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DOE OSTI2022

Preliminary Safety Analysis for a 400-kW Molten Salt Nuclear Battery

The Molten Salt Nuclear battery (MsNB) is a microreactor based on technology developed and operated at Oak Ridge National Laboratory in the 1960s [1]. But the MsNB has been simplified by removing pumps and valves for improved reliability and safety. The MsNB can safely provide up to 10 MWe of power for up to 10 years and potentially it can be transported by air, truck, and rail thanks due to to its small footprint. A computer model has been developed to represent a prototypical 400-kW MsNB using the ANL system code SAM [2]. The model has been used to produce a reactor thermal-hydraulic performance map and perform analysis of unprotected loss of heat sink accident scenario.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2022

Analysis of Reactive Power Load Modeling Techniques for PV Impact Studies [Slides]

The increasing availability of advanced metering infrastructure (AMI) data has led to significant improvements in load modeling accuracy. However, since many AMI devices were installed to facilitate billing practices, few utilities record or store reactive power demand measurements from their AMI. When reactive power measurements are unavailable, simplifying assumptions are often applied for load modeling purposes, such as applying constant power factors to the loads. The objective of this work is to quantify the impact that reactive power load modeling practices can have on distribution system analysis, with a particular focus on evaluating the behaviors of distributed photovoltaic (PV) systems with advanced inverter capabilities. Quasi-static time-series simulations were conducted after applying a variety of reactive power load modeling approaches, and the results were compared to a baseline scenario in which real and reactive power measurements were available at all customer locations on the circuit. Overall, it was observed that applying constant power factors to loads can lead to significant errors when evaluating customer voltage profiles, but that performing per-phase time-series reactive power allocation can be utilized to reduce these errors by about 6x, on average, resulting in more accurate evaluations of advanced inverter functions.

14 SOLAR ENERGY↗

DOE OSTI2025

Modeling MTS pyrolysis and SiC deposition kinetics using principal component analysis and neural networks

Accurate chemical kinetics modeling is crucial for improving the efficiency of chemical processing and synthesis of ceramic matrix composites. Detailed kinetic models are computationally expensive due to the large number of transported chemical species, while the simplified physics-based models, such as single-step global mechanisms, are efficient but often overlook key chemical intermediates and pathways. Recent deep learning approaches promise accurate and cost-effective models. Yet, they require additional closures for the transported nonlinear latent variables, complicating integration with existing solvers. In this work, we develop a hybrid linear—nonlinear reduced model for silicon carbide deposition from methyltrichlorosilane precursor by combining principal component analysis (PCA) and autoencoder (AE) neural network (NN) approaches. PCA is used to identify a smaller set of linear transport variables, enabling direct reuse of conventional transport solvers. NNs then reconstruct the full chemical state from these reduced variables. We demonstrate the method on a chemical vapor deposition reactor—comprising a gas-phase pyrolysis plug flow reactor and a heterogeneous surface reactor—over a wide range of temperatures, pressures, and residence times. Our PCA–AE model achieves high accuracy with only five transported scalars, achieving an eightfold cost reduction compared to detailed mechanisms, in both a priori (using data from the test set only) and a posteriori (coupled with a differential equation solver). In conclusion, notable errors arise primarily near training domain boundaries and for long residence times, indicating the need for domain shift indicators and better long-horizon predictions in future reduced chemistry model development.

autoencoder neural networks↗

DOE OSTI2025

Fuel performance analysis of fully-resolved TRISO compact

The TRi-structural ISOtropic (TRISO) fuel multilayered coating structure offers multiple barriers to fission product release, enhancing safety and performance. The heterogeneous nature of TRISO fuel compacts, comprising thousands of randomly distributed coated fuel particles embedded in a graphite matrix, creates intricate stress fields and thermal gradients that cannot be accurately modeled using simplified one-dimensional or homogenized approaches. Consequently, three-dimensional modeling enables the prediction of fuel compact dimensional changes, internal pressure buildup, and fission product transport pathways under diverse irradiation and thermal conditions. This capability facilitates detailed analysis of particle-to-particle interactions, matrix cracking mechanisms, and the statistical distribution of coating failures, which directly impact fuel performance and safety margins. This capability is particularly critical for advanced reactors, such as high-temperature gas-cooled reactors and other Generation IV reactor designs where TRISO fuel operates at elevated temperatures and burn-up levels. This work introduces a novel method to generate an optimized packing of TRISO compacts and a complete 3D mesh with random distribution of TRISO particles, which are discretized into each coating component layer.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2021

