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DOE OSTI2025

Laser wakefield acceleration driven by a discrete flying focus

Laser wakefield acceleration (LWFA) may enable the next generation of TeV-scale lepton colliders. Reaching such energies will likely require multiple LWFA stages to overcome limitations on the energy gain achievable in a single stage. The use of stages, however, introduces challenges such as alignment, adiabatic matching between stages, and a lower average accelerating gradient. Here, we propose a discrete flying focus that can deliver higher energy gain in a single stage, thereby reducing the number of stages required for a target energy. A sequence of laser pulses with staggered focal points and delays drives a plasma wave in which an electron beam experiences a near-constant accelerating gradient over distances beyond those attainable with a conventional pulse. Simulations demonstrate that a discrete flying focus with a total energy of 150 J can transfer 40 GeV per electron to a 50-pC beam in a single 30-cm stage, corresponding to 50 dephasing lengths.

laser wakefield acceleration↗

NASA NTRS1975

Design and implementation of a medium speed communications interface and protocol for a low cost, refreshed display computer

The design and implementation of hardware and software systems involved in using a 40,000 bit/second communication line as the connecting link between an IMLAC PDS 1-D display computer and a Univac 1108 computer system were described. The IMLAC consists of two independent processors sharing a common memory. The display processor generates the deflection and beam control currents as it interprets a program contained in the memory; the minicomputer has a general instruction set and is responsible for starting and stopping the display processor and for communicating with the outside world through the keyboard, teletype, light pen, and communication line. The processing time associated with each data byte was minimized by designing the input and output processes as finite state machines which automatically sequence from each state to the next. Several tests of the communication link and the IMLAC software were made using a special low capacity computer grade cable between the IMLAC and the Univac.

Phyne, J. R.↗

NASA NTRS1994

A Low-Erosion Starting Technique for High-Performance Arcjets

The NASA arcjet program is currently sponsoring development of high specific impulse thrusters for next generation geosynchronous communications satellites (2 kW-class) and low-power arcjets for power limited spacecraft (approx. 0.5 kW-class). Performance goals in both of these efforts will require up to 1000 starts at propellant mass flow rates significantly below those used in state-of-the-art arcjet thruster systems (i.e., high specific power levels). Reductions in mass flow rate can lead to damaging modes of operation, particularly at thruster ignition. During the starting sequence, the gas dynamic force due to low propellant flow is often insufficient to rapidly push the arc anode attachment to its steady-state position in the diverging section of the nozzle. This paper describes the development and demonstration of a technique which provides for non-damaging starts at low steady-state flow rates. The technique employs a brief propellant pressure pulse at ignition to increase gas dynamic forces during the critical ignition/transition phase of operation. Starting characteristics obtained using both pressure-pulsed and conventional starting techniques were compared across a wide range of propellant flow rates. The pressure-pulsed starting technique provided reliable starts at mass flow rates down to 21 mg/s, typically required for 700 s specific impulse level operation of 2 kW thrusters. Following the comparison, a 600 start test was performed across a wide flow rate range. Post-test inspection showed minimal erosion of critical arcjet anode/nozzle surfaces.

Sankovic, John M.↗

NASA NTRS2008

Cassini Information Management System in Distributed Operations Collaboration and Cassini Science Planning

