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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 235 records · Page 13

DEMO-FTES: Development, Monitoring, and Control of Fracture Thermal Energy Storage in Crystalline Rock Formations (CRADA Final Report)

The DEMO-FTES project investigated the feasibility of Fracture Thermal Energy Storage (FTES) as a seasonal energy storage solution in crystalline rock formations. FTES leverages hydraulically induced fractures to exchange heat between circulating fluids and the surrounding rock mass, enabling long-term thermal energy retention due to the high specific heat and low thermal conductivity of rock. This approach has the potential to reduce heating and cooling energy demands and enhance building energy resilience. The project combined dimensional analysis, numerical modeling, laboratory experiments, and meso-scale field tests to evaluate FTES performance and advance its technology readiness level from 3 to 5. Scaling analysis identified key dimensionless parameters governing heat transfer and fluid flow, ensuring laboratory and field tests were representative of larger-scale systems. Numerical simulations using TOUGH and iTOUGH2 frameworks supported experiment design and interpretation, modeling fracture geometry, thermal-hydraulic behavior, and thermo-mechanical coupling. Laboratory tests at EPFL involved creating single and multiple fractures in 25 cm cubic samples of Gabbro and Granite under true triaxial stress.

25 ENERGY STORAGE↗

Deep convolutional autoencoders as generic feature extractors in seismological applications

The idea of using a deep autoencoder to encode seismic waveform features and then use them in different seismological applications is appealing. In this paper, we designed tests to evaluate this idea of using autoencoders as feature extractors for different seismological applications, such as event discrimination (i.e., earthquake vs. noise waveforms, earthquake vs. explosion waveforms), and phase picking. These tests involve training an autoencoder, either undercomplete or overcomplete, on a large amount of earthquake waveforms, and then using the trained encoder as a feature extractor with subsequent application layers (either a fully connected layer, or a convolutional layer plus a fully connected layer) to make the decision. By comparing the performance of these newly designed models against the baseline models trained from scratch, we conclude that the autoencoder feature extractor approach may only outperform the baseline under certain conditions, such as when the target problems require features that are similar to the autoencoder encoded features, when a relatively small amount of training data is available, and when certain model structures and training strategies are utilized. The model structure that works best in all these tests is an overcomplete autoencoder with a convolutional layer and a fully connected layer to make the estimation.

58 GEOSCIENCES↗

Low-Cost, Accessible Vaccine Cooler Options

In response to cold chain management requirements for COVID-19 vaccines, Los Alamos National Laboratory has investigated, built, and demonstrated viability for different cryogenic storage options. With ease-of-access and affordability in mind, these cooler units have been built using commercial off-the-shelf (COTS) components. The team was also able to design a testing method for evaluating the performance of the different vaccine cooler options as part of the Technology Evaluation and Demonstration program. The tested cooler units demonstrated compatibility with either dry ice or liquid nitrogen as the cryogen, along with several commercial solvents. This compatibility demonstration would potentially offer sufficient flexibility for temperature control continuity. Next steps are to investigate industry interest in supporting field testing of the cooler units.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Titanium-Cerium Electrode-Decoupled Redox Flow Batteries Integrated With Fossil Fuel Assets For Load-Following, Long-Duration Energy Storage

Operation of fossil plants at partial capacity with frequent cycling results in decreased efficiency, increased emissions and increased wear and maintenance. The objective of this project is to advance the integration of a titanium-cerium electrode-decoupled redox flow battery (RFB) system with conventional fossil-fueled power plants through technical and economic system-level studies and component scale-up and R&D. The Ti-Ce chemistry has a pathway to meet the DOE cost targets of $\$$100/kWh and $\$$0.05/kWh-cycle owing to the use of low-cost, earth abundant elemental actives and incorporation of inexpensive carbon felt electrodes and non-fluorinated anion exchange membrane (AEM) separators. The initial unit cell design was scaled up, with some modifications made to improve ease of manufacturing, from 25 cm 2 cell area to 400 cm 2 . Electrochemical tests demonstrated operation at a current density up to 50 mA/cm 2 , which is on par with other commercial RFB offerings. Furthermore, the Ti-Ce technology developed by WashU was evaluated and tested by industrial team partner, Giner, Inc., in their modular 3-cell stack. Several cell design modifications and alternate component material selections were successfully implemented to accommodate this chemistry while reducing polarization and leakage. Results from stack testing show high columbic efficiency and indicate that further optimization of cell compression and components will lead to successful operation of the Ti-Ce ED-RFB over longer duration at the multi-cell stack level. Engineering and cost analysis showed that an RFB system with power output on the order of 100 MW and with a charge/discharge duration of approx. 12 hours is the most cost effective for integration with fossil plants. At this scale, projected cycling of fossil fuel power plants can be significantly reduced. The use of a storage system is shown to reduce the fossil plant standalone cost of electricity by $\$$7/MWh, through increased capacity factor and improved average efficiency, in the scenario of high penetration of renewable power.

