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At least 73 records · Page 4

Electrodynamic Dust Shield (EDS) Preparation for MISSE-11 Launch

The dusty surfaces of the Moon, Mars, and various asteroids present a significant challenge to NASA’s manned and unmanned space exploration efforts. The fine, electrostatically charged dust is difficult to remove and has resulted in vision obscuration, false instrument readings, contamination, elevated temperatures, performance reduction, and equipment failure. To alleviate these problems, NASA KSC’s Electrostatics and Surface Physics Laboratory (ESPL) is developing active dust mitigation systems for solar system exploration and in situ resource utilization (ISRU). Part of KSC’s Swamp Works system, the lab emphasizes fast-paced, hands-on, cost-effective, and collaborative innovation. The Electrodynamic Dust Shield (EDS) is an ESPL technology being developed to prevent dust accumulation on space components. It consists of a dielectric substrate embedded with parallel electrodes which, when applied with high voltage out-of-phase waveforms, produce a traveling electric field wave that scatters dust particles from its surface via dielectrophoretic and electrostatic forces. The EDS is currently fully functional and has been tested for scalability and endurance in reduced gravity/pressure flight. Next, it will be part of the May 2019 Materials International Space Station Experiment-11 (MISSE-11) payload, which will test small shield samples for performance durability with exposure to the harsh space environment. The summer objective was to test EDS functionality before active and passive dust shield samples launch on MISSE-11, in order to screen for good flight/control samples as well as to compare pre-flight and post-flight clearing efficiencies. I imaged glass and Kapton shields of 2-phase and 3-phase electrode configurations with the Keyence VHX-5000 digital microscope to check for damage before and after all testing for a qualitative pre-flight baseline; helped with vacuum testing of high-voltage shield breakdown; assembled shields and wires using Electrobond 004 silver epoxy; and helped with vacuum and cryogenic dust clearance testing of assembled EDS systems. I learned CAD (computer-aided design) and 3D printing skills to create parts for a shaker table/motor assembly, which will allow for repeatable experiments by evening out EDS dust distribution in a consistent manner prior to dust scattering testing. I will also be improving the interfacing with Alpha Space’s prototype Data Communications Unit (DCU), a payload component to control power to the EDS and store data, by mapping the DCU structure upon power-up and writing shell scripts to improve various processes. Finally, I also CADed and 3D-printed plastic supports for three different geometries of the Electrostatic Precipitator (ESP), a project that aims to use high voltage electrodes to charge and filter out dust from the Martian atmosphere drawn for ISRU devices. This work on dust mitigation technologies will help to support future robotic and human space exploration missions, including NASA’s Journey to Mars; the EDS has especially significant applications to spacecraft solar panels, thermal radiators, viewports, and astronaut visors. This opportunity has also allowed me to become more familiar with various lab equipment and hardware testing, develop key modeling skills in SolidWorks, explore past and present components critical to America’s space program, work with inspiring peers and mentors, and ascertain my dream of working permanently for NASA.

space↗

March of the Interns

Summer 2019 brought 70 interns — from Puerto Rico, 44 continental US states, Sweden, and the Republic of Trinidad and Tobago — into the NASA Ames Aeromechanics Branch. Some were high school students learning engineering for the first time, while most were mechanical and aerospace engineering students, though two physics majors and a math major jumped into the mix to provide balance. This year’s interns completed work on 30 different projects with a collective of 30,000 dedicated hours of work. The projects this year were on urban air mobility (UAM), search and rescue vehicle design, all things Mars, Titan exploration concept designs, 3D modeling (i.e. computer aided design, CAD), computational fluid dynamics (CFD), and much more. Last year we addressed the question of what to do with an army of interns. This year, we are following its path to change the world.

