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At least 1,297 records · Page 72

Procedure for estimating stability and control parameters from flight test data by using maximum likelihood methods employing a real-time digital system

A maximum likelihood parameter estimation procedure and program were developed for the extraction of the stability and control derivatives of aircraft from flight test data. Nonlinear six-degree-of-freedom equations describing aircraft dynamics were used to derive sensitivity equations for quasilinearization. The maximum likelihood function with quasilinearization was used to derive the parameter change equations, the covariance matrices for the parameters and measurement noise, and the performance index function. The maximum likelihood estimator was mechanized into an iterative estimation procedure utilizing a real time digital computer and graphic display system. This program was developed for 8 measured state variables and 40 parameters. Test cases were conducted with simulated data for validation of the estimation procedure and program. The program was applied to a V/STOL tilt wing aircraft, a military fighter airplane, and a light single engine airplane. The particular nonlinear equations of motion, derivation of the sensitivity equations, addition of accelerations into the algorithm, operational features of the real time digital system, and test cases are described.

Grove, R. D.↗

Static performance of a 13.97 cm (5.5 inch) diameter model VTOL lift fan

A tip-turbine-driven fan of the type currently being used in wind tunnel tests of VTOL lift fan models was tested. Values of thrust, weight flow, exit total and static pressure, exit swirl angle, and turbine temperature drop were measured as a function of fan speed for several inlet and exit configurations. A standard fan performance map was also obtained.

Lowe, W. H.↗

Validation of Fitness for Duty Standards Using Pre- and Post-Flight Capsule Egress and Suited Functional Performance Tasks in Simulated Reduced Gravity (Pilot Egress Fitness)

As NASA prepares for exploration missions, it will be critical to understand and build upon known crew capabilities. Specifically, we need to know the functional capacities of crew at different stages of a mission and characterize these profiles so that the appropriate vehicle requirements and mission concepts of operations (ConOps) can be developed. One of the most complex phases of any missions is when there is a transition between gravity environments. For instance, both physiological adaptation to microgravity and subsequent re-entry into a gravity environment result in reduced functional capacity, even with rigorous adherence to inflight countermeasures. Quantification of the astronauts’ post-landing functional performance is necessary to design ConOps for exploration missions. Specifically, these two high-risk tasks may have to be performed soon after gravity transitions: •Unassisted capsule egress task after return to Earth •Planetary extravehicular activity (EVA) soon after landing on Mars or the Moon This study has been broken down into two phases. A pilot phase to assess the overall feasibility and demonstrate the capability to do these tasks shortly after landing and the full Egress Fitness study, which will be part of the CIPHER complement. This study uses a functional task approach to characterize performance of these high-risk tasks in long-duration ISS crewmembers before flight and shortly after return to Earth. Prior to any testing, each astronaut subject completes a suit fit check to ensure adequate sizing and mobility to be able to complete the EVA tasks. Pilot Egress Fitness pre-flight and post-flight testing includes an Earth based emergency egress out of a functional capsule mockup, and a short Mars gravity EVA simulation including suit donning, hatch egress, ladder descent, task board cable operations, baggage transfer over sand/rocky regolith, alignment with a rear entry port, and suit egress. Pre-flight testing can occur almost anytime pre-flight, but post-flight scheduling is much more critical with the capsule egress test occurring 1-4 hours after landing and the planetary EVA approximately 18-36 hours after landing. Data collected for both tasks includes task completion time, photo, and video. The EVA portion also includes collection of metabolic and heart rate. Pilot Egress Fitness study has completed baseline pre-flight testing on 3 astronaut subjects. Post-flight testing of the first two subjects will be completed in November 2021 and the final subject around March 2022. Results and lessons learned from this pilot study will inform the full Egress Fitness study, which will incorporate additional pre-flight sessions, longer EVA tasks, and post-flight testing on R+1, 4, and 7 to characterize the timeframe of recovery

J R Norcross↗

Design of an advanced energy management system for microgrid control using a state machine

A state machine is proposed as the solution for an automated microgrid energy management system (EMS) to improve transient performance during transition operations. It characterizes microgrid operation by seven states that cover all the operating modes: two for steady-state operation (grid-connected and islanded), four for transition operation (preparing for disconnection, transitioning to islanding, preparing for reconnection, and transitioning to grid-connected), and one for emergency operation (black-start operation). A unique dispatch algorithm is developed for each state to achieve the control objective, and the transition function is implemented in the state machine as control logics to transition the system from one state to the next. The feasibility and effectiveness of the developed state machine is validated by simulation in MATLAB with an example microgrid, and the test results show excellent performance of the state machine to achieve the target control objective in each state and to improve the system's transient performance during transition operation.

