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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
NASA NTRS2001

The Interaction Between Dynamics and Chemistry of Ozone in the Set-up Phase of the Northern Hemisphere Polar Vortex

The morphology and evolution of the stratospheric ozone (O3) distribution at high latitudes in the Northern Hemisphere (NH) are examined for the late summer and fall seasons of 1999. This time period sets the O3 initial condition for the SOLVE/THESEO field mission performed during winter 1999-2000. In situ and satellite data are used along with a three-dimensional model of chemistry and transport (CTM) to determine the key processes that control the distribution of O3 in the lower-to-middle stratosphere. O3 in the vortex at the beginning of the winter season is found to be nearly constant from 500 to above 800 K with a value at 3 ppmv +/- approx. 10%. Values outside the vortex are up to a factor of 2 higher and increase significantly with potential temperature. The seasonal time series of data from POAM shows that relatively low O3 mixing ratios, which characterize the vortex in late fall, are already present at high latitudes at the end of summer before the vortex circulation sets up. Analysis of the CTM output shows that the minimum O3 and increase in variance in late summer are the result of: 1) stirring of polar concentric O3 gradients by nascent wave-driven transport, and 2) an acceleration of net photochemical loss with decreasing solar illumination. The segregation of low O3 mixing ratios into the vortex as the circulation strengthens through the fall suggests a possible feedback role between O3 chemistry and the vortex formation dynamics. Trajectory calculations from O3 sample points early in the fall, however, show only a weak correlation between initial O3 mixing ratio and potential vorticity later in the season consistent with order-of-magnitude calculations for the relative importance of O3 in the fall radiative balance at high latitudes. The possible connection between O3 chemistry and the dynamics of vortex formation does suggest that these feedbacks and sensitivities need to be better understood in order to make confident predictions of the recovery of NH O3.

Kawa, S. R.↗
DOE OSTI2020

Investigation of Superluminescent Diodes for Smart Lighting Systems. Final Report

The solid-state lighting ecosystem has evolved very rapidly over the last few years, with significant improvements in the technical performance of light-emitting diodes (LEDs) and the commoditization of LED-based lighting fixtures. As the performance of conventional lighting products begins to saturate, there is growing market interest in “Lighting as a Service” applications that will leverage advanced systems to impart new functionalities to lighting and improve energy efficiency, human health, and productivity. These “Smart Lighting” systems will include high-performance light sources, specialized sensors, and dynamic controls to deliver high quality, energy efficient, color tunable lighting with customized spatial light delivery and integrated visible light communication capability. To achieve these capabilities, smart lighting systems will place greater demands on the performance of light sources. Highly efficient sources with additional functionalities compared to conventional LEDs, such as small form factor, large modulation bandwidth, and spatially coherent output beams, will be required. While laser diodes have been proposed as potential sources for smart lighting systems, they also exhibit several properties that pose challenges, such as temporal coherence, extremely high spatial coherence, and ultra-narrow linewidths. To address these issues, we propose an investigation of an alternative device architecture known as a superluminescent diode (SLD). SLDs are similar in form to ridge laser diodes and share many of the same characteristics, such as stimulated emission operation, spatially coherent output, small form factor, and the potential for large modulation bandwidth. However, the operating principle for SLDs is distinct from laser diodes in that SLDs lack a strong cavity feedback mechanism, resulting in spatially coherent but temporally incoherent light output. Thus, SLDs may address the issues with laser diodes for lighting, while simultaneously maintaining some of the desirable characteristics of both laser diodes and LEDs. The objectives of this proposal are to design, grow, and fabricate blue (450 nm) SLDs on polar c-plane and nonpolar m-plane free-standing GaN substrates, and to evaluate their potential as sources in smart lighting systems through basic device characterization and detailed investigations of their efficiency droop and modulation bandwidth. The primary scientific aims of this work are to understand the fundamental role of optical gain in the superluminescent (non-lasing) regime on efficiency droop and modulation bandwidth in III-nitride emitters and to understand the effects of higher optical gain on SLD performance by comparing polar c-plane and nonpolar m-plane SLDs. The University of New Mexico (UNM) will collaborate with Sandia National Laboratories (SNL) and the Center for Integrated Nanotechnologies to design, fabricate, grow, and characterize the SLDs. UNM will perform the design and epitaxial growth, while SNL will focus on the fabrication and device characterization. The novelty of the proposed work includes the first comprehensive theoretical and experimental investigations of efficiency droop and the first investigation of modulation bandwidth in GaN-based emitters operating in the superluminescent regime. Moreover, the comparison of c-plane and m-plane SLDs will enable the first analysis of the effects of higher optical gain on the device performance. The development of high-performance GaN-based SLDs may enable efficiency gains and improved functionality in next-generation smart lighting systems.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS2020

