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DOE OSTI2025

Raptor

Raptor is an efficient Python-based tool for predicting the formation and morphology of stochastic lack of fusion defects in metal AM processes. A major obstacle for the qualification and certification of additively manufactured parts in critical applications continues to be performance variability caused in part by porosity-related defects. High-fidelity process models that could predict these defect features are currently too computationally expensive for component-level analysis. To address this, Raptor employs a high-performance geometric method to model the dynamic melt pool rather than relying on computationally intensive thermal fluid dynamics. This allows Raptor to rapidly identify regions of unmelted material that correspond to lack of fusion pores. The efficiency of this approach significantly reduces the time and resources needed for generating 3D defect predictions, which enables users to conduct large-scale parameter studies and evaluate how process variations affect part quality. The framework offers operational flexibility; users can execute simulations through a simple command line interface or integrate core functions as a library within larger computational workflows. Simulation outputs include 3D porosity maps for visualization and tools for quantitative morphological analysis. These results are suitable for direct comparison with experimental characterization data from methods such as X-ray computed tomography and can be used for statistical process optimization.

Subraveti, Vamsi [Vanderbilt Univ., Nashville, TN ↗

NASA NTRS1991

A new technique for oil backstreaming contamination measurements

Due to the large size and the number of diffusion pumps, space simulation chambers cannot be easily calibrated by the usual test dome method for measuring backstreaming from oil diffusion pumps. In addition, location dependent contamination may be an important parameter of the test. The backstreaming contamination was measured in the Space Power Facility (SPF) near Sandusky, OH, the largest space simulation vacuum test chamber in the U.S.. Small clean silicon wafers placed at all desired measurement sites were used as contamination sensors. The facility used diffusion pumps with DC 705 oil. The thickness of the contamination oil film was measured using ellipsometry. Since the oil did not wet the silicon substrate uniformly, two analysis models were developed to measure the oil film: (1) continuous, homogeneous film; and (2) islands of oil with the islands varying in coverage fraction and height. In both cases, the contamination film refractive index was assumed to be that of DC 705. The second model improved the ellipsometric analysis quality parameter by up to two orders of magnitude, especially for the low coverage cases. Comparison of the two models shows that the continuous film model overestimates the oil volume by less than 50 percent. Absolute numbers for backstreaming are in good agreement with published results for diffusion pumps. Good agreement was also found between the ellipsometric results and measurements done by x-ray photoelectron spectroscopy (XPS) and by scanning electron microscopy (SEM) on examples exposed to the same vacuum runs.

Alterovitz, S. A.↗

DOE OSTI2025

Advancing continuous enzymatic hydrolysis for improved biomass saccharification

Background: A deployable, continuous enzymatic hydrolysis (CEH) process can address cost and commercialization risks associated with second-generation (Gen2) biorefinery sugar/lignin/ethanol production while contributing to energy supply and security. Developments in commercial enzymatic hydrolysis formulations targeting Gen2 pretreated biomass such as deacetylated mechanically refined (DMR) biomass necessitate a reassessment of the existing hybrid simultaneous saccharification and fermentation (SSF) approach. Notably, the practice of "finishing hydrolysis" in SSF has become problematic with the introduction of oxidative enzymes, such as lytic polysaccharide monooxygenases (LPMOs), into commercial cellulase formulations as these require specific redox conditions and cofactor. Moreover, continuous SSF has not been demonstrated at commercial scale, limiting deployment and the associated economic benefits to farmers, producers, and support industries. Results: Continuous enzymatic hydrolysis (CEH) was demonstrated at bench scale to enable optimal saccharification performance of deacetylated mechanically refined (DMR) pretreated biomass. Diafiltration was demonstrated to retain pretreated biomass solids and enzymes for continuous reaction while removing solubilized product sugars in situ. A significant breakthrough afforded by the CEH process is its ability to achieve equivalent endpoint conversions with approximately 50% lower enzyme loading. Yields of glucose and xylose were increased ~ 15% and ~ 4%, respectively, over batch hydrolysis. Unlike SSF using yeast or Zymomonas, CEH allows precise optimization of pH, temperature, oxygen tension, LPMO mediator concentration, and removal of end-product inhibitors. Conclusions: Advanced CEH holds promise as a transformational, process-intensified, and cost-effective method for producing soluble clarified biomass sugars and insoluble lignin-rich streams. Enhancing saccharification performance, optimizing operating parameters, and employing membrane filtration will help overcome existing challenges and enable the efficient production of valuable biomaterials from lignocellulosic biomass.

