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DOE OSTI2023

Development of a wind turbine model and simulation platform using an acausal approach: Multiphysics modeling, validation, and control

This article presents the development of the Control-oriented, Reconfigurable, and Acausal Floating Turbine Simulator (CRAFTS). CRAFTS has a modular, hierarchical model architecture that enables rapid and accurate simulation of wind turbines. The architecture facilitates the incorporation of model variants, and its system reconfiguration features help simulate multiple design variants. CRAFTS also supports the integration of models developed on a causality-free platform (e.g., Modelica®) with existing causal models. This article focuses on the validation of a land-based wind turbine models against OpenFAST, an industry-standard platform, for several test cases. Closed-loop scenarios are also tested using the standard ROSCO controller and compared against OpenFAST. In addition, a nonlinear controller developed in our prior work is also evaluated. The test cases demonstrate the user-friendly and computationally efficient capabilities of CRAFTS to facilitate control co-design, assist in incorporating multiphysics models, be adaptable to design variants, and allow for rapid simulations to validate models and evaluate controllers.

17 WIND ENERGY↗

DOE OSTI2025

Per-Phase Control for CHB Converters with Negative-Sequence Current and DC Voltage Balancing Control

This paper presents a per-phase controller for a grid-connected Cascaded H-Bridge (CHB) converter featuring negative sequence current regulation and DC bus voltage balancing capabilities. Unlike conventional three-phase controllers, each phase of the CHB can be separately and controlled to regulate the DC voltage and reactive power flow. per-phase negative sequence current control strategy is incorporated into the proposed controller to ensure compliance with IEEE Standard 2800-2022, which requires the absorption of negative-sequence reactive current during grid voltage disturbances. Furthermore, a feed-forward control-based DC bus voltage balancing method is employed, which eliminates the need for the integrator commonly used in traditional approaches. The performance of the proposed controller is validated under various unbalanced grid scenarios and DC bus voltage imbalances through electromagnetic transient (EMT) simulation using a three-phase, three-level grid-connected CHB–Dual Active Bridge (DAB) converter testbed developed on MATLAB/Simulink. Additionally, the performance of the negative-sequence current regulation is investigated through simulation under different unbalanced grid voltage scenarios.

negative sequence current↗

DOE OSTI2020

Acceptance Calculation and Study of Fault Scenarios in the PIP-II Linac

The Proton Improvement Plan (PIP)-II is a proposed high intensity proton facility being developed at the Fermilab. The PIP-II is primarily based on construction of a new superconducting radio frequency (SRF) linear accelerator (linac) that would deliver an average beam current of 2mA with output energy up to 800 MeV. The acceptance of an accelerator outlines its sensitivity against deviations from its nominal design parameters. Consequently, a higher acceptance minimizes possibility of the beam loss. This paper presents longitudinal and transverse acceptance of the PIP-II SRF linac. Furthermore, paper also discusses implications of fault scenarios, such as the cavity failure, on the beam optics and acceptances.

43 PARTICLE ACCELERATORS↗

DOE OSTI2020

Generation and representation of synthetic smart meter data

Advanced energy algorithms running at big-data scale will be necessary to identify, realize, and verify energy savings to meet government and utility goals of building energy efficiency. Any algorithm must be well characterized and validated before it is trusted to run at these scales. Smart meter data from real buildings will ultimately be required for the development, testing, and validation of these energy algorithms and processes. However, for initial development and testing, smart meter data are difficult to work with due to privacy restrictions, noise from unknown sources, data accessibility, and other concerns which can complicate algorithm development and validation. This paper describes a new methodology to generate synthetic smart meter data of electricity use in buildings using detailed building energy modeling, which aims to capture the variability and stochastics of real energy use in buildings. The methodology can create datasets tailored to represent specific scenarios with known truth and controllable amounts of synthetic noise. Knowledge of ground truth also allows the development and validation of enhanced processes which leverage building metadata, such as building type or size (floor area), in addition to smart meter data. The methodology described in this paper includes the key influencing factors of real-world building energy use including weather data, occupant-driven loads, building operation and maintenance practices, and special events. Data formats to support workflows leveraging both synthetic meter data and associated metadata are proposed and discussed. Finally, example use cases of the synthetic meter data are described to illustrate potential applications.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2020

