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At least 145 records · Page 8

Development of magnetic field monitoring system for the MAGIS-100 experiment

The MAGIS-100 collaboration is building a long-baseline atom interferometer designed to investigate dark matter, novel forces, gravitational waves, and quantum science. A major design challenge is external, time-varying magnetic fields, the effect of which can mimic gravitational waves or expected dark matter signals. Several mitigations will be enacted, including mu-metal shielding and a suite of magnetometers. This presentation will discuss the development of a magnetic field monitoring system based on commercial magneto-inductive sensors to be installed at several points along the interferometer.

Arce, Edwin [Unlisted; Fermilab]↗

Nanopore Sequencing-Based Microbial Air Profiling Method for Crewed Spacecraft

Microbial monitoring of the International Space Station (ISS) atmosphere is vital to maintaining the health of the spacecraft and crew. Key to NASA’s microbial risk assessment is the identity of contaminating microorganisms in the environment. Historically, this has been achieved through impaction-based air sampling followed by culture. Identification of the microorganisms present requires sample return to Earth and lab-based analyses. While this culture-based approach has served to provide alerts to anomalies and overall confidence in the controls in place, it is not suitable for exploration missions with no sample return. Recently, significant advancements in molecular-based microbial monitoring via nanopore sequencing have been implemented onboard the ISS. Building on this work, multiple commercially available air samplers, compatible with downstream molecular analysis, were evaluated for use in the spaceflight environment. Through this assessment, the Coriolis Compact (Bertin Technologies), which uses cyclonic technology to collect bioaerosols onto the surface of a sterile cone, was selected for a larger-scale comparison to the current culture-based monitoring method. Using the Coriolis Compact, 1000 L of air was collected from the breakroom of an office building and a fitness center. The buffer used to dissociate the microbial cells from the surface of the cone was split between the NASA Microbiology Laboratory’s standard culture and Sanger sequencing-based method and the culture-independent nanopore sequencing method. The bacteria identified through culture were present in the nanopore data, with Micrococcus, Staphylococcus, and Moraxella being the most common cultured isolates, which is expected based on the media and growth conditions. Not surprisingly, the nanopore data yielded much higher diversity and paralleled that of previous atmospheric microbiome studies of human-occupied built environments. As compared to the culture-based data where the breakroom and fitness center data sets cluster in proximity, the nanopore data depicts the contrast of these atmospheric microbiomes. Moreover, the nanopore data were sufficient to meet NASA’s risk assessment needs and noted the culturable isolates routinely observed. This nanopore-based atmospheric microbial profiling method will enable near real-time environmental monitoring of crewed spacecraft as future missions extend beyond low-Earth orbit.

Brandon Dunbar↗

Reuse of a Formal Model for Requirements Validation

This paper reports experience from how a project engaged in the process of requirements analysis for evolutionary builds can reuse the formally specified design model produced for a similar, earlier project in the same domain. Two levels of reuse are described here. First, a formally specified generic design model was generated on one project to systematically capture the design commonality in a set of software monitors on board a spacecraft. These monitors periodically check for faults and invoke recovery software when needed. The paper summarizes the use of the design model to validate the software design of the various monitors on that first project. Secondly, the paper describes how the formal design model created for the first project was reused on a second, subsequent project. The model was reused to validate the evolutionary requirements for the second project's software monitors, which were being developed in a series of builds. Some mismatches due to the very different architectures on the two projects suggested changes to make the model more generic. In addition, several advantages to the reuse of the first project's formal model on the second project are reported.

Lutz, Robyn R.↗

Development of a magnetic field monitoring system for the MAGIS-100 experiment

The MAGIS-100 collaboration is building a long-baseline atom interferometer designed to investigate dark matter, novel forces, gravitational waves, and quantum science. A major design challenge is external, time-varying magnetic fields, the effect of which can mimic gravitational waves or expected dark matter signals; static magnetic fields must also be tightly controlled to manage measurement resolution. Several tools are being applied to the problem, including mu-metal shielding, field biasing, and a suite of magnetometers. This report details the development of a magnetic field monitoring system to be built from commercially available parts and installed at seventeen locations, one for each of the modular sections making up the length of the MAGIS-100 apparatus.

