SEARCH · Search NASA

Results for “space parts consortium”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 37 records · Page 2

All sources NASA NTRS DOE OSTI

NASA NTRS2005

California Space Grant Consortium

The organizational and administrative structure of the CaSGC has the Consortium Headquarters Office (Principal Investigator - Dr. John Kosmatka, California Statewide Director - Dr. Michael Wiskerchen) at UC San Diego. Each affiliate member institution has a campus director and an scholarship/fellowship selection committee. Each affiliate campus director also serves on the CaSGC Advisory Council and coordinates CMIS data collection and submission. The CaSGC strives to maintain a balance between expanded affiliate membership and continued high quality in targeted program areas of aerospace research, education, workforce development, and public outreach. Associate members are encouraged to participate on a project-by-project basis that meets the needs of California and the goals and objectives of the CaSGC. Associate members have responsibilities relating only to the CaSGC projects they are directly engaged in. Each year, as part of the CaSGC Improvement Plan, the CaSGC Advisory Council evaluates the performance of the affiliate and associate membership in terms of contributions to the CaSGC Strategic Plan, These CaSGC membership evaluations provide a constructive means for elevating productive members and removing non-performing members. This Program Improvement and Results (PIR) report will document CaSGC program improvement results and impacts that directly respond to the specific needs of California in the area of aerospace-related education and human capital development and the Congressional mandate to "increase the understanding, assessment, development and utilization of space resources by promoting a strong education base, responsive research and training activities, and broad and prompt dissemination of knowledge and technology".

Kosmatka, John↗

NASA NTRSDate not supplied

Cultivating Capabilities for Lunar Extreme Environments

Space Directive 1 establishes that NASA is to " return of humans to the Moon for long-term exploration and utilization". Inherent in this direction, there are environmental challenges including ionizing radiation, extreme thermal ranges, and lunar dust. NASA is making significant investments in technologies to address the array of destinations and mission applications inherent in that challenge. As part of commercial, industry, and academic engagement, NASA has established Lunar Surface Innovation Consortium (LSIC) as an open forum to engage a larger community through six focus groups: in-situ resource utilization (ISRU), excavation and construction, power, extreme access, dust mitigation, and extreme environments. A general overview of the investments – both technology and community development – is presented.

technology↗

NASA NTRS1993

Activities involving aeronautical, space science, and technology support for minority institutions

The Final Report addressed the activities with which the Interracial Council for Business Opportunity (ICBO) was involved over the past 12 months. ICBO was involved in the design and development of a CARES Student Tracking System Software (CARES). Cares is intended to provide an effective means of maintaining relevant current and historical information on NASA-funded students through a range of educational program initiatives. ICBP was extensively involved in the formation of a minority university consortium amd implementation of collaborative research activities by the consortium as part of NASA's Mission to Planet Earth/Earth Observing System. ICBO was involved in the formation of an HBCU/MI Consortium to facilitate technology transfer efforts to the small and minority business community in their respective regions.

