Search NASA⌕ Search

SEARCH · Search NASA

Results for “engineered interventions”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Methane Mitigation Thermoelectric Generator (MMTEG) (Final Scientific/ Technical Report)

Gas Technology Institute (GTI) has completed a $1.815M (plus $500K cost share), 54-month Co-operative agreement with the Department of Energy’s National Energy Technology Laboratory to develop a Methane Mitigation Thermoelectric Generator (MMTEG) system for gas field applications. This novel system uses fugitive gas to produce electrical power and consists of Thermoelectric Generators (TEG) driven by a linear burner, an air compressor, an accumulator, valves, batteries, and power electronics. The electrical power generated by the system is used to compress air and, in turn, the air is used to operate the pneumatic valves at the well site instead of using natural gas (NG) which would then be vented. The team completed the project objectives which included (1) Design, fabricate and test an integrated 6We nominal MMTEG prototype system, (2) Design a “retrofit kit” MMTEG system capable of being field tested at a gas well production site, and (3) build and test the field MMTEG system in a laboratory environment. Multiple system options were developed prior to selecting a “Passive” system which meets cost, NG savings, and greenhouse gas (GHG) reduction targets although not as efficient as initially planned. The MMTEG system is built primarily from commercial off-the-shelf parts (in some cases re-purposed) including the heat exchanger, heat rejection, electronic components, and also the TEGs. The team developed and implemented a novel system including the control system developed by Morrison Applied Sciences (MAS). The team completed incremental demonstrations of the hardware prior to the MMTEG system demonstration. A one-year simulation of the air delivery and battery charging subsystems was completed prior to the integration into the MMTEG system. In addition, the team simulated two-years of thermal cycles for integrated Burner/TEG/heat rejection subsystem. Finally, the entire MMTEG system was assembled, and troubleshooting was completed over a two-week period. Next, the MMTEG system was tested to simulate over 15 weeks of entire system operation over approximately four weeks in an accelerated test fashion with minimal intervention (such as changing fuel tanks). The MMTEG system met the key goals of a unit cost of under $1500 while saving 97% of NG expended today (including leakage) on average by pneumatic systems venting to the atmosphere. The MMTEG system reduced GHG emissions by 1000X (using the methane intensification factor of 28 relative to CO2). GTI is currently pursuing a field test of the MMTEG system. Interfacing with producers has provided additional insight into system improvements. Planned improvements include additional weather protection and control system improvements including the implementation of a long- range radio capability to notify operators if there is a fault.

03 NATURAL GAS↗
NASA NTRSDate not supplied

Prediction of Calcium Oxalate Stone Risk with Interventions

Introduction Mitigations intended to reduce bone mineral loss in-flight also influence the level of renal stone risk to astronauts. Extending a recent study completed by our group [1], we investigate the likely influence of combined fluid intake and Ca excretion mitigation strategies. Methods A computational biochemistry model representing CaOx crystal precipitation, growth, and agglomeration [2] is combined with a probabilistic analysis to predict the in-flight CaOx renal stone incidence risk ratio (IRR) relative to pre-flight values using 1517 astronaut 24-hour urine chemistries. The output of this simulation is used to assess the combined impact of controlling fluid intake and Ca excretion on maintaining IRR < 1.2 for > 95% of the population, a threshold determined from initial analysis of the model output compared to referent populations [1]. Results and Conclusions Figure 1 illustrates the simulated in-flight astronaut population (n=40000) with CaOx IRR > 1.2. The red lines indicate the known clinical risk boundary of each factor, and the white box is considered the area of high combined clinical risk. The simulation and identified risk threshold conform well to the expected clinical risk boundaries. The results, assuming insensible water losses equal or exceed 0.7 L/day, imply mitigations achieve risks similar to pre-flight levels when either Ca < 150 mg/day or fluid volume intake > 3.2 L/day individually, or combined Ca < 200 and fluid volume intake > 2.5 L/day. We continue to investigate similar compounded effects and look to apprise engineering trades by informing relative risk changes during mission design. References [1] D. A. Goodenow-Messman, S. A. Gokoglu, M. Kassemi, and J. Myers, Jerry G., “Characterization of Astronaut CaOx Renal Stone Incidence Rates to Quantify In-flight and Post-flight Relative Risk,” npj Microgravity, in review, 2021. [2] M. Kassemi and D. Thompson, “Prediction of renal crystalline size distributions in space using a PBE analytic model. 1. Effect of microgravity-induced biochemical alterations,” Am. J. Physiol. Physiol., vol. 311, no. 3, pp. F520–F530, Sep. 2016, doi: 10.1152/ajprenal.00401.2015.

