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At least 163 records · Page 9

Be-10 in terrestrial bauxite and industrial aluminum: An LDEF fallout

Work has continued on the search for Be-10 on metals other than aluminum flown on LDEF. Much time-consuming extractive chemistry has been performed at Rutgers University on turnings obtained from the ends of two stainless steel trunnions from LDEF and the prepared samples will be run on the University of Pennsylvania accelerator mass spectrometer. We have continued to investigate our discovery of naturally-occurring Be-10 contamination in bauxite and industrial aluminums from different sources. Measurements of Be-10 in ores from three different sites, and from four different samples of commercial aluminum have been made. Our investigators indicate that the contamination in commercial aluminum metal originates in its principal ore, bauxite. The levels in some bauxite samples were much greater than the maximum possible for in situ production by cosmic ray secondaries. Absorption of atmospheric Be-10 by surface ores exposed to rainfall is a reasonable explanation.

Gregory, J. C.↗

Challenges in the Use of AI-Driven Non-Destructive Spectroscopic Tools for Rapid Food Analysis

Routine, remote, and process analysis for foodstuffs is gaining attention and can provide more confidence for the food supply chain. A new generation of rapid methods is emerging both in the literature and in industry based on spectroscopy coupled with AI-driven modelling methods. Current published studies using these advanced methods are plagued by weaknesses, including sample size, abuse of advanced modelling techniques, and the process of validation for both the acquisition method and modelling. This paper aims to give a comprehensive overview of the analytical challenges faced in research and industrial settings where screening analysis is performed while providing practical solutions in the form of guidelines for a range of scenarios. After extended literature analysis, we conclude that there is no easy way to enhance the accuracy of the methods by using state-of-the-art modelling methods and the key remains that capturing good quality raw data from authentic samples in sufficient volume is very important along with robust validation. A comprehensive methodology involving suitable analytical techniques and interpretive modelling methods needs to be considered under a tailored experimental design whenever conducting rapid food analysis.

59 BASIC BIOLOGICAL SCIENCES↗

Modified MEE Industries static thermal gradient diffusion cloud chamber

The experiments performed at the Workshop were undertaken to confirm the calculated sample volume, determine the usable range of supersaturation, and minimum detectable size. Comparison of absolute CCN concentrations with other state-of-the-art continuous flow diffusion chambers at supersaturations near 1 percent indicated that the volume used produced CCN concentrations well within the range of CCN concentrations determined at the workshop. This agreement is interpreted to mean the sample volume was correct. Direct measurements of the beam geometry done in the laboratory indicated a factor of 4-5 error. This error is apparently due to the larger apparent visible beam diameter versus the actual usable beam diameter given the droplet illumination, chamber optical geometry, microscope optics and film characteristics.

Borys, R. D.↗

Deciphering Degradation: Machine Learning on Real-World Performance Data (Final Report)

This project addresses a fundamental flaw in solar PV research and solar project financing; the assumed rate of degradation for solar plants. The solar industry currently relies on an out-dated report that observed a 0.5% degradation rate based on a small sample size of systems (~100). While the research conducted at the time was new and innovative, the solar community has not updated this research and universally applies this 0.5% degradation assumption in financial models. Our project updates this assumption by analyzing observed degradation from the industry’s largest dataset of operating solar assets (>10,000 systems) and creating the first machine-learning model based on these observed results to quantify and identify features that drive degradation. There are two strategic goals for this award: reduce the cost of capital (enable solar to attract more capital) and improve the reliability of solar itself. These dual goals are achieved by leveraging an industry dataset to observe system degradation on a large scale, deploying advanced data analysis and machine learning methods to quantify and predict system reliability, and engaging with industry stakeholders to help them accurately price degradation in financial models.

