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At least 1,009 records · Page 56

Crew State and Risk Model Development to Predict Hydration Status During Extravehicular Activity Training Events

Introduction: Hydration is critical for optimal human health and performance and dehydration can lead to impaired cardiovascular function, thermal dysregulation, decreased blood plasma volume, and cognitive impacts, particularly during physical activity. Prolonged and repeated extravehicular activities (EVA) without sufficiently available drinking water may increase risk for dehydration, which could impair crew health and impact mission success. Understanding hydration needs and potential effects on health and performance are necessary to optimize crew well-being and enable successful EVA objectives. This study aims to develop a model of hydration status during EVA using water balance techniques. Methods: Water balance measures were collected on 15 healthy astronauts who performed ≈6-hour simulated microgravity extravehicular activity (EVA) training in the NASA Neutral Buoyancy Laboratory (NBL). Data collected included pre-and post-EVA nude body weight (BW), maximum absorption garment (MAG) weight, Disposable In-suit Drink Bag (DIDB) weight, urine specific gravity (USG), and extra pre-EVA intake (W). Variables were combined to create the water balance model as pre-EVA (Hn)= BWn+ MAGn+ DIDBn+ Wnand post EVA (Hn+1) = BWn+1+ MAGn+1+ DIDBn+1. Urine specific gravity values were used to refine water balance measures into hydration categories: Hydrated, Marginally Hydrated, and Dehydrated. Results: Pre-EVA modeling indicated53% of crew were hydrated, 20% were marginally hydrated, and 27% were dehydrated. Alternately, Hn+1 showed 13% of crew remained hydrated, 47% were marginally hydrated, and 40% were dehydrated at the end of the EVA. Furthermore, 75% of the crewmembers who started sufficiently hydrated finished the run marginally hydrated or dehydrated. According to USG indices presented by Casa and Lawrence, et al. (2000), only 25% of the crew started and remained hydrated throughout the EVA, and those who were dehydrated at the outset stayed dehydrated. Conclusion: Model outcomes assessing hydration status during 6-hour simulated microgravity EVAs demonstrate the necessity to further address hydration requirements for optimal human performance during spaceflight and EVA. This study enables additional baseline development of the Crew State and Risk Model Hydration, Nutrition, and Waste Management component that aims to provide individualized crew state and risk predictions during EVAs. Reference: Casa, D. J., Armstrong, L. E., et al. (2000). National Athletic Trainers’ Association Position Statement: Fluid Replacement for Athletes. Journal of Athletic Training, 35:212-224.

L Cooper↗

Implicit Thermochemical Nonequilibrium Flow Simulations on Unstructured Grids using GPUs

Thermochemical nonequilibrium flow simulation capabilities have been previously implemented, verified, and validated for central processing unit (CPU) systems in NASA’s unstructured-grid computational fluid dynamics solver FUN3D. Many exascale-class high-performance computing systems will rely on graphics processing unit (GPU) architectures for high throughput and energy efficiency; thus, CPU-based scientific computing software unable to effectively utilize these systems must be updated. In this work, we present a CUDA C++ implementation of FUN3D’s thermochemical nonequilibrium flow simulation capabilities targeting NVIDIA Tesla GPUs. An overview of the porting and optimization strategy is described and performance comparisons with other recent architectures are presented. Scaling to thousands of GPUs is demonstrated, yielding computational performance equivalent to that of several million CPU cores. The implementation enables efficient, high-fidelity, scale-resolving simulations of thermochemical nonequilibrium flows for many applications including atmospheric entry, hypersonics, and combustion.

