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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 1,477 records · Page 82
All sourcesNASA NTRSDOE OSTI
DOE OSTI2013

Removal of Radiocesium from Food by Processing: Data Collected after the Fukushima Daiichi Nuclear Power Plant Accident - 13167

Removal of radiocesium from food by processing is of great concern following the accident of TEPCO's Fukushima Daiichi Nuclear Power Plant accident. Foods in markets are monitored and recent monitoring results have shown that almost all food materials were under the standard limit concentration levels for radiocesium (Cs-134+137), that is, 100 Bq kg{sup -1} in raw foods, 50 Bq kg{sup -1} in baby foods, and 10 Bq kg{sup -1} in drinking water; those food materials above the limit cannot be sold. However, one of the most frequently asked questions from the public is how much radiocesium in food would be removed by processing. Hence, information about radioactivity removal by processing of food crops native to Japan is actively sought by consumers. In this study, the food processing retention factor, F{sub r}, which is expressed as total activity in processed food divided by total activity in raw food, is reported for various types of corps. For white rice at a typical polishing yield of 90-92% from brown rice, the F{sub r} value range was 0.42-0.47. For leafy vegetable (indirect contamination), the average F{sub r} values were 0.92 (range: 0.27-1.2) after washing and 0.55 (range: 0.22-0.93) after washing and boiling. The data for some fruits are also reported. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2016

Separation of Zirconium from Zircaloy-2 for Spent Nuclear Fuel Cladding Applications using a Chloride Volatility Process

The United States produces a large amount of cladding material from used nuclear fuel, expected to approach 1,000 MT/year for the next 50 years. The recovery of zirconium from the cladding material would represent a ∼50% savings on the geologic waste disposal requirement, and savings of >$40 M/year due to the cost of hafnium-free zirconium. Previous simulation studies have shown that in the irradiated cladding, the major activation products found are {sup 125}Sb, {sup 60}Co, and {sup 93m}Nb, and the major fission product found is {sup 137}Cs. These radioisotopes make it impossible to treat the cladding as low level waste. In a chlorination method, zirconium cladding reacts with Cl{sub 2} at 350-380 deg. C to produce mainly ZrCl{sub 4}. The zirconium tetrachloride has a relatively low boiling point (sublimes at 330 deg. C) which allows its separation from other products, and so it can be treated as low level waste for disposal or recycling. This chlorination approach has been proposed for the reprocessing of zirconium. However, previous work has observed element impurities (Fe, Sn, Cr, Cs, Sb, and Nb) in the recovered ZrCl{sub 4} meaning that additional steps are necessary in a chlorination process previous to the reduction of ZrCl{sub 4} to the metallic form. The chlorination process for zirconium reprocessing has been highly encouraged as it has proven more efficient than previous mechanical processes, redox processes, and other chemical methods such as iodination. The overall goal of this project is to develop the road map for a chlorination process that will yield high purity zirconium. The current study focuses on the recovery of ZrCl{sub 4} from non-irradiated alloys used as nuclear fuel cladding. (authors)

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

Evaluation of Material Balance Approaches for Hanford Direct-Feed Low Activity Waste Processing - 20022

