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NASA NTRSDate not supplied

Small Satellite-sized Hypersonic Inflatable Aerodynamic Decelerators for Interplanetary Science Missions

To make the most of ridesharing opportunities, small satellite (SmallSat) mission designers endeavor to pack as much payload into a SmallSat-class form factor as possible. The mass and volume constraints of this smaller vehicle class present a challenge for interplanetary mission sets that require a means of achieving orbit insertion at their destination of interest. For a fully propulsive orbit insertion design, this may translate to the propellant mass being a significant fraction of the overall vehicle mass and prolonged insertion time. Aerocapture is a single quick maneuver that can significantly reduce the required propellant mass for orbit insertion. Because aerocapture uses a planet’s atmosphere to achieve the necessary change in velocity, a protective aeroshell is needed. The constraints imposed on secondary payloads render traditional rigid aeroshells mass and space prohibitive for the SmallSat class of vehicles; thus, warranting consideration of deployable designs that can be stowed compactly until needed for atmospheric entry. The Hypersonic Inflatable Aerodynamic Decelerator (HIAD) is a deployable aeroshell that leverages inflatable toroids to achieve the large drag area needed for aerodynamic deceleration. While the technology is currently being analyzed for Mars human-scale missions, it has the potential applicability for interplanetary SmallSat-scale missions as well. This paper highlights a study conducted during an internship at NASA Langley Research Center to investigate the feasibility of using a scaled-down HIAD design in SmallSat aerocapture missions. Several scaling methodologies are investigated including use of parametric models and direct computer-aided design (CAD) model scaling. Candidate HIAD configurations that conform to secondary payload adapter requirements are identified. The Program to Optimize Simulated Trajectories II (POST2) is utilized to conduct orbit insertion performance and trajectory sensitivity studies using the candidate configurations at Earth, Venus, and Mars. The results of the study indicate that multiple SmallSat-sized HIAD designs, targeting a range of SmallSat payload classes, are feasible for planetary aerocapture missions to Mars and Venus as well as Earth-based aerocapture missions.

Shelly C. Mann↗
NASA NTRSDate not supplied

Aerocapture Trajectory Design for Uranus Orbiter

Introduction: The recently released National Academies Planetary Science and Astrobiology Decadal Survey 2023-2032 [1] identified the Ice Giants as the top priority science destination. While the survey acknowledged the potential for either a Uranus Orbiter and Probe (UOP) mission or a Neptune-Triton Odyssey mission, it ultimately identified the former as the highest priority new flagship mission. UOP missions calls for a launch window of opportunity between 2031-2038 with 12-15 year interplanetary cruise time along with a fully-propulsive Uranus Orbit Insertion burn on the order of a few km/s. However, a mission to Uranus with the same science payload could utilize aerocapture for orbit insertion to achieve both a significant reduction in the interplanetary cruise time and reduction in propulsive burn costs. Why Aerocapture: Aerocapture is a promising propellant and time-saving orbital insertion technique for planetary destinations with an atmosphere. Although not flight-proven, previous aerocapture systems studies in the literature have demonstrated both the validity and robustness of the technique at various planetary destinations. With respect to the Ice Giant planets, Neptune has seen more of the analysis in the literature. For science missions at Neptune, aerocapture can enable 1.4 times more delivered mass to orbit than an all-propulsive mission for the same launch vehicle while reducing interplanetary cruise times by more than 3 years [2] Additionally with modern guidance and control, Neptune aerocapture with blunt-body aeroshells is realizable [3][4]. There are limited papers in the literature investigating Uranus aerocapture with those available providing a preliminary feasibility assessment [5]. Consequently, the two-year funded NASA Space Technology Mission Directorate (STMD)-funded project, titled Aerocapture System as an Enabling Technology for Ice Giants Missions, aims to mature the analysis and technology state of Uranus aerocapture. Trajectory Design: This paper presents the current state of the trajectory design in support of the new aerocapture project. The project design philosophy is inspired from recent Neptune aerocapture studies, which employed modern guidance and control, in the sense that blunt-body aeroshells are analyzed. An assessment of the theoretical flight path angle corridor width is conducted for a range of ballistic coefficients and lift-to-drag ratios for both Space Launch System and Falcon Heavy Launch Vehicle interplanetary trajectory solutions. The results from the corridor width assessment provide an assessment of the aerocapture design-space and qualitative metrics on trajectory design considerations. The Program to Optimize Simulated Trajectories II (POST2) is utilized to run Monte Carlo simulations of Uranus aerocapture three-degree-of-freedom bank angle modulated trajectories using a closed-loop numerical-predictor corrector guidance algorithm. UranusGRAM 2021 is utilized as the atmospheric model [6]. A Uranus-developed aerodatabase, originally derived from Mars Science Laboratory (MSL), is utilized to provide vehicle aerodynamics over a wide range of hypersonic flow regimes. A MSL-derived 70 deg 4.5m diameter sphere-cone aeroshell that houses the UOP payload mass is assumed. Robustness testing and performance analysis is conducted, including the assessment of entry state errors, atmosphere density variations, and aerodynamic dispersions. Post-aerocapture Delta-V and aerothermal statistics are formulated into propellant mass and TPS requirements. The results presented in the paper will demonstrate the trajectory viability of Uranus aerocapture. Preliminary Results: Preliminary trajectory design results indicates successful Uranus aerocapture with a blunt-body aeroshell housing the same payload mass as the UOP mission from an Earth-to-Uranus interplanetary trajectory arriving in less than 7 years. From this interplanetary trajectory, aerocapture provides an orbit insertion Delta-V capability of 6.9 km/s requiring less than 300 m/s for post-aerocapture correction burns (15% of wet mass allocated to propellant). To put this into perspective, the UOP study utilized an Earth-to-Uranus trajectory that arrives in 13 years and requires more than 1000 m/s for fully-propulsive orbit insertion (40% of wet mass allocated to propellant). Achieving the same 6.9 km/s Delta-V capability fully-propulsively is mass prohibitive (97% of wet mass allocated to propellant). Nevertheless, aerocapture has the potential to reduce interplanetary transit times to Uranus by half while delivering the same payload mass to orbit in a reduced propellant mass footprint.