Dynamic IT Security Database and Analytics for Launch Control Systems Software

During the Summer 2020 session, I worked with intern Destani S. Van Arsdalen of EGS Software. Together, we co-created a tool to aid the dynamic investigation, updated over time,of the security compliance of LCS COTS and open source software. We originally planned touse spreadsheet software for management and analysis, but through this exploratoryproject, chose to use Python and JSON after receiving feedback on our project’s current anddesired capabilities at that time.At first, the project was solely designed to help on-board new COTS software, based on aquestionnaire that could be filled out for each software package. This, combined with usingthe spreadsheet application’s web-query capabilities to fetch information from the NVD,allowed presentation and analytics cells to automatically populate as elements of themanually-filled questionnaire changed. While this system was promising, we decided tochange technologies for a few reasons. In the spreadsheet, single cells could not hold complexdata like arrays and objects. The automatic population of cells and dynamic updates made itdifficult to manage and add new features. And finally, it had limited extensibility sinceadding new software required significant understanding of how both the spreadsheet wasconstructed, and the more obscure, proprietary scripting languages packaged with it.The pivot to a standard computer science database language of JSON, aided by thescripting capabilities of Python, greatly helped to improve the project’s functionality. First,and most importantly, the script’s import and analysis of database data is easilyreproducible. Additional data analysis can be modularly added without requiringmodification of the script and is capable of routine scheduling. The revised process can besplit into three parts. First, the conversion of LCS asset and software documentation into theJSON hierarchical database format. Second, the merging of this database with the NVD,forming a new data structure, using CPEs of the CVE object as a linking element betweenthem. And third, the automatically performed analytics and analysis of the combined data,in a modular and extensible format, to produce better informed business decisions. The outputted graphs, for example, are automatically generated by the Python script inconnection with the combined database. This allows updated graphs and any analytics to be re-rendered automatically following updates to the LCS’s initial asset documentation. Afinal report can then be programmatically and easily constructed from these sources to allow fully reproducible metrics for heavily evidenced risk management decisions.

it↗
NASA NTRS1991

Adaptive control of interface by temperature and interface profile feedback in transparent multi-zone crystal growth furnace

The objective of this research is to control the dynamics of multizone programmable crystal growth furnaces. Due to the inevitable heat exchange among different heating zones and the transient nature of the process, the dynamics of multizone furnaces is time varying, distributed, and therefore complex in nature. Electrical power to heating zones and the translational speed of the ampoule are employed as inputs to control the dynamics. Structural properties of the crystal is the ultimate aim of this adaptive control system. These properties can be monitored in different ways. Following an order of complexity, these may include: (1) on line measurement of the material optical properties such as the refractive index of crystal; (2) on line x-ray imaging of the interface topology; (3) on line optical quantification of the interface profile such as the determination of concavity or convexity of the interface shape; and (4) on line temperature measurement at points closest to the material such as measurements of the ampoule's outside and inside surface temperatures. The research performed makes use of the temperature and optical measurements, specified in (3) and (4) as the outputs of furnace dynamics. However, if the instrumentation is available, the proposed control methodology can be extended to the measurements listed in (1) and (2).

Batur, Celal↗
NASA NTRS2000

The Life Cycle Application of Intelligent Software Modeling for the First Materials Science Research Rack

