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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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Rocket Launch Detection with Smartphone Audio and Transfer Learning

Rocket launches generate infrasound signatures that have been detected at great distances. Due to the sparsity of the networks that have made these detections, however, most signals are detected tens of minutes to hours after the rocket launch. In this work, a method of near-real-time detection of rocket launches using data from a network of smartphones located 10–70 km from launch sites is presented. A machine learning model is trained and tested on the open-access Aggregated Smartphone Timeseries of Rocket-generated Acoustics (ASTRA), Smartphone High-explosive Audio Recordings Dataset (SHAReD), and ESC-50 datasets, resulting in a final accuracy of 97% and a false positive rate of <1%. The performance and behavior of the model are summarized, and its suitability for persistent monitoring applications is discussed.

acoustics↗
DOE OSTI2025

Smartphone application for visualizing building air leakage

Annually, unwanted air leakage through building envelopes accounts for 4 quads of energy consumption in the United States, which translates to about 10% of total building energy consumption. Locating and sealing leakage sites is crucial fordecreasing building energy consumption. Smartphones are ubiquitous and contain sophisticated cameras and highperformance processors that could be employed to visualize air leakage using the background-oriented schlieren imaging technique, making leak detection cheaper and easier. This technique requires a textured and high-contrast background such as a brick or concrete masonry unit wall, a building air leak that has a temperature difference compared with the ambient air, and an imaging system. This work focuses on using smartphones as the imaging system to visualize air leakages. The paper discusses application development and the results of testing to determine leakage visualization performance as a function of leak temperature. The results show that leaks with a temperature difference greater than 16°C compared with the ambient air temperature were visualized using existing smartphones.

Boudreaux, Philip [ORNL] (ORCID:0000000229564665)↗
DOE OSTI2024

GPS-supported smartphone app-based integrated travel diary and time-use data collection: challenges and lessons learned

Travel behaviour and time-use data are two vital data sources for travel demand modelling. Travel behaviour is traditionally collected through household travel surveys, enhanced by using GPS-supported smartphone apps for passive location data collection. However, recruiting individuals willing to install these apps with sustained motivation to continue participation has been a critical challenge. This paper shares insights from a travel and time-use data collection procedure in Chicago and Sydney using the Fourstep app. Social media platforms were utilised as a solution to recruit participants in Chicago, where an international market research company failed to accomplish the task. This paper also discusses the challenges we faced and suggests ways to overcome them, offering valuable guidance to researchers in recruiting participants for smartphone application-based data collection. It also offers an analysis of travel, time-use, and travel-based multitasking behaviours based on the data collected from the Chicago and Sydney samples.

GPS-supported smartphone apps↗
NASA NTRS2013

PhoneSat - The Smartphone Nanosatellite

PhoneSat 2.4, carried into space on November 19, 2013 aboard a Minotaur I rocket from the Mid-Atlantic Regional Spaceport at NASAs Wallops Flight Facility in Virginia, is the first of the PhoneSat family to use a two-way S-band radio to allow engineers to command the satellite from Earth. This mission also serves as a technology demonstration for a novel attitude determination and control system (ADCS) that establishes and stabilizes the satellites attitude relative to Earth. Unlike the earlier PhoneSats that used a Nexus One, PhoneSat 2.4 uses the Nexus S smartphone, which runs Googles Android operating system, and is made by Samsung Electronics Co., Suwon, So. Korea. The smartphone provides many of the functions needed by the satellite such as a central computer, data memory, ready-made interfaces for communications, navigation and power all pre-assembled in a rugged electronics package.

PhoneSat↗
NASA NTRS2017

Robust Targeting for the Smartphone Video Guidance Sensor

The Smartphone Video Guidance Sensor (SVGS) is a miniature, self-contained autonomous rendezvous and docking sensor developed using a commercial off the shelf Android-based smartphone. It aims to provide a miniaturized solution for rendezvous and docking, enabling small satellites to conduct proximity operations and formation flying while minimizing interference with a primary payload. Previously, the sensor was limited by a slow (2 Hz) refresh rate and its use of retro-reflectors, both of which contributed to a limited operating environment. To advance the technology readiness level, a modified approach was developed, combining a multi-colored LED target with a focused target-detection algorithm. Alone, the use of an LED system was determined to be much more reliable, though slower, than the retro-reflector system. The focused target-detection system was developed in response to this problem to mitigate the speed reduction of using color. However it also improved the reliability. In combination these two methods have been demonstrated to dramatically increase sensor speed and allow the sensor to select the target even with significant noise interfering with the sensor, providing millimeter level precision at a range of two meters with a 1U target.