14 SOLAR ENERGY↗

Lamb Wave Response of Fatigued Composite Samples

Composite materials are being more widely used today by aerospace, automotive, sports equipment, and a number of other commercial industries because of their advantages over conventional metals. Composites have a high strength-to-weight ratio and can be constructed to meet specific design needs. Composite structures are already in use in secondary parts of the Douglas MD-11 and are planned to be used in the new MD-12X. Plans also exist for their use in primary and secondary structures on the Boeing 777. Douglas proposed MD-XX may also incorporate composite materials into primary structures such as the wings and tail. Use of composites in these structures offers weight savings, corrosion resistance, and improved aerodynamics. Additionally, composites have been used to repair cracks in many B-1Bs where traditional repair techniques were not very effective. Plans have also been made to reinforce all of the remaining B-1s with composite materials. Verification of the structural integrity of composite components is needed to insure safe operation of these aerospace vehicles. One aspect of the use of these composites is their response to fatigue. To track this progression of fatigue in aerospace structures, a convenient method to nondestructively monitor this damage needs to be developed. Traditional NDE techniques used on metals are not easily adaptable to composites due to the inhomogeneous and anisotropic nature of these materials. Finding an effective means of nondestructively monitoring fatigue damage is extremely important to the safety and reliability of such structures. Lamb waves offer one method of evaluating these composite materials. As a material is fatigued, the modulus degrades. Since the Lamb wave velocity can be related to the modulus of the material, an effective tool can be developed to monitor fatigue damage in composites by measuring the velocity of these waves. In this work, preliminary studies have been conducted which monitor fatigue damage in composite samples using strain gage measurements as well as Lamb wave velocity measurements. A description of the test samples is followed by the results of two different measurements of Lamb wave velocity. The first technique is a contact measurement done at a single frequency, while the second involves an immersion study of Lamb waves in which dispersion curves are obtained. The results of the Lamb wave monitoring of fatigue damage is compared to the damage progression measured by strain gages. The final section discusses the results and conclusions.

Seale, Michael↗

Sewage Treatment Plant #1 Area, SWMU 117 Per- and Polyfluoroalkyl Substances (PFAS) Site Assessment Progress Report

This Per- and Polyfluoroalkyl Substances (PFAS) Site Assessment (SA) Progress Report (SAPR) discusses the investigation activities and findings for the Sewage Treatment Plant #1 (STP1) Area located at Kennedy Space Center (KSC), Florida (Figure 1-1). This site has been designated Solid Waste Management Unit (SWMU) 117 under KSC’s Resource Conservation and Recovery Act (RCRA) Corrective Action Program, as the sewage treatment plant and associated areas were identified as a potential source of PFAS to the environment. This PFAS SAPR was prepared by Tetra Tech, Inc., for the National Aeronautics and Space Administration (NASA) under Indefinite Delivery Indefinite Quantity Contract 80KSC019D0011-80KSC019F0070. This is the first progress report to document on-going SA activities; supplemental progress reports will be provided as additional data is collected. PFAS SA activities were conducted between April 2020 and March 2022 to collect additional data to supplement the existing datasets to better understand the extent of PFAS impacts to the environment in the STP1 Area. The SA for the STP1 Area covers an approximately 130-acre investigation area with multiple structures and buildings. The focus of the SA is the STP1 Complex and associated structures, including the former Polishing Pond, former Sludge Disposal8 Area, and former Spray Field. The STP1 Complex is located in the KSC Industrial Area, at the southwest corner of 4th Street SE and C Avenue SE. The STP1 Complex is located approximately ¼-mile south and downgradient of the Fire Station #1 site (SWMU 116), which is also currently undergoing a PFAS SA because of potential releases of PFAS-containing aqueous film-forming foam (AFFF). During the SA, a total of seven soil, 131 groundwater direct push technology (DPT), 24 groundwater monitoring well, and 11 surface water samples were collected between April 2020 and March 2022. Monitoring well samples were analyzed for 18 PFAS compounds, with all other samples analyzed for 28 PFAS compounds. The SA sample results were used along with historical results to evaluate the extent of PFAS impacts to the environment in the STP1 Area. Data generated to date and prior results were screened against the United States Environmental Protection Agency (USEPA) May 2022 Tap Water Regional Screening Levels (RSL) for groundwater and residential RSLs for soil (hazard quotient of 0.1). Surface water results were screened against the State of Florida Human Health Surface Water Screening Levels (SWSLs). Results from the SA showed exceedances of the applicable screening criteria for groundwater and surface water. Considering the current and historical dataset, PFOS is the prevalent PFAS compound. Based on these results, additional groundwater DPT and surface water sampling should be considered for PFAS analysis, focused on evaluating surface water bodies in the southeast portion of the Industrial Area, which discharge into the Banana River. Additionally, installation of monitoring wells should be considered to evaluate the interaction between the groundwater and surface water at the site. Collection of additional samples for TOC analysis should also be considered from representative groundwater (saturated soils) and surface water locations to further evaluate potential correlations between PFAS and TOC to provide a more comprehensive dataset to assist in fate and transport analyses.

