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At least 1,477 records · Page 82

Flight control systems development of highly maneuverable aircraft technology /HiMAT/ vehicle

The highly maneuverable aircraft technology (HiMAT) program was conceived to demonstrate advanced technology concepts through scaled-aircraft flight tests using a remotely piloted technique. Closed-loop primary flight control is performed from a ground-based cockpit, utilizing a digital computer and up/down telemetry links. A backup flight control system for emergency operation resides in an onboard computer. The onboard systems are designed to provide fail-operational capabilities and utilize two microcomputers, dual uplink receiver/decoders, and redundant hydraulic actuation and power systems. This paper discusses the design and validation of the primary and backup digital flight control systems as well as the unique pilot and specialized systems interfaces.

Petersen, K. L.↗

Design of a LQR Controller of Reduced Inputs for Multiple Spacecraft Formation Flying

Regarding multiple spacecraft formation flying, the observation is made that control thrust need only be applied coplanar to the local horizon to achieve complete controllability of a two-satellite formation. Without the need for zenith-nadir (radial) thrust, simplifications and reduction of the weight of the propulsion system may be accomplished. This work focuses on the validation of this radial-excluding control system on its own merits, and in comparison to a related system which does provide thrust parallel to the orbital radius. Simulations are performed using commercial ODE solvers to propagate the Keplerian dynamics of a controlled satellite relative to an uncontrolled, leader satellite. The conclusion is drawn that, despite the exclusion of the radial thrust axis, the remaining control thrust available still provides enough control to design a gain matrix of adequate performance using linear-quadratic regulator (LQR) techniques.

Starin, Scott R.↗

Evaluation of Erosion Resistance of Advanced Turbine Thermal Barrier Coatings

The erosion resistant turbine thermal barrier coating system is critical to aircraft engine performance and durability. By demonstrating advanced turbine material testing capabilities, we will be able to facilitate the critical turbine coating and subcomponent development and help establish advanced erosion-resistant turbine airfoil thermal barrier coatings design tools. The objective of this work is to determine erosion resistance of advanced thermal barrier coating systems under simulated engine erosion and/or thermal gradient environments, validating advanced turbine airfoil thermal barrier coating systems based on nano-tetragonal phase toughening design approaches.

Zhu, Dongming↗

Machine-learning Solution for Automatic Spacesuit Motion Recognition and Measurement from Conventional Video

Extravehicular Activity (EVA) spacesuits exhibit unique movement patterns due to their design characteristics. Mobility assessments using traditional motion capture systems are cost prohibitive and not feasible for some training conditions (e.g., simulated lunar outdoor terrain). This paper aims to present the ongoing development of machine learning solutions to quantify suit motions from conventional videos without special sensors or hardware. Given the fast growth in deep/machine learning technologies, external expertise was sought from open-source communities. This was expected to accelerate development and provide more cost-effective, time-saving solutions. This work was selected for a NASA Crowdsourcing project through an agency-wide solicitation. Partnerships were formed with the NASA JSC Center of Excellence for Collaborative Innovation and an execution crowdsourcing platform partner to solicit framework developments from external contenders. NASA provided contenders with video clips of spacesuits and simultaneously measured motion capture data during EVA simulation tasks. The contenders used this data to train and develop generalized algorithms to predict motions. At the end of the crowdsourcing event, five solutions were selected from 250 submissions. Each submission was tested and scored using video clips not previously disclosed to the contenders. The scoring metrics measured how well the algorithm detected the suit shape, the 2D suit joint detection accuracy, and 3D joint detection accuracy. The winning solution was able to achieve roughly 85% prediction accuracy (weighted combination of scoring metrics). Overall, the algorithms could efficiently detect various types of spacesuits and motions across different EVA simulation environments such as the Neutral Buoyancy Lab (NBL). However, 3D joint identification is less reliable when parts of the suit were obstructed in the image. After continued improvements and validation, the fully developed system will enable EVA stakeholders to quantify suit kinematic patterns, which can help optimize suit, hardware, and task designs.