The Hanford Site has accumulated millions of gallons of tank waste from reprocessing spent fuel to recover plutonium, uranium, cesium, and strontium. The supernatant from the accumulated tank waste will be treated using a Direct Feed Low-Activity Waste approach. The supernatant will be treated to remove solids and cesium in the Tank-Side Cesium Removal process in the Hanford tank farm, then vitrified in a semi-batch process in the Hanford Waste Treatment and Immobilization Plant (WTP). Currently, each batch of feed is sampled at three locations prior to being fed to the melter: the feed qualification tank in the Hanford tank farm as well as the concentrate receipt vessel (CRV) and melter feed preparation vessel (MFPV) in the WTP. The feed qualification sample is taken from a large batch of accumulated feed, only two to three samples are expected each year. Approximately 275 samples from the CRVs and 1100 samples from the MFPV are expected each year. An evaluation was performed to determine if a material balance based on the feed qualification sample could replace most of the sampling in the CRVs and MFPVs. The evaluation consisted of three elements: (1) determination of the practicality of using a material balance to estimate the stream composition of the CRV and MFPV contents, (2) evaluation of whether the material balance could be automated using the existing process control system, and (3) determination of the uncertainty in glass composition using the material balance approach. It is assumed that periodic sampling at the CRV and MFPV would be performed periodically to re-baseline the material balance, evaluations are in progress to determine the frequency of this periodic sampling. Process sample locations downstream of the melter were reviewed as well, but the partitioning of semi-volatile species in the melter was determined to preclude extending the material balance approach past the melter. It was determined that replacement of the CRV sample location was feasible and did not increase process uncertainty or significantly impact waste loading. Replacement of the MFPV sample was also determined to be feasible, but that measurement of the glass former chemical addition may be needed prior to addition of these chemicals to the MFPV. This measurement could be performed by an in situ laser-induced breakdown spectroscopy (LIBS) system. Limited tests were performed to evaluate LIBS for direct measurements of the low-activity waste melter feed. The use of a material balance would eliminate over 1200 samples each year if only 10% of the CRV and MFPV batches are sampled and could likely allow the WTP laboratory to operate on days only versus 24/7 operation. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2026

Pulsed Electric Field Processing of Apples

Pulsed electric field (PEF) processing is a nonthermal technology that has the potential to improve the efficiency of apple processing, particularly for firm cultivars that are growing in popularity. This study evaluated the effects of PEF pretreatment on the processability and product quality of Cosmic Crisp apples, a modern cultivar known for its firmness. Apples were treated with PEF and assessed for tissue softening, mechanical energy requirements, particle size reduction, browning tendencies, and juice yield. PEF treatment significantly softened the apple tissue, as demonstrated by reduced compression forces in Instron testing, and this softening translated to decreased grinding energy during applesauce production. There were no changes to the particle size distribution of the resulting applesauce. PEF treatment also altered browning behavior and produced higher juice yields following mechanical disruption, suggesting enhanced membrane permeability and mass transfer. Together, these results show that PEF pretreatment can reduce mechanical energy demands and increase extractability without reducing product quality in firm apple varieties. These outcomes highlight the potential of PEF to increase the value recovered from processing-grade apples and to support more efficient and sustainable apple processing operations.

32 - ENERGY CONSERVATION, CONSUMPTION, AND UTILIZA↗
DOE OSTI2019

Potential synergies of drop-in biofuel production with further co-processing at oil refineries

Drop-in biofuels have been defined as functionally equivalent to petroleum-based transportation fuels and are fully compatible with the existing petroleum infrastructure. They will be essential in sectors such as aviation if we are to achieve emission reduction and climate mitigation goals. Currently, 'conventional' drop-in biofuels, which are primarily based on upgrading of lipids / oleochemicals, are the only significant source of commercial volumes of drop-in biofuels. However, the necessary increased, future volumes will likely come from 'advanced' drop-in biofuels based on biomass feedstocks such as forest and agriculture residues. Biocrudes / bio-oils produced from lignocellulosic feedstocks using thermochemical technologies such as gasification, pyrolysis, and hydrothermal liquefaction need to be further upgraded to drop-in biofuels. However, advanced drop-in biofuels have been slow to reach commercial maturity due to significant technical challenges, high capital costs, and the challenge of generally lower oil prices. It is likely that the co-processing of drop-in biofuels with conventional petroleum refining could considerably reduce capital costs. Initially, co-processing is likely to be established through the upgrading of conventional / oleochemical feedstocks (lipids). Lipids are readily available in large volumes (global production in 2017 was ~185 million metric tonnes) and can be more easily integrated into oil-refinery processes. In contrast, lignocellulose-derived biocrudes / bio-oils are not yet available in significant volumes and are more complex to co-process in a refinery. The likely strategies for co-processing of oleochemicals (lipids) and bio-oil and biocrude feedstocks based on different insertion points within the refinery infrastructure are discussed.

