Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “human systems modeling”

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 1,189 records · Page 66
All sourcesNASA NTRSDOE OSTI
NASA NTRS1997

Space Biosensor Systems: Implications for Technology Transfer

To meet the need for continuous, automated monitoring of animal subjects, including; humans, during space flight, NASA is developing advanced physiologic sensor and biotelemetry system technologies. The ability to continuously track basic physiological parameters, such as heart rate, blood pH, and body temperature, in untethered subjects in space is a challenging task. At NASA's Ames Research Center, where a key focus is gravitational biology research, engineers have teamed with life scientists to develop wireless sensor systems for automated physiologic monitoring of animal models as small as the rat. This technology is also being adapted, in collaboration with medical professionals, to meet human clinical monitoring needs both in space and on the ground. Thus, these advanced monitoring technologies have important dual-use functions; they meet space flight data collection requirements and constraints, while concurrently addressing a number of monitoring and data acquisition challenges on the ground in areas of clinical monitoring and biomedical research. Additional applications for these and related technologies are being sought and additional partnerships established that enhance development efforts, reduce costs and facilitate technology infusion between the public and private sectors. This paper describes technology transfer and co-development projects that have evolved out of NASA's miniaturized, implantable chemical sensor development efforts.

Hines, J. W.↗
NASA NTRS1980

Pilot-aircraft system response to wind shear

The nonlinear aircraft motion and automatic control computer model of Frost and Reddy has been expanded to incorporate the human pilot into simulations of aircraft response to wind shear. Fixed-stick, autopilot, and manned computer simulations are made with an aircraft having characteristics of a Queen Air (small commuter-type aircraft) flown through longitudinal winds measured by a Doppler radar beamed along the glide slope during the SESAME '79 experiments in Oklahoma. Simulations are also made flying a model Boeing 727 through sinusoidal head wind to tail wind shears at the phugoid frequency to evaluate the response of manned aircraft in thunderstorm wind environments.

Turkel, B. S.↗
DOE OSTI2024

Efficient Anomaly Detection Driven By Different Machine Learning Architectures And Models

The rapid growth and ubiquitous adoption of the internet and cyber-physical systems (CPS) have fundamentally transformed modern communication, work, and human-system interactions. While networks now form the backbone of critical digital ecosystems, enabling seamless data transmission across diverse, interconnected systems, this increased connectivity also expands the attack surface, making real-time detection of network intrusions and anomalies a pressing challenge. Detecting unusual activities within network infrastructure requires advanced data traffic analysis to differentiate between legitimate and malicious interactions. Traditional approaches to network anomaly detectionâ??such as rule-based and signature-based systemsâ??often depend on predefined patterns to identify known anomalies, limiting their effectiveness against emerging, stealthy, or previously unseen threats. These conventional methods suffer from high false alarm rates and fail to adapt to the ever-evolving nature of network traffic, particularly in large-scale, decentralized environments where data volume, velocity, and variety are constantly increasing. This dissertation presents artificial intelligence (AI)-driven approaches to anomaly detection that leverage graphics processing unit (GPU)-enabled high-performance computing (HPC) platforms for processing massive network traffic data and monitoring the components of cyber-physical systems (CPS) for potentially hazardous conditions. The research advances several key contributions: (1) Designing efficient machine learning techniques for CPS condition monitoring and anomaly detection; (2) enabling federated learning (FL) frameworks that enable distributed detection while preserving data privacy and system resilience; (3) exploring graph-based methodologies combining graph neural networks (GNN) and graph machine learning (ML) approaches for the Internet of Things (IoT) and automotive network security, and (4) performing distributed edge computing optimizations that integrate FL with scalable technologies for reduced communication overhead. Through extensive experiments, these methodologies demonstrate that complex anomaly detection and condition monitoring tasks can be achieved while balancing computational efficiency and detection accuracy through fine-grained network information processing. The frameworks developed in this research establish a robust foundation for network anomaly detection, providing scalable, adaptive, and privacy-preserving solutions for safeguarding CPS and IoT networks in an increasingly interconnected digital landscape. The practical implications of these research findings are significant, as they can inform the development of next-generation network security systems and contribute to the protection of critical infrastructure against sophisticated cyber attacks.

