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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 469 records · Page 26
All sourcesNASA NTRSDOE OSTI
NASA NTRS1997

An Initial Multi-Domain Modeling of an Actively Cooled Structure

A methodology for the simulation of turbine cooling flows is being developed. The methodology seeks to combine numerical techniques that optimize both accuracy and computational efficiency. Key components of the methodology include the use of multiblock grid systems for modeling complex geometries, and multigrid convergence acceleration for enhancing computational efficiency in highly resolved fluid flow simulations. The use of the methodology has been demonstrated in several turbo machinery flow and heat transfer studies. Ongoing and future work involves implementing additional turbulence models, improving computational efficiency, adding AMR.

Steinthorsson, Erlendur↗
NASA NTRS1998

Conversion from Engineering Units to Telemetry Counts on Dryden Flight Simulators

Dryden real-time flight simulators encompass the simulation of pulse code modulation (PCM) telemetry signals. This paper presents a new method whereby the calibration polynomial (from first to sixth order), representing the conversion from counts to engineering units (EU), is numerically inverted in real time. The result is less than one-count error for valid EU inputs. The Newton-Raphson method is used to numerically invert the polynomial. A reverse linear interpolation between the EU limits is used to obtain an initial value for the desired telemetry count. The method presented here is not new. What is new is how classical numerical techniques are optimized to take advantage of modem computer power to perform the desired calculations in real time. This technique makes the method simple to understand and implement. There are no interpolation tables to store in memory as in traditional methods. The NASA F-15 simulation converts and transmits over 1000 parameters at 80 times/sec. This paper presents algorithm development, FORTRAN code, and performance results.

Fantini, Jay A.↗
NASA NTRS1998

Current Grid Generation Strategies and Future Requirements in Hypersonic Vehicle Design, Analysis and Testing

Recent advances in computational power enable computational fluid dynamic modeling of increasingly complex configurations. A review of grid generation methodologies implemented in support of the computational work performed for the X-38 and X-33 are presented. In strategizing topological constructs and blocking structures factors considered are the geometric configuration, optimal grid size, numerical algorithms, accuracy requirements, physics of the problem at hand, computational expense, and the available computer hardware. Also addressed are grid refinement strategies, the effects of wall spacing, and convergence. The significance of grid is demonstrated through a comparison of computational and experimental results of the aeroheating environment experienced by the X-38 vehicle. Special topics on grid generation strategies are also addressed to model control surface deflections, and material mapping.

Papadopoulos, Periklis↗
NASA NTRS1998

Bi-Level Integrated System Synthesis (BLISS)

BLISS is a method for optimization of engineering systems by decomposition. It separates the system level optimization, having a relatively small number of design variables, from the potentially numerous sub-system optimizations that may each have a large number of local design variables. The subsystem optimizations are autonomous and may be conducted concurrently. Subsystem and system optimizations alternate, linked by sensitivity data, producing a design improvement in each iteration. Starting from a best guess initial design, the method improves that design in iterative cycles, each cycle comprised of two steps. In step one, the system level variables are frozen and the improvement is achieved by separate, concurrent, and autonomous optimizations in the local variable subdomains. In step two, further improvement is sought in the space of the system level variables. Optimum sensitivity data link the second step to the first. The method prototype was implemented using MATLAB and iSIGHT programming software and tested on a simplified, conceptual level supersonic business jet design, and a detailed design of an electronic device.

Sobieszczanski-Sobieski, Jaroslaw↗
NASA NTRS2010

Mechanics of Re-Torquing in Bolted Flange Connections

It has been widely accepted that the phenomenon of time-dependent loosening of flange connections is a strong consequence of the viscous nature of the compression seal material. Characterizing the coupled interaction between gasket creep and elastic bolt stiffness has been useful in predicting conditions that facilitate leakage. Prior advances on this sub-class of bolted joints has lead to the development of (1) constitutive models for elastomerics, (2) initial tightening strategies, (3) etc. The effect of re-torque, which is a major consideration for typical bolted flange seals used on the Space Shuttle fleet, has not been fully characterized, however. The current study presents a systematic approach to characterizing bolted joint behavior as the consequence of sequentially applied torques. Based on exprimenta1 and numerical results, the optimal re-torquing parameters have been identified that allow for the negligible load loss after pre-load application

