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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 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
NASA NTRS1989

CSI compensation for reduced-order model based control of a flexible robot manipulator

In controller design for flexible structures, certain system modes are extremely important for the overall performance of the structure. A reduced-order model (ROM) based control focuses on these modes, providing a viable, active control algorithm for large systems. Unfortunately, unmodeled structure dynamics can interact with the ROM controller (CSI) and cause crippling deterioration of system performance, possibly to the point that system stability is lost. A residual model filter (RMF) eliminates one channel of control structure interaction (CSI), while adding only a simple, second-order filter to the control loop. Thus, the ROM controller can be designed independently, based strictly on performance criteria, and residual mode filters can then be selected to compensate for CSI. A flexible robot manipulator is used for preliminary experimentation with the ROM/RMF design methodology. Since the controller was to be implemented both with, and without compensation for CSI, the ROM control gains are carefully chosen such that closed loop stability is never compromised. In this way, RMF effectiveness is easily evaluated in terms of the improvement in system performance resulting from CSI compensation.

Reisenauer, Brian T.↗
NASA NTRS1991

Physical lumping methods for developing linear reduced models for high speed propulsion systems

In gasdynamic systems, information travels in one direction for supersonic flow and in both directions for subsonic flow. A shock occurs at the transition from supersonic to subsonic flow. Thus, to simulate these systems, any simulation method implemented for the quasi-one-dimensional Euler equations must have the ability to capture the shock. In this paper, a technique combining both backward and central differencing is presented. The equations are subsequently linearized about an operating point and formulated into a linear state space model. After proper implementation of the boundary conditions, the model order is reduced from 123 to less than 10 using the Schur method of balancing. Simulations comparing frequency and step response of the reduced order model and the original system models are presented.

Immel, S. M.↗
DOE OSTI2021

Non-intrusive nonlinear model reduction via machine learning approximations to low-dimensional operators

Abstract Although projection-based reduced-order models (ROMs) for parameterized nonlinear dynamical systems have demonstrated exciting results across a range of applications, their broad adoption has been limited by their intrusivity: implementing such a reduced-order model typically requires significant modifications to the underlying simulation code. To address this, we propose a method that enables traditionally intrusive reduced-order models to be accurately approximated in a non-intrusive manner. Specifically, the approach approximates the low-dimensional operators associated with projection-based reduced-order models (ROMs) using modern machine-learning regression techniques. The only requirement of the simulation code is the ability to export the velocity given the state and parameters; this functionality is used to train the approximated low-dimensional operators. In addition to enabling nonintrusivity, we demonstrate that the approach also leads to very low computational complexity, achieving up to $$10^3{\times }$$ 10 3 × in run time. We demonstrate the effectiveness of the proposed technique on two types of PDEs. The domain of applications include both parabolic and hyperbolic PDEs, regardless of the dimension of full-order models (FOMs).

42 ENGINEERING↗
NASA NTRS1990

Model reduction by weighted Component Cost Analysis

Component Cost Analysis considers any given system driven by a white noise process as an interconnection of different components, and assigns a metric called 'component cost' to each component. These component costs measure the contribution of each component to a predefined quadratic cost function. A reduced-order model of the given system may be obtained by deleting those components that have the smallest component costs. The theory of Component Cost Analysis is extended to include finite-bandwidth colored noises. The results also apply when actuators have dynamics of their own. Closed-form analytical expressions of component costs are also derived for a mechanical system described by its modal data. This is very useful to compute the modal costs of very high order systems. A numerical example for MINIMAST system is presented.

Kim, Jae H.↗
DOE OSTI2021

Alpha Spectrometry Results for Groundwater Samples Collected in Northern Iraq and a Summary of the Environmental Setting of the Adaya Burial Site