Launched on October 15, 1997, the Cassini-Huygens spacecraft began its ambitious journey to the Saturnian system with a complex suite of 12 scientific instruments, and another 6 instruments aboard the European Space Agencies Huygens Probe. Over the next 6 1/2 years, Cassini would continue its relatively simplistic cruise phase operations, flying past Venus, Earth, and Jupiter. However, following Saturn Orbit Insertion (SOI), Cassini would become involved in a complex series of tasks that required detailed resource management, distributed operations collaboration, and a data base for capturing science objectives. Collectively, these needs were met through a web-based software tool designed to help with the Cassini uplink process and ultimately used to generate more robust sequences for spacecraft operations. In 2001, in conjunction with the Southwest Research Institute (SwRI) and later Venustar Software and Engineering Inc., the Cassini Information Management System (CIMS) was released which enabled the Cassini spacecraft and science planning teams to perform complex information management and team collaboration between scientists and engineers in 17 countries. Originally tailored to help manage the science planning uplink process, CIMS has been actively evolving since its inception to meet the changing and growing needs of the Cassini uplink team and effectively reduce mission risk through a series of resource management validation algorithms. These algorithms have been implemented in the web-based software tool to identify potential sequence conflicts early in the science planning process. CIMS mitigates these sequence conflicts through identification of timing incongruities, pointing inconsistencies, flight rule violations, data volume issues, and by assisting in Deep Space Network (DSN) coverage analysis. In preparation for extended mission operations, CIMS has also evolved further to assist in the planning and coordination of the dual playback redundancy of highvalue data from targets such as Titan and Enceladus. This paper will outline the critical role that CIMS has played for Cassini in the distributed ops paradigm throughout operations. This paper will also examine the evolution that CIMS has undergone in the face of new science discoveries and fluctuating operational needs. And finally, this paper will conclude with theoretical adaptation of CIMS for other projects and the potential savings in cost and risk reduction that could potentially be tapped into by future missions.

Equils, Douglas J.↗

DOE OSTI2022

High-throughput detection of T-DNA insertion sites for multiple transgenes in complex genomes

Abstract Background Genetic engineering of crop plants has been successful in transferring traits into elite lines beyond what can be achieved with breeding techniques. Introduction of transgenes originating from other species has conferred resistance to biotic and abiotic stresses, increased efficiency, and modified developmental programs. The next challenge is now to combine multiple transgenes into elite varieties via gene stacking to combine traits. Generating stable homozygous lines with multiple transgenes requires selection of segregating generations which is time consuming and labor intensive, especially if the crop is polyploid. Insertion site effects and transgene copy number are important metrics for commercialization and trait efficiency. Results We have developed a simple method to identify the sites of transgene insertions using T-DNA-specific primers and high-throughput sequencing that enables identification of multiple insertion sites in the T 1 generation of any crop transformed via Agrobacterium . We present an example using the allohexaploid oil-seed plant Camelina sativa to determine insertion site location of two transgenes. Conclusion This new methodology enables the early selection of desirable transgene location and copy number to generate homozygous lines within two generations.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2021

Surrogate Model of Flexible Research Platform EnergyPlus Models to Enable Sensitivity Analysis

This letter report describes the surrogate models developed from the EnergyPlus model of Oak Ridge National Laboratory’s Flexible Research Platform. Two data-driven black-box models were developed, and the outputs of the surrogate models were compared with the EnergyPlus model. The two models developed are a multilayer perceptron deep learning model, and a long short-term memory (LSTM) neural network model. The three factors for selecting the black-box models are scalability, computation time, and accuracy. A total of 107 input variables were the dominant variables in determining the outputs of building energy consumptions and thermal comfort. A total of 54 output variables were identified as the prediction targets, including the system- and zone-level outputs. The large set of the simulation cases were generated by integrating sensor errors into an emulator based on EnergyPlus and Python EMS, which includes advanced control sequences from ASHRAE Guideline 36-2018: High-Performance Sequences of Operation. The surrogate models were developed based on a set of large-scale simulation runs (i.e., 4,000 runs) on a cloud platform. The comparison analysis shows that the two black-box models had good accuracy for predicting new outputs for sensitivity analysis using the root mean square error metric. As a next step, the developed surrogate models will be used to perform sensitivity analysis for different sensor impacts (e.g., sensor types, sensor locations).

