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At least 1,747 records · Page 97
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

System Engineers and Decisions: It?s All about Knowledge

In order to guarantee that a system meets adequate levels of reliability and availability, system performances are continuously monitored and analyzed thanks to the technological advancements driving the Industry 4.0 revolution. An Industry 4.0 approach is typically based on advanced statistical, big data mining, machine learning, and internet-of-things methods designed to detect anomalies in the behavior of system, detect the most likely failure modes, and provide indications to system engineers on when maintenance activities should be performed before system performance are deemed unacceptable (which can be generated by diagnostic and prognostic methods). However, these analyses, which are designed to automatize and increase the efficacy of the system maintenance program, require large amount of data which can come in various forms: numeric, textual, images, sounds etc. Such data constitutes the historic knowledge benchmark to track system performances and support system engineer decisions. Here we claim that data is not sufficient to support this kind of analyses when applied to systems characterized by complex architectures and behaviors. Robust system engineer decisions require the ability to understand the system operational context that lies behind the observed data elements. In this respect, system models are in fact necessary to “put data in context” and capture relationships between data elements. Industry 4.0 methods require in fact contextual knowledge as a basis upon which hypotheses can be generated and assumptions tested. In our view, for complex systems, model-based system engineering (MBSE) models can afford this contextual knowledge, as they are typically used to describe systems architecture and dynamic behaviors. System knowledge is here intended as the blending of collected data and system architecture which takes the form of a “knowledge graph”. A knowledge graph is a database which consists of a large set of nodes (in our case an entity can be either a data or an MBSE element) which are linked to each other. The types of nodes and links follow a pre-defined topology, sometimes also refers as an ontology, that is designed to fit the actual decisions that needs to be performed. We show here how a knowledge graph can be defined to support system engineer maintenance decisions and how the same graph can be built based on system MBSE models and pre-processed data from numeric (through anomaly detections and diagnostic methods) and textual elements (through technical language processing TLP).

97 - MATHEMATICS AND COMPUTING↗
NASA NTRS1989

An evaluative model of system performance in manned teleoperational systems

Manned teleoperational systems are used in aerospace operations in which humans must interact with machines remotely. Manual guidance of remotely piloted vehicles, controling a wind tunnel, carrying out a scientific procedure remotely are examples of teleoperations. A four input parameter throughput (Tp) model is presented which can be used to evaluate complex, manned, teleoperations-based systems and make critical comparisons among candidate control systems. The first two parameters of this model deal with nominal (A) and off-nominal (B) predicted events while the last two focus on measured events of two types, human performance (C) and system performance (D). Digital simulations showed that the expression A(1-B)/C+D) produced the greatest homogeneity of variance and distribution symmetry. Results from a recently completed manned life science telescience experiment will be used to further validate the model. Complex, interacting teleoperational systems may be systematically evaluated using this expression much like a computer benchmark is used.

Haines, Richard F.↗
DOE OSTI2021

Attribution of Snowpack Errors to Simulated Temperature and Precipitation in E3SMv1 Over the Contiguous United States

Abstract Snow water equivalent (SWE), temperature, and precipitation biases and trends are evaluated in the atmosphere‐land simulations of the Energy Exascale Earth System Model version 1 (E3SMv1) in comparison to the Community Earth System Model version 2 (CESM2) and two other models using the ground measurement‐based University of Arizona (UA) snow product. SWE, temperature, and precipitation biases are highest in magnitude in the Western contiguous United States (CONUS). SWE errors are attributed to temperature and precipitation through multiple linear regressions of normalized errors, the coefficients of which represent the sensitivities to temperature and precipitation errors. SWE errors are more sensitive to temperature errors throughout the CONUS. Model SWE and temperature trends are generally opposite from UA product trends in the Western CONUS. SWE trend errors are also attributed to temperature and precipitation trend errors using multiple linear regressions of normalized trend errors. SWE trend errors are more sensitive to those of precipitation at higher elevations (>1,500 m) in the Western CONUS in these simulations. Thus, the sensitivity to temperature and precipitation differ for SWE errors and its trend errors. Furthermore, the SWE trend errors are more sensitive to temperature and precipitation in the atmosphere‐ocean coupled simulations in which the atmosphere‐land is coupled to an active ocean model. These results suggest that both errors in simulated temperature and precipitation contribute to SWE errors.