Dromiack, Hannah↗

Virtual Fit Assessment: Validation using Historical Spacesuit Fit Data

Virtual fit tests using 3D body scans have provided a cost-effective means to predictively assess spacesuit fit for the current and future astronaut population. However, fit is a complex issue influenced by physical interferences, subjective preference, and many other factors. Fit can substantially differ between the type of hardware, environmental conditions, and tasks being performed. Namely, fit changes across different contexts, such as 3D printed mockup evaluations, pressurized one-g suited test events, neutral buoyancy and other training events, and flight extravehicular activities (EVA). These challenges make it difficult to validate virtual fit frameworks to physical suit sizing. This study proposes a new method of validation using the wealth of historically archived suit fit data. Physically Assessed Fit (PAF) data was assessed from astronauts and test volunteers who wore the legacy Extravehicular Mobility Unit (EMU). The data was collected during the past decades at NASA and considered to be most reliable and dependable. Each participant was 3D scanned for body shape and spacesuit-critical dimensions were measured per NASA guidelines. The participants’ size preference for hard upper torso (HUT) assembly was retrieved from their pressurized suit fit check records. Fit assessments were also updated after one-g EVA training, neutral buoyancy training, and EVA flights. Virtually Assessed Fit (VAF) was done by overlaying the CAD model of a HUT with the 3D body scans of the PAF participants. Each body scan was iteratively adjusted for the position inside the HUT to minimize the suit-to-body contact interference while satisfying a set of prescribed requirements. Then the residual contact area, depth, and volume were quantified as VAF metrics. This process was repeated for the different HUT sizes, including medium, large, and extra-large. Statistical modeling is currently in progress and will be presented at the conference. A statistical classifier will be developed to predict a fit probability for different HUT sizes as a function of the corresponding person’s VAF metrics. The HUT size with the highest fit probability will constitute the most likely size selection for the person, and the prediction will be compared against the corresponding PAF data. The participant data will be randomly pre-grouped into either a model development or validation subset. While the model development subset will be used to build the probability model, the validation subset will be used to assess the model accuracy. Also, the locations and magnitudes of suit-body-contacts will be estimated from VAF. This information can identify the critical suit geometry and body shape features that influence suit fit. The variations found in PAF size selections by subjects with similar VAF metrics will allow for investigations into subjective preferences, for example, tight versus loose fit. Overall, this study is expected to provide a structured validation of a virtual suit fit framework, which has not been possible in the past. The outcome can also provide useful insights and potential limitations for interpreting virtual fit tests for future spacesuit designs and population accommodation.

Han Kim↗

3D Scanning Laboratory

The 3D Scanning Lab uses a number of technologies to capture 3D surface data. Those technologies are structured light scanning, discrete point measurement photogrammetry and Light Detecting and Ranging(LIDAR). Structured light is a non-contact optical technique used to capture as built surface geometries quickly and accurately. LIDAR is a laser scanning technique used to capture 3D surfaces. And photogrammetry uses a certified DSLR camera to measure discrete registered and non-registered points in 3D space. MSFC’s 3D Scanning Team uses 3D scanning to provide hardware inspections, reverse engineered CAD models, manufacturing/process development and digital assemblies. The inspection process compares the captured data to CAD, providing a color plot detailing the deviations of the scan data to the CAD model. Dimensional measurements and GD&T can also be interrogated. Inspection can provide scan-to-scan data comparisons which is ideal for assessing tested hardware, e.g. comparing data captured before and after hardware testing. Reverse engineering is used to develop CAD models from scan data. This is useful for heritage hardware studies, developing building or structural models and inputs for simulation studies and design efforts. The lab uses the 3D surface scan data to drive manufacturing/machining processes, termed match machining. This technique has been used to modify nozzles, injectors, additive manufactured parts, composite barrel sections, etc. Parts of an assembly can be scanned and assembled in a virtual environment providing an accurate 3D representation of the assembled hardware in its as-scanned state. This can provide detailed information of internal components that would otherwise not be accessible.