09 BIOMASS FUELS↗

NASA NTRS1996

High-temperature Strain Sensor and Mounting Development

This report describes Government Work Package Task 29 (GWP29), whose purpose was to develop advanced strain gage technology in support of the National Aerospace Plane (NASP) Program. The focus was on advanced resistance strain gages with a temperature range from room temperature to 2000 F (1095 C) and on methods for reliably attaching these gages to the various materials anticipated for use in the NASP program. Because the NASP program required first-cycle data, the installed gages were not prestabilized or heat treated on the test coupons before first-cycle data were recorded. NASA Lewis Research Center, the lead center for GWP29, continued its development of the palladium-chromium gage; NASA Langley Research Center investigated a new concept gage using Kanthal A1; and the NASA Dryden Flight Research Center chose the well-known BCL-3 iron-chromium-aluminum gage. Each center then tested all three gages. The parameters investigated were apparent strain, drift strain, and gage factor as a function of temperature, plus gage size and survival rate over the test period. Although a significant effort was made to minimize the differences in test equipment between the three test sites (e.g., the same hardware and software were used for final data processing), the center employed different data acquisition systems and furnace configurations so that some inherent differences may be evident in the final results.

Williams, W. Dan↗

NASA NTRSDate not supplied

Thin-Film Embedded Sensors for Battery Health Monitoring

Hybrid or all-electric aircraft are being developed as the next generation of aircraft to both allow new forms of aviation and decrease environmental impact. Since these types of aircraft are based on high-capacity battery technology, safe operation of these batteries becomes increasingly important. In particular, the potential for battery failure due to uncontrolled chemical reactions resulting in thermal runaway, catastrophic failure, and battery fires must be addressed in order for such battery technology to have the level of safety needed for standard aviation implementation. Efforts to ensure battery safety often involve engineering solutions that seek to contain rather than prevent such events by early detection. Such approaches increase the system weight and decrease the power per unit mass provided by the battery system. Existing methods for measuring battery parameters to determine the battery state-of-health are limited. These methods include electrical measurements of the cell current and/or voltage output as well as temperature measurements taken externally on the cell surface. Such external temperature measurements are limited in their ability to provide early warning of impending battery failure. In response, an effort to develop sensors operating internal to battery for health monitoring has been ongoing in the NASA Sensor-based Prognostics to Avoid Runaway Reactions & Catastrophic Ignition (SPARRCI) project. The basic approach associated with this sensor work is the deposition of thin film sensors on the battery separator located between the anode and cathode of the battery. These thin film sensors are then monitored to determine changes in battery parameters and health. Microfabrication techniques are employed to minimize the overall impact of the sensors on battery operation through the implementation of sensors with minimal size, weight, and power consumption. The thickness of the films, which are fabricated through physical vapor deposition (sputtering), are on the order of thousands of angstroms and can have minimal surface area. Thin film sensors for system health management have been implemented for a many decades on complex components for aerospace applications. However, the application of thin films of this type on a battery separator for internal battery monitoring applications has not previously been demonstrated to our knowledge. This paper describes the development of sensors for the internal battery monitoring through the use of thin film sensor technology. Thin metal films were successfully deposited on a battery separator polymer material with good adherence and electrical continuity. Multiple types of sensors have been deposited, as well as lead connections from the sensor to the edge of the separator material. The ability of these thin film sensors immersed in electrolyte to perform multiple types of battery parameter measurements has been demonstrated. For example, a multiparameter sensor system measured multiple properties simultaneously inside of a pouch cell over a wide temperature range. Further, real time measurement of interior temperature changes in a battery pouch cell with an integrated interior temperature sensor was demonstrated. These changes include detecting a fault in the battery (shorting) in situ with rapid response time (less than a minute) corresponding to a more limited response by a temperature sensor mounted externally. Other aspects of monitoring battery health were also explored, such as real-time measurement of simulated dendrite growth/metal deposition by sensor on separator material demonstrated. Future efforts will include improvements in the durability of the sensor structure to allow introduction of the approach into standard battery fabrication techniques. Overall, this work is a step forward in providing a method to prevent catastrophic battery failures and provide a foundation for safer, lighter, and higher energy batteries for the electric aircraft industry.

