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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 OSTI2022

Tempering kinetics during multilayer laser additive manufacturing of a ferritic steel

Grade 91 steel forms martensite during additive manufacturing and the extent of tempering of martensite significantly affects the mechanical properties of parts. Currently, there is a lack of quantitative understanding of the tempering kinetics for Grade 91 steel, and as a result, the effects of repeated thermal cycles on properties for different processing conditions cannot be determined. Here we evaluate the tempering kinetics by determining the constant terms in the Johnson Mehl Avrami kinetic equation from the tempering data available in the literature and the thermal cycles computed using a rigorously-tested heat and fluid flow model of multi-layer additive manufacturing. The raw tempering data are cleaned using a neural network to enhance accuracy. The lower layers experience repeating cycles of heating and cooling when the upper layers are added. As a result, the hardness is reduced owing to the tempering of martensite. In contrast, martensite formed in the upper layers is not tempered to the same extent and the hardness remains high. Therefore, the hardness of the part increases with the distance from the substrate. Variations in the heat input at different laser powers and scanning speeds significantly affect the extent of tempering. Finally, since the method used here can provide a quantitative understanding of the tempering of martensite and the spatial variation in hardness, it can be used to tailor the microstructure and hardness of heat treatable printed metallic parts.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Performance of Pulsed Thermal Tomography Imaging with Machine Learning-Based Classification of Defects in Additively Manufactured Structures

Additive manufacturing (AM) is an emerging method for cost-efficient fabrication of complex topology nuclear reactor parts from high-strength corrosion resistance alloys, such as stainless steel and Inconel. AM of metallic structures for nuclear energy applications is currently based on laser powder bed fusion (LPBF) process. Some of the challenges with using LPBF method for nuclear manufacturing include the possibility of introducing pores into metallic structures. Integrity of AM structures needs to be evaluated nondestructively because material flaws could lead to premature failures in high temperature nuclear reactor environment. Currently, there exist limited capabilities to evaluate actual AM structures non-destructively. Pulsed Thermal Tomography Imaging (PTT) provides a capability for non-destructive evaluation (NDE) of subsurface defects in arbitrary size structures. The PTT method is based on recording material surface temperature transients with infrared (IR) camera following thermal pulse delivered on material surface with flash light. The PTT method has advantages for NDE of actual AM structures because the method involves one-sided non-contact measurements and fast processing of large sample areas captured in one image. Following initial qualification of an AM component for deployment in a nuclear reactor, a PTT system can also be used for in-service nondestructive evaluation (NDE) applications. In this report, we describe recent progress in enhancing PTT capabilities in detecting and visualizing microscopic defects in metallic specimens. The thermal tomography (TT) algorithm obtains depth reconstructions of spatial effusivity from the data cube of sequentially recorded surface temperatures. However, interpretation of TT images is non-trivial because of blurring of images with increasing depth. To address this challenge, we have developed a deep learning convolutional neural network (CNN) to classify size and orientation subsurface defects in simulated TT images. CNN is trained on a database of TT images created for a set of simulated metallic structures with elliptical subsurface voids. Test of CNN performance demonstrate the ability to classify radii and angular orientation of subsurface defects in TT images. In addition, we have shown that CNN trained on elliptical defects is capable of classifying irregular-shaped defects obtained from scanning electron microscopy (SEM) of stainless steel sections printed with LPBF.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
NASA NTRS1994

Design of an unmanned Martian polar exploration system

The design of an unmanned Martian polar exploration system is presented. The system elements include subsystems for transportation of material from earth to Mars, study of the Martian north pole, power generation, and communications. Early next century, three Atlas 2AS launch vehicles will be used to insert three Earth-Mars transfer vehicles, or buses, into a low-energy transfer orbit. Capture at Mars will be accomplished by aerobraking into a circular orbit. Each bus contains four landers and a communications satellite. Six of the twelve total landers will be deployed at 60 deg intervals along 80 deg N, and the remaining six landers at 5 deg intervals along 30 deg E from 65 deg N to 90 deg N by a combination of retrorockets and parachutes. The three communications satellites will be deployed at altitudes of 500 km in circular polar orbits that are 120 deg out of phase. These placements maximize the polar coverage of the science and communications subsystems. Each lander contains scientific equipment, two microrovers, power supplies, communications equipment, and a science computer. The lander scientific equipment includes a microweather station, seismometer, thermal probe, x-ray spectrometer, camera, and sounding rockets. One rover, designed for short-range (less than 2 km) excursions from the lander, includes a mass spectrometer for mineral analysis, an auger/borescope system for depth profiling, a deployable thermal probe, and charge coupled device cameras for terrain visualization/navigation. The second rover, designed for longer-range (2-5 km) excursions from the lander, includes radar sounding/mapping equipment, a seismometer, and laser ranging devices. Power for all subsystems is supplied by a combination of solar cells, Ni-H batteries, and radioisotope thermoelectric generators. Communications are sequenced from rovers, sounding rockets, and remote sensors to the lander, then to the satellites, through the Deep Space Network to and from earth.