Advanced Manufacturing↗

Full-wave modeling of RF waves in fusion plasmas with finite element method: Progress in past decades and its future role

This paper reviews the progress in computing radio frequency (RF) wave fields in fusion plasmas, specifically focusing on simulations utilizing the finite element method (FEM) over the past few decades. Computing RF wave fields in fusion plasmas presents unique challenges due to large simulation domains, complex antenna structures, non-local dielectric properties, and wide ranges of spatial scales. It highlights key developments and outlines future directions, primarily addressing waves in the ion cyclotron (IC) to lower hybrid (LH) frequency range. We begin with briefly revisiting earlier developments before the widespread availability of modern computer-aided engineering (CAE) software based on FEM. This historical perspective illuminates early progress and the physics difficulties that motivated ongoing work within the community. Modern wave simulations for RF antennas based on FEM are characterized by the use of detailed 3D antenna model geometry generated from engineering CAD software and localized wave dielectric model. Significant advancements have also been made in improving physics models to include phenomena such as RF sheath rectification and wave scattering. FEM-based RF simulations have also been applied to compute wave propagation in the core region, where the inclusion of non-local dielectric response is crucial. This is a challenging goal, and several promising approaches have been proposed in this area. Additionally, RF simulation development initiatives based on open-source libraries have gained popularity, demonstrating scalability and flexibility in extending physics models. This paper will discuss the advantages and disadvantages of using such a publicly available FEM library.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Cooling Strategies for an Electric Motor with Additively Manufactured Hollow Conductors and Distributed Power Electronics Integrated with Heat Pipes

This paper discusses design tradeoffs and thermal modeling explored in cooling strategies for an aircraft propulsion electric motor with additively manufactured coils and distributed power electronics integrated with heat pipes. Design tradeoffs include heat pipe Qmax performance related to inclination, condenser configuration, coolant type, coolant flow path complexity, and ease of access to modular power electronics. Three cooling strategies were selected and realized into CAD models. These models were further evaluated using 3D thermal FEA and optimization tools to explore cooling geometry details that include fin thickness, spacing and count with the objective to minimize fin mass under a set of constraints. Lastly, motorette test data is presented comparing air versus liquid cooling of heat pipes.

additive manufacturing↗

Development of Human-Spacesuit Interaction Models

Today’s astronaut corps represents a wide range of various anthropometric dimensions. Accommodating this wide range of anthropometry and protecting for size variations in future crews, makes spacesuit sizing and fit a challenging and necessary aspect of suit development. Spacesuit fit can play an important role in performance, but a suit fit assessment, especially in dynamic postures, is difficult without extensive human-in-the-loop testing. One approach to address this issue is to model and simulate the human-spacesuit interactions for a target population early in the design process. The Anthropometry and Biomechanics Facility (ABF) at the NASA Johnson Space Center has been working to incorporate parametric human models based on 3D full-body scan data with spacesuit CAD models that can be driven by the user or imported motion capture data. An articulated spacesuit model combined with a poseable high-fidelity human model allows comparisons to be made between spacesuit capabilities and normal human ranges of motion. Furthermore, predictions can be made as to how a specific individual or population may perform in the suit from the perspective of reach and mobility. In this paper, we will present case study examples of reach, mobility, and fit analyses that can be done with these models and the methodology developed thus far. These models have the potential to become powerful tools for evaluating future spacesuit design architectures from the perspective of optimizing fit and performance.

Jarvis, Sarah↗

4. Geometry Data Storage

3D-printing begins with the design of an object using computer aided design (CAD) software. The geometry of the object must be exported and saved in a data file format that can be used in the slicing process to generate machine instructions for printing. The standard method of saving the data is to tessellate the object as a triangulated mesh stored as a .stl file. Due to the flat triangular faces used to store the data, this mesh is a low-resolution representation of the high-fidelity object designed in CAD. The STL has its limitations with respect to geometrical accuracy, material information, and instances of invalid mesh data, but can still be used for the 3D-printing process. New file variants, such as OBJ, AMF, and 3MF, are being developed to fix some of these issues and increase the capabilities of geometry data storage for 3D-printing.

Roschli, Alex↗

CrossLink: Meshing a 3D part from a STEP file [Slides]

This example shows how to use CrossLink to create a mesh for a 3D geometry part read in from a STEP file. A STEP file (Standard for the Exchange of Product data) is a common file format used for 3D modelling that can be written out from a CAD program (e.g., Creo Parametric). Being able to read and mesh STEP file geometries is essential for meshing parts from engineering models. Creating the mesh typically involves: (1) Importing the geometry; (2) Creating geometry groups; (3) Assigning curves and surfaces to the geometry groups; (4) Building a topology; (5) Applying geometric and mesh constraints; and (6) Generating the final mesh. Current issues with this process in CrossLink include: (1) The GUI does not display trimmed surfaces; (2) The user must manually create and assign geometry groups; and (3) The user must be aware of duplicate curves and surfaces from the CAD model.

