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DOE OSTI2024

Point-of-use filtration units as drinking water distribution system sentinels

Abstract Municipal drinking water distribution systems (DWDSs) and associated premise plumbing (PP) systems are vulnerable to proliferation of opportunistic pathogens, even when chemical disinfection residuals are present, thus presenting a public health risk. Monitoring the structure of microbial communities of drinking water is challenging because of limited continuous access to faucets, pipes, and storage tanks. We propose a scalable household sampling method, which uses spent activated carbon and reverse osmosis (RO) membrane point-of-use (POU) filters to evaluate mid- to long-term occurrence of microorganisms in PP systems that are relevant to consumer exposure. As a proof of concept, POU filter microbiomes were collected from four different locations and analyzed with 16S rRNA gene amplicon sequencing. The analyses revealed distinct microbial communities, with occasional detection of potential pathogens. The findings highlight the importance of local, and if possible, continuous monitoring within and across distribution systems. The continuous operation of POU filters offers an advantage in capturing species that may be missed by instantaneous sampling methods. We suggest that water utilities, public institutions, and regulatory agencies take advantage of end-of-life POU filters for microbial monitoring. This approach can be easily implemented to ensure drinking water safety, especially from microbes of emerging concerns; e.g., pathogenic Legionella and Mycobacterium species.

42 ENGINEERING↗

NASA NTRS1994

Effects of historical and predictive information on ability of transport pilot to predict an alert

In the aviation community, the early detection of the development of a possible subsystem problem during a flight is potentially useful for increasing the safety of the flight. Commercial airlines are currently using twin-engine aircraft for extended transport operations over water, and the early detection of a possible problem might increase the flight crew's options for safely landing the aircraft. One method for decreasing the severity of a developing problem is to predict the behavior of the problem so that appropriate corrective actions can be taken. To investigate the pilots' ability to predict long-term events, a computer workstation experiment was conducted in which 18 airline pilots predicted the alert time (the time to an alert) using 3 different dial displays and 3 different parameter behavior complexity levels. The three dial displays were as follows: standard (resembling current aircraft round dial presentations); history (indicating the current value plus the value of the parameter 5 sec in the past); and predictive (indicating the current value plus the value of the parameter 5 sec into the future). The time profiles describing the behavior of the parameter consisted of constant rate-of-change profiles, decelerating profiles, and accelerating-then-decelerating profiles. Although the pilots indicated that they preferred the near term predictive dial, the objective data did not support its use. The objective data did show that the time profiles had the most significant effect on performance in estimating the time to an alert.

Trujillo, Anna C.↗

DOE OSTI2024

Autonomous Anomaly Detection for MPC Forecasts of HVAC Systems in Residential Communities

The use of residential heating, ventilation, and air conditioning (HVAC) to shift peak demand or provide ancillary services is a potential solution in the presence of older grids and distributed renewables. However, to ensure the efficient use of devices, utilities need to accurately forecast the load and adopt error correction schemes when necessary. While significant theoretical research exists in the area of predictive control of HVAC, little experimental evidence exists. The lack of experimental data in turn causes researchers to be unprepared for unsystematic errors which emerge due to the higher complexity of the data generating process. This study offers an anomaly detection methodology that uses unsupervised machine learning algorithms to detect and isolate these errors with different forecast error ranges. The results of anomaly detection procedure can then be used for error correction and would eventually help develop better predictive controllers. The methodology is tested using real world data from a smart neighborhood that currently operates in Atlanta. GA.

Lebakula, Viswadeep↗

NASA NTRS2019

Does Seed Sanitization Affect the Plant Rhizosphere Microbiome and Its Ability to Compete with the Human Associated Pathogen, E. coli on Salad Crops?

