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At least 1,297 records · Page 72
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Ice Growth Model and Lunar Tanker for Polar Water Extraction

In-Situ Resource Utilization (ISRU) is a major component of sustainable and cost-effective missions to the Moon and beyond. Ever since it has been identified in the Permanently Shadowed Regions (PSRs) of the Moon, water has become a resource of interest for it’s wide range of uses such as life support and hydrogen and oxygen rocket propellant. It is ice-bound in the regolith, so separation typically involves heating to sublimation temperatures and capturing at very low pressure. One option is to then store it in ice form and transport it out of the PSR and into a sunlit ridge. From here, processes such as electrolysis can be performed. An understanding of frost growth dynamics under rarefied conditions is necessary for successful water production, though. An analytical model was developed using a Diffusion-Limited Aggregation (DLA) approach to evaluate bulk thermal conductivity changes of frost under varying conditions. This model will be evaluated using a one-dimensional frost growth experiment on a horizontal, flat plate under vacuum and cryogenic conditions. The tests will measure frost growth rate and bulk density, and the thermal conductivity of the ice layer as a function of thickness for different plate temperatures. The test data will then be used to validate and improve the analytical model.

Lunar water↗
NASA NTRS2022

New Rover Conops with High-Performance Onboard Computing: Give Up Raw Data to Reduce Ops Cost and Do More Science

A major portion of time during the tactical operation of Mars rovers is spent for selecting, prioritizing, and coordinating sciences and engineering activities such that they fit within resource constraints, including the downlink data volume, energy, and time. In particular, the downlink data volume constraint is getting particularly tighter in recent missions because modern instruments produce increasingly high data volume while the communication bandwidth is essentially bounded by the law of physics. Tactical operation would be substantially simplified, hence the operation cost could be reduced, if the data volume constraint is relaxed or even removed. In this abstract, we propose a new operation paradigm for achieving this goal. The key observation is that, both in science and engineering applications, the bit size of raw data is typically much greater than the volume of processed information that is needed for scientific or engineering analysis. For example, a full-resolution image from Mastcam-Z, the main science camera on Perseverance, is about 700 kB in volume and we downlinked 29,685 images up to Sol 243, totaling ~20 GB of data. But of course, scientists do not use every pixel of these images; what they really look for in the images are geological features, typically represented by specific geometric configurations or textures. An end product after processing hundreds of Mascam-Z images could be a single geological map summarizing the spatial distribution of the features. For another example, a 100-meter drive of Perseverance produces 7-12 MB of drive telemetry, which records every detail of the rover's motion at 8 Hz, including position, attitude, steering angles, encoder readings, motor currents and many other information. But what the ground engineers eventually pay attention to is the signs of anomaly, such as excessive motor currents or high slip; if a drive is nominal, the vast majority of this data is unused. What if, then, we process the raw data onboard and only downlink the processed data that is relevant to scientific or engineering analyses, such as a list of detected science features (with cropped images) or a list of potential signs of anomaly while driving? A major roadblock for such onboard, high-level information processing has been the onboard computational resource. RAD750, the main onboard computer of Perseverance, is obviously not sufficient for performing complex image or signal processing such as object detection, semantic segmentation, or anomaly detection. Interestingly, RAD750 is not the best processor that Perseverance has; Qualcomm's Snapdragon 801, a modern mobile processor, is on her Heli Base Station, a device for communicating with Mars Helicopter Ingenuity; also, Intel's Atom E3845 processors are on engineering cameras. In the reminder of this paper, we will introduce two particular uses cases of these high-performance co-processors (meaning auxiliary CPU, GPU, or other types of processors that are separate from the main processor that runs the main flight software) for lowering operation cost and accommodating more science activities for a given communication constraint.