20 FOSSIL-FUELED POWER PLANTS↗

The outer stellar mass of massive galaxies: a simple tracer of halo mass with scatter comparable to richness and reduced projection effects

ABSTRACT Using the weak gravitational lensing data from the Hyper Suprime-Cam Subaru Strategic Program (HSC survey), we study the potential of different stellar mass estimates in tracing halo mass. We consider galaxies with log10(M⋆/M⊙) > 11.5 at 0.2 < z < 0.5 with carefully measured light profiles, and clusters from the redMaPPer and CAMIRA richness-based algorithms. We devise a method (the ‘Top-N test’) to evaluate the scatter in the halo mass–observable relation for different tracers, and to inter-compare halo mass proxies in four number density bins using stacked galaxy–galaxy lensing profiles. This test reveals three key findings. Stellar masses based on CModel photometry and aperture luminosity within R <30 kpc are poor proxies of halo mass. In contrast, the stellar mass of the outer envelope is an excellent halo mass proxy. The stellar mass within R = [50, 100] kpc, M⋆, [50, 100], has performance comparable to the state-of-the-art richness-based cluster finders at log10Mvir ≳ 14.0 and could be a better halo mass tracer at lower halo masses. Finally, using N-body simulations, we find that the lensing profiles of massive haloes selected by M⋆, [50, 100] are consistent with the expectation for a sample without projection or mis-centring effects. Richness-selected clusters, on the other hand, display an excess at R ∼ 1 Mpc in their lensing profiles, which may suggest a more significant impact from selection biases. These results suggest that M⋆-based tracers have distinct advantages in identifying massive haloes, which could open up new avenues for cluster cosmology. The codes and data used in this work can be found here:

79 ASTRONOMY AND ASTROPHYSICS↗

Feasibility study for test rig assessments of fish passage conditions in a Kaplan turbine

The assessment of fish passage conditions in hydroelectric turbines consists of identifying and quantifying physical magnitudes leading to increased risks of injury of fish passing through turbines in operation. Such assessments are usually carried out either with the use of computer-based methods during design or with field testing of live fish and sensors passing through prototypes. A method in between consists of test rig experimentation, which is critical for testing fish-focused design concepts and offers the opportunity for implementing the most effective design measures for improved fish survivability. However, fish-related assessments in test rigs are not sufficiently documented for industrial applications. This work presents the main findings of an experimental campaign to quantify fish-related hydraulic magnitudes in a physical model of a Kaplan turbine in a commercial test rig. Two operating conditions were tested by releasing miniaturized autonomous sensor devices (termed Sensor Fish Mini) at the turbine intake flow, passing them through the runner in motion and recovering them at the draft tube exit. During passage, time series of acceleration, absolute pressure and rotational velocity were recorded. The recordings were then interpreted to determine the magnitude and likely location of hydraulic stressors hazardous to fish. The statistical tests on the reported measurements indicated that low pressure, collisions on the runner and rotations in the draft tube were not different between the two tested operating points. On the other hand, pressure drop and collision rates on the distributor differed considerably as a function of net head. The outcomes of this investigation showed that test rig evaluations of fish-related properties with Sensor Fish Mini can contribute to an evidence-based development of turbine geometries designed for providing safer passage conditions. Future work will investigate the scaling of test rig measurements to hydraulically equivalent magnitudes in the prototype and their biological consequences.

