Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Model Based System Engineering”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 883 records · Page 49
All sourcesNASA NTRSDOE OSTI
NASA NTRS2002

Liquid Engine Test Facilities Assessment

The John C. Stennis Space Center (SSC) requested The Aerospace Corporation to examine the current testing capability of all existing large liquid engine test facilities located in the United States. That information along with projected liquid rocket engine development was used to examine future liquid rocket engine testing facilities needs in the coming decade. Current domestic liquid engine test facilities capabilities, when examined against engine concepts for the coming decade, indicate there are ample facilities offering altitude simulation during test. In addition, it was observed that many contractor facilities have limited ambient test capability of larger thrust engines under current consideration. Finally, it was concluded that diminished contractor participation engine development testing will drive this activity to the government sector. Only three facilities are seen as key contributors to engine testing in the coming decade, namely John C. Stennis Space Center (SSC), Marshall Space Flight Center (MSFC), and Air Force Research Laboratory (AFRL). Past rocket engine test experience was evaluated as a possible resource for projecting future engine test needs. A database comprised of various engine models and the level of testing performed to flight qualify those systems for their first flight was constructed. For comparison purposes in this study, development and qualification efforts were totaled and treated as one test program. Based on experience with past Air Force programs, the time on the test stand accounts for typically 50% or more of the total program time. Historical data show that the time to design and develop new engines has increased over the last 40 years, most likely due to scarcer resources in today's funding environment.

Adams, Michael J.↗
DOE OSTI2025

Reduced Order Modeling conditioned on monitored features for response and error bounds estimation in engineered systems

Reduced Order Models (ROMs) form essential tools across engineering domains by virtue of their function as surrogates for computationally intensive digital twinning simulators. Although purely data-driven methods are available for ROM construction, schemes that allow to retain a portion of the physics tend to enhance the interpretability and generalization of ROMs. However, physics-based techniques can adversely scale when dealing with nonlinear systems that feature parametric dependencies. This study introduces a generative physics-based ROM that is suited for nonlinear systems with parametric dependencies and is additionally able to provide numerical error bounds associated with the respective estimates. A main contribution of this work is the conditioning of these parametric ROMs to features that can be derived from monitoring measurements, feasibly in an online fashion. This is contrary to most existing ROM schemes, which remain restricted to the prescription of the physics-based, and usually a priori unknown, system parameters. Our work utilizes conditional Variational Autoencoders to continuously map the required reduction bases to a feature vector extracted from limited output measurements, while additionally allowing for a probabilistic assessment of the ROM-estimated Quantities of Interest. An auxiliary task using a neural network-based parametrization of suitable probability distributions is introduced to re-establish the link with physical model parameters. We verify the proposed scheme on a series of simulated case studies incorporating effects of geometric and material nonlinearity under parametric dependencies related to system properties and input load characteristics.

Conditional VAEs↗
DOE OSTI2021

A simulation-based assessment of technologies to reduce heat emissions from buildings

Heat emissions from buildings are part of anthropogenic heat leading to urban overheating. This paper aims to assess how technologies (i.e., energy conservation measures - ECMs), used to decrease energy use, may also reduce heat emissions from buildings. This study employs the physics-based engine EnergyPlus to simulate the main components of heat emissions from buildings to ambient air: envelope, zone, and systems. Hourly simulations are run for IECC single- and multi-family reference models with three representative climates: Miami, Baltimore, and Chicago. The results show that the performance of ECMs varies among weather, seasons, and residential typologies. Particularly, some ECMs (i.e., cool coatings, heat pumps, additional insulation, energy-awareness occupants) show a strong decrease in heat emissions, yet they are not always correlated with proportional decreases in energy use. When all ECMs are combined, the reductions are larger on heat emissions (89%) than on site energy (65%) from the base cases. During summer in Miami, the combination of ECMs shows a decrease in heat emissions from the building surface component of 80% during daytime, 92% for the HVAC component and a counterbalanced increase in the zone component of 88%, bringing to a daily decrease in total heat emissions. The main contributions of this study are quantifying how typical ECMs influence residential building heat emissions using EnergyPlus simulations and informing urban planners and stakeholders on prioritizing measures for mitigating urban overheating problems.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Generating synthetic signaling networks for in silico modeling studies

Predictive models of signaling pathways have proven to be difficult to develop. Reasons include the uncertainty in the number of species, the complexity in species’ interactions, and the sparseness and uncertainty in experimental data. Traditional approaches to developing mechanistic models rely on collecting experimental data and fitting a single model to that data. This approach works for simple systems but has proven unreliable for complex systems such as biological signaling networks. For example, uncertainty and sparseness of the data often result in overfitted models that have little predictive value beyond recapitulating the experimental data itself. Thus, there is a need to develop new approaches to create predictive mechanistic models of complex systems. However, to determine the effectiveness of any new algorithm, a baseline model is needed to test its performance. To meet this need, we developed a method for generating artificial synthetic networks that are reasonably realistic and thus can be treated as ground truth models. These synthetic models can then be used to generate synthetic data for developing and testing algorithms designed to recover the underlying network topology and associated parameters. Here, we describe a simple approach for generating synthetic signaling networks that can be used for this purpose.