42 ENGINEERING↗

NASA NTRSDate not supplied

GL4U: Using Space Biology Omics Data to Provide Bioinformatics Training for Students and Educators

NASA’s GeneLab project provides researchers open access to space-relevant multi-omics data via the Open Science Data Repository (OSDR) that can be mined to understand the effects of spaceflight on biological systems. To maximize the number of scientists who understand and utilize GeneLab data and data processing pipelines, GeneLab created GeneLab for Colleges and Universities (GL4U). GL4U provides space biology-relevant training in bioinformatics to the next generation of scientists through direct (training students) and indirect (training educators) approaches. The GL4U pilot programs were conducted in June 2021 (direct training) and 2022 (indirect training). During the pilots, students and educators at Historically Black Colleges and Universities (HBCUs) and Minority Serving Institutions (MSIs) participated in a week-long (direct training) or two-week-long (indirect training) bootcamp consisting of space biology-specific lectures and hands-on instruction using Jupyter Notebooks to analyze space biology RNA sequencing data from OSDR. During the educator pilot, participants received materials, training, and the necessary compute resources to enable them to run the bootcamp at their home institutions, thereby extending the reach of this initiative. In July 2023, GeneLab is partnering with JPL to expand GL4U to include amplicon sequencing (Amp-Seq) analysis training. During the GL4U Amp-Seq bootcamp, student and educator participants will receive training on how to analyze and interpret Amp-Seq data using the NASA GeneLab data processing pipeline. All bootcamp material, including instructions for requesting compute resources, will be made publicly available on GitHub for educators to teach the GL4U content in subsequent semesters. GL4U provides undergraduate students from underrepresented groups the opportunity to learn about NASA and Space Biology, and to enhance their career prospects by gaining hands-on experience analyzing omics data, a skillset that is highly applicable and marketable in the life sciences. We present results from pre- and post-training surveys completed by all participants of the Amp-Seq bootcamp.

Amanda M Saravia-Butler↗

DOE OSTI2024

Tailoring Growth Interfaces of Virtual Substrates for Power Electronics

Power electronics materials are poised to play a critical role in fulfilling next generation energy needs, with up to 90% of future energy demand predicted to flow through power electronics at some point. AlxGa1-xN ranks high among candidate materials, having bipolar dopability, thermal and chemical stability and an ultra-wide bandgap. However, AlGaN growth is limited by a lack of lattice-matched substrates, ultimately stunting material quality at higher thicknesses needed for power electronics applications. Further, high power applications increasingly call for fully vertical device structures, necessitating a conductive substrate. Recently our group identified the (111) plane of TaC as a conductive surface lattice-matched to Al0.55Ga0.45N, taking inspiration from prior work of AlN and GaN binaries on carbide and boride substrates. In this talk we demonstrate the growth of (111)-oriented TaC by RF sputtering. We investigate the interface of TaC with sapphire and SiC substrates and identify means to suppress competing Ta2C nucleation in order to stabilize (111)-oriented TaC. Potential stacking sequences are identified with respect to crystal structure and observed twinning in the TaC films. We next assess structural changes and film recrystallization that results from face-to-face annealing of TaC thin films at high temperatures above 1500 degrees C. Changes to grain structure and domain size are assessed by x-ray diffraction and surface morphology is explored using atomic force microscopy. Figure 1 shows significant improvements to in- and out-of-plane strain following annealing along with the formation of terraced step edges at the film surface. Strain as a function of material composition and thickness is considered, as this may play a major role in future nucleation of AlGaN layers. (1) R. J. in a face-to-face configuration, as illustrated in the schematic at left. Kaplar et al 2017, ECS J. Solid State Sci. Technol. 6 Q3061; (2) D. M. Roberts et al 2022, https://arxiv.org/abs/2208.11769; (3) T. Aizawa et al 2008, J Crys Growth 310, 1 22; (4) R. Liu et al 2002, Appl. Phys. Lett. 81, 3182-3184.

