simulations and what was observed; and to incorporate the findings of these and related research findings in at least two refereed journal articles.

Cushman, Paula P.↗

Neutronics Analysis of Shielding Material Alternative to Tungsten Carbide in the FESS-FNSF Facility

Neutron transport calculations have been performed on advanced shielding materials. Metal hydrides and borohydrides were evaluated to find an alternative to tungsten carbide (WC), which is used in the in-vessel components. The study was conducted using a 22.5° sector and a detailed 360° geometry of the Fusion Energy System Studies-Fusion Nuclear Science Facility (FESS-FNSF) using OpenMC and FENDL-3.2b nuclear data library. Here, the neutronics analysis in this article was concentrated on calculating total nuclear (neutron and photon) heating at the magnet and the radiation damage of the inboard vacuum vessel (IBVV). For example, yttrium hydride (YH 2 ) and vanadium hydride (VH 2 ) showed lower radiation damage values compared to WC and other metals. Whereas alternative shielding materials did not show a significant change in the magnet nuclear heating.

36 MATERIALS SCIENCE↗

Geochemical and microbial characteristics of seepage water and mineral precipitates in a radwaste disposal facility impacted by seawater intrusion and high alkalinity

The construction of an underground facility can dramatically change the quality, flow direction, and level of groundwater. It may also impact subsurface microbial composition and activity. Groundwater quality was monitored over eight years in two observational wells near an underground disposal facility on the east coast of South Korea. The results showed dramatic increases in dissolved ions such as O 2 , Na, Ca, Mg, and SO 4 during facility construction. Seepage water samples downgradient from the silos and tunnels, and precipitates deposited along the seepage water flow path were collected to determine the impact inside the disposal facility. X-ray analysis (powder X-ray diffraction (pXRD) and X-ray absorption fine structure (XAFS)) were used to characterize the mineral precipitates. Microbial community composition was determined by 16S rRNA gene sequencing. The seepage water composition was of two types: Ca-Cl and Ca-Na-HCO 3 . The ratio of Cl and δ 18 O showed that the Ca-Cl type seepage water was influenced by groundwater mixed with seawater ranging from 2.7% to 15.1%. Various sulfate-reducing bacteria were identified in the Ca-Cl type seepage water, exhibiting relatively high sulfate content from seawater intrusion. Samples from the Ca-Na-HCO 3 type seepage water had an extremely high pH (>10) and abundance of Hydrogenophaga. The precipitates observed along the flow path of the seepage water included calcite, ferrihydrite, green rust, and siderite, depending on seepage water chemistry and microbial activity. This study suggests that the construction of underground structures creates distinct, localized geochemical conditions (e.g., high alkalinity, high salinity, and oxic conditions), which may impact microbial communities. These biogeochemical changes may have undesirable large-scale impacts such as water pump clogging. Overall, an understanding of the process and long-term monitoring are essential to assess the safety of underground facilities.

54 ENVIRONMENTAL SCIENCES↗

Modelling Tritium Production and Release at High-Energy Proton Accelerators

Tritium is a well-known byproduct of particle accelerator operations. To keep levels of tritium below regulatory limits, tritium production is actively monitored and managed at Fermilab. We plan to study tritium production in the targets, beamline components, and shielding elements of the Fermilab facilities such as NuMI, BNB, and MI-65. To facilitate the analysis, we construct a simple model and use three Monte Carlo radiation codes, FLUKA, MARS, and PHITS, to estimate the amount of tritium produced in these facilities. The analysis could also serve as an intercomparison between these code results related to tritium production. To assess the actual amounts of tritium that would be released from various materials, we employ a semi-empirical diffusion model. The results of this analysis are compared to experimental data whenever possible. This approach also helps to optimize proposed target materials with respect to the tritium production and release.