GPU↗

Improving Fidelity of Launch Vehicle Liftoff Acoustic Simulations

Launch vehicles experience high acoustic loads during ignition and liftoff affected by the interaction of rocket plume generated acoustic waves with launch pad structures. Application of highly parallelized Computational Fluid Dynamics (CFD) analysis tools optimized for application on the NAS computer systems such as the Loci/CHEM program now enable simulation of time-accurate, turbulent, multi-species plume formation and interaction with launch pad geometry and capture the generation of acoustic noise at the source regions in the plume shear layers and impingement regions. These CFD solvers are robust in capturing the acoustic fluctuations, but they are too dissipative to accurately resolve the propagation of the acoustic waves throughout the launch environment domain along the vehicle. A hybrid Computational Fluid Dynamics and Computational Aero-Acoustics (CFD/CAA) modeling framework has been developed to improve such liftoff acoustic environment predictions. The framework combines the existing highly-scalable NASA production CFD code, Loci/CHEM, with a high-order accurate discontinuous Galerkin (DG) solver, Loci/THRUST, developed in the same computational framework. Loci/THRUST employs a low dissipation, high-order, unstructured DG method to accurately propagate acoustic waves away from the source regions across large distances. The DG solver is currently capable of solving up to 4th order solutions for non-linear, conservative acoustic field propagation. Higher order boundary conditions are implemented to accurately model the reflection and refraction of acoustic waves on launch pad components. The DG solver accepts generalized unstructured meshes, enabling efficient application of common mesh generation tools for CHEM and THRUST simulations. The DG solution is coupled with the CFD solution at interface boundaries placed near the CFD acoustic source regions. Both simulations are executed simultaneously with coordinated boundary condition data exchange.

Liever, Peter↗

A Scalable and Robust Multi-Agent Approach to Distributed Optimization

Modularizing a large optimization problem so that the solutions to the subproblems provide a good overall solution is a challenging problem. In this paper we present a multi-agent approach to this problem based on aligning the agent objectives with the system objectives, obviating the need to impose external mechanisms to achieve collaboration among the agents. This approach naturally addresses scaling and robustness issues by ensuring that the agents do not rely on the reliable operation of other agents We test this approach in the difficult distributed optimization problem of imperfect device subset selection [Challet and Johnson, 2002]. In this problem, there are n devices, each of which has a "distortion", and the task is to find the subset of those n devices that minimizes the average distortion. Our results show that in large systems (1000 agents) the proposed approach provides improvements of over an order of magnitude over both traditional optimization methods and traditional multi-agent methods. Furthermore, the results show that even in extreme cases of agent failures (i.e., half the agents fail midway through the simulation) the system remains coordinated and still outperforms a failure-free and centralized optimization algorithm.

Tumer, Kagan↗

Development of Carbon Dioxide Removal Systems for Advanced Exploration Systems

"NASA's Advanced Exploration Systems (AES) program is pioneering new approaches for rapidly developing prototype systems, demonstrating key capabilities, and validating operational concepts for future human missions beyond Earth orbit" (NASA 2012). These forays beyond the confines of earth's gravity will place unprecedented demands on launch systems. They must not only blast out of earth's gravity well as during the Apollo moon missions, but also launch the supplies needed to sustain a crew over longer periods for exploration missions beyond earth's moon. Thus all spacecraft systems, including those for the separation of metabolic carbon dioxide and water from a crewed vehicle, must be minimized with respect to mass, power, and volume. Emphasis is also placed on system robustness both to minimize replacement parts and ensure crew safety when a quick return to earth is not possible. Current efforts are focused on improving the current state-of-the-art systems utilizing fixed beds of sorbent pellets by seeking more robust pelletized sorbents, evaluating structured sorbents, and examining alternate bed configurations to improve system efficiency and reliability. These development efforts combine testing of sub-scale systems and multi-physics computer simulations to evaluate candidate approaches, select the best performing options, and optimize the configuration of the selected approach, which is then implemented in a full-scale integrated atmosphere revitalization test. This paper describes the carbon dioxide (CO2) removal hardware design and sorbent screening and characterization effort in support of the Atmosphere Resource Recovery and Environmental Monitoring (ARREM) project within the AES program. A companion paper discusses development of atmosphere revitalization models and simulations for this project.

Knox, James C.↗

Modeling human response errors in synthetic flight simulator domain

This paper presents a control theoretic approach to modeling human response errors (HRE) in the flight simulation domain. The human pilot is modeled as a supervisor of a highly automated system. The synthesis uses the theory of optimal control pilot modeling for integrating the pilot's observation error and the error due to the simulation model (experimental error). Methods for solving the HRE problem are suggested. Experimental verification of the models will be tested in a flight quality handling simulation.

