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At least 1,423 records · Page 79

Orion Cabin Lighting System: Filter Workaround for Maintaining Crew Circadian Entrainment

Introduction: Suboptimal crew circadian entrainment (CCE) is common and results in cumulative fatigue and reduced cognitive function. This may promote use of psychostimulants and hypnotics. The Orion Cabin Lighting System (OCLS) consists of 15 dimmable lamps circuited to several zones. The OCLS monochromatic white lamp design is insufficient for maintaining CCE. While blue light (480-nm) elicits peak wake-cycle response, it is a powerful disruptor of CCE. We propose OCLS lamp filters (OLFs) as a workaround for maintaining CCE. Methods: Preliminary OLFs testing utilized a tunable-white LED to serve as a baseline lamp in the NASA Lighting Lab’s controlled environment (prototype OCLS lamps were unavailable). Illuminance and spectral irradiances were measured with the NASA Lighting Lab’s spectroradiometer. ConOps is proposed for OLFs. Results: OLFs markedly attenuated 480-nm light and illumination with minimal mass/volume requirements. ConOps includes in-flight deployment of OLFs and reducing OCLS lamp intensity prior to bedtime. Pros: minimal mass/volume, no added power, and a simplistic design. Cons: manual twice-daily articulation of OLFs, undetermined frangibility/flammability/off-gassing and effects on thermal regulation, and untested task illumination or color fidelity in the Orion cabin. Discussion: While OLFs aptly attenuate 480-nm light from our tunable LED lamp in the Lighting Lab’s controlled environment, they remain untested within the Orion cabin on OCLS lamps. Future tests include Orion cabin illumination optimization for appropriate Lux delivery and ensuring task/color fidelity with OLFs deployed. Adequate OCLS cooling should be similarly assessed. Other safety testing includes OLF frangibility/flammability/off-gassing in an enriched-O 2 /hypobaric environment. Together, these data will demonstrate OLFs provide a viable workaround for maintaining CCE further ensuring mission safety and success.

Carlos Rene Dostal↗

November Mega-AI Newsletter

Mega AI, an internal investment at Pacific Northwest National Laboratory, aims to develop next-generation artificial intelligence (AI) capabilities unique to the Department of Energy national lab complex to address research gaps in large-scale multimodal representation learning, multitask inferences, and the need for increased generalizability, rapid adaptivity, and usability of AI technologies. In this newsletter, we highlight recent developments in the research community on next-gen AI technologies focusing on massive-scale model development, deployment and evaluation, data and code availability, model interactions, and new features and capabilities that are relevant to Mega AI’s goals and science and security applications.

Volkova, Svitlana↗

Understanding Multifamily Energy Use in the Greater Columbia-Fayetteville-Jefferson City-Joplin-Springfield-Wichita Areas: Building Stock Segmentation for Retrofit Planning

This report is an addendum to a publication series that focuses on approximately 100 different local geographies, or "clusters". This addendum expands the report series to include large multifamily building characteristics as well as energy and emission data for each local geography. The intention of this addendum is to help policymakers at the city, county, and state levels better understand building energy use and emissions in large multifamily buildings.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Understanding Multifamily Energy Use in the Albuquerque-Santa Fe Area: Building Stock Segmentation for Retrofit Planning

This report is an addendum to a publication series that focuses on approximately 100 different local geographies, or "clusters". This addendum expands the report series to include large multifamily building characteristics as well as energy and emission data for each local geography. The intention of this addendum is to help policymakers at the city, county, and state levels better understand building energy use and emissions in large multifamily buildings.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Accelerating Discovery of Atomistic Defects via Machine Learning

The quantification of defects such as vacancies in crystalline structures is a cornerstone of materials science research. Traditional efforts often rely on manual detection, a process that is time-intensive, prone to human error, and challenging to scale. Here we leverage machine learning (ML) methods to identify and quantify vacancies within a crystalline lattice, aiming to expedite detection while improving accuracy. Additionally, we explore the transferability of these ML techniques, identifying characteristics of atomistic imaging data that complicate this task. We show how the integration of ML can drive innovation, providing a powerful tool that will play an increasingly crucial role in the future of materials science.

