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NASA NTRS2017

Time Dependence of Collision Probabilities During Satellite Conjunctions

The NASA Conjunction Assessment Risk Analysis (CARA) team has recently implemented updated software to calculate the probability of collision (P (sub c)) for Earth-orbiting satellites. The algorithm can employ complex dynamical models for orbital motion, and account for the effects of non-linear trajectories as well as both position and velocity uncertainties. This “3D P (sub c)” method entails computing a 3-dimensional numerical integral for each estimated probability. Our analysis indicates that the 3D method provides several new insights over the traditional “2D P (sub c)” method, even when approximating the orbital motion using the relatively simple Keplerian two-body dynamical model. First, the formulation provides the means to estimate variations in the time derivative of the collision probability, or the probability rate, R (sub c). For close-proximity satellites, such as those orbiting in formations or clusters, R (sub c) variations can show multiple peaks that repeat or blend with one another, providing insight into the ongoing temporal distribution of risk. For single, isolated conjunctions, R (sub c) analysis provides the means to identify and bound the times of peak collision risk. Additionally, analysis of multiple actual archived conjunctions demonstrates that the commonly used “2D P (sub c)” approximation can occasionally provide inaccurate estimates. These include cases in which the 2D method yields negligibly small probabilities (e.g., P (sub c)) is greater than 10 (sup -10)), but the 3D estimates are sufficiently large to prompt increased monitoring or collision mitigation (e.g., P (sub c) is greater than or equal to 10 (sup -5)). Finally, the archive analysis indicates that a relatively efficient calculation can be used to identify which conjunctions will have negligibly small probabilities. This small-P (sub c) screening test can significantly speed the overall risk analysis computation for large numbers of conjunctions.

Hall, Doyle T.↗

DOE OSTI2025

pyTCR: A tropical cyclone rainfall model for python

pyTCR is a climatology software package developed in the Python programming language. It integrates the capabilities of several legacy physical models and increases computational efficiency to allow rapid estimation of tropical cyclone (TC) rainfall consistent with the large-scale environment. Specifically, pyTCR implements a horizontally distributed and vertically integrated model [Zhu et al., 2013] for simulating rainfall driven by TCs. Along storm tracks, rainfall is estimated by computing the cross-boundary-layer, upward water vapor transport caused by different mechanisms including frictional convergence, vortex stretching, large-scale baroclinic effect (i.e., wind shear), topographic forcing, and radiative cooling [Lu et al., 2018]. The package provides essential functionalities for modeling and interpreting spatio-temporal TC rainfall data. pyTCR requires a limited number of model input parameters, making it a convenient and useful tool for analyzing rainfall mechanisms driven by TCs. To sample rare (most intense) rainfall events that are often of great societal interest, pyTCR adapts and leverages outputs from a statistical-dynamical TC downscaling model [Lin et al., 2023] capable of rapidly generating a large number of synthetic TCs given a certain climate. As a result, pyTCR significantly reduces computational effort and improves the efficiency in capturing extreme TC rainfall events at the tail of the distributions from limited datasets. Furthermore, the TC downscaling model is forced entirely by large-scale environmental conditions from reanalysis data or coupled General Circulation Models (GCMs), simplifying the projection of TC-induced rainfall and wind speed under future climate using pyTCR. Finally, pyTCR can be coupled with hydrological and wind models to assess risks associated with independent and compound events (e.g., storm surges and freshwater flooding).

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

National User Resource for Biological Accelerator Mass Spectrometry (Final Report)