Source record↗

NASA NTRSDate not supplied

INCREASING THE TRANSPARENCY AND REPRODUCIBILITY OF SPACE RADIATION SCIENCE: THE RADIATION BIOLOGY ONTOLOGY

Among the primary objectives of the Open/Open-Source Science paradigm are making scientific investigation data transparent and results reproducible [1], objectives shared by the FAIR principles [2]. To accomplish this, the conceptual framework that includes all the investigation objects needs to be accurately captured and communicated to all data consumers. A large part of this requires using metadata standards to annotate data collected. These standards should be readily accessible, informed by scientific community consensus and sufficiently specific to encompass all of the important aspects of the investigation. Starting in 2020 we have been co-leading an open consortium to develop a new metadata standard, the Radiation Biology Ontology (RBO), through the Open Biological and Biomedical Ontologies (OBO) Foundry [3]. We began by transforming many of the terms from the National Council on Radiation Protection and Measurement into concepts that can be formally related to existing OBO Foundry classes or attributes. We then identified and imported into the RBO existing OBO Foundry classes that have obvious relevance for radiation biomedicine (for example, concepts from the Environment Ontology that describe radiative processes, and concepts from the Gene Ontology dealing with molecular and cellular responses to radiation). Finally, we scrutinized datasets from investigations of radiation effects held in NASA GeneLab and LSDA repositories and added additional classes, instances, and attributes into the RBO that should be used to annotate these data. We developed the RBO using the open-source tools of GitHub and publish the RBO periodically through the NIH/NCBI BioPortal website, so systems worldwide can leverage the knowledge it contains [4]. This initial phase of concept modeling has yielded an RBO that at present has more than 300 declared concepts, with more than 3500 additional concepts imported from other OBO Foundry ontologies. While this first phase has focused on concepts for annotating samples, environments, exposures, and measurements, the next phase will center on supporting annotation of results and findings, such as concept models of molecular, cellular and tissue effects. The value of the RBO will be determined in part by our ability to engage the community in its development, and we have established a Radiobiology Informatics Consortium with unrestricted membership as the owner of the RBO in order to encourage investigators, system owners and other to join in this effort. Anyone can report issues or request new concept modeling or other features directly on GitHub. By using the BioPortal application programming interface, systems can pose dynamic queries to the latest version of the RBO for information on individual classes or entire hierarchies; this design eliminates the need for systems to be updated in order to use newer versions of the RBO. We hope to contribute to the advancement of open radiobiological science through the continued, open development of the RBO, that will provide more precise, machine-interpretable descriptions of investigations, as well as support data meta-analysis through machine learning or other artificial intelligence methods.

knowledge↗

NASA NTRS2014

United States Nuclear Rocket Company (USNRC)

Historically, the development of advanced space technology has been accomplished by the federal government providing funding to commercial companies through the standard contracting process. Although recently, commercial space ventures, such as Space X, have begun to develop enhanced commercial space launch capabilities, and many companies provide space related services - including satellite development and operations, advanced technology development still requires (and should require) participation by the federal agency assigned this role - the National Aeronautics and Space Administration (NASA). However, this standard funding model may not be the most efficient and stable means of developing the advanced technology systems. And while the federal government does not need to be involved in areas where private industry can reasonably operate, it should remain the leader in supporting the development of new and advanced space technologies to further increase our national capability. And as these technologies mature, then private industry can begin the commercialization process, freeing up resources and funds for NASA to develop the next generations of advanced space technology. In fact, simply examining the last decades of space technology development shows that there is room for improvement. Part of the problem is that there are realistically two space frontiers. There is the commercialization frontier (the realm of Space X and others) and the exploratory frontier (the realm of NASA.). Often technologies that can support the exploratory frontier can also immediately support the commercialization frontier. Yet, these technologies are still developed under the standard model of federal funding and contracting. Is that really the best way to proceed? In this paper, the argument is put forward that a new process is required, a new paradigm. A consortium of federal agencies as well as commercial companies is needed - in a collaborative rather than a contractual relationship.

Hardin, L. A.↗

NASA NTRS2011

Single-Event Effect (SEE) Survey of Advanced Reconfigurable Field Programmable Gate Arrays: NASA Electronic Parts and Packaging (NEPP) Program Office of Safety and Mission Assurance

The NEPP Reconfigurable Field-Programmable Gate Array (FPGA) task has been charged to evaluate reconfigurable FPGA technologies for use in space. Under this task, the Xilinx single-event-immune, reconfigurable FPGA (SIRF) XQR5VFX130 device was evaluated for SEE. Additionally, the Altera Stratix-IV and SiliconBlue iCE65 were screened for single-event latchup (SEL).