Linh Vu↗

TRANSENSOR: Transformer Real-time Assessment INtelligent System with Embedded Network of Sensors and Optical Readout. Final Report

Utilities across the world are wrestling with evolving market dynamics, population growth and climate change. Distributed Energy Resources (DERs) such as solar photovoltaics, distributed generators and energy storage systems are becoming important parts of the U.S. energy mix. These factors are driving an increasing need for low-cost grid asset monitoring. Aside from being costly, traditional utility monitoring systems are not sufficiently robust and do not provide real-time visibility into the condition of grid assets such as transformers. Lack of accurate real-time measurements on performance has resulted in the use of lagging indicators, such as oil sample analysis. To address this need, an innovative embedded optical sensing technology, Transformer Real-time Assessment Intelligent System (TRANSENSOR) was developed, validated and demonstrated in this project. To date, TRANSENSOR has focused on transformers but is extendable to other grid assets. In addition to the technology being embedded into new transformers during manufacturing, a retrofit configuration that can be installed on existing transformers in the field was also developed. It is anticipated that the ability to retrofit existing transformers will help accelerate adoption of the underlying TRANSENSOR technology. Phase 1 of the project focused on laboratory development and qualification of the technology. Following iterations and exploration of relevant optical sensing modalities and multiplexed configurations of interest for the transformer environment, an effective candidate configuration was agreed upon, down-selected and custom-designed for embedding into General Electric (GE) network transformers. Two new GE 500 kilovolt ampere (kVA), 27 kilovolt (kV) distribution network transformers were built with embedded fiber-optic (FO) sensors and successfully qualified per industry standards at GE’s Shreveport, Louisiana facility during Phase 1 of the project. Following the successful completion of Phase 1, the team proceeded to Phase 2, which focused on a field demonstration of the technology. Over Phase 2, the first new GE transformer built with embedded fiber-optic sensors was installed in an above-ground cage and connected to the grid at Con Edison’s Astoria facility. A second transformer equipped with TRANSENSOR was installed in an underground vault. Additionally, an older (1982 year model) GE transformer in an above-ground cage was retrofitted with fiber- optic sensors and reconnected to the grid at ConEd’s facility. Analysis of data acquired from the sensors showed interesting correlations with transformer loading. Additionally, key events such as transformer low-voltage network connection, primary-side energizing, and a pressure loss event from an oil sampling were detected by the TRANSENSOR system. Online data processing/feature extraction algorithms for the second transformer in the underground vault detected key features and event alerts that were transmitted through a wireless 4G connection. The remote deployment concept showed promising results with data collection running for a total of 8 months across the three (3) GE transformers instrumented for the Phase 2 field demonstration. This sets the stage well for further development and commercialization.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Evolving dual-trait EPSP synthase variants using a synthetic yeast selection system

The enzyme 5-enolpyruvylshikimate-3-phosphate synthase (EPSPS) functions in the shikimate pathway which is responsible for the production of aromatic amino acids and precursors of other essential secondary metabolites in all plant species. EPSPS is also the molecular target of the herbicide glyphosate. While some plant EPSPS variants have been characterized with reduced glyphosate sensitivity and have been used in biotechnology, the glyphosate insensitivity typically comes with a cost to catalytic efficiency. Thus, there exists a need to generate additional EPSPS variants that maintain both high catalytic efficiency and high glyphosate tolerance. Here, we create a synthetic yeast system to rapidly study and evolve heterologous EPSP synthases for these dual traits. Using known EPSPS variants, we first validate that our synthetic yeast system is capable of recapitulating growth characteristics observed in plants grown in varying levels of glyphosate. Next, we demonstrate that variants from mutagenesis libraries with distinct phenotypic traits can be isolated depending on the selection criteria applied. By applying strong dual-trait selection pressure, we identify a notable EPSPS mutant after just a single round of evolution that displays robust glyphosate tolerance (K i of nearly 1 mM) and improved enzymatic efficiency over the starting point (~2.5 fold). Finally, we show the crystal structure of corn EPSPS and the top resulting mutants and demonstrate that certain mutants have the potential to outperform previously reported glyphosate-resistant EPSPS mutants, such as T102I and P106S (denoted as TIPS), in whole-plant testing. Altogether, this platform helps explore the trade-off between glyphosate resistance and enzymatic efficiency.