Baldwin, Curt↗
DOE OSTI2025

Toward a Generalizable Prediction Model of Molten Salt Mixture Density with Chemistry‐Informed Transfer Learning

Optimally designing applications of molten salts requires knowledge of their thermophysical properties over a wide range of temperatures and compositions. There exist significant gaps in existing databases and this data can be challenging to experimentally measure due to high temperatures, salt corrosivity, and salt hygroscopicity. Existing databases have been used to create Redlich–Kister (RK) models for mixture density showing improved accuracy with respect to ideal mixing assumptions, but these models require subcomponent data measurements for each new system, therefore lacking generality. In order to address generalizability and data sparsity, a transfer learning procedure is proposed to train deep neural networks (DNNs) using a combination of semi‐empirical relationships (RK), data from the thermophysical arm of the molten salt thermal properties database and universal ab initio properties of component mixtures taken from the joint automated repository for various integrated simulations (JARVIS) classical force‐field inspired descriptors database to predict density in molten salts. Herein, it is shown that DNNs predict molten salt density with an r 2 over 0.99 and a mean absolute percentage error under 1%, outperforming alternative methods.

inorganic materials↗
DOE OSTI2026

Machine learning-enhanced hybrid modeling approach for better identification of a building thermal network model and improved prediction

The gray-box modeling approach, which uses a semi-physical thermal network model, has been widely used in building prediction applications, such as model predictive control (MPC). However, unmeasured disturbances, such as occupants, lighting, and in/exfiltration loads, make it challenging to apply this approach to practical buildings. In this word, we propose a hybrid modeling approach that integrates the gray-box model with a model for unmeasured disturbance. After reviewing several system identification approaches, we systematically designed the unmeasured disturbance model with a model selection process based on statistical tests to make it robust. We generated data based on the building model calibrated by real operational data and then trained the hybrid model for two different weather conditions. The hybrid model approach demonstrates an RMSE reduction of approximately 0.2–0.9 °C and 0.3–2 °C on 1-day ahead temperature prediction compared to the Conventional approach for mild (Berkeley, CA) and cold (Chicago, IL) climates, respectively. In addition, this approach was applied to experimental data obtained from the laboratory building to be used for the MPC application, showing superior prediction performances.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2026

Heat Loss Effects on Emissions in an NH 3 RRQL Combustor

Ammonia (NH 3 ) is a carbon-free energy carrier with an infrastructure for production, storage, and distribution. There is interest in direct NH 3 combustion, but managing pollutant emissions is a key challenge, particularly nitric oxides (NO x ) due to the fuel-bound nitrogen atom, nitrous oxide (N 2 O), which is a potent greenhouse gas, and unburned NH 3 , which is harmful to humans and the environment. Rich staged combustor concepts with extended primary residence times (τ res,primary ), like Rich-Relax- Quick-mix-Lean (RRQL), offer a viable pathway for direct NH 3 combustion with low levels of NO x formation. However, minimizing secondary emissions such as N 2 O and unburned NH 3 and hydrogen (H 2 ) remains a critical challenge. Prior atmospheric-pressure studies have demonstrated that RRQL operation with sufficiently long τ res,primary enables substantial NO x relaxation and promotes NH 3 cracking to H 2 , if heat losses from the relaxation stage are limited. However, the combined influence of elevated pressure and long residence time on RRQL performance has not been explored. The present work examines RRQL operation at pressures up to 5 bar and elevated τ res,primary . Exhaust measurements of NO x , NH 3 , and N 2 O are used to quantify the extent of NO x relaxation and NH 3 cracking under nonadiabatic conditions. To contextualize and quantify the effects of heat losses in the experimental data, chemical reactor networks (CRNs) incorporating prescribed heat loss rates are employed to assess the sensitivity of emissions to thermal losses in the relaxation stage. Collectively, the results demonstrate that management and quantification of heat losses are essential to preserve NO x relaxation and limit NH 3 and N 2 O emissions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Shifts in Evapotranspiration Components During Heatwaves Alter Surface Cooling