36 MATERIALS SCIENCE↗

Ares I-X: First Step in a New Era of Exploration

Since 2005, NASA's Constellation Program has been designing, building, and testing the next generation of launch and space vehicles to carry humans beyond low-Earth orbit (LEO). On October 28, 2009, the Ares Projects successfully launched the first suborbital development flight test of the Ares I crew launch vehicle, Ares I-X, from Kennedy Space Center (KSC). Although the final Constellation Program architecture is under review, data and lessons obtained from Ares I-X can be applied to any launch vehicle. This presentation will discuss the mission background and future impacts of the flight. Ares I is designed to carry up to four astronauts to the International Space Station (ISS). It also can be used with the Ares V cargo launch vehicle for a variety of missions beyond LEO. The Ares I-X development flight test was conceived in 2006 to acquire early engineering, operations, and environment data during liftoff, ascent, and first stage recovery. Engineers are using the test flight data to improve the Ares I design before its critical design review the final review before manufacturing of the flight vehicle begins. The Ares I-X flight test vehicle incorporated a mix of flight and mockup hardware, reflecting a similar length and mass to the operational vehicle. It was powered by a four-segment SRB from the Space Shuttle inventory, and was modified to include a fifth, spacer segment that made the booster approximately the same size as the five-segment SRB. The Ares I-X flight closely approximated flight conditions the Ares I will experience through Mach 4.5, performing a first stage separation at an altitude of 125,000 feet and reaching a maximum dynamic pressure ("Max Q") of approximately 850 pounds per square foot. The Ares I-X Mission Management Office (MMO) was organized functionally to address all the major test elements, including: first stage, avionics, and roll control (Marshall Space Flight Center); upper stage simulator (Glenn Research Center); crew module/launch abort system simulator (Langley Research Center); and ground systems and operations (KSC). Interfaces between vehicle elements and vehicle-ground elements, as well as environment analyses were performed by a systems engineering and integration team at Langley. Experience and lessons learned from these integrated product teams area are already being integrated into the Ares Projects to support the next generation of exploration launch vehicles.

Davis, Stephan R.↗

Evaluation of the ICET Test Stand to Assess the Performance of a Range of Ceramic Media Filter Elements in Support of ASME AG-1 Subsection FO

High Efficiency Particulate Air (HEPA) filters are defined as extended-medium, dry-type filters with: (1) a minimum particle removal efficiency of no less than 99.97 percent for 0.3 micrometer particles, (2) a maximum, clean resistance of 1.0 inch water column (in. WC) when operated at 1,000 cubic feet per minute (CFM), and (3) a rigid casing that extends the full depth of the medium. Specifically, ceramic media HEPA filters provide better performance at elevated temperatures, are moisture resistant and nonflammable, can perform their function if wetted and exposed to greater pressures, and can be cleaned and reused. This paper describes the modification and design of a large scale test stand which properly evaluates the filtration characteristics of a range of ceramic media filters challenged with a nuclear aerosol agent in order to develop Section FO of ASME AG-1.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Extreme Environment Hot Fire Durability of Post-Processed Additively Manufactured GRCop-Alloy Combustion Chambers in LOX/Hydrogen and LOX/Methane

Extreme environment survivability of metal additive manufactured (AM) GRCop-alloy thrust chambers has been demonstrated in different bi-propellants at near stoichiometric and even oxygen rich combustion. GRCop-alloy chambers tested at NASA Marshall Space Flight Center (MSFC) have accumulated over 26,000 seconds of hot fire duration and over 500 starts. These chambers are produced using an AM process called laser powder bed fusion (L-PBF). A major feature of this process is high wall surface roughness which can be customized in post processing to leverage various performance advantages. Post-processing can include heat treatment, final machining, polishing, and welding and is key to hardware survivability in extreme environments. Surface finish enhancement techniques were applied to the hot wall and coolant channels to reduce the overall total heat load to the chamber walls. Performance optimization of various thrust class TCA’s is a strategic technology goal of NASA MSFC. Three different chamber geometries using cryogenic methane and de-ionized water as coolants were hot fire tested to obtain their life cycle, pressure drop, and heat load performances. Several 1.2K lbf LOX/H2 chambers, 1K lbf LOX/CH4 chambers, and 7K lbf LOX/CH4 chambers were tested. All post-processed configurations performed remarkably well when subjected to extreme hot fire test conditions. Streaking and blanching due to localized oxygen rich conditions were observed on some test articles in their as-built surface finish state. However, this is actually a function of the injector mixing and only serves to further establish the durability of L-PBF GRCop-alloy thrust chambers. Several different polishing techniques were applied to the hot wall and integrated coolant channels prior to hot fire testing and their performances assessed. Overall, AM produced GRCop chambers are extremely reliable, durable, and customizable to the desired performance metrics.