Xilinx Single-Event Effects (SEE) Test Consortium↗

NASA NTRS1992

Consortium for materials development in space interaction with Space Station Freedom

The Consortium for Materials Development in Space (CMDS) is one of seventeen Centers for the Commercial Development of Space (CCDS) sponsored by the Office of Commercial Programs of NASA. The CMDS formed at the University of Alabama in Huntsville in the fall of 1985. The Consortium activities therefore will have progressed for over a decade by the time Space Station Freedom (SSF) begins operation. The topic to be addressed here is: what are the natural, mutually productive relationships between the CMDS and SSF? For management and planning purposes, the Consortium organizes its activities into a number of individual projects. Normally, each project has a team of personnel from industry, university, and often government organizations. This is true for both product-oriented materials projects and for infrastructure projects. For various projects Space Station offers specific mutually productive relationships. First, SSF can provide a site for commercial operations that have evolved as a natural stage in the life cycle of individual projects. Efficiency and associated cost control lead to another important option. With SSF in place, there is the possibility to leave major parts of processing equipment in SSF, and only bring materials to SSF to be processed and return to earth the treated materials. This saves the transportation costs of repeatedly carrying heavy equipment to orbit and back to the ground. Another generic feature of commercial viability can be the general need to accomplish large through-put or large scale operations. The size of SSF lends itself to such needs. Also in addition to processing equipment, some of the other infrastructure capabilities developed in CCDS projects may be applied on SSF to support product activities. The larger SSF program may derive mutual benefits from these infrastructure abilities.

Lundquist, Charles A.↗

NASA NTRS2005

Event Generators for Simulating Heavy Ion Interactions of Interest in Evaluating Risks in Human Spaceflight

Simulating the Space Radiation environment with Monte Carlo Codes, such as FLUKA, requires the ability to model the interactions of heavy ions as they penetrate spacecraft and crew member's bodies. Monte-Carlo-type transport codes use total interaction cross sections to determine probabilistically when a particular type of interaction has occurred. Then, at that point, a distinct event generator is employed to determine separately the results of that interaction. The space radiation environment contains a full spectrum of radiation types, including relativistic nuclei, which are the most important component for the evaluation of crew doses. Interactions between incident protons with target nuclei in the spacecraft materials and crew member's bodies are well understood. However, the situation is substantially less comfortable for incident heavier nuclei (heavy ions). We have been engaged in developing several related heavy ion interaction models based on a Quantum Molecular Dynamics-type approach for energies up through about 5 GeV per nucleon (GeV/A) as part of a NASA Consortium that includes a parallel program of cross section measurements to guide and verify this code development.

Wilson, Thomas L.↗

NASA NTRS1991

An assessment of secondary loss reduction techniques for STME LOX turbine

One of the primary objectives of the National Launch System (NLS) program, explored jointly by NASA and several other government agencies, is to develop a new Space Transportation Main Engine (STME) which will perform better and is more reliable than the present Space Shuttle Main Engine (SSME). Preliminary design of the Oxidizer (LOX) turbine in STME has recently been completed by Pratt and Whitney (P&W). It is a single-stage, high impulsive turbine with an approximately 170-degree deflection angle across the rotor. Due mainly to strong flow turning, the secondary loss in the rotor passage accounts for nearly 50 percent of the total loss over the entire stage, based on a mean-line prediction reported by P&W. To reduce such a significant loss with an aim to further improve STME, performance has recently become one of the major research tasks for the Consortium Turbine Team at MSFC. As part of this team effort, the primary objective of the study is to identify and examine prospective approaches for secondary loss reduction. Relevant information reported earlier in the open literature, primarily for jet-engine applications, was also reviewed to a great extent. It is hoped that information gained from this study will promote further understanding toward these approaches and their potential applicability in STME turbines.

Chyu, Mingking K.↗

NASA NTRS1994

Engineering design knowledge recycling in near-real-time

It is hypothesized that the capture and reuse of machine readable design records is cost beneficial. This informal engineering notebook design knowledge can be used to model the artifact and the design process. Design rationale is, in part, preserved and available for examination. Redesign cycle time is significantly reduced (Baya et al, 1992). These factors contribute to making it less costly to capture and reuse knowledge than to recreate comparable knowledge (current practice). To test the hypothesis, we have focused on validation of the concept and tools in two 'real design' projects this past year: (1) a short (8 month) turnaround project for NASA life science bioreactor researchers was done by a team of three mechanical engineering graduate students at Stanford University (in a class, ME210abc 'Mechatronic Systems Design and Methodology' taught by one of the authors, Leifer); and (2) a long range (8 to 20 year) international consortium project for NASA's Space Science program (STEP: satellite test of the equivalence principle). Design knowledge capture was supported this year by assigning the use of a Team-Design PowerBook. Design records were cataloged in near-real time. These records were used to qualitatively model the artifact design as it evolved. Dedal, an 'intelligent librarian' developed at NASA-ARC, was used to navigate and retrieve captured knowledge for reuse.