Georgobiani, Dali [Fermilab]↗

Resurgence of a Nation’s Radiation Science Driven by Its Nuclear Industry Needs

This article describes the radiation facilities and associated sample preparation, management, and analysis equipment currently in place at the Dalton Cumbrian Facility, a facility which opened in 2011 to support the UK’s nuclear industry. Examples of measurements performed using these facilities are presented to illustrate their versatility and the breadth of research they make possible. Results are presented from research which furthers our understanding of radiation damage to polymeric materials, radiolytic yield of gaseous products in situations relevant to nuclear materials, radiation chemistry in light water reactor cooling systems, material chemistry relevant to immobilization of nuclear waste, and radiation-induced corrosion of fuel cladding elements. Applications of radiation chemistry relevant to health care are also described. Research concerning the mechanisms of radioprotection by dietary carotenoids is reported. An ongoing open-labware project to develop a suite of modular sample handling components suited to radiation research is described, as is the development of a new neutron source able to provide directional beams of neutrons.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Steady-State Mechanical Analysis for Target Assembly in the Material Plasma Exposure eXperiment Facility

The Material Plasma Exposure eXperiment (MPEX) steady-state linear plasma facility is currently under design at Oak Ridge National Laboratory to expose target specimens to fusion divertor regimes. The neutron-irradiated target is actively cooled and remote handled in the MPEX facility for conducting plasma-material–interaction (PMI) experiments. Here, the steady-state stresses in the target and target assembly system are investigated using two-dimensional (2-D) and three-dimensional (3-D) models to provide expected stresses/strains under the heat loads to which various system components would be exposed during MPEX operation. The calculated temperatures from the 2-D axisymmetric mechanical model were found to be in excellent agreement with those from the full 3-D thermohydraulic model, providing a strong model validation. Numerical simulation results for the steady-state mechanical model indicate nonuniform distributions for the temperature, stress, and deformation within the critical components. For the initial design, the deformation results indicate possible gap openings between contacting surfaces below the plasma-facing materials. To reduce the possibility of interfacial gap opening, the target assembly was slightly changed and evaluated using the 2-D stress model. Numerical simulation results indicate that the interfacial gap openings can be minimized without drastically changing the entire target assembly. The stress-strain conditions for the target will be further used to assess the appropriate operation during MPEX experiments and gain insight into materials science phenomena during PMI.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Space station software reliability analysis based on failures observed during testing at the multisystem integration facility

Quality of software not only is vital to the successful operation of the space station, it is also an important factor in establishing testing requirements, time needed for software verification and integration as well as launching schedules for the space station. Defense of management decisions can be greatly strengthened by combining engineering judgments with statistical analysis. Unlike hardware, software has the characteristics of no wearout and costly redundancies, thus making traditional statistical analysis not suitable in evaluating reliability of software. A statistical model was developed to provide a representation of the number as well as types of failures occur during software testing and verification. From this model, quantitative measure of software reliability based on failure history during testing are derived. Criteria to terminate testing based on reliability objectives and methods to estimate the expected number of fixings required are also presented.

Tamayo, Tak Chai↗

LCLS Big Data Handling – How I Learned to Stop Worrying and Love the Data Deluge

Advanced data and computing systems are vital to Linac Coherent Light Source (LCLS) operations, data interpretation and overall scientific productivity. The transition to MHz-era operation marks a fundamental change in scale that requires new infrastructure and architectures to link LCLS to the required scale of computing needed for scientific interpretation. The LCLS-II Data System meets big data challenges by implementing configurable data reduction that can adapt to multiple science areas, real-time analysis frameworks to provide visualization and fast feedback, and the ability to transfer data to local and remote computational facilities for near real time analysis at the appropriate scale. Feature extracted information generated in the data analysis pipeline - at the edge, local compute, or remote High-Performance Computing (HPC) resources - can be used to steer experiments and inform user decisions during beam time. Artificial Intelligence and Machine Learning (AI/ML) techniques present new opportunities to rapidly analyse large datasets and direct experiments, but create new challenges in scaling, adaptability, complexity, and trustworthiness. We describe how the LCLS-II Data System architecture addresses its data-driven challenges in the areas of data acquisition, data processing, data management, and workflow orchestration to decrease the overall time-to-science and provide a vision for future developments.

artificial intelligence↗

Performance Criteria for Capture and/or Immobilization Technologies (Revision 1)