Debra A Goodenow↗
DOE OSTI2026

Design and Integration of a Compact Mobile Outdoor Soil Sampling Agricultural Robot

The lack of feedback on soil management for crop systems necessitates the collection of soil samples to derive insights into prevailing soil conditions. Achieving an accurate model of these plantations requires a substantial number of soil samples, which is a labor-intensive process that can suffer from inconsistencies in both the methodology of collection and the locations from which samples are gathered. In addition, the close spacing of crop rows constrains the maneuverability of mobile agricultural equipment during sample collection. This article proposes the use of agricultural robotics to facilitate the acquisition of composite soil samples with minimal human intervention, allowing for precise data collection for a Populus plant system. More specifically, this article presents a case study on the design and construction of a compact agricultural robot for soil sample collection. The performance of the robot, including its soil collection efficacy, maneuverability, and positional accuracy, is evaluated.

42 ENGINEERING↗
NASA NTRS1982

Component-specific modeling

The ability to accurately structurally analyze engine components to assure that they can survive for their designed lifetime in an increasingly harsh environment is discussed. Under the HOST (HOt Section Technology) program, advanced component-specific modeling methods, with built-in analysis capability, will be developed separately for burner liners, turbine blades and vanes. These modeling methods will make maximum use of, but will not rely solely on, existing analysis methods and techniques, to analyze the three identified components. Nor will the complete structural analysis of a component necessarily be performed as a single analysis. The approach to be taken will develop complete software analysis packages with internal, component-specific, self-adaptive solution strategies. Each package will contain a set of modeling and analysis tools. The selection and order of specific methods and techniques within the set to be applied will depend on the specific-component, the current thermo-mechanical loading, and the current state of the component. All modeling and analysis decisions will be made internally based on developed decision criteria within the solution strategies; minimal user intervention will be required.

Hirschbein, M. S.↗
DOE OSTI2020

Genome-scale metabolic rewiring improves titers rates and yields of the non-native product indigoidine at scale

Abstract High titer, rate, yield (TRY), and scalability are challenging metrics to achieve due to trade-offs between carbon use for growth and production. To achieve these metrics, we take the minimal cut set (MCS) approach that predicts metabolic reactions for elimination to couple metabolite production strongly with growth. We compute MCS solution-sets for a non-native product indigoidine, a sustainable pigment, in Pseudomonas putida KT2440, an emerging industrial microbe. From the 63 solution-sets, our omics guided process identifies one experimentally feasible solution requiring 14 simultaneous reaction interventions. We implement a total of 14 genes knockdowns using multiplex-CRISPRi. MCS-based solution shifts production from stationary to exponential phase. We achieve 25.6 g/L, 0.22 g/l/h, and ~50% maximum theoretical yield (0.33 g indigoidine/g glucose). These phenotypes are maintained from batch to fed-batch mode, and across scales (100-ml shake flasks, 250-ml ambr®, and 2-L bioreactors).

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Approaches for effective negative pressure isolation space control to minimize airborne transmission of contaminants in residential homes

Controlling airborne transmission of contaminants including respired viruses such as SARS-CoV-2 is necessary to protect occupants living in the same house with a contagious person. The effectiveness of interventions requiring minor efforts that create a negative pressure isolation zone (IZ) for a contagious person has yet to be systematically tested for residential homes. In this study, ASHRAE Standard 170, which offers guidance for negative pressure isolation space control in healthcare facilities, was used in developing practical and attainable recommendations for residential single-family homes. The relative effectiveness of several control strategies was evaluated through experimentally conducting 17 different test cases in a manufactured single-family house laboratory. These cases were designed based on various heating, ventilation and air-conditioning (HVAC) operating scenarios, intervention measures including closing the IZ door and/or sealing over supply and return air grilles in the IZ, and utilization of bathroom exhaust or portable window fans for pressure control. Four out of 17 test cases were identified as having the potential for strong containment with adequate depressurization in the IZ. The most effective IZ depressurization was achieved through continuously operating the exhaust fan in the bathroom attached to the IZ, by installing a portable window fan that extracted air out of the IZ, and a portable room air conditioner with the AC unit exhaust duct installed in one of the IZ windows.