Rohan Deshmukh↗
NASA NTRSDate not supplied

SPIKE-Dx : A Low-Power High-Throughput Fault Diagnostics Tool using Spiking Neural Networks for Constrained Systems

Diagnostic systems are important for many aerospace systems, which are severely limited in available power, like cubesats or UAVs. Therefore, traditional diagnostics systems cannot be used due to their substantial footprint and constraints. In this paper, we present our very low power diagnostic tool SPIKE-DX to monitor critical systems with constrained computational and energy resources. This is made possible through spiking neural networks (SNNs), which are executable within optimized simulation environments and further implemented on on cutting-edge neuromorphic hardware. Based upon FMEA (Failure Mode and Effect Analysis) framework, Diagnostic Bayesian Networks (DBNs) can be constructed that provide powerful means for diagnostic reasoning. In this paper, we describe such DBNs and a method to automatically translate the DBN into highly structured networks of spiking neurons for execution in SPIKE-DX.

Spiking Neural Networks↗
NASA NTRSDate not supplied

POST Explorer: A Design Space Exploration Tool for POST2

Recent improvements for the Program to Optimize Simulated Trajectories II (POST2) have included the development of an application programming interface (API). This API allows POST2 simulation inputs to be directly manipulated from other applications (such as MATLAB or Python), and the outputs from POST2 are streamed directly to the external application that enables visualization, data manipulation, etc. Through this framework, a new tool called POST Explorer is being developed that provides a user the capability to modify the simulation inputs and interrogate the outputs within the same application, with raw data inspection and visualization embedded. This tool can be leveraged for multiple types of analyses, such as parametric sweeps and sensitivity studies, and will be available with a future release of the POST2 software.

Robert Anthony Williams↗
NASA NTRSDate not supplied

POST Explorer: A Design Space Exploration Tool for POST2

Recent improvements for the Program to Optimize Simulated Trajectories II (POST2) have included the development of an application programming interface (API). This API allows POST2 simulation inputs to be directly manipulated from other applications (such as MATLAB or Python), and the outputs from POST2 are streamed directly to the external application that enables visualization, data manipulation, etc. Through this framework, a new tool called POST Explorer is being developed that provides a user the capability to modify the simulation inputs and interrogate the outputs within the same application, with raw data inspection and visualization embedded. This tool can be leveraged for multiple types of analyses, such as parametric sweeps and sensitivity studies, and will be available with a future release of the POST2 software.