09 BIOMASS FUELS↗
DOE OSTI2025

Bayesian D‐Optimal Designs for Gaussian Process Surrogate Models

Computer experiments often employ space-filling strategies to create surrogate models with strong predictive performance. The impact of model parameter estimation for Gaussian process surrogates, however, is often overlooked. Obtaining a better initial estimate of the covariance lengthscale parameter, θ, can greatly improve the resulting Gaussian process fit through more effective sequential acquisitions during active learning. In this work, we propose a novel initial design maximizing the Bayesian D-optimality criterion of the Gaussian process lengthscale parameter. Previously published results have shown the emphasis on lengthscale estimation to be promising, but relied on an empirically driven design creation process. Our Bayesian D-optimal designs are rooted in information theory and lead to more informative sequential acquisitions by improving lengthscale estimation. In many cases, these gains eventually result in better surrogates than those seeded with space-filling initial designs. Furthermore, Bayesian D-optimal designs can be tailored to either isotropic or anisotropic covariance structures, and the Bayesian framework enables the inclusion of prior knowledge in the design process, offering greater flexibility and adaptability. Through several simulation studies, we demonstrate the advantages of Bayesian D-optimal designs in terms of both lengthscale estimation accuracy and predictive performance during active learning.

Bayesian experimental design↗
DOE OSTI2019

Max-Compound Cox Processes. I

Extreme values are considered in samples with random size that have a mixed Poisson distribution that is generated by a doubly stochastic Poisson process. Some inequalities are proved relating the distributions and moments of extrema with those of the leading process (the mixing distribution). Limit theorems are proved for the distributions of max-compound Cox processes, and limit distributions are described. An important particular case of the negative binomial distribution of a sample size corresponding to the case where the Cox process is led by a gamma Lévy process is considered, explaining a possible genesis of tempered asymptotic models.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Friction Hydro-Pillar Processing of a High Carbon Steel: Joint Structure and Properties

A coupled experimental and theoretical study is reported here on friction hydro-pillar processing of AISI 4140 steel, which is a novel solid-state joining technique to repair and fill crack holes in thick-walled components by an external stud. The stud is rotated and forced to fill a crack hole by plastic flow. During the process, frictional heating occurs along the interface of the stud and the wall of crack hole leading to thermal softening of the stud that eases its plastic deformation. The effect of the stud force, its rotational speed and the total processing time on the rate of heat generation and resulting transient temperature field is therefore examined to correlate the processing variables with the joint structure and properties in a systematic and quantitative manner, which is currently scarce in the published literature. The results show that a gentler stud force rate and greater processing time can promote proper filling of the crack hole and facilitate a defect-free joint between the stud and original component.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Primary Processing Parameters, Porosity Production, and Fatigue Prediction for Additively Manufactured Alloy 718

Powder bed fusion processes commonly introduce voids and defects into components. It has been shown that many of these features and their size and shape characteristics are controllable through process parameter manipulation, but this process is typically time-consuming and expensive. In spite of this, an experiment was developed to explore a wide region of laser powder bed fusion process space, and several void measurements were obtained to characterize component density percentage, pore size, and pore shape. Then, multiple models commonly used in the literature to predict porosity were examined and compared with the experimental data. Using the developed porosity model, a fatigue life prediction framework was adapted, and the predictions were compared to the previously published experimental data. Results of this investigation reveal the strengths and weaknesses of multiple literature models in predicting porosity, and they depict how porosity and resulting fatigue lives vary across process space.

36 MATERIALS SCIENCE↗
DOE OSTI2020

An active learning high-throughput microstructure calibration framework for solving inverse structure–process problems in materials informatics

Determining a process–structure–property relationship is the holy grail of materials science, where both computational prediction in the forward direction and materials design in the inverse direction are essential. Problems in materials design are often considered in the context of process–property linkage by bypassing the materials structure, or in the context of structure–property linkage as in microstructure-sensitive design problems. However, there is a lack of research effort in studying materials design problems in the context of process–structure linkage, which has a great implication in reverse engineering. In this paper, given a target microstructure, we propose an active learning high-throughput microstructure calibration framework to derive a set of processing parameters, which can produce an optimal microstructure that is statistically equivalent to the target microstructure. The proposed framework is formulated as a noisy multi-objective optimization problem, where each objective function measures a deterministic or statistical difference of the same microstructure descriptor between a candidate microstructure and a target microstructure. Furthermore, to significantly reduce the physical waiting wall-time, we enable the high-throughput feature of the microstructure calibration framework by adopting an asynchronously parallel Bayesian optimization to exploit high-performance computing resources. Case studies in additive manufacturing and grain growth are used to demonstrate the applicability of the proposed framework, where kinetic Monte Carlo (kMC) simulation is used as a forward predictive model, such that for a given target microstructure, the target processing parameters that produced this microstructure are successfully recovered.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Benchmarking thermal energy storage cost for industrial process heat