Ntuen, Celestine A.↗

Discrete Event Supervisory Control Applied to Propulsion Systems

The theory of discrete event supervisory (DES) control was applied to the optimal control of a twin-engine aircraft propulsion system and demonstrated in a simulation. The supervisory control, which is implemented as a finite-state automaton, oversees the behavior of a system and manages it in such a way that it maximizes a performance criterion, similar to a traditional optimal control problem. DES controllers can be nested such that a high-level controller supervises multiple lower level controllers. This structure can be expanded to control huge, complex systems, providing optimal performance and increasing autonomy with each additional level. The DES control strategy for propulsion systems was validated using a distributed testbed consisting of multiple computers--each representing a module of the overall propulsion system--to simulate real-time hardware-in-the-loop testing. In the first experiment, DES control was applied to the operation of a nonlinear simulation of a turbofan engine (running in closed loop using its own feedback controller) to minimize engine structural damage caused by a combination of thermal and structural loads. This enables increased on-wing time for the engine through better management of the engine-component life usage. Thus, the engine-level DES acts as a life-extending controller through its interaction with and manipulation of the engine s operation.

Litt, Jonathan S.↗

Evaluation of Response Surface Experiment Designs for Distributed Propulsion Aircraft Aero-Propulsive Modeling

Modern distributed hybrid and electric propulsion aircraft, including vertical, short, and conventional takeoff and landing configurations, exhibit significant aero-propulsive complexity and a large number of interacting test factors. This paper presents the development and evaluation of experiment designs for aero-propulsive characterization of distributed propulsion aircraft. Five different foundational response surface designs are evaluated to inform the development of two sequential design approaches tailored to complex aircraft aerodynamic characterization experiments. The first approach, which builds on sequential face-centered central composite designs, has been used previously to develop aero-propulsive models for complex aircraft using wind tunnel testing. The second approach is a new design strategy leveraging a regular I-optimal and nested I-optimal design that was developed for this study. The two sequential design strategies are compared for experiments with a large number of test factors using pre-experiment design evaluation metrics, as well as modeling results obtained from simulated wind tunnel data for the NASA LA-8 aircraft. The design evaluation metrics show that the sequential I-optimal base design has higher statistical power, lower correlation among candidate regressors, lower prediction variance, and more precise parameter estimates. The simulated wind tunnel experiments conducted using each design reveal that the sequential I-optimal base design has better predictive capability with fewer test points. The experiment design and evaluation procedures are described in detail to inform future aerodynamic characterization experiments for complex aircraft.

design of experiments↗

Peak-Seeking Optimization of Spanwise Lift Distribution for Wings in Formation Flight

A method is presented for the optimization of the lift distribution across the wing of an aircraft in formation flight. The usual elliptical distribution is no longer optimal for the trailing wing in the formation due to the asymmetric nature of the encountered flow field. Control surfaces along the trailing edge of the wing can be configured to obtain a non-elliptical profile that is more optimal in terms of minimum drag. Due to the difficult-to-predict nature of formation flight aerodynamics, a Newton-Raphson peak-seeking controller is used to identify in real time the best aileron and flap deployment scheme for minimum total drag. Simulation results show that the peak-seeking controller correctly identifies an optimal trim configuration that provides additional drag savings above those achieved with conventional anti-symmetric aileron trim.

Hanson, Curtis E.↗

Thermoplastic Matrix Composite Design for Cryotanks Using Multiscale Modeling and Bayesian Optimization

Designing lightweight, robust cryogenic storage tanks is critical for future launch vehicles, in-space propellant storage, and hydrogen powered aircraft. This work presents a multiscale modeling and Bayesian optimization framework for the design of thermoplastic matrix composite cryotanks. Molecular dynamics simulations are first used to determine temperature-dependent constituent properties for candidate thermoplastic matrices, which are homogenized to the lamina scale using NASA’s Multiscale Analysis Tool (NASMAT). These lamina properties, in combination with laminate family generation rules, are evaluated in HyperX structural optimization software to identify stacking sequences that meet all cryogenic load requirements. A Bayesian optimization framework is applied, with HyperX in the loop (via the HyperX API) to efficiently search across material and laminate design variables, yielding an optimized cryotank configuration with significant reductions in design cycle time compared to exhaustive search approaches.

thermoplastics↗

Software Would Largely Automate Design of Kalman Filter

Embedded Navigation Filter Automatic Designer (ENFAD) is a computer program being developed to automate the most difficult tasks in designing embedded software to implement a Kalman filter in a navigation system. The most difficult tasks are selection of error states of the filter and tuning of filter parameters, which are timeconsuming trial-and-error tasks that require expertise and rarely yield optimum results. An optimum selection of error states and filter parameters depends on navigation-sensor and vehicle characteristics, and on filter processing time. ENFAD would include a simulation module that would incorporate all possible error states with respect to a given set of vehicle and sensor characteristics. The first of two iterative optimization loops would vary the selection of error states until the best filter performance was achieved in Monte Carlo simulations. For a fixed selection of error states, the second loop would vary the filter parameter values until an optimal performance value was obtained. Design constraints would be satisfied in the optimization loops. Users would supply vehicle and sensor test data that would be used to refine digital models in ENFAD. Filter processing time and filter accuracy would be computed by ENFAD.

