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All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

A Comprehensive Review of Latent Space Dynamics Identification Algorithms for Intrusive and Non-Intrusive Reduced-Order-Modeling

Numerical solvers of partial differential equations (PDEs) have been widely employed for simulating physical systems. However, the computational cost remains a major bottleneck in various scientific and engineering applications, which has motivated the development of reduced-order models (ROMs). Recently, machine-learning-based ROMs have gained significant popularity and are promising for addressing some limitations of traditional ROM methods, especially for advection dominated systems. In this chapter, we focus on a particular framework known as Latent Space Dynamics Identification (LaSDI), which transforms the high-fidelity data, governed by a PDE, to simpler and low-dimensional latent-space data, governed by ordinary differential equations (ODEs). These ODEs can be learned and subsequently interpolated to make ROM predictions. Each building block of LaSDI can be easily modulated depending on the application, which makes the LaSDI framework highly flexible. In particular, we present strategies to enforce the laws of thermodynamics into LaSDI models (tLaSDI), enhance robustness in the presence of noise through the weak form (WLaSDI), select high-fidelity training data efficiently through active learning (gLaSDI, GPLaSDI), and quantify the ROM prediction uncertainty through Gaussian processes (GPLaSDI). We demonstrate the performance of different LaSDI approaches on Burgers equation, a non-linear heat conduction problem, and a plasma physics problem, showing that LaSDI algorithms can achieve relative errors of less than a few percent and up to thousands of times speed-ups.

Computational Engineering, Finance, and Science (c↗
NASA NTRS1977

An analysis of the technical status of high level radioactive waste and spent fuel management systems

The technical status of the old U.S. mailine program for high level radioactive nuclear waste management, and the newly-developing program for disposal of unreprocessed spent fuel was assessed. The method of long term containment for both of these waste forms is considered to be deep geologic isolation in bedded salt. Each major component of both waste management systems is analyzed in terms of its scientific feasibility, technical achievability and engineering achievability. The resulting matrix leads to a systematic identification of major unresolved technical or scientific questions and/or gaps in these programs.

English, T.↗
NASA NTRS1985

Space station configuration and flight dynamics identification

The Space Station will be assembled in low earth orbit by a combination of deployable and space erectable modules that are progressively integrated during successive flights of the Shuttle. The crew assisted space construction will result in a configuration which is a large scale composite of structural elements having connectivity with a wide range of possible end conditions and imprecisely known dynamic characteristics. The generic applications of Flight Dynamics Identification to the candidate Space Station configurations currently under consideration are described. Identification functions are categorized, and the various methods for extracting parameter estimates are correlated with the sensing of parameter estimates are correlated with the sensing of specific characteristics of interest to both engineering subsystems and users of the Station's commercial and scientific facilities. Onboard implementation architecture and constraints are discussed from the viewpoint of maximizing integration of the Identification process with the flight subsystem's data and signal flow.

Metter, E.↗
NASA NTRS1989

Effective Use of Cray Supercomputers

The effective use of a supercomputer depends on many aspects, including the ability of users to write efficient programs to use the resources of the system in an optimal manner. However, it is the responsibility of the system managers of these systems to insure the maximum effectiveness of the overall system is achieved. Many varying techniques have been developed at the Numerical Aerodynamic Simulation (NAS) Program to advance the management of these critical systems. Many of the issues and techniques used for managing supercomputers are common to multi-user UNIX systems, regardless of the version of UNIX or the power of the hardware. However, a UNICOS supercomputer presents some special challenges and requires additional features and tools to be developed to effectively manage the system. Only part of the challenge is related to performance monitoring and improvement. Much of the responsibility of the system manager is to provide fair and consistent access to the system resources, which is at times a difficult problem. After an introduction to the environment at the Numerical Aerodynamic Simulation Project is given as background this paper will first discuss the areas which are common to UNDC system management. Then the paper will discuss the specific areas of UNICOS which must be used to operate the system efficiently. The paper goes on to discuss the methods of supporting individual users in order to increase their effectiveness and the efficiency of their programs. This is accomplished through a professional support staff who interact on a daily basis to support the NAS scientific client community.