Marshall Space Flight Center (MSFC) has been funding development of intelligent software models to benefit payload ground operations for nearly a decade. Experience gained from simulator development and real-time monitoring and control is being applied to engineering design, testing, and operation of the First Material Science Research Rack (MSRR-1). MSRR-1 is the first rack in a suite of three racks comprising the Materials Science Research Facility (MSRF) which will operate on the International Space Station (ISS). The MSRF will accommodate advanced microgravity investigations in areas such as the fields of solidification of metals and alloys, thermo-physical properties of polymers, crystal growth studies of semiconductor materials, and research in ceramics and glasses. The MSRR-1 is a joint venture between NASA and the European Space Agency (ESA) to study the behavior of different materials during high temperature processing in a low gravity environment. The planned MSRR-1 mission duration is five (5) years on-orbit and the total design life is ten (IO) years. The MSRR-1 launch is scheduled on the third Utilization Flight (UF-3) to ISS, currently in February of 2003). The objective of MSRR-1 is to provide an early capability on the ISS to conduct material science, materials technology, and space product research investigations in microgravity. It will provide a modular, multi-user facility for microgravity research in materials crystal growth and solidification. An intelligent software model of MSRR-1 is under development and will serve multiple purposes to support the engineering analysis, testing, training, and operational phases of the MSRR-1 life cycle development. The G2 real-time expert system software environment developed by Gensym Corporation was selected as the intelligent system shell for this development work based on past experience gained and the effectiveness of the programming environment. Our approach of multi- uses of the simulation model and its intuitive graphics capabilities is providing a concurrent engineering environment for rapid prototyping and development. Operational schematics of the MSRR-1 electrical, thermal control, vacuum access, and gas supply systems, and furnace inserts are represented graphically in the environment. Logic to represent first order engineering calculations is coded into the knowledge base to simulate the operational behavior of the MSRR-1 systems. An example of engineering data provided includes electrical currents, voltages, operational power, temperatures, thermal fluid flow rates. pressures, and component status indications. These type of data are calculated and displayed at appropriate instrumentation points, and the schematics are animated to reflect the simulated operational status of the MSRR-1. The software control functions are also simulated to represent appropriate operational behavior based on automated control and response to commands received by the crew or ground controllers. The first benefit of this simulation environment is being realized in the high fidelity engineering analysis results from the electrical power system G2 model. Secondly, the MSRR-1 simulation model will be embedded with a hardware mock-up of the MSRR-1 to provide crew training on MSRR-1 integrated payload operations. G2 gateway code will output the simulated instrumentation values, termed as telemetry, in a flight-like data stream so that the crew has realistic and accurate simulated MSRR-1 data on the flight displays which will be designed for crew use. The simulation will also respond appropriately to crew or ground initiated commands, which will be part of normal facility operations. A third use of the G2 model is being planned; the MSRR-1 simulation will be integrated with additional software code as part of the test configuration of the primary onboard computer, or Master Controller, for MSRR-1. We will take advantage of the G2 capability to simulate the flight like data stream to test flight software responses and behavior. A fourth use of the G2 model will be to train the Ground Support Personnel that will monitor the MSRR-1 systems and payloads while they are operating aboard the ISS. The intuitive, schematic based environment will provide an excellent foundation for personnel to understand the integrated configuration and operation of the MSRR-1, and the anticipated telemetry feedback based on operational modes of the equipment. Expert monitoring features will be enhanced to provide a smart monitoring environment for the operators. These features include: (1) Animated, intuitive schematic-based displays which reflect telemetry values, (1) Real-time plotting of simulated or incoming sensor values, (3) High/Low exception monitoring for analog data, (4) Expected state monitoring for discrete data, (5) Data trending, (6) Automated malfunction procedure execution to diagnose problems, (7) Look ahead capability to planned MSRR-1 activities in the onboard timeline. And finally, the logic to calculate telemetry values will be deactivated, and the same environment will interface to the incoming data for the real-time telemetry stream to schematically represent the onboard hardware configuration. G2 will be the foundation for the real-time monitoring and control environment. In summary, our MSRR-1 simulation model spans many elements of the life cycle development of this project: Engineering Analysis, Test and Checkout, Training of Crew and Ground Personnel, and Real-time monitoring and control. By utilizing the unique features afforded by an expert system development environment, we have been able to synergize a powerful tool capable of addressing our project needs at every phase of project development.

Rice, Amanda↗
NASA NTRS2004

Active Suppression of Instabilities in Engine Combustors

A method of feedback control has been proposed as a means of suppressing thermo-acoustic instabilities in a liquid- fueled combustor of a type used in an aircraft engine. The basic principle of the method is one of (1) sensing combustor pressure oscillations associated with instabilities and (2) modulating the rate of flow of fuel to the combustor with a control phase that is chosen adaptively so that the pressure oscillations caused by the modulation oppose the sensed pressure oscillations. The need for this method arises because of the planned introduction of advanced, lean-burning aircraft gas turbine engines, which promise to operate with higher efficiencies and to emit smaller quantities of nitrogen oxides, relative to those of present aircraft engines. Unfortunately, the advanced engines are more susceptible to thermoacoustic instabilities. These instabilities are hard to control because they include large dead-time phase shifts, wide-band noise characterized by amplitudes that are large relative to those of the instabilities, exponential growth of the instabilities, random net phase walks, and amplitude fluctuations. In this method (see figure), the output of a combustion-pressure sensor would be wide-band-pass filtered and then further processed to generate a control signal that would be applied to a fast-actuation valve to modulate the flow of fuel. Initially, the controller would rapidly take large phase steps in order to home in, within a fraction of a second, to a favorable phase region within which the instability would be reduced. Then the controller would restrict itself to operate within this phase region and would further restrict itself to operate within a region of stability, as long as the power in the instability signal was decreasing. In the phase-shifting scheme of this method, the phase of the control vector would be made to continuously bounce back and forth from one boundary of an effective stability region to the other. Computationally, this scheme would be implemented by the adaptive sliding phaser averaged control (ASPAC) algorithm, which requires very little detailed knowledge of the combustor dynamics. In the ASPAC algorithm, the power of the instability signal would be calculated from the wide-bandpass- filtered combustion-pressure signal and averaged over a period of time (typically of the order of a few hundredths of a second) corresponding to the controller updating cycle [not to be confused with the controller sampling cycle, which would be much shorter (typically of the order of 10(exp -4) second)].

