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

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At least 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
NASA NTRS1990

Digital Controller For Emergency Beacon

Prototype digital controller intended for use in 406-MHz emergency beacon. Undergoing development according to international specifications, 406-MHz emergency beacon system includes satellites providing worldwide monitoring of beacons, with Doppler tracking to locate each beacon within 5 km. Controller turns beacon on and off and generates binary codes identifying source (e.g., ship, aircraft, person, or vehicle on land). Codes transmitted by phase modulation. Knowing code, monitor attempts to communicate with user, monitor uses code information to dispatch rescue team appropriate to type and locations of carrier.

Ivancic, William D.↗
NASA NTRS1957

Flight Investigation of the Effectiveness of an Automatic Aileron Trim Control Device for Personal Airplanes

A flight investigation to determine the effectiveness of an automatic aileron trim control device installed in a personal airplane to augment the apparent spiral stability has been conducted. The device utilizes a rate-gyro sensing element in order to switch an on-off type of control that operates the ailerons at a fixed rate through control centering springs. An analytical study using phase-plane and analog-computer methods has been carried out to determine a desirable method of operation for the automatic trim control.

Phillips, William H↗
NASA NTRS1992

Human performance in the modern cockpit

This panel was organized by the Aerospace Human Factors Committee to illustrate behavioral research on the perceptual, cognitive, and group processes that determine crew effectiveness in modern cockpits. Crew reactions to the introduction of highly automated systems in the cockpit will be reported on. Automation can improve operational capabilities and efficiency and can reduce some types of human error, but may also introduce entirely new opportunities for error. The problem solving and decision making strategies used by crews led by captains with various personality profiles will be discussed. Also presented will be computational approaches to modeling the cognitive demands of cockpit operations and the cognitive capabilities and limitations of crew members. Factors contributing to aircrew deviations from standard operating procedures and misuse of checklist, often leading to violations, incidents, or accidents will be examined. The mechanisms of visual perception pilots use in aircraft control and the implications of these mechanisms for effective design of visual displays will be discussed.

Dismukes, R. K.↗
NASA NTRS2010

Asbestos Exposure Assessment Database

Exposure to particular hazardous materials in a work environment is dangerous to the employees who work directly with or around the materials as well as those who come in contact with them indirectly. In order to maintain a national standard for safe working environments and protect worker health, the Occupational Safety and Health Administration (OSHA) has set forth numerous precautionary regulations. NASA has been proactive in adhering to these regulations by implementing standards which are often stricter than regulation limits and administering frequent health risk assessments. The primary objective of this project is to create the infrastructure for an Asbestos Exposure Assessment Database specific to NASA Johnson Space Center (JSC) which will compile all of the exposure assessment data into a well-organized, navigable format. The data includes Sample Types, Samples Durations, Crafts of those from whom samples were collected, Job Performance Requirements (JPR) numbers, Phased Contrast Microscopy (PCM) and Transmission Electron Microscopy (TEM) results and qualifiers, Personal Protective Equipment (PPE), and names of industrial hygienists who performed the monitoring. This database will allow NASA to provide OSHA with specific information demonstrating that JSC s work procedures are protective enough to minimize the risk of future disease from the exposures. The data has been collected by the NASA contractors Computer Sciences Corporation (CSC) and Wyle Laboratories. The personal exposure samples were collected from devices worn by laborers working at JSC and by building occupants located in asbestos-containing buildings.

Arcot, Divya K.↗
NASA NTRS1991

General-Purpose Ada Software Packages

Collection of subprograms brings to Ada many features from other programming languages. All generic packages designed to be easily instantiated for types declared in user's facility. Most packages have widespread applicability, although some oriented for avionics applications. All designed to facilitate writing new software in Ada. Written on IBM/AT personal computer running under PC DOS, v.3.1.