Heatwave events significantly alter ecosystem water and energy balance and are often accompanied by extreme surface temperatures. Understanding how surface temperatures during such events are regulated by soil evaporation (E) and vegetation transpiration (T) remains limited due to challenges in partitioning total evapotranspiration (ET). Here, high-frequency turbulence methods are used to partition observed ET at 32 National Ecological Observatory Network sites across the contiguous United States. Heatwaves were defined as at least three consecutive days with daily maximum air temperature exceeding the site-specific 90th percentile of the 2019–2021 record. Across 268 identified events, the T/ET ratio decreased by 32% ± 16% relative to the non-heatwave baseline of 0.65, with greater reductions at lower biomass sites. The T/ET ratio was typically suppressed below non-heatwave conditions during the early and middle stages of the heatwave (first two-thirds of event duration), but was on average higher than non-heatwave baseline levels during late stages (final third) due to extremely low soil evaporation. Of the studied heatwaves, 71% of these had surface temperatures above 38°C in their late stage; however, heatwaves sustaining higher evaporation fluxes (upper tertile of observed fluxes) during the late stage were associated with relative surface temperature anomalies that were on average 45% lower than those of heatwaves with lower evaporation fluxes (lower tertile). The commensurate surface cooling induced by higher transpiration was only 2% during heatwaves, suggesting that transpiration has a limited ability to mitigate extreme surface temperatures. This study allows for improved prediction of ecosystem feedbacks under extreme thermal stress.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Functional Photoresists for Energy Applications. Final Report

Monolithic ultralow-density porous bulk materials have recently attracted much interest due to many emerging applications in the areas of catalysis, energy storage and conversion, and thermal insulation. They are also important components of high energy density (HED) and inertial confinement fusion (ICF) targets. However, despite tremendous progress that has been made in the synthesis of porous materials, deterministic and independent control over microscopic architecture, density and composition remain key issues, and their integration in high precision devices requires cost and time-intensive mechanical machining that not only reduces reproducibility by generating debris but also limits the complexity of the 3D shapes that can be realized. In this project, we overcame these limitations by developing a universal templating capability that provides deterministic and independent control over density, composition, architecture, and macroscopic sample shape. This was achieved by developing the technology to 1) 3D print ultrahigh resolution, ultra-high precision polymeric micro-lattice templates, 2) coat these templates with the desired materials, and 3) removing the template (Fig. 1a). Atomic layer deposition (ALD) provides the atomic scale coating thickness accuracy required for precisely controlling density. While this templating approach had been demonstrated in prior work, limitations in suitable photoresists, 3D print technologies, print design, and template removal techniques did not allow the fabrication of millimeter-sized high-precision parts with sub-micron resolution. To enable this technology, we developed 1) two-photon polymerization (TPP) print designs that enable the fabrication of millimeter-sized, mechanically robust polymeric templates with sub-micron resolution and 2) a continuum level TPP printing simulation capability for additional print design guidance; 3) atomistic models to study photoresist polymerization kinetics and network topography, 4) refractive index matched polymeric and preceramic TPP photoresists, and 5) functional TPP photoresists including porous voxel structures and self-immolative polymer photoresist chemistries; and 6) damage free template removal techniques that enable the fabrication of defect-free high-precision low-density foam components. We also developed a templating approach for pure carbon microlattices with a unique tube-in-tube ligament morphology. As a test platform, we pursued the fabrication of foam liners that promise to further increase the neutron yield in indirect drive ICF experiments by improving implosion symmetry control and coupling between the laser and the deuterium-tritium fuel. This application requires fabrication and integration of a ultra-high precision, millimeter-sized, thin-walled (200-400 micrometer thick), low-density (10-30 mg/cc), high atomic number (high Z) cylindrical foam tube into the gold hohlraum of an indirect drive ICF target (Fig. 1b). While our hohlraum liner test case will mainly find application in HED and ICF experiments, the underlying science will also directly apply to previously developed nanoparticle and additive manufacturing technologies and will advance those techniques as well.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Capsule network-based semantic segmentation model for thermal anomaly identification on building envelopes

Thermography technology is widely used to inspect thermal anomalies in building façade systems. Computer vision-based techniques provide opportunities to autonomously detect such heat anomalies to significantly improve the efficiency of decision-making for building envelope retrofitting and maintenance. Here, in this work, we propose a novel Capsule Network-based deep learning model – CapsLab – that detects and identifies thermal anomalies by semantic segmentation. CapsLab is built based on our proposed prediction-tuning capsule (PT-Capsule) layer. Different from a traditional capsule layer, which consists of part-whole transformation and capsule-routing process, the proposed layer is composed of a prediction and tuning process, which helps decreasing the number of model parameters significantly. While the applicability of traditional Capsule Networks (CapsNets) has been limited to simpler tasks and smaller datasets due to their scalability issue, we can leverage the lightweight of the proposed PT-Capsule layer, and apply it to the semantic segmentation task. In this work, we also employ our previously presented performance metric, referred to as the Anomaly Identification Metric (AIM) (Kakillioglua et al. 2021), to evaluate the segmentation outputs. Traditional performance metrics do not accurately reflect the true performance of the segmentation models in thermal anomaly identification due to the high subjectivity in the annotation process and higher overlap ratio sensitivity of the standard metrics. AIM, on the other hand, is robust to these drawbacks. Experimental results show, both qualitatively and quantitatively, that our proposed segmentation method can effectively segment the thermal anomalies. Specifically, our model provides 9.38% and 13.53% improvements over the baseline model – DeepLabV3+ – based on traditional mIoU score and the AIM score, respectively, while requiring less model parameters and less computation at the same time. In addition, the scores that the AIM metric generates better align with the scores provided by building performance experts.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

