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All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

FORCE Regression Testing

Via programs including the Light Water Reactor Sustainability and Integrated Energy Systems, the U.S. Department of Energy has invested in the Framework for Optimization of ResourCes and Economics (FORCE) software framework (Idaho National Laboratory 2024a) for the technical and economic analysis of nuclear-integrated energy systems (IES). Nuclear IES expand the use of nuclear from traditional baseload electricity generation to a flexible and adaptive source of combined heat and power. Nuclear heat can be used in the production of a variety of energy currencies such as hydrogen and ammonia as well as other heat applications including water desalination and district heating. FORCE is designed with the intent to provide interconnected analysis tools that enable the accurate technical and economic assessment of specific nuclear IES configurations for individual energy markets. FORCE consists of three main analysis pathways: HYBRID (Idaho National Laboratory 2024b), which contains high-resolution physical models for IES; Holistic Energy Resource Optimization Network (HERON) (Idaho National Laboratory 2024c), which analyzes IES long-term economic viability; and Optimization of Real-time Capacity Allocation (ORCA) (Idaho National Laboratory 2024d), designed for real-time control of IES via digital twins and optimal decision making, including autonomous and remote operation research. Development of the FORCE ecosystem is guided by three pillars: capability, which assures that the computational requirements of IES analysis are met by the software tools; reliability, which provides for consistent code performance and expected behaviors; and accessibility, which lowers the barrier to entry for using the software and accelerates analysis by users beyond the FORCE primary developers. Reliability of the FORCE ecosystem is established according to the American Nuclear Society?s Nuclear Quality Assurance (NQA-1) program [American Society of Mechanical Engineers 1982], with specific levels of software quality assurance (SQA) within NQA-1 applied to each software tool in FORCE. As the tools within FORCE have matured, some integration algorithms to accurately connect the software tools for holistic analysis have been developed and deployed within the FORCE software repository. In accordance with NQA-1 standards, regression tests are required to guarantee the software performs consistently even when new capabilities are added to the software. In this report, we document the deployment of both unit tests, which test the consistent behavior of small pieces of the FORCE code base, as well as integration tests, which test the consistent performance of full use cases for the FORCE integration algorithms. We further document the encapsulation of these tests within a test harness, which collectively checks for each successful test completion on demand. Finally, we document the automation of the test harness using GitHub Actions [GitHub 2024], which require all tests succeed before any new capability or other changes can be added to the FORCE integration software

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Human-Building Collaboration: Toward lighting enabled collaborative system design

The profession of lighting design is evolving as contemporary lighting systems increasingly rely on cutting-edge computational technologies, sensors, and IOT systems. This trend requires designers to incorporate ideas of automation, dynamic controls, and user-system interaction into their design logic. However, real-time lighting simulations are constrained by inherent limitations arising from the reductive assumptions inevitably introduced in simulated lighting environments. This raises the question of how can designers account for the discrepancies between simulated and real lighting environments, and how can collaboration between humans and autonomous lighting systems bridge this gap. To address this question, we propose a protocol for designing collaborative interactions between humans and systems. Furthermore, this protocol builds on the Human-Lighting System Interaction Framework and demonstrates how human and system intelligence can be combined to fine-tune lighting qualities in a given space. Our paper shows how interactive lighting systems can customize lighting based on user preferences in real-time and how global lighting configurations can be adjusted over time. Specifically, we demonstrate: a) Human-system collaboration assumptions and goals, as well as how the protocol can be integrated into digitally programmable lighting systems. b) Implementations of collaboration that reveal how system autonomy, performance, and user experience are improved over short and long-term timeframes. c) How lighting design can be enhanced beyond simulation-driven design optimization capacities. The associated affordances and limitations are discussed with respect to existing lighting simulation design frameworks.

autonomous systems↗
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↗
NASA NTRSDate not supplied

Global 3D Data Visualization and Analysis Platform with Advanced Machine Learning Capabilities in Support of Lunar Exploration