Klumpp, Allan R.↗
DOE OSTI2022

Defining the Prototype Convenience Store Building Characteristics

The US Department of Energy supports the development of commercial building energy codes and standards. To support commercial building energy research activities and the development of commercial building energy codes and standards, continuous efforts have been made to convert 30 prototype building models (20 different building types), which cover 80% of US commercial building floor space, to OpenStudio prototype buildings. Additionally, the suite of prototype building models was expanded to include the addition of new building prototype models (e.g., courthouse, college building). This report documents the building and system characteristics of the prototype convenience store building model. Multiple sources, including databases, documented projects, and personal communications, were used to define the prototype convenience store building characteristics, and a one-story, 3,000 ft 2 building was considered as the prototype convenience store to represent an average-sized convenience store in the United States. The Oak Ridge National Laboratory team defined the operational hours of the convenience store as 17 hours per day. The types of exterior walls, roof, and floor were defined as brick wall, metal surfacing roof, and slab-on-grade floor, respectively. Double glazing was selected, and the window-towall ratio was set as 15% on the front side. For the system part, packaged system and centralized water heater were selected for the space heating and cooling system and water heater system, respectively. In terms of the refrigerator system, the number of refrigerators and freezers were determined as eight closed cases and two walk-in units.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS1985

Optical multicolors - A poor person's z machine for galaxies

The feasibility, limits, accuracy, and uncertainties of using optical broadband colors in the form of two-color plots to measure the redshifts of faint galaxies are explored. Comparison of redshifts from slit spectra and 4-m photographic UBVI photometry of 100 faint galaxies confirms that colors do yield redshifts. These galaxies of 17-23 mag in B span a wide range of intrinsic color and are thus unlike previous samples of faint galaxies that were largely radio or cluster galaxies of early (red) type. For redshifts less than 0.35, two-thirds of the color redshifts agree with the spectroscopic values to within + or - 0.04 in z; for higher redshifts to z of 0.6, the errors increase to + or - 0.06. These accuracies were achieved for blue as well as red galaxies, and ensure that multicolors can serve as a poor person's redshift machine to study distant galaxies in clusters and the field.

Koo, D. C.↗
DOE OSTI2023

A general spatial-temporal framework for short-term building temperature forecasting at arbitrary locations with crowdsourcing weather data

Weather forecasting has been a critical component to predict and control building energy consumption for better building energy management. Without accessibility to other data sources, the onsite observed temperatures or the airport temperatures are used in forecast models. In this paper, we present a novel approach by utilizing the crowdsourcing weather data from neighboring personal weather stations (PWS) to improve the weather forecast accuracy around buildings using a general spatial-temporal modeling framework. The final forecast is based on the ensemble of local forecasts for the target location using neighboring PWSs. Our approach is distinguished from existing literature in various aspects. First, we leverage the crowdsourcing weather data from PWS in addition to public data sources. In this way, the data is at much finer time resolution (e.g., at 5-minute frequency) and spatial resolution (e.g., arbitrary location vs grid). Second, our proposed model incorporates spatial-temporal correlation information of weather variables between the target building and a set of neighboring PWSs so that underlying correlations can be effectively captured to improve forecasting performance. Here, we demonstrate the performance of the proposed framework by comparing to the benchmark models on temperature forecasting for a building located at an arbitrary location at San Antonio, Texas, USA. In general, the proposed model framework equipped with machine learning technique such as Random Forest can improve forecasting by 50% compares with persistent model and has 90% chance to outperform airport forecast in short-term forecasting. In a real-time setting, the proposed model framework can provide more accurate temperature forecasting results compared with using airport temperature forecast for most forecast horizon. Moreover, we analyze the sensitivity of model parameters to gain insights on how crowdsourcing data from the neighboring personal weather stations impacts forecasting performance. Finally, we implement our model in other cities such as Syracuse and Chicago to test the model's performance in different landforms and climate types.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1991

An integrated Ka/Ku-band payload for personal, mobile and private business communications

The Canadian Department of Communications has been studying options for a government-sponsored demonstration payload to be launched before the end of the century. A summary of the proposed system concepts and network architectures for providing an advanced private business network service at Ku-band and personal and mobile communications at Ka-band is presented. The system aspects addressed include coverage patterns, traffic capacity, and grade of service, multiple access options as well as special problems, such as Doppler in mobile applications. Earth terminal types and the advanced payload concept proposed in a feasibility study for the demonstration mission are described. This concept is a combined Ka-band/Ku-band payload which incorporates a number of advanced satellite technologies including a group demodulator to convert single-channel-per-carrier frequency division multiple access uplink signals to a time division multiplex downlink, on-board signal regeneration, and baseband switching to support packet switched data operation. The on-board processing capability of the payload provides a hubless VSAT architecture which permits single-hop full mesh interconnectivity. The Ka-band and Ku-band portions of the payload are fully integrated through an on-board switch, thereby providing the capability for fully integrated services, such as using the Ku-band VSAT terminals as gateway stations for the Ka-band personal and mobile communications services.