The National User Resource for Biological Accelerator Mass Spectrometry (User Resource) will provide isotopic analysis (primarily radiocarbon or 14C) by accelerator mass spectrometry (AMS) for NIH- funded researchers across the United States and will be the only User Resource of its type in the United States. The User Resource will provide measurement capability and expertise to a research community that requires highly sensitive, quantitative isotope analyses. Since commissioning a new accelerator mass spectrometer in June 2014, we have measured over 4000 samples a year for collaborators and service users. The User Resource will enable us to continue to meet these research needs, as well as provide for new users whose research programs would benefit from AMS as a measurement tool. The User Resource’s forte will be ultra-high sensitivity quantitation of radiocarbon and selected other radioisotopes for research studies where isotopes are required. Radioisotope labeling studies have been and will continue to be an important tool for addressing many complex biomedical science problems. AMS is a specialized and unique type of mass spectrometry that provides absolute quantitation of radiocarbon and other relevant radioisotopes with extreme sensitivity, having limits of detection in real samples on the order of a few attomol/mg of sample at measurement precisions of ~3%. It is the only instrumental method capable of quantifying radioisotope-labeled agents routinely in real-world samples with such precision and sensitivity. The sensitivity of AMS allows for the quantification of radiolabeled metabolites in extremely complex matrices of cells and organisms at very low concentrations and in small samples. AMS allows studies to be conducted without perturbing metabolism leading to more relevant quantification of metabolic rates and pathways. In addition, it enables quantification of pharmacokinetic and metabolic properties of toxicants at environmentally relevant concentrations in model systems as well as the ability to quantify pharmacokinetics and other molecular endpoints directly in humans. Such quantitative assessments can 1) improve risk assessment for toxicants, 2) address safety and efficacy considerations for therapeutic entities, 3) deepen understanding of xenobiotic and intermediary metabolism, 4) help understand the interactions between critical molecular pathways, and 5) improve efforts to model and predict various metabolic and biological states. These capabilities have been applied in a number of areas including research in carcinogenesis, toxicology, nutrition, pharmacology/drug development and basic biological science. As a NIGMS National Resource the National User Resource for Biological Accelerator Mass Spectrometry will help NIH funded scientists achieve a deeper understanding of the etiology of human health concerns by (1) enabling the quantification of pharmacokinetics and other molecular endpoints directly in humans; (2) offering the ability to conduct quantitative studies using biologics such as proteins or lipids, and thereby reducing the amount of radioisotope usage in biomedical labs; and (3) enabling more relevant studies of metabolic pathways in health and disease through the use of much lower, more biologically-relevant, concentrations of metabolic substrates in cells and intact organisms. Such studies support NIGMS’s basic biomedical research areas that contribute to the understanding of fundamental cellular and physiological principles and enable research supported by the Biophysics, Biomedical Technology, and Computational Biosciences (BBCB); Genetics and Molecular, Cellular, and Developmental Biology (GMCDB); Pharmacology, Physiology, Biological Chemistry (PPBC) and Training, Workforce Development, and Diversity (TWD) Divisions. Over the next five years, our goals are to: 1. Improve the efficiency of operation for AMS measurements through installation of new interfaces to our AMS systems, technical modifications to improve gas accepting ion source efficiency and upgrading our data analysis software for improved ease of use and data reporting. 2. Increase the accessibility and visibility of ultra-sensitive 14C measurements for the biomedical research community by training of new investigators and expanding our national user base. 3. Provide high throughput, ultra-sensitive 14C analysis for the NIGMS and NIH user community.

47 OTHER INSTRUMENTATION↗

DOE OSTI2016

Preparatory Verification of a New Monte Carlo Code cosRMC based on VERA Core Physics Benchmark

To promote nuclear power plant system design and simulation software self-reliance development, DOE of China approved a R and D key project to develop an integrated engine for pressurized water reactor core and system design and analysis, referred as COSINE hereafter. The scope of this code package includes reactor physics, thermal hydraulics, safety analysis, severe accidents, probability safety assessment and etc. Many universities, research institutes and nuclear related corporations in China are involved in the code development, among which the State Nuclear Power Software Development Center (SNPSDC) plays the leading role. With the requirement of accurate three-dimensional modeling of the advanced, special or new complex core in reactor neutronics and shielding analysis, Monte Carlo method is becoming a more powerful tool for reactor analysis. Thus, a new Monte Carlo transport code named cosRMC (abbreviation for COSINE Reactor Monte Carlo) has been developed jointly by SNPSDC and Department of Engineering Physics, Tsinghua University, the main developer of RMC code. The cosRMC now has many functions as criticality calculation, fixed-source calculation, burnup calculation, and etc. Some techniques for geometry treatment, new burnup algorithm, source convergence acceleration, massive tally and parallel calculation have been implemented in cosRMC to improve the efficiency. In order to ensure its reliability, several types of V and V work have been and are being carried out for cosRMC. In this paper, some preparatory verification results based on VERA Core Physics Benchmark are presented. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2015

Optimizing Geothermal Drilling: Oil and Gas Technology Transfer

There is a significant amount of financial risk associated with geothermal drilling. This study of drilling operations seeks opportunities to improve upon current practices and technologies. The scope of this study included analyzing 21 geothermal wells and 21 oil and gas wells. The goal was to determine a 'Perfect Well' using historical data to compare the best oil and gas well to the best geothermal well. Unfortunately, limitations encountered in the study included missing data (bit records, mud information, etc.) and poor data collection practices An online software database was used to format drilling data to IADC coded daily drilling reports and generate figures for analysis. Six major issues have been found in geothermal drilling operations. These problems include lost circulation, rig/ equipment selection, cementing, penetration rate, drilling program, and time management. As a result of these issues, geothermal drilling averaged 56.4 days longer than drilling comparable oil and gas wells in the wells in this study. Roughly $13.9 million was spent on non-productive time in the 21 geothermal wells, compared with only $1.3 million in the oil and gas wells, assuming a cost of $50,000 per day. Comparable events such as drilling the same sized hole, tripping in/out, cementing, and running the same size casing took substantially less time in the oil and gas wells. Geothermal wells were drilled using older and/or less advanced technology to depths less than 10,000 feet, while oil and gas wells reached 12,500 feet faster with purpose built rigs. A new approach is now underway that will optimize drilling programs throughout the drilling industry using Mechanical Specific Energy (MSE) as a tool to realize efficient drilling processes. Potential improvements for current geothermal operations are: the use of electronic records, real time services, and official glossary terms to describe rig operations, and advanced drilling rigs/technology.

