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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Adaptive Computing for Scale-Up Problems

Adaptive Computing is an application-agnostic outer loop framework to strategically deploy simulations and experiments to guide decision making for scale-up analysis. Resources are allocated over successive batches, which makes the allocation adaptive to some objective such as optimization or model training. The framework enables the characterization and management of uncertainties associated with predictive models of complex systems when scale-up questions lead to significant model extrapolation. A key advancement of this framework is its integration of multi-fidelity surrogate modeling, uncertainty management, and automated orchestration of various computing and experimentation resources into a single integrated software package. This enables efficient multi-fidelity modeling across multiple computing resources by incorporating real-world constraints such as relative queue times and throughput on individual machines into the multi-fidelity sampling decision. We discuss applications of this framework to problems in the renewable energy space, including biofuels production, material synthesis, perovskite crystal growth, and building electrical loads.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2019

Effect of Carbon Dioxide Recirculation and Pressure on Efficiency of the TIPS and ENEL Oxy-Coal Power Cycles

This paper presents the results of thermal efficiency of two coal based oxy-combustion thermodynamic cycles that are modeled using aspen plus. The objective of the present study is to perform a parametric analysis, investigating the effect of different recirculation ratios at different pressures on the efficiencies of the cycle named for the company, ENEL, and the thermo energy power system, TIPS, cycles using aspen plus® software. Variables include the flue gas recycle flow rate, the combustor temperature, and the operational pressure. Five recirculation ratios were investigated, ranging from 20% to 75%. It was determined that as the amount of recycled gas into the combustor increased, the thermal efficiency increased for both the TIPS and ENEL cycles. Here, the highest thermal efficiency for TIPS is 37% and for ENEL is 38%, both occurring at a 75% recirculation ratio. After investigation, since combustion temperature and specific heat capacity decreases at higher recirculation ratios, the mass flow rate was the dominant factor that contributes to the increase in thermal efficiency of the cycle. At each recirculation ratio, the effect of pressure is also determined. For ENEL, the increase in cycle efficiency is 10% over the pressure range of 1–12 bar at a recirculation ratio of 20%, while the increase in cycle efficiency is only 1.5% at a higher recirculation ratio of 75%. For TIPS, the cycle efficiency increases by 4% at the recirculation ratio of 20% and increases by 3% at the recirculation ratio of 75% for a pressure range of 50–80 bar.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2022

Computational Fluid Dynamic Modeling of Dry Cask Simulator with Crosswind

The purpose of this study is to create a STAR-CCM+ model of a Belowground Vertical Dry Cask Simulator (BVDCS) at Sandia National Laboratories (SNL) and validate the model with SNL’s experimental results. The BVDCS consists of a single boiling water reactor assembly fitted with electric heaters encompassed by a containment vessel and shell to represent a belowground spent nuclear fuel (SNF) dry storage system. Blowers are located near the inlet and outlet of the BVDCS to simulate crosswind conditions. In addition to the experimental results, the STAR-CCM+ model developed for this study is compared with a previous computational fluid dynamics (CFD) model in a different software program, which is used as a software-to-software benchmark. The experimental results provide a dataset to compare the STAR-CCM+ model results for a variety of different conditions. The main objective is to validate and improve STAR-CCM+ CFD models for spent nuclear fuel storage systems with explicitly modeled external environments and “wind driven” crossflows. These CFD models aide in the study of external particle deposition in spent nuclear fuel storage systems, which is important to predicting the significance of chloride induced stress corrosion cracking (CISCC). In addition to experimental comparison, a sensitivity analysis study is performed using the STAR-CCM+ model. The sensitivity analysis provides a quantitative assessment of the sensitivity of various parameters. This helps provide information on various parameters that are of particular importance to constructing a model representative of real life systems. The STAR-CCM+ model compared well to the experimental results showing similar responses to changes in cross wind flow, and a number of parameters are identified for model improvement.

Jensen, Ben J.↗
DOE OSTI2026

TETA Autoresearch [SWR-26-089]

TETA Autoresearch is a template repository based on github.com/karpathy/autoresearch for AI-assisted research science in the TETA group in the Center for Integrated Mobility Sciences (CIMS) center at the National Laboratory of the Rockies. This software is a template for running autonomous research experiments that iteratively improve an ML model for a single optimization objective. Two execution modes share one harness: LLM mode - an agent (e.g. Claude Code) edits a scaffold train.py one change at a time, tagging each experiment, logging reasoning, and pushing results. Defined by program.md. Optimizer mode - an Optuna-backed driver (TPE / CMA-ES / Random) iterates over a domain-defined search space. Defined by optimizers/. RouteE (vehicle energy prediction) is the reference domain under domains/routee/. Adding a new domain is mechanical - see EXTENDING.md.