Hayes, Edward J.↗
NASA NTRSDate not supplied

INFLUENCE OF ACTN3 GENE ON MUSCLE HEALTH AND PHYSICAL FITNESS TO INFORM FUTURE INTERVENTIONS IN SPACEFLIGHT MISSIONS

INTRODUCTION: Exposure to reduced gravity environments leads to diminished muscle size, strength, and endurance. Preservation of physical fitness is critical for mission essential tasks such as extravehicular activities or adaptation to changes in gravity loads. Current countermeasures to maintain ISS astronauts’ muscle mass and fitness include dedicated time for a combination of cardiovascular exercise and resistance training. Countermeasure effectiveness is monitored through VO2 max and isometric mid-thigh pulls. It is important to understand both environmental and genetic contributors to astronaut physical fitness. Multiple genes, including ACTN3, are known to correlate with exercise phenotypes and have the potential to help personalize countermeasures based on an astronaut’s genotypic makeup. TOPIC: The ACTN3 gene encodes a protein expressed only in fast-twitch muscles and correlates with sprint and power phenotypes. A common polymorphism in ACTN3 gene is R577X (rs1815739), produced by a C−to−T base substitution resulting in a nonsense mutation from arginine (R) to a premature stop codon (X) present in approximately 18% of the population. This polymorphism causes an absence of α−actinin−3 in type II muscle fibers but does not lead to a disease phenotype. The RR genotype is associated with elite athletes, especially in sprint and power sports. The XX genotype is believed to be more common in endurance athletes. The ACTN3 gene also has potential associations with training adaptation, post-exercise recovery, and exercise-associated injuries. APPLICATION: Understanding how ACTN3 and other genetic determinates of fitness phenotypes affect astronaut physical performance can inform personalized exercise and recovery prescriptions. For example, individuals with the RR or RX genotype may respond better to high-load and low repetition exercise, while XX may benefit from high repetition with low weight exercise. Since the wild-type protein may confer more resistance to muscle damage, those individuals with the RR or RX genotype may benefit from high intensity interval training for improved VO2 max, whereas those with an XX genotype may benefit from low intensity, high volume endurance activity. Additionally, omics data related to health and performance could be used as biomarkers to monitor astronaut fitness and the effectiveness of training regimens during a mission. Learning objectives: • Learn about the phenotypic effects on muscle function and fitness secondary to R577X mutation in the ACTN3 gene • Learn how mutations in the ACTN3 gene may inform future countermeasures for future spaceflight missions

Lynn K Stanwyck↗
NASA NTRS1987

Technology demonstrator program for Space Station Environmental Control Life Support System

The main objectives and requirements of the NASA/Marshall Space Flight Center Technology Demonstration Program are discussed. The program consists of a comparative test and a 90-day manned system test to evaluate an Environmental Control and Life Support System (ECLSS). In the comparative test phase, 14 types of subsystems which perform oxygen and water reclamation functions are to be examined in terms of performance maintenance/service requirements, reliability, and safety. The manned chamber testing phase involves a four person crew using a partial ECLSS for 90 days. The schedule for the program and the program hardware requirements are described.

Adams, Alan M.↗
NASA NTRS1983

Commercial transport aircraft composite structures

The role that analysis plays in the development, production, and substantiation of aircraft structures is discussed. The types, elements, and applications of failure that are used and needed; the current application of analysis methods to commercial aircraft advanced composite structures, along with a projection of future needs; and some personal thoughts on analysis development goals and the elements of an approach to analysis development are discussed.

Mccarty, J. E.↗
NASA NTRS1984

Subjective workload and individual differences in information processing abilities

This paper describes several experiments examining the source of individual differences in the experience of mental workload. Three sources of such differences were examined: information processing abilities, timesharing abilities, and personality traits/behavior patterns. On the whole, there was little evidence that individual differences in information processing abilities or timesharing abilities are related to perceived differences in mental workload. However, individuals with strong Type A coronary prone behavior patterns differed in both single- and multiple-task performance from individuals who showed little evidence of such a pattern. Additionally, individuals with a strong Type A pattern showed some dissociation between objective performance and the experience of mental workload.