Didier, A.↗
DOE OSTI2021

Development and Advanced Testing of DPC Cement Fillers

The fillers research and development (R&D) program, mostly experimental, is part of a broader R&D program that includes new process modeling and performance assessment of criticality effects and the overall importance of criticality to repository performance (consequence screening). A literature research and consultation effort with experts by Hardin and Brady (2018) identified several potentially effective and workable filler materials including cements (primarily phosphate based), moltenmetal alloys, and low-temperature glasses. Filler attributes were defined, and the preliminary lists were compared qualitatively. Further comparative analysis will be done (e.g., cost estimates) after experimental screening has narrowed the list of alternatives. The research presented here is focused Sandia’s efforts for the development of phosphate-based cement fillers. Molten metal filler research is an ongoing activity at Oak Ridge National Laboratories and is not discussed herein. After the completion of the FY20 research effort the following cement filler compositions were selected for further experimental development work and advanced testing in FY21: 1. Aluminum phosphate cements (APCs); more specifically aluminum oxide / aluminum phosphate (Al 2 O 3 / AlPO 4 ) cements in which Al 2 O 3 serves as the filler material bound by an AlPO 4 binder formed by the reaction of Al 2 O 3 with various phosphate sources; 2. Wollastonite phosphate cements (WPCs), specifically wollastonite and aluminum or calcium aluminum phosphates in which CaSiO 3 serves as the filler material bound by a calcium phosphate that serves as the binder; and 3. Calcium aluminate phosphate cements (CAPCs) specifically grossite (CaAl 4 O 7 ) and hibonite (CaAl 11 O 18 ) fillers bound by an aluminum phosphate that serves as the binder. This effort focused on the optimization and subsequent processing of these three cements to achieve dense and well-consolidated monolithic samples. Upon completion of the FY21 effort the aluminum phosphate cements (APCs) and the calcium aluminate phosphate cements (CAPCs) show the most promise for advanced testing and scale up. We will begin the work in FY22 focused on testing the performance of these two cements in small scale DPCs as well as advanced materials testing to evaluate cement performance under expected radiation doses and representative post-closure geochemical environments.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2026

Active Learning‐Driven Inkless Additive Nanomanufacturing for Printed Electronics

Inkless additive nanomanufacturing for printed electronics promises broad material and substrate versatility, yet the high-dimensional print parameter space makes tuning print parameters time-intensive. We present a Bayesian optimization study that constructs a digital twin from printed-silver data to benchmark surrogate models, acquisition functions, and batch sizes head-to-head to achieve user-specified target resistance. Tested surrogate models included Gaussian process, random forest, and Bayesian neural network surrogates with expected improvement and confidence bound acquisition functions. In total, we evaluate 48 unique model configurations alongside a random sampling baseline for comparison. For printed silver, the Bayesian neural network with a batch size of one achieved the lowest average cumulative regret, approximately four times more efficient on average than random sampling. To balance performance and substrate space, a random forest model with expected improvement and a batch size of four was chosen as the model for validation testing. Applying this chosen configuration to copper with an additional print parameter, the model achieved a resistance within 0.15 Ω of a 1 Ω target in fewer than 30 printed lines across five validation sets. Altogether, the workflow yields a tuned and validated model that efficiently guides experiments toward the target while simultaneously learning the parameter space.

Bevel, Colton [Auburn University, AL (United State↗
DOE OSTI2024

Parallel computing for power system climate resiliency: Solving a large-scale stochastic capacity expansion problem with mpi-sppy

Here we propose a nodal stochastic generation and transmission expansion planning model that incorporates the output from high-resolution global climate models through load and generation availability scenarios. We implement our model in Pyomo and perform computational studies on a realistically-sized test case of the California electric grid in a high performance computing environment. We propose model reformulations and algorithm tuning to efficiently solve this large problem using a variant of the Progressive Hedging Algorithm. We utilize the parallelization capabilities and overall versatility of mpi-sppy, exploiting its hub-and-spoke architecture to concurrently obtain inner and outer bounds on an optimal expansion plan. Initial results show that instances with 360 representative days on a system with over 8,000 buses can be solved to within 5% of optimality in under 4 h of wall clock time, a first step towards solving a large-scale power system expansion planning problem across a wide range of climate-informed operational scenarios.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Mechanistic Pathways for N 2 O Elimination from trans -R 3 Sn-O-N=N-O-SnR 3 and for Reversible Binding of CO 2 to R 3 Sn-O-SnR 3 (R = Ph, Cy)

