Search NASA⌕ Search

SEARCH · Search NASA

Results for “Streaming Analysis”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,441 records · Page 80

Opportunities for Hybrid Wind and Solar PV Plants in India

The share of variable renewable energy (VRE) on India's grid has surpassed 100 GW, and the government has ambitious plans reach 450 GW by 2030. One strategy to increase wind and solar PV deployment is through the co-location of wind and solar PV plants to form a single hybrid power plant. Hybrid plants have the potential to reduce transmission infrastructure costs and variability in the output power profile compared to a standalone plant with a single technology, and this resource analysis aims to take a first step towards quantifying the potential savings from hybridizing wind and solar PV plants in India and the size of this opportunity. We utilize a brute-force optimization to minimize the levelized cost of energy (LCOE) for standalone wind, standalone solar PV, and hybrid wind/solar PV plants across all of India. By comparing these LCOEs, we determine that locations where hybrid plants exhibit potential cost savings and grid benefits exhibit both; a high interconnection cost and; a wind capacity factor between roughly 34% and 38%. However, because our work does not capture the value of the electricity generated by looking at energy prices, nor does it quantify the potential of hybrids to provide other value streams such as firm capacity and reserves. Further, because the work does not compare solar PV and wind hybrids to alternative generation technologies or storage systems, it cannot be considered a holistic cost-benefit analysis.

14 SOLAR ENERGY↗

Assessing the cumulative effects of nearshore habitat restoration actions for multiple populations of juvenile salmon in Whidbey Basin, Washington: foundation and approach for synthesis and evaluation

Ecosystem restoration is a common tool for re-establishing ecosystem processes, structures, and functions to improve biodiversity and services in coastal and estuarine ecosystems. In the Salish Sea, salmon habitats have been fragmented, reduced in size, and diminished in quality, and the ecosystem processes that form and sustain these habitats have been degraded and disrupted as well. This loss is especially prevalent in estuaries, where up to 90% of former salmon habitat has been lost or compromised. Salmon species are integral to the identities and cultures of people in the Pacific Northwest, yet salmon abundances remain at historic lows, especially in urbanized areas. Recent investments in restoration are creating rearing habitat and repairing lost ecosystem function. However, restoration efforts in this region have largely proceeded at the site scale, with less attention to big-picture thinking regarding how restoration will effectively recover degraded or lost habitats for target species. As a result, no landscape-scale evaluation program exists, and the cumulative benefits of multiple interventions are unknown. We describe innovative methods for science synthesis related to the evaluation of cumulative effects of ecosystem restoration for Pacific salmon, using years of existing, but disparate data. Building from previous work on cumulative effects evaluation and incorporating a hierarchy of hypotheses approach, we propose using causal inference across numerous hypotheses in a framework to assess the cumulative benefits to Pacific salmon from multiple estuarine restoration projects. We present the framework as a method that can be used to address many complex questions and provide examples from the Salish Sea where the approach is being implemented. The framework draws on science synthesis from numerous fields and uses a hierarchy of hypotheses, causal analysis at multiple scales, and a new hierarchy of synthesis for assessing multiple lines of evidence documenting restoration effects on Pacific salmon. We propose causal inference to synthesize dissimilar data streams, in our case, to identify various manifestations of cumulative effects of restoration and benefits to salmon, and to further inform restoration and recovery planning. A unifying framework would allow for the detection of thresholds at which restoration provides measurable improvement and would greatly advance understanding of the effects of restoration on ecosystems.