42 ENGINEERING↗
DOE OSTI2020

Novel Fault Location Method for Power Systems Based on Attention Mechanism and Double Structure GRU Neural Network

Fault location is one of the most essential techniques to maintain the stable operation of power systems. A fast and accurate fault location allows operators to restore power grids faster and avoid economic losses. Conventional methods rely on expert knowledge to extract the necessary features (e.g. DWT, DFT). For large systems, more coupling effects of transmission lines require more complex feature engineering, and incomplete features can easily introduce large errors. To overcome this, a deep learning approach without manual feature extraction is introduced to the fault location model under big data application. Towards this end, in the proposed method, the attention mechanism, the Bi-GRU and a dual structure network are applied to analyze the current data from different perspectives. Complete information for the fault features is extracted for the fault location. Based on a time series model and benefit from the ability to internally acquire the information architecture of faulty line, the established model is adaptive to the power grids with very complex topologies. Simulation results indicate that the proposed double-structure model reduces the maximum error and is less affected by noise. In comparison with different structures and different models, the proposed method shows better performance in IEEE 39-bus system.

42 ENGINEERING↗
NASA NTRS1995

Steady-state dynamic behavior of an auxiliary bearing supported rotor system

This paper investigates the steady-state responses of a rotor system supported by auxiliary bearings in which there is a clearance between the rotor and the inner race of the bearing. A simulation model based upon the rotor of a production jet engine is developed and its steady-state behavior is explored over a wide range of operating conditions for various parametric configurations. Specifically, the influence of rotor imbalance, support stiffness, and damping is studied. It is found that imbalance may change the rotor responses dramatically in terms of frequency contents at certain operating speeds. Subharmonic responses of 2nd order through 10th order are all observed except the 9th order. Chaotic phenomenon is also observed. Jump phenomena (or double-valued responses) of both hard-spring type and soft-spring type are shown to occur at low operating speeds for systems with low auxiliary bearing damping or large clearance even with relatively small imbalance. The effect of friction between the shaft and the inner race of the bearing is also discussed.

Xie, Huajun↗
NASA NTRS1997

The Design of Model-Based Training Programs

This paper proposes a model-based training program for the skills necessary to operate advance avionics systems that incorporate advanced autopilots and fight management systems. The training model is based on a formalism, the operational procedure model, that represents the mission model, the rules, and the functions of a modem avionics system. This formalism has been defined such that it can be understood and shared by pilots, the avionics software, and design engineers. Each element of the software is defined in terms of its intent (What?), the rationale (Why?), and the resulting behavior (How?). The Advanced Computer Tutoring project at Carnegie Mellon University has developed a type of model-based, computer aided instructional technology called cognitive tutors. They summarize numerous studies showing that training times to a specified level of competence can be achieved in one third the time of conventional class room instruction. We are developing a similar model-based training program for the skills necessary to operation the avionics. The model underlying the instructional program and that simulates the effects of pilots entries and the behavior of the avionics is based on the operational procedure model. Pilots are given a series of vertical flightpath management problems. Entries that result in violations, such as failure to make a crossing restriction or violating the speed limits, result in error messages with instruction. At any time, the flightcrew can request suggestions on the appropriate set of actions. A similar and successful training program for basic skills for the FMS on the Boeing 737-300 was developed and evaluated. The results strongly support the claim that the training methodology can be adapted to the cockpit.