Introduction: The science goals for NASA’s Artemis program include: a) Understanding the character and origin of lunar polar volatiles, b) Conducting experimental science in the lunar environment and c) Investigating and mitigating exploration risks. The permanently shadowed regions (PSRs) on the Lunar south pole are expected to host large quantities of water-ice and volatiles that are important for sustainable Lunar exploration. There are several missions such as onboard Korea Pathfinder Lunar Orbiter (KPLO: Korean name Danuri) with onboard ShadowCam camera, Astrobotic Peregrine Mission One [4], and other efforts underway to obtain high resolution topographic, minerals, volatiles and other information on the moon. We envision a need in immediate future for platforms to integrate these data sets, provide rendering and visualization capabilities in the context of a 3D Lunar globe for easier information access and analysis. NASA's Celestial Mapping System (CMS) is developed to address the need for 3D tools for planetary science investigations, mission planning, in-situ operations, in a 3D-first design constructed around a unified view of a planetary globe. At present CMS provides many critical functionalities that include: 1) equipment planning and optimized placement on Lunar surface 2) line-of-sight (LOS) analysis 3) powerful measurement tools based on 3D terrain with realistic 3D models to represent rovers, astronauts and equipment 4) visualization of derived mapping products (e.g. resource maps), and 5) a data engine for hosting new observations that are not available in other contemporary lunar data tools. Planetary Data Ingestion: CMS can consume and analyze data from locally hosted and external third party sources. It is compatible with Open Geospatial Consortium (OGC) data and file standards and currently integrates datasets from the Astrogeology Science Center of USGS. This includes global and local data acquired from NASA (LRO, Clementine, Lunar Orbiter) and JAXA (SELENE/Kaguya), with capability of integrating more datasets. In addition, users can specify other WMS-hosted data endpoints, which CMS can then query and stream data from automatically. To set-up an automated process for ingestion and accurate rendering, visualization and analysis of external 3rd party planetary datasets within CMS, we initiated the process of ingesting unique dataset of super-enhanced images of the permanently shadowed regions (PSRs) at the lunar poles which were produced by the Hyper-effective nOise Removal U-net Software (HORUS) tool. This tool was developed to enhance the extremely low-light images of the interior of PSRs and provide the ability to see within these regions at and discern surface features (i.e. boulders and craters) down to 3 meters in size. We focused on the Nobile region on the Lunar south pole, selected site for VIPER mission and stitched several images to create a high-resolution map within one of the PSR of Nobile crater. Figure 1 shows the dark PSR zone form the original NAC layer of LRO as the base layer (left image) and the illuminated areas within that crater (center) which was created by ingesting and merging several of HORUS generated images. At present we employ a semi-automated process to ensure spatial accuracy and merger of several overlapping zones. However, we are in the process of completely automating this process by employing AI based techniques that would rank, sort, and stack the images based on their information density. The georectification of the images would employ selected features. Analysis on Ingested Planetary Datasets: Once an external planetary data-set is successfully ingested, georectified and merged seamlessly as a data-layer; CMS’ numerous analysis tools can be used on this data. A Line of Sight (LOS) tool has been developed for CMS which analyzes terrain profiles and obstructions to determine visibility for remote observers. Figure 1 (right image) shows the viewshed analysis on the same PSR in the Nobile region. The yellow pin shows the observer location outside the PSR. The yellow area shows the visible part of PSR. The obstructed area with no visibility for the observer is shown in red. The Measurements tool allows the user to take area and distance measurements of features on the terrain using various shapes. Measurement type can be specified in a number of ways: Line, Path, Polygon, Circle, Ellipse, Square, Rectangle or Freehand. Once the shape is specified, elevation information can then be extracted along each of these shapes. Figure 2 (left) shows the measurements performed on a crater n illuminated PSR in Nobile region. The equipment placement tool allows the user to place a 3D equipment model at a desired location and analyze its coverage area. The equipment placement tool is coupled with LOS to determine the coverage. Figure 2 (right) shows an equipment placed on the Lunar terrain and it’s coverage area. The red rays are blocked sight lines and the green rays are non-obstructed sight lines with the cyan lines showing the point of intersection with the terrain. More details are provided in the video demonstrations in Reference 5. Overcoming Polar Distortions: 3D geospatial applications exhibit significant distortions in polar imagery due to several reasons: 1) distortions in the source imagery, 2) incompatible tessellation algorithms at the poles, and 3) map projections. We are leveraging new tessellation algorithms and reprojecting data using projections that are better suited for Lunar poles. The goal is to seamlessly switch to polar projections while maintaining 3D view and navigation.

Maps↗
NASA NTRS1989

Space biology initiative program definition review. Trade study 1: Automation costs versus crew utilization

A significant emphasis upon automation within the Space Biology Initiative hardware appears justified in order to conserve crew labor and crew training effort. Two generic forms of automation were identified: automation of data and information handling and decision making, and the automation of material handling, transfer, and processing. The use of automatic data acquisition, expert systems, robots, and machine vision will increase the volume of experiments and quality of results. The automation described may also influence efforts to miniaturize and modularize the large array of SBI hardware identified to date. The cost and benefit model developed appears to be a useful guideline for SBI equipment specifiers and designers. Additional refinements would enhance the validity of the model. Two NASA automation pilot programs, 'The Principal Investigator in a Box' and 'Rack Mounted Robots' were investigated and found to be quite appropriate for adaptation to the SBI program. There are other in-house NASA efforts that provide technology that may be appropriate for the SBI program. Important data is believed to exist in advanced medical labs throughout the U.S., Japan, and Europe. The information and data processing in medical analysis equipment is highly automated and future trends reveal continued progress in this area. However, automation of material handling and processing has progressed in a limited manner because the medical labs are not affected by the power and space constraints that Space Station medical equipment is faced with. Therefore, NASA's major emphasis in automation will require a lead effort in the automation of material handling to achieve optimal crew utilization.

