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At least 1,783 records · Page 99

Single-atom implanted two-dimensional MOFs as efficient electrocatalysts for the oxygen evolution reaction

The exploration of novel electrochemical energy conversion and storage devices has been extensively studied in recent decades for their specific advantages. Therefore, the design of highly efficient, stable, and noble-metal-free electrocatalysts for oxygen-related reactions (OER) is critical but challenging and is still worth improving. Herein, a facile and controllable synthesis strategy for bimetallic electrocatalysts for the OER from a two-dimensional iron-based metal–organic framework (HUST-8, HUST = Huazhong University of Science and Technology) precursor has been reported. The unoccupied porphyrin center has been disposed into the layer structure of HUST-8, which is very facile for the introduction of a second type of metal center via post-modification treatment. Guided by the synthesis strategy, Fe/Ni, Fe/Co, Fe/Zn, Fe/Mn and Fe/Fe species have been fabricated, and their electrocatalytic performance for the OER has been further characterized, among which the Fe/Ni type exhibits the best efficiency and conversion. For Fe/Ni species of HUST-8 (labeled as Ni@HUST-8), in 1 M KOH, the initial potential for OER activity performance is 170 mV (vs. RHE). At 10 mA cm -2 , the corresponding overpotential is 240 mV and the Tafel slope is simulated as 60.8 mV dec -1 . All of these experimental results of Ni@HUST-8 illustrate its better performance than commercial IrO 2 . Compared to the MOF parent and other bimetallic species, the higher electrocatalytic performance of Ni@HUST-8 should be ascribed to the special synergistic effect of Fe and Ni centers, which tends to greatly improve the reaction kinetics and charge transfer efficiency, while increasing the activity of the OER and achieving the best catalytic performances. The systematic investigation clearly manifests the important role of the synergistic effect of bimetallic centers in the OER and provides other insight into fabricating tailored electrocatalysts derived from MOF-based templates.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

The role of thermal conduction on the size scaling of laser direct-drive implosions

Ablation pressure is a key parameter controlling laser drive performance in direct-drive inertial confinement fusion implosions. In this work, we develop a theoretical framework to clarify the role of thermal conduction in determining how ablation pressure scales with laser intensity, wavelength, and target size. We focus on a steady-state, spherically expanding plasma produced when an over-dense pellet is irradiated by a high-intensity laser. Scaling laws for ablation pressure and the mass ablation rate are derived with respect to laser intensity, wavelength, and target size. As a result, the theoretical predictions are found to be in good agreement with one-dimensional hydrodynamics simulations in spherical geometry.

Ablation↗

Machine learning method for enforcing variable independence in background estimation with LHC data: ABCDisCoTEC

A novel solution is presented for the problem of estimating the backgrounds of a signal search using observed data while simultaneously maximizing the sensitivity of the search to the signal. The 'ABCD method' provides a reliable framework for background estimation by partitioning events into one signal-enhanced region (A) and three background-enhanced control regions (B, C, and D) via two smoothly varying, statistically independent variables. In practice, even slight correlations between the two variables can significantly undermine the method's performance. Thus, choosing appropriate variables by hand can present a formidable challenge, especially when background and signal differ only subtly. To address this issue, the ABCD with distance correlation (ABCDisCo) method was developed to construct two learned variables via a neural network trained to provide strong signal-background discrimination with small values of the distance correlation (DisCo) measure between the two learned variables. However, relying solely on minimizing the DisCo can result in learned variables that may not have distributions of background events that are smoothly varying and localized at extreme values, as necessary for the validity of the background estimation. The ABCDisCo training enhanced with closure (ABCDisCoTEC) method is introduced to solve this issue by directly minimizing the nonclosure, expressed as a dedicated differentiable loss term. This extended method is applied to a data set of proton-proton collisions at a center-of-mass energy of 13 TeV recorded by the CMS detector at the CERN Large Hadron Collider. Additionally, given the complexity of the minimization problem with constraints on multiple loss terms, the modified differential method of multipliers is applied and shown to greatly improve the stability and robustness of the ABCDisCoTEC method, compared to grid search hyperparameter optimization procedures.