ENGINEERING↗

NASA NTRS2001

[Growth and development of plants in a sequence of generations under the conditions of space flight (experiment Greenhouse-3)]

The purpose was to study characteristic features of growth and development of several plant generations in space flight in experiment GREENHOUSE-3 as a part of the Russian-US space research program MIR/NASA in 1997. The experiment consisted of cultivation of Brassica rapa L. in board greenhouse Svet. Two vegetative cycles were fully completed and the third vegetation was terminated on day 13 on the phase of budding. The total duration of the space experiment was 122 days, i.e. same as in the ground controls. In the experiment with Brassica rapa L. viable seeds produced by the first crop were planted in space flight and yielded next crop. Crops raised from the ground and space seeds were found to differ in height and number of buds. Both parameters were lowered in the plants grown from the space seeds. The prime course for smaller size and reduced organogenic potential of plantTs reproductive system seems to be a less content of nutrients in seeds that had matured in the space flight. Experiment GREENHOUSE-3 demonstrated principle feasibility of plant reproduction in space greenhouse from seeds developed in microgravity.

manned↗

NASA NTRS2009

A Summary of the Development of a Nominal Land Landing Airbag Impact Attenuation System for the Orion Crew Module

Airborne Systems North America (formally Irvin Aerospace Inc) has developed an Airbag Landing System for the Orion Crew Module of the Crew Exploration Vehicle. This work is in support of the NASA Langley Research Center Landing System Advanced Development Project. Orion is part of the Constellation Program to send human explorers back to the moon, and then onwards to Mars and other destinations in the Solar System. A component of the Vision for Space Exploration, Orion is being developed to also enable access to space following the retirement of the Space Shuttle in the next decade. This paper documents the development of a conceptual design, fabrication of prototype assemblies, component level testing and two generations of airbag landing system testing. The airbag system has been designed and analyzed using the transient dynamic finite element code LS-DYNA(RegisteredTradeMark). The landing system consists of six airbag assemblies; each assembly comprising a primary impact venting airbag and a non-venting anti-bottoming airbag. The anti-bottoming airbag provides ground clearance following the initial impact attenuation sequence. Incorporated into each primary impact airbag is an active vent that allows the entrapped gas to exit the control volume. The size of the vent is tailored to control the flow-rate of the exiting gas. An internal shaping structure is utilized to control the shape of the primary or main airbags prior to ground impact; this significantly improves stroke efficiency and performance.