Sewage Treatment Plant↗

MODELING AND METHOD FOR OPTICAL PERFORMANCE OF A RECEIVER COATING AND ITS DEGRADATION DUE TO OPERATION

The optical properties of the coating used on a concentrated solar power (CSP)’s receiver directly impact the performance of the power plant. Receiver coatings are designed to absorb as much heat as possible and transfer it to the circulating fluid. Over time, the absorptivity of the receiver coating degrades due to environmental and operational conditions. This project aims to (1) create a test apparatus that allows coatings to undergo accelerated lifetime testing under conditions that mimic what the coating will experience on-tower; and (2) develop a mathematical model that based on the test data predicts absorptivity over time. To create the mathematical model, samples of BrightSource Energy’s Gen1 and Gen2 coatings were tested first looking at individual failure modes (such as high temperature cycling) and then for combined failure modes in the newly developed apparatus. In addition to taking optical measurements, the samples were destroyed to allow for metalogical evaluation to understand what was happening on a microscopic level. Pre-existing models from the literature that describe accelerated testing as well as individual phenomena observed in the coating were then combined to create the model. Additionally, the Gen2 and Gen3 coatings are being testing at the Plataforma Solar de Almería (PSA) facility in Almeria, Spain to confirm that the apparatus test results are similar to those received on-sun. (PSA’s facility closely mimics on-tower conditions). The goal is to enable industry players to test coatings using the new apparatus, gather absorptivity measurements (without needing to destroy samples), and input the information into the model to determine how the coating will perform over time, thus allowing the optical performance of coatings to be compared even before they are used on-tower. The model will be publicly available by the end of the project (currently projected as December 2024).

14 SOLAR ENERGY↗

Discovering the Regulatory Considerations of the Federal Aviation Administration: Interviewing the Aviation Rulemaking Advisory Committee

Maintenance Resource Management (MRM) training for aviation mechanics has become mandatory in many industrialized countries since 1998. Yet, to date, MRM training remains optional in the U.S. Interestingly, a similar safety discipline, namely Crew/Cockpit Resource Management (CRM), is mandatory for pilots, flight engineers, flight attendants, and dispatchers and is regulated in the Federal Aviation Administration s (FAA) Federal Aviation Regulations (FARs). If MRM training is important to enhance aviation technicians working behavior, the rationale to not regulate it opens a window for study. This research aims to inductively investigate the FAA s regulatory rationale concerning MRM training based on direct inputs from the FAA s Aviation Rulemaking Advisory Committee (ARAC) members. Delphi methodology associated with purposive sampling technique was adopted. The result revealed that the FAA cannot regulate MRM because the aviation industry is strongly opposed to it due to the lack of training budgets, the need of a quantifiable cost-effect analysis, concern over the FAA s inspection workforce, an ongoing voluntary alternative called the Air Transportation Surveillance System (ATOS), the government s lower priority on maintenance after 9/11, and the airlines tight embracement of operational flexibility without regulation.