Reinicke, Nicholas [National Laboratory of the Roc↗
DOE OSTI2021

Deep reinforcement learning for dynamic control of fuel injection timing in multi-pulse compression ignition engines

Conventional compression-ignition (CI) engines have long offered high thermal efficiencies and torque across a wide range of loads, but often require extensive exhaust gas treatment that decreases efficiency to meet ever-increasing emissions regulations. One strategy to decrease emissions is to split the fuel injection into a series of smaller injections. In this paper, we explore a new way of discovering optimal control strategies for the next generation of CI engines using deep reinforcement learning (DRL). We outline a DRL procedure to maximize the weighted reward of engine work while minimizing end-of-cycle NO x emissions. Through the procedure outlined in this paper, we show that the DRL agent is able to reduce NO x emissions threefold while only decreasing network by 2%. We demonstrate the use of transfer learning (TL) across hierarchies of physical models to accelerate the learning process, making this approach feasible for a range of control problems within this space. This paper presents a framework and demonstration for using DRL to design control systems in technology areas such as multi-pulse engine control where a hierarchy of models combined with multi-objective rewards are used for optimal operation.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2018

Data Driven Temperature Control of Heat Exchangers

The following poster presents a couple of approaches for temperature control at heat exchanger’s exit. One of the approaches is based on using n-step ahead neural network while the other approach utilizes a combination of control + learning module for temperature control. Designing robust controllers for typical heat exchangers is very challenging primarily because of complexities associated with the synthesis of dynamics of industrial heat exchangers. Even if a dynamics model is synthesized, the accuracy of it would be called into question as there can be lot of unmodeled system dynamics and random noise in input parameters. In many situations, the degree of uncertainty in the model of system being controlled limits the utility of optimal control design. Controller can be manually tuned on the field but it is very difficult to determine manual adjustments that result in overall improvement. These practical challenges call for learning based approaches for temperature control that would result in optimal heat exchanger performance. We utilize the existing mathematical model for air-water system synthesized by Underwood and Crawford for testing our algorithms. Underwood and Crawford developed a model of heating coil by fitting a second-order non-linear equations to measurements of air and water temperature and flow rates obtained from the actual coil. The uncertainties in the model include air and water inlet temperatures and air-flow rate. These uncertainties are modeled as random variables that are sampled from a uniform distribution. The control variable is the water flow rate which is controlled for regulating the air-outlet temperature. Neural networks are frequently used in various literatures for learning time-series. We propose a modified version of neural networks known as n-step ahead neural network that take the state variables and output at time t as input to successfully predict output at time t+n. The variable n is a hyper-parameter which can be optimized based on performance constraints. The n-step ahead neural network was then trained on training data generated from experimental model to high training accuracies. This trained model performed appreciably in its objective to regulate outlet temperature of a heat exchanger. The second approach uses a combination of control and learning module for temperature regulation. The control module used is a proportional controller while the learning module used is steady state neural network. The steady state neural network is used to learn the controller output as a function of random variables and temperature set-point. The proportional controller is then used to compensate for transient behavior of linearized system around various operating points. The algorithm works effectively for temperature regulation as neural network captures the non-linear input-output behavior of closed loop system leaving proportional controller to compensate for steady state errors of a linearized plant. The proposed algorithm’s performances were evaluated against the performance of a PI controller. Further, the robustness of the algorithms were also studied in great detail under small perturbations around tuned parameters of the proposed algorithms.

Sundar, Sreenath↗
DOE OSTI2020

Decovalex-2019 (Executive Summary)

