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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.

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At least 289 records · Page 16

Computing Instability In Combustion Of Liquid Propellants

Computational fluid dynamics (CFD) code developed for use in design analyses of flow instabilities associated with combustion of sprayed liquid propellants in rocket engines. Code also contributes to design of improved commercial sprayed-fuel combustors in furnaces and jet engines. Proves robust, user-friendly software tool with comprehensive analysis capability. Enables characterization of stability or instability of engine in terms of such physically meaningful parameters as initial conditions of spray, spatial distribution of ratio between concentrations of fuel and oxidizer at injector faces, geometry of combustor, and configurations of baffles.

Chen, Yen-Sen↗

Linear Parameter Varying Control Synthesis for Actuator Failure, Based on Estimated Parameter

The design of a linear parameter varying (LPV) controller for an aircraft at actuator failure cases is presented. The controller synthesis for actuator failure cases is formulated into linear matrix inequality (LMI) optimizations based on an estimated failure parameter with pre-defined estimation error bounds. The inherent conservatism of an LPV control synthesis methodology is reduced using a scaling factor on the uncertainty block which represents estimated parameter uncertainties. The fault parameter is estimated using the two-stage Kalman filter. The simulation results of the designed LPV controller for a HiMXT (Highly Maneuverable Aircraft Technology) vehicle with the on-line estimator show that the desired performance and robustness objectives are achieved for actuator failure cases.

Shin, Jong-Yeob↗

The structure of robust observers

Conventional observers for linear time-invariant systems are shown to be structurally inadequate from a sensitivity standpoint. It is proved that if a linear dynamic system is to provide observer action despite arbitrary small perturbations in a specified subset of its parameters, it must: (1) be a closed loop system, be driven by the observer error, (2) possess redundancy, the observer must be generating, implicitly or explicitly, at least one linear combination of states that is already contained in the measurements, and (3) contain a perturbation-free model of the portion of the system observable from the external input to the observer. The procedure for design of robust observers possessing the above structural features is established and discussed.

Bhattacharyya, S. P.↗

Integration of Uncertainty Quantification in a Model-Based Systems Analysis and Engineering Framework

This paper presents a technical approach to improve the confidence in the systems analysis process by integrating Uncertainty Quantification (UQ) techniques within a Model-Based Systems Analysis and Engineering (MBSA&E) framework. The MBSA&E architecture uses system models and multidisciplinary analytical solutions as central artifacts for system design and analysis. The integration of UQ enables engineers to assess and mitigate uncertainties associated with a system model, design parameters, and constraint inputs, leading to more complete design studies and further informed decision-making processes. The proposed approach leverages the strengths of MBSA&E and extends it with a UQ methodology to quantify uncertainties in the input parameters and to trace the uncertainties as they propagate throughout the system model. To demonstrate the effectiveness of an integrated MBSA&E-UQ approach, a case study involving a simplified analysis of a Transonic Truss-Braced Wing (TTBW) concept vehicle is performed. This integration enables a more comprehensive evaluation of system performance and behavior under uncertainty and a more robust approach for system design and analysis. Lastly, the paper addresses the challenges and considerations associated with integrating UQ into an MBSA&E framework.

systems analysis↗

Integration of Uncertainty Quantification in a Model-Based Systems Analysis and Engineering Framework

This paper presents a technical approach to improve the confidence in the systems analysis process by integrating Uncertainty Quantification (UQ) techniques within a Model-Based Systems Analysis and Engineering (MBSA&E) framework. The MBSA&E architecture uses system models and multidisciplinary analytical solutions as central artifacts for system design and analysis. The integration of UQ enables engineers to assess and mitigate uncertainties associated with a system model, design parameters, and constraint inputs, leading to more complete design studies and further informed decision-making processes. The proposed approach leverages the strengths of MBSA&E and extends it with a UQ methodology to quantify uncertainties in the input parameters and to trace the uncertainties as they propagate throughout the system model. To demonstrate the effectiveness of an integrated MBSA&E-UQ approach, a case study involving a simplified analysis of a Transonic Truss-Braced Wing (TTBW) concept vehicle is performed. This integration enables a more comprehensive evaluation of system performance and behavior under uncertainty and a more robust approach for system design and analysis. Lastly, the paper addresses the challenges and considerations associated with integrating UQ into an MBSA&E framework.

systems analysis↗

Forward Bay Cover Separation Modeling and Testing for the Orion Multi-Purpose Crew Vehicle