Recent Developments at the Raft River Geothermal Field

The Raft River geothermal field, located in Cassia County in southwestern Idaho, is the site of a Department of Energy Enhanced Geothermal System project. U.S. Geothermal, Inc. currently produces about 11 MWe from Precambrian metamorphic rocks. These lie beneath ~5,000 ft of Quaternary and Tertiary volcaniclastic and volcanic deposits. Maximum temperatures range from 271°F to 300°F. Well RRG-9 ST1, the well targeted for stimulation is located approximately 1 mile south of the main bore field. The open hole section of the well, from 5,551 to 5,900 ft MD, consists of Precambrian Elba Quartzite, the stimulation target, granite and minor diabase. Prior to setting the casing acoustic, gamma ray, and density logs were run. After completing the well, a step rate/step down test was conducted. The maximum injection rate achieved was 18 bpm at a wellhead pressure of 1,150 psig. A borehole televiewer run in the open hole section showed evidence of more than eighty fractures. The majority of these fractures trend from N20⁰W to N20°E and dip from 40° to 60°W. Permeable fractures were encountered in the Elba Quartzite at 5,640-5,660 ft MD. Analysis of the injection test indicates that the minimum in-situ principal stress in this zone is 3,050-3,200 psi, corresponding to a fracture gradient of 0.59-0.62 psi/ft. A discrete fracture network model was developed using measured and inferred fracture orientations, distributions and dimensions. A three-phase stimulation program is proposed for RRG-9 ST-1. During the first two stages, water at 140°F, and later 40°F, will be injected to pre-condition and thermally fracture the reservoir. Here, the third stage will consist of a high rate, large volume conventional hydraulic stimulation.

Bradford, Jacob↗
DOE OSTI2023

Demonstration of acoustic monitoring for structural health of microreactors: Through use of neural networks and resonant ultrasound spectroscopy

Nuclear microreactors prioritize modularity and portability and are intended to be a cost-effective technology for non-conventional nuclear markets. As such, the development of microreactors into a safe and feasible solution for energy security applications will necessitate the development of non-destructive technologies to monitor the integrity of inaccessible reactors components during operation. This demonstration applies linear and nonlinear acoustic techniques, in combination with machine learning, to detect and classify mechanical changes (stress and damage) in a test article which are broadly representative of potential operating challenges within a functioning microreactor. All necessary data has been collected for this demonstration, with minor experimental issues identified that can be addressed in follow-on work. Motivated by the expected conditions within a functioning microreactor, we have demonstrated our monitoring techniques on a core-block-like test article using an unstructured excitation source that approximates the noisy acoustic environment expected during reactor operation. At all stress states mechanically applied to the test article, a machine learning model using an artificial neural network was able to classify with 100% accuracy whether a 3D laser vibrometry point measurement was made on an intact or artificially defective test article. Further, model predictions about whether the defect interface was rough or smooth were 95% accurate, indicating the ability of acoustic techniques to recover defect characteristics. Resonant ultrasound spectroscopy (RUS) was also applied to the dataset to provide further quantitative insights about material properties. RUS analysis was ultimately hampered by several minor experimental and data issues, limiting results to certain cases for this demonstration. Last, analysis using nonlinear RUS exhibited sensitivity to changing levels of applied stresses for each intact and defective state. As presented in this demonstration, acoustic monitoring exhibits sensitivity to stress changes, which are of concern due to high thermal gradients expected during startup and operation. Further, our techniques distinguish between measurements made on intact and damaged test articles.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
NASA NTRS2006