13 HYDRO ENERGY↗

TEAMER: Biofouling Analysis for Wave Energy Piston Design - Load Cell Data

Biofouling and corrosion are a major concern for all ocean-deployed components, especially when mechanical motion is involved. Triton has developed the concept of a biofouling mitigation seal as part of the piston sealing assembly for the Triton Wave Energy Converter (TSI-WEC). This mitigation seal has the purpose of preventing the formation of a biofilm on the inside of the piston cylinder. It is hypothesized that the prevention of a biofilm will reduce the amount of macro-biofouling that can occur in the piston assembly. The mitigation seal can also reduce the wear on the main dynamic seal, helping to maintain smooth operation and water-tightness. The cylinder is made from a thermoset composite epoxy, which is resistant to corrosion. However, no studies have researched the material's performance with biofouling. Triton placed two prototype Power Take-Off (PTO) assemblies in a PNNL biofouling tank, one with a biofouling mitigation seal and one without, allowing for an evaluation of seal effectiveness at the prevention of biofouling. In actual WEC operation, wave action would react against the piston, which would drive the linear actuator and electric generator, providing electrical power. In the test setup, this was reversed; a linear actuator was powered to drive the piston in a consistent motion within the cylinder. There are two assemblies: one has a biofouling mitigation seal, the other (control) does not. The following data encompasses a 4 month test period, with load cells being used to monitor piston friction force. Results from this testing will be used to improve seal design and material selection, mitigating risk of premature failure during open water testing and evaluation. This project is part of the TEAMER RFTS 3 (request for technical support) program.

16 TIDAL AND WAVE POWER↗

USHPRR MP-1 Irradiation Test: Assessment of Edge Pitting and Bond Line Corrosion in Vendor Produced Fuel Plates

This report summarizes an effort to identify the source of anomalous localized edge pitting and bond line corrosive attack of experimental mini fuel plates manufactured at the commercial fuel vendor BWXT and tested in the Advanced Test Reactor (ATR) at Idaho National Laboratory (INL) as part of the Miniplate 1 (MP-1) irradiation test. The MP-1 test was conducted by the US High Performance Research Reactor Project (USHPRR) and overseen by the Fuel Qualification Pillar (FQ). The test involved evaluation of a mix of 62 “vendor” fuel plates fabricated at BWXT and 12 “laboratory” fuel plates fabricated at Idaho National Laboratory using commercial-scale and labscale fabrication processes respectively. The MP-1 test was the first in a series of tests to generate data to support qualification of a new plate-type low-enriched uranium (LEU) U-10Mo monolithic fuel system. The major objective of the MP-1 experiment was to test, for the first time, miniplates fabricated by a commercial fuel vendor over the range of irradiation conditions relevant to conversion of NRC regulated High Performance Research Reactors (HPRRs) from high-enriched uranium to LEU. The focus of the efforts described in this report are the vendor fuel plates to inform changes in the fabrication process prior to fabrication of the next miniplate experiment MP2.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

An Assessment of Machine Learning Applied to Ultrasonic Nondestructive Evaluation

In the United States, the nuclear industry performs inservice inspection (ISI) through nondestructive examination (NDE) methods in accordance with guidelines specified in the American Society of Mechanical Engineers (ASME) Boiler and Pressure Vessel Code (BPVC), Section XI, Rules for Inservice Inspection of Nuclear Power Plant Components. Ultrasonic nondestructive testing and evaluation (NDT&E) is one of the more commonly used techniques for inspecting Class 1 structural components in nuclear power systems. As the number of qualified NDE inspectors declines, the nuclear industry is looking to take advantage of advances in automation to enhance inspection capabilities. Advances in computational power, cloud-based computing, and machine learning algorithms make automated data analysis possible. Machine learning (ML) has shown huge potential in automated data analyses for ultrasonic NDE in the context of weld inspections.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Evaluation of bifacial module technologies with combined–accelerated stress testing

In view of the increasing interest and market share of bifacial cells and modules, suitable substrates such as glass and transparent backsheets along with ethylene vinyl acetate (EVA) and polyolefin elastomer (POE) encapsulants were examined in combined-accelerated stress testing (C-AST) to evaluate and compare degradation modes. Testing with both monofacial and bifacial cells, we found glass-glass modules with monofacial cells led to greater grid finger breakage than those with polymeric backsheets. Furthermore, this is attributed to previous X-ray topography and modeling work showing higher stress in cells and interconnections in glass-glass modules than glass-backsheet modules. Consistent with the objectives of C-AST, which stresses modules at levels corresponding to the limits seen in the natural environment, we observed the UV-fluorescence signatures of modules tested in C-AST (considering the degradation associated with developing chromophores, moisture penetration and photobleaching effects) to be like those in fielded modules, more so than other chamber stress testing implemented for comparison. We found light-induced degradation (LID) in module types with regenerated (inactive) cells with C-AST, suggesting the possibility of LID destabilization in some field conditions. We could also distinguish potential-induced degradation (PID) on the back of the bifacial passivated emitter and rear cells (PERC) in C-AST. Confirming with ex-situ tests, we found polarization-type PID most prevalent in glass-glass modules with EVA as would be anticipated considering the greater leakage current through such module encapsulation. Unlike PID tests performed in the dark, which can lead to false positive PID test results, field-representative illumination is experienced by the modules on the front and back side while –1200 V system voltage is applied in C-AST, supporting the conclusion that this module type with glass-glass construction would be susceptible to PID in the field.