59 BASIC BIOLOGICAL SCIENCES↗

Development of CFD Flow Analysis for Nuclear Facility Ventilation Systems

Understanding and modeling of particulate transport has importance related to safety in ventilated environments that contain hot cells, gloveboxes, and fume hoods. In particular, good modeling of the airflow in these spaces is required to understand areas of stagnation where particles drop out of the free stream and accumulate. This accumulation of particulate can cause either contamination and/or higher than acceptable local dose levels. It is known that multiple sites across the DOE complex take credit for hot cells, gloveboxes, and/or hoods in their safety basis for providing a defense-in-depth benefit for both onsite and offsite releases. By providing confinement of radioactive materials, such features serve to reduce direct doses to facility workers and mitigate the consequences to the environment due to an uncontrolled release. Each of these features has access points that interface with the personnel space. Understanding how air flow behaves at these access points is of great interest to those performing hazard analysis. Computational Fluid Dynamics (CFD) can be used to analyze and model the flows in hot cells and glove boxes as a way to confirm operation. While CFD capability continues to advance, there are still important modeling assumptions that are left to the analyst's discretion. These are most notably the choice of the turbulence models, mesh structure, and wall boundary condition assumptions used in the model. In this work, we apply CFD in modeling airflow through an occupiable work area of the Alpha Gamma Hot Cell Facility (AGHCF) at Argonne National Laboratory (ANL). This modeling is then compared to field test data to both inform and verify the modeling assumptions. Based on the results of field tests, modeling assumptions and boundary conditions are refined and the process is repeated until the results are found to be reliable with a high level of confidence.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Automated Performance Characterization of DSN System Frequency Stability Using Spacecraft Tracking Data

This software provides an automated capability to measure and qualify the frequency stability performance of the Deep Space Network (DSN) ground system, using daily spacecraft tracking data. The results help to verify if the DSN performance is meeting its specification, therefore ensuring commitments to flight missions; in particular, the radio science investigations. The rich set of data also helps the DSN Operations and Maintenance team to identify the trends and patterns, allowing them to identify the antennas of lower performance and implement corrective action in a timely manner. Unlike the traditional approach where the performance can only be obtained from special calibration sessions that are both time-consuming and require manual setup, the new method taps into the daily spacecraft tracking data. This new approach significantly increases the amount of data available for analysis, roughly by two orders of magnitude, making it possible to conduct trend analysis with good confidence. The software is built with automation in mind for end-to-end processing. From the inputs gathering to computation analysis and later data visualization of the results, all steps are done automatically, making the data production at near zero cost. This allows the limited engineering resource to focus on high-level assessment and to follow up with the exceptions/deviations. To make it possible to process the continual stream of daily incoming data without much effort, and to understand the results quickly, the processing needs to be automated and the data summarized at a high level. Special attention needs to be given to data gathering, input validation, handling anomalous conditions, computation, and presenting the results in a visual form that makes it easy to spot items of exception/deviation so that further analysis can be directed and corrective actions followed.

Pham, Timothy T.↗

DeepCare: Improving Patient Care using Deep Learning on Electronic Health Records

Coordinating patient care using electronic health records (EHR) data presents an exciting but formidable opportunity in data extraction, analysis and modeling. Traditional methods use a manual feature driven approach to model patients with age, family history and symptoms to predict disease outcomes. We propose a novel approach to model patients based on their streaming electronic health records data combined with information from medical knowledge bases, which has been gained over years of medical research. Using a combination of representation learning and long short term memory (LSTM) networks we plan to model patient evolution over time, leading to more accurate and individualized predictive models for patient’s diseases. Our approach will be transformative in providing critical decision support for patient care, enabling accurate understanding and evolution of diseases in patients.

