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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

Radiation-induced bowing of SiC/SiC composites under neutron flux gradients—integral experimental data for model validation

Here, the radiation-induced swelling of SiC and its composites, including strong dependencies on temperature and dose, can drive significant lateral bowing in the presence of temperature and/or dose gradients. In recent years, simulations have been performed to assess the extent of bowing in SiC composite light-water reactor (LWR) fuel cladding and boiling water reactor (BWR) channel boxes. However, to date, no integral experimental data exist to validate these models. This work provides the first experimental bowing evaluation of three ∼380 mm long SiC composite specimens irradiated under varying neutron dose gradients (∼50°C–60°C, 0.03–0.06 dpa): two tubes (∼9.8 mm diameter) and a miniature BWR channel box (∼30 mm square). The measured radiation-induced length swelling (∼0.3%–0.7% linear) was consistently 10%–21% higher than values obtained from 3D finite element structural analyses with inputs from 3D radiation transport calculations. This discrepancy could be at least partially explained by differences in dose rate (∼10 -8 dpa/s) compared to the literature data (∼10-6 dpa/s) used to establish the dose-to-swelling correlations in the model. Nevertheless, the modeled bowing magnitudes (<2 mm) obtained from finite element analyses and simple analytical equations were within the bounds of the experimental measurements for all specimens. With improved confidence in the ability to predict the structural response and measure the macroscopic deformations, future experiments will target transient bowing under neutron flux gradients at representative LWR temperatures and assess whether grid spacers can mitigate the tens of millimeters of bowing that would otherwise be expected in ∼4 m long LWR components.

bowing↗

Design, Analysis, and Experimental Testing of Hydrogen Lean Direct Injection Nozzles at Elevated Pressure

Abstract There are many challenges of commissioning a hydrogen combustor into future gas turbine engines; especially regarding achieving emissions goals. Previously, Escudero et al. and Tran et al. conducted a study to adapt the liquid fuel Lean Direct Injection (LDI) concept from Jet-A to gaseous natural gas-hydrogen blends and pure hydrogen [1], [2]. Experimental data was collected at atmospheric conditions using a Box Behnken design of experiments. The design of experiments suggested that biasing the air split in favor of the inner air circuit and increasing the swirl strength of this inner air passage resulted in improved NOx emissions, while the inverse was true for stability, which was quantified by studying the lean blowoff point (LBO) [1], [2]. The trends revealed by the original experiment [1], [2] provided a design direction for further iterations of the experimental hardware. The study presented herein describes the further investigation of such LDI injectors through experimental methods and computational fluid dynamic (CFD) simulations at atmospheric conditions, which were used to identify potential flow behaviors driving enhanced emissions performance. Further evaluation of select injectors from both studies was then conducted at elevated pressures up to 6 atmospheres. The results from both experiments are presented in this study, which include flame observations, emissions measurements, and operational challenges. NOx emissions results are reported on a volume basis in ppmvd corrected to 15% O2 and corrected for fuel. A predictive model for relating NOx emissions to test conditions at atmospheric conditions show high significance to adiabatic flame temperature while little to no significance to fuel composition for the best performing configurations. The results illustrate the connection between atmospheric testing and testing elevated pressures. The design direction indicated by the initial tests and CFD results in promising configurations for implementation into a Multi-point LDI array.