Damos, D. L.↗
NASA NTRS1990

Antenna Beam Coverage Concepts

The strawman Personal Access Satellite System (PASS) design calls for the use of a CONUS beam for transmission between the supplier and the satellite and for fixed beams for transmission between the basic personal terminal and the satellite. The satellite uses a 3 m main reflector for transmission at 20 GHz and a 2 m main reflector for reception at 30 GHz. There are several types of spot beams under consideration for the PASS system besides fixed beams. The beam pattern of a CONUS coverage switched beam is shown along with that of a scanning beam. A switched beam refers to one in which the signal from the satellite is connected alternatively to various feed horns. Scanning beams are taken to mean beams whose footprints are moved between contiguous regions in the beam's coverage area. The advantages and disadvantages of switched and/or scanning beams relative to fixed beams. The consequences of using switched/scanning in lieu of fixed beams in the PASS design and attempts are made to evaluate the listed advantages and disadvantages. Two uses of switched/scanning beams are examined. To illustrate the implications of switched beams use on PASS system design, operation at two beam scan rates is explored.

Estabrook, Polly↗
NASA NTRS2004

A Survey of Formal Methods for Intelligent Swarms

Swarms of intelligent autonomous spacecraft, involving complex behaviors and interactions, are being proposed for future space exploration missions. Such missions provide greater flexibility and offer the possibility of gathering more science data than traditional single spacecraft missions. The emergent properties of swarms make these missions powerful, but simultaneously far more difficult to design, and to assure that the proper behaviors will emerge. These missions are also considerably more complex than previous types of missions, and NASA, like other organizations, has little experience in developing or in verifying and validating these types of missions. A significant challenge when verifying and validating swarms of intelligent interacting agents is how to determine that the possible exponential interactions and emergent behaviors are producing the desired results. Assuring correct behavior and interactions of swarms will be critical to mission success. The Autonomous Nano Technology Swarm (ANTS) mission is an example of one of the swarm types of missions NASA is considering. The ANTS mission will use a swarm of picospacecraft that will fly from Earth orbit to the Asteroid Belt. Using an insect colony analogy, ANTS will be composed of specialized workers for asteroid exploration. Exploration would consist of cataloguing the mass, density, morphology, and chemical composition of the asteroids, including any anomalous concentrations of specific minerals. To perform this task, ANTS would carry miniaturized instruments, such as imagers, spectrometers, and detectors. Since ANTS and other similar missions are going to consist of autonomous spacecraft that may be out of contact with the earth for extended periods of time, and have low bandwidths due to weight constraints, it will be difficult to observe improper behavior and to correct any errors after launch. Providing V&V (verification and validation) for this type of mission is new to NASA, and represents the cutting edge in system correctness, and requires higher levels of assurance than other (traditional) missions that use a single or small number of spacecraft that are deterministic in nature and have near continuous communication access. One of the highest possible levels of assurance comes from the application of formal methods. Formal methods are mathematics-based tools and techniques for specifying and verifying (software and hardware) systems. They are particularly useful for specifying complex parallel systems, such as exemplified by the ANTS mission, where the entire system is difficult for a single person to fully understand, a problem that is multiplied with multiple developers. Once written, a formal specification can be used to prove properties of a system (e.g., the underlying system will go from one state to another or not into a specific state) and check for particular types of errors (e.g., race or livelock conditions). A formal specification can also be used as input to a model checker for further validation. This report gives the results of a survey of formal methods techniques for verification and validation of space missions that use swarm technology. Multiple formal methods were evaluated to determine their effectiveness in modeling and assuring the behavior of swarms of spacecraft using the ANTS mission as an example system. This report is the first result of the project to determine formal approaches that are promising for formally specifying swarm-based systems. From this survey, the most promising approaches were selected and are discussed relative to their possible application to the ANTS mission. Future work will include the application of an integrated approach, based on the selected approaches identified in this report, to the formal specification of the ANTS mission.