grcop↗

Density-Functional Tight-Binding for Platinum Clusters and Bulk: Electronic vs Repulsive Parameters

We present a general purpose Pt-Pt density-functional tight-binding (DFTB) parameter for Pt clusters as well as bulk, using a genetic algorithm (GA) to automatize the parameterization effort. First we quantify the improvement possible by only optimizing the repulsive potential alone, and second we investigate the effect of improving the electronic parameter as well. During both parameterization efforts we employed our own training set and test sets, with one set containing ~20,000 spin-polarized DFT structures. We analyze the performance of our two DFTB Pt-Pt parameter sets against density functional theory (DFT) as well as an earlier DFTB Pt-Pt parameters. Our study sheds light on the role of both repulsive and electronic parameters with regards to DFTB performance.

36 MATERIALS SCIENCE↗

Identification and Characterization of the Major Porin of Desulfovibrio vulgaris Hildenborough

ABSTRACT Due in large part to their ability to facilitate the diffusion of a diverse range of solutes across the outer membrane (OM) of Gram-negative bacteria, the porins represent one of the most prominent and important bacterial membrane protein superfamilies. Notably, for the Gram-negative bacterium Desulfovibrio vulgaris Hildenborough, a model organism for studies of sulfate-reducing bacteria, no genes for porins have been identified or proposed in its annotated genome. Results from initial biochemical studies suggested that the product of the DVU0799 gene, which is one of the most abundant proteins of the D. vulgaris Hildenborough OM and purified as a homotrimeric complex, was a strong porin candidate. To investigate this possibility, this protein was further characterized biochemically and biophysically. Structural analyses via electron microscopy of negatively stained protein identified trimeric particles with stain-filled depressions and structural modeling suggested a β-barrel structure for the monomer, motifs common among the known porins. Functional studies were performed in which crude OM preparations or purified DVU0799 was reconstituted into proteoliposomes and the proteoliposomes were examined for permeability against a series of test solutes. The results obtained establish DVU0799 to be a pore-forming protein with permeability properties similar to those observed for classical bacterial porins, such as those of Escherichia coli . Taken together, these findings identify this highly abundant OM protein to be the major porin of D. vulgaris Hildenborough. Classification of DVU0799 in this model organism expands the database of functionally characterized porins and may also extend the range over which sequence analysis strategies can be used to identify porins in other bacterial genomes. IMPORTANCE Porins are membrane proteins that form transmembrane pores for the passive transport of small molecules across the outer membranes of Gram-negative bacteria. The present study identified and characterized the major porin of the model sulfate-reducing bacterium Desulfovibrio vulgaris Hildenborough, observing its preference for anionic sugars over neutral ones. Its predicted architecture appears to be novel for a classical porin, as its core β-barrel structure is of a type typically found in solute-specific channels. Broader use of the methods employed here, such as assays for channel permeability and electron microscopy of purified samples, is expected to help expand the database of confirmed porin sequences and improve the range over which sequence analysis-based strategies can be used to identify porins in other Gram-negative bacteria. Functional characterization of these critical gatekeeping proteins from divergent Desulfovibrio species should offer an improved understanding of the physiological features that determine their habitat range and supporting activities.