Anthony Williams↗
NASA NTRSDate not supplied

Parametric Mechanism Design Through Numerical Optimization and Physics Simulation

Design-Build-Test approaches for developing spaceflight hardware are prohibitively time and cost intensive and often lead to suboptimal mechanism designs. Approaches that couple machine learning and high-fidelity physics simulation could eliminate the need for hardware prototyping and dramatically accelerate the engineering design cycle, ultimately reducing cost. This work presents a modular NASA-developed toolchain to optimize hardware mechanisms in a virtual environment using numerical optimization and multi-body physics simulation. The toolchain enables multi-objective optimization, generates parametric CAD files that can be further post-processed by an end user, and can be expanded to optimize full systems and non-mechanical parameters such as feedback control variables. We demonstrate the toolchain through an independently verifiable design problem that optimizes wheel radius to achieve a desired linear velocity in a rigid-body physics environment when the wheel rotates at a constant angular speed, and then post-process the parametric CAD file of the optimal design generated by the tool before ultimately manufacturing it via 3D printing. We end with a discussion of how the toolchain can incorporate other analysis tools, including finite element analysis, computational fluid dynamics, and granular media simulations.

Optimization↗
NASA NTRS1989

A large scale software system for simulation and design optimization of mechanical systems

The concept of an advanced integrated, networked simulation and design system is outlined. Such an advanced system can be developed utilizing existing codes without compromising the integrity and functionality of the system. An example has been used to demonstrate the applicability of the concept of the integrated system outlined here. The development of an integrated system can be done incrementally. Initial capabilities can be developed and implemented without having a detailed design of the global system. Only a conceptual global system must exist. For a fully integrated, user friendly design system, further research is needed in the areas of engineering data bases, distributed data bases, and advanced user interface design.

Dopker, Bernhard↗
NASA NTRS1989

Parallel processing of real-time dynamic systems simulation on OSCAR (Optimally SCheduled Advanced multiprocessoR)

Parallel processing of real-time dynamic systems simulation on a multiprocessor system named OSCAR is presented. In the simulation of dynamic systems, generally, the same calculation are repeated every time step. However, we cannot apply to Do-all or the Do-across techniques for parallel processing of the simulation since there exist data dependencies from the end of an iteration to the beginning of the next iteration and furthermore data-input and data-output are required every sampling time period. Therefore, parallelism inside the calculation required for a single time step, or a large basic block which consists of arithmetic assignment statements, must be used. In the proposed method, near fine grain tasks, each of which consists of one or more floating point operations, are generated to extract the parallelism from the calculation and assigned to processors by using optimal static scheduling at compile time in order to reduce large run time overhead caused by the use of near fine grain tasks. The practicality of the scheme is demonstrated on OSCAR (Optimally SCheduled Advanced multiprocessoR) which has been developed to extract advantageous features of static scheduling algorithms to the maximum extent.

Kasahara, Hironori↗
NASA NTRS2013

Robust Multivariable Optimization and Performance Simulation for ASIC Design

Application-specific-integrated-circuit (ASIC) design for space applications involves multiple challenges of maximizing performance, minimizing power, and ensuring reliable operation in extreme environments. This is a complex multidimensional optimization problem, which must be solved early in the development cycle of a system due to the time required for testing and qualification severely limiting opportunities to modify and iterate. Manual design techniques, which generally involve simulation at one or a small number of corners with a very limited set of simultaneously variable parameters in order to make the problem tractable, are inefficient and not guaranteed to achieve the best possible results within the performance envelope defined by the process and environmental requirements. What is required is a means to automate design parameter variation, allow the designer to specify operational constraints and performance goals, and to analyze the results in a way that facilitates identifying the tradeoffs defining the performance envelope over the full set of process and environmental corner cases. The system developed by the Mixed Signal ASIC Group (MSAG) at the Goddard Space Flight Center is implemented as a framework of software modules, templates, and function libraries. It integrates CAD tools and a mathematical computing environment, and can be customized for new circuit designs with only a modest amount of effort as most common tasks are already encapsulated. Customization is required for simulation test benches to determine performance metrics and for cost function computation.