2D materials↗

Ozonesonde Quality Assurance: JOSIE-SHADOZ (2017) and SHALLOTS (2018)

Ozonesonde data constitute a mainstay of satellite calibration and are used for climatologies and analysis of trends, especially in the lower stratosphere where satellites are most uncertain. The electrochemical-concentration cell (ECC) ozonesonde has been deployed at ~100 stations worldwide since the 1960s, with changes over time in manufacture and procedures, including details of the cell chemical solution and data processing. As a consequence, there are biases among different stations and discontinuities in profile timeseries from individual site records. Since 1996 the Jülich [Germany] Ozone Sonde Intercomparison Experiment (JOSIE) has periodically tested ozonesondes in a simulation chamber designated the World Calibration Centre for Ozonesondes by WMO. In October- November 2017 a JOSIE campaign evaluated the sondes and procedures used in SHADOZ (Southern Hemisphere Additional Ozonesondes), a 14-station tropical and subtropical network. A distinctive feature of the 2017 JOSIE was that the tests were conducted by operators from eight SHADOZ stations; Nairobi, Natal, Irene, Costa Rica, Paramaribo, Reunion, Hanoi, Kuala Lumpur. Experimental protocols and preliminary results for the SHADOZ sonde configurations, which represent most of those in use today, are described. SHADOZ stations that follow WMO-recommended protocols record total ozone within 3% of the JOSIE reference instrument. Instrument biases noted in prior JOSIE and field tests like BESOS (2004) were noted in JOSIE-2017, with maximum effect in the stratosphere. In June 2018 we organized a series of dual launches during the OWLETS II campaign in the Maryland and Chesapeake Bay area (SHALLOTS = SHADOZ-OWLETS ParaLLel Ozonesonde Test Study). Instrument and solution types were varied as in JOSIE-2017 and three radiosonde-ozonesonde variants were tested. An example of a parallel sampling in SHALLOTS, from a Greenbelt EnSCI-iMet sonde combination flown with the Wallops SPCLMS package, is illustrated in the Figure. The result was a range of biases but in general the instrument combination (EnSCI-iMet) deployed at 11 SHADOZ stations recorded ~5-10% less ozone in the stratosphere than the SPC ECC sonde flown with a Vaisala or LMS system. These 2017 and 2018 results and prior JOSIEs demonstrate that regular testing is essential to maintain best practices in ozonesonde operations and to ensure high-quality data for the ozone assessment communities.

Quality assurance↗

Open-Source Data for MAC-POSTS: Mobility Data Analytics Center - Prediction, Optimization, and Simulation Toolkit for Transportation Systems

MAC-POSTS (Mobility Data Analytics Center - Prediction, Optimization, and Simulation toolkit for Transportation Systems) is a toolkit for dynamic transportation network modeling. Developed by the Mobility Data Analytics Center (MAC) at Carnegie Mellon University, this package implements many classic dynamic transportation network models, as well as new models proposed by MAC members. It has served as one building block for many other models and research projects. As such, this package used to be treated as an internal research project of the MAC lab, and admittedly, the code base is messy, and the interface is hard to use. However, we are working hard to make it a generally usable and useful toolkit for dynamic transportation network modeling. We would really appreciate any feedback, comments, suggestions, or criticisms.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Life sciences flight experiments microcomputer

A promising microcomputer configuration for the Spacelab Life Sciences Lab. Equipment inventory consists of multiple processors. One processor's use is reserved, with additional processors dedicated to real time input and output operations. A simple form of such a configuration, with a processor board for analog to digital conversion and another processor board for digital to analog conversion, was studied. The system used digital parallel data lines between the boards, operating independently of the system bus. Good performance of individual components was demonstrated: the analog to digital converter was at over 10,000 samples per second. The combination of the data transfer between boards with the input or output functions on each board slowed performance, with a maximum throughput of 2800 to 2900 analog samples per second. Any of several techniques, such as use of the system bus for data transfer or the addition of direct memory access hardware to the processor boards, should give significantly improved performance.