Jackson, L. Neal↗
NASA NTRS2009

NASA Tech Briefs, May 2009

Topics covered include: Valve-"Health"-Monitoring System; Microstrip Antenna for Remote Sensing of Soil Moisture and Sea Surface Salinity; Biomedical Wireless Ambulatory Crew Monitor; Wireless Avionics Packet to Support Fault Tolerance for Flight Applications; Aerobot Autonomy Architecture; Submillimeter Confocal Imaging Active Module; Traveling-Wave Maser for 32 GHz; System Synchronizes Recordings from Separated Video Cameras; Piecewise-Planar Parabolic Reflectarray Antenna; Reducing Interference in ATC Voice Communication; EOS MLS Level 1B Data Processing, Version 2.2; Auto-Generated Semantic Processing Services; Geospatial Authentication; Maneuver Automation Software; Event Driven Messaging with Role-Based Subscriptions; Estimating Relative Positions of Outer-Space Structures; Fabricating PFPE Membranes for Capillary Electrophoresis; Linear Actuator Has Long Stroke and High Resolution; Installing a Test Tap on a Metal Battery Case; Fabricating PFPE Membranes for Microfluidic Valves and Pumps; Room-Temperature-Cured Copolymers for Lithium Battery Gel Electrolytes; Catalysts for Efficient Production of Carbon Nanotubes; Amorphous Silk Fibroin Membranes for Separation of CO2; "Zero-Mass" Noninvasive Pressure Transducers; Radial-Electric-Field Piezoelectric Diaphragm Pumps; Ejector-Enhanced, Pulsed, Pressure-Gain Combustor; Suppressing Ghost Diffraction in E-Beam-Written Gratings; Target-Tracking Camera for a Metrology System; Polarimetric Imaging using Two Photoelastic Modulators; Miniature Wide-Angle Lens for Small-Pixel Electronic Camera; Modal Filters for Infrared Interferometry; Mo(3)Sb(7-x)Te(x) for Thermoelectric Power Generation; Two-Dimensional Quantum Model of a Nanotransistor; Scanning Miniature Microscopes without Lenses; Manipulating Neutral Atoms in Chip-Based Magnetic Traps; Expansion Compression Contacts for Thermoelectric Legs; Processing Electromyographic Signals to Recognize Words; Physical Principle for Generation of Randomness; DSN Beowulf Cluster-Based VLBI Correlator; Hybrid NN/SVM Computational System for Optimizing Designs; Criteria for Modeling in LES of Multicomponent Fuel Flow; Computerized Machine for Cutting Space Shuttle Thermal Tiles; Orbiting Depot and Reusable Lander for Lunar Transportation; FPGA-Based Networked Phasemeter for a Heterodyne Interferometer; Aquarius Digital Processing Unit; Three-Dimensional Optical Coherence Tomography; Benchtop Antigen Detection Technique using Nanofiltration and Fluorescent Dyes; Isolation of Precursor Cells from Waste Solid Fat Tissue; Identification of Bacteria and Determination of Biological Indicators; Further Development of Scaffolds for Regeneration of Nerves; Chemically Assisted Photocatalytic Oxidation System; Use of Atomic Oxygen for Increased Water Contact Angles of Various Polymers for Biomedical Applications; Crashworthy Seats Would Afford Superior Protection; Open-Access, Low-Magnetic-Field MRI System for Lung Research; Microfluidic Mixing Technology for a Universal Health Sensor; Microfluidic Extraction of Biomarkers using Water as Solvent; Microwell Arrays for Studying Many Individual Cells; Droplet-Based Production of Liposomes; and Identifying and Inactivating Bacterial Spores

Source record↗
DOE OSTI2022

Feedback Control Approaches for Restoration of Power Grids from Blackouts

The automated restoration of power systems with variable energy resources is a timely problem to tackle. Automated restoration advice can support operators in deciding on strategic actions to restore power grids from a blackout with a mix of conventional and renewable generation resources. To this end, this paper frames the restoration process of power grids with solar resources as a nonlinear dynamic model with algebraic constraints in discrete time which is steered by feedback control loops. We discuss two feedback-control strategies based on greedy and reinforcement learning algorithms, and contrast their performance with restoration plans generated by a mixed-integer linear program. We found that the reinforcement learning algorithm infers restoration actions faster than the greedy one. However, the tuning process of the reinforcement learning parameters is slower than for the greedy one.