Kopasakis, George↗
NASA NTRS2002

Limb neurovascular control during altered otolithic input in humans

Head-down rotation (HDR), which activates the vestibulosympathetic reflex, increases leg muscle sympathetic nerve activity (MSNA) and produces calf vasoconstriction with no change in either cardiac output or arterial blood pressure. Based on animal studies, it was hypothesized that differential control of arm and leg MSNA explains why HDR does not alter arterial blood pressure. Fifteen healthy subjects were studied. Heart rate, arterial blood pressure, forearm and calf blood flow, and leg MSNA responses were measured during HDR in these subjects. Simultaneous recordings of arm and leg MSNA were obtained from five of the subjects. Forearm and calf blood flow, vascular conductances, and vascular resistances were similar before HDR, as were arm and leg MSNA. HDR elicited similar significant increases in leg (Delta 6 +/- 1 bursts min(-1); 59 +/- 16 % from baseline) and arm MSNA (Delta 5 +/- 1 bursts min(-1); 80 +/- 28 % from baseline). HDR significantly decreased calf (-19 +/- 2 %) and forearm vascular conductance (-12 +/- 2 %) and significantly increased calf (25 +/- 4 %) and forearm vascular resistance (15 +/- 2 %), with ~60 % greater vasoconstriction in the calf than in the forearm. Arterial blood pressure and heart rate were not altered by HDR. These results indicate that there is no differential control of MSNA in the arm and leg during altered feedback from the otolith organs in humans, but that greater vasoconstriction occurs in the calf than in the forearm. These findings indicate that vasodilatation occurs in other vascular bed(s) to account for the lack of increase in arterial blood pressure during HDR.

Non-NASA Center↗
DOE OSTI2022

Non-growing Season Plant Nutrient Uptake Controls Arctic Tundra Vegetation Composition: Modeling Archive

This Modeling Archive is in support of a NGEE-Arctic publication: Riley et al. (2021) “Non-growing season plant nutrient uptake controls Arctic tundra vegetation composition under future climate” (Riley et al., 2021). The dataset contains “ecosys” model outputs reported in Riley et al. (2021) that examines the role of non-growing season (NGS) nutrient dynamics on 21st century vegetation composition. The study highlighted the importance of these nutrient dynamics on the emergent plant functional type distributions, focusing on their role in shrub expansion. The study showed that ignoring NGS nutrient dynamics led to a dramatic under-prediction of shrub expansion by year 2100, motivating the need to include these processes in Earth System Models. Included are modeled net primary production (NPP) and nitrogen (N) uptake for two scenarios: (1) baseline and (2) no NGS N uptake. The output is provided (1) at 25 km resolution across the North American tundra; (2) for years 2012 through 2100; and (3) PFT-specific. Dataset contains 20 NetCDF files in a zip file and one pdf.The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy’s Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy’s Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2007

Noise-Canceling Helmet Audio System

A prototype helmet audio system has been developed to improve voice communication for the wearer in a noisy environment. The system was originally intended to be used in a space suit, wherein noise generated by airflow of the spacesuit life-support system can make it difficult for remote listeners to understand the astronaut s speech and can interfere with the astronaut s attempt to issue vocal commands to a voice-controlled robot. The system could be adapted to terrestrial use in helmets of protective suits that are typically worn in noisy settings: examples include biohazard, fire, rescue, and diving suits. The system (see figure) includes an array of microphones and small loudspeakers mounted at fixed positions in a helmet, amplifiers and signal-routing circuitry, and a commercial digital signal processor (DSP). Notwithstanding the fixed positions of the microphones and loudspeakers, the system can accommodate itself to any normal motion of the wearer s head within the helmet. The system operates in conjunction with a radio transceiver. An audio signal arriving via the transceiver intended to be heard by the wearer is adjusted in volume and otherwise conditioned and sent to the loudspeakers. The wearer s speech is collected by the microphones, the outputs of which are logically combined (phased) so as to form a microphone- array directional sensitivity pattern that discriminates in favor of sounds coming from vicinity of the wearer s mouth and against sounds coming from elsewhere. In the DSP, digitized samples of the microphone outputs are processed to filter out airflow noise and to eliminate feedback from the loudspeakers to the microphones. The resulting conditioned version of the wearer s speech signal is sent to the transceiver.