Leifer, Larry↗

DOE OSTI2025

MPEX AI Digital Twins

All magnetically confined plasma fusion power plant concepts (Tokamak, Spherical Tokamak, Stellarator, Mirror, ...) must exhaust the heat and plasma from the core confinement region to the material walls. The primary channel for this exhaust is through a plasma divertor which directs plasma along open magnetic field lines to a material target. The Material Plasma Exposure eXperiment (MPEX) illustrated in Figure 1, is a high-power, steady-state linear plasma device designed to produce the plasma material interaction (PMI) conditions of the divertor of future magnetic confinement fusion power plants: energy flux 20MW/m 2 , ion fluence 1031/m 2 , pulse duration 106 sec. These goals of plasma exposure in MPEX are well beyond those achieved in magnetic fusion experimental devices. Successfully achieving these high power steady state conditions for long pulses requires operational control of the heating and particle sources and the plasma flux to the walls and target. The MPEX AI Hot Spot Controller, proposed in this project, will help achieve the operational milestones of MPEX. The MPEX device will begin commissioning at the end of FY26. A smaller proto-MPEX was operated for 14,666 plasma discharges and will resume operation in September of 2025 as proto-MPEX-lite, with reduced capability, to test a new window for the Helicon plasma source. The proto-MPEX data has undergone surrogate modeling with machine learning methods (R. Archibald, 2022 IEEE International Conference on Big Data). This proto-MPEX data will be used to begin development of the AI digital twins described in this white paper. The scientific mission of MPEX is to qualify materials of different composition for use in the high energy and plasma flux conditions of a fusion power plant. The materials exposed in MPEX will in some cases be exposed to high neutron fluxes at other ORNL facilities to measure the changes to their PMI properties. The targets exposed in MPEX will be transported under vacuum to a Surface Analysis Station (SAS). The SAS will be equipped with the following diagnostics: Focused Ion Beam (FIB) for trench milling, 100-400 angstrom resolution scanning electron microscope (SEM), surface mapping x-ray spectrometer, high resolution camera, and a future upgrade to a laser induced breakdown spectroscopy quadruple mass spectrometer (LIBS-QMS). The MPEX experiments will generate diverse pre- and post-exposure measurement data of detailed material properties down to the crystal grain level in 3D for post-exposure assessment of PMI damage (e.g. cracking, melting, erosion and redeposition of the material). Physics models for the PMI, and how the material composition and manufacturing impact its performance under high energy plasma exposure, need to be validated with MPEX data to guide the selection of new candidate materials. Our vision for the MPEX AI Digital Twins project is to supply experimental and physics model simulation data to train Artificial Intelligence (AI) models for data processing, analysis, operational control, PMI and materials simulation to maximize the scientific output of the MPEX device. Ultimately, an AI digital twin of MPEX material assessment metrics for tested and synthetic material types with simulated PMI will be trained by the AI Modeling Teams on the experimental and physics simulation data submitted to the American Science Cloud by this project. A purely empirical search for the best material is inefficient given the finite number of samples that can be tested on MPEX. In order to expand the material properties database for training the MPEX Material Assessment AI Digital Twin, and to gain physics understanding of the PMI processes, physics models of the material properties and PMI processes are required. The physics simulations provide detailed simulation data, like impact angles for plasma ions, sputtering yields, transport of the ionized sputtered target material in the plasma, and redeposition locations. This simulation data expands the measurement data for deeper physics understanding. The experimental data is essential to validate the PMI and material structure simulation models. The validated models can then be used to generate new simulation data of MPEX material assessments for synthetic material compositions that have not been exposed in MPEX. These predictive simulations, plus the whole experimental dataset, will be used to train the MPEX Material Assessment AI Digital Twin allowing a rapid generative AI search for new materials with reduced PMI damage by interpolating the domain of the training set. These new optimum materials can be simulated with the physics codes and/or tested in MPEX. The ability of AI neural networks to interpolate multi-dimensional parameter spaces and generate virtual data is exploited for a more efficient search for optimum materials. The advent of the Transformational AI Models Consortium (TAIMC) is an opportunity to engage with state of the art private and public AI developers to achieve the goals of the AI digital twins and AI accelerated physics models proposed in this project. Our partners at ORNL from the Advance Scientific Computing Research (ASCR) organization will collaborate in accelerating the integrated plasma material interaction simulation framework. This simulation framework will provide a platform for generating simulation data across a range of physical fidelities, including hybrid methods that produce multi-fidelity results. This data will be leveraged for AI model development, both for generation of surrogates and the automation of simulation campaigns. A part of the research below will include collaborative efforts with the TAIMC to (i) adapt data storage approaches to ensure AI-readiness, (ii) provide a protypical exemplar to inform and exercise constructed workflows, and (iii) generate and share data, using the TAIMC unified AI data standard, for foundational models that will be trained from multiple sources across the DOE complex. We will also collaborate with the TAIMC, as well as the planned AI modeling teams, to develop approaches for reducing the cost of data generation. These include tailored multi-fidelity approaches as well as fine-tuning strategies to augment general, large-scale foundational models.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