machine learning↗
NASA NTRS2001

Laser Materials Processing for NASA's Aerospace Structural Materials

Lasers are useful for performing operations such as joining, machining, built-up freeform fabrication, and surface treatment. Due to the multifunctional nature of a single tool and the variety of materials that can be processed, these attributes are attractive in order to support long-term missions in space. However, current laser technology also has drawbacks for space-based applications. Specifically, size, power efficiency, lack of robustness, and problems processing highly reflective materials are all concerns. With the advent of recent breakthroughs in solidstate laser (e.g., diode-pumped lasers) and fiber optic technologies, the potential to perform multiple processing techniques in space has increased significantly. A review of the historical development of lasers from their infancy to the present will be used to show how these issues may be addressed. The review will also indicate where further development is necessary to realize a laser-based materials processing capability in space. The broad utility of laser beams in synthesizing various classes of engineering materials will be illustrated using state-of-the art processing maps for select lightweight alloys typically found on spacecraft. Both short- and long-term space missions will benefit from the development of a universal laser-based tool with low power consumption, improved process flexibility, compactness (e.g., miniaturization), robustness, and automation for maximum utility with a minimum of human interaction. The potential advantages of using lasers with suitable wavelength and beam properties for future space missions to the moon, Mars and beyond will be discussed. The laser processing experiments in the present report were performed using a diode pumped, pulsed/continuous wave Nd:YAG laser (50 W max average laser power), with a 1064 nm wavelength. The processed materials included Ti-6AI-4V, Al-2219 and Al-2090. For Phase I of this project, the laser process conditions were varied and optimized to see the effects on melt-quenching, cladding/alloying (using the pre-placed powder technique), and cutting. Key parameters such laser power, pulse repetition frequency, process speed, and shield gas flow and the observed process characteristics such as plasma formation during laser/material interaction, have been reported for all experimental runs. Preliminary materials characterization of select samples was carried out using various microscopy, diffraction, spectroscopy and microhardness test methods, and reported. Select nitridation results of Ti-6AI-4V using nitrogen assist gas indicated the successful formation of hard titanium nitrides with much higher hardness (2180 kg/sq mm). A cost-effective and simple powder delivery system has been successfully fabricated for the further experimentation in Phase H.

Nagarathnam, Karthik↗
NASA NTRSDate not supplied

Global 3D Data Visualization and Analysis Platform With Advanced Machine Learning Capabilities in Support of Lunar Exploration

Introduction: The science goals for NASA’s Artemis program include: a) Understanding the character and origin of lunar polar volatiles, b) Conducting experimental science in the lunar environment and c) Investigating and mitigating exploration risks [1]. The permanently shadowed regions (PSRs) on the Lunar south pole are expected to host large quantities of water-ice and volatiles that are important for sustainable Lunar exploration [2]. There are several missions such as onboard Korea Pathfinder Lunar Orbiter (KPLO: Korean name Danuri) with onboard ShadowCam camera [3], Astrobotic Peregrine Mission One [4], and other efforts underway to obtain high resolution topographic, minerals, volatiles and other information on the moon. We envision a need in immediate future for platforms to integrate these data sets, provide rendering and visualization capabilities in the context of a 3D Lunar globe for easier information access and analysis. NASA's Celestial Mapping System (CMS) [5] is developed to address the need for 3D tools for planetary science investigations, mission planning, in-situ operations, in a 3D-first design constructed around a unified view of a planetary globe. At present CMS provides many critical functionalities that include: 1) equipment planning and optimized placement on Lunar surface 2) line-of-sight (LOS) analysis 3) powerful measurement tools based on 3D terrain with realistic 3D models to represent rovers, astronauts and equipment 4) visualization of derived mapping products (e.g. resource maps), and 5) a data engine for hosting new observations that are not available in other contemporary lunar data tools [5, 7]. Planetary Data Ingestion: CMS can consume and analyze data from locally hosted and external third party sources. It is compatible with Open Geospatial Consortium (OGC) data and file standards and currently integrates datasets from the Astrogeology Science Center of USGS. This includes global and local data acquired from NASA (LRO, Clementine, Lunar Orbiter) and JAXA (SELENE/Kaguya), with capability of integrating more datasets. In addition, users can specify other WMS-hosted data endpoints, which CMS can then query and stream data from automatically. To set-up an automated process for ingestion and accurate rendering, visualization and analysis of external 3rd party planetary datasets within CMS, we initiated the process of ingesting unique dataset of super-enhanced images of the permanently shadowed regions (PSRs) at the lunar poles which were produced by the Hyper-effective nOise Removal U-net Software (HORUS) tool [8]. This tool was developed to enhance the extremely low-light images of the interior of PSRs and provide the ability to see within these regions at and discern surface features (i.e. boulders and craters) down to 3 meters in size. We focused on the Nobile region on the Lunar south pole, selected site for VIPER mission and stitched several images to create a high-resolution map within one of the PSR of Nobile crater. Figure 1 shows the dark PSR zone form the original NAC layer of LRO as the base layer (left image) and the illuminated areas within that crater (center) which was created by ingesting and merging several of HORUS generated images. At present we employ a semi-automated process to ensure spatial accuracy and merger of several overlapping zones. However, we are in the process of completely automating this process by employing AI based techniques that would rank, sort, and stack the images based on their information density. The georectification of the images would employ selected features. Analysis on Ingested Planetary Datasets: Once an external planetary data-set is successfully ingested, georectified and merged seamlessly as a data-layer; CMS’ numerous analysis tools can be used on this data. A Line of Sight (LOS) tool has been developed for CMS which analyzes terrain profiles and obstructions to determine visibility for remote observers [5,6]. Figure 1 (right image) shows the viewshed analysis on the same PSR in the Nobile region. The yellow pin shows the observer location outside the PSR. The yellow area shows the visible part of PSR. The obstructed area with no visibility for the observer is shown in red. The Measurements tool allows the user to take area and distance measurements of features on the terrain using various shapes. Measurement type can be specified in a number of ways: Line, Path, Polygon, Circle, Ellipse, Square, Rectangle or Freehand. Once the shape is specified, elevation information can then be extracted along each of these shapes. Figure 2 (left) shows the measurements performed on a crater n illuminated PSR in Nobile region. The equipment placement tool allows the user to place a 3D equipment model at a desired location and analyze its coverage area. The equipment placement tool is coupled with LOS to determine the coverage. Figure 2 (right) shows an equipment placed on the Lunar terrain and it’s coverage area. The red rays are blocked sight lines and the green rays are non-obstructed sight lines with the cyan lines showing the point of intersection with the terrain. More details are provided in the video demonstrations in Reference 5. Overcoming Polar Distortions: 3D geospatial applications exhibit significant distortions in polar imagery due to several reasons: 1) distortions in the source imagery, 2) incompatible tessellation algorithms at the poles, and 3) map projections. We are leveraging new tessellation algorithms and reprojecting data using projections that are better suited for Lunar poles. The goal is to seamlessly switch to polar projections while maintaining 3D view and navigation.