Science & Technology - Other Topics↗

DSN data systems software methodology

A software methodology for JPL deep space network (DSN) data systems software implementations through transfer and delivery is presented. The DSN Data Systems Software Methodology is compatible with and depends on DSN software methodology and also incorporates the characteristics of real-time program development in a DSN environment. The DSN Data Systems software implementation consists of a series of six distinct phases. An Independent Group is responsible for verification and validation of the DSN Data Systems software during developing phases. The DSN data systems software methodology is applied to all development software provided for or by the DSN data systems section in Mark IV where there is a desire for reliability, maintainability, and usability within budget and schedule constraints.

Hung, C. K.↗

Multi-viewpoint clustering analysis

In this paper, we address the feasibility of partitioning rule-based systems into a number of meaningful units to enhance the comprehensibility, maintainability and reliability of expert systems software. Preliminary results have shown that no single structuring principle or abstraction hierarchy is sufficient to understand complex knowledge bases. We therefore propose the Multi View Point - Clustering Analysis (MVP-CA) methodology to provide multiple views of the same expert system. We present the results of using this approach to partition a deployed knowledge-based system that navigates the Space Shuttle's entry. We also discuss the impact of this approach on verification and validation of knowledge-based systems.

Mehrotra, Mala↗

Connecting Research and Practice: An Experience Report on Research Infusion with SAVE

NASA systems need to be highly dependable to avoid catastrophic mission failures. This calls for rigorous engineering processes including meticulous validation and verification. However, NASA systems are often highly distributed and overwhelmingly complex, making the software portion of these systems challenging to understand, maintain, change, reuse, and test. NASA's systems are long-lived and the software maintenance process typically constitutes 60-80% of the total cost of the entire lifecycle. Thus, in addition to the technical challenges of ensuring high life-time quality of NASA's systems, the post-development phase also presents a significant financial burden. Some of NASA's software-related challenges could potentially be addressed by some of the many powerful technologies that are being developed in software research laboratories. Many of these research technologies seek to facilitate maintenance and evolution by for example architecting, designing and modeling for quality, flexibility, and reuse. Other technologies attempt to detect and remove defects and other quality issues by various forms of automated defect detection, architecture analysis, and various forms of sophisticated simulation and testing. However promising, most such research technologies nevertheless do not make the transition from the research lab to the software lab. One reason the transition from research to practice seldom occurs is that research infusion and technology transfer is difficult. For example, factors related to the technology are sometimes overshadowed by other types of factors such as reluctance to change and therefore prohibits the technology from sticking. Successful infusion might also take very long time. One famous study showed that the discrepancy between the conception of the idea and its practical use was 18 years plus or minus three. Nevertheless, infusing new technology is possible. We have found that it takes special circumstances for such research infusion to succeed: 1) there must be evidence that the technology works in the practitioner's particular domain, 2) there must be a potential for great improvements and enhanced competitive edge for the practitioner, 3) the practitioner has to have strong individual curiosity and continuous interest in trying out new technologies, 4) the practitioner has to have support on multiple levels (i.e. from the researchers, from management, from sponsors etc), and 5) to remain infused, the new technology has to be integrated into the practitioner's processes so that it becomes a natural part of the daily work. NASA IV&V's Research Infusion initiative sponsored by NASA's Office of Safety & Mission Assurance (OSMA) through the Software Assurance Research Program (SARP), strives to overcome some of the problems related to research infusion.