Polson, Peter↗
DOE OSTI2018

NSLS-II: Turn-by-Turn BPM Data Analysis – A Use Case Approach

A modern ring-based light source is a complex dynamic system for which the design is guided by a realistic computer model with predictable results. State-of-the-arts beam requirements translate into tight engineering tolerances. So, quality assurance for the equipment, e.g. ring magnets, girder system, power supplies, RF system, etc. is crucial to deliver on the design goals for the beam quality. For a streamlined commissioning and an effective approach for integration of insertion devices, the latter being an activity that is typically on-going for the entire life cycle of the facility, it is equally important to be able to calibrate the beam dynamics design model against the real system and pursue e.g. “gap analysis”, linear and nonlinear optics corrections, improvements to the baseline design, etc. In particular, for high-end insertion devices. Conceptually, it can be thought of as pursuing Model-Based and Adaptive Control; instead of “flying blind”. A straightforward approach is to use a pinger, a ~30 cm long hor/ver kicker that can kick the beam to about 1 mrad in each plane [1-2] and a Turn-by-Turn BPM data acquisition system that records the betatron motion on a Turn-by-Turn basis. Examples include: ALS, SLS, DIAMOND, and SOLEIL. We first outline how to measure the Beam Impulse Response (BIR) function and related Beam Transfer Function (BTF) with a Turn-by-Turn BPM data acquisition system and a pinger. In particular, how to obtain the amplitude and phase of the spectral components in the betatron spectrum with high precision by using signal processing. We also quantify how the impact of noise affects the accuracy of the measurements.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1987

Reliability modeling of fault-tolerant computer based systems

Digital fault-tolerant computer-based systems have become commonplace in military and commercial avionics. These systems hold the promise of increased availability, reliability, and maintainability over conventional analog-based systems through the application of replicated digital computers arranged in fault-tolerant configurations. Three tightly coupled factors of paramount importance, ultimately determining the viability of these systems, are reliability, safety, and profitability. Reliability, the major driver affects virtually every aspect of design, packaging, and field operations, and eventually produces profit for commercial applications or increased national security. However, the utilization of digital computer systems makes the task of producing credible reliability assessment a formidable one for the reliability engineer. The root of the problem lies in the digital computer's unique adaptability to changing requirements, computational power, and ability to test itself efficiently. Addressed here are the nuances of modeling the reliability of systems with large state sizes, in the Markov sense, which result from systems based on replicated redundant hardware and to discuss the modeling of factors which can reduce reliability without concomitant depletion of hardware. Advanced fault-handling models are described and methods of acquiring and measuring parameters for these models are delineated.

Bavuso, Salvatore J.↗
NASA NTRS1989

Vibration analysis of rotor systems using reduced subsystem models

A general impedance method using reduced submodels has been developed for the linear dynamic analysis of rotor systems. Formulated in terms of either modal or physical coordinates of the subsystems, the method enables imbalance responses at specific locations of the rotor systems to be efficiently determined from a small number of 'master' degrees of freedom. To demonstrate the capability of this impedance approach, the Space Shuttle Main Engine high-pressure oxygen turbopump has been investigated to determine the bearing loads due to imbalance. Based on the same formulation, an eigenvalue analysis has been performed to study the system stability. A small 5-DOF model has been utilized to illustrate the application of the method to eigenvalue analysis. Because of its inherent characteristics of allowing formulation of reduced submodels, the impedance method can significantly increase the computational speed.

Fan, Uei-Jiun↗
NASA NTRS2002

The Use of Probabilistic Methods to Evaluate the Systems Impact of Component Design Improvements on Large Turbofan Engines

Probabilistic Structural Analysis (PSA) is now commonly used for predicting the distribution of time/cycles to failure of turbine blades and other engine components. These distributions are typically based on fatigue/fracture and creep failure modes of these components. Additionally, reliability analysis is used for taking test data related to particular failure modes and calculating failure rate distributions of electronic and electromechanical components. How can these individual failure time distributions of structural, electronic and electromechanical component failure modes be effectively combined into a top level model for overall system evaluation of component upgrades, changes in maintenance intervals, or line replaceable unit (LRU) redesign? This paper shows an example of how various probabilistic failure predictions for turbine engine components can be evaluated and combined to show their effect on overall engine performance. A generic model of a turbofan engine was modeled using various Probabilistic Risk Assessment (PRA) tools (Quantitative Risk Assessment Software (QRAS) etc.). Hypothetical PSA results for a number of structural components along with mitigation factors that would restrict the failure mode from propagating to a Loss of Mission (LOM) failure were used in the models. The output of this program includes an overall failure distribution for LOM of the system. The rank and contribution to the overall Mission Success (MS) is also given for each failure mode and each subsystem. This application methodology demonstrates the effectiveness of PRA for assessing the performance of large turbine engines. Additionally, the effects of system changes and upgrades, the application of different maintenance intervals, inclusion of new sensor detection of faults and other upgrades were evaluated in determining overall turbine engine reliability.