Marfo, William↗
NASA NTRS2016

Computational Modeling of Space Physiology

The Digital Astronaut Project (DAP), within NASAs Human Research Program, develops and implements computational modeling for use in the mitigation of human health and performance risks associated with long duration spaceflight. Over the past decade, DAP developed models to provide insights into space flight related changes to the central nervous system, cardiovascular system and the musculoskeletal system. Examples of the models and their applications include biomechanical models applied to advanced exercise device development, bone fracture risk quantification for mission planning, accident investigation, bone health standards development, and occupant protection. The International Space Station (ISS), in its role as a testing ground for long duration spaceflight, has been an important platform for obtaining human spaceflight data. DAP has used preflight, in-flight and post-flight data from short and long duration astronauts for computational model development and validation. Examples include preflight and post-flight bone mineral density data, muscle cross-sectional area, and muscle strength measurements. Results from computational modeling supplement space physiology research by informing experimental design. Using these computational models, DAP personnel can easily identify both important factors associated with a phenomenon and areas where data are lacking. This presentation will provide examples of DAP computational models, the data used in model development and validation, and applications of the model.

simulation↗
NASA NTRS1977

A dual-loop model of the human controller in single-axis tracking tasks

A dual loop model of the human controller in single axis compensatory tracking tasks is introduced. This model possesses an inner-loop closure which involves feeding back that portion of the controlled element output rate which is due to control activity. The sensory inputs to the human controller are assumed to be system error and control force. The former is assumed to be sensed via visual, aural, or tactile displays while the latter is assumed to be sensed in kinesthetic fashion. A nonlinear form of the model is briefly discussed. This model is then linearized and parameterized. A set of general adaptive characteristics for the parameterized model is hypothesized. These characteristics describe the manner in which the parameters in the linearized model will vary with such things as display quality. It is demonstrated that the parameterized model can produce controller describing functions which closely approximate those measured in laboratory tracking tasks for a wide variety of controlled elements.

Hess, R. A.↗
DOE OSTI2020

SMART Mobility. Mobility Decision Science Capstone Report

The U.S. Department of Energy’s Systems and Modeling for Accelerated Research in Transportation (SMART) Mobility Consortium is a multiyear, multi-laboratory collaborative, managed by the Energy Efficient Mobility Systems Program of the Office of Energy Efficiency and Renewable Energy, Vehicle Technologies Office, dedicated to further understanding the energy implications and opportunities of advanced mobility technologies and services. The first three-year research phase of SMART Mobility occurred from 2017 through 2019, and included five research pillars: Connected and Automated Vehicles, Mobility Decision Science, Multi-Modal Freight, Urban Science, and Advanced Fueling Infrastructure. A sixth research thrust integrated aspects of all five pillars to develop a SMART Mobility Modeling Workflow to evaluate new transportation technologies and services at scale. This report summarizes the work of the Mobility Decision Science Pillar. The Mobility Decision Science Pillar sought to fill gaps in existing knowledge about the human role in the mobility system including travel decision-making and technology adoption in the context of future mobility. The objective was to study how underlying preferences, needs, and contextual factors might constrain or hasten future transportation system scenarios. For information about the other Pillars and about the SMART Mobility Modeling Workflow, please refer to the relevant pillar’s Capstone Report.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS2017

Human Factors Virtual Analysis Techniques for NASA's Space Launch System Ground Support using MSFC's Virtual Environments Lab (VEL)

Using virtual environments to assess complex large scale human tasks provides timely and cost effective results to evaluate designs and to reduce operational risks during assembly and integration of the Space Launch System (SLS). NASA's Marshall Space Flight Center (MSFC) uses a suite of tools to conduct integrated virtual analysis during the design phase of the SLS Program. Siemens Jack is a simulation tool that allows engineers to analyze human interaction with CAD designs by placing a digital human model into the environment to test different scenarios and assess the design's compliance to human factors requirements. Engineers at MSFC are using Jack in conjunction with motion capture and virtual reality systems in MSFC's Virtual Environments Lab (VEL). The VEL provides additional capability beyond standalone Jack to record and analyze a person performing a planned task to assemble the SLS at Kennedy Space Center (KSC). The VEL integrates Vicon Blade motion capture system, Siemens Jack, Oculus Rift, and other virtual tools to perform human factors assessments. By using motion capture and virtual reality, a more accurate breakdown and understanding of how an operator will perform a task can be gained. By virtual analysis, engineers are able to determine if a specific task is capable of being safely performed by both a 5% (approx. 5ft) female and a 95% (approx. 6'1) male. In addition, the analysis will help identify any tools or other accommodations that may to help complete the task. These assessments are critical for the safety of ground support engineers and keeping launch operations on schedule. Motion capture allows engineers to save and examine human movements on a frame by frame basis, while virtual reality gives the actor (person performing a task in the VEL) an immersive view of the task environment. This presentation will discuss the need of human factors for SLS and the benefits of analyzing tasks in NASA MSFC's VEL.