59 BASIC BIOLOGICAL SCIENCES↗

Dark Energy Survey Year 1 Results: Joint Analysis of Galaxy Clustering, Galaxy Lensing, and CMB Lensing Two-point Functions

We perform a joint analysis of the auto and cross-correlations between three cosmic fields: the galaxy density field, the galaxy weak lensing shear field, and the cosmic microwave background (CMB) weak lensing convergence field. These three fields are measured using roughly 1300 sq. deg. of overlapping optical imaging data from first year observations of the Dark Energy Survey and millimeter-wave observations of the CMB from both the South Pole Telescope Sunyaev-Zel'dovich survey and Planck. We present cosmological constraints from the joint analysis of the two-point correlation functions between galaxy density and galaxy shear with CMB lensing. We test for consistency between these measurements and the DES-only two-point function measurements, finding no evidence for inconsistency in the context of flat $\Lambda$CDM cosmological models. Performing a joint analysis of five of the possible correlation functions between these fields (excluding only the CMB lensing autospectrum) yields $S_{8}\equiv \sigma_8\sqrt{\Omega_{\rm m}/0.3} = 0.782^{+0.019}_{-0.025}$ and $\Omega_{\rm m}=0.260^{+0.029}_{-0.019}$. We test for consistency between these five correlation function measurements and the Planck-only measurement of the CMB lensing autospectrum, again finding no evidence for inconsistency in the context of flat $\Lambda$CDM models. Combining constraints from all six two-point functions yields $S_{8}=0.776^{+0.014}_{-0.021}$ and $\Omega_{\rm m}= 0.271^{+0.022}_{-0.016}$. These results provide a powerful test and confirmation of the results from the first year DES joint-probes analysis.

79 ASTRONOMY AND ASTROPHYSICS↗

Group structure selection with random forests

Choosing an appropriate group structure for multigroup transport is far from an exact science. For some applications, one blindly uses a group structure developed years ago by forgotten methods. Furthermore, one sometimes uses the same group structure for a variety of problems, even if the group structure was originally developed with a certain application in mind. In this work, we create optimized group structures with simulated annealing for critical assembly test problems and apply a random forest regressor with bagging to choose the best group structure based on parameters of the different test problems. The optimized group structures were generated using a simulated annealing optimizer for several simple, spherical, and unreflected problems. The optimization was performed to minimize a cost function that included fission rate, absorption rate, leakage, and k{sub eff}. A random forest regressor was then trained on a set of International Criticality Safety Benchmark Evaluation Project inputs and used to select one of these six group structures. The trained machine learning model chose the best group structure 65% of the time, and one of the three best 89% of the time. Furthermore, it decreased the L2 error over all test problems by a factor of 25 when compared to the standard Los Alamos 70-group structure. In other words, the model chose group structure that were far more appropriate for the test problems than the traditional LANL group structure. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Orion Launch Abort System Performance on Exploration Flight Test 1

This paper will present an overview of the flight test objectives and performance of the Orion Launch Abort System during Exploration Flight Test-1. Exploration Flight Test-1, the first flight test of the Orion spacecraft, was managed and led by the Orion prime contractor, Lockheed Martin, and launched atop a United Launch Alliance Delta IV Heavy rocket. This flight test was a two-orbit, high-apogee, high-energy entry, low-inclination test mission used to validate and test systems critical to crew safety. This test included the first flight test of the Launch Abort System preforming Orion nominal flight mission critical objectives. NASA is currently designing and testing the Orion Multi-Purpose Crew Vehicle (MPCV). Orion will serve as NASA's new exploration vehicle to carry astronauts to deep space destinations and safely return them to earth. The Orion spacecraft is composed of four main elements: the Launch Abort System, the Crew Module, the Service Module, and the Spacecraft Adapter (Fig. 1). The Launch Abort System (LAS) provides two functions; during nominal launches, the LAS provides protection for the Crew Module from atmospheric loads and heating during first stage flight and during emergencies provides a reliable abort capability for aborts that occur within the atmosphere. The Orion Launch Abort System (LAS) consists of an Abort Motor to provide the abort separation from the Launch Vehicle, an Attitude Control Motor to provide attitude and rate control, and a Jettison Motor for crew module to LAS separation (Fig. 2). The jettison motor is used during a nominal launch to separate the LAS from the Launch Vehicle (LV) early in the flight of the second stage when it is no longer needed for aborts and at the end of an LAS abort sequence to enable deployment of the crew module's Landing Recovery System. The LAS also provides a Boost Protective Cover fairing that shields the crew module from debris and the aero-thermal environment during ascent. Although the Orion Program has tested a number of the critical systems of the Orion spacecraft on the ground, the launch environment cannot be replicated completely on Earth. A number of flight tests have been conducted and are planned to demonstrate the performance and enable certification of the Orion Spacecraft. Exploration Flight Test 1, the first flight test of the Orion spacecraft, was successfully flown on December 5, 2014 from Cape Canaveral Air Force Station's Space Launch Complex 37. Orion's first flight was a two-orbit, high-apogee, high-energy entry, low-inclination test mission used to validate and test systems critical to crew safety, such as heat shield performance, separation events, avionics and software performance, attitude control and guidance, parachute deployment and recovery operations. One of the key separation events tested during this flight was the nominal jettison of the LAS. Data from this flight will be used to verify the function of the jettison motor to separate the Launch Abort System from the crew module so it can continue on with the mission. The LAS nominal jettison event on Exploration Flight Test 1 occurred at six minutes and twenty seconds after liftoff (See Fig. 3). The abort motor and attitude control motors were inert for Exploration Flight Test 1, since the mission did not require abort capabilities. A suite of developmental flight instrumentation was included on the flight test to provide data on spacecraft subsystems and separation events. This paper will focus on the flight test objectives and performance of the LAS during ascent and nominal jettison. Selected LAS subsystem flight test data will be presented and discussed in the paper. Exploration Flight Test -1 will provide critical data that will enable engineering to improve Orion's design and reduce risk for the astronauts it will protect as NASA continues to move forward on its human journey to Mars. The lessons learned from Exploration Flight Test 1 and the other Flight Test Vehicles will certainly contribute to the vehicle architecture of a human-rated space launch vehicle.

