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At least 1,531 records · Page 85

Optimizing Mars Airplane Trajectory with the Application Navigation System

Planning complex missions requires a number of programs to be executed in concert. The Application Navigation System (ANS), developed in the NAS Division, can execute many interdependent programs in a distributed environment. We show that the ANS simplifies user effort and reduces time in optimization of the trajectory of a martian airplane. We use a software package, Cart3D, to evaluate trajectories and a shortest path algorithm to determine the optimal trajectory. ANS employs the GridScape to represent the dynamic state of the available computer resources. Then, ANS uses a scheduler to dynamically assign ready task to machine resources and the GridScape for tracking available resources and forecasting completion time of running tasks. We demonstrate system capability to schedule and run the trajectory optimization application with efficiency exceeding 60% on 64 processors.

Frumkin, Michael↗

Advances in Ground Transmitters for the NASA Deep Space Network

The Deep Space Network (DSN), managed by the Jet Propulsion Laboratory for NASA, is equipped with multiple microwave transmitters ranging in average radiated power from 200 W to 400 kW. The transmitters are used for routine or emergency communication with spacecraft, for navigation, and for radio science tasks. The latest advances in transmitter engineering were implemented in a new generation of 20-kW dual-band transmitters developed for the DSN 34-m beam waveguide antennas. Innovations include additional X-band communication capability for near Earth missions, new control algorithms, automated calibration, improved and expanded computerized monitoring and diagnostics, reduced cabling, and improved maintainability. The innovations were very beneficial for the DSN 'overload' during the Mars 2003/2004 missions and will benefit other missions throughout the next decade. This paper describes the current design of the new transmitters and possible future developments.

microwaves↗

Building on 50 Years of Mission Operations Experience for a New Era of Space Exploration

The U.S. National Space Policy, I the 14-nation Global Exploration Strategy,2 and the National Aeronautics and Space Administration's (NASA) 2006 Strategic Plan3 provide foundational direction for far-ranging missions, from safely flying the Space Shuttle and completing construction of the International Space Station by 2010, to fielding a next generation space transportation system consisting of the Ares I Crew Launch Vehicle!Orion Crew Exploration Vehicle and the Ares V Cargo Launch Vehicle!Altair Lunar Lander (fig. 1). Transportation beyond low-Earth orbit will open the frontier for a lunar outpost, where astronauts will harness in-situ resources while exploring this 4 billion-year-old archaeological site, which may hold answers to how the Earth and its satellite were formed. Ultimately, this experience will pave the way for the first human footprint on Mars. In October 2007, NASA" announced assignments for this lunar exploration work.4 The Marshall Space Flight Center is responsible for designing, developing, testing, and evaluating the Ares I and Ares V, which are Space Shuttle derived launch vehicles, along with a number of lunar tasks. The Marshall Center's Engineering Directorate provides the skilled workforce and unique manufacturing, testing, and operational infrastructure needed to deliver space transportation solutions that meet the requirements stated in the Constellation Architecture Requirements Document (CARD). While defining design reference missions to the Station and the Moon, the CARD includes goals that include reducing recurring and nonrecurring costs, while increasing safety and reliability. For this reason, future systems are being designed with operability considerations and lifecycle expenses as independent variables in engineering trade studies.

Onken, Jay F.↗

An expert system for integrated structural analysis and design optimization for aerospace structures

The results of a research study on the development of an expert system for integrated structural analysis and design optimization is presented. An Object Representation Language (ORL) was developed first in conjunction with a rule-based system. This ORL/AI shell was then used to develop expert systems to provide assistance with a variety of structural analysis and design optimization tasks, in conjunction with procedural modules for finite element structural analysis and design optimization. The main goal of the research study was to provide expertise, judgment, and reasoning capabilities in the aerospace structural design process. This will allow engineers performing structural analysis and design, even without extensive experience in the field, to develop error-free, efficient and reliable structural designs very rapidly and cost-effectively. This would not only improve the productivity of design engineers and analysts, but also significantly reduce time to completion of structural design. An extensive literature survey in the field of structural analysis, design optimization, artificial intelligence, and database management systems and their application to the structural design process was first performed. A feasibility study was then performed, and the architecture and the conceptual design for the integrated 'intelligent' structural analysis and design optimization software was then developed. An Object Representation Language (ORL), in conjunction with a rule-based system, was then developed using C++. Such an approach would improve the expressiveness for knowledge representation (especially for structural analysis and design applications), provide ability to build very large and practical expert systems, and provide an efficient way for storing knowledge. Functional specifications for the expert systems were then developed. The ORL/AI shell was then used to develop a variety of modules of expert systems for a variety of modeling, finite element analysis, and design optimization tasks in the integrated aerospace structural design process. These expert systems were developed to work in conjunction with procedural finite element structural analysis and design optimization modules (developed in-house at SAT, Inc.). The complete software, AutoDesign, so developed, can be used for integrated 'intelligent' structural analysis and design optimization. The software was beta-tested at a variety of companies, used by a range of engineers with different levels of background and expertise. Based on the feedback obtained by such users, conclusions were developed and are provided.

