NASA STTR 2022-I Solicitation

Proposal Summary

Proposal Information

Proposal Number:
22-1- T13.01-2230
Subtopic Title:
Intelligent Sensor Systems
Proposal Title:
Machine-Learning (ML) Enabled Reliable Multi-Modal Sensor Operation for Rocket Propulsion Systems

Small Business Concern

   
Firm:
          
Alphacore, Inc.
          
   
Address:
          
304 South Rockford Drive, Tempe, AZ 85281 - 3052
          
   
Phone:
          
(480) 494-5618                                                                                                                                                                                
          

Research Institution:

   
Name:
          
Arizona State University-Tempe
          
   
Address:
          
University Drive and Mill Avenue, AZ 85281 -
          
   
Phone:
          
(480) 727-7547                                                                                                                                                                                
          

Principal Investigator:

   
Name:
          
Dr. Joseph Smith
          
   
E-mail:
          
engineering@alphacoreinc.com
          
   
Address:
          
304 South Rockford Drive, AZ 85281 - 3052
          
   
Phone:
          
(480) 494-5618                                                                                                                                                                                
          

Business Official:

   
Name:
          
Esko Mikkola
          
   
E-mail:
          
engineering@alphacoreinc.com
          
   
Address:
          
304 S Rockford Dr, AZ 85281 - 3052
          
   
Phone:
          
(480) 494-5618                                                                                                                                                                                
          

Summary Details:

   
Estimated Technology Readiness Level (TRL) :                                                                                                                                                          
Begin: 2
End: 4
          
          
     
Technical Abstract (Limit 2000 characters, approximately 200 words):

Alphacore and its Research Partner, Arizona State University, will develop a framework for self-calibrating sensors, backed by artificial intelligence with in-field calibration capabilities. In Phase I we will prove the feasibility of our approach by modeling MEMS and electronics-based pressure, temperature, strain, and acoustics sensors, designing electrical tests to correlate with physical characteristics, and designing a hardened parametrizable self-test IP. In Phase II we will fabricate test and prototype circuits that implement and validate the work done in Phase I, as well as extend the concepts developed in Phase I to other types of sensors.

Phase I of this program will target capacitive pressure sensors, electronics-based temperature sensors, and a MEMS based acoustic sensors. In developing the self-test IP, Alphacore will make every effort to accommodate a large portion of the commercially available collection of MEMS sensors. The self-test IP specifics will be determined based on research on commercially available devices.

This project will develop methodologies for 2-tier calibration of sensor-based machine learning systems. The goal of sensor front-end calibration is to maintain highest level of sensor performance throughout the operation. To this end, the sensor hardware is monitored and calibrated continuously in real-time based on the readings built-in self-test monitors. These monitors are implemented as electrical excitation units with an area overhead less than 5% and negligible performance impact. The monitors can be used for extracting sensor performance as well as determining an error model to calibrate the software. Sensor hardware calibration can be in terms of changing bias conditions or determining sensor offset and sensitivity that converts the voltage/current reading back to the value of the physical stimulus, i.e., pressure or acceleration.
 

          
          
     
Potential NASA Applications (Limit 1500 characters, approximately 150 words):

Alphacore’s intelligent sensors will give NASA the ability to monitor the performance and the level of strain within test structures and systems, helping engineers access more accurate info to guide advancements and risk mitigation in future systems designs. Prominent programs include propulsion system testing at Stennis Space Center, Artemis II crew vehicle and Space Launch System, the Lunar Gateway, Moon-to-Mars, and the Origin Space Telescope as well as mission concepts such as the FARSIDE, LUVOIR, HabEx, Lynx X-ray Observatory and AXIS.

          
          
     
Potential Non-NASA Applications (Limit 1500 characters, approximately 150 words):

Primary customers for monitoring sensor are in testing and designs to modernize defense capabilities like missile launch systems and nanosatellite constellations for hypersonic missile defense. Commercial spaceflight and re-launchable vehicles and satellite-based weather, global intelligence companies, high-speed vehicles, flight control systems, and autonomous vehicles can use proposed sensors.

          
          
     
Duration:     13
          
          

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