Cultivation of crops in controlled environmental agricultural systems may limit microbial colonization and reduce diversity of the microbial communities. Practices like seed and growth medium sanitization may further impact microbial communities in the mature plant and the plant’s capacity to limit the growth of pathogens through competition. As humans expand their travels to space, understanding plant growth, health, and development in closed environments will be critical to the success of producing a safe, supplemental food source for astronauts. To determine the persistence of a potential human pathogen in plant growth and development, sanitized and unsanitized seeds from, mizuna (Brassica rapa var japonica) and red romaine lettuce (Lactuca sativa cultivar ‘Outredgeous’), were inoculated with Escherichia coli, ATCC 21445, germinated under simulated International Space Station (ISS) environmental conditions and harvested every 7 days until maturity. The persistence of E. coli in the rhizosphere was determined by plating on selective media, real time PCR (Polymerase Chain Reaction) and community sequencing of the rhizosphere communities. E. coli was detected in the crops’ roots and leaves for several weeks post germination. At day 28, plants from sanitized seeds had significantly higher counts of E. coli on the roots than those from unsanitized seeds. E. coli was also detected on a few uninoculated plants indicating airborne cross contamination among plants in the same growth chamber and suggesting an influence of the natural microbiome on human pathogen survival and persistence in leafy greens. Sequencing analysis revealed variations in composition and diversity between the communities. Understanding the microbial community of the rhizospheric microbiome is only the first step in determining the relationships between plants. Additional studies to include genotypic and phenotypic variations in the plants should be considered to determine if the natural microbes in the rhizosphere may contribute to the health and therefore, safety of the edible plants.

Khodadad, Christina L. M.↗

DOE OSTI2024

Metrics and Methods for Radiation Detection Algorithm Characterization for Nuclear/Radiological Source Search

This report presents a series of recommendations for data to train and evaluate radiation detection algorithms and performance metrics to evaluate these algorithms. These recommendations were formed through a community consensus approach through the Detection Radiation Algorithms Group (DRAG), a multi-institution collaboration spanning eight Department of Energy laboratories and John Hopkins Applied Physics Laboratory. This report includes recommendations on background data variability, and metrics to quantify variability, sources and shielding configurations to include in data collection campaigns and detector response variability. In addition, this report describes several anomaly detection and identification algorithms and recommends metrics to report their performance. Finally, this report ends with a discussion on machine learning algorithms.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

NASA NTRS1996

Algal Accessory Pigment Detection Using AVIRIS Image-Derived Spectral Radiance Data

Visual and derivative analyses of AVIRIS spectral data can be used to detect algal accessory pigments in aquatic communities. This capability extends the use of remote sensing for the study of aquatic ecosystems by allowing detection of taxonomically significant pigment signatures which yield information about the type of algae present. Such information allows remote sensing-based assessment of aquatic ecosystem health, as in the detection of nuisance blooms of cyanobacteria or toxic blooms of dinoflagellates. Remote sensing of aquatic systems has traditionally focused on quantification of chlorophyll a, a photoreactive (and light-harvesting) pigment which is common to all algae as well as cyanobacteria (bluegreen algae). Due to the ubiquitousness of this pigment within algae, chl a is routinely measured to estimate algal biomass both during ground-truthing and using various airborne or satellite based sensors, including AVIRIS. Within the remote sensing and aquatic sciences communities, ongoing research has been performed to detect algal accessory pigments for assessment of algal population composition. This research is based on the fact that many algal accessory pigments are taxonomically significant, and all are spectrally unique. Aquatic scientists have been refining pigment analysis techniques, primarily high performance liquid chromatography, or HPLC, to detect specific pigments as a time-saving alternative to individual algal cell identifications and counts. Remote sensing scientists are investigating the use of pigment signatures to construct pigment libraries analogous to mineral spectral libraries used in geological remote sensing applications. The accessory pigment approach has been used successfully in remote sensing using data from the Thematic Mapper, low-altitude, multiple channel scanners, field spectroradiometers and the AVIRIS hyperspectral scanner. Due to spectral and spatial resolution capabilities, AVIRIS is the sensor of choice for such studies. We present here our results on detection of algal accessory pigments using AVIRIS data.