Chuang, Jason C. H.↗

Comparison of joint space versus task force load distribution optimization for a multiarm manipulator system

It is often proposed that the redundancy in choosing a force distribution for multiple arms grasping a single object should be handled by minimizing a quadratic performance index. The performance index may be formulated in terms of joint torques or in terms of the Cartesian space force/torque applied to the body by the grippers. The former seeks to minimize power consumption while the latter minimizes body stresses. Because the cost functions are related to each other by a joint angle dependent transformation on the weight matrix, it might be argued that either method tends to reduce power consumption, but clearly the joint space minimization is optimal. A comparison of these two options is presented with consideration given to computational cost and power consumption. Simulation results using a two arm robot system are presented to show the savings realized by employing the joint space optimization. These savings are offset by additional complexity, computation time and in some cases processor power consumption.

Soloway, Donald I.↗

Cirrus Heterogeneity Effects on Cloud Optical Properties Retrieved with an Optimal Estimation Method from MODIS VIS to TIR Channels.

This study presents preliminary results on the effect of cirrus heterogeneities on top-of-atmosphere (TOA) simulated radiances or reflectances for MODIS channels centered at 0.86, 2.21, 8.56, 11.01 and 12.03 micrometers , and on cloud optical properties retrieved with a research-level optimal estimation method (OEM). Synthetic cirrus cloud fields are generated using a 3D cloud generator (3DCLOUD) and radiances/reflectances are simulated using a 3D radiative transfer code (3DMCPOL). We find significant differences between the heterogeneity effects on either visible and near-infrared (VNIR) or thermal infrared (TIR) radiances. However, when both wavelength ranges are combined, heterogeneity effects are dominated by the VNIR horizontal radiative transport effect. As a result, small optical thicknesses are overestimated and large ones are underestimated. Retrieved effective diameter are found to be slightly affected, contrarily to retrievals using TIR channels only.

MODIS↗

SATCOM simulator speeds MSS deployment and lowers costs

Mobile satellite systems (MSS) are being proposed and licensed at an accelerating rate. How can the design, manufacture, and performance of these systems be optimized at costs that allow a reasonable return on investment? The answer is the use of system simulation techniques beginning early in the system design and continuing through integration, pre- and post-launch monitoring, and in-orbit monitoring. This paper focuses on using commercially available, validated simulation instruments to deliver accurate, repeatable, and cost effective measurements throughout the life of a typical mobile satellite system. A satellite communications test set is discussed that provides complete parametric test capability with a significant improvement in measurement speed for manufacturing, integration, and pre-launch and in-orbit testing. The test set can simulate actual up and down link traffic conditions to evaluate the effects of system impairments, propagation and multipath on bit error rate (BER), channel capacity and transponder and system load balancing. Using a standard set of commercial instruments to deliver accurate, verifiable measurements anywhere in the world speeds deployment, generates measurement confidence, and lowers total system cost.

Carey, Tim↗

Usability Evaluation of Fleet Management Interface for High Density Vertiplex Environments