NASA NTRSDate not supplied

A Pipeline for Assessing the Quality of Rna-Seq Datasets in GeneLab

Transcriptome profiling by RNA sequencing (RNA-seq) is a powerful approach to identify gene expression changes in organisms exposed to unique environments such as spaceflight. One of the challenges of evaluating RNA-seq data both within and across different space-relevant studies is the ability to control for technical differences, including the use of different library preparation kits, sequencing platforms, RNA yield, and person-to-person variation. To help address this issue, the National Institute of Standards and Technology (NIST, nist.gov) initiated a consortium, at the request of industry and academia, to develop a set of controls for gene expression measurements. The result was a set of 92 unlabeled, polyadenylated transcripts that range from 250 – 2,000 nucleotides in length to mimic natural eukaryotic mRNAs. These External RNA Controls Consortium (ERCC) genes can be used in any RNA-seq experiment, by adding known concentrations of the ERCC genes to samples after RNA extraction, to offer a standard measurement for data comparison. At NASA GeneLab, we employ these controls as part of our standard operating procedures for every in-house RNA-seq study to assess the limit of detection, dynamic range, and power of differential expression analysis both within and across experiments. Here we will discuss the use, benefits, and limitations of ERCC genes and other types of controls, such as universal RNA references, to generate quality control information for RNA-seq studies conducted at GeneLab.

GeneLab↗

NASA NTRS2023

Statistical Approach on Utilizing Ground-Based Experiments to Model Break-Up Events

Two laboratory-based impact tests have been conducted to develop and extend the capability of NASA satellite breakup models. The first experiment, the Satellite Orbital Debris Characterization Impact Test (SOCIT), was conducted by the U.S. Department of Defense and NASA in 1992. It employed a fully functional U.S. Navy Transit spacecraft, fabricated from materials commonly used in the 1960s. SOCIT fragmentation data formed the basis of the current NASA Standard Satellite Breakup Model (SSBM). A second experiment, DebriSat, was conducted in 2014 by the DebriSat consortium: the NASA Orbital Debris Program Office, the United States Space Force Space Systems Command, formerly the Air Force Space and Missile Systems Center, the Air Force Arnold Engineering Development Complex, and the University of Florida. This impact test was performed on a high-fidelity mock-up satellite assembled from modern components. Data from both experiments are expected to contribute to the next-generation models for on-orbit breakup analyses, long-term environment predictions, and debris risk assessment. This paper uses the direct statistical sampling of the SOCIT and DebriSat data ensembles to model an on-orbit breakup event, rather than the analytic expressions estimated from the samples in the SSBM and its predecessor. This direct method involves drawing fragments (i.e., sampling with replacement) from each fragmentation data-subset containing mass, shape category, material density, characteristic length, mass, and cross-sectional area. As part of the sampling process, the properties of sampled fragment data (e.g., area-to-mass ratios) are numerically checked to ensure they do not contain unrealistic quantities. The process to simulate a breakup cloud composed of fragments from SOCIT and DebriSat datasets is discussed. The methodology for ensuring that conservation of overall mass of the sampled fragment cloud under this sampling approach is highlighted. Finally, the results are compared with simulated clouds generated from SSBM for specific historical breakup events.