Kramer, William T. C.↗
NASA NTRS2015

Detailed Results from the Flame Extinguishment Experiment (FLEX) March 2009 to December 2011

The Flame Extinguishment Experiment (FLEX) program is a continuing set of experiments on droplet combustion, performed employing the Multi-User Droplet Combustion Apparatus (MDCA), inside the chamber of the Combustion Integrated Rack (CIR), which is located in the Destiny module of the International Space Station (ISS). This report describes the experimental hardware, the diagnostic equipment, the experimental procedures, and the methods of data analysis for FLEX. It also presents the results of the first 284 tests performed. The intent is not to interpret the experimental results but rather to make them available to the entire scientific community for possible future interpretations.

International Space Station↗
NASA NTRSDate not supplied

Isolation Standard Measures: A Set of Validated and Feasible Measurements Ensuring Comparability Across Isolation and Confinement Studies

Isolation and confinement studies have been essential to the preparation of crewed long-duration space missions, acting as analogues that facilitate the study of psychological and physiological responses to isolation and confinement. They also serve as opportunities for the development, testing, and validation of countermeasures and coping methods to handle the challenges that arise in such scenarios. Due to the small sample sizes in combination with high inter-individual variability, single isolation campaigns are not always sufficient for obtaining statistically significant scientific findings. To address this issue and improve comparability between different studies, the need for standardized measures to be collected in all future isolation and confinement studies was identified. Additionally, these measures should also be shown to be generally valid, reliable, feasible and acceptable in analogue and spaceflight environments. Standard measures in isolation and confinement studies allow for more direct comparisons of results and synthesis of data across isolation and confinement studies as well as provide an important step toward standard measures in spaceflight. An international expert group with representatives from different space agencies worldwide was brought together to define a core set of standard measures for isolation and confinement studies. This paper provides an overview of the expert group’s recommendations for international standard measures for future isolation and confinement studies, along with subsequent updates coordinated by the International Countermeasures Working Group (ICMWG), which was established as a sub-Working Group under the International Space Life Sciences Working Group (ISLSWG). Additional experts were consulted by the ICMWG partner agencies as required. The collection of the described set of isolation standard measures will provide data on the following parameters: sleep, mood, psychological state, psychophysiology, cognitive performance, stress and the immune system, general health and well-being, team measures, nutritional measures, and environmental conditions. For each measure, recommendations were made about duration and frequency of administration, along with specific implementation recommendations in relation to the duration of the isolation study. The set of isolation standard measures will be reassessed every two years at a minimum to ensure they are up to date and reflect the current state-of-the-art.

Isolation↗
DOE OSTI2021

Evaluation of the Large-Scale and Regional Climatic Response Across North Africa to Natural Variability in Oceanic Modes and Terrestrial Vegetation Among the CMIP5 Models

Hydrologic variability is a serious threat to the poverty-stricken regions of North Africa. Meanwhile, the scientific community struggles to attribute these extreme climatic episodes to specific oceanic and land drivers. Prior modeling studies have not assessed simulated feedbacks over North Africa against an established observational benchmark, so their results are considered as untested, model-specific findings. The Coupled Model Intercomparison Project Phase Five (CMIP5) archive represents the state-of-the-art in climate projections, with most CMIP5 models now containing interactive vegetation phenology; however, there have been no studies to date of their simulated vegetation feedbacks. The capability of CMIP5 models at accurately simulating the forcing of both sea-surface temperature (SST) and regional leaf area index (LAI) anomalies on North African climate needs to be a key consideration in assessing the models’ overall credibility and determining appropriate model weighting for developing climate projections. The Generalized Equilibrium Feedback Assessment (GEFA) is a promising statistical method, which can be applied to either model output or observations, for isolating the local and remote impacts of individual oceanic or terrestrial forcings on regional climate. We performed a combined observational and modeling assessment of land-ocean-atmosphere interactions across the distinct ecological and moisture gradients of North Africa. We evaluated and demonstrated the reliability of the GEFA statistical method over North Africa using the Community Earth System Model (CESM), applied GEFA to observational data to quantify the observed forcing of ocean basin SST anomalies and regional LAI anomalies on North African climate, evaluated the CMIP5 models’ performance in terms of representing these key observed feedbacks, and formulated CMIP5 feedback performance metrics for weighting North African climate projections. Our study represented the first attempt to separate the observed roles of oceanic and vegetation feedbacks across North Africa, the first systematic assessment and intercomparison of land-ocean-atmosphere feedbacks in CMIP5, and the first exploration of vegetation feedbacks among CMIP5 models. The following work was accomplished. (1) The team generated 14 scientific publications and 30 presentations based on the DOE-funded research. (2) A stepwise version of the GEFA statistical method was developed in which unimportant forcings were dropped to increase the reliability of the results. (3) SGEFA was successfully validated through experiments with CESM in terms of its ability to isolate the atmospheric responses to individual oceanic or land forcings. (4) Observational evidence was revealed for the Sahel’s positive vegetation-rainfall feedback on the seasonal to interannual time scale, and it was attributed to a moisture recycling mechanism rather than an albedo mechanism. (5) An approach with SGEFA was developed in which the individual contributions of soil moisture versus vegetation forcings could be separated, revealing that the former forcing outweighed the latter for sub-Saharan Africa. (6) Tropical ocean temperatures were found to be key regulators of pan-tropical vegetation variability, especially for arid and semi-arid regions, including sub-Saharan Africa. (7) The CMIP5 models largely underestimated the importance of land feedbacks across the Sahel. (8) The general consensus among CMIP5 models indicates, for the late 21st century, a diminished seasonal predictability of sub-Saharan African regional climate and an elevated role of the land surface compared to oceanic drivers in regulating regional climate variability. (9) Land-ocean-atmosphere interactions were demonstrated to be key contributors to the seasonal predictability of African wildfire activity. (10) The El Djouf was determined to be of greater importance than the Bodélé depression in terms of providing trans-Atlantic dust transport to the Americas.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Delving into the depths of NGC 3783 with XRISM II. Cross-calibration of X-ray instruments used in the large, multi-mission observational campaign