15 GEOTHERMAL ENERGY↗

NASA NTRS2013

NASA Tech Briefs, July 2013

Dielectrophoresis-Based Particle Sensor Using Nanoelectrode Arrays; Multi-Dimensional Damage Detection for Surfaces and Structures; ULTRA: Underwater Localization for Transit and Reconnaissance Autonomy; Autonomous Cryogenic Leak Detector for Improving Launch Site Operations; Submillimeter Planetary Atmospheric Chemistry Exploration Sounder; Method for Reduction of Silver Biocide Plating on Metal Surfaces; Silicon Micromachined Microlens Array for THz Antennas; Forward-Looking IED Detector Ground Penetrating Radar; Fully Printed, Flexible, Phased Array Antenna for Lunar Surface Communication, Battery Charge Equalizer with Transformer Array; An Efficient, Highly Flexible Multi-Channel Digital Downconverter Architecture; Dimmable Electronic Ballast for a Gas Discharge Lamp; Conductive Carbon Nanotube Inks for Use with Desktop Inkjet Printing Technology; Enhanced Schapery Theory Software Development for Modeling Failure of Fiber-Reinforced Laminates; High-Performance, Low-Temperature-Operating, Long-Lifetime Aerospace Lubricants; Carbon Nanotube Microarrays Grown on Nanoflake Substrates; Differential Muon Tomography to Continuously Monitor Changes in the Composition of Subsurface Fluids; Microgravity Drill and Anchor System; 20 Granular Media-Based Tunable Passive Vibration Suppressor; 21 Miga Aero Actuator and 2D Machined Mechanical Binary Latch; Micro-XRF for In Situ Geological Exploration of Other Planets; Hydrogen-Enhanced Lunar Oxygen Extraction and Storage Using Only Solar Power; Uplift of Ionospheric Oxygen Ions During Extreme Magnetic Storms; Miniaturized, High-Speed, Modulated X-Ray Source; Hollow-Fiber Spacesuit Water Membrane Evaporator 25 High-Power Single-Mode 2.65-micrometers InGaAsSb/AlInGaAsSb Diode Lasers; Optical Device for Converting a Laser Beam Into Two Co-aligned but Oppositely Directed Beams; A Hybrid Fiber/Solid-State Regenerative Amplifier with Tunable Pulse Widths for Satellite Laser Ranging; X-Ray Diffractive Optics; SynGenics Optimization System (SynOptSys); 29 CFD Script for Rapid TPS Damage Assessment; radEq Add-On Module for CFD Solver Loci-CHEM; Science Opportunity Analyzer (SOA) Version 8; 30 Autonomous Byte Stream Randomizer; Distributed Engine Control Empirical/Analytical Verification Tools; Dynamic Server-Based KML Code Generator Method for Level-of-Detail Traversal of Geospatial Data; Automated Planning of Science Products Based on Nadir Overflights and Alerts for Onboard and Ground Processing; Linked Autonomous Interplanetary Satellite Orbit Navigation; Risk-Constrained Dynamic Programming for Optimal Mars Entry, Descent, and Landing; Scheduling Operations for Massive Heterogeneous Clusters; Deepak Condenser Model (DeCoM); Flight Software Math Library; Recirculating 1-K-Pot for Pulse-Tube Cryostats; 35 Method for Processing Lunar Regolith Using Microwaves; Wells for In Situ Extraction of Volatiles from Regolith (WIEVR); and Estimating the Backup Reaction Wheel Orientation Using Reaction Wheel Spin Rates Flight Telemetry from a Spacecraft.

Source record↗

DOE OSTI2022

WISP: Watching grid Infrastructure Stealthily through Proxies (Final Technical Report)

The complex interdependencies of cyber systems (sensors and communications), physical grids and associated electricity market operations make protecting electric power grids a significant challenge. The energy sector is constantly under new, targeted, advanced and dangerous cyber-attacks that have the potential to result in the loss of human life. These threats are further exacerbated by our need to modernize the grid. One focus of cyber security research in smart grids is the securing of the SCADA system through advanced intrusion detection systems (IDS) and bad data detection algorithms in state estimation. These methods either require full knowledge of the system topology and parameters or fail to understand the physical behaviors under attack. WISP (Watching grid Infrastructure Stealthily through Proxies) is designed to provide additional protection to the power grid using only publicly available data. In particular, WISP exploits the spatio-temporal nature of the real time locational marginal prices (LMPs), in conjunction with other information such as bids, weather, outages and load data to analyze anomalous power pricing behaviors and then correlate those observations to localize regions of interest and identify potential cyber events. WISP is non-intrusive as the tool is deployed as a service in the Cloud or on premise and provides reliable information to system operators for enhanced situational awareness, without impeding energy delivery functions. The WISP technology comprises three modules: the data-driven anomaly detection core, the vulnerability and risk analysis and the root cause analysis. The data-driven anomaly detection core performs the tasks of feature selection, anomaly detection and attack region localization. The vulnerability and risk analysis module provides system level information of the vulnerable variables and times, assisting the operators in selecting monitoring and protection nodes. The root cause analysis module takes the detection results and identifies potential operational conditions that contribute to the detected anomalies. In Phase I, we have demonstrated the feasibility and effectiveness of WISP. We developed a realistic electricity market simulator capable of generating normal and attack market data under various operational conditions. We developed a series of cyber-attack detection and analysis algorithms and evaluated them under multiple data sources. Finally, we integrated all modules into an end-to-end software, providing functions for data management, data analytics and visualization. Specifically, we have achieved: (i) real-time data acceptance from external utility interfaces with >99% acceptance rate; (ii) high performance anomaly detection algorithms with >98% detection accuracy and <0.1% false alarm rate; and (iii) ultra-low computing delay <50 milliseconds. Additionally, our team developed algorithms to identify the vulnerable variables in electricity market operations and root cause analysis functions to identify major contributors to the price spikes. These ancillary modules are necessary when deploying WISP in real world industry environment. In Phase II, we have demonstrated the effectiveness of WISP software on realistic largescale power systems. We performed red team testing for the Phase I WISP software and identified software vulnerabilities and implemented corresponding mitigation solutions. We adapted the electricity market simulator for the Texas synthetic 2000-bus system and generated datasets for the false data injection attacks. We created database and visualization interfaces for the Texas system and the ISO New England system. We performed software optimization in terms of operation efficiency, computing speed and detection accuracy. Finally, we tested the software on the Texas system and the ISO New England system and evaluated the detection performance. Overall, we achieved above 89% detection rate, below 3% false alarm rate and below 37 seconds of end-to-end detection delay.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2015