Lu, Chien-tsung↗

Pre-trained network-based transfer learning: A small-sample machine learning approach to nuclear power plant classification problem

Some research topics belonging to classification problems in the nuclear industry, such as fault diagnosis and accident identification, can be solved by feature extraction and subsequent application of statistical machine learning classifiers. Recently, deep neural network-based methods with automatic feature extraction and high accuracy have gained wide attention. They usually require large-scale training data, however, plant fault or accident data are scarce or difficult to obtain. Here this paper proposes a convolutional network (CNN)-based transfer learning method to solve this problem. The network's shallow layer is derived from a pre-trained CNN based on the ImageNet database to automatically extract features, and the deep layer is customized to match the classification problem. Data in non-image formats are converted to image formats and subsequently used to train the network. Case studies of rotating machines fault diagnosis show that the proposed method requires only limited training data to achieve high accuracy.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Mechanistic insights into N 2 O formation as a side product in NH 3 -SCR over small pore Cu-zeolites

Here, the present contribution provides clarity to N 2 O formation mechanisms and key influencing factors during low temperature NH 3 -SCR, with the goal of enabling the rational design of advanced SCR catalysts with low greenhouse gas impact. By studying more than 50 small pore Cu-exchanged zeolite SCR catalyst samples, including model catalysts synthesized in our laboratories and state-of-the-art industrial catalysts, we explored a wide range of factors affecting N 2 O formation. These factors included Cu loading, support Si/Al ratio, support topology, catalyst aging, reaction temperature and reactant feed composition effects. We probed N 2 O formation under both steady-state SCR, and during NH 4 NO 3 decomposition via temperature programmed desorption (TPD). Finally, we used DFT to probe energetics of possible N 2 O formation pathways. Based on these studies, we confirm that low temperature N 2 O formation occurs via multiple reaction pathways that all involve NH 4 NO 3 and are supported by Cu moieties that facilitate in-situ NO oxidation to NO 2 .

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Application of Quantum Machine Learning to High Energy Physics Analysis at LHC Using Quantum Computer Simulators and Quantum Computer Hardware

Machine learning enjoys widespread success in High Energy Physics (HEP) analyses at LHC. However the ambitious HL-LHC program will require much more computing resources in the next two decades. Quantum computing may offer speed-up for HEP physics analyses at HL-LHC, and can be a new computational paradigm for big data analyses in High Energy Physics.We have successfully employed three methods (1) Variational Quantum Classifier (VQC) method, (2) Quantum Support Vector Machine Kernel (QSVM-kernel) method and (3) Quantum Neural Network (QNN) method for two LHC flagship analyses: ttH (Higgs production in association with two top quarks) and H->mumu (Higgs decay to two muons, the second generation fermions). We shall address the progressive improvements in performance from method (1) to method (3).We will present our experiences and results of a study on LHC High Energy Physics data analyses with IBM Quantum Simulator and Quantum Hardware (using IBM Qiskit framework), Google Quantum Simulator (using Google Cirq framework), and Amazon Quantum Simulator (using Amazon Braket cloud service). The work is in the context of a Qubit platform (a gate-model quantum computer). Taking into account the present limitation of hardware access, different quantum machine learning methods are studied on simulators and the results are compared with classical machine learning methods (BDT, classical Support Vector Machine and classical Neural Network). Furthermore, we do apply quantum machine learning on IBM quantum hardware to compare performance between quantum simulator and quantum hardware. The work is performed by an international and interdisciplinary collaboration with the Department of Physics and Department of Computer Sciences of University of Wisconsin, CERN Quantum Technology Initiative, IBM Research Zurich, IBM T.J. Watson Research Center, Fermilab Quantum Institute, BNL Computational Science Initiative, State University of New York at Stony Brook, and Quantum Computing and AI Research of Amazon Web Services. This work pioneers a close collaboration of academic institutions with industrial corporations in the High Energy Physics analyses effort. Though the size of event samples in future HL-LHC physics and the limited number of qubits pose some challenges to the Quantum Machine learning studies for High Energy Physics, more advanced quantum computers with larger number of qubits, reduced noise and improved running time (as envisioned by IBM and Google) may outperform classical machine learning in both classification power and in speed.Although the era of efficient quantum computing may still be years away, we have made promising progress and obtained preliminary results in applying quantum machine learning to High Energy Physics. A PROOF OF PRINCIPLE.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Automated space processing payloads study. Volume 2, book 2: Technical report, appendices A through E

Experiment hardware and operational requirements for space shuttle experiments are discussed along with payload and system concepts. Appendixes are included in which experiment data sheets, chamber environmental control and monitoring, method for collection and storage of electrophoretically-separated samples, preliminary thermal evaluation of electromagnetic levitation facilities L1, L2, and L3, and applicable industrial automation equipment are discussed.