60 APPLIED LIFE SCIENCES↗

WHONDRS River Corridor Surface Water Metabolites and Geochemistry from Global Sites

This dataset supports a broader study examining the character of organic matter that may be delivered to subsurface sediments via hydrologic exchange. To implement the global survey, free stream sampling kits were provided to interested volunteers throughout the world. Samples were collected with minimal constraints in terms of location, but following strict protocols, and shipped for metabolomic analysis via Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS). In addition, basic geochemistry analyses (e.g., dissolved organic matter concentration) were conducted, standardized photos of each field system were taken, and extensive metadata were captured. Sampling began in 2018 and is ongoing as of 2025. This dataset is comprised of one folders of field photos, one folder of raw Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) data, and one main data folder containing (1) file-level metadata; (2) data dictionary; (3) field metadata; (4) readme; (5) international generic sample number (IGSN) mapping file; (6) field protocol; and (7) a subfolder with sample data. The sample data subfolder contains (1) surface water dissolved organic carbon (DOC, measured as non-purgeable organic carbon, NPOC) data and averages; (2) methods codes; (3) surface water FTICR methods; and (4) a subfolder of 12 Tesla (12T) FTICR-MS data. This folder contains three subfolders, one containing the.xml files, one containing the CoreMS output files, and the other containing instructions and scripts for processing the files in CoreMS (https://github.com/EMSL-Computing/CoreMS). All files are .csv, .pdf, .R, .xml, .html, .Rmd, .py, .cal, .json, .jpg, .jpeg, or .png. For details on how to navigate data packages generated by this project, see https://data.ess-dive.lbl.gov/portals/PNNLRiverCorridorSFA/About.

Biogeochemistry↗

Sensitivity of the latitude of the westerly jet stream to climate forcing

The latitude of the westerly jet stream is influenced by a variety of climate forcings. Their effects often manifest as a tug-of-war between tropical forcing, characterized by tropical upper-tropospheric warming, and polar forcing, with a signature of Antarctic stratospheric cooling or Arctic amplification. Here we present a unified forcing-feedback frame work relating different climate forcings to their forced jet changes, in which the interactions between the westerly jet and synoptic storms are synthesized by a zonal advection feedback, analogous to the feedback framework for assessing climate sensitivity. This framework is supported by a prototype feedback analysis in the atmospheric dynamical core of a climate model with diverse thermal and mechanical forcings. Our analysis indicates that the latitude of a westerly jet is most sensitive to the thermally-induced jet speed changes near the tropopause. The jet shift also displays a larger sensitivity than linearity for the equatorward shift.

atmospheric dynamics, atmospheric variability, cli↗

Automated Performance Characterization of DSN System Frequency Stability Using Spacecraft Tracking Data

This software provides an automated capability to measure and qualify the frequency stability performance of the Deep Space Network (DSN) ground system, using daily spacecraft tracking data. The results help to verify if the DSN performance is meeting its specification, therefore ensuring commitments to flight missions; in particular, the radio science investigations. The rich set of data also helps the DSN Operations and Maintenance team to identify the trends and patterns, allowing them to identify the antennas of lower performance and implement corrective action in a timely manner. Unlike the traditional approach where the performance can only be obtained from special calibration sessions that are both time-consuming and require manual setup, the new method taps into the daily spacecraft tracking data. This new approach significantly increases the amount of data available for analysis, roughly by two orders of magnitude, making it possible to conduct trend analysis with good confidence. The software is built with automation in mind for end-to-end processing. From the inputs gathering to computation analysis and later data visualization of the results, all steps are done automatically, making the data production at near zero cost. This allows the limited engineering resource to focus on high-level assessment and to follow up with the exceptions/deviations. To make it possible to process the continual stream of daily incoming data without much effort, and to understand the results quickly, the processing needs to be automated and the data summarized at a high level. Special attention needs to be given to data gathering, input validation, handling anomalous conditions, computation, and presenting the results in a visual form that makes it easy to spot items of exception/ deviation so that further analysis can be directed and corrective actions followed.