Optimizing Geothermal Drilling: Oil and Gas Technology Transfer

There is a significant amount of financial risk associated with geothermal drilling; however, there are opportunities to improve upon current practices and technologies used. The scope of this drilling operational study included 21 geothermal wells and 21 oil and gas wells. The goal was to determine a 'perfect well' using historical data to compare the best oil and gas well to the best geothermal well. Unfortunately, limitations encountered in the study included missing data (bit records, mud information, etc.), poor data collection, and difficult to ascertain handwriting. An online software database was used to format drilling data to IADC coded daily drilling reports and generate analysis figures. Six major issues have been found in geothermal drilling operations. These problems include lost circulation, rig/equipment selection, cementing, penetration rate, drilling program, and time management. As a result of these issues, geothermal drilling averages 56.4 days longer than drilling comparable oil and gas wells in the wells in this study. Roughly $13.9 million would be lost due to non-productive time in the 21 geothermal wells and only $1.3 million in the oil and gas wells, assuming a cost of $50,000 per day. Comparable events such as drilling the same sized hole, tripping in/out, cementing, and running the same size casing took substantially less time in the oil and gas wells. Geothermal wells were drilled using older and/or less advanced technology to depths less than 10,000 feet, while oil and gas wells reached 12,500 feet faster with purpose built rigs. A new approach is now underway that will optimize drilling programs throughout the drilling industry. It is the use of Mechanical Specific Energy (MSE) as a tool to realize efficient drilling processes. However, a work-flow must also be established in order for there to be an efficient drilling program. Potential improvements for current geothermal operations are: the use of electronic records, real time services, and official glossary terms to describe rig operations, and advanced drilling rigs/technology.

15 GEOTHERMAL ENERGY↗

NASA NTRS2004

Advanced Signal Conditioners for Data-Acquisition Systems

Signal conditioners embodying advanced concepts in analog and digital electronic circuitry and software have been developed for use in data-acquisition systems that are required to be compact and lightweight, to utilize electric energy efficiently, and to operate with high reliability, high accuracy, and high power efficiency, without intervention by human technicians. These signal conditioners were originally intended for use aboard spacecraft. There are also numerous potential terrestrial uses - especially in the fields of aeronautics and medicine, wherein it is necessary to monitor critical functions. Going beyond the usual analog and digital signal-processing functions of prior signal conditioners, the new signal conditioner performs the following additional functions: It continuously diagnoses its own electronic circuitry, so that it can detect failures and repair itself (as described below) within seconds. It continuously calibrates itself on the basis of a highly accurate and stable voltage reference, so that it can continue to generate accurate measurement data, even under extreme environmental conditions. It repairs itself in the sense that it contains a micro-controller that reroutes signals among redundant components as needed to maintain the ability to perform accurate and stable measurements. It detects deterioration of components, predicts future failures, and/or detects imminent failures by means of a real-time analysis in which, among other things, data on its present state are continuously compared with locally stored historical data. It minimizes unnecessary consumption of electric energy. The design architecture divides the signal conditioner into three main sections: an analog signal section, a digital module, and a power-management section. The design of the analog signal section does not follow the traditional approach of ensuring reliability through total redundancy of hardware: Instead, following an approach called spare parts tool box, the reliability of each component is assessed in terms of such considerations as risks of damage, mean times between failures, and the effects of certain failures on the performance of the signal conditioner as a whole system. Then, fewer or more spares are assigned for each affected component, pursuant to the results of this analysis, in order to obtain the required degree of reliability of the signal conditioner as a whole system. The digital module comprises one or more processors and field-programmable gate arrays, the number of each depending on the results of the aforementioned analysis. The digital module provides redundant control, monitoring, and processing of several analog signals. It is designed to minimize unnecessary consumption of electric energy, including, when possible, going into a low-power "sleep" mode that is implemented in firmware. The digital module communicates with external equipment via a personal-computer serial port. The digital module monitors the "health" of the rest of the signal conditioner by processing defined measurements and/or trends. It automatically makes adjustments to respond to channel failures, compensate for effects of temperature, and maintain calibration.

