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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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Propeller slipstream effects as determined from wing pressure distribution of a large-scale six-propeller vtol model at static thrust
Static aerodynamic loads measurements from wind tunnel tests of a full-scale upper surface blown jet flap configuration are presented. The measured loads are compared with calculations using a method for predicting longitudinal aerodynamic characteristics of upper surface blown jet flap configurations.
The integration of nuclear power into energy systems presents a promising avenue to address the growing global energy demands while minimizing greenhouse gas emissions. In this paper, we introduce a data-driven quasi-static surrogate model for nuclear-powered Integrated Energy Systems (IES) that comprises various components, including a small modular reactor (SMR), energy manifold (EM), balance of plant (BOP), high-temperature steam electrolysis (HTSE), and district heating (DH) system. Traditional physics-based models for these components often entail significant computational overhead and time consumption, necessitating the development of efficient surrogate models. The development of a complete surrogate model for the IES involves the creation of individual surrogate models for each component, leveraging machine learning techniques and simulated data. These isolated surrogate models are subsequently integrated, enabling a holistic view of the IES and reducing the computational burden associated with detailed physics-based simulations. This paper outlines the development process, validation, and the performance evaluation of the surrogate models. The findings shed light on the accuracy and applicability of the surrogate models in practical scenarios, demonstrating their potential to expedite the analysis of nuclear-powered IES and inform future research and development efforts.
The integration of nuclear power into energy systems presents a promising avenue to address the growing global energy demands while minimizing greenhouse gas emissions. In this paper, we introduce a data-driven quasi-static surrogate model for nuclear-powered Integrated Energy Systems (IES) that comprises various components, including a small modular reactor (SMR), steam manifold, balance of plant (BOP), high-temperature steam electrolysis (HTSE), and district heating (DH) system. Traditional physics-based models for these components often entail significant computational resource and time consumption, necessitating the development of efficient surrogate models. The development of a complete surrogate model for the IES involves the creation of individual surrogate models for each component, leveraging machine learning techniques and simulated data. These isolated surrogate models are subsequently integrated, enabling a holistic view of the IES and reducing the computational burden associated with detailed physics-based simulations. This paper outlines the development process, validation, and the performance evaluation of the surrogate models. The exceptional performance, with low root-mean-squared errors and R-squared scores of at least 99.8% across all individual surrogate models, underscores their accuracy and practical applicability. These results demonstrate the potential of these models to expedite the analysis of nuclear-powered IES, offering insights that can shape future research and development efforts.
A helical actuator driven by biased shape memory alloy (SMA) patterns embedded into a soft composite ribbon base is presented in this work. Instead of common U-shape SMA wires, a single SMA wire is woven into planar patterns, which enable helical deformation of the composite ribbon from an initially flat geometry. An analytical static model is established for accurate and rapid prediction of the helical reconfiguration arising from the shape memory effect of woven SMA patterns, followed by validation of the static model using the finite element method (FEM). The finite element results are compared with the analytical solutions given by this static model, which show a high agreement. Parametric study of the influences of eight independent design variables on the dependent helical parameters, such as combined curvatures, pitches, and helical angles, is completed. It is found that the helically deformed geometry is mainly dominated by diameters, biased positions, inclined angles, and numbers of skewed segments of the SMA wire. Fabrication and in-situ experimental test of a prototype of such helical actuators qualitatively demonstrate its dramatic three-dimensional (3D) spiral reconfiguration from a two-dimensional (2D) flat ribbon. In conclusion, such SMA patterns will allow more diverse designs of soft actuators for a wider range of robotic applications.
The NATO Human View is a system architectural viewpoint that focuses on the human as part of a system. Its purpose is to capture the human requirements and to inform on how the human impacts the system design. The viewpoint contains seven static models that include different aspects of the human element, such as roles, tasks, constraints, training and metrics. It also includes a Human Dynamics component to perform simulations of the human system under design. One of the static models, termed Human Networks, focuses on the human-to-human communication patterns that occur as a result of ad hoc or deliberate team formation, especially teams distributed across space and time. Parameters of human teams that effect system performance can be captured in this model. Human centered aspects of networks, such as differences in operational tempo (sense of urgency), priorities (common goal), and team history (knowledge of the other team members), can be incorporated. The information captured in the Human Network static model can then be included in the Human Dynamics component so that the impact of distributed teams is represented in the simulation. As the NATO militaries transform to a more networked force, the Human View architecture is an important tool that can be used to make recommendations on the proper mix of technological innovations and human interactions.