The capture and subsequent immobilization of regulated volatile radionuclides from the off-gas streams of a used nuclear fuel (UNF) reprocessing facility has been a topic of substantial research interest for the US Department of Energy and its international counterparts. Removal of specific radionuclides from the plant effluent streams before discharge to the environment is required to meet regulations set forth by the US Environmental Protection Agency. Upon removal, the radionuclides, as well as associated sorbents that cannot be regenerated in a cost-effective manner, are destined for conversion to a waste form. Research in separation and capture methodologies has included a wide range of technology types, and studies of waste forms are correspondingly diverse. In considering the future development and implementation of both sorbents and waste forms, it is necessary to identify benchmark measures of performance to objectively evaluate each sorbent system or waste form. Sets of performance criteria and associated metrics have been developed for sorbent and waste form evaluation. These criteria address physical, radiological, and chemical characteristics, technical practicality, technical maturity, cost, and, for sorbents, system performance. The criteria and metrics appear to be robust and should be applicable despite the eventual waste classification (as either high- or low-level waste). They are flexible enough to address both aqueous reprocessing and electrochemical reprocessing of UNF. These criteria sets can serve as tools to evaluate performance at multiple stages within the development process, and in this revision (Revision 1) they have been used to assess technologies relating to krypton/xenon separations and iodine capture from off-gas streams arising from UNF reprocessing. Assessment of krypton/xenon separations using engineered forms of two zeolite minerals (silver mordenite and hydrogen mordenite in a polyacrylonitrile-based binder [AgZ-PAN/HZ-PAN]) found that the zeolite-based separation is relatively advanced in its development, but several key issues require resolution. First, desorption processes for both krypton and xenon require refinement to provide an understanding of the product purity that can be achieved. Second, adsorption rate data is needed in order to calculate the bed depth required for effective separation. Finally, it is strongly recommended that a technical review of krypton/xenon separation by AgZ-PAN/HZ-PAN be performed to synergize available data and assess the cost savings and operational benefits that may be realized from implementation of this technology. Assessment of metal organic frameworks (MOFs) for their use in the separation of krypton/xenon found that the ideal separation would be performed using a single-column system with a MOF selective for krypton over xenon. A robust research effort should work to identify a krypton-selective MOF designed to operate at temperatures of approximately 0°C or higher, which could be preferred over cryogenic krypton/xenon capture for used fuel reprocessing off-gas streams. In the case of the CaSDB-MOF (the most well-understood xenon sorbent to date), two issues are judged of high importance. First, xenon breakthrough capacity for the CaSDB-MOF in prototypical conditions should be determined. Preliminary research indicates that breakthrough may be near immediate, presenting a substantial obstacle in separative system design. Second, development of desorption methodology should be performed to determine regeneration time, energy requirements, and the product stream composition. Silver-based sorbents (AgZ and AgAero) for use in iodine capture from the dissolver off-gas were evaluated against the established criteria. These sorbents are significantly better understood for this application as a result of research efforts over the past decade. The potential implementation of AgAero at a large scale is hindered by its physical degradation by components of the dissolver off-gas stream. Less is known about the adsorption of iodine by these sorbents from other off-gas streams in the plant. Initial experimental efforts have been closely coordinated in an effort to understand organic iodine (such as would be found in the vessel off-gas) adsorption by AgZ and AgAero. Future work should expand this experimental program, and analysis of other reprocessing facility off-gas streams such as the vitrification off-gas stream should be conducted to better understand other potential applications for iodine sorbents. A review of iodine waste form development shows that this area is diverse and that multiple promising waste forms have been identified for the immobilization of radioactive iodine. Efforts related to the direct conversion of iodine sorbents (including AgZ and AgAero) should be continued because of the advantages of direct conversion in a waste management strategy and other sorbents should continue to be advanced as merited.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Optimizing inference of segmentation on high-resolution images in MLExchange

MLExchange is a machine learning (ML) operations platform providing web user-interfaces (UIs) for data visualization and analysis pipelines at synchrotron facilities. Among these UIs is the segmentation app which helps synchrotron users utilize ML algorithms to automatically segment high-resolution scientific images with minimal manual annotation effort. In this work, we share code optimizations that significantly speed up the segmentation inference workflow of large data in short time. By optimizing the sequence of CPU-GPU data transfers and introducing CPU parallelization to key operations, we improve the per-device, per-image frame computational efficiency and observe close to 3×$$\times$$ speedup over the original segmentation inference workflow run time when utilizing a single GPU. Further adaptations enabling multi-GPU inference yield more than 40×$$\times$$ speedup with 100 GPUs compared to the optimized single GPU inference workflow. This acceleration of the segmentation inference workflow will provide MLExchange users with easy access to segmentation results with little wait time.