Packard, Michael H.↗
NASA NTRS1993

Model-based reasoning for power system management using KATE and the SSM/PMAD

The overall goal of this research effort has been the development of a software system which automates tasks related to monitoring and controlling electrical power distribution in spacecraft electrical power systems. The resulting software system is called the Intelligent Power Controller (IPC). The specific tasks performed by the IPC include continuous monitoring of the flow of power from a source to a set of loads, fast detection of anomalous behavior indicating a fault to one of the components of the distribution systems, generation of diagnosis (explanation) of anomalous behavior, isolation of faulty object from remainder of system, and maintenance of flow of power to critical loads and systems (e.g. life-support) despite fault conditions being present (recovery). The IPC system has evolved out of KATE (Knowledge-based Autonomous Test Engineer), developed at NASA-KSC. KATE consists of a set of software tools for developing and applying structure and behavior models to monitoring, diagnostic, and control applications.

Morris, Robert A.↗
NASA NTRS2012

Antenna Calibration and Measurement Equipment

A document describes the Antenna Calibration & Measurement Equipment (ACME) system that will provide the Deep Space Network (DSN) with instrumentation enabling a trained RF engineer at each complex to perform antenna calibration measurements and to generate antenna calibration data. This data includes continuous-scan auto-bore-based data acquisition with all-sky data gathering in support of 4th order pointing model generation requirements. Other data includes antenna subreflector focus, system noise temperature and tipping curves, antenna efficiency, reports system linearity, and instrument calibration. The ACME system design is based on the on-the-fly (OTF) mapping technique and architecture. ACME has contributed to the improved RF performance of the DSN by approximately a factor of two. It improved the pointing performances of the DSN antennas and productivity of its personnel and calibration engineers.

Rochblatt, David J.↗
NASA NTRS2021

Modernizing NASA’s Space Flight Safety and Mission Success (S&MS) Assurance Framework In Line With Evolving Acquisition Strategies and Systems Engineering Practices

This paper presents the objectives-driven, case-based safety and mission success (S&MS) assurance framework being developed by the NASA Office of Safety and Mission Assurance (OSMA), including its motivations and its implementation via a S&MS Assurance Standard that is under development, supplemented by supporting standards including an S&MS Analysis Management Standard that is also under development. A need to evolve NASA’s S&MS assurance framework has emerged in recent years, resulting from the need to accommodate new acquisition models; the need to accommodate evolving systems engineering (SE) practices; the need to stipulate acceptable levels of S&MS risk; the need for improved integration of S&MS into SE; and the need for clearer risk acceptance accountability. The objectives-driven, case-based S&MS assurance framework proposed here is responsive to that need. Its key features include: • The establishment, by NASA Acquirers, of fundamental S&MS performance objectives that define limits of acceptability for the likelihoods that mission technical objectives will be accomplished and that people, assets, and environments put at risk by the mission will not be adversely affected; • The development and approval of Providers’ S&MS plans for meeting Acquirers’ S&MS performance objectives, including commitments to support Acquirer audit, investigation, and reporting needs; • The development, by Providers, of S&MS assurance cases that argue, supported by evidence, that the Provider has met, or is on track to meeting, the fundamental S&MS objectives; • The evaluation, throughout the program/project life cycle, of Provider S&MS assurance cases as the primary S&MS-related technical basis for Acquirer risk acceptance and the granting to the Provider of authority to proceed through the program/project life cycle. This proposed S&MS assurance framework is notable for its lack of prescription of traditional S&MS requirements and strategies such as defined failure tolerances, margins, or analysis requirements. Instead, Providers are given latitude to propose their own strategies for meeting the fundamental S&MS performance objectives, subject to independent review and Acquirer approval. The result is a framework for S&MS assurance that is at once both rigorous and flexible.

Assurance Case↗
NASA NTRS2002

Radio Wave Propagation Handbook for Communication on and Around Mars

This handbook examines the effects of the Martian environment on radio wave propagation on Mars and in the space near the planet. The environmental effects include these from the Martian atmosphere, ionosphere, global dust storms, aerosols, clouds, and geomorphologic features. Relevant Martian environmental parameters were extracted from the measurements of Mars missions during the past 30 years, especially from Mars Pathfinder and Mars Global Surveyor. The results derived from measurements and analyses have been reviewed through an extensive literature search. The updated parameters have been theoretically analyzed to study their effects on radio propagation. This handbook also provides basic information about the entire telecommunications environment on and around Mars for propagation researchers, system engineers, and link analysts. Based on these original analyses, some important recommendations have been made, including the use of the Martian ionosphere as a reflector for Mars global or trans-horizon communication between future Martian colonies, reducing dust storm scattering effects, etc. These results have extended our wave propagation knowledge to a planet other than Earth; and the tables, models, and graphics included in this handbook will benefit telecommunication system engineers and scientific researchers.