Context. Accurate X-ray spectroscopic measurements are fundamental for deriving basic physical parameters of the most abundant baryon components in the Universe. The plethora of X-ray observatories currently operational enables a panchromatic view of the high-energy emission of celestial sources. However, uncertainties in the energy-dependent calibration of the instrument transfer functions (e.g. the effective area, energy redistribution, or gain) can limit - and historically, did limit - the accuracy of X-ray spectroscopic measurements. Aims. We revised the status of the cross-calibration among the scientific payload on board four operation missions: Chandra, NuSTAR, XMM-Newton, and the recently launched XRISM. XRISM carries the micro-calorimeter Resolve, which yields the best energy resolution at energies ≥2 keV. For this purpose, we used the data from a 10-day-long observational campaign targeting the nearby active galactic nucleus NGC 3783, carried out in July 2024. Methods. We present a novel model-independent method for assessing the cross-calibration status that is based on a multi-node spline of the spectra with the highest-resolving power (XRISM/Resolve in our campaign). We also estimated the impact of the intrinsic variability of NGC 3783 on the cross-calibration status due to the different time coverages of participating observatories and performed an empirical reassessment of the Resolve throughput at low energies. Results. Based on this analysis, we derived a set of energy-dependent correction factors of the observed responses, enabling a statistically robust analysis of the whole spectral dataset. They will be employed in subsequent papers describing the astrophysical results of the campaign. Aims. We revised the status of the cross-calibration among the scientific payload on board four operation missions: Chandra, NuSTAR, XMM-Newton, and the recently launched XRISM. XRISM carries the micro-calorimeter Resolve, which yields the best energy resolution at energies ≥2 keV. For this purpose, we used the data from a 10-day-long observational campaign targeting the nearby active galactic nucleus NGC 3783, carried out in July 2024. Methods. We present a novel model-independent method for assessing the cross-calibration status that is based on a multi-node spline of the spectra with the highest-resolving power (XRISM/Resolve in our campaign). We also estimated the impact of the intrinsic variability of NGC 3783 on the cross-calibration status due to the different time coverages of participating observatories and performed an empirical reassessment of the Resolve throughput at low energies. Results. Based on this analysis, we derived a set of energy-dependent correction factors of the observed responses, enabling a statistically robust analysis of the whole spectral dataset. They will be employed in subsequent papers describing the astrophysical results of the campaign.