Source record↗

Novel Estimation of Pilot Performance Characteristics

Two mechanisms internal to the pilot that affect performance during a tracking task are: 1) Pilot equalization (i.e. lead/lag); and 2) Pilot gain (i.e. sensitivity to the error signal). For some applications McRuer's Crossover Model can be used to anticipate what equalization will be employed to control a vehicle's dynamics. McRuer also established approximate time delays associated with different types of equalization - the more cognitive processing that is required due to equalization difficulty, the larger the time delay. However, the Crossover Model does not predict what the pilot gain will be. A nonlinear pilot control technique, observed and coined by the authors as 'amplitude clipping', is shown to improve stability, performance, and reduce workload when employed with vehicle dynamics that require high lead compensation by the pilot. Combining linear and nonlinear methods a novel approach is used to measure the pilot control parameters when amplitude clipping is present, allowing precise measurement in real time of key pilot control parameters. Based on the results of an experiment which was designed to probe workload primary drivers, a method is developed that estimates pilot spare capacity from readily observable measures and is tested for generality using multi-axis flight data. This paper documents the initial steps to developing a novel, simple objective metric for assessing pilot workload and its variation over time across a wide variety of tasks. Additionally, it offers a tangible, easily implementable methodology for anticipating a pilot's operating parameters and workload, and an effective design tool. The model shows promise in being able to precisely predict the actual pilot settings and workload, and observed tolerance of pilot parameter variation over the course of operation. Finally, an approach is proposed for generating Cooper-Harper ratings based on the workload and parameter estimation methodology.

Human pilot models↗

Real-time mixed reality display of dual particle radiation detector data

Radiation source localization and characterization are challenging tasks that currently require complex analyses for interpretation. Mixed reality (MR) technologies are at the verge of wide scale adoption and can assist in the visualization of complex data. Herein, we demonstrate real-time visualization of gamma ray and neutron radiation detector data in MR using the Microsoft HoloLens 2 smart glasses, significantly reducing user interpretation burden. Radiation imaging systems typically use double-scatter events of gamma rays or fast neutrons to reconstruct the incidence directional information, thus enabling source localization. The calculated images and estimated ’hot spots’ are then often displayed in 2D angular space projections on screens. By combining a state-of-the-art dual particle imaging system with HoloLens 2, we propose to display the data directly to the user via the head-mounted MR smart glasses, presenting the directional information as an overlay to the user’s 3D visual experience. We describe an open source implementation using efficient data transfer, image calculation, and 3D engine. We thereby demonstrate for the first time a real-time user experience to display fast neutron or gamma ray images from various radioactive sources set around the detector. We also introduce an alternative source search mode for situations of low event rates using a neural network and simulation based training data to provide a fast estimation of the source’s angular direction. Using MR for radiation detection provides a more intuitive perception of radioactivity and can be applied in routine radiation monitoring, education & training, emergency scenarios, or inspections.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Maximizing efficiency of dataset compression for machine learning potentials with information theory

Machine learning interatomic potentials (MLIPs) balance high accuracy and lower costs compared to density functional theory calculations, but their performance often depends on the size and diversity of training datasets. Large datasets improve model accuracy and generalization but are computationally expensive to produce and train on, while smaller datasets risk discarding rare but important atomic environments and compromising MLIP accuracy/reliability. Here, we develop an information-theoretical framework to quantify the efficiency of dataset compression methods and propose an algorithm that maximizes this efficiency. By framing atomistic dataset compression as an instance of the minimum set cover (MSC) problem over atom-centered environments, our method identifies the smallest subset of structures that contains as much information as possible from the original dataset while pruning redundant information. The approach is extensively demonstrated on the GAP-20 and TM23 datasets and validated on 64 varied datasets from the ColabFit repository. Across all cases, MSC consistently retains outliers, preserves dataset diversity, and reproduces the long-tail distributions of forces even at high compression rates, outperforming other subsampling methods. Furthermore, MLIPs trained on MSC-compressed datasets exhibit reduced error for out-of-distribution data even in low-data regimes. We explain these results using an outlier analysis and show that such quantitative conclusions could not be achieved with conventional dimensionality reduction methods. The algorithm is implemented in the open-source QUESTS package and can be used for several tasks in atomistic modeling, from data subsampling, outlier detection, and training improved MLIPs at a lower cost.

