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 1,243 records · Page 69
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Embracing the Fourth Industrial Revolution - Challenges, Opportunities and Path Forward for Propulsion

The aerospace industry is at a point where components are reaching design maturity and performance improvements are incremental. Aggressive goals to achieve sustainability and the threat of climate change necessitate a new paradigm. An artificial intelligence (AI) approach that enables revolutionary changes in system architecture, mission analysis and performance metrics is needed. The growing interest and development in the field of machine learning presents an opportunity to speed up by 10X or more the discovery, analysis and development of aerospace systems using artificial intelligence. Through IDEAS (Intelligent Design and Engineering of Aerospace Systems) we are embarking on a research and development effort that addresses this opportunity. The objective of IDEAS is to enable design of systems based on requirements. We discuss possible approaches to generating data, training models and applying them to near term applications. Results of recent workshops with industry, academia and other agencies to identify challenges to adopting AI and machine learning are presented.

Machine learning↗
NASA NTRSDate not supplied

Pre-Flight Hazardous Gas Assessment Methodology for the Space Launch System

The complexity of the Artemis I liquid rocket propulsion systems produces many sources of hazards during the operation of the vehicle. Pre-flight hazardous gas leakages pose fire and explosion risks to rocket that could potentially lead to loss of the vehicle, mission, and crew. The National Aeronautics and Space Administration (NASA) uses a probability risk assessment strategy to assess the likelihood of the hazard and the consequence should the hazardous situation occur. For high probability hazards that pose a potentially catastrophic consequence to the vehicle, the most effective strategy for reducing the risk is accomplished by engineering and implementing systems that actively mitigate the hazard. A hazards analysis is completed to determine the likelihood and severity of each hazard. These hazard analyses are informed using relevant empirical data and physics-based analytical models. Time-accurate Computational Fluid Dynamics models used to quantify and understand the risks posed to Artemis I due to expulsions of hazardous gas near the vehicle. Several sources of hazardous gas that posed a risk to Artemis I during nominal pre-flight operations are analyzed in this work. The results of the analyses were used to develop flight rationale and make risk acceptance decisions for the Artemis I launch.

Brian R. Richardson↗
NASA NTRSDate not supplied

Pre-Flight Hazardous Gas Assessment Methodology for the Space Launch System

The complexity of the Artemis I liquid rocket propulsion systems produces many sources of hazards during the operation of the vehicle. Pre-flight hazardous gas leakages pose fire and explosion risks to rocket that could potentially lead to loss of the vehicle, mission, and crew. The National Aeronautics and Space Administration (NASA) uses a probability risk assessment strategy to assess the likelihood of the hazard and the consequence should the hazardous situation occur. For high probability hazards that pose a potentially catastrophic consequence to the vehicle, the most effective strategy for reducing the risk is accomplished by engineering and implementing systems that actively mitigate the hazard. A hazards analysis is completed to determine the likelihood and severity of each hazard. These hazard analyses are informed using relevant empirical data and physics-based analytical models. Time-accurate Computational Fluid Dynamics models used to quantify and understand the risks posed to Artemis I due to expulsions of hazardous gas near the vehicle. Several sources of hazardous gas that posed a risk to Artemis I during nominal pre-flight operations are analyzed in this work. The results of the analyses were used to develop flight rationale and make risk acceptance decisions for the Artemis I launch.

Brian R. Richardson↗
DOE OSTI2020

Long Reach Robotic Arm

The Accelerator Division at Fermilab began a robotics program, known as the AD Robotics Initiative. A multi-axis robotic arm was proposed to be included in the program. This summer internship, our team began the planning and design for this project, called the Long Reach Robotic Arm. The problem is that critical systems around the magnets require analysis when water leaks cause them to fail. However, the tightly compacted parts and the quadrupole magnet, weighing approximately 1,000 pounds, cause access viewing problems. The process of having to dismantle and remove the magnet is time-consuming; it is not an efficient solution. The goal for the Long Reach Robotic Arm was to extend and reach behind the component of the Main Injector while "snaking" around and avoiding obstructions. At the start of the project, my teammate, Amanda Hoeksema, and I coded a program in the C language that will determine the number of links and their respective lengths for the robot arm. After, we began the 3D CAD model of the robot arm, base, and counterweight system. The design of the Long Reach Robotic Arm provided a learning experience in learning how to code in the C programming language, using SDL libraries and understanding mechanical engineering.