Bartram, Peter N.↗

Aviation Research and the Internet

The Internet is a network of networks. It was originally funded by the Defense Advanced Research Projects Agency or DOD/DARPA and evolved in part from the connection of supercomputer sites across the United States. The National Science Foundation (NSF) made the most of their supercomputers by connecting the sites to each other. This made the supercomputers more efficient and now allows scientists, engineers and researchers to access the supercomputers from their own labs and offices. The high speed networks that connect the NSF supercomputers form the backbone of the Internet. The World Wide Web (WWW) is a menu system. It gathers Internet resources from all over the world into a series of screens that appear on your computer. The WWW is also a distributed. The distributed system stores data information on many computers (servers). These servers can go out and get data when you ask for it. Hypermedia is the base of the WWW. One can 'click' on a section and visit other hypermedia (pages). Our approach to demonstrating the importance of aviation research through the Internet began with learning how to put pages on the Internet (on-line) ourselves. We were assigned two aviation companies; Vision Micro Systems Inc. and Innovative Aerodynamic Technologies (IAT). We developed home pages for these SBIR companies. The equipment used to create the pages were the UNIX and Macintosh machines. HTML Supertext software was used to write the pages and the Sharp JX600S scanner to scan the images. As a result, with the use of the UNIX, Macintosh, Sun, PC, and AXIL machines, we were able to present our home pages to over 800,000 visitors.

Scott, Antoinette M.↗

Wireless Telemetry and Command (T and C) Program

The Wireless Telemetry and Command (T&C) program is to investigate methods of using commercial telecommunications service providers to support command and telemetry services between a remote user and a base station. While the initial development is based on ground networks, the development is being done with an eye towards future space communications needs. Both NASA and the Air Force have indicated a plan to consider the use of commercial telecommunications providers to support their space missions. To do this, there will need to be an understanding of the requirements and limitations of interfacing with the commercial providers. The eventual payoff will be the reduced operations cost and the ability to tap into commercial services being developed by the commercial networks. This should enable easier realization of EP services to the end points, commercial routing of data, and quicker integration of new services into the space mission operations. Therefore, the ultimate goal of this program is not just to provide wireless radio communications for T&C services but to enhance those services through wireless networking and provider enhancements that come with the networks. In the following chapters, the detailed technical procedure will be showed step by step. Chapter 2 will talk about the general idea of simulation as well as the implementation of data acquisition including sensor array data and GPS data. Chapter 3 will talk about how to use LabVEEW and Component Works to do wireless communication simulation and how to distribute the real-time information over the Internet by using Visual Basic and ActiveX controls. Also talk about the test configuration and validation. Chapter 4 will show the test results both from In-Lab test and Networking Test. Chapter 5 will summarize the whole procedure and give the perspective for the future consideration.

Jiang, Hui↗

Interplanetary navigation using a continental baseline large antenna arrays

Navigation is a key component of interplanetary missions and must continue to be precise with the changing landscape of antenna design. Improvements for the Deep Space Network (DSN) may include the use of antenna arrays to simulate the power of a larger single antenna at much lower operating and construction costs. Therefore, it is necessary to test the performance of arrayed antennas from a navigational point-of-view. This initial investigation focuses on the performance of arrayed antennas from a navigational point-of-view. This initial investigation focuses on the performance of delta one-way range measurements using a shorter baseline with more data collection then current systems use. With all other parameter equal, the longer the baseline, the better the accuracy for navigation making the number of data packets very important. This trade study compares baseline distances ranging from 1 to 1000km with an in use baseline, looking at a due east baseline, a due north baseline at 45 degrees East of North. The precision of the baseline systems can be found through a simulated created for this purpose using the Jet Propulsion Lab based Monte navigation and mission design tool. The simulation combines the delta one-way range measurements with two-range and two-way Doppler measurements and puts the measurements through a Kalman filter to determine an orbit solution. Noise is added along with initial errors to give the simulation realism. This study is an important step towards the assessment of the utility of arrays for navigational purposes. The preliminary results have showed a decrease in reliability as the baseline is shortened but the larger continental baselines show comparable results t that of the current Goldstone to Canberra.

very long baseline interferometry (VLBI)↗

NASA Kennedy Space Center Swamp Works 10th Anniversary: Innovative Research & Technology Development Summary