Enhancement of risk informed validation framework for external hazard scenario

In recent years, the U.S. Nuclear Regulatory Commission (USNRC) and the International Atomic Energy Agency (IAEA) have developed methodologies to assess the vulnerabilities of nuclear plants against site specific extreme hazards. In many cases, advanced simulation tools are being considered to simulate multi-physics, multi-scale phenomena and to evaluate vulnerability of nuclear facilities. The credibility of advanced simulation tools is assessed based on a formal verification, validation, and uncertainty quantification procedure. One of the key limitations in validation is the lack of relevant experimental data at system-level. This limitation leads to a decrease in the confidence of system-level risk predictions. Therefore, a robust validation framework is needed to formalize the confidence in predictive capability of advanced simulation results. Additionally, this study enhances the existing risk informed validation methodology, originally proposed by Kwag et al. [1] and Bodda et al. [2], by developing additional attributes and a new set of validation indicies for a complete and wider applicability of the framework. In this manuscript, the methodology to identify the critical path that leads to the system-level failure is illustrated. The overall validation is checked for completeness and consistency by comparing the critical path for both the system-level simulation and experimental models. The applicability of the code for an intended application is represented in terms of various maturity levels and helps in the process of decision making.

42 ENGINEERING↗

DOE OSTI2024

DECOVALEX-2023: Task F2 Salt Final Report

The subject of Task F of DECOVALEX-2023 concerns performance assessment modelling of radioactive waste disposal in deep mined repositories. The primary objectives of Task F are to build confidence in the models, methods, and software used for performance assessment (PA) of deep geologic nuclear waste repositories, and/or to bring to the fore additional research and development needed to improve PA methodologies. In Task F2- (salt), these objectives have been accomplished through staged development and comparison of the models and methods used by participating teams in their PA frameworks. Coupled-process submodels and deterministic simulations of the entire PA model for a reference scenario for waste disposal in domal salt have been conducted. The task specification has been updated continuously since the initiation of the project to reflect the staged development of the conceptual repository model and performance metrics. Thermal, hydrological, mechanical, and chemical properties of individual components of the engineered and natural system were chosen for relevance by participating teams. The salt reference case system was characterized using data and measurements collected at relevant underground research laboratories (URLs), field sites, and simulation results from teams with specialized modelling capability. Participating teams made a wide range of model assumptions from compartmentalized networks to full 3D models of the salt formation. No single contributed model includes full-fidelity representation of all the features, events, and processes (FEPs) detailed in the task specification, but almost all features and processes are represented in at least one model. Despite differences in the modelling strategies developed by participating teams, all models indicate that salt compaction and radionuclide diffusion are key processes in the repository, and for the FEPs and model scenario considered, little of the disposed radionuclides will migrate beyond the repository seal over the 100,000 year simulations. In general, the model output quantities have the largest differences over the short term and near the waste. The models tend to be more similar further from waste and at later time. Disparities between the models are believed to be due to differing simplifications from the task specification, some of which are chosen simplifications to reduce complexity, and some are restrictions imposed by the modelling tools. A second round of this task has been accepted for DECOVALEX-2027 in conjunction with Task F1 on crystalline PA modelling. The future round includes waste package heating, improved modelling of salt creep closure, additional comparisons of coupled-process sub-models, and the impact of repository engineering design on radionuclide migration in the repository. Participants will also propose and finalize a set of uncertain inputs for the reference case simulations, propagate these uncertainties in a set of realizations, and conduct sensitivity analyses on the simulation results.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2020

Explainable Artificial Intelligence Recommendation System by Leveraging the Semantics of Adverse Childhood Experiences: Proof-of-Concept Prototype Development