Hayrapetyan, Aram [Yerevan Phys. Inst.]↗

Elastic Bayesian Model Calibration

Functional data are ubiquitous in scientific modeling. For instance, quantities of interest are modeled as functions of time, space, energy, density, etc. Uncertainty quantification methods for computer models with functional response have resulted in tools for emulation, sensitivity analysis, and calibration that are widely used. However, many of these tools do not perform well when the computer model’s parameters control both the amplitude variation of the functional output and its alignment (or phase variation). This paper introduces a framework for Bayesian model calibration when the model responses are misaligned functional data. The approach generates two types of data out of the misaligned functional responses: (1) aligned functions so that the amplitude variation is isolated and (2) warping functions that isolate the phase variation. These two types of data are created for the computer simulation data (both of which may be emulated) and the experimental data. The calibration approach uses both types so that it seeks to match both the amplitude and phase of the experimental data. The framework is careful to respect constraints that arise, especially when modeling phase variation, and is framed in a way that it can be done with readily available calibration software. In conclusion, we demonstrate the techniques on two simulated data examples and on two dynamic material science problems: a strength model calibration using flyer plate experiments and an equation of state model calibration using experiments performed on the Sandia National Laboratories’ Z-machine.

97 MATHEMATICS AND COMPUTING↗

FLORIS v3.5 Wake Modeling and Wind Farm Controls Software [SWR-17-43 and SWR-14-20]

FLORIS is a controls-focused wind farm simulation software incorporating steady-state engineering wake models into a performance-focused Python framework. It has been in active development at NREL since 2013 and the latest release is FLORIS v3.5.Online documentation is available at https://nrel.github.io/floris. The software is in active development and engagement with the development team is highly encouraged. If you are interested in using FLORIS to conduct studies of a wind farm or extending FLORIS to include your own wake model, please join the conversation in GitHub Discussions! https://www.nrel.gov/wind/floris.html

Fleming, Paul↗

Four principles to establish a universal virus taxonomy

A universal taxonomy of viruses is essential for a comprehensive view of the virus world and for communicating the complicated evolutionary relationships among viruses. However, there are major differences in the conceptualisation and approaches to virus classification and nomenclature among virologists, clinicians, agronomists, and other interested parties. Here, we provide recommendations to guide the construction of a coherent and comprehensive virus taxonomy, based on expert scientific consensus. Firstly, assignments of viruses should be congruent with the best attainable reconstruction of their evolutionary histories, i.e., taxa should be monophyletic. This fundamental principle for classification of viruses is currently included in the International Committee on Taxonomy of Viruses (ICTV) code only for the rank of species. Secondly, phenotypic and ecological properties of viruses may inform, but not override, evolutionary relatedness in the placement of ranks. Thirdly, alternative classifications that consider phenotypic attributes, such as being vector-borne (e.g., “arboviruses”), infecting a certain type of host (e.g., “mycoviruses,” “bacteriophages”) or displaying specific pathogenicity (e.g., “human immunodeficiency viruses”), may serve important clinical and regulatory purposes but often create polyphyletic categories that do not reflect evolutionary relationships. Nevertheless, such classifications ought to be maintained if they serve the needs of specific communities or play a practical clinical or regulatory role. However, they should not be considered or called taxonomies. Finally, while an evolution-based framework enables viruses discovered by metagenomics to be incorporated into the ICTV taxonomy, there are essential requirements for quality control of the sequence data used for these assignments. Combined, these four principles will enable future development and expansion of virus taxonomy as the true evolutionary diversity of viruses becomes apparent.

59 BASIC BIOLOGICAL SCIENCES↗

Evaluation of automated decisionmaking methodologies and development of an integrated robotic system simulation, volume 2, part 1. Appendix A: Software documentation

Documentation of the preliminary software developed as a framework for a generalized integrated robotic system simulation is presented. The program structure is composed of three major functions controlled by a program executive. The three major functions are: system definition, analysis tools, and post processing. The system definition function handles user input of system parameters and definition of the manipulator configuration. The analysis tools function handles the computational requirements of the program. The post processing function allows for more detailed study of the results of analysis tool function executions. Also documented is the manipulator joint model software to be used as the basis of the manipulator simulation which will be part of the analysis tools capability.