Pham, Timothy T.↗

An Uncertainty Quantification of the Computational Fluid Dynamics Solution to the Modeling of the Contact Point in a Wire-Wrapped Fuel Assembly

An uncertainty quantification and sensitivity analysis of the turbulent flow in a wire-wrapped pin bundle to the contact-point model and the inlet conditions is presented. Three geometries are considered in this work that are an infinitely large bundle (single subchannel with periodic boundary conditions in the stream-wisedirection), a 7-pin bundle and a 19-pin bundle. The response functions of this study are the friction factor, thevorticity and the mixing parameters. The results show that the friction factor is not sensitive to the contact-point model. The vorticity shows a strong dependency to the inclusion of prismatic layers near the wall boundaries. Results for the mixing parameters are inconclusive. A variance-based sensitivity analysis(Sobol indices) indicates that the influence of the contact-point model on the variance of the friction factor decreases when increasing the size of the bundle. Other response functions (vorticity and mixing parameters)show little sensitivity to the size of the bundle.

42 ENGINEERING↗

Neutronics Analysis for ITER Diagnostic Generic Upper Port Plug

This paper presents new results of neutronics analysis performed for the updated design of the ITER Diagnostic Generic Upper Port Plug (DGUPP). Such analysis is performed regularly during the development of the ITER Ports design. Neutronics analysis is an important step in support of the development of ITER components irradiated by 14 MeV neutrons generated in D-T fusion thermonuclear reactions. The neutrons are born in the ITER tokamak plasma chamber and then impinge on the surrounding blanket and port plugs, after that they diffuse through shielding material of vacuum vessel components or could stream through the diagnostic channels and assembly gaps far away from plasma up to the bio-shield and in a small amount beyond it. While ITER machine is in operation it is inaccessible, after the shut-down it is planned to provide personnel access to the Upper Port Inter-Space Structure (UP ISS) behind the Port Plug via the corridors. Neutrons activate the ITER materials and those radioactive materials emit decay gammas during the shut-down causing a Shut-Down Dose Rate (SDDR) field distributed all around the activated materials. Decay gammas could also stream through the void channels. That emphasizes the need for calculation of decay gamma transport in evaluations of SDDR, which is reflected in the use of transport - activation interface code described in Section of Computational Modelling. The assessment of radiation environment (fluxes and SDDR) at DGUPP was focused on the port back-side area of UP ISS, where personnel access is planned along the ISS maintenance corridors. Minimization of SDDR at the front part of the ISS maintenance corridors was the target value for optimization of the DGUPP shielding and analysis of related neutronics effects. Following the dose ALARA (As Low As Reasonably Achievable) principle, every possibility to reduce SDDR should be investigated, emphasizing the importance of this analysis. The challenges of such analysis are inextricably connected with the engineering complexity of the ITER machine, with integration of many diagnostics systems having channels and gaps inside the ITER ports. Those gaps result in radiation streaming and negatively affect the shielding performance of the port plugs. The computational complication is caused by the need to model precisely the ITER geometry and then to run deep penetrating radiation transport in the substantially heterogenic toroidal geometry of ITER large-size tokamak, with 30 m height and diameter of its bio-shield. The whole mass of Upper Port Plug (UPP) could be up to 25 tons and it must be very precisely positioned inside the port opening in blanket and Vacuum Vessel. Facing the engineering challenges for the assembly of DGUPP, there were proposed two Project Change Requests (PCRs) No. 439 and 709 concerning the design updates of UPP/blanket interface and its remote handling.

61 RADIATION PROTECTION AND DOSIMETRY↗

MESA: Message-Based System Analysis Using Runtime Verification

In this paper, we present a novel approach and framework for run-time verication of large, safety critical messaging systems. This work was motivated by verifying the System Wide Information Management (SWIM) project of the Federal Aviation Administration (FAA). SWIM provides live air traffic, site and weather data streams for the whole National Airspace System (NAS), which can easily amount to several hundred messages per second. Such safety critical systems cannot be instrumented, therefore, verification and monitoring has to happen using a nonintrusive approach, by connecting to a variety of network interfaces. Due to a large number of potential properties to check, the verification framework needs to support efficient formulation of properties with a suitable Domain Specific Language (DSL). Our approach is to utilize a distributed system that is geared towards connectivity and scalability and interface it at the message queue level to a powerful verification engine. We implemented our approach in the tool called MESA: Message-Based System Analysis, which leverages the open source projects RACE (Runtime for Airspace Concept Evaluation) and TraceContract. RACE is a platform for instantiating and running highly concurrent and distributed systems and enables connectivity to SWIM and scalability. TraceContract is a runtime verication tool that allows for checking traces against properties specified in a powerful DSL. We applied our approach to verify a SWIM service against several requirements.We found errors such as duplicate and out-of-order messages.