Kennedy Space Center’s (KSC) Swamp Works, provides government and commercial space ventures with the technologies required for working and living on the surfaces of the Moon or other planets and bodies in our solar system. The Swamp Works team establishes rapid, innovative and cost-effective exploration mission solutions through leveraging of partnerships across NASA, industry and academia. Concepts start small and build up fast, with lean development processes and a hands-on approach. Testing is performed in early stages to drive design improvements and progressively increase Technology Readiness Levels (TRL). Swamp Works provides concepts, architecture studies and trades, designs, data, technology development, technology demonstration hardware, flight hardware, testing, flight support and knowledge in support of the development of surface systems. It consists of several teams with associated laboratories and test capabilities. The Granular Mechanics and Regolith Operations (GMRO) Laboratory and the Electrostatics and Surface Physics Laboratory (ESPL) are co-located in the Engineering Development Lab (EDL) facility high bay. The Applied Chemistry Lab (ACL) is in an adjacent facility and other KSC labs are being influenced by the innovation methods pioneered at the Swamp Works. The Swamp Works was founded in January 2013 by a group of scientists and engineers at KSC with the over-arching vision of expanding humanity and civilization into the solar system by the use of space resources via advanced technology. Ultimately, this will create a solar system economy that will improve the human condition due to the abundance of energy and resources. This paper will summarize the projects and technology development that have been performed by the Swamp Works to celebrate its 10th Anniversary of innovation success.

Robotic Mining↗

Swamp Works Technology Development 10th Anniversary: 2013-2023

Kennedy Space Center’s (KSC) Swamp Works, provides government and commercial space ventures with the technologies required for working and living on the surfaces of the Moon or other planets and bodies in our solar system. The Swamp Works team establishes efficient, innovative and cost-effective exploration mission solutions through leveraging of partnerships across NASA, industry and academia. Concepts start small and build up momentum, with lean development processes and a hands-on approach. Testing is performed in early stages to drive design improvements and progressively increase Technology Readiness Levels (TRL). Swamp Works provides concepts, architecture studies and trades, designs, data, technology development, technology demonstration hardware, flight hardware, testing, flight support and knowledge in support of the development of surface systems. It consists of several teams with associated laboratories and test capabilities. The Granular Mechanics and Regolith Operations (GMRO) Laboratory and the Electrostatics and Surface Physics Laboratory (ESPL) are co-located in the Engineering Development Lab (EDL) facility high bay. The Applied Chemistry Lab (ACL) is in an adjacent facility and other KSC labs are being influenced by the innovation methods pioneered at the Swamp Works. The Swamp Works was founded in January 2013 by a group of scientists and engineers at KSC with the over-arching vision of expanding humanity and civilization into the solar system by the use of space resources via advanced technology. Ultimately, this will create a solar system economy that will improve the human condition due to the abundance of energy and resources. This presentation will summarize the projects and technology development that have been performed by the Swamp Works to celebrate its 10th Anniversary of innovation success.

Swamp Works↗

Swamp Works Technology Development 10th Anniversary: 2013-2023 - Innovative Research & Technology Development Summary

Kennedy Space Center’s (KSC) Swamp Works, provides government and commercial space ventures with the technologies required for working and living on the surfaces of the Moon or other planets and bodies in our solar system. The Swamp Works team establishes rapid, innovative and cost-effective exploration mission solutions through leveraging of partnerships across NASA, industry and academia. Concepts start small and build up efficiently, with lean development processes and a hands-on approach. Testing is performed in early stages to drive design improvements and progressively increase Technology Readiness Levels (TRL). Swamp Works provides concepts, architecture studies and trades, designs, data, technology development, technology demonstration hardware, flight hardware, testing, flight support and knowledge in support of the development of surface systems. It consists of several teams with associated laboratories and test capabilities. The Granular Mechanics and Regolith Operations (GMRO) Laboratory and the Electrostatics and Surface Physics Laboratory (ESPL) are co-located in the Engineering Development Lab (EDL) facility high bay. The Applied Chemistry Lab (ACL) is in an adjacent facility and other KSC labs are being influenced by the innovation methods pioneered at the Swamp Works. The Swamp Works was founded in January 2013 by a group of scientists and engineers at KSC with the over-arching vision of expanding humanity and civilization into the solar system by the use of space resources via advanced technology. Ultimately, this will create a solar system economy that will improve the human condition due to the abundance of energy and resources. This presentation will summarize the projects and technology development that have been performed by the Swamp Works to celebrate its 10th Anniversary of innovation success.