thin film battery health↗

NASA NTRS1979

Dynamic properties of elastomer cartridge specimens under a rotating load

This paper presents the results of a program of analysis and test to determine the dynamic properties of elastomer cartridges operating under a rotating load. These measured properties were compared to predictions based on results of unidirectional tests with the same elastomer material. The test method for the dynamic stiffness and damping measurements was essentially the same as the Base Excitation Resonant Mass Method. The primary difference is that the exciting force used for these most recent tests was exerted by rotating unbalance in a rotational test rig rather than a shake table. The specimens tested were: two rectangular cross-section, continuous ring cartridges of different cross-section and three cylindrical button cartridges of different button thickness. Tests were performed for strains from about 0.0001 to about 0.01 (double amplitude). Material properties and prediction equations determined from reciprocating tests were used to make numerical predictions of stiffness, damping, and loss coefficient for the test elements, with encouraging results. Strain was shown to be an important parameter in determining these dynamic properties, particularly damping and loss coefficient.

Darlow, M. S.↗

NASA NTRS1993

The use of designed experiments in the process development of continuous propellant mixing

A continuous mix pilot plant was constructed at Aerojet Propulsion Division in Sacramento, California to develop a robust propellant mixing process for the full scale plant that was to be built at the NASA Advanced Solid Rocket Motor facility Yellow Creek, Mississippi. The plant was used to conduct dozens of subsystem and full system mixing tests for evaluation of equipment, processing methods, and control schemes for later use at the production plant. As a culmination to this work, a series of designed experiments were conducted using an eight run Taguchi analysis with four factors at two levels each to determine the primary effect of processing parameters on propellant ballistic and mechanical properties. The factors examined in these runs included the propellant production rate (454 (1000) and 622 kg/hr (1371 Ib/hr)), the product temperature out of the mixer (49 (120) and 63 deg C (145 deg F)), mixer screw speed (75 and 90 rpm), and the deaerator excess capacity (20 and 80 percent). Measured response variables included the uncured and cured density, Crawford Bomb liquid strand burning rates, and selected mechanical properties. The experiment revealed that several of the response variables displayed significant changes from run-to-run with the product temperature being the single most important factor. After concluding this experiment, a twenty-six hour confirmation run was conducted to verify the conclusions reached in the designed experiment. The extended run produced over 12,250 kgs (27,000 lbs) of propellant meeting all of the pre-run targeted properties including density (1.803 g/cc (0.065 lb/in(exp 3)) with a 0.12 percent coefficient of variation (CV) at 25 deg C (77 deg F)), liquid strand burn rate (0.889 cm/s (0.350 in/s) with a 0.69 percent CV at 4210 KPa (610 psig), 15.6 deg C (60 deg F)), nominal maximum stress (828 KPa (120 psig) with a 2.84 percent CV, S&E at 25 deg C (77 deg F), 5.08 cm/min (2 in/min)), strain at nominal maximum (47.4 percent with a 3.96 percent CV), and initial tangent modulus (5349 KPa (775 psig) with a 7.26 percent CV).

Campbell, J. A.↗

NASA NTRSDate not supplied

Joint Acceptance Attenuation Factor of Integrated Pressure with Unsteady Pressure-Sensitive Paint Measurements

The Unsteady Pressure-Sensitive Paint (uPSP) is widely used to measure the surface pressure of scaled models in wind tunnel tests. Compared to the conventional pressure transducers, uPSP has the advantage of high spatial resolution. With multiple high-speed Complementary Metal Oxide Superconductor (CMOS) cameras, the uPSP data collected with the camera pixels are mapped to the surface grid of the scaled model and converted to pressure. The shot noise is the dominant component of the noise in the uPSP measurement. The integrated pressure is usually computed on the grid nodes of a user-defined patch. The effect of shot noise is reduced in the integrated pressure on the patch; however, the measurement of the aerodynamic pressure may also be attenuated by the decorrelation of the flow pressure field being measured. This paper discusses the Joint Acceptance Attenuation Factor (JAAF) of the integrated pressure with uPSP measurements. The JAAF, a function of frequency, is defined as the ratio of the Power Spectral Density (PSD) of the integrated aerodynamic pressure on the patch to the average PSD of the aerodynamic pressure on the grid nodes of the patch. In this paper, the JAAF is investigated for the integrated pressure on rectangular patches, whose edges are defined in the direction along the streamline or across the streamline. Based on the assumption that the surface pressure field can be described by the Corcos model, the closed-form formulas to compute the JAAFs of the integrated pressure on the discrete grid nodes of a rectangular patch and over the continuous area of a rectangular patch are derived respectively. It is shown that the JAAF of the integrated pressure over the continuous area of a rectangular patch is the limit of that on discrete nodes of the rectangular patch when the number of nodes in each row or column goes to infinity. The closed-form formulas of the JAAF derived in this paper, with estimated parameters of the model, are verified with the measurements of the uPSP and the conventional pressure transducer collected in the Space Launch System Ascent Unsteady Aerodynamics Test at NASA Ames Research Center in November 2017. The closed-form formulas of the JAAF of the integrated pressure on the rectangular patches, based on the Corcos model, provide an efficient method to estimate the attenuation of integration by the decorrelation of the flow pressure field and set references for the comparison of the spectrum of the integrated uPSP measurements and the conventional pressure transducer measurements. The work described in this paper is a part of NASA’s development of a new state-of-the-art uPSP capability in production wind tunnels. Funding was provided by the NASA Aerosciences Evaluation and Test Capabilities Portfolio Office.