Searcy, Brittani↗
NASA NTRS2016

Human Mars Entry, Descent, and Landing Architecture Study Overview

The Entry, Descent, and Landing (EDL) Architecture Study is a multi-NASA center activity to analyze candidate EDL systems as they apply to human Mars landing in the context of the Evolvable Mars Campaign. The study, led by the Space Technology Mission Directorate (STMD), is performed in conjunction with the NASA's Science Mission Directorate and the Human Architecture Team, sponsored by NASA's Human Exploration and Operations Mission Directorate. The primary objective is to prioritize future STMD EDL technology investments by (1) generating Phase A-level designs for selected concepts to deliver 20 t human class payloads, (2) developing a parameterized mass model for each concept capable of examining payloads between 5 and 40 t, and (3) evaluating integrated system performance using trajectory simulations. This paper summarizes the initial study results.

Cianciolo, Alicia D.↗
NASA NTRSDate not supplied

Combining Disparate Measures of Metabolic Rate During Simulated Spacewalks

Scientists from NASA's Extravehicular Activities (EVA) Physiology Systems and Performance Project help design space suits for future missions, during which astronauts are expected to perform EVA activities on the Lunar or Martian surface. During an EVA, an astronaut's integrated metabolic rate is used to predict how much longer the activity can continue and still provide a safe margin of remaining consumables. For EVAs in the Apollo era, NASA physicians monitored live data feeds of heart rate, O 2 consumption, and liquid cooled garment (LCG) temperatures, which were subjectively combined or compared to produce an estimate of metabolic rate. But these multiple data feeds sometimes provided conflicting estimates of metabolic rate, making real-time calculations of remaining time difficult for physician/monitors. Currently, designs planned for the Constellation Program EVAs utilize an automated, but largely heuristic methodology for incorporating the above three measurements, plus an additional one - CO 2 production, ignoring data that appears in conflict; however a more rigorous model-based approach is desirable. In this study, we show how principal axis factor analysis, in combination with OLS regression and LOWESS smoothing can be used to estimate metabolic rate as a data-driven weighted average of heart rate, O 2 consumption, LCG temperature data, and CO 2 production. Preliminary results suggest less sensitivity to occasional spikes in observed data feeds, and reasonable within-subject reproducibility when applied to subsequent tasks. These methods do not require physician monitoring and as such can be automated in the electronic components of future space suits. With additional validation, our models show promise for increasing astronaut safety, while reducing the need for and potential errors associated with human monitoring of multiple systems.

Alan H Feiveson↗
NASA NTRSDate not supplied

Parametric Cost Modeling of a Mid-Lift-to-Drag Ratio Vehicle for Human Mars Entry, Descent, and Landing

Cost is one of the biggest obstacles to sending humans to Mars. However, spacecraft costs are typically estimated after the preliminary vehicle and mission concepts have been designed. By automating the cost estimation process, the effect of any change in vehicle or mission design on the mission cost can be determined more rapidly. This paper uses the tool SAPE-C (Systems Analysis for Planetary Entry, Descent, and Landing-Cost). SAPE-C integrates the cost modeling software SEER-H (System Estimation and Evaluation of Resources-Hardware) with a number of systems analysis tools and enables large design tradespace exploration early in the design process. SAPE-C is used to analyze several tradespaces of the Mid-Lift-to-Drag ratio rigid entry vehicle for human Mars missions. Key findings include quantifying the impacts of payload, vehicle length, and main engine specific impulse on the overall cost of the vehicle, and how the payload per lander and number of landers affects the cost of a campaign to Mars.