Spacecraft multi-body separation events during atmospheric descent require complex testing and analysis to validate the flight separation dynamics models used to verify no re-contact. The NASA Orion Multi-Purpose Crew Vehicle (MPCV) architecture includes a highly-integrated Forward Bay Cover (FBC) jettison assembly design that combines parachutes and piston thrusters to separate the FBC from the Crew Module (CM) and avoid re-contact. A multi-disciplinary team across numerous organizations examined key model parameters and risk areas to develop a robust but affordable test campaign in order to validate and verify the FBC separation event for Exploration Flight Test-1 (EFT-1). The FBC jettison simulation model is highly complex, consisting of dozens of parameters varied simultaneously, with numerous multi-parameter interactions (coupling and feedback) among the various model elements, and encompassing distinct near-field, mid-field, and far-field regimes. The test campaign was composed of component-level testing (for example gas-piston thrusters and parachute mortars), ground FBC jettison tests, and FBC jettison air-drop tests that were accomplished by a highly multi-disciplinary team. Three ground jettison tests isolated the testing of mechanisms and structures to anchor the simulation models excluding aerodynamic effects. Subsequently, two air-drop tests added aerodynamic and parachute elements, and served as integrated system demonstrations, which had been preliminarily explored during the Orion Pad Abort-1 (PA-1) flight test in May 2010. Both ground and drop tests provided extensive data to validate analytical models and to verify the FBC jettison event for EFT-1. Additional testing will be required to support human certification of this separation event, for which NASA and Lockheed Martin are applying knowledge from Apollo and EFT-1 testing and modeling to develop a robust human-rated FBC separation event.

Ali, Yasmin↗

DEVELOPMENT OF INEXPENSIVE HIGH TEMPERATURE NITI-BASED SHAPE MEMORY ALLOYS FOR POWDER BED ADDITIVE MANUFACTURING

NiTi and NiTi-based Shape Memory Alloys (SMA) exhibit a reversible solid-state phase transformation from martensite to austenite driven by thermal energy. High temperature (Mf>100°C) SMAs are martensite at room temperature and can be fabricated into solid-state actuators that return to a pre-programmed shape against a designed load after heating to transformation threshold. Reactive as-fabricated additively manufactured parts (4-D printing) is the current state of the art in manufacturing of SMAs but requires compositions compliant to rapid solidification. Existing actuator designs are developed from commercially available, highly investigated material compositions. However, existing high temperature high performance (high actuation strain, low thermal hysteresis) shape memory alloys contain significant (>10% at.) portions of high-cost Platinum Group Metals (PGMs). It is of significant scientific interest to investigate material compositions that are peer performing or superior to PGMs whose constituent elements represent a significant cost savings. Shape memory alloy properties vary significantly with small (0.1% at.) compositional changes making robust investigative sample sets very large. Computational material design can be deployed to shrink the compositional space of possible alloy combinations and reduce the experimental load in material discovery. Investigating shape memory effect (SME) and validating process additive process parameters for a single novel composition is cost intensive in both time and consumed materials. Additionally, sub-optimal processing, oxygen, or solidification rate sensitivity could render additively manufacturing specimens without micro, macro cracks, or significant chemical variance impossible. Unfortunately, such failure susceptibility cannot be simulated. Therefore, a research pathway to validate novel shape memory alloy compositions for powder bed fusion additive manufacturing without the need for powdered feedstock is also proposed. This research investigates novel high temperature shape memory alloys for actuators without platinum group alloying elements to discover one that could be commercially viable as an additive manufacturing feedstock.

Sundermann, Tayler↗

An approach to simultaneous system design. II - Nonswitching gain and dynamic feedback compensation by algebraic geometric methods

This paper studies structured uncertainty problems in feedback system design, considers a compact parameterization of the space of linear dynamical systems and introduces 'base points' and 'critical points' as two algebraic-geometric objects that have significance in sensitivity and robustness studies, respectively. Using the Nevanlinna-Pick interpolation theory, the author obtains a necessary and sufficient condition for simultaneous stabilization of a structured one-parameter family of plants. A recent result due to Kharitonov, on the simultaneous stability of a parameterized family of polynomials, leads to a sufficiency condition for simultaneous stabilization of a structured multiparameter family of plants. Furthermore, the author considers 'simultaneous pole placement' of an r-tuple of plants as a means to arbitrarily tune the natural frequencies of a multimode linear dynamical system. The concept of 'nondegenerate' and 'twisted' r-tuples of plants is introduced as the pole placement problem is studied via Schubert enumerative geometry as an intersection problem on the associated Grassmannian. Various other design problems, viz., the strong stabilization problem and the dead beat control problem, are also considered.