acoustics↗

NASA NTRSDate not supplied

Joint Acceptance Attenuation Factor of Integrated Pressure with Unsteady Pressure-Sensitive Paint Measurements

acoustics↗

NASA NTRS1994

Investigation of the effects of manufacturing variations and materials on fatigue crack detection methods in gear teeth

The fatigue life of a gear tooth can be thought of as the sum of the number of cycles required to initiate a crack, N(sub i), plus the number of cycles required to propagate the crack to such a length that fracture occurs, N(sub p). The factors that govern crack initiation are thought to be related to localized stress or strain at a point, while propagation of a fatigue crack is a function of the crack tip parameters such as crack shape, stress state, and stress intensity factor. During a test there is no clear transition between initiation and propagation. The mechanisms of initiation and propagation are quite different and modeling them separately produces a higher degree of accuracy, but then the question that continually arises is 'what is a crack?' The total life prediction in a fracture mechanics model presently hinges on the assumption of an initial crack length, and this length can significantly affect the total life prediction. The size of the initial crack is generally taken to be in the range of 0.01 in. to 0.2 in. Several researchers have used various techniques to determine the beginning of the crack propagation stage. Barhorst showed the relationship between dynamic stiffness changes and crack propagation. Acoustic emissions, which are stress waves produced by the sudden movement of stressed materials, have also been successfully used to monitor the growth of cracks in tensile and fatigue specimens. The purpose of this research is to determine whether acoustic emissions can be used to define the beginning of crack propagation in a gear using a single-tooth bending fatigue test.

Wheitner, Jeffrey A.↗

DOE OSTI2025

Machine Learning Prediction of Tritium‐Helium Groundwater Ages in the Central Valley, California, USA

Abstract Groundwater ages provides insight into recharge rates, flow velocities, and vulnerability to contaminants. The ability to predict groundwater ages based on more accessible parameters via Machine Learning (ML) would advance our ability to guide sustainable management of groundwater resources. In this study, ML models were trained and tested on a large data set of tritium concentrations and tritium‐helium groundwater ages from the California Central Valley, a large groundwater basin with complex land use, irrigation, and water management practices. The ML models were trained on 63 features, including location, well construction information, landscape characteristics, and climate variables, water chemistry, and stable isotopes. The Bagging regressor method can accurately classify (F1‐score = 0.91) groundwater samples as either modern or pre‐modern whereas the accuracy of the ML prediction of continuous tritium‐helium groundwater ages is limited and explains only of the variability in this data set. In general, ML groundwater age prediction relies mostly on features related to (a) the source of groundwater recharge, (b) contaminant history, (c) aquifer materials, (d) well construction, and (e) geochemical reactions along flow paths.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Leverage modern artificial intelligence (AI) enabled systems for waste reduction