08 HYDROGEN↗

Towards a NEAMS-based high-fidelity model of the MARVEL reactor

This report outlines the progress of Idaho National Laboratory in developing a high-fidelity and high-resolution model of the Microreactor Applications Research Validation and Evaluation reactor. The model was developed under the Nuclear Energy Advanced Modeling and Simulation microreactor application driver at Idaho National Laboratory. The overarching objective of this activity is the development of a high-fidelity multiphysics MARVEL model using NEAMS tools, and to verify and validate NEAMS tools against MARVEL reference simulation and experimental data, respectively. This is a unique opportunity to conduct multiphysics analysis on a soon-to-be-deployed microreactor. This multiphysics model developed under the NEAMS-funded INL microreactor application driver leverages three single-physics models coupled via the MOOSE’s MultiApp and Transfer systems. The latter systems enable in-memory data transfer between MOOSE-based and MOOSE-wrapped applications. The first single-physics model, that functions as main application, leverages Griffin to model the neutron transport in the core through the discontinuous finite element (DFEM) discrete ordinates solver (SN). Several optimization flags that were developed by the Griffin developer team were beta-tested to enhance the solver’s performance. These include the combined use of using_average_xs and update_averaged_xs_on that enable to avoid expensive on-the-fly cross sections evaluations at each linear iterations in favor of evaluations of the macroscopic cross sections at each Picard iteration. The second single-physics model uses BISON to handle solid heat transfer and asymptotic hydrogen redistribution analysis in the fuel. While the model returns consistent results for the temperature and hydrogen distribution in the fuel, a mismatch was noticed in the calculated temperature in the reflector due to the value of the gap conductance used in our model. Ongoing investigations are being performed to assess the origin of this discrepancy. Finally, the System Analysis Module (SAM) was used to model the flow of the sodium-potassium eutectic in the primary loop. A first verification was also performed showing good agreement in terms of mass flow rate and inlet temperature. All mesh files were generated using the MOOSE Reactor module, removing the need for external meshing tools. Notably, this workscope represents one of the initial applications of the MOOSE Reactor module for modeling highly irregular geometries. The use of the reactor module significantly streamlined the mesh generation process. The full multiphysics mode, that combines all the single physics models, was leveraged to conduct initial steady-state multiphysics simulations to compute power, and temperature distribution in the reactor. Initial testing was performed for transient simulations as well. In this case, the new checkpoint restart capability for eigenvalue calculations was tested showing the capability for streamlined restart of transient calculations. Future work will focus on improving the fidelity of the model by performing comprehensive code-to-code comparisons. For instance, the full-core Griffin neutronics model will be benchmarked against MCNP reference results, that were provided by the MARVEL design team. Additionally, the SAM T/H model will be verified against reference RELAP-5 results for selected accident scenarios. Besides code-to-code verification exercises, the model fidelity will be improved by replacing the single-channel SAM model with a more complex SAM-Pronghorn coupled model, in which the sub-channel capability is deployed to obtain radial temperature resolution in the coolant. This model will be developed in synergy with the NEAMS thermal hydraulics team.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Scalability analysis of heavy-duty gas turbines using data-driven machine learning

With the increasing integration of variable renewable energy sources into power systems, the role of flexible power generation technologies like gas turbines (GT) in rapid grid balancing remains crucial. This sustained importance underscores the need for scaled and precise modeling of GT to ensure effective integration within evolving energy frameworks. While physics-driven GT models integrate thermodynamics, fluid dynamics, and combustion principles, they often rely on approximate mathematical representations to accommodate scaling that may not capture the actual complex dynamics for GTs and inertial effects associated to GTs with different ratings. In this study, a data-driven model is proposed using machine learning (ML) techniques to conduct GT scalability analysis and performance evaluation with high accuracy. The ML model, trained on data from various operating conditions and performance parameters, aims to uncover intricate relationships and patterns, resembling GT characteristics at different scales (ratings). The model is developed to capture complex system interaction and to adapt to changing operational scenarios at different capacities, providing valuable insights of power system dynamics. In this study, the real-time digital simulator platform was employed to generate training data for the ML model and assess its dynamic characteristics. The ultimate objective was to develop a detailed modeling framework based on governing equations and data-driven ML capable of predicting key performance indicators, in thermal systems such as GTs, including power output, speed, fuel consumption, and exhaust temperature under diverse operating conditions at different scales. The developed ML framework demonstrated high accuracy, with mean relative errors for GT power prediction, reference speed, exhaust temperature, and compressor pressure ratio (CPR) parameters consistently below 0.1% across typical load fluctuation scenarios. Maximum deviations were limited to approximately 0.5 K for exhaust temperature and 0.009 for CPR, underscoring the model’s ability to replicating dynamic GT behavior with high precision. The adaptability of the ML model enables its application across diverse operational conditions and its extension to other thermal systems. By leveraging advanced ML techniques, this study presents a robust and scalable modeling framework that enhances GT simulation precision, facilitating improved integration into evolving power systems.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Prediction of The TREAT Facility Power and Temperature of Sirius-2c Nuclear Propulsion Fuel Experiment

