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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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ART Program First Quarter report for 2023. Entries for Fuels Development and Qualification, High Temperature Materials Development, Graphite Development and Qualification, and Design Methods Modeling and Validation.
The purpose of this paper is to provide an overview of the current trends and practices in small-satellite software verification and validation. This document is not intended to promote a specific software assurance method. Rather, it seeks to present an unbiased survey of software assurance methods used to verify and validate small satellite software and to make mention of the benefits and value of each approach. These methods include simulation and testing, verification and validation with model-based design, formal methods, and fault-tolerant software design with run-time monitoring. Although the literature reveals that simulation and testing has by far the longest legacy, model-based design methods are proving to be useful for software verification and validation. Some work in formal methods, though not widely used for any satellites, may offer new ways to improve small satellite software verification and validation. These methods need to be further advanced to deal with the state explosion problem and to make them more usable by small-satellite software engineers to be regularly applied to software verification. Last, it is explained how run-time monitoring, combined with fault-tolerant software design methods, provides an important means to detect and correct software errors that escape the verification process or those errors that are produced after launch through the effects of ionizing radiation.
By the 1960s, researchers began to investigate the feasibility of using active controls technology (ACT) for increasing the capabilities of military and commercial aircraft. Since then many researchers, too numerous to mention, have investigated and demonstrated the usefulness of ACT for favorably modifying the aeroelastic response characteristics of flight vehicles. As a result, ACT entered the limelight as a viable tool for answering some very difficult design questions and had the potential for obtaining structural weight reductions optimizing maneuvering performance, and satisfying the multimission requirements being imposed on future military and commercial aircraft designs. Over the past 40 years, the NASA Langley Research Center (LaRC) has played a major role in developing ACT in part by its participation in many wind-tunnel programs conducted in the Transonic Dynamics Tunnel (TDT). These programs were conducted for the purposes of: (1) establishing concept feasibility; (2) demonstrating proof of concept; and (3) providing data for validating new modeling, analysis, and design methods. This paper provides an overview of the ACT investigations conducted in the TDT. For each program discussed herein, the objectives of the effort, the testing techniques, the test results, any, signIficant findings, and the lessons learned with respect to ACT testing are presented.
Adaptive and self-optimizing intelligent systems such as digital twins are increasingly important in science and engineering. Digital twins utilize mathematical models to provide added precision to decision-making. However, physics-informed models are challenging to build, calibrate, and validate with existing data science methods. Model-based design of experiments (MBDoE) is a popular framework for optimizing data collection to maximize parameter precision in mathematical models and digital twins. In this work, we apply MBDoE, facilitated by the open-source package Pyomo.DoE, to train and validate mathematical models for batch crystallization. We quantitatively examined the estimability of the model parameters for experiments with different cooling rates. This analysis provides a quantitative explanation for the heuristic of using multiple experiments at different cooling rates.
This technical publication describes the methodology, model, software tool, input data, and analysis result that support aerospace design reliability studies. The focus of these activities is on propulsion systems mechanical design reliability. The goal of these activities is to support design from a reliability perspective. Paralleling performance analyses in schedule and method, this requires the proper use of metrics in a validated reliability model useful for design, sensitivity, and trade studies. Design reliability analysis in this view is one of several critical design functions. A design reliability method is detailed and two example analyses are provided-one qualitative and the other quantitative. The use of aerospace and commercial data sources for quantification is discussed and sources listed. A tool that was developed to support both types of analyses is presented. Finally, special topics discussed include the development of design criteria, issues of reliability quantification, quality control, and reliability verification.