Lowrie, J. W.↗

Procedure for utilizing the lift and thrust forces of ornithopters

This procedure is distinguished by two beating wings which together describe, in space, a succession of interlaced triangles. On these wings, whose incidence varies automatically, identical forces are exerted: simultaneous lift and thrust when they make their descent, which is inclined toward the front of the craft, and lift alone when they make their ascent, which is inclined toward the rear of the craft and follows a slide horizontal movement. A mechanical device makes these movements possible. It includes: two wings with hollow profiles, connected by a framework located above a rigid frame and attached to it by bars with joints. These bars are moved with control rods which gear down the drive force. A mechanism with elastic bands or springs automatically varies the incidence of the wings.

Bezard, C.↗

Linear quadratic servo control of a reusable rocket engine

The paper deals with the development of a design method for a servo component in the frequency domain using singular values and its application to a reusable rocket engine. A general methodology used to design a class of linear multivariable controllers for intelligent control systems is presented. Focus is placed on performance and robustness characteristics, and an estimator design performed in the framework of the Kalman-filter formalism with emphasis on using a sensor set different from the commanded values is discussed. It is noted that loop transfer recovery modifies the nominal plant noise intensities in order to obtain the desired degree of robustness to uncertainty reflected at the plant input. Simulation results demonstrating the performance of the linear design on a nonlinear engine model over all power levels during mainstage operation are discussed.

Musgrave, Jeffrey L.↗

Approach for Autonomous Control of Unmanned Aerial Vehicle Using Intelligent Agents for Knowledge Creation

This paper describes the development of a planned approach for Autonomous operation of an Unmanned Aerial Vehicle (UAV). A Hybrid approach will seek to provide Knowledge Generation through the application of Artificial Intelligence (AI) and Intelligent Agents (IA) for UAV control. The applications of several different types of AI techniques for flight are explored during this research effort. The research concentration is directed to the application of different AI methods within the UAV arena. By evaluating AI and biological system approaches. which include Expert Systems, Neural Networks. Intelligent Agents, Fuzzy Logic, and Complex Adaptive Systems, a new insight may be gained into the benefits of AI and CAS techniques applied to achieving true autonomous operation of these systems. Although flight systems were explored, the benefits should apply to many Unmanned Vehicles such as: Rovers. Ocean Explorers, Robots, and autonomous operation systems. A portion of the flight system is broken down into control agents that represent the intelligent agent approach used in AI. After the completion of a successful approach, a framework for applying an intelligent agent is presented. The initial results from simulation of a security agent for communication are presented.

Dufrene, Warren R., Jr.↗

Mission Control Technologies: A New Way of Designing and Evolving Mission Systems

Current mission operations systems are built as a collection of monolithic software applications. Each application serves the needs of a specific user base associated with a discipline or functional role. Built to accomplish specific tasks, each application embodies specialized functional knowledge and has its own data storage, data models, programmatic interfaces, user interfaces, and customized business logic. In effect, each application creates its own walled-off environment. While individual applications are sometimes reused across multiple missions, it is expensive and time consuming to maintain these systems, and both costly and risky to upgrade them in the light of new requirements or modify them for new purposes. It is even more expensive to achieve new integrated activities across a set of monolithic applications. These problems impact the lifecycle cost (especially design, development, testing, training, maintenance, and integration) of each new mission operations system. They also inhibit system innovation and evolution. This in turn hinders NASA's ability to adopt new operations paradigms, including increasingly automated space systems, such as autonomous rovers, autonomous onboard crew systems, and integrated control of human and robotic missions. Hence, in order to achieve NASA's vision affordably and reliably, we need to consider and mature new ways to build mission control systems that overcome the problems inherent in systems of monolithic applications. The keys to the solution are modularity and interoperability. Modularity will increase extensibility (evolution), reusability, and maintainability. Interoperability will enable composition of larger systems out of smaller parts, and enable the construction of new integrated activities that tie together, at a deep level, the capabilities of many of the components. Modularity and interoperability together contribute to flexibility. The Mission Control Technologies (MCT) Project, a collaboration of multiple NASA Centers, led by NASA Ames Research Center, is building a framework to enable software to be assembled from flexible collections of components and services.

