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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 487 records · Page 27

Integrated residential photovoltaic array development

Sixteen conceptual designs of residential photovoltaic arrays are described. Each design concept was evaluated by an industry advisory panel using a comprehensive set of technical, economic and institutional criteria. Key electrical and mechanical concerns that effect further array subsystem development are also discussed. Three integrated array design concepts were selected by the advisory panel for further optimization and development. From these concepts a single one will be selected for detailed analysis and prototype fabrication. The three concepts selected are: (1) An array of frameless panels/modules sealed in a T shaped zipper locking neoprene gasket grid pressure fitted into an extruded aluminum channel grid fastened across the rafters. (2) An array of frameless modules pressure fitted in a series of zipper locking EPDM rubber extrusions adhesively bonded to the roof. Series string voltage is developed using a set of integral tongue connectors and positioning blocks. (3) An array of frameless modules sealed by a silicone adhesive in a prefabricated grid of rigid tape and sheet metal attached to the roof.

Royal, G. C., III↗

Preliminary Design of a Manned Nuclear Electric Propulsion Vehicle Using Genetic Algorithms

Nuclear electric propulsion (NEP) vehicles will be needed for future manned missions to Mars and beyond. Candidate designs must be identified for further detailed design from a large array of possibilities. Genetic algorithms have proven their utility in conceptual design studies by effectively searching a large design space to pinpoint unique optimal designs. This research combined analysis codes for NEP subsystems with a genetic algorithm. The use of penalty functions with scaling ratios was investigated to increase computational efficiency. Also, the selection of design variables for optimization was considered to reduce computation time without losing beneficial design search space. Finally, trend analysis of a reference mission to the asteroids yielded a group of candidate designs for further analysis.

Irwin, Ryan W.↗

Global cost and weight evaluation of fuselage keel design concepts

The Boeing program entitled Advanced Technology Composite Aircraft Structure (ATCAS) is focused on the application of affordable composite technology to pressurized fuselage structure of future aircraft. As part of this effort, a design study was conducted on the keel section of the aft fuselage. A design build team (DBT) approach was used to identify and evaluate several design concepts which incorporated different material systems, fabrication processes, structural configurations, and subassembly details. The design concepts were developed in sufficient detail to accurately assess their potential for cost and weight savings as compared with a metal baseline representing current wide body technology. The cost and weight results, along with an appraisal of performance and producibility risks, are used to identify a globally optimized keel design; one which offers the most promising cost and weight advantages over metal construction. Lastly, an assessment is given of the potential for further cost and weight reductions of the selected keel design during local optimization.

Flynn, B. W.↗

Design of optimal probing signals for vector parameter estimation.

In the design of optimal inputs or probing signals for parameter estimation, it is more natural to consider functions of the Fisher information matrix as the criterion of optimality instead of some function of the error covariance matrix. The input which maximizes the Fisher information measure for efficient estimation of a scalar parameter also provides the minimum error variance. The information is thus a logical choice for the optimality criterion in scalar problems. No such obvious choice is apparent for vector parameter estimation. A number of performance measures are examined and compared in the present study, and a useful criterion is selected. The design of an optimal probing signal using this criterion is shown to be equivalent to an optimal control problem in which certain equality constraints must be satisfied. This problem may be solved by conventional techniques of deterministic or stochastic optimal control.

Nahi, N. E.↗

Optimal design of compact spur gear reductions

The optimal design of compact spur gear reductions includes the selection of bearing and shaft proportions in addition to gear mesh parameters. Designs for single mesh spur gear reductions are based on optimization of system life, system volume, and system weight including gears, support shafts, and the four bearings. The overall optimization allows component properties to interact, yielding the best composite design. A modified feasible directions search algorithm directs the optimization through a continuous design space. Interpolated polynomials expand the discrete bearing properties and proportions into continuous variables for optimization. After finding the continuous optimum, the designer can analyze near optimal designs for comparison and selection. Design examples show the influence of the bearings on the optimal configurations.