This paper presents simulation results of the Sirius-2c full power experiment that was performed at the TREAT facility to support experiment modeling and transient analysis of the NASA-sponsored Sirius series of experiments for nuclear thermal propulsion applications. We presents a novel approach to predict the control rod motion and power of the reactor and the temperature of the specimen during transient experiments using the Griffin and Bison packages of the Multiphysics Object Oriented Simulation Environment (MOOSE). First, the model predicts the transient rod motion that results in the desired reactor power shape. Then, the temperature of the specimen is predicted based on the power deposited in the specimen. The prediction results are in good agreement with the measured reactor power and control rod position and over-predicted the specimen temperature which is mainly related to specimen surface emissivities. The reactor reaches a peak power of 80 MW and a specimen temperature of 2500 K and considering the right specimen emissivities the predicted temperature is in an excellent agreement with the measured values. This model can be utilized in helping and supporting the design and optimization a new experiments that are going to be irradiated in the TREAT facility.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

X501 Experiment Simulation and PIE Data Comparison

Fuel performance simulations have been developed for X501 MA bearing fuel in BISON. The results of these simulations are compared with PIE results to assess the applicability of metallic fuel models in BISON to MA bearing metallic fuel.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

3D TRISO particle-explicit compact meshing

The TRI-structural ISOtropic (TRISO) layered fuel particle is a robust nuclear fuel form offering enhanced safety and performance for advanced reactor concepts, including high-temperature gas-cooled reactors and other Generation IV designs. These poppy-seed-sized particles are embedded in a graphite matrix to form fuel elements that must withstand elevated temperatures and high burn-up levels. The heterogeneous nature of these fuel elements — comprising thousands of randomly distributed TRISO particles — produces complex stress fields and thermal gradients that one- and two-dimensional models cannot accurately capture. While three-dimensional modeling has improved predictions of dimensional changes, internal pressure buildup, and fission product transport under irradiation, current approaches rely on homogenized material properties that are known to have considerable divergence from experimental observations. This work presents a methodology for optimized random packing of TRISO fuel compacts and full three-dimensional mesh generation within the BISON fuel performance code, with each particle coating layer individually discretized. The resulting mesh was demonstrated through heat conduction simulations under representative in-reactor operating conditions, showing strong agreement with expected behavior. This capability enables detailed analysis of particle-to-particle interactions, matrix cracking mechanisms, and the statistical distribution of coating layer failures — all of which directly govern fuel performance and safety margins.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Serpent - Bison - THM Preliminary Multiphysics Modeling of a Nuclear Thermal Propulsion System Fuel Assembly

This work demonstrates the Monte Carlo neutronic and Thermo-Hydraulic coupling scheme using the Serpent code and MOOSE application Bison and Thermo Hydraulic Module. The coupling scheme is then applied to the reference BWX Technologies Nuclear Ther- mal Propulsion system at he fuel assembly level where it’s used to perform an analysis of the isothermal material coefficients and potential material reactivity worth. A method is developed to isolate which feedback effects should be considered for proceeding with reduced order deterministic neutronic modeling where branch off analysis must be con- ducted. The convergence behavior of the coupling scheme is demonstrated where it fol- lows the standard Picard iteration approach. Verification studies for the method of deduc- ing relevant feedback effects is also demonstrated.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗

Hydrogen Infrastructure Analysis for the Port Applications [Slides]

The International Maritime Organization has committed to 50% reduction in GHG emissions by 2050 worldwide as of 2023. This analysis includes performing an inventory and modeling efforts to understand the energy, equipment and cost requirements to support decarbonization of cargo handling and shore power at U.S. Ports, along with assessment of zero- and near- zero emission fuel supplies at or near U.S. ports focused upon Hydrogen technologies. Initial market assessment for ocean going vessels for harbor support and ocean-going vessels is explored. An energy analysis is performed on the port system using a holistic approach and considering the port as an entire ecosystem that functions as a transportation and energy node. Presently, a comprehensive view is lacking for future analysis efforts, this analysis seeks to address this gap in data by evaluating four representative port types and the potential for utilizing hydrogen for the maritime industry. Every port is different, but broadly they could be bracketed into reference cases with scaling factors for the relative size of the port operations. These reference ports are for future use, potentially as baselines for analysis and development of demonstration programs. An equipment inventory for each reference port type (container, bulk, breakbulk, and inland waterway) is presented. A comparative analysis of fuel cell electric and battery electric equipment is conducted based on the following criteria: technology readiness level, refueling/charging time, operational range, energy consumption, and fuel cost savings compared to baseline internal combustion engine equipment. The tradeoffs and synergies between two alternative powertrains is highlighted. Based on energy and infrastructure analysis, average and high equipment utilization profiles across different port types is identified and quantified baseline fuel and electricity demand for various decarbonization scenarios. Based on the portfolio of equipment converted to fuel cell electric, the estimates of initial capital investment are provided for hydrogen refueling stations across ports. An energy demand model is developed that predicts well the all-electric cargo handling equipment annual energy consumption for ports with annual tonnage under 2 million twenty-foot equivalent units (TEUs). The model is a good rubric to follow for further energy demand models that can create a scalable solution to understand the energy needs of cargo handling equipment, whether they are all-electric, hydrogen fuel cell, or powered by another fuel-type. Zero and near-zero emission fuel supply at ports is evaluated looking into the characteristics of hydrogen, ammonia, and methanol as an alternative fuel, as well as the bunkering status. The readiness of reference ports to produce ammonia or methanol and bunker the fuel is examined based on the framework developed by the Global Maritime Forum and Rocky Mountain Institute.