DuMonthier, Jeffrey↗
NASA NTRS2013

Model-Based Control of a Nonlinear Aircraft Engine Simulation using an Optimal Tuner Kalman Filter Approach

This paper covers the development of a model-based engine control (MBEC) methodology featuring a self tuning on-board model applied to an aircraft turbofan engine simulation. Here, the Commercial Modular Aero-Propulsion System Simulation 40,000 (CMAPSS40k) serves as the MBEC application engine. CMAPSS40k is capable of modeling realistic engine performance, allowing for a verification of the MBEC over a wide range of operating points. The on-board model is a piece-wise linear model derived from CMAPSS40k and updated using an optimal tuner Kalman Filter (OTKF) estimation routine, which enables the on-board model to self-tune to account for engine performance variations. The focus here is on developing a methodology for MBEC with direct control of estimated parameters of interest such as thrust and stall margins. Investigations using the MBEC to provide a stall margin limit for the controller protection logic are presented that could provide benefits over a simple acceleration schedule that is currently used in traditional engine control architectures.

Control Theory↗
NASA NTRS2022

Finite Difference Methods for Turbulence Simulations

The optimal finite difference discretization used in simulations of turbulent flows is influenced by both, the type of the scale resolving simulation (DNS or LES), as well as the flow-physics (hydrodynamic instabilities, shocks, acoustics, etc.) one expects to resolve. Insight into dispersion and dissipation error requirements for some common scale-resolving simulation scenarios help to highlight the issues faced in selecting a scheme.

Finite Difference Methods↗
NASA NTRS1995

Computer-Simulation Surrogates for Optimization: Application to Trapezoidal Ducts and Axisymmetric Bodies

Engineering design and optimization efforts using computational systems rapidly become resource intensive. The goal of the surrogate-based approach is to perform a complete optimization with limited resources. In this paper we present a Bayesian-validated approach that informs the designer as to how well the surrogate performs; in particular, our surrogate framework provides precise (albeit probabilistic) bounds on the errors incurred in the surrogate-for-simulation substitution. The theory and algorithms of our computer{simulation surrogate framework are first described. The utility of the framework is then demonstrated through two illustrative examples: maximization of the flowrate of fully developed ow in trapezoidal ducts; and design of an axisymmetric body that achieves a target Stokes drag.

Otto, John C.↗
NASA NTRS1989

Optimal placement of excitations and sensors by simulated annealing

The optimal placement of discrete actuators and sensors is posed as a combinatorial optimization problem. Two examples for truss structures were used for illustration; the first dealt with the optimal placement of passive dampers along existing truss members, and the second dealt with the optimal placement of a combination of a set of actuators and a set of sensors. Except for the simplest problems, an exact solution by enumeration involves a very large number of function evaluations, and is therefore computationally intractable. By contrast, the simulated annealing heuristic involves far fewer evaluations and is best suited for the class of problems considered. As an optimization tool, the effectiveness of the algorithm is enhanced by introducing a number of rules that incorporate knowledge about the physical behavior of the problem. Some of the suggested rules are necessarily problem dependent.

Salama, Moktar↗
NASA NTRS1973

Computer simulation for time optimal or energy optimal attitude control of spin-stabilized spacecraft.

An original technique for determining the optimal magnetic torque strategy for control of the attitude of spin stabilized spacecraft is presented. By employing Lagrange multipliers and the Calculus of Variations, optimal control equations are derived which define minimum time and minimum energy attitude maneuvers. Computer program algorithms to numerically solve these optimal control equations are also described. The performance of this technique is compared with a commonly employed planning method.

Woolley, R. D.↗
NASA NTRS1977

Simulator evaluation of optimal thrust management/fuel conservation strategies for airbus aircraft on short haul routes

The feasibility of incorporating optimal concepts into a practical system was determined. Various earlier theoretical analyses were confirmed, and insight was gained into the sensitivity of fuel conservation strategies to nonlinear and second order aerodynamic and engine characteristics. In addition to the investigation of optimal trajectories the study ascertained combined fuel savings by utilizing various procedure-oriented improvements such as delayed flap/decelerating approaches and great circle navigation.

Bochem, J. H.↗
NASA NTRS1997

Rapid Modeling, Assembly and Simulation in Design Optimization

A new capability for design is reviewed. This capability provides for rapid assembly of detail finite element models early in the design process where costs are most effectively impacted. This creates an engineering environment which enables comprehensive analysis and design optimization early in the design process. Graphical interactive computing makes it possible for the engineer to interact with the design while performing comprehensive design studies. This rapid assembly capability is enabled by the use of Interface Technology, to couple independently created models which can be archived and made accessible to the designer. Results are presented to demonstrate the capability.

Housner, Jerry↗