97 MATHEMATICS AND COMPUTING↗

Rapid Model Import Tool (RMIT) User Guide

The NASA Rapid Model Import Tool (RMIT) is designed to import 3D models built in commercially available Computer Aided Design (CAD) and Digital Content Creation (DCC) development software such as; Catia, Creo, 3DS Max, Maya, etc. Upon import, RMIT processes the models to reduce file size and exports the results in a format compatible with Augmented Reality (AR) and Virtual Reality (VR) development software applications. RMIT intends to make CAD models directly accessible to engineers from local AR/VR compatible laptops and desktops.

Joseluis Chavez↗

Manufacturing of Thermoset Polyimide Composites by Laser Sintering

Selective Laser Sintering (SLS) is an additive manufacturing technique that builds 3D models layer by layer using a laser to selectively melt cross sections in powdered polymeric materials, following sequential slices of the computer-aided design (CAD) model. SLS generally uses thermoplastic polymeric powders such as polyamides. The resultant 3D-printed objects are often weaker in their strength compared to traditionally processed materials, due to their higher porosity. This paper described the process development of using melt-processable imide oligomers terminated with reactive 4-phenylethynylphthalic anhydride (4-PEPA) to conduct laser sintering (LS). The first successful 3D-printing of high temperature RTM370 thermoset polyimide carbon fiber composites were further post-cured to promote additional crosslinking for achieving higher temperature (T g = 370°C) capability. Another novel imide oligomer, RTM385-SLS, formulated with a complex melt viscosity [ƞ*] of ~104-105 poise is also suitable for LS. RTM385-SLS resin powder was mixed with 20-25% of hexagonal boron nitride (h-BN) and subjected to LS to print out “Green” specimens which could be further post-cured to afford a thermally conductive but electrically insulating composites with high T g of 385 °C. The cured composite specimens were then subjected to mechanical testing, thermal conductivity and porosity measurements as well as SEM characterization.

additive Manufacturing↗

Challenges in Laser Sintering of Melt-Processable Thermoset Imide Resin

Polymer Laser Sintering (LS) is an additive manufacturing technique that builds 3D models layer by layer using a laser to selectively melt cross sections in powdered polymeric materials, following sequential slices of the CAD model. LS generally uses thermoplastic polymeric powders, such as polyamides (i.e. Nylon), and the resultant 3D objects are often weaker in their strength compared to traditionally processed materials, due to the lack of polymer inter-chain connection in the z-direction. The objective of this project is to investigate the possibility of printing a melt-processable RTM370 imide resin powder terminated with reactive phenylethynyl groups by LS, followed by a postcure in order to promote additional crosslinking to achieve higher temperature (250-300 C) capability. A preliminary study to build tensile specimens by LS and the corresponding DSC and rheology study of RTM370 during LS process is presented.

Additive Manufacturing↗

Challenges in Laser Sintering of Thermoset Imide Resin

Polymer Laser Sintering (LS) is an additive manufacturing technique that builds 3D models layer by layer using a laser to selectively melt cross sections in powdered polymeric materials, following sequential slices of the CAD model. LS generally uses thermoplastic polymeric powders, such as polyamides (i.e. Nylon), and the resultant 3D objects are often weaker in their strength compared to traditionally processed materials, due to the lack of polymer inter-chain connection in the z-direction. The objective of this project is to investigate the possibility of printing a melt-processable RTM370 imide resin powder terminated with reactive phenylethynyl groups by LS, followed by a postcure in order to promote additional crosslinking to achieve higher temperature (250-300 C) capability. A preliminary study to build tensile specimens by LS and the corresponding DSC and rheology study of RTM370 during LS process is presented.