NASA Tech Briefs, September 2006

Topics covered include: Improving Thermomechanical Properties of SiC/SiC Composites; Aerogel/Particle Composites for Thermoelectric Devices; Patches for Repairing Ceramics and Ceramic- Matrix Composites; Lower-Conductivity Ceramic Materials for Thermal-Barrier Coatings; An Alternative for Emergency Preemption of Traffic Lights; Vehicle Transponder for Preemption of Traffic Lights; Automated Announcements of Approaching Emergency Vehicles; Intersection Monitor for Traffic-Light-Preemption System; Full-Duplex Digital Communication on a Single Laser Beam; Stabilizing Microwave Frequency of a Photonic Oscillator; Microwave Oscillators Based on Nonlinear WGM Resonators; Pointing Reference Scheme for Free-Space Optical Communications Systems; High-Level Performance Modeling of SAR Systems; Spectral Analysis Tool 6.2 for Windows; Multi-Platform Avionics Simulator; Silicon-Based Optical Modulator with Ferroelectric Layer; Multiplexing Transducers Based on Tunnel-Diode Oscillators; Scheduling with Automated Resolution of Conflicts; Symbolic Constraint Maintenance Grid; Discerning Trends in Performance Across Multiple Events; Magnetic Field Solver; Computing for Aiming a Spaceborne Bistatic- Radar Transmitter; 4-Vinyl-1,3-Dioxolane-2-One as an Additive for Li-Ion Cells; Probabilistic Prediction of Lifetimes of Ceramic Parts; STRANAL-PMC Version 2.0; Micromechanics and Piezo Enhancements of HyperSizer; Single-Phase Rare-Earth Oxide/Aluminum Oxide Glasses; Tilt/Tip/Piston Manipulator with Base-Mounted Actuators; Measurement of Model Noise in a Hard-Wall Wind Tunnel; Loci-STREAM Version 0.9; The Synergistic Engineering Environment; Reconfigurable Software for Controlling Formation Flying; More About the Tetrahedral Unstructured Software System; Computing Flows Using Chimera and Unstructured Grids; Avoiding Obstructions in Aiming a High-Gain Antenna; Analyzing Aeroelastic Stability of a Tilt-Rotor Aircraft; Tracking Positions and Attitudes of Mars Rovers; Stochastic Evolutionary Algorithms for Planning Robot Paths; Compressible Flow Toolbox; Rapid Aeroelastic Analysis of Blade Flutter in Turbomachines; General Flow-Solver Code for Turbomachinery Applications; Code for Multiblock CFD and Heat-Transfer Computations; Rotating-Pump Design Code; Covering a Crucible with Metal Containing Channels; Repairing Fractured Bones by Use of Bioabsorbable Composites; Kalman Filter for Calibrating a Telescope Focal Plane; Electronic Absolute Cartesian Autocollimator; Fiber-Optic Gratings for Lidar Measurements of Water Vapor; Simulating Responses of Gravitational-Wave Instrumentation; SOFTC: A Software Correlator for VLBI; Progress in Computational Simulation of Earthquakes; Database of Properties of Meteors; Computing Spacecraft Solar-Cell Damage by Charged Particles; Thermal Model of a Current-Carrying Wire in a Vacuum; Program for Analyzing Flows in a Complex Network; Program Predicts Performance of Optical Parametric Oscillators; Processing TES Level-1B Data; Automated Camera Calibration; Tracking the Martian CO2 Polar Ice Caps in Infrared Images; Processing TES Level-2 Data; SmaggIce Version 1.8; Solving the Swath Segment Selection Problem; The Spatial Standard Observer; Less-Complex Method of Classifying MPSK; Improvement in Recursive Hierarchical Segmentation of Data; Using Heaps in Recursive Hierarchical Segmentation of Data; Tool for Statistical Analysis and Display of Landing Sites; Automated Assignment of Proposals to Reviewers; Array-Pattern-Match Compiler for Opportunistic Data Analysis; Pre-Processor for Compression of Multispectral Image Data; Compressing Image Data While Limiting the Effects of Data Losses; Flight Operations Analysis Tool; Improvement in Visual Target Tracking for a Mobile Robot; Software for Simulating Air Traffic; Automated Vectorization of Decision-Based Algorithms; Grayscale Optical Correlator Workbench; "One-Stop Shopping" for Ocean Remote-Sensing and Model Data; State Analysis Database Tool; Generating CAHV and CAHVOmages with Shadows in ROAMS; Improving UDP/IP Transmission Without Increasing Congestion; FORTRAN Versions of Reformulated HFGMC Codes; Program for Editing Spacecraft Command Sequences; Flight-Tested Prototype of BEAM Software; Mission Scenario Development Workbench; Marsviewer; Tool for Analysis and Reduction of Scientific Data; ASPEN Version 3.0; Secure Display of Space-Exploration Images; Digital Front End for Wide-Band VLBI Science Receiver; Multifunctional Tanks for Spacecraft; Lightweight, Segmented, Mostly Silicon Telescope Mirror; Assistant for Analyzing Tropical-Rain-Mapping Radar Data; and Anion-Intercalating Cathodes for High-Energy- Density Cells.