Seibert, Marc A.↗
DOE OSTI2026

Data and scripts associated with a manuscript modeling microbial regulation of priming effects

This data package is associated with the publication “Modeling Microbial Regulatory Feedback in Organic Matter Decomposition Identifies Copiotrophic Traits as Key Drivers of Positive Priming” published as a preprint on BioRXiv by Ahamed et al. (2026); https://doi.org/10.1101/2024.08.11.607483. The package contains MATLAB scripts and saved simulation outputs used to implement a cybernetic model of microbial regulation during complex organic matter (OM) decomposition governing priming effects. It includes models of (i) single microbial functional groups (copiotrophic or oligotrophic degraders) and (ii) binary consortia composed of degraders and non-degraders with contrasting or common growth traits. Simulation results were generated using Monte Carlo analyses, with randomized key model parameters across a range of environmental mixing fractions of complex and labile OM. The dataset was created to provide a transparent and reusable computational framework for systematically exploring how microbial growth traits, metabolic regulation, and community composition influence OM decomposition dynamics and priming effects. For details on how to navigate data packages generated by this project, see https://data.ess-dive.lbl.gov/portals/PNNLRiverCorridorSFA/About. In addition to a readme, this data package also includes a file-level metadata (FLMD) file that describes each file and a data dictionary (DD) that describes the variable definitions. This package includes: (1) annotated MATLAB code implementing the system of ordinary differential equations and cybernetic control laws; (2) saved output files containing data (e.g., biomass, substrates, enzyme levels, priming metrics); and (3) scripts for processing saved outputs and regenerating figures. Specifically, the data package contains three main MATLAB scripts: runPrimingModel.m, runPlotData.m, and runPlotSuppFigS1.m, along with this readme and supporting documentation. Users should begin with runPrimingModel.m, which contains the annotated code implementing the system of ordinary differential equations and cybernetic control laws. This script runs the Monte Carlo simulations of microbial OM decomposition and allows users to modify microbial trait definitions, adjust parameter distributions, or define new community configurations. Simulation outputs are automatically saved as .mat files in the folder named SavedData, which stores all pre-generated results included in this package. The second script, runPlotData.m, reads files from the SavedData folder and processes them to regenerate the figures presented in the manuscript. The third script, runPlotSuppFigS1.m, specifically generates Figure S1 in the Supplementary Material of the manuscript. The package also includes the aforementioned files in non-proprietary .txt format. If users intend to use them, they should first save the files in their respective .m or .mat formats prior to execution in MATLAB.

Biomass concentration↗
NASA NTRS2007

Electro-Optical Modulator Bias Control Using Bipolar Pulses

An improved method has been devised for controlling the DC bias applied to an electro-optical crystal that is part of a Mach-Zehnder modulator that generates low-duty-cycle optical pulses for a pulse-position modulation (PPM) optical data-communication system. In such a system, it is desirable to minimize the transmission of light during the intervals between pulses, and for this purpose, it is necessary to maximize the extinction ratio of the modulator (the ratio between the power transmitted during an "on" period and the power transmitted during an "off" period). The present method is related to prior dither error feedback methods, but unlike in those methods, there is no need for an auxiliary modulation subsystem to generate a dithering signal. Instead, as described below, dither is effected through alternation of the polarity of the modulation signal. The upper part of Figure 1 schematically depicts a Mach-Zehnder modulator. The signal applied to the electro-optical crystal consists of a radio-frequency modulating pulse signal, VRF, superimposed on a DC bias Vbias. Maximum extinction occurs during the off (VRF = 0) period if Vbias is set at a value that makes the two optical paths differ by an odd integer multiple of a half wavelength so that the beams traveling along the two paths interfere destructively at the output beam splitter. Assuming that the modulating pulse signal VRF has a rectangular waveform, maximum transmission occurs during the "on" period if the amplitude of VRF is set to a value, V , that shifts the length of the affected optical path by a half wavelength so that now the two beams interfere constructively at the output beam splitter. The modulating pulse signal is AC-coupled from an amplifier to the electro-optical crystal. Sometimes, two successive pulses occur so close in time that the operating point of the amplifier drifts, one result being that there is not enough time for the signal level to return to ground between pulses. Also, the difference between the optical-path lengths can drift with changes in temperature and other spurious effects. The effects of both types of drift are suppressed in the present method, in which one takes advantage of the fact that when Vbias is set at the value for maximum extinction, equal-magnitude positive and negative pulses applied to the electro-optical crystal produce equal output light pulses.