Arce, Edwin [Unlisted, US, CA]↗

Application of Machine Learning to Rotorcraft Health Monitoring

Machine learning is a powerful tool for data exploration and model building with large data sets. This project aimed to use machine learning techniques to explore the inherent structure of data from rotorcraft gear tests, relationships between features and damage states, and to build a system for predicting gear health for future rotorcraft transmission applications. Classical machine learning techniques are difficult, if not irresponsible to apply to time series data because many make the assumption of independence between samples. To overcome this, Hidden Markov Models were used to create a binary classifier for identifying scuffing transitions and Recurrent Neural Networks were used to leverage long distance relationships in predicting discrete damage states. When combined in a workflow, where the binary classifier acted as a filter for the fatigue monitor, the system was able to demonstrate accuracy in damage state prediction and scuffing identification. The time dependent nature of the data restricted data exploration to collecting and analyzing data from the model selection process. The limited amount of available data was unable to give useful information, and the division of training and testing sets tended to heavily influence the scores of the models across combinations of features and hyper-parameters. This work built a framework for tracking scuffing and fatigue on streaming data and demonstrates that machine learning has much to offer rotorcraft health monitoring by using Bayesian learning and deep learning methods to capture the time dependent nature of the data. Suggested future work is to implement the framework developed in this project using a larger variety of data sets to test the generalization capabilities of the models and allow for data exploration.

machine learning↗

Boreal Forest Watch: A BOREAS Outreach Program

The Boreal Forest Watch program was initiated in the fall of 1994 to act as an educational outreach program for the BOREAS project in both the BOREAS Southern Study Area (SSA) and Northern Study Area (NSA). Boreal Forest Watch (13FW) was designed to introduce area high school teachers and their students to the types of research activities occurring as part of the BOREAS study of Canadian boreal forests. Several teacher training workshops were offered to teachers from central and northern Saskatchewan and northern Manitoba between May, 1995 and February, 1999; teachers were introduced to techniques for involving their students in on-going environmental monitoring studies within local forested stands. Boreal Forest Watch is an educational outreach program which brings high school students and research scientists together to study the forest and foster a sustainable relationship between people and the planetary life-support system we depend upon. Personnel from the University of New Hampshire (UNH), Complex Systems Research Center (CSRC), with the cooperation from the Prince Albert National Park (PANP), instituted this program to help teachers within the BOREAS Study Areas offer real science research experience to their students. The program has the potential to complement large research projects, such as BOREAS, by providing useful student- collected data to scientists. Yet, the primary goal of BFW is to allow teachers and students to experience a hands-on, inquiry-based approach to leaming science - emulating the process followed by research scientists. In addition to introducing these teachers to on-going BOREAS research, the other goals of the BFW program were to: 1) to introduce authentic science topics and methods to students and teachers through hands-on, field-based activities; and, 2) to build a database of student-collected environmental monitoring data for future global change studies in the boreal region.

Rock, Barrett N.↗

Enhancing Human Health Using Space Imagery: Summary of Research

The International Space University (ISU) 2002 Summer Session was conducted in Pomona, California, June 29-August 30, 2002. Ninety-nine professionals and students from thirty-one countries attended the Summer Session. More than half of these students participated in the Student Research Design Project entitled, "HI-STAR: Health Improvements through Space Technologies and Resources." ISU's interdisciplinary Student Research Design Projects are intended to have great educational value for the participants and, at the same time, to result in a product that will be useful to the field. The HI-STAR project was a success on both counts. The mission of the ISU students' effort on HI-STAR was to develop and promote a global strategy to help combat malaria using space technology. Like the tiny yet powerful mosquito, HI-STAR is a small program that aspires to make a difference. Timely detection of malaria danger zones is essential to help health authorities and policy makers make decisions about how to manage limited resources for combating malaria. In 2001, the technical support network for prevention and control of malaria epidemics published a study called "Malaria Early Warning Systems: Concepts, Indicators and Partners." This study, funded by Roll Back Malaria, a World Health Organization initiative, offered a framework for a monitoring and early warning system. HI-STAR seeks to build on this proposal and enhance the space elements of the suggested framework. Malaria disease dynamics and distributions are related to environmental variables. From space, environmental conditions that support the growth of mosquito populations can be monitored, Malaria-specific information can be gathered from satellite-borne remote sensing instruments and ground-based sensors. This information can be integrated via geographic information systems (GIS) into a Malaria Information System (MIS) that can provide assessment analyses and risk maps as output. HI-STAR defines and suggests the development of an active MIS as a low-cost tool to help organizations plan their efforts to fight malaria.