43 PARTICLE ACCELERATORS↗
NASA NTRS1994

Towards an integral computer environment supporting system operations analysis and conceptual design

VITROCISET has in house developed a prototype tool named System Dynamic Analysis Environment (SDAE) to support system engineering activities in the initial definition phase of a complex space system. The SDAE goal is to provide powerful means for the definition, analysis, and trade-off of operations and design concepts for the space and ground elements involved in a mission. For this purpose SDAE implements a dedicated modeling methodology based on the integration of different modern (static and dynamic) analysis and simulation techniques. The resulting 'system model' is capable of representing all the operational, functional, and behavioral aspects of the system elements which are part of a mission. The execution of customized model simulations enables: the validation of selected concepts with respect to mission requirements; the in-depth investigation of mission specific operational and/or architectural aspects; and the early assessment of performances required by the system elements to cope with mission constraints and objectives. Due to its characteristics, SDAE is particularly tailored for nonconventional or highly complex systems, which require a great analysis effort in their early definition stages. SDAE runs under PC-Windows and is currently used by VITROCISET system engineering group. This paper describes the SDAE main features, showing some tool output examples.

Barro, E.↗
DOE OSTI2024

Process systems engineering enables efficient and sustainable membrane-based critical material separations

This presentation summarizes work completed over the past year for PrOMMiS Task 2.1. The first half of the preseation motivates the need to develop sustainable critical mineral separation technology, and how PSE is particularly well-suited to tackle this problem. The second half of the presentation presents preliminary results for the custom cost model for diafiltration (2.1) using the superstructure flowsheet developed by Carnegie Mellon University. The presentation serves to emphasize the multi-disciplinary and collaborate nature of developing a circular economy of critical minerals and materials.

Dougher, Molly↗
NASA NTRS2016

Preliminary Results From a Heavily Instrumented Engine Ice Crystal Icing Test in a Ground Based Altitude Test Facility

Preliminary results from the heavily instrumented ALF502R-5 engine test conducted in the NASA Glenn Research Center Propulsion Systems Laboratory are discussed. The effects of ice crystal icing on a full scale engine is examined and documented. This same model engine, serial number LF01, was used during the inaugural icing test in the Propulsion Systems Laboratory facility. The uncommanded reduction of thrust (rollback) events experienced by this engine in flight were simulated in the facility. Limited instrumentation was used to detect icing on the LF01 engine. Metal temperatures on the exit guide vanes and outer shroud and the load measurement were the only indicators of ice formation. The current study features a similar engine, serial number LF11, which is instrumented to characterize the cloud entering the engine, detect/characterize ice accretion, and visualize the ice accretion in the region of interest. Data were acquired at key LF01 test points and additional points that explored: icing threshold regions, low altitude, high altitude, spinner heat effects, and the influence of varying the facility and engine parameters. For each condition of interest, data were obtained from some selected variations of ice particle median volumetric diameter, total water content, fan speed, and ambient temperature. For several cases the NASA in-house engine icing risk assessment code was used to find conditions that would lead to a rollback event. This study further helped NASA develop necessary icing diagnostic instrumentation, expand the capabilities of the Propulsion Systems Laboratory, and generate a dataset that will be used to develop and validate in-house icing prediction and risk mitigation computational tools. The ice accretion on the outer shroud region was acquired by internal video cameras. The heavily instrumented engine showed good repeatability of icing responses when compared to the key LF01 test points and during day-to-day operation. Other noticeable observations are presented.

Enigine Icing↗
NASA NTRS2016

Preliminary Results From a Heavily Instrumented Engine Ice Crystal Icing Test in a Ground Based Altitude Test Facility

Preliminary results from the heavily instrumented ALF502R-5 engine test conducted in the NASA Glenn Research Center Propulsion Systems Laboratory are discussed. The effects of ice crystal icing on a full scale engine is examined and documented. This same model engine, serial number LF01, was used during the inaugural icing test in the Propulsion Systems Laboratory facility. The uncommanded reduction of thrust (rollback) events experienced by this engine in flight were simulated in the facility. Limited instrumentation was used to detect icing on the LF01 engine. Metal temperatures on the exit guide vanes and outer shroud and the load measurement were the only indicators of ice formation. The current study features a similar engine, serial number LF11, which is instrumented to characterize the cloud entering the engine, detect/ characterize ice accretion, and visualize the ice accretion in the region of interest. Data were acquired at key LF01 test points and additional points that explored: icing threshold regions, low altitude, high altitude, spinner heat effects, and the influence of varying the facility and engine parameters. For each condition of interest, data were obtained from some selected variations of ice particle median volumetric diameter, total water content, fan speed, and ambient temperature. For several cases the NASA in-house engine icing risk assessment code was used to find conditions that would lead to a rollback event. This study further helped NASA develop necessary icing diagnostic instrumentation, expand the capabilities of the Propulsion Systems Laboratory, and generate a dataset that will be used to develop and validate in-house icing prediction and risk mitigation computational tools. The ice accretion on the outer shroud region was acquired by internal video cameras. The heavily instrumented engine showed good repeatability of icing responses when compared to the key LF01 test points and during day-to-day operation. Other noticeable observations are presented.