Meteorology & Atmospheric Sciences↗
NASA NTRS1992

Engine structures modeling software system: Computer code. User's manual

ESMOSS is a specialized software system for the construction of geometric descriptive and discrete analytical models of engine parts, components and substructures which can be transferred to finite element analysis programs such as NASTRAN. The software architecture of ESMOSS is designed in modular form with a central executive module through which the user controls and directs the development of the analytical model. Modules consist of a geometric shape generator, a library of discretization procedures, interfacing modules to join both geometric and discrete models, a deck generator to produce input for NASTRAN and a 'recipe' processor which generates geometric models from parametric definitions. ESMOSS can be executed both in interactive and batch modes. Interactive mode is considered to be the default mode and that mode will be assumed in the discussion in this document unless stated otherwise.

Source record↗
NASA NTRS1996

A Higher Harmonic Optimal Controller to Optimise Rotorcraft Aeromechanical Behaviour

Three methods to optimize rotorcraft aeromechanical behavior for those cases where the rotorcraft plant can be adequately represented by a linear model system matrix were identified and implemented in a stand-alone code. These methods determine the optimal control vector which minimizes the vibration metric subject to constraints at discrete time points, and differ from the commonly used non-optimal constraint penalty methods such as those employed by conventional controllers in that the constraints are handled as actual constraints to an optimization problem rather than as just additional terms in the performance index. The first method is to use a Non-linear Programming algorithm to solve the problem directly. The second method is to solve the full set of non-linear equations which define the necessary conditions for optimality. The third method is to solve each of the possible reduced sets of equations defining the necessary conditions for optimality when the constraints are pre-selected to be either active or inactive, and then to simply select the best solution. The effects of maneuvers and aeroelasticity on the systems matrix are modelled by using a pseudo-random pseudo-row-dependency scheme to define the systems matrix. Cases run to date indicate that the first method of solution is reliable, robust, and easiest to use, and that it was superior to the conventional controllers which were considered.

Leyland, Jane Anne↗
DOE OSTI2024

AutoCSM

A template system-of-systems modeling approach for automating the development, deployment, and integration of cooling system models (CSMs) for supercomputing facilities within the ExaDigiT framework. AutoCSM is a Python-based framework to assist in CSM developers in accelerating the creation and deployment of system-level thermal-hydraulic CSMs. The intention is for this tool specifically to help standardize digital twin workflows for ExaDigiT. However, this tool can be used independent of ExaDigiT (and even other systems besides CSMs).

Greenwood, MichaelScott [Oak Ridge National Labora↗
NASA NTRS2007

POST2 End-To-End Descent and Landing Simulation for the Autonomous Landing and Hazard Avoidance Technology Project

The Program to Optimize Simulated Trajectories II (POST2) is used as a basis for an end-to-end descent and landing trajectory simulation that is essential in determining the design and performance capability of lunar descent and landing system models and lunar environment models for the Autonomous Landing and Hazard Avoidance Technology (ALHAT) project. This POST2-based ALHAT simulation provides descent and landing simulation capability by integrating lunar environment and lander system models (including terrain, sensor, guidance, navigation, and control models), along with the data necessary to design and operate a landing system for robotic, human, and cargo lunar-landing success. This paper presents the current and planned development and model validation of the POST2-based end-to-end trajectory simulation used for the testing, performance and evaluation of ALHAT project system and models.