Ho, Christian↗
DOE OSTI2022

Development of Integrated Thermal Fluids Modeling Capability for MSRs

The DOE Nuclear Energy Advanced Modeling and Simulation (NEAMS) program supports a full range of computational thermal fluids analysis capabilities and code developments for a broad class of light-water and advanced reactor concepts. The research and development approach under thermal fluids technical area synergistically combines three length and time scales in a hierarchal multi-scale approach. To demonstrate the feasibility and capabilities of a multi-scale thermal fluids capability using these codes, a key joint effort has been pursued to develop an integrated system-and engineering-scale thermal fluids analysis capability with the MOOSE-based codes, through integration of SAM and Pronghorn, both based on the MOOSE framework. This report summarizes the progress in developing an integrated system- and engineering-scale thermal fluids analysis capability based on SAM and Pronghorn for molten salt reactors (MSRs), which gained significant interest in recently years. Two coupling approaches were studied, i.e. separate domain or domain-segregated coupling approach and the domain-overlapping approach. A series of coupled multi-physics models have been developed for a common reference molten salt fast reactor (MSFR) concept, ranging from standalone SAM system model to integrated SAM-Pronghorn-Griffin models. Both the steady state and the transient simulations are performed to the state-of-the-art simulation capabilities of NEAMS software suite in MSFR system applications. This report also covers further development and testing of the gas transport model in SAM for MSR modeling support. The presence of noncondensable gas in MSR systems would have strong impacts on fission gas removal and transport of noble metals throughout the system. Fission products removed through the off-gas system can also impact reactivity and can act as an additional point of heat removal. To ensure that the gas transport model is adequately tested, the supported modeling capabilities and features of SAM were identified, and a suite of tests were developed to test the model for each identified feature. Validation and UQ testing were also performed for the model and demonstrated that the buoyancy term, which was originally developed using non-salt/helium gas experimental data, can capture the experimental gas bubble velocity and diameter to within experimental and code uncertainty. An existing MSRE model was also modified in this work to include the gas transport model and to demonstrate the gas model behavior for realistic conditions of interest.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

Reinforcement learning for adaptive maintenance policy optimization under imperfect knowledge of the system degradation model and partial observability of system states

Maintenance policy optimization usually is faced with challenges that arise from an imperfect knowledge of system degradation models and from the partial observability of system degradation states. Here, this paper proposes a reinforcement learning method to address these two challenges for a class of maintenance problems with Markov degradation processes. The reinforcement learning approach consists of a learning component and a planning component. Using sequentially collected observations, at each step of decision-making the learning component improves the knowledge of system degradation in terms of the probability distributions of the transition rates based on sequential Bayesian inference. Using the updated transition rates, at each step of decision-making the maintenance policy optimization problem is then formulated as a partially observable Markov decision problem, and the planning component computes the optimal maintenance policy that maximizes the expected cumulative reward. The proposed method is illustrated using a numerical example with repair and inspection maintenance actions. The result shows that as more observations are collected, the learning component progressively learns the true system degradation process, and the planning component adjusts the optimal maintenance policy accordingly as well, which leads to increased reward.

42 ENGINEERING↗
DOE OSTI2026

Finite-element-based simulations of electrodes for CO 2 cascade reduction reactions

The multielectron reduction of CO 2 to liquid fuels could be a path to scalable energy storage, but reaching this goal requires major advances in catalysis and systems engineering. Cascade catalysis, which couples sequential reactions without isolating intermediates, has emerged as a promising route to enhance selectivity and efficiency in CO 2 reduction (CO 2 R). In this review, we examine how finite-element-based simulations of continuum model [finite element method (FEM)] approaches are being used to analyze and guide CO 2 R cascade systems. We first outline the fundamentals of cascade catalysis and recent advances in catalytic materials (metallic, molecular, and hybrid architectures). We then focus on FEM developments at the electrode and device scales, emphasizing how these models capture transport phenomena, local microenvironments, and geometry-dependent effects. To clarify design principles, we present case studies of cascade electrodes organized in systems without and with integrated semiconductors. We further emphasize the integration of FEM with multiscale frameworks (density functional theory, molecular dynamics, kinetic Monte Carlo) and its role in bridging atomic-level insights with device-level performance. Finally, we identify current limitations and future prospects, including improved boundary conditions, coupling with operando experiments, and machine learning-accelerated model development. Together, these insights provide design principles for next-generation CO 2 R cascade systems for efficient solar fuel production.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