14 SOLAR ENERGY↗

Predicting the Cetane Number, Yield Sooting Index, Kinematic Viscosity, and Cloud Point for Catalytically Upgraded Pyrolysis Oil Using Artificial Neural Networks

Abstract The conversion of biomass using fast pyrolysis has the potential to be significantly less expensive at scale compared to alternative methods such as fermentation and gasification. Selective upgrading of the products of fast pyrolysis through chemical catalysis produces compounds with lower oxygen content and lower acidity; however, identifying the specific catalytic pathways for producing viable fuels and fuel additives often requires a trial-and-error approach. Specifically, key properties of the compounds must be experimentally tested to evaluate the viability of the resultant compounds. The present work proposes predictive models constructed with artificial neural networks (ANNs) for cetane number (CN), yield sooting index (YSI), kinematic viscosity (KV), and cloud point (CP), with blind test set median absolute errors of 5.14 cetane units, 3.36 yield sooting index units, 0.07 millimeters squared per second, and 4.89 degrees Celsius, respectively. Furthermore, the cetane number, yield sooting index, kinematic viscosity, and cloud point were predicted for over three hundred expected products from the catalytic upgrading of pyrolysis oil. It was discovered that 130 of these compounds have predicted cetane numbers greater than 40, with four of these compounds possessing predicted yield sooting index values significantly less than that of diesel fuel and predicted viscosities and cloud points comparable to that of diesel fuel.

09 BIOMASS FUELS↗

Three-point Analysis for Butler-Volmer Electrochemical Kinetics

This file contains a spreadsheet and equations that evaluate corrosion test data. The data (which can be inserted by the user) is current vs voltage data. This spreadsheet will be part of the supplemental information of a journal article that is under review. Specifically, the spreadsheet evaluates the classical Butler Volmer equation in the presence of several different forms of noise found in electrochemical systems. The forms of noise are: 1) solution resistance, 2) random noise in the current, 3) drift of the open circuit potential voltage.

Cho, Seongkoo [Lawrence Livermore National Laborat↗

A System Engineering Approach in the Analysis of Ionic Liquids Properties [Thesis]

Room temperature ionic liquids (RTIL) are ionic compounds, comprised of a cation and anion, in the liquid state at temperatures below 100 ⁰C. There are estimated 10 18 anion and cation combinations, which can create RTILs with unique properties. While the ionic character of RTILs made them attractive in a wide variety of electrochemical applications, their behaviors under electrochemical conditions are not well understood. In this research, we developed a RTIL testbed to investigate how RTILs differ from molecular solvents and electrolytes in electrochemical systems through the study of the effects of their morphology and chemical properties on the electron transfer processes. The test bed is composed of three modules: Electrochemistry, Material characterization, Computational. All modules have been completely developed, verified, and integrated and two of them, i.e., Electrochemistry and Material characterization have been validated in this dissertation. To evaluate the proposed system, experiments were performed on solutions of a redox active species in RTILs. It was found that it is possible to investigate the RTIL's morphology and chemical properties' impact on the electron transfer processes of the solute based on the outcomes and evaluations of tests performed by the RTIL testbed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