Paul D Friz↗
NASA NTRSDate not supplied

Parametric Cost Modeling of a Mid-Lift-to-Drag Ratio Vehicle for Human Mars Entry, Descent, and Landing

Cost is one of the biggest obstacles to sending humans to Mars. However, spacecraft costs are typically estimated after the preliminary vehicle and mission concepts have been designed. By automating the cost estimation process, the effect of any change in vehicle or mission design on the mission cost can be determined more rapidly. This paper uses the tool SAPE-C (Systems Analysis for Planetary Entry, Descent, and Landing-Cost). SAPE-C integrates the cost modeling software SEER-H (System Estimation and Evaluation of Resources-Hardware) with a number of systems analysis tools and enables large design tradespace exploration early in the design process. SAPE-C is used to analyze several tradespaces of the Mid-Lift-to-Drag ratio rigid entry vehicle for human Mars missions. Key findings include quantifying the impacts of payload, vehicle length, and main engine specific impulse on the overall cost of the vehicle, and how the payload per lander and number of landers affects the cost of a campaign to Mars.

Paul D Friz↗
NASA NTRSDate not supplied

Evaluation of Aerosol Data Assimilation and Forecasts in the NASA GEOS Model during the ASIA-AQ Campaign

Fine particulate matter (PM2.5) poses significant risks to human health and the environment by penetrating the lungs and causing respiratory and cardiovascular diseases, making it crucial to understand its sources and behavior for effective air quality management. The Goddard Earth Observing System (GEOS) Forward Processing (FP) system model, operated by the Global Modeling and Assimilation Office (GMAO) at NASA's Goddard Space Flight Center, provides real-time weather and aerosol analyses and forecasts. In addition to meteorological data assimilation, the GEOS-FP system also assimilates aerosol using Moderate Resolution Imaging Spectroradiometer (MODIS) Aerosol Optical Depth (AOD) and Aerosol Robotic Network (AERONET) AOD data. In this study, the aerosol data assimilation and forecasts performance of the GEOS-FP model were evaluated for predicting PM2.5 in Korea using observations from the Airborne and Satellite Investigation of Asian Air Quality (ASIA-AQ) campaign. The ASIA-AQ campaign, an international collaborative field study initiative, aims to enhance understanding of local air quality issues and address common challenges in interpreting satellite data and air quality modeling. Conducted in South Korea from February 15 to March 13, 2024, during the high PM2.5 concentration winter season, this campaign provided extensive airborne and ground observations for intensive analysis of PM2.5 model simulations. We demonstrate how the assimilation runs and the forecasting performance of PM2.5 at 24-hour and 48-hour intervals vary. Additionally, we analyzed the differences and characteristics of PM2.5 composition in cases of long-range transport and local emissions. Using ASIA-AQ airborne data, we also examined the vertical profile of fine particulate matter. Through the intensive observations of this campaign, the GEOS model was assessed over South Korea using both in situ and airborne measurements to establish a baseline and identify priorities for future development.

Seunghee Lee↗
NASA NTRSDate not supplied

Orion SysML Model, Digital Twin, and Lessons Learned for Artemis I

In 2015 it was recognized by NASA’s Orion Chief Engineer that NASA’s design insight into the Orion subsystems for Artemis I were not sufficient to provide traditional engineering support to flight operations. To address these concerns and provide an opportunity to apply emerging model-based systems engineering and digital twin methodologies and provide opportunities for employees across NASA to get hands-on training, an Orion digital twin pilot project was initiated in 2020. With the increase in complexities of spacecraft, and decreased time to made decisions during missions in critical or emergency situations, digital modeling and integration of design can reduce the time to answer questions by days and required human resources by an order of magnitude over historical approaches and was identified to be critical capability for NASA’s future. This paper describes the genesis of this digital twin pilot project, efforts undertaken, a reproducible methodology to take available system information from a mature program to create an executable SysML model that supports a link to unit-specific data, thus forming a connection to the physical asset, and associated lessons learned and project deliverables.