Preliminary geothermal reservoir simulations were performed using a homogeneous static model to evaluate and understand the effects of fluid and rock properties that could influence the delivery of thermal energy in a doublet system. A 5000 feet by 5100 feet by 500 feet homogeneous model having a constant porosity and permeability of 20% and 100 mD was used to perform preliminary geothermal reservoir simulations. The model was discretized in the x-, y-, and z-directions into 100, 101, and 100, gridblocks. Two wells were placed on the opposite ends of the central column of the discretized model. One of the wells was designated as a producer and the other an injector. Equal volumes of water was extracted and then injected into the reservoir via the production and injection wells. Water was extracted at a temperature of 109 deg F and re-injected at 50 deg F at the 1000 bbl/day. The files attached contains the input and output files of this simulation case. The input and some of the output files can be viewed in any text editor.
A simple, rational approach is presented for developing continuum models for large repetitive lattice structures subjected to static and dynamic loadings. The procedure involves introducing kinematic assumptions to reduce the dimensionality of the lattice, and equating the strain and kinetic energies of the continuum model to those of the original lattice structure. The proposed procedure is applied to obtain effective elastic and dynamic characteristics of continuum plate models for double-layered grids. Numerical results are presented of stress and free vibration problems for two double-layered grids. These problems demonstrate the high accuracy of the continuum plate models developed. Also, an assessment is made of different approximations to these models.
This paper provides an approach to answer the question of whether one can rely solely on static data taken during a transonic model test to provide the certainty needed that a new aircraft will or will not have Abrupt Wing Stall (AWS) events during its flight operations. By comparing traditional- and alternate-static-Figures of Merit (FOMs) with the Free-To-Roll (FTR) response data, a rational basis for assessing the merits of using standard testing techniques for the prediction of AWS events has been established. Using the FTR response data as a standard, since these results compare well with flight, the conclusion from this study is that neither traditional nor alternate FOMs can be trusted to provide an indication as to whether a configuration will or will not have AWS tendencies. Even though these FOMs may flag features which have a high degree of correlation with the FTR response data, there are as many or more of these FOM flagged features which do not correlate. Thus, one needs to use the FTR rig to assess AWS tendencies on new configurations.
Static strain measurements are relevant for Integrated System Health Monitoring of civil structures, aircrafts, power plants and advanced manufacturing equipment, with implications for safety, process efficiency, and maintenance costs. Wireless strain sensing is highly desirable where the presence of wires poses significant safety concerns, increases maintenance, and thus overall costs, or where they are not feasible, such as in applications which contain moving parts. This paper presents wireless interrogation of surface acoustic wave resonators (SAWRs) fabricated on langasite (LGS) along Euler angles (0°, 138.5°, 32.9°) and aimed at the detection of static strain at hightemperature (HT, above 100°C). Both commercial HT strain gauges and finite element analysis (FEA Abaqus software) were used and compared for SAWR strain calibration from room temperature (RT) to HT. In addition, this work investigated a compromise between high temperature operation vs. sensitivity based on the thickness of ceramic adhesive used. For instance, a reduction in the adhesive thickness from about 150 μm to 135 μm, resulted in a 39% increase in sensitivity at RT. It was also observed that the sensitivity dropped up to 34% from RT to 200°C. Furthermore, wireless operation, calibration, and increase in sensitivity constitute important advances in the use of LGS SAW devices to monitor static stress in high-temperature harsh environments.
The theoretical quasi-static model of the solar corona during sunspot minimum developed in an earlier paper (Osherovich et al., 1984) is extended to include a quasi-radial outflow. The requirement imposed in the above paper on a plasma flow is relaxed. The dynamic equation derived for the combination of a dipole-like and a radial field is used to calculate the electric current density around the sun in the region 1.5-5 solar radii. Comparison with the current density given by the quasi-static model shows that the outflow decreases the current density only slightly in the dynamic case. The dynamic coronal model with a magnetic quadrupole field is also considered, in relation to the north-south asymmetry in the solar corona.
The present work addresses the development of an experimental and computational procedure for validating finite element models. A torus structure, part of an inflatable/rigidizable Hexapod, is used to demonstrate the approach. Because of fabrication, materials, and geometric uncertainties, a statistical approach combined with optimization is used to modify key model parameters. Static test results are used to update stiffness parameters and dynamic test results are used to update the mass distribution. Updated parameters are computed using gradient and non-gradient based optimization algorithms. Results show significant improvements in model predictions after parameters are updated. Lessons learned in the areas of test procedures, modeling approaches, and uncertainties quantification are presented.