A number of new aircraft concepts have recently been proposed which tightly couple the propulsion system design and operation with the overall vehicle design and performance characteristics. These concepts include propulsion technology such as boundary layer ingestion, hybrid electric propulsion systems, distributed propulsion systems and variable cycle engines. Initial studies examining these concepts have typically used a traditional decoupled approach to aircraft design where the aerodynamics and propulsion designs are done a-priori and tabular data is used to provide inexpensive look ups to the trajectory ana-ysis. However the cost of generating the tabular data begins to grow exponentially when newer aircraft concepts require consideration of additional operational parameters such as multiple throttle settings, angle-of-attack effects on the propulsion system, or propulsion throttle setting effects on aerodynamics. This paper proposes a new modeling approach that eliminated the need to generate tabular data, instead allowing an expensive propulsion or aerodynamic analysis to be directly integrated into the trajectory analysis model and the entire design problem optimized in a fully coupled manner. The new method is demonstrated by implementing a canonical optimal control problem, the F-4 minimum time-to-climb trajectory optimization using three relatively new analysis tools: Open M-DAO, PyCycle and Pointer. Pycycle and Pointer both provide analytic derivatives and Open MDAO enables the two tools to be combined into a coupled model that can be run in an efficient parallel manner that helps to cost the increased cost of the more expensive propulsion analysis. Results generated with this model serve as a validation of the tightly coupled design method and guide future studies to examine aircraft concepts with more complex operational dependencies for the aerodynamic and propulsion models.
Structural models are usually tested by comparing their response with that of a reference structure (an actual structure or a more refined model) to a limited number of arbitrary loads. This test is not always reliable because the loads are arbitrary. An antioptimization-based method is proposed to test structural models. This method compares a structural model with a reference model or an actual structure under the worst loading case that maximizes the error in the model. Specifically, the method identifies the loading case that maximizes the difference between the responses of two models of the same structure using optimization. This method can be used to design experiments in order to validate a structural model. It can also be applied to identify damage in a structure by determining the load that maximizes the difference in the behavior of the damaged and the intact structure. The proposed method is illustrated by applying it to a plate and an automotive structure.
Full text of publication follows. Due to the ever-increasing safety requirements, the current trend of nuclear reactor analysis is shifting towards high-fidelity multi-physics models, which have a very high computational cost and modelling complexity. As the cost of even a single model run makes it impossible to analyse the behaviour and performance of these models on large-scale commercial plants, it has become even more significant to provide suitable benchmarks to validate and test them extensively. In this sense, research reactors offer a promising solution for the initial validation of high-fidelity models, as they are significantly smaller than commercial reactors and their characteristics are well known. In particular, the reactors of the TRIGA family have been used to assess and validate models and methods for Generation-IV designs, as they have some similar features (such as the dominance of natural convection as cooling mechanism and the difficulties in performing sub-channel analysis using standard codes). Still, the computational requirements of high-fidelity models make them unsuitable for real-time analysis, even following their assessment on research reactors. In this sense, Model Order Reduction (MOR) techniques give an additional strategy to reduce the computational cost of high-fidelity models (whilst preserving sufficient accuracy). In particular, this work focuses on Dynamic Mode Decomposition (DMD), a non-intrusive MOR technique that aims at representing models with explicit temporal dynamics by extracting the time-varying characteristics and the governing structures based only on a set of available data, thus without needing any underlying knowledge of the governing equations. In addition, DMD also computes a low-dimensional surrogate of the dynamic matrix of the system, making it suited for stability analysis and real-time evaluations. This work focuses on the application and validation of the DMD method on the Computational Fluid-Dynamics (CFD) model TRIGA Mark II reactor, also discussing in detail the potentiality of this algorithm as an advanced modelling tool for nuclear reactor analysis. (author)
Over the past quarter century, the NASA Langley Research Center (LaRC) and the NASA Dryden Flight Research Center (DFRC) have played major roles in the development, demonstration, and validation of aeroservoelastic modeling, analysis, design, and testing methods. Many of their contributions resulted from their participation in wind-tunnel and flight-test programs aimed at demonstrating advanced active control concepts that interact with and/or exploit the aeroelastic characteristics of flexible structures. Other contributions are a result of their interest in identifying and solving adverse aeroservoelastic interactions that allow unique flight-test demonstrations or flight envelope clearance programs to be successfully completed. This paper provides an overview of some of the more interesting aeroservoelastic investigations conducted in the transonic dynamics tunnel (TDT) at LaRC and in flight at DFRC. Four flight-test projects are reviewed in this paper. These test projects were selected because of their contributions to the state-of-the-art in active controls technology (ACT) or because of the knowledge gained in further understanding the complex mechanisms that cause adverse aeroservoelastic interactions.