Active Galactic Nuclei, individual: NGC 3783↗
NASA NTRSDate not supplied

Development of Additive Manufacturing Technologies for 3D Printing of Spacecraft Heat Shields

Introduction: Ablative heat shields are an enabling technology for entry into planetary atmospheres. From the PICA heatshields used for several Mars rovers to the carbon phenolic material used for Galileo’s Jupiter entry probe, the heat shield manages the heat load transferred to the payload, protecting the sensitive scientific instruments carried on entry probes. The Additive Manufacturing of Thermal Protection Systems (AMTPS) project, an Early Career Initiative (ECI) funded by NASA’s Space Technology Mission Directorate and led by NASA Johnson Space Center, seeks to develop materials and processes for 3D printing ablative heat shields for spacecraft. Current methods for producing ablative heat shields are extremely labor intensive and re-quire extensive hands-on processes and quality control characterization. Additive manufacturing (AM) offers the possibility of reduced production times, improved reliability, and enhanced performance via graded compositions. Costs will also be reduced by reducing the time and labor required for heat shield production. Direct integration of the heat shield onto the structure during processing simplifies integration and reduces risk. Material Development: A critical challenge for the project is development of a material system that can (1) be printed in a near-net shape process and (2) perform well as an ablator. Achieving printability requires the material to flow under applied pressure, but maintain its shape once extruded from the printer nozzle. Ablative performance is measured by a multitude of markers, including char yield, char strength, thermal conductivity, and recession rate. Furthermore, there are several mechanical and thermal property considerations for vehicle integration including coefficient of thermal expansion (CTE) and residual stress. AM technology will be leveraged to grade the material formulation and properties through the thickness of the heat shield, an architecture not possible with current manufacturing processes. To this end, “robust” material formulations have been pre-pared with higher density for use on the surface where most ablation will occur. “Insulative” material formulations, with lower density and lower thermal conductivity, are prepared for use in the depth of the heat shield. This graded architecture will re-duce the overall mass of the heat shield and reduce costs and/or increase scientific payload capacities. To achieve a material system with the required properties, multiple resins have been investigated in collaboration with NASA Ames Research Center. To tune printability and performance, resin additives were studied to improve flexibility of the cured material while maintaining acceptable ablative performance. Material coupons were printed and studied via a suite of mechanical and thermal characterization methods. Arc jet testing was conducted at NASA Ames Research Center to evaluate ablative performance and thermal protection under conditions expected in atmospheric entry. Manufacturing Scale-Up: A partnership with Oak Ridge National Laboratory (ORNL) aims to enable full-scale fabrication of a 3D printed heat shield. Leveraging expertise in manufacturing and 3D printing at ORNL, a mid-scale manufacturing demonstration unit will be built and tested, using a dual-layer ablative system printed directly onto the titanium structure. Work on robotic system integration is ongoing and efforts to scale up material mixing with a material compound will ensure accurate and homogenous composition. Flight Test: A hypersonic sub-orbital flight test will provide a rigorous test of material performance ranging from ablation, thermal management, and mechanical integrity. Design of the capsule has taken place in collaboration with the University of Kentucky. Data collected from the flight will inform future design efforts in material formulation, printing methodology, and heat shield-capsule integration.

additive manufacturing↗
DOE OSTI2020

Correction: A universal method for sensitive and cell-free detection of CRISPR-associated nucleases

In the original article, incorrect grant information from the Department of Energy was provided. The corrected Acknowledgementssection is provided below, with the correct grant number:This work was supported by the Burroughs Wellcome Fund (Career Award at the Scientific Interface to A. C.), DARPA (BrdiN66001-17-2-4055 to A. C.), NIH (1R21AI126239-01 to A. C.), Army Research Office award W911NF1610586 (to A. C.), and by theDepartment of Energy through grant DE-SC0010595 to E. F., which supported the salary of H. K. K. S. This work is dedicated toProfessor Ronald T. Raines on the occasion of his 60th birthday.The Royal Society of Chemistry apologises for these errors and any consequent inconvenience to authors and readers.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1997

Automated Reuse of Scientific Subroutine Libraries through Deductive Synthesis

Systematic software construction offers the potential of elevating software engineering from an art-form to an engineering discipline. The desired result is more predictable software development leading to better quality and more maintainable software. However, the overhead costs associated with the formalisms, mathematics, and methods of systematic software construction have largely precluded their adoption in real-world software development. In fact, many mainstream software development organizations, such as Microsoft, still maintain a predominantly oral culture for software development projects; which is far removed from a formalism-based culture for software development. An exception is the limited domain of safety-critical software, where the high-assuiance inherent in systematic software construction justifies the additional cost. We believe that systematic software construction will only be adopted by mainstream software development organization when the overhead costs have been greatly reduced. Two approaches to cost mitigation are reuse (amortizing costs over many applications) and automation. For the last four years, NASA Ames has funded the Amphion project, whose objective is to automate software reuse through techniques from systematic software construction. In particular, deductive program synthesis (i.e., program extraction from proofs) is used to derive a composition of software components (e.g., subroutines) that correctly implements a specification. The construction of reuse libraries of software components is the standard software engineering solution for improving software development productivity and quality.