Ghosh, Bijoy K.↗

Booster Main Engine Selection Criteria for the Liquid Fly-Back Booster

The Liquid Fly-Back Booster (LFBB) Program seeks to enhance the Space Shuttle system safety, performance and economy of operations through the use of an advanced, liquid propellant Booster Main Engine (BME). There are several viable BME candidates that could be suitable for this application. The objective of this study was to identify the key Criteria to be applied in selecting among these BME candidates. This study involved an assessment of influences on the overall LFBB utility due to variations in the candidate rocket-engines characteristics. This includes BME impacts on vehicle system weight, performance, design approaches, abort modes, margins of safety, engine-out operations, and maintenance and support concepts. Systems engineering analyses and trade studies were performed to identify the LFBB system level sensitivities to a wide variety of BME related parameters. This presentation summarizes these trade studies and the resulting findings of the LFBB design teams regarding the BME characteristics that most significantly affect the LFBB system. The resulting BME choice should offer the best combination of reliability, performance, reusability, robustness, cost, and risk for the LFBB program.

Ryan, Richard M.↗

Booster Main Engine Selection Criteria for the Liquid Fly-Back Booster

The Liquid Fly-Back Booster (LFBB) Program seeks to enhance the Space Shuttle system safety performance and economy of operations through the use of an advanced, liquid propellant Booster Main Engine (BME). There are several viable BME candidates that could be suitable for this application. The objective of this study was to identify the key criteria to be applied in selecting among these BME candidates. This study involved an assessment of influences on the overall LFBB utility due to variations in the candidate rocket engines' characteristics. This includes BME impacts on vehicle system weight, perfortnance,design approaches, abort modes, margins of safety, engine-out operations, and maintenance and support concepts. Systems engineering analyses and trade studies were performed to identify the LFBB system level sensitivities to a wide variety of BME related parameters. This presentation summarizes these trade studies and the resulting findings of the LFBB design teams regarding the BME characteristics that most significantly affect the LFBB system. The resulting BME choice should offer the best combination of reliability, performance, reusability, robustness, cost, and risk for the LFBB program.

Ryan, Richard M.↗

Genetic Algorithm-Guided, Adaptive Model Order Reduction of Flexible Aircrafts

This paper presents a methodology for automated model order reduction (MOR) of flexible aircrafts to construct linear parameter-varying (LPV) reduced order models (ROM) for aeroservoelasticity (ASE) analysis and control synthesis in broad flight parameter space. The novelty includes utilization of genetic algorithms (GAs) to automatically determine the states for reduction while minimizing the trial-and-error process and heuristics requirement to perform MOR; balanced truncation for unstable systems to achieve locally optimal realization of the full model; congruence transformation for "weak" fulfillment of state consistency across the entire flight parameter space; and ROM interpolation based on adaptive grid refinement to generate a globally functional LPV ASE ROM. The methodology is applied to the X-56A MUTT model currently being tested at NASA/AFRC for flutter suppression and gust load alleviation. Our studies indicate that X-56A ROM with less than one-seventh the number of states relative to the original model is able to accurately predict system response among all input-output channels for pitch, roll, and ASE control at various flight conditions. The GA-guided approach exceeds manual and empirical state selection in terms of efficiency and accuracy. The adaptive refinement allows selective addition of the grid points in the parameter space where flight dynamics varies dramatically to enhance interpolation accuracy without over-burdening controller synthesis and onboard memory efforts downstream. The present MOR framework can be used by control engineers for robust ASE controller synthesis and novel vehicle design.

Numerical Analysi↗

Design of LQG controllers with reduced parameter sensitivity

A method is presented for improving the tolerance of LQG controllers to parameter errors. The improvement is achieved by introducing terms reflecting the structure of the errors into the LQR cost function and the process and measurement noise models. Adjusting the sizes of these additional terms permits a tradeoff between robustness and nominal performance.