Finarelli, Margaret G.↗

The design of an intelligent human-computer interface for the test, control and monitor system

The graphical intelligence and assistance capabilities of a human-computer interface for the Test, Control, and Monitor System at Kennedy Space Center are explored. The report focuses on how a particular commercial off-the-shelf graphical software package, Data Views, can be used to produce tools that build widgets such as menus, text panels, graphs, icons, windows, and ultimately complete interfaces for monitoring data from an application; controlling an application by providing input data to it; and testing an application by both monitoring and controlling it. A complete set of tools for building interfaces is described in a manual for the TCMS toolkit. Simple tools create primitive widgets such as lines, rectangles and text strings. Intermediate level tools create pictographs from primitive widgets, and connect processes to either text strings or pictographs. Other tools create input objects; Data Views supports output objects directly, thus output objects are not considered. Finally, a set of utilities for executing, monitoring use, editing, and displaying the content of interfaces is included in the toolkit.

Shoaff, William D.↗

How to Leverage the Power of SAR Observations for Forest Monitoring Systems

Earth observations from Synthetic Aperture Radar (SAR) can provide unique observations related to forest structure and condition. Furthermore, SAR has many potential applications in forest monitoring systems, particularly where clouds have impeded optical observations. Currently, there is a reliable, freely-available, provision of SAR datasets, such as Sentinel-1, and there are plans to have more observations in the near- future (NISAR, BIOMASS). Given SAR’s enhanced earth observation characteristics, there is broad interest in using SAR datasets for decision support systems, such as deforestation early warning systems. However, applications of SAR are still underutilized. What is preventing users from using SAR data in their decision support systems? This study documents the experiences and lessons learned from the SERVIR network on the main limitations of incorporating SAR datasets into existing forest monitoring systems. This research also focuses on the major technical and scientific barriers we experience and best practices to address them. The results of this study are part of the SERVIR- SilvaCarbon collaboration. The primary goal of this collaboration is to build capacity in the applied use of SAR for forest monitoring and biomass estimation. The products of this effort aim to start closing the gap between SAR-science and forest applications. We will also present results to generate applied-ready knowledge for SAR.

SAR↗

Optimizing Hydronic Heating for Comfort and Performance in Multifamily Housing

Inefficient control settings in multifamily boilers often lead to substantial energy and cost penalties. To address this, a Fault Detection and Diagnostic (FDD) tool was developed to automate data analysis and identify operational faults such as suboptimal outdoor temperature sensor placement, misconfigured outdoor air reset (OAR) curves, excess boiler cycling, and domestic hot water (DHW) setpoint errors. By comparing pre- and post-implementation periods and applying engineering models, the tool quantifies energy savings and reduces manual analysis time by over 90%. Testing on over 100 monitored sites and a targeted subset of 12 buildings showed an average 11% energy savings from remote optimization; further validation across 19 OAR curve changes confirmed the tool’s accuracy, predicting actual savings within ±5% for most cases. Simple payback can be under three years for many multifamily buildings, though rising hardware, labor, and fuel costs create uncertainties, and decarbonization goals increasingly shift focus to electrification. The FDD tool remains invaluable for optimizing existing boilers, enhancing future electrification measures, and adapting to new technologies by refining building load estimates. In doing so, it supports both near-term efficiency and long-term transitions to low-carbon alternatives, ensuring buildings achieve substantial cost and energy benefits throughout their system lifecycles.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Matrix Failure Modes and Effects Analysis as a Knowledge Base for a Real Time Automated Diagnosis Expert System

Failure Modes and Effects Analysis contain a wealth of information that can be used to create the knowledge base required for building automated diagnostic Expert systems. A real time monitoring and diagnosis expert system based on an actual NASA project's matrix failure modes and effects analysis was developed. This Expert system Was developed at NASA Ames Research Center. This system was first used as a case study to monitor the Research Animal Holding Facility (RAHF), a Space Shuttle payload that is used to house and monitor animals in orbit so the effects of space flight and microgravity can be studied. The techniques developed for the RAHF monitoring and diagnosis Expert system are general enough to be used for monitoring and diagnosis of a variety of other systems that undergo a Matrix FMEA. This automated diagnosis system was successfully used on-line and validated on the Space Shuttle flight STS-58, mission SLS-2 in October 1993.