Lucena, Angel↗

DOE OSTI2016

SU-D-204-01: A Methodology Based On Machine Learning and Quantum Clustering to Predict Lung SBRT Dosimetric Endpoints From Patient Specific Anatomic Features

Purpose: To develop a data-mining methodology based on quantum clustering and machine learning to predict expected dosimetric endpoints for lung SBRT applications based on patient-specific anatomic features. Methods: Ninety-three patients who received lung SBRT at our clinic from 2011–2013 were retrospectively identified. Planning information was acquired for each patient, from which various features were extracted using in-house semi-automatic software. Anatomic features included tumor-to-OAR distances, tumor location, total-lung-volume, GTV and ITV. Dosimetric endpoints were adopted from RTOG-0195 recommendations, and consisted of various OAR-specific partial-volume doses and maximum point-doses. First, PCA analysis and unsupervised quantum-clustering was used to explore the feature-space to identify potentially strong classifiers. Secondly, a multi-class logistic regression algorithm was developed and trained to predict dose-volume endpoints based on patient-specific anatomic features. Classes were defined by discretizing the dose-volume data, and the feature-space was zero-mean normalized. Fitting parameters were determined by minimizing a regularized cost function, and optimization was performed via gradient descent. As a pilot study, the model was tested on two esophageal dosimetric planning endpoints (maximum point-dose, dose-to-5cc), and its generalizability was evaluated with leave-one-out cross-validation. Results: Quantum-Clustering demonstrated a strong separation of feature-space at 15Gy across the first-and-second Principle Components of the data when the dosimetric endpoints were retrospectively identified. Maximum point dose prediction to the esophagus demonstrated a cross-validation accuracy of 87%, and the maximum dose to 5cc demonstrated a respective value of 79%. The largest optimized weighting factor was placed on GTV-to-esophagus distance (a factor of 10 greater than the second largest weighting factor), indicating an intuitively strong correlation between this feature and both endpoints. Conclusion: This pilot study shows that it is feasible to predict dose-volume endpoints based on patient-specific anatomic features. The developed methodology can potentially help to identify patients at risk for higher OAR doses, thus improving the efficiency of treatment planning. R01-184173.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2019

A Model for Lean Corporate/ Startup Interfaces: Unlocking Resources of Midcap Corporations Providing a Pathway to Advanced Energy Technologies

Commercializing energy technologies through traditional market pathways is challenging for early-stage energy innovators. Development cycles in energy are long and expensive, and adoption is difficult, making energy technologies of limited interest to venture capital relative to industries with faster growth and shorter product life cycles such as life sciences and software. As such, partnerships with established corporations are one of the most promising, and in some cases only, go-to-market pathways for energy technologies. Startups often seek to work with, large well-known Fortune 500 (and similar) companies. However, the size and risk aversion of those firms often makes partnering challenging. It can take well over 12 months for a large corporation to agree to commercial terms and get internal board / management approval to move forward with a binding agreement with a startup for even a simple starting partnership. This timeline is prohibitive for most early-stage companies who are both time and money constrained, and often working in highly competitive commodity sectors. Mid-cap corporations ($\$ $100M to $\$ $10B) are a promising but untapped resource for partnering with technology developers because they are often nimbler, tend to be fiercely competitive, and are looking for new revenue or cost-saving opportunities. These factors make them both more receptive to disruptive technologies, and more capable of integrating them. However, while Fortune 500 companies often have venturing groups that facilitate the initial connection process, most midcap incumbents do not have the resources to create standalone corporate venture groups. As a result, although they could help each other significantly (startup technologies make midcaps more competitive; midcaps offer a faster commercialization pathway to startups), midcap companies and startups rarely work together. In 2017, ADL Ventures (ADL) received Award #DE-EE0008111 from DOE EERE’s Innovative Pathways program to unlock the domain expertise and material resources of midcap companies. The goal of the award was to support energy technology commercialization via an innovation platform for startups to interface with midcap corporations. During the grant period, we have developed a novel open innovation platform that allows financially conservative incumbents to efficiently engage with energy innovators and startups, thereby unlocking the incumbents’ domain expertise, strategic capital, R&D facilities, supply chain, and pathways to market. We have executed full-scale open innovation challenges for three clients, exceeding the initial proposed goal of two. We also built a diversified opportunity pipeline which resulted in four projects contracted for 2020, meeting the goals of the proposal, with others pending.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

NASA NTRS2001

Extraction of Airport Features from High Resolution Satellite Imagery for Design and Risk Assessment