Fisher, Jody l.↗
DOE OSTI2026

Impact of light output on the timing resolution of organic glass scintillator bars in a dual-ended readout configuration

The effectiveness of detector system modeling and validation depends on the quality of characterization performed on the system. For nuclear nonproliferation applications, which require detectors to address complex and variable field conditions, access to accurate system models is essential. This study presents the timing characterization of organic glass scintillator bars used in an imaging system developed at the University of Michigan. 137 Cs and 60 Co gamma-ray sources were used to determine the coincidence time resolution as a function of measured light output for two Compton scatter events between two organic glass scintillator bars. Timing resolution for two events, each with light output ranging from 100 to 1100 keVee were characterized. The resulting data were fit to a parametric function that was validated to agree with experimental results within ±25 ps. Simulations were performed to establish appropriate calibration points for each organic scintillator, thereby ensuring accurate calibration of light output values during analysis. This work successfully characterized the light output dependence of the coincidence timing resolution of a pair of organic glass detectors for use in an imaging system. Depending on the amount of scintillation light output from the events, the full width at half maximum of the measured coincidence time resolution ranged from 653.2 ± 16.1 ps for low light yields, 100 keVee, to 121.0 ± 8.4 ps for higher yields at 1100 keVee. The insights obtained from the timing resolution behavior will allow for accurate simulation capabilities in future security and verification efforts using scatter-based imaging systems.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

Modeling the Joint Effects of Vegetation Characteristics and Soil Properties on Ecosystem Dynamics in a Panama Tropical Forest

Abstract In tropical forests, both vegetation characteristics and soil properties are important not only for controlling energy, water, and gas exchanges directly but also determining the competition among species, successional dynamics, forest structure and composition. However, the joint effects of the two factors have received limited attention in Earth system model development. Here we use a vegetation demographic model, the Functionally Assembled Terrestrial Ecosystem Simulator (FATES) implemented in the Energy Exascale Earth System Model (E3SM) Land Model (ELM), ELM‐FATES, to explore how plant traits and soil properties affect tropical forest growth and composition concurrently. A large ensemble of simulations with perturbed vegetation and soil hydrological parameters is conducted at the Barro Colorado Island, Panama. The simulations are compared against observed carbon, energy, and water fluxes. We find that soil hydrological parameters, particularly the scaling exponent of the soil retention curve ( B sw ), play crucial roles in controlling forest diversity, with higher B sw values (>7) favoring late successional species in competition, and lower B sw values (1 ∼ 7) promoting the coexistence of early and late successional plants. Considering the additional impact of soil properties resolves a systematic bias of FATES in simulating sensible/latent heat partitioning with repercussion on water budget and plant coexistence. A greater fraction of deeper tree roots can help maintain the dry‐season soil moisture and plant gas exchange. As soil properties are as important as vegetation parameters in predicting tropical forest dynamics, more efforts are needed to improve parameterizations of soil functions and belowground processes and their interactions with aboveground vegetation dynamics.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Digital Twin for Hydropower System Object Modeling: Alder Dam (FY2023)

Hydropower is the world's largest source of renewable electricity, and hydropower plants are distributed all over the world. Typical major components of a hydropower plant are the governor, excitation, generator, thrust bearing, hydraulic turbine, transformer, the main lead, metering and control, tailwater depression, and dissolved oxygen. For each component, various measures are taken. The measurements are acquired by various heterogeneous systems, including standalone sensors, programmable logic controllers (PLC), Supervisory control and data acquisition (SCADA), Internet of Things (IoT), and data acquisition and integration platforms such as OSI/PI. The measured data are often archived within the plant by a data management platform, and many institutions have cloud-based archive systems, such as Hydropower Research Institution (HRI), U.S. Army Corps of Engineers (USACE), and Columbia River Data Access in Real Time (DART). Object Modeling is a general framework for designing information systems. It focuses on objects, the actions they perform, and the messages they send to one another to cause those actions to be taken. The major differences among object modeling, network modeling, data modeling, and process modeling are that in the first we focus on the actions in response to information, objects which form the system, the actions they perform, and how they pass information to one another, while in the second we concentrate on where, when and how much information is moved, while in the third we focus on what information is moved and where it is moved, while in the last we focus on how it is moved and when it is moved. Object modeling was developed basically as a method to develop object-oriented systems and to support object-oriented programming. It describes the static structure of the system. The object Modeling Technique is easy to draw and use. That is why we choose object modeling to connect physical hydropower plants to Digital Twin. It recognizes the objects and the relationship between them. It identifies the attributes and functions of each class. Dynamic Modeling: It explains how objects respond to events. Functional Modeling indicates the processes executed in an object and how data changes when it moves to objects. It has been used in many applications like telecommunication, transportation, etc.