Gordon, Ali P.↗
NASA NTRS2013

Motorized Beam Alignment of a Commercial X-ray Diffractometer

X-ray diffraction (XRD) is a powerful analysis method that allows researchers to noninvasively probe the crystalline structure of a material. This includes the ability to determine the crystalline phases present, quantify surface residual stresses, and measure the distribution of crystallographic orientations. The Structures and Materials Division at the NASA Glenn Research Center (GRC) heavily uses the on-site XRD lab to characterize advanced metal alloys, ceramics, and polymers. One of the x-ray diffractometers in the XRD lab (Bruker D8 Discover) uses three different x-ray tubes (Cu, Cr, and Mn) for optimal performance over numerous material types and various experimental techniques. This requires that the tubes be switched out and aligned between experiments. This alignment maximizes the x-ray tube s output through an iterative process involving four set screws. However, the output of the x-ray tube cannot be monitored during the adjustment process due to standard radiation safety engineering controls that prevent exposure to the x-ray beam when the diffractometer doors are open. Therefore, the adjustment process is a very tedious series of blind adjustments, each followed by measurement of the output beam using a PIN diode after the enclosure doors are shut. This process can take up to 4 hr to perform. This technical memorandum documents an in-house project to motorize this alignment process. Unlike a human, motors are not harmed by x-ray radiation of the energy range used in this instrument. Therefore, using motors to adjust the set screws will allow the researcher to monitor the x-ray tube s output while making interactive adjustments from outside the diffractometer. The motorized alignment system consists of four motors, a motor controller, and a hand-held user interface module. Our goal was to reduce the alignment time to less than 30 min. The time available was the 10-week span of the Lewis' Educational and Research Collaborative Internship Project (LERCIP) summer internship program and the budget goal was $1200. In this report, we will describe our motorization design and discuss the results of its implementation.

Van Zandt, Noah R.↗
NASA NTRS2015

Multiscale and Multiphysics Modeling of Additive Manufacturing of Advanced Materials

The objective of this proposed project is to research and develop a prediction tool for advanced additive manufacturing (AAM) processes for advanced materials and develop experimental methods to provide fundamental properties and establish validation data. Aircraft structures and engines demand materials that are stronger, useable at much higher temperatures, provide less acoustic transmission, and enable more aeroelastic tailoring than those currently used. Significant improvements in properties can only be achieved by processing the materials under nonequilibrium conditions, such as AAM processes. AAM processes encompass a class of processes that use a focused heat source to create a melt pool on a substrate. Examples include Electron Beam Freeform Fabrication and Direct Metal Deposition. These types of additive processes enable fabrication of parts directly from CAD drawings. To achieve the desired material properties and geometries of the final structure, assessing the impact of process parameters and predicting optimized conditions with numerical modeling as an effective prediction tool is necessary. The targets for the processing are multiple and at different spatial scales, and the physical phenomena associated occur in multiphysics and multiscale. In this project, the research work has been developed to model AAM processes in a multiscale and multiphysics approach. A macroscale model was developed to investigate the residual stresses and distortion in AAM processes. A sequentially coupled, thermomechanical, finite element model was developed and validated experimentally. The results showed the temperature distribution, residual stress, and deformation within the formed deposits and substrates. A mesoscale model was developed to include heat transfer, phase change with mushy zone, incompressible free surface flow, solute redistribution, and surface tension. Because of excessive computing time needed, a parallel computing approach was also tested. In addition, after investigating various methods, a Smoothed Particle Hydrodynamics Model (SPH Model) was developed to model wire feeding process. Its computational efficiency and simple architecture makes it more robust and flexible than other models. More research on material properties may be needed to realistically model the AAM processes. A microscale model was developed to investigate heterogeneous nucleation, dendritic grain growth, epitaxial growth of columnar grains, columnar-to-equiaxed transition, grain transport in melt, and other properties. The orientations of the columnar grains were almost perpendicular to the laser motion's direction. Compared to the similar studies in the literature, the multiple grain morphology modeling result is in the same order of magnitude as optical morphologies in the experiment. Experimental work was conducted to validate different models. An infrared camera was incorporated as a process monitoring and validating tool to identify the solidus and mushy zones during deposition. The images were successfully processed to identify these regions. This research project has investigated multiscale and multiphysics of the complex AAM processes thus leading to advanced understanding of these processes. The project has also developed several modeling tools and experimental validation tools that will be very critical in the future of AAM process qualification and certification.