Trimble, Jay↗

Spaceport Command and Control System Support Software Development

The Spaceport Command and Control System (SCCS) is a project developed and used by NASA at Kennedy Space Center in order to control and monitor the Space Launch System (SLS) at the time of its launch. One integral subteam under SCCS is the one assigned to the development of a data set building application to be used both on the launch pad and in the Launch Control Center (LCC) at the time of launch. This web application was developed in Ruby on Rails, a web framework using the Ruby object-oriented programming language, by a 15 - employee team (approx.). Because this application is such a huge undertaking with many facets and iterations, there were a few areas in which work could be more easily organized and expedited. As an intern working with this team, I was charged with the task of writing web applications that fulfilled this need, creating a virtual and highly customizable whiteboard in order to allow engineers to keep track of build iterations and their status. Additionally, I developed a knowledge capture web application wherein any engineer or contractor within SCCS could ask a question, answer an existing question, or leave a comment on any question or answer, similar to Stack Overflow.

Knowledge Transfer↗

Achieving Resilient In-Flight Performance for Advanced Air Mobility through Simplified Vehicle Operations

A research and development (R&D) approach is proposed for developing and validating concepts and technologies to achieve vehicle autonomy goals of Advanced Air Mobility (AAM) through Simplified Vehicle Operations (SVO). The approach applies resilience-engineering and human-automation teaming (HAT) principles to a framework for defining vehicle-based functions for the management of missions and flight trajectories, focusing initially on the en route flight domain. To achieve the SVO goal of reducing pilot training requirements and thereby increasing the pilot pool for AAM, while at the same time promoting ever-safer operations, a framework for identifying essential functions is proposed. In this framework, functions are first categorized by high-level functional purpose (mission management, flightpath management, tactical operations, and vehicle control) and then subcategorized by attributes of resilient-performing systems (abilities to monitor, respond, learn, and anticipate). The categorization by functional purpose provides structure within which HAT designs can be holistically explored and total levels of human vs. automation responsibility can be varied. The subcategorization by resilient-system attributes provides a mechanism for capturing safety-critical functions that may not be codified in current operational procedures and training curricula, particularly those where humans proactively enhance safety in currently undocumented ways. An R&D approach consisting of seven strategies is proposed in which automation engineering and human-factors communities can collaborate in the research, development, and design of an SVO roadmap to enable the ambitious objectives of AAM.

AAM↗

Novel Remediation of Mercury-Contaminated Sediments Using Manganese Oxide and Activated Carbon Amendments - 20394

Mercury contamination in sediments poses a challenging remediation problem because of its ability to biogeochemically cycle and biomagnify in the food chain as methylmercury from low resident sediment and porewater concentrations. One mitigation approach is to lower the overall rate of net methylmercury production by creating conditions unfavorable for sulfate and iron reduction or methanogenesis, the primary pathways for methylation of inorganic mercury. Manganese oxides and other redox-active amendments are a promising and novel in situ amendment technology aimed at reducing net methylation of mercury though control of redox conditions in mercury-contaminated sediment-water systems. This paper reviews the thermodynamic and kinetic framework for this remediation technology, presents experimental and spectroscopic data illustrating the approach using solid manganese oxides, and discusses potential advantages, disadvantages, and applications. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

IBR Bulk System Protection Issues and Modeling Challenges

Issue to be Address: Difficulty in predicting Inverter (IBR) generation dynamic response characteristics. Main challenges are unavailability of proprietary control details for modeling and the aggregate mixed IBRs with different dynamic response characteristics all contributing during system faults. Framework for Discussion: Identifying issues by sharing experience Reviewing options to improve IBR modeling accuracy, computation speed, use of test results. Presenting related research by EPRI and PG&E (DOE project) Desired Outcomes: Provide technical update for participants Get feedback and suggestions for ongoing research Improve research collaboration

IBR, Protection Challenges, dynamic response, IBR ↗

A Framework for Integration of IVHM Technologies for Intelligent Integration for Vehicle Management