Tutt, Ben↗

NASA NTRSDate not supplied

GL4U: GeneLab for Colleges and Universities

GeneLab for Colleges and Universities (GL4U) will provide space biology-relevant training in bioinformatics to the next generation of scientists through direct and indirect approaches. The GeneLab (GL) team will host two annual data processing bootcamps, one for college-level students (direct) and one for college educators (indirect – Training of Trainers), in which participants learn to analyze space-relevant omics data hosted on GL. The first bootcamp took place in early June 2021 with about 30 SJSU undergraduate students and covered space biology-specific lectures and hands-on instruction using Jupyter Notebooks (JNs) for RNA sequence (RNAseq) data analysis. All training materials including the enclosed files listed below will be made publicly available on GitHub. RNAseq Bootcamp Lectures (attached in combined file): Introduction to NASA, Space Biology, GeneLab, and the Command Line: NASA_GL_CL_Intro_FINAL.pdf - DRAFT from initial submission NASA_SB_GL_CL_Intro_FULL.pdf - FINAL version presented during the bootcamp - only minor edits from the draft version RNAseq and Data Processing Overview: RNAseq_Overview_FINAL.pdf - DRAFT from initial submission RNAseq_Overview_FULL.pdf - FINAL version presented during the bootcamp - only minor edits from the draft version Overview of the Statistics Used for RNAseq Data Analysis: SJSU_Statistics_Intro_Lecture_FINAL.pdf - DRAFT from initial submission Statistics_Overview_FULL.pdf - FINAL version presented during the bootcamp - only minor edits from the draft version Completed JNs in HTML format (attached in combined file): Unix_Intro_JN_06-2021_completed.html R_Intro_JN_06-2021_completed.html RNAseq_fastq_to_counts_JN_06-2021_completed.html RNAseq_DGE_JN_06-2021_completed.html RNAseq Bootcamp Recordings (attached): GL4U_RNAseq_Bootcamp_June_2021_Pilot_Day1_Part_1_of_5.mp4 GL4U_RNAseq_Bootcamp_June_2021_Pilot_Day1_Part_2_of_5.mp4 GL4U_RNAseq_Bootcamp_June_2021_Pilot_Day1_Part_3_of_5.mp4 *There were issues with the part 4 recording so that is not available GL4U_RNAseq_Bootcamp_June_2021_Pilot_Day1_Part_5_of_5.mp4 GL4U_RNAseq_Bootcamp_June_2021_Pilot_Day2_Part_1_of_3.mp4 GL4U_RNAseq_Bootcamp_June_2021_Pilot_Day2_Part_2_of_3.mp4 GL4U_RNAseq_Bootcamp_June_2021_Pilot_Day2_Part_3_of_3.mp4 GL4U_RNAseq_Bootcamp_June_2021_Pilot_Day3_Part_1_of_4.mp4 GL4U_RNAseq_Bootcamp_June_2021_Pilot_Day3_Part_2_of_4.mp4 GL4U_RNAseq_Bootcamp_June_2021_Pilot_Day3_Part_3_of_4.mp4 GL4U_RNAseq_Bootcamp_June_2021_Pilot_Day3_Part_4_of_4.mp4 GL4U_RNAseq_Bootcamp_June_2021_Pilot_Day4_Part_1_of_4.mp4 GL4U_RNAseq_Bootcamp_June_2021_Pilot_Day4_Part_2_of_4.mp4 GL4U_RNAseq_Bootcamp_June_2021_Pilot_Day4_Part_3_of_4.mp4 GL4U_RNAseq_Bootcamp_June_2021_Pilot_Day4_Part_4_of_4.mp4 GL4U_RNAseq_Bootcamp_June_2021_Pilot_Day5_Part_1_of_4.mp4 GL4U_RNAseq_Bootcamp_June_2021_Pilot_Day5_Part_2_of_4.mp4 GL4U_RNAseq_Bootcamp_June_2021_Pilot_Day5_Part_3_of_4.mp4 GL4U_RNAseq_Bootcamp_June_2021_Pilot_Day5_Part_4_of_4.mp4

GeneLab↗

DOE OSTI2021

An Introduction to Word Embeddings and Language Models

Language models have advanced at a phenomenal pace over the past decade. This document provides a short introduction to terminology, word embeddings (aka low-dimensional representations), and popular large-scale language models (LMs). Word embeddings are used to represent words as numerical vectors and are context-independent, meaning a word can only have a single representation (e.g., club can only be club sandwich, not golf club ). Language models can determine the probability of a given sequence of words occurring in a sentence and can provide context to distinguish between words and phrases that sound similar. LMs are context-dependent (e.g., club can be club sandwich or golf club ) and largely fall in two main classes – autoregressive and autoencoding models. Autoregressive models are pretrained on the classic language modeling task: guess the next token having read all the previous ones. Those models can be fine-tuned and achieve great results on many tasks, the most natural application is text generation. A typical example of such models is GPT, but others include GPT-2, GPT-3, CTLR, TRANSFORMER-XL, REFORMER, XLNET. Autoencoding models are pretrained by corrupting the input tokens in some way and trying to reconstruct the original sentence. They can be fine-tuned and achieve great results on many tasks such as text generation, but their most natural application is sentence classification or token classification. A typical example of such models is BERT, but others include ROBERTA, ALBERT, XML, XML-ROBERTA, FLAUBERT AND LONGFORMER.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS1990

Gas flows in elliptical galaxies

In preparation for the next generation of x ray telescopes, researchers have begun a program investigating the evolving x ray properties of elliptical galaxies. Their galaxy models consist of a modified King profile for the luminous portion of the galaxy and can include an isothermal dark halo comprising 90 percent of the total mass. The stellar population is assumed to form at a rate which decreases exponentially on a dynamical time scale with a Salpeter initial mass function. Stellar mass loss occurs instantaneously as stars evolve off the main sequence. All stars more massive than 8 solar mass produce type II supernovae, while less massive stars loss mass through a planetary nebulae. The evolving rate of type I supernovae is normalized to a fraction, gamma sub sn I, of Tammann's (1974) value. All of this information is then incorporated into a one-dimensional hydrodynamics code to determine the evolving dynamical state of the interstellar medium.