This paper describes the methodology, model, input data, and analysis results of a reusable launch vehicle engine operability study conducted with the goal of supporting design from an operations perspective. Paralleling performance analyses in schedule and method, this requires the use of metrics in a validated operations model useful for design, sensitivity, and trade studies. Operations analysis in this view is one of several design functions. An operations concept was developed given an engine concept and the predicted operations and maintenance processes incorporated into simulation models. Historical operations data at a level of detail suitable to model objectives were collected, analyzed, and formatted for use with the models, the simulations were run, and results collected and presented. The input data used included scheduled and unscheduled timeline and resource information collected into a Space Transportation System (STS) Space Shuttle Main Engine (SSME) historical launch operations database. Results reflect upon the importance not only of reliable hardware but upon operations and corrective maintenance process improvements.
The solar farm is garnering attention for its contribution to ecosystem services, particularly in supporting pollinators. Although numerous studies have focused on the distinct microclimates of solar farms, there has been limited effort to validate and model the impact of these conditions on insects [1]. To effectively evaluate and leverage the ecosystem services from solar farms in policymaking, understanding how insects react to microclimate variations in diverse designs and management methods is essential. This study aims to validate and model the impact of temperature and shade at solar farms on pollinator populations and their frequency of pollination as well as compare the potential for increased pollination under different types of panels within a solar grazing setup.
A time-series technique is presented for identifying the dynamic characteristics of the human operator in manual control tasks from relatively short records of experimental data. Control of system excitation signals used in the identification is not required. The approach is a multi-channel identification technique for modeling multi-input/multi-output situations. The method presented includes statistical tests for validity, is designed for digital computation, and yields estimates for the frequency responses of the human operator. A comprehensive relative power analysis may also be performed for validated models. This method is applied to several sets of experimental data; the results are discussed and shown to compare favorably with previous research findings. New results are also presented for a multi-input task that has not been previously modeled to demonstrate the strengths of the method.
A time-series technique is presented for identifying the dynamic characteristics of the human operator in manual control tasks from relatively short records of experimental data. Control of system excitation signals used in the identification is not required. The approach is a multi-channel identification technique for modeling multi-input/multi-output situations. The method presented includes statistical tests for validity, is designed for digital computation, and yields estimates for the frequency response of the human operator. A comprehensive relative power analysis may also be performed for validated models. This method is applied to several sets of experimental data; the results are discussed and shown to compare favorably with previous research findings. New results are also presented for a multi-input task that was previously modeled to demonstrate the strengths of the method.
It has long been established in the literature that the buckling response of thin-shell structures can be very sensitive to the presence of small geometric and loading imperfections. The Shell Buckling Knockdown Factor Project (SBKF) was established by the NASA Engineering and Safety Center (NESC) to develop analysis-based shell buckling design recommendations for stiffened-metallic and composite launch-vehicle shell structures. Large-scale buckling tests were used to validate the modeling and analysis methods applied in developing these analysis-based recommendations. Herein, the test article design methodology for 8-ft-diameter, honeycomb-core sandwich composite cylinder validation tests is discussed and cylinder designs are presented. In this methodology, first, the sandwich composite design space was defined using several nondimensional parameters, and the desired test article design space was determined by examining the designs of launch-vehicle cylinder structures. Essentially all test article designs within certain design parameters were generated and then downselected based on simple closed-form failure calculations and the nondimensional design-space parameters. Four of these designs that spanned a significant portion of the design space of interest and had global buckling as the first predicted failure mode were selected and subjected to higher-fidelity finite element analyses (FEAs): shell-element-based analyses, axisymmetric-element-based analyses, and global-local analyses. The analysis flow discussed in this report supported the design objective. As the analysis flow progressed, designs were downselected so the fidelity of the analysis methods, and consequently their computational cost and accuracy, was increased. The selection of the FEA types created an analysis framework where particular methods complemented each other and reduced the uncertainty of the predicted test article responses. The analysis results are illustrated using several designs when the computationally expeditious closed-form analysis stage is discussed. Once this stage is complete, the higher-fidelity FEA types are illustrated using one selected detailed test article design. Both perfect and imperfect test article geometries were considered.