Lowry, Michael R.↗
NASA NTRS2008

Conceptual Design Methods and the Application of a Tradespace Modeling Tool for Deep Space Missions

Concept studies for deep space missions are typically time-consuming and costly, given the variety of missions and uniqueness of each design. Yet, in an increasingly cost-constrained environment, it is critical to identify the most scientifically valuable and cost-effective designs early in the design process. Modeling is an integral part in helping to identify the most desirable design option. While some spacecraft design models currently exist for Earth-orbiting spacecraft, there has been less success with deep space missions. Instead, these missions require a modified design and modeling approach to enable the same construction of a comprehensive, yet credible, mission tradespace. This paper presents an approach for efficiently constructing such a mission tradespace. In addition to a proposed design and modeling approach, three case study missions are presented including a solar orbiter, a Europa orbiter, and a near-Earth asteroid (NEA) sample return mission.

space vehicles↗
DOE OSTI2024

Astronomaly at scale: searching for anomalies amongst 4 million galaxies

ABSTRACT Modern astronomical surveys are producing data sets of unprecedented size and richness, increasing the potential for high-impact scientific discovery. This possibility, coupled with the challenge of exploring a large number of sources, has led to the development of novel machine-learning-based anomaly detection approaches, such as astronomaly. For the first time, we test the scalability of astronomaly by applying it to almost 4 million images of galaxies from the Dark Energy Camera Legacy Survey. We use a trained deep learning algorithm to learn useful representations of the images and pass these to the anomaly detection algorithm isolation forest, coupled with astronomaly’s active learning method, to discover interesting sources. We find that data selection criteria have a significant impact on the trade-off between finding rare sources such as strong lenses and introducing artefacts into the data set. We demonstrate that active learning is required to identify the most interesting sources and reduce artefacts, while anomaly detection methods alone are insufficient. Using astronomaly, we find 1635 anomalies among the top 2000 sources in the data set after applying active learning, including eight strong gravitational lens candidates, 1609 galaxy merger candidates, and 18 previously unidentified sources exhibiting highly unusual morphology. Our results show that by leveraging the human–machine interface, astronomaly is able to rapidly identify sources of scientific interest even in large data sets.

Astronomy & Astrophysics↗
DOE OSTI2025

Kβ X-ray Emission Spectra Analysis Using Bayesian Optimization

The Kβ X-ray emission spectrum of 3 d transition metals is rich with electronic and structural information due to strong exchange interactions with the valence shell of the metal, and has become crucial for understanding their spin and oxidation states. The spectrum is commonly treated using crystal-field multiplet theory, a semi-empirical theory that uses tunable parameters to control the strength of the effects present in X-ray emission spectroscopy (XES). However, determining the experimental values of these parameters remains a challenge. We present a methodology that applies Bayesian optimization to crystal-field multiplet theory to determine parameter values. The algorithm is tested on the X-ray emission spectra of a collection of Mn, Co, and Ni oxides. We are able to find optimal values for the four most impactful parameters: Slater−Condon reduction factors F dd , F pd , and G pd , and crystal field splitting 10 Dq . The algorithm produces significantly improved accuracy compared to current analysis methods, and probes interparameter dependencies by modeling the error landscape. This advancement enhances XES analysis by offering an approach of obtaining quantitative electronic structural information on 3 d transition metal valence shells, facilitating applications across various scientific fields.