Richardson, Laurie L.↗

NASA NTRS1998

Lidar Measurements of Tropospheric Wind Profiles with the Double Edge Technique

Research has established the importance of global tropospheric wind measurements for large scale improvements in numerical weather prediction. In addition, global wind measurements provide data that are fundamental to the understanding and prediction of global climate change. These tasks are closely linked with the goals of the NASA Earth Science Enterprise and Global Climate Change programs. NASA Goddard has been actively involved in the development of direct detection Doppler lidar methods and technologies to meet the wind observing needs of the atmospheric science community. A variety of direct detection Doppler wind lidar measurements have recently been reported indicating the growing interest in this area. Our program at Goddard has concentrated on the development of the edge technique for lidar wind measurements. Implementations of the edge technique using either the aerosol or molecular backscatter for the Doppler wind measurement have been described. The basic principles have been verified in lab and atmospheric lidar wind experiments. The lidar measurements were obtained with an aerosol edge technique lidar operating at 1064 nm. These measurements demonstrated high spatial resolution (22 m) and high velocity sensitivity (rms variances of 0.1 m/s) in the planetary boundary layer (PBL). The aerosol backscatter is typically high in the PBL and the effects of the molecular backscatter can often be neglected. However, as was discussed in the original edge technique paper, the molecular contribution to the signal is significant above the boundary layer and a correction for the effects of molecular backscatter is required to make wind measurements. In addition, the molecular signal is a dominant source of noise in regions where the molecular to aerosol ratio is large since the energy monitor channel used in the single edge technique measures the sum of the aerosol and molecular signals. To extend the operation of the edge technique into the free troposphere we have developed a variation of the edge technique called the double edge technique. In this paper a ground based aerosol double edge lidar is described and the first measurements of wind profiles in the free troposphere obtained with this lidar will be presented.

Gentry, Bruce M.↗

NASA NTRS2007

Mission Risk Reduction Regulatory Change Management

NASA Headquarters Environmental Management Division supports NASA's mission to pioneer the future in space exploration, scientific discovery, and aeronautics research by integrating environmental considerations into programs and projects early-on, thereby proactively reducing NASA's exposure to institutional, programmatic and operational risk. As part of this effort, NASA established the Principal Center for Regulatory Risk Analysis and Communication (RRAC PC) as a resource for detecting, analyzing, and communicating environmental regulatory risks to the NASA stakeholder community. The RRAC PC focuses on detecting emerging environmental regulations and other operational change drivers that may pose risks to NASA programs and facilities, and effectively communicating the potential risks. For example, regulatory change may restrict how and where certain activities or operations may be conducted. Regulatory change can also directly affect the ability to use certain materials by mandating a production phase-out or restricting usage applications of certain materials. Regulatory change can result in significant adverse impacts to NASA programs and facilities due to NASA's stringent performance requirements for materials and components related to human-rated space vehicles. Even if a regulation does not directly affect NASA operations, U.S. and international regulations can pose program risks indirectly through requirements levied on manufacturers and vendors of components and materials. For example, manufacturers can change their formulations to comply with new regulatory requirements. Such changes can require time-consuming and costly requalification certification for use in human spaceflight programs. The RRAC PC has implemented a system for proactively managing regulatory change to minimize potential adverse impacts to NASA programs and facilities. This presentation highlights the process utilized by the RRACPC to communicate regulatory change and the associated potential risks within NASA, as well as the process for communicating and cooperating with other government agencies and industry partners, both domestic and international, to ensure mission success.

Scroggins, Sharon↗

DOE OSTI2020

GADRAS Batch Inject Tool User Guide

Gamma Detector Response and Analysis Software (GADRAS) is used by the radiation detection and emergency response community to perform modeling and spectral analysis for gamma detector systems. Built into GADRAS is the ability to define a detector, geometry, background characteristics and source composition to generate synthetic spectra for drills and exercises (injects). Consequence Management is currently in development of a sample result data simulator tool in which a deposition model is probed for source conditions at moments in time and locations in space. These values are used to generate realistic sample results for use in drills and exercises. In addition to sample results, there is a need to simulate the actual spectra that would be observed in the field by downlooking HPGe instruments given a deposition activity. This way, the FRMAC Gamma Spectroscopist can practice their process of generating quantified results from spectra on realistic data as well. Recognizing the decades of work done in GADRAS to accurately generate synthetic spectra, this team decided to build a link between the new simulator and GADRAS to generate these spectra quickly and easily. The simulator tool will generate a file that specifies the name of the spectra, its location, date/time of measurement, duration of measurement, height off the ground, and the deposition activity and age for every radionuclide in the simulation. Then, a new tool within the Inject Tab of GADRAS was developed to read in this file given a detector selection and generate In-Situ spectra for each row in the file in any file format the user chooses. This way, simulation cell staff can take these files and then upload them to the appropriate data system (RAMS or RadResponder) for use during drills and exercises. An advanced feature of this tool allows for generating any spectra given an appropriate model and mapping of source to model layer in the batch inject tool. This way, spectra from field sample counts, mobile laboratories, or even fixed laboratories can be generated in bulk given an estimate of the radioactivity concentration or total radioactivity in an import file. This expands the capabilities of this tool a great deal and will make it a more useful tool for CM and others to help estimate detector response for nearly any situation. This user guide will explain the steps needed to perform a batch inject file generation.