Maps↗
DOE OSTI2022

High-Throughput Microfluidics Platform for Intracellular Delivery and Sampling of Biomolecules from Live Cells

Nondestructive cell membrane permeabilization systems enable the intracellular delivery of exogenous biomolecules for cell engineering tasks as well as the temporal sampling of cytosolic contents from live cells for the analysis of dynamic processes. Here, in this paper, we report a microwell array format live-cell analysis device (LCAD) that can perform localized-electroporation induced membrane permeabilization, for cellular delivery or sampling, and directly interfaces with surface-based biosensors for analyzing the extracted contents. We demonstrate the capabilities of the LCAD via an automated high-throughput workflow for multimodal analysis of live-cell dynamics, consisting of quantitative measurements of enzyme activity using self-assembled monolayers for MALDI mass spectrometry (SAMDI) and deep-learning enhanced imaging and analysis. By combining a fabrication protocol that enables robust assembly and operation of multilayer devices with embedded gold electrodes and an automated imaging workflow, we successfully deliver functional molecules (plasmid and siRNA) into live cells at multiple time-points and track their effect on gene expression and cell morphology temporally. Furthermore, we report sampling performance enhancements, achieving saturation levels of protein tyrosine phosphatase activity measured from as few as 60 cells, and demonstrate control over the amount of sampled contents by optimization of electroporation parameters using a lumped model. Lastly, we investigate the implications of cell morphology on electroporation-induced sampling of fluorescent molecules using a deep-learning enhanced image analysis workflow.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

CIRCLES: Congestion Impacts Reduction via CAV-in-the-loop Lagrangian Energy Smoothing

The energy efficiency of today’s vehicular mobility relies on the un-integrated combination of i) control via static assets (traffic lights, metering, variable speed limits, etc.); and ii) onboard vehicle automation (adaptive cruise control (ACC), ecodriving, etc.). These two families of control were not co-designed and are not engineered to work in coordination. Recent studies have shown i) limitations of controls, and even ii) negative impacts of ACC. This project focused on the technology development, implementation and prototyping, and validation of Mobile Traffic Control (MTC). MTC can be viewed as an extension of classical traffic control (in which static infrastructure actuates traffic flow). In the MTC paradigm, automated vehicles actuate the entire flow via their behavior, offering enhanced possibilities to optimize the energy footprint of traffic, if designed correctly. We set out to demonstrate for the first time that considerably reduced fuel consumption of all vehicles in traffic can be achieved via distributed control of a small proportion of CAVs. Compared to baseline vehicular technologies, our work offers a significant design departure: control algorithms for the CAVs consider the impact one vehicle can have on overall traffic, improving resulting overall fuel consumption. We focus on using a few vehicles (as traffic controllers via CAV technology) to improve the energy efficiency of traffic flow to further optimize energy efficiency. A live-traffic demonstration in November 2022 featured the deployment of 100 specially-equipped CAVs, constituting an approximate local penetration rate upwards of 2%.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS1994