36 MATERIALS SCIENCE↗

Compressing deep neural networks on FPGAs to binary and ternary precision with hls4ml

We present the implementation of binary and ternary neural networks in the hls4ml library, designed to automatically convert deep neural network models to digital circuits with FPGA firmware. Starting from benchmark models trained with floating point precision, we investigate different strategies to reduce the network's resource consumption by reducing the numerical precision of the network parameters to binary or ternary. We discuss the trade-off between model accuracy and resource consumption. In addition, we show how to balance between latency and accuracy by retaining full precision on a selected subset of network components. As an example, we consider two multiclass classification tasks: handwritten digit recognition with the MNIST data set and jet identification with simulated proton-proton collisions at the CERN Large Hadron Collider. The binary and ternary implementation has similar performance to the higher precision implementation while using drastically fewer FPGA resources.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Artificial Neural Network-based State Estimation for Low Observable, Unbalanced Microgrids for Microgrid Building Blocks

The microgrid building blocks (MBB) were proposed as microgrid components with combined sub-components with power conversion, communication, and microgrid control capability, or a subset of such sub-components. This work addresses the microgrid controller, present in an MBB, which requires accurate state estimation to perform its tasks, including for monitoring, power flow (dispatch), fault detection, etc. In this paper, an artificial neural network (ANN)-based framework for state estimation is proposed for an MBB, especially for unbalanced and low observable microgrids. To overcome the challenge of low observability in unbalanced systems, a concept of extended adjacent matrix is introduced to reduce the required number of measurements for state estimation. Addressing the challenges, a feed forward neural network (FNN) is utilized to enhance estimation accuracy and reliability with the reduced number of measurements. The proposed state estimation is validated through extensive simulations on a microgrid, which was achieved from the modified IEEE 34-bus distribution test feeder with multiple distributed energy resources (DERs) and demonstrated superior performance in estimation accuracy and low observability.

Choi, Jongchan↗

Big Data Sanitization and Cyber Situational Awareness: A Network Telescope Perspective

This paper addresses the problems of data sanitization and cyber situational awareness by analyzing 910 GB of real Internet-scale traffic, which has been passively collected by monitoring close to 16.5 million darknet IP addresses from a /8 and a /13 network telescopes. First, the paper offers a novel probabilistic darknet preprocessing model, which aims at sanitizing darknet data to prepare it for effective use in the task of cyber threat intelligence generation. Such model has been engineered using a distributed multithreaded approach, rendering it highly effective on darknet big data. Second, the paper further contributes by presenting an innovative approach to infer large-scale orchestrated probing campaigns by leveraging darknet data, for Internet cyber situational awareness. The approach uniquely reduces the dimensionality of such big data by utilizing its artifacts, instead of processing the actual raw data. This is accomplished by extracting and analyzing probing time series using formal methods rooted in Fourier transform and Kalman filtering. Thorough empirical evaluations indeed validate the accuracy and the performance of the proposed methods. We assert that such approaches are of significant value, given their highly applicable nature to the field of Internet measurements for cyber security in the era of big data.

Bou-Harb, Elias↗

Semi-Annual Report for Modular Integrated Gas High Temperature Reactor Development during Performance Period April 2022 - September 2022