To meet the rising demand for an Advanced Air Mobility (AAM) (i.e. urban and rural unmanned aircraft systems) ecosystem, the NASA Aeronautics Research Mission Directorate (ARMD) is hosting a series of simulations and flight tests under the High Density Vertiplex sub-project (HDV) to prototype and study the effectiveness AAM capabilities under various operational contexts. HDV aims to develop an integrated automation architecture to support terminal area flight operations. The HDV simulations and flight tests address safety, integration, and operational challenges, while integrated systems and software demonstrate design readiness, robustness, and interoperability. During the initial HDV simulation in 2021, a prototype traffic management tool developed by NASA called the Fleet Management Interface (FMI) was tested. FMI was designed to introduce an advanced level of human-automation interaction to aid both Ground Control Station Operators (GCSOs) and Fleet Managers (FMs) in remotely managing flights under their ownership. In a human-in-the-loop simulation, a usability study was conducted with the FMI to identify optimal approaches for displaying information to human operators using subjective measures of usability, workload, situation awareness, risk, and trust, along with qualitative feedback. This study consisted of task analysis in which GCSO and FM subjects used an Urban Air Mobility (UAM) environment to develop and execute a plan for two different traffic scenarios of remotely controlled vehicles. In each scenario, a remotely controlled vehicle completed a takeoff, active flight, and landing sequence while simulated traffic flew in the background at a rate of 20 operations per hour. In the first scenario, the controlled vehicle flew a nominal route with takeoff and landing at the same vertiport. In the second scenario, the controlled vehicle started on the nominal route, then diverted to an unplanned location mid-flight. Results showed that self- reported performance, usability, trust, and situation awareness ratings of FMI were moderately to strongly high. There were small differences between scenarios, with Scenario 2 being perceived as more unstable, complex, variable, risky, and potentially harmful than Scenario 1. Furthermore, participants described improvements that could be made to create a better user experience. For example, users suggested customizable interfaces to accommodate information display preferences, and the ability to review routes before assigning them. The results from this study will inform future development of the FMI with the end goal of creating a reference automation tool for airspace management procedures in AAM. The FMI could serve to reduce dependency on traditional air navigation services through increased automation in high density vertiplex environments.

Fleet manager↗

SPASIM: A Spacecraft Simulator

The SPAcecraft SIMulator (SPASIM) simulates the functions and resources of a spacecraft to quickly perform conceptual design (Phase A) trade-off and sensitivity analyses and uncover any operational bottlenecks during any part of the mission. Failure modes and operational contingencies can be evaluated allowing operational planning (what-if scenarios) and optimization for a range of mission scenarios. The payloads and subsystems are simulated, using a hierarchy of graphical models, in terms of how their functions affect resources such as propellant, power, and data. Any of the inputs and outputs of the payloads and subsystems can be plotted during the simulation or stored in a file so they can be used by other programs. Most trade-off analyses, including those that compare current versus advanced technology, can be performed by changing values in the parameter menus. However, when a component is replaced by one with a different functional architecture, its graphical model can also be modified or replaced by drawing from a component library. SPASIM has been validated using several spacecraft designs that were at least at the Critical Design Review level. The user and programmer guide, including figures, is available on line as a hypertext document. This is an easy-to-use and expandable tool which is based on MATLAB(R) and SIMULINK(R). It runs on Silicon Graphics Inc. workstations and personal computers with Windows 95(TM) or NT(TM).

Liceaga, Carlos A.↗

Peak-Seeking Optimization of Spanwise Lift Distribution for Wings in Formation Flight

A method is presented for the in-flight optimization of the lift distribution across the wing for minimum drag of an aircraft in formation flight. The usual elliptical distribution that is optimal for a given wing with a given span is no longer optimal for the trailing wing in a formation due to the asymmetric nature of the encountered flow field. Control surfaces along the trailing edge of the wing can be configured to obtain a non-elliptical profile that is more optimal in terms of minimum combined induced and profile drag. Due to the difficult-to-predict nature of formation flight aerodynamics, a Newton-Raphson peak-seeking controller is used to identify in real time the best aileron and flap deployment scheme for minimum total drag. Simulation results show that the peak-seeking controller correctly identifies an optimal trim configuration that provides additional drag savings above those achieved with conventional anti-symmetric aileron trim.

Hanson, Curtis E.↗

Grayscale Optical Correlator Workbench

Grayscale Optical Correlator Workbench (GOCWB) is a computer program for use in automatic target recognition (ATR). GOCWB performs ATR with an accurate simulation of a hardware grayscale optical correlator (GOC). This simulation is performed to test filters that are created in GOCWB. Thus, GOCWB can be used as a stand-alone ATR software tool or in combination with GOC hardware for building (target training), testing, and optimization of filters. The software is divided into three main parts, denoted filter, testing, and training. The training part is used for assembling training images as input to a filter. The filter part is used for combining training images into a filter and optimizing that filter. The testing part is used for testing new filters and for general simulation of GOC output. The current version of GOCWB relies on the mathematical software tools from MATLAB binaries for performing matrix operations and fast Fourier transforms. Optimization of filters is based on an algorithm, known as OT-MACH, in which variables specified by the user are parameterized and the best filter is selected on the basis of an average result for correct identification of targets in multiple test images.

Hanan, Jay↗