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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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Activities leading to the detail design of a wind turbine generator having a nominal rating of 1.8 megawatts are reported. Topics covered include (1) system description; (2) structural dynamics; (3) stability analysis; (4) mechanical subassemblies design; (5) power generation subsystem; and (6) control and instrumentation subsystem.
The state-of-the-art interoperability between Building Information Modeling (BIM) and Building Energy Modeling (BEM) is mainly one-way. BEM software like EnergyPlus takes design input from BIM and simulates the energy consumption of the building. BIM, however, is unable to leverage energy simulation results from BEM smoothly. This lack of bi-directional interoperability between BIM and BEM prevents buildings from seeking more energy-efficient design options and limits BIM applications in optimal generative design. In this research, the authors have conducted the following activities related to two-way interoperability between BIM and BEM: (1) surveyed its current status through literature review, (2) investigated barriers to the bi-directional interoperability, and (3) suggested possible approaches to enable bi-directional interoperability and research outlook in the field. As a result, the authors have identified three main barriers to BIM BEM interoperability, namely, inefficient collaboration, limited scope in information transformation, and lack of BEM to BIM transformation. Future directions are suggested to address these barriers.
The design of a control system using the linear-quadratic regulator (LQR) control law theory for time invariant systems in conjunction with an incremental gradient procedure is presented. The incremental gradient technique reduces the full-state feedback controller design, generated by the LQR algorithm, to a realizable design. With a realizable controller, the feedback gains are based only on the available system outputs instead of being based on the full-state outputs. The design is for a remotely piloted research vehicle (RPRV) stability augmentation system. The design includes methods for accounting for noisy measurements, discrete controls with zero-order-hold outputs, and computational delay errors. Results from simulation studies of the response of the RPRV to a step in the elevator and frequency analysis techniques are included to illustrate these abnormalities and their influence on the controller design.
The Mod-OA wind turbine project which was to gain early experience in the operation of large wind turbines in a utility environment is discussed. The Mod-OA wind turbines were a first generation design, and even though not cost effective, the operating experience and performance characteristics had a significant effect on the design and development of the second and third generation machines. The Mod-OA machines were modified as a result of the operational experience, particularly the blade development and control system strategy. The results of study to investigate the interaction of a Mod-OA wind turbine with an isolated diesel generation system are discussed. The machine configuration, its advantages and disadvantages and the machine performance and availability are discussed.
Designers are increasingly using Generative Artificial Intelligence (GenAI) in design processes; however, knowing how designers use GenAI--especially in professional design practice--is under-explored. This paper presents an ethnographic study of a design team at NASA that explores the natural variation of GenAI use across team members during a speculative design workflow. We aimed to uncover when, how, and why GenAI tools were or were not employed using ethnographic observations to map the team's speculative design process and follow-up interviews to provide deeper insights into team members' interactions (or lackthereof) with GenAI. Through inductive qualitative coding, our analysis revealed three strategies of GenAI use observed among professional engineers and designers--intimate co-design with GenAI, selective delegation to GenAI, and minimal use of GenAI--as well as factors that appeared to influence their decisions whether or not to use GenAI. This study proposes new theory in human-AI collaboration that sheds light on the strategies, rationale, and circumstances under which design professionals use GenAI. Future work that builds upon these insights include examining a larger sample size of engineering and design professionals in uncontrolled design process experiences and exploring the impact that design tasks, goals, and constraints have on a participants decision to leverage GenAI tools.
An inviscid technique for designing forebodies which produce uniformly precompressed flows at the inlet entrance for bottom-mounted scramjets has been developed so that geometric constraints resulting from design trade-offs can be effectively evaluated. The flow fields resulting from several forebody designs generated in support of a hypersonic research airplane conceptual design study have been analyzed in detail with three-dimensional characteristics calculations to verify the uniform flow conditions. For the designs analyzed, uniform flow is maintained over a wide range of flight conditions (Mach number equals 4 to 10; angle of attack equals 6 deg to 10 deg) corresponding to scramjet operation flight envelope of the research airplane.
In this paper, a unique system level spacecraft design optimization will be presented. A Genetic Algorithm is used to design the global pattern of the reinforcing structure, while a gradient routine is used to adequately stiffen the sub-structure. The system level structural design includes determining the optimal physical location (and number) of reinforcing beams of a lunar pallet lander deck structure. Design of the substructure includes determining placement of secondary stiffeners and the number of rivets required for assembly.. In this optimization, several considerations are taken into account. The primary objective was to raise the primary natural frequencies of the structure such that the Pallet Lander primary structure does not significantly couple with the launch vehicle. A secondary objective is to determine how to properly stiffen the reinforcing beams so that the beam web resists the shear buckling load imparted by the spacecraft components mounted to the pallet lander deck during launch and landing. A third objective is that the calculated stress does not exceed the allowable strength of the material. These design requirements must be met while, minimizing the overall mass of the spacecraft. The final paper will discuss how the optimization was implemented as well as the results. While driven by optimization algorithms, the primary purpose of this effort was to demonstrate the capability of genetic algorithms to enable design automation in the preliminary design cycle. By developing a routine that can automatically generate designs through the use of Finite Element Analysis, considerable design efficiencies, both in time and overall product, can be obtained over more traditional brute force design methods.
