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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 883 records · Page 49
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Boron-10 Doped Polysiloxanes as Matrix Materials for Application in the Simultaneous Detection and Discrimination of Gamma Rays and Fast and Thermal Neutrons

Three boron-10 enriched aromatic molecules have been synthesized and incorporated into two different commercial polysiloxane resins, Shin Etsu KER-6000 and Wacker SilRes H62-C. Scintillating fluorophores, 9,9-dimethyl-2-phenylfluorene (PhF) and 2,5-diphenyloxazole (PPO), were tested in combination with each resin and boron-10 molecule for the simultaneous detection of gamma rays, fast neutrons, and thermal neutrons. Here, the H62-C resin was able to solubilize a large amount of PhF, in excess of 20 wt%. Cure kinetics were controlled through the addition of divinylbenzene and phenyl tris(dimethylsiloxy)silane cross-linker solution to the H62-C resin, with rheology experiments demonstrating a large reduction in time to gelation when 20 wt% cross-linker solution was added, from more than 4 hours to less than 1 hour. These polysiloxane resins can be cured in 3 hours under air, while common poly(vinyltoluene) scintillators require at least 4 days of heating and oxygen-free conditions. PhF-doped KER-6000 with tolyl boronate pinacol ester exhibited the best overall performance with a light yield of 62% relative to EJ-200 and thermal neutron capture at energies up to 103 keVee (84 keVee for EJ254B-5). Additionally, four samples exhibited light yields surpassing an industry-standard boron-doped plastic scintillator, Eljen’s EJ254B-5. Over the course of ten months, the KER-6000 samples showed precipitation of dopant molecules, which reduced their light yield by 15% on average, while H62-C proved to be more stable with only a 6% reduction.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Seeded Stage III glass dissolution behavior of a statistically designed glass matrix

The glass dissolution rate of some glasses accelerates after prolonged time spent at a slow, residual glass dissolution rate. This phenomenon is referred to as Stage III behavior. Here, the acceleration in glass dissolution rate linked to Stage III behavior is significant and may be the most impactful to long-term performance of glass in a repository. This work is aimed at understanding the effect of glass composition on Stage III behavior to add a level of technical defensibility to glass disposal. To this end, a set of twenty-four glass compositions were statistically designed, where eight glass components (SiO 2 , B 2 O 3 , Al 2 O 3 , CaO, Na 2 O, SnO 2 , ZrO 2 , and Others) have been independently varied in order to study the individual effects of each. These glasses have been subjected to static dissolution tests at 90 °C in deionized water and then seeded with zeolite Na-P2 28 days into the testing to induce Stage III behavior. The response of the glasses to the zeolite seeds fell into four primary types: 1) no response to seeds; 2) an immediate linear sustained acceleration in the rate; 3) an immediate linear acceleration in the rate followed by a decrease; and, 4) a progressive acceleration in the rate that is concurrent with the addition of the seeds. The main glass components observed to influence these behaviors were CaO, Al 2 O 3 , B 2 O 3 , and ZrO 2 , where: 1) CaO influenced which glasses showed a Stage III response to seeds (high CaO: Types 2, 3, and 4) or did not respond to seeds (low CaO: Type 1), 2) Al 2 O 3 and B 2 O 3 influenced which glasses showed a sustainable Stage III response (high Al 2 O 3 : Types 2 and 4) versus transitory response (low Al 2 O 3 and high B 2 O 3 : Type 3), and 3) ZrO 2 concentration influenced whether glasses showed a linear (high ZrO 2 : Type 2) versus progressive (low ZrO 2 : Type 4) response to seeds.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Construction of a Code Verification Matrix for Heat Conduction With Finite Element Code Applications

When establishing the pedigree of a simulation tool, code verification is used to ensure that the implemented numerical algorithm is a faithful representation of its underlying mathematical model. During this process, numerical results on various meshes are systematically compared to a reference analytic solution. The selection of analytic solutions can be a laborious process, as it is difficult to establish adequate code confidence without performing redundant work. In this report we address this issue by applying a physics-based process that establishes a set of reference problems. In this process, code simulation options are categorized and systematically tested, which ensures that gaps in testing are easily identified and addressed. The resulting problems are primarily intended for code verification analysis but may also be useful for comparison to other simulation codes, troubleshooting activities, or training exercises. The process is used to select fifteen code verification problems relevant for the one-dimensional steady-state heat conduction equation. These problems are applicable to a wide variety of simulation tools, but, in this work, a demonstration is performed using the finite element-based nuclear fuel performance code BISON. Convergence to the analytic solution at the theoretical rate is quantified for a selection of the problems, which establishes a baseline pedigree for the code. Not only can this standard set of conduction solutions be used for verification of other codes, but also the physics-based process for selecting problems can be utilized to quantify and expand testing for any simulation tool.

42 ENGINEERING↗
DOE OSTI2024

A Microchannel Heat Exchanger Produced From a Metal Matrix Composite by Hybrid Laser Powder Bed Fusion and Inkjet Printing

Abstract This paper explores the production of an oxide dispersion strengthened (ODS) 304L stainless steel microchannel heat exchanger (HX) using a hybrid additive manufacturing process of laser powder bed fusion and inkjet printing. The study investigates the capabilities and economics of the hybrid inkjet-laser powder bed fusion (LPBF) process and evaluates the dimensional accuracy, functionality, and mechanical properties of the resulting ODS alloy. The effectiveness and pressure drop of the ODS heat exchangers produced by the hybrid LPBF tool are also determined. Results show that the inkjet-doped samples have a lower mean channel height with higher standard deviation than samples produced by LPBF alone. This is attributed to greater absorption of laser energy for the powder coated with the oxide precursor. The economic analysis shows that the hybrid process has a potential for reducing the unit cost of the heat exchanger based on cost modeling assumptions.

Engineering↗
DOE OSTI2020

A data-driven approach to sampling matrix selection for compressive sensing

Sampling is a fundamental aspect of any implementation of compressive sensing. Typically, the choice of sampling method is guided by the reconstruction basis. However, this approach can be problematic with respect to certain hardware constraints and is not responsive to domain-specific context. We propose a method for defining an order for a sampling basis that is optimal with respect to capturing variance in data, thus allowing for meaningful sensing at any desired level of compression. We focus on the Walsh-Hadamard sampling basis for its relevance to hardware constraints, but our approach applies to any sampling basis of interest. We illustrate the effectiveness of our method on the Physical Sciences Inc. Fabry-Perot interferometer sensor multispectral dataset, the Johns Hopkins Applied Physics Lab FTIR-based longwave infrared sensor hyperspectral dataset, and a Colorado State University Swiss Ranger depth image dataset. The spectral datasets consist of simulant experiments, including releases of chemicals such as GAA and SF6. We combine our sampling and reconstruction with the adaptive coherence estimator (ACE) and bulk coherence for chemical detection and we incorporate an algorithmic threshold for ACE values to determine the presence or absence of a chemical. We compare results across sampling methods in this context. We have successful chemical detection at a compression rate of 90%. For all three datasets, we compare our sampling approach to standard orderings of sampling basis such as random, sequency, and an analog of sequency that we term `frequency.' In one instance, the peak signal to noise ratio was improved by over 30% across a test set of depth images.

compressive sensing, hyperspectral imaging, Walsh-↗