Savage, M.↗

Robust Trajectory Optimization for Guided Powered Descent and Landing

A robust trajectory optimization approach for guidance algorithm gain selection for powered descent and landing is developed. This approach uses a genetic algorithm to determine optimal guidance algorithm parameters while incorporating uncertainty information from linear covariance analysis. The optimal guidance algorithm parameters are determined while accounting for environment, navigation, and vehicle property uncertainty and sensor suite fidelity. As a demonstration of this method, the optimal gains for the fractional polynomial powered descent guidance are found for the braking phase of a robotic lunar landing mission. Scenarios with differing sensor suites and sensor qualities are considered, with objective functions to minimize variability in propellant usage or terminal position. Results show that the optimal guidance algorithm gains for a given trajectory differ based on the sensor suite, and optimal guidance algorithm gains may result in up to 20% performance improvements over the baseline in propellant usage and landed accuracy.

Grace E Calkins↗

Exploring Applications of Machine Learning for Wildfire Monitoring and Detection using Unmanned Aerial Vehicles

Wildfires are increasing in frequency and severity around the world, including the United States. The losses caused by wildfires could be mitigated if high-risk areas, hotspots, and flare-ups could be monitored continuously, such as through the use of Unmanned Aerial Vehicles (UAVs). This paper documents exploratory efforts using machine learning to determine efficient flight paths for UAVs and to detect wildfires using image classification. On path planning, three machine learning techniques—Genetic Algorithm, Simulated Annealing, and Dynamic Programming—were explored. Genetic Algorithm was found to be an effective approach for path planning for wildfire monitoring and surveillance by UAVs. For a scenario of 25 locations in a circular arrangement, the algorithm was able to return the optimal path. The accuracy and execution time was found to be sensitive to the algorithm hyperparameters selected, which was especially evident in scenarios with hundreds or thousands of locations. Simulated Annealing was also found to be an effective approach for UAV path planning, with a major benefit of avoiding getting trapped in local minima and being straightforward to implement. Like Genetic Algorithm, the performance of Simulated Annealing was also found to be sensitive to the algorithm hyperparameters selected. By comparison, Dynamic Programming guarantees optimality for any number of locations, but it was found to be less practical in terms of execution time for scenarios with more than about a couple dozen locations. On wildfire detection, image classification using deep learning with a convolutional neural network was explored. Transfer learning was found to be a useful technique to efficiently train deep learning models. Also, it was determined that GPU processing can increase training speed by an order of magnitude, which enables significantly faster development. For a validation test set of 500 images, there were only two false negatives and zero false positives. These results demonstrate that detecting wildfires in static cameras using machine learning is feasible and establish a baseline for using images captured by UAVs in flight for wildfire detection.

Wildfire management↗

On modeling performance of open-loop mechanisms

A technique is presented for modeling the performance of open-loop mechanisms or systems, where performance is measured by success or failure as a function of the selected target for movement along a constrained trajectory and without corrective feedback. A modification of signal detection theory is used, which normalizes dissimilar data and indicates two independent parameters of performance: (1) discriminability and (2) optimality of the distribution of selected moves. An illustrative application is made to experimental data.

Sheridan, T. B.↗

Aerodynamic optimization studies on advanced architecture computers

The approach to carrying out multi-discipline aerospace design studies in the future, especially in massively parallel computing environments, comprises of choosing (1) suitable solvers to compute solutions to equations characterizing a discipline, and (2) efficient optimization methods. In addition, for aerodynamic optimization problems, (3) smart methodologies must be selected to modify the surface shape. In this research effort, a 'direct' optimization method is implemented on the Cray C-90 to improve aerodynamic design. It is coupled with an existing implicit Navier-Stokes solver, OVERFLOW, to compute flow solutions. The optimization method is chosen such that it can accomodate multi-discipline optimization in future computations. In the work , however, only single discipline aerodynamic optimization will be included.