08 HYDROGEN↗

As-Run Neutronic Calculations of HFIR Mini-Fuel Experiments: Guidelines for Analysts

This report provides guidelines for analysts performing radiation transport calculations for mini-fuel experiments irradiated in the High Flux Isotope Reactor (HFIR). Procedures, practical recommendations, and modeling conventions which are essential to ensuring consistency and high fidelity in as-run simulations have been compiled. The content is intended to be a portion of the official training material for new staff in this area, offering both technical references and practical guidance derived from previous experience. This report is a living document and will be periodically updated to incorporate new developments, methodological improvements, and lessons learned from ongoing and future irradiation campaigns.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Design of a High-Pressure Fuel System for Use with Dimethyl Ether

The paper documents the modeling and experimental work on a common rail fuel injection system for Dimethyl Ether, a potential diesel substitute with a low carbon intensity signature. The DME fuel system is deployed on a light duty 2.2L compression ignition engine. The paper describes the injector optimization to shift to higher flows to account for the lower heating value and density of the DME when compared to diesel. The type of the injection system used for the DME application is an advanced rendering of the Common rail noted for a one-piece piston-needle injector construction and a solenoid driven spill valve featuring a pressure balanced poppet. A dedicated high-pressure fuel pump designed to pressurize DME is used. The design results in a fast acting open and close injection event, reduced leakage, with reduced cavitation in the fuel injector volume. Design parameters for system optimization included fill and spill orifices, needle lift, bias spring, and injector hole size. The design model provides good correlation of the instantaneous rates of injection with experiments across a wide range of pressure and injection timings. Proposed performance milestones for the design included similar DME injection duration to the diesel counterpart for same fuel energy injected into the cylinder to retain high engine cycle efficiency. Here, the dedicated DME design provided reduced hydraulic delays of 50%. Tests demonstrated sustained operation at pressures of 1000 bar, with capability to reach 1500bar. Durability tests showed no cavitation-deterioration over a 200-hour test cycle by means of spray imaging and hardware inspection.

De Ojeda, William [WM International Engineering, L↗

Source term analysis of FeCrAl accident tolerant fuel using MELCOR

It has been established that incremental improvements in beyond design basis accident performance can be achieved through accident tolerant fuel (ATF). However, they have the potential to recover margin with respect to conventional fuel and therefore enhance plant economics through uprate or cycle length increase. To realize this potential, it is necessary to quantify the reduction in source term due to use of ATF, and correspondingly how this is affected by increasing the cycle length and/or burnup. This requires development of a risk informed analysis methodology for ATF under high burnup conditions, which is being developed within LWRS. To this end, a MELCOR simulation of FeCrAl ATF in a recovered Large Break LOCA (LBLOCA) scenario has been developed, using a model based on the Zion Pressurized Water Reactor (PWR). The new user defined material capability, along with the inclusion of detailed neutronics- and depletion-derived parameters such as core power distribution, decay heat behavior, and fission product inventories, allows a more detailed simulation of FeCrAl clad material properties and behavior than has previously been possible using MELCOR. These detailed FeCrAl results were compared with a zircaloy clad model to investigate the differences between the two clad types and quantify the benefits of FeCrAl ATF with an 18-month cycle. Next, the fuel cycle with ATF was extended to 24 months, to determine whether any additional safety margin provided by FeCrAl ATF could be leveraged to implement high burnup FeCrAl-clad fuel while retaining the same operating and safety limits as current zircaloy-clad fuel. For the particular scenario analyzed, the delay to fuel failure from using ATF was of the same order as the LOCA recovery time, and hence significant in reducing fission product release, with the 24-month FeCrAl core performing better than the 18-month zircaloy core. It is noted that for other transients, the reduction in release due to using FeCrAl may be less significant. Furthermore, the material model developed here can be used in such further studies in support of determining the overall source term.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Boron and lithium aqueous thermochemistry to model crud deposition in pressurized water reactors