Liou, Frank↗
NASA NTRS2018

A Singular Value Decomposition Framework for Retrievals with Vertical Distribution Information from Greenhouse Gas Column Absorption Spectroscopy Measurements

We describe a variation of the Optimal Estimation (OE) method for greenhouse gas remote sensing retrievals using a singular value decomposition (SVD) and an uninformative prior. The SVD method is capable of discerning vertical information in column integrated absorption measurements. While traditional Bayesian optimal estimation (OE) assumes a prior distribution in order to regularize the inversion problem, the SVD approach identifies principal components that can be retrieved from the measurement without explicitly specifying a prior mean and prior covariance matrix. We discuss the method, illustrate its use on an integrated path differential absorption CO2 lidar measurement model, and compare it to traditional optimal estimation using numerical simulations. In the absence of forward model error, the mathematics behind the SVD method guarantee it to be bias-free, which is confirmed by the numerical simulations. In contrast, traditional OE retrievals exhibit bias when the prior mean used in the retrieval differs from the true mean. While the SVD approach can be used for most trace gas retrievals, it is particularly useful for situations where prior knowledge of the trace gas profile is poor. The SVD analysis is also useful in illustrating how vertical information is treated by the traditional OE approach.

Ramanathan, Anand K.↗
NASA NTRS2018

A Singular Value Decomposition Framework for Retrievals with Vertical Distribution Information from Greenhouse Gas Column Absorption Spectroscopy Measurements

We review the singular value decomposition (SVD) framework and use it for quantifying and discerning vertical information in greenhouse gas retrievals from column integrated absorption measurements. While the commonly used traditional Bayesian optimal estimation (OE) assumes a prior distribution in order to regularize the inversion problem, the SVD approach identifies principal components that can be retrieved from the measurement without explicitly specifying a prior mean and prior covariance matrix. We review the SVD method, explicitly recognize the use of an uninformative prior and show it to incur no bias from the choice of the prior. We also make the connection between the SVD method and the pseudo-inverse, which makes it more intuitive and easy to understand. We illustrate the use of the SVD method on an integrated path differential absorption CO2 lidar measurement model and verify our derivations and bias-free properties versus optimal estimation using numerical simulations. In contrast, traditional OE retrievals exhibit bias when the prior mean used in the retrieval differs from the true mean. Hence, the SVD method is particularly useful for situations in which knowledge of the prior mean and prior covariance of the true state (e.g., greenhouse gas profiles) is inadequate.

Ramanathan, Anand K.↗
NASA NTRS2015

“PowerCell”: The Interface Between Mars Resources and Human Exploration

The barriers to forming human settlements on Mars are high but surmountable within our lifetime. While the Apollo astronauts carried their life support with them, our success in exploring and forming settlements on Mars depends on our ability to use local Martian resources to generate the materials and conditions humans need to survive, so-called in situ resource utilization (ISRU). On Earth, biology provides us with food, shelter, oxygen, and other materials. Off-planet, synthetic biology will enable numerous parallel productions: optimized food production, water treatment, air treatment, environmental monitoring, regolith biomining, waste management, cell based biomaterial production, biocementation, and in situ synthesis based on received DNA sequences. How will the organisms responsible for these synthetic production systems obtain organic carbon and fixed nitrogen in the hostile Martian environment? We envision a synthetic-biology enabled Martian colony and introduce here the critical intermediate component a biological power source needed to transform the in situ resources found on Mars into biological feedstocks to enable growth of production organisms. Here, we present our first PowerCell, a photosynthetic and nitrogen-fixing filamentous cyanobacterium engineered to provide a carbon-rich fuel source for a biological life support system on Mars. We provide a vision of how the PowerCell system will operate in a Martian colony based on ground experiments and preparations for testing in space as a NASA secondary payload aboard the upcoming DLR Eu:CROPIS satellite mission experiments.

Rothschild, Lynn J.↗
NASA NTRS2020

Multi-Agent Motion Planning using Deep Learning for Space Applications

State-of-the-art motion planners cannot scale to a large number of systems. Motion planning for multiple agents is an NP (non-deterministic polynomial-time) hard problem, so the computation time increases exponentially with each addition of agents. This computational demand is a major stumbling block to the motion planner's application to future NASA missions involving the swarm of space vehicles. We applied a deep neural network to transform computationally demanding mathematical motion planning problems into deep learning-based numerical problems. We showed optimal motion trajectories can be accurately replicated using deep learning-based numerical models in several 2D and 3D systems with multiple agents. The deep learning-based numerical model demonstrates superior computational efficiency with plans generated 1000 times faster than the mathematical model counterpart.