Intensities of auroral and magnetospheric hiss generated by the Cherenkov radiation process of electrons in the lower magnetosphere were calculated with respect to a realistic model of the earth's magnetosphere. In this calculation, the magnetic field was expressed by the Mead-Fairfield Model, and a static model of the iono-magnetospheric plasma distribution was constructed by accumulated data obtained by recent satellite observations. The energy range of hiss producing electrons and the frequency range of produced VLF in the computation are 100 eV to 200 keV, and 2 to 200 kHz, respectively. The maximum hiss intensity produced by soft electrons is more than one order higher than that of hard electron produced hiss. Higher rate of hiss occurrence in the daytime side, particularly in the soft electron precipitation zone in the morning sector, and less association of auroral hiss in nighttime sectors must be, therefore, due to the local time dependence of the energy spectra of precipitating electrons rather than the difference in the geomagnetic field and in the geoplasma distributions.
Computing systems are employed for aerospace applications with high reliability requirements. In order to provide the needed reliability, it was necessary to make use of computing systems with fault-tolerance characteristics. Traditionally, fault tolerance is achieved through the use of hardware redundance. However, fault-tolerant techniques based on suitable software design considerations have also been developed. The present paper is concerned with the major issues arising in the context of an application of fault-tolerant software techniques to dynamic systems. Attention is given to fault-tolerant flight software, software component stability, system stability with fault-tolerant software, the preservation of functional performance, N-version vs. recovery blocks in flight software, systems-based software, static and dynamic models, static and dynamic consistency tests, and recovery block initialization.
The derivation of the magnetosphere configuration is discussed, with consideration given to both descriptive models, which represent the observed magnetic field B and perhaps the electric field E, and physical models, which also include plasma effects. Consideration is given to global field models, static physical magnetohydrostatic models, slowly variable E, and MHD tail models, and to the type of data used for their derivation. It is emphasized that the current trend in derivation of magnetospheric models is for incorporating more physics( e.g., V x B) to match regions of observed current flow, plasma pressure obeying equilibrium conditions, E linked to interplanetary sources, and time-dependent convective flows.
The physical modeling of active regions (ARs) and of the global coronal is receiving increasing interest lately. Recent attempts to model ARs using static equilibrium models were quite successful in reproducing AR images of hot soft X-ray (SXR) loops. They however failed to predict the bright EUV warm loops permeating ARs: the synthetic images were dominated by intense footpoint emission. We demonstrate that this failure is due to the very weak dependence of loop temperature on loop length which cannot simultaneously account for both hot and warm loops in the same AR. We then consider time-dependent AR models based on nanoflare heating. We demonstrate that such models can simultaneously reproduce EUV and SXR loops in ARs. Moreover, they predict radial intensity variations consistent with the localized core and extended emissions in SXR and EUV AR observations respectively. We finally show how the AR morphology can be used as a gauge of the properties (duration, energy, spatial dependence, repetition time) of the impulsive heating.
An analytical/numerical method has been developed to predict the static thrust performance of non-axisymmetric, two-dimensional convergent-divergent exhaust nozzles. Thermodynamic nozzle performance effects due to over- and underexpansion are modeled using one-dimensional compressible flow theory. Boundary layer development and skin friction losses are calculated using an approximate integral momentum method based on the classic karman-Polhausen solution. Angularity effects are included with these two models in a computational Nozzle Performance Analysis Code, NPAC. In four different case studies, results from NPAC are compared to experimental data obtained from subscale nozzle testing to demonstrate the capabilities and limitations of the NPAC method. In several cases, the NPAC prediction matched experimental gross thrust efficiency data to within 0.1 percent at a design NPR, and to within 0.5 percent at off-design conditions.
For large-scale interconnected power systems that cover large geographical areas, certain electrical studies are required so that appropriate decisions ensure system reliability and low cost. For such studies, it is often neither practical nor necessary to model in detail the entire power system, which is increasingly complex due to a more diverse range of grid assets to choose from in both short and long-term planning. The goal of this paper is to present a methodology to reduce the order of large-scale power networks based on spectral graph theory given that current methods for static network reduction are not scalable. A brief analysis of some spectral clustering properties to determine which graph Laplacian matrix should be used and why is included. The analysis shows that the utilization of the normalized graph Laplacian is more advantageous for clustering purposes. Techniques are proposed to approximate cost functions for the aggregated generators. This is done via linear regression. The reduced-order model obtained with the proposed methodology has an accuracy above 94% and solves the scalability issue commonly present in other reduction methods. If the utilization of the reduced-order model is either constrained to load levels above mid-peak demand, or cost functions of aggregated units are approximated via a piecewise quadratic approach, then the error distribution is in the order of 10^-3. .