13 HYDRO ENERGY↗
NASA NTRS2011

Ontological Modeling for Integrated Spacecraft Analysis

Current spacecraft work as a cooperative group of a number of subsystems. Each of these requiresmodeling software for development, testing, and prediction. It is the goal of my team to create anoverarching software architecture called the Integrated Spacecraft Analysis (ISCA) to aid in deploying the discrete subsystems' models. Such a plan has been attempted in the past, and has failed due to the excessive scope of the project. Our goal in this version of ISCA is to use new resources to reduce the scope of the project, including using ontological models to help link the internal interfaces of subsystems' models with the ISCA architecture.I have created an ontology of functions specific to the modeling system of the navigation system of a spacecraft. The resulting ontology not only links, at an architectural level, language specificinstantiations of the modeling system's code, but also is web-viewable and can act as a documentation standard. This ontology is proof of the concept that ontological modeling can aid in the integration necessary for ISCA to work, and can act as the prototype for future ISCA ontologies.

ontological modeling↗
NASA NTRS1989

Methodology for analysis and simulation of large multidisciplinary problems

The Integrated Structural Modeling (ISM) program is being developed for the Air Force Weapons Laboratory and will be available for Air Force work. Its goal is to provide a design, analysis, and simulation tool intended primarily for directed energy weapons (DEW), kinetic energy weapons (KEW), and surveillance applications. The code is designed to run on DEC (VMS and UNIX), IRIS, Alliant, and Cray hosts. Several technical disciplines are included in ISM, namely structures, controls, optics, thermal, and dynamics. Four topics from the broad ISM goal are discussed. The first is project configuration management and includes two major areas: the software and database arrangement and the system model control. The second is interdisciplinary data transfer and refers to exchange of data between various disciplines such as structures and thermal. Third is a discussion of the integration of component models into one system model, i.e., multiple discipline model synthesis. Last is a presentation of work on a distributed processing computing environment.

Russell, William C.↗
NASA NTRS2014

MDO and Cross-Disciplinary Practice in R&D: A Portrait of Principles and Current Practice

For several decades, Multidisciplinary Design Optimization (MDO) has served an important role in aerospace engineering by incorporating physics based disciplinary models into integrated system or sub-system models for use in research, development, (R&D) and design. This paper examines MDO's role in facilitating the integration of the researchers from different single disciplines during R&D and early design of large-scale complex engineered systems (LaCES) such as aerospace systems. The findings in this paper are summarized from a larger study on interdisciplinary practices and perspectives that included considerable empirical data from surveys, interviews, and ethnography. The synthesized findings were derived by integrating the data with theories from organization science and engineering. The over-arching finding is that issues related to cognition, organization, and social interrelations mostly dominate interactions across disciplines. Engineering issues, such as the integration of hardware or physics-based models, are not as significant. Correspondingly, the data showed that MDO is not the primary integrator of researchers working across disciplines during R&D and early design of LaCES. Cognitive focus such as analysis versus design, organizational challenges such as incentives, and social opportunities such as personal networks often drove the human interactive practices among researchers from different disciplines. Facilitation of the inherent confusion, argument, and learning in crossdisciplinary research was identified as one of several needed elements of enabling successful research across disciplines.