MBSE↗
NASA NTRS1994

Real-time remote scientific model validation

This paper describes flight results from the use of a CLIPS-based validation facility to compare analyzed data from a space life sciences (SLS) experiment to an investigator's preflight model. The comparison, performed in real-time, either confirms or refutes the model and its predictions. This result then becomes the basis for continuing or modifying the investigator's experiment protocol. Typically, neither the astronaut crew in Spacelab nor the ground-based investigator team are able to react to their experiment data in real time. This facility, part of a larger science advisor system called Principal Investigator in a Box, was flown on the space shuttle in October, 1993. The software system aided the conduct of a human vestibular physiology experiment and was able to outperform humans in the tasks of data integrity assurance, data analysis, and scientific model validation. Of twelve preflight hypotheses associated with investigator's model, seven were confirmed and five were rejected or compromised.

Frainier, Richard↗
NASA NTRS2002

Human Motion Tracking and Glove-Based User Interfaces for Virtual Environments in ANVIL

The Army/NASA Virtual Innovations Laboratory (ANVIL) at Marshall Space Flight Center (MSFC) provides an environment where engineers and other personnel can investigate novel applications of computer simulation and Virtual Reality (VR) technologies. Among the many hardware and software resources in ANVIL are several high-performance Silicon Graphics computer systems and a number of commercial software packages, such as Division MockUp by Parametric Technology Corporation (PTC) and Jack by Unigraphics Solutions, Inc. These hardware and software platforms are used in conjunction with various VR peripheral I/O (input / output) devices, CAD (computer aided design) models, etc. to support the objectives of the MSFC Engineering Systems Department/Systems Engineering Support Group (ED42) by studying engineering designs, chiefly from the standpoint of human factors and ergonomics. One of the more time-consuming tasks facing ANVIL personnel involves the testing and evaluation of peripheral I/O devices and the integration of new devices with existing hardware and software platforms. Another important challenge is the development of innovative user interfaces to allow efficient, intuitive interaction between simulation users and the virtual environments they are investigating. As part of his Summer Faculty Fellowship, the author was tasked with verifying the operation of some recently acquired peripheral interface devices and developing new, easy-to-use interfaces that could be used with existing VR hardware and software to better support ANVIL projects.

Joseph D. Dumas, II↗
NASA NTRS2011

From Paper to Production to Test: An Update on NASA's J-2X Engine for Exploration

The NASA/industry team responsible for developing the J-2X upper stage engine for the Space Launch System (SLS) Program has made significant progress toward moving beyond the design phase and into production, assembly, and test of development hardware. The J-2X engine exemplifies the SLS Program goal of using proven technology and experience from more than 50 years of United States spaceflight experience combined with modern manufacturing processes and approaches. It will power the second stage of the fully evolved SLS Program launch vehicle that will enable a return to human exploration of space beyond low earth orbit. Pratt & Whitney Rocketdyne (PWR) is under contract to develop and produce the engine, leveraging its flight-proven LH2/LOX, gas generator cycle J-2 and RS-68 engine capabilities, recent experience with the X-33 aerospike XRS-2200 engine, and development knowledge of the J-2S tap-off cycle engine. The J- 2X employs a gas generator operating cycle designed to produce 294,000 pounds of vacuum thrust in primary operating mode with its full nozzle extension. With a truncated nozzle extension suitable to support engine clustering on the stage, the nominal vacuum thrust level in primary mode is 285,000 pounds. It also has a secondary mode, during which it operates at 80 percent thrust by altering its mixture ratio. The J-2X development philosophy is based on proven hardware, an aggressive development schedule, and early risk reduction. NASA Marshall Space Flight Center (MSFC) and PWR began development of the J-2X in June 2006. The government/industry team of more than 600 people within NASA and PWR successfully completed the Critical Design Review (CDR) in November 2008, following extensive risk mitigation testing. Assembly of the first development engine was completed in May 2011 and the first engine test was conducted at the NASA Stennis Space Center (SSC), test stand A2, on 14 July 2011. Testing of the first development engine will continue through the autumn of 2011, be paused for test stand modifications to the passive diffuser, and then restart in the spring of 2012. This testing will be followed by specialized powerpack testing intended to examine the design and operating margins of the engine turbomachinery. The development plan beyond this point leads through more system-level, engine testing of several samples, analytical model validation activities, functional and performance verification, and then ultimate certification to support human spaceflight. This paper will discuss the J-2X development background, provide top-level information on design and development planning, and will explore some of the development challenges and mitigation activities pursued to date.

Kynard, Michael↗