Construction & Building Technology↗
NASA NTRS2010

Launch Pad Coatings for Smart Corrosion Control

Corrosion is the degradation of a material as a result of its interaction with the environment. The environment at the KSC launch pads has been documented by ASM International (formerly American Society for Metals) as the most corrosive in the US. The 70 tons of highly corrosive hydrochloric acid that are generated by the solid rocket boosters during a launch exacerbate the corrosiveness of the environment at the pads. Numerous failures at the pads are caused by the pitting of stainless steels, rebar corrosion, and the degradation of concrete. Corrosion control of launch pad structures relies on the use of coatings selected from the qualified products list (QPL) of the NASA Standard 5008A for Protective Coating of Carbon Steel, Stainless Steel, and Aluminum on Launch Structures, Facilities, and Ground Support Equipment. This standard was developed to establish uniform engineering practices and methods and to ensure the inclusion of essential criteria in the coating of ground support equipment (GSE) and facilities used by or for NASA. This standard is applicable to GSE and facilities that support space vehicle or payload programs or projects and to critical facilities at all NASA locations worldwide. Environmental regulation changes have dramatically reduced the production, handling, use, and availability of conventional protective coatings for application to KSC launch structures and ground support equipment. Current attrition rate of qualified KSC coatings will drastically limit the number of commercial off the shelf (COTS) products available for the Constellation Program (CxP) ground operations (GO). CxP GO identified corrosion detection and control technologies as a critical, initial capability technology need for ground processing of Ares I and Ares V to meet Constellation Architecture Requirements Document (CARD) CxP 70000 operability requirements for reduced ground processing complexity, streamlined integrated testing, and operations phase affordability. Researchers at NASA's Corrosion Technology Laboratory at KSC are developing a smart, environmentally friendly coating system for early corrosion detection, inhibition, and self healing of mechanical damage without external intervention. This smart coating will detect and respond actively to corrosion and mechanical damage such as abrasion and scratches, in a functional and predictable manner, and will be capable of adapting its properties dynamically. This coating is being developed using corrosion sensitive microcapsules that deliver the contents of their core (corrosion inhibiting compounds, corrosion indicators, and self healing agents) on demand when corrosion or mechanical damage to the coating occurs.

Calle, Luz M.↗
DOE OSTI2026

An end-to-end workflow for executing a classically bootstrapped variational quantum algorithm on an academic quantum computer

Academic quantum computing platforms often face unique challenges in executing quantum workloads due to fragmented software environments and limited engineering support. Unlike commercial ecosystems, academic devices typically evolve without full-stack integration in mind, making it difficult to run complex applications—such as variational quantum algorithms (VQA)—reliably and efficiently. Issues such as incompatible software layers and lack of automated job management significantly increase the overhead of theory-experiment collaboration. To address these challenges, we develop a modular, end-to-end workflow that decouples application-layer code from low-level hardware control, automates circuit submission and result collection, and supports fine-grained circuit-level job scheduling and recovery. The architecture employs a dual-end application programming interface (API) design, enabling robust operation across unstable or resource-constrained hardware backends. For practical use, the framework is lightweight and user-friendly, allowing rapid prototyping of full-stack workflows using basic Python tools. We validate this workflow on a high-fidelity trapped-ion quantum computer by demonstrating a variational quantum eigensolver (VQE) experiment with a classically bootstrapped ansatz initialization technique. The system successfully executed over 60,000 circuits across multiple molecular test cases with minimal human intervention, highlighting the framework’s effectiveness in enabling reproducible, resilient quantum experimentation in academic settings.