Chawla, Kalpana↗

Optimization methods applied to hybrid vehicle design

The use of optimization methods as an effective design tool in the design of hybrid vehicle propulsion systems is demonstrated. Optimization techniques were used to select values for three design parameters (battery weight, heat engine power rating and power split between the two on-board energy sources) such that various measures of vehicle performance (acquisition cost, life cycle cost and petroleum consumption) were optimized. The apporach produced designs which were often significant improvements over hybrid designs already reported on in the literature. The principal conclusions are as follows. First, it was found that the strategy used to split the required power between the two on-board energy sources can have a significant effect on life cycle cost and petroleum consumption. Second, the optimization program should be constructed so that performance measures and design variables can be easily changed. Third, the vehicle simulation program has a significant effect on the computer run time of the overall optimization program; run time can be significantly reduced by proper design of the types of trips the vehicle takes in a one year period. Fourth, care must be taken in designing the cost and constraint expressions which are used in the optimization so that they are relatively smooth functions of the design variables. Fifth, proper handling of constraints on battery weight and heat engine rating, variables which must be large enough to meet power demands, is particularly important for the success of an optimization study. Finally, the principal conclusion is that optimization methods provide a practical tool for carrying out the design of a hybrid vehicle propulsion system.

Donoghue, J. F.↗

TPSAS-NF1676L-32708-DND

Proposed Effort under Advanced Air Transport Technology (AATT): - Select advanced Al alloy with formability and additive manufacturability, high combined strength and toughness - Fabricate single-piece Integrally Stiffened Cylinders (~10 ft. dia. x 10 ft. long) with longitudinal stiffeners - Demonstrate joining technology for assembly of two cylinders into 20-ft. long fuselage structure - Optimize structural design incorporating tailored, selective reinforcement for durability and damage tolerance - Build-up window, door and circumferential ring frames with large-scale additive manufacturing - Structural test to validate manufacturing demonstration, structural models and analysis

Taminger, Karen M↗

Lunar base heat pump, phase 1

This report describes the Phase 1 process and analysis used to select a refrigerant and thermodynamic cycle as the basis of a vapor compression heat pump requiring a high temperature lift, then to perform a preliminary design to implement the selected concept, including major component selection. Use of a vapor compression heat pump versus other types was based on prior work performed for the Electric Power Research Institute. A high lift heat pump is needed to enable a thermal control system to remove heat down to 275 K from a habitable volume when the external thermal environment is severe. For example, a long-term lunar base habitat will reject heat from a space radiator to a 325 K environment. The first step in the selection process was to perform an optimization trade study, quantifying the effect of radiator operating temperature and heat pump efficiency on total system mass; then, select the radiator operating temperature corresponding to the lowest system mass. Total system mass included radiators, all heat pump components, and the power supply system. The study showed that lunar night operation, with no temperature lift, dictated the radiator size. To operate otherwise would require a high mass penalty to store power. With the defined radiation surface, and heat pump performances assumed to be from 40 percent to 60 percent of the Carnot ideal, the optimum heat rejection temperature ranged from 387 K to 377 K, as a function of heat pump performance. Refrigerant and thermodynamic cycles were then selected to best meet the previously determined design conditions. The system was then adapted as a ground-based prototype lifting temperature to 360 K (versus 385 K for flight unit) and using readily available commercial-grade components. Over 40 refrigerants, separated into wet and dry compression behavioral types, were considered in the selection process. Refrigerants were initially screened for acceptable critical temperature. The acceptable refrigerants were analyzed in ideal single and two-stage thermodynamic cycles. Top candidates were analyzed assuming realistic component limits and system pressure drops, and were evaluated for other considerations such as safety, environmental impact, and commercial availability. A maximum coefficient of performance (COP) of 56 percent of the Carnot ideal was achievable for a three-stage CFC-11 cycle operating under the flight conditions above. The program was completed by defining a control scheme and by researching and selecting the major components, compressor and heat exchangers, that could be used to implement the thermodynamic cycle selected. Special attention was paid to using similar technologies for the SIRF and flight heat pumps resulting in the commercially available equivalent of the flight unit. A package concept was generated for the components selected and mass and volume estimated.