Source record↗
DOE OSTI2023

Two-dimensional patterning of mesoscale fibers using acoustophoresis

The performance of functional composites can rely critically on the arrangement of secondary phases; for example, patterned networks of conductive particles can impart anisotropic thermal, electric or ionic conductivity while preserving flexibility in the matrix. We demonstrate the use of standing acoustic waves to generate periodic patterns of short fibers. We extend the range of possible patterns with the first demonstration of both rectangular grids and arrays of octagons interspersed with rectangles. These newly demonstrated patterns are rationalized using theoretical models of acoustic forces and torques on fibers that account for two-dimensional spatial variations arising from applied acoustic fields. The models enable simulations of fiber motion, which are used to (i) map out final fiber positions as a function of initial position and orientation, and (ii) corroborate experiments visualizing fiber motion and final patterns. This approach provides a fast and accurate way to predict emergent fiber patterns as a function of excitation modality and fiber length. The theory and experiments clearly indicate strong coupling between the length of the fibers and the spacing of the acoustic nodes. Furthermore, this coupling is used to estimate reductions in percolation thresholds associated with the ratio of fiber length and acoustic wavelength.

25 ENERGY STORAGE↗
DOE OSTI2023

Packaged Combined Heat and Power Technology Overview and Market Profile

Combined heat and power (CHP), sometimes referred to as cogeneration, is an efficient and clean approach to generating electric power and useful thermal energy onsite from a single fuel source, offering reliable and affordable energy services to businesses and institutions. Furthermore, CHP provides a cost effective opportunity to improve the environmental footprint and resilience of industrial and commercial facilities across the United States. CHP equipment can be custom-engineered or installed as a predesigned and assembled package. A packaged CHP system is a standardized, pre-engineered system that includes all equipment, piping, wiring, and ancillary components to deliver electricity and thermal energy to a host facility with minimal onsite engineering and design time. Packaged CHP systems can be shipped as single or multiple modules with standard interconnections (e.g., fuel; electrical; thermal—hot water, steam, and/or chilled water), which simplifies installation and reduces the costs associated with the project. Most containerized or single packaged CHP system offerings range from 10 kW to 3 MW in capacity. Packaged CHP systems are extending the operating, efficiency, and emissions benefits of CHP to nontraditional markets in commercial, institutional, multifamily, light manufacturing, government, and military applications. These markets tend to be served by smaller systems (less than 5 MW) that are conducive to pre-engineered packaging and/or modularization. Many of these sectors have limited CHP experience and technical resources to adequately evaluate, install, and maintain onsite CHP systems. The introduction of packaged CHP offerings from experienced CHP Packagers and Solution Providers has accelerated CHP adoption, lowered energy costs, reduced emissions, and strengthened energy resilience in these sectors. In 2019, the US Department of Energy (DOE) launched the Packaged CHP eCatalog to promote increased acceptance of efficient, cost-effective CHP in these applications. The Packaged CHP eCatalog is a web-based, searchable platform that hosts DOE-recognized packaged CHP systems with features designed to reduce economic and performance risks for designers, developers, owners, and facility operators interested in installing CHP. DOE established the Packaged CHP Accelerator at the same time to help launch and publicize the eCatalog, and to validate project performance, cost, and installation time of CHP packages across a variety of applications. Accelerator efforts documented installed cost reductions and installation time reductions of more than 20% for packaged CHP systems over 100 kW compared with custom-engineered systems. The Packaged CHP Accelerator and eCatalog established a peer-to-peer network connecting public and private sector partners including utilities, state energy offices, and energy efficiency program administrators interested in promoting cost-effective, efficient CHP systems, Packagers, and Solution Providers. Feedback from these partners, along with input from DOE’s CHP Technical Assistance Partnerships (CHP TAPs), was critical in understanding the current market for packaged CHP technologies, stimulating investment in these technologies, and guiding future directions for packaged CHP systems and their applications. This report provides background on packaged CHP systems, an overview of their benefits, a profile of current packaged CHP installations, and a summary of future market trends; this report is intended for facility owners, project developers, engineers, policymakers, and other stakeholders looking to increase the adoption of efficient, flexible, and resilient packaged CHP systems.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
NASA NTRS1993

Investigation of the role of thermal boundary layer processes in initiating convection under the NASA SPACE Field Program