The DECOVALEX Project is an on-going international research collaboration, established in 1992, to advance the understanding and modeling of coupled Thermal (T), Hydrological (H), Mechanical (M) and Chemical (C) processes in geological in geological systems. DECOVALEX was initially motivated by the recognition that prediction of these coupled effects is an essential part of the performance and safety assessment of geologic disposal systems for radioactive waste and spent nuclear fuel. Later it was realized that these processes also play a critical role in other subsurface engineering activities, such as subsurface CO 2 storage, enhanced geothermal systems, and unconventional oil and gas production through hydraulic fracturing. Research teams from many countries (e.g., Canada, China, Czech Republic, Finland, France, Germany, Japan, Republic of Korea, Spain, Sweden, Switzerland, Taiwan, United Kingdom, and the United States) various institutions have participated in the DECOVALEX Project over the years, providing a wide range of perspectives and solutions to these complex problems. These institutions represent radioactive waste management organizations, national research institutes, regulatory agencies, universities, as well as industry and consulting groups. The overall aim of DECOVALEX-2019 was to increase the understanding of various thermo-hydro-mechanical-chemical processes of importance for radionuclide release and transport from a repository to the biosphere and how they can be described and modelled using mathematical models. The scientific and technical objectives are: to increase the basic understanding of T-H-M-C coupled processes in fractured rocks (crystalline, sedimentary, argillaceous) and buffer materials; to investigate the predictive capabilities of different codes to field experiments and to perform verification of codes; to exchange experimental data, and improve the understanding of the constitutive behavior of crystalline and argillaceous rock masses and buffer materials; and to perform THMC calculations in a performance/safety assessment context.

58 GEOSCIENCES↗
DOE OSTI2021

Streaming Generalized Canonical Polyadic Tensor Decompositions

In this paper, we develop a method which we call OnlineGCP for computing the Generalized Canonical Polyadic (GCP) tensor decomposition of streaming data. GCP differs from traditional canonical polyadic (CP) tensor decompositions as it allows for arbitrary objective functions which the CP model attempts to minimize. This approach can provide better fits and more interpretable models when the observed tensor data is strongly non-Gaussian. In the streaming case, tensor data is gradually observed over time and the algorithm must incrementally update a GCP factorization with limited access to prior data. In this work, we extend the GCP formalism to the streaming context by deriving a GCP optimization problem to be solved as new tensor data is observed, formulate a tunable history term to balance reconstruction of recently observed data with data observed in the past, develop a scalable solution strategy based on segregated solves using stochastic gradient descent methods, describe a software implementation that provides performance and portability to contemporary CPU and GPU architectures and integrates with Matlab for enhanced usability, and demonstrate the utility and performance of the approach and software on several synthetic and real tensor data sets.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Development and Bench-Scale Testing of a Novel Biphasic Solvent-Enabled Absorption Process for Post-Combustion Carbon Capture (Final Technical Report)

A new class of biphasic solvents was developed, and the concept of the enabled carbon dioxide (CO 2 ) absorption process was tested for post-combustion carbon capture in our previous lab-scale research. The primary goals of this project were to advance the development of the novel biphasic CO 2 absorption process (BiCAP) and validate its technical advantages by testing the integrated technology at a 40 kWe bench-scale with actual coal-derived flue gas in a power plant environment. The project was led by the University of Illinois at Urban-Champaign (UIUC), and Trimeric Corporation served as a sub-awardee providing support in basic design and techno-economic studies. To achieve the project goals and objectives, solvent management studies, process modeling and optimization, bench-scale equipment design, construction and testing, and technical, economic and environmental assessments have been conducted. The two top-performing biphasic solvents developed in our previous research were used in this project. Biphasic solvent emissions and control were investigated in the laboratory. The emissions of the biphasic solvents from the absorber were comparable to or lower than the reference 30 wt% monoethanolamine (MEA) solution, while they could be more effectively removed in the water wash column. Lab-scale testing of solvent degradation reclamation has revealed that vacuum distillation was feasible for biphasic solvent reclamation. Aspen Plus models were used to optimize the BiCAP, and a CO 2 stripping configuration introducing a secondary cold solvent feed to the stripper was identified to be the most energy efficient. A 40 kWe bench-scale, integrated BiCAP system was successfully designed, fabricated, and installed at the UIUC’s Abbott Power Plant. Parametric testing with synthetic flue gas has demonstrated that the two biphasic solvents required a more than 40% lower heat duty for CO 2 desorption as compared to the reference MEA tested on the same bench-scale skid. Slipstream testing with actual coal flue gas for a total of 31 days in two test campaigns has further demonstrated stable operation of the bench-scale skid. During the first campaign targeting 90% CO 2 removal, the heat duty averaged at 2,183 MJ/tonne of CO 2 captured and during the second campaign targeting 95% removal, the heat duty averaged at 2,450 MJ/tonne of CO 2 captured. A techno-economic analysis has revealed that for integration of the BiCAP into a 650-MWe pulverized coal-fired power plant, the parasitic power loss was reduced by ~20%, and the cost of CO 2 capture was reduced by ~21% ($36.3/tonne on a December 2018 dollar basis) compared to the U.S. Department of Energy (DOE)’s baseline Case B12B. As progression from this bench-scale development effort, a new project “Engineering-Scale Testing of the Biphasic Solvent Based CO 2 Absorption Capture Technology at a Covanta Waste-to-Energy Facility” was awarded by the DOE, launched in February 2023, to allow the team to further test the technology and demonstrate its technical and economic advantages at a pilot scale.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2023