Lin, J. Y.↗

Trajectory Design of the Lunar Impactor Mission Concept

The National Aeronautics and Space Administration (NASA) solicited proposals in 2006 for an opportunity to include a small secondary payload with the launch of the Lunar Reconnaissance Orbiter (LRO) scheduled for October 2008. The cost cap of the proposal was between $50 and $80M, and the mass cap was 1,000 kilograms. JPL proposed a Lunar Impactor (LI) concept for this solicitation. The mission objective of LI was to impact the permanently shadowed region of a South polar crater ultimately to detect the presence of water. The detection of water ice would prove to be an important factor on future lunar exploration. NASA Ames Research Center also proposed a similar concept, the Lunar Crater observation and Sensing Satellite (LCROSS), which was selected by NASA for the mission. However, in this paper, the trajectory design of the LI proposed by JPL is considered. Since the LI spacecraft was to be launched on the LRO launch vehicle as a secondary payload, its initial trajectory must be diverted at some later time from the LRO trans-lunar trajectory for the subsequent impact. Several such trajectories have been considered, where each trajectory option fields some specific values for the mission parameters. The mission parameters include the availability of LRO instruments at the time of impact for the observation by LRO, the mission duration, the impact velocity, the impact angle, etc. It is possible for the LI to be deflected with a relatively low delta-V to impact a South polar crater at a reasonable impact velocity and impact angle directly with no delay. However, the instruments on-board LRO may not be ready for observation. Thus, several delayed trajectory options have been considered further. The lunar phase at the time of impact may also play an important factor for observation, especially from Earth. Several lunar flyby trajectory maneuvers have been identified to arrive at the Moon for impact at the desired lunar phase. By using a combination of these successive lunar flyby maneuvers, the impact lunar phase may be adjusted to the desired location. A few such trajectories have been suggested. Also, some attempts have been made to maximize the impact velocity by converting the impact trajectory into a retrograde orbit with respect to Earth. Since these types of trajectories take advantage of the Sun-Earth three-body region to minimize the delta-V, the mission duration is relatively long. A few such trajectories are suggested. Also, an attempt has been made to adjust the lunar impact within a desired time period for the optimum Earth observation for the above trajectories. The mission parameters resulting from each trajectory option above are considered and weighed against the cost and robustness of the mission in a brief summary.

trajectory design↗

Demonstration of Probabilistic Sensitivity Analyses Tools on the Structural Response of a Representative Inflatable Space Structure

This work provides an initial step toward demonstrating a probabilistic numerical simulation capability to support trade studies and the development of a certification plan for inflatable space habitats. This study concentrates on interpreting the results from probabilistic analysis and numerical simulation tools to identify parameter sensitivities for a novel inflatable airlock concept, specifically the Non‐Axisymmetric Inflatable Pressure Structure (NAIPS) that was designed and tested under NASA's Minimalistic Advanced Softgoods Hatch (MASH) Program. A brief overview of the finite element model is provided along with the probabilistic sensitivity analysis approach. The sensitivity studies required a model that was numerically stable and efficient enough that hundreds of simulations could be completed in the allotted time. Therefore, the existing full model was simplified by: extracting a quarter symmetry section of the dome; focusing on a single inflation pressure; and replacing the non‐linear material stress‐strain curves with linear, isotropic materials defined by elastic moduli. Responses of interest include the sensitivity of various structural component loads to material properties, cord lengths, inflation pressure and friction. Multiple sensitivity studies were completed and three are reported here. The first study focused on utilizing wide input parameter ranges to provide an opportunity to assess numerical robustness. The next two studies narrowed the parameter ranges to enable focus on understanding uncertainty at a fixed operating condition. The completion of the sensitivity studies improved understanding of the interdependence of multiple inputs on the responses. In addition, numerical stability of the simulations over wide parameter ranges, shows the feasibility of incorporating uncertainty‐based methods in the design and certification of inflatable space habitats. With the experience and trust gained, it is anticipated that these same methods will be applied to nonlinear, orthotropic models in the future.

Lyle, Karen H.↗

Uncertainty Quantification of a Rotorcraft Conceptual Sizing Toolsuite

A computational framework to support the quantification of system uncertainties and sensitivities for rotorcraft applications is presented using the NASA Design and Analysis of Rotorcraft (NDARC) conceptual sizing tool. A 90 passenger conceptual tiltrotor configuration was used for case demonstration in the modeling of uncertainties in NDARCs emission module. A non-intrusive forward propagation uncertainty quantification approach was applied to ensemble simulations using a Monte Carlo methodology with stratified Latin hypercube sampling. An off-the-shelf software, DAKOTA, which supports trade studies and design space exploration, including optimization, surrogate modeling and uncertainty analysis was used to address the research goals. A toolsuite was further developed incorporating DAKOTA with automated design processes and methods using function wrappers to execute program routines including support for data post-processing. Uncertainties in rotorcraft emissions modeling using the Average Temperature Response metric for a set mission profile were studied. It was shown that for the current study, using the base-line best estimate modeling parameters for the Average Temperature Response metric, NDARC under-estimates the effects of emissions when compared with results from Monte Carlo simulations. A global sensitivity analysis was further undertaken to quantify the contribution of the various emission species on output sensitivity, hence uncertainty. The work demonstrates that the developed toolsuite is robust and will support the quantification of system uncertainties and sensitivities in future rotorcraft design efforts.