David, L. P.↗

NASA NTRSDate not supplied

Probabalistic Risk Analysis and Thermal Margin Process for an Inflatable Aeroshell

Uncertainties always exist in atmospheric entry aeroheating environments and the thermal response of thermal protection system (TPS) material. These uncertainties are mitigated in the design by ap-plying margin and factors of safety to the TPS. Entry vehicle TPS is often conservatively over-sized for the heat loads that are experienced along the entry trajectory by stacking worst-case scenarios together. Additionally, the current TPS design and margin process used by NASA offers very little insight into the risk of over-temperature during flight and the reliability of the heat shield performance [1,3]. A probabilistic margin process can be used to calculate the amount of TPS margin necessary to survive a given entry heat load at a specified level of risk [2,3,4]. The vehicle’s initial entry state (entry velocity, flight path angle, and entry mass) determines the expected atmospheric entry environmental conditions and resulting heat load that the entry vehicle will experience. If there is flexibility in the entry state, then this process can be used to select an appropriate combination of entry state parameters and TPS size to target a desired reentry reliability. This probabilistic margin process allows engineers to make informed aeroshell design, entry-trajectory design, and TPS performance risk trades while preventing excessive TPS margin from being applied. The probabilistic TPS margin process has been performed to determine TPS thickness and entry heating constraints given an acceptable risk level for the Low Earth Orbit Flight Experiment of an Inflatable Decelerator (LOFTID) flight project. The process is used in a manner to size the entry heat load for a given flexible TPS (FTPS) thickness so that it meets project reliability standards while allowing the FTPS and the underlying inflatable structure (IS) to be pushed to adequately high temperatures. Since the LOFTID project is an experimental flight demonstration, it is de-sired to drive the FTPS and IS to temperatures that cover a large range of their thermal response models’ applicability. This will allow the thermal response models to be better improved and validated post-flight using LOFTID’s extensive instrumentation embedded within the aeroshell. The presentation demonstrates how uncertainty analysis is carried out using an end-to-end Monte Carlo process where three separate Monte Carlo simulations are run in sequence. The first Monte Carlo simulation operates on the entry trajectory model to generate trajectory parameter dispersions that are fed into the second Monte Carlo simulation. The second Monte Carlo simulation operates on the aerothermodynamics model to generate aeroheating parameter dispersions that are fed into the third Monte Carlo simulation. The third Monte Carlo simulation operates on the FTPS material thermal response model to generate the final FTPS/IS thermal response dispersions. The end-to-end Monte Carlo simulation propagates the uncertainties of each model into the next to quantify the resulting uncertainty of the FTPS/IS thermal response. The fractional contributions of the uncertain parameters in the trajectory, aerothermal, and thermal response models to the variance in the FTPS/IS thermal response is determined as a byproduct of the Monte Carlo analysis. The structural uncertainty of the FTPS thermal response model is evaluated by flight relevant ground testing and model error analysis using test measurements. This probabilistic TPS margin process had never been applied to an entry vehicle and it is one of the LOFTID project’s goals to demonstrate its merits.