Carter, C.↗
NASA NTRS2017

Robust Targeting for the Smartphone Video Guidance Sensor

The Smartphone Video Guidance Sensor (SVGS) is a miniature, self-contained autonomous rendezvous and docking sensor developed using a commercial off the shelf Android-based smartphone. It aims to provide a miniaturized solution for rendezvous and docking, enabling small satellites to conduct proximity operations and formation flying while minimizing interference with a primary payload. Previously, the sensor was limited by a slow (2 Hz) refresh rate and its use of retro-reflectors, both of which contributed to a limited operating environment. To advance the technology readiness level, a modified approach was developed, combining a multi-colored LED target with a focused target-detection algorithm. Alone, the use of an LED system was determined to be much more reliable, though slower, than the retro-reflector system. The focused target-detection system was developed in response to this problem to mitigate the speed reduction of using color. However, it also improved the reliability. In combination these two methods have been demonstrated to dramatically increase sensor speed and allow the sensor to select the target even with significant noise interfering with the sensor, providing millimeter level accuracy at a range of two meters with a 1U target.

Carter, Christopher↗
DOE OSTI2025

Acoustic Rocket Signatures Collected by Smartphones

Rockets generate complex acoustic signatures that can be detected over a thousand kilometers from their source. While many far-field acoustic rocket signatures have been collected and released to the public, very few signatures collected at distances less than 100 km are available. This work presents a curated and annotated dataset of acoustic signatures of 243 rocket launches collected by a network of smartphones stationed at distances between 10 and 70 km from the launch sites, resulting in 1089 individual recordings. Due to the frequency dependence of atmospheric attenuation and the relatively short propagation distances, higher-frequency features not preserved in most publicly available data are observed. The signals are time-aligned to allow for different segments of the signal (ignition, launch, trajectory, chronology) to be more easily examined and compared. Initial analysis of the features of these rocket launch stages is performed, observed features are compared to those found in the existing literature, and comparisons between signals from launches of different rocket types are made. The dataset is annotated and made available to the public to aid future analysis of the characteristics and source mechanisms of rocket acoustics as well as applications such as rocket detection and classification models.

33 ADVANCED PROPULSION SYSTEMS↗
NASA NTRS2013

PhoneSat - The Smartphone Nanosatellite

NASA's PhoneSat project tests whether spacecraft can be built using smartphones to launch the lowest-cost satellites ever flown in space. Each PhoneSat nanosatellite is one cubesat unit - a satellite in a 10 cm (approx. 4 inches) cube or about the size of a tissue box - and weighs approximately 1 kg (2.2 pounds). Engineers believe PhoneSat technology will enable NASA to launch multiple new satellites capable of conducting science and exploration missions at a small fraction of the cost of conventional satellites.

COTS satellite components↗
NASA NTRS2013

PhoneSat - The Smartphone Nanosatellite

NASAs PhoneSat project will test whether spacecraft can be built using smartphones to launch the lowest-cost satellites ever flown in space. Each PhoneSat nanosatellite is one cubesat unit - a satellite in a 10 cm (approx. 4 inches) cube or about the size of a tissue box - and weighs approximately three pounds. Engineers believe PhoneSat technology will enable NASA to launch multiple new satellites capable of conducting science and exploration missions at a small fraction of the cost of conventional satellites.

COTS satellite components↗
NASA NTRS2018

Smartphone scene generator for efficient characterization of visible imaging detectors

Full characterization of imaging detectors involves subjecting them to spatially and temporally varying illumination patterns over a large dynamic range. Here we present a scene generator that fulfills many of these functions. Based on a modern smartphone, it has a number of good features, including high spatial resolution (13 um), high dynamic range (∼104), near-Poisson limited illumination stability over time periods from 100 ms to many days, and no background noise. The system does not require any moving parts and may be constructed at modest cost. We present the optical, mechanical, and software design, test data validating the performance, and application examples.