Embedded Error Bayesian Calibration of Thermal Decomposition of Organic Materials

Organic materials are an attractive choice for structural components due to their light weight and versatility. However, because they decompose at low temperatures relative to tradiational materials they pose a safety risk due to fire and loss of structural integrity. To quantify this risk, analysts use chemical kinetics models to describe the material pyrolysis and oxidation using thermogravimetric analysis. This process requires the calibration of many model parameters to closely match experimental data. Previous efforts in this field have largely been limited to finding a single best-fit set of parameters even though the experimental data may be very noisy. Furthermore the chemical kinetics models are often simplified representations of the true de- composition process. The simplification induces model-form errors that the fitting process cannot capture. In this work we propose a methodology for calibrating decomposition models to thermogravimetric analysis data that accounts for uncertainty in the model-form and experimental data simultaneously. The methodology is applied to the decomposition of a carbon fiber epoxy composite with a three-stage reaction network and Arrhenius kinetics. The results show a good overlap between the model predictions and thermogravimetric analysis data. Uncertainty bounds capture devia- tions of the model from the data. The calibrated parameter distributions are also presented. In conclusion, the distributions may be used in forward propagation of uncertainty in models that leverage this material.

36 MATERIALS SCIENCE↗

NASA NTRSDate not supplied

Extraction and Analysis of the Properties of Shape Memory Alloys

Shape Memory Alloys (SMA) are materials of high industrial importance, increasingly used for the aerospace applications. Use of SMA allows to simplify flight systems and reduce the total weight. Through the literature-based data mining, we extracted the computed SMA properties from the high-impact journals. We plotted the selected pairs of properties, found and parametrized correlations.

Jason Ernesto Diaz↗

DOE OSTI2022

Geomechanical and Hydrogeological Evaluation of a Shallow Hydraulic Fracture at the Devine Fracture Pilot Site, Medina County, Texas

UT-Austin’s Devine Fracture Pilot Site, 50 miles southwest of San Antonio, Texas, has been targeted for a comprehensive, multidisciplinary development of fracture diagnostic techniques that are cross-validated by ground-truth data acquisition near a recently created, 175-ft-deep, horizontal hydraulic fracture (Ahmadian et al. 2018 Demonstration of proof of concept of electromagnetic geophysical methods for high resolution illumination of induced fracture networks. In Proceedings of the SPE Hydraulic Fracturing Technology Conference and Exhibition, The Woodlands, Texas, USA, 23–25 January 2018. SPE-189858-MS.). To evaluate the fracture diagnostic methods at this site, we conducted injection tests with a predefined volumetric flow-rate profile, resembling a diagnostic fracture injection test on September 2020. Subsequently, we developed hydrogeological and geomechanical models based on flow-rate and bottomhole-pressure measurements. History-matching efforts using a simplified layer-cake hydrogeological model resulted in the field-scale formation permeability of 9.87 × 10 –15 m 2 (10 mD) and Darcy-scale fracture permeability. The analysis of the bottomhole pressure and injection-rate history showed that (1) the newly created horizontal fracture was closed adjacent to the injection well pre-injection and (2) the initial pump-pressure increase at a nominal volumetric injection rate led to near-well fracture reopening, fluid conductivity increase, and abrupt injection-rate increase. To overcome hydrogeological-model limitations of predicting fracture reopening throughout injection, we extended the modeling to a finite-element, poroelastic analysis of horizontal-fracture growth using a cohesive-zone model. Using this fracture-reopening model, we improved the history match of the transient-pressure response during the experiment by adjusting the hydromechanical properties. Furthermore, post-injection pressure transient analyses helped reduce uncertainty in the overburden-stress gradient, and the initial hydraulic-fracturing simulation verified the plausibility of achieving the surveyed propped fracture area.

02 PETROLEUM↗

DOE OSTI2025

Three-dimensional analysis of microbunched electron cooling

Microbunched electron cooling (MBEC, Ratner, ), a special category of coherent electron cooling, has been under consideration as a candidate method for the strong hadron cooling component of the Electron Ion Collider (EIC) at BNL. Most of the theoretical treatments of this scheme so far have been based on simplified models for the key space charge effect in which electrons and/or hadrons are approximated by charged disks. Although such disk-based models provide a flexible tool that captures a good part of the underlying physics, they lack the fidelity and robustness of a rigorous analysis that explicitly treats the hadron and cooler electron beams as collections of point charges. In this paper, we present such a rigorous, three-dimensional (3D) model, both from a theory-based and a simulation perspective. Specifically, we calculate the generalized wakefield (or Green’s function) of the cooling system—a crucial quantity that determines the overall performance—paying special attention to the dependence of the wake on the hadron transverse positions. Additionally, our treatment takes into account previously neglected 3D effects that can cause damping of the plasma oscillations in the amplification section of the cooler, such as focusing and the angular spread of the electron beam. Published by the American Physical Society 2025