Manufacturing industries continue to face challenges in reducing waste, as upstream strategies such as source reduction and product redesign require a deeper understanding of processes compared to conventional recycling methods. Recent advancements in artificial intelligence (AI) and machine learning (ML) have opened new opportunities to integrate modern computational techniques with traditional waste minimization strategies. This paper explores AI-enabled approaches for product redesign, source reduction, and recycling that can significantly reduce waste generation while improving efficiency and sustainability. AI-driven material substitution and lightweighting in product design enable discovery of novel materials with optimized properties, reducing waste without compromising performance. Reinforcement learning models optimize process parameters, raw material specifications, and machine sequencing to minimize production losses, while Industrial Internet of Things (IIoT) systems paired with AI analytics enhance real-time waste tracking, predictive maintenance, and quality inspection. Furthermore, AI-based demand forecasting and production planning reduce overproduction and excess inventory, as demonstrated in industrial applications. In recycling, ML-powered pattern recognition and robotic sorting technologies achieve higher accuracy in waste segregation, directly improving recycling efficiency. Complementary solutions such as smart bins and AI-enabled waste pickup scheduling optimize collection logistics, reducing both costs and emissions. Although implementation requires upfront investment in infrastructure and training, the long-term benefits include higher material efficiency, reduced waste, improved product quality, and stronger sustainability outcomes across the supply chain. By leveraging AI-enabled systems, manufacturers can align waste minimization efforts with circular economy principles, creating scalable solutions for both industry and society.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2025

Performance Evaluation of LPBF Manufactured 316H Components

This work represents the continuation of a benchmark study that includes modeling, fabrication and characterization as demonstration to support industry’s adoption of advanced manufacturing processes in a variety of structures. This comprehensive study investigated the feasibility of using additive manufacturing (AM) technologies, specifically Laser Powder Direct Energy Deposition (LP-DED) and Laser Powder Bed Fusion (LPBF), to produce complex nuclear microreactor components using 316H stainless steel. The research focused on manufacturing an expanded elbow pipe component with transitioning sections, which are traditionally difficult and costly to produce through conventional manufacturing methods. The overall study’s primary objectives are therefore demonstrating AM viability for nuclear applications, optimizing process parameters, developing comprehensive material characterization protocols, validating computational modeling approaches, and establishing manufacturing guidelines for complex geometries. Although the initial work included the phased approach of cubical, upscaled cylindrical components, it is to enable to obtain more knowledge for the printing of the expanded elbow structure. The project achieved significant progress in process development by successfully optimizing LP-DED parameters to achieve 99.16-99.97% relative density in 316H stainless steel components. Through systematic evaluation of sixteen cube samples with varied laser powers (400-700W) and scan speeds (600-900 mm/min), optimal processing windows were identified at 500-550W with 600-700 mm/min or 650-700W with 650-900 mm/min scan speeds. The DED manufactured 316H demonstrated mechanical properties comparable or superior to wrought materials, with Young's modulus ranging from 153-208 GPa and controlled microstructural characteristics including greater than 95% face-centered cubic (FCC) phases and engineered cellular structures with sizes between 3.23-6.17 µm.

36 MATERIALS SCIENCE↗

NASA NTRS1990

The dynamics and control of large flexible space structures - 13

The optimal control of three-dimensional large angle maneuvers and vibrations of a Shuttle-mast-reflector system is considered. The nonlinear equations of motion are formulated by using Lagrange's formula, with the mast modeled as a continuous beam subject to three-dimensional deformations. Pontryagin's Maximum Principle is applied to the slewing problem, to derive the necessary conditions for the optimal controls, which are bounded by given saturation levels. The resulting two point boundary value problem is then solved by using the quasilinearization algorithm and the method of particular solutions. The study of the large angle maneuvering of the Shuttle-beam-reflector spacecraft in the plane of a circular earth orbit is extended to consider the effects of the structural offset connection, the axial shortening, and the gravitational torque on the slewing motion. Finally the effect of additional design parameters (such as related to additional payload requirement) on the linear quadratic regulator based design of an orbiting control/structural system is examined.

Bainum, Peter M.↗

DOE OSTI2025

Pilot-Scale Validation of Distributed Optical Fiber Sensors for Underground Pipeline Monitoring

Distributed fiber optic sensing is a cutting-edge technology that has found extensive applications in the monitoring of Ensuring the safety, integrity, and operational efficiency of underground product pipelines is vital for maintaining the nation’s critical infrastructure. Monitoring parameters such as hoop strain, pressure, and acoustic vibrations is key to detecting potential leaks, intrusions, or structural issues. Distributed optical fiber sensor (DOFS) systems provide a compelling solution for continuous, real-time monitoring over long distances. This paper details the development and pilot-scale implementation of DOFS systems for underground pipeline monitoring, evolving from a proof-of-concept stage. Multiple custom-designed DOFS interrogator units—such as optical frequency-domain reflectometry (OFDR), Brillouin optical time-domain analysis (BOTDA), and multimodal interferometer-based fiber acoustic sensors—were employed to measure key parameters like hoop strain, pressure, and acoustic vibrations. The underground product pipeline's outer diameter is 30 inches, the wall thickness is 1.28 inches, and the 3-foot depth. The fiber deployment strategies, and sensing data acquisition methods for these systems are discussed. The results demonstrate the effectiveness of DOFS in detecting hoop strain, temperature changes, and acoustic vibrations, showcasing their potential for real-time monitoring and enhancing pipeline safety.