61 RADIATION PROTECTION AND DOSIMETRY↗

NASA NTRS1997

Reduction of Helicopter Blade-Vortex Interaction Noise by Active Rotor Control Technology

Helicopter blade-vortex interaction noise is one of the most severe noise sources and is very important both in community annoyance and military detection. Research over the decades has substantially improved basic physical understanding of the mechanisms generating rotor blade-vortex interaction noise and also of controlling techniques, particularly using active rotor control technology. This paper reviews active rotor control techniques currently available for rotor blade vortex interaction noise reduction, including higher harmonic pitch control, individual blade control, and on-blade control technologies. Basic physical mechanisms of each active control technique are reviewed in terms of noise reduction mechanism and controlling aerodynamic or structural parameters of a blade. Active rotor control techniques using smart structures/materials are discussed, including distributed smart actuators to induce local torsional or flapping deformations, Published by Elsevier Science Ltd.

Yu, Yung H.↗

NASA NTRS2018

Identifying the Community Structure of the Food-Trade International Multi-Network

Achieving international food security requires improved understanding of how international trade networks connect countries around the world through the import-export flows of food commodities. The properties of international food trade networks are still poorly documented, especially from a multi-network perspective. In particular, nothing is known about the multi-network's community structure. Here we find that the individual crop-specific layers of the multi-network have densely connected trading groups, a consistent characteristic over the period 2001-2011. Further, the multi-network is characterized by low variability over this period but with substantial heterogeneity across layers in each year. In particular, the layers are mostly assortative: more-intensively connected countries tend to import from and export to countries that are themselves more connected. We also fit econometric models to identify social, economic and geographic factors explaining the probability that any two countries are co-present in the same community. Our estimates indicate that the probability of country pairs belonging to the same food trade community depends more on geopolitical and economic factors-such as geographical proximity and trade-agreement co-membership-than on country economic size and/or income. These community-structure findings of the multi-network are especially valuable for efforts to understand past and emerging dynamics in the global food system, especially those that examine potential 'shocks' to global food trade.

complex networks↗

NASA NTRS2022

PACE: How One NASA Mission Aligns With the United Nations Decade of Ocean Science for Sustainable Development (Ocean Shot #2)

The PACE satellite observatory will follow a Sun synchronous, polar orbit at an altitude of 676.5 km with a local 13:00 Equatorial crossing time. Its payload consists of three instruments, a primary hyperspectral imaging radiometer being built at NASA Goddard Space Flight Center and two multispectral, multiangle polarimeters, the combination of which advances far beyond heritage capabilities. The Ocean Color Instrument (OCI) offers one-day global coverage with a ground sample distance of 1 km2 at nadir. As described in this OceanShot, this leap in technology will enable improved understanding of aquatic ecosystems and biogeochemistry, as well as provide new information on phytoplankton community composition and improved detection of algal blooms. OCI will be complemented by two small multi-angle polarimeters with spectral ranges that span the visible to near infrared spectral region. When sunlight interacts with clouds or aerosols, it comes away from that interaction changed. By measuring changes in how reflected light oscillates within a geometric plane (i.e., its viewing angle-specific polarization), we can infer useful properties of the clouds or aerosols. This information is crucial to deciphering the way sunlight is reflected and absorbed by our planet and how aerosols affect cloud formation. The polarimeters include the Spectro-polarimeter for Planetary Exploration (SPEXone) and the Hyper Angular Research Polarimeter (HARP2), both of which will significantly improve aerosol and cloud characterizations and provide opportunities for novel ocean color atmospheric correction. (Figure 3). These instruments offer complementary capabilities: SPEXone is hyperspectral, multiangular, and narrow swath to support advanced atmospheric aerosol characterizations, whereas HARP2 is multispectral, hyper-angular, and wide swath to advance cloud property retrievals. In total, the combined PACE instrument suite will revolutionize studies of global biogeochemistry, carbon cycles, and air–sea exchanges in the ocean–atmosphere system.