Lu, Shizhao↗

Optimization models for integrated biorefinery operations

Variations of physical and chemical characteristics of biomass lead to an uneven flow of biomass in a biorefinery, which reduces equipment utilization and increases operational costs. Uncertainty of biomass supply and high processing costs increase the risk of investing in the US’s cellulosic biofuel industry. We propose a stochastic programming model to streamline processes within a biorefinery. A chance constraint models system’s reliability requirement that the reactor is operating at a high utilization rate given uncertain biomass moisture content, particle size distribution, and equipment failure. The model identifies operating conditions of equipment and inventory level to maintain a continuous flow of biomass to the reactor. Furthermore, the sample average approximation method approximates the chance constraint and a bisection search-based heuristic solves this approximation. A case study is developed using real-life data collected at Idaho National Laboratory’s biomass processing facility. An extensive computational analysis indicates that sequencing of biomass bales based on moisture level, increasing storage capacity, and managing particle size distribution, increases utilization of the reactor and reduces operational costs.

09 BIOMASS FUELS↗

Daily grass reference evapotranspiration with Meteosat Second Generation shortwave radiation and reference ET products

Here we assess the accuracy of estimating daily grass reference evapotranspiration (PM-ET o ) using daily shortwave radiation (R s ) and reference evapotranspiration (ET REF ) products provided by the Meteosat Second Generation (MSG) geostationary satellite delivered by the Satellite Applications Facility on Land Surface Analysis (LSA-SAF) framework. The accuracy of using reanalysis ERA5 shortwave radiation data (R s ERA5 ) provided by the European Center for Medium-Range Weather Forecasts (ECMWF) is also evaluated. The assessments were performed using observed weather variables at 37 weather stations distributed across continental Portugal, where climate conditions range from semi-arid to humid, and 12 weather stations located in Azores islands, characterized by humid, windy and often cloudy conditions. This study&#x27;s use of data from a variety of climate conditions contributed to a unique and innovative assessment of the usability of LSA-SAF and ERA5 products for ET o estimation. The first assessment focused on comparing LSA-SAF estimates of R s (R s LSA-SAF ) against ground stations (R s ground ). The results showed a good matching between the two R s data sets for continental Portugal but a tendency for R s LSA-SAF to under-estimate R s ground in the cloudy islands of Azores. ET o values computed using R s LSA-SAF data and observed temperature, humidity and wind speed (ET o LSA-SAF ) were then compared with PM-ET o estimates with ground-based data, which were used as benchmark; input data of temperature and humidity needed for PM-ET o were quality checked for surface aridity effects. It was observed that ET o LSA-SAF is strongly correlated with PM-ET o (R 2 > 0.97) for most locations in continental Portugal, with regression coefficient of a linear regression forced to the origin ranging between 0.95 and 1.05, mean root mean square error (RMSE) of 0.13 mm d –1 , and Nash and Sutcliff efficiency of modeling (EF) above 0.95. For most Azores locations, ET o LSA-SAF over-estimated PM-ET o . This is likely a consequence of the high spatio-temporal heterogeneity of weather conditions that occur in these oceanic islands together with the different footprints of satellite (averaged over the pixel) and station observations. Reanalysis ERA5 shortwave radiation data presented similar behavior to the LSA-SAF products, however with slightly lower accuracy. The daily LSA-SAF ET REF product (ET REF LSA-SAF ) was assessed and results have shown a good accuracy of this product, with acceptable RMSE and high EF values, for continental Portugal but a low accuracy for the Azores islands. A simplified bias correction approach was shown to improve both ET o derived from the LSA-SAF products, namely for Azores stations, which seem to be representative of smaller areas. The use of the FAO-PM temperature approach (PMT) was also assessed using the R s LSA-SAF and R s ERA5 data, which showed a superiority of the LSA-SAF product for ET o estimations (ET o PMT LSA-SAF ). No significant differences (p < 0.05) were observed in terms of the median value of the RMSE when adopting ET o PMT and ET REF LSA-SAF . Differently, results showed that using the R s LSA-SAF in the PMT approach (ET o PMT LSA-SAF ) produces significantly better RMSE results than ET o PMT and ET REF LSA-SAF . Overall, the performed assessment allows concluding that the use of R s LSA-SAF, and to a lesser extent the use of the R s ERA5 , highly improves the accuracy of computation of ET o when R s observations are not available, including when only temperature data are accessible. The use of the ET REF LSA-SAF product is a good alternative when observed weather data are not available.

54 ENVIRONMENTAL SCIENCES↗