The rate and mechanism of the elimination of N 2 O from trans-R 3 Sn-O-N=N-O-SnR 3 (R = Ph ( 1 Ph ) and R = Cy ( 1 Cy )) to form R 3 Sn-O-SnR 3 (R = Ph ( 2 Ph ) and R = Cy ( 2 Cy )) have been studied using both NMR and IR techniques to monitor the reactions in the temperature range of 39–79 °C in C 6 D 6 . Activation parameters for this reaction are ΔH ‡ = 15.8 ± 2.0 kcal·mol –1 and ΔS ‡ = –28.5 ± 5 cal·mol –1 ·K –1 for 1 Ph and ΔH ‡ = 22.7 ± 2.5 kcal·mol –1 and ΔS ‡ = –12.4 ± 6 cal·mol –1 ·K –1 for 1 Cy . Addition of O 2 , CO 2 , N 2 O, or PPh 3 to sealed tube NMR experiments did not alter in a detectable way the rate or product distribution of the reactions. Computational DFT studies of elimination of hyponitrite from trans-Me 3 Sn-O-N=N-O-SnMe 3 ( 1 Me ) yield a mechanism involving initial migration of the R 3 Sn group from O to N passing through a marginally stable intermediate product and subsequent N 2 O elimination. Reactions of 1 Ph with protic acids HX are rapid and lead to formation of R 3 SnX and trans-H 2 N 2 O 2 . Reaction of 1 Ph with the metal radical •Cr(CO) 3 C 5 Me 5 at low concentrations results in rapid evolution of N 2 O. At higher •Cr(CO) 3 C 5 Me 5 concentrations, evolution of CO 2 rather than N 2 O is observed. Addition of 1 atm or less CO 2 to benzene or toluene solutions of 2 Ph and 2 Cy resulted in very rapid reaction to form the corresponding carbonates R 3 Sn-O-C(=O)-O-SnR 3 (R = Ph ( 3 Ph ) and R = Cy ( 3 Cy )) at room temperature. Evacuation results in fast loss of bound CO 2 and regeneration of 2 Ph and 2 Cy . Variable temperature data for formation of 3 Cy yield ΔH o = –8.7 ± 0.6 kcal·mol –1 , ΔS o = –17.1 ± 2.0 cal·mol –1 ·K –1 , and ΔG o 298K = –3.6 ± 1.2 kcal·mol –1 . Furthermore, DFT studies were performed and provide additional insight into the energetics and mechanisms for the reactions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Statistical data analysis of x-ray spectroscopy data enabled by neural network accelerated Bayesian inference

Bayesian inference applied to x-ray spectroscopy data analysis enables uncertainty quantification necessary to rigorously test theoretical models. However, when comparing to data, detailed atomic physics and radiation transfer calculations of x-ray emission from non-uniform plasma conditions are typically too slow to be performed in line with statistical sampling methods, such as Markov Chain Monte Carlo sampling. Furthermore, differences in transition energies and x-ray opacities often make direct comparisons between simulated and measured spectra unreliable. Here, we present a spectral decomposition method that allows for corrections to line positions and bound–bound opacities to best fit experimental data, with the goal of providing quantitative feedback to improve the underlying theoretical models and guide future experiments. In this work, we use a neural network (NN) surrogate model to replace spectral calculations of isobaric hot-spots created in Kr-doped implosions at the National Ignition Facility. The NN was trained on calculations of x-ray spectra using an isobaric hot-spot model post-processed with Cretin, a multi-species atomic kinetics and radiation code. The speedup provided by the NN model to generate x-ray emission spectra enables statistical analysis of parameterized models with sufficient detail to accurately represent the physical system and extract the plasma parameters of interest.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

Quantum routing with teleportation

We study the problem of implementing arbitrary permutations of qubits under interaction constraints in quantum systems that allow for arbitrarily fast local operations and classical communication (LOCC). In particular, we show examples of speedups over swap-based and more general unitary routing methods by distributing entanglement and using LOCC to perform quantum teleportation. We further describe an example of an interaction graph for which teleportation gives a logarithmic speedup in the worst-case routing time over swap-based routing. We also study limits on the speedup afforded by quantum teleportation—showing an O ( N log N ) upper bound on the separation in routing time for any interaction graph—and give tighter bounds for some common classes of graphs. Published by the American Physical Society 2024

Devulapalli, Dhruv (ORCID:000000022612308X)↗
DOE OSTI2023

Modeling Nanoscale Ohmics in Carbon Supports of Fuel Cell Cathodes

Here, reducing platinum (Pt) loading in polymer electrolyte fuel cells (PEFCs) while meeting performace requirements is critical to their widespread deployment. However, significant polarization losses manifest at higher current densities in cathodes with lower Pt content. The morphology of the carbon supports in PEFC cathodes affects the location of Pt deposition into the micropits or onto the surface of the carbon support, translating into different kinetic and transport resistances. In this work, we derive an agglomerate scale model that differentiates the sink terms for Pt on the surface and in the pits of carbon supports. We develop an approach to assess the impact of nanoscale ohmic resistance to Pt in the micropits arising from weakly ionic solution in the carbon support on PEFC performance. Effectiveness factors relating the actual reaction rate to the maximum reaction rate (had all the Pt been exposed) are derived and embedded into a one-dimensional catalyst layer model. Parameters in the catalyst layer model are tuned based on experimental local oxygen transport resistances. Subsequently, we estimate bounds for the micropore resistances based on geometric and physical arguments. Lastly, polarization curves are simulated to assess the effect of the micropore resistance in fully-humidified and oxygen-rich environments.