CGSim: A Simulation Framework for Large Scale Distributed Computing Environment

Large-scale distributed computing infrastructures such as the Worldwide LHC Computing Grid (WLCG) require comprehensive simulation tools for evaluating performance, testing new algorithms, and optimizing resource allocation strategies. However, existing simulators suffer from limited scalability, hardwired algorithms, lack of real-time monitoring, and inability to generate datasets suitable for modern machine learning approaches. We present CGSim, a simulation framework for large-scale distributed computing environments that addresses these limitations. Built upon the validated SimGrid simulation framework, CGSim provides high-level abstractions for modeling heterogeneous grid environments while maintaining accuracy and scalability. Key features include a modular plugin mechanism for testing custom workflow scheduling and data movement policies, interactive real-time visualization dashboards, and automatic generation of event-level datasets suitable for AI-assisted performance modeling. We demonstrate CGSim’s capabilities through a comprehensive evaluation using production ATLAS PanDA workloads, showing significant calibration accuracy improvements across WLCG computing sites. Scalability experiments show near-linear scaling for multi-site simulations, with distributed workloads achieving 6 × better performance compared to single-site execution. The framework enables researchers to simulate WLCG-scale infrastructures with hundreds of sites and thousands of concurrent jobs within practical time budget constraints on commodity hardware.

Vatsavai, Sairam Sri [Brookhaven National Laborato↗

A Data-Driven Method for Synthetic Extreme Weather Generation and Solar Impact Assessment: Preprint

High-resolution, high-fidelity weather datasets are essential for testing and evaluating the resilience of power systems, particularly under extreme weather conditions. However, existing extreme weather datasets are typically derived from historical events that are localized and may lack the spatial and temporal resolution or scenario diversity needed to test largescale power systems. In this work, we propose a synthetic extreme weather simulation approach capable of generating targeted extreme events, such as hurricanes, using publicly available data sources. Preliminary results demonstrate the impact of a simulated Category 1 hurricane on renewable generation and critical infrastructure in California. The work aims to provide a flexible approach for creating multiple types of extreme weather scenarios across different regions, enabling comprehensive system stress testing, training, and resilience assessment.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Post-irradiation examination of legacy high burnup fuel to support safety testing

Safety/transient testing to evaluate performance under off-normal conditions is an essential pillar for both the development of Accident Tolerant Fuels (ATF) and the optimization of fuel operation economics beyond current discharge burnups. Among other factors, the successful interpretation of the transient testing results relies upon the knowledge of the initial conditions of the test, including the characteristics of the fuel system under scrutiny. When testing pre-irradiated material, the assumptions that the fuel and the cladding still have the same properties as in the pre-irradiation stage is obviously wrong and could affect the results of the test. This is particularly true the more burnup accumulates in the fuel rod and irradiation progresses. The knowledge of the initial microstructure of both fuel and cladding allows a clearer interpretation of the subsequent transient testing results, provides validation of the physical phenomena underlying the model predictions and eliminates the uncertainties related to the limited knowledge of the sample status before the test. One example is the phenomenon of fine fragmentation that occurs in Light Water reactor (LWR) fuel. During a Loss of Coolant Accident (LOCA) or Reactivity Initiated Transient (RIA) the fuel can severely fragment. During LOCA, high burnup fuel tend to finely fragment, which has raised safety concerns due to the increased likelihood of dispersal of such small particles once the cladding has burst and due to the increased fission gas release. Therefore, efforts have been devoted to the assessment of a pulverization threshold that could determine the conditions under which fine fragmentation is predominant. However, the lack of information regarding the initial conditions of the fuel, and the connections between those conditions and the pre-transient irradiation history, have hindered the development of a fully mechanistic fragmentation and pulverization criterion. The empirical relationships rely on conservative estimations, due to the lack of information on critical material properties and characteristics. More generally, experimental evidence of the irradiation-induced modifications at microstructural scale are necessary to determine the behavior of the material at the macroscopic scale, with the latter being the one of technological interest. Significant progress has been made in the last two decades in the developments of analytical materials science techniques that can be applied to highly radioactive materials, such as high burnup fuels. The availability of new techniques and the improvement of existing ones has enabled investigations previously not possible that can deepen the understanding of the fuel characteristics and properties at high burnup. The better knowledge of material behavior and irradiation-induced phenomena could help the prediction of its performance. In this context, the scope of the present work is to apply a wide portfolio of advanced characterization techniques to determine properties that are relevant for safety and performance. The results are interpreted in the context of engineering scale post-irradiation examinations and available information on the irradiation conditions.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Submersible Multistage Centrifugal Pump for Versatile Test Reactor Cartridge Test Loop