Bayesian optimization↗
DOE OSTI2025

Water Mass Transformation Budgets in Finite‐Volume Generalized Vertical Coordinate Ocean Models

Water Mass Transformation (WMT) theory provides conceptual tools that in principle enable innovative analyses of numerical ocean models; in practice, however, these methods can be challenging to implement and interpret, and therefore remain under-utilized. Our aim is to demonstrate the feasibility of diagnosing all terms in the water mass budget and to exemplify their usefulness for scientific inquiry and model development by quantitatively relating water mass changes, overturning circulations, boundary fluxes, and interior mixing. We begin with a pedagogical derivation of key results of classical WMT theory. We then describe best practices for diagnosing each of the water mass budget terms from the output of Finite-Volume Generalized Vertical Coordinate (FV-GVC) ocean models, including the identification of a non-negligible remainder term as the spurious numerical mixing due to advection scheme discretization errors. We illustrate key aspects of the methodology through the analysis of a polygonal region of the Greater Baltic Sea in a regional demonstration simulation using the Modular Ocean Model v6 (MOM6). We verify the convergence of our WMT diagnostics by brute-force, comparing time-averaged (“offline”) diagnostics on various vertical grids to timestep-averaged (“online”) diagnostics on the native model grid. Finally, we briefly describe a stack of xarray-enabled Python packages for evaluating WMT budgets in FV-GVC models (culminating in the new xwmb package), which is intended to be model-agnostic and available for community use and development.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Analysis of Needlet Internal Linear Combination performance on B -mode data from sub-orbital experiments

The observation of primordial B modes in cosmic microwave background (CMB) polarisation data represents the main scientific goal of most of the future CMB experiments. This signal is predicted to be much lower than polarised Galactic emission (foregrounds) in any region of the sky, pointing to the need for effective component separation methods. Aims. Among all the techniques, the blind Needlet Internal Linear Combination (NILC) is of great relevance given our current limited knowledge of the B-mode foregrounds. In this work, we explore the possibility of employing NILC for the analysis of B modes reconstructed from partial-sky data, specifically addressing the complications that such an application yields such as E–B leakage, needlet filtering, and beam convolution. We consider two complementary simulated datasets of future experiments: the balloon-borne Short Wavelength Instrument for the Polarisation Explorer (SWIPE) of the Large Scale Polarisation Explorer, which targets the observation of both reionisation and recombination peaks of the primordial CMB B-mode angular power spectrum, and the ground-based Small Aperture Telescope of Simons Observatory, which, instead, is designed to observe only the recombination bump at ℓ ~ 80. We assessed the performance of the following two alternative techniques to correct for the CMB E–B leakage: the recycling technique and the Zhao-Baskaran method. We find that both techniques reduce the E–B leakage residuals at a negligible level given the sensitivity of the considered experiments, except for the recycling method in the SWIPE footprint at ℓ < 20. Thus, we implemented two extensions of the pipeline, the iterative B decomposition and the diffusive inpainting, which enabled us to recover the input CMB B-mode power for ℓ ≥ 5. For the considered experiments, we demonstrate that needlet filtering and beam convolution do not affect the CMB B-mode reconstruction. Finally, with an appropriate masking strategy, we find that NILC foregrounds subtraction allows one to achieve sensitivities on the tensor-to-scalar ratio in agreement with the targets of the considered CMB experiments.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Enhancing Electron Microscopy Image Classification Using Data Augmentation

Manual labeling for machine learning tasks such as image classification is tedious and labor-intensive; as a result, scientific datasets suitable for deep learning applications are scarce and limited. While data augmentation techniques have shown promise for extending image datasets, very little work has been done to understand the impact of combining multiple augmentation methods sequentially or the limits of their effectiveness when combined. Our work addresses this gap by examining how standard and combinatorial data augmentation affects the performance of machine learning models when trained on small datasets for label classification tasks. For our analysis, we generate single, double and quadruple-augmented datasets for a microscopy image classification task using six standard augmentation methods, and compare the resultant improvements observed in binary classification accuracy with three standard image classification models (DenseNet169, MobileNetV2, ResNet101V2). Our experiments show a non-monotonic relationship between the number of simultaneous augmentation methods and classification accuracy, indicating that there is a trade-off between the degree of augmentation and the model performance. These findings suggest that the optimal number of augmentation methods will vary by domain and use case. We also find that the order in which augmentation methods are applied to a limited dataset matters when combining augmentation schemes, with our use case showing performance differences up to 2.6% when the augmentation order is reversed for double-augmented datasets. Our work offers insights to the limits of data augmentation when working on image classification tasks with limited datasets.

Welsman, Jordan A↗