Clifford↗
DOE OSTI2023

Accident event progression, gaps, and key performance indicators for steam generator tube rupture events in water-cooled SMRs: A review

According to historical records of reactor-related incidents, a steam generator tube rupture (SGTR) is one of the most common occurrences at operating pressurized water reactors (PWRs). Such design-basis accidents (DBAs) could lead to a direct path for radionuclides to be released to the atmosphere via the safety and relief valves, making assessments of radionuclide discharge from operating nuclear power plants (NPPs) into the environment crucial for ensuring safety. In such analyses, the primary focus has been on the extent of radioactive release, not the potential damage to the core. Moreover, significant and timely intervention by operators is needed during the initial stages of SGTRs in order to avert overfilling of the SGs, as well as to restrict the dissemination of radioactive materials. Determining the event sequence and phases that occur during an SGTR incident in an advanced passive (e.g., AP1000) water-cooled nuclear reactor is crucial for implementing effective passive safety systems (PSSs) for a specific water-cooled small modular reactor (SMR) design. Here this study provides a comprehensive review of the accident event progression, associated physical phenomena, knowledge gaps, and key performance indicators that must be evaluated and assessed in thermal-hydraulics models, based on relevant test data, respectively.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
NASA NTRS2005

SQL-RAMS

SQL-RAMS (where "SQL" signifies Structured Query Language and "RAMS" signifies Rocketdyne Automated Management System) is a successor to the legacy version of RAMS -- a computer program used to manage all work, nonconformance, corrective action, and configuration management on rocket engines and ground support equipment at Stennis Space Center. The legacy version resided in the File-Maker Pro software system and was constructed in modules that could act as standalone programs. There was little or no integration among modules. Because of limitations on file-management capabilities in FileMaker Pro, and because of difficulty of integration of FileMaker Pro with other software systems for exchange of data using such industry standards as SQL, the legacy version of RAMS proved to be limited, and working to circumvent its limitations too time-consuming. In contrast, SQL-RAMS is an integrated SQL-server-based program that supports all data-exchange software industry standards. Whereas in the legacy version, it was necessary to access individual modules to gain insight into a particular workstatus document, SQL-RAMS provides access through a single-screen presentation of core modules. In addition, SQL-RAMS enables rapid and efficient filtering of displayed statuses by predefined categories and test numbers. SQL-RAMS is rich in functionality and encompasses significant improvements over the legacy system. It provides users the ability to perform many tasks, which in the past required administrator intervention. Additionally, many of the design limitations have been corrected, allowing for a robust application that is user centric.

Alfaro, Victor O.↗
NASA NTRS2005

SQL-RAMS

SQL-RAMS (where "SQL" signifies Structured Query Language and "RAMS" signifies Rocketdyne Automated Management System) is a successor to the legacy version of RAMS a computer program used to manage all work, nonconformance, corrective action, and configuration management on rocket engines and ground support equipment at Stennis Space Center. The legacy version resided in the FileMaker Pro software system and was constructed in modules that could act as stand-alone programs. There was little or no integration among modules. Because of limitations on file-management capabilities in FileMaker Pro, and because of difficulty of integration of FileMaker Pro with other software systems for exchange of data using such industry standards as SQL, the legacy version of RAMS proved to be limited, and working to circumvent its limitations too time-consuming. In contrast, SQL-RAMS is an integrated SQL-server-based program that supports all data-exchange software industry standards. Whereas in the legacy version, it was necessary to access individual modules to gain insight to a particular work-status documents, SQL-RAMS provides access through a single-screen presentation of core modules. In addition, SQL-RAMS enable rapid and efficient filtering of displayed statuses by predefined categories and test numbers. SQL-RAMS is rich in functionality and encompasses significant improvements over the legacy system. It provides users the ability to perform many tasks which in the past required administrator intervention. Additionally many of the design limitations have been corrected allowing for a robust application that is user centric.