Message-based System↗

Synthetic Methanol/Fischer–Tropsch Fuel Production Capacity, Cost, and Carbon Intensity Utilizing CO 2 from Industrial and Power Plants in the United States

Captured CO 2 is a potential feedstock to produce fuel/chemicals using renewable electricity as the energy source. In this study, we explored resource availability and synergies by region in the United States and conducted cost and environmental analysis to identify unique opportunities in each region to inform possible regional and national actions for carbon capture and utilization development. This study estimated production cost of synthetic methanol and Fischer–Tropsch (FT) fuels by using CO 2 captured from the waste streams emitted from six industrial [ethanol, ammonia, natural gas (NG) processing, hydrogen, cement, and iron/steel production plants] and two power generation (coal and NG) processes across the United States. The results showed that a total of 1594 million metric ton per year of waste CO 2 can be captured and converted into 85 and 319 billion gallons of FT fuels and methanol, respectively. FT fuels can potentially substitute for 36% of the total petroleum fuels used in the transportation sector in 2018. Technoeconomic analysis shows that the minimum selling prices for synthetic FT fuels and methanol are 1.8–2.8 times the price of petroleum fuel/chemicals, but the total CO 2 reduction potential is 935–1777 MMT/year.

54 ENVIRONMENTAL SCIENCES↗

Expanded Analysis of Hot Isostatic Pressed Iodine-Loaded Silver-Exchanged Mordenite

Reduced silver-exchanged mordenite (Ag0Z) is being evaluated as a potential material to control the release of radioactive iodine that is released during the reprocessing of used nuclear fuel into the plant off-gas streams. The purpose of this study was to determine if hot pressing could directly convert this iodine loaded sorbent into a waste form suitable for long-term disposition. The minimal pretreatment required for production of pressed pellets makes hot pressing a technically and economically desirable process. Initial scoping studies utilized hot uniaxial pressing (HUPing) to prepare samples of non-iodine-loaded reduced silver exchanged mordenite (Ag0Z). The resulting samples were very fragile due to the low pressure (~ 28 MPa) used. It was recommended that hot isostatic pressing (HIPing), performed at higher temperatures and pressures, be investigated. HIPing was carried out in two phases, with a third and final phase currently underway. Phase I evaluated the effects of pressure and temperature conditions on the manufacture of a pressed sample. The base material was an engineered form of silver zeolite. Six samples of Ag0Z and two samples of I-Ag0Z were pressed. It was found that HIPing produced a pressed pellet of high density. Analysis of each pressed pellet by scanning electron microscopy-energy dispersive spectrophotometry (SEM-EDS) and X-ray diffraction (XRD) demonstrated that under the conditions used for pressing, the majority of the material transforms into an amorphous structure. The only crystalline phase observed in the pressed Ag0Z material was SiO2. For the samples loaded with iodine (I-Ag0Z) iodine was present as AgI clusters at low temperatures, and transformed into AgIO4 at high temperatures. Surface mapping and EDS demonstrate segregation between silver iodide phases and silicon dioxide phases. Based on the results of the Phase I study, an expanded test matrix was developed to examine the effects of multiple source materials, compositional variations, and an expanded temperature range. Each sample was analyzed with the approach used in Phase I. In all cases, there is nothing in the SEM or XRD analyses that indicates creation of any AgI-containing silicon phase, with the samples being found to be largely amorphous. Phase III of this study has been initiated and is the final phase of scoping tests. It will expand upon the test matrix completed in Phase II and will examine the durability of the pressed pellets through product consistency testing (PCT) studies. Transformation of the component material into a well-characterized iodine-containing mineral phase would be desirable. This would limit the additional experimental testing and modeling required to determine the long-term stability of the pressed pellet, as much of that information has already been learned for several common iodine-containing minerals. However, this is not an absolute requirement, especially if pellets produced by hot isostatic pressing can be demonstrated through initial PCT studies to retain iodine well despite their amorphous composition.