Submersible multistage centrifugal pumps are ideal for pumping in narrow confined spaces and achieving necessary head pressures and flow rates. Once a diameter is determined then manipulation of the number of stages and motor speed are all that are required to meet desired flow conditions. The Versatile Test Reactor (VTR) closed loop cartridge systems will need forced convection cooling independent of the main reactor. A multistage centrifugal pump can meet the necessary flow rates and pumping pressures while minimizing space taken. The pump considered for this work was based off a deep well submersible pump, a variation of a multistage centrifugal pump. We experimented with two pump sizes, 5 cm (2 inch) and 7.5 cm (3 inch) diameters. These diameters were chosen to fit into the inner diameter of standard 5 and 7.5 (2 and 3 inch) Schedule 40 pipe, respectively. This made the design for the test loop both simpler and less expensive as the need for an engineered pump housing was eliminated. Initial test cartridge planning indicated space for only a 5 cm (2 inch) diameter pump, though early testing of this size showed the need for an abnormally high-speed and high-power motor. Fine tuning of the cartridge design allowed a pump size increase to 7.5 cm (3 inches), which was the pump size most extensively tested in this work. The test loop is composed of various sizes of PVC and aluminum piping components in a loop configuration. The pump is driven by a Pittman 250 W (1/3 horsepower) electric motor with maximum speed of 3,450 RPM. Testing consisted of running the pump at a constant motor speed while varying a control valve to restrict flow through the loop, with differential pressure and flow rate recorded. This was done for one and two stage configurations for the 5 cm (2 inch) diameter impeller design and one, two, and three stage configurations for the 7.5 cm (3 inch diameter) impeller design, respectively. Due to pumping power requirements, two and three stage 7.5 cm (3 inch) diameter impeller testing at higher flowrates lowered the motor speed substantially. In regions where motor speed could not be maintained constant, the data were discarded. The test loop was also reconfigured to allow for the pump to be tested for pressure drop in a stalled or inoperable (0 RPM) flow condition. Demonstration of adequate natural convection cooling of the test cartridge fuel type is necessary under accident conditions, and this will depend upon the flow resistance through the impeller assembly when the pump is not operating. Thus, accurate knowledge of the effective impeller assembly loss coefficient is important for safety evaluations. The test loop was modified to provide water inlet and outlets on either side of the pump impeller stack, and a metered flow of lab water was provided in order to measure the pressure drop across the cartridges as a function of flowrate. Data from the pump head curve testing developed as part of this work and supported by analysis using pump head affinity laws indicates that a three stage 7.5 cm (3 inch) pump impeller design will meet target requirements for coolant flow within the VTR cartridge sodium cartridge at full power conditions [1] with margin; this corresponds to a flowrate of 45 l/min (12 gpm) at a pressure drop of 6.1 m (20 feet) of water head. The results of the pressure loss measurements across the impeller assembly when the pump is stationary (i.e., at 0 RPM) indicate that the pressure loss coefficient is 0.921 for a two impeller stack configuration; this value is calculated based on the flow velocity through the minimum available flow area within a single stage of the impeller which corresponds to 1.4 cm2.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

A comparative study of multimodal data fusion strategies for planetary spectroscopy

Integrating heterogeneous data sources can improve scientific inference when different modalities capture complementary information, but doing so is challenging in high-dimensional, small-sample settings. In spectroscopy for planetary exploration, Laser-Induced Breakdown Spectroscopy (LIBS), Raman Spectroscopy (Raman), Visible Infrared Spectroscopy (VISIR), and Mid-Infrared Spectroscopy (MIR) each examine different aspects of composition and mineralogy, raising fundamental questions about when and how data fusion improves predictive performance. Using a Mars-relevant set of geologic standards with measurements from all four modalities, we present a rigorous systematic evaluation of four data fusion strategies: low-level (data) fusion, mid-level (feature) fusion, high-level (decision) fusion, and residual-boosting (sequential) fusion. We assess performance in predicting oxide composition via nested cross-validation and corrected significance testing to evaluate whether data fusion improves upon single-modality baselines. We show that data fusion does not uniformly improve accuracy, and that observed gains are modest, oxide-dependent, and sensitive to modality and model structure. To move beyond aggregate accuracy metrics, we use model coefficients, permutation importance, and residual gain analysis to examine how the fusion models weight individual modalities and to identify patterns of apparent complementarity or redundancy. Though focused on spectroscopy for planetary exploration, our framework for data fusion evaluation and interpretation extends to other scientific domains with heterogeneous and scarce data and provides a principled approach evaluating data fusion strategies, interpreting modality contributions, and understanding tradeoffs among data fusion strategies.

97 MATHEMATICS AND COMPUTING↗