As a part of the overall goal of developing Integrated Vehicle Health Management (IVHM) systems for aerospace vehicles, the NASA Faculty Fellowship Program (NFFP) at Marshall Space Flight Center has performed a pilot study on IVHM principals which integrates researched IVHM technologies in support of Integrated Intelligent Vehicle Management (IIVM). IVHM is the process of assessing, preserving, and restoring system functionality across flight and ground systems (NASA NGLT 2004). The framework presented in this paper integrates advanced computational techniques with sensor and communication technologies for spacecraft that can generate responses through detection, diagnosis, reasoning, and adapt to system faults in support of IIVM. These real-time responses allow the IIVM to modify the effected vehicle subsystem(s) prior to a catastrophic event. Furthermore, the objective of this pilot program is to develop and integrate technologies which can provide a continuous, intelligent, and adaptive health state of a vehicle and use this information to improve safety and reduce costs of operations. Recent investments in avionics, health management, and controls have been directed towards IIVM. As this concept has matured, it has become clear the IIVM requires the same sensors and processing capabilities as the real-time avionics functions to support diagnosis of subsystem problems. New sensors have been proposed, in addition, to augment the avionics sensors to support better system monitoring and diagnostics. As the designs have been considered, a synergy has been realized where the real-time avionics can utilize sensors proposed for diagnostics and prognostics to make better real-time decisions in response to detected failures. IIVM provides for a single system allowing modularity of functions and hardware across the vehicle. The framework that supports IIVM consists of 11 major on-board functions necessary to fully manage a space vehicle maintaining crew safety and mission objectives: Guidance and Navigation; Communications and Tracking; Vehicle Monitoring; Information Transport and Integration; Vehicle Diagnostics; Vehicle Prognostics; Vehicle mission Planning; Automated Repair and Replacement; Vehicle Control; Human Computer Interface; and Onboard Verification and Validation. Furthermore, the presented framework provides complete vehicle management which not only allows for increased crew safety and mission success through new intelligence capabilities, but also yields a mechanism for more efficient vehicle operations. The representative IVHM technologies for IIVH includes: 1) robust controllers for use in re-usable launch vehicles, 2) scaleable/flexible computer platform using heterogeneous communication, 3) coupled electromagnetic oscillators for enhanced communications, 4) Linux-based real-time systems, 5) genetic algorithms, 6) Bayesian Networks, 7) evolutionary algorithms, 8) dynamic systems control modeling, and 9) advanced sensing capabilities. This paper presents IVHM technologies developed under NASA's NFFP pilot project. The integration of these IVHM technologies forms the framework for IIVM.

Paris, Deidre E.↗

Control-oriented modeling of combustion and flow processes in liquid propellant rocket engines

This paper presents a control-oriented model of the flow, reaction, and transport processes in liquid propellant rocket combustion chambers, based on the multicomponent conservation laws of gas dynamics. This model provides a framework for the inclusion of detailed chemical kinetic relations, viscous and other dissipative effects, a variety of actuators and sensors, as well as process and measurement disturbances. In addition to its potential usefulness to the designer in understanding the dynamical complexity of the system and the sources of model uncertainty, the model provides a rigorous basis for control system design. An appraisal of current and feasible actuators and sensors, and their mathematical representation are included.

Bentsman, Joseph↗

Knowledge Discovery for Early Failure Assessment of Complex Engineered Systems Using Natural Language Processing

Emerging complex engineered systems may have unexpected safety issues due to novel operational environments, increasing autonomy, human-machine interaction, and other factors. To prevent failures in operation or testing that necessitate costly redesign, it is desirable to predict likely failure modes early in the design process. Text-based information about past engineering failures presents one possible solution by facilitating the retrieval of information that can inform new designs. However, identifying documents containing relevant information and extracting required information can be prohibitively time-consuming when implemented at scale. In this research, an automated natural language processing-based framework is proposed to discover relevant knowledge from documents containing failure-related design information. Documents containing usable information are filtered using sentiment analysis based on a custom lexicon specialized for engineering design and by filtering out documents containing only irrelevant topics. Next, from the identified usable documents, information relating to engineering failures, contributing factors that can be controlled at design time (“risk factors”), and recommended preventative actions are extracted. Semantic similarity is then used to group similar pieces of extracted information for improved generalizability. The proposed framework is applied to NASA’s Lessons Learned Information System (LLIS). The framework can be used to identify documents containing usable failure-related design information from other databases, extract relevant information from these documents, and generalize the acquired knowledge such that it can be applied to novel systems.

Sequoia R. Andrade↗