Lindvall, Mikael↗

Integrated operation scenarios: Chapter 6 of the special issue: on the path to tokamak burning plasma operation

Here we report the progress of the development and optimization of operational scenarios for ITER and beyond, focusing upon baseline, hybrid, and steady-state scenarios since 2007. This includes advancements made by the integrated operation scenarios (IOS) topical group of the international tokamak physical activity as well as contributions from the broader tokamak community. The key area of research involves developing IOSs that encompass tokamak physics, operation, and technology by utilizing integrated modeling and control strategies. This requires leveraging available actuators to simultaneously control plasma position and shape, MHD activities that could lead to disruptions, transport, plasma-wall interaction and power exhaust, fuel cycle, fusion burn, and tritium breeding. The control extends from the plasma initiation phase, through the current ramp-up, flattop, start and end of the fusion burn, and current ramp-down, to the plasma termination phase. A review of the currently developed scenarios and modeling is provided in terms of (i) optimizing plasma initiation in ITER, (ii) preparing for the low activation phase to fully commission all tokamak systems and establish and validate physics and scenario conditions in preparation for deuterim-tritium (DT) operation, (iii) developing and preparing baseline and hybrid scenarios to demonstrate the feasibility of achieving these regimes within device constraints, (iv) exploring steady-state scenarios to meet ITER’s steady-state goals, (v) evaluating and preparing actuators for ITER, (vi) developing integrated control solutions using shared actuators. The most notable achievements include; (i) the development of ITER demonstration discharges by matching various dimensionless parameters, (ii) the development of scenarios in an ITER-like tungsten environment and DT operation, and (iii) the development of scenarios in superconducting tokamaks, enabling long-pulse operations with similar coil constraints to ITER. Along with these significant achievements, outstanding issues and recommendations for further research and development are provided. Importantly, this study goes beyond simply updating the ITER Physics Basis; it carries profound implications for the broader field of burning plasma research, offering valuable insights and guidance for the next generation of fusion experiments and devices.

ITER↗

A validation methodology for fault-tolerant clock synchronization

A validation method for the synchronization subsystem of a fault-tolerant computer system is presented. The high reliability requirement of flight crucial systems precludes the use of most traditional validation methods. The method presented utilizes formal design proof to uncover design and coding errors and experimentation to validate the assumptions of the design proof. The experimental method is described and illustrated by validating an experimental implementation of the Software Implemented Fault Tolerance (SIFT) clock synchronization algorithm. The design proof of the algorithm defines the maximum skew between any two nonfaulty clocks in the system in terms of theoretical upper bounds on certain system parameters. The quantile to which each parameter must be estimated is determined by a combinatorial analysis of the system reliability. The parameters are measured by direct and indirect means, and upper bounds are estimated. A nonparametric method based on an asymptotic property of the tail of a distribution is used to estimate the upper bound of a critical system parameter. Although the proof process is very costly, it is extremely valuable when validating the crucial synchronization subsystem.

Johnson, S. C.↗

A Bilevel Voltage Regulation Operation for Distribution Systems With Self-Operated Microgrids

The emerging of microgrids in distribution systems has significantly enhanced the resilience of power grids. However, the operators of a distribution system and microgrids therein can be different and have accessibility to different devices. To model the operation of such a grid, this work proposes a bilevel formulation and probes into the voltage regulation operation, considering the interaction between different systems. The proposed bilevel formulation considers the cooperation of active energy resources (AER), transformer tap-changers, and capacitor banks that are controlled by different operators. To facilitate the solution time of the target bilevel optimization, the lower-level problems with different objectives are modeled using deep neural networks (DNNs) which are then converted into a set of constraints. Hence, the bilevel problem can be reformed to a single-level problem. Lastly, the proposed solution procedures are validated using a customized joint system constructed by the IEEE 123-bus system and a real distribution system in Iowa. According to the numerical validation results, the solution time of the proposed nonlinear activation function based DNN model is 69 times faster than other methods in solving voltage regulation with a bilevel structure.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Experimental platforms for investigating feature-driven jets for HED mix model validation

