Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Parametric systems”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Multi-modality deep learning for pulse prediction in homogeneous nonlinear systems via parametric conversion

In this Letter, we introduce FusionNet, a multi-modality deep learning framework designed to predict and analyze output pulses in high-power rare-earth-doped laser systems driving parametric conversion in homogeneous guided nonlinear media. FusionNet integrates temporal, spectral, and physical experimental conditions to model ultrafast nonlinear phenomena, including parametric nonlinear frequency conversion, self-phase modulation, and cross-phase modulation in homogeneous guided systems such as gas-filled hollow-core fibers. These systems bridge physical models with experimental data, advancing our understanding of light-guiding principles and nonlinear interactions while expediting the design and optimization of on-demand high-power, high-brightness systems. Our results demonstrate a 73% reduction in prediction error and an 83% improvement in computational efficiency compared to conventional neural networks. This work establishes a new paradigm for accelerating parametric simulations and optimizing experimental designs in high-power laser systems, with further implications for high-precision spectroscopy, quantum information science, and distributed entangled interconnects.

47 OTHER INSTRUMENTATION↗
NASA NTRS1980

Parametric infrared tunable laser system

A parametric tunable infrared laser system was built to serve as transmitter for the remote detection and density measurement of pollutant, poisonous, or trace gases in the atmosphere. The system operates with a YAG:Nd laser oscillator amplifier chain which pumps a parametric tunable frequency converter. The completed system produced pulse energies of up to 30 mJ. The output is tunable from 1.5 to 3.6 micrometers at linewidths of 0.2-0.5 /cm (FWHM), although the limits of the tuning range and the narrower line crystals presently in the parametric converter by samples of the higher quality already demonstrated is expected to improve the system performance further.

Garbuny, M.↗
NASA NTRS1972

Effects of radiation environment on reusable nuclear shuttle system

Parametric tradeoff analyses of a wide spectrum of alternate tank configurations to minimize both primary and secondary, direct and scattered radiation sources emanating from the NERVA are reported. The analytical approach utilizing point kernel techniques is described and detailed data are presented on the magnitude of neutron/gamma doses for different locations. Single-tank configurations utilizing smaller cone angles and end cap radii were found to minimize integral radiation levels, hence, stage shielding-weight penalties for shuttle missions. Hybrid configurations employing an upper tank with a reduced cone angle and end cap radius result in low integral payload doses primarily due to the increased separation distance caused by the elongation of the larger capacity upper tank. A preliminary radiation damage assessment is discussed of possible reusable nuclear shuttle materials, components, and subsystems, and the possible effects of the radiation environment on various phases of RNS mission operations.

Lane, A. G.↗
NASA NTRS1977

Parametric design of ground data processing/support systems for advanced sensor systems

A parametric system design technique has been applied to ground data processing/support systems for advanced sensor applications. The system establishes a direct link between budget analysts and system planners. Three primary phases are identified: the definition of requirements, system design, and system costing. The system is evaluated for three cases: (1) a study of ground data handling systems for earth resource satellites, (2) a ground data mass storage and processing system for agricultural remote-sensing studies, and (3) a parametric study of shuttle era data processing support required for atmospheric and space physics.

Denny, C.↗
DOE OSTI2020

GMRES with embedded ensemble propagation for the efficient solution of parametric linear systems in uncertainty quantification of computational models

In a previous work, embedded ensemble propagation was proposed to improve the efficiency of sampling-based uncertainty quantification methods of computational models on emerging computational architectures. It consists of simultaneously evaluating the model for a subset of samples together, instead of evaluating them individually. A first approach introduced to solve parametric linear systems with ensemble propagation is ensemble reduction. In Krylov methods for example, this reduction consists in coupling the samples together using an inner product that sums the sample contributions. Ensemble reduction has the advantages of being able to use optimized implementations of BLAS functions and having a stopping criterion which involves only one scalar. However, the reduction potentially decreases the rate of convergence due to the gathering of the spectra of the samples. In this paper, we investigate a second approach: ensemble propagation without ensemble reduction in the case of GMRES. This second approach solves each sample simultaneously but independently to improve the convergence compared to ensemble reduction. This raises two new issues which are solved in this paper: the fact that optimized implementations of BLAS functions cannot be used anymore and that ensemble divergence, whereby individual samples within an ensemble must follow different code execution paths, can occur. We tackle those issues by implementing a high-performing ensemble GEMV and by using masks. The proposed ensemble GEMV leads to a similar cost per GMRES iteration for both approaches, i.e. with and without reduction. For illustration, we study the performances of the new linear solver in the context of a mesh tying problem. Furthermore, this example demonstrates improved ensemble propagation speed-up without reduction.