Alfaro, Victor O.↗
NASA NTRS2006

NASA Crew Launch Vehicle Approach Builds on Lessons from Past and Present Missions

The United States Vision for Space Exploration, announced in January 2004, outlines the National Aeronautics and Space Administration's (NASA) strategic goals and objectives, including retiring the Space Shuttle and replacing it with a new human-rated system suitable for missions to the Moon and Mars. The Crew Exploration Vehicle (CEV) that the new Crew Launch Vehicle (CLV) lofts into space early next decade will initially ferry astronauts to the International Space Station and be capable of carrying crews back to lunar orbit and of supporting missions to Mars orbit. NASA is using its extensive experience gained from past and ongoing launch vehicle programs to maximize the CLV system design approach, with the objective of reducing total lifecycle costs through operational efficiencies. To provide in-depth data for selecting this follow-on launch vehicle, the Exploration Systems Architecture Study was conducted during the summer of 2005, following the confirmation of the new NASA Administrator. A team of aerospace subject matter experts used technical, budget, and schedule objectives to analyze a number of potential launch systems, with a focus on human rating for exploration missions. The results showed that a variant of the Space Shuttle, utilizing the reusable Solid Rocket Booster as the first stage, along with a new upper stage that uses a derivative of the RS-25 Space Shuttle Main Engine to deliver 25 metric tons to low-Earth orbit, was the best choice to reduce the risks associated with fielding a new system in a timely manner. The CLV Project, managed by the Exploration Launch Office located at NASA's Marshall Space Flight Center, is leading the design, development, testing, and operation of this new human-rated system. The CLV Project works closely with the Space Shuttle Program to transition hardware, infrastructure, and workforce assets to the new launch system . leveraging a wealth of lessons learned from Shuttle operations. The CL V is being designed to reduce costs through a number of methods, ranging from validating requirements to conducting trades studies against the concept design. Innovations such as automated processing will build on lessons learned from the Shuttle, other launch systems, Department of Defense operations experience, and subscale flight tests such as the Delta Clipper-Experimental Advanced (DCXA) vehicle operations that utilized minimal touch labor, automated cryogen ic propellant loading , and an 8-hour turnaround for a cryogenic propulsion system. For the CLV, the results of hazard analyses are contributing to an integrated vehicle health monitoring system that will troubleshoot anomalies and determine which ones can be solved without human intervention. Such advances will help streamline the mission operations process for pilots and ground controllers alike. In fiscal year 2005, NASA invested approximately $4.5 billion of its $16 bill ion budget on the Space Shuttle. The ultimate goal of the CLV Project is to deliver a safe, reliable system designed to minimize lifecycle costs so that NASA's budget can be invested in missions of scientific discovery. Lessons learned from developing the CLV will be applied to the growth path for future systems, including a heavy lift launch vehicle.

Dumbacher, Daniel L.↗
NASA NTRS2006

Towards Robust Designs Via Multiple-Objective Optimization Methods

Fabricating and operating complex systems involves dealing with uncertainty in the relevant variables. In the case of aircraft, flow conditions are subject to change during operation. Efficiency and engine noise may be different from the expected values because of manufacturing tolerances and normal wear and tear. Engine components may have a shorter life than expected because of manufacturing tolerances. In spite of the important effect of operating- and manufacturing-uncertainty on the performance and expected life of the component or system, traditional aerodynamic shape optimization has focused on obtaining the best design given a set of deterministic flow conditions. Clearly it is important to both maintain near-optimal performance levels at off-design operating conditions, and, ensure that performance does not degrade appreciably when the component shape differs from the optimal shape due to manufacturing tolerances and normal wear and tear. These requirements naturally lead to the idea of robust optimal design wherein the concept of robustness to various perturbations is built into the design optimization procedure. The basic ideas involved in robust optimal design will be included in this lecture. The imposition of the additional requirement of robustness results in a multiple-objective optimization problem requiring appropriate solution procedures. Typically the costs associated with multiple-objective optimization are substantial. Therefore efficient multiple-objective optimization procedures are crucial to the rapid deployment of the principles of robust design in industry. Hence the companion set of lecture notes (Single- and Multiple-Objective Optimization with Differential Evolution and Neural Networks ) deals with methodology for solving multiple-objective Optimization problems efficiently, reliably and with little user intervention. Applications of the methodologies presented in the companion lecture to robust design will be included here. The evolutionary method (DE) is first used to solve a relatively difficult problem in extended surface heat transfer wherein optimal fin geometries are obtained for different safe operating base temperatures. The objective of maximizing the safe operating base temperature range is in direct conflict with the objective of maximizing fin heat transfer. This problem is a good example of achieving robustness in the context of changing operating conditions. The evolutionary method is then used to design a turbine airfoil; the two objectives being reduced sensitivity of the pressure distribution to small changes in the airfoil shape and the maximization of the trailing edge wedge angle with the consequent increase in airfoil thickness and strength. This is a relevant example of achieving robustness to manufacturing tolerances and wear and tear in the presence of other objectives.