Ocean color↗

DOE OSTI2023

SARS-CoV-2 raw wastewater surveillance from student residences on an urban university campus

The COVID-19 pandemic brought about an urgent need to monitor the community prevalence of infection and detect the presence of SARS-CoV-2. Testing individual people is the most reliable method to measure the spread of the virus in any given community, but it is also the most expensive and time-consuming. Wastewater-based epidemiology (WBE) has been used since the 1960s when scientists implemented monitoring to measure the effectiveness of the Polio vaccine. Since then, WBE has been used to monitor populations for various pathogens, drugs, and pollutants. In August 2020, the University of Tennessee-Knoxville implemented a SARS-CoV-2 surveillance program that began with raw wastewater surveillance of the student residence buildings on campus, the results of which were shared with another lab group on campus that oversaw the pooled saliva testing of students. Sample collection began at 8 am, and the final RT-qPCR results were obtained by midnight. The previous day’s results were presented to the campus administrators and the Student Health Center at 8 am the following morning. The buildings surveyed included all campus dormitories, fraternities, and sororities, 46 buildings in all representing an on-campus community of over 8,000 students. The WBE surveillance relied upon early morning “grab” samples and 24-h composite sampling. Because we only had three Hach AS950 Portable Peristaltic Sampler units, we reserved 24-h composite sampling for the dormitories with the highest population of students. Samples were pasteurized, and heavy sediment was centrifuged and filtered out, followed by a virus concentration step before RNA extraction. Each sample was tested by RT-qPCR for the presence of SARS-CoV-2, using the CDC primers for N Capsid targets N1 and N3. The subsequent pooled saliva tests from sections of each building allowed lower costs and minimized the total number of individual verification tests that needed to be analyzed by the Student Health Center. Our WBE results matched the trend of the on-campus cases reported by the student health center. The highest concentration of genomic copies detected in one sample was 5.06 × 10 7 copies/L. Raw wastewater-based epidemiology is an efficient, economical, fast, and non-invasive method to monitor a large community for a single pathogen or multiple pathogen targets.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2024

Peeling back the many layers of competitive exclusion

Baby chicks administered a fecal transplant from adult chickens are resistant to Salmonella colonization by competitive exclusion. A two-pronged approach was used to investigate the mechanism of this process. First, Salmonella response to an exclusive (Salmonella competitive exclusion product, Aviguard ® ) or permissive microbial community (chicken cecal contents from colonized birds containing 7.85 Log 10 Salmonella genomes/gram) was assessed ex vivo using a S. typhimurium reporter strain with fluorescent YFP and CFP gene fusions to rrn and hilA operon, respectively. Second, cecal transcriptome analysis was used to assess the cecal communities’ response to Salmonella in chickens with low (≤5.85 Log 10 genomes/g) or high (≥6.00 Log 10 genomes/g) Salmonella colonization. The ex vivo experiment revealed a reduction in Salmonella growth and hilA expression following co-culture with the exclusive community. The exclusive community also repressed Salmonella’s SPI-1 virulence genes and LPS modification, while the anti-virulence/inflammatory gene avrA was upregulated. Salmonella transcriptome analysis revealed significant metabolic disparities in Salmonella grown with the two different communities. Propanediol utilization and vitamin B12 synthesis were central to Salmonella metabolism co-cultured with either community, and mutations in propanediol and vitamin B12 metabolism altered Salmonella growth in the exclusive community. There were significant differences in the cecal community’s stress response to Salmonella colonization. Cecal community transcripts indicated that antimicrobials were central to the type of stress response detected in the low Salmonella abundance community, suggesting antagonism involved in Salmonella exclusion. This study indicates complex community interactions that modulate Salmonella metabolism and pathogenic behavior and reduce growth through antagonism may be key to exclusion.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2025

Common practices for quantifying methane emissions from plumes detected by remote sensing

This document provides a set of community-accepted practices for quantifying methane emissions based on plumes detected via spectroscopic remote sensing. Its primary goal is to promote consistency in the generation, validation, reporting, and quality assessment of methane emission estimates derived from remote sensing radiances. Developed by subject matter experts with deep experience across all stages of the measurement process, this guidance reflects a critical evaluation of current methodologies and highlights key practices needed to produce reliable, interoperable, and traceable products. The focus is specifically on methane emissions quantified from distinct plumes originating from localized sources, rather than diffuse emissions spread over large regions, which are beyond the scope of this work. This document is intended to serve both data producers and users. For producers, it offers a framework for aligning with field-recognized standards to ensure their outputs meet rigorous quality and transparency criteria. For users, it provides a reference to assess dataset fitness-for-purpose by highlighting essential metadata, assumptions, and methodological choices that underpin emission estimates. By fostering a shared understanding of best practices, this work aims to enhance comparability, confidence, and utility of remotely sensed methane emission products.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2013