The Radiation Protection Center (RPC) of the Iraqi Ministry of Environment continues to evaluate the potential health impacts associated with the Adaya Burial Site, which is located 33 kilometers (20.5 miles) southwest of Mosul. This report documents the radiological analyses of 16 groundwater samples collected from wells located in the vicinity of the Adaya Burial Site and at other sites in northern Iraq. The Adaya Burial Site is a high-risk dump site because a large volume of radioactive material and contaminated soil is located on an unsecure hillside above the village of Tall ar Ragrag. The uranium activities for the 16 water samples in northern Iraq are considered to be naturally occurring and do not indicate artificial (man-made) contamination. With one exception, the alpha spectrometry results for the 16 wells that were sampled in 2019 indicate that the water quality concerning the three uranium isotopes (Uranium-233/234, Uranium-235/236, and Uranium-238) was acceptable for potable purposes (drinking and cooking). However, Well 7 in Mosul had a Uranium-233/234 activity concentration that slightly exceeded the World Health Organization guidance level. Eight of the 16 wells are located in the villages of Tall ar Ragrag and Adaya and had naturally occurring uranium concentrations. Wells in the villages of Tall ar Ragrag and Adaya are located near the Adaya Burial Site and should be sampled on an annual schedule. The list of groundwater analytes should include metals, total uranium, isotopic uranium, gross alpha/beta, gamma spectroscopy, organic compounds, and standard water quality parameters. Our current understanding of the hydrogeologic setting in the vicinity of the Adaya Burial Site is solely based on villager's domestic wells, topographic maps, and satellite imagery. To better understand the hydrogeologic setting, a Groundwater Monitoring Program needs to be developed and should include the installation of twelve groundwater monitoring wells in the vicinity of Tall ar Ragrag and the Adaya Burial Site. Characterization of the limestone aquifer and overlying alluvium is needed. RPC should continue to support health assessments for the villagers in Tall ar Ragrag and Adaya. Collecting samples for surface water (storm water), airborne dust, vegetation, and washway sediment should be conducted on a routine basis. Human access to the Adaya Burial Site needs to be strictly limited. Livestock access on or near the burial site needs to be eliminated. The surface-water exposure pathway is likely a greater threat than the groundwater exposure pathway. Installation of a surface-water diversion or collection system is recommended in order to reduce the potential for humans and livestock to come in contact with contaminated water and sediment. To reduce exposure to villagers, groundwater treatment should be considered if elevated uranium or other contaminants are detected in drinking water. Installing water-treatment systems would likely be quicker to accomplish than remediation and excavation of the Adaya Burial Site. The known potential for human exposure to uranium and metals (such as arsenic, chromium, selenium, and strontium) at the Adaya Burial Site is serious. Additional characterization , mitigation, and remediation efforts should be given a high priority.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Projection-Based Model Reduction for Coupled Conduction—Enclosure Radiation Systems

We report a projection-based reduced order model (pROM) methodology has been developed for transient heat transfer problems involving coupled conduction and enclosure radiation. The approach was demonstrated on two test problems of varying complexity. The reduced order models demonstrated substantial speedups (up to 185×) relative to the full order model with good accuracy (less than 3% L ∞ error). An attractive feature of pROMs is that there is a natural error indicator for the ROM solution: the final residual norm at each time-step of the converged ROM solution. Using example test cases, we discuss how to interpret this error indicator to assess the accuracy of the ROM solution. The approach shows promise for many-query applications, such as uncertainty quantification and optimization. The reduced computational cost of the ROM relative to the full-order model (FOM) can enable the analysis of larger and more complex systems as well as the exploration of larger parameter spaces.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Component-wise reduced-order model design optimization such as for lattice design optimization

Systems and methods for optimizing a lattice structure design are disclosed herein. In some embodiments, a method for optimizing a lattice structure design can include (i) modeling the lattice structure with a component-wise reduced-order model (CWROM) and (ii) optimizing the CWROM based on a selected criterion using a topology optimization algorithm for lattice design. The selected criterion can include a boundary condition and a load applied to the lattice structure. By modeling the lattice structure as a CWROM, the optimization process can be very fast while still permitting the accurate computation of physical quantities of the lattice structure.