Man Mohan, Rai↗
DOE OSTI2021

Vehicle-Cycle Inventory for Medium- and Heavy-Duty Vehicles

The United States has witnessed multiple attempts to improve fuel economy and reduce pollutant emissions in the transportation sector, guided chiefly via technological interventions by original equipment manufacturers (OEMs) and by specific policies of the U.S. Federal Government, like Corporate Average Fuel Economy (CAFE) norms (Burnham et al., 2006; U.S. DoT, 2013). These efforts have resulted in the growing adoption of alternatives to conventional materials, fuels, and vehicle propulsion technologies across various transportation modes, while also helping to lower global pollution (greenhouse gas, or GHG, emissions). Yet, a holistic evaluation of the ecofriendliness of these alternatives, particularly their energy use and emissions, merits detailed focus on their entire life-cycle, and thereby, on the life-cycle of associated transport modes. This is vital since alternative fuels and materials can differ vastly in energy sources and production methods employed for their processing vis-à-vis their existing counterparts — and this difference causes significant variation in their respective upstream emissions.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2023

Long-run Marginal Emission Rates for Electricity - Workbooks for 2022 Cambium Data

These workbooks contain modeled estimates of long-run marginal emission rates (LRMER) for the contiguous United States. A LRMER is an estimate of the rate of emissions that would be either induced or avoided by a change in electric demand, taking into account how the change could influence both the operation as well as the structure of the grid (i.e., the building and retiring of capital assets, such as generators and transmission lines). It is therefore distinct from the more-commonly-known short-run marginal, which treat grid assets as fixed. Long-run marginal emissions rates are generally appropriate to use when trying to comprehensively estimate the impact of a long-lived (i.e., more than several years) intervention. There are two workbooks that supply the data at two different geographic resolutions: states and GEA regions (20 regions that are similar to, but not exactly the same as, the US EPA's eGRID regions). For more data underlying these emissions factors, see the Cambium 2022 project at https://scenarioviewer.nrel.gov/. For more details on input assumptions and methodology see the associated report (Cambium 2022 Scenario Descriptions and Documentation, https://www.nrel.gov/docs/fy23osti/84916.pdf). This data is planned to be updated annually. Information on the latest versions can be found at https://www.nrel.gov/analysis/cambium.html.

01 COAL, LIGNITE, AND PEAT↗
NASA NTRS2007

Automated Target Planning for FUSE Using the SOVA Algorithm

The SOVA algorithm was originally developed under the Resilient Systems and Operations Project of the Engineering for Complex Systems Program from NASA s Aerospace Technology Enterprise as a conceptual framework to support real-time autonomous system mission and contingency management. The algorithm and its software implementation were formulated for generic application to autonomous flight vehicle systems, and its efficacy was demonstrated by simulation within the problem domain of Unmanned Aerial Vehicle autonomous flight management. The approach itself is based upon the precept that autonomous decision making for a very complex system can be made tractable by distillation of the system state to a manageable set of strategic objectives (e.g. maintain power margin, maintain mission timeline, and et cetera), which if attended to, will result in a favorable outcome. From any given starting point, the attainability of the end-states resulting from a set of candidate decisions is assessed by propagating a system model forward in time while qualitatively mapping simulated states into margins on strategic objectives using fuzzy inference systems. The expected return value of each candidate decision is evaluated as the product of the assigned value of the end-state with the assessed attainability of the end-state. The candidate decision yielding the highest expected return value is selected for implementation; thus, the approach provides a software framework for intelligent autonomous risk management. The name adopted for the technique incorporates its essential elements: Strategic Objective Valuation and Attainability (SOVA). Maximum value of the approach is realized for systems where human intervention is unavailable in the timeframe within which critical control decisions must be made. The Far Ultraviolet Spectroscopic Explorer (FUSE) satellite, launched in 1999, has been collecting science data for eight years.[1] At its beginning of life, FUSE had six gyros in two IRUs and four reaction wheels. Over time through various failures, the satellite has been left with one reaction wheel on the vehicle skew axis and two gyros. To remain operational, a control scheme has been implemented using the magnetic torque rods and the remaining momentum wheel.[2] As a consequence, there are attitude regions where there is insufficient torque authority to overcome environmental disturbances (e.g. gravity gradient torques). The situation is further complicated by the fact that these attitude regions shift inertially with time as the spacecraft moves through earth s magnetic field during the course of its orbit. Under these conditions, the burden of planning targets and target-to-target slew maneuvers has increased significantly since the beginning of the mission.[3] Individual targets must be selected so that the magnetic field remains roughly aligned with the skew wheel axis to provide enough control authority to the other two orthogonal axes. If the field moves too far away from the skew axis, the lack of control authority allows environmental torques to pull the satellite away from the target and can potentially cause it to tumble. Slew maneuver planning must factor the stability of targets at the beginning and end, and the torque authority at all points along the slew. Due to the time varying magnetic field geometry relative to any two inertial targets, small modifications in slew maneuver timing can make large differences in the achievability of a maneuver.