The LPA Group, consisting of 17 offices located throughout the eastern and central United States is an architectural, engineering and planning firm specializing in the development of Airports, Roads and Bridges. The primary focus of this ARC project is concerned with assisting their aviation specialists who work in the areas of Airport Planning, Airfield Design, Landside Design, Terminal Building Planning and design, and various other construction services. The LPA Group wanted to test the utility of high-resolution commercial satellite imagery for the purpose of extracting airport elevation features in the glide path areas surrounding the Columbia Metropolitan Airport. By incorporating remote sensing techniques into their airport planning process, LPA wanted to investigate whether or not it is possible to save time and money while achieving the equivalent accuracy as traditional planning methods. The Affiliate Research Center (ARC) at the University of South Carolina investigated the use of remotely sensed imagery for the extraction of feature elevations in the glide path zone. A stereo pair of IKONOS panchromatic satellite images, which has a spatial resolution of 1 x 1 m, was used to determine elevations of aviation obstructions such as buildings, trees, towers and fence-lines. A validation dataset was provided by the LPA Group to assess the accuracy of the measurements derived from the IKONOS imagery. The initial goal of this project was to test the utility of IKONOS imagery in feature extraction using ERDAS Stereo Analyst. This goal was never achieved due to problems with ERDAS software support of the IKONOS sensor model and the unavailability of imperative sensor model information from Space Imaging. The obstacles encountered in this project pertaining to ERDAS Stereo Analyst and IKONOS imagery will be reviewed in more detail later in this report. As a result of the technical difficulties with Stereo Analyst, ERDAS OrthoBASE was used to derive aviation obstruction measurements for this project. After collecting ancillary data such as GPS locations, South Carolina Geodetic Survey and Aero Dynamics ground survey points to set up the OrthoBASE Block File, measurements were taken of the various glide path obstructions and compared to the validation dataset. This process yielded the following conclusions: The IKONOS stereo model in conjunction with Imagine OrthoBASE can provide The LPA Group with a fast and cost efficient method for assessing aviation obstructions. Also, by creating our own stereo model we achieved any accuracy better currently available commercial products.

Robinson, Chris↗

DOE OSTI2020

Heat Integration Optimization and Dynamic Modeling Investigation for Advancing the Coal-Direct Chemical Looping Process

The purpose of the project is to address the optimization and startup operation of a modular coal direct chemical looping (CDCL) combustion system integrated with a steam cycle for power generation to reduce the risks involved in further scale-up of the technology. The modular reactor design of the CDCL process provides flexibility in the fabrication of the reactor and in its operating capacity (i.e. turndown ratio) at the cost of a more complex heat exchange network (HEN) design and integration. To address the technology gaps and advance the efficiency and economic feasibility of the CDCL technology, the project will perform a detailed and comprehensive analysis of the integration of a modular CDCL reactor system and a steam cycle system under both static and transient conditions via HEN process performance simulations and system dynamic modeling, respectively. The scope of work consists of 1) Experimental and computational studies of the CDCL combustor reactor 2) Comprehensive static (i.e. steady-state) system HEN design analysis in CDCL 550 MWe commercial unit for power generation and 3) Dynamic modeling of site specific design of 10MWe CDCL large pilot plant. The project team has successfully developed and validated a kinetic model for the oxidation of oxygen carriers in the combustor using the unreacted shrinking core model (UCSM). The model is capable of capturing the oxidation kinetics of fully or partially reduced oxygen carrier particles. A computational fluid dynamics (CFD) model is developed to simulate the hydrodynamics, heat transfer, and chemical reaction occurring in the CDCL combustor. The model is developed in MFIX and ANSYS Fluent. Key aspects of CDCL combustor operation, including heat transfer, oxygen carrier oxidation, and the transport of oxygen carrier particles, are simulated using this CFD model. The HEN for a commercial scale 550 MWe CDCL power plant is simulated and optimized using ASPEN Plus. Practical design considerations are incorporated based on industrial experiences. The performance and cost for the commercial CDCL plant is updated based on these analyses. A dynamic model for the 10 MWe CDCL pilot plant is developed in ProTRAX simulation software. The model is based on the pilot plant design developed in project DE-FE0027654 “10 MWe CDCL Large Pilot Plang – Pre-FEED Study” and the steam cycle data obtained from Dover Light & Power plant. The transient behaviors during pilot plant load variation are simulated using the dynamic model.

01 COAL, LIGNITE, AND PEAT↗

NASA NTRS2026

Prototype Demonstration of Solar Carbothermal System to Extract Oxygen from Regolith