Swamp Works↗

Module-OT: A Turnkey Solution for Securing Energy Systems

The Modular Security Apparatus for Managing Distributed Cryptography for Command-and-Control Messages on Operational Technology Networks (Module-OT) is a flexible and lightweight solution for grid-edge devices focusing on end-to-end security. It is a bump- in- the-wire solution acting as a secure conduit for data between devices or systems across a network. It improves the cybersecurity posture of DER systems by providing authentication, authorization, and data integrity to secure DER communications. Additionally, it performs key management, provides data security through whitelisting Internet Protocol addresses and ports, blocks unauthorized connections, controls user access, and allows serial or Ethernet connections for added flexibility. The core software is portable to various Linux-based operating systems and is developed to be customized by the developer and researcher communities. Module-OT has been validated in the lab, has been demonstrated at a 500-KW PV-plus-storage site, and has been proven ready to secure operational technology devices. Its core functionality meets current standards, including validation procedures of the NIST Cryptographic Algorithm Validation Program (CAVP) and the Federal Information Processing Standard (FIPS 140-2). Because of its capability to provide an accessible and affordable option for stepping up security across modern energy systems, Module-OT can serve as an effective technological option to standardize cybersecurity moving forward.

cryptography↗

Leveraging Hydropower Multi-Sensor Data for Inference and Age-Informed Modeling

Increased demand of operational flexibility such as faster ramp up/down in generation, and more frequent start/stops are putting hydropower plants and their associated components in unprecedented stress. Consequently, these plants are at the high risk of extended and more frequent outage to accommodate unscheduled, and unexpected maintenance. Therefore, hydropower plants are in critical need of data driven and age-informed analysis for their regular and unscheduled operation. Yet not all hydropower plants are exhaustively equipped with sensors and/or measurement streams for their respective components – demanding solutions on how to detect, identify, and locate the cause of any event from the unobservable. Idaho National Laboratory (INL) analyzed the anonymized measurements and event records from the Hydropower Research Institute (HRI) to address this issue, as part of the Water Power Technologies Office (WPTO) funded one year multi-lab project. First, we investigated how time series of multiple sensor measurements can be leveraged to identify an event “root cause” as well as to develop an inference (i.e., estimate the unobservable) problem. INL also investigated how individual hydropower components’ reaction or response times vary across the pre-event, during event, and post-event conditions – enabling the hydropower dynamic models to be age-informed. Finally, the impact of clustering multi-sensor time series on short-term vibration prediction is analyzed. INL will present key findings from these analyses and recommend next steps for stakeholder adoption.

13 HYDRO ENERGY↗

Using Near Real-Time Mission Data for Education and Public Outreach: Strategies from the Life in the Atacama E/PO Effort

The EventScope educational telepresence project has been involved with education and public outreach for a number of NASA-sponsored missions including the Mars Exploration Rovers, the Odyssey Mission, and the Life in the Atacama project. However, during the second year of operations in the Atacama, a modified version of the EventScope public interface was used as the remote science operations interface. In addition, the EventScope lab hosted remote science operations. This intimate connection with the mission operations allowed the EventScope team to bring the experience of the mission to the public in near real-time. Playing to this strength, the lab developed strategies for releasing E/PO content as close to real-time as possible.

Myers, E.↗

Differential Property Prediction: A Machine Learning Approach to Experimental Design in Advanced Manufacturing

Advanced manufacturing techniques have enabled the production of materials with state-of-the-art properties. In many cases however, the development of physics-based models of these techniques lags behind their development in the lab. This means that material and process development proceeds largely via trial and error. This is sub-optimal since experiments are cost-, time-, and labor-intensive. In this work we propose a machine learning framework, differential property classification (DPC), which enables an experimenter to leverage machine learning's unparalleled pattern matching capability to pursue data-driven experimental design. DPC takes two possible experiment parameter sets and outputs a prediction of which will produce a material with a more desirable property specified by the operator. We demonstrate the success of DPC on AA7075 tube manufacturing process and mechanical property data using shear assisted processing and extrusion (ShAPE), an emerging solid phase processing technology. We show that by focusing on the experimenter's need to choose between multiple candidate experimental parameters, we can reframe the challenging regression task of predicting material properties from processing parameters, into a classification task on which machine learning models can achieve good performance.

advanced manufacturing, machine learning, ShAPE↗