Acoustic Research under the Source Physics Experiment

The Source Physics Experiment series is a long-term research and development (R&D) effort under the U.S. Department of Energy’s National Nuclear Security Administration focused on improving the physical understanding of how chemical explosions generate seismoacoustic signals. Beginning in 2011, a series of subsurface chemical explosions in two different and highly contrasting geologies were conducted at the Nevada National Security Site in Nevada, USA with the objective of improving simulation and modeling approaches to explosion identification, yield estimation and other monitoring applications. The two executed phases of the series provide new explosion signature source data from a wide range of geophysical diagnostic equipment; recorded data from the test series is now openly available to the broader seismoacoustic community. This manuscript details the executed test series, deployed seismoacoustic networks, and summarizes major scientific achievements utilizing recorded signatures from the explosive tests.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2018

Automated Calculation of Bulk-Stamping Matrices for Circular Blanks

The bulk stamping of circular blanks is considered. There is a clear need for automatic stamping. The input and output data for calculating the working part of the bulk-stamping matrix are analyzed. Software for automated calculation of bulk-stamping matrices is developed. The program code and a possible interface for the calculation of matrix parameters and construction of 3D models by means of the Object Pascal language are presented.

42 ENGINEERING↗
DOE OSTI2017

Evidence That the Directly Imaged Planet HD 131399 Ab Is a Background Star

Herein we present evidence that the recently discovered, directly imaged planet HD 131399 Ab is a background star with nonzero proper motion. From new JHK1L ' photometry and spectroscopy obtained with the Gemini Planet Imager, VLT/SPHERE, and Keck/NIRC2, and a reanalysis of the discovery data obtained with VLT/SPHERE, we derive colors, spectra, and astrometry for HD 131399 Ab. The broader wavelength coverage and higher data quality allow us to reinvestigate its status. Its near-infrared spectral energy distribution excludes spectral types later than L0 and is consistent with a K or M dwarf, which are the most likely candidates for a background object in this direction at the apparent magnitude observed. If it were a physically associated object, the projected velocity of HD 131399 Ab would exceed escape velocity given the mass and distance to HD 131399 A. We show that HD 131399 Ab is also not following the expected track for a stationary background star at infinite distance. Solving for the proper motion and parallax required to explain the relative motion of HD 131399 Ab, we find a proper motion of 12.3 mas yr –1 . When compared to predicted background objects drawn from a galactic model, we find this proper motion to be high but consistent with the top 4% fastest-moving background stars. From our analysis, we conclude that HD 131399 Ab is a background K or M dwarf.

stars: individual (HD 131399)↗
DOE OSTI2021

Searching for Active Low-mass Stars in the CMa Star-forming Region: Multi-band Photometry with T80S

An exotic environment surrounds the young stellar groups associated with the Canis Major (CMa) OB1/R1 region, which probably was formed under feedback from at least three supernova events having occurred a few million years ago. We use astrometric data from the Gaia-DR2 to confirm the membership of the stars in CMa R1, based on proper motion and parallax, which revealed 514 new members and candidates. The mean age of 5 Myr estimated from the color–magnitude diagram characterizes the sources as likely pre-main-sequence candidates. In total, a sample of 694 stars detected with the T80-South telescope was analyzed according to different color–color diagrams, which were compared with theoretical colors from evolutionary models, aiming to reveal the objects that exhibit color excess due to accretion processes. Accretion and magnetic activity were also explored on the basis of empirical flux–flux relation, such as F {sub 660} and F {sub 861} that are related to Hα and Ca ii triplet emission, respectively. A low fraction (∼3 percent) of the sample have Hα excess and other colors expected for stars exhibiting chromospheric activity. The number of Class I and Class II objects, identified by the infrared (Wide-field Infrared Survey Explorer) colors, indicates a disk fraction of ∼6 percent, which is lower than that expected for stellar clusters with a similar age. Such a large sample of objects associated with CMa R1 without evidences of circumstellar accretion can be interpreted as a lack of disk-bearing stars, unusual for young star-forming regions. However, this may be explained as the result of supernova events.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

A Deep Study of an Intermediate-age Open Cluster SAI 35 (Juchert 20) Using Ground-based Imaging and Gaia EDR3 Astrometry