Source record↗

Consistent Tolerance Bounds for Statistical Distributions

Assumption that sample comes from population with particular distribution is made with confidence C if data lie between certain bounds. These "confidence bounds" depend on C and assumption about distribution of sampling errors around regression line. Graphical test criteria using tolerance bounds are applied in industry where statistical analysis influences product development and use. Applied to evaluate equipment life.

Mezzacappa, M. A.↗

A Sample of NASA Langley Unsteady Pressure Experiments for Computational Aerodynamics Code Evaluation

As computational fluid dynamics methods mature, code development is rapidly transitioning from prediction of steady flowfields to unsteady flows. This change in emphasis offers a number of new challenges to the research community, not the least of which is obtaining detailed, accurate unsteady experimental data with which to evaluate new methods. Researchers at NASA Langley Research Center (LaRC) have been actively measuring unsteady pressure distributions for nearly 40 years. Over the last 20 years, these measurements have focused on developing high-quality datasets for use in code evaluation. This paper provides a sample of unsteady pressure measurements obtained by LaRC and available for government, university, and industry researchers to evaluate new and existing unsteady aerodynamic analysis methods. A number of cases are highlighted and discussed with attention focused on the unique character of the individual datasets and their perceived usefulness for code evaluation. Ongoing LaRC research in this area is also presented.

Schuster, David M.↗

Spinoff 1978

Spinoff '78 is the annual report of NASA's Technology Utilization Program, which is charged with promoting and stimulating the practical application of government-sponsored aerospace technology. The report is organized in three sections: 1) Aerospace Aims; 2) Technology Twice Used; and 3) Technology Utilization. Section 1 outlines NASA's major programs in space exploration, aeronautical research and technology application, and describes the potential benefits of a direct nature that are accruing from these efforts. Section 2 contains a representative sampling of the indirect benefits resulting from the secondary use of aerospace technology in industry and the economy. Section 3 details the nationwide activities of the Technology Utilization Program in encouraging the broadest possible secondary use of new technology emerging from aerospace programs. The latter section also includes a list of regional NASA officials and others who can be contacted by those seeking NASA technical information or assistance.

Haggerty, James J.↗

Pulmonary Toxicity Studies of Lunar Dusts in Rodents

NASA will build an outpost on the lunar surface for long-duration human habitation and research. The surface of the Moon is covered by a layer of fine, reactive dust, and the living quarters in the lunar outpost are expected to be contaminated by lunar dust. Because the toxicity of lunar dust is not known, NASA has tasked its toxicology laboratory to evaluate the risk of exposure to the dust and to establish safe exposure limits for astronauts working in the lunar habitat. Studies of the pulmonary toxicity of a dust are generally done first in rodents by intratracheal/intrapharyngeal instillation. This toxicity screening test is then followed by an inhalation study, which requires much more of the test dust and is labor intensive. Preliminary results obtained by examining lung lavage fluid from dust-treated mice show that lunar dust was somewhat toxic (more toxic than TiO2, but less than quartz dust). More extensive studies are in progress to further examine lung lavage fluid for biomarkers of toxicity and lung tissues for histopathological lesions in rodents exposed to aged and activated (ground) lunar dust samples. In these studies, reference dusts (TiO2 and quartz) of known toxicities and have industrial exposure limits will be studied in parallel so the relative toxicity of lunar dust can be determined. The results from the instillation studies will be useful for choosing exposure concentrations for the animal inhalation study. The animal inhalation exposure will be conducted with lunar dust simulant prior to the study with the lunar dust. The experiment with the simulate will ensure that the study techniques used with actual lunar dust will be successful. The results of instillation and inhalation studies will reveal the toxicological risk of exposures and are essential for setting exposure limits on lunar dust for astronauts living in the lunar habitat.