High-energy-density (HED) systems, such as inertial confinement fusion (ICF), are susceptible to hydrodynamic instabilities that can significantly affect both experimental results and modeling predictions. Isolated features, such as fill tubes or divots in the capsule, can cause material to jet as a result of the compressive shock exciting the Richtmyer–Meshkov instability, and serve as one of the primary degradation mechanisms in ICF yield. Simulations of feature-driven jets and how they mix require extensive experimental validation, particularly for understanding to what degree the initial size and shape of a feature influence jet dynamics, and how much instability feeds through downstream layers. A better understanding of feature-driven jetting can improve our mix modeling capabilities and increase hydrodynamic simulation accuracy. This manuscript describes a series of experimental platforms fielded by Los Alamos National Laboratory as a part of the Mshock Omega 60 and ModCons Omega EP campaigns to explore feature-driven jetting. These platforms are designed to benchmark jet evolution and growth as a function of initial feature size and shape, investigate jet-layer interactions leading to instability feedthrough, and will be used to characterize jet-jet interactions resulting from clusters of features. In conclusion, preliminary results for both platforms are shown. The ModCons experiments are on-going, and a discussion of future work directions is included.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Risk management and expert system development methodology

A risk-based expert-system development methodology has been developed to provide guidance to managers and technical personnel and to serve as a standard for developing expert systems. Expert-system development differs from conventional software development in that the information needed to prepare system requirements for expert systems is not known at the outset of a project and is obtained by knowledge engineering methods. The paper describes the expert-system life cycle, development methodology, and the approach taken in this methodology to manage and reduce the risks in expert system development. Also examined are the risks of using and of not using a methodology, the studies undertaken to validate the provisions of the expert system development methodology, and the results of these validation studies.

Hull, Larry↗

Mechanistic modeling of in vitro transcription incorporating effects of magnesium pyrophosphate crystallization

The in vitro transcription (IVT) reaction used in the production of messenger RNA vaccines and therapies remains poorly quantitatively understood. Mechanistic modeling of IVT could inform reaction design, scale-up, and control. In this work, we develop a mechanistic model of IVT to include nucleation and growth of magnesium pyrophosphate crystals and subsequent agglomeration of crystals and DNA. To help generalize this model to different constructs, a novel quantitative description is included for the rate of transcription as a function of target sequence length, DNA concentration, and T7 RNA polymerase concentration. The model explains previously unexplained trends in IVT data and quantitatively predicts the effect of adding the pyrophosphatase enzyme to the reaction system. The model is validated on additional literature data showing an ability to predict transcription rates as a function of RNA sequence length.

59 BASIC BIOLOGICAL SCIENCES↗

Calibration and Validation of a Mechanistic COVID-19 Model for Translational Quantitative Systems Pharmacology – A Proof-of-Concept Model Development for Remdesivir

With the ongoing global pandemic of coronavirus disease 2019 (COVID-19), there is an urgent need to accelerate the traditional drug development process. Many studies identified potential COVID-19 therapies based on promising nonclinical data. However, the poor translatability from nonclinical to clinical settings has led to failures of many of these drug candidates in the clinical phase. In this study, we propose a mechanism-based, quantitative framework to translate nonclinical findings to clinical outcome. Adopting a modularized approach, this framework includes an in silico disease model for COVID-19 (virus infection and human immune responses) and a pharmacological component for COVID-19 therapies. Here, the disease model was able to reproduce important longitudinal clinical data for patients with mild and severe COVID-19, including viral titer, key immunological cytokines, antibody responses, and time courses of lymphopenia. Using remdesivir as a proof-of-concept example of model development for the pharmacological component, we developed a pharmacological model that describes the conversion of intravenously administered remdesivir as a prodrug to its active metabolite nucleoside triphosphate through intracellular metabolism and connected it to the COVID-19 disease model. After being calibrated with the placebo arm data, our model was independently and quantitatively able to predict the primary endpoint (time to recovery) of the remdesivir clinical study, Adaptive Covid-19 Clinical Trial (ACTT). Our work demonstrates the possibility of quantitatively predicting clinical outcome based on nonclinical data and mechanistic understanding of the disease and provides a modularized framework to aid in candidate drug selection and clinical trial design for COVID-19 therapeutics.