Choi, Youngsoo↗
NASA NTRS1993

A homotopy algorithm for digital optimal projection control GASD-HADOC

The linear-quadratic-gaussian (LQG) compensator was developed to facilitate the design of control laws for multi-input, multi-output (MIMO) systems. The compensator is computed by solving two algebraic equations for which standard closed-loop solutions exist. Unfortunately, the minimal dimension of an LQG compensator is almost always equal to the dimension of the plant and can thus often violate practical implementation constraints on controller order. This deficiency is especially highlighted when considering control-design for high-order systems such as flexible space structures. This deficiency motivated the development of techniques that enable the design of optimal controllers whose dimension is less than that of the design plant. A homotopy approach based on the optimal projection equations that characterize the necessary conditions for optimal reduced-order control. Homotopy algorithms have global convergence properties and hence do not require that the initializing reduced-order controller be close to the optimal reduced-order controller to guarantee convergence. However, the homotopy algorithm previously developed for solving the optimal projection equations has sublinear convergence properties and the convergence slows at higher authority levels and may fail. A new homotopy algorithm for synthesizing optimal reduced-order controllers for discrete-time systems is described. Unlike the previous homotopy approach, the new algorithm is a gradient-based, parameter optimization formulation and was implemented in MATLAB. The results reported may offer the foundation for a reliable approach to optimal, reduced-order controller design.

Collins, Emmanuel G., Jr.↗
NASA NTRSDate not supplied

A New Vision and A More Rational Process Will Advance Space Life Support Through Better Projects

Many space life support assumptions are obviously mistaken but they are generally accepted because they mutually support each other and because they advance a mistaken futuristic vision of closed human ecosystems in space. Many projects have been mistakenly selected to increase life support system closure or reduce launch mass in order to implement this impractical vision. Project members rarely challenge their project’s assumptions and guiding vision. Systems engineering including cost, reliability, risk, and system trade-offs has been very strongly discouraged to prevent rational criticism of these dubious assumptions, the projects, and the ecosystem vision. A more realistic vision can define better near term life support goals and future aspirations that will improve mission support and increase public interest. Given more realistic goals, it will be possible to develop effective technical alternatives, use open rational project selection methods, conduct professional project management, and make swifter progress in the inevitable human advance into space. The current unworkable human space settlement scenario involves moon visits and permanent bases, zero gravity trips to Mars, Mars visits and bases, all leading to extensive human settlements on the moon and Mars. This is unrealistic because the moon and Mars have less than Earth normal gravity and high radiation that can seriously damage human health. A better alternative would use rotating space colonies that produce Earth gravity and are radiation shielded. The attractive fantasy of reproducing terrestrial ecology in space should be replaced by the idea of building a closed system based on advancing technology such as artificial photosynthesis. Past mistaken projects include growing plants for food to replicate terrestrial food sources, recovering small amounts of water from difficult to process waste to achieve high system closure, and using newly designed, lighter, but unreliable hardware to reduce launch mass. The political process supporting the false assumptions, projects, and vision has deliberately prevented the usual systems engineering and cost-benefit analysis. We are going to do much better.

Harry W. Jones↗
NASA NTRS1974

Inclusion of known integrals in the optimal trajectory problem

The classical problem of determination of the rocket trajectory which minimizes mass expenditure during motion between two points in the field of a single gravitating body is analyzed. The known integrals of the system are incorporated into the adjoint equations resulting in a reduction from a seventh-order adjoint system to a third-order adjoint system. The first case which is treated in that of planar motion under specific end conditions. In this case a regularization of the recently derived equations is achieved. The general three-dimensional case is also reduced from a seventh-order adjoint system to a third-order adjoint system. In this case a regularization has not been found.

Burns, R. E.↗
NASA NTRS1985

Model Reduction for Control System Design

An approach and a technique for effectively obtaining reduced order mathematical models of a given large order model for the purposes of synthesis, analysis and implementation of control systems is developed. This approach involves the use of an error criterion which is the H-infinity norm of a frequency weighted error between the full and reduced order models. The weightings are chosen to take into account the purpose for which the reduced order model is intended. A previously unknown error bound in the H-infinity norm for reduced order models obtained from internally balanced realizations was obtained. This motivated further development of the balancing technique to include the frequency dependent weightings. This resulted in the frequency weighted balanced realization and a new model reduction technique. Two approaches to designing reduced order controllers were developed. The first involves reducing the order of a high order controller with an appropriate weighting. The second involves linear quadratic Gaussian synthesis based on a reduced order model obtained with an appropriate weighting.