turbomachinery↗
NASA NTRS2016

Preliminary Results From a Heavily Instrumented Engine Ice Crystal Icing Test in a Ground Based Altitude Test Facility

Preliminary results from the Heavily Instrumented ALF503R-5 Engine test conducted in the NASA Glenn Research Center Propulsion Systems Laboratory will be discussed. The effects of ice crystal icing on a full scale engine is examined and documented. This model engine, serial number LF01, was used during the inaugural icing test in the PSL facility. The reduction of thrust (rollback) events experienced by this engine in flight were replicated in the facility. Limited instrumentation was used to detect icing. Metal temperature on the exit guide vanes and outer shroud and the load measurement were the only indicators of ice formation. The current study features a similar engine, serial number LF11, which is instrumented to characterize the cloud entering the engine, detect characterize ice accretion, and visualize the ice accretion in the region of interest.

enigine icing↗
NASA NTRS1988

Hierarchical representation and machine learning from faulty jet engine behavioral examples to detect real time abnormal conditions

The theoretical basis and operation of LEBEX, a machine-learning system for jet-engine performance monitoring, are described. The behavior of the engine is modeled in terms of four parameters (the rotational speeds of the high- and low-speed sections and the exhaust and combustion temperatures), and parameter variations indicating malfunction are transformed into structural representations involving instances and events. LEBEX extracts descriptors from a set of training data on normal and faulty engines, represents them hierarchically in a knowledge base, and uses them to diagnose and predict faults on a real-time basis. Diagrams of the system architecture and printouts of typical results are shown.

Gupta, U. K.↗
DOE OSTI2023

Predicting partner fitness based on spatial structuring in a light-driven microbial community

Microbial communities have vital roles in systems essential to human health and agriculture, such as gut and soil microbiomes, and there is growing interest in engineering designer consortia for applications in biotechnology ( e . g ., personalized probiotics, bioproduction of high-value products, biosensing). The capacity to monitor and model metabolite exchange in dynamic microbial consortia can provide foundational information important to understand the community level behaviors that emerge, a requirement for building novel consortia. Where experimental approaches for monitoring metabolic exchange are technologically challenging, computational tools can enable greater access to the fate of both chemicals and microbes within a consortium. In this study, we developed an in-silico model of a synthetic microbial consortia of sucrose-secreting Synechococcus elongatus PCC 7942 and Escherichia coli W. Our model was built on the NUFEB framework for Individual-based Modeling (IbM) and optimized for biological accuracy using experimental data. We showed that the relative level of sucrose secretion regulates not only the steady-state support for heterotrophic biomass, but also the temporal dynamics of consortia growth. In order to determine the importance of spatial organization within the consortium, we fit a regression model to spatial data and used it to accurately predict colony fitness. We found that some of the critical parameters for fitness prediction were inter-colony distance, initial biomass, induction level, and distance from the center of the simulation volume. We anticipate that the synergy between experimental and computational approaches will improve our ability to design consortia with novel function.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2014

A Monte Carlo Approach to Modeling the Breakup of the Space Launch System EM-1 Core Stage with an Integrated Blast and Fragment Catalogue

The Liquid Propellant Fragment Overpressure Acceleration Model (L-FOAM) is a tool developed by Bangham Engineering Incorporated (BEi) that produces a representative debris cloud from an exploding liquid-propellant launch vehicle. Here it is applied to the Core Stage (CS) of the National Aeronautics and Space Administration (NASA) Space Launch System (SLS launch vehicle). A combination of Probability Density Functions (PDF) based on empirical data from rocket accidents and applicable tests, as well as SLS specific geometry are combined in a MATLAB script to create unique fragment catalogues each time L-FOAM is run-tailored for a Monte Carlo approach for risk analysis. By accelerating the debris catalogue with the BEi blast model for liquid hydrogen / liquid oxygen explosions, the result is a fully integrated code that models the destruction of the CS at a given point in its trajectory and generates hundreds of individual fragment catalogues with initial imparted velocities. The BEi blast model provides the blast size (radius) and strength (overpressure) as probabilities based on empirical data and anchored with analytical work. The coupling of the L-FOAM catalogue with the BEi blast model is validated with a simulation of the Project PYRO S-IV destruct test. When running a Monte Carlo simulation, L-FOAM can accelerate all catalogues with the same blast (mean blast, 2 σ blast, etc.), or vary the blast size and strength based on their respective probabilities. L-FOAM then propagates these fragments until impact with the earth. Results from L-FOAM include a description of each fragment (dimensions, weight, ballistic coefficient, type and initial location on the rocket), imparted velocity from the blast, and impact data depending on user desired application. LFOAM application is for both near-field (fragment impact to escaping crew capsule) and far-field (fragment ground impact footprint) safety considerations. The user is thus able to use statistics from a Monte Carlo set of L-FOAM catalogues to quantify risk for a multitude of potential CS destruct scenarios. Examples include the effect of warning time on the survivability of an escaping crew capsule or the maximum fragment velocities generated by the ignition of leaking propellants in internal cavities.