hot isostatic pressing↗

Predicting properties of gas and solid streams by intrinsic kinetics of fast pyrolysis of wood

Pyrolysis has the potential to create a biocrude oil from biomass sources that can be used as fuel or as feedstock for subsequent upgrading to hydrocarbon fuels or other chemicals. The product distribution/composition, however, is linked to the biomass source. This work investigates the products formed from pyrolysis of woody biomass with a previously developed chemical kinetics model. Different woody feedstocks reported in prior literature are placed on a common basis (moisture, ash, fixed carbon free) and normalized by initial elemental composition through ultimate analysis. Observed product distributions over the full devolatilization range are explored, reconstructed by the model, and verified with independent experimental data collected with a microwave-assisted pyrolysis system. These trends include production of permanent gas (CO, CO 2 ), char, and condensable (oil, water) species. Elementary compositions of these streams are also investigated. As a result, close agreement between literature data, model predictions, and independent experimental data indicate that the proposed model/method is able to predict the ideal distribution from fast pyrolysis given reaction temperature, residence time, and feedstock composition.

09 BIOMASS FUELS↗

Advanced Concept Studies for Supersonic Commercial Transports Entering Service in the 2018-2020 Period Phase 2

Lockheed Martin Aeronautics Company (LM), working in conjunction with General Electric Global Research (GE GR) and Stanford University, executed a 19 month program responsive to the NASA sponsored "N+2 Supersonic Validation: Advanced Concept Studies for Supersonic Commercial Transports Entering Service in the 2018-2020 Period" contract. The key technical objective of this effort was to validate integrated airframe and propulsion technologies and design methodologies necessary to realize a supersonic vehicle capable of meeting the N+2 environmental and performance goals. The N+2 program is aligned with NASA's Supersonic Project and is focused on providing system level solutions capable of overcoming the efficiency, environmental, and performance barriers to practical supersonic flight. The N+2 environmental and performance goals are outlined in the technical paper, AIAA-2014-2138 (Ref. 1) along with the validated N+2 Phase 2 results. Our Phase 2 efforts built upon our Phase 1 studies (Ref. 2) and successfully demonstrated the ability to design and test realistic configurations capable of shaped sonic booms over the width of the sonic boom carpet. Developing a shaped boom configuration capable of meeting the N+2 shaped boom targets is a key goal for the N+2 program. During the LM Phase 1 effort, LM successfully designed and tested a shaped boom trijet configuration (1021) capable of achieving 85 PLdB under track (forward and aft shock) and up to 28 deg off-track at Mach 1.6. In Phase 2 we developed a refined configuration (1044-2) that extended the under 85 PLdB sonic boom level over the entire carpet of 52 deg off-track at a cruise Mach number of 1.7. Further, the loudness level of the configuration throughout operational conditions calculates to an average of 79 PLdB. These calculations rely on propagation employing Burger's (sBOOM) rounding methodology, and there are indications that the configuration average loudness would actually be 75 PLdB. We also added significant fidelity to the design of the configuration in this phase by performing a low speed wind tunnel test at our LTWT facility in Palmdale, by more complete modelling of propulsion effects in our sonic boom analysis, and by refining our configuration packaging and performance assessments. Working with General Electric, LM performed an assessment of the impact