Enns, D. F.↗
DOE OSTI2022

Reduced-Order Modeling Method for Phase-Change Thermal Energy Storage Heat Exchangers

Thermal energy storage can facilitate the effective utilization of renewable energy. To speed up the design process of thermal energy storage devices, it is critical to develop fast and accurate modeling methods for phase change material embedded heat exchangers (PCM HXs). This study developed and compared two approximation-assisted reduced-order PCM HX models for the simulation of thermal storage components and systems, which were verified against a validated finite-volume model. They are a pure black-box model, and a grey-box model based on the Number of Transfer Units (or effectiveness-NTU) approach. We used the reduced-order models to predict the performance of standalone PCM HX for 1000 cases with different fluid inlet conditions and HX designs. We also integrated the models with a vapor compression system to predict the compressor energy consumption and total charging time under various conditions. The results show that overall, the black-box model gave more accurate results than the grey-box model. On average, the mean absolute deviation in the PCM HX fluid outlet temperature was 0.05 K and 0.1 K for the black-box model and grey-box model, respectively. The grey-box model gave larger temperature deviation toward the end of the phase change process, due to the simplified two-node PCM representation. On the system level, the mean absolute deviation in compressor energy consumption was 0.2% and 0.3% for the black-box model and grey-box model, respectively. Their mean absolute deviation in total charging time was 1.1% and 2.6%, respectively. In terms of computation efficiency, the system simulation speedup ratio gained by using the reduced-order models was 11 to 57. System simulation time was decreased from an average of 1465 s to an average of 59 s. This shows that the proposed reduced-order modeling methods can be used to predict system performance of PCM HXs with less than 3% accuracy penalty, and 25 times less computational time than finite-volume models, enabling faster design and evaluation of PCM thermal storage devices.

25 ENERGY STORAGE↗
NASA NTRS1990

Integration of system identification and robust controller designs for flexible structures in space

A novel approach is developed using experimental data from the structural testing of a physical system to identify a reduced-order model and its error for a robust controller design. There are three steps involved in the approach. First, an approximately balanced model is identified using the eigensystem realization algorithm, which is an identification algorithm. Second, the model error is calculated and described in frequency domain in terms of the H(infinity) norm. Third, a pole-placement technique in combination with an H(infinity) control method is applied to design a controller for the system. A set of experimental data from an existing setup, namely the Mini-Mast system, is used to illustrate and verify the approach development in this paper.

Juang, Jer-Nan↗
DOE OSTI2024

Improving Grid Awareness by Empowering Utilities with Machine Learning and Artificial Intelligence

Gap filling time series data typically depends on linear interpolation. More recently gap filling advancements include machine learning techniques. However, none leverage advanced learning approach that uses cohort training or a neighborhood informed approach, which is described in this report. The report also describes a physics informed approach using Reduced Order Models (ROM). There are several methods to capture the nature of the detailed system in aggregated models, however there is a trade-off for these methods developed for multiple applications. These methods have specific requirements and applications that includes consideration of dynamics or covering a larger range of operating conditions, etc. The various methods of aggregation are: 1) Thevenin equivalents for downstream networks 2) Equivalent feeder representation to capture downstream network losses accurately 3) Structured reduced order models for dynamics 4) System identification-based ROM (abstract dynamical model) Methods described in items 1 and 2 above are ideal for steady-state models and useful for this application. Of these two methods, based on the data availability, the targeted application, the reduced order model that is proposed to be developed is the equivalent feeder model representation. This includes a structure of the reduced order model whose parameters can be determined by the system load and losses with the meter measurements.

14 SOLAR ENERGY↗
NASA NTRS1991

Flight Projects Office Information Systems Testbed (FIST)

Viewgraphs on the Flight Projects Office Information Systems Testbed (FIST) are presented. The goal is to perform technology evaluation and prototyping of information systems to support SFOC and JPL flight projects in order to reduce risk in the development of operational data systems for such projects.

Liggett, Patricia↗
NASA NTRS1989

Orthogonal canonical forms for second-order systems

The authors prove that a linear second-order system with arbitrary damping cannot be reduced to Hessenberg-triangular form by means of orthogonal transformations, while this reduction is always possible for the modal damping commonly assumed for models of flexible structures. The type of canonical form obtainable by means of orthogonal transformations acting on a second-order system is heavily dependent on the type of damping considered. If the damping matrix is merely positive semi-definite symmetric, it is generally not possible to obtain a reduction to Hessenberg-triangular form, while this reduction is trivial for zero or Rayleigh damping. If damping is modal, however, as is commonly assumed in structural models, the reduction exists and is nontrivial. Furthermore, reduction to triangular second-order Schur form is always possible for such damping: this canonical form appears likely to have applications to second-order system theory.

Williams, Trevor↗