Integration of computational fluid dynamics (CFD) for design and analysis of turbomachinery components is needed as the requirements of pump performance and reliability become more stringent for the new generation of rocket engine. A fast grid generator, designed specially for centrifugal pump impeller, which allows a turbomachinery designer to use CFD to optimize the component design will be presented. The CFD grid is directly generated from the impeller blade G-H blade coordinates. The grid points are first generated on the meridional plane with the desired clustering near the end walls. This is followed by the marching of grid points from the pressure side of one blade to the suction side of a neighboring blade. This fast grid generator has been used to optimize the consortium pump impeller design. A grid dependency study has been conducted for the consortium pump impeller. Two different grid sizes, one with 10,000 grid points and one with 80,000 grid points were used for the grid dependency study. The effects of grid resolution on the turnaround time, including the grid generation and completion of the CFD analysis, is discussed. The impeller overall mass average performance is compared for different designs. Optimum design is achieved through systematic change of the design parameters. In conclusion, it is demonstrated that CFD can be effectively used not only for flow analysis but also for design and optimization of turbomachinery components.
The design of gas generators intended to provide hot gases for turbine drive is discussed. Emphasis is placed on the design and operation of bipropellant gas generators because of their wider use. Problems and limitations involved in turbine operation due to temperature effects are analyzed. Methods of temperature control of gas turbines and combustion products are examined. Drawings of critical sections of gas turbines to show their operation and areas of stress are included.
Confirmation of the general trends of a previously reported parametric study of plutonia-fueled thermionic generators in a detailed 100-We generator design. The detailed design takes into account the additional weight of system-integration components and shows that design refinements of all aeroshell components are possible when a specific generator configuration is considered. An optimized 100-We thermionic power supply design is presented, reflecting a 0.98 reliability goal after five years of operation. The optimum multicell array consists of 28 isomite converters, each producing approximately 3.6 We at end-of-life. The optimum arrangement of converters in the aeroshell is a four-column, seven-row stacking configuration connected electrically as a two-column, 14-row array.
Flights were made in natural icing conditions at the NACA Ice Research Project, Minneapolis, Minn. to test several designs of thermal-electric propeller de-icing blade shoes and a hub-generator design. It was found that a minimum average unit power of 2.5 watts per square inch of blade-shoe area would protect the propeller blades at the test conditions. The most satisfactory blade shoe of the three designs tested extended to the 20-percent-chord point and to 90 percent of the blade radius. A concentration of heat in the leading-edge region of this shoe was found to reduce the power input necessary for satisfactory de-icing. A satisfactory thermal design of blade shoe and a hub generator of sufficient capacity were developed.
In this paper, we introduce a density-based topology optimization framework to design porous electrodes for maximum energy storage. We simulate the full cell with a model that incorporates electronic potential, ionic potential, and electrolyte concentration. The system consists of three materials, namely pure liquid electrolyte and the porous solids of the anode and cathode, for which we determine the optimal placement. We use separate electronic potentials to model each electrode, which allows interdigitated designs. As a result, a penalization is required to ensure that the anode and cathode do not touch, i.e., causing a short circuit. We compare multiple 2D designs generated for different fixed conditions, e.g. material properties. A 3D design with complex channel and interlocked structure is also created. All optimized designs are far superior to the traditional monolithic electrode design with respect to energy storage metrics. We observe up to a 750% increase in energy storage for cases with slow effective ionic diffusion within the porous electrode.
The considerations and the resultant approach used to implement design sensitivity capability for grids into a large scale, general purpose finite element system (MSC/NASTRAN) are presented. The design variables are grid perturbations with a rather general linking capability. Moreover, shape and sizing variables may be linked together. The design is general enough to facilitate geometric modeling techniques for generating design variable linking schemes in an easy and straightforward manner. Test cases have been run and validated by comparison with the overall finite difference method. The linking of a design sensitivity capability for shape variables in MSC/NASTRAN with an optimizer would give designers a powerful, automated tool to carry out practical optimization design of real life, complicated structures.