60 APPLIED LIFE SCIENCES↗

Evaluating the mutagenicity of N-nitrosodimethylamine in 2D and 3D HepaRG cell cultures using error-corrected next generation sequencing

Human liver-derived metabolically competent HepaRG cells have been successfully employed in both two-dimensional (2D) and 3D spheroid formats for performing the comet assay and micronucleus (MN) assay. In the present study, we have investigated expanding the genotoxicity endpoints evaluated in HepaRG cells by detecting mutagenesis using two error-corrected next generation sequencing (ecNGS) technologies, Duplex Sequencing (DS) and High-Fidelity (HiFi) Sequencing. Both HepaRG 2D cells and 3D spheroids were exposed for 72 h to N-nitrosodimethylamine (NDMA), followed by an additional incubation for the fixation of induced mutations. NDMA-induced DNA damage, chromosomal damage, and mutagenesis were determined using the comet assay, MN assay, and ecNGS, respectively. The 72-h treatment with NDMA resulted in concentration-dependent increases in cytotoxicity, DNA damage, MN formation, and mutation frequency in both 2D and 3D cultures, with greater responses observed in the 3D spheroids compared to 2D cells. The mutational spectrum analysis showed that NDMA induced predominantly A:T → G:C transitions, along with a lower frequency of G:C → A:T transitions, and exhibited a different trinucleotide signature relative to the negative control. These results demonstrate that the HepaRG 2D cells and 3D spheroid models can be used for mutagenesis assessment using both DS and HiFi Sequencing, with the caveat that severe cytotoxic concentrations should be avoided when conducting DS. With further validation, the HepaRG 2D/3D system may become a powerful human-based metabolically competent platform for genotoxicity testing.

3D spheroids↗

Effect of disorder on thermodynamic instability of binary Rare-earth – Nickel – Palladium compounds

In this work, we have investigated the thermodynamic stability of disordered rare-earth phases SmX 2 and Sm 10 X 21 (X=Ni, Pd) using machine-learning based analytical descriptor and first-principles density functional theory methods. The absence of Laves phase compounds in R-Pd binary systems is a longstanding problem of rare earth science: even though Ni and Pd belong to the same group of the periodic table and have similar electronic structure, the Pd compound crystallizes in a monoclinic (C2/m) phase with 10:21 stoichiometry, i.e., Sm 10 Pd 21 , while the Ni compound adopts a cubic Laves phase (MgCu 2 ) structure. To understand this contrasting phase stability, we performed thermodynamic convex hull analysis of Sm x Ni 1-x and Sm x Pd 1-x binary systems, which is experimentally validated using powder X-ray diffraction (PXRD) analyzes of polycrystalline Sm(Ni x Pd 1-x ) 2 samples with x=0, 0.5, and 1. A detailed electronic-structure (band-structure, charge density, and Fermi-surface) analysis of the differences between SmNi 2 /SmPd 2 and Sm 10 Ni 21 /Sm 10 Pd 21 compounds provides the quantum mechanical origin of the unfavorable mixing of Pd with Ni in cubic Laves phase. We show that the stability of Sm-Pd in 10:21 stoichiometry arises from improved intra-/inter-layer 5d-4d bonding compared to the 1:2 stoichiometry. Our work emphasizes the importance of ab-initio methods and computationally inexpensive analytical descriptors for the detailed analysis of thermodynamic and electronic properties of hard-to-prepare rare-earth compounds.

36 MATERIALS SCIENCE↗