Microgravity Flight - Accommodating Non-Human Primates

Spacelab Life Sciences-3 (SLS-3) was scheduled to be the first United States man-tended microgravity flight containing Rhesus monkeys. The goal of this flight as in the five untended Russian COSMOS Bion flights and an earlier American Biosatellite flight, was to understand the biomedical and biological effects of a microgravity environment using the non-human primate as human surrogate. The SLS-3/Rhesus Project and COSMOS Primate-BIOS flights all utilized the rhesus monkey Macaca mulatta. The ultimate objective of all flights with an animal surrogate has been to evaluate and understand biological mechanisms at both the system and cellular level, thus enabling rational effective countermeasures for future long duration human activity under microgravity conditions and enabling technical application to correction of common human physiological problems within earth's gravity, e.g., muscle strength and reloading, osteoporosis, immune deficiency diseases. Hardware developed for the SLS-3/Rhesus Project was the result of a joint effort with the French Centre National d'Etudes Spatiales (CNES) and the United States National Aeronautics and Space Administration (NASA) extending over the last decade. The flight hardware design and development required implementation of sufficient automation to insure flight crew and animal bio-isolation and maintenance with minimal impact to crew activities. A variety of hardware of varying functional capabilities was developed to support the scientific objectives of the original 22 combined French and American experiments, along with 5 Russian co-investigations, including musculoskeletal, metabolic, and behavioral studies. Unique elements of the Rhesus Research Facility (RRF) included separation of waste for daily delivery of urine and fecal samples for metabolic studies and a psychomotor test system for behavioral studies along with monitored food measurement. As in untended flights, telemetry measurements would allow monitoring of thermoregulation, muscular, and cardiac responses to weightlessness. In contrast, the five completed Cosmos/Bion flights, lacked the metabolic samples and behavioral task monitoring, but did facilitate studies of the neurovestibular system during several of the flights. The RRF accommodated two adult 8-11 kg rhesus monkeys, while the Russian experiments and hardware were configured for a younger animal in the 44 kg range. Both the American and Russian hardware maintained a controlled environmental system, specifically temperature, humidity, a timed lighting cycle, and had means for providing food and fluids to the animal(s). Crew availability during a Shuttle mission was to be an optimal condition for retrieval and refrigeration of the animal urine samples along with a manual calcein injection which could lead to greater understanding of bone calcium incorporation. A special portable bioisolation glove box was under development to support this aspect of the experiment profile along with the capability of any contingency human intervention. As a result of recent U.S./Russian negotiations, funding for Space Station, and a series of other events, the SLS-3 mission was cancelled and applicable Rhesus Project experiments incorporated into the Russian Bion 11 and 12 missions. A presentation of the RRF and COSMOS/Bion rhesus hardware is presented along with current plans for the hardware.

Dalton, Bonnie P.↗
NASA NTRS1995

Microgravity Flight: Accommodating Non-Human Primates

Spacelab Life Sciences-3 (SLS-3) was scheduled to be the first United States man-tended microgravity flight containing Rhesus monkeys. The goal of this flight as in the five untended Russian COSMOS Bion flights and an earlier American Biosatellite flight, was to understand the biomedical and biological effects of a microgravity environment using the non-human primate as human surrogate. The SLS-3/Rhesus Project and COSMOS Primate-BIOS flights all utilized the rhesus monkey, Macaca mulatta. The ultimate objective of all flights with an animal surrogate has been to evaluate and understand biological mechanisms at both the system and cellular level, thus enabling rational effective countermeasures for future long duration human activity under microgravity conditions and enabling technical application to correction of common human physiological problems within earth's gravity, e.g., muscle strength and reloading, osteoporosis, immune deficiency diseases. Hardware developed for the SLS-3/Rhesus Project was the result of a joint effort with the French Centre National d'Etudes Spatiales (CNES) and the United States National Aeronautics and Space Administration (NASA) extending over the last decade. The flight hardware design and development required implementation of sufficient automation to insure flight crew and animal bio-isolation and maintenance with minimal impact to crew activities. A variety of hardware of varying functional capabilities was developed to support the scientific objectives of the original 22 combined French and American experiments, along with 5 Russian co-investigations, including musculoskeletal, metabolic, and behavioral studies. Unique elements of the Rhesus Research Facility (RRF) included separation of waste for daily delivery of urine and fecal samples for metabolic studies and a psychomotor test system for behavioral studies along with monitored food measurement. As in untended flights, telemetry measurements would allow monitoring of thermoregulation, muscular, and cardiac responses to weightlessness. In contrast, the five completed Cosmos/Bion flights, lacked the metabolic samples and behavioral task monitoring, but did facilitate studies of the neurovestibular system during several of the flights. The RRF accommodated two adult 8-11 kg rhesus monkeys, while the Russian experiments and hardware were configured for a younger animal in the 44 kg range. Both the American and Russian hardware maintained a controlled environmental system, specifically temperature, humidity, a timed lighting cycle, and had means for providing food and fluids to the animal(s). Crew availability during a Shuttle mission was to be an optimal condition for retrieval and refrigeration of the animal urine samples along with a manual calcein injection which could lead to greater understanding of bone calcium incorporation. A special portable bioisolation glove box was under development to support this aspect of the experiment profile along with the capability of any contingency human intervention. As a result of recent U.S./Russian negotiations, funding for Space Station, and a series of other events, the SLS-3 mission was cancelled and applicable Rhesus Project experiments incorporated into the Russian Bion 11 and 12 missions. A presentation of the RRF and COSMOS/Bion rhesus hardware is presented along with current plans for the hardware.

Dalton, Bonnie P.↗
NASA NTRS2016

Unmanned Aircraft Systems Traffic Management (UTM) Safely Enabling UAS Operations in Low-Altitude Airspace