Horizontal Compact High Temperature Gas Reactor (HC-HTGR) is being designed by a multidisciplinary team of nuclear, mechanical, and structural engineers under the support of a DOE-NE Advanced Reactor Demonstration Program’s Advanced Reactor Concepts-20 (ARC-20) award. The objective of this ARC-20 project is to deliver a conceptual design for the proposed HC-HTGR in 3 years and support its commercialization as a safe, low-cost HTGR. Argonne National Laboratory (Argonne) is responsible for the design and analysis of the reactor cavity cooling system (RCCS) as a safety system for passive decay heat removal of the reactor concept. Additionally, Argonne is providing analysis of the primary coolant system to ensure temperatures within the core remain below safety margins during steady-state and potential accident scenarios. This second semi-annual report summarized the progress made at Argonne on the two tasks during the second half of FY22. As a part of the RCCS design task, a scoping calculation in estimating HVAC capability for the HC-HTGR reactor building was performed. A water panel modeling study was first performed with the test case, which confirms the capability of the RELAP5-3D modeling approach to explore various design options of the HC-HTGR RCCS under consideration. Then, a reference RELAP5-3D model for the unit geometry of the preliminary design of the HC-HTGR RCCS was developed. A preliminary performance analysis was conducted to evaluate the performances of a single-phase natural circulation and panel conduction in various operating conditions. For the primary coolant system analysis task, preliminary thermal hydraulic analysis of the HC-HTGR core design was performed with a high resolution 1D fluid-3D solid coupled model using the System Analysis Module (SAM) to assess the assembly coolant channel and bypass flow mass flow rate distribution. Some preliminary work on the development of a full core reduced order model was discussed following the assembly level model to predict the core wide coolant flow distribution and to model certain operational and accidental transients.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Evaluation of control and display configurations for helicopter shipboard operations

A simulation evaluation of several approach and landing flight-control configurations and of two out-of-the-cockpit display devices (a head-up display and a helmet-mounted display) was performed for the task of landing a helicopter on a destroyer in adverse weather. The results indicated that the ship airwake turbulence was the most significant environmental variable affecting hover performance. In addition, to achieve adequate landing performance, attitude-command control compensation was required for the pilot regardless of the display used. For improved performance with reduced pilot effort, a velocity-command, position-hold control system was desired.

Paulk, C. H., Jr.↗

Artificial intelligence planning applications for space exploration and space robotics

Mission sequencing involves the plan for actuation of the experiments to be conducted aboard a spacecraft; automation is under study by NASA as a means to reduce time and manpower costs in mission planning and in robotic implementation. The development of a mission sequence is conditioned by the limited duration of advantageous spacecraft encounters with objects of study, more research requests than can be satisfied, and requested changes in objectives. Autonomous robot development is hampered by the absence of task-level programming languages, the existence of anomalies in real-world interactions, and a lack of required capabilities in current sensor technology.

Rokey, Mark↗

Automated procedure execution for space vehicle autonomous control

Increased operational autonomy and reduced operating costs have become critical design objectives in next-generation NASA and DoD space programs. The objective is to develop a semi-automated system for intelligent spacecraft operations support. The Spacecraft Operations and Anomaly Resolution System (SOARS) is presented as a standardized, model-based architecture for performing High-Level Tasking, Status Monitoring and automated Procedure Execution Control for a variety of spacecraft. The particular focus is on the Procedure Execution Control module. A hierarchical procedure network is proposed as the fundamental means for specifying and representing arbitrary operational procedures. A separate procedure interpreter controls automatic execution of the procedure, taking into account the current status of the spacecraft as maintained in an object-oriented spacecraft model.

Broten, Thomas A.↗

Effects of Mistuning on the Forced Response of Turbomachinery Rotors

The basic purpose of this research has been to develop a fundamental understanding of the effects of blade-to-blade dissimilarities, or mistuning, on the dynamics of nearly cyclic bladed-disk assemblies. This topic is of importance as mistuning has been shown to increase the forced response amplitudes of some blades significantly, and even to lead to blade failure. Furthermore, the current trend toward high performance propulsion turbomachinery designed for finite service life demands an accurate prediction of system performance and dynamics at the design stage. This objective has been achieved by carrying out the following tasks. First, the investigation of the free and forced responses of representative, yet sufficiently simple blade assembly models that capture all the important characteristics of typical turbomachinery rotors. Second, the development of computational methods that predict the effects of mistuning in a systematic and reliable way, along with the development of a systematic reduced-order modeling procedure for mistuned bladed disks. Third, the application of these findings and the tools developed to an industrial rotor, namely the first stage of turbine blades of the oxidizer turbopump in the space shuttle main rocket engine (SSME). The research supported by NASA has led to the development of a coherent theory for mistuned blade assemblies. The further implementation of these computational tools into the forced response prediction system currently under development in the Structural Dynamics Branch-FREPS-would enable the designer and the analyst to: (1) identify types of blade assemblies highly sensitive to mistuning in various frequency and other parameter ranges and (2) characterize mistuning effects on their forced response by predicting true response amplitudes and fatigue life estimates.