McCauley, R.↗

Accelerated basis adaptation in homogeneous chaos spaces

Polynomial chaos expansions (PCE) provide an efficient approach to uncertainty quantification (UQ) and have been adapted to diverse applications across the spectrum of science and engineering. For situations involving large stochastic parameterizations, the curse of dimensionality renders PCE-based methods computationally prohibitive. A basis adaptation approach for PCE was proposed by Tipireddy and Ghanem (2014) which transforms the input random variables through an isometry such that sufficient probabilistic characterization of specific quantities of interest (QoI) is concentrated in an algebraic manifold embedded in the linear span of the dominant transformed variables. While quite versatile, that original version of the PCE basis adaptation exhibited slow convergence for a number of problems of practical significance. In the present paper, we propose two novel methods to accelerate the convergence of the original basis adaptation approach, thus expanding its reach while also providing insight into its performance. In the first method, information gained from a pilot PCE representation is used to correct the mean and Gaussian coefficients in the adapted space. By taking advantages of probabilistic information in higher dimensional adaptation gleaned from an initial adaptation, the second method updates the rotation matrix used to identify the dominant transformed variables. In this manner, the new rotation matrix concentrates even more probabilistic information in its first few dimensions. These two method can be combined to achieve even better performance, the combined method is referred to as sequentially optimized adaptation method. Here, the methods are demonstrated on an analytical test function and a model of a space structure with several sub-components and a non-smooth quantity of interest representing the maximum acceleration over time. Both methods achieve accelerated convergence of the basis adaptation approach with negligible additional costs.

Accelerated convergence↗

Gold-Standard Chemical Database 137 (GSCDB137): A Diverse Set of Accurate Energy Differences for Assessing and Developing Density Functionals

We present GSCDB137, a rigorously curated benchmark library of 137 data sets (8377 entries) covering main-group and transition-metal reaction energies and barrier heights, (intra- and intermolecular) noncovalent interactions, dipole moments, polarizabilities, electric-field response energies, and vibrational frequencies. Legacy data from GMTKN55 and MGCDB84 have been updated to today's best reference values; redundant or low-quality points were removed, and many new, property-focused sets were added. Testing 29 popular density functional approximations (DFAs) confirms the expected Jacob's-ladder hierarchy overall but also reveals notable exceptions: functional performance for frequencies and electric-field properties correlates poorly with that for other ground-state energetics. ωB97M-V and ωB97X-V are the most balanced hybrid meta-GGA and hybrid GGA, respectively; B97M-V and revPBE-D4 lead the meta-GGA and GGA classes. Double hybrids lower mean errors by about 30% versus their hybrid analogues but demand careful frozen-core, basis set, and spin contamination treatment. GSCDB137 offers a comprehensive, openly documented platform for rigorous validation of DFA and universal machine learning potentials, and training of the next generation of exchange-correlation functionals.