Process heat accounts for roughly half of industrial energy demand, and currently 95% of process heat is derived from the combustion of natural gas, oil, and coal. Electrification of industrial heating could be an alternative, potentially expanding locations suitable for manufacturing; however, industrial facility owners may desire energy storage to stabilize energy costs. In this work, the economic benefits of pairing thermal storage with electrified process heat to reduce the average price paid for energy are analyzed. Cost savings focus on energy arbitrage, or leveraging flexible energy pricing schemes, alone. The cost of natural gas combustion across decades (2019-2060) is compared to the costs of electricity and thermal energy storage in four United States Independent System Operator (ISO) regions. Systems installed today may not yield positive net present value (NPV) compared to the use of natural gas. However, using estimated electricity prices, systems installed in 2030 using arbitrage alone could be profitable when compared to natural gas in some regions of the U.S. Furthermore, if capital expenditures could be reduced by 50% for sensible thermal storage systems by 2030, profitable systems are found across all regions. This implies that electrification of industrial process heat, when paired with inexpensive thermal energy storage systems, could be less expensive than brownfield natural gas systems, using arbitrage as the only source of revenue and without a dependency on any future policy drivers such as pricing externalities that could further incentivize the electrification of industrial process heat.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

An integrated methane dehydroaromatization and chemical looping process

Most of the natural gas co-produced in oil wells is flared due to the high transportation costs of bringing it to market. Onsite upgrading of natural gas to liquid products could address this issue but there are few processes for effective direct conversion of natural gas to liquid products. Methane dehydroaromatization (DHA) over Mo/HZSM- 5 offers a potential route to a value-added liquid product, however, DHA conversion is severely limited by thermodynamics at most industrially relevant temperatures. Here we propose an integrated process coupling methane DHA, chemical looping for selective hydrogen oxidation, and subsequent water removal to achieve higher yields of aromatic products limited by the thermodynamics in one-pass systems. Here, we validate this process via the construction and operation of a one-of-a-kind multibed recirculating reactor, and achieve a combined aromatics yield of 42%. Detailed technoeconomic analysis of the process for mobile applications show that such a process could be economically viable under certain circumstances.

03 NATURAL GAS↗
DOE OSTI2015

Microwave processing of cement and concrete materials – towards an industrial reality?

Each year a substantial body of literature is published on the use of microwave to process cement and concrete materials. Yet to date, very few if any have lead the realisation of a commercial scale industrial system and is the context under which this review has been undertaken. The state-of the–art is evaluated for opportunities, and the key barriers to the development of new microwave-based processing techniques to enhance production, processing and recycling of cement and concrete materials. Applications reviewed include pyro-processing of cement clinker; accelerated curing, non-destructive testing and evaluation (NDT&E), and end-of-life processing including radionuclide decontamination.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2018

Major trends and roadblocks in CFD-aided process intensification of biomass pyrolysis

Process intensification is critical to increase product yields and reduce external power consumption in biomass pyrolysis. Computational fluid dynamics offers great possibilities for fast and economical process intensification of biomass pyrolysis. This succinct but in-depth current-perspective feature article discusses the major trends and roadblocks with respect to CFD-aided process intensification of biomass pyrolysis. Major trends such as multiscale coupling, fast parametric analysis and design, and coupling between CFD and process modeling, are reviewed. Major roadblocks such as lack of accurate chemical kinetics, and difficulty in accurate description of microstructural change, are pointed out. In conclusion, it is believed that the clarification of these directions and problems will lead to a more objective but efficient application of CFD to process intensification of biomass pyrolysis.