43 PARTICLE ACCELERATORS↗

DOE OSTI2026

The nucleardatapy toolkit for simple access to experimental nuclear data, astrophysical observations, and theoretical predictions

Systematic comparisons across theoretical predictions for the properties of dense matter, nuclear physics data, and astrophysical observations (also called meta-analyses) are performed. Existing predictions for symmetric nuclear and neutron matter properties are considered, and they are shown in this paper as an illustration of the present knowledge. Asymmetric matter is constructed assuming the isospin asymmetry quadratic approximation. It is employed to predict the pressure at twice saturation energy-density based only on nuclear-physics constraints, and we find it compatible with the one from the gravitational-wave community. To make our meta-analysis transparent, updated in the future, and to publicly share our results, the Python toolkit nucleardatapy is described and released here. Hence, this paper accompanies nucleardatapy, which simplifies access to nuclear-physics data, including theoretical calculations, experimental measurements, and astrophysical observations. This Python toolkit is designed to easily provide data for: (i) predictions for uniform matter (from microscopic or phenomenological approaches); (ii) correlation among nuclear properties induced by experimental and theoretical constraints; (iii) measurements for finite nuclei (nuclear chart, charge radii, neutron skins or nuclear incompressibilities, etc.) and hypernuclei (single particle energies); and (iv) astrophysical observations. This toolkit provides data in a unified format for easy comparison and provides new meta-analysis tools. It will be continuously developed, and we expect contributions from the community in our endeavor.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2026

A Unified Workflow for Sensitivity-Based Kinetic Analysis in Microkinetic Models

Degrees of rate control (DRC), apparent activation energies, and apparent reaction orders are established local sensitivity diagnostics for interpreting microkinetic models, but applying them routinely to large mechanisms often requires substantial reaction-specific bookkeeping, perturbation design, and postprocessing. Here, in this study, we present a unified derivative-based workflow that evaluates these quantities from a single compiled reaction-network model and target-rate definition. For any user-provided microkinetic model, the workflow compiles the mechanism into stoichiometrically consistent mass-action rate equations, solves the surface dynamics, and uses automatic differentiation to compute sensitivities with respect to rate constants, temperature, and gas partial pressures. By combining their calculations in the same framework, the workflow clearly demonstrates the relationships between different DRCs and the apparent activation energy. Using existing examples of propylene partial oxidation and methane oxidation on Pd(100), we verify expected transient redistribution of rate control, distinguish net Campbell DRCs from one-sided directional sensitivities, and show how apparent activation energy can be reconstructed either from one-sided DRCs or from state-based DRCs while critical mechanistic insights are obtained consistently. In the methane oxidation case, a pathway-subset test further illustrates how a simplified mechanism preserves key kinetic signatures of a full model, showing the potential of our user-friendly tool for model construction beyond kinetic analysis.

36 MATERIALS SCIENCE↗

NASA NTRS2013

Numerical Investigation of a Fuselage Boundary Layer Ingestion Propulsion Concept

In the present study, a numerical assessment of the performance of fuselage boundary layer ingestion (BLI) propulsion techniques was conducted. This study is an initial investigation into coupling the aerodynamics of the fuselage with a BLI propulsion system to determine if there is sufficient potential to warrant further investigation of this concept. Numerical simulations of flow around baseline, Boundary Layer Controlled (BLC), and propelled boundary layer controlled airships were performed. Computed results showed good agreement with wind tunnel data and previous numerical studies. Numerical simulations and sensitivity analysis were then conducted on four BLI configurations. The two design variables selected for the parametric study of the new configurations were the inlet area and the inlet to exit area ratio. Current results show that BLI propulsors may offer power savings of up to 85% over the baseline configuration. These interim results include the simplifying assumption that inlet ram drag is negligible and therefore likely overstate the reduction in power. It has been found that inlet ram drag is not negligible and should be included in future analysis.