A Survey of LIDAR Technology and Its Use in Spacecraft Relative Navigation

This paper provides a survey of modern LIght Detection And Ranging (LIDAR) sensors from a perspective of how they can be used for spacecraft relative navigation. In addition to LIDAR technology commonly used in space applications today (e.g. scanning, flash), this paper reviews emerging LIDAR technologies gaining traction in other non-aerospace fields. The discussion will include an overview of sensor operating principles and specific pros/cons for each type of LIDAR. This paper provides a comprehensive review of LIDAR technology as applied specifically to spacecraft relative navigation. HE problem of orbital rendezvous and docking has been a consistent challenge for complex space missions since before the Gemini 8 spacecraft performed the first successful on-orbit docking of two spacecraft in 1966. Over the years, a great deal of effort has been devoted to advancing technology associated with all aspects of the rendezvous, proximity operations, and docking (RPOD) flight phase. After years of perfecting the art of crewed rendezvous with the Gemini, Apollo, and Space Shuttle programs, NASA began investigating the problem of autonomous rendezvous and docking (AR&D) to support a host of different mission applications. Some of these applications include autonomous resupply of the International Space Station (ISS), robotic servicing/refueling of existing orbital assets, and on-orbit assembly.1 The push towards a robust AR&D capability has led to an intensified interest in a number of different sensors capable of providing insight into the relative state of two spacecraft. The present work focuses on exploring the state-of-the-art in one of these sensors - LIght Detection And Ranging (LIDAR) sensors. It should be noted that the military community frequently uses the acronym LADAR (LAser Detection And Ranging) to refer to what this paper calls LIDARs. A LIDAR is an active remote sensing device that is typically used in space applications to obtain the range to one or more points on a target spacecraft. As the name suggests, LIDAR sensors use light (typically a laser) to illuminate the target and measure the time it takes for the emitted signal to return to the sensor. Because the light must travel from the source, to

Christian, John A.↗

DOE OSTI2020

Winter warming rapidly increases carbon degradation capacities of fungal communities in tundra soil: Potential consequences on carbon stability

We report high-latitude tundra ecosystems are increasingly affected by climate warming. As an important fraction of soil microorganisms, fungi play essential roles in carbon degradation, especially the old, chemically recalcitrant carbon. However, it remains obscure how fungi respond to climate warming and whether fungi, in turn, affect carbon stability of tundra. In a 2-year winter soil warming experiment of 2°C by snow fences, we investigated responses of fungal communities to warming in the active layer of an Alaskan tundra. Although fungal community composition, revealed by the 28S rRNA gene amplicon sequencing, remained unchanged (p > .05), fungal functional gene composition, revealed by a microarray named GeoChip, was altered (p < .05). Changes in functional gene composition were linked to winter soil temperature, thaw depth, soil moisture, and gross primary productivity (canonical correlation analysis, p < .05). Specifically, relative abundances of fungal genes encoding invertase, xylose reductase and vanillin dehydrogenase significantly increased (p < .05), indicating higher carbon degradation capacities of fungal communities under warming. Accordingly, we detected changes in fungal gene networks under warming, including higher average path distance, lower average clustering coefficient and lower percentage of negative links, indicating that warming potentially changed fungal interactions. Together, our study reveals higher carbon degradation capacities of fungal communities under short-term warming and highlights the potential impacts of fungal communities on tundra ecosystem respiration, and consequently future carbon stability of high-latitude tundra.

59 BASIC BIOLOGICAL SCIENCES↗

NASA NTRS1961

Noise Considerations in the Design and Operation of V/STOL Aircraft

Available propulsion-system noise data have been applied to the problems of design and operation of V/STOL aircraft. In particular, considerations have been given to minimizing adverse community reaction for operations between airports and to minimizing detection due to noise for special missions. For minimizing adverse community reaction, configurations incorporating low-blade-loading rotors, low-tip-speed propellers, or turbofan-type engines are judged to be most satisfactory. For minimizing detection, consideration must be given to minimizing the noise of the generating airplane, having maximum background noise in the vicinity of the observer, and operating the aircraft at minimum altitude.

Maglieri, Domenic J.↗