The study of adverse childhood experiences and their consequences has emerged over the past 20 years. Although the conclusions from these studies are available, the same is not true of the data. Accordingly, it is a complex problem to build a training set and develop machine-learning models from these studies. Classic machine learning and artificial intelligence techniques cannot provide a full scientific understanding of the inner workings of the underlying models. This raises credibility issues due to the lack of transparency and generalizability. Explainable artificial intelligence is an emerging approach for promoting credibility, accountability, and trust in mission-critical areas such as medicine by combining machine-learning approaches with explanatory techniques that explicitly show what the decision criteria are and why (or how) they have been established. Hence, thinking about how machine learning could benefit from knowledge graphs that combine “common sense” knowledge as well as semantic reasoning and causality models is a potential solution to this problem. In this study, we aimed to leverage explainable artificial intelligence, and propose a proof-of-concept prototype for a knowledge-driven evidence-based recommendation system to improve mental health surveillance. We used concepts from an ontology that we have developed to build and train a question-answering agent using the Google DialogFlow engine. In addition to the question-answering agent, the initial prototype includes knowledge graph generation and recommendation components that leverage third-party graph technology. To showcase the framework functionalities, we here present a prototype design and demonstrate the main features through four use case scenarios motivated by an initiative currently implemented at a children’s hospital in Memphis, Tennessee. Ongoing development of the prototype requires implementing an optimization algorithm of the recommendations, incorporating a privacy layer through a personal health library, and conducting a clinical trial to assess both usability and usefulness of the implementation. This semantic-driven explainable artificial intelligence prototype can enhance health care practitioners’ ability to provide explanations for the decisions they make.

adverse childhood experiences↗

NASA NTRS1991

Intelligent Robotic Systems Study (IRSS), phase 3

This phase of the Intelligent Robotic Systems Study (IRSS) examines some basic dynamics and control issues for a space manipulator attached to its worksite through a compliant base. One example of this scenario is depicted, which is a simplified, planar representation of the Flight Telerobotic Servicer (FTS) Development Test Flight 2 (DTF-2) experiment. The system consists of 4 major components: (1) dual FTS arms to perform dextrous tasks; (2) the main body to house power and electronics; (3) an Attachment Stabilization and Positioning Subsystem (ASPS) to provide coarse positioning and stabilization of the arms, and (4) the Worksite Attachment Mechanism (WAM) which anchors the system to its worksite, such as a Space Station truss node or Shuttle bay platform. The analysis is limited to the DTF-2 scenario. The goal is to understand the basic interaction dynamics between the arm, the positioner and/or stabilizer, and the worksite. The dynamics and controls simulation model are described. Analysis and simulation results are presented.

Source record↗

NASA NTRS2014

Towards Co-evolution of Membranes and Metabolism

Conceptually, the most robust way to explain how primitive cell-like structures acquired and increased their capabilities is on the basis of Darwinian evolution. A population of protocells containing material that produced more environmentally fit progeny would increase in time at the expense of other protocells. In this scenario, protocellular boundaries were inextricably connected to the metabolism they encapsulated: to be inheritable, early metabolism must have led to an increased rate of growth and division of vesicles and, similarly, transport through vesicle boundaries must have supported the evolution of metabolism. Everything that could not be delivered from the environment had to be produced and retained inside protocells. Despite their importance to the understanding of the origin of life, only a few cases of coupling between metabolism and membrane-related processes have been identified so far. For example, reactions inside fatty-acid vesicles have been linked to their competitive growth and division, and mechanisms by which membrane permeability might have coupled to information polymers have been proposed and explained. Most recently, it has been shown that a dipeptide inside fatty-acid vesicles catalyzes the formation of another dipeptide that binds to vesicle walls and, by doing so, promotes their growth at the expense of other vesicles, thus demonstrating evolutionary advantage of small, membrane-bound peptides. It has been shown that the appearance of phospholipids imparted selective advantage to protocells bound by phospholipid-containing membranes, eventually driving fatty-acid vesicles to extinction. Phospholipid membranes, however, are nearly impermeable to charged species. Yet, the ability to transport ions across membranes was vital for regulating cellular volume, pH homeostasis, generating energy and sensing the environment. To account for this, evolutionary scenarios for the emergence of simple ion channels, protein structures surrounding water-filled pores in the membrane that facilitate ion transport, have been developed. We will review recent progress in experimental and theoretical studies on coupling properties of membranes to metabolism, with the focus on how they impose constraints on scenarios for the origin of life, and discuss how these studies form the basis for future work on this topic.