Unmanned Aircraft System (UAS) Traffic Management (UTM) Enabling Civilian Low-Altitude Airspace and Unmanned Aircraft System Operations What is the problem? Many beneficial civilian applications of UAS have been proposed, from goods delivery and infrastructure surveillance, to search and rescue, and agricultural monitoring. Currently, there is no established infrastructure to enable and safely manage the widespread use of low-altitude airspace and UAS operations, regardless of the type of UAS. A UAS traffic management (UTM) system for low-altitude airspace may be needed, perhaps leveraging concepts from the system of roads, lanes, stop signs, rules and lights that govern vehicles on the ground today, whether the vehicles are driven by humans or are automated. What system technologies is NASA exploring? Building on its legacy of work in air traffic management for crewed aircraft, NASA is researching prototype technologies for a UAS Traffic Management (UTM) system that could develop airspace integration requirements for enabling safe, efficient low-altitude operations. While incorporating lessons learned from the today's well-established air traffic management system, which was a response that grew out of a mid-air collision over the Grand Canyon in the early days of commercial aviation, the UTM system would enable safe and efficient low-altitude airspace operations by providing services such as airspace design, corridors, dynamic geofencing, severe weather and wind avoidance, congestion management, terrain avoidance, route planning and re-routing, separation management, sequencing and spacing, and contingency management. One of the attributes of the UTM system is that it would not require human operators to monitor every vehicle continuously. The system could provide to human managers the data to make strategic decisions related to initiation, continuation, and termination of airspace operations. This approach would ensure that only authenticated UAS could operate in the airspace. In its most mature form, the UTM system could be developed using autonomicity characteristics that include self-configuration, self-optimization and self-protection. The self-configuration aspect could determine whether the operations should continue given the current andor predicted windweather conditions. NASA envisions concepts for two types of possible UTM systems. The first type would be a Portable UTM system, which would move from between geographical areas and support operations such as precision agriculture and disaster relief. The second type of system would be a Persistent UTM system, which would support low-altitude operations and provide continuous coverage for a geographical area. Either system would require persistent communication, navigation, and surveillance (CNS) coverage to track, ensure, and monitor conformance. What is NASA doing to test the technologies? NASA's near-term goal is the development and demonstration of a possible future UTM system that could safely enable low-altitude airspace and UAS operations. Working alongside many committed government, industry and academic partners, NASA is leading the research, development and testing that is taking place in a series of activities called Technology Capability Levels (TCL), each increasing in complexity. UTM TCL1 concluded field testing in August 2015 and is undergoing additional testing at an FAA site.

UTM Low-altitude↗
NASA NTRS2019

The ILRS: Approaching 20 Years and Planning for the Future

The International Laser Ranging Service (ILRS) was established by the International Association of Geodesy (IAG) in 1998 to support programs in geodesy, geophysics, fundamental constants and lunar research, and to provide the International Earth Rotation Service with data products that are essential to the maintenance and improvement in the International Terrestrial Reference Frame (ITRF), the basis for metric measurements of changes in the Earth and Earth–Moon system. Other scientific products derived from laser ranging include precise geocentric positions and motions of ground stations, satellite orbits, components of Earth’s gravity field and their temporal variations, Earth Orientation Parameters, precise lunar ephemerides and information about the internal structure of the Moon. Laser ranging systems are already measuring the one-way distance to remote optical receivers in space and are performing very accurate time transfer between remote sites in the Earth and in Space. The ILRS works closely with the IAG’s Global Geodetic Observing System. The ILRS develops (1) the standards and specifications necessary for product consistency, and (2) the priorities and tracking strategies required to maximize network efficiency. The service collects, merges, analyzes, archives and distributes satellite and lunar laser ranging data to satisfy a variety of scientific, engineering, and operational needs and encourages the application of new technologies to enhance the quality, quantity, and cost effectiveness of its data products. The ILRS works with (1) new satellite missions in the design and building of retroreflector targets to maximize data quality and quantity, and (2) science programs to optimize scientific data yield. Since its inception, the ILRS has grown to include forty laser ranging stations distributed around the world. The ILRS stations track more than ninety satellites from low Earth orbit (LEO) to the geosynchronous orbit altitude as well as retroreflector arrays on the surface of the Moon. Applications have been expanded to include time transfer, asynchronous ranging for targets at extended ranges, free space quantum telecommunications, and the tracking of space debris. Laser ranging technology is moving to lower energy, higher repetition rates (kHz), single-photon-sensitive detectors, shorter pulse widths, shorter normal point intervals for faster data acquisition, and increased pass interleaving, automated to autonomous operation with remote access, and embedded software for real-time updates and decision making. An example of pass interleaving is presented for the Yarragadee station (see Fig. 4); tracking of LEO satellites is often accommodated during break in LEO and GNSS passes. New satellites arrays provide more compact targets and work continues on the development of lighter less expensive arrays for satellites and the moon. The service now provides operational ITRF products including daily/ weekly station positions and daily resolution Earth orientation products; the flow of weekly combination of satellite orbit files for LAGEOS/Etalon-1 and -2 has recently been established. New products are under testing through a pilot project on systematic error monitoring currently underway. The article will give an overview of activities underway within the service, paths forward presently envisioned, and current issues and challenges.