Elmiligui, Alaa A.↗

DOE OSTI2022

GIS-Based Graphical User Interface Tools for Analyzing Solar Thermal Desalination Systems & High-Potential Implementation

This project developed a user-friendly, open-source, software that enables a comparative evaluation of solar thermal desalination technology options and employs geospatial data layers to identify regions of high-potential for solar thermal desalination. This was accomplished by integrating solar models with desalination models and enhancing their utility by providing GIS-based data inputs. The developed Solar Energy Desalination Analysis Tool (SEDAT) enables techno-economical evaluation of desalination technologies and selection of regions with the highest potential for using solar energy to power desalination plants. It simplifies the planning, design, and valuation of solar thermal and solar hybrid desalination systems in the U.S. and worldwide. SEDAT uses Dash for integrating various layers of large volumes of GIS data with Python-based models of solar energy generation and desalination technologies. It derives time-series of energy generation and water production, with details of plant performance and suggestions for improving the solar-desalination coupling. It is a one of-a-kind tool of analysis representing a definitive advancement in the state-of-the-art. Of solar desalination modeling This report summarizes the various phases of the tool’s development, and presents examples of the results.

14 SOLAR ENERGY↗

DOE OSTI2025

The impact of simplified window and exhaust fan assumptions on indoor air quality in multifamily buildings

In residential buildings, the indoor air quality can be significantly affected by ventilation measures initiated by occupants, including the operation of windows and in-unit exhaust fans in kitchens and bathrooms. Many simulations simplify these factors by disregarding window opening behaviors and using fixed schedules for exhaust fan operation across all residential units. To estimate the impact of these simplifications in the U.S. context, this study used coupled CONTAM and EnergyPlus models to simulate airflow and contaminant transport in multifamily buildings. The coupled models parametrically varied climate zone, building airtightness, and mechanical ventilation system types. The study conducted a sensitivity analysis on two key occupant behaviors: (1) operating kitchen and bathroom exhausts on different schedules in individual dwelling units, and (2) scheduling open windows on ground and top floors. The simplified assumptions (i.e. uniform in-unit exhaust fan operation and window operation) had a minimal impact on inter-unit air flow and contaminant transport simulations across a broad range of building air leakage and mechanical ventilation system types. These findings suggest that for buildings with tight construction it is reasonable for most modelling and simulation efforts to ignore the effects of non-uniform exhaust fan operation and window opening.

Occupant behavior↗

NASA NTRS1990

Modeling and model simplification of aeroelastic vehicles

The rigid-body degrees of freedom and elastic degrees of freedom of aeroelastic vehicles are typically treated separately in dynamic analysis. Such a decoupling, however, is not always justified and modeling assumptions that imply decoupling must be used with caution. The frequency separation between the rigid-body and elastic degrees of freedom for advanced aircraft may no longer be sufficient to permit the typical treatment of the vehicle dynamics. Integrated, elastic vehicle models must be developed initially and simplified in a manner appropriate to and consistent with the intended application. This paper summarizes key results from the research aimed at developing and implementing integrated aeroelastic vehicle models for flight controls analysis and design. Three major areas will be addressed: (1) the accurate representation of the dynamics of aeroelastic vehicles, (2) properties of several model simplification methods, and (3) the importance of understanding the physics of the system being modeled and of having a model which exposes the underlying physical causes for critical dynamic characteristics.

Waszak, Martin R.↗

NASA NTRS1992

Modeling and model simplification of aeroelastic vehicles: An overview

The rigid-body degrees of freedom and elastic degrees of freedom of aeroelastic vehicles are typically treated separately in dynamic analysis. Such a decoupling, however, is not always justified and modeling assumptions that imply decoupling must be used with caution. The frequency separation between the rigid-body and elastic degrees of freedom for advanced aircraft may no longer be sufficient to permit the typical treatment of the vehicle dynamics. Integrated, elastic vehicle models must be developed initially and simplified in a manner appropriate to and consistent with the intended application. This paper summarizes key results from past research aimed at developing and implementing integrated aeroelastic vehicle models for flight controls analysis and design. Three major areas will be addressed: (1) the accurate representation of the dynamics of aeroelastic vehicles, (2) properties of several model simplification methods, and (3) the importance of understanding the physics of the system being modeled and of having a model which exposes the underlying physical causes for critical dynamic characteristics.