metabolism↗

NASA NTRS2013

State Machine Modeling of the Space Launch System Solid Rocket Boosters

The Space Launch System is a Shuttle-derived heavy-lift vehicle currently in development to serve as NASA's premiere launch vehicle for space exploration. The Space Launch System is a multistage rocket with two Solid Rocket Boosters and multiple payloads, including the Multi-Purpose Crew Vehicle. Planned Space Launch System destinations include near-Earth asteroids, the Moon, Mars, and Lagrange points. The Space Launch System is a complex system with many subsystems, requiring considerable systems engineering and integration. To this end, state machine analysis offers a method to support engineering and operational e orts, identify and avert undesirable or potentially hazardous system states, and evaluate system requirements. Finite State Machines model a system as a finite number of states, with transitions between states controlled by state-based and event-based logic. State machines are a useful tool for understanding complex system behaviors and evaluating "what-if" scenarios. This work contributes to a state machine model of the Space Launch System developed at NASA Ames Research Center. The Space Launch System Solid Rocket Booster avionics and ignition subsystems are modeled using MATLAB/Stateflow software. This model is integrated into a larger model of Space Launch System avionics used for verification and validation of Space Launch System operating procedures and design requirements. This includes testing both nominal and o -nominal system states and command sequences.

model-based systems engineering↗

NASA NTRS2005

Real-Time Analysis of Electrocardiographic Data for Heart Rate Turbulence

Episodes of ventricular ectopy (premature ventricular contractions, PVCs) have been reported in several astronauts and cosmonauts during space flight. Indeed, the "Occurrence of Serious Cardiac Dysrhythmias" is now NASA's #1 priority critical path risk factor in the cardiovascular area that could jeopardize a mission as well as the health and welfare of the astronaut. Epidemiological, experimental and clinical observations suggest that severe autonomic dysfunction and/or transient cardiac ischemia can initiate potentially lethal ventricular arrhythmias. On earth, Heart Rate Turbulence (HRT) in response to PVCs has been shown to provide not only an index of baroreflex sensitivity (BRS), but also more importantly, an index of the propensity for lethal ventricular arrhythmia. An HRT procedure integrated into the existing advanced electrocardiographic system under development in JSC's Human Adaptation and Countermeasures Office was developed to provide a system for assessment of PVCs in a real-time monitoring or offline (play-back) scenario. The offline heart rate turbulence software program that was designed in the summer of 2003 was refined and modified for "close to" real-time results. In addition, assistance was provided with the continued development of the real-time heart rate variability software program. These programs should prove useful in evaluating the risk for arrhythmias in astronauts who do and who do not have premature ventricular contractions, respectively. The software developed for these projects has not been included in this report. Please contact Dr. Todd Schlegel for information on acquiring a specific program.

Greco, E. Carl, Jr.↗

DOE OSTI2026

Structure-Aware Unsupervised, Transformational Machine Learning for Drug Discovery (DTRA Basic Research Final Report)

The major goal of this project is to develop machine learning (ML) methods to enable improved predictive power on real drug discovery for novel targets. More specifically, we planned to demonstrate the capability and effectiveness of ML tools utilizing unlabeled large-volume protein-ligand datasets. We investigated multiple pre-training approaches for 3D protein-ligand structure-based foundation models, without relying on experimental binding data. We also addressed scenarios in which crystal structures are unavailable or binding data are limited. We also planned to develop a complete pipeline to screen novel compounds as well as to demonstrate the capability and effectiveness of the developed methods by testing on a realistic drug discovery task such as SARS-CoV-2. While the major goals and milestones remain consistent with the original proposal, certain technical details have been adjusted, based on the experimental results and related outcomes.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS2007

Not So Rare Earth? New Developments in Understanding the Origin of the Earth and Moon