Lam, Chiu-wing↗

PMA-PhyloChip DNA Microarray to Elucidate Viable Microbial Community Structure

Since the Viking missions in the mid-1970s, traditional culture-based methods have been used for microbial enumeration by various NASA programs. Viable microbes are of particular concern for spacecraft cleanliness, for forward contamination of extraterrestrial bodies (proliferation of microbes), and for crew health/safety (viable pathogenic microbes). However, a "true" estimation of viable microbial population and differentiation from their dead cells using the most sensitive molecular methods is a challenge, because of the stability of DNA from dead cells. The goal of this research is to evaluate a rapid and sensitive microbial detection concept that will selectively estimate viable microbes. Nucleic acid amplification approaches such as the polymerase chain reaction (PCR) have shown promise for reducing time to detection for a wide range of applications. The proposed method is based on the use of a fluorescent DNA intercalating agent, propidium monoazide (PMA), which can only penetrate the membrane of dead cells. The PMA-quenched reaction mixtures can be screened, where only the DNA from live cells will be available for subsequent PCR reaction and microarray detection, and be identified as part of the viable microbial community. An additional advantage of the proposed rapid method is that it will detect viable microbes and differentiate from dead cells in only a few hours, as opposed to less comprehensive culture-based assays, which take days to complete. This novel combination approach is called the PMA-Microarray method. DNA intercalating agents such as PMA have previously been used to selectively distinguish between viable and dead bacterial cells. Once in the cell, the dye intercalates with the DNA and, upon photolysis under visible light, produces stable DNA adducts. DNA cross-linked in this way is unavailable for PCR. Environmental samples suspected of containing a mixture of live and dead microbial cells/spores will be treated with PMA, and then incubated in the dark. Thereafter, the sample is exposed to visible light for five minutes, so that the DNA from dead cells will be cross-linked. Following this PMA treatment step, the sample is concentrated by centrifugation and washed (to remove excessive PMA) before DNA is extracted. The 16S rRNA gene fragments will be amplified by PCR to screen the total microbial community using PhyloChip DNA microarray analysis. This approach will detect only the viable microbial community since the PMA intercalated DNA from dead cells would be unavailable for PCR amplification. The total detection time including PCR reaction for low biomass samples will be a few hours. Numerous markets may use this technology. The food industry uses spore detection to validate new alternative food processing technologies, sterility, and quality. Pharmaceutical and medical equipment companies also detect spores as a marker for sterility. This system can be used for validating sterilization processes, water treatment systems, and in various public health and homeland security applications.

Venkateswaran, Kasthuri J.↗

Background contamination by coplanar polychlorinated biphenyls (PCBs) in trace level high resolution gas chromatography/high resolution mass spectrometry (HRGC/HRMS) analytical procedures

The addition of the "dioxin-like" polychlorinated biphenyl (PCB) congeners to the assessment of risk associated with the 2,3,7,8-chlorine substituted dioxins and furans has dramatically increased the number of laboratories worldwide that are developing analytical procedures for their detection and quantitation. Most of these procedures are based on established sample preparation and analytical techniques employing high resolution gas chromatography/high resolution mass spectrometry (HRGC/HRMS), which are used for the analyses of dioxin/furans at low parts-per-trillion (ppt) levels. A significant and widespread problem that arises when using these sample preparation procedures for the analysis of coplanar PCBs is the presence of background levels of these congeners. Industrial processes, urban incineration, leaking electrical transformers, hazardous waste accidents, and improper waste disposal practices have released appreciable quantities of PCBs into the environment. This contamination has resulted in the global distribution of these compounds via the atmosphere and their ubiquitous presence in ambient air. The background presence of these compounds in method blanks must be addressed when determining the exact concentrations of these and other congeners in environmental samples. In this study reliable procedures were developed to accurately define these background levels and assess their variability over the course of the study. The background subtraction procedures developed and employed increase the probability that the values reported accurately represent the concentrations found in the samples and were not biased due to this background contamination.

Polychlorinated Biphenyls/analysis/metabolism↗