BLAS↗
NASA NTRS1992

ACSYNT - A standards-based system for parametric, computer aided conceptual design of aircraft

A group of eight US aerospace companies together with several NASA and NAVY centers, led by NASA Ames Systems Analysis Branch, and Virginia Tech's CAD Laboratory agreed, through the assistance of Americal Technology Initiative, in 1990 to form the ACSYNT (Aircraft Synthesis) Institute. The Institute is supported by a Joint Sponsored Research Agreement to continue the research and development in computer aided conceptual design of aircraft initiated by NASA Ames Research Center and Virginia Tech's CAD Laboratory. The result of this collaboration, a feature-based, parametric computer aided aircraft conceptual design code called ACSYNT, is described. The code is based on analysis routines begun at NASA Ames in the early 1970's. ACSYNT's CAD system is based entirely on the ISO standard Programmer's Hierarchical Interactive Graphics System and is graphics-device independent. The code includes a highly interactive graphical user interface, automatically generated Hermite and B-Spline surface models, and shaded image displays. Numerous features to enhance aircraft conceptual design are described.

Jayaram, S.↗
DOE OSTI2021

MTW-OPAL: a technology development platform for ultra-intense optical parametric chirped-pulse amplification systems

Optical parametric chirped-pulse amplification implemented using multikilojoule Nd:glass pump lasers is a promising approach for producing ultra-intense pulses (>10 23 W/cm 2 ). We report on the MTW-OPAL Laser System, an optical parametric amplifier line (OPAL) pumped by the Nd:doped portion of the multi-terawatt (MTW) laser. This midscale prototype was designed to produce 0.5-PW pulses with technologies scalable to tens of petawatts. Technology choices made for MTW-OPAL were guided by the longer-term goal of two full-scale OPALs pumped by the OMEGA EP to produce 2 × 25-PW beams that would be co-located with kilojoule–nanosecond ultraviolet beams. Several MTW-OPAL campaigns that have been completed since “first light” in March 2020 show that the laser design is fundamentally sound, and optimization continues as we prepare for “first-focus” campaigns later this year.

42 ENGINEERING↗
NASA NTRS1996

Comparison of System Identification Techniques for the Hydraulic Manipulator Test Bed (HMTB)

In this thesis linear, dynamic, multivariable state-space models for three joints of the ground-based Hydraulic Manipulator Test Bed (HMTB) are identified. HMTB, housed at the NASA Langley Research Center, is a ground-based version of the Dexterous Orbital Servicing System (DOSS), a representative space station manipulator. The dynamic models of the HMTB manipulator will first be estimated by applying nonparametric identification methods to determine each joint's response characteristics using various input excitations. These excitations include sum of sinusoids, pseudorandom binary sequences (PRBS), bipolar ramping pulses, and chirp input signals. Next, two different parametric system identification techniques will be applied to identify the best dynamical description of the joints. The manipulator is localized about a representative space station orbital replacement unit (ORU) task allowing the use of linear system identification methods. Comparisons, observations, and results of both parametric system identification techniques are discussed. The thesis concludes by proposing a model reference control system to aid in astronaut ground tests. This approach would allow the identified models to mimic on-orbit dynamic characteristics of the actual flight manipulator thus providing astronauts with realistic on-orbit responses to perform space station tasks in a ground-based environment.

Morris, A. Terry↗
DOE OSTI2021

Data-Driven Learning of Nonautonomous Systems

In this work, we present a numerical framework for recovering unknown nonautonomous dynamical systems with time-dependent inputs. To circumvent the difficulty presented by the nonautonomous nature of the system, our method transforms the solution state into piecewise integration of the system over a discrete set of time instances. The time-dependent inputs are then locally parameterized by using a proper model, for example, polynomial regression, in the pieces determined by the time instances. This transforms the original system into a piecewise parametric system that is locally time invariant. We then design a deep neural network structure to learn the local models. Once the network model is constructed, it can be iteratively used over time to conduct global system prediction. We provide theoretical analysis of our algorithm and present a number of numerical examples to demonstrate the effectiveness of the method.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Data-Driven Learning of Non-Autonomous Systems

We present a numerical framework for recovering unknown non-autonomous dynamical systems with time-dependent inputs. To circumvent the difficulty presented by the non-autonomous nature of the system, our method transforms the solution state into piecewise integration of the system over a discrete set of time instances. The time-dependent inputs are then locally parameterized by using a proper model, for example, polynomial regression, in the pieces determined by the time instances. This transforms the original system into a piecewise parametric system that is locally time invariant. We then design a deep neural network structure to learn the local models. Once the network model is constructed, it can be iteratively used over time to conduct global system prediction. We provide theoretical analysis of our algorithm and present a number of numerical examples to demonstrate the effectiveness of the method.

97 MATHEMATICS AND COMPUTING↗