The Carbothermal Reduction Demonstration (CaRD) project was an effort to develop a prototype system to demonstrate the extraction of oxygen from simulated lunar regolith using concentrated solar energy and a carbothermal reaction. The prototype consisted of a deployable solar concentrator capable of tracking the sun, carbothermal reactor, fluid system, gas analysis, and a solar concentrator control system consisting of avionics and software. These subsystems were developed by multiple NASA centers and a private industry partner, Sierra Space. The various teams worked together to define requirements and interfaces to successfully assemble the complex system and demonstrate an integrated solar carbothermal process. The solar concentrator developed at Glenn Research Center (GRC) was designed to be stowed for a launch environment then deployed on the lunar surface. It utilized a crossed dragone configuration of composite mirrors to direct horizontal sunlight onto a target 90° from the incoming sunlight. The key performance parameters for the solar concentrator were efficiency and power density. The carbothermal reactor was developed by Sierra Space through a separate project called the Carbothermal Oxygen Production Reactor (COPR) where it successfully demonstrated a fully automated process in a thermal vacuum environment. The fluid system needed for the carbothermal reaction was also developed by Sierra Space and successfully demonstrated in the same thermal vacuum test. The gas analysis system was developed at Kennedy Space Center (KSC) and was required to determine the amount of oxygen extracted during each test. The gas analysis system was based on the Mass Spectrometer Observing Lunar Operations (MSOLO) instrument. Avionics and software for the CaRD prototype were also developed at KSC and based on experience with MSOLO avionics and software. The control system was designed to stow, deploy, track the sun, and perform beam alignment of the concentrated light. The prototype subsystems were integrated and tested at Johnson Space Center’s (JSC) Energy Systems Test Area. A heliostat was used to direct sunlight toward the prototype in a way that is representative of the sunlight conditions at the south pole of the Moon. When concentrated sunlight was focused on simulated lunar regolith within the reactor, the gas analysis team confirmed the presence of carbon monoxide gas, which confirmed that a solar carbothermal reaction took place. The key performance parameter for the integrated prototype was grams of oxygen extracted per kilowatt hour of energy arriving at the concentrator primary mirror. The prototype design successfully demonstrated end-to-end capability and further steps to achieve a flight capable system have been defined. With lunar data, engineers would be able to design a scaled-up system capable of extracting oxygen from regolith at useful quantities for crew life support and rocket propellant. On the long term, this method of In-Situ Resource Utilization could be used to drastically reduce the cost and risk of a sustained human presence on the Moon by reducing the amount of oxygen that would have to be delivered.

Aaron Paz↗

NASA NTRS2026

Prototype Demonstration of an Integrated Solar Concentrator System and Carbothermal Reactor Using Solar Energy to Extract Oxygen from Regolith

Oxygen from Regolith↗

NASA NTRS2026

Prototype Demonstration of Solar-Carbothermal System to Extract Oxygen From Regolith

The Carbothermal Reduction Demonstration (CaRD) project was an effort to develop a prototype system to demonstrate the extraction of oxygen from simulated lunar regolith using concentrated solar energy and a carbothermal reaction. The prototype consisted of a deployable solar concentrator capable of tracking the sun, carbothermal reactor, fluid system, gas analysis, and a solar concentrator control system consisting of avionics and software. These subsystems were developed by multiple NASA centers and a private industry partner, Sierra Space. The various teams worked together to define requirements and interfaces to successfully assemble the complex system and demonstrate an integrated solar carbothermal process. The solar concentrator developed at Glenn Research Center (GRC) was designed to be stowed for a launch environment then deployed on the lunar surface. It utilized a crossed dragone configuration of composite mirrors to direct horizontal sunlight onto a target 90° from the incoming sunlight. The key performance parameters for the solar concentrator were efficiency and power density. The carbothermal reactor was developed by Sierra Space through a separate project called the Carbothermal Oxygen Production Reactor (COPR) where it successfully demonstrated a fully automated process in a thermal vacuum environment [1]. The fluid system needed for the carbothermal reaction was also developed by Sierra Space and successfully demonstrated in the same thermal vacuum test. The gas analysis system was developed at Kennedy Space Center (KSC) and was required to determine the amount of oxygen extracted during each test. The gas analysis system was based on the Mass Spectrometer Observing Lunar Operations (MSOLO) instrument. Avionics and software for the CaRD prototype were also developed at KSC and based on experience with MSOLO avionics and software. The control system was designed to stow, deploy, track the sun, and perform beam alignment of the concentrated light. The prototype subsystems were integrated and tested at Johnson Space Center’s (JSC) Energy Systems Test Area. A heliostat was used to direct sunlight toward the prototype in a way that is representative of the sunlight conditions at the south pole of the Moon. When concentrated sunlight was focused on simulated lunar regolith within the reactor, the gas analysis team confirmed the presence of carbon monoxide gas, which confirmed that a solar carbothermal reaction took place. The key performance parameter for the integrated prototype was grams of oxygen extracted per kilowatt hour of energy arriving at the concentrator primary mirror. The prototype design successfully demonstrated end-to-end capability and further steps to achieve a flight capable system have been defined. With lunar data, engineers would be able to design a scaled-up system capable of extracting oxygen from regolith at useful quantities for crew life support and rocket propellant. On the long term, this method of In-Situ Resource Utilization could be used to drastically reduce the cost and risk of a sustained human presence on the Moon by reducing the amount of oxygen that would have to be delivered.