Additive Manufacturing↗

Laser Sintering of Thermoset Polyimide Composites

Selective Laser Sintering (SLS) is an additive manufacturing technique that builds 3D models layer by layer using a laser to selectively melt cross sections in powdered polymeric materials, following sequential slices of the CAD model. SLS generally uses thermoplastic polymeric powders, such as polyamides (i.e. Nylon), and the resultant 3D objects are often weaker in their strength compared to traditionally processed materials, due to the lack of polymer inter-chain connection in the z-direction. Our previous effort showed the challenges of printing a melt-processable RTM370 imide resin powder terminated with reactive 4-phenylethynylphthalic anhydride by LS, due to its inherently low viscosity of these oligomers. This paper presented the first successful 3D printing of high temperature carbon fiber filled thermoset polyimide composites, followed by post cure cycles to promote additional crosslinking for achieving higher temperature (Tg = 370 °C) capability. The processes to build tensile specimens and a component by LS, and the characterization of RTM370 imide resin by DSC and rheology as well as evaluation of the LS printed polyimide composite specimens by SEM and mechanical tests will be discussed.

Polyimide Composites↗

Development of ARGOS Offloading Assessments and Methodology for Lunar EVA Simulations

The Active Response Gravity Offload System (ARGOS) at NASA Johnson Space Center (JSC) is an analog environment that can offload pressurized suited subjects at various gravity levels. The suit is suspended from a robotic overhead crane by a cable connected to the suit via a gimbal with an adjustable pivot point. There has been increased interest in providing lunar pressurized suited training at ARGOS in preparation for lunar missions. Determination of the appropriate gimbal pivot point location for a given subject is vital for a high-fidelity and functional lunar simulation. Interactions between the pivot point location and center of gravity (CG) can result in righting moments that may lead to artificially stable or unrealistically challenging configurations. Changing the pivot point location is time consuming and repeated adjustment can result in significant loss of valuable pressurized suited time. This paper aims to share the knowledge obtained from the offloading characterization efforts during pressurized suited testing at ARGOS and document the ongoing process to define an appropriate pivot point location through iterative quantitative and qualitative assessments. The human-spacesuit CG locations for the ARGOS lunar simulation were estimated using a 3D body scan and density model combined with spacesuit hardware CAD and specifications. Early pilot testing of the gimbal revealed that setting the pivot point coincident with the modeled CG location was not always possible due to the current gimbal design, and small shifts forward and aft had noticeable effects on subject stability. Fifteen subjects performed a series of CG-related tasks in the xEMU spacesuit to assess simulation acceptability. Through iterative testing, this task list evolved to streamline the process needed to efficiently identify a suitable pivot point for a given subject. The developed methodology will be critical to determine pivot point selection for astronaut training in the xEMU ARGOS environment.

Sarah L. Jarvis↗

Development of ARGOS (Active Response Gravity Offload System) Offloading Assessments and Methodology for Lunar EVA Simulations

The Active Response Gravity Offload System (ARGOS) at NASA Johnson Space Center (JSC) is an analog environment that can offload pressurized suited subjects for various reduced gravity simulations. The suit is suspended from a robotic overhead crane by a cable connected to the suit via a gimbal with an adjustable pivot point (i.e. offload attachment). There has been increased interest in providing planetary pressurized suited training at ARGOS in preparation for lunar missions. Determination of the appropriate gimbal pivot point location for a given subject is vital for a high-fidelity functional lunar simulation. Interactions between the pivot point location and human-spacesuit center of gravity (CG) can result in righting moments that may lead to artificially stable or unrealistically challenging configurations. Changing the pivot point location is time consuming and repeated adjustment can result in loss of valuable pressurized suited time. This paper aims to share knowledge obtained from the offloading characterization efforts during pressurized suited testing at ARGOS and document the ongoing process to define an appropriate pivot point location through iterative quantitative and qualitative assessments. Human-spacesuit CG locations for the ARGOS lunar simulation were estimated using a 3D body scan and density model combined with spacesuit hardware CAD and specifications. Early pilot testing of the gimbal revealed that setting the pivot point coincident with the modeled CG location was not always possible due to the current gimbal design, and small pivot point shifts had noticeable effects on subject stability. Fourteen subjects performed a series of CG-related tasks in the Exploration Extravehicular Mobility Unit (xEMU) to assess simulation characteristics. Through iterative testing, this task list evolved to streamline the process needed to efficiently identify a suitable pivot point for a given subject. The developed methodology will be critical for pivot point selection during astronaut training in the ARGOS environment.