Laser retroreflectors↗
NASA NTRSDate not supplied

SatCORPS Global Cloud Composite (GCC): the Design and Delivery of A High Quality, High Resolution, Global Cloud Product Available in Near-Real Time

The NASA Satellite ClOud and Radiation Property retrieval System (SatCORPS) supports the development of an analysis ready and cloud-optimized data transformation pipeline and geospatial service enablement of a global cloud composite (GCC) product derived from global geostationary satellite imagery. This geospatial service will be available at high temporal and spatial resolution via the SatCORPS web mapping application for visualization and analysis as well as direct ingestion to common geospatial software and custom programming. The resulting global cloud composite products from the processing pipeline can then be geospatially-service enabled as ArcGIS Image Services and Open Geospatial Consortium (OGC) Web Mapping/Coverage Services for visualization and analysis via a web mapping application and common geospatial software. Near real time global observations are created through the composition of five geostationary satellites that provides modelling and forecasting communities with the capability to provide high quality and timely information to start the projection process. The Global Cloud Composite product combines information from geostationary satellites, GOES-16, GOES-17, Himawari-8, Meteosat-11 and Meteosat-9 to create a single global composite netcdf file and images using the different products within the netcdf file. The SatCORPS team, though our Global Cloud Composite (GCC) product and web-based visualization tools including Geographical Information System (GIS) services provide near real time global cloud product information to both automated processes and traditional web users that is timely and high quality derived from geostationary satellites. The Global Cloud Composite product takes advantage of the scalable processing resources provided by the AWS batch service to provide new composites every thirty minutes. Because information from each of the low earth orbiting satellites is available on schedules tuned to the specific satellite, the processing algorithm temporally composites the final dataset as each satellite’s information becomes available. The SatCORPS team has leveraged our experience using Amazon Web Services (AWS) to build a low latency high availability tool that allows end users both human and automated to acquire high quality and high-resolution Geostationary Earth Orbiting (GEO) information at zero cost to the end user. This presentation will describe how we architected and implemented the service as well as lessons learned based on our experiences both developing and operating the system. The lessons learned include how we integrated multiple services including Amazon Batch, Amazon S3 and Amazon Lambda service to create a low cost but high-performance processing system that is capable of identifying and processing the most appropriate satellite overpass information into global cloud composites. We will also describe our web-based tools including our Geographic Information System that can be used for visualization and analysis. The products from the processing can be geospatially-service enabled as ArcGIS Image Services and Open Geospatial Consortium (OGC) Web Mapping/Coverage Services for visualization and analysis via a web mapping application and common geospatial software. The SatCORPS Global Composite Cloud product provides sophisticated global composited cloud research products with very low latency that we see that as filling a rapidly growing need in the research and modelling community with no up-front nor ongoing costs associated with downloading or using the information.

AWS AMCE SMCE GCC SATCORPS GLOBAL CLOUD COMPOSITE ↗
DOE OSTI2023

Aero‐servo‐elastic co‐optimization of large wind turbine blades with distributed aerodynamic control devices

Abstract This work introduces automated wind turbine optimization techniques based on full aero‐servo‐elastic models and investigates the potential of trailing edge flaps to reduce the levelized cost of energy (LCOE) of wind turbines. The Wind Energy with Integrated Servo‐control (WEIS) framework is improved to conduct the presented research. Novel methods for the generic implementation and tuning of trailing edge flap devices and their controller are also introduced. Primary flap and controller parameters are optimized to demonstrate potential maximum blade tip deflection reductions of 21 % . Concurrent design optimization (i.e., co‐design) of a novel segmented wind turbine blade with trailing edge flaps and its controller is then conducted to demonstrate blade cost savings of 5 % . Additionally, rotor diameter co‐design optimization is demonstrated to reduce the LCOE by 1.3 % without significant load increases to the tower. These results demonstrate the efficacy of control co‐design optimization using trailing edge flaps, and the entirety of this work provides a foundation for numerous control co‐design‐oriented studies for distributed aerodynamic control devices.

17 WIND ENERGY↗
DOE OSTI2025

Enhancing occupant behavior representation for interoperability between building information modeling and building energy modeling

Building Performance Simulation (BPS) has been adopted as an essential tool for designing, operating, and retrofitting buildings to optimize energy efficiency throughout the building life cycle. The Green Building XML (gbXML) schema facilitates seamless data exchange between Building Information Modeling (BIM) and Building Energy Modeling (BEM) software tools. However, limited occupant behavior (OB) representation in BIM often leads to inconsistent and inaccurate energy simulation in BEM software. This paper presents 154 systematic enhancements to the existing occupant behavior XML (obXML) schema v1.3.4, initially developed for standardizing OB representation for BEM, to address existing limitations and improve interoperability with BIM models. The enhancements encompass improved integration with BIM models through extended building representations and system operations, expanded support for advanced OB models with additional environmental parameters and mathematical capabilities, and implementation of a standardized model documentation framework. To facilitate seamless data transformation between gbXML and obXML schemas, we developed a publicly available gb-obXML Schema Converter. Three case studies demonstrate the enhanced schema’s capabilities: representation of building information using a two-story office building model, documentation of a window operation behavior model, and validation of the schema converter’s functionality. The enhanced obXML schema v1.4 enables sophisticated modeling of occupant-building interactions while maintaining consistency with industry-standard BIM schemas. The standardized documentation framework facilitates reproducibility and knowledge sharing in the OB research community, while the schema converter automates the integration of building information into OB simulation workflows. These enhancements establish a foundation for more accurate building performance simulation by supporting sophisticated representation of occupant behavior within the BIM-to-BEM simulation workflows.

Chung, Jihoon↗