Computational design and analysis of three-dimensional hypersonic inlets with shape transition has been a significant challenge due to the complex geometry and grid required for three-dimensional viscous flow calculations. Currently, the design process utilizes an inviscid design tool to produce initial inlet shapes by streamline tracing through an axisymmetric compression field. However, the shape is defined by a large number of points rather than a continuous surface and lacks important features such as blunt leading edges. Therefore, a design system has been developed to parametrically construct true CAD geometry and link the topology of a structured grid to the geometry. The Adaptive Modeling Language (AML) constitutes the underlying framework that is used to build the geometry and grid topology. Parameterization of the CAD geometry allows the inlet shapes produced by the inviscid design tool to be generated, but also allows a great deal of flexibility to modify the shape to account for three-dimensional viscous effects. By linking the grid topology to the parametric geometry, the GridPro grid generation software can be used efficiently to produce a smooth hexahedral multiblock grid. To demonstrate the new capability, a matrix of inlets were designed by varying four geometry parameters in the inviscid design tool. The goals of the initial design study were to explore inviscid design tool geometry variations with a three-dimensional analysis approach, demonstrate a solution rate which would enable the use of high-fidelity viscous three-dimensional CFD in future design efforts, process the results for important performance parameters, and perform a sample optimization.
A commercially available 3-ton residential Lithium Bromide (LiBr) absorption air conditioner was modified for use with lower temperature solar heated water. The modification included removal of components such as the generator, concentration control chamber, liquid trap, and separator; and the addition of a Chrysler designed generator, an off-the-shelf LiBr-solution pump. The design goal of the modified unit was to operate with water as the heat-transfer fluid at a target temperature of 85 C (185 F), 29.4 C (85 F) cooling water inlet, producing 10.5 kW (3 tons) of cooling. Tests were performed on the system before and after modification to provide comparative data. At elevated temperatures (96 C, 205 F), the test results show that Lithium Bromide was carried into the condenser due to the extremely violent boiling and degraded the evaporator performance.
We demonstrate a multi-fidelity (MF) machine learning ensemble framework for the inverse design of photonic surfaces, trained on a dataset of 11,759 samples that we fabricate using high throughput femtosecond laser processing. The MF ensemble combines an initial low fidelity model for generating design solutions, with a high fidelity model that refines these solutions through local optimization. The combined MF ensemble can generate multiple disparate sets of laser-processing parameters that can each produce the same target input spectral emissivity with high accuracy (root mean squared errors < 2%). SHapley Additive exPlanations analysis shows transparent model interpretability of the complex relationship between laser parameters and spectral emissivity. Finally, the MF ensemble is experimentally validated by fabricating and evaluating photonic surface designs that it generates for improved efficiency energy harvesting devices. Our approach provides a powerful tool for advancing the inverse design of photonic surfaces in energy harvesting applications.
Generative artificial intelligence (AI) is emerging as a powerful tool for advancing the design of nanoporous materials such as metal–organic frameworks, covalent–organic frameworks, and zeolites. These materials have potential application in important areas such as carbon capture, catalysis, gas storage, chemical separation, and drug delivery due to their modular, tunable structures, and their performance in these areas depends on precise control over their structure, chemical functionalities, and properties. Herein, we provide a review of generative AI algorithms that are emerging as powerful tools for the design of nanoporous materials, namely generative adversarial networks, variational autoencoders, diffusion models, genetic algorithms, reinforcement learning, and large language models. Some models are particularly good at generating diverse and high-quality designs, while others excel at exploring large design spaces or optimizing materials with desired properties. Certain algorithms also allow for efficient transitions between different designs, and some offer versatility in generating materials based on textual input. We discuss the advantages, limitations, and applications of these algorithms in porous material design and emphasize the future potential of integrating AI with experimental workflows to accelerate the development and validation of AI-generated materials.
Household dishwashers must address several performance goals: maximize washing and drying performance, while minimizing cycle duration, energy consumption, and water consumption. This study develops and examines a novel thermoelectric heating and cooling (TEHC) system with thermal energy storage applied to a household dishwasher (DW), aiming to improve the energy and drying performance of a commercially-available dishwasher while maintaining its washing performance, water consumption, and cycle duration. Experimental testing conducted on the novel TEHC-DW system demonstrates an 8.7% reduction in total energy consumption, lowering the per-cycle usage to 0.952 kWh, and a 40% reduction in energy consumption for internal water heating. The novel TEHC-DW system also demonstrates better drying performance, shortening the drying time by 42% to reach the same remaining moisture content as a commercially-available system. In addition, a resistance-capacitance network model is developed that predicts total drying time, total energy consumption, and the highest temperature reached in the tub (53.4 °C). The model accuracy is validated with experimental data (within ±1 K), and the model functions as a design tool via a parametric study to evaluate the next-generation design and the effect of the number of thermoelectric modules and thermoelectric driving force (i.e., current). Overall, this study demonstrates the potential for TEHC technology to improve energy efficiency and drying performance in household dishwashers.