Richardson, Erin↗
DOE OSTI2022

Radiation Belt Remediation: A Complex Engineered System (RBR-ACES) (Institutional Computing Report)

We have performed the simulation campaigns in support of LDRD-DR project Radiation Belt Remediation: A Complex Engineered System (RBR-ACES). This project involves modeling wave generation and wave propagation in plasma environment and studying the effect of waves on the distribution of high energy electrons with the focus on electrons appeared after a high-altitude nuclear explosion (HANE). One of the major goal of this research is strong validation of the numerical models with laboratory experiments and space-based experiments and observations.

42 ENGINEERING↗
NASA NTRSDate not supplied

Jet Noise Flyover and Scale Model Tests

Renewed interest in commercial supersonic flight has rekindled the need for accurate jet-noise predictions as this source is believed to dominate at aircraft takeoff conditions. The current study compares scale-model data acquired in the NASA Aero-Acoustic Propulsion Laboratory with data obtained using a well-instrumented Learjet 25 in a flyover test completed in September 2022. The flight test included 73 flyovers with engine conditions ranging from 1.5 to 2.0 engine pressure ratios and flight Mach numbers between 0.24 and 0.27. Acoustic data were acquired with an 800-ft linear ground plate microphone array. Wind speed data were acquired up to 1000-ft altitude with a ground-based LiDAR system. Layered ambient temperature, pressure, and humidity were acquired with a weather drone. A 6% increase in the physical scale factor for the scale-model data was found to reasonably align the peak frequencies of the scale-model and flight data and resulted in peak levels for the scale model being roughly 0.7 dB above those for the flight data at NPR = 1.56 and roughly 1 dB below those for the flight data at NPR = 1.91 in the peak jet-noise direction. Comparisons with the SAE ARP876 model were poor especially at emission angles greater than, or equal to, 110° and at high frequencies.

jet noise, supersonic transport↗
NASA NTRSDate not supplied

Jet Noise Flyover and Scale Model Tests

Renewed interest in commercial supersonic flight has rekindled the need for accurate jet-noise predictions as this source is believed to dominate at aircraft takeoff conditions. The current study compares scale-model data acquired in the NASA Aero-Acoustic Propulsion Laboratory with data obtained using a well-instrumented Learjet 25D in a flyover test completed in September 2022. The flight test included 73 flyovers with engine conditions ranging from 1.5 to 2.0 engine pressure ratios and flight Mach numbers between 0.24 and 0.27. Acoustic data were acquired with an 800-ft linear ground plate microphone array. Wind speed data were acquired up to 1000-sft altitude with a ground-based LiDAR system. Layered ambient temperature, pressure, and humidity were acquired with a weather drone. A 6% increase in the physical scale factor for the scale-model data was found to reasonably align the peak frequencies of the scale-model and flight data and resulted in peak levels for the scale model being roughly 0.7 dB above those for the flight data at NPR = 1.56 and roughly 1 dB below those for the flight data at NPR = 1.91 in the peak jet-noise direction. Comparisons with the SAE ARP876 model were poor especially at emission angles greater than, or equal to, 110° and at high frequencies.