Steven A. Tobin↗

DOE OSTI2023

Tailoring Growth Interfaces of Virtual Substrates for Power Electronics

Power electronics materials are poised to play a critical role in fulfilling next generation energy needs, with up to 90% of future energy demand predicted to flow through power electronics at some point.[1] Among a number of candidate materials, AlxGa1-xN is the strongest, having bipolar dopability, thermal and chemical stability, an ultra-wide bandgap, and demonstrated experimental feasibility. However, AlGaN growth is limited by a lack of lattice-matched substrates, ultimately stunting material quality at higher thicknesses needed for power electronics applications. Further, high power applications increasingly call for fully vertical device structures, necessitating a conductive substrate. [1] Recently our group identified the (111) plane of TaC as a conductive surface lattice-matched to Al0.55Ga0.45N, taking inspiration from prior work of AlN and GaN binaries on carbide and boride substrates. [2,3,4] In this talk we demonstrate the growth of (111)-oriented TaC by RF sputtering. We investigate the interface of TaC with sapphire and SiC substrates and identify means to suppress competing Ta2C nucleation in order to stabilize (111)-oriented TaC. Potential stacking sequences are identified with respect to crystal structure and observed twinning in the TaC films. We next assess structural changes and film recrystallization that results from face-to-face annealing of TaC thin films at high temperatures above 1500 degrees Celsius. Changes to grain structure and domain size are assessed by x-ray diffraction and surface morphology is explored using atomic force microscopy. Figure 1 shows significant improvements to in- and out-of-plane strain following annealing along with the formation of terraced step edges at the film surface. Strain as a function of material composition and thickness is considered, as this may play a major role in future nucleation of AlGaN layers.

CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND SU↗

NASA NTRS2010

Stage Separation Failure: Model Based Diagnostics and Prognostics

Safety of the next-generation space flight vehicles requires development of an in-flight Failure Detection and Prognostic (FD&P) system. Development of such system is challenging task that involves analysis of many hard hitting engineering problems across the board. In this paper we report progress in the development of FD&P for the re-contact fault between upper stage nozzle and the inter-stage caused by the first stage and upper stage separation failure. A high-fidelity models and analytical estimations are applied to analyze the following sequence of events: (i) structural dynamics of the nozzle extension during the impact; (ii) structural stability of the deformed nozzle in the presence of the pressure and temperature loads induced by the hot gas flow during engine start up; and (iii) the fault induced thrust changes in the steady burning regime. The diagnostic is based on the measurements of the impact torque. The prognostic is based on the analysis of the correlation between the actuator signal and fault-induced changes in the nozzle structural stability and thrust.

Luchinsky, Dmitry↗

NASA NTRSDate not supplied

GL4U: Bioinformatics training for students and educators using space omics data

Amanda Marie Saravia-butler↗

NASA NTRSDate not supplied

GL4U: Using Space Omics Data to Provide Bioinformatics Training for Students and Educators

NASA’s GeneLab project provides researchers open access to space-relevant experiment multi-omics data that can be mined to understand the effects of spaceflight on biological systems. To maximize the number of scientists who understand and utilize GeneLab data and data processing pipelines, GeneLab has created GeneLab for Colleges and Universities (GL4U). GL4U provides space biology-relevant training in bioinformatics to the next generation of scientists through direct and indirect approaches. The GeneLab team plans to host two annual data processing bootcamps, one for college-level students (direct) and one for college educators (indirect – training of trainers), in which participants learn to analyze GeneLab’s space-relevant omics data. The GL4U direct training pilot program was conducted in June 2021. During the pilot, students participated in a week-long bootcamp consisting of space biology-specific lectures and hands-on instruction using Jupyter Notebooks to analyze RNA sequence data. This pilot demonstrated the capacity of GL4U for training young scientists and encouraging data re-use. In June 2022, GL4U partnered with Jet Propulsion Laboratory’s (JPL) Planetary Protection Center of Excellence to conduct the indirect training pilot program by training educators at historically black colleges and universities (HBCUs) and minority serving institutions (MSIs). During the educator pilot, participants received materials, training, and will be provided the necessary compute resources to enable them to run the bootcamp at their home institutions or alternatively to adapt the content to implement within existing courses, thereby extending the reach of this initiative. The GL4U training program provides undergraduate students from underrepresented groups the opportunity to learn about NASA and Space Biology, and to enhance their career prospects by gaining hands-on experience analyzing omics data, a skillset that is highly applicable and marketable in the life sciences. Pre- and post-bootcamp surveys were completed by all participants and show the overwhelming success of the bootcamps.

Amanda M. Saravia-Butler↗