A widely accepted model for the origin of the Earth and Moon has been a somewhat specific giant impact scenario involving an impactor to proto-Earth mass ratio of 3:7, occurring 50-60 Ma after T(sub 0), when the Earth was only half accreted, with the majority of Earth's water then accreted after the main stage of growth, perhaps from comets. There have been many changes to this specific scenario, due to advances in isotopic and trace element geochemistry, more detailed, improved, and realistic giant impact and terrestrial planet accretion modeling, and consideration of terrestrial water sources other than high D/H comets. The current scenario is that the Earth accreted faster and differentiated quickly, the Moon-forming impact could have been mid to late in the accretion process, and water may have been present during accretion. These new developments have broadened the range of conditions required to make an Earth-Moon system, and suggests there may be many new fruitful avenues of research. There are also some classic and unresolved problems such as the significance of the identical O isotopic composition of the Earth and Moon, the depletion of volatiles on the lunar mantle relative to Earth's, the relative contribution of the impactor and proto-Earth to the Moon's mass, and the timing of Earth's possible atmospheric loss relative to the giant impact.

Righter, Kevin↗

NASA NTRSDate not supplied

From BERTopic to SysML: Informing Model-Based Failure Analysis With Natural Language Processing for Complex Aerospace Systems

The development of emerging complex aerospace systems will require new approaches for capturing safety incident scenarios as early as possible in the design phase. However, for novel systems, relevant data available is limited. In this work, we propose a framework informing model-based mission assurance activities with historical incident reports, lessons learned, or other relevant engineering documents using natural language processing. In doing so, we investigate whether there is useful information in data sets that are relevant, if not identical, to the system under design and whether, through rigorous systems engineering practice, this information can be effectively leveraged through model-based failure analysis. In a worked case study, we apply state-of-the-art topic modeling techniques to two data sets, a mission relevant data set and a system relevant data set. The sets of topics are merged and interpreted to form a preliminary list of failure topics that can be used to inform the identification of off-nominal modes in the model-based failure modes and effects analysis development. Once data from the system in operation is available, it can be used to update the topics identified. By extracting information about likely failures from relevant historical data sets and utilizing model-based mission assurance to ensure relevance and rigor, unanticipated failures can be reduced, and projects can more effectively learn from past missions.

Failure Analysis↗

NASA NTRSDate not supplied

From BERTopic to SysML: Informing Model-Based Failure Analysis With Natural Language Processing for Complex Aerospace Systems

Failure Analysis↗

NASA NTRS2012

Benchmarking Evaluation Results for Prototype Extravehicular Activity Gloves

The Space Suit Assembly (SSA) Development Team at NASA Johnson Space Center has invested heavily in the advancement of rear-entry planetary exploration suit design but largely deferred development of extravehicular activity (EVA) glove designs, and accepted the risk of using the current flight gloves, Phase VI, for unique mission scenarios outside the Space Shuttle and International Space Station (ISS) Program realm of experience. However, as design reference missions mature, the risks of using heritage hardware have highlighted the need for developing robust new glove technologies. To address the technology gap, the NASA Game-Changing Technology group provided start-up funding for the High Performance EVA Glove (HPEG) Project in the spring of 2012. The overarching goal of the HPEG Project is to develop a robust glove design that increases human performance during EVA and creates pathway for future implementation of emergent technologies, with specific aims of increasing pressurized mobility to 60% of barehanded capability, increasing the durability by 100%, and decreasing the potential of gloves to cause injury during use. The HPEG Project focused initial efforts on identifying potential new technologies and benchmarking the performance of current state of the art gloves to identify trends in design and fit leading to establish standards and metrics against which emerging technologies can be assessed at both the component and assembly levels. The first of the benchmarking tests evaluated the quantitative mobility performance and subjective fit of four prototype gloves developed by Flagsuit LLC, Final Frontier Designs, LLC Dover, and David Clark Company as compared to the Phase VI. All of the companies were asked to design and fabricate gloves to the same set of NASA provided hand measurements (which corresponded to a single size of Phase Vi glove) and focus their efforts on improving mobility in the metacarpal phalangeal and carpometacarpal joints. Four test subjects representing the design ]to hand anthropometry completed range of motion, grip/pinch strength, dexterity, and fit evaluations for each glove design in both the unpressurized and pressurized conditions. This paper provides a comparison of the test results along with a detailed description of hardware and test methodologies used.