Here, a comprehensive database of boron and lithium aqueous thermochemistry has been developed for use at elevated temperatures. The Helgeson-Kirkham-Flowers (HKF) formalism provides a framework to describe thermodynamic properties over a broad range of temperatures and pressures. Accuracy at high temperatures is vital to modeling nickel oxide and ferrite fuel deposits that occur in pressurized water nuclear reactors (PWRs). CALPHAD (CALculation of PHAse Diagrams) calculations are performed at PWR crud conditions to predict the stability regions of the solid lithium metaborate (LiBO 2 ) and lithium tetraborate (Li 2 B 4 O 7 ) precipitates. In addition, similar calculations are performed using sodium and potassium instead of lithium in order to assess the thermodynamics associated with preventing the formation of such precipitates. This database contributes to understanding of crud formation and composition and will aid in the prediction of phenomena such as Crud-Induced Power Shifts (CIPS).

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Demonstration and technoeconomic analysis of dodecanol production from acetate using metabolically engineered Escherichia coli

In a circular bioeconomy, the one-way conversion of petroleum to chemicals and CO 2 is replaced with processes that reduce CO 2 to energy carriers and useful materials that are returned to CO 2 upon combustion. A circular bioeconomy that relies on photosynthesis to generate sugars as the chief energy carrier and precursor to chemical building blocks has yet to overcome many recalcitrant aspects of plant-based photosynthesis, namely, high feedstock costs, arable land scarcity, food competition, and fertilizer overuse. Acetate is a potential sustainable energy carrier because it can be produced from CO 2 either electrocatalytically or by acetogens via the Wood-Ljungdahl pathway. Here, in this work, we conducted a metabolic engineering study of Escherichia coli 's ability to convert acetate into dodecanol as a model oleochemical product. We performed techno-economic and life cycle analyses to determine break-even points with alternative fossil fuel-based strategies and identified critical process performance parameters for supporting an industrial acetate-based bioprocess. These analyses showed that oleochemical yield is the primary driver of minimum oleochemical selling price and carbon intensity. Therefore, to increase yield on acetate, we deleted the aceBAK operon, which facilitates funneling of acetate into biomass instead of product. We performed additional strain engineering to increase flux towards dodecanol and increase acetate uptake. Finally, we demonstrated increased yield in controlled bioreactors, improving from 13% of the maximum theoretical yield to 37%. Rigorous uncertainty analyses assuming a range of market conditions and future technological performances resulted in 88% and 37% of simulated scenarios having lower carbon intensities than fossil fuel-based routes and lower minimum selling prices than the market price.

Acetate↗

Criticality Analysis of FSV Spent Nuclear Fuel in the DOE Standard Canister

The U.S. Department of Energy (DOE) is responsible for managing over 300 types of spent nuclear fuel (SNF). To manage this large variety of fuel types, DOE plans to employ standardized canisters for the transportation, long-term storage, and eventual disposal of SNF. Idaho National Laboratory is currently supporting DOE’s SNF Packaging Demonstration Project, in which Fort Saint Vrain (FSV) fuel assemblies will be loaded into a DOE Standard Canister. This paper presents criticality calculations demonstrating that all four or five FSV fuel assemblies loaded into the DOE Standard Canister will remain subcritical in any expected normal or credible abnormal conditions. Previous criticality analyses were performed for one FSV fuel assembly and 12 Peach Bottom Core 2 fuel elements loaded into a DOE Standard Canister. This paper covers the criticality analysis performed for loading both four and five FSV fuel assemblies into a DOE Standard Canister. Various intact and degraded mode configurations were modeled in conducting the criticality calculations. This analysis encompassed three different configurations: (1) a single DOE Standard Canister loaded into a concrete storage overpack, (2) seven DOE Standard Canisters loaded into a concrete storage overpack, and (3) nine DOE Standard Canisters loaded into a concrete storage overpack. The overpack dimensions were varied for each of the three configurations, and transport, storage, and disposal scenarios were analyzed for each configuration. For transport scenarios, a pair of degradation cases was analyzed. In the first case, the fuel compacts became degraded and were removed from the fuel block, then deposited at the bottom of a horizontally placed canister, thereby simulating a drop event. The canister was considered to remain intact. In the second case, the spacing between horizontally placed canisters in a nine-canister overpack was reduced such that the canisters were piled on top of each other, simulating a drop event. For this case, no degradation of the canister internals or fuel was considered. For storage scenarios, the water moderator location in the system was varied to enable identification of the most reactive configurations. Dry and wet conditions were analyzed for the fuel materials, canister, and overpack. For disposal scenarios, two degradation cases were analyzed. In the first, the stainless-steel internals of the canister degraded to either hematite or goethite under both dry and wet conditions. In the second case, degraded FSV fuel formed a uranium-water slurry that filled the coolant/void holes. None of the cases presented exceeded the application specific upper subcritical limit.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Preliminary Modeling of Triply Periodic Minimal Surface (TPMS) Structures with RELAP5-3D