Analysis serves many roles in the Active Aeroelastic Wing (AAW) program. It has been employed to ensure safe testing of both a flight vehicle and wind tunnel model, has formulated models for control law design, has provided comparison data for validation of experimental methods and has addressed several analytical research topics. Aeroelastic analyses using mathematical models of both the flight vehicle and the wind tunnel model configurations have been conducted. Static aeroelastic characterizations of the flight vehicle and wind tunnel model have been produced in the transonic regime and at low supersonic Mach numbers. The flight vehicle has been analyzed using linear aerodynamic theory and transonic small disturbance theory. Analyses of the wind-tunnel model were performed using only linear methods. Research efforts conducted through these analyses include defining regions of the test space where transonic effects play an important role and investigating transonic similarity. A comparison of these aeroelastic analyses for the AAW flight vehicle is presented in this paper. Results from a study of transonic similarity are also presented. Data sets from these analyses include pressure distributions, stability and control derivatives, control surface effectiveness, and vehicle deflections.
Turbulent flow of supercritical hydrogen through a uniformly heated circular tube has been investigated using numerical methods, for the range of 4 x 10(exp 5) less than Re less than 3 x 10(exp 6), 5 less than or equal to q(sub W) less than or equal to 10 MW/sq m, 30 less than or equal to T(sub in) less than or equal to 90 K, and 5 less than or equal to P(sub in) less than or equal to 15 MPa. The purpose is to validate a turbulence model and calculation method for the design of active cooling systems of hydrogen-fueled hypersonic aircraft, where the hydrogen fuel a used as coolant. The PHOENICS software package was used for the computations, which required special provision for evaluation of the thermophysical properties of the supercritical hydrogen, and a low Reynolds number form of the k-epsilon turbulence model. Pressure drop and heat transfer data were compared with experiment and existing correlations and good agreement was demonstrated. For the pressure range considered here a "thermal spike" was observed and shown to be due to the secondary peak in specific heat, rather than the primary peak.
As part of the NASA Aviation Safety Program at Langley Research Center, a dynamically scaled unmanned aerial vehicle (UAV) and associated ground based control system are being developed to investigate dynamics modeling and control of large transport vehicles in upset conditions. The UAV is a 5.5% (seven foot wingspan), twin turbine, generic transport aircraft with a sophisticated instrumentation and telemetry package. A ground based, real-time control system is located inside an operations vehicle for the research pilot and associated support personnel. The telemetry system supports over 70 channels of data plus video for the downlink and 30 channels for the control uplink. Data rates are in excess of 200 Hz. Dynamic scaling of the UAV, which includes dimensional, weight, inertial, actuation, and control system scaling, is required so that the sub-scale vehicle will realistically simulate the flight characteristics of the full-scale aircraft. This testbed will be utilized to validate modeling methods, flight dynamics characteristics, and control system designs for large transport aircraft, with the end goal being the development of technologies to reduce the fatal accident rate due to loss-of-control.
The development and experimental validation of a method for analytically modeling the noise mechanism in the helicopter geared power transmission systems is described. This method can be used within the design process to predict interior noise levels and to investigate the noise reducing potential of alternative transmission design details. Examples are discussed.