25 ENERGY STORAGE↗
DOE OSTI2023

Real-Time Krylov Theory for Quantum Computing Algorithms

Quantum computers provide new avenues to access ground and excited state properties of systems otherwise difficult to simulate on classical hardware. New approaches using subspaces generated by real-time evolution have shown efficiency in extracting eigenstate information, but the full capabilities of such approaches are still not understood. In recent work, we developed the variational quantum phase estimation (VQPE) method, a compact and efficient real-time algorithm to extract eigenvalues on quantum hardware. Here we build on that work by theoretically and numerically exploring a generalized Krylov scheme where the Krylov subspace is constructed through a parametrized real-time evolution, which applies to the VQPE algorithm as well as others. We establish an error bound that justifies the fast convergence of our spectral approximation. We also derive how the overlap with high energy eigenstates becomes suppressed from real-time subspace diagonalization and we visualize the process that shows the signature phase cancellations at specific eigenenergies. We investigate various algorithm implementations and consider performance when stochasticity is added to the target Hamiltonian in the form of spectral statistics. To demonstrate the practicality of such real-time evolution, we discuss its application to fundamental problems in quantum computation such as electronic structure predictions for strongly correlated systems.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1975

An analysis of aircraft accidents involving fires

All U. S. Air Carrier accidents between 1963 and 1974 were studied to assess the extent of total personnel and aircraft damage which occurred in accidents and in accidents involving fire. Published accident reports and NTSB investigators' factual backup files were the primary sources of data. Although it was frequently not possible to assess the relative extent of fire-caused damage versus impact damage using the available data, the study established upper and lower bounds for deaths and damage due specifically to fire. In 12 years there were 122 accidents which involved airframe fires. Eighty-seven percent of the fires occurred after impact, and fuel leakage from ruptured tanks or severed lines was the most frequently cited cause. A cost analysis was performed for 300 serious accidents, including 92 serious accidents which involved fire. Personal injury costs were outside the scope of the cost analysis, but data on personnel injury judgements as well as settlements received from the CAB are included for reference.

Lucha, G. V.↗
NASA NTRS1988

Crater size estimates for large-body terrestrial impact

Calculating the effects of impacts leading to global catastrophes requires knowledge of the impact process at very large size scales. This information cannot be obtained directly but must be inferred from subscale physical simulations, numerical simulations, and scaling laws. Schmidt and Holsapple presented scaling laws based upon laboratory-scale impact experiments performed on a centrifuge (Schmidt, 1980 and Schmidt and Holsapple, 1980). These experiments were used to develop scaling laws which were among the first to include gravity dependence associated with increasing event size. At that time using the results of experiments in dry sand and in water to provide bounds on crater size, they recognized that more precise bounds on large-body impact crater formation could be obtained with additional centrifuge experiments conducted in other geological media. In that previous work, simple power-law formulae were developed to relate final crater diameter to impactor size and velocity. In addition, Schmidt (1980) and Holsapple and Schmidt (1982) recognized that the energy scaling exponent is not a universal constant but depends upon the target media. Recently, Holsapple and Schmidt (1987) includes results for non-porous materials and provides a basis for estimating crater formation kinematics and final crater size. A revised set of scaling relationships for all crater parameters of interest are presented. These include results for various target media and include the kinematics of formation. Particular attention is given to possible limits brought about by very large impactors.