of inlet and nozzle effects on the sonic boom signature of the LM N+2 configurations. Our results indicate that inlet/exhaust streamtube boundary conditions are adequate for conceptual design studies, but realistic propulsion modeling at similar stream-tube conditions does have a small but measurable impact on the sonic boom signature. Previous supersonic transport studies have identified aeroelastic effects as one of the major challenges associated with the long, slender vehicles particularly common with shaped boom aircraft (Ref. 3). Under the Phase 2 effort, we have developed a detailed structural analysis model to evaluate the impact of flexibility and structural considerations on the feasibility of future quiet supersonic transports. We looked in particular at dynamic structural modes and flutter as a failure that must be avoided. We found that for our N+2 design in particular, adequate flutter margin existed. Our flutter margin is large enough to cover uncertainties like large increases in engine weight and the margin is relatively easy to increase with additional stiffening mass. The lack of major aeroelastic problems probably derives somewhat from an early design bias. While shaped boom aircraft require long length, they are not required to be thin. We intentionally developed our structural depths to avoid major flexibility problems. So at the end of Phase 2, we have validated that aeroelastic problems are not necessarily endemic to shaped boom designs. Experimental validation of sonic boom design and analysis techniques was the primary objective of the N+2 Supersonic Validations contract; and in this Phase, LM participated in four high speed wind tunnel tests. The first so-called Parametric Test in the Ames 9x7 tunnel did an exhaustive look at variation effects of the parameters: humidity, total pressure, sample time, spatial averaging distance and number of measurement locations, and more. From the results we learned to obtain data faster and more accurately, and made test condition tolerances easy to meet (eliminating earlier 60 percent wasted time when condition tolerances could not be held). The next two tests used different tunnels. The Ames 11 ft tunnel was used to test lower Mach numbers of 1.2 and 1.4. There were several difficulties using this tunnel for the first time for sonic boom including having to shift the measurement Mach numbers to 1.15 and 1.3 to avoid flow problems. It is believed that the 11 ft could be used successfully to measure sonic boom but there are likely to be a number of test condition restrictions. The Glenn 8x6 ft tunnel was used next and the tunnel has a number of desirable features for sonic boom measurement. While the Ames 9x7 can only test Mach 1.55 to 2.55 and the 11 ft can only test Mach 1.3 and lower, the Glenn 8x6 can test continuously from Mach 0.3 to 2.0. Unfortunately test measurement accuracy was compromised by a reference pressure drift. Post-test analysis revealed that the drift occurred when Mach number drifted slightly. Test measurements indicated that if Mach number drift is eliminated, results from the 8x6 would be more accurate, especially at longer distances, than results from the 9x7. The fourth test in the 9x7, called LM4, used everything we learned to comprehensively and accurately measure our new 1044-02 configuration with a full-carpet shaped signature design. Productivity was 8 times greater than our Phase 1 LM3 test. Measurement accuracy and repeatability was excellent out to 42 in. However, measurements at greater distances require the rail in the aft position and become substantially less accurate. Further signature processing or measurement improvements are needed for beyond near-field signature validation.

Morgenstern, John↗

Contaminant Investigation and Pre‐Processing Opportunities for Textile‐To‐Textile Recycling