Pierre, Christophe↗

I/O Parallelization for the Goddard Earth Observing System Data Assimilation System (GEOS DAS)

The National Aeronautics and Space Administration (NASA) Data Assimilation Office (DAO) at the Goddard Space Flight Center (GSFC) has developed the GEOS DAS, a data assimilation system that provides production support for NASA missions and will support NASA's Earth Observing System (EOS) in the coming years. The DAO's support of the EOS project along with the requirement of producing long-term reanalysis datasets with an unvarying system levy a large I/O burden on the future system. The DAO has been involved in prototyping parallel implementations of the GEOS DAS for a number of years and is now converting the production version from shared-memory parallelism to distributed-memory parallelism using the portable Message-Passing Interface (MPI). If the MPI-based GEOS DAS is to meet these production requirements, we must make I/O from the parallel system efficient. We have designed a scheme that allows efficient I/O processing while retaining portability, reducing the need for post-processing, and producing data formats that are required by our users, both internal and external. The first phase of the GEOS DAS Parallel I/O System (GPIOS) will expand upon the common method of gathering global data to a Single PE for output. Instead of using a PE also tasked with primary computation, a number of PEs will be dedicated to I/O and its related tasks. This allows the data transformations and formatting required prior to output to take place asynchronously with respect to the GEOS DAS assimilation cycle, improving performance and generating output data sets in a format convenient for our users. I/O PEs can be added as needed to handle larger data volumes or to meet user file specifications. We will show I/O performance results from a prototype MPI GCM integrated with GPIOS. Phase two of GPIOS development will examine ways of integrating new software technologies to further improve performance and build scalability into the system. The maturing of MPI-IO implementations and other supporting libraries such as parallel HDF should provide performance gains while retaining portability.

Lucchesi, R.↗

Effects of Mistuning on the Forced Response of Turbomachinery Rotors

The basic purpose of this research has been to develop a fundamental understanding of the effects of blade-to-blade dissimilarities, or mistuning, on the dynamics of nearly cyclic bladed-disk assemblies. This topic is of importance as mistuning has been shown to increase the forced response amplitudes of some blades significantly, and even to lead to blade failure. Furthermore, the current trend toward high performance propulsion turbomachinery designed for finite service life demands an accurate prediction of system performance and dynamics at the design stage. This objective has been achieved by carrying out the following tasks. First, the investigation of the free and forced responses of representative, yet sufficiently simple blade assembly models that capture all the important characteristics of typical turbomachinery rotors. Second, the development of computational methods that predict the effects of mistuning in a systematic and reliable way, along with the development, of a systematic reduced-order modeling procedure for mistuned bladed disks. Third, the application of these findings and the tools developed to an industrial rotor, namely the first stage of turbine blades of the oxidizer turbopump in the space shuttle main rocket engine (SSME). The research supported by NASA has led to the development of a coherent theory for mistuned blade assemblies. The further implementation of these computational tools into the forced response prediction system currently under development in the Structural Dynamics Branch Forced Response Prediction System (FREPS) would enable the designer and the analyst (1) to identify types of blade assemblies highly sensitive to mistuning in various frequency and other parameter ranges and (2), to characterize mistuning effects on their forced response by predicting true response amplitudes and fatigue life estimates.

Stefko, George L.↗

Composite Bear Canister

To many national park campers and mountain climbers saving their foods in a safe and unbreakable storage container without worrying being attacked by a bear is a challenging task. In some parks, the park rangers have mandated that park visitors rent a bear canister for their food storage. Commercially available bear canisters are made of ABS plastic, weigh 2.8 pounds, and have a 180 cubic inch capacity for food storage. A new design with similar capacity was conducted in this study to reduce its weight and make it a stiffer and stronger canister. Two prototypes incorporating carbon prepreg with and without honeycomb constructions were manufactured using hand lay-up and vacuum bag forming techniques. A 6061-T6-aluminum ring was machined to dimensions in order to reinforce the opening area of the canister. Physical properties (weight and volume) along with mechanical properties (flexural strength and specific allowable moment) of the newly fabricated canisters are compared against the commercial ones. The composite canister weighs only 56% of the ABS one can withstand 9 times of the force greater. The advantages and limitations of using composite bear canisters will be discussed in the presentation.

Chung, W. Richard↗