Rotorcraft↗

Mixed Enthalpy–Entropy Descriptor for the Rational Design of Synthesizable High-Entropy Materials Over Vast Chemical Spaces

The practically unlimited high-dimensional composition space of high-entropy materials (HEMs) has emerged as an exciting platform for functional material design and discovery. However, the identification of stable and synthesizable HEMs and robust design rules remains a daunting challenge. Here, we propose a mixed enthalpy–entropy descriptor (MEED) that enables highly efficient, robust, high-throughput prediction of synthesizable HEMs across vast chemical spaces from first-principles. The MEED is based on two parameters: the relative formation enthalpy with respect to the most stable competing compound and the spread of the point-defect formation energy spectrum. The former measures the relative synthesizability of an HEM to its most stable competing phase, going beyond the conventional thermodynamic understanding. Further, the latter gauges the relative entropy forming ability of an HEM, entailing no sampling over numerous alloy configurations. By applying the MEED to two structurally distinct representative material systems (i.e., 3D rocksalt carbides and 2D layered sulfides), we not only successfully identify all experimentally reported HEMs within these systems but also reveal a cutoff criterion for assessing their relative synthesizability within each system. By the MEED, tens of new high-entropy carbides and 2D high-entropy sulfides are also predicted, which have the potential for a wide variety of applications such as coating in aerospace devices, energy conversion and storage, and flexible electronics.

36 MATERIALS SCIENCE↗

Data-Driven Tailoring Optimization of Thermoset Polymers Using Ultrasonics and Machine Learning

Thermoset polymers are highly demanded for their structural robustness, thermal stability, and chemical resistance. Tailoring the properties of these polymers for high-performance applications is often preferred to designing brand-new polymers. However, the traditional destructive techniques used to characterize their properties as a function of manufacturing parameters are expensive and time-consuming. A novel non-destructive, data-driven method leveraging ultrasonics and machine learning techniques to tailor the properties of thermosets as a function of the manufacturing parameters is demonstrated. Thermoset epoxy samples with varying curing temperatures (15–40 °C) and curing agent amounts (±40%) were manufactured and tested. Their curing kinetics were monitored by determining the sound speed in the material in real time, while the longitudinal modulus of the samples was determined post-cure. Machine learning models were developed using a k-nearest neighbors algorithm. These models were implemented to predict the curing and final elastic properties using the manufacturing parameters, i.e., stoichiometry and curing temperature, and vice versa. Understanding and modeling how these parameters affect the cure kinetics and final properties will allow for efficient and reliable optimization of thermoset tailoring and manufacturing.

36 MATERIALS SCIENCE↗

Design Under Uncertainty with Design-Dependent Uncertain Variables

Uncertainty quantification (UQ) can provide a more robust understanding of a system, leading to better informed decisions earlier in the design process. The additional information that UQ provides can be leveraged during a design optimization process known as design under uncertainty that, when incorporated with multidisciplinary design and optimization, can become computationally infeasible due to the large number of responses required for meaningful results. Previous work addressed reducing the computational expense in design under uncertainty by incorporating analytic derivatives throughout polynomial chaos expansion. Although this allows design under uncertainty to be feasible for more systems, some multidisciplinary systems have design-dependent uncertain variables. This paper details an implementation of design dependent uncertain variables in a manner than preserves derivatives required for efficient gradient-based optimization throughout the process. Two analytic examples of design-dependent uncertain variables are given: the first transforms a uniform uncertain variable with one design variable and the second transforms a normal uncertain variable with two design variables. The polynomial chaos expansion (PCE) results are comparable to both the Monte Carlo (MC) results and the analytic results for the two examples. A case study that maximizes the lift-to-drag ratio with a design-dependence between the wing leading edge sweep angle and uncertain parameter percentage of laminar flow is compared to a MC and alternative optimization formulations. This paper demonstrates that design-dependent uncertain variables are valid and hold throughout PCE.

robust design↗