Millions of metric tons of textiles are landfilled or incinerated each year in the United States, with less than 1% of textiles recycled into new clothing or fabrics. To counter this trend, a growing number of companies and researchers are exploring how a circular economy can be applied to support textile‐to‐textile recycling. A significant barrier they face comes down to quickly and efficiently extracting pure feedstock material from post‐consumer garments that feature a mix of natural and synthetic fibers. Textile recyclers prefer pure feedstocks, as working with mixed sources typically means lower throughput, higher risk of equipment failure, and diminished business margins. To facilitate a circular economy for textiles, methods, and technologies are needed that can efficiently separate out materials and contaminants from end‐of‐life textiles to increase the flow of pure feedstocks to recyclers. This paper summarizes findings from interviews with a cross section of textile recyclers and from a review of literature to define basic feedstock requirements. In addition to our qualitative research, we deconstruct a bale of post‐consumer textiles and analyze them using computer‐vision imaging, Fourier transform infrared spectroscopy (FTIR), and machine learning. The resulting data are used to set system‐level design inputs for an automated contaminant removal system to process post‐consumer clothing into appropriate feedstocks for recycling. To set the system's levels for automated real‐time near‐infrared analysis, we identify the minimum percentage of primary material that any single garment in a load of used clothing must contain for the average of the full output stream to meet the target purity levels of recyclers. Here, the envisioned automated system can also address undesirable trace materials that might contaminate the processed stream by using imaging cameras coupled with artificial intelligence to identify sections of clothing for de‐trimming. Proof‐of‐concept machine learning algorithms are evaluated to locate and identify trims or garment areas with hidden contaminant materials. Integrating these methods into automated textile cutting systems can provide a cost‐effective means for increasing feedstock purity from used clothing, which can advance circularity for textiles by helping recyclers to reach production volumes and quality targets that were not possible solely with manual dismantling operations.

Parsons, Ryan [Rochester Institute of Technology, ↗

Advances and challenges in computational fluid dynamics of atmospheric pressure plasmas

Atmospheric pressure plasmas (APPs) are at the core of diverse technological applications in materials processing, chemical synthesis, resource recovery, water treatment, and medicine, among others. APPs span a wide range of power density, from low-power non-thermal to high-power thermal discharges, and typically involve interactions with a stream of working gas, processing material, or gas environment. The article provides an overview of Computational Fluid Dynamics (CFD) approaches, from mathematical models to software strategies, for the analysis of APP flows. Its focus is flows with large variations in ionization degree and significant fluid dynamic-thermal-electromagnetic coupling, as particularly found in mid- to high-power discharges. The advances achieved and challenges faced by CFD of APP flows have been driven by established and emerging applications, and can be broadly characterized in terms of model fidelity and numerical accuracy. Fidelity refers to the degree of underlying phenomena captured by the model, whereas accuracy to the precision of the numerical solution of the model. Two distinct numerical accuracy challenges are addressed: the capture of instability and pattern formation phenomena, and of plasma-gas interaction and turbulence; as well as two representative fidelity challenges: radiative transport under nonequilibrium conditions, and nonequilibrium electron and particle kinetics. The purpose of this article is to offer guidance to researchers, from modelers and code developers to open-source and commercial software users, working on CFD analyses of APP flows within technological contexts.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Defining a Metric Space of Host Logs and Operational Use Cases

Host logs, in particular, Windows Event Logs, are a valuable source of information often collected by security operation centers (SOCs). The semi-structured nature of host logs inhibits automated analytics, and while manual analysis is common, the sheer volume makes manual inspection of all logs impossible. Although many powerful algorithms for analyzing time-series and sequential data exist, utilization of such algorithms for most cyber security applications is either infeasible or requires tailored, research-intensive preparations. In particular, basic mathematic and algorithmic developments for providing a generalized, meaningful similarity metric on system logs is needed to bridge the gap between many existing sequential data mining methods and this currently available but under-utilized data source. In this paper, we provide a rigorous definition of a metric product space on Windows Event Logs, providing an embedding that allows for the application of established machine learning and time-series analysis methods. We then demonstrate the utility and flexibility of this embedding with multiple use-cases on real data: (1) comparing known infected to new host log streams for attack detection and forensics, (2) collapsing similar streams of logs into semantically-meaningful groups (by user, by role), thereby reducing the quantity of data but not the content, (3) clustering logs as well as short sequences of logs to identify and visualize user behaviors and background processes over time. Overall, we provide a metric space framework for general host logs and log sequences that respects semantic similarity and facilitates a wide variety of data science analytics to these logs without data-specific preparations for each.

Verma, Miki↗