distributed fiber sensing↗

NASA NTRS1950

Investigation of Power Requirements for Ice Prevention and Cyclical De-Icing of Inlet Guide Vanes with Internal Electric Heaters

An investigation was conducted to determine the electric power requirements necessary for ice protection of inlet guide vanes by continuous heating and by cyclical de-icing. Data are presented to show the effect of ambient-air temperature, liquid-water content, air velocity, heat-on period, and cycle times on the power requirements for these two methods of ice protection. The results showed that for a hypothetical engine using 28 inlet guide vanes under similar icing conditions, cyclical de-icing can provide a total power saving as high as 79 percent over that required for continuous heating. Heat-on periods in the order of 10 seconds with a cycle ratio of about 1:7 resulted in the best over-all performance with respect to total power requirements and aerodynamic losses during the heat-off period. Power requirements reported herein may be reduced by as much as 25 percent by achieving a more uniform surface-temperature distribution. A parameter in terms of engine mass flow, vane size, vane surface temperature, and the icing conditions ahead of the inlet guide vanes.was developed by which an extension of the experimental data to icing conditions and inlet guide vanes, other than those investigated was possible.

VonGlahn, Uwe↗

NASA NTRS2000

Comparative Study in Laboratory Rats to Validate Sperm Quality Methods and Endpoints

Abstract The Naval Health Research Center, Detachment (Toxicology) performs toxicity studies in laboratory animals to characterize the risk of exposure to chemicals of Navy interest. Research was conducted at the Toxicology Detachment at WPAFB, OH in collaboration with Wright State University, Department of Biological Sciences for the validation of new bioassay methods for evaluating reproductive toxicity. The Hamilton Thorne sperm analyzer was used to evaluate sperm damage produced by exposure to a known testicular toxic agent, methoxyacetic acid and by inhalation exposure to JP-8 and JP-5 in laboratory rats. Sperm quality parameters were evaluated (sperm concentration, motility, and morphology) to provide evidence of sperm damage. The Hamilton Thorne sperm analyzer utilizes a DNA specific fluorescent stain (similar to flow cytometry) and digitized optical computer analysis to detect sperm cell damage. The computer assisted sperm analysis (CASA) is a more rapid, robust, predictive and sensitive method for characterizing reproductive toxicity. The results presented in this poster report validation information showing exposure to methoxyacetic acid causes reproductive toxicity and inhalation exposure to JP-8 and JP-5 had no significant effects. The CASA method detects early changes that result in reproductive deficits and these data will be used in a continuing program to characterize the toxicity of chemicals, and combinations of chemicals, of military interest to formulate permissible exposure limits.

Price, W. A.↗

DOE OSTI2025

CoCoMET v1.0: a unified open-source toolkit for atmospheric object tracking and analysis

Advances in performance and analysis capabilities have accelerated the development of object tracking algorithms for atmospheric research. This has resulted in a growing number of studies using Lagrangian tracking techniques to analyze the evolution of atmospheric phenomena and the underlying processes. However, the increasing complexity and variety of tracking algorithms present a steep learning curve for new users and make it difficult for existing users to compare algorithm performance. We introduce CoCoMET (Community Cloud Model Evaluation Toolkit), an open-source toolkit that addresses these issues. CoCoMET simplifies the process of running multiple tracking algorithms simultaneously and analyzing objects in both model and observational datasets by specifying parameters in a single configuration file. It standardizes input data from different sources into a consistent format and unifies the tracking output across algorithms. CoCoMET enhances the functionality of existing tracking methods by calculating additional properties such as cell growth and dissipation rates, perimeter, surface area, convexity, and irregularity. In addition, CoCoMET includes a novel method for identifying mergers and splits in 2D and 3D tracks and supports the integration of Eulerian/stationary datasets external to the tracking data for process studies. Its potential utility is demonstrated through examples of model intercomparison, model evaluation against observations, and comparisons between tracking algorithms. Designed for open-source environments, CoCoMET will continue to expand with future releases, incorporating more input data types and tracking algorithms.

54 ENVIRONMENTAL SCIENCES↗