Herrin, Stephanie↗

Evaluation of portable air samplers for monitoring airborne culturable bacteria

Airborne culturable bacteria were monitored at five locations (three in an office/laboratory building and two in a private residence) in a series of experiments designed to compare the efficiency of four air samplers: the Andersen two-stage, Burkard portable, RCS Plus, and SAS Super 90 samplers. A total of 280 samples was collected. The four samplers were operated simultaneously, each sampling 100 L of air with collection on trypticase soy agar. The data were corrected by applying positive hole conversion factors for the Burkard portable, Andersen two-stage, and SAS Super 90 air samplers, and were expressed as log10 values prior to statistical analysis by analysis of variance. The Burkard portable air sampler retrieved the highest number of airborne culturable bacteria at four of the five sampling sites, followed by the SAS Super 90 and the Andersen two-stage impactor. The number of bacteria retrieved by the RCS Plus was significantly less than those retrieved by the other samplers. Among the predominant bacterial genera retrieved by all samplers were Staphylococcus, Bacillus, Corynebacterium, Micrococcus, and Streptococcus.

NASA Center JSC↗

Wireless Sensor Networks for Developmental and Flight Instrumentation

Wireless sensor networks (WSN) based on the IEEE 802.15.4 Personal Area Network and ZigBee Pro 2007 standards are finding increasing use in home automation and smart energy markets providing a framework for interoperable software. The Wireless Connections in Space Project, funded by the NASA Engineering and Safety Center, is developing technology, metrics and requirements for next-generation spacecraft avionics incorporating wireless data transport. The team from Stennis Space Center and Mobitrum Corporation, working under a NASA SBIR grant, has developed techniques for embedding plug-and-play software into ZigBee WSN prototypes implementing the IEEE 1451 Transducer Electronic Datasheet (TEDS) standard. The TEDS provides meta-information regarding sensors such as serial number, calibration curve and operational status. Incorporation of TEDS into wireless sensors leads directly to building application level software that can recognize sensors at run-time, dynamically instantiating sensors as they are added or removed. The Ames Research Center team has been experimenting with this technology building demonstration prototypes for on-board health monitoring. Innovations in technology, software and process can lead to dramatic improvements for managing sensor systems applied to Developmental and Flight Instrumentation (DFI) aboard aerospace vehicles. A brief overview of the plug-and-play ZigBee WSN technology is presented along with specific targets for application within the aerospace DFI market. The software architecture for the sensor nodes incorporating the TEDS information is described along with the functions of the Network Capable Gateway processor which bridges 802.15.4 PAN to the TCP/IP network. Client application software connects to the Gateway and is used to display TEDS information and real-time sensor data values updated every few seconds, incorporating error detection and logging to help measure performance and reliability in relevant target environments. Test results from our prototype WSN running the Mobitrum software system are summarized and the implications to the scalability and reliability for DFI applications are discussed. Our demonstration system, incorporating sensors for life support system and structural health monitoring is described along with test results obtained by running the demonstration prototype in relevant environments such as the Wireless Habitat Testbed at Johnson Space Center in Houston. An operations concept for improved sensor process flow from design to flight test is outlined specific to the areas of Environmental Control and Life Support System performance characterization and structural health monitoring of human-rated spacecraft. This operations concept will be used to highlight the areas where WSN technology, particularly plug-and-play software based on IEEE 1451, can improve the current process, resulting in significant reductions in the technical effort, overall cost and schedule for providing DFI capability for future spacecraft. RELEASED -

Alena, Richard↗

Processing TES Level-1B Data

TES L1B Subsystem is a computer program that performs several functions for the Tropospheric Emission Spectrometer (TES). The term "L1B" (an abbreviation of "level 1B"), refers to data, specific to the TES, on radiometric calibrated spectral radiances and their corresponding noise equivalent spectral radiances (NESRs), plus ancillary geolocation, quality, and engineering data. The functions performed by TES L1B Subsystem include shear analysis, monitoring of signal levels, detection of ice build-up, and phase correction and radiometric and spectral calibration of TES target data. Also, the program computes NESRs for target spectra, writes scientific TES level-1B data to hierarchical- data-format (HDF) files for public distribution, computes brightness temperatures, and quantifies interpixel signal variability for the purpose of first-order cloud and heterogeneous land screening by the level-2 software summarized in the immediately following article. This program uses an in-house-developed algorithm, called "NUSRT," to correct instrument line-shape factors.