The current NWS ground based network is not sufficient to capture the dynamic or thermodynamic structure leading to the initiation and organization of air mass moist convective events. Under this investigation we intend to use boundary layer mesoscale models (McNider and Pielke, 1981) to examine the dynamic triggering of convection due to topography and surface thermal contrasts. VAS and MAN's estimates of moisture will be coupled with the dynamic solution to provide an estimate of the total convective potential. Visible GOES images will be used to specify incoming insolation which may lead to surface thermal contrasts and JR skin temperatures will be used to estimate surface moisture (via the surface thermal inertia) (Weizel and Chang, 1988) which can also induce surface thermal contrasts. We will use the SPACE-COHMEX data base to evaluate the ability of the joint mesoscale model satellite products to show skill in predicting the development of air mass convection. We will develop images of model vertical velocity and satellite thermodynamic measures to derive images of predicted convective potential. We will then after suitable geographic registration carry out a pixel by pixel correlation between the model/satellite convective potential and the 'truth' which are the visible images. During the first half of the first year of this investigation we have concentrated on two aspects of the project. The first has been in generating vertical velocity fields from the model for COHMEX case days. We have taken June 19 as the first case and have run the mesoscale model at several different grid resolutions. We are currently developing the composite model/satellite convective image. The second aspect has been the attempted calibration of the surface energy budget to provide the proper horizontal thermal contrasts for convective initiation. We have made extensive progress on this aspect using the FIFE data as a test data set. The calibration technique looks very promising.

Mcnider, Richard T.↗
NASA NTRS1997

The Solar-Stellar Connection (NAG5-6124: SOHO Guest Investigator Program)

The following is a final report from the SOHO Guest Investigator program to use the SUMER far-UV spectrometer to obtain imaging spectroscopy in support of the goals of the so-called "solar-stellar connection." In particular, a major emphasis was utilization of the long-slit time-resolved maps of the solar surface in bright far-UV emission lines to deduce how particular aspects of the temporally and spatially averaged line profiles trace back to individual structural features of the magnetically disturbed outer atmosphere; to help interpret the unresolved line profiles from high quality stellar observations (say, with the Space Telescope Imaging Spectrograph). The researchers served two tours of duty in the SOHO Operations Center as SUMER planners, during which time we conducted an extensive series of observing programs. These can be divided into three general categories: surface mapping, translimb spectroscopy, and active region diagnostics. We have analyzed some of the large volumes of data to the point where we have presented them in poster papers, and in invited papers at national and international meetings. Listed below are the titles of the preliminary publications we have written, including brief abstracts to indicate the main results. (1) Chromospheric structure and Dynamics-- Observations -- The chromosphere is a highly structured dynamic 'layer' of the solar outer atmosphere. Here, not only are the effects of mechanical heating first evident (moving upward in altitude from the deep photosphere), but also the amount of nonradiative energy deposited is far greater than in the albeit much hotter overlying transition region and corona. Further, the chromosphere is by far the thickest zone of the solar atmosphere with respect to the pressure scale height. A major goal of stellar astrophysics is to understand how the chromosphere is heated and why it adopts its peculiar structure. A cursory examination of solar filtergrams and high-resolution movies demonstrates that much of the chromospheric "action" must be occurring on fine spatial scales and short times; particularly in the cell interior transient brightenings, but also in the longer-lived network fragments. That regime of investigation is far removed from what one usually associates with "synoptic" measurements. Nevertheless, synoptic observations of chromospheric indices, filtergrams, and globally-averaged profile parameters not only can provide important insight concerning the crucial role of the cycle-variable part of the solar magnetic field; but they also can forge a key link with analogous measurements of the stars, where often the phenomena can be significantly exaggerated from the solar case, but high spatial resolution reconnaissance is not even a remote possibility. In addition to discussing the synoptic aspects of chromospheric structure and dynamics, I summarized new insights into the general problem of the solar chromosphere that have been obtained recently with the SUMER far-ultraviolet spectrometer on SOHO. (2) CO and the Temperature Structure of the Solar Atmosphere -- The surface layers of the Sun provide a crucial boundary condition for many of the processes that occur in the deep interior. The stratification of the outer solar atmosphere once was thought to be well understood. However, studies of thermally sensitive molecular absorptions in the infrared revealed puzzling anomalies. Strong lines of the CO fundamental vibration-rotation bands near 5 microns showed very cool temperatures at the extreme limb, and remarkable off-limb emissions extending well into the supposedly hot chromosphere. The conflicting pictures of the photosphere/chromosphere interface, from the widely separated wavelength regimes, has raised suspicions that those "layers" of the atmosphere are much more inhomogeneous than previously suspected. One proposal is that the low chromosphere is dominated by cool gas, the "COmosphere," which is threaded by a network of persistent small-scale hot magnetic filaments and occasionally disrupted by localized acoustic disturbances. The COmosphere is capped by the merged fields of the network elements in the chromospheric "canopy." (3) Translimb Spectroscopy with SOHO/SUMER -- We have used SUMER to obtain deep exposures of the 1300-1400 A spectrum, at the extreme limb and off-limb. Previous "translimb" studies in the thermal infrared had revealed remarkable extensions of cold material (T is approximately equal to 3000 K)-traced by carbon monoxide emission lines-into the heart of the hot chromosphere. A main objective of our program was to search for corresponding far-UV signatures of the "thermally-bifurcated" low chromosphere; for example, radiatively fluoresced emissions of the CO A-X 4th-positive system (collisional excitation would be negligible in cold gas). We conducted two separate observing programs with SUMER. Both made use of the 1 inch-diameter circular aperture, translated across the limb in the minimum motor step increments of 0."375, along the central meridian in the Northern polar coronal hole. The first program executed for nine hours beginning 19UT 25 Oct 1996. The full wavelength range was 1340-1400 A. It was recorded in two overlapping segments, placing key regions of the spectrum alternately on the KBr and bare parts of the detector, to help isolate 2nd-order features. Each segment was integrated for 500 s, and 32 pairs were obtained to span a 12" swath centered on the optical limb. The second program was conducted 00-09UT 01 Dec 1996. It consisted of a single wavelength setting (1300-1340 A) with exposure time 500 s, but twice the spatial coverage of the earlier series: 64 steps, for a total displacement of 24". The strong chromospheric resonance lines of atomic oxygen (1302-1305 A) and ionized carbon (1334-1335 A) were observed on the bare part of the MCP camera.