Aitchison, Lindsay↗

NASA NTRS2014

An Approach for Performance Assessments of Extravehicular Activity Gloves

The Space Suit Assembly (SSA) Development Team at NASA Johnson Space Center has invested heavily in the advancement of rear‐entry planetary exploration suit design but largely deferred development of extravehicular activity (EVA) glove designs, and accepted the risk of using the current flight gloves, Phase VI, for unique mission scenarios outside the Space Shuttle and International Space Station (ISS) Program realm of experience. However, as design reference missions mature, the risks of using heritage hardware have highlighted the need for developing robust new glove technologies. To address the technology gap, the NASA Game‐Changing Technology group provided start‐up funding for the High Performance EVA Glove (HPEG) Project in the spring of 2012. The overarching goal of the HPEG Project is to develop a robust glove design that increases human performance during EVA and creates pathway for future implementation of emergent technologies, with specific aims of increasing pressurized mobility to 60% of barehanded capability, increasing the durability by 100%, and decreasing the potential of gloves to cause injury during use. The HPEG Project focused initial efforts on identifying potential new technologies and benchmarking the performance of current state of the art gloves to identify trends in design and fit leading to establish standards and metrics against which emerging technologies can be assessed at both the component and assembly levels. The first of the benchmarking tests evaluated the quantitative mobility performance and subjective fit of two sets of prototype EVA gloves developed ILC Dover and David Clark Company as compared to the Phase VI. Both companies were asked to design and fabricate gloves to the same set of NASA provided hand measurements (which corresponded to a single size of Phase Vi glove) and focus their efforts on improving mobility in the metacarpal phalangeal and carpometacarpal joints. Four test subjects representing the design‐to hand anthropometry completed range of motion, grip/pinch strength, dexterity, and fit evaluations for each glove design in pressurized conditions, with and without thermal micrometeoroid garments (TMG) installed. This paper provides a detailed description of hardware and test methodologies used and lessons learned.

Aitchison, Lindsay↗

NASA NTRS2017

Hybrid Guidance Control for a Hypervelocity Small Size Asteroid Interceptor Vehicle

Near-Earth Objects (NEOs) are comets and/or asteroids that have orbits in proximity with Earth's own orbit. NEOs have collided with the Earth in the past, which can be seen at such places as Chicxulub crater, Barringer crater, and Manson crater, and will continue in the future with potentially significant and devastating results. Fortunately such NEO collisions with Earth are infrequent, but can happen at any time. Therefore it is necessary to develop and validate techniques as well as technologies necessary to prevent them. One approach to mitigate future NEO impacts is the concept of high-speed interceptor. This concept is to alter the NEO's trajectory via momentum exchange by using kinetic impactors as well as nuclear penetration devices. The interceptor has to hit a target NEO at relative velocity which imparts a sufficient change in NEO velocity. NASA's Deep Impact mission has demonstrated this scenario by intercepting Comet Temple 1, 5 km in diameter, with an impact relative speed of approximately 10 km/s. This paper focuses on the development of hybrid guidance navigation and control (GNC) algorithms for precision hypervelocity intercept of small sized NEOs. The spacecraft's hypervelocity and the NEO's small size are critical challenges for a successful mission as the NEO will not fill the field of view until a few seconds before intercept. The investigation needs to consider the error sources modeled in the navigation simulation such as spacecraft initial state uncertainties in position and velocity. Furthermore, the paper presents three selected spacecraft guidance algorithms for asteroid intercept and rendezvous missions. The selected algorithms are classical Proportional Navigation (PN) based guidance that use a first order difference to compute the derivatives, Three Plane Proportional Navigation (TPPN), and the Kinematic Impulse (KI). A manipulated Bennu orbit that has been changed to impact Earth will be used as a demonstrative example to compare the three methods. In addition, a hybrid approach that is a combination between proportional navigation and kinematic impulse will be investigated to find an effective, error tolerant, and power saving approach. A 3-dimension mission scenario for both the asteroid and the interceptor spacecraft software simulator is developed for testing of the controllers. The current result demonstrates that a miss distance magnitude of less than 10m is found using the PN and TPPN guidance laws for small asteroid in the presence of error in the spacecraft states. Moreover, the paper presents these results and also the hybrid control approach simulation results.

asteroid↗