Demers, Richard T.↗
DOE OSTI2026

AI-supported mini-labs: combining smartphone-based experiments and multimodal AI

Multimedia learning has always been a topic in physics education—whether through specialized digital data acquisition systems, simulations, or animations. Due to increasing digitalization, more and more media from our everyday lives have also found their way into education in recent decades. This contribution introduces a conceptual framework and illustrative examples for AI-supported experimentation in physics education. It does not yet present empirical data but outlines directions for forthcoming classroom studies evaluating learning outcomes and engagement.

generative AI↗
NASA NTRS2016

Project Hermes 'Use of Smartphones for Receiving Telemetry and Commanding a Satellite'

TCPIP protocols can be applied for satellite command, control, and data transfer. Project Hermes was an experiment set-up to test the use of the TCPIP protocol for communicating with a space bound payload. The idea was successfully demonstrated on high altitude balloon flights and on a sub-orbital sounding rocket launched from NASAs Wallops Flight Facility. TCPIP protocols can be applied for satellite command, control, and data transfer. Project Hermes was an experiment set-up to test the use of the TCPIP protocol for communicating with a space bound payload. The idea was successfully demonstrated on high altitude balloon flights and on a sub-orbital sounding rocket launched from NASAs Wallops Flight Facility.

Telemetry↗
NASA NTRS2014

Phonesat In-flight Experience Results

Consumer technology, over the last decade, has begun to encompass devices that enable us to figure out where we are, which way we are pointing, observe the world around us, and store and transmit this information to wherever we want. Once separate consumer products such as GPS units, digital cameras and mobile phones are now combined into the modern day Smartphone. Since these capabilities are remarkably similar to those required for the multi-million dollar satellites - so why not use a multihundred dollar Smartphone instead? The PhoneSat project of NASA Ames Research Center is developing technology demonstrations utilizing these extraordinary advances to show just how simple and cheap Space can be. The style of development revolves around the "release early, release often" Silicon Valley mentality. PhoneSat is a series of 1U CubeSat size spacecrafts that use an off-the-shelf Smartphone as their onboard computer. By doing so, PhoneSat takes advantage of the high computational capability, large memory as well as ultra-tiny sensors like high-resolution cameras and navigation devices that Smartphones offer. Along with a Smartphone, PhoneSat is equipped with other commercially available technology products, such as medical brushless motors that are used as reaction wheels. Over the four years that NASA Ames Research Center has been developing the PhoneSat project, different suborbital and orbital flight activities have proven the validity of this revolutionary approach. In early 2013, the PhoneSat project launched the first triage of PhoneSats into LEO. In the five day orbital life time, the nano-satellites flew the first functioning Smartphone based satellites (using the Nexus One and Nexus S phones), the cheapest satellite (a total parts cost below $3,500) and one of the fastest on-board processors (CPU speed of 1GHz). In late 2013, the PhoneSat project launched an improved version of its bus to a higher altitude orbit which provided data about the overall system's tolerance to the space environment. In this paper, an overview of the PhoneSat project as well as a summary of the in-flight experimental results is presented. NASA Ames Research Center is carrying on its effort to bring a paradigm shift in the way we conceive Space exploration, this new approach is certainly incarnated by PhoneSat. A set of eight PhoneSat-based CubeSats is manifested to launch in 2014 with the purpose of demonstrating new technical capabilities and being a pathfinder for future Spacecraft technology missions.

CubeSat↗
DOE OSTI2025

2022 Central California Travel Study

# 2022 Central California Travel Study The 2022 Central California Travel Study collected demographic and travel pattern information to better understand household travel behavior in the state’s San Joaquin Valley region. ## Data Collection Agency The Fresno Council of Governments conducted the household travel study in collaboration with metropolitan planning organizations in Fresno, Kern, Kings, Madera, Merced, San Joaquin, Stanislaus, and Tulare counties in California. ## Survey Methodology The two-part study consisted of a survey and a travel diary. The survey gathered data on household demographic composition and typical travel behaviors. The travel diary gathered individual travel data during a specified travel period for all members of a given household. ## Travel Diary Methods Households with smartphones were encouraged to complete their travel diaries using the rMove smartphone app for up to seven consecutive days. Households without smartphones or those unwilling to participate via smartphone completed their travel diaries online (using the web-version of rMove) or by calling the survey call center. These households reported travel for one day (Tuesday, Wednesday, or Thursday). ## Recruitment Sampling Methods The majority of the recruitment was conducted via address-based sampling, a type of probability sampling, with a focus on reaching county-level targets in collaboration with metropolitan planning organizations in the region. Supplemental sampling methods, primarily non-probability, were employed during all waves of data collection to improve survey representation. The supplemental sample included targeted outreach to hard-to-survey populations via transit rider email lists; local housing authorities; Nichols Research, a California-based market research firm; and the Ipsos™ KnowledgePanel, an online random probability panel. See the documentation for more information about sampling and weighting. ## Survey Records, Data, and Documentation In total, 7,406 households completed 19,084 surveys representing 150,012 trips across 42,567 person-days.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