DeBaca, Richard C.↗

Operational Assessment of Apollo Lunar Surface Extravehicular Activity

Quantifying the operational variability of extravehicular activity (EVA) execution is critical to help design and build future support systems to enable astronauts to monitor and manage operations in deep-space, where ground support operators will no longer be able to react instantly and manage execution deviations due to the significant communication latency. This study quantifies the operational variability exhibited during Apollo 14-17 lunar surface EVA operations to better understand the challenges and natural tendencies of timeline execution and life support system performance involved in surface operations. Each EVA (11 in total) is individually summarized as well as aggregated to provide descriptive trends exhibited throughout the Apollo missions. This work extends previous EVA task analyses by calculating deviations between planned and as-performed timelines as well as examining metabolic rate and consumables usage throughout the execution of each EVA. The intent of this work is to convey the natural variability of EVA operations and to provide operational context for coping with the variability inherent to EVA execution as a means to support future concepts of operations.

planning and scheduling↗

Developing a Community of Practice for Applied Uses of Future PACE Data to Address Food Security Challenges

Ocean color satellite measurements have yielded valuable information about the base of the marine food web for over 20 years. The Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) mission is building an advanced spectrometer to further refine ecosystem monitoring. Higher spectral resolution data from PACE will enable identification of additional marine biological indicators and their response to multiple stressors to guide sustainable management. Seafood is an important source of protein for a significant number of people. Wild catches cannot match increasing demand and their sustainability is in question. Aquaculture is an ever more important industry to feed the world's population. We share early efforts to engage a community of practice around food security to increase satellite data product use in support of resource management, business decisions, and policy analysis. Understanding the needs of applied scientists as well as non-traditional users of satellite data early in the PACE mission process will improve planning and preparation for a broader user base and hopefully help to mitigate food insecurity.

Schollaert Uz, Stephanie↗

Pyroelectric Sandwich Thermal Energy Harvesters

Systems, methods, and devices of the various embodiments provide pyroelectric sandwich thermal energy harvesters. In the various embodiment pyroelectric sandwich thermal energy harvesters, generated electrical energy may be stored in a super-capacitor/battery as soon as it is generated. The various embodiment pyroelectric sandwich thermal energy harvesters may harvest electrical energy from any environment where temperature variations occur. The various embodiment pyroelectric sandwich thermal energy harvesters may be power sources for space equipment and vehicles in space and/or on earth, as well as the for wireless sensor networks, such as health monitoring systems of oil pipes, aircraft, bridges, and buildings.

Xu, Tian-Bing↗

Building a Bilingual Google Earth Engine Dashboard to Increase Accessibility to Long-term Time Series Remote Sensing Data for Monitoring Saline System Changes in Chile’s Atacama Desert

Saline systems, consisting of salt flats, ponds, and marshes, provide vital water resources to wildlife and communities in northern Chile’s Atacama Desert, one of the driest regions in the world. Mining is extensive in the Atacama, which contains 30% of the world’s lithium reserves and is abundant in potassium and boron. The groundwater that feeds into salt marshes and ponds is extracted in large volumes for mining operations, limiting the availability of water for ecosystems. However, identifying long-term and large-scale environmental impacts from local lithium mining on the saline systems is limited by region inaccessibility and terrain variability. Open access satellite imagery and cloud computing technology has made studying Atacama saline systems feasible and allowed for collaboration across different agencies and countries. The NASA DEVELOP Program partnered with Chile’s la Universidad de La Serena and Servicio Nacional de Geología y Minería (SERNAGEOMIN) to create the Saline Analysis Tool (SalT) in Google Earth Engine (GEE). SalT is used to analyze the extent and distribution of remote saline systems in the Atacama from 1986 to the present day. The tool filters Landsat 5 Thematic Mapper (TM) and Landsat 8 Operational Land Imager (OLI) data from GEE’s data catalog and creates a single composite image per year for analysis. Additional output analyses include land cover classification, Normalized Difference Vegetation Index (NDVI) and Normalized Difference Water Index (NDWI) raster images that can be displayed on the map interface or exported. The tool can also generate time-lapse videos and charts displaying NDVI, NDWI, and land cover over time. A key feature of the tool is the use of a bilingual graphical user interface to make analysis accessible and customizable to different users’ needs—SalT provides options to select an analysis area, analysis time period, and outputs to display or export. The tool also incorporates new Earth observations as they are added to GEE’s catalog. The ability to easily visualize and analyze long-term remote sensing imagery will enable SERNAGEOMIN and la Universidad de la Serena to continually monitor changes in these saline systems and inform future land management policy.

NASA DEVELOP↗