We present a CCD UBVI photometric study of poorly studied intermediate-age open cluster SAI 35 (Juchert 20) for the first time. To accomplish this study, we also used LAMOST DR5, Two Micron All Sky Survey, and Gaia EDR3 databases. We identified 214 most probable cluster members with membership probability higher than 50%. The mean proper motion of the cluster is found as μ{sub α}cos δ=1.10±0.01 and μ {sub δ} = −1.66 ± 0.01 mas yr{sup −1}. We find the normal interstellar extinction law using the various two-color diagrams. The age, distance, reddening, and radial velocity of the cluster are estimated to be 360 ± 40 Myr, 2.9 ± 0.15 kpc, 0.72 ± 0.05 mag, and −91.62 ± 6.39 km s{sup −1}, respectively. The overall mass function slope for main-sequence stars is found to be 1.49 ± 0.16 within the mass range 1.1–3.1 M {sub ⊙}, which is in agreement with Salpeter’s value within uncertainty. The present study demonstrates that SAI 35 is dynamically relaxed. Galactic orbital parameters are determined using Galactic potential models. We found that this object follows a circular path around the Galactic center.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Hot Degenerates in the MCT Survey. III. A Sample of White Dwarf Stars in the Southern Hemisphere

Here, we present optical spectra of 144 white dwarfs detected in the Montreal–Cambridge–Tololo colorimetric survey, including 120 DA, 12 DB, 4 DO, 1 DQ, and 7 DC stars. We also perform a model atmosphere analysis of all objects in our sample using the so-called spectroscopic technique, or the photometric technique in the case of DC white dwarfs. The main objective of this paper is to contribute to the ongoing effort of confirming spectroscopically all white dwarf candidates in the Gaia survey, in particular in the southern hemisphere. All our spectra are made available in the Montreal White Dwarf Database.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Final Report for Grant

This is the final report for this project. The major objectives were to develop full models and standard cells of CMOS silicon photomultipliers (SiPM) for neutron detection applications. Specifically, the research seeks to replace photomultiplier tubes, used in neutron detection applications, with SiPMs containing integrated readout electronics fabricated in standard CMOS processes. The detectors improve on the detection efficiency, readout speed, resolution (sensitivity), and spatial resolution of current systems. In particular, this work involved collaboration with the instrument and detector group at ORNL who build detectors based on discrete commercially available PMTs and SiPMs. The SiPM detectors developed in this work are based on Perimeter Gated Single Photon Avalanche Diodes (PGSPAD). These devices have tunable breakdown voltage which affects other performance characteristics of the detectors. The ability of the detectors to have integrated readout and tune the noise floor and dynamic range in addition to offering a method for non-uniformity compensation in a compact form significantly impacts the imaging research field and includes the nuclear sciences field, circuits and systems field in addition to varied fields such as geography and biology/medicine.

42 ENGINEERING↗
DOE OSTI2025

Improving Thermal Management Strategies for Data Centers: A Physical Testbed Incorporating Small Modular Reactor and Microreactor Technology

This study aims to accelerate the demonstration of various thermal management systems for data centers using nuclear-generated heat to enhance energy and grid reliability. Utilizing mobile containerized and stationary test beds at INL's High Performance Computing (HPC) facility, this project integrates with various nuclear-related energy systems testing facilities. Key components include immersion cooling apparatus, absorption chillers, and adjustable thermal management simulators. Tasks involve acquiring necessary hardware, sensors, and cooling apparatus, engaging with data center industry stakeholders, and providing a testing platform for algorithms, models, tools, and software. The objective is to expedite the deployment of nuclear-powered data centers, thereby improving energy reliability and affordability.

21 - SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLAN↗
DOE OSTI2024

Proof-of-Concept for Sensor Modeling in MOOSE for the Design of Autonomous Nuclear Reactor Control

Autonomous operation is essential for the deployment of microreactors and fission batteries, both in terrestrial and space applications. However, prototypes of microreactors and fission batteries do not exist yet, and even the design space has not been narrowed down conclusively, making the instrumentation and control system design difficult. For this reason, there is a need for flexible computational capabilities to create a numerical stand-in of potential microreactor and fission battery designs. The latter can be used to design and test control strategies to support autonomous operations. In this paper, we describe the initial implementation of a pluggable sensor system for the easy implementation of realistic sensor models in the multiphysics object-oriented simulation environment (MOOSE) framework. This new capability will enable MOOSE users to create a numerical stand-in of microreactors and fission batteries, ultimately allowing them to easily test new control algorithms, and instrumentation strategies for advanced systems in the design phase

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