Andrew Vavrin↗

NASA NTRSDate not supplied

Statistical Approach on Utilizing Ground-based Experiments to Model Break-up Events

Two laboratory-based impact tests have been conducted to develop and extend the capability of NASA satellite breakup models. The first experiment, the Satellite Orbital Debris Characterization Impact Test (SOCIT), was conducted by the U.S. Department of Defense and NASA in 1992. It employed a fully functional U.S. Navy Transit spacecraft, fabricated from materials commonly used in the 1960s. SOCIT fragmentation data formed the basis of the current NASA Standard Satellite Breakup Model (SSBM). A second experiment, DebriSat, was conducted in 2014 by the DebriSat consortium: the NASA Orbital Debris Program Office; the United States Space Force Space Systems Command, formerly the Air Force Space and Missile Systems Center, the Air Force Arnold Engineering Development Complex, and the University of Florida. This impact test was performed on a high-fidelity mock-up satellite assembled from modern components. Data from both experiments are expected to contribute to the next-generation models for on-orbit breakup analyses, long-term environment predictions, and debris risk assessment. This paper uses the direct statistical sampling of the SOCIT and DebriSat data ensembles to model an on-orbit breakup event, rather than the analytic expressions estimated from the samples as with as with the NASA SSBM and its predecessor. This direct method involves drawing fragments (i.e., sampling with replacement) from each fragmentation data-subset containing mass, shape category, material density, characteristic length, mass, and cross-sectional area. As part of the sampling process, the properties of sampled fragment data (e.g., area-to-mass ratios) are numerically checked to ensure they do not contain unrealistic quantities. The process to simulate a breakup cloud composed of fragments from SOCIT and DebriSat datasets is discussed. The methodology for ensuring that conservation of overall mass of the sampled fragment cloud under this sampling approach is highlighted. Finally, the results are compared with simulated clouds generated from SSBM for specific historical breakup events.

Andrew Vavrin↗

NASA NTRSDate not supplied

Study of Advanced Occupant Models to Quantify Injury Risk for eVTOL Vehicles

Urban transportation is currently evolving from traditional ground-based vehicles (cars, taxis, and buses) to include air-based electric vertical take-off and landing (eVTOL) vehicles which can be utilized for on-demand transportation, cargo transport, and emergency services. These new eVTOL vehicles are designed to be small, lightweight, and able to operate autonomously without user intervention. Safety is a big part of eventual eVTOL adoption, however gaps in the consideration of safety features exist. Anthropomorphic test devices (ATDs) are used in aerospace crashworthiness standards to quantify occupant injury risk and develop improved safety designs for emergency landing situations, but the ATDs currently used in aircraft certification requirements were developed many decades ago. Developments have occurred over the years involving ATD technology, which includes a host of newer and more biofidelic ATDs such as the Test Device for Human Occupant Restraint (THOR). Increased computing power has also allowed for detailed computational human body models (HBMs) to be created, such as the Global Human Body Model Consortium (GHBMC). This study aims to assess the capability of both HBMs and new ATD designs to identify injury mechanisms within eVTOL relevant emergency landing conditions. Finite element (FE) analysis was used to expand upon full-scale and seat level impact testing conducted by researchers at the National Aeronautics and Space Administration (NASA) to look at effects of occupant model configurations on prediction of injury. The GHBMC HBM and THOR ATD models were simulated in the seat level test conditions to characterize differences between these advanced assessment tools and traditional ATDs in the isolated seat loading environment. Results identified key differences in the responses from each of the models utilized and compared their impact response in head, neck, and spinal injury metrics. The THOR model identified potential risks for head injuries due to head impacts on the seat, however it predicted lower spinal loads than the other occupant surrogates. The GHBMC showed distinctly different biomechanical responses compared to the ATD. The GHBMC model is much more deformable than the ATDs and it exhibited higher distribution of forces and increased sensitivity to the duration of acceleration pulses. Both models incorporated into this study identified key mechanisms for injury that should be considered for passenger safety in the development of these novel aircraft. In addition, this study demonstrated the value of FE modeling for running a variety of complex human surrogates to identify potential injury mechanisms for consideration in regulation and development of new aircraft. Continued research in this field to improve validation these models will only lead to safer aircraft and more comprehensive safety measures.