Rivas McGowan, Anna-Maria↗
DOE OSTI2021

Climate Change Projection in the Twenty-First Century Simulated by NIMS-KMA CMIP6 Model Based on New GHGs Concentration Pathways

Abstract The National Institute of Meteorological Sciences-Korea Meteorological Administration (NIMS-KMA) has participated in the Coupled Model Inter-comparison Project (CMIP) and provided long-term simulations using the coupled climate model. The NIMS-KMA produces new future projections using the ensemble mean of KMA Advanced Community Earth system model (K-ACE) and UK Earth System Model version1 (UKESM1) simulations to provide scientific information of future climate changes. In this study, we analyze four experiments those conducted following the new shared socioeconomic pathway (SSP) based scenarios to examine projected climate change in the twenty-first century. Present day (PD) simulations show high performance skill in both climate mean and variability, which provide a reliability of the climate models and reduces the uncertainty in response to future forcing. In future projections, global temperature increases from 1.92 °C to 5.20 °C relative to the PD level (1995–2014). Global mean precipitation increases from 5.1% to 10.1% and sea ice extent decreases from 19% to 62% in the Arctic and from 18% to 54% in the Antarctic. In addition, climate changes are accelerating toward the late twenty-first century. Our CMIP6 simulations are released to the public through the Earth System Grid Federation (ESGF) international data sharing portal and are used to support the establishment of the national adaptation plan for climate change in South Korea.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1991

Space Station Freedom solar dynamic modules structural modelling and analysis

In support of the Space Station Freedom (SSF) Solar Dynamic Power Module effort, structural design studies were performed to investigate issues related to the design of the power module, its pointing capabilities, and the integration of the module into the SSF infrastructure. Of particular concern from a structural viewpoint are the dynamics of the power module, the impact of the power module on the Space Station dynamics and controls, and the required control effort for obtaining the specified Solar Dynamic Power Module pointing accuracy. Structural analyses were performed to determine the structural dynamics attributes of both the existing and the proposed structural dynamics module designs. The objectives of these analyses were to generate validated Solar Dynamic Power Module NASTRAN finite element models, combine Space Station and power module models into integrated system models, perform finite element modal analyses to assess the effect of the relocations of the power module center of mass, and provide modal data to controls designers for control systems design.

Lawrence, Charles↗
DOE OSTI2021

Physics‐based iterative reconstruction for dual‐source and flying focal spot computed tomography

Purpose For single‐source helical Computed Tomography (CT), both Filtered‐Back Projection (FBP) and statistical iterative reconstruction have been investigated. However, for dual‐source CT with flying focal spot (DS‐FFS CT), a statistical iterative reconstruction that accurately models the scanner geometry and acquisition physics remains unknown to researchers. Therefore, our purpose is to present a novel physics‐based iterative reconstruction method for DS‐FFS CT and assess its image quality. Methods Our algorithm uses precise physics models to reconstruct from the native cone‐beam geometry and interleaved dual‐source helical trajectory of a DS‐FFS CT. To do so, we construct a noise physics model to represent data acquisition noise and a prior image model to represent image noise and texture. In addition, we design forward system models to compute the locations of deflected focal spots, the dimension, and sensitivity of voxels and detector units, as well as the length of intersection between x‐rays and voxels. The forward system models further represent the coordinated movement between the dual sources by computing their x‐ray coverage gaps and overlaps at an arbitrary helical pitch. With the above models, we reconstruct images by an advanced Consensus Equilibrium (CE) numerical method to compute the maximum a posteriori estimate to a joint optimization problem that simultaneously fits all models. Results We compared our reconstruction with Siemens ADMIRE, which is the clinical standard hybrid iterative reconstruction (IR) method for DS‐FFS CT, in terms of spatial resolution, noise profile, and image artifacts through both phantoms and clinical scan datasets. Experiments show that our reconstruction has a higher spatial resolution, with a Task‐Based Modulation Transfer Function (MTF task ) consistently higher than the clinical standard hybrid IR. In addition, our reconstruction shows a reduced magnitude of image undersampling artifacts than the clinical standard. Conclusions By modeling a precise geometry and avoiding data rebinning or interpolation, our physics‐based reconstruction achieves a higher spatial resolution and fewer image artifacts with smaller magnitude than the clinical standard hybrid IR.

Wang, Xiao↗
NASA NTRS2009

AP233: An Information Model for Systems Engineering

In today's world, information is abundant. We have no problems generating it. But we are challenged to find, organize, and exchange information. center dot A standardized model of information can help. Such a model nearly completed its development for Systems Engineering. It is referred to as AP233 (AP = Application Protocol).

Siebes, Georg↗