Sarah L. Jarvis↗

Design and scale-up of 3D printed bat houses with biomass-derived polymer composites

Biomass (e.g., pine sawdust, especially high–ash content pine sawdust) is commonly disposed of as waste. Combining biomass with polymers to make composite feedstocks for 3D printing has been explored as a method to reduce or repurpose the biomass waste. Although not all biocomposite properties are known, the wood-based polylactic acid (PLA) composite has promising qualities for applications in ecological settings. In this work, pine wood–PLA composite feedstock was used to 3D print supplemental roost structures for endangered tree-roosting bats, which often face a paucity of suitable naturally occurring roosts. This material combination was selected because it is estimated to degrade faster than the synthetic material systems that are used widely in supplemental bat roosting structures to aid in the conservation of tree roosting bats. The layered, rough surface created by the 3D printing process serves as a surface that bats can grip while roosting. Computer-aided design (CAD) models were generated based on natural roost structures, and a full-size bat house was successfully additively manufactured using a pellet-fed large-scale 3D printing system. The 3D printed hexagon exhibited a tensile strength of 22–23 MPa and a Young’s modulus of 3202–3218 MPa in the x-direction. It has been demonstrated that the 3D printed bat house can be installed on a tree in a stable fashion. This successful demonstration of a bat roost manufactured using a bioderived composite should promote its use in other fish and wildlife structures and broader industrial applications such as construction and automobiles.

3D printing↗

A Dose of Reality: Radiation Analysis for Realistic Human Spacecraft

INTRODUCTION As with most computational analyses, a tradeoff exists between problem complexity, resource availability and response accuracy when modeling radiation transport from the source to a detector. The largest amount of analyst time for setting up an analysis is often spent ensuring that any simplifications made have minimal impact on the results. The vehicle shield geometry of interest is typically simplified from the original CAD design in order to reduce computation time, but this simplification requires the analyst to "re-draw" the geometry with a limited set of volumes in order to accommodate a specific radiation transport software package. The resulting low-fidelity geometry model cannot be shared with or compared to other radiation transport software packages, and the process can be error prone with increased model complexity. The work presented here demonstrates the use of the DAGMC (Direct Accelerated Geometry for Monte Carlo) Toolkit from the University of Wisconsin, to model the impacts of several space radiation sources on a CAD drawing of the US Lab module. METHODS The DAGMC toolkit workflow begins with the export of an existing CAD geometry from the native CAD to the ACIS format. The ACIS format file is then cleaned using SpaceClaim to remove small holes and component overlaps. Metadata is then assigned to the cleaned geometry file using CUBIT/Trelis from csimsoft (Registered Trademark). The DAGMC plugin script removes duplicate shared surfaces, facets the geometry to a specified tolerance, and ensures that the faceted geometry is water tight. This step also writes the material and scoring information to a standard input file format that the analyst can alter as desired prior to running the radiation transport program. The scoring results can be transformed, via python script, into a 3D format that is viewable in a standard graphics program. RESULTS The CAD model of the US Lab module of the International Space Station, inclusive of all the racks and components, was simplified to remove holes and volume overlaps. Problematic features within the drawing were also removed or repaired to prevent runtime issues. The cleaned drawing was then run through the DAGMC workflow to prepare for analysis. Pilot tests modeling transport of 1GeV proton and 800MeV/A oxygen sources show that reasonable results are converged upon in an acceptable amount of overall computation time from drawing preparation to data analysis. The FLUKA radiation transport code will next be used to model both a GCR and a trapped radiation source. These results will then be compared with measurements that have been made by the radiation instrumentation deployed inside the US Lab module. DISCUSSION Early analyses have indicated that the DAGMC workflow is a promising toolkit for running vehicle geometries of interest to NASA through multiple radiation transport codes. In addition, recent work has shown that a realistic human phantom, provided via a subcontract with the University of Florida, can be placed inside any vehicle geometry for a combinatorial analysis. This added functionality gives the user the ability to score various parameters at the organ level, and the results can then be used as input for cancer risk models.

Barzilla, J. E.↗