Waszak, Martin R.↗

NASA NTRS1997

Biogeochemistry of DMS in Surface Waters

Dimethylsulfide (DMS) is important in influencing the formation of aerosols in the troposphere over large areas of the world's oceans. Understanding the dynamics of aerosols is important to understanding the earth's radiation balance. In evaluating the factors controlling DMS in the troposphere it is vital to understand the dynamics of DMS in the surface ocean. The biogeochemical processes controlling DMS concentration in seawater are myriad; modeling and theoretical estimation are problematic. At the beginning of this project we believed that we were on the verge of simplifying the ship-track measurement of DMS, and we proposed to deploy such a system to develop a database relating high frequency DMS measurements to biological and physicochemical and optical properties of surface water that can be quantified by remote sensing techniques. We designed a system to measure DMS concomitantly with other basic chemical and biological data in a flow-through system. The project was collaborative between Woods Hole Oceanographic Institution (WHOI) and Bermuda Biological Station for Research (BBSR). The project on which we are reporting was budgeted for only one year with a one year no-cost extension. At WHOI our effort was directed towards designing traps which would be used to concentrate DMS from seawater and allow storage for subsequent analysis. At that time, GC systems were too large for easy long-term deployment on a research vessel like R/V Weatherbird, so we focused on simplifying the shipboard sampling procedure. Initial studies of sample recovery with high levels of DMS suggested that Carboxen 1000, a relatively new carbon molecular sieve, could be used as a stable storage medium. The affinity of Carboxen for DMS is several orders of magnitude higher than gold wool (another adsorbent used for DMS collection) on a weight or volume basis. Furthermore, Carboxen's affinity for DMS is also far less susceptible to humidity than gold wool. Unfortunately, further experiments with low level DMS indicated that recovery of DMS after storage was not quantitative. The material has proven to be completely acceptable for short term storage and has been incorporated into a micro-GC system. Since working on this project, we have collaborated with RVM Scientific in Santa Barbara in the design and construction of small portable micro-GC's that will make feasible at-sea measurement in moving ships, making rapid gas analysis and quantification feasible in a ship-track mode. Throughout this period at both WHOI and BBSR, we continued to analyze field data to understand that patterns of time and space variability in DMS and the processes that govern it. These insights will be crucial to determining the specifications for our automated sampling program. The data from this, the longest continuous sampling program for ocean DMS, provided insights into year to year and short-term variability.

Dacey, J. W. H.↗

NASA NTRS2010

Orbit Determination Toolbox

The Orbit Determination Toolbox is an orbit determination (OD) analysis tool based on MATLAB and Java that provides a flexible way to do early mission analysis. The toolbox is primarily intended for advanced mission analysis such as might be performed in concept exploration, proposal, early design phase, or rapid design center environments. The emphasis is on flexibility, but it has enough fidelity to produce credible results. Insight into all flight dynamics source code is provided. MATLAB is the primary user interface and is used for piecing together measurement and dynamic models. The Java Astrodynamics Toolbox is used as an engine for things that might be slow or inefficient in MATLAB, such as high-fidelity trajectory propagation, lunar and planetary ephemeris look-ups, precession, nutation, polar motion calculations, ephemeris file parsing, and the like. The primary analysis functions are sequential filter/smoother and batch least-squares commands that incorporate Monte-Carlo data simulation, linear covariance analysis, measurement processing, and plotting capabilities at the generic level. These functions have a user interface that is based on that of the MATLAB ODE suite. To perform a specific analysis, users write MATLAB functions that implement truth and design system models. The user provides his or her models as inputs to the filter commands. The software provides a capability to publish and subscribe to a software bus that is compliant with the NASA Goddard Mission Services Evolution Center (GMSEC) standards, to exchange data with other flight dynamics tools to simplify the flight dynamics design cycle. Using the publish and subscribe approach allows for analysts in a rapid design center environment to seamlessly incorporate changes in spacecraft and mission design into navigation analysis and vice versa.

Carpenter, James R.↗

NASA NTRS2021

Residual Stresses Induced due to Curing of the Bulk Matrix in a Simplified Three-Dimensional (3D) Woven Repeating Unit Cell

It has been observed that 3D woven materials are highly susceptible to processes induced defects including tow misalignment, intratow and intertow cracking and/or voids. Adequate process modeling of 3D woven Polymer Matrix Composites (PMCs) is necessary to predict and estimate the effects of the manufacturing process on these defects. A preliminary step towards this is achieved with the commercial Finite Element Analysis (FEA) tool Abaqus complemented with written user subroutines to account for the effect of shrinkage and thermoelastic properties evolution as a function of the degree of cure of the bulk matrix phase in a 3D woven composite repeating unit cell (RUC). As a pathfinder, the process modeling framework is demonstrated on a simplified 3D woven RUC of an AS4/RIMR 135 system. Curing simulations are performed on the 3D woven RUC to observe the processing induced residual stresses. The results of the analysis show that high stress concentrations, present within the 3D intertow matrix bordering the binder tow, coincide with X-Ray computed tomography (X-Ray-CT) scan data depicting cracking in the same location

3D Woven↗