Koorosh R Araghi↗

DOE OSTI2021

DOE Deep Energy Retrofit Cost Survey

A survey was conducted by the Lawrence Berkeley National Laboratory on deep energy retrofit (DER) market drivers, opportunities, and challenges. The survey was part a research study sponsored by the U.S. Department of Energy to gather information on the costs of DER from home performance contractors and stakeholders. Cost data was gathered from DER projects that use a comprehensive, whole-home approach to drastically reduce energy use and improve performance. DER projects often aim at reducing energy use by 50% or more. In addition, these projects can improve home comfort and potentially benefiting occupant health. Yet, market adoption of DER has been limited. Major limiting factors include complex projects, high costs, perceived risks, extensive disruption, and unfamiliar work scopes to some contractors. In order to better understand what motivates and deters DER projects in today’s market, a survey was conducted to gather this information, and to learn about promising approaches and technologies from the industry perspective. Past surveys on homeowners and home energy performance professionals have studied the motivations and barriers of energy efficiency retrofits. Two surveys of home energy performance professionals were conducted in recent years. The Resources for the Future (RFF) Home Energy Audit and Retrofit Survey was conducted in 2011 by recruiting energy auditors and retrofit installers through members of Efficiency First and Building Performance Institute (BPI) accredited contractors. The survey asked about the business and services that respondents provide, how often homeowners follow their recommendations to retrofit their homes, and the respondents’ opinion on barriers faced by the industry. The survey found that not enough homeowners know about energy audits, but more importantly, it is the high cost of retrofits compared to low energy prices that is responsible for few energy audits and retrofits being completed. The RESNET Deep Retrofit Industry Stakeholder Survey was conducted shortly after launching of the EnergySmart Home Performance Team program. The EnergySmart Team program involves a formal agreement among allied contractors who are engaged in high performance retrofits. Using this allied team approach, teams can pool their expertise and provide each other with customer referrals. The survey asked EnergySmart Team members and outside stakeholders on questions about market and technical barriers in performing home energy retrofits. Survey respondents identified lack of consumer awareness and lack of affordable financing for consumers as the leading market barriers to home energy retrofits. In their written comments, many survey respondents also echoed that the high costs of retrofit compared to low energy prices is a market barrier. Respondents found “certain housing characteristics that prevent effective retrofit” and “energy analysis software inaccuracy or limitations” are the two leading technical barriers. Their choices for technical barriers were reflective of the energy rater/auditor role played by the majority (78%) of the survey respondents. In comparison to past surveys, this work aimed to gather inputs from a broader segment of the home performance industry to identify the opportunities and barriers faced by DERs from all perspectives. The survey asks for project costs to help breakdown the high costs of DERs. This survey is also motivated by a need to better understand the role of DERs in reducing energy use by the residential sectors and meeting climate goals. The survey is designed towards obtaining more substantive inputs from survey respondents by encouraging written comments, rather than setting the goal to reach a large number of respondents. We took this approach because DER is currently still a niche market, so it is more valuable to gather in-depth inputs from individuals who are performing this work rather than getting to the masses.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

NASA NTRSDate not supplied

Human Capabilities Assessments for Autonomous Missions: A Multi-Team Research Effort to Reduce Risk in the Human-System Integration Architecture for Future Deep-Space Missions

In future exploration missions beyond low earth-orbit, crew will have to execute complex operations and respond to off-nominal events, without real-time support from Mission Control. It is anticipated that increased reliance on automated systems, including human-centric vehicle and information architecture, will need to be designed to support the crew; increased risk to performance, health, and safety may occur if these are not implemented appropriately. The Human Factors and Behavioral Performance Element (HFBP) in the NASA Human Research Program supports research to characterize and mitigate such human health and performance risks, including the Risk of Adverse Outcome Due to Inadequate Human Systems Integration Architecture (HSIA). The HSIA risk addresses the integration of onboard capability and the crew roles and responsibilities necessary to enable the crew to respond effectively and efficiently in the increasingly autonomous mission operations environment. In 2017, HFBP released the “Human Capabilities Assessments for Autonomous Missions” (HCAAM) research topic to address HSIA related questions. HCAAM is a major NASA research effort that has assembled a multidisciplinary team from seven institutions to work closely with design and engineering efforts on research towards developing and refining human performance standards, guidelines and automation tools. The scientific focus is on quantitative assessment of human capabilities relevant to future deep-space missions during which earth/spacecraft communication is so delayed and intermittent that the crew must be able to function autonomously. The integrated strategy of the HCAAM project characterizes human capabilities and limitations related to potential performance decrements during long duration exploration mission spaceflight as relevant to both routine and complex task performance; defines system characteristics that reduce the likelihood or impact of potential decrements in human performance capabilities; performs integrated assessment of intelligent system responses within the context of an operational environment with relevant NASA tools, systems, and data structures in order to determine positive or negative interactions and validate recommended approaches; and proposes specific updates to existing standards and guidelines for inclusion in NASA handbooks for the design of future spacecraft intelligent systems that provide crew performance assessment/feedback, and to also serve as decision-support aids for the onboard crew (i.e., NASA-STD-3001, and NASA/SP-Human Integration Design Handbook (HIDH)). The scientific research vectors being addressed by the seven HCAAM teams include: - crew task performance (accuracy, efficiency) (crew + automation) - crew performance (accuracy, efficiency) - crew Situation Awareness - procedure design and multi-modal enhancement - concurrent tasking (mixed manual + some level of autonomy) - task handover - crew self-planning and time-lining - task design - trust in automation, real-time calibration - human multi-sensory feedback and guidance - human trust in on-board software-based intelligent assistants - virtual assistants The presentation will highlight plans and progress made in each of these research areas as well as the methods by which surrogate astronaut crews in the NASA JSC HERA spaceflight analog facility will function as human test subjects for all of the HCAAM research projects.

HCAAM VNSCOR↗