Truszkowski, Walt↗
DOE OSTI2025

IM3 Open Source Data Center Atlas

IM3 Open Source Data Center Atlas Description This dataset contains locations of existing data center facilities in the United States. Data center locations were derived from OpenStreetMap (OSM), a crowd-sourced database. Data points from OSM are processed in various ways to determine additional variables provided in the data including: facility area (square feet), associated US county, and US state. This dataset can be used to identify areas of concentrated data center development and inform government and private sector planning strategies for future buildout of data centers and the infrastructure necessary to support it. Usage Notes Validation of OSM-derived data center locations is an ongoing development under the IM3 project, and the database will be updated as new information becomes available. In some instances, both the data center area (e.g., campus) and individual data center buildings are included as overlapping areas in the database. Both values are retained. Data center points, buildings, and campus areas are provided as separate layers in the downloadable data package. Note that data items are not necessarily complete across layers. That is, a specific data center may only be present as a single point geometry in the "point" layer while other data centers are represented in both the campus and building layers. In some cases, data center campuses and/or buildings straddle a county boundary line. Mappings to both counties are retained in the database as separate rows. These data rows will have the same data center id information, but each will have different county information. Crowd-sourced data, by nature, relies on individuals and communities to provide information. As a result, some data may be missing where it has not yet been reported. As we collect information on additional data center locations and as OSM receives additional contributions, the database will be updated to capture additional data points not yet shown. Technical Information Data is available for download under the following formats: GeoPackage (GPKG) CSV Geospatial data is provided in the WGS84 (EPSG:4326) coordinate reference system. The GeoPackage download contains the following layers. See usage notes for more information. "point" "building" "campus" The "point" layer includes all data from OSM that had POINT geometry type (i.e., individual coordinates). The "building" layer includes all OSM data that did not have POINT geometry and where the building tag in the OSM export was neither equal to "no" or null. Data that did not meet the "point" or "building" qualification was assumed to be a facility campus and included in the "campus" layer. The dataset contains the following parameters. Variables provided by OSM are labeled with (OSM-provided). id - unique identification number (OSM-provided with prefix of "node/", "relation/" and similar attributes removed) state - name of US state state_abb - two letter US state abbreviation state_id - state ID number county - name of US county county_id - county ID number ref - reference numbers or codes (OSM-provided) operator - the name of the company, corporation, or person in charge facility (OSM-provided) name - name of facility (OSM-provided) sqft - surface area of facility polygon, measured in square feet. Only available for "building" and "campus" layers lat - latitude of data centroid point lon - longitude of data centroid point type – represented spatial information. One of "point", "building", or "campus". geometry – POLYGON geometry of area footprint (in "campus" and "building" layers) or POINT geometry of locations (in "point" layer). This parameter is not included in the csv download. Attribution Data center locations were derived from OpenStreetMap, which is made available at openstreetmap.org under the Open Database License (ODbL). US state and county boundary information was collected from the US Census Bureau for the year 2024, which is made publicly available at https://www.census.gov/geographies/mapping-files.html Acknowledgment IM3 is a multi-institutional effort led by Pacific Northwest National Laboratory and supported by the U.S. Department of Energy's Office of Science as part of research in MultiSector Dynamics, Earth and Environmental Systems Modeling Program. License The IM3 Open Source Data Center Atlas is made available under the Open Database License: http://opendatacommons.org/licenses/odbl/1.0/. Disclaimer This material was prepared as an account of work sponsored by an agency of the United States Government. Neither the United States Government nor the United States Department of Energy, nor the Contractor, nor any or their employees, nor any jurisdiction or organization that has cooperated in the development of these materials, makes any warranty, express or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness or any information, apparatus, product, software, or process disclosed, or represents that its use would not infringe privately owned rights. Reference herein to any specific commercial product, process, or service by trade name, trademark, manufacturer, or otherwise does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States Government or any agency thereof, or Battelle Memorial Institute. The views and opinions of authors expressed herein do not necessarily state or reflect those of the United States Government or any agency thereof. PACIFIC NORTHWEST NATIONAL LABORATORYoperated byBATTELLEfor theUNITED STATES DEPARTMENT OF ENERGYunder Contract DE-AC05-76RL01830