Liang, Jiashu [University of California, Berkeley,↗

Augmenting machine learning of energy landscapes with local structural information

We present a machine learning approach for accurately predicting formation energies of binary compounds in the context of crystal structure predictions. The success of any machine learning model depends significantly on the choice of representation used to encode the relevant physical information into machine-learnable data. We test different representation schemes based on partial radial and angular distribution functions (RDF+ADF) on Al–Ni and Cd–Te structures generated using our genetic algorithm for structure prediction. We observe a remarkable improvement in predictive accuracy upon transitioning from global to atom-centered representations, resulting in a threefold decrease in prediction errors. We show that a support vector regression model using a combination of atomic radial and angular distribution functions performs best at the formation energy prediction task, providing small root mean squared errors of 3.9 meV/atom and 10.9 meV/atom for Al–Ni and Cd–Te, respectively. We test the performance of our models against common traditional descriptors and find that RDF- and ADF-based representations significantly outperform many of those in the prediction of formation energies. The high accuracy of predictions makes our machine learning models great candidates for the exploration of energy landscapes.

Honrao, Shreyas J. (ORCID:0000000166155257)↗

CMB-PAInT: An inpainting tool for the cosmic microwave background

Abstract The presence of astrophysical emissions in microwave observations forces us to perform component separation to extract the Cosmic Microwave Background (CMB) signal. However, even in the most optimistic cases, there are still strongly contaminated regions, such as the Galactic plane or those with emission from extragalactic point sources, which require the use of a mask. Since many CMB analyses, especially the ones working in harmonic space, need the whole sky map, it is crucial to develop a reliable inpainting algorithm that replaces the values of the excluded pixels by others statistically compatible with the rest of the sky. This is especially important when working withQandUsky maps in order to obtainE- andB-mode maps which are free fromE-to-Bleakage. In this work we study a method based on Gaussian Constrained Realizations (GCR), that can deal with both intensity and polarization. Several tests have been performed to asses the validation of the method, including the study of the one-dimensional probability distribution function (1-PDF),E- andB-mode map reconstruction, and power spectra estimation. We have considered two scenarios for the input simulation: one case with only CMB signal and a second one including also Planck PR4 semi-realistic noise. Even if we are limited to low resolution maps, N side = 64 ifT,QandUare considered, we believe that this is a useful approach to be applied to future missions such as LiteBIRD, where the target are the largest scales.

Astronomy & Astrophysics↗

Measuring nonlinearities of a cantilever beam using a low-cost efficient wireless intelligent sensor for strain (LEWIS-S)

In the context of experimental vibration data, strain gauges can obtain linear and nonlinear dynamic measurements. However, measuring strain can be disincentivizing and expensive due to the complexity of data acquisition systems, lack of portability, and high costs. This research introduces the use of a low-cost efficient wireless intelligent sensor for strain (LEWIS-S) that is based on a portable-sensor-design platform that streamlines strain sensing. Additionally, the softening behavior of a cantilever beam with geometric and inertial nonlinearities is characterized by the LEWIS-S based on high force level inputs. Two experiments were performed on a nonlinear cantilever beam with measurements obtained by the LEWIS-S sensor and an accelerometer. First, a sine sweep test was performed through the fundamental resonance of the system, then a ring-down test was performed from a large initial static deformation. Good agreement was revealed in quantities of interest such as frequency response functions, the continuous wavelet transforms, and softening behavior in the backbone curves.

42 ENGINEERING↗

A comparison of deep-learning-based inpainting techniques for experimental X-ray scattering

The implementation is proposed of image inpainting techniques for the reconstruction of gaps in experimental X-ray scattering data. The proposed methods use deep learning neural network architectures, such as convolutional autoencoders, tunable U-Nets, partial convolution neural networks and mixed-scale dense networks, to reconstruct the missing information in experimental scattering images. In particular, the recovered pixel intensities are evaluated against their corresponding ground-truth values using the mean absolute error and the correlation coefficient metrics. The results demonstrate that the proposed methods achieve better performance than traditional inpainting algorithms such as biharmonic functions. Overall, tunable U-Net and mixed-scale dense network architectures achieved the best reconstruction performance among all the tested algorithms, with correlation coefficient scores greater than 0.9980.

97 MATHEMATICS AND COMPUTING↗