Farr, William↗
NASA NTRS2003

System for Centering a Turbofan in a Nacelle During Tests

A feedback position-control system has been developed for maintaining the concentricity of a turbofan with respect to a nacelle during acoustic and flow tests in a wind tunnel. The system is needed for the following reasons: Thermal and thrust loads can displace the fan relative to the nacelle; In the particular test apparatus (see Figure 1), denoted as a rotor-only nacelle (RAN), the struts, vanes, and other stator components of a turbofan engine that ordinarily maintain the required concentricity in the face of thermal and thrust loads are not present; and The struts and stator components are not present because it is necessary to provide a flow path that is acoustically clean in the sense that the measured noise can be attributed to the fan alone. The system is depicted schematically in Figure 2. The nacelle is supported by two struts attached to a two-axis traverse table located outside the wind-tunnel wall. Two servomotors acting through 100:1 gearboxes drive the table along the Y and Z axes, which are perpendicular to the axis of rotation. The Y and Z components of the deviation from concentricity are measured by four laser displacement sensors mounted on the nacelle and aimed at reflective targets on the center body, which is part of the fan assembly. The outputs of the laser displacement sensors are digitized and processed through a personal computer programmed with control software. The control output of the computer commands the servomotors to move the table as needed to restore concentricity. Numerous software and hardware travel limits and alarms are provided to maximize safety. A highly ablative rub strip in the nacelle minimizes the probability of damage in the event that a deviation from concentricity exceeds the radial clearance [<0.004 in. (<0.1 mm)] between the inner surface of the nacelle and the tips of the fan blades. To be able to prevent an excursion in excess of the tip clearance, the system must be accurate enough to control X and Y displacements to within 0.001 in. (.0.025 mm). One characteristic essential to such accuracy is sufficient rigidity in the mechanical components of the system to prevent excitation of vibrations in the strut/ nacelle subsystem. The need for such a high degree of accuracy prompted a comprehensive analysis of sources of measurement and control errors, followed by rigorous design efforts to minimize these errors. As a result, the design of the system incorporates numerous improvements in hardware, software, and operational procedures.

Cunningham, Cameron C.↗
DOE OSTI2026

Data and scripts associated with a manuscript analyzing ELM-FATES parameter sensitivity under pre-fire and postfire scenarios using machine learning

NOTE: The manuscript associated with this data package is currently in review. The data may be revised based on reviewer feedback. Upon manuscript acceptance, this data package will be updated with the final dataset and additional metadata. This data package is associated with the manuscript “Fire Severity-Dependent Shifts in Vegetation Parameter Sensitivity: A Pre- and Post-Fire Analysis Using ELM-FATES and Explainable AI” submitted to Journal of Advances in Modeling Earth Systems (Zahura et al. 2026). The study examines vegetation physiological parameters controlling pre-fire and post-fire vegetation dynamics. To support this analysis, 73 vegetation parameters in Functionally Assembled Terrestrial Ecosystem Simulator (FATES) (Fisher et al., 2018) , which is coupled with E3SM (Energy Exascale Earth System Model) land model (ELM, ELM-FATES), were perturbed using a Sobol sequence to generate 1,024 ensemble members for two plant functional types: needleleaf evergreen extratropical trees (NEET) and C3 grass. Simulations were conducted for the pre-fire period (2016) and post-fire period (2018–2023). Burn severity was represented by modifying the Nesterov index in FATES to 75,000, 150,000, and 300,000 for low, moderate, and high severity, respectively. A no-fire scenario was also included. Simulations were performed for 16 grid cells in the American River Watershed across different burn severities and plant functional types. XGBoost (eXtreme Gradient Boosting) models were trained using the parameter ensembles and ELM-FATES-simulated outputs, including leaf area index (LAI), gross primary productivity (GPP), aboveground biomass, vegetation evaporation, transpiration, and soil evaporation. Models were trained separately for each year and burn severity, followed by SHAP (SHapley Additive exPlanations) analysis to identify changes in dominant parameters after fire disturbance. For details on how to navigate data packages generated by this project, see https://data.ess-dive.lbl.gov/portals/PNNLRiverCorridorSFA/About. The data package contains the ELM-FATES simulation data. The scripts and data related to the analysis will be added later. The inputs and outputs from ELM-FATES are inside the “FATES” folder. “FATES_domain_surface” contains the domain and surface netcdfs that were used to run ELM-FATES in the study area. “FATES_parameters” contains the 1024 ensembles that were generated using Sobol sequence. “FATES_outputs” folder contains ELM-FATES simulated variables. All files are .csv and .nc (NetCDF).

Aboveground biomass↗
NASA NTRS2010

Wavefront Control and Image Restoration with Less Computing

PseudoDiversity is a method of recovering the wavefront in a sparse- or segmented- aperture optical system typified by an interferometer or a telescope equipped with an adaptive primary mirror consisting of controllably slightly moveable segments. (PseudoDiversity should not be confused with a radio-antenna-arraying method called pseudodiversity.) As in the cases of other wavefront- recovery methods, the streams of wavefront data generated by means of PseudoDiversity are used as feedback signals for controlling electromechanical actuators of the various segments so as to correct wavefront errors and thereby, for example, obtain a clearer, steadier image of a distant object in the presence of atmospheric turbulence. There are numerous potential applications in astronomy, remote sensing from aircraft and spacecraft, targeting missiles, sighting military targets, and medical imaging (including microscopy) through such intervening media as cells or water. In comparison with prior wavefront-recovery methods used in adaptive optics, PseudoDiversity involves considerably simpler equipment and procedures and less computation. For PseudoDiversity, there is no need to install separate metrological equipment or to use any optomechanical components beyond those that are already parts of the optical system to which the method is applied. In Pseudo- Diversity, the actuators of a subset of the segments or subapertures are driven to make the segments dither in the piston, tilt, and tip degrees of freedom. Each aperture is dithered at a unique frequency at an amplitude of a half wavelength of light. During the dithering, images on the focal plane are detected and digitized at a rate of at least four samples per dither period. In the processing of the image samples, the use of different dither frequencies makes it possible to determine the separate effects of the various dithered segments or apertures. The digitized image-detector outputs are processed in the spatial-frequency (Fourier-transform) domain to obtain measures of the piston, tip, and tilt errors over each segment or subaperture. Once these measures are known, they are fed back to the actuators to correct the errors. In addition, measures of errors that remain after correction by use of the actuators are further utilized in an algorithm in which the image is phase-corrected in the spatial-frequency domain and then transformed back to the spatial domain at each time step and summed with the images from all previous time steps to obtain a final image having a greater signal-to-noise ratio (and, hence, a visual quality) higher than would otherwise be attainable.