Mongird, Kendall [Pacific Northwest National Labor↗
DOE OSTI2026

IM3 Open Source Data Center Atlas

IM3 Open Source Data Center Atlas Description This dataset contains locations of existing data center facilities in the United States. Data center locations were derived from OpenStreetMap (OSM), a crowd-sourced database. Data points from OSM are processed in various ways to determine additional variables provided in the data including: facility area (square feet), associated US county, and US state. This dataset can be used to identify areas of concentrated data center development and inform government and private sector planning strategies for future buildout of data centers and the infrastructure necessary to support it. Usage Notes Validation of OSM-derived data center locations is an ongoing development under the IM3 project, and the database will be updated as new information becomes available. In some instances, both the data center area (e.g., campus) and individual data center buildings are included as overlapping areas in the database. Both values are retained. Data center points, buildings, and campus areas are provided as separate layers in the downloadable data package. Note that data items are not necessarily complete across layers. That is, a specific data center may only be present as a single point geometry in the "point" layer while other data centers are represented in both the campus and building layers. In some cases, data center campuses and/or buildings straddle a county boundary line. Mappings to both counties are retained in the database as separate rows. These data rows will have the same data center id information, but each will have different county information. Crowd-sourced data, by nature, relies on individuals and communities to provide information. As a result, some data may be missing where it has not yet been reported. As we collect information on additional data center locations and as OSM receives additional contributions, the database will be updated to capture additional data points not yet shown. Data items will occasionally be removed from OSM if they are misidentified, if they no longer exist, if they are duplicates of another item, or similar. For that reason, updated versions of this database may not contain all data center locations included in previous versions. Technical Information Data is available for download under the following formats: GeoPackage (GPKG) CSV Geospatial data is provided in the WGS84 (EPSG:4326) coordinate reference system. The GeoPackage download contains the following layers. See usage notes for more information. "point" "building" "campus" The "point" layer includes all data from OSM that had POINT geometry type (i.e., individual coordinates). The "building" layer includes all OSM data that did not have POINT geometry and where the building tag in the OSM export was neither equal to "no" or null. Data that did not meet the "point" or "building" qualification was assumed to be a facility campus and included in the "campus" layer. The dataset contains the following parameters. Variables provided by OSM are labeled with (OSM-provided). id - unique identification number (OSM-provided with prefix of "node/", "relation/" and similar attributes removed) state - name of US state state_abb - two letter US state abbreviation state_id - state ID number county - name of US county county_id - county ID number ref - reference numbers or codes (OSM-provided) operator - the name of the company, corporation, or person in charge facility (OSM-provided) name - name of facility (OSM-provided) sqft - surface area of facility polygon, measured in square feet. Only available for "building" and "campus" layers lat - latitude of data centroid point lon - longitude of data centroid point type – represented spatial information. One of "point", "building", or "campus". geometry – POLYGON geometry of area footprint (in "campus" and "building" layers) or POINT geometry of locations (in "point" layer). This parameter is not included in the csv download. Attribution Data center locations were derived from OpenStreetMap, which is made available at openstreetmap.org under the Open Database License (ODbL). US state and county boundary information was collected from the US Census Bureau for the year 2024, which is made publicly available at https://www.census.gov/geographies/mapping-files.html Acknowledgment IM3 is a multi-institutional effort led by Pacific Northwest National Laboratory and supported by the U.S. Department of Energy's Office of Science as part of research in MultiSector Dynamics, Earth and Environmental Systems Modeling Program. License The IM3 Open Source Data Center Atlas is made available under the Open Database License: http://opendatacommons.org/licenses/odbl/1.0/. Disclaimer This material was prepared as an account of work sponsored by an agency of the United States Government. Neither the United States Government nor the United States Department of Energy, nor the Contractor, nor any or their employees, nor any jurisdiction or organization that has cooperated in the development of these materials, makes any warranty, express or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness or any information, apparatus, product, software, or process disclosed, or represents that its use would not infringe privately owned rights. Reference herein to any specific commercial product, process, or service by trade name, trademark, manufacturer, or otherwise does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States Government or any agency thereof, or Battelle Memorial Institute. The views and opinions of authors expressed herein do not necessarily state or reflect those of the United States Government or any agency thereof. PACIFIC NORTHWEST NATIONAL LABORATORYoperated byBATTELLEfor theUNITED STATES DEPARTMENT OF ENERGYunder Contract DE-AC05-76RL01830

Mongird, Kendall [Pacific Northwest National Labor↗
NASA NTRS1978

Air pollution from aircraft operations at San Jose Municipal Airport, California

The amount of air pollution discharged by arriving and departing aircraft at the San Jose Municipal Airport was estimated. These estimates were made for each one hour interval of a summer weekday in 1977. The contributions of both general aviation (personal and business aircraft) and certified air carriers (scheduled airliners) were considered. The locations at which the pollutants were discharged were estimated by approximating the flight paths of arriving and departing aircraft. Three types of pollutants were considered: carbon monoxide, hydrocarbons, and oxides of nitrogen.

Schairer, E. T.↗