Ayres, Thomas R.↗
DOE OSTI2026

Sub-melt nanosecond pulsed-laser induced densification and strain-field relaxation in single-crystal diamond

Dislocations and polishing-induced defect networks in synthetic diamond introduce local strain fields and broaden Raman features, limiting performance in optical, thermal, and electronic applications. Laser annealing is emerging as a promising approach to repair surface and near-surface defects in diamond without entering the melt regime, yet surface densification, defect-state modification, and associated structural changes have not been well quantified. In this work, we show that sub-melt nanosecond pulsed-laser annealing (PLA) induces near-surface densification and defect-mediated strain relaxation in single-crystal Chemical Vapor Deposition (CVD) diamond. Single- and two-pulse PLA were applied, and structural evolution was quantified using co-registered ISO 25,178 white-light interferometry, depth-resolved Raman spectroscopy, and cross-sectional STEM with geometric phase analysis (GPA). Across a 5 × 6 grid (n = 30), responsive regions exhibit large reductions in local slope (Sdq 45–65%), developed area (Sdr 60–90%), height spread (Sp, Sz 30–65%), void volume (Vv 57–60%), and roughness amplitude (Sa, Sq 48–57%), consistent with densification of ∼4–6.5 nm. Raman profiling shows narrowing of the diamond line and improved spectral uniformity to depths of ∼2–3 μm. Given that the Raman probing depth significantly exceeds the densified layer thickness, this response is interpreted as consistent with long-range strain-field redistribution originating from the near-surface region. STEM-GPA strain maps further support this interpretation, showing smoother strain fields, suppressed hotspots, and redistribution of localized strain concentrations following PLA. These results are consistent with defect-mediated strain relaxation and densification-driven modification of the near-surface energy state. The approach provides a scalable pathway for improving near-surface structural quality in diamond relevant to electronic, photonic, and quantum applications.

Areal surface metrology (ISO 25,178)↗
DOE OSTI2024

Embedding Neural Thermal Scattering (NeTS) Modules in SERPENT for Higher Fidelity Advanced Reactor Analysis

When a neutron born in fission thermalizes to the order of $k$ $B$ $T$, it’s de-Broglie wavelength and energy approach the order of inter-atomic spacing and elementary lattice oscillations, respectively. $S$($a,β,t$) or the scattering law, uuantify these temperature-dependent crystallographic contributions to total cross section (or reaction rate). In a Monte Carlo analysis, cumulative distribution functions (CDFs) of $S$($a,β,t$) are loaded to memory from “A Compact ENDF” (ACE) files for stochastically selecting thermal scattered neutron trajectories. In this work, novel neural thermal scattering (NeTS) modules for $S$($a,β,t$) CDFs are designed, trained, serialized and embedded within SERPENT using Python’s limited C-API for on-the-fly deployment of crystalline graphite $S$($a,β,t$) sampling. Torchscript tracing and Numba just-in-time (JIT) compilation streamline neural inference on NVIDIA GPUs with CUDA libraries. Demonstrations of bare sphere thermalization of fast and thermal sources show excellent agreement between embedded NeTS in SERPENT and MCNP. With an explicit model of the reactor, NeTS can predict on-the-fly changes in TREAT neutron spectra as a function of local temperature, which can serve to improve transient and accident predictions in a multiphysics analysis framework. This framework can be further extended to account on-the-fly for changes in local graphitic microstructure to scattering cross sections, and outlines a novel coupling of modern machine learning with state-of-the-art reactor physics methods.

97 MATHEMATICS AND COMPUTING↗