Acoustics, jet noise, supersonic transport↗
NASA NTRSDate not supplied

Jet Noise Flyover and Scale Model Tests

Renewed interest in commercial supersonic flight has rekindled the need for accurate jet-noise predictions as this source is believed to dominate at aircraft takeoff conditions. The current study compares scale-model data acquired in the NASA Aero-Acoustic Propulsion Laboratory with data obtained using a well-instrumented Learjet 25 in a flyover test completed in September 2022. The flight test included 73 flyovers with engine conditions ranging from 1.5 to 2.0 engine pressure ratios and flight Mach numbers between 0.24 and 0.27. Acoustic data were acquired with an 800-ft linear ground plate microphone array. Wind speed data were acquired up to 1000-ft altitude with a ground-based LiDAR system. Layered ambient temperature, pressure, and humidity were acquired with a weather drone. A 6% increase in the physical scale factor for the scale-model data was found to reasonably align the peak frequencies of the scale-model and flight data and resulted in peak levels for the scale model being roughly 0.7 dB above those for the flight data at NPR = 1.56 and roughly 1 dB below those for the flight data at NPR = 1.91 in the peak jet-noise direction. Comparisons with the SAE ARP876 model were poor especially at emission angles greater than, or equal to, 110° and at high frequencies.

Acoustics, jet noise, supersonic transport↗
DOE OSTI2020

Update to the Performance Assessment for the Savannah River Site Saltstone Disposal Facility - 20124

In 2019, Savannah River Remediation developed a revision to the performance assessment (PA) on behalf of the U.S. Department of Energy (DOE) Savannah River Operations Office (SR) for the near-surface disposal of low-level waste at the Savannah River Site (SRS) Saltstone Disposal Facility (SDF). Soluble waste from SRS Tank Farms undergoes salt processing to remove cesium and other high activity constituents. The low-activity decontaminated salt solution (DSS) is then immobilized by mixing it into a cementitious waste form known as saltstone. After mixing, the saltstone is poured into leak-tight concrete vaults, known as saltstone disposal units (SDUs), where the waste form cures. By the time of facility closure, the SDF is expected to consist of 15 SDUs with a combined capacity of 1.06 E+09 L (280 Mgal) of cured saltstone. The facility operates under a Disposal Authorization Statement (DAS) from DOE and a permit from the South Carolina Department of Health and Environmental Control (SCDHEC). Since the start of operations in 1990, the SDF has received almost 6.7 E+07 L (18 Mgal) of DSS, resulting in the safe disposal of 2.7 E+16 Bq (7.3 E+05 Ci) of activity. Due to the radioactive decay of short-lived contaminants, the total remaining activity in the disposed waste is estimated to be approximately 1.4 E+16 Bq (3.9 E+05 Ci), as of September 2018. The Disposal Authorization Statement requires a demonstration that the system of engineered and natural features of the disposal facility will limit releases from the facility and be protective of human health and the environment for at least the next 1,000 years. The long-term performance of the facility was evaluated under the requirements of the DoE's Radioactive Waste Management Manual (US DOE Manual 435.1-1). Simulations were performed to demonstrate that the disposal facility would meet performance objectives specified in the manual. The evaluation was based on numerical models that simulate the releases of contaminants from the saltstone waste form. Contaminants were transported through groundwater and air pathways to points of assessment to evaluate compliance. In addition, the potential consequences of an inadvertent human intrusion (IHI) were also evaluated. In accordance with the guidance and recommendations in US DoE's technical standard for DAS, deterministic and probabilistic analyses were performed to demonstrate the SDF system, which includes the engineered cover system, the SDUs, the waste form, and the natural features of the site, provides a reasonable expectation that saltstone disposal will meet performance objectives. Post-closure doses to future members of the public (MOP) were evaluated; dose estimates from the air pathway were well below the 1.0 E-04 Sv/yr (10 mrem/yr) performance objective within 1,000 years, and the calculated doses to the MOP from all exposure pathways, including the groundwater and air pathways, were well below the 2.5 E-04 Sv/yr (25 mrem/yr) performance objective within 1,000 years. Doses following an assumed intrusion event within the facility boundaries were well below the IHI performance objectives, where the acute IHI dose was below the acute IHI dose performance objective of 5.0 E-03 Sv (500 mrem) and the chronic IHI dose was below the chronic IHI dose performance objective of 1.0 E-03 Sv/yr (100 mrem/yr) within 1,000 years. (author)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2018

Asymptotic analysis of the fluid flow with a pressure-dependent viscosity in a system of thin pipes

We consider the incompressible fluid with a pressure-dependent viscosity flowing through a multiple pipe system. The viscosity–pressure relation is given by the Barus law commonly used in the engineering applications. Assuming that the ratio between pipes thickness and its length is small, we propose a rigorous asymptotic approach based on the concept of the transformed pressure. As a result, we obtain new macroscopic model describing the effective behavior of the fluid in the system. In particular, the generalized version of the Kirchhoff’s law is derived giving the explicit formula for the junction pressure. The error estimate for the asymptotic approximation is also provided. Mathematical analysis presented here can be applied to a general viscosity–pressure relation satisfied by other empiric laws.

97 MATHEMATICS AND COMPUTING↗