This poster goes over preliminary work performed on modeling triply periodic minimal surfaces (TPMS) with RELAP5-3D. The poster starts off with the need for advanced nuclear fuel designs for future reactors, and how TPMS are being researched for this purpose. There is then a focus on what a TPMS is and then moves onto the motivation for why this geometry is being modeled and looked into. The methodology is then shown for how data from different experiments will be used for pre-test predictions and eventual creation of empirical coefficients and multipliers to be used in models. Then there is a show of how data would be compared between the experimental tests, CFD, and RELAP5-3D values. The results from the simulations and comparisons are then presented to show how the CFD and RELAP5-3D compare to each other currently, with no experimental data to compare to for one test model. Results from the second test model are also presented to show that there is stability in the solving of that model.

42 - ENGINEERING↗

Capability Enhancements for System-level thermal Hydraulic Modeling of Lead Fast Reactors

This project has focused on the use, assessment, and development of the SAS4A/SASSYS-1 (SAS) safety analysis software. Although SAS was originally intended as a safety analysis tool for Liquid Metal cooled Fast Reactors (LMFRs), which includes both Sodium Fast Reactors (SFRs) and Lead Fast Reactors (LFRs), the vast majority of its recent development and customization has been tailored to SFRs. In general, enhancements that are made to the software for SFRs are applicable to LFRs, however, the fuel composition and corrosive nature of lead requires careful consideration when performing safety analysis of an LFR. In this project an emphasis was placed on closing gaps that are associated with modeling LFRs using SAS. The principal objective of the project was to enhance the ability of SAS as a licensing tool for LFRs. This objective was to be accomplished through three tasks: 1) Enhance the ability of SAS to couple with external software; 2) Improve the underlying physics models in SAS, with priority given to models that are highly relevant to LFRs; 3) Extend the Verification and Validation (V&V) basis of the software

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Rapid measurement of soluble xylo-oligomers using near-infrared spectroscopy (NIRS) and multivariate statistics: calibration model development and practical approaches to model optimization

Rapid monitoring of biomass conversion processes using techniques such as near-infrared (NIR) spectroscopy can be substantially quicker and less labor-, resource-, and energy-intensive than conventional measurement techniques such as gas or liquid chromatography (GC or LC) due to the lack of solvents and preparation methods, as well as removing the need to transfer samples to an external lab for analytical evaluation. The purpose of this study was to determine the feasibility of rapid monitoring of a biomass conversion process using NIR spectroscopy combined with multivariate statistical modeling, and to examine the impact of (1) subsetting the samples in the original dataset by process location and (2) reducing the spectral range used in the calibration model on model performance. We develop multivariate calibration models for the concentrations of soluble xylo-oligosaccharides (XOS), monomeric xylose, and total solids at multiple points in a biomass conversion process which produces and then purifies XOS compounds from sugar cane bagasse. A single model using samples from multiple locations in the process stream showed acceptable performance as measured by standard statistical measures. However, compared to the single model, we show that separate models built by segregating the calibration samples according to process location show improved performance. We also show that combining an understanding of the sample spectra with simple multivariate analysis tools can result in a calibration model with a substantially smaller spectral range that provides essentially equal performance to the full-range model. We demonstrate that real-time monitoring of soluble xylo-oligosaccharides (XOS), monomeric xylose, and total solids concentration at multiple points in a process stream using NIR spectroscopy coupled with multivariate statistics is feasible. Segregation of sample populations by process location improves model performance. Models using a reduced spectral range containing the most relevant spectral signatures show very similar performance to the full-range model, reinforcing the importance of performing robust exploratory data analysis before beginning multivariate modeling.

09 BIOMASS FUELS↗