Heatwole, Scott↗
DOE OSTI2024

Learning model combining convolutional deep neural network with a self-attention mechanism for AC optimal power flow

Alternating current optimal power flow (OPF) analysis is critical for efficient and reliable operation of power systems. For large systems or repetitive computations, the traditional methods such as the direct and gradient methods, or non-traditional methods, such as the genetic algorithm and simulating annealing, are time-consuming and unsuitable for real-time computing. The work in this paper proposes a novel framework to obtain the optimal solution of power flow in real-time using a combination of convolutional neural networks and a self-attention mechanism. All parameters of the power networks are rearranged in an image-like shape of a multi-channel image where each channel is a two-dimensional matrix. The proposed approach is adaptive with every input size of power systems as well as frequent variations of network topologies without intervention to the framework core. The encompassment of all power system contexts in which all parameters of internal elements, generation costs, and topology information are included, contributes to the higher accuracy of inference compared to other current machine-learning-based OPF-solving methods. Besides, the proposed framework established on ubiquitous platforms is effortlessly integrated into current infrastructures of power systems, and the great efficiency along with the computation speed may serve as a critical point for practical implications, such as enabling faster decision-making during real-time operations, predicting system contingencies, and remedial actions based on an offline pre-trained model. Furthermore, this supervised learning process is applied to the dataset of four case studies of meshed power systems: the IEEE 5-bus system (IEEE-5), the IEEE 30-bus system (IEEE-30), the IEEE 39-bus system (IEEE-39), and the IEEE 57-bus system (IEEE-57) to prove the efficacy of the proposed method.

42 ENGINEERING↗
DOE OSTI2024

Toward Smart, Automated Junctional Tourniquets—AI Models to Interpret Vessel Occlusion at Physiological Pressure Points

Hemorrhage is the leading cause of preventable death in both civilian and military medicine. Junctional hemorrhages are especially difficult to manage since traditional tourniquet placement is often not possible. Ultrasound can be used to visualize and guide the caretaker to apply pressure at physiological pressure points to stop hemorrhage. However, this process is technically challenging, requiring the vessel to be properly positioned over rigid boney surfaces and applying sufficient pressure to maintain proper occlusion. As a first step toward automating this life-saving intervention, we demonstrate an artificial intelligence algorithm that classifies a vessel as patent or occluded, which can guide a user to apply the appropriate pressure required to stop flow. Neural network models were trained using images captured from a custom tissue-mimicking phantom and an ex vivo swine model of the inguinal region, as pressure was applied using an ultrasound probe with and without color Doppler overlays. Using these images, we developed an image classification algorithm suitable for the determination of patency or occlusion in an ultrasound image containing color Doppler overlay. Separate AI models for both test platforms were able to accurately detect occlusion status in test-image sets to more than 93% accuracy. In conclusion, this methodology can be utilized for guiding and monitoring proper vessel occlusion, which, when combined with automated actuation and other AI models, can allow for automated junctional tourniquet application.

60 APPLIED LIFE SCIENCES↗