Madani, Ramtin↗
NASA NTRS1992

Aerodynamic design and optimization in one shot

This paper describes an efficient numerical approach for the design and optimization of aerodynamic bodies. As in classical optimal control methods, the present approach introduces a cost function and a costate variable (Lagrange multiplier) in order to achieve a minimum. High efficiency is achieved by using a multigrid technique to solve for all the unknowns simultaneously, but restricting work on a design variable only to grids on which their changes produce nonsmooth perturbations. Thus, the effort required to evaluate design variables that have nonlocal effects on the solution is confined to the coarse grids. However, if a variable has a nonsmooth local effect on the solution in some neighborhood, it is relaxed in that neighborhood on finer grids. The cost of solving the optimal control problem is shown to be approximately two to three times the cost of the equivalent analysis problem. Examples are presented to illustrate the application of the method to aerodynamic design and constraint optimization.

Ta'asan, Shlomo↗
NASA NTRS1994

Airfoil optimization by the one-shot method

An efficient numerical approach for the design of optimal aerodynamic shapes is presented in this paper. The objective of any optimization problem is to find the optimum of a cost function subject to a certain state equation (Governing equation of the flow field) and certain side constraints. As in classical optimal control methods, the present approach introduces a costate variable (Language multiplier) to evaluate the gradient of the cost function. High efficiency in reaching the optimum solution is achieved by using a multigrid technique and updating the shape in a hierarchical manner such that smooth (low-frequency) changes are done separately from high-frequency changes. Thus, the design variables are changed on a grid where their changes produce nonsmooth (high-frequency) perturbations that can be damped efficiently by the multigrid. The cost of solving the optimization problem is approximately two to three times the cost of the equivalent analysis problem.

Kuruvila, G.↗
NASA NTRS1995

Airfoil Design and Optimization by the One-Shot Method

An efficient numerical approach for the design of optimal aerodynamic shapes is presented in this paper. The objective of any optimization problem is to find the optimum of a cost function subject to a certain state equation (governing equation of the flow field) and certain side constraints. As in classical optimal control methods, the present approach introduces a costate variable (Lagrange multiplier) to evaluate the gradient of the cost function. High efficiency in reaching the optimum solution is achieved by using a multigrid technique and updating the shape in a hierarchical manner such that smooth (low-frequency) changes are done separately from high-frequency changes. Thus, the design variables are changed on a grid where their changes produce nonsmooth (high-frequency) perturbations that can be damped efficiently by the multigrid. The cost of solving the optimization problem is approximately two to three times the cost of the equivalent analysis problem.

Kuruvila, G.↗
NASA NTRS1990

Robust control of systems with real parameter uncertainty and unmodelled dynamics

Two significant contributions have been made during this research period in the research 'Robust Control of Systems with Real Parameter Uncertainty and Unmodelled Dynamics' under NASA Research Grant NAG-1-1102. They are: (1) a fast algorithm for computing the optimal H(sub infinity) norm for the four-block, the two block, or the one-block optimal H(sub infinity) optimization problem; and (2) a construction of an optimal H infinity controller without numerical difficulty. In using GD (Glover and Doyle) or DGKF (Doyle, Glover, Khargonekar, and Francis) approach to solve the standard H infinity norm which required bisection search. In this research period, we developed a very fast iterative algorithm for this computation. Our algorithm was developed based on hyperbolic interpolations which is much faster than any existing algorithm. The lower bound of the parameter, gamma, in the H infinity Riccati equation for solution existence is shown to be the square root of the supremum over all frequencies of the maximum eigenvalue of a given transfer matrix which can be computed easily. The lower band of gamma such that the H infinity Riccati equation has positive semidefinite solution can be also obtained by hyperbolic interpolation search. Another significant result in this research period is the elimination of the numerical difficulties arising in the construction of an optimal H infinity controller by directly applying the Glover and Doyle's state-space formulas. With the fast iterative algorithm for the computation of the optimal H infinity norm and the reliable construction of an optimal H infinity controller, we are ready to apply these tools in the design of robust controllers for the systems with unmodelled uncertainties. These tools will be also very useful when we consider systems with structured uncertainties.