Schmidt, Robert M.↗
NASA NTRS1991

Transparent process migration: Design alternatives and the Sprite implementation

The Sprite operating system allows executing processes to be moved between hosts at any time. We use this process migration mechanism to offload work onto idle machines, and also to evict migrated processes when idle workstations are reclaimed by their owners. Sprite's migration mechanism provides a high degree of transparency both for migrated processes and for users. Idle machines are identified, and eviction is invoked, automatically by daemon processes. On Sprite it takes up to a few hundred milliseconds on SPARCstation 1 workstations to perform a remote exec, while evictions typically occur in a few seconds. The pmake program uses remote invocation to invoke tasks concurrently. Compilations commonly obtain speedup factors in the range of three to six; they are limited primarily by contention for centralized resources such as file servers. CPU-bound tasks such as simulations can make more effective use of idle hosts, obtaining as much as eight-fold speedup over a period of hours. Process migration has been in regular service for over two years.

Douglis, Fred↗
NASA NTRS2014

Passive Thermal Control for the Low Density Supersonic Decelerator (LDSD) Test Vehicle Spin Motors Sub-System

Future missions to Mars will require improved entry, descent, and landing (EDL) technology over the Viking-heritage systems which recently landed the largest payload to date, the 900 kg Mars Science Laboratory. As a result, NASA's Low Density Supersonic Decelerator (LDSD) project is working to advance the state of the art in Mars EDL systems by developing and testing three key technologies which will enable heavier payloads and higher altitude landing sites on the red planet. These technologies consist of a large 33.5 m diameter Supersonic Disk Sail (SSDS) parachute and two different Supersonic Inflatable Aerodynamic Decelerator (SIAD) devices - a robotic class that inflates to a 6 m diameter torus (SIAD-R), and an exploration class that inflates to an 8 m diameter isotensoid (SIADE). All three technologies will be demonstrated on test vehicles at high earth altitudes in order to simulate the Mars EDL environment. Each vehicle will be carried to altitude by a large helium balloon, released, spun up using spin motors to stabilize the vehicle's trajectory, and accelerated to supersonic speeds using a large solid rocket motor. The vehicle will then be spun down using another set of spin motors, and will deploy either the SIAD-R or SIAD-E, followed by the SSDS parachute until the vehicle lands in the ocean. Component level testing and bounding analysis are used to ensure the survival of system components in extreme thermal environments and predict temperatures throughout the flight. This paper presents a general description of the thermal testing, model correlation, and analysis of the spin motor passive thermal control sub-system to maintain spin motor performance, prescribed vehicle trajectory, and structural integrity of the test vehicle. The spin motor subsystem is predicted to meet its requirements with margin.

thermal analysis↗
DOE OSTI2025

Metasurfaces with Multipolar Resonances and Enhanced Light–Matter Interaction

Metasurfaces, composed of engineered nanoantennas, enable unprecedented control over electromagnetic waves by leveraging multipolar resonances to tailor light–matter interactions. This review explores key physical mechanisms that govern their optical properties, including the role of multipolar resonances in shaping metasurface responses, the emergence of bound states in the continuum (BICs) that support high-quality factor modes, and the Purcell effect, which enhances spontaneous emission rates at the nanoscale. These effects collectively underpin the design of advanced photonic devices with tailored spectral, angular, and polarization-dependent properties. This review discusses recent advances in metasurfaces and applications based on them, highlighting research that employs full-wave numerical simulations, analytical and semi-analytic techniques, multipolar decomposition, nanofabrication, and experimental characterization to explore the interplay of multipolar resonances, bound and quasi-bound states, and enhanced light–matter interactions. A particular focus is given to metasurface-enhanced photodetectors, where structured nanoantennas improve light absorption, spectral selectivity, and quantum efficiency. By integrating metasurfaces with conventional photodetector architectures, it is possible to enhance responsivity, engineer photocarrier generation rates, and even enable functionalities such as polarization-sensitive detection. The interplay between multipolar resonances, BICs, and emission control mechanisms provides a unified framework for designing next-generation optoelectronic devices. This review consolidates recent progress in these areas, emphasizing the potential of metasurface-based approaches for high-performance sensing, imaging, and energy-harvesting applications.

