Search NASA⌕ Search

NASA NTRS · 20220002528

Smart Twisting Active Rotor (STAR) – Pre-Test Predictions

Abstract

A Mach-scaled model rotor with active twist capability is in preparation for a wind tunnel test in the large lowspeed facility (LLF) of the German-Dutch wind tunnel (DNW) with international participation by DLR, US Army, NASA, ONERA, KARI, Konkuk University, JAXA, Glasgow University and DNW. To get the maximum benefit from the test and most valuable data within the available test time, the tentative test matrix was covered by predictions of the partners, active twist benefits were evaluated, and support was provided to the test team to focus on the key operational conditions.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Berend G. van der Wall, Joon W. Lim, Johannes Riemenschneider, Steffen Kalow, Gunther A. Wilke, D. Douglas Boyd, Jr., Joelle Bailly, Yves Delrieux, Italo Cafarelli, Yasutada Tanabe, Hideaki Sugawara, Sung N. Jung, Seong H. Hong, Do-Hyung Kim, Hee J. Kang, George Barakos, Rinaldo Steininger. Smart Twisting Active Rotor (STAR) – Pre-Test Predictions. https://ntrs.nasa.gov/citations/20220002528

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related reports

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↗

Noise Correction for Supersonic Inlet Geometry

Engine inlet geometry for supersonic aircraft is quite different than for subsonic aircraft. The present study considers whether inlet shape has a significant impact on the radiated sound and flyover noise. Axisymmetric two-dimensional simulations were performed for both subsonic and supersonic inlet geometries with the same acoustic input. The effect in the far field is complicated but overall impact on flyover noise from the effective perceived noise level (EPNL) metric was found to be only about 0.5 dB.

acoustics↗

Advanced Air Mobility(AAM) Ecosystems Working Group Briefing Urban Air Mobility Noise Working Group (UNWG) Subgroup 2: Ground & Flight Testing

Overview of Urban Air Mobility Noise Working Group (UNWG) activities of Subgroup 2, responsible for developing Urban Air Mobility (UAM) vehicle ground and flight testing recommendations for those tasked with evaluating the acoustic characteristics of UAM vehicles under development. This topic is being briefed to an audience at the Advanced Air Mobility (AAM) Ecosystems Working Group Meeting (AEWG).

acoustics↗