Chang, Bor-Chin↗
NASA NTRS2017

Spacecraft Mission Design for the Mitigation of the 2017 PDC Hypothetical Asteroid Threat

This paper presents a detailed mission design analysis results for the 2017 Planetary Defense Conference (PDC) Hypothetical Asteroid Impact Scenario, documented at https://cneos.jpl.nasa.gov/ pd/cs/pdc17/. The mission design includes campaigns for both reconnaissance (flyby or rendezvous) of the asteroid (to characterize it and the nature of the threat it poses to Earth) and mitigation of the asteroid, via kinetic impactor deflection, nuclear explosive device (NED) deflection, or NED disruption. Relevant scenario parameters are varied to assess the sensitivity of the design outcome, such as asteroid bulk density, asteroid diameter, momentum enhancement factor, spacecraft launch vehicle, and mitigation system type. Different trajectory types are evaluated in the mission design process from purely ballistic to those involving optimal midcourse maneuvers, planetary gravity assists, and/or lowthrust solar electric propulsion. The trajectory optimization is targeted around peak deflection points that were found through a novel linear numerical technique method. The optimization process includes constrain parameters, such as Earth departure date, launch declination, spacecraft/asteroid relative velocity and solar phase angle, spacecraft dry mass, minimum/maximum spacecraft distances from Sun and Earth, and Earth/spacecraft communications line of sight. Results show that one of the best options for the 2017 PDC deflection is solar electric propelled rendezvous mission with a single spacecraft using NED for the deflection

Barbee, Brent W.↗
NASA NTRS2017

Spacecraft Mission Design for the Mitigation of the 2017 PDC Hypothetical Asteroid Threat

This paper presents a detailed mission design analysis results for the 2017 Planetary Defense Conference (PDC) Hypothetical Asteroid Impact Scenario, documented at https:cneos.jpl.nasa.govpdcspdc17. The mission design includes campaigns for both reconnaissance (flyby or rendezvous) of the asteroid (to characterize it and the nature of the threat it poses to Earth) and mitigation of the asteroid, via kinetic impactor deflection, nuclear explosive device (NED) deflection, or NED disruption. Relevant scenario parameters are varied to assess the sensitivity of the design outcome, such as asteroid bulk density, asteroid diameter, momentum enhancement factor, spacecraft launch vehicle, and mitigation system type. Different trajectory types are evaluated in the mission design process from purely ballistic to those involving optimal midcourse maneuvers, planetary gravity assists, and/or low-thrust solar electric propulsion. The trajectory optimization is targeted around peak deflection points that were found through a novel linear numerical technique method. The optimization process includes constrain parameters, such as Earth departure date, launch declination, spacecraft, asteroid relative velocity and solar phase angle, spacecraft dry mass, minimum/maximum spacecraft distances from Sun and Earth, and Earth-spacecraft communications line of sight. Results show that one of the best options for the 2017 PDC deflection is solar electric propelled rendezvous mission with a single spacecraft using NED for the deflection.

Barbee, Brent W.↗
NASA NTRSDate not supplied

Wind-Optimal Trajectories for Multirotor eVTOL Aircraft on UAM Missions

Distributed electric propulsion powered electric vertical takeoff and landing aircraft are expected to enable urban air mobility. Low specific energy of onboard lithium-ion polymer batteries and wind conditions impose constraints on flight endurance. Therefore, from the safety and efficiency perspective, planning and flying minimum energy trajectories are important.The primary motivation for this paper is to determine if there is an operational benefit to flying wind-optimal trajectories for short flights (less than 60 miles) in the urban environment. This study employs wind-optimal trajectories for a NASA-proposed conceptual multirotor aircraft flight in the urban environment. The optimal control model presented includes a wind model for quantifying the effect of wind on the trajectory. The optimal control problem is numerically solved using the direct method. Energy consumption and flight duration flying wind-optimal trajectories between origins and destinations in a metropolitan area are compared with energy consumption and flight duration flying on the great-circle paths between the same origin and destination pairs to determine the operational benefit of wind-optimal routing for short flights.The flight duration results for different scenarios are validated using a simulation tool designed and developed by NASA for exploring advanced air traffic management concepts. In summary,this research study suggests that for short flights in an urban environment, the wind-optimal trajectories have a very slight (insignificant) operational advantage over the great-circle trajectories in terms of energy consumption and flight duration. As expected, headwinds and tailwinds along the route of flight have a significant impact on energy consumption and flight duration.

Urban Air Mobility↗