09 BIOMASS FUELS↗
DOE OSTI2022

Data-driven simultaneous process optimization and adsorbent selection for vacuum pressure swing adsorption

Technologies for post-combustion carbon capture are essential for the reduction of greenhouse gas emissions to the atmosphere. However, they are still associated with high costs and energy consumption. Intensified processes for carbon capture have the potential to overcome these challenges due to their higher efficiency, lower capital cost, and increased operational flexibility. Here, this work investigates simultaneous optimization of process conditions and adsorbent selection for a modular Vacuum Pressure-Swing Adsorption system designed for CO 2 capture. Both surrogate-based Nonlinear Programming and Mixed-Integer Nonlinear Programming approaches are applied and compared in terms of computational efficiency and solution accuracy. Moreover, process performance results are examined by applying several data analytics techniques to gain insights into the material-process correlations. Data-driven classifiers and neural networks can accurately predict whether a material is likely to satisfy purity, recovery, and energy constraints when operated at optimal process conditions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

Sustainable network design for multi-purpose pellet processing depots under biomass supply uncertainty

This work develops a two-stage stochastic mixed-integer programming model to manage multi- purpose pellet processing depots under feedstock supply uncertainty. The proposed optimization model would help to minimize cost and to mitigate emissions from the supply chain network. We consider three alternative Biomass Processing and Densi cation Depot (BPDD) technologies; namely, conventional pellet processing, high moisture pellet processing, and ammonia ber expansion. These three technologies pre-process/pre-treat and densify different types of biomass into more highly densi ed intermediate products for different markets in order to improve movability and overall supply network performance in terms of costs and emissions. A hybrid decomposition algorithm was developed that combines sample average approximation with an enhanced Progressive Hedging (PH) algorithm to solve this challenging NP -hard problem. Some heuristics such as Rolling Horizon (RH) heuristic, variable xing technique were later applied to further enhance the PH algorithm. Mississippi and Alabama were selected as a testing ground and ArcGIS was employed to visualize and validate the modeling results. The results of the analysis reveal promising insights that could lead to recommendations to help decision makers achieve a more cost-effective environmentally-friendly supply chain network.

09 BIOMASS FUELS↗
DOE OSTI2024

A numerical study of process complexity in permafrost dominated regions

Numerical modeling of permafrost dynamics requires adequate representation of atmospheric and surface processes, a reasonable parameter estimation strategy, and site-specific model development. The three main research objectives of the study are: (i) to propose a novel methodology that determines the required level of surface process complexity of permafrost models by conducting parameter sensitivity and calibration, (ii) to design and compare three numerical models of increasing surface process complexity, and (iii) to calibrate and validate the numerical models at the Yakou catchment on the Qinghai-Tibet Plateau as an exemplary study site. The calibration was carried out by coupling the Advanced Terrestrial Simulator (numerical model) and PEST (calibration tool). Simulation results showed that (i) A simple numerical model that considers only subsurface processes can simulate active layer development with the same accuracy as other more complex models that include surface processes. (ii) Peat and mineral soil layer permeability, Van Genuchten alpha, and porosity are highly sensitive. (iii) Liquid precipitation aids in increasing the rate of permafrost degradation. (iv) Deposition of snow insulated the subsurface during the thaw initiation period. We have developed and released an integrated code that couples the numerical software ATS to the calibration software PEST. The numerical model can be further used to determine the impacts of climate change on permafrost degradation.

Calibration↗
DOE OSTI2024

Review of allanite: Properties, occurrence and mineral processing technologies

Allanite is commonly encountered as an accessory rare-earth silicate mineral in association with minerals such as garnet, biotite, and feldspar. It is distributed globally and occurs in igneous formations such as granites, pegmatites, and syenites, as well as in various metamorphic rocks such as schist, gneiss, and amphibolite. Moreover, it can be found in mineral veins formed through hydrothermal activity. While allanite has not yet been extensively utilized for the production of rare-earth elements, recent discoveries of high-grade rare-earth-rich allanite deposits in Wyoming, USA, highlight its economic potential. However, despite ongoing research on the mineralogy and processing of rare-earth minerals, allanite has not received widespread attention in mineral processing. To achieve economical extraction of rare-earth elements from allanite in the future, systematic studies on processing techniques (e.g., density separation, magnetic separation, flotation, leaching) are imperative to fully unlock the potential of allanite as a rare-earth element source. To pave the way for future investigation of allanite and address the unique processing challenges, this review article aims to comprehensively summarize previous studies, encompassing properties, occurrences, and processing technologies of allanite.

42 ENGINEERING↗