Lyon, Richard G.↗
DOE OSTI2025

Toward Drilling the Perfect Geothermal Well: An International Research Coordination Network for Geothermal Drilling Optimization Supported by Deep Machine Learning and Cloud Based Data Aggregation

The EDGE project, supported by the U.S. Department of Energy Geothermal Technologies Office under award DE-EE0008793, established a data-driven framework for improving the efficiency, cost-effectiveness, and reliability of geothermal well drilling. The project focused on developing scalable data infrastructure, advanced machine learning and probabilistic models, and integrated analytics tools to support continuous drilling optimization. A central objective was to reduce geothermal drilling costs by up to seventy percent while minimizing the risk of well failure through predictive diagnostics and adaptive planning. Over the project period, a comprehensive data repository was designed and deployed, incorporating records from over one hundred geothermal wells across varied geological settings. This repository supported both structured and unstructured data and adhered to FAIR data principles, enabling provenance tracking, quality control, and standardized metadata. The project introduced automated ingestion pipelines and a cloud-hosted platform that facilitated access to raw, processed, and derived datasets. This infrastructure served as the foundation for model development and analysis. Machine learning workflows were developed to predict key drilling metrics including rate of penetration, non-productive time, and total drilling costs. Self-organizing maps and dimensionality reduction methods were used to uncover operational patterns and outliers, while supervised learning algorithms such as random forests and deep neural networks were applied to forecast performance outcomes. The models were validated on heterogeneous datasets from both U.S. and Icelandic fields, demonstrating variable but significant predictive accuracy. The results indicated that finer temporal resolution, inclusion of lithological data, and consistency in operational annotations could substantially improve model performance. The project also implemented process mining techniques to reconstruct state-transition models from drilling event logs. These models enabled the identification of deviations from optimal workflows and provided insights into recurring failure modes. Analysis of non-productive time highlighted the impact of equipment failures, geological challenges, and human factors, offering opportunities for targeted mitigation strategies. The EDGE Dashboard was developed as a web-based expert system integrating data visualization, model outputs, and user-driven queries. It provided an accessible interface for operators to explore historical data, evaluate predicted outcomes, and compare drilling scenarios. Initial feedback from project partners suggested that the dashboard could serve as a foundation for more advanced advisory and optimization tools. Overall, the EDGE project demonstrated the feasibility and value of applying modern data science techniques to geothermal drilling. It delivered a set of interoperable tools and models that can support more efficient, lower-risk well development. The findings point toward a viable path for transitioning from advisory analytics to semi-autonomous drilling systems, contingent on continued collaboration, expanded datasets, and field validation. The project results have immediate relevance for drilling operations, data management practices, and future geothermal R&D efforts aimed at achieving reliable, cost-competitive geothermal energy at scale.

15 GEOTHERMAL ENERGY↗
DOE OSTI2021

A data-driven global soil heterotrophic respiration dataset and the drivers of its inter-annual variability

Soil heterotrophic respiration (SHR), one of the primary carbon fluxes from terrestrial ecosystems to the atmosphere, is important for carbon-climate feedbacks because of its sensitivity to available litter and soil carbon, climatic conditions, and nutrient availability. However, until recently limited SHR data were available, and most published global SHR estimates have either a short time span, coarse spatial resolution, or reply on overly-simple model formulations. To better understand and quantify the global distribution of SHR and its sensitivity to climate variability, we produced a new global SHR dataset using Random Forest algorithms, up-scaling 455 point data from the Global Soil Respiration Database (SRDB 4.0) with gridded fields of climatic, edaphic and productivity as explanatory variables. We estimated a global total SHR of 46.8 Pg C yr-1 over 1985-2013 (95% confidence interval: 38.6-56.3 Pg C yr-1), with a significant increasing trend of 0.03 Pg C yr-2 during this period. We found that the choice of soil moisture datasets contributes more to the difference among these data-driven SHR members rather than that of productivity, temperature and precipitation data sources. We also analyzed the influence of climatic variables on the inter-annual variability (IAV) of our SHR product. Water availability was the dominant driver of IAV at global scales, although the inferred sensitivity depends on the choice of the soil moisture gridded dataset. At the ecosystem scale, temperature strongly controls the IAV of SHR in tropical forests, while water availability dominates in extra-tropical forest and semi-arid regions. Our machine-learning gridded SHR dataset and outputs from process-based land surface models (TRENDYv6) show agreement for a strong association between water variability and SHR IAV at the global scale, but the two approaches lead to different temporal trend globally and different controlling variables for IAV at the ecosystem scale. Our study provides evidence for the pervasive and important role of water availability in driving SHR, indicating both a direct effect limiting decomposition rates and an indirect effect through the amount of fresh organic matter made available to SHR from productivity. In consideration of potential limitations and uncertainties remaining in our data-driven SHR datasets, we call for a more scientifically designed observation network for SHR, more observation data compilation, and increased use of deep learning methods making maximum use of observation data in hand. This will benefit process-based models, and improve our understanding of SHR response to future anomalous environmental conditions.