Crashworthiness↗

NASA NTRSDate not supplied

Study of Advanced Occupant Models to Quantify Injury Risk for eVTOL Vehicles

Crashworthiness↗

NASA NTRS2022

Thinking Inside the Box: A Hands-on Student Activity for Building a Contamination Containment Glovebox to Encourage Problem Solving in a Collaborative Environment

Engineers from the National Aeronautics and Space Administration (NASA) and education experts from the Virginia Space Grant Consortium (VSGC) partnered together to create a hands-on student activity to teach students about problem solving, working in a collaborative environment, and about the unique career fields of contamination control and planetary protection. The activity focuses on contamination containment gloveboxes, which are sealed containers where operators outside the glovebox can safely manipulate hazardous or contamination-sensitive materials inside the glovebox through glove ports on the container. The activity utilizes common household materials and teams of students work together to design and build a glovebox using the materials provided. Once the glovebox has been constructed, students perform a task under a time constraint by using their glovebox to assemble a puzzle “contaminated” with corn starch. In a post-activity debrief, teams discuss lessons learned such as how the actual built glovebox differed from the sketched design, the challenge of managing a budget for materials, how the team dealt with surprises, and if their glovebox allowed enough room for the operator to perform the task. This activity has been part of VSGC’s Virginia Earth System Science Scholars (VESSS) summer academy program for high school students since 2016, and has been an engaging method to teach students teamwork, creativity, hands-on experimentation, communication, and reasoning skills while also teaching them about unique engineering fields such as contamination control and planetary protection.

Student activity↗

NASA NTRS2023

Numerical Investigation of Occupant Injury Risks During A Realistic Transport Aircraft Crash Conditions

Researchers at the National Aeronautics and Space Administration (NASA) Langley Research Center (LaRC) have conducted a full-scale crash test of a Fokker F28 MK1000 aircraft to investigate the performance of transport aircraft under realistic crash conditions. This crash test was computationally recreated using finite element (FE) human body models (HBMs) to further explore potential injury risks to occupants and analyze the utilization of HBMs in the aerospace crash environment. The Global Human Body Model Consortium (GHBMC) male 50th percentile occupant detailed model (v6.0) and the Toyota Human Model for Safety (THUMS) male 50th percentile occupant model (v6.1) were selected to be used in the crash simulations. The HBMs were simulated in conditions matching those of anthropomorphic test device (ATD) experiments included within the aircraft cabin during the crash test. Seven occupant locations within the cabin were simulated utilizing each of the models. The models were positioned in a neutral upright posture with hands resting on the legs and the feet contacting the floor. Head, brain, neck, and lumbar vertebra injury metrics were calculated for all trials. Both HBM models required minor modifications to stabilize these simulations. The GHBMC model required added erosion for six parts while the THUMS model only required one in order to complete the full simulation. The THUMS model, however, required a much smaller timestep for stability and therefore took significantly more computational time. In addition the GHBMC model includes integrated instrumentation while the THUMS model requires development and implementation of instrumentation. Both models predicted 100% injury risk for lumbar vertebra fracture in all test conditions. This prediction was in family with high lumbar load values measured by the ATDs during the crash test. The THUMS model consistently predicted lower injury risks than the GHBMC model in all three other metrics varying depending on the crash pulse. Overall, the THUMS model required less modifications to allow for this study. However, the GHBMC models significantly faster run time and integrated instrumentation make it a more intuitive model for this research.

Crashworthiness↗