Kerker effect↗
NASA NTRS2013

Tuning and Robustness Analysis for the Orion Absolute Navigation System

The Orion Multi-Purpose Crew Vehicle (MPCV) is currently under development as NASA's next-generation spacecraft for exploration missions beyond Low Earth Orbit. The MPCV is set to perform an orbital test flight, termed Exploration Flight Test 1 (EFT-1), some time in late 2014. The navigation system for the Orion spacecraft is being designed in a Multi-Organizational Design Environment (MODE) team including contractor and NASA personnel. The system uses an Extended Kalman Filter to process measurements and determine the state. The design of the navigation system has undergone several iterations and modifications since its inception, and continues as a work-in-progress. This paper seeks to show the efforts made to-date in tuning the filter for the EFT-1 mission and instilling appropriate robustness into the system to meet the requirements of manned space ight. Filter performance is affected by many factors: data rates, sensor measurement errors, tuning, and others. This paper focuses mainly on the error characterization and tuning portion. Traditional efforts at tuning a navigation filter have centered around the observation/measurement noise and Gaussian process noise of the Extended Kalman Filter. While the Orion MODE team must certainly address those factors, the team is also looking at residual edit thresholds and measurement underweighting as tuning tools. Tuning analysis is presented with open loop Monte-Carlo simulation results showing statistical errors bounded by the 3-sigma filter uncertainty covariance. The Orion filter design uses 24 Exponentially Correlated Random Variable (ECRV) parameters to estimate the accel/gyro misalignment and nonorthogonality. By design, the time constant and noise terms of these ECRV parameters were set to manufacturer specifications and not used as tuning parameters. They are included in the filter as a more analytically correct method of modeling uncertainties than ad-hoc tuning of the process noise. Tuning is explored for the powered-flight ascent phase, where measurements are scarce and unmodelled vehicle accelerations dominate. On orbit, there are important trade-off cases between process and measurement noise. On entry, there are considerations about trading performance accuracy for robustness. Process Noise is divided into powered flight and coasting ight and can be adjusted for each phase and mode of the Orion EFT-1 mission. Measurement noise is used for the integrated velocity measurements during pad alignment. It is also used for Global Positioning System (GPS) pseudorange and delta- range measurements during the rest of the flight. The robustness effort has been focused on maintaining filter convergence and performance in the presence of unmodeled error sources. These include unmodeled forces on the vehicle and uncorrected errors on the sensor measurements. Orion uses a single-frequency, non-keyed GPS receiver, so the effects due to signal distortion in Earth's ionosphere and troposphere are present in the raw measurements. Results are presented showing the efforts to compensate for these errors as well as characterize the residual effect for measurement noise tuning. Another robustness tool in use is tuning the residual edit thresholds. The trade-off between noise tuning and edit thresholds is explored in the context of robustness to errors in dynamics models and sensor measurements. Measurement underweighting is also presented as a method of additional robustness when processing highly accurate measurements in the presence of large filter uncertainties.

Holt, Greg N.↗
NASA NTRSDate not supplied

Bounds on Robustness Limitations for Unstable Aircraft Using the Bode Sensitivity Integral

This paper investigates limitations in achievable robustness of statically unstable aircraft using the Bode sensitivity integral. A previous analysis of the X-29 aircraft is studied, and details about the available bandwidth and robustness limitations are re-examined using high-fidelity linear models of the aircraft and control system. Based on these results, a modified analysis was performed on the X-59 Low-Boom Flight Demonstrator to illustrate the same type of fundamental limitations and difficulties in meeting traditional specifications on gain and phase margins.

Bode sensitivity integral↗
DOE OSTI2020

Non-destructive simulation of node defects in additively manufactured lattice structures

Additive Manufacturing (AM), commonly referred to as 3D printing, offers the ability to not only fabricate geometrically complex lattice structures but parts in which lattice topologies in-fill volumes bounded by complex surface geometries. However, current AM processes produce defects on the strut and node elements which make up the lattice structure. This creates an inherent difference between the as-designed and as-fabricated geometries, which negatively affects predictions (via numerical simulation) of the lattice’s mechanical performance. Although experimental and numerical analysis of an AM lattice’s bulk structure, unit cell and struts have been performed, there exists almost no research data on the mechanical response of the individual as-manufactured lattice node elements. Here we propose a methodology that, for the first time, allows non-destructive quantification of the mechanical response of node elements within an as-manufactured lattice structure. A custom-developed tool is used to extract and classify each individual node geometry from micro-computed tomography scans of an AM fabricated lattice. Voxel-based finite element meshes are generated for numerical simulation and the mechanical response distribution is compared to that of the idealised computer-aided design model. The method demonstrates compatibility with Uncertainty Quantification methods that provide opportunities for efficient prediction of a population of nodal responses from sampled data. Overall, the non-destructive and automated nature of the node extraction and response evaluation is promising for its application in qualification and certification of additively manufactured lattice structures.

36 MATERIALS SCIENCE↗