Yao, Yitong↗
NASA NTRS2012

Predictive Sea State Estimation for Automated Ride Control and Handling - PSSEARCH

PSSEARCH provides predictive sea state estimation, coupled with closed-loop feedback control for automated ride control. It enables a manned or unmanned watercraft to determine the 3D map and sea state conditions in its vicinity in real time. Adaptive path-planning/ replanning software and a control surface management system will then use this information to choose the best settings and heading relative to the seas for the watercraft. PSSEARCH looks ahead and anticipates potential impact of waves on the boat and is used in a tight control loop to adjust trim tabs, course, and throttle settings. The software uses sensory inputs including IMU (Inertial Measurement Unit), stereo, radar, etc. to determine the sea state and wave conditions (wave height, frequency, wave direction) in the vicinity of a rapidly moving boat. This information can then be used to plot a safe path through the oncoming waves. The main issues in determining a safe path for sea surface navigation are: (1) deriving a 3D map of the surrounding environment, (2) extracting hazards and sea state surface state from the imaging sensors/map, and (3) planning a path and control surface settings that avoid the hazards, accomplish the mission navigation goals, and mitigate crew injuries from excessive heave, pitch, and roll accelerations while taking into account the dynamics of the sea surface state. The first part is solved using a wide baseline stereo system, where 3D structure is determined from two calibrated pairs of visual imagers. Once the 3D map is derived, anything above the sea surface is classified as a potential hazard and a surface analysis gives a static snapshot of the waves. Dynamics of the wave features are obtained from a frequency analysis of motion vectors derived from the orientation of the waves during a sequence of inputs. Fusion of the dynamic wave patterns with the 3D maps and the IMU outputs is used for efficient safe path planning.

Huntsberger, Terrance L.↗
NASA NTRS1996

A Burst Mode, Ultrahigh Temperature UF4 Vapor Core Reactor Rankine Cycle Space Power System Concept

Static and dynamic neutronic analyses have been performed on an innovative burst mode (100's of MW output for a few thousand seconds) Ulvahigh Temperature Vapor Core Reactor (UTVR) space nuclear power system. The NVTR employs multiple, neutronically-coupled fissioning cores and operates on a direct, closed Rankine cycle using a disk Magnetohydrodynamic (MHD) generater for energy conversion. The UTVR includes two types of fissioning core regions: (1) the central Ultrahigh Temperature Vapor Core (UTVC) which contains a vapor mixture of highly enriched UF4 fuel and a metal fluoride working fluid and (2) the UF4 boiler column cores located in the BeO moderator/reflector region. The gaseous nature of the fuel the fact that the fuel is circulating, the multiple coupled fissioning cores, and the use of a two phase fissioning fuel lead to unique static and dynamic neutronic characteristics. Static neutronic analysis was conducted using two-dimensional S sub n, transport theory calculations and three-dimensional Monte Carlo transport theory calculations. Circulating-fuel, coupled-core point reactor kinetics equations were used for analyzing the dynamic behavior of the UTVR. In addition to including reactivity feedback phenomena associated with the individual fissioning cores, the effects of core-to-core neutronic and mass flow coupling between the UTVC and the surrounding boiler cores were also included in the dynamic model The dynamic analysis of the UTVR reveals the existence of some very effectlve inherent reactivity feedback effects that are capable of quickly stabilizing this system, within a few seconds, even when large positive reactivity insertions are imposed. If the UTVC vapor fuel density feedback is suppressed, the UTVR is still inherently stable because of the boiler core liquid-fuel volume feedback; in contrast, suppression of the vapor fuel density feedback in 'conventional" gas core cavity reactors causes them to become inherently unstable. Due to the strength of the negative reactivity feedback in the UTVR, it is found that external reactivity insertions alone are inadequate for bringing about significant power level changes during normal reactor operations. Additional methods of reactivity control such as variations in the gaseous fuel mass flow rate, are needed to achieve the desired power level oontrol.

Dugan, E. T.↗