Goldman, Jeffrey H.↗

Coupled Multi-Disciplinary Optimization for Structural Reliability and Affordability

A computational simulation method is presented for Non-Deterministic Multidisciplinary Optimization of engine composite materials and structures. A hypothetical engine duct made with ceramic matrix composites (CMC) is evaluated probabilistically in the presence of combined thermo-mechanical loading. The structure is tailored by quantifying the uncertainties in all relevant design variables such as fabrication, material, and loading parameters. The probabilistic sensitivities are used to select critical design variables for optimization. In this paper, two approaches for non-deterministic optimization are presented. The non-deterministic minimization of combined failure stress criterion is carried out by: (1) performing probabilistic evaluation first and then optimization and (2) performing optimization first and then probabilistic evaluation. The first approach shows that the optimization feasible region can be bounded by a set of prescribed probability limits and that the optimization follows the cumulative distribution function between those limits. The second approach shows that the optimization feasible region is bounded by 0.50 and 0.999 probabilities.

Abumeri, Galib H.↗

A Disturbance Rejection Approach to Actuator and Sensor Placement

For various reasons as discussed for instance in, the selection of actuator and sensor positions is still ad hoc. This is especially true for flexible structures where many candidate configurations can exist. This study is an attempt to make the selection process more methodical. One approach to actuator and sensor placement is to optimize a closed loop performance metric directly by selecting the actuators, sensors, and controller gains simultaneously. This direct approach makes sense if the desired closed loop performance is well defined. Since the individual actuator and sensor contributions to the closed loop performance metric is complex, the solution strategy usually employs non linear programming with many design and numerical iterations. A second approach is to select actuators and/or sensors based on open loop properties so that closed loop performance is indirectly optimized. Since the individual sensor and actuator contributions to the open loop metric is simple, nonlinear optimization is usually not needed. This approach will suggest efficient actuator and sensor configurations for any type of control law. The method suggested in this study falls into the latter class of approaches.

Lim, K. B.↗

Fabrication of aluminum-carbon composites

A screening, optimization, and evaluation program is reported of unidirectional carbon-aluminum composites. During the screening phase both large diameter monofilament and small diameter multifilament reinforcements were utilized to determine optimum precursor tape making and consolidation techniques. Difficulty was encountered in impregnating and consolidating the multifiber reinforcements. Large diameter monofilament reinforcement was found easier to fabricate into composites and was selected to carry into the optimization phase in which the hot pressing parameters were refined and the size of the fabricated panels was scaled up. After process optimization the mechanical properties of the carbon-aluminum composites were characterized in tension, stress-rupture and creep, mechanical fatigue, thermal fatigue, thermal aging, thermal expansion, and impact.

Novak, R. C.↗

Modal insensitivity with optimality

This paper deals with the design of a constant gain, feedback controller which results in selected modal insensitivity, and at the same time optimizes a quadratic performance index representative of desired system performance for nominal plant parameter values. Both full state and output feedback control are considered. A constraint is established for the feedback gain matrix that results in modal insensitivity, and necessary conditions for optimality subject to this constraint are given. This forms the basis for a numerical algorithm to compute the optimal feedback gain. To illustrate the procedure, a design is carried out using the lateral dynamics of an L-1011 aircraft.

Calise, A. J.↗

Integrated control-structure design of the JPL phase B testbed

Structure and damper optimization problems driven by control objective metrics are developed for the optimal design of a testbed structure emulating a spaceborne interferometer. The structure optimization problem uses a multiobjective criterion to generate a family of optimized design that allows trades to be made between the competing objectives of minimizing structural mass and maximizing disturbance attenuation. The damper optimization problems focus on the placement and tuning of viscous elements to maximally damp selected modes of the testbed structure. The optimization techniques are verified on a large model of the testbed.

Milman, M.↗